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采用改进验证技术的四种眼动(EOG)校正方法的测试。

A test of four EOG correction methods using an improved validation technique.

机构信息

Brain Sciences Institute, Swinburne University of Technology, Victoria 3122, Australia.

出版信息

Int J Psychophysiol. 2011 Feb;79(2):203-10. doi: 10.1016/j.ijpsycho.2010.10.008. Epub 2010 Oct 27.

Abstract

A group of methods that are employed for removing ocular artifact from the electroencephalogram (EEG) is referred to as electrooculogram (EOG) correction methods. These use least-square linear regression, and the relative success of these is yet to be established. Improving on previous EOG correction validation studies, we present a new validation technique (with greater face validity) and use it to compare four commonly employed EOG correction methods. Data consisted of ERP traces to auditory stimuli that were embedded in up, down, left and right eye movements (EMs), recorded from 24 subjects. A 'Peak Difference' validation measure was employed, which determined the magnitude of the difference of two auditory N100 peaks (those associated with EMs with opposing polarities). All correction methods produced data that was better than not correcting at all. EOG correction methods that accounted for vertical EM, horizontal EM and blink artifact separately using separate EOG channels, produced the best corrections, with some further advantage in methods that enhanced signal (EOG) to noise (EEG) ratios when calculating correction coefficients.

摘要

一种用于从脑电图 (EEG) 中去除眼电伪迹的方法被称为眼电图 (EOG) 校正方法。这些方法使用最小二乘线性回归,其相对成功率尚未确定。为了改进以前的 EOG 校正验证研究,我们提出了一种新的验证技术(具有更高的表面有效性),并使用它来比较四种常用的 EOG 校正方法。数据由记录自 24 名受试者的听觉刺激诱发的 ERP 轨迹组成,这些刺激嵌入在上、下、左、右眼运动 (EM) 中。采用了“峰值差”验证度量标准,该标准确定了两个听觉 N100 峰值(与具有相反极性的 EM 相关的峰值)之间差异的幅度。所有校正方法产生的数据都优于完全不校正的数据。使用单独的 EOG 通道分别校正垂直 EM、水平 EM 和眨眼伪迹的 EOG 校正方法产生了最佳的校正效果,在计算校正系数时增强信号 (EOG) 与噪声 (EEG) 比的方法具有一些进一步的优势。

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