Skip to main content
SpringerLink
Log in

Toward Ubiquitous BCIs

  • Chapter
  • First Online:
Brain-Computer Interfaces

Part of the book series: The Frontiers Collection ((FRONTCOLL))

Abstract

The preceding chapters in this book described modern BCI systems. This concluding chapter instead discusses future directions. While there are some specific predictions, I mainly analyze key factors and trends relating to practical mainstream BCI development. While I note some disruptive technologies that could dramatically change BCIs, this chapter focuses mainly on realistic, incremental progress and how progress could affect user groups and ethical issues.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 54.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    This term is a contraction of electro-(anything)-gram. ExG sensors refer to any devices used to record people’s electrophysiological activity. The word “sensor” is used in its colloquial meaning throughout this chapter, not the stricter definition within electrical engineering.

  2. 2.

    Some groups use the term mu or SMR instead of ERD

  3. 3.

    Our team with the BrainAble research project at http://www.brainable.org is working toward implementing Hex-O-Select.

  4. 4.

    This chapter was originally written in 2008, and this sentence was true through 2009. However, numerous groups began reporing hybrid BCI research in 2010.

References

  1. B.Z. Allison, C. Brunner, S. Grissmann, and C. Neuper (2010). Toward a multidimensional “hybrid” BCI based on simultaneous SSVEP and ERD activity. Program No. 227.4. 2010 Neuroscience Meeting Planner. San Diego, CA: Society for Neuroscience, 2010. Online. Presentation accepted and scheduled for Nov 2010.

    Google Scholar 

  2. B.Z. Allison, D. Valbuena, T. Lueth, A. Teymourian, I. Volosyak, and A. Gräser, BCI demographics: How many (and what kinds of) people can use an SSVEP BCI? IEEE Trans Neural Syst Rehabil Eng, 18(2), 107–116, (2010).

    Google Scholar 

  3. B.Z. Allison, Human-computer interaction: Novel interaction methods and techniques, chapter The I of BCIs: next generation interfaces for brain – computer interface systems that adapt to individual users. Springer, New York, (2009).

    Google Scholar 

  4. B.Z. Allison, J.B. Boccanfuso, C. Agocs, L.A. McCampbell, D.S. Leland, C. Gosch, and M. Moore Jackson, Sustained use of an SSVEP BCI under adverse conditions. Cogn Neurosci Soc, 129, (2006).

    Google Scholar 

  5. B.Z. Allison, C. Brunner, V. Kaiser, G. Müller-Putz, C. Neuper, and G. Pfurtscheller. A hybrid brain-computer interface based on imagined movement and visual attention. J Neural Eng, 7(2), 26007, (2010).

    Google Scholar 

  6. B.Z. Allison, D.J. McFarland, G. Schalk, S.D. Zheng, M.M. Jackson, and J.R. Wolpaw, Towards an independent brain–computer interface using steady state visual evoked potentials. Clin Neurophysiol, 119, 399–408, (2008).

    Article  PubMed  Google Scholar 

  7. B.Z. Allison, and M.M. Moore (2004). Field validation of a P3 BCI under adverse conditions. Society for Neuroscience Conference. Program No. 263.9. San Diego, CA.

    Google Scholar 

  8. B.Z. Allison and C. Neuper, Could anyone use a BCI? In D.S. Tan and A. Nijholt, (Eds.), (B+H)CI: The human in brain–computer interfaces and the brain in human-computer interaction, volume in press. Springer, New York, (2010).

    Google Scholar 

  9. B.Z. Allison and J.A. Pineda, Effects of SOA and flash pattern manipulations on ERPs, performance, and preference: Implications for a BCI system. Int J Psychophysiol, 59, 127–140, (2006).

    Article  PubMed  Google Scholar 

  10. B.Z. Allison, A. Vankov, and J.A. Pineda., EEGs and ERPs associated with real and imagined movement of single limbs and combinations of limbs and applications to brain computer interface (BCI) systems. Soc Neurosci Abs, 25, 1139, (1999).

