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okbalefthanded / aawedha

Deep Learning toolbox for EEG based Brain-Computer Interface signals decoding and benchmarking
GNU General Public License v3.0
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[DL] Add Models #6

Closed okbalefthanded closed 2 years ago

okbalefthanded commented 5 years ago

EEGNet and the models available with it are well tested, newer and different architectures are required.

okbalefthanded commented 5 years ago

ConvNet models available in EEGNet:

References : [1] Lawhern V Solon A Waytowich N Gordon S Hung C Lance B, EEGNet: a compact convolutional neural network for EEG-based brain–computer interfaces, Journal of Neural Engineering 2018 vol: 15 (5) pp: 056013 [2] Schirrmeister R Springenberg J Fiederer L Glasstetter M Eggensperger K Tangermann M Hutter F Burgard W Ball T, Deep learning with convolutional neural networks for EEG decoding and visualization, Human Brain Mapping 2017 vol: 38 (11) pp: 5391-5420

okbalefthanded commented 4 years ago

SSVEP model added:

References : [3] N.-S. Kwak, K.-R. Müller, S.-W. Lee, A convolutional neural network for steady state visual evoked potential classification under ambulatory environment, PLoS One. 12 (2017) e0172578. doi:10.1371/journal.pone.0172578.

[4] N.K.N. Aznan, S. Bonner, J.D. Connolly, N. Al Moubayed, T.P. Breckon, On the Classification of SSVEP-Based Dry-EEG Signals via Convolutional Neural Networks, (2018). doi:10.1007/s11245-014-9238-7.

[5] J.J. Podmore, T.P. Breckon, N.K.N. Aznan, J.D. Connolly, On the Relative Contribution of Deep Convolutional Neural Networks for SSVEP-Based BioSignal Decoding in BCI Speller Applications, IEEE Trans. Neural Syst. Rehabil. Eng. 27 (2019) 611–618. doi:10.1109/TNSRE.2019.2904791.

[6] X. Zhang, G. Xu, X. Mou, A. Ravi, M. Li, Y. Wang, N. Jiang, A Convolutional Neural Network for the Detection of Asynchronous Steady State Motion Visual Evoked Potential, IEEE Trans. Neural Syst. Rehabil. Eng. 27 (2019) 1303–1311. doi:10.1109/TNSRE.2019.2914904.

okbalefthanded commented 3 years ago

MultiTask ERP models:

[7] A. Ditthapron, N. Banluesombatkul, S. Ketrat, E. Chuangsuwanich, and T. Wilaiprasitporn, “Universal Joint Feature Extraction for P300 EEG Classification Using Multi-Task Autoencoder, ” IEEE Access, vol. 7, pp. 68415–68428, 2019.

okbalefthanded commented 3 years ago
okbalefthanded commented 3 years ago

Transformer architectures:

okbalefthanded commented 3 years ago