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Various artifacts reduction algorithms for EEG recorded in continuous fMRI scan environment

机译:连续fMRI扫描环境中记录的各种脑电信号减少算法

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The EEG recorded in fMRI scanner are totally submerged in gradient, ballistocardiogram and ocular artifacts. Traditional ways to reduce these artifacts have many limitations. AAS has a high requirement on recording and calculating and ICA denoising can be hardly done objectively without extra references. In this paper, we try to simplify and improve the AAS to lower its requirements on calculating. PCA dimension reduction is also introduced to overcome the problem of ICA denoising. A various artifacts removal method is developed based on improved AAS called Re-seg AAS and ICA&PCA. Comparisons before and after each processing step in both time and frequency domain shows that proposed method reduce gradient, ballistocardiogram and ocular artifacts effectively.
机译:用fMRI扫描仪记录的脑电图完全浸没在梯度,心动描记图和眼部伪影中。减少这些伪像的传统方法有很多局限性。 AAS对记录和计算有很高的要求,如果没有额外的参考,很难客观地完成ICA去噪。在本文中,我们试图简化和改进AAS,以降低其对计算的要求。还引入了PCA降维以克服ICA去噪的问题。基于改进的AAS(称为Re-seg AAS和ICA&PCA),开发了各种伪影去除方法。在时域和频域上,每个处理步骤前后的比较表明,该方法可以有效地减少梯度,心动描记图和眼部伪影。

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