ArticleSensors (Basel, Switzerland)2026
Computer-Vision-Enabled Worker Video Analysis for Motion Amount Quantification.
Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- A scoping review on emerging technologies and automation of musculoskeletal ergonomic assessments.Ergonomics · 2026Article
- CLUMM: Contrastive Learning for Unobtrusive Motion Monitoring.Sensors (Basel, Switzerland) · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
The performance of physical workers is significantly influenced by the extent and quality of their motions. However, accurately measuring and assessing these motions remains a challenge due to the limitations in conventional instrumentation; wearable sensors require calibration and restrict mobility, while marker-based motion capture systems are costly and impractical for field deployment. Recent advancements have enabled in situ video analysis for the real-time observation of worker behaviors. To address these measurement constraints, this paper introduces a novel framework for tracking and quantifying upper and lower limb motions, issuing alerts when critical thresholds are reached. Using joint position data from posture estimation, the framework employs Hotelling's T2 statistic to quantify and monitor motion amounts. A significant positive correlation was noted between motion warnings and the overall NASA Task Load Index (TLX) workload rating (
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.