Epileptic seizure prediction by the detection of seizure waveform from the pre-ictal phase of EEG signal

Khakon Das, Debashis Das Chakladar, Partha Pratim Roy, Atri Chatterjee, Shankar Prasad Saha

Abstract: Highlights•Proposed model has 3 parts: feature extraction, pattern matching and post-processing.•Proposed model efficiently predicts the seizure from the pre-ictal phase of EEG.•Pre-ictal follows the ictal phase, so advanced prediction can be done.•It provides a warning message to the doctors regarding the upcoming seizure.•The accuracy and F1-measure of the model are 92.66% and 94.86% respectively.