Neural Networks for Eye Detection

Authors

  • Ron Ye
  • Jing Ma
  • Yu-Jen Chen

DOI:

https://doi.org/10.53896/ijc.v5i1.66

Keywords:

Performance evaluation, Deep learning, Visualization

Abstract

In this study a Deep Learning (DL) based-Brain-Computer Interface (BCI) system able to automatically detect and decode voluntary eye blinks from the analysis of electroen-cephalographic (EEG) signals.

References

J. R. Wolpaw, N. Birbaumer, W. J. Heetderks, D. J. McFarland, P. H. Peckham, G. Schalk, E. Donchin, L. A. Quatrano, C. J. Robinson, T. M. Vaughan et al., "Brain-computer interface technology: a review of the first international meeting", IEEE transactions on rehabilitation engineering, vol. 8, no. 2, pp. 164-173, 2000.

P. L. Nunez, R. Srinivasan et al., Electric fields of the brain: the neurophysics of EEG, USA:Oxford University Press, 2006.

D. Denney and C. Denney, "The eye blink electro-oculogram", British journal of ophthalmology, vol. 68, no. 4, pp. 225-228, 1984.

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Published

2012-05-14

Issue

Vol. 5 No. 1 (2012)

Section

Articles

License

Copyright (c) 2012 International Journal of Computer (IJC)

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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How to Cite

Ye, R., Ma, J., & Chen, Y.-J. (2012). Neural Networks for Eye Detection. International Journal of Computer (IJC), 5(1), 1-30. https://doi.org/10.53896/ijc.v5i1.66