Volume : IV, Issue : VI, June - 2015

EPILEPTIC SEIZURE CLASSIFICATION USING TIME–FREQUENCY ANALYSIS OF EEG SIGNALS.

Priyanka R. Khot

Abstract :

 Seizure is a transient abnormal behavior of neurons within one or several neural networks, which limits the patients physical and mental activities. This review paper gives idea to transform the EEG data using twelve Cohen class kernel functions in order to facilitate the time–frequency analysis. The transformed data thus obtained is exploited to formulate a feature vector consists of modular energy and modular entropy that can better model the time–frequency behavior of the EEG data. The feature vector is fed to an Artificial Neural Network (ANN) classifier in order to classify epileptic seizure data originating from different parts.

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Article: Download PDF   DOI : 10.36106/ijsr  

Cite This Article:

Priyanka R. Khot Epileptic Seizure Classification Using TimeFrequency Analysis of Eeg Signals International Journal of Scientific Research, Vol : 4, Issue : 6 June 2015

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