Motor Control Laboratory, Research Center for Movement Control and Neuroplasticity, Department of Biomedical Kinesiology, KU Leuven, Belgium.
J Biomech. 2011 Sep 2;44(13):2401-8. doi: 10.1016/j.jbiomech.2011.06.031. Epub 2011 Jul 16.
Measures calculated from unperturbed walking patterns, such as variability measures and maximum Floquet multipliers, are often used to study the stability of walking. However, it is unknown if, and to what extent, these measures correlate to the probability of falling. We studied whether in a simple model of human walking, i.e., a passive dynamic walker, the probability of falling could be predicted from maximum Floquet multipliers, kinematic state variability, and step time variability. We used an extended version of the basic passive dynamic walker with arced feet and a hip spring. The probability of falling was manipulated by varying the foot radius and hip spring stiffness, or varying these factors while co-varying the slope to keep step length constant. The simulation data indicated that Floquet multipliers and kinematic state variability correlated inconsistently with probability of falling. Step time variability correlated well with probability of falling, but a more consistent correlation with the probability of falling was found by calculating the variability of the log transform of the step time. Our findings speak against the use of maximum Floquet multipliers and suggest instead that variability of critical variables may be a good predictor of the probability to fall.
从未受干扰的行走模式中计算出的措施，如变异性指标和最大 Floquet 乘数，通常用于研究行走的稳定性。然而，目前尚不清楚这些措施是否以及在何种程度上与跌倒的概率相关。我们研究了在一个简单的人类行走模型中，即被动动力步行者，是否可以从最大 Floquet 乘数、运动状态变异性和步时变异性来预测跌倒的概率。我们使用了带有弧形脚和臀部弹簧的基本被动动力步行者的扩展版本。通过改变脚半径和臀部弹簧刚度来操纵跌倒的概率，或者在保持步长不变的情况下同时改变这些因素和坡度。模拟数据表明，Floquet 乘数和运动状态变异性与跌倒概率的相关性不一致。步时变异性与跌倒概率相关性较好，但通过计算步时对数变换的变异性，发现与跌倒概率的相关性更为一致。我们的研究结果表明，最大 Floquet 乘数的使用不可靠，因此，关键变量的变异性可能是跌倒概率的良好预测指标。
