BZ Allison, C Brunner, V Kaiser, GR Mullerputz, C Neuper, G Pfurtscheller. Toward a hybrid brain-computer interface based on imagined movement and visual attention. J Neural Eng 2010, 7: 026007.
JJ Vidal. Real-time detection of brain events in EEG. Proc IEEE 1977, 65(5): 633-641.
J Kalcher, D Flotzinger, C Neuper, S Gölly, G Pfurtscheller. Graz brain-computer interface II: towards communication between humans and computers based on online classification of three different EEG patterns. Med Biol Eng Comput 1996, 34(5): 382-388.
LA Farwell, E Donchin. Talking off the top of your head: toward a mental prosthesis utilizing event-related brain potentials. Electroencephalogr Clin Neurophysiol 1988, 70(6): 510-523.
L Yao, XJ Sheng, DG Zhang, N Jiang, D Farina, XY Zhu. A BCI system based on somatosensory attentional orientation. IEEE Trans Neural Syst Rehabil Eng 2017, 25(1): 81-90.
L Yao, XJ Sheng, N Mrachacz-Kersting, XY Zhu, D Farina, N Jiang. Decoding covert somatosensory attention by a BCI system calibrated with tactile sensation. IEEE Trans Biomed Eng 2018, 65(8): 1689-1695.
CR Muller-Putz, R Scherer, C Neuper, G Pfurtscheller. Steady-state somatosensory evoked potentials: Suitable brain signals for brain-computer interfaces? IEEE Trans Neural Syst Rehabil Eng 2006, 14(1): 30-37.
S Ahn, M Ahn, H Cho, S Chan Jun. Achieving a hybrid brain-computer interface with tactile selective attention and motor imagery. J Neural Eng 2014, 11(6): 066004.
C Breitwieser, C Pokorny, RM Gernot, P Müller-Putz. A hybrid three-class brain-computer interface system utilizing SSSEPs and transient ERPs. J Neural Eng 2016, 13(6): 066015.
BZ Allison, J Faller, CH Neuper. BCIs that use steady-state visual evoked potentials or slow cortical potentials. In Brain-Computer Interfaces: Principles and Practice. J Wolpaw, EW Wolpaw, Eds. Oxford: Oxford University Press, 2012.
N Birbaumer, N Ghanayim, T Hinterberger, I Iversen, B Kotchoubey, A Kübler, J Perelmouter, E Taub, H Flor. A spelling device for the paralysed. Nature 1999, 398(6725): 297-298.
E Sellers, Y Arbel, E Donchin. BCIs that uses P300 event-related potentials. In Brain-Computer Interfaces: Principles and Practice. J Wolpaw, EW Wolpaw, Eds. Oxford: Oxford University Press, 2012.
EE Sutter. The brain response interface: communication through visually-induced electrical brain responses. J Microcomput Appl 1992, 15(1): 31-45.
JJ Vidal. Toward direct brain-computer communication. Annu Rev Biophys Bioeng 1973, 2: 157-180.
BZ Allison, EW Wolpaw, JR Wolpaw. Brain-computer interface systems: Progress and prospects. Expert Rev Med Devices 2007, 4(4): 463-474.
C Brunner, BZ Allison, DJ Krusienski, V Kaiser, GR Müller-Putz, G Pfurtscheller, C Neuper. Improved signal processing approaches in an offline simulation of a hybrid brain-computer interface. J Neurosci Methods 2010, 188(1): 165-173.
M Fatourechi, A Bashashati, RK Ward, GE Birch. EMG and EOG artifacts in brain computer interface systems: A survey. Clin Neurophysiol 2007, 118(3): 480-494.
A Flexer, H Bauer, J Pripfl, G Dorffner. Using ICA for removal of ocular artifacts in EEG recorded from blind subjects. Neural Netw 2005, 18(7): 998-1005.
JF Gao, Y Yang, P Lin, P Wang, CX Zheng. Automatic removal of eye-movement and blink artifacts from EEG signals. Brain Topogr 2010, 23(1): 105-114.
DJ Krusienski, DJ McFarland, JR Wolpaw. An evaluation of autoregressive spectral estimation model order for brain-computer interface applications. In Proceedings of 2006 International Conference of the IEEE Engineering in Medicine and Biology Society, New York, NY, USA, 2006, pp 1323-1326.
J Wang, GZ Xu, L Wang, HY Zhang. Feature extraction of brain-computer interface based on improved multivariate adaptive autoregressive models. In Proceedings of the 2010 3rd International Conference on Biomedical Engineering and Informatics, Yantai, China, 2010, pp 895-898.
