Literature DB >> 16761826

Run-to-run control of blood glucose concentrations for people with Type 1 diabetes mellitus.

Camelia Owens1, Howard Zisser, Lois Jovanovic, Bala Srinivasan, Dominique Bonvin, Francis J Doyle.   

Abstract

Run-to-run control has been applied to several traditional batch processes in the chemical industry. The 24-h cycle of eating meals, measuring blood glucose concentrations, and delivering the correct insulin bolus, with the goal of achieving the optimal blood glucose profile, can be viewed in the same spirit as traditional batch processes such as emulsion polymerization. In this paper, we aim to exploit the "repetitive" nature of the insulin therapy of people with Type 1 diabetes. A run-to-run algorithm is used on a virtual diabetic patient model to control blood glucose concentrations. The insulin input is parameterized into the timing and amount of the dose while the glucose output is parameterized into the maximum and minimum glucose concentrations. Robustness of the algorithm to variations in the meal amount, meal timing, and insulin sensitivity parameter is addressed. In general, the algorithm is able to converge when the meal timing is varied within +/- 40 min. If the meal size is underestimated by approximately 10 grams (g), the algorithm is able to converge within a reasonable time frame for breakfast, lunch, and dinner. If the meal size is overestimated by 20-25 g, the algorithm is able to converge. When random variations in the meal timing and the meal amount are introduced, the variation on the output variables, Gmax and Gmin, scales according to the amount of variation allowed. Along with this, the insulin sensitivity of the virtual patient model is varied. The algorithm is robust for differences in insulin sensitivity less than +/- 50% of the nominal value.

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Year:  2006        PMID: 16761826     DOI: 10.1109/TBME.2006.872818

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  21 in total

1.  Anticipating the next meal using meal behavioral profiles: a hybrid model-based stochastic predictive control algorithm for T1DM.

Authors:  C S Hughes; S D Patek; M Breton; B P Kovatchev
Journal:  Comput Methods Programs Biomed       Date:  2010-06-19       Impact factor: 5.428

2.  Closed-loop artificial pancreas using subcutaneous glucose sensing and insulin delivery and a model predictive control algorithm: preliminary studies in Padova and Montpellier.

Authors:  Daniela Bruttomesso; Anne Farret; Silvana Costa; Maria Cristina Marescotti; Monica Vettore; Angelo Avogaro; Antonio Tiengo; Chiara Dalla Man; Jerome Place; Andrea Facchinetti; Stefania Guerra; Lalo Magni; Giuseppe De Nicolao; Claudio Cobelli; Eric Renard; Alberto Maran
Journal:  J Diabetes Sci Technol       Date:  2009-09-01

3.  Run-to-Run Optimization Control Within Exact Inverse Framework for Scan Tracking.

Authors:  Ivan L Yeoh; Per G Reinhall; Martin C Berg; Howard J Chizeck; Eric J Seibel
Journal:  J Dyn Syst Meas Control       Date:  2017-06-05       Impact factor: 1.372

4.  Parameters affecting postprandial blood glucose: effects of blood glucose measurement errors.

Authors:  Theodor Koschinsky; Sascha Heckermann; Lutz Heinemann
Journal:  J Diabetes Sci Technol       Date:  2008-01

Review 5.  Advances in management of type 1 diabetes mellitus.

Authors:  Ravindranath Aathira; Vandana Jain
Journal:  World J Diabetes       Date:  2014-10-15

6.  The UVA/Padova Type 1 Diabetes Simulator Goes From Single Meal to Single Day.

Authors:  Roberto Visentin; Enrique Campos-Náñez; Michele Schiavon; Dayu Lv; Martina Vettoretti; Marc Breton; Boris P Kovatchev; Chiara Dalla Man; Claudio Cobelli
Journal:  J Diabetes Sci Technol       Date:  2018-02-16

7.  Multinational study of subcutaneous model-predictive closed-loop control in type 1 diabetes mellitus: summary of the results.

Authors:  Boris Kovatchev; Claudio Cobelli; Eric Renard; Stacey Anderson; Marc Breton; Stephen Patek; William Clarke; Daniela Bruttomesso; Alberto Maran; Silvana Costa; Angelo Avogaro; Chiara Dalla Man; Andrea Facchinetti; Lalo Magni; Giuseppe De Nicolao; Jerome Place; Anne Farret
Journal:  J Diabetes Sci Technol       Date:  2010-11-01

8.  Run-to-run tuning of model predictive control for type 1 diabetes subjects: in silico trial.

Authors:  Lalo Magni; Marco Forgione; Chiara Toffanin; Chiara Dalla Man; Boris Kovatchev; Giuseppe De Nicolao; Claudio Cobelli
Journal:  J Diabetes Sci Technol       Date:  2009-09-01

9.  A Run-to-Run Control Strategy to Adjust Basal Insulin Infusion Rates in Type 1 Diabetes.

Authors:  Cesar C Palerm; Howard Zisser; Lois Jovanovič; Francis J Doyle
Journal:  J Process Control       Date:  2008       Impact factor: 3.666

10.  Telemedical artificial pancreas: PARIS (Pancreas Artificial Telemedico Inteligente) research project.

Authors:  Alberto de Leiva; María Elena Hernando; M Rigla; I Capel; E Brugués; B Pons; L Erdozain; A Prados; R Corcoy; E J Gómez; G García-Sáez; I Martínez-Sarriegui; A Rodríguez-Herrero; C Pérez-Gandía; F del Pozo
Journal:  Diabetes Care       Date:  2009-11       Impact factor: 19.112

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