Monocular 3D Multi-Person Pose Estimation for On-Site Joint Flexion Assessment: A Case of Extreme Knee Flexion Detection.

Work-related musculoskeletal disorders (WMSDs) represent a significant health challenge for workers in construction environments, often arising from prolonged exposure to ergonomic risks associated with manual labor, awkward postures, and repetitive motions. These conditions not only lead to diminished worker productivity but also incur substantial economic costs for employers and healthcare systems alike. Thus, there is an urgent need for effective tools to assess and mitigate these ergonomic risks. This study proposes a novel monocular 3D multi-person pose estimation method designed to enhance ergonomic risk assessments in construction environments. Leveraging advanced computer vision and deep learning techniques, this approach accurately captures and analyzes the spatial dynamics of workers' postures, with a focus on detecting extreme knee flexion, a critical indicator of work-related musculoskeletal disorders (WMSDs). A pilot study conducted on an actual construction site demonstrated the method's feasibility and effectiveness, achieving an accurate detection rate for extreme flexion incidents that closely aligned with supervisory observations and worker self-reports. The proposed monocular approach enables universal applicability and enhances ergonomic analysis through 3D pose estimation and group pose recognition for timely interventions. Future efforts will focus on improving robustness and integration with health monitoring to reduce WMSDs and promote worker health.

An integrated ergonomic risk assessment framework based on fuzzy logic and IVSF-AHP for optimising ergonomic risks in a mixed-model assembly line.

This study proposes a systematic approach to address ergonomic factors, including physical, environmental and psychosocial aspects, in solving assembly line balancing problems. A three-stage framework is developed, starting with determining weights for ergonomic risk assessment methods using the interval-valued spherical fuzzy analytical hierarchy process. In the second stage, a fuzzy logic model for integrated ergonomic risk assessment is constructed based on these weights, and the integrated ergonomic risk score is determined. In the third stage, a mathematical model is formulated to minimise the cycle time while balancing the ergonomic risk level. A case study conducted in a wire harness factory validated the effectiveness of the proposed approach, showing a 10-11% improvement in line efficiency and a 12-25% enhancement in ergonomic risk balancing performance. These findings underscore the potential benefits of implementing this approach, which can significantly improve occupational safety and overall performance.

This article presents a practical and systematic approach for enhancing ergonomic conditions in assembly lines. The proposed approach aims to balance the ergonomic risk level while minimising the cycle time by considering physical, environmental and psychosocial risk factors. A case study conducted in a wire harness factory demonstrated significant improvements in balancing ergonomic risks, highlighting the real-world applicability of this research.

Effects of an ergonomic intervention program based on the PRECEDE-PROCEED model for reducing work-related health problems and exposure risks among emergency medical dispatchers.

OBJECTIVE: To evaluate the effectiveness of an ergonomic intervention program based on the PRECEDE-PROCEED model in terms of improving exposure risks and work-related health problems in emergency medical dispatchers. METHODS: This quasi-experimental study used an interrupted time series design. Participants were 55 employees working in an Emergency Medical Communications Center in Iran. The intervention program was based on the PRECEDE-PROCEED model and included five face-to-face training sessions and installing auxiliary equipment according to best ergonomic principles. Direct observations of the emergency medical dispatchers' working postures using the Rapid Office Strain Assessment and a survey which included a modified Nordic Questionnaire, Work Ability Score, Visual Fatigue Questionnaire, and a Behavioral Factors Questionnaire were used at three time points: baseline, 1 month post-intervention, and 3 months post-intervention. RESULTS: The modified Nordic Questionnaire showed significant reductions in pain intensity scores for neck, lower back, knee and ankle after the ergonomic intervention program. In addition, there were considerable post-training improvements in behavioral factors (knowledge and enabling factors) and working postures. No significant changes were observed in Work Ability Scores, or visual symptoms. CONCLUSIONS: An ergonomic intervention program based on a systematic framework such as the PRECEDE-PROCEED model and on-site interventions can be effective in improving and enhancing the working conditions of emergency medical dispatchers. Therefore, it is suggested that ergonomic interventions be implemented based on standard and valid behavioral change models such as PRECEDE-PROCEED model in other work environments in which musculoskeletal pain and digital eye strain are common.

