Optimum spatio-spectral filtering network for brain-computer interface

IEEE Transactions on Neural Networks

Volumn 22, Issue 1, 2011, Pages 52-63

  Zhang, Haihong ^a   Chin, Zheng Yang ^a   Ang, Kai Keng ^a   Guan, Cuntai ^a   Wang, Chuanchu ^a  

^a INSTITUTE FOR INFOCOMM RESEARCH   (Singapore)

Author keywords

Braincomputer interface; motor imagery electroencephalography; spatio spectral filtering

Indexed keywords

CLASS LABELS; CLASSIFICATION ACCURACY; CONFIDENCE LEVELS; DATA SETS; EVENT RELATED DESYNCHRONIZATION; EXISTING METHOD; FEATURE EXTRACTION METHODS; GRADIENT-BASED LEARNING; HUMAN SUBJECTS; LEARNING TASKS; MOTOR IMAGERY; MOTOR IMAGERY CLASSIFICATION; MUTUAL INFORMATIONS; NON-PARAMETRIC ESTIMATES; SPATIAL FILTERS; SPECTRAL FILTERING; STATISTICAL SIGNIFICANCE;

BANDPASS FILTERS; ELECTROENCEPHALOGRAPHY; ELECTROPHYSIOLOGY; FEATURE EXTRACTION; INTERFACES (COMPUTER); LEARNING ALGORITHMS; OPTICAL SENSORS; OPTIMIZATION;

BRAIN COMPUTER INTERFACE;

ARTICLE; ARTIFICIAL NEURAL NETWORK; AUTOMATED PATTERN RECOGNITION; BRAIN; COMPARATIVE STUDY; COMPUTER INTERFACE; ELECTROENCEPHALOGRAPHY; EVOKED MUSCLE RESPONSE; HUMAN; MALE; METHODOLOGY; PHYSIOLOGY; STANDARD;

BRAIN; ELECTROENCEPHALOGRAPHY; EVOKED POTENTIALS, MOTOR; HUMANS; MALE; NEURAL NETWORKS (COMPUTER); PATTERN RECOGNITION, AUTOMATED; USER-COMPUTER INTERFACE;

EID: 78651271654     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNN.2010.2084099     Document Type: Article

References (41)

