Analysis of alpha wave epileptic EEG signals based on symbolic transfer entropy

Epilepsy is a common neurological diseases caused by abnormal discharge of neurons in the brain. The attack is sudden and repeated. Therefore, advancing seizure prediction has important meaning for patients to take timely measures. In this paper, we can use the way of symbolic transfer entropy to study and analyze when epilepsy seizures. Through the EEG signal of epilepsy patients during attacked and normal human alpha wave is extracted, by using the method of symbolic transfer entropy for analysis and research. The study found that using this method can distinguish the normal EEG and EEG in patients with epilepsy. It was also found that the existence of nonlinear large amount of time series of EEG. This method also proved symbolic transfer entropy based on algorithm can be used to analyze the EEG signals fully and revealed the difference between epileptic EEG and normal EEG, which has clinical contribution to make certain detection and prediction of epilepsy.