Study On Muscle Synergy Properties In Stroke Rehabilitation Exercise

Muscle synergy,also called modularization structure for the motion control,refer to the coordination and control among multiple sets of muscles by the central nervous system(CNS),to simplify the complexity of human limb movement control.Muscle synergy structure has multi-domain characteristics of space and time,action and rhythmicity,but the existing muscle synergy analysis research mainly adopts the matrix decomposition method to extract the muscle synergy structure from the perspective of single space-time in time domain.On the one hand,the existing research and analysis of surface electromyographic(s EMG)signal based on the muscle synergy structure have ignored the characteristics of shared synergy and special synergy characteristics of task actions and the characteristics of interactive information between task actions.On the other hand,it doesn’t consider the frequency characteristics within the muscle synergy.It reduced the effectiveness of the analysis results.Moreover,s EMG and muscle synergy structure have a causal effect in human exercise.Therefore,the muscle synergy analysis in stroke patients based on s EMG is of great significance for how to effectively reveal the formation mechanism of exercise,the synergy mechanism of neural oscillation and the abnormal motor function mechanism of stroke patients.Therefore,in view of the above problems.This study proposes Nonnegative Tensor Factorization(NTF)from the perspective of multi-domain muscle synergy analysis.Taking healthy subjects and stroke patients as the research subjects,we analyzed and explored the shared and specific synergy characteristics and time-frequency-space and empty characteristics.The main work of this study is as follows:(1)To discuss the synergistic effect of shared muscle synergy and specific muscle synergy in the tasks,we have proposed the shared and specific muscle synergy feature analysis algorithm based on NTF.Through the analysis of healthy young subjects,this study shows that the NTF provides a more effective method for shared muscle synergy and specific muscle synergy characteristics compared with traditional muscle synergy analysis methods(2)In order to explore time-frequency-space muscle synergy feature,we have proposed the time-frequency-space muscle synergy analysis algorithm based on the Wavelet Decomposition-Nonnegative Tensor Factorization(WD-NTF).By analyzing the experimental data of healthy young subjects,the muscle synergy matrix,the time activation coefficient and the spectrum components related to muscle weight components were extracted.It verified that NTF could effectively extract muscle time-frequency-space synergy characteristics compared with traditional muscle synergy analysis methods.(3)In the muscle synergy analysis of s EMG in stroke patients and healthy controls,this study compared the shared and special muscle synergy characteristics and time-frequency-space muscle synergy characteristics.The experimental results show that the muscle synergy characteristics of stroke patients are different from healthy controls in different degrees,which reflects the abnormal muscle synergy in upper limb movement can lead to abnormal muscle activation of the upper limb.The results of this study can contribute to the deep understanding of the multi-domain muscle synergistic characteristics of human,and put forward a theoretical reference for the formulation of personalized treatment of stroke patients in clinical exercise rehabilitation.