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通过使用单平面智能手机视频对上肢功能的自动评估与修改的马莱特得分.

Cancan Su1, Lianne Brandt1, Guangwen Sun1

  • 1Children's Hospital of Eastern Ontario Research Institute, Ottawa, ON K1H 8L1, Canada.

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|March 17, 2025
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概括

这项研究介绍了一种使用智能手机视频的AI驱动系统,用于自动化上肢功能的修改马莱特评分 (MMS) 评估,实现高精度并实现远程评估.

关键词:
打开Pose,可以使用.临床相关的解释.修改后的马莱特分数构成估计估计的估计.智能手机的智能手机智能手机的智能手机.两个维的坐标是两个维的坐标.视频 视频 视频 视频 视频

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科学领域:

  • 医疗技术 医学技术
  • 人工智能的人工智能是人工智能.
  • 生物力学 生物力学

背景情况:

  • 修改的马莱特评分 (MMS) 是一种标准的临床工具,用于评估上肢功能.
  • 目前的MMS评估需要经验丰富的临床医生,限制了可访问性和可扩展性.
  • 需要客观,远程和高效的MMS评估方法.

研究的目的:

  • 开发和验证使用人工智能 (AI) 和智能手机视频进行修改马莱特分数 (MMS) 评估的自动化系统.
  • 与专家临床评估相比,评估人工智能驱动的MMS评分系统的准确性和可靠性.
  • 探索基于人工智能的远程评估上肢功能的潜力.

主要方法:

  • 使用了四名参与者的智能手机视频,涵盖了所有MMS等级.
  • 使用OpenPose BODY25模型从视频中提取身体关键点数据.
  • 开发了一种算法来计算关节角度和自动化MMS得分.
  • 将自动化得分与专家医生手动评分进行比较 (地面真相).

主要成果:

  • 该自动化系统在关键上肢运动中表现出高精度,包括全球绑架,手到子,手到脊柱和手到嘴.
  • 通过比0.9大的皮尔森相关系数 (PCC) 和低根平均平方误差 (RMSE) 实现了高可靠性.
  • 显示强烈同意全球外部旋转,尽管与其他运动相比,准确性略低.

结论:

  • 智能手机视频的AI驱动分析提供了一种可靠的方法来自动化MMS评估.
  • 这项技术有可能促进远程,客观和可访问的上肢功能评估.
  • 这些发现支持将人工智能纳入临床实践,以有效监测和评估患者.