Mutual information-based selection of optimal spatial-temporal patterns for single-trial EEG-based BCIs

Pattern Recognition

Volumn 45, Issue 6, 2012, Pages 2137-2144

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

^a INSTITUTE FOR INFOCOMM RESEARCH   (Singapore)

Author keywords

Bayesian classification; Brain computer interface (BCI); Electroencephalogram (EEG); Feature selection; Mutual information

Indexed keywords

BAND PASS FILTERING; BAYESIAN CLASSIFICATION; BRAIN-COMPUTER INTERFACE (BCI); CLASSIFICATION RESULTS; COMMON SPATIAL PATTERNS; DATA SETS; EEG SIGNALS; ELECTROENCEPHALOGRAM (EEG); ELECTROENCEPHALOGRAM SIGNALS; MULTI-CLASS; MUTUAL INFORMATIONS; NEURONAL ACTIVITIES; SINGLE-TRIAL EEG; SPATIAL FILTERINGS; SPATIAL PATTERNS; SPATIAL TEMPORALS; SUBJECT-SPECIFIC; TEMPORAL FREQUENCY; TIME SEGMENTS;

BRAIN COMPUTER INTERFACE; ELECTROENCEPHALOGRAPHY; FEATURE EXTRACTION; FREQUENCY BANDS; OPTIMIZATION;

NEUROIMAGING;

EID: 84857063455     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2011.04.018     Document Type: Article

References (50)

