Type I diabetes: modeling, identification and non-linear model predictive control

Author

Schlotthauer, G. ; Nicolini, G.A. ; Gamero, L.G. ; Torres, M.E.

Author_Institution

Fac. de Ingenieria, Univ. Nacional de Entre Rios, Parana, Argentina

Volume

1

fYear

2002

fDate

2002

Firstpage

226

Abstract

Patients with diabetic type I nearly always need a therapy with insulin. The most desirable treatment would be to mimic the operation of a normal pancreas. In this work we model a patient affected with this pathology, identify it with a neural network, and evaluate a control strategy known as nonlinear model predictive control as an approach to command an insulin pump using the subcutaneous route.

Keywords

biocontrol; diseases; multilayer perceptrons; nonlinear control systems; parameter estimation; predictive control; Insulin-Dependent Diabetes Mellitus; chronic metabolic disorder; identification; insulin pump; insulin therapy; multilayer perceptions; neural network; nonlinear model predictive control; normal pancreas operation; subcutaneous route; type I diabetes; Absorption; Blood; Diabetes; Insulin; Neural networks; Pancreas; Plasmas; Predictive control; Predictive models; Sugar;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology, 2002. 24th Annual Conference and the Annual Fall Meeting of the Biomedical Engineering Society EMBS/BMES Conference, 2002. Proceedings of the Second Joint

ISSN

1094-687X

Print_ISBN

0-7803-7612-9

Type

conf

DOI

10.1109/IEMBS.2002.1134465

Filename

1134465