A new algorithm for epilepsy seizure onset detection and spread estimation from EEG signals

Autores
Antonio Quintero, Rincón; Pereyra, Marcelo Fabián; D'Giano, Carlos; Batatia, Hadj; Risk, Marcelo
Año de publicación
2016
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Appropriate diagnosis and treatment of epilepsy is a main public health issue. Patients suffering from this disease often exhibit different physical characterizations, which result from the synchronous and excessive discharge of a group of neurons in the cerebral cortex. Extracting this information using EEG signals is an important problem in biomedical signal processing. In this work we propose a new algorithm for seizure onset detection and spread estimation in epilepsy patients. The algorithm is based on a multilevel 1-D wavelet decomposition that captures the physiological brain frequency signals coupled with a generalized gaussian model. Preliminary experiments with signals from 30 epilepsy crisis and 11 subjects, suggest that the proposed methodology is a powerful tool for detecting the onset of epilepsy seizures with his spread across the brain.
Fil: Antonio Quintero, Rincón. Instituto Tecnológico de Buenos Aires; Argentina
Fil: Pereyra, Marcelo Fabián. University of Bristol; Reino Unido
Fil: D'Giano, Carlos. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; Argentina
Fil: Batatia, Hadj. Instituto Polytechnique de Toulouse; Francia. University of Toulouse; Francia
Fil: Risk, Marcelo. Instituto Tecnológico de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Materia
epilepsy
seizures
EEG
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/105953
Acceder
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network_name_str CONICET Digital (CONICET)
spelling A new algorithm for epilepsy seizure onset detection and spread estimation from EEG signalsAntonio Quintero, RincónPereyra, Marcelo FabiánD'Giano, CarlosBatatia, HadjRisk, MarceloepilepsyseizuresEEGhttps://purl.org/becyt/ford/2.6https://purl.org/becyt/ford/2Appropriate diagnosis and treatment of epilepsy is a main public health issue. Patients suffering from this disease often exhibit different physical characterizations, which result from the synchronous and excessive discharge of a group of neurons in the cerebral cortex. Extracting this information using EEG signals is an important problem in biomedical signal processing. In this work we propose a new algorithm for seizure onset detection and spread estimation in epilepsy patients. The algorithm is based on a multilevel 1-D wavelet decomposition that captures the physiological brain frequency signals coupled with a generalized gaussian model. Preliminary experiments with signals from 30 epilepsy crisis and 11 subjects, suggest that the proposed methodology is a powerful tool for detecting the onset of epilepsy seizures with his spread across the brain.Fil: Antonio Quintero, Rincón. Instituto Tecnológico de Buenos Aires; ArgentinaFil: Pereyra, Marcelo Fabián. University of Bristol; Reino UnidoFil: D'Giano, Carlos. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; ArgentinaFil: Batatia, Hadj. Instituto Polytechnique de Toulouse; Francia. University of Toulouse; FranciaFil: Risk, Marcelo. Instituto Tecnológico de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaIOP Publishing2016-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/105953Antonio Quintero, Rincón; Pereyra, Marcelo Fabián; D'Giano, Carlos; Batatia, Hadj; Risk, Marcelo; A new algorithm for epilepsy seizure onset detection and spread estimation from EEG signals; IOP Publishing; Journal of Physics: Conference Series; 705; 4-2016; 1-111742-6596CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://iopscience.iop.org/article/10.1088/1742-6596/705/1/012032info:eu-repo/semantics/altIdentifier/doi/10.1088/1742-6596/705/1/012032info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:16:03Zoai:ri.conicet.gov.ar:11336/105953instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:16:03.63CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A new algorithm for epilepsy seizure onset detection and spread estimation from EEG signals
title A new algorithm for epilepsy seizure onset detection and spread estimation from EEG signals
spellingShingle A new algorithm for epilepsy seizure onset detection and spread estimation from EEG signals
Antonio Quintero, Rincón
epilepsy
seizures
EEG