1. G. Pfurtscheller, and C. Neuper Motor imagery and direct braincomputer communication Proc. IEEE 89 7 2001 1123 1134 (Pubitemid 33766616)
2. 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. 25 1 2008 41 56
3. H. Ramoser, J. Müller-Gerking, and G. Pfurtscheller Optimal spatial filtering of single trial EEG during imagined hand movement IEEE Trans. Rehabil. Eng. 8 4 2000 441 446 (Pubitemid 32178931)
4. H. Yuan, A. Doud, A. Gururajan, and B. He Cortical imaging of event-related (de) synchronization during online control of braincomputer interface using minimum-norm estimates in frequency domain IEEE Trans. Neural Syst. Rehabil. Eng. 16 5 2008 425 431
5. X. Liao, D. Yao, D. Wu, and C. Li Combining spatial filters for the classification of single-trial EEG in a finger movement task IEEE Trans. Biomed. Eng. 54 5 2007 821 831 (Pubitemid 46628576)
6. B. Blankertz, G. Dornhege, M. Krauledat, K.-R. Muller, V. Kunzmann, F. Losch, and G. Curio The Berlin braincomputer interface: EEG-based communication without subject training IEEE Trans. Neural Syst. Rehabil. Eng. 14 2 2006 147 152 (Pubitemid 44150229)
7. G. Pfurtscheller, and C. Neuper Future prospects of ERD/ERS in the context of braincomputer interface (BCI) developments C. Neuper, W. Klimeschm, Progress in Brain Research: Event-Related Dynamics of Brain Oscillations 159 2006 Elsevier 433 437 (Pubitemid 44634659)
8. P. Herman, G. Prasad, T.M. McGinnity, and D. Coyle Comparative analysis of spectral approaches to feature extraction for EEG-based motor imagery classification IEEE Trans. Neural Syst. Rehabil. Eng. 16 4 2008 317 326
9. M. Naeem, C. Brunner, R. Leeb, B. Graimann, and G. Pfurtscheller Seperability of four-class motor imagery data using independent components analysis J. Neural Eng. 3 3 2006 208 216 (Pubitemid 44262021)
10. L. Qin, and B. He A wavelet-based time-frequency analysis approach for classification of motor imagery for braincomputer interface applications J. Neural Eng. 2 4 2005 65 72 (Pubitemid 41740523)
11. T. Wang, J. Deng, and B. He Classifying EEG-based motor imagery tasks by means of time-frequency synthesized spatial patterns Clin. Neurophysiol. 115 12 2004 2744 2753 (Pubitemid 39531337)
12. T. Wang, and B. He An efficient rhythmic component expression and weighting synthesis strategy for classifying motor imagery EEG in a braincomputer interface J. Neural Eng. 1 1 2004 1 7 (Pubitemid 41079666)
13. D.J. McFarland, D.J. Krusienski, W.A. Sarnacki, and J.R. Wolpaw Emulation of computer mouse control with a noninvasive braincomputer interface J. Neural Eng. 5 2 2008 101 110 (Pubitemid 351999178)
14. A. Schlögl, F. Lee, H. Bischof, and G. Pfurtscheller Characterization of four-class motor imagery EEG data for the BCI-competition 2005 J. Neural Eng. 2 4 2005 L14 L22
15. D.P. Burke, S.P. Kelly, P. de Chazal, R.B. Reilly, and C. Finucane A parametric feature extraction and classification strategy for braincomputer interfacing IEEE Trans. Neural Syst. Rehabil. Eng. 13 1 2005 12 17 (Pubitemid 40469217)
16. J.R. Wolpaw, and D.J. McFarland Control of a two-dimensional movement signal by a noninvasive braincomputer interface in humans Proc. Acad. Natl. Sci. 101 51 2004 17849 17854 (Pubitemid 40051975)
17. C. Brunner, M. Naeem, R. Leeb, B. Graimann, and G. Pfurtscheller Spatial filtering and selection of optimized components in four class motor imagery EEG data using independent components analysis Pattern Recognition Lett. 28 8 2007 957 964 (Pubitemid 46413377)
18. L. Qin, L. Ding, and B. He Motor imagery classification by means of source analysis for braincomputer interface applications J. Neural Eng. 1 3 2004 135 141 (Pubitemid 41094820)
19. B. Kamousi, Z. Liu, and B. He Classification of motor imagery tasks for brain-computer interface applications by means of two equivalent dipoles analysis IEEE Trans. Neural Syst. Rehabil. Eng. 13 2 2005 166 171 (Pubitemid 41017703)
20. D. Coyle, G. Prasad, and T.M. McGinnity A time-series prediction approach for feature extraction in a braincomputer interface IEEE Trans. Neural Syst. Rehabil. Eng. 13 4 2005 461 467 (Pubitemid 43015552)
21. D. Coyle, A. Satti, G. Prasad, T.M. McGinnity, Neural time-series prediction preprocessing meets common spatial patterns in a braincomputer interface, in: Proceedings of the 30th Annual International Conference on IEEE Engineering in Medicine and Biology Society, Vancouver, BC, Canada, 2008, pp. 26262629.
22. C. Brunner, R. Scherer, B. Graimann, G. Supp, and G. Pfurtscheller Online control of a braincomputer interface using phase synchronization IEEE Trans. Biomed. Eng. 53 12 2006 2501 2506 (Pubitemid 46019537)
