IS WALKING A RANDOM-WALK - EVIDENCE FOR LONG-RANGE CORRELATIONS IN STRIDE INTERVAL OF HUMAN GAIT
IS WALKING A RANDOM-WALK - EVIDENCE FOR LONG-RANGE CORRELATIONS IN STRIDE INTERVAL OF HUMAN GAIT
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DOI：
10.1152/jappl.1995.78.1.349
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发表时间：
1995-01-01
影响因子：
3.3
通讯作者：
GOLDBERGER, AL
中科院分区：
文献类型：
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作者：
HAUSDORFF, JM;PENG, CK;GOLDBERGER, AL
复杂的未知来源的波动出现在正常的步态模式。这些波动可以被描述为1)不相关的白噪声，2)短距离相关性，或3)幂律缩放的长期相关性。为了测试这些可能性，研究人员测量了10名健康年轻男性以正常速度步行9分钟时的步幅间隔。从这些时间序列中，我们使用改进的随机游走分析和功率谱分析计算尺度指数。这两个指标都表明存在延伸数百步的长期自相似相关性；任何时候的步幅间隔依赖于远前时间的步幅间隔，这种依赖性以无标度（分形）幂律的方式衰减。这些标度指标与原始时间序列随机洗牌后的标度指标有显著差异，说明步长区间的顺序排序的重要性。我们证明了传统的步态生成模型无法再现观察到的缩放行为，并引入了一种新型的中心模式生成器模型，该模型成功地解释了实验观察到的远程相关性。
Complex fluctuations of unknown origin appear in the normal gait pattern. These fluctuations might be described as being 1) uncorrelated white noise, 2) short-range correlations, or 3) long-range correlations with power-law scaling. To test these possibilities, the stride interval of 10 healthy young men was measured as they walked for 9 min at their usual rate. From these time series, we calculated scaling indexes by using a modified random walk analysis and power spectral analysis. Both indexes indicated the presence of long-range self-similar correlations extending over hundreds of steps; the stride interval at any time depended on the stride interval at remote previous times, and this dependence decayed in a scale-free (fractallike) power-law fashion. These scaling indexes were significantly different from those obtained after random shuffling of the original time series, indicating the importance of the sequential ordering of the stride interval. We demonstrate that conventional models of gait generation fail to reproduce the observed scaling behavior and introduce a new type of central pattern generator model that successfully accounts for the experimentally observed long-range correlations.