Research ArticleCognitive Behavior Evaluation Based onPhysiological Parameters among Young Healthy Subjects withYoga as Intervention

H Nagendra12 Vinod Kumar2 and S Mukherjee3

1Faculty in E amp CE Department Poojya Doddappa Appa College of Engineering Kalaburagi 585 102 India2Department of Electrical Engineering Indian Institute of Technology Roorkee Roorkee 247 667 India3Moradabad Institute of Technology Moradabad 244 001 India

Correspondence should be addressed to H Nagendra hnagendra1gmailcom

Received 20 August 2014 Revised 27 December 2014 Accepted 1 January 2015

Academic Editor Irena Cosic

Copyright copy 2015 H Nagendra et al This is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

Objective To investigate the effect of yoga practice on cognitive skills autonomic nervous system and heart rate variability byanalyzing physiological parameters Methods The study was conducted on 30 normal young healthy engineering students Theywere randomly selected into two groups yoga group and control group The yoga group practiced yoga one and half hour per dayfor six days in a week for a period of five months Results The yoga practising group showed increased 120572 120573 and 120575 EEG bandpowers and significant reduction in 120579 and 120574 band powersThe increased 120572 and 120573 power can represent enhanced cognitive functionssuch as memory and concentration and that of 120575 signifies synchronization of brain activity The heart rate index 120579120572 decreasedneural activity 120573120579 increased attention resource index 120573(120572 + 120579) increased executive load index (120575 + 120579)120572 decreased and the ratio(120575 + 120579)(120572 + 120573) decreased The yoga practice group showed improvement in heart rate variability increased SDNNRMSSD andreduction in LFHF ratioConclusion Yoga practising group showed significant improvement in various cognitive functions such asperformance enhancement neural activity attention and executive function It also resulted in increase in the heart rate variabilityparasympathetic nervous system activity and balanced autonomic nervous system reactivity

1 Introduction

Thepractice of yoga synchronizes human physiology throughcontrolled postures breathing meditation a set of regularphysical exercises and relaxations [1ndash4] Certain types ofyoga practice improve autonomic nervous system by mod-ulating parasympathetic and sympathetic activity significantchanges in brain rhythms sensory motor rhythm regulationof breathing rate and improvement in the cardiac activity andenhance the sense of ldquowell-beingrdquo [5 6] Yoga practice hasmany physiological benefits including increase of heart ratevariability (HRV) decreased blood pressure and increasein respiratory rate and baroreflex sensitivity and balancesautonomic nervous system (ANS) activity by reducing sym-pathetic activity and increasing parasympathetic activity [2]Previous research suggests that yoga practices have immenseimpact on performance of central nervous system and

improve their attention concentration and other cognitivefaculties [7] Regular practice of yoga has benefits in theimprovement of the body mind and spirit guiding to ahealthier and more fulfilling life [8] The practice of yoga canincrease grey matter volumes in temporal and frontal lobesproducing positive impacts on mental health and improvedcognitive functions [3] Study also suggested that yogapractice could also bring improvement in tasks which arerelated to selective attention concentration visual processingcapacity and enhancement in motor activity [9] In anotherstudy the practice of yoga resulted in improved eye-handcoordination improved reversal skills speed accuracy andenhanced cognitive processes [3] Practicing of pranayamaasanas and meditation resulted in improved verbal skillsimprovement in hand-eye coordination and improved neu-ral performances [3 10] It is believed that the practice of

Hindawi Publishing CorporationComputational and Mathematical Methods in MedicineVolume 2015 Article ID 821061 13 pageshttpdxdoiorg1011552015821061

2 Computational and Mathematical Methods in Medicine

yoga can also result in changes in perception attention andcognition Investigations have shown the beneficial effects ofyoga on cognition such as increased performances on visualand verbal memory and improved memory scores [11]

Compared to physical exercise yogamay bemore effectiveor even better in improving health related conditions Despitecorpus of research on the subjects the lack of evidencebased on scientific approaches has limited the application ofyoga as an accepted method for improvement of health [11]Hence further research is needed on the impact of yoga andits potential benefits on healthy subjects Thus yoga offersmany positive effects on cognitive faculties reduction ofstress and emotional intensity Previous studies were mainlyconducted on unhealthy or relatively elder subjects Thefocus was generally on physical and neurological benefitsFurther investigation is required to study the potential ben-efits of yoga on cognitive functions and their relation withphysiological parameters In this study the effects of yogapractices on cognitive skills autonomic nervous system heartrate variability and mental health are analyzed in terms ofphysiological parameters such as electroencephalogram andelectrocardiogram

Therefore the objective of this study is to investigate theeffectiveness of yoga practice and to evaluate physiologicalparameters related to cognitive aspects on novice subjectsThe study primarily focused the effect of yoga on cognitivebehavior in terms of physiological parameters In the currentstudy the yoga practice involved combined practice of easyasanas (postures) meditation and pranayama (breathingexercise) It is known that yoga involving relaxation tech-niques improve the functioning of cardiovascular autonomicnervous system Yoga is correlated with decreased sym-pathetic adrenergic receptor sensitivity which might affectcardiovascular response during stress [12]

11 Heart Rate Variability and Its Indices Heart rate vari-ability (HRV) is a measure of deviations in the interbeatR-R intervals It is a noninvasive method used to assessthe functioning of the autonomic nervous system (ANS)which is responsible for the regulations of many physi-ological processes of the human being [13] The HRV iscaused due to changes in input to the sinus node fromthe autonomic nervous system (ANS) [14] The sinus node(natural pace maker) is one of the major components ofthe cardiac conduction system that regulates the heart rate(HR) by controlling sympathetic nervous system (SNS) andparasympathetic nervous system (PNS) limbs of the ANS[15] Higher HRV is an indicator of adequate adaptation tothe new environment and effective functioning of the ANSwhile lower HRV is an indicator of inadequate adaptation ofANS and poor physiological function of the individuals [13]HRV and HR are inversely correlated The escalation in theHR is due to increased sympathetic and decreased parasym-pathetic activity whereas its reductionmainly depends on thedominance of parasympathetic activity

Generally forHRV analysis parameters can be computedby two methods [13 15ndash17]

Table 1 The equations used to compute time domain measures

Index Equations Unit

mHRV 1

119873 minus 1

119873

sum

119894=1

(RR119894) ms

mHR119873

sum

119894=1

(

1000

RR119894

) lowast 60 bpm

SDNN sqrtsum119873

119894=1(RR119894minusmRR)2

119873 minus 1

ms

RMSSD sqrt mean ((RR119894+1minus RR119894)2) ms

CVRR SDNNmean (RR)

lowast 100 mdash

(i) Time domain measures are directly computed fromthe time series of the RR intervals In the literaturethere are many time domain measures available forHRV analysis In this paper the following indices areused for its analysismHR mean RR intervalsmHRV mean heart rate variability and it indicatesthe total amount of deviations of both instantaneousHR and RR intervals It reflects sympathetic andparasympathetic activity of the ANS on the sinusnode of the heartSDNN standard deviation of all NN intervals andan indicative of global HRV It indicates all the longterm elements and circadian rhythms responsible forvariability in the recording intervalRMSSD the Square roots of the mean of the sumof the squares of differences between adjacent NNintervals and it reflects the short cyclical variability inthe autonomic tone that is largely vagally mediatedCVRR coefficient of variations of RR intervals and itis used to reflect the parasympathetic nervous systemactivitythe important time domain parameters are shown inTable 1

(ii) Frequency domain parameters are computed byapplying fast Fourier transform (FFT) to the timeseries of the raw RR intervals FFT is the most pow-erful and efficient algorithm used to break the HRVsignal into a series of sine and cosine componentsThis Fourier transformed signal is further translatedto power spectrum by squaring magnitude of each[18] The fundamental frequency components werecomputed by integrating the periodogram Generallythe power spectrum can be classified into the follow-ing four groups [19]Very low frequency (VLF 00033ndash004Hz) powerthe function of this frequency range is not welldefined but sometimes it can be used as the index ofsympathetic activity of ANS

Computational and Mathematical Methods in Medicine 3

05

10152025303540

Frontal Central Perietal Occipital Temporal Total

PSD

(120583V2H

z)

(a) 120573 power

Frontal Central Perietal Occipital Temporal Total0

5

10

15

20

25

30

PSD

(120583V2H

z)

(b) 120572 power

Frontal Central Perietal Occipital Temporal Total0

20

40

60

80

100

120

PSD

(120583V2H

z)

(c) 120579 power

Frontal Central Perietal Occipital Temporal Total0

5

10

15

20

25

30

35

PSD

(120583V2H

z)

(d) 120575 power

Frontal Central Perietal Occipital Temporal Total

BeforeAfter

02468

101214161820

PSD

(120583V2H

z)

(e) 120574 power

Figure 1 EEG band powers of yoga group in various lobes of the brain before and after intervention

Low frequency (LF 004ndash015Hz) power this band iscomplex in nature and an index of both sympatheticand parasympathetic activity and influences HRVpatterns

High frequency (HF 015ndash04Hz) power it is theindex of parasympathetic activity and is used toindicate slow changes in the HR

Very high frequency (VHF gt04Hz) this frequencyis generally considered as noise and has no clinicalsignificance

LFHF ratio It reflects the overall balance of the ANSThe lower ratio is recommended by the task force

In normal in resting condition this ratio lies in therange of 1 and 2

Total power (TP) variance of all NN intervals in thefrequency range less than 04Hz

The VLF LF HF and TP are expressed in ms2 unitswhen computed in absolute values The important frequencydomain parameters used for the computation are shown inTable 2

The spectral parameters of HRV are usually normalizedto minimize the effect of redundancy inherent in them inmost of the research work The important frequency domainparameters are shown in Figure 2

4 Computational and Mathematical Methods in Medicine

Table 2 The equations used to compute frequency domain mea-sures

Index Equations Unit

LFnuLF(LF +HF)

lowast 100

HFnuHF(LF +HF)

lowast 100

SVI LFHF

mdash

LFRelpowerLFTPlowast 100 mdash

HFRelpowerHFTPlowast 100 mdash

dLFHF 1003816100381610038161003816LFnu minusHFnu

1003816100381610038161003816

where TP = VLF + LF + HF

11611976

10682

2109 19022455 2837

7942

28941824

0

20

40

60

80

100

120

BeforeAfter

minus20120573 120572 120579 120575 120574

PSD

(120583V2H

z)

Figure 2 Global EEG band powers of yoga group before and afterintervention

12 EEG Band Frequencies and Cognitive Processes Thebrainactivity which changes continuously with time is called ldquoelec-troencephalogramrdquo (EEG) which can be used to investigatethe cognitive abilities and memory executions of individualsin terms of its band of frequencies

The EEG is highly complex and is combination of fivedifferent frequency waveforms namely 120575 (delta) 120579 (theta) 120573(beta)120572 (alpha) and 120574 (gamma)waves respectively [20]Theamplitude of the brain waves is approximately in the rangeof 10 120583V to 250120583V and the frequency varies between 05Hzand 100HzThe frequency range and their characteristics areshown in Table 3

The EEG waveforms may be global or localized to thespecific areas on the scalp This kind of electrical data isimportant to study the correlation between yoga asanas andphysiological states because any shift in the EEG frequencyrange reflects the physiological arousalThe various EEG ratioindices and their physiological and cognitive interpretationsare shown in Table 4

13 Extraction of EEG Band Frequencies Using DiscreteWavelet Transforms (DWT) Discrete wavelet transforms(DWT) are widely used for the analysis of physiological

signals as compared to the classical techniques such as fastFourier transforms (FFT) When FFT is applied on thetime series signal the signal information is available in theform of spectral parameters That is the whole time domaininformation will be lost It is equivalent to windowed Fouriertransform and can be used to measure both the time andfrequency changes of a signal [21]

The DWT splits the input signal into approximation(trend) and detailed coefficients (fluctuation) respectivelyThe approximation coefficient can further be split into anew approximation and detailed coefficients This process iscontinued progressively to get a new set of approximation anddetailed coefficients of a signal at various levels of decomposi-tion [22] The selection of analyzing wavelet is called motherwavelet and number of decomposition levels to be carried outis the critical pointThemother wavelet determines the shapeof the signal to be decomposed In this paper the waveletfunction db4 is used to extract five frequency bands (120575 120579120572 120573 and 120574) of EEG signal The application of higher orderwavelet function such as db20 produces large number ofcoefficients Larger number of coefficients average out thedetail components of the signal and fail to detect fast movingsignals such as EEG To retrieve the information at a specificinstant of time the wavelets with less number of coefficientsare better choice The lower order wavelet function db4has good time and frequency localization properties andin addition this wavelet has similar morphology as thatof EEG signal to be detected Therefore db4 wavelets arebetter choice for precisely detecting fast moving transientsand short duration information signals Thus by the processof decomposition DWT can detect the important hiddenfeatures from the original signal

In this study the EEG signal was acquired with samplingfrequency of 500Hz The useful information of this signallies in the range of 05ndash70Hz Hence a level of 7 usingdb4 was applied to decompose the EEG signal into itsapproximate (A1ndashA7) and detail (D1ndashD7) coefficients Afterthe seventh level of decomposition the band of frequenciesobtained are D1 (250ndash500Hz) A1 (0ndash250Hz) D2 (125ndash250Hz) A2 (0ndash125Hz) D3 (625ndash125Hz) A3 (0ndash625Hz)D4 (3125ndash625Hz) A4 (0ndash3125Hz) D5 (15625ndash3125Hz)A5 (0ndash15625Hz) D6 (78125ndash15625Hz) A6 (0ndash78125Hz)D7 (3906ndash7813Hz) and A7 (0ndash3906Hz) respectively Thedecomposition levels from D1 to D3 were considered asnoise components and hence excluded from the analysisThe finer detailed coefficients from levels D4ndashD7 and finalapproximate coefficients from level A7 are retained as theyapproximately represent the EEG physiological frequencysubbands of 120574120573120572 120579 and120575 respectivelyThese five frequencybands are analyzed to investigate different cognitive effectsdue to yoga among healthy subjects Different EEG ratiosused in this study to investigate cognitive performances interms of physiological parameters are shown in Figure 4which are derived from various sources

2 Methodology and Experimental Procedure

21 Subjects The total number of subjects who participatedin the experiment was 30 young healthy graduate and

Computational and Mathematical Methods in Medicine 5

Table 3 Five EEG frequency bands

Parameters Frequency range (Hz) Magnitude (120583V) Activity Remark120573 13ndash30 lt30 120583V Desynchronized Mental occupation120572 8ndash13 50ndash100 120583V Synchronized Relaxed tranquility and wakefulness120579 4ndash8 20ndash40 120583V Desynchronized Dreaming state120575 05ndash4 75ndash150 120583V Desynchronized State of dreamless sleep120574 30ndash70 mdash Synchronized Sensory integration

Table 4 EEG band ratios and their physiologicalcognitive activityindex interpretation

EEG band ratios Activitycorrelation Sources120579120572 Heart rate (HR) [23]

120572120579 Performance enhancementindex or ldquowellbeingrdquo [24]

120573120572 Arousal index [25]120573120579 Neural activity [25]

120573(120572 + 120579) Cognitive performance andattentional resource index [26]

120579(frontal)120572(parietal) Task load index [27](120575 + 120579)120572 Executive load index [28]120572120575 Brain perfusion [29]120579120573 CNS arousal [30](120579 + 120575)(120572 + 120573) Sum of LF to HF ratio [29]120572120573 Desynchronization [31]120575120579 Synchronization(120579 + 120572)120573 Vigilance index [31]

postgraduate engineering students of IIT Roorkee (male =27 female = 3) All the subjects were right handed withnormal eye sight The study population was divided intotwo groups experimental group and control group In thisstudy the sample size is relatively small and both groupshave the same size The study population was randomlyassigned to either of the groups by block randomizationmethod to achieve the balance The block size of two wasused Both participants and investigators were unaware of thegroups to be assigned in advance Each group consisted of15 subjects with two females in experimental group and onein control group The mean and standard deviation of eachgroup were 2242 plusmn 230 and 2367 plusmn 209 respectively Thesame subjects were chosen for both experimental and controlgroups to diminish misperceiving influences and make thestudy more effective Subjects with previous yoga practicehistory of alcohol consumption smoking and any other drugconsumption were excluded from this studyThe participantswere informed a priori about the study and their consent wasobtained Subjects participated voluntarily and cooperatedthroughout the training period The subjects were asked tonot to deviate their regular life style during this study All thesubjects of experimental group obtained same yoga trainingfor a period of fivemonths for 15 hours per day between 6 pmand 730 pm

In this study the physiological parameters such as ECGand their ratio indices have been evaluated to assess thecognitive benefits of the yoga practice along with its wellestablished health benefits This may provide the windowfor further investigation to correlate the actual measures ofcognitive functions and their physiological parameters

The practice of yoga schedule consisted of prayerpranayama (breathing techniques) and simple yogic pos-tures Explanations on stress management importance ofmeditation and yoga in everyday life were also briefed

The subjects practiced yoga under observation of trainedyoga instructor During practice session various types ofasanas (postural exercises) pranayama (breathing tech-niques) and dhyana (meditation) were performed Theseasanas increase the strength concentration will power andmindfulness by manipulating the natural energy of the body[1 32 33]

(1) Standing asanas (postures) they consisted of suryanamaskar dandasana urdhave asana trikonasanaardha asana hasta padasana mahavir asana andvatayanasana

(2) Sitting asanas (postures) they include mandookasana and oorm asana ushtra asan ardha matsy-endrasana vakrasana supt asana matsyendrasanauttan mandukasana vakasana mayoor asan padmvak asan padma mayurasana pashchimottanasaneka padangusthasana vipreet pad asan and purnachakrasana

(3) Asana (posture) lying on back this includes uttanpad asana pawanmuktasana market asan shree-shan sarvangasana halasana setu bandhasana andchakrasana

(4) Asana (posture) lying on stomach this includes nau-kasana yan asan shalabh asan and dhanurasana

(5) Pranayama (breathing) and kriya include Anulom-vilom kapalbhati Ujjayi pranayama Bhramari pra-nayama sheetali pranayama sheetkari pranayamasurya bheda pranayama bhastrika pranayama bahyapranayama udgeeth pranayama kaki mudra andshanmukhi mudra Everyday practice session wasconcluded with prayer and meditation

22 Recording ECG and EEG Signals and Analysis BothECG and EEG signals were recorded simultaneously usingBIOPACMP150 System (EEG100C = 10 nos and ECG100C =3 nos) with Acqknowledge 40 software

6 Computational and Mathematical Methods in Medicine

ECG signal was recorded using five electrodes by con-necting to left and right wrinkles and left and right armsand one electrode at chest Before fixing the electrodes theywere cleaned and electrode gel was applied to reduce theskin resistance to get good quality of recording signal EEGsignal was recorded by fixing the CAP100C on the scalp ofthe subjects This cap was made of Lycra type fabric with20 reusable tin electrodes attached to it according to theinternational 10ndash20 norms Before fixing the cap on subjectsscalp the electrodes were cleaned with saline water andelectrode gel was appliedThismaintains the resistance below5 kΩ between the scalp and electrodes

All the data were collected during 6 pm to 730 pm atthe yoga centre of the temple premises in two stages Thedata collected at the beginning of the intervention period wasconsidered as the first stage during which five minutes ofbaseline ECG and EEG signals were recorded from subjectsof both experimental and control groups in sitting positionwith eyes closed The baseline signal was saved on the harddisk for offline processing

Both ECG and EEG signals were recorded with a sam-pling frequency of 512Hz to have better resolution of R-Rtime interval series and EEG activity

The experimental group practiced yoga for a period of fivemonths for 15 hr per day in the evening from 6 pm to 730pmThe control group was asked not to practice any form ofyogic practices or physical exercises during this period Theend of five months yoga training period was considered assecond stage During this stage again both ECG and EEGdata were collected from experimental and control groupfor a period of 10 minutes During recording subjects wereasked to minimize eye blinks and avoid body movements tominimize any artifacts that could be introduced If artifactswere introduced due to uncontrolled bodymovements or eyeblinks or due to technical reasons the recording time wasprolonged for a few more minutes The data was again savedon the hard disk for offline processing These data were usedfor the evaluation of various cognitive functions in terms ofphysiological parameters

Though maximum care was taken the recorded data wascontaminated with many artifacts Manual editing was per-formed for both ECG and EEG signalsThe RR intervals werethen extracted from the Acqknowledge 40 software whichuses modified Pan and Tompkins algorithm The intervalsless than 300ms and above 1200ms were eliminated fromtime series data set and were saved in text format for furtherprocessing using MATLAB 71 Any data whose standarddeviation was less than or equal to three times the standarddeviation was considered outliers and removed from the databefore determining the time domain parameters of heartrate variability (HRV) The artifact free data was segmentedinto five groups with 10 seconds segments each The averagevalue of each 10 seconds data was used in the analysis Theimportant time domainmeasures of HRV such asmeanHRVSDANN RMSSD and mean HR were computed

The frequency domain parameters namely VLF LFHF LF HF ratio and VHF were extracted from the FFTalgorithm The normalized values were computed by divid-ing the respective frequencies by total power minus VLF

4077

0092

6472

2048

0228

3820

0

1

2

3

4

5

6

7

8

Enga

gem

ent i

ndex

val

ue

Before yogaAfter yoga

(120575 + 120579)(120572 + 120573) 120573(120572 + 120579) (120575 + 120579)120572

Figure 3 CNS activity engagement index and executive load indexof yoga group before and after intervention

The normalization reduces the effect of LF and HF on totalpower In conformity with the task force recommendationThe artifact free signal of two minutes duration was used forcomputing frequency domain parameters

Hypotheses of the StudyHypothesis 1 There is no significant difference in physiolog-ical parameters (HR HRV) and cognitive functions of thesubjects of experimental group before and after yoga training(intervention)

Hypothesis 2 There is no significant difference in physio-logical parameters (HR HRV) and cognitive functions ofthe subjects of control group before and after yoga training(intervention)

3 Results and Discussion

Results are grouped in two parts firstly HRV analysis whichincludes time and frequency domain parameters secondlycognitive performance evaluation based on EEG engagementindices Both EEG and ECG signals reflect global arousal oralertness of the brain [34]

31 HRVAnalysis Theheart rate variability (HRV) is an indi-cator of cardiac ANS and HR is controlled by neural activity[35] The yogic exercise particularly pranayama (breathingtechniques) activatesANSThe yoga practicing group showedsignificant increase in HRV (119875 lt 00304) and reduction inresting HR (119875 lt 00389) The significant reduction in restingHR indicates a relaxed state of physiology and increasedmental alertness Depending on left or right cerebral hemi-spherical dominance there will be improvement in spatialor verbal skills The SDNN which reflects the total powersignificantly increased (119875lt00012)TheRMSSD an indicatorof parasympathetic activity also increased significantly (119875 lt00058) The ratio of SDNNRMSSD which is surrogate ofLFHF ratio [36] increased significantly (119875lt00039) LF was

Computational and Mathematical Methods in Medicine 7

Frontal Central Perietal Occipital Temporal Total0

5

10

15

20

25PS

D (120583

V2H

z)

(a) 120573 power

Frontal Central Perietal Occipital Temporal Total0

5

10

15

20

25

PSD

(120583V2H

z)

(b) 120572 power

0

20

40

60

80

100

120

Frontal Central Perietal Occipital Temporal Total

PSD

(120583V2H

z)

(c) 120579 power

0

5

10

15

20

25

Frontal Central Perietal Occipital Temporal Total

PSD

(mV2H

z)

(d) 120575 power

0

2

4

6

8

10

12

14

16

BeforeAfter

Frontal Central Perietal Occipital Temporal Total

PSD

(120583V2H

z)

(e) 120574 power

Figure 4 EEG band powers of control group in various lobes of the brain before and after intervention

significantly decreased (119875 lt 00002) while HF was increased(119875 lt 00003) The decrease of LF and increase of HF reflectsthe improvement in the dominance in the parasympatheticactivity A significant improvement in HRV may be dueto an increase in parasympathetic activity or a decrease insympathetic activity [35] These indirectly help in reducingthe psychological parameters such as distress anxiety anddepression in young healthy subjects

There was significant reduction in LF power (119875 lt 00002)whereas parasympathetic activity significantly increased (119875 lt00003) The LF powers indicate both sympathetic andparasympathetic modulation whereas HF power reflects

parasympathetic activation Hence reduction in sympatheticactivity and enhanced parasympathetic activity results indeceleration in the cardiac activity The ratio LFHF whichis an indicator of autonomic ANS balance between sym-pathetic and parasympathetic nervous system activity [37]was significantly decreased (119875 lt 00000) There is alwaysconstant interaction between sympathetic and parasympa-thetic activity to regulate heart rate variability The VLFincreased without significance in yoga group while there wassignificant increase in control group The VLF representsslow changes in the heart rate [38] but the exact functionof it is yet to be understood A significant reduction in

8 Computational and Mathematical Methods in Medicine

Table 5 Time and frequency domain parameters before and after intervention of yoga and control group

Parameters Yoga group Control groupBefore After 119875 value Before After 119875 value

mHRV (ms) 75721 plusmn 6537 81329 plusmn 7891 00304 87467 plusmn 9155 85572 plusmn 7048 02505mHR (bpm) 7979 plusmn 774 7457 plusmn 705 00389 6950 plusmn 943 7050 plusmn 622 02759SDNN (ms) 4443 plusmn 2176 5214 plusmn 2327 00012 5322 plusmn 2169 5383 plusmn 1951 09044RMSSD (ms) 3993 plusmn 2365 5521 plusmn 2278 00058 5483 plusmn 2946 49 plusmn 2789 01999SDNNRMSSD 077 plusmn 037 111 plusmn 057 00039 077 plusmn 037 121 plusmn 028 01336VLF (nu) 402 plusmn 096 1163 plusmn 983 00177 342 plusmn 991 1404 plusmn 1006 00007LF (nu) 12306 plusmn 2110 5685 plusmn 1016 00002 4514 plusmn 1309 4157 plusmn 1660 00000HF (nu) 2739 plusmn 844 4315 plusmn 1016 00003 4648 plusmn 461 220 plusmn 579 00269LFrelative 7133 plusmn 567 5116 plusmn 951 00000 4642 plusmn 1070 7081 plusmn 713 00000HFrelative 2739 plusmn 844 4315 plusmn 1016 00003 4648 plusmn 461 4220 plusmn 579 00269TP (nu) 17199 plusmn 2241 11163 plusmn 983 00000 9503 plusmn 1129 9781 plusmn 1244 00000LF HF 499 plusmn 198 1411 plusmn 045 00000 099 plusmn 032 355 plusmn 156 00000119875 gt 010 not significant 119875 lt 010marginal 119875 lt 005 fair 119875 lt 001 good 119875 lt 0001 excellent difference 119875 lt 005 is considered significant level and for anyvalue less than this the null hypothesis is rejected 119905stat gt 119905valu for the null hypothesis to be rejected If 119875 = 005 there is 5 chance of no real difference

total power was observed in yoga group This might be dueto significant decrease of sympathetic activity compared tosignificant increase of parasympathetic activity The VHFpower generally reflects part of noise component and doesnot possess clinically significant information

Control group showed significant increase of LF power(119875 lt 00000) decreased HF power (119875 lt 0029) increasedLFHF ratio (119875 lt 00000) and increased VLF power But nosignificant changes were observed in time domain parame-ters

The LF and HF band power of HRV are expressed innormalized units The representation of these frequencyband powers in normalized units articulates the degree ofcontrol exercised and the relative balance of two limbs ofthe autonomic nervous system [35]Moreover normalized LFpower is thought to represent the sympathetic modulation asopposed to absolute units Since theHRV spectral parametersare computed by the autonomic nervous system (ANS) mea-surement of HRV may have greater application in assessingautonomic statues

Studentrsquos paired 119905-test was performed on set of pre- andpostintervention data samples to investigate whether therewas any real difference between them Each 119905 value has acorresponding 119875 value The 119875 value which is the probabilitythat the pattern of data samples in the sample could beproduced by random data provides the information aboutthe likelihood that there is a real difference in the data patternThis significant difference in the data set could be due to theeffect of particular training or an intervention given to thesubjects

The various time and frequency domain parameters ofboth yoga and control group are shown in Table 5 Anyvariations in these parameters could be due to relative age dif-ferences between yoga and control groups or methodologicaldifferences or limited number of samples in the study

The decrease in HR could be due to combined effect ofelements of yoga The reduction in stress after yoga couldbe other possible reason for improved HRV in this study

The previous researches suggest that yoga practice resultsin neurophysiological balance by lowering level of cholin-esterase and catecholamines Further this result increasedparasympathetic and decreased sympathetic activity Theresults of this study are in concurrence with previous studies[6 9 35] These studies indicated reduced sympatheticactivity and enhanced parasympathetic activity after yoga

32 Cognitive Performance Analysis The regular practice ofyoga for a period of fivemonths by young healthy engineeringstudents resulted in the increase of 120572 120573 and 120575 EEG bandpowers and decrease in the 120579 and 120574 band powers Theincreased 120573 band power indicate enhancement in certaincognitive functions such as alertness while increased 120572and decreased 120575 reflect enhanced vigilance level indicatingincreased alertnessThus the increase of high frequency bandpowers (120572 120573) and decrease of low frequency band powers (120575120579) are associated with enhancement in certain cognitive skillssuch as memory and visual information processing

The various cognitive behavior parameters have beenevaluated based on various EEG indices such as 120579120572 120573120572120573120579 (120575 + 120579)120572 120573(120572 + 120579) and (120575 + 120579)(120572 + 120573) Increasein 120573 band power indicates a higher level of alertness andenhanced engagement task and enhancement in variouscognitive abilities The increased band powers of 120572 and 120579indicate decreased alertness reduced engagement task andgood information processing capabilities [25] The 120575 and 120582activity are used for analysis of many cognitive processes[39]The ratio 120573120579which is representative of improvement incognitive skills increasedThe heart rate index 120579120572 decreasedperformance enhancement index 120572120579 increased attentionresource index 120573(120572 + 120579) significantly increased executiveload index (120575 + 120579)120572 decreased and ratio (120575 + 120579)(120572 + 120573)decreased The 120572 120573 and 120575 band power increased in frontalcentral parietal occipital and temporal lobes The 120579 bandpower was increased only in occipital lobe while 120574 bandpower in frontal and slightly in temporal lobes As the frontallobe is associated with reasoning planning problem solving

Computational and Mathematical Methods in Medicine 9

Table 6 Mean powers of EEG frequency bands averaged across all the lobes of the brain before and after yoga intervention

EEG band powers120574 (120583V2Hz) 120573 (120583V2Hz) 120572 (120583V2Hz) 120579 (120583V2Hz) 120575 (120583V2Hz)

Yoga groupBefore yoga 380 plusmn 093 232 plusmn 049 395 plusmn 070 2136 plusmn 343 422 plusmn 042After yoga 365 plusmn 069 491 plusmn 163 567 plusmn 168 1588 plusmn 257 579 plusmn 106

Control groupBefore yoga 298 plusmn 136 386 plusmn 096 392 plusmn 097 1757 plusmn 254 446 plusmn 089After yoga 294 plusmn 133 372 plusmn 082 387 plusmn 090 2112 plusmn 387 437 plusmn 078

and cognition parietal lobe with visual perception recogni-tion information processing and spatial reasoning temporallobe with memory and processing of verbal and auditorysignals and occipital lobe with visual spatial processing andrecognition An increase of EEG frequency band powers inthese lobes indicates the enhancement of certain type ofcognitive skillsThe type of the cognitive skills developed canbe assessed based on increased or decreased EEG band powerin these lobesThemean absolute values of these band powersin various lobes of the brain are shown in Table 6

The increase of frontal 120579 band power indicates intellectualconcentration andmeditative state of relief from nervousnessand is negatively related with sympathetic activation Thisreflects a near relationship between autonomic functionactivity of medial frontal neural circuitry and probability ofcontrolling central nervous system (CNS) functions owing toyoga practice and meditation [12] 120572 waves are indicative ofincreased relaxed state ofmind and its bandpower is inverselyrelated to mental activity Yoga enhanced various cognitiveskills improved sense of wellbeing and responsiveness andenhanced cognitive functions as substantiated by increased120572 and 120573 band powers and various engagement indices Italso improves mental consciousness and achieves reductionin stress and strain and thus advocates complete health andwellbeing in an individual [40] Increase in 120573 band powerwould indicate a higher level of alertness and enhancedengagement task whereas increased band powers of 120572 and 120579would indicate decreased alertness and reduced engagementtask [25] The increase of 120573 power reflects improvement ofcertain cognitive functions such as memory and reactiontime That of 120572 and 120575 indicates synchronization of brainactivity The total EEG band power also increased in yogagroup compared to the control group

The ratio 120579120572 is associated with HR This ratio decreasedin all lobes of the brain indicating the relaxed state of sub-jectsThis reduction could be either increase of 120572 band poweror decrease of 120579 band power Since 120572 power increased in yogagroup this ratio decreased indicating enhancement of certaincognitive faculties (memory attention) and improvement inthe HRV These in turn indicate indirect improvement incertain cognitive functions such as reaction time The ratio120573120572 [25] is called arousal indexThis indicates level of arousalbased on interbeat intervals (IBI) activity Arousal level gt0indicates higher than normal arousal and lt0 indicates lowerthan normal arousal

This ratio increased (4711) in yoga group whiledecreased in control group (243) The increases of thisratio indicate enhanced cognitive functions such as attentionThe decreases of this ratio reflect reduction in the corecapabilities of cognitive functions This ratio increased in alllobes of the brain but the maximum increase was observedin parietal (7805) central (5312) and temporal (4504)lobes It increased to (3824) and (1976) in frontal andoccipital lobes respectively The ratio (120575 + 120579)120572 is calledexecutive load index [28] and is a measure of executive loador comprehension Positive value indicates increased loadand negative value indicates decreased load It reflects theoscillations in precise cortical network active among spatiallydisjoint brain compartment This ratio decreased (4098)in experimental group while it increased (1719) slightlyin control group The decrease in this ratio may be dueto increase in 120572 band power or reduced band power ofeither 120575 or 120579 or both It is observed that 120572 band power wasincreased in yoga practicing group This ratio was also founddecreased in all the lobes of the brain Another importantparameter 120579(fro)120572(par) [27] is called task load index Thisratio decreases in experimental group while it increases incontrol group It is evident from the relation that the ratiodecreases due to increase in 120572 band power These results areshown in Tables 7 and 8

The ratio 120579120573 indicates central nervous system (CNS)arousal [30] and increased ratio is marker of under arousalThis ratio decreased in yoga group The reductions in thisratio reflect the shift of 120572 and 120579 activity towards 120573 activityThe increased 120573 band powers indicate enhanced cognitiveperformance such as memory attention and concentrationThe ratio 120572120575 which is called ldquobrain perfusionrdquo index [29]was increased (46) in yoga practiced group This indicatessufficient amount of blood flow to the different parts ofthe brain among yoga group These in turn enhances thebetter functioning of the brain The ratio LFHF can beexpressed in terms of (120579 + 120575)(120572 + 120573) [29] Slower brainoscillations (120579 and 120575) harmonize considerable neuron groupsacross larger brain areas and faster oscillations (120572 and 120573)synchronize smaller focused neuronal assemblies [41]Whengroups of neurons oscillate together synchronously theymore effectively communicated with each other The index(120579 + 120575)(120572 + 120573) indicates sympathovagal balance of theautonomic nervous system (ANS) Lower ratios indicatebetter balance of ANSThis ratio decreased in yoga group but

10 Computational and Mathematical Methods in Medicine

Table 7 Cognitive index parameters of yoga group before and after yoga intervention Postintervention values are shown within theparenthesis

EEG indices Yoga groupFrontal Central Parietal Occipital Temporal

120579120572 4621 (2806) 4951 (2063) 5059 (2973) 8792 (4609) 4604 (2480)120572120579 0216 (0356) 0202 (0485) 0198 (0336) 0114 (0217) 0217 (0403)120573120572 0612 (0846) 0625 (0957) 0523 (0931) 0607 (0727) 0564 (0818)120573120579 0132 (0302) 0126 (0464) 0103 (0313) 0069 (0158) 0123 (0330)120573(120572 + 120579) 0109 (0222) 0105 (0312) 0086 (0234) 0062 (0130) 0101 (0235)120579(fro)120572(par) 4621 (2806) 4951 (2063) 5059 (2973) 8792 (4609) 4604 (2480)(120575 + 120579)120572 5590 (3926) 5964 (3200) 6168 (3961) 10112 (5907) 5614 (3243)sum(120575 + 120579)120572 = 46392 (27876)

Table 8 Global EEG band power ratios before and after yoga inter-vention

EEG indices Yoga group Control groupBefore yoga After yoga Before yoga After yoga

120579120572 5405 2800 4485 5460120572120579 0185 0357 0228 0183120573120572 0588 0865 0986 0962120573120579 0109 0309 0220 0176120573(120572 + 120579) 0092 0228 0180 0149120579(fro)120572(par) 5405 2800 4485 5460(120575 + 120579)120572 6472 3820 5623 6590sum(120575 + 120579)120572 46392 27876 40456 47080

Table 9 EEG indices and their values before and after yoga inter-vention

Parameters Yoga group ControlBefore After Before After

120572120575 0937 0980 0879 0885(120579 + 120575)(120572 + 120573) 408 205 332 289120572120573 170 116 10139 10394120575120579 0197 0364 0209 2488120579120573 9198 3235 5530 4721

did not change in control group The ratio 120572120573 [31] which iscalled desynchronization is used to analyze vigilance indexand 120575120579 is called synchronization The ratio 120572120573 decreasedwhich is desirable The increase 120573 of band power indicatesimproved cognitive performance Since the parameter is indenominator the ratio decreases when there is increasedcognitive performance However in control group this ratiowas slightly increased Another ratio 120575120579 was increasedrelatively by small amount in experimental group than thecontrol groupThe 120572120575 ratio was decreased in frontal centraland occipital lobes while it increased in parietal and temporallobes These results are shown in Tables 9 10 and 11

The relative EEG band powers of 120573 120572 and 120575 increasedin yoga group in all the lobes of the brain The increases ofthese band powers indicate improvement of certain cognitivefunctions such as memory attention executive functionsand concentration The increase of 120575 power and decrease of

1932 1958

8783

222914911860 1618

10558

21181189

0

20

40

60

80

100

120

PSD

(120583V2H

z)

BeforeAfter

120573 120572 120579 120575 120574

Figure 5 Global EEG band powers of control group before andafter intervention

120579 power indicate improvement in neural activityThe variousEEG band powers are shown in Figure 1

The total band power (global) of 120573 120572 and 120575 increasedamong yoga group The increased 120573 power was associatedwith enhanced cognitive performance such as improvedalertness The maximum 120573 power increased in frontal andcentral lobes of the brain This indicates the improvementin emotion process and cognition The increased 120572 anddecreased 120579 powers physiologically signify the enhancedvigilance and increased alertness level of subjects These areshown in Figure 2 The improvement in cognitive functionswas associated with increased power in high frequency band(120573) and reduction in low frequency band (120579) Therefore 120573120579ratio is suitable index to assess the improvement in cognitiveskills of the subjectsThe cognitive performance index 120573(120572 +120579) increased and ratio of sum of low frequency to sum of highfrequency (120579 + 120575)(120573 + 120572) was decreased among yoga groupwhich is shown in Figure 3

There were no significant changes in EEG band powersengagement indices total power and cognitive performancesindices among control group The various performancesparameters of control group are shown in Figures 4 5 6 and7

Computational and Mathematical Methods in Medicine 11

Table 10 EEG index values of yoga group in different lobes of the brain before and after yoga intervention Postintervention values are shownin parenthesis

Parameters Brain lobesFrontal Central Parietal Occipital Temporal

120572120575 1032 (0893) 0988 (0879) 0902 (1011) 0757 (0770) 0990 (1312)(120579 + 120575)(120572 + 120573) 3468 (0534) 3669 (0566) 4050 (0402) 6294 (0363) 3589 (0363)120572120573 1634 (2806) 1599 (2063) 1913 (2973) 1648 (4609) 1772 (2480)120575120579 0210 (0814) 0205 (0524) 0219 (0614) 0150 (0570) 0219 (0657)120579120573 7550 (3316) 7916 (2156) 9675 (3194) 14492 (6341) 8159 (3032)

Table 11 EEG index values of control group in different lobes of the brain before and after yoga intervention Postintervention values areshown in parenthesis

Parameters Brain lobesFrontal Central Parietal Occipital Temporal

120572120575 0914 (0944) 0940 (0940) 0760 (0760) 0825 (0825) 0930 (0931)(120579 + 120575)(120572 + 120573) 0424 (0356) 0326 (0261) 0271 (0241) 0262 (0218) 0486 (0438)120572120573 3428 (4186) 3711 (4891) 6412 (7311) 5513 (6817) 4385 (4970)120575120579 0716 (0741) 0445 (0445) 0524 (0523) 0409 (0409) 1433 (1433)120579120573 3269 (4185) 3958 (5251) 5747 (6647) 6633 (8531) 4235 (4839)

After yogaBefore yoga

736686

586694

576

737 776

585

752

571

0

1

2

3

4

5

6

7

8

9

Frontal Central Perietal Occipital Temporal

PSD

(120583V2H

z)

Figure 6 Global EEGband powers of control group in various lobesof the brain before and after intervention

4 Conclusions

The regular practices of yoga for a period of five months byyoung healthy engineering students enhance different typesof cognitive skills Apart from cognitive the yoga practiceresulted in many health benefits such as improvement inheart rate variability The ratio SDNNRMSSD increasedwhile the ratio LFHF decreasedThis indicates improvementin the parasympathetic activity and decrease in sympatheticactivity Hence the current results suggest that the practice ofyoga modifies the sympathovagal balance towards parasym-pathetic activation improved the heart rate variability andenhanced sense of wellbeing Since the study population isyoung healthy engineering graduates it would be interestingto investigate whether the yoga practice could result inimprovement in the academic performances

3319

0153

6593

2891

0174

5672

0

1

2

3

4

5

6

7

8

Enga

gem

ent i

ndex

val

ue

Before yogaAfter yoga

(120575 + 120579)(120572 + 120573) 120573(120572 + 120579) (120575 + 120579)120572

Figure 7 CNS activity engagement index and executive load indexof control group before and after intervention

In a nutshell it is proved beyond doubt that yogapractices resulted in effective improvements in physiologicalparameters indirectly improving psychological parametersand various cognitive functions The results of this studygreatly encourage further investigation to study whether thepractice of yoga could also enhance academic performance

Limitations of the Study

Limitations of this study include small number of samplesand lack of dedicated control group and methodologicaldifferences Further investigation can be done by employingpsychological tests to evaluate cognitive behavior

12 Computational and Mathematical Methods in Medicine

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

The authors acknowledge the Principal of PDA College ofEngineering Kalaburagi for deputingHNagendra to pursuePhD degree and Department of Electrical EngineeringIIT Roorkee for providing an opportunity under QualityImprovement Programme (QIP) They also acknowledge thestudents who participated in this study and give specialthanks to the yoga instructor

References

[1] P Sengupta ldquoHealth impacts of yoga and pranayama a state-of-the-art reviewrdquo International Journal of Preventive Medicinevol 3 no 7 pp 444ndash458 2012

[2] A Ross and S Thomas ldquoThe health benefits of yoga and exer-cise a review of comparison studiesrdquoThe Journal of Alternativeand Complementary Medicine vol 16 no 1 pp 3ndash12 2010

[3] P A Balaji S R Varne and S S Ali ldquoPhysiological effects ofyogic practices and transcendental meditation in health anddiseaserdquo North American Journal of Medical Sciences vol 4 no10 pp 442ndash448 2012

[4] A Bussing A Michalsen S B S Khalsa S Telles and K JSherman ldquoEffects of yoga on mental and physical health ashort summary of reviewsrdquo Evidence-based Complementary andAlternative Medicine vol 2012 Article ID 165410 7 pages 2012

[5] T N Sathyaprabha P Satishchandra C Pradhan et al ldquoModu-lation of cardiac autonomic balance with adjuvant yoga therapyin patients with refractory epilepsyrdquo Epilepsy and Behavior vol12 no 2 pp 245ndash252 2008

[6] S Telles N Singh and A Balkrishna ldquoHeart rate variabil-ity changes during high frequency yoga breathingand breathawarenessrdquo BioPsychoSocial Medicine vol 5 article 4 2011

[7] L Jatiya KUdupa andA B Bhavanani ldquoEffect of yoga trainingon handgrip respiratory pressures and pulmonary functionrdquoIndian Journal of Physiology and Pharmacology vol 47 no 4pp 387ndash392 2003

[8] D Nangia and R Malhotra ldquoYoga cognition and mentalhealthrdquo Journal of the IndianAcademy ofApplied Psychology vol38 no 2 pp 262ndash269 2012

[9] S Telles and P Sarang ldquoEffects of two yoga based relaxationtechniques on Heart Rate Variability (HRV)rdquo InternationalJournal of Stress Management vol 13 no 4 pp 460ndash475 2006

[10] S Telles R Nagarathna P R Vani and H R Nagendra ldquoAcombination of focusing and defocusing through yoga reducesoptical illusion more than focusing alonerdquo Indian Journal ofPhysiology and Pharmacology vol 41 no 2 pp 179ndash182 1997

[11] K K F Rocha A M Ribeiro K C F Rocha et al ldquoImprove-ment in physiological and psychological parameters after6months of yoga practicerdquo Consciousness and Cognition vol 21no 2 pp 843ndash850 2012

[12] R Khadka B H Paudel V P Sharma S Kumar and N Bhat-tacharya ldquoEffect of yoga on cardiovascular autonomic reactivityin essential hypertensive patientsrdquo Health Renaissance vol 8no 2 pp 102ndash109 2010

[13] L C M Vanderlei C M Pastre R A Hoshi T D de Carvalhoand M F de Godoy ldquoBasic notions of heart rate variabilityand its clinical applicabilityrdquo Brazilian Journal of CardiovascularSurgery vol 24 no 2 pp 205ndash217 2009

[14] M V Hoslashjgaard N-H Holstein-Rathlou E Agner and JK Kanters ldquoDynamics of spectral components of heart ratevariability during changes in autonomic balancerdquoTheAmericanJournal of PhysiologymdashHeart and Circulatory Physiology vol275 no 1 pp H213ndashH219 1998

[15] S Boonnithi and S Phongsuphap ldquoComparison of heart ratevariability measures for mental stress detectionrdquo in Proceedingsof the Computing in Cardiology (CinC rsquo11) pp 85ndash88 2011

[16] H Kobayashi K Ishibashi and H Noguchi ldquoHeart ratevariability an index for monitoring and analyzing humanautonomic activitiesrdquo Journal of Physiological Anthropology andApplied Human Science vol 18 no 2 pp 53ndash59 1999

[17] J Sztajzel ldquoHeart rate variability a noninvasive electrocardio-graphic method to measure the autonomic nervous systemrdquoSwiss Medical Weekly vol 134 no 35-36 pp 514ndash522 2004

[18] J Taelman S Vandeput A Spaepen and S van Huffel ldquoInflu-ence of mental stress on heart rate and heart rate variabilityrdquo inProceedings of the 4th European Conference of the InternationalFederation for Medical and Biological Engineering (IFMBE rsquo08)vol 22 pp 1366ndash1369 November 2008

[19] E Tharion S Parthasarathy and N Neelakantan ldquoShort-termheart rate variability measures in students during examina-tionsrdquo National Medical Journal of India vol 22 no 2 pp 63ndash66 2009

[20] Y Sun N Ye and X Xu ldquoEEG analysis of alcoholics andcontrols based on feature extractionrdquo in Proceedings of the 8thInternational Conference on Signal Processing (ICSP rsquo06) 2006

[21] C Y Chen W K Wong C D Kuo Y T Liao and MD Ke ldquoWavelet real time monitoring system a case studyof the musical influence on electroencephalographyrdquo WSEASTransactions on Systems vol 7 no 2 pp 56ndash62 2008

[22] C Parameswariah and M Cox ldquoFrequency characteristics ofwaveletsrdquo IEEE Power Engineering Review vol 22 no 1 p 722002

[23] A Holm K Lukander J Korpela M Sallinen and K M IMuller ldquoEstimating brain load from the EEGrdquo The ScientificWorld Journal vol 9 pp 639ndash651 2009

[24] J Gruzelier ldquoA theory of alphatheta neurofeedback creativeperformance enhancement long distance functional connectiv-ity and psychological integrationrdquo Cognitive Processing vol 10no 1 supplement pp 101ndash109 2009

[25] F G Freeman P J Mikulka L J Prinzel and M W ScerboldquoEvaluation of an adaptive automation system using three EEGindices with a visual tracking taskrdquo Biological Psychology vol50 no 1 pp 61ndash76 1999

[26] A F Rabbi K Ivanca A V Putnam A Musa C B Thadenand R Fazel-Rezai ldquoHuman performance evaluation based onEEG signal analysis a prospective reviewrdquo in Proceedings of the31st Annual International Conference of the IEEE Engineeringin Medicine and Biology Society (EMBC rsquo09) pp 1879ndash1882September 2009

[27] A Gevins M E Smith LMcEvoy andD Yu ldquoHigh-resolutionEEGmapping of cortical activation related to workingmemoryeffects of task difficulty type of processing and practicerdquoCerebral Cortex vol 7 no 4 pp 374ndash385 1997

[28] J T Coyne C Baldwin A Cole C Sibley and D M RobertsldquoApplying real time physiological measures of cognitive load

Computational and Mathematical Methods in Medicine 13

to improve trainingrdquo in Foundations of Augmented CognitionNeuroergonomics and Operational Neuroscience vol 5638 ofLecture Notes in Computer Science pp 469ndash478 SpringerBerlin Germany 2009

[29] G Bashein M L Nessly S W Bledsoe et al ldquoElectroen-cephalography during surgery with cardiopulmonary bypassand hypothermiardquo Anesthesiology vol 76 no 6 pp 878ndash8911992

