A Body Sensor Network can sense health parameters directly on the patient’s body, allowing 24/7 monitoring in an unobtrusive way. Several tiny sensors collect and route data to a special sink node. A new intra-vaginal biosensor was developed to study the relation between temperature variations and women health conditions, such as ovulation period, among others. We present a biosensor prototype and some initial results on real scenarios with a woman. One of the main issues in a body sensor network is the transformation of the sensor raw data into meaningful medical data for medical staff. Several approaches exist, from mobile device-based approaches to more powerful hardware such as a personal computer. This paper presents our current work in body sensor networks, namely a prototype for intra-vaginal temperature monitoring with initial results, and a mobile tool for data presentation of a three-tier body sensor network. The gathered results demonstrate the feasibility of the approach, contributing to the widespread application of body sensor networks

Caldeira, J.M.L.P.

Mendes, Américo

Neves, P.A.C.S.

Pereira, Orlando

Rodrigues, Joel

Repositório Científico do Instituto Politécnico de Castelo Branco

A Biosensor and Data Presentation Solution for Body Sensor Networks 
Paulo Neves†¥, João Caldeira†¥, Américo Mendes†, Orlando Pereira†, Joel Rodrigues† 
† Instituto de Telecomunicações, University of Beira Interior, Rua Marquês D’Ávila e Bolama, 6201-001 Covilhã, Portugal 
Phone +351-275319891, Fax +351-275319899, email: americo.mendes@sapo.pt; opereira@ubi.pt; joel.rodrigues@co.it.pt 
¥ Superior School of Technology, Polytechnic Institute of Castelo Branco, Av. do Empresário, 6000-767 C. Branco, Portugal 
Phone +351-272339300, Fax +351-272339399, email: pneves@co.it.pt; jcaldeira@est.ipcb.pt 
 
Abstract1— A Body Sensor Network can sense health 
parameters directly on the patient’s body, allowing 24/7 
monitoring in an unobtrusive way. Several tiny sensors collect 
and route data to a special sink node. A new intra-vaginal 
biosensor was developed to study the relation between 
temperature variations and women health conditions, such as 
ovulation period, among others. We present a biosensor 
prototype and some initial results on real scenarios with a 
woman. One of the main issues in a body sensor network is the 
transformation of the sensor raw data into meaningful medical 
data for medical staff. Several approaches exist, from mobile 
device-based approaches to more powerful hardware such as a 
personal computer. This paper presents our current work in 
body sensor networks, namely a prototype for intra-vaginal 
temperature monitoring with initial results, and a mobile tool 
for data presentation of a three-tier body sensor network. The 
gathered results demonstrate the feasibility of the approach, 
contributing to the widespread application of body sensor 
networks. 
I. INTRODUCTION 
Wireless sensor networks began in military applications, 
driven by the need to sense data on hostile environments with 
cost-effective solutions. Such networks are composed of 
small smart sensing nodes with a processing unit and 
memory, a wireless transceiver, and a limited power supply. 
One of the civil applications of sensor networks is in 
medical care, providing healthcare monitoring services. From 
the nature of the in-body sensing capabilities where the 
sensors are placed in contact or very near the person’s body, 
the designation evolved to body sensor networks [1]. 
Smart sensors scattered around a person’s body can sense 
medical parameters such as body temperature, perform 
Electro Cardio Grams (ECG), Electro Mio Grams (EMG), 
calculate heartbeat rate, in an efficient and unobtrusive way 
[2]. 
Figure 1 presents a typical body sensor network scenario 
[3]. A sink node is responsible for capturing raw sensor data 
from every sensor placed on the human body. Sink data can 
then be sent for latter processing and analysis. 
                                                
The authors would like to thank Prof. José Moutinho (M.D.), FCS-UBI, 
Portugal, for his expertise, sensor testing and validation, and invaluable 
assistance in this project. Part of this work has been supported by Instituto de 
Telecomunicações, Next Generation Networks and Applications (NetGNA), 
Portugal, and by the Euro-NF Network of Excellence of Seven Framework 
Program of EU. 
Although offline analysis of health data is essential, the 
online analysis is also needed. Moreover, a real-time 
biosensor data presentation for the patient and medical staff is 
more than desirable. Such scenario demands on-site 
transformation of raw sensor data to some meaningful form 
of data presentation that can easily be interpreted by the 
patient and the medical staff. 
 
