This page is a copy of research/systems_and_control/biomed/glucosecontrol (Wed, 31 Aug 2022 15:08:02)
This page is a copy of research/syscon/biomed/glucosecontrol (Wed, 27 May 2015 14:18:27)
Blood glucose control is a challenging research topic, which has as goal to regulate glucose levels within normal range. Alterations in blood glucose levels are presented in patients with diabetes mellitus due to the pancreas inability, having either little or no endogenous insulin production, type 1 diabetes, or a combination of insulin resistance and insufficient pancreatic insulin release, type 2 diabetes. These alterations (i.e. hyperglycaemia) are also presented in critically ill patients, in both diabetics and non diabetics. In this case, elevated glucose levels are produced by a stimulation of endogenous glucose production and an increment of insulin resistance when counter-regulatory hormone secretion is increased. Hyperglycaemia effects are well known and they are associated with worsening of the severity state of the patients.
For diabetic patients, the development of an artificial pancreas replaces the b-cells functions in glucose sensing and insulin delivery. It consists of three main components: a glucose sensor to measure glucose concentration, a pump for insulin delivery, and a closed-loop control algorithm to bridge between the glucose measurements and the dose of insulin to be delivered. For critically ill patients, although for the most of them the endogenous insulin section is still active, some exogenously administered insulin flow is required due to the increased insulin resistance and the insufficient activity of the pancreas.
For automatic glucose control, contributions in identification and control algorithms are essential. Although there are some non-linear models based in physiological principles in the literature, in most cases the identification of such models is not feasible from a practical clinical point of view. Moreover, there is an intra- and inter-patient variability. Obtaining models from process input-output data is desirable for blood glucose control. Black-box nonlinear identification of glucose-insulin system for control could be applied. Developing of robust control techniques are needed, due to the strong nonlinear behavior, unmodeled disturbances, and the imprecise and time-delayed glucose measurements together with the intra-patient variability.
- A. AbuRmileh; et. al. Internal model sliding mode control approach for glucose regulation in type 1 diabetes. Biomedical Signal Processing and Control, (5) 94-102, 2010.
- D. Zambrano, et. al. Glucose Control in Critically ill Patients Using Sliding Mode Control with Robust Differentiators. 7th IFAC Symposium on Modelling and Control in Biomedical Systems, 2009. Aalborg, Denmark.
- W. Garcia-Gabin, et. al. A sliding mode predictive control approach to closed-loop glucose control for type 1 diabetes. 7th IFAC Symposium on Modelling and Control in Biomedical Systems, 2009. Aalborg, Denmark.
- W. GarcÃa-GabÃn, et. al. Robust sliding mode predictive control to closed-loop glucose control for patients with type 1 diabetes mellitus. 1st International Conference on Advanced Technologies & Treatments for Diabetes. 2008. Prague, Czhec Republic.