A review of classification algorithms for EEG-based brain–computer interfaces: A 10 year update

Lotte, F, Bougrain, L, Cichocki, A, Clerc, M, Congedo, M, Rakotomamonjy, A, Yger, F·2018·Journal of Neural Engineering
DOI 10.1088/1741-2552/aab2f2

Cites (266)

Items 201–261 of 261

  1. CSP patches: an ensemble of optimized spatial filters. An evaluation study
    Claudia Sannelli, Carmen Vidaurre, Klaus‐Robert Müller, Benjamin Blankertz · 2011 · Journal of Neural Engineering
  2. Increasing session-to-session transfer in a brain–computer interface with on-site background noise acquisition
    Hohyun Cho, Minkyu Ahn, Kiwoong Kim, Sung Chan Jun · 2015 · Journal of Neural Engineering
  3. A Generalizable Brain-Computer Interface (BCI) Using Machine Learning for Feature Discovery
    Ewan Scott Nurse, Philippa J. Karoly, David Bruce Grayden, Dean Robert Freestone · 2015 · PLoS ONE
  4. Feature selection using a genetic algorithm in a motor imagery-based Brain Computer Interface
    Rebeca Corralejo, Roberto Hornero, Daniel Álvarez · 2011 · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
  5. Performance of a Simulated Adaptive BCI Based on Experimental Classification of Movement-Related and Error Potentials
    Xavier Artusi, Imran Khan Niazi, Marie-Françoise Lucas, Dario Farina · 2011 · IEEE Journal on Emerging and Selected Topics in Circuits and Systems
  6. A genetic algorithm for automatic feature extraction in P300 detection
    Bernardo Dal Seno, Matteo Matteucci, Luca Tommaso Mainardi · 2008 · IEEE International Joint Conference on Neural Networks (IJCNN)
  7. Signal Processing and Machine Learning for Brain-Machine Interfaces
    Stober, Sebastian (Dr.-Ing.), Sternin, Avital · 2018 · Institution of Engineering and Technology eBooks
  8. EEG Source Analysis
    Marco Congedo, Leslie H. Sherlin · 2010 · Elsevier eBooks
  9. A Generic Framework for Adaptive EEG-Based BCI Training and Operation
    Jelena Mladenović, Jérémie Mattout, Fabien Lotte · 2018 · CRC Press eBooks
  10. Guest Editorial: Brain/neuronal - Computer game interfaces and interaction
    Damien Coyle, José Carlos Príncipe, Fabien Lotte · 2013 · IEEE Transactions on Computational Intelligence and AI in Games
  11. Classifying EEG Signals during Stereoscopic Visualization to Estimate Visual Comfort
    Jérémy Frey, Aurélien Appriou, Fabien Lotte, Martin Hachet · 2015 · Computational Intelligence and Neuroscience
  12. Variable Selection with Optimal Cell Damage
    Tautvydas Cibas, Françoise Fogelman Soulié, Patrick Gallinari · 1994 · Springer eBooks
  13. Improving quantification of functional networks with EEG inverse problem: Evidence from a decoding point of view
    Michel Besserve, Jacques M. Martinerie, Line Garnero · 2011 · NeuroImage
  14. A linear feature space for simultaneous learning of spatio-spectral filters in BCI
    Jason D. R. Farquhar · 2009 · Neural Networks
  15. Incremental Common Spatial Pattern algorithm for BCI
    Qibin Zhao, Liqing Zhang, Andrzej S Cichocki, Jie Li · 2008 · International Joint Conference on Neural Networks (IJCNN)
  16. Understanding Brain Connectivity Patterns during Motor Imagery for Brain-Computer Interfacing
    Moritz Grosse‐Wentrup · 2008
  17. Self-calibration algorithm in an asynchronous P300-based brain–computer interface
    Francesca Schettini, Fabio Aloise A, Pietro Aricò, Serenella Salinari, Donatella Mattia A, Febo Cincotti A · 2014 · Journal of Neural Engineering
  18. Adaptive Multiclass Classification for Brain Computer Interfaces
    Alberto Llera, Vicenç Gómez, Hilbert J. Kappen · 2014 · Neural Computation
  19. Adaptive Classification on Brain-Computer Interfaces Using Reinforcement Signals
    Alberto Llera, Vicenç Gómez, Hilbert J. Kappen · 2012 · Neural Computation
  20. Classification of motor imagery tasks for BCI with multiresolution analysis and multiobjective feature selection
    Julio Ortega, Javier Asensio-Cubero, John Q. Gan, Andrés Ortíz · 2016 · BioMedical Engineering OnLine
  21. Fixed Point Algorithms for Estimating Power Means of Positive Definite Matrices
    Marco Congedo, Alexandre Barachant, Ehsan Kharatikoopaei · 2017 · IEEE Transactions on Signal Processing
  22. Bilateral adaptation and neurofeedback for brain computer interface system
    Junhua Li, Liqing Zhang · 2010 · Journal of Neuroscience Methods
  23. An Efficient P300-based Brain-Computer Interface with Minimal Calibration Time
    Fabien Lotte, Cuntai Guan · 2009 · HAL
  24. A review of kernels on covariance matrices for BCI applications
    Florian Yger · 2013 · Machine learning for signal processing ...
