• DocumentCode
    1474656
  • Title

    BCI Demographics II: How Many (and What Kinds of) People Can Use a High-Frequency SSVEP BCI?

  • Author

    Volosyak, Ivan ; Valbuena, Diana ; Lüth, Thorsten ; Malechka, Tatsiana ; Gräser, Axel

  • Author_Institution
    Inst. of Autom., Univ. of Bremen, Bremen, Germany
  • Volume
    19
  • Issue
    3
  • fYear
    2011
  • fDate
    6/1/2011 12:00:00 AM
  • Firstpage
    232
  • Lastpage
    239
  • Abstract
    Brain-computer interface (BCI) systems use brain activity as an input signal and enable communication without movement. This study is a successor of our previous study (BCI demographics I) and examines correlations among BCI performance, personal preferences, and different subject factors such as age or gender for two sets of steady-state visual evoked potential (SSVEP) stimuli: one in the medium frequency range (13, 14, 15 and 16 Hz) and another in the high-frequency range (34, 36,38, 40 Hz). High-frequency SSVEPs (above 30 Hz) diminish user fatigue and risk of photosensitive epileptic seizures. Results showed that most people, despite having no prior BCI experience, could use the SSVEP-based Bremen-BCI system in a very noisy field setting at a fair. Results showed that demographic parameters as well as handedness, tiredness, alcohol and caffeine consumption, etc., have no significant effect on the performance of SSVEP-based BCI. Most subjects did not consider the flickering stimuli annoying, only five out of total 86 participants indicated change in fatigue during the experiment. 84 subjects performed with a mean information transfer rate of 17.24 ± 6.99 bit/min and an accuracy of 92.26 ± 7.82% with the medium frequency set, whereas only 56 subjects performed with a mean information transfer rate of 12.10 ± 7.31 bit/min and accuracy of 89.16 ± 9.29% with the high-frequency set. These and other demographic analyses may help identify the best BCI for each user.
  • Keywords
    brain-computer interfaces; neurophysiology; visual evoked potentials; BCI demographics; Bremen-BCI system; brain activity; brain-computer interface; flickering stimuli; high-frequency SSVEP BCI; photosensitive epileptic seizure; steady-state visual evoked potential; user fatigue; Accuracy; Analysis of variance; Computers; Electrodes; Electroencephalography; Robot sensing systems; Brain–computer interface (BCI); demographics; electroencephalography (EEG); high-frequency visual stimulation; steady-state visual evoked potential (SSVEP); Adolescent; Adult; Age Factors; Algorithms; Brain; Computers; Demography; Electroencephalography; Evoked Potentials, Visual; Fatigue; Female; Humans; Information Theory; Male; Middle Aged; Photic Stimulation; Psychomotor Performance; Questionnaires; Robotics; Sex Factors; Signal Processing, Computer-Assisted; Software; User-Computer Interface; Video Games; Young Adult;
  • fLanguage
    English
  • Journal_Title
    Neural Systems and Rehabilitation Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1534-4320
  • Type

    jour

  • DOI
    10.1109/TNSRE.2011.2121919
  • Filename
    5733429