Abstract: In order to effectively prevent the occurrence of occupational musculoskeletal disorder,an approach was developed for assessing the risk levels of working postures based on deep neural network.The spatial locations of joints were estimated from on-site video through DNN,then the REBA was employed based on the calculating limb angels for the ergonomic analysis.The method was verified by analyzing typical construction working postures.The results show that the developed methodology can automatically and continually analyze sequence of postures and satisfies the recording conditions like dim light,occlusion of the partial body and low resolution of camera,and that the developed approach improves the traditional REBA via DNN,leading to higher efficiency of assessment for improving professional health of workers.

Key words: occupational health, musculoskeletal disorder, deep neural network (DNN), work posture, rapid entire body assessment