Fatigue Detection during Sit-To-Stand Test Based on Surface Electromyography and Acceleration: A Case Study.

The latest studies of the 30-second sit-to-stand (30-STS) test aim to describe it by employing kinematic variables, muscular activity, or fatigue through electromyography (EMG) instead of a number of repetitions. The aim of the present study was to develop a detection system based on acceleration me...

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Detalles Bibliográficos
Autores: Roldán Jiménez, Cristina, Bennett, Paul, Ortiz García, Andrés, Cuesta Vargas, Antonio I
Tipo de recurso: artículo
Fecha de publicación:2019
País:España
Institución:Instituto de Salud Carlos III (ISCIII)
Repositorio:Repisalud
Idioma:inglés
OAI Identifier:oai:repisalud.isciii.es:20.500.12105/17914
Acceso en línea:http://hdl.handle.net/20.500.12105/17914
Access Level:acceso abierto
Palabra clave:Acceleration
Electromyography
Fatigue
Kinematics
Motion analysis
Sit-to-stand
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spelling Fatigue Detection during Sit-To-Stand Test Based on Surface Electromyography and Acceleration: A Case Study.Roldán Jiménez, CristinaBennett, PaulOrtiz García, AndrésCuesta Vargas, Antonio IAccelerationElectromyographyFatigueKinematicsMotion analysisSit-to-standThe latest studies of the 30-second sit-to-stand (30-STS) test aim to describe it by employing kinematic variables, muscular activity, or fatigue through electromyography (EMG) instead of a number of repetitions. The aim of the present study was to develop a detection system based on acceleration measured using a smartphone to analyze fatigue during the 30-STS test with surface electromyography as the criterion. This case study was carried out on one woman, who performed eight trials. EMG data from the lower limbs and trunk muscles, as well as trunk acceleration were recorded. Both signals from eight trials were preprocessed, being averaged and temporarily aligned. The EMG signal was processed, calculating the spectral centroid (SC) by Discrete Fourier Transform, while the acceleration signal was processed by Discrete Wavelet Transform to calculate its energy percentage. Regarding EMG, fatigue in the vastus medialis of the quadriceps appeared as a decrease in SC, with a descending slope of 12% at second 12, indicating fatigue. However, acceleration analysis showed an increase in the percentage of relative energy, acting like fatigue firing at second 19. This assessed fatigue according to two variables of a different nature. The results will help clinicians to obtain information about fatigue using an accessible and inexpensive device, i.e., as a smartphone.20242024-02-1020192019-09-2720192019-09-27research articlehttp://purl.org/coar/resource_type/c_2df8fbb1VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articlehttp://hdl.handle.net/20.500.12105/17914reponame:Repisaludinstname:Instituto de Salud Carlos III (ISCIII)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Attribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:repisalud.isciii.es:20.500.12105/179142026-06-12T12:43:37Z
dc.title.none.fl_str_mv Fatigue Detection during Sit-To-Stand Test Based on Surface Electromyography and Acceleration: A Case Study.
title Fatigue Detection during Sit-To-Stand Test Based on Surface Electromyography and Acceleration: A Case Study.
spellingShingle Fatigue Detection during Sit-To-Stand Test Based on Surface Electromyography and Acceleration: A Case Study.
Roldán Jiménez, Cristina
Acceleration
Electromyography
Fatigue
Kinematics
Motion analysis
Sit-to-stand
title_short Fatigue Detection during Sit-To-Stand Test Based on Surface Electromyography and Acceleration: A Case Study.
title_full Fatigue Detection during Sit-To-Stand Test Based on Surface Electromyography and Acceleration: A Case Study.
title_fullStr Fatigue Detection during Sit-To-Stand Test Based on Surface Electromyography and Acceleration: A Case Study.
title_full_unstemmed Fatigue Detection during Sit-To-Stand Test Based on Surface Electromyography and Acceleration: A Case Study.
title_sort Fatigue Detection during Sit-To-Stand Test Based on Surface Electromyography and Acceleration: A Case Study.
dc.creator.none.fl_str_mv Roldán Jiménez, Cristina
Bennett, Paul
Ortiz García, Andrés
Cuesta Vargas, Antonio I
author Roldán Jiménez, Cristina
author_facet Roldán Jiménez, Cristina
Bennett, Paul
Ortiz García, Andrés
Cuesta Vargas, Antonio I
author_role author
author2 Bennett, Paul
Ortiz García, Andrés
Cuesta Vargas, Antonio I
author2_role author
author
author
dc.contributor.none.fl_str_mv
dc.subject.none.fl_str_mv Acceleration
Electromyography
Fatigue
Kinematics
Motion analysis
Sit-to-stand
topic Acceleration
Electromyography
Fatigue
Kinematics
Motion analysis
Sit-to-stand
description The latest studies of the 30-second sit-to-stand (30-STS) test aim to describe it by employing kinematic variables, muscular activity, or fatigue through electromyography (EMG) instead of a number of repetitions. The aim of the present study was to develop a detection system based on acceleration measured using a smartphone to analyze fatigue during the 30-STS test with surface electromyography as the criterion. This case study was carried out on one woman, who performed eight trials. EMG data from the lower limbs and trunk muscles, as well as trunk acceleration were recorded. Both signals from eight trials were preprocessed, being averaged and temporarily aligned. The EMG signal was processed, calculating the spectral centroid (SC) by Discrete Fourier Transform, while the acceleration signal was processed by Discrete Wavelet Transform to calculate its energy percentage. Regarding EMG, fatigue in the vastus medialis of the quadriceps appeared as a decrease in SC, with a descending slope of 12% at second 12, indicating fatigue. However, acceleration analysis showed an increase in the percentage of relative energy, acting like fatigue firing at second 19. This assessed fatigue according to two variables of a different nature. The results will help clinicians to obtain information about fatigue using an accessible and inexpensive device, i.e., as a smartphone.
publishDate 2019
dc.date.none.fl_str_mv 2019
2019-09-27
2019
2019-09-27
2024
2024-02-10
dc.type.none.fl_str_mv research article
http://purl.org/coar/resource_type/c_2df8fbb1
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/20.500.12105/17914
url http://hdl.handle.net/20.500.12105/17914
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:Repisalud
instname:Instituto de Salud Carlos III (ISCIII)
instname_str Instituto de Salud Carlos III (ISCIII)
reponame_str Repisalud
collection Repisalud
repository.name.fl_str_mv
repository.mail.fl_str_mv
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