A Study of an EMG-controlled HCI Method by Clenching Teeth

  • Hyuk Jeong
  • Jong-Sung Kim
  • Jin-Seong Choi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3101)


In this paper, a new Human-Computer-Interaction (HCI) method for a quadriplegic, which is controlled by clenching teeth, is proposed. By simple combination of two clenching patterns, seven instructions including rest, up, down, left and right as well as click and double click actions are made for the control of a pointing device. The control source is EMGs (electromyograms), which are generated by clenching teeth and acquired on two temporal muscles in one’s forehead. For easy-to-wear, the prototype device is designed for attaching EMG electrodes on a forehead by using a headband. Stochastic values such as difference absolute mean value are used for feature extractions and Fuzzy Min-Max Neural Network (FMMNN) is used for classifying clenching patterns. The usefulness of the proposed system is confirmed by the user test.


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  1. 1.
    Park, S.H.: The Biosignal Processing and Application, Edtech (1999)Google Scholar
  2. 2.
    Delsys Inc., Surface Electromyography: Detection and Recording, Delsys Tutorial (1996)Google Scholar
  3. 3.
    Rosenberg, R.: The Biofeedback Pointer: EMG Control of a Two Dimensional Pointer. In: Second International Symposium on Wearable Computers, pp. 162–163 (1998)Google Scholar
  4. 4.
    Tarng, Y.H., Chang, G.C., Lai, J.S., Kuo, T.S.: Design of the Human/Computer Interface for Human with Disability Using Myoelectric Signal Control. In: Proceedings of the 19th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, vol. 5, pp. 1909–1910 (1997)Google Scholar
  5. 5.
    Tsuji, T., Fukuda, O., Murakami, M., Kaneko, M.: An EMG Controlled Pointing Device Using a Neural Network. Transactions of the Society of Instrument and Control Engineers 37(5), 425–431 (2001)Google Scholar
  6. 6.
    Jeong, H., Choi, C.S.: An EMG-Controlled Graphic Interface Considering Wearability. In: Proceeding of the Human-Computer Interaction-INTERACT 2003, pp. 958–961 (2003)Google Scholar
  7. 7.
    Han, J.S., Bien, Z.Z., Kim, D.J., Lee, H.E., Kim, J.S.: Human-Machine Interface for Wheel-chair Control With EMG and Its Evaluation. In: Proc. EMBS 2003, pp. 1602–1605 (2003)Google Scholar
  8. 8.
    Delagi, E.F., Iazzetti, J., Perotto, A., Morrison, D.: Anatomical Guide For The Electro-myographer. The Limbs and Trunk, Springfield (1994)Google Scholar
  9. 9.
    Simpson, P.K.: Fuzzy Min-Max Neural Networks-Part 1: Classification. IEEE Trans, On Neural Networks 3(5), 776–786 (1992)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Hyuk Jeong
    • 1
  • Jong-Sung Kim
    • 1
  • Jin-Seong Choi
    • 1
  1. 1.Digital Content Research DivisionElectronics and Telecommunications Research InstituteDaejeonKorea

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