Evidence map›Paper›PMID 23544672›Full record

ArticleDiabetes technology & therapeutics2013

Multivariable adaptive closed-loop control of an artificial pancreas without meal and activity announcement.

Kamuran Turksoy, Elif Seyma Bayrak, Lauretta Quinn, Elizabeth Littlejohn, Ali Cinar

Abstract read
In one paragraph

Article in Diabetes technology & therapeutics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers.

0numbers the graph read from it
0cells of the map it votes in
61citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

61 citing papers in PubMed.

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  8. An integrated multivariable artificial pancreas control system.Journal of diabetes science and technology · 2014
    Trial
  9. Article
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  11. Metabolic Models, in Silico Trials, and Algorithms.Diabetes technology & therapeutics · 2025
    Review
  12. Metabolic Models, in Silico Trials, and Algorithms.Journal of diabetes science and technology · 2025
    Review
  13. Review
  14. Article
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1 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Kamuran TurksoyDepartment of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL 60616, USA.
Elif Seyma Bayrak
Lauretta Quinn
Elizabeth Littlejohn
Ali Cinar

Funding

Multivariable Closed Loop Technologies for Physically Active Young Adults with TyR01DK085611 · NIDDK · ILLINOIS INSTITUTE OF TECHNOLOGY · PI CINAR, ALI · 2009 to 2010
$438k
NIDDK NIH HHS R01 DK 085611
6 · The paper itself

Abstract

backgroundAccurate closed-loop control is essential for developing artificial pancreas (AP) systems that adjust insulin infusion rates from insulin pumps. Glucose concentration information from continuous glucose monitoring (CGM) systems is the most important information for the control system. Additional physiological measurements can provide valuable information that can enhance the accuracy of the control system. Proportional-integral-derivative control and model predictive control have been popular in AP development. Their implementations to date rely on meal announcements (e.g., bolus insulin dose based on insulin:carbohydrate ratios) by the user. Adaptive control techniques provide a powerful alternative that do not necessitate any meal or activity announcements. MATERIALS AND

methodsAdaptive control systems based on the generalized predictive control framework are developed by extending the recursive modeling techniques. Physiological signals such as energy expenditure and galvanic skin response are used along with glucose measurements to generate a multiple-input-single-output model for predicting future glucose concentrations used by the controller. Insulin-on-board (IOB) is also estimated and used in control decisions. The controllers were tested with clinical studies that include seven cases with three different patients with type 1 diabetes for 32 or 60 h without any meal or activity announcements.

resultsThe adaptive control system kept glucose concentration in the normal preprandial and postprandial range (70-180 mg/dL) without any meal or activity announcements during the test period. After IOB estimation was added to the control system, mild hypoglycemic episodes were observed only in one of the four experiments. This was reflected in a plasma glucose value of 56 mg/dL (YSI 2300 STAT; Yellow Springs Instrument, Yellow Springs, OH) and a CGM value of 63 mg/dL).

conclusionsRegulation of blood glucose concentration with an AP using adaptive control techniques was successful in clinical studies, even without any meal and physical activity announcement.

Indexed as

Pancreas, ArtificialAdolescentAdultAlgorithmsBlood GlucoseBlood Glucose Self-MonitoringDiabetes Mellitus, Type 1Dietary CarbohydratesFemaleGlycated HemoglobinHumansHyperglycemiaHypoglycemiaHypoglycemic AgentsInsulinMaleBlood GlucoseDietary CarbohydratesGlycated Hemoglobinhemoglobin A1c protein, humanHypoglycemic AgentsInsulin

Identifiers

PMID23544672
PMCPMC3643229

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.