• DocumentCode
    2488983
  • Title

    Model identification of the neural control of the cardiovascular system using NARMAX models

  • Author

    Vallverdú, M. ; Korenberg, M.J. ; Caminal, P.

  • Author_Institution
    Inst. de Cibernetica, Univ. Politecnica de Cataluna, Barcelona, Spain
  • fYear
    1991
  • fDate
    23-26 Sep 1991
  • Firstpage
    585
  • Lastpage
    588
  • Abstract
    The neural control of the human cardiovascular system has been modeled using a NARMAX (non-linear autoregressive moving-average model with exogenous inputs) model, and compared with MA (moving-average) model and an ARMAX (autoregressive moving-average model with exogenous inputs) model. In these approaches, models are sought in the form of difference equations with unknown parameters to be estimated on the basis of input-output data. The input variable considered has been the carotid-sinus blood pressure and five output variables have been analyzed: heart rate control, peripheral resistance control, myocardial contractility control, venous tone control, and coronary resistance control. Results obtained show that NARMAX models present a better fit than the ARMAX models
  • Keywords
    biocontrol; cardiology; haemodynamics; identification; neurophysiology; physiology; ARMAX models; NARMAX models; cardiovascular system; carotid-sinus blood pressure; coronary resistance control; difference equations; exogenous inputs; heart rate control; input-output data; model identification; myocardial contractility control; neural control; nonlinear autoregressive moving-average model; peripheral resistance control; venous tone control; Blood pressure; Cardiology; Cardiovascular system; Difference equations; Humans; Immune system; Input variables; Nonlinear control systems; Parameter estimation; Pressure control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computers in Cardiology 1991, Proceedings.
  • Conference_Location
    Venice
  • Print_ISBN
    0-8186-2485-X
  • Type

    conf

  • DOI
    10.1109/CIC.1991.168978
  • Filename
    168978