A Feature-Level Fusion-Based Multimodal Analysis of Recognition and Classification of Awkward Working Postures in Construction-Reference-Cited by-同舟云学术

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A Feature-Level Fusion-Based Multimodal Analysis of Recognition and Classification of Awkward Working Postures in Construction

Published:2023-12 Issue:12 Volume:149 Page:
ISSN:0733-9364
Container-title:Journal of Construction Engineering and Management
language:en
Short-container-title:J. Constr. Eng. Manage.

Author:

Xiahou Xiaer¹,Li Zirui²,Xia Jikang³,Zhou Zhipeng⁴,Li Qiming⁵

Affiliation:

1. Associate Professor, School of Civil Engineering, Southeast Univ., Nanjing 211189, China (corresponding author).

2. Ph.D. Student, School of Civil Engineering, Southeast Univ., Nanjing 211189, China.

3. Undergraduate Student, School of Civil Engineering, Southeast Univ., Nanjing 211189, China.

4. Associate Professor, School of Economics and Management, Nanjing Univ. of Aeronautics and Astronautics, Nanjing 210000, China.

5. Professor, School of Civil Engineering, Southeast Univ., Nanjing 211189, China.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Strategy and Management,Industrial relations,Building and Construction,Civil and Structural Engineering

Link

https://ascelibrary.org/doi/pdf/10.1061/JCEMD4.COENG-13795

Reference79 articles.

1. RGB-D ergonomic assessment system of adopted working postures

2. Tracking multiple construction workers through deep learning and the gradient based method with re-matching based on multi-object tracking accuracy

3. Fall risk assessment of construction workers based on biomechanical gait stability parameters using wearable insole pressure system

4. Biomechanical analysis of risk factors for work-related musculoskeletal disorders during repetitive lifting task in construction workers

5. Automated detection and classification of construction workers' loss of balance events using wearable insole pressure sensors

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Data-driven ergonomic assessment of construction workers;Automation in Construction;2024-09

2. Monitoring and evaluating the status and behaviour of construction workers using wearable sensing technologies;Automation in Construction;2024-09

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