• DocumentCode
    1513605
  • Title

    VEP-based brain-computer interfaces: time, frequency, and code modulations [Research Frontier]

  • Author

    Bin, Guangyu ; Gao, Xiaorong ; Wang, Yijun ; Hong, Bo ; Gao, Shangkai

  • Author_Institution
    Tsinghua Univ., Beijing, China
  • Volume
    4
  • Issue
    4
  • fYear
    2009
  • fDate
    11/1/2009 12:00:00 AM
  • Firstpage
    22
  • Lastpage
    26
  • Abstract
    A brain computer interface (BCI) translates human intentions into control signals to establish a direct communication channel between the human brain and external devices. Because a BCI does not depend on the brain´s normal output pathways of peripheral nerves and muscles, it can provide a new communication channel to people with severe motor disabilities. Electroencephalograms (EEGs) recorded from the surface of the scalp are widely used in current BCIs for their non-invasive nature and easy applications. Among EEG based BCIs, systems based on visual evoked potentials (VEPs) have received widespread attention in recent decades. We described the three stimulus modulation approaches used in current VEP based BCIs: time modulation (t-VEP), frequency modulation (f-VEP), and pseudorandom code modulation (c-VEP). We then carried out a detailed comparison of system performance between an f-VEP BCI and a c-VEP BCI. The results show that an f-VEP BCI has the advantage of little or no training and simple system configuration, while the c-VEP based BCI has a higher communication speed. The stimulus modulation design is the crux of VEP based BCI systems.
  • Keywords
    brain-computer interfaces; electroencephalography; frequency modulation; medical signal processing; visual evoked potentials; EEG; brain-computer interface; communication channel; electroencephalogram; frequency modulation; human brain; pseudorandom code modulation; severe motor disability; stimulus modulation; time modulation; visual evoked potential; Brain computer interfaces; Communication channels; Communication system control; Electroencephalography; Frequency modulation; Humans; Modulation coding; Muscles; Scalp; System performance;
  • fLanguage
    English
  • Journal_Title
    Computational Intelligence Magazine, IEEE
  • Publisher
    ieee
  • ISSN
    1556-603X
  • Type

    jour

  • DOI
    10.1109/MCI.2009.934562
  • Filename
    5294934