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Evaluating Human Gait Simulations Across Diverse Walking Conditions
Computer simulations based on detailed musculoskeletal models reproduce human walking under varied conditions such as incline, load, and speed. By comparing these simulations to experimental gait data, we assess how well they predict real movement and metabolic energy use. The simulations accurately capture overall gait patterns but underestimate metabolic cost—particularly during energetically demanding tasks like uphill walking—due to overly efficient metabolic modeling and overestimated muscle fiber work. Improving these models in the future may help develop more effective assistive devices and therapies for people with movement difficulties. Afschrift et al. 2025
Image Credit: Maarten Afschrift
Citation: (2025) PLoS Computational Biology Issue Image | Vol. 21(11) December 2025. PLoS Comput Biol 21(11): ev21.i11. https://doi.org/10.1371/image.pcbi.v21.i11
Published: December 9, 2025
Copyright: © 2025 . This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Computer simulations based on detailed musculoskeletal models reproduce human walking under varied conditions such as incline, load, and speed. By comparing these simulations to experimental gait data, we assess how well they predict real movement and metabolic energy use. The simulations accurately capture overall gait patterns but underestimate metabolic cost—particularly during energetically demanding tasks like uphill walking—due to overly efficient metabolic modeling and overestimated muscle fiber work. Improving these models in the future may help develop more effective assistive devices and therapies for people with movement difficulties. Afschrift et al. 2025
Image Credit: Maarten Afschrift