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Sensors and Actuators A 180 (2012) 137– 147

Contents lists available at SciVerse ScienceDirect

Sensors and Actuators A: Physical

jo u rn al hom epage: www.elsev ier .com/ locate /sna

n ultra-wideband wireless body area network: Evaluation in static and dynamichannel conditions

hee Keong Hoa, Terence S.P. Seeb, Mehmet R. Yucec,∗

School of Electrical Engineering and Computer Science, University of Newcastle, Callaghan, NSW 2308, AustraliaInstitute for Infocomm Research, 1 Fusionopolis Way, #21-01 Connexis, Singapore 138632, SingaporeDepartment of Electrical and Computer Systems Engineering, Monash University, Vic. 3800, Australia

r t i c l e i n f o

rticle history:eceived 14 December 2011eceived in revised form 26 March 2012ccepted 29 March 2012vailable online 23 April 2012

eywords:ireless body area network

ltra wideband sensor networkedical sensor network

a b s t r a c t

Wireless body area network is a collection of wearable wireless sensors placed around or in a humanbody that are used to monitor important information from a human body. A receiver (i.e. control unit)is required to connect these sensors to remote locations (i.e. hospital database and call centres). In thiswork an ultra-wideband (UWB) body sensor node has been designed and tested to analyze the realisticperformance of a UWB-based wireless body area network. The results indicate that the locations of sensorsand the control unit on a human body play an important role on the performance of the wireless bodyarea network system. The work herein also investigates optimal receiver positions for different sensorconfigurations. The results are evaluated in both static and dynamic channel conditions based on datatransmission from the UWB sensor node developed for wireless body area network applications. Fourcommon sensor positions, namely the chest, head, wrist and waist and three receiver positions-chest,waist and arm are considered. The experiment is conducted in an Anechoic chamber to minimize the

effects of the environment. In the static experiment, the subject under test remains motionless for theentire test duration. Under static channel conditions, it was seen that the transmission power can bereduced by 26 dB, when the receiver is positioned at the optimum point on the body. The evaluation ofthe dynamic channel condition is also performed by allowing the test subject to move the body as in awalking motion. Due to the body movements, the transmission power should be increased by 7 dB tomaintain the same bit error rate as that of the static experiment.

. Introduction

Wireless body area network (WBAN) is a collection of wirelessensors placed around or in a human body that are used to collectmportant information wirelessly [1,2]. In recent years, there haseen some interest in using ultra-wideband (UWB) wireless tech-ology for wireless body area network (WBAN) applications [3,4]ecause of some important benefits it offers such as low-powerransmitter, low radio frequency (RF) and electromagnetic inter-erence (EMI) effects in medical environment, small size antenna5], and high data rate [6]. UWB communication has been used for

onitoring continuous medical signals [7,8], high speed medicalonitoring such as electronic pills [9], as a wireless video system

n hospital environment [10], and multi-channel neural record-

ng to obtain a data rate as high as 100 Mbps for brain–computernterfaces [6]. UWB is also attractive for medical gait analysis

∗ Corresponding author.E-mail address: Mehmet.Yuce@monash.edu (M.R. Yuce).

924-4247/$ – see front matter © 2012 Elsevier B.V. All rights reserved.ttp://dx.doi.org/10.1016/j.sna.2012.03.046

© 2012 Elsevier B.V. All rights reserved.

and tracking due to the highly accurate performance that can beobtained [11].

In a WBAN system, very stringent requirements have beenplaced on the sensor node. The sensor nodes should be small,consume extremely low power and reliable. Therefore, it is veryimportant to minimize the power consumption of a sensor node.For the current WBAN efforts in the literature, the commerciallyavailable narrowband wireless platforms such as Crossbow’s Micanodes and Texas Instrument’ CC1010 and CC2400 platforms areused for the developments of WBAN sensor nodes. These nodeshave been based on Bluetooth or ZigBee wireless modules [1].Unlike narrowband WBAN nodes, the UWB chips/hardware plat-forms are not available in the commercial domain in order to usethem extensively. It is thus very important to develop a wearablesensor node based on UWB communication to analyze communi-cation around a human body. There are significant efforts in theliterature in the design of UWB transceivers [3,12], however these

transceivers should be low-power to utilize a small-size batteryas well as integrated with other components of sensor nodes ona small electronic boards in order to make a UWB sensor systemwearable for WBAN applications.

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38 C.K. Ho et al. / Sensors and

A typical WBAN system consists of multiple sensor nodes and aingle receiver node (i.e. control unit) attached to each user [1].lthough the locations of the sensor nodes are generally fixed,epending on the specific physiological signals to be measured,he receiver position (the controller unit), on the other hand, isot fixed. It is normally placed at a location identified by the sys-em designer or at a location that enhances the user’s comfort level.electing an optimal position for the receiver can enable a reliableransmission with a lower transmission power. This will enhancehe battery lifespan of the sensor nodes. Three popular positions,amely the waist, chest and arm that can be used for the locationf a WBAN receiver are studied in this paper. The evaluation is per-ormed with the test subject in both static and walking scenarios.

