Literature DB >> 31931478

Blood glucose concentration control for type 1 diabetic patients: a multiple-model strategy.

Yazdan Batmani1, Shadi Khodakaramzadeh2.   

Abstract

In this study, a multiple-model strategy is evaluated as an alternative closed-loop method for subcutaneous insulin delivery in type 1 diabetes. Non-linearities of the glucose-insulin regulatory system are considered by modelling the system around five different operating points. After conducting some identification experiments in the UVA/Padova metabolic simulator (accepted simulator by the US Food and Drug Administration (FDA)), five transfer functions are obtained for these operating points. Paying attention to some physiological facts, the control objectives such as the required settling time and permissible bounds of overshoots and undershoots are determined for any transfer functions. Then, five PID controllers are tuned to achieve these objectives and a bank of controllers is constructed. To cope with difficulties of the presence of delays in subcutaneous blood glucose (BG) measuring and in administration of insulin, a glucose-dependent setpoint is considered as the desired trajectory for the BG concentration. The performance of the obtained closed-loop glucose-insulin regulatory system is investigated on the in silico adult cohort of the UVA/Padova metabolic simulator. The obtained results show that the proposed multiple-model strategy leads to a closed-loop mechanism with limited hyperglycemia and no severe hypoglycemia.

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Year:  2020        PMID: 31931478      PMCID: PMC8687239          DOI: 10.1049/iet-syb.2018.5049

Source DB:  PubMed          Journal:  IET Syst Biol        ISSN: 1751-8849            Impact factor:   1.615


  18 in total

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Journal:  Artif Organs       Date:  2005-08       Impact factor: 3.094

3.  Closed-loop control of artificial pancreatic Beta -cell in type 1 diabetes mellitus using model predictive iterative learning control.

Authors:  Youqing Wang; Eyal Dassau; Francis J Doyle
Journal:  IEEE Trans Biomed Eng       Date:  2009-06-12       Impact factor: 4.538

4.  First use of model predictive control in outpatient wearable artificial pancreas.

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Journal:  Diabetes Care       Date:  2014       Impact factor: 19.112

5.  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

6.  Mathematical investigation of diabetically impaired ultradian oscillations in the glucose-insulin regulation.

Authors:  B Huard; A Bridgewater; M Angelova
Journal:  J Theor Biol       Date:  2017-01-24       Impact factor: 2.691

7.  Personalized glucose-insulin model based on signal analysis.

Authors:  Simon L Goede; Bastiaan E de Galan; Melvin Khee Shing Leow
Journal:  J Theor Biol       Date:  2016-12-28       Impact factor: 2.691

8.  On-line adaptive algorithm with glucose prediction capacity for subcutaneous closed loop control of glucose: evaluation under fasting conditions in patients with Type 1 diabetes.

Authors:  H C Schaller; L Schaupp; M Bodenlenz; M E Wilinska; L J Chassin; P Wach; T Vering; R Hovorka; T R Pieber
Journal:  Diabet Med       Date:  2006-01       Impact factor: 4.359

9.  Switched LPV Glucose Control in Type 1 Diabetes.

Authors:  Patricio H Colmegna; Ricardo S Sanchez-Pena; Ravi Gondhalekar; Eyal Dassau; Frank J Doyle
Journal:  IEEE Trans Biomed Eng       Date:  2015-10-05       Impact factor: 4.538

10.  Blood glucose concentration control for type 1 diabetic patients: a non-linear suboptimal approach.

Authors:  Yazdan Batmani
Journal:  IET Syst Biol       Date:  2017-08       Impact factor: 1.615

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2.  Sliding mode control for a fractional-order non-linear glucose-insulin system.

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Journal:  IET Syst Biol       Date:  2020-10       Impact factor: 1.615

  2 in total

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