Brain–computer interfaces based on code-modulated visual evoked potentials (c-VEP): a literature review

• Published in: Journal of neural engineering 2021-12, Vol.18 (6), p.61002
• Main Authors: Martínez-Cagigal, Víctor, Thielen, Jordy, Santamaría-Vázquez, Eduardo, Pérez-Velasco, Sergio, Desain, Peter, Hornero, Roberto
• Format: Article
• Language: English
• Subjects: Brain-Computer Interfaces; brain–computer interface (BCI); code-modulated VEP (c-VEP); electroencephalogram (EEG); Electroencephalography - methods; Evoked Potentials, Visual; Language; literature review; Signal Processing, Computer-Assisted; visual evoked potential (VEP)
• ISSN: 1741-2560; 1741-2552
• DOI: 10.1088/1741-2552/ac38cf

Code-modulated visual evoked potentials (c-VEP) have been consolidated in recent years as robust control signals capable of providing non-invasive brain-computer interfaces (BCIs) for reliable, high-speed communication. Their usefulness for communication and control purposes has been reflected in an exponential increase of related articles in the last decade. The aim of this review is to provide a comprehensive overview of the literature to gain understanding of the existing research on c-VEP-based BCIs, since its inception (1984) until today (2021), as well as to identify promising future research lines. The literature review was conducted according to the Preferred Reporting Items for Systematic reviews and Meta-Analysis guidelines. After assessing the eligibility of journal manuscripts, conferences, book chapters and non-indexed documents, a total of 70 studies were included. A comprehensive analysis of the main characteristics and design choices of c-VEP-based BCIs was discussed, including stimulation paradigms, signal processing, modeling responses, applications, etc. The literature review showed that state-of-the-art c-VEP-based BCIs are able to provide an accurate control of the system with a large number of commands, high selection speeds and even without calibration. In general, a lack of validation in real setups was observed, especially regarding the validation with disabled populations. Future work should be focused toward developing self-paced c-VEP-based portable BCIs applied in real-world environments that could exploit the unique benefits of c-VEP paradigms. Some aspects such as asynchrony, unsupervised training, or code optimization still require further research and development. Despite the growing popularity of c-VEP-based BCIs, to the best of our knowledge, this is the first literature review on the topic. In addition to providing a joint discussion of the advances in the field, some future lines of research are suggested to contribute to the development of reliable plug-and-play c-VEP-based BCIs.