Performance predictors of motor imagery brain-computer interface based on spatial abilities for upper limb rehabilitation

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Motor Imagery based BCIs (MI-BCIs) allow the control of devices and communication by imagining different mental tasks. Despite many years of research, BCIs are still not the most accurate systems to control applications, due to two main factors: signal processing with classification, and users. It i...

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Detalles Bibliográficos
Autores: Pacheco, Kevin, Acuna, Kevin, Carranza, Erick, Achanccaray, David, Andreu-Perez, Javier
Formato: objeto de conferencia
Fecha de Publicación:2017
Institución:Consejo Nacional de Ciencia Tecnología e Innovación
Repositorio:CONCYTEC-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorio.concytec.gob.pe:20.500.12390/1314
Enlace del recurso:https://hdl.handle.net/20.500.12390/1314
https://doi.org/10.1109/embc.2017.8036998
Nivel de acceso:acceso abierto
Materia:Neurorehabilitation
Brain-computer/machine interface
Neural signal processing
https://purl.org/pe-repo/ocde/ford#3.02.25
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network_acronym_str CONC
network_name_str CONCYTEC-Institucional
repository_id_str 4689
dc.title.none.fl_str_mv Performance predictors of motor imagery brain-computer interface based on spatial abilities for upper limb rehabilitation
title Performance predictors of motor imagery brain-computer interface based on spatial abilities for upper limb rehabilitation
spellingShingle Performance predictors of motor imagery brain-computer interface based on spatial abilities for upper limb rehabilitation
Pacheco, Kevin
Neurorehabilitation
Brain-computer/machine interface
Neural signal processing
https://purl.org/pe-repo/ocde/ford#3.02.25
title_short Performance predictors of motor imagery brain-computer interface based on spatial abilities for upper limb rehabilitation
title_full Performance predictors of motor imagery brain-computer interface based on spatial abilities for upper limb rehabilitation
title_fullStr Performance predictors of motor imagery brain-computer interface based on spatial abilities for upper limb rehabilitation
title_full_unstemmed Performance predictors of motor imagery brain-computer interface based on spatial abilities for upper limb rehabilitation
title_sort Performance predictors of motor imagery brain-computer interface based on spatial abilities for upper limb rehabilitation
author Pacheco, Kevin
author_facet Pacheco, Kevin
Acuna, Kevin
Carranza, Erick
Achanccaray, David
Andreu-Perez, Javier
author_role author
author2 Acuna, Kevin
Carranza, Erick
Achanccaray, David
Andreu-Perez, Javier
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Pacheco, Kevin
Acuna, Kevin
Carranza, Erick
Achanccaray, David
Andreu-Perez, Javier
dc.subject.none.fl_str_mv Neurorehabilitation
topic Neurorehabilitation
Brain-computer/machine interface
Neural signal processing
https://purl.org/pe-repo/ocde/ford#3.02.25
dc.subject.es_PE.fl_str_mv Brain-computer/machine interface
Neural signal processing
dc.subject.ocde.none.fl_str_mv https://purl.org/pe-repo/ocde/ford#3.02.25
description Motor Imagery based BCIs (MI-BCIs) allow the control of devices and communication by imagining different mental tasks. Despite many years of research, BCIs are still not the most accurate systems to control applications, due to two main factors: signal processing with classification, and users. It is admitted that BCI control involves certain characteristics and abilities in its users for optimal results. In this study, spatial abilities are evaluated in relation to MI-BCI control regarding flexion and extension mental tasks. Results show considerable correlation (r=0.49) between block design test (visual motor execution and spatial visualization) and extension-rest tasks. Additionally, rotation test (mental rotation task) presents significant correlation (r=0.56) to flexion-rest tasks.
publishDate 2017
dc.date.accessioned.none.fl_str_mv 2024-05-30T23:13:38Z
dc.date.available.none.fl_str_mv 2024-05-30T23:13:38Z
dc.date.issued.fl_str_mv 2017-07
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
format conferenceObject
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12390/1314
dc.identifier.doi.none.fl_str_mv https://doi.org/10.1109/embc.2017.8036998
url https://hdl.handle.net/20.500.12390/1314
https://doi.org/10.1109/embc.2017.8036998
dc.language.iso.none.fl_str_mv eng
language eng
dc.relation.ispartof.none.fl_str_mv 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers Inc.
publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers Inc.
