Tonic Clonic Seizure Classification Based on EEG Signal Using Artificial Neural Network Method

Abstract

Abstract—An instrument to record the activity of brainwave in specific time called Electroencephalography (EEG). EEG signal can be used to analyze the epilepsy disease. One of a signal that appears when a seizure happens called Tonic Clonic Seizure (TCSZ) signal. Brainwave of seizure patient has a low frequency with a tighter pattern than brainwave of normal people. The purpose of this research is to classify between the tonic clonic seizure signal and normal EEG signal using Artificial Neural Network (ANN) Backpropagation method. At first, the features of signals will be extracted by using Mel Frequency Cepstral Coefficients (MFCC). The output of MFCC will be the input for ANN Backpropagation classifier. The result of this research has reached 100% of accuracy value with 13-MFCCs features and 25-MFCCs features.

Keywords—TCSZ, ANN Backpropagation, MFCC, Epilepsy