Kurz Max J, Stergiou Nicholas
Laboratory of Integrated Physiology, University of Houston, Department of Health and Human Performance, Houston, Texas, USA.
J Neuroeng Rehabil. 2007 Aug 15;4:30. doi: 10.1186/1743-0003-4-30.
Several investigations have suggested that changes in the nonlinear gait dynamics are related to the neural control of locomotion. However, no investigations have provided insight on how neural control of the locomotive pattern may be directly reflected in changes in the nonlinear gait dynamics. Our simulations with a passive dynamic walking model predicted that toe-off impulses that assist the forward motion of the center of mass influence the nonlinear gait dynamics. Here we tested this prediction in humans as they walked on the treadmill while the forward progression of the center of mass was assisted by a custom built mechanical horizontal actuator.
Nineteen participants walked for two minutes on a motorized treadmill as a horizontal actuator assisted the forward translation of the center of mass during the stance phase. All subjects walked at a self-select speed that had a medium-high velocity. The actuator provided assistive forces equal to 0, 3, 6 and 9 percent of the participant's body weight. The largest Lyapunov exponent, which measures the nonlinear structure, was calculated for the hip, knee and ankle joint time series. A repeated measures one-way analysis of variance with a t-test post hoc was used to determine significant differences in the nonlinear gait dynamics.
The magnitude of the largest Lyapunov exponent systematically increased as the percent assistance provided by the mechanical actuator was increased.
These results support our model's prediction that control of the forward progression of the center of mass influences the nonlinear gait dynamics. The inability to control the forward progression of the center of mass during the stance phase may be the reason the nonlinear gait dynamics are altered in pathological populations. However, these conclusions need to be further explored at a range of walking speeds.
多项研究表明,非线性步态动力学的变化与运动的神经控制有关。然而,尚无研究深入探讨运动模式的神经控制如何直接反映在非线性步态动力学的变化中。我们使用被动动态步行模型进行的模拟预测,有助于质心向前运动的蹬离冲量会影响非线性步态动力学。在此,我们在人类在跑步机上行走时对这一预测进行了测试,在此过程中,质心的向前推进由一个定制的机械水平致动器提供辅助。
19名参与者在电动跑步机上行走两分钟,在站立阶段,水平致动器辅助质心向前平移。所有受试者均以自我选择的中高速行走。致动器提供的辅助力相当于参与者体重的0%、3%、6%和9%。计算髋关节、膝关节和踝关节时间序列的最大Lyapunov指数,该指数用于衡量非线性结构。采用重复测量单因素方差分析和事后t检验来确定非线性步态动力学的显著差异。
随着机械致动器提供的辅助百分比增加,最大Lyapunov指数的大小系统性增加。
这些结果支持了我们模型的预测,即质心向前推进的控制会影响非线性步态动力学。在站立阶段无法控制质心的向前推进可能是病理人群中非线性步态动力学改变的原因。然而,这些结论需要在一系列行走速度下进一步探索。