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A review of developments of EEG-based automatic medical support systems for epilepsy diagnosis and seizure detection

机译:基于EEG的癫痫诊断和癫痫发作自动医疗支持系统的发展综述

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Epilepsy is one of the most common neurological disorders-approximately one in every 100 people worldwide are suffering from it. The electroencephalogram (EEG) is the most common source of information used to monitor, diagnose and manage neurological disorders related to epilepsy. Large amounts of data are produced by EEG monitoring devices, and analysis by visual inspection of long recordings of EEG in order to find traces of epilepsy is not routinely possible. Therefore, automated detection of epilepsy has been a goal of many researchers for a long time. Until now, reviews of epileptic seizure detection have been published but none of them has specifically reviewed developments of automatic medical support systems utilized for EEG-based epileptic seizure detection. This review aims at filling this lack. The main objective of this review will be to briefly discuss different methods used in this research field and describe their critical properties.
机译:癫痫病是最常见的神经系统疾病之一,全世界每100人中就有大约1人患有癫痫病。脑电图(EEG)是用于监视,诊断和管理与癫痫相关的神经系统疾病的最常见信息源。脑电图监测设备会产生大量数据,通常无法通过目视检查脑电图的长记录进行分析以发现癫痫的痕迹。因此,癫痫的自动检测长期以来一直是许多研究者的目标。到目前为止,癫痫发作检测的评论已经发表,但是没有一个专门审查基于EEG的癫痫发作检测的自动医疗支持系统的开发。这篇综述旨在填补这一不足。这篇综述的主要目的是简要讨论该研究领域中使用的不同方法,并描述它们的关键特性。

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