Coefficient of friction testing parameters influence the prediction of human slips

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.

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.

Different Influencing Factors for Risk of Falls Between Men and Women while Descending from Mount Fuji

INTRODUCTION

Annually, approximately 250,000 people climb Mount Fuji in Japan. Nonetheless, only few studies have examined the prevalence of falls and related factors on Mount Fuji.

METHODS

We conducted a questionnaire survey of 1061 participants (703 men and 358 women) who had climbed Mount Fuji. The following information was collected: age, height, body weight, luggage weight, experience on Mount Fuji, experience on other mountains, presence or absence of a tour guide, single-day climber or overnight-stay lodger, information on the downhill trail (volcanic gravel, long distance, and the risk of falls), presence or absence of trekking poles, shoe type, shoe sole condition, and fatigue feeling.

RESULTS

The fall rate in women (174/358; 49%) was greater than that in men (246/703; 35%). A prediction model using multiple logistic regression (no fall, 0; fall, 1) indicated that the following factors decreased the risk of falls: male sex, younger age, previous experience on Mount Fuji, having information about long-distance downhill trails, wearing hiking shoes or mountaineering boots rather than other types of shoes (eg, running shoes, sneakers) or worn-out shoes, and not feeling fatigued. Additionally, the following factors may decrease the risk of falls in women only: experience hiking on any other mountains, not being part of a guided tour, and using trekking poles.

CONCLUSIONS

Women had a higher risk of falls on Mount Fuji than men. Specifically, having less experience on any other mountains, being part of a guided tour, and nonuse of trekking poles may relate to higher risks of falls in women. These results suggest that different precautionary measures for men and women are useful.

Estimation of Seagrass Beds Changes in the Barugaiya Village Waters over a Period of 5 Years 2019-2023

<b>Background and Objective:</b> Barugaiya Village is one of the villages located in Selayar Islands Regency, South Sulawesi, which has seagrass beds that are spread almost evenly in its waters. Environmental changes are in the form of declining water quality and damage to coastal ecosystems, one of which is seagrass. Therefore, it is necessary to observe changes in the area of seagrass beds in the waters of Barugaiya Village so that it is known how much seagrass has actually been in the area in the last 5 years. <b>Materials and Methods:</b> Observations were made from March to May, 2023 in the waters of Barugaiya Village, Selayar Islands Regency, South Sulawesi. The method used is seagrass classification using Sentinel-2A images corrected by the water column with the Lyzenga algorithm to reduce the effect of depth. <b>Results:</b> The distribution area of seagrass in Barugaiya Village for the 2019-2023 period was 111.03, 107.16, 103.81, 102.54 and 99.70 ha, respectively. Every year there is a decrease in seagrass area, the rate of decline is around 0.02% each year (1.27-3.87 ha). The change in area over the past 5 years has decreased by 0.11% (11.33 ha). <b>Conclusion:</b> Therefore, long-term monitoring of seagrass beds in the waters of Barugaiya Village which are experiencing a decline is needed so that effective management strategies can be identified.

Friction performance of resilient flooring under contaminant conditions relevant to healthcare settings

Flooring is among the factors known to influence slip and fall risk. Slips are common in the healthcare industry, where resilient flooring is prevalent. This study assessed coefficient of friction (COF) across resilient flooring products specific to conditions relevant to healthcare. The COF for eleven resilient flooring surfaces were tested in their dry condition and under six contaminant conditions. Data was analyzed using ANOVA and principal component analysis. The COF was strongly influenced by the contaminant condition (p < 0.001) with hand sanitizer and canola oil having the lowest COF values. COF was also influenced by the flooring product (p < 0.001) although to a lesser extent than the contaminant condition. The contaminants differentially affected the friction performance across the flooring products (interaction effect p < 0.001). These effects were described by the first two principal components. This study reveals high slipping potential for certain contaminants on resilient flooring and that flooring influences friction performance in contaminant-specific ways.