[30] R J Barry A R Clarke S J Johnstone R McCarthy andM Selikowitz ldquoElectroencephalogram 120572120573 ratio and arousal inattention-deficithyperactivity disorder evidence of indepen-dent processesrdquoBiological Psychiatry vol 66 no 4 pp 398ndash4012009

[31] L Cao J Li Y Sun H Zhu and C Yan ldquoEEG-based vig-ilance analysis by using fisher score and PCA algorithmrdquo inProceedings of the 1st IEEE International Conference on Progressin Informatics and Computing (PIC rsquo10) pp 175ndash179 ShanghaiChina December 2010

[32] L I Aftanas and S A Golocheikine ldquoNon-linear dynamiccomplexity of the humanEEGduringmeditationrdquoNeuroscienceLetters vol 330 no 2 pp 143ndash146 2002

[33] M Balasubramaniam S Telles and P M Doraiswamy ldquoYogaon our minds a systematic review of yoga for neuropsychiatricdisordersrdquo Frontiers in Psychiatry vol 3 Article ID Article 117pp 1ndash16 2013

[34] B S Moon H C Lee Y H Lee J C Park I S Oh and JW Lee ldquoFuzzy systems to process ECG and EEG signals forquantification of the mental workloadrdquo Information Sciencesvol 142 no 1ndash4 pp 23ndash35 2002

[35] P Raghuraj A G Ramakrishnan H R Nagendra and S TellesldquoEffect of two selected yogic breathing techniques on heart ratevariabilityrdquo Indian Journal of Physiology and Pharmacology vol42 no 4 pp 467ndash472 1998

[36] J J Sollers III T W Buchanan S M Mowrer L K Hill and JFThayer ldquoComparison of the ratio of the standard deviation ofthe r-r interval and the rootmean squared successive differences(SDrMSSD) to the low frequency-to-high frequency (LFHF)ratio in a patient population and normal healthy controlsrdquoBiomedical Sciences Instrumentation vol 43 pp 158ndash163 2007

[37] C Zhao C Zheng M Zhao and J Liu ldquoPhysiological assess-ment of driving mental fatigue using wavelet packet energy andrandom forestsrdquo The American Journal of Biomedical Sciencesvol 2 no 3 pp 262ndash274 2010

[38] O V Grishin V G Grishin D Yu Uryumtsev S V Smirnovand I G Jilina ldquoMetabolic rate variability impact on verylow-frequency of heart rate variabilityrdquo World Applied SciencesJournal vol 19 no 8 pp 1133ndash1139 2012

[39] E Basar C Basar-Eroglu S Karakas and M SchurmannldquoGamma alpha delta and theta oscillations govern cognitiveprocessesrdquo International Journal of Psychophysiology vol 39 no2-3 pp 241ndash248 2000

[40] K C Khare and S K Nigam ldquoA study of electroencephalogramin meditatorsrdquo Indian Journal of Physiology and Pharmacologyvol 44 no 2 pp 173ndash178 2000

[41] J Jacobs and M J Kahana ldquoDirect brain recordings fueladvances in cognitive electrophysiologyrdquo Trends in CognitiveSciences vol 14 no 4 pp 162ndash171 2010

Submit your manuscripts athttpwwwhindawicom

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Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

MEDIATORSINFLAMMATION

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Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Behavioural Neurology

EndocrinologyInternational Journal of

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Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Disease Markers

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BioMed Research International

OncologyJournal of

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Oxidative Medicine and Cellular Longevity

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

PPAR Research

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Immunology ResearchHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal of

ObesityJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Computational and Mathematical Methods in Medicine

OphthalmologyJournal of

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Diabetes ResearchJournal of

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Research and TreatmentAIDS

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

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Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Parkinsonrsquos Disease

Evidence-Based Complementary and Alternative Medicine

Volume 2014Hindawi Publishing Corporationhttpwwwhindawicom

2 Computational and Mathematical Methods in Medicine

yoga can also result in changes in perception attention andcognition Investigations have shown the beneficial effects ofyoga on cognition such as increased performances on visualand verbal memory and improved memory scores [11]

Compared to physical exercise yogamay bemore effectiveor even better in improving health related conditions Despitecorpus of research on the subjects the lack of evidencebased on scientific approaches has limited the application ofyoga as an accepted method for improvement of health [11]Hence further research is needed on the impact of yoga andits potential benefits on healthy subjects Thus yoga offersmany positive effects on cognitive faculties reduction ofstress and emotional intensity Previous studies were mainlyconducted on unhealthy or relatively elder subjects Thefocus was generally on physical and neurological benefitsFurther investigation is required to study the potential ben-efits of yoga on cognitive functions and their relation withphysiological parameters In this study the effects of yogapractices on cognitive skills autonomic nervous system heartrate variability and mental health are analyzed in terms ofphysiological parameters such as electroencephalogram andelectrocardiogram

Therefore the objective of this study is to investigate theeffectiveness of yoga practice and to evaluate physiologicalparameters related to cognitive aspects on novice subjectsThe study primarily focused the effect of yoga on cognitivebehavior in terms of physiological parameters In the currentstudy the yoga practice involved combined practice of easyasanas (postures) meditation and pranayama (breathingexercise) It is known that yoga involving relaxation tech-niques improve the functioning of cardiovascular autonomicnervous system Yoga is correlated with decreased sym-pathetic adrenergic receptor sensitivity which might affectcardiovascular response during stress [12]

11 Heart Rate Variability and Its Indices Heart rate vari-ability (HRV) is a measure of deviations in the interbeatR-R intervals It is a noninvasive method used to assessthe functioning of the autonomic nervous system (ANS)which is responsible for the regulations of many physi-ological processes of the human being [13] The HRV iscaused due to changes in input to the sinus node fromthe autonomic nervous system (ANS) [14] The sinus node(natural pace maker) is one of the major components ofthe cardiac conduction system that regulates the heart rate(HR) by controlling sympathetic nervous system (SNS) andparasympathetic nervous system (PNS) limbs of the ANS[15] Higher HRV is an indicator of adequate adaptation tothe new environment and effective functioning of the ANSwhile lower HRV is an indicator of inadequate adaptation ofANS and poor physiological function of the individuals [13]HRV and HR are inversely correlated The escalation in theHR is due to increased sympathetic and decreased parasym-pathetic activity whereas its reductionmainly depends on thedominance of parasympathetic activity

Generally forHRV analysis parameters can be computedby two methods [13 15ndash17]

Table 1 The equations used to compute time domain measures

Index Equations Unit

mHRV 1

119873 minus 1

119873

sum

119894=1

(RR119894) ms

mHR119873

sum

119894=1

(

1000

RR119894

) lowast 60 bpm

SDNN sqrtsum119873

119894=1(RR119894minusmRR)2

119873 minus 1

ms

RMSSD sqrt mean ((RR119894+1minus RR119894)2) ms

CVRR SDNNmean (RR)

lowast 100 mdash

(i) Time domain measures are directly computed fromthe time series of the RR intervals In the literaturethere are many time domain measures available forHRV analysis In this paper the following indices areused for its analysismHR mean RR intervalsmHRV mean heart rate variability and it indicatesthe total amount of deviations of both instantaneousHR and RR intervals It reflects sympathetic andparasympathetic activity of the ANS on the sinusnode of the heartSDNN standard deviation of all NN intervals andan indicative of global HRV It indicates all the longterm elements and circadian rhythms responsible forvariability in the recording intervalRMSSD the Square roots of the mean of the sumof the squares of differences between adjacent NNintervals and it reflects the short cyclical variability inthe autonomic tone that is largely vagally mediatedCVRR coefficient of variations of RR intervals and itis used to reflect the parasympathetic nervous systemactivitythe important time domain parameters are shown inTable 1

(ii) Frequency domain parameters are computed byapplying fast Fourier transform (FFT) to the timeseries of the raw RR intervals FFT is the most pow-erful and efficient algorithm used to break the HRVsignal into a series of sine and cosine componentsThis Fourier transformed signal is further translatedto power spectrum by squaring magnitude of each[18] The fundamental frequency components werecomputed by integrating the periodogram Generallythe power spectrum can be classified into the follow-ing four groups [19]Very low frequency (VLF 00033ndash004Hz) powerthe function of this frequency range is not welldefined but sometimes it can be used as the index ofsympathetic activity of ANS

Computational and Mathematical Methods in Medicine 3

05

10152025303540

Frontal Central Perietal Occipital Temporal Total

PSD

(120583V2H

z)

(a) 120573 power

Frontal Central Perietal Occipital Temporal Total0

5

10

15

20

25

30

PSD

(120583V2H

z)

(b) 120572 power

Frontal Central Perietal Occipital Temporal Total0

20

40

60

80

100

120

PSD

(120583V2H

z)

(c) 120579 power

Frontal Central Perietal Occipital Temporal Total0

5

10

15

20

25

30

35

PSD

(120583V2H

z)

(d) 120575 power

Frontal Central Perietal Occipital Temporal Total

BeforeAfter

02468

101214161820

PSD

(120583V2H

z)

(e) 120574 power

Figure 1 EEG band powers of yoga group in various lobes of the brain before and after intervention

Low frequency (LF 004ndash015Hz) power this band iscomplex in nature and an index of both sympatheticand parasympathetic activity and influences HRVpatterns

High frequency (HF 015ndash04Hz) power it is theindex of parasympathetic activity and is used toindicate slow changes in the HR

Very high frequency (VHF gt04Hz) this frequencyis generally considered as noise and has no clinicalsignificance

LFHF ratio It reflects the overall balance of the ANSThe lower ratio is recommended by the task force

In normal in resting condition this ratio lies in therange of 1 and 2

Total power (TP) variance of all NN intervals in thefrequency range less than 04Hz

The VLF LF HF and TP are expressed in ms2 unitswhen computed in absolute values The important frequencydomain parameters used for the computation are shown inTable 2

The spectral parameters of HRV are usually normalizedto minimize the effect of redundancy inherent in them inmost of the research work The important frequency domainparameters are shown in Figure 2

4 Computational and Mathematical Methods in Medicine

Table 2 The equations used to compute frequency domain mea-sures

Index Equations Unit

LFnuLF(LF +HF)

lowast 100

HFnuHF(LF +HF)

lowast 100

SVI LFHF

mdash

LFRelpowerLFTPlowast 100 mdash

HFRelpowerHFTPlowast 100 mdash

dLFHF 1003816100381610038161003816LFnu minusHFnu

1003816100381610038161003816

where TP = VLF + LF + HF

11611976

10682

2109 19022455 2837

7942

28941824

0

20

40

60

80

100

120

BeforeAfter

minus20120573 120572 120579 120575 120574

PSD

(120583V2H

z)

Figure 2 Global EEG band powers of yoga group before and afterintervention

12 EEG Band Frequencies and Cognitive Processes Thebrainactivity which changes continuously with time is called ldquoelec-troencephalogramrdquo (EEG) which can be used to investigatethe cognitive abilities and memory executions of individualsin terms of its band of frequencies

The EEG is highly complex and is combination of fivedifferent frequency waveforms namely 120575 (delta) 120579 (theta) 120573(beta)120572 (alpha) and 120574 (gamma)waves respectively [20]Theamplitude of the brain waves is approximately in the rangeof 10 120583V to 250120583V and the frequency varies between 05Hzand 100HzThe frequency range and their characteristics areshown in Table 3

The EEG waveforms may be global or localized to thespecific areas on the scalp This kind of electrical data isimportant to study the correlation between yoga asanas andphysiological states because any shift in the EEG frequencyrange reflects the physiological arousalThe various EEG ratioindices and their physiological and cognitive interpretationsare shown in Table 4

13 Extraction of EEG Band Frequencies Using DiscreteWavelet Transforms (DWT) Discrete wavelet transforms(DWT) are widely used for the analysis of physiological

signals as compared to the classical techniques such as fastFourier transforms (FFT) When FFT is applied on thetime series signal the signal information is available in theform of spectral parameters That is the whole time domaininformation will be lost It is equivalent to windowed Fouriertransform and can be used to measure both the time andfrequency changes of a signal [21]

The DWT splits the input signal into approximation(trend) and detailed coefficients (fluctuation) respectivelyThe approximation coefficient can further be split into anew approximation and detailed coefficients This process iscontinued progressively to get a new set of approximation anddetailed coefficients of a signal at various levels of decomposi-tion [22] The selection of analyzing wavelet is called motherwavelet and number of decomposition levels to be carried outis the critical pointThemother wavelet determines the shapeof the signal to be decomposed In this paper the waveletfunction db4 is used to extract five frequency bands (120575 120579120572 120573 and 120574) of EEG signal The application of higher orderwavelet function such as db20 produces large number ofcoefficients Larger number of coefficients average out thedetail components of the signal and fail to detect fast movingsignals such as EEG To retrieve the information at a specificinstant of time the wavelets with less number of coefficientsare better choice The lower order wavelet function db4has good time and frequency localization properties andin addition this wavelet has similar morphology as thatof EEG signal to be detected Therefore db4 wavelets arebetter choice for precisely detecting fast moving transientsand short duration information signals Thus by the processof decomposition DWT can detect the important hiddenfeatures from the original signal

In this study the EEG signal was acquired with samplingfrequency of 500Hz The useful information of this signallies in the range of 05ndash70Hz Hence a level of 7 usingdb4 was applied to decompose the EEG signal into itsapproximate (A1ndashA7) and detail (D1ndashD7) coefficients Afterthe seventh level of decomposition the band of frequenciesobtained are D1 (250ndash500Hz) A1 (0ndash250Hz) D2 (125ndash250Hz) A2 (0ndash125Hz) D3 (625ndash125Hz) A3 (0ndash625Hz)D4 (3125ndash625Hz) A4 (0ndash3125Hz) D5 (15625ndash3125Hz)A5 (0ndash15625Hz) D6 (78125ndash15625Hz) A6 (0ndash78125Hz)D7 (3906ndash7813Hz) and A7 (0ndash3906Hz) respectively Thedecomposition levels from D1 to D3 were considered asnoise components and hence excluded from the analysisThe finer detailed coefficients from levels D4ndashD7 and finalapproximate coefficients from level A7 are retained as theyapproximately represent the EEG physiological frequencysubbands of 120574120573120572 120579 and120575 respectivelyThese five frequencybands are analyzed to investigate different cognitive effectsdue to yoga among healthy subjects Different EEG ratiosused in this study to investigate cognitive performances interms of physiological parameters are shown in Figure 4which are derived from various sources

2 Methodology and Experimental Procedure

21 Subjects The total number of subjects who participatedin the experiment was 30 young healthy graduate and

Computational and Mathematical Methods in Medicine 5

Table 3 Five EEG frequency bands

Parameters Frequency range (Hz) Magnitude (120583V) Activity Remark120573 13ndash30 lt30 120583V Desynchronized Mental occupation120572 8ndash13 50ndash100 120583V Synchronized Relaxed tranquility and wakefulness120579 4ndash8 20ndash40 120583V Desynchronized Dreaming state120575 05ndash4 75ndash150 120583V Desynchronized State of dreamless sleep120574 30ndash70 mdash Synchronized Sensory integration

Table 4 EEG band ratios and their physiologicalcognitive activityindex interpretation

EEG band ratios Activitycorrelation Sources120579120572 Heart rate (HR) [23]

120572120579 Performance enhancementindex or ldquowellbeingrdquo [24]

120573120572 Arousal index [25]120573120579 Neural activity [25]

120573(120572 + 120579) Cognitive performance andattentional resource index [26]

120579(frontal)120572(parietal) Task load index [27](120575 + 120579)120572 Executive load index [28]120572120575 Brain perfusion [29]120579120573 CNS arousal [30](120579 + 120575)(120572 + 120573) Sum of LF to HF ratio [29]120572120573 Desynchronization [31]120575120579 Synchronization(120579 + 120572)120573 Vigilance index [31]

postgraduate engineering students of IIT Roorkee (male =27 female = 3) All the subjects were right handed withnormal eye sight The study population was divided intotwo groups experimental group and control group In thisstudy the sample size is relatively small and both groupshave the same size The study population was randomlyassigned to either of the groups by block randomizationmethod to achieve the balance The block size of two wasused Both participants and investigators were unaware of thegroups to be assigned in advance Each group consisted of15 subjects with two females in experimental group and onein control group The mean and standard deviation of eachgroup were 2242 plusmn 230 and 2367 plusmn 209 respectively Thesame subjects were chosen for both experimental and controlgroups to diminish misperceiving influences and make thestudy more effective Subjects with previous yoga practicehistory of alcohol consumption smoking and any other drugconsumption were excluded from this studyThe participantswere informed a priori about the study and their consent wasobtained Subjects participated voluntarily and cooperatedthroughout the training period The subjects were asked tonot to deviate their regular life style during this study All thesubjects of experimental group obtained same yoga trainingfor a period of fivemonths for 15 hours per day between 6 pmand 730 pm

In this study the physiological parameters such as ECGand their ratio indices have been evaluated to assess thecognitive benefits of the yoga practice along with its wellestablished health benefits This may provide the windowfor further investigation to correlate the actual measures ofcognitive functions and their physiological parameters

The practice of yoga schedule consisted of prayerpranayama (breathing techniques) and simple yogic pos-tures Explanations on stress management importance ofmeditation and yoga in everyday life were also briefed

The subjects practiced yoga under observation of trainedyoga instructor During practice session various types ofasanas (postural exercises) pranayama (breathing tech-niques) and dhyana (meditation) were performed Theseasanas increase the strength concentration will power andmindfulness by manipulating the natural energy of the body[1 32 33]

(1) Standing asanas (postures) they consisted of suryanamaskar dandasana urdhave asana trikonasanaardha asana hasta padasana mahavir asana andvatayanasana

(2) Sitting asanas (postures) they include mandookasana and oorm asana ushtra asan ardha matsy-endrasana vakrasana supt asana matsyendrasanauttan mandukasana vakasana mayoor asan padmvak asan padma mayurasana pashchimottanasaneka padangusthasana vipreet pad asan and purnachakrasana

(3) Asana (posture) lying on back this includes uttanpad asana pawanmuktasana market asan shree-shan sarvangasana halasana setu bandhasana andchakrasana

(4) Asana (posture) lying on stomach this includes nau-kasana yan asan shalabh asan and dhanurasana

(5) Pranayama (breathing) and kriya include Anulom-vilom kapalbhati Ujjayi pranayama Bhramari pra-nayama sheetali pranayama sheetkari pranayamasurya bheda pranayama bhastrika pranayama bahyapranayama udgeeth pranayama kaki mudra andshanmukhi mudra Everyday practice session wasconcluded with prayer and meditation

22 Recording ECG and EEG Signals and Analysis BothECG and EEG signals were recorded simultaneously usingBIOPACMP150 System (EEG100C = 10 nos and ECG100C =3 nos) with Acqknowledge 40 software

6 Computational and Mathematical Methods in Medicine

ECG signal was recorded using five electrodes by con-necting to left and right wrinkles and left and right armsand one electrode at chest Before fixing the electrodes theywere cleaned and electrode gel was applied to reduce theskin resistance to get good quality of recording signal EEGsignal was recorded by fixing the CAP100C on the scalp ofthe subjects This cap was made of Lycra type fabric with20 reusable tin electrodes attached to it according to theinternational 10ndash20 norms Before fixing the cap on subjectsscalp the electrodes were cleaned with saline water andelectrode gel was appliedThismaintains the resistance below5 kΩ between the scalp and electrodes

All the data were collected during 6 pm to 730 pm atthe yoga centre of the temple premises in two stages Thedata collected at the beginning of the intervention period wasconsidered as the first stage during which five minutes ofbaseline ECG and EEG signals were recorded from subjectsof both experimental and control groups in sitting positionwith eyes closed The baseline signal was saved on the harddisk for offline processing

Both ECG and EEG signals were recorded with a sam-pling frequency of 512Hz to have better resolution of R-Rtime interval series and EEG activity

The experimental group practiced yoga for a period of fivemonths for 15 hr per day in the evening from 6 pm to 730pmThe control group was asked not to practice any form ofyogic practices or physical exercises during this period Theend of five months yoga training period was considered assecond stage During this stage again both ECG and EEGdata were collected from experimental and control groupfor a period of 10 minutes During recording subjects wereasked to minimize eye blinks and avoid body movements tominimize any artifacts that could be introduced If artifactswere introduced due to uncontrolled bodymovements or eyeblinks or due to technical reasons the recording time wasprolonged for a few more minutes The data was again savedon the hard disk for offline processing These data were usedfor the evaluation of various cognitive functions in terms ofphysiological parameters

Though maximum care was taken the recorded data wascontaminated with many artifacts Manual editing was per-formed for both ECG and EEG signalsThe RR intervals werethen extracted from the Acqknowledge 40 software whichuses modified Pan and Tompkins algorithm The intervalsless than 300ms and above 1200ms were eliminated fromtime series data set and were saved in text format for furtherprocessing using MATLAB 71 Any data whose standarddeviation was less than or equal to three times the standarddeviation was considered outliers and removed from the databefore determining the time domain parameters of heartrate variability (HRV) The artifact free data was segmentedinto five groups with 10 seconds segments each The averagevalue of each 10 seconds data was used in the analysis Theimportant time domainmeasures of HRV such asmeanHRVSDANN RMSSD and mean HR were computed

The frequency domain parameters namely VLF LFHF LF HF ratio and VHF were extracted from the FFTalgorithm The normalized values were computed by divid-ing the respective frequencies by total power minus VLF

4077

0092

6472

2048

0228

3820

0

1

2

3

4

5

6

7

8

Enga

gem

ent i

ndex

val

ue

Before yogaAfter yoga

(120575 + 120579)(120572 + 120573) 120573(120572 + 120579) (120575 + 120579)120572

Figure 3 CNS activity engagement index and executive load indexof yoga group before and after intervention

The normalization reduces the effect of LF and HF on totalpower In conformity with the task force recommendationThe artifact free signal of two minutes duration was used forcomputing frequency domain parameters

Hypotheses of the StudyHypothesis 1 There is no significant difference in physiolog-ical parameters (HR HRV) and cognitive functions of thesubjects of experimental group before and after yoga training(intervention)

Hypothesis 2 There is no significant difference in physio-logical parameters (HR HRV) and cognitive functions ofthe subjects of control group before and after yoga training(intervention)

3 Results and Discussion

Results are grouped in two parts firstly HRV analysis whichincludes time and frequency domain parameters secondlycognitive performance evaluation based on EEG engagementindices Both EEG and ECG signals reflect global arousal oralertness of the brain [34]

31 HRVAnalysis Theheart rate variability (HRV) is an indi-cator of cardiac ANS and HR is controlled by neural activity[35] The yogic exercise particularly pranayama (breathingtechniques) activatesANSThe yoga practicing group showedsignificant increase in HRV (119875 lt 00304) and reduction inresting HR (119875 lt 00389) The significant reduction in restingHR indicates a relaxed state of physiology and increasedmental alertness Depending on left or right cerebral hemi-spherical dominance there will be improvement in spatialor verbal skills The SDNN which reflects the total powersignificantly increased (119875lt00012)TheRMSSD an indicatorof parasympathetic activity also increased significantly (119875 lt00058) The ratio of SDNNRMSSD which is surrogate ofLFHF ratio [36] increased significantly (119875lt00039) LF was

Computational and Mathematical Methods in Medicine 7

Frontal Central Perietal Occipital Temporal Total0

5

10

15

20

25PS

D (120583

V2H

z)

(a) 120573 power

Frontal Central Perietal Occipital Temporal Total0

5

10

15

20

25

PSD

(120583V2H

z)

(b) 120572 power

0

20

40

60

80

100

120

Frontal Central Perietal Occipital Temporal Total

PSD

(120583V2H

z)

(c) 120579 power

0

5

10

15

20

25

Frontal Central Perietal Occipital Temporal Total

PSD

(mV2H

z)

(d) 120575 power

0

2

4

6

8

10

12

14

16

BeforeAfter

Frontal Central Perietal Occipital Temporal Total

PSD

(120583V2H

z)

(e) 120574 power

Figure 4 EEG band powers of control group in various lobes of the brain before and after intervention

significantly decreased (119875 lt 00002) while HF was increased(119875 lt 00003) The decrease of LF and increase of HF reflectsthe improvement in the dominance in the parasympatheticactivity A significant improvement in HRV may be dueto an increase in parasympathetic activity or a decrease insympathetic activity [35] These indirectly help in reducingthe psychological parameters such as distress anxiety anddepression in young healthy subjects

There was significant reduction in LF power (119875 lt 00002)whereas parasympathetic activity significantly increased (119875 lt00003) The LF powers indicate both sympathetic andparasympathetic modulation whereas HF power reflects

parasympathetic activation Hence reduction in sympatheticactivity and enhanced parasympathetic activity results indeceleration in the cardiac activity The ratio LFHF whichis an indicator of autonomic ANS balance between sym-pathetic and parasympathetic nervous system activity [37]was significantly decreased (119875 lt 00000) There is alwaysconstant interaction between sympathetic and parasympa-thetic activity to regulate heart rate variability The VLFincreased without significance in yoga group while there wassignificant increase in control group The VLF representsslow changes in the heart rate [38] but the exact functionof it is yet to be understood A significant reduction in

8 Computational and Mathematical Methods in Medicine

Table 5 Time and frequency domain parameters before and after intervention of yoga and control group

Parameters Yoga group Control groupBefore After 119875 value Before After 119875 value

mHRV (ms) 75721 plusmn 6537 81329 plusmn 7891 00304 87467 plusmn 9155 85572 plusmn 7048 02505mHR (bpm) 7979 plusmn 774 7457 plusmn 705 00389 6950 plusmn 943 7050 plusmn 622 02759SDNN (ms) 4443 plusmn 2176 5214 plusmn 2327 00012 5322 plusmn 2169 5383 plusmn 1951 09044RMSSD (ms) 3993 plusmn 2365 5521 plusmn 2278 00058 5483 plusmn 2946 49 plusmn 2789 01999SDNNRMSSD 077 plusmn 037 111 plusmn 057 00039 077 plusmn 037 121 plusmn 028 01336VLF (nu) 402 plusmn 096 1163 plusmn 983 00177 342 plusmn 991 1404 plusmn 1006 00007LF (nu) 12306 plusmn 2110 5685 plusmn 1016 00002 4514 plusmn 1309 4157 plusmn 1660 00000HF (nu) 2739 plusmn 844 4315 plusmn 1016 00003 4648 plusmn 461 220 plusmn 579 00269LFrelative 7133 plusmn 567 5116 plusmn 951 00000 4642 plusmn 1070 7081 plusmn 713 00000HFrelative 2739 plusmn 844 4315 plusmn 1016 00003 4648 plusmn 461 4220 plusmn 579 00269TP (nu) 17199 plusmn 2241 11163 plusmn 983 00000 9503 plusmn 1129 9781 plusmn 1244 00000LF HF 499 plusmn 198 1411 plusmn 045 00000 099 plusmn 032 355 plusmn 156 00000119875 gt 010 not significant 119875 lt 010marginal 119875 lt 005 fair 119875 lt 001 good 119875 lt 0001 excellent difference 119875 lt 005 is considered significant level and for anyvalue less than this the null hypothesis is rejected 119905stat gt 119905valu for the null hypothesis to be rejected If 119875 = 005 there is 5 chance of no real difference

total power was observed in yoga group This might be dueto significant decrease of sympathetic activity compared tosignificant increase of parasympathetic activity The VHFpower generally reflects part of noise component and doesnot possess clinically significant information

Control group showed significant increase of LF power(119875 lt 00000) decreased HF power (119875 lt 0029) increasedLFHF ratio (119875 lt 00000) and increased VLF power But nosignificant changes were observed in time domain parame-ters

The LF and HF band power of HRV are expressed innormalized units The representation of these frequencyband powers in normalized units articulates the degree ofcontrol exercised and the relative balance of two limbs ofthe autonomic nervous system [35]Moreover normalized LFpower is thought to represent the sympathetic modulation asopposed to absolute units Since theHRV spectral parametersare computed by the autonomic nervous system (ANS) mea-surement of HRV may have greater application in assessingautonomic statues

Studentrsquos paired 119905-test was performed on set of pre- andpostintervention data samples to investigate whether therewas any real difference between them Each 119905 value has acorresponding 119875 value The 119875 value which is the probabilitythat the pattern of data samples in the sample could beproduced by random data provides the information aboutthe likelihood that there is a real difference in the data patternThis significant difference in the data set could be due to theeffect of particular training or an intervention given to thesubjects

The various time and frequency domain parameters ofboth yoga and control group are shown in Table 5 Anyvariations in these parameters could be due to relative age dif-ferences between yoga and control groups or methodologicaldifferences or limited number of samples in the study

The decrease in HR could be due to combined effect ofelements of yoga The reduction in stress after yoga couldbe other possible reason for improved HRV in this study

The previous researches suggest that yoga practice resultsin neurophysiological balance by lowering level of cholin-esterase and catecholamines Further this result increasedparasympathetic and decreased sympathetic activity Theresults of this study are in concurrence with previous studies[6 9 35] These studies indicated reduced sympatheticactivity and enhanced parasympathetic activity after yoga

32 Cognitive Performance Analysis The regular practice ofyoga for a period of fivemonths by young healthy engineeringstudents resulted in the increase of 120572 120573 and 120575 EEG bandpowers and decrease in the 120579 and 120574 band powers Theincreased 120573 band power indicate enhancement in certaincognitive functions such as alertness while increased 120572and decreased 120575 reflect enhanced vigilance level indicatingincreased alertnessThus the increase of high frequency bandpowers (120572 120573) and decrease of low frequency band powers (120575120579) are associated with enhancement in certain cognitive skillssuch as memory and visual information processing

The various cognitive behavior parameters have beenevaluated based on various EEG indices such as 120579120572 120573120572120573120579 (120575 + 120579)120572 120573(120572 + 120579) and (120575 + 120579)(120572 + 120573) Increasein 120573 band power indicates a higher level of alertness andenhanced engagement task and enhancement in variouscognitive abilities The increased band powers of 120572 and 120579indicate decreased alertness reduced engagement task andgood information processing capabilities [25] The 120575 and 120582activity are used for analysis of many cognitive processes[39]The ratio 120573120579which is representative of improvement incognitive skills increasedThe heart rate index 120579120572 decreasedperformance enhancement index 120572120579 increased attentionresource index 120573(120572 + 120579) significantly increased executiveload index (120575 + 120579)120572 decreased and ratio (120575 + 120579)(120572 + 120573)decreased The 120572 120573 and 120575 band power increased in frontalcentral parietal occipital and temporal lobes The 120579 bandpower was increased only in occipital lobe while 120574 bandpower in frontal and slightly in temporal lobes As the frontallobe is associated with reasoning planning problem solving

Computational and Mathematical Methods in Medicine 9

Table 6 Mean powers of EEG frequency bands averaged across all the lobes of the brain before and after yoga intervention

EEG band powers120574 (120583V2Hz) 120573 (120583V2Hz) 120572 (120583V2Hz) 120579 (120583V2Hz) 120575 (120583V2Hz)

Yoga groupBefore yoga 380 plusmn 093 232 plusmn 049 395 plusmn 070 2136 plusmn 343 422 plusmn 042After yoga 365 plusmn 069 491 plusmn 163 567 plusmn 168 1588 plusmn 257 579 plusmn 106

Control groupBefore yoga 298 plusmn 136 386 plusmn 096 392 plusmn 097 1757 plusmn 254 446 plusmn 089After yoga 294 plusmn 133 372 plusmn 082 387 plusmn 090 2112 plusmn 387 437 plusmn 078

and cognition parietal lobe with visual perception recogni-tion information processing and spatial reasoning temporallobe with memory and processing of verbal and auditorysignals and occipital lobe with visual spatial processing andrecognition An increase of EEG frequency band powers inthese lobes indicates the enhancement of certain type ofcognitive skillsThe type of the cognitive skills developed canbe assessed based on increased or decreased EEG band powerin these lobesThemean absolute values of these band powersin various lobes of the brain are shown in Table 6

The increase of frontal 120579 band power indicates intellectualconcentration andmeditative state of relief from nervousnessand is negatively related with sympathetic activation Thisreflects a near relationship between autonomic functionactivity of medial frontal neural circuitry and probability ofcontrolling central nervous system (CNS) functions owing toyoga practice and meditation [12] 120572 waves are indicative ofincreased relaxed state ofmind and its bandpower is inverselyrelated to mental activity Yoga enhanced various cognitiveskills improved sense of wellbeing and responsiveness andenhanced cognitive functions as substantiated by increased120572 and 120573 band powers and various engagement indices Italso improves mental consciousness and achieves reductionin stress and strain and thus advocates complete health andwellbeing in an individual [40] Increase in 120573 band powerwould indicate a higher level of alertness and enhancedengagement task whereas increased band powers of 120572 and 120579would indicate decreased alertness and reduced engagementtask [25] The increase of 120573 power reflects improvement ofcertain cognitive functions such as memory and reactiontime That of 120572 and 120575 indicates synchronization of brainactivity The total EEG band power also increased in yogagroup compared to the control group

The ratio 120579120572 is associated with HR This ratio decreasedin all lobes of the brain indicating the relaxed state of sub-jectsThis reduction could be either increase of 120572 band poweror decrease of 120579 band power Since 120572 power increased in yogagroup this ratio decreased indicating enhancement of certaincognitive faculties (memory attention) and improvement inthe HRV These in turn indicate indirect improvement incertain cognitive functions such as reaction time The ratio120573120572 [25] is called arousal indexThis indicates level of arousalbased on interbeat intervals (IBI) activity Arousal level gt0indicates higher than normal arousal and lt0 indicates lowerthan normal arousal

This ratio increased (4711) in yoga group whiledecreased in control group (243) The increases of thisratio indicate enhanced cognitive functions such as attentionThe decreases of this ratio reflect reduction in the corecapabilities of cognitive functions This ratio increased in alllobes of the brain but the maximum increase was observedin parietal (7805) central (5312) and temporal (4504)lobes It increased to (3824) and (1976) in frontal andoccipital lobes respectively The ratio (120575 + 120579)120572 is calledexecutive load index [28] and is a measure of executive loador comprehension Positive value indicates increased loadand negative value indicates decreased load It reflects theoscillations in precise cortical network active among spatiallydisjoint brain compartment This ratio decreased (4098)in experimental group while it increased (1719) slightlyin control group The decrease in this ratio may be dueto increase in 120572 band power or reduced band power ofeither 120575 or 120579 or both It is observed that 120572 band power wasincreased in yoga practicing group This ratio was also founddecreased in all the lobes of the brain Another importantparameter 120579(fro)120572(par) [27] is called task load index Thisratio decreases in experimental group while it increases incontrol group It is evident from the relation that the ratiodecreases due to increase in 120572 band power These results areshown in Tables 7 and 8

The ratio 120579120573 indicates central nervous system (CNS)arousal [30] and increased ratio is marker of under arousalThis ratio decreased in yoga group The reductions in thisratio reflect the shift of 120572 and 120579 activity towards 120573 activityThe increased 120573 band powers indicate enhanced cognitiveperformance such as memory attention and concentrationThe ratio 120572120575 which is called ldquobrain perfusionrdquo index [29]was increased (46) in yoga practiced group This indicatessufficient amount of blood flow to the different parts ofthe brain among yoga group These in turn enhances thebetter functioning of the brain The ratio LFHF can beexpressed in terms of (120579 + 120575)(120572 + 120573) [29] Slower brainoscillations (120579 and 120575) harmonize considerable neuron groupsacross larger brain areas and faster oscillations (120572 and 120573)synchronize smaller focused neuronal assemblies [41]Whengroups of neurons oscillate together synchronously theymore effectively communicated with each other The index(120579 + 120575)(120572 + 120573) indicates sympathovagal balance of theautonomic nervous system (ANS) Lower ratios indicatebetter balance of ANSThis ratio decreased in yoga group but

10 Computational and Mathematical Methods in Medicine

Table 7 Cognitive index parameters of yoga group before and after yoga intervention Postintervention values are shown within theparenthesis

EEG indices Yoga groupFrontal Central Parietal Occipital Temporal

120579120572 4621 (2806) 4951 (2063) 5059 (2973) 8792 (4609) 4604 (2480)120572120579 0216 (0356) 0202 (0485) 0198 (0336) 0114 (0217) 0217 (0403)120573120572 0612 (0846) 0625 (0957) 0523 (0931) 0607 (0727) 0564 (0818)120573120579 0132 (0302) 0126 (0464) 0103 (0313) 0069 (0158) 0123 (0330)120573(120572 + 120579) 0109 (0222) 0105 (0312) 0086 (0234) 0062 (0130) 0101 (0235)120579(fro)120572(par) 4621 (2806) 4951 (2063) 5059 (2973) 8792 (4609) 4604 (2480)(120575 + 120579)120572 5590 (3926) 5964 (3200) 6168 (3961) 10112 (5907) 5614 (3243)sum(120575 + 120579)120572 = 46392 (27876)

Table 8 Global EEG band power ratios before and after yoga inter-vention

EEG indices Yoga group Control groupBefore yoga After yoga Before yoga After yoga

120579120572 5405 2800 4485 5460120572120579 0185 0357 0228 0183120573120572 0588 0865 0986 0962120573120579 0109 0309 0220 0176120573(120572 + 120579) 0092 0228 0180 0149120579(fro)120572(par) 5405 2800 4485 5460(120575 + 120579)120572 6472 3820 5623 6590sum(120575 + 120579)120572 46392 27876 40456 47080

Table 9 EEG indices and their values before and after yoga inter-vention

Parameters Yoga group ControlBefore After Before After

120572120575 0937 0980 0879 0885(120579 + 120575)(120572 + 120573) 408 205 332 289120572120573 170 116 10139 10394120575120579 0197 0364 0209 2488120579120573 9198 3235 5530 4721

did not change in control group The ratio 120572120573 [31] which iscalled desynchronization is used to analyze vigilance indexand 120575120579 is called synchronization The ratio 120572120573 decreasedwhich is desirable The increase 120573 of band power indicatesimproved cognitive performance Since the parameter is indenominator the ratio decreases when there is increasedcognitive performance However in control group this ratiowas slightly increased Another ratio 120575120579 was increasedrelatively by small amount in experimental group than thecontrol groupThe 120572120575 ratio was decreased in frontal centraland occipital lobes while it increased in parietal and temporallobes These results are shown in Tables 9 10 and 11

The relative EEG band powers of 120573 120572 and 120575 increasedin yoga group in all the lobes of the brain The increases ofthese band powers indicate improvement of certain cognitivefunctions such as memory attention executive functionsand concentration The increase of 120575 power and decrease of

1932 1958

8783

222914911860 1618

10558

21181189

0

20

40

60

80

100

120

PSD

(120583V2H

z)

BeforeAfter

120573 120572 120579 120575 120574

Figure 5 Global EEG band powers of control group before andafter intervention

120579 power indicate improvement in neural activityThe variousEEG band powers are shown in Figure 1

The total band power (global) of 120573 120572 and 120575 increasedamong yoga group The increased 120573 power was associatedwith enhanced cognitive performance such as improvedalertness The maximum 120573 power increased in frontal andcentral lobes of the brain This indicates the improvementin emotion process and cognition The increased 120572 anddecreased 120579 powers physiologically signify the enhancedvigilance and increased alertness level of subjects These areshown in Figure 2 The improvement in cognitive functionswas associated with increased power in high frequency band(120573) and reduction in low frequency band (120579) Therefore 120573120579ratio is suitable index to assess the improvement in cognitiveskills of the subjectsThe cognitive performance index 120573(120572 +120579) increased and ratio of sum of low frequency to sum of highfrequency (120579 + 120575)(120573 + 120572) was decreased among yoga groupwhich is shown in Figure 3

There were no significant changes in EEG band powersengagement indices total power and cognitive performancesindices among control group The various performancesparameters of control group are shown in Figures 4 5 6 and7

Computational and Mathematical Methods in Medicine 11

Table 10 EEG index values of yoga group in different lobes of the brain before and after yoga intervention Postintervention values are shownin parenthesis

Parameters Brain lobesFrontal Central Parietal Occipital Temporal

120572120575 1032 (0893) 0988 (0879) 0902 (1011) 0757 (0770) 0990 (1312)(120579 + 120575)(120572 + 120573) 3468 (0534) 3669 (0566) 4050 (0402) 6294 (0363) 3589 (0363)120572120573 1634 (2806) 1599 (2063) 1913 (2973) 1648 (4609) 1772 (2480)120575120579 0210 (0814) 0205 (0524) 0219 (0614) 0150 (0570) 0219 (0657)120579120573 7550 (3316) 7916 (2156) 9675 (3194) 14492 (6341) 8159 (3032)

Table 11 EEG index values of control group in different lobes of the brain before and after yoga intervention Postintervention values areshown in parenthesis

Parameters Brain lobesFrontal Central Parietal Occipital Temporal

120572120575 0914 (0944) 0940 (0940) 0760 (0760) 0825 (0825) 0930 (0931)(120579 + 120575)(120572 + 120573) 0424 (0356) 0326 (0261) 0271 (0241) 0262 (0218) 0486 (0438)120572120573 3428 (4186) 3711 (4891) 6412 (7311) 5513 (6817) 4385 (4970)120575120579 0716 (0741) 0445 (0445) 0524 (0523) 0409 (0409) 1433 (1433)120579120573 3269 (4185) 3958 (5251) 5747 (6647) 6633 (8531) 4235 (4839)

After yogaBefore yoga

736686

586694

576

737 776

585

752

571

0

1

2

3

4

5

6

7

8

9

Frontal Central Perietal Occipital Temporal

PSD

(120583V2H

z)

Figure 6 Global EEGband powers of control group in various lobesof the brain before and after intervention

4 Conclusions

The regular practices of yoga for a period of five months byyoung healthy engineering students enhance different typesof cognitive skills Apart from cognitive the yoga practiceresulted in many health benefits such as improvement inheart rate variability The ratio SDNNRMSSD increasedwhile the ratio LFHF decreasedThis indicates improvementin the parasympathetic activity and decrease in sympatheticactivity Hence the current results suggest that the practice ofyoga modifies the sympathovagal balance towards parasym-pathetic activation improved the heart rate variability andenhanced sense of wellbeing Since the study population isyoung healthy engineering graduates it would be interestingto investigate whether the yoga practice could result inimprovement in the academic performances

3319

0153

6593

2891

0174

5672

0

1

2

3

4

5

6

7

8

Enga

gem

ent i

ndex

val

ue

Before yogaAfter yoga

(120575 + 120579)(120572 + 120573) 120573(120572 + 120579) (120575 + 120579)120572

Figure 7 CNS activity engagement index and executive load indexof control group before and after intervention

In a nutshell it is proved beyond doubt that yogapractices resulted in effective improvements in physiologicalparameters indirectly improving psychological parametersand various cognitive functions The results of this studygreatly encourage further investigation to study whether thepractice of yoga could also enhance academic performance

Limitations of the Study

Limitations of this study include small number of samplesand lack of dedicated control group and methodologicaldifferences Further investigation can be done by employingpsychological tests to evaluate cognitive behavior

12 Computational and Mathematical Methods in Medicine

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

The authors acknowledge the Principal of PDA College ofEngineering Kalaburagi for deputingHNagendra to pursuePhD degree and Department of Electrical EngineeringIIT Roorkee for providing an opportunity under QualityImprovement Programme (QIP) They also acknowledge thestudents who participated in this study and give specialthanks to the yoga instructor

References

[1] P Sengupta ldquoHealth impacts of yoga and pranayama a state-of-the-art reviewrdquo International Journal of Preventive Medicinevol 3 no 7 pp 444ndash458 2012

[2] A Ross and S Thomas ldquoThe health benefits of yoga and exer-cise a review of comparison studiesrdquoThe Journal of Alternativeand Complementary Medicine vol 16 no 1 pp 3ndash12 2010

[3] P A Balaji S R Varne and S S Ali ldquoPhysiological effects ofyogic practices and transcendental meditation in health anddiseaserdquo North American Journal of Medical Sciences vol 4 no10 pp 442ndash448 2012

[4] A Bussing A Michalsen S B S Khalsa S Telles and K JSherman ldquoEffects of yoga on mental and physical health ashort summary of reviewsrdquo Evidence-based Complementary andAlternative Medicine vol 2012 Article ID 165410 7 pages 2012

[5] T N Sathyaprabha P Satishchandra C Pradhan et al ldquoModu-lation of cardiac autonomic balance with adjuvant yoga therapyin patients with refractory epilepsyrdquo Epilepsy and Behavior vol12 no 2 pp 245ndash252 2008

[6] S Telles N Singh and A Balkrishna ldquoHeart rate variabil-ity changes during high frequency yoga breathingand breathawarenessrdquo BioPsychoSocial Medicine vol 5 article 4 2011

[7] L Jatiya KUdupa andA B Bhavanani ldquoEffect of yoga trainingon handgrip respiratory pressures and pulmonary functionrdquoIndian Journal of Physiology and Pharmacology vol 47 no 4pp 387ndash392 2003

[8] D Nangia and R Malhotra ldquoYoga cognition and mentalhealthrdquo Journal of the IndianAcademy ofApplied Psychology vol38 no 2 pp 262ndash269 2012

[9] S Telles and P Sarang ldquoEffects of two yoga based relaxationtechniques on Heart Rate Variability (HRV)rdquo InternationalJournal of Stress Management vol 13 no 4 pp 460ndash475 2006

[10] S Telles R Nagarathna P R Vani and H R Nagendra ldquoAcombination of focusing and defocusing through yoga reducesoptical illusion more than focusing alonerdquo Indian Journal ofPhysiology and Pharmacology vol 41 no 2 pp 179ndash182 1997

[11] K K F Rocha A M Ribeiro K C F Rocha et al ldquoImprove-ment in physiological and psychological parameters after6months of yoga practicerdquo Consciousness and Cognition vol 21no 2 pp 843ndash850 2012

[12] R Khadka B H Paudel V P Sharma S Kumar and N Bhat-tacharya ldquoEffect of yoga on cardiovascular autonomic reactivityin essential hypertensive patientsrdquo Health Renaissance vol 8no 2 pp 102ndash109 2010

[13] L C M Vanderlei C M Pastre R A Hoshi T D de Carvalhoand M F de Godoy ldquoBasic notions of heart rate variabilityand its clinical applicabilityrdquo Brazilian Journal of CardiovascularSurgery vol 24 no 2 pp 205ndash217 2009

[14] M V Hoslashjgaard N-H Holstein-Rathlou E Agner and JK Kanters ldquoDynamics of spectral components of heart ratevariability during changes in autonomic balancerdquoTheAmericanJournal of PhysiologymdashHeart and Circulatory Physiology vol275 no 1 pp H213ndashH219 1998

[15] S Boonnithi and S Phongsuphap ldquoComparison of heart ratevariability measures for mental stress detectionrdquo in Proceedingsof the Computing in Cardiology (CinC rsquo11) pp 85ndash88 2011

[16] H Kobayashi K Ishibashi and H Noguchi ldquoHeart ratevariability an index for monitoring and analyzing humanautonomic activitiesrdquo Journal of Physiological Anthropology andApplied Human Science vol 18 no 2 pp 53ndash59 1999

[17] J Sztajzel ldquoHeart rate variability a noninvasive electrocardio-graphic method to measure the autonomic nervous systemrdquoSwiss Medical Weekly vol 134 no 35-36 pp 514ndash522 2004

[18] J Taelman S Vandeput A Spaepen and S van Huffel ldquoInflu-ence of mental stress on heart rate and heart rate variabilityrdquo inProceedings of the 4th European Conference of the InternationalFederation for Medical and Biological Engineering (IFMBE rsquo08)vol 22 pp 1366ndash1369 November 2008

[19] E Tharion S Parthasarathy and N Neelakantan ldquoShort-termheart rate variability measures in students during examina-tionsrdquo National Medical Journal of India vol 22 no 2 pp 63ndash66 2009

[20] Y Sun N Ye and X Xu ldquoEEG analysis of alcoholics andcontrols based on feature extractionrdquo in Proceedings of the 8thInternational Conference on Signal Processing (ICSP rsquo06) 2006

[21] C Y Chen W K Wong C D Kuo Y T Liao and MD Ke ldquoWavelet real time monitoring system a case studyof the musical influence on electroencephalographyrdquo WSEASTransactions on Systems vol 7 no 2 pp 56ndash62 2008

[22] C Parameswariah and M Cox ldquoFrequency characteristics ofwaveletsrdquo IEEE Power Engineering Review vol 22 no 1 p 722002

[23] A Holm K Lukander J Korpela M Sallinen and K M IMuller ldquoEstimating brain load from the EEGrdquo The ScientificWorld Journal vol 9 pp 639ndash651 2009

[24] J Gruzelier ldquoA theory of alphatheta neurofeedback creativeperformance enhancement long distance functional connectiv-ity and psychological integrationrdquo Cognitive Processing vol 10no 1 supplement pp 101ndash109 2009

[25] F G Freeman P J Mikulka L J Prinzel and M W ScerboldquoEvaluation of an adaptive automation system using three EEGindices with a visual tracking taskrdquo Biological Psychology vol50 no 1 pp 61ndash76 1999

[26] A F Rabbi K Ivanca A V Putnam A Musa C B Thadenand R Fazel-Rezai ldquoHuman performance evaluation based onEEG signal analysis a prospective reviewrdquo in Proceedings of the31st Annual International Conference of the IEEE Engineeringin Medicine and Biology Society (EMBC rsquo09) pp 1879ndash1882September 2009

[27] A Gevins M E Smith LMcEvoy andD Yu ldquoHigh-resolutionEEGmapping of cortical activation related to workingmemoryeffects of task difficulty type of processing and practicerdquoCerebral Cortex vol 7 no 4 pp 374ndash385 1997

[28] J T Coyne C Baldwin A Cole C Sibley and D M RobertsldquoApplying real time physiological measures of cognitive load

Computational and Mathematical Methods in Medicine 13

to improve trainingrdquo in Foundations of Augmented CognitionNeuroergonomics and Operational Neuroscience vol 5638 ofLecture Notes in Computer Science pp 469ndash478 SpringerBerlin Germany 2009

