Effect of using real motion versus predicted motion as input for digital human modeling of back and shoulder loads during manual material handling

Digital human modeling (DHM) technology is considered the state of the art in designing and evaluating workstations. Previous studies examined the differences between DHM's posture and motion prediction relative to human experimental data. Yet, the effect the two different inputs on biomechanical loads was not assessed. Therefore, this study evaluates the differences in L4/L5 compression force and shoulder torques during a work process calculated using DHM with motion prediction (Jack by Siemens) and DHM with experimental data. The work process is a sequential removing, carrying, and depositing task performed by nine females and nine males and recorded using a motion capture system. The analysis shows that using experimental data results in larger back compression force during the removing task (average 15.4%), similar force during the depositing task (average 0.68%), and less force during the carrying task (19.875%). Using experimental data resulted in larger shoulder torque during all tasks (average 24.97%).