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基于手势交互的辅助膝关节疾病患者康复的运动游戏系统的设计与评估

Design and evaluation of an exergame system to assist knee disorders patients' rehabilitation based on gesture interaction.

作者信息

Wang Guangjun, Zhu Bangguo, Fan Yi, Wu Ming, Wang Xueshu, Zhang Hanyuan, Yao Liangliang, Sun Yining, Su Benyue, Ma Zuchang

机构信息

Anhui Province Key Laboratory of Medical Physics and Technology, Institute of Intelligent Machines, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, 230031 China.

Science Island Branch of Graduate School, University of Science and Technology of China, Hefei, 230026 China.

出版信息

Health Inf Sci Syst. 2022 Aug 26;10(1):20. doi: 10.1007/s13755-022-00189-5. eCollection 2022 Dec.

Abstract

UNLABELLED

We designed a knee rehabilitation exercise game (Exergame) for home-based rehabilitation of patients with knee disorders. The system includes three functional components: knee exercise plan formulation, exergame, and exercise feedback. The 3D Human Pose Estimation based on images is used as the gesture interaction to capture the patient's primary joint motion data. We recruited 20 knee osteoarthritis (KOA) to evaluate the system's feasibility and user experience. The physician's group formulated the patient's exercise plans. The average accuracy of motion recognition is 95.2%, indicating that the system can effectively guide rehabilitation training for KOA patients. The results of the UEQ-S questionnaire, namely the practical quality value (1.63 ± 0.85), hedonic quality value (1.75 ± 0.86), and the total value (1.69 ± 0.86) of 20 patients, indicate that the system provides an excellent user experience, which improves the willingness and compliance of the patients for the active exercise. The above evidence confirms that the proposed approach is suitable for Knee disorders rehabilitation exercise and has promising application prospects.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s13755-022-00189-5.

摘要

未标注

我们设计了一款用于膝关节疾病患者居家康复的膝关节康复锻炼游戏(运动游戏)。该系统包括三个功能组件:膝关节锻炼计划制定、运动游戏和锻炼反馈。基于图像的3D人体姿态估计用作手势交互,以捕捉患者的主要关节运动数据。我们招募了20名膝关节骨关节炎(KOA)患者来评估该系统的可行性和用户体验。医生团队制定患者的锻炼计划。运动识别的平均准确率为95.2%,表明该系统能够有效地指导KOA患者的康复训练。20名患者的UEQ-S问卷结果,即实用质量值(1.63±0.85)、享乐质量值(1.75±0.86)和总值(1.69±0.86),表明该系统提供了出色的用户体验,提高了患者主动锻炼的意愿和依从性。上述证据证实,所提出的方法适用于膝关节疾病的康复锻炼,具有广阔的应用前景。

补充信息

在线版本包含可在10.1007/s13755-022-00189-5获取的补充材料。

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