Lightweight Vision Transformer for Frame-Level Ergonomic Posture Classification in Industrial Workflows.

Background: Work-related musculoskeletal disorders (WRMSDs) are prevalent among physical therapy professionals due to the physical demands of patient handling, repetitive tasks, and prolonged static postures. Despite international evidence documenting high WRMSD rates, data from Pakistan remain scarce, limiting targeted ergonomic interventions. Objective: To determine the prevalence of WRMSDs and identify ergonomic hazards among physical therapy professionals in Rawalpindi and Islamabad, Pakistan, and to compare prevalence by career stage. Methods: A descriptive cross-sectional study was conducted between September 2020 and February 2021 among 500 licensed physical therapists aged 25–60 years with at least six months of practice. Participants were recruited through convenience sampling from public and private healthcare facilities. Ergonomic risks were assessed using the Quick Exposure Check (QEC) and WRMSDs were identified via the body mapping tool. Demographic, occupational, and exposure data were analysed using descriptive statistics, chi-square tests, and independent t-tests, with p<0.05 considered significant. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. Results: Participants had a mean age of 30.0 ± 10.86 years, mean experience of 3.54 ± 1.96 years, and 71.4% were female. The prevalence of WRMSDs was 72.4%, with neck (56.2%), lower back (49.0%), and upper back (45.6%) most affected. Mean QEC score was 45.72 ± 5.53, with 68.0% requiring investigation or intervention. Early-career therapists (≤5 years’ experience) had a significantly higher one-year WRMSD incidence than experienced therapists (>5 years) (34.0% vs. 24.0%; OR 1.61, 95% CI 1.02–2.54; p=0.040). Excessive hand force was reported by 94.6% of participants, and 12.6% frequently lifted or moved heavy patients or objects. Conclusion: WRMSDs are highly prevalent among physical therapy professionals in Pakistan, with early-career clinicians at increased risk. Targeted ergonomic education, mentorship, and workplace modifications are needed to reduce injury risk and promote career longevity.

Mining is often associated with the risk of Work-Related Musculoskeletal Disorders (WRMSDs). Despite being a coal-rich country, Pakistan’s mining sector stays behind in terms of occupational health and safety. Only a few research studies have been conducted on ergonomics in the mining industry. The current study aimed at evaluating workstations for WRMSDs and ergonomic factors among coal mine workers. Survey data were gathered from a total of 103 workers using a structured questionnaire. Information on the incidence of musculoskeletal disorders was obtained using the Standardized Nordic Questionnaire. The questions about ergonomics awareness, workstation, environment, demands, and risks were based on the available literature studies. The association between the incidence of WRMSDs and age was explored using chi-square analysis. The results showed a high rate of uneducated workers with a lack of ergonomics awareness. Back, shoulders, and legs were the most vulnerable body areas to WRMSDs. A significant association between workers’ age and WRMSDs was found. The workers’ opinion towards workstation was at a very low level. The current work conditions were found to have risks of potential hazards and economic losses. Ergonomic interventions are suggested to be developed and implemented to improve workplace conditions.

Introduction: Musculoskeletal disorders (MSDs) are injuries or disorders affecting muscles, nerves, tendons, joints, cartilage, and spinal discs. Work-related musculoskeletal disorders (WMSDs) are significantly influenced by the work environment and performance, often exacerbated by job conditions. WMSDs affect various body parts associated with movement, including upper and lower limbs and the back, caused or aggravated by work activities. Factors like joint positions, repetitive motions, and high static muscle loads contribute to these issues. Grocery store workers, particularly those involved in manual labor and repetitive tasks, have a high incidence of WMSDs, with prevalent complaints of lower back, knee, and upper extremity pain. Materials & Methods: This cross-sectional study involved 96 participants aged 18-50, working a minimum of 5 hours daily with at least one year of experience in material handling. Exclusions were made for those receiving treatment for musculoskeletal diseases, with deformities, degenerative conditions, unwilling participants, or cash register workers. Data collection included the Nordic Musculoskeletal Questionnaire (NMQ) in Hindi and photographs of participants in their most attended work postures. The Rapid Entire Body Assessment (REBA) was used to evaluate ergonomic risks. Results: The study found a high prevalence of musculoskeletal discomfort among grocery store workers, particularly in the lower back, knees, neck, and ankles. The number of working years which shows that 50% of the population lies in the range of 1-5 years followed by 30.02% in 6-10 Years. The number of working hours which shows that 42.7% of subjects work for 6-7 hours and 20.83% for 9-10 hours. The REBA scores indicated that 42.7% of participants were at high risk (scores 8-10), 38.54% at medium risk (scores 4-7), and 14.5% at very high risk (scores 11-15), necessitating immediate ergonomic interventions. Conclusion: Grocery store workers are at a high risk of developing WMSDs, with significant discomfort in the lower back, knees, ankles, and neck. Limitations include lack of segregation among working patterns, and not considering rest intervals or BMI. Future research should focus on intervention studies, segregating working patterns, and advising preventive measures to mitigate these risks. Keywords: Work-related musculoskeletal disorders, Ergonomic risk assessment, Grocery store workers, Musculoskeletal disorder prevalence, Nordic Musculoskeletal Questionnaire, REBA (Rapid Entire Body Assessment)

