ArticleJournal of diabetes science and technology2013
Periodic-zone model predictive control for diurnal closed-loop operation of an artificial pancreas.
Article in Journal of diabetes science and technology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled 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.
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.
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Who cites it
23 citing papers in PubMed, 1 synthesis or guideline pooled it, 74 citations in OpenAlex.
- Pooled it
- Randomized Crossover Comparison of Personalized MPC and PID Control Algorithms for the Artificial Pancreas.Diabetes care · 2016Trial
- Adjustment of Open-Loop Settings to Improve Closed-Loop Results in Type 1 Diabetes: A Multicenter Randomized Trial.The Journal of clinical endocrinology and metabolism · 2015Trial
- Extended Kalman filter state estimation-based nonlinear explicit model predictive control design for blood glucose regulation of type 1 diabetic patient.Medical & biological engineering & computing · 2022Article
- Review
- Embedded Model Predictive Control for a Wearable Artificial Pancreas.IEEE transactions on control systems technology : a publication of the IEEE Control Systems Society · 2020Article
- Closed-Loop Control with Unannounced Exercise for Adults with Type 1 Diabetes using the Ensemble Model Predictive Control.Journal of process control · 2019Article
- Adaptive Zone Model Predictive Control of Artificial Pancreas Based on Glucose- and Velocity-Dependent Control Penalties.IEEE transactions on bio-medical engineering · 2019Article
- Identifiability Analysis of Three Control-Oriented Models for Use in Artificial Pancreas Systems.Journal of diabetes science and technology · 2018Article
- Extremum Seeking Control for Personalized Zone Adaptation in Model Predictive Control for Type 1 Diabetes.IEEE transactions on bio-medical engineering · 2018Article
- Velocity-weighting & velocity-penalty MPC of an artificial pancreas: Improved safety & performance.Automatica : the journal of IFAC, the International Federation of Automatic Control · 2018Article
- Event-Triggered Model Predictive Control for Embedded Artificial Pancreas Systems.IEEE transactions on bio-medical engineering · 2018Article
- An Enhanced Model Predictive Control for the Artificial Pancreas Using a Confidence Index Based on Residual Analysis of Past Predictions.Journal of diabetes science and technology · 2017Article
- An Adaptive Nonlinear Basal-Bolus Calculator for Patients With Type 1 Diabetes.Journal of diabetes science and technology · 2017Article
- A Review of Safety and Design Requirements of the Artificial Pancreas.Annals of biomedical engineering · 2016Review
- Periodic zone-MPC with asymmetric costs for outpatient-ready safety of an artificial pancreas to treat type 1 diabetesAutomatica : the journal of IFAC, the International Federation of Automatic Control · 2016Article
- Switched LPV Glucose Control in Type 1 Diabetes.IEEE transactions on bio-medical engineering · 2016Article
- Velocity-weighting to prevent controller-induced hypoglycemia in MPC of an artificial pancreas to treat T1DM.Proceedings of the ... American Control Conference. American Control Conference · 2015Article
- Tackling problem nonlinearities & delays via asymmetric, state-dependent objective costs in MPC of an artificial pancreas.IFAC-PapersOnLine · 2015Article
- Moving-horizon-like state estimation via continuous glucose monitor feedback in MPC of an artificial pancreas for type 1 diabetes.Proceedings of the ... IEEE Conference on Decision & Control. IEEE Conference on Decision & Control · 2014Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundThe objective of this research is an artificial pancreas (AP) that performs automatic regulation of blood glucose levels in people with type 1 diabetes mellitus. This article describes a control strategy that performs algorithmic insulin dosing for maintaining safe blood glucose levels over prolonged, overnight periods of time and furthermore was designed with outpatient, multiday deployment in mind. Of particular concern is the prevention of nocturnal hypoglycemia, because during sleep, subjects cannot monitor themselves and may not respond to alarms. An AP intended for prolonged and unsupervised outpatient deployment must strategically reduce the risk of hypoglycemia during times of sleep, without requiring user interaction.
methodsA diurnal insulin delivery strategy based on predictive control methods is proposed. The so-called "periodic-zone model predictive control" (PZMPC) strategy employs periodically time-dependent blood glucose output target zones and furthermore enforces periodically time-dependent insulin input constraints to modulate its behavior based on the time of day.
resultsThe proposed strategy was evaluated through an extensive simulation-based study and a preliminary clinical trial. Results indicate that the proposed method delivers insulin more conservatively during nighttime than during daytime while maintaining safe blood glucose levels at all times. In clinical trials, the proposed strategy delivered 77% of the amount of insulin delivered by a time-invariant control strategy; specifically, it delivered on average 1.23 U below, compared with 0.31 U above, the nominal basal rate overnight while maintaining comparable, and safe, blood glucose values.
conclusionsThe proposed PZMPC algorithm strategically prevents nocturnal hypoglycemia and is considered a significant step toward deploying APs into outpatient environments for extended periods of time in full closed-loop operation.
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Registered trials
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.