Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada.
Hum Mov Sci. 2010 Feb;29(1):125-36. doi: 10.1016/j.humov.2009.09.002. Epub 2010 Jan 8.
Fluctuations in the stride interval of human gait have been found to exhibit statistical persistence over hundreds of strides, the extent of which changes with age, pathology, and speed-constrained walking. Thus, recent investigations have focused on quantifying this scaling behavior in order to gain insight into locomotor control. While the ability of a given analysis technique to provide an accurate scaling estimate depends largely on the stationary properties of the given series, direct investigation of stride interval stationarity has been largely overlooked. In the present study we test the stride interval time series obtained from able-bodied children for weak stationarity. Specifically, we analyze signals obtained during three distinct modes of self-paced locomotion: (i) overground walking, (ii) unsupported (hands-free) treadmill walking, and (iii) handrail-supported treadmill walking. Using the reverse arrangements test, we identify non-stationary signals in all three walking conditions and find the major known cause to be due to time-varying first and second moments. We further discuss our findings in terms of locomotor control and the differences between the locomotor modalities investigated. Overall, our results advocate against scaling analysis techniques that assume stationarity.
人类步态的步幅间隔波动被发现具有数百步的统计持续性，其程度随年龄、病理学和速度限制的行走而变化。因此，最近的研究集中在量化这种标度行为上，以深入了解运动控制。虽然给定分析技术提供准确标度估计的能力在很大程度上取决于给定序列的平稳性，但对步幅间隔平稳性的直接研究在很大程度上被忽视了。在本研究中，我们测试了来自健康儿童的步幅间隔时间序列的弱平稳性。具体来说，我们分析了在三种不同的自主运动模式下获得的信号：（i）地面行走，（ii）无支撑（无手）跑步机行走，以及（iii）扶手支撑跑步机行走。使用反转排列测试，我们在所有三种行走条件下都识别出了非平稳信号，并发现主要的已知原因是由于时变的第一和第二矩。我们进一步根据运动控制和所研究的运动模式之间的差异讨论了我们的发现。总体而言，我们的结果反对假设平稳性的标度分析技术。
