title: Seizure detection in EEG signals: a comparison of different approaches.
abstract: In this paper, the performance of traditional variance-based method for detection of epileptic seizures in EEG signals are compared with various methods based on nonlinear time series analysis, entropies, logistic regression,discrete wavelet transform and time frequency distributions.We noted that variance-based method in compare to the mentioned methods had the best result (100%) applied on the same database.
authors.affiliation: Biomedical Signal and Image Processing Laboratory (BiSIPL), Sharif University of Technology, Tehran. Iran.
authors.forename: Hamid R
authors.initials: HR
authors.lastname: Mohseni
authors.forename: A
authors.initials: A
authors.lastname: Maghsoudi
authors.forename: Mohammad B
authors.initials: MB
authors.lastname: Shamsollahi
mesh_terms: D004569:Electroencephalography / Q000379:methods*; D019277:Entropy; D004827:Epilepsy / Q000503:physiopathology*; D006801:Humans; D017711:Nonlinear Dynamics; D013269:Stochastic Processes