A novel approach of independent brain-computer interface based on SSVEP
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Tipo de documento: | Tese |
Idioma: | eng |
Título da fonte: | Repositório Institucional da Universidade Federal do Espírito Santo (riUfes) |
Texto Completo: | http://repositorio.ufes.br/handle/10/9683 |
Resumo: | Over the past ten years, Brain Computer Interfaces (BCIs) based on Steady- State Visual Evoked Potentials (SSVEP) have attracted the attention of many researchers due to the promissory results and the high accuracy rates achieved. This type of BCI provides to people with severe neuromotor difficulties the possibility to communicate with the world around them using visual attention modulation to blinking lights at a given frequency. This thesis aiming at developing a new approach of Independent BCI, in which users are not required to perform neuromuscular tasks to select visual targets, a feature that distinguishes it from traditional SSVEP-BCIs. Thus, people with severe motor disabilities as Amyotrophic Lateral Sclerosis (ALS) have a new alternative channel to communicate with the world around them using brain signals. Several contributions were done in this thesis, such as: improvement of the feature extractor called Multivariate Synchronization Index (MSI) for detecting evoked potentials; development of a new method for detecting evoked potentials through correlating multidimensional models (tensors); a first study on the influence of colored stimuli in SSVEPs detection using LEDs; the development of the concept of Compressive sensing applied to SSVEPs; and, finally, the development of a novel independent BCI under an approach named Figure-Ground Perception (FGP) |
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Ferreira, AndréMüller, Sandra Mara TorresBastos Filho, Teodiano FreireTello, Richard Junior Manuel GodinezCiarelli, Patrick MarquesLima, Eduardo Roncon deSá, Antônio Maurício Miranda de2018-08-02T00:01:45Z2018-08-012018-08-02T00:01:45Z2016-09-01Over the past ten years, Brain Computer Interfaces (BCIs) based on Steady- State Visual Evoked Potentials (SSVEP) have attracted the attention of many researchers due to the promissory results and the high accuracy rates achieved. This type of BCI provides to people with severe neuromotor difficulties the possibility to communicate with the world around them using visual attention modulation to blinking lights at a given frequency. This thesis aiming at developing a new approach of Independent BCI, in which users are not required to perform neuromuscular tasks to select visual targets, a feature that distinguishes it from traditional SSVEP-BCIs. Thus, people with severe motor disabilities as Amyotrophic Lateral Sclerosis (ALS) have a new alternative channel to communicate with the world around them using brain signals. Several contributions were done in this thesis, such as: improvement of the feature extractor called Multivariate Synchronization Index (MSI) for detecting evoked potentials; development of a new method for detecting evoked potentials through correlating multidimensional models (tensors); a first study on the influence of colored stimuli in SSVEPs detection using LEDs; the development of the concept of Compressive sensing applied to SSVEPs; and, finally, the development of a novel independent BCI under an approach named Figure-Ground Perception (FGP)Durante os últimos dez anos, as Interfaces Cérebro Computador (ICC) baseadas em Potenciais Evocados Visuais de Regime Permanente (SSVEP) têm chamado a atenção de muitos pesquisadores devido aos resultados promissores e as altas taxas de precisão atingidas. Este tipo de ICC permite que pessoas com dificuldades motoras severas possam se comunicar com o mundo exterior através da modulação da atenção visual a luzes piscantes com frequência determinada. Esta Tese de Doutorado tem o intuito de desenvolver um novo enfoque dentro das chamadas ICC Independentes, nas quais os usuários não necessitam executar tarefas neuromusculares para seleção visual de objetivos específicos, característica que a distingue das tradicionais ICCs-SSVEP. Assim, pessoas com difculdades motoras severas, como pessoas com Esclerose Lateral Amiotrófca (ELA), contam com uma nova alternativa de se comunicar através de sinais cerebrais. Diversas contribuições foram realizadas neste trabalho, como, por exemplo, melhoria do algoritmo extrator de características, denominado Índice de Sincronização Multivariável (ou MSI, do Inglês), para a detecção de potenciais evocados; desenvolvimento de um novo método de detecção de potenciais evocados através da correlação entre modelos multidimensionais (tensores); o desenvolvimento do primeiro estudo sobre a influência de estímulos coloridos na detecção de SSVEPs usando LEDs; a aplicação do conceito de Compressão na detecção de SSVEPs; e, fnalmente, o desenvolvimento de uma nova ICC independente que utiliza o enfoque de Percepção Fundo-Figura (ou FGP, do Inglês).Texthttp://repositorio.ufes.br/handle/10/9683engUniversidade Federal do Espírito SantoDoutorado em Engenharia ElétricaPrograma de Pós-Graduação em Engenharia ElétricaUFESBRCentro TecnológicoSinais cerebraisPercepção fundo-figura (FGP)Potenciais evocados visuais de regime permanente (SSVEP)Interface cérebro-computadorPotencial evocado (Eletrofisiologia)Engenharia Elétrica621.3A novel approach of independent brain-computer interface based on SSVEPinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da Universidade Federal do Espírito Santo (riUfes)instname:Universidade Federal do Espírito Santo (UFES)instacron:UFESORIGINALtese_10281_TeseDoutoradoRichardTello2016.pdfapplication/pdf12331551http://repositorio.ufes.br/bitstreams/05bafc68-204c-4d6a-8f7b-14a307ed997e/download0dae4547527893319ca299b5e22f6234MD5110/96832024-07-17 16:58:24.901oai:repositorio.ufes.br:10/9683http://repositorio.ufes.brRepositório InstitucionalPUBhttp://repositorio.ufes.br/oai/requestopendoar:21082024-10-15T18:00:05.808141Repositório Institucional da Universidade Federal do Espírito Santo (riUfes) - Universidade Federal do Espírito Santo (UFES)false |
