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DEVELOPMENT OF A GENERIC AND FLEXIBLE HUMAN BODY

WIRELESS SENSOR NETWORK

Evdokimos I. Konstantinidisa, Panagiotis D. Bamidis

a, Dimitrios Koufogiannis

a 

aAristotle University of Thessaloniki, School of Medicine, Laboratory of Medical Informatics,P.O. Box 323 54124, Thessaloniki, Greece

evdokimosk@gmail.com

Abstract: Wireless sensor networks on human

body have become essential in the field of patient

monitoring. The fact that completely non-invasive

sensors can be used attached on clothes, facilitates

measurements in daily tasks. The aim of this paper is

to demonstrate the approach we followed upon

developing a generic and flexible patient tele-monitoring system based on custom sensor devices

and a communication control unit (CCU). A sensor

device consists of the measurement control part

(microcontroller) and the sensing part (be it

commercial or homemade sensors). The CCU plays

the role of the master device of the wearable network

and is based on a microcontroller and a Bluetooth

module. The CCU scans all possible attached sensors

on the bus of the network and constructs XML files

based on the sensor devices and the network

structure. In addition a software suite has also been

developed in order to i) manage the different

protocols and projects, ii) manage the operatingsystem service and iii) provide different

representations/visualizations of the signals (online

or offline) in 2D graphs, FFT or 3D human model in

the appropriate environment. At the PC side, the

operating system service utilizes the XML

descriptions in order to acquire the measurement

from the CCU and store them in a database. The

usefulness of the system is demonstrated through a

set of conducted experiments, while the importance

of the approach is discussed in the light of recent

published literature. 

I. Introduction

The last decade has witnessed a rapid surge of 

interest in new sensing and monitoring devices for 

healthcare and the use of wearable/wireless devices and 

sensor networks for clinical applications. Technological

achievements led to small, low power, intelligent and

low cost sensors[1]. Besides that, MEMS

(Microelectromechanical systems), a relatively new

technology of sensors, plays an important role in recent

sensing and monitoring devices. MEMS are small

integrated devices or systems that combine electrical

and mechanical components. MEMS scale and benefits

made them very popular in modern designs [2].

Based on these investments, the research and

development of sensor networks has flourished recent

years. One of the most promising applications of sensor

networks is for human health monitoring. Body Sensor

Network (BSN) is considered as a vital system for home

patient monitoring. A number of small sensors,

strategically placed on the human body, create a bodyarea network that can provide a lot of information not

only for patients monitoring but also for human daily

activities. The main goal for such type of body networks

is to monitoring patients under natural physiological

conditions for the detection and prevention of transient 

but possibly life threatening abnormalities [3]. The very

small size of the sensing systems, the non-invasive

methods, and the wireless and wearable functionality

makes this goal reachable.

The Body Sensor Networks can produce raw datafrom the measurements or factors that depend on these

measurements. In case of raw data production, a storage

system must accompany the whole system (Laptop,PC). In the other case a mobile phone or a storage media

(cards) can satisfy the data manipulation. However,

factors depend on raw data analysis and repeatableexperiments. The analysis of the acquired data of each

sensor’s measurements and the analysis of the

integration of all the measurements can reveal important

conclusions about health, body movements,

physiological status and daily activities.

Despite the technological achievements in sensingand monitoring devices, a big effort must be done so all

the requirements of such an assuming system to be

fulfilled. Issues related to system integration, sensor

size, low-power sensor’s consumption, wireless linksand signal processing have still to be researched. 

 Moreover, issues related to quality of service, security,

multi-sensor data fusion, and decision support are

active research topics needed for deploying body sensor 

networks [4]. 

The aim of this paper is to present the approach we

followed upon developing a generic and flexible patient

tele-monitoring system based on custom sensor devices

and a communication control unit (CCU). We present

hardware and software architecture of a working

wireless sensor network system for monitoring patient

health and daily activities. The system consists of an

unknown volume of different type sensor devices, theCCU (network coordinator), the accompanying software

and the database. This platform is extendable and can

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meet the requirements of medical research in a lot of 

sections that deal with body status and health.

