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Sensors and Actuators A 162 (2010) 116129

Contents lists available at ScienceDirect

Sensors and Actuators A: Physical

j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / s n a

Implementation of wireless body area networks for healthcare systems

Mehmet R. Yuce

The School of Electrical Engineering and Computer Science, University of Newcastle, University Drive, Callaghan, NSW 2300, Australia

a r t i c l e i n f o

Article history:

Received 4 June 2009

Received in revised form 22 May 2010

Accepted 8 June 2010

Available online 12 June 2010

Keywords:

Medical sensor network

Body area network

Telemetry

Body sensor network

Medical monitoring

a b s t r a c t

This work describes the implementation of a complete wireless body-area network (WBAN) system to

deploy in medical environments. Issues related to hardware implementations, software and wireless

protocol designs are addressed. In addition to reviewing and discussing the current attempts in wireless

body area network technology, a WBANsystem thathas been designed forhealthcare applicationswill bepresented in detail herein. The wireless system in the WBAN uses medical bands to obtain physiological

data from sensor nodes. The medical bands are selected to reduce the interference and thus increase the

coexistence of sensornode devices with other network devices available at medicalcenters.The collected

datais transferredto remote stations witha multi-hopping technique usingthe medical gateway wireless

boards. The gateway nodes connect the sensor nodes to the local area network or the Internet. As such

facilities are already available in medical centers; medical professions can access patients physiological

signals anywhere in the medicalcenter. The data can alsobe accessedoutside the medicalcenter as they

will be made available online.

2010 Elsevier B.V. All rights reserved.

1. Introduction

As portable devices like cellular phones, pagers and MP3 play-

ers become popular; people start to carry such devices around

their bodies. In 2001, Zimmerman [1] studied how such electronic

devices operate on and near the human body. He used the term

wireless personal area network (PAN). He characterizedthe human

body and used it as a communication channel for intra-body com-

munications.Later around 2001, the termPAN has beenmodifiedto

body area network (BAN)to representall the applications and com-

munications on, in andnear the body [2]. One of the most attractive

applications to use BAN is in the medical environment to monitor

physiological signals from patients.

Wireless body-area network (WBAN) is a special purpose

wireless-sensor network that incorporates different networks and

wireless devices to enable remote monitoring for various environ-

ments [3,4]. One of the targeted applications of WBAN is in medical

environments where conditions of a large number of patients arecontinuously being monitored in real-time. Wireless monitoring

of physiological signals of a large number of patients is one of

the current needs in order to deploy a complete wireless sensor

network in healthcare system. Such an application presents some

challenges in both software and hardware designs. Some of them

are as follows: reliable communication by eliminating collisions of

two sensor signals and interference from other external wireless

Tel.: +61 2 49215204; fax: +61 2 4921 6993.

E-mail address: [email protected].

devices, low-cost, low power consumption, and providing flexibil-

ity to the patients [5,6]. A WBAN-based wireless medical sensor

network system when implemented in medical centers has sig-

nificant advantages over the traditional wired-based patient-data

collection schemes by providing better rehabilitationand improved

patients quality of life. In addition a WBAN system has the poten-

tial to reducethe healthcare cost as well as the workloadof medical

professions, resulting in higher efficiency.

There is already a number of monitoring systems developed or

being used in medical centers [717]. The available medical moni-

toring systems are generally bulky and thus uncomfortable to be

carried by patients. Most of the current effort has mainly been

focused on the devices thatare monitoring one or few physiological

signals only. When multiple sensors are involved, wires are used to

connect the sensors to a wearable wireless transmitter. Wired sys-

tems restrict patients mobility and comfort level, especiallyduring

sleep studies. Future implementation of medical monitoring neces-

sitates the use of small, low-power sensor nodes with wirelesscapability [1719].

Thus far there is no available standard for a wireless body-area

network specifically targeting health care. Most popular wireless

communication technologies and protocols proposed or used in

medical monitoring systems are listed in Table 1. Existing moni-

toringsystemsuse the short-range wireless systems such as ZigBee

(IEEE 802.15.4) [911], WLANs [5,8], GSM [12] and Bluetooth (IEEE

802.15.1) [1315]. To make the power consumption and the size of

the device low, short-range devices like Bluetooth and ZigBee are

mostly used with sensors to collect medical data from a patient

body. Especially WLAN technologies are avoided for low power

0924-4247/$ see front matter 2010 Elsevier B.V. All rights reserved.

doi:10.1016/j.sna.2010.06.004
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M.R. Yuce / Sensors and Actuators A 162 (2010) 116129 117

Table 1

Wireless technologies used in medical monitoring.

MICS [6] WMTS [6] UWB IEEE

(802.15.6) [28]

IEEE 802.15.4

(ZigBee)

IEEE 802. 15.1

(Bluetooth)

WLANs

(802.11b/g)

Frequency band 402405 MHz 608614,

13951400,

14291432 MHz

310 GHz 2.4 GHz

(868/915MHz

Eur./US)

2.4 GHz 2.4 GHz

Bandwidth 3 MHz 6 MHz >500 MHz 5 MHz 1 MHz 20 MHz

Data rate 19 or 76 kbps 76 kbps 850 kbps to

20Mbps

250kbps

(2.4GHz)

721 kbps >11 Mbps

Mul tiple acc ess CSMA /C A, polling C SMA/CA,

polling

Not defined. CSMA/CA FHSS/GFSK OFDMA,

CSMA/CA

Trans. power 16 dBm (25W) 10 dBm and

100 m 1, 2 m 010 m 10, 100 m 0100 m

sensor nodes because of their large size and power consumption

used to provide longer ranges (i.e. 100 m). As these technologies

may most probably be installed in medical environments due to

other applications, medical gateway devices should be designed in

a WBAN to interfacewith these wireless systems to provide a wire-

less link between the control unit and a mobile device (i.e. PALM)

or between the control unit and Internet via a WiFi link.