23. N. Yamawaki, C. Wilke, Z. Liu, and B. He An enhanced time-frequency- spatial approach for motor imagery classification IEEE Trans. Neural Syst. Rehabil. Eng. 14 2 2006 250 254 (Pubitemid 44150254)
24. W. Wu, X. Gao, B. Hong, and S. Gao Classifying single-trial EEG during motor imagery by iterative spatio-spectral patterns learning (ISSPL) IEEE Trans. Biomed. Eng. 55 6 2008 1733 1743 (Pubitemid 351728022)
25. R. Tomioka, G. Dornhege, G. Nolte, B. Blankertz, K. Aihara, K.-R. Müller, Spectrally weighted common spatial pattern algorithm for single trial EEG classification, Mathematical Engineering Technical Reports, 2006.
26. G. Dornhege, B. Blankertz, M. Krauledat, F. Losch, G. Curio, and K.-R. Müller Combined optimization of spatial and temporal filters for improving braincomputer interfacing IEEE Trans. Biomed. Eng. 53 11 2006 2274 2281 (Pubitemid 44629866)
27. 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. 52 9 2005 1541 1548 (Pubitemid 41462184)
28. B. Blankertz, G. Dornhege, M. Krauledat, K.-R. Müller, and G. Curio The non-invasive Berlin braincomputer interface: fast acquisition of effective performance in untrained subjects NeuroImage 37 2 2007 539 550 (Pubitemid 47444247)
29. K.K. Ang, Z.Y. Chin, H. Zhang, C. Guan, Filter bank common spatial pattern (FBCSP) in braincomputer interface, in: Proceedings of the IEEE International Joint Conference on Neural Networks, Hong Kong, 2008, pp. 23912398.
30. K.P. Thomas, C. Guan, C.T. Lau, A.P. Vinod, and K.K. Ang A new discriminative common spatial pattern method for motor imagery braincomputer interfaces IEEE Trans. Biomed. Eng. 56 11 2009 2730 2733
31. N. Kwak, and C.-H. Choi Input feature selection by mutual information based on Parzen window IEEE Trans. Pattern Anal. Mach. Intell. 24 12 2002 1667 1671
32. E. Parzen On estimation of a probability density function and mode Ann. Math. Statist. 33 3 1962 1065 1076
33. R. Battiti Using mutual information for selecting features in supervised neural net learning IEEE Trans. Neural Networks 5 4 1994 537 550
34. K.K. Ang, C. Quek, Rough set-based neuro-fuzzy system, in: Proceedings of the IEEE International Joint Conference on Neural Networks, Vancouver, BC, Canada, 2006, pp. 742749.
35. R.O. Duda, P.E. Hart, and D.G. Stork Pattern Classification second ed. 2001 John Wiley New York
36. V.N. Vapnik Statistical Learning Theory, Adaptive and Learning Systems for Signal Processing, Communications, and Control 1998 Wiley New York
37. L. Breiman, J.H. Friedman, R.A. Olshen, C.J. Stone, Classification and regression trees, in: The Wadsworth Statistics/Probability Series, Wadsworth International Group, Belmont, CA, 1984.
38. T. Cover, and P. Hart Nearest neighbor pattern classification IEEE Trans. Inf. Theory 13 1 1967 21 27
39. K.K. Ang, and C. Quek Rough Set-Based Neuro-Fuzzy System: Towards Increasing Interpretability Without Compromising Accuracy 2009 VDM Verlag Germany
40. N.K. Kasabov, and Q. Song DENFIS: dynamic evolving neural-fuzzy inference system and its application for time-series prediction IEEE Trans. Fuzzy Syst. 10 2 2002 144 154 (Pubitemid 34554860)
41. A.W. Bowman, and A. Azzalini Applied Smoothing Techniques for Data Analysis: the Kernel Approach with S-Plus Illustrations 1997 Oxford University Press New York
42. G. Dornhege, B. Blankertz, G. Curio, and K.-R. Müller Increase information transfer rates in BCI by CSP extension to multi-class S. Thrun, L. Saul, B. Schölkopf, Advances in Neural Information Processing Systems vol. 16 2004 MIT Press Cambridge, MA
43. R. Leeb, F. Lee, C. Keinrath, R. Scherer, H. Bischof, and G. Pfurtscheller Braincomputer communication: motivation, aim, and impact of exploring a virtual apartment IEEE Trans. Neural Syst. Rehabil. Eng. 15 4 2007 473 482 (Pubitemid 350274168)
44. J. Müller-Gerking, G. Pfurtscheller, and H. Flyvbjerg Designing optimal spatial filters for single-trial EEG classification in a movement task Clin. Neurophysiol. 110 5 1999 787 798 (Pubitemid 29281678)
45. P. Shenoy, M. Krauledat, B. Blankertz, R.P.N. Rao, and K.-R. Muller Towards adaptive classification for BCI J. Neural Eng. 3 1 2006 R13
46. A. Schlögl, J. Kronegg, J. Huggins, and S. Mason Evaluation criteria for BCI research Toward BrainComputer Interfacing 2007 MIT Press USA 327 342
47. J. Cohen A coefficient of agreement for nominal scales Educ. Psychol. Meas. 20 1 1960 37 46
48. A. Schlögl, and C. Brunner BioSig: a free and open source software library for BCI research Computer 41 10 2008 44 50
49. B. Blankertz, BCI Competition IV 〈 http://www.bbci.de/competition/ iv/ 〉, 2008.
50. D. Coyle Neural network based auto association and time-series prediction for biosignal processing in braincomputer interfaces IEEE Comput. Intell. Mag. 4 4 2009 47 59