Walking Path Research Articles

Vertical back movement of cows during locomotion: detecting lameness with a simple image processing technique.

This research paper proposes a simple image processing technique for automatic lameness detection in dairy cows under farm conditions. Seventy-five cows were selected from a dairy farm and visually assessed for a reference/real lameness score (RLS) as they left the milking parlor, while simultaneously being video-captured. The method employed a designated walking path and video recordings processed through image analysis to derive a new computerized automatic lameness score (ALDS) based on calculated factors from back arch posture. The proposed automatic lameness detection system was calibrated using 12 cows, and the remaining 63 were used to evaluate the diagnostic characteristics of the ALDS. The agreement and correlation between ALDS and RLS were investigated. ALDS demonstrated high diagnostic accuracy with 100% sensitivity and specificity and was found to be 100% accurate with a perfect agreement (ρc = 1) and strong correlation (r = 1, P < 0.001) for lameness detection in binary scores (lame/non-lame). Moreover, the ALDS had a strong agreement (ρc = 0.885) and was highly correlated (r = 0.840; 0.796-1.000 95% confidence interval, P < 0.001) with RLS in ordinal scores (lameness severity; LS1 to LS5). Our findings suggest that the proposed method has the potential to compete with vision-based lameness detection methods in dairy cows in farm conditions.

Maze based image encryption method constructed by random number generation

Due to the large size of image files and the high correlation between the numerical values of the pixels, various improved algorithms have been used for image encryption in recent years. In most cases improvement is obtained by taking into account the characteristics of chaotic and random processes in encryption algorithms. In this study, an algorithm is proposed that encrypts images based on a maze created by keys consisting of random numbers generated with Feigembaum’s quadratic function. For the generation of the maze, deep first search (DFS) algorithm has been used. During the generation with this algorithm, numbers representing the walking paths and as well as the length of the used stack are included in the encryption process. Algorithm security verification was carried out according to key space and differential analysis, statistical analysis such as entropy estimation, and analysis of correlation between the histogram and neighboring pixels of the image.

Placing the leading limb closer to an obstacle reduces collision of the trailing limb: an investigation in a virtual environment.

When walking and stepping over an obstacle of a certain height, tripping occurs more frequently with the trailing limb than the leading limb. The present study was designed to address whether collisions involving the trailing limb can be improved with experimental manipulation of the placement of the leading limb after stepping over an obstacle. We used an immersive, virtual obstacle-crossing task to ensure that the collision was not improved simply due to the experience of physical collision with an obstacle. Fourteen young participants (12 males and 2 females, 28.7 ± 3.5 years) were required to walk and step over a virtual horizontal pole under one of four conditions. In three conditions, participants were required to place their leading foot on a square target located along their walking path after crossing the obstacle. The target was positioned so that it was relatively close to the obstacle (10 cm from the obstacle, referred to hereafter as the closer condition), at a position that would naturally be stepped on in successful trials without a collision (20 cm from the obstacle, the middle condition), or relatively far from the obstacle (40 cm from the obstacle, the farther condition). For the fourth condition, participants were free to select where they would step after stepping over the obstacle (the control condition). The results showed that the collision rate of the trailing limb was significantly lower under the closer condition than under the other three conditions. Compared to the control condition, under the closer condition the movement of the trailing limb was modified so that obstacle crossing was performed at approximately the moment when the height of the toe of the trailing limb was higher, and the walking speed was slower. These findings suggest that placing the foot of the leading limb closer to the obstacle after crossing the obstacle may ensure safe obstacle avoidance by the trailing limb.

Prevalence and correlates of meeting 24-hour movement behavior guidelines among 8523 youth prescribed eyeglasses/contact lenses

