• DocumentCode
    933586
  • Title

    Improving Auditory Steady-State Response Detection Using Independent Component Analysis on Multichannel EEG Data

  • Author

    Van Dun, Bram ; Wouters, Jan ; Moonen, Marc

  • Author_Institution
    Katholieke Univ., Leuven
  • Volume
    54
  • Issue
    7
  • fYear
    2007
  • fDate
    7/1/2007 12:00:00 AM
  • Firstpage
    1220
  • Lastpage
    1230
  • Abstract
    Over the last decade, the detection of auditory steady-state responses (ASSR) has been developed for reliable hearing threshold estimation at audiometric frequencies. Unfortunately, the duration of ASSR measurement can be long, which is unpractical for wide scale clinical application. In this paper, we propose independent component analysis (ICA) as a tool to improve the ASSR detection in recorded single-channel as well as multichannel electroencephalogram (EEG) data. We conclude that ICA is able to reduce measurement duration significantly. For a multichannel implementation, near-optimal performance is obtained with five-channel recordings.
  • Keywords
    biological techniques; hearing; independent component analysis; neurophysiology; audiometric frequency; auditory steady state response detection; hearing threshold estimation; independent component analysis; multichannel EEG data; multichannel electroencephalogram; Auditory system; Deafness; Ear; Electroencephalography; Frequency estimation; Frequency modulation; Independent component analysis; Pediatrics; Steady-state; Testing; Auditory steady-state response; electroencephalogram; independent component analysis; multichannel; Algorithms; Audiometry, Evoked Response; Diagnosis, Computer-Assisted; Electroencephalography; Evoked Potentials, Auditory; Humans; Principal Component Analysis; Reproducibility of Results; Sensitivity and Specificity;
  • fLanguage
    English
  • Journal_Title
    Biomedical Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9294
  • Type

    jour

  • DOI
    10.1109/TBME.2007.897327
  • Filename
    4237337