Technical Papers
Feb 22, 2019

Joint-Level Vision-Based Ergonomic Assessment Tool for Construction Workers

Publication: Journal of Construction Engineering and Management
Volume 145, Issue 5

Abstract

Construction workers are commonly subjected to ergonomic risks. Accurate ergonomic assessment is needed to reduce ergonomic risks. However, the diverse and dynamic nature of construction sites makes it difficult to collect workers posture data for ergonomic assessment without intrusiveness. Therefore, this paper proposed a joint-level vision-based ergonomic assessment tool for construction workers (JVEC) to provide automatic and detailed ergonomic assessments of construction workers based on construction videos. JVEC extracts construction workers’ skeleton data from videos with advanced deep learning methods, then Rapid Entire Body Assessment (REBA) is used to conduct the joint-level ergonomic assessment. This approach was demonstrated and tested with a laboratory experiment and an on-site experiment, which indicated the accuracy of the ergonomic risk scores (70%–96%) and its feasibility for use on construction sites. This research contributes to an accurate and nonintrusive ergonomic assessment method for construction workers. In addition, this research for the first time introduces two-dimensional (2D) video–based three-dimensional (3D) pose estimation algorithms to the construction industry, which may benefit research on construction health, safety, and productivity by providing long-term and accurate behavior data.

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Data Availability Statement

Data generated or analyzed during the study are available from the corresponding author by request. Information about the Journal’s data-sharing policy can be found here: http://ascelibrary.org/doi/10.1061/(ASCE)CO.1943-7862.0001263.

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Go to Journal of Construction Engineering and Management
Journal of Construction Engineering and Management
Volume 145Issue 5May 2019

History

Received: Feb 2, 2018
Accepted: Oct 17, 2018
Published online: Feb 22, 2019
Published in print: May 1, 2019
Discussion open until: Jul 22, 2019

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Yantao Yu, S.M.ASCE [email protected]
Ph.D. Student, Dept. of Building and Real Estate, Hong Kong Polytechnic Univ., Hung Hom, Kowloon 999077, Hong Kong. Email: [email protected]
Xincong Yang [email protected]
Ph.D. Candidate, Dept. of Building and Real Estate, Hong Kong Polytechnic Univ., Hung Hom, Kowloon 999077, Hong Kong. Email: [email protected]
Chair Professor, Dept. of Building and Real Estate, Hong Kong Polytechnic Univ., Hung Hom, Kowloon 999077, Hong Kong. Email: [email protected]
Xiaochun Luo [email protected]
Senior Research Fellow, Dept. of Building and Real Estate, Hong Kong Polytechnic Univ., Hung Hom, Kowloon 999077, Hong Kong. Email: [email protected]
Hongling Guo [email protected]
Associate Professor, Dept. of Construction Management, Tsinghua Univ., Beijing 100000, China (corresponding author). Email: [email protected]
Ph.D. Student, School of Civil Engineering and Mechanics, Huazhong Univ. of Science and Technology, Wuhan 430000, China. Email: [email protected]

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