On-body ergonomic lifting aid: It's effectiveness, safety and user acceptability
Bibliographic record
Abstract
T purpose of this presentation is to summarize 14 research studies involving an on-body ergonomic aid called the Personal Lift-Assist Device (PLAD). Three major questions asked were: 1) Is PLAD effective? 2) Is PLAD safe? 3) Is PLAD user-friendly? Data were collected using several different measurement tools: Liberty® electromagnetic sensors, Delsys® and Bortec® electromyography, Optotrak® position sensors, AEI Moxus® metabolic cart and subjective questionnaires. Measures of effectiveness revealed a 13.2-19.4% (p<0.05) reduction in back moments under the PLAD condition and 17-27% (p<0.05) in lumbar and thoracic EMG. During a fatiguing test, erector spinae EMG amplitudes were reduced by ~70% (p<0.001) over the No-PLAD condition. Measures of safety demonstrated that the PLAD altered the lifting technique so that lifts had less lumbar spine flexion and greater hip rotation (p<0.05). In addition, there was increased lumbar spine-hip coordination (p<0.05) and greater dynamic stability (p<0.05). In terms of user-acceptability, 83% of workers stated that they believed PLAD was effective and 67% said they would wear it for specific jobs. When energy consumption demands were evaluated, there was no significant difference between the PLAD and No-PLAD conditions indicating that the same amount of work was being done by specific leg muscles rather than the back. In conclusion, the PLAD is effective at reducing numerous risk factors and safety-related factors that are predispose workers to low back pain. It is also inexpensive, durable and suitable to many manual handling tasks including specific tasks in farming, construction, warehouse distribution, and assembly work.
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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".