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Multi-objective optimization digital human models permit users to predict postures that follow performance criteria, such as minimizing torques. Currently, it is unknown how to weight different objective functions to best predict postures. Objective one was to describe a response surface method to determine optimal objective function weightings to predict lift postures. Objective two was to evaluate the sensitivity of different error calculation methods. Our response surface approach has utility for determining optimal objective function weightings when using a digital human model to evaluate human-system interactions in early design stages. The approach was not dependent on variations in error calculation methods.

computer methods in biomechanics and biomedical engineering

A response surface methodology to determine the optimal objective function weightings within a multi-objective optimization digital human model used to predict postures