Motor imagery BCI classification based on multivariate variational mode decomposition

Motor imagery BCI classification based on multivariate variational mode decomposition

In this article, a novel computer-aided diagnosis framework is proposed for the classification of motor imagery (MI) electroencephalogram (EEG) signals. First, a multivariate variational mode decomposition (MVMD) method was employed to obtain joint modes in frequency scale across all channels. Secon...

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Bibliographic Details
Main Authors: Sadiq, Muhammad Tariq, Yu, Xiaojun, Yuan, Zhaohui, Aziz, Muhammad Zulkifal, Rehman, Naveed ur, Ding, Weiping, Xiao, Gaoxi
Other Authors: School of Electrical and Electronic Engineering
Format: Journal Article
Language:English
Published: 2022
Subjects:
Engineering::Electrical and electronic engineering
Feature Extraction
Electroencephalography
Online Access:https://hdl.handle.net/10356/162830

Internet

https://hdl.handle.net/10356/162830

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