Epileptic seizure detection using Inclined Planes system Optimization algorithm(IPO)

About 1% of the people in the world suffer from epilepsy. The first stage of the treatment of epilepsy is the accurate diagnosis. One way to diagnose epilepsy is the precise analysis of EEG signals. Therefore various techniques have been proposed in the literature for the detection of epileptic seizures in EEG signals. In this article, we have distinguished and separated the epileptic EEG signals from the normal EEGs, by using a new intelligent and heuristic algorithm, called Inclined Planes system Optimization. We used wavelet transform for extracting features, because of nonlinear and non-stationary properties of the EEG signals. Then we diagnosed epilepsy, by using extracted features from wavelet transform and implement them on IPO algorithm. According to this study, we found out the IPO has got a high ability to diagnosis epilepsy in complicated and non-stationary EEG signals.