Aleksandr Agafonov
Department of Computer Science, University of Tromsø - The Arctic University of Norway, Norway
Eirik Årsand
Department of Computer Science, University of Tromsø - The Arctic University of Norway, Norway / Norwegian Centre for Integrated Care and Telemedicine, University Hospital of North Norway
Alexandra Makhlysheva
Norwegian Centre for Integrated Care and Telemedicine, University Hospital of North Norway
Håvard Blixgård
Norwegian Centre for Integrated Care and Telemedicine, University Hospital of North Norway
Meghan Bradway
Norwegian Centre for Integrated Care and Telemedicine, University Hospital of North Norway
Gunnar Hartvigsen
Department of Computer Science, University of Tromsø - The Arctic University of Norway, Norway / Norwegian Centre for Integrated Care and Telemedicine, University Hospital of North Norway
Ladda ner artikel
Ingår i: SHI 2015, Proceedings from The 13th Scandinavien Conference on Health Informatics, June 15-17, 2015, Tromsø, Norway
Linköping Electronic Conference Proceedings 115:8, s. 47-54
Publicerad: 2015-06-26
ISBN: 978-91-7685-985-8
ISSN: 1650-3686 (tryckt), 1650-3740 (online)
For individuals with diabetes to live a healthy life, they must balance carbohydrate intake, insulin injections, physical activity, and monitoring of blood glucose levels. For adolescents with diabetes, this can be challenging – measuring blood glucose and injecting insulin often feels awkward, especially in public areas. In the long run, the result of not managing the factors affecting their diabetes can cause serious consequences. In order to motivate this particular group with diabetes to maintain recommended levels of blood glucose, serious games can be used. The Diabetes Automata project is a part of the research being done on serious games for diabetes at the Norwegian Centre for Integrated Care and Telemedicine. In the project, we have developed a prototype version of a software engine on which diabetes-related serious games, simulators and other tools for diabetes management on various platforms can be based. The Diabetes Automata calculates blood glucose levels based upon relevant patient-gathered data such as insulin, carbohydrates, physical activity, and the user’s biometry. The prototype is not yet evaluated.
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