Causality analysis of atrial fibrillation electrograms

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dc.contributor.author Luengo García, David
dc.contributor.author Ríos Muñoz, Gonzalo Ricardo
dc.contributor.author Elvira Arregui, Víctor
dc.date.accessioned 2022-05-16T14:06:44Z
dc.date.available 2022-05-16T14:06:44Z
dc.date.issued 2015-09-06
dc.identifier.bibliographicCitation 2015 Computing in Cardiology Conference (CinC 2015), September 6-9, 2015, Nice, France (pp. 585-588.) Estados Unidos: IEEE.
dc.identifier.isbn 978-1-5090-0684-7 (online)
dc.identifier.isbn 978-1-5090-0685-4 (print)
dc.identifier.issn 2325-887X-3 (online)
dc.identifier.issn 2325-8861-2 (print)
dc.identifier.uri http://hdl.handle.net/10016/34814
dc.description Proceeding of 2015 Computing in Cardiology Conference (CinC 2015), September 6-9, 2015, Nice, France
dc.description.abstract Multi-channel intracardiac electrocardiograms (electrograms) are sequentially acquired during heart surgery performed on patients with sustained atrial fibrillation (AF) to guide radio frequency catheter ablation. These electrograms are used by cardiologists to determine candidate areas for ablation (e.g., areas corresponding to high dominant frequencies or complex electrograms). In this paper, we introduce a novel hierarchical causality analysis method for the multi-output sequentially acquired electrograms. The causal model obtained provides important information regarding delays among signals as well as the direction and strength of their causal connections. The tool developed may ultimately serve to guide cardiologists towards candidate areas for catheter ablation. Preliminary results on synthetic signals are used to validate the proposed approach.
dc.description.sponsorship This work has been supported by the Spanish government’s projects ALCIT (TEC2012-38800-C03-01), AGES (S2010/BMD-2422), and OTOSiS (TEC2013-41718-R), and COMPREHENSION (TEC2012-38883-C02-01). D. Luengo has also been funded by the BBVA Foundation’s “I Convocatoria de Ayudas Fundación BBVA a Investigadores, Innovadores y Creadores Culturales”.
dc.format.extent 4
dc.language.iso eng
dc.publisher IEEE
dc.rights ©2015 IEEE
dc.subject.other Silicon
dc.subject.other Reactive power
dc.subject.other Catheters
dc.subject.other Heart
dc.subject.other Standards
dc.subject.other Sensors
dc.subject.other Rotors
dc.title Causality analysis of atrial fibrillation electrograms
dc.type conferenceObject
dc.type bookPart
dc.description.status Publicado
dc.subject.eciencia Biología y Biomedicina
dc.identifier.doi https://doi.org/10.1109/CIC.2015.7410978
dc.rights.accessRights openAccess
dc.relation.projectID Gobierno de España. TEC2012-38800-C03-01/ALCIT
dc.relation.projectID Gobierno de España. S2010/BMD-2422/AGES
dc.relation.projectID Gobierno de España. TEC2013-41718-R/OTOSiS
dc.relation.projectID Gobierno de España. TEC2012-38883-C02-01/COMPREHENSION
dc.type.version acceptedVersion
dc.relation.eventdate September 6-9,2015
dc.relation.eventplace Niza, Francia
dc.relation.eventtitle Computing in Cardiology (CinC 2015), 42nd Annual Conference, 6-9 September, 2015
dc.relation.eventtype proceeding
dc.identifier.publicationfirstpage 585
dc.identifier.publicationlastpage 588
dc.identifier.publicationtitle 2015 Computing in Cardiology Conference (CinC), September 6-9, 2015, Nice, France
dc.identifier.uxxi CC/0000033183
dc.contributor.funder Ministerio de Economía y Competitividad (España)
dc.affiliation.dpto UC3M. Departamento de Teoría de la Señal y Comunicaciones
dc.affiliation.grupoinv UC3M. Grupo de Investigación: Tratamiento de la Señal y Aprendizaje (GTSA)
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