The Influence of Footwear Sole Edges on Slip Resistance Prediction

Slips and falls are a significant public health concern worldwide, especially in environments with slippery surfaces. Wearing footwear with high slip resistance is a critical strategy for preventing slips. Outsole patterns are known to play a key role in determining slip resistance, which is typically assessed through mechanical or human-centered testing methods. In this paper, we analyzed the slip resistance ratings of 100 types of footwear to investigate whether the outsole edge, as one of the design factors, influences these ratings. Our dataset consists of 50 high-and 50 low-slip-resistance footwear samples. We trained two Data-Efficient Image Transformers (DeiT): one using only the outsole tread images and the other incorporating both outsole and side sole edge images to predict the binary slip resistance category. The models were evaluated using a 5-fold cross-validation. Our results demonstrated that incorporating the side sole edge into the DeiT model significantly improved performance, with the fused model achieving 81.00% 4.18% accuracy, compared to 72.00% 5.70% for the outsole-only model. Statistical analysis also confirmed the effectiveness of the fused model, highlighting the importance of the edge of the side of the outsole to determine the characteristics of slip resistance. These findings suggested that the side edge that also includes curvature should be considered in future AI-based models for slip resistance prediction and ultimately, footwear designs for enhanced safety, particularly in high-risk environments such as icy surfaces.Clinical relevance- This study highlights that the outsole side edge improves slip resistance prediction, which clinically can help reduce fall injuries, especially for at-risk populations.