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Prior studies have produced models to predict metabolic rates based onexperimental observations of isolated muscle contraction from various species.Such models can provide reliable predictions of metabolic rates in humans ifmuscle properties and control are accurately modeled. This study aimed toexamine how muscle-tendon model calibration and metabolic energy modelsinfluenced estimation of muscle-tendon states and time-series metabolic rates,to evaluate the agreement with empirical data, and to provide predictions ofthe metabolic rate of muscle groups and gait phases across walking speeds.Three-dimensional musculoskeletal simulations with prescribed kinematics anddynamics were performed. An optimal control formulation was used to computemuscle-tendon states with four levels of individualization, ranging from ascaled generic model and muscle controls based on minimal activations, tocalibration of passive muscle forces, personalization of Achilles andquadriceps tendon stiffnesses, to finally informing muscle controls withelectromyography. We computed metabolic rates based on existing models.Simulations with calibrated passive forces and personalized tendon stiffnessmost accurately estimate muscle excitations and fiber lengths. Interestingly,the inclusion of electromyography did not improve our estimates. The whole-bodyaverage metabolic cost was better estimated using Bhargava et al. 2004 andUmberger 2010 models. We estimated metabolic rate peaks near early stance,pre-swing, and initial swing at all walking speeds. Plantarflexors accountedfor the highest cost among muscle groups at the preferred speed and was similarto the cost of hip adductors and abductors combined. Also, the swing phaseaccounted for slightly more than one-quarter of the total cost in a gait cycle,and its relative cost decreased with walking speed.

Insights into muscle metabolic energetics: Modelling muscle-tendon mechanics and metabolic rates during walking across speeds