Eye Movement Recognition Using Support Vector Machine
DOI:
https://doi.org/10.32792/jeps.v12i2.217Keywords:
EOG, Eye Movement and SVMAbstract
People with disabilities suffer from inability to communicate with their surroundings, so Human-
Computer Interaction (HCI) technologies are used to have a means of communication for people with
disabilities with their surroundings. HCI is an emerging technology in the disciplines of Artificial
Intelligence and Biomedical Engineering. To power an external device, HCI technology uses several
basic signals such as ECG, EMG, and EEG. Electrooculography (EOG) is a technique for measuring the
potential difference between the cornea and the retina located between the front and back of the human
eye, and the main application of EOG is to determine the directions of different eye movements. This
study aims to assess eye movement for communication by persons with disabilities using
electrocardiogram (EOG) data. In this study, the Supporting Vector Machine (SVM) classification
technique was used and two types of features (statistical and time domain features) were used.
Classification accuracy was 90.7% and 93.9% when using SVM with statistical domain and time domain
features, respectively
References
F. Cincotti et al., “Non-invasive brain–computer interface system: towards its application as
assistive technology,” Brain Res. Bull., vol. 75, no. 6, pp. 796–803, 2008.
R. Barea, L. Boquete, M. Mazo, and E. López, “System for assisted mobility using eye movements
based on electrooculography,” IEEE Trans. Neural Syst. Rehabil. Eng., vol. 10, no. 4, pp. 209–
, Dec. 2002, doi: 10.1109/TNSRE.2002.806829.
J. Keegan, E. Burke, J. Condron, and E. Coyle, “Improving electrooculogram-based computer
mouse systems: The accelerometer trigger,” Bioeng. Irel., vol. 201, no. 1, 2011.
R. Barea, L. Boquete, M. Mazo, and E. López, “Wheelchair guidance strategies using EOG,” J.
Intell. Robot. Syst., vol. 34, no. 3, pp. 279–299, 2002.
T. Wissel and R. Palaniappan, “Considerations on strategies to improve EOG signal analysis,” Int.
J. Artif. Life Res., vol. 2, no. 3, pp. 6–21, 2011.
G. Teng, Y. He, H. Zhao, D. Liu, J. Xiao, and S. Ramkumar, “Design and Development of Human
Computer Interface Using Electrooculogram With Deep Learning,” Artif. Intell. Med., vol. 102, p.
, 2020, doi: 10.1016/j.artmed.2019.101765.
R. Barea, L. Boquete, J. M. Rodriguez-Ascariz, S. Ortega, and E. López, “Sensory system for
implementing a human—computer interface based on electrooculography,” Sensors, vol. 11, no. 1,
pp. 310–328, 2010.
N. Itakura and K. Sakamoto, “A new method for calculating eye movement displacement from AC
coupled electro-oculographic signals in head mounted eye–gaze input interfaces,” Biomed. Signal
Process. Control, vol. 5, no. 2, pp. 142–146, 2010.
T. Gandhi, M. Trikha, J. Santosh, and S. Anand, “VHDL based electro-oculogram signal
classification,” in 2007 15th International Conference on Advanced Computing and
Communications, 2007, pp. 153–158.
A. Banerjee, M. Pal, S. Datta, D. N. Tibarewala, and A. Konar, “Eye movement sequence analysis
using electrooculogram to assist autistic children,” Biomed. Signal Process. Control, vol. 14, pp.
–140, 2014.
F. E. Samann and M. S. Hadi, “Human to Television Interface for Disabled People Based on
EOG,” J. Duhok Univ., vol. 21, no. 1, pp. 54–64, 2018.
P. Majaranta and A. Bulling, “Eye tracking and eye-based human–computer interaction,” in
Advances in physiological computing, Springer, 2014, pp. 39–65.
R. Barea, L. Boquete, S. Ortega, E. López, and J. M. Rodríguez-Ascariz, “EOG-based eye
movements codification for human computer interaction,” Expert Syst. Appl., vol. 39, no. 3, pp.
–2683, 2012.
A. U. Kabir, F. Bin Shahin, and M. Kafiul Islam, “Design and Implementation of an EOG-based
Mouse Cursor Control for Application in Human-Computer Interaction,” J. Phys. Conf. Ser., vol.
, no. 1, 2020, doi: 10.1088/1742-6596/1487/1/012043.
T. Ravichandran, N. Kamel, A. A. Al-Ezzi, K. Alsaih, and N. Yahya, “Electrooculography-based
Eye Movement Classification using Deep Learning Models,” Proc. - 2020 IEEE EMBS Conf
Biomed. Eng. Sci. IECBES 2020, pp. 57–61, 2021, doi: 10.1109/IECBES48179.2021.9398730.
https://www.um.edu.mt/cbc/ourprojects/EOG/EOGdataset.
L. J. Qi and N. Alias, “Comparison of ANN and SVM for classification of eye movements in EOG
signals,” J. Phys. Conf. Ser., vol. 971, no. 1, 2018, doi: 10.1088/1742-6596/971/1/012012.
S. Roy, A. De, and N. Panigrahi, “Saccade and Fix detection from EOG signal,” Proc. - 2019 IEEE
Int. Symp. Smart Electron. Syst. iSES 2019, pp. 406–408, 2019, doi:
1109/iSES47678.2019.00099.
R. Zebari, A. Abdulazeez, D. Zeebaree, D. Zebari, and J. Saeed, “A Comprehensive Review of
Dimensionality Reduction Techniques for Feature Selection and Feature Extraction,” J. Appl. Sci.
Technol. Trends, vol. 1, no. 2, pp. 56–70, 2020, doi: 10.38094/jastt1224.
S. Aungsakul, A. Phinyomark, P. Phukpattaranont, and C. Limsakul, “Evaluating feature extraction
methods of electrooculography (EOG) signal for human-computer interface,” Procedia Eng., vol.
, no. January, pp. 246–252, 2012, doi: 10.1016/j.proeng.2012.01.1264.
Y. LeCun, K. Kavukcuoglu, and C. Farabet, “Circuits and systems (ISCAS),” in Proceedings of
IEEE International Symposium on, 2010, pp. 253–256.
M. M. Hasan, C. N. Watling, and G. S. Larue, “Physiological signal-based drowsiness detection
using machine learning: Singular and hybrid signal approaches,” J. Safety Res., vol. 80, pp. 215–
, 2022, doi: 10.1016/j.jsr.2021.12.001.
Downloads
Published
Issue
Section
License
The Authors understand that, the copyright of the articles shall be assigned to Journal of education for Pure Science (JEPS), University of Thi-Qar as publisher of the journal.
Copyright encompasses exclusive rights to reproduce and deliver the article in all form and media, including reprints, photographs, microfilms and any other similar reproductions, as well as translations. The reproduction of any part of this journal, its storage in databases and its transmission by any form or media, such as electronic, electrostatic and mechanical copies, photocopies, recordings, magnetic media, etc. , will be allowed only with a written permission from Journal of education for Pure Science (JEPS), University of Thi-Qar.
Journal of education for Pure Science (JEPS), University of Thi-Qar, the Editors and the Advisory International Editorial Board make every effort to ensure that no wrong or misleading data, opinions or statements be published in the journal. In any way, the contents of the articles and advertisements published in the Journal of education for Pure Science (JEPS), University of Thi-Qar are sole and exclusive responsibility of their respective authors and advertisers.