ArticleSensors (Basel, Switzerland)2020
An Evaluation of Posture Recognition Based on Intelligent Rapid Entire Body Assessment System for Determining Musculoskeletal Disorders.
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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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.
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Who cites it
11 citing papers in PubMed.
- Evaluation of ergonomic work postures among dental students during restorative procedures using an artificial intelligence-based assessment model.Frontiers in oral health · 2026Article
- Technologies and Sensors for Artificial Muscles in Rehabilitation.Sensors (Basel, Switzerland) · 2024Review
- Validation of computer vision-based ergonomic risk assessment tools for real manufacturing environments.Scientific reports · 2024Article
- Compensation Method for Missing and Misidentified Skeletons in Nursing Care Action Assessment by Improving Spatial Temporal Graph Convolutional Networks.Bioengineering (Basel, Switzerland) · 2024Article
- Predictions of thumb, hand, and arm muscle parameters derived using force measurements of varying complexity and neural networks.Journal of biomechanics · 2023Article
- Analysis of the Reduction of Ergonomic Risks through the Implementation of an Automatic Tape Packaging Machine.International journal of environmental research and public health · 2022Article
- Accuracy Assessment of Joint Angles Estimated from 2D and 3D Camera Measurements.Sensors (Basel, Switzerland) · 2022Article
- Automatic real-time occupational posture evaluation and select corresponding ergonomic assessments.Scientific reports · 2022Article
- Validation of two-dimensional video-based inference of finger kinematics with pose estimation.PloS one · 2022Article
- Return Strategy and Machine Learning Optimization of Tennis Sports Robot for Human Motion Recognition.Frontiers in neurorobotics · 2022Article
- Prototype System for Measuring and Analyzing Movements of the Upper Limb for the Detection of Occupational Hazards.Sensors (Basel, Switzerland) · 2020Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Determining the potential risks of musculoskeletal disorders through working postures in a workplace is expensive and time-consuming. A novel intelligent rapid entire body assessment (REBA) system based on convolutional pose machines (CPM), entitled the Quick Capture system, was applied to determine the risk levels. The aim of the study was to validate the feasibility and reliability of the CPM-based REBA system through a simulation experiment. The reliability was calculated from the differences of motion angles between the CPM-based REBA and a motion capture system. Results show the data collected by the Quick Capture system were consistent with those of the motion capture system; the average of root mean squared error (RMSE) was 4.77 and the average of Spearman's rho (ρ) correlation coefficient in the different 12 postures was 0.915. For feasibility evaluation, the linear weighted Cohen's kappa between the REBA score obtained by the Quick Capture system and those from the three experts were used. The result shows good agreement, with an average proportion agreement index (P
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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.