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dc.contributor.authorQuintero Zea, Andrés-
dc.contributor.authorSepúlveda Cano, Lina M.-
dc.contributor.authorRodríguez Calvache, Mónica Viviana-
dc.contributor.authorTrujillo Orrego, Sandra Patricia-
dc.contributor.authorTrujillo Orrego, Natalia-
dc.contributor.authorLópez Hincapié, José David-
dc.date.accessioned2023-11-13T20:16:30Z-
dc.date.available2023-11-13T20:16:30Z-
dc.date.issued2017-
dc.identifier.citationQuintero Zea, Andrés & Sepúlveda-Cano, Lina & Calvache, Mónica & Trujillo, Sandra & Trujillo, Natalia & Lopez, Jose. (2017). Characterization Framework for Ex-combatants Based on EEG and Behavioral Features. 10.1007/978-981-10-4086-3_52.spa
dc.identifier.issn1680-0737-
dc.identifier.urihttps://hdl.handle.net/10495/37294-
dc.description.abstractABSTRACT: This paper presents a framework to characterize the emotional processing of Colombian ex-combatants from illegal groups. The classification process is performed using EEG-ERP data and behavioral features from psychological tests. The results show that ex-combatant and civilian populations can be automatically separated using supervised techniques. With this, we can provide a decision support system for psychologists to improve current interventions aimed to help ex-combatants to make a successful reintegration to civilian life.spa
dc.format.extent5spa
dc.format.mimetypeapplication/pdfspa
dc.language.isoengspa
dc.publisherSpringerspa
dc.publisherInternational Federation for Medical & Biological Engineeringspa
dc.type.hasversioninfo:eu-repo/semantics/publishedVersionspa
dc.rightsinfo:eu-repo/semantics/openAccessspa
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/2.5/co/*
dc.titleCharacterization framework for ex-combatants based on EEG and behavioral featuresspa
dc.typeinfo:eu-repo/semantics/articlespa
dc.publisher.groupSalud Mentalspa
dc.publisher.groupSistemas Embebidos e Inteligencia Computacional (SISTEMIC)spa
dc.identifier.doi10.1007/978-981-10-4086-3_52-
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85spa
dc.rights.accessrightshttp://purl.org/coar/access_right/c_abf2spa
oaire.citationtitleIFMBE Proceedingsspa
oaire.citationstartpage1spa
oaire.citationendpage5spa
oaire.citationvolume60spa
dc.rights.creativecommonshttps://creativecommons.org/licenses/by-nc-nd/4.0/spa
oaire.fundernameUniversidad de Antioquia. Vicerrectoría de investigación. Comité para el Desarrollo de la Investigación - CODIspa
oaire.fundernameColombia. Ministerio de Ciencia Tecnología e Innovación - Minicienciasspa
dc.publisher.placeAlemaniaspa
dc.type.coarhttp://purl.org/coar/resource_type/c_2df8fbb1spa
dc.type.redcolhttps://purl.org/redcol/resource_type/ARTspa
dc.type.localArtículo de investigaciónspa
dc.subject.decsElectroencefalografía-
dc.subject.decsElectroencephalography-
dc.subject.decsAprendizaje Automático Supervisado-
dc.subject.decsSupervised Machine Learning-
dc.subject.proposalExcombatientesspa
dc.subject.proposalEx-combatantsspa
dc.description.researchgroupidCOL0010717spa
dc.description.researchgroupidCOL0015983spa
oaire.awardnumberINV518-16spa
oaire.awardnumber122266140116 and 111556933399spa
dc.relation.ispartofjournalabbrevIFMBE Procspa
oaire.funderidentifier.rorRoR:03bp5hc83-
oaire.funderidentifier.rorRoR:048jthh02-
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