基于改进功率谱熵的抑郁症脑电信号活跃性研究

发布时间：2018-10-08 13:49

【摘要】：采用非线性动力学方法研究脑精神疾病是近年来国内外学者研究的热点和趋势.针对脑精神疾病的研究和诊断中缺少客观有效的量化参数和量化指标的状况,提出了一种根据对时间序列功率谱划分而定义的谱熵,然后用其计算和分析脑电信号谱熵的方法.通过数据仿真试验证明该谱熵和信号活跃性之间存在正相关关系.基于这种相关性,应用该方法对抑郁症患者和正常对照组的脑电信号功率谱熵进行了数值计算,然后进行了分析对比和统计检验.实验结果表明:抑郁症患者脑电信号的功率谱熵在部分脑区显著弱于正常健康人.证明该谱熵能够表征大脑电生理活动状况,提供反映其活动性强弱的信息,可以作为度量大脑电生理活动性的一个参数.这对于能否将该功率谱熵作为诊断脑精神疾病的物理参数具有积极意义.
[Abstract]:In recent years, the research of brain mental disease by nonlinear dynamics has been a hot topic and trend of scholars at home and abroad. In view of the lack of objective and effective quantization parameters and quantification indexes in the research and diagnosis of brain mental diseases, a method of calculating and analyzing the spectral entropy of EEG signal is proposed, which is defined according to the power spectrum division of time series. The data simulation results show that there is a positive correlation between the spectral entropy and the signal activity. Based on this correlation, the EEG power spectral entropy of depression patients and normal controls was calculated numerically, and then analyzed and compared with statistical tests. The results showed that the power spectral entropy of EEG in depression patients was significantly lower than that in normal controls. It is proved that the spectral entropy can be used as a parameter to measure the electrophysiological activity of the brain. This has a positive significance for whether the power spectrum entropy can be used as a physical parameter for the diagnosis of brain mental illness.
【作者单位】：北京工业大学国际WIC研究院;磁共振成像脑信息学北京市重点实验室;脑信息智慧服务北京市国际科技合作基地;前桥工业大学生命科学与信息工程系;
【基金】：国家重点基础研究发展计划(批准号:2014CB744605,2014CB744603) 国家国际科技合作专项(批准号:2013DFA32180) 国家自然科学基金(批准号:61272345)资助的课题~~
【分类号】：TN911.7

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