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.

Validating the ability of a portable shoe-floor friction testing device, NextSTEPS, to predict human slips

Measuring shoe-floor friction is critical for assessing the safety of footwear products. Portable devices for measuring coefficient of friction (COF) are needed. This study introduces such a device and evaluates its ability to predict human slip events across shoe designs. A portable device (18 kg) was utilized to measure 66 unique shoe-floor-fluid coefficients of friction (COF). Consistent with the shoes, flooring, and fluid contaminants from the COF tests, participants (n = 66) were unexpectedly exposed to the fluid while walking. Slip predictions were made based on a separate training data set. Slip predictions were made prospectively and using logistic regression analyses. The slip predictions were valid (p < 0.001), 91% sensitive, and 64% specific. The logistic regression fit also revealed that the COF values predicted slip outcomes (p = 0.006). This device is expected to expand the capacity of researchers, product developers, forensic engineers, and safety professionals to prevent slips and enhance human safety.

Futsal playing surface characteristics significantly affect perceived traction and change of direction performance among experienced futsal players

We aimed to clarify the effect of different futsal playing surface structural properties on the resultant change of direction (COD) performance, perceived traction and frictional properties. Twenty experienced male university soccer players performed a COD slalom-course test and perceived traction evaluation on three different types of playing surfaces (area-elastic: AE, point-elastic no.1: PE1 and point-elastic no.2: PE2). Frictional properties of these surfaces were mechanically evaluated against a futsal shoe, using a hydraulic moving force platform, and expressed as available friction coefficient (AFC). In the COD performance test, the participants performed significantly better on the point-elastic surfaces (PE1 and PE2) when compared to the area-elastic surface (AE) (p < 0.05). Also, the PE2 surface was found to have the highest perceived traction (p < 0.001). The findings suggest that the relatively higher (4%) AFC explains the improvement in performance and traction perception on the PE2 surface. In this study, we successfully demonstrated that the structural difference (AE or PE) of futsal playing surface has a significant impact on the COD performance of experienced futsal players and their perceived level of traction (PE2) and the frictional properties.

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.

Development and Evaluation of a Slip Detection Algorithm for Walking on Level and Inclined Ice Surfaces

Slip-resistant footwear can prevent fall-related injuries on icy surfaces. Winter footwear slip resistance can be measured by the Maximum Achievable Angle (MAA) test, which measures the steepest ice-covered incline that participants can walk up and down without experiencing a slip. However, the MAA test requires the use of a human observer to detect slips, which increases the variability of the test. The objective of this study was to develop and evaluate an automated slip detection algorithm for walking on level and inclined ice surfaces to be used with the MAA test to replace the need for human observers. Kinematic data were collected from nine healthy young adults walking up and down on ice surfaces in a range from 0° to 12° using an optical motion capture system. Our algorithm segmented these data into steps and extracted features as inputs to two linear support vector machine classifiers. The two classifiers were trained, optimized, and validated to classify toe slips and heel slips, respectively. A total of approximately 11,000 steps from 9 healthy participants were collected, which included approximately 4700 slips. Our algorithm was able to detect slips with an overall F₁ score of 90.1%. In addition, the algorithm was able to accurately classify backward toe slips, forward toe slips, backward heel slips, and forward heel slips with F₁ scores of 97.3%, 54.5%, 80.9%, and 86.5%, respectively.

