A comparison of digital human model ergonomics outputs driven by optical and inertial motion capture systems in virtual reality

Abstract

Digital human models (DHM), or virtual human avatars, can be used within digital virtual manufacturing to conduct proactive ergonomics analyses. Recent technological advancements have allowed for dynamic posturing of the DHM using motion capture technology and virtual reality immersion, providing a potentially powerful approach to evaluate ergonomics outputs including hand location and spine compression. The purpose of this thesis was to compare the hand locations, joint angles and spine compressions produced by a DHM software program when driven by three different types of motion capture systems during a virtual reality task. Findings show that the inertial-driven model consistently underestimated hand locations by 24.3 cm, whereas the Vive trackers showed an overall RMS error of 13.7 cm. This error is further supported by spine compression values, where IMU-driven DHMs underestimated up to 213N compared to the optical system. As a result, the DHM generated using kinematic data from the Vive Trackers system provided the most similar results to the actual location and represent a promising, low cost solution for future ergonomics analyses.