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Computational Intelligence and Neuroscience
Volume 2016, Article ID 7354082, 10 pages
http://dx.doi.org/10.1155/2016/7354082
Research Article

EOG-sEMG Human Interface for Communication

1Department of Environmental Robotics, University of Miyazaki, Miyazaki 889-2192, Japan
2Organization for Promotion of “Center of Community” Program, University of Miyazaki, Miyazaki 889-2192, Japan
3Interdisciplinary Graduate School of Agriculture and Engineering, University of Miyazaki, Miyazaki 889-2192, Japan
4Department of Electrical and Systems Engineering, University of Miyazaki, Miyazaki 889-2192, Japan

Received 26 November 2015; Revised 26 April 2016; Accepted 17 May 2016

Academic Editor: Hasan Ayaz

Copyright © 2016 Hiroki Tamura et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. S. Venkataramanan, P. Prabhat, S. R. Choudhury, H. B. Nemade, and J. S. Sahambi, “Biomedical instrumentation based on Electrooculogram (EOG) signal processing and application to a hospital alarm system,” in Proceedings of the Proceedings of International Conference on Intelligent Sensing and Information Processing (ICISIP '05), pp. 535–540, IEEE, Chennai, India, January 2005. View at Publisher · View at Google Scholar · View at Scopus
  2. R. Barea, L. Boquete, M. Mazo, and E. López, “System for assisted mobility using eye movements based on electrooculography,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 10, no. 4, pp. 209–218, 2002. View at Publisher · View at Google Scholar · View at Scopus
  3. K. Tomohiro, M. Tadashi, K. Tohru, and S. Tsugutake, Biomechanism Library Practical Usage of Surface Electromyogram, Tokyo Denki University Press, Tokyo, Japan, 2006.
  4. A. Assareh, S. Konjkav, A. Fallah, and S. M. P. Firoozabadi, “A new approach for navigating automatic wheelchairs using EMG signals feature extraction and classification with an adaptive controller,” in Proceedings of the 12th International Conference on Biomedical Engineering, Singapore, December 2005.
  5. H. Tamura, T. Murata, Y. Yamashita, K. Tanno, and Y. Fuse, “Development of the electric wheelchair hands-free semi-automatic control system using the surface-electromyogram of facial muscles,” Artificial Life and Robotics, vol. 17, no. 2, pp. 300–305, 2012. View at Publisher · View at Google Scholar · View at Scopus
  6. H. Tamura, T. Manabe, T. Goto, Y. Yamashita, and K. Tanno, “A study of the electric wheelchair hands-free safety control system using the surface-electromygram of facial muscles,” in Intelligent Robotics and Applications: Third International Conference, ICIRA 2010, Shanghai, China, November 10–12, 2010. Proceedings, Part II, vol. 6425 of Lecture Notes in Computer Science, pp. 97–104, Springer, Berlin, Germany, 2010. View at Google Scholar
  7. C. K. Young and M. Sasaki, “Mobile robot control by neural network EOG gesture recognition,” in Proceedings of the 8th International Conference on Neural Information Processing, vol. 1, pp. 322–328, 2001.
  8. H. Tamura, M. Miyashita, K. Tanno, and Y. Fuse, “Mouse cursor control system using electrooculogram signals,” in Proceedings of the World Automation Congress, IFMIP 239, pp. 1–6, September 2010. View at Scopus
  9. H. Tamura, M. Yan, M. Miyashita, T. Manabe, K. Tanno, and Y. Fuse, “Development of mouse cursor control system using DC and AC elements of electrooculogram signals and its applications,” International Journal of Intelligent Computing in Medical Sciences and Image Processing, vol. 5, no. 1, pp. 3–15, 2013. View at Publisher · View at Google Scholar · View at Scopus
  10. M. Yan, H. Tamura, and K. Tanno, “Gaze estimation using electrooculogram signals and its mathematical modeling,” in Proceedings of the CDROM, IEEE 43rd International Symposium on Multiple-Valued Logic, pp. 18–22, Toyama , Japan, May 2013.
  11. A. Schlögl, C. Keinrath, D. Zimmermann, R. Scherer, R. Leeb, and G. Pfurtscheller, “A fully automated correction method of EOG artifacts in EEG recordings,” Clinical Neurophysiology, vol. 118, no. 1, pp. 98–104, 2007. View at Publisher · View at Google Scholar · View at Scopus
  12. H. S. Dhillion, R. Singla, N. S. Rekhi, and R. Jha, “EOD and EMG based virtual keyboard: a brain-computer interface,” in Proceedings of the 2nd IEEE International Conference on Computer Science and Information Technology, pp. 259–262, 2009.
  13. Tobii, http://www.tobii.com.
  14. J. G. Thomas, “The dynamics of small saccadic eye movements,” Journal of Physiology, vol. 200, no. 1, pp. 109–127, 1969. View at Publisher · View at Google Scholar · View at Scopus