The low-data rate IEEE 802.15.4 technology (ZigBee) has been

the most popular short-range standard used recently in medicalmonitoring systems due to its low transmitter power [20,21]. Sys-

tems using Zigbee wireless platform may however suffer from the

stronginterference by WLANs whichshare the same spectrum and

transmitat a larger signal power [22]. Installing an interference free

medical network in a hospital may thus be quite challenging since

there exista lotof other wireless systems and equipments usingthe

2.4GHz band. Thedevice technologies operatingat the 2.4GHz ISM

band should thus deal with the interference and coexistence issues

when they arelocatedin thesameenvironment [23]. Ascanbeseen

in Table 1, in addition to unlicensed ISM bands, there are medical

bands such as MICS (Medical Implant Communication Service) and

WMTS (Wireless Medical Telemetry Service) that are specifically

regulated for medical monitoring by communication commissions

around the world [2426]. The recent short-range, low-data rate,ultra-wideband (UWB) technology is another attractive technology

that could be used for body-area network applications because of

its regulated low transmitter power [7].

In addition to review and discuss the current attempts in body-

area network technology, a WBAN system that has been designed

for healthcare applications will be presented in this paper.1 The

proposed WBAN is a multi-hopping wireless medical network that

usesthe MICSband to obtain physiologicaldata fromsensorsplaced

on or in the body and the WMTS band as an intermediate node

for a longer wireless communication. The data is transferred to

remote stations through the local area network or the Internet

already available in medical centers as a part of their ICT (Infor-

mation and communication technologies) infrastructure. Unlike

the other medical sensor networks (they usually use 2.4 GHz ISMband); we use medical standards occupying the frequency bands

that are mainly assigned to medical applications.

The paper is organized as follows. Section 2 describes an

overview of WBANs for the medical environment. It gives the con-

cept of WBAN applications with their important design features.

Section 3 presents a complete WBAN implementation. Different

medical scenarios are defined for a real implementation in hospital

environment. This section also discusses the hardware implemen-

tation details for the proposed prototype system. The multi-access

protocol used for multi-sensor and multi-patient scenario is also

given here. Section 4 presents computer programs used for record-

1

This work is an expanded version of the conference paper given in Ref. [6].

ing, monitoring and processing the medical data captured through

the prototype system. An overall system performance evaluation

as well as comparisons with the recent attempts of WBAN-based

patient monitoring systems have been given in Section 5. And

finally Section 6 concludes the paper.

2. Wireless body-area networks in medical environment

The application of WBAN in a medical environment may con-

sist of wearable and implantable sensornodes that sense biological

information from the human body and transmit over a short dis-

tancewirelesslyto a control devicewornon the body orplaced atan

accessible location. The sensor electronics should be miniaturized,

low-power and detect medical signals such as electrocardiogram

(ECG), photoplethysmogram (PPG), electroencephalography (EEG),

pulse rate, pressure, and temperature. The collected data from the

control devices are then transferred to remote destinations in a

wireless body-area network for diagnostic and therapeutic pur-

poses by incorporating another wireless network for long-range

transmission (see Fig. 1).

The monitoring devices currently used in medical centers are

not completely wearable because their electronics are bulky andwires are used for connections to multiple sensors. Fig. 1(a) shows

the current application of a sensor network used in some mod-

ern medical centers. A wireless control unit (i.e. CCU) is collecting

information from sensors through wires and transmits to a remote

station for monitoring. In this implementation, the control unit

is cumbersome and using wires is not advised for the comfort of

patients. As shown in Fig. 1(b) the future medical sensor network

requires miniaturized and wearable sensor nodes thatcan commu-

nicate with the receiving device wirelessly. The system will consist

of individual wireless sensor nodes that can transfer a persons

physiological data such as heart rate, blood pressure, ECG via a

wireless link, without the need of any wired connection. Each sen-

sor will have wireless capability and its design will be optimized

in terms of the physical characteristics of the physiological signal.Having individual wireless nodes is also very beneficial since not

all patients require all the physiological parameters for diagnosis.

In the future, sensor node electronics could be designed using flex-

ible and stretchable technology so that sensor nodes can easily be

embedded in textile (i.e. patient clothes) to improve the patients

comfort in a healthcare environment [27].

Low power operation and miniaturization are two essential

physical requirements of sensor nodes as they determine the life-

time of the devices and their suitability to be worn by patients.

Power consumption of sensor nodes is dominated by the operation

of the wireless chip, RF (radio frequency) transmission and recep-

tion. Thus it is desirable to use a wireless platform that will provide

low power consumption and has a minimum transmitted power

while still meeting the required range of a body-area network.

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118 M.R. Yuce / Sensors and Actuators A 162 (2010) 116129

Fig. 1. A wirelesssensor network system detecting and transmitting signals froma humanbody: (a) current applicationof medical sensor network and (b) future application

of medical sensor network targeted by wireless body area network.

A study group of IEEE has been launched in November 2007

to work on the WBAN standardization [4]. One of the main tasks

of the group is to investigate a secure wireless platform to be

dedicated to a WBAN application only as the existing wireless

standards are employed in many different applications and arenot exactly optimized for healthcare systems. UWB is one of the

wireless candidates considered by this new standard. One big

advantage of UWB wireless technology is that its data rate ranges

from 850 kbp to 20 Mbp which can be used for simultaneous mon-

itoring of many continuous physiological signals such as ECC, EEG

and EMG [7,28]. In addition, UWB wireless technology does not

also present an EMI (electromagnetic interference) risk to other

narrow band systems and medical equipments in healthcare since

its transmitter power is low and the frequencies used are not

crowded.

