Evaluating Across-Hinge Dragging with Pen and Touch on Curved and Foldable Displays
Bibliographic record
Abstract
Foldable touch screens are increasingly popular, but little research has explored how the hinge impacts usability and performance. We evaluate across- and along-hinge drag gestures on a series of prototypes emulating foldable all-screen laptops with a curved hinge radius ranging from 1mm to 24mm. Results show that using a large 24mm hinge radius instead of a small 1mm hinge radius can decrease drag time by 13% and movement variability by 7% for touch input. However, hinge radius had no effect on performance for pen input. Further, we found that dragging along the hinge was up to 30% faster than dragging across the hinge, especially when dragging across at an acute angle to the hinge. Using these results, we demonstrate use cases for across- and along-hinge gestures. Our findings provide guidance for hardware and interaction designers seeking to create foldable touchscreen devices and their accompanying software.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".