Evaluating a prototype device designed to alleviate night vision goggle induced neck strain among military personnel
Bibliographic record
Abstract
The purpose of this study was verify the design of a novel Helmet System Support Device (HSSD) that can be used by military aircrew to help intervene on and reduce the high prevalence of neck trouble. Twelve healthy participants repeated simulated helicopter aircrew tasks on 3 separate days. On each day they wore a different helmet configuration, where measures of performance, perceived demand/preference and muscular demand were recorded. The results showed that vigilance tasks were performed over 10% faster with the HSSD configuration compared to wearing the normal helmet configuration. Participants were able to maintain static (endurance) postures for 28% longer, and use of the HSSD helped to prevent neck muscle fatigue in the most demanding task. The results of this design verification study indicate that the HSSD may be a realistic, feasible near-term solution to intervene on the high prevalence of neck trouble among rotary-wing aircrew. Practitioner Summary: This paper verifies the effectiveness of the Helmet System Support Device (HSSD) as an on-body personal protective device to help control exposures associated with aircrew neck trouble. The HSSD reduced perceived demand, reduced cumulative muscle activity in select muscles and provided improved fatigue resistance, meeting its desired design objectives.
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 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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".