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Classification of Visual Attention Level During Target Gazing Using Microsaccades

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Transactions on Computational Science XXXV

Part of the book series: Lecture Notes in Computer Science ((TCOMPUTATSCIE,volume 11960))

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Abstract

In the previous researches on microsaccades, a typical and basic experimental method involves the following: a dot is displayed as a visual target in the middle or near the middle of a monitor, and eye movements of the subject are measured, and then the number of microsaccades is extracted from the measured eye movements. However, it is difficult to determine whether or not the subject is paying visual attention while gazing at the target, and the degree of visual attention paid by the subject. This paper proposes a system that uses microsaccades to classify visual attention levels during visual target gazing. In our experiment, ten subjects performed three tasks requiring different levels of visual attention. Microsaccades were measured and the number of microsaccades was extracted for each task. Statistical analysis showed that the number of microsaccades differed among the tasks. Our results suggest that visual attention level can be classified by the number of microsaccades.

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Acknowledgements

We would like to thank Dr. Takao Fukui at Tokyo Metropolitan University for comments that greatly improved the manuscript.

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Authors and Affiliations

  1. Graduate School of Systems Design, Faculty of Computer Science, Tokyo Metropolitan University, 6-6 Asahigaoka, Hino, Tokyo, 191-0065, Japan

    Soichiro Yokoo & Nobuyuki Nishiuchi

  2. Graduate School of Natural Science, Faculty of Intelligence and Informatics, Konan University, 8-9-1 Okamoto, Higashi-Nada, Kobe, Hyogo, 658-8501, Japan

    Kimihiro Yamanaka

Authors
  1. Soichiro Yokoo
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  2. Nobuyuki Nishiuchi
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  3. Kimihiro Yamanaka
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Corresponding author

Correspondence to Soichiro Yokoo .

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Editors and Affiliations

  1. University of Calgary, Calgary, AB, Canada

    Marina L. Gavrilova

  2. Sardina Systems OÜ, Tallinn, Estonia

    C. J. Kenneth Tan

  3. Bialystok University of Technology, Bialystok, Poland

    Khalid Saeed

  4. University of Calcutta, Kolkata, India

    Nabendu Chaki

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Yokoo, S., Nishiuchi, N., Yamanaka, K. (2020). Classification of Visual Attention Level During Target Gazing Using Microsaccades. In: Gavrilova, M., Tan, C., Saeed, K., Chaki, N. (eds) Transactions on Computational Science XXXV. Lecture Notes in Computer Science(), vol 11960. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-61092-3_1

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  • DOI: https://doi.org/10.1007/978-3-662-61092-3_1

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-61091-6

  • Online ISBN: 978-3-662-61092-3

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