使用SHAP和LDA进行VR练习评估的可解释生物力学特征选择
Urszula Czajkowska1, Magdalena Żuk1, Michał Popek1
1Faculty of Mechanical Engineering, Wroclaw University of Science and Technology, Wybrzeże Wyspianskiego 27, 50-370 Wrocław, Poland.
Sensors (Basel, Switzerland)
|January 28, 2026
概括
虚拟现实 (VR) 康复可以使用生物机械特征客观地评估人类运动质量. 简化的传感器设置为诊所和家庭的可解释VR系统提供了可靠的见解.
科学领域:
- 生物力学 生物力学
- 康复工程 康复工程
- 虚拟现实 虚拟现实 虚拟现实
背景情况:
- 虚拟现实 (VR) 提供交互式康复,但缺乏客观的人类运动质量评估 (HMQA).
- 在VR中确定准确的HMQA的关键生物力学特征对于有效的康复至关重要.
研究的目的:
- 为了确定区分正确和不正确的横侧肺的生物力学特征.
- 确定可靠VR运动分析的最小传感器,优先考虑可解释性.
主要方法:
- 32名健康成年人进行了侧侧肺检查,并用7个传感器的HTC Vive追踪系统进行了记录.
- 线性差异分析 (LDA) 和夏普利增量扩展 (SHAP) 分析了关节的角度,速度,加速和传感器距离.
- 物理治疗师的视频观察分类重复对地面真理.
主要成果:
- 角形特征 (例如,部曲,膝盖旋转加速) 显示出较高的LDA性能 (F1=0.89),而不是距离特征 (F1=0.78).
- SHAP和LDA分析一致认为关键特征,包括传感器与身体的空间关系.
- 较少的传感器可以提供可靠的诊断信息,角度特征更稳定.
结论:
- 目标在VR中的HMQA是可行的,使用选定的生物力学特征.
- 简化的传感器配置可以实现可靠和可解释的运动分析.
- 这有助于为各种环境开发可访问的VR康复系统.
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