Gotman J
Montreal Neurological Institute, Quebec, Canada.
J Clin Neurophysiol. 1985 Jul;2(3):251-65. doi: 10.1097/00004691-198507000-00004.
Computer methods can automatically recognize interictal spikes and seizures quite reliably, but they still make a large number of false detections because of physiological or artifactual nonepileptiform transients. In the context of long-term monitoring, these methods can be used efficiently and safely despite their imperfection. They allow considerable data reduction, by selecting epileptiform activity and discarding the largest part of the recording. In addition to data reduction, computer methods can be useful in refining the analysis of epileptic seizures, revealing information not available from visual inspection of the paper tracing. Recent technological advances make these applications affordable in a clinical EEG laboratory.
计算机方法能够相当可靠地自动识别发作间期棘波和癫痫发作，但由于生理或人为的非癫痫样瞬变，它们仍会产生大量误报。在长期监测的背景下，尽管这些方法存在缺陷，但仍可有效且安全地使用。它们通过选择癫痫样活动并丢弃大部分记录，实现了可观的数据缩减。除了数据缩减外，计算机方法还可用于完善癫痫发作的分析，揭示从纸质记录的目视检查中无法获得的信息。最近的技术进步使这些应用在临床脑电图实验室中变得经济实惠。
