Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/41760
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dc.contributor.authorMartín-González, Sofíaen_US
dc.contributor.authorNavarro-Mesa, Juan L.en_US
dc.contributor.authorJuliá-Serdá, Gabrielen_US
dc.contributor.authorRamirez-Avila, G. Marceloen_US
dc.contributor.authorRavelo-García, Antonio G.en_US
dc.date.accessioned2018-08-03T15:29:15Z-
dc.date.available2018-08-03T15:29:15Z-
dc.date.issued2018en_US
dc.identifier.issn1932-6203en_US
dc.identifier.urihttp://hdl.handle.net/10553/41760-
dc.description.abstractOur contribution focuses on the characterization of sleep apnea from a cardiac rate point of view, using Recurrence Quantification Analysis (RQA), based on a Heart Rate Variability (HRV) feature selection process. Three parameters are crucial in RQA: those related to the embedding process (dimension and delay) and the threshold distance. There are no overall accepted parameters for the study of HRV using RQA in sleep apnea. We focus on finding an overall acceptable combination, sweeping a range of values for each of them simultaneously. Together with the commonly used RQA measures, we include features related to recurrence times, and features originating in the complex network theory. To the best of our knowledge, no author has used them all for sleep apnea previously. The best performing feature subset is entered into a Linear Discriminant classifier. The best results in the "Apnea-ECG Physionet database" and the "HuGCDN2014 database" are, according to the area under the receiver operating characteristic curve, 0.93 (Accuracy: 86.33%) and 0.86 (Accuracy: 84.18%), respectively. Our system outperforms, using a relatively small set of features, previously existing studies in the context of sleep apnea. We conclude that working with dimensions around 7-8 and delays about 4-5, and using for the threshold distance the Fixed Amount of Nearest Neighbours (FAN) method with 5% of neighbours, yield the best results. Therefore, we would recommend these reference values for future work when applying RQA to the analysis of HRV in sleep apnea. We also conclude that, together with the commonly used vertical and diagonal RQA measures, there are newly used features that contribute valuable information for apnea minutes discrimination. Therefore, they are especially interesting for characterization purposes. Using two different databases supports that the conclusions reached are potentially generalizable, and are not limited by database variability.en_US
dc.languageengen_US
dc.relationMAC/1/C121en_US
dc.relation.ispartofPLoS ONEen_US
dc.sourcePLoS ONE [ISSN 1932-6203], v. 13 (e0194462)en_US
dc.subject3314 Tecnología médicaen_US
dc.subject.otherHeart-Rate-Variabilityen_US
dc.subject.otherCardiovascular-Systemen_US
dc.subject.otherEmbedding Dimensionen_US
dc.subject.otherNonlinear Dynamicsen_US
dc.subject.otherNetwork Physiologyen_US
dc.subject.otherTimeen_US
dc.subject.otherComplexen_US
dc.subject.otherElectrocardiogramen_US
dc.subject.otherAlgorithmen_US
dc.subject.otherSelectionen_US
dc.titleImproving the understanding of sleep apnea characterization using Recurrence Quantification Analysis by defining overall acceptable values for the dimensionality of the system, the delay, and the distance thresholden_US
dc.typeinfo:eu-repo/semantics/Articleen_US
dc.typeArticleen_US
dc.identifier.doi10.1371/journal.pone.0194462en_US
dc.identifier.scopus85045133945-
dc.identifier.isi000429206800018-
dc.contributor.authorscopusid16069177700-
dc.contributor.authorscopusid9634488300-
dc.contributor.authorscopusid6603171553-
dc.contributor.authorscopusid23969068000-
dc.contributor.authorscopusid9634135600-
dc.identifier.issue4-
dc.description.firstpagee0194462en_US
dc.relation.volume13en_US
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Artículoen_US
dc.contributor.daisngid4774892-
dc.contributor.daisngid2630721-
dc.contributor.daisngid2942583-
dc.contributor.daisngid3068581-
dc.contributor.daisngid1986395-
dc.utils.revisionen_US
dc.contributor.wosstandardWOS:Martin-Gonzalez, S-
dc.contributor.wosstandardWOS:Navarro-Mesa, JL-
dc.contributor.wosstandardWOS:Julia-Serda, G-
dc.contributor.wosstandardWOS:Ramirez-Avila, GM-
dc.contributor.wosstandardWOS:Ravelo-Garcia, AG-
dc.date.coverdateAbril 2018en_US
dc.identifier.ulpgcen_US
dc.contributor.buulpgcBU-TELen_US
dc.description.sjr1,1
dc.description.jcr2,776
dc.description.sjrqQ1
dc.description.jcrqQ2
dc.description.scieSCIE
dc.description.erihplusERIH PLUS
item.grantfulltextopen-
item.fulltextCon texto completo-
crisitem.author.deptGIR IDeTIC: División de Procesado Digital de Señales-
crisitem.author.deptIU para el Desarrollo Tecnológico y la Innovación-
crisitem.author.deptDepartamento de Señales y Comunicaciones-
crisitem.author.deptGIR IDeTIC: División de Procesado Digital de Señales-
crisitem.author.deptIU para el Desarrollo Tecnológico y la Innovación-
crisitem.author.deptDepartamento de Señales y Comunicaciones-
crisitem.author.deptDepartamento de Señales y Comunicaciones-
crisitem.author.deptGIR IDeTIC: División de Procesado Digital de Señales-
crisitem.author.deptIU para el Desarrollo Tecnológico y la Innovación-
crisitem.author.deptDepartamento de Señales y Comunicaciones-
crisitem.author.orcid0000-0002-5001-9223-
crisitem.author.orcid0000-0003-3860-3424-
crisitem.author.orcid0000-0002-8512-965X-
crisitem.author.parentorgIU para el Desarrollo Tecnológico y la Innovación-
crisitem.author.parentorgIU para el Desarrollo Tecnológico y la Innovación-
crisitem.author.parentorgIU para el Desarrollo Tecnológico y la Innovación-
crisitem.author.fullNameMartín González, Sofía Isabel-
crisitem.author.fullNameNavarro Mesa, Juan Luis-
crisitem.author.fullNameRavelo García, Antonio Gabriel-
Colección:Artículos
miniatura
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