dc.title.none.fl_str_mv |
A novel approach of independent brain-computer interface based on SSVEP |
title |
A novel approach of independent brain-computer interface based on SSVEP |
spellingShingle |
A novel approach of independent brain-computer interface based on SSVEP Tello, Richard Junior Manuel Godinez Sinais cerebrais Percepção fundo-figura (FGP) Potenciais evocados visuais de regime permanente (SSVEP) Interface cérebro-computador Potencial evocado (Eletrofisiologia) Engenharia Elétrica 621.3 |
title_short |
A novel approach of independent brain-computer interface based on SSVEP |
title_full |
A novel approach of independent brain-computer interface based on SSVEP |
title_fullStr |
A novel approach of independent brain-computer interface based on SSVEP |
title_full_unstemmed |
A novel approach of independent brain-computer interface based on SSVEP |
title_sort |
A novel approach of independent brain-computer interface based on SSVEP |
author |
Tello, Richard Junior Manuel Godinez |
author_facet |
Tello, Richard Junior Manuel Godinez |
author_role |
author |
dc.contributor.advisor-co1.fl_str_mv |
Ferreira, André |
dc.contributor.advisor-co2.fl_str_mv |
Müller, Sandra Mara Torres |
dc.contributor.advisor1.fl_str_mv |
Bastos Filho, Teodiano Freire |
dc.contributor.author.fl_str_mv |
Tello, Richard Junior Manuel Godinez |
dc.contributor.referee1.fl_str_mv |
Ciarelli, Patrick Marques |
dc.contributor.referee2.fl_str_mv |
Lima, Eduardo Roncon de |
dc.contributor.referee3.fl_str_mv |
Sá, Antônio Maurício Miranda de |
contributor_str_mv |
Ferreira, André Müller, Sandra Mara Torres Bastos Filho, Teodiano Freire Ciarelli, Patrick Marques Lima, Eduardo Roncon de Sá, Antônio Maurício Miranda de |
dc.subject.por.fl_str_mv |
Sinais cerebrais Percepção fundo-figura (FGP) Potenciais evocados visuais de regime permanente (SSVEP) Interface cérebro-computador Potencial evocado (Eletrofisiologia) |
topic |
Sinais cerebrais Percepção fundo-figura (FGP) Potenciais evocados visuais de regime permanente (SSVEP) Interface cérebro-computador Potencial evocado (Eletrofisiologia) Engenharia Elétrica 621.3 |
dc.subject.cnpq.fl_str_mv |
Engenharia Elétrica |
dc.subject.udc.none.fl_str_mv |
621.3 |
description |
Over the past ten years, Brain Computer Interfaces (BCIs) based on Steady- State Visual Evoked Potentials (SSVEP) have attracted the attention of many researchers due to the promissory results and the high accuracy rates achieved. This type of BCI provides to people with severe neuromotor difficulties the possibility to communicate with the world around them using visual attention modulation to blinking lights at a given frequency. This thesis aiming at developing a new approach of Independent BCI, in which users are not required to perform neuromuscular tasks to select visual targets, a feature that distinguishes it from traditional SSVEP-BCIs. Thus, people with severe motor disabilities as Amyotrophic Lateral Sclerosis (ALS) have a new alternative channel to communicate with the world around them using brain signals. Several contributions were done in this thesis, such as: improvement of the feature extractor called Multivariate Synchronization Index (MSI) for detecting evoked potentials; development of a new method for detecting evoked potentials through correlating multidimensional models (tensors); a first study on the influence of colored stimuli in SSVEPs detection using LEDs; the development of the concept of Compressive sensing applied to SSVEPs; and, finally, the development of a novel independent BCI under an approach named Figure-Ground Perception (FGP) |
publishDate |
2016 |
dc.date.issued.fl_str_mv |
2016-09-01 |
dc.date.accessioned.fl_str_mv |
2018-08-02T00:01:45Z |
dc.date.available.fl_str_mv |
2018-08-01 2018-08-02T00:01:45Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/doctoralThesis |
format |
doctoralThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://repositorio.ufes.br/handle/10/9683 |
url |
http://repositorio.ufes.br/handle/10/9683 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
Text |
dc.publisher.none.fl_str_mv |
Universidade Federal do Espírito Santo Doutorado em Engenharia Elétrica |
dc.publisher.program.fl_str_mv |
Programa de Pós-Graduação em Engenharia Elétrica |
dc.publisher.initials.fl_str_mv |
UFES |
dc.publisher.country.fl_str_mv |
BR |
dc.publisher.department.fl_str_mv |
Centro Tecnológico |
publisher.none.fl_str_mv |
Universidade Federal do Espírito Santo Doutorado em Engenharia Elétrica |
dc.source.none.fl_str_mv |
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Repositório Institucional da Universidade Federal do Espírito Santo (riUfes) |
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