Epileptic seizure suppression: A computational approach for identification and control using real data

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorUniversidade de São Paulo (USP)-
Autor(es): dc.contributorUniversidad Nacional Autónoma de Honduras-
Autor(es): dc.creatorBrogin, João A.F.-
Autor(es): dc.creatorFaber, Jean-
Autor(es): dc.creatorReyes-Garcia, Selvin Z.-
Autor(es): dc.creatorCavalheiro, Esper A.-
Autor(es): dc.creatorBueno, Douglas D.-
Data de aceite: dc.date.accessioned2025-08-21T22:27:23Z-
Data de disponibilização: dc.date.available2025-08-21T22:27:23Z-
Data de envio: dc.date.issued2025-04-29-
Data de envio: dc.date.issued2024-01-31-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1371/journal.pone.0298762-
Fonte completa do material: dc.identifierhttps://hdl.handle.net/11449/297807-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/297807-
Descrição: dc.descriptionEpilepsy affects millions of people worldwide every year and remains an open subject for research. Current development on this field has focused on obtaining computational models to better understand its triggering mechanisms, attain realistic descriptions and study seizure suppression. Controllers have been successfully applied to mitigate epileptiform activity in dynamic models written in state-space notation, whose applicability is, however, restricted to signatures that are accurately described by them. Alternatively, autoregressive modeling (AR), a typical data-driven tool related to system identification (SI), can be directly applied to signals to generate more realistic models, and since it is inherently convertible into state-space representation, it can thus be used for the artificial reconstruction and attenuation of seizures as well. Considering this, the first objective of this work is to propose an SI approach using AR models to describe real epileptiform activity. The second objective is to provide a strategy for reconstructing and mitigating such activity artificially, considering non-hybrid and hybrid controllers - designed from ictal and interictal events, respectively. The results show that AR models of relatively low order represent epileptiform activities fairly well and both controllers are effective in attenuating the undesired activity while simultaneously driving the signal to an interictal condition. These findings may lead to customized models based on each signal, brain region or patient, from which it is possible to better define shape, frequency and duration of external stimuli that are necessary to attenuate seizures.-
Descrição: dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)-
Descrição: dc.descriptionInstituto Nacional de Ciência e Tecnologia de Neurociência Translacional-
Descrição: dc.descriptionCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)-
Descrição: dc.descriptionUniversidad Nacional Autónoma de México-
Descrição: dc.descriptionDepartment of Mechanical Engineering São Paulo State University (UNESP) School of Engineering of Ilha Solteira, Ilha Solteira-
Descrição: dc.descriptionDepartment of Neurology and Neurosurgery Federal University of São Paulo (UNIFESP), São Paulo-
Descrição: dc.descriptionDepartamento de Ciencias Morfológicas Facultad de Ciencias Médicas Universidad Nacional Autónoma de Honduras-
Descrição: dc.descriptionDepartment of Mathematics São Paulo State University (UNESP) School of Engineering of Ilha Solteira, Ilha Solteira-
Descrição: dc.descriptionDepartment of Mechanical Engineering São Paulo State University (UNESP) School of Engineering of Ilha Solteira, Ilha Solteira-
Descrição: dc.descriptionDepartment of Mathematics São Paulo State University (UNESP) School of Engineering of Ilha Solteira, Ilha Solteira-
Descrição: dc.descriptionCNPq: 442563-2016/7-
Descrição: dc.descriptionInstituto Nacional de Ciência e Tecnologia de Neurociência Translacional: 573604/2008-8-
Descrição: dc.descriptionCAPES: 88887.481049/2020-00-
Descrição: dc.descriptionUniversidad Nacional Autónoma de México: CU-O-041-05-2014-
Idioma: dc.languageen-
Relação: dc.relationPLoS ONE-
???dc.source???: dc.sourceScopus-
Título: dc.titleEpileptic seizure suppression: A computational approach for identification and control using real data-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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