• DocumentCode
    739150
  • Title

    FORCe: Fully Online and Automated Artifact Removal for Brain-Computer Interfacing

  • Author

    Daly, Ian ; Scherer, Reinhold ; Billinger, Martin ; Muller-Putz, Gernot

  • Author_Institution
    Institute for Knowledge Discovery, Laboratory of Brain-Computer Interfaces, Graz University of Technology, Graz, Austria
  • Volume
    23
  • Issue
    5
  • fYear
    2015
  • Firstpage
    725
  • Lastpage
    736
  • Abstract
    A fully automated and online artifact removal method for the electroencephalogram (EEG) is developed for use in brain-computer interfacing (BCI). The method (FORCe) is based upon a novel combination of wavelet decomposition, independent component analysis, and thresholding. FORCe is able to operate on a small channel set during online EEG acquisition and does not require additional signals (e.g., electrooculogram signals). Evaluation of FORCe is performed offline on EEG recorded from 13 BCI particpants with cerebral palsy (CP) and online with three healthy participants. The method outperforms the state-of the-art automated artifact removal methods Lagged Auto-Mutual Information Clustering (LAMIC) and Fully Automated Statistical Thresholding for EEG artifact Rejection (FASTER), and is able to remove a wide range of artifact types including blink, electromyogram (EMG), and electrooculogram (EOG) artifacts.
  • Keywords
    Approximation methods; Electroencephalography; Electromyography; Force; Integrated circuits; Scalp; Standards; Automated online artifact removal; brain-computer interface (BCI); electroencephalogram (EEG); independent component analysis; wavelets;
  • fLanguage
    English
  • Journal_Title
    Neural Systems and Rehabilitation Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1534-4320
  • Type

    jour

  • DOI
    10.1109/TNSRE.2014.2346621
  • Filename
    6877740