In practice, the structural analysis and design of pedestrian systems subjected to human-induced vibrations is often based on simplified biodynamic models that can be used in place of even more complex computational strategies to describe Human-Structure Interaction (HSI) phenomena. Among various walking features, the vertical reaction force that a pedestrian transfers to the supporting structure during motion is a key input for design, but results from the combination of multiple influencing parameters and dynamic interactions. Robust and practical strategies to support a realistic HSI description and analysis have hence been the object of several studies. Following earlier research efforts, this paper focuses on the optimised calibration of the input parameters for the consolidated Spring-Mass-Damper (SMD) biodynamic model, which reduces a single pedestrian to an equivalent SDOF (with body mass m, spring stiffness k, and viscous damping coefficient c) and is often used for vibration serviceability purposes. In the present study, this calibration process is carried out with smartphone-based acquisitions and experimental records from the Centre of Mass (CoM) of each pedestrian to possibly replace more complex laboratory configurations and devices. To verify the potential and accuracy of such a smartphone-based approach, different pedestrians/volunteers and substructures (i.e., a rigid concrete slab or a timber floor prototype) are taken into account, and a total of 145 original gaits are post-processed for SMD modelling purposes. The analysis of the experimental results shows a rather close match with previous findings in terms of key pedestrian parameters. This outcome poses the basis for a more generalised application of the smartphone-based strategy to a multitude of similar applications and configurations of practical interest. The validity of calibration output and its possible sensitivity are further assessed in terms of expected effects on substructures, with a critical discussion of the most important results.
