Digitalización de imágenes de ECG para la detección del síndrome de Bayés

Autores
Franco, Lorena G.; Escobar Robledo, Luis A.; Bayés de Luna, Antoni; Massa, José María
Año de publicación
2018
Idioma
español castellano
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Bayes Syndrome is a recently recognized by medical community sickness. This desease has been studied in the last decades by its discoverer, MD. Antonio Bayés de Luna. Since several works shows that this desease is related to multiple symptoms, an early detection is considered relevant. Given that digital support of the EKG signal is mandatory for its analysis by a computer algorithm and considering that even with the technological advances, a big number of health institutions rely on paper or image digitalized support por EKGs. Hence, an image digitalization method that preserves the signal features that are relevant to diagnose the Bayes Syndrome is needed. In this paper, some alternatives of digitalization are analyzed for a representative dataset. Results are promising and shows that developed digitalization algorithm could be used for the further project stages that involves signal processing and classification.
IX Workshop Procesamiento de Señales y Sistemas de Tiempo Real (WPSTR)
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
síndrome de Bayés
Arritmias Cardíacas
ECG
bloqueo interauricular avanzado
procesamiento digital
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:10915/73595
Acceder
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spelling Digitalización de imágenes de ECG para la detección del síndrome de BayésFranco, Lorena G.Escobar Robledo, Luis A.Bayés de Luna, AntoniMassa, José MaríaCiencias Informáticassíndrome de BayésArritmias CardíacasECGbloqueo interauricular avanzadoprocesamiento digitalBayes Syndrome is a recently recognized by medical community sickness. This desease has been studied in the last decades by its discoverer, MD. Antonio Bayés de Luna. Since several works shows that this desease is related to multiple symptoms, an early detection is considered relevant. Given that digital support of the EKG signal is mandatory for its analysis by a computer algorithm and considering that even with the technological advances, a big number of health institutions rely on paper or image digitalized support por EKGs. Hence, an image digitalization method that preserves the signal features that are relevant to diagnose the Bayes Syndrome is needed. In this paper, some alternatives of digitalization are analyzed for a representative dataset. Results are promising and shows that developed digitalization algorithm could be used for the further project stages that involves signal processing and classification.IX Workshop Procesamiento de Señales y Sistemas de Tiempo Real (WPSTR)Red de Universidades con Carreras en Informática (RedUNCI)2018-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf979-987http://sedici.unlp.edu.ar/handle/10915/73595spainfo:eu-repo/semantics/altIdentifier/isbn/978-950-658-472-6info: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:UNLP2025-10-22T16:53:24Zoai:sedici.unlp.edu.ar:10915/73595Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-22 16:53:25.157SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Digitalización de imágenes de ECG para la detección del síndrome de Bayés
title Digitalización de imágenes de ECG para la detección del síndrome de Bayés
spellingShingle Digitalización de imágenes de ECG para la detección del síndrome de Bayés
Franco, Lorena G.
Ciencias Informáticas
síndrome de Bayés
Arritmias Cardíacas
ECG
bloqueo interauricular avanzado
procesamiento digital
title_short Digitalización de imágenes de ECG para la detección del síndrome de Bayés
title_full Digitalización de imágenes de ECG para la detección del síndrome de Bayés
title_fullStr Digitalización de imágenes de ECG para la detección del síndrome de Bayés
title_full_unstemmed Digitalización de imágenes de ECG para la detección del síndrome de Bayés
title_sort Digitalización de imágenes de ECG para la detección del síndrome de Bayés
dc.creator.none.fl_str_mv Franco, Lorena G.
Escobar Robledo, Luis A.
Bayés de Luna, Antoni
Massa, José María
author Franco, Lorena G.
author_facet Franco, Lorena G.
Escobar Robledo, Luis A.
Bayés de Luna, Antoni
Massa, José María
author_role author
author2 Escobar Robledo, Luis A.
Bayés de Luna, Antoni
Massa, José María
author2_role author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
síndrome de Bayés
Arritmias Cardíacas
ECG
bloqueo interauricular avanzado
procesamiento digital
topic Ciencias Informáticas
síndrome de Bayés
Arritmias Cardíacas
ECG
bloqueo interauricular avanzado
procesamiento digital
dc.description.none.fl_txt_mv Bayes Syndrome is a recently recognized by medical community sickness. This desease has been studied in the last decades by its discoverer, MD. Antonio Bayés de Luna. Since several works shows that this desease is related to multiple symptoms, an early detection is considered relevant. Given that digital support of the EKG signal is mandatory for its analysis by a computer algorithm and considering that even with the technological advances, a big number of health institutions rely on paper or image digitalized support por EKGs. Hence, an image digitalization method that preserves the signal features that are relevant to diagnose the Bayes Syndrome is needed. In this paper, some alternatives of digitalization are analyzed for a representative dataset. Results are promising and shows that developed digitalization algorithm could be used for the further project stages that involves signal processing and classification.
IX Workshop Procesamiento de Señales y Sistemas de Tiempo Real (WPSTR)
Red de Universidades con Carreras en Informática (RedUNCI)
description Bayes Syndrome is a recently recognized by medical community sickness. This desease has been studied in the last decades by its discoverer, MD. Antonio Bayés de Luna. Since several works shows that this desease is related to multiple symptoms, an early detection is considered relevant. Given that digital support of the EKG signal is mandatory for its analysis by a computer algorithm and considering that even with the technological advances, a big number of health institutions rely on paper or image digitalized support por EKGs. Hence, an image digitalization method that preserves the signal features that are relevant to diagnose the Bayes Syndrome is needed. In this paper, some alternatives of digitalization are analyzed for a representative dataset. Results are promising and shows that developed digitalization algorithm could be used for the further project stages that involves signal processing and classification.
publishDate 2018
dc.date.none.fl_str_mv 2018-10
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
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status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/73595
url http://sedici.unlp.edu.ar/handle/10915/73595
dc.language.none.fl_str_mv spa
language spa
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/isbn/978-950-658-472-6
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)
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
979-987
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repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
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