Detection of Epileptic Seizure from EEG Signal Using Discrete Wavelet Transform and J48 Classifier

Detection of Epileptic Seizure from EEG Signal Using Discrete Wavelet Transform and J48 Classifier

 we present the application on wavelet decomposition and J48 Decision tree model for Electroencephalograph signals (ECG) and its classification. Decision making perform by feature extraction using the discrete wavelet transform (DWT) with different function and the EEG classification using J48 classifiers. In this work, the extracted features using DWT are fed into J48 classifier for seizure detection of EEG signal with an accuracy of 95%. The proposed J48 model achieved higher accuracy rates than that of the K-NN algorithm.