Effects of natural shoe wear on traction performance: a longitudinal study

Footwear outsole design is an important factor for shoe-floor friction and for preventing slipping. Shoes with small, uniformly-separated tread blocks (often included on slip-resistant shoes) have decreased slip risk due to their increased friction and better under-shoe fluid drainage. However, these traction performance metrics (friction and fluid drainage) diminish with wear. This study quantifies shoe traction performance in response to natural wear and compares the relationship between common wear metrics: time, distance walked, and worn region size (WRS). Participants wore two pairs of shoes in the workplace for up to 11 months and the distance walked was tracked with a pedometer. After each month of wear, traction performance and WRS of each shoe were measured. Traction performance was quantified by the under-shoe available coefficient of friction and fluid force during a simulated slip condition. Increased wear (months worn, distance walked, and WRS) was associated with decreased traction performance. A WRS of 800 mm2 was associated with reductions in friction of 16-38% and increases in fluid force by 286-528%. Three and six months of wear were associated with WRS values of 251 mm2 and 462 mm2 and distances of 203 km and 519 km, respectively. A walking distance of 500 km was associated with a WRS of 406 mm2. This study showed that all these wear metrics are good indicators of shoe traction performance loss. Thus, the most practical metric in a particular application can be selected. We argue that WRS may be the best indicator due to variations in wear rate from the user and environment. Therefore, tracking footwear usage and monitoring outsole wear can aid in shoe replacement recommendations to reduce slips and falls.

Relationship between Friction Coefficient and Surface Roughness of Stone and Ceramic Floors

Slips and falls are common occupational incidents worldwide. The friction on a floor surface is one of the critical environmental factors affecting the risk of a slip. In this research, we conducted friction measurements on stone and ceramic floor tiles under dry, wet, and water–detergent (WD) solution covered conditions using a horizontal pull slip meter (HPS). Our purposes were to quantify the slip resistance of commonly used stone and ceramic floors under different surface conditions and to validate the curvilinear relationship between the coefficient of friction (COF) and surface roughness of the floors proposed in the literature. The COF data were analyzed together with a surface profile parameter (Ra) of the floor samples. The results showed that the COFs of the stone floors were significantly (p < 0.0001) higher than those of the ceramic floors. All the floors under the dry conditions were slip resistant when adopting the ANSI 1264.2 criterion. Two and five ceramic floors were not slip resistant under the wet and WD solution covered conditions, respectively. Three polynomial regression equations were established to describe the relationship between the COF and Ra. The curvilinear functions of these models indicate that the three-zone (initial growth, steady-growth, and plateau) concept concerning the COF–Ra relationship in the literature was valid when static COF values measured using an HPS were adopted. In addition, the three-zone concept was valid not only on WD solution covered surfaces but also on dry and wet surfaces.

Differences in Friction Performance between New and Worn Shoes

Occupational ApplicationsSlips and falls are among the most common reason for non-fatal work accidents. Preventing slips in the workplace can be achieved by ensuring sufficient friction between the shoe and floor. As shoes are worn down, there is a decrease in the coefficient of friction, which increases the risk of injury from a slip and fall for the wearer. We found that shoes worn in the workplace commonly had friction performance that is about 25% lower than their new condition and that this effect was largest for shoes with the highest initial friction performance. These results inform the magnitude of improvement in friction performance that can be achieved through footwear replacement programs.

Effect of foot-floor friction on the external moment about the body center of mass during shuffling gait: a pilot study

Herein, we investigated the effect of friction between foot sole and floor on the external forward moment about the body center of mass (COM) in normal and shuffling gaits. Five young male adults walked with normal and shuffling gaits, under low- and high-friction surface conditions. The maximum external forward moment about the COM (MEFM-COM) in a normal gait appeared approximately at initial foot contact and was unaffected by floor condition. However, MEFM-COM in a shuffling gait under high-friction conditions exceeded that under low-friction conditions (p < 0.001). Therein, MEFM-COM increased with an increasing utilized coefficient of friction at initial foot contact; this effect was weaker during a normal gait. These findings indicate that increased friction between foot sole and floor might increase tripping risk during a shuffling gait, even in the absence of discrete physical obstacles.

