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At present, people usually use some methods based on convolutional neural networks (CNNs) for Electroencephalograph (EEG) decoding.
X. Ma, S. Qiu, C. Du, J. Xing, and H. He, “Improving EEG-Based Motor Imagery Classification via Spatial and Temporal Recurrent Neural Networks,” in 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) . Honolulu, HI: IEEE, Jul. 2018, pp. 1903–1906
1906
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G. Pfurtscheller, C. Brunner, A. Schlögl, and F. Lopes da Silva, “Mu rhythm (de)synchronization and EEG single-trial classification of different motor imagery tasks,” NeuroImage , vol. 31, no. 1, pp. 153–159, May 2006
2006
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F. Lotte, M. Congedo, A. Lécuyer, F. Lamarche, and B. Arnaldi, “A review of classification algorithms for EEG-based brain–computer interfaces,” Journal of Neural Engineering , vol. 4, no. 2, pp. R1–R13, Jun. 2007
2007
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Kai Keng Ang, Zhang Yang Chin, Haihong Zhang, and Cuntai Guan, “Filter Bank Common Spatial Pattern (FBCSP) in Brain-Computer Interface,” in 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence) . Hong Kong, China: IEEE, Jun. 2008, pp. 2390–2397
2008
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C. Brunner, R. Leeb, G. R. Muller-Putz, and A. Schlogl, “BCI Competition 2008 – Graz data set A,” p. 6
2008
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R. Leeb, C. Brunner, G. R. Muller-Putz, and A. Schlogl, “BCI Competition 2008 – Graz data set B,” p. 6
2008
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L. van der Maaten and G. Hinton, “Visualizing data using t-sne,” Journal of Machine Learning Research , vol. 9, no. 86, pp. 2579–2605, 2008
2008
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2010
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Yinxia Liu, Weidong Zhou, Qi Yuan, and Shuangshuang Chen, “Automatic Seizure Detection Using Wavelet Transform and SVM in Long-Term Intracranial EEG,” IEEE Transactions on Neural Systems and Rehabilitation Engineering , vol. 20, no. 6, pp. 749–755, Nov. 2012
2012
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K. K. Ang, Z. Y. Chin, C. Wang, C. Guan, and H. Zhang, “Filter Bank Common Spatial Pattern Algorithm on BCI Competition IV Datasets 2a and 2b,” Frontiers in Neuroscience , vol. 6, 2012
2012
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2014
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Jie Xu, Yuan Yan Tang, Bin Zou, Zongben Xu, Luoqing Li, and Yang Lu, “The Generalization Ability of Online SVM Classification Based on Markov Sampling,” IEEE Transactions on Neural Networks and Learning Systems , vol. 26, no. 3, pp. 628–639, Mar. 2015
2015
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2015
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2016
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E. Tidoni, M. Abu-Alqumsan, D. Leonardis, C. Kapeller, G. Fusco, C. Guger, C. Hintermuller, A. Peer, A. Frisoli, F. Tecchia, M. Bergamasco, and S. M. Aglioti, “Local and Remote Cooperation With Virtual and Robotic Agents: A P300 BCI Study in Healthy and People Living With Spinal Cord Injury,” IEEE Transactions on Neural Systems and Rehabilitation Engineering , vol. 25, no. 9, pp. 1622–1632, Sep. 2017
2017
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O. W. Samuel, Y. Geng, X. Li, and G. Li, “Towards Efficient Decoding of Multiple Classes of Motor Imagery Limb Movements Based on EEG Spectral and Time Domain Descriptors,” Journal of Medical Systems , vol. 41, no. 12, p. 194, Dec. 2017
2017
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2017
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S. K. Goh, H. A. Abbass, K. C. Tan, A. Al-Mamun, C. Wang, and C. Guan, “Automatic EEG Artifact Removal Techniques by Detecting Influential Independent Components,” IEEE Transactions on Emerging Topics in Computational Intelligence , vol. 1, no. 4, pp. 270–279, Aug. 2017
2017
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2017
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R. T. Schirrmeister, J. T. Springenberg, L. D. J. Fiederer, M. Glasstetter, K. Eggensperger, M. Tangermann, F. Hutter, W. Burgard, and T. Ball, “Deep learning with convolutional neural networks for EEG decoding and visualization: Convolutional Neural Networks in EEG Analysis,” Human Brain Mapping , vol. 38, no. 11, pp. 5391–5420, Nov. 2017
2017
Cited alongside, same era.
