Evaluation of tactile cues for simulated patients’ status under high and low workload
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The intensive care unit (ICU) is one of the most complex areas in hospital care, as patients require continuous monitoring by physicians and nurses. Currently, clinicians are informed about the patients’ physiological conditions through visual color-coded signals and auditory alarms. Previous studies have shown that vibrotactile cues can be used to inform clinicians of a patient’s vital signs status, either in a unisensory or multisensory alarm scheme. We present the results of the first in a series of experiments devoted to examining the feasibility to use tactile cues to convey detailed physiological information about more than one patient, rendered through a lower-leg tactile interface. The current experiment utilized a simulated clinical environment with 14 undergraduate students. Participants were required to interpret information delivered by the tactile interface, for two different patients, while they performed a continuous cognitively demanding task. Results indicate that under such conditions, it is possible to deliver critical information with a successful interpretation rate of approximately 85% but not without cost to the continuous demanding task. Future experiments should evaluate more tactile patterns in order to increase their interpretation success rate, and evaluate the use of these tactile cues with clinicians.
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.
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 | 0.000 |
| 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) | 0.000 | 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 it