Gesture recognition system and method based on muscle electrical impedance signals

Abstract

The invention relates to a gesture recognition system based on muscle electrical impedance signals. The gesture recognition system comprises a signal acquisition unit and an upper computer data processing unit, the signal acquisition unit comprises a main control module, a signal driving module, a signal detection module, an AD acquisition module and a wireless communication module; the main control module is connected with the signal driving module, the AD acquisition module and the wireless communication module; the signal detection module is respectively connected with an electrode and theAD acquisition module; the wireless communication module is connected with an upper computer through wireless transmission and transmits collected signals to the upper computer for processing. The system and method can directly reflect the intrinsic state of the muscle, has good sensitivity to low-speed movement, and is high in muscle contraction sensitivity, good in robustness, large in signal amplitude, controllable in frequency and simple in preprocessing.

Description

technical field [0001] The invention relates to the field of machine vision, and relates to a gesture recognition system based on muscle electrical impedance signals. Background technique [0002] Machine vision is the most commonly used gesture recognition method by capturing human motion images. However, its privacy is intrusive, easily affected by light, limited observation range, and easily occluded. These problems limit the use of machine vision in gesture recognition. Identify field applications. With the development of sensor technology, some wearable gesture recognition devices based on sensor technology have gradually emerged in recent years, mainly including motion sensors (such as gyroscopes, accelerometers, etc.) and surface electromyography sensors. Accelerometers and gyroscopes reflect the movement information of the limbs, which are less sensitive to low-speed movements. The surface electromyographic signal reflects the essential information of the muscle, b...

AI Technical Summary

Problems solved by technology

The surface electromyographic signal reflects the essential information of the muscle, but it is a very weak electrical signal. The acquisition is easily disturbed by the outside world, and the subsequent processing process is complicated, which increases the difficulty of the hardware and software design of wearable devices.

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