In home telerehabilitation for geriatric patients

GERONTECHNOLOGY
In-Home Telerehabilitation
for Geriatric Patients

© DIGITAL STOCK & EYEWIRE
Use of Wearable Wireless Body Area Sensor
Networks for Increased Telepresence

BY MATHIEU HAMEL,

REJEAN FONTAINE,
AND PATRICK BOISSY

I
n the last decade, changes in the organization and financing dedicated modular software interfaces for user-friendly control
of health services in Canada have reduced the length of stay of videoconferencing connections, PTZ camera function, and
in acute care hospitals, increased the number of day sur- external devices (i.e., tablet PC and sensors). An overview of
geries, and generally reoriented the hospital-centric care the telerehabilitation platform and the software interface for the
toward dispensation of health services in the community. The clinician is illustrated in Figure 1.
demographic imperative of an aging population creates unique Iterative changes were made to the hardware and software
opportunities to look at new paradigms in delivering health components to ensure transparent dynamic interactions be-
care services in the community. In this context, in-home telere- tween the clinicians and the clients during a telerehabilitation
habilitation (i.e., the delivery of rehabilitation services at an session. Special attention was given to provide a mouse-based
individual’s home over telecommunication networks) has been interface to control intuitively from a unique screen through
identified as a promising avenue. The rationale for in-home tel- point-and-click or area-zoom PTZ camera functions at both
erehabilitation is to expand and facilitate the delivery of reha- sites. Results from our ongoing trial and debriefing of clinicians
bilitation services to people who cannot travel to a clinic have shown that telerehabilitation practices challenge conven-
because of disability or travel time [1], [2]. Evidence support- tional communication behaviors underlying the professional
ing the use of telerehabilitation as a viable alternative or com- patient-client relationship found in face-to-face encounters in
plement to traditional in-home therapy is slowly emerging in rehabilitation. Although videoconferencing can create a tele-
the literature [3], [4]. presence experience for the clinician by providing visible and
Most types of telerehabilitation services fall into two catego- nonverbal information about the behavior of an individual in
ries: clinical assessment (the patient’s functional abilities in his/ his/her environment, it is difficult for the clinician to interpret
her environment) and clinical therapy. To provide both types of detailed information such as the kinematics and kinetics of the
services remotely while interacting with the patient, the rehabil- individual’s movement and physiological responses to exer-
itation professionals rely on establishing a telepresence through cises in a telerehabilitation context. This is even more evident
bidirectional video and audio from videoconferencing equip- when operating under suboptimal optical conditions such as
ment connected through a high-speed Internet connection. those found in the home environment. Increased telepresence
Telepresence [5] refers to the phenomenon whereby a human combining information from wearable sensors with audio and
operator develops a sense of being physically present at a video streams might be part of the solution to complement the
remote location through interaction with the user and the subse- traditional telerehabilitation practices [9], [10].
quent perceptual feedback he/she receives via the appropriate
teleoperation technology [6]. Wireless Body Area Sensor Networks
We investigate in this study, following the positive results Wireless body area sensor networks (WBANs) are well suited
from a proof-of-concept study [7], the effectiveness of provid- to increase telepresence, as they can provide specific informa-
ing in-home telerehabilitation services as an alternative to tion about an individual’s behavior without using complex
home care visits for physical therapy in orthopedic conditions laboratory equipment and without interfering with the person’s
following discharge from an acute care hospital and rehabilita- natural behavior [11]. WBANs are generally built around
tion unit [8]. Based on the results from the initial proof- several sensing devices wirelessly linked together using nar-
of-concept study and a user-centered design approach, a row-band radio communication [12]. Recent developments in
telerehabilitation platform was developed consisting of two the field of wireless networks have generated many new
H264 videoconferencing codecs (Tandberg 500 MXP) with commercial wireless communication platforms based on dif-
integrated wide-angle view cameras and remotely controlled ferent protocols and technologies (Wi-Fi, WiMax, Bluetooth,
pan tilt zoom (PTZ) functions, local and remote computers with Zigbee, UMTS, UWB) [13]. These technologies offer a wide
range of characteristics in terms of speed, transmission range,
Digital Object Identifier 10.1109/MEMB.2008.919491 power requirements, connectivity, and cost. The choice of

