title: An algorithm for detecting seizure termination in scalp EEG.
abstract: Little effort has been devoted to developing algorithms that can detect the cessation of seizure activity in scalp EEG. Such algorithms could facilitate clinical applications such as the estimation of seizure duration or the delivery of therapies designed to mitigate postictal period symptoms. In this paper, we present a method for detecting the termination of seizure activity. When tested on 133 seizures from a public database, our method detected the end of 132 seizures with a mean absolute error of 10.3 ± 5.5 seconds of the time marked by an electroencephalographer. Furthermore, by pairing our seizure end detector with a previously published seizure onset detector, we could automatically estimate the duration of 85% of test seizures within a 15 second error margin.
authors.affiliation: Massachusetts General Hospital, Boston, USA. ashoeb@partners.org
authors.forename: Ali
authors.initials: A
authors.lastname: Shoeb
authors.forename: Alaa
authors.initials: A
authors.lastname: Kharbouch
authors.forename: Jacqueline
authors.initials: J
authors.lastname: Soegaard
authors.forename: Steven
authors.initials: S
authors.lastname: Schachter
authors.forename: John
authors.initials: J
authors.lastname: Guttag
mesh_terms: D000465:Algorithms; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D004569:Electroencephalography / Q000379:methods*; D004827:Epilepsy / Q000175:diagnosis*; D015203:Reproducibility of Results; D012535:Scalp / Q000503:physiopathology; D012680:Sensitivity and Specificity