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Advances in Human-Computer Interaction
Volume 2013, Article ID 187024, 8 pages
http://dx.doi.org/10.1155/2013/187024
Review Article

A Review of Hybrid Brain-Computer Interface Systems

Biomedical Signal and Image Processing Laboratory, Department of Electrical Engineering, University of North Dakota, Grand Forks, ND, USA

Received 7 July 2012; Revised 30 October 2012; Accepted 4 December 2012

Academic Editor: Dimitrios Pantazis

Copyright © 2013 Setare Amiri 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. J. R. Wolpaw, N. Birbaumer, D. J. McFarland, G. Pfurtscheller, and T. M. Vaughan, “Brain-computer interfaces for communication and control,” Clinical Neurophysiology, vol. 113, no. 6, pp. 767–791, 2002. View at Publisher · View at Google Scholar · View at Scopus
  2. N. Weiskopf, R. Veit, M. Erb et al., “Physiological self-regulation of regional brain activity using real-time functional magnetic resonance imaging (fMRI): methodology and exemplary data,” NeuroImage, vol. 19, no. 3, pp. 577–586, 2003. View at Publisher · View at Google Scholar · View at Scopus
  3. S. Waldert, H. Preissl, E. Demandt et al., “Hand movement direction decoded from MEG and EEG,” Journal of Neuroscience, vol. 28, no. 4, pp. 1000–1008, 2008. View at Publisher · View at Google Scholar · View at Scopus
  4. S. Coyle, T. Ward, C. Markham, and G. McDarby, “On the suitability of near-infrared (NIR) systems for next-generation brain-computer interfaces,” Physiological Measurement, vol. 25, no. 4, pp. 815–822, 2004. View at Publisher · View at Google Scholar · View at Scopus
  5. N. Birbaumer, N. Ghanayim, T. Hinterberger et al., “A spelling device for the paralysed,” Nature, vol. 398, no. 6725, pp. 297–298, 1999. View at Google Scholar · View at Scopus
  6. E. E. Sutter, “The brain response interface: communication through visually-induced electrical brain responses,” Journal of Microcomputer Applications, vol. 15, no. 1, pp. 31–45, 1992. View at Google Scholar · View at Scopus
  7. J. J. Vidal, “Toward direct brain-computer communication,” Annual Review of Biophysics and Bioengineering, vol. 2, pp. 157–180, 1973. View at Google Scholar · View at Scopus
  8. J. J. Vidal, “Real-time detection of brain events in EEG,” Proceedings of the IEEE, vol. 65, no. 5, pp. 633–641, 1977. View at Google Scholar · View at Scopus
  9. B. Allison, J. Faller, and C. H. Neuper, “BCIs that use steady-state visual evoked potentials or slow cortical potentials,” in Brain-Computer Interfaces: Principles and Practice, Wolpaw and E. W. Wolpaw, Eds., Oxford University Press, 2012. View at Google Scholar
  10. E. Sellers, Y. Arbel, and E. Donchin, “BCIs that uses P300 event-related potentials,” in Brain-Computer Interfaces: Principles and Practice, J. Wolpaw and E. W. Wolpaw, Eds., Oxford University Press, 2012. View at Google Scholar
  11. J. Kalcher, D. Flotzinger, C. Neuper, S. Gölly, and G. Pfurtscheller, “Graz brain-computer interface II: towards communication between humans and computers based on online classification of three different EEG patterns,” Medical and Biological Engineering and Computing, vol. 34, no. 5, pp. 382–388, 1996. View at Publisher · View at Google Scholar · View at Scopus
  12. B. Z. Allison, E. W. Wolpaw, and J. R. Wolpaw, “Brain-computer interface systems: progress and prospects,” Expert Review of Medical Devices, vol. 4, no. 4, pp. 463–474, 2007. View at Publisher · View at Google Scholar · View at Scopus
  13. L. A. Farwell and E. Donchin, “Talking off the top of your head: toward a mental prosthesis utilizing event-related brain potentials,” Electroencephalography and Clinical Neurophysiology, vol. 70, no. 6, pp. 510–523, 1988. View at Google Scholar · View at Scopus
