Investigating the Relationship Between Eye Movement and Brain Wave Activity Using Video Games: Pilot Study
Bibliographic record
Abstract
BACKGROUND: All eye movements are related in one way or another to our mental processes with lateral eye movements being associated with the different hemispheres of the brain. Eye movement techniques form the basis of eye movement desensitization and reprocessing therapy, wherein forced eye movements activate neurological pathways to treat the subject. OBJECTIVE: The objective of our study was to examine the relationship between players' eye movements and their brain wave activities using a video game. METHODS: We used similar eye movement techniques in the form of a video game called Lifeguard that could potentially stimulate different eye movement mode and create a more engaging experience for the user. By designing an experiment, we further explored the differences in electroencephalogram spectral power activity for the alpha, beta, theta, delta, and gamma frequency bands in Lifeguard and Tetris. RESULTS: The game based on eye movement technologies resulted in decreased delta power and increased beta power, but significant difference between 2 games was not found. CONCLUSIONS: The applied uses of this research could mean that eye movement desensitization and reprocessing can be conducted in a more fun and engaging way through the use of gaming technology.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".