title: Changes in dynamical characteristics of epileptic EEG in rats using recurrence quantification analysis.
abstract: In this paper, we used Recurrence Quantification Analysis (RQA) in order to study pre-epileptic characteristics in rat's EEG recordings. Four adult rats were used to collect epileptic EEG data in an experiment of animal model of epilepsy. Three RQA measures, recurrence rate, determinism, and entropy were calculated from EEG recordings from rats. A moving average filter was used to identify the decreasing trend in pre-epileptic dynamics which will be useful early detection of seizures.
authors.affiliation: Biomedical Signal Processing Laboratory, Department of Electrical Engineering, University of North Dakota, Grand Forks, ND 58202, USA. ahmed.rabbi@und.edu
authors.forename: Ahmed F
authors.initials: AF
authors.lastname: Rabbi
authors.forename: Manoj K
authors.initials: MK
authors.lastname: Jaiswal
authors.forename: Saobo
authors.initials: S
authors.lastname: Lei
authors.forename: Reza
authors.initials: R
authors.lastname: Fazel-Rezai
mesh_terms: D000818:Animals; D004195:Disease Models, Animal; D004569:Electroencephalography / Q000379:methods*; D004827:Epilepsy / Q000503:physiopathology*; D051381:Rats; D017207:Rats, Sprague-Dawley