Automatic EEG spike detection: what should the computer imitate?

W. R.S. Webber, B. Litt, R. P. Lesser, R. S. Fisher, I. Bankman

Research output: Contribution to journalArticle

Abstract

We conducted a study to explore how electroencephalographers (EEGers) read EEGs and reach clinical impressions based upon them. Eight EEGers and a rule-based computerized "spike" detector marked epileptiform discharges ("EDs") in 12 test records. Of all marked events, 18% were marked by all readers and 38% were marked by only one reader. Readers agreed on basic clinical features of the records, such as whether a record demonstrated EDs, the rank order of ED sources by location, and the ranking of test records in order of the number of EDs detected. Readers marked records in a consistent pattern that was independent of an objective measure of expertise and experience. Our computerized ED detector had lower sensitivity and selectivity than human readers, but either parameter could be adjusted to be comparable to human EEGers at the expense of the other. We propose that EEGers employ reproducible, quantitatively different styles of reading EEG tracings to reach qualitatively similar clinical impressions. In practice, EDs are not absolutely defined, but appear to represent a continuum of activity which lends itself better to description and rank ordering than to absolute quantitation. More than just counting EDs, a successful computerized ED detector should be adaptable to the style of individual readers in order to help them efficiently formulate their clinical impressions.

Original languageEnglish (US)
Pages (from-to)364-373
Number of pages10
JournalElectroencephalography and Clinical Neurophysiology
Volume87
Issue number6
DOIs
StatePublished - Dec 1993

Keywords

  • Computer analysis
  • EEG analysis
  • EEG reader expertise
  • EEG reader variation
  • Rank scores
  • Spike detection

ASJC Scopus subject areas

  • Neuroscience(all)
  • Clinical Neurology

Fingerprint Dive into the research topics of 'Automatic EEG spike detection: what should the computer imitate?'. Together they form a unique fingerprint.

  • Cite this