T Demiralp, J Yordanova, V Kolev, A Ademoglu, M Devrim, VJ Samar. Time-frequency analysis of single-sweep event-related potentials by means of fast wavelet transform. Brain Lang 1999, 66(1): 129-145.
D Farina, OF do Nascimento, MF Lucas, C Doncarli. Optimization of wavelets for classification of movement-related cortical potentials generated by variation of force-related parameters. J Neurosci Methods 2007, 162(1–2): 357-363.
H Ramoser, J Muller-Gerking, G Pfurtscheller. Optimal spatial filtering of single trial EEG during imagined hand movement. IEEE Trans Rehabil Eng 2000, 8(4): 441-446.
M Grosse-Wentrup, M Buss. Multiclass common spatial patterns and information theoretic feature extraction. IEEE Trans Biomed Eng 2008, 55(8): 1991-2000.
S Lemm, B Blankertz, G Curio, KR Muller. Spatio-spectral filters for improving the classification of single trial EEG. IEEE Trans Biomed Eng 2005, 52(9): 1541-1548.
G Dornhege, B Blankertz, M Krauledat, F Losch, G Curio, KR Muller. Combined optimization of spatial and temporal filters for improving brain-computer interfacing. IEEE Trans Biomed Eng 2006, 53(11): 2274-2281.
Q Novi, CT Guan, TH Dat, P Xue. Sub-band common spatial pattern (SBCSP) for brain-computer interface. In Proceedings of the 2007 3rd International IEEE/ EMBS Conference on Neural Engineering, Kohala Coast, USA, 2007, pp 204-207.
KK Ang, ZY Chin, HH Zhang, CT Guan. Filter bank common spatial pattern (FBCSP) in brain-computer interface. In Proceedings of 2008 IEEE International Joint Conference on Neural Networks, Hong Kong, China, 2008, pp 2390-2397.
EA Mousavi, JJ Maller, PB Fitzgerald, BJ Lithgow. Wavelet common spatial pattern in asynchronous offline brain computer interfaces. Biomed Signal Process Control 2011, 6(2): 121-128.
AS Aghaei, MS Mahanta, KN Plataniotis. Separable common spatio-spectral patterns for motor imagery BCI systems. IEEE Trans Biomed Eng 2016, 63(1): 15-29.
WC Zhang, FC Sun, CQ Tan, SB Liu. Linear dynamical systems modeling for EEG-based motor imagery brain-computer interface. In Proceedings of the 3rd International Conference on Cognitive Systems and Signal Processing, Beijing, China, 2016.
WC Zhang, FC Sun, CQ Tan, SB Liu. Low-rank linear dynamical systems for motor imagery EEG. Comput Intell Neurosci 2016, 2016: 2637603.
X An, DP Kuang, XJ Guo, YL Zhao, LH He. A deep learning method for classification of EEG data based on motor imagery. In Proceedings of the 10th International Conference on Intelligent Computing in Bioinformatics, Taiyuan, China, 2014, pp 203-210.
CQ Tan, FC Sun, WC Zhang, T Kong. Electroencephalography classification in brain-computer interface with manifold constraints transfer. In Proceedings of the 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Honolulu, HI, USA, 2018.
CQ Tan, FC Sun, WC Zhang, T Kong, C Yang, XY Zhang. Adaptive adversarial transfer learning for electroencephalography classification. In Proceedings of 2018 International Joint Conference on Neural Networks, Rio de Janeiro, Brazil, 2018.
CQ Tan, FC Sun, WC Zhang. Deep transfer learning for EEG-based brain computer interface. In Proceedings of 2018 IEEE International Conference on Acoustics, Speech and Signal Processing, Calgary, AB, Canada, 2018.
CQ Tan, FC Sun, WC Zhang, JH Chen, CF Liu. Multimodal classification with deep convolutional-recurrent neural networks for electroencephalography. In Proceedings of the 24th International Conference on Neural Information Processing, Guangzhou, China, 2017.
CQ Tan, FC Sun, WC Zhang, SB Liu, CF Liu. Spatial and spectral features fusion for EEG classification during motor imagery in BCI. In Proceedings of 2017 IEEE EMBS International Conference on Biomedical & Health Informatics, Orlando, FL, USA, 2017, pp 309-312.
