Abstract

Race walking has been shown to be a lower impact alternative to running. In fact, lower injury rates are reported in race walkers than runners. This may be due to lower joint forces. However, this theory has not been explicitly tested since joint contact forces are difficult to measure. Therefore, these joint forces are calculated using either a serial or cosimulation approach. In both strategies, a detailed joint model and multibody dynamics model are used in tandem to calculate muscle forces. These muscle forces then contribute to the joint contact forces. Computed muscle control (CMC) is an algorithm that utilizes a proportional-derivative controller, static optimization, and forward dynamics to calculate muscle activations, which are used to subsequently calculate muscle forces. The goal of this study was to investigate the viability of using CMC to calculate muscle activations during race walking, with the intent of using these activations in future studies to calculate joint forces. Instrumented motion capture data (kinematics, kinetics, and electromyography (EMG)) of a representative subject was used from a previous study. In this study, subjects walked, race walked, and ran at a self-selected pace across a walkway with embedded forceplates while marker trajectories and EMG were collected. Muscle actuated forward dynamics simulations (i.e. CMC) were created for each movement. The muscle activations resulting from these CMC simulations were compared to the experimentally measured EMG by performing a cross-correlation. The CMC results were fairly accurate across all muscles (gluteus medius, rectus femoris, vastus lateralis, adductor longus, semitendinosus, tibialis anterior, gastrocnemius, peroneus longus) with correlation coefficients greater than 0.5. There was no apparent relationship between movement type and coefficient. Future work is needed to determine if correlation coefficients of 0.5 are accurate enough for studies looking to accurately quantify joint contact forces.

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