Tuning in to a hip-hop beat: Pursuit eye movements reveal processing of biological motion.

Smooth pursuit eye movements are mainly driven by motion signals to achieve their goal of reducing retinal motion blur. However, they can also show anticipation of predictable movement patterns. Oculomotor predictions may rely on an internal model of the target kinematics. Most investigations on the nature of those predictions have concentrated on simple stimuli, such as a decontextualized dot. However, biological motion is one of the most important visual stimuli in regulating human interaction and its perception involves integration of form and motion across time and space. Therefore, we asked whether there is a specific contribution of an internal model of biological motion in driving pursuit eye movements. Unlike previous contributions, we exploited the cyclical nature of walking to measure eye movement's ability to track the velocity oscillations of the hip of point-light walkers. We quantified the quality of tracking by cross-correlating pursuit and hip velocity oscillations. We found a robust correlation between signals, even along the horizontal dimension, where changes in velocity during the stepping cycle are very subtle. The inversion of the walker and the presentation of the hip-dot without context incurred the same additional phase lag along the horizontal dimension. These findings support the view that information beyond the hip-dot contributes to the prediction of hip kinematics that controls pursuit. We also found a smaller phase lag in inverted walkers for pursuit along the vertical dimension compared to upright walkers, indicating that inversion does not simply reduce prediction. We suggest that pursuit eye movements reflect the visual processing of biological motion and as such could provide an implicit measure of higher-level visual function.

Stepping up with GGIR: Validity of step cadence derived from wrist-worn research-grade accelerometers using the verisense step count algorithm.

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%).

Normative wrist-worn accelerometer values for self-paced walking and running: a walk in the park.

This study aimed to a) determine whether wrist acceleration varies by accelerometer brand, wear location, and age for self-paced "slow", "normal" and "brisk" walking; b) develop normative acceleration values for self-paced walking and running for adults. One-hundred-and-three adults (40-79 years) completed self-paced "slow", "normal" and "brisk" walks, while wearing three accelerometers (GENEActiv, Axivity, ActiGraph) on each wrist. A sub-sample (n = 22) completed a self-paced run. Generalized estimating equations established differences by accelerometer brand, wrist, and age-group (walking only, 40-49, 50-59, 60-69, 70-79 years) for self-paced walking and running. Brand*wrist interactions showed ActiGraph dominant wrist values were ~10% lower than GENEActiv/Axivity values for walking and running, and non-dominant ActiGraph values were ~5% lower for running only (p < 0.001). Acceleration during brisk walking was lower in those aged 70-79 (p < 0.05). Normative acceleration values (non-dominant wrist, all brands; dominant wrist GENEActiv/Axivity) for slow and normal walking were 140 mg and 210 mg. Brisk walking, values were 350 mg in those aged 40-69 years, but 270 mg in those aged 70-79 years. Accelerations >600 mg approximated running. These values facilitate user-friendly interpretation of accelerometer-determined physical activity in large cohort and epidemiological datasets.

The role of eye movements in perceiving vehicle speed and time-to-arrival at the roadside.

To avoid collisions, pedestrians depend on their ability to perceive and interpret the visual motion of other road users. Eye movements influence motion perception, yet pedestrians' gaze behavior has been little investigated. In the present study, we ask whether observers sample visual information differently when making two types of judgements based on the same virtual road-crossing scenario and to which extent spontaneous gaze behavior affects those judgements. Participants performed in succession a speed and a time-to-arrival two-interval discrimination task on the same simple traffic scenario-a car approaching at a constant speed (varying from 10 to 90 km/h) on a single-lane road. On average, observers were able to discriminate vehicle speeds of around 18 km/h and times-to-arrival of 0.7 s. In both tasks, observers placed their gaze closely towards the center of the vehicle's front plane while pursuing the vehicle. Other areas of the visual scene were sampled infrequently. No differences were found in the average gaze behavior between the two tasks and a pattern classifier (Support Vector Machine), trained on trial-level gaze patterns, failed to reliably classify the task from the spontaneous eye movements it elicited. Saccadic gaze behavior could predict time-to-arrival discrimination performance, demonstrating the relevance of gaze behavior for perceptual sensitivity in road-crossing.

Emergence of the London Millennium Bridge instability without synchronisation.

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.

Performance of Optical Structural Vibration Monitoring Systems in Experimental Modal Analysis.

