A Novel Mobile Epilepsy Warning System

  • Ahmet Alkan
  • Yasar Guneri Sahin
  • Bekir Karlik
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4304)


This paper presents a new design of mobile epilepsy warning system for medical application in telemedical environment. Mobile Epilepsy Warning System (MEWS) consists of a wig with a cap equipped with sensors to get Electroencephalogram (EEG) signals, a collector which is used for converting signals to data, Global Positioning System (GPS), a Personal Digital Assistant (PDA) which has Global System for Mobile (GSM) module and execute Artificial Neural Network (ANN) software to test current patient EEG data with pre-learned data, and a calling center for patient assistance or support. The system works as individual sensors obtain EEG signals from patient who has epilepsy and establishes a communication between the patient and Calling Center (CC) in case of an epileptic attack. MEWS learning process has artificial neural network classifier, which consists of Multi Layered Perceptron (MLP) neural networks structure and back-propagation training algorithm.


Global Position System Artificial Neural Network Artificial Neural Network Model Personal Digital Assistant Multi Layer Perceptron 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Langfitt, J., Meador, K.: Want to Improve Epilepsy Care? Ask the Patient. Neurology 62, 6–7 (2004)Google Scholar
  2. 2.
    Adeli, H., Zhou, Z., Dadmehr, N.: Analysis of Eeg Records In An Epileptic Patient Using Wavelet Transform. J. Neuroscience Math. 123, 69–87 (2003)CrossRefGoogle Scholar
  3. 3.
    Alkan, A., Koklukaya, E., Subasi, A.: Automatic Seizure Detection In EEG Using Logistic Regression and Artificial Neural Network. Journal of Neuroscience Methods 148(2), 167–176 (2005)CrossRefGoogle Scholar
  4. 4.
    Misra, U.K., Kalita, J., Mishra, S.K., Yadav, R.K.: Telemedicine in neurology: Underutilized potential. Neurology India 53(1), 27–31 (2005)CrossRefGoogle Scholar
  5. 5.
    Bingham, E., Patterson, V.: Nurse led epilepsy clinics: A telemedicine approach. Journal of Neurology Neurosurgery and Psychiatry 72(2), 216–216 (2002)Google Scholar
  6. 6.
    Patterson, V., Bingham, E.: Telemedicine for epilepsy: A useful contribution. Epilepsia 46(5), 614–615 (2005)CrossRefGoogle Scholar
  7. 7.
    Subasi, A.: Automatic detection of epileptic seizure using dynamic fuzzy neural networks. Expert Systems with Applications 31(2), 320–328 (2006)CrossRefMathSciNetGoogle Scholar
  8. 8.
    Subasi, A., Alkan, A., Koklukaya, E., Kiymik, M.K.: Wavelet Neural Network Classification Of EEG Signals By Using AR Model With MLE. Preprocessing Neural Networks 18(7), 985–997 (2005)CrossRefGoogle Scholar
  9. 9.
    Subasi, A., Erçelebi, E., Alkan, A., Koklukaya, E.: Comparison of Subspace-Based Methods With AR Parametric Methods In Epileptic Seizure Detection. Computers in Biology and Medicine 36(2), 195–208 (2006)Google Scholar
  10. 10.
    Ceylan, R., Ozbay, Y.: Comparison of FCM, PCA and WT Techniques for Classification ECG Arrhythmias Using Artificial Neural Network. Expert Systems with Applications, Corrected Proof, available online (in Press, 2006)Google Scholar
  11. 11.
    Kiymik, M.K., Akin, M., Subasi, A.: Automatic Recognition Of Alertness Level By Using Wavelet Transform And Artificial Neural Network. Journal of Neuroscience Methods 139(2), 231–240 (2004)CrossRefGoogle Scholar
  12. 12.
    Andrzejak, R.G., Lehnertz, K., Rieke, C., Mormann, F., David, P., Elger, C.E.: Indications of Nonlinear Deterministic And Finite Dimensional Structures In Time Series Of Brain Electrical Activity: Dependence On Recording Region And Brain State. Physics Rev. E. 64, 061907 (2001)CrossRefGoogle Scholar
  13. 13.
    Karlik, B., Tokhi, O., Alci, M.: A Novel Technique for Classification of Myoelectric Signals for Prosthesis. In: CD-ROM Proceeding of IFAC 2002, Barcelona (July 2002)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Ahmet Alkan
    • 1
  • Yasar Guneri Sahin
    • 1
  • Bekir Karlik
    • 2
  1. 1.Department of Computer EngineeringYasar UniversityIzmirTurkey
  2. 2.Department of Computer Engineering, BuyukcekmeceFatih UniversityIstanbulTurkey

Personalised recommendations