title: Anticipating epileptic seizures in real time by a non-linear analysis of similarity between EEG recordings.
abstract: In a previous publication we showed that non-linear analysis can extract spatio-temporal changes of brain electrical activity prior to epileptic seizures. Here we describe a new method to analyze this long-term non-stationarity in the EEG by a measure of dynamical similarity between different parts of the time series. We apply this method to the study of a group of patients with temporal lobe epilepsy recorded intracranially during transitions to seizure. We show that the method, which can be implemented on a personal computer, can track in real time spatio-temporal changes in brain dynamics several minutes prior to seizure.
authors.affiliation: Laboratoire de Neurosciences Cognitives et Imagerie Cérébrale (CNRS UPR 640) and Unité D'epileptologie, Hôpital de la Salpêtrière, Paris, France.
authors.forename: M
authors.initials: M
authors.lastname: Le Van Quyen
authors.forename: J
authors.initials: J
authors.lastname: Martinerie
authors.forename: M
authors.initials: M
authors.lastname: Baulac
authors.forename: F
authors.initials: F
authors.lastname: Varela
mesh_terms: D000465:Algorithms; D003199:Computer Systems; D004569:Electroencephalography; D004833:Epilepsy, Temporal Lobe / Q000503:physiopathology*; D006801:Humans; D017711:Nonlinear Dynamics; D011237:Predictive Value of Tests; D014741:Video Recording