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Maarten Afschrift¹, Dinant Kistemaker¹, Maarten Bobbert¹

¹Faculty of Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.

Plos Computational Biology

|November 17, 2025

Summary

Physics-based simulations accurately predict walking kinematics but underestimate metabolic power variations. This highlights the need for improved neuro-musculoskeletal models to enhance the realism of human movement simulations.

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Area of Science:

Biomechanics
Computational modeling
Human locomotion

Background:

Physics-based simulations using neuro-musculoskeletal models offer insights into locomotion.
Discrepancies between simulated and experimental gait patterns and metabolic powers indicate modeling limitations.

Purpose of the Study:

To systematically evaluate the predictive accuracy of a 3D musculoskeletal model for gait mechanics, muscle activity, and metabolic power across various conditions.
To identify sources of error in simulated metabolic power predictions.

Main Methods:

Simulated effects of adding mass, varying walking speed, incline walking, and crouched walking.
Compared simulation predictions against experimental data for kinematics and metabolic power.

Main Results:

Simulations accurately predicted stride frequency and walking kinematics.
Metabolic power variations were underestimated, particularly during incline walking (27% underestimation).
Identified high simulated mechanical efficiency and overestimation of positive muscle work as key issues.

Conclusions:

Current musculoskeletal models require refinement in mechanics, energetics, and neural control for realistic human movement simulation.
Validation across diverse conditions is crucial for identifying and rectifying model shortcomings.