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  • Title: An EMG-to-Force Processing Approach to Estimating Knee Muscle Forces during Adult, Self-Selected Speed Gait.
    Author: Bogey R.
    Journal: Bioengineering (Basel); 2023 Aug 20; 10(8):. PubMed ID: 37627865.
    Abstract:
    BACKGROUND: The purpose of this study was to determine the force production during self-selected speed normal gait by muscle-tendon units that cross the knee. The force of a single knee muscle is not directly measurable without invasive methods, yet invasive techniques are not appropriate for clinical use. Thus, an EMG-to-force processing (EFP) model was developed which scaled muscle-tendon unit (MTU) force output to gait EMG. METHODS: An EMG-to-force processing (EFP) model was developed which scaled muscle-tendon unit (MTU) force output to gait EMG. Active muscle force power was defined as the product of MTU forces (derived from EFP) and that muscle's contraction velocity. Net knee EFP moment was determined by summing individual active knee muscle moments. Net knee moments were also calculated for these study participants via inverse dynamics (kinetics plus kinematics, KIN). The inverse dynamics technique used are well accepted and the KIN net moment was used to validate or reject this model. Closeness of fit of the moment power curves for the two methods (during active muscle forces) was used to validate the model. RESULTS: The correlation between the EFP and KIN methods was sufficiently close, suggesting validation of the model's ability to provide reasonable estimates of knee muscle forces. CONCLUSIONS: The EMG-to-force processing approach provides reasonable estimates of active individual knee muscle forces in self-selected speed walking in neurologically intact adults.
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