Motor Imagery EEG Signals Decoding by Multivariate Empirical Wavelet Transform-Based Framework for Robust Brain–Computer Interfaces

Motor Imagery EEG Signals Decoding by Multivariate Empirical Wavelet Transform-Based Framework for Robust Brain–Computer Interfaces

The robustness and computational load are the key challenges in motor imagery (MI) based on electroencephalography (EEG) signals to decode for the development of practical brain-computer interface (BCI) systems. In this study, we propose a robust and simple automated multivariate empirical wavelet t...

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Bibliographic Details
Main Authors: Muhammad Tariq Sadiq, Xiaojun Yu, Zhaohui Yuan, Fan Zeming, Ateeq Ur Rehman, Inam Ullah, Guoqi Li, Gaoxi Xiao
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Electroencephalography
multiscale principal component analysis
brain-computer interface
multivariate empirical wavelet transform
Online Access:https://ieeexplore.ieee.org/document/8913546/

Internet

https://ieeexplore.ieee.org/document/8913546/

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