Search Results (371)

Objectives: The aim of this study was to evaluate the impact of four working heights on lumbar biomechanics during wall construction tasks, focusing on work-related musculoskeletal disorders (WMSDs). Methods: Fifteen young male participants performed simulated mortar-spreading and bricklaying tasks while actual body movements were recorded using Inertial Measurement Unit (IMU) sensors. Muscle activities of the lumbar erector spinae (ES), quadratus lumborum (QL), multifidus (MF), gluteus maximus (GM), and iliopsoas (IL) were estimated using a 3D musculoskeletal (MSK) model and measured via surface electromyography (sEMG). The analysis of variance (ANOVA) test was conducted to identify the significant differences in muscle activities across four working heights (i.e., foot, knee, waist, and shoulder). Results: Findings showed that working at foot-level height resulted in the highest muscle activity (7.6% to 40.6% increase), particularly in the ES and QL muscles, indicating an increased risk of WMSDs. The activities of the ES, MF, and GM muscles were statistically significant across both tasks and all working heights (p < 0.01). Conclusions: Both MSK and sEMG analyses indicated significantly lower muscle activities at knee and waist heights, suggesting these as the best working positions (47 cm to 107 cm) for minimizing the risk of WMSDs. Conversely, working at foot and shoulder heights was identified as a significant risk factor for WMSDs. Additionally, the similar trends observed between MSK simulations and sEMG data suggest that MSK modeling can effectively substitute for sEMG in future studies. These findings provide valuable insights into ergonomic work positioning to reduce WMSD risks among wall construction workers. Full article

Work-related musculoskeletal disorders (WMSDs) are a leading concern in industrial ergonomics, often stemming from sustained non-neutral postures and repetitive tasks. This paper presents a vision-based framework for real-time, frame-level ergonomic risk classification using a lightweight Vision Transformer (ViT). The proposed system operates directly on raw RGB images without requiring skeleton reconstruction, joint angle estimation, or image segmentation. A single ViT model simultaneously classifies eight anatomical regions, enabling efficient multi-label posture assessment. Training is supervised using a multimodal dataset acquired from synchronized RGB video and full-body inertial motion capture, with ergonomic risk labels derived from RULA scores computed on joint kinematics. The system is validated on realistic, simulated industrial tasks that include common challenges such as occlusion and posture variability. Experimental results show that the ViT model achieves state-of-the-art performance, with F1-scores exceeding 0.99 and AUC values above 0.996 across all regions. Compared to previous CNN-based system, the proposed model improves classification accuracy and generalizability while reducing complexity and enabling real-time inference on edge devices. These findings demonstrate the model’s potential for unobtrusive, scalable ergonomic risk monitoring in real-world manufacturing environments. Full article

This study analyzes the relationship between ergonomic and psychosocial risk factors and labor productivity using a bibliometric approach through a general analysis and one that includes inclusion criteria such as English language, open access, and primary research publications to identify only those articles that explicitly address the relationship between ergonomic and psychosocial risk factors and labor productivity. It is recognized that both physical and psychosocial conditions of the work environment directly influence workers’ health and organizational performance. For this purpose, a bibliometric review was conducted in academic databases, including Scopus, Web of Science, ScienceDirect, and Taylor & Francis, resulting in the selection of 4794 relevant articles for general analysis. Additionally, 116 relevant articles were selected based on the inclusion criteria. Tools and methodologies, such as Rayyan, Excel, VOSviewer 1.6.20, and PRISMA, were used to classify the studies and identify trends, collaboration networks, and geographical distribution. The results reveal a sustained growth in scientific production, with clusters on occupational safety and health, work environment factors, and the characteristics of the population, approach, and methodologies used in the studies. Likewise, Procedia Manufacturing, International Journal of Occupational Safety and Ergonomics, and Ergonomics stand out as the main sources of publication, while countries such as Sweden, Poland, and the United States lead the scientific production in this field. In addition, the network of co-occurrence of keywords evidences a comprehensive approach that articulates physical or ergonomic and psychosocial risk factors with organizational performance, while the network of authors shows consolidated collaborations and studies focused on analyzing the relationship between physical demands and musculoskeletal disorders from advanced ergonomic approaches. Full article

