Search Results (66)

Work-related musculoskeletal disorders (WMSDs) are common in the agricultural industry due to repetitive tasks, like plant transplanting, which involve sustained bending, squatting, and awkward postures. This study uses wearable sensors to evaluate human biomechanics during simulated transplanting and assesses the potential of collaborative robot (cobot) assistance to reduce physical strain. Sixteen participants performed transplanting tasks under manual and cobot-assisted conditions. Kinematic and electromyographic (EMG) data were collected using Xsens motion capture and Trigno EMG systems. Cobot assistance significantly reduced the segment velocity and acceleration in key spinal regions (L5/S1, L1/T12, T1/C7), indicating lower dynamic spinal loading. It also altered muscle activation, decreasing biceps brachii use while increasing activation in stabilizing muscles such as the flexor carpi radialis, brachioradialis, and upper trapezius. Task duration decreased by 59.46%, suggesting improved efficiency. These findings highlight cobots’ potential to enhance ergonomic outcomes by encouraging controlled movements and reducing postural stress. However, the shift in muscle activation underscores the need for task-specific cobot tuning. This research supports the use of integrated IMU and EMG systems to inform cobot design and enable real-time biomechanical monitoring in labor-intensive settings. Full article

Aircraft mechanical maintenance involves high loads, repetitive movements, and awkward postures, significantly increasing the risk of work-related musculoskeletal disorders (WMSDs). Traditional static evaluation methods based on posture analysis fail to capture the complexity and dynamic nature of these tasks, limiting their applicability in maintenance settings. To address this limitation, this study introduces a novel quantitative WMSD risk assessment model that leverages 3D motion data collected through an optical motion capture system. The model evaluates dynamic human postures and employs an inverse trigonometric function algorithm to quantify the loading effects on working joints. Experimental validation was conducted through quasi-real-life scenarios to ensure the model’s reliability and applicability. The findings demonstrate that the proposed methodology provides both innovative and practical advantages, overcoming the constraints of conventional assessment techniques. Specifically, it enables precise quantification of physical task loads and enhances occupational injury risk assessments. The model is particularly valuable in physically demanding industries, such as aircraft maintenance, where accurate workload and fatigue monitoring are essential. By facilitating real-time ergonomic analysis, this approach allows managers to monitor worker health, optimize task schedules, and mitigate excessive fatigue and injury risks, ultimately improving both efficiency and workplace safety. Full article

Background and Objectives: Musculoskeletal disorders (MSDs) are a leading cause of absenteeism among healthcare workers (HCWs), impacting healthcare delivery. Pediatric HCWs face specific physical demands such as lifting and awkward postures. While absenteeism rose during the COVID-19 pandemic, its effects on pediatric MSD-related leave remain unclear. This study examined MSD-related absenteeism trends among pediatric HCWs in a Romanian hospital across the pre-pandemic (2017–2019), pandemic (2020–2021), and post-pandemic (2022–2023) periods. Materials and Methods: We conducted a retrospective observational study using records from the hospital’s occupational health database. We included all HCWs who took MSD-related leave during 2017–2023. Diagnoses included arthropathies, dorsopathies, other osteoarticular/connective tissue disorders, and acute trauma or fractures. We used chi-square tests, ANOVA, and regression models to identify trends and predictors. Results: A total of 3388 cases were analyzed. Post-pandemic absenteeism increased significantly (40.1%), especially among women (86.8%), nurses (46.7%), and workers aged ≥46 (62.7%). A seasonal shift was observed, with spring peaks (March 9.7% and May 9.9%) replacing the pre-pandemic autumn peaks (October 11.9% and November 12.8%). The regression models identified age, occupation, and diagnosis type as significant predictors of leave duration. Conclusions: MSD-related absenteeism rose post-pandemic and showed altered seasonal patterns. Occupational and demographic predictors identified through a multivariate analysis highlight the need for anticipatory, evidence-based strategies to support pediatric HCWs, enhance workforce resilience, and sustain healthcare performance. Full article

Assistive devices, such as Exoskeletons (EXOs) can enhance endurance, but could inadvertently alter body mechanics, compromise balance, and elevate fall risk, particularly under fatigue. We evaluated effects of an EXO on postural stability during standing still and sustained trunk flexion tasks as users become fatigued during intermittently performed tasks. As trunk bending is common across many occupational/routine tasks, a repetitive 45° trunk flexion task was selected. In this controlled laboratory study, symmetric and asymmetric trunk flexion tasks were performed by twelve participants with a Back-support EXO until medium-high fatigue level (7/10 on Borg CR10 scale). Outcomes showed that the device increased trunk flexion durations (~16~25%), and upper-body movement beyond intended position. EXO-use improved stability by reducing maximum deviation (~22%) and mean velocity (~57%) of Center of Pressure (COP) co-ordinates. Asymmetric trunk flexion without assistance led to highest mean velocity of COP during fatigued state, but the same remained lower (~67%) with EXO-use, even with fatigue. The device decreased variance of COP during in medial/lateral direction (~44%), but increased the same in anterior/posterior direction by the same amount. Efforts in this study contribute towards understanding implications of using assistive devices for improving human performance across diverse applications. Full article

