Automated Posture Assessment for construction workers

Ren-Jye Dzeng, H. H. Hsueh, C. W. Ho

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Construction workers often suffer various kinds of musculoskeletal disorders (MSDs), which are injuries in the human musculoskeletal system. MSDs are often aroused due to sudden exertion such as lifting heavy equipment, or repeated and cumulative stressed motions. OWAS (Ovako Working posture Assessment System) may be used to evaluate the exposure of MSDs risk by sampling the snapshots of a worker's postures and categorize the postures. However, tracking and categorizing postures of different body parts by human eyes are tedious work with limited accuracy and easy to make mistakes even with facilitation of video recording. This research develops an automatic tracking and categorizing system, named Posture Assessment System for MSD (PAS-MSD) for OWAS using Microsoft Kinect. The PAS-MSD captures human postures during his/her movement, recognizes human skeleton, and assesses the risk of MSD. An experiment with typical construction activities such as handling and moving of materials, hammering, and tiling was conducted. Except for the hammering activity where the subjects' body parts were easily blocked by the target hammered box and could not be detected by Kinect, the posture identification accuracies for all other activities exceed 90% (i.e., 91.6%-93.9%). The OWAS categorization accuracies are also satisfactory, ranging from 85.4%-88.5%.

Original languageEnglish
Title of host publication2017 40th International Convention on Information and Communication Technology, Electronics and Microelectronics, MIPRO 2017 - Proceedings
EditorsMarina Cicin-Sain, Filip Hormot, Tihana Galinac Grbac, Boris Vrdoljak, Edvard Tijan, Karolj Skala, Slobodan Ribaric, Stjepan Gros, Vlado Sruk, Mladen Mauher, Petar Biljanovic, Marko Koricic
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1027-1031
Number of pages5
ISBN (Electronic)9789532330922
DOIs
StatePublished - 10 Jul 2017
Event40th International Convention on Information and Communication Technology, Electronics and Microelectronics, MIPRO 2017 - Opatija, Croatia
Duration: 22 May 201726 May 2017

Publication series

Name2017 40th International Convention on Information and Communication Technology, Electronics and Microelectronics, MIPRO 2017 - Proceedings

Conference

Conference40th International Convention on Information and Communication Technology, Electronics and Microelectronics, MIPRO 2017
CountryCroatia
CityOpatija
Period22/05/1726/05/17

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  • Cite this

    Dzeng, R-J., Hsueh, H. H., & Ho, C. W. (2017). Automated Posture Assessment for construction workers. In M. Cicin-Sain, F. Hormot, T. G. Grbac, B. Vrdoljak, E. Tijan, K. Skala, S. Ribaric, S. Gros, V. Sruk, M. Mauher, P. Biljanovic, & M. Koricic (Eds.), 2017 40th International Convention on Information and Communication Technology, Electronics and Microelectronics, MIPRO 2017 - Proceedings (pp. 1027-1031). [7973575] (2017 40th International Convention on Information and Communication Technology, Electronics and Microelectronics, MIPRO 2017 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.23919/MIPRO.2017.7973575