Presentation
A Single-Camera Computer Vision-Based Method for 3D L5/S1 Moment Estimation During Lifting Tasks
Event Type
Lecture
In-Person
Occupational Ergonomics
TimeWednesday, October 6th10:45am - 11:00am EDT
LocationHarborside Salon B
DescriptionExcessive low back joint loading during material handling tasks is considered as a critical risk factor of musculoskeletal disorders (MSD). Therefore, it is necessary to understand the low-back joint loading during manual material handling to prevent low-back injuries. Recently, computer vision-based pose reconstruction methods have shown the potential in human kinematics and kinetics analysis. In this study, we performed L5/S1jonit moment estimation by combining VideoPose3D, an open-source pose reconstruction library, and a biomechanical model. Twelve participants lifting a 10 kg plastic crate from floor to a knuckle-height shelf were captured by a camera and a laboratory-based motion tracking system. The L5/S1 joint moments obtained from the camera video were compared with those obtained from the motion tracking system. The comparison results indicate that estimated total peak L5/S1 moments during lifting tasks were positively correlated to the reference L5/S1 joint moment, and the percentage error is 7.7%.