Musculotendon Parameters in Lower Limb Models: Simplifications, Uncertainties, and Muscle Force Estimation...

Area of Science:

• Biomechanics
• Musculoskeletal Modeling
• Computational Physiology

Background:

• Musculotendon parameters are essential for accurate Hill-type muscle contraction dynamics in musculoskeletal models.
• Muscle architecture datasets have driven model development, but their impact on simulation accuracy is often unclear.

Purpose of the Study:

• To clarify the derivation and accuracy of musculotendon parameters used in musculoskeletal models.
• To assess the influence of parameter uncertainties on muscle force estimation.
• To guide model users in selecting appropriate datasets and parameters.

Main Methods:

• Detailed examination of musculotendon parameter derivation in six muscle architecture datasets and four OpenSim lower limb models.
• Identification of simplifications leading to parameter uncertainties.
• Numerical and analytical sensitivity analysis of muscle force estimation to parameter variations.

Main Results:

• Nine common simplifications in parameter derivation were identified.
• Tendon slack length was found to be the most sensitive parameter for muscle force estimation.
• Pennation angle demonstrated the least impact on force estimation accuracy.

Conclusions:

• Anatomical measurements alone are insufficient for calibrating musculotendon parameters.
• Relying solely on muscle architecture datasets offers limited improvements in force estimation accuracy.
• Focusing on other model parameters or alternative strategies may yield greater gains in simulation accuracy.