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
- 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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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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1844618740274036736 |
score |
13.070432 |