Skip to main content
SpringerLink
Log in

Implementation of the “Labyrinth” Game by Brain –Computer Interface Tools

  • Informatics
  • Published:
Computational Mathematics and Modeling Aims and scope Submit manuscript

The article describes an implementation of the “Labyrinth” game using pattern recognition in EEG signals. The game is controlled by eye blinking. Unlike other techniques utilized for implementation of man – computer interaction by BCI methods, eye blinking may be recognized with high reliability. The article also proposes methods for the construction of the feature space for eye blinking recognition and compares these methods with the analysis of signal spectral characteristics used in most BCI eye blinking studies.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. R. Singla, B. Chambayil, A. Khosla, and J. Santosh, “Comparison of SVM and ANN for classification of eye events in EEG,” J. Biomed. Science and Engineering, 4, 62–69 (2011).

    Article  Google Scholar 

  2. S. Rihana, P. Damien, and T. Moujaess, “EEG-eye blink detection system for brain-computer interface,” Converging Clinical and Engineerign Research on Neurorehabilitation Biosystems and Biorobotics, 1, 603–608 (2013).

    Article  Google Scholar 

  3. J. B. Ochoa, EEG Signal Classification for Brain Computer Interface Applications (2002).

  4. K. V. Vorontsov, Mathematical Precedent-Based Learning Methods (Machine Learning Methods) [http://www.machinelearning.ru/wiki/images/6/6d/Voron-ML-1.pdf].

  5. A. Binke, A. Lenhardt, and H. Ritter, “The MindGame: A P300-based brain-computer interface game,” Neural Networks, 22, 1329–1333 (2009).

    Article  Google Scholar 

  6. D. Knuth, G. Graham, and O. Patashnik, Concrete Mathematics: A Foundation of Computer Science [Russian translation], Mir, Moscow (1998).

    Google Scholar 

  7. http://www.csie.ntu.eu.tw/

  8. http://www.csie.ntu.eu.tw/

  9. L. Breiman, “Random forests,” Machine Learning, 45, No. 1, 5–32 (2001).

    Article  MATH  Google Scholar 

  10. Y. Freund, R. Schapire, and N. Abe, “A short introduction to boosting,” J. Japanese Soc. Artif. Intelligence, 14, 771–780, 1612 (1999).

Download references

Author information

Authors and Affiliations

  1. Faculty of Computational Mathematics and Cybernetics, Moscow State University, Moscow, Russia

    D. A. Podoprikhin

Authors
  1. D. A. Podoprikhin
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to D. A. Podoprikhin.

Additional information

Translated from Prikladnaya Matematika i Informatika, No. 47, 2014, pp. 107–121.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Podoprikhin, D.A. Implementation of the “Labyrinth” Game by Brain –Computer Interface Tools. Comput Math Model 26, 555–565 (2015). https://doi.org/10.1007/s10598-015-9292-z

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10598-015-9292-z

Keywords

Search

Navigation