Prediction of Epileptic Seizure based on Approximate Entropy of EEG
Yi Zhou · Journal of Biomedical Engineering Research · 2011
In this study,we try to find out the general regularity and method to predict absences seizure by studying regularities of dynamics of spatiotemporal transitions of EEG during epileptic seizures.With nonlinear dynamical method,using Approximate Entropy(ApEn),we studied the dynamical features of EEG signal which was obtained from clinical data.The selection of critical cortical cites involved a model which could optimize the probability to be best.Before epileptic absence seizure,the T-index of those critical cites will change to some degree and will progressively converge.Then,a probably prediction can be given.The prediction scheme of optima electrode is better than using fixed electrodeduring two seizures is considerable.