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A passive BCI for monitoring the intentionality of the gaze-based moving object selection

机译:用于监视基于凝视的移动对象选择的意向的被动BCI

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摘要

Objective. The use of an electroencephalogram (EEG) anticipation-related component, theexpectancy wave (E-wave), in brain–machine interaction was proposed more than 50 years ago.This possibility was not explored for decades, but recently it was shown that voluntary attempts toselect items using eye fixations, but not spontaneous eye fixations, are accompanied by the E-wave.Thus, the use of the E-wave detection was proposed for the enhancement of gaze interactiontechnology, which has a strong need for a mean to decide if a gaze behavior is voluntary or not.Here, we attempted at estimating whether this approach can be used in the context of movingobject selection through smooth pursuit eye movements. Approach. Eighteen participants selected,one by one, items which moved on a computer screen, by gazing at them. In separate runs, theparticipants performed tasks not related to voluntary selection but also provoking smooth pursuit.A low-cost consumer-grade eye tracker was used for item selection. Main results. A componentresembling the E-wave was found in the averaged EEG segments time-locked to voluntary selectionevents of every participant. Linear discriminant analysis with shrinkage regularization classified theintentional and spontaneous smooth pursuit eye movements, using single-trial 300 ms long EEGsegments, significantly above chance in eight participants. When the classifier output was averagedover ten subsequent data segments, median group ROC AUC of 0.75 was achieved. Significance.The results suggest the possible usefulness of the E-wave detection in the gaze-based selection ofmoving items, e.g. in video games. This technique might be more effective when trial data can beaveraged, thus it could be considered for use in passive interfaces, for example, in estimating thedegree of the user’s involvement during gaze-based interaction.
机译:客观的。使用脑电图(EEG)预期相关组分,在50多年前提出脑机相互作用的寿命波(E-Wave)。几十年来探讨了这种可能性,但最近有人认为自愿尝试选择使用眼睛固定,但不是自发的眼睛固定的物品伴随着E波。因此,提出了用于增强凝视相互作用的e波检测的使用技术,强烈需要一个意味着决定凝视行为是否是自愿的。在这里,我们尝试估算这种方法是否可以在移动的上下文中使用通过平滑追求眼睛运动的对象选择。方法。 18名参与者选择,一个接一个,通过凝视在计算机屏幕上移动的物品。在单独的运行中,参与者执行与自愿选择无关的任务,但也引发了平稳的追求。低成本的消费类眼跟踪器用于项目选择。主要结果。一个组成部分类似于E-Wave的eg段在截止到自愿选择的平均eeg段中找到每个参与者的事件。线性判别分析与收缩正则化分类故意和自发平滑的追求眼球运动,使用单试300毫秒长脑电图细分,显着高于八个参与者的机会。当分类器输出平均时在10个后续数据段中,实现了0.75的中位数群体ROC AUC。意义。结果表明了在基于凝视的选择中的电子波检测可能的有用性移动物品,例如在电子游戏中。当试验数据可以是时,这种技术可能更有效平均值,因此可以考虑用于被动接口,例如估计用户在基于凝视的互动期间参与的程度。

著录项

  • 来源
    《Journal of neural engineering》 |2021年第2期|1-18|共18页
  • 作者单位

    Laboratory for Neurocognitive Technologies NRC Kurchatov Institute Moscow Russia;

    Laboratory for Neurocognitive Technologies NRC Kurchatov Institute Moscow Russia Laboratory for Neurophysiology and Neuro-Computer Interfaces M.V. Lomonosov Moscow State University Moscow Russia MEG Center Moscow State University of Psychology and Education Moscow Russia;

    Laboratory for Neurocognitive Technologies NRC Kurchatov Institute Moscow Russia Department of Data Science EURECOM Biot France;

    Laboratory for Neurocognitive Technologies NRC Kurchatov Institute Moscow Russia;

    Laboratory for Neurocognitive Technologies NRC Kurchatov Institute Moscow Russia Institute of NBCIS S&T Moscow Institute of Physics and Technology Moscow Russia;

    Laboratory for Neurocognitive Technologies NRC Kurchatov Institute Moscow Russia Institute of NBCIS S&T Moscow Institute of Physics and Technology Moscow Russia;

    Laboratory for Neurocognitive Technologies NRC Kurchatov Institute Moscow Russia MEG Center Moscow State University of Psychology and Education Moscow Russia;

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  • 正文语种 eng
  • 中图分类
  • 关键词

    brain-computer interface; gaze interaction; E-wave; contingent negative variation; stimulus preceding negativity;

    机译:脑电脑界面;凝视互动;e-wave;或有负面变异;消极性前后的刺激;

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