生物医学工程学杂志

生物医学工程学杂志

脑肌电信号同步耦合分析方法研究进展

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运动神经系统通过神经振荡活动传递运动控制信息,从而引起相应肌肉的同步性振荡活动反映运动响应信息,并反馈至大脑皮层,使其能够感知肢体的状态。这种同步振荡活动可反映皮层肌肉功能耦合的连接信息。其中,耦合的强弱由多种因素决定,包括肌肉收缩的力量、注意力、运动意图等,分析不同因素影响下的脑肌电信号同步耦合的强弱对运动功能评价及控制方法等研究有重要意义。针对脑肌电信号同步耦合的分析方法,本文主要介绍与比较了线性方法中的相干性分析和格兰杰因果分析,以及非线性方法中的互信息以及传递熵,总结了各方法在脑肌电信号同步耦合的应用研究,以便于相关领域的科研工作者更系统地了解目前脑肌电信号同步耦合分析方法的研究进展。

The motor nervous system transmits motion control information through nervous oscillations, which causes the synchronous oscillatory activity of the corresponding muscle to reflect the motion response information and give the cerebral cortex feedback, so that it can sense the state of the limbs. This synchronous oscillatory activity can reflect connectivity information of electroencephalography-electromyography (EEG-EMG) functional coupling. The strength of the coupling is determined by various factors including the strength of muscle contraction, attention, motion intention etc. It is very significant to study motor functional evaluation and control methods to analyze the changes of EEG-EMG synchronous coupling caused by different factors. This article mainly introduces and compares coherence and Granger causality of linear methods, the mutual information and transfer entropy of nonlinear methods in EEG-EMG synchronous coupling, and summarizes the application of each method, so that researchers in related fields can understand the current research progress on analysis methods of EEG-EMG synchronous systematically.

关键词: 相干性分析; 格兰杰因果分析; 互信息; 传递熵

Key words: coherence analysis; Granger causality; mutual information; transfer entropy

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