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Eye Movements Recognition Using Electrooculography Signals

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Proceedings of the International Conference on Artificial Intelligence and Computer Vision (AICV2020) (AICV 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1153))

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Abstract

Nowadays, the number of people who suffer from severe motor disabilities is increasing remarkably. This disability gradually prevents them from moving all their limbs and they can communicate with their external environment only through the movement of their eyes. Hence, Human Computer Interfaces (HCI) have come out to provide those people with new communication way based on detecting eye movements. Eye movements are recorded by Electrooculogram (EOG). These signals are captured by placing electrodes horizontally and vertically around the eyes. In this work, the five eye movements left, right, up, down and blinking are classified by investigating both horizontal and vertical EOG signals. Statistical and geometrical features are extracted from EOG signals after applying Discrete Wavelet Transform (DWT). Six classifiers are examined in this study using both horizontal and vertical EOG features. The experimental results show the superiority of Naïve Bayes classifier.

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Author information

Authors and Affiliations

  1. Scientific Computing Department, Faculty of Computer and Information Science, FCIS, Ain Shams University, Cairo, Egypt

    Radwa Reda, Manal Tantawi, Howida Shedeed & Mohamed F. Tolba

Authors
  1. Radwa Reda
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  2. Manal Tantawi
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  3. Howida Shedeed
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  4. Mohamed F. Tolba
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Corresponding author

Correspondence to Radwa Reda .

Editor information

Editors and Affiliations

  1. Information Technology Department, Cairo University, Faculty of Computers and Information, Giza, Egypt

    Aboul-Ella Hassanien

  2. Faculty of Computers and Information, Benha University, Banha, Egypt

    Ahmad Taher Azar

  3. Faculty of Computers and Information, Suez Canal University, Ismailia, Egypt

    Tarek Gaber

  4. Departamento de Ciencias Computacionales, Universidad de Guadalajara, CUCEI, Guadajalara, Jalisco, Mexico

    Diego Oliva

  5. Faculty of Computer and Information Sciences, Ain Shams University, Cairo, Egypt

    Fahmy M. Tolba

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Reda, R., Tantawi, M., Shedeed, H., Tolba, M.F. (2020). Eye Movements Recognition Using Electrooculography Signals. In: Hassanien, AE., Azar, A., Gaber, T., Oliva, D., Tolba, F. (eds) Proceedings of the International Conference on Artificial Intelligence and Computer Vision (AICV2020). AICV 2020. Advances in Intelligent Systems and Computing, vol 1153. Springer, Cham. https://doi.org/10.1007/978-3-030-44289-7_46

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