title_short A new algorithm for epilepsy seizure onset detection and spread estimation from EEG signals
title_full A new algorithm for epilepsy seizure onset detection and spread estimation from EEG signals
title_fullStr A new algorithm for epilepsy seizure onset detection and spread estimation from EEG signals
title_full_unstemmed A new algorithm for epilepsy seizure onset detection and spread estimation from EEG signals
title_sort A new algorithm for epilepsy seizure onset detection and spread estimation from EEG signals
dc.creator.none.fl_str_mv Antonio Quintero, Rincón
Pereyra, Marcelo Fabián
D'Giano, Carlos
Batatia, Hadj
Risk, Marcelo
author Antonio Quintero, Rincón
author_facet Antonio Quintero, Rincón
Pereyra, Marcelo Fabián
D'Giano, Carlos
Batatia, Hadj
Risk, Marcelo
author_role author
author2 Pereyra, Marcelo Fabián
D'Giano, Carlos
Batatia, Hadj
Risk, Marcelo
author2_role author
author
author
author
dc.subject.none.fl_str_mv epilepsy
seizures
EEG
topic epilepsy
seizures
EEG
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.6
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv Appropriate diagnosis and treatment of epilepsy is a main public health issue. Patients suffering from this disease often exhibit different physical characterizations, which result from the synchronous and excessive discharge of a group of neurons in the cerebral cortex. Extracting this information using EEG signals is an important problem in biomedical signal processing. In this work we propose a new algorithm for seizure onset detection and spread estimation in epilepsy patients. The algorithm is based on a multilevel 1-D wavelet decomposition that captures the physiological brain frequency signals coupled with a generalized gaussian model. Preliminary experiments with signals from 30 epilepsy crisis and 11 subjects, suggest that the proposed methodology is a powerful tool for detecting the onset of epilepsy seizures with his spread across the brain.
Fil: Antonio Quintero, Rincón. Instituto Tecnológico de Buenos Aires; Argentina
Fil: Pereyra, Marcelo Fabián. University of Bristol; Reino Unido
Fil: D'Giano, Carlos. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; Argentina
Fil: Batatia, Hadj. Instituto Polytechnique de Toulouse; Francia. University of Toulouse; Francia
Fil: Risk, Marcelo. Instituto Tecnológico de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
description Appropriate diagnosis and treatment of epilepsy is a main public health issue. Patients suffering from this disease often exhibit different physical characterizations, which result from the synchronous and excessive discharge of a group of neurons in the cerebral cortex. Extracting this information using EEG signals is an important problem in biomedical signal processing. In this work we propose a new algorithm for seizure onset detection and spread estimation in epilepsy patients. The algorithm is based on a multilevel 1-D wavelet decomposition that captures the physiological brain frequency signals coupled with a generalized gaussian model. Preliminary experiments with signals from 30 epilepsy crisis and 11 subjects, suggest that the proposed methodology is a powerful tool for detecting the onset of epilepsy seizures with his spread across the brain.
publishDate 2016
dc.date.none.fl_str_mv 2016-04
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/105953
Antonio Quintero, Rincón; Pereyra, Marcelo Fabián; D'Giano, Carlos; Batatia, Hadj; Risk, Marcelo; A new algorithm for epilepsy seizure onset detection and spread estimation from EEG signals; IOP Publishing; Journal of Physics: Conference Series; 705; 4-2016; 1-11
1742-6596
CONICET Digital
CONICET
url http://hdl.handle.net/11336/105953
identifier_str_mv Antonio Quintero, Rincón; Pereyra, Marcelo Fabián; D'Giano, Carlos; Batatia, Hadj; Risk, Marcelo; A new algorithm for epilepsy seizure onset detection and spread estimation from EEG signals; IOP Publishing; Journal of Physics: Conference Series; 705; 4-2016; 1-11
1742-6596
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://iopscience.iop.org/article/10.1088/1742-6596/705/1/012032
info:eu-repo/semantics/altIdentifier/doi/10.1088/1742-6596/705/1/012032
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv IOP Publishing
publisher.none.fl_str_mv IOP Publishing
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.070432

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