A review of classification algorithms for EEG-based brain–computer interfaces
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M Congedo | F Lotte | A Lécuyer | F Lamarche | B Arnaldi | M. Congedo | F. Lotte | A. Lécuyer | F. Lamarche | B. Arnaldi | F. Lamarche
[1] Gabriel Curio,et al. MACHINE LEARNING TECHNIQUES FOR BRAIN-COMPUTER INTERFACES , 2004 .
[2] J. Wolpaw,et al. Brain-computer communication: unlocking the locked in. , 2001, Psychological bulletin.
[3] Steven Lemm,et al. BCI competition 2003-data set III: probabilistic modeling of sensorimotor /spl mu/ rhythms for classification of imaginary hand movements , 2004, IEEE Transactions on Biomedical Engineering.
[4] Stephen Grossberg,et al. Fuzzy ARTMAP: A neural network architecture for incremental supervised learning of analog multidimensional maps , 1992, IEEE Trans. Neural Networks.
[5] L. Breiman. Arcing classifier (with discussion and a rejoinder by the author) , 1998 .
[6] S. Rezaei,et al. Classification of mental tasks using Gaussian mixture Bayesian network classifiers , 2004, IEEE International Workshop on Biomedical Circuits and Systems, 2004..
[7] Justin Werfel,et al. BCI competition 2003-data set Ia: combining gamma-band power with slow cortical potentials to improve single-trial classification of electroencephalographic signals , 2004, IEEE Transactions on Biomedical Engineering.
[8] Anil K. Jain,et al. Statistical Pattern Recognition: A Review , 2000, IEEE Trans. Pattern Anal. Mach. Intell..
[9] Gert Pfurtscheller,et al. Brain-computer interface: a new communication device for handicapped persons , 1993 .
[10] G. Pfurtscheller,et al. Information transfer rate in a five-classes brain-computer interface , 2001, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[11] J.-M. Vesin,et al. Classification of EEG signals in the ambiguity domain for brain computer interface applications , 2002, 2002 14th International Conference on Digital Signal Processing Proceedings. DSP 2002 (Cat. No.02TH8628).
[12] Kristin P. Bennett,et al. Support vector machines: hype or hallelujah? , 2000, SKDD.
[13] Wu Xiao-pei,et al. Mental task classification for brain computer interface application , 2007 .
[14] C.W. Anderson,et al. Comparison of linear, nonlinear, and feature selection methods for EEG signal classification , 2003, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[15] José del R. Millán,et al. Noninvasive brain-actuated control of a mobile robot by human EEG , 2004, IEEE Transactions on Biomedical Engineering.
[16] Armando Barreto,et al. Classification of spatio-temporal EEG readiness potentials towards the development of a brain-computer interface , 1996, Proceedings of SOUTHEASTCON '96.
[17] Fusheng Yang,et al. BCI competition 2003-data set IV:An algorithm based on CSSD and FDA for classifying single-trial EEG , 2004, IEEE Transactions on Biomedical Engineering.
[18] G.A. Barreto,et al. On the classification of mental tasks: a performance comparison of neural and statistical approaches , 2004, Proceedings of the 2004 14th IEEE Signal Processing Society Workshop Machine Learning for Signal Processing, 2004..
[19] Mohammad Reza Hashemi Golpayegani,et al. Classification of chaotic signals using HMM classifiers:EEG-based mental task classification , 2005, 2005 13th European Signal Processing Conference.
[20] Andrew R. Webb,et al. Statistical Pattern Recognition , 1999 .
[21] Jianting Cao,et al. CLASSIFICATION OF SINGLE TRIAL EEG SIGNALS BY A COMBINED PRINCIPAL + INDEPENDENT COMPONENT ANALYSIS AND PROBABILISTIC NEURAL NETWORK APPROACH , 2003 .
[22] G Pfurtscheller,et al. Using time-dependent neural networks for EEG classification. , 2000, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.
[23] William D. Penny,et al. EEG-based communication via dynamic neural network models , 1999, IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339).
[24] A Kostov,et al. Parallel man-machine training in development of EEG-based cursor control. , 2000, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.
[25] T. Felzer,et al. Analyzing EEG signals using the probability estimating guarded neural classifier , 2003, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[26] U. Hoffmann,et al. A Boosting Approach to P300 Detection with Application to Brain-Computer Interfaces , 2005, Conference Proceedings. 2nd International IEEE EMBS Conference on Neural Engineering, 2005..
