Active hand rehabilitation system for stroke based on brain-computer interaction and deep learning

Abstract

The invention discloses an active hand rehabilitation system for stroke based on brain-computer interaction and deep learning: it includes an EEG cap, an FPGA acquisition device, an image stimulation module, a host computer and a hand movement support; the EEG cap and FPGA acquisition The equipment is used to collect the EEG signal of the subject's motor imagery, perform preprocessing operations, and transmit it to the host computer through wireless; the image stimulation module generates corresponding visual prompts for the movement according to the training items to prompt the subject to perform corresponding actions. Imagine; at the same time, the host computer decodes the EEG signal after receiving the EEG signal and generates a corresponding control signal; the hand movement support receives the control signal and pulls the subject's hand movement to complete the corresponding training. The invention has the characteristics of high safety, manpower saving and high interest, and can maximize the user's initiative and improve the rehabilitation effect.

Description

technical field [0001] The invention belongs to the fields of rehabilitation engineering, brain-computer interface, neural control and the like, and more specifically relates to a stroke active hand rehabilitation system 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 increasing aging of our society, the number of patients with motor dysfunction caused by stroke has continued to increase. According to the survey, stroke in both urban and rural areas has become the first cause of death in my country and the leading cause of disability among Chinese adults. Stroke has the characteristics of high morbidity, high mortality and high disability rate. Post-stroke patients often suffer from hemiplegia in different parts and degrees. When hemiplegia occurs in the hand, the ner...

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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