Statistical Complexity Analysis of Sleep Stages

Autores
Duarte, Cristina Daiana; Pacheco, Marianela; Iaconis, Francisco Ramiro; Rosso, Osvaldo A.; Gasaneo, Gustavo; Delrieux, Claudio Augusto
Año de publicación
2025
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Studying sleep stages is crucial for understanding sleep architecture, which can help identify various health conditions, including insomnia, sleep apnea, and neurodegenerative diseases, allowing for better diagnosis and treatment interventions. In this paper, we explore the effectiveness of generalized weighted permutation entropy (GWPE) in distinguishing between different sleep stages from EEG signals. Using classification algorithms, we evaluate feature sets derived from both standard permutation entropy (PE) and GWPE to determine which set performs better in classifying sleep stages, demonstrating that GWPE significantly enhances sleep stage differentiation, particularly in identifying the transition between N1 and REM sleep. The results highlight the potential of GWPE as a valuable tool for understanding sleep neurophysiology and improving the diagnosis of sleep disorders.
Fil: Duarte, Cristina Daiana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Física del Sur. Universidad Nacional del Sur. Departamento de Física. Instituto de Física del Sur; Argentina
Fil: Pacheco, Marianela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Física del Sur. Universidad Nacional del Sur. Departamento de Física. Instituto de Física del Sur; Argentina
Fil: Iaconis, Francisco Ramiro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Física del Sur. Universidad Nacional del Sur. Departamento de Física. Instituto de Física del Sur; Argentina
Fil: Rosso, Osvaldo A.. Universidade Federal de Alagoas; Brasil
Fil: Gasaneo, Gustavo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Física del Sur. Universidad Nacional del Sur. Departamento de Física. Instituto de Física del Sur; Argentina
Fil: Delrieux, Claudio Augusto. Laboratorio de Ciencias de Las Imágenes ; Departamento de Ingenieria Electrica y de Computadoras ; Universidad Nacional del Sur; . Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina
Materia
Permutation entropy
statistical complexity
generalized weighted permutation entropy
sleep stages
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/276492
Acceder
id CONICETDig_6b131aae94a3cde6ea529646badfd68e
oai_identifier_str oai:ri.conicet.gov.ar:11336/276492
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Statistical Complexity Analysis of Sleep StagesDuarte, Cristina DaianaPacheco, MarianelaIaconis, Francisco RamiroRosso, Osvaldo A.Gasaneo, GustavoDelrieux, Claudio AugustoPermutation entropystatistical complexitygeneralized weighted permutation entropysleep stageshttps://purl.org/becyt/ford/1.3https://purl.org/becyt/ford/1Studying sleep stages is crucial for understanding sleep architecture, which can help identify various health conditions, including insomnia, sleep apnea, and neurodegenerative diseases, allowing for better diagnosis and treatment interventions. In this paper, we explore the effectiveness of generalized weighted permutation entropy (GWPE) in distinguishing between different sleep stages from EEG signals. Using classification algorithms, we evaluate feature sets derived from both standard permutation entropy (PE) and GWPE to determine which set performs better in classifying sleep stages, demonstrating that GWPE significantly enhances sleep stage differentiation, particularly in identifying the transition between N1 and REM sleep. The results highlight the potential of GWPE as a valuable tool for understanding sleep neurophysiology and improving the diagnosis of sleep disorders.Fil: Duarte, Cristina Daiana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Física del Sur. Universidad Nacional del Sur. Departamento de Física. Instituto de Física del Sur; ArgentinaFil: Pacheco, Marianela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Física del Sur. Universidad Nacional del Sur. Departamento de Física. Instituto de Física del Sur; ArgentinaFil: Iaconis, Francisco Ramiro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Física del Sur. Universidad Nacional del Sur. Departamento de Física. Instituto de Física del Sur; ArgentinaFil: Rosso, Osvaldo A.. Universidade Federal de Alagoas; BrasilFil: Gasaneo, Gustavo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Física del Sur. Universidad Nacional del Sur. Departamento de Física. Instituto de Física del Sur; ArgentinaFil: Delrieux, Claudio Augusto. Laboratorio de Ciencias de Las Imágenes ; Departamento de Ingenieria Electrica y de Computadoras ; Universidad Nacional del Sur; . Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; ArgentinaMolecular Diversity Preservation International2025-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/276492Duarte, Cristina Daiana; Pacheco, Marianela; Iaconis, Francisco Ramiro; Rosso, Osvaldo A.; Gasaneo, Gustavo; et al.; Statistical Complexity Analysis of Sleep Stages; Molecular Diversity Preservation International; Entropy; 27; 1; 1-2025; 1-141099-4300CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.mdpi.com/1099-4300/27/1/76info:eu-repo/semantics/altIdentifier/doi/10.3390/e27010076info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-12-03T09:55:10Zoai:ri.conicet.gov.ar:11336/276492instacron: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:34982025-12-03 09:55:10.784CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Statistical Complexity Analysis of Sleep Stages
title Statistical Complexity Analysis of Sleep Stages
spellingShingle Statistical Complexity Analysis of Sleep Stages
Duarte, Cristina Daiana
Permutation entropy
statistical complexity
generalized weighted permutation entropy
sleep stages
title_short Statistical Complexity Analysis of Sleep Stages
title_full Statistical Complexity Analysis of Sleep Stages
title_fullStr Statistical Complexity Analysis of Sleep Stages
title_full_unstemmed Statistical Complexity Analysis of Sleep Stages
title_sort Statistical Complexity Analysis of Sleep Stages
dc.creator.none.fl_str_mv Duarte, Cristina Daiana
Pacheco, Marianela
Iaconis, Francisco Ramiro
Rosso, Osvaldo A.