Generally, there are two types of channel models for WBAN,tatic and dynamic channels. The channel models for WBAN haveypically been obtained in the literature using a vector networknalyser (VNA). For example in [13] the channel model for a statictanding position is measured using a VNA. Another study in [14]s undertaken to obtain the channel model for a static seated posi-ion. The channel condition of a WBAN is always changing due tohe movement of the body. Therefore a static channel model willot be a good representation of the network characteristics as itoes not provide the complete operating scenario of a WBAN. Theffect of body motions (i.e. dynamic channel) on the WBAN has beennvestigated by [15] using a VNA. The measurement is conductedy measuring the static channel condition for the different phasesf walking motion. A real time measurement of the body motion isot technically feasible with a VNA because of its limited functions.herefore, an alternative performance indicator is needed to evalu-te the optimum receiver positions for both the static and dynamichannel conditions.

In this paper, the effect of body movements on the performancef a UWB based WBAN is studied using the practical bit error rateBER) performances that are obtained from a UWB hardware sensorlatform specifically developed for an on-body usage. In additiono charactering the UWB propagation around the body, the BERerformance indicator is also used to show that it is possible torrange the locations of the receiver such that transmitted powerevels of the sensor nodes can be controlled within the body areaetwork.

This paper is organized as follows: Section 2 describes the pro-osed UWB WBA system. In Section 3, the design specifications ofhe proposed UWB-WBAN system used in the experimental setups presented. The optimum receiver positions for the static channelondition are investigated in Section 4. The effect of body move-ents on the different receiver positions is analyzed in Section 5.nd the conclusion is given in Section 6.

. UWB-WBAN system

A generic definition of UWB is that the emitting signals have aractional bandwidth larger than 0.2 or at least 500 MHz. The frac-ional bandwidth is defined as the bandwidth between the −10 dBower and upper corner frequency. UWB is allowed to operate in–960 MHz and the 3.1–10.6 GHz band; however the effective iso-opic radiated power must be kept below −41 dBm/MHz.

.1. UWB sensor node

The sensor node block diagram for wireless body area net-ork applications is depicted in Fig. 1. The physiological signal

rom the electrodes enters the sensor node through the front-endmplification circuit and is processed by the microcontroller. Theicrocontroller then performs the analog to digital conversion,

etermines the transmission format, modulation scheme and sets

ors A 180 (2012) 137– 147

the data rate. The UWB pulses are generated by passing the narrowrectangular pulse trains through a band-pass filter (BPF), followedby an amplifier. The UWB pulse rate is independent of the data rate,therefore enabling the system to vary the number of UWB pulsesper data bit [7]. The square narrow pulses from the pulse generatorare multiplied using logic gates to form a modulated UWB signal.For an OOK (on–off keying) modulation, the multiplier is a simpleAND gate. The band-pass filter has a bandwidth of 1 GHz centeredat 4 GHz to ensure that the UWB spectrum mask requirements aremet. A wideband antenna designed for 3–5 GHz with an antennagain of 2 dBi is used for wireless transmission.

Fig. 1(b) shows the photo of the UWB sensor node developed forthe UWB-WBAN system. The sensor nodes are assembled on a fourlayers printed circuit board with dimensions of 27 mm (L) × 25 mm(W) × 15 mm (H) including the battery, which is sufficiently com-pact for use in a WBAN application. The node is able to producenarrow pulse ranging from 0.3 ns to 2 ns, with a variable pulserepetitive frequency of between 17 MHz and 170 MHz. After theBPF, the UWB pulse is amplified using a wideband low noise ampli-fier (LNA) to meet the regulated −41.3 dBm/MHz transmissionpower level. This amplifier has initially been included to guaran-tee that the amplitude of the UWB pulses is sufficient enough forthe distance targeted by a WBAN application. The existence of thisamplifier is also useful for the study presented in this paper as ithelps to modify the power level of the transmitted signal.

2.2. Comparison of UWB systems

Table 1 shows the detailed specifications of the existing wire-less sensor platforms used for WBAN applications. Wireless sensornode technologies based on narrow bands especially 2.4 GHz ISMhave been used in medical monitoring widely. The UWB node iscompared to narrowband WBAN nodes because the existing UWBboards presented either in the literature or in the commercialdomain are either not for a WBAN application or they have largephysical dimension of electronic boards, which are not wearable.The presented UWB sensor node is superior to the existing narrow-band ones in terms of power consumption, size and the high datarate capability [16]. The UWB-WBAN node is based transmit-only(UWB Tx-Only), which is utilized to avoid the use of power hungryreceiver structure. The UWB-BAN nodes in this work accommodatedifferent UWB pulse rate and asynchronous package transmissionpattern to provide a multi-access communication [17].

