title: A novel wavelet-based index to detect epileptic seizures using scalp EEG signals.
abstract: In this paper, we propose a novel wavelet-based algorithm for the detection of epileptic seizures. The algorithm is based on the recognition of rhythmic activities associated with ictal states in surface EEG recordings. Using a moving-window analysis, we first decomposed each EEG segment into a wavelet packet tree. Then, we extracted the coefficients corresponding to the frequency band of interest defined for rhythmic activities. Finally, a normalized index sensitive to both the rhythmicity and energy of the EEG signal was derived, based on the resulting coefficients. In our study, we evaluated this combined index for real-time detection of epileptic seizures using a dataset of approximately 11.5 hours of multichannel scalp EEG recordings from three patients and compared it to our previously proposed wavelet-based index. In this dataset, the novel combined index detected all epileptic seizures with a false detection rate of 0.52/hr.
authors.affiliation: Department of Electrical & Computer Engineering at The University of British Columbia, Vancouver, BC V6T 1Z4, Canada.
authors.forename: Ali Shahidi
authors.initials: AS
authors.lastname: Zandi
authors.forename: Guy A
authors.initials: GA
authors.lastname: Dumont
authors.forename: Manouchehr
authors.initials: M
authors.lastname: Javidan
authors.forename: Reza
authors.initials: R
authors.lastname: Tafreshi
authors.forename: Bernard A
authors.initials: BA
authors.lastname: MacLeod
authors.forename: Craig R
authors.initials: CR
authors.lastname: Ries
authors.forename: Ernie
authors.initials: E
authors.lastname: Puil
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D004569:Electroencephalography / Q000379:methods*; D006801:Humans; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012535:Scalp; D012640:Seizures / Q000175:diagnosis*; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted