ArticleInternational journal of environmental research and public health2020
Development and Validation of a Wearable Inertial Sensors-Based Automated System for Assessing Work-Related Musculoskeletal Disorders in the Workspace.
Article in International journal of environmental research and public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
What it found
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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
21 citing papers in PubMed, 1 synthesis or guideline pooled it, 74 citations in OpenAlex.
- Transparency as a Means to Analyse the Impact of Inertial Sensors on Users during the Occupational Ergonomic Assessment: A Systematic Review.Sensors (Basel, Switzerland) · 2024Pooled it
- Ergonomic Risk Assessment of Professional Dance Using Motion Capture with Ergonomic Evaluation by the Rapid Entire Body Assessment (REBA).Sensors (Basel, Switzerland) · 2025Article
- Wearable sensor technologies for individuals with back pain: a scoping review.Pain management · 2025Article
- Ergo4Workers: A User-Centred App for Tracking Posture and Workload in Healthcare Professionals.Sensors (Basel, Switzerland) · 2025Article
- Review
- A new approach for the implementation of ergonomics in sonography to prevent work-related musculoskeletal disorders (ErgoSon).Journal of occupational medicine and toxicology (London, England) · 2025Article
- Review
- Ergonomic Analysis of Dental Work in Different Oral Quadrants: A Motion Capture Preliminary Study among Endodontists.Bioengineering (Basel, Switzerland) · 2024Article
- The Three-Dimensional Body Center of Mass at the Workplace under Hypogravity.Bioengineering (Basel, Switzerland) · 2023Article
- The Use of Wearable Inertial Sensors and Workplace-Based Exercises to Reduce Lateral Epicondylitis in the Workstation of a Textile Logistics Center.Sensors (Basel, Switzerland) · 2023Article
- A Wearable Multi-Modal Digital Upper Limb Assessment System for Automatic Musculoskeletal Risk Evaluation.Sensors (Basel, Switzerland) · 2023Article
- Exploring the Efficacy of a Set of Smart Devices for Postural Awareness for Workers in an Industrial Context: Protocol for a Single-Subject Experimental Design.JMIR research protocols · 2023Article
- Wearable Motion Capture Devices for the Prevention of Work-Related Musculoskeletal Disorders in Ergonomics-An Overview of Current Applications, Challenges, and Future Opportunities.Sensors (Basel, Switzerland) · 2023Review
- Evaluation of In-Cloth versus On-Skin Sensors for Measuring Trunk and Upper Arm Postures and Movements.Sensors (Basel, Switzerland) · 2023Article
- Prevalence of low back pain and its associated factors among traditional cloth weavers in Gulele sub-city, Addis Ababa, Ethiopia.Frontiers in public health · 2023Article
- Sensor-Based Motion Tracking System Evaluation for RULA in Assembly Task.Sensors (Basel, Switzerland) · 2022Article
- A Work-Related Musculoskeletal Disorders (WMSDs) Risk-Assessment System Using a Single-View Pose Estimation Model.International journal of environmental research and public health · 2022Article
- Prevalence and factors associated with work-related musculoskeletal disorder among health care providers working in the operation room.Annals of medicine and surgery (2012) · 2021Article
- Implementation of Kinetic and Kinematic Variables in Ergonomic Risk Assessment Using Motion Capture Simulation: A Review.International journal of environmental research and public health · 2021Review
- A Wearable Sensor-Based Platform for Surgeon Posture Monitoring: A Tool to Prevent Musculoskeletal Disorders.International journal of environmental research and public health · 2021Article
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 at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The industrial societies face difficulty applying traditional work-related musculoskeletal disorder (WMSD) risk assessment methods in practical applications due to in-situ task dynamics, complex data processing, and the need of ergonomics professionals. This study aims to develop and validate a wearable inertial sensors-based automated system for assessing WMSD risks in the workspace conveniently, in order to enhance workspace safety and improve workers' health. Both postural ergonomic analysis (RULA/REBA) and two-dimensional static biomechanical analysis were automatized as two toolboxes in the proposed system to provide comprehensive WMSD risk assessment based on the kinematic data acquired from wearable inertial sensors. The effectiveness of the developed system was validated through a follow-up experiment among 20 young subjects when performing representative tasks in the heavy industry. The RULA/REBA scores derived from our system achieved high consistency with experts' ratings (intraclass correlation coefficient ≥0.83, classification accuracy >88%), and good agreement was also found between low-back compression force from the developed system and the reference system (mean intersystem coefficient of multiple correlation >0.89 and relative error <9.5%). These findings suggested that the wearable inertial sensors-based automated system could be effectively used for WMSD risk assessment of workers when performing tasks in the workspace.
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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.