DiaGame: Serious and personalized game for selfmanagement of diabetes

The DiaGame project applies the sciences of data learning and biomedical simulations to an existing serious diabetes gaming platform (SugarVita). We aim to make the current SugarVita, a data-driven, personalized serious game that empowers individuals with diabetes to manage the disease they are facing. In order to personalize the game, we will integrate our expertise on processing of personal data collected from health-related smartphone apps into our game platform. The information that this approach will be used to personalize the simulation that drives the game. Together, this will allow the use of patient-gathered health data to make the diabetes game a realistic representation of the condition of the gamer.
This allows the gamer to play SugerVita-P4 using personal settings for improved educational value, since typically for diabetes, knowledge and skill are the key to effectively self-manage their condition. We will provide support for the notion that playing SugarVita-P4 creates reward and motivation and is therefore more effective.
We are already integrating the development of the game and the encompassing academic (data-processing and simulation) activities into the daily practice in diabetes care. Because of this, we generate the capacity to employ a lean development process that iteratively uses in-game observations to improve the approach to data-to-information-to-education flow.
Collectively, DiaGame can change the approach to diabetes care by using data sciences in support of a data-driven personal diabetes game. Ultimately, this will improve the quality of life for patients and lighten the socio-economic and medical burden that diabetes has.

SugarVita aims to give people with diabetes more control over their chronic condition. Self-care is now seen as the primary approach to diabetes, which is a complex task, with many facets, where training and education are crucial. However, a "dry" explanation does not work for everyone.

Patient gathered health data will be collected to optimize a personalized diabetesgame, which we hypothese will improve self management

2 visits ( V 2 will be two weeks after visit 1)

Registration of daily life by continu glucose monitoring with a Freestyle Libre Pro sensor (Abbott) and exercise, nutrition, medication and mental status by Gamebus app and smartwatch