EEG-Based Brain-Computer Interactions in Immersive Virtual and Augmented Reality: A Systematic Review
Why this work is in the frame
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Bibliographic record
Abstract
Brain-computer interactions allow humans to passively or actively control computer systems using their brain activity. For more than a decade now, these interactions have been implemented and evaluated in immersive virtual environments where they prompt novel means of human interaction with systems. In this paper, we present a systematic review of 76 studies published over the last 10 years that develop and evaluate immersive virtual reality or augmented reality systems with electroencephalography-based interactions. The aim of the review is to summarize and highlight trends in technology design, research methods, current practices, techniques used in systems of this kind, challenges and opportunities that present direction for future research in this area. Our analysis uncovers useful insights, limitations, and highlights of the trends, innovations, and usability and technical challenges at the intersection of brain-computer interfaces and immersive technologies, as well as recommendations for future research.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it