Skip to main content
SpringerLink
Log in
Book cover

International Conference on Intelligent Data Engineering and Automated Learning

IDEAL 2018: Intelligent Data Engineering and Automated Learning – IDEAL 2018 pp 821–828Cite as

Peak Alpha Based Neurofeedback Training Within Survival Shooter Game

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11314))

Abstract

Neurofeedback has been proven to be a useful tool in games, music or video applications for both treating various disorders and disabilities, as well as potentially enhancing cognitive functions of healthy individuals. However, most neurofeedback protocols are tedious to use, and the usefulness of the results is difficult to validate. In this paper, we present a framework that allows connecting various types of neurofeedback protocols inside a computer game in a way that the user can gain full benefits of the neurofeedback based training by simply playing a game. The paper outlines the full potential of cognitive training and its effectiveness when implemented in an entertaining scenario.

This is a preview of subscription content, 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   84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
Price excludes VAT (USA)
  • Compact, lightweight 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

Learn about institutional subscriptions

References

  1. Angelakis, E., Stathopoulou, S., Frymiare, J.L., Green, D.L., Lubar, J.F., Kounios, J.: EEG neurofeedback: a brief overview and an example of peak alpha frequency training for cognitive enhancement in the elderly. Clin. Neuropsychol. 21(1), 110–129 (2007)

    Article  Google Scholar 

  2. Arns, M., Heinrich, H., Ros, T., Rothenberger, A., Strehl, U.: Neurofeedback in ADHD. Front. Hum. Neurosci. 9, 602 (2015)

    Article  Google Scholar 

  3. Bazanova, O.M., Auer, T., Sapina, E.: On the efficiency of individualized theta/beta ratio neurofeedback combined with forehead emg training in ADHD children. Front. Hum. Neurosci. 12, 3 (2018)

    Article  Google Scholar 

  4. Davelaar, E.J.: Mechanisms of neurofeedback: a computation-theoretic approach. Neuroscience 378, 175–188 (2017)

    Article  Google Scholar 

  5. Egner, T., Strawson, E., Gruzelier, J.H.: EEG signature and phenomenology of alpha/theta neurofeedback training versus mock feedback. Appl. Psychophysiol. Biofeedback 27(4), 261 (2002)

    Article  Google Scholar 

  6. Escolano, C., Navarro-Gil, M., Garcia-Campayo, J., Congedo, M., De Ridder, D., Minguez, J.: A controlled study on the cognitive effect of alpha neurofeedback training in patients with major depressive disorder. Front. Behav. Neurosci. 8, 296 (2014)

    Article  Google Scholar 

  7. Fernández, T., et al.: EEG and behavioral changes following neurofeedback treatment in learning disabled children. Clin. EEG Neurosci. 34(3), 145–152 (2003). https://doi.org/10.1177/155005940303400308

    Article  Google Scholar 

  8. Ghasemian, M., Taheri, H., Kakhki, A.S., Ghoshuni, M.: The effect of alpha neurofeedback training on motor skill acquisition. Biosci. Biotechnol. Res. Asia 13(3), 1651–1656 (2016)

    Article  Google Scholar 

  9. Gruzelier, J.H.: EEG-neurofeedback for optimising performance. I: a review of cognitive and affective outcome in healthy participants. Neurosci. Biobehav. Rev. 44, 124–141 (2014)

    Article  Google Scholar 

  10. Hsueh, J.J., Chen, T.S., Chen, J.J., Shaw, F.Z.: Neurofeedback training of EEG alpha rhythm enhances episodic and working memory. Hum. Brain Mapp. 37(7), 2662–2675 (2016)

    Article  Google Scholar 

  11. Jurewicz, K., Paluch, K., Kublik, E., Rogala, J., Mikicin, M., Wróbel, A.: EEG-neurofeedback training of beta band (12–22 Hz) affects alpha and beta frequencies-a controlled study of a healthy population. Neuropsychologia 108, 13–24 (2018)

    Article  Google Scholar 

  12. Keizer, A.W., Verment, R.S., Hommel, B.: Enhancing cognitive control through neurofeedback: a role of gamma-band activity in managing episodic retrieval. Neuroimage 49(4), 3404–3413 (2010)

