인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
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.
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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