Multiscales Synchronization Method For Estimating Functional Corticomuscular Coupling Based On EEG And EMG Signals

The electroencephalogram signals(EEG)over brain scalp and surface electromyography signals(sEMG)from the body of the contralateral muscles reflect the motion control information and functional response information of the muscles to the intention of brain control,respectively.At the same time,the interaction between the physiological system of complex structure is on multiple spatial and temporal scales,thus the synchronization analysis of EEG and EMG signals could reveal the different levels of the oscillatory connections between sensorimotor cortex and motor units firing in a target muscle during the process of movement,and evaluation of sports system function.This research has become a hot issue in the field of motor neuroscience.Firstly,this article introduces the generation and characteristics of EEG and EMG,and describes the research progress of synchronous analysis of EEG and EMG signals based on neuromuscular coupling.Then,determine the research contents of this paper are: starting from the nonlinear and multiscale characteristic of EEG and EMG signals,and construct the model of multiscale synchronization analysis of EEG and EMG signals to quantitatively describe the coupling strength and the amount of transmitted information of corticomuscular on different scales and directions.Secondly,according to the time scale characteristics of EEG and EMG signals,a multiscale transfer entropy(MSTE)model is constructed to describe the functional coupling between the different temporal scales.At the same time,a significant indicator of MSTE was defined to quantitatively analyze the discrepancies of functional corticomuscular coupling(FCMC)interaction strength in specific frequency band.The simulation results show that the MSTE can effectively describe the coupling strength and the amount of transmitted information on the different time scales of the two systems.The validity of the MSTE algorithm is verifiedThirdly,due to the prominent characteristics of EEG and EMG signals in the frequency domain,the wavelet transform is introduced to this article to construct the wavelet transform-transfer entropy(WTE)model for the synchronization analysis of corticomuscular on the temporal and spatial scales.Then,proposed the variational modal decomposition-transfer entropy(VMD-TE)analysis method to adaptive extraction the time-frequency scales of EEG and EMG signals,because of the wavelet transform too dependent on the selection of wavelet basis function.The simulation results show that the WTE and the VMD-TE method can be used to quantitatively describe the nonlinear synchronization features and functional connections between the cerebral cortex and the muscles.Finally,experimental study was conducted.The scalp EEG and sEMG signals of 8 healthy subjects were collected,which recorded simultaneously during grip task with steady-state force output.The MSTE,WTE and VMD-TE methods were used to research the multiscales corticomuscular coupling and discrepancies in different pathways(EEG→EMG and EMG→EEG)various scales.Synchronization analysis based on the measured data,it is verified that the methods proposed in this paper can quantitatively estimate the nonlinear interconnection and functional corticomuscular coupling between sensorimotor cortex and muscle.