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ECG Signal Being recorded from an adult human being.Signals includes several artifacts like Baseline fluctuations due to Pulmonary Activities and skin contraction expansion and Power Line frequency due to AC power Supply.Objective is to remove these basic artifacts with the simplest design procedure.FIR Filters being used almost completely to keep the linearity of phase intact.
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Abstract—ECG Signal is the measure of the Electrical Activity
of the heart. The electrical activities are detected through
electrodes attached to the surface of skin. For diagnosis and
proper interpretation from the ECG plot, the signal has to be free
from several artifacts which degrade the signal thus recorded. In
this paper, two of the phenomena are studied and attempted to
remove, viz. Baseline fluctuation-BLF (due to skin movement)
and Power line frequency interference 50Hz. Firstly the spectral
density is estimated for the power content of BLF. Based on the
study following filters are implemented viz. Multiple IIR notch
filter for removal of 50Hz frequency component (also harmonics
at 100Hz), Digital FIR High pass filter for attenuation of the
BLF. A linear phase response which is one of the primary
requirement of the ECG Signal is observed. The power line noise
in the ECG signal has also been considerably reduced.
Index Terms— Baseline Removal, Finite Impulse Response
Filter, IIR Filters, Spectral Analysis.
I. INTRODUCTION
HE Electrocardiogram (ECG) is process of recording the
electrical activity of the heart. A time plot of the recorded
ECG data sample as shown of the form Fig. 1, is of special
interest to the clinicians and doctors. The ECG signal is
recorded using several electrical devices and the signal is
captured by plotting the potential difference between the leads
of the ECG probe, which is kept in touch with the skin surface
of the patient. In the process of recording the signals, several
other forms of interfering signals are also recorded which
distorts the original signal, thereby showing an improper set of
samples. In order to extract useful information from the noisy
ECG signals, the raw ECG is pre-processed.[1]. Preprocessing
ECG signals helps in removing contaminants from the ECG
signals. Broadly speaking, ECG contaminants can be classified
into the following categories:
--Power line interference
--Electrode pop or contact noise
--Patient–electrode motion artifacts
--Electromyographic (EMG) noise
--Baseline wandering/Fluctuation.ss
Manuscript received December 4, 2012.
The Author is with the Department of Electrical and Computer Engineering,
University of Florida, Gainesville 32601, Florida, USA. (352-870-7208; e-
mail : [email protected])
The most prominent amongst the enlisted media of
contamination are the Baseline Fluctuation (BLF) and the
Power Line Interference (PLI). The BLF or Baseline Wander
as it may be called is inherent in the recorded signal due to the
muscular contraction and expansion of the patient. The second
artifact that is subjected to in this paper is the PLI, because of
the presence of 50Hz AC power line frequency components
and its higher Harmonics in the Electronic Systems. The goal
is attenuation of these prominent artifacts with special
emphasis to prevention of phase distortion.
Fig. 1.
PQRST Complex of an ideal ECG data recording.
Following the a small clinical interpretation of the Complex
shown in Fig. 1
--Atrial contractions shows P wave.
--Ventricular contractions show as QRS complex.
--Electrical activity produced when the ventricles are
recharging for the next contraction T wave. [3]
II. METHODOLOGY
A. Data Analysis
The sample has been recorded and experimented based on
the readings taken in EUROPE. Therefore the Power Line
frequency is 50Hz. The continuous time data has been
amplified through an Instrumentation Amplifier with a gain of
1,000 and digitized with a 12 bit A/D Converter. Sampling
frequency is maintained at 1,000 Hz. The time sample plot of
Baseline fluctuation attenuation and Power line
frequency removal in ECG Signal.
ANKAN ROYBARDHAN
T
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the signal is shown as in Fig. 2a. High frequency component is
present in the signal as depicted in the figure.
ECG standards shows that the maximum frequency
content in the ECG signal for a normal adult is about 150Hz.
(95% of the information is in-between 0.5Hz to 100Hz). So,
the signal is therefore down sampled to a sampling frequency
of 250Hz, the nyquist maximum frequency content being about
125Hz.
Fig. 2. ECG Signal Plot of the original sampled data.
B. Power Spectral Estimates and Analysis
Considering the Signal to be a Random Process, the time
domain sequence can be transformed to frequency domain
using Fourier Transform. The power content at each
frequency can be determined using the Power Spectrum
Density Plot.
