The file associated with this record is under a permanent embargo in accordance with the publisher's policy on archiving final published versions, available on the SHERPA/RoMEO website. It is not available to read.Although many models of pedestrian dynamic loading have been proposed, possible bidirectional interactions between the walker and the excited structure are generally ignored, particularly for vertical vibrations. This shortcoming has arisen from scarcity of data on gait-adaptation strategies used in the presence of structural motion and, as a consequence, the absence of a credible fundamental pedestrian model capable of capturing the underlying relations between the two dynamic systems. To address this inadequacy of current approaches, a biomechanically inspired inverted-pendulum pedestrian model has been applied to the human-structure interaction problem. The behavior of the model is studied when subjected to vertical motion of the supporting structure, in particular, in relation to potential self-excited forces that can be generated. A mechanism has been identified by which the timing of pedestrian footsteps can be altered subtly, giving a net damping effect on the structure, without necessarily involving full synchronization. It has been found that depending on the ratio between the bridge vibration frequency and pedestrian pacing frequency, walkers can effectively act as positive or negative dampers to the structural motion, but it is expected that for a group of pedestrians with distributed parameters, their action is, on average, to add damping and mass.\ud \ud \ud Read More: http://ascelibrary.org/doi/abs/10.1061/(ASCE)BE.1943-5592.0000490Peer-reviewedPublisher Versio

The file associated with this record is under embargo until 12 months after publication, in accordance with the publisher's self-archiving policy. The full text may be available through the publisher links provided above.Bridge failure to pass load capacity assessment is unfortunately not an uncommon problem in bridge engineering and it is a potentially expensive problem for the bridge owner. Using load test data to justify increase in assessed load capacity is recognised as a viable approach in professional codes of practice. However, load tests are rarely carried out in practice because traditionally they are expensive to conduct and may not always justify an increase in assessed load capacity. Therefore this paper proposes a simple, quick and reliable approach for bridge load testing. In particular a procedure to calculate the bridge displacement to a moving truck by double integration of bridge acceleration is presented. Integrating acceleration to calculate displacement is not a new approach, with authors reporting difficulties due to errors in acceleration signals and unknown initial conditions. Many of the previous approaches have focused on developing signal processing algorithms to correct for the signal errors and while some good results have been reported, typically the derived displacements are very sensitive to parameters used in the correction algorithm, such as passband filter frequencies. Consequently, without comparison with directly measured displacement data, reliability of the procedure cannot be established and errors quantified. Therefore in this study a stripped down procedure is applied placing emphasis instead on minimising the errors in the recorded acceleration by using appropriate hardware and developing a quality control procedure that allows the user to assess the likely accuracy of the calculated displacement signal. The effectiveness of the proposed approach is trialled in the laboratory and in the field, with an accuracy of ±0.5 mm observed.The research leading to these results has received funding from the People Programme (Marie Curie Actions) of the European Union’s Seventh Framework Programme (FP7/2007-2013) under grant agreement n° 330195.Peer-reviewedPost-prin

The pedestrian-induced instability of the London Millennium Bridge is a widely used example of Kuramoto synchronisation. Yet, reviewing observational, experimental, and modelling evidence, we argue that increased coherence of pedestrians’ foot placement is a consequence of, not a cause of the instability. Instead, uncorrelated pedestrians produce positive feedback, through negative damping on average, that can initiate significant lateral bridge vibration over a wide range of natural frequencies. We present a simple general formula that quantifies this effect, and illustrate it through simulation of three mathematical models, including one with strong propensity for synchronisation. Despite subtle effects of gait strategies in determining precise instability thresholds, our results show that average negative damping is always the trigger. More broadly, we describe an alternative to Kuramoto theory for emergence of coherent oscillations in nature; collective contributions from incoherent agents need not cancel, but can provide positive feedback on average, leading to global limit-cycle motion.

Monitoring natural human gait in real-life environment is essential in many applications including the quantification of disease progression, and monitoring the effects of treatment and alteration of performance biomarkers in professional sports. Nevertheless, reliable and practical techniques and technologies necessary for continuous real-life monitoring of gait is still not available. This paper explores in detail the correlations between the acceleration of different body segments and walking ground reaction forces GRF(t) in three dimensions and proposes three sensory systems, with one, two, and three inertial measurement units (IMUs), to estimate GRF(t) in the vertical (V), medial-lateral (ML), and anterior-posterior (AP) directions. The nonlinear autoregressive moving average model with exogenous inputs (NARMAX) non-linear system identification method was utilized to identify the optimal location for IMUs on the body for each system. A simple linear model was then proposed to estimate GRF(t) based on the correlation of segmental accelerations with each other. It was found that, for the three-IMU system, the proposed model estimated GRF(t) with average peak-to-peak normalized root mean square error (NRMSE) of 7%, 16%, and 18% in V, AP, and ML directions, respectively. With a simple subject-specific training at the beginning, these errors were reduced to 7%, 13%, and 13% in V, AP, and ML directions, respectively. These results were found favorably comparable with the results of the benchmark NARMAX model, with subject-specific training, with 0% (V), 4% (AP), and 1% (ML) NRMSE difference.

The Verisense Step Count Algorithm facilitates generation of steps from wrist-worn accelerometers. Based on preliminary evidence suggesting a proportional bias with overestimation at low steps/day, but underestimation at high steps/day, the algorithm parameters have been revised. We aimed to establish validity of the original and revised algorithms relative to waist-worn ActiGraph step cadence. We also assessed whether step cadence was similar across accelerometer brand and wrist. Ninety-eight participants (age: 58.6±11.1 y) undertook six walks (~500 m hard path) at different speeds (cadence: 92.9±9.5–127.9±8.7 steps/min) while wearing three accelerometers on each wrist (Axivity, GENEActiv, ActiGraph) and an ActiGraph on the waist. Of these, 24 participants also undertook one run (~1000 m). Mean bias for the original algorithm was −21 to −26.1 steps/min (95% limits of agreement (LoA) ~±65 steps/min) and mean absolute percentage error (MAPE) 17–22%. This was unevenly distributed with increasing error as speed increased. Mean bias and 95%LoA were halved with the revised algorithm parameters (~-10 to −12 steps/min, 95%LoA ~30 steps/min, MAPE ~10-12%). Performance was similar across brand and wrist. The revised step algorithm provides a more valid measure of step cadence than the original, with MAPE similar to recently reported wrist-wear summary MAPE (7–11%).