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Electrode Clustering and Bandpass Analysis of EEG Data for Gaze Estimation
Ard Kastrati · Martyna Plomecka · Joël Küchler · Nicolas Langer · Roger Wattenhofer

Sat Dec 03 08:20 AM -- 08:32 AM (PST) @
in Gaze meets ML »
Event URL: https://openreview.net/forum?id=We5h1Vcezei »

In this study, we validate the findings of previously published papers, showing the feasibility of an Electroencephalography (EEG) based gaze estimation. Moreover, we extend previous research by demonstrating that with only a slight drop in model performance, we can significantly reduce the number of electrodes, indicating that a high-density, expensive EEG cap is not necessary for the purposes of EEG-based eye tracking. Using data-driven approaches, we establish which electrode clusters impact gaze estimation and how the different types of EEG data preprocessing affect the models’ performance. Finally, we also inspect which recorded frequencies are most important for the defined tasks.

Keywords: EEG · eye tracking · eye movements · electrode clustering · bandpass analysis

Author Information

Ard Kastrati (ETH Zurich)
Martyna Plomecka (University of Zurich)
Joël Küchler (University of Zurich)
Nicolas Langer (University of Zurich)
Roger Wattenhofer (ETH Zurich)

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