Although the WBAN standard is still working on the develop-

ment of transmission band for the body-area networks, the UWB

wireless chips are not available commercially to apply in a WBAN

at the moment. Although UWB claimed very low power initiallyin the literature, the attempts of such technology in the integrated

circuits have exhibited power consumption more than that of the

conventional narrowband short-range wireless chips [29]. High

power consumption mainly comes from the design of the receiver

as higher RF and analog gains are required at the front-end to

receive the very low level transmit power. For an implant node in

WBAN, UWB will cause high penetration loss because it operates

at high frequencies (310 GHz for medical applications) [28]. This

maysignificantly affect theperformanceand sizeof theimplantable

nodes. UWB receivers are already more complex than the narrow-

band system ones due the low transmitted signal. The additional

loss from the skin will necessitate a higher gain at the front-end of

the receiver. Providing high gain at high frequencies is not feasi-

ble in RF technology. One method to overcome this problem is touse a transmit-only (Tx-only) UWB sensor node [37]. In a transmit

only WBANsystem, the sensor nodes contain a transmitter without

a receiver and should be programmed to send sensor data using a

special multi-access protocol to reduce collisions in orderto realize

a multi-patient monitoring.

It is envisioned that the sensor nodes of a WBAN will use a ded-

icated wireless link which will most likely be a narrow ISM band

considering the current wireless technology developments. How-

ever the UWB technology could still be incorporated in a WBAN for

the applications that require higher data rate as well as in case a

coexistence issue arises.

Inthefuture, a WBANsystem, inorderto beappliedin a medical

environment, should incorporate the following significant design

improvements and features [3,5,810,12]:

Low-cost andlow-size sensor node electronics designwith wire-

less capability. A sensor node will be able to transfer date over a

distance up to a few meters. And sensor nodes should be minia-

turized so that they can be easily wearable.

Energy optimizationtechniques should be developedby thecom-bination of the link- and physical-layer functionalities of the

wireless devices, leading to increase in the battery life and thus

the lifetime of the sensor nodes. Sleep mode technique should be

used so that the sensor nodes will spend most of their time inthe

low-power state when data transmission is not required. Physiological data should be categorized as crucial and non-

crucial data for each patient. As an example, although it could

be different with different patients, vital signals like ECG can be

more crucial than temperature for certain patients.Thus a WBAN

system should prioritize the crucial data. High gain miniaturized antennas should be developed for sensor

nodes to increase the transmission reliability and to minimize

interference hence reducing power consumption.

Each sensor should be optimized according to its characteristicsusing a variable sampling rate.

Unlike other sensor network systems, in a WBAN system, each

sensor signalhas a differentfrequency (i.e. notuniform)and thus

each sensor node should be optimized according to its sensors

frequency band. In addition, considering that some non-crucial

physiological signals like temperature information may only be

measured for a longer period of time (e.g. every hour), a WBAN

will result in better performances if an adaptive communica-

tion protocol is utilized to accommodate such differences in the

system which will clearly make the system power efficient. In order to provide a long-range remote monitoring, several

gateway devices should be developed to interface with the exist-

ing wireless systems in healthcare. These gateway devices will

mainly be used to provide communications between the CCUsand the remote computers or mobile devices. Handover mechanismshould be integrated in a WBAN that could

be useful for free movement of patients in a large medical envi-

ronment. It can be used to track patient throughout the hospital

or can track patient locations when they are outdoor doing their

daily activities. An alarm option may be included if a patient

leaves a room or goes out of the range of a CCU. This can give

the last location of patients that would allow staff to easily track

patient location. Such features can be included in the system

by detecting signals through several remote stations, which are

usually known as soft handover. Another necessary component in a WBAN is the wireless-

network security. Key software components should be defined

and developed to accommodate secure and effective wireless

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Fig. 2. Targeted three differentscenarios in our wireless body area network system for multi-patient monitoring in medical centers,(a) whenthe deviceis usedindividually,

or (b) and (c) for multi-patient monitoring in a medical center, representing one room and one floor respectively.

networking. Data shouldbe only accessible by an authorized per-

son at remote destinations. Hardware components and software

programs should be coordinated together to provide secure and

reliable communications. Lastly, a WBAN system should have its own standards for data

collection and storing techniques, and also for the wireless links

to eliminate coexistence issues.

3. A body-area network implementation for healthcare

Currentlywe are developing a complete wireless body-areanet-work that is based on different frequencies in order to eliminate

interference issues as well as to apply to different environments.

We use MICS, WMTS and 433 ISM bands to detect signals from the

sensors on the body. The goal in a WBAN application is to dedicate

onesensor node to onephysiologicalsignal as described in Fig.1(b)

to eliminate placing wires on the patient body. However, there

maybe some clinical applications that requires the monitoring of

more channels of the same physiological signal simultaneously

to provide a good quality screening [43,44]. More channels may

be required when considering EEG signal for brain activities. For

the applications that require monitoring of more channels such as

ECG/EEG/EMG, we incorporate the UWB technology to achieve a

high data rate wireless link [28]. We also like to point out that we

are working to interface our devices with IEEE 802.15.4 (ZigBee)

and Wi-Fi links to cover a large area of body-area network. The

selection of wireless schemes for sensor nodes will depend very

much on the environment that the sensor nodes will be used.

The body-area network prototyping system presented in this

paper uses a multi-hopping structure where the MICS band is used

forgatheringsignalsfromsensorsandWMTSis used totransmit the

sensor data to remote stations allowing a longer range monitoring.

Thesefrequency bands are internationally available andare permit-

ted for a remote monitoring of several patients simultaneously. The

MICS band has a lowemissionpower(25W, comparable to UWB)

leading to a lower power consumption, and will thus provide oneof the most suitable transmission bands for medical sensor nodes

[26,30]. Although a few incidents have been reported due to the

interference from some local TV channels in USA, WMTS is still the

most popular band for wireless telemetry used in hospitals [31].

