ArticleJournal of diabetes science and technology2009
Run-to-run tuning of model predictive control for type 1 diabetes subjects: in silico trial.
Article in Journal of diabetes science and technology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed.
- Fully integrated artificial pancreas in type 1 diabetes: modular closed-loop glucose control maintains near normoglycemia.Diabetes · 2012Trial
- Adaptive Control of an Artificial Pancreas Using Model Identification, Adaptive Postprandial Insulin Delivery, and Heart Rate and Accelerometry as Control Inputs.Journal of diabetes science and technology · 2019Article
- Controlling the AP Controller: Controller Performance Assessment and Modification.Journal of diabetes science and technology · 2019Article
- Design of an online-tuned model based compound controller for a fully automated artificial pancreas.Medical & biological engineering & computing · 2019Article
- Extremum Seeking Control for Personalized Zone Adaptation in Model Predictive Control for Type 1 Diabetes.IEEE transactions on bio-medical engineering · 2018Article
- The UVA/Padova Type 1 Diabetes Simulator Goes From Single Meal to Single Day.Journal of diabetes science and technology · 2018Article
- Insulin Sensitivity Index-Based Optimization of Insulin to Carbohydrate Ratio: In Silico Study Shows Efficacious Protection Against Hypoglycemic Events Caused by Suboptimal Therapy.Diabetes technology & therapeutics · 2018Article
- Multivariable Adaptive Artificial Pancreas System in Type 1 Diabetes.Current diabetes reports · 2017Review
- Modelling the effect of insulin on the disposal of meal-attributable glucose in type 1 diabetes.Medical & biological engineering & computing · 2017Article
- Artificial pancreas: model predictive control design from clinical experience.Journal of diabetes science and technology · 2013Article
- "Turn it off!": diabetes device alarm fatigue considerations for the present and the future.Journal of diabetes science and technology · 2013Article
- Model-based sensor-augmented pump therapy.Journal of diabetes science and technology · 2013Article
- Wearable and implantable pancreas substitutes.Journal of artificial organs : the official journal of the Japanese Society for Artificial Organs · 2013Review
- Systematically in silico comparison of unihormonal and bihormonal artificial pancreas systems.Computational and mathematical methods in medicine · 2013Article
- Modular closed-loop control of diabetes.IEEE transactions on bio-medical engineering · 2012Article
- Italian contributions to the development of continuous glucose monitoring sensors for diabetes management.Sensors (Basel, Switzerland) · 2012Review
- The artificial pancreas.Diabetes · 2012Article
- Artificial pancreas: past, present, future.Diabetes · 2011Review
- AP@home: a novel European approach to bring the artificial pancreas home.Journal of diabetes science and technology · 2011Article
- Development of a multi-parametric model predictive control algorithm for insulin delivery in type 1 diabetes mellitus using clinical parameters.Journal of process control · 2011Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe technological advancements in subcutaneous continuous glucose monitoring and insulin pump delivery systems have paved the way to clinical testing of artificial pancreas devices. The experience derived by clinical trials poses technological challenges to the automatic control expert, the most notable being the large interpatient and intrapatient variability and the inherent uncertainty of patient information.
methodsA new model predictive control (MPC) glucose control system is proposed. The starting point is an MPC algorithm applied in 20 type 1 diabetes mellitus (T1DM) subjects. Three main changes are introduced: individualization of the ARX model used for prediction; synthesis of the MPC law on top of the open-loop basal/bolus therapy; and a run-to-run approach for implementing day-by-day tuning of the algorithm. In order to individualize the ARX model, a sufficiently exciting insulin profile is imposed by splitting the premeal bolus into two smaller boluses (40% and 60%) injected 30 min before and 30 min after the meal.
resultsThe proposed algorithm was tested on 100 virtual subjects extracted from an in silico T1DM population. The trial simulates 44 consecutive days, during which the patient receives breakfast, lunch, and dinner each day. For 10 days, meals are multiplied by a random variable uniformly distributed in [0.5, 1.5], while insulin delivery is based on nominal meals. Moreover, for 10 days, either a linear increase or decrease of insulin sensitivity (+/-25% of nominal value) is introduced.
conclusionsThe ARX model identification procedure offers an automatic tool for patient model individualization. The run-to-run approach is an effective way to auto-tune the aggressiveness of the closed-loop control law, is robust to meal variation, and is also capable of adapting the regulator to slow parameter variations, e.g., on insulin sensitivity.
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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.