Upper limb exoskeleton control method and system based on motor imagery

Abstract

The invention provides an upper limb exoskeleton control method based on motor imagery. The method comprises following steps: 1), according to left arrow prompt or down arrow prompt in a display screen, a subject performs corresponding motor imagery, namely, left hand motor imagery and foot motor imagery, and produced original electroencephalogram signals are pre-processed; 2), the pre-processed original electroencephalogram signals are input into a CNN structure and subjected to feature extraction and classification, and an identification result is output; 3), a driver control signal is acquired according to the output identification result, upper limb exoskeleton is driven and front arms are driven to correspondingly move; if the classification result indicates the left hand motor imagery, the upper limb exoskeleton performs a stretching action, and if the classification result indicates the foot motor imagery, the upper limb exoskeleton performs a bending action. When the CNN structure is designed, a convolution kernel is set as a vector according to the characteristic of time and space feature combination of the electroencephalogram signals. The invention further provides an upper limb exoskeleton control system based on the motor imagery. The classification and identification rate is higher, and experience effect is good.

Description

technical field [0001] The invention relates to rehabilitation medicine and motor imagery EEG classification technology, in particular to an upper limb exoskeleton control method and system based on motor imagery. Background technique [0002] In recent years, rehabilitation upper extremity exoskeleton, as an auxiliary therapeutic equipment, can provide different intensities and different modes of training for stroke patients in different rehabilitation stages through intelligent man-machine interface. Brain-computer interface technology (brain-computer interface, BCI) utilizes electroencephalogram (EEG) to realize communication and control between the human brain and computers or other electronic devices, and has been widely used in rehabilitation training. As a control method of human-computer interaction, brain-computer interface technology can not only identify the movement intention of patients like other traditional control methods (surface electromyography signals and...

AI Technical Summary

Problems solved by technology

[0005] In order to overcome the disadvantages of low classification recognition rate and poor experience effect of existing EEG signals due to low signal-to-noise ratio, the present invention provides a control method for upper limb exoskeleton based on motor imagery with high classification recognition rate and good experience effect and system

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