Table of Contents Author Guidelines Submit a Manuscript
Computational Intelligence and Neuroscience
Volume 2007, Article ID 28692, 12 pages
http://dx.doi.org/10.1155/2007/28692
Research Article

Enhanced Detection of Visual-Evoked Potentials in Brain-Computer Interface Using Genetic Algorithm and Cyclostationary Analysis

Department of Computing and Electronic Systems, University of Essex, Wivenhoe Park, Colchester CO4 3SQ, UK

Received 18 February 2007; Accepted 4 July 2007

Academic Editor: Andrzej Cichocki

Copyright © 2007 Cota Navin Gupta and Ramaswamy Palaniappan. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. K. E. Misulis, Sphelmann's Evoked Potential Primer: Visual, Auditory, and Somatosensory Evoked Potentials in Clinical Diagnosis, Butterworth-Heinemann, Oxford, UK, 1994.
  2. J. I. Aunon, C. D. McGillem, and D. G. Childers, “Signal processing in event potential research: averaging and modelling,” CRC Critical Reviews in Bioengineering, vol. 5, pp. 323–367, 1981.
  3. D. H. Lange, H. T. Siegelmann, H. Pratt, and G. F. Inbar, “Overcoming selective ensemble averaging: unsupervised identification of event-related brain potentials,” IEEE Transactions on Biomedical Engineering, vol. 47, no. 6, pp. 822–826, 2000. View at Publisher · View at Google Scholar
  4. C. T. Handy, Event-Related Potentials: A Methods Handbook, MIT Press, Cambridge, Mass, USA, 2005.
  5. M. Kutas, G. McCarthy, and E. Donchin, “Augmenting mental chronometry: the P300 as a measure of stimulus evaluation time,” Science, vol. 197, no. 4305, pp. 792–795, 1977. View at Publisher · View at Google Scholar
  6. E. Donchin, W. Ritter, and C. McCallum, “Cognitive psychophysiology: the endogenous components of the ERP,” in Brain Event-Related Potentials in Man, E. Callaway, P. Tueting, and S. H. Koslow, Eds., pp. 349–411, Academic Press, New York, NY, USA, 1978.
  7. M. G. H. Coles and M. D. Rugg, “Event-related brain potentials: an introduction,” in Electrophysiology of Mind: Event-Related Brain Potentials and Cognition, M. D. Rugg and M. G. H. Coles, Eds., pp. 1–26, Oxford University Press, New York, NY, USA, 1995.
  8. E. Donchin, K. M. Spencer, and R. Wijesinghe, “The mental prosthesis: assessing the speed of a P300-based brain-computer interface,” IEEE Transactions on Rehabilitation Engineering, vol. 8, no. 2, pp. 174–179, 2000. View at Publisher · View at Google Scholar
  9. H. Serby, E. Yom-Tov, and G. F. Inbar, “An improved P300-based brain-computer interface,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 13, no. 1, pp. 89–98, 2005. View at Publisher · View at Google Scholar · View at PubMed
  10. L. A. Farwell and E. Donchin, “Talking off the top of your head: toward a mental prosthesis utilizing event-related brain potentials,” Electroencephalography and Clinical Neurophysiology, vol. 70, no. 6, pp. 510–523, 1988. View at Publisher · View at Google Scholar
  11. C. D. Woody, “Characterization of an adaptive filter for the characterization of variable latency neuroelectric signals,” Medical and Biological Engineering and Computing, vol. 5, no. 6, pp. 539–553, 1967. View at Publisher · View at Google Scholar
  12. D. G. Wastell, “Statistical detection of individual evoked responses: an evaluation of Woody's adaptive filter,” Electroencephalography and Clinical Neurophysiology, vol. 42, no. 6, pp. 835–839, 1977. View at Publisher · View at Google Scholar
  13. T.-P. Jung, S. Makeig, M. Westerfield, J. Townsend, E. Courchesne, and T. J. Sejnowski, “Analysis and visualization of single-trial event-related potentials,” Human Brain Mapping, vol. 14, no. 3, pp. 166–185, 2001. View at Publisher · View at Google Scholar · View at PubMed
  14. S. Makeig, M. Westerfield, and T.-P. Jung et al., “Functionally independent components of the late positive event-related potential during visual spatial attention,” Journal of Neuroscience, vol. 19, no. 7, pp. 2665–2680, 1999.
  15. M. Drozd, P. Husar, A. Nowakowski, and G. Henning, “Detecting evoked potentials with SVD- and ICA-based statistical models,” IEEE Engineering in Medicine and Biology Magazine, vol. 24, no. 1, pp. 51–58, 2005. View at Publisher · View at Google Scholar
  16. J. M. Moser and J. I. Aunon, “Classification and detection of single evoked brain potentials using time-frequency amplitude features,” IEEE Transactions on Biomedical Engineering, vol. 33, no. 12, pp. 1096–1106, 1986. View at Publisher · View at Google Scholar
  17. A. S. Gevins, N. H. Morgan, S. L. Bressler, J. C. Doyle, and B. A. Cutillo, “Improved event-related potentials estimation using statistical pattern classification,” Electroencephalography and Clinical Neurophysiology, vol. 64, no. 2, pp. 177–186, 1986. View at Publisher · View at Google Scholar
  18. G. Zouridakis, B. H. Jansen, and N. N. Boutros, “A fuzzy clustering approach to EP estimation,” IEEE Transactions on Biomedical Engineering, vol. 44, no. 8, pp. 673–680, 1997. View at Publisher · View at Google Scholar