IEEE ENGINEERING IN MEDICINE AND BIOLOGY MAGAZINE 0739-5175/08/$25.00©2008IEEE JULY/AUGUST 2008 29

wireless network architecture
Clinical Site for a WBAN application is
2 context and sensor depend-
ent. Table 1 presents some
Home Site of the existing BAN/WBAN
1
technologies and their wire-
less networking character-
istics. The use of a WBAN
system in a telerehabilitation
context calls for a small, reli-
able, low-power platform ca-
pable of seamlessly integrating
several modules.
The Zigbee technology was
designed for this type of appli-
cation. The IEEE 802.15.4
physical radio standard oper-
(a)
ates on the 2.4-GHz unli-
censed band over 16 channels,
and the network layer supports
topologies such as star, tree,
1 and mesh. Depending on the
power output and environ-
mental characteristics, trans-
mission distances range from
10–100 m [14]. Recent publi-
cations [11], [15], [16] have
3 illustrated projects geared to-
ward developing application-
specific WBAN systems
based on Zigbee technologies.
Recommendations on a mul-
2 titier architecture for WBAN
systems in the context of
patient monitoring or the types
of sensors to use and their lo-
cations have been proposed
[15], and different WBAN
systems are currently under
development. ActiS, an ac-
tivity sensor developed by
Jovanov, is built around a
(b) wireless platform that integra-
tes a Zigbee-compliant radio
Fig. 1. Telerehabilitation platform. (a) Hardware components including two H264 videocon-
and a microcontroller called
ferencing codecs (Tandberg 500 MXP) with integrated wide-angle view cameras and
Telos from Moteiv [17]. A
remotely controlled PTZ functions. (b) Software interface for user-friendly control of video-
custom sensor board con-
conferencing connections, PTZ cameras function, and external devices (i.e., tablet PC and
nected to the Telos platform
sensors).
enables concurrent wireless
ECG and accelerometer mea-
surements. As a heart sensor,
ActiS can be used to monitor
Table 1. Wireless technologies and possible BAN/WBAN platforms. the heart activity and trunk
position. CodeBlue is another
Technology Transfer Rate Range BAN/WBAN project developing wireless
Wi-Fi 11–54 Mb/s 30–50 m DPAC Airborne, PDAs body area networks for medi-
WiMax 4.5–70 Mb/s 100 m–50 km Portable computers cal care. The goal of the
Bluetooth 57 kb/s–3 Mb/s 100 m Smart-Its, iMotes project is to develop sensors
Zigbee 20–250 kb/s 100 m MICAz, Telos, tMotes for stroke rehabilitation patients
UMTS 50 kb/s–2 Mb/s 5–100 km Mobihealth and to monitor vital signs to
UWB 54 kb/s–48 Mb/s 1–10 m Magnet help in emergency response
(ECG, blood pressure) [18].

30 IEEE ENGINEERING IN MEDICINE AND BIOLOGY MAGAZINE JULY/AUGUST 2008

WBAN Home Site
1 3 5
2

4
1 WBAN Transceivers
2 WBAN Receiver
3 Tablet PC
4 Tandberg 550 MXP 6

Clinician Site

Pulse 9
Oximeter + 8
Accelerometers
Instrumented Soles Respiratory Belt Sensors
7
5 VPN Router 8 Tandberg 550 MXP
6 Internet 9 Clinician PC
7 VPN Router

Fig. 2. Complete system used for a telerehabilitation session. The WBAN system comprises four wireless sensor nodes.
A total of 32 analog signals are sampled at 100 Hz frequency and sent to the host computer. Sensors measure the
heart rate, blood saturation, changes in thoracic and abdominal circumference, weight-bearing, acceleration,
and angular rate. Video, audio, and sensor data are sent to a remote site using a high-speed Internet connection.

The wireless platform chosen for this project is the MICAz
from Crossbow [19], which is also based on a Zigbee- Transmitter Receiver
Flash Flash
compliant radio. Memory Memory

WBANs for Telerehabilitation Processor Processor
Sensors Analog I/O Analog I/O PC
Digital I/O Digital I/O
System Architecture
2.4 GHz 2.4 GHz
For use in telerehabilitation applications, we recently developed Radio Radio
a Zigbee-based WBAN system with custom sensor platforms
and adaptable sensing inputs capable of accommodating differ- Wireless
ent sensor configurations. The system designed for telerehabi- Module
litation applications is composed of sensor platforms with
application-specific signal conditioning units connected to wire-
less communication modules. An overview of the system archi-
tecture and components is illustrated in Figure 2. The system
consists of four eight-channel Zigbee-based wireless sensor
nodes with a total theoretical bandwidth of 250 kbps configured Li-Ion
Sensor Board Battery
in a star configuration to a single receiver connected to a
computer. The current sensor node configuration comprises
a custom sensor board with an embedded three-dimensional Fig. 3. WBAN and sensors. Wireless sensor network comprises
accelerometer (LIS3L02AQ, STMicroelectronics) [20], one one- up to four sensor nodes configured with the star topology.
dimensional gyroscope (ENC-03M, Murata) [21], and connectiv- Wireless modules include a custom sensor board and a
ity to four external analog or digital sensors (Figure 3). External MICAz communication module from Crossbow Technology.
sensors can take many forms: we currently use load cells, respira-
tory belts, and a pulse oximeter. The two respiratory belt sensors external sensors described in this article (oximeter, respiratory
(MLT1132, ADInstruments) [22] are connected to the first sen- belts, and the instrumented shoes) can all be installed with no
sor node worn on the trunk. The second and third sensor nodes or minimal exterior help. The modules, as shown in Figure 2,
are linked to custom instrumented shoes, which provide weight- have elastic bands and adjustable bracelets that enable the sub-
bearing data during ambulatory activities. The last sensor node jects to install them with relative ease. In certain cases, individ-
uses onboard sensors to measure acceleration and angular rate of uals with reduced mobility or dexterity (e.g., stroke) could get
the subject’s dominant hand. assistance from a third party to install the sensor module if
In the context of telerehabilitation, sensor placement is a needed.
critical issue. While the ergonomics, usability, and design of The communication module is an off-the-shelf MICAz
wearable sensors can affect the reliability of the data, the available from Crossbow [19]. The module consists of an

