Nonlinear time series analysis of electrocardiograms

A. Bezerianos, T. Bountis, G. Papaioannou, P. Polydoropoulos

Research output: Contribution to journalArticle

38 Citations (Scopus)

Abstract

In recent years there has been an increasing number of papers in the literature, applying the methods and techniques of Nonlinear Dynamics to the time series of electrical activity in normal electrocardiograms (ECGs) of various human subjects. Most of these studies are based primarily on correlation dimension estimates, and conclude that the dynamics of the ECG signal is deterministic and occurs on a chaotic attractor, whose dimension can distinguish between healthy and severely malfunctioning cases. In this paper, we first demonstrate that correlation dimension calculations must be used with care, as they do not always yield reliable estimates of the attractor's "dimension." We then carry out a number of additional tests (time differencing, smoothing, principal component analysis, surrogate data analysis, etc.) on the ECGs of three "normal" subjects and three "heavy smokers" at rest and after mild exercising, whose cardiac rhythms look very similar. Our main conclusion is that no major dynamical differences are evident in these signals. A preliminary estimate of three to four basic variables governing the dynamics (based on correlation dimension calculations) is updated to five to six, when temporal correlations between points are removed. Finally, in almost all cases, the transition between resting and mild exercising seems to imply a small increase in the complexity of cardiac dynamics.

Original languageEnglish
Pages (from-to)95-101
Number of pages7
JournalChaos
Volume5
Issue number1
Publication statusPublished - 1995
Externally publishedYes

Fingerprint

Nonlinear Time Series Analysis
electrocardiography
Correlation Dimension
time series analysis
Time series analysis
Electrocardiography
Cardiac
Estimate
Surrogate Data
Temporal Correlation
Chaotic Attractor
estimates
Nonlinear Dynamics
Principal Component Analysis
Smoothing
Attractor
Data analysis
Time series
rhythm
Principal component analysis

ASJC Scopus subject areas

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

Cite this

Bezerianos, A., Bountis, T., Papaioannou, G., & Polydoropoulos, P. (1995). Nonlinear time series analysis of electrocardiograms. Chaos, 5(1), 95-101.

Nonlinear time series analysis of electrocardiograms. / Bezerianos, A.; Bountis, T.; Papaioannou, G.; Polydoropoulos, P.

In: Chaos, Vol. 5, No. 1, 1995, p. 95-101.

Research output: Contribution to journalArticle

Bezerianos, A, Bountis, T, Papaioannou, G & Polydoropoulos, P 1995, 'Nonlinear time series analysis of electrocardiograms', Chaos, vol. 5, no. 1, pp. 95-101.
Bezerianos A, Bountis T, Papaioannou G, Polydoropoulos P. Nonlinear time series analysis of electrocardiograms. Chaos. 1995;5(1):95-101.
Bezerianos, A. ; Bountis, T. ; Papaioannou, G. ; Polydoropoulos, P. / Nonlinear time series analysis of electrocardiograms. In: Chaos. 1995 ; Vol. 5, No. 1. pp. 95-101.
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