An Efficient Approach to Define the Input Stimuli to Suppress Epileptic Seizures Described by the Epileptor Model

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dc.contributor.authorBrogin, João Angelo Ferres [UNESP]
dc.contributor.authorFaber, Jean
dc.contributor.authorBueno, Douglas Domingues [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.contributor.institutionUniversidade de São Paulo (USP)
dc.date.accessioned2021-06-25T10:35:20Z
dc.date.available2021-06-25T10:35:20Z
dc.date.issued2020-11-01
dc.description.abstractEpilepsy affects about 70 million people in the world. Every year, approximately 2.4 million people are diagnosed with epilepsy, two-thirds of them will not know the etiology of their disease, and 1% of these individuals will decease as a consequence of it. Due to the inherent complexity of predicting and explaining it, the mathematical model Epileptor was recently developed to reproduce seizure-like events, also providing insights to improve the understanding of the neural dynamics in the interictal and ictal periods, although the physics behind each parameter and variable of the model is not fully established in the literature. This paper introduces an approach to design a feedback-based controller for suppressing epileptic seizures described by Epileptor. Our work establishes how the nonlinear dynamics of this disorder can be written in terms of a combination of linear sub-models employing an exact solution. Additionally, we show how a feedback control gain can be computed to suppress seizures, as well as how specific shapes applied as input stimuli for this purpose can be obtained. The practical application of the approach is discussed and the results show that the proposed technique is promising for developing controllers in this field.en
dc.description.affiliationDepartment of Mechanical Engineering São Paulo State University (UNESP) School of Engineering of Ilha Solteira, 56 Brasil Avenue
dc.description.affiliationDepartment of Neurology and Neurosurgery Federal University of São Paulo (UNIFESP), 667 Pedro de Toledo Street
dc.description.affiliationDepartment of Mathematics São Paulo State University (UNESP) School of Engineering of Ilha Solteira, 56 Brasil Avenue
dc.description.affiliationUnespDepartment of Mechanical Engineering São Paulo State University (UNESP) School of Engineering of Ilha Solteira, 56 Brasil Avenue
dc.description.affiliationUnespDepartment of Mathematics São Paulo State University (UNESP) School of Engineering of Ilha Solteira, 56 Brasil Avenue
dc.identifierhttp://dx.doi.org/10.1142/S0129065720500628
dc.identifier.citationInternational Journal of Neural Systems, v. 30, n. 11, 2020.
dc.identifier.doi10.1142/S0129065720500628
dc.identifier.issn1793-6462
dc.identifier.issn0129-0657
dc.identifier.scopus2-s2.0-85092222059
dc.identifier.urihttp://hdl.handle.net/11449/206622
dc.language.isoeng
dc.relation.ispartofInternational Journal of Neural Systems
dc.sourceScopus
dc.subjectEpileptic seizure suppression
dc.subjectEpileptor model
dc.subjectfuzzy Takagi-Sugeno modeling
dc.subjectlinear matrix inequalities
dc.titleAn Efficient Approach to Define the Input Stimuli to Suppress Epileptic Seizures Described by the Epileptor Modelen
dc.typeArtigo

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Artigos - Engenharia Mecânica - FEIS
Artigos - Matemática - FEIS