Long-term EEG-video-audio monitoring: computer detection of focal EEG seizure patterns.
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 conjunction with SS.
Department of Medicine, University of Washington, School of Medicine, Seattle.
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D000293:Adolescent; D000328:Adult; D002648:Child; D004569:Electroencephalography / Q000379:methods*; D004828:Epilepsies, Partial / Q000503:physiopathology*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008297:Male; D008875:Middle Aged; D008991:Monitoring, Physiologic / Q000379:methods; D013637:Tape Recording; D013997:Time Factors; D014743:Videotape Recording