Epileptic State Detection: Pre-ictal, Inter-ictal, Ictal

Authors

  • Apdullah Yayik Turkish Army Forces Mustafa Kemal University
  • Esen Yildirim
  • Yakup Kutlu
  • Serdar Yildirim

Keywords:

Epileptic State Detection, Second-Order Difference Plot, Neural Network

Abstract

Epileptic seizure detection and prediction from electroencephalography (EEG) is a vital area of research. In this study, Second-Order Difference Plot (SODP) is used to extract features based on consecutive difference of time domain values from three states of EEG (pre-ictal, ictal and inter-ictal), and Multi-Layer Neural Network classifier is used to classify these three classes. The proposed technique is tested on a publicly available EEG database and classified with Naive Bayes and k-nearest neighbor classifiers. As a result, it is shown that overall accuracy of 98.70% can be achieved by using the proposed system with Neural Network classifier.

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Author Biography

Apdullah Yayik, Turkish Army Forces Mustafa Kemal University

Communication Officer 

PhD Student

 

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Published

16.02.2015

How to Cite

Yayik, A., Yildirim, E., Kutlu, Y., & Yildirim, S. (2015). Epileptic State Detection: Pre-ictal, Inter-ictal, Ictal. International Journal of Intelligent Systems and Applications in Engineering, 3(1), 14–18. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/153

Issue

Vol. 3 No. 1 (2015)

Section

Research Article

License

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