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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
Study of denoising of simultaneous electroencephalogram-functional magnetic resonance imaging signal based on real-time constrained independent components analysis
【摘要】 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。
【Abstract】 Simultaneous recording of electroencephalogram(EEG)-functional magnetic resonance imaging(fMRI) plays an important role in scientific research and clinical field due to its high spatial and temporal resolution.However,the fusion results are seriously influenced by ballistocardiogram(BCG) artifacts under MRI environment.In this paper,we improve the off-line constrained independent components analysis using real-time technique(rt-cICA),which is applied to the simulated and real resting-state EEG data.The results show that for simulated data analysis,the value of error in signal amplitude(Er) obtained by rt-cICA method was obviously lower than the traditional methods such as average artifact subtraction(P<0.005).In real EEG data analysis,the improvement of normalized power spectrum(INPS) calculated by rt-cICA method was much higher than other methods(P<0.005).In conclusion,the novel method proposed by this paper lays the technical foundation for further research on the fusion model of EEG-fMRI.
【Key words】 electroencephalogram-functional magnetic resonance imaging; ballistocardiogram artifacts; constrained independent components analysis; artifacts removal;
- 【文献出处】 生物医学工程学杂志 ,Journal of Biomedical Engineering , 编辑部邮箱 ,2019年01期
- 【分类号】R318
- 【被引频次】3
- 【下载频次】143