Epilepsy Prediction And Model Research For Pre-treatment Automatically

Epilepsy is a chronic neurological disease of brain dysfunction, which is mainly due to the excessive synchronous discharge from brain neurons. The epileptic patients account for 0.5%-1%, and its recurrent attacks seriously hurt patients'physical and mental health. The mechanism of epilepsy is complex, and the statement is not clear at present. The brain damage caused by epileptic seizures is severe, and it brings great harm even the death to patients. Therefore the best way is to predict epileptic seizures accurately and give the patients preventive treatment.In this paper, an improved non-linear chaotic operator is used to analyze the nonlinear dynamics characteristics in different state of normal, pre-ictal and ictal state of rat EEG. Then the epilepsy prediction model is established. Based on the automatic identification, the drug auto-release system simulation model which is controlled by EEG features can be designed. When the alarm signal is given by the forecast system, a certain dose of anti-epileptic drugs can be automatically released by the drug pump, which can achieve the purpose for prevention of epileptic seizures. The patients can receive preventive treatment to avoid brain damage.In this paper, the rats EEG induced by Pilocarpine is as the sample for forecasting epileptic seizures. The simulation model of drug auto-release micro-pump which is controlled by epilepsy prediction signal can be designed. The study has important practical value and scientific importance for the expansion of brain research.