Convolutional and Recurrent Neural Networks for Physical Action Forecasting by Brain-Computer Interface-Reference-Cited by-同舟云学术

Convolutional and Recurrent Neural Networks for Physical Action Forecasting by Brain-Computer Interface

Published:2021-09-22 Issue: Volume: Page:
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Container-title:2021 11th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)
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Author:

Kostiukevych Kostiantyn,Stirenko Sergii,Gordienko Nikita,Rokovyi Oleksandr,Alienin Oleg,Gordienko Yuri

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9660827/9660386/09660880.pdf?arnumber=9660880

Reference26 articles.

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2. Applying deep learning to single-trial EEG data provides evidence for complementary theories on action control

3. Hand motion identification of grasp-and-lift task from electroencephalography recordings using recurrent neural networks;an;2016 International Conference on Big Data and Smart Computing (BigComp),2016

4. Ajile movement prediction: Multimodal deep learning for natural human neural recordings and video;wang;Proceedings of the AAAI Conference on Artificial Intelligence,0

5. Source aware deep learning framework for hand kinematic reconstruction using eeg signal;pancholi;ArXiv Preprint,2021

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