Multi-scale Predictive Human Model for Preventing Injuries in the Ankle and Knee

Abstract

One of the primary applications for digital human models (DHMs) is injury prevention. In the case of orthopedic or soft-tissue injuries, it becomes especially useful to couple whole-body predictive DHMs that can simulate tasks with high-fidelity finite element analysis (FEA) models that provide more accurate analyses related to the propensity of injury. In general, the complexity of the human body necessitates multi-scale models in order to improve fidelity, which becomes critical when trying to relate performance to safety or injury. To be sure, FEA models are certainly useful as independent tools, but their benefits are fully realized only when they are integrated with a complete system-level human model that essentially connects the local model to a virtual environment. Incorporating high-fidelity local models within a larger-scale DHM provides more reliable input to the local models and increases ease of use. Although multi-scale modeling is an active area of research, there have been few, if any, efforts to seamlessly link high-fidelity biomechanical models with a complete system-level DHM for injury prevention. Thus, the proposed work integrates Santos, a joint-based, physics-based, predictive DHM, with an OpenSim muscle model and FEA models for both the ankle and the knee. Initial results for this integrated multi-scale DHM have been successful and allow one to track joint angles and torques, muscle activation, and joint stress during a simulated task. In addition, a joint injury system is introduced based on the yield stress of the ankle and knee components. This system includes both the bone and soft tissue structures. The bone was modeled as elastic material, whereas soft tissue was modeled as hyper-elastic material with the Noe-Hookean method. Predicted dynamic motion and ground-reaction-force values, as well as results from the FEA models are in agreement with results in the literature. This integrated system allows one to study the effects of various motions and task parameters on both the ankle and knee joints so as to modify tasks and reduce the likelihood of injury.