Abstract：To measure the relationship between different muscles accurately and reasonably under the regulation of central nervous system is a challenging research topic. Based on the time-varying copula function and combining with the entropy theory, a time-varying copula mutual information (MI) estimation method was proposed in this paper and applied it to the coupling analysis of sEMG signals of biceps brachii (BB) and triceps brachii (TB) in the characteristic frequency bands (theta, alpha and beta) during wrist flexion (WF) and wrist extension (WE) movement of 10 subjects. Meanwhile, the method was compared with the static copula function to verify its effectiveness. The data we used were derived from Ninapro DB4. Experimental results show that compared to the static copula function, the time-varying copula function has a better fitting degree for the intermuscular dependent structure. There was a significant frequency band difference in the intermuscular coupling strength described by the time-varying copula MI (P<0.05), which was specifically expressed as: the higher the frequency band, the lower the intermuscular coupling strength (WF: 0.075 7~0.214 7 bit. WE: 0.078 0~0.237 3 bit), while the static copula MI incorrectly underestimates the intermuscular coupling strength. In conclusion, the time-varying copula MI provided an advanced theoretical guidance method for intermuscular coupling analysis and showed a very broad application prospect.
王洪安, 佘青山, 马玉良, 孔万增, 田玉平. 基于时变copula互信息的肌间耦合分析[J]. 中国生物医学工程学报, 2022, 41(2): 140-150.
Wang Hongan, She Qingshan, Ma Yuliang, Kong Wanzeng, Tian Yuping. Time-Varying Copula Mutual Information for Intermuscular Coupling Analysis. Chinese Journal of Biomedical Engineering, 2022, 41(2): 140-150.
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