title: SIGNAL REGULARITY-BASED AUTOMATED SEIZURE DETECTION SYSTEM FOR SCALP EEG MONITORING.
abstract: The purpose of the present study was to build a clinically useful automated seizure detection system for scalp EEG recordings. To achieve this, a computer algorithm was designed to translate complex multichannel scalp EEG signals into several dynamical descriptors, followed by the investigations of their spatiotemporal properties that relate to the ictal (seizure) EEG patterns as well as to normal physiologic and artifact signals. This paper describes in detail this novel seizure detection algorithm and reports its performance in a large clinical dataset.
authors.affiliation: Optima Neuroscience, Inc., Gainesville, FL, USA.
authors.forename: Deng-Shan
authors.initials: DS
authors.lastname: Shiau
authors.forename: J J
authors.initials: JJ
authors.lastname: Halford
authors.forename: K M
authors.initials: KM
authors.lastname: Kelly
authors.forename: R T
authors.initials: RT
authors.lastname: Kern
authors.forename: M
authors.initials: M
authors.lastname: Inman
authors.forename: Jui-Hong
authors.initials: JH
authors.lastname: Chien
authors.forename: P M
authors.initials: PM
authors.lastname: Pardalos
authors.forename: M C K
authors.initials: MC
authors.lastname: Yang
authors.forename: J Ch
authors.initials: JC
authors.lastname: Sackellares