Predictive Health Analysis in Industry 50: A Scientometric and Systematic Review of Motion Capture in Construction
<|reference_start|>Predictive Health Analysis in Industry 50: A Scientometric and Systematic Review of Motion Capture in Construction: In an era of rapid technological advancement, the rise of Industry 4.0 has prompted industries to pursue innovative improvements in their processes. As we advance towards Industry 5.0, which focuses more on collaboration between humans and intelligent systems, there is a growing requirement for better sensing technologies for healthcare and safety purposes. Consequently, Motion Capture (MoCap) systems have emerged as critical enablers in this technological evolution by providing unmatched precision and versatility in various workplaces, including construction. As the construction workplace requires physically demanding tasks, leading to work-related musculoskeletal disorders (WMSDs) and health issues, the study explores the increasing relevance of MoCap systems within the concept of Industry 4.0 and 5.0. Despite the growing significance, there needs to be more comprehensive research, a scientometric review that quantitatively assesses the role of MoCap systems in construction. Our study combines bibliometric, scientometric, and systematic review approaches to address this gap, analyzing articles sourced from the Scopus database. A total of 52 papers were carefully selected from a pool of 962 papers for a quantitative study using a scientometric approach and a qualitative, indepth examination. Results showed that MoCap systems are employed to improve worker health and safety and reduce occupational hazards.The in-depth study also finds the most tested construction tasks are masonry, lifting, training, and climbing, with a clear preference for markerless systems.<|reference_end|>
@article{rahman2024predictive,
    title={Predictive Health Analysis in Industry 5.0: A Scientometric and
  Systematic Review of Motion Capture in Construction},
    author={Md Hadisur Rahman, Md Rabiul Hasan, Nahian Ismail Chowdhury, Md Asif
  Bin Syed, Mst Ummul Farah},
    journal={arXiv preprint arXiv:2402.01689},
    year={2024},
    archivePrefix={arXiv},
    eprint={2402.01689},
    primaryClass={cs.CY}
}