Control-relevant models for glucose control using a priori patient characteristics

IEEE Transactions on Biomedical Engineering

Volumn 59, Issue 7, 2012, Pages 1839-1849

  Van Heusden, Klaske ^a   Dassau, Eyal ^b,c   Zisser, Howard C ^b,c   Seborg, Dale E ^b   Doyle III, Francis J ^b,c  

^a UNIVERSITY OF BRITISH COLUMBIA   (Canada)

^b University of California   (United States)

^c SANSUM DIABETES RESEARCH INSTITUTE   (United States)

Author keywords

Artificial pancreas; control relevant modeling; model predictive control (MPC); type 1 diabetes mellitus (T1DM)

Indexed keywords

ARTIFICIAL PANCREAS; CLOSED-LOOP; CONTROL APPROACH; GLUCOSE CONTROL; GLUCOSE LEVEL; IN-SILICO; PREDICTION ERRORS; TYPE 1 DIABETES MELLITUS; ZONE MODEL;

ALGORITHMS; ARTIFICIAL ORGANS; GLUCOSE; INSULIN; MODEL PREDICTIVE CONTROL; PREDICTIVE CONTROL SYSTEMS;

CONTROLLERS;

GLUCOSE;

ALGORITHM; ARTICLE; BLOOD GLUCOSE MONITORING; CARBOHYDRATE INTAKE; COMPUTER MODEL; CONTROLLED STUDY; GLUCOSE BLOOD LEVEL; HYPOGLYCEMIA; INSULIN DEPENDENT DIABETES MELLITUS; MEAL; POSTPRANDIAL STATE; PREDICTIVE VALUE;

ALGORITHMS; BLOOD GLUCOSE; BLOOD GLUCOSE SELF-MONITORING; COMPUTER SIMULATION; DIABETES MELLITUS, TYPE 1; DIET; HUMANS; HYPOGLYCEMIA; HYPOGLYCEMIC AGENTS; INSULIN; MODELS, BIOLOGICAL; MODELS, STATISTICAL; PANCREAS, ARTIFICIAL;

EID: 84862746976     PISSN: 00189294     EISSN: 15582531     Source Type: Journal    
DOI: 10.1109/TBME.2011.2176939     Document Type: Article

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