IEEE ENGINEERING IN MEDICINE AND BIOLOGY MAGAZINE JULY/AUGUST 2008 31

ATmega128 microcontroller with eight 10-b analog-to-digital to the videoconferencing equipment (Tandberg 550 MXP,
converters (ADCs), flash memory, and a Chipcon 2.4-GHz H.264 codec). A secured VPN communication channel was
radio transmitter/receiver. Modules can be programmed as established between the two sites using a second identical
receivers, transmitters, or both using an event-driven, highly router at the clinical site. Raw signals provided by the wireless
modular operating system called TinyOS [23]. This operating sensors (Figure 4) can be directly visualized at the clinical site
system is based on a library of components that can be easily and further be processed through an algorithm that interprets
connected using well-defined interfaces. Custom components, in real time the variables such as body angles, weight-bearing,
written with the NesC language [24], can directly interact with respiration, and heart rates [Figure 1(b)].
components from the TinyOS library with minimal use To assess the feasibility of using the proposed WBAN sys-
of resources. The network is formed by assigning a unique tem with the existing telerehabilitation platform, we evaluated
address to each wireless module individually. The main its radio communication performance, operational range, and
receiver module acts as a coordinator by sending start and stop functionality under telerehabilitation conditions. More specif-
commands to transmitters, enabling synchronized data acquisi- ically, the objectives of the system’s evaluation were to 1)
tion. Small 580-mAh Li-ion batteries (UBP363450/PCM) assess the impact of the number of sensor nodes used, the
power both the sensor boards and the communication modules number of sensor inputs per node used, and the sampling rate
and are embedded in bracelets that can be attached to the body. used on the reliability of the radio communication; 2) charac-
The WBAN is configured with four wireless sensor nodes. terize the performance of this system during continuous use in
A tablet PC served as the WBAN receiver at the home site and a home environment; and 3) assess the performance in con-
was connected wirelessly (802.11 b) to a router [Linksys with junction with a videoconference link over the Internet.
virtual private network (VPN)] connected to a digital
subscriber line (DSL) modem for Internet access. The WBAN System Evaluation
was connected to the computer via a USB interface board Although the Zigbee-based WBAN systems described in
(MIB520). The router also provided wireless Internet access the literature are quite innovative and their development is

A A
Left Foot
0–900 N

Right Foot Weight Bearing
B
±2G

aX aZ WY Left Ankle
aY

Right Ankle

Left Wrist

Abdominal Respiratory
Thoracic Belt Transducer
97%
87 bpm

% Oxygen Saturation 86 bpm
% Pulse Rate
96% 96%
85 bpm
Pulse Oximeter

1s 2s 3s

Fig. 4. Signals output from the WBAN system during a walking activity. The A and B cycle shows the applied
vertical forces on the insoles and the leg movements during a normal walk cycle. Activity levels can be cal-
culated by combining heart rate, respiratory data, and a sum vector of accelerometer signals.


