Long-term EEG-video-audio monitoring: computer detection of focal EEG seizure patterns

Flavia Pauri, Francesco Pierelli, Gian Emilio Chatrian, William W. Erdly

Research output: Contribution to journalArticle

Abstract

Twelve individuals with medically refractory partial seizures had undergone EEG-video-audio (EVA) monitoring over 1-15 (mean 10.5) days. We selectively reexamined available 15-channel EEGs (video-cassettes) totaling 461 h and containing 253 EEG focal seizures. Computer analysis (CA) of these bipolar records was performed using a mimetic method of seizure detection at 6 successive computer settings. We determined the computer parameters at which this method correctly detected a reasonably large percentage of seizures (81.42%) while generating an acceptable rate of false positive results (5.38/h). These parameters were adopted as the default setting for identifying focal EEG seizure patterns in all subsequent long-term bipolar scalp and sphenoidal recordings. Factors hindering or facilitating automatic seizure identification are discussed. It is concluded that on-line computer detection of focal EEG seizure patterns by this method offers a satisfactory alternative to and represents a distinct improvement over the extremely time consuming and fatiguing off-line fast visual review (FVR). Combining CA with seizure signaling (SS) by the patients and other observers increased the correct detections to 85.38%. CA is best used in conjuncton with SS.

Original languageEnglish
Pages (from-to)1-9
Number of pages9
JournalElectroencephalography and Clinical Neurophysiology
Volume82
Issue number1
DOIs
Publication statusPublished - 1992

Keywords

  • Computer seizure detection
  • EEG-video-audio monitoring
  • Focal EEG
  • Partial seizures
  • Seizure signaling
  • seizures
  • Visual seizure detection

ASJC Scopus subject areas

  • Clinical Neurology
  • Neuroscience(all)

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