Biomechanical analysis of gait based on surface electromyography signals

Human walking is a fundamental and complex action. Through analysis, we can understand its basic mechanism and provide a foundation for the treatment and rehabilitation of related gait disorders. This article conducts biomechanical analysis of human gait walking based on surface electromyographic signals, which enables accurate estimation of internal physiological parameters and dynamic tracking of physiological activities during walking. Firstly, based on the optical capture markers, a human lower limb musculoskeletal model was constructed. Secondly, using the Hill model and introducing muscle damping viscosity elements, and considering the submaximally activated conditions, a static parameter optimization algorithm was designed to accurately estimate the force of lower limb muscles. Finally, we calculated joint torque and established a lower limb dynamics model. The simulated joint torque was input into the lower limb rigid body model to obtain the various joint movements of the human body. The correlation coefficient and root mean square error of joint torque are 0.975 and 7.822Nm respectively. This work has successfully completed the dynamic biomechanical analysis.