Gasaneo, Gustavo
Delrieux, Claudio Augusto
author Duarte, Cristina Daiana
author_facet Duarte, Cristina Daiana
Pacheco, Marianela
Iaconis, Francisco Ramiro
Rosso, Osvaldo A.
Gasaneo, Gustavo
Delrieux, Claudio Augusto
author_role author
author2 Pacheco, Marianela
Iaconis, Francisco Ramiro
Rosso, Osvaldo A.
Gasaneo, Gustavo
Delrieux, Claudio Augusto
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Permutation entropy
statistical complexity
generalized weighted permutation entropy
sleep stages
topic Permutation entropy
statistical complexity
generalized weighted permutation entropy
sleep stages
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.3
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Studying sleep stages is crucial for understanding sleep architecture, which can help identify various health conditions, including insomnia, sleep apnea, and neurodegenerative diseases, allowing for better diagnosis and treatment interventions. In this paper, we explore the effectiveness of generalized weighted permutation entropy (GWPE) in distinguishing between different sleep stages from EEG signals. Using classification algorithms, we evaluate feature sets derived from both standard permutation entropy (PE) and GWPE to determine which set performs better in classifying sleep stages, demonstrating that GWPE significantly enhances sleep stage differentiation, particularly in identifying the transition between N1 and REM sleep. The results highlight the potential of GWPE as a valuable tool for understanding sleep neurophysiology and improving the diagnosis of sleep disorders.
Fil: Duarte, Cristina Daiana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Física del Sur. Universidad Nacional del Sur. Departamento de Física. Instituto de Física del Sur; Argentina
Fil: Pacheco, Marianela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Física del Sur. Universidad Nacional del Sur. Departamento de Física. Instituto de Física del Sur; Argentina
Fil: Iaconis, Francisco Ramiro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Física del Sur. Universidad Nacional del Sur. Departamento de Física. Instituto de Física del Sur; Argentina
Fil: Rosso, Osvaldo A.. Universidade Federal de Alagoas; Brasil
Fil: Gasaneo, Gustavo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Física del Sur. Universidad Nacional del Sur. Departamento de Física. Instituto de Física del Sur; Argentina
Fil: Delrieux, Claudio Augusto. Laboratorio de Ciencias de Las Imágenes ; Departamento de Ingenieria Electrica y de Computadoras ; Universidad Nacional del Sur; . Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina
description Studying sleep stages is crucial for understanding sleep architecture, which can help identify various health conditions, including insomnia, sleep apnea, and neurodegenerative diseases, allowing for better diagnosis and treatment interventions. In this paper, we explore the effectiveness of generalized weighted permutation entropy (GWPE) in distinguishing between different sleep stages from EEG signals. Using classification algorithms, we evaluate feature sets derived from both standard permutation entropy (PE) and GWPE to determine which set performs better in classifying sleep stages, demonstrating that GWPE significantly enhances sleep stage differentiation, particularly in identifying the transition between N1 and REM sleep. The results highlight the potential of GWPE as a valuable tool for understanding sleep neurophysiology and improving the diagnosis of sleep disorders.
publishDate 2025
dc.date.none.fl_str_mv 2025-01
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/11336/276492
Duarte, Cristina Daiana; Pacheco, Marianela; Iaconis, Francisco Ramiro; Rosso, Osvaldo A.; Gasaneo, Gustavo; et al.; Statistical Complexity Analysis of Sleep Stages; Molecular Diversity Preservation International; Entropy; 27; 1; 1-2025; 1-14
1099-4300
CONICET Digital
CONICET
url http://hdl.handle.net/11336/276492
identifier_str_mv Duarte, Cristina Daiana; Pacheco, Marianela; Iaconis, Francisco Ramiro; Rosso, Osvaldo A.; Gasaneo, Gustavo; et al.; Statistical Complexity Analysis of Sleep Stages; Molecular Diversity Preservation International; Entropy; 27; 1; 1-2025; 1-14
1099-4300
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.mdpi.com/1099-4300/27/1/76
info:eu-repo/semantics/altIdentifier/doi/10.3390/e27010076
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Molecular Diversity Preservation International
publisher.none.fl_str_mv Molecular Diversity Preservation International
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
_version_ 1850505959136296960
score 13.275514

Publicaciones similares