Ashenafi Zebene Woldaregay
Department of Computer Science, University of Tromsø – The Arctic University of Norway, Tromsø, Norway
Eirik Årsand
Norwegian Centre for E-health Research, University Hospital of North Norway, Tromsø, Norway
Alain Giordanengo
Department of Computer Science, University of Tromsø – The Arctic University of Norway, Tromsø, Norway / Norwegian Centre for E-health Research, University Hospital of North Norway, Tromsø, Norway
David Albers
Columbia University, N.Y., USA
Lena Mamykina
Columbia University, N.Y., USA
Taxiarchis Botsis
Department of Computer Science, University of Tromsø – The Arctic University of Norway, Tromsø, Norway
Gunnar Hartvigsen
Department of Computer Science, University of Tromsø – The Arctic University of Norway, Tromsø, Norway / Norwegian Centre for E-health Research, University Hospital of North Norway, Tromsø, Norway
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Published in: Proceedings from The 15th Scandinavian Conference on Health Informatics 2017 Kristiansand, Norway, August 29–30, 2017
Linköping Electronic Conference Proceedings 145:3, p. 14-20
Published: 2018-01-04
ISBN: 978-91-7685-364-1
ISSN: 1650-3686 (print), 1650-3740 (online)
The relation between an infection incident and elevated blood glucose (BG) levels has been known for long time. People with diabetes often experience variable episodes of elevated BG levels up on infections incident. Hence, we proposed an Electronic Disease Surveillance Monitoring Network (EDMON) that uses BG pattern and other relevant parameters to detect infected diabetes individuals during the incubation period. The project is an extension of the results achieved in the mobile diabetes (mDiabetes) field within our research team for the last 15 years. The proposed EDMON system is a kind of public health surveillance, which uses events analysis at individual levels (called micro events) to reach on a conclusion for uncovering events on the general populations (called macro events) based on spatio-temporal cluster detection. It incorporates self-management mobile apps, sensors, wearables, and point of care (POC) devices to collect real-time health information from individuals with Type 1 diabetes. In this paper, we will present the proposed EDMON system architecture along with the design requirements, system components, communication protocols and challenges involved herein.
Type 1 Diabetes, Wireless Communication, BG Pattern Detection, Infection Detection
