Intervention-free selection using EEG and eye tracking

In this paper, we show how recordings of gaze movements (via eye tracking) and brain activity (via electroencephalography) can be combined to provide an interface for implicit selection in a graphical user interface. This implicit selection works completely without manual intervention by the user. In our approach, we formulate implicit selection as a classification problem, describe the employed features and classification setup and introduce our experimental setup for collecting evaluation data. With a fully online-capable setup, we can achieve an F_0.2-score of up to 0.74 for temporal localization and a spatial localization accuracy of more than 0.95.