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| Functional cortical muscle coupling method of multi-scale compensated transfer entropy |
Guo-mei JIN1( ),Qing-shan SHE1,*(),Min ZHANG1,Yu-liang MA1,Jian-hai ZHANG2,Ming-xu SUN3 |
1. School of automation, Hangzhou Dianzi University, Hangzhou 310018, China
2. Key Laboratory of Brain-Computer Collaborative Intelligence of Zhejiang Province, Hangzhou 310018, China
3. School of Automation and Electrical Engineering, University of Jinan, Jinan 250022, China |
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Abstract A new multi-scale compensation transfer entropy (MeTE) method was proposed, in order to describe accurately the coupling characteristics between electroencephalogram (EEG) and electromyographic (EMG) signals at different scales. An adaptive-projection intrinsically transformed multivariate empirical mode decomposition method and the compensation transfer entropy were combined in the proposed method. The multi-scale compensation transfer entropy values at different scales were calculated, and calculation results were used to quantitatively analyze the coupling characteristics of different coupling directions. Results show that under constant grip strength, the coupling strength between the beta frequency band (13-35 Hz) is significant, and the coupling strength of the ${\text{EEG}} \to {\text{EMG}}$direction is higher than ${\text{EMG}} \to {\text{EEG}}$direction. In the high gamma frequency band (50-72 Hz), the coupling strength of EEG and EMG in ${\text{EEG}} \to {\text{EMG}}$direction is generally higher than that in ${\text{EMG}} \to {\text{EEG}}$direction. Research results reveal that the coupling intensity of EEG and EMG signals in different coupling directions and different scales is different. And the McTE can estimate accurately the coupling characteristics and functional connection between EEG and EMG signals at different scales are estimated accurately by using McTE method.
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Received: 21 March 2022
Published: 30 June 2022
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| Fund: 国家自然科学基金资助项目(61871427, 62071161)；浙江省自然科学基金重点项目(LZ22F010003) |
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Corresponding Authors:
Qing-shan SHE
E-mail: 1377368847@qq.com;qsshe@hdu.edu.cn
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多尺度补偿传递熵的皮层肌肉功能耦合方法
为了准确描述脑电(EEG)和肌电(EMG)信号在不同尺度上的耦合特征，提出新的多尺度补偿传递熵(McTE)方法. 该方法结合自适应投影多元经验模态(APITMEMD)方法和补偿传递熵(cTE)，计算不同尺度上的多尺度补偿传递熵值，计算结果用于定量分析不同耦合方向( ${\text{EEG}} \to {\text{EMG}}$和 ${\text{EMG}} \to {\text{EEG}}$)上的耦合特征. 结果表明，在恒定握力下，beta频段(13~35 Hz)的耦合强度最大，且 ${\text{EEG}} \to {\text{EMG}}$方向的耦合强度高于 ${\text{EMG}} \to $ $ {\text{EEG}}$方向；在高gamma频段(50~72 Hz)， ${\text{EEG}} \to {\text{EMG}}$方向EEG与EMG的耦合强度总体高于 ${\text{EMG}} \to {\text{EEG}}$方向的. 研究结果表明，脑肌电耦合强度在不同耦合方向和不同尺度上有所差异，McTE方法能准确刻画脑肌电多尺度间的耦合特征及功能联系.
关键词：
脑卒中,
康复评估,
多尺度,
脑肌电信号,
皮层肌肉功能耦合
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