Literature DB >> 12877683

Coefficient of friction: tribological studies in man - an overview.

Raja K Sivamani1, Jack Goodman, Norm V Gitis, Howard I Maibach.   

Abstract

BACKGROUND/
PURPOSE: Compared to other studies of skin, relatively few studies have focused on the friction of skin. This work reviews existing skin friction, emphasizing test apparatuses and parameters that have added to information regarding the friction coefficient. This review also outlines what factors are important to consider in future friction studies.
METHODS: Past studies have utilized numerous designs for a test apparatus, including probe geometry and material, as well as various probe motions (rotational vs. linear). Most tests were performed in vivo; a few were performed in vitro and on porcine skin.
RESULTS: Differences in probe material, geometry and smoothness affect friction coefficient measurements. An increase in skin hydration, either through water or through moisturizer application, increases its friction coefficient; a decrease in skin hydration, either through clinical dermatitis or through alcohol addition, decreases the coefficient. Differences are present between anatomical sites. Conflicting results are found regarding age and no differences are apparent as a result of gender or race.
CONCLUSION: Skin friction appears to be dependent on several factors - such as age, anatomical site and skin hydration. The choice of the probe and the test apparatus also influence the measurement.

Entities:  

Mesh:

Year:  2003        PMID: 12877683     DOI: 10.1034/j.1600-0846.2003.02366.x

Source DB:  PubMed          Journal:  Skin Res Technol        ISSN: 0909-752X            Impact factor:   2.365


  12 in total

1.  A technique to determine friction at the fingertips.

Authors:  Adriana V Savescu; Mark L Latash; Vladimir M Zatsiorsky
Journal:  J Appl Biomech       Date:  2008-02       Impact factor: 1.833

2.  Force coordination in static manipulation tasks performed using standard and non-standard grasping techniques.

Authors:  Paulo B de Freitas; Slobodan Jaric
Journal:  Exp Brain Res       Date:  2009-02-27       Impact factor: 1.972

3.  Interpretation of the human skin biotribological behaviour after tape stripping.

Authors:  C Pailler-Mattei; C Guerret-Piécourt; H Zahouani; S Nicoli
Journal:  J R Soc Interface       Date:  2011-01-12       Impact factor: 4.118

4.  Fingerprint ridges allow primates to regulate grip.

Authors:  Seoung-Mok Yum; In-Keun Baek; Dongpyo Hong; Juhan Kim; Kyunghoon Jung; Seontae Kim; Kihoon Eom; Jeongmin Jang; Seonmyeong Kim; Matlabjon Sattorov; Min-Geol Lee; Sungwan Kim; Michael J Adams; Gun-Sik Park
Journal:  Proc Natl Acad Sci U S A       Date:  2020-11-30       Impact factor: 11.205

5.  Force fluctuations while pressing and moving against high- and low-friction touch screen surfaces.

Authors:  Mukta N Joshi; Kevin G Keenan
Journal:  Exp Brain Res       Date:  2016-02-22       Impact factor: 1.972

6.  Influence of epidermal hydration on the friction of human skin against textiles.

Authors:  L-C Gerhardt; V Strässle; A Lenz; N D Spencer; S Derler
Journal:  J R Soc Interface       Date:  2008-11-06       Impact factor: 4.118

7.  Influence of physico-chemical, mechanical and morphological fingerpad properties on the frictional distinction of sticky/slippery surfaces.

Authors:  Pierre-Henri Cornuault; Luc Carpentier; Marie-Ange Bueno; Jean-Marc Cote; Guy Monteil
Journal:  J R Soc Interface       Date:  2015-09-06       Impact factor: 4.118

8.  How to identify water from thickener aqueous solutions by touch.

Authors:  Yoshimune Nonomura; Taku Miura; Takaaki Miyashita; Yuka Asao; Hirokazu Shirado; Yasutoshi Makino; Takashi Maeno
Journal:  J R Soc Interface       Date:  2011-11-09       Impact factor: 4.118

9.  Quantifying the Frictional Forces between Skin and Nonwoven Fabrics.

Authors:  Kavinda Jayawardana; Nicholas C Ovenden; Alan Cottenden
Journal:  Front Physiol       Date:  2017-03-06       Impact factor: 4.566

10.  Modeling of Friction Phenomena of Ti-6Al-4V Sheets Based on Backward Elimination Regression and Multi-Layer Artificial Neural Networks.

Authors:  Tomasz Trzepieciński; Marcin Szpunar; Ľuboš Kaščák
Journal:  Materials (Basel)       Date:  2021-05-15       Impact factor: 3.623

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