Literature DB >> 26602374

Identification of hyperelastic properties of passive thigh muscle under compression with an inverse method from a displacement field measurement.

Jean-Sébastien Affagard1, Pierre Feissel2, Sabine F Bensamoun3.   

Abstract

The mechanical behavior of muscle tissue is an important field of investigation with different applications in medicine, car crash and sport, for example. Currently, few in vivo imaging techniques are able to characterize the mechanical properties of muscle. Thus, this study presents an in vivo method to identify a hyperelatic behavior from a displacement field measured with ultrasound and Digital Image Correlation (DIC) techniques. This identification approach was composed of 3 inter-dependent steps. The first step was to perform a 2D MRI acquisition of the thigh in order to obtain a manual segmentation of muscles (quadriceps, ischio, gracilis and sartorius) and fat tissue, and then develop a Finite Element model. In addition, a Neo-Hookean model was chosen to characterize the hyperelastic behavior (C10, D) in order to simulate a displacement field. Secondly, an experimental compression device was developed in order to measure the in vivo displacement fields in several areas of the thigh. Finally, an inverse method was performed to identify the C10 and D parameters of each soft tissue. The identification procedure was validated with a comparison with the literature. The relevance of this study was to identify the mechanical properties of each investigated soft tissues.
Copyright © 2015 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Digital Image Correlation (DIC); In vivo mechanical properties; Inverse method; Medical imaging; Thigh muscles

Mesh:

Year:  2015        PMID: 26602374     DOI: 10.1016/j.jbiomech.2015.10.007

Source DB:  PubMed          Journal:  J Biomech        ISSN: 0021-9290            Impact factor:   2.712


  2 in total

1.  Template models for simulation of surface manipulation of musculoskeletal extremities.

Authors:  Sean Doherty; Ben Landis; Tammy M Owings; Ahmet Erdemir
Journal:  PLoS One       Date:  2022-08-15       Impact factor: 3.752

Review 2.  Image-Based Finite Element Modeling Approach for Characterizing In Vivo Mechanical Properties of Human Arteries.

Authors:  Liang Wang; Akiko Maehara; Rui Lv; Xiaoya Guo; Jie Zheng; Kisten L Billiar; Gary S Mintz; Dalin Tang
Journal:  J Funct Biomater       Date:  2022-09-11
  2 in total

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