ReviewBrain sciences2018
Brain-Computer Interface Spellers: A Review.
Review in Brain sciences, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 113 papers, 3 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
113 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- A systematic review of research on augmentative and alternative communication brain-computer interface systems for individuals with disabilities.Frontiers in human neuroscience · 2022Pooled it
- Noninvasive Electroencephalography Equipment for Assistive, Adaptive, and Rehabilitative Brain-Computer Interfaces: A Systematic Literature Review.Sensors (Basel, Switzerland) · 2021Pooled it
- Beyond Technologies of Electroencephalography-Based Brain-Computer Interfaces: A Systematic Review From Commercial and Ethical Aspects.Frontiers in neuroscience · 2020Pooled it
- Validation of portable, semi-dry electrode-based electroencephalography device for its application in brain-computer interface solutions.Scientific reports · 2026Article
- Rethinking Brain-Computer Interfaces for Soft Robotic Systems: A Unified Framework and Perspective.Sensors (Basel, Switzerland) · 2026Article
- A Cheonjiin Layout Mental Speller: Developing a Simple and Cost-Effective EEG-Based Brain-Computer Interface System.Sensors (Basel, Switzerland) · 2026Article
- ChatBCI, a P300 speller BCI with context-driven word prediction leveraging large language models, from concept to evaluation.Scientific reports · 2026Article
- Clinical evaluation of communication brain computer interfaces in amyotrophic lateral sclerosis: a landscape analysis.Frontiers in human neuroscience · 2026Article
- SSVEP-driven BCI authentication with reduced number of EEG electrodes across high and low frequency ranges.Frontiers in neuroergonomics · 2026Article
- Beyond flickering: introducing code-modulated motion visual evoked potentials for brain-computer interfacing.Frontiers in neuroergonomics · 2026Article
- Brain-Computer Interfaces for Vision Recovery in Precortical Vision Loss.Eye and brain · 2026Review
- Optimized hybrid Transformer-based model for EEG classification: application to wheelchair control.AIMS neuroscience · 2026Article
- Polarity-considered EEG microstates improve classification accuracy of oddball stimulus.Frontiers in human neuroscience · 2026Article
- Brain-computer interface: an update for the clinicians.Frontiers in human neuroscience · 2026Review
- Spiking neural networks provide accurate and time-efficient models for whisker stimulus classification of the awake mouse.Frontiers in neuroscience · 2026Article
- Optimal sensor set for MEG-based spontaneous and intended speech decoding toward practical communication.Frontiers in human neuroscience · 2026Article
- [Prospects and technical challenges of non-invasive brain-computer interfaces in manned space missions].Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2025Article
- Towards Predictive Communication: The Fusion of Large Language Models and Brain-Computer Interface.Sensors (Basel, Switzerland) · 2025Review
- EEG-Driven Arm Movement Decoding: Combining Connectivity and Amplitude Features for Enhanced Brain-Computer Interface Performance.Bioengineering (Basel, Switzerland) · 2025Article
- Exploring the feasibility of olfactory brain-computer interfaces.Scientific reports · 2025Article
53 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.