基于Infomax算法的脑电信号中心电伪迹的消除

介绍了一种基于信息最大化(Infomax)算法的盲源分离(BlindSourceSeparation,简称BSS)方法,并将其应用于脑电信号的预处理中,有效地去除了脑电信号中的心电伪迹。

基于高阶累积量算法的脑电信号中心电伪迹的消除

在脑电信号测量过程中,不可避免的会存在心电信号的干扰,给医生的诊断带来困难。本文将盲源分离理论用于研究脑电信号中的心电伪迹消除,介绍了盲源分离问题的基本模型、基于高阶累积量的独立性判决准则以及联合近似对角化算法。仿真实验表明,该方法能有效去除脑电信号中的心电伪迹干扰。

如何消除脑电地形图的常见伪迹?

答:脑电地形图的伪迹很多,常见的伪迹有眼动、心电、电极、出汗、移动、肌电、电磁波。下面是消除脑电地形图常见伪迹的几种常用方法。 1.眼协伪迹的消除:病人精神紧张时出现眨眼等眼动伪迹。消除病人的精神紧张因素,让病人处于自动放松状念,假如病人不能自制,可用手把眼皮压上即可消除之。

Effect of heartbeat perception on heartbeat evoked potential waves

Objective Early researches found that different heartbeat perceivers have different heartbeat evoked potential （HEP）waves.Two tasks were considered in our experiments to get more details about the differences between good and poor heartbeat perceivers at attention and resting state.Methods Thirty channels of electroencephalogram（EEG）were recorded in 22 subjects,who had been subdivided into good and poor heartbeat perceivers by mental tracking task. Principal component analysis（PCA）was applied to remove cardiac field artifact（CFA）from the HEP.Results（1）The good heart-beat perceivers showed difference between attention and resting state in the windows from 250 ms to 450 ms after R wave at C3 location and from 100 ms to 300 ms after R wave at C4 location;（2）The difference waveforms between good and poor heartbeat perceivers was a positive waveform at FZ from 220 ms to 340 ms after R wave,which was more significant in attention state.Conclusion Attention state had more effect on the HEPs of good heartbeat perceivers than that of poor heartbeat perceivers;and perception ability influenced HEPs more strongly in the attention state than in the resting state.

基于实时约束独立成分分析方法的核磁脑电信号去噪研究

同步脑电—功能磁共振融合技术因其高精度的时空分辨率,在科学研究和临床领域发挥着重要作用。然而,核磁环境下的心电伪迹严重影响了融合结果。本文利用实时技术改进了离线约束独立成分分析算法,并采用该方法处理了模拟数据和真实静息态数据。结果表明:对于模拟信号,本方法得到的Er值小于平均模板减法等传统方法(P<0.005);对于真实信号,本方法得到的INPS值高于其他方法(P<0.005)。本文提出的去噪算法为脑电核磁的融合模型研究奠定了技术基础。