The introduction of resistant and lightweight materials in the construction industry has led to civil structures being vulnerable to excessive vibrations, particularly in footbridges exposed to human-induced gait loads. This interaction, known as Human–Structure Interaction (HSI), involves a complex interplay between structural vibrations and gait loads. Despite extensive research on HSI, the simultaneous effects of lateral structural vibrations with fundamental frequencies close to human gait frequency (around 1.0 Hz) and wide amplitudes (over 30.0 mm) remain inadequately understood, posing a contemporary structural challenge highlighted by incidents in iconic bridges like the Millennium Bridge in London, Solferino Bridge in Paris, and Premier Bridge in Cali, Colombia. This paper focuses on the experimental exploration of Structure-to-Human Interaction (S2HI) effects using the Human–Structure Interaction Multi-Axial Test Framework (HSI-MTF). The framework enables the simultaneous measurement of vertical and lateral loads induced by human gait on surfaces with diverse frequency ranges and wide-amplitude lateral harmonic motions. The study involved seven test subjects, evaluating gait loads on rigid and harmonic lateral surfaces with displacements ranging from 5.0 to 50.0 mm and frequency content from 0.70 to 1.30 Hz. A low-cost vision-based motion capture system with smartphones analyzed the support (T_su) and swing (T_sw) periods of human gait. Results indicated substantial differences in T_su and T_sw on lateral harmonic protocols, reaching up to 96.53% and 58.15%, respectively, compared to rigid surfaces. Normalized lateral loads (L_L) relative to the subject’s weight (W₀) exhibited a linear growth proportional to lateral excitation frequency, with increased proportionality constants linked to higher vibration amplitudes. Linear regressions yielded an average R² of 0.815. Regarding normalized vertical load (L_V) with respect to W₀, a consistent behavior was observed for amplitudes up to 30.0 mm, beyond which a linear increase, directly proportional to frequency, resulted in a 28.3% increment compared to rigid surfaces. Correlation analyses using Pearson linear coefficients determined relationships between structural surface vibration and pedestrian lateral motion, providing valuable insights into Structure-to-Human Interaction dynamics.

This study assessed the accuracy of a low-cost marker-based motion capture system with smartphone devices to estimate the spatiotemporal behavior of human gait in comparison with the performance of the commercial OptiTrack system. Initially, three test subjects were selected for the study, and after equipping them with passive retroreflective markers, they were recorded for gait velocities of 1.50, 1.90, and 2.30 $$m\bullet {s}^{-1}$$ m ∙ s - 1 while collecting kinematic data and videos. The results showed that the smartphone motion capture system exhibited significant spatiotemporal tracking and accuracy in the x-y trajectories and estimation of joint relative angles of the hip, knee, and ankle joints (θ₁, θ₂, and θ₃, respectively) compared to the commercial OptiTrack system. In this comparison, an average goodness-of-FIT and normalized root mean square error of over 88.93% and 2.71% were obtained, respectively, for the joint relative angles of the hip and knee (θ₁ and θ2) in all tests performed. However, the accuracy of the joint relative angle of the ankle (θ3, average FIT: 71.04% and nRMSE: 4.26%) was lower because of the low capture rate of the retroreflective markers in the smartphone system and the higher relative velocity in the lower extremities of the test subjects, which generated noise in the calculation of x-y trajectories. This decrease in accuracy has been reported in other studies. However, both motion capture systems experienced marker data loss at the hip, highlighting the need for improvement in the spatial distribution of the optical devices. The OptiTrack system demonstrated better optical redundancy but still required improvements. In contrast, the smartphone system, with its inherent limitations in terms of optical redundancy and spatial distribution, can be enhanced by incorporating multiple cameras for a three-dimensional view. Despite these limitations, the low-cost smartphone system showed optimal performance with minimal errors compared with the commercial system, making it a cost-effective option with potential for further development. The rapid advancement of smartphone technology and its accessibility make it an attractive choice for motion capture applications.

The dynamic performance of base isolation systems provides an effective means to reduce the seismic vulnerability of buildings. However, large displacements in the base isolation during seismic events pose a major challenge for this control system. Recently, novel control systems have been implemented to control and reduce the excessive displacements. This study presents an evaluation of the seismic performance of unconnected‐fiber‐reinforced elastomeric isolators (U‐FREI) and variable orifice damper (VOD) devices used together as a hybrid control system for a low‐degree‐of‐freedom reference structure by employing real‐time hybrid simulation (RTHS) testing technique. This physical cybernetic testing methodology allows a dynamic system of interest to be substructured into two components: numerical and experimental. In this study, the numerical substructure corresponds to a 2‐degree of freedom model, representing a reference structure, and an experimental substructure was formed using the hybrid control system described. To develop an interface between the two substructures, a horizontal transfer system (HTS) was implemented and coupled with a vertical transfer system (VTS). Using RTHS, the performance of the reference structure and the hybrid control system was evaluated under six seismic events: CAM, CAT, El Centro, Loma Prieta, Pizarro, and Chihuahua, at a maximum acceleration of 0.10 g (0.981 m·s⁻²). The experimental behavior of the hybrid control system allows the reference structure to reduce its maximum drift by more than 24% compared to the fixed structure. Finally, the performance and accuracy of the RTHS tests were calculated.

Pedestrian bridges, which are essential in urban and rural infrastructures, are vulnerable to vibrations induced by pedestrian traffic owing to their low mass, stiffness, and damping. This paper presents a novel predictive model of Human-Structure Interaction (HSI) that integrates a three-dimensional biomechanical model of the human body, and a pedestrian bridge represented as a simply supported Euler-Bernoulli beam. Using inverse dynamics, the human model accurately captures three-dimensional gait and its interaction with structural vibrations. The results show that this approach provides precise estimates of human gait kinematics and kinetics, as well as the bridge response under pedestrian loads. The incorporation of a three-dimensional human gait model reflects the changes induced by bridge vibrations, providing a robust tool for evaluating and improving the effect of structural vibrations on the properties and gait patterns.

Many modern pedestrian bridges exhibit flexibility and susceptibility to vibrations due to the use of lightweight and high‐strength materials, which can cause discomfort for pedestrians and affect their serviceability. Although gait biomechanics have been extensively studied and optimisation techniques for gait prediction on rigid surfaces have been previously employed, there is a paucity of studies investigating the effects of human‐structure interaction on pedestrian crossings over flexible structures. In this study, inverse dynamics and optimisation techniques were employed to predict human gait on a flexible structure in the sagittal plane. Gait was formulated as an optimal motor task subject to multiple constraints, with the performance criterion being the minimization of mechanical energy expenditure throughout a complete gait cycle. Segmental movements, pedestrian‐applied forces, and bridge vibrations were predicted based on parameters describing gait (such as gait speed, gait frequency, and double support duration), as well as physical and dynamic parameters characterizing the pedestrian bridge (including natural frequency, damping coefficient, and bridge length).