Abstract
The steady-state visual evoked potential (SSVEP), measured by the electroencephalograph (EEG), has high rates of information transfer and signal-to-noise ratio, and has been used to construct brain–computer interface (BCI) spellers. In BCI spellers, the targets of alphanumeric characters are assigned different visual stimuli and the fixation of each target generates a unique SSVEP. Matching the SSVEP to the stimulus allows users to select target letters and numbers. Many BCI spellers that harness the SSVEP have been proposed over the past two decades. Various paradigms of visual stimuli, including the procedure of target selection, layout of targets, stimulus encoding, and the combination with other triggering methods are used and considered to influence on the BCI speller performance significantly. This paper reviews these stimulus paradigms and analyzes factors influencing their performance. The fundamentals of BCI spellers are first briefly described. SSVEP-based BCI spellers, where only the SSVEP is used, are classified by stimulus paradigms and described in chronological order. Furthermore, hybrid spellers that involve the use of the SSVEP are presented in parallel. Factors influencing the performance and visual fatigue of BCI spellers are provided. Finally, prevailing challenges and prospective research directions are discussed to promote the development of BCI spellers.
Highlights
The brain–computer interface (BCI) is a communication system that allows humans to send messages and commands to the outside world without depending on peripheral nerves and muscles [1]
The BCI can be used for control and communication such that it provides a mode of communication for patients with motor neuron diseases (MNDs) such as amyotropic lateral sclerosis (ALS) and locked-in syndrome (LIS), to significantly improve their quality of life
Some studies have shown that single-channel acquisition using two electrodes is feasible for state visual evoked potential (SSVEP) detection [29], whereas others have shown that SSVEP signals can be collected from hairless regions of the body, but the signal-to-noise ratio (SNR) in this case is lower than that extracted from the occipital region [30]
Summary
The brain–computer interface (BCI) is a communication system that allows humans to send messages and commands to the outside world without depending on peripheral nerves and muscles [1]. The principle of the SSVEP-based BCI speller is to present a series of visual stimuli at specific frequencies to users and detect the SSVEP evoked by them through frequency domain analysis to find the user’s target. The frequencies that can be used to evoke the SSVEP are limited by the refresh frequency of the screen Another problem is that the SSVEP-based BCI speller induces visual fatigue in the user, where such fatigue is not severe but cannot be eliminated [8]. To improve the performance of BCI spellers, a number of spellers based on other triggering methods other than that mentioned above have been proposed.
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