Feasibility study demonstrates friction prediction through strain mapping in finger pads, suggesting new insights into grip control.
Finger pad strain governs grip control and tactile feedback, yet in vivo measurements during sliding remain scarce. This feasibility study utilised 3D‐digital image correlation (3D‐DIC) and optical coherence tomography (OCT) for quantifying surface strains and subsurface deformation in a human finger pad during static/dynamic glass contact, linking both to the respective friction behaviour. Principal strains increase systematically with normal load (0.5–3 N), concentrating at the mechanoreceptor‐rich fingertip under dynamic sliding (peak ε 1 2%–7.5%). Friction (CoF 0.4–0.8) and apparent contact area follow load‐dependent power laws, with adhesion dominating. Multiscale imaging validates surface strain as a reliable friction predictor, providing good proof‐of‐concept for strain‐based human finger pad friction modelling despite subsurface measurement limitations.
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Lee et al. (2026) studied this question.
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