Observational ergonomic postural assessment methods have been commonly used to evaluate the risks of musculoskeletal disorders. Researchers have proposed semi-automatic methods using Kinect, known for limitations with body occlusions and non-frontal tracking. Meanwhile, new human pose estimation methods have been actively developed, and a popular open-source technology is OpenPose. This study aims to propose the OpenPose-based system for computing joint angles and RULA/REBA scores and validate against the reference motion capture system, and compare its performance to the Kinect-based system. Recordings of 10 participants performing 12 experimental tasks under different conditions: with/without body occlusions and tracked from frontal/non-frontal views were analyzed. OpenPose showed good performance under all task conditions, whereas Kinect performed significantly worse than OpenPose especially at cases with body occlusions or non-frontal tracking. The findings suggested that OpenPose could be a promising technology to measure joint angles and conduct semi-automatic ergonomic postural assessments in the real workspace where the conditions are often non-ideal.

观察性人体工程学姿势评估方法已普遍用于评估肌肉骨骼疾病的风险。研究人员提出了使用 Kinect 的半自动方法，该方法以身体遮挡和非正面跟踪的局限性而闻名。同时，新的人体姿态估计方法也在积极开发中，一种流行的开源技术是 OpenPose。本研究旨在提出基于 OpenPose 的系统来计算关节角度和 RULA/REBA 分数，并针对参考运动捕捉系统进行验证，并将其性能与基于 Kinect 的系统进行比较。分析了 10 名参与者在不同条件下执行 12 项实验任务的记录：有/无身体遮挡和从正面/非正面视图跟踪。OpenPose 在所有任务条件下都表现出良好的性能，而 Kinect 的表现明显比 OpenPose 差，尤其是在身体遮挡或非正面跟踪的情况下。研究结果表明，OpenPose 可能是一种很有前途的技术，可以在条件通常不理想的真实工作空间中测量关节角度并进行半自动人体工程学姿势评估。