  25. Calibration-Free BCI Based Control
    Jonathan Grizou, Iñaki Iturrate, Luis Montesano, Pierre‐Yves Oudeyer, Manuel C. Lopes · 2014 · Proceedings of the AAAI Conference on Artificial Intelligence
  26. Adaptive classification for Brain Computer Interface systems using Sequential Monte Carlo sampling
    Ji Won Yoon, Stephen Roberts, Dyson M · 2009 · Neural Networks
  27. A new feature and associated optimal spatial filter for EEG signal classification: Waveform Length
    Fabien Lotte, Inria Bordeaux · 2012
  28. Improved GMM with parameter initialization for unsupervised adaptation of Brain–Computer interface
    Guangquan Liu, Gan Huang, Jianjun Meng, Dingguo Zhang, Xiangyang Zhu · 2009 · International Journal for Numerical Methods in Biomedical Engineering
  29. Optimizing spatial filter pairs for EEG classification based on phase-synchronization
    Nicoletta Caramia, Fabien Lotte, Stefano Ramat · 2014 · IEEE International Conference on Acoustics Speech and Signal Processing
  30. Improving zero-training brain-computer interfaces by mixing model estimators
    Thibault Verhoeven, David Hübner, Michael Tangermann, K. Robert Müller, Joni Dambre, Pieter-Jan Kindermans · 2017 · Journal of Neural Engineering
  31. EEG Feature Extraction
    Fabien Lotte, Marco Congedo · 2016
  32. Brain-computer interface for the communication of acute patients: a feasibility study and a randomized controlled trial comparing performance with healthy participants and a traditional assistive device
    Louis Mayaud, Salvador Cabanilles, Aurélien van Langhenhove, Marco Congedo, Alexandre Barachant, Samuel Pouplin, Sabine Filipe, Lucie Pétégnief, Olivier Rochecouste, Éric Azabou et al. · 2016 · Brain-Computer Interfaces
  33. EEG sensor selection by sparse spatial filtering in P300 speller brain-computer interface
    Bertrand Rivet, Hubert Cecotti, Ronald Phlypo, Olivier Bertrand, Emmanuel Maby, Jérémie Mattout · 2010 · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
  34. Partially supervised P300 speller adaptation for eventual stimulus timing optimization: target confidence is superior to error-related potential score as an uncertain label
    Timothy J. Zeyl, Erwei Yin, Michelle Keightley, Tom T. Chau · 2016 · Journal of Neural Engineering
  35. Adaptive Common Spatial Pattern for single-trial EEG classification in multisubject BCI
    Xiaomu Song, Suk-Chung Yoon, Viraga Perera · 2013 · International IEEE/EMBS Conference on Neural Engineering
  36. Unsupervised adaptation of electroencephalogram signal processing based on fuzzy C‐means algorithm
    Guangquan Liu, Dingguo Zhang, Jianjun Meng, Gan Huang, Xiangyang Zhu · 2011 · International Journal of Adaptive Control and Signal Processing
  37. A Multi-label Classification Method for Detection of Combined Motor Imageries
    Cecilia Lindig-León, Laurent Bougrain · 2015 · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics
  38. Discriminant brain connectivity patterns of performance monitoring at average and single-trial levels
    Huaijian Zhang, Ricardo Chavarriaga, José del R. Millán · 2015 · NeuroImage
  39. A novel technique for phase synchrony measurement from the complex motor imaginary potential of combined body and limb action
    Zhongxing Zhou, Baikun Wan, Dong Ming · 2010 · Journal of Neural Engineering
  40. Classifying Regularized Sensor Covariance Matrices: An Alternative to CSP
    Linsey Roijendijk, Stan C. A. M. Gielen, Jason D. R. Farquhar · 2015 · IEEE Transactions on Neural Systems and Rehabilitation Engineering