ongoing, there are little or no published data concerning the data packet was used for these experiments. Transmission
performance and limitations of these systems in terms of radio errors are either a missing message from one of the transmitters
communication, operational range, and functionality under or a message not received in the right order. During the experi-
unconstrained conditions in a home environment when worn ments, precautions were taken to make sure that the batteries
by an individual. Indeed, proximity issues regarding the place- of each module were properly charged and that the modules
ment of several modules on the body may lead to severe inter- were worn correctly (two bracelets on the wrists and two on the
ference problems, and the reliability of continuously streaming leg shank). The distance from the receiver (DFR) was also
high volumes of data to a receiver at a determined rate over a standardized between tests, making sure it would not exceed
long period is untested. 50 ft between the receiver and the person. A total of 25 trials of
Wireless platforms such as Moteiv, MicaZ, and other Zigbee- 30 min each were performed while varying the number of mod-
compliant devices were mainly developed for commercial and ules from one to five and the sampling frequency from 50 to
industrial practices. The goal of the following experiments was 100, 200, 400, or 800 Hz. During each trial, tasks related to
to establish the performance of a typical WBAN in real condi- office work were done (walking, typing on the computer, etc.).
tions to provide guidelines for future WBAN development and Results illustrated in both graphs of Figure 5 summarize the
implementation. First, a reliability experiment was conducted to performances of several WBAN setups and suggest a typical
determine the performance of several WBAN configurations in network comprising four active modules, which minimizes the
an ideal laboratory environment. Second, a similar experiment probability of communication errors and optimizes the number
was done in a home environment to evaluate the effect of this of active modules and their sampling rates.
environment on the WBAN system. Finally, the last experiment
consisted of streaming data from the WBAN system in the con- Real Home Environment
text of in-home telerehabilitation (i.e., shared bandwidth be- Special precautions have to be taken considering that the
tween videoconferencing equipment and the WBAN system WBAN system would be used in a home environment.
over a DSL Internet connection). Although laboratory experiments give an idea of system
performance, it is essential to evaluate the system in a typical
WBAN Reliability in a Laboratory Environment home with interwall and interfloor communication, possible
The purpose of the reliability experiment was to determine the sources of signal reflections and noise. The purpose of this
bandwidth limitations of this kind of system in a controlled experiment was to determine whether or not it is viable to use
laboratory environment and evaluate the possible problems this system in an in-home telerehabilitation context. Assump-
related to interference and body movement. Several tests were tions were made concerning the communication algorithm
conducted while varying the number of active modules and and bandwidth requirements, as these parameters could be
the sampling frequency of the ADCs. The system reliability optimized. The system configuration used during these tests
was evaluated by assuming that communication errors would was taken from previous results derived from the laboratory
happen independently of the algorithm programmed in the experiments (four modules, 100 Hz). A typical multilevel
microcontrollers. It is also possible to avoid transmissions house was chosen as the testing environment (Figure 6).
errors by programming a more robust error detection algorithm The receiver module and host computer were situated on
that would send back bad or missing data packets. A simpler the second floor of the house. Two parameters were eval-
algorithm that associates a message number and origin of each uated during the trials: the percentage of communication

30 100%
Time (min) to Loss of Communication

25 1 Module 1 Module
2 Modules 2 Modules
3 Modules 3 Modules
% Transmission Errors

4 Modules 0.7 4 Modules
20 5 Modules 5 Modules
0.6
15 0.5
0.4
10
0.3
0.2
5
0.1

50 Hz 100 Hz 200 Hz 400 Hz 800 Hz 50 Hz 100 Hz 200 Hz 400 Hz 800 Hz

(a) (b)

Fig. 5. WBAN reliability experiment results. (a) Total time required over a 30-min experiment before losing communication
between the WBAN transmitters and the receiver for multiple setups. (b) Percentage of transmission errors during these experi-
ments while varying the number of modules and the sampling frequency of the eight analog inputs.


errors as described earlier in this article and the number of appliances, and body movements did not prevent the system
communication losses. This last parameter was evaluated by from working properly.
counting the number of times the system completely lost
track of the wireless network during the 1-h trials. The vari- WBAN in a Telerehabilitation Context
ous activities performed during these trials included both A last experiment was conducted to evaluate the performance
static and dynamic movements. More precisely, activities in and impact of the WBAN system when used in conjunction
Room 1 (office) included writing in a sitting position, vac- with a videoconferencing system (i.e., shared bandwidth). A
uuming, and tidying the closet. In Room 2 (second-floor bed- 60-min telerehabilitation session took place at the home site,
room), vacuuming and office work were done. Cooking and data from the WBAN were sent to the host computer (clini-
lunch, washing the dishes, and cleaning were done in Room cal site) in real time via a high-speed Internet connection. Fig-
3 (kitchen). Activities in Room 4 (dining room) included ure 2 shows the system used during this experiment. A DSL
vacuuming and computer work (sitting at the dinner table). high-speed Internet access at the two sites provides a theoreti-
Room 5 (bathroom) included some laundry, vacuuming, and cal bandwidth of 3 Mb/s in download and 800 kb/s in upload.
scrubbing. Finally, some vacuuming and reading (lying on From this available bandwidth, 384 kb/s was dedicated to the
the bed) were done in Room 7 (first-floor bedroom). The videoconferencing equipment to establish a quality audio and
mean linear distances between the receiver and the WBAN video link (320 kb/s for video data and 64 kb/s for audio data).
transmitters (DFR) were computed using the mid-point Bandwidth allocation was estimated experimentally during
(length, width, height) of each room and the receiver location the telerehabilitation session using communication statistics
on the second floor. The WBAN performances obtained in (upload and download transfer speed) computed by the router
each room in terms of communication errors and loss of com- and the videoconferencing equipment located at the clinical
munication did not differ from the performances obtained in site. Communication statistics were retrieved from both devi-
the laboratory environment. The effect of walls, electrical ces at 5-s intervals. Bandwidth allocation for the WBAN was
calculated as the bandwidth
statistics recorded on the
router minus the bandwidth
Second Floor
statistics provided by the
Area: 14.33 m 2 2 videoconferencing unit.
DFR: 6.87 m Continuously polling the sta-
Receiver

