9 Computational EEG Analysis for Brain-Computer Interfaces
213
10. L.A. Farwell, E. Donchin, Talking off the top of your head: toward a mental prosthesis utilizing
event-related brain potentials. Electroencephalogr. Clin. Neurophysiol. 70(6), 510–523 (1988)
11. R. Fazel-Rezai, B.Z. Allison, C. Guger, E.W. Sellers, S.C. Kleih, A. Kübler, P300 brain computer interface: current challenges and emerging trends. Front. Neuroeng. 5, 14 (2012)
12. A. Hyvärinen, E. Oja, Independent component analysis: algorithms and applications. Neural.
Netw. 13, 411–430 (2000)
13. S.P. Kelly, E.C. Lalor, R.B. Reilly, J.J. Foxe, Visual spatial attention tracking using highdensity SSVEP data for independent brain-computer communication. IEEE Trans. Neural Syst.
Rehabil. Eng. 13, 172–178 (2005)
14. D.J. Krusienski, E.W. Sellers, F. Cabestaing, S. Bayoudh, D.J. McFarland, T.M. Vaughan,
J.R. Wolpaw, A comparison of classification techniques for the P300 Speller. J. Neural Eng. 3,
299 (2006)
15. D.J. Krusienski, E.W. Sellers, D.J. McFarland, T.M. Vaughan, J.R. Wolpaw, Toward enhanced
P300 speller performance. J. Neurosci. Methods 167, 15–21 (2008)
16. S. Lemm, B. Blankertz, G. Curio, K.R. Muller, Spatio-spectral filters for improving the classification of single trial EEG. IEEE Trans. Biomed. Eng. 52, 1541–1548 (2005)
17. Z. Lin, C. Zhang, W. Wu, X. Gao, Frequency recognition based on canonical correlation analysis
for SSVEP-based BCIs. IEEE Trans. Biomed. Eng. 54, 1172–1176 (2007)
18. F. Lotte, M. Congedo, A. Lécuyer, F. Lamarche, B. Arnaldi, A review of classification algorithms for EEG-based brain–computer interfaces. J. Neural Eng. 4, R1 (2007)
19. S. Makeig, S. Enghoff, T.P. Jung, T.J. Sejnowski, A natural basis for efficient brain-actuated
control. IEEE Trans. Neural Syst. Rehabil. Eng. 8, 208–211 (2000)
20. S. Mallat, A Wavelet Tour of Signal Processing (Academic Press, Orlando, FL, 2008)
21. D.J. McFarland, D.J. Krusienski, W.A. Sarnacki, J.R. Wolpaw, Emulation of computer mouse
control with a noninvasive brain–computer interface. J. Neural Eng. 5, 101 (2008)
22. D.J. McFarland, L.M. McCane, S.V. David, J.R. Wolpaw, Spatial filter selection for EEG-based
communication. Electroencephalogr. Clin. Neurophysiol. 103, 386–394 (1997)
23. D.J. McFarland, W.A. Sarnacki, J.R. Wolpaw, Should the parameters of a BCI translation
algorithm be continually adapted? J. Neurosci. Methods 199, 103–107 (2011)
24. D.J. McFarland, J.R. Wolpaw, Sensorimotor rhythm-based brain–computer interface (BCI):
model order selection for autoregressive spectral analysis. J. Neural Eng. 5, 155 (2008)
25. K.R. Muller, C.W. Anderson, G.E. Birch, Linear and nonlinear methods for brain-computer
interfaces. IEEE Trans. Neural Syst. Rehabil. Eng. 11, 165–169 (2003)
26. J. Müller-Gerking, G. Pfurtscheller, H. Flyvbjerg, Designing optimal spatial filters for singletrial EEG classification in a movement task. Clin. Neurophysiol. 110, 787–798 (1999)
27. A.M. Norcia, L.G. Appelbaum, J.M. Ales, B.R. Cottereau, B. Rossion, The steady-state visual
evoked potential in vision research: a review. J. Vis. 15, 4 (2015)
28. J. Proakis, D. Manolakis, Digital Signal Processing: Principles, Algorithms and Applications
(Prentice Hall, New York, NY, US, 2007)
29. L. Qin, B. He, A wavelet-based time–frequency analysis approach for classification of motor
imagery for brain–computer interface applications. J. Neural Eng. 2, 65 (2005)
30. H. Ramoser, J. Muller-Gerking, G. Pfurtscheller, Optimal spatial filtering of single trial EEG
during imagined hand movement. IEEE Trans. Rehabil. Eng. 8, 441–446 (2000)
31. E.W. Sellers, D. Krusienski, D. Mcfarland, J. Wolpaw, Non-invasive brain-computer interface
research at the wadsworth center, in Toward Brain-Computer Interfacing, ed. by G. Dornhege,
J.R. Millan, T. Hinterberger, D.J. McFarland, K.R. Muller (The MIT Press, Cambridge, 2007),
pp. 31–42
32. J.R. Wolpaw, D.J. McFarland, Multichannel EEG-based brain-computer communication. Electroencephalogr. Clin. Neurophysiol. 90, 444–449 (1994)
33. J.R. Wolpaw, D.J. McFarland, Control of a two-dimensional movement signal by a noninvasive
brain-computer interface in humans. Proc. Natl. Acad. Sci. USA 101, 17849–17854 (2004)
213
10. L.A. Farwell, E. Donchin, Talking off the top of your head: toward a mental prosthesis utilizing
event-related brain potentials. Electroencephalogr. Clin. Neurophysiol. 70(6), 510–523 (1988)
11. R. Fazel-Rezai, B.Z. Allison, C. Guger, E.W. Sellers, S.C. Kleih, A. Kübler, P300 brain computer interface: current challenges and emerging trends. Front. Neuroeng. 5, 14 (2012)
