DocumentCode
728596
Title
The contribution of glucagon in an Artificial Pancreas for people with type 1 diabetes
Author
Batora, Vladimir ; Tarnik, Marian ; Murgas, Jan ; Schmidt, Signe ; Norgaard, Kirsten ; Poulsen, Niels Kjostad ; Madsen, Henrik ; Boiroux, Dimitri ; Jorgensen, John Bagterp
Author_Institution
Fac. of Electr. Eng. & Inf. Technol., Slovak Univ. of Technol., Bratislava, Slovakia
fYear
2015
fDate
1-3 July 2015
Firstpage
5097
Lastpage
5102
Abstract
The risk of hypoglycemia is one of the main concerns in treatment of type 1 diabetes (T1D). In this paper we present a head-to-head comparison of a currently used insulin-only controller and a prospective bihormonal controller for blood glucose in people with T1D. The bihormonal strategy uses insulin to treat hyperglycemia as well as glucagon to ensure fast recovery from hypoglycemic episodes. Two separate model predictive controllers (MPC) based on patient-specific models handle insulin and glucagon infusion. In addition, the control algorithm consists of a Kalman filter and a meal time insulin bolus calculator. The feedback is obtained from a continuous glucose monitor (CGM). We implement a bihormonal simulation model with time-varying parameters available for 3 subjects to compare the strategies. We consider a protocol with 3 events - a correct mealtime insulin bolus, a missed bolus and a bolus overestimated by 60%. During normal operation both strategies provide similar results. The contribution of glucagon becomes evident after administration of the overestimated insulin bolus. In a 10h period following an overbolused meal, the bihormonal strategy reduces time spent in hypoglycemia in the most severe case by almost 15% (1.5h), outperforming the insulin-only control. Therefore, glucagon contributes to the safety of an Artificial Pancreas.
Keywords
Kalman filters; artificial organs; blood; feedback; medical control systems; patient treatment; predictive control; sugar; time-varying systems; CGM; Kalman filter; MPC; T1D; Type 1 diabetes treatment; artificial pancreas; bihormonal controller; bihormonal simulation model; blood glucose; continuous glucose monitor; feedback; glucagon; hypoglycemia risk; insulin-only controller; meal time insulin bolus calculator; model predictive controller; time-varying parameter; Absorption; Control systems; Diabetes; Insulin; Plasmas; Predictive models; Sugar;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference (ACC), 2015
Conference_Location
Chicago, IL
Print_ISBN
978-1-4799-8685-9
Type
conf
DOI
10.1109/ACC.2015.7172134
Filename
7172134
Link To Document