Current methods for physical demands descriptions often lack detail and format standardization, require technical training and expertise, and are time-consuming to complete. A video-based physical demands description tool may improve time and accuracy concerns with current methods. Ten simulated occupational tasks were synchronously recorded using a motion capture system and digital video. Digital video was processed with a novel video-based assessment tool to produce 3D joint trajectories (PDAi), and joint angle and reach envelope measures were calculated from both data sources. These measures were compared to joint angle and reach envelope estimates from experienced ergonomists (3) and novice ergonomists (3) in a simulated traditional physical demands description format. The video-based joint estimated showed 62.5% agreement with motion capture data across 80 measures (8 summary measures x 10 tasks). Video-based posture estimates were equal or better than human raters for 72.5% of ratings, and were outright better than human groups for 32.5% of ratings. The high level of agreement between video-based and motion capture measures suggest video-based job task assessment may be a viable approach to improve accuracy and standardization of field physical demands descriptions and minimize error in joint posture and reach envelope estimates compared to traditional pen-and-paper methods.
Ergomechanic: A markerless motion capture and ergonomic assessment tool developed using the Workspace workflow engine
