Ergonomic assessment based on monocular RGB camera in elderly care by a new multi-person 3D pose estimation technique (ROMP)

Abstract

Nursing staff members are at high risk of work-related musculoskeletal disorders (WMSDs), which not only threaten their health but also impact the quality of elderly care. Ergonomic posture risk assessment (EPRA) is usually employed to identify potential WMSD risks such as extreme posture and repetitive movements. A monocular RGB camera has been used for the EPRA in recent years due to its short time requirements and low cost. However, most work scenarios do not involve multi-person situations.Therefore, based on the latest 3D pose estimation algorithm—Monocular, One-stage Regression of Multiple 3D People (ROMP)—this study proposes a method that uses one monocular RGB camera to conduct the EPRA in multi-person and occluded scenarios. The accuracy of our method was calculated through 12 care tasks involving multi-person and occlusion, using the Noitom motion capture (MoCap) system.The results show that our method performed well, with an average accuracy of 83.8% and 90.7%, respectively, using two EPRA scoring tools, RULA and OWAS. The mean absolute error (MAE) of each joint angle was 9.4°. Thus, ROMP seems to be a potential method for conducting the EPRA in nursing workspaces with unsatisfactory conditions using a single monocular RGB camera.