Brain-controlled rehabilitation system motor imagery recognition system integrating complex network and graph convolution

Abstract

A motor imagery recognition system for a brain-controlled rehabilitation system that integrates complex networks and graph convolution. The subjects perform motor imagery by watching the video of hand clenching and stretching movements, and at the same time, the EEG signal acquisition equipment collects the subjects' motor imagery EEG brain Electrical signal; the movement intention recognition module constructs a multi-entropy complex network for the obtained motor imagery EEG EEG signal, extracts the characteristics of symbol fluctuation, frequency energy distribution and amplitude fluctuation in the motor imagery EEG EEG signal, and inputs the graph convolutional neural network Classify and identify the EEG signals of the fist-clenching movement and the EEG signal of the hand-stretching movement imagination, and transmit the classification results to the brain-controlled rehabilitation system, prompting the subjects to perform hand-clenching and stretching movements; the brain-controlled rehabilitation system The system enables the formation of a closed-loop pathway between motor intentions and body sensations, gradually enhances the subject's muscle strength and nerve conduction velocity, promotes the recovery of damaged brain motor areas, and gradually restores activity.

Description

technical field [0001] The invention relates to a motor imagery recognition system. In particular, it involves a brain-controlled rehabilitation system motor imagery recognition system that integrates complex networks and graph convolution. Background technique [0002] The Brain-Computer Interface (BCI) system provides a connection between the human brain and external devices. The system first collects brain activity signals, then detects the user's intention through the signal processing part, and finally converts the intention into instructions to control the external device. Motor imagery is a classic BCI paradigm. When a person imagines a limb movement, it will cause the activation of a certain area of ​​the brain's motor perception cortex. The activation of the motor perception cortex will trigger a change in cortical potential. This electrical signal is called a motor imagination signal. Different motor imagery tasks observed oscillatory activity in different regions...

AI Technical Summary

Problems solved by technology

However, due to the characteristics of weak and noisy EEG signals, it is still impossible to accurately classify motor imagery signals. The accurate extraction of motor imagery signal features needs further exploration.

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