Searching biosignal databases by content and context: Research Oriented Integration System for ECG Signals (ROISES)

Authors:
Alexandra Kokkinaki;Ioanna Chouvarda;Nicos Maglaveras
Affiliations:
Lab. of Medical Informatics, The Medical School, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece;Lab. of Medical Informatics, The Medical School, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece;Lab. of Medical Informatics, The Medical School, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
Venue:
Computer Methods and Programs in Biomedicine
Year:
2012

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Abstract

Technological advances in textile, biosensor and electrocardiography domain induced the wide spread use of bio-signal acquisition devices leading to the generation of massive bio-signal datasets. Among the most popular bio-signals, electrocardiogram (ECG) possesses the longest tradition in bio-signal monitoring and recording, being a strong and relatively robust signal. As research resources are fostered, research community promotes the need to extract new knowledge from bio-signals towards the adoption of new medical procedures. However, integrated access, query and management of ECGs are impeded by the diversity and heterogeneity of bio-signal storage data formats. In this scope, the proposed work introduces a new methodology for the unified access to bio-signal databases and the accompanying metadata. It allows decoupling information retrieval from actual underlying datasource structures and enables transparent content and context based searching from multiple data resources. Our approach is based on the definition of an interactive global ontology which manipulates the similarities and the differences of the underlying sources to either establish similarity mappings or enrich its terminological structure. We also introduce ROISES (Research Oriented Integration System for ECG Signals), for the definition of complex content based queries against the diverse bio-signal data sources.