The sample entropy and its application in EEG based epilepsy detection / 生物医学工程学杂志

ABSTRACT

It is of great importance for the detection of epilepsy in clinical applications. Based on the limitations of the common used approximate entropy (ApEn) in the epilepsy detection, this paper analyzes epileptic EEG signals with the sample entropy (SampEn) approach, a new method for signal analysis with much higher precision than that of the ApEn. Data analysis results show that the values from both ApEn and SampEn decrease significantly when the epilepsy is burst. Furthermore, the SampEn is more sensitive to EEG changes caused by the epilepsy, about 15%-20% higher than the results of the ApEn.