BackgroundContemporary 24-h movement behavior (24-HMB) guidelines provide recommendations on time spent on physical activity (PA), screen time (ST), and sleep (SL). There is evidence of physiological and psychological health benefits associated with meeting such guidelines. However, the prevalence of meeting 24-HMB guidelines among youth prescribed eyeglasses/contact lenses is less clear. The primary purpose of this cross-sectional analysis was to examine the prevalence of partially or fully meeting 24-HMB guidelines in U.S. youth prescribed eyeglasses/contact lenses, and variations in meeting the guidelines by demographic, health status, and environmental attributes. MethodsData from the 2021 National Survey of Children's Health (NSCH) yielded a target subpopulation of 8523 youth aged 6–17 years (54.22 % girls) prescribed eyeglasses/contact lenses. The representative sample of US children and adolescents was used to estimate the prevalence of meeting 24-HMB guidelines, and a multinomial logistic regression analysis was conducted to examine the odds of meeting 24-HMB guidelines by demographic, health status, and environmental variables. ResultsOverall, only 6.57 % met all three 24-HMB guidelines, 23.74 % did not meet any of the three 24-HMB guidelines, and 3.57 %, 10.88 %, and 29.98 % met single guidelines for physical activity, screen time, or sleep duration, respectively, while 25.27 % met any of two 24-HMB guidelines. Female participants were less likely to meet PA + SL guidelines (OR = 0.57, 95 % CI [0.38, 0.56]) but more likely to meet ST + SL guidelines (OR = 1.52, 95 % CI [1.20, 1.91]). Hispanic participants were less likely to meet PA + ST (OR = 0.28, 95 % CI [0.14, 0.52]) guidelines and all three guidelines (OR = 0.41, 95 % CI [0.23, 0.71]) while participants identified as black (OR = 0.33, 95 % CI [0.21, 0.51]) were significantly less likely to meet ST + SL guidelines. With respect to health status, overweight status, repeated/chronic physical pain, and born premature, were detrimentally associated with meeting two or more 24-HMB guidelines. Living in neighborhoods with parks or playgrounds and neighborhood safety were positively linked to meeting the guidelines while living in neighborhoods with sidewalks or walking paths was negatively linked to meeting PA + ST guidelines. ConclusionIn U.S. youth prescribed eyeglasses/contact lenses the prevalence of meeting all three 24-HMB guidelines was low, especially the low prevalence observed in female participants, Hispanic and black participants, participants with overweight status, repeated/chronic pain, born premature, living in neighborhoods with sidewalks. Policy makers should take initiative to promote integrated guidelines among this special age group for health benefits.

The Design Concept of Integrated Pedestrian Sidewalk with Solar Plants as a Form of Green Campus Development at the Bali Land Transportation Polytechnic

Abstract An important aspect of creating a viable campus environment is providing safe and comfortable walking paths. Proper walking paths give some advantages for students, including improved physical and mental health, transportation efficiency, and increased Student satisfaction and happiness. The pedestrian sidewalk area at Bali Land Transportation Polytechnic (Poltrada Bali) covers 3800 m2, experiencing high pedestrian activity but lacking protective roofing to enhance pedestrian comfort. Based on the pedestrian sidewalk area, a solar power plant as support for the green canopy construction combined with shading vines is possible. The generated electrical energy serves as the power source for the Public Electric Vehicle Charging Stations (PEVCS) in the campus parking lot as a support for the electric vehicle acceleration program in Bali province. In addition to PEVCS, energy extraction surplus is used as alternative energy for street lighting facilities in the campus area. In this study, the design concept of a shaded pedestrian sidewalk has been carried out, with multiple benefits as solar plants using Delphi as a variable identification and validation tool, and SketchUp software to visualize design shapes aesthetically. The results show that a pedestrian comfort level of 94% was obtained and the maximum power generation of 934,800 Wp, thus it was able to meet the 887,832 W campus operational power reserve needs, street and garden lights of 9,728 W, and the power requirements of two PEVCS units of 22,000 W with a surplus of 15,240 W electric power.

Public safety considerations constraint the conservation of large old trees and their crucial ecological heritage in urban green spaces

Large old trees in urban public green spaces deliver a diversity of values essential for human well-being, including biodiversity conservation. Yet, the conservation of large old trees bearing key wildlife microhabitats interferes with safety considerations. This intuitive notion, however, is backed by an insufficient and scattered body of evidence. Here, we empirically examined this process using data on 5974 trees across 510 sample plots, organized as quintuplets within 102 sample sites, including urban parks, cemeteries, recreational forests, and historic reserves in the urban agglomeration of Kraków, Poland. Our analyses demonstrate that trees situated in areas frequently visited by people, or those near walking paths, benches, or playgrounds, have elevated accident hazards and, therefore, necessitate intensive tree surgeries (pruning and logging) to remain harmless. Large old trees, which bear the most diverse microhabitats and pose greater risks when they collapse, are especially affected by these measures. Accordingly, we found that the co-occurrence of large trees with elevated accident hazards results in significant losses of dead and sloped trees, and trees with cavities, injuries, crown deadwood, fungal fruiting bodies, or epiphytes, particularly in parks and, to a lesser extent, in recreational forests. Apparently, some tree-related microhabitats, such as injuries, cavities, and microsoils, also emerge in risky spots after pruning. Our findings underscore that the conservation of large old trees and their ecological functions faces significant challenges due to safety considerations. To address conservation challenges and harmonize human coexistence with biodiversity, we recommend enhancing environmental awareness and reevaluating arboricultural and planning policies. This would involve establishing strategic and pocket reserves on city peripheries and interiors, allowing larger older trees to thrive and develop important microhabitats without compromising public safety. Otherwise, we risk losing many large old trees and/or their superior value for wildlife, which will regenerate over decades, if not centuries.

