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Human Facial Soft Tissue Thickness and Mechanical Properties: A Literature Review


Abstract and Figures

The finite element method (FEM) has been used in human facial modeling both in clinical and engineering fields for decades. Applications of human head modeling include the interaction of personal protective equipment with the human head and modeling head impact. In human head modeling, it is critical to have a high fidelity model including accurate thicknesses of each layer and accurate material properties. Various experiments have been performed but do not report consistent results; therefore, it is difficult to find reliable parameter values to create an effective model of the human head. This paper attempts to review and summarize the state of the art of human facial studies including experimental measurements of different layer thicknesses and the mechanical properties of these layers.
Content may be subject to copyright.
Ming Xu
Human-Centric Design Research Lab
Department of Mechanical Engineering
Texas Tech University
Lubbock, TX 79409, USA
James Yang*
Human-Centric Design Research Lab
Department of Mechanical Engineering
Texas Tech University
Lubbock, TX 79409, USA
The finite element method (FEM) has been used in human
facial modeling both in clinical and engineering fields for
decades. Applications of human head modeling include the
interaction of personal protective equipment with the human
head and modeling head impact. In human head modeling, it is
critical to have a high fidelity model including accurate
thicknesses of each layer and accurate material properties.
Various experiments have been performed but do not report
consistent results; therefore, it is difficult to find reliable
parameter values to create an effective model of the human
head. This paper attempts to review and summarize the state of
the art of human facial studies including experimental
measurements of different layer thicknesses and the mechanical
properties of these layers.
Keywords: Human head modeling; facial soft tissue; material
properties; finite element method.
The human head houses several of the most important
components of the body, including the brain, mouth, nose, and
eyes. Significant research has been dedicated to the creation of
personal protective equipment (PPE) such as helmets and
respirators which protect against brain trauma and restrict
contaminants from entering the respiratory system.
Additionally, a significant portion of vehicle design is aimed at
preventing injury to the head during a collision. Traditional
evaluation of PPE tests physical prototypes using experiments.
However, with high speed computational tools and advanced
software, it is much easier to assess new protective equipment
designs at an early stage without physical prototypes. To create
effective simulations, it is critical to have high fidelity human
head models which include accurate segment geometries and
mechanical properties. In the literature, various thicknesses of
human facial skin and soft tissues and linear and nonlinear
mechanical properties have been reported. It is difficult to
determine which parameter values are acceptable for an
interaction simulation between the head and PPE. The objective
of this paper is to provide a summary of the literature reporting
mechanical properties and thicknesses of human facial skin and
soft tissues which will be useful for the creation of human head
models. In literature, finite element facial models simulating
facial soft tissues are mainly divided into two groups: linear
elastic models and nonlinear elastic models. Linear elastic
models treat the facial tissue as a homogeneous, linear elastic
material. For a linear elastic model, Hooke’s law is applied to
describe the material properties using two parameters: Young’s
modulus and Poisson’s ratio. The stress-strain response is
assumed to be linear under the condition that the tissues have
small deformations. Several researchers (Keeve et al., 1998;
Koch et al., 1999; Zachow et al., 2000) have used this method
to model the deformation of the facial tissue. These simplified
linear models produce solutions much more quickly; however,
some researchers have reported that linear facial models
become inaccurate when the deformations are large (Picinbono
et al., 2000, Gladilin et al., 2003). Fung (1993) showed in an
experiment that stress increases much faster than linearly after
relative strain becomes larger than 10% or 15%. The skin has
been proved to be a non-linear, anistropic and viscoelastic
material, which is too complex for a linear elastic model to
describe (Daly, 1982; Silver et al., 2001). Gerard et al. (2005)
created FE hyperelastic models for the cheek and tongue. Other
researchers created nonlinear isotropic models to describe the
mechanical behavior of the human skin. These include Ogden
(Lapeer et al., 2010; Shergold et al., 2006; Evans and Holt,
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Computers and Information in Engineering Conference
August 2-5, 2015, Boston, Massachusetts, USA
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2009; Flyn et al., 2011), Mooney-Rivlin (Hendriks, 2003) and
neo-Hookean (Delalleau et al., 2008) material models. For the
muscle, hyperplastic (Cox et al., 2007; Jia et al., 2006; Linder-
Ganz and Gefen, 2004) and viscoelastic (Aritan et al., 2008;
Best et al., 1994; Bosboom et al., 2001; Van Loocke et al.,
2008) models have been introduced in literature.
