Realistic Walking Research Articles

In-plane density gradation of shoe midsoles for optimal energy absorption performance

Midsoles are important components in footwear as they provide shock absorption and stability, thereby improving comfort and effectively preventing certain foot injuries. A strategically engineered midsole designed to mitigate plantar pressure can enhance athletic performance and comfort levels. Despite the importance of midsole design, the potential of using in-plane density gradation (deliberate variation of material density across the horizontal plane) in midsoles has been rarely explored. The present work investigated the effectiveness of in-plane density gradation in shoe midsoles using novel polyurea foams as the material candidate. Different polyurea foam densities, ranging from 95 to 350 kg/m2 were examined and tested to construct density-dependent correlative mathematical relations required for optimizing the midsole design for enhanced cushioning and reduced weight. This study combined mechanical testing and plantar pressure measurements to validate the efficacy of density-graded midsoles. The methodology introduced here is relevant to realistic walking conditions, ensured by biomechanical tests supplemented by digital image correlation analyses. An optimization framework was then created to allocate foam densities at certain plantar zones based on the required cushioning performance constrained by the local pressure. The optimization algorithm was specifically tailored to accommodate varying local pressures experienced by different areas of the foot. The optimization strategy in this study aimed at reducing the overall weight of the midsole while ensuring there were no compromises in cushioning efficacy or distribution of plantar pressure. The approach presented herein has the potential to be applied to a wide range of gait speeds and user-specific plantar pressure patterns.

A study on contaminant leakage from Airborne Infection Isolation room during medical staff entry; Implementation of walking motion on hypothetical human model in CFD simulation

The recent outbreak of respiratory infectious diseases such as Middle East Respiratory Syndrome (MERS) and Coronavirus Disease-19 (COVID-19) highlights the critical role of Air Infection Isolation (AII) rooms in preventing the spread of disease. However, the risk of contaminant leakage from the AII room during medical staff interactions remains a significant challenge. This study advances our understanding by employing Computational Fluid Dynamics (CFD) simulations with a novel approach. While CFD simulations mitigate some limitations of field experiments, such as measurement resolution and variable changes, their accuracy is often limited by the oversimplification of models, particularly in representing human models and movement. Unlike prior studies, we incorporate minimal simplification, featuring a human model with Personal Protective Equipment (PPE) and realistic walking motions. This study explores four distinct scenarios with varied human movements, offering a comprehensive analysis of airflow and contaminant dispersion in AII rooms. The results indicated significant differences in airflow patterns and contaminant distribution when realistic walking motion was implemented in the human model, as opposed to simplified movement models. The contaminant leakage from the AII room ranged from 20.6 % to 28.6 %, suggesting that prior studies may underestimate infection risks due to oversimplified human models and motions. These findings underscore the importance of implementing realistic human models and motions in CFD simulations for accurate infection risk assessment in AII rooms. Additionally, our study opens pathways for future research to explore more complex human interactions in clinical settings, enhancing infection control strategies.

Single-leg stance on a challenging surface can enhance cortical activation in the right hemisphere – A case study

Maintaining body balance, whether static or dynamic, is critical in performing everyday activities and developing and optimizing basic motor skills. This study investigates how a professional alpine skier's brain activates on the contralateral side during a single-leg stance. Continuous-wave functional near-infrared spectroscopy (fNIRS) signals were recorded with sixteen sources and detectors over the motor cortex to investigate brain hemodynamics. Three different tasks were performed: barefooted walk (BFW), right-leg stance (RLS), and left-leg stance (LLS). The signal processing pipeline includes channel rejection, the conversation of raw intensities into hemoglobin concentration changes using modified Beer-Lambert law, baseline zero-adjustments, z-normalization, and temporal filtration. The hemodynamic brain signal was estimated using a general linear model with a 2-gamma function. Measured activations (t-values) with p-value <0.05 were only considered as statistically significant active channels. Compared to all other conditions, BFW has the lowest brain activation. LLS is associated with more contralateral brain activation than RLS. During LLS, higher brain activation was observed across all brain regions. The right hemisphere has comparatively more activated regions-of-interest. Higher ΔHbO demands in the dorsolateral prefrontal, pre-motor, supplementary motor cortex, and primary motor cortex were observed in the right hemisphere relative to the left which explains higher energy demands for balancing during LLS. Broca's temporal lobe was also activated during both LLS and RLS. Comparing the results with BFW– which is considered the most realistic walking condition–, it is concluded that higher demands of ΔHbO predict higher motor control demands for balancing. The participant struggled with balance during the LLS, showing higher ΔHbO in both hemispheres compared to two other conditions, which indicates the higher requirement for motor control to maintain balance. A post-physiotherapy exercise program is expected to improve balance during LLS, leading to fewer changes to ΔHbO.