EEG
ECG
BODY SENSOR NETWORK
TemperatureHeartbeat 
rate
SINK
 
Fig. 1. An example of a body sensor network. 
 
Some solutions rely on a personal computer [3], while 
others rely entirely on a mobile phone as a sink node [4]. 
Some even rely on dedicated portable hardware such as a 
wristwatch [5]. The mobile tool uses the convenience of a 
generic mobile phone with Bluetooth and Java technology; 
with a body sensor network where the sink is responsible for 
data capture and communication coordination among smart 
sensor nodes [6]. 
Medical research has been striving to find relationships 
between intra-vaginal temperature and certain female health 
conditions, such as ovulation period. A study presents some 
conclusions on the correlation between covert attention and 
basal temperature changes during the menstrual cycle phase 
on 22 adult females proves the importance of basal (intra-
vaginal) temperature [7].  
To measure the temperature a digital thermometer was 
given to each female to measure oral temperature each 
morning. Such process greatly disturbs the women, which 
need to take the measurement themselves, in opposite to a 
biosensor-based solution. 
Another proof of the importance of internal body 
temperature comes from a study using a radio pill developed 
for astronaut use, to access internal body temperature on 
athletes and take measures to cool them down, avoiding 
excessive fatigue [8]. 
This paper presents recent work on body sensor network, 
namely a prototype of an innovative intra-vaginal biosensor, 
and a mobile tool for data presentation on a Java and 
Bluetooth-enabled phone.  
The paper is organized as follows. Section II introduces the 
intra-vaginal biosensor with a software tool for data logging 
and initial measurements. On Section III a mobile tool for 
data presentation is briefly described and finally, on Section 
IV draws some conclusions and notes on future work. 
II. A BIOSENSOR FOR INTRA-VAGINAL TEMPERATURE 
MONITORING 
This section presents a prototype for intra-vaginal biosensor 
construction, with hardware details, a software tool, and some 
initial results. Due to the innovation of the proposed task, we 
find very encouraging the results obtained with this first 
prototype. 
A. Challenges 
The main challenge is the construction of a totally new 
biosensor for intra-vaginal temperature  (a. k. a. basal 
temperature) monitoring. To the best of the authors’ 
knowledge and medical team involved there is no biosensor 
that can sense intra-vaginal temperature, not even studies. 
The information provided by this sensor can be used to 
detect fertile cycle from temperature variation due to the 
association with ovulation, but can also be used to study 
temperature effects of some administrated medicines. The 
medical team also points its use for the detection of preterm 
labor and the discovery of new contraceptive methods. 
The biosensor must take into account the sensitivity of the 
body area, critical for the comfort of the user on a daily basis. 
Such comfort is related to the biosensor size, materials and 
produced heat. 
B. Biosensor architecture 
A first prototype has already been developed, based on a 
MA100 temperature sensor (thermistor) from General 
Electric (GE) [9] and an ALFATxp [10] development board. 
The development board features Java programming with 
integrated SD card reader/writer for permanent storage. 
Figure 2 shows the MA100 thermistor, which is able to 
measure temperatures in the range of 0ºC to 50ºC, and 
converts temperature values into electric resistance. 
 
Fig. 2. A detail on the MA100 thermistor from GE. 
Figure 3 presents the developed prototype. The MA100 
thermistor connects to the analog input of ALFATxp that 
translates an up to 3V signal with a 10 bits resolution, and 
connects to the personal computer through a USB connection. 
 
Fig. 3. Biosensor for intra-vaginal temperature monitoring 
prototype. 
 
The ALFATxp board connects to the personal computer in 
operation mode through a RS-232 serial connection. The 
USB connector allows personal computer access to the SD 
card content, like a flash drive (pen drive). Figure 4 shows 
computer connections needed to operate ALFATxp board. A 
preliminary study was performed with ambient temperature 
to asset the feasibility of the temperature monitoring solution 
before real testing on the field. 
 
Fig. 4. One of the development phases of the project where 
ALFATxp is connected to a PC using USB and serial bus. 
 
C. Software and Initial results 
A Java-based software tool to collect and present the 
readings on a personal computer was also developed, as 
shown in Figure 5. The values are collected into a comma-
separated values file on the personal computer, that can be 
imported for an available application, such as Microsoft® 
Excel®, for further processing if needed. 
The application has a simple interface that controls the 
sampling frequency, shows the read sensor values, allows 
basic control over sampling operation (start/stop) and 
presents the total samples gathered. 
 
