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Construction workers executing manual-intensive tasks are susceptible to musculoskeletal disorders (MSDs) due to overexposure to awkward postures. Automated posture recognition and assessment based on wearable sensor output can help reduce MSDs risks through early risk-factor detection. However, extant studies mainly focus on optimizing recognition models. There is a lack of studies exploring the design of a wearable sensing system that assesses the MSDs risks based on detected postures and then provides feedback for injury prevention. This study aims at investigating the design of an effective wearable MSDs prevention system. This study first proposes the design of a wearable inertial measurement unit (IMU) sensing system, then develops the prototype for end-user evaluation. Construction workers and managers evaluated a proposed system by interacting with wearable sensors and user interfaces (UIs), followed by an evaluation survey. The results suggest that wearable sensing is a promising approach for collecting motion data with low discomfort; posture-based MSDs risk assessment has a high potential in improving workers’ safety awareness; and mobile- and cloud-based UIs can deliver the risk assessment information to end-users with ease. This research contributes to the design, development, and validation of wearable sensing-based injury prevention systems, which may be adapted to other labor-intensive occupations.

Lessons can be learned from a "Web of Causation" approach that is being used to characterize and analyse the development progress of the disease. This is a data-intensive approach. It is the contention of this paper that the required data collection and processing needs can be addressed using emerging Wearable Technologies (WT). The collected motion data can be used to improve the detection of activities that have MSD-related risks and enhance the understanding of the nature of the risk. The output can be used to perform more robust quantitative assessments of risk factors. It can also be used to develop proactive strategies that can be used to minimize the occurrence of MSD.