Scalp-Targeted Haptic Proprioception for Upper-Limb Prosthetics
Bibliographic record
Abstract
In this paper, a head-worn wearable haptic feedback device (WHFD) is developed to communicate sensory information from an upper-limb prosthesis. A 14-week, 6-stage, between-subjects study was created to investigate the learning trajectory as participants were stimulated with haptic patterns conveying joint proprioception. Healthy participants were divided into three groups, with each group using a different haptic stimulation methods. 18 participants completed the study within 7-14 weekly sessions, demonstrating that participants were, in fact, learning to interpret the haptic information. Participants in the spatiotemporal stimulation group had some advantages in interpreting the haptic information over the others; however, each stimulation method has advantages that can be exploited and hybridized for future models of the WHFD. Overall, the proposed WHFD is an effective non-invasive device that can promote greater sensory awareness for wearers of prostheses.
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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 | 0.000 | 0.001 |
| 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) | 0.002 | 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 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".