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: Sadiq, Muhammad Tariq, Yu, Xiaojun, Yuan, Zhaohui, Zeming, Fan, Rehman, Ateeq Ur, Ullah, Inam, Li, Guoqi, Xiao, Gaoxi
Other Authors: School of Electrical and Electronic Engineering
Format: Journal Article
Language:English
Published: 2021
Subjects:
Engineering::Electrical and electronic engineering
Electroencephalography
Multiscale Principal Component Analysis
Online Access:https://hdl.handle.net/10356/145924

Internet

https://hdl.handle.net/10356/145924

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