Exoskeleton walking mode identification method based on electromyographic signals

Abstract

The invention relates to an exoskeleton walking mode identification method based on electromyographic signals. The exoskeleton walking mode identification method based on the electromyographic signal comprises the steps of (1) electromyographic signal collection, wherein an electromyographic electrode is attached to the muscle belly along the selected muscle group muscle fibers, an electromyographic signal sensor is connected with the electromyographic electrode through an electrode buckle, and a single-chip microcomputer fixed to the exoskeleton is connected with the electromyographic signal sensor through a wire and used for collecting the electromyographic signals; (2) electromyographic signal conditioning, wherein after the step (1), surface electromyographic signals collected by the electromyographic electrode are input to the electromyographic signal sensor for signal conditioning; (3) exoskeleton walking mode identification through an SVM-KNN classification algorithm based on threshold segmentation, wherein the surface electromyographic signals processed in the step (2) are input to the single-chip microcomputer for A / D conversion, preprocessing for elimination of zero drift, detection feature extraction initial time, feature extraction and classification through the SVM-KNN classification algorithm based on threshold segmentation, and finally the exoskeleton walking mode is identified.

Description

technical field [0001] The invention relates to a human walking pattern recognition method applied to an exoskeleton, in particular to a walking pattern recognition method for an exoskeleton based on electromyographic signals. Background technique [0002] With the increasing problem of aging in modern society, the health problems of the elderly have been widely concerned by the whole society. Inflexible legs and feet are very troublesome problems in the life of the elderly. Many elderly people will go up the steps or walk for a long time. He felt weak in his legs and feet, which seriously affected his normal life. Exoskeletons can provide external assistance for the elderly or those with walking difficulties when walking on flat ground, going up and down stairs, and helping them maintain appropriate activities. It is of great significance for improving the quality of life of the elderly and reducing the burden on the family and society. [0003] The exoskeleton is guided b...

AI Technical Summary

Problems solved by technology

[0004] The Chinese patent No. CN201210214871.4 discloses a lower limb movement trajectory prediction method based on the fusion of EMG signals and joint angle information. Using EMG signals and knee joint angle information, four types of lower limbs can be identified: walking, standing up, squatting and knee extension The motion mode is used to control lower limb prostheses. The disadvantage is that the Vicon 3D motion capture system is used to calculate the knee joint angle, which increases the difficulty of information collection and limits the subject's activity area to a specific laboratory, which is not conducive to the promotion of technology. application, and did not mention the identification of common road conditions such as up and down stairs and up and down slopes

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