Fractal, entropic and chaotic approaches to complex physiological time series analysis: a critical appraisal
Name
Cheng-2009-Fractal, entropic and chaotic approaches to complex physiological time series analysis a critical appraisal.pdf
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726.34 KB
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Adobe PDF
Checksum (MD5)
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Author(s)
Wu, Guo-Qiang
Ding, Guang-Hong
Li, Cheng
Poon, Chi-Sang
Date Issued
November 2009
Journal
Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2009. EMBC 2009.
Publisher
Institute of Electrical and Electronics Engineers
Citation
Cheng Li et al. “Fractal, entropic and chaotic approaches to complex physiological time series analysis: A critical appraisal.” Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE. 2009. 3429-3432.
©2009 Institute of Electrical and Electronics Engineers.
Version
Final published version
Abstract
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.
MIT Department
Harvard University--MIT Division of Health Sciences and Technology
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Persistent DSpace Link
DOI of Published Version
http://dx.doi.org/10.1109/IEMBS.2009.5332501
