High-speed brain-computer communication interface based on code-modulated visual evoked potentials

Grigoryan, Rafael; Филатов, Д Б; Kaplan, Arline

doi:10.24075/brsmu.2019.019

Cited by 1 publication

(2 citation statements)

References 17 publications

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“…Many of the reviewed studies (18/70) applied adaptive early stopping techniques to dynamically choose in real-time the time required to perform a selection in online mode [14,22,24,25,50,57,67,72,74,75,80,83,84,86,89,93,98,99]. All of these studies based their approaches on threshold comparisons, delivering the selected command when an optimized measure surpassed a predefined value.…”

Section: Early Stopping and Asynchronymentioning

confidence: 99%

“…These measures are usually derived from the correlation coefficients ρ between the online trials and the templates, such as direct comparison with ρ max [14,43,44,67,72,74,80,83,84,86,87], cumulative correlation [75], logistic regression models [89], comparisons between ρ max and a Beta distribution fitted to the rest of coefficients [22,25], or transformations into p-values [98,99]. Others used a margin criterion: difference between the first and second highest correlation [24,93] or class margins in OCSVM hyperplanes [57].…”

Section: Early Stopping and Asynchronymentioning

confidence: 99%

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

et al. 2021

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Objective. 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. Approach. 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. Main results. 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. Significance. 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.

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