(1) Background: Work-related musculoskeletal disorders (WMSDs) are a major occupational health concern in the construction industry owing to the physically demanding tasks and poor ergonomic conditions present. Limited data exist on the prevalence of WMSDs and their ergonomic determinants among construction workers in India. This study investigated the prevalence of work-related musculoskeletal disorders (WMSDs) and the associated ergonomic risk factors among construction workers in India. (2) Methods: This cross-sectional study was conducted among 250 construction workers in India. Data on musculoskeletal disorders were collected using the Nordic Musculoskeletal Questionnaire (NMQ), and ergonomic risk was assessed using the Rapid Entire Body Assessment (REBA) tool. Logistic regression was used to identify factors associated with WMSDs, and Spearman’s correlation was used to assess the relationship between the REBA scores and the number of affected body regions. (3) Results: The prevalence of WMSDs was 60.4%. The most affected regions were the lower back (48%), knees (45%), shoulders (40%), and the neck (30%). The REBA scores indicated that 60% of the workers were at high or very high ergonomic risk and 30% at medium risk. Workers in the high/very high-risk category had significantly higher odds of developing WMSDs (OR = 4.5, 95% CI: 1.8–11.2, p = 0.001). Age above 40 years was also significantly associated with WMSDs (OR = 3.5, 95% CI: 1.2–10.2, p = 0.02). (4) Conclusions: This study demonstrated a high prevalence of WMSDs among Indian construction workers and established a clear association with poor ergonomic conditions. Targeted ergonomic interventions, including posture improvement, tool redesign, and safety training, are essential for reducing the risk of WMSDs in this population.

HighlightsWhat are the main findings?Markerless camera-based motion capture systems (MCBSs) for ergonomic risk assessment in industrial settings offer substantial accuracy and reliability.Markerless systems (MCBSs) provide a feasible, scalable alternative to traditional ergonomic methods.What is the implication of the main finding?Markerless systems (MCBSs) have strong potential for practical, real-world applications and automation.Markerless systems (MCBS) support Industry 5.0 goals in occupational risk prevention.Ergonomic risk assessment is crucial for preventing work-related musculoskeletal disorders (WMSDs), which often arise from repetitive tasks, prolonged sitting, and load handling, leading to absenteeism and increased healthcare costs. Biomechanical risk assessment, such as RULA/REBA, is increasingly being enhanced by camera-based motion capture systems, either marker-based (MBSs) or markerless systems (MCBSs). This systematic review compared MBSs and MCBSs regarding accuracy, validity, and reliability for industrial ergonomic risk analysis. A comprehensive search of PubMed, WoS, ScienceDirect, IEEE Xplore, and PEDro (31 May 2025) identified 898 records; after screening with PICO-based eligibility criteria, 20 quantitative studies were included. Methodological quality was assessed with the COSMIN Risk of Bias tool, synthesized using PRISMA 2020, and graded with EBRO criteria. MBSs showed the highest precision (0.5–1.5 mm error) and reliability (ICC > 0.90) but were limited by cost and laboratory constraints. MCBSs demonstrated moderate-to-high accuracy (5–20 mm error; mean joint-angle error: 2.31° ± 4.00°) and good reliability (ICC > 0.80), with greater practicality in field settings. Several studies reported strong validity for RULA/REBA prediction (accuracy up to 89%, κ = 0.71). In conclusion, MCBSs provide a feasible, scalable alternative to traditional ergonomic assessment, combining reliability with usability and supporting integration into occupational risk prevention.

