Fractal, entropic and chaotic approaches to complex physiological time series analysis: a critical appraisal

Author(s)
Wu, Guo-Qiang; Ding, Guang-Hong; Li, Cheng; Poon, Chi-Sang
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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.
Date issued
2009-11
URI
http://hdl.handle.net/1721.1/53731
Department
Harvard University--MIT Division of Health Sciences and Technology
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
Other identifiers
INSPEC Accession Number: 10984160
ISBN
978-1-4244-3296-7
ISSN
1557-170X
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