[Research progress of automated ergonomic assessment methods based on RULA and REBA]

This paper summarizes the research progress in automated ergonomic contact risk assessment technology based on the rapid upper limb assessment (RULA) and rapid entire body assessment (REBA) , with a focus on analyzing current status and challenges in data acquisition, transmission and processing, application scenarios, and accuracy validation, as well as providing an outlook on future research directions. The analysis indicates that currently, inertial measurement unit (IMU) , conventional/depth cameras, and infrared motion capture systems are the primary hardware devices, with data processing predominantly relying on computer vision and deep learning algorithms. There are significant variations in the accuracy of system assessments, with Cohen's kappa (κ) ranging from 0.21 to 0.95 and the proportion agreement index (Po) ranging from 0.37 to 0.97. Limited by the constraints of data collection and transmission and the reliability of the system, current research primarily employs semi-automated methods in simulated scenarios. Future studies should aim to develop more reliable hardware solutions, establish unified validation standards, and promote the continuous and holistic assessment application of systems in real-world work scenarios.