Preview

Bulletin of Siberian Medicine

Advanced search

EXPERIMENTAL AND THEORETICAL FOUNDATIONS AND PRACTICAL IMPLEMENTATION OF TECHNOLOGY BRAIN-COMPUTER INTERFACE

https://doi.org/10.20538/1682-0363-2013-2-21-29

Abstract

Technology brain-computer interface (BCI) allow saperson to learn how to control external devices via thevoluntary regulation of own EEG directly from the brain without the involvement in the process of nerves and muscles. At the beginning the main goal of BCI was to replace or restore motor function to people disabled by neuromuscular disorders. Currently, the task of designing the BCI increased significantly, more capturing different aspects of life a healthy person. This article discusses the theoretical, experimental and technological base of BCI development and systematized critical fields of real implementation of these technologies.

About the Authors

A. Ya. Kaplan
Moscow State University named after M.V. Lomonosov, Moscow
Russian Federation
Kaplan Alexander Ya. - Laboratory of Neurophysiology and Neurocomputing Interfaces Faculty of Biology


A. G. Kochetova
Moscow State University named after M.V. Lomonosov, Moscow
Russian Federation
Kochetova Arina G.- Laboratory of Neurophysiology and Neurocomputing Interfaces Faculty of Biology


S. L. Shishkin
Research Center Kurchatov Institute, NBIKS Center, Moscow
Russian Federation
Shishkin Sergey L.


I. A. Basyul
Institute of Psychology, Russian Academy of Sciences, Moscow
Russian Federation
Basyul Ivan A.- a graduate student Postgraduate


I. P. Ganin
Moscow State University named after M.V. Lomonosov, Moscow
Russian Federation
Ganin Ilya P.- a graduate student of Biological Faculty


A. N. Vasilev
Moscow State University named after M.V. Lomonosov, Moscow
Russian Federation
Vasilyev Anatoly N. - a graduate student of Biological Faculty


S. P. Liburkina
Moscow State University named after M.V. Lomonosov, Moscow
Russian Federation
Liburkina Sofia P. - a graduate student of Biological Faculty


References

1. Bazanova O.M., Shtark M.B. Human Physiology, 2007, vol. 33 (4), pp. 24–32 (in Russian).

2. Dzhafarova O.A., Donskaya O.G., Zubkov A.A., Shtark M.B. Biofeedback-4. Theory and practice. Novosibirsk, 2002. Pp. 86–96 (in Russian).

3. Ganin I.P., Shishkin S.L., Kochetova A.G., Kaplan A.Ya. Human Physiology, 2012, vol. 38, no 2, pp. 5–13 (in Russian).

4. Kaplan A.Ya, Logachev S.A. The game and the way to fight it: patent for invention № 2406554. (14.07.2009) (in Russian).

5. Kochetova A.G., Kaplan A.Ya. How far should we go in augmented humans: ethical aspects of BCI. Materials of the2nd international Symposium «Interface „brain-computer“». Rostov/D: South federal University Publ., 2012, vol. 2,pp. 61–64 (in Russian).

6. Shtark M.B. Bulletin of Siberian Medicine, 2010, vol. 9, no 1, pp. 5–6(in Russian). tice. Novosibirsk, 1998. Pp. 130–141 (in Russian).

7. Allison1 B.Z., R Leeb R., Brunner C. et al. Toward smarter BCIs: extending BCIs through hybridization and intelligentcontrol. J. Neural. Eng., 2012, vol. 9, pp. 1–7.

8. Bayliss J.D., Ballard D.H. A virtual reality testbed for braincomputer interface research. IEEE Trans. Rehabil. Eng., 2000, vol. 8, pp. 188–190.

9. Bensch M. et al. Nessi: an EEG controlled web browser for severely paralyzed patients. Comput. Intell. Neurosci., 2007. V. 5. Article ID 71863.

