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计算机视觉和增强现实引导的肩部康复

S Pravin Kumar, Kavitha A, S Saranya

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |December 3, 2025
    PubMed
    概括

    这项研究引入了一种计算机视觉系统,用于在康复期间测量肩膀运动范围 (ROM). 这种可访问的技术提供了准确的实时反,改善了患者参与和肌肉骨疾病的结果.

    科学领域:

    • 生物医学工程 生物医学工程
    • 计算机视觉 计算机视觉
    • 康复医学 康复医学 康复医学

    背景情况:

    • 肩部的肌肉骨疾病 (MSD) 需要准确的运动范围 (ROM) 评估.
    • 传统的度测量方法可能是繁的,远程监控也难以使用.
    • 需要具有成本效益的,非侵入性的工具来评估肩部康复进展.

    研究的目的:

    • 开发和验证基于计算机视觉 (CV) 的系统,用于在康复中测量肩部ROM.
    • 为传统的ROM测量工具提供一个具有成本效益和可访问性的替代方案.
    • 通过实时视觉反在肩部康复练习中增强患者参与度.

    主要方法:

    • 利用MediaPipe Pose模型来预测肩膀关节的角度.
    • 开发了一个CV系统,用于远程康复评估肩部ROM.
    • 基于实现的ROM角度 (<80°,80°-100°,>100°) 实现实时彩色编码视觉反.

    主要成果:

    • CV系统与标准ROM测量系统 (LoA在±2.5°以内,RMSE<1) 达成高度一致.
    • 整合了实时视觉反机制以激励患者.
    • 该系统的性能与商业运动跟踪传感器进行了验证,以确定其临床适用性.

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    结论:

    • 基于CV的系统提供了一种新,准确和易于使用的方法,用于在康复中量化肩部ROM.
    • 实时反增强了患者的参与度,并可能改善康复结果.
    • 这项技术对肌肉骨疾病护理和远程物理治疗有重大影响.