(1)
2 (2)
Eq. (2) gives the power density spectrum at a given frequency
. This called the periodogram estimate. In other words, the
signal is considered to be Wise Sense Stationary, thus its
Power density spectrum is given by –
(3)
Which is the Fourier transform of the Auto-correlation
function of the input signal, X(n) in this case (Sampled version
of X(t)).[7] A plot of the spectral density has been shown in
Fig. 3, the estimate helps to determine the Power content at the
specific points of interests of that of BLF and PLI. Sampling
frequency is 250Hz, therefore 50Hz corresponds to 0.4π. Its
harmonics at 100Hz (0.8π) is also present in the signal. The
150Hz part(3rd
harmonic) is attenuated since the signal is down
sampled at 250Hz.
Fig. 3. Power Spectral Density of the down sampled data
The peaks at 0.4π, 0.8π are prominent in the figure. These
correspond to the PLI.
The frequency content for the BLF corresponds to a
maximum of 0.5Hz. But during Bradycardia, the heart
pumping may go down to 40beats/mins leading to 0.675Hz as
the lowest frequency content in the ECG Signal data. So, our
objective for BLF removal is to attenuate frequency contents
lesser than 0.5Hz (0.004π) by designing a High Pass filter. The
same is also evident by a peak shown in the lower part of
PSD.[4]
A passband of 0.5Hz (0.004π) till 105Hz (0.84 π) is
attained, since the maximum information is limited between
0.5Hz through 100Hz. Frequency higer than 0.84 π is thus
attenuated by passing through a Low Pass Filter.
III. FILTER DESIGN ALGORITHM
The objective is to preserve the phase response of the data
recorded. So, the use of FIR filter is of main concern in this
paper. FIR Symmetric filter co-efficients are calculated by
firstly approximating a window, where the signal is passed
through and arbitrarily truncate and shift (to make it causal)
the window length so as to get the best possible frequency
response of the filtered output. It has been observed that filter
co-efficients and thus the filter order pertaining to this
windowing technique results in order of filter to approximately
1500 to get the desired cutoff. [2]
(4)
where ,
(5)
[5]
The Parks-McClellan algorithm is therefore chosen to design
the High Pass and the Low Pass filter. The PM Filter is an
iterative algorithm for finding the optimal Chebyshev finite
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impulse response (FIR) filter. This means, due to the inherent
ripple quality of Chebyshev design, the PM filter also comes
with pass band and stop band ripple. The reason to choose PM
filter is that, with a given filter specifications viz. band
attenuations, least filter co-efficients and best tradeoff between
Mainlobe width and side lobe height, the iterative algorithm
helps calculating the least order of the FIR filter.
To remove PLI frequency content, we use 02 nos. 2nd
order
IIR notch filters with specifications as mentioned in the
subsequent design section of this paper.
A. Design of Digital Filters.
1. Design of Low Pass Filter- The frequency content
above 105Hz (0.84 π) is removed by passing the down
sampled version of the signal through a Low Pass filter of
cutoff frequency at 106.25Hz (0.86 π) with 217 order. The
frequency reponse of the filter is shown in fig. 4.
Fig. 4. Parks-McClellan Low Pass filter with cutoff at 0.86π.
2. Design of High Pass Filter- The pass-band of 0.5Hz to
100Hz is preserved as it is. A high-pass filter with transition
band of 0.25Hz to 0.5Hz (0.002π to 0.004π) is designed with
Parks-McClellan algorithm. The filter order comes up to be
1156. The frequency response is shown in fig. 5
Fig. 5. Parks-McClellan High Pass filter for BLF removal.
3. IIR Notch – The wires carrying the electrical pulses
from the patient’s body till the recording device is prone to the
power line frequency interference. The use of IIR notch filter
is justified based on the unsatisfactory performance shown by
Equiripple FIR multi band stop filter. Firstly, the filter order
goes up to the order of 800 for a sharp cutoff at 50Hz and its
harmonics at 100Hz, and secondly, the ripples in the pass-band
induces humming in the signal information part.
2 notch filters, one at 50Hz and one at 100Hz are applied to
attenuate the PLI at 50Hz and its harmonics as well. The
frequency response of each notch filter is shown in fig. 6a and
fig. 6b
Fig. 6a. IIR Notch filter with cutoff at 0.4π and -3dB bandwidth of 2Hz.