12. A. Hyvärinen, E. Oja, Independent component analysis: algorithms and applications. Neural.
Netw. 13, 411–430 (2000)
13. S.P. Kelly, E.C. Lalor, R.B. Reilly, J.J. Foxe, Visual spatial attention tracking using highdensity SSVEP data for independent brain-computer communication. IEEE Trans. Neural Syst.
Rehabil. Eng. 13, 172–178 (2005)
14. D.J. Krusienski, E.W. Sellers, F. Cabestaing, S. Bayoudh, D.J. McFarland, T.M. Vaughan,
J.R. Wolpaw, A comparison of classification techniques for the P300 Speller. J. Neural Eng. 3,
299 (2006)
15. D.J. Krusienski, E.W. Sellers, D.J. McFarland, T.M. Vaughan, J.R. Wolpaw, Toward enhanced
P300 speller performance. J. Neurosci. Methods 167, 15–21 (2008)
16. S. Lemm, B. Blankertz, G. Curio, K.R. Muller, Spatio-spectral filters for improving the classification of single trial EEG. IEEE Trans. Biomed. Eng. 52, 1541–1548 (2005)
17. Z. Lin, C. Zhang, W. Wu, X. Gao, Frequency recognition based on canonical correlation analysis
for SSVEP-based BCIs. IEEE Trans. Biomed. Eng. 54, 1172–1176 (2007)
18. F. Lotte, M. Congedo, A. Lécuyer, F. Lamarche, B. Arnaldi, A review of classification algorithms for EEG-based brain–computer interfaces. J. Neural Eng. 4, R1 (2007)
19. S. Makeig, S. Enghoff, T.P. Jung, T.J. Sejnowski, A natural basis for efficient brain-actuated
control. IEEE Trans. Neural Syst. Rehabil. Eng. 8, 208–211 (2000)
20. S. Mallat, A Wavelet Tour of Signal Processing (Academic Press, Orlando, FL, 2008)
21. D.J. McFarland, D.J. Krusienski, W.A. Sarnacki, J.R. Wolpaw, Emulation of computer mouse
control with a noninvasive brain–computer interface. J. Neural Eng. 5, 101 (2008)
22. D.J. McFarland, L.M. McCane, S.V. David, J.R. Wolpaw, Spatial filter selection for EEG-based
communication. Electroencephalogr. Clin. Neurophysiol. 103, 386–394 (1997)
23. D.J. McFarland, W.A. Sarnacki, J.R. Wolpaw, Should the parameters of a BCI translation
algorithm be continually adapted? J. Neurosci. Methods 199, 103–107 (2011)
24. D.J. McFarland, J.R. Wolpaw, Sensorimotor rhythm-based brain–computer interface (BCI):
model order selection for autoregressive spectral analysis. J. Neural Eng. 5, 155 (2008)
25. K.R. Muller, C.W. Anderson, G.E. Birch, Linear and nonlinear methods for brain-computer
interfaces. IEEE Trans. Neural Syst. Rehabil. Eng. 11, 165–169 (2003)
26. J. Müller-Gerking, G. Pfurtscheller, H. Flyvbjerg, Designing optimal spatial filters for singletrial EEG classification in a movement task. Clin. Neurophysiol. 110, 787–798 (1999)
27. A.M. Norcia, L.G. Appelbaum, J.M. Ales, B.R. Cottereau, B. Rossion, The steady-state visual
evoked potential in vision research: a review. J. Vis. 15, 4 (2015)
28. J. Proakis, D. Manolakis, Digital Signal Processing: Principles, Algorithms and Applications
(Prentice Hall, New York, NY, US, 2007)
29. L. Qin, B. He, A wavelet-based time–frequency analysis approach for classification of motor
imagery for brain–computer interface applications. J. Neural Eng. 2, 65 (2005)
30. H. Ramoser, J. Muller-Gerking, G. Pfurtscheller, Optimal spatial filtering of single trial EEG
during imagined hand movement. IEEE Trans. Rehabil. Eng. 8, 441–446 (2000)
31. E.W. Sellers, D. Krusienski, D. Mcfarland, J. Wolpaw, Non-invasive brain-computer interface
research at the wadsworth center, in Toward Brain-Computer Interfacing, ed. by G. Dornhege,
J.R. Millan, T. Hinterberger, D.J. McFarland, K.R. Muller (The MIT Press, Cambridge, 2007),
pp. 31–42
32. J.R. Wolpaw, D.J. McFarland, Multichannel EEG-based brain-computer communication. Electroencephalogr. Clin. Neurophysiol. 90, 444–449 (1994)
33. J.R. Wolpaw, D.J. McFarland, Control of a two-dimensional movement signal by a noninvasive
brain-computer interface in humans. Proc. Natl. Acad. Sci. USA 101, 17849–17854 (2004)