Background: Musculoskeletal disorders significantly affect healthcare professionals, particularly physiotherapists, due to the physical demands of their work. The link between physical ailments and psychological distress is especially prominent in clinical settings. Objectives: To assess the prevalence of work-related low back pain (LBP), stress, anxiety, and depression among physiotherapists in Saudi Arabia, and to identify associated local risk factors. Methods: A cross-sectional study using convenience sampling included 710 licensed physiotherapists across Saudi Arabia. Participants completed an online survey containing demographic data and the validated measures, including the Visual Analog Scale (VAS) for pain, the Oswestry Disability Index (ODI), and the Depression, Anxiety, and Stress Scale-21 (DASS-21) for psychological distress. Data were analysed using descriptive statistics, chi-square tests, correlation, and regression analyses. Results: Of 710 responses, 697 were valid; 378 physiotherapists reported work-related LBP. The mean pain intensity was 4.6 (SD = 1.6), with 54.2% experiencing moderate to severe disability. Mental health results showed 49.7% had depressive symptoms and 33.9% experienced some level of anxiety. Significant correlations were observed between disability and psychological distress (anxiety: r = 0.382; depression: r = 0.375; stress: r = 0.406; all p < 0.001). Regression analyses indicated psychological distress significantly predicted disability, with R² values ranging from 0.125 to 0.248, being higher among inpatient physiotherapists. Conclusions: This study reveals a high prevalence of LBP and psychological distress among Saudi physiotherapists, with stress being the strongest predictor of LBP severity. Integrated ergonomic and mental health interventions, including workplace wellness programs and psychological support, are recommended to reduce risks and promote a healthier, more sustainable physiotherapy workforce. Full article

Work-related musculoskeletal disorders (WMSDs) are among the most prevalent occupational health issues, particularly affecting public transport drivers due to prolonged sitting, constrained postures, and poorly adaptable cabins. This study addresses the ergonomic risks associated with tram driving, aiming to evaluate biomechanical load and postural stress in relation to drivers’ anthropometric characteristics. A combined methodological approach was applied, integrating two standardized observational tools—RULA and REBA—with anthropometric modeling based on three representatives European morphotypes (SmallW, MidM, and TallM). ErgoFellow 3.0 software was used for digital posture evaluation, and lumbar moments at the L4/L5 vertebral level were calculated to estimate lumbar loading. The analysis was simulation-based, using digital human models, and no real subjects were involved. The results revealed uniform REBA (Rapid Entire Body Assessment) and RULA (Rapid Upper Limb Assessment) scores of 6 across all morphotypes, indicating moderate to high risk and a need for ergonomic intervention. Lumbar moments ranged from 51.35 Nm (SmallW) to 101.67 Nm (TallM), with the tallest model slightly exceeding the recommended ergonomic thresholds. These findings highlight a systemic mismatch between cabin design and user variability. In conclusion, ergonomic improvements such as adjustable seating, better control layout, and driver education are essential to reduce the risk of WMSDs. The study proposes a replicable methodology combining anthropometric, observational, and biomechanical tools for evaluating and improving transport workstation design. Full article

In recent decades, information technology has grown. Computers have become a daily activity, facilitating access to information, faster communication and faster work. If used responsibly, it has many advantages. Objectives: To explore the potential link between prolonged use of computer input devices—such as keyboards and mice—and the development of compressive neuropathies, including carpal tunnel syndrome (CTS) and cubital tunnel syndrome (CuTS), in individuals whose daily routines are heavily reliant on computer-based activities. Methods: A comprehensive review of the literature was undertaken to assess the correlation between the use of computer input devices and the incidence of compressive neuropathies in the upper limbs, with particular attention to repetitive strain, ergonomic posture deviations, and personal risk factors. Results: Current evidence indicates a potential association between prolonged computer use and the development of upper limb compressive neuropathies; however, a definitive consensus within the scientific literature remains elusive. Repetitive movements and non-neutral postures appear to be significant contributing factors, particularly among individuals with predisposing risk factors. Despite increasing awareness of this issue, standardized, evidence-based clinical guidelines for the evaluation and management of work-related nerve disorders remain lacking. Conclusions: While the relationship between computer use and compressive neuropathies remains debated, healthcare professionals should be aware of the risks, particularly in individuals exposed to repetitive strain and ergonomic stress. Further research and the development of clinical guidelines are needed to better understand and manage these work-related conditions. Full article