This study examines the hazards faced by food manufacturing workers during their daily work hours and compares the exposure time between pain complainants and non-complainants. Also, this study identifies key factors influencing musculoskeletal pain. This study selected 552 food manufacturing workers and compared the exposure time to hazards between groups using t-tests. Additionally, this study conducted a logistic regression analysis to identify factors contributing to musculoskeletal pain, considering worker-related factors (gender, age, work experience, working hours per week, occupation, and industry type) and hazard exposure levels (physical, biochemical, and ergonomic hazards) as independent variables. The results of the exposure time analysis for hazards indicated that workers were most exposed to standing or repetitive movements, followed by awkward postures, handling heavy loads, and vibration. The mean comparison test of hazard exposure time between groups revealed that workers with musculoskeletal pain exhibited the greatest difference in low-temperature exposure time compared to workers without pain, followed by awkward postures and handling heavy loads. Logistic regression analysis showed that musculoskeletal pain increases with years of work experience and exposure time to handling heavy loads. In addition, females were more likely to complain of pain in the upper and lower limbs than males, and older workers were more likely to complain of back pain. Meanwhile, vibration exposure time increased the likelihood of upper limb pain, and low-temperature exposure time increased the likelihood of lower limb pain. The analysis of factors affecting musculoskeletal pain among food manufacturing workers showed that improvements are needed to focus on a universal design that considers female and older workers. Furthermore, this study’s results can help prioritize improvements and provide baseline data for developing tailored strategies and preventive measures. Full article

Awkward postures are a significant contributor to work-related musculoskeletal disorders (WRMSDs), which represent great social and economic burdens. Various posture assessment tools assess WRMSD risk but fall short in providing an elucidating risk breakdown to expedite the typical time-consuming ergonomic assessments. Quantifying, automating, but also complementing posture risk assessment become crucial. Thus, we developed a framework for a holistic posture assessment, able to, through inertial data, quantify the ergonomic risk and also qualitatively identify the posture leading to it, using Deep Learning. This innovatively enabled the generation of a report in a graphical user interface (GUI), where the ergonomic score is intuitively associated with the postures adopted, empowering workers to learn which are the riskiest postures, and helping ergonomists and managers to redesign critical work tasks. The continuous posture assessment also considered the previous postures’ impact on joint stress through a kinematic wear model. As use case, thirteen subjects replicated harvesting and bricklaying, work tasks of the two activity sectors most affected by WRMSDs, agriculture and construction, and a posture assessment was conducted. Three ergonomists evaluated this report, considering it very useful in improving ergonomic assessments’ effectiveness, expeditiousness, and ease of use, with the information easily understandable and reachable. Full article

Musculoskeletal disorders (MSDs) are associated with awkward postures, causing health problems for workers. MSDs impact physical activity levels and decrease professional work capacity. The objective of this study is to investigate the ergonomic risks in a handicraft community enterprise group using Krajood as the main raw material. The sample group consisted of craftsmen who engage in woven bags, and it was selected using inclusion and exclusion criteria. Data were collected with a general information questionnaire, a risk assessment questionnaire for musculoskeletal disorders, and the Rapid Upper Limb Assessment (RULA) worksheet. The results indicate that musculoskeletal disorders were experienced by all the workers during the past year, with pain or discomfort in all 12 body parts. Moreover, most commonly, the pains were in the shoulders, upper back, lower back, and hands/wrists on both the left and the right side. The lower back exhibited a 100% prevalence of symptoms. The risk assessment by RULA indicated that the jobs had the highest possible total risk score at 7 points (45%), which needs to improve immediately. The top three high-risk work processes were the product line hammering steps, using a sewing machine to form the product, and the weaving and forming stage. Therefore, this study provides critical information for the craftsmen and their employers to improve workers’ health and production efficiency. Full article

