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Computational Intelligence and Neuroscience
Volume 2017, Article ID 5863512, 16 pages
https://doi.org/10.1155/2017/5863512
Research Article

Development of a Novel Motor Imagery Control Technique and Application in a Gaming Environment

1School of Computer Science, Xi’an Polytechnic University, Xi’an, China
2State Key Laboratory for Manufacturing Systems Engineering, School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an, China

Correspondence should be addressed to Ting Li; moc.anis@euxoahnaitgnac

Received 18 October 2016; Revised 5 December 2016; Accepted 30 January 2017; Published 9 May 2017

Academic Editor: Jing Jin

Copyright © 2017 Ting Li 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. K. Huotari and J. Hamari, “Defining gamification—a service marketing perspective,” in Proceedings of the 16th International Academic MindTrek Conference: “Envisioning Future Media Environments” (MindTrek '12), pp. 17–22, Tampere, Finland, October 2012. View at Publisher · View at Google Scholar · View at Scopus
  2. S. Deterding, D. Dixon, R. Khaled, and L. Nacke, “From game design elements to gamefulness: defining “gamification”,” in Proceedings of the 15th International Academic MindTrek Conference: Envisioning Future Media Environments (MindTrek '11), pp. 9–15, Tampere, Finland, September 2011. View at Publisher · View at Google Scholar · View at Scopus
  3. J. Hamari, “Transforming homo economicus into homo ludens: a field experiment on gamification in a utilitarian peer-to-peer trading service,” Electronic Commerce Research and Applications, vol. 12, no. 4, pp. 236–245, 2013. View at Publisher · View at Google Scholar · View at Scopus
  4. J. Hamari, “Do badges increase user activity? A field experiment on the effects of gamification,” Computers in Human Behavior, vol. 71, pp. 469–478, 2017. View at Publisher · View at Google Scholar
  5. G. Zichermann, Gamification by Design: Implementing Game Mechanics in Web and Mobile Apps, O'Reilly Media, Sebastopol, Calif, USA, 1st edition, 2011.
  6. J. Hamari and J. Koivisto, “‘Working out for likes’: an empirical study on social influence in exercise gamification,” Computers in Human Behavior, vol. 50, pp. 333–347, 2015. View at Publisher · View at Google Scholar · View at Scopus
  7. The Speed Camera Lottery. The Fun Theory.
  8. https://en.wikipedia.org/wiki/Gamification.
  9. “FANGO delivers on Social TV,” Impulse Gamer, 2012.
  10. K. Adam, “HOW TO: Gamify Your Marketing,” Mashable, 2011.
  11. D. Takahashi, “Website builder DevHub gets users hooked by ‘gamifying’ its service,” VentureBeat, 2010.
  12. O. Toubia, “Idea generation, creativity, and incentives,” Marketing Science, vol. 25, no. 5, pp. 411–425, 2006. View at Publisher · View at Google Scholar · View at Scopus
  13. C. Lister, J. H. West, B. Cannon, T. Sax, and D. Brodegard, “Just a fad? Gamification in health and fitness apps,” JMIR Serious Games, vol. 2, no. 2, article e9, 2014. View at Publisher · View at Google Scholar
  14. J. Markoff, “In a video game, tackling the complexities of protein folding,” The New York Times, 2010. View at Google Scholar
  15. The Gamification of Education. Knewton.
  16. S. De Sousa Borges, V. H. S. Durelli, H. M. Reis, and S. Isotani, “A systematic mapping on gamification applied to education,” in Proceedings of the 29th Annual ACM Symposium on Applied Computing (SAC '14), pp. 216–222, March 2014. View at Publisher · View at Google Scholar · View at Scopus
  17. https://en.wikipedia.org/wiki/Brain%E2%80%93computer_interface.
  18. T. Hanakawa, “Organizing motor imageries,” Neuroscience Research, vol. 104, pp. 56–63, 2016. View at Publisher · View at Google Scholar · View at Scopus
