EEG signal classification for real-time brain-computer interface applications: A review

2011 4th International Conference on Mechatronics: Integrated Engineering for Industrial and Societal Development, ICOM'11 - Conference Proceedings

Volumn , Issue , 2011, Pages

  Khorshidtalab, A ^a   Salami, M J E ^a  

^a INTERNATIONAL ISLAMIC UNIVERSITY MALAYSIA   (Malaysia)

Author keywords

Brain Computer Interface; EEG; realtime signal processing

Indexed keywords

BRAIN ACTIVITY; BRAIN WAVE; BRAIN-COMPUTER INTERFACE APPLICATIONS; CONTROL DEVICE; CONTROL ROBOTS; CONTROLLING DEVICES; EEG SIGNAL CLASSIFICATION; EEG SIGNALS; ELECTROENCEPHALOGRAM SIGNALS; FEASIBLE ALTERNATIVES; REAL-TIME SIGNAL PROCESSING; SEVERE DISABILITIES; STATE OF RESEARCH; REALTIME SIGNAL PROCESSING;

BRAIN; COMPUTER APPLICATIONS; ELECTROENCEPHALOGRAPHY; INTERFACES (COMPUTER); MECHATRONICS; SIGNAL PROCESSING;

BRAIN COMPUTER INTERFACE;

EID: 79961192889     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICOM.2011.5937125     Document Type: Conference Paper

References (33)

