Skip to main content

Are R-R-Intervals Data Appropriate to Study the Dynamics of Heart?

  • Conference paper

Abstract

We consider the problem of recovering the implied dynamical system, which describes the dynamics of heart, from a time series of RR intervals. The main conclusion is that on small time scales such recovery fails, and on large time scales the correlation integral behaves like that for noisy system. Consequently, it seems that recovery of underlying dynamical system and measuring its parameters (dimension, Lyapunov exponents etc.) from these data is hardly possible and more adequate is application of statistical techniques.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Abarbanel H.D.I., Brown R., Sidorowich J.J., Tsimring L.S. (1993): The analysis of observed chaotic data in physical systems. Rev. Mod. Phys. 65 1331

    Article  MathSciNet  ADS  Google Scholar 

  • Anishchenko V.S., Postnov D.E., Saparin P.I., Safonova M.A. (1992): Diagnostics of self-oscillating systems by methods of nonlinear dynamics. Applied Nonlinear Dynamics 1, 10

    Google Scholar 

  • Babloyantz A., Destexhe A. (1988): Is the normal heart a periodic oscillator? Biol. Cybernetics 58, 203

    Article  MathSciNet  Google Scholar 

  • Chaos, 5, (1995): 1–215 present some recent results in processing of physiological time series

    Google Scholar 

  • Eckmann J.P., Ruelle D. (1985): Ergodic theory of chaos and strange attractors, Rev. Mod. Phys. 57 617

    Article  MathSciNet  ADS  Google Scholar 

  • Isliker H., Kurths J. (1993): A test for stationarity: finding parts in time series apt for correlation dimension estimates. Int. J. Bifurc. Chaos 3 1573

    Article  MATH  Google Scholar 

  • Ivanov P.Ch., Rosenblum M.G., Peng C.-K., Mietus J., Havlin S., Stanley H.E., Goldberger A.L. (1996): Scaling behaviour of heartbeat intervals obtained by wavelet-based time series analysis. Nature 383 323

    Article  ADS  Google Scholar 

  • Lefebvre J.H., Goodings D.A., Kamath M.V., Fallen E.L. (1993): Predictability of normal heart rhythms and deterministic chaos. Chaos 3 267

    Article  ADS  Google Scholar 

  • Mayer-Kress G. (1994): Localized measures for non-stationary time-series of physiological data. Integrative Psychological and Behavioral Science 29 203

    Article  Google Scholar 

  • Malinetskii G.G., Potapov A.B., Rakhmanov A.L. (1993): Limitations of delay reconstruction for chaotic dynamical systems. Phys. Rev. E 48 904

    Article  ADS  Google Scholar 

  • Packard N.H., Crutchfield J.P., Farmer J.D., Shaw R.S. (1980): Geometry from a time series. Phys. Rev. Lett. 45 712

    Article  ADS  Google Scholar 

  • Pompe B. (1993): Measuring statistical dependencies in a time series. J. Stat. Phys. 73 587

    Article  MathSciNet  ADS  MATH  Google Scholar 

  • Sauer T. (1995): Interspike interval embedding of chaotic signals. Chaos 5, 127–132

    Article  ADS  Google Scholar 

  • Sauer T., Yorke J.A., Casdagli M. (1991): Embedology. J. Stat. Phys. 65 579

    Article  MathSciNet  ADS  MATH  Google Scholar 

  • Schreiber T. (1993): Determination of the noise level of chaotic time series. Phys. Rev. E 48 R13

    Article  MathSciNet  ADS  Google Scholar 

  • Takens F. (1981): Detecting strange attractors in turbulence, In Dynamical systems and turbulence. Lecture Notes in Mathematics Vol. 898. Springer, Berlin, Heidelberg, p. 336

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 1998 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Potapov, A. (1998). Are R-R-Intervals Data Appropriate to Study the Dynamics of Heart?. In: Kantz, H., Kurths, J., Mayer-Kress, G. (eds) Nonlinear Analysis of Physiological Data. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-71949-3_8

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-71949-3_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-71951-6

  • Online ISBN: 978-3-642-71949-3

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics