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

• المؤلفون الرئيسيون: Arvaneh, Mahnaz, Guan, Cuntai, Ang, Kai Keng, Quek, Chai
• مؤلفون آخرون: School of Computer Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2014
• الموضوعات: DRNTU::Engineering::Computer science and engineering::Computer applications
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/100036; http://hdl.handle.net/10220/18440
• المؤسسة: 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...