EEG Channel Selection Based User Identification via Improved Flower Pollination Algorithm

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversity of Kufa-
Autor(es): dc.contributorUniversity of Sharjah-
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorAjman University-
Autor(es): dc.contributorAl-Balqa Applied University-
Autor(es): dc.contributorAl-Muthanna University-
Autor(es): dc.contributorUniversity of Anbar-
Autor(es): dc.contributorNorrof University College-
Autor(es): dc.contributorChiang Mai University-
Autor(es): dc.creatorAlyasseri, Zaid Abdi Alkareem-
Autor(es): dc.creatorAlomari, Osama Ahmad-
Autor(es): dc.creatorPapa, João P.-
Autor(es): dc.creatorAl-Betar, Mohammed Azmi-
Autor(es): dc.creatorAbdulkareem, Karrar Hameed-
Autor(es): dc.creatorMohammed, Mazin Abed-
Autor(es): dc.creatorKadry, Seifedine-
Autor(es): dc.creatorThinnukool, Orawit-
Autor(es): dc.creatorKhuwuthyakorn, Pattaraporn-
Data de aceite: dc.date.accessioned2025-08-21T20:09:28Z-
Data de disponibilização: dc.date.available2025-08-21T20:09:28Z-
Data de envio: dc.date.issued2022-05-01-
Data de envio: dc.date.issued2022-05-01-
Data de envio: dc.date.issued2022-03-01-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.3390/s22062092-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/234242-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/234242-
Descrição: dc.descriptionThe electroencephalogram (EEG) introduced a massive potential for user identification. Several studies have shown that EEG provides unique features in addition to typical strength for spoofing attacks. EEG provides a graphic recording of the brain’s electrical activity that electrodes can capture on the scalp at different places. However, selecting which electrodes should be used is a challenging task. Such a subject is formulated as an electrode selection task that is tackled by optimization methods. In this work, a new approach to select the most representative electrodes is introduced. The proposed algorithm is a hybrid version of the Flower Pollination Algorithm and β-Hill Climbing optimizer called FPAβ-hc. The performance of the FPAβ-hc algorithm is evaluated using a standard EEG motor imagery dataset. The experimental results show that the FPAβ-hc can utilize less than half of the electrode numbers, achieving more accurate results than seven other methods.-
Descrição: dc.descriptionChiang Mai University-
Descrição: dc.descriptionECE Department Faculty of Engineering University of Kufa-
Descrição: dc.descriptionInformation Technology Research and Development Center (ITRDC) University of Kufa-
Descrição: dc.descriptionMLALP Research Group University of Sharjah-
Descrição: dc.descriptionDepartment of Computing UNESP—São Paulo State University-
Descrição: dc.descriptionArtificial Intelligence Research Center (AIRC) College of Engineering and Information Technology Ajman University-
Descrição: dc.descriptionDepartment of Information Technology Al-Huson University College Al-Balqa Applied University-
Descrição: dc.descriptionCollege of Agriculture Al-Muthanna University-
Descrição: dc.descriptionCollege of Computer Science and Information Technology University of Anbar-
Descrição: dc.descriptionDepartment of Applied Data Science Norrof University College-
Descrição: dc.descriptionCollege of Arts Media and Technology Chiang Mai University-
Descrição: dc.descriptionDepartment of Computing UNESP—São Paulo State University-
Idioma: dc.languageen-
Relação: dc.relationSensors-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectAuto-repressive-
Palavras-chave: dc.subjectBiometric-
Palavras-chave: dc.subjectEEG-
Palavras-chave: dc.subjectFeature selection-
Palavras-chave: dc.subjectFlower pollination algorithm-
Palavras-chave: dc.subjectβ-hill climbing-
Título: dc.titleEEG Channel Selection Based User Identification via Improved Flower Pollination Algorithm-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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