Age-independent seizure detection.
This paper examines whether an appropriate algorithm, developed for use with neonatal data, could also be used, without alteration, for the detection of seizures in adults with epilepsy. The performance of a feature extraction and SVM classifier system is evaluated on databases of 17 neonatal patients and 15 adult patients. Mean ROC curve areas of 0.96 and 0.94 for neonatal and adult databases respectively show that high accuracy can be achieved independent of age. It is also shown that features contribute differently for neonatal and adult data.
Faul
Stephen
S
Department of Electrical Engineering, University College, Cork, Ireland. stephenf@rennes.ucc.ie
Temko
Andriy
A
Marnane
William
W
D000293:Adolescent; D000328:Adult; D000375:Aging / Q000473:pathology*; D000465:Algorithms; D016477:Artifacts; D004569:Electroencephalography / Q000379:methods*; D006801:Humans; D007231:Infant, Newborn; D012372:ROC Curve; D012640:Seizures / Q000175:diagnosis*; D055815:Young Adult