Hardware electronics and software programs are developed for

three scenarios in the proposed WBAN as shown in Fig. 2. The first

scenario targets individual use in the medical center or can be used

in home care. This wireless body-area network comprises of sen-

sor nodes, a CCU that transmits data to a local PC and then to a

receiver station (i.e. remotePC) at a medical center. After obtaining

the physiological data from a human body, sensor nodes transmit

those data to the CCU via the RF link using the MICS band. The CCU

then re-packages the data and transmits to the local PC. The data

collected at the local PC is transferred to a remote PC across the

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Fig. 3. A multi-hopping WBAN prototyping system for multi-patient monitoring.

This prototyping system uses two medical standards: MICS for short distance and

WMTS for long distance wireless transmission respectively.

network in a medical center or through Internet if the patient is at

a different location than the medical center.

In the second and third scenarios, more than one patient share

a CCU box. The CCU can either be connected to a local PC in theroom(Scenario-2) or it cantransmit datawirelessly to a remote CCU

box that is attached to a PC via another wireless link (e.g. WMTS

(600MHz)). In the latter case, the CCUs act as portable wireless

gateway devices (e.g. intermediate devices) and hence the system

will form a multi-hopping wireless networking. The arrangement

in the last scenario can be used for one or more rooms in a medical

center. A hardware setup to realize the Scenario-2 and -3 is given

in Fig.3. Patients physiological parameters are sent to the interme-

diate CCUs and then to the base station (a remote PC). The system

consists of three networking structures. A network between sen-

sors and CCUs, another network between CCUs and a base station,

andthe lastcommunication is between basestations(This is mainly

a LAN connection).

Deploying a complete wireless medical system in a hospitalenvironment requires monitoring of a few hundred patients. With

this article we discuss issues related to the implementation of

such a large-scale body-area network and introduce techniques

that suit well for an implementation in hospitals. The existing and

reported body-area network projects have mainly focused on the

scenario given in Fig. 2(a) mostly with the wired sensors connec-

tions described in Fig. 1(a) [3,912,14]. We have particularly been

interested in a WBAN system which deals with the implementa-

tions shown in Fig. 2(b) and (c), Scenarios 2 and 3 respectively.

Two pieces of software are created in this project. The software

residing at the local PC is named GATEWAY. The job of GATEWAY

is to gather data from the CCU through RS232/USB2 cable and for-

wards it to one or more remote PCs using TCP/IP sockets over an

Ethernet network. Thesoftware residing at the remotePC is namedas BSNapplication. The BSN application collates data from thelocal

PC, interprets and stores them onto the remote PC to be analyzed

later by healthprofessionals. Thebase station (i.e. the remote PC)is

capable of displaying allthe received data on a graphical user inter-

face (GUI) and is also capable of storing all the data in the database

system of a medical center (see Section 4).

The MICS regulations require that the output power of any

terminal must be kept under 16dBm and is not intended for

long-range wireless connections [24,26]. To facilitate a long-range

communication, a WMTS link operating in the 608614 MHz band

2 We have used both wired USB and RS232 connections. USB has a faster data

communication and removes the necessity of holding data in the base station.

Table 2

Physiological parameter ranges and signal frequencies.

Parameter Range of parameter Signal frequency (Hz)

ECG signal 0.54 mV 0.01250

Respiratory rate 250 breaths/min 0.110

Blood pressure (BP) 10400 mmHg 050

EEG 3300V 0.560

Body temperature 3240 C 00.1

EMG (electromyogram) 10V to 15 mV 10500

GSR (galvanic skin reflex) 30V to 3 mV 0.0320

is used between the CCU and the base station allowing for a much

longer range. This implies that the intermediate CCUs must be able

to operate both at MICS and WMTS frequencies, providing a link

between the nodes and the computer. The CCU remains in close

range with the patient and may be attached to their belt for exam-

ple when it is for individual use. The nominal wireless distance for

the MICS link is around 10 m. The WMTS link targets a distance

more than 100 m.

3.1. Sensor nodes and CCU hardware designs

We develop our individual sensor nodes to detect and transmit

the physiological signals listed in Table 2. Characteristics of thesephysiologicalsignals are obtainedfrom the public domain available

on theInternet. Mostphysiological signalshave lowamplitudes and

frequencies in nature, and occupy a small information bandwidth

[43]. At such low frequencies and low amplitudes, some problems

inherent to circuits need additional attention. For a reliable infor-

mation transfer it is necessary that the interface electronics in the

sensor nodes detect the physiological signals in the presence of

noise and increase the signal-to-noise ration (SNR) of the detected

signalfor a betterprocessingby thesubsequentblocks of thesensor

nodes.

Sensornodes aredesignedto besmallandpower efficientso that

their battery can last for a long time. They collect the signals from

a human body which are usually weak and coupled with noise. An

amplification/filtering process is utilized first to increase the signalstrength and to remove the unwanted signals and noise. Then an

Analog to Digital conversion (ADC) stage is employed to convertthe

analog body signals into digital for a digital signal processing. The

digitized signal is processed and stored in a microcontroller. The

microcontroller willthen packthe dataand transmitover the air via

a wireless transceiver. Fig. 4 shows the hardware implementation

of our sensor nodes and the block diagram.

Inour system we designed sensor nodes that can measure up to

four body signals for a single patient. One node is dedicated to one

of continuous physiological signals such as ECC, EEG or EMG. Four

sensor nodes electronics (i.e. 4-channel) are built on a common

PCB board so that some electronics can be used interchangeably

Fig. 4. An example of sensor node hardware designed.

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Table 3

Summary of devices used in sensor nodes and CCUs.