    Google Scholar 

  11. B.Z. Allison, E.W. Wolpaw, and J.R. Wolpaw, Brain–computer interface systems: progress and prospects. Expert Rev Med Devices, 4, 463–474, (2007).

    Article  PubMed  Google Scholar 

  12. C. Brunner, B.Z. Allison, C. Altstätter, and C. Neuper (2010). A hybrid brain-computer interface based on motor imagery and steady-state visual evoked potentials. Program No. 227.3. 2010 Neuroscience Meeting Planner. San Diego, CA: Society for Neuroscience, 2010. Online. Presentation accepted and scheduled for Nov 2010.

    Google Scholar 

  13. N. Bigdely-Shamlo, A. Vankov, R.R. Ramirez, and S. Makeig, Brain activity-based image classification from rapid serial visual presentation. IEEE Trans Neural Syst Rehabil Eng, 16(5), 432–441, Oct (2008).

    Article  PubMed  Google Scholar 

  14. N. Birbaumer and L. G. Cohen, brain–computer interfaces: communication and restoration of movement in paralysis. J Physiol, 579, 621–636, (2007).

    Article  CAS  PubMed  Google Scholar 

  15. N. Birbaumer, N. Ghanayim, T. Hinterberger, I. Iversen, B. Kotchoubey, A. Kübler, J. Perelmouter, E. Taub, and H. Flor, A spelling device for the paralysed. Nature, 398, 297–298, (1999).

    Article  CAS  PubMed  Google Scholar 

  16. T. Blakely, K.J. Miller, S.P. Zanos, R.P.N. Rao, and J.G. Ojemann, Robust, long-term control of an electrocorticographic brain–computer interface with fixed parameters. Neurosurg Focus, 27(1), E13, Jul (2009).

    Article  PubMed  Google Scholar 

  17. C. Brunner, B.Z. Allison, D.J. Krusienski, V. Kaiser, G.R. Müller-Putz, C. Neuper, and G. Pfurtscheller Improved signal processing approaches for a hybrid brain-computer interface simulation. J Neurosci Method, 188(1),165–73.

    Google Scholar 

  18. A. Buttfield, P. W. Ferrez, and J. del R. Millán, Towards a robust BCI: Error potentials and online learning. IEEE Trans Neural Syst Rehabil Eng, 14, 164–168, 2006.

    Article  PubMed  Google Scholar 

  19. J.M. Carmena, M.A. Lebedev, R.E. Crist, J.E. O’Doherty, D.M. Santucci, D.F. Dimitrov, P.G. Patil, C.S. Henriquez, and M.A.L. Nicolelis, Learning to control a brain-machine interface for reaching and grasping by primates. PLoS Biol, 1, E42, (2003).

    Article  PubMed  Google Scholar 

  20. F. Cincotti, D. Mattia, F. Aloise, S. Bufalari, G. Schalk, G. Oriolo, A. Cherubini, M.G. Marciani, and F. Babiloni, Non-invasive brain–computer interface system: towards its application as assistive technology. Brain Res Bull, 75(6), 796–803, Apr (2008).

    Google Scholar 

  21. L. Citi, R. Poli, C. Cinel, and F. Sepulveda, P300-based BCI mouse with genetically-optimized analogue control. IEEE Trans Neural Syst Rehabil Eng, 16, 51–61, (2008).

    Article  PubMed  Google Scholar 

  22. J. J. Daly and J. R. Wolpaw, brain–computer interfaces in neurological rehabilitation. Lancet Neurol, 7, 1032–1043, (2008).

    Article  PubMed  Google Scholar 

  23. B.J. de Kruif, R. Schaefer, and P. Desain, Classification of imagined beats for use in a brain computer interface. Conf Proc IEEE Eng Med Biol Soc, 2007, 678–681, (2007).

    PubMed  Google Scholar 

  24. B. H. Dobkin, brain–computer interface technology as a tool to augment plasticity and outcomes for neurological rehabilitation. J Physiol, 579, 637–642, (2007).

