Stress assessment based on EEG univariate features and functional connectivity measures

The biological response to stress originates in the brain but involves different biochemical and physiological effects. Many common clinical methods to assess stress are based on the presence of specific hormones and on features extracted from different signals, including electrocardiogram, blood pr...

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Autores: Alonso, JF, Romero, S, Ballester, MR, Antonijoan, RM, Mananas, MA
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2015
País:España
Recursos:Institut d’Investigació Biomèdica Sant Pau (IIB Sant Pau)
Repositorio:r-IIB SANT PAU. Repositorio Institucional de Producción Científica del Instituto de Investigación Biomédica Sant Pau
OAI Identifier:oai:iibsantpau.fundanetsuite.com:p8588
Acesso em linha:https://iibsantpau.fundanetsuite.com/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=8588
Access Level:acceso abierto
Palavra-chave:stress
EEG
stroop test
sleep deprivation
spectral analysis
mutual information function
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spelling Stress assessment based on EEG univariate features and functional connectivity measuresAlonso, JFRomero, SBallester, MRAntonijoan, RMMananas, MAstressEEGstroop testsleep deprivationspectral analysismutual information functionThe biological response to stress originates in the brain but involves different biochemical and physiological effects. Many common clinical methods to assess stress are based on the presence of specific hormones and on features extracted from different signals, including electrocardiogram, blood pressure, skin temperature, or galvanic skin response. The aim of this paper was to assess stress using EEG-based variables obtained from univariate analysis and functional connectivity evaluation. Two different stressors, the Stroop test and sleep deprivation, were applied to 30 volunteers to find common EEG patterns related to stress effects. Results showed a decrease of the high alpha power (11 to 12 Hz), an increase in the high beta band (23 to 36 Hz, considered a busy brain indicator), and a decrease in the approximate entropy. Moreover, connectivity showed that the high beta coherence and the interhemispheric nonlinear couplings, measured by the cross mutual information function, increased significantly for both stressors, suggesting that useful stress indexes may be obtained from EEG-based features.IOP PUBLISHING LTD2015info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttps://iibsantpau.fundanetsuite.com/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=8588PHYSIOLOGICAL MEASUREMENTISSN: 09673334ISSNe: 13616579reponame:r-IIB SANT PAU. Repositorio Institucional de Producción Científica del Instituto de Investigación Biomédica Sant Pauinstname:Institut d’Investigació Biomèdica Sant Pau (IIB Sant Pau)Inglésinfo:eu-repo/semantics/openAccessoai:iibsantpau.fundanetsuite.com:p85882026-06-14T12:41:47Z
dc.title.none.fl_str_mv Stress assessment based on EEG univariate features and functional connectivity measures
title Stress assessment based on EEG univariate features and functional connectivity measures
spellingShingle Stress assessment based on EEG univariate features and functional connectivity measures
Alonso, JF
stress
EEG
stroop test
sleep deprivation
spectral analysis
mutual information function
title_short Stress assessment based on EEG univariate features and functional connectivity measures
title_full Stress assessment based on EEG univariate features and functional connectivity measures
title_fullStr Stress assessment based on EEG univariate features and functional connectivity measures
title_full_unstemmed Stress assessment based on EEG univariate features and functional connectivity measures
title_sort Stress assessment based on EEG univariate features and functional connectivity measures
dc.creator.none.fl_str_mv Alonso, JF
Romero, S
Ballester, MR
Antonijoan, RM
Mananas, MA
author Alonso, JF
author_facet Alonso, JF
Romero, S
Ballester, MR
Antonijoan, RM
Mananas, MA
author_role author
author2 Romero, S
Ballester, MR
Antonijoan, RM
Mananas, MA
author2_role author
author
author
author
dc.subject.none.fl_str_mv stress
EEG
stroop test
sleep deprivation
spectral analysis
mutual information function
topic stress
EEG
stroop test
sleep deprivation
spectral analysis
mutual information function
description The biological response to stress originates in the brain but involves different biochemical and physiological effects. Many common clinical methods to assess stress are based on the presence of specific hormones and on features extracted from different signals, including electrocardiogram, blood pressure, skin temperature, or galvanic skin response. The aim of this paper was to assess stress using EEG-based variables obtained from univariate analysis and functional connectivity evaluation. Two different stressors, the Stroop test and sleep deprivation, were applied to 30 volunteers to find common EEG patterns related to stress effects. Results showed a decrease of the high alpha power (11 to 12 Hz), an increase in the high beta band (23 to 36 Hz, considered a busy brain indicator), and a decrease in the approximate entropy. Moreover, connectivity showed that the high beta coherence and the interhemispheric nonlinear couplings, measured by the cross mutual information function, increased significantly for both stressors, suggesting that useful stress indexes may be obtained from EEG-based features.
publishDate 2015
dc.date.none.fl_str_mv 2015
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://iibsantpau.fundanetsuite.com/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=8588
url https://iibsantpau.fundanetsuite.com/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=8588
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv IOP PUBLISHING LTD
publisher.none.fl_str_mv IOP PUBLISHING LTD
dc.source.none.fl_str_mv PHYSIOLOGICAL MEASUREMENT
ISSN: 09673334
ISSNe: 13616579
reponame:r-IIB SANT PAU. Repositorio Institucional de Producción Científica del Instituto de Investigación Biomédica Sant Pau
instname:Institut d’Investigació Biomèdica Sant Pau (IIB Sant Pau)
instname_str Institut d’Investigació Biomèdica Sant Pau (IIB Sant Pau)
reponame_str r-IIB SANT PAU. Repositorio Institucional de Producción Científica del Instituto de Investigación Biomédica Sant Pau
collection r-IIB SANT PAU. Repositorio Institucional de Producción Científica del Instituto de Investigación Biomédica Sant Pau
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.812429

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