Nonlinear dynamics indicates aging affects variability during gait
Nonlinear dynamics indicates aging affects variability during gait
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DOI：
10.1016/s0268-0033(03)00029-9
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发表时间：
2003-06-01
影响因子：
1.8
通讯作者：
Heidel, J
中科院分区：
文献类型：
--
作者：
Buzzi, UH;Stergiou, N;Heidel, J
Objective.通过非线性分析研究两个不同年龄组步态参数产生的时间序列中存在的变异性的性质。非线性动力学的措施被用来比较老年和年轻女性之间的运动学参数。背景衰老可能导致行走过程中运动变异性的变化，这可能解释老年人福尔斯的高发病率。20名女性，10名年轻（20-37岁）和10名老年人（71-79岁）在跑步机上连续行走30个步态周期。从右下肢的运动学参数的时间序列进行了分析，使用非线性动力学。计算了所有时间序列的最大李雅普诺夫指数和关联维数，以及替代原始时间序列的最大李雅普诺夫指数。还计算了每个步态周期中选定离散点的标准差和变异系数。采用独立t检验进行统计学比较。的李雅普诺夫指数被发现是显着不同的替代品。这表明在时间序列中观察到的波动可能反映了神经肌肉系统的确定性过程。老年人表现出显着较大的Lyapunov指数和相关维数的所有参数进行评估，表明局部不稳定。线性测量表明，老年人表现出显着更高的变异性。非线性分析表明，某些步态参数的时间序列中的波动不是随机的，而是显示出确定性的行为。这种行为可能会随着生理老化而退化，导致局部不稳定。
Objective. To investigate the nature of variability present in time series generated from gait parameters of two different age groups via a nonlinear analysis.Design. Measures of nonlinear dynamics were used to compare kinematic parameters between elderly and young females. Background. Aging may lead to changes in motor variability during walking, which may explain the large incidence of falls in the elderly.Methods. Twenty females, 10 younger (20-37 yr) and 10 older (71-79 yr) walked on a treadmill for 30 consecutive gait cycles. Time series from selected kinematic parameters of the right lower extremity were analyzed using nonlinear dynamics. The largest Lyapunov exponent and the correlation dimension of all time series, and the largest Lyapunov exponent of the original time series surrogated were calculated. Standard deviations and coefficient of variations were also calculated for selected discrete points from each gait cycle. Independent t-tests were used for statistical comparisons.Results. The Lyapunov exponents were found to be significantly different from their surrogate counterparts. This indicates that the fluctuations observed in the time series may reflect deterministic processes by the neuromuscular system. The elderly exhibited significantly larger Lyapunov exponents and correlation dimensions for all parameters evaluated indicating local instability. The linear measures indicated that the elderly demonstrated significantly higher variability.Conclusions. The nonlinear analysis revealed that fluctuations in the time series of certain gait parameters are not random but display a deterministic behavior. This behavior may degrade with physiologic aging resulting in local instability.