A closed-loop artificial pancreas using model predictive control and a sliding meal size estimator.
The objective of this article is to present a comprehensive strategy for a closed-loop artificial pancreas. A meal detection and meal size estimation algorithm is developed for situations in which the subject forgets to provide a meal insulin bolus. A pharmacodynamic model of insulin action is used to provide insulin-on-board constraints to explicitly include the future effect of past and currently delivered insulin boluses. In addition, a supervisory pump shut-off feature is presented to avoid hypoglycemia. All of these components are used in conjunction with a feedback control algorithm using model predictive control (MPC). A model for MPC is developed based on a study of 20 subjects and is tested in a hypothetical clinical trial of 100 adolescent and 100 adult subjects using a Food and Drug Administration-approved diabetic subject simulator. In addition, a performance comparison of previously and newly proposed meal size estimation algorithms using 200 in silico subjects is presented. Using the new meal size estimation algorithm, the integrated artificial pancreas system yielded a daily mean glucose of 138 and 132 mg/dl for adolescents and adults, respectively, which is a substantial improvement over the MPC-only case, which yielded 159 and 145 mg/dl.
Lee
Hyunjin
H
Department of Chemical and Biological Engineering, Rensselaer Polytechnic Institute, Troy, New York, USA.
Buckingham
Bruce A
BA
Wilson
Darrell M
DM
Bequette
B Wayne
BW
D000293:Adolescent; D000328:Adult; D000465:Algorithms; D001786:Blood Glucose / Q000187:drug effects* / Q000378:metabolism; D015190:Blood Glucose Self-Monitoring / Q000295:instrumentation*; D003198:Computer Simulation; D003920:Diabetes Mellitus / Q000097:blood / Q000175:diagnosis / Q000188:drug therapy*; D003936:Diagnosis, Computer-Assisted; D004040:Dietary Carbohydrates / Q000008:administration & dosage / Q000378:metabolism*; D004360:Drug Therapy, Computer-Assisted; D006442:Glycated Hemoglobin / Q000378:metabolism; D006801:Humans; D007003:Hypoglycemia / Q000139:chemically induced / Q000517:prevention & control; D007004:Hypoglycemic Agents / Q000008:administration & dosage* / Q000009:adverse effects / Q000493:pharmacokinetics; D007328:Insulin / Q000008:administration & dosage* / Q000009:adverse effects / Q000493:pharmacokinetics; D007332:Insulin Infusion Systems; D008954:Models, Biological; D015233:Models, Statistical; D019397:Pancreas, Artificial; D011237:Predictive Value of Tests; D018511:Systems Integration; D016896:Treatment Outcome
D001786:Blood Glucose; D004040:Dietary Carbohydrates; D006442:Glycated Hemoglobin; D007004:Hypoglycemic Agents; D007328:Insulin; C517652:hemoglobin A1c protein, human