Artificial Pancreas Control Strategies Used for Type 1 Diabetes Control and Treatment: A Comprehensive Analysis

Mehmood, Sohaib; Ahmad, Imran; Arif, Hadeeqa; Ammara, Umm E; Majeed, Abdul

doi:10.3390/asi3030031

Cited by 26 publications

(12 citation statements)

References 199 publications

(257 reference statements)

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“…IWO is a new evolutionary computational algorithm that relies on the natural behavior of weeds in searching for a suitable place for growth and reproduction by simulating the reproductive and growth behaviors of weeds in nature as the IWO algorithm is a random numerical search algorithm that IWO searches for the optimal solution to the problem in the solution space. In general, its most important steps in the calculation are based on four steps: initialization, cloning, spatial dispersion, and selection, which are as follows [30,31].…”

Section: Invasive Weed Optimization (Iwo)mentioning

confidence: 99%

“…After that, all Wj grass in the community reproduces seeds, and the seeds grow into multiple weeds through spatial dispersal. The amount (Nsj) of seeds produced by Wj is calculated using the following equation [30,31]:…”

Section: Initializationmentioning

confidence: 99%

“…By repeating Itermax times, weeds with the highest fitness value are the perfect solution to the problem. The formula is as follows [30,31]:…”

Section: Reproductionmentioning

confidence: 99%

“…That is why our contribution to this research was on the application of a FOPID controller for good blood glucose control, closed loop control, and good response determination respectively. By finding a better solution by applying several new meta-heuristic algorithms including the Particle Swarm Optimization (PSO) [28,29], The bat optimization algorithm (BA), Invasive Weed Optimization (IWO) [30,31], Ant Colony Optimization (ACO) [32]. and technology Genetic algorithm (GA) [33].…”

Section: Introductionmentioning

confidence: 99%

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Design an Optimal Fractional Order PID Controller Based on New Algorithms and a Fuzzy Logic Controller to Regulate Type 1 Diabetes Patients

Benzian¹,

Ameur²,

Rebai³

2021

JESA

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Diabetes is one of the most important diseases that researchers have focused on in scientific research since the time, because of the seriousness of this disease if it is not properly dealt with, especially with the emergence of some global epidemics such as Corona Virus (COVID 19), as the pancreas is the organ responsible for regulating sugar in the blood by secreting the insulin enzyme, insulin is widely used to control blood sugar. Therefore, it is important that the required insulin value is constant and controlled. The aim of this study is to control the blood glucose value that is achieved as a desired value and to maintain it as a constant value using a proportional, integral, and derivative control unit (FOPID) fractional order of the control parameters. In this research, the new control unit is applied to Bergman's mathematical model as a non-linear and simple model that simulates the mechanism of the interaction of glucose and insulin in the blood, and based on this, a closed control loop was designed to regulate the level of blood sugar to be an automatic control of blood glucose using the measured data from Special sensor. The contribution in this scientific paper is to define the (FOPID) parameters according to the closed loop responses of the system, and these parameters were adjusted using new meta-heuristic algorithms including the Invasive Weed Optimization (IWO), the PSO Particle Swarm optimization, the Genetic Algorithm (GA), The bat optimization algorithm (BA) and (ACO). As a result, the results of the five modern algorithms were compared based on several criteria to find out which one was better using MATLAB / SIMULINK simulation. It was found that the IWO algorithm performs better than PSO. The simulation results of the closed-loop system of this controller at the time of settling, overshoot and control inputs indicate very positive results compared to previous results. In addition, a new method has been proposed which is to design a pump in the form of a valve to control insulin pumping by controlling it with the fuzzy logic control unit, which in turn, we obtained better results, compared to the results of other previous studies.

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Section: Invasive Weed Optimization (Iwo)mentioning

confidence: 99%

Section: Initializationmentioning

confidence: 99%

“…By repeating Itermax times, weeds with the highest fitness value are the perfect solution to the problem. The formula is as follows [30,31]:…”

Section: Reproductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Design an Optimal Fractional Order PID Controller Based on New Algorithms and a Fuzzy Logic Controller to Regulate Type 1 Diabetes Patients

Benzian¹,

Ameur²,

Rebai³

2021

JESA

View full text Add to dashboard Cite

show abstract

“…Diabetes mellitus is a serious and prevalent chronic disease [1,2]. The number of diabetes mellitus patients has increased.…”

Section: Introductionmentioning

confidence: 99%

Self-Care IoT Platform for Diabetic Mellitus

2021

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Diabetes mellitus is a severe chronic disease, and the number of patients has increased. To manage blood glucose levels, patients should frequently measure their blood glucose and analyze which lifestyle habits affect blood glucose levels. However, it is hard to record and analyze the relationship between their blood glucose levels and lifestyle. The internet of things (IoT) is useful to interconnect, monitor, obtain, and process data between various devices used in everyday life to fulfill a common objective. This paper proposes an intelligent self-care platform using IoT technology that helps patients with chronic diabetes manage their blood glucose levels in their target range. In particular, we developed various devices called the self-care IoT pack. It consists of five different types of devices to obtain blood glucose levels, physical activities, food intake, medication, sleeping, and so on. They can collect blood glucose levels with lifestyles that automatically impact the patient’s blood glucose level. We also devised a self-care application to display and analyze the data obtained from the IoT pack. Consequently, the proposed self-care IoT platform collects the blood glucose levels and the lifestyles without any burden of record. By reviewing the accumulated information, the patients can find bad habits in blood glucose management and improve their lifestyle.

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