Multiscale Entropy Analysis of Complex Physiologic Time Series

Madalena Costa, Ary L. Goldberger, and C.-K. Peng
Phys. Rev. Lett. 89, 068102 – Published 19 July 2002

Abstract

There has been considerable interest in quantifying the complexity of physiologic time series, such as heart rate. However, traditional algorithms indicate higher complexity for certain pathologic processes associated with random outputs than for healthy dynamics exhibiting long-range correlations. This paradox may be due to the fact that conventional algorithms fail to account for the multiple time scales inherent in healthy physiologic dynamics. We introduce a method to calculate multiscale entropy (MSE) for complex time series. We find that MSE robustly separates healthy and pathologic groups and consistently yields higher values for simulated long-range correlated noise compared to uncorrelated noise.

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  • Received 26 March 2002

DOI:https://doi.org/10.1103/PhysRevLett.89.068102

©2002 American Physical Society

Authors & Affiliations

Madalena Costa1,2, Ary L. Goldberger1, and C.-K. Peng1

  • 1Cardiovascular Division, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts 02215
  • 2Institute of Biophysics and Biomedical Engineering, Faculty of Science of the University of Lisbon, Campo Grande, 1749-016 Lisbon, Portugal

Comments & Replies

Costa, Goldberger, and Peng Reply:

Madalena Costa, Ary L. Goldberger, and C.-K. Peng
Phys. Rev. Lett. 91, 119802 (2003)

Intermittently Decreased Beat-To-Beat Variability in Congestive Heart Failure

Niels Wessel, Alexander Schirdewan, and Jürgen Kurths
Phys. Rev. Lett. 91, 119801 (2003)

Costa, Goldberger, and Peng Reply:

Madalena Costa, Ary L. Goldberger, and C.-K. Peng
Phys. Rev. Lett. 92, 089804 (2004)

Comment on “Multiscale Entropy Analysis of Complex Physiologic Time Series”

Vadim V. Nikulin and Tom Brismar
Phys. Rev. Lett. 92, 089803 (2004)

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Vol. 89, Iss. 6 — 5 August 2002

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