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Mechanical characterisation of commercial artificial skin models. | LitMetric

Mechanical characterisation of commercial artificial skin models.

J Mech Behav Biomed Mater

UCD Centre for Biomedical Engineering, University College Dublin, Belfield Dublin 4, Ireland; I-Form Advanced Manufacturing Research Centre, School of Mechanical & Materials Engineering, University College Dublin, Belfield Dublin 4, Ireland; UCD Charles Institute of Dermatology, School of Medicine, University College Dublin, Belfield Dublin 4, Ireland. Electronic address:

Published: November 2023

Understanding of the mechanical properties of skin is crucial in evaluating the performance of skin-interfacing medical devices. Artificial skin models (ASMs) have rapidly gained attention as they are able to overcome the challenges in ethically sourcing consistent and representative ex vivo animal or human tissue models. Although some ASMs have become commercialised, a thorough understanding of the mechanical properties of the skin models is crucial to ensure that they are suitable for the purpose of the study. In the present study, skin and fat layers of ASMs (Simulab, LifeLike, SynDaver and Parafilm) were mechanically characterised through hardness, needle insertion, tensile and compression testing. Different boundary constraint conditions (minimally and highly constrained) were investigated for needle insertion testing, while anisotropic properties of the skin models were investigated through different specimen orientations during tensile testing. Analysis of variance (ANOVA) tests were performed to compare the mechanical properties between the skin models. Properties of the skin models were compared against literature to determine the suitability of the skin models based on the material property of interest. All skin models offer relatively consistent mechanical performance, providing a solid basis for benchtop evaluation of skin-interfacing medical device performance. Through prioritising models with mechanical properties that are consistent with human skin data, and with limited variance, researchers can use the data presented here as a toolbox to select the most appropriate ASM for their particular application.

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Source
http://dx.doi.org/10.1016/j.jmbbm.2023.106090DOI Listing

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