The Consistency of Subjective and Objective Factors Influencing Walking Path Choice around Rail Transit Stations

The Consistency of Subjective and Objective Factors Influencing Walking Path Choice around Rail Transit Stations

Inter-joint coordination with and without dopaminergic medication in Parkinson’s disease: a case-control study

BackgroundHow the joints exactly move and interact and how this reflects PD-related gait abnormalities and the response to dopaminergic treatment is poorly understood. A detailed understanding of these kinematics can inform clinical management and treatment decisions. The aim of the study was to investigate the influence of different gait speeds and medication on/off conditions on inter-joint coordination, as well as kinematic differences throughout the whole gait cycle in well characterized pwPD.Methods29 controls and 29 PD patients during medication on, 8 of them also during medication off walked a straight walking path in slow, preferred and fast walking speeds. Gait data was collected using optical motion capture system. Kinematics of the hip and knee and coordinated hip-knee kinematics were evaluated using Statistical Parametric Mapping (SPM) and cyclograms (angle-angle plots). Values derived from cyclograms were compared using repeated-measures ANOVA for within group, and ttest for between group comparisons.ResultsPD gait differed from controls mainly by lower knee range of motion (ROM). Adaptation to gait speed in PD was mainly achieved by increasing hip ROM. Regularity of gait was worse in PD but only during preferred speed. The ratios of different speed cyclograms were smaller in the PD groups. SPM analyses revealed that PD participants had smaller hip and knee angles during the swing phase, and PD participants reached peak hip flexion later than controls. Withdrawal of medication showed an exacerbation of only a few parameters.ConclusionsOur findings demonstrate the potential of granular kinematic analyses, including > 1 joint, for disease and treatment monitoring in PD. Our approach can be extended to further mobility-limiting conditions and other joint combinations.Trial registrationThe study is registered in the German Clinical Trials Register (DRKS00022998, registered on 04 Sep 2020).

Random walks in the high-dimensional limit II: The crinkled subordinator

A crinkled subordinator is an ℓ2-valued random process which can be thought of as a version of the usual one-dimensional subordinator with each out of countably many jumps being in a direction orthogonal to the directions of all other jumps. We show that the path of a d-dimensional random walk with n independent identically distributed steps with heavy-tailed distribution of the radial components and asymptotically orthogonal angular components converges in distribution in the Hausdorff distance up to isometry and also in the Gromov–Hausdorff sense, if viewed as a random metric space, to the closed range of a crinkled subordinator, as d,n→∞.

Multigenerational spaces: the usage and activities of different age groups within six community parks in Victoria, Australia.

This study investigated how different spaces within multigenerational local parks are being used by older people and other age groups. Observation of park visitors occurred in six Victorian parks one month after park refurbishment. Parks were classified into six spaces based on equipment/amenities and associated expected activity. Observations were summarized descriptively, and negative binomial regression models were used to examine the association between visitor counts and classified targeted areas. A total of 12501 people visited the parks with 4.1% older visitors. The number of older visitors in each park area was consistently less than other age groups, with counts of older visitors being 50% less in mixed spaces (95% confidence interval [CI] 0.38, 0.65), 40% less in adult exercise equipment areas (95% CI 0.46, 0.77) and 59% less in walking paths (95% CI 0.31, 0.55). The number of older visitors engaging in physical activity were significantly greater in walking paths (incidence rate ratios 1.75; 95% CI 1.16, 2.64) compared with children's play spaces. The number of visitors across different age groups varied significantly between the park targeted areas. Most spaces were mainly used by the intended target age group/user, with no particular area used by all age groups in similar proportions.