There are basically two types of UWB systems: multi-bandcarrier based systems and impulse-radio (IR-UWB) systems. Multi-band systems using Orthogonal Frequency Division Multiplexing(OFDM) modulation schemes with the spectrum divided into bandsof 528 MHz is supported by WiMedia Alliance [18]. The WiMediaAlliance is a global organization certifying UWB devices for multi-media applications. The power consumption of multi-band systemsis high due to complex real time signal processing required for theOFDM modulation. The average power consumption of a WiMediacompatible chip set is about 300 mW [19], therefore they are notsuitable for battery powered devices like WBAN nodes (see Table 2).IR-UWB systems send very short pulses and simpler modulationschemes such as pulse position modulation (PPM) or OOK, whichresult in significant power savings. They are therefore more suitablefor battery operated WBAN applications.

Several IR-UWB transceivers have been proposed for WBANapplications recently. Table 2 provides a comparison table for thedesign of these UWB transceiver hardwares with our completeUWB sensor node. Unlike narrowband WBAN platforms most UWB

based platforms in the literature have not been integrated withsensors, front-end circuits, microcontroller, receiver back-end pro-cessing units and graphical user interfaces (GUI) at the workstation.The unique feature of the UWB hardware platform in this paper is

C.K. Ho et al. / Sensors and Actuators A 180 (2012) 137– 147 139

Fig. 1. (a) Block diagram of a UWB-WBAN sensor node, (b) a photo of the UWB sensor board.

Table 1Comparison of some existing narrowband sensor nodes with the UWB-BAN node.

Model Company Frequency Data rate Trans. power(dBm)

Physical dimension Power consumptionTx Rx

Mica2 (MPR400) Crossbow 868/916 MHz 38.4 kbps −24 to +5 58 mm × 32 mm × 7 mm 27 mA at 3.3 V 10 mA at 3.3 VMicAz Crossbow 2400–2483.5 MHz (IEEE

802.15.4)250 kbps −24 to 0 58 mm × 32 mm × 7 mm 17.4 mA at 3.3 V 19.7 mA at 3.3 V

Mica2DOT Crossbow 868/916 and 433 MHz 38.4 kbps −20 to +10 25 mm × 6 mm 25 mA at 3.3 V 8 mA at 3.3 VTmote Sky node Moteiv 2.4 GHz (IEEE 802.15.4) 250 kbps 25–0 66 mm × 32.6 mm × 7 mm 19.5 mAat 3 V 21.8 mA at 3 VT-node SOWNet 868, 433, 915, or 315 MHz 52.2 kbps −20 to −5 Diameter of 23 mm 25 mA at 3 V 13 mA at 3 VMICS Node [1] Monash 402–405 MHz 76 kbps −16 30 mm×75 mm 27 mA at 3.3 V 8 mA at 3.3 V

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UniversityUWB-BAN Node

(this work)MonashUniversity

3.5–4.5 GHz Up to 10 Mbps −

he integration of the micro-controller that provides a multi-accessommunication in addition to controlling the pulse generation forn optimum signal transmission. The size of the sensor nodes devel-ped is sufficiently small to be wearable and placed on a humanody. Although the size of chips developed for UWB transmittersnd receivers can be quite small in integrated circuit technology,hey are required to be placed on an electronics board togetherith other components such as microcontroller, matching circuits,

egulator, battery and antenna.

. UWB-WBAN specifications and experimental setup

The block diagram of the experiment setup is shown in Fig. 2.he UWB sensor node is attached to the body and transmits a

able 2omparison of UWB sensor node with UWB hardware developments.

Design CPU Frequency

Our Platform PIC18F14K22 3.5–4.5 GHz

[3] (Only transmitter IC) N/A 3.432 GHz, 3.960 GHz, and4.488 GHz (500 MHz Bandwidth)

[20] N/A 3.1–5.1 GHz

[21] N/A 3–5 GHz

[22] N/A 0.5–2.5 GHz

[19] (Alereon) – 3.1–10.6 GHz

Bm/MHz) 25 mm×27 mm 15 mA at 3 V 0 (no receiver)

pseudorandom data sequence to the UWB receiver (e.g. controlunit). The receiver receives the data, decodes it, and calculates theBER. As described above, the pulse generation technique in theUWB sensor node is based on direct modulation (i.e. no carrier isused). The signal entering the receiver passes through a receiverfront-end circuit, which includes a 3.5–4.5 GHz band pass filterto eliminate the unwanted out-of-band signals, followed by anamplification of 48 dB using three wideband LNAs before downconverting to the baseband signal using a mixer and a 4 GHz VCO(voltage controlled oscillator). The baseband signal passes through

a low pass filter with 100 MHz bandwidth before going throughthe baseband amplification stage. The recovered UWB pulse isdigitalized using a high speed ADC and processed by the FPGAbefore transferring the data to the laptop using a serial cable.

