Decoding Multi-Class EEG Signals of Hand Movement Using Multivariate Empirical Mode Decomposition and Convolutional Neural Network

Decoding Multi-Class EEG Signals of Hand Movement Using Multivariate Empirical Mode Decomposition and Convolutional Neural Network

Brain-computer interface (BCI) is a technology that connects the human brain and external devices. Many studies have shown the possibility of using it to restore motor control in stroke patients. One specific challenge of such BCI is that the classification accuracy is not high enough for multi-clas...

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Bibliographic Details
Main Authors: Yi Tao, Weiwei Xu, Guangming Wang, Ziwen Yuan, Maode Wang, Michael Houston, Yingchun Zhang, Badong Chen, Xiangguo Yan, Gang Wang
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Transactions on Neural Systems and Rehabilitation Engineering
Subjects:
Electroencephalogram
hand movement
brain–computer interface
multivariate empirical mode decomposition
convolutional neural network
Online Access:https://ieeexplore.ieee.org/document/9899476/

Internet

https://ieeexplore.ieee.org/document/9899476/

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