Knee joint angle prediction method and system based on electromyographic signals and angle signals

Abstract

The invention relates to a knee joint angle prediction method based on electromyographic signals and angle signals. A human body lower limb motion information acquisition unit and acquisition hardware, an experimental platform and test unit, a signal preprocessing and feature extraction unit and a machine learning system training and testing unit are integrally designed; the human body lower limbmotion information acquisition unit and acquisition hardware extract human body rectus femoris and biceps femoris electromyographic signals and hip joint and knee joint angle signals; the experiment platform and test unit are worn on the human body and are connected with the human body lower limb motion information acquisition unit and a notebook computer through interfaces; the signal preprocessing and feature extraction unit is used for carrying out preprocessing and feature extraction on the acquired electromyographic signals and angle signals, eliminating signal noises and extracting signal features; and the machine learning system training and testing unit takes the hip joint angle signals, the rectus femoris electromyographic signals and the biceps femoris electromyographic signals as a neural network input set and the knee joint angle signals as an output set, trains a selected model, predicts knee joint angle values and calculates errors, thereby providing reliable data for intelligent wearable equipment.

Description

technical field [0001] The invention relates to the technical field of intelligent prosthetic knee joints, in particular to a method and system for predicting knee joint angles based on electromyographic signals and angle signals. Background technique [0002] With the rapid development of the manufacturing industry, computer industry, and rehabilitation medical industry, research on intelligent prosthetics and wearable exoskeletons has also been further advanced. Rehabilitation of the disabled, mental issues, and social issues have become increasingly concerned issues in China and the world. As a medical device, lower limb prosthesis can not only make up for the lack of appearance for the physically disabled, but also help this group of people regain confidence and solve physical and psychological problems. And help the physically disabled to better integrate into social life, improve the ability to live independently, and also reduce the burden on family members. The cor...

AI Technical Summary

Problems solved by technology

[0005] At present, the research on the analysis of the knee joint motion signal of the human lower limbs mainly focuses on the motion pattern recognition of the lower limbs, that is, the recognition of the movement gait, and the joint angle prediction research mainly focuses on the upper limbs, and there are few studies on the knee joint angle prediction.

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