An Implicit Brain Computer Interface Supported by Gaze Monitoring for Virtual Therapy

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Advanced Brain-Computer Interface (BCI) paradigms aim to solve some problems as BCI illiteracy and unfamiliarity of the subjects to be able to control their elicited motor imagery (MI) successfully, hence improving training time and performance of BCI systems. This work evaluates the effect and perf...

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Detalles Bibliográficos
Autores: Achanccaray, David, Mylonas, George, Andreu-Perez, Javier
Formato: artículo
Fecha de Publicación:2019
Institución:Consejo Nacional de Ciencia Tecnología e Innovación
Repositorio:CONCYTEC-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorio.concytec.gob.pe:20.500.12390/2832
Enlace del recurso:https://hdl.handle.net/20.500.12390/2832
https://doi.org/10.1109/SMC.2019.8913962
Nivel de acceso:acceso abierto
Materia:Training
Resists
Task analysis
Electroencephalography
Support vector machines
Monitoring
Brain
https://purl.org/pe-repo/ocde/ford#1.02.01
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network_acronym_str CONC
network_name_str CONCYTEC-Institucional
repository_id_str 4689
dc.title.none.fl_str_mv An Implicit Brain Computer Interface Supported by Gaze Monitoring for Virtual Therapy
title An Implicit Brain Computer Interface Supported by Gaze Monitoring for Virtual Therapy
spellingShingle An Implicit Brain Computer Interface Supported by Gaze Monitoring for Virtual Therapy
Achanccaray, David
Training
Resists
Task analysis
Electroencephalography
Support vector machines
Monitoring
Brain
https://purl.org/pe-repo/ocde/ford#1.02.01
title_short An Implicit Brain Computer Interface Supported by Gaze Monitoring for Virtual Therapy
title_full An Implicit Brain Computer Interface Supported by Gaze Monitoring for Virtual Therapy
title_fullStr An Implicit Brain Computer Interface Supported by Gaze Monitoring for Virtual Therapy
title_full_unstemmed An Implicit Brain Computer Interface Supported by Gaze Monitoring for Virtual Therapy
title_sort An Implicit Brain Computer Interface Supported by Gaze Monitoring for Virtual Therapy
author Achanccaray, David
author_facet Achanccaray, David
Mylonas, George
Andreu-Perez, Javier
author_role author
author2 Mylonas, George
Andreu-Perez, Javier
author2_role author
author
dc.contributor.author.fl_str_mv Achanccaray, David
Mylonas, George
Andreu-Perez, Javier
dc.subject.none.fl_str_mv Training
topic Training
Resists
Task analysis
Electroencephalography
Support vector machines
Monitoring
Brain
https://purl.org/pe-repo/ocde/ford#1.02.01
dc.subject.es_PE.fl_str_mv Resists
Task analysis
Electroencephalography
Support vector machines
Monitoring
Brain
dc.subject.ocde.none.fl_str_mv https://purl.org/pe-repo/ocde/ford#1.02.01
description Advanced Brain-Computer Interface (BCI) paradigms aim to solve some problems as BCI illiteracy and unfamiliarity of the subjects to be able to control their elicited motor imagery (MI) successfully, hence improving training time and performance of BCI systems. This work evaluates the effect and performance of an Implicit BCI supported by the Gaze Monitoring (IBCI-GM) paradigm for virtual rehabilitation therapy of patients suffering from partial or total paralysis of their upper limbs; this paradigm also was compared with alternative forms of advanced BCI methods such as Virtual Reality-based BCI (VR-BCI) with a head-mounted display (HMD) and a computer screen (CS). Eight subjects participated in the experiments; four subjects tested the VR-BCI with a CS, and the rest of them tested both BCI advanced methods (IBCI-GM and VR-BCI with an HMD). The subjects were asked to control a virtual arm through MI of flexion and extension movements. The VR-BCI HMD was the approached best method; however, IBCI-GM had significant results and was more practical for users, but it depends on the ability to perform eye movements to be applied by patients. Therefore, these methods should be tested with more subjects to have definitive results.
