STRENGTH MAPPING ALGORITHM (SMA) FOR BIOMECHANICAL HUMAN MODELLING USING EMPIRICAL POPULATION DATA
Editor: Christian Weber, Stephan Husung, Marco CantaMESsa, Gaetano Cascini, Dorian Marjanovic, Srinivasan Venkataraman
Author: Miehling, Joerg; Wartzack, Sandro
Institution: Friedrich-Alexander-Universitaet Erlangen-Nuernberg, Germany
Section: Design Information and Knowledge Management
Despite the increasing level of detail in biomechanical simulation, human models are not yet valid to represent specific individuals or populations. Therefore, the generic models need adaptation to depict the varying competencies of the respective person or user group aimed to investigate. There have been achievements in scaling single modelling domains (e.g. anthropometry). However, a comprehensive approach is still lacking. This paper extends available methods by introducing a Strength Mapping Algorithm (SMA) for the adaption of individual maximum isometric forces to match empirical strength data. This procedure involves static optimization simulation of predefined body postures to reveal the dependencies between muscle forces and joint torques of a generic model specifying the skeletal and muscular geometry. Based on this information, we determine a set of muscle scaling factors for a given age, gender and strength percentile. As a result, the SMA enables the quick generation of a large number of individuals in order to implement a design for populations paradigm. This leads one step closer to gain deeper insight on how health relevant products and processes are to be developed.