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Polish Information Processing Society
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Annals of Computer Science and Information Systems, Volume 8

Proceedings of the 2016 Federated Conference on Computer Science and Information Systems

Semiotic Training for Brain-Computer Interfaces

DOI: http://dx.doi.org/10.15439/2016F75

Citation: Proceedings of the 2016 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 8, pages 921–925 ()

Full text

Abstract. With time education becomes more personified. New categories of learners join in educational processes and new areas of education appear. Brain-computer interfaces have good perspective to contribute to these tendencies. This technology may allow disabled people to participate in social life, including education, and may let healthy people to develop the skill of controlling brain waves. Training the skill is the object of investigation and researchers recommend taking into account human factors: general principles of learning, motivations, personal patterns and abilities (among them, spatial). Education may be a source of highly motivated training tasks. The paper treats brain-computer interface as a type of communication and argues for semiotic training that is a variant of training spatial abilities. Semiotic training have proved effectiveness in other areas of education. Theoretical background and preliminary empirical comments of the approach are considered.

References

  1. Jan B.F. Van Erp, F. Lotte, M. Tangermann, “Brain-computer interfaces: beyond medical applications”, Computer -IEEE Computer Society-, IEEE, 2012, 45 (4), pp.26-34. http://doi.ieeecomputersociety.org/10.1109/MC.2012.107.
  2. C. Ring, A. Cooke, M. Kaussanu, D. Mclntyre, R. Masters, “Investigating the efficiency of neurofeedback training for expediting expertise and excellence in sport”, in Psychology of sport and exercise, vol. 16, part 1, January 2015, pp. 118-127. http://dx.doi.org/10.1016/j.psychsport.2014.08.005.
  3. B. Sabitzer, “Neurodidactics – a new stimulus in ICT and computer science education”, INTED2011 Proceedings, 2011, pp. 5881-5889.
  4. M. Ferrari and H. McBride, “Mind, Brain, and Education: The Birth of a New Science”, in LEARNing Landscapes, vol. 5, No. 1, autumn 2011, pp. 85-100.
  5. J. E. Garrido, V. M. R. Penichet, M. D. Lozano and L. A. Sánchez, "Mobility and memory training through movement interaction," Computer Science and Information Systems (FedCSIS), 2012 Federated Conference on, Wroclaw, 2012, pp. 883-889.
  6. F. Lotte, F. Larrue, Ch. Mühl, “Flaws in current human training protocols for spontaneous brain-computer interfaces: lessons learned from instructional design”, in Frontiers in Human Neuroscience, 2013, vol. 7, N 568 (11 p.). http://dx.doi.org/10.3389/fnhum.2013.00568.
  7. C. Neuper and G. Pfurtscheller, “Neurofeedback training for BCI control”, in Brain-computer interfaces, Eds. B. Graimann, G. Pfurtscheller and B. Allison, London: Springer, 2010, pp. 65–78. http://dx.doi.org/10.1007/978-3-642-02091-9_4.
  8. H.-J. Hwang, K. Kwon, and C.-H. Im, “Neurofeedback-based motor imagery training for brain-computer interface (BCI)”, in Journal of neuroscience methods, vol. 179, issue 1, April 2009. Pp. 150-156. http://dx.doi.org/10.1016/j.jneumeth.2009.01.015.
  9. Brain-computer interfaces. Revolutionizing human-computer interaction. The Frontiers Collection. Eds. B. Graimann, G. Pfurtscheller and B. Allison, London: Springer, 2010, 393 p. DOI: 10.1007/978-3-642-02091-9.
  10. C. Jeunet, B. N’Kaoua, S. Subramanian, M. Hacher, and F. Lotte, “Predicting mental imagery-based BCI performance from personality, cognitive profile and neurophysiological patterns”, PLOS ONE, vol. 10 (12): Dec. 2015. http://dx.doi.org/http://dx.doi.org/10.1371/journal.pone.0143962.
  11. F. Lotte, C. Jeunet, “Towards improved BCI based on human learning principles”, 3rd International Winter Conference on Brain-Computer Interfaces, High1 Resort, South Korea, Jan. 2015, <hal-01111843>. http://dx.doi.org/10.1109/IWW-BCI.2015.7073024.
  12. F. de Saussure, Course in general linguistics, trans. Roy Harris, [1916] London: Duckworth, 1983.
  13. C. S. Peirce, Collected writings (8 Vols.), Ed. Charles Hartshorne, Paul Weiss and Arthur W. Burks, Cambridge, MA: Harvard University Press, 1931-58.
  14. W. C. Stokoe, “Sign Language structure: an outline of the visual communication systems of the American deaf”, in J. of Deaf Studies and Deaf Education. 2005; 10(1), pp. 3-37. http://dx.doi.org/10.1093/deafed/eni001.
  15. M. Huenerfauth, “A survey and critique of American Sign Language natural language generation and machine translation systems”, Technical Report MS-CIS-03-32, Computer and Information Science, University of Pennsylvania, 2003, 36 p.
  16. A. Kibrik, The methodology of field investigations in linguistics (setting up the problem), Janua Linguarum. Series Minor, 142, The Hague/Paris: Mouton, 1977, 130 p.
  17. H. Gleason, An introduction to descriptive linguistics, rev. ed., New York: Holt. Rinehart & Winston, 1961, 503 p.
  18. N. Cohn, “Comics, linguistics, and visual language: the past and the future of a field”, in F. Bramlett (Ed.), Linguistics and the study of comics, New York: Palgrave MacMillan, 2012, pp. 92-118. http://dx.doi.org/10.1057/9781137004109_5.
  19. H.Erhan, B. Yousuf, and B. Berry, “Teaching Spatial Thinking in Design Computation Contexts: Challenges and Opportunities”, in N. Gu, & X. Wang (Eds.) Computational Design Methods and Technologies: Applications in CAD, CAM and CAE Education, 2012, pp. 365-389 (chapter 21). Hershey, PA: Information Science Reference. http://dx.doi.org/10.4018/978-1-61350-180-1.ch021.
  20. A. Doxiadis, C. H. Papadimitriou, Logicomix: An Epic Search for Truth, London: Bloomsbury Publishing PLC, 2009, 352 p.