Data rate Power cons. Size (mm)

10 Mbps 10 nJ/bit 27 × 25 × 15 (sensor board)– 2 mW (50 pJ/pulse) N/A

250 kbps–10 Mbps – 5 × 5 (chip size)10 Mbps 0.35 nJ/bit ∼50 × 15 (board)100 kbps 0.19 nJ/bit 2.25 × 1.1 (chip size)53–480 Mbps 300 mW (0.625 nJ/bit) 5 × 5 (chip size)

140 C.K. Ho et al. / Sensors and Actuators A 180 (2012) 137– 147

etup w

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Fig. 2. Block diagram of the experimental s

Bit error rates are obtained based on the experimental parame-ers in Table 3. As mentioned earlier, the UWB pulse rate is selectedo be much higher than the actual data rate. This helps to increasehe processing gain as well as the synchronisation process. More-ver the technique using multiple UWB pulses per data bit enableshe sensor node to perform a gating operation. The Federal Com-

unications Commission (FCC) has regulated the peak and averageower of a gated UWB signal in 2005 [23].

By gating process, the average transmission power is reduced,hile a higher peak transmission power is allowed. FCC has

tringent requirements on UWB transmission, allowing a peakransmission power limit of 0 dBm and an average limit of41.3 dBm/MHz [24]. The measurement of the average and peakower can be calculated easily using a spectrum analyser inractice. For the average power measurement, the resolution band-idth is 1 MHz with an integration time of 1 ms. A resolution

andwidth of between 1 and 50 MHz can be used for the mea-urement of the peak power. The peak limit is dependent on theesolution bandwidth and varies according to:

eak power = 20 log(

resolution bandwidth50

)dBm (1)

In our setup, the UWB transmitter is allowed to transmit at aaximum peak power level of −24.4 dBm based on a 3 MHz res-

lution bandwidth according to the gating operation utilised. Apectrum plot and time domain plot according to the parameters in

able 3 are presented in Fig. 3(a) and (b), respectively. As depicted,he average transmitted power used in our experiment is lowerhan the regulated power level of UWB communication.

able 3WB transmission signal parameters used in the experiment.

Parameter Values

UWB pulse rate 25 MHzUWB pulse width 2 nsUWB frequency band 3.5–4.5 GHzData rate 1 MbpsModulation OOKMaximum transmission peak power −24.4 dBm

ith UWB transmitter and receiver shown.

Fig. 4 shows an example of UWB pulses recovered wirelesslyat the receiver before the analog-to-digital converter (ADC) (seeFig. 2). The measurement is taken with the transmitter placed 1 maway from the receiver. This recovered pulse is digitalized usinga high-speed ADC and processed by the field programmable gatearray (FPGA) before transferring the data to a laptop using a serialcable. The role of the FPGA is to process the received multiple UWBpulses and determine whether it is bit “1” or bit “0” before send-ing to the laptop. The BER is computed on the laptop using Matlabsoftware package based on a known pseudorandom data sequencethat is sent by the transmitter. The sensitivity of the proposed UWBreceiver is −83.4 dBm.

The sensor and receiver positions evaluated in this study areillustrated in Fig. 5. Most of the commonly monitored physiologicalsignals are located on the front upper half of the body. Thereforethe four sensor positions commonly used for physiological signalmonitoring are chosen to evaluate the performance of the UWB-WBAN system. Sensor 1 is placed at the ECG position, sensor 2 isat the EEG position, sensor 3 is on the wrist and finally sensor 4 isplaced on the waist. For each sensor and receiver pair, five sets ofreadings are taken. Each set of readings consists of 10,000 data bits.

It is known that the orientation of the antenna affects the mea-surement results [25]. As the goal of this on-body study is to identifythe optimal receiver positions, all readings are taken with theantenna orientation that gives the strongest signal. Apart from theantenna orientation, the separation distance between the antennaand the body also affects the antenna’s performance. The perfor-mance degrades as the antenna is placed close to the body (lessthan 1 mm) due to mismatch in impedance, which increases thesystem losses [5]. To mitigate this problem, the sensor nodes andthe receiver antenna are placed 10 mm away from the body in orderto reduce the effect of the body on the antenna. The selection of10 mm separation distance is a realistic choice because for any com-mercial products there will be a case to house the sensor nodes, andthus provide the separation distance required.

The measurements are conducted in an Anechoic chamber to

minimize the effects of the environment. The measurement setupused for off-body analysis is shown in Fig. 6, meanwhile the on-body measurement setup for an ECG position is given in Fig. 7. Anomni-directional UWB antenna is used at the transmitter, and a

C.K. Ho et al. / Sensors and Actuators A 180 (2012) 137– 147 141

Fig. 3. UWB signal generation from the UWB sensor node: (a) spectrum, (b) time domain plots.

Fig. 4. An example of recovered

Fig. 5. Sensors and receiver locations.

UWB pulse at the receiver.

directional UWB antenna is used at the receiver. This combina-tion is selected as this provides the best performance [26]. Thephysical dimension of the UWB sensor node is 27 mm (L) × 25 mm(W) × 15 mm (H) with the battery attached which is small enoughto be wearable (Fig. 7).

