• DocumentCode
    2377867
  • Title

    An online coherence-based BCI for driving a mechanical arm

  • Author

    Abdalla, Marcos Antônio, Jr. ; Barroso, Marcio Falcão Santos ; Felix, Leonardo Bonato

  • Author_Institution
    Post-Graduation Eng. Program, Fed. Univ. of Sao Joao del-Rei, São João del-Rei, Brazil
  • fYear
    2012
  • fDate
    9-11 Jan. 2012
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    The present work describes the simulation to be used in the control of a mechanical arm using a Visual Evoked Potential to drive a Brain Computer Interface system. The signal processing and classifying was done using the Multiple Coherence K2N. The proposed classifier was able to detect the difference between four different frequencies presented at the same time. The Multiple Coherence classifier had a hit rate of 95%.
  • Keywords
    brain-computer interfaces; medical robotics; medical signal processing; signal classification; visual evoked potentials; brain computer interface; mechanical arm; multiple coherence classifier; on-line control; online coherence-based BCI; robotic arm; signal classification; signal processing; visual evoked potential; Brain modeling; Coherence; Electroencephalography; Equations; Mathematical model; Signal to noise ratio; Brain Computer Interface; Multiple Coherence; Visual Evoked Potential;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biosignals and Biorobotics Conference (BRC), 2012 ISSNIP
  • Conference_Location
    Manaus
  • Print_ISBN
    978-1-4673-2476-2
  • Type

    conf

  • DOI
    10.1109/BRC.2012.6222175
  • Filename
    6222175
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2377867