Methods Inf Med 1997; 36(04/05): 274-277
DOI: 10.1055/s-0038-1636877
Original Article
Schattauer GmbH

Study of the Lyapunov Exponents in Heart Rate Variability Signals

A. Casaleggio
1   TCE-CNR, Genova, Polytechnic University, Milan; Italy
,
S. Cerutti
2   Biomedical Engineering Dept, Polytechnic University, Milan; Italy
,
M. G. Signorini
2   Biomedical Engineering Dept, Polytechnic University, Milan; Italy
› Institutsangaben
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Publikationsverlauf

Publikationsdatum:
19. Februar 2018 (online)

Abstract:

Heart rate variability signals obtained from 24 h recordings are analyzed for normal and pathological subjects. This time series contains information about the autonomic nervous system action regulating the beat-to-beat heart rate. Nonlinear contributions to the long period variability have been assessed by the calculation of the entire spectrum of Lyapunov exponents, after the system trajectory reconstruction, starting from the original variability signal. The positivity of Lyapunov exponent values, obtained from an unknown process, can establish whether the structure generating it shows nonlinear chaotic characteristics. This is what happens for the cardiovascular signals. Moreover, the different values obtained for the Lyapunov exponents operate a classification among the considered pathophysiological cases.

 
  • REFERENCES

  • 1 Ott E, Sauer T, Yorke JA. Coping with Chaos: Analysis of Chaotic Data and the Exploitation of Chaotic Systems. New York: Wiley; 1994
  • 2 Sano M, Sawada Y. Measurement of the Lyapunov Spectrum from a Chaotic Time Series. Phys Rev Lett 1985; 55: 1082-5.
  • 3 Eckmann JP, Kamphorst OS, Ruelle D, Ciliberto S. Lyapunov exponents from time series. Phys Rev A 1986; 34: 4971-9.
  • 4 Casaleggio A, Braiotta S. On the Influence of Working Parameters in Lyapunov Exponent Estimate from Time Series. (unpublished)
  • 5 Casaleggio A, Braiotta S, Corana A. Study of the Lyapunov Exponents of ECG Signals from MIT-BIH Database. Proc Comput Cardiol IEEE Conf 1995; 95: 697-700.
  • 6 Cerutti S, Signorini MG. The heart rate variability signal: among rhythms, noise and chaos. Biomedical Signal Processing. Inbar G, Gath I. eds. Plenum Press; 1996: 235-49.
  • 7 Task Force of ESC and NASPE, Heart Rate Variability, Standards of Measurements, Physiological Interpretation, and Clinical Use. Circulation 1996; 93 (05) 1043-65.
  • 8 Guzzetti S, Signorini MG, Cogliati C, Mezzetti S, Porta A, Cerutti S, Malliani A. Deterministic chaos indices in heart rate variability of normal subjects and heart transplanted patients. Cardiovascular Research 1996; 31: 441-6.
  • 9 Packard NH, Crutchfield JP, Farmer JD, Shaw RS. Geometry from a time series. Phys. Rev. Lett 1980; 45: 712-6.
  • 10 Fraser AM, Swinney HL. Independent coordinates for strange attractors from mutual information. Phys. Rev A 1986; 33: 1134-40.
  • 11 Wolf A, Swift BJ, Swinney HL, Vastano JA. Determining Lyapunov exponents from time series. Physica 1985; 16D: 285-317.
  • 12 Kaplan JL, Yorke JA. Chaotic behaviour of multidimensional difference equations, in Lecture notes in mathematics, vol. 730. Springer; Berlin: 1978