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

Year 2015, Volume: 3 Issue: 1, 14 - 18, 13.01.2015

Apdullah Yayik , Esen Yildirim Yakup Kutlu Serdar Yildirim

https://doi.org/10.18201/ijisae.14531

Cited By: 8

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.

Keywords

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

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