• Login
    View Item 
    •   SMARTech Home
    • Georgia Tech Theses and Dissertations
    • Georgia Tech Theses and Dissertations
    • View Item
    •   SMARTech Home
    • Georgia Tech Theses and Dissertations
    • Georgia Tech Theses and Dissertations
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    THINK: Toward practical general-purpose brain-computer communication

    Thumbnail
    View/Open
    AGARWAL-THESIS-2017.pdf (1.435Mb)
    Date
    2017-04-28
    Author
    Agarwal, Mohit
    Metadata
    Show full item record
    Abstract
    In this work, we present THINK, a practical general-purpose brain-computer communication platform that relies on the OpenBCI and OpenViBE hardware and software platforms, and allows for a simple three-alphabet vocabulary. Specifically, we consider the scenario where a subject is wearing a sensor array (an electrode cap), and consciously manipulating her thoughts to communicate wirelessly with an external computing entity (a smartphone) without the aid of any external stimuli. Using THINK, we explore general aspects of brain computer communication that are application agnostic. In particular, we study the system accuracy and usability with real user experiments. The system accuracy was found to be highly variable across subjects and trials. We achieved a maximum accuracy of 83.4% and average accuracy of 53.4%. Even with low accuracy, we demonstrate that how is it possible to construct a successful BCC system. Further, in usability, we explore (i) how fast can the subject switch thoughts corresponding to symbols; (ii) is there an impact on accuracy with learning time; and (iv) how does accuracy drop with decreasing number of sensors (electrodes)? Using purely experimental analysis, we present some results that provide preliminary answers for these questions. We also provide motivation results for the future work in the context of (i) alphabet design as per user preference, and (ii) importance of pre-processing and requirement of better algorithms.
    URI
    http://hdl.handle.net/1853/58345
    Collections
    • Georgia Tech Theses and Dissertations [23877]
    • School of Electrical and Computer Engineering Theses and Dissertations [3381]

    Browse

    All of SMARTechCommunities & CollectionsDatesAuthorsTitlesSubjectsTypesThis CollectionDatesAuthorsTitlesSubjectsTypes

    My SMARTech

    Login

    Statistics

    View Usage StatisticsView Google Analytics Statistics
    facebook instagram twitter youtube
    • My Account
    • Contact us
    • Directory
    • Campus Map
    • Support/Give
    • Library Accessibility
      • About SMARTech
      • SMARTech Terms of Use
    Georgia Tech Library266 4th Street NW, Atlanta, GA 30332
    404.894.4500
    • Emergency Information
    • Legal and Privacy Information
    • Human Trafficking Notice
    • Accessibility
    • Accountability
    • Accreditation
    • Employment
    © 2020 Georgia Institute of Technology