4. Optimal receiver positions for UWB-WBAN

In this section, optimal receiver positions are investigated forfour positions of main physiological signals, as shown in Fig. 5.Herein all readings are taken in a controlled environment where

the subject under test remains static throughout each measure-ment. The comparison of performances is discussed based on a BERof 10−3. A BER of 10−3 is selected as a performance indicator here inthis work because it is a reasonable BER value for a sufficient data

142 C.K. Ho et al. / Sensors and Actuat

Fig. 6. Off-body measurement setup.

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Fig. 7. An on-body measurement setup for ECG position.

ecovery performance for the OOK modulation. It is important toote any other BER can easily be selected for our BER measurementso investigate performance of UWB sensor networks.1

The experimentally measured BER plots for the ECG sensor posi-ion are presented in Fig. 8. By using the peak transmission poweriven in Fig. 3, the UWB sensor node is able to operate reliably forll the receiver positions.2 It is observed that for ECG sensors, theeceiver placed at the chest requires 12 dB less power compared tohe receiver placed on the waist. The superior performance of thehest receiver with respect to the ECG sensor is mainly due to theroximity of the sensor to the receiver. The receiver placed at therm exhibited the worst performance, requiring 17 dB more powerompared to that of the receiver placed at the chest. It is obvioushat the distance between the ECG sensor and the arm receiver ishorter compared to the waist receiver. However, the arm receivers placed at the side of the body and thus does not have a directine-of-sight with the ECG sensor.

The measured BER plots for an EEG sensor position are presented

n Fig. 9. The experimental results show that the best receiver posi-ion is on the chest, while the worst receiver position is on theaist. For a BER of 10−3, there is only 8 dB difference between

1 It is important to note that the UWB receiver designed is able to detect theransmitted UWB pulses up to 2 m with a BER lower than 10−5 for most cases. Inhis section the transmitted power level is considered as it is important for theensor node. Although the power level of the received signal could be obtained forach scenario, the transmitted power levels were used as a performance indicatoror BER curves. BER plots are obtained wirelessly with a receiver having sensitivityf −83 dBm.2 Note that the maximum transmission power in BER measurements is selected

s −24 dBm because this was the maximum peak power level for the UWB sensorode configured for the targeted body area network application.

ors A 180 (2012) 137– 147

the best receiver and the worst receiver positions. The distancebetween the EEG sensor and the waist receiver is the furthest, thusrequiring more gain. Although the arm receiver is closer to the EEGsensor, there is only a 3 dB gain when compared to the case of waistreceiver. This is because the arm receiver is located at the rightside of the body, while the EEG sensor and a waist receiver arepositioned at the middle of the body.

The BER plots for a wrist sensor are shown in Fig. 10. For thesensor on the wrist, the receiver placed at the arm performs muchbetter than the receiver placed at the waist and chest. For a BERof 10−3, the receiver placed at the arm requires 18 dB less powercompared to the receiver placed at the waist. The receiver on thewaist is partially blocked by the body; therefore the performanceis greatly affected.

Fig. 11 shows the BER plots when the UWB WBAN sensor is posi-tioned at the waist. The sensor placed on the waist requires thelowest transmission power. A transmission power of −46 dBm isenough to operate with a BER of 10−3 for all receiver positions. Forsensors on the waist, the best receiver position is on the waist, fol-lowed by the arm, and then the chest. The difference in the requiredtransmit power for the best and worst receiver positions is only7 dB. The low transmission power characteristic of the waist sensormakes it suitable for the gateway node to be further from the waistsensor and closer to other sensors that require higher transmissionpower.

The performance of the proposed UWB sensor node withrespect to three receiver positions is tabulated in Table 4. Differentsensor node configurations are considered based on a BER of 10−3.For a WBAN application, there may be more than one sensoractive at one time. Thus it is important to observe the powersaving when all or some of the main sensors are active. The bestreceiver position for each combination is highlighted. The bestreceiver position is evaluated based on the average transmit powerrequired to attain a bit error rate of at least 10−3 for the all thesensor nodes in the particular configuration. From the resultsobtained, the chest receiver position is the most optimal receiverposition whenever an ECG sensor is used, which is a predictedresult. If the ECG sensor is not used and a wrist sensor is used,the most optimal receiver position in this case will be the arm.The receiver located at the waist is preferred when there is onlyone waist sensor in use. Differences shown under the column ofthe total transmit power in Table 4 are differences between thetotal transmit power required for an optimum receiver positionand the worst receiver position. For example for the first rowwhen all main sensors are used, difference = (Tecg + Teeg + Twrist +Twaist)waist − (Tecg + Teeg + Twrist + Twaist)chest = (−43 dBm +−31 dBm + −28 dBm + −53 dBm) − (−53 dBm + −41 dBm + −34 dBm+ −46 dBm) = 19 dB, where Tecg, Teeg, Twrist, Twaist are the trans-mission powers for sensors ECG, EEG, Wrist and Waist, respectively.The transmit power can be reduced up to 26 dB by selecting theoptimum receiver position. The 26 dB is calculated based on thetotal transmission power reduction for ECG, EEG and wrist sensors.There may be numerous configurations for the sensor nodes in aWBAN system, however this study considers the practical sensornode locations used in medical application. The receiver positionat the middle of the chest is the preferred choice for most of casesespecially when an ECG sensing is used.

