• myGriffith
    • Staff portal
    • Contact Us⌄
      • Future student enquiries 1800 677 728
      • Current student enquiries 1800 154 055
      • International enquiries +61 7 3735 6425
      • General enquiries 07 3735 7111
      • Online enquiries
      • Staff phonebook
    View Item 
    •   Home
    • Griffith Research Online
    • Journal articles
    • View Item
    • Home
    • Griffith Research Online
    • Journal articles
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

  • All of Griffith Research Online
    • Communities & Collections
    • Authors
    • By Issue Date
    • Titles
  • This Collection
    • Authors
    • By Issue Date
    • Titles
  • Statistics

  • Most Popular Items
  • Statistics by Country
  • Most Popular Authors
  • Support

  • Contact us
  • FAQs
  • Admin login

  • Login
  • A Hybrid Speller Design Using Eye Tracking and SSVEP Brain-Computer Interface

    View/Open
    Mannan502034_Published.pdf (4.099Mb)
    File version
    Version of Record (VoR)
    Author(s)
    Mannan, Malik M Naeem
    Kamran, M Ahmad
    Kang, Shinil
    Choi, Hak Soo
    Jeong, Myung Yung
    Griffith University Author(s)
    Mannan, Malik Muhammad Naeem
    Year published
    2020
    Metadata
    Show full item record
    Abstract
    Steady‐state visual evoked potentials (SSVEPs) have been extensively utilized to develop brain–computer interfaces (BCIs) due to the advantages of robustness, large number of commands, high classification accuracies, and information transfer rates (ITRs). However, the use of several simultaneous flickering stimuli often causes high levels of user discomfort, tiredness, annoyingness, and fatigue. Here we propose to design a stimuli‐responsive hybrid speller by using electroencephalography (EEG) and video‐based eye‐tracking to increase user comfortability levels when presented with large numbers of simultaneously flickering ...
    View more >
    Steady‐state visual evoked potentials (SSVEPs) have been extensively utilized to develop brain–computer interfaces (BCIs) due to the advantages of robustness, large number of commands, high classification accuracies, and information transfer rates (ITRs). However, the use of several simultaneous flickering stimuli often causes high levels of user discomfort, tiredness, annoyingness, and fatigue. Here we propose to design a stimuli‐responsive hybrid speller by using electroencephalography (EEG) and video‐based eye‐tracking to increase user comfortability levels when presented with large numbers of simultaneously flickering stimuli. Interestingly, a canonical correlation analysis (CCA)‐based framework was useful to identify target frequency with a 1 s duration of flickering signal. Our proposed BCI‐speller uses only six frequencies to classify forty-eight targets, thus achieve greatly increased ITR, whereas basic SSVEP BCI‐spellers use an equal number of frequencies to the number of targets. Using this speller, we obtained an average classification accuracy of 90.35 ± 3.597% with an average ITR of 184.06 ± 12.761 bits per minute in a cued‐spelling task and an ITR of 190.73 ± 17.849 bits per minute in a free‐spelling task. Consequently, our proposed speller is superior to the other spellers in terms of targets classified, classification accuracy, and ITR, while producing less fatigue, annoyingness, tiredness and discomfort. Together, our proposed hybrid eye tracking and SSVEP BCI‐based system will ultimately enable a truly high-speed communication channel.
    View less >
    Journal Title
    Sensors
    Volume
    20
    Issue
    3
    Publisher URI
    https://www.mdpi.com/
    DOI
    https://doi.org/10.3390/s20030891
    Copyright Statement
    © 2020 by the authors. Licensee MDPI, Basel, Switzerland. article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
    Subject
    Human-computer interaction
    Software engineering
    Analytical chemistry
    Ecology
    Distributed computing and systems software
    Science & Technology
    Physical Sciences
    Technology
    Chemistry, Analytical
    Engineering, Electrical & Electronic
    Publication URI
    http://hdl.handle.net/10072/407856
    Collection
    • Journal articles

    Footer

    Disclaimer

    • Privacy policy
    • Copyright matters
    • CRICOS Provider - 00233E

    Tagline

    • Gold Coast
    • Logan
    • Brisbane - Queensland, Australia
    First Peoples of Australia
    • Aboriginal
    • Torres Strait Islander