Deviations from uniform power law scaling in nonstationary time series.
Deviations from uniform power law scaling in nonstationary time series.
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DOI：
10.1103/physreve.55.845
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发表时间：
1997
期刊：
影响因子：
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通讯作者：
G. Viswanathan;Chung-Kang Peng;H. Stanley;A. Goldberger
中科院分区：
文献类型：
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作者：
G. Viswanathan;Chung-Kang Peng;H. Stanley;A. Goldberger
物理学中的一个经典问题是分析高度非平稳的时间序列，这些时间序列通常表现出长程相关性。在这里，我们测试的假设，健康的生理系统的动态的缩放特性比那些病理系统更稳定，通过研究心跳到心跳的波动，在人类的心率。我们开发的技术的基础上的Fano因子和Allan因子函数，以及去趋势波动分析，量化的偏差从均匀幂律缩放非平稳时间序列。通过分析11名健康受试者高达N = 10（5）次心跳的极长数据集，我们发现心率的波动在几个时间量级上大致均匀。相比之下，我们发现，在14名心脏病患者的可比长度的数据集中，波动不规则地增长，表明失去了缩放稳定性。
A classic problem in physics is the analysis of highly nonstationary time series that typically exhibit long-range correlations. Here we test the hypothesis that the scaling properties of the dynamics of healthy physiological systems are more stable than those of pathological systems by studying beat-to-beat fluctuations in the human heart rate. We develop techniques based on the Fano factor and Allan factor functions, as well as on detrended fluctuation analysis, for quantifying deviations from uniform power-law scaling in nonstationary time series. By analyzing extremely long data sets of up to N = 10(5) beats for 11 healthy subjects, we find that the fluctuations in the heart rate scale approximately uniformly over several temporal orders of magnitude. By contrast, we find that in data sets of comparable length for 14 subjects with heart disease, the fluctuations grow erratically, indicating a loss of scaling stability.