BCI Signal Processing: Feature Translation

Brain-Computer Interfaces: Principles and Practice

Volumn , Issue , 2012, Pages

  McFarland, Dennis J ^a   Krusienski, Dean J ^b  

^a WADSWORTH CENTER   (United States)

^b Old Dominion University   (United States)

Author keywords

Brain signals; Brain computer interfaces; Feature selection; Model selection; Parameterization; Translation algorithms

Indexed keywords

EID: 84921259814     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1093/acprof:oso/9780195388855.003.0008     Document Type: Chapter

References (45)

1. Akaike, H. (1974) A new look at statistical model identification. IEEE Transactions on Automation and Control, 19, 716-723.
2. Besserve, M., Jerbi, K., Laurent, F., Baillet, S., Martinerie, J., and Garnero, L. (2007) Classification methods for ongoing EEG and MEG signals. Biological Research, 40, 415-437.
3. Bickel, P., and Levina, E. (2004) Some theory for Fisher's linear discriminant function, "naive Bayes," and some alternatives when there are many more variables than observations. Bernoulli, 10, 989-1010.
4. Birbaumer, N, Hinterberger, T., Kübler, A., and Newman, N. (2003) The thought-translation device: Neurobehavioral mechanisms and clinical outcomes. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 11, 120-123.
5. Black, M.J., and Donoghue, J.P. (2007) Probabilistic modeling and decoding neural population activity in motor cortex. In G. Dornhege, J. R. Millán, T. Hinterberger, D. J. McFarland, and K.-R. Müller (Eds.) Toward Brain-Computer Interfacing, Cambridge, MA: MIT Press, 147-159.
6. Blankertz, B., Dornege, G., Schafer, C., Krepki, R., Kohlmorgen, J., Müller, K-R., Kunzmann, V., Losch, F., and Curio, G. (2003) Boosting bit rates and error detection for the classification of fast-paced motor commands based on single-trial EEG analysis. IEEE Transactions on Rehabilitation Engineering, 11, 100-104.
7. Blankertz, B., Müller, K.-R., Curio, G., Vaughan, T.M., Schalk, G., Wolpaw, J.R., Schlogl, A., Neuper, C., Pfurtscheller, G., Hinterberger, T., Schroder, M., and Birbaumer, N. (2004) The BCI competition 2003: Progress and perspectives in detection and discrimination of EEG single trials. IEEE Transactions on Biomedical Engineering, 51, 1044-1051.
8. Blankertz, B., Müller, K.-R., Krusienski, D., Schalk, G., Wolpaw, J.R., Schlogl, A., Pfurtscheller, G., Millan, J., Schroder, M., and Birbaumer, N. (2006) The BCI competition III: Validating alternative approaches to actual BCI problems. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 14, 153-159.
9. Donchin, E., Spencer, K.M., and Wijesinghe, R. (2000) The mental prosthesis: Assessing the speed of a P300-based brain-computer interface. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 8, 174-179.
10. Fisher, R.A. (1936) The use of multiple measurements in taxonomic problems. Annals of Eugenics, 7, 179-188.
11. Friedman, L., and Wall, M. (2005) Graphical views of suppression and multicollinearity in multiple linear regression. American Statistician, 59, 127-136.
12. Haykin, S. (1996) Adaptive Filter Theory, Upper Saddle River, NJ: Prentice-Hall.
13. Kieseppa, I.A. (2001) Statistical model selection criteria and the philosophical problem of underdetermination. British Journal of the Philosophy of Science, 52, 761-794.
14. Krusienski, D.J., and Jenkins, W.K. (2005) Design and performance of adaptive systems based on structured stochastic optimization strategies. IEEE Circuits and Systems Magazine, 5, 8-20.
15. Krusienski, D., Sellers, E.W., Cabestaing, F., Bayoudh, S., McFarland, D.J., Vaughan, T.M., and Wolpaw, J.R. (2006) A comparison of classification techniques for the P300 speller. Journal of Neural Engineering, 3, 299-305.
16. Krusienski, D.J., Sellers, E.W., McFarland, D.J., Vaughan, T.M., and Wolpaw, J.R. (2008) Toward enhanced P300 speller performance, Journal of Neuroscience Methods, 167, 15-21.
17. Li, Y., Kambara, H., Koike, Y., and Sugiyama, M. (2010) Application of covariance shift adaptation techniques in brain-computer interfaces. IEEE Transactions on Biomedical Engineering, 57, 1318-1324.
18. Lotte, F., Congedo, M., Leuyer, A., Lmarche, F., and Arnaldi, B. (2007) A review of classification algorithms for EEG-based brain-computer interfaces, Journal of Neural Engineering, 4, 1-13.
19. Luce, R.D. (2003) Whatever happened to information theory in psychology, Review of General Psychology, 7, 183-188.
20. McFarland, D.J., Anderson, C.W., Müller, K.R., Schlogl, A., and Krusienski, D.J. (2006) BCI meeting 2005-Workshop on BCI signal processing: Feature extraction and translation. IEEE Transactions on Neural Systems and Rehabilition Engineering, 14, 135-138.