Realistic walking experience for system-automated virtual reality tour

Realistic walking experience for system-automated virtual reality tour

A three-dimensional whole-body model to predict human walking on level ground

Predictive simulation of human walking has great potential in clinical motion analysis and rehabilitation engineering assessment, but large computational cost and reliance on measurement data to provide initial guess have limited its wide use. We developed a computationally efficient model combining optimization and inverse dynamics to predict three-dimensional whole-body motions and forces during human walking without relying on measurement data. Using the model, we explored two different optimization objectives, mechanical energy expenditure and the time integral of normalized joint torque. Of the two criteria, the sum of the time integrals of the normalized joint torques produced a more realistic walking gait. The reason for this difference is that most of the mechanical energy expenditure is in the sagittal plane (based on measurement data) and this leads to difficulty in prediction in the other two planes. We conclude that mechanical energy may only account for part of the complex performance criteria driving human walking in three dimensions.

Neural model generating klinotaxis behavior accompanied by a random walk based on C. elegans connectome

Klinotaxis is a strategy of chemotaxis behavior in Caenorhabditis elegans (C. elegans), and random walking is evident during its locomotion. As yet, the understanding of the neural mechanisms underlying these behaviors has remained limited. In this study, we present a connectome-based simulation model of C. elegans to concurrently realize realistic klinotaxis and random walk behaviors and explore their neural mechanisms. First, input to the model is derived from an ASE sensory neuron model in which the all-or-none depolarization characteristic of ASEL neuron is incorporated for the first time. Then, the neural network is evolved by an evolutionary algorithm; klinotaxis emerged spontaneously. We identify a plausible mechanism of klinotaxis in this model. Next, we propose the liquid synapse according to the stochastic nature of biological synapses and introduce it into the model. Adopting this, the random walk is generated autonomously by the neural network, providing a new hypothesis as to the neural mechanism underlying the random walk. Finally, simulated ablation results are fairly consistent with the biological conclusion, suggesting the similarity between our model and the biological network. Our study is a useful step forward in behavioral simulation and understanding the neural mechanisms of behaviors in C. elegans.

Finite element modeling of an energy storing and return prosthetic foot and implications of stiffness on rollover shape.

Energy storing and return (ESAR) prosthetic feet showed continuous improvements during the last 30 years. Despite this, standard guidelines are still missing to achieve an optimal foot design in terms of performances. One of the most important design parameters in ESAR feet is the Rollover Shape (RoS). This represents the foot Center of Pressure (CoP) path in a shank-based coordinate system during stance. RoS objectively describes the foot behavior according to its stiffness, which depends on foot geometry and material. This work presents the development of a finite element modeling methodology able to predict the stiffness characteristic of an ESAR foot and its RoS. The validation of the model is performed on a well-known commercially available prosthetic foot both in bench tests and realistic walking scenario. The obtained results confirm an error of +6.1% on stiffness estimation and +10.2% on RoS evaluation, which underlines that the proposed method is a powerful tool able to replicate the mechanical behavior of a prosthetic foot.

A Mechanical Descriptor of Instability in Human Locomotion: Experimental Findings in Control Subjects and People with Transfemoral Amputation

While multiple criteria to quantify gait instability exist, some limitations hinder their computation during realistic walking conditions. A descriptor, computed as the distance between the center of mass of the body and the minimal moment axis ( d C O M − Δ ) , has been proposed recently. This present study aims at characterizing the behavior of the mentioned descriptor in a population at a higher risk of falls. Five individuals with transfemoral amputation and 14 healthy individuals were involved in an experiment composed of motion capture and force plates acquisition during overground walking at a self-selected speed. For both groups of participants, the profile of d C O M − Δ was analyzed and descriptive parameters were calculated. The plot of d C O M − Δ was different between groups and different relative to the leading limb considered (prosthetic or contralateral). All descriptive parameters calculated, except one, were statistically different between groups. As a conclusion, amputees seem to be able to limit the average of d C O M − Δ in spite of a different evolution pattern. This is consistent with the ability of the subjects to maintain their dynamic balance. However, the extracted parameters showed the significant asymmetry of the gait profile between prosthetic and contralateral stances and highlighted the potential sources of imbalance.

