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Atrial location optimization by electrical measures for Electrocardiographic Imaging

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Atrial location optimization by electrical measures for Electrocardiographic Imaging

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dc.contributor.author Gisbert Soler, Víctor es_ES
dc.contributor.author Jiménez-Serrano, Santiago es_ES
dc.contributor.author Roses-Albert, Eduardo es_ES
dc.contributor.author RODRIGO BORT, MIGUEL es_ES
dc.date.accessioned 2021-04-23T03:31:13Z
dc.date.available 2021-04-23T03:31:13Z
dc.date.issued 2020-12 es_ES
dc.identifier.issn 0010-4825 es_ES
dc.identifier.uri http://hdl.handle.net/10251/165515
dc.description.abstract [EN] Background: The Electrocardiographic Imaging (ECGI) technique, used to non-invasively reconstruct the epicardial electrical activity, requires an accurate model of the atria and torso anatomy. Here we evaluate a new automatic methodology able to locate the atrial anatomy within the torso based on an intrinsic electrical parameter of the ECGI solution. Methods: In 28 realistic simulations of the atrial electrical activity, we randomly displaced the atrial anatomy for +/- 2.5 cm and +/- 30 degrees on each axis. An automatic optimization method based on the L-curve curvature was used to estimate the original position using exclusively non-invasive data. Results: The automatic optimization algorithm located the atrial anatomy with a deviation of 0.5 +/- 0.5 cm in position and 16.0 +/- 10.7 degrees in orientation. With these approximate locations, the obtained electrophysiological maps reduced the average error in atrial rate measures from 1.1 +/- 1.1 Hz to 0.5 +/- 1.0 Hz and in the phase singularity position from 7.2 +/- 4.0 cm to 1.6 +/- 1.7 cm (p < 0.01). Conclusions: This proposed automatic optimization may help to solve spatial inaccuracies provoked by cardiac motion or respiration, as well as to use ECGI on torso and atrial anatomies from different medical image systems. es_ES
dc.description.sponsorship This work was supported in part by: Generalitat Valenciana Grants [APOSTD/2017] and projects [GVA/2018/103]; Nvidia Corporation with GPU QUADRO P6000 donation. es_ES
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation.ispartof Computers in Biology and Medicine es_ES
dc.rights Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) es_ES
dc.subject Inverse problem es_ES
dc.subject L-curve curvature es_ES
dc.subject Electrophysiology es_ES
dc.subject Mapping es_ES
dc.subject Dominant frequency es_ES
dc.subject Phase analysis es_ES
dc.subject Reentry es_ES
dc.subject Rotor es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.subject.classification TECNOLOGIA ELECTRONICA es_ES
dc.subject.classification ESTADISTICA E INVESTIGACION OPERATIVA es_ES
dc.title Atrial location optimization by electrical measures for Electrocardiographic Imaging es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.compbiomed.2020.104031 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/GVA//APOSTD%2F2017%2F068/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/GVA//GV%2F2018%2F103/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto Universitario de Aplicaciones de las Tecnologías de la Información - Institut Universitari d'Aplicacions de les Tecnologies de la Informació es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Estadística e Investigación Operativa Aplicadas y Calidad - Departament d'Estadística i Investigació Operativa Aplicades i Qualitat es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Electrónica - Departament d'Enginyeria Electrònica es_ES
dc.description.bibliographicCitation Gisbert Soler, V.; Jiménez-Serrano, S.; Roses-Albert, E.; Rodrigo Bort, M. (2020). Atrial location optimization by electrical measures for Electrocardiographic Imaging. Computers in Biology and Medicine. 127:1-8. https://doi.org/10.1016/j.compbiomed.2020.104031 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1016/j.compbiomed.2020.104031 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 8 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 127 es_ES
dc.relation.pasarela S\419922 es_ES
dc.contributor.funder Nvidia es_ES
dc.contributor.funder Generalitat Valenciana es_ES
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