• DocumentCode
    830602
  • Title

    Modeling and parameter identification of the human respiratory system

  • Author

    Wiberg, D.M. ; Bellville, J.W. ; Brovko, O. ; Maine, R. ; Tai, T.C.

  • Author_Institution
    University of California, Los Angeles, CA, USA
  • Volume
    24
  • Issue
    5
  • fYear
    1979
  • fDate
    10/1/1979 12:00:00 AM
  • Firstpage
    716
  • Lastpage
    720
  • Abstract
    The human respiratory response to breathing an excess of carbon dioxide gas is modeled on physiological grounds as an almost linear second-order system. The parameters corresponding to the gains, time constants, threshold, and noise powers are identified by both least squares and maximum likelihood methods. The purpose is both to find the site of action of drugs and to gain understanding of this part of the respiratory control system. It is concluded that the maximum likelihood method is necessary in cases where the noise is not white and when unbiased estimates of the gains and variances are essential, such as in drug studies and in some physiological modeling.
  • Keywords
    Delay systems; Least-squares estimation; Parameter identification; Respiratory systems; maximum-likelihood (ML) estimation; Carbon dioxide; Control systems; Drugs; Humans; Least squares methods; Maximum likelihood estimation; Parameter estimation; Power system modeling; Respiratory system; White noise;
  • fLanguage
    English
  • Journal_Title
    Automatic Control, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9286
  • Type

    jour

  • DOI
    10.1109/TAC.1979.1102156
  • Filename
    1102156