F. Lotte, L. Bougrain, A. Cichocki, M. Clerc, M. Congedo, A. Rakotomamonjy, and F. Yger, “A review of classification algorithms for EEG-based brain–computer interfaces: a 10 year update,” Journal of Neural Engineering , vol. 15, no. 3, p. 031005, Jun. 2018
2018
Cited alongside, same era.
S. Sakhavi, C. Guan, and S. Yan, “Learning Temporal Information for Brain-Computer Interface Using Convolutional Neural Networks,” IEEE Transactions on Neural Networks and Learning Systems , vol. 29, no. 11, pp. 5619–5629, Nov. 2018
2018
Cited alongside, same era.
C.-T. Lin, C.-H. Chuang, Y.-C. Hung, C.-N. Fang, D. Wu, and Y.-K. Wang, “A Driving Performance Forecasting System Based on Brain Dynamic State Analysis Using 4-D Convolutional Neural Networks,” IEEE Transactions on Cybernetics , pp. 1–9, 2020
2020
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G. Dai, J. Zhou, J. Huang, and N. Wang, “HS-CNN: a CNN with hybrid convolution scale for EEG motor imagery classification,” Journal of Neural Engineering , vol. 17, no. 1, p. 016025, Jan. 2020
2020
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J. He, L. Zhao, H. Yang, M. Zhang, and W. Li, “HSI-BERT: Hyperspectral Image Classification Using the Bidirectional Encoder Representation From Transformers,” IEEE Transactions on Geoscience and Remote Sensing , vol. 58, no. 1, pp. 165–178, Jan. 2020
2020
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N. Zhang, “Learning Adversarial Transformer for Symbolic Music Generation,” IEEE Transactions on Neural Networks and Learning Systems , pp. 1–10, 2020
2020
Later among the works it cites.
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2018
Cited alongside, same era.
J. S. Kirar and R. K. Agrawal, “Relevant Frequency Band Selection using Sequential Forward Feature Selection for Motor Imagery Brain Computer Interfaces,” in 2018 IEEE Symposium Series on Computational Intelligence (SSCI) . Bangalore, India: IEEE, Nov. 2018, pp. 52–59
2018
Cited alongside, same era.
V. J. Lawhern, A. J. Solon, N. R. Waytowich, S. M. Gordon, C. P. Hung, and B. J. Lance, “EEGNet: a compact convolutional neural network for EEG-based brain–computer interfaces,” Journal of Neural Engineering , vol. 15, no. 5, p. 056013, Oct. 2018
2018
Cited alongside, same era.
J. Hu, L. Shen, and G. Sun, “Squeeze-and-Excitation Networks,” in 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition . Salt Lake City, UT: IEEE, Jun. 2018, pp. 7132–7141
2018
Cited alongside, same era.
R. Fu, Y. Tian, T. Bao, Z. Meng, and P. Shi, “Improvement Motor Imagery EEG Classification Based on Regularized Linear Discriminant Analysis,” Journal of Medical Systems , vol. 43, no. 6, p. 169, Jun. 2019
2019
Cited alongside, same era.
S. U. Amin, M. Alsulaiman, G. Muhammad, M. A. Mekhtiche, and M. Shamim Hossain, “Deep Learning for EEG motor imagery classification based on multi-layer CNNs feature fusion,” Future Generation Computer Systems , vol. 101, pp. 542–554, Dec. 2019
2019
Cited alongside, same era.
T. Zhang, W. Zheng, Z. Cui, Y. Zong, and Y. Li, “Spatial–Temporal Recurrent Neural Network for Emotion Recognition,” IEEE Transactions on Cybernetics , vol. 49, no. 3, pp. 839–847, Mar. 2019
2019
Cited alongside, same era.
