Extended Data Fig. 9: Surface texture classification results using SS values recorded after mechanical stimulation.

For ML, we collected 2560 EPSC signals (1280 SA signals and 1280 FA signals) using the ASMRs array, spanning 16 categories of textures. a-c, Confusion matrices illustrating the surface texture classification accuracy (highest) using features from (a) SA, (b) FA ASMRs, and (c) multimodal fusion of SA and FA (SA/FA) features for the classification of 16 texture categories (that is, 1: Cotton 100%, 2: polyester 100%, 3: rayon 100%, 4: nylon 100%, 5: acetate 100%, 6: cotton 65%-polyester 35%, 7: polyester 85%-spandex 15%, 8: cotton 52%-nylon 48%, 9: polyester 56%-rayon 44%, 10: nylon 54%-rayon 46%, 11: cashmere 100%, 12: linen 100%, 13: cowhide 100%, 14: skin, 15: nitrile 100%, and 16: Al foil). d-f, Receiver operating characteristic (ROC) curves for texture classification using (d) SA features, (e) FA features, and (f) combined SA/FA features.