Commanding a robotic wheelchair with a high-frequency steady-state visual evoked potential based brain-computer interface

Autores
Diez, Pablo Federico; Torres Müller, Sandra M.; Mut, Vicente Antonio; Laciar Leber, Eric; Avila Perona, Enrique Mario; Freire Bastos Filho, Teodiano; Sarcinelli Filho, Mário
Año de publicación
2013
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
This work presents a brain–computer interface (BCI) used to operate a robotic wheelchair. The experiments were performed on 15 subjects (13 of them healthy). The BCI is based on steady-state visual-evoked potentials (SSVEP) and the stimuli flickering are performed at high frequency (37, 38, 39 and 40 Hz). This high frequency stimulation scheme can reduce or even eliminate visual fatigue, allowing the user to achieve a stable performance for long term BCI operation. The BCI system uses power-spectral density analysis associated to three bipolar electroencephalographic channels. As the results show, 2 subjects were reported as SSVEP-BCI illiterates (not able to use the BCI), and, consequently, 13 subjects (12 of them healthy) could navigate the wheelchair in a room with obstacles arranged in four distinct configurations. Volunteers expressed neither discomfort nor fatigue due to flickering stimulation. A transmission rate of up to 72.5 bits/min was obtained, with an average of 44.6 bits/min in four trials. These results show that people could effectively navigate a robotic wheelchair using a SSVEP-based BCI with high frequency flickering stimulation.
Fil: Diez, Pablo Federico. Universidad Nacional de San Juan. Facultad de Ingeniería. Departamento de Electrónica y Automática. Gabinete de Tecnología Médica; Argentina. 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: Torres Müller, Sandra M.. Universidade Federal Do Espirito Santo; Brasil
Fil: Mut, Vicente Antonio. 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: Laciar Leber, Eric. Universidad Nacional de San Juan. Facultad de Ingeniería. Departamento de Electrónica y Automática. Gabinete de Tecnología Médica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Avila Perona, Enrique Mario. 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: Freire Bastos Filho, Teodiano. Universidade Federal Do Espirito Santo. Centro Tecnológico. Departamento de Ingeniería Eléctrica; Brasil
Fil: Sarcinelli Filho, Mário. Universidade Federal Do Espirito Santo. Centro Tecnológico. Departamento de Ingeniería Eléctrica; Brasil
Materia
Brain-Computer Interface (Bci)
Steady-State Visual Evoked Potentials (Ssvep)
Robotic Wheelchair
Electroencephalogram (Eeg)
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:11336/24716
Acceder
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network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Commanding a robotic wheelchair with a high-frequency steady-state visual evoked potential based brain-computer interfaceDiez, Pablo FedericoTorres Müller, Sandra M.Mut, Vicente AntonioLaciar Leber, EricAvila Perona, Enrique MarioFreire Bastos Filho, TeodianoSarcinelli Filho, MárioBrain-Computer Interface (Bci)Steady-State Visual Evoked Potentials (Ssvep)Robotic WheelchairElectroencephalogram (Eeg)https://purl.org/becyt/ford/2.2https://purl.org/becyt/ford/2This work presents a brain–computer interface (BCI) used to operate a robotic wheelchair. The experiments were performed on 15 subjects (13 of them healthy). The BCI is based on steady-state visual-evoked potentials (SSVEP) and the stimuli flickering are performed at high frequency (37, 38, 39 and 40 Hz). This high frequency stimulation scheme can reduce or even eliminate visual fatigue, allowing the user to achieve a stable performance for long term BCI operation. The BCI system uses power-spectral density analysis associated to three bipolar electroencephalographic channels. As the results show, 2 subjects were reported as SSVEP-BCI