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dc.contributor.authorMiguel Jiménez, Juan Manuel 
dc.contributor.authorBlanco, R.
dc.contributor.authorSantiago Rodrigo, Luis de 
dc.contributor.authorFernández Rodríguez, Alfredo José 
dc.contributor.authorRodríguez Ascariz, José Manuel 
dc.contributor.authorBarea Navarro, Rafael 
dc.contributor.authorMartín Sánchez, José Luis 
dc.contributor.authorAmo, C.
dc.contributor.authorSánchez Morla, Eva María 
dc.contributor.authorBoquete Vázquez, Luciano 
dc.date.accessioned2021-07-20T12:59:40Z
dc.date.available2021-07-20T12:59:40Z
dc.date.issued2015-04-08
dc.identifier.bibliographicCitationMiguel Jiménez, J.M. et al. 2015, "Continuous‑wavelet‑transform analysis of the multifocal ERG waveform in glaucoma diagnosis", Medical & Biological Engineering & Computing, vol. 53, no. 9, pp. 771-780.
dc.identifier.urihttp://hdl.handle.net/10017/49179
dc.description.abstractThe vast majority of multifocal electroretinogram (mfERG) signal analyses to detect glaucoma study the signals’ amplitudes and latencies. The purpose of this paper is to investigate application of wavelet analysis of mfERG signals in diagnosis of glaucoma. This analysis method applies the continuous wavelet transform (CWT) to the signals, using the real Morlet wavelet. CWT coefficients resulting from the scale of maximum correlation are used as inputs to a neural network, which acts as a classifier. mfERG recordings are taken from the eyes of 47 subjects diagnosed with chronic open-angle glaucoma and from those of 24 healthy subjects. The high sensitivity in the classification (0.894) provides reliable detection of glaucomatous sectors, while the specificity achieved (0.844) reflects accurate detection of healthy sectors. The results obtained in this paper improve on the previous findings reported by the authors using the same visual stimuli and database.en
dc.description.sponsorshipMinisterio de Ciencia e Innovaciónes_ES
dc.format.mimetypeapplication/pdfen
dc.language.isoengen
dc.publisherSpringer
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectGlaucomaen
dc.subjectMultifocal ERGen
dc.subjectContinuous wavelet transformen
dc.subjectNeural networken
dc.titleContinuous‑wavelet‑transform analysis of the multifocal ERG waveform in glaucoma diagnosisen
dc.typeinfo:eu-repo/semantics/articleen
dc.subject.ecienciaElectrónicaes_ES
dc.subject.ecienciaElectronicsen
dc.contributor.affiliationUniversidad de Alcalá. Departamento de Electrónicaes_ES
dc.relation.publisherversionhttps://doi.org/10.1007/s11517-015-1287-6
dc.type.versioninfo:eu-repo/semantics/publishedVersionen
dc.identifier.doi10.1007/s11517-015-1287-6
dc.relation.projectIDinfo:eu-repo/grantAgreement/MICINN//TEC2011-26066/ES/ANALISIS AVANZADO DE LAS SEÑALES DE LOS POTENCIALES EVOCADOS MULTIFOCALES Y DE LA ELECTRORRETINOGRAFIA MULTIFOCAL APLICADOS AL DIAGNOSTICO DE LAS NEUROPATIAS OPTICAS/en
dc.relation.projectIDFIS PI11/00533 (Ministerio de Ciencia e Innovación)
dc.relation.projectIDRETICS RD12/0034/0006 (Ministerio de Ciencia e Innovación)
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessen
dc.identifier.publicationtitleMedical & Biological Engineering & Computing
dc.identifier.publicationvolume53
dc.identifier.publicationlastpage780
dc.identifier.publicationissue9
dc.identifier.publicationfirstpage771


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