1(Yanshan University, College of Electrical Engineering, Key Lab of Measurement Technology and Instrumentation of Hebei Province, Qinhuangdao Hebei 066000, China) 2(Yanshan University, Key Laboratory of Control Engineering of Hebei Province, Biological Information Research Center, Qinhuangdao Hebei 066000, China) 3(Department of Rehabilitation Medicine, the No.281 Hospital of Chinese People's Liberation Army, Qinhuangdao, Hebei 066004,China)
Abstract：The corticomuscular coordinate mechanism of hand movements has important application values in prosthesis control, rehabilitation treatment and evaluation. This paper proposed Gabor wavelet transform-Granger causality (WT-GC) method to analyze corticomuscular coupling (CMC). Furthermore, the GC peak frequency and significant GC area were defined to quantitatively describe the corticomuscular function coupling and information flow direction at different frequencies. We collected the EEG and EMG datasets acquired simultaneously from 10 healthy subjects during maintaining static forces at 10% and 60% of their maximal voluntary contraction (MVC) isometrically. The proposed wavelet transform-Granger causality (WT-GC) method was used to analyze the synchronization between EEG and EMG data. Results showed a shift of GC peak frequency to higher frequency range for 60% MVC as compared with 10% MVC in both EEG→EMG and EMG→EEG directions. There was a decreased significant GC area appearing at beta band in EEG→EMG direction for 60% MVC. It was verified that the TF-GC method proposed could describe the corticomuscular coupling frequency and directional features. In addition, corticomuscular controls the force output of hand by adjusting neuronal oscillation amplitude, frequency and flow direction. In conclusion, this analysis provided a basis for exploring the motor control and feedback information encoding of hand.
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