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Anticipation of epileptic seizure in advance and localization of seizure onset zone using power spectral density

机译:使用功率谱密度预期癫痫发作的预期和定位癫痫发作区域的定位

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To have an accurate prediction of epileptic seizure and identification of the epileptogenic region is a difficult task. This paper utilizes scalp electroencephalogram to predict an epileptic seizure and detect an epileptogenic region. To detect epileptogenic region, the signals from five different regions of brain are taken into consideration. Forty-four non-linear features are extracted from eight frequency bands theta, θ, (4–8 Hz), alpha, α, (8–13 Hz), beta, β, (13–30 Hz), gamma1, γ1, (30–50 Hz), gamma 2, γ2 (50–70 Hz), gamma3, γ3 (70–90 Hz), gamma4, γ4 (90–110 Hz) and gamma5, γ5 (110–128 Hz). Features include eight absolute spectral powers, eight relative spectral powers and twenty eight spectral power ratios. These features have been computed for ten seizure cases using a ten minute non overlapping window. From these forty four features the spectral power ratio from gamma band [30–128 Hz] [gamma1 (30–50 Hz) / gamma 3(70–90 Hz)] shows a prominent change for all the seizure cases during pre-ictal duration. The results also show that epileptic seizure is predicted in the second segment i.e. twenty minutes before the onset of seizure. Zone2 (temporal zone in this work) shows the highest change as compared to other zones so it is identified as the epileptogenic region in this work.
机译:为了准确预测对癫痫发作并鉴定癫痫区域是一项艰巨的任务。本文利用头皮脑电图来预测癫痫癫痫发作并检测癫痫区域。为了检测癫痫区域,考虑来自五种不同地区的脑的信号。从八个频带θ,θ,(4-8 hz),α,α,β,β,β,γ1,γ1,γ1,γ1,γ1,提取四十四个非线性特征(30-50Hz),γ2,γ2(50-70Hz),γ3,γ3(70-90Hz),γ4,γ4(90-110 Hz)和γ5,γ5(110-128 Hz)。功能包括八个绝对光谱功率,八个相对光谱功率和二十八个光谱功率比。使用10分钟非重叠窗口的十个癫痫盒已经计算了这些功能。从这些四十四个特征,来自γ频段的光谱功率比[30-128 Hz] [γ1(30-50Hz)/γ3(70-90Hz)]显示出在胰岛前持续时间内所有癫痫病例的突出变化。结果还表明,在癫痫发作前的第二段中预测了癫痫癫痫发作。 Zone2(本工作中的时间区)显示与其他区域相比的最高变化,因此它在这项工作中被鉴定为癫痫发生区域。

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