10. Birbaumer N., Murguialday A.R., Cohen L. Brain-computer interface in paralysis. Curr. Opin. Neurol., 2008, vol. 21, pp. 634–638.

11. Donchin E., Spencer K.M., Wijesinghe R. The mental prosthesis: assessing the speed of a P300-based brain-computer interface. IEEE Trans Rehabil. Eng., 2000, vol. 8 (2), pp. 174–179.

12. Farwell L.A., Donchin E. Talking off the top of your head: toward a mental prosthesis utilizingevent-relatedbrain potentials. Electroenceph. Clin. Neurophysiol., 1988, vol. 70, pp. 510–23.

13. Jeannerod M., Frak V. Mental imaging of motor activity in humans Current Opinion. Neurobiology, 1999, vol. 9 (6), pp. 735–739.

14. Hinterberger T., Veit R., Wilhelm B., Weiskopf N., Vatine J.J., Birbaumer N. Neuronal mechanisms underlying control of a brain-computer interface. Eur. J. Neurosci., 2005, vol. 21 (11), pp. 3169–3181.

15. Höller Y., Bergmann J., Kronbichler M., et al. E. Real movement vs. motor imagery in healthy subjects. Int. J. Psychophysiol. 2012. pp. S0167–8760.

16. Kamiya J. Conscious control of brain wave. Psychol. Today, 1968, vol. 1, pp. 56–60.

17. Kaplan A.Ya., Lim J.J., Jin K.S. et al. Unconscious operant conditioning in the paradigm of brain-computer interface based on color perception. Intern. J. Neuroscience, 2005, vol. 115, pp. 781–802.

18. Kaplan A., Shishkin S., Ganin I., Basul I. The prospects of the P300-based brain-computer interface in game control. IEEE Transactions on Computational Intelligence and AI in Games, 2013 (in press).

19. Kelly S.P., Lalor E.C., Finucane C., McDarby G., Reilly R.B. Visual spatial attention control in an independent brain– computer interface. IEEE Trans. Biomed. Eng., 2005, vol. 52 (9), pp. 1588–1596.

20. Krusienski D., Sellers E., Cabestaing F. et al. A comparison of classification techniques for the P300 speller. J. of Neural Engineering, 2006, vol. 6, pp. 299–305,

21. Krusienski D.J., Schalk G., McFarland D.J., Wolpaw J.R. A mu-rhythm matched filter for continuous control of a braincomputer interface. IEEE Trans. Biomed. Eng., 2007, vol. 54 (2), pp. 273–280.

22. Leeb R., Gubler M., Tavella M., Miller H., Del Millan J.R. On the road to a neuroprosthetic hand: a novel hand grasp orthosis based on functional electrical stimulation. Conf. Proc. IEEE Eng. Med. Biol. Society, 2010. P. 146–149.

23. Leeb R., Sagha H., Chavarriaga R., Del Millan J.R. A hybrid brain-computer interface based on the fusion of electroencephalographic and electromyographic activities. J. Neural Eng., 2011, vol. 8, pp. 1–5.

24. Lin Z., Zhang C., Wu W., Gao X. Frequency recognition based on canonical correlation analysis for SSVEP-based BCIs. IEEE Trans. Biomed. Eng., 2006, vol. 53 (12), pp. 2610–2614.

25. Long J., Li Y., Wang H., Yu T., Pan J., Li F.. Ahybrid brain computer interface to control the direction and speed of a simulated or real wheelchair. IEEE Trans. Neural. Syst. Rehabil. Eng., 2012, vol. 20 (5), pp. 720–729.

26. Lopez Miguel A., Pelayo Francisco, Madrid Eduardo, Prieto Alberto. Statistical characterization of steady-state visual evoked potentials and their use in brain-computer interfaces. Neural. Process. Lett., 2009, vol. 29, pp. 179–187.

27. Müller-Putz G.R. еt al. Brain-computer interfaces for control of neuroprostheses. Biomed. Tech., 2006, vol. 51, pp. 57–63.

