Sloppiness Consistency in Biomechanical Models and Its Inspired Dual-Space Model Optimization (Adv. Phys. Res. 6/2025)

Abstract

Sloppiness Consistency Drives Balance in Mechanical Modeling

The study by Wenyang Liu, Shujuan Hou and co-workers (see article number 2500002) introduces an information-geometry-based approach for simplifying biomechanical constitutive models. By analyzing parameter sensitivity matrices, it reveals the inherent “sloppiness” of soft tissue models and constructs a parameter hyperspace with a four-step optimization strategy to reduce model complexity while maintaining identifiability and predictive accuracy, as successfully demonstrated in brain tissue and patellar tendon models.