illiterates (not able to use the BCI), and, consequently, 13 subjects (12 of them healthy) could navigate the wheelchair in a room with obstacles arranged in four distinct configurations. Volunteers expressed neither discomfort nor fatigue due to flickering stimulation. A transmission rate of up to 72.5 bits/min was obtained, with an average of 44.6 bits/min in four trials. These results show that people could effectively navigate a robotic wheelchair using a SSVEP-based BCI with high frequency flickering stimulation.Fil: Diez, Pablo Federico. Universidad Nacional de San Juan. Facultad de Ingeniería. Departamento de Electrónica y Automática. Gabinete de Tecnología Médica; Argentina. 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: Torres Müller, Sandra M.. Universidade Federal Do Espirito Santo; BrasilFil: Mut, Vicente Antonio. 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: Laciar Leber, Eric. Universidad Nacional de San Juan. Facultad de Ingeniería. Departamento de Electrónica y Automática. Gabinete de Tecnología Médica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Avila Perona, Enrique Mario. 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: Freire Bastos Filho, Teodiano. Universidade Federal Do Espirito Santo. Centro Tecnológico. Departamento de Ingeniería Eléctrica; BrasilFil: Sarcinelli Filho, Mário. Universidade Federal Do Espirito Santo. Centro Tecnológico. Departamento de Ingeniería Eléctrica; BrasilElsevier2013-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/24716Diez, Pablo Federico; Torres Müller, Sandra M.; Mut, Vicente Antonio; Laciar Leber, Eric; Avila Perona, Enrique Mario; et al.; Commanding a robotic wheelchair with a high-frequency steady-state visual evoked potential based brain-computer interface; Elsevier; Medical Engineering & Physics; 35; 8; 1-2013; 1155-11641350-4533CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S1350453312003335info:eu-repo/semantics/altIdentifier/doi/10.1016/j.medengphy.2012.12.005info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T10:11:13Zoai:ri.conicet.gov.ar:11336/24716instacron: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:34982025-09-03 10:11:14.01CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Commanding a robotic wheelchair with a high-frequency steady-state visual evoked potential based brain-computer interface
title Commanding a robotic wheelchair with a high-frequency steady-state visual evoked potential based brain-computer interface
spellingShingle Commanding a robotic wheelchair with a high-frequency steady-state visual evoked potential based brain-computer interface
Diez, Pablo Federico
Brain-Computer Interface (Bci)
Steady-State Visual Evoked Potentials (Ssvep)
Robotic Wheelchair
Electroencephalogram (Eeg)
title_short Commanding a robotic wheelchair with a high-frequency steady-state visual evoked potential based brain-computer interface
title_full Commanding a robotic wheelchair with a high-frequency steady-state visual evoked potential based brain-computer interface
title_fullStr Commanding a robotic wheelchair with a high-frequency steady-state visual evoked potential based brain-computer interface
title_full_unstemmed Commanding a robotic wheelchair with a high-frequency steady-state visual evoked potential based brain-computer interface
title_sort Commanding a robotic wheelchair with a high-frequency steady-state visual evoked potential based brain-computer interface
dc.creator.none.fl_str_mv Diez, Pablo Federico
Torres Müller, Sandra M.
Mut, Vicente Antonio
Laciar Leber, Eric
Avila Perona, Enrique Mario
Freire Bastos Filho, Teodiano
Sarcinelli Filho, Mário
author Diez, Pablo Federico
author_facet Diez, Pablo Federico
Torres Müller, Sandra M.
Mut, Vicente Antonio
Laciar Leber, Eric
Avila Perona, Enrique Mario
Freire Bastos Filho, Teodiano
Sarcinelli Filho, Mário
author_role author
author2 Torres Müller, Sandra M.
