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dc.contributor.authorMartínez-Cagigal, Víctor
dc.contributor.authorSantamaría-Vázquez, Eduardo
dc.contributor.authorGomez-Pilar, Javier
dc.contributor.authorHornero, Roberto
dc.date.accessioned2024-02-05T14:08:42Z
dc.date.available2024-02-05T14:08:42Z
dc.date.issued2019-04-15
dc.identifier.citationExpert Systems With Applications, Abril, 2019, vol. 120, 155-166es
dc.identifier.urihttps://uvadoc.uva.es/handle/10324/65729
dc.description.abstractThis study presents an asynchronous P300-based Brain–Computer Interface (BCI) system for controlling social networking features of a smartphone. There are very few BCI studies based on these mobile devices and, to the best of our knowledge, none of them supports networking applications or are focused on an assistive context, failing to test their systems with motor-disabled users. Therefore, the aim of the present study is twofold: (i) to design and develop an asynchronous P300-based BCI system that allows users to control Twitter and Telegram in an Android device; and (ii) to test the usefulness of the developed system with a motor-disabled population in order to meet their daily communication needs. Row-col paradigm (RCP) is used in order to elicitate the P300 potentials in the scalp of the user, which are immediately processed for decoding the user’s intentions. The expert system integrates a decision-making stage that analyzes the attention of the user in real-time, providing a comprehensive and asynchronous control. These intentions are then translated into application commands and sent via Bluetooth to the mobile device, which interprets them and provides visual feedback to the user. During the assessment, both qualitative and quantitative metrics were obtained, and a comparison among other state-ofthe-art studies was performed as well. The system was tested with 10 healthy control subjects and 18 motor-disabled subjects, reaching average online accuracies of 92.3% and 80.6%, respectively. Results suggest that the system allows users to successfully control two socializing features of a smartphone, bridging the accessibility gap in these trending devices. Our proposal could become a useful tool within households, rehabilitation centers or even companies, opening up new ways to support the integration of motor-disabled people, and making an impact in their quality of life by improving personal autonomy and self-dependence.es
dc.format.mimetypeapplication/pdfes
dc.language.isospaes
dc.publisherElsevieres
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subject.classificationBrain-computer interface (BCI)es
dc.subject.classificationSmartphoneses
dc.subject.classificationAsynchronous controles
dc.subject.classificationSocial networkses
dc.subject.classificationP300 Event-related potentialses
dc.subject.classificationElectroencephalography (EEG)es
dc.titleTowards an accessible use of smartphone-based social networks through brain-computer interfaceses
dc.typeinfo:eu-repo/semantics/articlees
dc.identifier.doihttps://doi.org/10.1016/j.eswa.2018.11.026es
dc.relation.publisherversionhttps://doi.org/10.1016/j.eswa.2018.11.026es
dc.identifier.publicationfirstpage155es
dc.identifier.publicationlastpage166es
dc.identifier.publicationvolume120es
dc.peerreviewedSIes
dc.description.projectTEC2014-53196-R, DPI2017-84280-R, 0378_AD_EEGWA_2_P y VA037U16es
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.type.hasVersioninfo:eu-repo/semantics/acceptedVersiones


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