Order/disorder in brain electrical activity

Autores
Rosso, O.A.; Figliola, A.
Año de publicación
2004
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The processing of information by the brain is reflected in dynamical changes of the electrical activity in time, frequency, and space. Therefore, the concomitant studies require methods capable of describing the quantitative variation of the signal in both time and frequency. Here we present a quantitative EEC (qEEG) analysis, based on the Orthogonal Discrete Wavelet Transform (ODWT), of generalized epileptic tonic-clonic EEG signals. Two quantifiers: the Relative Wavelet Energy (RWE) and the Normalized Total Wavelet Entmpy (NTWS) have been used. The RWE gives information about the relative energy associated with the different frequency bands present in the EEO and their corresponding degree of importance. The NTWS is a measure of the order/disorder degree in the EEG signal. These two quantifiers were computing in EEG signals as provided by scalp electrodes of epileptic patients. We showed that the epileptic recruitment rhythm observed for generalized epileptic tonic-clonic seizures is accurately described by the RWE quantifier. In addition, a significant decrease in the NTWS was observed in the recruitment epoch, indicating a more rhythmic and ordered behavior in the brain electrical activity.
Fil:Figliola, A. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.
Fuente
Rev. Mex. Fis. 2004;50(2):149-155
Materia
EEG
Epileptic seizures
Signal entropy
Time-frequency signal analysis
Wavelet analysis
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by/2.5/ar
Repositorio
Biblioteca Digital (UBA-FCEN)
Institución
Universidad Nacional de Buenos Aires. Facultad de Ciencias Exactas y Naturales
OAI Identificador
paperaa:paper_0035001X_v50_n2_p149_Rosso

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oai_identifier_str paperaa:paper_0035001X_v50_n2_p149_Rosso
network_acronym_str BDUBAFCEN
repository_id_str 1896
network_name_str Biblioteca Digital (UBA-FCEN)
spelling Order/disorder in brain electrical activityRosso, O.A.Figliola, A.EEGEpileptic seizuresSignal entropyTime-frequency signal analysisWavelet analysisThe processing of information by the brain is reflected in dynamical changes of the electrical activity in time, frequency, and space. Therefore, the concomitant studies require methods capable of describing the quantitative variation of the signal in both time and frequency. Here we present a quantitative EEC (qEEG) analysis, based on the Orthogonal Discrete Wavelet Transform (ODWT), of generalized epileptic tonic-clonic EEG signals. Two quantifiers: the Relative Wavelet Energy (RWE) and the Normalized Total Wavelet Entmpy (NTWS) have been used. The RWE gives information about the relative energy associated with the different frequency bands present in the EEO and their corresponding degree of importance. The NTWS is a measure of the order/disorder degree in the EEG signal. These two quantifiers were computing in EEG signals as provided by scalp electrodes of epileptic patients. We showed that the epileptic recruitment rhythm observed for generalized epileptic tonic-clonic seizures is accurately described by the RWE quantifier. In addition, a significant decrease in the NTWS was observed in the recruitment epoch, indicating a more rhythmic and ordered behavior in the brain electrical activity.Fil:Figliola, A. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.2004info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://hdl.handle.net/20.500.12110/paper_0035001X_v50_n2_p149_RossoRev. Mex. Fis. 2004;50(2):149-155reponame:Biblioteca Digital (UBA-FCEN)instname:Universidad Nacional de Buenos Aires. Facultad de Ciencias Exactas y Naturalesinstacron:UBA-FCENenginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/2.5/ar2025-09-29T13:43:09Zpaperaa:paper_0035001X_v50_n2_p149_RossoInstitucionalhttps://digital.bl.fcen.uba.ar/Universidad públicaNo correspondehttps://digital.bl.fcen.uba.ar/cgi-bin/oaiserver.cgiana@bl.fcen.uba.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:18962025-09-29 13:43:10.431Biblioteca Digital (UBA-FCEN) - Universidad Nacional de Buenos Aires. Facultad de Ciencias Exactas y Naturalesfalse
dc.title.none.fl_str_mv Order/disorder in brain electrical activity
title Order/disorder in brain electrical activity
spellingShingle Order/disorder in brain electrical activity
Rosso, O.A.
