Design and Development of a Training System for Manual Handling Tasks in Masonry

Abstract

The construction industry is one of the industries with the highest rates of musculoskeletal disorders (MSDs). Masons are particularly susceptible to overexertion and back injuries due to the physical demands of their jobs. In the past, optoelectronic motion capture has been considered the ‘gold standard’ for motion capture in biomechanics; however, it is often not feasible for onsite data collection. Therefore, most onsite assessment tools in the industry rely on observational techniques of postures to estimate risk that cannot accurately estimate internal joint demands. Advancements in inertial measurement unit (IMU) technology have led to the development of data collection systems comparable to that of the aforementioned ‘gold standard’, thereby enabling the quantification of joint loads and forces on masons in the working environment. Previous research has reported that “technique” during manual handling tasks, such as lifting, can have a large impact on spinal loads. The comparison of expert and novice working techniques reveals that experts use distinct working strategies, which can lead to both lower joint forces and increased productivity. Furthermore, training based on expert work strategies has been shown to reduce exposures to biomechanical risks. Despite frequency of injuries, MSD risks are often under-prioritized in terms of safety training. Researchers emphasize a need to integrate ergonomics training within apprentices’ skill training classes.

This thesis focuses on the development of an enhanced training tool and program to reduce MSD risk in apprentice masons. A novel quantitative scoring system was developed to estimate MSD risk based on the peak joint loads of expert masons. This scoring system was integrated into the enhanced training tool to better assess risk based on onsite measurement of joint loads. Furthermore, the movement patterns of novice, apprentice and expert masons were analysed to determine key characteristics of inexpert and expert techniques. These characteristics were compared to high-risk postures in the literature to establish clear postural guidelines, which were then implemented into the enhanced training tool. The tool was designed to provide evidence-based recommendations to improve posture and technique based on kinematic analyses of masons’ movements. User interviews were conducted with masonry instructors to evaluate challenges, needs, and values for the training program. These insights directed the design of the accompanying educational module and overall training program. The training program and tool has the capacity to reduce biomechanical exposures of apprentice masons and increase productivity.