    Article  CAS  PubMed  Google Scholar 

  25. P. W. Ferrez and J. del R. Millán, Error-related EEG potentials generated during simulated brain–computer interaction. IEEE Trans Biomed Engi, 55, 923–929, 2008.

    Article  Google Scholar 

  26. F. Galán, M. Nuttin, E. Lew, P. W. Ferrez, G. Vanacker, J. Philips, and J. del R. Millán, A brain-actuated wheelchair: asynchronous and non-invasive brain?computer interfaces for continuous control of robots. Clin Neurophysiol, 119, 2159–2169, 2008.

    Article  PubMed  Google Scholar 

  27. X. Gao, D. Xu, M. Cheng, and S. Gao, A BCI-based environmental controller for the motion-disabled. IEEE Trans Neural Syst Rehabil Eng, 11, 137–140, 2003.

    Article  PubMed  Google Scholar 

  28. T. Geng, J. Q. Gan, M. Dyson, C. S. Tsui, and F. Sepulveda, A novel design of 4-class BCI using two binary classifiers and parallel mental tasks. Comput Intell Neurosci, 2008, 437306, (2008).

    Google Scholar 

  29. A. D. Gerson, L. C. Parra, and P. Sajda, Cortically coupled computer vision for rapid image search. IEEE Trans Neural Syst Rehabil Eng, 14(2), 174–179, Jun (2006).

    Article  PubMed  Google Scholar 

  30. Vora, J.Y., Allison, B.Z., & Moore, M.M. (2004). A P3 brain computer interface for robot arm control. Society for Neuroscience Abstract, 30, Program No. 421.19.

    Google Scholar 

  31. F.H. Guenther, J.S. Brumberg, E.J. Wright, A. Nieto-Castanon, J.A. Tourville, M. Panko, R. Law, S.A. Siebert, J.L. Bartels, D.S. Andreasen, P. Ehirim, H. Mao, and P.R. Kennedy., A wireless brain-machine interface for real-time speech synthesis. PLoS One, 4(12), e8218, (2009).

    Article  PubMed  Google Scholar 

  32. C. Guger, S. Daban, E. Sellers, C. Holzner, G. Krausz, R. Carabalona, F. Gramatica, and G. Edlinger. How many people are able to control a P300-based brain–computer interface (BCI)? Neurosci Lett, 462, 94–98, (2009).

    Article  CAS  PubMed  Google Scholar 

  33. C. Guger, G. Edlinger, W. Harkam, I. Niedermayer, and G. Pfurtscheller, How many people are able to operate an EEG-based brain–computer interface (BCI)? IEEE Trans Neural Syst Rehabil Eng, 11, 145–147, (2003).

    Article  CAS  PubMed  Google Scholar 

  34. L.R. Hochberg, M.D. Serruya, G.M. Friehs, J.A. Mukand, M. Saleh, A.H. Caplan, A. Branner, D. Chen, R.D. Penn, and J.P. Donoghue, Neuronal ensemble control of prosthetic devices by a human with tetraplegia. Nature, 442, 164–171, (2006).

    Article  CAS  PubMed  Google Scholar 

  35. A. Kübler and K.-R. Müller, An introduction to brain–computer interfacing. In G. Dornhege, J. del R. Millán, T. Hinterberger, D.J. McFarland, and K.-R. Müller, (Eds.), Toward brain–computer interfacing, MIT Press, Cambridge, MA, pp. 1–25, (2007).

    Google Scholar 

  36. A. Kübler, N. Neumann, J. Kaiser, B. Kotchoubey, T. Hinterberger, and N. Birbaumer, brain–computer communication: self-regulation of slow cortical potentials for verbal communication. Arch Phys Med Rehabil, 82, 1533–1539, (2001).

    Article  PubMed  Google Scholar 

  37. P.R. Kennedy, R.A. Bakay, M.M. Moore, K. Adams, and J. Goldwaithe, Direct control of a computer from the human central nervous system. IEEE Trans Rehabil Eng, 8(2), 198–202, Jun (2000).

