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Evaluating the accuracy and feasibility of a commercial AI-powered ergonomic assessment system for automotive
Saman Jamshid Nezhad Zahabi1, Sunwook Kim1, Maury A Nussbaum1
1Department of Industrial and Systems Engineering, Virginia Tech, Blacksburg, VA, 24061, USA.
Abstract:
Accurate ergonomic risk assessment is essential to prevent work-related musculoskeletal disorders. Artificial intelligence (AI) and computer vision offer new opportunities for automatic risk assessment, but accuracy and usability remain uncertain. We evaluated a commercial, AI-powered, ergonomic assessment system through two studies: In an exploratory evaluation (Study 1; n = 10), we compared risk estimates and joint angles using three camera placements vs. a gold-standard 3D motion capture system. In Study 2 (n = 10), we interviewed ergonomics professionals who used the software system for automotive assembly tasks. We found substantial inaccuracies in joint angles (especially left elbow and bilateral wrists) and risk estimates, and important variability across camera setups. Although the software system was reported as easy to use and visually intuitive, concerns were noted about reliability-particularly in cluttered environments and tasks involving fine hand motions. While promising, these systems may require further refinements to improve accuracy and adaptability.
