A validation framework for predictive human models

Abstract

A validation framework is introduced in this work to evaluate the motion of a predictive human model and provide feedback to the model developers for refinement in ergonomic applications. Two qualitative and two quantitative benchmark tests were designed and used to assess the strength and weakness of the model and to localise abnormalities in the predicted motion. Twelve subjects participated in a whole-body motion task, and another 12 subjects participated in the subjective evaluation of the predicted motion. The validation framework was able to highlight the weakness and limitations of a predicted human model with 55 degrees of freedom in a box-lifting task. The results have shown that the proposed framework was very effective in identifying the flaws in the model under investigation and in giving guides for improvement and acceptance.