Brain–Computer Interface Spellers: A Review

Abstract

A Brain–Computer Interface (BCI) provides a novel non-muscular communication method via brain signals. A BCI-speller can be considered as one of the first published BCI applications and has opened the gate for many advances in the field. Although many BCI-spellers have been developed during the last few decades, to our knowledge, no reviews have described the different spellers proposed and studied in this vital field. The presented speller systems are categorized according to major BCI paradigms: P300, steady-state visual evoked potential (SSVEP), and motor imagery (MI). Different BCI paradigms require specific electroencephalogram (EEG) signal features and lead to the development of appropriate Graphical User Interfaces (GUIs). The purpose of this review is to consolidate the most successful BCI-spellers published since 2010, while mentioning some other older systems which were built explicitly for spelling purposes. We aim to assist researchers and concerned individuals in the field by illustrating the highlights of different spellers and presenting them in one review. It is almost impossible to carry out an objective comparison between different spellers, as each has its variables, parameters, and conditions. However, the gathered information and the provided taxonomy about different BCI-spellers can be helpful, as it could identify suitable systems for first-hand users, as well as opportunities of development and learning from previous studies for BCI researchers.

Preliminary Results Using a P300 Brain-Computer Interface Speller: A Possible Interaction Effect Between Presentation Paradigm and Set of Stimuli

“…The P300 potential when used in a speller is influenced by numerous parameters, such as the number of elements of the matrix, the stimuli presentation duration or the use of some stimuli over others (see [9] for a detailed review of BCI spellers). In relation to this last parameter, the presented stimuli, it has been shown how the use of symbols of different colors or complex figures, instead of simple letters, can increase performance [10][11][12].…”

Coupled CP Decomposition of Simultaneous MEG-EEG Signals for Differentiating Oscillators During Photic Driving

“…The tensor decomposition approach can be of high practical value when integrated into brain-computer-interfaces, such as a speller application for paralyzed users (Rezeika et al, 2018). Such spellers detect user selections from the brain's response to steady state visual stimulation.…”

Evaluation of flashing stimuli shape and colour heterogeneity using a P300 brain-computer interface speller

“…Following the previously explained paradigm, numerous proposals have been suggested to improve the use of a P300 speller matrix (see Rezeika et al (2018) for a detailed review). For example, some works have been focused on certain parameters such as variations in the lighting patterns (Townsend et al, 2010), presentation times and brightness intensity (Li et al, 2014), size of the stimuli and the distance between them (Li et al, 2011), colour (Takano et al, 2009), number of stimuli (Sellers et al, 2006), or the nature of these, e.g., letters, faces, or geometrical figures (Kaufmann et al, 2011;Treder et al, 2011).…”