Automatic Ergonomic Risk Assessment Using a Variational Deep Network Architecture.

Ergonomic risk assessment is vital for identifying work-related human postures that can be detrimental to the health of a worker. Traditionally, ergonomic risks are reported by human experts through time-consuming and error-prone procedures; however, automatic algorithmic methods have recently started to emerge. To further facilitate the automatic ergonomic risk assessment, this paper proposes a novel variational deep learning architecture to estimate the ergonomic risk of any work-related task by utilizing the Rapid Entire Body Assessment (REBA) framework. The proposed method relies on the processing of RGB images and the extraction of 3D skeletal information that is then fed to a novel deep network for accurate and robust estimation of REBA scores for both individual body parts and the entire body. Through a variational approach, the proposed method processes the skeletal information to construct a descriptive skeletal latent space that can accurately model human postures. Moreover, the proposed method distills knowledge from ground truth ergonomic risk scores and leverages it to further enhance the discrimination ability of the skeletal latent space, leading to improved accuracy. Experiments on two well-known datasets (i.e., University of Washington Indoor Object Manipulation (UW-IOM) and Technische Universität München (TUM) Kitchen) validate the ability of the proposed method to achieve accurate results, overcoming current state-of-the-art methods.

Development of an educational protocol for ergonomic risk assessment of working postures to enhance the competence of occupational health nurses.

AIM: To develop a protocol and provide a valid, evidence-based procedure for identifying the ergonomic risk of working postures by occupational health nurses. BACKGROUND: Although ergonomic risk assessment tools have been used for the early detection of risky working postures, their operational procedures and validations do not target the competence of occupational nursing personnel. DESIGN: This study developed and validated an educational protocol, comprised of 13 procedures in five stages. First, the number of work tasks in the workplace is determined. Second, the working postures are confirmed. Third, the raters are trained to use the assessment tools. Fourth, high-risk postures are identified and categorized. Fifth, the inter-rater reliability of the tool is reported. The content of the protocol is validated by experts, with a validity value of 0.87. DATA SOURCES: The protocol was created through review of literature published from 1991 to 2021, protocol development (between 2018 to 2020) and expert validation (2020). CONCLUSION: The protocol can be applied to educate occupational health nurses and increase their competence in detecting workers' ergonomic risks. It can be used as a reference in occupational health nursing education to evaluate work tasks and detect risky postures.

An Evaluation of Motion Trackers with Virtual Reality Sensor Technology in Comparison to a Marker-Based Motion Capture System Based on Joint Angles for Ergonomic Risk Assessment.

The reproduction and simulation of workplaces, and the analysis of body postures during work processes, are parts of ergonomic risk assessments. A commercial virtual reality (VR) system offers the possibility to model complex work scenarios as virtual mock-ups and to evaluate their ergonomic designs by analyzing motion behavior while performing work processes. In this study a VR tracking sensor system (HTC Vive tracker) combined with an inverse kinematic model (Final IK) was compared with a marker-based optical motion capture system (Qualisys). Marker-based optical motion capture systems are considered the gold standard for motion analysis. Therefore, Qualisys was used as the ground truth in this study. The research question to be answered was how accurately the HTC Vive System combined with Final IK can measure joint angles used for ergonomic evaluation. Twenty-six subjects were observed simultaneously with both tracking systems while performing 20 defined movements. Sixteen joint angles were analyzed. Joint angle deviations between ±6∘ and ±42∘ were identified. These high deviations must be considered in ergonomic risk assessments when using a VR system. The results show that commercial low-budget tracking systems have the potential to map joint angles. Nevertheless, substantial weaknesses and inaccuracies in some body regions must be taken into account. Recommendations are provided to improve tracking accuracy and avoid systematic errors.

Frequency of work related musculoskeletal disorders and ergonomic risk assessments among tailors.