1. J. R. Wolpaw, "Brain-computer interfaces as new brain output pathways," J. Physiol., vol. 579, no. 3, pp. 613-619, Mar. 2007.
2. A. Nijholt and D. Tan, "Brain-computer interfacing for intelligent systems," IEEE Intell. Syst., vol. 23, no. 3, pp. 72-79, May-Jun. 2008.
3. J. R. Wolpaw, N. Birbaumer, D. J. MacFarland, G. Pfurtscheller, and T. M. Vaughan, "Brain-computer interfaces for communication and control," Clin. Neurophysiol., vol. 113, no. 6, pp. 767-791, Jun. 2002.
4. G. Pfurtscheller, C. Neuper, D. Flotzinger, and M. Pregenzer, "EEGbased discrimination between imagination of right and left hand movement," Electroencephalogr. Clin. Neurophysiol., vol. 103, no. 6, pp. 642- 651, Dec. 1997.
5. J. Muller-Gerking, G. Pfurtscheller, and H. Flyvbjerg, "Designing optimal spatial filtering of single trial EEG classification in a movement task," Clin. Neurophysiol., vol. 110, no. 5, pp. 787-798, May 1999.
6. A. Kübler, F. Nijboer, J. Mellinger, T. M. Vaughan, H. Pawelzik, G. Schalk, D. J. McFarland, N. Birbaumer, and J. R. Wolpaw, "Patients with ALS can use sensorimotor rhythms to operate a brain-computer interface," Neurology, vol, 64, no. 10, pp. 1775-1777, May 2005.
7. G. Dornhege, B. Blankertz, G. Curio, and K.-R. Müller, "Boosting bit rates in noninvasive EEG single-trial classifications by feature combination and multiclass paradigms," IEEE Trans. Biomed. Eng., vol. 51, no. 6, pp. 993-1002, Jun. 2004.
8. M. Grosse-Wentrup and M. Buss, "Multiclass common spatial patterns and information theoretic feature extraction," IEEE Trans. Biomed. Eng., vol. 55, no. 8, pp. 1991-2000, Aug. 2008.
9. B. Blankertz, G. Dornhege, C. Schafer, R. Krepki, J. Kohlmorgen, K.- R. Müller, V. Kunzmann, F. Losch, and G. Curio, "Boosting bit rates and error detection for the classification of fast-paced motor commands based on single-trial EEG analysis," IEEE Trans. Neural Syst. Rehabil. Eng., vol. 11, no. 2, pp. 127-131, Jun. 2003.
10. P. L. Nunez, R. Srinivasan, A. F. Westdorp, R. S. Wijesinghe, D. M. Tucker, R. B. Silberstein, and P. J. Cadusch, "EEG coherency I: Statistics, reference electrode, volume conduction, laplacians, cortical imaging, and interpretation at multiple scales," Electroencephalogr. Clin. Neurophysiol., vol. 103, no. 5, pp. 499-515, Nov. 1997.
11. P. L. Nunez, R. B. Silberstein, Z. Shi, M. R. Carpenter, R. Srinivasan, D. M. Tucker, S. M. Doran, P. J. Cadusch, and R. S. Wijesinghe, "EEG coherency II: Experimental comparisons of multiple measures," Clin. Neurophysiol., vol. 110, no. 3, pp. 469-486, Mar. 1999.
12. I. I. Goncharova, D. J. McFarland, T. M. Vaughan, and J. R. Wolpaw, "EMG contamination of EEG: Spectral and topographical characteristics, " Clin. Neurophysiol., vol. 114, no. 9, pp. 1580-1593, Sep. 2003.
13. A. Bashashati, M. Fatourechi, R. K. Ward, and G. E. Birch, "A survey of signal processing algorithms in brain-computer interfaces based on electrical brain signals," J. Neural Eng., vol. 4, no. 2, pp. R32-R57, Jun. 2007.
14. L. Qin, L. Ding, and B. He, "Motor imagery classification by means of source analysis for brain-computer interface applications," J. Neural Eng., vol. 1, no. 3, pp. 135-141, 2004.
15. M. Grosse-Wentrup, C. Liefhold, K. Gramann, and M. Buss, "Beamforming in noninvasive brain-computer interfaces," IEEE Trans. Biomed. Eng., vol. 56, no. 4, pp. 1209-1219, Apr. 2009.
16. H. Ramoser, J. Muller-Gerking, and G. Pfurtscheller, "Optimal spatial filtering of single trial EEG during imagined hand movement," IEEE Trans. Rehabil. Eng., vol. 8, no. 4, pp. 441-446, Dec. 2000.
17. B. Blankertz, R. Tomioka, S. Lemm, M. Kawanabe, and K.-R. Müller, "Optimizing spatial filters for robust EEG single-trial analysis," IEEE Signal Process. Mag., vol. 25, no. 1, pp. 41-56, Jan. 2008.
18. M. Naeem, C. Brunner, R. Leeb, B. Graimann, and G. Pfurtscheller, "Separability of four-class motor imagery data using independent components analysis," J. Neural Eng., vol. 3, no. 3, pp. 208-216, Sep. 2006.