dc.source.none.fl_str_mv reponame:CONCYTEC-Institucional
instname:Consejo Nacional de Ciencia Tecnología e Innovación
instacron:CONCYTEC
instname_str Consejo Nacional de Ciencia Tecnología e Innovación
instacron_str CONCYTEC
institution CONCYTEC
reponame_str CONCYTEC-Institucional
collection CONCYTEC-Institucional
repository.name.fl_str_mv Repositorio Institucional CONCYTEC
repository.mail.fl_str_mv repositorio@concytec.gob.pe
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spelling Publicationrp03818600rp03816600rp03819600rp03820600rp03817600Pacheco, KevinAcuna, KevinCarranza, ErickAchanccaray, DavidAndreu-Perez, Javier2024-05-30T23:13:38Z2024-05-30T23:13:38Z2017-07https://hdl.handle.net/20.500.12390/1314https://doi.org/10.1109/embc.2017.8036998Motor Imagery based BCIs (MI-BCIs) allow the control of devices and communication by imagining different mental tasks. Despite many years of research, BCIs are still not the most accurate systems to control applications, due to two main factors: signal processing with classification, and users. It is admitted that BCI control involves certain characteristics and abilities in its users for optimal results. In this study, spatial abilities are evaluated in relation to MI-BCI control regarding flexion and extension mental tasks. Results show considerable correlation (r=0.49) between block design test (visual motor execution and spatial visualization) and extension-rest tasks. Additionally, rotation test (mental rotation task) presents significant correlation (r=0.56) to flexion-rest tasks.Fondo Nacional de Desarrollo Científico y Tecnológico - FondecytengInstitute of Electrical and Electronics Engineers Inc.2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)info:eu-repo/semantics/openAccessNeurorehabilitationBrain-computer/machine interface-1Neural signal processing-1https://purl.org/pe-repo/ocde/ford#3.02.25-1Performance predictors of motor imagery brain-computer interface based on spatial abilities for upper limb rehabilitationinfo:eu-repo/semantics/conferenceObjectreponame:CONCYTEC-Institucionalinstname:Consejo Nacional de Ciencia Tecnología e Innovacióninstacron:CONCYTEC20.500.12390/1314oai:repositorio.concytec.gob.pe:20.500.12390/13142024-05-30 16:02:38.96http://purl.org/coar/access_right/c_14cbinfo:eu-repo/semantics/closedAccessmetadata only accesshttps://repositorio.concytec.gob.peRepositorio Institucional CONCYTECrepositorio@concytec.gob.pe#PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE#<Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="10cb0119-506b-48d9-8955-886bc3e77ed6"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Performance predictors of motor imagery brain-computer interface based on spatial abilities for upper limb rehabilitation</Title> <PublishedIn> <Publication> <Title>2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)</Title> </Publication> </PublishedIn> <PublicationDate>2017-07</PublicationDate> <DOI>https://doi.org/10.1109/embc.2017.8036998</DOI> <Authors> <Author> <DisplayName>Pacheco, Kevin</DisplayName> <Person id="rp03818" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Acuna, Kevin</DisplayName> <Person id="rp03816" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Carranza, Erick</DisplayName> <Person id="rp03819" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Achanccaray, David</DisplayName> <Person id="rp03820" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Andreu-Perez, Javier</DisplayName> <Person id="rp03817" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Institute of Electrical and Electronics Engineers Inc.</DisplayName> <OrgUnit /> </Publisher> </Publishers> <Keyword>Neurorehabilitation</Keyword> <Keyword>Brain-computer/machine interface</Keyword> <Keyword>Neural signal processing</Keyword> <Abstract>Motor Imagery based BCIs (MI-BCIs) allow the control of devices and communication by imagining different mental tasks. Despite many years of research, BCIs are still not the most accurate systems to control applications, due to two main factors: signal processing with classification, and users. It is admitted that BCI control involves certain characteristics and abilities in its users for optimal results. In this study, spatial abilities are evaluated in relation to MI-BCI control regarding flexion and extension mental tasks. Results show considerable correlation (r=0.49) between block design test (visual motor execution and spatial visualization) and extension-rest tasks. Additionally, rotation test (mental rotation task) presents significant correlation (r=0.56) to flexion-rest tasks.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication> -1
score 13.413352
Performance predictors of motor imagery brain-computer interface based on spatial abilities for upper limb rehabilitation
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