Ergonomic Assessment Method of Risk Factors for Musculoskeletal Disorders Associated with Sitting Postures

Author:

Li Jianwei1ORCID,Huang Sihan1,Wang Faming1,Chen Sixi1,Zheng Huiru2

Affiliation:

1. College of Physics and Information Engineering, Fuzhou University, No. 2, Xueyuan Road, Fuzhou, Fujian 350116, P. R. China

2. School of Computing, Ulster University, Shore Road, Newtownabbey, County Antrim BT370QB, UK

Abstract

Musculoskeletal disorders (MSDs) are associated with sitting postures. The assessment and prevention of risk factors for workplace exposure are indispensable aspects of reducing the occurrence of MSDs. This paper proposes an ergonomic assessment method of risk factors for MSDs associated with sitting postures in the actual working conditions. A Kinect sensor with the RULA method was primarily used to collect the data and evaluate the relevant postures. The results obtained were compared with the evaluation results by a human expert. Additionally, we verified the capability and effectiveness of this method. A program system for human joint recognition and acquisition was implemented. The results indicated that the Kinect joint data is generally accurate and can adequately complete the RULA evaluation table. The results from the front and right-hand side obtained by the Kinect were consistent with the results of the expert evaluation, and no significant difference was observed between them ([Formula: see text]). However, when the participants faced the Kinect, the sensor performed better, and the evaluation result was more accurate. A high consistency was observed between the evaluation results obtained from the front and the expert (proportion agreement [Formula: see text], Cohen’s [Formula: see text]). Only a slight consistency was observed between the evaluation results obtained from the right-hand side and the expert (proportion agreement [Formula: see text], Cohen’s [Formula: see text]). This research created a new ergonomic method for the risk assessment of MSDs associated with sitting postures. The combination of theory and practice is crucial in the risk assessment of sitting postures in workplaces.

Funder

the National Natural Science Foundation of China

the Natural Science Foundation of Fujian Province

the China Postdoctoral Science Foundation

Publisher

World Scientific Pub Co Pte Ltd

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

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