Technology in the Management of Type 1 and Type 2 Diabetes Mellitus: Recent Status and Future Prospects

Biswas, Titas; Behera, Biplab Kumar; Madhu, Nithar Ranjan

doi:10.1007/978-981-19-0027-3_6

Cited by 5 publications

(6 citation statements)

References 75 publications

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“…Despite having a significant negative impact on resources and human well-being, chronic diseases such as DM continue to be disregarded by many countries. The number of people with DM is rising as a result of population growth, urbanization, the spread of obesity, and physical inertia [ 22 ]. Due to ignorance of their condition, people with DM may have several problems such as hypertension and DR.…”

Section: Discussionmentioning

confidence: 99%

“…Due to ignorance of their condition, people with DM may have several problems such as hypertension and DR. There is growing evidence that patient education is the most effective strategy for easing the complications brought on by DM [ 22 ]. The major consequence of DM is DR. Around 1.8 million people globally are known to go blind as a result of DR, if not treated properly [ 23 ].…”

Section: Discussionmentioning

confidence: 99%

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Unveiling the Veil: Exploring Diabetic Retinopathy Awareness and Behaviors of the General Population of Hafr Al Batin, Saudi Arabia

Alswailmi

2023

Cureus

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Background: Diabetic retinopathy (DR) is a potentially blinding complication of diabetes mellitus (DM). The current study set out to explore the awareness level and attitude of the general population of Hafr Al Batin, Saudi Arabia, where DM prevalence is high. Methodology: Data was collected through community-based, self-administered questionnaires in the general population of Hafr Al Batin, Saudi Arabia. The study included 406 participants, and the analysis revealed varying levels of knowledge, attitude, and practices related to DR. The study also explored the associations between sociodemographic factors and knowledge, attitude, and practices related to DR. The analysis showed that the participants had medium (67.4%) knowledge levels, while 32.5% had low knowledge. Results: The participants comprised 55.7% males and 44.3% females, with varying education levels and economic statuses. The majority were diagnosed with diabetes (94.3%). Attitude scores revealed that 30.8% had a favorable attitude, and 69.2% had medium attitude levels. Regarding practices, 71.2% of the respondents had low practice levels. The association between sociodemographic factors and knowledge, attitude, and practice were also explored. Conclusion: The current study concluded a medium level of knowledge (67.4%), and attitude toward DR is also low (69.2%). More than half of the respondents followed a poor level of practice (71.2%). The results of the current investigation demonstrated that the general population does not have sufficient knowledge, attitude, and practices regarding DR in Saudi Arabia. By promoting greater knowledge and understanding of DR, the burden of visual impairment brought on by this complication can be lessened by early detection and efficient care.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Unveiling the Veil: Exploring Diabetic Retinopathy Awareness and Behaviors of the General Population of Hafr Al Batin, Saudi Arabia

Alswailmi

2023

Cureus

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“…In India, diabetes is a growing public health concern, with a sizable section of the population at risk of having the disease at some point in the future. In India, those who reside in urban areas and large cities are more likely than ever to get diabetes (Sur et al, 2023;Biswas et al, 2023;Roy et al, 2023). To some extent, this is predicted because metropolitan regions are developing a style of life that might change a person's weight profile (BMI).…”

