Publication

Reducing complexity in muscle-tendon kinematics parameterization improves convergence speed in musculoskeletal simulations

Journal Article (2026)

Journal

International Journal for Numerical Methods in Biomedical Engineering

Pages

e70143

Volume

42

Number

2

Doc link

https://doi.org/10.1002/cnm.70143

File

Download the digital copy of the doc pdf document

Authors

Abstract

Musculoskeletal simulations play a crucial role in rehabilitation, orthopedic implant design and athletic performance enhancement. A computational challenge within these simulations involves efficiently estimating muscle-tendon lengths and momentarms, especially in multijoint, multidegree-of-freedom (DoF) systems. When modeling muscles spanning joints with six DoFs,the required number of terms can significantly increase, which could compromise computational speed. This study introducesa method that significantly reduces the polynomial coefficients needed for muscle-tendon length and moment arm parametri-zation, ensuring computational efficiency without compromising accuracy. The approach was applied with two different errorthresholds and was validated across four gait movements recorded from an elderly subject with a knee prosthesis, using data fromthe dataset of the Grand Challenge to predict in vivo contact forces. The results indicate that this reduction strategy decreasedthe required polynomial coefficients by approximately 50%, particularly for muscles spanning the knee and ankle joints, whilepreserving high accuracy in joint angle and knee contact force tracking. We demonstrate that our method decreases the compu-tation time required for simulating full-body dynamics by 15.6%, estimating knee contact pressures including a knee joint withall six DoFs. We observed minimal differences between the optimal solutions obtained using the full and reduced polynomials.This approach offers a simplified and computationally efficient method for muscle- driven simulations, making it more practicalfor clinical applications like in physiotherapy, robotic-assisted surgery, and athletic training. By increasing computational speed without losing accuracy, this method marks a notable advance in musculoskeletal modeling

Categories

dynamic programming, optimal control, optimisation.

Author keywords

computational efficiency, ground reaction forces, kinematics, moment arm, muscle forces, muscle-tendon length, musculoskeletal simulation, optimal control problem, polynomial coefficients

Scientific reference

M. Harba, J. Badia and G. Serrancolí. Reducing complexity in muscle-tendon kinematics parameterization improves convergence speed in musculoskeletal simulations. International Journal for Numerical Methods in Biomedical Engineering, 42(2): e70143, 2026.