Brain-Computer Interfaces Based on Visual Evoked Potentials

By Xiaorong Gao, Bo Hong, Chuan Jia, Shangkai Gao. IEEE Engineering in Medicine and Biology Magazine, 2008

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Steady-state visually evoked potentials: focus on essential paradigms and future perspectives. (2010, background): “Recent investigations already discus these parameters (Piccini et al., 2005; Jia et al., 2007; Wang et al., 2008), which demonstrates how close we are from industrial practical applications.”
Filter bank canonical correlation analysis for implementing a high-speed SSVEP-based brain–computer interface (2015, background): “The steady-state visual evoked potential (SSVEP)-based brain – computer interface (BCI) has attracted more and more attention in the ﬁ eld of BCI due to its advantages such as high information transfer rate (ITR) and little user training (Wang et al 2008, Vialatte et al 2010).”
A Benchmark Dataset for SSVEP-Based Brain–Computer Interfaces (2017, background): “Recently, steady-state visual evoked potentials (SSVEPs) have been widely used in visual BCIs due to advantages of high information transfer rate (ITR) and little user training [8], [9].”