基于C-FFuzzyEn的神经电生理信号同步性分析

基于传统互模糊熵，结合分数阶微积分提出分数阶互模糊熵（C-FFuzzyEn），并基于该算法分析混沌耦合系统的同步性，进行健康对照者和癫痫患者不同脑区脑电信号的耦合性对比。结果表明，与传统互模糊熵相比，C-FFuzzyEn提高了不同耦合度模型的区分能力；与健康对照者相比，癫痫患者在癫痫发作时不同通道脑电信号之间C-FFuzzyEn较小，与癫痫发作时各神经元同步放电现象相吻合；相比互模糊熵，C-FFuzzyEn区分健康对照者与癫痫患者脑区之间脑电信号同步性的效果更好。C-FFuzzyEn可应用于脑电信号等神经电生理信号的同步性分析。

Neural electrophysiological signal synchronization analysis using C-FFuzzyEn

Based on cross fuzzy entropy (C-FuzzyEn) and fractional calculus, cross fractional fuzzy entropy (C-FFuzzyEn) is proposed for analyzing the synchronization of coupled chaotic system and comparing the changes of EEG signal synchronization in healthy controls and epileptic patients. The results demonstrate that C-FFuzzyEn is superior to C-FuzzyEn in distinguishing models of different coupling degrees. In addition, compared with healthy controls, patients with epilepsy has lower C-FFuzzyEn during seizure activity, which is consistent with the synchronous firing of neurons during epileptic seizures. C-FFuzzyEn is better than C-FuzzyEn at distinguishing the synchronicity of EEG signals between brain regions in healthy controls and epileptic patients. C-FFuzzyEn can be used to analyze the synchronization of neural electrophysiological signals such as EEG signals.