DVS Edition Citation

Patoz, A, Lussiana, T, Breine, B, Grindre, C & Malatesta, D. (2025). Comparison of different machine learning models to enhance sacral acceleration-based estimations of running stride temporal variables and peak vertical ground reaction force. Sports Biomechanics, 24 (4), 825-841. Zugriff am 18.11.2023 unter https://doi.org/10.1080/14763141.2022.2159870

APA (7th ed.) Citation

Patoz, A., Lussiana, T., Breine, B., Grindre, C., & Malatesta, D. (2025). Comparison of different machine learning models to enhance sacral acceleration-based estimations of running stride temporal variables and peak vertical ground reaction force. Sports Biomechanics, 24(4), 825-841.

Chicago Style (17th ed.) Citation

Patoz, A., T. Lussiana, B. Breine, C. Grindre, and D. Malatesta. "Comparison of Different Machine Learning Models to Enhance Sacral Acceleration-based Estimations of Running Stride Temporal Variables and Peak Vertical Ground Reaction Force." Sports Biomechanics 24, no. 4 (2025): 825-841.

MLA (9th ed.) Citation

Patoz, A., et al. "Comparison of Different Machine Learning Models to Enhance Sacral Acceleration-based Estimations of Running Stride Temporal Variables and Peak Vertical Ground Reaction Force." Sports Biomechanics, vol. 24, no. 4, 2025, pp. 825-841.