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Real-time estimation system of the gaze position based on an electrooculogram

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Abstract

This article describes an online eye-tracking method based on an electrooculogram (EOG) to estimate gaze position. The objective is to use a biomedical signal EOG as the input of a human-machine interface for both disabled and healthy people. In this study, features of horizontal and vertical EOG signals were extracted to estimate the gaze position. Compensation for time-shift and nonlinearity were applied to improve the performance of the estimation. The estimated locus of the moving eye was compared with the locus of the target, and the deviation was about 3 cm. The results can be applied in some raw tracking fields, such as online communication, EOG-based pointers, and so on.

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Author information

Authors and Affiliations

  1. Department of Automation, East China University of Science and Technology, 130 St. Meilong, Shanghai, China

    Xiu Zhang & Xingyu Wang

  2. Department of Electrical and Electronic Engineering, Saga University, Saga, Japan

    Takenao Sugi

  3. Research Institute of Systems Control, Institute for Advanced Research and Education, Saga University, Saga, Japan

    Xiu Zhang & Masatoshi Nakamura

Authors
  1. Xiu Zhang
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  2. Takenao Sugi
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  3. Xingyu Wang
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  4. Masatoshi Nakamura
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Corresponding author

Correspondence to Xiu Zhang.

Additional information

This work was presented in part at the 14th International Symposium on Artificial Life and Robotics, Oita, Japan, February 5–7, 2009

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Zhang, X., Sugi, T., Wang, X. et al. Real-time estimation system of the gaze position based on an electrooculogram. Artif Life Robotics 14, 182–185 (2009). https://doi.org/10.1007/s10015-009-0649-2

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  • DOI: https://doi.org/10.1007/s10015-009-0649-2

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