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Detection of synchrony in biosignals using cross fuzzy entropy
Hong-Bo Xie1, Yong-Ping Zheng, Guo Jing-Yi
1Jiangsu University, Jiangsu, 212013 PR of China. xiehb@sjtu.org
Abstract:
A new method, namely Cross fuzzy entropy (C-FuzzyEn) analysis, that could enable the measurement of the synchrony or similarity of patterns between two distinct signals, was presented in this study. Tests on simulated data sets showed that C-FuzzyEn was superior to the conventional cross sample entropy (C-SampEn) in several aspects, including giving entropy definition in case of small parameters, better relative consistency, and less dependence on record length. The proposed C-FuzzyEn was then applied for the analysis of simultaneously recorded electromyography (EMG) and mechanomyography (MMG) signals during sustained isometric contraction for monitoring local muscle fatigue. The results showed that the C-FuzzyEn of EMG-MMG decreased significantly during the development of muscle fatigue. The time-decrease trend of C-FuzzyEn is similar to the mean frequency (MNF) of EMG, the commonly used muscle fatigue indicator.
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