Improved GMM with parameter initialization for unsupervised adaptation of Brain-Computer interface

International Journal for Numerical Methods in Biomedical Engineering

Volumn 26, Issue 6, 2010, Pages 681-691

  Liu, Guangquan ^a   Huang, Gan ^a   Meng, Jianjun ^a   Zhang, Dingguo ^a   Zhu, Xiangyang ^a  

^a SHANGHAI JIAO TONG UNIVERSITY   (China)

Author keywords

Brain computer interface (BCI); Electroencephalogram (EEG); Expectation maximization (EM); Gaussian mixture model (GMM); Unsupervised adaptation

Indexed keywords

ARTIFICIAL DATA; BRAIN SIGNALS; CHANGING BRAIN STATE; CLASS INFORMATION; DATA PROPERTIES; ERROR RATE; EXPECTATION MAXIMIZATION; GAUSSIAN MIXTURE MODEL; MODEL PARAMETERS; NON-STATIONARITIES; REAL APPLICATIONS; UNSUPERVISED ADAPTATION; UNSUPERVISED METHOD;

COMPUTATIONAL METHODS; ELECTROENCEPHALOGRAPHY; GAUSSIAN DISTRIBUTION; IMAGE SEGMENTATION; INTERFACES (COMPUTER); MAXIMUM PRINCIPLE; OPTICAL SENSORS; OPTIMIZATION; PARAMETER ESTIMATION;

BRAIN COMPUTER INTERFACE;

EID: 77953165121     PISSN: 20407939     EISSN: 20407947     Source Type: Journal    
DOI: 10.1002/cnm.1362     Document Type: Article

References (27)

1. Wolpaw J, Birbaumer N, McFarland D, Pfurtscheller G, Vaughan T. Brain-computer interfaces for communication and control. Clinical Neurophysiology 2002; 113(6):767-791.
2. Millan J. On the need for on-line learning in brain-computer interfaces. Proceedings of the International Joint Conference on Neural Networks, Budapest, Hungary, July 2004 (IDIAP-RR03-30).
3. Kawanabe M, Krauledat M, Blankertz B. A Bayesian approach for adaptive BCI classification. Proceedings of the 3rd International Brain-Computer Interface Workshop and Training Course, Graz, Austria, 2006; 54-55.
4. Shenoy P, Krauledat M, Blankertz B, Rao R, M̈uller K. Towards adaptive classification for BCI. Journal of Neural Engineering 2006; 3(1):13-23.
5. Penny W, Roberts S, Curran E, Stokes M. EEG-based communication: a pattern recognition approach. IEEE Transactions on Rehabilitation Engineering 2000; 8(2):214-215.
6. Tomioka R, Hill J, Blankertz B, Aihara K. Adapting spatial filtering methods for nonstationary BCIs. Proceedings of Workshop on Information-based Induction Sciences, Osaka, Japan, November 2006; 65-70.
7. Vidaurre C, Schlogl A, Cabeza R, Scherer R, Pfurtscheller G. A fully on-line adaptive BCI. IEEE Transactions on Biomedical Engineering 2006; 53(6):1214-1219.
8. Sykacek P, Roberts S, Stokes M. Adaptive BCI based on variational Bayesian Kalman filtering: an empirical evaluation. IEEE Transactions on Biomedical Engineering 2004; 51(5):719-727.
9. Sykacek P, Roberts S, Stokes M, Curran E, Gibbs M, Pickup L. Probabilistic methods in BCI research. IEEE Transactions on Neural Systems and Rehabilitation Engineering 2003; 11(2):192-194.
10. Blankertz B, Kawanabe M, Tomioka R, Hohlefeld F, Nikulin V, M̈uller K. Invariant common spatial patterns: alleviating nonstationarities in brain-computer interfacing. Advances in Neural Information Processing Systems 2008; 20:113-120.
11. Vidaurre C, Schlogl A, Blankertz B, Kawanabe M, M̈uller K. Unsupervised adaptation of the LDA classifier for brain-computer interfaces. Proceedings of the 4th International Brain-Computer Interface Workshop and Training Course 2008; 2008:122-127.
12. Liu H, Wang J, Zheng C. Using Self-organizing Map for Mental Tasks Classification in Brain-Computer Interface. Lecture Notes in Computer Science, vol. 3497. Springer: Berlin, 2005; 327-332.
13. Buttfield A, Ferrez P, del RMillan J. Towards a robust BCI: error potentials and online learning. IEEE Transactions on Neural Systems and Rehabilitation Engineering 2006; 14(2):164.
14. Blankertz B, Curio G, Muller K. Classifying single trial EEG: towards brain computer interfacing. Advances in Neural Information Processing Systems 2002; 1:157-164.
15. Pfurtscheller G, Neuper C, Guger C, Harkam W, Ramoser H, Schlogl A, Obermaier B, Pregenzer M. Current trends in Graz brain-computer interface (BCI) research. IEEE Transactions on Rehabilitation Engineering 2000; 8(2):216-219.
16. Birbaumer N, Hinterberger T, Kubler A, Neumann N. The thought-translation device (TTD): neurobehavioral mechanisms and clinical outcome. IEEE Transactions on Neural Systems and Rehabilitation Engineering 2003; 11(2):120-123.
17. Millan J, Mouri{ogonek}no J. Asynchronous BCI and local neural classifiers: an overview of the adaptive brain interface project. IEEE Transactions on Neural Systems and Rehabilitation Engineering 2003; 11(2):159-161.
18. Vidaurre C, Schlogl A, Cabeza R, Scherer R, Pfurtscheller G. Study of on-line adaptive discriminant analysis for EEG-based brain computer interfaces. IEEE Transactions on Biomedical Engineering 2007; 54(3):550-556.
19. Sugiyama M, Krauledat M, M̈uller K. Covariate shift adaptation by importance weighted cross validation. The Journal of Machine Learning Research 2007; 8:985-1005.
20. Gan J. Self-adapting BCI Based on Unsupervised Learning. Third International Workshop on Brain-Computer Interfaces, Graz, Austria, 2006; 50-51.
21. Eren S, Grosse-Wentrup M, Buss M. Unsupervised classification for non-invasive brain-computer interfaces. Proceedings of Automed Workshop. VDI Verlag: D̈usseldorf, Germany, October 2007; 65-66.
22. Blumberg J, Rickert J, Waldert S, Schulze-Bonhage A, Aertsen A, Mehring C. Adaptive classification for brain computer interfaces. Conference Proceedings-IEEE Engineering in Medicine and Biology Society. IEEE: New York, 2007; 2536-2539.
23. Fukunaga K. Introduction to Statistical Pattern Recognition. Academic Press: New York, 1990.
24. M̈uller-Gerking J, Pfurtscheller G, Flyvbjerg H. Designing optimal spatial filters for single-trial EEG classification in a movement task. Clinical Neurophysiology 1999; 110(5):787-798.
25. Duda R, Hart P, Stork D. Pattern Classification (2nd edn). Wiley: New York, 2001.
26. Jasper H. The ten-twenty electrode system of the international federation in electroencephalography and clinical neurophysiology. EEG Journal 1958; 10:371-375.
27. Oostenveld R, Praamstra P. The five percent electrode system for high-resolution EEG and ERP measurements. Clinical Neurophysiology 2001; 112(4):713-719.