基于平滑最小方差无失真响应的一致性同步算法研究  

Coherence Synchronization Analysis Based on Smoothing Minimum Variance Distortionless Response

作　　者：顾广华[1,2] 崔冬 王娟[1,2] 齐顺爱 李小俚[3] Gu Guanghua;Cui Dong;Wang Juan;Qi Shunai;Li Xiaoli(School of Information Science and Engineering,Yanshan University,Qinhuangdao 066004,Hebei,China;Hebei Key Laboratory of Information Transmission and Signal Processing,Qinhuangdao 066004,Hebei China;State Key Laboratory of Cognitive Neuroscience and Learning,Beijing Normal University,Beijing 100875)

机构地区：[1]燕山大学信息科学与工程学院,河北秦皇岛066004 [2]河北省信息传输与信号处理重点实验室,河北秦皇岛066004 [3]北京师范大学认知神经科学和学习国家重点实验室,北京100875

出　　处：《中国生物医学工程学报》2018年第6期680-687,共8页Chinese Journal of Biomedical Engineering

基　　金：国家自然科学基金(61603327);河北省自然科学基金(F2018203239;F2017203169)

摘　　要：脑电信号一致性反映双通道信号在一定频率范围上波动形式的一致程度,反映相应位点大脑之间的联络性。将基于最小方差无失真响应的一致性算法与核滤波相结合,提出平滑最小方差无失真响应一致性算法(SMVDR);仿真实验表明,SMVDR在窄带信号和宽带信号中均有较好的准确性和抗噪性能。利用新算法SMVDR,对31例糖尿病患者(遗忘型轻度认知障碍aMCI组18人,认知功能正常对照组13人)的脑电信号在大脑不同区域、不同频带(δ,θ,α,β)进行一致性分析,统计分析发现:aMCI组在左右颞间δ频段的一致性下降而β频段一致性增加,前额-枕区的θ频段的一致性增加,右颞-枕区和前额-右颞区域的α频段一致性下降。一致性值与MOCA得分的相关性分析发现,在特征通道下δ和α频段的一致性与MOCA得分存在显著的正相关,θ和β频段一致性与MOCA分数呈负相关。SMVDR算法可以更好地计算双通道脑电信号之间的一致程度,对于理解老年期轻度认知障碍的患病机制并进行早期诊断与干预具有重要的意义。EEG coherence reflects the degree of spectral correlation between two-channels EEG signals, which can assess the connections between neurons in the brain. Combined the coherence method based on minimum variance distortionless response (MVDR) with kernel filter, a new method named smoothing minimum variance distortionless response (SMVDR) was proposed in this study. The simulation analysis indicated that the new method SMVDR provides more accuracy and better anti-noise performance in both narrow-band signals and broad-band signals. SMVDR was used to analyze the EEG coherence of 18 amnesic MCI (aMCI) and 13 normal controls of patients with diabetes between different brain regions in four frequency bands (delta, theta, alpha, beta). We observed a decrease in delta coherence and an increase in beta coherence in left temporal-right temporal region, and an increase in theta coherence in frontal-occipital region, and an increase in alpha coherence in both right temporal-occipital region and frontal-right temporal region in aMCI patients through statistical analysis. Correlation analysis between coherence values and MOCA scores shows that coherence values in alpha band and delta band and MOCA scores had a significant positive correlation in some specific channels, while coherence values in both theta band and beta band and MOCA scores had a significant negative correlation. The new method SMVDR can compute the coherence better between two-channels EEG signals. It is important in exploring the mechanism, early diagnosis and intervention treatment of aMCI.

关 键 词：脑电信号 轻度认知障碍 一致性 平滑的最小方差无失真响应算法 

分 类 号：R318[医药卫生—生物医学工程]