Features Devices

AMIS (52100) CC1000 CC1010a PIC16F887

Size (mm) 7.57.8 9.76.4 12.912.9 17.5317.53

Modulation ASK/OOK FSK/OOK FSK

Sensitivity 117dBm 109dBm 107 dBm

Power

Transmitter Tx: 25 mA Tx: 26.7 mA Tx: 26.6 mA

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signalfromtheCCU.Theyare also dynamic innature andoffer mini-

mumpacket transfer delays whenoperatingunder lowto moderate

load conditions. The performance of a contention-based protocol

could degrade when the total traffic load increases significantly,

which is an unlikely scenario in a medical sensor network appli-

cation. In addition to its carrier sense ability, CSMA can also use a

collision avoidance (CA) mechanism (so called CSMA/CA) to allow

only one sensor node to communicate and send a packet at one

time to avoid the interference and collision between sensor nodes

[20,21]. The CSMA/CA MAC protocol is used by the IEEE802.11

based Wi-Fi and the IEEE802.15.4 based WPAN (wireless personal

area network) standards. The CSMA/CA protocol offers lower delay

and reliable transmission of packets in small size networks like a

WBNA-based medical network [16,35]. Thus the use of this mech-

anism is attractive for the transmission of critical data in medical

centers.

Unlike other sensor network applications, in a WBAN system,

not all sensor signals are required to be monitored all the time.

As an example, a temperature reading is usually taken every hour

in hospitals and thus a schedule-based protocol would be more

suitable for such sensor signals. Therefore we have decided to use

the combination of a polling protocol and CSMA/CA MAC protocol

to transmit the sensor data from multiple sensors to the CCU in our

WBAN application.A critical data (e.g. ECG, it could change according to the status

of a patient) will particularly be used in a CSMA/CA-based sensor

node. A packet can be transmitted immediately without waiting

for its turn eliminating any delay [34,35]. For non-critical data like

temperature where the data collection is not necessary allthe time,

the polling network will be used for these nodes. In this case, the

information will be sent whenever it is needed as it is not critical.

Sensor nodes that are configured in a polling scheme will enter

the CSMA/CA scheme during the data transmission so that it will

not affect the transmission of the critical data. In our system we

use a collision avoidance-based CSMA (CSMA/CA) by including the

RTS/CTS (ready to send/clear to send) and ACK (Acknowledgement)

signals to eliminate the collision probability (see Fig. 7) [16,21].

The sensor nodes in polling scheme will sleep most of the timeand wake up for a duration required for a reliable data transfer.

The polling sensor node is basically programmed to go sleep mode

after a successful packet transmission as shown in Fig. 7(a). When

data has been sent to the CCU successfully, then the CCU sends an

acknowledgment of receiving data correctly (see ACK command in

Fig.7(b)). The sensornode will thengo backto the sleep mode until

a pre-defined time arrangedby themicrocontroller. It will wake up

before a polling signal. If thepolling signalfrom theCCU is request-

ing a transmission from a particular sensor node, that sensor node

will thentry tosenddatawiththesimilardataformatof CSMA/CA.It

is assumed that thepolling sensornodeshave the knowledgeof the

polling time the time that CCU will request data from a polling

sensor node. This is a valid assumption for medical applications

because medical data like temperature canhave a pre-defined datareading times assigned by medical professions. The polling frame

includes the information about all sensors (sensor-IDs) that need

to be polled to get a data. In other words, they are triggered to send

data. The nominal active period of the polling nodes is 1 min (more

than enough until a successful packet is sent in CSMA/CA mode)

while the sleep mode time could be up to half an hour.

Fig. 7(b) shows the details of the MAC protocol used to coor-

dinate the transmission of all signals between sensors and the

CCU-Computer. The MAC protocol uses the CSMA/CA packet trans-

mission technique with the RTS/CTS messages. It is incorporated in

the firm wares at both the sensor nodes and the CCU to provide a

bi-directional communication, to control the wireless transmission

andto prevent collision between sensornodes. When a sensornode

wants to transmit a packet to the station (i.e. CCU), first it checks

the status of the transmission channel as shown in Fig. 7(b). If the

channel is free i.e. no carrier signal is present, then the CCU waits

for a certain time period and then transmits a packet if the channel

remains free for a specified period as shown in the figure. If the

CCU senses the channel busy then it backs off a random time and

reschedules its transmission attempt at a later time.

The RTS packet contains the ID of the transmitter (sensor)

and a particular receiver (CCU) so that the transmitter and the

receiver (CCU) can pair up for a packet transmission. After the

RTS transmission, the sensor node moves into the wait state

expecting a CTS packet from the CCU. The CCU will transmit a

CTS signal after the short wait period known as the SIFS (short

interframe spacing). Other sensor nodes in the network can read

the RTS/CTS packet transmissions and will refrain from further

packet transmission by calculating the channel occupancy period.

This process can avoid collisions and can improve the packet

transmission reliability. When a sensor node receives the CTS

packet, it initiates a data packet transmission which would be

followed by an ACK or a negative ACK (NACK) packet by the

receiver station (CCU). The ACK or NACK responses are gener-

ated by the CCU after performing a packet error-check mechanism

using the checksum field of the data packet. If the checksum

fails, the CCU will ask for retransmission using the NACK packet

else an ACK packet is transmitted. A packet might be corruptedeither due to the transmission error caused by low SNR or due

to a collision when two or more transmissions overlap in time.

During a RTS/CTS packet transmission or a data packet transmis-

sion if any collision happens the sensor node either receives a

NACK packet or it times out initiating a retransmission using the

RTS/CTS procedures. The time out procedure allows a sensor node

to come out of the wait state if the ACK or NACK packet goes

missing due to transmission errors. Above discussions show that

the CSMA/CA-based protocol can efficiently support transmission

of physiological data packets in a medical networking environ-

ment.

In case of a large traffic like in a hospital emergency ward, as

described in Scenario 3 in Fig. 2, four or more patients will be

assigned to a particular CCU unit. This way the number of sen-sor nodes assigned to a CCU is limited and thus the performance

of the WBAN system will not be affected due to a large volume

of people. When the patients are in action walking around, then

each patient can be connected to one CCU as described earlier. In

addition, using polling in a CSMA-based system will allow certain

sensor nodes to stay silent for a certain amount of time, and thus

only the important sensors data will be transmitted at a present

time. This adaptive scheme also helps the WBAN to reduce the

delay in the system or to increase the number of sensors to be

monitored.

