Rehabilitation training method for motor dysfunction based on video stream matching

Abstract The development of artificial intelligence technology has also promoted the development of the field of sports rehabilitation. The existing motion matching assisted sports rehabilitation technology has poor applicability in complex environments and slow response time. A video stream matching based rehabilitation training method for motor dysfunction is developed to address the existing problems in motion matching in the field of sports rehabilitation. The research design method compares the movement posture to determine the patient’s rehabilitation level and provides rehabilitation guidance. At the same time, a keyframe comparison action similarity measurement algorithm and an unmatched keyframe action flow similarity algorithm were designed for different rehabilitation stages of patients to improve user experience. The results show that the key frame comparison action similarity metric algorithm has a matching time of about 40 ms and a matching accuracy of about 0.85. The unmatched key frame action flow similarity algorithm has no obvious advantage in the matching time of key frames, but it has an obvious advantage in the matching accuracy, which is as high as 0.9. The proposed video flow matching algorithm effectively improves the speed of patients’ rehabilitation training and the patients’ evaluation of this algorithm is higher than that of the video flow matching algorithm. And the patients’ evaluation of the algorithm is high.