Ergonomic risk classification during manual lifting tasks is crucial for the prevention of workplace injuries. This study addresses the challenge of classifying lifting task risk levels (low, medium, and high risk, labeled as 0, 1, and 2) using multi-modal time-series data comprising raw facial landmarks and bio-signals (electrocardiography [ECG] and electrodermal activity [EDA]). Classifying such data presents inherent challenges due to multi-source information, temporal dynamics, and class imbalance. To overcome these challenges, this paper proposes a Multi-Adaptive Functional Neural Network (Multi-AdaFNN), a novel method that integrates functional data analysis with deep learning techniques. The proposed model introduces a novel adaptive basis layer composed of micro-networks tailored to each individual time-series feature, enabling end-to-end learning of discriminative temporal patterns directly from raw data. The Multi-AdaFNN approach was evaluated across five distinct dataset configurations: (1) facial landmarks only, (2) bio-signals only, (3) full fusion of all available features, (4) a reduced-dimensionality set of 12 selected facial landmark trajectories, and (5) the same reduced set combined with bio-signals. Performance was rigorously assessed using 100 independent stratified splits (70% training and 30% testing) and optimized via a weighted cross-entropy loss function to manage class imbalance effectively. The results demonstrated that the integrated approach, fusing facial landmarks and bio-signals, achieved the highest classification accuracy and robustness. Furthermore, the adaptive basis functions revealed specific phases within lifting tasks critical for risk prediction. These findings underscore the efficacy and transparency of the Multi-AdaFNN framework for multi-modal ergonomic risk assessment, highlighting its potential for real-time monitoring and proactive injury prevention in industrial environments. Full article

In recent years, the application of ergonomics to workplace safety monitoring has gained increasing interest from companies and public institutions, allowing for the evaluation of the potential impact that dangerous situations may have on workers during their routine activities. This study presents a method for real-time monitoring of human physiological and motor responses to simulated workplace hazards during virtual reality safety training. The setup allows for precise measurements of both physiological and postural parameters during simulated scenarios. Moreover, a representative case study involving the sudden arrival of a forklift in a warehouse is presented. Five healthy participants were exposed to this scenario, with changes in heart rate variability and trunk posture being captured. The results demonstrate the effectiveness of sensor-based monitoring in detecting stress responses and postural adaptations to hazardous stimuli. This approach provides a basis for understanding human responses in simulated hazardous environments and may help to optimize safety training aimed at increasing workers’ risk perception and improving overall workplace safety. Although based on a small sample, the findings provide preliminary insights into the feasibility of sensor-based monitoring during VR safety training. Full article

Human Factors and Ergonomics (HF/E) play an essential role in the development of sustainable manufacturing systems. By prioritizing worker wellbeing through the mitigation of occupational hazards and the enhancement of workplace health, HF/E contributes significantly to improved system performance. In accordance with the principles of Industry 5.0 and Society 5.0, which emphasize human-centered design and wellbeing, organizations that effectively integrate HF/E principles can achieve a competitive advantage on the market. Based on a globally recognized ranking system utilized by investors in making informed decisions, the study focuses on manufacturing companies ranked by their occupational health and safety (OHS) scores, a key criterion for assessing the social dimension of company performance. This research aims to identify and analyze top-ranked companies that explicitly highlight HF/E-related benefits within their public documents and sustainability reports. The paper investigates aspects related to the integration of AI and digital technologies to enhance safety and health in manufacturing systems, with a specific focus on human presence detection in hazardous zones, improvements in machines and equipment design, occupational risk assessments, and initiatives for enhancing worker wellbeing. The findings are expected to provide compelling evidence for companies to prioritize HF/E consideration during the design and redesign phases of sustainable manufacturing systems. The paper provides significant value to non-indexed companies by offering a dual approach for improving OHS performance, based on an empirical evaluation assessment method and practical strategies for effective OHS implementation in different manufacturing industries and countries. Full article

Manual wheelchair users are at high risk of upper limb overuse injuries due to repetitive propulsion mechanics. To address this, we developed a novel detachable push–pull dual-propulsion device that enables both forward and backward propulsion, aiming to reduce shoulder strain and promote balanced muscle engagement. This study presents a protocol to evaluate the device’s biomechanical impact and ergonomic effects, focusing on objective, quantitative analysis using a repeated-measures within-subject design. Thirty participants with spinal cord injury will perform standardized propulsion trials under two conditions: push and pull. Motion capture and surface electromyography (EMG) will assess upper limb kinematics and muscle activation. Each propulsion mode will be repeated over a 10-m track, and maximum voluntary contraction (MVC) data will be collected for EMG normalization. The protocol aims to provide objective evidence on the propulsion efficiency, muscle distribution, and ergonomic safety of the device. Findings will inform future assistive technology development and rehabilitation guidelines for manual wheelchair users. Full article