In terms of power consumption, sensors nodes with polling

mechanism have longer battery life comparing to CSMA/CA based

nodes (the crucial signals). Sleep and wake up patterns can be

controlled by the acquired signal and by the application. Wakeup pattern could be periodic or it can be demand driven. Only

a small portion of the microcontroller (oscillator and counters),

which operates with a very low clock rate, always stays awake in

the system and will trigger the awakening process. As a result of

thisprocess, significant power saving is achievedand hence battery

life is increased. The power consumption of the polling based sen-

sor nodes can be kept significantly low and thus their battery life

can last several years [6,16]. In case of CSMA/CA communication,

the nodes are always active either in transmission (the transmitter

is active) or reception (the receiver is active). A CSMA node is also

consuming power when its receiver is waiting to receive the ACK

and the CTS packets. A continuously active CSMA-based node can

last about three days, a lifetime similar to current cellular phones

when using a battery of 300 mAh.

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Fig. 8. Live monitoring of multi-patients (physiological data presented in a graphical form at the remote PC). SensorID is used to define each patient.

4. Database, software programs and monitoring

In order to monitor data, several computer programs have been

developed during this project. The necessary software programs

have been identified in Fig. 2. The software called GATEWAY is

developed at the monitoring PC to control the communication

with the CCU to get readings from sensors and then forward them

through the network/internet to an application on a remote PC

(at a medical profession center). While performing this task, the

GATEWAY also verifies the data integrity and schedules retrans-

mission if required. Another software program is developed at

the remote PC (called BSN) that gets readings from GATEWAY via

the network/internet. These readings are stored in the remote PCfor analysis. The BSN application can collect and store readings

automatically so that no person is required to be stationed at the

application. It can undertake the administration of patients par-

ticulars such as assigning new sensor ID (i.e. userID) to patients,

segregating sensor readings from different patients and storing

them into the database. Using sensorID for each patient will ensure

safety in healthcare environmentswhen multiplepatientsare mon-

itored.

A graphical user interface (GUI) at the local PC as well as at

remote PCs displays medical data. The GUI also allows the medical

personnelto enter the patients information. Boththe datareceived

from the CCU and the data sent to the BSN can also been shown by

Fig. 9. A clean wireless ECG monitoring showing pulse rate as well.

the GUI in text or graphical formats. The physiological signals of

patients can be accessed by medical staff anywhere in a medical

center as long as their computers are connected to the local area

network in the building. An example of live monitoring from two

patients scenario is shown in Fig. 8. It displays temperature and

pulse rate information of two patients at the same time. Every sen-

sor device has a unique Sensor ID and must be registered under a

patient name beforetheyare used [16]. In theevent thatan unregis-

tered sensornode is used, allits readings received will be discarded

by the BSN application. Although it is not implemented in the cur-

rent prototype, a warning signal could be generated by the BSN

application to warn the health profession to track the sensor node

trying to send a signal. This feature will strengthen the reliabil-ity and safety in the implementation which would be useful for

patients.

The monitoring of the continuous signal like ECG, EMG and EEG

is more complicated compared to parameters such as pulse rate

and temperature signals. Unlike temperature and pulse rate, the

information sent to the CCU requires a continual and undisturbed

sampling period as high as 400 samples per second. Each sample

will generate a data rate of 4000 with a sampling size of 10 bits. To

allow for MAC overhead and packet retransmission, the baud rate

(i.e. data rate) for the RF link should be at least twice this rate. The

transceivers used in this prototype are able to transmit such data

rates.

Fig. 9 is an ECG signal obtained from our set up. Each sensor

node representingonly onepatient canonly have one ECG. In orderto eliminate the DC noise (50 Hz/60Hz interference) a recursive

filter taken from [36] has been software implemented to obtain an

accurate ECG signal. Shown in Fig. 10, by clicking on 50 Hz filter,

the recursive notch filter operates on the received ECG signal.

A database serverhas been developedto maintaindataintegrity

which is necessary for big medical centers. A monitoring of ECG

for an individual particular is shown in the Fig. 10. In the GUI, a

moredetailedof patientsparticularscan be seenfrom thedatabase.

Clicking on a patient shows the sensors attached to them and

their personal information/picture. Clicking on a sensor displays

the sensors information (e.g. interval). It also depicts the number of

recordings that are available. Single clicking a record shows when

the record was made. Double clicking displays the record on the

graph. In the following figure (Fig. 10), it is arranged for an ECG

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Fig. 10. An example of live monitoring of ECG via database. Note that ECG electrodes were reversely polarized during measurement taken.

monitoring. It is very handy to have a data file compatible with

Matlab program for signal analysis as mentioned earlier.

5. Performance evaluation and discussion

One way to analyze the performance of a WBAN system is to

measure the end-to-end delay during monitoring of patients. The

end-to-end delay performance herein refers to the time taken for a

packet to be transmitted from the sensor nodes to the monitoring

computer. In order to evaluate the performance of the proposed

WBAN, we have analysed the data received from an active patient

(subject) when moving from a CCU towards other patients, as

shown in Fig. 11. To observe the end-to-end delay of sensor read-ings from this patient body, we checked the arrival times of the

Fig.11. A block diagram of real-timemulti-patient monitoring to measure theper-

formance of the WBAN system.

Fig. 12. Monitoring screen: monitoring, text data at the remote PC, estimating data arrival times from stored data in database.

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Fig. 13. Data arrival times at the remote computer.

stored data (i.e. the received data) at the remote PC. Fig. 12 shows

an example of ourmonitoringsignalsand the storeddata (asa text)where the arrival times can be observed. Difference between two

readings in time will be the end-to-end delay performance of the

system.