Background: Musculoskeletal disorders (MSD) are, to this day, considered one of the major occupational health risks, especially among healthcare workers. Poor working conditions, such as awkward postures, are associated with the development of MSD. This study aimed to evaluate the knowledge, attitudes, and practices (KAP) of nurses at a public tertiary hospital in Botswana relating to ergonomic principles. Methods: The researchers conducted a cross-sectional survey, using a self-administered questionnaire to collect the data. The researchers employed Stata v18 (StataCorp, USA) to perform descriptive and inferential statistics. The chi-square test was used to determine the association between knowledge levels and sociodemographic variables. p-values ≤ 0.05 were deemed statistically significant. Results: In total, 306 nurses participated in the study, and a response rate of 88.4% was achieved. The mean age was 35.5 (SD± 8.79) years. Most (69%) participants were female nurses. About 99.3% (95%CI: 97.7–99.9) of the participants were familiar with the concept of ergonomics. Only a small proportion of participants (26%) possessed high levels of knowledge, exhibited positive attitudes, and demonstrated good practices in relation to ergonomic principles, following the composite analysis. A statistically significant relationship was found to exist between sex and practice (p = 0.030) and between length of work and practice (p = 0.013). Conclusions: The KAP analysis indicated that most nurses had poor practices regarding essential ergonomic principles. These findings could inform policy development and enable employers to design prevention strategies, especially those aimed at preventing lower back pain (LBP). Full article

Prolonged awkward arm postures and repetitive tasks in industrial environments can easily lead to worker injuries. The occupational shoulder exoskeleton is a promising solution to reducing the incidence of work-related musculoskeletal disorders, especially in the shoulder. In general, the device has to be compatible with the human shoulder, which is one of the most complex joints, thus posing significant challenges in existing efforts to design occupational shoulder exoskeletons. The purpose of this paper is to present a comprehensive review of exoskeletons designed to support human shoulders and arms in industrial applications. Recent developments and advancements in mechanism design, actuators, and control aspects are discussed in detail. A brief overview of the evaluation (i.e., participants, task design, objective, and subjective assessment) is also reported, and the experiment protocol to assess performance is summarized. Finally, existing challenges and possible future research directions for occupational shoulder exoskeletons are provided. Full article

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. Full article

Musculoskeletal Disorders (MSDs) stand as a prominent cause of injuries in modern agriculture. Scientific research has highlighted a causal link between MSDs and awkward working postures. Several methods for the evaluation of working postures, and related risks, have been developed such as the Rapid Upper Limb Assessment (RULA). Nevertheless, these methods are generally applied with manual measurements on pictures or videos. As a consequence, their applicability could be scarce, and their effectiveness could be limited. The use of wearable sensors to collect kinetic data could facilitate the use of these methods for risk assessment. Nevertheless, the existing system may not be usable in the agricultural and vine sectors because of its cost, robustness and versatility to the various anthropometric characteristics of workers. The aim of this study was to develop a technology capable of collecting accurate data about uncomfortable postures and repetitive movements typical of vine workers. Specific objectives of the project were the development of a low-cost, robust, and wearable device, which could measure data about wrist angles and workers’ hand positions during possible viticultural operations. Furthermore, the project was meant to test its use to evaluate incongruous postures and repetitive movements of workers’ hand positions during pruning operations in vineyard. The developed sensor had 3-axis accelerometers and a gyroscope, and it could monitor the positions of the hand–wrist–forearm musculoskeletal system when moving. When such a sensor was applied to the study of a real case, such as the pruning of a vines, it permitted the evaluation of a simulated sequence of pruning and the quantification of the levels of risk induced by this type of agricultural activity. Full article

Awkward hand-arm posture and overhead work increase the risk of musculoskeletal symptoms. These adverse health effects can also be caused by additional workloads such as hand-arm vibration exposure while carrying or holding a power tool. This pilot trial investigated posture and muscle activity of 11 subjects while using an impact wrench for three working directions: upwards, forwards and downwards. Although the vibration exposure did not show notable differences in the magnitude (4.8 m/s² upwards, 4.4 m/s² forwards and 4.7 m/s² downwards), postural behavior and the muscle activity showed significantly higher workloads for working upwards compared to forwards direction. The muscle activity results for working downwards also showed elevated levels of muscle activity due to the awkward wrist posture. The results demonstrate that not only the working direction but also more importantly the arm, wrist and head posture need to be considered while investigating hand-arm vibration exposure. Full article