  41. Adaptive Waveform Learning: A Framework for Modeling Variability in Neurophysiological Signals
    Sebastian Hitziger, Maureen Clerc, Sandrine Saillet · 2017 · IEEE Transactions on Signal Processing
  42. Sequential non-stationary dynamic classification with sparse feedback
    D. R. Lowne, Stephen Roberts, Roman Garnett · 2009 · Pattern Recognition
  43. Optimization of Alpha-Beta Log-Det Divergences and their Application in the Spatial Filtering of Two Class Motor Imagery Movements
    Deepa Beeta Thiyam, Sergio Cruces, Javier Olias · 2017 · Entropy
  44. Optimal Transport Applied To Transfer Learning For P300 Detection
    Nathalie Gayraud, Alain Rakotomamonjy, Maureen Clerc · 2020 · HAL
  45. SELF-ADAPTING BCI BASED ON UNSUPERVISED LEARNING
    John Q. Gan · 2006
  46. Recreational Applications of OpenViBE: Brain Invaders and Use‐the‐Force
    Anton Andreev, Alexandre Barachant, Fabien Lotte, Marco Congedo · 2016
  47. A Critical Review on the Usage of Ensembles for BCI
    Aureli Soria‐Frisch · 2012 · Biological and medical physics series
  48. Tensor classification for P300-based brain computer interface
    Akinari Onishi, Anh Huy Phan, Kiyotoshi Matsuoka · 2012 · IEEE International Conference on Acoustics Speech and Signal Processing
  49. From basis components to complex structural patterns
    Anh Huy Phan, Andrzej S Cichocki, Petr Tichavský · 2013 · IEEE International Conference on Acoustics Speech and Signal Processing
  50. Tensor Based Simultaneous Feature Extraction and Sample Weighting for EEG Classification
    Yoshikazu Washizawa, Hiroshi Higashi, Tomasz M. Rutkowski · 2010 · Lecture notes in computer science
  51. What are the Causes of Performance Variation in Brain-Computer Interfacing?
    Moritz Grosse‐Wentrup · 2011
  52. Data augmentation in Riemannian space for Brain-Computer Interfaces
    Emmanuel K. Kalunga, Sylvain Chevallier, Quentin Barthélemy · 2015 · HAL
  53. Online Classification Accuracy Is A Poor Metric To Study Mental Imagery-Based Bci User Learning: An Experimental Demonstration And New Metrics
    Fabien Lotte, Camille Jeunet · 2020 · HAL
  54. Dimensionality Reduction For Bci Classification Using Riemannian Geometry
    Pedro Luiz Coelho Rodrigues, Florent Bouchard, Marco Congedo, Christian Jutten B · 2020 · HAL
  55. From circular ordinal regression to multilabel classification
    Dieter Devlaminck, Willem Waegeman, Bruno Bauwens · 2010 · Ghent University Academic Bibliography (Ghent University)
  56. Comparison of sensorimotor rhythms in EEG signals during simple and combined motor imageries over the contra and ipsilateral hemispheres
    Cecilia Lindig-León, Laurent Bougrain · 2015
  57. As above, so below? Towards understanding inverse models in BCI
    Jussi T. Lindgren · 2017 · Journal of Neural Engineering
  58. Riemannian Classification for SSVEP-Based BCI: Offline versus Online Implementations
    Sylvain Chevallier, Emmanuel K. Kalunga, Quentin Barthélemy · 2018 · HAL (Le Centre pour la Communication Scientifique Directe)
  59. Geometry-aware stationary subspace analysis
    Inbal Horev, Florian Yger, Masashi Sugiyama · 2016 · arXiv (Cornell University)
  60. Comparison of Hierarchical and Non-Hierarchical Classification for Motor Imagery Based BCI Systems
    Cecilia Lindig-León, Nathalie Gayraud, Laurent Bougrain · 2016 · HAL (Le Centre pour la Communication Scientifique Directe)
  61. Towards Usable Electroencephalography-based Brain-Computer Interfaces
    Fabien Lotte · 2016 · HAL (Le Centre pour la Communication Scientifique Directe)