Department of Bioengineering, University of Pittsburgh, 3700 O'Hara St., Pittsburgh, PA, 15213, USA.
Department of Bioengineering, University of Pittsburgh, 3700 O'Hara St., Pittsburgh, PA, 15213, USA.
Appl Ergon. 2024 Jan;114:104110. doi: 10.1016/j.apergo.2023.104110. Epub 2023 Aug 16.
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.
鞋底设计极大地影响滑倒风险。某些易于测量的胎面特征已被证明可以预测摩擦性能。本研究旨在复制这些发现，并量化它们预测滑倒的能力。参与者（n=34）穿着防滑鞋，暴露在涂有低摩擦油的地板表面上。根据胎面表面积、斜角和硬度预测每个鞋底的动摩擦系数（COF）。测量 COF，并确定滑倒结果。预测的和测量的 COF 相关，测量的 COF 是滑倒结果的敏感预测因子。预测 COF 与滑倒结果的关系比预期的要弱，且不具有统计学意义。本研究部分证实了先前回归方程预测 COF 的能力。然而，效应大小比之前报道的要弱，预测 COF 对预测滑倒并不敏感。
