Design and ergonomic evaluation of a new adapted endoscope holder to reduce muscle pressure and discomfort during endoscopy
Bibliographic record
Abstract
BACKGROUND: Laparoscopic surgeons who regularly perform endoscopy are more likely to develop musculoskeletal disorders than other internal medicine specialists, a difference that attributed to repetitive movements, poor postures, and sub-optimal equipment design. OBJECTIVE: This study aimed to design, build, and evaluate an endoscope holder for reducing the static load applied by the weight of the endoscope, in order to reduce musculoskeletal disorders risk factors in the surgeon's hand, shoulder and back issues regions. METHODS: A new endoscope holder was designed according to ergonomic design principles. The designed holder was evaluated by surface electromyography (sEMG) and discomfort assessment including 15 laparoscopic surgeons. The results were analyzed with centrality statistics and compared with the independent t-test using SPSS version 22. RESULTS: The evaluation of the new endoscope holder shows a statistical significant decrease in the average electrical activity of biceps brachii, triceps brachii, lateral deltoid, T9 Thoracic erector spinae, L4 Lumbar erector spinae, and external oblique after using the holder (p < 0.05). CONCLUSION: The results shows that using the new endoscope holder is associated with a lower level of discomfort, as well as a lower induced muscle activity. The results also highlight the need to upgrade the holder to offer rotability in all directions (perpendicular to the ground) which will be included in the next design.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.002 | 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".