Blood glucose regulation in diabetes mellitus patients: a review on mathematical plant model and control algorithms

Dias, Cifha Crecil; Kamath, Surekha; Vidyasagar, Sudha

doi:10.1504/ijbra.2018.10009350

Cited by 2 publications

(5 citation statements)

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“…Sorensen model is a human glucose–insulin glucagon regulatory interaction model. The complex interaction of this model is captured and is delivered in terms of mathematical differential ordinary equations [40, 41 ]. The captured dynamics of the Sorensen model is non‐linear model equations, which is linearised with an operating point.…”

Section: Methodsmentioning

confidence: 99%

Design of dual hormone blood glucose therapy and comparison with single hormone using MPC algorithm

Dias

Kamath

Vidyasagar

2020

IET Systems Biology

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The complete automated control and delivery of insulin and glucagon in type 1 diabetes is the developing technology for artificial pancreas. This improves the quality of life of a diabetic patient with the precise infusion. The amount of infusion of these hormones is controlled using a control algorithm, which has the prediction property. The control algorithm model predictive control (MPC) predicts one step ahead and infuses the hormones continuously according to the necessity for the regulation of blood glucose. In this research, the authors propose a MPC control algorithm, which is novel for a dual hormone infusion, for a mathematical model such as Sorenson model, and compare it with the insulin alone or single hormone infusion developed with MPC. Since they aim for complete automatic control and regulation, unmeasured disturbances at a random time are integrated and the performance evaluation is projected through statistical analysis. The blood glucose risk index (BGRI) and control variability grid analysis (CVGA) plot gives the additional evaluation for the comparative results of the two controllers claiming 88% performance by dual hormone evaluated through CVGA plot and 2.05 mg/dl average tracking error, 2.20 BGRI. The MPC developed for dual hormone significantly performs better and the time spent in normal glycaemia is longer while eliminating the risk of hyperglycaemia and hypoglycaemia.

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Section: Methodsmentioning

confidence: 99%

Design of dual hormone blood glucose therapy and comparison with single hormone using MPC algorithm

Dias

Kamath

Vidyasagar

2020

IET Systems Biology

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“…It mainly uses an adaptive proportional derivative algorithm, which keeps an account on the absorption of the subcutaneous substance. It takes the patient's total daily requirement initially using first glucose reading by the patient and the patient's basal insulin rate at the beginning [ 42 ]. PID controller : This is the most widely used controller used to detect the dynamics of the system.…”

Section: Background Studymentioning

confidence: 99%

“…Owing to its non‐linear characteristic, it spans of the target system. It is designed in such a way that it does not depend on the parametric or the uncertainties in the system model, which provides robustness [ 42 ]. Fuzzy logic control (FLC) : PID‐FLC is an effective strategy that takes into account all the components that are necessary and reacts to the possible changes in glucose concentration in the human body.…”

Section: Background Studymentioning

confidence: 99%

“… Fuzzy logic control (FLC) : PID‐FLC is an effective strategy that takes into account all the components that are necessary and reacts to the possible changes in glucose concentration in the human body. It helps to raise the patients’ quality of life and reduces the occurrence of hypoglycaemia and hyperglycaemia by keeping the glucose level in the ideal range [ 42 ]. To address this issue, this research is being carried on for bihormonal control with insulin and glucagon infusion and maintain normal glycaemia for a longer time.…”

Section: Background Studymentioning

confidence: 99%

Section: Background Studymentioning

confidence: 99%

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Blood glucose regulation and control of insulin and glucagon infusion using single model predictive control for type 1 diabetes mellitus

2020

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This study elaborates on the design of artificial pancreas using model predictive control algorithm for a comprehensive physiological model such as the Sorensen model, which regulates the blood glucose and can have a longer control time in normal glycaemic region. The main objective of the proposed algorithm is to eliminate the risk of hyper and hypoglycaemia and have a precise infusion of hormones: insulin and glucagon. A single model predictive controller is developed to control the bihormones, insulin, and glucagon for such a development unmeasured disturbance is considered for a random time. The simulation result for the proposed algorithm performed good regulation lowering the hypoglycaemia risk and maintaining the glucose level within the normal glycaemic range. To validate the performance of the tracking of output and setpoint, average tracking error is used and 4.4 mg/dl results are obtained while compared with standard value (14.3 mg/dl).

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Blood glucose regulation in diabetes mellitus patients: a review on mathematical plant model and control algorithms

Cited by 2 publications

References 0 publications

Design of dual hormone blood glucose therapy and comparison with single hormone using MPC algorithm

Design of dual hormone blood glucose therapy and comparison with single hormone using MPC algorithm

Blood glucose regulation and control of insulin and glucagon infusion using single model predictive control for type 1 diabetes mellitus

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