Characterization framework for ex-combatants based on EEG and behavioral features
ABSTRACT: 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...
- Autores:
-
Quintero Zea, Andrés
Sepúlveda Cano, Lina M.
Rodríguez Calvache, Mónica Viviana
Trujillo Orrego, Sandra Patricia
Trujillo Orrego, Natalia
López Hincapié, José David
- Tipo de recurso:
- Article of investigation
- Fecha de publicación:
- 2017
- Institución:
- Universidad de Antioquia
- Repositorio:
- Repositorio UdeA
- Idioma:
- eng
- OAI Identifier:
- oai:bibliotecadigital.udea.edu.co:10495/37294
- Acceso en línea:
- https://hdl.handle.net/10495/37294
- Palabra clave:
- Electroencefalografía
Electroencephalography
Aprendizaje Automático Supervisado
Supervised Machine Learning
Excombatientes
Ex-combatants
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/2.5/co/
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Characterization framework for ex-combatants based on EEG and behavioral features |
| title |
Characterization framework for ex-combatants based on EEG and behavioral features |
| spellingShingle |
Characterization framework for ex-combatants based on EEG and behavioral features Electroencefalografía Electroencephalography Aprendizaje Automático Supervisado Supervised Machine Learning Excombatientes Ex-combatants |
| title_short |
Characterization framework for ex-combatants based on EEG and behavioral features |
| title_full |
Characterization framework for ex-combatants based on EEG and behavioral features |
| title_fullStr |
Characterization framework for ex-combatants based on EEG and behavioral features |
| title_full_unstemmed |
Characterization framework for ex-combatants based on EEG and behavioral features |
| title_sort |
Characterization framework for ex-combatants based on EEG and behavioral features |
| dc.creator.fl_str_mv |
Quintero Zea, Andrés Sepúlveda Cano, Lina M. Rodríguez Calvache, Mónica Viviana Trujillo Orrego, Sandra Patricia Trujillo Orrego, Natalia López Hincapié, José David |
| dc.contributor.author.none.fl_str_mv |
Quintero Zea, Andrés Sepúlveda Cano, Lina M. Rodríguez Calvache, Mónica Viviana Trujillo Orrego, Sandra Patricia Trujillo Orrego, Natalia López Hincapié, José David |
| dc.contributor.researchgroup.spa.fl_str_mv |
Salud Mental Sistemas Embebidos e Inteligencia Computacional (SISTEMIC) |
| dc.subject.decs.none.fl_str_mv |
Electroencefalografía Electroencephalography Aprendizaje Automático Supervisado Supervised Machine Learning |
| topic |
Electroencefalografía Electroencephalography Aprendizaje Automático Supervisado Supervised Machine Learning Excombatientes Ex-combatants |
| dc.subject.proposal.spa.fl_str_mv |
Excombatientes Ex-combatants |
| description |
ABSTRACT: 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. |
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2017 |
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2017 |
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2023-11-13T20:16:30Z |
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2023-11-13T20:16:30Z |
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Quintero 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. |
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1680-0737 |
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https://hdl.handle.net/10495/37294 |
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10.1007/978-981-10-4086-3_52 |
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Quintero 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. 1680-0737 10.1007/978-981-10-4086-3_52 |
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https://hdl.handle.net/10495/37294 |
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eng |
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eng |
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IFMBE Proc |
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5 |
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60 |
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IFMBE Proceedings |
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Alemania |
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Quintero Zea, AndrésSepúlveda Cano, Lina M.Rodríguez Calvache, Mónica VivianaTrujillo Orrego, Sandra PatriciaTrujillo Orrego, NataliaLópez Hincapié, José DavidSalud MentalSistemas Embebidos e Inteligencia Computacional (SISTEMIC)2023-11-13T20:16:30Z2023-11-13T20:16:30Z2017Quintero 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_52.1680-0737https://hdl.handle.net/10495/3729410.1007/978-981-10-4086-3_52ABSTRACT: 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.Universidad de Antioquia. Vicerrectoría de investigación. Comité para el Desarrollo de la Investigación - CODIColombia. Ministerio de Ciencia Tecnología e Innovación - MinicienciasCOL0010717COL00159835application/pdfengSpringerInternational Federation for Medical & Biological EngineeringAlemaniahttp://creativecommons.org/licenses/by-nc-nd/2.5/co/https://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Characterization framework for ex-combatants based on EEG and behavioral featuresArtículo de investigaciónhttp://purl.org/coar/resource_type/c_2df8fbb1https://purl.org/redcol/resource_type/ARThttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionElectroencefalografíaElectroencephalographyAprendizaje Automático SupervisadoSupervised Machine LearningExcombatientesEx-combatantsIFMBE Proc5160IFMBE ProceedingsINV518-16122266140116 and 111556933399RoR:03bp5hc83RoR:048jthh02PublicationCC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8927https://bibliotecadigital.udea.edu.co/bitstreams/8cc53061-84a8-461e-8e13-e3fe2cc65177/download1646d1f6b96dbbbc38035efc9239ac9cMD52falseAnonymousREADLICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://bibliotecadigital.udea.edu.co/bitstreams/75708305-7398-4696-a3fa-77e587211bcb/download8a4605be74aa9ea9d79846c1fba20a33MD53falseAnonymousREADORIGINALQuinteroAndres_2016_CharacterizationFrameworkEXcombatants.pdfQuinteroAndres_2016_CharacterizationFrameworkEXcombatants.pdfArtículo de investigaciónapplication/pdf383616https://bibliotecadigital.udea.edu.co/bitstreams/c6fc49da-924d-4822-a252-3d9002ed2917/download4d1d4b0b46f5a6593bc6266c464d2fdaMD54trueAnonymousREADTEXTQuinteroAndres_2016_CharacterizationFrameworkEXcombatants.pdf.txtQuinteroAndres_2016_CharacterizationFrameworkEXcombatants.pdf.txtExtracted texttext/plain17127https://bibliotecadigital.udea.edu.co/bitstreams/c2398af6-8813-4147-ade0-a64a57973f01/download797bfd1a40c57f435be7562e943e1129MD57falseAnonymousREADTHUMBNAILQuinteroAndres_2016_CharacterizationFrameworkEXcombatants.pdf.jpgQuinteroAndres_2016_CharacterizationFrameworkEXcombatants.pdf.jpgGenerated Thumbnailimage/jpeg15060https://bibliotecadigital.udea.edu.co/bitstreams/eef96aca-d687-434f-9c72-bfabfdd1b24d/download3e5b4001b300cbf978ef524407015f01MD58falseAnonymousREAD10495/37294oai:bibliotecadigital.udea.edu.co:10495/372942025-03-26 17:43:12.732http://creativecommons.org/licenses/by-nc-nd/2.5/co/open.accesshttps://bibliotecadigital.udea.edu.coRepositorio Institucional de la Universidad de Antioquiaaplicacionbibliotecadigitalbiblioteca@udea.edu.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 |