Spike based Epilepsy Detection Algorithm from an EEG Signal

Epilepsy seizures are the assumed brain activities which interrupt the common brain activity of the brain. To detect the epilepsy we use the EEG signals. This paper shows new spike based component as it is one of principle qualities of epilepsy inclined EEG. The IMFs (Intrinsic Mode Decomposition) of the EEG is computed by utilizing EMD (Empirical Mode Decomposition) and initial five IMFs are utilized as a part of proposed study. Since the nearness of spikes builds the adequacy of sign, greatest estimation of each IMF is utilized as highlight to prepare the classifier. The characterization of EEG sign into seizure or no-seizure is finished by utilizing ANN. The consequences of the every IMF is recorded exclusively and finished up the third IMF demonstrates the best nearness of spikes. The after effects of proposed technique are moreover contrast and other existing strategies for the approval.