Norwegian School of Sport Sciences, P.O. Box 4014, Ulleval Stadion, 0806 Oslo, Norway; Human Performance Lab, Faculty of Kinesiology, University of Calgary, Canada.
J Biomech. 2013 Oct 18;46(15):2626-33. doi: 10.1016/j.jbiomech.2013.08.008. Epub 2013 Aug 27.
Postural control research describes ankle-, hip-, or multi-joint strategies as mechanisms to control upright posture. The objectives of this study were, first, development of an analysis technique facilitating a direct comparison of the structure of such multi-segment postural movement patterns between subjects; second, comparison of the complexity of postural movements between three stances of different difficulty levels; and third, investigation of between-subject differences in the structure of postural movements and of factors that may contribute to these differences. Twenty-nine subjects completed 100-s trials in bipedal (BP), tandem (TA) and one-leg stance (OL). Their postural movements were recorded using 28 reflective markers distributed over all body segments. These marker coordinates were interpreted as 84-dimensional posture vectors, normalized, concatenated from all subjects, and submitted to a principal component analysis (PCA) to extract principal movement components (PMs). The PMs were characterized by determining their relative contribution to the subject's entire postural movements and the smoothness of their time series. Four, eight, and nine PM were needed to represent 90% of the total variance in BP, TA, and OL, respectively, suggesting that increased task difficulty is associated with increased complexity of the movement structure. Different subjects utilized different combinations of PMs to control their posture. In several PMs, the relative contribution of a PM to a subject's overall postural movements correlated with the smoothness of the PM's time series, suggesting that utilization of specific postural PMs may depend on the subject's ability to control the PM's temporal evolution.
姿势控制研究将踝关节、髋关节或多关节策略描述为控制直立姿势的机制。本研究的目的首先是开发一种分析技术,以方便在受试者之间直接比较多关节姿势运动模式的结构;其次,比较三种不同难度水平的姿势的复杂性;第三,研究姿势运动结构的个体差异,以及可能导致这些差异的因素。29 名受试者在双足(BP)、并足(TA)和单足(OL)姿势下完成了 100 秒的试验。他们的姿势运动通过分布在所有身体部位的 28 个反射标记进行记录。这些标记坐标被解释为 84 维的姿势向量,经过所有受试者的归一化和串联,然后提交给主成分分析(PCA),以提取主要运动成分(PMs)。PM 以确定它们对主体整个姿势运动的相对贡献及其时间序列的平滑度来进行特征描述。BP、TA 和 OL 分别需要 4、8 和 9 个 PM 来表示 90%的总方差,这表明任务难度的增加与运动结构的复杂性增加有关。不同的受试者使用不同的 PM 组合来控制他们的姿势。在几个 PM 中,PM 对主体整体姿势运动的相对贡献与 PM 时间序列的平滑度相关,这表明特定姿势 PM 的利用可能取决于主体控制 PM 时间演化的能力。