Corticalmuscle Coupling And Analysis Method Of Upper Extremity Movement

At present,corticomuscular coupling research has become a research focus in the field of brain science and rehabilitation assessment.In the process of neural control of human movement,the interaction between the two major systems of the cerebral cortex and the motor neuromuscular tissue,as well as their internal interaction constitute the cortical muscle coupling relationship.The EEG signals of the motor cortex and the EMG signals of the contralateral muscle tissue of the brain reflect the motion control information and the functional response information of the muscle to the brain’s control intention,respectively.The analysis of time-frequency domain synchronization characteristics of EEG-EMG signals under different exercise modes can help to understand the functional coupling characteristics and information transmission between cerebral cortical and contralateral muscle,and also provide a theoretical basis for constructing objective quantitative evaluation of rehabilitation function.In this paper,the basic knowledge of EEG and EMG signals are introduced firstly.Then the research content of this paper is determined via the analysis of development status of corticomuscular coupling and synchronous analysis methods.Transfer entropy,coherence,generalized partial directed coherence and Copula-GC analysis method was used to analyse the corticomuscular function coupling relationship between healthy and stroke patients in the time and frequency domain.The specific work is as follows:(1)The multivariate time series frequency domain synchronization analysis methods are studied at the principle level,including coherence,partial coherence,directional coherence,generalized partial directed coherence method under multivariate autoregressive model and extended multivariate autoregressive model.Then the simulation data is used to verify the effectiveness of the algorithm and lay a solid theoretical foundation for the next step.(2)Considering that traditional coherence analysis method is not effective to describe the intermuscle coupling direction and nonlinear coupling characteristics,and meanwhile it can’t exclude the impact of indirect connections.The transfer entropy(TE)and generalized partial directed coherence(gPDC)are introduced into the intermuscle coupling analysis in this paper,in order to investigate the intermuscular bidirectional functional coupling characteristics.The EMG data was collected from eight healthy subjects.TE was used for analysis in the time domain,and gPDC was computed in the frequency domain,compared with the traditional coherence analysis method.The experimental results show that the proposed method can effectively reveal the characteristics of intermuscular coupling and information transmission during upper limb exercise.(3)However,the Granger causality(GC)is limited in identifying linear cause-effect relationship.It is difficult to quantitatively analyse nonlinear and high-order causality.In this study,a time-frequency domain copula-based GC(copula-GC)method is proposed to assess corticomuscular coupling during hand gripping.Five post-stroke patients and five healthy volunteers were recruited and participated in left and right hand gripping tasks.The EEG signals and EMG signals from the upper limb were collected from the subjects.Then Copula-GC was employed to evaluate the corticomuscular coupling strength in time-frequency domain for both directions.We suggest that the proposed time-frequency domain analysis method based on Copula-GC can effectively detect functional complex coupling between cortical oscillations and muscle activities,and provide a potential quantitative analysis measure for motion control and rehabilitation evaluation.