Force Closure Mechanism Modeling for Musculoskeletal Multibody Simulation.

Area of Science:

• Biomechanics and Computational Modeling
• Neuro-musculoskeletal Disorders
• Medical Simulation

Background:

• Neuro-musculoskeletal multibody simulation (NMBS) aims to optimize patient treatment for neuro-musculoskeletal disorders.
• Clinical practice faces challenges with inter-subject variability and limited experimental testing, hindering reliable NMBS model identification.
• These limitations necessitate novel approaches for accurate and personalized modeling.

Purpose of the Study:

• To introduce and validate a novel modeling approach, force closure mechanism modeling (FCM²), for NMBS.
• To assess FCM²'s capability in capturing subject-specific joint function and deriving equations of motion.
• To evaluate FCM² as an inverse dynamic model for computed muscle control in clinical applications.

Main Methods:

• FCM² reconstructs instantaneous screw axes (ISA) from relative velocity states to model joint dynamics.
• The approach reduces complex multibody topologies to force closure n-link pendulums.
• A computational study on the human knee joint compared FCM² with a classic hinge joint model and experimental data.

Main Results:

• FCM² successfully predicted joint dynamics, aligning with established methods and experimental findings.
• The novel approach demonstrated proof-of-principle for NMBS, freeing users from predefined joint formulations.
• While experimental results were closely predicted, muscle moment arms were overestimated due to ISA estimation noise (R = 0.84 vs. 0.97).

Conclusions:

• FCM² automatically derives equations of motion in closed form, minimizing modeling and parameterization efforts.
• The method captures subject-specific joint function, offering a significant advancement in personalized modeling.
• Robust ISA estimation is identified as crucial for optimizing FCM² performance in clinical settings.