Comparison between effective features used for the Bayesian and the SVM classifiers in BCI

Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings

Volumn 7 VOLS, Issue , 2005, Pages 5365-5368

  Arbabi, E ^b   Shamsollahi, M B ^b   Sameni, R ^a  

^a IEEE

^b NONE

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; BIOELECTRIC POTENTIALS; FEATURE EXTRACTION; HUMAN COMPUTER INTERACTION; NEUROPHYSIOLOGY; STATISTICAL METHODS;

BRAIN COMPUTER INTERFACE (BCI); DISCRIMINATION ALGORITHMS; SCALP; SUPPORT VECTOR MACHINES (SVM);

LEARNING SYSTEMS;

EID: 33846912022     PISSN: 05891019     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/iembs.2005.1615694     Document Type: Conference Paper

References (17)

1. M. A. L. Nicolelis , N. Birbaumer and K..-L. Muller, "Guest Editorial," IEEE Trans. Biomed. Eng., vol. 51, pp. 877-879, June 2004.
2. Y. Li, X. Gao, H. Liu, and S. Gao, "Classification of Single-Trial Electroencephalogram During Finger Movement," IEEE Trans. Biomed. Eng., vol. 51, pp. 1019-1025, June 2004.
3. R. Scherer, G. R. Muller, C. Neuper, B. Graimann, and G. Pfurtscheller, "An Asynchronously Controlled EEG-Based Virtual Keyboard: Improvement of the Spelling Rate," IEEE Trans. Biomed. Eng., vol. 51, pp. 979-984, June 2004.
4. E. Arbabi and M. B. Shamsollahi, "Discrimination between 'reading concentration' and 'listening concentration' in electroencephalogram," Int. Con. on Biological and Medical Physics (ICBMP05), UAE, Al-Ain, March 2005.
5. M. Dash, H. Liu, "Feature Selection for Classification," Intelligent Data Analysis, vol 1, pp. 131-156, 1997.
6. nd Ed., San Diego, CA: Academic Press, 2003.
7. T. Lal, T. Hinterberger, G. Widman, M. Schröder, J. Hill, W. Rosenstiel, C. Elger, B. Schölkopf, and N. Birbaumer, "Methods Towards Invasive Human Brain Computer Interfaces," Advances in Neural Information Processing Systems (NIPS), 2004 (to appear).
8. C. L. Nikias and A. P. Petropula, Higher - Order Spectra Analysis, NJ, Englewood Cliffs: PTR Prentice Hall, 1993.
9. N. M. Branston, W. El-Deredy, and F. P. McGlone, "Changes in neural complexity of the EEG during a visual oddball task," Clinical Neurophysiology, pp. 1-9, 2004.
10. A. Lempel and J. Ziv, "On complexity of finite sequences," IEEE Trans. on Inform. Theor., vol. 22, pp. 75-88, 1976.
11. S. Tong, A. Bezerianos, A. Malhotra, Y. Zhu, and N. Thakor, "Parameterized entropy analysis of EEG following hypoxic-ischemic brain injury," Physics Letters A, vol. 314, pp. 354-361, 2003.
12. S. M. Pincus, "Approximation entropy as a measure of system complexity," Proc. Natl. Acad. Sci. USA 88,1991, pp. 2297-2301.
13. R. M. Rangayyan, Biomedical Signal Processing, NYC, NY: Johns Wiely & Sons Inc., 2002.
14. International Pharmaco EEG Society, [Online]. Available: http://www.ipeg.demon.nl/.
15. A. Cohen, Biomedical Signal Processing, Vol. II, CRC Press Inc., Boca Raton, Florida, 2000, pp. 39-50.
16. P.-H. Chen, C.-J. Lin, and B. Schölkopf, "A Tutorial on v-Support Vector Machines."
17. J. Ma, Y. Zhao, and S. Ahalt, OSU SVM Classifier Matlab Toolbox (ver 3.00).