Department of Electrical and Computer Engineering,University of British Columbia, Vancouver, Canada.
IEEE Trans Biomed Eng. 2012 Aug;59(8):2103-10. doi: 10.1109/TBME.2011.2108295. Epub 2011 Jan 28.
A novel approach is presented for using an eye tracker-based reference instead of EOG for methods that require an EOG reference to remove ocular artifacts (OA) from EEG. It uses a high-speed eye tracker and a new online algorithm for extracting the time course of a blink from eye tracker images to remove both eye movement and blink artifacts. It eliminates the need for EOG electrodes attached to the face, which is critical for practical daily applications. The ability of two adaptive filters (RLS and H^ ) to remove OA is measured using: 1) EOG; 2) frontal EEG only (fEEG); and 3) the eye tracker with frontal EEG (ET + fEEG) as reference inputs. The results are compared for different eye movements and blinks of varying amplitudes at electrodes across the scalp. Both the RLS and H^ methods were shown to benefit from using the proposed eye tracker-based reference (ET + fEEG) instead of either an EOG reference or a reference based on frontal EEG alone.
提出了一种新的方法,使用基于眼动追踪器的参考而不是 EOG,来代替那些需要 EOG 参考来从 EEG 中去除眼动伪迹 (OA) 的方法。它使用高速眼动追踪器和一种新的在线算法,从眼动追踪器图像中提取眨眼的时间历程,以去除眼动和眨眼伪迹。它消除了对面部附着 EOG 电极的需求,这对于实际的日常应用至关重要。使用以下参考输入来衡量两种自适应滤波器 (RLS 和 H^) 去除 OA 的能力:1)EOG;2)仅额部 EEG (fEEG);3)带有额部 EEG 的眼动追踪器 (ET + fEEG)。将结果与不同电极在不同幅度的眼球运动和眨眼时进行比较。RLS 和 H^方法都受益于使用基于眼动追踪器的参考 (ET + fEEG),而不是 EOG 参考或仅基于额部 EEG 的参考。