Jayakar P, Patrick J P, Shwedyk E, Seshia S S
Section of Pediatric Neurosciences, Children's Hospital, Winnipeg, Manitoba, Canada.
Electroencephalogr Clin Neurophysiol. 1989 Feb;72(2):165-75. doi: 10.1016/0013-4694(89)90178-8.
We describe algorithms, developed on a PDP-11/73 microcomputer, which identify spikes/sharp waves (STs), spike-and-wave complexes (SSWs), artifacts and background activity in 4-channel ambulatory EEGs. The algorithms were trained using 40 database segments. Time domain/mimetic methods were used and semantic rules, based on morphology and multi-channel contextual information, were developed to mimic the principles used in visual interpretation. The likelihood of STs/SSWs being genuine was graded from 10 to 1. This approach avoids forced classification of each event as genuine ST/SSW or not. The algorithms were then evaluated using 60 independent segments. STs/SSWs graded greater than 7 had significantly higher probability (P less than 0.005) of being genuine than those graded less than or equal to 7. Less than 4% of STs/SSWs identified by both electroencephalographers were missed. None was distinct. All 113 artifacts resembling STs/WWs were graded less than or equal to 7. Classification of 969/1117 (86%) waves in the background matched that of one electroencephalographer. The algorithms can be extended to 8- or more-channel EEGs.
我们描述了在PDP - 11/73微型计算机上开发的算法，这些算法可识别4通道动态脑电图中的尖峰/锐波（STs）、棘慢复合波（SSWs）、伪迹和背景活动。使用40个数据库片段对算法进行了训练。采用时域/模拟方法，并基于形态学和多通道上下文信息制定了语义规则，以模仿视觉解读中使用的原则。将STs/SSWs为真实信号的可能性从10到1进行分级。这种方法避免了将每个事件强制分类为真实的ST/SSW或非真实信号。然后使用60个独立片段对算法进行评估。分级大于7的STs/SSWs为真实信号的概率显著高于分级小于或等于7的信号（P小于0.005）。两位脑电图专家识别出的STs/SSWs中，漏检率低于4%。无一例明显漏检。所有113个类似STs/WWs的伪迹分级均小于或等于7。背景中969/1117（86%）的波形分类与一位脑电图专家的分类结果相符。这些算法可扩展至8通道或更多通道的脑电图。