[29] G Bashein M L Nessly S W Bledsoe et al ldquoElectroen-cephalography during surgery with cardiopulmonary bypassand hypothermiardquo Anesthesiology vol 76 no 6 pp 878ndash8911992

[30] R J Barry A R Clarke S J Johnstone R McCarthy andM Selikowitz ldquoElectroencephalogram 120572120573 ratio and arousal inattention-deficithyperactivity disorder evidence of indepen-dent processesrdquoBiological Psychiatry vol 66 no 4 pp 398ndash4012009

[31] L Cao J Li Y Sun H Zhu and C Yan ldquoEEG-based vig-ilance analysis by using fisher score and PCA algorithmrdquo inProceedings of the 1st IEEE International Conference on Progressin Informatics and Computing (PIC rsquo10) pp 175ndash179 ShanghaiChina December 2010

[32] L I Aftanas and S A Golocheikine ldquoNon-linear dynamiccomplexity of the humanEEGduringmeditationrdquoNeuroscienceLetters vol 330 no 2 pp 143ndash146 2002

[33] M Balasubramaniam S Telles and P M Doraiswamy ldquoYogaon our minds a systematic review of yoga for neuropsychiatricdisordersrdquo Frontiers in Psychiatry vol 3 Article ID Article 117pp 1ndash16 2013

[34] B S Moon H C Lee Y H Lee J C Park I S Oh and JW Lee ldquoFuzzy systems to process ECG and EEG signals forquantification of the mental workloadrdquo Information Sciencesvol 142 no 1ndash4 pp 23ndash35 2002

[35] P Raghuraj A G Ramakrishnan H R Nagendra and S TellesldquoEffect of two selected yogic breathing techniques on heart ratevariabilityrdquo Indian Journal of Physiology and Pharmacology vol42 no 4 pp 467ndash472 1998

[36] J J Sollers III T W Buchanan S M Mowrer L K Hill and JFThayer ldquoComparison of the ratio of the standard deviation ofthe r-r interval and the rootmean squared successive differences(SDrMSSD) to the low frequency-to-high frequency (LFHF)ratio in a patient population and normal healthy controlsrdquoBiomedical Sciences Instrumentation vol 43 pp 158ndash163 2007

[37] C Zhao C Zheng M Zhao and J Liu ldquoPhysiological assess-ment of driving mental fatigue using wavelet packet energy andrandom forestsrdquo The American Journal of Biomedical Sciencesvol 2 no 3 pp 262ndash274 2010

[38] O V Grishin V G Grishin D Yu Uryumtsev S V Smirnovand I G Jilina ldquoMetabolic rate variability impact on verylow-frequency of heart rate variabilityrdquo World Applied SciencesJournal vol 19 no 8 pp 1133ndash1139 2012

[39] E Basar C Basar-Eroglu S Karakas and M SchurmannldquoGamma alpha delta and theta oscillations govern cognitiveprocessesrdquo International Journal of Psychophysiology vol 39 no2-3 pp 241ndash248 2000

[40] K C Khare and S K Nigam ldquoA study of electroencephalogramin meditatorsrdquo Indian Journal of Physiology and Pharmacologyvol 44 no 2 pp 173ndash178 2000

[41] J Jacobs and M J Kahana ldquoDirect brain recordings fueladvances in cognitive electrophysiologyrdquo Trends in CognitiveSciences vol 14 no 4 pp 162ndash171 2010

Submit your manuscripts athttpwwwhindawicom

Stem CellsInternational

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

MEDIATORSINFLAMMATION

of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Behavioural Neurology

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Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Disease Markers

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

BioMed Research International

OncologyJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Oxidative Medicine and Cellular Longevity

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

PPAR Research

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Immunology ResearchHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal of

ObesityJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Computational and Mathematical Methods in Medicine

OphthalmologyJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Diabetes ResearchJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Research and TreatmentAIDS

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Gastroenterology Research and Practice

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Parkinsonrsquos Disease

Evidence-Based Complementary and Alternative Medicine

Volume 2014Hindawi Publishing Corporationhttpwwwhindawicom

Computational and Mathematical Methods in Medicine 3

05

10152025303540

Frontal Central Perietal Occipital Temporal Total

PSD

(120583V2H

z)

(a) 120573 power

Frontal Central Perietal Occipital Temporal Total0

5

10

15

20

25

30

PSD

(120583V2H

z)

(b) 120572 power

Frontal Central Perietal Occipital Temporal Total0

20

40

60

80

100

120

PSD

(120583V2H

z)

(c) 120579 power

Frontal Central Perietal Occipital Temporal Total0

5

10

15

20

25

30

35

PSD

(120583V2H

z)

(d) 120575 power

Frontal Central Perietal Occipital Temporal Total

BeforeAfter

02468

101214161820

PSD

(120583V2H

z)

(e) 120574 power

Figure 1 EEG band powers of yoga group in various lobes of the brain before and after intervention

Low frequency (LF 004ndash015Hz) power this band iscomplex in nature and an index of both sympatheticand parasympathetic activity and influences HRVpatterns

High frequency (HF 015ndash04Hz) power it is theindex of parasympathetic activity and is used toindicate slow changes in the HR

Very high frequency (VHF gt04Hz) this frequencyis generally considered as noise and has no clinicalsignificance

LFHF ratio It reflects the overall balance of the ANSThe lower ratio is recommended by the task force

In normal in resting condition this ratio lies in therange of 1 and 2

Total power (TP) variance of all NN intervals in thefrequency range less than 04Hz

The VLF LF HF and TP are expressed in ms2 unitswhen computed in absolute values The important frequencydomain parameters used for the computation are shown inTable 2

The spectral parameters of HRV are usually normalizedto minimize the effect of redundancy inherent in them inmost of the research work The important frequency domainparameters are shown in Figure 2

4 Computational and Mathematical Methods in Medicine

Table 2 The equations used to compute frequency domain mea-sures

Index Equations Unit

LFnuLF(LF +HF)

lowast 100

HFnuHF(LF +HF)

lowast 100

SVI LFHF

mdash

LFRelpowerLFTPlowast 100 mdash

HFRelpowerHFTPlowast 100 mdash

dLFHF 1003816100381610038161003816LFnu minusHFnu

1003816100381610038161003816

where TP = VLF + LF + HF

11611976

10682

2109 19022455 2837

7942

28941824

0

20

40

60

80

100

120

BeforeAfter

minus20120573 120572 120579 120575 120574

PSD

(120583V2H

z)

Figure 2 Global EEG band powers of yoga group before and afterintervention

12 EEG Band Frequencies and Cognitive Processes Thebrainactivity which changes continuously with time is called ldquoelec-troencephalogramrdquo (EEG) which can be used to investigatethe cognitive abilities and memory executions of individualsin terms of its band of frequencies

The EEG is highly complex and is combination of fivedifferent frequency waveforms namely 120575 (delta) 120579 (theta) 120573(beta)120572 (alpha) and 120574 (gamma)waves respectively [20]Theamplitude of the brain waves is approximately in the rangeof 10 120583V to 250120583V and the frequency varies between 05Hzand 100HzThe frequency range and their characteristics areshown in Table 3

The EEG waveforms may be global or localized to thespecific areas on the scalp This kind of electrical data isimportant to study the correlation between yoga asanas andphysiological states because any shift in the EEG frequencyrange reflects the physiological arousalThe various EEG ratioindices and their physiological and cognitive interpretationsare shown in Table 4

13 Extraction of EEG Band Frequencies Using DiscreteWavelet Transforms (DWT) Discrete wavelet transforms(DWT) are widely used for the analysis of physiological

signals as compared to the classical techniques such as fastFourier transforms (FFT) When FFT is applied on thetime series signal the signal information is available in theform of spectral parameters That is the whole time domaininformation will be lost It is equivalent to windowed Fouriertransform and can be used to measure both the time andfrequency changes of a signal [21]

The DWT splits the input signal into approximation(trend) and detailed coefficients (fluctuation) respectivelyThe approximation coefficient can further be split into anew approximation and detailed coefficients This process iscontinued progressively to get a new set of approximation anddetailed coefficients of a signal at various levels of decomposi-tion [22] The selection of analyzing wavelet is called motherwavelet and number of decomposition levels to be carried outis the critical pointThemother wavelet determines the shapeof the signal to be decomposed In this paper the waveletfunction db4 is used to extract five frequency bands (120575 120579120572 120573 and 120574) of EEG signal The application of higher orderwavelet function such as db20 produces large number ofcoefficients Larger number of coefficients average out thedetail components of the signal and fail to detect fast movingsignals such as EEG To retrieve the information at a specificinstant of time the wavelets with less number of coefficientsare better choice The lower order wavelet function db4has good time and frequency localization properties andin addition this wavelet has similar morphology as thatof EEG signal to be detected Therefore db4 wavelets arebetter choice for precisely detecting fast moving transientsand short duration information signals Thus by the processof decomposition DWT can detect the important hiddenfeatures from the original signal

In this study the EEG signal was acquired with samplingfrequency of 500Hz The useful information of this signallies in the range of 05ndash70Hz Hence a level of 7 usingdb4 was applied to decompose the EEG signal into itsapproximate (A1ndashA7) and detail (D1ndashD7) coefficients Afterthe seventh level of decomposition the band of frequenciesobtained are D1 (250ndash500Hz) A1 (0ndash250Hz) D2 (125ndash250Hz) A2 (0ndash125Hz) D3 (625ndash125Hz) A3 (0ndash625Hz)D4 (3125ndash625Hz) A4 (0ndash3125Hz) D5 (15625ndash3125Hz)A5 (0ndash15625Hz) D6 (78125ndash15625Hz) A6 (0ndash78125Hz)D7 (3906ndash7813Hz) and A7 (0ndash3906Hz) respectively Thedecomposition levels from D1 to D3 were considered asnoise components and hence excluded from the analysisThe finer detailed coefficients from levels D4ndashD7 and finalapproximate coefficients from level A7 are retained as theyapproximately represent the EEG physiological frequencysubbands of 120574120573120572 120579 and120575 respectivelyThese five frequencybands are analyzed to investigate different cognitive effectsdue to yoga among healthy subjects Different EEG ratiosused in this study to investigate cognitive performances interms of physiological parameters are shown in Figure 4which are derived from various sources

2 Methodology and Experimental Procedure

21 Subjects The total number of subjects who participatedin the experiment was 30 young healthy graduate and

Computational and Mathematical Methods in Medicine 5

Table 3 Five EEG frequency bands

Parameters Frequency range (Hz) Magnitude (120583V) Activity Remark120573 13ndash30 lt30 120583V Desynchronized Mental occupation120572 8ndash13 50ndash100 120583V Synchronized Relaxed tranquility and wakefulness120579 4ndash8 20ndash40 120583V Desynchronized Dreaming state120575 05ndash4 75ndash150 120583V Desynchronized State of dreamless sleep120574 30ndash70 mdash Synchronized Sensory integration

Table 4 EEG band ratios and their physiologicalcognitive activityindex interpretation

EEG band ratios Activitycorrelation Sources120579120572 Heart rate (HR) [23]

120572120579 Performance enhancementindex or ldquowellbeingrdquo [24]

120573120572 Arousal index [25]120573120579 Neural activity [25]

120573(120572 + 120579) Cognitive performance andattentional resource index [26]

120579(frontal)120572(parietal) Task load index [27](120575 + 120579)120572 Executive load index [28]120572120575 Brain perfusion [29]120579120573 CNS arousal [30](120579 + 120575)(120572 + 120573) Sum of LF to HF ratio [29]120572120573 Desynchronization [31]120575120579 Synchronization(120579 + 120572)120573 Vigilance index [31]

postgraduate engineering students of IIT Roorkee (male =27 female = 3) All the subjects were right handed withnormal eye sight The study population was divided intotwo groups experimental group and control group In thisstudy the sample size is relatively small and both groupshave the same size The study population was randomlyassigned to either of the groups by block randomizationmethod to achieve the balance The block size of two wasused Both participants and investigators were unaware of thegroups to be assigned in advance Each group consisted of15 subjects with two females in experimental group and onein control group The mean and standard deviation of eachgroup were 2242 plusmn 230 and 2367 plusmn 209 respectively Thesame subjects were chosen for both experimental and controlgroups to diminish misperceiving influences and make thestudy more effective Subjects with previous yoga practicehistory of alcohol consumption smoking and any other drugconsumption were excluded from this studyThe participantswere informed a priori about the study and their consent wasobtained Subjects participated voluntarily and cooperatedthroughout the training period The subjects were asked tonot to deviate their regular life style during this study All thesubjects of experimental group obtained same yoga trainingfor a period of fivemonths for 15 hours per day between 6 pmand 730 pm

In this study the physiological parameters such as ECGand their ratio indices have been evaluated to assess thecognitive benefits of the yoga practice along with its wellestablished health benefits This may provide the windowfor further investigation to correlate the actual measures ofcognitive functions and their physiological parameters

The practice of yoga schedule consisted of prayerpranayama (breathing techniques) and simple yogic pos-tures Explanations on stress management importance ofmeditation and yoga in everyday life were also briefed

The subjects practiced yoga under observation of trainedyoga instructor During practice session various types ofasanas (postural exercises) pranayama (breathing tech-niques) and dhyana (meditation) were performed Theseasanas increase the strength concentration will power andmindfulness by manipulating the natural energy of the body[1 32 33]

(1) Standing asanas (postures) they consisted of suryanamaskar dandasana urdhave asana trikonasanaardha asana hasta padasana mahavir asana andvatayanasana

(2) Sitting asanas (postures) they include mandookasana and oorm asana ushtra asan ardha matsy-endrasana vakrasana supt asana matsyendrasanauttan mandukasana vakasana mayoor asan padmvak asan padma mayurasana pashchimottanasaneka padangusthasana vipreet pad asan and purnachakrasana

(3) Asana (posture) lying on back this includes uttanpad asana pawanmuktasana market asan shree-shan sarvangasana halasana setu bandhasana andchakrasana

(4) Asana (posture) lying on stomach this includes nau-kasana yan asan shalabh asan and dhanurasana

(5) Pranayama (breathing) and kriya include Anulom-vilom kapalbhati Ujjayi pranayama Bhramari pra-nayama sheetali pranayama sheetkari pranayamasurya bheda pranayama bhastrika pranayama bahyapranayama udgeeth pranayama kaki mudra andshanmukhi mudra Everyday practice session wasconcluded with prayer and meditation

22 Recording ECG and EEG Signals and Analysis BothECG and EEG signals were recorded simultaneously usingBIOPACMP150 System (EEG100C = 10 nos and ECG100C =3 nos) with Acqknowledge 40 software

6 Computational and Mathematical Methods in Medicine

ECG signal was recorded using five electrodes by con-necting to left and right wrinkles and left and right armsand one electrode at chest Before fixing the electrodes theywere cleaned and electrode gel was applied to reduce theskin resistance to get good quality of recording signal EEGsignal was recorded by fixing the CAP100C on the scalp ofthe subjects This cap was made of Lycra type fabric with20 reusable tin electrodes attached to it according to theinternational 10ndash20 norms Before fixing the cap on subjectsscalp the electrodes were cleaned with saline water andelectrode gel was appliedThismaintains the resistance below5 kΩ between the scalp and electrodes

All the data were collected during 6 pm to 730 pm atthe yoga centre of the temple premises in two stages Thedata collected at the beginning of the intervention period wasconsidered as the first stage during which five minutes ofbaseline ECG and EEG signals were recorded from subjectsof both experimental and control groups in sitting positionwith eyes closed The baseline signal was saved on the harddisk for offline processing

Both ECG and EEG signals were recorded with a sam-pling frequency of 512Hz to have better resolution of R-Rtime interval series and EEG activity

The experimental group practiced yoga for a period of fivemonths for 15 hr per day in the evening from 6 pm to 730pmThe control group was asked not to practice any form ofyogic practices or physical exercises during this period Theend of five months yoga training period was considered assecond stage During this stage again both ECG and EEGdata were collected from experimental and control groupfor a period of 10 minutes During recording subjects wereasked to minimize eye blinks and avoid body movements tominimize any artifacts that could be introduced If artifactswere introduced due to uncontrolled bodymovements or eyeblinks or due to technical reasons the recording time wasprolonged for a few more minutes The data was again savedon the hard disk for offline processing These data were usedfor the evaluation of various cognitive functions in terms ofphysiological parameters

Though maximum care was taken the recorded data wascontaminated with many artifacts Manual editing was per-formed for both ECG and EEG signalsThe RR intervals werethen extracted from the Acqknowledge 40 software whichuses modified Pan and Tompkins algorithm The intervalsless than 300ms and above 1200ms were eliminated fromtime series data set and were saved in text format for furtherprocessing using MATLAB 71 Any data whose standarddeviation was less than or equal to three times the standarddeviation was considered outliers and removed from the databefore determining the time domain parameters of heartrate variability (HRV) The artifact free data was segmentedinto five groups with 10 seconds segments each The averagevalue of each 10 seconds data was used in the analysis Theimportant time domainmeasures of HRV such asmeanHRVSDANN RMSSD and mean HR were computed

The frequency domain parameters namely VLF LFHF LF HF ratio and VHF were extracted from the FFTalgorithm The normalized values were computed by divid-ing the respective frequencies by total power minus VLF

4077

0092

6472

2048

0228

3820

0

1

2

3

4

5

6

7

8

Enga

gem

ent i

ndex

val

ue

Before yogaAfter yoga

(120575 + 120579)(120572 + 120573) 120573(120572 + 120579) (120575 + 120579)120572

Figure 3 CNS activity engagement index and executive load indexof yoga group before and after intervention

The normalization reduces the effect of LF and HF on totalpower In conformity with the task force recommendationThe artifact free signal of two minutes duration was used forcomputing frequency domain parameters

Hypotheses of the StudyHypothesis 1 There is no significant difference in physiolog-ical parameters (HR HRV) and cognitive functions of thesubjects of experimental group before and after yoga training(intervention)

Hypothesis 2 There is no significant difference in physio-logical parameters (HR HRV) and cognitive functions ofthe subjects of control group before and after yoga training(intervention)

3 Results and Discussion

Results are grouped in two parts firstly HRV analysis whichincludes time and frequency domain parameters secondlycognitive performance evaluation based on EEG engagementindices Both EEG and ECG signals reflect global arousal oralertness of the brain [34]

31 HRVAnalysis Theheart rate variability (HRV) is an indi-cator of cardiac ANS and HR is controlled by neural activity[35] The yogic exercise particularly pranayama (breathingtechniques) activatesANSThe yoga practicing group showedsignificant increase in HRV (119875 lt 00304) and reduction inresting HR (119875 lt 00389) The significant reduction in restingHR indicates a relaxed state of physiology and increasedmental alertness Depending on left or right cerebral hemi-spherical dominance there will be improvement in spatialor verbal skills The SDNN which reflects the total powersignificantly increased (119875lt00012)TheRMSSD an indicatorof parasympathetic activity also increased significantly (119875 lt00058) The ratio of SDNNRMSSD which is surrogate ofLFHF ratio [36] increased significantly (119875lt00039) LF was

Computational and Mathematical Methods in Medicine 7

Frontal Central Perietal Occipital Temporal Total0

5

10

15

20

25PS

D (120583

V2H

z)

(a) 120573 power

Frontal Central Perietal Occipital Temporal Total0

5

10

15

20

25

PSD

(120583V2H

z)

(b) 120572 power

0

20

40

60

80

100

120

Frontal Central Perietal Occipital Temporal Total

PSD

(120583V2H

z)

(c) 120579 power

0

5

10

15

20

25

Frontal Central Perietal Occipital Temporal Total

PSD

(mV2H

z)

(d) 120575 power

0

2

4

6

8

10

12

14

16

BeforeAfter

Frontal Central Perietal Occipital Temporal Total

PSD

(120583V2H

z)

(e) 120574 power

Figure 4 EEG band powers of control group in various lobes of the brain before and after intervention

significantly decreased (119875 lt 00002) while HF was increased(119875 lt 00003) The decrease of LF and increase of HF reflectsthe improvement in the dominance in the parasympatheticactivity A significant improvement in HRV may be dueto an increase in parasympathetic activity or a decrease insympathetic activity [35] These indirectly help in reducingthe psychological parameters such as distress anxiety anddepression in young healthy subjects

There was significant reduction in LF power (119875 lt 00002)whereas parasympathetic activity significantly increased (119875 lt00003) The LF powers indicate both sympathetic andparasympathetic modulation whereas HF power reflects

parasympathetic activation Hence reduction in sympatheticactivity and enhanced parasympathetic activity results indeceleration in the cardiac activity The ratio LFHF whichis an indicator of autonomic ANS balance between sym-pathetic and parasympathetic nervous system activity [37]was significantly decreased (119875 lt 00000) There is alwaysconstant interaction between sympathetic and parasympa-thetic activity to regulate heart rate variability The VLFincreased without significance in yoga group while there wassignificant increase in control group The VLF representsslow changes in the heart rate [38] but the exact functionof it is yet to be understood A significant reduction in

8 Computational and Mathematical Methods in Medicine

Table 5 Time and frequency domain parameters before and after intervention of yoga and control group

Parameters Yoga group Control groupBefore After 119875 value Before After 119875 value

mHRV (ms) 75721 plusmn 6537 81329 plusmn 7891 00304 87467 plusmn 9155 85572 plusmn 7048 02505mHR (bpm) 7979 plusmn 774 7457 plusmn 705 00389 6950 plusmn 943 7050 plusmn 622 02759SDNN (ms) 4443 plusmn 2176 5214 plusmn 2327 00012 5322 plusmn 2169 5383 plusmn 1951 09044RMSSD (ms) 3993 plusmn 2365 5521 plusmn 2278 00058 5483 plusmn 2946 49 plusmn 2789 01999SDNNRMSSD 077 plusmn 037 111 plusmn 057 00039 077 plusmn 037 121 plusmn 028 01336VLF (nu) 402 plusmn 096 1163 plusmn 983 00177 342 plusmn 991 1404 plusmn 1006 00007LF (nu) 12306 plusmn 2110 5685 plusmn 1016 00002 4514 plusmn 1309 4157 plusmn 1660 00000HF (nu) 2739 plusmn 844 4315 plusmn 1016 00003 4648 plusmn 461 220 plusmn 579 00269LFrelative 7133 plusmn 567 5116 plusmn 951 00000 4642 plusmn 1070 7081 plusmn 713 00000HFrelative 2739 plusmn 844 4315 plusmn 1016 00003 4648 plusmn 461 4220 plusmn 579 00269TP (nu) 17199 plusmn 2241 11163 plusmn 983 00000 9503 plusmn 1129 9781 plusmn 1244 00000LF HF 499 plusmn 198 1411 plusmn 045 00000 099 plusmn 032 355 plusmn 156 00000119875 gt 010 not significant 119875 lt 010marginal 119875 lt 005 fair 119875 lt 001 good 119875 lt 0001 excellent difference 119875 lt 005 is considered significant level and for anyvalue less than this the null hypothesis is rejected 119905stat gt 119905valu for the null hypothesis to be rejected If 119875 = 005 there is 5 chance of no real difference

total power was observed in yoga group This might be dueto significant decrease of sympathetic activity compared tosignificant increase of parasympathetic activity The VHFpower generally reflects part of noise component and doesnot possess clinically significant information

Control group showed significant increase of LF power(119875 lt 00000) decreased HF power (119875 lt 0029) increasedLFHF ratio (119875 lt 00000) and increased VLF power But nosignificant changes were observed in time domain parame-ters

The LF and HF band power of HRV are expressed innormalized units The representation of these frequencyband powers in normalized units articulates the degree ofcontrol exercised and the relative balance of two limbs ofthe autonomic nervous system [35]Moreover normalized LFpower is thought to represent the sympathetic modulation asopposed to absolute units Since theHRV spectral parametersare computed by the autonomic nervous system (ANS) mea-surement of HRV may have greater application in assessingautonomic statues

Studentrsquos paired 119905-test was performed on set of pre- andpostintervention data samples to investigate whether therewas any real difference between them Each 119905 value has acorresponding 119875 value The 119875 value which is the probabilitythat the pattern of data samples in the sample could beproduced by random data provides the information aboutthe likelihood that there is a real difference in the data patternThis significant difference in the data set could be due to theeffect of particular training or an intervention given to thesubjects

The various time and frequency domain parameters ofboth yoga and control group are shown in Table 5 Anyvariations in these parameters could be due to relative age dif-ferences between yoga and control groups or methodologicaldifferences or limited number of samples in the study

The decrease in HR could be due to combined effect ofelements of yoga The reduction in stress after yoga couldbe other possible reason for improved HRV in this study

The previous researches suggest that yoga practice resultsin neurophysiological balance by lowering level of cholin-esterase and catecholamines Further this result increasedparasympathetic and decreased sympathetic activity Theresults of this study are in concurrence with previous studies[6 9 35] These studies indicated reduced sympatheticactivity and enhanced parasympathetic activity after yoga

32 Cognitive Performance Analysis The regular practice ofyoga for a period of fivemonths by young healthy engineeringstudents resulted in the increase of 120572 120573 and 120575 EEG bandpowers and decrease in the 120579 and 120574 band powers Theincreased 120573 band power indicate enhancement in certaincognitive functions such as alertness while increased 120572and decreased 120575 reflect enhanced vigilance level indicatingincreased alertnessThus the increase of high frequency bandpowers (120572 120573) and decrease of low frequency band powers (120575120579) are associated with enhancement in certain cognitive skillssuch as memory and visual information processing

The various cognitive behavior parameters have beenevaluated based on various EEG indices such as 120579120572 120573120572120573120579 (120575 + 120579)120572 120573(120572 + 120579) and (120575 + 120579)(120572 + 120573) Increasein 120573 band power indicates a higher level of alertness andenhanced engagement task and enhancement in variouscognitive abilities The increased band powers of 120572 and 120579indicate decreased alertness reduced engagement task andgood information processing capabilities [25] The 120575 and 120582activity are used for analysis of many cognitive processes[39]The ratio 120573120579which is representative of improvement incognitive skills increasedThe heart rate index 120579120572 decreasedperformance enhancement index 120572120579 increased attentionresource index 120573(120572 + 120579) significantly increased executiveload index (120575 + 120579)120572 decreased and ratio (120575 + 120579)(120572 + 120573)decreased The 120572 120573 and 120575 band power increased in frontalcentral parietal occipital and temporal lobes The 120579 bandpower was increased only in occipital lobe while 120574 bandpower in frontal and slightly in temporal lobes As the frontallobe is associated with reasoning planning problem solving

Computational and Mathematical Methods in Medicine 9

Table 6 Mean powers of EEG frequency bands averaged across all the lobes of the brain before and after yoga intervention

EEG band powers120574 (120583V2Hz) 120573 (120583V2Hz) 120572 (120583V2Hz) 120579 (120583V2Hz) 120575 (120583V2Hz)

Yoga groupBefore yoga 380 plusmn 093 232 plusmn 049 395 plusmn 070 2136 plusmn 343 422 plusmn 042After yoga 365 plusmn 069 491 plusmn 163 567 plusmn 168 1588 plusmn 257 579 plusmn 106

Control groupBefore yoga 298 plusmn 136 386 plusmn 096 392 plusmn 097 1757 plusmn 254 446 plusmn 089After yoga 294 plusmn 133 372 plusmn 082 387 plusmn 090 2112 plusmn 387 437 plusmn 078

and cognition parietal lobe with visual perception recogni-tion information processing and spatial reasoning temporallobe with memory and processing of verbal and auditorysignals and occipital lobe with visual spatial processing andrecognition An increase of EEG frequency band powers inthese lobes indicates the enhancement of certain type ofcognitive skillsThe type of the cognitive skills developed canbe assessed based on increased or decreased EEG band powerin these lobesThemean absolute values of these band powersin various lobes of the brain are shown in Table 6

The increase of frontal 120579 band power indicates intellectualconcentration andmeditative state of relief from nervousnessand is negatively related with sympathetic activation Thisreflects a near relationship between autonomic functionactivity of medial frontal neural circuitry and probability ofcontrolling central nervous system (CNS) functions owing toyoga practice and meditation [12] 120572 waves are indicative ofincreased relaxed state ofmind and its bandpower is inverselyrelated to mental activity Yoga enhanced various cognitiveskills improved sense of wellbeing and responsiveness andenhanced cognitive functions as substantiated by increased120572 and 120573 band powers and various engagement indices Italso improves mental consciousness and achieves reductionin stress and strain and thus advocates complete health andwellbeing in an individual [40] Increase in 120573 band powerwould indicate a higher level of alertness and enhancedengagement task whereas increased band powers of 120572 and 120579would indicate decreased alertness and reduced engagementtask [25] The increase of 120573 power reflects improvement ofcertain cognitive functions such as memory and reactiontime That of 120572 and 120575 indicates synchronization of brainactivity The total EEG band power also increased in yogagroup compared to the control group

The ratio 120579120572 is associated with HR This ratio decreasedin all lobes of the brain indicating the relaxed state of sub-jectsThis reduction could be either increase of 120572 band poweror decrease of 120579 band power Since 120572 power increased in yogagroup this ratio decreased indicating enhancement of certaincognitive faculties (memory attention) and improvement inthe HRV These in turn indicate indirect improvement incertain cognitive functions such as reaction time The ratio120573120572 [25] is called arousal indexThis indicates level of arousalbased on interbeat intervals (IBI) activity Arousal level gt0indicates higher than normal arousal and lt0 indicates lowerthan normal arousal

This ratio increased (4711) in yoga group whiledecreased in control group (243) The increases of thisratio indicate enhanced cognitive functions such as attentionThe decreases of this ratio reflect reduction in the corecapabilities of cognitive functions This ratio increased in alllobes of the brain but the maximum increase was observedin parietal (7805) central (5312) and temporal (4504)lobes It increased to (3824) and (1976) in frontal andoccipital lobes respectively The ratio (120575 + 120579)120572 is calledexecutive load index [28] and is a measure of executive loador comprehension Positive value indicates increased loadand negative value indicates decreased load It reflects theoscillations in precise cortical network active among spatiallydisjoint brain compartment This ratio decreased (4098)in experimental group while it increased (1719) slightlyin control group The decrease in this ratio may be dueto increase in 120572 band power or reduced band power ofeither 120575 or 120579 or both It is observed that 120572 band power wasincreased in yoga practicing group This ratio was also founddecreased in all the lobes of the brain Another importantparameter 120579(fro)120572(par) [27] is called task load index Thisratio decreases in experimental group while it increases incontrol group It is evident from the relation that the ratiodecreases due to increase in 120572 band power These results areshown in Tables 7 and 8

The ratio 120579120573 indicates central nervous system (CNS)arousal [30] and increased ratio is marker of under arousalThis ratio decreased in yoga group The reductions in thisratio reflect the shift of 120572 and 120579 activity towards 120573 activityThe increased 120573 band powers indicate enhanced cognitiveperformance such as memory attention and concentrationThe ratio 120572120575 which is called ldquobrain perfusionrdquo index [29]was increased (46) in yoga practiced group This indicatessufficient amount of blood flow to the different parts ofthe brain among yoga group These in turn enhances thebetter functioning of the brain The ratio LFHF can beexpressed in terms of (120579 + 120575)(120572 + 120573) [29] Slower brainoscillations (120579 and 120575) harmonize considerable neuron groupsacross larger brain areas and faster oscillations (120572 and 120573)synchronize smaller focused neuronal assemblies [41]Whengroups of neurons oscillate together synchronously theymore effectively communicated with each other The index(120579 + 120575)(120572 + 120573) indicates sympathovagal balance of theautonomic nervous system (ANS) Lower ratios indicatebetter balance of ANSThis ratio decreased in yoga group but

10 Computational and Mathematical Methods in Medicine

Table 7 Cognitive index parameters of yoga group before and after yoga intervention Postintervention values are shown within theparenthesis

EEG indices Yoga groupFrontal Central Parietal Occipital Temporal

120579120572 4621 (2806) 4951 (2063) 5059 (2973) 8792 (4609) 4604 (2480)120572120579 0216 (0356) 0202 (0485) 0198 (0336) 0114 (0217) 0217 (0403)120573120572 0612 (0846) 0625 (0957) 0523 (0931) 0607 (0727) 0564 (0818)120573120579 0132 (0302) 0126 (0464) 0103 (0313) 0069 (0158) 0123 (0330)120573(120572 + 120579) 0109 (0222) 0105 (0312) 0086 (0234) 0062 (0130) 0101 (0235)120579(fro)120572(par) 4621 (2806) 4951 (2063) 5059 (2973) 8792 (4609) 4604 (2480)(120575 + 120579)120572 5590 (3926) 5964 (3200) 6168 (3961) 10112 (5907) 5614 (3243)sum(120575 + 120579)120572 = 46392 (27876)

Table 8 Global EEG band power ratios before and after yoga inter-vention

EEG indices Yoga group Control groupBefore yoga After yoga Before yoga After yoga

120579120572 5405 2800 4485 5460120572120579 0185 0357 0228 0183120573120572 0588 0865 0986 0962120573120579 0109 0309 0220 0176120573(120572 + 120579) 0092 0228 0180 0149120579(fro)120572(par) 5405 2800 4485 5460(120575 + 120579)120572 6472 3820 5623 6590sum(120575 + 120579)120572 46392 27876 40456 47080

Table 9 EEG indices and their values before and after yoga inter-vention

Parameters Yoga group ControlBefore After Before After

120572120575 0937 0980 0879 0885(120579 + 120575)(120572 + 120573) 408 205 332 289120572120573 170 116 10139 10394120575120579 0197 0364 0209 2488120579120573 9198 3235 5530 4721

did not change in control group The ratio 120572120573 [31] which iscalled desynchronization is used to analyze vigilance indexand 120575120579 is called synchronization The ratio 120572120573 decreasedwhich is desirable The increase 120573 of band power indicatesimproved cognitive performance Since the parameter is indenominator the ratio decreases when there is increasedcognitive performance However in control group this ratiowas slightly increased Another ratio 120575120579 was increasedrelatively by small amount in experimental group than thecontrol groupThe 120572120575 ratio was decreased in frontal centraland occipital lobes while it increased in parietal and temporallobes These results are shown in Tables 9 10 and 11

The relative EEG band powers of 120573 120572 and 120575 increasedin yoga group in all the lobes of the brain The increases ofthese band powers indicate improvement of certain cognitivefunctions such as memory attention executive functionsand concentration The increase of 120575 power and decrease of

1932 1958

8783

222914911860 1618

10558

21181189

0

20

40

60

80

100

120

PSD

(120583V2H

z)

BeforeAfter

120573 120572 120579 120575 120574

Figure 5 Global EEG band powers of control group before andafter intervention

120579 power indicate improvement in neural activityThe variousEEG band powers are shown in Figure 1

The total band power (global) of 120573 120572 and 120575 increasedamong yoga group The increased 120573 power was associatedwith enhanced cognitive performance such as improvedalertness The maximum 120573 power increased in frontal andcentral lobes of the brain This indicates the improvementin emotion process and cognition The increased 120572 anddecreased 120579 powers physiologically signify the enhancedvigilance and increased alertness level of subjects These areshown in Figure 2 The improvement in cognitive functionswas associated with increased power in high frequency band(120573) and reduction in low frequency band (120579) Therefore 120573120579ratio is suitable index to assess the improvement in cognitiveskills of the subjectsThe cognitive performance index 120573(120572 +120579) increased and ratio of sum of low frequency to sum of highfrequency (120579 + 120575)(120573 + 120572) was decreased among yoga groupwhich is shown in Figure 3

There were no significant changes in EEG band powersengagement indices total power and cognitive performancesindices among control group The various performancesparameters of control group are shown in Figures 4 5 6 and7

Computational and Mathematical Methods in Medicine 11

Table 10 EEG index values of yoga group in different lobes of the brain before and after yoga intervention Postintervention values are shownin parenthesis

Parameters Brain lobesFrontal Central Parietal Occipital Temporal

120572120575 1032 (0893) 0988 (0879) 0902 (1011) 0757 (0770) 0990 (1312)(120579 + 120575)(120572 + 120573) 3468 (0534) 3669 (0566) 4050 (0402) 6294 (0363) 3589 (0363)120572120573 1634 (2806) 1599 (2063) 1913 (2973) 1648 (4609) 1772 (2480)120575120579 0210 (0814) 0205 (0524) 0219 (0614) 0150 (0570) 0219 (0657)120579120573 7550 (3316) 7916 (2156) 9675 (3194) 14492 (6341) 8159 (3032)

Table 11 EEG index values of control group in different lobes of the brain before and after yoga intervention Postintervention values areshown in parenthesis

Parameters Brain lobesFrontal Central Parietal Occipital Temporal

120572120575 0914 (0944) 0940 (0940) 0760 (0760) 0825 (0825) 0930 (0931)(120579 + 120575)(120572 + 120573) 0424 (0356) 0326 (0261) 0271 (0241) 0262 (0218) 0486 (0438)120572120573 3428 (4186) 3711 (4891) 6412 (7311) 5513 (6817) 4385 (4970)120575120579 0716 (0741) 0445 (0445) 0524 (0523) 0409 (0409) 1433 (1433)120579120573 3269 (4185) 3958 (5251) 5747 (6647) 6633 (8531) 4235 (4839)

After yogaBefore yoga

736686

586694

576

737 776

585

752

571

0

1

2

3

4

5

6

7

8

9

Frontal Central Perietal Occipital Temporal

PSD

(120583V2H

z)

Figure 6 Global EEGband powers of control group in various lobesof the brain before and after intervention

4 Conclusions

The regular practices of yoga for a period of five months byyoung healthy engineering students enhance different typesof cognitive skills Apart from cognitive the yoga practiceresulted in many health benefits such as improvement inheart rate variability The ratio SDNNRMSSD increasedwhile the ratio LFHF decreasedThis indicates improvementin the parasympathetic activity and decrease in sympatheticactivity Hence the current results suggest that the practice ofyoga modifies the sympathovagal balance towards parasym-pathetic activation improved the heart rate variability andenhanced sense of wellbeing Since the study population isyoung healthy engineering graduates it would be interestingto investigate whether the yoga practice could result inimprovement in the academic performances

3319

0153

6593

2891

0174

5672

0

1

2

3

4

5

6

7

8

Enga

gem

ent i

ndex

val

ue

Before yogaAfter yoga

(120575 + 120579)(120572 + 120573) 120573(120572 + 120579) (120575 + 120579)120572

Figure 7 CNS activity engagement index and executive load indexof control group before and after intervention

In a nutshell it is proved beyond doubt that yogapractices resulted in effective improvements in physiologicalparameters indirectly improving psychological parametersand various cognitive functions The results of this studygreatly encourage further investigation to study whether thepractice of yoga could also enhance academic performance

Limitations of the Study

Limitations of this study include small number of samplesand lack of dedicated control group and methodologicaldifferences Further investigation can be done by employingpsychological tests to evaluate cognitive behavior

12 Computational and Mathematical Methods in Medicine

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

The authors acknowledge the Principal of PDA College ofEngineering Kalaburagi for deputingHNagendra to pursuePhD degree and Department of Electrical EngineeringIIT Roorkee for providing an opportunity under QualityImprovement Programme (QIP) They also acknowledge thestudents who participated in this study and give specialthanks to the yoga instructor

References

[1] P Sengupta ldquoHealth impacts of yoga and pranayama a state-of-the-art reviewrdquo International Journal of Preventive Medicinevol 3 no 7 pp 444ndash458 2012

[2] A Ross and S Thomas ldquoThe health benefits of yoga and exer-cise a review of comparison studiesrdquoThe Journal of Alternativeand Complementary Medicine vol 16 no 1 pp 3ndash12 2010

[3] P A Balaji S R Varne and S S Ali ldquoPhysiological effects ofyogic practices and transcendental meditation in health anddiseaserdquo North American Journal of Medical Sciences vol 4 no10 pp 442ndash448 2012

[4] A Bussing A Michalsen S B S Khalsa S Telles and K JSherman ldquoEffects of yoga on mental and physical health ashort summary of reviewsrdquo Evidence-based Complementary andAlternative Medicine vol 2012 Article ID 165410 7 pages 2012

[5] T N Sathyaprabha P Satishchandra C Pradhan et al ldquoModu-lation of cardiac autonomic balance with adjuvant yoga therapyin patients with refractory epilepsyrdquo Epilepsy and Behavior vol12 no 2 pp 245ndash252 2008

[6] S Telles N Singh and A Balkrishna ldquoHeart rate variabil-ity changes during high frequency yoga breathingand breathawarenessrdquo BioPsychoSocial Medicine vol 5 article 4 2011

[7] L Jatiya KUdupa andA B Bhavanani ldquoEffect of yoga trainingon handgrip respiratory pressures and pulmonary functionrdquoIndian Journal of Physiology and Pharmacology vol 47 no 4pp 387ndash392 2003

[8] D Nangia and R Malhotra ldquoYoga cognition and mentalhealthrdquo Journal of the IndianAcademy ofApplied Psychology vol38 no 2 pp 262ndash269 2012

[9] S Telles and P Sarang ldquoEffects of two yoga based relaxationtechniques on Heart Rate Variability (HRV)rdquo InternationalJournal of Stress Management vol 13 no 4 pp 460ndash475 2006

[10] S Telles R Nagarathna P R Vani and H R Nagendra ldquoAcombination of focusing and defocusing through yoga reducesoptical illusion more than focusing alonerdquo Indian Journal ofPhysiology and Pharmacology vol 41 no 2 pp 179ndash182 1997

[11] K K F Rocha A M Ribeiro K C F Rocha et al ldquoImprove-ment in physiological and psychological parameters after6months of yoga practicerdquo Consciousness and Cognition vol 21no 2 pp 843ndash850 2012

[12] R Khadka B H Paudel V P Sharma S Kumar and N Bhat-tacharya ldquoEffect of yoga on cardiovascular autonomic reactivityin essential hypertensive patientsrdquo Health Renaissance vol 8no 2 pp 102ndash109 2010

[13] L C M Vanderlei C M Pastre R A Hoshi T D de Carvalhoand M F de Godoy ldquoBasic notions of heart rate variabilityand its clinical applicabilityrdquo Brazilian Journal of CardiovascularSurgery vol 24 no 2 pp 205ndash217 2009

[14] M V Hoslashjgaard N-H Holstein-Rathlou E Agner and JK Kanters ldquoDynamics of spectral components of heart ratevariability during changes in autonomic balancerdquoTheAmericanJournal of PhysiologymdashHeart and Circulatory Physiology vol275 no 1 pp H213ndashH219 1998

[15] S Boonnithi and S Phongsuphap ldquoComparison of heart ratevariability measures for mental stress detectionrdquo in Proceedingsof the Computing in Cardiology (CinC rsquo11) pp 85ndash88 2011

[16] H Kobayashi K Ishibashi and H Noguchi ldquoHeart ratevariability an index for monitoring and analyzing humanautonomic activitiesrdquo Journal of Physiological Anthropology andApplied Human Science vol 18 no 2 pp 53ndash59 1999

[17] J Sztajzel ldquoHeart rate variability a noninvasive electrocardio-graphic method to measure the autonomic nervous systemrdquoSwiss Medical Weekly vol 134 no 35-36 pp 514ndash522 2004

[18] J Taelman S Vandeput A Spaepen and S van Huffel ldquoInflu-ence of mental stress on heart rate and heart rate variabilityrdquo inProceedings of the 4th European Conference of the InternationalFederation for Medical and Biological Engineering (IFMBE rsquo08)vol 22 pp 1366ndash1369 November 2008

[19] E Tharion S Parthasarathy and N Neelakantan ldquoShort-termheart rate variability measures in students during examina-tionsrdquo National Medical Journal of India vol 22 no 2 pp 63ndash66 2009

[20] Y Sun N Ye and X Xu ldquoEEG analysis of alcoholics andcontrols based on feature extractionrdquo in Proceedings of the 8thInternational Conference on Signal Processing (ICSP rsquo06) 2006

[21] C Y Chen W K Wong C D Kuo Y T Liao and MD Ke ldquoWavelet real time monitoring system a case studyof the musical influence on electroencephalographyrdquo WSEASTransactions on Systems vol 7 no 2 pp 56ndash62 2008

[22] C Parameswariah and M Cox ldquoFrequency characteristics ofwaveletsrdquo IEEE Power Engineering Review vol 22 no 1 p 722002

[23] A Holm K Lukander J Korpela M Sallinen and K M IMuller ldquoEstimating brain load from the EEGrdquo The ScientificWorld Journal vol 9 pp 639ndash651 2009

[24] J Gruzelier ldquoA theory of alphatheta neurofeedback creativeperformance enhancement long distance functional connectiv-ity and psychological integrationrdquo Cognitive Processing vol 10no 1 supplement pp 101ndash109 2009

[25] F G Freeman P J Mikulka L J Prinzel and M W ScerboldquoEvaluation of an adaptive automation system using three EEGindices with a visual tracking taskrdquo Biological Psychology vol50 no 1 pp 61ndash76 1999

[26] A F Rabbi K Ivanca A V Putnam A Musa C B Thadenand R Fazel-Rezai ldquoHuman performance evaluation based onEEG signal analysis a prospective reviewrdquo in Proceedings of the31st Annual International Conference of the IEEE Engineeringin Medicine and Biology Society (EMBC rsquo09) pp 1879ndash1882September 2009

[27] A Gevins M E Smith LMcEvoy andD Yu ldquoHigh-resolutionEEGmapping of cortical activation related to workingmemoryeffects of task difficulty type of processing and practicerdquoCerebral Cortex vol 7 no 4 pp 374ndash385 1997

[28] J T Coyne C Baldwin A Cole C Sibley and D M RobertsldquoApplying real time physiological measures of cognitive load

Computational and Mathematical Methods in Medicine 13

to improve trainingrdquo in Foundations of Augmented CognitionNeuroergonomics and Operational Neuroscience vol 5638 ofLecture Notes in Computer Science pp 469ndash478 SpringerBerlin Germany 2009

[29] G Bashein M L Nessly S W Bledsoe et al ldquoElectroen-cephalography during surgery with cardiopulmonary bypassand hypothermiardquo Anesthesiology vol 76 no 6 pp 878ndash8911992

[30] R J Barry A R Clarke S J Johnstone R McCarthy andM Selikowitz ldquoElectroencephalogram 120572120573 ratio and arousal inattention-deficithyperactivity disorder evidence of indepen-dent processesrdquoBiological Psychiatry vol 66 no 4 pp 398ndash4012009

[31] L Cao J Li Y Sun H Zhu and C Yan ldquoEEG-based vig-ilance analysis by using fisher score and PCA algorithmrdquo inProceedings of the 1st IEEE International Conference on Progressin Informatics and Computing (PIC rsquo10) pp 175ndash179 ShanghaiChina December 2010

[32] L I Aftanas and S A Golocheikine ldquoNon-linear dynamiccomplexity of the humanEEGduringmeditationrdquoNeuroscienceLetters vol 330 no 2 pp 143ndash146 2002

[33] M Balasubramaniam S Telles and P M Doraiswamy ldquoYogaon our minds a systematic review of yoga for neuropsychiatricdisordersrdquo Frontiers in Psychiatry vol 3 Article ID Article 117pp 1ndash16 2013

[34] B S Moon H C Lee Y H Lee J C Park I S Oh and JW Lee ldquoFuzzy systems to process ECG and EEG signals forquantification of the mental workloadrdquo Information Sciencesvol 142 no 1ndash4 pp 23ndash35 2002

[35] P Raghuraj A G Ramakrishnan H R Nagendra and S TellesldquoEffect of two selected yogic breathing techniques on heart ratevariabilityrdquo Indian Journal of Physiology and Pharmacology vol42 no 4 pp 467ndash472 1998

[36] J J Sollers III T W Buchanan S M Mowrer L K Hill and JFThayer ldquoComparison of the ratio of the standard deviation ofthe r-r interval and the rootmean squared successive differences(SDrMSSD) to the low frequency-to-high frequency (LFHF)ratio in a patient population and normal healthy controlsrdquoBiomedical Sciences Instrumentation vol 43 pp 158ndash163 2007

[37] C Zhao C Zheng M Zhao and J Liu ldquoPhysiological assess-ment of driving mental fatigue using wavelet packet energy andrandom forestsrdquo The American Journal of Biomedical Sciencesvol 2 no 3 pp 262ndash274 2010

[38] O V Grishin V G Grishin D Yu Uryumtsev S V Smirnovand I G Jilina ldquoMetabolic rate variability impact on verylow-frequency of heart rate variabilityrdquo World Applied SciencesJournal vol 19 no 8 pp 1133ndash1139 2012

[39] E Basar C Basar-Eroglu S Karakas and M SchurmannldquoGamma alpha delta and theta oscillations govern cognitiveprocessesrdquo International Journal of Psychophysiology vol 39 no2-3 pp 241ndash248 2000

[40] K C Khare and S K Nigam ldquoA study of electroencephalogramin meditatorsrdquo Indian Journal of Physiology and Pharmacologyvol 44 no 2 pp 173ndash178 2000

[41] J Jacobs and M J Kahana ldquoDirect brain recordings fueladvances in cognitive electrophysiologyrdquo Trends in CognitiveSciences vol 14 no 4 pp 162ndash171 2010

Submit your manuscripts athttpwwwhindawicom

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Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

MEDIATORSINFLAMMATION

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Behavioural Neurology

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Disease Markers

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OncologyJournal of

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Oxidative Medicine and Cellular Longevity

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PPAR Research

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Immunology ResearchHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal of

ObesityJournal of

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Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Computational and Mathematical Methods in Medicine

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Research and TreatmentAIDS

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Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Parkinsonrsquos Disease

