通过主要组件分析分析分析的姿势控制运动的无标记 (Theia3DTM) 与基于标记 (ViconTM) 的运动捕捉数据的验证
Peter Federolf1, Mareike Kühne1, Katharina Schiel1
1Department of Sport Science, University of Innsbruck, Innsbruck, Austria.
无标记运动捕捉 (Theia3D) 与基于标记器的系统 (Vicon) 密切匹配,用于分析姿势控制运动. 这证实了Theia3D作为使用主要组件分析 (PCA) 的研究的一个有效替代方案.
科学领域:
- 生物力学 生物力学
- 人类运动分析 人类运动分析
- 姿势控制研究研究 姿势控制研究
背景情况:
- 像Vicon这样的基于标记器的运动捕捉系统是运动分析的标准.
- 无标记系统提供了潜在的优势,但需要验证以进行姿势控制研究.
- 主要组件分析 (PCA) 是一种识别主动移动 (PM) 的方法.
研究的目的:
- 为了比较来自无标记 (Theia3D) 和基于标记 (Vicon) 系统的主要运动 (PMs).
- 评估Theia3D和Vicon数据在静态状态期间的一致性和敏感性.
- 评估Theia3D作为姿势控制研究的潜在替代方案.
主要方法:
- 从13名志愿者收集了安静的双脚姿势数据,眼睛开着和闭着.
- 从Theia3D和Vicon数据中使用主要组件分析 (PCA) 来得出的本金流动 (PMs).
- 计算PM时间序列的相关系数和对视觉条件的评估灵敏度.
主要成果:
- Theia3D和Vicon产生了非常相似的PM结构,特别是对于前两个PM (前后脚策略和中侧摆动).
- 在前两个PM中观察到近乎完美的相关性 (r=99.8%,99.0%),解释了可比的姿势变异.
- 在前七个PM中发现了强大的一致性 (r=0.814到0.928),占姿势变异的97%.
- 这两种系统对视觉剥夺对姿势控制的影响具有相似的敏感性.
- 在更高阶的PM中,theia3D表现出更高的噪音,这表明预处理是有益的.
结论:
- 通过PCA.获得的姿势主要运动 (PMs) 的结果与Vicon具有高度可比性.
- Theia3D是姿势控制研究的一个有效和高效的替代方案.
- 考虑在PCA之前过Theia3D数据,以减轻更高阶PM中的噪声.
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