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
|
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。
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.
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.
引文
1 Guo Qian,Zhou Tiantong,Li Wenjie,et al.Single-trial EEGinformed fMRI analysis of emotional decision problems in hot executive function.Brain Behav,2017,7(7):e00728.
2邹凌,严永,杨彪,等.基于同步EEG-fMRI采集的情绪认知重评数据特征融合分析研究.自动化学报,2016,42(5):771-781.
3李静,王金甲,李慧.融合脑电特征的弹性网特征选择和分类.生物医学工程学杂志,2016,33(3):413-419.
4 Allen P J,Josephs O,Turner R.A method for removing imaging artifact from continuous EEG recorded during functional MRI.Neuroimage,2000,12(2):230-239.
5 Mullinger K J,Havenhand J,Bowtell R.Identifying the sources of the pulse artefact in EEG recordings made inside an MR scanner.Neuroimage,2013,71:75-83.
6 Mayeli A,Zotev V,Refai H,et al.Real-time EEG artifact correction during fMRI using ICA.J Neurosci Methods,2016,274:27-37.
7 Grouiller F,Vercueil L,Krainik A A,et al.A comparative study of different artefact removal algorithms for EEG signals acquired during functional MRI.Neuroimage,2007,38(1):124-137.
8 Leclercq Y,Balteau E,Dang-Vu T,et al.Rejection of pulse related artefact(PRA)from continuous electroencephalographic(EEG)time series recorded during functional magnetic resonance imaging(fMRI)using constraint independent component analysis(cICA).NeuroImage,2009,44(3):679-691.
9 Niazy R K,Beckmann C F,Iannetti G D,et al.Removal of FMRI environment artifacts from EEG data using optimal basis sets.Neuroimage,2005,28(3):720-737.
10 Krishnaswamy P,Bonmassar G,Poulsen C A,et al.Reference-free removal of EEG-fMRI ballistocardiogram artifacts with harmonic regression.Neuroimage,2016,128:398-412.
11 Abolghasemi V,Ferdowsi S.EEG-fMRI:Dictionary learning for removal of ballistocardiogram artifact from EEG.Biomed Signal Process Control,2015,18:186-194.
12 Wu X,Wu T,Zhan Z,et al.A real-time method to reduce ballistocardiogram artifacts from EEG during fMRI based on optimal basis sets(OBS).Computer Methods and Programs in Biomedicine,2016,127:114-125.
13 Xia Hongjing,Ruan Dan,Cohen M S.Separation and reconstruction of BCG and EEG signals during continuous EEG and fMRI recordings.Front Neurosci,2014,8(8):163.
14 Abreu R,Leite M,Jorge J,et al.Ballistocardiogram artifactcorrection taking into account physiological signal preservation in simultaneous EEG-fMRI.Neuroimage,2016,135:45-63.
15 Yao D Z.A method to standardize a reference of scalp EEG recordings to a point at infinity.Physiol Meas,2001,22(4):693-711.
16 Christov I I.Real time electrocardiogram QRS detection using combined adaptive threshold.Biomed Eng Online,2004,3(1):1-9.
2邹凌,严永,杨彪,等.基于同步EEG-fMRI采集的情绪认知重评数据特征融合分析研究.自动化学报,2016,42(5):771-781.
3李静,王金甲,李慧.融合脑电特征的弹性网特征选择和分类.生物医学工程学杂志,2016,33(3):413-419.
4 Allen P J,Josephs O,Turner R.A method for removing imaging artifact from continuous EEG recorded during functional MRI.Neuroimage,2000,12(2):230-239.
5 Mullinger K J,Havenhand J,Bowtell R.Identifying the sources of the pulse artefact in EEG recordings made inside an MR scanner.Neuroimage,2013,71:75-83.
6 Mayeli A,Zotev V,Refai H,et al.Real-time EEG artifact correction during fMRI using ICA.J Neurosci Methods,2016,274:27-37.
7 Grouiller F,Vercueil L,Krainik A A,et al.A comparative study of different artefact removal algorithms for EEG signals acquired during functional MRI.Neuroimage,2007,38(1):124-137.
8 Leclercq Y,Balteau E,Dang-Vu T,et al.Rejection of pulse related artefact(PRA)from continuous electroencephalographic(EEG)time series recorded during functional magnetic resonance imaging(fMRI)using constraint independent component analysis(cICA).NeuroImage,2009,44(3):679-691.
9 Niazy R K,Beckmann C F,Iannetti G D,et al.Removal of FMRI environment artifacts from EEG data using optimal basis sets.Neuroimage,2005,28(3):720-737.
10 Krishnaswamy P,Bonmassar G,Poulsen C A,et al.Reference-free removal of EEG-fMRI ballistocardiogram artifacts with harmonic regression.Neuroimage,2016,128:398-412.
11 Abolghasemi V,Ferdowsi S.EEG-fMRI:Dictionary learning for removal of ballistocardiogram artifact from EEG.Biomed Signal Process Control,2015,18:186-194.
12 Wu X,Wu T,Zhan Z,et al.A real-time method to reduce ballistocardiogram artifacts from EEG during fMRI based on optimal basis sets(OBS).Computer Methods and Programs in Biomedicine,2016,127:114-125.
13 Xia Hongjing,Ruan Dan,Cohen M S.Separation and reconstruction of BCG and EEG signals during continuous EEG and fMRI recordings.Front Neurosci,2014,8(8):163.
14 Abreu R,Leite M,Jorge J,et al.Ballistocardiogram artifactcorrection taking into account physiological signal preservation in simultaneous EEG-fMRI.Neuroimage,2016,135:45-63.
15 Yao D Z.A method to standardize a reference of scalp EEG recordings to a point at infinity.Physiol Meas,2001,22(4):693-711.
16 Christov I I.Real time electrocardiogram QRS detection using combined adaptive threshold.Biomed Eng Online,2004,3(1):1-9.