Evidence-Based Complementary and Alternative Medicine

Volume 2014Hindawi Publishing Corporationhttpwwwhindawicom

4 Computational and Mathematical Methods in Medicine

Table 2 The equations used to compute frequency domain mea-sures

Index Equations Unit

LFnuLF(LF +HF)

lowast 100

HFnuHF(LF +HF)

lowast 100

SVI LFHF

mdash

LFRelpowerLFTPlowast 100 mdash

HFRelpowerHFTPlowast 100 mdash

dLFHF 1003816100381610038161003816LFnu minusHFnu

1003816100381610038161003816

where TP = VLF + LF + HF

11611976

10682

2109 19022455 2837

7942

28941824

0

20

40

60

80

100

120

BeforeAfter

minus20120573 120572 120579 120575 120574

PSD

(120583V2H

z)

Figure 2 Global EEG band powers of yoga group before and afterintervention

12 EEG Band Frequencies and Cognitive Processes Thebrainactivity which changes continuously with time is called ldquoelec-troencephalogramrdquo (EEG) which can be used to investigatethe cognitive abilities and memory executions of individualsin terms of its band of frequencies

The EEG is highly complex and is combination of fivedifferent frequency waveforms namely 120575 (delta) 120579 (theta) 120573(beta)120572 (alpha) and 120574 (gamma)waves respectively [20]Theamplitude of the brain waves is approximately in the rangeof 10 120583V to 250120583V and the frequency varies between 05Hzand 100HzThe frequency range and their characteristics areshown in Table 3

The EEG waveforms may be global or localized to thespecific areas on the scalp This kind of electrical data isimportant to study the correlation between yoga asanas andphysiological states because any shift in the EEG frequencyrange reflects the physiological arousalThe various EEG ratioindices and their physiological and cognitive interpretationsare shown in Table 4

13 Extraction of EEG Band Frequencies Using DiscreteWavelet Transforms (DWT) Discrete wavelet transforms(DWT) are widely used for the analysis of physiological

signals as compared to the classical techniques such as fastFourier transforms (FFT) When FFT is applied on thetime series signal the signal information is available in theform of spectral parameters That is the whole time domaininformation will be lost It is equivalent to windowed Fouriertransform and can be used to measure both the time andfrequency changes of a signal [21]

The DWT splits the input signal into approximation(trend) and detailed coefficients (fluctuation) respectivelyThe approximation coefficient can further be split into anew approximation and detailed coefficients This process iscontinued progressively to get a new set of approximation anddetailed coefficients of a signal at various levels of decomposi-tion [22] The selection of analyzing wavelet is called motherwavelet and number of decomposition levels to be carried outis the critical pointThemother wavelet determines the shapeof the signal to be decomposed In this paper the waveletfunction db4 is used to extract five frequency bands (120575 120579120572 120573 and 120574) of EEG signal The application of higher orderwavelet function such as db20 produces large number ofcoefficients Larger number of coefficients average out thedetail components of the signal and fail to detect fast movingsignals such as EEG To retrieve the information at a specificinstant of time the wavelets with less number of coefficientsare better choice The lower order wavelet function db4has good time and frequency localization properties andin addition this wavelet has similar morphology as thatof EEG signal to be detected Therefore db4 wavelets arebetter choice for precisely detecting fast moving transientsand short duration information signals Thus by the processof decomposition DWT can detect the important hiddenfeatures from the original signal

In this study the EEG signal was acquired with samplingfrequency of 500Hz The useful information of this signallies in the range of 05ndash70Hz Hence a level of 7 usingdb4 was applied to decompose the EEG signal into itsapproximate (A1ndashA7) and detail (D1ndashD7) coefficients Afterthe seventh level of decomposition the band of frequenciesobtained are D1 (250ndash500Hz) A1 (0ndash250Hz) D2 (125ndash250Hz) A2 (0ndash125Hz) D3 (625ndash125Hz) A3 (0ndash625Hz)D4 (3125ndash625Hz) A4 (0ndash3125Hz) D5 (15625ndash3125Hz)A5 (0ndash15625Hz) D6 (78125ndash15625Hz) A6 (0ndash78125Hz)D7 (3906ndash7813Hz) and A7 (0ndash3906Hz) respectively Thedecomposition levels from D1 to D3 were considered asnoise components and hence excluded from the analysisThe finer detailed coefficients from levels D4ndashD7 and finalapproximate coefficients from level A7 are retained as theyapproximately represent the EEG physiological frequencysubbands of 120574120573120572 120579 and120575 respectivelyThese five frequencybands are analyzed to investigate different cognitive effectsdue to yoga among healthy subjects Different EEG ratiosused in this study to investigate cognitive performances interms of physiological parameters are shown in Figure 4which are derived from various sources

2 Methodology and Experimental Procedure

21 Subjects The total number of subjects who participatedin the experiment was 30 young healthy graduate and

Computational and Mathematical Methods in Medicine 5

Table 3 Five EEG frequency bands

Parameters Frequency range (Hz) Magnitude (120583V) Activity Remark120573 13ndash30 lt30 120583V Desynchronized Mental occupation120572 8ndash13 50ndash100 120583V Synchronized Relaxed tranquility and wakefulness120579 4ndash8 20ndash40 120583V Desynchronized Dreaming state120575 05ndash4 75ndash150 120583V Desynchronized State of dreamless sleep120574 30ndash70 mdash Synchronized Sensory integration

Table 4 EEG band ratios and their physiologicalcognitive activityindex interpretation

EEG band ratios Activitycorrelation Sources120579120572 Heart rate (HR) [23]

120572120579 Performance enhancementindex or ldquowellbeingrdquo [24]

120573120572 Arousal index [25]120573120579 Neural activity [25]

120573(120572 + 120579) Cognitive performance andattentional resource index [26]

120579(frontal)120572(parietal) Task load index [27](120575 + 120579)120572 Executive load index [28]120572120575 Brain perfusion [29]120579120573 CNS arousal [30](120579 + 120575)(120572 + 120573) Sum of LF to HF ratio [29]120572120573 Desynchronization [31]120575120579 Synchronization(120579 + 120572)120573 Vigilance index [31]

postgraduate engineering students of IIT Roorkee (male =27 female = 3) All the subjects were right handed withnormal eye sight The study population was divided intotwo groups experimental group and control group In thisstudy the sample size is relatively small and both groupshave the same size The study population was randomlyassigned to either of the groups by block randomizationmethod to achieve the balance The block size of two wasused Both participants and investigators were unaware of thegroups to be assigned in advance Each group consisted of15 subjects with two females in experimental group and onein control group The mean and standard deviation of eachgroup were 2242 plusmn 230 and 2367 plusmn 209 respectively Thesame subjects were chosen for both experimental and controlgroups to diminish misperceiving influences and make thestudy more effective Subjects with previous yoga practicehistory of alcohol consumption smoking and any other drugconsumption were excluded from this studyThe participantswere informed a priori about the study and their consent wasobtained Subjects participated voluntarily and cooperatedthroughout the training period The subjects were asked tonot to deviate their regular life style during this study All thesubjects of experimental group obtained same yoga trainingfor a period of fivemonths for 15 hours per day between 6 pmand 730 pm

In this study the physiological parameters such as ECGand their ratio indices have been evaluated to assess thecognitive benefits of the yoga practice along with its wellestablished health benefits This may provide the windowfor further investigation to correlate the actual measures ofcognitive functions and their physiological parameters

The practice of yoga schedule consisted of prayerpranayama (breathing techniques) and simple yogic pos-tures Explanations on stress management importance ofmeditation and yoga in everyday life were also briefed

The subjects practiced yoga under observation of trainedyoga instructor During practice session various types ofasanas (postural exercises) pranayama (breathing tech-niques) and dhyana (meditation) were performed Theseasanas increase the strength concentration will power andmindfulness by manipulating the natural energy of the body[1 32 33]

(1) Standing asanas (postures) they consisted of suryanamaskar dandasana urdhave asana trikonasanaardha asana hasta padasana mahavir asana andvatayanasana

(2) Sitting asanas (postures) they include mandookasana and oorm asana ushtra asan ardha matsy-endrasana vakrasana supt asana matsyendrasanauttan mandukasana vakasana mayoor asan padmvak asan padma mayurasana pashchimottanasaneka padangusthasana vipreet pad asan and purnachakrasana

(3) Asana (posture) lying on back this includes uttanpad asana pawanmuktasana market asan shree-shan sarvangasana halasana setu bandhasana andchakrasana

(4) Asana (posture) lying on stomach this includes nau-kasana yan asan shalabh asan and dhanurasana

(5) Pranayama (breathing) and kriya include Anulom-vilom kapalbhati Ujjayi pranayama Bhramari pra-nayama sheetali pranayama sheetkari pranayamasurya bheda pranayama bhastrika pranayama bahyapranayama udgeeth pranayama kaki mudra andshanmukhi mudra Everyday practice session wasconcluded with prayer and meditation

22 Recording ECG and EEG Signals and Analysis BothECG and EEG signals were recorded simultaneously usingBIOPACMP150 System (EEG100C = 10 nos and ECG100C =3 nos) with Acqknowledge 40 software

6 Computational and Mathematical Methods in Medicine

ECG signal was recorded using five electrodes by con-necting to left and right wrinkles and left and right armsand one electrode at chest Before fixing the electrodes theywere cleaned and electrode gel was applied to reduce theskin resistance to get good quality of recording signal EEGsignal was recorded by fixing the CAP100C on the scalp ofthe subjects This cap was made of Lycra type fabric with20 reusable tin electrodes attached to it according to theinternational 10ndash20 norms Before fixing the cap on subjectsscalp the electrodes were cleaned with saline water andelectrode gel was appliedThismaintains the resistance below5 kΩ between the scalp and electrodes

All the data were collected during 6 pm to 730 pm atthe yoga centre of the temple premises in two stages Thedata collected at the beginning of the intervention period wasconsidered as the first stage during which five minutes ofbaseline ECG and EEG signals were recorded from subjectsof both experimental and control groups in sitting positionwith eyes closed The baseline signal was saved on the harddisk for offline processing

Both ECG and EEG signals were recorded with a sam-pling frequency of 512Hz to have better resolution of R-Rtime interval series and EEG activity

The experimental group practiced yoga for a period of fivemonths for 15 hr per day in the evening from 6 pm to 730pmThe control group was asked not to practice any form ofyogic practices or physical exercises during this period Theend of five months yoga training period was considered assecond stage During this stage again both ECG and EEGdata were collected from experimental and control groupfor a period of 10 minutes During recording subjects wereasked to minimize eye blinks and avoid body movements tominimize any artifacts that could be introduced If artifactswere introduced due to uncontrolled bodymovements or eyeblinks or due to technical reasons the recording time wasprolonged for a few more minutes The data was again savedon the hard disk for offline processing These data were usedfor the evaluation of various cognitive functions in terms ofphysiological parameters

Though maximum care was taken the recorded data wascontaminated with many artifacts Manual editing was per-formed for both ECG and EEG signalsThe RR intervals werethen extracted from the Acqknowledge 40 software whichuses modified Pan and Tompkins algorithm The intervalsless than 300ms and above 1200ms were eliminated fromtime series data set and were saved in text format for furtherprocessing using MATLAB 71 Any data whose standarddeviation was less than or equal to three times the standarddeviation was considered outliers and removed from the databefore determining the time domain parameters of heartrate variability (HRV) The artifact free data was segmentedinto five groups with 10 seconds segments each The averagevalue of each 10 seconds data was used in the analysis Theimportant time domainmeasures of HRV such asmeanHRVSDANN RMSSD and mean HR were computed

The frequency domain parameters namely VLF LFHF LF HF ratio and VHF were extracted from the FFTalgorithm The normalized values were computed by divid-ing the respective frequencies by total power minus VLF

4077

0092

6472

2048

0228

3820

0

1

2

3

4

5

6

7

8

Enga

gem

ent i

ndex

val

ue

Before yogaAfter yoga

(120575 + 120579)(120572 + 120573) 120573(120572 + 120579) (120575 + 120579)120572

Figure 3 CNS activity engagement index and executive load indexof yoga group before and after intervention

The normalization reduces the effect of LF and HF on totalpower In conformity with the task force recommendationThe artifact free signal of two minutes duration was used forcomputing frequency domain parameters

Hypotheses of the StudyHypothesis 1 There is no significant difference in physiolog-ical parameters (HR HRV) and cognitive functions of thesubjects of experimental group before and after yoga training(intervention)

Hypothesis 2 There is no significant difference in physio-logical parameters (HR HRV) and cognitive functions ofthe subjects of control group before and after yoga training(intervention)

3 Results and Discussion

Results are grouped in two parts firstly HRV analysis whichincludes time and frequency domain parameters secondlycognitive performance evaluation based on EEG engagementindices Both EEG and ECG signals reflect global arousal oralertness of the brain [34]

31 HRVAnalysis Theheart rate variability (HRV) is an indi-cator of cardiac ANS and HR is controlled by neural activity[35] The yogic exercise particularly pranayama (breathingtechniques) activatesANSThe yoga practicing group showedsignificant increase in HRV (119875 lt 00304) and reduction inresting HR (119875 lt 00389) The significant reduction in restingHR indicates a relaxed state of physiology and increasedmental alertness Depending on left or right cerebral hemi-spherical dominance there will be improvement in spatialor verbal skills The SDNN which reflects the total powersignificantly increased (119875lt00012)TheRMSSD an indicatorof parasympathetic activity also increased significantly (119875 lt00058) The ratio of SDNNRMSSD which is surrogate ofLFHF ratio [36] increased significantly (119875lt00039) LF was

Computational and Mathematical Methods in Medicine 7

Frontal Central Perietal Occipital Temporal Total0

5

10

15

20

25PS

D (120583

V2H

z)

(a) 120573 power

Frontal Central Perietal Occipital Temporal Total0

5

10

15

20

25

PSD

(120583V2H

z)

(b) 120572 power

0

20

40

60

80

100

120

Frontal Central Perietal Occipital Temporal Total

PSD

(120583V2H

z)

(c) 120579 power

0

5

10

15

20

25

Frontal Central Perietal Occipital Temporal Total

PSD

(mV2H

z)

(d) 120575 power

0

2

4

6

8

10

12

14

16

BeforeAfter

Frontal Central Perietal Occipital Temporal Total

PSD

(120583V2H

z)

(e) 120574 power

Figure 4 EEG band powers of control group in various lobes of the brain before and after intervention

significantly decreased (119875 lt 00002) while HF was increased(119875 lt 00003) The decrease of LF and increase of HF reflectsthe improvement in the dominance in the parasympatheticactivity A significant improvement in HRV may be dueto an increase in parasympathetic activity or a decrease insympathetic activity [35] These indirectly help in reducingthe psychological parameters such as distress anxiety anddepression in young healthy subjects

There was significant reduction in LF power (119875 lt 00002)whereas parasympathetic activity significantly increased (119875 lt00003) The LF powers indicate both sympathetic andparasympathetic modulation whereas HF power reflects

parasympathetic activation Hence reduction in sympatheticactivity and enhanced parasympathetic activity results indeceleration in the cardiac activity The ratio LFHF whichis an indicator of autonomic ANS balance between sym-pathetic and parasympathetic nervous system activity [37]was significantly decreased (119875 lt 00000) There is alwaysconstant interaction between sympathetic and parasympa-thetic activity to regulate heart rate variability The VLFincreased without significance in yoga group while there wassignificant increase in control group The VLF representsslow changes in the heart rate [38] but the exact functionof it is yet to be understood A significant reduction in

8 Computational and Mathematical Methods in Medicine

Table 5 Time and frequency domain parameters before and after intervention of yoga and control group

Parameters Yoga group Control groupBefore After 119875 value Before After 119875 value

mHRV (ms) 75721 plusmn 6537 81329 plusmn 7891 00304 87467 plusmn 9155 85572 plusmn 7048 02505mHR (bpm) 7979 plusmn 774 7457 plusmn 705 00389 6950 plusmn 943 7050 plusmn 622 02759SDNN (ms) 4443 plusmn 2176 5214 plusmn 2327 00012 5322 plusmn 2169 5383 plusmn 1951 09044RMSSD (ms) 3993 plusmn 2365 5521 plusmn 2278 00058 5483 plusmn 2946 49 plusmn 2789 01999SDNNRMSSD 077 plusmn 037 111 plusmn 057 00039 077 plusmn 037 121 plusmn 028 01336VLF (nu) 402 plusmn 096 1163 plusmn 983 00177 342 plusmn 991 1404 plusmn 1006 00007LF (nu) 12306 plusmn 2110 5685 plusmn 1016 00002 4514 plusmn 1309 4157 plusmn 1660 00000HF (nu) 2739 plusmn 844 4315 plusmn 1016 00003 4648 plusmn 461 220 plusmn 579 00269LFrelative 7133 plusmn 567 5116 plusmn 951 00000 4642 plusmn 1070 7081 plusmn 713 00000HFrelative 2739 plusmn 844 4315 plusmn 1016 00003 4648 plusmn 461 4220 plusmn 579 00269TP (nu) 17199 plusmn 2241 11163 plusmn 983 00000 9503 plusmn 1129 9781 plusmn 1244 00000LF HF 499 plusmn 198 1411 plusmn 045 00000 099 plusmn 032 355 plusmn 156 00000119875 gt 010 not significant 119875 lt 010marginal 119875 lt 005 fair 119875 lt 001 good 119875 lt 0001 excellent difference 119875 lt 005 is considered significant level and for anyvalue less than this the null hypothesis is rejected 119905stat gt 119905valu for the null hypothesis to be rejected If 119875 = 005 there is 5 chance of no real difference

total power was observed in yoga group This might be dueto significant decrease of sympathetic activity compared tosignificant increase of parasympathetic activity The VHFpower generally reflects part of noise component and doesnot possess clinically significant information

Control group showed significant increase of LF power(119875 lt 00000) decreased HF power (119875 lt 0029) increasedLFHF ratio (119875 lt 00000) and increased VLF power But nosignificant changes were observed in time domain parame-ters

The LF and HF band power of HRV are expressed innormalized units The representation of these frequencyband powers in normalized units articulates the degree ofcontrol exercised and the relative balance of two limbs ofthe autonomic nervous system [35]Moreover normalized LFpower is thought to represent the sympathetic modulation asopposed to absolute units Since theHRV spectral parametersare computed by the autonomic nervous system (ANS) mea-surement of HRV may have greater application in assessingautonomic statues

Studentrsquos paired 119905-test was performed on set of pre- andpostintervention data samples to investigate whether therewas any real difference between them Each 119905 value has acorresponding 119875 value The 119875 value which is the probabilitythat the pattern of data samples in the sample could beproduced by random data provides the information aboutthe likelihood that there is a real difference in the data patternThis significant difference in the data set could be due to theeffect of particular training or an intervention given to thesubjects

The various time and frequency domain parameters ofboth yoga and control group are shown in Table 5 Anyvariations in these parameters could be due to relative age dif-ferences between yoga and control groups or methodologicaldifferences or limited number of samples in the study

The decrease in HR could be due to combined effect ofelements of yoga The reduction in stress after yoga couldbe other possible reason for improved HRV in this study

The previous researches suggest that yoga practice resultsin neurophysiological balance by lowering level of cholin-esterase and catecholamines Further this result increasedparasympathetic and decreased sympathetic activity Theresults of this study are in concurrence with previous studies[6 9 35] These studies indicated reduced sympatheticactivity and enhanced parasympathetic activity after yoga

32 Cognitive Performance Analysis The regular practice ofyoga for a period of fivemonths by young healthy engineeringstudents resulted in the increase of 120572 120573 and 120575 EEG bandpowers and decrease in the 120579 and 120574 band powers Theincreased 120573 band power indicate enhancement in certaincognitive functions such as alertness while increased 120572and decreased 120575 reflect enhanced vigilance level indicatingincreased alertnessThus the increase of high frequency bandpowers (120572 120573) and decrease of low frequency band powers (120575120579) are associated with enhancement in certain cognitive skillssuch as memory and visual information processing

The various cognitive behavior parameters have beenevaluated based on various EEG indices such as 120579120572 120573120572120573120579 (120575 + 120579)120572 120573(120572 + 120579) and (120575 + 120579)(120572 + 120573) Increasein 120573 band power indicates a higher level of alertness andenhanced engagement task and enhancement in variouscognitive abilities The increased band powers of 120572 and 120579indicate decreased alertness reduced engagement task andgood information processing capabilities [25] The 120575 and 120582activity are used for analysis of many cognitive processes[39]The ratio 120573120579which is representative of improvement incognitive skills increasedThe heart rate index 120579120572 decreasedperformance enhancement index 120572120579 increased attentionresource index 120573(120572 + 120579) significantly increased executiveload index (120575 + 120579)120572 decreased and ratio (120575 + 120579)(120572 + 120573)decreased The 120572 120573 and 120575 band power increased in frontalcentral parietal occipital and temporal lobes The 120579 bandpower was increased only in occipital lobe while 120574 bandpower in frontal and slightly in temporal lobes As the frontallobe is associated with reasoning planning problem solving

Computational and Mathematical Methods in Medicine 9

Table 6 Mean powers of EEG frequency bands averaged across all the lobes of the brain before and after yoga intervention

EEG band powers120574 (120583V2Hz) 120573 (120583V2Hz) 120572 (120583V2Hz) 120579 (120583V2Hz) 120575 (120583V2Hz)

Yoga groupBefore yoga 380 plusmn 093 232 plusmn 049 395 plusmn 070 2136 plusmn 343 422 plusmn 042After yoga 365 plusmn 069 491 plusmn 163 567 plusmn 168 1588 plusmn 257 579 plusmn 106

Control groupBefore yoga 298 plusmn 136 386 plusmn 096 392 plusmn 097 1757 plusmn 254 446 plusmn 089After yoga 294 plusmn 133 372 plusmn 082 387 plusmn 090 2112 plusmn 387 437 plusmn 078

and cognition parietal lobe with visual perception recogni-tion information processing and spatial reasoning temporallobe with memory and processing of verbal and auditorysignals and occipital lobe with visual spatial processing andrecognition An increase of EEG frequency band powers inthese lobes indicates the enhancement of certain type ofcognitive skillsThe type of the cognitive skills developed canbe assessed based on increased or decreased EEG band powerin these lobesThemean absolute values of these band powersin various lobes of the brain are shown in Table 6

The increase of frontal 120579 band power indicates intellectualconcentration andmeditative state of relief from nervousnessand is negatively related with sympathetic activation Thisreflects a near relationship between autonomic functionactivity of medial frontal neural circuitry and probability ofcontrolling central nervous system (CNS) functions owing toyoga practice and meditation [12] 120572 waves are indicative ofincreased relaxed state ofmind and its bandpower is inverselyrelated to mental activity Yoga enhanced various cognitiveskills improved sense of wellbeing and responsiveness andenhanced cognitive functions as substantiated by increased120572 and 120573 band powers and various engagement indices Italso improves mental consciousness and achieves reductionin stress and strain and thus advocates complete health andwellbeing in an individual [40] Increase in 120573 band powerwould indicate a higher level of alertness and enhancedengagement task whereas increased band powers of 120572 and 120579would indicate decreased alertness and reduced engagementtask [25] The increase of 120573 power reflects improvement ofcertain cognitive functions such as memory and reactiontime That of 120572 and 120575 indicates synchronization of brainactivity The total EEG band power also increased in yogagroup compared to the control group

The ratio 120579120572 is associated with HR This ratio decreasedin all lobes of the brain indicating the relaxed state of sub-jectsThis reduction could be either increase of 120572 band poweror decrease of 120579 band power Since 120572 power increased in yogagroup this ratio decreased indicating enhancement of certaincognitive faculties (memory attention) and improvement inthe HRV These in turn indicate indirect improvement incertain cognitive functions such as reaction time The ratio120573120572 [25] is called arousal indexThis indicates level of arousalbased on interbeat intervals (IBI) activity Arousal level gt0indicates higher than normal arousal and lt0 indicates lowerthan normal arousal

This ratio increased (4711) in yoga group whiledecreased in control group (243) The increases of thisratio indicate enhanced cognitive functions such as attentionThe decreases of this ratio reflect reduction in the corecapabilities of cognitive functions This ratio increased in alllobes of the brain but the maximum increase was observedin parietal (7805) central (5312) and temporal (4504)lobes It increased to (3824) and (1976) in frontal andoccipital lobes respectively The ratio (120575 + 120579)120572 is calledexecutive load index [28] and is a measure of executive loador comprehension Positive value indicates increased loadand negative value indicates decreased load It reflects theoscillations in precise cortical network active among spatiallydisjoint brain compartment This ratio decreased (4098)in experimental group while it increased (1719) slightlyin control group The decrease in this ratio may be dueto increase in 120572 band power or reduced band power ofeither 120575 or 120579 or both It is observed that 120572 band power wasincreased in yoga practicing group This ratio was also founddecreased in all the lobes of the brain Another importantparameter 120579(fro)120572(par) [27] is called task load index Thisratio decreases in experimental group while it increases incontrol group It is evident from the relation that the ratiodecreases due to increase in 120572 band power These results areshown in Tables 7 and 8

The ratio 120579120573 indicates central nervous system (CNS)arousal [30] and increased ratio is marker of under arousalThis ratio decreased in yoga group The reductions in thisratio reflect the shift of 120572 and 120579 activity towards 120573 activityThe increased 120573 band powers indicate enhanced cognitiveperformance such as memory attention and concentrationThe ratio 120572120575 which is called ldquobrain perfusionrdquo index [29]was increased (46) in yoga practiced group This indicatessufficient amount of blood flow to the different parts ofthe brain among yoga group These in turn enhances thebetter functioning of the brain The ratio LFHF can beexpressed in terms of (120579 + 120575)(120572 + 120573) [29] Slower brainoscillations (120579 and 120575) harmonize considerable neuron groupsacross larger brain areas and faster oscillations (120572 and 120573)synchronize smaller focused neuronal assemblies [41]Whengroups of neurons oscillate together synchronously theymore effectively communicated with each other The index(120579 + 120575)(120572 + 120573) indicates sympathovagal balance of theautonomic nervous system (ANS) Lower ratios indicatebetter balance of ANSThis ratio decreased in yoga group but

10 Computational and Mathematical Methods in Medicine

Table 7 Cognitive index parameters of yoga group before and after yoga intervention Postintervention values are shown within theparenthesis

EEG indices Yoga groupFrontal Central Parietal Occipital Temporal

120579120572 4621 (2806) 4951 (2063) 5059 (2973) 8792 (4609) 4604 (2480)120572120579 0216 (0356) 0202 (0485) 0198 (0336) 0114 (0217) 0217 (0403)120573120572 0612 (0846) 0625 (0957) 0523 (0931) 0607 (0727) 0564 (0818)120573120579 0132 (0302) 0126 (0464) 0103 (0313) 0069 (0158) 0123 (0330)120573(120572 + 120579) 0109 (0222) 0105 (0312) 0086 (0234) 0062 (0130) 0101 (0235)120579(fro)120572(par) 4621 (2806) 4951 (2063) 5059 (2973) 8792 (4609) 4604 (2480)(120575 + 120579)120572 5590 (3926) 5964 (3200) 6168 (3961) 10112 (5907) 5614 (3243)sum(120575 + 120579)120572 = 46392 (27876)

Table 8 Global EEG band power ratios before and after yoga inter-vention

EEG indices Yoga group Control groupBefore yoga After yoga Before yoga After yoga

120579120572 5405 2800 4485 5460120572120579 0185 0357 0228 0183120573120572 0588 0865 0986 0962120573120579 0109 0309 0220 0176120573(120572 + 120579) 0092 0228 0180 0149120579(fro)120572(par) 5405 2800 4485 5460(120575 + 120579)120572 6472 3820 5623 6590sum(120575 + 120579)120572 46392 27876 40456 47080

Table 9 EEG indices and their values before and after yoga inter-vention

Parameters Yoga group ControlBefore After Before After

120572120575 0937 0980 0879 0885(120579 + 120575)(120572 + 120573) 408 205 332 289120572120573 170 116 10139 10394120575120579 0197 0364 0209 2488120579120573 9198 3235 5530 4721

did not change in control group The ratio 120572120573 [31] which iscalled desynchronization is used to analyze vigilance indexand 120575120579 is called synchronization The ratio 120572120573 decreasedwhich is desirable The increase 120573 of band power indicatesimproved cognitive performance Since the parameter is indenominator the ratio decreases when there is increasedcognitive performance However in control group this ratiowas slightly increased Another ratio 120575120579 was increasedrelatively by small amount in experimental group than thecontrol groupThe 120572120575 ratio was decreased in frontal centraland occipital lobes while it increased in parietal and temporallobes These results are shown in Tables 9 10 and 11

The relative EEG band powers of 120573 120572 and 120575 increasedin yoga group in all the lobes of the brain The increases ofthese band powers indicate improvement of certain cognitivefunctions such as memory attention executive functionsand concentration The increase of 120575 power and decrease of

1932 1958

8783

222914911860 1618

10558

21181189

0

20

40

60

80

100

120

PSD

(120583V2H

z)

BeforeAfter

120573 120572 120579 120575 120574

Figure 5 Global EEG band powers of control group before andafter intervention

120579 power indicate improvement in neural activityThe variousEEG band powers are shown in Figure 1

The total band power (global) of 120573 120572 and 120575 increasedamong yoga group The increased 120573 power was associatedwith enhanced cognitive performance such as improvedalertness The maximum 120573 power increased in frontal andcentral lobes of the brain This indicates the improvementin emotion process and cognition The increased 120572 anddecreased 120579 powers physiologically signify the enhancedvigilance and increased alertness level of subjects These areshown in Figure 2 The improvement in cognitive functionswas associated with increased power in high frequency band(120573) and reduction in low frequency band (120579) Therefore 120573120579ratio is suitable index to assess the improvement in cognitiveskills of the subjectsThe cognitive performance index 120573(120572 +120579) increased and ratio of sum of low frequency to sum of highfrequency (120579 + 120575)(120573 + 120572) was decreased among yoga groupwhich is shown in Figure 3

There were no significant changes in EEG band powersengagement indices total power and cognitive performancesindices among control group The various performancesparameters of control group are shown in Figures 4 5 6 and7

Computational and Mathematical Methods in Medicine 11

Table 10 EEG index values of yoga group in different lobes of the brain before and after yoga intervention Postintervention values are shownin parenthesis

Parameters Brain lobesFrontal Central Parietal Occipital Temporal

120572120575 1032 (0893) 0988 (0879) 0902 (1011) 0757 (0770) 0990 (1312)(120579 + 120575)(120572 + 120573) 3468 (0534) 3669 (0566) 4050 (0402) 6294 (0363) 3589 (0363)120572120573 1634 (2806) 1599 (2063) 1913 (2973) 1648 (4609) 1772 (2480)120575120579 0210 (0814) 0205 (0524) 0219 (0614) 0150 (0570) 0219 (0657)120579120573 7550 (3316) 7916 (2156) 9675 (3194) 14492 (6341) 8159 (3032)

Table 11 EEG index values of control group in different lobes of the brain before and after yoga intervention Postintervention values areshown in parenthesis

Parameters Brain lobesFrontal Central Parietal Occipital Temporal

120572120575 0914 (0944) 0940 (0940) 0760 (0760) 0825 (0825) 0930 (0931)(120579 + 120575)(120572 + 120573) 0424 (0356) 0326 (0261) 0271 (0241) 0262 (0218) 0486 (0438)120572120573 3428 (4186) 3711 (4891) 6412 (7311) 5513 (6817) 4385 (4970)120575120579 0716 (0741) 0445 (0445) 0524 (0523) 0409 (0409) 1433 (1433)120579120573 3269 (4185) 3958 (5251) 5747 (6647) 6633 (8531) 4235 (4839)

After yogaBefore yoga

736686

586694

576

737 776

585

752

571

0

1

2

3

4

5

6

7

8

9

Frontal Central Perietal Occipital Temporal

PSD

(120583V2H

z)

Figure 6 Global EEGband powers of control group in various lobesof the brain before and after intervention

4 Conclusions

The regular practices of yoga for a period of five months byyoung healthy engineering students enhance different typesof cognitive skills Apart from cognitive the yoga practiceresulted in many health benefits such as improvement inheart rate variability The ratio SDNNRMSSD increasedwhile the ratio LFHF decreasedThis indicates improvementin the parasympathetic activity and decrease in sympatheticactivity Hence the current results suggest that the practice ofyoga modifies the sympathovagal balance towards parasym-pathetic activation improved the heart rate variability andenhanced sense of wellbeing Since the study population isyoung healthy engineering graduates it would be interestingto investigate whether the yoga practice could result inimprovement in the academic performances

3319

0153

6593

2891

0174

5672

0

1

2

3

4

5

6

7

8

Enga

gem

ent i

ndex

val

ue

Before yogaAfter yoga

(120575 + 120579)(120572 + 120573) 120573(120572 + 120579) (120575 + 120579)120572

Figure 7 CNS activity engagement index and executive load indexof control group before and after intervention

In a nutshell it is proved beyond doubt that yogapractices resulted in effective improvements in physiologicalparameters indirectly improving psychological parametersand various cognitive functions The results of this studygreatly encourage further investigation to study whether thepractice of yoga could also enhance academic performance

Limitations of the Study

Limitations of this study include small number of samplesand lack of dedicated control group and methodologicaldifferences Further investigation can be done by employingpsychological tests to evaluate cognitive behavior

12 Computational and Mathematical Methods in Medicine

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

The authors acknowledge the Principal of PDA College ofEngineering Kalaburagi for deputingHNagendra to pursuePhD degree and Department of Electrical EngineeringIIT Roorkee for providing an opportunity under QualityImprovement Programme (QIP) They also acknowledge thestudents who participated in this study and give specialthanks to the yoga instructor

References

[1] P Sengupta ldquoHealth impacts of yoga and pranayama a state-of-the-art reviewrdquo International Journal of Preventive Medicinevol 3 no 7 pp 444ndash458 2012

[2] A Ross and S Thomas ldquoThe health benefits of yoga and exer-cise a review of comparison studiesrdquoThe Journal of Alternativeand Complementary Medicine vol 16 no 1 pp 3ndash12 2010

[3] P A Balaji S R Varne and S S Ali ldquoPhysiological effects ofyogic practices and transcendental meditation in health anddiseaserdquo North American Journal of Medical Sciences vol 4 no10 pp 442ndash448 2012

[4] A Bussing A Michalsen S B S Khalsa S Telles and K JSherman ldquoEffects of yoga on mental and physical health ashort summary of reviewsrdquo Evidence-based Complementary andAlternative Medicine vol 2012 Article ID 165410 7 pages 2012

[5] T N Sathyaprabha P Satishchandra C Pradhan et al ldquoModu-lation of cardiac autonomic balance with adjuvant yoga therapyin patients with refractory epilepsyrdquo Epilepsy and Behavior vol12 no 2 pp 245ndash252 2008

[6] S Telles N Singh and A Balkrishna ldquoHeart rate variabil-ity changes during high frequency yoga breathingand breathawarenessrdquo BioPsychoSocial Medicine vol 5 article 4 2011

[7] L Jatiya KUdupa andA B Bhavanani ldquoEffect of yoga trainingon handgrip respiratory pressures and pulmonary functionrdquoIndian Journal of Physiology and Pharmacology vol 47 no 4pp 387ndash392 2003

[8] D Nangia and R Malhotra ldquoYoga cognition and mentalhealthrdquo Journal of the IndianAcademy ofApplied Psychology vol38 no 2 pp 262ndash269 2012

[9] S Telles and P Sarang ldquoEffects of two yoga based relaxationtechniques on Heart Rate Variability (HRV)rdquo InternationalJournal of Stress Management vol 13 no 4 pp 460ndash475 2006

[10] S Telles R Nagarathna P R Vani and H R Nagendra ldquoAcombination of focusing and defocusing through yoga reducesoptical illusion more than focusing alonerdquo Indian Journal ofPhysiology and Pharmacology vol 41 no 2 pp 179ndash182 1997

[11] K K F Rocha A M Ribeiro K C F Rocha et al ldquoImprove-ment in physiological and psychological parameters after6months of yoga practicerdquo Consciousness and Cognition vol 21no 2 pp 843ndash850 2012

[12] R Khadka B H Paudel V P Sharma S Kumar and N Bhat-tacharya ldquoEffect of yoga on cardiovascular autonomic reactivityin essential hypertensive patientsrdquo Health Renaissance vol 8no 2 pp 102ndash109 2010

[13] L C M Vanderlei C M Pastre R A Hoshi T D de Carvalhoand M F de Godoy ldquoBasic notions of heart rate variabilityand its clinical applicabilityrdquo Brazilian Journal of CardiovascularSurgery vol 24 no 2 pp 205ndash217 2009

[14] M V Hoslashjgaard N-H Holstein-Rathlou E Agner and JK Kanters ldquoDynamics of spectral components of heart ratevariability during changes in autonomic balancerdquoTheAmericanJournal of PhysiologymdashHeart and Circulatory Physiology vol275 no 1 pp H213ndashH219 1998

[15] S Boonnithi and S Phongsuphap ldquoComparison of heart ratevariability measures for mental stress detectionrdquo in Proceedingsof the Computing in Cardiology (CinC rsquo11) pp 85ndash88 2011

[16] H Kobayashi K Ishibashi and H Noguchi ldquoHeart ratevariability an index for monitoring and analyzing humanautonomic activitiesrdquo Journal of Physiological Anthropology andApplied Human Science vol 18 no 2 pp 53ndash59 1999

[17] J Sztajzel ldquoHeart rate variability a noninvasive electrocardio-graphic method to measure the autonomic nervous systemrdquoSwiss Medical Weekly vol 134 no 35-36 pp 514ndash522 2004

[18] J Taelman S Vandeput A Spaepen and S van Huffel ldquoInflu-ence of mental stress on heart rate and heart rate variabilityrdquo inProceedings of the 4th European Conference of the InternationalFederation for Medical and Biological Engineering (IFMBE rsquo08)vol 22 pp 1366ndash1369 November 2008

[19] E Tharion S Parthasarathy and N Neelakantan ldquoShort-termheart rate variability measures in students during examina-tionsrdquo National Medical Journal of India vol 22 no 2 pp 63ndash66 2009

[20] Y Sun N Ye and X Xu ldquoEEG analysis of alcoholics andcontrols based on feature extractionrdquo in Proceedings of the 8thInternational Conference on Signal Processing (ICSP rsquo06) 2006

[21] C Y Chen W K Wong C D Kuo Y T Liao and MD Ke ldquoWavelet real time monitoring system a case studyof the musical influence on electroencephalographyrdquo WSEASTransactions on Systems vol 7 no 2 pp 56ndash62 2008

[22] C Parameswariah and M Cox ldquoFrequency characteristics ofwaveletsrdquo IEEE Power Engineering Review vol 22 no 1 p 722002

[23] A Holm K Lukander J Korpela M Sallinen and K M IMuller ldquoEstimating brain load from the EEGrdquo The ScientificWorld Journal vol 9 pp 639ndash651 2009

[24] J Gruzelier ldquoA theory of alphatheta neurofeedback creativeperformance enhancement long distance functional connectiv-ity and psychological integrationrdquo Cognitive Processing vol 10no 1 supplement pp 101ndash109 2009

[25] F G Freeman P J Mikulka L J Prinzel and M W ScerboldquoEvaluation of an adaptive automation system using three EEGindices with a visual tracking taskrdquo Biological Psychology vol50 no 1 pp 61ndash76 1999

[26] A F Rabbi K Ivanca A V Putnam A Musa C B Thadenand R Fazel-Rezai ldquoHuman performance evaluation based onEEG signal analysis a prospective reviewrdquo in Proceedings of the31st Annual International Conference of the IEEE Engineeringin Medicine and Biology Society (EMBC rsquo09) pp 1879ndash1882September 2009

[27] A Gevins M E Smith LMcEvoy andD Yu ldquoHigh-resolutionEEGmapping of cortical activation related to workingmemoryeffects of task difficulty type of processing and practicerdquoCerebral Cortex vol 7 no 4 pp 374ndash385 1997

[28] J T Coyne C Baldwin A Cole C Sibley and D M RobertsldquoApplying real time physiological measures of cognitive load

Computational and Mathematical Methods in Medicine 13

to improve trainingrdquo in Foundations of Augmented CognitionNeuroergonomics and Operational Neuroscience vol 5638 ofLecture Notes in Computer Science pp 469ndash478 SpringerBerlin Germany 2009

[29] G Bashein M L Nessly S W Bledsoe et al ldquoElectroen-cephalography during surgery with cardiopulmonary bypassand hypothermiardquo Anesthesiology vol 76 no 6 pp 878ndash8911992

[30] R J Barry A R Clarke S J Johnstone R McCarthy andM Selikowitz ldquoElectroencephalogram 120572120573 ratio and arousal inattention-deficithyperactivity disorder evidence of indepen-dent processesrdquoBiological Psychiatry vol 66 no 4 pp 398ndash4012009

[31] L Cao J Li Y Sun H Zhu and C Yan ldquoEEG-based vig-ilance analysis by using fisher score and PCA algorithmrdquo inProceedings of the 1st IEEE International Conference on Progressin Informatics and Computing (PIC rsquo10) pp 175ndash179 ShanghaiChina December 2010

[32] L I Aftanas and S A Golocheikine ldquoNon-linear dynamiccomplexity of the humanEEGduringmeditationrdquoNeuroscienceLetters vol 330 no 2 pp 143ndash146 2002

[33] M Balasubramaniam S Telles and P M Doraiswamy ldquoYogaon our minds a systematic review of yoga for neuropsychiatricdisordersrdquo Frontiers in Psychiatry vol 3 Article ID Article 117pp 1ndash16 2013

[34] B S Moon H C Lee Y H Lee J C Park I S Oh and JW Lee ldquoFuzzy systems to process ECG and EEG signals forquantification of the mental workloadrdquo Information Sciencesvol 142 no 1ndash4 pp 23ndash35 2002

[35] P Raghuraj A G Ramakrishnan H R Nagendra and S TellesldquoEffect of two selected yogic breathing techniques on heart ratevariabilityrdquo Indian Journal of Physiology and Pharmacology vol42 no 4 pp 467ndash472 1998

[36] J J Sollers III T W Buchanan S M Mowrer L K Hill and JFThayer ldquoComparison of the ratio of the standard deviation ofthe r-r interval and the rootmean squared successive differences(SDrMSSD) to the low frequency-to-high frequency (LFHF)ratio in a patient population and normal healthy controlsrdquoBiomedical Sciences Instrumentation vol 43 pp 158ndash163 2007

[37] C Zhao C Zheng M Zhao and J Liu ldquoPhysiological assess-ment of driving mental fatigue using wavelet packet energy andrandom forestsrdquo The American Journal of Biomedical Sciencesvol 2 no 3 pp 262ndash274 2010

[38] O V Grishin V G Grishin D Yu Uryumtsev S V Smirnovand I G Jilina ldquoMetabolic rate variability impact on verylow-frequency of heart rate variabilityrdquo World Applied SciencesJournal vol 19 no 8 pp 1133ndash1139 2012

[39] E Basar C Basar-Eroglu S Karakas and M SchurmannldquoGamma alpha delta and theta oscillations govern cognitiveprocessesrdquo International Journal of Psychophysiology vol 39 no2-3 pp 241ndash248 2000

[40] K C Khare and S K Nigam ldquoA study of electroencephalogramin meditatorsrdquo Indian Journal of Physiology and Pharmacologyvol 44 no 2 pp 173ndash178 2000

[41] J Jacobs and M J Kahana ldquoDirect brain recordings fueladvances in cognitive electrophysiologyrdquo Trends in CognitiveSciences vol 14 no 4 pp 162ndash171 2010

Submit your manuscripts athttpwwwhindawicom

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Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

MEDIATORSINFLAMMATION

of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Behavioural Neurology

EndocrinologyInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Disease Markers

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

BioMed Research International

OncologyJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Oxidative Medicine and Cellular Longevity

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

PPAR Research

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Immunology ResearchHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal of

ObesityJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Computational and Mathematical Methods in Medicine

OphthalmologyJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Diabetes ResearchJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Research and TreatmentAIDS

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Gastroenterology Research and Practice

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Parkinsonrsquos Disease

Evidence-Based Complementary and Alternative Medicine

Volume 2014Hindawi Publishing Corporationhttpwwwhindawicom

Computational and Mathematical Methods in Medicine 5

Table 3 Five EEG frequency bands

Parameters Frequency range (Hz) Magnitude (120583V) Activity Remark120573 13ndash30 lt30 120583V Desynchronized Mental occupation120572 8ndash13 50ndash100 120583V Synchronized Relaxed tranquility and wakefulness120579 4ndash8 20ndash40 120583V Desynchronized Dreaming state120575 05ndash4 75ndash150 120583V Desynchronized State of dreamless sleep120574 30ndash70 mdash Synchronized Sensory integration

Table 4 EEG band ratios and their physiologicalcognitive activityindex interpretation

EEG band ratios Activitycorrelation Sources120579120572 Heart rate (HR) [23]

120572120579 Performance enhancementindex or ldquowellbeingrdquo [24]

120573120572 Arousal index [25]120573120579 Neural activity [25]

120573(120572 + 120579) Cognitive performance andattentional resource index [26]

120579(frontal)120572(parietal) Task load index [27](120575 + 120579)120572 Executive load index [28]120572120575 Brain perfusion [29]120579120573 CNS arousal [30](120579 + 120575)(120572 + 120573) Sum of LF to HF ratio [29]120572120573 Desynchronization [31]120575120579 Synchronization(120579 + 120572)120573 Vigilance index [31]

postgraduate engineering students of IIT Roorkee (male =27 female = 3) All the subjects were right handed withnormal eye sight The study population was divided intotwo groups experimental group and control group In thisstudy the sample size is relatively small and both groupshave the same size The study population was randomlyassigned to either of the groups by block randomizationmethod to achieve the balance The block size of two wasused Both participants and investigators were unaware of thegroups to be assigned in advance Each group consisted of15 subjects with two females in experimental group and onein control group The mean and standard deviation of eachgroup were 2242 plusmn 230 and 2367 plusmn 209 respectively Thesame subjects were chosen for both experimental and controlgroups to diminish misperceiving influences and make thestudy more effective Subjects with previous yoga practicehistory of alcohol consumption smoking and any other drugconsumption were excluded from this studyThe participantswere informed a priori about the study and their consent wasobtained Subjects participated voluntarily and cooperatedthroughout the training period The subjects were asked tonot to deviate their regular life style during this study All thesubjects of experimental group obtained same yoga trainingfor a period of fivemonths for 15 hours per day between 6 pmand 730 pm

In this study the physiological parameters such as ECGand their ratio indices have been evaluated to assess thecognitive benefits of the yoga practice along with its wellestablished health benefits This may provide the windowfor further investigation to correlate the actual measures ofcognitive functions and their physiological parameters

The practice of yoga schedule consisted of prayerpranayama (breathing techniques) and simple yogic pos-tures Explanations on stress management importance ofmeditation and yoga in everyday life were also briefed

The subjects practiced yoga under observation of trainedyoga instructor During practice session various types ofasanas (postural exercises) pranayama (breathing tech-niques) and dhyana (meditation) were performed Theseasanas increase the strength concentration will power andmindfulness by manipulating the natural energy of the body[1 32 33]

(1) Standing asanas (postures) they consisted of suryanamaskar dandasana urdhave asana trikonasanaardha asana hasta padasana mahavir asana andvatayanasana

(2) Sitting asanas (postures) they include mandookasana and oorm asana ushtra asan ardha matsy-endrasana vakrasana supt asana matsyendrasanauttan mandukasana vakasana mayoor asan padmvak asan padma mayurasana pashchimottanasaneka padangusthasana vipreet pad asan and purnachakrasana

(3) Asana (posture) lying on back this includes uttanpad asana pawanmuktasana market asan shree-shan sarvangasana halasana setu bandhasana andchakrasana

(4) Asana (posture) lying on stomach this includes nau-kasana yan asan shalabh asan and dhanurasana

(5) Pranayama (breathing) and kriya include Anulom-vilom kapalbhati Ujjayi pranayama Bhramari pra-nayama sheetali pranayama sheetkari pranayamasurya bheda pranayama bhastrika pranayama bahyapranayama udgeeth pranayama kaki mudra andshanmukhi mudra Everyday practice session wasconcluded with prayer and meditation

22 Recording ECG and EEG Signals and Analysis BothECG and EEG signals were recorded simultaneously usingBIOPACMP150 System (EEG100C = 10 nos and ECG100C =3 nos) with Acqknowledge 40 software

6 Computational and Mathematical Methods in Medicine

ECG signal was recorded using five electrodes by con-necting to left and right wrinkles and left and right armsand one electrode at chest Before fixing the electrodes theywere cleaned and electrode gel was applied to reduce theskin resistance to get good quality of recording signal EEGsignal was recorded by fixing the CAP100C on the scalp ofthe subjects This cap was made of Lycra type fabric with20 reusable tin electrodes attached to it according to theinternational 10ndash20 norms Before fixing the cap on subjectsscalp the electrodes were cleaned with saline water andelectrode gel was appliedThismaintains the resistance below5 kΩ between the scalp and electrodes

All the data were collected during 6 pm to 730 pm atthe yoga centre of the temple premises in two stages Thedata collected at the beginning of the intervention period wasconsidered as the first stage during which five minutes ofbaseline ECG and EEG signals were recorded from subjectsof both experimental and control groups in sitting positionwith eyes closed The baseline signal was saved on the harddisk for offline processing

Both ECG and EEG signals were recorded with a sam-pling frequency of 512Hz to have better resolution of R-Rtime interval series and EEG activity

The experimental group practiced yoga for a period of fivemonths for 15 hr per day in the evening from 6 pm to 730pmThe control group was asked not to practice any form ofyogic practices or physical exercises during this period Theend of five months yoga training period was considered assecond stage During this stage again both ECG and EEGdata were collected from experimental and control groupfor a period of 10 minutes During recording subjects wereasked to minimize eye blinks and avoid body movements tominimize any artifacts that could be introduced If artifactswere introduced due to uncontrolled bodymovements or eyeblinks or due to technical reasons the recording time wasprolonged for a few more minutes The data was again savedon the hard disk for offline processing These data were usedfor the evaluation of various cognitive functions in terms ofphysiological parameters