Nurses face not only musculoskeletal disorders but also psychological health issues. The purpose of this study is to analyze the factors influencing overall fatigue, anxiety, and depression, respectively, by comprehensively considering work characteristics, exposure to hazards, and the presence of musculoskeletal pain. This study used binary logistic regression to analyze factors influencing fatigue, anxiety, and depression, respectively. The independent variables were occupation; age; work experience; healthcare organization; working hours per week; shift type; exposure time to physical, biochemical, and ergonomic hazards; and the presence of back, upper limb, or lower limb pain. The factors influencing overall fatigue were shift type (p = 0.007), exposure to vibration (p = 0.042), awkward posture (p = 0.001), repetitive motion (p = 0.017), and presence of back (p = 0.002) or upper (p < 0.001) limb pain. The factors influencing anxiety were age (p = 0.031), hours worked per week (p = 0.006), performing patient lifting/carrying (p = 0.041), and presence of upper (p = 0.022) or lower (p = 0.039) limb pain. In addition, the factors influencing depression were found to be hours worked per week (p = 0.042), exposure to infection (p = 0.005), and the presence of lower limb pain (p = 0.011). This study found that musculoskeletal pain has a significant impact on psychological health problems, suggesting that integrated management of musculoskeletal pain and psychological health problems may be effective in addressing health problems in the nursing profession. Full article

Without physically intensive building, modern infrastructure development would be impossible. Musculoskeletal diseases (MSDs) and other occupational health issues may arise in such a demanding environment. Construction workers often develop MSDs from repeated actions, uncomfortable postures, and heavy lifting. Musculoskeletal disorders may damage muscles, bones, tendons, ligaments, etc. The effect of MSDs is well known; occupational health studies increasingly include gender-specific aspects. Despite being in the minority, the number of female construction employees is growing. However, physiological variations and occupational activities and environments may provide distinct obstacles. Thus, identifying gender-specific MSDs in construction is essential for worker safety. This research proposes a gender-specific machine learning (ML)-based musculoskeletal disorder detection framework (GS-ML-MSD2F) in the construction industry. A simple random selection procedure chose 250 female and 250 male rebar workers with at least six months of experience for the dataset. In January and June 2023, face-to-face interviews and ergonomic evaluations were undertaken. The data were analyzed using different machine learning methods, and the effectiveness of the methods was studied. The data showed that 60% of female rebar workers had MSD symptoms. The lower back and shoulders accounted for 40% of cases. Multiple machine learning methods revealed two significant factors related to musculoskeletal disorders: lengthy working hours and uncomfortable postures, and long working hours had an adjusted odds ratio of 8.5%, whereas awkward posture had an adjusted odds ratio of 42.5%. These results emphasize the relevance of working hours and posture in MSD prevention for female rebar workers in the construction sector. Full article

Laparoscopic surgeons are at high risk of experiencing musculoskeletal discomfort, which is considered the result of long-lasting static and awkward body postures. We primarily aimed to evaluate whether passive and active work breaks can reduce ratings of perceived discomfort among laparoscopic surgeons compared with no work breaks. We secondarily aimed to examine potential differences in performance and workload across work break conditions and requested the surgeons evaluate working with passive or active work breaks. Following a balanced, randomized cross-over design, laparoscopic surgeons performed three 90 min laparoscopic simulations without and with 2.5 min passive or active work breaks after 30 min work blocks on separate days. The simulation included the following tasks: a hot wire, peg transfer, pick-and-place, pick-and-tighten, pick-and-thread, and pull-and-stick tasks. Ratings of perceived discomfort (CR10 Borg Scale), performance per subtask, and perceived workload (NASA-TLX) were recorded, and the break interventions were evaluated (self-developed questionnaire). Statistical analyses were performed on the rating of perceived discomfort and a selection of the performance outcomes. Twenty-one participants (9F) were included, with a mean age of 36.6 years (SD 9.7) and an average experience in laparoscopies of 8.5 years (SD 5.6). Ratings of perceived musculoskeletal discomfort slightly increased over time from a mean level of 0.1 to 0.9 but did not statistically significantly differ between conditions (p = 0.439). Performance outcomes of the hot wire and peg transfer tasks did not statistically significantly differ between conditions. The overall evaluation by the participants was slightly in favor regarding the duration and content of active breaks and showed a 65% likelihood of implementing them on their own initiative in ≥90 min-lasting laparoscopic surgeries, compared with passive breaks. Both passive and active breaks did not statistically significantly influence ratings of perceived discomfort or perceived workload in a 90 min simulation of laparoscopic surgery, with an overall low mean level of perceived discomfort of 0.9 (SD 1.4). As work breaks do not lead to performance losses, rest breaks should be tested in real-life situations across a complete working shift, where perceived discomfort may differ from this laboratory situation. However, in this respect, it is crucial to investigate the acceptance and practicality of intraoperative work breaks in feasibility studies in advance of assessing their effectiveness in follow-up longitudinal trials. Full article