Section: Figure 1 Causes Of Diabetes Mellitus [Source: Self]mentioning

confidence: 99%

Application of Genetic Algorithms for Medical Diagnosis of Diabetes Mellitus

Tyagi,

Kumar,

Gupta

2024

IJERR

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The system of glucose-insulin control and associated problems in diabetes mellitus were studied by mathematical modeling. It is a helpful theoretical tool for understanding the basic concepts of numerous distinct medical and biological functions. It delves into the various risk factors contributing to the onset of diabetes, such as sedentary lifestyle, obesity, family history, viruses, and increasing age. The study emphasizes the importance of mathematical models in understanding the dynamic characteristics of biological systems. The study emphasizes the increasing prevalence of diabetes, especially in India, where urbanization and lifestyle changes contribute to the rising incidence. The present investigation describes the use of John Holland's evolutionary computing approach and the Genetic Algorithm (GA) in diabetes mellitus. The Genetic Algorithm is applied to address issues related to diabetes, offering a generic solution and utilizing MATLAB's Genetic Algorithm tool. The Mathematical Model provides differential equations representing glucose and insulin concentrations in the blood. The results represent testing outcomes for normal, prediabetic, and diabetic individuals, optimized with Genetic Algorithm showcased through fitness value plots. The conclusion highlights the effectiveness of Genetic Algorithm as an optimization tool in predicting optimal samples for diabetes diagnosis. The paper encourages the use of heuristic algorithms, such as Genetic Algorithms, to address complex challenges in the field of diabetes research. Future scope includes further exploration of biomathematics and Genetic Algorithm applications for enhanced understanding and management of diabetes mellitus. It is critical for people with diabetes to consistently check their blood glucose levels and follow their treatment plan.

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“…In Type 1 diabetes, the pancreatic β-cells responsible for insulin regulation are progressively destroyed, rendering precise blood glucose management elusive [6][7][8][9]. Even in Type 2 diabetes, in which some insulin remains in the patient's body, challenges persist because of the inadequacy of insulin for effective glucose control [10]. This study primarily focused on type 1 diabetes; a condition characterized by the inability of the pancreas to produce insulin.…”

Section: Introductionmentioning

confidence: 99%

Optimizing Blood Glucose Regulation in Type 1 Diabetes Patients via Genetic Algorithm-Based Fuzzy Logic Controller Considering Substantial Meal Protocol

Ndakara Abubakar,

Essabbar,

Saikouk

2024

Int. J. Onl. Eng.

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Effective management of blood glucose levels in individuals with type 1 diabetes, especially after meals, is crucial for diabetes care. Artificial pancreas systems (APS) perform automated insulin delivery in subjects with type 1 diabetes mellitus (T1DM). In this study, an optimized fuzzy logic controller was designed to achieve a euglycemic range after a substantial meal intake. All in silico simulations were performed using the MATLAB/Simulink environment, leveraging control variability grid analysis (CVGA), and the performance of the controller was evaluated. The proposed controller is based on a fuzzy-logic control law designed in three stages. First, a nonlinear framework of the glucose-insulin regulatory system was identified based on the heavy meal protocol of three patients given as follows: for subject ID 117-1, a total of 295 gCHO; for subject ID 126-1, 236 gCHO; and subject ID 128-1, 394 gCHO over a day. Then, an iterative tree structure was employed to establish a stabilizing control rule for insulin delivery, integrating inputs from two Mamdani Fuzzy Inference System (FIS) objects. Finally, a genetic algorithm refines the control system by fine-tuning the uncertainty of the fuzzy membership functions. Two scenarios were considered for three patients to assess the performance of the proposed controller. The results indicated its effectiveness under various conditions, achieving a time in the range of 61.25%, 71% and 61.10% respectively for the three subjects. The obtained results are analyzed and compared with IMC and multi-objective output feedback controllers. The findings of the study reveal that the proposed controller shows promising advancements in tailored strategies for type 1 diabetes patients, outperforming the other controllers in terms of blood glucose regulation.

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Technology in the Management of Type 1 and Type 2 Diabetes Mellitus: Recent Status and Future Prospects

Cited by 5 publications

References 75 publications

Unveiling the Veil: Exploring Diabetic Retinopathy Awareness and Behaviors of the General Population of Hafr Al Batin, Saudi Arabia

Unveiling the Veil: Exploring Diabetic Retinopathy Awareness and Behaviors of the General Population of Hafr Al Batin, Saudi Arabia

Application of Genetic Algorithms for Medical Diagnosis of Diabetes Mellitus

Optimizing Blood Glucose Regulation in Type 1 Diabetes Patients via Genetic Algorithm-Based Fuzzy Logic Controller Considering Substantial Meal Protocol

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