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目的:研究儿童失神癫癎脑电图的多尺度定量特征。方法:对15例失神癫癎患儿10次临床发作和20次亚临床癎样放电的脑电图进行子波分析,提取失神癫癎发作过程中脑电信号的多尺度定量典型特征,与发作前10 s及发作后10 s的脑电信号进行比较,并与12例正常同龄儿童脑电图进行比较。结果:研究显示儿童失神癫癎发作过程中脑电信号的多尺度典型特征主要表现为12尺度(对应频率3 Hz)的节律性活动显著增强,发作时20尺度(低频大尺度,对应频率0．12 Hz)结构与频率3 Hz的结构具有非正常的跳跃式尺度关系,3 Hz节律性棘慢复合波与大尺度(频率1 Hz以下)背景低频放电结构共同存在。发作过程中分尺度功率主要集中在20尺度和12尺度,其演变规律为20尺度能量逐渐减低,12尺度能量逐渐增加。10次临床发作的脑电信号均显示上述特征。发作前10 s和后10 s的脑电多尺度信号中仍然存在隐性的3 Hz棘慢复合波成分,与一般认为3 Hz棘慢复合波突起突止不同．而从传统的脑电图上无法分辨出发作前后的这些多尺度细节的定量特征。亚临床癎样放电的多尺度特征与发作期无明显差别,但持续时间短。结论:子波分析作为一种新的信号分析方法,适合于脑电信号的分析,可以获得比传统视觉脑电图更多的定量信息。通过对失神癫癎患儿的脑电信号进行子波分析,得到其发作过程中典型的多尺度定量特征,有助于失神癫癎发作的临床辅助诊断、预后评价以及神经电生理机理的基础研究。
Objective: To study the multi-scale quantitative characteristics of children’s absence epileptic EEG. Methods: EEG analysis was performed on 10 clinical seizures and 20 subclinical 癎-like discharges in 15 children with absence of epilepsy. The multi-scale quantitative typical features of EEG signals during the absence of epilepsy were extracted and compared with seizures The first 10 seconds and 10 seconds after the onset of EEG signals were compared with 12 normal children’s EEG comparison. Results: The multi-scale typical features of EEG in deafness epileptic seizures were mainly manifested as significantly increased rhythmic activity at 12 scales (corresponding to a frequency of 3 Hz), with 20 scales at the time of attack (large scale at low frequency and corresponding frequency 0). 12 Hz) structure with a frequency of 3 Hz has a non-normal jumping scale relationship, and the 3 Hz rhythmic spinous-slow complex wave co-exists with a large scale (below 1 Hz) background low frequency discharge structure. During the attack, the power of sub-scale mainly concentrated on the 20-scale and the 12-scale. The evolution of the sub-scale power was gradually reduced at 20-scale and gradually increased at 12-scale. 10 clinical seizures of the EEG signals show the above characteristics. The implicit 3 Hz spinous-slow complex wave components still existed in EEG multi-scale signals at 10 s and 10 s after the onset of attack, which is different from that of 3 Hz spinous-slow complex waves. However, the quantitative features of these multi-scale details before and after the attack can not be distinguished from the traditional EEG. There were no significant differences in the multi-scale characteristics of subclinical 放-like discharges with the duration of attack, but the duration was short. Conclusion: Wavelet analysis as a new signal analysis method is suitable for the analysis of EEG signal, and can obtain more quantitative information than traditional visual EEG. By analyzing the EEG signals of children with absence of epilepsy, the typical multiscale quantitative features during the onset of the epileptic seizures are helpful to the clinical diagnosis, prognosis evaluation and the electrophysiological mechanism of deafness epilepsy .