Development and evaluation of multidimensional tactons for a wearable tactile display
Bibliographic record
Abstract
We developed a novel wearable tactile display system as an alternative to the visual and audio displays routinely used by anesthesiologists to monitor patients in the operating room (OR). Visual displays and auditory alarms can be distracting or insufficient in their alarm transmission whereas a tactile display, which utilizes the sense of touch, can act as an effective conduit for alert delivery. A sophisticated alarm scheme is essential to convey the complex array of physiological information available in current monitoring systems; therefore, to report all relevant alerts to the attending anesthesiologist, it is essential that an augmenting or replacement display system be at least as effective and efficacious as conventional systems. Using multidimensional Tactons, we designed a tactile alert scheme consisting of 36 unique stimuli and evaluated the accuracy and response time in stimuli recognition using a tactile prototype worn as a belt. We observed an overall accuracy of 81% and a response time of 4.8 seconds. 4.18 bits (18.07 tokens) of messages were successfully communicated without loss of information. These results demonstrate that the novel tactile display represents an effective and potentially work-load-reducing method to convey vital information non-visually and non-aurally.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".