Haptics to improve task performance in people with disabilities: A review of previous studies and a guide to future research with children with disabilities
Bibliographic record
Abstract
This review examines the studies most pertinent to the potential of haptics on the functionality of assistive robots in manipulation tasks for use by children with disabilities. Haptics is the fast-emerging science that studies the sense of touch concerning the interaction of a human and his/her environment; this paper particularly studies the human-machine interaction that happens through a haptic interface to enable touch feedback. Haptics-enabled user interfaces for assistive robots can potentially benefit children whose haptic exploration is impaired due to a disability in their infancy and throughout their childhood. A haptic interface can provide touch feedback and potentially contribute to an enhancement in perception of objects and overall ability to perform manipulation tasks. The intention of this paper is to review the research on the applications of haptics, exclusively focusing on attributes affecting task performance. A review of studies will give a retrospective insight into previous research with various disability populations, and inform potential limitations/challenges in research regarding haptic interfaces for assistive robots for use by children with disabilities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".