Predictive multiscale computational model of shoe-floor coefficient of friction

Machine learning prediction of footwear slip resistance on glycerol-contaminated surfaces: A pilot study

Slippery surfaces due to oil spills pose a significant risk in various environments, including industrial workplaces, kitchens, garages, and outdoor areas. These situations can lead to accidents and falls, resulting in injuries that range from minor bruises to severe fractures or head trauma. To mitigate such risks, the use of slip resistant footwear plays a crucial role. In this study, we aimed to develop an Artificial Intelligence model capable of classifying footwear as having either high or low slip resistance based on the geometric characteristics and material parameters of their outsoles. Our model was trained on a unique dataset comprising images of 37 indoor work footwear outsoles made of rubber. To evaluate the slip resistant property of the footwear, all samples were tested using a cart-type friction measurement device, and the static and dynamic Coefficient of Frictions (COFs) of each outsole was determined on a glycerol-contaminated surface. Machine learning techniques were implemented, and a classification model was developed to determine high and low slip resistant footwear. Among the various models evaluated, the Support Vector Classifier (SVC) obtained the best results. This model achieved an accuracy of 0.68 ± 0.15 and an F1-score of 0.68 ± 0.20. Our results indicate that the proposed model effectively yet modestly identified outsoles with high and low slip resistance. This model is the first step in developing a model that footwear manufacturers can utilize to enhance product quality and reduce slip and fall incidents.

Prospective validity assessment of a friction prediction model based on tread outsole features of slip-resistant shoes

Shoe outsole design strongly influences slip and fall risk. Certain tread features that can be readily measured have been shown to predict friction performance. This research aimed to replicate those findings and quantify their ability to predict slipping. Participants (n = 34) were exposed to a low friction oil-coated floor surface, while wearing slip-resistant shoes. The coefficient of friction (COF) of each shoe were predicted based on tread surface area, the presence of a bevel, and hardness. The COF was measured, and the slip outcome was determined. Predicted and measured COF were correlated, and measured COF was a sensitive predictor of slip outcome. The relationship of predicted COF on slip outcome was weaker than anticipated and was not statistically significant. This study partially confirmed the ability of previous regression equations to predict COF. However, the effect size was weaker than previously reported and predicted COF was not sensitive for predicting slips.

The effect of tread patterns on slip resistance of footwear outsoles based on composite materials in icy conditions

INTRODUCTION

Falls on icy surfaces are the leading cause of injuries for outdoor workers. Footwear outsole material and geometrical design parameters are the most significant factors affecting slips-and-falls. Recently, composite materials have been incorporated into outsoles to improve traction, yet the best design parameters are not fully understood.

METHOD

In this effort, based on Taguchi orthogonal array design, 27 outsole prototypes were fabricated with different tread pattern features using our patented composites and tested in a simulated winter condition.

RESULTS

An analysis of variance (ANOVA) showed that surface area (p = 0.041, Contribution = 15.63%) was the only factor significantly affecting the slip-resistance of our prototypes. The best performance was observed for the maximized surface area covered by our composite material with circular and half circular plugs laid obliquely, mostly in the forefoot area.

PRACTICAL APPLICATIONS

These findings suggest that some tread design features of composite-based footwear have a great role in affecting slip-resistance properties of composite-based footwear.

Validation of a portable shoe tread scanner to predict slip risk

PROBLEM

Worn shoes are an important contributor to occupational slip and fall injuries. Tools to assess worn tread are emerging; imaging tools offer the potential to assist. The aim of this study was to develop a shoe tread scanner and evaluate its effectiveness to predict slip risk.

METHODS

This study analyzed data from two previous studies in which worn or new slip-resistant shoes were donned during an unexpected slip condition. The shoe tread for each shoe was scanned using a portable scanner that utilized frustrated total internal reflection (FTIR) technology. The shoe tread parameters of the worn region size (WRS) for worn shoes and total contact area for new shoes were measured. These parameters were then used to predict slip risk from the unexpected slip conditions.

RESULTS

The WRS was able to accurately predict slip risk, but the contact area was not.

DISCUSSION

These findings support that increased WRS on the shoe outsole is associated with worse slip outcomes. Furthermore, the tool was able to offer robust feedback across a wide range of tread designs, but the results of this study show that the tool may be more applicable for slip-resistant shoes that are worn compared to their new counterparts.

SUMMARY

This study shows that FTIR technology utilized in this tool may be a useful and portable method for determining slip risk for worn shoes.

PRACTICAL APPLICATIONS

This tool has the potential to be an efficient, objective, end-user tool that improves timely replacement of shoes and prevention of injuries.