BackgroundA substantial body of research has documented a high prevalence of neck, shoulder, wrist, and back pain among sonography users. However, the specific postures that contribute to these complaints have scarcely been systematically investigated, to date. This proposed study offers a novel method to record users’ body posture during sonography examinations kinematically and to survey the complaints of sonography users in various specialities. Using this data, well-founded ergonomic recommendations for the prevention of work-related musculoskeletal disorders (WRMSDs) will be developed.MethodsA minimum of 38 study participants across two groups (19 beginners; 19 experienced) per speciality (head and neck sonography, abdominal sonography, cardiac sonography, musculoskeletal sonography, and obstetric/gynaecological sonography) will be assessed using kinematic whole-body (including finger movements) analysis based on inertial motion capture. Subsequently, ergonomic risk will be determined by integrating the quantitative data into the Rapid Upper Limb Assessment (RULA). Moreover, a questionnaire on musculoskeletal complaints and ergonomics in sonography will be used in certified sonography courses, ultrasound-based centres, and university teaching. The primary outcome measures of this proposed study include typical tasks based on joint angles and assessment using RULA scores. In addition, the prevalence of WRMSDs will be recorded.The Mann-Whitney-U test will be employed to calculate the differences between the two study groups in each speciality. In addition, inferential statistical comparisons will be conducted for continuous data using confidence bands; the statistical parametric mapping method will be employed here. The significance level will be set at p = 0.05.ConclusionsThis article proposes a study (or series of studies) to describe the continuous ergonomic risk for typical tasks across different disciplines of sonography and to identify increased ergonomic risks. Such studies offer significant potential for preventing WRMSDs. The insights gained could inform the future design of prevention programmes and the development of recommendations for action, as well as teaching sonography users an ergonomically optimised way of working. The results could suggest that ergonomics training is incorporated more thoroughly into ultrasound training curricula to minimise health risks for future users.

Ergonomic risk assessment methods for work-related musculoskeletal disorders among healthcare workers: A systematic review.

This study applies a digital human modelling–driven approach to ergonomic risk assessment, workstation redesign, and usability evaluation in a manufacturing assembly line. Work-related musculoskeletal disorders (WMSDs) remain a major occupational health concern in manufacturing environments, particularly in standing manual assembly workstations. Inadequate workstation design often leads to awkward postures, prolonged static loading, and repetitive movements, contributing to discomfort, fatigue, and reduced productivity. This study evaluates ergonomic risks associated with working postures at a manual insert workstation in an air-conditioner manufacturing company using Digital Human Modelling (DHM) integrated with Rapid Upper Limb Assessment (RULA) and Rapid Entire Body Assessment (REBA). A cross-sectional assessment involving ten female operators was conducted using observational analysis, anthropometric measurement, and the Cornell Musculoskeletal Discomfort Questionnaire (CMDQ). Existing work postures were simulated in CATIA to quantify ergonomic risk levels. Based on identified risk factors, an ergonomically improved workstation was designed and re-evaluated using RULA. Results showed that the existing workstation posed medium to very high ergonomic risks (RULA scores up to 7; REBA scores up to 11), particularly affecting the neck, lower back, and lower limbs. The redesigned workstation reduced the RULA score to 3, indicating a substantial improvement in postural risk. The findings demonstrate the effectiveness of DHM-supported ergonomic interventions in reducing WMSDs risk and highlight the importance of user-centered workstation design in manufacturing settings.

The Internet of Things (IoT) is an essential component of the digital age, particularly in ensuring reliable and efficient operations as well as the timely and precise recognition of anomalies within IoT systems. However, anomaly detection in time-series data—especially data collected by edge devices—poses several challenges, including concerns over data privacy and communication overhead. To address these issues, this research proposes a novel deep learning (DL)-based anomaly detection model capable of being trained in real-time on edge devices within an IoT environment. The framework ensures user privacy by enabling distributed edge devices to cooperatively train an anomaly recognition system. This study introduces a new, Intelligent Shark Smell Tuned Deep Isolation Forest (ISS-DIF), which effectively detects anomalies and identifies outliers in industrial IoT sensor data with high accuracy. The hybrid model isolates anomalies rather than profiling normal data, making it particularly suitable for identifying rare anomalies within large datasets. Industrial data are collected from real-world manufacturing environments using IoT edge devices. Following data collection, median filtering is applied to reduce noise, and min-max scaling is employed for data normalization. The ISS component allows for fine-tuning the hyperparameters of the Deep Isolation Forest (DIF) to optimize detection performance. The DIF model is tailored to enhance anomaly detection capabilities in sensor data from industrial IoT applications. For validation, 80% of the dataset was used for training, while the remaining 20% served as the test set. The results demonstrate that the proposed ISS-DIF framework achieved superior training accuracy of 99.30%, with precision of 97.89%, recall of 98.76%, and an F1-score of 97.21%, outperforming the testing metrics. This approach integrates real-time anomaly detection with the processing capabilities of edge devices, thereby improving IoT data analytics and providing a scalable, efficient solution that preserves privacy in irregularity recognition within IoT environments.

