Dorsal suspension in full-body harnesses: Comparison of perceived discomfort, pressure and physiological response
Bibliographic record
Abstract
Falls from height are still a major occupational hazard, particularly in the construction industry, where it is the leading cause of fatal injuries. When opting for personal fall arrest systems, the use of a safety harness is mandatory. Following a fall arrest, motionless suspension in a full-body harness can be hazardous and lead to death. This paper investigates the effect of harness type, gender, and somatotype on perceived discomfort, the pressure exerted by the harness straps, and the evolution of physiological parameters in motionless suspension. For this study, 30 male and 30 female students (10 ectomorph, 10 mesomorph, and 10 endomorph for each gender) were suspended for a maximum of ten minutes from the dorsal D-ring, in four different harnesses. The selected harnesses for this study are commercially available, one of them is X-configuration, another is Y-configuration, and the other two are the more traditional H-configuration. The results show that the H-configuration harnesses, which are very common in the industry and often the cheapest models, are perceived as the least tolerable in suspension. Moreover, H-configuration harnesses lead to greater reduction in muscular blood oxygenation and greater increase in the heart rate, which could make this type of harness hazardous. The Y-configuration harness seems to be the best performer in suspension. The influence of the sub-pelvic strap on suspension tolerance is not very clear and could be studied further. Those results could be useful to develop new harness models that would increase the suspension time tolerance.
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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".