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<dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:invenio="http://invenio-software.org/elements/1.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>doi:10.23919/CinC49843.2019.9005931</dc:identifier><dc:language>eng</dc:language><dc:creator>Riccio, J.</dc:creator><dc:creator>Alcaine, A.</dc:creator><dc:creator>De Groot, N.M.S.</dc:creator><dc:creator>Houben, R.</dc:creator><dc:creator>Laguna, P.</dc:creator><dc:creator>Martínez, J.P.</dc:creator><dc:title>Characterization of Propagation Patterns with Omnipolar EGM in Epicardial Multi-Electrode Arrays</dc:title><dc:identifier>ART-2019-121998</dc:identifier><dc:description>Omnipolar Electrogram (OP-EGM) is a recently proposed technique to characterize myocardial propagation in multi-electrode catheters regardless of the angle between propagation direction and catheter bipolar. This work aims to evaluate the accuracy of atrial propagation parameters obtained with OP-EGM in sinus rhythm (SR) and in different patterns of atrial fibrillation (AF).Real and simulated unipolar electrograms (u-EGMs) were used in this study. For both types of data, conduction velocity was obtained for each clique of 4 neighbour electrodes using OP-EGM. As a reference, conduction velocity was also computed from local activation times (LATs) using a linear propagation model.Analysis of simulated data showed that conduction velocity had good concordance with propagation patterns for both estimations, although the LAT-based errors were lower in most of the cases. When conduction velocity magnitude (CV) was 1 mm/ms, its estimation errors (expressed as mean ± std) calculated with OP-EGM and from LATs were 0.053 ± 0.005 mm/ms and 0.003 ±2.1 ×10-5 mm/ms, respectively, when focus was at 30 mm from the bottom of the tissue slice, while propagation direction angular errors were 6.64 ± 4.3°and 4.35 ± 2.8°. In real data, maps obtained with OP-EGM presented smoother and more coherent patterns than those based on LATs.</dc:description><dc:date>2019</dc:date><dc:source>http://zaguan.unizar.es/record/98280</dc:source><dc:doi>10.23919/CinC49843.2019.9005931</dc:doi><dc:identifier>http://zaguan.unizar.es/record/98280</dc:identifier><dc:identifier>oai:zaguan.unizar.es:98280</dc:identifier><dc:relation>info:eu-repo/grantAgreement/EC/H2020/766082/EU/MultidisciplinarY training network for ATrial fibRillation monItoring, treAtment and progression/MY-ATRIA</dc:relation><dc:relation>This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 766082-MY-ATRIA</dc:relation><dc:identifier.citation>Computing in Cardiology 46 (2019), [4 pp]</dc:identifier.citation><dc:rights>by</dc:rights><dc:rights>http://creativecommons.org/licenses/by/3.0/es/</dc:rights><dc:rights>info:eu-repo/semantics/openAccess</dc:rights></dc:dc>

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