September 2021
Volume 21, Issue 9
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2021
Using electrooculography to track closed-eye movements.
Author Affiliations & Notes
  • Raymond R. MacNeil
    The University of British Columbia
  • P.D.S.H. Gunawardane
    The University of British Columbia
  • Jamie Dunkle
    The University of British Columbia
  • Leo Zhao
    The University of British Columbia
  • Mu Chiao
    The University of British Columbia
  • Clarence W. de Silva
    The University of British Columbia
  • James T. Enns
    The University of British Columbia
  • Footnotes
    Acknowledgements  We acknowledge the support of the Natural Sciences and Engineering Research Council of Canada (NSERC). RRM: Canadian Graduate Scholarship-Master’s 6563 and Postgraduate Scholarship-Doctoral 547166-2020; CWdS/MC: Strategic Partnership Grants Project 493908; JTE: Discovery Grant.
Journal of Vision September 2021, Vol.21, 1898. doi:https://doi.org/10.1167/jov.21.9.1898
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      Raymond R. MacNeil, P.D.S.H. Gunawardane, Jamie Dunkle, Leo Zhao, Mu Chiao, Clarence W. de Silva, James T. Enns; Using electrooculography to track closed-eye movements.. Journal of Vision 2021;21(9):1898. https://doi.org/10.1167/jov.21.9.1898.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

There are several areas in the study of visual cognition—including memory, imagery, and human-machine interaction—where researchers are interested in how the eyes move behind closed eyelids. However, reliably and affordably measuring closed-eye movements has proven elusive. Electrooculography (EOG) offers a low-cost solution to monitoring closed-eye gaze position, but it is not without its challenges. To determine the direction and amplitude of eye movements, the electrical potentials measured by EOG somehow must be calibrated with the angular displacement of the eye. EOG is also susceptible to noise arising from various sources, such as electromyographic activity and electrode impedance. Here we describe a method for estimating a corrected EOG signal by calibrating it with an industry-standard, pupil-corneal reflection (PCR) eye tracker. First, data were collected while simultaneously using both eye-tracking techniques as participants performed a simple horizontal saccade task with their eyes open under conditions of normal illumination and complete darkness. The EOG signal, when using only a standard calibration procedure, was less precise than that of PCR and tended to overestimate saccadic amplitude. We applied robust regression methods to the EOG and PCR data recorded in normal illumination to estimate a calibration factor to adjust the EOG signal acquired in darkness. This adjustment yielded an EOG-based measure of saccade end-points that was more comparable—in both accuracy and precision—to that obtained from the PCR data. Having validated this calibration procedure, we applied it to compute an adjusted EOG measure of saccadic amplitude in another condition where participants’ eyes were closed. This adjustment likely improved our measurement of how accurately participants were able to execute closed-eye movements to remembered target locations. We propose that the refinement and application of this methodology can advance research under conditions where researchers would like to measure the kinematics of closed-eye movements.

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