000048707 001__ 48707 000048707 005__ 20210121114518.0 000048707 0247_ $$2doi$$a10.1109/CIC.2015.7411038 000048707 0248_ $$2sideral$$a94574 000048707 037__ $$aART-2015-94574 000048707 041__ $$aeng 000048707 100__ $$0(orcid)0000-0002-0166-2837$$aAlcaine, A.$$uUniversidad de Zaragoza 000048707 245__ $$aEstimation of high-density activation maps during atrial fibrillation 000048707 260__ $$c2015 000048707 5060_ $$aAccess copy available to the general public$$fUnrestricted 000048707 5203_ $$aThe study of activation maps using multi-electrode arrays (MEA) can help to understand atrial fibrillation (AF) mechanisms. Activation mapping based on recorded unipolar electrograms (u-EGM) rely on the local activation time (LAT) detector, which has a limited robustness, accuracy, and generally requires manual post-edition. In general, LAT detection ignores spatiotemporal information about activation and conduction conveyed by the relation between signals of the MEA sensor. This work proposes an approach to construct activation maps by simultaneous analysis of u-EGMs from small clusters of MEA electrodes. The algorithm iteratively fits an activation pattern model to the acquired data. Accuracy was evaluated by comparing with audited maps created by expert electrophysiologists from a patient undergoing open-chest surgery during AF. The estimation error was -0.29 ± 6.01 ms (236 maps, 28369 LATs) with high correlation (¿ = 0.93). Therefore, activation maps can be decomposed into local activation patterns derived from fitting an activation model, resulting in smooth and comprehensive high-density activation maps. 000048707 536__ $$9info:eu-repo/grantAgreement/ES/MINECO/BES-2011-046644$$9info:eu-repo/grantAgreement/ES/MINECO/EEBB-I-13-06613$$9info:eu-repo/grantAgreement/ES/MINECO/TEC2013-42140-R 000048707 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/ 000048707 592__ $$a0.294$$b2015 000048707 593__ $$aComputer Science (miscellaneous)$$c2015 000048707 593__ $$aCardiology and Cardiovascular Medicine$$c2015 000048707 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion 000048707 700__ $$aDe Groot, N.M.S. 000048707 700__ $$0(orcid)0000-0003-3434-9254$$aLaguna, P.$$uUniversidad de Zaragoza 000048707 700__ $$0(orcid)0000-0002-7503-3339$$aMartínez, J.P.$$uUniversidad de Zaragoza 000048707 700__ $$aHouben, R.P.M. 000048707 7102_ $$15008$$2800$$aUniversidad de Zaragoza$$bDpto. Ingeniería Electrón.Com.$$cÁrea Teoría Señal y Comunicac. 000048707 773__ $$g42 (2015), 825-828$$pComput. cardiol.$$tComputing in Cardiology$$x2325-8861 000048707 8564_ $$s1597094$$uhttps://zaguan.unizar.es/record/48707/files/texto_completo.pdf$$yVersión publicada 000048707 8564_ $$s108392$$uhttps://zaguan.unizar.es/record/48707/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada 000048707 909CO $$ooai:zaguan.unizar.es:48707$$particulos$$pdriver 000048707 951__ $$a2021-01-21-11:01:02 000048707 980__ $$aARTICLE