Medizinische Universität Graz Austria/Österreich - Forschungsportal - Medical University of Graz

Logo MUG-Forschungsportal

Gewählte Publikation:

SHR Neuro Krebs Kardio Lipid Stoffw Microb

Hovorka, R; Canonico, V; Chassin, LJ; Haueter, U; Massi-Benedetti, M; Orsini Federici, M; Pieber, TR; Schaller, HC; Schaupp, L; Vering, T; Wilinska, ME.
Nonlinear model predictive control of glucose concentration in subjects with type 1 diabetes.
PHYSIOL MEAS. 2004; 25(4): 905-920. Doi: 10.1088%2F0967-3334%2F25%2F4%2F010
Web of Science PubMed FullText FullText_MUG Google Scholar

 

Co-Autor*innen der Med Uni Graz
Pieber Thomas
Schaupp Lukas
Altmetrics:

Dimensions Citations:

Plum Analytics:

Scite (citation analytics):

Abstract:
A nonlinear model predictive controller has been developed to maintain normoglycemia in subjects with type 1 diabetes during fasting conditions such as during overnight fast. The controller employs a compartment model, which represents the glucoregulatory system and includes submodels representing absorption of subcutaneously administered short-acting insulin Lispro and gut absorption. The controller uses Bayesian parameter estimation to determine time-varying model parameters. Moving target trajectory facilitates slow, controlled normalization of elevated glucose levels and faster normalization of low glucose values. The predictive capabilities of the model have been evaluated using data from 15 clinical experiments in subjects with type 1 diabetes. The experiments employed intravenous glucose sampling (every 15 min) and subcutaneous infusion of insulin Lispro by insulin pump (modified also every 15 min). The model gave glucose predictions with a mean square error proportionally related to the prediction horizon with the value of 0.2 mmol L(-1) per 15 min. The assessment of clinical utility of model-based glucose predictions using Clarke error grid analysis gave 95% of values in zone A and the remaining 5% of values in zone B for glucose predictions up to 60 min (n = 1674). In conclusion, adaptive nonlinear model predictive control is promising for the control of glucose concentration during fasting conditions in subjects with type 1 diabetes.
Find related publications in this database (using NLM MeSH Indexing)
Blood Glucose - physiology
Diabetes Mellitus, Type 1 - physiopathology
Forecasting - physiopathology
Humans - physiopathology
Hypoglycemic Agents - pharmacokinetics
Insulin - analogs and derivatives
Models, Theoretical - analogs and derivatives

Find related publications in this database (Keywords)
nonlinear control
compartment modeling
Bayesian estimation
© Med Uni Graz Impressum