Motor imagery BCI classification based on multivariate variational mode decomposition

• المؤلفون الرئيسيون: Sadiq, Muhammad Tariq, Yu, Xiaojun, Yuan, Zhaohui, Aziz, Muhammad Zulkifal, Rehman, Naveed ur, Ding, Weiping, Xiao, Gaoxi
• مؤلفون آخرون: School of Electrical and Electronic Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2022
• الموضوعات: Engineering::Electrical and electronic engineering; Feature Extraction; Electroencephalography
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/162830
• المؤسسة: Nanyang Technological University

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...