ArticleBrain sciences2018
Code-VEP vs. Eye Tracking: A Comparison Study.
Article in Brain sciences, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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
5 citing papers in PubMed, 10 citations in OpenAlex.
- Streamlining cVEP Paradigms: Effects of a Minimized Electrode Montage on Brain-Computer Interface Performance.Brain sciences · 2025Article
- Influence of spatial frequency in visual stimuli for cVEP-based BCIs: evaluation of performance and user experience.Frontiers in human neuroscience · 2023Article
- A BCI Gaze Sensing Method Using Low Jitter Code Modulated VEP.Sensors (Basel, Switzerland) · 2019Article
- Robust Fusion of c-VEP and Gaze.IEEE sensors letters · 2019Article
- Workshops of the Seventh International Brain-Computer Interface Meeting: Not Getting Lost in Translation.Brain computer interfaces (Abingdon, England) · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Even with state-of-the-art techniques there are individuals whose paralysis prevents them from communicating with others. Brain⁻Computer-Interfaces (BCI) aim to utilize brain waves to construct a voice for those whose needs remain unmet. In this paper we compare the efficacy of a BCI input signal, code-VEP via Electroencephalography, against eye gaze tracking, among the most popular modalities used. These results, on healthy individuals without paralysis, suggest that while eye tracking works well for some, it does not work well or at all for others; the latter group includes individuals with corrected vision or those who squint their eyes unintentionally while focusing on a task. It is also evident that the performance of the interface is more sensitive to head/body movements when eye tracking is used as the input modality, compared to using c-VEP. Sensitivity to head/body movement could be better in eye tracking systems which are tracking the head or mounted on the face and are designed specifically as assistive devices. The sample interface developed for this assessment has the same reaction time when driven with c-VEP or with eye tracking; approximately 0.5⁻1 second is needed to make a selection among the four options simultaneously presented. Factors, such as system reaction time and robustness play a crucial role in participant preferences.
Indexed as
Identifiers
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.