无抽搐电休克治疗中脑电的小波样本熵分析

Wavelet sample entropy analysis of EEG of Modified Electroconvulsive Therapy

无抽搐电休克治疗(Modified Electroconvulsive Therapy,MECT)是精神障碍疾病临床治疗的方法之一,有效的脑电信号量化参数有助于认识MECT的治疗效果和进行临床规划。该文针对MECT期间精神障碍患者单通道脑电信号进行分析,利用离散小波变换将脑电信号分解到不同频段,采用样本熵分析MECT过程中诱导的人工癫痫充分发作后和非充分发作后各频段脑电信号的复杂度。实验和分析结果表明,接受MECT的精神障碍患者经诱导人工癫痫充分发作后的额叶皮层脑电信号小波系数A4、D4和D3的样本熵值显著小于非充分发作后对应样本熵值,表明癫痫充分发作可以有效增加脑电信号的规律性,降低脑电信号的复杂程度。利用t检验对结果进行分析,证明了该方法的可行性和准确性,其将为MECT治疗的疗效评估和临床规划提供有效的量化指标。

Modified Electroconvulsive Therapy(MECT)is one of the clinical treatment methods of mental disorders,and effective quantitative indicator of EEG signals is helpful for measuring the treatment efficacy and clinical planning.In this paper,the single-channel EEG recordings of patients with mental disorders during MECT are decomposed into different frequency bands by Discrete Wavelet Transform(DWT),and the complexity of the EEG signals across all frequency bands after adequate and inadequate MECT-induced seizures artificially is evaluated by sample entropy.The results show that the sample entropy values of wavelet coefficients A4,D4 and D3 in frontal cortex of patients with mental disorders who received MECT after adequate MECT-induced seizures artificially are significantly lower than those after inadequate MECT-induced seizures.It indicates that MECT-induced adequate seizures can effectively increase the regularity of EEG signals and reduce the complexity of EEG signals.The t-test statistical analysis is performed to prove the accuracy and the feasibility of this method,provide an effective quantitative indicator for the evaluation of MECT efficacy and clinical planning.