tistics also requires part of
LOC %ERR the total bandwidth for both
1 0.098
upload and download. It was
included in the WBAN band-
Area: 15.68 m2 1 width for simplicity. Results
DFR: 1.68 m from this experiment are il-
lustrated in Figure 7.
LOC %ERR Area: 15.65 m2 6 The WBAN setup used for
0 0.158 DFR: 6.93 m
the experiment accounted for
LOC %ERR approximately, on average
First Floor 2 0.151 over the 60-min session,
209 kb/s of the total band-
Area: 15.02 m2 7 width allocated during the ses-
DFR: 1.26 m sion. The bandwidth needed
to stream the data from the
LOC %ERR
WBAN system in real time
0 0.134 Area: 10.33 m2 4
DFR: 7.86 m over the Internet did not affect
the overall quality of the audio
Area: 6.39 m2 5 LOC %ERR and video signals received
DFR: 3.51 m 3 0.128 from the videoconferencing
equipment. During the experi-
LOC %ERR ment, the WBAN encountered
2 0.123
communication errors and
was restarted three times. The
Area: 12.94 m 2 3 Tandberg unit recorded 192
Area: Total Area of the Room (m2) (download) and 95 (upload)
DFR: 5.12 m
DFR: Mean Linear Distance from Receiver (m) missing data packets through-
LOC: Number of Loss of Communication LOC %ERR out the session.
%ERR: Percentage of Communication Errors 1 0.082
Power Consumption
A custom sensor board
Fig. 6. In-home communication reliability results. Percentage of transmission errors and number was built for the telerehabilita-
of communication losses during a 1-h continuous transmission from all rooms in a typical house tion application. As described
using four modules at a 100-Hz sampling rate (eight channels). in the ‘‘System Architecture’’


Download Upload
700 500
Total BW (588 kb/s)
Total BW (407 kb/s)
600
400
Bandwidth (kb/s)

500

Bandwidth (kb/s)
400 300
Video (315 kb/s) Video (228 kb/s)

300
200

200

WBAN (209 kb/s) 100 Audio (64 kb/s)
100

0 Audio (64 kb/s) 0
0 30 60 0 30 60
Time (min) Time (min)
(a) (b)

Fig. 7. WBAN performances and bandwidth allocation during a 60-min telerehabilitation session. (a) Bandwidth allocation
during download composed of video, audio (Tandberg 550 MXP), and sensor data from the WBAN. (b) Bandwidth allocation
during upload composed of audio and video only.

section, it contains a tree axial accelerometer, a gyroscope,
Table 2. Theoretical power consumption of WBAN
and four amplifiers for external circuitry. The theoretical
sensor nodes.
power consumption is presented in Table 2. The total battery
life was tested experimentally during the real home environ- Active Items Operating Current
ment experiment. Continuous transmission of the WBAN
Wireless module (Crossbow) 17 mA* (Tx mode)
lasted until the first module had no power left. A total battery
Accelerometer (STElectronics) 1.5 mA
life of 24 h was expected based on the theoretical power con-
Gyroscope (Murata) 5 mA
sumption (Table 2). Operating current from onboard sensors
Amplifiers (Analog Devices) 0.250 mA
(accelerometers, gyroscopes, and amplifiers) was added to the
Total 23.75 mA
power consumption of the MICAz module in continuous
Battery life (Li-Ion at 580 mAh) 24.42 h
transmit mode. Experimental results suggested a total battery
life of approximately 15.45 h.

Discussion Onboard data processing can be achieved to substantially
reduce the overall dataflow by transmitting the already ana-
Performance and Limitations of In-Home WBAN lyzed data and warnings to the clinician, as suggested in other
During the reliability experiments, the system’s farthest limits studies [11], [12], [15]. Event management, as described by
of radio communication were tested in terms of sampling fre- Otto, would considerably reduce the overall transmit rate by
quencies and number of active sensor nodes. From the results recognizing characteristic features of raw sensor data. How-
shown in Figures 5 and 6, it is possible to determine some sort ever, onboard data processing also has a great impact on power
of comfort zone where the proposed WBAN system works consumption and signal latency. Compared with long-time
well and minimizes the probability of errors. This information monitoring scenarios, telerehabilitation sessions are relatively
gives a starting point for using a WBAN system during telere- short (1–2 h) and require real-time data transfer for quick access
habilitation sessions. An optimal configuration consisting of by clinicians. A compromise solution between the amount of
four active sensor nodes, each capable of accommodating computing done and overall bandwidth usage should be consid-
eight sensor inputs and a sampling rate of 100 Hz, was found ered. No consensus has yet been reached in regard to choosing
to offer the most reliability. It should be noted that this particu- the right sensors and data format relevant to clinicians. The
lar setup is a compromise solution between the number of multitude of applications makes it difficult to obtain a unique
active modules and the bandwidth requirement of the body standard. During experiments, signals from onboard sensors
sensors. Results also showed the possibility of using five were transmitted in their raw format, as this gives important
active modules by using a 50-Hz sampling frequency or by information about the limitations of the system.
taking only four of the eight available analog inputs. The sys- Unlike the results obtained by Ylisaukko-oja [25], the
tem was found to work correctly up to 800 Hz by using a sin- experiments conducted in the home environment showed
gle active sensor node with eight sensor inputs. However, the promising results as the system behaved the same way it did
addition of another active sensor node at this sampling during laboratory experiments. The presence of walls, floors,
frequency resulted in an immediate loss of communication and possible sources of noise (home appliances) did not
with the receiver. increase the overall number of transmission errors. In fact,


