99442 20230914083818.0 doi 10.22489/CinC.2020.434 sideral 123038 ART-2020-123038 eng Riccio, Jennifer Universidad de Zaragoza (orcid)0000-0002-6264-4229 Unipolar Electrogram Eigenvalue Distribution Analysis for the Identification of Atrial Fibrosis 2020 Access copy available to the general public Unrestricted Atrial fibrosis plays an important role in the pathogenesis of atrial fibrillation (AF). Low bipolar electrograms (b-EGMs) peak-to-peak voltage areas indicate scar tissue and are considered targets for AF substrate ablation. However, this approach ignores the spatiotemporal information embedded in the signal and the dependence of b-EGMs on catheter orientation. This work proposes an approach to detect fibrosis based on the eigenvalue dominance ratio (EIGDR) in an ensemble (clique) of unipolar electrograms (u-EGMs). A 2-D tissue with a central circular patch of fibrosis has been simulated using the Courtemanche cellular model. Maps of EIGDR have been computed using two sizes of electrode cliques, from the original u-EGMs within the ensemble or after a time alignment of these signals. Performance of each map in detecting fibrosis has been evaluated using receiver operating characteristic curves and detection accuracy. Best results achieve an area under the curve (AUC) of 0.98 and an accuracy (ACC) of 1 when we use as marker the gain in eigenvalue dominance produced by the ensemble alignment. info:eu-repo/grantAgreement/ES/DGA-FSE/T39-20R-BSICoS group info:eu-repo/grantAgreement/EC/H2020/766082/EU/MultidisciplinarY training network for ATrial fibRillation monItoring, treAtment and progression/MY-ATRIA This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 766082-MY-ATRIA info:eu-repo/grantAgreement/ES/MICINN/PID2019-104881RB-I00 info:eu-repo/semantics/openAccess by http://creativecommons.org/licenses/by/3.0/es/ 0.257 2020 Computer Science (miscellaneous) 2020 Cardiology and Cardiovascular Medicine 2020 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Rocher Ventura, Sara Martínez Mateu, Laura Alcaine Otín, Alejandro (orcid)0000-0002-0166-2837 Sáiz Rodríguez, Javier Martínez Cortés, Juan Pablo Universidad de Zaragoza (orcid)0000-0002-7503-3339 Laguna Lasaosa, Pablo Universidad de Zaragoza (orcid)0000-0003-3434-9254 5008 800 Universidad de Zaragoza Dpto. Ingeniería Electrón.Com. Área Teoría Señal y Comunicac. 47 (2020), [ 4 pp.] Comput. cardiol. Computing in Cardiology 2325-8861 883113 http://zaguan.unizar.es/record/99442/files/texto_completo.pdf Versión publicada 2692825 http://zaguan.unizar.es/record/99442/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:99442 articulos driver 2023-09-13-15:32:51 ARTICLE