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A novel approach to study human posture control: “Principal movements” obtained from a principal component analysis of kinematic marker data

机译:一种研究人体姿势控制的新方法:从运动学标记数据的主成分分析中获得的“主要运动”

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摘要

Human upright posture is maintained by postural movements, which can be quantified by “principal movements” (PMs) obtained through a principal component analysis (PCA) of kinematic marker data. The current study expands the concept of “principal movements” in analogy to Newton׳s mechanics by defining “principal position” (PP), “principal velocity” (PV), and “principal acceleration” (PA) and demonstrates that a linear combination of PPs and PAs determines the center of pressure (COP) variance in upright standing. Twenty-one subjects equipped with 27-markers distributed over all body segments stood on a force plate while their postural movements were recorded using a standard motion tracking system. A PCA calculated on normalized and weighted posture vectors yielded the PPs and their time derivatives, the PVs and PAs. COP variance explained by the PPs and PAs was obtained through a regression analysis. The first 15 PMs quantified 99.3% of the postural variance and explained 99.60%±0.22% (mean±SD) of the anterior–posterior and 98.82±0.74% of the lateral COP variance in the 21 subjects. Calculation of the PMs thus provides a data-driven definition of variables that simultaneously quantify the state of the postural system (PPs and PVs) and the activity of the neuro-muscular controller (PAs). Since the definition of PPs and PAs is consistent with Newton׳s mechanics, these variables facilitate studying how mechanical variables, such as the COP motion, are governed by the postural control system.
机译:人体直立姿势通过姿势运动来维持,姿势运动可以通过运动学标记数据的主成分分析(PCA)获得的“主要运动”(PM)进行量化。当前的研究通过定义“主要位置”(PP),“主要速度”(PV)和“主要加速度”(PA)来扩展类似于牛顿力学的“主要运动”的概念,并证明了线性组合PP和PA的数量决定了直立站立时压力中心(COP)的变化。二十一个配有27个标记的受试者分布在所有身体部位上,并用标准运动跟踪系统记录了他们的姿势运动,并将它们置于姿势板上。根据归一化和加权姿态向量计算的PCA得出PP及其时间导数,PV和PA。通过回归分析获得由PP和PA解释的COP方差。前21名受试者的前15个PM量化了99.3%的姿势差异,解释了前后差异的99.60%±0.22%(平均值±SD)和侧面COP差异的98.82±0.74%。因此,PM的计算提供了变量的数据驱动定义,这些变量同时量化了姿势系统(PP和PV)的状态以及神经肌肉控制器(PA)的活动。由于PP和PA的定义与牛顿力学一致,因此这些变量有助于研究姿势控制系统如何控制机械变量(例如COP运动)。

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    Federolf, Peter Andreas;

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  • 年度 2016
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  • 原文格式 PDF
  • 正文语种 en
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