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dc.contributor.authorMartínez Cagigal, Víctor 
dc.contributor.authorSantamaría Vázquez, Eduardo
dc.contributor.authorPérez Velasco, Sergio
dc.contributor.authorMarcos Martínez, Diego
dc.contributor.authorMoreno Calderón, Selene
dc.contributor.authorHornero Sánchez, Roberto 
dc.date.accessioned2023-06-26T10:58:46Z
dc.date.available2023-06-26T10:58:46Z
dc.date.issued2023
dc.identifier.citationExpert Systems with Applications, 2023, vol. 232, 120815es
dc.identifier.issn0957-4174es
dc.identifier.urihttps://uvadoc.uva.es/handle/10324/59955
dc.descriptionProducción Científicaes
dc.description.abstractCode-modulated visual evoked potentials (c-VEPs) have marked a milestone in the scientific literature due to their ability to achieve reliable, high-speed brain–computer interfaces (BCIs) for communication and control. Generally, these expert systems rely on encoding each command with shifted versions of binary pseudorandom sequences, i.e., flashing black and white targets according to the shifted code. Despite the excellent results in terms of accuracy and selection time, these high-contrast stimuli cause eyestrain for some users. In this work, we propose the use of non-binary p-ary m-sequences, whose levels are encoded with different shades of gray, as a more pleasant alternative than traditional binary codes. The performance and visual fatigue of these p-ary m-sequences, as well as their ability to provide reliable c-VEP-based BCIs, are analyzed for the first time.es
dc.format.mimetypeapplication/pdfes
dc.language.isoenges
dc.publisherElsevieres
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectBiomedical engineeringes
dc.subjectNeuroscienceses
dc.subject.classificationNon-binary codeses
dc.subject.classificationBrain–computer interface (BCI)es
dc.subject.classificationElectroencephalography (EEG)es
dc.subject.classificationCódigos no binarioses
dc.subject.classificationInterfaz cerebro-computadora (BCI)es
dc.subject.classificationElectroencefalografía (EEG)es
dc.titleNon-binary m-sequences for more comfortable brain–computer interfaces based on c-VEPses
dc.typeinfo:eu-repo/semantics/articlees
dc.rights.holder© 2023 The Authorses
dc.identifier.doi10.1016/j.eswa.2023.120815es
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S0957417423013179?via%3Dihubes
dc.identifier.publicationfirstpage120815es
dc.identifier.publicationtitleExpert Systems with Applicationses
dc.identifier.publicationvolume232es
dc.peerreviewedSIes
dc.description.projectMinisterio de Ciencia e Innovación/AEI- FEDER [TED2021-129915B-I00, RTC2019-007350-1 y PID2020-115468RB-I00]es
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones
dc.subject.unesco32 Ciencias Médicases
dc.subject.unesco2490 Neurocienciases


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