基于IAF的alpha波段静息态脑磁信号特征提取  

Feature extraction of alpha resting state MEG based on IAF

作　　者：赵建英[1] 黄晓霞[1] 

机构地区：[1]上海海事大学信息工程学院,上海201306

出　　处：《微型机与应用》2015年第16期87-89,共3页Microcomputer & Its Applications

基　　金：第48批教育部留学回国人员科研启动基金;国家自然科学基金(61175044)

摘　　要：针对精神分裂患者静息态脑磁特征提取的问题,提出一种基于EMD和样本熵的非线性动力学方法对脑磁信号特征进行提取。该方法首先用ICA对静息态MEG数据进行预处理;继而基于IAF进行波段提取,得到快α、慢α1和慢α2波段;然后分别由EMD和样本熵进行处理。结果表明,精神分裂患者的各波段样本熵普遍高于正常人,尤其是慢α1波段大脑左半球额叶、枕叶、颞叶区。Using nonlinear dynamics method to analyze schizophrenic patients resting state meg data. ICA method is the first, followed by IAF for band extraction, to get quick alpha, slow alphal and slow alpha2, whose feature extractions are realized by sample entropy. The results of the study indicate that for schizophrenia patients, L-alphal of left hemisphere frontal lobe, occipital lobe, temporal lobe of sample entropy is significantly higher than that of normal people.

关 键 词：MEG IAF EMD 样本熵 精神分裂症 静息态 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]