Fig. 5. Temperature monitoring application screenshot. 
 
With the built prototype and the software tool, the medical 
team managed to achieve some preliminary results to asset 
the biosensor working condition. We ran a single test on one 
lady, and the results got us very encouraged to proceed. After 
biosensor placement we start collecting data, which is 
presented in graphical form in Figure 6. 
 
Fig. 6. Graphical representation of the measured 
temperature signal on a given woman. 
 
The graph shows three different phases of observation: (a) 
the first phase up to the 8-minute, (b) the second phase from 
8 to around 15-minute, and finally (c) from 15 to 17. The first 
phase corresponds to the sensor response to the difference 
between ambient and intra-vaginal temperature. The second 
phase is the real intra-vaginal temperature, while the last 
phase corresponds to the removal of the biosensor. 
III. MOBILE SOLUTION FOR DATA PRESENTATION 
This section presents a mobile tool for body sensor network 
data processing and presentation, using a Java and Bluetooth 
enabled phone. System architecture, the mobile tool with 
some screenshots and tests and validation are presented here. 
A. System architecture 
The mobile device connects to the body sensor network 
sink’s device through wireless communication (Bluetooth). 
The sink manages the network responsibilities at the 
biosensor level, so a failure on the mobile device (for 
instance the absence of it) does not yield a failure on the body 
sensor network. Such approach clearly shields the more 
critical part of the system, the body sensor network from the 
presentation layer. 
Figure 7 presents the system architecture. The mobile 
device can communicate with any body sensor network, 
provided it has the required authentication credentials. The 
number of biosensors that can me monitored is sink-
dependant; with currently up to 8 channels, although only one 
channel is displayed on the screen at a given time. 
EEG
ECG
BODY SENSOR NETWORK
TemperatureHeartbeat 
rate
Processing 
and 
visualization
SINK
 
Fig. 7. System architecture for mobile tool development. 
 
A mobile application development has different software 
engineering guidelines when compared to a personal 
computer application. The screen orientation, size, resolution 
and aspect ratio is radically different, the input methods are 
much more limited (only a D-Pad instead of a mouse), among 
other constraints. 
A special attention was given to resolution independence of 
the application GUI, with calculations to achieve the 
optimum readability based on screen resolution. Also the 
number of key presses was kept to a minimum, with shortcuts 
for the most used functions. 
B. Mobile tool 
The mobile tool was entirely developed in J2ME with 
Connected Limited Device Configuration (CLDC) version 
1.1 and Mobile Information Device Profile (MIDP) version 
2.0. Besides the communication API developed for 
authenticated Bluetooth connection with the sink, the mobile 
tool captures, processes and presents data on the screen of the 
mobile device. 
Two main information screens are defined in this mobile 
tool: a graphical screen with an oscilloscope-like presentation 
of a given channel, and a graphical screen with the actual 
sensor value. 
Figure 8 presents the two main screens of the application. 
On the left a shadowed area graphically represents signal 
value, and a line across the screen represents the threshold. 
On top several information is displayed about the signal 
itself, the programmed threshold value, among other values. 
 
Fig. 8. The two main screens of the mobile application: 
instant value (left) and oscilloscope-like (right). 
 
