Detection of Epileptic Spike-Wave Discharges Using SVM

Abstract

In this work, support vector machine (SVM) is applied for detecting epileptic spikes and sharp waves in EEG signal. EEG data are obtained from two-channels EEG monitor on Swiss mice. Our technique maps these intracranial electroencephalogram (EEG) time series into corresponding novelty sequences by classifying short-time, energy based statistics computed from one-second windows of data. Numeric simulation studies demonstrate the effect of the SVM detection, and a comparison between SVM and artificial neural network with back-propagation algorithm is presented to show the advantages of SVM algorithm for detecting epileptic spike-wave discharge in EEG time series.