Improving session-to-session transfer performance of motor imagery-based BCI using adaptive extreme learning machine

Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS

Volumn , Issue , 2013, Pages 2188-2191

  Bamdadian, Atieh ^a   Guan, Cuntai ^a   Ang, Kai Keng ^a   Xu, Jianxin ^b  

^a INSTITUTE FOR INFOCOMM RESEARCH   (Singapore)

^b NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

Author keywords

[No Author keywords available]

Indexed keywords

COMMON SPATIAL PATTERNS; DISCRIMINATIVE FEATURES; EXTREME LEARNING MACHINE; HEALTHY SUBJECTS; MOTOR IMAGERY; NON-STATIONARITIES; SVM CLASSIFIERS; TRANSFER PERFORMANCE;

ALGORITHMS; BRAIN COMPUTER INTERFACE; CALIBRATION; KNOWLEDGE ACQUISITION; LEARNING SYSTEMS; ONLINE SYSTEMS;

ELECTROENCEPHALOGRAPHY;

EID: 84886554632     PISSN: 1557170X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/EMBC.2013.6609969     Document Type: Conference Paper

References (22)

1. J. R. Wolpaw, N. Birbaumer, D. J. McFarland, G. Pfurtscheller, and T. M. Vaughan, "Brain-computer interfaces for communication and control, " Clinical Neurophysiology, vol. 113, pp. 767-791, 2002.
2. B. Blankertz, et al., "The Berlin Brain-Computer Interface: Non-Medical Uses of BCI Technology, " Frontiers in Neuroscience, vol. 4, 2010-December-8 2010.
3. J. N. Mak and J. R. Wolpaw, "Clinical Applications of Brain- Computer Interfaces: Current State and Future Prospects, " IEEE Reviews in Biomedical Engineering, vol. 2, pp. 187- 199, 2009.
4. A. Y. Kaplan, A. A. Fingelkurts, A. A. Fingelkurts, S. V. Borisov, and B. S. Darkhovsky, "Nonstationary nature of the brain activity as revealed by EEG MEG methodological, practical and conceptual challenges, " Signal Processing vol. 85, pp. 2190-2212, 2005.
5. P. Shenoy, M. Krauledat, B. Blankertz, R. P. N. Rao, and K.- R. Müller, "Towards adaptive classification for BCI, " Journal of Neural Engineering, vol. 3, pp. R13-R23, 2006.
6. M. Sugiyama, M. Krauledat, and K.-R. Müller, "Covariate Shift Adaptation by Importance Weighted Cross Validation " Machine Learning Research, vol. 8, pp. 985-1005, 2007.
7. W. Samek, C. Vidaurre, K.-R. Müller, and M. Kawanabe, "Stationary common spatial patterns for brain-computer interfacing, " Journal of Neural Engineering, vol. 9, p. 026013, 2012.
8. G. Ferber, "Treatment of Some Nonstationarities in the EEG, " Neuropsychobiology, vol. 17, pp. 100-104, 1987.
9. P. v. Bunau, F. C. Meinecke, and K.-R. Muller, "Stationary Subspace Analysis, " American Physics Letter, 2009.
10. C. Vidaurre, A. Schlogl, R. Cabeza, R. Scherer, and G. Pfurtscheller, "A fully on-line adaptive BCI, " IEEE Transactions on Biomedical Engineering, vol. 53, pp. 1214- 1219, 2006.
11. Z. Qibin, Z. Liqing, A. Cichocki, and L. Jie, "Incremental Common Spatial Pattern algorithm for BCI, " in IEEE International Joint Conference on Neural Networks (IJCNN ), 2008, pp. 2656-2659.
12. A. Bamdadian, C. Guan, K. K. Ang, and J. Xu, "Online Semi-supervised Learning with KL Distance Weighting for Motor Imagery-based BCI, " in Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2012.
13. S. Sun and C. Zhang, "Adaptive feature extraction for EEG signal classification, " Med Bio Eng Comput, vol. 44, pp. 931- 935, 2006.
14. M. Sugiyama, et al., "Direct importance estimation for covariate shift adaptation, " Annals of the Institute of Statistical Mathematics, vol. 60, pp. 699-746, 2008.
15. C. Vidaurre, et al., "Toward Unsupervised Adaptation of LDA for Brain Computer Interfaces, " IEEE Transactions on Biomedical Engineering, vol. 58, pp. 587-597, 2011.
16. 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 Transactions on Biomedical Engineering, vol. 54, pp. 550- 556, 2007.
17. K. K. Ang, Z. Y. Chin, H. Zhang, and C. Guan, "Filter Bank Common Spatial Pattern (FBCSP) algorithm using online adaptive and semi-supervised learning, " in IEEE International Joint Conference on Neural Networks (IJCNN ), 2011, pp. 392-396.
18. G.-B. Huang, Q.-Y. Zhu, and C.-K. Siew, "Extreme learning machine: Theory and applications, " Neurocomputing, vol. 70, pp. 489-501, 2006.
19. X. Liu, C. Gao, and P. Li, "A comparative analysis of support vector machines and extreme learning machines, " Neural Networks, vol. 33, pp. 58-66, 2012.
20. R. Minhas, A. A. Mohammed, and Q. M. Wu, "Incremental Learning in Human Action Recognition Based on Snippets, " IEEE Transactions on Circuits and Systems for Video Technology, pp. 1-1, 2011.
21. K. Choi, K.-A. Toh, and H. Byun, "Incremental face recognition for large-scale social network services, " Pattern Recognition, vol. 45, pp. 2868-2883, 2012.
22. B. Blankertz, R. Tomioka, S. Lemm, M. Kawanabe, and K. R. Muller, "Optimizing Spatial filters for Robust EEG Single- Trial Analysis, " IEEE Signal Processing Magazine, vol. 25, pp. 41-56, 2008.