基于深度学习的癫痫脑电数据的处理方法

With the rapid development of machine learning, the application of deep learning in the medical field is becoming more and more important. As an important basis for diagnosis and treatment of epilepsy, EEG data is very important in deep learning. How to process the epileptic EEG data properly is the key to solve the problem of epilepsy diagnosis and epileptic seizure prediction using deep learning technology. For the existing effective EEG data processing methods, experiments and research are carried out to explore the principles and shortcomings. At the same time, according to the data characteristics, neural network model and other principle knowledge, as well as the shortcomings of the previous methods, we try to find a more feasible and effective data processing method from other angles.