Hand function rehabilitation training system integrating eye movement direction classification and augmented reality technology

Abstract

The invention discloses a hand function rehabilitation training system integrating eye movement direction classification and augmented reality technology, which comprises an electroencephalogram acquisition device, a data analysis module, a data preprocessing module, a convolutional neural network module and a hand function rehabilitation module, the data analysis module receives the electroencephalogram signal and analyzes the electroencephalogram signal into an electroencephalogram signal of which the data format can be processed, the data preprocessing module preprocesses the electroencephalogram signal, and the convolutional neural network module receives the preprocessed electroencephalogram signal and carries out model training and testing; after the classification result is obtained, the classification result is used as an instruction for interacting with the hand function rehabilitation module. According to the method, augmented reality and eye movement recognition technologies are combined, more comfortable rehabilitation experience is brought to a stroke patient, the interaction requirement of the patient is met, and the enthusiasm of the patient to participate in rehabilitation is improved.

Description

technical field [0001] The invention relates to a hand function rehabilitation training system, in particular to a hand function rehabilitation training system integrating eye movement direction classification and augmented reality technology. Background technique [0002] With the aging of the population in my country, the incidence of stroke is increasing day by day, and the daily activities of patients are seriously affected. In order to more effectively promote the rehabilitation of the hand function of stroke patients, the rehabilitation training system based on the Brain-Computer Interface (BCI) technology has emerged as the times require, and is more and more widely used in clinical treatment. [0003] However, patients in the early stage of rehabilitation are mainly in the lying position. They need to go through a long period of adaptation and familiarization before they can officially enter the rehabilitation course. During this period, patients often have difficult...

AI Technical Summary

Problems solved by technology

[0005] Eye movements can be captured in a variety of ways, but the traditional methods are less applicable to patients in the early stage of rehabilitation. For example: 1. The electrooculogram is measured by patch electrodes. Since the electrodes are attached around the eyes, the visual field will be reduced. Wearing it for a long time will easily cause facial muscle discomfort and affect the signal quality at the same time, so it is not suitable for the rehabilitation process; second, the eye tracker captures eye movements through computer images, but it must not only bear the cost of the equipment, but also the burden of the rehabilitation therapist. study cost

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