5. Effect of body movements on the performance of WBAN

The effect of body movements on the performance of the UWB

WBAN is described in this section. The experimental setting and thetest subject are similar to that of the static scenario. During testing,the subject under test walks normally with body swaying move-ments and arm-swinging motion. The regular body movements

C.K. Ho et al. / Sensors and Actuators A 180 (2012) 137– 147 143

Fig. 8. BER performances for an ECG sensor position.

the EE

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Fig. 9. BER plot for

or the different sensors and receiver positions are highlighted inable 5.

The BER plots for ECG sensor based on the body movements areresented in Fig. 12. The required transmit power to achieve BER of

−3

0 is almost identical to that of the static scenario. However, ashe transmit power reduces, the BER performance for the receiverlaced at the arm degrades much faster than those of the remainingwo receiver positions.

Fig. 10. BER plot for the w

G sensor position.

Fig. 13 depicts the BER plots for the EEG sensor due to the bodymotions. The performance for all receiver locations degrades sig-nificantly compared to the ECG sensor scenario. The performanceof the chest receiver is degraded by 5 dB, while the performances

for the arm and waist receivers require 7 dB more transmissionpower. The higher transmission power requirement is caused bythe head movement. The effect of head movements based on thesignal strength measured from the oscilloscope is illustrated in

rist sensor position.

144 C.K. Ho et al. / Sensors and Actuators A 180 (2012) 137– 147

the w

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Fig. 11. BER plot for

able 6. The signal strength is measured from the receiver placedt the chest. When the head is looking up, the signal strength dropsy 60%, and when the head is looking down, the signal strength

s doubled. Therefore, It will be important for WBAN application toncrease the transmission power of EEG sensor node to compensateor the signal loss due to head movements.

The wrist sensor performance suffers most significantly due

o body movements as illustrated in Fig. 14. Due to the armwinging motion, which partially blocks the waist and chesteceivers, both receivers are unable to attain the required BERithin the transmission limit of the UWB sensor node. The

Table 4Optimum receiver positions for UWB-WBAN system

aist sensor position.

arm receiver is the only receiver position that the wrist sen-sor can operate reliably. The arm receiver performance is notincluded in this plot, as there was not any performance degrada-tion resulted from the movements. The performance of the armreceiver during the movement is similar to that of the static sce-nario.

In terms of the waist sensor location, there is no performance

degradation for the waist and chest receiver positions caused bybody movements. However, an arm receiver requires 7 dB moretransmission power to attain the required BER of 10−3 as illustratedin Fig. 15.

s.

C.K. Ho et al. / Sensors and Actuators A 180 (2012) 137– 147 145

Fig. 12. Effect of the body movements on an ECG sensor.

ovem

trctW

Fig. 13. Effect of body m

The optimal receiver positions for each sensor to operate effec-ively with body movements are presented in Table 7. The chest

eceiver position is still the preferred choice for different sensoronfigurations shown in Table 4. However, if a wrist sensor is used,he only possible receiver position is the arm. In summary, the

BAN performance degrades by a maximum of 7 dB due to the

Fig. 14. Effect of body movem

ents on an EEG sensor.

effect of walking motion for all sensor positions evaluated in thisstudy except for the wrist sensor. It is important to conclude that

the reliability of a WBAN system depends largely on the receiverposition. By selecting an appropriate receiver position, the effectof movements can be kept minimal for each individual sensornodes.

ent on a wrist sensor.

146 C.K. Ho et al. / Sensors and Actuators A 180 (2012) 137– 147

Fig. 15. Effect of body movem

Table 5Simulated body movements for the different sensors and receiver positions.

Sensor Receiverlocations

Simulated movements

ECG Chest Body swaying movement from side to sideECG Waist Body swaying movement from side to sideECG Arm Arm swinging motion with body swaying movementEEG Chest Head turning motion with body swaying movementEEG Waist Head turning motion with body swaying movementEEG Arm Head turning motion with arm swinging motionWrist Chest Arm swinging motion with body swaying movementWrist Waist Arm swinging motion with body swaying movementWrist Arm Arm swinging motion with body swaying movementWaist Chest Body swaying movement from side to sideWaist Waist Body swaying movement from side to sideWaist Arm Arm swinging motion with body swaying movement

Table 6Effect of head motions on the received signal strength.

Normal position Head up Head down Head left Head right

36 mV 12 mV 80 mV 20 mV 20 mV

Table 7Optimum receiver positions for body movements.

