Ankle EMG signal feature extraction based on improved noise reduction method

Ankle joint is an important hub to control the stability of human walking. Its early rehabilitation training and accurate assessment of rehabilitation status are of great significance to the recovery of walking ability of hemiplegic patients. This paper proposes to evaluate the rehabilitation status of patients ' ankle joints based on surface electromyography signals. Firstly, the surface electromyography signals that affect the human ankle dorsiflexion tibialis anterior muscle are collected by the electromyography sensing device. Then, the empirical mode decomposition combined with the improved wavelet threshold denoising method is used to denoise, and a relatively pure electromyography signal is obtained. Finally, the amplitude, electromyography value and other eigenvalues of the surface electromyography signal are extracted to evaluate the rehabilitation status. The experimental results show that the quantitative evaluation of ankle rehabilitation status based on the de-noised surface electromyography signal provides a certain reference for the quantitative evaluation technology of rehabilitation.