An Ontology Approach for Knowledge Representation of ECG Data.
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The number of features that can be extracted from ECG signals has increased with the advancement in signal processing techniques. At the same time, there is an increase in research efforts to support efficient and effective analysis and interpretation of these signals. In this paper, we propose the use of ontology for knowledge representation and discovery of ECG data. Given the lack of a widely acceptable standards, the use of ontology can support the establishment of common understanding of the kind of knowledge that can be extracted from the ECG data and shared among various heterogeneous systems. The proposed ontology is both platform and application independent. Furthermore, it is possible to enrich the proposed ontology with new knowledge that may not explicitly be expressed in the data.
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