ArticlePLoS computational biology2024
Insights into muscle metabolic energetics: Modelling muscle-tendon mechanics and metabolic rates during walking across speeds.
Article in PLoS computational biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Why inverse simulations overestimate optimal ankle exoskeleton assistance: the role of bi-articular coordination and joint stiffness.Journal of neuroengineering and rehabilitation · 2026Article
- Muscle-tendon mechanics resolve the trade-off between energy-efficient and robust locomotion.Biology letters · 2025Article
- Propulsion without penalty: greater soleus force with stiffer footwear does not necessarily increase estimated soleus metabolic cost across walking speeds.Journal of applied physiology (Bethesda, Md. : 1985) · 2025Article
- Springs vs. motors: Ideal assistance in the lower limbs during walking at different speeds.PLoS computational biology · 2024Article
- Experiment-guided tuning of muscle-tendon parameters to estimate muscle fiber lengths and passive forces.Scientific reports · 2024Article
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Authors and funding
4 authors.
Funding
Abstract
The metabolic energy rate of individual muscles is impossible to measure without invasive procedures. Prior studies have produced models to predict metabolic rates based on experimental observations of isolated muscle contraction from various species. Such models can provide reliable predictions of metabolic rates in humans if muscle properties and control are accurately modeled. This study aimed to examine how muscle-tendon model individualization and metabolic energy models influenced estimation of muscle-tendon states and time-series metabolic rates, to evaluate the agreement with empirical data, and to provide predictions of the metabolic rate of muscle groups and gait phases across walking speeds. Three-dimensional musculoskeletal simulations with prescribed kinematics and dynamics were performed. An optimal control formulation was used to compute muscle-tendon states with four levels of individualization, ranging from a scaled generic model and muscle controls based on minimal activations, inclusion of calibrated muscle passive forces, personalization of Achilles and quadriceps tendon stiffnesses, to finally informing muscle controls with electromyography. We computed metabolic rates based on existing models. Simulations with calibrated passive forces and personalized tendon stiffness most accurately estimate muscle excitations and fiber lengths. Interestingly, the inclusion of electromyography did not improve our estimates. The whole-body average metabolic cost was better estimated with a subset of metabolic energy models. We estimated metabolic rate peaks near early stance, pre-swing, and initial swing at all walking speeds. Plantarflexors accounted for the highest cost among muscle groups at the preferred speed and were similar to the cost of hip adductors and abductors combined. Also, the swing phase accounted for slightly more than one-quarter of the total cost in a gait cycle, and its relative cost decreased with walking speed. Our prediction might inform the design of assistive devices and rehabilitation treatment. The code and experimental data are available online.
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