OBJECTIVE: To determine the frequency of work-related musculoskeletal disorders and to assess postural ergonomic risk among tailors. METHODS: The cross-sectional study was conducted from September 2017 to February 2018 in Rawalpindi and Islamabad, Pakistan and comprised tailors of both genders aged 25-60 years, working for more than 6 months and having small and medium enterprises. To calculate ergonomic risk of work posture, Quick Exposure Check was used and work-related musculoskeletal disorders were determined through body mapping chart. Data was analysed using SPSS 20. RESULTS: Of the 400 tailors, 382(95.5%) were males. The overall mean age of the sample was 36.9±10.96 years. The mean Quick Exposure Check score was 46.11±14.83. Acceptable work posture was found in 373(93.25%) subjects. The most common work-related acute musculoskeletal symptoms were found in the upper back 320(80%). CONCLUSIONS: Most tailors had acceptable work posture but work-related pain in upper back was common.

A comparative study of biomechanical assessments in laboratory and field settings for manual material handling tasks using extractor tools and exoskeletons.

To enhance physical capabilities of workers who regularly perform physically demanding tasks involving heavy lifting and awkward postures, various tools and occupational exoskeletons can be used. Most of the studies aiming to explore the efficiency of these tools and exoskeletons have been performed in confined and controlled laboratory spaces, which do not represent the real-world work environment. This study aimed to compare the outcome of biomechanical assessment of using a back support exoskeleton and assistive tools (Lever and Jake) in the procedure of a high demanding manual material handling task versus the results found by performing the same task in a laboratory. Ten able-bodied participants and ten able-bodied utility workers performed the same manhole removal task in-lab and in-field, respectively, with the aid of an exoskeleton and Lever and Jake tools. Muscle activity and Rapid Entire Body Assessment (REBA) scores were recorded using surface electromyography and inertial measurement units, respectively and compared between in-lab and in-field trials. The field experiments indicated significant differences (p < 0.05) in normalized muscle activity across most muscles when compared to laboratory data. These results revealed how muscle activity is affected by the controlled lab setting compared to real-world field conditions. However, REBA scores indicate similar ergonomic implications regardless of the utilization of exoskeletons or tools. These findings underscore that real-world field assessments are crucial for evaluating ergonomic risks and effects of occupational exoskeletons and tools to account for environmental factors and workers' skills in ergonomic evaluations of this nature.

Musculoskeletal-Modeling-Based, Full-Body Load-Assessment Tool for Ergonomists (MATE): Method Development and Proof of Concept Case Studies.

A new ergonomic-risk-assessment tool was developed that combines musculoskeletal-model-based loading estimates with insights from fatigue failure theory to evaluate full-body musculoskeletal loading during dynamic tasks. Musculoskeletal-modeling output parameters, i.e., joint contact forces and muscle forces, were combined with tissue-specific injury thresholds that account for loading frequency to determine the injury risk for muscles, lower back, and hip cartilage. The potential of this new risk-assessment tool is demonstrated for defining ergonomic interventions in terms of lifting characteristics, back and shoulder exoskeleton assistance, box transferring, stoop lifting, and an overhead wiring task, respectively. The MATE identifies the risk of WMSDs in different anatomical regions during occupational tasks and allows for the evaluation of the impact of interventions that modify specific lifting characteristics, i.e., load weight versus task repetition. Furthermore, and in clear contrast to currently available ergonomic assessment scores, the effects of the exoskeleton assistance level on the risk of WMSDs of full-body musculoskeletal loading (in particular, the muscles, lower back, and hips) can be evaluated and shows small reductions in musculoskeletal loading but not in injury risk. Therefore, the MATE is a risk-assessment tool based on a full-body, musculoskeletal-modeling approach combined with insights from the fatigue failure theory that shows the proof of concept of a shoulder and back exoskeleton. Furthermore, it accounts for subject-specific characteristics (age and BMI), further enhancing individualized ergonomic-risk assessment.

Online Ergonomic Evaluation in Realistic Manual Material Handling Task: Proof of Concept.

Work-related musculoskeletal disorders are globally one of the leading causes of work-related injuries. They significantly impact worker health and business costs. Work task ergonomic risk indices have been developed that use observational assessments to identify potential injuries, and allow safety managers to promptly intervene to mitigate the risks. However, these assessments are very subjective and difficult to perform in real time. This work provides a technique that can digitalize this process by developing an online algorithm to calculate the NIOSH index and provide additional data for ergonomic risk assessment. The method is based on the use of inertial sensors, which are easily found commercially and can be integrated into the industrial environment without any other sensing technology. This preliminary study demonstrates the effectiveness of the first version of the Online Lifting Index (On-LI) algorithm on a common industrial logistic task. The effectiveness is compared to the standard ergonomic assessment method. The results report an average error of 3.6% compared to the NIOSH parameters used to calculate the ergonomic risk and a relative error of the Lifting Index of 2.8% when compared to observational methods.

