A contribution to the dynamics of epilepsy: identification and control for seizure attenuation

Detalhes bibliográficos
Autor(a) principal: Brogin, João Angelo Ferres
Data de Publicação: 2023
Tipo de documento: Tese
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: https://hdl.handle.net/11449/253611
Resumo: Epilepsy is one of the most common neurological disorders worldwide, affecting millions of people every year and leading to physical, psychological and social implications that may significantly compromise their lives. There are treatments today that help to mitigate the frequency and intensity of seizures, but none is fully successful, and the precise mechanisms that trigger them are not yet completely understood either. This has motivated researchers to address epilepsy from a theoretical point of view, resulting in the development of mathematical computational models that provide insights into seizure generation, synchronization and propagation. The Epileptor model is a breakthrough in this field due to its highly representative features, relatively easy implementation and adherence with experimental observations. Similarly, data-driven models have also been presented in the literature to describe the temporal signatures of electrophysiological recordings. Relevant questions that arise in this context are how to obtain dynamic models from real data for which a control system can be designed and how to define the nature of the control inputs that achieve seizure attenuation in both theoretical and experimental models. In this sense, the main contributions of this thesis are strategies to define the control inputs able to suppress or mitigate the epileptiform activity described by the Epileptor and real signals, based on the design of controllers, state observers and system identification techniques. Both are developed computationally but overcoming a series of numerical, theoretical and practical restrictions to obtain a final control approach with a strong practical appeal that can be potentially used by physicians as an auxiliary tool to better define the shape, intensity and frequency of the input stimulus that must be applied to attenuate seizures in electrical stimulation therapies. The results show that it is possible to reconstruct and attenuate the epileptiform patterns of both models from control signals that are specific to each level of brain activity and consistent with previous studies in the literature.
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spelling A contribution to the dynamics of epilepsy: identification and control for seizure attenuationA contribution to the dynamics of epilepsy: identification and control for seizure attenuationEpilepsySystem identificationSeizure attenuationEpilepsiaIdentificação de sistemasAtenuação de crisesEpilepsy is one of the most common neurological disorders worldwide, affecting millions of people every year and leading to physical, psychological and social implications that may significantly compromise their lives. There are treatments today that help to mitigate the frequency and intensity of seizures, but none is fully successful, and the precise mechanisms that trigger them are not yet completely understood either. This has motivated researchers to address epilepsy from a theoretical point of view, resulting in the development of mathematical computational models that provide insights into seizure generation, synchronization and propagation. The Epileptor model is a breakthrough in this field due to its highly representative features, relatively easy implementation and adherence with experimental observations. Similarly, data-driven models have also been presented in the literature to describe the temporal signatures of electrophysiological recordings. Relevant questions that arise in this context are how to obtain dynamic models from real data for which a control system can be designed and how to define the nature of the control inputs that achieve seizure attenuation in both theoretical and experimental models. In this sense, the main contributions of this thesis are strategies to define the control inputs able to suppress or mitigate the epileptiform activity described by the Epileptor and real signals, based on the design of controllers, state observers and system identification techniques. Both are developed computationally but overcoming a series of numerical, theoretical and practical restrictions to obtain a final control approach with a strong practical appeal that can be potentially used by physicians as an auxiliary tool to better define the shape, intensity and frequency of the input stimulus that must be applied to attenuate seizures in electrical stimulation therapies. The results show that it is possible to reconstruct and attenuate the epileptiform patterns of both models from control signals that are specific to each level of brain activity and consistent with previous studies in the literature.A epilepsia é uma das desordens neurológicas mais comuns no mundo, afetando milhões de pessoas todo ano e apresentando implicações físicas, psicológicas e sociais que podem comprometer significativamente suas vidas. Atualmente, há tratamentos que auxiliam a mitigar a frequência e intensidade das crises, mas nenhum deles é plenamente eficaz, e os mecanismos precisos que as causam também não são totalmente compreendidos ainda. Isso tem motivado pesquisadores a abordar a epilepsia a partir de um ponto de vista teórico, resultando no desenvolvimento de modelos matemáticos computacionais capazes de elucidar a geração, sincronização e propagação de crises. O modelo Epileptor é um marco nessa área de pesquisa devido a suas características altamente representativas, implementação relativamente simples e aderência a observações experimentais. Similarmente, modelos baseados em dados também têm sido propostos na literatura para descrever as assinaturas temporais de registros eletrofisiológicos. Questões relevantes que surgem nesse contexto são como obter modelos dinâmicos a partir de dados reais para os quais um sistema de controle pode ser projetado e como definir a natureza das entradas de controle que podem levar à atenuação de crises em ambos os modelos, teórico e experimental. Nesse sentido, as principais contribuições desta tese são estratégias para definir as entradas de controle capazes de suprimir ou mitigar as crises descritas pelo Epileptor e sinais reais, baseadas no projeto de controladores, observadores e identificação de sistemas. Ambos são desenvolvidos computacionalmente, mas superando uma série de restrições numéricas, teóricas e práticas para obter uma abordagem final de controle com forte apelo prático e potencialmente útil a médicos como ferramenta auxiliar para uma melhor definição do formato, intensidade e frequência dos estímulos que devem ser aplicados para atenuar crises em terapias de estimulação elétrica. Os resultados demonstram que é possível reconstruir e atenuar os padrões epileptiformes em ambos os modelos a partir de sinais de controle específicos a cada nível de atividade cerebral, sendo também consistentes com resultados previamente catalogados na literatura.