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An extensive review on development of EEG-based computer-aided diagnosis systems for epilepsy detection

机译:基于脑电图的癫痫检测计算机辅助诊断系统开发的广泛综述

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摘要

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.
机译:癫痫病被认为是世界上最重要的神经系统疾病,可以影响所有年龄段的人。目前,全世界约有6500万人患有癫痫病。显然,脑电图(EEG)信号最常用于检测癫痫发作,但如今已开发出许多现代技术来分析这些EEG信号的潜在特征。由于EEG包含大量复杂信息,因此许多研究人员正在尝试开发用于自动特征提取的自动系统。本文对近十年来开发的流行的癫痫发作检测算法进行了概述和性能比较。本文的主要目的是简要讨论用于癫痫检测的计算机辅助诊断系统领域中的所有现有发展,以便将来的研究人员可以为新发明找到更好的方法。

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