Mut, Vicente Antonio
Laciar Leber, Eric
Avila Perona, Enrique Mario
Freire Bastos Filho, Teodiano
Sarcinelli Filho, Mário
author2_role author
author
author
author
author
author
dc.subject.none.fl_str_mv Brain-Computer Interface (Bci)
Steady-State Visual Evoked Potentials (Ssvep)
Robotic Wheelchair
Electroencephalogram (Eeg)
topic Brain-Computer Interface (Bci)
Steady-State Visual Evoked Potentials (Ssvep)
Robotic Wheelchair
Electroencephalogram (Eeg)
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.2
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv This work presents a brain–computer interface (BCI) used to operate a robotic wheelchair. The experiments were performed on 15 subjects (13 of them healthy). The BCI is based on steady-state visual-evoked potentials (SSVEP) and the stimuli flickering are performed at high frequency (37, 38, 39 and 40 Hz). This high frequency stimulation scheme can reduce or even eliminate visual fatigue, allowing the user to achieve a stable performance for long term BCI operation. The BCI system uses power-spectral density analysis associated to three bipolar electroencephalographic channels. As the results show, 2 subjects were reported as SSVEP-BCI illiterates (not able to use the BCI), and, consequently, 13 subjects (12 of them healthy) could navigate the wheelchair in a room with obstacles arranged in four distinct configurations. Volunteers expressed neither discomfort nor fatigue due to flickering stimulation. A transmission rate of up to 72.5 bits/min was obtained, with an average of 44.6 bits/min in four trials. These results show that people could effectively navigate a robotic wheelchair using a SSVEP-based BCI with high frequency flickering stimulation.
Fil: Diez, Pablo Federico. Universidad Nacional de San Juan. Facultad de Ingeniería. Departamento de Electrónica y Automática. Gabinete de Tecnología Médica; Argentina. 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: Torres Müller, Sandra M.. Universidade Federal Do Espirito Santo; Brasil
Fil: Mut, Vicente Antonio. 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: Laciar Leber, Eric. Universidad Nacional de San Juan. Facultad de Ingeniería. Departamento de Electrónica y Automática. Gabinete de Tecnología Médica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Avila Perona, Enrique Mario. 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: Freire Bastos Filho, Teodiano. Universidade Federal Do Espirito Santo. Centro Tecnológico. Departamento de Ingeniería Eléctrica; Brasil
Fil: Sarcinelli Filho, Mário. Universidade Federal Do Espirito Santo. Centro Tecnológico. Departamento de Ingeniería Eléctrica; Brasil
description This work presents a brain–computer interface (BCI) used to operate a robotic wheelchair. The experiments were performed on 15 subjects (13 of them healthy). The BCI is based on steady-state visual-evoked potentials (SSVEP) and the stimuli flickering are performed at high frequency (37, 38, 39 and 40 Hz). This high frequency stimulation scheme can reduce or even eliminate visual fatigue, allowing the user to achieve a stable performance for long term BCI operation. The BCI system uses power-spectral density analysis associated to three bipolar electroencephalographic channels. As the results show, 2 subjects were reported as SSVEP-BCI illiterates (not able to use the BCI), and, consequently, 13 subjects (12 of them healthy) could navigate the wheelchair in a room with obstacles arranged in four distinct configurations. Volunteers expressed neither discomfort nor fatigue due to flickering stimulation. A transmission rate of up to 72.5 bits/min was obtained, with an average of 44.6 bits/min in four trials. These results show that people could effectively navigate a robotic wheelchair using a SSVEP-based BCI with high frequency flickering stimulation.
publishDate 2013
dc.date.none.fl_str_mv 2013-01
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/11336/24716
Diez, Pablo Federico; Torres Müller, Sandra M.; Mut, Vicente Antonio; Laciar Leber, Eric; Avila Perona, Enrique Mario; et al.; Commanding a robotic wheelchair with a high-frequency steady-state visual evoked potential based brain-computer interface; Elsevier; Medical Engineering & Physics; 35; 8; 1-2013; 1155-1164
1350-4533
CONICET Digital
CONICET
url http://hdl.handle.net/11336/24716
identifier_str_mv Diez, Pablo Federico; Torres Müller, Sandra M.; Mut, Vicente Antonio; Laciar Leber, Eric; Avila Perona, Enrique Mario; et al.; Commanding a robotic wheelchair with a high-frequency steady-state visual evoked potential based brain-computer interface; Elsevier; Medical Engineering & Physics; 35; 8; 1-2013; 1155-1164
1350-4533
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S1350453312003335
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.medengphy.2012.12.005
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
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
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
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score 13.13397

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