A chronic disease in which human body loses its ability to produce or use the produced insulin known as Diabetes Mellitus (DM). This failure in body’s ability would lead to high level of blood glucose that in a long time as a consequence it could damage different organs or part of organ systems such as heart, eyes, kidneys, blood vessel, and nervous system. Untreated DM causes many complications including diabetic nephropathy, foot ulcers, stroke, cardiovascular disease, and diabetic retinopathy. Although controlled diet and exercise along with regular monitoring and insulin therapy are the main tools of treating DM, these factors are often insufficient to alleviate the symptoms of the disease and prevent it from progression over time.
During the past decade, researchers have developed different mathematical models to describe the glucose-insulin regulatory system and gain a better understanding of the nonlinear mechanism of glucose management system in the human body toward reaching their ultimate goal which is building Artificial Pancreas (AP). AP has three components: a continuous glucose monitor (CGM), insulin pump, and closed-loop control algorithm. Researchers have developed algorithms based on control techniques such as Proportional Integral Derivative (PID) and Model Predictive Control (MPC) for blood glucose level (BGL) control; however, variability in metabolism between or within individuals hinders reliable control.
This study aims to develop a simple and accurate model of the glucose regulatory system and build PID controller based on that to perform proper insulin injections according to BGL in diabetic rats. This study is a groundwork to implement PID algorithm on real subjects. BGL data collected from diabetic rats using CGM are used with other inputs such as insulin and glucose injections information to develop a mathematical model of glucose-insulin homeostasis based on proposed models by Lombarte et al., and Bergman et al. Since these models proposed for healthy rats; a revised version of this model with three additional equations from Wilinska et al.’s model used to represent diabetic rats for the identiﬁcation of dynamics and the glycemic regulation of rats.
The developed models were fitted to actual data using particle swarm optimization method. The outcomes from of the fitted simulation to the actual data determine which model has better performance in generating more accurate results. At last a PID controller developed for the model with better performance to control BGL of the plant model within the normal range of 100 to 130 mg/dl by injecting the appropriate amount of insulin.
|Advisor:||Ko, Hoo S.|
|Commitee:||Lee, H. Felix, Kwon, Guim|
|School:||Southern Illinois University at Edwardsville|
|School Location:||United States -- Illinois|
|Source:||MAI 81/2(E), Masters Abstracts International|
|Keywords:||Diabetes Mellitus, Insulin, Blood glucose|
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