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

Beschorner, Kurt E.; Iraqi, Arian; Redfern, Mark S.; Cham, Rakié; Li, Yue

doi:10.1080/00140139.2019.1567828

Cited by 27 publications

(13 citation statements)

References 49 publications

(58 reference statements)

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“…Many of the participants then changed to a different pair of footwear, performed at least 15 baseline walking trials to allow them to return to baseline gait, and then were exposed to a second liquid contaminant. Data from the second exposure was not included if the participant experienced a slip during the first exposure or if they showed other signs of anticipation as described in Beschorner et al (2019).…”

Section: Review Of Previous Studymentioning

confidence: 99%

“…Receiver operating characteristic (ROC) curves were developed to map sensitivity and specificity of the model. For each of the intervals, the ROC curves were compared using a χ 2 test (Beschorner et al, 2019). Specifically, the three shorter intervals (2, 50, 100 ms) were compared relative to the longer time-interval (i.e., current practice, 200 ms, Bonferroni correction: 0.05/3 = 0.017).…”

Section: Validity Analysis-mentioning

confidence: 99%

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

et al. 2020

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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 timeinterval 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.

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Section: Review Of Previous Studymentioning

confidence: 99%

Section: Validity Analysis-mentioning

confidence: 99%

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

et al. 2020

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“…Some studies have evaluated the ability of the standard mechanical test method to provide a footwear slipperiness measurement representative of the actual footwear performance experienced by human participants walking on contaminated indoor surfaces [ 35 , 36 , 37 ]. Human-based approaches are more externally valid means of assessing footwear function, since they take into account the capacity of human beings to adapt their gait to hazardous conditions [ 15 , 38 ].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Winter Footwear: Comparison of Test Methods to Determine Footwear Slip Resistance on Ice Surfaces

Fekr

Gauvin

et al. 2021

IJERPH

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The use of slip-resistant winter footwear is crucial for the prevention of slips and falls on ice and snow. The main objective of this paper is to evaluate a mechanical testing method to determine footwear slip resistance on wet and dry ice surfaces and to compare it with the human-centred test method introduced by researchers at KITE (Knowledge, Innovation, Talent, Everywhere)-Toronto Rehabilitation Institute-University Health Network. Phase 1 of this study assessed the repeatability and reproducibility of the mechanical method by evaluating ten different occupational winter boots using two SATRA Slip resistance testers (STM 603, SATRA Technology Centre, Kettering, UK). One tester is located in Toronto and one in Montreal. These boots were chosen based on the needs of the IRSST (Institut de Recherche Robert-Sauvé en Santé et en Sécurité du Travail, Montréal, Quebec, Canada), who were primarily interested in providing safe winter footwear for police, firefighters and municipal workers. In Phase 2, the results of the human-centred test approach were compared with the mechanical results. In Phase 3, two of these boots with conflicting results from the previous phases were tested using a second human-centred method. In Phase 1, the mechanical testing results obtained in the two labs showed a high linear correlation (>0.94) and good agreement on both ice surfaces; however, they revealed a bias (~0.06) between the two labs on the dry ice condition. The mechanical and human-centred tests (phase 2) were found to be better correlated in the wet ice condition (R = 0.95) compared to the dry ice condition (R = 0.34). Finally, the rating of the footwear slip resistance based on the number of slips counted in phase 3 was consistent with the rating by the human-centred test method (phase 2), but not the mechanical method (phase 1). The findings of this study provide a better understanding of the limitations of the SATRA ice tray for measuring footwear slip resistance and demonstrate that the mechanical method must be further refined to make it more comparable to the human-centred methods to achieve better agreement with real-world performance.

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“…The former requires the recruitment of human participants and the use of one or more force platforms so as to analyze the ground reaction force of the foot on the floor [12,13]. The latter, on the other hand, requires the use of a friction measurement device, also called a tribometer or a slipmeter, to measure the COF of the floor under certain footwear and floor conditions [9,14]. The required friction depends on the gait pattern of a walker and is dependent on human factors [11,15,16].…”

Section: Introductionmentioning

confidence: 99%

“…The friction measurements conducted in the laboratory were normally performed to explore the mechanisms of slipping of the shoe sole on the floor. Studies testing the effects of the floor, footwear, floor inclined angle, and floor surface contaminations on slipperiness have been reported [14,18,[23][24][25][26][27][28][29][30][31][32]. There were also studies comparing the testing parameters, test methods, reliability, and validity of friction measurement devices [13,17,[32][33][34][35].…”

Section: Introductionmentioning

confidence: 99%

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

Khaday

Peng

et al. 2021

Coatings

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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.

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

Cited by 27 publications

References 49 publications

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

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

Evaluation of Winter Footwear: Comparison of Test Methods to Determine Footwear Slip Resistance on Ice Surfaces

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

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