A first look at individuals' affective ratings of vibrations
Bibliographic record
Abstract
Affective response may dominate users' reactions to the synthesized tactile sensations that are proliferating in today's handheld and gaming devices, yet it is largely unmeasured, modeled or characterized. A better understanding of user perception will aid the design of tactile behavior that engages touch, with an experience that satisfies rather than intrudes. We measured 30 subjects' affective response to vibrations varying in rhythm and frequency, then examined how differences in demographic, everyday use of touch, and tactile processing abilities contribute to variations in affective response. To this end, we developed five affective and sensory rating scales and two tactile performance tasks, and also employed a published `Need for Touch' (NFT) questionnaire. Subjects' ratings, aggregated, showed significant correlations among the five scales and significant effect of the signal content (rhythm and frequency). Ratings varied considerably among subjects, but this variation did not coincide with demographic, NFT score or tactile task performance. The linkages found among the rating scales confirm this as a promising approach. The next step towards a comprehensive picture of individuals' patterns of affective response to tactile sensations entails pruning, integration and redundancy reduction of these scales, then their formal validation.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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; both teacher heads agree on what is shown here.
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".