• DocumentCode
    968273
  • Title

    Context-based automated detection of epileptogenic sharp transients in the EEG: elimination of false positives

  • Author

    Glover, John R., Jr. ; Raghaven, N. ; Ktonas, Periklis Y. ; Frost, James D., Jr.

  • Author_Institution
    Dept. of Electr. Eng., Houston Univ., TX, USA
  • Volume
    36
  • Issue
    5
  • fYear
    1989
  • fDate
    5/1/1989 12:00:00 AM
  • Firstpage
    519
  • Lastpage
    527
  • Abstract
    A description is given of a knowledge-based system for the elimination of false positives in the automated detection of epileptogenic sharp transients in the EEG (electroencephalogram). The system makes comprehensive use of spatial and temporal context information available on 16 channels of EEG. EKG, (electrocardiogram) EMG (electromyogram), and EOG (electrooculogram). A knowledge-based implementation is used because of the ease with which it allows the contextual rules to be expressed and refined. The resulting system is shown to be capable of rejecting a wide variety of artifacts commonly found in EEG recordings that cause numerous false positive detections in systems making less comprehensive use of context.
  • Keywords
    electroencephalography; expert systems; medical diagnostic computing; EEG; artifacts rejection; contextual rules; epileptogenic sharp transients; false positives elimination; knowledge-based system; Blood; Electroencephalography; Electromyography; Electrooculography; Epilepsy; Heart; Helium; Knowledge based systems; Lungs; Nervous system; Artificial Intelligence; Electrocardiography; Electroencephalography; Electromyography; Electrooculography; Epilepsies, Partial; False Positive Reactions; Humans;
  • fLanguage
    English
  • Journal_Title
    Biomedical Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9294
  • Type

    jour

  • DOI
    10.1109/10.24253
  • Filename
    24253