坐
一致性(知识库)
表(数据库)
接头(建筑物)
人工智能
肌肉骨骼疾病
计算机科学
人为因素与人体工程学
机器学习
人机交互
应用心理学
工程类
心理学
数据挖掘
医学
毒物控制
结构工程
病理
环境卫生
作者
Jianwei Li,Sihan Huang,Faming Wang,Sixi Chen,Huiru Zheng
标识
DOI:10.1142/s0218001422560171
摘要
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.
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