AN ECoG BASED BRAIN COMPUTER INTERFACE WITH SPATIALLY ADAPTED TIME-FREQUENCY PATTERNS

Nuri F. Ince, Fikri Goksu, Ahmed H. Tewfik

2008

Abstract

In this paper we describe an adaptive approach for the classification of multichannel electrocorticogram (ECoG) recordings for a Brain Computer Interface. In particular the proposed approach implements a time-frequency plane feature extraction strategy from multichannel ECoG signals by using a dual-tree undecimated wavelet packet transform. The dual-tree undecimated wavelet packet transform generates a redundant feature dictionary with different time-frequency resolutions. Rather than evaluating the individual discrimination performance of each electrode or candidate feature, the proposed approach implements a wrapper strategy to select a subset of features from the redundant structured dictionary by evaluating the classification performance of their combination. This enables the algorithm to optimally select the most informative features coming from different cortical areas and/or time frequency locations. We show experimental classification results on the ECoG data set of BCI competition 2005. The proposed approach achieved a classification accuracy of 93% by using only three features.

References

  1. Ince N. F., Tewfik A., Arica S., 2007, “Extraction subjectspecific motor imagery time-frequency patterns for single trial EEG classification”, Comp. Biol. Med. Elsevier.
  2. Ince N. F., Arica S., Tewfik A., 2007, “Classification of single trial motor imagery EEG recordings by using subject adapted non-dyadic arbitrary time-frequency tilings,” J. Neural Eng. 3, 235-244.
  3. Lal Thomas N., et.al., 2005, Methods Towards Invasive Human Brain Computer Interfaces. Advances in Neural Information Processing Systems (NIPS17, 737- 744. (Eds.) Saul, L. K., Y. Weiss, L. Bottou, MIT Press, Cambridge, MA, USA).
  4. Leuthardt E. C. , Schalk G., Wolpaw J. R., Ojemann J. G. and Moran D. W., 2004, A brain-computer interface using electrocorticographic signals in humans, Journal of Neural Engineering, pp. 63-71.
  5. Pfurtscheller G., Neuper C., 2001. Motor Imagery and Direct Brain-Computer Interface. Proceedings of IEEE, vol.89, pp. 1123-1134.
  6. Prezenger M., Pfurtscheller G., 1999. Frequency component selection for an EEG-based brain computer interface. IEEE Trans. on Rehabil. Eng. 7, pp. 413- 419.
  7. Ramoser H., Müller-Gerking J., and Pfurtscheller G., 2000. Optimal spatial filtering of single trial EEG during imagined hand movement. IEEE Trans. Rehab. Eng., vol. 8, no. 4, pp. 441-446.
  8. Saito N. et al., 2002, Discriminant feature extraction using empirical probability density and a local basis library, Pattern Recognition, vol.35, pp. 1842-1852.
  9. Schlögl A., Flotzinger D., Pfurtscheller G., 1997. Adaptive autoregressive modeling used for single trial EEG classification. Biomed. Technik,42, pp. 162-167.
  10. Unser M., 1995. Texture classification and segmentation using wavelet frames. IEEE Trans. Image Proc., pp. 1549-60, Vol.4(11), Nov.
  11. Vetterli M., 2001. Wavelets, approximation, and compression,7878 IEEE Signal Proc. Magazine, pp. 59- 73, Sept..
  12. Wang T., and B. He, 2004. Classifying EEG-based motor imagery tasks by means of time-frequency synthesized spatial patterns. Clin. Neuro. vol.115, pp. 2744-2753.
  13. Wolpaw J. R., et.al., 2000. Brain-Computer Interface Technology: A review of the first international meeting, IEEE Trans. On Rehab. Eng. 8 164-73.
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Paper Citation


in Harvard Style

F. Ince N., Goksu F. and H. Tewfik A. (2008). AN ECoG BASED BRAIN COMPUTER INTERFACE WITH SPATIALLY ADAPTED TIME-FREQUENCY PATTERNS . In Proceedings of the First International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2008) ISBN 978-989-8111-18-0, pages 132-139. DOI: 10.5220/0001068701320139


in Bibtex Style

@conference{biosignals08,
author={Nuri F. Ince and Fikri Goksu and Ahmed H. Tewfik},
title={AN ECoG BASED BRAIN COMPUTER INTERFACE WITH SPATIALLY ADAPTED TIME-FREQUENCY PATTERNS},
booktitle={Proceedings of the First International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2008)},
year={2008},
pages={132-139},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001068701320139},
isbn={978-989-8111-18-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the First International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2008)
TI - AN ECoG BASED BRAIN COMPUTER INTERFACE WITH SPATIALLY ADAPTED TIME-FREQUENCY PATTERNS
SN - 978-989-8111-18-0
AU - F. Ince N.
AU - Goksu F.
AU - H. Tewfik A.
PY - 2008
SP - 132
EP - 139
DO - 10.5220/0001068701320139