Model Research for Epileptic Prediction Based on Improved Chaos Operator of Lyapunov

Epilepsy is a brain dysfunction disease, which is caused by brain neuron excessive discharge. The damage induced by seizure is irreversible, so it is necessary to propose a new method to prevent epileptic seizure and protect the brain. Therefore, the best way is to predict preictal state accurately and to give preventive treatment. In this paper, the calculation of the largest Lyapunov exponent based on improved Wolf algorithm was used to analyze characteristics of the nonlinear dynamics and extract feature model among rats´ preictal, ictal and normal state, which was applied to forecast the epilepsy. The results showed that the method can be used to predict the preictal state effectively, and it is important for preventive treatment of seizure.