publishDate 2019
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 2019
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12390/2832
dc.identifier.doi.none.fl_str_mv https://doi.org/10.1109/SMC.2019.8913962
url https://hdl.handle.net/20.500.12390/2832
https://doi.org/10.1109/SMC.2019.8913962
dc.language.iso.none.fl_str_mv eng
language eng
dc.relation.ispartof.none.fl_str_mv 2019 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS (SMC)
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv IEEE
publisher.none.fl_str_mv IEEE
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 Publicationrp03820600rp07693600rp03817600Achanccaray, DavidMylonas, GeorgeAndreu-Perez, Javier2024-05-30T23:13:38Z2024-05-30T23:13:38Z2019https://hdl.handle.net/20.500.12390/2832https://doi.org/10.1109/SMC.2019.8913962Advanced Brain-Computer Interface (BCI) paradigms aim to solve some problems as BCI illiteracy and unfamiliarity of the subjects to be able to control their elicited motor imagery (MI) successfully, hence improving training time and performance of BCI systems. This work evaluates the effect and performance of an Implicit BCI supported by the Gaze Monitoring (IBCI-GM) paradigm for virtual rehabilitation therapy of patients suffering from partial or total paralysis of their upper limbs; this paradigm also was compared with alternative forms of advanced BCI methods such as Virtual Reality-based BCI (VR-BCI) with a head-mounted display (HMD) and a computer screen (CS). Eight subjects participated in the experiments; four subjects tested the VR-BCI with a CS, and the rest of them tested both BCI advanced methods (IBCI-GM and VR-BCI with an HMD). The subjects were asked to control a virtual arm through MI of flexion and extension movements. The VR-BCI HMD was the approached best method; however, IBCI-GM had significant results and was more practical for users, but it depends on the ability to perform eye movements to be applied by patients. Therefore, these methods should be tested with more subjects to have definitive results.Fondo Nacional de Desarrollo Científico y Tecnológico - FondecytengIEEE2019 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS (SMC)info:eu-repo/semantics/openAccessTrainingResists-1Task analysis-1Electroencephalography-1Support vector machines-1Monitoring-1Brain-1https://purl.org/pe-repo/ocde/ford#1.02.01-1An Implicit Brain Computer Interface Supported by Gaze Monitoring for Virtual Therapyinfo:eu-repo/semantics/articlereponame:CONCYTEC-Institucionalinstname:Consejo Nacional de Ciencia Tecnología e Innovacióninstacron:CONCYTEC#PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE#20.500.12390/2832oai:repositorio.concytec.gob.pe:20.500.12390/28322024-05-30 15:25:40.0http://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#<Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="ce15bbe0-9059-4900-a6fb-11858d2ab914"> <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>An Implicit Brain Computer Interface Supported by Gaze Monitoring for Virtual Therapy</Title> <PublishedIn> <Publication> <Title>2019 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS (SMC)</Title> </Publication> </PublishedIn> <PublicationDate>2019</PublicationDate> <DOI>https://doi.org/10.1109/SMC.2019.8913962</DOI> <Authors> <Author> <DisplayName>Achanccaray, David</DisplayName> <Person id="rp03820" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Mylonas, George</DisplayName> <Person id="rp07693" /> <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>IEEE</DisplayName> <OrgUnit /> </Publisher> </Publishers> <Keyword>Training</Keyword> <Keyword>Resists</Keyword> <Keyword>Task analysis</Keyword> <Keyword>Electroencephalography</Keyword> <Keyword>Support vector machines</Keyword> <Keyword>Monitoring</Keyword> <Keyword>Brain</Keyword> <Abstract>Advanced Brain-Computer Interface (BCI) paradigms aim to solve some problems as BCI illiteracy and unfamiliarity of the subjects to be able to control their elicited motor imagery (MI) successfully, hence improving training time and performance of BCI systems. This work evaluates the effect and performance of an Implicit BCI supported by the Gaze Monitoring (IBCI-GM) paradigm for virtual rehabilitation therapy of patients suffering from partial or total paralysis of their upper limbs; this paradigm also was compared with alternative forms of advanced BCI methods such as Virtual Reality-based BCI (VR-BCI) with a head-mounted display (HMD) and a computer screen (CS). Eight subjects participated in the experiments; four subjects tested the VR-BCI with a CS, and the rest of them tested both BCI advanced methods (IBCI-GM and VR-BCI with an HMD). The subjects were asked to control a virtual arm through MI of flexion and extension movements. The VR-BCI HMD was the approached best method; however, IBCI-GM had significant results and was more practical for users, but it depends on the ability to perform eye movements to be applied by patients. 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