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Real time RULA assessment using Kinect v2 sensor.

Authors :
Manghisi, Vito Modesto
Uva, Antonio Emmanuele
Fiorentino, Michele
Bevilacqua, Vitoantonio
Trotta, Gianpaolo Francesco
Monno, Giuseppe
Source :
Applied Ergonomics. Nov2017, Vol. 65, p481-491. 11p.
Publication Year :
2017

Abstract

The evaluation of the exposure to risk factors in workplaces and their subsequent redesign represent one of the practices to lessen the frequency of work-related musculoskeletal disorders. In this paper we present K2RULA, a semi-automatic RULA evaluation software based on the Microsoft Kinect v2 depth camera, aimed at detecting awkward postures in real time, but also in off-line analysis. We validated our tool with two experiments. In the first one, we compared the K2RULA grand-scores with those obtained with a reference optical motion capture system and we found a statistical perfect match according to the Landis and Koch scale (proportion agreement index = 0.97, k = 0.87). In the second experiment, we evaluated the agreement of the grand-scores returned by the proposed application with those obtained by a RULA expert rater, finding again a statistical perfect match (proportion agreement index = 0.96, k = 0.84), whereas a commercial software based on Kinect v1 sensor showed a lower agreement (proportion agreement index = 0.82, k = 0.34). [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00036870
Volume :
65
Database :
Academic Search Index
Journal :
Applied Ergonomics
Publication Type :
Academic Journal
Accession number :
124577760
Full Text :
https://doi.org/10.1016/j.apergo.2017.02.015