Literature DB >> 16916082

Model-based blood glucose control for Type 1 diabetes via parametric programming.

Pinky Dua1, Francis J Doyle, Efstratios N Pistikopoulos.   

Abstract

An advanced model-based control technique for regulating the blood glucose for patients with Type 1 diabetes is presented. The optimal insulin delivery rate is obtained off-line as an explicit function of the current blood glucose concentration of the patient by using novel parametric programming algorithms, developed at Imperial College London. The implementation of the optimal insulin delivery rate, therefore, requires simple function evaluation and minimal on-line computations. The proposed framework also addresses the uncertainty in the model due to interpatient and intrapatient variability by identifying the model parameters which ensure that a feasible control law can be obtained. The developments reported in this paper are expected to simplify the insulin delivery mechanism, thereby enhancing the quality of life of the patient.

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Year:  2006        PMID: 16916082     DOI: 10.1109/TBME.2006.878075

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


  23 in total

1.  Development of a multi-parametric model predictive control algorithm for insulin delivery in type 1 diabetes mellitus using clinical parameters.

Authors:  M W Percival; Y Wang; B Grosman; E Dassau; H Zisser; L Jovanovič; F J Doyle
Journal:  J Process Control       Date:  2011-03-01       Impact factor: 3.666

2.  A switching control strategy for the attenuation of blood glucose disturbances.

Authors:  Mihalis G Markakis; Georgios D Mitsis; George P Papavassilopoulos; Petros A Ioannou; Vasilis Z Marmarelis
Journal:  Optim Control Appl Methods       Date:  2011       Impact factor: 2.530

Review 3.  Toward closing the loop: an update on insulin pumps and continuous glucose monitoring systems.

Authors:  Tandy Aye; Jen Block; Bruce Buckingham
Journal:  Endocrinol Metab Clin North Am       Date:  2010-09       Impact factor: 4.741

4.  Control to range for diabetes: functionality and modular architecture.

Authors:  Boris Kovatchev; Stephen Patek; Eyal Dassau; Francis J Doyle; Lalo Magni; Giuseppe De Nicolao; Claudio Cobelli
Journal:  J Diabetes Sci Technol       Date:  2009-09-01

5.  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

Review 6.  A Review of Emerging Technologies for the Management of Diabetes Mellitus.

Authors:  Konstantia Zarkogianni; Eleni Litsa; Konstantinos Mitsis; Po-Yen Wu; Chanchala D Kaddi; Chih-Wen Cheng; May D Wang; Konstantina S Nikita
Journal:  IEEE Trans Biomed Eng       Date:  2015-08-19       Impact factor: 4.538

7.  Artificial pancreas: model predictive control design from clinical experience.

Authors:  Chiara Toffanin; Mirko Messori; Federico Di Palma; Giuseppe De Nicolao; Claudio Cobelli; Lalo Magni
Journal:  J Diabetes Sci Technol       Date:  2013-11-01

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.  Multi-objective blood glucose control for type 1 diabetes.

Authors:  Pinky Dua; Francis J Doyle; Efstratios N Pistikopoulos
Journal:  Med Biol Eng Comput       Date:  2009-02-13       Impact factor: 2.602

10.  Model predictive control of type 1 diabetes: an in silico trial.

Authors:  Lalo Magni; Davide M Raimondo; Luca Bossi; Chiara Dalla Man; Giuseppe De Nicolao; Boris Kovatchev; Claudio Cobelli
Journal:  J Diabetes Sci Technol       Date:  2007-11
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