    Article  CAS  PubMed  Google Scholar 

  38. J. Kubánek, K.J. Miller, J.G. Ojemann, J.R. Wolpaw, and G. Schalk., Decoding flexion of individual fingers using electrocorticographic signals in humans. J Neural Eng, 6(6), 066001, Dec (2009).

    Article  PubMed  Google Scholar 

  39. K. G. Lambert. Rising rates of depression in today’s society: consideration of the roles of effort-based rewards and enhanced resilience in day-to-day functioning. Neurosci Behav Revi, 30, 497–510, (2006).

    Google Scholar 

  40. E.C. Lee; J.C. Woo, J.H. Kim et al. A brain-computer interface method combined with eye tracking for 3D interaction J Neurosci Method, 190(2), 289–298, (2010)

    Google Scholar 

  41. R. Leeb, R. Scherer, D. Friedman, F.Y. Lee, C. Keinrath, H. Bischof, M. Slater, and G. Pfurtscheller, Combining BCI and virtual reality: scouting virtual worlds. In G. Dornhege, J. del R. Millán, T. Hinterberger, D.J. McFarland, and K.-R. Müller, (Eds), Toward brain–computer interfacing, chapter 23, MIT Press, Cambridge, MA, pp. 393–408, (2007).

    Google Scholar 

  42. A. W. Mahncke, A. Bronstone, and M. M. Merzenich., Brain plasticity and functional losses in the aged: scientific basis for a novel intervention. Progress in brain research: Reprogramming the brain, Elsevier, New York, (2006).

    Google Scholar 

  43. D. Marr, Vision, W. H. Freeman, (1982). http://www.nature.com/nature/journal/v317/n6035/abs/317314a0.html

  44. S.G. Mason, A. Bashashati, M. Fatourechi, K.F. Navarro, and G.E. Birch, A comprehensive survey of brain interface technology designs. Ann Biomed Eng, 35, 137–169, (2007).

    Article  CAS  PubMed  Google Scholar 

  45. D.J. McFarland, D. J. Krusienski, W. A. Sarnacki, and J. R. Wolpaw, Emulation of computer mouse control with a noninvasive brain–computer interface. J Neural Eng, 5, 101–110, (2008).

    Article  PubMed  Google Scholar 

  46. J. Mellinger, G. Schalk, C. Braun, H. Preissl, W. Rosenstiel, N. Birbaumer, and A. Kübler, An MEG-based brain–computer interface (BCI). NeuroImage, 36, 581–593, (2007).

    Article  PubMed  Google Scholar 

  47. G.R. Müller, C. Neuper, and G. Pfurtscheller, Implementation of a telemonitoring system for the control of an EEG-based brain–computer interface. IEEE Trans Neural Syst Rehabil Eng, 11, 54–59, (2003).

    Article  PubMed  Google Scholar 

  48. K.-R. Müller, M. Tangermann, G. Dornhege, M. Krauledat, G. Curio, and B. Blankertz, Machine learning for real-time single-trial EEG analysis: From brain–computer interfacing to mental state monitoring. J Neurosci Methods, 167, 82–90, (2008).

    Article  PubMed  Google Scholar 

  49. M. M. Moore, Real-world applications for brain–computer interface technology. IEEE Trans Neural Syst Rehabil Eng, 11, 162–165, (2003).

    Article  PubMed  Google Scholar 

  50. T.M. Srihari Mukesh, V. Jaganathan, and M. Ramasubba Reddy, A novel multiple frequency stimulation method for steady state VEP based brain computer interfaces. Physiol Measure, 27, 61–71, 2006.

    Article  CAS  Google Scholar 

  51. N. Neumann, T. Hinterberger, J. Kaiser, U. Leins, N. Birbaumer, and A. Kübler, Automatic processing of self-regulation of slow cortical potentials: evidence from brain–computer communication in paralysed patients. Clin Neurophysiol, 115, 628–635, (2004).

    Article  CAS  PubMed  Google Scholar 

  52. C. Neuper, R. Scherer, M. Reiner, and G. Pfurtscheller, Imagery of motor actions: differential effects of kinaesthetic versus visual-motor mode of imagery on single-trial EEG. Brain Res Cogn Brain Res, 25, 668–677, 2005.

