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.
