Development Of A Warning System For The Epileptic Patients Which Detects The Crisis Moment And Production Of The Prototype #SciChallenge2017'

FATİH UÇAR
İLHAMİ OSMAN KARAKURT
11/IB (INTERNATIONAL BACCALAUREATE)
İSTANBUL KARTAL ANATOLIAN IMAM HATIP HIGH
SCHOOL

PROJECT NAME
Development Of A Warning System
For The Epileptic Patients Which
Detects The Crisis Moment And
Production Of The Prototype

EPİLEPSY
According to the World Health Organization, epilepsy affects 50 million
people in the world and at least 150 million people when their families
are involved. In addition to this, there are 2.4 million epilepsy cases
worldwide each year and about 700 thousand epilepsy patients are
estimated in Turkey.

EPİLEPSY
Epilepsy has important physical, psychological and social consequences
on the individual and the impact on one's quality of life is often greater
than other diseases. In epilepsy diagnosis, the information that the
patient's relatives give to the doctor is very important.

EPILEPSY
The frequency with which the vigil has come to pass has to be carefully
examined by the patient's relatives and the information should be
communicated to the doctor. Communication between doctors and
patients is very important.

SYSTEMS USED TODAY
EMPATICA
EPİLERT
EPİLEPSİ-SİZ

In this project, an electronic arm system was designed to help
individuals with epilepsy to perceive changes in the
individual's body, which will be helpful in public transport
during their daily lives. An Android phone application has been
developed that will analyze the data by working in harmony
with this electronic sleeve and inform the individual identified
in the system in the event of a crisis.
METHOD

When the present needs are observed, epileptic patients with sudden pulse
changes, vibrations in the body, muscle movements with the help of sensors
to detect the changes and the bluetooth application with the help of the
phone application to transfer the data is analyzed in the telephone
application is being done. If the data evaluated on the smart phone is
negative, the mobile application informs the identified persons in the system
by sending an emergency message and location information.
METHOD

The entire circuit is connected to the Arduino Mini circuit. For this, a
circuit design compatible with the Arduino mini has been designed. In
this circuit, the MPU6050 has 6 Axis Acceleration and Gyro Sensor,
EMG Sensor and Grove Heart Rate Sensor outputs.
ELECTRONIC DESIGN OF THE CIRCUIT

Figure-6 ARES Drawing of the Circuit Figure-7 Final Design of Printed Circuit Design

MPU6050 6 AXIS ACCELERATION AND GYRO SENSOR
With the axis acceleration and gyro sensor used in the system, the
movement speed of the arm of the individual with epilepsy is
measured and the data is sent to the processor of the system.
EMG SENSOR
The electrical signals generated by the muscles and nerves are a
sensor module for reading with Arduino and similar microcontroller
systems. By using this sensor module, changes in the nature of the
epileptic patient are observed.

GROVE HEART RATE SENSOR
This module can measure the variation of human blood motion in the
veins thanks to the optical technology. With the help of this sensor,
the heart rate of an individual with epilepsy is measured and the
received data is sent to the processor.
HC06 BLUETOOTH-SERIAL MODULE CARD
The project is also an important module card because it provides
communication. The data sent from the sensors and sent to the
processor are transferred to the phone application with the help of
bluetooth.

This circuit board, which is used as a processor in the project, collects the incoming
data and then transmits the data to the telephone application with bluetooth help.
These codes are loaded on this module card. The microcontroller on the module also
controls the sensors by this circuit board. In addition, the circuit elements are
integrated and operated on the Arduino pro mini card, and the data is collected and
transmitted through this circuit board.
Arduino Pro Mini

Table-1 Software Algorithm
DEVRENİN ELEKTRONİK YAZILIMI

DEVICE DESIGN
The integrated circuit was then designed and housed in a cuff. The integrated circuit,
which is placed in the armrest, works with rechargeable lipopiles. Besides, the sensors
used in the system are placed in the armrest considering the position where they can
measure in the cuff.
System Operator Arduino Mini
2. EMG Sensor Electrodes
3. EMG Sensor
4. Bluetooth Module
5. 6 Axis Acceleration and Gyro Sensor
6. Heart Rate Sensor
7. Lipopil
Figure-8 Drawing of the designed arm

Figure-9 Images from the designed mobile application
ANDROID TELEPHONE APPLICATION

ANDROID TELEPHONE APPLICATION
Phone app design in Android studio

Logical Processes of Design Processed Electronic
Device
The data from the sensors were evaluated and interpreted according to the
data obtained from the sources of America National Institute of Health,
Denmark Department of Clinical Neurophysiology and Beth Israel
Deaconess Medical Center. The alarm of the number defined in the system
occurs as a result of reading out data from the three sensors outside the data
range set at the same time. In this way, it is ensured that the moment of
crisis is accurately detected by observing these changes observed at the
time of crisis together.

HEART RATE DATA
Using data from the American Institute of Health's pulse data, the
age-pulse graph of a healthy individual is drawn and the data range
to be used in practice is determined. A healthy individual has an
average heart rate of 60-100 per minute. In addition, the limits of the
activities of the people have been determined to be between 75 and
170 considering the pulse rate. Exceeding the specified range of data
was defined as the probability of an epileptic individual having a
crisis.