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)CAPES: 88887.481049/2020-00CAPES: 001Universidade Estadual Paulista (Unesp)Bueno, Douglas Domingues [UNESP]Abreu, Jean Faber Ferreira deBrogin, João Angelo Ferres2024-03-11T13:28:14Z2024-03-11T13:28:14Z2023-12-19info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdfBROGIN, João Angelo Ferres. A contribution to the dynamics of epilepsy: identification and control for seizure attenuation. 2023. 238 f. Tese (Doutorado em Engenharia Mecânica) – Faculdade de Engenharia, Universidade Estadual Paulista - Unesp, Ilha Solteira, 2023.https://hdl.handle.net/11449/25361143920040864826260000-0002-1266-5902enginfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESP2024-03-12T07:23:36Zoai:repositorio.unesp.br:11449/253611Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T15:49:19.478018Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv A contribution to the dynamics of epilepsy: identification and control for seizure attenuation
A contribution to the dynamics of epilepsy: identification and control for seizure attenuation
title A contribution to the dynamics of epilepsy: identification and control for seizure attenuation
spellingShingle A contribution to the dynamics of epilepsy: identification and control for seizure attenuation
Brogin, João Angelo Ferres
Epilepsy
System identification
Seizure attenuation
Epilepsia
Identificação de sistemas
Atenuação de crises
title_short A contribution to the dynamics of epilepsy: identification and control for seizure attenuation
title_full A contribution to the dynamics of epilepsy: identification and control for seizure attenuation
title_fullStr A contribution to the dynamics of epilepsy: identification and control for seizure attenuation
title_full_unstemmed A contribution to the dynamics of epilepsy: identification and control for seizure attenuation
title_sort A contribution to the dynamics of epilepsy: identification and control for seizure attenuation
author Brogin, João Angelo Ferres
author_facet Brogin, João Angelo Ferres
author_role author
dc.contributor.none.fl_str_mv Bueno, Douglas Domingues [UNESP]
Abreu, Jean Faber Ferreira de
dc.contributor.author.fl_str_mv Brogin, João Angelo Ferres
dc.subject.por.fl_str_mv Epilepsy
System identification
Seizure attenuation
Epilepsia
Identificação de sistemas
Atenuação de crises
topic Epilepsy
System identification
Seizure attenuation
Epilepsia
Identificação de sistemas
Atenuação de crises
description Epilepsy is one of the most common neurological disorders worldwide, affecting millions of people every year and leading to physical, psychological and social implications that may significantly compromise their lives. There are treatments today that help to mitigate the frequency and intensity of seizures, but none is fully successful, and the precise mechanisms that trigger them are not yet completely understood either. This has motivated researchers to address epilepsy from a theoretical point of view, resulting in the development of mathematical computational models that provide insights into seizure generation, synchronization and propagation. The Epileptor model is a breakthrough in this field due to its highly representative features, relatively easy implementation and adherence with experimental observations. Similarly, data-driven models have also been presented in the literature to describe the temporal signatures of electrophysiological recordings. Relevant questions that arise in this context are how to obtain dynamic models from real data for which a control system can be designed and how to define the nature of the control inputs that achieve seizure attenuation in both theoretical and experimental models. In this sense, the main contributions of this thesis are strategies to define the control inputs able to suppress or mitigate the epileptiform activity described by the Epileptor and real signals, based on the design of controllers, state observers and system identification techniques. Both are developed computationally but overcoming a series of numerical, theoretical and practical restrictions to obtain a final control approach with a strong practical appeal that can be potentially used by physicians as an auxiliary tool to better define the shape, intensity and frequency of the input stimulus that must be applied to attenuate seizures in electrical stimulation therapies. The results show that it is possible to reconstruct and attenuate the epileptiform patterns of both models from control signals that are specific to each level of brain activity and consistent with previous studies in the literature.
publishDate 2023
dc.date.none.fl_str_mv 2023-12-19
2024-03-11T13:28:14Z
2024-03-11T13:28:14Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/doctoralThesis
format doctoralThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv BROGIN, João Angelo Ferres. A contribution to the dynamics of epilepsy: identification and control for seizure attenuation. 2023. 238 f. Tese (Doutorado em Engenharia Mecânica) – Faculdade de Engenharia, Universidade Estadual Paulista - Unesp, Ilha Solteira, 2023.
https://hdl.handle.net/11449/253611
4392004086482626
0000-0002-1266-5902
identifier_str_mv BROGIN, João Angelo Ferres. A contribution to the dynamics of epilepsy: identification and control for seizure attenuation. 2023. 238 f. Tese (Doutorado em Engenharia Mecânica) – Faculdade de Engenharia, Universidade Estadual Paulista - Unesp, Ilha Solteira, 2023.
4392004086482626
0000-0002-1266-5902
url https://hdl.handle.net/11449/253611
dc.language.iso.fl_str_mv eng
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dc.publisher.none.fl_str_mv Universidade Estadual Paulista (Unesp)
publisher.none.fl_str_mv Universidade Estadual Paulista (Unesp)
dc.source.none.fl_str_mv reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
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instname_str Universidade Estadual Paulista (UNESP)
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repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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