A haptic wristwatch for eyes-free interactions
Bibliographic record
Abstract
We present a haptic wristwatch prototype that makes it possible to acquire information from a companion mobile device through simple eyes-free gestures. The wristwatch we have built uses a custom-made piezoelectric actuator combined with sensors to create a natural, inconspicuous, gesture-based interface. Feedback is returned to the user in the form of haptic stimuli that are delivered to the wrist. We evaluated the capabilities and limitations of our prototype through two user experiments. One experiment verified that the apparatus could be used as a tactile notification mechanism. The other experiment assessed the feasibility of using a cover-and-hold gesture on the wristwatch to obtain numerical data tactually. Results from the numerosity experiment and feedback from participants prompted us to redesign the cover-and-hold gesture to provide users with additional control over the interaction. We qualitatively evaluated the redesigned interaction by handing the prototype to users so that they could use it in a realistic work environment. Taken together, results from the experiments and the validation process indicate that a wrist accessory can be effectively used to perform discreet, closed-loop, eyes-free interactions with a mobile device.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".