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.

A mobile app for the self-management of type 1 diabetes as tool for preventing of exercise-associated glycemic imbalances

Ajčević, Miloš
;
De Dea, Federica;Accardo, Agostino
2018-01-01

Abstract

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.
2018
978-981-10-9034-9
978-981-10-9035-6
http://www.springer.com/series/7403
File in questo prodotto:
File Dimensione Formato  
IUPESM Ajcevic.pdf

Accesso chiuso

Tipologia: Documento in Versione Editoriale
Licenza: Copyright Editore
Dimensione 179.22 kB
Formato Adobe PDF
179.22 kB Adobe PDF   Visualizza/Apri   Richiedi una copia
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/2928046
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 3
  • ???jsp.display-item.citation.isi??? 2
social impact