Impact of loading and work rest intervals on muscle micro-trauma

Smith, Tianqi Tenchi Gao; Gallagher, Sean

doi:10.1016/j.ergon.2018.03.002

Cited by 16 publications

(4 citation statements)

References 26 publications

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“…However, several investigations have been carried out regarding the connection of excessive repetitive movements and muscles-related back injuries [37]. In previous research, strong relationships between excessive repetition and back pain were observed in mining workers [37,38]. This investigation also corroborates these findings among coal mining workers.…”

Section: Discussionsupporting

confidence: 80%

“…Substantial physical fitness and adequate power is required by underground coal workers to perform their routine duties [35,36]. However, several investigations have been carried out regarding the connection of excessive repetitive movements and muscles-related back injuries [37]. In previous research, strong relationships between excessive repetition and back pain were observed in mining workers [37,38].…”

Section: Discussionmentioning

confidence: 99%

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Risk Factors Associated with the Prevalence of Upper and Lower Back Pain in Male Underground Coal Miners in Punjab, Pakistan

Ijaz

Akram

Ahmad

et al. 2020

IJERPH

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There is not enough data available on occupational health and safety issues of underground coal miners in Pakistan. This study focuses on spinal disorders in association with personal and occupational factors. The Nordic Musculoskeletal Questionnaire was used for a cross-sectional study of 260 workers of 20 mines located in four districts of Punjab, Pakistan. Regression models were created for upper back pain and lower back pain of workers whose mean age is 19.8 years (±SD 1.47). Results identify the coal cutting as the most harmful work with odds ratios (ORs) 13.06 (95% confidence interval (CI) 13.7–21.5) for lower back pain and 11.2 (95% CI 3.5–19.4) for upper back pain in participants. Those with greater years of work experience had higher odds of upper back pain (2.4, 95% CI 1.4–3.5) and lower back pain (3.3, 95% CI 1.1–4.4). Number of repetitions (mean value 25.85/minute with ±SD 9.48) are also significant for spinal disorder with ORs of 4.3 (95% CI 3.2–7.4) for lower back and 1.3 (95% CI 1.0–2.4) for upper back. Many other occupational and personal factors are positively associated with the back pain in underground coal mines workers, requiring immediate ergonomic intervention.

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Section: Discussionsupporting

confidence: 80%

Section: Discussionmentioning

confidence: 99%

Risk Factors Associated with the Prevalence of Upper and Lower Back Pain in Male Underground Coal Miners in Punjab, Pakistan

Ijaz

Akram

Ahmad

et al. 2020

IJERPH

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“…Considering the results found, except for the felling and delimbing/bucking activities, it is necessary to restructure the activities, with the adoption of scheduled breaks for worker recovery and maintenance of work pace. Breaks represent assistance to the physiological mechanism of worker compensation and recovery, allowing for the irrigation of muscles used in the activity, providing nutrition to the tissues being solicited, thus avoiding fatigue (Smith;Gallagher, 2018). Additionally, the intake of larger volumes of fluids, periodic consumption of energy foods during work, and the use of hats and shirts for protection against the elements by employees are alternatives to be implemented in the work process.…”

Section: Physical Workload (Pw)mentioning

confidence: 99%

Semi-mechanized wood harvesting: what are the ergonomic gaps in these workstations?

Menezes,

Fiedler,

Rodrigues

et al. 2024

CLCS

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Semi-mechanized wood harvesting is feasible for ventures with limited financial resources; however, it entails significant occupational risks for operators. Therefore, the objective of this study was to conduct an ergonomic analysis of semi-mechanized wood harvesting, correlating variables in an integrated manner with their intervention requirements. Hence, physical workload, hand and arm vibration, thermal comfort, noise, and illuminance were assessed during semi-mechanized cutting and manual wood extraction. Subsequently, a color-coded system was established to indicate the need for ergonomic intervention. Operators had an average age of 30 years and a Body Mass Index of 24.9. The manual extraction phase exhibited higher values for cardiovascular workload (> 40%), Maximum Heart Rate (194 bpm), and Average Partial Exposure (12.5 m. s-1) compared to the cutting phase. The average thermal comfort index recorded at the start of the work shift was 18.9 °C. Noise exposure levels during cutting surpassed regulated limits. Illuminance levels throughout the work shift averaged 22,701 lux. Consequently, it is concluded that both semi-mechanized harvesting and manual extraction require urgent ergonomic intervention in at least one variable. The use of personal protective equipment, implementation of controlled breaks, and replacement of machinery with more modern equipment are recommended.

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“…From health and safety perspectives, workers experiencing fatigue are more likely to give rise to occupational accidents or become injured while performing their jobs (Yung, 2016). They may also become dissatisfied with their jobs sooner (Saijo et al, 2008) or get involved in work-related musculoskeletal disorders (T. T. G. Smith & Gallagher, 2018). Thus, a labour-intensive order picking management system should avoid situations with high levels of fatigue in its staff by taking appropriate measures such as job rotation between different tasks (Rudin-Brown et al, 2019), scheduling work-rest (X.…”

Section: IIImentioning

confidence: 99%

Human Performance Modelling and Mission Planning Optimisation incorporating Human Performance

Asadayoobi

2024

Preprint

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Factors related to workers and tasks have a combined effect on system performance. Management tends to make effective decisions by understanding the dynamics of the workers' performance over time, affected by their time-varying learning, fatigue, and stress levels. Such managerial decisions could improve system productivity and ensure workforce safety. Despite the importance of the problem, the literature did not focus on the performance modelling or task planning framework that includes all the mentioned factors, i.e., learning, fatigue, and stress. This dissertation includes three main contributions with different performance modelling and task allocation/scheduling planning that help managers plan mission operations, characterized as uncertain, dynamic, and time-sensitive. The first contribution (Chapter 3) is a mathematical model that modifies a popular learning curve model from the literature by making its learning exponent dependent on the fatigue level. The results of applying this model to a data set (vs. the other available ones in the literature,) showed an outperformance in terms of efficiency and balance criteria.

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Impact of loading and work rest intervals on muscle micro-trauma

Cited by 16 publications

References 26 publications

Risk Factors Associated with the Prevalence of Upper and Lower Back Pain in Male Underground Coal Miners in Punjab, Pakistan

Risk Factors Associated with the Prevalence of Upper and Lower Back Pain in Male Underground Coal Miners in Punjab, Pakistan

Semi-mechanized wood harvesting: what are the ergonomic gaps in these workstations?

Human Performance Modelling and Mission Planning Optimisation incorporating Human Performance

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