# One step closer to EEG based eye tracking

arXiv: https://arxiv.org/abs/2303.06039 · HTML: https://mlsanity.com/paper/2303.06039/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 13 of its 55 references that are in the map.
- First posted on arXiv 3 Mar 2023.

## Builds on (most cited first, 13 of 13)

- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale](https://mlsanity.com/paper/2010.11929/) (2020)
- [PyTorch: An Imperative Style, High-Performance Deep Learning Library](https://mlsanity.com/paper/1912.01703/) (2019)
- [A ConvNet for the 2020s](https://mlsanity.com/paper/2201.03545/) (2022)
- [Appearance-Based Gaze Estimation in the Wild](https://mlsanity.com/paper/1504.02863/) (2015)
- [Pupil: An Open Source Platform for Pervasive Eye Tracking and Mobile Gaze-based Interaction](https://mlsanity.com/paper/1405.0006/) (2014)
- [EEGEyeNet: a Simultaneous Electroencephalography and Eye-tracking Dataset and Benchmark for Eye Movement Prediction](https://mlsanity.com/paper/2111.05100/) (2021)
- [A High-Level Description and Performance Evaluation of Pupil Invisible](https://mlsanity.com/paper/2009.00508/) (2020)
- [Fast camera focus estimation for gaze-based focus control](https://mlsanity.com/paper/1711.03306/) (2017)
- [Pistol: Pupil Invisible Supportive Tool to extract Pupil, Iris, Eye Opening, Eye Movements, Pupil and Iris Gaze Vector, and 2D as well as 3D Gaze](https://mlsanity.com/paper/2201.06799/) (2022)
- [Spatial Filtering for EEG-Based Regression Problems in Brain-Computer Interface (BCI)](https://mlsanity.com/paper/1702.02914/) (2017)
- [An Intelligent and Low-cost Eye-tracking System for Motorized Wheelchair Control](https://mlsanity.com/paper/2005.02118/) (2020)
- [GroupGazer: A Tool to Compute the Gaze per Participant in Groups with integrated Calibration to Map the Gaze Online to a Screen or Beamer Projection](https://mlsanity.com/paper/2201.07692/) (2022)

## Built on by (most cited first, 3 of 3)

- [Consumer-grade EEG-based Eye Tracking](https://mlsanity.com/paper/2503.14322/) (2025)
- [EEG-EyeTrack: A Benchmark for Time Series and Functional Data Analysis with Open Challenges and Baselines](https://mlsanity.com/paper/2504.03760/) (2025)
- [EEGMobile: Enhancing Speed and Accuracy in EEG-Based Gaze Prediction with Advanced Mobile Architectures](https://mlsanity.com/paper/2408.03449/) (2024)

## Abstract (arXiv)

In this paper, we present two approaches and algorithms that adapt areas of interest We present a new deep neural network (DNN) that can be used to directly determine gaze position using EEG data. EEG-based eye tracking is a new and difficult research topic in the field of eye tracking, but it provides an alternative to image-based eye tracking with an input data set comparable to conventional image processing. The presented DNN exploits spatial dependencies of the EEG signal and uses convolutions similar to spatial filtering, which is used for preprocessing EEG signals. By this, we improve the direct gaze determination from the EEG signal compared to the state of the art by 3.5 cm MAE (Mean absolute error), but unfortunately still do not achieve a directly applicable system, since the inaccuracy is still significantly higher compared to image-based eye trackers. Link: https://es-cloud.cs.uni-tuebingen.de/d/8e2ab8c3fdd444e1a135/?p=%2FEEGGaze&mode=list