A contact model to simulate human-artifact interaction based on force optimization: implementation and application to...

Area of Science:

• Biomechanics
• Computational modeling
• Human-computer interaction

Background:

• Musculoskeletal multibody models are vital for analyzing human-technical interactions.
• Accurate modeling of frictional contact forces is essential for robust simulations.
• Existing models often overlook aspects of Coulomb's friction law.

Purpose of the Study:

• To propose a novel parametric contact model for musculoskeletal multibody dynamics.
• To develop an inverse dynamics approach for estimating muscle and contact forces.
• To analyze and optimize human-machine interactions, specifically reducing tibiofemoral joint stress.

Main Methods:

• Formulation of a parametric contact model incorporating static and kinetic friction regimes.
• Development of a force optimization problem for inverse dynamic analysis.
• Application to a leg extension training machine scenario.

Main Results:

• The proposed model successfully estimates unknown muscle and contact forces from motion data.
• The approach allows for simultaneous analysis of static and kinetic friction.
• Simulation results highlight the impact of a tunable parameter on tibiofemoral joint stress.

Conclusions:

• The developed parametric contact model offers a robust method for analyzing frictional forces in human-machine interactions.
• This approach can be used to optimize training machines for reduced joint stress.
• Further investigation into parameter uncertainty is warranted for refining simulation accuracy.