Automated Detection of Epileptic Seizures Using Wavelet Entropy Feature with Recurrent Neural Network Classifier

Electroencephalograms (EEG) are the brain signals that provide us the valuable information about the normal or epileptic state of the brain. In this paper the EEG signals were characterized by wavelet, sample and spectral entropy approach and the recurrent neural network classifier is used for the automated detection of epileptic seizures.