A mobile app for the self-management of type 1 diabetes as tool for preventing of exercise-associated glycemic imbalances
| Autor: | Federica De Dea, Giovanni Barbieri, Miloš Ajčević, Agostino Accardo |
|---|---|
| Přispěvatelé: | Lhotska, L., Sukupova, L., Lacković, I., Ibbott, G.S. (Eds.), Ajčević, Miloš, De Dea, Federica, Barbieri, Giovanni, Accardo, Agostino |
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
medicine.medical_specialty
Decision support system Exercise Glycaemia mHealth Type 1 diabetes Bioengineering Biomedical Engineering 020205 medical informatics Type 1 diabete medicine.medical_treatment 02 engineering and technology Hypoglycemia 03 medical and health sciences 0302 clinical medicine Physical medicine and rehabilitation Diabetes mellitus 0202 electrical engineering electronic engineering information engineering medicine Mobile technology 030212 general & internal medicine Glycemic business.industry Insulin Usability medicine.disease business |
| Zdroj: | IFMBE Proceedings ISBN: 9789811090349 |
| Popis: | mHealth is a growing field of research, concerning the great potentialities of mobile technology as a tool for self-management of chronic conditions. Physical activity greatly influences blood glucose levels, therefore for type 1 diabetes patients is important to adapt their diet and therapy in order to avoid exercise-induced hyperglycemia and hypoglycemia. The later represents one of the major barriers to physical activity and it limits volitional exercise in type 1 diabetes patients. However, there is lack of stand-alone mobile tool that provides the support to the patient in order to perform physical activity and exercise under safe glycaemia levels. Recently, Exercise Carbohydrate Requirement Estimating Software (ECRES) algorithm was proposed to calculate patient-exercise tailored glucose supplement required to maintain safe blood glucose levels during physical activity. The objective of this study was to develop a mobile App which implements an individualized predictive system for blood glucose in type 1 diabetes, depending on exercise strength. Its usability and accuracy were compared to original ECRES estimating software in 15 volunteer subjects. The developed application provides relevant feedback to patients on carbohydrate intake needed to carry out a planned physical activity, in a safe manner. Furthermore, application provides other important features, for self-management of this chronicity, reported in recent literature: entry of blood glucose values, display of diabetes-related data, such as blood glucose readings and their analysis, carbohydrate intake, insulin doses, and easy data export. The application also incorporates food atlas in order to facilitate carbohydrates calculation. The results of the test showed that developed application accurately implements ECRES algorithm and the self-management features. In conclusion, proposed App could be a useful support tool to diabetes type 1 patents. The results should be confirmed in larger clinical study. |
| Databáze: | OpenAIRE |
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