Biomechanical modeling of footwear-fluid-floor interaction during slips

Slips and falls are among the major concerns for public safety. Slipping risks can be reduced by ensuring adequate traction at the shoe-floor interface. The outsole design of footwear is a critical factor to maintain sufficient shoe-floor traction in the presence of slippery contaminants such as water or oil. While the role of floorings and contaminants on footwear traction has been studied widely, limited works have investigated the role of footwear outsole geometry and tread patterns on shoe-floor traction. In this work, eight footwear outsole designs and their traction performance were tested on a common flooring with water contamination, through the development of a novel fluid-structure interaction based computational framework. Induced fluid pressure, mass flow rates, and contact areas were quantified across the outsole patterns, and their effect on footwear friction was investigated. The study results were validated using mechanical slip testing experiments. The results indicated that the outsoles which had horizontal treads or untreaded heel regions can lead to drastic reduction of footwear friction. Also, contact area alone was quantified to be a poor choice in estimating the traction performance of footwear on water contaminated floorings. Such novel study results have not been reported to date, and are anticipated to provide important guidelines to footwear manufacturers to evaluate and optimize footwear tread parameters which would help in reducing the risk of slips.

The effect of footwear outsole material on slip resistance on dry and contaminated surfaces with geometrically controlled outsoles

Previous studies have compared slip resistance of commercially available footwear, however, often lacking the ability to isolate factors such as material and surface properties, or/and geometry. The aim of this study was to compare slip resistance of geometrically identical shoes with varying outsole materials. Three left Ecco Xpedition III shoes were constructed out of three different outsole materials: polyurethane (PU), thermoplastic polyurethane (TPU) and vulcanised rubber (RU). The shoes were tested for dynamic coefficient of friction (DCOF) on a steel and a tile surface, without contamination and with glycerine and canola oil as contaminants. The shoes were significantly (p < 0.001) different from each other across all surface/contaminant conditions/combinations, with the PU having a significantly 61-125% (p < 0.001) higher DCOF on contaminated surfaces compared to the RU outsole.Practitioner summary: Previous research has suggested the importance of studying individual parameters separately of footwear in relation to slip resistance. In this study, we managed to construct geometrically identical shoes and compare the slip resistance between three different outsole materials. We found that the polyurethane outsole was the least slippery choice of material for this specific footwear model on contaminated surfaces.

In contrast to slip-resistant shoes, fluid drainage capacity explains friction performance across shoes that are not slip-resistant

Slip and fall injuries can be prevented through footwear with good friction performance. The factors that contribute to friction in non-slip-resistant (NSR) shoes are not well understood. The purpose of this study was to determine whether predictive models for slip-resistant (SR) shoes also apply to NSR shoes. This study also quantified the contributions of under-shoe fluid drainage to friction in NSR shoes. The coefficient of friction (ACOF) and under-shoe fluid pressures of fifteen NSR shoes were measured. A previously developed ACOF prediction model based on measurable outsole features was applied to the NSR shoes. The previously developed model did not apply well (in trends, as indicated by interaction effects involving SR/NSR classification, or in magnitude, p < 0.001) to NSR shoes. Instead, an increase in the fluid pressures were associated with a reduction in ACOF (p < 0.001). This study demonstrates that fluid pressures dominate performance in NSR shoes in contrast to SR shoes.

Assessment of the effect of horseshoes with and without traction adaptations on the gait kinetics of nonlame horses during a trot on a concrete runway

OBJECTIVE

To assess the effect of horseshoes with and without traction adaptations on the gait kinetics of nonlame horses during a trot on a concrete runway.

ANIMALS

5 nonlame adult light-breed horses.

PROCEDURES

Kinetic data were obtained for each horse when it was trotted across a force platform within a concrete runway unshod (control) and shod with standard horseshoes; standard horseshoes with high profile-low surface area calks, with low profile-high surface area calks, and coated with a thin layer of tungsten carbide (TLTC); and plastic-steel composite (PSC) horseshoes. Kinetic data were obtained for the control treatment first, then for each of the 5 shoe types, which were applied to each horse in a random order. Kinetic variables were compared among the 6 treatments.

RESULTS

Body weight distribution did not differ among the 6 treatments. Compared with the control, the greatest increase in forelimb peak vertical force was observed when horses were shod with PSC shoes. In the hind limbs, the greatest increase in peak braking force was observed when horses were shod with PSC shoes, followed by the TLTC and low profile-high surface area calked shoes. The PSC shoes yielded the greatest coefficient of friction in both the forelimbs and hind limbs. Stance time was longest when horses were shod with standard shoes.

CONCLUSIONS AND CLINICAL RELEVANCE

Results suggested that PSC and TLTC shoes provided the best hoof protection and traction and might be good options for horses that spend a large amount of time traversing paved surfaces.

