• DocumentCode
    873582
  • Title

    Single-trial processing of event-related potentials using outlier information

  • Author

    Birch, Gary E. ; Lawrence, Peter D. ; Hare, Robert D.

  • Author_Institution
    British Columbia Univ., Vancouver, BC, Canada
  • Volume
    40
  • Issue
    1
  • fYear
    1993
  • Firstpage
    59
  • Lastpage
    73
  • Abstract
    An approach to extracting single-trial event-related information is described. This approach, called the outlier processing method (OPM), is based on the concept that event-related information is contained in electroencephalogram (EEG) time-series outliers. In particular, the OPM has been effective in extracting motor-related information from single-trial EEG. An investigation into the viability of the OPM was carried out on single-trial EEG data from four subjects. The EEG was collected under two conditions: an active task in which the subject performed a skilled thumb movement and an idle task in which the subject remained alert but did not carry out any motor activity. The results of this investigation demonstrated that consistent single-trial motor related information can be successfully extracted using the OPM.
  • Keywords
    bioelectric potentials; electroencephalography; medical signal processing; event-related potentials; idle task; motor activity; outlier information; single-trial EEG data; single-trial event-related information; single-trial processing; thumb movement; Additives; Brain modeling; Councils; Data mining; Electroencephalography; Enterprise resource planning; Helium; Scalp; Signal processing; Thumb; Action Potentials; Bayes Theorem; Bias (Epidemiology); Electroencephalography; Evaluation Studies as Topic; Humans; Models, Neurological; Models, Statistical; Motor Activity; Normal Distribution; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted; Thumb; Time Factors;
  • fLanguage
    English
  • Journal_Title
    Biomedical Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9294
  • Type

    jour

  • DOI
    10.1109/10.204772
  • Filename
    204772