Leveraging temporal dependency for cross-subject-MI BCIs by contrastive learning and self-attention

• Main Authors: Sun, Hao, Ding, Yi, Bao, Jianzhu, Qin, Ke, Tong, Chengxuan, Jin, Jing, Guan, Cuntai
• Other Authors: School of Computer Science and Engineering
• Format: Article
• Language: English
• Published: 2024
• Subjects: Computer and Information Science; Motor imagery; Self-attention
• Online Access: https://hdl.handle.net/10356/180824
• Institution: Nanyang Technological University

Brain-computer interfaces (BCIs) built based on motor imagery paradigm have found extensive utilization in motor rehabilitation and the control of assistive applications. However, traditional MI-BCI systems often exhibit suboptimal classification performance and require significant time for new user...