Complexity, rate, and scale in sliding friction dynamics between a finger and textured surface

Abstract Sliding friction between the skin and a touched surface is highly complex, but lies at the heart of our ability to discriminate surface texture through touch. Prior research has elucidated neural mechanisms of tactile texture perception, but our understanding of the nonlinear dynamics of fr...

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Autores principales:	Behnam Khojasteh, Marco Janko, Yon Visell
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2018
Materias:	Real Finger Force Simulation Force Fluctuations Recurrence Analysis Tactile Exploration Medicine R Science Q
Acceso en línea:	https://doaj.org/article/e4c66104051641c29520502467f85b70
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spelling	oai:doaj.org-article:e4c66104051641c29520502467f85b702021-12-02T15:08:43ZComplexity, rate, and scale in sliding friction dynamics between a finger and textured surface10.1038/s41598-018-31818-32045-2322https://doaj.org/article/e4c66104051641c29520502467f85b702018-09-01T00:00:00Zhttps://doi.org/10.1038/s41598-018-31818-3https://doaj.org/toc/2045-2322Abstract Sliding friction between the skin and a touched surface is highly complex, but lies at the heart of our ability to discriminate surface texture through touch. Prior research has elucidated neural mechanisms of tactile texture perception, but our understanding of the nonlinear dynamics of frictional sliding between the finger and textured surfaces, with which the neural signals that encode texture originate, is incomplete. To address this, we compared measurements from human fingertips sliding against textured counter surfaces with predictions of numerical simulations of a model finger that resembled a real finger, with similar geometry, tissue heterogeneity, hyperelasticity, and interfacial adhesion. Modeled and measured forces exhibited similar complex, nonlinear sliding friction dynamics, force fluctuations, and prominent regularities related to the surface geometry. We comparatively analysed measured and simulated forces patterns in matched conditions using linear and nonlinear methods, including recurrence analysis. The model had greatest predictive power for faster sliding and for surface textures with length scales greater than about one millimeter. This could be attributed to the the tendency of sliding at slower speeds, or on finer surfaces, to complexly engage fine features of skin or surface, such as fingerprints or surface asperities. The results elucidate the dynamical forces felt during tactile exploration and highlight the challenges involved in the biological perception of surface texture via touch.Behnam KhojastehMarco JankoYon VisellNature PortfolioarticleReal FingerForce SimulationForce FluctuationsRecurrence AnalysisTactile ExplorationMedicineRScienceQENScientific Reports, Vol 8, Iss 1, Pp 1-10 (2018)
institution	DOAJ
collection	DOAJ
language	EN
topic	Real Finger Force Simulation Force Fluctuations Recurrence Analysis Tactile Exploration Medicine R Science Q
spellingShingle	Real Finger Force Simulation Force Fluctuations Recurrence Analysis Tactile Exploration Medicine R Science Q Behnam Khojasteh Marco Janko Yon Visell Complexity, rate, and scale in sliding friction dynamics between a finger and textured surface
description	Abstract Sliding friction between the skin and a touched surface is highly complex, but lies at the heart of our ability to discriminate surface texture through touch. Prior research has elucidated neural mechanisms of tactile texture perception, but our understanding of the nonlinear dynamics of frictional sliding between the finger and textured surfaces, with which the neural signals that encode texture originate, is incomplete. To address this, we compared measurements from human fingertips sliding against textured counter surfaces with predictions of numerical simulations of a model finger that resembled a real finger, with similar geometry, tissue heterogeneity, hyperelasticity, and interfacial adhesion. Modeled and measured forces exhibited similar complex, nonlinear sliding friction dynamics, force fluctuations, and prominent regularities related to the surface geometry. We comparatively analysed measured and simulated forces patterns in matched conditions using linear and nonlinear methods, including recurrence analysis. The model had greatest predictive power for faster sliding and for surface textures with length scales greater than about one millimeter. This could be attributed to the the tendency of sliding at slower speeds, or on finer surfaces, to complexly engage fine features of skin or surface, such as fingerprints or surface asperities. The results elucidate the dynamical forces felt during tactile exploration and highlight the challenges involved in the biological perception of surface texture via touch.
format	article
author	Behnam Khojasteh Marco Janko Yon Visell
author_facet	Behnam Khojasteh Marco Janko Yon Visell
author_sort	Behnam Khojasteh
title	Complexity, rate, and scale in sliding friction dynamics between a finger and textured surface
title_short	Complexity, rate, and scale in sliding friction dynamics between a finger and textured surface
title_full	Complexity, rate, and scale in sliding friction dynamics between a finger and textured surface
title_fullStr	Complexity, rate, and scale in sliding friction dynamics between a finger and textured surface
title_full_unstemmed	Complexity, rate, and scale in sliding friction dynamics between a finger and textured surface
title_sort	complexity, rate, and scale in sliding friction dynamics between a finger and textured surface
publisher	Nature Portfolio
publishDate	2018
url	https://doaj.org/article/e4c66104051641c29520502467f85b70
work_keys_str_mv	AT behnamkhojasteh complexityrateandscaleinslidingfrictiondynamicsbetweenafingerandtexturedsurface AT marcojanko complexityrateandscaleinslidingfrictiondynamicsbetweenafingerandtexturedsurface AT yonvisell complexityrateandscaleinslidingfrictiondynamicsbetweenafingerandtexturedsurface
_version_	1718388033146847232

Complexity, rate, and scale in sliding friction dynamics between a finger and textured surface

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