Ergonomic Assessment of Musculoskeletal Disorders in Occupational Settings

Work-related musculoskeletal disorders (MSDs) represent a leading cause of occupational ill health, encompassing a wide array of conditions affecting muscles, tendons, ligaments and joints. These disorders arise from repetitive tasks, awkward postures, forceful exertions and prolonged static positions. An ergonomic assessment seeks to identify and quantify biomechanical exposures, evaluate their relationship with MSD risk and guide the design of interventions. Traditional observational methods, such as checklists and posture-scoring systems, offer rapid appraisal but can lack objectivity and reproducibility. In contrast, direct measurement approaches—using motion capture systems, inertial sensors or electromyography—provide continuous quantitative data on joint angles, muscle activity and movement patterns. Recent advances in machine learning and computer vision have enabled automated posture recognition and risk estimation, reducing reliance on expert observers. Biofeedback systems can close the loop by delivering real-time cues to workers, prompting posture correction and mitigating cumulative strain. A comprehensive ergonomic programme integrates exposure assessment, risk modelling and intervention evaluation, drawing on both field-based measurements and laboratory validation. Such a holistic approach enables tailored solutions, from workstation redesign and task rotation to wearable technologies and adaptive feedback, with the ultimate aim of reducing MSD incidence and enhancing workforce well-being globally.

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Ergonomic Assessment of Musculoskeletal Disorders in Occupational Settings publication trend

The graph below shows the total number of articles in ergonomic assessment of musculoskeletal disorders in occupational settings across all publications each year (not limited to Nature Index journals).

Technical terms

Musculoskeletal disorder (MSD): A condition affecting muscles, tendons, ligaments or joints, often caused or aggravated by occupational factors.

Rapid Entire Body Assessment (REBA): An observational tool that scores whole-body posture to estimate MSD risk.

Rapid Upper Limb Assessment (RULA): A checklist-based method for evaluating postural load on the neck, trunk and upper limbs.

Inertial measurement unit (IMU): A wearable sensor combining accelerometers and gyroscopes to track body segment motion.

Biofeedback: The delivery of real-time sensory cues (e.g. vibrotactile, auditory) to prompt corrective movement.

Convolutional neural network (CNN): A class of machine-learning model designed to process visual data for pattern recognition, here applied to posture analysis.

References

1. A Natural Language Processing-Based Classification and Mode-Based Ranking of Musculoskeletal Disorder Risk Factors. Decision Analytics Journal (2024).
2. An attention-based CNN for automatic whole-body postural assessment. Expert Systems with Applications (2024).
3. Combining inertial-based ergonomic assessment with biofeedback for posture correction: A narrative review. Computers & Industrial Engineering (2024).