On the right side of Figure 8 an oscilloscope-type 
representation of the signal is displayed, with signal 
evolution over time. The maximum, minimum and average 
signal values, actual signal value, and graphical scale 
information is also given on the bottom part of this screen. 
The tool also creates a logging file on the mobile device, 
using comma-separated values, which can be imported into a 
personal computer (for instance using Bluetooth technology 
also) for further analysis. 
C. Deployment and validation 
The mobile tool can be deployed onto every mobile device 
in Bluetooth range through the use of a dedicated installer on 
a Windows® computer. This removes the burden of 
individual installations on every device. 
The mobile tool was validated through the use of on-field 
tests on several mobile phones from the World leader 
manufacturer, namely Symbian series 40 and S60 enabled 
phones such as Nokia® N80, N95, 6280 and 5200. Even in 
the least hardware-featured device, Nokia 5200 the 
application worked without flaws for a complete 24-hour 
cycle, even in the presence of cellular communication.  
Since such behavior is more operating system-related than 
the application itself, we also stressed the application with 
communication failures, namely with Bluetooth 
disconnection simulating loss of power on the sink device. 
IV. CONCLUSIONS AND FURTHER WORK 
We presented some of the latter research results obtained 
while working with body sensor networks. Such work is very 
promising with proven results both on the development of a 
new biosensor until now inexistent and the development of 
associated software tools. We clearly believe in our first 
results, however more results must be captured to validate the 
prototype. The medical team is also very enthusiastic and 
looking forward to try this new sensor to study more than the 
ovulation period. 
The mobile tool makes body sensor network solutions more 
reachable for non-technical persons, with appellative 
presentation of results, in two different forms.  
As for future work we are developing another prototype of 
the intra-vaginal biosensor, namely with miniaturization in 
mind, and using wireless communication. In terms of 
presentation tools, we are refining the existing solution for 
data presentation based on mobile devices. 
REFERENCES 
[1] D. Yun, J. Kang, J.-e. Kim, and D. Kim, "A Body 
Sensor Network Platform with Two-Level 
Communications", in IEEE International Symposium on 
Consumer Electronics (ISCE 2007), Irving, TX, USA, 
2007, pp. 1-6. 
[2] P. Neves, M. Stachyra, and J. Rodrigues, "Application 
of Wireless Sensor Networks to Healthcare Promotion", 
JCOMSS - Journal of Communications Software and 
Systems, Vol. 4, n. 3, pp. 181-190, September 2008. 
[3] S.-L. Chen, H.-Y. Lee, C.-A. Chen, C.-C. Lin, and C.-
H. Luo, "A Wireless Body Sensor Network System for 
Healthcare Monitoring Application", in IEEE 
Biomedical Circuits and Systems Conference (BIOCAS 
2007), Montréal, Qc, Canada, 2007, pp. 243-246. 
[4] L. Zhong, M. Sinclair, and R. Bittner, "A Phone-
centered Body Sensor Network Platform Cost, Energy 
Efficiency & User Interface", in International Workshop 
on Wearable and Implantable Body Sensor Networks 
(BSN 2006), Cambridge, MA, USA, 2006. 
[5] U. Maurer, A. Rowe, A. Smailagic, and D. P. 
Siewiorek, "eWatch: A Wearable Sensor and 
Notification Platform", in international Workshop on 
Wearable and Implantable Body Sensor Networks (BSN 
2006), Cambridge, MA, USA, 2006. 
[6] O. Pereira, P. Neves, and J. Rodrigues, "Mobile 
Solution for Three-tier Biofeedback Data Acquisition 
and Processing", in IEEE Global Communications 
Conference (IEEE GLOBECOM 2008), Ad Hoc, Sensor 
and Mesh Networking Symposium (GC '08 AHSN), New 
Orleans, LA, USA, 2008, pp. 1-5. 
[7] J. Beaudoin and R. Marrocco, "Attentional Validity 
Effect Across the Human Mentrual Cycle Varies With 
Basal Temperature Changes", Behaviourial Brains 
Research, vol. 158, pp. 23-29, 2005. 
[8] W. Jones, "Taking Body Temperature, Inside Out", 
IEEE Spectrum, pp. 13-15, January 2006. 
[9] MA100 Biomedical Chip Thermistor, URL: 
http://www.gesensing.com/products/MA100.htm, 
Accessed in November 2008. 
[10] ALFATxp Development System, URL: 
http://www.alfat.co.uk/alfatxp-development-
system.html, Accessed in November 2008. 


English

A biosensor and data presentation solution for body sensor networks

Neves, P.A.

