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An algorithm for detecting seizure termination in scalp EEG

机译:一种检测头脑eeg中癫痫发作终止的算法

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Little effort has been devoted to developing algorithms that can detect the cessation of seizure activity in scalp EEG. Such algorithms could facilitate clinical applications such as the estimation of seizure duration or the delivery of therapies designed to mitigate postictal period symptoms. In this paper, we present a method for detecting the termination of seizure activity. When tested on 133 seizures from a public database, our method detected the end of 132 seizures with a mean absolute error of 10.3 ± 5.5 seconds of the time marked by an electroencephalographer. Furthermore, by pairing our seizure end detector with a previously published seizure onset detector, we could automatically estimate the duration of 85% of test seizures within a 15 second error margin.
机译:致力于开发算法的小努力,这些算法可以检测到头皮脑油部癫痫发作活动的停止。这种算法可以促进临床应用,例如癫痫发作持续时间的估计或旨在减轻后期症状的疗法的递送。在本文中,我们提出了一种检测癫痫发作活动终止的方法。当从公共数据库中的133次癫痫发作时,我们的方法检测到132癫痫发作的末尾,其平均误差为10.3±5.5秒的脑电图。此外,通过将我们的癫痫发表的癫痫发布发作检测器配对我们的癫痫发布终端检测器,我们可以在15秒的错误边距内自动估计85%的测试癫痫发作的持续时间。

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