Towards a resilient e-health system for monitoring and early detection of severity in hospitalized patients during a pandemic

Autores
Cañibano, Rodrigo S.; Castagno, Santino; Conchillo, Mariano; Chiarotto, Guillermo; Rozas, Claudia; Zanellato, Claudio; Orlandi, Cristina; Balladini, Javier
Año de publicación
2022
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Different mobile applications and smart systems are being developed to increase users’ wellness and happiness. Unfortunately, some of the most recent technological advances in the field of affective computing, Internet of things or service computing have not yet been included in these solutions. In this paper, we briefly present a smart system that analyses the user’s emotions during her/his diary activities and configures mood regulation experiences when she/he comes back at home. These emotion-aware experiences are based on the Spotify music services and are personalised for each particular user considering her/his musical tastes and preferences. Besides, the system integrates an emotion recognition system based on wearables and artificial intelligence techniques. The recognised emotions are then used to determine the user’s mood and to make decisions on the music interventions to be carried out.
Instituto de Investigación en Informática
Materia
Ciencias Informáticas
Early severity detection
E-health monitoring
Fault tolerant distributed architecture
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:10915/140661
Acceder
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spelling Towards a resilient e-health system for monitoring and early detection of severity in hospitalized patients during a pandemicCañibano, Rodrigo S.Castagno, SantinoConchillo, MarianoChiarotto, GuillermoRozas, ClaudiaZanellato, ClaudioOrlandi, CristinaBalladini, JavierCiencias InformáticasEarly severity detectionE-health monitoringFault tolerant distributed architectureDifferent mobile applications and smart systems are being developed to increase users’ wellness and happiness. Unfortunately, some of the most recent technological advances in the field of affective computing, Internet of things or service computing have not yet been included in these solutions. In this paper, we briefly present a smart system that analyses the user’s emotions during her/his diary activities and configures mood regulation experiences when she/he comes back at home. These emotion-aware experiences are based on the Spotify music services and are personalised for each particular user considering her/his musical tastes and preferences. Besides, the system integrates an emotion recognition system based on wearables and artificial intelligence techniques. The recognised emotions are then used to determine the user’s mood and to make decisions on the music interventions to be carried out.Instituto de Investigación en Informática2022-07info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf76-80http://sedici.unlp.edu.ar/handle/10915/140661enginfo:eu-repo/semantics/altIdentifier/isbn/978-950-34-2126-0info:eu-repo/semantics/reference/hdl/10915/139373info: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:UNLP2025-10-15T11:27:35Zoai:sedici.unlp.edu.ar:10915/140661Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-15 11:27:35.91SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Towards a resilient e-health system for monitoring and early detection of severity in hospitalized patients during a pandemic
title Towards a resilient e-health system for monitoring and early detection of severity in hospitalized patients during a pandemic
spellingShingle Towards a resilient e-health system for monitoring and early detection of severity in hospitalized patients during a pandemic
Cañibano, Rodrigo S.
Ciencias Informáticas
Early severity detection
E-health monitoring
Fault tolerant distributed architecture
title_short Towards a resilient e-health system for monitoring and early detection of severity in hospitalized patients during a pandemic
title_full Towards a resilient e-health system for monitoring and early detection of severity in hospitalized patients during a pandemic
title_fullStr Towards a resilient e-health system for monitoring and early detection of severity in hospitalized patients during a pandemic
title_full_unstemmed Towards a resilient e-health system for monitoring and early detection of severity in hospitalized patients during a pandemic
title_sort Towards a resilient e-health system for monitoring and early detection of severity in hospitalized patients during a pandemic
dc.creator.none.fl_str_mv Cañibano, Rodrigo S.
Castagno, Santino
Conchillo, Mariano
Chiarotto, Guillermo
Rozas, Claudia
Zanellato, Claudio
Orlandi, Cristina
Balladini, Javier
author Cañibano, Rodrigo S.
author_facet Cañibano, Rodrigo S.
Castagno, Santino
Conchillo, Mariano
Chiarotto, Guillermo
Rozas, Claudia
Zanellato, Claudio
Orlandi, Cristina
Balladini, Javier
author_role author
author2 Castagno, Santino
Conchillo, Mariano
Chiarotto, Guillermo
Rozas, Claudia
Zanellato, Claudio
Orlandi, Cristina
Balladini, Javier
author2_role author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Early severity detection
E-health monitoring
Fault tolerant distributed architecture
topic Ciencias Informáticas
Early severity detection
E-health monitoring
Fault tolerant distributed architecture
dc.description.none.fl_txt_mv Different mobile applications and smart systems are being developed to increase users’ wellness and happiness. Unfortunately, some of the most recent technological advances in the field of affective computing, Internet of things or service computing have not yet been included in these solutions. In this paper, we briefly present a smart system that analyses the user’s emotions during her/his diary activities and configures mood regulation experiences when she/he comes back at home. These emotion-aware experiences are based on the Spotify music services and are personalised for each particular user considering her/his musical tastes and preferences. Besides, the system integrates an emotion recognition system based on wearables and artificial intelligence techniques. The recognised emotions are then used to determine the user’s mood and to make decisions on the music interventions to be carried out.
Instituto de Investigación en Informática
description Different mobile applications and smart systems are being developed to increase users’ wellness and happiness. Unfortunately, some of the most recent technological advances in the field of affective computing, Internet of things or service computing have not yet been included in these solutions. In this paper, we briefly present a smart system that analyses the user’s emotions during her/his diary activities and configures mood regulation experiences when she/he comes back at home. These emotion-aware experiences are based on the Spotify music services and are personalised for each particular user considering her/his musical tastes and preferences. Besides, the system integrates an emotion recognition system based on wearables and artificial intelligence techniques. The recognised emotions are then used to determine the user’s mood and to make decisions on the music interventions to be carried out.
publishDate 2022
dc.date.none.fl_str_mv 2022-07
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/10915/140661
url http://sedici.unlp.edu.ar/handle/10915/140661
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/isbn/978-950-34-2126-0
info:eu-repo/semantics/reference/hdl/10915/139373
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
rights_invalid_str_mv 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
76-80
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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