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

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

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...

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Bibliographic Details
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: Journal Article
Language:English
Published: 2024
Subjects:
Computer and Information Science
Motor imagery
Self-attention
Online Access:https://hdl.handle.net/10356/180824

Internet

https://hdl.handle.net/10356/180824

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