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Eye Movement Analysis for Activity Recognition Using Electrooculography

This dataset was recorded to investigate the problem of recognising common office activities from eye movements. The experimental scenario involved five office-based activities – copying a text, reading a printed paper, taking handwritten notes, watching a video, and browsing the Web – and periods during which participants took a rest (the NULL class).

The dataset has the following characteristics:

* ~8 hours of eye movement data recorded using a wearable Electrooculography (EOG) system
* 8 participants (2 female, 6 male), aged between 23 and 31 years
* 2 experimental runs for each participant, each run involving them in a sequence of five different, randomly ordered office activities and a period of rest
* separate horizontal and vertical EOG channels, joint sampling frequency of 128Hz
* fully ground truth annotated (5 activity classes plus NULL)

Download: Please download the full dataset here (20.9 Mb).

Contact: Andreas Bulling,

The data is only to be used for non-commercial scientific purposes. If you use this dataset in a scientific publication, please cite the following paper:

  1. Eye Movement Analysis for Activity Recognition Using Electrooculography

    Eye Movement Analysis for Activity Recognition Using Electrooculography

    Andreas Bulling, Jamie A. Ward, Hans Gellersen, Gerhard Tröster

    IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 33(4), pp. 741-753, 2011.

    Abstract Links BibTeX Project

  1. Eye Movement Analysis for Activity Recognition

    Eye Movement Analysis for Activity Recognition

    Andreas Bulling, Jamie A. Ward, Hans Gellersen, Gerhard Tröster

    Proc. ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp), pp. 41-50, 2009.

    Abstract Links BibTeX Project