• DocumentCode
    2813349
  • Title

    The Bergman´s insulin-glucose regulation model: DNN-state observer

  • Author

    Garcia, Alejandro ; Cabrera, Agustin I. ; Poznyak, Alexander ; Poznyak, Tatiana

  • Author_Institution
    Unidad Profesional Interdisciplinaria de Biotecnologia, Mexico
  • Volume
    2
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    1421
  • Abstract
    The nonlinear Bergman regulation model of insulin-glucose in plasma is analyzed using modern observability theory. The observability conditions are derived. The glucose concentration measurements in plasma or any its combinations with the other components are shown to provide the observability property, that is, they contain the complete information about the considered state space dynamic model. Because this model has several a priori unknown parameters and the measurable data may have noises, the dynamic neuro state observer is suggested to obtain immeasurable state estimates. Such an approach brings significant advantages with respect to the “insulin doses decision”, traditionally used in the normal insulin infusion pumps: it presents the opportunity to avoid any active patient actions, the numerical simulations illustrate the effectiveness of the suggested approach
  • Keywords
    biocontrol; blood; drug delivery systems; learning (artificial intelligence); neural nets; observability; observers; physiological models; state-space methods; DNN-state observer; dynamic neuro state observer; glucose concentration measurements; immeasurable state estimates; insulin doses decision; insulin infusion pumps; insulin-glucose in plasma; learning process; nonlinear Bergman regulation model; numerical simulations; observability theory; state space dynamic model; Insulin; Noise measurement; Numerical simulation; Observability; Observers; Plasma measurements; Plasma properties; State estimation; State-space methods; Sugar;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2000. Proceedings of the 22nd Annual International Conference of the IEEE
  • Conference_Location
    Chicago, IL
  • ISSN
    1094-687X
  • Print_ISBN
    0-7803-6465-1
  • Type

    conf

  • DOI
    10.1109/IEMBS.2000.898007
  • Filename
    898007