Abstract
This paper introduces a low-cost and low computational marker-less motion capture system based on the acquisition of frame images through standard RGB cameras. It exploits the open-source deep learning model CMU, from the tf-pose-estimation project. Its numerical accuracy and its usefulness for ergonomic assessment are evaluated by a proper experiment, designed and performed to: (1) compare the data provided by it with those collected from a motion capture golden standard system; (2) compare the RULA scores obtained with data provided by it with those obtained with data provided by the Vicon Nexus system and those estimated through video analysis, by a team of three expert ergonomists. Tests have been conducted in standardized laboratory conditions and involved a total of six subjects. Results suggest that the proposed system can predict angles with good consistency and give evidence about the tool’s usefulness for ergonomist.
Highlights
Nowadays, reducing the risk of musculoskeletal diseases (MSDs) for workers of manufacturing industries is of paramount importance to reduce absenteeism on work, due to illnesses related to bad working conditions, and to improve process efficiency in assembly lines
This study provides the results of a first assessment of the proposed system, with the aim to measure its accuracy and to preliminary determine its utility for ergonomic assessment
The lengthy part of their job is manually extracting human angles from video analysis based on video captures, by analyzing how ergonomists carry out an Rapid Upper Limb Assessment (RULA) assessment
Summary
Nowadays, reducing the risk of musculoskeletal diseases (MSDs) for workers of manufacturing industries is of paramount importance to reduce absenteeism on work, due to illnesses related to bad working conditions, and to improve process efficiency in assembly lines. According to the European Commission’s Ageing Report 2015 [3], the employment rate of people over-55 will reach 59.8% in 2023 and 66.7% by 2060, because many born during the “baby boom” are getting older, life expectancy and retirement age are increasing, while the birth rate is decreasing. Solving this problem is of extreme importance.
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