Deep Neural Network for Slip Detection on Ice Surface

Slip-induced falls are among the most common causes of major occupational injuries and economic loss in Canada. Identifying the risk factors associated with slip events is key to developing preventive solutions to reduce falls. One factor is the slip-resistance quality of footwear, which is fundamental to reducing the number of falls. Measuring footwear slip resistance with the recently developed Maximum Achievable Angle (MAA) test requires a trained researcher to identify slip events in a simulated winter environment. The human capacity for information processing is limited and human error is natural, especially in a cold environment. Therefore, to remove conflicts associated with human errors, in this paper a deep three-dimensional convolutional neural network is proposed to detect the slips in real-time. The model has been trained by a new dataset that includes data from 18 different participants with various clothing, footwear, walking directions, inclined angles, and surface types. The model was evaluated on three types of slips: Maxi-slip, midi-slip, and mini-slip. This classification is based on the slip perception and recovery of the participants. The model was evaluated based on both 5-fold and Leave-One-Subject-Out (LOSO) cross validation. The best accuracy of 97% was achieved when identifying the maxi-slips. The minimum accuracy of 77% was achieved when classifying the no-slip and mini-slip trials. The overall slip detection accuracy was 86% with sensitivity and specificity of 81% and 91%, respectively. The overall accuracy dropped by about 2% in LOSO cross validation. The proposed slip detection algorithm is not only beneficial for footwear manufactures to improve their footwear slip resistance quality, but it also has other potential applications, such as improving the slip resistance properties of flooring in healthcare facilities, commercial kitchens, and oil drilling platforms.

An observational ergonomic tool for assessing the worn condition of slip-resistant shoes

Worn shoes are known to contribute to slip-and-fall risk, a common cause of workplace injuries. However, guidelines for replacing shoes are not well developed. Recent experiments and lubrication theory suggest that the size of the worn region is an important contributor to the shoe tread's ability to drain fluid and therefore the under-shoe friction. This study evaluated a simple test for comparing the size of the worn region relative to a common object (AAA and AA battery) as a means of determining shoe replacement. This study consisted of three components involving slip-resistant shoes: Experiment #1: a longitudinal, mechanical, accelerated wear experiment; Experiment #2: a longitudinal experiment where the same shoes were tested after each month of worker use; and Experiment #3: a cross-sectional experiment that exposed participants to a slippery condition, while donning their own worn shoes. The COF (Experiments #1 and #2); under-shoe fluid pressure (all experiments); and slip severity (Experiment #3) were compared across outcomes (fail/pass) of the battery tests. Larger fluid pressures, lower coefficient of friction, and more severe slips were observed for shoes that failed the battery tests compared with those passing the tests. This method offers promise for assessing loss in friction and an increase in slip risk for slip-resistant shoes.

Traction performance across the life of slip-resistant footwear: Preliminary results from a longitudinal study

INTRODUCTION

Slips, trips, and falls are a major cause of injury in the workplace. Footwear is an important factor in preventing slips. Furthermore, traction performance (friction and under-shoe fluid drainage) are believed to change throughout the life of footwear. However, a paucity of data is available for how traction performance changes for naturally worn, slip-resistant footwear.

METHOD

The presented research is a preliminary analysis from an ongoing, larger study. Participants wore slip-resistant footwear while their distance walked was monitored. Friction and under-shoe fluid pressures were measured using a robotic slip tester under a diluted glycerol contaminant condition after each month of wear for the left and right shoes. The size of the worn region was also measured.

RESULTS

Friction initially increased and then steadily decreased as the distance walked and the size of the worn region increased. Fluid pressures increased as the shoes were worn and were associated with increased walking distance and size of the worn region.

DISCUSSION

Consistent with previous research, increases in the size of the worn region are associated with increased under-shoe fluid pressures and decreased traction. These trends are presumably due to reduced fluid drainage between the shoe-floor interface when the shoe becomes worn.

CONCLUSIONS

Traction performance changes with natural wear. The distance walked in the shoe and the size of the worn region may be valuable indicators for assessing loss of traction performance. Practical Applications: Current shoe replacement recommendations for slip-resistant shoes are based upon age and tread depth. This study suggests that tools measuring the size of the worn region and/or distance traveled in the shoes are appropriate alternatives for tracking traction performance loss due to shoe wear.

