A maximum entropy approach for predicting epileptic tonic-clonic seizure

Autores
Martín, María Teresa; Plastino, Ángel Luis; Vampa, Victoria
Año de publicación
2014
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The development of methods for time series analysis and prediction has always been and continues to be an active area of research. In this work, we develop a technique for modelling chaotic time series in parametric fashion. In the case of tonic-clonic epileptic electroencephalographic (EEG) analysis, we show that appropriate information theory tools provide valuable insights into the dynamics of neural activity. Our purpose is to demonstrate the feasibility of the maximum entropy principle to anticipate tonic-clonic seizure in patients with epilepsy.
Facultad de Ciencias Exactas
Instituto de Física La Plata
Facultad de Ingeniería
Materia
Ciencias Exactas
Ingeniería
Maximum entropy
Pseudo-inverse approach
Tonic-clonic EEG transition
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by/3.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/85041
Acceder
id SEDICI_5102dffba8cf7af5ed7b188b950dda76
oai_identifier_str oai:sedici.unlp.edu.ar:10915/85041
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling A maximum entropy approach for predicting epileptic tonic-clonic seizureMartín, María TeresaPlastino, Ángel LuisVampa, VictoriaCiencias ExactasIngenieríaMaximum entropyPseudo-inverse approachTonic-clonic EEG transitionThe development of methods for time series analysis and prediction has always been and continues to be an active area of research. In this work, we develop a technique for modelling chaotic time series in parametric fashion. In the case of tonic-clonic epileptic electroencephalographic (EEG) analysis, we show that appropriate information theory tools provide valuable insights into the dynamics of neural activity. Our purpose is to demonstrate the feasibility of the maximum entropy principle to anticipate tonic-clonic seizure in patients with epilepsy.Facultad de Ciencias ExactasInstituto de Física La PlataFacultad de Ingeniería2014info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdf4603-4611http://sedici.unlp.edu.ar/handle/10915/85041enginfo:eu-repo/semantics/altIdentifier/issn/1099-4300info:eu-repo/semantics/altIdentifier/doi/10.3390/e16084603info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/3.0/Creative Commons Attribution 3.0 Unported (CC BY 3.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-03T10:48:41Zoai:sedici.unlp.edu.ar:10915/85041Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-03 10:48:41.387SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv A maximum entropy approach for predicting epileptic tonic-clonic seizure
title A maximum entropy approach for predicting epileptic tonic-clonic seizure
spellingShingle A maximum entropy approach for predicting epileptic tonic-clonic seizure
Martín, María Teresa
Ciencias Exactas
Ingeniería
Maximum entropy
Pseudo-inverse approach
Tonic-clonic EEG transition
title_short A maximum entropy approach for predicting epileptic tonic-clonic seizure
title_full A maximum entropy approach for predicting epileptic tonic-clonic seizure
title_fullStr A maximum entropy approach for predicting epileptic tonic-clonic seizure
title_full_unstemmed A maximum entropy approach for predicting epileptic tonic-clonic seizure
title_sort A maximum entropy approach for predicting epileptic tonic-clonic seizure
dc.creator.none.fl_str_mv Martín, María Teresa
Plastino, Ángel Luis
Vampa, Victoria
author Martín, María Teresa
author_facet Martín, María Teresa
Plastino, Ángel Luis
Vampa, Victoria
author_role author
author2 Plastino, Ángel Luis
Vampa, Victoria
author2_role author
author
dc.subject.none.fl_str_mv Ciencias Exactas
Ingeniería
Maximum entropy
Pseudo-inverse approach
Tonic-clonic EEG transition
topic Ciencias Exactas
Ingeniería
Maximum entropy
Pseudo-inverse approach
Tonic-clonic EEG transition
dc.description.none.fl_txt_mv The development of methods for time series analysis and prediction has always been and continues to be an active area of research. In this work, we develop a technique for modelling chaotic time series in parametric fashion. In the case of tonic-clonic epileptic electroencephalographic (EEG) analysis, we show that appropriate information theory tools provide valuable insights into the dynamics of neural activity. Our purpose is to demonstrate the feasibility of the maximum entropy principle to anticipate tonic-clonic seizure in patients with epilepsy.
Facultad de Ciencias Exactas
Instituto de Física La Plata
Facultad de Ingeniería
description The development of methods for time series analysis and prediction has always been and continues to be an active area of research. In this work, we develop a technique for modelling chaotic time series in parametric fashion. In the case of tonic-clonic epileptic electroencephalographic (EEG) analysis, we show that appropriate information theory tools provide valuable insights into the dynamics of neural activity. Our purpose is to demonstrate the feasibility of the maximum entropy principle to anticipate tonic-clonic seizure in patients with epilepsy.
publishDate 2014
dc.date.none.fl_str_mv 2014
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Articulo
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://sedici.unlp.edu.ar/handle/10915/85041
url http://sedici.unlp.edu.ar/handle/10915/85041
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/issn/1099-4300
info:eu-repo/semantics/altIdentifier/doi/10.3390/e16084603
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/3.0/
Creative Commons Attribution 3.0 Unported (CC BY 3.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/3.0/
Creative Commons Attribution 3.0 Unported (CC BY 3.0)
dc.format.none.fl_str_mv application/pdf
4603-4611
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
_version_ 1842260362606411776
score 13.13397

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