Fig. 6a. IIR Notch filter with cutoff at 0.8π and -3dB bandwidth of 2Hz
Here is a tradeoff been presented between the usage of IIR
notch and FIR notch. With FIR notch of following filter
specifications, we get the filter frequency response as shown in
fig. 7
s1=0.388 π, p1=0.392 π, p2=0.408π, s2=0.412 π,
These frequencies correspond to 48.5Hz, 49Hz, 51Hz,
51.5Hz. The filter order comes up to be 918 using the Formula
given as eq. (4). We observe in the fig. 7. that even though the
ripples being quite low in pass-band, the filtered output using
the FIR filter is not as prominent as by using IIR. In addition
to it, this sharp cutoff at 50 Hz and its harmonics calls for such
a high order of FIR filter. A comparison has been drawn
between the filtered output using an IIR and FIR which has
been depicted in fig. 8a and fig. 8b.
4
.
Fig 8a. IIR 2nd order Notch filter at 0.4π (50Hz) and 0.8π (100Hz)
Fig 8b. FIR 918 order Notch filter at 0.4π (50Hz) and 0.8π (100Hz)
It is clearly observed that frequency content around 50Hz is
attenuated (Notched) to a major extent and such a high order
FIR filter is preferable avoided when such a sharp cutoff
response is of major concern.
An algorithm has been devised for such filtering process
which is shown in fig. 9. Where firstly Signal is down-sampled
to 250Hz, then it is low pass, so as to attenuate the frequency
content above 105Hz. This is quite justified since, from the
data and the abstract presented, the signal is considered to be
band limited and thereby down sampling to such extent will
not necessarily introduce aliasing. Although, essentially the
higher frequency content does not contains information, so it is
attenuated through a low pass here. Next, the signal is passed
through 2 IIR notches to remove the PLI frequencies. Finally,
the BLF is suppressed by implementing an FIR High pass filter
with a cutoff frequency around 0.5Hz.
Experimentations have shown that instead, using IIR
Chebyshev filter of order 7, the time plot of the output is a
close approximation of the required PQRST complex. This
response is obtained at the cost of distorting the phase of the
ECG signal thereby introducing different group delay for
different frequencies. Also, in literature, several other
sophisticated methods has been proposed for removal of PLI
and BLF viz. Wavelet Co-efficient method[8], Simplified
Lattice based adaptive filter [9], Subtraction [10], PLI
detector[11] etc. which primarily stresses upon symmetrical
impulse response filters with much lower order.
Studying the pole zero plot of the IIR notch that is used,
shows, there are 2 complex conjugate poles and zeros. The
zeros in the unit circle is at angles of (50Hz) and
(100Hz). The steep ness of the notch filter is controlled
by the proximity of the poles to the zeroes.
(6)
, Gain considered being unity.
Here, =72o
for =0.4π and =144o for =0.8π. fig. 9a,b
shows the pole zero plot of the notch filters.
Fig 9a. IIR 2nd order Notch filter at 0.4π (50Hz) Pole zero plot.
Fig 9b. IIR 2nd order Notch filter at 0.8π (100Hz) Pole zero plot
The in the second notch filter is different from that used in
notch1. The motive is, if we closely observe fig. 8a, the
frequency content around 50Hz has peaky distribution. Having
a sharp notch at that location will attenuate the 50Hz, but will
show the nearby frequency response as in fig. 8b. So, we have
less sharper -3dB band with for 50Hz attenuation as compared
to that in 100Hz.
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After applying the LPF, Notch and the HPF, a set of
following responses we get from fig. 10, 11, 12,13.
Fig 10. Original Signal (Fs=1000Hz) frequency response. Peaks at 0.1π,0.2π,
0.3π, 0.4π etc.
Fig 11. Down sampled signal (Fs=250Hz) frequency response Peaks at 0.4π,
0.8π.
Fig 12. Signal Passed through 2 Notch filter and LPF filter. Freq. resp. Notch
at 0.4π and 0.8π
Fig 13. Filtered signal passed through HPF for BLF removal.
The power spectral density shows the proper attenuation of the
BLF and PLI as in fig. 14a,14b.
Fig 14a. PSD of the downsampled signal. Noise at 0.5Hz, 50Hz and 100Hz.
Fig 14b. PSD of the filtered signal. BLF and PLI removed.
Clearly, the spectrum density at normalized frequency at
0.4π and 0.8π (PLI) and frequency content less than 0.004π
(0.5Hz BLF) are smoothened. A sharp dip at frequencies
above 0.84π (105Hz) is due to Low pass filter which removed
unnecessary high frequency content, which automatically
removed the most prominent (3rd
harmonic at 150Hz) PLI
harmonic.
