Motor imagery BCI classification based on multivariate variational mode decomposition

• Main Authors: Sadiq, Muhammad Tariq, Yu, Xiaojun, Yuan, Zhaohui, Aziz, Muhammad Zulkifal, Rehman, Naveed ur, Ding, Weiping, Xiao, Gaoxi
• 其他作者: School of Electrical and Electronic Engineering
• 格式: Article
• 語言: English
• 出版: 2022
• 主題: Engineering::Electrical and electronic engineering; Feature Extraction; Electroencephalography
• 在線閱讀: https://hdl.handle.net/10356/162830

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...