Metabolic cost of each step: model biofidelity leads to accurate estimations

Objective: We examined how muscle-tendon model personalization and metabolic energy models influenced estimation of muscle-tendon states and time-series metabolic rates across walking speeds. Methods: 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 personalization, ranging from a scaled generic model and muscle controls based on minimal activations, to calibration of passive muscle forces, personalization of Achilles and quadriceps tendon stiffnesses, to finally informing muscle controls with electromyography. We computed metabolic rates based on existing models. Results: Simulations with calibrated passive forces and personalized tendon stiffness most accurately estimate muscle excitations and fiber lengths. Interestingly, the inclusion of EMGs did not improve our estimates. The whole-body average metabolic cost was better estimated using Bhargava et al. 2004 and Umberger 2010 models. We predicted 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 was similar to the cost of hip adductors and abductors combined. Also, the swing phase accounted for slightly higher than one-quarter of the total cost in a gait cycle, and its relative cost decreased with walking speed. Conclusion: We identified modeling assumptions that lead to estimating muscle-tendon states and metabolic rates with high accuracy. Significance: Our prediction might inform the design of assistive devices and rehabilitation treatment.