Almost free of calibration for SSVEP-based brain-computer interfaces
Ruixin Luo,
Xiaolin Xiao,
Enze Chen
et al.
Abstract:Objective. Steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) is a promising technology that can achieve high information transfer rate (ITR) with supervised algorithms such as ensemble task-related component analysis (eTRCA) and task-discriminant component analysis (TDCA). However, training individual models requires a tedious and time-consuming calibration process, which hinders the real-life use of SSVEP-BCIs. A recent data augmentation method, called source aliasing matrix es… Show more
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