28. Müller-Putz G.R., Breitwieser C., Tangermann M. et al. Tobi hybrid BCI: principle of a new assistive method. International Journal of Bioelectromagnetism, 2011, vol. 13, no. 3, pp. 144–145.

29. Nicolas-Alonso L.F., Gomez-Gil J. Brain computer interfaces, a review. Sensors (Basel), 2012, vol. 12 (2), pp. 1211–1279.

30. Pfurtscheller G. et al. Thought-control of functional electrical stimulation to restore hand grasp in a patient with tetraplegia. Neurosci. Lett., 2003, vol. 351, pp. 33–36.

31. Rak R.R.J., Kołodziej M., Majkowski A. Brain-computer interface as measurement and control system: the review paper. Metrol. Meas. Syst., 2012, vol. 19, pp. 427–444.

32. Wang Y., Jung T-P. A Collaborative brain-computer interface for improving human performance. PLoS ONE, 2011, vol. 6 (5), pp. 1–4.

33. Salvaris M., Cinel C., Citi L., Poli R. Novel protocols for P300-based brain-computer interfaces. IEEE Trans. Neural. Syst. Rehabil. Eng., 2012, vol. 20 (1), pp. 8–17.

34. Sellers E.W., Vaughan T.M., Wolpaw J.R. A brain-computer interface for long-term independent home use. Amyotroph. LateralScler., 2010, vol. 11, pp. 455.

35. Silvoni S. et al. P300-based brain-computer interface communication: evaluation and follow-up in amyotrophic laterals clerosis. Front. Neurosci., 2009, vol. 3, pp. 60.

36. Shishkin S.L., Ganin I.P., Kaplan A.Y. Event-related potentials in a moving matrix modification of the P300 braincomputer interface paradigm. Neuroscience Letters, 2011, vol. 496 (2), P. 95–99.

37. Vidal J.J. Toward direct brain-computer communication. Annu. ReV. Biophys. Bioeng., 1973, vol. 2, pp. 157–180.

38. Vlek R.J., Steines D., Szibbo D., Kübler A., Schneider M.J., Haselager P., Nijboer F. Ethicalissues in brain-computer interface research, development, and dissemination. J. Neurol. Phys. Ther., 2012, vol. 36 (2), pp. 94–99

39. Wang D., Miao D., Blohm G. Multi-class motor imagery EEG decoding for brain-computer interfaces. Front Neurosci., 2012, vol. 6, pp. 151.

40. Williamson J. et al. Designing for uncertain, asymmetric control: interaction design for brain-computer interfaces. Int. J. Hum. Comput. Stud., 2009, vol. 67, pp. 827–841.

41. Wills S., and MacKay D. DASHER – an efficient writing system for brain-computer interfaces?. IEEE Trans. Neural Syst. Rehabil. Eng., 2006, vol. 14, pp. 244–246.

42. Wolpaw J., Birbaumer N., McFarland D., Pfurtscheller G., Vaughan T. Brain-computer interfaces for communication and control. Clin. Neurophysiol., 2002, vol. 113, pp. 767– 791.

43. Wolpaw J.R. Brain-computer interfaces as new brain output pathways. The Journal of Physiology, 2007, vol. 579 (3), pp. 613–619.


Review

For citations:


Kaplan A.Ya., Kochetova A.G., Shishkin S.L., Basyul I.A., Ganin I.P., Vasilev A.N., Liburkina S.P. EXPERIMENTAL AND THEORETICAL FOUNDATIONS AND PRACTICAL IMPLEMENTATION OF TECHNOLOGY BRAIN-COMPUTER INTERFACE. Bulletin of Siberian Medicine. 2013;12(2):21-29. (In Russ.) https://doi.org/10.20538/1682-0363-2013-2-21-29

Views: 1031


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


ISSN 1682-0363 (Print)
ISSN 1819-3684 (Online)