19. S. Lemm, B. Blankertz, G. Curio, and K.-R. Müller, "Spatio-spectral filters for improving the classification of single trial EEG," IEEE Trans. Biomed. Eng., vol. 52, no. 9, pp. 1541-1548, Sep. 2005.
20. G. Dornhege, B. Blankertz, M. Krauledat, F. Losch, G. Curio, and K.- R. Müller, "Combined optimization of spatial and temporal filters for improving brain-computer interfacing," IEEE Trans. Biomed. Eng., vol. 53, no. 11, pp. 2274-2281, Nov. 2006.
21. W. Wu, X. R. Gao, B. Hong, and S. K. Gao, "Classifying single-trial EEG during motor imagery by iterative spatio-spectral patterns learning (ISSPL)," IEEE Trans. Biomed. Eng., vol. 55, no. 6, pp. 1733-1743, Jun. 2008.
22. K. K. Ang, Z. Y. Chin, H. Zhang, and C. Guan, "Filter bank common spatial pattern (FBCSP) in brain-computer interface," in Proc. Int. Joint Conf. Neural Netw., Hong Kong, China, 2008, pp. 2391-2398.
23. K. K. Ang, C. Guan, K. S. G. Chua, B. T. Ang, C. W. K. Kuah, C. Wang, K. S. Phua, Z. Y. Chin, and H. H. Zhang, "A clinical evaluation of non-invasive motor imagery-based brain-computer interface in stroke," in Proc. 30th Annu. Int. Conf. IEEE Eng. Med. Biol. Soc., Vancouver, BC, Canada, Aug. 2008, pp. 4178-4181.
24. BCI Competition IV [Online]. Available: http://www.bbci.de/competition/
25. H. Zhang, C. Guan, and C. Wang, "Spatio-spectral feature selection based on robust mutual information estimate for brain-computer interfaces," in Proc. Annu. Int. Conf. IEEE Eng. Med. Biol. Soc., Minneapolis, MN, Sep. 2009, pp. 2391-2398.
26. K. Fukunaga, Introduction to Statistical Pattern Recognition. New York: Academic, 1990.
27. T. M. Cover and J. A. Thomas, Elements of Information Theory, 2nd ed. New York: Wiley, 2006.
28. M. Ben-Bassat, "User of distance measures, information measures and error bounds in feature evaluation," in Handbook of Statistics, vol. 2, P. Krishnaiah and L. Kanal, Eds. Amsterdam, The Netherlands: North Holland, 1982, ch. 35, pp. 773-791.
29. S. Petridis and S. J. Perantonis, "On the relation between discriminant analysis and mutual information for supervised linear feature extraction," Pattern Recognit., vol. 37, no. 5, pp. 857-874, May 2004.
30. J. M. Sotoca and F. Pla, "Supervised feature selection by clustering using conditional mutual information-based distances," Pattern Recognit., vol. 43, no. 6, pp. 2068-2081, Jun. 2010.
31. P. A. Estevez, M. Tesmer, C. A. Perez, and J. M. Zurada, "Normalized mutual information feature selection," IEEE Trans. Neural Netw., vol. 20, no. 2, pp. 189-201, Feb. 2009.
32. P. Viola and W. M. Wells, III, "Alignment by maximization of mutual information," Int. J. Comput. Vis., vol. 24, no. 2, pp. 137-154, Sep. 1997.
33. D. W. Scott, Multivariate Density Estimation: Theory, Practice, and Visualization. New York: Wiley, 1992.
34. A. W. Bowman and A. Azzalini, Applied Smoothing Techniques for Data Analysis: The Kernel Approach with S-Plus Illustrations. New York: Oxford Univ. Press, 1997.
35. N. Yamawaki, C. Wilke, Z. Liu, and B. He, "An enhanced timefrequency- spatial approach for motor imagery classification," IEEE Trans. Neural Syst. Rehabil. Eng., vol. 14, no. 2, pp. 250-254, Jun. 2006.
36. R. Scherer, F. Lee, A. Schlögl, R. Leeb, H. Bischof, and G. Pfurtscheller, "Toward self-paced brain-computer communication: Navigation through virtual worlds," IEEE Trans. Biomed. Eng., vol. 55, no. 2, pp. 675-682, Feb. 2008.
37. G. Pfurtscheller and C. Neuper, "Motor imagery and direct braincomputer communication," Proc. IEEE, vol. 89, no. 7, pp. 1123-1134, Jul. 2001.
38. C.-C. Chang and C.-J. Lin. (2001). LIBSVM: A Library for Support Vector Machines [Online]. Available: http://www.csie.ntu.edu.tw/cjlin/libsvm
39. B. Obermaier, G. R. Muller, and G. Pfurtscheller, "Virtual keyboard controlled by spontaneous EEG activity," IEEE Trans. Neural Syst. Rehabil. Eng., vol. 11, no. 4, pp. 422-426, Dec. 2003.
40. M. Fatourechi, R. K. Ward, and G. E. Birch, "A self-paced braincomputer interface system with a low false positive rate," J. Neural Eng., vol. 5, no. 1, pp. 9-23, Mar. 2008.
41. 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, no. 2, pp. 539-550, Aug. 2007.