The facial soft tissues are those from the skin surface to the
most superficial surface of the underlying bone (Stephan and
Simpson, 2008). The facial soft tissues consist of three layers:
skin, subcutaneous tissue and muscle (Gladilin, 2003), where
the subcutaneous layer is mainly composed of fatty tissue. The
structure of these layers is shown in Figure 1. The thickness of
facial soft tissues varies for different sites, and in the literature,
most researchers have tested the thickness of facial soft tissues
at several different sites (Pelican and Seidenari, 1999). Figure 2
shows the names of different sites on human face. The major
facial muscles include the masseter, levator labii superioris, and
zygomaticus major muscles shown in Figure 3.
Figure 1. Facial soft tissue structure
Figure 2. Facial sites
Facial skin thickness
Accurate measurements for the thickness of human facial skin
are valuable in both clinical and scientific fields. The thickness
of human facial skin varies with age, race, and exposure to
sunlight (Warren et al., 1991). The measured thickness of
human facial skin depends on the method of measurement. In
the literature, methods of measuring skin thickness can be
divided into two groups: in vivo which is on living people
(Takema et al., 1994) and in vitro which is on cadavers (Ha et
al., 2005). Generally, in vivo studies are considered more
accurate than in vitro studies. However, there is no significant
difference between the results of these two kinds of studies (Ha
et al., 2005; Takema et al., 1994). Most researchers have used
in vivo methods to measure skin thickness because of the lower
cost and higher efficiency compared to the in vitro method. In
vivo, pulsed ultrasound, micrometer screw gauges (Newton et
al., 1984), skinfold caliper (Dykes et al., 1976), and
radiography methods (Bilznak and Staple, 1975; Cho et al.,
2011; Newton et al., 1984) have been used to provide absolute
values for facial skin thickness. It is well believed that the
radiography method might pose a biomedical hazard to the
human body. The skinfold caliper is not popular among
researchers because it can’t provide sufficient results compared
to other measurement methods. Most of the researchers used
ultrasound to measure the skin thickness (Denda and
Takahashi, 1990; Diridollou et al., 2001; Gibney et al., 2010;
Laurent et al., 2007; Mak et al., 2014; Ploin et al., 2011; Rigal
et al., 1989; Seidenari et al., 1994). There are two forms of
ultrasound measuring methods: A mode and B mode. A-mode
ultrasound devices are believed to be easier to operate than B-
mode ultrasound devices (Seidenari et al., 1994). Tan et al.
(1982) reported that the skin thicknesses obtained from in vitro
measurement are larger than those obtained from in vivo
measurement because of the loss of resting dermal tension and
potential distortion of the sample during biopsy. Denda and
Takahasi (1990) reported that the facial skin thickness on the
forehead and cheek decreases with age. However, Takema et al.
(1994) reported that the facial skin thickness has a linear
increase with age on the forehead and cheek while in the corner
of the mouth the skin thickness remains constant. Both groups
used and A-mode scanner (Dermascan A, Cortex Technology,
Denmark), and their conclusions are contradictory. A potential
reason is that the A-mode scanner cannot determine the
interface between the dermis and subcutaneous tissue.
Pellacani and Seidenari (1999) used a 20 MHz B-mode scanner
(Dermascan C, Cortex Technology, Denmark) to obtain the in
vivo skin thicknesses of 40 healthy Caucasian women for the
cheeks, upper lips, chin and nose as shown in Table 1. The B-
mode scanner can provide cross-sectional imaging of the skin
and therefore produces a more reliable measurement of skin
thickness where the dermis-hypodermis interface is hard to
Ha et al. (2004) conducted an in vitro study on 3 fresh adult
cadavers and examined the facial skin thickness on the similar
facial sites tested by Pelican and Seidenari (1999). The result
showed that the skin on the eyelid is thinnest, and results are
very close to those obtained by Pelican and Seidenari (1999).