    Article  PubMed  Google Scholar 

  53. F. Nijboer, A. Furdea, I. Gunst, J. Mellinger, D.J. McFarland, N. Birbaumer, and A. Kübler. An auditory brain–computer interface (BCI). Neurosci Lett, 167, 43–50, (2008).

    Google Scholar 

  54. F. Nijboer, N. Birbaumer, and A. Kübler. The influence of psychological state and motivation on brain-computer interface performance in patients with amyotrophic lateral sclerosis–a longitudinal study. Front Neurosci, 4, (2010)

    Google Scholar 

  55. A. Nijholt, D. Tan, G. Pfurtscheller, C. Brunner, J. del R. Millán, B.Z. Allison, B. Graimann, F. Popescu, B. Blankertz, and K.-R. Müller, brain–computer interfacing for intelligent systems. IEEE Intell Syst, 23, 72–79, (2008).

    Article  Google Scholar 

  56. V.V. Nikulin, F.U. Hohlefeld, A.M. Jacobs, and G. Curio. Quasi-movements: a novel motor-cognitive phenomenon. Neuropsychologia, 46:727–742, (2008).

    Article  PubMed  Google Scholar 

  57. G. Pfurtscheller, B.Z. Allison, C. Brunner, G. Bauernfeind, T. Solis Escalante, R. Scherer, T.O. Zander, G. Müller-Putz, C. Neuper, and N. Birbaumer,. The hybrid BCI. Front Neurosci, 4, 42. doi:10.3389/fnpro.2010.00003, (2010).

    Google Scholar 

  58. G. Pfurtscheller, R. Leeb, D. Friedman, and M. Slater, Centrally controlled heart rate changes during mental practice in immersive virtual environment: a case study with a tetraplegic. Int J Psychophysiol, 68, 1–5, (2008).

    Article  CAS  PubMed  Google Scholar 

  59. G. Pfurtscheller, G. Müller-Putz, R. Scherer, and C. Neuper, Rehabilitation with brain–computer interface systems. IEEE Comput Mag, 41, 58–65, (2008).

    Google Scholar 

  60. G. Pfurtscheller, G.R. Müller-Putz, A. Schlögl, B. Graimann, R. Scherer, R. Leeb, C. Brunner, C. Keinrath, F. Lee, G. Townsend, C. Vidaurre, and C. Neuper, 15 years of BCI research at Graz University of Technology: current projects. IEEE Trans Neural Syst Rehabil Eng, 14, 205–210, (2006).

    Article  CAS  PubMed  Google Scholar 

  61. G. Pfurtscheller, T. Solis-Escalante, R. Ortner, P. Linortner, and G.R. Müller-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 Trans Neural Syst Rehabil Eng, 18(4), 409–414, Aug (2010).

    Google Scholar 

  62. J.A. Pineda, B.Z. Allison, and A. Vankov, The effects of self-movement, observation, and imagination on mu rhythms and readiness potentials (RP’s): toward a brain–computer interface (BCI). IEEE Trans Rehabil Eng, 8(2), 219–222, Jun (2000).

    Article  CAS  PubMed  Google Scholar 

  63. J.A. Pineda, D. Brang, E. Hecht, L. Edwards, S. Carey, M. Bacon, C. Futagaki, D. Suk, J. Tom, C. Birnbaum, and A. Rork, Positive behavioral and electrophysiological changes following neurofeedback training in children with autism. Res Autism Spect Disorders, 2(3), 557–581, (2008).

    Article  Google Scholar 

  64. J.A. Pineda, D.S. Silverman, A. Vankov, and J. Hestenes, Learning to control brain rhythms: making a brain–computer interface possible. IEEE Trans Neural Syst Rehabil Eng, 11, 181–184, (2003).

    Article  PubMed  Google Scholar 

  65. F. Popescu, S. Fazli, Y. Badower, B. Blankertz, and K.-R. Müller, Single trial classification of motor imagination using 6 dry EEG electrodes. PLoS ONE, 2, e637, (2007).