[27] Fabien Lotte,et al. The Use of Fuzzy Inference Systems for Classification in EEG-based Brain-Computer Interfaces , 2006 .
[28] F. Cincotti,et al. Comparison of different feature classifiers for brain computer interfaces , 2003, First International IEEE EMBS Conference on Neural Engineering, 2003. Conference Proceedings..
[29] D.J. McFarland,et al. Sensorimotor rhythm-based brain-computer interface (BCI): feature selection by regression improves performance , 2005, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[30] G. Pfurtscheller,et al. Brain-Computer Interfaces for Communication and Control. , 2011, Communications of the ACM.
[31] B. Kamousi,et al. Classification of motor imagery tasks for brain-computer interface applications by means of two equivalent dipoles analysis , 2005, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[32] Anil K. Jain,et al. 39 Dimensionality and sample size considerations in pattern recognition practice , 1982, Classification, Pattern Recognition and Reduction of Dimensionality.
[33] Sankar K. Pal,et al. Fuzzy models for pattern recognition , 1992 .
[34] E Donchin,et al. Brain-computer interface technology: a review of the first international meeting. , 2000, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.
[35] Gert Pfurtscheller,et al. EEG event-related desynchronization (ERD) and synchronization (ERS) , 1997 .
[36] Helge J. Ritter,et al. BCI competition 2003-data set IIb: support vector machines for the P300 speller paradigm , 2004, IEEE Transactions on Biomedical Engineering.
[37] Gert Pfurtscheller,et al. Characterization of four-class motor imagery EEG data for the BCI-competition 2005 , 2005, Journal of neural engineering.
[38] G. Pfurtscheller,et al. EEG-based discrimination between imagination of right and left hand movement. , 1997, Electroencephalography and clinical neurophysiology.
[39] J. Mourino,et al. Asynchronous BCI and local neural classifiers: an overview of the adaptive brain interface project , 2003, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[40] M. Thulasidas,et al. Robust classification of EEG signal for brain-computer interface , 2006, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[41] Anil K. Jain,et al. Small Sample Size Effects in Statistical Pattern Recognition: Recommendations for Practitioners , 1991, IEEE Trans. Pattern Anal. Mach. Intell..
[42] Vladimir Vapnik,et al. An overview of statistical learning theory , 1999, IEEE Trans. Neural Networks.
[43] Klaus-Robert Müller,et al. The BCI competition 2003: progress and perspectives in detection and discrimination of EEG single trials , 2004, IEEE Transactions on Biomedical Engineering.
[44] S. Puthusserypady,et al. Multilayer perceptrons for the classification of brain computer interface data , 2005, Proceedings of the IEEE 31st Annual Northeast Bioengineering Conference, 2005..
[45] Gilles Blanchard,et al. BCI competition 2003-data set IIa: spatial patterns of self-controlled brain rhythm modulations , 2004, IEEE Transactions on Biomedical Engineering.
[46] Alain Rakotomamonjy,et al. Ensemble of SVMs for Improving Brain Computer Interface P300 Speller Performances , 2005, ICANN.
[47] C.W. Anderson,et al. Multivariate autoregressive models for classification of spontaneous electroencephalographic signals during mental tasks , 1998, IEEE Transactions on Biomedical Engineering.
[48] Samy Bengio,et al. HMM and IOHMM modeling of EEG rhythms for asynchronous BCI systems , 2004, ESANN.
[49] Mohammad Hassan Moradi,et al. A new approach in the BCI research based on fractal dimension as feature and Adaboost as classifier , 2004, Journal of neural engineering.
[50] Bin He,et al. BRAIN^COMPUTER INTERFACE , 2007 .
[51] Bin He,et al. Classifying EEG-based motor imagery tasks by means of time–frequency synthesized spatial patterns , 2004, Clinical Neurophysiology.
[52] Lei Ding,et al. Motor imagery classification by means of source analysis for brain–computer interface applications , 2004, Journal of neural engineering.
[53] Klaus-Robert Müller,et al. Classifying Single Trial EEG: Towards Brain Computer Interfacing , 2001, NIPS.
[54] K.-R. Muller,et al. BCI meeting 2005-workshop on BCI signal processing: feature extraction and translation , 2006, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[55] R Thull,et al. Vergleichende Untersuchungen zur Eignung eines neuen Oberflächenkonditionierungsverfahrens (Airsonic Mini Sandblaster®) in der Klebebrückentechnik / Comparative Studies on the Applicability of a New Surface Conditioning System (Airsonic Mini Sandblaster®) in Adhesive Bridging Technic , 2004, Biomedizinische Technik. Biomedical engineering.