Testing the Level of Agreement between Two Methodological Approaches of the Rapid Upper Limb Assessment (RULA) for Occupational Health Practice-An Exemplary Application in the Field of Dentistry.

BACKGROUND: The Rapid Upper Limb Assessment (RULA) is used for the risk assessment of workplace-related activities. Thus far, the paper and pen method (RULA-PP) has been predominantly used for this purpose. In the present study, this method was compared with an RULA evaluation based on kinematic data using inertial measurement units (RULA-IMU). The aim of this study was, on the one hand, to work out the differences between these two measurement methods and, on the other, to make recommendations for the future use of the respective method on the basis of the available findings. METHODS: For this purpose, 130 (dentists + dental assistants, paired as teams) subjects from the dental profession were photographed in an initial situation of dental treatment and simultaneously recorded with the IMU system (Xsens). In order to compare both methods statistically, the median value of the difference of both methods, the weighted Cohen's Kappa, and the agreement chart (mosaic plot) were applied. RESULTS: In Arm and Wrist Analysis-area A-here were differences in risk scores; here, the median difference was 1, and the agreement in the weighted Cohen's kappa test also remained between 0.07 and 0.16 (no agreement to poor agreement). In area B-Neck, Trunk, and Leg Analysis-the median difference was 0, with at least one poor agreement in the Cohen's Kappa test of 0.23-0.39. The final score has a median of 0 and a Cohen's Kappa value of 0.21-0.28. In the mosaic plot, it can be seen that RULA-IMU had a higher discriminatory power overall and more often reached a value of 7 than RULA-PP. CONCLUSION: The results indicate a systematic difference between the methods. Thus, in the RULA risk assessment, RULA-IMU is mostly one assessment point above RULA-PP. Therefore, future study results of RULA by RULA-IMU can be compared with literature results obtained by RULA-PP to further improve the risk assessment of musculoskeletal diseases.

Healthy working in inclusive companies - a study protocol of the GAIN project.

BACKGROUND: The research project GAIN (working healthy in inclusion companies) deals with the topics of health and work in inclusive companies. Due to a great need for research on (occupational) health (e.g. physical and mental health status) and workplace design in companies employing people with disabilities, this project pursues the primary goal of generating information for the development and implementation of health-preserving measures within the framework of occupational health and safety, and risk assessment, for employees with and without impairments in inclusive companies. METHODS: Within the framework of the project, the employees of three inclusive companies will be examined with the help of an interdisciplinary and triangulative approach. Using quantitative and qualitative methods, specific physical workloads and hazards will be investigated by means of baseline screening methods and measurement techniques, specifically among employees with physical disabilities and impairments. In the statistical analysis, descriptive methods will be used to record the current state, while inferential statistical methods will be used to evaluate health maintenance measures. Inferential statistics for continuous data with confidence intervals based on the statistical parametric mapping (SPM) method will also be performed. The significance level will be set at 5%. Qualitative methods will be used to analyse structures and working conditions within the companies, with particular attention to the specific construction of the relationship between work, health and disability. CONCLUSIONS: The structures in inclusion companies must be specifically designed to support and promote the understanding of work and health in relation to the idea of one's own body, its positioning in space and its performance. These characteristics are to be identified in the course of the project and bundled into best-practice recommendations. Furthermore, it is the aim of the research project to derive recommendations for action at its conclusion and to present further advice for the promotion of health in inclusive companies.

K-score: A novel scoring system to quantify fatigue-related ergonomic risk based on joint angle measurements via wearable inertial measurement units.