    Article  Google Scholar 

  13. Kober, S.E., et al.: Specific effects of EEG based neurofeedback training on memory functions in post-stroke victims. J. Neuroeng. Rehabil. 12(1), 107 (2015)

    Article  Google Scholar 

  14. Kosunen, I., Salminen, M., Järvelä, S., Ruonala, A., Ravaja, N., Jacucci, G.: Relaworld: neuroadaptive and immersive virtual reality meditation system. In: Proceedings of the 21st International Conference on Intelligent User Interfaces, pp. 208–217. ACM (2016)

    Google Scholar 

  15. Kouijzer, M.E., de Moor, J.M., Gerrits, B.J., Buitelaar, J.K., van Schie, H.T.: Long-term effects of neurofeedback treatment in autism. Res. Autism Spectr. Disord. 3(2), 496–501 (2009). https://doi.org/10.1016/j.rasd.2008.10.003

    Article  Google Scholar 

  16. Kuikkaniemi, K., Laitinen, T., Turpeinen, M., Saari, T., Kosunen, I., Ravaja, N.: The influence of implicit and explicit biofeedback in first-person shooter games. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 859–868. ACM (2010)

    Google Scholar 

  17. Lubar, J., Swartwood, M., Swartwood, J., O’Donnell, P.: Evaluation of the effectiveness of EEG neurofeedback training for ADHD in a clinical setting as measured by changes in T.O.V.A. scores, behavioral ratings, and WISC-R performance. Biofeedback Self-regul. 20(1), 83–99 (1995). https://doi.org/10.1007/BF01712768

    Article  Google Scholar 

  18. Marzbani, H., Marateb, H.R., Mansourian, M.: Neurofeedback: a comprehensive review on system design, methodology and clinical applications. Basic Clin. Neurosci. 7(2), 143 (2016)

    Google Scholar 

  19. Mierau, A., et al.: The interrelation between sensorimotor abilities, cognitive performance and individual EEG alpha peak frequency in young children. Clin. Neurophysiol. 127(1), 270–276 (2016)

    Article  Google Scholar 

  20. Pineda, J.A., Silverman, D.S., Vankov, A., Hestenes, J.: Learning to control brain rhythms: making a brain-computer interface possible. IEEE Trans. Neural Syst. Rehabil. Eng. 11(2), 181–184 (2003)

    Article  Google Scholar 

  21. Stein, A., Yotam, Y., Puzis, R., Shani, G., Taieb-Maimon, M.: EEG-triggered dynamic difficulty adjustment for multiplayer games. Entertain. Comput. 25, 14–25 (2018)

    Article  Google Scholar 

  22. Sterman, M., Egner, T.: Foundation and practice of neurofeedback for the treatment of epilepsy. Appl. Psychophysiol. Biofeedback 31(1), 21–35 (2006). https://doi.org/10.1007/s10484-006-9002-x

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. University of Craiova, Craiova, Romania

    Radu AbuRas, Gabriel Turcu & Marian Cristian Mihaescu

  2. University of Tallinn, Tallinn, Estonia

    Ilkka Kosunen

Authors
  1. Radu AbuRas
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Gabriel Turcu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ilkka Kosunen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Marian Cristian Mihaescu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Radu AbuRas .

Editor information

Editors and Affiliations

  1. University of Manchester, Manchester, UK

    Hujun Yin

  2. Autonomous University of Madrid, Madrid, Spain

    David Camacho

  3. Campus of Gualtar, University of Minho, Braga, Portugal

    Paulo Novais

  4. University of Seville, Seville, Spain

    Antonio J. Tallón-Ballesteros

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

AbuRas, R., Turcu, G., Kosunen, I., Mihaescu, M.C. (2018). Peak Alpha Based Neurofeedback Training Within Survival Shooter Game. In: Yin, H., Camacho, D., Novais, P., Tallón-Ballesteros, A. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2018. IDEAL 2018. Lecture Notes in Computer Science(), vol 11314. Springer, Cham. https://doi.org/10.1007/978-3-030-03493-1_85

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-03493-1_85

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-03492-4

  • Online ISBN: 978-3-030-03493-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation