Literature DB >> 22481809

Modular closed-loop control of diabetes.

S D Patek1, L Magni, E Dassau, C Karvetski, C Toffanin, G De Nicolao, S Del Favero, M Breton, C Dalla Man, E Renard, H Zisser, F J Doyle, C Cobelli, B P Kovatchev.   

Abstract

Modularity plays a key role in many engineering systems, allowing for plug-and-play integration of components, enhancing flexibility and adaptability, and facilitating standardization. In the control of diabetes, i.e., the so-called "artificial pancreas," modularity allows for the step-wise introduction of (and regulatory approval for) algorithmic components, starting with subsystems for assured patient safety and followed by higher layer components that serve to modify the patient's basal rate in real time. In this paper, we introduce a three-layer modular architecture for the control of diabetes, consisting in a sensor/pump interface module (IM), a continuous safety module (CSM), and a real-time control module (RTCM), which separates the functions of insulin recommendation (postmeal insulin for mitigating hyperglycemia) and safety (prevention of hypoglycemia). In addition, we provide details of instances of all three layers of the architecture: the APS© serving as the IM, the safety supervision module (SSM) serving as the CSM, and the range correction module (RCM) serving as the RTCM. We evaluate the performance of the integrated system via in silico preclinical trials, demonstrating 1) the ability of the SSM to reduce the incidence of hypoglycemia under nonideal operating conditions and 2) the ability of the RCM to reduce glycemic variability.

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Year:  2012        PMID: 22481809      PMCID: PMC4607512          DOI: 10.1109/TBME.2012.2192930

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


  48 in total

Review 1.  The intravenous route to blood glucose control.

Authors:  R S Parker; F J Doyle; N A Peppas
Journal:  IEEE Eng Med Biol Mag       Date:  2001 Jan-Feb

2.  Statistical tools to analyze continuous glucose monitor data.

Authors:  William Clarke; Boris Kovatchev
Journal:  Diabetes Technol Ther       Date:  2009-06       Impact factor: 6.118

3.  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

4.  A model-based algorithm for blood glucose control in type I diabetic patients.

Authors:  R S Parker; F J Doyle; N A Peppas
Journal:  IEEE Trans Biomed Eng       Date:  1999-02       Impact factor: 4.538

Review 5.  Hypoglycemia is the limiting factor in the management of diabetes.

Authors:  P E Cryer
Journal:  Diabetes Metab Res Rev       Date:  1999 Jan-Feb       Impact factor: 4.876

6.  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

7.  Feasibility of automating insulin delivery for the treatment of type 1 diabetes.

Authors:  Garry M Steil; Kerstin Rebrin; Christine Darwin; Farzam Hariri; Mohammed F Saad
Journal:  Diabetes       Date:  2006-12       Impact factor: 9.461

8.  Modular artificial beta-cell system: a prototype for clinical research.

Authors:  Eyal Dassau; Howard Zisser; Cesar C Palerm; Bruce A Buckingham; Lois Jovanovic; Francis J Doyle
Journal:  J Diabetes Sci Technol       Date:  2008-09

Review 9.  Banting Lecture. Hypoglycemia: the limiting factor in the management of IDDM.

Authors:  P E Cryer
Journal:  Diabetes       Date:  1994-11       Impact factor: 9.461

Review 10.  Artificial pancreas: past, present, future.

Authors:  Claudio Cobelli; Eric Renard; Boris Kovatchev
Journal:  Diabetes       Date:  2011-11       Impact factor: 9.461

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  43 in total

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Journal:  Med Biol Eng Comput       Date:  2015-12-30       Impact factor: 2.602

2.  Report from IPITA-TTS Opinion Leaders Meeting on the Future of β-Cell Replacement.

Authors:  Stephen T Bartlett; James F Markmann; Paul Johnson; Olle Korsgren; Bernhard J Hering; David Scharp; Thomas W H Kay; Jonathan Bromberg; Jon S Odorico; Gordon C Weir; Nancy Bridges; Raja Kandaswamy; Peter Stock; Peter Friend; Mitsukazu Gotoh; David K C Cooper; Chung-Gyu Park; Phillip OʼConnell; Cherie Stabler; Shinichi Matsumoto; Barbara Ludwig; Pratik Choudhary; Boris Kovatchev; Michael R Rickels; Megan Sykes; Kathryn Wood; Kristy Kraemer; Albert Hwa; Edward Stanley; Camillo Ricordi; Mark Zimmerman; Julia Greenstein; Eduard Montanya; Timo Otonkoski
Journal:  Transplantation       Date:  2016-02       Impact factor: 4.939

3.  In silico optimization of basal insulin infusion rate during exercise: implication for artificial pancreas.

Authors:  Michele Schiavon; Chiara Dalla Man; Yogish C Kudva; Ananda Basu; Claudio Cobelli
Journal:  J Diabetes Sci Technol       Date:  2013-11-01

4.  Physical activity measured by physical activity monitoring system correlates with glucose trends reconstructed from continuous glucose monitoring.

Authors:  Chiara Zecchin; Andrea Facchinetti; Giovanni Sparacino; Chiara Dalla Man; Chinmay Manohar; James A Levine; Ananda Basu; Yogish C Kudva; Claudio Cobelli
Journal:  Diabetes Technol Ther       Date:  2013-08-14       Impact factor: 6.118

5.  Model-based closed-loop glucose control in type 1 diabetes: the DiaCon experience.

Authors:  Signe Schmidt; Dimitri Boiroux; Anne Katrine Duun-Henriksen; Laurits Frøssing; Ole Skyggebjerg; John Bagterp Jørgensen; Niels Kjølstad Poulsen; Henrik Madsen; Sten Madsbad; Kirsten Nørgaard
Journal:  J Diabetes Sci Technol       Date:  2013-09-01

6.  Design and in silico evaluation of an intraperitoneal-subcutaneous (IP-SC) artificial pancreas.

Authors:  Justin J Lee; Eyal Dassau; Howard Zisser; Francis J Doyle
Journal:  Comput Chem Eng       Date:  2014-11-05       Impact factor: 3.845

7.  In silico evaluation of an artificial pancreas combining exogenous ultrafast-acting technosphere insulin with zone model predictive control.

Authors:  Justin J Lee; Eyal Dassau; Howard Zisser; Rebecca A Harvey; Lois Jovanovič; Francis J Doyle
Journal:  J Diabetes Sci Technol       Date:  2013-01-01

Review 8.  Hypo- and Hyperglycemic Alarms: Devices and Algorithms.

Authors:  Daniel Howsmon; B Wayne Bequette
Journal:  J Diabetes Sci Technol       Date:  2015-04-30

9.  Designing an artificial pancreas architecture: the AP@home experience.

Authors:  Giordano Lanzola; Chiara Toffanin; Federico Di Palma; Simone Del Favero; Lalo Magni; Riccardo Bellazzi
Journal:  Med Biol Eng Comput       Date:  2014-11-28       Impact factor: 2.602

10.  Successful At-Home Use of the Tandem Control-IQ Artificial Pancreas System in Young Children During a Randomized Controlled Trial.

Authors:  Gregory P Forlenza; Laya Ekhlaspour; Marc Breton; David M Maahs; R Paul Wadwa; Mark DeBoer; Laurel H Messer; Marissa Town; Jennifer Pinnata; Geoff Kruse; Bruce A Buckingham; Daniel Cherñavvsky
Journal:  Diabetes Technol Ther       Date:  2019-03-19       Impact factor: 6.118

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