title: EEG seizure prediction: Measures and challenges.
abstract: Different types of analyses of scalp and intracranial electroencephalography (EEG) recordings using linear and nonlinear time series analysis method have been done. They showed strong evidence of detectable changes in the EEG dynamics from minutes up to several hours in advance of seizure onset. The predictive performance of univariate and bivariate measures, comprising both linear and non-linear approaches have been carried in different studies Direct comparison among different measures and methods in seizure prediction is not possible, unless they are applied to the same dataset. In this review paper, we describe different seizure prediction measures briefly and discuss the existing challenges.
authors: Electrical and Computer Engineering, The University of Manitoba., Winnipeg, MB, Canada. aarabi@ee.umanitoba.ca
authors: A
authors: A
authors: Aarabi
authors: R
authors: R
authors: Fazel-Rezai
authors: Y
authors: Y
authors: Aghakhani
mesh_terms: D000704:Analysis of Variance; D001921:Brain / Q000503:physiopathology*; D004569:Electroencephalography / Q000379:methods*; D006801:Humans; D008959:Models, Neurological; D017711:Nonlinear Dynamics; D011237:Predictive Value of Tests; D012640:Seizures / Q000175:diagnosis / Q000453:epidemiology / Q000503:physiopathology*; D015398:Signal Transduction; D013223:Statistics as Topic