title: Computerized seizure detection of complex partial seizures.
abstract: In this study, we describe a computerized method that uses 3 quantified EEG features and discriminant analysis to automatically detect seizure EEG. The quantified EEG features were relative amplitude, dominant frequency and rhythmicity. Using EEGs recorded from intracranial electrodes, the seizure detection method was applied to consecutive non-overlapping 2-channel EEG epochs. A seizure detection sensitivity, ranging from 90% to 100%, was associated with a false positive detection rate of 1.5-2.5/h. The performance of the seizure detection method remained stable for EEG recorded over variable time periods.
authors.affiliation: Department of Neurology, VA Medical Center, Augusta, GA 30912.
authors.forename: A M
authors.initials: AM
authors.lastname: Murro
authors.forename: D W
authors.initials: DW
authors.lastname: King
authors.forename: J R
authors.initials: JR
authors.lastname: Smith
authors.forename: B B
authors.initials: BB
authors.lastname: Gallagher
authors.forename: H F
authors.initials: HF
authors.lastname: Flanigin
authors.forename: K
authors.initials: K
authors.lastname: Meador
mesh_terms: D016002:Discriminant Analysis; D004569:Electroencephalography / Q000379:methods*; D017029:Epilepsy, Complex Partial / Q000503:physiopathology*; D005583:Fourier Analysis; D006801:Humans; D012640:Seizures / Q000175:diagnosis*; D012815:Signal Processing, Computer-Assisted