Exploring Finger-Worn Solutions for Transitioning between the Reality-Virtuality Continuum
Bibliographic record
Abstract
Head-mounted displays (HMDs) enable users to navigate the Reality-Virtuality Continuum, facilitating transitions between the Real world, Augmented Reality, Augmented Virtuality, and the Virtual world. Traditional transition methods use double taps on HMDs or buttons on handheld controllers to transition between the worlds. However, this can often disrupt hands-free interaction and hinder the overall immersion. Although prior work explored transitioning within a reality, little is known about solutions facilitating transitioning across multiple worlds. In this paper, we investigate index finger-based solutions for transitioning between multiple realities. We designed and fabricated finger-worn button configurations of 2 × 2, 2 × 1, and 4 × 1, and compared them with finger-worn solutions such as Joystick, Rotary wheel, and Slider. The results showed that the 2 × 2 button configuration is the most effective technique, minimizing trial time and ensuring user comfort. Overall, this research enhances VR user experiences by improving interaction techniques for fluid switching between realities in the Reality-Virtuality Continuum.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".