  14. C. Brunner, B. Z. Allison, D. J. Krusienski et al., “Improved signal processing approaches in an offline simulation of a hybrid brain-computer interface,” Journal of Neuroscience Methods, vol. 188, no. 1, pp. 165–173, 2010. View at Publisher · View at Google Scholar · View at Scopus
  15. B. Z. Allison, C. Brunner, V. Kaiser, G. R. Müller-Putz, C. Neuper, and G. Pfurtscheller, “Toward a hybrid brain-computer interface based on imagined movement and visual attention,” Journal of Neural Engineering, vol. 7, no. 2, Article ID 026007, 2010. View at Publisher · View at Google Scholar · View at Scopus
  16. G. Pfurtscheller, T. Solis-Escalante, R. Ortner, P. Linortner, and G. R. Muller-Putz, “Self-paced operation of an SSVEP-based orthosis with and without an imagery-based “brain switch”: a feasibility study towards a hybrid BCI,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 18, no. 4, pp. 409–414, 2010. View at Publisher · View at Google Scholar · View at Scopus
  17. B. Allison, T. Luth, D. Valbuena, A. Teymourian, I. Volosyak, and A. Graser, “BCI demographics: How many (and what kind of) people can use a SSVEP BCI?” IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 18, no. 2, pp. 107–116, 2010. View at Google Scholar
  18. E. E. Sutter, “The visual evoked response as a communication channel,” in Proceedings of the Symposium on Biosensors, pp. 95–100, 1984.
  19. Y. Wang, Y. T. Wang, and T. P. Jung, “Visual stimulus design for high-rate SSVEP BCI,” Electronics Letters, vol. 46, no. 15, pp. 1057–1058, 2010. View at Publisher · View at Google Scholar · View at Scopus
  20. R. Fazel-Rezai, B. Z. Allison, C. Guger, E. W. Sellers, S. C. Kleih, and A. Kübler, “P300 brain computer interface: current challenges and emerging trends,” Frontiers in Neuroengineering, vol. 5, 2012. View at Publisher · View at Google Scholar
  21. E. Donchin and M. G. Coles, “Is the P300 component a manifestation of context updating?” Behavioral and Brain Functions, vol. 11, pp. 357–374, 1998. View at Google Scholar
  22. W. Lutzenberger, T. Elbert, B. Rockstroh, and N. Birbaumer, “The effects of self-regulation of slow control potentials on performance in a signal detection task,” International Journal of Neuroscience, vol. 9, no. 3, pp. 175–183, 1979. View at Google Scholar · View at Scopus
  23. A. Kübler, B. Kotchoubey, T. Hinterberger et al., “The thought translation device: a neurophysiological approach to communication in total motor paralysis,” Experimental Brain Research, vol. 124, no. 2, pp. 223–232, 1999. View at Publisher · View at Google Scholar · View at Scopus
  24. G. Pfurtscheller and F. H. Lopes Da Silva, “Event-related EEG/MEG synchronization and desynchronization: basic principles,” Clinical Neurophysiology, vol. 110, no. 11, pp. 1842–1857, 1999. View at Publisher · View at Google Scholar · View at Scopus
  25. http://www.scopus.com/home.url.
  26. G. Pfurtscheller, B. Z. Allison, C. Brunner et al., “The hybrid BCI,” Frontiers in Neuroscience, vol. 4, 2010. View at Publisher · View at Google Scholar
  27. A. Savic, U. Kisic, and M. Popovic, “Toward a hybrid BCI for grasp rehabilitation,” in Proceedings of the 5th European Conference of the International Federation for Medical and Biological Engineering Proceedings, pp. 806–809, 2012.
  28. C. Brunner, B. Z. Allison, C. Altstätter, and C. Neuper, “A comparison of three brain-computer interfaces based on event-related desynchronization, steady state visual evoked potentials, or a hybrid approach using both signals,” Journal of Neural Engineering, vol. 8, no. 2, Article ID 025010, 2011. View at Publisher · View at Google Scholar · View at Scopus
