Preprint Article Version 1 This version is not peer-reviewed

Simplified Cost Functions Meet Advanced Muscle Models to Streamline Muscle Force Estimation

Version 1 : Received: 11 July 2024 / Approved: 11 July 2024 / Online: 11 July 2024 (13:02:14 CEST)

How to cite: Ahmed, M. H.; N'Guessan, J. E.; Das, R.; Goyal, S.; Leineweber, M. Simplified Cost Functions Meet Advanced Muscle Models to Streamline Muscle Force Estimation. Preprints 2024, 2024070947. https://doi.org/10.20944/preprints202407.0947.v1 Ahmed, M. H.; N'Guessan, J. E.; Das, R.; Goyal, S.; Leineweber, M. Simplified Cost Functions Meet Advanced Muscle Models to Streamline Muscle Force Estimation. Preprints 2024, 2024070947. https://doi.org/10.20944/preprints202407.0947.v1

Abstract

This study explores an optimal strategy for muscle force estimation by integrating simplified cost functions with detailed muscle models, demonstrating significant advantages over traditional complex methods. Using elbow flexion as a case study, we characterize the interplay between muscle models and cost functions, showing that accurate muscle force estimations can be achieved effectively without electromyography (EMG) data while also substantially reducing computational demands. Validated against established bio-mechanical data, our models confirm their accuracy in predicting muscle behavior. This approach has profound implications for enhancing rehabilitation protocols and athletic training, providing a more accessible and adaptable tool for muscle force analysis. It broadens the applicability of muscle force estimation in clinical and sports settings and paves the way for future innovations in bio-mechanical research.

Keywords

computational model; muscle force; cost function; elbow flexion

Subject

Engineering, Mechanical Engineering

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