From 1/f noise to multifractal cascades in heartbeat dynamics

Plamen Ch Ivanov*, Luís A. Nunes Amaral, Ary L. Goldberger, Shlomo Havlin, Michael G. Rosenblum, H. Eugene Stanley, Zbigniew R. Struzik

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

304 Scopus citations

Abstract

We explore the degree to which concepts developed in statistical physics can be usefully applied to physiological signals. We illustrate the problems related to physiologic signal analysis with representative examples of human heartbeat dynamics under healthy and pathologic conditions. We first review recent progress based on two analysis methods, power spectrum and detrended fluctuation analysis, used to quantify long-range power-law correlations in noisy heartbeat fluctuations. The finding of power-law correlations indicates presence of scale-invariant, fractal structures in the human heartbeat. These fractal structures are represented by self-affine cascades of beat-to-beat fluctuations revealed by wavelet decomposition at different time scales. We then describe very recent work that quantifies multifractal features in these cascades, and the discovery that the multifractal structure of healthy dynamics is lost with congestive heart failure. The analytic tools we discuss may be used on a wide range of physiologic signals.

Original languageEnglish (US)
Pages (from-to)641-652
Number of pages12
JournalChaos
Volume11
Issue number3
DOIs
StatePublished - Sep 2001

ASJC Scopus subject areas

  • Statistical and Nonlinear Physics
  • Mathematical Physics
  • Physics and Astronomy(all)
  • Applied Mathematics

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