Background The central sterile supply department (CSSD) is wrongly seen as a place in the hospital environment that does not require skills and physical effort, being commonly a hospital sector for the relocation of functionally-readapted professionals. However, CSSD is a work environment that demands professional experience and presents itself as a sector that does not have a healthy work environment. This study aims to evaluate the frequency of comorbidities and functionally-readapted people among nursing professionals allocated to a CSSD and, also, to seek the perception of these professionals about the ergonomic risks and the degree of difficulty to perform activities within a CSSD. Methods This is a cross-sectional study that analyzed the opinions of nursing professionals who work in the CSSD of public hospitals in Rio de Janeiro, Brazil. Nurses, nursing technicians and nursing assistants aged ≥18 years were included. Results Seventy-two nursing professionals were consecutively evaluated. It was observed that 43 of them (59.7%) had never worked in a CSSD. The most prevalent comorbidity in the present study was chronic rhinosinusitis, observed in more than half of the sample, although it is interesting to note the high frequency of participants with work-related musculoskeletal disorders (WMSD) and repetitive strain injuries (RSI). There is a relationship between previous work in a CSSD and the ability to identify surgical tweezers by visual recognition (p=0.031). There is a relationship between the time the participant had previously worked in the hospital and the skill regarding the information contained in the conference folders for preparing the tray surgical procedures (τb = −0.34, p=0.001). Conclusion Almost a third of nursing professionals working in a CSSD are rehabilitated, with a high prevalence of WMSD and RSI. The commitment of managers to an internal health policy aimed at workers is necessary for health promotion.

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.

ObjectiveThe aim of this study is to determine the risk factors related to upper extremities work-related musculoskeletal disorders (WRMSDs) in cameramen.MethodsA questionnaire survey was performed on 166 cameramen in a broadcasting station. The questionnaire consisted of questions on the general characteristics, the health behavior, work type and duration, physical burden, ergonomic posture, and musculoskeletal symptoms. Definition of musculoskeletal disorders was based on NIOSH criteria.ResultsThe positive rate of WRMSDs symptoms by parts of the body was turned out to be the highest in the shoulder (14.5%) and the lowest in arm and elbow (6%). Logistic regression analysis revealed that symptoms in the shoulders increased with BMI (OR = 3.62, 95% CI = 1.03-12.71), physical burden (OR = 9.29, 95% CI = 1.72-61.78 in the very hard group) and ergonomic factors (OR = 4.50, 95% CI = 1.03-19.68). Ergonomic factors were only related to the symptoms of hand and wrist (OR = 10.21, 95% CI = 1.02-102.20). WRMSDs symptoms, in the whole upper extremities, were higher in the 50 or older age group (OR = 5.86, 95% CI = 1.03-33.26), higher BMI group (OR = 3.26, 95% CI = 1.28-13.53), non-exercise group (OR = 2.37, 95% CI = 1.24-12.59), high physical burden group (OR = 7.6, 95% CI = 1.34-52.74), and high grade ergonomic risk group (OR = 4.82, 95% CI = 1.29-16.06).ConclusionThe most serious musculoskeletal disorders of male cameramen were shoulder pain. Ergonomic factors and physical burden were the most significant factors affecting WRMSDs in cameramen in this study. Cameramen should be educated to be able to improve the ergonomic occupational environment and to set up preventive measures against the risk factors during work.

Work-related musculoskeletal disorders (WMSDs) represent approximately one third of workers' compensation costs in US private industry, yet estimates of acceptable exposure levels for forceful and repetitive tasks are imprecise, in part, due to lack of measures of tissue injury in humans. In this review, the authors discuss the scope of upper-extremity WMSDs, the relationship between repetition rate and forcefulness of reaching tasks and WMSDs, cellular responses to injury in vivo and in vitro, and animal injury models of repetitive, forceful tasks. The authors describe a model using albino rats and present evidence related to tissue injury and inflammation due to a highly repetitive reaching task. A conceptual schematic for WMSD development and suggestions for further research are presented. Animal models can enhance our ability to predict risk and to manage WMSDs in humans because such models permit the direct observation of exposed tissues as well as motor behavior.

OCCUPATIONAL APPLICATIONS Based on a 45-year career as a practitioner in industrial ergonomics, I offer in this paper a personal memoir on how ergonomics came to the shop floor in North America, involving ordinary workers in an early effort to prevent what was at the time an unknown problem — work-related Musculoskeletal Disorders. The actions included the beginning of a low-tech, practical improvement process that is still effective today. In total, the experience can provide encouragement to everybody to be confident in their ability when trying new endeavors and to remember that small initial steps can eventually lead to major change.

Postural reconfiguration and cycle-to-cycle variability in patients with work-related musculoskeletal disorders compared to healthy controls and in relation to pain emerging during a repetitive movement task