Muscle synergy analysis method based on human dynamics modeling and surface EMG signal correction

Abstract

The invention discloses a muscle synergy analysis method based on human dynamics modeling and surface EMG signal correction. The method is characterized in that firstly, personalized human musculoskeletal model scaling of an experimental subject is performed; secondly, kinematics and dynamics data and EMG signals of the experimental subject in a moving state are collected, joint angles are solvedthrough inverse kinematics, physiological parameters are calculated through muscle and tendon kinematics, and joint moments are solved through inverse dynamics; an optimal control problem of joint moment distribution on the muscle synergy structure and a recruitment mode is solved according to the joint angles, the physiological parameters, the joint moments and the processed EMG signals, and themuscle synergy structure driving a human dynamics model and the recruitment mode are obtained. The method is advantaged in that the method is convenient to use, has high comfort level and security, iscompatible with joint moment and EMG signal errors and improves simulation model accuracy.

Description

technical field [0001] The invention relates to the field of biomedical engineering, in particular to a muscle synergy analysis method based on human body dynamics modeling and surface electromyographic signal correction. Background technique [0002] Muscle synergy analysis is an important means of human motion function analysis, and it is of great significance for the quantitative analysis of human muscle, nerve and other motor functions. Usually, the muscle synergy analysis first needs to obtain the EMG signals of the muscles involved through the EMG sensor, and after processing the original EMG signals, the synergistic structure and recruitment mode of each synergy can be obtained through the matrix decomposition algorithm. This method needs to use as many myoelectric sensors as possible, stick surface electrodes on the skin surface of superficial muscles, or insert invasive needle electrodes into deep muscles, otherwise it is difficult to measure deep muscle EMG signals...

AI Technical Summary

Problems solved by technology

This method needs to use as many myoelectric sensors as possible, stick surface electrodes on the skin surface of superficial muscles, or puncture invasive needle electrodes into deep muscles, otherwise it is difficult to measure deep muscle EMG signals. The electrodes of the sensor will cause discomfort or even pain to the human body, which will affect the normal movement function of the human body, and then affect the muscle synergy analysis, and the invasive needle electrode has a greater risk of infection to the human body. In addition, the myoelectric sensor is also very easy to disturbed

Images