C. S. Zandvoort, J. H. van Dieën, N. Dominici, and A. Daffertshofer, “The human sensorimotor cortex fosters muscle synergies through cortico-synergy coherence,” NeuroImage , vol. 199, pp. 30–37, Oct. 2019
2019
Cited alongside, same era.
X. Zhao, H. Zhang, G. Zhu, F. You, S. Kuang, and L. Sun, “A Multi-Branch 3D Convolutional Neural Network for EEG-Based Motor Imagery Classification,” IEEE Transactions on Neural Systems and Rehabilitation Engineering , vol. 27, no. 10, pp. 2164–2177, Oct. 2019
2019
Cited alongside, same era.
P. Kant, S. H. Laskar, J. Hazarika, and R. Mahamune, “CWT Based Transfer Learning for Motor Imagery Classification for Brain computer Interfaces,” Journal of Neuroscience Methods , vol. 345, p. 108886, Nov. 2020
2020
Later among the works it cites.
J. Chen, Z. Yu, Z. Gu, and Y. Li, “Deep Temporal-Spatial Feature Learning for Motor Imagery-Based Brain–Computer Interfaces,” IEEE Transactions on Neural Systems and Rehabilitation Engineering , vol. 28, no. 11, pp. 2356–2366, Nov. 2020
2020
Later among the works it cites.
W. Tao, C. Li, R. Song, J. Cheng, Y. Liu, F. Wan, and X. Chen, “EEG-based Emotion Recognition via Channel-wise Attention and Self Attention,” IEEE Transactions on Affective Computing , pp. 1–1, 2020
2020
Later among the works it cites.
D. Zhang, K. Chen, D. Jian, and L. Yao, “Motor Imagery Classification via Temporal Attention Cues of Graph Embedded EEG Signals,” IEEE Journal of Biomedical and Health Informatics , vol. 24, no. 9, pp. 2570–2579, Sep. 2020
2020
Later among the works it cites.
2020
Later among the works it cites.
X. Tang, W. Li, X. Li, W. Ma, and X. Dang, “Motor imagery EEG recognition based on conditional optimization empirical mode decomposition and multi-scale convolutional neural network,” Expert Systems with Applications , vol. 149, p. 113285, Jul. 2020
2020
Later among the works it cites.
F. R. Willett, D. T. Avansino, L. R. Hochberg, J. M. Henderson, and K. V. Shenoy, “High-performance brain-to-text communication via handwriting,” Nature , vol. 593, no. 7858, pp. 249–254, 2021
2021
Closest in time.
A. Cruz, G. Pires, A. Lopes, C. Carona, and U. J. Nunes, “A Self-Paced BCI With a Collaborative Controller for Highly Reliable Wheelchair Driving: Experimental Tests With Physically Disabled Individuals,” IEEE Transactions on Human-Machine Systems , vol. 51, no. 2, pp. 109–119, Apr. 2021
2021
Closest in time.
A. Al-Saegh, S. A. Dawwd, and J. M. Abdul-Jabbar, “Deep learning for motor imagery EEG-based classification: A review,” Biomedical Signal Processing and Control , vol. 63, p. 102172, Jan. 2021
2021
Closest in time.
2021
Closest in time.
M. Li and W. Chen, “FFT-based deep feature learning method for EEG classification,” Biomedical Signal Processing and Control , vol. 66, p. 102492, Apr. 2021
2021
Closest in time.
L. Yang, Y. Song, K. Ma, and L. Xie, “Motor Imagery EEG Decoding Method Based on a Discriminative Feature Learning Strategy,” IEEE Transactions on Neural Systems and Rehabilitation Engineering , vol. 29, pp. 368–379, 2021
2021
Closest in time.
R. Zhang, Q. Zong, L. Dou, X. Zhao, Y. Tang, and Z. Li, “Hybrid deep neural network using transfer learning for EEG motor imagery decoding,” Biomedical Signal Processing and Control , vol. 63, p. 102144, Jan. 2021
2021
Closest in time.
X. Zheng and W. Chen, “An Attention-based Bi-LSTM Method for Visual Object Classification via EEG,” Biomedical Signal Processing and Control , vol. 63, p. 102174, Jan. 2021
2021
Closest in time.