Though maximum care was taken the recorded data wascontaminated with many artifacts Manual editing was per-formed for both ECG and EEG signalsThe RR intervals werethen extracted from the Acqknowledge 40 software whichuses modified Pan and Tompkins algorithm The intervalsless than 300ms and above 1200ms were eliminated fromtime series data set and were saved in text format for furtherprocessing using MATLAB 71 Any data whose standarddeviation was less than or equal to three times the standarddeviation was considered outliers and removed from the databefore determining the time domain parameters of heartrate variability (HRV) The artifact free data was segmentedinto five groups with 10 seconds segments each The averagevalue of each 10 seconds data was used in the analysis Theimportant time domainmeasures of HRV such asmeanHRVSDANN RMSSD and mean HR were computed

The frequency domain parameters namely VLF LFHF LF HF ratio and VHF were extracted from the FFTalgorithm The normalized values were computed by divid-ing the respective frequencies by total power minus VLF

4077

0092

6472

2048

0228

3820

0

1

2

3

4

5

6

7

8

Enga

gem

ent i

ndex

val

ue

Before yogaAfter yoga

(120575 + 120579)(120572 + 120573) 120573(120572 + 120579) (120575 + 120579)120572

Figure 3 CNS activity engagement index and executive load indexof yoga group before and after intervention

The normalization reduces the effect of LF and HF on totalpower In conformity with the task force recommendationThe artifact free signal of two minutes duration was used forcomputing frequency domain parameters

Hypotheses of the StudyHypothesis 1 There is no significant difference in physiolog-ical parameters (HR HRV) and cognitive functions of thesubjects of experimental group before and after yoga training(intervention)

Hypothesis 2 There is no significant difference in physio-logical parameters (HR HRV) and cognitive functions ofthe subjects of control group before and after yoga training(intervention)

3 Results and Discussion

Results are grouped in two parts firstly HRV analysis whichincludes time and frequency domain parameters secondlycognitive performance evaluation based on EEG engagementindices Both EEG and ECG signals reflect global arousal oralertness of the brain [34]

31 HRVAnalysis Theheart rate variability (HRV) is an indi-cator of cardiac ANS and HR is controlled by neural activity[35] The yogic exercise particularly pranayama (breathingtechniques) activatesANSThe yoga practicing group showedsignificant increase in HRV (119875 lt 00304) and reduction inresting HR (119875 lt 00389) The significant reduction in restingHR indicates a relaxed state of physiology and increasedmental alertness Depending on left or right cerebral hemi-spherical dominance there will be improvement in spatialor verbal skills The SDNN which reflects the total powersignificantly increased (119875lt00012)TheRMSSD an indicatorof parasympathetic activity also increased significantly (119875 lt00058) The ratio of SDNNRMSSD which is surrogate ofLFHF ratio [36] increased significantly (119875lt00039) LF was

Computational and Mathematical Methods in Medicine 7

Frontal Central Perietal Occipital Temporal Total0

5

10

15

20

25PS

D (120583

V2H

z)

(a) 120573 power

Frontal Central Perietal Occipital Temporal Total0

5

10

15

20

25

PSD

(120583V2H

z)

(b) 120572 power

0

20

40

60

80

100

120

Frontal Central Perietal Occipital Temporal Total

PSD

(120583V2H

z)

(c) 120579 power

0

5

10

15

20

25

Frontal Central Perietal Occipital Temporal Total

PSD

(mV2H

z)

(d) 120575 power

0

2

4

6

8

10

12

14

16

BeforeAfter

Frontal Central Perietal Occipital Temporal Total

PSD

(120583V2H

z)

(e) 120574 power

Figure 4 EEG band powers of control group in various lobes of the brain before and after intervention

significantly decreased (119875 lt 00002) while HF was increased(119875 lt 00003) The decrease of LF and increase of HF reflectsthe improvement in the dominance in the parasympatheticactivity A significant improvement in HRV may be dueto an increase in parasympathetic activity or a decrease insympathetic activity [35] These indirectly help in reducingthe psychological parameters such as distress anxiety anddepression in young healthy subjects

There was significant reduction in LF power (119875 lt 00002)whereas parasympathetic activity significantly increased (119875 lt00003) The LF powers indicate both sympathetic andparasympathetic modulation whereas HF power reflects

parasympathetic activation Hence reduction in sympatheticactivity and enhanced parasympathetic activity results indeceleration in the cardiac activity The ratio LFHF whichis an indicator of autonomic ANS balance between sym-pathetic and parasympathetic nervous system activity [37]was significantly decreased (119875 lt 00000) There is alwaysconstant interaction between sympathetic and parasympa-thetic activity to regulate heart rate variability The VLFincreased without significance in yoga group while there wassignificant increase in control group The VLF representsslow changes in the heart rate [38] but the exact functionof it is yet to be understood A significant reduction in

8 Computational and Mathematical Methods in Medicine

Table 5 Time and frequency domain parameters before and after intervention of yoga and control group

Parameters Yoga group Control groupBefore After 119875 value Before After 119875 value

mHRV (ms) 75721 plusmn 6537 81329 plusmn 7891 00304 87467 plusmn 9155 85572 plusmn 7048 02505mHR (bpm) 7979 plusmn 774 7457 plusmn 705 00389 6950 plusmn 943 7050 plusmn 622 02759SDNN (ms) 4443 plusmn 2176 5214 plusmn 2327 00012 5322 plusmn 2169 5383 plusmn 1951 09044RMSSD (ms) 3993 plusmn 2365 5521 plusmn 2278 00058 5483 plusmn 2946 49 plusmn 2789 01999SDNNRMSSD 077 plusmn 037 111 plusmn 057 00039 077 plusmn 037 121 plusmn 028 01336VLF (nu) 402 plusmn 096 1163 plusmn 983 00177 342 plusmn 991 1404 plusmn 1006 00007LF (nu) 12306 plusmn 2110 5685 plusmn 1016 00002 4514 plusmn 1309 4157 plusmn 1660 00000HF (nu) 2739 plusmn 844 4315 plusmn 1016 00003 4648 plusmn 461 220 plusmn 579 00269LFrelative 7133 plusmn 567 5116 plusmn 951 00000 4642 plusmn 1070 7081 plusmn 713 00000HFrelative 2739 plusmn 844 4315 plusmn 1016 00003 4648 plusmn 461 4220 plusmn 579 00269TP (nu) 17199 plusmn 2241 11163 plusmn 983 00000 9503 plusmn 1129 9781 plusmn 1244 00000LF HF 499 plusmn 198 1411 plusmn 045 00000 099 plusmn 032 355 plusmn 156 00000119875 gt 010 not significant 119875 lt 010marginal 119875 lt 005 fair 119875 lt 001 good 119875 lt 0001 excellent difference 119875 lt 005 is considered significant level and for anyvalue less than this the null hypothesis is rejected 119905stat gt 119905valu for the null hypothesis to be rejected If 119875 = 005 there is 5 chance of no real difference

total power was observed in yoga group This might be dueto significant decrease of sympathetic activity compared tosignificant increase of parasympathetic activity The VHFpower generally reflects part of noise component and doesnot possess clinically significant information

Control group showed significant increase of LF power(119875 lt 00000) decreased HF power (119875 lt 0029) increasedLFHF ratio (119875 lt 00000) and increased VLF power But nosignificant changes were observed in time domain parame-ters

The LF and HF band power of HRV are expressed innormalized units The representation of these frequencyband powers in normalized units articulates the degree ofcontrol exercised and the relative balance of two limbs ofthe autonomic nervous system [35]Moreover normalized LFpower is thought to represent the sympathetic modulation asopposed to absolute units Since theHRV spectral parametersare computed by the autonomic nervous system (ANS) mea-surement of HRV may have greater application in assessingautonomic statues

Studentrsquos paired 119905-test was performed on set of pre- andpostintervention data samples to investigate whether therewas any real difference between them Each 119905 value has acorresponding 119875 value The 119875 value which is the probabilitythat the pattern of data samples in the sample could beproduced by random data provides the information aboutthe likelihood that there is a real difference in the data patternThis significant difference in the data set could be due to theeffect of particular training or an intervention given to thesubjects

The various time and frequency domain parameters ofboth yoga and control group are shown in Table 5 Anyvariations in these parameters could be due to relative age dif-ferences between yoga and control groups or methodologicaldifferences or limited number of samples in the study

The decrease in HR could be due to combined effect ofelements of yoga The reduction in stress after yoga couldbe other possible reason for improved HRV in this study

The previous researches suggest that yoga practice resultsin neurophysiological balance by lowering level of cholin-esterase and catecholamines Further this result increasedparasympathetic and decreased sympathetic activity Theresults of this study are in concurrence with previous studies[6 9 35] These studies indicated reduced sympatheticactivity and enhanced parasympathetic activity after yoga

32 Cognitive Performance Analysis The regular practice ofyoga for a period of fivemonths by young healthy engineeringstudents resulted in the increase of 120572 120573 and 120575 EEG bandpowers and decrease in the 120579 and 120574 band powers Theincreased 120573 band power indicate enhancement in certaincognitive functions such as alertness while increased 120572and decreased 120575 reflect enhanced vigilance level indicatingincreased alertnessThus the increase of high frequency bandpowers (120572 120573) and decrease of low frequency band powers (120575120579) are associated with enhancement in certain cognitive skillssuch as memory and visual information processing

The various cognitive behavior parameters have beenevaluated based on various EEG indices such as 120579120572 120573120572120573120579 (120575 + 120579)120572 120573(120572 + 120579) and (120575 + 120579)(120572 + 120573) Increasein 120573 band power indicates a higher level of alertness andenhanced engagement task and enhancement in variouscognitive abilities The increased band powers of 120572 and 120579indicate decreased alertness reduced engagement task andgood information processing capabilities [25] The 120575 and 120582activity are used for analysis of many cognitive processes[39]The ratio 120573120579which is representative of improvement incognitive skills increasedThe heart rate index 120579120572 decreasedperformance enhancement index 120572120579 increased attentionresource index 120573(120572 + 120579) significantly increased executiveload index (120575 + 120579)120572 decreased and ratio (120575 + 120579)(120572 + 120573)decreased The 120572 120573 and 120575 band power increased in frontalcentral parietal occipital and temporal lobes The 120579 bandpower was increased only in occipital lobe while 120574 bandpower in frontal and slightly in temporal lobes As the frontallobe is associated with reasoning planning problem solving

Computational and Mathematical Methods in Medicine 9

Table 6 Mean powers of EEG frequency bands averaged across all the lobes of the brain before and after yoga intervention

EEG band powers120574 (120583V2Hz) 120573 (120583V2Hz) 120572 (120583V2Hz) 120579 (120583V2Hz) 120575 (120583V2Hz)

Yoga groupBefore yoga 380 plusmn 093 232 plusmn 049 395 plusmn 070 2136 plusmn 343 422 plusmn 042After yoga 365 plusmn 069 491 plusmn 163 567 plusmn 168 1588 plusmn 257 579 plusmn 106

Control groupBefore yoga 298 plusmn 136 386 plusmn 096 392 plusmn 097 1757 plusmn 254 446 plusmn 089After yoga 294 plusmn 133 372 plusmn 082 387 plusmn 090 2112 plusmn 387 437 plusmn 078

and cognition parietal lobe with visual perception recogni-tion information processing and spatial reasoning temporallobe with memory and processing of verbal and auditorysignals and occipital lobe with visual spatial processing andrecognition An increase of EEG frequency band powers inthese lobes indicates the enhancement of certain type ofcognitive skillsThe type of the cognitive skills developed canbe assessed based on increased or decreased EEG band powerin these lobesThemean absolute values of these band powersin various lobes of the brain are shown in Table 6

The increase of frontal 120579 band power indicates intellectualconcentration andmeditative state of relief from nervousnessand is negatively related with sympathetic activation Thisreflects a near relationship between autonomic functionactivity of medial frontal neural circuitry and probability ofcontrolling central nervous system (CNS) functions owing toyoga practice and meditation [12] 120572 waves are indicative ofincreased relaxed state ofmind and its bandpower is inverselyrelated to mental activity Yoga enhanced various cognitiveskills improved sense of wellbeing and responsiveness andenhanced cognitive functions as substantiated by increased120572 and 120573 band powers and various engagement indices Italso improves mental consciousness and achieves reductionin stress and strain and thus advocates complete health andwellbeing in an individual [40] Increase in 120573 band powerwould indicate a higher level of alertness and enhancedengagement task whereas increased band powers of 120572 and 120579would indicate decreased alertness and reduced engagementtask [25] The increase of 120573 power reflects improvement ofcertain cognitive functions such as memory and reactiontime That of 120572 and 120575 indicates synchronization of brainactivity The total EEG band power also increased in yogagroup compared to the control group

The ratio 120579120572 is associated with HR This ratio decreasedin all lobes of the brain indicating the relaxed state of sub-jectsThis reduction could be either increase of 120572 band poweror decrease of 120579 band power Since 120572 power increased in yogagroup this ratio decreased indicating enhancement of certaincognitive faculties (memory attention) and improvement inthe HRV These in turn indicate indirect improvement incertain cognitive functions such as reaction time The ratio120573120572 [25] is called arousal indexThis indicates level of arousalbased on interbeat intervals (IBI) activity Arousal level gt0indicates higher than normal arousal and lt0 indicates lowerthan normal arousal

This ratio increased (4711) in yoga group whiledecreased in control group (243) The increases of thisratio indicate enhanced cognitive functions such as attentionThe decreases of this ratio reflect reduction in the corecapabilities of cognitive functions This ratio increased in alllobes of the brain but the maximum increase was observedin parietal (7805) central (5312) and temporal (4504)lobes It increased to (3824) and (1976) in frontal andoccipital lobes respectively The ratio (120575 + 120579)120572 is calledexecutive load index [28] and is a measure of executive loador comprehension Positive value indicates increased loadand negative value indicates decreased load It reflects theoscillations in precise cortical network active among spatiallydisjoint brain compartment This ratio decreased (4098)in experimental group while it increased (1719) slightlyin control group The decrease in this ratio may be dueto increase in 120572 band power or reduced band power ofeither 120575 or 120579 or both It is observed that 120572 band power wasincreased in yoga practicing group This ratio was also founddecreased in all the lobes of the brain Another importantparameter 120579(fro)120572(par) [27] is called task load index Thisratio decreases in experimental group while it increases incontrol group It is evident from the relation that the ratiodecreases due to increase in 120572 band power These results areshown in Tables 7 and 8

The ratio 120579120573 indicates central nervous system (CNS)arousal [30] and increased ratio is marker of under arousalThis ratio decreased in yoga group The reductions in thisratio reflect the shift of 120572 and 120579 activity towards 120573 activityThe increased 120573 band powers indicate enhanced cognitiveperformance such as memory attention and concentrationThe ratio 120572120575 which is called ldquobrain perfusionrdquo index [29]was increased (46) in yoga practiced group This indicatessufficient amount of blood flow to the different parts ofthe brain among yoga group These in turn enhances thebetter functioning of the brain The ratio LFHF can beexpressed in terms of (120579 + 120575)(120572 + 120573) [29] Slower brainoscillations (120579 and 120575) harmonize considerable neuron groupsacross larger brain areas and faster oscillations (120572 and 120573)synchronize smaller focused neuronal assemblies [41]Whengroups of neurons oscillate together synchronously theymore effectively communicated with each other The index(120579 + 120575)(120572 + 120573) indicates sympathovagal balance of theautonomic nervous system (ANS) Lower ratios indicatebetter balance of ANSThis ratio decreased in yoga group but

10 Computational and Mathematical Methods in Medicine

Table 7 Cognitive index parameters of yoga group before and after yoga intervention Postintervention values are shown within theparenthesis

EEG indices Yoga groupFrontal Central Parietal Occipital Temporal

120579120572 4621 (2806) 4951 (2063) 5059 (2973) 8792 (4609) 4604 (2480)120572120579 0216 (0356) 0202 (0485) 0198 (0336) 0114 (0217) 0217 (0403)120573120572 0612 (0846) 0625 (0957) 0523 (0931) 0607 (0727) 0564 (0818)120573120579 0132 (0302) 0126 (0464) 0103 (0313) 0069 (0158) 0123 (0330)120573(120572 + 120579) 0109 (0222) 0105 (0312) 0086 (0234) 0062 (0130) 0101 (0235)120579(fro)120572(par) 4621 (2806) 4951 (2063) 5059 (2973) 8792 (4609) 4604 (2480)(120575 + 120579)120572 5590 (3926) 5964 (3200) 6168 (3961) 10112 (5907) 5614 (3243)sum(120575 + 120579)120572 = 46392 (27876)

Table 8 Global EEG band power ratios before and after yoga inter-vention

EEG indices Yoga group Control groupBefore yoga After yoga Before yoga After yoga

120579120572 5405 2800 4485 5460120572120579 0185 0357 0228 0183120573120572 0588 0865 0986 0962120573120579 0109 0309 0220 0176120573(120572 + 120579) 0092 0228 0180 0149120579(fro)120572(par) 5405 2800 4485 5460(120575 + 120579)120572 6472 3820 5623 6590sum(120575 + 120579)120572 46392 27876 40456 47080

Table 9 EEG indices and their values before and after yoga inter-vention

Parameters Yoga group ControlBefore After Before After

120572120575 0937 0980 0879 0885(120579 + 120575)(120572 + 120573) 408 205 332 289120572120573 170 116 10139 10394120575120579 0197 0364 0209 2488120579120573 9198 3235 5530 4721

did not change in control group The ratio 120572120573 [31] which iscalled desynchronization is used to analyze vigilance indexand 120575120579 is called synchronization The ratio 120572120573 decreasedwhich is desirable The increase 120573 of band power indicatesimproved cognitive performance Since the parameter is indenominator the ratio decreases when there is increasedcognitive performance However in control group this ratiowas slightly increased Another ratio 120575120579 was increasedrelatively by small amount in experimental group than thecontrol groupThe 120572120575 ratio was decreased in frontal centraland occipital lobes while it increased in parietal and temporallobes These results are shown in Tables 9 10 and 11

The relative EEG band powers of 120573 120572 and 120575 increasedin yoga group in all the lobes of the brain The increases ofthese band powers indicate improvement of certain cognitivefunctions such as memory attention executive functionsand concentration The increase of 120575 power and decrease of

1932 1958

8783

222914911860 1618

10558

21181189

0

20

40

60

80

100

120

PSD

(120583V2H

z)

BeforeAfter

120573 120572 120579 120575 120574

Figure 5 Global EEG band powers of control group before andafter intervention

120579 power indicate improvement in neural activityThe variousEEG band powers are shown in Figure 1

The total band power (global) of 120573 120572 and 120575 increasedamong yoga group The increased 120573 power was associatedwith enhanced cognitive performance such as improvedalertness The maximum 120573 power increased in frontal andcentral lobes of the brain This indicates the improvementin emotion process and cognition The increased 120572 anddecreased 120579 powers physiologically signify the enhancedvigilance and increased alertness level of subjects These areshown in Figure 2 The improvement in cognitive functionswas associated with increased power in high frequency band(120573) and reduction in low frequency band (120579) Therefore 120573120579ratio is suitable index to assess the improvement in cognitiveskills of the subjectsThe cognitive performance index 120573(120572 +120579) increased and ratio of sum of low frequency to sum of highfrequency (120579 + 120575)(120573 + 120572) was decreased among yoga groupwhich is shown in Figure 3

There were no significant changes in EEG band powersengagement indices total power and cognitive performancesindices among control group The various performancesparameters of control group are shown in Figures 4 5 6 and7

Computational and Mathematical Methods in Medicine 11

Table 10 EEG index values of yoga group in different lobes of the brain before and after yoga intervention Postintervention values are shownin parenthesis

Parameters Brain lobesFrontal Central Parietal Occipital Temporal

120572120575 1032 (0893) 0988 (0879) 0902 (1011) 0757 (0770) 0990 (1312)(120579 + 120575)(120572 + 120573) 3468 (0534) 3669 (0566) 4050 (0402) 6294 (0363) 3589 (0363)120572120573 1634 (2806) 1599 (2063) 1913 (2973) 1648 (4609) 1772 (2480)120575120579 0210 (0814) 0205 (0524) 0219 (0614) 0150 (0570) 0219 (0657)120579120573 7550 (3316) 7916 (2156) 9675 (3194) 14492 (6341) 8159 (3032)

Table 11 EEG index values of control group in different lobes of the brain before and after yoga intervention Postintervention values areshown in parenthesis

Parameters Brain lobesFrontal Central Parietal Occipital Temporal

120572120575 0914 (0944) 0940 (0940) 0760 (0760) 0825 (0825) 0930 (0931)(120579 + 120575)(120572 + 120573) 0424 (0356) 0326 (0261) 0271 (0241) 0262 (0218) 0486 (0438)120572120573 3428 (4186) 3711 (4891) 6412 (7311) 5513 (6817) 4385 (4970)120575120579 0716 (0741) 0445 (0445) 0524 (0523) 0409 (0409) 1433 (1433)120579120573 3269 (4185) 3958 (5251) 5747 (6647) 6633 (8531) 4235 (4839)

After yogaBefore yoga

736686

586694

576

737 776

585

752

571

0

1

2

3

4

5

6

7

8

9

Frontal Central Perietal Occipital Temporal

PSD

(120583V2H

z)

Figure 6 Global EEGband powers of control group in various lobesof the brain before and after intervention

4 Conclusions

The regular practices of yoga for a period of five months byyoung healthy engineering students enhance different typesof cognitive skills Apart from cognitive the yoga practiceresulted in many health benefits such as improvement inheart rate variability The ratio SDNNRMSSD increasedwhile the ratio LFHF decreasedThis indicates improvementin the parasympathetic activity and decrease in sympatheticactivity Hence the current results suggest that the practice ofyoga modifies the sympathovagal balance towards parasym-pathetic activation improved the heart rate variability andenhanced sense of wellbeing Since the study population isyoung healthy engineering graduates it would be interestingto investigate whether the yoga practice could result inimprovement in the academic performances

3319

0153

6593

2891

0174

5672

0

1

2

3

4

5

6

7

8

Enga

gem

ent i

ndex

val

ue

Before yogaAfter yoga

(120575 + 120579)(120572 + 120573) 120573(120572 + 120579) (120575 + 120579)120572

Figure 7 CNS activity engagement index and executive load indexof control group before and after intervention

In a nutshell it is proved beyond doubt that yogapractices resulted in effective improvements in physiologicalparameters indirectly improving psychological parametersand various cognitive functions The results of this studygreatly encourage further investigation to study whether thepractice of yoga could also enhance academic performance

Limitations of the Study

Limitations of this study include small number of samplesand lack of dedicated control group and methodologicaldifferences Further investigation can be done by employingpsychological tests to evaluate cognitive behavior

12 Computational and Mathematical Methods in Medicine

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

The authors acknowledge the Principal of PDA College ofEngineering Kalaburagi for deputingHNagendra to pursuePhD degree and Department of Electrical EngineeringIIT Roorkee for providing an opportunity under QualityImprovement Programme (QIP) They also acknowledge thestudents who participated in this study and give specialthanks to the yoga instructor

References

[1] P Sengupta ldquoHealth impacts of yoga and pranayama a state-of-the-art reviewrdquo International Journal of Preventive Medicinevol 3 no 7 pp 444ndash458 2012

[2] A Ross and S Thomas ldquoThe health benefits of yoga and exer-cise a review of comparison studiesrdquoThe Journal of Alternativeand Complementary Medicine vol 16 no 1 pp 3ndash12 2010

[3] P A Balaji S R Varne and S S Ali ldquoPhysiological effects ofyogic practices and transcendental meditation in health anddiseaserdquo North American Journal of Medical Sciences vol 4 no10 pp 442ndash448 2012

[4] A Bussing A Michalsen S B S Khalsa S Telles and K JSherman ldquoEffects of yoga on mental and physical health ashort summary of reviewsrdquo Evidence-based Complementary andAlternative Medicine vol 2012 Article ID 165410 7 pages 2012

[5] T N Sathyaprabha P Satishchandra C Pradhan et al ldquoModu-lation of cardiac autonomic balance with adjuvant yoga therapyin patients with refractory epilepsyrdquo Epilepsy and Behavior vol12 no 2 pp 245ndash252 2008

[6] S Telles N Singh and A Balkrishna ldquoHeart rate variabil-ity changes during high frequency yoga breathingand breathawarenessrdquo BioPsychoSocial Medicine vol 5 article 4 2011

[7] L Jatiya KUdupa andA B Bhavanani ldquoEffect of yoga trainingon handgrip respiratory pressures and pulmonary functionrdquoIndian Journal of Physiology and Pharmacology vol 47 no 4pp 387ndash392 2003

[8] D Nangia and R Malhotra ldquoYoga cognition and mentalhealthrdquo Journal of the IndianAcademy ofApplied Psychology vol38 no 2 pp 262ndash269 2012

[9] S Telles and P Sarang ldquoEffects of two yoga based relaxationtechniques on Heart Rate Variability (HRV)rdquo InternationalJournal of Stress Management vol 13 no 4 pp 460ndash475 2006

[10] S Telles R Nagarathna P R Vani and H R Nagendra ldquoAcombination of focusing and defocusing through yoga reducesoptical illusion more than focusing alonerdquo Indian Journal ofPhysiology and Pharmacology vol 41 no 2 pp 179ndash182 1997

[11] K K F Rocha A M Ribeiro K C F Rocha et al ldquoImprove-ment in physiological and psychological parameters after6months of yoga practicerdquo Consciousness and Cognition vol 21no 2 pp 843ndash850 2012

[12] R Khadka B H Paudel V P Sharma S Kumar and N Bhat-tacharya ldquoEffect of yoga on cardiovascular autonomic reactivityin essential hypertensive patientsrdquo Health Renaissance vol 8no 2 pp 102ndash109 2010

[13] L C M Vanderlei C M Pastre R A Hoshi T D de Carvalhoand M F de Godoy ldquoBasic notions of heart rate variabilityand its clinical applicabilityrdquo Brazilian Journal of CardiovascularSurgery vol 24 no 2 pp 205ndash217 2009

[14] M V Hoslashjgaard N-H Holstein-Rathlou E Agner and JK Kanters ldquoDynamics of spectral components of heart ratevariability during changes in autonomic balancerdquoTheAmericanJournal of PhysiologymdashHeart and Circulatory Physiology vol275 no 1 pp H213ndashH219 1998

[15] S Boonnithi and S Phongsuphap ldquoComparison of heart ratevariability measures for mental stress detectionrdquo in Proceedingsof the Computing in Cardiology (CinC rsquo11) pp 85ndash88 2011

[16] H Kobayashi K Ishibashi and H Noguchi ldquoHeart ratevariability an index for monitoring and analyzing humanautonomic activitiesrdquo Journal of Physiological Anthropology andApplied Human Science vol 18 no 2 pp 53ndash59 1999

[17] J Sztajzel ldquoHeart rate variability a noninvasive electrocardio-graphic method to measure the autonomic nervous systemrdquoSwiss Medical Weekly vol 134 no 35-36 pp 514ndash522 2004

[18] J Taelman S Vandeput A Spaepen and S van Huffel ldquoInflu-ence of mental stress on heart rate and heart rate variabilityrdquo inProceedings of the 4th European Conference of the InternationalFederation for Medical and Biological Engineering (IFMBE rsquo08)vol 22 pp 1366ndash1369 November 2008

[19] E Tharion S Parthasarathy and N Neelakantan ldquoShort-termheart rate variability measures in students during examina-tionsrdquo National Medical Journal of India vol 22 no 2 pp 63ndash66 2009

[20] Y Sun N Ye and X Xu ldquoEEG analysis of alcoholics andcontrols based on feature extractionrdquo in Proceedings of the 8thInternational Conference on Signal Processing (ICSP rsquo06) 2006

[21] C Y Chen W K Wong C D Kuo Y T Liao and MD Ke ldquoWavelet real time monitoring system a case studyof the musical influence on electroencephalographyrdquo WSEASTransactions on Systems vol 7 no 2 pp 56ndash62 2008

[22] C Parameswariah and M Cox ldquoFrequency characteristics ofwaveletsrdquo IEEE Power Engineering Review vol 22 no 1 p 722002

[23] A Holm K Lukander J Korpela M Sallinen and K M IMuller ldquoEstimating brain load from the EEGrdquo The ScientificWorld Journal vol 9 pp 639ndash651 2009

[24] J Gruzelier ldquoA theory of alphatheta neurofeedback creativeperformance enhancement long distance functional connectiv-ity and psychological integrationrdquo Cognitive Processing vol 10no 1 supplement pp 101ndash109 2009

[25] F G Freeman P J Mikulka L J Prinzel and M W ScerboldquoEvaluation of an adaptive automation system using three EEGindices with a visual tracking taskrdquo Biological Psychology vol50 no 1 pp 61ndash76 1999

[26] A F Rabbi K Ivanca A V Putnam A Musa C B Thadenand R Fazel-Rezai ldquoHuman performance evaluation based onEEG signal analysis a prospective reviewrdquo in Proceedings of the31st Annual International Conference of the IEEE Engineeringin Medicine and Biology Society (EMBC rsquo09) pp 1879ndash1882September 2009

[27] A Gevins M E Smith LMcEvoy andD Yu ldquoHigh-resolutionEEGmapping of cortical activation related to workingmemoryeffects of task difficulty type of processing and practicerdquoCerebral Cortex vol 7 no 4 pp 374ndash385 1997

[28] J T Coyne C Baldwin A Cole C Sibley and D M RobertsldquoApplying real time physiological measures of cognitive load

Computational and Mathematical Methods in Medicine 13

to improve trainingrdquo in Foundations of Augmented CognitionNeuroergonomics and Operational Neuroscience vol 5638 ofLecture Notes in Computer Science pp 469ndash478 SpringerBerlin Germany 2009

[29] G Bashein M L Nessly S W Bledsoe et al ldquoElectroen-cephalography during surgery with cardiopulmonary bypassand hypothermiardquo Anesthesiology vol 76 no 6 pp 878ndash8911992

[30] R J Barry A R Clarke S J Johnstone R McCarthy andM Selikowitz ldquoElectroencephalogram 120572120573 ratio and arousal inattention-deficithyperactivity disorder evidence of indepen-dent processesrdquoBiological Psychiatry vol 66 no 4 pp 398ndash4012009

[31] L Cao J Li Y Sun H Zhu and C Yan ldquoEEG-based vig-ilance analysis by using fisher score and PCA algorithmrdquo inProceedings of the 1st IEEE International Conference on Progressin Informatics and Computing (PIC rsquo10) pp 175ndash179 ShanghaiChina December 2010

[32] L I Aftanas and S A Golocheikine ldquoNon-linear dynamiccomplexity of the humanEEGduringmeditationrdquoNeuroscienceLetters vol 330 no 2 pp 143ndash146 2002

[33] M Balasubramaniam S Telles and P M Doraiswamy ldquoYogaon our minds a systematic review of yoga for neuropsychiatricdisordersrdquo Frontiers in Psychiatry vol 3 Article ID Article 117pp 1ndash16 2013

[34] B S Moon H C Lee Y H Lee J C Park I S Oh and JW Lee ldquoFuzzy systems to process ECG and EEG signals forquantification of the mental workloadrdquo Information Sciencesvol 142 no 1ndash4 pp 23ndash35 2002

[35] P Raghuraj A G Ramakrishnan H R Nagendra and S TellesldquoEffect of two selected yogic breathing techniques on heart ratevariabilityrdquo Indian Journal of Physiology and Pharmacology vol42 no 4 pp 467ndash472 1998

[36] J J Sollers III T W Buchanan S M Mowrer L K Hill and JFThayer ldquoComparison of the ratio of the standard deviation ofthe r-r interval and the rootmean squared successive differences(SDrMSSD) to the low frequency-to-high frequency (LFHF)ratio in a patient population and normal healthy controlsrdquoBiomedical Sciences Instrumentation vol 43 pp 158ndash163 2007

[37] C Zhao C Zheng M Zhao and J Liu ldquoPhysiological assess-ment of driving mental fatigue using wavelet packet energy andrandom forestsrdquo The American Journal of Biomedical Sciencesvol 2 no 3 pp 262ndash274 2010

[38] O V Grishin V G Grishin D Yu Uryumtsev S V Smirnovand I G Jilina ldquoMetabolic rate variability impact on verylow-frequency of heart rate variabilityrdquo World Applied SciencesJournal vol 19 no 8 pp 1133ndash1139 2012

[39] E Basar C Basar-Eroglu S Karakas and M SchurmannldquoGamma alpha delta and theta oscillations govern cognitiveprocessesrdquo International Journal of Psychophysiology vol 39 no2-3 pp 241ndash248 2000

[40] K C Khare and S K Nigam ldquoA study of electroencephalogramin meditatorsrdquo Indian Journal of Physiology and Pharmacologyvol 44 no 2 pp 173ndash178 2000

[41] J Jacobs and M J Kahana ldquoDirect brain recordings fueladvances in cognitive electrophysiologyrdquo Trends in CognitiveSciences vol 14 no 4 pp 162ndash171 2010

Submit your manuscripts athttpwwwhindawicom

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MEDIATORSINFLAMMATION

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Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Behavioural Neurology

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Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Disease Markers

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

BioMed Research International

OncologyJournal of

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Oxidative Medicine and Cellular Longevity

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

PPAR Research

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Immunology ResearchHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal of

ObesityJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Computational and Mathematical Methods in Medicine

OphthalmologyJournal of

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Research and TreatmentAIDS

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Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Parkinsonrsquos Disease

Evidence-Based Complementary and Alternative Medicine

Volume 2014Hindawi Publishing Corporationhttpwwwhindawicom

6 Computational and Mathematical Methods in Medicine

ECG signal was recorded using five electrodes by con-necting to left and right wrinkles and left and right armsand one electrode at chest Before fixing the electrodes theywere cleaned and electrode gel was applied to reduce theskin resistance to get good quality of recording signal EEGsignal was recorded by fixing the CAP100C on the scalp ofthe subjects This cap was made of Lycra type fabric with20 reusable tin electrodes attached to it according to theinternational 10ndash20 norms Before fixing the cap on subjectsscalp the electrodes were cleaned with saline water andelectrode gel was appliedThismaintains the resistance below5 kΩ between the scalp and electrodes

All the data were collected during 6 pm to 730 pm atthe yoga centre of the temple premises in two stages Thedata collected at the beginning of the intervention period wasconsidered as the first stage during which five minutes ofbaseline ECG and EEG signals were recorded from subjectsof both experimental and control groups in sitting positionwith eyes closed The baseline signal was saved on the harddisk for offline processing

Both ECG and EEG signals were recorded with a sam-pling frequency of 512Hz to have better resolution of R-Rtime interval series and EEG activity

The experimental group practiced yoga for a period of fivemonths for 15 hr per day in the evening from 6 pm to 730pmThe control group was asked not to practice any form ofyogic practices or physical exercises during this period Theend of five months yoga training period was considered assecond stage During this stage again both ECG and EEGdata were collected from experimental and control groupfor a period of 10 minutes During recording subjects wereasked to minimize eye blinks and avoid body movements tominimize any artifacts that could be introduced If artifactswere introduced due to uncontrolled bodymovements or eyeblinks or due to technical reasons the recording time wasprolonged for a few more minutes The data was again savedon the hard disk for offline processing These data were usedfor the evaluation of various cognitive functions in terms ofphysiological parameters

Though maximum care was taken the recorded data wascontaminated with many artifacts Manual editing was per-formed for both ECG and EEG signalsThe RR intervals werethen extracted from the Acqknowledge 40 software whichuses modified Pan and Tompkins algorithm The intervalsless than 300ms and above 1200ms were eliminated fromtime series data set and were saved in text format for furtherprocessing using MATLAB 71 Any data whose standarddeviation was less than or equal to three times the standarddeviation was considered outliers and removed from the databefore determining the time domain parameters of heartrate variability (HRV) The artifact free data was segmentedinto five groups with 10 seconds segments each The averagevalue of each 10 seconds data was used in the analysis Theimportant time domainmeasures of HRV such asmeanHRVSDANN RMSSD and mean HR were computed

The frequency domain parameters namely VLF LFHF LF HF ratio and VHF were extracted from the FFTalgorithm The normalized values were computed by divid-ing the respective frequencies by total power minus VLF

4077

0092

6472

2048

0228

3820

0

1

2

3

4

5

6

7

8

Enga

gem

ent i

ndex

val

ue

Before yogaAfter yoga

(120575 + 120579)(120572 + 120573) 120573(120572 + 120579) (120575 + 120579)120572

Figure 3 CNS activity engagement index and executive load indexof yoga group before and after intervention

The normalization reduces the effect of LF and HF on totalpower In conformity with the task force recommendationThe artifact free signal of two minutes duration was used forcomputing frequency domain parameters

Hypotheses of the StudyHypothesis 1 There is no significant difference in physiolog-ical parameters (HR HRV) and cognitive functions of thesubjects of experimental group before and after yoga training(intervention)

Hypothesis 2 There is no significant difference in physio-logical parameters (HR HRV) and cognitive functions ofthe subjects of control group before and after yoga training(intervention)

3 Results and Discussion

Results are grouped in two parts firstly HRV analysis whichincludes time and frequency domain parameters secondlycognitive performance evaluation based on EEG engagementindices Both EEG and ECG signals reflect global arousal oralertness of the brain [34]

31 HRVAnalysis Theheart rate variability (HRV) is an indi-cator of cardiac ANS and HR is controlled by neural activity[35] The yogic exercise particularly pranayama (breathingtechniques) activatesANSThe yoga practicing group showedsignificant increase in HRV (119875 lt 00304) and reduction inresting HR (119875 lt 00389) The significant reduction in restingHR indicates a relaxed state of physiology and increasedmental alertness Depending on left or right cerebral hemi-spherical dominance there will be improvement in spatialor verbal skills The SDNN which reflects the total powersignificantly increased (119875lt00012)TheRMSSD an indicatorof parasympathetic activity also increased significantly (119875 lt00058) The ratio of SDNNRMSSD which is surrogate ofLFHF ratio [36] increased significantly (119875lt00039) LF was

Computational and Mathematical Methods in Medicine 7

Frontal Central Perietal Occipital Temporal Total0

5

10

15

20

25PS

D (120583

V2H

z)

(a) 120573 power

Frontal Central Perietal Occipital Temporal Total0

5

10

15

20

25

PSD

(120583V2H

z)

(b) 120572 power

0

20

40

60

80

100

120

Frontal Central Perietal Occipital Temporal Total

PSD

(120583V2H

z)

(c) 120579 power

0

5

10

15

20

25

Frontal Central Perietal Occipital Temporal Total

PSD

(mV2H

z)

(d) 120575 power

0

2

4

6

8

10

12

14

16

BeforeAfter

Frontal Central Perietal Occipital Temporal Total

PSD

(120583V2H

z)

(e) 120574 power

Figure 4 EEG band powers of control group in various lobes of the brain before and after intervention

significantly decreased (119875 lt 00002) while HF was increased(119875 lt 00003) The decrease of LF and increase of HF reflectsthe improvement in the dominance in the parasympatheticactivity A significant improvement in HRV may be dueto an increase in parasympathetic activity or a decrease insympathetic activity [35] These indirectly help in reducingthe psychological parameters such as distress anxiety anddepression in young healthy subjects

There was significant reduction in LF power (119875 lt 00002)whereas parasympathetic activity significantly increased (119875 lt00003) The LF powers indicate both sympathetic andparasympathetic modulation whereas HF power reflects

parasympathetic activation Hence reduction in sympatheticactivity and enhanced parasympathetic activity results indeceleration in the cardiac activity The ratio LFHF whichis an indicator of autonomic ANS balance between sym-pathetic and parasympathetic nervous system activity [37]was significantly decreased (119875 lt 00000) There is alwaysconstant interaction between sympathetic and parasympa-thetic activity to regulate heart rate variability The VLFincreased without significance in yoga group while there wassignificant increase in control group The VLF representsslow changes in the heart rate [38] but the exact functionof it is yet to be understood A significant reduction in

8 Computational and Mathematical Methods in Medicine

Table 5 Time and frequency domain parameters before and after intervention of yoga and control group

Parameters Yoga group Control groupBefore After 119875 value Before After 119875 value

mHRV (ms) 75721 plusmn 6537 81329 plusmn 7891 00304 87467 plusmn 9155 85572 plusmn 7048 02505mHR (bpm) 7979 plusmn 774 7457 plusmn 705 00389 6950 plusmn 943 7050 plusmn 622 02759SDNN (ms) 4443 plusmn 2176 5214 plusmn 2327 00012 5322 plusmn 2169 5383 plusmn 1951 09044RMSSD (ms) 3993 plusmn 2365 5521 plusmn 2278 00058 5483 plusmn 2946 49 plusmn 2789 01999SDNNRMSSD 077 plusmn 037 111 plusmn 057 00039 077 plusmn 037 121 plusmn 028 01336VLF (nu) 402 plusmn 096 1163 plusmn 983 00177 342 plusmn 991 1404 plusmn 1006 00007LF (nu) 12306 plusmn 2110 5685 plusmn 1016 00002 4514 plusmn 1309 4157 plusmn 1660 00000HF (nu) 2739 plusmn 844 4315 plusmn 1016 00003 4648 plusmn 461 220 plusmn 579 00269LFrelative 7133 plusmn 567 5116 plusmn 951 00000 4642 plusmn 1070 7081 plusmn 713 00000HFrelative 2739 plusmn 844 4315 plusmn 1016 00003 4648 plusmn 461 4220 plusmn 579 00269TP (nu) 17199 plusmn 2241 11163 plusmn 983 00000 9503 plusmn 1129 9781 plusmn 1244 00000LF HF 499 plusmn 198 1411 plusmn 045 00000 099 plusmn 032 355 plusmn 156 00000119875 gt 010 not significant 119875 lt 010marginal 119875 lt 005 fair 119875 lt 001 good 119875 lt 0001 excellent difference 119875 lt 005 is considered significant level and for anyvalue less than this the null hypothesis is rejected 119905stat gt 119905valu for the null hypothesis to be rejected If 119875 = 005 there is 5 chance of no real difference

total power was observed in yoga group This might be dueto significant decrease of sympathetic activity compared tosignificant increase of parasympathetic activity The VHFpower generally reflects part of noise component and doesnot possess clinically significant information

Control group showed significant increase of LF power(119875 lt 00000) decreased HF power (119875 lt 0029) increasedLFHF ratio (119875 lt 00000) and increased VLF power But nosignificant changes were observed in time domain parame-ters

The LF and HF band power of HRV are expressed innormalized units The representation of these frequencyband powers in normalized units articulates the degree ofcontrol exercised and the relative balance of two limbs ofthe autonomic nervous system [35]Moreover normalized LFpower is thought to represent the sympathetic modulation asopposed to absolute units Since theHRV spectral parametersare computed by the autonomic nervous system (ANS) mea-surement of HRV may have greater application in assessingautonomic statues

Studentrsquos paired 119905-test was performed on set of pre- andpostintervention data samples to investigate whether therewas any real difference between them Each 119905 value has acorresponding 119875 value The 119875 value which is the probabilitythat the pattern of data samples in the sample could beproduced by random data provides the information aboutthe likelihood that there is a real difference in the data patternThis significant difference in the data set could be due to theeffect of particular training or an intervention given to thesubjects

The various time and frequency domain parameters ofboth yoga and control group are shown in Table 5 Anyvariations in these parameters could be due to relative age dif-ferences between yoga and control groups or methodologicaldifferences or limited number of samples in the study

The decrease in HR could be due to combined effect ofelements of yoga The reduction in stress after yoga couldbe other possible reason for improved HRV in this study

The previous researches suggest that yoga practice resultsin neurophysiological balance by lowering level of cholin-esterase and catecholamines Further this result increasedparasympathetic and decreased sympathetic activity Theresults of this study are in concurrence with previous studies[6 9 35] These studies indicated reduced sympatheticactivity and enhanced parasympathetic activity after yoga

32 Cognitive Performance Analysis The regular practice ofyoga for a period of fivemonths by young healthy engineeringstudents resulted in the increase of 120572 120573 and 120575 EEG bandpowers and decrease in the 120579 and 120574 band powers Theincreased 120573 band power indicate enhancement in certaincognitive functions such as alertness while increased 120572and decreased 120575 reflect enhanced vigilance level indicatingincreased alertnessThus the increase of high frequency bandpowers (120572 120573) and decrease of low frequency band powers (120575120579) are associated with enhancement in certain cognitive skillssuch as memory and visual information processing

The various cognitive behavior parameters have beenevaluated based on various EEG indices such as 120579120572 120573120572120573120579 (120575 + 120579)120572 120573(120572 + 120579) and (120575 + 120579)(120572 + 120573) Increasein 120573 band power indicates a higher level of alertness andenhanced engagement task and enhancement in variouscognitive abilities The increased band powers of 120572 and 120579indicate decreased alertness reduced engagement task andgood information processing capabilities [25] The 120575 and 120582activity are used for analysis of many cognitive processes[39]The ratio 120573120579which is representative of improvement incognitive skills increasedThe heart rate index 120579120572 decreasedperformance enhancement index 120572120579 increased attentionresource index 120573(120572 + 120579) significantly increased executiveload index (120575 + 120579)120572 decreased and ratio (120575 + 120579)(120572 + 120573)decreased The 120572 120573 and 120575 band power increased in frontalcentral parietal occipital and temporal lobes The 120579 bandpower was increased only in occipital lobe while 120574 bandpower in frontal and slightly in temporal lobes As the frontallobe is associated with reasoning planning problem solving

Computational and Mathematical Methods in Medicine 9

Table 6 Mean powers of EEG frequency bands averaged across all the lobes of the brain before and after yoga intervention

EEG band powers120574 (120583V2Hz) 120573 (120583V2Hz) 120572 (120583V2Hz) 120579 (120583V2Hz) 120575 (120583V2Hz)

Yoga groupBefore yoga 380 plusmn 093 232 plusmn 049 395 plusmn 070 2136 plusmn 343 422 plusmn 042After yoga 365 plusmn 069 491 plusmn 163 567 plusmn 168 1588 plusmn 257 579 plusmn 106

Control groupBefore yoga 298 plusmn 136 386 plusmn 096 392 plusmn 097 1757 plusmn 254 446 plusmn 089After yoga 294 plusmn 133 372 plusmn 082 387 plusmn 090 2112 plusmn 387 437 plusmn 078

and cognition parietal lobe with visual perception recogni-tion information processing and spatial reasoning temporallobe with memory and processing of verbal and auditorysignals and occipital lobe with visual spatial processing andrecognition An increase of EEG frequency band powers inthese lobes indicates the enhancement of certain type ofcognitive skillsThe type of the cognitive skills developed canbe assessed based on increased or decreased EEG band powerin these lobesThemean absolute values of these band powersin various lobes of the brain are shown in Table 6

The increase of frontal 120579 band power indicates intellectualconcentration andmeditative state of relief from nervousnessand is negatively related with sympathetic activation Thisreflects a near relationship between autonomic functionactivity of medial frontal neural circuitry and probability ofcontrolling central nervous system (CNS) functions owing toyoga practice and meditation [12] 120572 waves are indicative ofincreased relaxed state ofmind and its bandpower is inverselyrelated to mental activity Yoga enhanced various cognitiveskills improved sense of wellbeing and responsiveness andenhanced cognitive functions as substantiated by increased120572 and 120573 band powers and various engagement indices Italso improves mental consciousness and achieves reductionin stress and strain and thus advocates complete health andwellbeing in an individual [40] Increase in 120573 band powerwould indicate a higher level of alertness and enhancedengagement task whereas increased band powers of 120572 and 120579would indicate decreased alertness and reduced engagementtask [25] The increase of 120573 power reflects improvement ofcertain cognitive functions such as memory and reactiontime That of 120572 and 120575 indicates synchronization of brainactivity The total EEG band power also increased in yogagroup compared to the control group

The ratio 120579120572 is associated with HR This ratio decreasedin all lobes of the brain indicating the relaxed state of sub-jectsThis reduction could be either increase of 120572 band poweror decrease of 120579 band power Since 120572 power increased in yogagroup this ratio decreased indicating enhancement of certaincognitive faculties (memory attention) and improvement inthe HRV These in turn indicate indirect improvement incertain cognitive functions such as reaction time The ratio120573120572 [25] is called arousal indexThis indicates level of arousalbased on interbeat intervals (IBI) activity Arousal level gt0indicates higher than normal arousal and lt0 indicates lowerthan normal arousal

This ratio increased (4711) in yoga group whiledecreased in control group (243) The increases of thisratio indicate enhanced cognitive functions such as attentionThe decreases of this ratio reflect reduction in the corecapabilities of cognitive functions This ratio increased in alllobes of the brain but the maximum increase was observedin parietal (7805) central (5312) and temporal (4504)lobes It increased to (3824) and (1976) in frontal andoccipital lobes respectively The ratio (120575 + 120579)120572 is calledexecutive load index [28] and is a measure of executive loador comprehension Positive value indicates increased loadand negative value indicates decreased load It reflects theoscillations in precise cortical network active among spatiallydisjoint brain compartment This ratio decreased (4098)in experimental group while it increased (1719) slightlyin control group The decrease in this ratio may be dueto increase in 120572 band power or reduced band power ofeither 120575 or 120579 or both It is observed that 120572 band power wasincreased in yoga practicing group This ratio was also founddecreased in all the lobes of the brain Another importantparameter 120579(fro)120572(par) [27] is called task load index Thisratio decreases in experimental group while it increases incontrol group It is evident from the relation that the ratiodecreases due to increase in 120572 band power These results areshown in Tables 7 and 8

