{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T00:58:21Z","timestamp":1776128301718,"version":"3.50.1"},"reference-count":28,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2024,9,24]],"date-time":"2024-09-24T00:00:00Z","timestamp":1727136000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["52108286"],"award-info":[{"award-number":["52108286"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["GXWD20220818002513001"],"award-info":[{"award-number":["GXWD20220818002513001"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["RCBS20221008093128076"],"award-info":[{"award-number":["RCBS20221008093128076"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["ZDSYS20210929115800001"],"award-info":[{"award-number":["ZDSYS20210929115800001"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Shenzhen Science and Technology Programs","award":["52108286"],"award-info":[{"award-number":["52108286"]}]},{"name":"Shenzhen Science and Technology Programs","award":["GXWD20220818002513001"],"award-info":[{"award-number":["GXWD20220818002513001"]}]},{"name":"Shenzhen Science and Technology Programs","award":["RCBS20221008093128076"],"award-info":[{"award-number":["RCBS20221008093128076"]}]},{"name":"Shenzhen Science and Technology Programs","award":["ZDSYS20210929115800001"],"award-info":[{"award-number":["ZDSYS20210929115800001"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Work-related musculoskeletal disorders (WMSDs) represent a significant health challenge for workers in construction environments, often arising from prolonged exposure to ergonomic risks associated with manual labor, awkward postures, and repetitive motions. These conditions not only lead to diminished worker productivity but also incur substantial economic costs for employers and healthcare systems alike. Thus, there is an urgent need for effective tools to assess and mitigate these ergonomic risks. This study proposes a novel monocular 3D multi-person pose estimation method designed to enhance ergonomic risk assessments in construction environments. Leveraging advanced computer vision and deep learning techniques, this approach accurately captures and analyzes the spatial dynamics of workers\u2019 postures, with a focus on detecting extreme knee flexion, a critical indicator of work-related musculoskeletal disorders (WMSDs). A pilot study conducted on an actual construction site demonstrated the method\u2019s feasibility and effectiveness, achieving an accurate detection rate for extreme flexion incidents that closely aligned with supervisory observations and worker self-reports. The proposed monocular approach enables universal applicability and enhances ergonomic analysis through 3D pose estimation and group pose recognition for timely interventions. Future efforts will focus on improving robustness and integration with health monitoring to reduce WMSDs and promote worker health.<\/jats:p>","DOI":"10.3390\/s24196187","type":"journal-article","created":{"date-parts":[[2024,9,25]],"date-time":"2024-09-25T04:01:24Z","timestamp":1727236884000},"page":"6187","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Monocular 3D Multi-Person Pose Estimation for On-Site Joint Flexion Assessment: A Case of Extreme Knee Flexion Detection"],"prefix":"10.3390","volume":"24","author":[{"given":"Guihai","family":"Yan","sequence":"first","affiliation":[{"name":"Central Research Institute of Building and Construction Co., Ltd., MCC Group, Shenzhen 518088, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-7671-7136","authenticated-orcid":false,"given":"Haofeng","family":"Yan","sequence":"additional","affiliation":[{"name":"School of Civil Engineering, Harbin Institute of Technology, Harbin 150090, China"}]},{"given":"Zhidong","family":"Yao","sequence":"additional","affiliation":[{"name":"Central Research Institute of Building and Construction Co., Ltd., MCC Group, Shenzhen 518088, China"}]},{"given":"Zhongliang","family":"Lin","sequence":"additional","affiliation":[{"name":"Central Research Institute of Building and Construction Co., Ltd., MCC Group, Shenzhen 518088, China"}]},{"given":"Gang","family":"Wang","sequence":"additional","affiliation":[{"name":"China Jingye Engineering Technology, Co., Ltd., Shenzhen 518055, China"}]},{"given":"Changyong","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Civil Engineering, Harbin Institute of Technology, Harbin 150090, China"}]},{"given":"Xincong","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Civil and Environmental Engineering, Harbin Institute of Technology, Shenzhen 518055, China"},{"name":"Guangdong Provincial Key Laboratory of Intelligent and Resilient Structures for Civil Engineering, Shenzhen 518055, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,9,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"103921","DOI":"10.1016\/j.autcon.2021.103921","article-title":"Risk Assessment for Musculoskeletal Disorders Based on the Characteristics of Work Posture","volume":"131","author":"Wang","year":"2021","journal-title":"Autom. 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