Work-related musculoskeletal disorders have been recognized as a global problem that affects millions of people annually. Fatigue is one of the main contributors to musculoskeletal disorders. Thus, this study investigated fatigue detection based on the measured body motion by wearable inertial measurement units. We quantified the body motion during manual handling tasks using a novel kinematic score (i.e., K-score), and the Rapid Entire Body Assessment (REBA). K-score and REBA were calculated using joint angles. Nevertheless, unlike REBA, K-score showed a significant correlation (Spearman's correlation coefficient of ρ(302) = 0.21, p < 0.05) with electromyography (EMG) signal amplitude, which was affected by muscle fatigue. Therefore, in-field measurement of K-score using inertial measurement units could detect the fatigue-induced change of body motion in long-duration manual handling tasks. Our proposed K-score can be used to assess fatigue-related ergonomic risk in long-term and real-world working conditions without the need for tedious EMG recording at workplaces.

Accuracy of a markerless motion capture system for postural ergonomic risk assessment in occupational practice.

Established methods for postural ergonomic risk assessment in occupational practice are mostly time-consuming and need to be conducted by experts. Use of technology could improve postural ergonomic risk assessments with regard to time efficiency and accuracy. A study was conducted to assess the accuracy of a markerless motion capture system (Microsoft Kinect V2) compared to a marker-based motion capture system (Vicon Bonita). Angles of different body segments were analysed. The results show major inaccuracies of the markerless motion capture system for capturing axial trunk rotation (mean angular deviation of 14.04°) indicating that potential health risks could be underestimated. Combined working postures of axial trunk rotation and arm anteversion show issues with self-occlusion. Based on the findings, it is discussed whether the detected inaccuracies for axial trunk rotation are likely to lead to overestimation or underestimation of potential health risks when conducting an ergonomic risk assessment.

Biomechanics Analysis of the Firefighters' Thorax Movement on Personal Protective Equipment during Lifting Task Using Inertial Measurement Unit Motion Capture.

Back injury is a common musculoskeletal injury reported among firefighters (FFs) due to their nature of work and personal protective equipment (PPE). The nature of the work associated with heavy lifting tasks increases FFs' risk of back injury. This study aimed to assess the biomechanics movement of FFs on personal protective equipment during a lifting task. A set of questionnaires was used to identify the prevalence of musculoskeletal pain experienced by FFs. Inertial measurement unit (IMU) motion capture was used in this study to record the body angle deviation and angular acceleration of FFs' thorax extension. The descriptive analysis was used to analyze the relationship between the FFs' age and body mass index with the FFs' thorax movement during the lifting task with PPE and without PPE. Sixty-three percent of FFs reported lower back pain during work, based on the musculoskeletal pain questionnaire. The biomechanics analysis of thorax angle deviation and angular acceleration has shown that using FFs PPE significantly causes restricted movement and limited mobility for the FFs. As regards human factors, the FFs' age influences the angle deviation while wearing PPE and FFs' BMI influences the angular acceleration without wearing PPE during the lifting activity.

Emerging Trends of Ergonomic Risk Assessment in Construction Safety Management: A Scientometric Visualization Analysis.

Ergonomic risk assessment is critical for identifying working posture hazardous to the health of construction workers. Work-related musculoskeletal disorders (WMSDs) are predominant non-fatal injuries in the construction industry owing to manual handling activities and poor working conditions. However, there is a lack of scientific synopsis aiming to better understand the emerging research focus in this field. To fill the research gap, this study performed a scientometric evaluation of the bibliometric data on ergonomic risk assessment from the Web of Science database using VOSviewer software. The purpose of this study is to analyze the co-occurrence network of keywords, co-authorship network, most active countries, and the sources of publication. The results indicate that research related to risk assessment in construction has fluctuating growth, peaking in 2020 with significant advancements in the USA, China, and Canada. WMSDs, risk factors, construction workers, and ergonomics are hot research topics in this field. Furthermore, the research gaps of previous studies and suggestions for future research have been provided to bridge the knowledge gap. We believe that this scientometric review provides useful reference points for early-stage researchers as well as beneficial in-depth information to experienced practitioners and scholars in the construction industry.

A data analytic end-to-end framework for the automated quantification of ergonomic risk factors across multiple tasks using a single wearable sensor.

