Jobert M, Poiseau E, Jähnig P, Schulz H, Kubicki S
AFB-Parexel, Arzneimittelforschung GmbH, Berlin, FRG.
Neuropsychobiology. 1992;26(1-2):100-7. doi: 10.1159/000118902.
The evaluation of sleep EEG patterns is mostly accomplished by visual analysis. With modern personal computers however, it is possible to perform signal detection within a reasonable length of time automatically. This paper presents a method for signal processing based on matched filtering. This allows the detection of sleep spindles and K-complexes in a sleep EEG recording with a high degree of accuracy. First the technique is described, and the results of a validation study based on the comparison of visual evaluations and computer analysis are presented. Thereafter, results of an application study are presented. Sleep spindle and K-complex density under the influence of lormetazepam and zopiclone were examined. Under both medications sleep spindle density increased while K-complex density decreased. Computation of Pearson's correlation coefficients demonstrated that the interindividual sleep spindle and K-complex variations under both treatments are highly correlated. The data suggest that lormetazepam and zopiclone, although chemically different, have a similar mode of action and display comparable effects on the sleep EEG.
睡眠脑电图模式的评估大多通过视觉分析来完成。然而，借助现代个人计算机，能够在合理的时间长度内自动进行信号检测。本文提出一种基于匹配滤波的信号处理方法。这使得在睡眠脑电图记录中能够高度准确地检测到睡眠纺锤波和K复合波。首先描述该技术，并给出基于视觉评估与计算机分析比较的验证研究结果。此后，给出应用研究结果。研究了氯美扎酮和佐匹克隆影响下的睡眠纺锤波和K复合波密度。在两种药物作用下，睡眠纺锤波密度增加而K复合波密度降低。皮尔逊相关系数的计算表明，两种治疗下个体间睡眠纺锤波和K复合波的变化高度相关。数据表明，氯美扎酮和佐匹克隆虽然化学结构不同，但具有相似的作用方式，并且对睡眠脑电图显示出可比的效果。
