Brain-Computer Interface Speller Based on Steady-State Visual Evoked Potential: A Review Focusing on the Stimulus Paradigm and Performance

Overview

Journal Brain Sci

Publisher MDPI

Date 2021 Apr 30

PMID 33916189

Citations 20

Authors

Minglun Li

Dianning He

Chen Li

Shouliang Qi

Affiliations

Soon will be listed here.

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.

Citing Articles

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MP: A steady-state visual evoked potential dataset based on multiple paradigms.

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Evaluation of Different Visual Feedback Methods for Brain-Computer Interfaces (BCI) Based on Code-Modulated Visual Evoked Potentials (cVEP).

Fodor M, Herschel H, Canturk A, Heisenberg G, Volosyak I Brain Sci. 2024; 14(8).

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Dual-Alpha: a large EEG study for dual-frequency SSVEP brain-computer interface.

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