Pulse Artifact Detection in Simultaneous EEG-fMRI Recording Based on EEG Map Topography
Pulse Artifact Detection in Simultaneous EEG-fMRI Recording Based on EEG Map Topography
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DOI：
10.1007/s10548-014-0409-z
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发表时间：
2015-01-01
期刊：
影响因子：
2.7
通讯作者：
Grouiller, Frederic
中科院分区：
文献类型：
--
作者：
Iannotti, Giannina R.;Pittau, Francesca;Grouiller, Frederic
在功能磁共振成像（fMRI）中，干扰脑电图（EEG）的主要伪影之一是脉冲伪影（PA）。这主要是由于每次心跳后，头部和附着在磁场中的电极和电线的运动。在这项研究中，我们提出了一种新的方法，通过考虑左右脑电电极之间的强梯度和反向极性来改进PA检测。我们在3 t时获得高密度的EEG-fMRI（256个电极）和同时进行的心电图（ECG）， PA被估计为来自显示最强伪影（面部和颞部）的电极的左右信号之间的电压差。在这个估计信号上检测到峰值，并与ECG记录中的峰值进行比较。我们分析了11名健康受试者、2名癫痫患者和4名在电极和头皮之间有绝缘层的健康受试者的数据。两种方法的准确性用三个标准来评估：(i)标准差，（ii）峰度和（iii）限制在峰间间隔的生理范围内。我们还检查了新方法是否对癫痫峰的识别有影响。结果表明，与ECG方法相比，估计的PA在15/17的病例中改善了伪影检测。此外，癫痫尖峰的识别并没有被纠正。所提出的方法改进了脉冲相关伪影的检测，特别是当ECG质量差或无法记录时。这将有助于提高脑电图的质量，增加脑电图信息fMRI分析的可靠性。
One of the major artifact corrupting electroencephalogram (EEG) acquired during functional magnetic resonance imaging (fMRI) is the pulse artifact (PA). It is mainly due to the motion of the head and attached electrodes and wires in the magnetic field occurring after each heartbeat. In this study we propose a novel method to improve PA detection by considering the strong gradient and inversed polarity between left and right EEG electrodes. We acquired high-density EEG-fMRI (256 electrodes) with simultaneous electrocardiogram (ECG) at 3 T. PA was estimated as the voltage difference between right and left signals from the electrodes showing the strongest artifact (facial and temporal). Peaks were detected on this estimated signal and compared to the peaks in the ECG recording. We analyzed data from eleven healthy subjects, two epileptic patients and four healthy subjects with an insulating layer between electrodes and scalp. The accuracy of the two methods was assessed with three criteria: (i) standard deviation, (ii) kurtosis and (iii) confinement into the physiological range of the inter-peak intervals. We also checked whether the new method has an influence on the identification of epileptic spikes. Results show that estimated PA improved artifact detection in 15/17 cases, when compared to the ECG method. Moreover, epileptic spike identification was not altered by the correction. The proposed method improves the detection of pulse-related artifacts, particularly crucial when the ECG is of poor quality or cannot be recorded. It will contribute to enhance the quality of the EEG increasing the reliability of EEG-informed fMRI analysis.