The rationale for in-home telerehabilitation is to
extend rehabilitation services to the people in
remote locations or with disabilities.

0.167% of transmission errors occurred during the reliability 1) The WBAN comprising four continuously streaming
test and a mean value of 0.125% was obtained throughout the modules (100 Hz, eight channels per module) is the opti-
house. A link can be made between the DFR and the number of mal configuration in terms of the number of active mod-
communication losses. As expected, the further the WBAN is ules and communication errors.
located from the receiver module, the greater the likelihood of 2) The WBAN when worn by an individual in a multilevel
losing contact with the base station. Telerehabilitation sessions house during daily activities provides comparable per-
usually take place in just one room where the camera, screen, formances and reliability as when in use under controlled
and microphone are installed. Although not always the case, laboratory conditions.
this study shows that the receiver unit could be located in 3) Data from the WBAN can be streamed over the Internet
another room for wiring convenience. The embedded algo- without interfering with the performances of a videocon-
rithms used for the experiments did not include any error man- ference link.
agement functions. As explained previously, a missing data Future Applications and Challenges
packet retransmission function could be embedded in the pro- Rehabilitation of patients with hip and knee replacements
gram. Loss of communication also implies data loss. Every time usually involves the presence of a clinician for the assessment
losses occur, the system must be restarted by consecutively of parameters such as joint range of motion. Remote assess-
sending a ‘‘stop’’ and a ‘‘start’’ command. This process takes a ment of this parameter is possible using WBANs and acceler-
few seconds and could be decreased to about 500 ms by auto- ometers. Wireless modules located at the patient’s ankle,
mating the process. Although not desirable, occasionally miss- knee, and hip could serve as a goniometer providing angles for
ing data packets is not critical during telerehabilitation sessions each segment using gravitational acceleration as a reference
as long as the packets are correctly identified as missing. [10]. These measurements could help clinicians to better
During the telerehabilitation session, sensors were wired to the assess their patients remotely. Combined signals from the sen-
WBAN, and data were sent over the Internet to a remote site shar- sors, such as respiratory belts, pulse oximeter, and accelerom-
ing the available bandwidth with a duplex audio and video signal eters, provide important information about a patient’s activity
from a Tandberg system (Tandberg 550 MXP). The WBAN level during rehabilitation. The WBAN could remotely
worked as expected, but some adjustments were made to transfer provide real-time data relating to patients’ exercise load and
the data throughput from the sensors via the Internet to the clinical fatigue. This information could also be used to monitor
site. Data reduction had to be done in order for the custom TCP/IP changes in patients’ health from one telerehabilitation session
Labview application to work correctly and keep the connection to the next. Wireless weight-bearing is possible using instru-
active. Data were filtered and downsampled three times before mented insoles wired to the WBAN. These sensors could be
sending them to a remote computer, resulting in a bandwidth of used during telerehabilitation to evaluate gait and posture
209 kb/s (Figure 7). This bandwidth also includes polling the parameters and provide real-time feedback for the patient as
router for statistics. Better results should be possible by allowing well as the clinician. Difficulties encountered during the home
more lag in the communication and by establishing an error- telerehabilitation experiments provided important information
managing algorithm for missing data packets. Overall, the telere- regarding design considerations for the next generation of
habilitation session was not affected by the presence of the wireless platforms. The bracelets should be robust, comforta-
WBAN system. Both clinical and home sites recorded great video ble, and easy for the patients to put on themselves [26]. The
and sound performances throughout the session. Data from the docking station used for battery charging and remote program-
sensors appeared on the clinician’s computer almost synchronized ming should be simple enough for the patients to clearly see
with the video signals. From a telerehabilitation viewpoint, the that the modules are correctly docked. Overall, the study dem-
battery life of the WBAN modules showed satisfactory results, as onstrated that remote monitoring from multiple sensor nodes
they can be used extensively through the day and recharged at is technically feasible using a WBAN system and videocon-
night using a docking station for charging batteries and remote ferencing system together. Future research will focus on data
programming. Despite the manufacturer’s warnings about not reduction, choice of relevant sensors for remote assessment,
using the transceivers within 1 m of each other, the system per- and software interfaces that will meet the emerging technical
formed well in all dynamic tasks done by the subject. Special care guidelines for telehealth applications [27].
must be taken with the whip antenna that projects from the brace-
let casing. These antennas will be replaced by smaller helix anten- Conclusions
nas embedded directly in the bracelets. The use of a wireless body area network linked to embedded
Experimental results obtained from laboratory and in-home and external sensors can increase the telepresence of rehabilita-
testing of the proposed WBAN system can be synthesized as tion professionals by providing important information that is
the following elements: otherwise difficult to obtain in that context. This article


