本研究采用脑电信号的整体子波熵和分尺度子波熵研究脑电信号的信息复杂性，探索儿童失神癫痫（CAE）发作的动力学机制。研究采集儿童失神癫痫患者及正常对照的脑电信号；采用连续子波变换提取脑电信号的时频特征；采用子波功率谱分析提取分尺度功率谱特征；根据分尺度功率谱计算整体子波熵和分尺度子波熵，分析整体子波熵和分尺度子波熵随 CAE 发作的时间演变过程，并与正常对照进行比较。结果显示：CAE 患者发作期脑电信号的整体子波熵显著低于正常对照组，也低于发作间期。CAE 发作时第 12 尺度（对应中心频率 3 Hz）的分尺度子波熵显著高于正常对照，α 频带（中心频率 10 Hz）脑电节律的子波熵明显低于正常对照。脑电信号整体子波熵可以反映脑电信号的复杂程度，CAE 发作时脑电信号的信息复杂度明显降低。子波熵降低有可能成为癫痫发作的特征神经电生理参数，为癫痫发作的神经调控技术的研究提供依据。
The integral and individual-scale wavelet entropy of electroencephalogram (EEG) were employed to investigate the information complexity in EEG and to explore the dynamic mechanism of child absence epilepsy (CAE). The digital EEG signals were collected from patients with CAE and normal controls. Time-frequency features were extracted by continuous wavelet transformation. Individual scale power spectrum characteristics were represented by wavelet-transform. The integral and individual-scale wavelet entropy of EEG were computed on the basis of individual scale power spectrum. The evolutions of wavelet entropy across ictal EEG of CAE were investigated and compared with normal controls. The integral wavelet entropy of ictal EEG is lower than inter-ictal EEG for CAE, and it also lower than normal controls. The individual-scale wavelet entropies of 12th scale (centered at 3 Hz) of ictal EEG in CAE was significantly higher than normal controls. The individual-scale wavelet entropies for α band (centered at 10 Hz) of ictal EEG in CAE were much lower than normal controls. The integral wavelet entropy of EEG can be considered as a quantitative parameter of complexity for EEG signals. The complexity of ictal EEG for CAE is obviously declined in CAE. The wavelet entropies declined could become quantitative electrophysiological parameters for epileptic seizures, and it also could provide a theoretical basis for the study of neuromodulation techniques in epileptic seizures.
引用本文： 张美云, 王晨, 张莹, 陈英, 吴波, 张玉琴, 王凤楼. 儿童失神癫痫发作期脑电信号子波熵分析. 生物医学工程学杂志, 2018, 35(4): 530-538. doi: 10.7507/1001-5515.201701002 复制