EEG4Home: A Human-In-The-Loop Machine Learning Model for EEG-Based BCI

Author:

Qu XiaodongORCID,Hickey Timothy J.

Publisher

Springer International Publishing

Reference30 articles.

1. Bashivan, P., Rish, I., Yeasin, M., Codella, N.: Learning representations from EEG with deep recurrent-convolutional neural networks. arXiv preprint arXiv:1511.06448 (2015)

2. Chevalier, J.A., Gramfort, A., Salmon, J., Thirion, B.: Statistical control for spatio-temporal MEG/EEG source imaging with desparsified multi-task Lasso. arXiv preprint arXiv:2009.14310 (2020)

3. Coyle, D., Principe, J., Lotte, F., Nijholt, A.: Guest editorial: brain/neuronal-computer game interfaces and interaction. IEEE Trans. Comput. Intell. AI Games 5(2), 77–81 (2013)

4. Craik, A., He, Y., Contreras-Vidal, J.L.: Deep learning for electroencephalogram (EEG) classification tasks: a review. J. Neural Eng. 16(3), 031001 (2019)

5. Devlaminck, D., Waegeman, W., Bauwens, B., Wyns, B., Santens, P., Otte, G.: From circular ordinal regression to multilabel classification. In: Proceedings of the 2010 Workshop on Preference Learning (European Conference on Machine Learning, ECML), p. 15 (2010)

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