Bruijn Sjoerd M, van Dieën Jaap H, Meijer Onno G, Beek Peter J
Research Institute MOVE, Faculty of Human Movement Sciences, VU University Amsterdam, Van der Boechorststraat 9, NL-1081 BT Amsterdam, The Netherlands.
Research Institute MOVE, Faculty of Human Movement Sciences, VU University Amsterdam, Van der Boechorststraat 9, NL-1081 BT Amsterdam, The Netherlands.
J Biomech. 2009 Jul 22;42(10):1506-1512. doi: 10.1016/j.jbiomech.2009.03.047. Epub 2009 May 15.
Several efforts have been made to study gait stability using measures derived from nonlinear time-series analysis. The maximum finite time Lyapunov exponent (lambda(max)) quantifies how a system responds to an infinitesimally small perturbation. Recent studies suggested that slow walking leads to lower lambda(max) values, and thus is more stable than fast walking, but these studies suffer from methodological limitations. We studied the effects of walking speed on the amount of kinematic variability and stability in human walking. Trunk motions of 15 healthy volunteers were recorded in 3D during 2 min of treadmill walking at different speeds. From those time series, maximum Lyapunov exponents, indicating short-term and long-term divergence (lambda(S-stride) and lambda(L-stride)), and mean standard deviation (MeanSD) were calculated. lambda(S-stride) showed a linear decrease with increasing speed for forward-backward (AP) movements and quadratic effects (inverted U-shaped) for medio-lateral (ML) and up-down (VT) movements. lambda(L-stride) showed a quadratic effect (inverted U-shaped) of walking speed for AP movements, a linear decrease for ML movements, and a linear increase for VT movements. Moreover, positive correlations between lambda(S) and MeanSD were found for all directions, while lambda(L-stride) and MeanSD were correlated negatively in the AP direction. The different effects of walking speed on lambda(S-stride) and lambda(L-stride) for the different planes suggest that slow walking is not necessarily more stable than fast walking. The absence of a consistent pattern of correlations between lambda(L-stride) and MeanSD over the three directions suggests that variability and stability reflect, at least to a degree, different properties of the dynamics of walking.
已经开展了多项研究，旨在使用源自非线性时间序列分析的测量方法来研究步态稳定性。最大有限时间李雅普诺夫指数（lambda(max)）量化了系统对无穷小扰动的响应方式。最近的研究表明，慢走会导致较低的lambda(max)值，因此比快走更稳定，但这些研究存在方法上的局限性。我们研究了步行速度对人体步行中运动学变异性和稳定性的影响。在跑步机上以不同速度行走2分钟期间，对15名健康志愿者的躯干运动进行了三维记录。从这些时间序列中，计算出了最大李雅普诺夫指数，分别表示短期和长期发散（lambda(S-stride)和lambda(L-stride)）以及平均标准差（MeanSD）。lambda(S-stride)在前后（AP）运动中随速度增加呈线性下降，在内外侧（ML）和上下（VT）运动中呈二次效应（倒U形）。lambda(L-stride)在AP运动中呈二次效应（倒U形），在ML运动中呈线性下降，在VT运动中呈线性增加。此外，在所有方向上lambda(S)与MeanSD之间均发现正相关，而在AP方向上lambda(L-stride)与MeanSD呈负相关。步行速度对不同平面上的lambda(S-stride)和lambda(L-stride)的不同影响表明，慢走不一定比快走更稳定。在三个方向上lambda(L-stride)与MeanSD之间缺乏一致的相关模式，这表明变异性和稳定性至少在一定程度上反映了步行动力学的不同特性。