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.

Influence of averaging time-interval on shoe-floor-contaminant available coefficient of friction measurements

Available coefficient of friction (ACOF) is a common metric of footwear traction performance. ACOF is the ratio of friction to normal force, often averaged over a time-interval. The time-interval needed to achieve repeatable and valid ACOF is unknown. A post-hoc analysis was performed on nine shoe-floor-contaminant combinations to assess the repeatability and bias of data averaged across 4 time-intervals (2 ms, 50 ms, 100 ms, 200 ms) after the target normal force was reached. The ability to predict human slips was assessed for ACOF across these intervals. Differences in repeatability and validity across the four intervals were small. However, statistically significant differences were observed for the shortest compared with the longest interval (lower repeatability yet modestly improved predictive ability). Given the limited impact of time-interval on the results, a shorter interval of 50 ms is recommended to enable testing of smaller floor samples.

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.

Changes in under-shoe traction and fluid drainage for progressively worn shoe tread

Shoe wear is known to increase slipping risk, but few studies have systematically studied this relationship. This study investigated the impact of progressive shoe wear on the available coefficient of friction (ACOF) and under-shoe fluid dynamics. Five different slip-resistant shoes were progressively worn using an accelerated, abrasive, wear protocol. The ACOF and fluid forces (the load supported by the fluid) were measured as shoes were slipped across a surface contaminated with a diluted glycerol solution. As the shoes became worn, an initial increase in ACOF was followed by a steady decrease. Low fluid forces were observed prior to wear followed by increased fluid forces as the worn region became larger. Results suggest that traction performance decreases particularly when the heel region without tread exceeds a size of 800 mm2. This study supports the concept of developing shoe replacement guidelines based upon the size of the worn region to reduce occupational slips.

Effect of heel base area and walking speed on the utilized coefficient of friction during high-heeled walking

BACKGROUND

The utilized coefficient of friction (uCOF) and the risk of slipping are known to increase as the heel height of shoes increases. The heel base area of shoes can also affect the uCOF.

OBJECTIVE

The purpose of this study is to investigate the effect of the heel base area of high heels and walking speed on the uCOF during walking and their interaction effect.

METHODS

The walking experiment was conducted at the speed of 1.0 m/s and 1.25 m/s using four 9-cm high heels having different heel areas (narrow, moderate, wide, and wedge heels).

RESULTS

The peak uCOF was significantly lower when wearing the wide heels than when wearing the other heels. Wearing the narrow and moderate heels reduced the vertical ground reaction force (GRF) owing to the early timing of the peak anterior-posterior GRF and increased the peak uCOF. As the walking speed became faster, the peak uCOF became greater with more increases by the interaction effect when wearing the narrow and moderate heels than when wearing the wide and wedge heels.

CONCLUSIONS

These results imply that wearing narrow high heels should be considered carefully, as the potential for a slip could be high owing to the increase in the peak uCOF. If it is inevitable to wear narrow high heels, it is critical to walk at a slower speed than usual. It is better to wear high heels with a wide heel area, e.g., 3 cm*3 cm, rather than narrow high heels or even wedge heels to reduce the possibility of slipping.

Vinyl Composite Tile Surrogate for Mechanical Slip Testing

BACKGROUND

Vinyl composite tile (VCT), which is a common flooring in workplaces, is sometimes utilized as the standard floor material for mechanical slip testing experiments. Unfortunately, VCT is a sub-optimal standard test material, since it changes over time and is difficult to manufacture consistently.

PURPOSE

This study aimed to identify a durable laboratory-grade substitute flooring that could provide traction results that are representative of footwear performance on VCT.