Image-based optical vibration measurement is an attractive alternative to the conventional measurement of structural dynamics predominantly relying on accelerometry. Although various optical vibration monitoring systems are now readily available, their performance is currently not well defined, especially in the context of experimental modal analysis. To this end, this study provides some of the first evidence of the capability of optical vibration monitoring systems in modal identification using input-output measurements. A comparative study is conducted on a scaled model of a 3D building frame set in a laboratory environment. The dynamic response of the model to an impulse excitation from an instrumented hammer, and an initial displacement, is measured by means of five optical motion capture systems. These include commercial and open-source systems based on laser Doppler velocimetry, fiducial markers and marker-less pattern recognition. The performance of these systems is analysed against the data obtained with a set of high-precision accelerometers. It is shown that the modal parameters identified from each system are not always equivalent, and that each system has limitations inherent to its design. Informed by these findings, a guidance for the deployment of the considered optical motion capture systems is given, aiding in their choice and implementation for structural vibration monitoring.

Gait coordination in overground walking with a virtual reality avatar.

Little information is currently available on interpersonal gait synchronization in overground walking. This is caused by difficulties in continuous gait monitoring over many steps while ensuring repeatability of experimental conditions. These challenges could be overcome by using immersive virtual reality (VR), assuming it offers ecological validity. To this end, this study provides some of the first evidence of gait coordination patterns for overground walking dyads in VR. Six subjects covered the total distance of 27 km while walking with a pacer. The pacer was either a real human subject or their anatomically and biomechanically representative VR avatar driven by an artificial intelligence algorithm. Side-by-side and front-to-back arrangements were tested without and with the instruction to synchronize steps. Little evidence of spontaneous gait coordination was found in both visual conditions, but persistent gait coordination patterns were found in the case of intentional synchronization. Front-to-back rather than side-by-side arrangement consistently yielded in the latter case higher mean synchronization strength index. Although the mean magnitude of synchronization strength index was overall comparable in both visual conditions when walking under the instruction to synchronize steps, quantitative and qualitative differences were found which might be associated with common limitations of VR solutions.

Topological assessment of gait synchronisation in overground walking groups.

Walking is one of the fundamental forms of human gross motor activity in which spatiotemporal movement coordination can occur. While considerable body of evidence already exists on pedestrian movement coordination while walking in pairs, little is known about gait control while walking in more complex topological arrangements. To this end, this study provides some of the first evidence of spontaneous gait synchronisation while walking in a group. Nine subjects covered the total distance of 40 km at different speeds while assembled in a three-by-three formation. Two experimental protocols were applied in which the subjects were either not specifically asked to or specifically asked to synchronise their gait. To obtain results representative from the point of view of gait control, the movement coordination was quantified using the indirectly measured vertical component of ground reaction force, based on output from a network of wireless motion monitors. Bivariate phase difference analysis was conducted using wavelet transform, synchronisation strength measures derived from Shannon entropy, and circular statistics. A fundamental relationship describing the influence of the group walking speed on individuals' pacing frequency was established, showing a positive correlation different from that previously reported for walking in solitude. A positive correlation was found between the average synchronisation strength within a group and group's walking speed. The most persistent coordination patterns were identified for pedestrians walking front-to-back and side-by-side. Overall, the spontaneous gait synchronisation while walking in a group is relatively weak, well below the levels reported for walking in pairs.

Real-Life Measurement of Tri-Axial Walking Ground Reaction Forces Using Optimal Network of Wearable Inertial Measurement Units.

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.

Experimental identification of the behaviour of and lateral forces from freely-walking pedestrians on laterally oscillating structures in a virtual reality environment.

Modelling pedestrian loading on lively structures such as bridges remains a challenge. This is because pedestrians have the capacity to interact with vibrating structures which can lead to amplification of the structural response. Current design guidelines are often inaccurate and limiting as they do not sufficiently acknowledge this effect. This originates in scarcity of data on pedestrian behaviour on vibrating ground and uncertainty as to the accuracy of results from previous experimental campaigns aiming to quantify pedestrian behaviour in this case. To this end, this paper presents a novel experimental setup developed to evaluate pedestrian actions on laterally oscillating ground in the laboratory environment while avoiding the implications of artificiality and allowing for unconstrained gait. A biologically-inspired approach was adopted in its development, relying on appreciation of operational complexities of biological systems, in particular their adaptability and control requirements. In determination of pedestrian forces to the structure consideration was given to signal processing issues which have been neglected in past studies. The results from tests conducted on the setup are related to results from previous experimental investigations and outputs of the inverted pendulum pedestrian model for walking on laterally oscillating ground, which is capable of generating self-excited forces.