Pattern recognition for brain-computer interfaces by combining support vector machine with adaptive genetic algorithm

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4689 LNBI, Issue , 2007, Pages 307-316

  Yang, Banghua ^a   Ma, Shiwei ^a   Li, Zhihua ^a  

^a SHANGHAI UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ADAPTIVE ALGORITHMS; ELECTROENCEPHALOGRAPHY; GENETIC ALGORITHMS; MATHEMATICAL MODELS; PARAMETER ESTIMATION; PROBLEM SOLVING; SUPPORT VECTOR MACHINES;

BRAIN COMPUTER INTERFACES (BCI); HYBRID OPTIMIZATION; MOTOR IMAGINATIONS; SYNCHRONOUS OPTIMIZATION;

PATTERN RECOGNITION;

EID: 38049110805     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-74771-0_35     Document Type: Conference Paper

References (13)

1. Wolpaw, J.R., Birbaumer, N., Heetderks, W.J.: Brain computer interface technology: a review of the first international meeting. IEEE Trans. Rehab. Eng. 8, 64-73 (2000)
2. Millán, J.d.R., Mouriño, J., Franzé, M., Cincotti, F.: A local neural classifier for the recognition of EEG patterns associated to mental tasks. IEEE Trans. Neural Networks 13, 678-686 (2002)
3. Millán, J.d.R.: Adaptive brain interfaces. Commun. ACM 46, 74-80 (2003)
4. Wolpaw, J.R., McFarland, D.J., Neat, G.W., Forneris, C.A.: An EEG-based brain-computer interface for cursor control. Electroenceph. Clin. Neurophysiol. 78, 252-259 (1991)
5. Schroder, M., Bogdan, M., Rosenstiel, W., Hinterberger, T. (ed.): Automated EEG Feature Selection for Brain Computer Interfaces. In: Proc. 1st Int. IEEE EMBS Conf. Neural Engineering, Capri Island, Italy, pp. 626-629 (2003)
6. Garrett, D., Peterson, D.A., Anderson, C.W., Thaut, M.H.: Comparison of Linear, Nonlinear, and Feature Selection Methods for EEG Signal Classification. IEEE Trans. Neural Syst. Rehab. Eng. 11, 141-144 (2003)
7. Graimann, B., Huggins, J.E., Levine, S.P., Pfurtscheller, G.: Detection of ERP and ERD/ERS patterns in single ECoG channels. In: Proc. 1st Int. IEEE EMBS Conf. Neural Engineering, Capri Island, Italy, pp. 614-617 (2003)
8. Yom-Tov, E., Inbar, G.F.: Feature selection for the classification of movements from single movement-related potentials. IEEE Trans. Neural Syst. Rehab. Eng. 10, 170-177 (2002)
9. Kaper, M., Meinicke, P., Grossekathoefer, U., Lingner, T., Ritter, H.: BCI Competition 2003 - Data Set IIb: Support Vector Machines for the P300 Speller Paradigm. IEEE Trans. Biomed. Eng. 51, 1073-1076 (2004)
10. Lal, T.N., Schröder, M., Hinterberger, T., Weston, J., Bogdan, M., Birbaumer, N., Schölkopf, B.: Support vector channel selection in BCI. IEEE Trans. Biomed. Eng. 51, 1003-1010 (2004)
11. Guangnan, X., Ruiwei, C.: Genetic Algorithm and Engineering Optimization. Tsinghua, Beijing, China (2004)
12. Brett, D.M., Justin, W., Sebastian Seung, H.: BCI competition 2003-Data Set Ia: combining gamma-band power with slow cortical potentials to improve single-trial classification of electroencephalographic signals. IEEE Trans. Biomed. Eng. 51, 1052-1056 (2004)
13. Guozheng, Y., Ting, W., Banghua, Y.: Automated feature selection based on an adaptive genetic algorithm for brain-computer interfaces. LNCS, pp. 575-582 (2006)