康复
计算机科学
运动(物理)
手势
物理医学与康复
人工智能
资源(消歧)
比例(比率)
人机交互
物理疗法
医学
计算机网络
物理
量子力学
标识
DOI:10.1109/cyber55403.2022.9907662
摘要
The lack of rehabilitation therapists and the increase of disabled individuals have reduced the opportunities for patients to receive well rehabilitation assessment. Towards solving this challenge, establishing a therapist-assistance assessment system to reduce the medical resource consumption is demanding. This paper proposes an automatic hand rehabilitation assessment system based on the Leap Motion vision sensor and a self-designed hand strength measurement device. The assessment algorithm requires the patients to complete every motion given in Fugl-Meyer assessment scale (FMA), and automatically scores the completion level of each motion via recognizing different hand gestures and hand grasping strength. As illustrated by the experiments on ten volunteers, the proposed assessment system can obtain the reliable scores which are consistent with the ones manually obtained via FMA.
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