基于时变copula互信息的肌间耦合分析

如何准确、合理地衡量中枢神经系统调控下的肌间耦合关系,是一个富有挑战性的研究课题。在时变copula函数的基础上,通过与熵理论相结合,提出一种时变copula互信息估计方法,并将其应用于10名被试腕屈、腕展运动过程中,肱二头肌(BB)和肱三头肌(TB)记录的表面肌电(sEMG)信号在theta、alpha、beta等特征频段的耦合分析,同时对照静态copula函数验证其有效性,所用数据源自Ninapro DB4。实验结果表明,较之静态copula函数,时变copula函数对肌间相依结构的拟合优度更高,由时变copula互信息描述的肌间耦合强度存在显著的频段差异(P<0.05),具体表现为频段越高肌间耦合强度越低(腕屈:0.075 7~0.214 7 bit;腕展:0.078 0~0.237 3 bit),而静态copula互信息严重地低估肌间耦合强度。时变copula互信息为肌间耦合分析提供一种先进的理论指导方法,具有广阔的应用前景。

Time-Varying Copula Mutual Information for Intermuscular Coupling Analysis

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.