癫痫特征的自动检测在临床上有很重要的意义,可以减轻医疗工作者的劳动量。本文综述和分析了癫痫特征检测的各种方法,包括非线性滤波、模板匹配、拟态法等传统的方法和小波变换、神经网络等近年发展起来的新方法。 The automatic detection of epilepsy features in clinical significance is very important, can reduce the workload of medical workers. This article reviews and analyzes various methods of epilepsy feature detection, including traditional methods such as nonlinear filtering, template matching, mimicry and other new methods developed in recent years, such as wavelet transform and neural network.