Existing ergonomic risk assessment tools require monitoring of multiple risk factors. To eliminate the direct observation, we investigated the effectiveness of an end-to-end framework that works with the data from a single wearable sensor. The framework is used to identify the performed task as the major contextual risk factor, and then estimate the task duration and number of repetitions as two main indicators of task intensity. For evaluation of the framework, we recruited 37 participants to complete 10 simulated work tasks in a laboratory setting. In testing, we achieved an average accuracy of 92% for task identification, 7.3% error in estimation of task duration, and 7.1% error for counting the number of task repetitions. Moreover, we showed the utility of the framework outputs in two ergonomic tools to estimate the risk of injury. Overall, we indicated the feasibility of using data from wearable sensors to automate the ergonomic risk assessment in workplaces.

Musculoskeletal disorders and selecting an appropriate tool for ergonomic risk assessment in the dental profession.

BACKGROUND: Work-related Musculoskeletal Disorders (WMSDs) are major challenges in the occupational health services industry. Dental practitioners are regularly subjected to ergonomic risks, which can cause Musculoskeletal Disorders (MSDs) in various body regions. OBJECTIVE: This comparative cross-sectional study aimed to investigate MSDs and select a proper ergonomic risk assessment method in dental practice. METHODS: This study was conducted on 70 dentists and 70 administrative staff of dental offices (comparison group) from Shahroud, Iran. The Cornell Musculoskeletal Discomfort Questionnaire (CMDQ) and two observational ergonomic risk assessment methods, including Quick Exposure Check (QEC) and Rapid Entire Body Assessment (REBA), were utilized. RESULTS: The results suggested that the mean score of musculoskeletal discomforts was significantly higher in dentists than in the administrative personnel. Additionally, the results of multiple regression analysis technique inferred that job tenure, working hours, and age had a significant impact on total MSDs. Regular exercise was found to significantly reduce neck discomfort complaints. It was also found that QEC was more effective in predicting musculoskeletal discomforts compared to REBA. CONCLUSION: Considering the high incidence of WMSDs in dentists, various interventional measures revolving around ergonomically redesigned workstations, enhanced physical working conditions, and ergonomic training courses are suggested.

Implementation of Kinetic and Kinematic Variables in Ergonomic Risk Assessment Using Motion Capture Simulation: A Review.

Work-related musculoskeletal disorders (WMSDs) are among the most common disorders in any work sector and industry. Ergonomic risk assessment can reduce the risk of WMSDs. Motion capture that can provide accurate and real-time quantitative data has been widely used as a tool for ergonomic risk assessment. However, most ergonomic risk assessments that use motion capture still depend on the traditional ergonomic risk assessment method, focusing on qualitative data. Therefore, this article aims to provide a view on the ergonomic risk assessment and apply current motion capture technology to understand classical mechanics of physics that include velocity, acceleration, force, and momentum in ergonomic risk assessment. This review suggests that using motion capture technologies with kinetic and kinematic variables, such as velocity, acceleration, and force, can help avoid inconsistency and develop more reliable results in ergonomic risk assessment. Most studies related to the physical measurement conducted with motion capture prefer to use non-optical motion capture because it is a low-cost system and simple experimental setup. However, the present review reveals that optical motion capture can provide more accurate data.

Application of AULA Risk Assessment Tool by Comparison with Other Ergonomic Risk Assessment Tools.

Agricultural upper limb assessment (AULA), which was developed for evaluating upper limb body postures, was compared with the existing assessment tools such as rapid upper limb assessment (RULA), rapid entire body assessment (REBA), and ovako working posture analysis system (OWAS) based on the results of experts' assessments of 196 farm tasks in this study. The expert group consisted of ergonomists, industrial medicine experts, and agricultural experts. As a result of the hit rate analysis, the hit rate (average: 48.6%) of AULA was significantly higher than those of the other assessment tools (RULA: 33.3%, REBA: 30.1%, and OWAS: 34.4%). The quadratic weighted kappa analysis also showed that the kappa value (0.718) of AULA was significantly higher than those of the other assessment tools (0.599, 0.578, and 0.538 for RULA, REBA, and OWAS, respectively). Based on the results, AULA showed a better agreement with expert evaluation results than other evaluation tools. In general, other assessment tools tended to underestimate the risk of upper limb posture in this study. AULA would be an appropriate evaluation tool to assess the risk of various upper limb postures.