Repositório do Instituto Politécnico de Castelo Branco

A Biosensor and Data Presentation Solution for Body Sensor Networks Paulo Neves†¥, João Caldeira†¥, Américo Mendes†, Orlando Pereira†, Joel Rodrigues† † Instituto de Telecomunicações, University of Beira Interior, Rua Marquês D’Ávila e Bolama, 6201-001 Covilhã, Portugal Phone +351-275319891, Fax +351-275319899, email: americo.mendes@sapo.pt; opereira@ubi.pt; joel.rodrigues@co.it.pt ¥ Superior School of Technology, Polytechnic Institute of Castelo Branco, Av. do Empresário, 6000-767 C. Branco, Portugal Phone +351-272339300, Fax +351-272339399, email: pneves@co.it.pt; jcaldeira@est.ipcb.pt  Abstract1— A Body Sensor Network can sense health parameters directly on the patient’s body, allowing 24/7 monitoring in an unobtrusive way. Several tiny sensors collect and route data to a special sink node. A new intra-vaginal biosensor was developed to study the relation between temperature variations and women health conditions, such as ovulation period, among others. We present a biosensor prototype and some initial results on real scenarios with a woman. One of the main issues in a body sensor network is the transformation of the sensor raw data into meaningful medical data for medical staff. Several approaches exist, from mobile device-based approaches to more powerful hardware such as a personal computer. This paper presents our current work in body sensor networks, namely a prototype for intra-vaginal temperature monitoring with initial results, and a mobile tool for data presentation of a three-tier body sensor network. The gathered results demonstrate the feasibility of the approach, contributing to the widespread application of body sensor networks. I. INTRODUCTION Wireless sensor networks began in military applications, driven by the need to sense data on hostile environments with cost-effective solutions. Such networks are composed of small smart sensing nodes with a processing unit and memory, a wireless transceiver, and a limited power supply. One of the civil applications of sensor networks is in medical care, providing healthcare monitoring services. From the nature of the in-body sensing capabilities where the sensors are placed in contact or very near the person’s body, the designation evolved to body sensor networks [1]. Smart sensors scattered around a person’s body can sense medical parameters such as body temperature, perform Electro Cardio Grams (ECG), Electro Mio Grams (EMG), calculate heartbeat rate, in an efficient and unobtrusive way [2]. Figure 1 presents a typical body sensor network scenario [3]. A sink node is responsible for capturing raw sensor data from every sensor placed on the human body. Sink data can then be sent for latter processing and analysis.                                                 The authors would like to thank Prof. José Moutinho (M.D.), FCS-UBI, Portugal, for his expertise, sensor testing and validation, and invaluable assistance in this project. Part of this work has been supported by Instituto de Telecomunicações, Next Generation Networks and Applications (NetGNA), Portugal, and by the Euro-NF Network of Excellence of Seven Framework Program of EU. Although offline analysis of health data is essential, the online analysis is also needed. Moreover, a real-time biosensor data presentation for the patient and medical staff is more than desirable. Such scenario demands on-site transformation of raw sensor data to some meaningful form of data presentation that can easily be interpreted by the patient and the medical staff.  EEGECGBODY SENSOR NETWORKTemperatureHeartbeat rateSINK Fig. 1. An example of a body sensor network.  Some solutions rely on a personal computer [3], while others rely entirely on a mobile phone as a sink node [4]. Some even rely on dedicated portable hardware such as a wristwatch [5]. The mobile tool uses the convenience of a generic mobile phone with Bluetooth and Java technology; with a body sensor network where the sink is responsible for data capture and communication coordination among smart sensor nodes [6]. Medical research has been striving to find relationships between intra-vaginal temperature and certain female health conditions, such as ovulation period. A study presents some conclusions on the correlation between covert attention and basal temperature changes during the menstrual cycle phase on 22 adult females proves the importance of basal (intra-vaginal) temperature [7].  To measure the temperature a digital thermometer was given to each female to measure oral temperature each morning. Such process greatly disturbs the women, which need to take the measurement themselves, in opposite to a biosensor-based solution. Another proof of the importance of internal body temperature comes from a study using a radio pill developed for astronaut use, to access internal body temperature on athletes and take measures to cool them down, avoiding excessive fatigue [8]. This paper presents recent work on body sensor network, namely a prototype of an innovative intra-vaginal biosensor, and a mobile tool for data presentation on a Java and Bluetooth-enabled phone.  