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《Chinese Journal of Sensors and Actuators》 2018-06
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Functional Coupling Analyses of EEG and EMG Based on Multivariate Empirical Mode Decomposition

MA Penggang;SHE Qingshan;GAO Yunyuan;ZHANG Qizhong;LUO Zhizeng;Institute of Intelligent Control and Robotics,Hangzhou Dianzi University;  
Functional corticomuscular coupling( FCMC) is the interaction between the cerebral cortex and muscles.The multi-scale coupling characteristics of the Electroencephalography( EEG) and electromyography( EMG) signals can reflect the multiple temporal and spatial function of the cortex-muscle. The multivariate empirical modal decomposition( MEMD) and transfer entropy( TE) are combined to construct a MEMD-TE model,applied to analysis coupling between cortical and muscle activities. Firstly,the EEG and EMG signals were pre-processed,and then the multivariate empirical modal decomposition algorithm was used to perform time-frequency scaling on the signals. Finally,the entropy values were calculated on different scales,and nonlinear coupling characteristics were analyzed on different coupling direction( EEG →EMG and EMG →EEG). EEG and EMG signals of 10 subjects were collected under static grip( 5 kg,10 kg and 20 kg),experimental results show that the MEMD-TE value from EEG to EMG is higher than that from EMG to EEG in the high frequency band( 40 Hz ~ 75 Hz),and FCMC is bi-directional and has differences in the coupling strength of different coupling directions and bands. In addition,the significance test revelas no significant difference between the MEMD-TE values from EEG to EMG under different grip forces.
【Fund】: 国家自然科学基金项目(61201302 61671197);; 浙江省自然科学基金项目(LY15F010009)
【CateGory Index】: R318;TN911.6
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