Ducharme Scott W, Liddy Joshua J, Haddad Jeffrey M, Busa Michael A, Claxton Laura J, van Emmerik Richard E A
Motor Control Laboratory, University of Massachusetts-Amherst, Amherst, MA, USA; Physical Activity & Health Laboratory, University of Massachusetts-Amherst, Amherst, MA, USA.
Motor Development and Control Laboratory, Purdue University, West Lafayette, IN, USA.
Hum Mov Sci. 2018 Apr;58:248-259. doi: 10.1016/j.humov.2018.02.011. Epub 2018 Mar 12.
Human locomotion is an inherently complex activity that requires the coordination and control of neurophysiological and biomechanical degrees of freedom across various spatiotemporal scales. Locomotor patterns must constantly be altered in the face of changing environmental or task demands, such as heterogeneous terrains or obstacles. Variability in stride times occurring at short time scales (e.g., 5-10 strides) is statistically correlated to larger fluctuations occurring over longer time scales (e.g., 50-100 strides). This relationship, known as fractal dynamics, is thought to represent the adaptive capacity of the locomotor system. However, this has not been tested empirically. Thus, the purpose of this study was to determine if stride time fractality during steady state walking associated with the ability of individuals to adapt their gait patterns when locomotor speed and symmetry are altered. Fifteen healthy adults walked on a split-belt treadmill at preferred speed, half of preferred speed, and with one leg at preferred speed and the other at half speed (2:1 ratio asymmetric walking). The asymmetric belt speed condition induced gait asymmetries that required adaptation of locomotor patterns. The slow speed manipulation was chosen in order to determine the impact of gait speed on stride time fractal dynamics. Detrended fluctuation analysis was used to quantify the correlation structure, i.e., fractality, of stride times. Cross-correlation analysis was used to measure the deviation from intended anti-phasing between legs as a measure of gait adaptation. Results revealed no association between unperturbed walking fractal dynamics and gait adaptability performance. However, there was a quadratic relationship between perturbed, asymmetric walking fractal dynamics and adaptive performance during split-belt walking, whereby individuals who exhibited fractal scaling exponents that deviated from 1/f performed the poorest. Compared to steady state preferred walking speed, fractal dynamics increased closer to 1/f when participants were exposed to asymmetric walking. These findings suggest there may not be a relationship between unperturbed preferred or slow speed walking fractal dynamics and gait adaptability. However, the emergent relationship between asymmetric walking fractal dynamics and limb phase adaptation may represent a functional reorganization of the locomotor system (i.e., improved interactivity between degrees of freedom within the system) to be better suited to attenuate externally generated perturbations at various spatiotemporal scales.
人类运动是一项本质上复杂的活动,需要在各种时空尺度上对神经生理和生物力学自由度进行协调与控制。面对不断变化的环境或任务需求,如不同的地形或障碍物,运动模式必须不断改变。在短时间尺度(如5 - 10步)上出现的步幅时间变异性与在较长时间尺度(如50 - 100步)上出现的较大波动在统计上相关。这种关系被称为分形动力学,被认为代表了运动系统的适应能力。然而,这尚未经过实证检验。因此,本研究的目的是确定在稳态行走过程中步幅时间分形性是否与个体在运动速度和对称性改变时调整步态模式的能力相关。15名健康成年人在分体式跑步机上以偏好速度、偏好速度的一半以及一条腿以偏好速度而另一条腿以一半速度(2:1比例的不对称行走)行走。不对称的皮带速度条件引发了步态不对称,这需要对运动模式进行调整。选择慢速操作是为了确定步态速度对步幅时间分形动力学的影响。去趋势波动分析用于量化步幅时间的相关结构,即分形性。互相关分析用于测量双腿之间与预期反相位的偏差,作为步态适应性的一种度量。结果显示,未受干扰的行走分形动力学与步态适应性能之间没有关联。然而,在分体式跑步机行走过程中,受干扰的不对称行走分形动力学与适应性能之间存在二次关系,即表现出分形标度指数偏离1/f的个体表现最差。与稳态偏好行走速度相比,当参与者进行不对称行走时,分形动力学更接近1/f。这些发现表明,未受干扰的偏好或慢速行走分形动力学与步态适应性之间可能没有关系。然而,不对称行走分形动力学与肢体相位适应之间新出现的关系可能代表了运动系统的功能重组(即系统内自由度之间改善的交互性),以便更好地适应在各种时空尺度上外部产生的干扰。