A product development process establishes requirements not just for the new product’s quality and performance, but also for its manufacturing process, to guarantee that the item is manufactured with minimal impact. This is because, if an issue is discovered after the product has been released, the implications go beyond the expensive cost of the repair; the physical ergonomics problem can affect the worker’s comfort, productivity, and product quality. Virtual reality and digital human modeling are often employed in Industry 4.0 to evaluate ergonomics, but they are rarely used to examine physical ergonomics throughout the product development phases. Our study presents design guidelines to combine virtual reality and digital human modeling to anticipate the physical ergonomics evaluations of the assembly process while the product is still in development. Based on physical observations of body-posture angles and total effort classification, our proof of concept performed comparably to conventional methods. We also observed comparable results when we analyzed attributive factors such as hand clearance and strength. In contrast, our proof of concept has been shown to be limited for occupations involving extra ergonomic physical risk factors, such as touch perception, temperature fluctuations, or size changes. Full article

Background: Lower back pain (LBP) is defined as any recurring lumbar pain between the rib cage and the buttocks present at the time of the study. This study investigated the point prevalence, associated risk factors, and degree of disability of LBP among medical students at Alfaisal University, Riyadh, Saudi Arabia. Methods: A cross-sectional study evaluated 331 medical students using the Oswestry Disability Index (ODI; used to gauge LBP degree of disability) supplemented with demographic and lifestyle questions. The respondents were mostly first-year, female, and between the ages of 17 and 21 years. Results: Analysis uncovered that Female students, extended durations of phone usage, and those who did not exercise were more likely to experience LBP (p < 0.001; p = 0.042; p = 0.001). A higher degree of disability was associated with participants older than 21 years, who used their devices for extended periods, and who slept less (β = 0.170, p = 0.006). While most students experienced LBP (73.4%), the ODI revealed that the majority were not deemed disabled (56.9%). Factors associated with LBP prevalence were not necessarily associated with a higher degree of disability per the ODI. Conclusions: LBP is highly prevalent among medical students, with several associated risk factors. Female medical students remain a significant at-risk group. These findings highlight the need for a broader intervention against LBP, such as ergonomic and lifestyle improvements that consider a multitude of factors. Full article

(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. Full article

Advanced technology systems and neuroelectronics for crash risk assessment and anticipation may be a promising field for advancing responsible automated driving on urban roads. In principle, there are prospects of an artificially intelligent (AI)-powered automated vehicle (AV) system that tracks the degree of perceived crash risk (as either low, mid, or high) and perceived safety. As a result, communicating (verbally or nonverbally) this information to the user based on human factor aspects should be reflected. As humans and vehicle automation systems are prone to error, we need to design advanced information and communication technologies that monitor risks and act as a mediator when necessary. One possible approach is towards designing a crash risk classification and management system. This would be through responsible AI that monitors the user’s mental states associated with risk-taking behaviour and communicates this information to the user, in conjunction with the driving environment and AV states. This concept is based on a literature review and industry experts’ perspectives on designing advanced technology systems that support users in preventing crash risk encounters due to long-term effects. Equally, learning strategies for responsible automated driving on urban roads were designed. In a sense, this paper offers the reader a meticulous discussion on conceptualising a safety-inspired ‘ergonomically responsible AI’ concept in the form of an intelligent risk assessment system (iRisk) and an AI-powered Risk information Human–Machine Interface (AI rHMI) as a useful concept for responsible automated driving and safe human–automation interaction. Full article

Introduction: Musculoskeletal disorders (MSDs) are a significant occupational health concern worldwide, particularly among healthcare professionals such as laboratory technicians. MSDs lead to chronic pain, decreased productivity, and reduced quality of life. This study aimed to investigate the prevalence of MSDs and associated ergonomics risk factors among Saudi clinical laboratory technicians. Methodology: This cross-sectional study was conducted on 167 clinical laboratory technicians in Taif city, Saudi Arabia. Data were collected through an online self-administered questionnaire, distributed via Google Forms. The questionnaire collected demographics information, assessed the prevalence of musculoskeletal pain using the Nordic Musculoskeletal Questionnaire (NMQ), and evaluated ergonomics risk factors using the Dutch Musculoskeletal Questionnaire (DMQ). Results: In total, 77.3% of the sample exhibited musculoskeletal issues in the last 12 months, with lower back (52.1%), neck (48.5%), and shoulders (40.7%) being the most frequent muscular complaints among laboratory technicians. Experience and nationality showed significant associations with MSDs (p ≤ 0.05). Lower back and neck complaints were commonly recorded with multiple laboratory tasks, including sustained sitting and standing and repetitive movement, whereas lower back and shoulder pain were notably prevalent with pipetting work. Conclusions: Work-related musculoskeletal disorders were highly apparent in laboratory practice. Periodic ergonomic training is mandated among laboratory personnel to limit occupational disability. Full article