earticle

영어

Patients with shoulder joint injuries exhibit excessive activation of trunk muscles to compensate for limited range of motion. This study implements a digital twin system that utilizes video analysis technology to detect compensatory movements during shoulder exercises in real-time and applies this to functional rehabilitation games. Using RGB camera-based pose estimation algorithms, we quantified compensatory movements of the spine and trunk during shoulder elevation, and developed a system that evaluates exercise effectiveness by measuring key joint angles including flexion, extension, abduction, and adduction. Demonstration content was developed by integrating this with a game interface to provide real-time biofeedback. Pilot testing with one elderly shoulder rehabilitative exercise patient demonstrated that the system detected arm compensatory movements with improved accuracy, achieving a user satisfaction score of 4.3 out of 5.0. This research demonstrates the potential of an accessible rehabilitation game platform utilizing non-contact video analysis and digital twin technology

한국어

본 연구는 RGB 카메라 기반 자세 추정 알고리즘을 활용하여 어깨 운동 중 보상 움직임을 실시간으로 검출하고, 관절 각도를 측정하는 디지털 트윈 재활 시스템을 구현하였다. 게임 인터페이스와 통합하여 실시간 바이오피드백을 제공하며, 파일럿 테스트 결과 사용자 만족도 4.3/5.0점을 기록하였다. 본 연구는 비접촉식 영상 분석 기술을 통한 접근성 높은 재활 게임 플랫폼의 가능성을 제시한다.