Research On Evolutionary Regularity Of Muscle Synergy-coupling In Motor Function Reconstruction After Stroke

Motor dysfunction is the most common symptom of stroke clinical lesions,with over80% of stroke patients experiencing abnormal limb motor ability due to brain lesions.It will cause the changes in the modular structure and synergistic interaction of motor related muscles.The intrinsic evolution of muscle synergy-coupling in the motor function reconstruction after stroke can contribute to revealing the pathological mechanism of motor dysfunction.Therefore,this research focused on the muscle synergy-coupling analysis method based on multi-channel electromyography signal analysis from the perspective of the response muscle.Additionally,multi-level synergy-coupling indicators describing the abnormal structures were obtained to analyze the evolution of muscle synergy-coupling characteristics for stroke patients under different rehabilitation stages.This research could excavate the pathology of motor dysfunction and functional reconstruction mechanisms of stroke.Firstly,focusing on the issue of the muscle abnormal synergy-coupling characteristics and evolution patterns in motor function reconstruction of stroke patients,combined with the clinical rehabilitation symptoms and behavioral manifestations of patients,a multi task experimental paradigm and plan are designed to reflect the motor ability of patients at different rehabilitation stages,and the surface electromyographic signals of motor related muscles under specific task paradigms are recorded;Establish a multi-level preprocessing strategy for electromyography signals to effectively remove artifacts such as power frequency interference and electrocardiogram interference.Secondly,to explore the changing characteristics of the modular structure of motion related muscle collaboration after stroke,the nonnegative matrix decomposition method and data variability calculation method were introduced to determine the optimal number of motion related muscle collaboration modules in the minimum redundancy state.After that,we analyzed the changes in the collaborative modular structure and indicators for stroke from the perspectives of the modules number and structure.Furthermore,we explored the mechanism by which stroke patients mobilize muscle synergy modules to complete specific tasks,providing theoretical support for further exploring the functional recovery status of stroke patients at different rehabilitation stages.Thirdly,an intermuscular coupling model was constructed based on partial directional coherence and complex small-world networks to study the coupling strength and information flow between different muscles,with aiming to explore the abnormal changes in intermuscular coupling characteristics of motor control system after stroke.Furthermore,we extracted the topological characteristics and causal connections of muscle function networks with graph theory,and screen the functional network indicators of intermuscular coupling with significant differences.This can provide a reference for exploring the evolution law of muscle synergy-coupling in stroke.Finally,to explore the evolution of muscle synergy-coupling characteristics in stroke motor function reconstruction,from the two levels of muscle synergy and intermuscular coupling,nonnegative matrix factorization and partially directed coherence analysis methods were used to explore the differences in changes in muscle synergy,intermuscular coupling,and small world network indicators.Therefore,this research excavates the evolution law of muscle synergy-coupling in stroke motor function reconstruction,explore the differences in the evolution law among different stroke patients,and provide a basis for mining the mechanism of stroke motor function reconstruction.