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Asymmetry of foot position and weight distribution channels the inter-leg coordination dynamics of standing

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Abstract

The study of quiet standing has mainly been conducted in the foot side-by-side position with the assumption that the contribution of the lower limbs is structurally and functionally equivalent. The purpose of this study was to examine how the two mechanical factors of foot position and weight distribution interact to influence postural control and inter-leg coordination dynamics. Participants were required, while standing in either a side-by-side, staggered, or tandem right foot forward position, to intentionally produce three different levels of weight distribution (50/50, 30/70, and 70/30) over the two feet. Our results showed that the interaction effects of the two mechanical constraints were represented in both linear and nonlinear analyses. The center of pressure (COP) mean velocity was predominantly influenced by body weight distribution in the side-by-side stance, whereas foot position was more influential in the tandem stance. The nonlinear analysis showed that the least experienced postural condition (i.e., tandem stance with a 70/30 loading level) had the lowest number and total duration of COPL–COPR phase synchronization epochs in the AP direction that were compensated by “stable” coordination dynamics in the ML direction. The findings revealed that the staggered stance represents a “hybrid” blend of the properties of the side-by-side and tandem foot positions. Collectively, foot position and weight distribution interact to determine the stability and flexibility of inter-leg coordination dynamics in postural control.

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Notes

  1. In applied statistics, when the assumption of normality has been violated, nonparametric statistics are mostly recommended. However, often it is assumed that nonparametric methods lacks statistical power and that there is a paucity of techniques in more complicated research designs, such as in testing for interaction effects. In these situations, two distinct approaches can be applied: (1) transform the data to a form more closely resembling a normal distribution framework, such as log transformation, square root transformation, etc. or (2) use a distribution free procedure such as rank transformation (RT). Rank transformation procedures are ones in which the usual parametric procedure (e.g., the standard analysis of variance—ANOVA) is applied to the ranks of the data instead of to the data themselves. One form of the rank transformations is to rank the entire set of observations from its smallest to largest, with the smallest observation having rank 1, the second smallest rank 2, and so on. Average ranks are assigned in case of ties.

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  1. Department of Kinesiology, The Pennsylvania State University, 23 Rec Building, University Park, PA, 16802, USA

    Zheng Wang & Karl M. Newell

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  1. Zheng Wang
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  2. Karl M. Newell
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Correspondence to Zheng Wang.

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Wang, Z., Newell, K.M. Asymmetry of foot position and weight distribution channels the inter-leg coordination dynamics of standing. Exp Brain Res 222, 333–344 (2012). https://doi.org/10.1007/s00221-012-3212-7

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