Adaptive subject-based feature extraction in brain–computer interfaces using wavelet packet best basis decomposition

References 

1. Wolpaw JR, Birbaumer N, Heetderks WJ. Brain computer interface technology: a review of the first international meeting. IEEE Trans Rehab Eng. 2000;8(2):64–73
2. Millán JdR, Mouriño J, Franzé M, Cincotti F, Varsta M. A local neural classifier for the recognition of EEG patterns associated to mental tasks. IEEE Trans Neural Networks. 2002;13(3):678–686
3. Millán JdR, Mouriño J. Asynchronous BCI and local neural classifiers: an overview of the adaptive brain interface project. IEEE Trans Neural Syst Rehab Eng. 2003;11(2):159–161
4. Wolpaw JR, McFarland DJ, Neat GW, Forneris CA. An EEG-based brain–computer interface for cursor control. Electroenceph Clin Neurophysiol. 1991;78(3):252–259
5. Birbaumer N, Ghanayim N, Hinterberger T, Iversen I, Kotchoubey B. A spelling device for the paralyzed. Nature. 1999;398:297–298
   • MEDLINE
   • CrossRef
6. Burke DP, Kelly SP, Chazal PD, Reilly RB, Finucane C. A parametric feature extraction and classification strategy for brain–computer interfacing. IEEE Trans Neural Syst Rehab Eng. 2005;13(1):12–17
7. Pei XM, Zheng CX. Feature extraction and classification of brain motor imagery task based on MVAR model. In: Proceedings of the Third International Conference on Machine Learning and Cybernetics. 2004;p. 3726–3730
8. Keirn ZA, Aunon JI. A new mode of communication between man and his surroundings. IEEE Trans Biomed Eng. 1990;37(12):1209–1214
   • MEDLINE
   • CrossRef
9. Anderson CW, Stolz EA, Shamsunder S. Multivariate autoregressive models for classification of spontaneous electroencephalographic signals. IEEE Trans Biomed Eng. 1998;45(3):277–286
   • MEDLINE
   • CrossRef
10. Graimann B, Huggins JE, Levine SP. Toward a direct brain interface based on human subdural recordings and wavelet-packet analysis. IEEE Trans Biomed Eng. 2004;51(6):954–962
    • MEDLINE
    • CrossRef
11. Xue JZ, Zhang H, Zheng CX, Yan XG. Wavelet packet transform for feature extraction of EEG during mental tasks.. In: Proceedings of the Second International Conference on Machine Learning and Cybernetics. 2003;p. 360–363
12. Galka A. Topics in non-linear time series analysis: with implications for EEG analysis. Advanced series in non-linear dynamics. World Science Publishers; 2000;
13. Vuckovic A, Radivojevic V, Andrew CN Chen, Popovic D. Automatic recognition of alertness and drowsiness from EEG by an artificial neural network an artificial neural network. Med Eng Phys. 2002;24(5):349–360
    • Abstract
    • Full Text
    • Full-Text PDF (251 KB)
    • CrossRef
14. Wu Ya, Du R. Feature extraction and assessment using wavelet packets for monitoring of machining processes. Mech Syst Signal Process. 1996;10(1):29–53
15. Doppelmayr M, Klimesch W, Pachinger T, Ripper B. Individual differences in brain dynamics: important implications for the calculation of event-related band power. Biol Cybern. 1998;79(1):49–57
    • MEDLINE
    • CrossRef
16. Unser M, Aldroubi A. A review of wavelets in biomedical application. Proc IEEE. 1996;84(4):626–638
17. Mallat S. A wavelet tour of signal processing. 2nd ed.. San Diego, CA: Academic Press; 1999;
18. Saito N, Coifman RR. Local discriminant bases and their applications. J Math Vis Imag. 1995;5(4):337–358
19. Tian YJ, Qi ZQ. A new support vector machine for multi-class classification.. In: Proceedings of the fifth international conference on computer and information technology. 2005;
20. Jasper HH. The ten twenty electrode system of the International Federation. Electroenceph Clin Neurophysiol. 1958;10:371–375
21. Mao KZ, Tan KC, Ser W. Probabilistic neural-network structure determination for pattern classification. IEEE Trans Neural Networks. 2000;11(4):1010–1017