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

Citation

Beschorner, Kurt et al. (2021), Worn region size of shoe outsole impacts human slips: Testing a mechanistic model, Dryad, Dataset, https://doi.org/10.5061/dryad.vmcvdncsk

Abstract

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.

Methods

Detailed information on this study is available in [1].

Row structure:

Each row represents a separate participant

Column Structure:

Column A (“Worn Region Size [mm^2]”) represents the product of the worn region length and width in mm2 [1].

Column B (“ACOF”) represents the shoe average available coefficient of friction from the five slip testing trials [1].

Column C (“Slip Distance [m]”) represents the slip distance after exposure to the slippery contaminant. This variable was not reported in [1]. The methodological details for calculating this value is reported in [2].

Column D (“Peak Slip Speed [m/s]”) represents the peak slipping speed after exposure to the slippery contaminant as reported in [1].

Column E (“Age”) represents the age of the shoe as reported by the participant. The value “0” represents less than 6 months old, “6” represents between 6 and 12 months old, and “12” indicates more than 12 months.

Column F (“Slip outcome based on slip distance”) represents a binary outcome variable to determine whether the participant experienced a slip. A value of 1 means a slip (Slip Distance [m] > 0.03) and a value of 0 means no slip [2].

Column G (“Slip outcome based on peak slip speed”) represents a binary outcome variable to determine whether the participant experienced a slip. A value of 1 means a slip (Peak Slip Speed [m/s]> 0.2) and a value of 0 means no slip [1].

Column H (“Peak fluid pressure [kPa]”) represents the peak fluid pressure throughout the slip and across the fluid pressure sensors [1].

Column I (“Slip Resistant Shoe”) represents a binary variable to indicate whether the shoe was considered to be slip-resistant (1) or no slip-resistant (0) as described in [1].

Column J (“Excluded from analyses?”) indicates whether a variable was excluded from some of the analyses. “Exclude from pressure” indicates that the participant was excluded from all analyses involving fluid pressure data because their foot did not slide over the fluid pressure sensors. "Exclude from ACOF" indicates that the participant was excluded from analyses involving ACOF because of missing data. "none" indicates that none of the data was excluded from the analyses.

[1] Sundaram, V.H., Hemler, S.L., Chanda, A., Haight, J.M., Redfern, M.S. and Beschorner, K.E., 2020. Worn region size of shoe outsole impacts human slips: Testing a mechanistic model. Journal of Biomechanics, p.109797.

[2] Iraqi, A., Cham, R., Redfern, M.S. and Beschorner, K.E., 2018. Coefficient of friction testing parameters influence the prediction of human slips. Applied ergonomics70, pp.118-126.

Funding

National Science Foundation, Award: DGE 1650115

National Center for Research Resources, Award: S10RR027102

National Institute for Occupational Safety and Health, Award: R01OH010940