At some point, we could observe a couple of different data

readings in the same second, which indicates that the delay per-

formance is less than one second. We have calculated the value

of the delay simply dividing one second (i.e. 1 s) by the number

of data readings seen in a second for such occasions. In our test

environment, we have measured the delay performances for dis-

tances of 1.5, 3, 5, 10 and 15m. At these distances, the active

subject was very close to other patients, that is where the maxi-

mumcollision between sensor nodes could happen.The monitoring

and the recording of the proposed WBAN system are done when

the Wi-Fi link and a few Bluetooth devices are operating in theenvironment. These devices will not affect our prototype because

the transmission frequency of our prototype is different. Selecting

medical bands for a WBAN application is one of the advantages to

eliminate external interferences. The measurement is taken in a

room 15m long and 4 m wide.

We have implemented error-checking code in our CCU where

only a correct packet is accepted. An erroneous packet is discarded

and resubmission is requested which is also part of the CSMA/CA

protocol explained in Section 3.2. In a CSMA/CA protocol, a sen-

sor node sends an RTS signal to the CCU. The RTS signal includes

the ID of the sensor node. Once the CCU sends a CTS signal back

to that particular sensor node, a communication link is then estab-

lished. Other sensor nodes in the environment will also read these

RTS/CTS signals and will back offfor a periodof time3

ifthe channelis not free. We also used a packeterror-checkmechanism(usingthe

checksum field of the data packet) for the communication protocol

between the gateway CCUandthe localPC. Ifthe checksumfails, the

PC will askfor a retransmission using the NACK (negative acknowl-

edgement)packet else an ACKpacket is transmitted fora successful

data receiving process, in the similar way done in CSMA/CA.

The medical signal in our WBAN system will not be recorded or

monitoredunless it is a correct package. Thepacket error rate how-

3 During these backoff periods, the sensor nodes can operate in sniff mode(see

Table 3) to reducepowerconsumption.In sniff mode,the sensornodedoesnotsend

anysignal, it is only in receive mode, by tryingto receive a simplesignal like ACKor

NACK to follow the channel.

ever increases the number of retransmission and thus will increase

the end-to-end delay to display correct medical data [35]. A packetmight be corrupted either due to the transmission error caused by

a low SNR (a parameter related to the distance) or due to a colli-

sion when two or more transmissions overlap in time. When the

active subject moves close to other subjects (Fig. 11), the packet

from the desired subject will be corrupted at a higher rate due to

thetransmissionchannel conditionwhichrequiresretransmissions

if there is overlap between two patient signals. Especially these

events occur frequently when the sensor node is at a far distance

away from the CCU. This has particularly been observed at the dis-

tance of 15 m. At this distance, we were not able to see any data

being recorded,whenthe active sensor nodeis blockedby theactive

patient body (when the patient turns his back to the CCU). This is

expected because at this distance, the received data power level is

less than the receivers sensitivity given in Table 3.Inour test environment, when theactive subject is around other

subjects,he has been asked to do fewroutineactions such as sitting,

standing, facing, andturning back with the same amount of time at

the distance of1, 1.5,3, 5, 10and 15m. This routine actionhas been

repeated at least ten times. And the average and worst case delays

have been recorded and plotted in Fig. 13. The worst case delay

was observed as 20s when the distance between the active subject

and the gateway CCU is 15m. A medical data can be monitored less

than 300 ms when the active subject is within distance of 1m and

facingthe CCU. When theactive patient is doing allsort of activities

e.g. sitting standing, turning aroundthe other patients, the average

delay is 1 s up to 5 m and 2 s at the distance of 10 m. These values

show that our WBAN system exhibits a correct, timely and reliable

communication performance up to 10 m with a time performanceless than 2 s for a multi-patient scenario. We have observed that

under the worst condition the average retransmission rate is 5 for

a distance up to 10 m. The distance of 10 m has been our initial

target during the development of the boards. Such a distance is

sufficient for multi-patient monitoring. Usually the CCU is targeted

to be placed within 2 m of the patients. However having 10m will

provide patient more flexibility and free movements in hospital

environment.

5.1. Comparison of WBAN systems

This section discusses and compares the existing WBAN sys-

tems in the literature in terms of categories given in Figs. 1 and 2.

The goal here is to compare these existing systems in terms their

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Table 4

Comparisons of current implemented WBAN systems from literature.

WBAN systems Wireless device Sensor Categorya Comments

Jovanov et al. [3] ZigBee (2.4 GHz) Activity sensor Similar to Fig. 2(a) The control device connects with a computer

for data display directly or wirelessly using a

Wi-Fi link. It is a multi-hopping system with

multi-sensors; however one patient data has

been implemented. No internet transmission

has been indicated

Gao et al. [9] IEEE 802.15.4(MICAZ) Pulse oximeter,blood pressure Fig. 2(a) Sensor nodes directly communicate with atabled PC. A secure web portal to allow sharing

real-time patient information (Internet

connection)

Anliker et al. [12] GSM Blood pressure,

SpO2, one lead ECG

Figs. 1(a) and 2(a) Multiple sensors have been integrated in one

handheld device

Park et al. [17] nRF24E1 radio

(2.4GHz)

ECG Fig. 2(a) One of the smallest custom-made sensor nodes

in the literature. The ECG sensor communicates

to a computer wirelessly or a base station with

Wi-Fi link. No multi-patient scenario

Espina et al. [38] IEEE 802.15.4

(2.4GHz)

ECG, PPG, blood

pressure

Fig. 2(a) Single user data is presented

ODonovan et al. [42] ZigBee Motion, blood

pressure, ECG

Fig. 2(a) Data is sent to a base station (computer)

wirelessly. No multi-patient data is presented

Chen et al. [41] IEEE 802.15.4

(ZigBee)

8-Channel EEG Figs. 1(a) and 2(a) Single patient. Internet data transmission is

provided. No wireless gateways

Zhang and Xiao [40] Bluetooth (2 .4 G Hz) ECG Fig. 2(a) and (b) Although it mentions it is done for two persons

ECG, one continuous ECG monitoring data is

shown. The control device is directly

connected to a home computer via USB (no

wireless gateways). No data transmission

through Internet

Huang et al. [39] ZigBee (2.4 GHz) No sensor Fig. 2 (a) Only one ZigBee device is used to

communicate with an existing IEEE 802.11g

device to measure interference in terms of BER.