II. Materials and Methods

II.1 Main Concept

The proposed wireless body area sensor network forhealth monitoring relies on the hardware part (CCU andsensors network) and the software (PC with the

appropriate setup). A lot of different type of sensors can

be integrated in the network. This option arises from the

ability of the CCU to survey and to identify all the

connected sensors. The CCU generates XML files based

on the collected information. The XML file describesthe whole network structure. Making use of this file, the

appropriate software on the PC side is able to acquire

measurement data. An operating system service has

been developed for the acquisition and data storing

procedures. The data storing is based on MySQL

engine. Apart from the XML files and servicemanagement, the software is also responsible for

providing different representations/visualizations of the

signals (online or offline) in 2D graphs, FFT or 3D

human model. The main concept is presented at Figure

1.

Figure 1 Main concept

II.2 SensorsFor experimenting purposes, three different types of 

sensors have been developed: a) accelerometer [8], b)

temperature and c) skin conductance. Every sensor is

accompanied by a microcontroller [5]. The

microcontroller is responsible for communicating and

gathering data from the sensor, knowing what type of 

sensor is and answering to network questions (arriving

from CCU). During firmware programming, special

registers in the microcontroller are programmed

according to the sensor’s type and output format. Due to

the effort for less power consumption, every sensor

consists of as less as possible parts. Figure 3 presents

the accelerometer sensor.

II.3 Communication Control Unit (CCU)

Playing the role of the gateway, the CCU isresponsible for collecting data from the sensor network 

and forwarding them to the PC. As the master of the

network, during the initialization process, scans all

possible connected sensors and identifies the attached

ones. The initialization process proceeds with a virtualtransmition of acquired data. In this stage the CCUestimates the time needed for a complete cycle of 

gathering and transmitting data (maximum sampling

frequency that can be achieved). The XML file that is

generated by the CCU contains information about the

available protocols of communication, the number and

type of sensors and the registers that participate in theconversion of acquired data to measured data. The

format of a child of the XML, which describes the

sensors, is:

-<signal_1 signal_name="a1x"> 

<signal_type>accelerometer</ signal_type> 

<zero_offset>512</ zero_offset> <number_to_multiply>5</ number_to_multiply> 

<measurement_unit>"mG "</ measurement_unit> 

</ signal_1> 

The conversion relies on the OS service in order not

to cumber the CCU. While the CCU receives a

command from the PC, it starts gathering data from the

sensor network and transmits it through Bluetooth

wireless connection. The CCU and the sensors are

connected physically through four wires. Two of them

comprise the communication bus layer and the other

two provide with power every device.

Figure 2 CCU connection diagram

Figure 3 CCU homemade device (left). Accelerometer sensor,

top and bottom view (right).

II.4 Service and Database

Trying to develop a user friendly platform on the PC

side, we developed an OS service which is responsible

for data acquisition and storing. The service’s argument

is an XML file. This file contains all the description for

the hardware as well as information for the database andthe patient under monitoring. The service can be

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controlled from a wide variety of software. As a

transmitted packet from the hardware contains headerdata, the service can distinguish packets between

successive raw data.

The database engines that are supported by the

service are MySQL and MS Access files. When a

project depended on new XML file is started, a newtable is constructed in the selected database. The tablecontains fields according to the attached sensors on the

network (information from the XML file). In addition,

the table contains fields about date and time of each

sample.

II.5 SoftwareThe software suite that has been developed

integrates the control and management of the units that

have been described up to this point. If a user needs to

begin a new project, a wizard by the software asks for

the XML file that describes the hardware, the desirable

data storage engine, information about the patient undermonitoring and a description of the sensors position on

the human body. The software is able to control the OS

service and to provide different

representations/visualizations of the signals. 2D graphs

of selected or all the signals can be displayed (filtered or

not) in combination with their FFT transformations. The

3D human model, making use of the position

description of the accelerometer sensors, represents the

body movements [8].

