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Australasian Joint Conference on Artificial Intelligence

AI 2015: AI 2015: Advances in Artificial Intelligence pp 498–504Cite as

Turning Gaming EEG Peripherals into Trainable Brain Computer Interfaces

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Part of the Lecture Notes in Computer Science book series (LNAI,volume 9457)

Abstract

Companies such as NeuroSky and Emotiv Systems are selling non-medical EEG devices for human computer interaction. These devices are significantly more affordable than their medical counterparts, and are mainly used to measure levels of engagement, focus, relaxation and stress. This information is sought after for marketing research and games. However, these EEG devices have the potential to enable users to interact with their surrounding environment using thoughts only, without activating any muscles. In this paper, we present preliminary results that demonstrate that despite reduced voltage and time sensitivity compared to medical-grade EEG systems, the quality of the signals of the Emotiv EPOC neuroheadset is sufficiently good in allowing discrimination between imaging events. We collected streams of EEG raw data and trained different types of classifiers to discriminate between three states (rest and two imaging events). We achieved a generalisation error of less than 2 % for two types of non-linear classifiers.

Keywords

  • EEG
  • Machine learning
  • Device control
  • BCI
  • K-nearest Neighbors
  • SVM

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References

  1. Emotiv Systems: Emotiv EPOC / EPOC+ (2014). https://emotiv.com/epoc.php

  2. Farwell, L.A., Donchin, E.: Talking off the top of your head: toward a mental prosthesis utilizing event-related brain potentials. Electroen. Clin. Neuro. 70(6), 510–523 (1988)

    CrossRef  Google Scholar 

  3. Guneysu, A., Akin, H.L.: An SSVEP based BCI to control a humanoid robot by using portable EEG device, vol. 2013, pp. 6905–6908. IEEE, United States (2013)

    Google Scholar 

  4. Hood, D., Joseph, D., Rakotonirainy, A., Sridharan, S., Fookes, C.: Use of brain computer interface to drive: preliminary results. In: Proceedings of the 4th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, AutomotiveUI 2012, pp. 103–106. ACM (2012). http://doi.acm.org/10.1145/2390256.2390272

  5. Jeannerod, M.: The representing brain: neural correlates of motor intention and imagery. Behav. Brain Sci. 17(2), 187–202 (1994)

    CrossRef  Google Scholar 

  6. Millett, D.: Hans berger: from psychic energy to the EEG. Perspect. Biol. Med. 44(4), 522–542 (2001)

    CrossRef  Google Scholar 

  7. Paxion, J., Galy, E., Berthelon, C.: Mental workload and driving. Front. Psychol. 5, 1344 (2014)

    CrossRef  Google Scholar 

  8. Pfurtscheller, G., Neuper, C.: Motor imagery and direct brain-computer communication. P. IEEE 89(7), 1123–1134 (2001)

    CrossRef  Google Scholar 

  9. Polich, J.: Updating P300: an integrative theory of P3a and P3b. Clin. Neurophysiol. 118(10), 2128–2148 (2007)

    CrossRef  Google Scholar 

  10. Prindle, D.: Thoughts into motion: Amazing brain-controlled devices that are already here (2012). http://www.digitaltrends.com/cool-tech/brain-control-the-user-interface-of-the-future/

  11. Raajan, N.R., Jayabhavani, G.N.: A smart way to play using brain machine interface (BMI), pp. 1130–1135. IEEE (2013)

    Google Scholar 

  12. Sanei, S., Chambers, J.: EEG Signal Processing: Fundamentals of EEG Signal Processing. Wiley, New York (2007)

    CrossRef  Google Scholar 

  13. Sheth, D., Benbadis, R.: EEG in common epilepsy syndromes (2014). http://emedicine.medscape.com/article/1138154-overview

  14. Singla, R., Chambayil, B., Khosla, A., Santosh, J.: Comparison of SVM and ANN for classification of eye events in EEG. J. Biomed. Sci. Eng. 4(1), 62–69 (2011)

    CrossRef  Google Scholar 

  15. Sutton, S., Braren, M., Zubin, J., John, E.R.: Evoked-potential correlates of stimulus uncertainty. Science 150(3700), 1187–1188 (1965)

    CrossRef  Google Scholar 

  16. Szafir, D., Signorile, R.: An exploration of the utilization of electroencephalography and neural nets to control robots. In: Campos, P., Graham, N., Jorge, J., Nunes, N., Palanque, P., Winckler, M. (eds.) INTERACT 2011, Part IV. LNCS, vol. 6949, pp. 186–194. Springer, Heidelberg (2011)

    CrossRef  Google Scholar 

  17. Vidal, J.J.: Toward direct brain-computer communication. Annu. Rev. Biophys. Bio. 2(1), 157–180 (1973)

    CrossRef  Google Scholar 

  18. Wolpaw, J.R., Birbaumer, N., Heetderks, W.J., McFarland, D.J., Peckham, P.H., Schalk, G., Donchin, E., Quatrano, L.A., Robinson, C.J., Vaughan, T.M.: Brain-computer interface technology: a review of the first international meeting. IEEE T. Rehabil. Eng. 8(2), 164–173 (2000)

    CrossRef  Google Scholar 

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Author information

Authors and Affiliations

  1. Science and Engineering Faculty, Queensland University of Technology, 2 George Street, Brisbane, 4078, Australia

    Manisha Senadeera & Frederic Maire

  2. Faculty of Health, Queensland University of Technology, 2 George Street, Brisbane, 4078, Australia

    Andry Rakotonirainy

Authors
  1. Manisha Senadeera
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  2. Frederic Maire
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  3. Andry Rakotonirainy
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Corresponding author

Correspondence to Frederic Maire .

Editor information

Editors and Affiliations

  1. The University of Waikato, Hamilton, New Zealand

    Bernhard Pfahringer

  2. The Australian National University, Canberra, Aust Capital Terr, Australia

    Jochen Renz

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Senadeera, M., Maire, F., Rakotonirainy, A. (2015). Turning Gaming EEG Peripherals into Trainable Brain Computer Interfaces. In: Pfahringer, B., Renz, J. (eds) AI 2015: Advances in Artificial Intelligence. AI 2015. Lecture Notes in Computer Science(), vol 9457. Springer, Cham. https://doi.org/10.1007/978-3-319-26350-2_44

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  • DOI: https://doi.org/10.1007/978-3-319-26350-2_44

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26349-6

  • Online ISBN: 978-3-319-26350-2

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