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    Por favor, use este identificador para citar o enlazar este ítem:https://uvadoc.uva.es/handle/10324/65729

    Título
    Towards an accessible use of smartphone-based social networks through brain-computer interfaces
    Autor
    Martínez Cagigal, VíctorAutoridad UVA Orcid
    SantaMaría Vazquez, EduardoAutoridad UVA
    Gómez Pilar, JavierAutoridad UVA Orcid
    Hornero Sánchez, RobertoAutoridad UVA Orcid
    Año del Documento
    2019
    Editorial
    Elsevier
    Descripción
    Producción Científica
    Documento Fuente
    Expert Systems With Applications, Abril, 2019, vol. 120, 155-166
    Resumo
    This 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.
    Palabras Clave
    Brain-computer interface (BCI)
    Smartphones
    Asynchronous control
    Social networks
    P300 Event-related potentials
    Electroencephalography (EEG)
    Revisión por pares
    SI
    DOI
    10.1016/j.eswa.2018.11.026
    Patrocinador
    TEC2014-53196-R, DPI2017-84280-R, 0378_AD_EEGWA_2_P y VA037U16
    Version del Editor
    https://www.sciencedirect.com/science/article/pii/S0957417418307462
    Idioma
    eng
    URI
    https://uvadoc.uva.es/handle/10324/65729
    Tipo de versión
    info:eu-repo/semantics/acceptedVersion
    Derechos
    openAccess
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    • DEP71 - Artículos de revista [358]
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    Universidad de Valladolid

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