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Central tendency measure and wavelet transform combined in the non-invasive analysis of atrial fibrillation recordings

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Central tendency measure and wavelet transform combined in the non-invasive analysis of atrial fibrillation recordings

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dc.contributor.author Alcaraz, Raúl es_ES
dc.contributor.author Rieta Ibañez, José Joaquín es_ES
dc.date.accessioned 2014-12-11T12:47:56Z
dc.date.available 2014-12-11T12:47:56Z
dc.date.issued 2012-08-09
dc.identifier.issn 1475-925X
dc.identifier.uri http://hdl.handle.net/10251/45358
dc.description.abstract Background Atrial fibrillation (AF) is the most common supraventricular arrhythmia in the clinical practice, being the subject of intensive research. Methods The present work introduces two different Wavelet Transform (WT) applications to electrocardiogram (ECG) recordings of patients in AF. The first one predicts spontaneous termination of paroxysmal AF (PAF), whereas the second one deals with the prediction of electrical cardioversion (ECV) outcome in persistent AF patients. In both cases, the central tendency measure (CTM) from the first differences scatter plot was applied to the AF wavelet decomposition. In this way, the wavelet coefficients vector CTM associated to the AF frequency scale was used to assess how atrial fibrillatory (f) waves variability can be related to AF events. Results Structural changes into the f waves can be assessed by combining WT and CTM to reflect atrial activity organization variation. This fact can be used to predict organization-related events in AF. To this respect, results in the prediction of PAF termination regarding sensitivity, specificity and accuracy were 100%, 91.67% and 96%, respectively. On the other hand, for ECV outcome prediction, 82.93% sensitivity, 90.91% specificity and 85.71% accuracy were obtained. Hence, CTM has reached the highest diagnostic ability as a single predictor published to date. Conclusions Results suggest that CTM can be considered as a promising tool to characterize non-invasive AF signals. In this sense, therapeutic interventions for the treatment of paroxysmal and persistent AF patients could be improved, thus, avoiding useless procedures and minimizing risks. es_ES
dc.description.sponsorship This work was supported by the projects TEC2010-20633 from the Spanish Ministry of Science and Innovation and PPII11-0194-8121 and PII1C09-0036-3237 from Junta de Comunidades de Castilla-La Mancha. en_EN
dc.language Inglés es_ES
dc.publisher BioMed Central es_ES
dc.relation Spanish Ministry of Science and Innovation [TEC2010-20633] es_ES
dc.relation Junta de Comunidades de Castilla-La Mancha [PPII11-0194-8121, PII1C09-0036-3237] es_ES
dc.relation.ispartof BioMedical Engineering OnLine es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Atrial Fibrillation es_ES
dc.subject Central Tendency Measure es_ES
dc.subject Electrical Cardioversion es_ES
dc.subject Electrocardiogram es_ES
dc.subject Wavelet Transform es_ES
dc.subject.classification TECNOLOGIA ELECTRONICA es_ES
dc.title Central tendency measure and wavelet transform combined in the non-invasive analysis of atrial fibrillation recordings es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1186/1475-925X-11-46
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Electrónica - Departament d'Enginyeria Electrònica es_ES
dc.contributor.affiliation Universitat Politècnica de València. Grupo de ingeniería en bioseñales e imagen radiológica es_ES
dc.description.bibliographicCitation Alcaraz, R.; Rieta Ibañez, JJ. (2012). Central tendency measure and wavelet transform combined in the non-invasive analysis of atrial fibrillation recordings. BioMedical Engineering OnLine. 11(46):1-19. doi:10.1186/1475-925X-11-46 es_ES
dc.description.accrualMethod Senia es_ES
dc.relation.publisherversion http://dx.doi.org/10.1186/1475-925X-11-46 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 19 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 11 es_ES
dc.description.issue 46 es_ES
dc.relation.senia 239059
dc.identifier.pmid 22877316 en_EN
dc.identifier.pmcid PMC3444389 en_EN


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