Literature DB >> 20936056

Diabetes: Models, Signals, and Control.

Claudio Cobelli1, Chiara Dalla Man, Giovanni Sparacino, Lalo Magni, Giuseppe De Nicolao, Boris P Kovatchev.   

Abstract

The control of diabetes is an interdisciplinary endeavor, which includes a significant biomedical engineering component, with traditions of success beginning in the early 1960s. It began with modeling of the insulin-glucose system, and progressed to large-scale in silico experiments, and automated closed-loop control (artificial pancreas). Here, we follow these engineering efforts through the last, almost 50 years. We begin with the now classic minimal modeling approach and discuss a number of subsequent models, which have recently resulted in the first in silico simulation model accepted as substitute to animal trials in the quest for optimal diabetes control. We then review metabolic monitoring, with a particular emphasis on the new continuous glucose sensors, on the analyses of their time-series signals, and on the opportunities that they present for automation of diabetes control. Finally, we review control strategies that have been successfully employed in vivo or in silico, presenting a promise for the development of a future artificial pancreas and, in particular, discuss a modular architecture for building closed-loop control systems, including insulin delivery and patient safety supervision layers. We conclude with a brief discussion of the unique interactions between human physiology, behavioral events, engineering modeling and control relevant to diabetes.

Entities:  

Year:  2009        PMID: 20936056      PMCID: PMC2951686          DOI: 10.1109/RBME.2009.2036073

Source DB:  PubMed          Journal:  IEEE Rev Biomed Eng        ISSN: 1937-3333


  266 in total

1.  Approximate entropy as a measure of system complexity.

Authors:  S M Pincus
Journal:  Proc Natl Acad Sci U S A       Date:  1991-03-15       Impact factor: 11.205

2.  Bayesian two-compartment and classic single-compartment minimal models: comparison on insulin modified IVGTT and effect of experiment reduction.

Authors:  Tiziano Callegari; Andrea Caumo; Claudio Cobelli
Journal:  IEEE Trans Biomed Eng       Date:  2003-12       Impact factor: 4.538

3.  Minimal model estimation of glucose absorption and insulin sensitivity from oral test: validation with a tracer method.

Authors:  Chiara Dalla Man; Andrea Caumo; Rita Basu; Robert Rizza; Gianna Toffolo; Claudio Cobelli
Journal:  Am J Physiol Endocrinol Metab       Date:  2004-05-11       Impact factor: 4.310

Review 4.  Continuous glucose monitoring: roadmap for 21st century diabetes therapy.

Authors:  David C Klonoff
Journal:  Diabetes Care       Date:  2005-05       Impact factor: 19.112

5.  Calculating glucose fluxes during meal tolerance test: a new computational approach.

Authors:  Roman Hovorka; Harsha Jayatillake; Eduard Rogatsky; Vlad Tomuta; Tomas Hovorka; Daniel T Stein
Journal:  Am J Physiol Endocrinol Metab       Date:  2007-05-22       Impact factor: 4.310

6.  A minimal model of insulin secretion and kinetics to assess hepatic insulin extraction.

Authors:  Gianna Toffolo; Marco Campioni; Rita Basu; Robert A Rizza; Claudio Cobelli
Journal:  Am J Physiol Endocrinol Metab       Date:  2005-09-06       Impact factor: 4.310

7.  Validation of mathematical models of complex endocrine-metabolic systems. A case study on a model of glucose regulation.

Authors:  C Cobelli; A Mari
Journal:  Med Biol Eng Comput       Date:  1983-07       Impact factor: 2.602

8.  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

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.  Is an automatic pump suspension feature safe for children with type 1 diabetes? An exploratory analysis with a closed-loop system.

Authors:  Eda Cengiz; Karena L Swan; William V Tamborlane; Garry M Steil; Amy T Steffen; Stuart A Weinzimer
Journal:  Diabetes Technol Ther       Date:  2009-04       Impact factor: 6.118

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  100 in total

1.  AP@home: a novel European approach to bring the artificial pancreas home.

Authors:  Lutz Heinemann; Carsten Benesch; J Hans DeVries
Journal:  J Diabetes Sci Technol       Date:  2011-11-01

2.  Continuous glucose monitoring: real-time algorithms for calibration, filtering, and alarms.

Authors:  B Wayne Bequette
Journal:  J Diabetes Sci Technol       Date:  2010-03-01

3.  Impact of blood glucose self-monitoring errors on glucose variability, risk for hypoglycemia, and average glucose control in type 1 diabetes: an in silico study.

Authors:  Marc D Breton; Boris P Kovatchev
Journal:  J Diabetes Sci Technol       Date:  2010-05-01

4.  Non-invasive continuous glucose monitoring: improved accuracy of point and trend estimates of the Multisensor system.

Authors:  Mattia Zanon; Giovanni Sparacino; Andrea Facchinetti; Michela Riz; Mark S Talary; Roland E Suri; Andreas Caduff; Claudio Cobelli
Journal:  Med Biol Eng Comput       Date:  2012-06-22       Impact factor: 2.602

5.  Measures of Risk and Glucose Variability in Adults Versus Youths.

Authors:  Boris P Kovatchev
Journal:  Diabetes Technol Ther       Date:  2015-09-08       Impact factor: 6.118

6.  Visual Predictive Check in Models with Time-Varying Input Function.

Authors:  Anna Largajolli; Alessandra Bertoldo; Marco Campioni; Claudio Cobelli
Journal:  AAPS J       Date:  2015-08-12       Impact factor: 4.009

7.  A simplification of Cobelli's glucose-insulin model for type 1 diabetes mellitus and its FPGA implementation.

Authors:  Peng Li; Lei Yu; Qiang Fang; Shuenn-Yuh Lee
Journal:  Med Biol Eng Comput       Date:  2015-12-30       Impact factor: 2.602

8.  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

9.  Performance of individually measured vs population-based C-peptide kinetics to assess β-cell function in the presence and absence of acute insulin resistance.

Authors:  Ron T Varghese; Chiara Dalla Man; Marcello C Laurenti; Francesca Piccinini; Anu Sharma; Meera Shah; Kent R Bailey; Robert A Rizza; Claudio Cobelli; Adrian Vella
Journal:  Diabetes Obes Metab       Date:  2017-09-27       Impact factor: 6.577

10.  Periodic zone-MPC with asymmetric costs for outpatient-ready safety of an artificial pancreas to treat type 1 diabetes.

Authors:  Ravi Gondhalekar; Eyal Dassau; Francis J Doyle
Journal:  Automatica (Oxf)       Date:  2016-06-01       Impact factor: 5.944

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