A Tongue-Machine Interface: Detection of Tongue Positions by Glossokinetic Potentials

  • Yunjun Nam
  • Qibin Zhao
  • Andrzej Cichocki
  • Seungjin Choi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6444)

Abstract

Artifacts are electrical activities that are detected along the scalp by an electroencephalography (EEG) but that originate from non-cerebral origin, which often need to be eliminated before further processing of EEG signals. Glossokinetic potentials are artifacts related to tongue movements. In this paper we use these glossokinetic artifacts (instead of eliminating them) to automatically detect and classify tongue positions, which is important in developing a tongue-machine interface. We observe that with a specific selection of a few electrode positions, glossokinetic potentials show contralateral patterns, so that the magnitude of potentials is linearly proportional to the tongue positions flicking at the left to the right inside of cheek. We design a simple linear model based on principal component analysis (PCA) to translate glossokinetic potentials into tongue positions. Experiments on cursor control confirm the validity of our method for tongue position detection using glossokinetic potentials.

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References

  1. 1.
    Krishnamurthy, G., Ghovanloo, M.: Tongue drive: A tongue operated magnetic sensor based wireless assistive technology for people with severe disabilities. In: Proceedings of the IEEE International Symposium on Circuits and Systems (ISCAS), Island of Kos, Greece, pp. 5551–5554 (2006)Google Scholar
  2. 2.
    Huo, X., Ghovanloo, M.: Using unconstrained tongue motion as an alternative control mechanism for wheeled mobility. IEEE Transactions on Biomedical Engineering 56(6), 1719–1726 (2009)CrossRefGoogle Scholar
  3. 3.
    Struijk, L.N.S.A.: An inductive tongue computer interface for control of computers and assistive devices. IEEE Transactions on Biomedical Engineering 53(12), 2594–2597 (2006)CrossRefGoogle Scholar
  4. 4.
    ThinkAMove: (Introduction to think-a-move’s technology), http://www.think-a-move.com/pdfs/Intro_to_TAM_Technology.pdf (accessed 6/14/10)
  5. 5.
    Nutt, W., Arlanch, C., Nigg, S., Staufert, G.: Tongue-mouse for quadriplegics. Journal of Micromechanics and Microengineering 8, 155–157 (1998)CrossRefGoogle Scholar
  6. 6.
    TongueTouchKeypad (Tonguetouch keypadTM), http://newabilities.com
  7. 7.
    Salem, C., Zhai, S.: An isometric tongue pointing device. In: Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI), pp. 538–359 (1997)Google Scholar
  8. 8.
    Klass, D., Bickford, R.G.: Glossokinetic potentials appearing in the electroencephalogram. EEG and Clinical Neurophysilology 12 (1960)Google Scholar
  9. 9.
    Fisch, B.J.: Fisch and Spehlmann’s EEG Primer, 3rd edn. Elsevier, Amsterdam (1999)Google Scholar
  10. 10.
    Vanhatalo, S., Dewaraja, A., Holmes, M.D., Miller, J.W.: Topography and elimination of slow EEG responses related to tongue movements. NeuroImage 20, 1419–1423 (2003)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Yunjun Nam
    • 1
  • Qibin Zhao
    • 2
  • Andrzej Cichocki
    • 2
  • Seungjin Choi
    • 1
    • 3
    • 4
  1. 1.School of Interdisciplinary Bioscience and BioengineeringPohang University of Science and TechnologyPohangKorea
  2. 2.Lab for Advanced Brain Signal Processing, Brain Science InstituteRIKENJapan
  3. 3.Department of Computer SciencePohang University of Science and TechnologyPohangKorea
  4. 4.Division of IT Convergence EngineeringPohang University of Science and TechnologyPohangKorea

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