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

Bibliographic Details
Main Author: Arcolezi, Heber Hwang [UNESP]
Publication Date: 2019
Other Authors: Nunes, Willian R.B.M., Nahuis, Selene Leya Cerna [UNESP], Sanches, Marcelo A.A. [UNESP], Teixeira, Marcelo C.M. [UNESP], De Carvalho, Aparecido A. [UNESP]
Format: Conference object
Language: eng
Source: Repositório Institucional da UNESP
Download full: http://dx.doi.org/10.1109/CoDIT.2019.8820357
http://hdl.handle.net/11449/197976
Summary: In 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.
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spelling A RISE-based controller fine-tuned by an improved genetic algorithm for human lower limb rehabilitation via neuromuscular electrical stimulationIn 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.Department of Electrical Engineering São Paulo State University UNESPDepartment of Electrical Engineering Federal University of Technology - Paraná UTFPRDepartment of Electrical Engineering São Paulo State University UNESPUniversidade Estadual Paulista (Unesp)UTFPRArcolezi, Heber Hwang [UNESP]Nunes, Willian R.B.M.Nahuis, Selene Leya Cerna [UNESP]Sanches, Marcelo A.A. [UNESP]Teixeira, Marcelo C.M. [UNESP]De Carvalho, Aparecido A. [UNESP]2020-12-12T00:55:36Z2020-12-12T00:55:36Z2019-04-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject1197-1202http://dx.doi.org/10.1109/CoDIT.2019.88203572019 6th International Conference on Control, Decision and Information Technologies, CoDIT 2019, p. 1197-1202.http://hdl.handle.net/11449/19797610.1109/CoDIT.2019.88203572-s2.0-85072820406Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPeng2019 6th International Conference on Control, Decision and Information Technologies, CoDIT 2019info:eu-repo/semantics/openAccess2021-10-23T07:34:15Zoai:repositorio.unesp.br:11449/197976Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestrepositoriounesp@unesp.bropendoar:29462021-10-23T07:34:15Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv A RISE-based controller fine-tuned by an improved genetic algorithm for human lower limb rehabilitation via neuromuscular electrical stimulation
title A RISE-based controller fine-tuned by an improved genetic algorithm for human lower limb rehabilitation via neuromuscular electrical stimulation
spellingShingle A RISE-based controller fine-tuned by an improved genetic algorithm for human lower limb rehabilitation via neuromuscular electrical stimulation
Arcolezi, Heber Hwang [UNESP]
title_short A RISE-based controller fine-tuned by an improved genetic algorithm for human lower limb rehabilitation via neuromuscular electrical stimulation
title_full A RISE-based controller fine-tuned by an improved genetic algorithm for human lower limb rehabilitation via neuromuscular electrical stimulation
title_fullStr A RISE-based controller fine-tuned by an improved genetic algorithm for human lower limb rehabilitation via neuromuscular electrical stimulation
title_full_unstemmed A RISE-based controller fine-tuned by an improved genetic algorithm for human lower limb rehabilitation via neuromuscular electrical stimulation
title_sort A RISE-based controller fine-tuned by an improved genetic algorithm for human lower limb rehabilitation via neuromuscular electrical stimulation
author Arcolezi, Heber Hwang [UNESP]
author_facet Arcolezi, Heber Hwang [UNESP]
Nunes, Willian R.B.M.
Nahuis, Selene Leya Cerna [UNESP]
Sanches, Marcelo A.A. [UNESP]
Teixeira, Marcelo C.M. [UNESP]
De Carvalho, Aparecido A. [UNESP]
author_role author
author2 Nunes, Willian R.B.M.
Nahuis, Selene Leya Cerna [UNESP]
Sanches, Marcelo A.A. [UNESP]
Teixeira, Marcelo C.M. [UNESP]
De Carvalho, Aparecido A. [UNESP]
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
UTFPR
dc.contributor.author.fl_str_mv Arcolezi, Heber Hwang [UNESP]
Nunes, Willian R.B.M.
Nahuis, Selene Leya Cerna [UNESP]
Sanches, Marcelo A.A. [UNESP]
Teixeira, Marcelo C.M. [UNESP]
De Carvalho, Aparecido A. [UNESP]
description In 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.
publishDate 2019
dc.date.none.fl_str_mv 2019-04-01
2020-12-12T00:55:36Z
2020-12-12T00:55:36Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/conferenceObject
format conferenceObject
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1109/CoDIT.2019.8820357
2019 6th International Conference on Control, Decision and Information Technologies, CoDIT 2019, p. 1197-1202.
http://hdl.handle.net/11449/197976
10.1109/CoDIT.2019.8820357
2-s2.0-85072820406
url http://dx.doi.org/10.1109/CoDIT.2019.8820357
http://hdl.handle.net/11449/197976
identifier_str_mv 2019 6th International Conference on Control, Decision and Information Technologies, CoDIT 2019, p. 1197-1202.
10.1109/CoDIT.2019.8820357
2-s2.0-85072820406
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2019 6th International Conference on Control, Decision and Information Technologies, CoDIT 2019
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 1197-1202
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv repositoriounesp@unesp.br
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