VIVR: Presence of Immersive Interaction for Visual Impairment Virtual Reality

The immersive virtual reality (VR) to provide a realistic walking experience for the visually impaired is proposed in this study. To achieve this, a novel immersive interaction using a walking aid, i.e., a white cane, is designed. The key structure of the proposed interaction consists of a walking process that enables users with visual impairments to process the ground recognition and inference processes realistically by connecting the white cane to the VR controller. Additionally, a decision-making model using deep learning is proposed to design interactions that can be applied to real-life situations instead of being limited to virtual environment experiences. A learning model is designed that can accurately and efficiently process sensing of braille block, which is an important process in the walking of visually impaired people using a white cane assistance tool. The goal is to implement a white cane walking system that can be used in the real world in addition to a virtual environment. Finally, a survey is conducted to confirm that the proposed immersive interaction provides a walking experience with high presence in virtual reality when compared with the real-world experience. The applicability of the proposed deep-learning-based decision-making model in the real world is verified by its high accuracy in recognition of braille block.

Vibration serviceability assessment of office floors for realistic walking and floor layout scenarios: Literature review

Over the last two decades, office floors have been built progressively lightweight with increasing spans and slenderness. Therefore, vibration performance of office floors due to walking dynamic loads is becoming their governing design criterion, determining their size and shape, and therefore overall weight and embodied energy of the building. To date, floor design guidelines around the world recommend walking load scenarios in offices featuring some or all of the following standard characteristics: (a) walking loads are assumed to be periodic dynamic excitation represented by the Fourier series, including harmonics corresponding to up to the first four integer multiples of the pacing frequency of which at least one is exciting the floor at a resonant frequency and (b) single person walking. However, the literature surveyed provides evidence that such assessment methodology is potentially an over-simplification which does not reflect real walking load scenarios, since crucial features of the floor vibration source, path and receiver are missing. First, in terms of vibration source, realistic scenarios need to feature (a) moving rather than stationary walking forces, (b) stochastic nature of human gait, (c) simultaneous multi-person walking and (d) human–structure interaction. Second, for the transmission path (i.e. office floor structure), two features are needed to consider: (a) realistic office floor layouts and (b) presence, or absence, of non-structural elements. Finally, for the vibration receivers (i.e. floor occupants), (a) vibrations calculated at floor locations occupied by users (instead of at the potential highest response location which may not be occupied), (b) actual period over which occupants feel vibration due to such excitation and (c) assessment of vibration levels based on their probability of occurrence. This study therefore addresses these seldom considered but increasingly important features and discusses realistic approaches to floor design for vibration serviceability.

Indoor particle inhalability of a stationary and moving manikin

Understanding particle inhalation caused by human activity is vital for developing estimates of inhalation exposure in indoor environments. This study used Computational Fluid Dynamics to compare nasal aspiration efficiency of a stationary manikin in uniform airflow and a moving manikin in stagnant air. The model was a full-scale body with detailed facial features at the nose. The stationary manikin case adopted a constant freestream velocities of 0.2 m/s and 0.4 m/s representing typical office wind environments; while the moving manikin case considered a walking speed of 0.4 m/s as a comparison case, followed with additional higher walking speeds (0.8 m/s and 1.6 m/s) to investigate realistic walking scenarios. Inhalation rates through the nose included light and medium breathing at 15 and 27 L per minute.The aspiration efficiency (AE) was used to quantify the nasal particle inhalability from an upstream release source. In order to evaluate the inhalability for the moving manikin, a 3-dimensional particle source was created and validated with a 2-dimensional particle source, which was common in studies for stationary manikins. Discrepancies in aspiration efficiencies were quantified between using 2- and 3-dimensional particle sources. The particle inhalability for a moving manikin was estimated for three particle sizes and three walking speeds. The inhalability of a walking manikin was found higher than a stationary manikin facing the wind, less relevant to particle sizes but more related to walking speeds. This study quantified the particle inhalability for moving manikins to characterise a more comprehensive scenario for modelling human respiration and developing estimations of particle exposure.

Combined predisposed preferences for colour and biological motion make robust development of social attachment through imprinting.

To study how predisposed preferences shape the formation of social attachment through imprinting, newly hatched domestic chicks (Gallus gallus domesticus) were simultaneously exposed to two animations composed of comparable light points in different colours (red and yellow), one for a walking motion and another for a linear motion. When a walking animation in red was combined with a linear one in yellow, chicks formed a learned preference for the former that represented biological motion (BM). When the motion-colour association was swapped, chicks failed to form a preference for a walking in yellow, indicating a bias to a specific association of motion and colour. Accordingly, experiments using realistic walking chicken videos revealed a preference for a red video over a yellow one, when the whole body or the head was coloured. On the other hand, when the BM preference had been pre-induced using an artefact moving rigidly (non-BM), a clear preference for a yellow walking animation emerged after training by the swapped association. Even if the first-seen moving object was a nonbiological artefact such as the toy, the visual experience would induce a predisposed BM preference, making chicks selectively memorize the object with natural features. Imprinting causes a rapid inflow of thyroid hormone in the telencephalon leading to the induction of the BM preference, which would make the robust formation of social attachment selectively to the BM-associated object such as the mother hen.

