A RISE-based controller fine-tuned by an improved genetic algorithm for human lower limb rehabilitation via neuromuscular electrical stimulation

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (Unesp)-
Autor(es): dc.contributorUTFPR-
Autor(es): dc.creatorArcolezi, Heber Hwang [UNESP]-
Autor(es): dc.creatorNunes, Willian R.B.M.-
Autor(es): dc.creatorNahuis, Selene Leya Cerna [UNESP]-
Autor(es): dc.creatorSanches, Marcelo A.A. [UNESP]-
Autor(es): dc.creatorTeixeira, Marcelo C.M. [UNESP]-
Autor(es): dc.creatorDe Carvalho, Aparecido A. [UNESP]-
Data de aceite: dc.date.accessioned2022-02-22T00:23:11Z-
Data de disponibilização: dc.date.available2022-02-22T00:23:11Z-
Data de envio: dc.date.issued2020-12-11-
Data de envio: dc.date.issued2020-12-11-
Data de envio: dc.date.issued2019-04-01-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1109/CoDIT.2019.8820357-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/197976-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/197976-
Descrição: dc.descriptionIn the last few years, several studies have been carried out showing that Functional Electrical Stimulation (FES) and Neuromuscular Electrical Stimulation (NMES) produce good therapeutic results in patients with Spinal Cord Injury (SCI). This paper presents the proposal of a fine-tuning method based on an Improved Genetic Algorithm (IGA) to a continuous and robust control technique for uncertain nonlinear systems named Robust Integral of the Sign of the Error (RISE), for knee joint control. Simulation results are provided for three paraplegic and one healthy identified patients on ideal and nonideal conditions. Although in the literature this controller presents good results without any fine tuning method, we provide an approach to improve it, even more, believing on the minimization of fatigue and other problems that often occurs in SCI patients treated with FES/NMES, by selecting adequately the gain parameters of the RISE controller.-
Descrição: dc.descriptionDepartment of Electrical Engineering São Paulo State University UNESP-
Descrição: dc.descriptionDepartment of Electrical Engineering Federal University of Technology - Paraná UTFPR-
Descrição: dc.descriptionDepartment of Electrical Engineering São Paulo State University UNESP-
Formato: dc.format1197-1202-
Idioma: dc.languageen-
Relação: dc.relation2019 6th International Conference on Control, Decision and Information Technologies, CoDIT 2019-
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Título: dc.titleA RISE-based controller fine-tuned by an improved genetic algorithm for human lower limb rehabilitation via neuromuscular electrical stimulation-
Aparece nas coleções:Repositório Institucional - Unesp

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