Thesis (M.Ing. (Mechanical Engineering))--North-West University, Potchefstroom Campus, 2007.

Type 1 Diabetes is a dangerous and life-long disease for which its prevalence is global. Research has shown that tight glycaemic control of this disease significantly reduces the risks of developing several life threatening diabetic complications. The Ets-Insulin-Bolus Calculator (EIBC), inspired by the Ets concept (Equivalent Teaspoon Sugar), was primarily designed to assist type I diabetics in improving their blood glucose control. The EIBC has shown to improve the average blood glucose level of type 1 diabetics. The need for this study however is to determine whether the ET!3C promotes tighter glycaemic control for type 1 diabetics based on a more-in-depth numerical analysis. With the use of the latest technology in blood glucose monitoring, the CGMS from Medtronic, mathematical models expressing and rating blood glucose control have been proposed and derived in this study. A clinical trial with type 1 diabetics has also been conducted. The use of the models together with the clinical trial results have shown that the EIBC does in fact promote tighter glycaemic control for type 1 diabetics. / Thesis (M.Ing. (Mechanical Engineering))--North-West University, Potchefstroom Campus, 2007.

Type 1 Diabetes is a dangerous and life-long disease for which its prevalence is global. Research has shown that tight glycaemic control of this disease significantly reduces the risks of developing several life threatening diabetic complications. The Ets-Insulin-Bolus Calculator (EIBC), inspired by the Ets concept (Equivalent Teaspoon Sugar), was primarily designed to assist type I diabetics in improving their blood glucose control. The EIBC has shown to improve the average blood glucose level of type 1 diabetics. The need for this study however is to determine whether the ET!3C promotes tighter glycaemic control for type 1 diabetics based on a more-in-depth numerical analysis. With the use of the latest technology in blood glucose monitoring, the CGMS from Medtronic, mathematical models expressing and rating blood glucose control have been proposed and derived in this study. A clinical trial with type 1 diabetics has also been conducted. The use of the models together with the clinical trial results have shown that the EIBC does in fact promote tighter glycaemic control for type 1 diabetics. / Thesis (M.Ing. (Mechanical Engineering))--North-West University, Potchefstroom Campus, 2007.

abstract: Type 1 diabetes (T1D) is a chronic disease that affects 1.25 million people in the United States. There is no known cure and patients must self-manage the disease to avoid complications resulting from blood glucose (BG) excursions. Patients are more likely to adhere to treatments when they incorporate lifestyle preferences. Current technologies that assist patients fail to consider two factors that are known to affect BG: exercise and alcohol. The hypothesis is postprandial blood glucose levels of adult patients with T1D can be improved by providing insulin bolus or carbohydrate recommendations that account for meal and alcohol carbohydrates, glycemic excursion, and planned exercise. I propose an evidence-based decision support tool, iDECIDE, to make recommendations to improve glucose control by taking into account meal and alcohol carbohydrates, glycemic excursion and planned exercise. iDECIDE is deployed as a low-cost and easy to disseminate smartphone application. A literature review was conducted on T1D and the state-of-the-art in diabetes technology. To better understand self-management behaviors and guide the development of iDECIDE, several data sources were collected and analyzed: surveys, insulin pump paired with glucose monitoring, and self-tracking of exercise and alcohol. The analysis showed variability in compensation techniques for exercise and alcohol and that patients made unaided decisions, suggesting a need for better decision support. The iDECIDE algorithm can make insulin and carbohydrate recommendations. Since there were no existing in-silico methods for assessing bolus calculators, like iDECIDE, I proposed a novel methodology to retrospectively compare insulin pump bolus calculators. Application of the methodology shows that iDECIDE outperformed the Medtronic insulin pump bolus calculator and could have improved glucose control. This work makes contributions to diabetes technology researchers, clinicians and patients. The iDECIDE app provides patients easy access to a decision support tool that can improve glucose control. The study of behaviors from diabetes technology and self-report patient data can inform clinicians and the design of future technologies and bedside tools that integrate patient’s behaviors and perceptions. The comparison methodology provides a means for clinical informatics researchers to identify and retrospectively test promising insulin blousing algorithms using real-life data. / Dissertation/Thesis / Doctoral Dissertation Biomedical Informatics 2017

Type 1 diabetes (T1D) is an auto-immune disease characterized by insulin-deficiency. Insulin is a metabolic hormone that is involved in lowering blood glucose (BG) levels in order to control BG level to a tight range. In T1D this glycemic control is lost, causing chronic hyperglycemia (excess glucose in blood stream). Chronic hyperglycemia damages vital tissues. Therefore, glycemic control must be restored. A common therapy for restoring glycemic control is intensive insulin therapy, where the missing insulin is replaced with regular insulin injections. When dosing this compensatory insulin many factors that affect glucose metabolism must be considered. Linkura is a company that has developed tools for monitoring the most important factors, which are meals and exercise. In the Linkura meal and exercise tools, the nutrition content in meals and the calorie consumption during exercise are estimated. Another tool designed to aid control of BG is the bolus calculator. Bolus calculators use input of BG level, carbohydrate intake, and insulin history to estimate insulin need. The accuracy of these insulin bolus calculations suffer from two problems. First, errors occur when users inaccurately estimate the carbohydrate content in meals. Second, exercise is not included in bolus calculations. To reduce these problems, it was suggested that the Linkura web tools could be utilized in combination with a bolus calculator. For this purpose, a bolus calculator was developed. The bolus calculator was based on existing models that utilize clinical parameters to relate changes in BG levels to meals, insulin, and exercise stimulations. The bolus calculator was evaluated using data collected from Linkura's web tools. The collected data showed some inconsistencies which cannot be explained by any model.  The performance of the bolus calculator in predicting BG levels using general equations to derive the clinical parameters was inadequate. Performance was increased by adopting an update-algorithm where the clinical parameters were updated daily using previous data. Still, better model performance is prefered for use in a bolus calculator.   The results show potential in developing bolus calculator tools combined with the Linkura tools. For such bolus calculator, further evaluation on modeling long-term exercise and additional safety features minimizing risk of hypoglycemia are required.