Rapid predictive simulations with complex musculoskeletal models suggest that diverse healthy and pathological human gaits can emerge from similar control strategies

Physics-based predictive simulations of human movement have the potential to support personalized medicine, but large computational costs and difficulties to model control strategies have limited their use. We have developed a computationally efficient optimal control framework to predict human gaits based on optimization of a performance criterion without relying on experimental data. The framework generates three-dimensional muscle-driven simulations in 36 min on average—more than 20 times faster than existing simulations—by using direct collocation, implicit differential equations and algorithmic differentiation. Using this framework, we identified a multi-objective performance criterion combining energy and effort considerations that produces physiologically realistic walking gaits. The same criterion also predicted the walk-to-run transition and clinical gait deficiencies caused by muscle weakness and prosthesis use, suggesting that diverse healthy and pathological gaits can emerge from the same control strategy. The ability to predict the mechanics and energetics of a broad range of gaits with complex three-dimensional musculoskeletal models will allow testing novel hypotheses about gait control and hasten the development of optimal treatments for neuro-musculoskeletal disorders.

시각 장애인 가상현실 체험 환경을 위한 딥 러닝을 활용한 몰입형 보행 상호작용 설계

In this study, a novel virtual reality (VR) experience environment is proposed for enabling walking adaptation of visually impaired people. The core of proposed VR environment is based on immersive walking interactions and deep learning based braille blocks recognition. To provide a realistic walking experience from the perspective of visually impaired people, a tracker-based walking process is designed for determining the walking state by detecting marching in place, and a controller-based VR white cane is developed that serves as the walking assistance tool for visually impaired people. Additionally, a learning model is developed for conducting comprehensive decision-making by recognizing and responding to braille blocks situated on roads that are followed during the course of directions provided by the VR white cane. Based on the same, a VR application comprising an outdoor urban environment is designed for analyzing the VR walking environment experience. An experimental survey and performance analysis were also conducted for the participants. Obtained results corroborate that the proposed VR walking environment provides a presence of high-level walking experience from the perspective of visually impaired people. Furthermore, the results verify that the proposed learning algorithm and process can recognize braille blocks situated on sidewalks and roadways with high accuracy.

Simple solutions for downslope pipeline walking on elastic-perfectly-plastic soils

Pipeline Walking is a phenomenon that occurs when high pressure and high temperature pipelines experience axial instability over their operational lifetime, and migrate globally in one direction. Existing analytical solutions treat the axial soil response as rigid-plastic but this does not match the response observed in physical model tests. In this paper, the authors develop a new analytical strategy using elastic-perfectly-plastic axial pipe-soil interaction, which leads to more realistic walking rate predictions. The new analytical methodology is benchmarked with a series of Finite Element Analyses (FEA), which constitutes a parametric study performed to test the proposed expressions and improve on the understanding of the influence of axial mobilisation distance.

Robust vibration serviceability assessment of footbridges subjected to pedestrian excitation: strategy and applications

The present paper proposes a strategy for the robust vibration serviceability assessment of footbridges. The response of the footbridge to vertical walking loading is predicted by simulating continuous flows of pedestrians on the structure. In the calculations, both variability in the walking characteristics and human-structure interaction effects are accounted for. Uncertainty in the modal parameters of the footbridge is considered in a multi-interval approach. The resulting range in predicted response levels is subsequently compared to vibration comfort criteria. A case study serves as illustration of the procedure. First, the response of the footbridge is evaluated in a multi-interval assessment showing how the predicted vibration levels are affected by uncertainties. The multi-interval approach allows understanding how uncertainties in the modal parameters of the structure affects the response. Second, the procedure is applied for the design of Tuned Mass Dampers (TMD). The TMD parameters are tuned by solving an optimisation problem such that an effective reduction of the accelerations under realistic walking scenarios is ensured. The total TMD mass is minimised, considered as the determining factor for the cost of the TMD. A higher TMD mass is needed to satisfy the vibration serviceability constraints for higher levels of uncertainty, showing the trade-off between cost and robustness.

