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A review on the pattern detection methods for epilepsy seizure detection from EEG signals

机译:脑电信号检测癫痫发作的模式检测方法综述

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摘要

Over several years, research had been conducted for the detection of epileptic seizures to support an automatic diagnosis system to comfort the clinicians' encumbrance. In this regard, a number of research papers have been published for the identification of epileptic seizures. A thorough review of all these papers is required. So, an attempt has been made to review on the pattern detection methods for epilepsy seizure detection from EEG signals. More than 150 research papers have been discussed to determine the techniques for detecting epileptic seizures. Further, the literature review confirms that the pattern recognition techniques required to detect epileptic seizures varies across the electroencephalogram (EEG) datasets of different conditions. This is mostly owing to the fact that EEG detected under different conditions have different characteristics. This consecutively necessitates the identification of the pattern recognition technique to efficiently differentiate EEG epileptic data from the EEG data of various conditions.
机译:几年来,已经进行了有关癫痫发作检测的研究,以支持自动诊断系统来缓解临床医生的负担。在这方面,已经发表了许多用于鉴定癫痫发作的研究论文。需要对所有这些论文进行彻底的审查。因此,已经尝试审查用于从EEG信号中检测癫痫发作的模式检测方法。为了确定检测癫痫发作的技术,已经讨论了150多篇研究论文。此外,文献综述证实,检测癫痫发作所需的模式识别技术在不同条件的脑电图(EEG)数据集之间会有所不同。这主要是由于在不同条件下检测到的脑电图具有不同的特征。这连续需要模式识别技术的识别,以有效地区分各种条件下的脑电图数据和脑电图癫痫数据。

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