The Role of Machine Learning and Artificial Intelligence in Preventing and Addressing Musculoskeletal Disorders in Industrial Workforces

Abstract

Musculoskeletal disorders (MSDs) are among the most prevalent occupational health issues affecting industrial workforces, often leading to decreased productivity, increased absenteeism, and long-term disability. In recent years, the integration of machine learning (ML) and artificial intelligence (AI) has become a transformative approach to proactively prevent and manage MSDs in industrial settings. By leveraging real-time data from wearable sensors, cameras, and biomechanical monitoring systems, AI-driven solutions can identify hazardous postures, repetitive strain movements, and fatigue indicators before injuries occur. ML algorithms can analyse vast datasets to detect early warning signs, predict injury risks, and recommend ergonomic interventions tailored to individual workers. AI technologies also enhance workplace training through simulation-based learning and virtual reality environments, enabling workers to adopt safe practices more effectively. In addition, AI-powered exoskeletons and robotics are being developed to support manual labour, reducing physical strain on the musculoskeletal system. Predictive analytics models are increasingly being used by occupational health and safety professionals to design safer workspaces and optimise workload distribution. Furthermore, the integration of natural language processing (NLP) with incident reporting systems helps analyse unstructured data to uncover trends and causes of MSD-related issues, facilitating quicker response and prevention strategies. Despite the promising potential, challenges remain, including data privacy concerns, the need for large, high-quality datasets, and resistance to technological adoption in traditional industries. ML has become a powerful tool in predicting, preventing, and managing these disorders by analysing large datasets and providing actionable insights. This paper explores the ML and AI algorithms to monitor worker health in real-time, detect early signs of MSDs, and suggest corrective measures. AI and ML have demonstrated immense potential in revolutionising health care by providing advanced tools for predicting and managing health issues. AI and ML algorithms can analyse large datasets, such as medical records, genetic information, and patient demographics, to identify patterns and correlations that may not be immediately obvious to healthcare professionals. These technologies enable early detection of diseases, personalised treatment plans, and improved diagnosis accuracy. The paper discusses the challenges and future potential of AI/ML in transforming industrial health and safety management, thereby improving worker productivity and reducing health care costs.

Keywords: Artificial intelligence, Disorders, Ergonomics, Industrial workforce, Machine learning, Musculoskeletal.

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