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Tactile perception of randomly rough surfaces

  • Most everyday surfaces are randomly rough and self-similar on sufficiently small scales. We investigated the tactile perception of randomly rough surfaces using 3D-printed samples, where the topographic structure and the statistical properties of scale-dependent roughness were varied independently. We found that the tactile perception of similarity between surfaces was dominated by the statistical micro-scale roughness rather than by their topographic resemblance. Participants were able to notice differences in the Hurst roughness exponent of 0.2, or a difference in surface curvature of 0.8 $$\hbox {mm}^{-1}$$mm-1for surfaces with curvatures between 1 and 3 $$\hbox {mm}^{-1}$$mm-1. In contrast, visual perception of similarity between color-coded images of the surface height was dominated by their topographic resemblance. We conclude that vibration cues from roughness at the length scale of the finger ridge distance distract the participants from including the topography into the judgement of similarity. The interaction between surface asperities and fingertip skin led to higher friction for higher micro-scale roughness. Individual friction data allowed us to construct a psychometric curve which relates similarity decisions to differences in friction. Participants noticed differences in the friction coefficient as small as 0.035 for samples with friction coefficients between 0.34 and 0.45.

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Document Type:Article
Author:Riad SahliORCiD, Aubin Prot, Anle WangORCiD, Martin MüserORCiD, Michal PiovarciORCiD, Piotr DidykORCiD, Roland BennewitzORCiD
Parent Title (English):Scientific reports
First Page:15800
Year of first Publication:2020
Release Date:2022/08/30
Tag:materials Science; mathematics and computing; physics; physiology; psychology
Impact:04.379 (2020)
Interaktive Oberflächen
DDC classes:500 Naturwissenschaften und Mathematik / 530 Physik
600 Technik, Medizin, angewandte Wissenschaften / 610 Medizin, Gesundheit
000 Allgemeines, Informatik, Informationswissenschaft / 004 Informatik
Open Access:Open Access
Signature:INM 2020/100
Licence (German):License LogoCreative Commons - CC BY - Namensnennung 4.0 International