Murro A M, King D W, Smith J R, Gallagher B B, Flanigin H F, Meador K
Department of Neurology, VA Medical Center, Augusta, GA 30912.
Electroencephalogr Clin Neurophysiol. 1991 Oct;79(4):330-3. doi: 10.1016/0013-4694(91)90128-q.
In this study, we describe a computerized method that uses 3 quantified EEG features and discriminant analysis to automatically detect seizure EEG. The quantified EEG features were relative amplitude, dominant frequency and rhythmicity. Using EEGs recorded from intracranial electrodes, the seizure detection method was applied to consecutive non-overlapping 2-channel EEG epochs. A seizure detection sensitivity, ranging from 90% to 100%, was associated with a false positive detection rate of 1.5-2.5/h. The performance of the seizure detection method remained stable for EEG recorded over variable time periods.
在本研究中,我们描述了一种计算机化方法,该方法使用3种量化脑电图特征和判别分析来自动检测癫痫脑电图。量化脑电图特征为相对振幅、主导频率和节律性。利用颅内电极记录的脑电图,将癫痫检测方法应用于连续的、不重叠的双通道脑电图片段。癫痫检测灵敏度在90%至100%之间,假阳性检测率为每小时1.5 - 2.5次。癫痫检测方法的性能在不同时间段记录的脑电图中保持稳定。