METHODS

Eight polymer tiles (cast nylon, polyethylene, polycarbonate, acetal, Delrin, PTFE, polypropylene, and nylon) were tested and the available coefficient of friction (ACOF) was measured and compared with that of two VCT designs. First, a screening test was performed to identify good material candidates based on six shoes and two contaminants (water and oil). Two surrogate candidate tiles were then tested across 17 shoes and three contaminant conditions (water, sodium laurel sulfate, and oil).

RESULTS

Cast nylon tile was found to be the most generalizable VCT surrogate, exhibiting strong correlations with both VCTs for oil contamination. None of candidates were representative of the VCTs for other contaminants.

CONCLUSIONS

Cast nylon may be a useful alternative for VCT for standard slip testing of footwear in oily conditions.

Predicting slips based on the STM 603 whole-footwear tribometer under different coefficient of friction testing conditions

Assessing footwear slip-resistance is critical to preventing slip and fall accidents. The STM 603 (SATRA Technology) is commonly used to assess footwear friction but its ability to predict human slips while walking is unclear. This study assessed this apparatus' ability to predict slips across footwear designs and to determine if modifying the test parameters alters predictions. The available coefficient of friction (ACOF) was measured with the device for nine different footwear designs using 12 testing conditions with varying vertical force, speed and shoe angle. The occurrence of slipping and the required coefficient of friction was quantified from human gait data including 124 exposures to liquid contaminants. ACOF values varied across the test conditions leading to different slip prediction models. Generally, a steeper shoe angle (13°) and higher vertical forces (400 or 500 N) modestly improved predictions of slipping. This study can potentially guide improvements in predictive test conditions for this device. Practitioner Summary: Frictional measures by the STM603 (SATRA Technology) were able to predict human slips under liquid contaminant conditions. Test parameters did have an influence on the measurements. An increased shoe-floor testing angle resulted in better slip predictions than test methods specified in the ASTM F2913 standard.

Computational Model of Shoe Wear Progression: Comparison with Experimental Results

Worn shoes increase the risk of slip and fall accidents. Few research efforts have attempted to predict the progression of shoe wear. This study presents a computational modeling framework that simulates wear progression in footwear outsoles based on finite element analysis and Archard's equation for wear. The results of the computational model were qualitatively and quantitatively compared with experimental results from shoes subjected to an accelerated wear protocol. Key variables of interest were the order in which individual tread blocks were worn and the size of the worn region. The order in which shoe treads became completely worn were strongly correlated between the models and experiments (rs > 0.74, p < 0.005 for all of the shoes). The ability of the model to predict the size of the worn region varied across the shoe designs. Findings demonstrate the capability of the computational modeling methodology to provide realistic predictions of shoe wear progression. This model represents a promising first step to developing a model that can guide footwear replacement programs and footwear design with durable slip-resistance.

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.

Kinematics and kinetics of the shoe during human slips

This paper quantified the heel kinematics and kinetics during human slips with the goal of guiding available coefficient of friction (ACOF) testing methods for footwear and flooring. These values were then compared to the testing parameters recommended for measuring shoe-floor ACOF. Kinematic and kinetic data of thirty-nine subjects who experienced a slip incident were pooled from four similar human slipping studies for this secondary analysis. Vertical ground reaction force (VGRF), center of pressure (COP), shoe-floor angle, side-slip angle, sliding speed and contact time were quantified at slip start (SS) and at the time of peak sliding speed (PSS). Statistical comparisons were used to test if any discrepancies exist between the state of slipping foot and current ACOF testing parameters. The main findings were that the VGRF (26.7 %BW, 179.4 N), shoe-floor angle (22.1°) and contact time (0.02 s) at SS were significantly different from the recommended ACOF testing parameters. Instead, the testing parameters are mostly consistent with the state of the shoe at PSS. We argue that changing the footwear testing parameters to conditions at SS is more appropriate for relating ACOF to conditions of actual slips, including lower vertical forces, larger shoe-floor angles and shorter contact duration.