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InfoResearchPeer-reviewed
Multimodal Transformer-Based Gait Analysis and Deep Learning Model for Slip-Resistant Footwear Evaluation
- Published
- Record updated
Summary
Researchers built a transformer-based regression model that fuses temporal biomechanical features, outsole images, footwear metadata and anthropometric data to predict personalized slip resistance scores for 84 footwear models. Trained on 578 walking trials by 18 participants on wet and dry ice, the model performed better on dry surfaces (RMSE 1.34° ± 0.34°, R² 0.45 ± 0.09, MAPE 10.48% ± 3.58%) than on wet surfaces (RMSE 2.34° ± 0.43°, R² 0.47 ± 0.12, MAPE 21.45% ± 6.89%).