Journal of Health and Safety at Work

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Introduction: Carpet-weaving is one of the hard and harmful jobs, which affect the health of the workforce. Based on the previously conducted research, musculoskeletal disorders in the neck, shoulder, and lower back regions are common among carpet weavers. This study conducted to investigate the muscle activity of the shoulder and lower back regions in carpet weavers during work on traditional and ergonomic workstations by surface electromyography.
Material and Methods: 18 experienced male weavers with a mean age of 38 and mean weaving experience of 11.1 years participated in this study. Each weaver took part in two trails of 120 min. Surface EMG signal recordings were done during weaving for four muscles (bilaterally in trapezius and erector spine). The RMS and MPF values were extracted from the raw EMG signal to estimate muscle activity and fatigue.
Results: The results obtained from the 5-time intervals indicated the lowered MPF in the ergonomic workstation compared to the traditional one. The result of the mean RMS in most of the recorded times was lower in the ergonomic workstation than that in the traditional one.
Conclusion: According to the results of the study, the modified workstation was well-suited for trapezius muscles, and the traditional one had an advantage for the erector spine muscles.

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Introduction: Physical fatigue is one of the major risk factors for work-related musculoskeletal disorders and has many life and financial costs. The impact of physical/biomechanical, psychosocial, environmental, and individual risk factors on muscle fatigue is undeniable. The aim of this study is to model the phenomenon of muscle fatigue (as output) in the hand in work environments based on these risk factors (as input) using soft computing methods.
Material and Methods: In the first step, associated risk factors of fatigue for 156 subjects (in three job categories) were assessed using Copenhagen environmental, psychosocial, demographic, and Man-TRA tools. Then, the Roman-Liu equation and mean square amplitude of acceleration waves were used to measure fatigue with a dynamometer and a three-axis accelerometer, respectively. Finally, according to the nature of risk factors and the phenomenon of fatigue, six categories (24 methods) of supervised machine learning (SML) based on classification were selected. MatLab software (MatLab R2017b, The Mathworks Inc., MA, U.S.A.) was used to fit the models using SML.
Results: The best-fitted models in the first and second half of the work shift were obtained using support vector machine methods. Physical risk factors had a significant impact on physical fatigue. After filtering low-priority risk factors, in the first half of the work shift, the most optimal model had an accuracy of 71.8%, precision of 72.5%, sensitivity of 76.9%, specificity of 70.8%, and discrimination power equal to 73%. In the second half of the work shift, the accuracy, precision, sensitivity, and specificity of the optimized model were 60.3%, 57.5%, 50%, and 46.9%, respectively, and the discrimination power was obtained at about 62%.
Conclusion: The fitted models for hand fatigue had acceptable performance in both sections of the shift but can still be optimized. Therefore, it is necessary for future studies to improve the quality of input and output data and include other dimensions affecting fatigue such as cognitive workload and type of work shift in future models.

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Introduction: In many occupations, users must sit for prolonged periods during their job activities. Prolonged sitting is associated with fatigue, leading to postural changes that can increase spinal loads. Despite the importance of this topic in terms of the extent of prolonged sitting and its subsequent adverse consequences, little attention has been given to this occupational activity. Hence, this study investigates changes in neck, trunk, and muscle activities and fatigue levels in prolonged sitting computer tasks.
Material and Methods: Twenty healthy subjects (gender-balanced) from the student community with at least five years of experience in computer work aged between 20-30 years were asked to randomly perform three types of computer tasks for 90 minutes (each task for 30 minutes). Electromyographic (EMG) activities of right and left cervical (ESCR and ESCL), thoracic (ESTR and ESTL), and lumbar (ESLR and ESLL) erector spine and upper trapezius (UTR and UTL) muscles were continuously recorded. Root mean square (RMS) and median frequency were extracted as EMG metrics. Subjects also rated their perceived discomfort using a Visual Analogue Scale (VAS). The effect of time, gender, and their interaction on muscle EMG activities, fatigue, and discomfort were explored.
Results: Time had a statistically significant effect on UTR, ESCR, and ESTR muscle activities. UTL and ESCR muscle activities significantly differed between male and female subjects. Further, the findings confirmed the interactive effect of time and gender on ESTR muscle activity. UTR, ESCR, ESCL, ESTL, and ESLL muscles’ fatigue index changed statistically over time.
Conclusion: The findings confirmed neck and trunk muscles’ fatigue by increasing muscular activity and reducing frequency contents over time, per the subjective rating of discomfort.

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Introduction: Prolonged sitting postures are among the risk factors for musculoskeletal disorders in occupational settings, leading to increased musculoskeletal discomfort in various body regions. This discomfort can negatively impact individuals’ health and impose high costs on society in terms of work absences, early disabilities, and reduced productivity. The purpose of this study is to investigate the effect of stretching exercises on the level of discomfort, muscle activity, and muscle fatigue in the neck and trunk region during prolonged sitting tasks.
Material and Methods: This experimental study was conducted among 20 healthy male and female participants under two test conditions: control and intervention. In the control condition, participants performed cognitive tasks (watching videos, typing, text editing, and nback cognitive test) without any intervention. In the intervention condition, participants performed stretching exercises before each task. The Visual Analogue Scale was used to assess perceived discomfort. Also, muscle fatigue was evaluated using an electromyography (EMG) device and RMS and MPF measures.
Results: Discomfort in hands and arms (p-value=0.04) and lower back (p-value=0.03) during video-watching was higher in the control condition than in the intervention. Regarding muscle activity, the activity of the right cervical erector spinae during the video-watching task was lower in the control condition than in the intervention. In the n-back cognitive test and text editing, the right lumbar erector spinae muscle activity was significantly higher in the control condition than in the stretching exercises intervention. Regarding the left cervical erector spinae, a significant difference was observed between fatigue in control and intervention conditions during the video-watching task. Also, right thoracic erector spinae fatigue in text editing was higher in the control condition than in the exercise intervention; however, for the n-back test, the level of fatigue was lower in the control condition compared to the intervention.
Conclusion: The perceived discomfort in seated computer tasks is generally lower in the exercise intervention compared to the control condition. The stretching exercises used in this study improved muscle activity and reduced fatigue in some of the trunk muscles, although the effects of the exercises depend on the type of task. Overall, muscle fatigue in two cognitive tasks, text editing and n-back, was more affected by stretching exercises than other tasks.