Application of covariate shift adaptation techniques in brain-computer interfaces

IEEE Transactions on Biomedical Engineering

Volumn 57, Issue 6, 2010, Pages 1318-1324

  Li, Yan ^a   Kambara, Hiroyuki ^a   Koike, Yasuharu ^a   Sugiyama, Masashi ^a  

^a TOKYO INSTITUTE OF TECHNOLOGY   (Japan)

Author keywords

Bagging; Brain computer interface (BCI); Covariate shift adaptation

Indexed keywords

ADAPTATION TECHNIQUES; ATTENTION LEVEL; COVARIATES; DATA SETS; ELECTRODE PLACEMENT; NON-STATIONARITIES; ONLINE EXPERIMENT; SESSION TRANSFER; TESTING SESSIONS;

COMPETITION; COMPUTATIONAL METHODS; INTERFACES (COMPUTER);

BRAIN COMPUTER INTERFACE;

ADAPTATION; ARTICLE; BRAIN; COMPUTER INTERFACE; COVARIANCE; ELECTRODE; FATIGUE; IMPEDANCE;

ALGORITHMS; BRAIN MAPPING; DATA INTERPRETATION, STATISTICAL; ELECTROENCEPHALOGRAPHY; EVOKED POTENTIALS, MOTOR; HUMANS; IMAGINATION; MOTOR CORTEX; USER-COMPUTER INTERFACE;

EID: 77952578375     PISSN: 00189294     EISSN: None     Source Type: Journal    
DOI: 10.1109/TBME.2009.2039997     Document Type: Article

References (22)

1. A. Buttfield, P.W. Ferrez, and JD R. Millan, "Towards a robust BCI: Error potentials and online learning," IEEE Trans. Neural Syst. Rehabil. Eng., vol.14, no.2, pp. 164-168, Jun. 2006.
2. T.W. Berger, J. K. Chapin,G. A. Gerhardt, D. J. McFarland, J. C. Principe, W. V. Soussou, D. M. Taylor, and P. A. Tresco. (2008, Aug. 26). WTEC Panel Report on International Assessment of Research and Development in Brain-Computer Interfaces.World Technology Evaluation Center, Inc., Baltimore, MD. [Online]. Available: http://www.wtec.org/bci/BCIfinalreport-26Aug2008- lowres.pdf
3. C. Vidaurre, A. Schlogl, R. Cabeza, R. Scherer, and G. Pfurtscheller, "A fully online adaptive BCI," IEEE Trans. Biomed. Eng., vol.53, no.6, pp. 1214-1219, Jun. 2006.
4. C. Vidaurre, A. Schlogl, R. Cabeza, R. Scherer, and G. Pfurtscheller, "Study of on-line adaptive discriminant analysis for EEG-based brain computer interfaces," IEEE Trans. Biomed. Eng., vol.54, no.3, pp. 550-556, Mar. 2007.
5. J. Blumberg, J. Rickert, S.Waldert, A. Schulze-Bonhage, A. Aertsen, and C. Mehring, "Adaptive classification for brain computer interfaces," in Proc. Conf. Proc. IEEE Eng. Med. Biol. Soc., 2007, pp. 2536-2539.
6. M. Sugiyama,M.Krauledat, and K.-R.Müller, "Covariate shift adaptation by importance weighted cross validation," J. Mach. Learning Res., vol.8, pp. 985-1005, May 2007.
7. S. Sun, C. Zhang, and D. Zhang, "An experimental evaluation of ensemble methods for EEG signal classification," Pattern Recognit. Lett., vol.28, pp. 2157-2163, Nov. 2007.
8. C. Lehmann, T. Koenig, V. Jelic, L. Prichep, E. R. John, L.-O. Wahlund, Y. Dodge, and T. Dierks, "Application and comparison of classification algorithms for recognition of Alzheimer's disease in electrical brain activity (EEG)," J. Neurosci. Methods, vol.161, pp. 342-350, Apr. 2007.
9. B. Blankertz, G. Dornhege, M. Krauledat, K.-R. Müller, and G. Curio, "The non-invasive berlin brain-computer interface: Fast acquisition of effective performance in untrained subjects," NeuroImage, vol.37, pp. 539-550, Aug. 2007.
10. Y.Wang, B. Hong, X. Gao, and S. Gao, "Mu rhythm-based cursor control: An offline analysis," Clin. Neurophysiol., vol.115, pp. 745-751, Apr. 2004.
11. Y. Wang, B. Hong, X. Gao, and S. Gao, "Implementation of a braincomputer interface based on three states of motor imagery," in Proc. Conf. Proc. IEEE Eng. Med. Biol. Soc., 2007, pp. 5059-5062.
12. G. Pfurtscheller, C. Neuper, C. Guger, W. Harkam, H. Ramoser, A. Schlogl, B.Obermaier, and M. Pregenzer, "Current trends in graz braincomputer interface (BCI) research," IEEE Trans. Rehab. Eng., vol.8, no.2, pp. 216-219, Jun. 2000.
13. F. Lotte1, M. Congedo, A. Lecuyer, F. Lamarche, and B. Arnaldi, "A review of classification algorithms for EEG-based brain-computer interfaces," J. Neural Eng., vol.4, pp. 1-13, Jun. 2007.
14. H. Shimodaira, "Improving predictive inference under covariate shift by weighting the log-likelihood function," J. Statist. Plann. Inference, vol.90, pp. 227-244, Nov. 2000.
15. M. Sugiyama, T. Suzuki, S. Nakajima, H. Kashima, P. von Buenau, and M. Kawanabe, "Direct importance estimation for covariate shift adaptation," Ann. Inst. Statist. Math., vol.60, pp. 699-746, Dec. 2008.
16. T. Kanamori, S. Hido, and M. Sugiyama, "A least-squares approach to direct importance estimation," J. Mach. Learning Res., vol.10, pp. 1391-1445, Jul. 2009.
17. Eugene Tuv, Feature Extraction Foundations and Applications. The Netherlands: Springer-Verlag, 2006, pp. 188-204.
18. D. Zhang, Y. Wang, X. Gao, B. Hong, and S. Gao, (2007, Jul. 12). An algorithm for idle-state detection in motor-imagery-based braincomputer interface. Comput. Intell. Neurosci. [Online]. vol.2007, 9 pp. Available: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1994518/pdf/ CIN2007-39714.pdf
19. G. Dornhege, B. Blankertz, G. Curio, and K.-R.Müller, "Boosting bit rates in non-invasive EEG single-trial classifications by feature combination and multi-class paradigms," IEEE Trans. Biomed. Eng., vol.51, no.6, pp. 993-1002, Jun. 2004.
20. G. Schalk,D. J.Mcfarland, T. Hinterberger,N.Birbaumer, and J. R.Wolpa, "BCI2000: A general-purpose brain-computer interface (BCI) system," IEEE Trans. Biomed. Eng., vol.51, no.6, pp. 1034-1043, 2004.
21. H. Peng, F. Long, and C. Ding, "Feature selection based on mutual information: Criteria of max-dependency, max-relevance, and minredundancy," IEEE Trans. Pattern Anal. Mach. Intell., vol.27, no.8, pp. 1226-1238, Aug. 2005.
22. P. Shenoy, M. Krauledat, B. Blankertz, R. P. N. Rao, and K.-R. Müller, "Towards adaptive classification for BCI," J. Neural Eng., vol.3, pp. 13-23, Mar. 2006.