Simulation And Experimental Study Of Muscle Synergy For Human Lower Extremity

Muscle synergy is considered as the smallest unit of the central nervous system for motor control and has great research value for understanding the motor control strategies of the nervous system.Traditional studies on muscle synergy have relied on EMG signals that reflect muscle activation.The development of the musculoskeletal simulation provides a new method for the quick and convenient analysis of muscle activation.In this paper,extracting muscle synergies based on musculoskeletal system is realized.A musculoskeletal model of human lower extremity is firstly built in OpenSim software.Then a musculoskeletal system based on Hill model is built.A human movement measurement and simulation analysis system is built to realize experimental data acquisition and processing of human movement,as well as biomechanical simulation of the musculoskeletal system.In this paper,both biomechanical simulation and experimental data are considered,to track the experimental joint moments and the selected muscle activations,two methods of extracting muscle synergies are presented in this paper:(1)Extracting muscle synergies based on non-negative matrix factorization is used to optimize the solution of the muscle activation matrix,then the synergy structure matrix and the synergy activation matrix are solved from activation matrix by non-negative matrix factorization,the muscle activation matrix is reconstructed to realize the control of muscle synergy;(2)Muscle activation model based on muscle synergy is used to optimize the solution ofthe synergy structure matrix and synergy activation matrix directly,instead of optimizing the solution of the muscle activation matrix,and the control of muscle synergy for muscle activation is realized in the optimization iteration process.In order to compare the two methods,we recruited adult subjects to take part in the gait experiment,and the muscle synergies were extracted by using the two methods.which showed that muscle activation model based on muscle synergy is superior to extracting muscle synergies based on non-negative matrix factorization,in which the root mean square error of joint moments and muscle activations decreased by average of 62.0%,33.2%,respectively,the mean absolute deviation of joint moments and muscle activations decreased by average of 63.2%,36.9%,respectively,and the correlation coefficient between experimental and predicted joint moments and muscle activations increased by average of 9.0%,10.1%,respectively.After extracting muscle synergies based on non-negative matrix factorization,the number of synergies was set based on the threshold of variability accounted for the reconstructed muscle activation matrix.Then the error can be reduced by applying muscle activation model based on muscle synergy.Finally,this paper applied the method to the research on the muscle synergy-based control strategies for human foot slip recovery.We recruited adult subjects to take part in the gait experiment,then muscle synergies of the two motion states were extracted,thus the influence of foot slip recovery on muscle synergies was analyzed with normal walking as the control group.The results showed that compared with normal walking,muscles synergies completed the emergency response process of foot slip recovery with the control strategies of higher muscle contribution in synergies,higher synergy activation and higher synergy co-activation ratio.