Multimodal Transformer-Based Gait Analysis and Deep Learning Model for Slip-Resistant Footwear Evaluation

Researchers developed a transformer-based regression model (a type of deep learning architecture that processes sequential data) that combines movement data, shoe sole images, shoe information, and body measurements to predict how slip-resistant different shoes are on icy surfaces. Testing on 84 different shoes across 578 walking trials showed the model worked better on dry ice than wet ice, suggesting that combining biomechanical data with shoe characteristics could help prevent slip-related injuries.