Enhancing fall risk assessment: instrumenting vision with deep learning during walks

BackgroundFalls are common in a range of clinical cohorts, where routine risk assessment often comprises subjective visual observation only. Typically, observational assessment involves evaluation of an individual’s gait during scripted walking protocols within a lab to identify deficits that potentially increase fall risk, but subtle deficits may not be (readily) observable. Therefore, objective approaches (e.g., inertial measurement units, IMUs) are useful for quantifying high resolution gait characteristics, enabling more informed fall risk assessment by capturing subtle deficits. However, IMU-based gait instrumentation alone is limited, failing to consider participant behaviour and details within the environment (e.g., obstacles). Video-based eye-tracking glasses may provide additional insight to fall risk, clarifying how people traverse environments based on head and eye movements. Recording head and eye movements can provide insights into how the allocation of visual attention to environmental stimuli influences successful navigation around obstacles. Yet, manual review of video data to evaluate head and eye movements is time-consuming and subjective. An automated approach is needed but none currently exists. This paper proposes a deep learning-based object detection algorithm (VARFA) to instrument vision and video data during walks, complementing instrumented gait.MethodThe approach automatically labels video data captured in a gait lab to assess visual attention and details of the environment. The proposed algorithm uses a YoloV8 model trained on with a novel lab-based dataset.ResultsVARFA achieved excellent evaluation metrics (0.93 mAP50), identifying, and localizing static objects (e.g., obstacles in the walking path) with an average accuracy of 93%. Similarly, a U-NET based track/path segmentation model achieved good metrics (IoU 0.82), suggesting that the predicted tracks (i.e., walking paths) align closely with the actual track, with an overlap of 82%. Notably, both models achieved these metrics while processing at real-time speeds, demonstrating efficiency and effectiveness for pragmatic applications.ConclusionThe instrumented approach improves the efficiency and accuracy of fall risk assessment by evaluating the visual allocation of attention (i.e., information about when and where a person is attending) during navigation, improving the breadth of instrumentation in this area. Use of VARFA to instrument vision could be used to better inform fall risk assessment by providing behaviour and context data to complement instrumented e.g., IMU data during gait tasks. That may have notable (e.g., personalized) rehabilitation implications across a wide range of clinical cohorts where poor gait and increased fall risk are common.

Entity type inference based on path walking and inter-types relationships

As a crucial task for knowledge graphs (KGs), knowledge graph entity type inference (KGET) has garnered increasing attention in recent years. However, recent methods overlook the long-distance information pertaining to entities and the inter-types relationships. The neglect of long-distance information results in the omission of crucial entity relationships and neighbors, consequently leading to the loss of path information associated with missing types. To address this, a path-walking strategy is utilized to identify two-hop triplet paths of the crucial entity for encoding long-distance entity information. Moreover, the absence of inter-types relationships can lead to the loss of the neighborhood information of types, such as co-occurrence information. To ensure a comprehensive understanding of inter-types relationships, we consider interactions not only with the types of single entity but also with different types of entities. Finally, in order to comprehensively represent entities for missing types, considering both the dimensions of path information and neighborhood information, we propose an entity type inference model based on path walking and inter-types relationships, denoted as “ET-PT”. This model effectively extracts comprehensive entity information, thereby obtaining the most complete semantic representation of entities. The experimental results on publicly available datasets demonstrate that the proposed method outperforms state-of-the-art approaches.

Visualizing congestion at large-scale events with an interactive-view system incorporating proximity-based networks

Contact with infected individuals can lead to the spread of infectious diseases. During the COVID-19 pandemic, people were strongly urged to avoid the three Cs: closed spaces, crowded places, and close-contact settings. To hold large-scale events under such circumstances, reducing crowd congestion is key to preventing the further spread of infection. Therefore, identifying the pedestrian behaviors and walking patterns that pose a high risk of infection and utilizing them for effective crowd control is necessary. In this study, we propose an approach for visualizing walking paths while maintaining visibility from large-scale human flow data and representing both spatial and temporal features. The proposed method enables the visualization of the pedestrian proximity status as a network containing three components: a proximity network, proximity path, and pedestrian statistics that interact with each other. By operating the three components of this system interactively, we can observe the spatial and temporal features of situations with a high risk of infection during crowd congestion. An example of the operation of this system is presented by visualizing real-world human flow data measured at an event venue and identifying the proximity of the pedestrians.

