A RISE-based controller fine-tuned by an improved genetic algorithm for human lower limb rehabilitation via neuromuscular electrical stimulation
Main Author: | |
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Publication Date: | 2019 |
Other Authors: | , , , , |
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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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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1834483726853079040 |