III. RESULTS

III.1 Evaluation MethodIn order to validate the system that has been

developed, an experiment took place. Eight

accelerometer sensors and a temperature sensor attached

on the body. The eight accelerometers attached on the

body limbs (before and after every joint). The

temperature sensor position was on the chest (near the

right elbow). In order to take under consideration the

communication lost packets, we selected a stadium as

the experiment environment (big range between PC andhuman). The sampling frequency that achieved was

98Hz.

Figure 4 Evaluation Method

The human under monitoring exercised in 5 stages:a) Walking for 60 meters.

b) Walking for 60 meters with a higher tempo

c) Relaxing at standing positiond) Relaxing at sitting position

e) Walking for 10 meters and sprinting for 10 meters

III.1 Experiment Results

The experiment time duration was ~12 minutes. Inthis period 50817 packets were sent and only two of them lost.

Figure 5 Communication lost packets (software module)

Figure 6 Right Calf acceleration and body temperature during

the experiment.

The normal walking is represented at the first stage.

The next stage represents the acceleration duringwalking with higher tempo (and more heavy footsteps).

In the next two stages the human was relaxing in

standing and sitting position. The final stages show the

sprint situations.

The upper visualization (Figure 6) is the

temperature. During walking and especially during

walking in higher tempo it started growing. The normal

fall of the temperature was during relaxing.

Figure 7 FFT transform of calf acceleration (512 samples

window ~ 5 seconds). The main frequncy reveal to be

proportional to the footsteps tempo.

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IV. DISCUSSION

Wireless sensor networks show great commitment

for biomedical monitoring systems. In this paper, a

system of wireless sensor network and data storing and

analysis structures has been developed to acquire and

represent measurements of different types of sensorsand especially accelerometers. Inertial movementsensing has a high potential for use in human movement

analysis. The low cost of the hardware and non-invasive

detection techniques make such systems essential and

desirable in home care and other managed healthcare

institutions [9].

The applications are not limited to the above

mentioned. Other potential applications include man-

machine interfacing and feedback in artificial human

movement control [6].

V. CONCLUSIONS

We present a first attempt towards understanding

and realizing a body sensor network and its sensing

infrastructure. Several challenges need to be addressed 

in building such a system. Our prototype demonstrates

initial design choices and helps reveal related issues.

VI. ACKNOWLEDGEMENTS

VII. REFERENCES

[1] Chris Otto, Aleksandar Milenkovic, Corey Sanders,

Emil Jovanov, System Architecture of a Wireless Body

Area Sensor Network for Ubiquitous HealthMonitoring.

[2] Stephen Beeby, Graham Ensell, Micahael Kraft,

Neil White, MEMS Mechanical Sensors, Artech House.

Boston London, 2004

[3] Benny P.L. Lo, Surapa Thiemjarus, Rachel King and

Guang-Zhong Yang, Body Sensor Network – A

Wireless Sensor Platform for Pervasive Healthcare

Monitoring, In proceedings of UbiHealth 2004,

Nottingham, England[4] A. Lymberis, L. Gatzoulis, Wearable Health

Systems: from smart technologies to real applications,

In proceedings of EMBC 2006, New York City, New

York, USA[5] Microchip. (2007, 10/2007). dsPIC30F6015

microcontroller: Technical data.[6] I.F. Akyildiz, W. Su, Y. Sankarasubramaniam, E.

Cayirci, Wireless sensor networks: a survey

[7] H. Kanasugi, R. Shibasaki. Measurement and

analysis of human behavior using wearable sensors., In

Proceedings of The 25th Asian Conference on Remote

Sensing, volume 2, pages 1218--1223, 2004.

[8] STMicroelectronics. (2007, 09/2007). LIS3L02AL

3-axis accelerometer: Technical data.

[9] J. A. Stankovic, Q. Cao, T. Doan, L. Fang, Z. He, R.

Kiran, S. Lin, S. Son, R. Stoleru, A. Wood, Wireless

Sensor Networks for In-Home Healthcare:Potential and Challenges, In HCMDSS, June 2005