  19. A. Schlögl, F. Lee, H. Bischof, and G. Pfurtscheller, “Characterization of four-class motor imagery EEG data for the BCI-competition 2005,” Journal of Neural Engineering, vol. 2, no. 4, pp. L14–L22, 2005. View at Publisher · View at Google Scholar · View at Scopus
  20. J. Li, H. Ji, L. Cao, R. Gu, B. Xia, and Y. Huang, “Wheelchair control based on multimodal brain-computer interfaces,” in Neural Information Processing, vol. 8226, pp. 434–444, Springer, New York, NY, USA, 2013. View at Google Scholar
  21. J. Winters, “Just short of telepathy: can you interact with the outside world if you can't even blink an eye?” Psychology Today, vol. 36, no. 3, p. 44, 2003. View at Google Scholar
  22. 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 Publisher · View at Google Scholar · View at Scopus
  23. E. Yin, Z. Zhou, J. Jiang, Y. Yu, and D. Hu, “A dynamically optimized SSVEP brain-computer interface (BCI) speller,” IEEE Transactions on Biomedical Engineering, vol. 62, no. 6, pp. 1447–1456, 2015. View at Publisher · View at Google Scholar · View at Scopus
  24. H. Yuan, T. Liu, R. Szarkowski, C. Rios, J. Ashe, and B. He, “Negative covariation between task-related responses in alpha/beta-band activity and BOLD in human sensorimotor cortex: an EEG and fMRI study of motor imagery and movements,” NeuroImage, vol. 49, no. 3, pp. 2596–2606, 2010. View at Publisher · View at Google Scholar · View at Scopus
  25. B. Allison, B. Graimann, and A. Gräser, “Why use a BCI if you are healthy,” in Proceedings of the Brain-Computer Interfaces and Games Workshop at ACE (Advances in Computer Entertainment) (BRAINPLAY '07), Salzburg, Austria, June 2007.
  26. J. B. F. Van Erp, F. Lotte, and M. Tangermann, “Brain-computer interfaces: beyond medical applications,” Computer, vol. 45, no. 4, Article ID 6165246, pp. 26–34, 2012. View at Publisher · View at Google Scholar · View at Scopus
  27. https://en.wikipedia.org/wiki/Motor_imagery.
  28. D. Marshall, D. Coyle, S. Wilson, and M. Callaghan, “Games, gameplay, and BCI: the state of the art,” IEEE Transactions on Computational Intelligence and AI in Games, vol. 5, no. 2, pp. 82–99, 2013. View at Publisher · View at Google Scholar · View at Scopus
  29. E. C. Lalor, S. P. Kelly, C. Finucane et al., “Steady-state VEP-based brain-computer interface control in an immersive 3D gaming environment,” EURASIP Journal on Advances in Signal Processing, vol. 2005, no. 19, Article ID 706906, pp. 3156–3164, 2005. View at Publisher · View at Google Scholar
  30. E. C. Lalor, S. P. Kelly, C. Finucane et al., “Steady-state VEP-based brain-computer interface control in an immersive 3D gaming environment,” EURASIP Journal on Applied Signal Processing, vol. 2005, no. 19, pp. 3156–3164, 2005. View at Publisher · View at Google Scholar · View at Scopus
  31. M. W. Tangermann, M. Krauledat, K. Grzeska et al., “Playing pinball with non-invasive BCI,” in Proceedings of the 22nd Annual Conference on Neural Information Processing Systems (NIPS '08), vol. 21, pp. 1641–1648, December 2008. View at Scopus
  32. B. Reuderink, A. Nijholt, and M. Poel, “Affective Pacman: a frustrating game for brain-computer interface experiments,” in Intelligent Technologies for Interactive Entertainment, vol. 9 of Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, pp. 221–227, Springer, Berlin, Germany, 2009. View at Publisher · View at Google Scholar
  33. G. Pires, M. Torres, N. Casaleiro, U. Nunes, and M. Castelo-Branco, “Playing Tetris with non-invasive BCI,” in Proceedings of the IEEE 1st International Conference on Serious Games and Applications for Health, (SeGAH '11), pp. 1–6, Braga, Portugal, November 2011. View at Publisher · View at Google Scholar · View at Scopus