For a heart rate of 40 bpm, the RR cycle (𝑇) is 1.5 s and the
first harmonic has a frequency of (1/1.5) 0.67 Hz. The
remaining harmonics have frequencies that are integer
multiples of this fundamental frequency (in this case, the
second harmonic 0 . 6 7 × 2 = 1 . 3 4 Hz, the third harmonic 0 .
6 7 × 3 = 2 . 0 1 Hz, etc.). According to this and assuming that
physiological heart rates are normally above 40 bpm, no
biological components or signals attributable to an ECG will
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exist below 0.67 Hz. So cutoff of 0.5Hz is chosen to be
correct.
IV. RESULTS
Following is a tabulated (Table 1) data sheet of the
specifications been followed for designing the above
mentioned filters – TABLE I
FILTER DESIGN SPECIFICATIONS-ECG SIGNAL PROCESSING
Symbol
Description Data
Fs1 Original Sampling Frequency
1000Hz
Fs Downsampled Frequency
250Hz (Normalized to
LOW PASS FILTER SPECIFICATIONS
Ftype FIR Parks-McClellan 217 Order
Cutoff Frequency
105Hz (Normalized to 0.84 )
Stopband Frequency 110Hz (Normalized to 0.88 )
Passband ripple 0.001
Stopband ripple 0.001 (-60dB)
NOTCH FILTER SPECIFICATIONS (PLI removal)
Ftype IIR Notch 2
Cutoff Frequency 1
50Hz (Normalized to 0.4 )
1 -3dB Cutoff 4Hz (Normalized to 0.0032 )
Cutoff Frequency 2
50Hz (Normalized to 0.4 )
2 -3dB Cutoff 3Hz (Normalized to 0.0024 )
HIGH PASS FILTER SPECIFICATIONS (BLF removal)
Ftype FIR Parks-McClellan 1156 Order
Cutoff Frequency
0.5Hz (Normalized to 0.004 )
Stopband Frequency 0.25Hz (Normalized to 0.002 )
Passband ripple 0.1
Stopband ripple 0.02 (-34dB)
The Passband ripple in High pass filter is sufficiently large
as compared to that for Low pass filter, since having a stricter
attenuation in Passband for HPF, calls for FIR filter order of
2100. The performance is not satisfactory at the cost of 2100
order FIR filter. Stopband attenuation of the HPF is kept
considerably low, since having attenuation of the order of -
40dB or -50db, the order of the filter shoots up again to 1900
and the PQ complex of the time plot is disrupted. So, a trade-
off occurs for this critical BLF removal filter.
Fig. 15 shows the time plot of the downsampled signal. A
zoomed version of the signal is shown in the figure, where the
signal mixed with PLI and BLF is prominent. Fig. 16 shows
the filtered output signal. Note, with such traded off filtered
specifications, the PQ complex is preserved to a major extent.
Also, the ST complex is clear High frequency content is
removed by the LPF and the intermediate PLI is also removed.
All filtration causes attenuation (amplitude response,
decrease of sinusoidal wave peak-to-peak amplitude) and/or
phase shifts (phase response, phase shifting of the waves) that
will affect one or other components according to the cut-off
frequency of the filter used (Figure 2). Attenuations or phase
shifts are produced from the cut-off frequency up to
approximately 10 times this value. In our case, the attenuation
caused by high-pass filtering with 0.5 Hz is minimal and only
affects the first harmonic.
Fig 15. Time Plot of the Original Signal
Fig 16. Time Plot of Filtered ECG Signal.
Fig 17. PQRST of the filtered Signal indicated.
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V. CONCLUSION
A filter with linear phase is desirable in order to avoid phase
distortion that can alter various temporal relationships in the
cardiac cycle. The use of IIR filters obviously reduced the
number of co-efficients of the filter, but introduces several
drawbacks –
--Difficult to realize in real time
--At higher Sampling rates, the application becomes
difficult, since the poles moves close to unit circle,
resulting in instability.
Moreover, Linear Phase Filtering is highly required to
preserve the ST Segment of the ECG Signal. [12]. In practice,
in case of IIR filters, they are using as forward backward
configuration to get a zero phase response and magnitude
response equivalent to that of FIR Filters. [13]
Fig 18. Power Spectral Density of the filtered signal using IIR Filter.
