Action recognition method and equipment based on surface electromyogram signals

Abstract

An embodiment of the invention provides an action recognition method and equipment based on surface electromyogram signals. The action recognition method includes: acquiring surface electromyogram signals of multiple channels, and determining effective surface electromyogram signals according to the surface electromyogram signals of the channels; determining frequency of the effective surface electromyogram signals, and determining limb actions corresponding to the surface electromyogram signals of the channels according to the effective surface electromyogram signals. Frequency of the surface electromyogram signals has nothing to do with features such as signal intensity, so that by the method, accuracy of action recognition based on the surface electromyogram signals can be improved remarkably. The frequency is taken as a recognition feature, so that a user does not need to perform large-amplitude actions, and better experience is brought to the user. In addition, according to the method, frequency and amplitude features of the surface electromyogram signals can be combined to recognize corresponding limb actions, so that surface electromyogram signal recognition accuracy can be improved, and recognition types of the limb actions can be increased.

Description

technical field [0001] Embodiments of the present invention relate to motion recognition technology, and in particular to a method and device for motion recognition based on surface electromyographic signals. Background technique [0002] Surface electromyography (EMG for short) is a bioelectrical signal related to neuromuscular activity. Surface electromyography can reflect information such as muscle contraction mode and contraction intensity. Different body movements correspond to different surface electromyography signals. , by analyzing the surface electromyography signal, the specific action corresponding to the surface electromyography signal can be identified. Therefore, the surface electromyography signal is widely used in many fields such as clinical medicine, sports medicine, biomedicine and rehabilitation engineering. [0003] In the prior art, the recognition of body movements is carried out using the amplitude characteristics of the surface electromyography sign...

AI Technical Summary

Problems solved by technology

[0004] The method of the prior art has the following problems: Since other actions of the user also generate surface electromyography signals, when the user performs other sports (running, typing, etc.), the generated interference surface electromyography signals and the target surface electromyography signals will occur. superposition, resulting in low recognition accuracy. In addition, the magnitude of the surface electromyography signal is proportional to the magnitude of the user's body movements. In the case of operation, it will make the user feel strenuous

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