The paper is organized as follows. Section II introduces the intra-vaginal biosensor with a software tool for data logging and initial measurements. On Section III a mobile tool for data presentation is briefly described and finally, on Section IV draws some conclusions and notes on future work. II. A BIOSENSOR FOR INTRA-VAGINAL TEMPERATURE MONITORING This section presents a prototype for intra-vaginal biosensor construction, with hardware details, a software tool, and some initial results. Due to the innovation of the proposed task, we find very encouraging the results obtained with this first prototype. A. Challenges The main challenge is the construction of a totally new biosensor for intra-vaginal temperature  (a. k. a. basal temperature) monitoring. To the best of the authors’ knowledge and medical team involved there is no biosensor that can sense intra-vaginal temperature, not even studies. The information provided by this sensor can be used to detect fertile cycle from temperature variation due to the association with ovulation, but can also be used to study temperature effects of some administrated medicines. The medical team also points its use for the detection of preterm labor and the discovery of new contraceptive methods. The biosensor must take into account the sensitivity of the body area, critical for the comfort of the user on a daily basis. Such comfort is related to the biosensor size, materials and produced heat. B. Biosensor architecture A first prototype has already been developed, based on a MA100 temperature sensor (thermistor) from General Electric (GE) [9] and an ALFATxp [10] development board. The development board features Java programming with integrated SD card reader/writer for permanent storage. Figure 2 shows the MA100 thermistor, which is able to measure temperatures in the range of 0ºC to 50ºC, and converts temperature values into electric resistance.  Fig. 2. A detail on the MA100 thermistor from GE. Figure 3 presents the developed prototype. The MA100 thermistor connects to the analog input of ALFATxp that translates an up to 3V signal with a 10 bits resolution, and connects to the personal computer through a USB connection.  Fig. 3. Biosensor for intra-vaginal temperature monitoring prototype.  The ALFATxp board connects to the personal computer in operation mode through a RS-232 serial connection. The USB connector allows personal computer access to the SD card content, like a flash drive (pen drive). Figure 4 shows computer connections needed to operate ALFATxp board. A preliminary study was performed with ambient temperature to asset the feasibility of the temperature monitoring solution before real testing on the field.  Fig. 4. One of the development phases of the project where ALFATxp is connected to a PC using USB and serial bus.  C. Software and Initial results A Java-based software tool to collect and present the readings on a personal computer was also developed, as shown in Figure 5. The values are collected into a comma-separated values file on the personal computer, that can be imported for an available application, such as Microsoft® Excel®, for further processing if needed. The application has a simple interface that controls the sampling frequency, shows the read sensor values, allows basic control over sampling operation (start/stop) and presents the total samples gathered.  Fig. 5. Temperature monitoring application screenshot.  With the built prototype and the software tool, the medical team managed to achieve some preliminary results to asset the biosensor working condition. We ran a single test on one lady, and the results got us very encouraged to proceed. After biosensor placement we start collecting data, which is presented in graphical form in Figure 6.  Fig. 6. Graphical representation of the measured temperature signal on a given woman.  The graph shows three different phases of observation: (a) the first phase up to the 8-minute, (b) the second phase from 8 to around 15-minute, and finally (c) from 15 to 17. The first phase corresponds to the sensor response to the difference between ambient and intra-vaginal temperature. The second phase is the real intra-vaginal temperature, while the last phase corresponds to the removal of the biosensor. III. MOBILE SOLUTION FOR DATA PRESENTATION This section presents a mobile tool for body sensor network data processing and presentation, using a Java and Bluetooth enabled phone. System architecture, the mobile tool with some screenshots and tests and validation are presented here. A. System architecture The mobile device connects to the body sensor network sink’s device through wireless communication (Bluetooth). The sink manages the network responsibilities at the biosensor level, so a failure on the mobile device (for instance the absence of it) does not yield a failure on the body sensor network. Such approach clearly shields the more critical part of the system, the body sensor network from the presentation layer. Figure 7 presents the system architecture. The mobile device can communicate with any body sensor network, provided it has the required authentication credentials. The number of biosensors that can me monitored is sink-dependant; with currently up to 8 channels, although only one channel is displayed on the screen at a given time. EEGECGBODY SENSOR NETWORKTemperatureHeartbeat rateProcessing and visualizationSINK Fig. 7. System architecture for mobile tool development.  