Worn region size of shoe outsole impacts human slips: Testing a mechanistic model

Shoe outsole tread wear has been shown to increase slip risk by reducing the tread's ability to channel fluid away from the shoe-floor interface. This study establishes a connection between geometric features of the worn region size and slipping. A mechanistic pathway that describes the relationship between the worn region size and slip risk is assessed. Specifically, it is hypothesized that an increased worn region size leads to an increase in under-shoe fluid pressure, which reduces friction, and subsequently increases slipping. The worn region size, fluid pressure, and slip outcome were recorded for 57 participants, who were exposed to an unexpected slip condition. Shoes were collected from each participant and the available coefficient of friction (ACOF) was measured using a tribometer. A greater shoe worn region size was associated with increased slip occurrence. Specifically, a 1 mm increase in the characteristic length of the worn region (geometric mean of its width and length) was associated with an increase in slip risk of ~10%. Fluid pressure and ACOF results supported the mechanistic model: an increase in worn region size correlated with an increase in peak fluid pressure; peak fluid pressures negatively correlated with ACOF; and increased ACOF correlated with decreased slip risk. This finding supports the use of worn region size as a metric to assess the risk of slipping.

Predicting Hydrodynamic Conditions under Worn Shoes using the Tapered-Wedge Solution of Reynolds Equation

Slips and falls are a leading cause of injuries in the workplace. The risk of slipping increases as shoe tread wears. Knowledge of the mechanics relating shoe wear to slip risk is needed to develop fall-prevention strategies. This research applies a rectangular, tapered-wedge bearing solution to worn shoes and compares the results to experimentally measured under-shoe fluid pressure results. Changes in the size of the shoe outsole worn region and fluid dispersion capabilities were recorded for four, slip-resistant shoes which were systematically abraded. The film thickness predicted by the solution correlated well with the measured force supported by the fluid. The results provide support that the tapered-wedge solution can be used to assess slip risk in worn shoes.

A Biomechanical Investigation of Athletic Footwear Traction Performance: Integration of Gait Analysis with Computational Simulation

Evaluations are vital to quantify the functionalities of athletic footwear, such as the performance of slip resistance, shock absorption, and rebound. Computational technology has progressed to become a promising solution for accelerating product development time and providing customized products in order to keep up with the competitive contemporary footwear market. In this research, the effects of various tread pattern designs on traction performance in a normal gait were analyzed by employing an approach that integrated computational simulation and gait analysis. A state-of-the-art finite element (FE) model of a shoe was developed by digital sculpting technology. A dynamic plantar pressure distribution was automatically applied to interpret individualized subject conditions. The traction performance and real contact area between the shoe and the ground during the gait could be characterized and predicted. The results suggest that the real contact area and the structure of the outsole tread design influence the traction performance of the shoe in dry conditions. This computational process is more efficient than mechanical tests in terms of both cost and time, and it could bring a noticeable benefit to the footwear industry in the early design phases of product development.

Prediction of coefficient of friction based on footwear outsole features

Traction testing of footwear is expensive, which may create barriers for certain users to assess footwear. This study aimed to develop a statistical model that predicts available coefficient of friction (ACOF) under boundary lubrication conditions based on inexpensive measurements of footwear outsole features. Geometric and material hardness parameters were measured from fifty-eight footwear designs labeled as slip-resistant. A robotic friction measurement device was used to quantify ACOF with canola oil as the contaminant. Stepwise regression methods were used to develop models based on the outsole parameters and floor type to predict ACOF. The predictive ability of the regression models was tested using the k-fold cross-validation method. Results indicated that 87% of ACOF variation was explained by three shoe outsole parameters (tread surface area, heel shape, hardness) and floor type. This approach may provide an assessment tool for safety practitioners to assess footwear traction and improve workers' safety.

Generalizability of Footwear Traction Performance across Flooring and Contaminant Conditions

Background

To prevent slip and fall events at the workplace, mechanical slip testing is conducted on shoes. Such experiments may involve redundant testing across floorings and contaminant conditions, causing wasted time and effort.

Purpose

Quantify the correlations between shoe traction across different contaminant-flooring conditions to reduce redundant slip testing efforts.

Methods

The available coefficient-of-friction (ACOF) was quantified for 17 shoes across five floorings and three contaminant conditions. Redundant testing conditions were identified when the shoe ACOF values for one floor-contaminant condition were highly correlated with a second floor-contaminant condition.

Results

High correlations were observed among quarry floorings across different contaminants and among vinyl (composite tile) floorings with the same contaminant. However, vinyl floorings exhibited low correlations with quarry floorings. Low correlations were also observed across contaminants within vinyl tiles.

Conclusions

This study was able to determine the generalizability of traction performance of shoes across vinyl and quarry floorings. This information is anticipated to reduce redundant traction testing of shoes across vinyl and quarry floorings.