Deep Residual Convolutional Neural Networks for Brain–Computer Interface to Visualize Neural Processing of Hand Movements in the Human Brain

Deep Residual Convolutional Neural Networks for Brain–Computer Interface to Visualize Neural Processing of Hand Movements in the Human Brain

Concomitant with the development of deep learning, brain–computer interface (BCI) decoding technology has been rapidly evolving. Convolutional neural networks (CNNs), which are generally used as electroencephalography (EEG) classification models, are often deployed in BCI prototypes to improve the e...

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Bibliographic Details
Main Authors: Yosuke Fujiwara, Junichi Ushiba
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-05-01
Series:Frontiers in Computational Neuroscience
Subjects:
deep learning
brain-computer interface
Grad-CAM
electroencephalography
deep residual convolutional neural networks (CNN)
Online Access:https://www.frontiersin.org/articles/10.3389/fncom.2022.882290/full

Internet

https://www.frontiersin.org/articles/10.3389/fncom.2022.882290/full

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