The ratio 120579120573 indicates central nervous system (CNS)arousal [30] and increased ratio is marker of under arousalThis ratio decreased in yoga group The reductions in thisratio reflect the shift of 120572 and 120579 activity towards 120573 activityThe increased 120573 band powers indicate enhanced cognitiveperformance such as memory attention and concentrationThe ratio 120572120575 which is called ldquobrain perfusionrdquo index [29]was increased (46) in yoga practiced group This indicatessufficient amount of blood flow to the different parts ofthe brain among yoga group These in turn enhances thebetter functioning of the brain The ratio LFHF can beexpressed in terms of (120579 + 120575)(120572 + 120573) [29] Slower brainoscillations (120579 and 120575) harmonize considerable neuron groupsacross larger brain areas and faster oscillations (120572 and 120573)synchronize smaller focused neuronal assemblies [41]Whengroups of neurons oscillate together synchronously theymore effectively communicated with each other The index(120579 + 120575)(120572 + 120573) indicates sympathovagal balance of theautonomic nervous system (ANS) Lower ratios indicatebetter balance of ANSThis ratio decreased in yoga group but

10 Computational and Mathematical Methods in Medicine

Table 7 Cognitive index parameters of yoga group before and after yoga intervention Postintervention values are shown within theparenthesis

EEG indices Yoga groupFrontal Central Parietal Occipital Temporal

120579120572 4621 (2806) 4951 (2063) 5059 (2973) 8792 (4609) 4604 (2480)120572120579 0216 (0356) 0202 (0485) 0198 (0336) 0114 (0217) 0217 (0403)120573120572 0612 (0846) 0625 (0957) 0523 (0931) 0607 (0727) 0564 (0818)120573120579 0132 (0302) 0126 (0464) 0103 (0313) 0069 (0158) 0123 (0330)120573(120572 + 120579) 0109 (0222) 0105 (0312) 0086 (0234) 0062 (0130) 0101 (0235)120579(fro)120572(par) 4621 (2806) 4951 (2063) 5059 (2973) 8792 (4609) 4604 (2480)(120575 + 120579)120572 5590 (3926) 5964 (3200) 6168 (3961) 10112 (5907) 5614 (3243)sum(120575 + 120579)120572 = 46392 (27876)

Table 8 Global EEG band power ratios before and after yoga inter-vention

EEG indices Yoga group Control groupBefore yoga After yoga Before yoga After yoga

120579120572 5405 2800 4485 5460120572120579 0185 0357 0228 0183120573120572 0588 0865 0986 0962120573120579 0109 0309 0220 0176120573(120572 + 120579) 0092 0228 0180 0149120579(fro)120572(par) 5405 2800 4485 5460(120575 + 120579)120572 6472 3820 5623 6590sum(120575 + 120579)120572 46392 27876 40456 47080

Table 9 EEG indices and their values before and after yoga inter-vention

Parameters Yoga group ControlBefore After Before After

120572120575 0937 0980 0879 0885(120579 + 120575)(120572 + 120573) 408 205 332 289120572120573 170 116 10139 10394120575120579 0197 0364 0209 2488120579120573 9198 3235 5530 4721

did not change in control group The ratio 120572120573 [31] which iscalled desynchronization is used to analyze vigilance indexand 120575120579 is called synchronization The ratio 120572120573 decreasedwhich is desirable The increase 120573 of band power indicatesimproved cognitive performance Since the parameter is indenominator the ratio decreases when there is increasedcognitive performance However in control group this ratiowas slightly increased Another ratio 120575120579 was increasedrelatively by small amount in experimental group than thecontrol groupThe 120572120575 ratio was decreased in frontal centraland occipital lobes while it increased in parietal and temporallobes These results are shown in Tables 9 10 and 11

The relative EEG band powers of 120573 120572 and 120575 increasedin yoga group in all the lobes of the brain The increases ofthese band powers indicate improvement of certain cognitivefunctions such as memory attention executive functionsand concentration The increase of 120575 power and decrease of

1932 1958

8783

222914911860 1618

10558

21181189

0

20

40

60

80

100

120

PSD

(120583V2H

z)

BeforeAfter

120573 120572 120579 120575 120574

Figure 5 Global EEG band powers of control group before andafter intervention

120579 power indicate improvement in neural activityThe variousEEG band powers are shown in Figure 1

The total band power (global) of 120573 120572 and 120575 increasedamong yoga group The increased 120573 power was associatedwith enhanced cognitive performance such as improvedalertness The maximum 120573 power increased in frontal andcentral lobes of the brain This indicates the improvementin emotion process and cognition The increased 120572 anddecreased 120579 powers physiologically signify the enhancedvigilance and increased alertness level of subjects These areshown in Figure 2 The improvement in cognitive functionswas associated with increased power in high frequency band(120573) and reduction in low frequency band (120579) Therefore 120573120579ratio is suitable index to assess the improvement in cognitiveskills of the subjectsThe cognitive performance index 120573(120572 +120579) increased and ratio of sum of low frequency to sum of highfrequency (120579 + 120575)(120573 + 120572) was decreased among yoga groupwhich is shown in Figure 3

There were no significant changes in EEG band powersengagement indices total power and cognitive performancesindices among control group The various performancesparameters of control group are shown in Figures 4 5 6 and7

Computational and Mathematical Methods in Medicine 11

Table 10 EEG index values of yoga group in different lobes of the brain before and after yoga intervention Postintervention values are shownin parenthesis

Parameters Brain lobesFrontal Central Parietal Occipital Temporal

120572120575 1032 (0893) 0988 (0879) 0902 (1011) 0757 (0770) 0990 (1312)(120579 + 120575)(120572 + 120573) 3468 (0534) 3669 (0566) 4050 (0402) 6294 (0363) 3589 (0363)120572120573 1634 (2806) 1599 (2063) 1913 (2973) 1648 (4609) 1772 (2480)120575120579 0210 (0814) 0205 (0524) 0219 (0614) 0150 (0570) 0219 (0657)120579120573 7550 (3316) 7916 (2156) 9675 (3194) 14492 (6341) 8159 (3032)

Table 11 EEG index values of control group in different lobes of the brain before and after yoga intervention Postintervention values areshown in parenthesis

Parameters Brain lobesFrontal Central Parietal Occipital Temporal

120572120575 0914 (0944) 0940 (0940) 0760 (0760) 0825 (0825) 0930 (0931)(120579 + 120575)(120572 + 120573) 0424 (0356) 0326 (0261) 0271 (0241) 0262 (0218) 0486 (0438)120572120573 3428 (4186) 3711 (4891) 6412 (7311) 5513 (6817) 4385 (4970)120575120579 0716 (0741) 0445 (0445) 0524 (0523) 0409 (0409) 1433 (1433)120579120573 3269 (4185) 3958 (5251) 5747 (6647) 6633 (8531) 4235 (4839)

After yogaBefore yoga

736686

586694

576

737 776

585

752

571

0

1

2

3

4

5

6

7

8

9

Frontal Central Perietal Occipital Temporal

PSD

(120583V2H

z)

Figure 6 Global EEGband powers of control group in various lobesof the brain before and after intervention

4 Conclusions

The regular practices of yoga for a period of five months byyoung healthy engineering students enhance different typesof cognitive skills Apart from cognitive the yoga practiceresulted in many health benefits such as improvement inheart rate variability The ratio SDNNRMSSD increasedwhile the ratio LFHF decreasedThis indicates improvementin the parasympathetic activity and decrease in sympatheticactivity Hence the current results suggest that the practice ofyoga modifies the sympathovagal balance towards parasym-pathetic activation improved the heart rate variability andenhanced sense of wellbeing Since the study population isyoung healthy engineering graduates it would be interestingto investigate whether the yoga practice could result inimprovement in the academic performances

3319

0153

6593

2891

0174

5672

0

1

2

3

4

5

6

7

8

Enga

gem

ent i

ndex

val

ue

Before yogaAfter yoga

(120575 + 120579)(120572 + 120573) 120573(120572 + 120579) (120575 + 120579)120572

Figure 7 CNS activity engagement index and executive load indexof control group before and after intervention

In a nutshell it is proved beyond doubt that yogapractices resulted in effective improvements in physiologicalparameters indirectly improving psychological parametersand various cognitive functions The results of this studygreatly encourage further investigation to study whether thepractice of yoga could also enhance academic performance

Limitations of the Study

Limitations of this study include small number of samplesand lack of dedicated control group and methodologicaldifferences Further investigation can be done by employingpsychological tests to evaluate cognitive behavior

12 Computational and Mathematical Methods in Medicine

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

The authors acknowledge the Principal of PDA College ofEngineering Kalaburagi for deputingHNagendra to pursuePhD degree and Department of Electrical EngineeringIIT Roorkee for providing an opportunity under QualityImprovement Programme (QIP) They also acknowledge thestudents who participated in this study and give specialthanks to the yoga instructor

References

[1] P Sengupta ldquoHealth impacts of yoga and pranayama a state-of-the-art reviewrdquo International Journal of Preventive Medicinevol 3 no 7 pp 444ndash458 2012

[2] A Ross and S Thomas ldquoThe health benefits of yoga and exer-cise a review of comparison studiesrdquoThe Journal of Alternativeand Complementary Medicine vol 16 no 1 pp 3ndash12 2010

[3] P A Balaji S R Varne and S S Ali ldquoPhysiological effects ofyogic practices and transcendental meditation in health anddiseaserdquo North American Journal of Medical Sciences vol 4 no10 pp 442ndash448 2012

[4] A Bussing A Michalsen S B S Khalsa S Telles and K JSherman ldquoEffects of yoga on mental and physical health ashort summary of reviewsrdquo Evidence-based Complementary andAlternative Medicine vol 2012 Article ID 165410 7 pages 2012

[5] T N Sathyaprabha P Satishchandra C Pradhan et al ldquoModu-lation of cardiac autonomic balance with adjuvant yoga therapyin patients with refractory epilepsyrdquo Epilepsy and Behavior vol12 no 2 pp 245ndash252 2008

[6] S Telles N Singh and A Balkrishna ldquoHeart rate variabil-ity changes during high frequency yoga breathingand breathawarenessrdquo BioPsychoSocial Medicine vol 5 article 4 2011

[7] L Jatiya KUdupa andA B Bhavanani ldquoEffect of yoga trainingon handgrip respiratory pressures and pulmonary functionrdquoIndian Journal of Physiology and Pharmacology vol 47 no 4pp 387ndash392 2003

[8] D Nangia and R Malhotra ldquoYoga cognition and mentalhealthrdquo Journal of the IndianAcademy ofApplied Psychology vol38 no 2 pp 262ndash269 2012

[9] S Telles and P Sarang ldquoEffects of two yoga based relaxationtechniques on Heart Rate Variability (HRV)rdquo InternationalJournal of Stress Management vol 13 no 4 pp 460ndash475 2006

[10] S Telles R Nagarathna P R Vani and H R Nagendra ldquoAcombination of focusing and defocusing through yoga reducesoptical illusion more than focusing alonerdquo Indian Journal ofPhysiology and Pharmacology vol 41 no 2 pp 179ndash182 1997

[11] K K F Rocha A M Ribeiro K C F Rocha et al ldquoImprove-ment in physiological and psychological parameters after6months of yoga practicerdquo Consciousness and Cognition vol 21no 2 pp 843ndash850 2012

[12] R Khadka B H Paudel V P Sharma S Kumar and N Bhat-tacharya ldquoEffect of yoga on cardiovascular autonomic reactivityin essential hypertensive patientsrdquo Health Renaissance vol 8no 2 pp 102ndash109 2010

[13] L C M Vanderlei C M Pastre R A Hoshi T D de Carvalhoand M F de Godoy ldquoBasic notions of heart rate variabilityand its clinical applicabilityrdquo Brazilian Journal of CardiovascularSurgery vol 24 no 2 pp 205ndash217 2009

[14] M V Hoslashjgaard N-H Holstein-Rathlou E Agner and JK Kanters ldquoDynamics of spectral components of heart ratevariability during changes in autonomic balancerdquoTheAmericanJournal of PhysiologymdashHeart and Circulatory Physiology vol275 no 1 pp H213ndashH219 1998

[15] S Boonnithi and S Phongsuphap ldquoComparison of heart ratevariability measures for mental stress detectionrdquo in Proceedingsof the Computing in Cardiology (CinC rsquo11) pp 85ndash88 2011

[16] H Kobayashi K Ishibashi and H Noguchi ldquoHeart ratevariability an index for monitoring and analyzing humanautonomic activitiesrdquo Journal of Physiological Anthropology andApplied Human Science vol 18 no 2 pp 53ndash59 1999

[17] J Sztajzel ldquoHeart rate variability a noninvasive electrocardio-graphic method to measure the autonomic nervous systemrdquoSwiss Medical Weekly vol 134 no 35-36 pp 514ndash522 2004

[18] J Taelman S Vandeput A Spaepen and S van Huffel ldquoInflu-ence of mental stress on heart rate and heart rate variabilityrdquo inProceedings of the 4th European Conference of the InternationalFederation for Medical and Biological Engineering (IFMBE rsquo08)vol 22 pp 1366ndash1369 November 2008

[19] E Tharion S Parthasarathy and N Neelakantan ldquoShort-termheart rate variability measures in students during examina-tionsrdquo National Medical Journal of India vol 22 no 2 pp 63ndash66 2009

[20] Y Sun N Ye and X Xu ldquoEEG analysis of alcoholics andcontrols based on feature extractionrdquo in Proceedings of the 8thInternational Conference on Signal Processing (ICSP rsquo06) 2006

[21] C Y Chen W K Wong C D Kuo Y T Liao and MD Ke ldquoWavelet real time monitoring system a case studyof the musical influence on electroencephalographyrdquo WSEASTransactions on Systems vol 7 no 2 pp 56ndash62 2008

[22] C Parameswariah and M Cox ldquoFrequency characteristics ofwaveletsrdquo IEEE Power Engineering Review vol 22 no 1 p 722002

[23] A Holm K Lukander J Korpela M Sallinen and K M IMuller ldquoEstimating brain load from the EEGrdquo The ScientificWorld Journal vol 9 pp 639ndash651 2009

[24] J Gruzelier ldquoA theory of alphatheta neurofeedback creativeperformance enhancement long distance functional connectiv-ity and psychological integrationrdquo Cognitive Processing vol 10no 1 supplement pp 101ndash109 2009

[25] F G Freeman P J Mikulka L J Prinzel and M W ScerboldquoEvaluation of an adaptive automation system using three EEGindices with a visual tracking taskrdquo Biological Psychology vol50 no 1 pp 61ndash76 1999

[26] A F Rabbi K Ivanca A V Putnam A Musa C B Thadenand R Fazel-Rezai ldquoHuman performance evaluation based onEEG signal analysis a prospective reviewrdquo in Proceedings of the31st Annual International Conference of the IEEE Engineeringin Medicine and Biology Society (EMBC rsquo09) pp 1879ndash1882September 2009

[27] A Gevins M E Smith LMcEvoy andD Yu ldquoHigh-resolutionEEGmapping of cortical activation related to workingmemoryeffects of task difficulty type of processing and practicerdquoCerebral Cortex vol 7 no 4 pp 374ndash385 1997

[28] J T Coyne C Baldwin A Cole C Sibley and D M RobertsldquoApplying real time physiological measures of cognitive load

Computational and Mathematical Methods in Medicine 13

to improve trainingrdquo in Foundations of Augmented CognitionNeuroergonomics and Operational Neuroscience vol 5638 ofLecture Notes in Computer Science pp 469ndash478 SpringerBerlin Germany 2009

[29] G Bashein M L Nessly S W Bledsoe et al ldquoElectroen-cephalography during surgery with cardiopulmonary bypassand hypothermiardquo Anesthesiology vol 76 no 6 pp 878ndash8911992

[30] R J Barry A R Clarke S J Johnstone R McCarthy andM Selikowitz ldquoElectroencephalogram 120572120573 ratio and arousal inattention-deficithyperactivity disorder evidence of indepen-dent processesrdquoBiological Psychiatry vol 66 no 4 pp 398ndash4012009

[31] L Cao J Li Y Sun H Zhu and C Yan ldquoEEG-based vig-ilance analysis by using fisher score and PCA algorithmrdquo inProceedings of the 1st IEEE International Conference on Progressin Informatics and Computing (PIC rsquo10) pp 175ndash179 ShanghaiChina December 2010

[32] L I Aftanas and S A Golocheikine ldquoNon-linear dynamiccomplexity of the humanEEGduringmeditationrdquoNeuroscienceLetters vol 330 no 2 pp 143ndash146 2002

[33] M Balasubramaniam S Telles and P M Doraiswamy ldquoYogaon our minds a systematic review of yoga for neuropsychiatricdisordersrdquo Frontiers in Psychiatry vol 3 Article ID Article 117pp 1ndash16 2013

[34] B S Moon H C Lee Y H Lee J C Park I S Oh and JW Lee ldquoFuzzy systems to process ECG and EEG signals forquantification of the mental workloadrdquo Information Sciencesvol 142 no 1ndash4 pp 23ndash35 2002

[35] P Raghuraj A G Ramakrishnan H R Nagendra and S TellesldquoEffect of two selected yogic breathing techniques on heart ratevariabilityrdquo Indian Journal of Physiology and Pharmacology vol42 no 4 pp 467ndash472 1998

[36] J J Sollers III T W Buchanan S M Mowrer L K Hill and JFThayer ldquoComparison of the ratio of the standard deviation ofthe r-r interval and the rootmean squared successive differences(SDrMSSD) to the low frequency-to-high frequency (LFHF)ratio in a patient population and normal healthy controlsrdquoBiomedical Sciences Instrumentation vol 43 pp 158ndash163 2007

[37] C Zhao C Zheng M Zhao and J Liu ldquoPhysiological assess-ment of driving mental fatigue using wavelet packet energy andrandom forestsrdquo The American Journal of Biomedical Sciencesvol 2 no 3 pp 262ndash274 2010

[38] O V Grishin V G Grishin D Yu Uryumtsev S V Smirnovand I G Jilina ldquoMetabolic rate variability impact on verylow-frequency of heart rate variabilityrdquo World Applied SciencesJournal vol 19 no 8 pp 1133ndash1139 2012

[39] E Basar C Basar-Eroglu S Karakas and M SchurmannldquoGamma alpha delta and theta oscillations govern cognitiveprocessesrdquo International Journal of Psychophysiology vol 39 no2-3 pp 241ndash248 2000

[40] K C Khare and S K Nigam ldquoA study of electroencephalogramin meditatorsrdquo Indian Journal of Physiology and Pharmacologyvol 44 no 2 pp 173ndash178 2000

[41] J Jacobs and M J Kahana ldquoDirect brain recordings fueladvances in cognitive electrophysiologyrdquo Trends in CognitiveSciences vol 14 no 4 pp 162ndash171 2010

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Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Parkinsonrsquos Disease

Evidence-Based Complementary and Alternative Medicine

Volume 2014Hindawi Publishing Corporationhttpwwwhindawicom

Computational and Mathematical Methods in Medicine 7

Frontal Central Perietal Occipital Temporal Total0

5

10

15

20

25PS

D (120583

V2H

z)

(a) 120573 power

Frontal Central Perietal Occipital Temporal Total0

5

10

15

20

25

PSD

(120583V2H

z)

(b) 120572 power

0

20

40

60

80

100

120

Frontal Central Perietal Occipital Temporal Total

PSD

(120583V2H

z)

(c) 120579 power

0

5

10

15

20

25

Frontal Central Perietal Occipital Temporal Total

PSD

(mV2H

z)

(d) 120575 power

0

2

4

6

8

10

12

14

16

BeforeAfter

Frontal Central Perietal Occipital Temporal Total

PSD

(120583V2H

z)

(e) 120574 power

Figure 4 EEG band powers of control group in various lobes of the brain before and after intervention

significantly decreased (119875 lt 00002) while HF was increased(119875 lt 00003) The decrease of LF and increase of HF reflectsthe improvement in the dominance in the parasympatheticactivity A significant improvement in HRV may be dueto an increase in parasympathetic activity or a decrease insympathetic activity [35] These indirectly help in reducingthe psychological parameters such as distress anxiety anddepression in young healthy subjects

There was significant reduction in LF power (119875 lt 00002)whereas parasympathetic activity significantly increased (119875 lt00003) The LF powers indicate both sympathetic andparasympathetic modulation whereas HF power reflects

parasympathetic activation Hence reduction in sympatheticactivity and enhanced parasympathetic activity results indeceleration in the cardiac activity The ratio LFHF whichis an indicator of autonomic ANS balance between sym-pathetic and parasympathetic nervous system activity [37]was significantly decreased (119875 lt 00000) There is alwaysconstant interaction between sympathetic and parasympa-thetic activity to regulate heart rate variability The VLFincreased without significance in yoga group while there wassignificant increase in control group The VLF representsslow changes in the heart rate [38] but the exact functionof it is yet to be understood A significant reduction in

8 Computational and Mathematical Methods in Medicine

Table 5 Time and frequency domain parameters before and after intervention of yoga and control group

Parameters Yoga group Control groupBefore After 119875 value Before After 119875 value

mHRV (ms) 75721 plusmn 6537 81329 plusmn 7891 00304 87467 plusmn 9155 85572 plusmn 7048 02505mHR (bpm) 7979 plusmn 774 7457 plusmn 705 00389 6950 plusmn 943 7050 plusmn 622 02759SDNN (ms) 4443 plusmn 2176 5214 plusmn 2327 00012 5322 plusmn 2169 5383 plusmn 1951 09044RMSSD (ms) 3993 plusmn 2365 5521 plusmn 2278 00058 5483 plusmn 2946 49 plusmn 2789 01999SDNNRMSSD 077 plusmn 037 111 plusmn 057 00039 077 plusmn 037 121 plusmn 028 01336VLF (nu) 402 plusmn 096 1163 plusmn 983 00177 342 plusmn 991 1404 plusmn 1006 00007LF (nu) 12306 plusmn 2110 5685 plusmn 1016 00002 4514 plusmn 1309 4157 plusmn 1660 00000HF (nu) 2739 plusmn 844 4315 plusmn 1016 00003 4648 plusmn 461 220 plusmn 579 00269LFrelative 7133 plusmn 567 5116 plusmn 951 00000 4642 plusmn 1070 7081 plusmn 713 00000HFrelative 2739 plusmn 844 4315 plusmn 1016 00003 4648 plusmn 461 4220 plusmn 579 00269TP (nu) 17199 plusmn 2241 11163 plusmn 983 00000 9503 plusmn 1129 9781 plusmn 1244 00000LF HF 499 plusmn 198 1411 plusmn 045 00000 099 plusmn 032 355 plusmn 156 00000119875 gt 010 not significant 119875 lt 010marginal 119875 lt 005 fair 119875 lt 001 good 119875 lt 0001 excellent difference 119875 lt 005 is considered significant level and for anyvalue less than this the null hypothesis is rejected 119905stat gt 119905valu for the null hypothesis to be rejected If 119875 = 005 there is 5 chance of no real difference

total power was observed in yoga group This might be dueto significant decrease of sympathetic activity compared tosignificant increase of parasympathetic activity The VHFpower generally reflects part of noise component and doesnot possess clinically significant information

Control group showed significant increase of LF power(119875 lt 00000) decreased HF power (119875 lt 0029) increasedLFHF ratio (119875 lt 00000) and increased VLF power But nosignificant changes were observed in time domain parame-ters

The LF and HF band power of HRV are expressed innormalized units The representation of these frequencyband powers in normalized units articulates the degree ofcontrol exercised and the relative balance of two limbs ofthe autonomic nervous system [35]Moreover normalized LFpower is thought to represent the sympathetic modulation asopposed to absolute units Since theHRV spectral parametersare computed by the autonomic nervous system (ANS) mea-surement of HRV may have greater application in assessingautonomic statues

Studentrsquos paired 119905-test was performed on set of pre- andpostintervention data samples to investigate whether therewas any real difference between them Each 119905 value has acorresponding 119875 value The 119875 value which is the probabilitythat the pattern of data samples in the sample could beproduced by random data provides the information aboutthe likelihood that there is a real difference in the data patternThis significant difference in the data set could be due to theeffect of particular training or an intervention given to thesubjects

The various time and frequency domain parameters ofboth yoga and control group are shown in Table 5 Anyvariations in these parameters could be due to relative age dif-ferences between yoga and control groups or methodologicaldifferences or limited number of samples in the study

The decrease in HR could be due to combined effect ofelements of yoga The reduction in stress after yoga couldbe other possible reason for improved HRV in this study

The previous researches suggest that yoga practice resultsin neurophysiological balance by lowering level of cholin-esterase and catecholamines Further this result increasedparasympathetic and decreased sympathetic activity Theresults of this study are in concurrence with previous studies[6 9 35] These studies indicated reduced sympatheticactivity and enhanced parasympathetic activity after yoga

32 Cognitive Performance Analysis The regular practice ofyoga for a period of fivemonths by young healthy engineeringstudents resulted in the increase of 120572 120573 and 120575 EEG bandpowers and decrease in the 120579 and 120574 band powers Theincreased 120573 band power indicate enhancement in certaincognitive functions such as alertness while increased 120572and decreased 120575 reflect enhanced vigilance level indicatingincreased alertnessThus the increase of high frequency bandpowers (120572 120573) and decrease of low frequency band powers (120575120579) are associated with enhancement in certain cognitive skillssuch as memory and visual information processing

The various cognitive behavior parameters have beenevaluated based on various EEG indices such as 120579120572 120573120572120573120579 (120575 + 120579)120572 120573(120572 + 120579) and (120575 + 120579)(120572 + 120573) Increasein 120573 band power indicates a higher level of alertness andenhanced engagement task and enhancement in variouscognitive abilities The increased band powers of 120572 and 120579indicate decreased alertness reduced engagement task andgood information processing capabilities [25] The 120575 and 120582activity are used for analysis of many cognitive processes[39]The ratio 120573120579which is representative of improvement incognitive skills increasedThe heart rate index 120579120572 decreasedperformance enhancement index 120572120579 increased attentionresource index 120573(120572 + 120579) significantly increased executiveload index (120575 + 120579)120572 decreased and ratio (120575 + 120579)(120572 + 120573)decreased The 120572 120573 and 120575 band power increased in frontalcentral parietal occipital and temporal lobes The 120579 bandpower was increased only in occipital lobe while 120574 bandpower in frontal and slightly in temporal lobes As the frontallobe is associated with reasoning planning problem solving

Computational and Mathematical Methods in Medicine 9

Table 6 Mean powers of EEG frequency bands averaged across all the lobes of the brain before and after yoga intervention

EEG band powers120574 (120583V2Hz) 120573 (120583V2Hz) 120572 (120583V2Hz) 120579 (120583V2Hz) 120575 (120583V2Hz)

Yoga groupBefore yoga 380 plusmn 093 232 plusmn 049 395 plusmn 070 2136 plusmn 343 422 plusmn 042After yoga 365 plusmn 069 491 plusmn 163 567 plusmn 168 1588 plusmn 257 579 plusmn 106

Control groupBefore yoga 298 plusmn 136 386 plusmn 096 392 plusmn 097 1757 plusmn 254 446 plusmn 089After yoga 294 plusmn 133 372 plusmn 082 387 plusmn 090 2112 plusmn 387 437 plusmn 078

and cognition parietal lobe with visual perception recogni-tion information processing and spatial reasoning temporallobe with memory and processing of verbal and auditorysignals and occipital lobe with visual spatial processing andrecognition An increase of EEG frequency band powers inthese lobes indicates the enhancement of certain type ofcognitive skillsThe type of the cognitive skills developed canbe assessed based on increased or decreased EEG band powerin these lobesThemean absolute values of these band powersin various lobes of the brain are shown in Table 6

The increase of frontal 120579 band power indicates intellectualconcentration andmeditative state of relief from nervousnessand is negatively related with sympathetic activation Thisreflects a near relationship between autonomic functionactivity of medial frontal neural circuitry and probability ofcontrolling central nervous system (CNS) functions owing toyoga practice and meditation [12] 120572 waves are indicative ofincreased relaxed state ofmind and its bandpower is inverselyrelated to mental activity Yoga enhanced various cognitiveskills improved sense of wellbeing and responsiveness andenhanced cognitive functions as substantiated by increased120572 and 120573 band powers and various engagement indices Italso improves mental consciousness and achieves reductionin stress and strain and thus advocates complete health andwellbeing in an individual [40] Increase in 120573 band powerwould indicate a higher level of alertness and enhancedengagement task whereas increased band powers of 120572 and 120579would indicate decreased alertness and reduced engagementtask [25] The increase of 120573 power reflects improvement ofcertain cognitive functions such as memory and reactiontime That of 120572 and 120575 indicates synchronization of brainactivity The total EEG band power also increased in yogagroup compared to the control group

The ratio 120579120572 is associated with HR This ratio decreasedin all lobes of the brain indicating the relaxed state of sub-jectsThis reduction could be either increase of 120572 band poweror decrease of 120579 band power Since 120572 power increased in yogagroup this ratio decreased indicating enhancement of certaincognitive faculties (memory attention) and improvement inthe HRV These in turn indicate indirect improvement incertain cognitive functions such as reaction time The ratio120573120572 [25] is called arousal indexThis indicates level of arousalbased on interbeat intervals (IBI) activity Arousal level gt0indicates higher than normal arousal and lt0 indicates lowerthan normal arousal

This ratio increased (4711) in yoga group whiledecreased in control group (243) The increases of thisratio indicate enhanced cognitive functions such as attentionThe decreases of this ratio reflect reduction in the corecapabilities of cognitive functions This ratio increased in alllobes of the brain but the maximum increase was observedin parietal (7805) central (5312) and temporal (4504)lobes It increased to (3824) and (1976) in frontal andoccipital lobes respectively The ratio (120575 + 120579)120572 is calledexecutive load index [28] and is a measure of executive loador comprehension Positive value indicates increased loadand negative value indicates decreased load It reflects theoscillations in precise cortical network active among spatiallydisjoint brain compartment This ratio decreased (4098)in experimental group while it increased (1719) slightlyin control group The decrease in this ratio may be dueto increase in 120572 band power or reduced band power ofeither 120575 or 120579 or both It is observed that 120572 band power wasincreased in yoga practicing group This ratio was also founddecreased in all the lobes of the brain Another importantparameter 120579(fro)120572(par) [27] is called task load index Thisratio decreases in experimental group while it increases incontrol group It is evident from the relation that the ratiodecreases due to increase in 120572 band power These results areshown in Tables 7 and 8

The ratio 120579120573 indicates central nervous system (CNS)arousal [30] and increased ratio is marker of under arousalThis ratio decreased in yoga group The reductions in thisratio reflect the shift of 120572 and 120579 activity towards 120573 activityThe increased 120573 band powers indicate enhanced cognitiveperformance such as memory attention and concentrationThe ratio 120572120575 which is called ldquobrain perfusionrdquo index [29]was increased (46) in yoga practiced group This indicatessufficient amount of blood flow to the different parts ofthe brain among yoga group These in turn enhances thebetter functioning of the brain The ratio LFHF can beexpressed in terms of (120579 + 120575)(120572 + 120573) [29] Slower brainoscillations (120579 and 120575) harmonize considerable neuron groupsacross larger brain areas and faster oscillations (120572 and 120573)synchronize smaller focused neuronal assemblies [41]Whengroups of neurons oscillate together synchronously theymore effectively communicated with each other The index(120579 + 120575)(120572 + 120573) indicates sympathovagal balance of theautonomic nervous system (ANS) Lower ratios indicatebetter balance of ANSThis ratio decreased in yoga group but

10 Computational and Mathematical Methods in Medicine

Table 7 Cognitive index parameters of yoga group before and after yoga intervention Postintervention values are shown within theparenthesis

EEG indices Yoga groupFrontal Central Parietal Occipital Temporal

120579120572 4621 (2806) 4951 (2063) 5059 (2973) 8792 (4609) 4604 (2480)120572120579 0216 (0356) 0202 (0485) 0198 (0336) 0114 (0217) 0217 (0403)120573120572 0612 (0846) 0625 (0957) 0523 (0931) 0607 (0727) 0564 (0818)120573120579 0132 (0302) 0126 (0464) 0103 (0313) 0069 (0158) 0123 (0330)120573(120572 + 120579) 0109 (0222) 0105 (0312) 0086 (0234) 0062 (0130) 0101 (0235)120579(fro)120572(par) 4621 (2806) 4951 (2063) 5059 (2973) 8792 (4609) 4604 (2480)(120575 + 120579)120572 5590 (3926) 5964 (3200) 6168 (3961) 10112 (5907) 5614 (3243)sum(120575 + 120579)120572 = 46392 (27876)

Table 8 Global EEG band power ratios before and after yoga inter-vention

EEG indices Yoga group Control groupBefore yoga After yoga Before yoga After yoga

120579120572 5405 2800 4485 5460120572120579 0185 0357 0228 0183120573120572 0588 0865 0986 0962120573120579 0109 0309 0220 0176120573(120572 + 120579) 0092 0228 0180 0149120579(fro)120572(par) 5405 2800 4485 5460(120575 + 120579)120572 6472 3820 5623 6590sum(120575 + 120579)120572 46392 27876 40456 47080

Table 9 EEG indices and their values before and after yoga inter-vention

Parameters Yoga group ControlBefore After Before After

120572120575 0937 0980 0879 0885(120579 + 120575)(120572 + 120573) 408 205 332 289120572120573 170 116 10139 10394120575120579 0197 0364 0209 2488120579120573 9198 3235 5530 4721

did not change in control group The ratio 120572120573 [31] which iscalled desynchronization is used to analyze vigilance indexand 120575120579 is called synchronization The ratio 120572120573 decreasedwhich is desirable The increase 120573 of band power indicatesimproved cognitive performance Since the parameter is indenominator the ratio decreases when there is increasedcognitive performance However in control group this ratiowas slightly increased Another ratio 120575120579 was increasedrelatively by small amount in experimental group than thecontrol groupThe 120572120575 ratio was decreased in frontal centraland occipital lobes while it increased in parietal and temporallobes These results are shown in Tables 9 10 and 11

The relative EEG band powers of 120573 120572 and 120575 increasedin yoga group in all the lobes of the brain The increases ofthese band powers indicate improvement of certain cognitivefunctions such as memory attention executive functionsand concentration The increase of 120575 power and decrease of

1932 1958

8783

222914911860 1618

10558

21181189

0

20

40

60

80

100

120

PSD

(120583V2H

z)

BeforeAfter

120573 120572 120579 120575 120574

Figure 5 Global EEG band powers of control group before andafter intervention

120579 power indicate improvement in neural activityThe variousEEG band powers are shown in Figure 1

The total band power (global) of 120573 120572 and 120575 increasedamong yoga group The increased 120573 power was associatedwith enhanced cognitive performance such as improvedalertness The maximum 120573 power increased in frontal andcentral lobes of the brain This indicates the improvementin emotion process and cognition The increased 120572 anddecreased 120579 powers physiologically signify the enhancedvigilance and increased alertness level of subjects These areshown in Figure 2 The improvement in cognitive functionswas associated with increased power in high frequency band(120573) and reduction in low frequency band (120579) Therefore 120573120579ratio is suitable index to assess the improvement in cognitiveskills of the subjectsThe cognitive performance index 120573(120572 +120579) increased and ratio of sum of low frequency to sum of highfrequency (120579 + 120575)(120573 + 120572) was decreased among yoga groupwhich is shown in Figure 3

There were no significant changes in EEG band powersengagement indices total power and cognitive performancesindices among control group The various performancesparameters of control group are shown in Figures 4 5 6 and7

Computational and Mathematical Methods in Medicine 11

Table 10 EEG index values of yoga group in different lobes of the brain before and after yoga intervention Postintervention values are shownin parenthesis

Parameters Brain lobesFrontal Central Parietal Occipital Temporal

120572120575 1032 (0893) 0988 (0879) 0902 (1011) 0757 (0770) 0990 (1312)(120579 + 120575)(120572 + 120573) 3468 (0534) 3669 (0566) 4050 (0402) 6294 (0363) 3589 (0363)120572120573 1634 (2806) 1599 (2063) 1913 (2973) 1648 (4609) 1772 (2480)120575120579 0210 (0814) 0205 (0524) 0219 (0614) 0150 (0570) 0219 (0657)120579120573 7550 (3316) 7916 (2156) 9675 (3194) 14492 (6341) 8159 (3032)

Table 11 EEG index values of control group in different lobes of the brain before and after yoga intervention Postintervention values areshown in parenthesis

Parameters Brain lobesFrontal Central Parietal Occipital Temporal

120572120575 0914 (0944) 0940 (0940) 0760 (0760) 0825 (0825) 0930 (0931)(120579 + 120575)(120572 + 120573) 0424 (0356) 0326 (0261) 0271 (0241) 0262 (0218) 0486 (0438)120572120573 3428 (4186) 3711 (4891) 6412 (7311) 5513 (6817) 4385 (4970)120575120579 0716 (0741) 0445 (0445) 0524 (0523) 0409 (0409) 1433 (1433)120579120573 3269 (4185) 3958 (5251) 5747 (6647) 6633 (8531) 4235 (4839)

After yogaBefore yoga

736686

586694

576

737 776

585

752

571

0

1

2

3

4

5

6

7

8

9

Frontal Central Perietal Occipital Temporal

PSD

(120583V2H

z)

Figure 6 Global EEGband powers of control group in various lobesof the brain before and after intervention

4 Conclusions

The regular practices of yoga for a period of five months byyoung healthy engineering students enhance different typesof cognitive skills Apart from cognitive the yoga practiceresulted in many health benefits such as improvement inheart rate variability The ratio SDNNRMSSD increasedwhile the ratio LFHF decreasedThis indicates improvementin the parasympathetic activity and decrease in sympatheticactivity Hence the current results suggest that the practice ofyoga modifies the sympathovagal balance towards parasym-pathetic activation improved the heart rate variability andenhanced sense of wellbeing Since the study population isyoung healthy engineering graduates it would be interestingto investigate whether the yoga practice could result inimprovement in the academic performances

3319

0153

6593

2891

0174

5672

0

1

2

3

4

5

6

7

8

Enga

gem

ent i

ndex

val

ue

Before yogaAfter yoga

(120575 + 120579)(120572 + 120573) 120573(120572 + 120579) (120575 + 120579)120572

Figure 7 CNS activity engagement index and executive load indexof control group before and after intervention

In a nutshell it is proved beyond doubt that yogapractices resulted in effective improvements in physiologicalparameters indirectly improving psychological parametersand various cognitive functions The results of this studygreatly encourage further investigation to study whether thepractice of yoga could also enhance academic performance

Limitations of the Study

Limitations of this study include small number of samplesand lack of dedicated control group and methodologicaldifferences Further investigation can be done by employingpsychological tests to evaluate cognitive behavior

12 Computational and Mathematical Methods in Medicine

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

The authors acknowledge the Principal of PDA College ofEngineering Kalaburagi for deputingHNagendra to pursuePhD degree and Department of Electrical EngineeringIIT Roorkee for providing an opportunity under QualityImprovement Programme (QIP) They also acknowledge thestudents who participated in this study and give specialthanks to the yoga instructor

References

[1] P Sengupta ldquoHealth impacts of yoga and pranayama a state-of-the-art reviewrdquo International Journal of Preventive Medicinevol 3 no 7 pp 444ndash458 2012

[2] A Ross and S Thomas ldquoThe health benefits of yoga and exer-cise a review of comparison studiesrdquoThe Journal of Alternativeand Complementary Medicine vol 16 no 1 pp 3ndash12 2010

[3] P A Balaji S R Varne and S S Ali ldquoPhysiological effects ofyogic practices and transcendental meditation in health anddiseaserdquo North American Journal of Medical Sciences vol 4 no10 pp 442ndash448 2012

[4] A Bussing A Michalsen S B S Khalsa S Telles and K JSherman ldquoEffects of yoga on mental and physical health ashort summary of reviewsrdquo Evidence-based Complementary andAlternative Medicine vol 2012 Article ID 165410 7 pages 2012

[5] T N Sathyaprabha P Satishchandra C Pradhan et al ldquoModu-lation of cardiac autonomic balance with adjuvant yoga therapyin patients with refractory epilepsyrdquo Epilepsy and Behavior vol12 no 2 pp 245ndash252 2008

[6] S Telles N Singh and A Balkrishna ldquoHeart rate variabil-ity changes during high frequency yoga breathingand breathawarenessrdquo BioPsychoSocial Medicine vol 5 article 4 2011

[7] L Jatiya KUdupa andA B Bhavanani ldquoEffect of yoga trainingon handgrip respiratory pressures and pulmonary functionrdquoIndian Journal of Physiology and Pharmacology vol 47 no 4pp 387ndash392 2003

[8] D Nangia and R Malhotra ldquoYoga cognition and mentalhealthrdquo Journal of the IndianAcademy ofApplied Psychology vol38 no 2 pp 262ndash269 2012

[9] S Telles and P Sarang ldquoEffects of two yoga based relaxationtechniques on Heart Rate Variability (HRV)rdquo InternationalJournal of Stress Management vol 13 no 4 pp 460ndash475 2006

[10] S Telles R Nagarathna P R Vani and H R Nagendra ldquoAcombination of focusing and defocusing through yoga reducesoptical illusion more than focusing alonerdquo Indian Journal ofPhysiology and Pharmacology vol 41 no 2 pp 179ndash182 1997

[11] K K F Rocha A M Ribeiro K C F Rocha et al ldquoImprove-ment in physiological and psychological parameters after6months of yoga practicerdquo Consciousness and Cognition vol 21no 2 pp 843ndash850 2012

[12] R Khadka B H Paudel V P Sharma S Kumar and N Bhat-tacharya ldquoEffect of yoga on cardiovascular autonomic reactivityin essential hypertensive patientsrdquo Health Renaissance vol 8no 2 pp 102ndash109 2010

[13] L C M Vanderlei C M Pastre R A Hoshi T D de Carvalhoand M F de Godoy ldquoBasic notions of heart rate variabilityand its clinical applicabilityrdquo Brazilian Journal of CardiovascularSurgery vol 24 no 2 pp 205ndash217 2009

[14] M V Hoslashjgaard N-H Holstein-Rathlou E Agner and JK Kanters ldquoDynamics of spectral components of heart ratevariability during changes in autonomic balancerdquoTheAmericanJournal of PhysiologymdashHeart and Circulatory Physiology vol275 no 1 pp H213ndashH219 1998

[15] S Boonnithi and S Phongsuphap ldquoComparison of heart ratevariability measures for mental stress detectionrdquo in Proceedingsof the Computing in Cardiology (CinC rsquo11) pp 85ndash88 2011

[16] H Kobayashi K Ishibashi and H Noguchi ldquoHeart ratevariability an index for monitoring and analyzing humanautonomic activitiesrdquo Journal of Physiological Anthropology andApplied Human Science vol 18 no 2 pp 53ndash59 1999

[17] J Sztajzel ldquoHeart rate variability a noninvasive electrocardio-graphic method to measure the autonomic nervous systemrdquoSwiss Medical Weekly vol 134 no 35-36 pp 514ndash522 2004

[18] J Taelman S Vandeput A Spaepen and S van Huffel ldquoInflu-ence of mental stress on heart rate and heart rate variabilityrdquo inProceedings of the 4th European Conference of the InternationalFederation for Medical and Biological Engineering (IFMBE rsquo08)vol 22 pp 1366ndash1369 November 2008

[19] E Tharion S Parthasarathy and N Neelakantan ldquoShort-termheart rate variability measures in students during examina-tionsrdquo National Medical Journal of India vol 22 no 2 pp 63ndash66 2009

[20] Y Sun N Ye and X Xu ldquoEEG analysis of alcoholics andcontrols based on feature extractionrdquo in Proceedings of the 8thInternational Conference on Signal Processing (ICSP rsquo06) 2006

[21] C Y Chen W K Wong C D Kuo Y T Liao and MD Ke ldquoWavelet real time monitoring system a case studyof the musical influence on electroencephalographyrdquo WSEASTransactions on Systems vol 7 no 2 pp 56ndash62 2008

[22] C Parameswariah and M Cox ldquoFrequency characteristics ofwaveletsrdquo IEEE Power Engineering Review vol 22 no 1 p 722002

[23] A Holm K Lukander J Korpela M Sallinen and K M IMuller ldquoEstimating brain load from the EEGrdquo The ScientificWorld Journal vol 9 pp 639ndash651 2009

[24] J Gruzelier ldquoA theory of alphatheta neurofeedback creativeperformance enhancement long distance functional connectiv-ity and psychological integrationrdquo Cognitive Processing vol 10no 1 supplement pp 101ndash109 2009

[25] F G Freeman P J Mikulka L J Prinzel and M W ScerboldquoEvaluation of an adaptive automation system using three EEGindices with a visual tracking taskrdquo Biological Psychology vol50 no 1 pp 61ndash76 1999

[26] A F Rabbi K Ivanca A V Putnam A Musa C B Thadenand R Fazel-Rezai ldquoHuman performance evaluation based onEEG signal analysis a prospective reviewrdquo in Proceedings of the31st Annual International Conference of the IEEE Engineeringin Medicine and Biology Society (EMBC rsquo09) pp 1879ndash1882September 2009

[27] A Gevins M E Smith LMcEvoy andD Yu ldquoHigh-resolutionEEGmapping of cortical activation related to workingmemoryeffects of task difficulty type of processing and practicerdquoCerebral Cortex vol 7 no 4 pp 374ndash385 1997

[28] J T Coyne C Baldwin A Cole C Sibley and D M RobertsldquoApplying real time physiological measures of cognitive load

Computational and Mathematical Methods in Medicine 13

to improve trainingrdquo in Foundations of Augmented CognitionNeuroergonomics and Operational Neuroscience vol 5638 ofLecture Notes in Computer Science pp 469ndash478 SpringerBerlin Germany 2009

[29] G Bashein M L Nessly S W Bledsoe et al ldquoElectroen-cephalography during surgery with cardiopulmonary bypassand hypothermiardquo Anesthesiology vol 76 no 6 pp 878ndash8911992

[30] R J Barry A R Clarke S J Johnstone R McCarthy andM Selikowitz ldquoElectroencephalogram 120572120573 ratio and arousal inattention-deficithyperactivity disorder evidence of indepen-dent processesrdquoBiological Psychiatry vol 66 no 4 pp 398ndash4012009

[31] L Cao J Li Y Sun H Zhu and C Yan ldquoEEG-based vig-ilance analysis by using fisher score and PCA algorithmrdquo inProceedings of the 1st IEEE International Conference on Progressin Informatics and Computing (PIC rsquo10) pp 175ndash179 ShanghaiChina December 2010

[32] L I Aftanas and S A Golocheikine ldquoNon-linear dynamiccomplexity of the humanEEGduringmeditationrdquoNeuroscienceLetters vol 330 no 2 pp 143ndash146 2002

[33] M Balasubramaniam S Telles and P M Doraiswamy ldquoYogaon our minds a systematic review of yoga for neuropsychiatricdisordersrdquo Frontiers in Psychiatry vol 3 Article ID Article 117pp 1ndash16 2013

[34] B S Moon H C Lee Y H Lee J C Park I S Oh and JW Lee ldquoFuzzy systems to process ECG and EEG signals forquantification of the mental workloadrdquo Information Sciencesvol 142 no 1ndash4 pp 23ndash35 2002

[35] P Raghuraj A G Ramakrishnan H R Nagendra and S TellesldquoEffect of two selected yogic breathing techniques on heart ratevariabilityrdquo Indian Journal of Physiology and Pharmacology vol42 no 4 pp 467ndash472 1998

[36] J J Sollers III T W Buchanan S M Mowrer L K Hill and JFThayer ldquoComparison of the ratio of the standard deviation ofthe r-r interval and the rootmean squared successive differences(SDrMSSD) to the low frequency-to-high frequency (LFHF)ratio in a patient population and normal healthy controlsrdquoBiomedical Sciences Instrumentation vol 43 pp 158ndash163 2007

[37] C Zhao C Zheng M Zhao and J Liu ldquoPhysiological assess-ment of driving mental fatigue using wavelet packet energy andrandom forestsrdquo The American Journal of Biomedical Sciencesvol 2 no 3 pp 262ndash274 2010

[38] O V Grishin V G Grishin D Yu Uryumtsev S V Smirnovand I G Jilina ldquoMetabolic rate variability impact on verylow-frequency of heart rate variabilityrdquo World Applied SciencesJournal vol 19 no 8 pp 1133ndash1139 2012

[39] E Basar C Basar-Eroglu S Karakas and M SchurmannldquoGamma alpha delta and theta oscillations govern cognitiveprocessesrdquo International Journal of Psychophysiology vol 39 no2-3 pp 241ndash248 2000

[40] K C Khare and S K Nigam ldquoA study of electroencephalogramin meditatorsrdquo Indian Journal of Physiology and Pharmacologyvol 44 no 2 pp 173ndash178 2000

[41] J Jacobs and M J Kahana ldquoDirect brain recordings fueladvances in cognitive electrophysiologyrdquo Trends in CognitiveSciences vol 14 no 4 pp 162ndash171 2010

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Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

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Disease Markers

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Oxidative Medicine and Cellular Longevity

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

PPAR Research

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Immunology ResearchHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal of

ObesityJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Computational and Mathematical Methods in Medicine

OphthalmologyJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Diabetes ResearchJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Research and TreatmentAIDS

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Gastroenterology Research and Practice

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Parkinsonrsquos Disease

Evidence-Based Complementary and Alternative Medicine

Volume 2014Hindawi Publishing Corporationhttpwwwhindawicom

8 Computational and Mathematical Methods in Medicine

Table 5 Time and frequency domain parameters before and after intervention of yoga and control group

