Dadkhah Davood, Ghomashchi Hamed, Dutta Tilak
KITE Research Institute, Toronto Rehabilitation Institute, 550 University Ave, Toronto, M5G 2A2, Ontario, Canada; Institute of Biomedical Engineering, University of Toronto, 164 College St., Toronto, M5S 3G9, Ontario, Canada.
KITE Research Institute, Toronto Rehabilitation Institute, 550 University Ave, Toronto, M5G 2A2, Ontario, Canada.
Appl Ergon. 2025 Jul;126:104487. doi: 10.1016/j.apergo.2025.104487. Epub 2025 Mar 18.
Fall-related injuries on icy surfaces are a major public health concern. Slip-resistant winter boots that incorporate the latest composite outsole technologies have demonstrated the potential to prevent falls in winter weather in lab-based testing. However, the real-world benefits of this composite footwear remain difficult to measure because of a lack of accurate evaluation methods. In particular, existing methods rely on comparing self-reported slip counts to identify differences in slip resistance performance between different footwear models. However, prior research has primarily focused on slip detection on soapy and oily surfaces, revealing that small slips (≤30 mm) often go undetected, with humans correctly identifying them only 50% of the time. No studies have yet examined slip perception on icy surfaces, which possess significantly lower coefficients of friction compared to soapy and oily environments. The objective of this study was to investigate the agreement between self-reported slip counts and motion capture detected slips while walking on ice with winter footwear. Twenty-five healthy participants were asked to walk on ice surfaces (melting ice 0.5 ± 1.0 °C and cold ice -3.5 ± 1.0 °C) while wearing three models of winter boots with varying slip resistance performance (poor, moderate, good) and were asked to report any slips they experienced. Ground truth slip identification and slip length measurement was done using an 8-camera Vicon motion capture system. Slips were categorized as small slips (≤30 mm), moderate slips (30-100 mm), or large slips (>100 mm) for each boot and the proportion detected by participants was calculated. A total of 7743 slips were identified from 53,944 steps captured by the motion capture system with 4395, 1999 and 1349 slips recorded from the boots with poor, moderate and good slip resistance, respectively. These included 1658 small slips, 2521 moderate slips, and 3564 large slips. Overall, participants only reported 38.3% of these slips including 375 small slips (22.6% reported), 823 moderate slips (32.6% reported) and 1767 large slips (49.6% reported). These findings showed a strong positive correlation between self-reported slips and slip length (ρ = 0.573, p<0.001) demonstrating that participants were significantly more likely to report larger slips. The findings of this study demonstrate the need to develop more objective methods of recording slip events for real-world winter footwear evaluations.
在结冰路面上因跌倒而导致的伤害是一个重大的公共卫生问题。采用最新复合外底技术的防滑冬季靴子在实验室测试中已显示出预防冬季跌倒的潜力。然而,由于缺乏准确的评估方法,这种复合鞋类在现实世界中的益处仍难以衡量。特别是,现有方法依赖于比较自我报告的滑倒次数来确定不同鞋类模型之间防滑性能的差异。然而,先前的研究主要集中在肥皂和油性表面的滑倒检测上,结果表明小滑倒(≤30毫米)往往未被察觉,人类正确识别它们的概率仅为50%。尚无研究考察在结冰表面上的滑倒感知情况,结冰表面的摩擦系数相比肥皂和油性环境要低得多。本研究的目的是调查在穿着冬季鞋类在冰面上行走时,自我报告的滑倒次数与动作捕捉检测到的滑倒之间的一致性。25名健康参与者被要求穿着三种防滑性能不同(差、中、好)的冬季靴子在冰面上行走(融冰温度0.5±1.0°C,冷冰温度-3.5±1.0°C),并要求他们报告所经历的任何滑倒情况。使用8台摄像机的Vicon动作捕捉系统进行地面真实滑倒识别和滑倒长度测量。为每双靴子将滑倒分为小滑倒(≤30毫米)、中滑倒(30 - 100毫米)或大滑倒(>100毫米),并计算参与者检测到的比例。动作捕捉系统从53944步中总共识别出7743次滑倒,其中防滑性能差、中、好的靴子分别记录到4395次、1999次和1349次滑倒。这些滑倒包括1658次小滑倒、2521次中滑倒和3564次大滑倒。总体而言,参与者仅报告了这些滑倒中的38.3%,包括375次小滑倒(报告了22.6%)、823次中滑倒(报告了32.6%)和1767次大滑倒(报告了49.6%)。这些发现表明自我报告的滑倒与滑倒长度之间存在很强的正相关(ρ = 0.573,p<0.001),这表明参与者报告较大滑倒的可能性显著更高。本研究的结果表明,需要开发更客观的方法来记录现实世界中冬季鞋类评估的滑倒事件。