Stroke patient rehabilitation training system and method based on brain myoelectricity and virtual scene

Abstract

Provided are a stroke patient rehabilitation training system and method based on brain myoelectricity and a virtual scene. Control over the virtual rehabilitation scene is achieved through myoelectric signals, and rehabilitation training intensity is adjusted in a self-adaptation mode with a brain myoelectricity fatigue index combined. The design of the virtual rehabilitation scene is completed with the needs of stroke patient rehabilitation training and the advice of a rehabilitation physician combined, the brain fatigue index is provided, and quantitative evaluation on brain region fatigue is achieved. The surface myoelectric signal features under different motion modes of an arm are extracted, the motion intention of a patient is obtained, and control over the virtual rehabilitation scene is achieved. The muscle fatigue and brain fatigue index comprehensive features are extracted, the fatigue state of a rehabilitation patient is obtained, self-adaptation rehabilitation training scene adjusting is achieved, rehabilitation training intensity is relieved or enhanced, and secondary damage caused by improper training is avoided. The system and method have the advantages of being high in safety, high in intelligence and scientific in training, and damage cannot happen easily.

Description

technical field [0001] The invention relates to the technical field of rehabilitation medical equipment, in particular to a rehabilitation training system and method for stroke patients. Background technique [0002] Stroke is known as stroke, which has the characteristics of high morbidity, high mortality, high disability rate, and high recurrence rate. Therefore, the medical community lists it as one of the three major diseases that threaten human health along with coronary heart disease and cancer. . Clinical studies have shown that through timely and active rehabilitation training, most stroke patients can recover the ability to move simple limbs and even recover. Traditional stroke recovery treatment methods are based on reflex or graded motor control, mainly relying on rehabilitation physicians to manually assist patients in rehabilitation training, but the time and course of rehabilitation training cannot be guaranteed, which affects the rehabilitation effect. [00...

AI Technical Summary

Problems solved by technology

However, the above-mentioned computer-aided training system can only assist patients to complete relatively simple rehabilitation training, and it is still difficult to mobilize patients' awareness of active participation and self-confidence

At the same time, due to the lack of an evaluation strategy for the patient's physiological state, the patient is fatigued during the rehabilitation process, and is prone to accidents leading to secondary injuries, which limits the clinical application of virtual reality technology.

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