Biomechanical analysis of construction workers has been considerably improved with the development of wearable sensors. Information delivered by these systems is playing an important role in the evaluation of postures as well as in the reduction of work-related musculoskeletal disorders (WRMSDs). In this article, we present a novel system and data processing framework to deliver intuitive and understandable motion-related information about workers. The system uniquely integrates Inertial Measurement Unit (IMU) devices in a wireless body area network, and the data processing uses a robust state machine-based approach that assesses inadequate working postures based on standard positions defined by the International Organization for Standardization (ISO). The system and data processing framework are collectively validated through experiments carried out with college trainees conducting typical bricklaying tasks. The results illustrate the robustness of the system under demanding circumstances, and suggest its applicability in actual working environments outside the college.
- wireless sensor network
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- School of Computing, Engineering and Physical Sciences - Senior Lecturer