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
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