A mobile application development has different software engineering guidelines when compared to a personal computer application. The screen orientation, size, resolution and aspect ratio is radically different, the input methods are much more limited (only a D-Pad instead of a mouse), among other constraints. A special attention was given to resolution independence of the application GUI, with calculations to achieve the optimum readability based on screen resolution. Also the number of key presses was kept to a minimum, with shortcuts for the most used functions. B. Mobile tool The mobile tool was entirely developed in J2ME with Connected Limited Device Configuration (CLDC) version 1.1 and Mobile Information Device Profile (MIDP) version 2.0. Besides the communication API developed for authenticated Bluetooth connection with the sink, the mobile tool captures, processes and presents data on the screen of the mobile device. Two main information screens are defined in this mobile tool: a graphical screen with an oscilloscope-like presentation of a given channel, and a graphical screen with the actual sensor value. Figure 8 presents the two main screens of the application. On the left a shadowed area graphically represents signal value, and a line across the screen represents the threshold. On top several information is displayed about the signal itself, the programmed threshold value, among other values.  Fig. 8. The two main screens of the mobile application: instant value (left) and oscilloscope-like (right).  On the right side of Figure 8 an oscilloscope-type representation of the signal is displayed, with signal evolution over time. The maximum, minimum and average signal values, actual signal value, and graphical scale information is also given on the bottom part of this screen. The tool also creates a logging file on the mobile device, using comma-separated values, which can be imported into a personal computer (for instance using Bluetooth technology also) for further analysis. C. Deployment and validation The mobile tool can be deployed onto every mobile device in Bluetooth range through the use of a dedicated installer on a Windows® computer. This removes the burden of individual installations on every device. The mobile tool was validated through the use of on-field tests on several mobile phones from the World leader manufacturer, namely Symbian series 40 and S60 enabled phones such as Nokia® N80, N95, 6280 and 5200. Even in the least hardware-featured device, Nokia 5200 the application worked without flaws for a complete 24-hour cycle, even in the presence of cellular communication.  Since such behavior is more operating system-related than the application itself, we also stressed the application with communication failures, namely with Bluetooth disconnection simulating loss of power on the sink device. IV. CONCLUSIONS AND FURTHER WORK We presented some of the latter research results obtained while working with body sensor networks. Such work is very promising with proven results both on the development of a new biosensor until now inexistent and the development of associated software tools. We clearly believe in our first results, however more results must be captured to validate the prototype. The medical team is also very enthusiastic and looking forward to try this new sensor to study more than the ovulation period. The mobile tool makes body sensor network solutions more reachable for non-technical persons, with appellative presentation of results, in two different forms.  As for future work we are developing another prototype of the intra-vaginal biosensor, namely with miniaturization in mind, and using wireless communication. In terms of presentation tools, we are refining the existing solution for data presentation based on mobile devices. REFERENCES [1] D. Yun, J. Kang, J.-e. Kim, and D. Kim, "A Body Sensor Network Platform with Two-Level Communications", in IEEE International Symposium on Consumer Electronics (ISCE 2007), Irving, TX, USA, 2007, pp. 1-6. [2] P. Neves, M. Stachyra, and J. Rodrigues, "Application of Wireless Sensor Networks to Healthcare Promotion", JCOMSS - Journal of Communications Software and Systems, Vol. 4, n. 3, pp. 181-190, September 2008. [3] S.-L. Chen, H.-Y. Lee, C.-A. Chen, C.-C. Lin, and C.-H. Luo, "A Wireless Body Sensor Network System for Healthcare Monitoring Application", in IEEE Biomedical Circuits and Systems Conference (BIOCAS 2007), Montréal, Qc, Canada, 2007, pp. 243-246. [4] L. Zhong, M. Sinclair, and R. Bittner, "A Phone-centered Body Sensor Network Platform Cost, Energy Efficiency & User Interface", in International Workshop on Wearable and Implantable Body Sensor Networks (BSN 2006), Cambridge, MA, USA, 2006. [5] U. Maurer, A. Rowe, A. Smailagic, and D. P. Siewiorek, "eWatch: A Wearable Sensor and Notification Platform", in international Workshop on Wearable and Implantable Body Sensor Networks (BSN 2006), Cambridge, MA, USA, 2006. [6] O. Pereira, P. Neves, and J. Rodrigues, "Mobile Solution for Three-tier Biofeedback Data Acquisition and Processing", in IEEE Global Communications Conference (IEEE GLOBECOM 2008), Ad Hoc, Sensor and Mesh Networking Symposium (GC '08 AHSN), New Orleans, LA, USA, 2008, pp. 1-5. [7] J. Beaudoin and R. Marrocco, "Attentional Validity Effect Across the Human Mentrual Cycle Varies With Basal Temperature Changes", Behaviourial Brains Research, vol. 158, pp. 23-29, 2005. [8] W. Jones, "Taking Body Temperature, Inside Out", IEEE Spectrum, pp. 13-15, January 2006. [9] MA100 Biomedical Chip Thermistor, URL: http://www.gesensing.com/products/MA100.htm, Accessed in November 2008. [10] ALFATxp Development System, URL: http://www.alfat.co.uk/alfatxp-development-system.html, Accessed in November 2008. 

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A biosensor and data presentation solution for body sensor networks

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