Dalibor Janckulík, Ondřej Krejcar and Jan Martinovič
VŠB – Technical University of Ostrava, FEI, 17. listopadu 15, 708 33 Ostrava, Czech Repulic
Keywords: PDA, embedded device, biotelemetry, wireless, ECG.
Abstract: This project deals with the problems of utilization of mobile equipment working in the biomedicine field,
particularly telemedicine. This field is relatively new; it focuses on the observation of life functions from a
distance. Practically developing system works with an ECG sensor connected to mobile equipment, such as
PDA/Embedded, based on Microsoft Windows operating system. The whole system is based on the
architecture of .NET Compact Framework, and other products, such as SQL Server by Microsoft too. This
work also deals with the communication of mobile equipment with sensors and with the server via
Bluetooth, WiFi, and GPRS/EDGE. The mobile equipment used serves primarily for measuring and
processing of data from the sensors and their visualization as a graph. The data is also given to the server for
further processing and the analysis of current health of the patients, due to small efficiency of the mobile
equipment (Janckulík, 2007). The main task we deal with in the server part of application is receiving of the
data via web services and further processing, management and analysis of this data. For the analysis of
received data and further evaluation of the electrocardiogram, there is a self-organizing neural network
(Vašíček, 2007).
Many middle-aged people like businessmen, CEOs,
managers and other have very hectic lives with
much stress and without good ways of living.
Sometimes these people have a collapse, breakdown
or heart attack and must be in hospitals or health
resorts for a long time to regenerate their bodies.
The time that they spend in these institutions, is
nonutilisable and very long for them. Possibilities of
today physics are restricted by many of prescripts so
patients cannot use some of the newest techniques
(like hyperbaric or arctic chambers), which make it
possible to reduce the regeneration time by weeks or
months. For example, these chambers are restricted
to patients in the first six months after heart attack
due to no information about patients’ conditions
during the procedure.
Here is the main area of utilization of our
telemetric system. Of course the use of our system is
not limited only to businessmen, but it is targeted to
middle-aged people with some knowledge about
new technology like mobile phones. The price of
client devices of our system is not low, so we
suppose people who can invest to these sorts of
The basic idea is to create a system that controls
important information about the state of a
wheelchair-bound person (monitoring of ECG and
pulse in early phases, then other optional values like
temperature or oxidation of blood ...), his situation
in time and place (GPS) and an axis tilt of his body
or wheelchair (2axis accelerometer).
Values are measured with the existing
equipment, which communicates with the module
for processing via Bluetooth wireless
communication technology. Most of the data
(according to heftiness) is processed directly in
PDA or Embedded equipment to a form that is
acceptable for simple visualization. Two variants
are possible in case of embedded equipment – with
visualization and without visualization (entity
with/without LCD display). Data is continually sent
by means of GPRS or WiFi to a server, where it is
being processed and evaluated in detail. Processing
and evaluating on the server consists of - receiving
data, saving data to data storage, visualization in an
advanced form (possibility to recur to the older
graph, zoom on a histogram (graph with historical
trend), copying from the graphs, printing graphs),
automatic evaluation of the critical states with the
help of advanced technologies (algorithms) that use
Janckulík D., Krejcar O. and Martinovi
c J. (2008).
In Proceedings of the First International Conference on Biomedical Electronics and Devices, pages 170-173
DOI: 10.5220/0001051901700173
Artificial intelligence to notify the operator about
the critical state and its archiving.
Application in PDA, Embedded equipment is
comfortable, with minimum time - the first
configuration, but also configuration after downfall
of application. The level of visualization will be
lower. The described system can be used with small
modifications for monitoring of patients in hospitals
or people working in extremely hard conditions. The
biggest limitation is the availability of measuring
devices in acceptable and adaptable sizes or
comfortable enough to have one around.
