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
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/63866
Ver los metadatos del registro completo
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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 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/conferenceObject info:eu-repo/semantics/publishedVersion Objeto de conferencia http://purl.org/coar/resource_type/c_5794 info:ar-repo/semantics/documentoDeConferencia |
format |
conferenceObject |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
http://sedici.unlp.edu.ar/handle/10915/63866 |
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http://sedici.unlp.edu.ar/handle/10915/63866 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/isbn/978-950-34-1539-9 |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
eu_rights_str_mv |
openAccess |
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http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
dc.format.none.fl_str_mv |
application/pdf 1030-1039 |
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reponame:SEDICI (UNLP) instname:Universidad Nacional de La Plata instacron:UNLP |
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SEDICI (UNLP) - Universidad Nacional de La Plata |
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13.070432 |