Sensors Optimum receiver position Performance

ECG Chest 1 dB lossEEG Chest 5 dB loss

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Wrist Arm No performance penaltyWaist Waist No performance penalty

. Conclusion

Ultra-wide band is an attractive wireless technology for medi-al monitoring systems and more importantly it does not presentn EMI risk to other narrow band systems and medical equip-ents in healthcare environment since its transmitter power is

uite low and the frequencies used are at very high frequencies>3.5 GHz). In this paper, a complete UWB based WBAN node haseen presented and its performance is analyzed using the practi-al bit error rate performances. Selecting an appropriate positionor the receiver ensures that reliable transmission can take placeith minimum transmission power levels. A lower transmission

ower will increase the battery lifespan of the WBAN sensor nodes.

t is shown that by carefully selecting the receiver position, theransmission power can be reduced by up to 26 dB.

[

ent on the waist sensor.

In summary, the chest area is the optimum receiver positionin the static scenario for the different sensor node configurations,as long as an ECG sensor is involved. Even when body movementis considered, the chest area is still the preferred choice for thereceiver position. However, if a wrist sensor is present in the net-work for the body movement scenario, the only possible receiverposition is the arm. Thus it is important for an UWB WBAN imple-mentation to configure body sensors and the control unit locationsaccordingly. Finally, this study shows that the performance of aUWB WBAN system can significantly be improved by carefullyarranging the sensor node as well as the control unit locations onthe human body.

Acknowledgment

This research was funded by Australian Research Council (ARC)under Discovery Projects Grant DP0772929.

References

[1] M.R. Yuce, Implementation of wireless body area networks for healthcare sys-tems, Sensors & Actuators A: Physical 162 (July) (2010) 116–129.

[2] K.V. Dam, S. Pitchers, M. Barnard, From PAN to BAN: why body area networks?in: Proceedings of the Wireless World Research Forum (WWRF) Second Meet-ing, Nokia Research Centre, Helsinki, Finland, May 10–11, 2001.

[3] J.R. Ryckaert, et al., Ultra-wide band transmitter for low-power wireless bodyarea networks: design and evaluation IEEE Transactions on Circuits and Sys-tems I, Regular Papers 52 (December (12)) (2005) 2515.

[4] M.R. Yuce, C.K. Ho, C. Moo Sung, Wideband communication for implantable andwearable systems, IEEE Transactions on Microwave Theory and Techniques 57(2009) 2597–2604.

[5] T.S.P. See, Z.N. Chen, X.M. Qing, Proximity effect of UWB antenna on humanbody, in: Asia Pacific Microwave Conference, December, 2009, pp. 2192–2195.

[6] M. Chae, Z. Yang, M.R. Yuce, L. Hoang, W. Liu, A 128-channel 6 mW wire-less neural recording IC with spike feature extraction and UWB transmitter,IEEE Transactions on Neural Systems & Rehabilitation Engineering 17 (August)(2009) 312–321.

[7] H.C. Keong, M.R. Yuce, Low data rate ultra-wideband ECG monitoring system,in: The IEEE Engineering in Medicine and Biology Society Conference (IEEEEMBC08), August, 2008, pp. 3413–3416.

[8] K. Takizawa, H.B. Li, K. Hamaguchi, R. Kohno, Wireless vital sign monitor-ing using ultra-wideband based personal area networks, in: Engineering inMedicine and Biology Society. EMBS. 29th Annual International Conference ofthe IEEE, 2007, pp. 1798–1801.

[9] M.R. Yuce, T. Dissanayake, H.C. Keong, Wireless telemetry for electronic pilltechnology, in: Proc. IEEE Sensors, 2009, pp. 1433–2143.

10] E. Ayar, UWB Wireless Video Transmission Technology in Medical Applications,August, 2010.

tem for clinical gait analysis via UWB radios, IEEE Transactions on InformationTechnology in Biomedicine 14 (March) (2010) 284–291.

12] W. Rhee, N. Xu, B. Zhou, Z. Wang, Low power non-invasive UWB sys-tems for WBAN and biomedical applications, 17–19 November, International

Actuat

[

[

[

[

[

[[[

[

[

[

[[

[

C.K. Ho et al. / Sensors and

Conference on Information and Communication Technology Convergence(ICTC) (2010) 35–40.

13] K. Takizawa, T. Aoyagi, J.-i. Takada, N. Katayama, K. Yekeh, Y. Take-hiko, K.R. Kohno, Channel models for wireless body area networks,in: Engineering in Medicine and Biology Society, 2008, EMBS 2008.30th Annual International Conference of the IEEE, 20–25 August, 2008,pp. 1549–1552.

14] C. Yifan, T. Jianqi, J.C.Y. Lai, E. Gunawan, L. Kay Soon, S. Cheong Boon, P.B. Rapajic,Cooperative communications in ultra-wideband wireless body area networks:channel modeling and system diversity analysis, IEEE Journal on Selected Areasin Communications 27 (2009) 5–16.