  34. B. Van de Laar, H. Gürkök, D. Plass-Oude Bos, M. Poel, and A. Nijholt, “Experiencing BCI control in a popular computer game,” IEEE Transactions on Computational Intelligence and AI in Games, vol. 5, no. 2, pp. 176–184, 2013. View at Publisher · View at Google Scholar · View at Scopus
  35. B. Z. Allison, J. Jin, Y. Zhang, and X. Wang, “A four-choice hybrid P300/SSVEP BCI for improved accuracy,” Brain-Computer Interfaces, vol. 1, no. 1, pp. 17–26, 2014. View at Publisher · View at Google Scholar
  36. M. Wang, I. Daly, B. Z. Allison et al., “A new hybrid BCI paradigm based on P300 and SSVEP,” Journal of Neuroscience Methods, vol. 244, pp. 16–25, 2015. View at Publisher · View at Google Scholar · View at Scopus
  37. E. Yin, T. Zeyl, R. Saab, D. Hu, Z. Zhou, and T. Chau, “An auditory-tactile visual saccade-independent P300 brain-computer interface,” International Journal of Neural Systems, vol. 26, no. 1, Article ID 1650001, 2016. View at Publisher · View at Google Scholar · View at Scopus
  38. E. Yin, T. Zeyl, R. Saab, T. Chau, D. Hu, and Z. Zhou, “A hybrid brain—computer interface based on the fusion of P300 and SSVEP scores,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 23, no. 4, pp. 693–701, 2015. View at Publisher · View at Google Scholar · View at Scopus
  39. https://en.wikipedia.org/wiki/3D_Tetris.
  40. http://www.bci2000.org/wiki/index.php/-User_Tutorial:Analyzing_the_Initial_Mu_Rhythm_Session.
  41. G. Pfurtscheller, C. Brunner, A. Schlögl, and F. H. Lopes da Silva, “Mu rhythm (de)synchronization and EEG single-trial classification of different motor imagery tasks,” NeuroImage, vol. 31, no. 1, pp. 153–159, 2006. View at Publisher · View at Google Scholar · View at Scopus
  42. T. Li, J. Hong, J. Zhang, and F. Guo, “Brain-machine interface control of a manipulator using small-world neural network and shared control strategy,” Journal of Neuroscience Methods, vol. 224, pp. 26–38, 2014. View at Google Scholar
  43. http://cn.mathworks.com/help/nnet/ref/hardlim.html?requestedDomain=www.mathworks.com.
  44. S. Siuly, Y. Li, and P. P. Wen, “Clustering technique-based least square support vector machine for EEG signal classification,” Computer Methods and Programs in Biomedicine, vol. 104, no. 3, pp. 358–372, 2011. View at Publisher · View at Google Scholar · View at Scopus
  45. http://www.wellapets.com.
  46. http://keas.com.
  47. http://www.kognito.com/products/.
  48. http://www.runanempire.com/.
  49. T. Sollfrank, D. Hart, R. Goodsell, J. Foster, and T. Tan, “3D visualization of movements can amplify motor cortex activation during subsequent motor imagery,” Frontiers in Human Neuroscience, vol. 9, article 463, 2015. View at Publisher · View at Google Scholar · View at Scopus
  50. O.-H. Cho and W.-H. Lee, “BCI sensor based environment changing system for immersion of 3D game,” International Journal of Distributed Sensor Networks, vol. 2014, Article ID 620391, 8 pages, 2014. View at Publisher · View at Google Scholar · View at Scopus
  51. T. Kondo, M. Saeki, Y. Hayashi, K. Nakayashiki, and Y. Takata, “Effect of instructive visual stimuli on neurofeedback training for motor imagery-based brain-computer interface,” Human Movement Science, vol. 43, pp. 239–249, 2015. View at Publisher · View at Google Scholar · View at Scopus
  52. A. N. Belkacem, S. Saetia, K. Zintus-Art et al., “Real-time control of a video game using eye movements and two temporal EEG sensors,” Computational Intelligence and Neuroscience, vol. 2015, Article ID 653639, 10 pages, 2015. View at Publisher · View at Google Scholar · View at Scopus