RT info:eu-repo/semantics/article
T1 Generating vertical ground reaction forces using a stochastic data-driven model for pedestrian walking
A1 Magdaleno González, Álvaro
A1 García Terán, José María
A1 Pelaez Rodríguez, César
A1 Fernández Ordóñez, Guillermo
A1 Lorenzana Ibán, Antolín
K1 Human loading
K1 Walking load model
K1 Stochastic data-driven model
K1 Virtual GRF
K1 33 Ciencias Tecnológicas
AB A novel time-domain approach to the characterization of the forces induced by a pedestrian is proposed.It focuses on the vertical component while walking, but thanks to how it is conceived, the algorithm canbe easily adapted to other activities or any other force component. The work has been developed fromthe statistical point of view, so a stochastic data-driven model is finally obtained after the algorithm isapplied to a set of experimentally measured steps. The model is composed of two mean vectors and theircorresponding covariance matrices to represent the steps, as well as some more means and standard deviationsto account for the step scaling and double support phase, under the assumption that the random variablesfollow normal distributions. Velocity and step length are also provided, so the model and the latter data enablethe realistic generation of virtual gaits. Some application examples at different walking paces are shown, inwhich comparisons between the original steps and a set of virtual ones are performed to show the similaritiesbetween both. For reproducibility purposes, the data and the developed algorithm have been made available
PB Elsevier
SN 1877-7503
YR 2025
FD 2025
LK https://uvadoc.uva.es/handle/10324/76284
UL https://uvadoc.uva.es/handle/10324/76284
LA eng
NO Journal of Computational Science, 2025, vol. 88, p. 102602
NO Producción Científica
DS UVaDOC
RD 25-jul-2025