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首页> 外文会议>Advances in biomedical research >An Extensive Review of Significant Researches on Epileptic Seizure Detection and Prediction using Electroencephalographic Signals
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An Extensive Review of Significant Researches on Epileptic Seizure Detection and Prediction using Electroencephalographic Signals

机译：关于脑电信号癫痫发作检测和预测的重要研究的广泛综述

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摘要

Epileptic seizure is a brain disorder caused by large number of small electrical discharges of nerve cells. Electroencephalographic (EEG) signals are the most commonly used source for Epileptic seizure prediction. A variety of temporal changes in perception and behavior may be caused by Epileptic seizures. In the human EEG, they are depicted by multiple ictal patterns, where epileptic seizures typically become perceptible as characteristic, usually rhythmic signals, often concurring with or even preceding the earliest observable changes in behavior. Earliest possible detection of observable onset of ictal patterns in the EEG can, thus, serve to initiate more-detailed diagnostic procedures during seizures and to distinguish epileptic seizures from other stipulations with seizure-like symptoms. Lately, warning and intervention systems triggered by the detection of ictal EEG patterns have fascinated escalating interest. As the workload implicated in the detection and prediction of seizures by human experts is quite formidable, a number of attempts have been made to devise automatic seizure detection and prediction systems. So far, none of these have found extensive application. There have been an increased number of researches carried out with the purpose of devising an automatic seizure detection and prediction system.In this paper, we present an extensive review of the significant researches associated with the detection and prediction of Epileptic Seizures using EEG signals, hi addition, we have presented an in depth description of Electroencephalogram, Epileptic Seizure and its types along with Epilepsy.
机译：癫痫病发作是由大量神经细胞小放电引起的脑部疾病。脑电图（EEG）信号是癫痫发作预测的最常用来源。癫痫性癫痫发作可能引起知觉和行为的各种时间变化。在人脑电图中，它们以多种发作模式描绘，在这种情况下，癫痫性发作通常可感知为特征性的（通常是节律性的）信号，通常与最早可观察到的行为改变同时发生，甚至早于可观察到的行为改变。因此，尽早发现可观察到的脑电图发作模式可有助于在癫痫发作期间启动更详细的诊断程序，并将癫痫性癫痫发作与其他具有癫痫样症状的规定区分开。最近，由短波脑电图模式检测触发的预警和干预系统引起了人们的浓厚兴趣。由于涉及人类专家检测和预测癫痫发作的工作量非常巨大，因此人们进行了许多尝试来设计自动癫痫发作检测和预测系统。到目前为止，这些都还没有找到广泛的应用。为了设计一种自动的癫痫发作检测和预测系统，已经进行了越来越多的研究。在本文中，我们对与使用脑电信号检测和预测癫痫发作相关的重要研究进行了广泛的综述。此外，我们还介绍了脑电图，癫痫发作及其类型与癫痫病的深入描述。

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