Reconocimiento de emociones en humanos mediante procesamiento de señales EEG y estimulación auditiva
dc.contributor.advisor | Niño Vásquez, Luis Fernando | |
dc.contributor.author | Ortega Loaiza, Christian Ortega | |
dc.contributor.researchgroup | LABORATORIO DE INVESTIGACIÓN EN SISTEMAS INTELIGENTES - LISI | spa |
dc.date.accessioned | 2021-07-22T14:11:19Z | |
dc.date.available | 2021-07-22T14:11:19Z | |
dc.date.issued | 2021 | |
dc.description | ilustraciones, fotografías, tablas | spa |
dc.description.abstract | Este trabajo aborda una problemática que no es ajena a la academia, pero que aún presenta resultados embrionarios. En particular, emplea estímulos auditivos con el objeto de implementar un algoritmo computacional que realice el reconocimiento de un grupo definido de emociones maximizando la precisión y reduciendo la cantidad de electrodos necesarios para dicha tarea. Para ello se definió un grupo de 6 emociones objetivo estimuladas mediante 30 audios, los cuales fueron presentados a un grupo de 14 personas voluntarias, de entre 18 y 35 años, sobre las cuales se realizó la lectura de las señales EEG. La metodología conllevó 3 fases, son sus respectivas etapas, y permitió construir un algoritmo basado tanto en características convencionales como en la Transformada Wavelet, la Dimensión Fractal y un modelo de Análisis Discriminante Cuadrático, el cual fue valorado bajo métricas de precisión, exactitud, exhaustividad y puntaje F1. Los resultados fueron comparados con aquellos reportados en otros trabajos similares disponibles en la literatura. (Texto tomado de la fuente) | spa |
dc.description.abstract | This work addresses a problem that is not beyond to academia, but which still presents embryonic results. In particular, it uses auditory stimuli in order to implement a computational algorithm that performs the recognition of a defined group of emotions maximizing accuracy and reducing the number of electrodes needed for this task. To this end, a group of 6 target emotions stimulated by 30 audio excerpts were defined and presented to a group of 14 volunteers, aged between 18 and 35, on whom the EEG signals were read. The methodology involved 3 phases, with their respective stages, and allowed the construction of an algorithm based on conventional features as well as on Wavelet Transform, Fractal Dimension and a Quadratic Discriminant Analysis model, which was evaluated under metrics of precision, accuracy, recall and F1 score. The results were compared with those reported in other similar works available in the literature. (Text taken from source) | eng |
dc.description.degreelevel | Maestría | spa |
dc.description.degreename | Magíster en Ingeniería - Ingeniería de Sistemas y Computación | spa |
dc.description.researcharea | Sistemas inteligentes | spa |
dc.format.extent | 122 páginas | spa |
dc.format.mimetype | application/pdf | spa |
dc.identifier.instname | Universidad Nacional de Colombia | spa |
dc.identifier.reponame | Repositorio Institucional Universidad Nacional de Colombia | spa |
dc.identifier.repourl | https://repositorio.unal.edu.co/ | spa |
dc.identifier.uri | https://repositorio.unal.edu.co/handle/unal/79832 | |
dc.language.iso | spa | spa |
dc.publisher | Universidad Nacional de Colombia | spa |
dc.publisher.branch | Universidad Nacional de Colombia - Sede Bogotá | spa |
dc.publisher.department | Departamento de Ingeniería de Sistemas e Industrial | spa |
dc.publisher.faculty | Facultad de Ingeniería | spa |
dc.publisher.place | Bogotá, Colombia | spa |
dc.publisher.program | Bogotá - Ingeniería - Maestría en Ingeniería - Ingeniería de Sistemas y Computación | spa |
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dc.rights | Derechos reservados al autor, 2021 | spa |
dc.rights.accessrights | info:eu-repo/semantics/openAccess | spa |
dc.rights.license | Atribución-NoComercial-CompartirIgual 4.0 Internacional | spa |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/4.0/ | spa |
dc.subject.ddc | 000 - Ciencias de la computación, información y obras generales::004 - Procesamiento de datos Ciencia de los computadores | spa |
dc.subject.decs | Emociones | |
dc.subject.decs | Emotions | |
dc.subject.proposal | Aprendizaje Automático | spa |
dc.subject.proposal | Dimensión Fractal | spa |
dc.subject.proposal | Emociones | spa |
dc.subject.proposal | Interfaces Cerebro-Computador | spa |
dc.subject.proposal | QDA | eng |
dc.subject.proposal | Wavelet Analysis | eng |
dc.subject.proposal | Machine Learning | eng |
dc.subject.proposal | Fractal Dimension | eng |
dc.subject.proposal | Emotions | eng |
dc.subject.proposal | Electroencephalography | eng |
dc.subject.proposal | Brain-Computer Interfaces | eng |
dc.subject.proposal | Análisis de ondículas | spa |
dc.subject.proposal | Electroencefalografía | spa |
dc.subject.unesco | Investigación sobre el cerebro | |
dc.subject.unesco | Brain research | |
dc.title | Reconocimiento de emociones en humanos mediante procesamiento de señales EEG y estimulación auditiva | spa |
dc.title.translated | Human emotion recognition using EEG signal processing and auditory stimulation | eng |
dc.title.translated | Menschliche Emotionserkennung mittels EEG-Signalverarbeitung und auditorischer Stimulation | deu |
dc.title.translated | Reconnaissance des émotions humaines par le traitement du signal EEG et la stimulation auditive | fra |
dc.title.translated | Reconhecimento das emoções humanas usando o processamento de sinais EEG e estimulação auditiva | por |
dc.type | Trabajo de grado - Maestría | spa |
dc.type.coar | http://purl.org/coar/resource_type/c_bdcc | spa |
dc.type.coarversion | http://purl.org/coar/version/c_ab4af688f83e57aa | spa |
dc.type.content | Text | spa |
dc.type.driver | info:eu-repo/semantics/masterThesis | spa |
dc.type.redcol | http://purl.org/redcol/resource_type/TM | spa |
dc.type.version | info:eu-repo/semantics/acceptedVersion | spa |
dcterms.audience | General | spa |
oaire.accessrights | http://purl.org/coar/access_right/c_abf2 | spa |
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