A Descriptive Analysis of a Formative Decade of Research in Affective Haptic System Design
Bibliographic record
Abstract
The global pandemic exposed serious drawbacks in relying on communication modalities in which social touch, however important, is absent. Considerable research has explored haptic technologies for sensing or displaying social touch and influencing affective state, for wellness, social communication, emotion regulation, and affect therapy. However, this Affective Haptic System design (AHSD) work varies widely in purpose and origin discipline, making it difficult to perceive overall progress and identify primary obstacles to practical deployment. We conducted a scoping review and conceptual analysis with a design lens, identifying 110 papers from the last decade in 11 ACM and IEEE venues that regularly attract AHSD work. Our analysis identified 38 dimensions within 8 facets: demographic, theoretical grounding, impact, system specification, usage specification, ethical consideration, technology, and evaluation. We visualize trends, disciplinary mixing, and topical focus over time, and highlight major advances while pinning down crucial gaps that can be addressed in the future.
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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 | 0.039 | 0.130 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.029 | 0.028 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".