The measuring device (ECG, plethysmograph)
was tested in extreme conditions in a cryogen room
in Teplice (-136°C), where the final system will be
installed. Implementation of the data transmission
security was not solved. The whole system is
classified as „work in progress“ system and it is in a
testing phase where we found mistakes and repaired
This system consists of several interconnected parts
that can communicate among themselves, so they
can approach their function. These parts are:
measuring sensor, PDA or embedded device, and
server for data processing and evaluation. Beside
these, the most important parts that are worth
mentioning are various kinds of accessories, such as
GPRS, WiFi, GSM, Bluetooth or GPS modules. By
means of them we can communicate. We mostly use
the fastest technology in signal coverage.
Data acquisition and data transmission are the
most important parts of this system. The
Responsible for correct working are: correct sensor
configuration, sensor calibration, data transfer
synchronization, and mutual communication
between sensors and data receiver.
Figure 2: Bluetooth communication.
The system can display saved data from a database
file. The doctor can configure or set a neurone
network. A change of that is shown in the XML file
enshrining, where the neurone network setting of the
patient is kept.
The doctor receives information about
worsening of patient’s status. In case of doctor’s
reaction, he sends for an expert assistance, such as a
helicopter or an ambulance. In case of false alarm,
he can configure a neurone network or leave it
unchanged if that was a sporadic incorrect
The patient can browse data concerning his
health status. Measured data is sent to server by
WEB service.
Client’s data are not only received but also
preprocessed (data checking, risk elimination etc.).
Measured data is saved. And now, it is possible to
analyze the data using a neurone network. If the
analysis shows that the measured data from ECG is
critical, a warning is sent. That notifies a doctor of
incoming data.
2.1 Mobile Part
The main part of the whole system is an Embedded
or PDA device. The difference in applications for
measurement units is the possibility to visualize the
measured data in both Real-time Graph and
Historical Trend Graph, which can be omitted on an
embedded device.
PDA is a much better choice for Personal
Healthcare, where the patient is already healthy and
needs to review his condition, or for multiple person
usage. Embedded devices can be designed for one
user, with the option to use an external display used
for settings or with the possibility of usage in
extreme conditions.
The application is communicating with an ECG
Measurement Unit (Corbelt or Blue Keg) through a
virtual serial port using wireless Bluetooth
technology. Then, after pushing a button, all
necessary parameters are set and the communication
may begin. Measured data is stored on a SD
Figure 1: Measurement schema.
Memory Card in a database in MS SQL Server 2005
Mobile Edition.
Figure 3: PDA/MDA/SmartPhone visualization.
The performance of available devices seems
insufficient for sequential access; parsing of
incoming packets is heavily time-consuming.
Pseudo paralleling is required. If Windows Mobile
OS versions 2003 to 5.0 are used, the processing of
data from a professional EKG is not realizable due
to thread count limitations. A newer operating
system (Windows Mobile 6) can be used to solve
Figure 4: PDA/MDA/SmartPhone application.
Current application is highly specialized and written
to accommodate specific hardware. Usage of any
other hardware is not possible. This is due to
different methods of packet folding, which are
unique on each device (
Corbelt, BlueEKG datasheet,
2007). This is partly caused by the length of the
Telemedicine branch. Operating of the device is
simplified as much as possible with the least
possible number of steps regarding user registration,
measurement device connection and the
measurement itself. The informations about user, as
ID, name, surname, address and application
properties are stored in the system registry
(HKEY_CURRENT_USER / Software / Guardian).
Working (saving, reading, finding) with registry is
easier and faster as saving this informations in file.
User registry values are crypted with simple
algorithm (shifting char ASCII value).
2.2 Server Part
In order to run a server, an operating system
supporting IIS is needed. IIS is an Internet
Information Server application allowing users to
connect to the web server by the well-known HTTP
protocol. The web service transfers data between the
server and PDA/Embedded devices. It reads the
data, sends acknowledgments, stores the data in the
database and reads it from there. The service is built
upon ASP.NET 2.0 technology. The SOAP protocol
is used for the transport of data, which is in XML
format. That is an advantage since it allows
communication of multiple different technologies
and platforms.