    Article  PubMed  Google Scholar 

  66. C. Sannelli, M. Braun, M. Tangermann, and K.-R. Müller, Estimating noise and dimensionality in BCI data sets: Towards illiteracy comprehension. In G.R. Müller-Putz, C. Brunner, R. Leeb, G. Pfurtscheller, and C. Neuper, (Eds.), Proceedings of the 4th International brain–computer Interface Workshop and Training Course 2008, pp. 26–31, Verlag der Technischen Universität Graz, (2008).

    Google Scholar 

  67. G. Santhanam, S.I. Ryu, B.M. Yu, A. Afshar, and K.V. Shenoy, A high-performance brain–computer interface. Nature, 442, 195–198, (2006).

    Article  CAS  PubMed  Google Scholar 

  68. G. Schalk. brain–computer symbiosis. J Neural Eng, 5, P1–P15, (2008).

    Article  Google Scholar 

  69. G. Schalk, X. Pei, N. Anderson, K. Wisneski, M.D. Smyth, W. Kim, D.L. Barbour, J.R. Wolpaw, and E.C. Leuthardt, Decoding spoken and imagined phonemes using electrocorticographic (ECoG) signals in humans: Initial data. Program No. 778.6. 2008 Abstract Viewer/Itinerary Planner. Society for Neuroscience, Washington, DC, (2008), Online.

    Google Scholar 

  70. G. Schalk, P. Brunner, L. A. Gerhardt, H. Bischof, and J. R. Wolpaw, brain–computer interfaces (BCIs): detection instead of classification. J Neurosci Methods, 167, 51–62, (2008).

    Article  CAS  PubMed  Google Scholar 

  71. G. Schalk, K.J. Miller, N.R. Anderson, J.A. Wilson, M.D. Smyth, J.G. Ojemann, D.W. Moran, J.R. Wolpaw, and E.C. Leuthardt, Two-dimensional movement control using electrocorticographic signals in humans. J Neural Eng, 5, 75–84, (2008).

    Article  CAS  PubMed  Google Scholar 

  72. R. Scherer, F. Lee, A. Schlögl, R. Leeb, H. Bischof, and G. Pfurtscheller, Toward self-paced brain–computer communication: navigation through virtual worlds. IEEE Trans Biomed Eng, 55, 675–682, (2008).

    Article  PubMed  Google Scholar 

  73. R. Scherer, G.R. Müller-Putz, and G. Pfurtscheller, Self-initiation of EEG-based brain–computer communication using the heart rate response. J Neural Eng, 4, L23–L29, (2007).

    Article  CAS  PubMed  Google Scholar 

  74. R. Scherer, G.R. Müller-Putz, and G. Pfurtscheller, Flexibility and practicality: Graz brain–computer interface approach. Int Rev Neurobiol, 86, 119–131, (2009).

    Article  PubMed  Google Scholar 

  75. E. W. Sellers, A. Kübler, and E. Donchin, brain–computer interface research at the University of South Florida Cognitive Psychophysiology Laboratory: The P300 speller. IEEE Trans Neural Syst Rehabil Eng, 14, 221–224, (2006).

    Article  PubMed  Google Scholar 

  76. R.M. Shiffrin and W. Schneider, Automatic and controlled processing revisited. Psychol Rev, 91, 269–276, 1984.

    Article  CAS  PubMed  Google Scholar 

  77. R. Sitaram, A. Caria, and N. Birbaumer, Hemodynamic brain–computer interfaces for communication and rehabilitation. Neural Netw, 22, 1320–1328, (2009).

    Article  PubMed  Google Scholar 

  78. P. Suppes, Z. L. Lu, and B. Han, Brain wave recognition of words. Proc Nat Acad Sci U S A, 94(26), 14965–14969, Dec (1997).