HEART RATE DATA
Age Heart Rateı (bpm/m)
20 100-170
30 95-162
35 93-157
40 90-153
45 88-149
50 85-145
55 83-140
60 80-136
65 78-132
70 75-128
Table-2 Age and Pulse Rates of Healthy Individual by
America National Institute of Health
Graph-1 Age and Pulse Rates of Healthy Individual by America
National Institute of Health

EMG DATA
During this analysis, it was determined that muscle measurements in the arm of a normal
individual were between -0.4mV and 0.4mV. This data has also been verified by Oxford
Instruments Medical, UK. However, in a study conducted by Beth Israel Deaconess
Medical Center, a healthy individual of 44 years old had an EMG test on his arm at
intervals of several minutes, and the average of these data was taken.
Graph-2 Beth Israel
Deaconess Medical Center
The probability of an
individual experiencing
crisis

Axis Acceleration and Gyro Sensor Data
When interpretation was performed, it was observed that the difference in the acceleration
of the arm of a normal individual was small, and this data proved to be correct comparing
with the data of Denmark Department of Clinical Neurophysiology. The interpretation of
the data shows that during the epileptic crisis, the difference in the rate of change in the
arm of the individual is greater, and the large changes in velocity are interpreted as an
individual's probability of crisis.
Graph-3 Acceleration Data of Possibility of Individual Crisis of Denmark Department of Clinical
Neurophysiology

Logical Processes of Design Processed Electronic
Device
STANDARD DATA
RANGE
CRISIS TIME RANGE
75-170(BPM) P<75 or P>170(bpm)
STANDARD DATA
RANGE
DIFFERENCE OF
DATA RANGE OF
CRISIS TIME
-0.4/+0.4(mV) E >8
STANDARD DATA
RANGE
DIFFERENCE OF
DATA RANGE OF
CRISIS TIME
-5/+5(m/s2) A >10
PULSE DATA EMG DATA
ACCELERATION DATA
DATA RANGE FOR CRISIS
EMG DIFFERENCE HIGHER THAN 8
ACCELERATION DIFFERENCE HIGHER
THAN 10
PULSE P < 75 or P > 120

RESULT
• The prototype of the designed electronic device has been produced and necessary
software codes have been created and loaded into the system and the device has
been started.
• Tests have been done for system calibration.

RESULT
• In the first step, the data of healthy individuals were measured and the
consistency of intervals determined for the detection of crisis moment in the
system was tested.
• In the second stage, these data intervals are designed by simulating the crisis
moment.

Development Of A Warning System For The Epileptic Patients Which Detects The Crisis Moment And Production Of The Prototype #SciChallenge2017'

RECOMMENDATIONS
 A mobile application compatible with all operating systems can be developed.
 Directives can be added to the application to intervene in the patient. Cuff design
can be improved, more ergonomic design can be made.
 By adding night mode to the device, the physical changes and standard data
ranges that occur in the body during sleep can be adjusted.

RECOMMENDATIONS
 Currently, several epilepsy patients have been tested and the results may be tested
on 200-300 patients, so that the interval of crisis data can be determined more
healthily, and it can be understood that what kind of seizures are seen more
frequently.
 By using more sensitive sensors instead of currently used sensors and by
improving the algorithm and improving the measurements, and by detecting the
movements of the brain waves, the possibility of epilepsy crisis can be
determined more quickly and reliably, so that those who can help can be informed
more accurately.

 1. Aksun,Z.(2011). Epilepsi Hastalarının Yakınlarının Nöbet Sırasındaki Davranışları Ve Bunun Epilepsi Hakkındaki Bilgileri İle İlişkisi.
Ankara Üniversitesi, Tıp Fakültesi, Ankara.
 2. Beniczky,S., Polster, T., Kjaer, T., Hjalgrim H..(2013). Detection of generalized tonic–clonic seizures by a wireless wrist
accelerometer: A prospective, multicenter study. Department of Clinical Neurophysiology, University of Aarhus, Aarhus, Denmark.
 3. Blum, D., MD. (1999). Total impact of epilepsy: Biological, psychological, social, and economic aspects. Division of Neurology,
Barrow Neurological Institute.
 4. Delebe, E. (2014), Projeler İle Arduino, KODLAB Yayıncılık, İstanbul.
 5. Gürses, C.(2015).İş ve okul hayatından dışlanan epilepsi hastalarının yaşadıkları zorluklara dikkat çekmek için sen de ‘Epilepsiye
Objektif Ol’. Epilepsiye Objektif Ol Kongresi. 18 Haziran, İstanbul.
 6. Mollaoğlu,M. (2012).Epilepsili Hastalarda Yaralanmalar Ve İlişkili Bazı Faktörler. Cumhuriyet Üniversitesi, Sağlık Bilimleri
Fakültesi, Sivas.
 7. Nei, M.(2000). EKG Abnormalities During Partial Seizures In Refractory Epilepsy, American Epilepsy Society Meeting,1998, San
Diego.
 8. World Health organization.(2016). Epilepsy. Epilepsia Official Journal of the International League Against Epilepsy.Switzerland.
REFERENCES

Development Of A Warning System For The Epileptic Patients Which Detects The Crisis Moment And Production Of The Prototype #SciChallenge2017'

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