Nonlinear Analysis of Human Gait Signals
Nonlinear Analysis of Human Gait Signals
复制标题
人类步态信号的非线性分析
DOI：
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发表时间：
2012
期刊：
影响因子：
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通讯作者：
A. Goshvarpour
中科院分区：
文献类型：
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作者：
Atefeh Goshvarpour;A. Goshvarpour
非线性动力学已经被引入到生物数据的分析中，并且越来越多地被认为是功能相关的。本研究的目的是评估步态信号的非线性和混沌动力学。为此，我们分析了10名健康受试者的步态数据，这些受试者以平常的、缓慢的和快速的步伐行走了一个小时。计算步态信号的Poincare图、Hurst指数和Lyapunov指数。结果表明，在慢速和快速的步伐赫斯特指数显着增加。对于所有受试者，在正常步态期间，李雅普诺夫指数增加，这表明信号更加混沌。这可能是由于在慢和快的步伐变量的非线性相互作用减少。Hurst指数的有限值和李雅普诺夫指数的正值表明，所有的步态信号具有低维混沌。此外，在缓慢和快速步态期间，信号的复杂度降低。结果对于常见步态病理的早期诊断很有用。
Nonlinear dynamics has been introduced to the analysis of biological data and increasingly recognized to be functionally relevant. The aim of this study is to evaluate nonlinear and chaotic dynamics of gait signals. For this purpose, we analyzed gait data in ten healthy subjects who walked for an hour at their usual, slow and fast paces. Poincare plots, Hurst Exponents and the Lyapunov Exponents of gait signals were calculated. The results show that the Hurst Exponents are significantly increased during slow and fast paces. For all subjects, the Lyapunov Exponents are increased during normal gait, which indicates that signals are more chaotic. This can be due to decreased nonlinear interaction of variables in slow and fast paces. The finite values of Hurst Exponents and positive values of Lyapunov Exponents suggest that all of gait signals have low dimensional chaos. In addition, the complexity of signals is decreased during slow and fast gait. Results are useful for the early diagnosis of common gait pathologies.
影响因子：
3.3
作者：
Hausdorff, JM;Purdon, PL;Goldberger, AL
通讯作者：
Goldberger, AL
影响因子：
3.3
作者：
Hausdorff, JM;Zemany, L;Goldberger, AL
通讯作者：
Goldberger, AL
影响因子：
3.3
作者：
HAUSDORFF, JM;PENG, CK;GOLDBERGER, AL
通讯作者：
GOLDBERGER, AL