ArticleMedical & biological engineering & computing2009
Multi-objective blood glucose control for type 1 diabetes.
Article in Medical & biological engineering & computing, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Clinical evaluation of a personalized artificial pancreas.Diabetes care · 2013Trial
- Blood glucose concentration prediction based on VMD-KELM-AdaBoost.Medical & biological engineering & computing · 2021Article
- Multiobjective Optimization of Mixed-Integer Linear Programming Problems: A Multiparametric Optimization Approach.Industrial & engineering chemistry research · 2021Article
- Robust multi-objective blood glucose control in Type-1 diabetic patient.IET systems biology · 2019Article
- Performance Analysis of Fuzzy-PID Controller for Blood Glucose Regulation in Type-1 Diabetic Patients.Journal of medical systems · 2016Article
- A comprehensive compartmental model of blood glucose regulation for healthy and type 2 diabetic subjects.Medical & biological engineering & computing · 2016Article
- 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
- Evaluation of short-term predictors of glucose concentration in type 1 diabetes combining feature ranking with regression models.Medical & biological engineering & computing · 2015Article
- Model of glucose sensor error components: identification and assessment for new Dexcom G4 generation devices.Medical & biological engineering & computing · 2015Article
- Designing an artificial pancreas architecture: the AP@home experience.Medical & biological engineering & computing · 2015Article
- MPC Design for Rapid Pump-Attenuation and Expedited Hyperglycemia Response to Treat T1DM with an Artificial Pancreas.Proceedings of the ... American Control Conference. American Control Conference · 2014Article
- A robust sliding mode controller with internal model for closed-loop artificial pancreas.Medical & biological engineering & computing · 2010Article
- Systems engineering medicine: engineering the inflammation response to infectious and traumatic challenges.Journal of the Royal Society, Interface · 2010Review
- Modelling and multi-parametric control for delivery of anaesthetic agents.Medical & biological engineering & computing · 2010Article
- Quest for the artificial pancreas: combining technology with treatment.IEEE engineering in medicine and biology magazine : the quarterly magazine of the Engineering in Medicine & Biology SocietyArticle
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
For people with type 1 diabetes, automatic controllers aim to maintain the blood glucose concentration within the desired range of 60-120 mg/dL by infusing the appropriate amount of insulin in the presence of meal and exercise disturbances. Blood glucose concentration outside the desired range can be harmful to an individual's health but concentration below 60 mg/dL, a state known as hypoglycemia, is considered to be more harmful than the concentration above 120 mg/dL, a state known as hyperglycemia. In this paper, two techniques to address this issue within a multi-parametric model based control framework are presented. The first technique introduces asymmetry into the objective function to penalize the deviation towards hypoglycemia more than the deviation towards hyperglycemia. The second technique is based upon placing higher priority on satisfaction of constraints on hypoglycemia than on satisfaction of constraints on hyperglycemia. The performance of both the control techniques is analyzed and compared in the presence of disturbances.
Indexed as
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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.