PSD of the IIR filtered signal is compared with FIR filtered
signal (fig. 14b). The lower frequency content is pre-dominant.
This IIR has the same passband and stopband attenuation with
Elliptic Filter of order 6. 50Hz PLI is still present.
With filter order below 1000, the PQ and the ST complex is
quite unclear and this poses a serious implication to the
interpretation
In contrast, if we choose 0.05 Hz as cutoff for high-pass
filters, it produce phase-shift harmonics up to approximately
0.5 Hz, a range where no intrinsic bioelectric signals exist,
and, therefore, the shape of the ST segment remains unaffected
(the first harmonic of our ECG was found at 0.9 Hz). But,
eventually, in the system presented in this paper, no
sophisticated instruments are used to reject other noises as
presented in Introducing section, having a stricter cutoff shoots
up the order of the FIR filter to about 2450, which is much
more complex, simulation takes sufficiently large time and
results are similar to what has been observed in this case
(Results has been analyzed with Personal PC screen
resolution.).[14]
The trade of between the IIR notch and FIR has been
discussed with illustrations as in fig. 8a and 8b, which shows
with an order of 918 FIR, a bandwidth of about 8-10Hz is
being attenuated in the region of 50Hz. IIR notch in that case,
shows fine performance with respect to sharp dip in the 50Hz
and 100Hz region without affecting much of the important
information.
VI. REFERENCES
[1] LabVIEW for ECG Signal Processing-National Instruments. Document
Type: Tutorial; Publish Date: Aug 16, 2012
[2] 1L Harika Bommadevara, 2 B. Surya Prasada Rao, 3 P.Rajesh kumar, 4
P.Rajesh Kumar “Interference Reduction in ECG using Digital FIR Filters”
ISSN : 2230-7109(Online) | ISSN : 2230-9543(Print) , India.
[3] Ambulance technician study ,
http://www.ambulancetechnicianstudy.co.uk/ecgbasics.html#.ULsjj4NlWSo
[4] LEIF SO¨ RNMO, Lund University, Sweden, PABLO LAGUNA,
Zaragoza University, Spain “ELECTROCARDIOGRAM (ECG) SIGNAL
PROCESSING” Wiley Encyclopedia of Biomedical Engineering, Copyright
& 2006 John Wiley & Sons, Inc
[5] Alan V. Oppenheim, Ronal W. Schafer, John R. Buck, “Discrete Time
Signal Processing” 2nd Edition Pearson Publications.
[6] http://en.wikipedia.org/wiki/Parks-McClellan_filter_design_algorithm
[7] Biomedical Signal and Image Processing Second Edition
By Kayvan Najarian, Robert Splinter.
[8] INSTITUTE OF PHYSICS PUBLISHING PHYSIOLOGICAL
MEASUREMENT Physiol. Meas. 26 (2005) R155–R199 doi:10.1088/0967-
3334/26/5/R01.
[9] Dhillon, S.S., Chakrabarti, S, Dept. of Electr. Eng., Indian Inst. of
Technol., Kharagpur,India “Power line interference removal from
electrocardiogram using a simplified lattice based adaptive IIR notch filter”
IEEE-Explore Digital Library.
[10] Mihov, G. , Dept. of Electron. Eng., Tech. Univ. of Sofia, Sofia,
Bulgaria “Subtraction procedure for removing powerline interference from
ECG: Dynamic threshold linearity criterion for interference suppression” ,
IEEE Explore Digital Library.
[11] US National Library of Medicine National Institute of Health "Power-
line interference detection and suppression in ECG signal processing” IEEE
Trans Biomed Eng. 2008 Jan;55(1):354-7.
[12] S Hargittai, Innomed Medical Inc, Budapest, Hungary “Efficient and
Fast ECG Baseline Wander Reduction without Distortion of Important
Clinical Information”
[13] V´ıctor Barbero Romero; Profesor director: David Atienza Alonso;
Profesora colaboradora: Nadia Khaled, UC3M, Madrid “ECG baseline
wander removal and noise suppression analysis in an embedded platform”.
[14] “High-Bandpass Filters in Electrocardiography: Source of Error in the
Interpretation of the ST Segment.” ISRN Cardiology; Volume 2012 (2012),
Article ID 706217, 10 pages; doi:10.5402/2012/706217
Fig. 19a. PQRST with FIR filter
order 1156
Fig. 19b. PQRST with FIR
filter order 900
Fig. 19a. PQRST with FIR filter order 750