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Preprints, Working Papers, ... Year : 2022

Bi-layer stiffness identification of soft tissues by aspiration


The aim of this work was to develop both experimental and inverse analyses methods of aspiration/suction measurement onto bilayered soft tissues structures. An original aspiration system is described. The main features are volumic measurements (no camera or mirror constraining the aperture design), cyclic partial vacuum (reproducibility, airtightness checking), low deformation loading (elasticity domain, damageless for in vivo and in situ applications) and the use of disposable aspiration cups of various aperture diameters ranging between 4 and 30 mm (easy to sterilize, adaptable to accessibility constaints). The aspiration system was tested in silico on controlled silicone bilayer specimens (reference layers' Young Moduli characterized by tensile test, reference layers' thickness destructively measured a posteriori); the apparent stiffness of the bilayer structure is measured for 9 different aperture sizes. Using the experimental apparent stiffness changes with diameters, (i) the upper and lower layer Young moduli are identified in almost real-time using a Finite Element database interpolated with a Principle Component Analysis. Optionally, the optimal upper layer thickness is also identified. (ii) the possible ill-posedness of the problem is analysed in terms of parameter identifiability/indifference region (prediction of experimental standard deviation). For an upper layer thickness of about 3 mm, the Young moduli identified by aspiration onto a bilayer sample presented a relative error lower than 10% compared to reference values. The layer thickness was also identified with an error lower than 2%. These validations give confidence to apply this method in vivo and in situ to soft tissues such as human skin if considered as bilayered structures.
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Dates and versions

hal-03718672 , version 1 (09-07-2022)
hal-03718672 , version 2 (06-01-2023)


  • HAL Id : hal-03718672 , version 1


N Connesson, N Briot, P Y Rohan, P A Barraud, S A Elahi, et al.. Bi-layer stiffness identification of soft tissues by aspiration. 2022. ⟨hal-03718672v1⟩
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