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Fuzzy Control pp 346-353 | Cite as

Fuzzy Modelling of Heart Rate Variability

  • J. Bíla
  • P. Zítek
  • P. Kuchar
Conference paper
Part of the Advances in Soft Computing book series (AINSC, volume 6)

Abstract

Heart rate, actual blood pressure, blood flow rate and other cardiovascular parameters fluctuate in their values even in quite steady physiological state. Unlike the earlier conception has been proved that these fluctuations are to be viewed as specific symptoms of heart performance control. Based on this idea a model of brain interventions into control strategy of heart is presented (consisted of fuzzy blocks, integration blocks and delays) performing “beat by beat” control principle and resulting in Heart rate variability signals with features of deterministic chaos. The model is implemented in MatLab/Simulink environment.

Keywords

Heart Rate Variability Stroke Volume Fuzzy Control Blood Flow Rate Heart Action 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Sramek, B.B., Valenta, J., Klimes, F: Biomechanics of the Cardiovascular System. Czech Technical University Press, Prague, CR (1995)Google Scholar
  2. 2.
    Trojan, S. et al.: Physiology (in Czech). Grada, Prague, CR (1996)Google Scholar
  3. 3.
    van Wijk, R. and van Brieving, P.: Biomedical Modelling and Simulation on a PC. Springer-Verlag, New York (1993)CrossRefGoogle Scholar
  4. 4.
    Malliani, A., Pagani, M., Lombardi, F., Cerrutti, S.: Cardiovascular Neural Regulation Explored in the Frequency Domain. Circulation, Vol. 84, No. 2 (1991) 482–485CrossRefGoogle Scholar
  5. 5.
    Akselrod, S., Eliash, S., Oz, O., Cohen, S.: Hemodynamics regulation in SHR: Investigation in Spectral Analysis. American Physiological Society (1987) 176–182Google Scholar
  6. 6.
    Appel, M.L., Berger, R.D., Saul, S.J., Smith, J.M.: Beat to Beat Variability in Cardiovascular Variables: Noise or Music? JACC 14 (1995) 1139–1143CrossRefGoogle Scholar
  7. 7.
    Teodorescu, H.N.L., Belous, V., Mlynek, D., Forte, M.W.: Creativity Models and Chaos in Networks of Fuzzy Systems. In: Gonzáles,E.L. (ed.): Proc. of Int. Conf. on Intelligent Technologies in Human-Related Sciences-ITHURS 96, Leon Spain (1996) 317–324Google Scholar
  8. 8.
    Teodorescu, H.N.L., Brezulianu, A., Yamakawa, T.: Temporary and permanent Self-Organization Phenomena in Chaotic Fuzzy Systems Networks (CFNS). In: Gonzâles,E.L. (ed.): Proc. of Int. Conf. on Intelligent Technologies in Human-Related Sciences-ITHURS 96, Leon Spain (1996) 283–288Google Scholar
  9. 9.
    Malik, M.: Heart Rate Variability. Standarts of Measurement, Physiological Interpretation and Clinical Use. Special Report of Task Force of the European Society of Cardiology and North American Society of Pacing and Electrophysiology. American Heart Association, Inc. (1996)Google Scholar
  10. 10.
    Zítek, P., BIla, J. and Kuchar, P.: Blood Circulation Control Model based on Heart Rate Variability Syndrome. In: Stefan, J. (ed.), Proc. of 32 Spring Int. Conf. On Modelling and Simulation of Systems — MOSIS 98, C.R. (1998) 297–302Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • J. Bíla
    • 1
  • P. Zítek
    • 1
  • P. Kuchar
    • 1
  1. 1.Institute of Instrumentation and Control technology, Faculty of Mechanical EngineeringThe Czech Technical University in PraguePrague 6Czech Republic

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