Angle and myoelectricity continuous decoding method for human body lower limb walking joint

Abstract

The invention discloses an angle and myoelectricity continuous decoding method for a human body lower limb walking joint. The movement track of a lower limb body surface optical marking point in the human body walking process is recorded through an optical movement capture system, and the movement angle of the lower limb joint is precisely calculated through the human body lower limb kinematical modeling; surface electromyogram signals of eight main muscles related to lower limb movement in the human body walking process are synchronously acquired, the activity intensity information of the signals is extracted through filtering and rectifying preprocessing, and the optical independent feature vector set describing the intensity of the surface electromyogram signals is extracted through the principle component analysis method; a nonlinear regression model from surface electromyogram signal features (independent variables) to the vertical plane joint movement angles (dependent variables) is established through the gene expression programming symbol regression analysis method, and the lower limb movement track is predicted. The method is mainly applied to design and manufacture of medical rehabilitation machines.

Description

technical field [0001] The invention relates to a medical rehabilitation device, in particular to a method for continuously decoding myoelectricity of walking joint angles of lower limbs of a human body. Background technique [0002] In today's society, the incidence of fractures, loss of limb motor function and its complications due to car accidents, engineering accidents, or cerebral apoplexy and other diseases has an increasing trend year by year. Among them, the loss of motor function of the lower limbs has a particularly serious impact on the daily life of patients. Experiments have shown that specific functional training can promote the reorganization and compensation of the central nervous system, and restore the patient's limb motor function. The lower limb rehabilitation robot was invented and developed accordingly. [0003] The surface electromyography signal (sEMG) of the human body is a bioelectrical signal that can directly reflect the movement intention of the...

AI Technical Summary

Problems solved by technology

[0010] Literature 1 and Literature 2 combine muscle physiology to establish a joint dynamics model with sEMG as input, and then calculate joint torque / angular acceleration equivalents, but the constructed model has a complex structure and contains many unmeasured physiological parameters, which is difficult for practical application

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