Active hand training system and method based on brain-computer interaction and deep learning

Abstract

The invention discloses an active hand training system and method based on brain-computer interaction and deep learning. The active hand training system comprises an electroencephalogram cap, an FPGAacquisition device, an image stimulation module, an upper computer and a hand movement support; the electroencephalogram cap and FPGA acquisition equipment are used for acquiring a motor imagery electroencephalogram signal of a testee, carrying out preprocessing operation and wirelessly transmitting the pretreated signal to the upper computer; the image stimulation module generates corresponding motion visual prompts according to the training items so as to prompt the testee to perform imagination of corresponding action; meanwhile, after receiving the electroencephalogram signal, the upper computer decodes the electroencephalogram signal and generates a corresponding control signal; and the hand movement support receives the control signal to pull the hand of the testee to move, and corresponding training is completed. The device has the characteristics of high safety, labor saving and high interestingness, the initiative of a user can be exerted to the maximum extent, and the rehabilitation effect is improved.

Description

technical field [0001] The invention belongs to the fields of rehabilitation engineering, brain-computer interface and neural control, and more specifically relates to an active hand training system and method based on brain-computer interaction and deep learning. Background technique [0002] According to the World Health Organization, stroke has become the second leading cause of death after cancer and coronary heart disease worldwide. In recent years, with the aging of society in our country, the number of patients with motor dysfunction caused by stroke has continued to increase. According to the survey, stroke has become the number one cause of death in my country combined in urban and rural areas, and it is also the leading cause of disability among Chinese adults. Stroke has the characteristics of high morbidity, high mortality and high disability rate. Patients after stroke often suffer from different parts and degrees of hemiplegia. When hemiplegia occurs in the ha...

AI Technical Summary

Problems solved by technology

[0005] However, there are still many shortcomings and deficiencies in the existing rehabilitation systems at home and abroad

The current mainstream functional rehabilitation therapy, such as cold therapy, electrical stimulation, and rehabilitation robots, not only consumes a lot of manpower and material resources, but also ignores the patient's initiative

Lack of direct involvement of the nervous system of the brain, these reasons make the repair of functional connectivity between the external limbs and the brain limited, and the rehabilitation effect is not satisfactory

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