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Record W4206246064 · doi:10.1080/00140139.2022.2030806

A design tool to estimate maximum acceptable manual arm forces for above-shoulder work

2022· article· en· W4206246064 on OpenAlexaff
David Rempel, Jim R. Potvin

Bibliographic record

VenueErgonomics · 2022
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsMcMaster University
FundersNational Institute for Occupational Safety and Health
KeywordsWork (physics)Shoulder jointMedicineAnterior shoulderPhysical therapyPhysical medicine and rehabilitationOrthodonticsSurgeryEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

There is a need for design criteria for above-shoulder work to prevent shoulder fatigue and supraspinatus injuries. A tool is developed to estimate maximum acceptable manual arm forces for above-shoulder work based on 25th % female strength with adjustments for supraspinatus tendon impingement and shoulder fatigue. The tool equations are presented along with tables of maximum acceptable manual arm forces in 77 locations in the 3 D space above the shoulder that accommodates a 50th % female reach. The largest acceptable anterior force, 140.3 N, occurs at shoulder height, 0.5 m anterior to the shoulder. The largest acceptable superior force, 84.4 N, occurs at shoulder height, 0.1 m anterior and 0.2 m medial to the shoulder. The new tool provides design criteria for arm exertions at a higher level of detail than prior ergonomic tools, making it useful for engineers. Based on sensitivity analyses, the tool is robust to parameter assumptions. Practitioner summary: Above-shoulder work is associated with increased risk for shoulder fatigue and injuries. A new tool is developed that estimates maximum acceptable manual arm forces for work at or above shoulder height. The tool can be used to design acceptable above-shoulder work so that it can be accomplished by most workers. Abbreviations: AFF: arm force field; AP: anterior/posterior; DC: duty cycle; GH: glenohumeral angle; HT: humerothoracic angle; LM: lateral/medial; MAE: maximum acceptable effort; MAF: maximum acceptable force; MAS: manual arm strength; MVC: maximum voluntary contraction; N: newton; OCRA: occupational repetitive action; R: reach distance; RMS: root means square; RULA: rapid upper limb assessment; SF: scale factor; SI: superior/inferior; ST: scapulothoracic angle; T: thoracicKEY POINTSA new design tool is introduced that estimates maximum acceptable hand forces for specific locations above the shoulder.This above-shoulder tool is based on a 50th percentile female anthropometry and 25th percentile female manual arm strength.These base strengths are multiplied by scaling factors that adjust for subacromial impingement and fatigue.The tool was shown to be robust based on sensitivity analysis.

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 imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.010
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.016
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.002

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.

Opus teacher head0.041
GPT teacher head0.342
Teacher spread0.301 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

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".

Quick stats

Citations7
Published2022
Admission routes1
Has abstractyes

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