1. Ebrahimi, T., Vesin, J.M., Garcia, G. "Brain-Computer Interfaces in Multimedia Communication," IEEE Signal Processing Magazine, Vol. 20 14-24,2003.
2. Wolpaw, J.R., Birbaumer, N., McFarland, D.J., Pfurtscheller, G., Vaughan, T.M.: "Brain-Computer Interfaces for Communication and Control," Clinical Neurophysiology,Vol. 113, 767-791,2002. (Pubitemid 34621187)
3. F. Lotte, M. Congedo, A. Lecuyer, F. Lamarche, and B. Arnaldi, "A review of classification algorithms for eegbased brain-computer interfaces," Journal of Neural Engineering, vol. 4,. R1-R13, 2007. (Pubitemid 46603810)
4. Milĺan, J.R. "On the Need for On-Line Learning in Brain-Computer Interfaces," Proceedings of 2004. International Joint Conference on Neural Networks. Budapest,Hungary 2004.
5. R. Bogacz, U. Markowska-Kaczmar, A. Kozik."Blinking artefact recognition in EEG signal using artificial neural network" In Proc. of 4th Conference on Neural Networks and Their Applications, Zakopane p.6,1999.
6. Allen, P.J., Josephs, O., Turner, R."A method for removing imaging artifact from continuous EEG recorded during functional MRI. Neuro-Image" 12, 230-239, 2000. (Pubitemid 30627023)
7. Niazy, R.K., Beckmann, C.F., Iannetti, G.D., Brady, J.M., Smith, S.M." Removal of FMRI environment artifacts from EEG data using optimal basis sets. NeuroImage 28,720-737,2005. (Pubitemid 41541965)
8. G. Srivastava.,S. Crottaz-Herbette,K.M Lau, Glover, G.H., Menon, V. "ICA-based procedures for removing ballistocardiogram artifacts from EEG data acquired in the MRI scanner". NeuroImage 24, 50-60.2005. (Pubitemid 39611025)
9. A. Schlogl C. Keinrath, D. Zimmermann, R. Scherer, R. Leeb, and G. Pfurtscheller, "A fully automated correction method of eog artifacts in eeg recordings," Clin Neurophysiol, vol. 118, no. 1, 98-104, 2007. (Pubitemid 44960931)
10. M. Phothisonothai and M.Nakagawa, "EEG Signal Classification Method Based on Fractal Features and Neural Network," 30th Annual International IEEE EMBS Conf. Vancouver, British Columbia, Canada, Aug. 20-24, 2008.
11. M. Sabeti, S.D. Katebi, R. Boostani, G.W. Price "A new approach for EEG signal classification of schizophrenic and control participants"Expert Systems with Applications 38, 2063-2071.2011.
12. K. Akrofi, R. Pal, M C. Baker, BS. Nutter1, R W. Schiffer "Classification of Alzheimer's Disease And Mild Cognitive impairment by pattern recognition of EEG Power and coherence" IEEE ICASSP,2010.
13. V. Jeybalan, A. Samraj, L. Chu Kiong, "Motor Imaginary Signal Classification using Adaptive Recursive Bandpass Filter and Adaptive Autoregressive Models for Brain Machine Interface Designs," International Journal of Biological and Medical Sciences, 2008.
14. W. Qiu, K. S. M. Fung, F. H. Y. Chan, F. K. Lam, P. W. F. Poon, and R. P. Hamernik, "Adaptive filtering of evoked potentials with Radial-Basis-Functions neural network prefilter," IEEE Trans. Biomed. Eng., vol. 49, 225-212,2002.
15. J. F. Borisoff, S. G. Mason, A. Bashashati, and G. E. Birch, "Brain-Computer Interface design for asynchronous control applications: improvements to the LF-ASD asynchronous brain switch," IEEE Trans. Biomed. Eng., vol. 51, June,. 985-993,2002.
16. B. O. Peters, G. Pfurscheller, and H. Flyvjberg, " Automaticdifferentiation of multichannel EEG signals," IEEE Trans. Biomed. Eng., vol. 48 (1), Jan. 111-116,2001.
17. D. Coyle, G. Prasad, and T. M. McGinnity, "A time-series prediction approach for feature extraction in a Brain-Computer Interface," IEEETrans. Neur. Syst. Rehabil. Eng., vol. 13, Dec, 461-467,2005. (Pubitemid 43015552)
18. C. Bigan, M. Ungureanu, R. Strungaru, and V. Lazarescu, "Mixture of Densities Approach for EEG Signals Source Separation," in Proc. 2nd European Medical&Biological Engineering Conference, Vienna, Austria, December,604-605.2002.
19. T.-P. Jung, S. Makeing, M. Westerfield, J. Townsend, E.Courchesne, T. J. Sejnowski, "Analysis and visualisation of singletrial event-related potentials," Human Brain Mapping, vol. 14, Nov. 166-185.2001. (Pubitemid 33032349)
20. V. Bostanov, "BCI Competition 2003-Data sets Ib and IIb," Feature extraction from Event-Related brain potentials with the continuous wavelet transform and t-Value scalogram," IEEE Trans. Biomed. Eng., vol. 51, June. 1057-1061.2004.
21. Pfurtscheller G, Neuper C, Schlögl A, Lugger K. "Separability of EEG signals recorded during right and left motor imagery using adaptive autoregressive parameters,". IEEE Trans Rehabil Eng;6:316-325.1998. (Pubitemid 28409340)
22. E. Haselsteiner and G. Pfurtscheller, "Using time dependent neural networks for EEG classification," IEEE Trans. Rehab. Eng., vol. 6,.457-463, Dec. 2000. (Pubitemid 32178933)
23. Tavakolian, A. M. Nasrabadi, S. Rezaei, "Selecting Better EEG channels for classification of Mental Tasks,", In the Proceedings of the IEEE International Symposium On Circuits and Systems ISCAS, pages 537-540, Vancouver, Canada, May,2004.
24. S. Rezaei, K. Tavakolian, A. M. Nasrabadi, and S. K. Setarehdan. "Different classification techniques considering brain computer interface applications," Journal of Neural Engineering," 3:139-144, 2006. (Pubitemid 43841062)
25. D. Coyle,G. Prasad and T M.McGinnity, "Extracting features for a brain-computer interface by self-organising fuzzy neural network-based time series prediction," Proc. 26th Annual Int. Conf. of the IEEE Engineering in Medicine and Biology Society (San Francisco, CA) 4371-4,2004. (Pubitemid 40035224)
26. Sun, S., Zhang, C., & Zhan, D." An experimental evaluation of ensemble methods for EEG signal classification," Pattern Recognition Letters, 28, 2157-2163.2007. (Pubitemid 47418328)
27. O. AlZoubi, I. Koprinska, and R. A. Calvo, "Classification of braincomputer interface data," in AusDm08, The Australasian Data Mining Conference: AusDM 2008 Stamford Grand, Glenelg, Adelaide, 27-28 November 2008.
28. H. Gandhi, D. Green, J. Kounios, C.M. Clark, and R. Polikar "Stacked Generalization for Early Diagnosis of Alzheimer's Disease," Proceedings of the 28th IEEE EMBS Annual International Conference New York City, USA, Aug 30-Sept 3, 2006
29. J.R. Wolpaw, D.J. McFarland, G.W. Neat, and C.A. Forneris. "An EEG-based brain-computer interface for cursor control,". Electroenceph. Clin. Neurophysiol., v.78,pp. 252-258, 1991.
30. G. Pfurtscheller, J. Kalcher, Ch. Neuper, D. Flotzinger, and M. Pregenzer, "On-line EEG classification during externally-paced hand movements using a neural networkbased classifier", Electroenceph. Clin. Neurophysiol.", v.99, pp. 416-425, 1996. (Pubitemid 27013887)
31. Lehtonen, J., Jylanki, P., Kauhanen, L., Sams, M.: Online Classification of Single EEG Trials During Finger Movements. IEEE Trans. on Biomed. Eng. 55(2 Pt 1), 713-720,2008.
32. K.-R. Müller, M. Tangermann, G. Dornhege, M. Krauledat, G. Curio,and B. Blankertz, "Machine learning for real-time single-trial EEGanalysis: From brain-computer interfacing to mental state monitoring,"J Neurosci Methods, vol. 167, no. 1, pp. 82-90, 2008. (Pubitemid 350180089)
33. A. Kumru, M.N Mohanty,and A. Routray "Design Of Support Vector Machines With Time Frequency Kernels For Classification Of EEG Signal" Proceedings of the 2010 IEEE Students' Technology Symposium, IIT Kharagpur, 2010.