    Article  CAS  Google Scholar 

  79. L.J. Trejo, N.J. McDonald, R. Matthews, and B.Z. Allison (2007) Experimental design and testing of a multimodal cognitive overload classifier. Automated Cognition International Conference, Baltimore, Maryland. Winner, best paper award. The conference was from 22–27 July: http://www.augmentedcognition.org/events.htm.

  80. T.M. Vaughan, D.J. McFarland, G. Schalk, W.A. Sarnacki, D.J. Krusienski, E.W. Sellers, and J.R. Wolpaw, The Wadsworth BCI Research and Development Program: at home with BCI. IEEE Trans Neural Syst Rehabil Eng, 14(2), 229–233, Jun (2006).

    Article  PubMed  Google Scholar 

  81. Vora, J.Y., Allison, B.Z., & Moore, M.M. (2004). A P3 brain computer interface for robot arm control. Society for Neuroscience Abstract, 30, Program No. 421.19.

    Google Scholar 

  82. J.R. Wolpaw, brain–computer interfaces as new brain output pathways. J Physiol, 579, 613–619, (2007).

    Article  CAS  PubMed  Google Scholar 

  83. J.R. Wolpaw, N. Birbaumer, D.J. McFarland, G. Pfurtscheller, and T.M. Vaughan, brain–computer interfaces for communication and control. Clin Neurophysiol, 113, 767–791, 2002.

    Article  PubMed  Google Scholar 

  84. J.R. Wolpaw, G.E. Loeb, B.Z. Allison, E. Donchin, O. Feix do Nascimento, W.J. Heetderks, F. Nijboer, W.G. Shain, and J.N. Turner, BCI Meeting 2005–workshop on signals and recording methods. IEEE Trans Neural Syst Rehabil Eng, 14(2), 138–141, Jun (2006).

    Article  PubMed  Google Scholar 

  85. J.R. Wolpaw and D.J. McFarland, Control of a two-dimensional movement signal by a noninvasive brain–computer interface in humans. Proc Nat Acad Sci USA, 101, 17849–17854, (2004).

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgments

This paper was supported in part by three grants: a Marie Curie European Transfer of Knowledge grant Brainrobot, MTKD-CT-2004-014211, within the 6th European Community Framework Program; the Information and Communication Technologies Coordination and Support action “FutureBNCI”, Project number ICT-2010-248320; and the Information and Communication Technologies Collaborative Project action “BrainAble”, Project number ICT-2010-247447. Thanks to Sara Carro-Martinez and Drs. Alida Allison, Clemens Brunner, Gary Garcia, Gaye Lightbody, Paul McCullagh, Femke Nijboer, Kai Miller, Jaime Pineda, Gerwin Schalk, and Jonathan Wolpaw for comments on this manuscript or on some ideas herein. The sentence about “fardels bear” is paraphrased from Hamlet.

Author information

Authors and Affiliations

  1. Institute for Knowledge Discovery, Laboratory of Brain–Computer Interfaces, Graz University of Technology, Krenngasse 37, 8010, Graz, Austria

    Brendan Z. Allison

Authors
  1. Brendan Z. Allison
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Brendan Z. Allison .

Editor information

Editors and Affiliations

  1. Otto Bock HealthCare GmbH, Max-Näder-Str. 15, Duderstadt, 37115, Germany

    Bernhard Graimann

  2. Institut für Semantische Datenanalyse/, Knowledge Discovery, Technische Universität Graz, Krenngasse 37, Graz, 8010, Austria

    Gert Pfurtscheller

  3. Inst. Semantische Datenanalyse, Brain-Computer Interface Labor (BCI), TU Graz, Krenngasse 37/III, Graz, 8010, Austria

    Brendan Allison

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Allison, B.Z. (2009). Toward Ubiquitous BCIs. In: Graimann, B., Pfurtscheller, G., Allison, B. (eds) Brain-Computer Interfaces. The Frontiers Collection. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02091-9_19

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-02091-9_19

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02090-2

  • Online ISBN: 978-3-642-02091-9

  • eBook Packages: Physics and AstronomyPhysics and Astronomy (R0)

Publish with us

Policies and ethics

Search

Navigation