1043-3155 Pediatr Neurol Briefs pedneurbriefs Pediatr Neurol Briefs Pediatric Neurology Briefs Pediatr Neurol Briefs 2166-6482 1043-3155 2166-3155 Pediatric Neurology Briefs Publishers Chicago, IL, USA PNB-11-78-b 10.15844/pedneurbriefs-11-10-11 Seizure Disorders Neurology Pediatrics Nervous System Diseases Child Development Brain Diseases Neurosurgery Child Infant Automatic Neonatal Seizure Detection by EEG http://orcid.org/0000-0002-0173-7931 Millichap J. Gordon MD 1 2 * Division of Neurology, Children's Memorial Hospital, Chicago, IL Departments of Pediatrics and Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL Correspondence: Dr. J. Gordon Millichap, E-mail: jgmillichap@northwestern.edu 10 1997 01 05 2016 11 10 78 79 Copyright: © 1997 The Author(s) 1997 This work is licensed under the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Automatic seizure detection in the newborn: methods and initial evaluation

EEGs obtained from 55 newborns, recorded at the Montreal, Sydney, and Texas Children’s Hospitals, were reviewed by 3 types of automatic analysis of sequential epochs aimed at detecting rhythmic paroxysmal discharges, repetitive spike patterns, arrhythmic runs of spikes, and low frequency discharges, and the methods are reported from the Montreal Neurological Institute, and the Montreal Children’s Hospital, Canada.

 Rhythmic Paroxysmal Discharges False Detection Rate Seizure Clusters

EEGs obtained from 55 newborns, recorded at the Montreal, Sydney, and Texas Children’s Hospitals, were reviewed by 3 types of automatic analysis of sequential epochs aimed at detecting rhythmic paroxysmal discharges, repetitive spike patterns, arrhythmic runs of spikes, and low frequency discharges, and the methods are reported from the Montreal Neurological Institute, and the Montreal Children’s Hospital, Canada. Initial evaluation detected 71% of seizures and 78% of seizure clusters, and the false detection rate was 1.7/hour of recording. [1]

COMMENT. The EEG is particularly important in the recognition of seizures in the newborn, since clinical observation alone may not be diagnostic. An algorithm that extracts rhythmic features from the EEG by spectral analysis may identify paroxysmal patterns indicative of seizure activity, but false detections may be a concern.

In a second publication, the authors evaluated their automatic EEG method of neonatal seizure detection, using recordings from a new set of 54 patients. The average seizure detection rate in the 3 institutions providing recordings was 69%, and the average false detection rate was 2.3/hour. Fluctuations in the false detection rates, ranging from a low of 1 to a high of 4/h, were a reflection of the technical quality and level of supervision of recordings. An experienced electroencephalographer must review “seizure” detections in conjunction with clinical observations, so that false or artifactual patterns may be excluded. [2]

Gotman J Flanagan D Zhang J Rosenblatt B Automatic seizure detection in the newborn: methods and initial evaluation Electroencephalogr Clin Neurophysiol 1997 Sep 103 3 356 62 10.1016/S0013-4694(97)00003-9 9305282 Gotman J Flanagan D Rosenblatt B Bye A Mizrahi EM Evaluation of an automatic seizure detection method for the newborn EEG Electroencephalogr Clin Neurophysiol 1997 Sep 103 3 363 9 10.1016/S0013-4694(97)00005-2 9305283