Towards Realistic Walk Path Simulation in Automotive Assembly Lines: A Probabilistic Approach

In the last years, automotive production planning has become increasingly time-consuming, since the trend towards mass-customization is currently leading to numerous possible assembly task-sequences within one assembly station. As a consequence of this development, walk paths for assembly operators in a manual assembly line may vary wildly from car to car. An increasing variety of routes, coupled with high requirements for efficiency and working conditions entails a growing demand for realistic walk path planning methods. In practice, walk paths are either planned with pen-and-paper methods or simulated using deterministic motion planning algorithms calculating a two-dimensional trajectory of the worker's Center of Mass. Both methods, however, do not consider gait and its influence on the actual walk path. Furthermore, by applying deterministic simulation approaches, the probabilistic nature of human motion is neglected. As a consequence, actual walk paths can significantly deviate from their corresponding plans. In order to overcome these limitations, this paper presents a two-dimensional motion planner incorporating fine grained information on human gait gathered from 600 000 samples of a probabilistic motion model. Those data points are drawn from a multivariate Gaussian Mixture Model based on real human motion capture data, thus guaranteeing natural human motions. By combining a global motion planner with this motion model, on the one hand, a realistic and collision-free trajectory can be computed in real-time. On the other hand, this novel probabilistic approach contributes to a better prediction quality of planning models by enabling production planning departments not only to calculate one valid walk path but to simulate all possible variants.

Comparison of TMD designs for a footbridge subjected to human-induced vibrations accounting for structural and load uncertainties

A vibration serviceability assessment of footbridges is required in design stage to evaluate the response to human-induced excitation. If the calculated response does not meet the desired criteria for vibration comfort, a Tuned Mass Damper (TMD) can be installed as a vibration mitigation device. The TMD mass, stiffness and damping constant must be tuned to the modal parameters of the structure to obtain the desired response reduction.The response prediction and TMD design rely on a good knowledge of the modal parameters of the footbridge and usually assume that the response is governed by a perfect harmonic loading causing resonance. Differences between the predicted and actual modal parameters may lead to both an unreliable response prediction and a suboptimal TMD performance. Therefore, a robust design of the TMD is proposed accounting for uncertainties in the modal parameters. Realistic walking scenarios of continuous pedestrian traffic are simulated to obtain an effective response reduction by the TMD.In this contribution, the robust design of a TMD is demonstrated for a slender footbridge accounting for reasonable levels of uncertainties in the modal parameters. Numerical optimisation is therefore applied and vibration serviceability requirements are imposed as design constraints. The obtained TMD parameters are compared to those obtained from the formulae proposed by Asami, determining the stiffness and damping constant as a function of its mass. It is found that the TMD mass can be further reduced when the TMD parameters are tuned independently from each other compared to the classical design according to Asami but a higher computation cost is needed. Furthermore, an increasing degree of robustness against variations in the modal parameters is obtained by increasing the TMD mass and damping.

Detection of moving human micro‐Doppler signature in forest environments with swaying tree components by wind

AbstractThe objective of this paper is to investigate human motion in forest medium with swaying tree components due to time‐varying wind effects and to observe the characteristics of the received Doppler signature from the scene. We provide the results of an accurate model accounting for the key contributions to the Doppler signature in this scenario. A realistic walking motion is generated using an analytical model extracted from empirical data. The swaying canopy motion is modeled by employing a spring response mechanism to the wind force. The backscattered field calculations from the scene comprise of contributions from the forest (including trunks, branches, and the ground) and human, and the interactions between them. An analytical forest scattering model, which accounts for the ground effects, is used to calculate the contribution from the forest. The attenuation effects due to the vegetation are accounted for. In order to characterize the effects of human motion accurately, a full wave technique, namely, method of moments (MOM) enhanced with fast multipole method (FMM), is employed for the human scattering calculations. A parallel version of MOM‐FMM is implemented on a graphics processing unit based cluster to handle the large problem size. The human walking signatures created by the model are analyzed for different winds.

Kinesthetic Force Feedback and Belt Control for the Treadport Locomotion Interface.

This paper describes an improved control system for the Treadport immersive locomotion interface, with results that generalize to any treadmill that utilizes an actuated tether to enable self-selected walking speed. A new belt controller is implemented to regulate the user's position; when combined with the user's own volition, this controller also enables the user to naturally self-select their walking speed as they would when walking over ground. A new kinesthetic-force-feedback controller is designed for the tether that applies forces to the user's torso. This new controller is derived based on maintaining the user's sense of balance during belt acceleration, rather than by rendering an inertial force as was done in our prior work. Based on the results of a human-subjects study, the improvements in both controllers significantly contribute to an improved perception of realistic walking on the Treadport. The improved control system uses intuitive dynamic-system and anatomical parameters and requires no ad hoc gain tuning. The control system simply requires three measurements to be made for a given user: the user's mass, the user's height, and the height of the tether attachment point on the user's torso.