Improved Hill-type musculotendon models with activation-force-length coupling.

Area of Science:

• Biomechanics
• Musculoskeletal modeling
• Computational biology

Background:

• Hill-type musculotendon models are standard in biomechanics but often assume maximal muscle activation and linear scaling.
• This linear scaling assumption is inaccurate under submaximal conditions, limiting model practicality.
• Muscles in vivo frequently operate under submaximal activation, necessitating improved modeling approaches.

Purpose of the Study:

• To propose two novel Hill-type musculotendon models designed for enhanced performance under submaximal activation.
• To address the limitations of linear scaling in current musculotendon models.

Main Methods:

• Developed two improved Hill-type musculotendon models incorporating activation-force-length coupling (AFLC).
• Evaluated model biological accuracy and computational speed through benchmark simulations.

Main Results:

• The two AFLC models demonstrated improved accuracy compared to experimental data, with percent root mean square errors below 13.98%.
• The second AFLC model showed marginal accuracy improvement over the first but was approximately 17 times slower.
• The first AFLC model offered a favorable balance between accuracy and computational speed.

Conclusions:

• The developed AFLC models are more accurate than traditional Hill-type models for submaximal muscle activation.
• The first AFLC model is recommended for constructing upper-layer musculoskeletal models due to its efficiency and accuracy.