High prevalence of musculoskeletal disorders among construction workers pose challenges to the productivity and occupational health of the construction industry. To mitigate the risk of musculoskeletal disorders, construction managers need to deepen their understanding of the physical and biomechanical demands of various construction tasks so that appropriate policies and preventive measures can be implemented. Among various construction trades, rebar workers are highly susceptible to lower-back disorders (LBDs) given the physically demanding nature of their work tasks. In particular, rebar tying is considered to be closely related to LBDs because it exposes workers to multiple ergonomic risk factors (repetitive works in prolonged static and awkward postures). The objective of the current study was to compare the differences in lumbar biomechanics during three typical rebar tying postures: stooping, one-legged kneeling, and squatting. Biomechanical variables including trunk muscle activity and trunk kinematics were measured by surface electromyography and motion sensors, respectively. Ten healthy male participants performed a simulated rebar tying task in each of the three postures in a laboratory setting. Repeated measures analysis of variance showed that while each posture has its unique trunk kinematic characteristics, all these postures involved excessive trunk inclination that exceeded the internationally recommended trunk inclination angle of 60° for static working postures. Of the three postures, stooping posture demonstrated a significant reduction in electromyographic activity of lumbar muscles (a reduction in 60–80% of muscle activity as compared to the other two postures). The reduced muscle activity may shift the loading to passive spinal structures (e.g., spinal ligaments and joint capsules), which is known to be a risk factor for LBD development. Collectively, the results from this study may help explain the high prevalence of LBDs in rebar workers. Future studies are warranted to confirm the findings at construction sites and to develop appropriate ergonomic approaches for rebar workers.

Overexertion-related construction activities are identified as a leading cause of work-related musculoskeletal disorders (WMSDs) among construction workers. However, few studies have focused on the automated recognition of overexertion-related construction workers’ activities as well as assessing ergonomic risk levels, which may help to minimize WMSDs. Therefore, this study examined the feasibility of using acceleration and foot plantar pressure distribution data captured by a wearable insole pressure system for automated recognition of overexertion-related construction workers’ activities and for assessing ergonomic risk levels. The proposed approach was tested by simulating overexertion-related construction activities in a laboratory setting. The classification accuracy of five types of supervised machine learning classifiers was evaluated with different window sizes to investigate classification performance and further estimate physical intensity, activity duration, and frequency information. Cross-validation results showed that the Random Forest classifier with a 2.56-s window size achieved the best classification accuracy of 98.3% and a sensitivity of more than 95.8% for each category of activities using the best features of combined data set. Furthermore, the estimation of corresponding ergonomic risk levels was within the same level of risk. The findings may help to develop a noninvasive wearable insole pressure system for the continuous monitoring and automated activity recognition, which could assist researchers and safety managers in identifying and assessing overexertion-related construction activities for minimizing the development of WMSDs’ risks among construction workers.

Plastic electronic waste (E-waste) is constantly growing around the world owing to the rapid increase in industrialization, urbanization, and population. The current annual production rate of E-waste is 3–4% in the world and is expected to increase to 55 million tons per year by 2025. To reduce the detrimental impact on the environment and save natural resources, one of the best solutions is to incorporate waste plastic in the construction industry to produce green concrete. This study examines the use of manufactured plastic coarse aggregate (PCA) obtained from E-waste as a partial replacement of natural coarse aggregate (NCA) in concrete. Six types of concrete mix with 10%, 20%, 30%, 40%, and 50% substitution of NCA (by volume) with PCA are prepared and tested. This study investigates the effect of manufactured PCA on the fresh and hardened characteristics of concrete. The properties of recycled plastic aggregate concrete (RPAC) studied include workability, fresh density, dry density, compressive strength (CS), splitting tensile strength (STS), flexural strength (FS), sorptivity coefficient, abrasion resistance, ultrasonic pulse velocity (UPV), and alternate wetting and drying (W–D). The results indicate that the CS, STS, and FS of RPAC declined in the range of 9.9–52.7%, 7.8–47.5%, and 11–39.4%, respectively, for substitution ratios of 10–50%. However, the results also indicate that the incorporation of PCA (10–50%) improved the workability and durability characteristics of concrete. A significant decrement in the sorptivity coefficient, abrasion loss, and UPV value was observed with an increasing amount of PCA. Furthermore, RPAC containing different percentages of PCA revealed better results against alternate W–D cycles with respect to ordinary concrete.