  19. L. Tong, G. Xu, and T. Kailath, “Blind identification and equalization based on second-order statistics: a time domain approach,” IEEE Transactions on Information Theory, vol. 40, no. 2, pp. 340–349, 1994. View at Publisher · View at Google Scholar
  20. D. Koenig and J. Boehme, “Application of cyclostationary and time-frequency signal analysisto car engine diagnosis,” in Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '94), vol. 4, pp. 149–152, Adelaide, Australia, April 1994. View at Publisher · View at Google Scholar
  21. S. Ohno and H. Sakai, “Optimization of filter banks using cyclostationary spectral analysis,” IEEE Transactions on Signal Processing, vol. 44, no. 11, pp. 2718–2725, 1996. View at Publisher · View at Google Scholar
  22. W. A. Gardner, “Identification of systems with cyclostationary input and correlated input/output measurement noise,” IEEE Transactions on Automatic Control, vol. 35, no. 4, pp. 449–452, 1990. View at Publisher · View at Google Scholar
  23. W. A. Gardner, “Exploitation of spectral redundancy in cyclostationary signals,” IEEE Signal Processing Magazine, vol. 8, no. 2, pp. 14–36, 1991. View at Publisher · View at Google Scholar
  24. W. A. Gardner, “Signal interception: a unifying theoretical framework for feature detection,” IEEE Transactions on Communications, vol. 36, no. 8, pp. 897–906, 1988. View at Publisher · View at Google Scholar
  25. R. Palaniappan and C. N. Gupta, “Genetic algorithm based independent component analysis to separate noise from Electrocardiogram signals,” in Proceedings of IEEE International Conference on Engineering of Intelligent Systems (ICEIS '06), pp. 1–5, Islamabad, Pakistan, April 2006.
  26. X.-Y. Zeng, Y.-W. Chen, Z. Nakao, and K. Yamashita, “Signal separation by independent component analysis based on agenetic algorithm,” in Proceedings of the 5th International Conference on Signal Processing (ICSP '00), vol. 3, pp. 1688–1694, Beijing, China, August 2000. View at Publisher · View at Google Scholar
  27. D. E. Goldberg, Genetic Algorithms in Search, Optimization and Machine Learning, Addison-Wesley, Reading, Mass, USA, 1989.
  28. F. Rojas, C. G. Puntonet, M. Rodríguez-Álvarez, I. Rojas, and R. Martín-Clemente, “Blind source separation in post-nonlinear mixtures using competitive learning, simulated annealing, and a genetic algorithm,” IEEE Transactions on Systems, Man and Cybernetics, vol. 34, no. 4, pp. 407–416, 2004. View at Publisher · View at Google Scholar
  29. J. Wang, T. Chen, and B. Huang, “Cyclo-period estimation for discrete-time cyclo-stationary signals,” IEEE Transactions on Signal Procesing, vol. 54, no. 1, pp. 83–94, 2006. View at Publisher · View at Google Scholar
  30. G. B. Giannakis, “Cyclo-stationary signal analysis,” in Digital Signal Processing Handbook, CRC Press, Boca Raton, Fla, USA, 1999.
  31. K. K. Paliwal and Y. Sagisaka, “Cyclic autocorrelation-based linear prediction analysis of speech,” in Proceedings of the 5th European Conference on Speech Communication and Technology (EUROSPEECH '97), pp. 279–282, Rhodes, Greece, September 1997.
  32. P. Sharmilakanna and R. Palaniappan, “EEG artifact reduction in VEP using 2-stage PCA and N4 analysis of alcoholics,” in Proceedings of the 3rd International Conference on Intelligent Sensing and Information Processing (ICISIP '05), pp. 1–7, Bangalore, India, December 2005.
  33. J. A. McEwen and G. B. Anderson, “Modeling the stationarity and gaussianity of spontaneous electroencephalographic activity,” IEEE Transactions on Biomedical Engineering, vol. 22, no. 5, pp. 361–369, 1975. View at Publisher · View at Google Scholar
  34. P. A. Karjalainen, J. P. Kaipio, A. S. Koistinen, and M. Vauhkonen, “Subspace regularization method for the single-trial estimation of evoked potentials,” IEEE Transactions on Biomedical Engineering, vol. 46, no. 7, pp. 849–860, 1999. View at Publisher · View at Google Scholar
  35. W. Klimesch, “The P300 wave and band power in the alpha and theta range,” Psycoloquy, vol. 6, no. 44, 1995, memory-brain.5.klimesch.
  36. R. Verleger, “Memory-related EEG potentials: slow negativities, priming positivity, recognition positivity, and Dm,” Psycoloquy, vol. 6, no. 27, 1995, memory-brain.3.verleger.
  37. A. Hyvarinen and E. Oja, “A survey on independent component analysis,” Neural Computing Surveys, vol. 2, pp. 94–128, 1999.
  38. D. W. Scott, Multivariate Density Estimation: Theory, Practice, and Visualization, John Wiley & Sons, New York, NY, USA, 1992.
  39. P. Comon, “Independent component analysis, a new concept?,” Signal Processing, vol. 36, no. 3, pp. 287–314, 1994. View at Publisher · View at Google Scholar
  40. A. Kraskov, H. Stögbauer, and P. Grassberger, “Estimating mutual information,” Physical Review E, vol. 69, no. 6, Article ID 066138, 16 pages, 2004. View at Publisher · View at Google Scholar · View at MathSciNet