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Chaotic Nature of Eye Movement Signal

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Intelligent Decision Technologies 2017 (IDT 2017)

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 72))

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Abstract

The eye movement analysis undertaken in many research is conducted to better understand the biology of the brain and oculomotor system functioning. The studies presented in this paper considered eye movement signal as an output of a nonlinear dynamic system and are concentrated on determining the chaotic behaviour existence. The system nature was examined during a fixation, one of key components of eye movement signal, taking its vertical velocity into account. The results were compared with those obtained in the case of the horizontal direction. This comparison showed that both variables provide the similar representation of the underlying dynamics. In both cases, the analysis revealed the chaotic nature of eye movement for the first 200 ms, just after a stimulus position change. Subsequently, the signal characteristic tended to be the convergent one, however, in some cases, depending on a part of the fixation duration the chaotic behaviour was still observable.

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Acknowledgments

The research presented in this paper was partially supported by the Silesian University of Technology Rector’s Pro-Quality Grant 02/020/RGJ17/0103.

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Authors and Affiliations

  1. Silesian University of Technology, ul. Akademicka 16, 44-100, Gliwice, Poland

    Katarzyna Harezlak & Pawel Kasprowski

Authors
  1. Katarzyna Harezlak
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  2. Pawel Kasprowski
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Corresponding author

Correspondence to Katarzyna Harezlak .

Editor information

Editors and Affiliations

  1. Maritime University , Gdynia, Poland

    Ireneusz Czarnowski

  2. Bournemouth University and KES International, Poole, Dorset, United Kingdom

    Robert J. Howlett

  3. University of Canberra, Canberra, Aust Capital Terr, Australia

    Lakhmi C. Jain

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Harezlak, K., Kasprowski, P. (2018). Chaotic Nature of Eye Movement Signal. In: Czarnowski, I., Howlett, R., Jain, L. (eds) Intelligent Decision Technologies 2017. IDT 2017. Smart Innovation, Systems and Technologies, vol 72. Springer, Cham. https://doi.org/10.1007/978-3-319-59421-7_11

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  • DOI: https://doi.org/10.1007/978-3-319-59421-7_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59420-0

  • Online ISBN: 978-3-319-59421-7

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