Statistical and physiologically analysis of using a Duffing-van der Pol oscillator to modeled ictal signals

Electroencephalography reflects the averaged electrical activity of neurons associated with physiological and neural disease processes, i.e., epilepsy. In this study, EEG signals recorded during a complex partial seizure are modeled using a coupled Duffing-van der Pol oscillator. The purpose of the paper is the statistical analysis of parameter variability during three phases of seizure: pre-, ictal, and post-ictal. In order to determine the impact of intra -variability on parameter values during seizure spread, in the study, signals from 10 patients are analyzed. Our data are reliable in terms of each patient's sex, age, and medical history. For the first time, the results of the optimal values model parameter are explained based on physiological phenomena. Non-linear models' parameters may be useful for pre-and post-ictal sequences differentiation.