EEG data space adaptation to reduce intersession nonstationarity in brain-computer interface

• Main Authors: Arvaneh, Mahnaz, Guan, Cuntai, Ang, Kai Keng, Quek, Chai
• 其他作者: School of Computer Engineering
• 格式: Article
• 語言: English
• 出版: 2014
• 主題: DRNTU::Engineering::Computer science and engineering::Computer applications
• 在線閱讀: https://hdl.handle.net/10356/100036; http://hdl.handle.net/10220/18440
• 機構: Nanyang Technological University

A major challenge in EEG-based brain-computer interfaces (BCIs) is the intersession nonstationarity in the EEG data that often leads to deteriorated BCI performances. To address this issue, this letter proposes a novel data space adaptation technique, EEG data space adaptation (EEG-DSA), to linearly...