  29. R. C. Panicker, S. Puthusserypady, and Y. Sun, “An asynchronous P300 BCI with SSVEP-based control state detection,” IEEE Transactions on Biomedical Engineering, vol. 58, no. 6, pp. 1781–1788, 2011. View at Publisher · View at Google Scholar · View at Scopus
  30. G. Edlinger, C. Holzner, and C. Guger, “A hybrid brain-computer interface for smart home control,” in Proceedings of the 14th international conference on Human-Computer Interaction. Interaction Techniques and Environments, pp. 417–426, 2011.
  31. B. Rebsamen, E. Burdet, Q. Zeng et al., “Hybrid P300 and Mu-Beta brain computer interface to operate a brain controlled wheelchair,” in Proceedings of the 2nd International Convention on Rehabilitation Engineering and Assistive Technology, pp. 51–55, 2008.
  32. Y. Su, Y. Qi, J. X. Luo et al., “A hybrid brain-computer interface control strategy in a virtual environment,” Journal of Zhejiang University, vol. 12, no. 5, pp. 351–361, 2011. View at Publisher · View at Google Scholar · View at Scopus
  33. H. Riechmann, N. Hachmeister, H. Ritter, and A. Finke, “Asynchronous, parallel on-line classification of P300 and ERD for an efficient hybrid BCI,” in Proceedings of the 5th International IEEE/EMBS Conference on Neural Engineering (NER '11), pp. 412–415, May 2011. View at Publisher · View at Google Scholar · View at Scopus
  34. S. Fazli, J. Mehnert, J. Steinbrink et al., “Enhanced performance by a hybrid NIRS-EEG brain computer interface,” Neuroimage, vol. 59, pp. 519–529, 2011. View at Google Scholar
  35. R. Leeb, H. Sagha, R. Chavarriaga, and J. D. R. Millán, “A hybrid brain-computer interface based on the fusion of electroencephalographic and electromyographic activities,” Journal of Neural Engineering, vol. 8, no. 2, Article ID 025011, 2011. View at Publisher · View at Google Scholar · View at Scopus
  36. Y. Punsawad, Y. Wongsawat, and M. Parnichkun, “Hybrid EEG-EOG brain-computer interface system for practical machine control,” in Proceedings of the IEEE Engineering in Medicine and Biology Society Conference (EMBC '10), pp. 1360–1363, 2010.
  37. X. Yong, M. Fatourechi, R. K. Ward, and G. E. Birch, “The design of a point-and-click system by integrating a self-paced brain-computer interface with an eye-tracker,” IEEE Journal on Emerging and Selected Topics in Circuits and Systems, vol. 1, no. 4, pp. 590–602, 2011. View at Google Scholar
  38. A. Kubler and K. R. Muller, “An introduction to brain-computer interfacing,” in Toward Brain-Computer Interfacing, G. Dornhedge, J. R. Millan, T. Hinterberger, D. J. McFarland, and K. R. Muller, Eds., pp. 1–25, MIT Press, Cambridge, Mass, USA, 2007. View at Google Scholar
  39. D. J. Krusienski, E. W. Sellers, F. Cabestaing et al., “A comparison of classification techniques for the P300 Speller,” Journal of Neural Engineering, vol. 3, no. 4, article 299, 2006. View at Publisher · View at Google Scholar · View at Scopus
  40. U. Hoffmann, J. M. Vesin, T. Ebrahimi, and K. Diserens, “An efficient P300-based brain-computer interface for disabled subjects,” Journal of Neuroscience Methods, vol. 167, no. 1, pp. 115–125, 2008. View at Publisher · View at Google Scholar · View at Scopus
  41. T. Tsubone, T. Muroga, and Y. Wada, “Application to robot control using brain function measurement by near-infrared spectroscopy,” in Proceedings of the 29th IEEE Engineering in Medicine and Biology Society (EMBC '07), pp. 5342–5345, August 2007. View at Publisher · View at Google Scholar · View at Scopus
  42. P. A. Lachenbruch and M. Goldstein, “Discriminant analysis,” Biometrics, vol. 35, no. 1, pp. 69–85, 1979. View at Google Scholar · View at Scopus
  43. X. Yong, M. Fatourechi, R. K. Ward, and G. E. Birch, “Automatic artefact removal in a self-paced hybrid brain-computer interface system,” Journal of NeuroEngineering and Rehabilitation, vol. 9, article 50, 2012. View at Google Scholar