EEG
Epileptic seizures
Signal entropy
Time-frequency signal analysis
Wavelet analysis
title_short Order/disorder in brain electrical activity
title_full Order/disorder in brain electrical activity
title_fullStr Order/disorder in brain electrical activity
title_full_unstemmed Order/disorder in brain electrical activity
title_sort Order/disorder in brain electrical activity
dc.creator.none.fl_str_mv Rosso, O.A.
Figliola, A.
author Rosso, O.A.
author_facet Rosso, O.A.
Figliola, A.
author_role author
author2 Figliola, A.
author2_role author
dc.subject.none.fl_str_mv EEG
Epileptic seizures
Signal entropy
Time-frequency signal analysis
Wavelet analysis
topic EEG
Epileptic seizures
Signal entropy
Time-frequency signal analysis
Wavelet analysis
dc.description.none.fl_txt_mv The processing of information by the brain is reflected in dynamical changes of the electrical activity in time, frequency, and space. Therefore, the concomitant studies require methods capable of describing the quantitative variation of the signal in both time and frequency. Here we present a quantitative EEC (qEEG) analysis, based on the Orthogonal Discrete Wavelet Transform (ODWT), of generalized epileptic tonic-clonic EEG signals. Two quantifiers: the Relative Wavelet Energy (RWE) and the Normalized Total Wavelet Entmpy (NTWS) have been used. The RWE gives information about the relative energy associated with the different frequency bands present in the EEO and their corresponding degree of importance. The NTWS is a measure of the order/disorder degree in the EEG signal. These two quantifiers were computing in EEG signals as provided by scalp electrodes of epileptic patients. We showed that the epileptic recruitment rhythm observed for generalized epileptic tonic-clonic seizures is accurately described by the RWE quantifier. In addition, a significant decrease in the NTWS was observed in the recruitment epoch, indicating a more rhythmic and ordered behavior in the brain electrical activity.
Fil:Figliola, A. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.
description The processing of information by the brain is reflected in dynamical changes of the electrical activity in time, frequency, and space. Therefore, the concomitant studies require methods capable of describing the quantitative variation of the signal in both time and frequency. Here we present a quantitative EEC (qEEG) analysis, based on the Orthogonal Discrete Wavelet Transform (ODWT), of generalized epileptic tonic-clonic EEG signals. Two quantifiers: the Relative Wavelet Energy (RWE) and the Normalized Total Wavelet Entmpy (NTWS) have been used. The RWE gives information about the relative energy associated with the different frequency bands present in the EEO and their corresponding degree of importance. The NTWS is a measure of the order/disorder degree in the EEG signal. These two quantifiers were computing in EEG signals as provided by scalp electrodes of epileptic patients. We showed that the epileptic recruitment rhythm observed for generalized epileptic tonic-clonic seizures is accurately described by the RWE quantifier. In addition, a significant decrease in the NTWS was observed in the recruitment epoch, indicating a more rhythmic and ordered behavior in the brain electrical activity.
publishDate 2004
dc.date.none.fl_str_mv 2004
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/20.500.12110/paper_0035001X_v50_n2_p149_Rosso
url http://hdl.handle.net/20.500.12110/paper_0035001X_v50_n2_p149_Rosso
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/2.5/ar
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/2.5/ar
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv Rev. Mex. Fis. 2004;50(2):149-155
reponame:Biblioteca Digital (UBA-FCEN)
instname:Universidad Nacional de Buenos Aires. Facultad de Ciencias Exactas y Naturales
instacron:UBA-FCEN
reponame_str Biblioteca Digital (UBA-FCEN)
collection Biblioteca Digital (UBA-FCEN)
instname_str Universidad Nacional de Buenos Aires. Facultad de Ciencias Exactas y Naturales
instacron_str UBA-FCEN
institution UBA-FCEN
repository.name.fl_str_mv Biblioteca Digital (UBA-FCEN) - Universidad Nacional de Buenos Aires. Facultad de Ciencias Exactas y Naturales
repository.mail.fl_str_mv ana@bl.fcen.uba.ar
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