described the capability of a Zigbee-based WBAN and its poten- geriatric rehabilitation. He is currently funded as a Chercheur
tial use in telerehabilitation applications. Experimental results Boursier Junior II by the Fonds de la recherche en sante du´
show that a typical setup of four wireless sensor nodes with eight ´
Quebec.
sensor inputs per node sampled at 100 Hz offers the most reli-
able radio communication performance and reliability. Tests in Address for Correspondence: Patrick Boissy, Research
a real house showed the possibility of using the wearable system Centre on Aging, University Institute of Geriatrics of Sher-
at home independently from the location of the receiver module brooke, Sherbrooke, Quebec, Canada. E-mail: patrick.
and in conjunction with videoconferencing equipment. boissy@usherbrooke.ca.

Acknowledgments
References
We wish to acknowledge the work done by Olivier Lessard- [1] L. Wakeford, P. P. Wittman, M. W. White, and M. R. Schmeler, ‘‘Telereha-
`
Fontaine and Simon Briere for the preliminary software bilitation position paper,’’ Am. J. Occup. Ther., vol. 59, no. 6, pp. 656–660,
developments on the WBAN and videoconferencing soft- 2005.
[2] J. M. Winters and J. M. Winters, ‘‘A telehomecare model for optimizing
ware. This project was funded by the Canadian Institutes for rehabilitation outcomes,’’ Telemed. J. E. Health., vol. 10, no. 2, pp. 200–212,
Health Research, Institute of Musculoskeletal Health and 2004.
[3] H. Hoenig, J. A. Sanford, T. Butterfield, and P. C. Griffiths, ‘‘Development of
Arthritis (IMHA) under the Invention—Tools, Techniques a teletechnology protocol for in-home rehabilitation,’’ J. Rehabil. Res. Dev.,
and Devices for Research and Medicine program (Grant No. vol. 43, no. 2, pp. 287–298, 2006.
200307ITM-120560). [4] J. A. Sanford, P. C. Griffiths, P. Richardson, K. Hargraves, T. Butterfield, and
H. Hoenig, ‘‘The effects of in-home rehabilitation on task self-efficacy in mobil-
ity-impaired adults: A randomized clinical trial,’’ J. Am. Geriatr. Soc., vol. 54,
Mathieu Hamel received his B.Eng. de- no. 11, pp. 1641–1648, 2006.
´
gree in 2003 from the Universite de Sher- [5] T. Sheridan, ‘‘Musings on telepresence and virtual presence,’’ Presence: Tele-
oper. Virtual Environ., vol. 1, no. 1, pp. 120–126, 1992.
brooke. In 2007, he completed his M.Sc. [6] W. Ijsselsteijn, H. de Ridder, J. Freeman, and S. Avons, ‘‘Presence: Concept,
degree in electrical engineering in the field determinants and measurement,’’ presented at the International Society for Optical
Engineering: Human Vision and Electronic Imaging, San Jose, CA, 2000.
of signal processing at the same university. [7] M. Tousignant, P. Boissy, H. Moffet, and H. Corriveau, ‘‘In home telerehabili-
He is now working at the Research Centre tation for older adults after discharge from an acute hospital or rehabilitation unit:
on Aging, Sherbrooke, Canada, as a research A proof-of-concept study and costs estimation,’’ Disabil. Rehabil.: Assist. Tech-
nol., vol. 1, no. 4, pp. 209–216, 2006.
engineer. His professional interests include [8] H. Moffet, M. Tousignant, H. Corriveau, P. Boissy, S. Robitaille, F. Marquis,
wireless devices applied to rehabilitation and biomedical signal and E. Anctil, ‘‘In home telerehabilitation after primary knee arthroplasty: A case
report,’’ presented at the World Conf. Physical Therapy, Vancouver, Canada,
processing. 2007.
[9] J. M. Winters, Y. Wang, and J. M. Winters, ‘‘Wearable sensors and telereha-
bilitation,’’ IEEE Eng. Med. Biol. Mag., vol. 22, no. 3, pp. 56–65, 2003.
[10] H. Zheng, N. D. Black, and N. D. Harris, ‘‘Position-sensing technologies for
´
Rejean J. G. Fontaine received his B.Eng. movement analysis in stroke rehabilitation,’’ Med. Biol. Eng. Comput., vol. 43,
´
degree in 1991 from the Universite de Sher- no. 4, pp. 413–420, 2005.
brooke. In 1999, he completed his Ph.D. [11] E. Jovanov, A. Milenkovic, C. Otto, and P. Groen, ‘‘A wireless body area
