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Project description

The aim of “360 Degree Health Data Integration” (HealthD360) is to develop an integrated data platform that combines today’s fragmented landscape of health-related data sources – in particular from various wearable sensors – for coherent, personalized treatment. This encompasses the collection, fusion, and analysis of such data, as well as its integration with established health care IT systems to combine traditional patient records with readily available streams of vital parameters, recognized physical activities and other events for providing tailored data-driven diagnoses and treatments. Within the scope of this project, this platform will be designed and tested for three use cases: for supporting and monitoring maternal and fetal health during pregnancy, for prevention and intervention in cases of mental and metabolic health problems, and for detecting and reducing the risk of chronical wounds. The research conducted by the Ubiquitous Computing and Interaction group concerns in particular all aspects of health data analysis, specifically the visual analysis and machine learning for longitudinal data to enable real-time analysis support. Of specific interest is the possibility to use the produced analysis results for providing continuous feedback to the individual patients about their condition.