Por favor, use este identificador para citar o enlazar este ítem: https://hdl.handle.net/11000/30687
Registro completo de metadatos
Campo DC Valor Lengua/Idioma
dc.contributor.authorSorinas Nerin, Jennifer-
dc.contributor.authorGrima Murcia, Mª Dolores-
dc.contributor.authorMinguillon, Jesus-
dc.contributor.authorSánchez Ferrer, Francisco-
dc.contributor.authorVal Calvo, Mikel-
dc.contributor.authorFerrández, Jose Manuel-
dc.contributor.authorFernández, Eduardo-
dc.contributor.otherDepartamentos de la UMH::Farmacología, Pediatría y Química Orgánicaes_ES
dc.date.accessioned2024-01-26T10:01:34Z-
dc.date.available2024-01-26T10:01:34Z-
dc.date.created2017-
dc.identifier.isbn978-3-319-59739-3-
dc.identifier.isbn978-3-319-59740-9-
dc.identifier.issn0302-9743-
dc.identifier.issn1611-3349-
dc.identifier.urihttps://hdl.handle.net/11000/30687-
dc.description.abstractThe development of a suitable EEG-based emotion recognition system has become a target in the last decades for BCI (Brain Computer Interface) applications. However, there are scarce algorithms and procedures for real time classification of emotions. In this work we introduce a new approach to select the appropriate parameters in order to build up a real-time emotion recognition system. We recorded the EEG-neural activity of 5 participants while they were looking and listening to an audiovisual database composed by positive and negative emotional video clips. We tested 11 different temporal window sizes, 6 ranges of frequency bands and 5 areas of interest located mainly on prefrontal and frontal brain regions. The most accurate time window segment was selected for each participant, giving us probable positive and negative emotional characteristic patterns, in terms of the most informative frequency-location pairs. Our preliminary results provide a reliable way to establish the more appropriate parameters to develop an accurate EEG-based emotion classifier in real-time.es_ES
dc.formatapplication/pdfes_ES
dc.format.extent12 p.es_ES
dc.language.isoenges_ES
dc.publisherSpringer International Publishing AGes_ES
dc.rightsinfo:eu-repo/semantics/closedAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectEEGes_ES
dc.subjectEmotionses_ES
dc.subjectVideo databasees_ES
dc.subjectBCIes_ES
dc.subjectReal-timees_ES
dc.titleSetting the Parameters for an Accurate EEG (Electroencephalography)-Based Emotion Recognition Systemes_ES
dc.typeinfo:eu-repo/semantics/bookPartes_ES
dc.relation.publisherversionhttps://doi.org/10.1007/978-3-319-59740-9es_ES
Aparece en las colecciones:
Artículos Farmacología, Pediatría y Química Orgánica


no-thumbnailVer/Abrir:

 Capitulo de libro Springer (sin libro completo).pdf



1,11 MB
Adobe PDF
Compartir:


Creative Commons La licencia se describe como: Atribución-NonComercial-NoDerivada 4.0 Internacional.