Coupling analysis of epileptic EEG signals based on the multiscale mutual model entropy
Ning Ji, Jiafei Dai, Jun Wang, Fengzhen Hou · 2016
The Multiscale Mutual Model Entropy algorithm is presented to quantify the coupling degree between two EEG time series collected at the same time on different scales.We extracted the characteristics of EEG signals from the healthy and epileptics based on the algorithm.The results show that the entropy value of healthy people is higher than that of epileptics.And with the increase of scale, the difference in entropy value between them is more obvious.It indicates that Multiscale Mutual Entropy can distinguish the coupling difference between normal samples and case samples, which is significant for the clinical pathological assessment and brain disease diagnosis.