Multimodal biometric recording architecture for the exploitation of applications in the context of affective computing

Autores
Calot, Enrique; Ierache, Jorge Salvador
Año de publicación
2017
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
In affective computing, it is important to design techniques that allow devices to acquire emotional states. To create and test these techniques it is necessary to have datasets that have several modalities namely, keystroke dynamics, electroencephalography, facial expressions, voice tone, heart rate, among others. This article presents a multimodal dataset that allowed us to detect the subjectivity that subsists in certain modalities -as are the surveys-and that is often overlooked, against objective modalities such as keystroke dynamics and electroencephalography. This article presents the creation of an environment in order to acquire a multimodal dataset. Work has also been done on the analysis of brain waves and their correspondence with other modalities.
IX Workshop Innovación en Sistemas de Software (WISS).
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
biosignal devices
affective computing
multimodal acquisition
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/63866

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spelling Multimodal biometric recording architecture for the exploitation of applications in the context of affective computingCalot, EnriqueIerache, Jorge SalvadorCiencias Informáticasbiosignal devicesaffective computingmultimodal acquisitionIn affective computing, it is important to design techniques that allow devices to acquire emotional states. To create and test these techniques it is necessary to have datasets that have several modalities namely, keystroke dynamics, electroencephalography, facial expressions, voice tone, heart rate, among others. This article presents a multimodal dataset that allowed us to detect the subjectivity that subsists in certain modalities -as are the surveys-and that is often overlooked, against objective modalities such as keystroke dynamics and electroencephalography. This article presents the creation of an environment in order to acquire a multimodal dataset. Work has also been done on the analysis of brain waves and their correspondence with other modalities.IX Workshop Innovación en Sistemas de Software (WISS).Red de Universidades con Carreras en Informática (RedUNCI)2017-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf1030-1039http://sedici.unlp.edu.ar/handle/10915/63866enginfo:eu-repo/semantics/altIdentifier/isbn/978-950-34-1539-9info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:08:34Zoai:sedici.unlp.edu.ar:10915/63866Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:08:34.548SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Multimodal biometric recording architecture for the exploitation of applications in the context of affective computing
title Multimodal biometric recording architecture for the exploitation of applications in the context of affective computing
spellingShingle Multimodal biometric recording architecture for the exploitation of applications in the context of affective computing
Calot, Enrique
Ciencias Informáticas
biosignal devices
affective computing
multimodal acquisition
title_short Multimodal biometric recording architecture for the exploitation of applications in the context of affective computing
title_full Multimodal biometric recording architecture for the exploitation of applications in the context of affective computing
title_fullStr Multimodal biometric recording architecture for the exploitation of applications in the context of affective computing
title_full_unstemmed Multimodal biometric recording architecture for the exploitation of applications in the context of affective computing
title_sort Multimodal biometric recording architecture for the exploitation of applications in the context of affective computing
dc.creator.none.fl_str_mv Calot, Enrique
Ierache, Jorge Salvador
author Calot, Enrique
author_facet Calot, Enrique
Ierache, Jorge Salvador
author_role author
author2 Ierache, Jorge Salvador
author2_role author
dc.subject.none.fl_str_mv Ciencias Informáticas
biosignal devices
affective computing
multimodal acquisition
topic Ciencias Informáticas
biosignal devices
affective computing
multimodal acquisition
dc.description.none.fl_txt_mv In affective computing, it is important to design techniques that allow devices to acquire emotional states. To create and test these techniques it is necessary to have datasets that have several modalities namely, keystroke dynamics, electroencephalography, facial expressions, voice tone, heart rate, among others. This article presents a multimodal dataset that allowed us to detect the subjectivity that subsists in certain modalities -as are the surveys-and that is often overlooked, against objective modalities such as keystroke dynamics and electroencephalography. This article presents the creation of an environment in order to acquire a multimodal dataset. Work has also been done on the analysis of brain waves and their correspondence with other modalities.
IX Workshop Innovación en Sistemas de Software (WISS).
Red de Universidades con Carreras en Informática (RedUNCI)
description In affective computing, it is important to design techniques that allow devices to acquire emotional states. To create and test these techniques it is necessary to have datasets that have several modalities namely, keystroke dynamics, electroencephalography, facial expressions, voice tone, heart rate, among others. This article presents a multimodal dataset that allowed us to detect the subjectivity that subsists in certain modalities -as are the surveys-and that is often overlooked, against objective modalities such as keystroke dynamics and electroencephalography. This article presents the creation of an environment in order to acquire a multimodal dataset. Work has also been done on the analysis of brain waves and their correspondence with other modalities.
publishDate 2017
dc.date.none.fl_str_mv 2017-10
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info:eu-repo/semantics/publishedVersion
Objeto de conferencia
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dc.language.none.fl_str_mv eng
language eng
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dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
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Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
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rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
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