Analysis of epileptic EEG based on improved sample entropy algorithm

The physiological state of the system can be evaluated by quantifying the complexity of pathological time series. For physiological time series with large amplitude changes, traditional methods often do not work. An improved sample entropy (iSampEn) algorithm is proposed based on wave mode to measure the complexity of nonlinear system. Through the analysis of the complexity of epileptic electroencephalogram (EEG), it is concluded that iSampEn algorithm can obviously distinguish epileptic EEG from normal EEG. The results of this study are helpful for clinical diagnosis.