ABSTRACT Epilepsy is considered as fourth most prominent neurological disorder in the world that can affect people of all age groups. Currently, around 65 million people throughout the world are suffering from epilepsy. It is evident that electroencephalograph (EEG) signals are most commonly used for detection of epileptic seizures but today many modern techniques have been developed to analyze underlying features of these EEG signals. As EEG contains a large amount of complicated information, so many researchers are trying to develop automatic systems for complete feature extraction. This paper provides a generalized review and performance comparison of popular seizure detection algorithms that are developed in the last decade. The main objective of this paper is to briefly discuss all existing developments in the field of computer-aided diagnosis system for epilepsy detection so that future researchers can find a better track for the new invention.

中文翻译：

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基于脑电图的癫痫检测计算机辅助诊断系统开发的广泛回顾

摘要 癫痫被认为是世界上第四大最突出的神经系统疾病，可影响所有年龄段的人。目前，全世界约有 6500 万人患有癫痫症。很明显，脑电图 (EEG) 信号最常用于检测癫痫发作，但今天已经开发了许多现代技术来分析这些 EEG 信号的潜在特征。由于脑电图包含大量复杂的信息，因此许多研究人员正在尝试开发自动系统来完成特征提取。本文对过去十年中开发的流行癫痫检测算法进行了概括回顾和性能比较。