15] A. Taparugssanagorn, C. Pomalaza-Raez, R. Tesi, M. Hamalainen, J. Iinatti, Effectof body motion and the type of antenna on the measured UWB channel char-acteristics in medical applications of wireless body area networks, in: IEEEInternational Conference on Ultra-Wideband, September, 2009, pp. 332–336.

16] H.C. Keong, M.R. Yuce, UWB-WBAN sensor node design, in: The InternationalConference of the IEEE Engineering in Medicine and Biology Society, 2011.

17] H.C. Keong, M.R. Yuce, Analysis of a multi-access scheme and asynchronoustransmit-only UWB for wireless body area networks, in: The 31st Annual Inter-national Conference of the IEEE Engineering in Medicine and Biology Society(EMBC’09), September, 2009.

18] http://www.wimedia.org/, 2012.19] http://www.alereon.com/products/chipsets/, 2012.20] T. Nakagawa, G. Ono, R. Fujiwara, T. Norimatsu, T. Terada, M. Miyazaki,

Fully integrated UWB-IR CMOS transceiver for wireless body area net-works, IEEE International Conference on Ultra-Wideband (September) (2009)768–772.

21] Yuan Gao, et al., Low-power ultra-wideband wireless telemetry transceiver formedical sensor applications, IEEE Transactions on Biomedical Engineering 58(March (3)) (2011).

22] R.K. Dokania, X.Y. Wang, S.G. Tallur, A.B. Apsel, A low power impulse radiodesign for body-area-networks, IEEE Transactions on Circuits and Systems—I58 (July (7)) (2011).

23] FCC 05-58: Petition for Waiver of the Part 15 UWB Regulations Filed by theMulti-band OFDM Alliance Special Interest Group, ET Docket 04-352, March11, 2005.

24] FCC 02-48 (UWB first report and order), 2002.25] Z. Yue Ping, L. Qiang, Performance of UWB impulse radio with planar

monopoles over on-human-body propagation channel for wireless body

area networks, IEEE Transactions on Antennas and Propagation 55 (2007)2907–2914.

26] T.S.P. See, T.M. Chiam, C.K. Ho, M.R. Yuce, Experimental study of optimal UWBantenna location for ECG application, in: Proc. the IEEE International Confer-ence on Ultra-wideband (ICUWB2010), September 20–23, 2010.

ors A 180 (2012) 137– 147 147

Biographies

Ho Chee Keong received the B.S. degree and Ph.D. degree in electrical engineeringfrom University of Newcastle, Australia, in 2006 and 2011, respectively. From 2006to 2007, he served as an electronic design engineer with ET Designers, specializingin LCD and touch panel design. In 2011, he joined the Institute of Microelectron-ics (IME), Singapore. His research Interests include UWB communication scheme,biomedical applications and system designs for wireless communications.

Terence S.P. See received the B.Eng. and M.Eng. degrees in electrical engineeringfrom the National University of Singapore in 2002 and 2004, respectively. In 2004,he joined the Institute for Infocomm Research, Singapore. He is currently holdingthe position of Senior Research Engineer in the Antenna Lab under the RF and OpticalDepartment. His main research interests include antenna design and theory, par-ticularly in small and broadband antennas and arrays, diversity antennas, antennasfor portable devices, and antennas for on-body communications and bio-medicalapplications.

Mehmet Rasit Yuce received the M.S. degree in Electricaland Computer Engineering from the University of Florida,Gainesville, Florida in 2001, and the Ph.D. degree in Elec-trical and Computer Engineering from North CarolinaState University (NCSU), Raleigh, NC in December 2004.He has served as a research assistant between August2001 and October 2004 with the Department of Electricaland Computer Engineering at NCSU, Raleigh, NC. He wasa post-doctoral researcher in the Electrical EngineeringDepartment at the University of California at Santa Cruz in2005. He was a Senior Lecturer in the School of ElectricalEngineering and Computer Science, University of Newcas-tle, New South Wales, Australia until July 2011. In July

2011, he joined the Department of Electrical and Computer Systems Engineering,Monash University, Australia. His research interests include wireless implantabletelemetry, wireless body area network (WBAN), bio-sensors, MEMs sensors, inte-grated circuit technology dealing with digital, analog and radio frequency circuitdesigns for wireless, biomedical, and RF applications. Dr. Yuce has published morethan 80 technical articles in the above areas and received a NASA group achievementaward in 2007 for developing an SOI transceiver. He received a research excellence

award in the Faculty of Engineering and Built Environment, University of Newcastlein 2010. He is an author of the book Wireless Body Area Networks published in 2011.He is a senior member of IEEE. He is also a member of the following professionalsocieties of IEEE: IEEE Solid-State Circuit Society, IEEE Engineering in Medicine andBiology Society, and IEEE Circuits and Systems Society.