Authors:
John Puentes
1
and
Jaakko Lähteenmäki
2
Affiliations:
1
Institut Telecom and Telecom Bretagne, France
;
2
VTT Technical Research Center of Finland, Finland
Keyword(s):
Body monitoring, Personal health record, Physiological sensors, Heterogeneous data integration, Knowledge model, Data understanding.
Related
Ontology
Subjects/Areas/Topics:
Biomedical Engineering
;
Data Engineering
;
Electronic Health Records and Standards
;
Enterprise Information Systems
;
Health Information Systems
;
Information Systems Analysis and Specification
;
Knowledge Management
;
Ontologies and the Semantic Web
;
Pervasive Health Systems and Services
;
Society, e-Business and e-Government
;
Web Information Systems and Technologies
Abstract:
Personal Health Records (PHR) containing physiological data collected by multiple sensors are being increasingly used for wellness monitoring or disease management. These abundant complementary raw data could be nevertheless disregarded given the challenges to understand and process it. We propose a knowledge-based integration model of PHR data from sensors and personal observations, intended to facilitate decision support in scenarios of cardiovascular disease monitoring. The model relates knowledge at three data integration layers: elements identification, relations assessment, and refinement. Details on specific elements of each layer are provided, along with a discussion of use and implementation guidelines.