Minimum dose walking path planning in a nuclear radiation environment based on a modified A* algorithm

An additional cost function for the case with turning points is introduced to the A* algorithm, which can reduce unnecessary turning points. Therefore, the modified A* algorithm consists of three parts: the actual cost function, the estimated cost function, and the turning point cost function. The three functions are normalized so that they can be compared without dimensionality to obtain the optimal path planning in radiation environments. Based on the Geant4 Monte Carlo program, the radiation field model is established and the dose distribution data is obtained. We assign weights to the functions to smooth out the three different cost functions and avoid scenarios in which one function is much greater than the other two. In a small-scale simulation experiment, the path generated by the modified algorithm is consistent with that calculated by the traditional A* method, but the number of turning points is significantly reduced. The modified algorithm takes less time and the cumulative dose on the path is slightly lower. Modified A*, traditional A* and PRM algorithms are used for path planning and comparison in the complex radiation environment of multiple γ sources. The PRM algorithm takes the least computation time to search the path, but the cumulative exposure dose is random. For the path planning of multi-task operation in a radiation field, the cumulative radiation dose of the path planned by the modified A* algorithm is equivalent to that of the traditional A* algorithm, but the modified A* algorithm significantly reduces the number of turning points, the calculation time is significantly shortened, and the execution efficiency is improved. The modified A* algorithm can be used as a reference for path planning for workers in radiation workplaces.

RedirectedDoors+: Door-Opening Redirection with Dynamic Haptics in Room-Scale VR.

RedirectedDoors is a visuo-haptic door-opening redirection technique in VR, and it has shown promise in its ability to efficiently compress the physical space required for a room-scale VR experience. However, its previous implementation has only supported laboratory experiments with a single door opening at a fixed location. To significantly expand this technique for room-scale VR, we have developed RedirectedDoors+, a robot-based system that permits consecutive door-opening redirection with haptics. Specifically, our system is mainly achieved with the use of three components: (1) door robots, a small number of wheeled robots equipped with a doorknob-like prop, (2) a robot-positioning algorithm that arbitrarily positions the door robots to provide the user with just-in-time haptic feedback during door opening, and (3) a user-steering algorithm that determines the redirection gain for every instance of door opening to keep the user away from the boundary of the play area. Results of simulated VR exploration in six virtual environments reveal our system's performance relative to user walking speed, paths, and number of door robots, from which we derive its usage guidelines. We then conduct a user study ($N=12$) in which participants experience a walkthrough application using the actual system. The results demonstrate that the system is able to provide haptic feedback while redirecting the user within a limited play area.

An Adaptive Heading Estimation Method based on Holding Styles Recognition Using Smartphone Sensors

Pedestrian Dead Reckoning (PDR), which comes with many sensors integrated into widely available smartphones, is known as one of the most popular indoor positioning techniques. Sensors such as accelerometers, gyroscopes, and magnetometers are used to determine three important components in PDR: step detection, step length estimation, and heading estimation. Among them, the last component is the most challenging since a small heading error accumulates to produce a very large positioning error, especially when the pedestrian holds the smartphone in unconstrained styles such as swinging the phone freely along the pedestrian’s walking direction or putting the phone into the pants’ front pockets. The research proposes an adaptive heading estimation method to deal with heading errors caused by smartphone holding styles. The novelties are described as follows. Firstly, the proposed method attempts to classify the four basic smartphone holding styles using a machine learning algorithm based on simple features of acceleration values to give pedestrians more freedom during the walking period. Secondly, the proposed method adaptively combines the two heading estimation methods, which are calculated from the integrated sensors, to determine the walking direction for different smartphone holding styles. The experimental results show that the proposed heading estimation method achieves average heading errors of less than 30 degrees when testing in two different walking paths with the smartphone held in dynamic styles. It helps to reduce the heading errors by more than 15% compared to previous heading estimation methods.

