A review of automatic detection of epilepsy based on EEG signals  

作　　者：Qirui Ren Xiaofan Sun Xiangqu Fu Shuaidi Zhang Yiyang Yuan Hao Wu Xiaoran Li Xinghua Wang Feng Zhang 

机构地区：[1]Laboratory of Microelectronic Devices&Integrated Technology,Institute of Microelectronics of the Chinese Academy of Sciences,Beijing 100029,China [2]School of Integrated Circuits,University of Chinese Academy of Sciences,Beijing 101408,China [3]School of Information and Electronics,Beijing Institute of Technology,Beijing 100081,China

出　　处：《Journal of Semiconductors》2023年第12期8-30,共23页半导体学报（英文版）

基　　金：supported by the Strategic Priority Research Program of Chinese Academy of Sciences,Grant No.XDA0330000 and Grant No.XDB44000000。

摘　　要：Epilepsy is a common neurological disorder that occurs at all ages.Epilepsy not only brings physical pain to patients,but also brings a huge burden to the lives of patients and their families.At present,epilepsy detection is still achieved through the observation of electroencephalography(EEG)by medical staff.However,this process takes a long time and consumes energy,which will create a huge workload to medical staff.Therefore,it is particularly important to realize the automatic detection of epilepsy.This paper introduces,in detail,the overall framework of EEG-based automatic epilepsy identification and the typical methods involved in each step.Aiming at the core modules,that is,signal acquisition analog front end(AFE),feature extraction and classifier selection,method summary and theoretical explanation are carried out.Finally,the future research directions in the field of automatic detection of epilepsy are prospected.

关 键 词：EPILEPSY ELECTROENCEPHALOGRAPHY automatic detection analog front end feature extraction CLASSIFIER 

分 类 号：R742.1[医药卫生—神经病学与精神病学] TN911.7[医药卫生—临床医学]