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dc.contributor.author | Castro, Daniel |
dc.contributor.author | Félix Lamas, Paulo |
dc.contributor.author | Rodríguez Presedo, Jesús María |
dc.date.accessioned | 2014-10-29T11:10:32Z |
dc.date.available | 2014-10-29T11:10:32Z |
dc.date.issued | 2014-10-08 |
dc.identifier.citation | Castro, D., Félix, P., Presedo, J. (2014). A method for context-based adaptive QRS clustering in real-time. "IEEE Journal of Biomedical and Health Informatics" , [Documento en línea] doi: 10.1109/JBHI.2014.2361659 |
dc.identifier.issn | 2168-2194 |
dc.identifier.uri | http://hdl.handle.net/10347/11733 |
dc.description.abstract | Continuous follow-up of heart condition through long-term electrocardiogram monitoring is an invaluable tool for diagnosing some cardiac arrhythmias. In such context, providing tools for fast locating alterations of normal conduction patterns is mandatory and still remains an open issue. This work presents a real-time method for adaptive clustering QRS complexes from multilead ECG signals that provides the set of QRS morphologies that appear during an ECG recording. The method processes the QRS complexes sequentially, grouping them into a dynamic set of clusters based on the information content of the temporal context. The clusters are represented by templates which evolve over time and adapt to the QRS morphology changes. Rules to create, merge and remove clusters are defined along with techniques for noise detection in order to avoid their proliferation. To cope with beat misalignment, Derivative Dynamic Time Warping is used. The proposed method has been validated against the MIT-BIH Arrhythmia Database and the AHA ECG Database showing a global purity of 98.56% and 99.56%, respectively. Results show that our proposal not only provides better results than previous offline solutions but also fulfills real-time requirements. |
dc.description.sponsorship | This work was supported by the Spanish Ministry of Science and Innovation (MICINN) under grant TIN2009-14372-C03-03. |
dc.language.iso | eng |
dc.publisher | IEEE |
dc.subject | QRS |
dc.subject | Clustering |
dc.subject | ECG |
dc.subject | Electrocardiogram |
dc.subject | Adaptive |
dc.subject | Realtime |
dc.subject | Context-based |
dc.subject | EKG |
dc.subject | Beat |
dc.subject | Heartbeat |
dc.subject.classification | Medical technology |
dc.subject.classification | Pattern recognition |
dc.subject.classification | Data processing |
dc.title | A method for context-based adaptive QRS clustering in real-time |
dc.type | journal article |
dc.relation.publisherversion | http://dx.doi.org/10.1109/JBHI.2014.2361659 |
dc.rights.accessRights | open access |
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