Fractal, entropic and chaotic approaches to complex physiological time series analysis: a critical appraisal.
Fractal, entropic and chaotic approaches to complex physiological time series analysis: a critical appraisal.
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复杂生理时间序列分析的分形、熵和混沌方法：批判性评估。
DOI：
10.1109/iembs.2009.5332501
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发表时间：
2009
期刊：
影响因子：
--
通讯作者：
Poon,Chi-Sang
中科院分区：
文献类型：
--
作者：
Li,Cheng;Ding,Guang-Hong;Wu,Guo-Qiang;Poon,Chi-Sang
A wide variety of methods based on fractal, entropic or chaotic approaches have been applied to the analysis of complex physiological time series. In this paper, we show that fractal and entropy measures are poor indicators of nonlinearity for gait data and heart rate variability data. In contrast, the noise titration method based on Volterra autoregressive modeling represents the most reliable currently available method for testing nonlinear determinism and chaotic dynamics in the presence of measurement noise and dynamic noise.