Parameters Yoga group Control groupBefore After 119875 value Before After 119875 value

mHRV (ms) 75721 plusmn 6537 81329 plusmn 7891 00304 87467 plusmn 9155 85572 plusmn 7048 02505mHR (bpm) 7979 plusmn 774 7457 plusmn 705 00389 6950 plusmn 943 7050 plusmn 622 02759SDNN (ms) 4443 plusmn 2176 5214 plusmn 2327 00012 5322 plusmn 2169 5383 plusmn 1951 09044RMSSD (ms) 3993 plusmn 2365 5521 plusmn 2278 00058 5483 plusmn 2946 49 plusmn 2789 01999SDNNRMSSD 077 plusmn 037 111 plusmn 057 00039 077 plusmn 037 121 plusmn 028 01336VLF (nu) 402 plusmn 096 1163 plusmn 983 00177 342 plusmn 991 1404 plusmn 1006 00007LF (nu) 12306 plusmn 2110 5685 plusmn 1016 00002 4514 plusmn 1309 4157 plusmn 1660 00000HF (nu) 2739 plusmn 844 4315 plusmn 1016 00003 4648 plusmn 461 220 plusmn 579 00269LFrelative 7133 plusmn 567 5116 plusmn 951 00000 4642 plusmn 1070 7081 plusmn 713 00000HFrelative 2739 plusmn 844 4315 plusmn 1016 00003 4648 plusmn 461 4220 plusmn 579 00269TP (nu) 17199 plusmn 2241 11163 plusmn 983 00000 9503 plusmn 1129 9781 plusmn 1244 00000LF HF 499 plusmn 198 1411 plusmn 045 00000 099 plusmn 032 355 plusmn 156 00000119875 gt 010 not significant 119875 lt 010marginal 119875 lt 005 fair 119875 lt 001 good 119875 lt 0001 excellent difference 119875 lt 005 is considered significant level and for anyvalue less than this the null hypothesis is rejected 119905stat gt 119905valu for the null hypothesis to be rejected If 119875 = 005 there is 5 chance of no real difference

total power was observed in yoga group This might be dueto significant decrease of sympathetic activity compared tosignificant increase of parasympathetic activity The VHFpower generally reflects part of noise component and doesnot possess clinically significant information

Control group showed significant increase of LF power(119875 lt 00000) decreased HF power (119875 lt 0029) increasedLFHF ratio (119875 lt 00000) and increased VLF power But nosignificant changes were observed in time domain parame-ters

The LF and HF band power of HRV are expressed innormalized units The representation of these frequencyband powers in normalized units articulates the degree ofcontrol exercised and the relative balance of two limbs ofthe autonomic nervous system [35]Moreover normalized LFpower is thought to represent the sympathetic modulation asopposed to absolute units Since theHRV spectral parametersare computed by the autonomic nervous system (ANS) mea-surement of HRV may have greater application in assessingautonomic statues

Studentrsquos paired 119905-test was performed on set of pre- andpostintervention data samples to investigate whether therewas any real difference between them Each 119905 value has acorresponding 119875 value The 119875 value which is the probabilitythat the pattern of data samples in the sample could beproduced by random data provides the information aboutthe likelihood that there is a real difference in the data patternThis significant difference in the data set could be due to theeffect of particular training or an intervention given to thesubjects

The various time and frequency domain parameters ofboth yoga and control group are shown in Table 5 Anyvariations in these parameters could be due to relative age dif-ferences between yoga and control groups or methodologicaldifferences or limited number of samples in the study

The decrease in HR could be due to combined effect ofelements of yoga The reduction in stress after yoga couldbe other possible reason for improved HRV in this study

The previous researches suggest that yoga practice resultsin neurophysiological balance by lowering level of cholin-esterase and catecholamines Further this result increasedparasympathetic and decreased sympathetic activity Theresults of this study are in concurrence with previous studies[6 9 35] These studies indicated reduced sympatheticactivity and enhanced parasympathetic activity after yoga

32 Cognitive Performance Analysis The regular practice ofyoga for a period of fivemonths by young healthy engineeringstudents resulted in the increase of 120572 120573 and 120575 EEG bandpowers and decrease in the 120579 and 120574 band powers Theincreased 120573 band power indicate enhancement in certaincognitive functions such as alertness while increased 120572and decreased 120575 reflect enhanced vigilance level indicatingincreased alertnessThus the increase of high frequency bandpowers (120572 120573) and decrease of low frequency band powers (120575120579) are associated with enhancement in certain cognitive skillssuch as memory and visual information processing

The various cognitive behavior parameters have beenevaluated based on various EEG indices such as 120579120572 120573120572120573120579 (120575 + 120579)120572 120573(120572 + 120579) and (120575 + 120579)(120572 + 120573) Increasein 120573 band power indicates a higher level of alertness andenhanced engagement task and enhancement in variouscognitive abilities The increased band powers of 120572 and 120579indicate decreased alertness reduced engagement task andgood information processing capabilities [25] The 120575 and 120582activity are used for analysis of many cognitive processes[39]The ratio 120573120579which is representative of improvement incognitive skills increasedThe heart rate index 120579120572 decreasedperformance enhancement index 120572120579 increased attentionresource index 120573(120572 + 120579) significantly increased executiveload index (120575 + 120579)120572 decreased and ratio (120575 + 120579)(120572 + 120573)decreased The 120572 120573 and 120575 band power increased in frontalcentral parietal occipital and temporal lobes The 120579 bandpower was increased only in occipital lobe while 120574 bandpower in frontal and slightly in temporal lobes As the frontallobe is associated with reasoning planning problem solving

Computational and Mathematical Methods in Medicine 9

Table 6 Mean powers of EEG frequency bands averaged across all the lobes of the brain before and after yoga intervention

EEG band powers120574 (120583V2Hz) 120573 (120583V2Hz) 120572 (120583V2Hz) 120579 (120583V2Hz) 120575 (120583V2Hz)

Yoga groupBefore yoga 380 plusmn 093 232 plusmn 049 395 plusmn 070 2136 plusmn 343 422 plusmn 042After yoga 365 plusmn 069 491 plusmn 163 567 plusmn 168 1588 plusmn 257 579 plusmn 106

Control groupBefore yoga 298 plusmn 136 386 plusmn 096 392 plusmn 097 1757 plusmn 254 446 plusmn 089After yoga 294 plusmn 133 372 plusmn 082 387 plusmn 090 2112 plusmn 387 437 plusmn 078

and cognition parietal lobe with visual perception recogni-tion information processing and spatial reasoning temporallobe with memory and processing of verbal and auditorysignals and occipital lobe with visual spatial processing andrecognition An increase of EEG frequency band powers inthese lobes indicates the enhancement of certain type ofcognitive skillsThe type of the cognitive skills developed canbe assessed based on increased or decreased EEG band powerin these lobesThemean absolute values of these band powersin various lobes of the brain are shown in Table 6

The increase of frontal 120579 band power indicates intellectualconcentration andmeditative state of relief from nervousnessand is negatively related with sympathetic activation Thisreflects a near relationship between autonomic functionactivity of medial frontal neural circuitry and probability ofcontrolling central nervous system (CNS) functions owing toyoga practice and meditation [12] 120572 waves are indicative ofincreased relaxed state ofmind and its bandpower is inverselyrelated to mental activity Yoga enhanced various cognitiveskills improved sense of wellbeing and responsiveness andenhanced cognitive functions as substantiated by increased120572 and 120573 band powers and various engagement indices Italso improves mental consciousness and achieves reductionin stress and strain and thus advocates complete health andwellbeing in an individual [40] Increase in 120573 band powerwould indicate a higher level of alertness and enhancedengagement task whereas increased band powers of 120572 and 120579would indicate decreased alertness and reduced engagementtask [25] The increase of 120573 power reflects improvement ofcertain cognitive functions such as memory and reactiontime That of 120572 and 120575 indicates synchronization of brainactivity The total EEG band power also increased in yogagroup compared to the control group

The ratio 120579120572 is associated with HR This ratio decreasedin all lobes of the brain indicating the relaxed state of sub-jectsThis reduction could be either increase of 120572 band poweror decrease of 120579 band power Since 120572 power increased in yogagroup this ratio decreased indicating enhancement of certaincognitive faculties (memory attention) and improvement inthe HRV These in turn indicate indirect improvement incertain cognitive functions such as reaction time The ratio120573120572 [25] is called arousal indexThis indicates level of arousalbased on interbeat intervals (IBI) activity Arousal level gt0indicates higher than normal arousal and lt0 indicates lowerthan normal arousal

This ratio increased (4711) in yoga group whiledecreased in control group (243) The increases of thisratio indicate enhanced cognitive functions such as attentionThe decreases of this ratio reflect reduction in the corecapabilities of cognitive functions This ratio increased in alllobes of the brain but the maximum increase was observedin parietal (7805) central (5312) and temporal (4504)lobes It increased to (3824) and (1976) in frontal andoccipital lobes respectively The ratio (120575 + 120579)120572 is calledexecutive load index [28] and is a measure of executive loador comprehension Positive value indicates increased loadand negative value indicates decreased load It reflects theoscillations in precise cortical network active among spatiallydisjoint brain compartment This ratio decreased (4098)in experimental group while it increased (1719) slightlyin control group The decrease in this ratio may be dueto increase in 120572 band power or reduced band power ofeither 120575 or 120579 or both It is observed that 120572 band power wasincreased in yoga practicing group This ratio was also founddecreased in all the lobes of the brain Another importantparameter 120579(fro)120572(par) [27] is called task load index Thisratio decreases in experimental group while it increases incontrol group It is evident from the relation that the ratiodecreases due to increase in 120572 band power These results areshown in Tables 7 and 8

The ratio 120579120573 indicates central nervous system (CNS)arousal [30] and increased ratio is marker of under arousalThis ratio decreased in yoga group The reductions in thisratio reflect the shift of 120572 and 120579 activity towards 120573 activityThe increased 120573 band powers indicate enhanced cognitiveperformance such as memory attention and concentrationThe ratio 120572120575 which is called ldquobrain perfusionrdquo index [29]was increased (46) in yoga practiced group This indicatessufficient amount of blood flow to the different parts ofthe brain among yoga group These in turn enhances thebetter functioning of the brain The ratio LFHF can beexpressed in terms of (120579 + 120575)(120572 + 120573) [29] Slower brainoscillations (120579 and 120575) harmonize considerable neuron groupsacross larger brain areas and faster oscillations (120572 and 120573)synchronize smaller focused neuronal assemblies [41]Whengroups of neurons oscillate together synchronously theymore effectively communicated with each other The index(120579 + 120575)(120572 + 120573) indicates sympathovagal balance of theautonomic nervous system (ANS) Lower ratios indicatebetter balance of ANSThis ratio decreased in yoga group but

10 Computational and Mathematical Methods in Medicine

Table 7 Cognitive index parameters of yoga group before and after yoga intervention Postintervention values are shown within theparenthesis

EEG indices Yoga groupFrontal Central Parietal Occipital Temporal

120579120572 4621 (2806) 4951 (2063) 5059 (2973) 8792 (4609) 4604 (2480)120572120579 0216 (0356) 0202 (0485) 0198 (0336) 0114 (0217) 0217 (0403)120573120572 0612 (0846) 0625 (0957) 0523 (0931) 0607 (0727) 0564 (0818)120573120579 0132 (0302) 0126 (0464) 0103 (0313) 0069 (0158) 0123 (0330)120573(120572 + 120579) 0109 (0222) 0105 (0312) 0086 (0234) 0062 (0130) 0101 (0235)120579(fro)120572(par) 4621 (2806) 4951 (2063) 5059 (2973) 8792 (4609) 4604 (2480)(120575 + 120579)120572 5590 (3926) 5964 (3200) 6168 (3961) 10112 (5907) 5614 (3243)sum(120575 + 120579)120572 = 46392 (27876)

Table 8 Global EEG band power ratios before and after yoga inter-vention

EEG indices Yoga group Control groupBefore yoga After yoga Before yoga After yoga

120579120572 5405 2800 4485 5460120572120579 0185 0357 0228 0183120573120572 0588 0865 0986 0962120573120579 0109 0309 0220 0176120573(120572 + 120579) 0092 0228 0180 0149120579(fro)120572(par) 5405 2800 4485 5460(120575 + 120579)120572 6472 3820 5623 6590sum(120575 + 120579)120572 46392 27876 40456 47080

Table 9 EEG indices and their values before and after yoga inter-vention

Parameters Yoga group ControlBefore After Before After

120572120575 0937 0980 0879 0885(120579 + 120575)(120572 + 120573) 408 205 332 289120572120573 170 116 10139 10394120575120579 0197 0364 0209 2488120579120573 9198 3235 5530 4721

did not change in control group The ratio 120572120573 [31] which iscalled desynchronization is used to analyze vigilance indexand 120575120579 is called synchronization The ratio 120572120573 decreasedwhich is desirable The increase 120573 of band power indicatesimproved cognitive performance Since the parameter is indenominator the ratio decreases when there is increasedcognitive performance However in control group this ratiowas slightly increased Another ratio 120575120579 was increasedrelatively by small amount in experimental group than thecontrol groupThe 120572120575 ratio was decreased in frontal centraland occipital lobes while it increased in parietal and temporallobes These results are shown in Tables 9 10 and 11

The relative EEG band powers of 120573 120572 and 120575 increasedin yoga group in all the lobes of the brain The increases ofthese band powers indicate improvement of certain cognitivefunctions such as memory attention executive functionsand concentration The increase of 120575 power and decrease of

1932 1958

8783

222914911860 1618

10558

21181189

0

20

40

60

80

100

120

PSD

(120583V2H

z)

BeforeAfter

120573 120572 120579 120575 120574

Figure 5 Global EEG band powers of control group before andafter intervention

120579 power indicate improvement in neural activityThe variousEEG band powers are shown in Figure 1

The total band power (global) of 120573 120572 and 120575 increasedamong yoga group The increased 120573 power was associatedwith enhanced cognitive performance such as improvedalertness The maximum 120573 power increased in frontal andcentral lobes of the brain This indicates the improvementin emotion process and cognition The increased 120572 anddecreased 120579 powers physiologically signify the enhancedvigilance and increased alertness level of subjects These areshown in Figure 2 The improvement in cognitive functionswas associated with increased power in high frequency band(120573) and reduction in low frequency band (120579) Therefore 120573120579ratio is suitable index to assess the improvement in cognitiveskills of the subjectsThe cognitive performance index 120573(120572 +120579) increased and ratio of sum of low frequency to sum of highfrequency (120579 + 120575)(120573 + 120572) was decreased among yoga groupwhich is shown in Figure 3

There were no significant changes in EEG band powersengagement indices total power and cognitive performancesindices among control group The various performancesparameters of control group are shown in Figures 4 5 6 and7

Computational and Mathematical Methods in Medicine 11

Table 10 EEG index values of yoga group in different lobes of the brain before and after yoga intervention Postintervention values are shownin parenthesis

Parameters Brain lobesFrontal Central Parietal Occipital Temporal

120572120575 1032 (0893) 0988 (0879) 0902 (1011) 0757 (0770) 0990 (1312)(120579 + 120575)(120572 + 120573) 3468 (0534) 3669 (0566) 4050 (0402) 6294 (0363) 3589 (0363)120572120573 1634 (2806) 1599 (2063) 1913 (2973) 1648 (4609) 1772 (2480)120575120579 0210 (0814) 0205 (0524) 0219 (0614) 0150 (0570) 0219 (0657)120579120573 7550 (3316) 7916 (2156) 9675 (3194) 14492 (6341) 8159 (3032)

Table 11 EEG index values of control group in different lobes of the brain before and after yoga intervention Postintervention values areshown in parenthesis

Parameters Brain lobesFrontal Central Parietal Occipital Temporal

120572120575 0914 (0944) 0940 (0940) 0760 (0760) 0825 (0825) 0930 (0931)(120579 + 120575)(120572 + 120573) 0424 (0356) 0326 (0261) 0271 (0241) 0262 (0218) 0486 (0438)120572120573 3428 (4186) 3711 (4891) 6412 (7311) 5513 (6817) 4385 (4970)120575120579 0716 (0741) 0445 (0445) 0524 (0523) 0409 (0409) 1433 (1433)120579120573 3269 (4185) 3958 (5251) 5747 (6647) 6633 (8531) 4235 (4839)

After yogaBefore yoga

736686

586694

576

737 776

585

752

571

0

1

2

3

4

5

6

7

8

9

Frontal Central Perietal Occipital Temporal

PSD

(120583V2H

z)

Figure 6 Global EEGband powers of control group in various lobesof the brain before and after intervention

4 Conclusions

The regular practices of yoga for a period of five months byyoung healthy engineering students enhance different typesof cognitive skills Apart from cognitive the yoga practiceresulted in many health benefits such as improvement inheart rate variability The ratio SDNNRMSSD increasedwhile the ratio LFHF decreasedThis indicates improvementin the parasympathetic activity and decrease in sympatheticactivity Hence the current results suggest that the practice ofyoga modifies the sympathovagal balance towards parasym-pathetic activation improved the heart rate variability andenhanced sense of wellbeing Since the study population isyoung healthy engineering graduates it would be interestingto investigate whether the yoga practice could result inimprovement in the academic performances

3319

0153

6593

2891

0174

5672

0

1

2

3

4

5

6

7

8

Enga

gem

ent i

ndex

val

ue

Before yogaAfter yoga

(120575 + 120579)(120572 + 120573) 120573(120572 + 120579) (120575 + 120579)120572

Figure 7 CNS activity engagement index and executive load indexof control group before and after intervention

In a nutshell it is proved beyond doubt that yogapractices resulted in effective improvements in physiologicalparameters indirectly improving psychological parametersand various cognitive functions The results of this studygreatly encourage further investigation to study whether thepractice of yoga could also enhance academic performance

Limitations of the Study

Limitations of this study include small number of samplesand lack of dedicated control group and methodologicaldifferences Further investigation can be done by employingpsychological tests to evaluate cognitive behavior

12 Computational and Mathematical Methods in Medicine

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

The authors acknowledge the Principal of PDA College ofEngineering Kalaburagi for deputingHNagendra to pursuePhD degree and Department of Electrical EngineeringIIT Roorkee for providing an opportunity under QualityImprovement Programme (QIP) They also acknowledge thestudents who participated in this study and give specialthanks to the yoga instructor

References

[1] P Sengupta ldquoHealth impacts of yoga and pranayama a state-of-the-art reviewrdquo International Journal of Preventive Medicinevol 3 no 7 pp 444ndash458 2012

[2] A Ross and S Thomas ldquoThe health benefits of yoga and exer-cise a review of comparison studiesrdquoThe Journal of Alternativeand Complementary Medicine vol 16 no 1 pp 3ndash12 2010

[3] P A Balaji S R Varne and S S Ali ldquoPhysiological effects ofyogic practices and transcendental meditation in health anddiseaserdquo North American Journal of Medical Sciences vol 4 no10 pp 442ndash448 2012

[4] A Bussing A Michalsen S B S Khalsa S Telles and K JSherman ldquoEffects of yoga on mental and physical health ashort summary of reviewsrdquo Evidence-based Complementary andAlternative Medicine vol 2012 Article ID 165410 7 pages 2012

[5] T N Sathyaprabha P Satishchandra C Pradhan et al ldquoModu-lation of cardiac autonomic balance with adjuvant yoga therapyin patients with refractory epilepsyrdquo Epilepsy and Behavior vol12 no 2 pp 245ndash252 2008

[6] S Telles N Singh and A Balkrishna ldquoHeart rate variabil-ity changes during high frequency yoga breathingand breathawarenessrdquo BioPsychoSocial Medicine vol 5 article 4 2011

[7] L Jatiya KUdupa andA B Bhavanani ldquoEffect of yoga trainingon handgrip respiratory pressures and pulmonary functionrdquoIndian Journal of Physiology and Pharmacology vol 47 no 4pp 387ndash392 2003

[8] D Nangia and R Malhotra ldquoYoga cognition and mentalhealthrdquo Journal of the IndianAcademy ofApplied Psychology vol38 no 2 pp 262ndash269 2012

[9] S Telles and P Sarang ldquoEffects of two yoga based relaxationtechniques on Heart Rate Variability (HRV)rdquo InternationalJournal of Stress Management vol 13 no 4 pp 460ndash475 2006

[10] S Telles R Nagarathna P R Vani and H R Nagendra ldquoAcombination of focusing and defocusing through yoga reducesoptical illusion more than focusing alonerdquo Indian Journal ofPhysiology and Pharmacology vol 41 no 2 pp 179ndash182 1997

[11] K K F Rocha A M Ribeiro K C F Rocha et al ldquoImprove-ment in physiological and psychological parameters after6months of yoga practicerdquo Consciousness and Cognition vol 21no 2 pp 843ndash850 2012

[12] R Khadka B H Paudel V P Sharma S Kumar and N Bhat-tacharya ldquoEffect of yoga on cardiovascular autonomic reactivityin essential hypertensive patientsrdquo Health Renaissance vol 8no 2 pp 102ndash109 2010

[13] L C M Vanderlei C M Pastre R A Hoshi T D de Carvalhoand M F de Godoy ldquoBasic notions of heart rate variabilityand its clinical applicabilityrdquo Brazilian Journal of CardiovascularSurgery vol 24 no 2 pp 205ndash217 2009

[14] M V Hoslashjgaard N-H Holstein-Rathlou E Agner and JK Kanters ldquoDynamics of spectral components of heart ratevariability during changes in autonomic balancerdquoTheAmericanJournal of PhysiologymdashHeart and Circulatory Physiology vol275 no 1 pp H213ndashH219 1998

[15] S Boonnithi and S Phongsuphap ldquoComparison of heart ratevariability measures for mental stress detectionrdquo in Proceedingsof the Computing in Cardiology (CinC rsquo11) pp 85ndash88 2011

[16] H Kobayashi K Ishibashi and H Noguchi ldquoHeart ratevariability an index for monitoring and analyzing humanautonomic activitiesrdquo Journal of Physiological Anthropology andApplied Human Science vol 18 no 2 pp 53ndash59 1999

[17] J Sztajzel ldquoHeart rate variability a noninvasive electrocardio-graphic method to measure the autonomic nervous systemrdquoSwiss Medical Weekly vol 134 no 35-36 pp 514ndash522 2004

[18] J Taelman S Vandeput A Spaepen and S van Huffel ldquoInflu-ence of mental stress on heart rate and heart rate variabilityrdquo inProceedings of the 4th European Conference of the InternationalFederation for Medical and Biological Engineering (IFMBE rsquo08)vol 22 pp 1366ndash1369 November 2008

[19] E Tharion S Parthasarathy and N Neelakantan ldquoShort-termheart rate variability measures in students during examina-tionsrdquo National Medical Journal of India vol 22 no 2 pp 63ndash66 2009

[20] Y Sun N Ye and X Xu ldquoEEG analysis of alcoholics andcontrols based on feature extractionrdquo in Proceedings of the 8thInternational Conference on Signal Processing (ICSP rsquo06) 2006

[21] C Y Chen W K Wong C D Kuo Y T Liao and MD Ke ldquoWavelet real time monitoring system a case studyof the musical influence on electroencephalographyrdquo WSEASTransactions on Systems vol 7 no 2 pp 56ndash62 2008

[22] C Parameswariah and M Cox ldquoFrequency characteristics ofwaveletsrdquo IEEE Power Engineering Review vol 22 no 1 p 722002

[23] A Holm K Lukander J Korpela M Sallinen and K M IMuller ldquoEstimating brain load from the EEGrdquo The ScientificWorld Journal vol 9 pp 639ndash651 2009

[24] J Gruzelier ldquoA theory of alphatheta neurofeedback creativeperformance enhancement long distance functional connectiv-ity and psychological integrationrdquo Cognitive Processing vol 10no 1 supplement pp 101ndash109 2009

[25] F G Freeman P J Mikulka L J Prinzel and M W ScerboldquoEvaluation of an adaptive automation system using three EEGindices with a visual tracking taskrdquo Biological Psychology vol50 no 1 pp 61ndash76 1999

[26] A F Rabbi K Ivanca A V Putnam A Musa C B Thadenand R Fazel-Rezai ldquoHuman performance evaluation based onEEG signal analysis a prospective reviewrdquo in Proceedings of the31st Annual International Conference of the IEEE Engineeringin Medicine and Biology Society (EMBC rsquo09) pp 1879ndash1882September 2009

[27] A Gevins M E Smith LMcEvoy andD Yu ldquoHigh-resolutionEEGmapping of cortical activation related to workingmemoryeffects of task difficulty type of processing and practicerdquoCerebral Cortex vol 7 no 4 pp 374ndash385 1997

[28] J T Coyne C Baldwin A Cole C Sibley and D M RobertsldquoApplying real time physiological measures of cognitive load

Computational and Mathematical Methods in Medicine 13

to improve trainingrdquo in Foundations of Augmented CognitionNeuroergonomics and Operational Neuroscience vol 5638 ofLecture Notes in Computer Science pp 469ndash478 SpringerBerlin Germany 2009

[29] G Bashein M L Nessly S W Bledsoe et al ldquoElectroen-cephalography during surgery with cardiopulmonary bypassand hypothermiardquo Anesthesiology vol 76 no 6 pp 878ndash8911992

[30] R J Barry A R Clarke S J Johnstone R McCarthy andM Selikowitz ldquoElectroencephalogram 120572120573 ratio and arousal inattention-deficithyperactivity disorder evidence of indepen-dent processesrdquoBiological Psychiatry vol 66 no 4 pp 398ndash4012009

[31] L Cao J Li Y Sun H Zhu and C Yan ldquoEEG-based vig-ilance analysis by using fisher score and PCA algorithmrdquo inProceedings of the 1st IEEE International Conference on Progressin Informatics and Computing (PIC rsquo10) pp 175ndash179 ShanghaiChina December 2010

[32] L I Aftanas and S A Golocheikine ldquoNon-linear dynamiccomplexity of the humanEEGduringmeditationrdquoNeuroscienceLetters vol 330 no 2 pp 143ndash146 2002

[33] M Balasubramaniam S Telles and P M Doraiswamy ldquoYogaon our minds a systematic review of yoga for neuropsychiatricdisordersrdquo Frontiers in Psychiatry vol 3 Article ID Article 117pp 1ndash16 2013

[34] B S Moon H C Lee Y H Lee J C Park I S Oh and JW Lee ldquoFuzzy systems to process ECG and EEG signals forquantification of the mental workloadrdquo Information Sciencesvol 142 no 1ndash4 pp 23ndash35 2002

[35] P Raghuraj A G Ramakrishnan H R Nagendra and S TellesldquoEffect of two selected yogic breathing techniques on heart ratevariabilityrdquo Indian Journal of Physiology and Pharmacology vol42 no 4 pp 467ndash472 1998

[36] J J Sollers III T W Buchanan S M Mowrer L K Hill and JFThayer ldquoComparison of the ratio of the standard deviation ofthe r-r interval and the rootmean squared successive differences(SDrMSSD) to the low frequency-to-high frequency (LFHF)ratio in a patient population and normal healthy controlsrdquoBiomedical Sciences Instrumentation vol 43 pp 158ndash163 2007

[37] C Zhao C Zheng M Zhao and J Liu ldquoPhysiological assess-ment of driving mental fatigue using wavelet packet energy andrandom forestsrdquo The American Journal of Biomedical Sciencesvol 2 no 3 pp 262ndash274 2010

[38] O V Grishin V G Grishin D Yu Uryumtsev S V Smirnovand I G Jilina ldquoMetabolic rate variability impact on verylow-frequency of heart rate variabilityrdquo World Applied SciencesJournal vol 19 no 8 pp 1133ndash1139 2012

[39] E Basar C Basar-Eroglu S Karakas and M SchurmannldquoGamma alpha delta and theta oscillations govern cognitiveprocessesrdquo International Journal of Psychophysiology vol 39 no2-3 pp 241ndash248 2000

[40] K C Khare and S K Nigam ldquoA study of electroencephalogramin meditatorsrdquo Indian Journal of Physiology and Pharmacologyvol 44 no 2 pp 173ndash178 2000

[41] J Jacobs and M J Kahana ldquoDirect brain recordings fueladvances in cognitive electrophysiologyrdquo Trends in CognitiveSciences vol 14 no 4 pp 162ndash171 2010

Submit your manuscripts athttpwwwhindawicom

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Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

MEDIATORSINFLAMMATION

of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Behavioural Neurology

EndocrinologyInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Disease Markers

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BioMed Research International

OncologyJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Oxidative Medicine and Cellular Longevity

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

PPAR Research

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Immunology ResearchHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal of

ObesityJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Computational and Mathematical Methods in Medicine

OphthalmologyJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Diabetes ResearchJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Research and TreatmentAIDS

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Gastroenterology Research and Practice

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Parkinsonrsquos Disease

Evidence-Based Complementary and Alternative Medicine

Volume 2014Hindawi Publishing Corporationhttpwwwhindawicom

Computational and Mathematical Methods in Medicine 9

Table 6 Mean powers of EEG frequency bands averaged across all the lobes of the brain before and after yoga intervention

EEG band powers120574 (120583V2Hz) 120573 (120583V2Hz) 120572 (120583V2Hz) 120579 (120583V2Hz) 120575 (120583V2Hz)

Yoga groupBefore yoga 380 plusmn 093 232 plusmn 049 395 plusmn 070 2136 plusmn 343 422 plusmn 042After yoga 365 plusmn 069 491 plusmn 163 567 plusmn 168 1588 plusmn 257 579 plusmn 106

Control groupBefore yoga 298 plusmn 136 386 plusmn 096 392 plusmn 097 1757 plusmn 254 446 plusmn 089After yoga 294 plusmn 133 372 plusmn 082 387 plusmn 090 2112 plusmn 387 437 plusmn 078

and cognition parietal lobe with visual perception recogni-tion information processing and spatial reasoning temporallobe with memory and processing of verbal and auditorysignals and occipital lobe with visual spatial processing andrecognition An increase of EEG frequency band powers inthese lobes indicates the enhancement of certain type ofcognitive skillsThe type of the cognitive skills developed canbe assessed based on increased or decreased EEG band powerin these lobesThemean absolute values of these band powersin various lobes of the brain are shown in Table 6

The increase of frontal 120579 band power indicates intellectualconcentration andmeditative state of relief from nervousnessand is negatively related with sympathetic activation Thisreflects a near relationship between autonomic functionactivity of medial frontal neural circuitry and probability ofcontrolling central nervous system (CNS) functions owing toyoga practice and meditation [12] 120572 waves are indicative ofincreased relaxed state ofmind and its bandpower is inverselyrelated to mental activity Yoga enhanced various cognitiveskills improved sense of wellbeing and responsiveness andenhanced cognitive functions as substantiated by increased120572 and 120573 band powers and various engagement indices Italso improves mental consciousness and achieves reductionin stress and strain and thus advocates complete health andwellbeing in an individual [40] Increase in 120573 band powerwould indicate a higher level of alertness and enhancedengagement task whereas increased band powers of 120572 and 120579would indicate decreased alertness and reduced engagementtask [25] The increase of 120573 power reflects improvement ofcertain cognitive functions such as memory and reactiontime That of 120572 and 120575 indicates synchronization of brainactivity The total EEG band power also increased in yogagroup compared to the control group

The ratio 120579120572 is associated with HR This ratio decreasedin all lobes of the brain indicating the relaxed state of sub-jectsThis reduction could be either increase of 120572 band poweror decrease of 120579 band power Since 120572 power increased in yogagroup this ratio decreased indicating enhancement of certaincognitive faculties (memory attention) and improvement inthe HRV These in turn indicate indirect improvement incertain cognitive functions such as reaction time The ratio120573120572 [25] is called arousal indexThis indicates level of arousalbased on interbeat intervals (IBI) activity Arousal level gt0indicates higher than normal arousal and lt0 indicates lowerthan normal arousal

This ratio increased (4711) in yoga group whiledecreased in control group (243) The increases of thisratio indicate enhanced cognitive functions such as attentionThe decreases of this ratio reflect reduction in the corecapabilities of cognitive functions This ratio increased in alllobes of the brain but the maximum increase was observedin parietal (7805) central (5312) and temporal (4504)lobes It increased to (3824) and (1976) in frontal andoccipital lobes respectively The ratio (120575 + 120579)120572 is calledexecutive load index [28] and is a measure of executive loador comprehension Positive value indicates increased loadand negative value indicates decreased load It reflects theoscillations in precise cortical network active among spatiallydisjoint brain compartment This ratio decreased (4098)in experimental group while it increased (1719) slightlyin control group The decrease in this ratio may be dueto increase in 120572 band power or reduced band power ofeither 120575 or 120579 or both It is observed that 120572 band power wasincreased in yoga practicing group This ratio was also founddecreased in all the lobes of the brain Another importantparameter 120579(fro)120572(par) [27] is called task load index Thisratio decreases in experimental group while it increases incontrol group It is evident from the relation that the ratiodecreases due to increase in 120572 band power These results areshown in Tables 7 and 8

The ratio 120579120573 indicates central nervous system (CNS)arousal [30] and increased ratio is marker of under arousalThis ratio decreased in yoga group The reductions in thisratio reflect the shift of 120572 and 120579 activity towards 120573 activityThe increased 120573 band powers indicate enhanced cognitiveperformance such as memory attention and concentrationThe ratio 120572120575 which is called ldquobrain perfusionrdquo index [29]was increased (46) in yoga practiced group This indicatessufficient amount of blood flow to the different parts ofthe brain among yoga group These in turn enhances thebetter functioning of the brain The ratio LFHF can beexpressed in terms of (120579 + 120575)(120572 + 120573) [29] Slower brainoscillations (120579 and 120575) harmonize considerable neuron groupsacross larger brain areas and faster oscillations (120572 and 120573)synchronize smaller focused neuronal assemblies [41]Whengroups of neurons oscillate together synchronously theymore effectively communicated with each other The index(120579 + 120575)(120572 + 120573) indicates sympathovagal balance of theautonomic nervous system (ANS) Lower ratios indicatebetter balance of ANSThis ratio decreased in yoga group but

10 Computational and Mathematical Methods in Medicine

Table 7 Cognitive index parameters of yoga group before and after yoga intervention Postintervention values are shown within theparenthesis

EEG indices Yoga groupFrontal Central Parietal Occipital Temporal

120579120572 4621 (2806) 4951 (2063) 5059 (2973) 8792 (4609) 4604 (2480)120572120579 0216 (0356) 0202 (0485) 0198 (0336) 0114 (0217) 0217 (0403)120573120572 0612 (0846) 0625 (0957) 0523 (0931) 0607 (0727) 0564 (0818)120573120579 0132 (0302) 0126 (0464) 0103 (0313) 0069 (0158) 0123 (0330)120573(120572 + 120579) 0109 (0222) 0105 (0312) 0086 (0234) 0062 (0130) 0101 (0235)120579(fro)120572(par) 4621 (2806) 4951 (2063) 5059 (2973) 8792 (4609) 4604 (2480)(120575 + 120579)120572 5590 (3926) 5964 (3200) 6168 (3961) 10112 (5907) 5614 (3243)sum(120575 + 120579)120572 = 46392 (27876)

Table 8 Global EEG band power ratios before and after yoga inter-vention

EEG indices Yoga group Control groupBefore yoga After yoga Before yoga After yoga

120579120572 5405 2800 4485 5460120572120579 0185 0357 0228 0183120573120572 0588 0865 0986 0962120573120579 0109 0309 0220 0176120573(120572 + 120579) 0092 0228 0180 0149120579(fro)120572(par) 5405 2800 4485 5460(120575 + 120579)120572 6472 3820 5623 6590sum(120575 + 120579)120572 46392 27876 40456 47080

Table 9 EEG indices and their values before and after yoga inter-vention

Parameters Yoga group ControlBefore After Before After

120572120575 0937 0980 0879 0885(120579 + 120575)(120572 + 120573) 408 205 332 289120572120573 170 116 10139 10394120575120579 0197 0364 0209 2488120579120573 9198 3235 5530 4721

did not change in control group The ratio 120572120573 [31] which iscalled desynchronization is used to analyze vigilance indexand 120575120579 is called synchronization The ratio 120572120573 decreasedwhich is desirable The increase 120573 of band power indicatesimproved cognitive performance Since the parameter is indenominator the ratio decreases when there is increasedcognitive performance However in control group this ratiowas slightly increased Another ratio 120575120579 was increasedrelatively by small amount in experimental group than thecontrol groupThe 120572120575 ratio was decreased in frontal centraland occipital lobes while it increased in parietal and temporallobes These results are shown in Tables 9 10 and 11

The relative EEG band powers of 120573 120572 and 120575 increasedin yoga group in all the lobes of the brain The increases ofthese band powers indicate improvement of certain cognitivefunctions such as memory attention executive functionsand concentration The increase of 120575 power and decrease of

1932 1958

8783

222914911860 1618

10558

21181189

0

20

40

60

80

100

120

PSD

(120583V2H

z)

BeforeAfter

120573 120572 120579 120575 120574

Figure 5 Global EEG band powers of control group before andafter intervention

120579 power indicate improvement in neural activityThe variousEEG band powers are shown in Figure 1

The total band power (global) of 120573 120572 and 120575 increasedamong yoga group The increased 120573 power was associatedwith enhanced cognitive performance such as improvedalertness The maximum 120573 power increased in frontal andcentral lobes of the brain This indicates the improvementin emotion process and cognition The increased 120572 anddecreased 120579 powers physiologically signify the enhancedvigilance and increased alertness level of subjects These areshown in Figure 2 The improvement in cognitive functionswas associated with increased power in high frequency band(120573) and reduction in low frequency band (120579) Therefore 120573120579ratio is suitable index to assess the improvement in cognitiveskills of the subjectsThe cognitive performance index 120573(120572 +120579) increased and ratio of sum of low frequency to sum of highfrequency (120579 + 120575)(120573 + 120572) was decreased among yoga groupwhich is shown in Figure 3

There were no significant changes in EEG band powersengagement indices total power and cognitive performancesindices among control group The various performancesparameters of control group are shown in Figures 4 5 6 and7

Computational and Mathematical Methods in Medicine 11

Table 10 EEG index values of yoga group in different lobes of the brain before and after yoga intervention Postintervention values are shownin parenthesis

Parameters Brain lobesFrontal Central Parietal Occipital Temporal

120572120575 1032 (0893) 0988 (0879) 0902 (1011) 0757 (0770) 0990 (1312)(120579 + 120575)(120572 + 120573) 3468 (0534) 3669 (0566) 4050 (0402) 6294 (0363) 3589 (0363)120572120573 1634 (2806) 1599 (2063) 1913 (2973) 1648 (4609) 1772 (2480)120575120579 0210 (0814) 0205 (0524) 0219 (0614) 0150 (0570) 0219 (0657)120579120573 7550 (3316) 7916 (2156) 9675 (3194) 14492 (6341) 8159 (3032)

Table 11 EEG index values of control group in different lobes of the brain before and after yoga intervention Postintervention values areshown in parenthesis

Parameters Brain lobesFrontal Central Parietal Occipital Temporal

120572120575 0914 (0944) 0940 (0940) 0760 (0760) 0825 (0825) 0930 (0931)(120579 + 120575)(120572 + 120573) 0424 (0356) 0326 (0261) 0271 (0241) 0262 (0218) 0486 (0438)120572120573 3428 (4186) 3711 (4891) 6412 (7311) 5513 (6817) 4385 (4970)120575120579 0716 (0741) 0445 (0445) 0524 (0523) 0409 (0409) 1433 (1433)120579120573 3269 (4185) 3958 (5251) 5747 (6647) 6633 (8531) 4235 (4839)

After yogaBefore yoga

736686

586694

576

737 776

585

752

571

0

1

2

3

4

5

6

7

8

9

Frontal Central Perietal Occipital Temporal

PSD

(120583V2H

z)

Figure 6 Global EEGband powers of control group in various lobesof the brain before and after intervention

4 Conclusions

The regular practices of yoga for a period of five months byyoung healthy engineering students enhance different typesof cognitive skills Apart from cognitive the yoga practiceresulted in many health benefits such as improvement inheart rate variability The ratio SDNNRMSSD increasedwhile the ratio LFHF decreasedThis indicates improvementin the parasympathetic activity and decrease in sympatheticactivity Hence the current results suggest that the practice ofyoga modifies the sympathovagal balance towards parasym-pathetic activation improved the heart rate variability andenhanced sense of wellbeing Since the study population isyoung healthy engineering graduates it would be interestingto investigate whether the yoga practice could result inimprovement in the academic performances

3319

0153

6593

2891

0174

5672

0

1

2

3

4

5

6

7

8

Enga

gem

ent i

ndex

val

ue

Before yogaAfter yoga

(120575 + 120579)(120572 + 120573) 120573(120572 + 120579) (120575 + 120579)120572

Figure 7 CNS activity engagement index and executive load indexof control group before and after intervention

In a nutshell it is proved beyond doubt that yogapractices resulted in effective improvements in physiologicalparameters indirectly improving psychological parametersand various cognitive functions The results of this studygreatly encourage further investigation to study whether thepractice of yoga could also enhance academic performance

Limitations of the Study

Limitations of this study include small number of samplesand lack of dedicated control group and methodologicaldifferences Further investigation can be done by employingpsychological tests to evaluate cognitive behavior

12 Computational and Mathematical Methods in Medicine

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

The authors acknowledge the Principal of PDA College ofEngineering Kalaburagi for deputingHNagendra to pursuePhD degree and Department of Electrical EngineeringIIT Roorkee for providing an opportunity under QualityImprovement Programme (QIP) They also acknowledge thestudents who participated in this study and give specialthanks to the yoga instructor

References

[1] P Sengupta ldquoHealth impacts of yoga and pranayama a state-of-the-art reviewrdquo International Journal of Preventive Medicinevol 3 no 7 pp 444ndash458 2012

[2] A Ross and S Thomas ldquoThe health benefits of yoga and exer-cise a review of comparison studiesrdquoThe Journal of Alternativeand Complementary Medicine vol 16 no 1 pp 3ndash12 2010

[3] P A Balaji S R Varne and S S Ali ldquoPhysiological effects ofyogic practices and transcendental meditation in health anddiseaserdquo North American Journal of Medical Sciences vol 4 no10 pp 442ndash448 2012

[4] A Bussing A Michalsen S B S Khalsa S Telles and K JSherman ldquoEffects of yoga on mental and physical health ashort summary of reviewsrdquo Evidence-based Complementary andAlternative Medicine vol 2012 Article ID 165410 7 pages 2012

[5] T N Sathyaprabha P Satishchandra C Pradhan et al ldquoModu-lation of cardiac autonomic balance with adjuvant yoga therapyin patients with refractory epilepsyrdquo Epilepsy and Behavior vol12 no 2 pp 245ndash252 2008

[6] S Telles N Singh and A Balkrishna ldquoHeart rate variabil-ity changes during high frequency yoga breathingand breathawarenessrdquo BioPsychoSocial Medicine vol 5 article 4 2011

[7] L Jatiya KUdupa andA B Bhavanani ldquoEffect of yoga trainingon handgrip respiratory pressures and pulmonary functionrdquoIndian Journal of Physiology and Pharmacology vol 47 no 4pp 387ndash392 2003

[8] D Nangia and R Malhotra ldquoYoga cognition and mentalhealthrdquo Journal of the IndianAcademy ofApplied Psychology vol38 no 2 pp 262ndash269 2012

[9] S Telles and P Sarang ldquoEffects of two yoga based relaxationtechniques on Heart Rate Variability (HRV)rdquo InternationalJournal of Stress Management vol 13 no 4 pp 460ndash475 2006

[10] S Telles R Nagarathna P R Vani and H R Nagendra ldquoAcombination of focusing and defocusing through yoga reducesoptical illusion more than focusing alonerdquo Indian Journal ofPhysiology and Pharmacology vol 41 no 2 pp 179ndash182 1997

[11] K K F Rocha A M Ribeiro K C F Rocha et al ldquoImprove-ment in physiological and psychological parameters after6months of yoga practicerdquo Consciousness and Cognition vol 21no 2 pp 843ndash850 2012

[12] R Khadka B H Paudel V P Sharma S Kumar and N Bhat-tacharya ldquoEffect of yoga on cardiovascular autonomic reactivityin essential hypertensive patientsrdquo Health Renaissance vol 8no 2 pp 102ndash109 2010

[13] L C M Vanderlei C M Pastre R A Hoshi T D de Carvalhoand M F de Godoy ldquoBasic notions of heart rate variabilityand its clinical applicabilityrdquo Brazilian Journal of CardiovascularSurgery vol 24 no 2 pp 205ndash217 2009

[14] M V Hoslashjgaard N-H Holstein-Rathlou E Agner and JK Kanters ldquoDynamics of spectral components of heart ratevariability during changes in autonomic balancerdquoTheAmericanJournal of PhysiologymdashHeart and Circulatory Physiology vol275 no 1 pp H213ndashH219 1998

[15] S Boonnithi and S Phongsuphap ldquoComparison of heart ratevariability measures for mental stress detectionrdquo in Proceedingsof the Computing in Cardiology (CinC rsquo11) pp 85ndash88 2011

[16] H Kobayashi K Ishibashi and H Noguchi ldquoHeart ratevariability an index for monitoring and analyzing humanautonomic activitiesrdquo Journal of Physiological Anthropology andApplied Human Science vol 18 no 2 pp 53ndash59 1999

[17] J Sztajzel ldquoHeart rate variability a noninvasive electrocardio-graphic method to measure the autonomic nervous systemrdquoSwiss Medical Weekly vol 134 no 35-36 pp 514ndash522 2004

[18] J Taelman S Vandeput A Spaepen and S van Huffel ldquoInflu-ence of mental stress on heart rate and heart rate variabilityrdquo inProceedings of the 4th European Conference of the InternationalFederation for Medical and Biological Engineering (IFMBE rsquo08)vol 22 pp 1366ndash1369 November 2008

[19] E Tharion S Parthasarathy and N Neelakantan ldquoShort-termheart rate variability measures in students during examina-tionsrdquo National Medical Journal of India vol 22 no 2 pp 63ndash66 2009

[20] Y Sun N Ye and X Xu ldquoEEG analysis of alcoholics andcontrols based on feature extractionrdquo in Proceedings of the 8thInternational Conference on Signal Processing (ICSP rsquo06) 2006

[21] C Y Chen W K Wong C D Kuo Y T Liao and MD Ke ldquoWavelet real time monitoring system a case studyof the musical influence on electroencephalographyrdquo WSEASTransactions on Systems vol 7 no 2 pp 56ndash62 2008

[22] C Parameswariah and M Cox ldquoFrequency characteristics ofwaveletsrdquo IEEE Power Engineering Review vol 22 no 1 p 722002

[23] A Holm K Lukander J Korpela M Sallinen and K M IMuller ldquoEstimating brain load from the EEGrdquo The ScientificWorld Journal vol 9 pp 639ndash651 2009

[24] J Gruzelier ldquoA theory of alphatheta neurofeedback creativeperformance enhancement long distance functional connectiv-ity and psychological integrationrdquo Cognitive Processing vol 10no 1 supplement pp 101ndash109 2009

[25] F G Freeman P J Mikulka L J Prinzel and M W ScerboldquoEvaluation of an adaptive automation system using three EEGindices with a visual tracking taskrdquo Biological Psychology vol50 no 1 pp 61ndash76 1999

[26] A F Rabbi K Ivanca A V Putnam A Musa C B Thadenand R Fazel-Rezai ldquoHuman performance evaluation based onEEG signal analysis a prospective reviewrdquo in Proceedings of the31st Annual International Conference of the IEEE Engineeringin Medicine and Biology Society (EMBC rsquo09) pp 1879ndash1882September 2009

[27] A Gevins M E Smith LMcEvoy andD Yu ldquoHigh-resolutionEEGmapping of cortical activation related to workingmemoryeffects of task difficulty type of processing and practicerdquoCerebral Cortex vol 7 no 4 pp 374ndash385 1997

[28] J T Coyne C Baldwin A Cole C Sibley and D M RobertsldquoApplying real time physiological measures of cognitive load

Computational and Mathematical Methods in Medicine 13

to improve trainingrdquo in Foundations of Augmented CognitionNeuroergonomics and Operational Neuroscience vol 5638 ofLecture Notes in Computer Science pp 469ndash478 SpringerBerlin Germany 2009

[29] G Bashein M L Nessly S W Bledsoe et al ldquoElectroen-cephalography during surgery with cardiopulmonary bypassand hypothermiardquo Anesthesiology vol 76 no 6 pp 878ndash8911992

[30] R J Barry A R Clarke S J Johnstone R McCarthy andM Selikowitz ldquoElectroencephalogram 120572120573 ratio and arousal inattention-deficithyperactivity disorder evidence of indepen-dent processesrdquoBiological Psychiatry vol 66 no 4 pp 398ndash4012009

[31] L Cao J Li Y Sun H Zhu and C Yan ldquoEEG-based vig-ilance analysis by using fisher score and PCA algorithmrdquo inProceedings of the 1st IEEE International Conference on Progressin Informatics and Computing (PIC rsquo10) pp 175ndash179 ShanghaiChina December 2010

[32] L I Aftanas and S A Golocheikine ldquoNon-linear dynamiccomplexity of the humanEEGduringmeditationrdquoNeuroscienceLetters vol 330 no 2 pp 143ndash146 2002

[33] M Balasubramaniam S Telles and P M Doraiswamy ldquoYogaon our minds a systematic review of yoga for neuropsychiatricdisordersrdquo Frontiers in Psychiatry vol 3 Article ID Article 117pp 1ndash16 2013

[34] B S Moon H C Lee Y H Lee J C Park I S Oh and JW Lee ldquoFuzzy systems to process ECG and EEG signals forquantification of the mental workloadrdquo Information Sciencesvol 142 no 1ndash4 pp 23ndash35 2002

[35] P Raghuraj A G Ramakrishnan H R Nagendra and S TellesldquoEffect of two selected yogic breathing techniques on heart ratevariabilityrdquo Indian Journal of Physiology and Pharmacology vol42 no 4 pp 467ndash472 1998

[36] J J Sollers III T W Buchanan S M Mowrer L K Hill and JFThayer ldquoComparison of the ratio of the standard deviation ofthe r-r interval and the rootmean squared successive differences(SDrMSSD) to the low frequency-to-high frequency (LFHF)ratio in a patient population and normal healthy controlsrdquoBiomedical Sciences Instrumentation vol 43 pp 158ndash163 2007

[37] C Zhao C Zheng M Zhao and J Liu ldquoPhysiological assess-ment of driving mental fatigue using wavelet packet energy andrandom forestsrdquo The American Journal of Biomedical Sciencesvol 2 no 3 pp 262ndash274 2010

