Purpose: The kinematic benefits of arm swing during running for upper body stability have been previously investigated, while its role in metabolic energy efficiency remains controversial. To address this, this study aimed to test the hypothesis that active arm swing during running reduces both torso angular motion around the longitudinal axis and metabolic energy consumption. Methods: We employed forward dynamics musculoskeletal running simulations with different arm conditions to investigate the hypothesis. Full-body musculoskeletal running models, incorporating 150 muscles, were developed using artificial neural network-based running controllers. Three arm conditions were simulated using the running models and controllers: active arm swing, passive arm swing, and fixed arms. Results: Our results revealed that the active arm swing model demonstrated the lowest total metabolic energy consumption per traveling distance. The costs of transport were 5.52, 5.73, and 5.82 J/kg-m for active, passive, and fixed arm models, respectively. Interestingly, while metabolic energy consumption in the upper limb muscles was higher during active arm swing, the total energy consumption was lower. Additionally, the longitudinal rotation of the torso was minimal in the active arm swing condition. Conclusion: These findings support our hypothesis, demonstrating that active arm swing during running reduces the angular motion of the torso and the metabolic energy consumption. This study provides evidence that arm swing during running is performed actively as an energy-saving mechanism. These results contribute to understanding of running biomechanics and may have implications for performance optimization in sports and rehabilitation settings.
KSP Keywords
Artificial Neural Network, Energy efficiency, Forward dynamics, Metabolic energy, Network-based, Performance Optimization, Running biomechanics, Total energy consumption, Upper Limb, Upper body, and rehabilitation
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