The Wireless ECG approaches a real
professional ECG with data rate as high as 800
records per second (
Corbelt, BlueEKG datasheet,
). That makes 48,000 records per minute and
2,880,000 per hour. Considering 100 patients, the
value gets to 288,000,000 records per hour. Even if
the server accepted only 50 records per second, the
sum of records for 100 patients per hour would be
18 million. That is an extreme load for both the
server and the database system; hence a better way
of storing data is needed.
Methods that devices communicating with the
web service can use include:
receiving measured data.
receiving patient data.
deleting a patient.
patient data sending.
To observe measured data effectively, visualization
is needed. A type of graph as used in professional
solutions is an ideal solution. To achieve this in a
server application, a freeware Zed Graph library can
be used. For data analysis, neural nets are a
convenient solution. However, there are problems in
the automatic detection of critical states. Every
person has a specific ECG pattern. What is
completely normal for one person can indicate crisis
for another. The Neural net has to learn to
distinguish critical states of each patient separately.
BIODEVICES 2008 - International Conference on Biomedical Electronics and Devices
Figure 5: Server visualization.
Basic characteristics of a neuron network:
10 x 10 neurons.
learning is based on 3-4 minutes of
recording, which is approximately 36,000-
45,000 recorded values.
incorrect values are filtered out.
filtering decreases the amount of values to
about 10%, which is still good enough for
the learning cycle with 4,200 values takes
approximately 30 seconds (CPU PIII 1.2
GHz) with C# implementation.
To make the specialist’s or operator’s intervention
possible, the system must be provided with a user-
friendly interface, possibly imitating those on
medical appliances. This area is still in an early
phase of development.
Data acquired from the measuring device is
incomprehensible for a man, because it is
represented by a HEX format packet. The data
needs to be stripped of redundant information like
packet numbering and transformed to a recognizable
state – a graph. This is done during the packet
parsing in PDA/Embedded device, where HEX
information 2 bytes in length are transformed to a
binary state, where the data is carried on the first 12
bits. It is transformed to a decimal state and sent for
further processing – sending the data to the server,
storing it in a local database or visualizing it.
The visualization using PDA/Embedded is just a
simple visualization of a curve in real-time or
historical graph. In the server application, the
visualization is far more complex, with the
possibility of storing the current curve as an image,
printing, or zooming.
Neural net of the SOM type on the server is
10x10 in size. The initial weight of each neuron is
random. The weights are assigned progressively by
learning. Finally, the whole structure is ready to
accept data to analyze. Each patient has his own
neural net stored on a server in XML format.
The evolution of Telemedicine is unstoppable and
apparent; therefore ways need to be found to
improve the quality of hospital services, spa services
or hazardous environment workplaces. The area of
software products working in embedded devices in
hazardous environments or PDAs in personal
healthcare is still open and unoccupied. Personal
healthcare products are freely available
(, and
with minor hardware modifications they can be used
for data acquisition using wireless Bluetooth, WiFi
or ZigBee technologies. By means of data transfers,
the acquired data can be gathered in database
systems providing access to your personal doctor,
who can be:
alerted in case of trouble.
send information and system message to our
remotely change properties of devices
(change alarm of critical limits in ECG,
Why are there systems available to protect our
property and not our health? Is it not the most
valuable property of ours?
Janckulík, D., 2007, bachelor thesis, Personal telemetric
system – Personal mobile assistant.
Vašíček, P., 2007, diploma thesis, Personal biotelemetric
Corbelt, BlueEKG datasheet, 2007;;
Neuron networks prognosis -
courseware/data/chapter/36nan060/s23.html - (16.4.
Selforganizing neuron network - SOM, Kohonen maps -
loclanku=2006051401 - (13.3.2007).