Study On Motor Behavior Of Lower Limbs Based On Electromyographic Synergy And Coherence

In recent years,with the aggravation of population aging and the increase of the number of disabled people,the development of rehabilitation robots has gradually become a hot topic of social concern.During lower limb movement,the central nervous system controls the coordination of multiple muscles and bones,forming a control unit module with coupling and low-dimensional characteristics.By analyzing the interaction and interaction between these modules,it can provide help for rehabilitation medicine,human-computer interaction and other fields.The main work is as follows:(1)Based on the squatting and gait movements in daily behaviors,this thesis collects the surface EMG signals under different actions and selects Empirical Mode Decomposition(EMD)、Ensemble Empirical Mode Decomposition(EEMD)and Local Mean Decomposition(LMD)according to the noise characteristics of the original signals.Three kinds of methods are used for denoising,and the main components of the decomposition are superimposed to reconstruct the original signal.Finally,the denoising performance index is compared and the optimized method is selected.(2)According to the characteristics of the sEMG signals,the envelope signals are extracted from the pre-processed signal,and the envelope signals are decomposed by non-negative matrix decomposition algorithm.Under the Stand-Squat and Squat-Stand actions,the 8 and 6 blocks of the normal group were decomposed into 5 and 4 synergistic elements and activation coefficient modules respectively.Since the muscles were easily affected by fatigue factors,the normal group and fatigue were analyzed.The effects of the group’s synergy and activation modules found that the corresponding muscles in the synergy module changed.Under the gait movement,four modules are decomposed,the entropy analysis and the motion function are mapped and analyzed between the collaborative structures,and the obtained results are consistent with the muscle function.(3)In order to explore the synergy between modules and participate in the relationship between muscles.Coherence analysis is performed on the muscle pairs with obvious synergy in the Stand-Squat and Squat-Stand modules;coherence analysis is performed on the corresponding muscle pairs in the gait movement,and the local energy of the band and wavelet spectrum analysis are performed by the signals in the synergistic module.Muscles with higher synergy have regular and stable coherence with each other.They are distributed in the main frequency domain of sEMG signals,and the coherence with lower synergy is more chaotic and irregular.In addition,it is found that the corresponding band energy of synergy is concentrated and corresponds to each other,and the spectrum energy starts higher and then gradually decreases.These show that the useful EMG signals with strong synergy in the module have strong regularity and high energy.In this dissertation,the exercises of the lower limb movements were conducted to analyze the synergy-coherence of signals under exercise.In the synergistic modules,the regularity,similarity and energy distribution of signals were explored.This method is helpful to understand the control strategy of lower limb movement,and has significance for quantitative analysis of motor function and guidance of human lower limb rehabilitation.