| Title |
Biomechanical behavior of human crural fascia in anterior and posterior regions of the lower limb
|
|---|---|
| Published in |
Medical & Biological Engineering & Computing, May 2015
|
| DOI | 10.1007/s11517-015-1308-5 |
| Pubmed ID | |
| Authors |
Piero G. Pavan, Paola Pachera, Carla Stecco, Arturo N. Natali |
| Abstract |
The present work focuses on the numerical modeling of the mechanical behavior of the crural fascia, the deep fascia enwrapping the lower limb muscles. This fascia has an important biomechanical role, due to its interaction with muscles during contraction and its association with pathological events, such as compartment syndrome. The mechanical response of the crural fascia is described by assuming a hyperelastic fiber-reinforced constitutive model, with families of fibers disposed according to the spatial disposition of the collagen network, as shown in histological analyses. A two-dimensional finite element model of a lower limb transversal section has been developed to analyze deformational behavior, with particular attention on interaction phenomena between crural fascia and enwrapped muscles. The constitutive model adopted for the crural fascia well fits experimental data taken along the proximal-distal and medial-lateral directions. The finite element analysis allows for interpreting the relation between change in volume and pressure of muscle compartments and the crural fascia deformation. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 46 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 11 | 24% |
| Student > Bachelor | 8 | 17% |
| Researcher | 5 | 11% |
| Professor | 3 | 7% |
| Student > Ph. D. Student | 3 | 7% |
| Other | 3 | 7% |
| Unknown | 13 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 9 | 20% |
| Engineering | 6 | 13% |
| Nursing and Health Professions | 6 | 13% |
| Sports and Recreations | 5 | 11% |
| Agricultural and Biological Sciences | 2 | 4% |
| Other | 5 | 11% |
| Unknown | 13 | 28% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 29 May 2015.
All research outputs
#20,657,128
of 25,374,917 outputs
Outputs from Medical & Biological Engineering & Computing
#1,812
of 2,053 outputs
Outputs of similar age
#206,119
of 279,894 outputs
Outputs of similar age from Medical & Biological Engineering & Computing
#12
of 16 outputs
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