[56] Christa Neuper,et al. An asynchronously controlled EEG-based virtual keyboard: improvement of the spelling rate , 2004, IEEE Transactions on Biomedical Engineering.
[57] Seungjin Choi,et al. PCA+HMM+SVM for EEG pattern classification , 2003, Seventh International Symposium on Signal Processing and Its Applications, 2003. Proceedings..
[58] Gary E. Birch,et al. Brain-computer interface design for asynchronous control applications: improvements to the LF-ASD asynchronous brain switch , 2004, IEEE Transactions on Biomedical Engineering.
[59] Christa Neuper,et al. Hidden Markov models for online classification of single trial EEG data , 2001, Pattern Recognit. Lett..
[60] Yuanqing Li,et al. ICA and Committee Machine-Based Algorithm for Cursor Control in a BCI System , 2005, ISNN.
[61] Heekuck Oh,et al. Neural Networks for Pattern Recognition , 1993, Adv. Comput..
[62] L. Breiman. Arcing Classifiers , 1998 .
[63] Kouhyar Tavakolian,et al. Different classification techniques considering brain computer interface applications. , 2006, Journal of neural engineering.
[64] Teuvo Kohonen,et al. The self-organizing map , 1990, Neurocomputing.
[65] R. Palaniappan,et al. Brain Computer Interface Design Using Band Powers Extracted During Mental Tasks , 2005, Conference Proceedings. 2nd International IEEE EMBS Conference on Neural Engineering, 2005..
[66] Michael I. Jordan,et al. On Discriminative vs. Generative Classifiers: A comparison of logistic regression and naive Bayes , 2001, NIPS.
[67] M J Stokes,et al. EEG-based communication: a pattern recognition approach. , 2000, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.
[68] William Z Rymer,et al. Guest Editorial Brain–Computer Interface Technology: A Review of the Second International Meeting , 2001 .
[69] David H. Wolpert,et al. Stacked generalization , 1992, Neural Networks.
[70] K. Shimohara,et al. EEG topography recognition by neural networks , 1990, IEEE Engineering in Medicine and Biology Magazine.
[71] G Pfurtscheller,et al. Estimating the Mutual Information of an EEG-based Brain-Computer Interface , 2002, Biomedizinische Technik. Biomedical engineering.
[72] S. Nishida,et al. A new brain-computer interface design using fuzzy ARTMAP , 2002, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[73] M. Congedo,et al. Open-ViBE: A Three Dimensional Platform for Real-Time Neuroscience , 2005 .
[74] Gary E. Birch,et al. A brain-controlled switch for asynchronous control applications , 2000, IEEE Trans. Biomed. Eng..
[75] Trevor J. Hastie,et al. Discriminative vs Informative Learning , 1997, KDD.
[76] Vladimir Bostanov,et al. 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 , 2004, IEEE Transactions on Biomedical Engineering.
[77] N. Birbaumer,et al. BCI2000: a general-purpose brain-computer interface (BCI) system , 2004, IEEE Transactions on Biomedical Engineering.
[78] G Pfurtscheller,et al. Separability of EEG signals recorded during right and left motor imagery using adaptive autoregressive parameters. , 1998, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.
[79] G. Pfurtscheller,et al. Graz brain-computer interface II: towards communication between humans and computers based on online classification of three different EEG patterns , 1996, Medical and Biological Engineering and Computing.
[80] Chng Eng Siong,et al. High accuracy classification of EEG signal , 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..
[81] Z. Keirn,et al. A new mode of communication between man and his surroundings , 1990, IEEE Transactions on Biomedical Engineering.
[82] Jukka Heikkonen,et al. Local Neural Classifier for EEG-Based Recognition of Mental Tasks , 2000, IJCNN.
[83] M. Congedo,et al. Open-ViBE: a 3D Platform for Real-Time Neuroscience , 2004 .
[84] Touradj Ebrahimi,et al. Support vector EEG classification in the Fourier and time-frequency correlation domains , 2003, First International IEEE EMBS Conference on Neural Engineering, 2003. Conference Proceedings..
[85] M Congedo,et al. Classification of movement intention by spatially filtered electromagnetic inverse solutions , 2006, Physics in medicine and biology.
[86] Lawrence R. Rabiner,et al. A tutorial on hidden Markov models and selected applications in speech recognition , 1989, Proc. IEEE.
[87] Charles W. Anderson,et al. Classification of EEG Signals from Four Subjects During Five Mental Tasks , 2007 .