Multiscale entropy analysis of human gait dynamics
Multiscale entropy analysis of human gait dynamics
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DOI：
10.1016/j.physa.2003.08.022
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发表时间：
2003-12-01
影响因子：
3.3
通讯作者：
Hausdorff, JM
中科院分区：
文献类型：
--
作者：
Costa, M;Peng, CK;Hausdorff, JM
我们比较了不同条件下健康人步态时间序列的复杂性。使用最近开发的多尺度熵算法，它提供了一种方法来衡量复杂性的范围内的规模，我们观察到，正常的自发行走具有最高的复杂性相比，慢速和快速行走，也步行节奏的节拍器。这些研究结果的影响，运动控制建模和量化步态动力学的生理和病理状态。(C)2003 Elsevier B.V.保留所有权利。
We compare the complexity of human gait time series from healthy subjects under different conditions. Using the recently developed multiscale entropy algorithm, which provides a way to measure complexity over a range of scales, we observe that normal spontaneous walking has the highest complexity when compared to slow and fast walking and also to walking paced by a metronome. These findings have implications for modeling locomotor control and for quantifying gait dynamics in physiologic and pathologic states. (C) 2003 Elsevier B.V. All rights reserved.