Does not provide monitoring signals

Yuce et al. [28] UWB (4 GHz) 8-Channel

ECG/EEG

Fig. 2(a) The design targets monitoring of

multi-channel continuous physiological

parameters for implantable and wearable

systems. No wireless gateways

This work MICS/WMTS Pulse

rate/temperature/ECG/EEG

Fig. 2(a)(c) The system has been designed to operate

according to Fig. 1(b) and all the scenarios

given in Fig. 2. Internet connection for long

range

a Fig. 2(a), single body monitoring; Fig. 2(b) and (c), multiple body monitoring.

suitability for a large-scale implementation in a medical environ-

ment. Comparisons of some of WBAN systems from literature are

listed in Table 4. The columnCategory indicates whether the sys-

tem demonstrates a multi-patient or a single patient monitoring.

In Espina et al. [38] presents a IEEE 802.15.4-based wearable body-

area network that monitors continuous cuff-less blood pressure

and ECG signals. The sensor data was measured on a single user.

Date taken from a sensor is displayed on a PDA or a wristwatch

device. In Ref. [9] sensor nodes directly talk to a tablet PC, a design

similar to Fig. 2(a), and the stored data can then be seen by a secure

web portal by medical professions. Anliker et al. [12] designed a

wrist-worn device to measure multiple physiological parameters

from one person. Sensors like blood pressure, SpO2, one lead ECGall have been integrated in one handheld device. The data is then

transmitted using a GSMdata link to a computer similar to Fig.1(a).

The device acts the same as a regular cellular phone since it oper-

ateswith theGSM network.Howevermeasurements morethan one

patient atthe same time have notbeenprovided.Another systemin

Ref. [17] designs verysmall wearable (probably one of smallest cus-

tommade sensor nodes) ECG sensors that communicate wirelessly

witha basestationconnectedto a computer.The system works sim-

ilar to a multi-hopping if a Wi-Fi link is used. Similar to previous

ones, this system also does not present any data for multi-patient

measurements and monitoring. Data presented is from a scenario

similar to Fig. 2(a).

Theavailable systems present medicalmonitoringmostlyfrom a

singlebody whichis more suitable for homecare. Although it is one

of the first and earlier WBAN implementations, E. Jovanov, 2005 in

[3] has provided monitoring results for multi-sensors from a multi-

hoping wireless link. To implement a WBAN system in a medical

environment, the future WBAN systems should make sure that the

implementation will operate the scenarios defined in Fig. 2(b) and

(c). Real-time and simultaneous multi-sensor and multi-patient

communication is required for future WBAN systems. In addition

to real-time multi-patient monitoring capability, our system pro-

vides data transmission through the Internet allowing access to

patient data at remote stations. It will be important for future

WBAN systems to evaluate their design for multi-patient environ-

ment especially devices using a wireless platform at 2.5GHz ISM

band, due to the existing of the other wireless devices and equip-ments at this frequency. Such a validation will be crucial. Future

WBAN systems should also develop small size sensor boards, as

in Ref. [17], specifically targeted for WBAN applications to meet

the size and power constraints. Most of the current system uses

the commercial available ZigBee board which is designed for many

other applications and thus is not entirely wearable.

6. Conclusions

In this paper we present a multi-hopping network for a WBAN

systemthat canbe used in medical environments forremote moni-

toring of physiological parameters. The system is differentthan the

existing implemented ones in thatwe consider monitoring of phys-

iological signals from many patients simultaneously to represent a

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real implementation in hospital environments. Issues related to a

complete WBAN system to deploy in a medical center have been

discussed.Portable and wireless gateway nodes are usedto connect

the sensor nodes to the local area network or the Internet already

available in medical centers. This allows medical professions to

access patient data anywhere in a medical centeror even if they are

away. Such a wireless body-area network system is very suitable

to be used in hospitals environments to reduce human errors, to

reduce health care cost, to provide more time to health profession-

als as well as to increase patients comfort level as they no longer

need to be wakening up for periodic checks.

A discussion of wireless technologies foruse in a WBAN applica-

tion has also been given in this paper. We are working to interface

our MICS/WMTS devices with other wireless standards such as

WLANs, ZigBee (IEEE 802.15.4), mobile networks (e.g. GSM) or

Bluetooth(IEEE 802.15.1) in order to extendthe applicationsin dif-

ferent environments. Such a heterogonous wireless network can

help to coordinate collaborations across medical centers. Imple-

menting a wireless body-area network will require integration of

external and implanted nodes. Miniaturization of the sensor node

electronics especially the sizes of the microcontroller, the wire-

less chip, the battery and low power consumption are current

hardware related issues for small sensor nodes in a WBAN. The

successful implementation of a complete WBAN system shouldoperate and co-exists with other network device and should pro-

vide: wearable, wireless (no wire connections),easy to removeand

attach sensor nodes, leading to increased mobility of patients and

flexibility.

Acknowledgements

This work was supported in part by the Australian Research

Council (ARC)under DiscoveryProjects Grant.I like tothank the fol-

lowingstudents Anthony Bott andNg Peng Choong fortheir help in

the developing boards. I also like to thank the anonymous review-

ers for their comments and suggestions to strengthen the quality

of the paper.

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