Biomechanical Analysis in Construction Engineering and Management Research: A Review

被引:0
|
作者
Ibrahim, Abdullahi [1 ]
Nnaji, Chukwuma [1 ]
Jin, Ziyu [1 ]
机构
[1] Univ Alabama, Dept Civil Construct & Environm Engn, Tuscaloosa, AL 35487 USA
关键词
ERGONOMIC ANALYSIS; WORKERS; POSTURE;
D O I
暂无
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
In construction, the high amount of work musculoskeletal disorders (WMSD) continues to be a major source of concern for practitioners and researchers. In response to this concern, construction stakeholders have increasingly utilized advanced simulation technics to investigate musculoskeletal risks that contribute to WMSDs and inform ergonomic changes to work environments and operations. Specifically, studies at the intersection of biomechanical analysis (BA) and construction worker safety and health have increased recently. While using BA tools in construction research and practice is commendable, synthesized information on the application and utility of these tools is lacking. To enhance the quality of research within this domain, it is essential to provide a synthesis that summarizes BA efficacy in examining working postural faults in construction activities, their relevance in construction research, data collection limitations, and future directions. Utilizing a three-phase review process, the present study queried SCOPUS database, which helped identify 15 articles adherent to the pre-defined inclusion criteria. Results from the present study suggest that research utilizing BA in construction more than doubled in the last 10 years. To improve the quality and generalizability of biomechanics and ergonomics research in construction safety and health management, future construction studies should: assess under-researched construction activities with high WMSD prevalence; include a more significant number of experienced workers; increase participants diversity (female and non-Caucasian) in experiments; and utilize advanced Artificial Intelligence algorithms to build robust and precise biomechanical models which will be useful in analyzing the growing wealth of high-dimensional data.
引用
收藏
页码:571 / 579
页数:9
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