ZL Lin, CS Zhang, W Wu, XR Gao. Frequency recognition based on canonical correlation analysis for SSVEP-based BCIs. IEEE Trans Biomed Eng 2006, 53(12): 2610-2614.
J Pan, XR Gao, F Duan, Z Yan, SK Gao. Enhancing the classification accuracy of steady-state visual evoked potential-based brain-computer interfaces using phase constrained canonical correlation analysis. J Neural Eng 2001, 8(3): 036027.
Y Zhang, GX Zhou, QB Zhao, A Onishi, J Jin, XY Wang, A Cichocki. Multiway canonical correlation analysis for frequency components recognition in SSVEP-Based BCIs. In Proceedings of the 18th International Conference on Neural Information Processing, Shanghai, China, 2011, pp 287-295.
Y Zhang, GX Zhou, J Jin, XY Wang, A Cichocki. Frequency recognition in SSVEP-based BCI using multiset canonical correlation analysis. Int J Neural Syst 2014, 24(4): 1450013.
H Cecotti, A Graeser. Convolutional neural network with embedded Fourier transform for EEG classification. In Proceedings of the 2008 19th International Conference on Pattern Recognition, Tampa, FL, USA, 2008, pp 1-4.
B Rivet, A Souloumiac, V Attina, G Gibert. xDAWN algorithm to enhance evoked potentials: application to brain-computer interface. IEEE Trans Biomed Eng 2009, 56(8): 2035-2043.
H Cecotti, A Graser. Convolutional neural networks for P300 detection with application to brain-computer interfaces. IEEE Trans Pattern Anal Mach Intell 2011, 33(3): 433-445.
G Pfurtscheller. Event-related EEG/MEG synchronization and desynchronization: basic principles. Clin Neurophysiol 1999, 110(11): 1842-1857.
V Bostanov. BCI competition 2003-data sets Ib and IIb: feature extraction from event-related brain potentials with the continuous wavelet transform and the t-value scalogram. IEEE Trans Biomed Eng 2004, 51(6): 1057-1061.
M Kaper, P Meinicke, U Grossekathoefer, T Lingner, H Ritter. BCI competition 2003-data set IIb: Support vector machines for the p300 speller paradigm. IEEE Trans Biomed Eng 2004, 51(6): 1073-1076.
A Rakotomamonjy, V Guigue, G Mallet, V Alvarado. Ensemble of SVMs for improving brain computer interface p300 speller performances. In Proceedings of the 15th International Conference on Artificial Neural Networks, Warsaw, Poland, 2005.
A Schlögl, F Lee, H Bischof, G Pfurtscheller. Characterization of four-class motor imagery EEG data for the BCI-competition 2005. J Neural Eng 2005, 2(4): L14-L22.
T Kayikcioglu, O Aydemir. A polynomial fitting and k-NN based approach for improving classification of motor imagery BCI data. Pattern Recognit Lett 2010, 31(11): 1207-1215.
E Haselsteiner, G Pfurtscheller. Using time-dependent neural networks for EEG classification. IEEE Trans Rehabil Eng 2000, 8(4): 457-463.
MK Hazrati, A Erfanian. An online EEG-based brain-computer interface for controlling hand grasp using an adaptive probabilistic neural network. Med Eng Phys 2010, 32(7): 730-739.
T Felzer, B Freisieben. Analyzing EEG signals using the probability estimating guarded neural classifier. IEEE Trans Neural Syst Rehabil Eng 2003, 11(4): 361-371.
G Pfurtscheller, T Solis-Escalante, R Ortner, P Linortner, GR Muller-Putz. Self-paced operation of an SSVEP-based orthosis with and without an imagery-based “brain switch”: A feasibility study towards a hybrid BCI. IEEE Trans Neural Syst Rehabil Eng 2010, 18(4): 409-414.
WC Zhang, FC Sun, CF Liu, WH Su, CQ Tan, SB Liu. A hybrid EEG-based BCI for robot grasp controlling. In Proceedings of 2017 IEEE International Conference on Systems, Man, and Cybernetics, Banff, Canada, 2017, pp 3278-3283.
BZ Allison, C Brunner, V Kaiser, GR Muller-Putz, C Neuper, G Pfurtscheller. Toward a hybrid brain-computer interface based on imagined movement and visual attention. J Neural Eng 2010, 7(2): 026007.
F Duan, DX Lin, WY Li, Z Zhang. Design of a multimodal EEG-based hybrid BCI system with visual servo module. IEEE Trans Auton Ment Dev 2015, 7(4): 332-341.
