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    Estimation of Glance from EEG using cursor control

    Access Status
    Fulltext not available
    Authors
    Tan, Tele
    Hakenberg, Jan
    Guan, C.
    Date
    2013
    Type
    Conference Paper
    
    Metadata
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    Citation
    Tan, Tele and Hakenberg, Jan Philipp and Guan, Cuntai. 2013. Estimation of Glance from EEG using cursor control, in 35th Annual International conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Jul 3-7 2013, pp. 2919-2923. Osaka, Japan: IEEE.
    Source Title
    35th Annual International conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
    Source Conference
    35th Annual International conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
    DOI
    10.1109/EMBC.2013.6610151
    URI
    http://hdl.handle.net/20.500.11937/47816
    Collection
    • Curtin Research Publications
    Abstract

    The variations in the electrooculogram (EOG) caused by eye motion are roughly proportional to the instantaneous horizontal and vertical glance angle. This linear correlation is exploited in systems using EOG to control software, and hardware such as artificial limbs, or wheelchairs. In these approaches, the drift in the electronics is commonly compensated by applying a high-pass filter. Consequently, the remaining EOG signal contains only blinks and rapid eye movement. However, repeating these eye gestures voluntarily is exhausting. This paper presents an algorithm that estimates the instantaneous glance of a subject from EEG signals. The subject is seated in front of a computer screen to control an application by glance. Because the visual field of interest, in this setting, is the limited area of the monitor, we can compensate the error in the glance estimate by detecting outliers. Because no high-pass filter is applied to the data, the user controls the applications by eye glance, which is comfortable and can be performed over extended periods of time. The numerical evaluation of the experiments with 12 volunteers, and video recordings of EOG controlled applications demonstrate the accuracy of our algorithm.

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