21. McFarland, D.J., Krusienski, D.J., and Wolpaw, J.R. (2006) Brain-computer interface signal processing at the Wadsworth Center: Mu and sensorimotor beta rhythms. Progress in Brain Research, 159, 411-419.
22. McFarland, D.J., and Wolpaw, J.R. (2005) Sensorimotor rhythm-based brain-computer interface (BCI): Feature selection by regression improves performance. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 14, 372-379.
23. Millán, J. del R., Franze, M., Mourino, J., Cincotti, F., and Babiloni, F. (2002) Relevant features for the classification of spontaneous motor-related tasks. Biological Cybernetics, 86, 89-05.
24. Müller, K.-R., Anderson, C.W., and Birch, G.E. (2003) Linear and nonlinear methods for brain-computer interfaces. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 11, 165-169.
25. Müller, K.-R., Mika, S., Ratsch, G., Tsuda, K., and Scholkopf, B. (2001) An introduction to kernal-based learning algorithms. IEEE Neural Networks, 12, 181-201.
26. Parra, L.C., Spence, C.D., Gerson, A.D., and Sajda, P. (2005) Recipes for the linear analysis of EEG. Neuroimage 28, 326-341.
27. Pierce, J.R. (1980) An Introduction to Information Theory. New York: Dover Press.
28. Press, W.H., Teukolsky, S.A., Vetterling, W.T., and Flannery, B.P. (2007) Numerical Recipes: The Art of Scientific Computing. 3rd ed. New York: Cambridge University Press.
29. Principe, J.C., and McFarland, D.J. (2008) BMI/BCI modeling and signal processing. In: TW Berger, JK Chapin, DJ McFarland, JC Principe, WV Soussou, DM Taylor and PA Tresco (Eds.) Brain-computer interfaces: An international assessment of research and development trends. Berlin: Springer 47-64.
30. Sajda, P., Gerson, A., Müller, K-R., Blankertz, B., and Parra, L. (2003) A data analysis competition to evaluate machine learning algorithms for use in brain-computer interfaces. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 11, 184-185.
31. Schalk, G., Leuthardt, E.C., Brunner, P., Ojemann, J.G., Gerhardt, L.A., and Wolpaw, J.R. (2008) Real-time detection of event-related brain activity. NeuroImage, 43, 245-249.
32. Schlogl, A., Neuper, C., and Pfurtscheller, G. (2002) Estimating the mutual information of an EEG-based brain-computer interface. Biomedizinische Technik, 47, 3-8.
33. Sellers, E.W., Krusienski, D.J., McFarland, D.J., Vaughan, T.M., and Wolpaw, J.R. (2006) A P300 event-related potential brain-computer interface (BCI): The effects of matrix size and inter stimulus interval on performance. Biological Psychology, 73, 242-252.
34. Serruya, M.D., Hatsopoulos, N.G., Paminski, L., Fellows, M.R., and Donoghue, J.P., (2002) Instant neural control of a movement signal. Nature, 416, 1411-1142.
35. Shannon, C.E., and Weaver, W. (1964) The Mathematical Theory of Communication. Urbana, IL: University of Illinois Press.
36. Shenoy, P., Krauledat, M., Blankertz, B., Rao, R.P., and Müller, K-R. (2006) Towards adaptive classification for BCI. Journal of Neural Engineering, 3, 13-23.
37. Shenoy, P., and Rao, R.P.N. (2005) Dynamic bayesian networks for brain-computer interfaces. In L. K. Saul, Y. Weiss, and L. Bottou (Eds.). Advances in Neural Information Processing Systems, Vol. 17. Cambridge, MA: MIT Press, 1265-1272.
38. Stoica, P., and Selen, Y. (2004) Model order selection: A review of information criterion rules. IEEE Signal Processing Magazine 21(4), 36-47.
39. Taylor, D.M., Tilery, S.I.H., and Schwartz, A.B. (2002) Direct cortical control of 3D neuroprosthetic devices. Science, 296, 1829-1832.
40. Tibshirani, R. (1996) Regression shrinkage and selection via the Lasso. Journal of the Royal Statistical Society, Series B, 58, 267-288.
41. Vidaurre, C., Scherer, R., Cabeza, R., Schlogl, A., and Pfurtscheller, G. (2007) Study of discriminant analysis applied to motor imagery bipolar data. Medical and Biological Engineering and Computing, 45, 61-68.
42. Vidaurre, C., Schlogl, A., Cabeza, R., Scherer, R., and Pfurtscheller, G. (2006) A fully on-line adaptive BCI. IEEE Transactions on Biomedical Engineering, 53, 1214-1219.
43. Wolpaw, J.R., Birbaumer, N., McFarland, D.J., Pfurtscheller, G., and Vaughan, T.M. (2002) Brain-computer interfaces for communication and control. Clinical Neurophysioogy, 113, 767-791.
44. Wolpaw, JR and McFarland, DJ. (2004) Control of a two-dimensional movement signal by a noninvasive brain-computer interface in humans. Proceedings of the National Academy of Sciences, 101, 17849-17854.
45. Wu, W., and Hatosopoulos, N.G. (2008) Real-time decoding of nonstationary neural activity in motor cortex. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 16, 213-222.