Method for recognizing gait of thigh amputation subject

Abstract

The invention discloses a method for recognizing the gait of a thigh amputation subject and relates to a prosthesis which is not transplanted in a human body. The method comprises the following steps of acquiring multichannel stump surface electromyographic signals of the thigh amputation subject at different gaits, and preprocessing the multichannel stump surface electromyographic signals; performing eigenvalue extraction on the acquired multichannel stump surface electromyographic signals to construct corresponding feature vectors; recognizing the gaits of the thigh amputation subject by using an improved clustering algorithm with a supervision Kohonen neural network. The invention relates to a method for recognizing walking modes of exoskeletons based on the electromyographic signals; five typical gaits of a thigh amputation patient, such as flat ground, upstairs, downstairs, upslope and downslope are accurately classified, and the defects in the prior art that the recognizing results of the walking modes are lagged, effective road condition recognizing is in shortage, and coordinate motion between men and a machine cannot be realized are overcome.

Description

technical field [0001] The technical solution of the invention relates to a prosthesis not implanted in a human body, specifically a gait recognition method for a person with a leg stump. Background technique [0002] In recent years, with the frequent occurrence of accidental injuries such as traffic accidents, industrial injuries, and natural disasters, and the continuous spread of chronic diseases such as cerebrovascular diseases, diabetes, and osteoarthritis, the number of thigh amputee patients is increasing at an alarming rate. Obtaining an effective signal source and accurately identifying the different gaits of a person with a thigh stump is an important guarantee for the intelligent control of active prostheses. Sensing the condition of the ground at any time and adjusting it at any time can ensure the safety, stability and adaptability of the prosthesis wearer. As the largest and most complex joint in the human body, the knee joint can withstand large forces and m...

AI Technical Summary

Problems solved by technology

[0004] The technical problem to be solved by the present invention is to provide a gait recognition method for thigh stumps, which is an exoskeleton walking pattern recognition method based on electromyographic signals, and five typical gaits of thigh amputee patients: flat ground, climbing stairs, Accurate classification of descending stairs, ascending slopes and descending slopes overcomes the shortcomings of the existing technology, such as lagging walking pattern recognition results, lack of effective road condition recognition methods, and human-machine inability to coordinate movements

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