Advanced Engineering Informatics

Quantifying the physical intensity of construction workers, a mechanical energy approach

Liulin Kong, Heng Li, Yantao Yu, Hanbin Luo, Martin Skitmore, Antwi-Afari Maxwell Fordjour

Department of Civil Engineering and Mechanics, Huazhong University of Science and Technology, Wuhan, PR China


Construction activity, Mechanical energy expenditure, Biomechanical analysis, Human 3D Pose Estimation


Construction workers typically undertake highly demanding physical tasks involving various types of stresses from awkward postures, using excessive force, highly repetitive actions, and excessive energy expenditure, which increases the likelihood of unsafe actions, productivity loss, and human errors. Biomechanical models have been developed to estimate joint loadings, which can help avoid strenuous physical exertion, potentially enhancing construction workforce productivity, safety, and well-being. However, the models used are mainly in 2D, or to predict static strength ignored their velocity and acceleration or using marker-based method for dynamic motion data collection. To address this issue, this paper proposes a novel framework for investigating the mechanical energy expenditure (MEE) of workers using a 3D biomechanical model based on computer vision-based techniques. Human 3D Pose Estimation algorithm based on 2D videos is applied to approximate the coordinates of human joints for working postures, and smart insoles are used to collect foot pressures and plantar accelerations, as input data for the biomechanical analyses. The results show a detailed MEE rate for the whole body, at which joints the maximum and minimum values were obtained to avoid excessive physical exertion. The proposed method can approximate the total daily MEE of construction tasks by summing the assumed cost of individual tasks (such as walking, lifting, and stooping), providing suggestions for the design of a daily workload that workers can sustain without developing cumulative fatigue.

Moticon's Summary

The study addresses the physical demands on construction workers, who often suffer from work-related musculoskeletal disorders (WMSDs) due to excessive force and repetitive actions. To mitigate these risks, the paper proposes a novel, non-invasive, and cost-effective method for estimating the mechanical energy expenditure (MEE) of workers using 3D human pose estimation and biomechanical modeling. The approach utilizes vision-based techniques to track joint movements and Moticon sensor insoles to measure external forces. Inverse dynamics and kinematics are applied to calculate joint forces and moments, enabling the estimation of MEE during various construction tasks. Experimental results show significant variations in joint forces and moments across different activities, highlighting the lumbar spine as particularly vulnerable during stooping tasks. The findings provide valuable insights into managing workload and preventing WMSDs, emphasizing the importance of considering dynamic postures and movements in ergonomic assessments.

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