Biometric authentication using electroencephalograms: a practical study using visual evoked potentials
Autor(a) principal: | |
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Data de Publicação: | 2010 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | https://proa.ua.pt/index.php/revdeti/article/view/16818 |
Resumo: | This paper studies the suitability of brain activity, namely electroencephalogram signals, as raw material for conducting biometric authentication of individuals. Brain responses were extracted in particular scenarios, namely with visual stimulation leading to biological brain responses known as visual evoked potentials. In our study, we evaluated a novel method, using only 8 occipital electrodes and the energy of differential EEG signals, to extract information about the subjects for further use as their biometric features.To classify the features obtained from each individual we used a one-class classifier per subject. These classifiers are trained only with target class features, which is the correct procedure to apply in biometric authentication scenarios. Two types of one-class classifiers were tested, K-Nearest Neighbor and Support Vector Data Description. Two other classifier architectures were also studied, both resulting from the combination of the two previously mentioned classifiers. After testing these classifiers with the features extracted from 70 subjects, the results showed that brain responses to visual stimuli are suitable for an accurate biometric authentication. |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Biometric authentication using electroencephalograms: a practical study using visual evoked potentialsThis paper studies the suitability of brain activity, namely electroencephalogram signals, as raw material for conducting biometric authentication of individuals. Brain responses were extracted in particular scenarios, namely with visual stimulation leading to biological brain responses known as visual evoked potentials. In our study, we evaluated a novel method, using only 8 occipital electrodes and the energy of differential EEG signals, to extract information about the subjects for further use as their biometric features.To classify the features obtained from each individual we used a one-class classifier per subject. These classifiers are trained only with target class features, which is the correct procedure to apply in biometric authentication scenarios. Two types of one-class classifiers were tested, K-Nearest Neighbor and Support Vector Data Description. Two other classifier architectures were also studied, both resulting from the combination of the two previously mentioned classifiers. After testing these classifiers with the features extracted from 70 subjects, the results showed that brain responses to visual stimuli are suitable for an accurate biometric authentication.Este artigo estuda a possibilidade de usar a actividade cerebral, nomeadamente encefalogramas, como material base para realizar autenticação biométrica de indivíduos. As respostas cerebrais foram obtidas num cenário específico, nomeadamente mediante estimulação visual conducente a respostas biológicas do cérebro conhecidas como potenciais evocados visuais. No estudo realizado, avaliou-se um novo método, recorrendo apenas a 8 eléctrodos na zona occipital e a energia de sinais EEG diferenciais, para extrair informação individual para usar como característica biométrica. Para classificar as características obtidas com cada indivíduo usou-se um classificador de classe unitária pessoal. Estes classificadores são treinados apenas com características do seu alvo, o que constitui a aproximação correcta para a autenticação biométrica. Foram testados dois tipos de classificadores de classe unitária, K Vizinhos Mais Próximos e Descrição com Vectores de Dados de Suporte, e duas arquitecturas de classificação, ambas resultantes da combinação dos dois classificadores antes mencionados. Após testar estes classificadores com características extraídas de 70 indivíduos, os resultados obtidos mostram que as respostas cerebrais a estímulos visuais são viáveis para efectuar uma autenticação biométrica eficaz.UA Editora2010-01-01T00:00:00Zjournal articleinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://proa.ua.pt/index.php/revdeti/article/view/16818oai:proa.ua.pt:article/16818Eletrónica e Telecomunicações; Vol 5 No 2 (2010); 185-194Eletrónica e Telecomunicações; vol. 5 n.º 2 (2010); 185-1942182-97721645-0493reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAPenghttps://proa.ua.pt/index.php/revdeti/article/view/16818https://proa.ua.pt/index.php/revdeti/article/view/16818/11916https://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessZúquete, AndréQuintela, BrunoCunha, João Paulo Silva2022-09-26T11:00:06Zoai:proa.ua.pt:article/16818Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T16:07:58.780921Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Biometric authentication using electroencephalograms: a practical study using visual evoked potentials |
title |
Biometric authentication using electroencephalograms: a practical study using visual evoked potentials |
spellingShingle |
Biometric authentication using electroencephalograms: a practical study using visual evoked potentials Zúquete, André |
title_short |
Biometric authentication using electroencephalograms: a practical study using visual evoked potentials |
title_full |
Biometric authentication using electroencephalograms: a practical study using visual evoked potentials |
title_fullStr |
Biometric authentication using electroencephalograms: a practical study using visual evoked potentials |
title_full_unstemmed |
Biometric authentication using electroencephalograms: a practical study using visual evoked potentials |
title_sort |
Biometric authentication using electroencephalograms: a practical study using visual evoked potentials |
author |
Zúquete, André |
author_facet |
Zúquete, André Quintela, Bruno Cunha, João Paulo Silva |
author_role |
author |
author2 |
Quintela, Bruno Cunha, João Paulo Silva |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Zúquete, André Quintela, Bruno Cunha, João Paulo Silva |
description |
This paper studies the suitability of brain activity, namely electroencephalogram signals, as raw material for conducting biometric authentication of individuals. Brain responses were extracted in particular scenarios, namely with visual stimulation leading to biological brain responses known as visual evoked potentials. In our study, we evaluated a novel method, using only 8 occipital electrodes and the energy of differential EEG signals, to extract information about the subjects for further use as their biometric features.To classify the features obtained from each individual we used a one-class classifier per subject. These classifiers are trained only with target class features, which is the correct procedure to apply in biometric authentication scenarios. Two types of one-class classifiers were tested, K-Nearest Neighbor and Support Vector Data Description. Two other classifier architectures were also studied, both resulting from the combination of the two previously mentioned classifiers. After testing these classifiers with the features extracted from 70 subjects, the results showed that brain responses to visual stimuli are suitable for an accurate biometric authentication. |
publishDate |
2010 |
dc.date.none.fl_str_mv |
2010-01-01T00:00:00Z |
dc.type.driver.fl_str_mv |
journal article info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://proa.ua.pt/index.php/revdeti/article/view/16818 oai:proa.ua.pt:article/16818 |
url |
https://proa.ua.pt/index.php/revdeti/article/view/16818 |
identifier_str_mv |
oai:proa.ua.pt:article/16818 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://proa.ua.pt/index.php/revdeti/article/view/16818 https://proa.ua.pt/index.php/revdeti/article/view/16818/11916 |
dc.rights.driver.fl_str_mv |
https://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by/4.0/ |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
UA Editora |
publisher.none.fl_str_mv |
UA Editora |
dc.source.none.fl_str_mv |
Eletrónica e Telecomunicações; Vol 5 No 2 (2010); 185-194 Eletrónica e Telecomunicações; vol. 5 n.º 2 (2010); 185-194 2182-9772 1645-0493 reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799130537705603072 |