Muscular synergy classification and myoelectric control using high-order cross-cumulants

Autores
Orosco, Eugenio Conrado; Di Sciascio, Fernando Agustín
Año de publicación
2017
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
High-order statistics (HOS) are well suited for describing non-Gaussian random processes. These techniques are increasingly being employed in myoelectric research, on both time and frequency domain techniques. This work presents HOS-based techniques using only HOS time domain features to classify myoelectric signals. The auto-, cross- and full- (joint) third-order cumulants are evaluated as EMG-signal feature vectors to be compared between them. Four surface EMG signals were processed for classify motions from the upper limbs. Synergy among channels is characterized by the features in both auto and cross modes, and their incidences for classifying five or six movements are analyzed. In contrast to the third-order auto-cumulants, it had been verified that the third-order cross-cumulants have the same classification rate by working with five or six movements. A myoelectric control scheme and its experimental application were executed with normal and disabled subjects, reaching a classification rates of 90%, in average. Accuracy in online experiments was similar to the off-line classification rate.
Fil: Orosco, Eugenio Conrado. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Automática. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Automática; Argentina
Fil: Di Sciascio, Fernando Agustín. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Automática. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Automática; Argentina
Materia
Cross-Cumulants
Hos
Muscular Synergy
Myoelectric Control
Semg
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/63543
Acceder
id CONICETDig_d229ce56c45e992b30c2855407199b91
oai_identifier_str oai:ri.conicet.gov.ar:11336/63543
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Muscular synergy classification and myoelectric control using high-order cross-cumulantsOrosco, Eugenio ConradoDi Sciascio, Fernando AgustínCross-CumulantsHosMuscular SynergyMyoelectric ControlSemghttps://purl.org/becyt/ford/2.2https://purl.org/becyt/ford/2High-order statistics (HOS) are well suited for describing non-Gaussian random processes. These techniques are increasingly being employed in myoelectric research, on both time and frequency domain techniques. This work presents HOS-based techniques using only HOS time domain features to classify myoelectric signals. The auto-, cross- and full- (joint) third-order cumulants are evaluated as EMG-signal feature vectors to be compared between them. Four surface EMG signals were processed for classify motions from the upper limbs. Synergy among channels is characterized by the features in both auto and cross modes, and their incidences for classifying five or six movements are analyzed. In contrast to the third-order auto-cumulants, it had been verified that the third-order cross-cumulants have the same classification rate by working with five or six movements. A myoelectric control scheme and its experimental application were executed with normal and disabled subjects, reaching a classification rates of 90%, in average. Accuracy in online experiments was similar to the off-line classification rate.Fil: Orosco, Eugenio Conrado. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Automática. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Automática; ArgentinaFil: Di Sciascio, Fernando Agustín. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Automática. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Automática; ArgentinaSpringer2017-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/63543Orosco, Eugenio Conrado; Di Sciascio, Fernando Agustín; Muscular synergy classification and myoelectric control using high-order cross-cumulants; Springer; Neural Computing And Applications; 28; 10; 10-2017; 2979-29930941-06431433-3058CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1007/s00521-017-2927-6info:eu-repo/semantics/altIdentifier/url/https://link.springer.com/article/10.1007%2Fs00521-017-2927-6info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T14:22:25Zoai:ri.conicet.gov.ar:11336/63543instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-15 14:22:26.055CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Muscular synergy classification and myoelectric control using high-order cross-cumulants
title Muscular synergy classification and myoelectric control using high-order cross-cumulants
spellingShingle Muscular synergy classification and myoelectric control using high-order cross-cumulants
Orosco, Eugenio Conrado
Cross-Cumulants
Hos
Muscular Synergy
Myoelectric Control
Semg
title_short Muscular synergy classification and myoelectric control using high-order cross-cumulants
title_full Muscular synergy classification and myoelectric control using high-order cross-cumulants
title_fullStr Muscular synergy classification and myoelectric control using high-order cross-cumulants
title_full_unstemmed Muscular synergy classification and myoelectric control using high-order cross-cumulants
title_sort Muscular synergy classification and myoelectric control using high-order cross-cumulants
dc.creator.none.fl_str_mv Orosco, Eugenio Conrado
Di Sciascio, Fernando Agustín
author Orosco, Eugenio Conrado
author_facet Orosco, Eugenio Conrado
Di Sciascio, Fernando Agustín
author_role author
author2 Di Sciascio, Fernando Agustín
author2_role author
dc.subject.none.fl_str_mv Cross-Cumulants
Hos
Muscular Synergy
Myoelectric Control
Semg
topic Cross-Cumulants
Hos
Muscular Synergy
Myoelectric Control
Semg
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.2
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv High-order statistics (HOS) are well suited for describing non-Gaussian random processes. These techniques are increasingly being employed in myoelectric research, on both time and frequency domain techniques. This work presents HOS-based techniques using only HOS time domain features to classify myoelectric signals. The auto-, cross- and full- (joint) third-order cumulants are evaluated as EMG-signal feature vectors to be compared between them. Four surface EMG signals were processed for classify motions from the upper limbs. Synergy among channels is characterized by the features in both auto and cross modes, and their incidences for classifying five or six movements are analyzed. In contrast to the third-order auto-cumulants, it had been verified that the third-order cross-cumulants have the same classification rate by working with five or six movements. A myoelectric control scheme and its experimental application were executed with normal and disabled subjects, reaching a classification rates of 90%, in average. Accuracy in online experiments was similar to the off-line classification rate.
Fil: Orosco, Eugenio Conrado. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Automática. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Automática; Argentina
Fil: Di Sciascio, Fernando Agustín. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Automática. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Automática; Argentina
description High-order statistics (HOS) are well suited for describing non-Gaussian random processes. These techniques are increasingly being employed in myoelectric research, on both time and frequency domain techniques. This work presents HOS-based techniques using only HOS time domain features to classify myoelectric signals. The auto-, cross- and full- (joint) third-order cumulants are evaluated as EMG-signal feature vectors to be compared between them. Four surface EMG signals were processed for classify motions from the upper limbs. Synergy among channels is characterized by the features in both auto and cross modes, and their incidences for classifying five or six movements are analyzed. In contrast to the third-order auto-cumulants, it had been verified that the third-order cross-cumulants have the same classification rate by working with five or six movements. A myoelectric control scheme and its experimental application were executed with normal and disabled subjects, reaching a classification rates of 90%, in average. Accuracy in online experiments was similar to the off-line classification rate.
publishDate 2017
dc.date.none.fl_str_mv 2017-10
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/63543
Orosco, Eugenio Conrado; Di Sciascio, Fernando Agustín; Muscular synergy classification and myoelectric control using high-order cross-cumulants; Springer; Neural Computing And Applications; 28; 10; 10-2017; 2979-2993
0941-0643
1433-3058
CONICET Digital
CONICET
url http://hdl.handle.net/11336/63543
identifier_str_mv Orosco, Eugenio Conrado; Di Sciascio, Fernando Agustín; Muscular synergy classification and myoelectric control using high-order cross-cumulants; Springer; Neural Computing And Applications; 28; 10; 10-2017; 2979-2993
0941-0643
1433-3058
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1007/s00521-017-2927-6
info:eu-repo/semantics/altIdentifier/url/https://link.springer.com/article/10.1007%2Fs00521-017-2927-6
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
_version_ 1846082623507529728
score 13.22299

Publicaciones similares