A structural description of pedestrian movement behavior in multiple surveillance videos

This study purpose of recording pedestrians' activities in all surveillance videos and then convert these records into structured descriptions to analyze a large number of surveillance videos. This paper proposes a four-stage processing method. The first stage uses convolutional neural network (CNN) to detect objects in the surveillance video and classify them. The second stage finds the correlation of pedestrians in continuous images and describes multiple objects' trajectories in the surveillance video. The third stage calculates the similarity of the pedestrian object sets of the surveillance video at different times as the basis for pedestrian re-identification. In the fourth stage, extract the walking path of the pedestrian in each surveillance video. Each pedestrian's actions in each surveillance video, including whether to stand, walking path, direction, clothing color and walking time. To construct a correlation table of pedestrian motion in multiple surveillance videos.This experiment uses two image datasets for experimentation and analysis to evaluate this method's effectiveness for pedestrian movement in multiple surveillance videos. The image datasets are the Multi-Camera Object Tracking (MCT) Challenge and PETS 2009 Benchmark Data. This experiment includes pedestrian detection, pedestrian identification, and multi-pedestrian tracking of pedestrians in single and multiple surveillance cameras. The results show that in the pedestrian detection experiment, the convolutional neural network can effectively solve the problems caused by static objects, light changes, similar colors, crowded pedestrians, and incomplete objects. In the pedestrian recognition and re-recognition experiments, the accuracy is reduced due to the influence of low-resolution surveillance videos. This detection method of the pedestrian is more accurate than traditional dynamic object detection methods. After the pedestrian tracking and re-identification are completed, the pedestrian relationships in multiple surveillance cameras are integrated, and a pedestrian behavior association table is built for surveillance videos.

An investigation of the open spaces and their impact on child interaction in high-rise urban environments: a case of the city of Colombo, Sri Lanka

ABSTRACT Most contemporary research on child psychology has studied the importance of child interactions and personality development. However, minimal research has been done to understand the blend between child psychology, natural environment, and placemaking. This study investigates how open spaces in high-rise condominiums promote child interactions and what open space characteristics catalyse such interactions by using a child-centered multiple method approach. The results depict that open spaces can act as a room for connecting children with their family and friends, natural environment and wider neighbourhoods while enhancing opportunities for self-actualization and routines. The study reveals that children’s usability and interactions are encouraged by natural elements equipped with play items and a strong sense of privacy and security. Supporting the assemblage theory, the assemblage of all the elements, such as buildings, greenery, seating, and walking paths, supports positive interactions among children. The study recommends that planners design spaces assembled as a functional sub-system of the main system to assist early child development competencies.

Commercial Corridor Development Strategy through the Application of the Walkable Commercial Strip Concept in Urban Area of Jember City

Walkability is an essential concept to consider when planning a sustainable city. This study aims to determine the walkability development strategy of the Jember City commercial corridors urban area based on people's and experts' perceptions of the Walkable Commercial Strip concept. The study was conducted in the urban area of Jember City Golden Triangle. The methods of analysis used in this study are ordinal logistic regression and AHP. Based on people's perceptions, the concepts that have the highest odds of influencing the first corridor's walkability level are the ones related to the available amenities variable, while the concept that has the highest odds of influencing the second and the third corridors' walkability level is the concept that is related to the walking path modal conflict variable. The order in which corridors have the highest development priority starts with the first corridor, Gajah Mada - Sultan Agung Street, followed by the second corridor, Ahmad Yani Street, and ends with the third corridor, Trunojoyo Street – HOS Cokroaminoto Street. The walkability development strategy for the urban area of Jember City commercial corridors is to start the order of development according to the order of priority and apply the development concepts that have the highest opportunity to influence the walkability level of each corridor based on people's perception.

Probabilistic assessment of the dynamic response of floors under multi-pedestrian walking loads

The dynamic behavior of floors under multi-pedestrian walking loads affects the safety, serviceability, and comfort of floor occupants. The complexity of pedestrian-induced dynamic loads necessitates a probabilistic approach to understand and predict the performance of floors under such conditions. This paper investigates the dynamic response of floors subjected to multiple-pedestrian walking loads, taking into account the randomness of the walking path and walking load. The research focuses on probabilistic multi-pedestrian walking load scenarios and utilizes Monte Carlo simulations to analyze the modal loading. An analytical equivalent Power Spectral Density (PSD) function for the modal force, based on an existing model introduced for footbridges, is proposed. Furthermore, a formula is developed to estimate the mean value of the peak acceleration response of floors. The findings of this study contribute to the advancement of simplified methods for predicting the dynamic response of floors under multiple pedestrian walking loads. These methods can enhance the accuracy and reliability of vibration serviceability assessment for floor structures.