SVM EVALUATION FOR BRAIN COMPUTER INTERFACE SYSTEMS

Mario Salerno, Giovanni Costantini, Daniele Casali, Giancarlo Orengo, Pietro Cavallo, Giovanni Saggio, Luigi Bianchi, Lucia Quitadamo, Maria Grazia Marciani

Abstract

A Support Vector Machine (SVM) classification method for data acquired by EEG registration for brain/computer interface systems is here proposed. The aim of this work is to evaluate the SVM performances in the recognition of a human mental task, among others. Such methodology could be very useful in important applications for disabled people. A prerequisite has been the developing of a system capable to recognize and classify the following four tasks: thinking to move the right hand, thinking to move the left hand, performing a simple mathematical operation, and thinking to a nursery rhyme. The data set exploited in the training and testing phases has been acquired by means of 61 EEG electrodes and consists of several time series. These time data sets were then transformed into the frequency domain, in order to obtain the power frequency spectrum. In such a way, for every electrode, 128 frequency channels were obtained. Finally, the SVM algorithm was used and evaluated to get the proposed classification.

References

  1. Huan N. J. and Palaniappan R., 2004. Neural network classification of autoregressive features from electroencephalogram signals for brain-computer interface design. In Journal of Neural Engineering vol. 1, 142-150.
  2. Wolpaw J. R., Birbaumer N. McFarland D. J, Pfurtscheller G. and Vaughan T. M. 2002. Brain-computer interfaces for communication and control. In Clinical.Neurophysiology, vol. 113, no. 6, , pp. 767- 791.
  3. Schogl, A. Lee F., Bischof H.and Pfurtscheller G., 2005 Characterization of four-class motor imagery EEG data for the BCI-competition. In Journal of NeuralEngineering, vol. 2, L14-L22.
  4. Yoo S.S., Fairneny T., Chen N. K., Choo S. E., Panych P., Park H., Lee S. Y., Jolesz F. A., 2004. “Braincomputer interface using fMRI: spatial navigation by thoughts”, In Neuroreport. Jul 19;15(10):1591-5.
  5. Sharbrough F, Chatrian G-E, Lesser RP, Lüders H, Nuwer M, Picton TW., 1991. American Electroencephalographic Society Guidelines for Standard Electrode Position Nomenclature. In J. Clin. Neurophysiol 8: 200-2.
  6. Blankertz B., Dornhege G., Krauledat M., Müller K.-R., Kunzmann V., Losch F., Curio G., 2006. The Berlin Brain-Computer Interface: EEG-based communication without subject training. In Transactions On Neural Systems And Rehabilitation Engineering, Vol. 14, Issue 2, pp. 147-152.
  7. Brazier, M. A. B., 1970. The Electrical Activity of the Nervous System, Pitman, London.
  8. Ward LM, Doesburg SM, Kitajo K, MacLean SE, Roggeveen AB., 2006. Neural synchrony in stochastic resonance, attention, and consciousness. In Can J Exp Psychol. Dec;60(4):319-26.
  9. Walker, 1999. Chambers Dictionary of Science and Technology, Chambers Harrap Publishers, 2nd ed., p. 312, P.M.B.
  10. Jolliffe I.T., 2002. Principal Component Analysis, 2nd ed., Springer, NY.
  11. Burges C.J.C., 1998. A tutorial on support vector machines for pattern recognition. In Data Mining and Knowledge Discovery 2, Kluwer, 1998, pp.121-167.
  12. Joachims T., 1999. Making large scale SVM learning practical.
  13. Scholkopf B., Burges C.J.C. and Smola A.J., 1999. Advances in Kernel Methods-Support Vector Learning, Eds, MIT Press, Cambridge, MA, 1999, pp. 169-184 (http://svmlight.joachims.org/).
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Paper Citation


in Harvard Style

Salerno M., Costantini G., Casali D., Orengo G., Cavallo P., Saggio G., Bianchi L., Quitadamo L. and Grazia Marciani M. (2010). SVM EVALUATION FOR BRAIN COMPUTER INTERFACE SYSTEMS . In Proceedings of the Third International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2010) ISBN 978-989-674-018-4, pages 240-244. DOI: 10.5220/0002721802400244


in Bibtex Style

@conference{biosignals10,
author={Mario Salerno and Giovanni Costantini and Daniele Casali and Giancarlo Orengo and Pietro Cavallo and Giovanni Saggio and Luigi Bianchi and Lucia Quitadamo and Maria Grazia Marciani},
title={SVM EVALUATION FOR BRAIN COMPUTER INTERFACE SYSTEMS},
booktitle={Proceedings of the Third International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2010)},
year={2010},
pages={240-244},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002721802400244},
isbn={978-989-674-018-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Third International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2010)
TI - SVM EVALUATION FOR BRAIN COMPUTER INTERFACE SYSTEMS
SN - 978-989-674-018-4
AU - Salerno M.
AU - Costantini G.
AU - Casali D.
AU - Orengo G.
AU - Cavallo P.
AU - Saggio G.
AU - Bianchi L.
AU - Quitadamo L.
AU - Grazia Marciani M.
PY - 2010
SP - 240
EP - 244
DO - 10.5220/0002721802400244