network of intelligent motion sensors for computer assisted physical rehabilita-
degree in electrical engineering at the same tion,’’ J. Neuroeng. Rehabil., vol. 2, no. 1, p. 6, 2005.
university in the field of microelectronics [12] P. Lukowicz, T. Kirstein, and G. Troster, ‘‘Wearable systems for health care
applications,’’ Methods Inf. Med., vol. 43, no. 3, pp. 232–238, 2004.
applied to neurostimulation (cochlear im- [13] J. Sakari and N. Jarkko, Wireless Technologies for Data Acquisition Systems.
plant). After a short stay in industry, he Dublin: Ireland: Trinity College Dublin, 2003.
´
returned to the Universite de Sherbrooke as [14] Zigbee-Alliance. (2006). ZigBee specifications [Online]. Available: http://
www.zigbee.org/en/spec_download/download_request.asp
a professor in 2001 and initiated works in electronics applied to [15] C. Otto, A. Milenkovic, A. Sanders, and E. Jovanov, ‘‘System architecture of
medical imaging. He is now the chairman of a research group a wireless body area sensor network for ubiquitous health monitoring,’’ J. Mobile
involved in the design of medical electronics dedicated to Multimedia, vol. 1, no. 4, pp. 307–326, 2006.
[16] S. Victor, C. Bor-rong, L. Konrad, R. F. F. J. Thaddeus, and W. Matt, Sensor
positron emission tomography scanners and to biomedical Networks for Medical Care. San Diego, CA: ACM Press, 2005.
signals. [17] Moteiv. (2006). Telos [Online]. Available: http://www.moteiv.com/
[18] K. Lorincz, D. J. Malan, T. R. F. Fulford-Jones, A. Nawoj, A. Clavel,
V. Shnayder, G. Mainland, M. Welsh, and S. Moulton, ‘‘Sensor networks for
Patrick Boissy received his B.Sc. degree emergency response: Challenges and opportunities,’’ IEEE Pervasive Comput.
in kinesiology from the Universite de ´ Mag., vol. 3, no. 4, pp. 16–23, 2004.
[19] MICAz. (2005). Crossbow technologies [Online]. Available: http://www.
Sherbrooke in 1991. He graduated from xbow.com/Products/Product_pdf_files/Wireless_pdf/MICAz_Datasheet.pdf
´ ´
the Universite de Montreal in 1999 with a [20] STMicroelectronics. (2004). LIS3L02AQ [Online]. Available: http://www.st.
Ph.D. degree in biomedical sciences with com/stonline/products/literature/ds/9321.pdf
[21] Murata. (2001). ENC-03M [Online]. Available: http://lc.fie.umich.mx/ifranco/
specialization in rehabilitation. After post- DATASHEET/giroscopio_CI/s42e3.pdf
doctoral training at Boston University’s [22] ADInstruments. (2005). MLT1133 [Online]. Available: http://www.adinstruments.
com/products/hardware/corporate/product/MLT1133/
Neuromuscular Research Centre, he joined [23] TinyOS. (2006). ‘‘Open-source operating system designed for wireless em-
´
the faculty of the Universite de Sherbrooke in 2002 in bedded sensor networks,’’ [Online]. Available: http://www.zigbee.org
the Kinesiology Department, where he is currently an associ- [24] NesC. (2003). nesC 1.1 language reference manual [Online]. Available:
http://nescc.sourceforge.net/papers/nesc-ref.pdf
ate professor. He holds appointments as a researcher at the [25] A.-A. Ylisaukko-oja, A.-E. Vildjiounaite, and A.-J. Mantyjarvi, ‘‘Five-point
Research Centre on Aging of the Health and Social Service acceleration sensing wireless body area network—Design and practical experien-
ces,’’ presented at ISWC, 8th IEEE Int. Symp. Wearable Computers, Arlington,
Centre, University Institute of Geriatrics of Sherbrooke, and VA, 2004.
at the Center of Excellence in Information Engineering of the [26] P. Bonato, ‘‘Advances in wearable technology and applications in physical
´
Universite de Sherbrooke. His research interests include medicine and rehabilitation,’’ J. Neuroeng. Rehabil., vol. 2, no. 1, p. 2, 2005.
[27] NIFTE. (2003). National initiative for telehealth framework of guidelines,
technological and clinical evaluation of telehealth applica- [Online]. Available: http://www.cst-sct.org/en/index.php?module=libraryVV_
tions and the study of the dose-response relationship in DocumentManager_op=downloadFileVV_File_id=54


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