Development of a Tiny Computer-Assisted Wireless EEG Biofeedback System

  • Haifeng Chen
  • Ssanghee Seo
  • Donghee Ye
  • Jungtae Lee
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4684)


This paper describes an on-going research to develop a Brain-Computer Interface (BCI) with which to conduct biofeedback training. A convenient portable wireless two-channel tiny Electroencephalogram (EEG) acquisition device has been developed for this study, which is based on Radio Frequency (RF) technology, and we developed a computer assisted EEG biofeedback system using Virtual Reality which provides an ideal medium to represent the spatial and temporal environment of electrical activity emanating from the brain. A system prototype system has been implemented with the proposed device for attention enhancement training with Virtual Reality (VR) environment, and 3 volunteers’ test results are reported in this paper. With the proposed system, lots of EEG biofeedback training can be designed easily and done at home in our daily life conveniently.


Electroencephalogram EEG biofeedback Attention Enhancement Training 


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  1. 1.
    Zousen, Z., Weiming, C.: Development of EEG biofeedback system and research of the biofeedback in the alpha frequency band. In: Proceedings of Annual International Conference of the IEEE Engineering in Medicine and Biology Society, New Orleans LA, USA, pp. 1482–1483. IEEE Computer Society Press, Los Alamitos (1988)Google Scholar
  2. 2.
    Allanson, J., Mariani, J.: Mind Over Virtual Matter: Using Virtual Environments for Neurofeedback Training. In: Proceedings of IEEE Virtual Reality Annual International Symposium, pp. 270–273 (1999)Google Scholar
  3. 3.
    Othmer, S., Kaiser, D.: Implementation of Virtual Reality in EEG Biofeedback. Cyberpsychology & Behavior 3(3), 415–420 (2000)CrossRefGoogle Scholar
  4. 4.
    Grin’-Yatsenko, V.A., Kropotov, Y.D., Ponomarev, V.A., Chutko, L.S., Yakovenko, E.A.: Effect of Biofeedback Training of Sensorimotor and β1 EEG Rhythms on Attention Parameters. Human Physiology 27(3), 259–266 (2001)CrossRefGoogle Scholar
  5. 5.
    Cho, B.H., Lee, J.M., Ku, J.H., Jang, D.P., Kim, J.S., Kim, I.Y., Lee, J.H., Kim, S.I.: Attention Enhancement System using Virtual Reality and EEG Biofeedback. In: Proceedings of IEEE Virtual Reality 2002, Orlando FL, USA, pp. 156–163. IEEE Computer Society Press, Los Alamitos (2002)CrossRefGoogle Scholar
  6. 6.
    Congedo, M., Lubar, J.F., Joffe, D.: Low-Resolution Electromagnetic Tomography Neurofeedback. IEEE Transactions on Neural Systems and Behabilitation Engineering 12(4), 387–397 (2004)CrossRefGoogle Scholar
  7. 7.
    Maricic, A., Leang, H.P.: Biofeedback Computer Game-based Training. In: Proceedings of the 47th International Symposium ELMAR, Zadar, Crotia, pp. 185–188 (2005)Google Scholar
  8. 8.
    Monastra, V.J., Lynn, S., Linden, M., Lubar, J.F., Gruzelier, J., LaVaque, T.J.: Electroencephalographic Biofeedback in the Treatment of Attention-Deficit/Hyperactivity Disorder. Applied Psychophysiology and Biofeedback 30(2), 95–114 (2005)CrossRefGoogle Scholar
  9. 9.
    Burdea, G.: Virtual Reality Systems and Applications. In: Proceedings of Electro 1993 International Conference, NJ, USA, pp. 164–167 (1993)Google Scholar
  10. 10.
    CC1020 datasheet, Texas Instruments, focus.
  11. 11.
    INA128 datasheet, Texas Instruments, focus.
  12. 12.
    LMC6464 datasheet, National Semiconductors,

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Haifeng Chen
    • 1
  • Ssanghee Seo
    • 1
  • Donghee Ye
    • 1
  • Jungtae Lee
    • 1
  1. 1.Department of Computer Science & Engineering, Pusan National University San-30, Jangjeon-Dong, Geumjeon-Gu, Busan, 609-735Republic of Korea

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