[38] O V Grishin V G Grishin D Yu Uryumtsev S V Smirnovand I G Jilina ldquoMetabolic rate variability impact on verylow-frequency of heart rate variabilityrdquo World Applied SciencesJournal vol 19 no 8 pp 1133ndash1139 2012

[39] E Basar C Basar-Eroglu S Karakas and M SchurmannldquoGamma alpha delta and theta oscillations govern cognitiveprocessesrdquo International Journal of Psychophysiology vol 39 no2-3 pp 241ndash248 2000

[40] K C Khare and S K Nigam ldquoA study of electroencephalogramin meditatorsrdquo Indian Journal of Physiology and Pharmacologyvol 44 no 2 pp 173ndash178 2000

[41] J Jacobs and M J Kahana ldquoDirect brain recordings fueladvances in cognitive electrophysiologyrdquo Trends in CognitiveSciences vol 14 no 4 pp 162ndash171 2010

Submit your manuscripts athttpwwwhindawicom

Stem CellsInternational

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

MEDIATORSINFLAMMATION

of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Behavioural Neurology

EndocrinologyInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Disease Markers

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

BioMed Research International

OncologyJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Oxidative Medicine and Cellular Longevity

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

PPAR Research

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Immunology ResearchHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal of

ObesityJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Computational and Mathematical Methods in Medicine

OphthalmologyJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Diabetes ResearchJournal of

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Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Research and TreatmentAIDS

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Gastroenterology Research and Practice

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Parkinsonrsquos Disease

Evidence-Based Complementary and Alternative Medicine

Volume 2014Hindawi Publishing Corporationhttpwwwhindawicom

10 Computational and Mathematical Methods in Medicine

Table 7 Cognitive index parameters of yoga group before and after yoga intervention Postintervention values are shown within theparenthesis

EEG indices Yoga groupFrontal Central Parietal Occipital Temporal

120579120572 4621 (2806) 4951 (2063) 5059 (2973) 8792 (4609) 4604 (2480)120572120579 0216 (0356) 0202 (0485) 0198 (0336) 0114 (0217) 0217 (0403)120573120572 0612 (0846) 0625 (0957) 0523 (0931) 0607 (0727) 0564 (0818)120573120579 0132 (0302) 0126 (0464) 0103 (0313) 0069 (0158) 0123 (0330)120573(120572 + 120579) 0109 (0222) 0105 (0312) 0086 (0234) 0062 (0130) 0101 (0235)120579(fro)120572(par) 4621 (2806) 4951 (2063) 5059 (2973) 8792 (4609) 4604 (2480)(120575 + 120579)120572 5590 (3926) 5964 (3200) 6168 (3961) 10112 (5907) 5614 (3243)sum(120575 + 120579)120572 = 46392 (27876)

Table 8 Global EEG band power ratios before and after yoga inter-vention

EEG indices Yoga group Control groupBefore yoga After yoga Before yoga After yoga

120579120572 5405 2800 4485 5460120572120579 0185 0357 0228 0183120573120572 0588 0865 0986 0962120573120579 0109 0309 0220 0176120573(120572 + 120579) 0092 0228 0180 0149120579(fro)120572(par) 5405 2800 4485 5460(120575 + 120579)120572 6472 3820 5623 6590sum(120575 + 120579)120572 46392 27876 40456 47080

Table 9 EEG indices and their values before and after yoga inter-vention

Parameters Yoga group ControlBefore After Before After

120572120575 0937 0980 0879 0885(120579 + 120575)(120572 + 120573) 408 205 332 289120572120573 170 116 10139 10394120575120579 0197 0364 0209 2488120579120573 9198 3235 5530 4721

did not change in control group The ratio 120572120573 [31] which iscalled desynchronization is used to analyze vigilance indexand 120575120579 is called synchronization The ratio 120572120573 decreasedwhich is desirable The increase 120573 of band power indicatesimproved cognitive performance Since the parameter is indenominator the ratio decreases when there is increasedcognitive performance However in control group this ratiowas slightly increased Another ratio 120575120579 was increasedrelatively by small amount in experimental group than thecontrol groupThe 120572120575 ratio was decreased in frontal centraland occipital lobes while it increased in parietal and temporallobes These results are shown in Tables 9 10 and 11

The relative EEG band powers of 120573 120572 and 120575 increasedin yoga group in all the lobes of the brain The increases ofthese band powers indicate improvement of certain cognitivefunctions such as memory attention executive functionsand concentration The increase of 120575 power and decrease of

1932 1958

8783

222914911860 1618

10558

21181189

0

20

40

60

80

100

120

PSD

(120583V2H

z)

BeforeAfter

120573 120572 120579 120575 120574

Figure 5 Global EEG band powers of control group before andafter intervention

120579 power indicate improvement in neural activityThe variousEEG band powers are shown in Figure 1

The total band power (global) of 120573 120572 and 120575 increasedamong yoga group The increased 120573 power was associatedwith enhanced cognitive performance such as improvedalertness The maximum 120573 power increased in frontal andcentral lobes of the brain This indicates the improvementin emotion process and cognition The increased 120572 anddecreased 120579 powers physiologically signify the enhancedvigilance and increased alertness level of subjects These areshown in Figure 2 The improvement in cognitive functionswas associated with increased power in high frequency band(120573) and reduction in low frequency band (120579) Therefore 120573120579ratio is suitable index to assess the improvement in cognitiveskills of the subjectsThe cognitive performance index 120573(120572 +120579) increased and ratio of sum of low frequency to sum of highfrequency (120579 + 120575)(120573 + 120572) was decreased among yoga groupwhich is shown in Figure 3

There were no significant changes in EEG band powersengagement indices total power and cognitive performancesindices among control group The various performancesparameters of control group are shown in Figures 4 5 6 and7

Computational and Mathematical Methods in Medicine 11

Table 10 EEG index values of yoga group in different lobes of the brain before and after yoga intervention Postintervention values are shownin parenthesis

Parameters Brain lobesFrontal Central Parietal Occipital Temporal

120572120575 1032 (0893) 0988 (0879) 0902 (1011) 0757 (0770) 0990 (1312)(120579 + 120575)(120572 + 120573) 3468 (0534) 3669 (0566) 4050 (0402) 6294 (0363) 3589 (0363)120572120573 1634 (2806) 1599 (2063) 1913 (2973) 1648 (4609) 1772 (2480)120575120579 0210 (0814) 0205 (0524) 0219 (0614) 0150 (0570) 0219 (0657)120579120573 7550 (3316) 7916 (2156) 9675 (3194) 14492 (6341) 8159 (3032)

Table 11 EEG index values of control group in different lobes of the brain before and after yoga intervention Postintervention values areshown in parenthesis

Parameters Brain lobesFrontal Central Parietal Occipital Temporal

120572120575 0914 (0944) 0940 (0940) 0760 (0760) 0825 (0825) 0930 (0931)(120579 + 120575)(120572 + 120573) 0424 (0356) 0326 (0261) 0271 (0241) 0262 (0218) 0486 (0438)120572120573 3428 (4186) 3711 (4891) 6412 (7311) 5513 (6817) 4385 (4970)120575120579 0716 (0741) 0445 (0445) 0524 (0523) 0409 (0409) 1433 (1433)120579120573 3269 (4185) 3958 (5251) 5747 (6647) 6633 (8531) 4235 (4839)

After yogaBefore yoga

736686

586694

576

737 776

585

752

571

0

1

2

3

4

5

6

7

8

9

Frontal Central Perietal Occipital Temporal

PSD

(120583V2H

z)

Figure 6 Global EEGband powers of control group in various lobesof the brain before and after intervention

4 Conclusions

The regular practices of yoga for a period of five months byyoung healthy engineering students enhance different typesof cognitive skills Apart from cognitive the yoga practiceresulted in many health benefits such as improvement inheart rate variability The ratio SDNNRMSSD increasedwhile the ratio LFHF decreasedThis indicates improvementin the parasympathetic activity and decrease in sympatheticactivity Hence the current results suggest that the practice ofyoga modifies the sympathovagal balance towards parasym-pathetic activation improved the heart rate variability andenhanced sense of wellbeing Since the study population isyoung healthy engineering graduates it would be interestingto investigate whether the yoga practice could result inimprovement in the academic performances

3319

0153

6593

2891

0174

5672

0

1

2

3

4

5

6

7

8

Enga

gem

ent i

ndex

val

ue

Before yogaAfter yoga

(120575 + 120579)(120572 + 120573) 120573(120572 + 120579) (120575 + 120579)120572

Figure 7 CNS activity engagement index and executive load indexof control group before and after intervention

In a nutshell it is proved beyond doubt that yogapractices resulted in effective improvements in physiologicalparameters indirectly improving psychological parametersand various cognitive functions The results of this studygreatly encourage further investigation to study whether thepractice of yoga could also enhance academic performance

Limitations of the Study

Limitations of this study include small number of samplesand lack of dedicated control group and methodologicaldifferences Further investigation can be done by employingpsychological tests to evaluate cognitive behavior

12 Computational and Mathematical Methods in Medicine

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

The authors acknowledge the Principal of PDA College ofEngineering Kalaburagi for deputingHNagendra to pursuePhD degree and Department of Electrical EngineeringIIT Roorkee for providing an opportunity under QualityImprovement Programme (QIP) They also acknowledge thestudents who participated in this study and give specialthanks to the yoga instructor

References

[1] P Sengupta ldquoHealth impacts of yoga and pranayama a state-of-the-art reviewrdquo International Journal of Preventive Medicinevol 3 no 7 pp 444ndash458 2012

[2] A Ross and S Thomas ldquoThe health benefits of yoga and exer-cise a review of comparison studiesrdquoThe Journal of Alternativeand Complementary Medicine vol 16 no 1 pp 3ndash12 2010

[3] P A Balaji S R Varne and S S Ali ldquoPhysiological effects ofyogic practices and transcendental meditation in health anddiseaserdquo North American Journal of Medical Sciences vol 4 no10 pp 442ndash448 2012

[4] A Bussing A Michalsen S B S Khalsa S Telles and K JSherman ldquoEffects of yoga on mental and physical health ashort summary of reviewsrdquo Evidence-based Complementary andAlternative Medicine vol 2012 Article ID 165410 7 pages 2012

[5] T N Sathyaprabha P Satishchandra C Pradhan et al ldquoModu-lation of cardiac autonomic balance with adjuvant yoga therapyin patients with refractory epilepsyrdquo Epilepsy and Behavior vol12 no 2 pp 245ndash252 2008

[6] S Telles N Singh and A Balkrishna ldquoHeart rate variabil-ity changes during high frequency yoga breathingand breathawarenessrdquo BioPsychoSocial Medicine vol 5 article 4 2011

[7] L Jatiya KUdupa andA B Bhavanani ldquoEffect of yoga trainingon handgrip respiratory pressures and pulmonary functionrdquoIndian Journal of Physiology and Pharmacology vol 47 no 4pp 387ndash392 2003

[8] D Nangia and R Malhotra ldquoYoga cognition and mentalhealthrdquo Journal of the IndianAcademy ofApplied Psychology vol38 no 2 pp 262ndash269 2012

[9] S Telles and P Sarang ldquoEffects of two yoga based relaxationtechniques on Heart Rate Variability (HRV)rdquo InternationalJournal of Stress Management vol 13 no 4 pp 460ndash475 2006

[10] S Telles R Nagarathna P R Vani and H R Nagendra ldquoAcombination of focusing and defocusing through yoga reducesoptical illusion more than focusing alonerdquo Indian Journal ofPhysiology and Pharmacology vol 41 no 2 pp 179ndash182 1997

[11] K K F Rocha A M Ribeiro K C F Rocha et al ldquoImprove-ment in physiological and psychological parameters after6months of yoga practicerdquo Consciousness and Cognition vol 21no 2 pp 843ndash850 2012

[12] R Khadka B H Paudel V P Sharma S Kumar and N Bhat-tacharya ldquoEffect of yoga on cardiovascular autonomic reactivityin essential hypertensive patientsrdquo Health Renaissance vol 8no 2 pp 102ndash109 2010

[13] L C M Vanderlei C M Pastre R A Hoshi T D de Carvalhoand M F de Godoy ldquoBasic notions of heart rate variabilityand its clinical applicabilityrdquo Brazilian Journal of CardiovascularSurgery vol 24 no 2 pp 205ndash217 2009

[14] M V Hoslashjgaard N-H Holstein-Rathlou E Agner and JK Kanters ldquoDynamics of spectral components of heart ratevariability during changes in autonomic balancerdquoTheAmericanJournal of PhysiologymdashHeart and Circulatory Physiology vol275 no 1 pp H213ndashH219 1998

[15] S Boonnithi and S Phongsuphap ldquoComparison of heart ratevariability measures for mental stress detectionrdquo in Proceedingsof the Computing in Cardiology (CinC rsquo11) pp 85ndash88 2011

[16] H Kobayashi K Ishibashi and H Noguchi ldquoHeart ratevariability an index for monitoring and analyzing humanautonomic activitiesrdquo Journal of Physiological Anthropology andApplied Human Science vol 18 no 2 pp 53ndash59 1999

[17] J Sztajzel ldquoHeart rate variability a noninvasive electrocardio-graphic method to measure the autonomic nervous systemrdquoSwiss Medical Weekly vol 134 no 35-36 pp 514ndash522 2004

[18] J Taelman S Vandeput A Spaepen and S van Huffel ldquoInflu-ence of mental stress on heart rate and heart rate variabilityrdquo inProceedings of the 4th European Conference of the InternationalFederation for Medical and Biological Engineering (IFMBE rsquo08)vol 22 pp 1366ndash1369 November 2008

[19] E Tharion S Parthasarathy and N Neelakantan ldquoShort-termheart rate variability measures in students during examina-tionsrdquo National Medical Journal of India vol 22 no 2 pp 63ndash66 2009

[20] Y Sun N Ye and X Xu ldquoEEG analysis of alcoholics andcontrols based on feature extractionrdquo in Proceedings of the 8thInternational Conference on Signal Processing (ICSP rsquo06) 2006

[21] C Y Chen W K Wong C D Kuo Y T Liao and MD Ke ldquoWavelet real time monitoring system a case studyof the musical influence on electroencephalographyrdquo WSEASTransactions on Systems vol 7 no 2 pp 56ndash62 2008

[22] C Parameswariah and M Cox ldquoFrequency characteristics ofwaveletsrdquo IEEE Power Engineering Review vol 22 no 1 p 722002

[23] A Holm K Lukander J Korpela M Sallinen and K M IMuller ldquoEstimating brain load from the EEGrdquo The ScientificWorld Journal vol 9 pp 639ndash651 2009

[24] J Gruzelier ldquoA theory of alphatheta neurofeedback creativeperformance enhancement long distance functional connectiv-ity and psychological integrationrdquo Cognitive Processing vol 10no 1 supplement pp 101ndash109 2009

[25] F G Freeman P J Mikulka L J Prinzel and M W ScerboldquoEvaluation of an adaptive automation system using three EEGindices with a visual tracking taskrdquo Biological Psychology vol50 no 1 pp 61ndash76 1999

[26] A F Rabbi K Ivanca A V Putnam A Musa C B Thadenand R Fazel-Rezai ldquoHuman performance evaluation based onEEG signal analysis a prospective reviewrdquo in Proceedings of the31st Annual International Conference of the IEEE Engineeringin Medicine and Biology Society (EMBC rsquo09) pp 1879ndash1882September 2009

[27] A Gevins M E Smith LMcEvoy andD Yu ldquoHigh-resolutionEEGmapping of cortical activation related to workingmemoryeffects of task difficulty type of processing and practicerdquoCerebral Cortex vol 7 no 4 pp 374ndash385 1997

[28] J T Coyne C Baldwin A Cole C Sibley and D M RobertsldquoApplying real time physiological measures of cognitive load

Computational and Mathematical Methods in Medicine 13

to improve trainingrdquo in Foundations of Augmented CognitionNeuroergonomics and Operational Neuroscience vol 5638 ofLecture Notes in Computer Science pp 469ndash478 SpringerBerlin Germany 2009

[29] G Bashein M L Nessly S W Bledsoe et al ldquoElectroen-cephalography during surgery with cardiopulmonary bypassand hypothermiardquo Anesthesiology vol 76 no 6 pp 878ndash8911992

[30] R J Barry A R Clarke S J Johnstone R McCarthy andM Selikowitz ldquoElectroencephalogram 120572120573 ratio and arousal inattention-deficithyperactivity disorder evidence of indepen-dent processesrdquoBiological Psychiatry vol 66 no 4 pp 398ndash4012009

[31] L Cao J Li Y Sun H Zhu and C Yan ldquoEEG-based vig-ilance analysis by using fisher score and PCA algorithmrdquo inProceedings of the 1st IEEE International Conference on Progressin Informatics and Computing (PIC rsquo10) pp 175ndash179 ShanghaiChina December 2010

[32] L I Aftanas and S A Golocheikine ldquoNon-linear dynamiccomplexity of the humanEEGduringmeditationrdquoNeuroscienceLetters vol 330 no 2 pp 143ndash146 2002

[33] M Balasubramaniam S Telles and P M Doraiswamy ldquoYogaon our minds a systematic review of yoga for neuropsychiatricdisordersrdquo Frontiers in Psychiatry vol 3 Article ID Article 117pp 1ndash16 2013

[34] B S Moon H C Lee Y H Lee J C Park I S Oh and JW Lee ldquoFuzzy systems to process ECG and EEG signals forquantification of the mental workloadrdquo Information Sciencesvol 142 no 1ndash4 pp 23ndash35 2002

[35] P Raghuraj A G Ramakrishnan H R Nagendra and S TellesldquoEffect of two selected yogic breathing techniques on heart ratevariabilityrdquo Indian Journal of Physiology and Pharmacology vol42 no 4 pp 467ndash472 1998

[36] J J Sollers III T W Buchanan S M Mowrer L K Hill and JFThayer ldquoComparison of the ratio of the standard deviation ofthe r-r interval and the rootmean squared successive differences(SDrMSSD) to the low frequency-to-high frequency (LFHF)ratio in a patient population and normal healthy controlsrdquoBiomedical Sciences Instrumentation vol 43 pp 158ndash163 2007

[37] C Zhao C Zheng M Zhao and J Liu ldquoPhysiological assess-ment of driving mental fatigue using wavelet packet energy andrandom forestsrdquo The American Journal of Biomedical Sciencesvol 2 no 3 pp 262ndash274 2010

[38] O V Grishin V G Grishin D Yu Uryumtsev S V Smirnovand I G Jilina ldquoMetabolic rate variability impact on verylow-frequency of heart rate variabilityrdquo World Applied SciencesJournal vol 19 no 8 pp 1133ndash1139 2012

[39] E Basar C Basar-Eroglu S Karakas and M SchurmannldquoGamma alpha delta and theta oscillations govern cognitiveprocessesrdquo International Journal of Psychophysiology vol 39 no2-3 pp 241ndash248 2000

[40] K C Khare and S K Nigam ldquoA study of electroencephalogramin meditatorsrdquo Indian Journal of Physiology and Pharmacologyvol 44 no 2 pp 173ndash178 2000

[41] J Jacobs and M J Kahana ldquoDirect brain recordings fueladvances in cognitive electrophysiologyrdquo Trends in CognitiveSciences vol 14 no 4 pp 162ndash171 2010

Submit your manuscripts athttpwwwhindawicom

Stem CellsInternational

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

MEDIATORSINFLAMMATION

of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Behavioural Neurology

EndocrinologyInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Disease Markers

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

BioMed Research International

OncologyJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Oxidative Medicine and Cellular Longevity

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

PPAR Research

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Immunology ResearchHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal of

ObesityJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Computational and Mathematical Methods in Medicine

OphthalmologyJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Diabetes ResearchJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Research and TreatmentAIDS

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Gastroenterology Research and Practice

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Parkinsonrsquos Disease

Evidence-Based Complementary and Alternative Medicine

Volume 2014Hindawi Publishing Corporationhttpwwwhindawicom

Computational and Mathematical Methods in Medicine 11

Table 10 EEG index values of yoga group in different lobes of the brain before and after yoga intervention Postintervention values are shownin parenthesis

Parameters Brain lobesFrontal Central Parietal Occipital Temporal

120572120575 1032 (0893) 0988 (0879) 0902 (1011) 0757 (0770) 0990 (1312)(120579 + 120575)(120572 + 120573) 3468 (0534) 3669 (0566) 4050 (0402) 6294 (0363) 3589 (0363)120572120573 1634 (2806) 1599 (2063) 1913 (2973) 1648 (4609) 1772 (2480)120575120579 0210 (0814) 0205 (0524) 0219 (0614) 0150 (0570) 0219 (0657)120579120573 7550 (3316) 7916 (2156) 9675 (3194) 14492 (6341) 8159 (3032)

Table 11 EEG index values of control group in different lobes of the brain before and after yoga intervention Postintervention values areshown in parenthesis

Parameters Brain lobesFrontal Central Parietal Occipital Temporal

120572120575 0914 (0944) 0940 (0940) 0760 (0760) 0825 (0825) 0930 (0931)(120579 + 120575)(120572 + 120573) 0424 (0356) 0326 (0261) 0271 (0241) 0262 (0218) 0486 (0438)120572120573 3428 (4186) 3711 (4891) 6412 (7311) 5513 (6817) 4385 (4970)120575120579 0716 (0741) 0445 (0445) 0524 (0523) 0409 (0409) 1433 (1433)120579120573 3269 (4185) 3958 (5251) 5747 (6647) 6633 (8531) 4235 (4839)

After yogaBefore yoga

736686

586694

576

737 776

585

752

571

0

1

2

3

4

5

6

7

8

9

Frontal Central Perietal Occipital Temporal

PSD

(120583V2H

z)

Figure 6 Global EEGband powers of control group in various lobesof the brain before and after intervention

4 Conclusions

The regular practices of yoga for a period of five months byyoung healthy engineering students enhance different typesof cognitive skills Apart from cognitive the yoga practiceresulted in many health benefits such as improvement inheart rate variability The ratio SDNNRMSSD increasedwhile the ratio LFHF decreasedThis indicates improvementin the parasympathetic activity and decrease in sympatheticactivity Hence the current results suggest that the practice ofyoga modifies the sympathovagal balance towards parasym-pathetic activation improved the heart rate variability andenhanced sense of wellbeing Since the study population isyoung healthy engineering graduates it would be interestingto investigate whether the yoga practice could result inimprovement in the academic performances

3319

0153

6593

2891

0174

5672

0

1

2

3

4

5

6

7

8

Enga

gem

ent i

ndex

val

ue

Before yogaAfter yoga

(120575 + 120579)(120572 + 120573) 120573(120572 + 120579) (120575 + 120579)120572

Figure 7 CNS activity engagement index and executive load indexof control group before and after intervention

In a nutshell it is proved beyond doubt that yogapractices resulted in effective improvements in physiologicalparameters indirectly improving psychological parametersand various cognitive functions The results of this studygreatly encourage further investigation to study whether thepractice of yoga could also enhance academic performance

Limitations of the Study

Limitations of this study include small number of samplesand lack of dedicated control group and methodologicaldifferences Further investigation can be done by employingpsychological tests to evaluate cognitive behavior

12 Computational and Mathematical Methods in Medicine

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

The authors acknowledge the Principal of PDA College ofEngineering Kalaburagi for deputingHNagendra to pursuePhD degree and Department of Electrical EngineeringIIT Roorkee for providing an opportunity under QualityImprovement Programme (QIP) They also acknowledge thestudents who participated in this study and give specialthanks to the yoga instructor

References

[1] P Sengupta ldquoHealth impacts of yoga and pranayama a state-of-the-art reviewrdquo International Journal of Preventive Medicinevol 3 no 7 pp 444ndash458 2012

[2] A Ross and S Thomas ldquoThe health benefits of yoga and exer-cise a review of comparison studiesrdquoThe Journal of Alternativeand Complementary Medicine vol 16 no 1 pp 3ndash12 2010

[3] P A Balaji S R Varne and S S Ali ldquoPhysiological effects ofyogic practices and transcendental meditation in health anddiseaserdquo North American Journal of Medical Sciences vol 4 no10 pp 442ndash448 2012

[4] A Bussing A Michalsen S B S Khalsa S Telles and K JSherman ldquoEffects of yoga on mental and physical health ashort summary of reviewsrdquo Evidence-based Complementary andAlternative Medicine vol 2012 Article ID 165410 7 pages 2012

[5] T N Sathyaprabha P Satishchandra C Pradhan et al ldquoModu-lation of cardiac autonomic balance with adjuvant yoga therapyin patients with refractory epilepsyrdquo Epilepsy and Behavior vol12 no 2 pp 245ndash252 2008

[6] S Telles N Singh and A Balkrishna ldquoHeart rate variabil-ity changes during high frequency yoga breathingand breathawarenessrdquo BioPsychoSocial Medicine vol 5 article 4 2011

[7] L Jatiya KUdupa andA B Bhavanani ldquoEffect of yoga trainingon handgrip respiratory pressures and pulmonary functionrdquoIndian Journal of Physiology and Pharmacology vol 47 no 4pp 387ndash392 2003

[8] D Nangia and R Malhotra ldquoYoga cognition and mentalhealthrdquo Journal of the IndianAcademy ofApplied Psychology vol38 no 2 pp 262ndash269 2012

[9] S Telles and P Sarang ldquoEffects of two yoga based relaxationtechniques on Heart Rate Variability (HRV)rdquo InternationalJournal of Stress Management vol 13 no 4 pp 460ndash475 2006

[10] S Telles R Nagarathna P R Vani and H R Nagendra ldquoAcombination of focusing and defocusing through yoga reducesoptical illusion more than focusing alonerdquo Indian Journal ofPhysiology and Pharmacology vol 41 no 2 pp 179ndash182 1997

[11] K K F Rocha A M Ribeiro K C F Rocha et al ldquoImprove-ment in physiological and psychological parameters after6months of yoga practicerdquo Consciousness and Cognition vol 21no 2 pp 843ndash850 2012

[12] R Khadka B H Paudel V P Sharma S Kumar and N Bhat-tacharya ldquoEffect of yoga on cardiovascular autonomic reactivityin essential hypertensive patientsrdquo Health Renaissance vol 8no 2 pp 102ndash109 2010

[13] L C M Vanderlei C M Pastre R A Hoshi T D de Carvalhoand M F de Godoy ldquoBasic notions of heart rate variabilityand its clinical applicabilityrdquo Brazilian Journal of CardiovascularSurgery vol 24 no 2 pp 205ndash217 2009

[14] M V Hoslashjgaard N-H Holstein-Rathlou E Agner and JK Kanters ldquoDynamics of spectral components of heart ratevariability during changes in autonomic balancerdquoTheAmericanJournal of PhysiologymdashHeart and Circulatory Physiology vol275 no 1 pp H213ndashH219 1998

[15] S Boonnithi and S Phongsuphap ldquoComparison of heart ratevariability measures for mental stress detectionrdquo in Proceedingsof the Computing in Cardiology (CinC rsquo11) pp 85ndash88 2011

[16] H Kobayashi K Ishibashi and H Noguchi ldquoHeart ratevariability an index for monitoring and analyzing humanautonomic activitiesrdquo Journal of Physiological Anthropology andApplied Human Science vol 18 no 2 pp 53ndash59 1999

[17] J Sztajzel ldquoHeart rate variability a noninvasive electrocardio-graphic method to measure the autonomic nervous systemrdquoSwiss Medical Weekly vol 134 no 35-36 pp 514ndash522 2004

[18] J Taelman S Vandeput A Spaepen and S van Huffel ldquoInflu-ence of mental stress on heart rate and heart rate variabilityrdquo inProceedings of the 4th European Conference of the InternationalFederation for Medical and Biological Engineering (IFMBE rsquo08)vol 22 pp 1366ndash1369 November 2008

[19] E Tharion S Parthasarathy and N Neelakantan ldquoShort-termheart rate variability measures in students during examina-tionsrdquo National Medical Journal of India vol 22 no 2 pp 63ndash66 2009

[20] Y Sun N Ye and X Xu ldquoEEG analysis of alcoholics andcontrols based on feature extractionrdquo in Proceedings of the 8thInternational Conference on Signal Processing (ICSP rsquo06) 2006

[21] C Y Chen W K Wong C D Kuo Y T Liao and MD Ke ldquoWavelet real time monitoring system a case studyof the musical influence on electroencephalographyrdquo WSEASTransactions on Systems vol 7 no 2 pp 56ndash62 2008

[22] C Parameswariah and M Cox ldquoFrequency characteristics ofwaveletsrdquo IEEE Power Engineering Review vol 22 no 1 p 722002

[23] A Holm K Lukander J Korpela M Sallinen and K M IMuller ldquoEstimating brain load from the EEGrdquo The ScientificWorld Journal vol 9 pp 639ndash651 2009

[24] J Gruzelier ldquoA theory of alphatheta neurofeedback creativeperformance enhancement long distance functional connectiv-ity and psychological integrationrdquo Cognitive Processing vol 10no 1 supplement pp 101ndash109 2009

[25] F G Freeman P J Mikulka L J Prinzel and M W ScerboldquoEvaluation of an adaptive automation system using three EEGindices with a visual tracking taskrdquo Biological Psychology vol50 no 1 pp 61ndash76 1999

[26] A F Rabbi K Ivanca A V Putnam A Musa C B Thadenand R Fazel-Rezai ldquoHuman performance evaluation based onEEG signal analysis a prospective reviewrdquo in Proceedings of the31st Annual International Conference of the IEEE Engineeringin Medicine and Biology Society (EMBC rsquo09) pp 1879ndash1882September 2009

[27] A Gevins M E Smith LMcEvoy andD Yu ldquoHigh-resolutionEEGmapping of cortical activation related to workingmemoryeffects of task difficulty type of processing and practicerdquoCerebral Cortex vol 7 no 4 pp 374ndash385 1997

[28] J T Coyne C Baldwin A Cole C Sibley and D M RobertsldquoApplying real time physiological measures of cognitive load

Computational and Mathematical Methods in Medicine 13

to improve trainingrdquo in Foundations of Augmented CognitionNeuroergonomics and Operational Neuroscience vol 5638 ofLecture Notes in Computer Science pp 469ndash478 SpringerBerlin Germany 2009

[29] G Bashein M L Nessly S W Bledsoe et al ldquoElectroen-cephalography during surgery with cardiopulmonary bypassand hypothermiardquo Anesthesiology vol 76 no 6 pp 878ndash8911992

[30] R J Barry A R Clarke S J Johnstone R McCarthy andM Selikowitz ldquoElectroencephalogram 120572120573 ratio and arousal inattention-deficithyperactivity disorder evidence of indepen-dent processesrdquoBiological Psychiatry vol 66 no 4 pp 398ndash4012009

[31] L Cao J Li Y Sun H Zhu and C Yan ldquoEEG-based vig-ilance analysis by using fisher score and PCA algorithmrdquo inProceedings of the 1st IEEE International Conference on Progressin Informatics and Computing (PIC rsquo10) pp 175ndash179 ShanghaiChina December 2010

[32] L I Aftanas and S A Golocheikine ldquoNon-linear dynamiccomplexity of the humanEEGduringmeditationrdquoNeuroscienceLetters vol 330 no 2 pp 143ndash146 2002

[33] M Balasubramaniam S Telles and P M Doraiswamy ldquoYogaon our minds a systematic review of yoga for neuropsychiatricdisordersrdquo Frontiers in Psychiatry vol 3 Article ID Article 117pp 1ndash16 2013

[34] B S Moon H C Lee Y H Lee J C Park I S Oh and JW Lee ldquoFuzzy systems to process ECG and EEG signals forquantification of the mental workloadrdquo Information Sciencesvol 142 no 1ndash4 pp 23ndash35 2002

[35] P Raghuraj A G Ramakrishnan H R Nagendra and S TellesldquoEffect of two selected yogic breathing techniques on heart ratevariabilityrdquo Indian Journal of Physiology and Pharmacology vol42 no 4 pp 467ndash472 1998

[36] J J Sollers III T W Buchanan S M Mowrer L K Hill and JFThayer ldquoComparison of the ratio of the standard deviation ofthe r-r interval and the rootmean squared successive differences(SDrMSSD) to the low frequency-to-high frequency (LFHF)ratio in a patient population and normal healthy controlsrdquoBiomedical Sciences Instrumentation vol 43 pp 158ndash163 2007

[37] C Zhao C Zheng M Zhao and J Liu ldquoPhysiological assess-ment of driving mental fatigue using wavelet packet energy andrandom forestsrdquo The American Journal of Biomedical Sciencesvol 2 no 3 pp 262ndash274 2010

[38] O V Grishin V G Grishin D Yu Uryumtsev S V Smirnovand I G Jilina ldquoMetabolic rate variability impact on verylow-frequency of heart rate variabilityrdquo World Applied SciencesJournal vol 19 no 8 pp 1133ndash1139 2012

[39] E Basar C Basar-Eroglu S Karakas and M SchurmannldquoGamma alpha delta and theta oscillations govern cognitiveprocessesrdquo International Journal of Psychophysiology vol 39 no2-3 pp 241ndash248 2000

[40] K C Khare and S K Nigam ldquoA study of electroencephalogramin meditatorsrdquo Indian Journal of Physiology and Pharmacologyvol 44 no 2 pp 173ndash178 2000

[41] J Jacobs and M J Kahana ldquoDirect brain recordings fueladvances in cognitive electrophysiologyrdquo Trends in CognitiveSciences vol 14 no 4 pp 162ndash171 2010

Submit your manuscripts athttpwwwhindawicom

Stem CellsInternational

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

MEDIATORSINFLAMMATION

of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Behavioural Neurology

EndocrinologyInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Disease Markers

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

BioMed Research International

OncologyJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Oxidative Medicine and Cellular Longevity

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

PPAR Research

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Immunology ResearchHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal of

ObesityJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Computational and Mathematical Methods in Medicine

OphthalmologyJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Diabetes ResearchJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Research and TreatmentAIDS

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Gastroenterology Research and Practice

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Parkinsonrsquos Disease

Evidence-Based Complementary and Alternative Medicine

Volume 2014Hindawi Publishing Corporationhttpwwwhindawicom

12 Computational and Mathematical Methods in Medicine

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

The authors acknowledge the Principal of PDA College ofEngineering Kalaburagi for deputingHNagendra to pursuePhD degree and Department of Electrical EngineeringIIT Roorkee for providing an opportunity under QualityImprovement Programme (QIP) They also acknowledge thestudents who participated in this study and give specialthanks to the yoga instructor

References

[1] P Sengupta ldquoHealth impacts of yoga and pranayama a state-of-the-art reviewrdquo International Journal of Preventive Medicinevol 3 no 7 pp 444ndash458 2012

[2] A Ross and S Thomas ldquoThe health benefits of yoga and exer-cise a review of comparison studiesrdquoThe Journal of Alternativeand Complementary Medicine vol 16 no 1 pp 3ndash12 2010

[3] P A Balaji S R Varne and S S Ali ldquoPhysiological effects ofyogic practices and transcendental meditation in health anddiseaserdquo North American Journal of Medical Sciences vol 4 no10 pp 442ndash448 2012

[4] A Bussing A Michalsen S B S Khalsa S Telles and K JSherman ldquoEffects of yoga on mental and physical health ashort summary of reviewsrdquo Evidence-based Complementary andAlternative Medicine vol 2012 Article ID 165410 7 pages 2012

[5] T N Sathyaprabha P Satishchandra C Pradhan et al ldquoModu-lation of cardiac autonomic balance with adjuvant yoga therapyin patients with refractory epilepsyrdquo Epilepsy and Behavior vol12 no 2 pp 245ndash252 2008

[6] S Telles N Singh and A Balkrishna ldquoHeart rate variabil-ity changes during high frequency yoga breathingand breathawarenessrdquo BioPsychoSocial Medicine vol 5 article 4 2011

[7] L Jatiya KUdupa andA B Bhavanani ldquoEffect of yoga trainingon handgrip respiratory pressures and pulmonary functionrdquoIndian Journal of Physiology and Pharmacology vol 47 no 4pp 387ndash392 2003

[8] D Nangia and R Malhotra ldquoYoga cognition and mentalhealthrdquo Journal of the IndianAcademy ofApplied Psychology vol38 no 2 pp 262ndash269 2012

[9] S Telles and P Sarang ldquoEffects of two yoga based relaxationtechniques on Heart Rate Variability (HRV)rdquo InternationalJournal of Stress Management vol 13 no 4 pp 460ndash475 2006

[10] S Telles R Nagarathna P R Vani and H R Nagendra ldquoAcombination of focusing and defocusing through yoga reducesoptical illusion more than focusing alonerdquo Indian Journal ofPhysiology and Pharmacology vol 41 no 2 pp 179ndash182 1997

[11] K K F Rocha A M Ribeiro K C F Rocha et al ldquoImprove-ment in physiological and psychological parameters after6months of yoga practicerdquo Consciousness and Cognition vol 21no 2 pp 843ndash850 2012

[12] R Khadka B H Paudel V P Sharma S Kumar and N Bhat-tacharya ldquoEffect of yoga on cardiovascular autonomic reactivityin essential hypertensive patientsrdquo Health Renaissance vol 8no 2 pp 102ndash109 2010

[13] L C M Vanderlei C M Pastre R A Hoshi T D de Carvalhoand M F de Godoy ldquoBasic notions of heart rate variabilityand its clinical applicabilityrdquo Brazilian Journal of CardiovascularSurgery vol 24 no 2 pp 205ndash217 2009

[14] M V Hoslashjgaard N-H Holstein-Rathlou E Agner and JK Kanters ldquoDynamics of spectral components of heart ratevariability during changes in autonomic balancerdquoTheAmericanJournal of PhysiologymdashHeart and Circulatory Physiology vol275 no 1 pp H213ndashH219 1998

[15] S Boonnithi and S Phongsuphap ldquoComparison of heart ratevariability measures for mental stress detectionrdquo in Proceedingsof the Computing in Cardiology (CinC rsquo11) pp 85ndash88 2011

[16] H Kobayashi K Ishibashi and H Noguchi ldquoHeart ratevariability an index for monitoring and analyzing humanautonomic activitiesrdquo Journal of Physiological Anthropology andApplied Human Science vol 18 no 2 pp 53ndash59 1999

[17] J Sztajzel ldquoHeart rate variability a noninvasive electrocardio-graphic method to measure the autonomic nervous systemrdquoSwiss Medical Weekly vol 134 no 35-36 pp 514ndash522 2004

[18] J Taelman S Vandeput A Spaepen and S van Huffel ldquoInflu-ence of mental stress on heart rate and heart rate variabilityrdquo inProceedings of the 4th European Conference of the InternationalFederation for Medical and Biological Engineering (IFMBE rsquo08)vol 22 pp 1366ndash1369 November 2008

[19] E Tharion S Parthasarathy and N Neelakantan ldquoShort-termheart rate variability measures in students during examina-tionsrdquo National Medical Journal of India vol 22 no 2 pp 63ndash66 2009

[20] Y Sun N Ye and X Xu ldquoEEG analysis of alcoholics andcontrols based on feature extractionrdquo in Proceedings of the 8thInternational Conference on Signal Processing (ICSP rsquo06) 2006

[21] C Y Chen W K Wong C D Kuo Y T Liao and MD Ke ldquoWavelet real time monitoring system a case studyof the musical influence on electroencephalographyrdquo WSEASTransactions on Systems vol 7 no 2 pp 56ndash62 2008

[22] C Parameswariah and M Cox ldquoFrequency characteristics ofwaveletsrdquo IEEE Power Engineering Review vol 22 no 1 p 722002

[23] A Holm K Lukander J Korpela M Sallinen and K M IMuller ldquoEstimating brain load from the EEGrdquo The ScientificWorld Journal vol 9 pp 639ndash651 2009

[24] J Gruzelier ldquoA theory of alphatheta neurofeedback creativeperformance enhancement long distance functional connectiv-ity and psychological integrationrdquo Cognitive Processing vol 10no 1 supplement pp 101ndash109 2009

[25] F G Freeman P J Mikulka L J Prinzel and M W ScerboldquoEvaluation of an adaptive automation system using three EEGindices with a visual tracking taskrdquo Biological Psychology vol50 no 1 pp 61ndash76 1999

[26] A F Rabbi K Ivanca A V Putnam A Musa C B Thadenand R Fazel-Rezai ldquoHuman performance evaluation based onEEG signal analysis a prospective reviewrdquo in Proceedings of the31st Annual International Conference of the IEEE Engineeringin Medicine and Biology Society (EMBC rsquo09) pp 1879ndash1882September 2009

[27] A Gevins M E Smith LMcEvoy andD Yu ldquoHigh-resolutionEEGmapping of cortical activation related to workingmemoryeffects of task difficulty type of processing and practicerdquoCerebral Cortex vol 7 no 4 pp 374ndash385 1997

[28] J T Coyne C Baldwin A Cole C Sibley and D M RobertsldquoApplying real time physiological measures of cognitive load

Computational and Mathematical Methods in Medicine 13

to improve trainingrdquo in Foundations of Augmented CognitionNeuroergonomics and Operational Neuroscience vol 5638 ofLecture Notes in Computer Science pp 469ndash478 SpringerBerlin Germany 2009

[29] G Bashein M L Nessly S W Bledsoe et al ldquoElectroen-cephalography during surgery with cardiopulmonary bypassand hypothermiardquo Anesthesiology vol 76 no 6 pp 878ndash8911992

[30] R J Barry A R Clarke S J Johnstone R McCarthy andM Selikowitz ldquoElectroencephalogram 120572120573 ratio and arousal inattention-deficithyperactivity disorder evidence of indepen-dent processesrdquoBiological Psychiatry vol 66 no 4 pp 398ndash4012009

[31] L Cao J Li Y Sun H Zhu and C Yan ldquoEEG-based vig-ilance analysis by using fisher score and PCA algorithmrdquo inProceedings of the 1st IEEE International Conference on Progressin Informatics and Computing (PIC rsquo10) pp 175ndash179 ShanghaiChina December 2010

[32] L I Aftanas and S A Golocheikine ldquoNon-linear dynamiccomplexity of the humanEEGduringmeditationrdquoNeuroscienceLetters vol 330 no 2 pp 143ndash146 2002

[33] M Balasubramaniam S Telles and P M Doraiswamy ldquoYogaon our minds a systematic review of yoga for neuropsychiatricdisordersrdquo Frontiers in Psychiatry vol 3 Article ID Article 117pp 1ndash16 2013

[34] B S Moon H C Lee Y H Lee J C Park I S Oh and JW Lee ldquoFuzzy systems to process ECG and EEG signals forquantification of the mental workloadrdquo Information Sciencesvol 142 no 1ndash4 pp 23ndash35 2002

[35] P Raghuraj A G Ramakrishnan H R Nagendra and S TellesldquoEffect of two selected yogic breathing techniques on heart ratevariabilityrdquo Indian Journal of Physiology and Pharmacology vol42 no 4 pp 467ndash472 1998

[36] J J Sollers III T W Buchanan S M Mowrer L K Hill and JFThayer ldquoComparison of the ratio of the standard deviation ofthe r-r interval and the rootmean squared successive differences(SDrMSSD) to the low frequency-to-high frequency (LFHF)ratio in a patient population and normal healthy controlsrdquoBiomedical Sciences Instrumentation vol 43 pp 158ndash163 2007

[37] C Zhao C Zheng M Zhao and J Liu ldquoPhysiological assess-ment of driving mental fatigue using wavelet packet energy andrandom forestsrdquo The American Journal of Biomedical Sciencesvol 2 no 3 pp 262ndash274 2010

[38] O V Grishin V G Grishin D Yu Uryumtsev S V Smirnovand I G Jilina ldquoMetabolic rate variability impact on verylow-frequency of heart rate variabilityrdquo World Applied SciencesJournal vol 19 no 8 pp 1133ndash1139 2012

[39] E Basar C Basar-Eroglu S Karakas and M SchurmannldquoGamma alpha delta and theta oscillations govern cognitiveprocessesrdquo International Journal of Psychophysiology vol 39 no2-3 pp 241ndash248 2000

[40] K C Khare and S K Nigam ldquoA study of electroencephalogramin meditatorsrdquo Indian Journal of Physiology and Pharmacologyvol 44 no 2 pp 173ndash178 2000

[41] J Jacobs and M J Kahana ldquoDirect brain recordings fueladvances in cognitive electrophysiologyrdquo Trends in CognitiveSciences vol 14 no 4 pp 162ndash171 2010

Submit your manuscripts athttpwwwhindawicom

Stem CellsInternational

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

MEDIATORSINFLAMMATION

of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Behavioural Neurology

EndocrinologyInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Disease Markers

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

BioMed Research International

OncologyJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Oxidative Medicine and Cellular Longevity

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

PPAR Research

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Immunology ResearchHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal of

ObesityJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Computational and Mathematical Methods in Medicine

OphthalmologyJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Diabetes ResearchJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Research and TreatmentAIDS

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Gastroenterology Research and Practice

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Parkinsonrsquos Disease

Evidence-Based Complementary and Alternative Medicine

Volume 2014Hindawi Publishing Corporationhttpwwwhindawicom

Computational and Mathematical Methods in Medicine 13

to improve trainingrdquo in Foundations of Augmented CognitionNeuroergonomics and Operational Neuroscience vol 5638 ofLecture Notes in Computer Science pp 469ndash478 SpringerBerlin Germany 2009

[29] G Bashein M L Nessly S W Bledsoe et al ldquoElectroen-cephalography during surgery with cardiopulmonary bypassand hypothermiardquo Anesthesiology vol 76 no 6 pp 878ndash8911992

[30] R J Barry A R Clarke S J Johnstone R McCarthy andM Selikowitz ldquoElectroencephalogram 120572120573 ratio and arousal inattention-deficithyperactivity disorder evidence of indepen-dent processesrdquoBiological Psychiatry vol 66 no 4 pp 398ndash4012009

[31] L Cao J Li Y Sun H Zhu and C Yan ldquoEEG-based vig-ilance analysis by using fisher score and PCA algorithmrdquo inProceedings of the 1st IEEE International Conference on Progressin Informatics and Computing (PIC rsquo10) pp 175ndash179 ShanghaiChina December 2010

[32] L I Aftanas and S A Golocheikine ldquoNon-linear dynamiccomplexity of the humanEEGduringmeditationrdquoNeuroscienceLetters vol 330 no 2 pp 143ndash146 2002

[33] M Balasubramaniam S Telles and P M Doraiswamy ldquoYogaon our minds a systematic review of yoga for neuropsychiatricdisordersrdquo Frontiers in Psychiatry vol 3 Article ID Article 117pp 1ndash16 2013

[34] B S Moon H C Lee Y H Lee J C Park I S Oh and JW Lee ldquoFuzzy systems to process ECG and EEG signals forquantification of the mental workloadrdquo Information Sciencesvol 142 no 1ndash4 pp 23ndash35 2002

[35] P Raghuraj A G Ramakrishnan H R Nagendra and S TellesldquoEffect of two selected yogic breathing techniques on heart ratevariabilityrdquo Indian Journal of Physiology and Pharmacology vol42 no 4 pp 467ndash472 1998

[36] J J Sollers III T W Buchanan S M Mowrer L K Hill and JFThayer ldquoComparison of the ratio of the standard deviation ofthe r-r interval and the rootmean squared successive differences(SDrMSSD) to the low frequency-to-high frequency (LFHF)ratio in a patient population and normal healthy controlsrdquoBiomedical Sciences Instrumentation vol 43 pp 158ndash163 2007

[37] C Zhao C Zheng M Zhao and J Liu ldquoPhysiological assess-ment of driving mental fatigue using wavelet packet energy andrandom forestsrdquo The American Journal of Biomedical Sciencesvol 2 no 3 pp 262ndash274 2010

[38] O V Grishin V G Grishin D Yu Uryumtsev S V Smirnovand I G Jilina ldquoMetabolic rate variability impact on verylow-frequency of heart rate variabilityrdquo World Applied SciencesJournal vol 19 no 8 pp 1133ndash1139 2012

[39] E Basar C Basar-Eroglu S Karakas and M SchurmannldquoGamma alpha delta and theta oscillations govern cognitiveprocessesrdquo International Journal of Psychophysiology vol 39 no2-3 pp 241ndash248 2000

[40] K C Khare and S K Nigam ldquoA study of electroencephalogramin meditatorsrdquo Indian Journal of Physiology and Pharmacologyvol 44 no 2 pp 173ndash178 2000

[41] J Jacobs and M J Kahana ldquoDirect brain recordings fueladvances in cognitive electrophysiologyrdquo Trends in CognitiveSciences vol 14 no 4 pp 162ndash171 2010

Submit your manuscripts athttpwwwhindawicom

Stem CellsInternational

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

MEDIATORSINFLAMMATION

of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Behavioural Neurology

EndocrinologyInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Disease Markers

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

BioMed Research International

OncologyJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Oxidative Medicine and Cellular Longevity

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

PPAR Research

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Immunology ResearchHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal of

ObesityJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Computational and Mathematical Methods in Medicine

OphthalmologyJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Diabetes ResearchJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Research and TreatmentAIDS

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Gastroenterology Research and Practice

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Parkinsonrsquos Disease

Evidence-Based Complementary and Alternative Medicine

Volume 2014Hindawi Publishing Corporationhttpwwwhindawicom

Submit your manuscripts athttpwwwhindawicom

Stem CellsInternational

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

MEDIATORSINFLAMMATION

of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Behavioural Neurology

EndocrinologyInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Disease Markers

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

BioMed Research International

OncologyJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Oxidative Medicine and Cellular Longevity

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

PPAR Research

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Immunology ResearchHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal of

ObesityJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Computational and Mathematical Methods in Medicine

OphthalmologyJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Diabetes ResearchJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Research and TreatmentAIDS

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Gastroenterology Research and Practice

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Parkinsonrsquos Disease

Evidence-Based Complementary and Alternative Medicine

Volume 2014Hindawi Publishing Corporationhttpwwwhindawicom