NDLI: Model predictive control for type 1 diabetes based on personalized linear time-varying subject model consisting of both insulin and meal inputs: In Silico evaluation

Content Provider	IEEE Xplore Digital Library
Author	Qian Wang Jinyu Xie Molenaar, P. Ulbrecht, J.
Copyright Year	2015
Description	Author affiliation: Dept. of Biobehavioral Health & Med., Pennsylvania State Univ., University Park, PA, USA (Ulbrecht, J.) \|\| Human Dev., Pennsylvania State Univ., University Park, PA, USA (Molenaar, P.) \|\| Mech. Eng., Pennsylvania State Univ., University Park, PA, USA (Qian Wang) \|\| Dept. of Mech. & Nucl. Eng., Pennsylvania State Univ., University Park, PA, USA (Jinyu Xie)
Abstract	An essential component of insulin therapy for type 1 diabetes involves the prediction of blood glucose levels as function of exogenous perturbations such as insulin dose and meal intake. Based on the authors' previously developed patient-specific linear time-varying model for glucose dynamics consisting of both insulin and meal inputs, this paper develops a model predictive control for determining the optimal insulin delivery to regulate blood glucose in euglycemic range. Evaluation of the developed controller using the UVa/Padova simulator shows promising results. In addition, results in this paper show the importance of explicitly including the meal intake in the regression model, which was often lacking in the existing empirical subject-model based control.
Starting Page	5782
Ending Page	5787
File Size	222886
Page Count	6
File Format	PDF
e-ISBN	9781479986842
DOI	10.1109/ACC.2015.7172245
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-07-01
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	American Automatic Control Council(AACC)
Subject Keyword	Sugar Insulin Blood Predictive models Finite impulse response filters Diabetes Predictive control
Content Type	Text
Resource Type	Article

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