EEG signal processing for eye tracking

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Colleges, School and Institutes

External organisations

  • Interactive Systems Engineering Research Group, University of Birmingham


Head-mounted Video-Oculography (VOG) eye tracking is visually intrusive due to a camera in the peripheral view. Electrooculography (EOG) eye tracking is socially intrusive because of face-mounted electrodes. In this work we explore Electroencephalography (EEG) eye tracking from less intrusive wireless cap scalp-based electrodes. Classification algorithms to detect eye movement and the focus of foveal attention are proposed and evaluated on data from a matched dataset of VOG and 16-channel EEG. The algorithms utilise EOG artefacts and the brain's steady state visually evoked potential (SSVEP) response while viewing flickering stimulus. We demonstrate improved performance by extracting features from source signals estimated by Independent Component Analysis (ICA) rather than the traditional band-pass preprocessed EEG channels. The work envisages eye tracking technologies that utilise non-facially intrusive EEG brain sensing via wireless dry contact scalp based electrodes.


Original languageEnglish
Title of host publicationSignal Processing Conference (EUSIPCO), 2013 Proceedings of the 22nd European
Publication statusPublished - 2014
Event22nd European Signal Processing Conference, EUSIPCO 2014 - Lisbon, United Kingdom
Duration: 1 Sep 20145 Sep 2014


Conference22nd European Signal Processing Conference, EUSIPCO 2014
CountryUnited Kingdom


  • eye tracking, ICA, SSVEP, visual attention, VOG