Please use this identifier to cite or link to this item:
http://hdl.handle.net/10553/44004
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Travieso, Carlos M. | en_US |
dc.contributor.author | Alonso, Jesús B. | en_US |
dc.contributor.author | del Pozo-Baños, Marcos | en_US |
dc.contributor.author | Ticay-Rivas, Jaime R. | en_US |
dc.contributor.author | Lopez-de-Ipiña, Karmele | en_US |
dc.contributor.other | Alonso-Hernandez, Jesus B. | - |
dc.contributor.other | Lopez-de-Ipina, Karmele | - |
dc.contributor.other | del Pozo Banos, Marcos | - |
dc.contributor.other | Travieso-Gonzalez, Carlos M. | - |
dc.date.accessioned | 2018-11-21T19:30:15Z | - |
dc.date.available | 2018-11-21T19:30:15Z | - |
dc.date.issued | 2013 | en_US |
dc.identifier.issn | 1866-9956 | en_US |
dc.identifier.uri | http://hdl.handle.net/10553/44004 | - |
dc.description.abstract | A new approach based on the transformation of the Cepstral domain is developed on this work. This approach reaches an automatic diagnosis for the syndrome of obstructive sleep apnea that includes a specific block for the removal of electrocardiogram (ECG) artifacts and the R wave detection. The system is modeled by a transformation of the Cepstral domain sequence using hidden Markov model (HMM). The final decision is done with two different approaches: one based on HMM as a classifier and a second one based on support vector machines classification and a parameterization based on the transformation of HMM by a kernel. The later approach reached results up to 99.23 %, using all test samples from Physionet Apnea-ECG Database. | en_US |
dc.language | spa | en_US |
dc.publisher | 1866-9956 | - |
dc.relation.ispartof | Cognitive Computation | en_US |
dc.source | Cognitive Computation[ISSN 1866-9956],v. 5, p. 558-565 | en_US |
dc.subject | 3307 Tecnología electrónica | en_US |
dc.subject.other | Automatic apnea detection Artifacts removal Hidden Markov model Kernel building Machine learning Pattern recognition Nonlinear processing | en_US |
dc.title | Automatic Apnea Identification by Transformation of the Cepstral Domain | en_US |
dc.type | info:eu-repo/semantics/Article | es |
dc.type | Article | es |
dc.identifier.doi | 10.1007/s12559-012-9184-x | |
dc.identifier.scopus | 84890114409 | - |
dc.identifier.isi | 000328221100016 | - |
dcterms.isPartOf | Cognitive Computation | - |
dcterms.source | Cognitive Computation[ISSN 1866-9956],v. 5 (4), p. 558-565 | - |
dc.contributor.authorscopusid | 6602376272 | - |
dc.contributor.authorscopusid | 24774957200 | - |
dc.contributor.authorscopusid | 35241841700 | - |
dc.contributor.authorscopusid | 37862263900 | - |
dc.contributor.authorscopusid | 56263484400 | - |
dc.description.lastpage | 565 | - |
dc.description.firstpage | 558 | - |
dc.relation.volume | 5 | - |
dc.investigacion | Ingeniería y Arquitectura | en_US |
dc.type2 | Artículo | en_US |
dc.identifier.wos | WOS:000328221100016 | - |
dc.contributor.daisngid | 265761 | - |
dc.contributor.daisngid | 418703 | - |
dc.contributor.daisngid | 2996557 | - |
dc.contributor.daisngid | 3828233 | - |
dc.contributor.daisngid | 1399740 | - |
dc.identifier.investigatorRID | N-5977-2014 | - |
dc.identifier.investigatorRID | K-4379-2013 | - |
dc.identifier.investigatorRID | R-8617-2016 | - |
dc.identifier.investigatorRID | N-5967-2014 | - |
dc.identifier.external | WOS:000328221100016 | - |
dc.contributor.wosstandard | WOS:Travieso, CM | |
dc.contributor.wosstandard | WOS:Alonso, JB | |
dc.contributor.wosstandard | WOS:del Pozo-Banos, M | |
dc.contributor.wosstandard | WOS:Ticay-Rivas, JR | |
dc.contributor.wosstandard | WOS:Lopez-de-Ipina, K | |
dc.date.coverdate | Diciembre 2013 | |
dc.identifier.ulpgc | Sí | es |
dc.description.sjr | 0,518 | |
dc.description.jcr | 1,1 | |
dc.description.sjrq | Q2 | |
dc.description.jcrq | Q3 | |
dc.description.scie | SCIE | |
item.grantfulltext | none | - |
item.fulltext | Sin texto completo | - |
crisitem.author.dept | GIR IDeTIC: División de Procesado Digital de Señales | - |
crisitem.author.dept | IU para el Desarrollo Tecnológico y la Innovación | - |
crisitem.author.dept | Departamento de Señales y Comunicaciones | - |
crisitem.author.dept | GIR IDeTIC: División de Procesado Digital de Señales | - |
crisitem.author.dept | IU para el Desarrollo Tecnológico y la Innovación | - |
crisitem.author.dept | Departamento de Señales y Comunicaciones | - |
crisitem.author.orcid | 0000-0002-4621-2768 | - |
crisitem.author.orcid | 0000-0002-7866-585X | - |
crisitem.author.parentorg | IU para el Desarrollo Tecnológico y la Innovación | - |
crisitem.author.parentorg | IU para el Desarrollo Tecnológico y la Innovación | - |
crisitem.author.fullName | Travieso González, Carlos Manuel | - |
crisitem.author.fullName | Alonso Hernández, Jesús Bernardino | - |
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