Name
Title | ||
|---|---|---|
Model-based personalization scheme of an artificial pancreas for Type 1 diabetes applications |
Abstract | ||
|---|---|---|
Automated controllers designed to regulate blood glucose concentrations in people with Type 1 diabetes mellitus (T1DM) must avoid hypoglycemia (blood glucose <;70 mg/dl) while minimizing hyperglycemia (>180 mg/dl), a challenging task. In this paper, a model-based control design approach with a personalized scheme based on readily available clinical factors is applied to a linearized control-relevant model of subject insulin-glucose response profiles. An insulin feedback strategy is included with specific personalization settings and variations in a tuning parameter, τc. The control strategy is challenged by an unannounced meal disturbance with 50 g carbohydrate content. A set of metrics are introduced as a method of evaluating the performance of different controllers. In-silico simulations of ten subjects in the Food and Drug Administration accepted Universities of Virginia and Padova metabolic simulator indicate that the personalization strategy with a τc setting of 270 minutes gives very good controller performance. Post-prandial glucose concentration peaks of 183 mg/dl were achieved with 97% of the total simulation time spent within a safe glycemic zone (70-180 mg/dl), without hypoglycemic incidents and without requiring a time-consuming model identification process. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/ACC.2013.6580276 | ACC |
Keywords | Field | DocType |
personalized scheme,time consuming model identification process,hypoglycemia,hypoglycemic incidents,medical control systems,linearized control relevant model,closed-loop,diseases,safe glycemic zone,metabolic simulator,insulin feedback,artificial pancreas,control system synthesis,model based control design,hyperglycemia,tuning parameter,type 1 diabetes mellitus,internal model control (imc),automated controllers,control strategy,proportional-integral-derivative (pid) control,personalization strategy,unannounced meal disturbance,insulin glucose response profiles,insulin feedback strategy,control-relevant modeling,personalization settings,blood glucose concentrations,type 1 diabetes applications,type 1 diabetes mellitus (t1dm),ap,three-term control,post prandial glucose concentration,model based personalization scheme,insulin,measurement,noise,diabetes,tuning | Artificial pancreas,Control theory,Computer science,Control theory,Control engineering,System identification,Type 1 diabetes,Insulin,Hypoglycemia,Glycemic,Personalization | Conference |
ISSN | ISBN | Citations |
0743-1619 | 978-1-4799-0177-7 | 3 |
PageRank | References | Authors |
0.45 | 2 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Joon Bok Lee | 1 | 3 | 0.45 |
| Eyal Dassau | 2 | 91 | 13.68 |
| Dale E. Seborg | 3 | 56 | 18.89 |
| Francis J Doyle | 4 | 244 | 45.10 |