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 (𝑝>0.05). 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 index=0.65, Cohen’s kappa=0.77). Only a slight consistency was observed between the evaluation results obtained from the right-hand side and the expert (proportion agreement index=0.41, Cohen’s kappa=0.08). 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.
|Article number||2256017 (2022)|
|Journal||International Journal of Pattern Recognition and Artificial Intelligence|
|Publication status||Published - 12 Jul 2022|
- Artificial Intelligence
- Computer Vision and Pattern Recognition