Medical Informatics & Telemedicine (MI&T)
The MI&T group was established 1994-95. From the beginning, the group has been responsible for teaching Medical Informatics courses. Since the formation of the group, it has been closely connection to NST (Norwegian Centre for Integrated Care and Telemedicine). Our research approach is experimental with a focus on technology (artefacts).
Description of research activities
The work within this area started in 1997-1998. The research in the Medical informatics & telemedicine group mainly focuses on (1) telemedicine systems for private homes and telecare/telehomecare systems, (2) distributed electronic health record (3), patient diary / EHR for children and (4) electronic health surveillance. All projects are done in cooperation with, or closely connected to, the Norwegian Centre for Telemedicine, University Hospital of North Norway. Students in the MI&T group participate in construction of medical & telemedicine systems from a computer science perspective.
The MI&T group members are involved in the following TTL research areas:
- Integrated Medical Sensors include research on sensors monitoring vital health parameters (e.g. ECG, blood glucose) and sensors for motivational health purposes (e.g. physical activity and eating habits). The sensors and sensor-based systems use both wearable and stationary sensors. In addition, interpretation of sensor data is addressed.
- Health Terminals for Personalized Health Care is a growing area in the health sector. Research contributions from this area include: Tools and procedures for improved regulation of diabetic patients, and tools and procedures for monitoring and control of patients with chronic diseases.
- Health Intelligence is defined as use and development of knowledge to improve the health of the population. In this research area, we focus on disease surveillance systems and how such systems can be used for the benefit of different patient groups. Furthermore, we address the development of methods for detection of deviations in spatio-temporal patterns of syndromic data, and develop models for spreads of infectious and non-infectious diseases for the purpose of prediction.