RC Panicker, S Puthusserypady, Y Sun. An asynchronous P300 BCI with SSVEP-based control state detection. IEEE Trans Biomed Eng 2011, 58(6): 1781-1788.
S Mouli, R Palaniappan. Hybrid BCI utilising SSVEP and P300 event markers for reliable and improved classification using LED stimuli. In Proceedings of 2017 IEEE Symposium on Computer Applications & Industrial Electronics, Langkawi, Malaysia, 2017, pp 127-131.
YQ Li, JH Pan, F Wang, ZL Yu. A hybrid BCI system combining P300 and SSVEP and its application to wheelchair control. IEEE Trans Biomed Eng 2013, 60(11): 3156-3166.
Y Su, Y Qi, JX Luo, B Wu, F Yang, Y Li, YT Zhuang, XX Zheng, WD Chen. A hybrid brain-computer interface control strategy in a virtual environment. J Zhejiang Univ Sci C 2011, 12(5): 351-361.
H Riechmann, N Hachmeister, H Ritter, A Finke. Asynchronous, parallel on-line classification of P300 and ERD for an efficient hybrid BCI. In Proceedings of the 2011 5th International IEEE/EMBS Conference on Neural Engineering, Cancun, Mexico, 2011, pp 412-415.
S Bhattacharyya, A Konar, DT Tibarewala. Motor imagery, P300 and error-related EEG-based robot arm movement control for rehabilitation purpose. Med Biol Eng Comput 2014, 52(12): 1007-1017.
L Yao, XJ Sheng, DG Zhang, N Jiang, N Mrachacz-Kersting, XY Zhu, D Farina. A stimulus-independent hybrid BCI based on motor imagery and somatosensory attentional orientation. IEEE Trans Neural Syst Rehabil Eng 2017, 25(9): 1674-1682.
SG Mason, GE Birch. A brain-controlled switch for asynchronous control applications. IEEE Trans Biomed Eng 2000, 47(10): 1297-1307.
G Townsend, B Graimann, G Pfurtscheller. Continuous EEG classification during motor imagery-simulation of an asynchronous BCI. IEEE Trans Neural Syst Rehabil Eng 2004, 12(2): 258-265.
JF Borisoff, SG Mason, GE Birch. Brain interface research for asynchronous control applications. IEEE Trans Neural Syst Rehabil Eng 2006, 14(2): 160-164.
Y Chae, J Jeong, S Jo. Toward brain-actuated humanoid robots: asynchronous direct control using an EEG-based BCI. IEEE Trans Rob 2012, 28(5): 1131-1144.
G Lisi, J Morimoto. EEG single-trial detection of gait speed changes during treadmill walk. PLoS One 2015, 10(5): e0125479.
T Geng, JQ Gan, HS Hu. A self-paced online BCI for mobile robot control. Int J Adv Mech Syst 2010, 2(1–2): 28-35.
T Geng, JQ Gan. Motor prediction in brain-computer interfaces for controlling mobile robots. In Proceedings of the 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Vancouver, Canada, 2008, pp 634-637.
T Sawaragi, S Takayuki, G Akashi. Foundations for designing an ecological interface for mobile robot teleoperation. Robot Auton Syst 2000, 31(3): 193-207.
I Ivanisevic, VJ Lumelsky. Configuration space as a means for augmenting human performance in teleoperation tasks. IEEE Trans Syst Man Cybern Part B Cybern 2000, 30(3): 471-484.
DRJ Millan, F Galan, D Vanhooydonck, E Lew, J Philips, M Nuttin. Asynchronous non-invasive brain-actuated control of an intelligent wheelchair. In Proceedings of 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Minneapolis, MN, USA, 2009, pp 3361-3364.
B Su, L Shen, L Wang, ZY Wang, YR Wang, LB Huang, W Shi. DCP: Improving the throughput of asynchronous pipeline by dual control path. In Proceedings of the 2013 IEEE 10th International Conference on High Performance Computing and Communications & 2013 IEEE International Conference on Embedded and Ubiquitous Computing, Zhangjiajie, China, 2013.
R Liu, YX Wang, L Zhang. An FDES-based shared control method for asynchronous brain-actuated robot. IEEE Trans Cybern 2016, 46(6): 1452-1462.
FC Sun, WC Zhang, JH Chen, H Wu, CQ Tan, WH Su. Fused fuzzy petri nets: a shared control method for brain computer interface systems. IEEE Trans Cogn Dev Syst, in press, .