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

• Main Authors: Arvaneh, Mahnaz, Guan, Cuntai, Ang, Kai Keng, Quek, Chai
• Other Authors: School of Computer Engineering
• Format: Article
• Language: English
• Published: 2014
• Subjects: DRNTU::Engineering::Computer science and engineering::Computer applications
• Online Access: https://hdl.handle.net/10356/100036; http://hdl.handle.net/10220/18440
• Institution: 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...