Automatic seizure detection: improvements and evaluation.
Improvements to an existing automatic seizure detection program are described. They are aimed at taking into account a larger temporal context and thus improving the specificity of the detections. Results were evaluated on 293 recordings from 49 patients, totaling 5303 h of 16-channel recording. They showed that 24% of the 244 seizures recorded were missed by the automatic detection; in 41% of the seizures, the patient alarm was not pressed but the computer made detections. The false detection rate was of the order of 1 false detection per hour of recording. Conclusions are: (1) automatic seizure detection must be used in conjunction with a patient alarm button since some seizures, having poorly defined EEG activity, are not detected; (2) the automatic detection allowed capture of many seizures, clinical and subclinical, for which the alarm was not pressed; (3) the low false detection rate indicates that lower detection threshold could be used, yielding better seizure detection.
Department of Neurology and Neurosurgery, McGill University, Montreal, Que., Canada.
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Gotman
D000293:Adolescent; D000328:Adult; D004569:Electroencephalography; D004576:Electromyography; D004585:Electrooculography; D004827:Epilepsy / Q000175:diagnosis* / Q000503:physiopathology; D006801:Humans; D008991:Monitoring, Physiologic