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(a) (b)
Figure 3. Major facial muscles (red parts): (a) masseter
muscles; (b) levator labii superioris; (c) zygomaticus major
Table 1. Mean and standard deviation (SD) of skin thickness at
different facial sites in young and elderly subjects (Pelican and
Seidenari, 1999)
Facial Sites Mean (SD) for Mean (SD) for
Young Subjects (mm) Elderly Subjects (mm)
Central Forehead 1.95 (0.22) 2.03 (0.37)
Cheeks 1.71 (0.35) 1.86 (0.25)
Upper Lip 2.62 (0.35) 3.05 (0.45)
Lower Lip 2.15 (0.40) 2.05 (0.42)
Chin 2.55 (0.55) 2.61 (0.45)
Nose 1.95 (0.32) 2.19 (0.34)
Devices measuring facial skin thickness
Diridollou et al. (2001) tested human skin thickness using a B-
mode real-time ultrasonic scanner (INSERM, Unit 316, G.I.P
Ultrasound Group, Ultrasound Technology Company, Tours,
France) and an imager (DermCup 2020, Atys Medical, Soucieu
en Jarrest, France). Gibney et al. (2010) used high frequency
Cortex Dermascan C ultrasound unit with a 20 MHz probe and
a GE LOGIQ e ultrasound unit (General Electric Healthcare,
Little Chalfont, Buckinghamshire, United Kingdom) and a 4.5-
13.0 MHz probe. Laurent et al. (2007) and Ploin et al. (2011)
used a high frequency Cortex Dermascan C ultrasound unit.
Mak et al. (2014) used an ultrasound biomicroscopic system,
Vevo 770 (Visualsonics Inc., Toronto, Canada) with a
transducer of 55 MHz.
Facial skin mechanical properties
In literature, there are few studies providing direct experimental
data for human facial skin mechanical properties. The skin
mechanical properties are different when measured using in
vivo and in vitro methods (Fung, 1993; Wilkes et al., 1973).
Barbarino et al. (2009) gained results for human facial skin
mechanical properties from an in vitro experiment. Diridollou
et al. (1998) claimed that in vitro tests for skin properties are
limited because the characteristics of the skin are different after
isolating skin from the human body. Different non-invasive
techniques have been developed to measure the skin
mechanical properties using in vivo methods. The in vivo
methods for testing mechanical properties can be generally
divided into two categories: imaging techniques and
mechanical testing methods (Hendriks, 2001). Imaging
techniques have mainly been used to observe deformation and
calculate the mechanical properties of skin. Imaging techniques
in literature include motion analysis (Mahmud et al., 2010),
digital image correlation (Evans and Holt, 2009; Staloff et al.,
2007), optical coherence tomography (OCT) (Hendriks et al.,
2006; Li et al., 2012; Liang and Boppart, 2010), magnetic
resonance imaging (MRI) (Tran et al., 2008) and ultrasound
(Diridollou, 2001; Diridollou et al., 1998; Gahagnon et al.,
2009; Gennisson et al., 2004; Moran et al., 1995; Pan et al.,
1998; Piotrzkowska et al., 2009; Zheng and Mak, 1996).
Commonly used in vivo mechanical methods were developed
in terms of measurement of suction (Barel et al., 1998; Bunegin
and Moore, 2006; Couturaud et al., 1995; Cua et al., 1990;
Diridollou et al., 2000; Grahame and Holt, 1969; Hendriks et
al., 2003, 2004; Khatyr et al., 2006; Malm et al., 1995), torsion
(Leveque et al., 1980; Escoffier et al., 1989; Sanders, 1973),
tension (Lapeer et al., 2010), indentation (Bader and Bowker,
1993; Delalleau et al., 2006; Pailler-Mattei and Zahouani,
2004; Pailler-Mattei et al., 2008; Tran et al., 2008; Zheng and
Mak, 1996), extension (Alexander and Cook, 1977; Khatyr et
al., 2004; Lim et al., 2008; Quan et al., 1997) and traction
(Wang and Hayward, 2007). Agache et al. (1980) obtained
values for Young’s modulus ranging from 0.42 MPa to 0.85
MPa with torsion tests. Manschot and Brakkee (1986) used
tensile tests and found values for Young’s modulus of the
human skin between 4.6 kPa and 20 kpa. For the suction tests,
Diridollou et al. (2000) measured Young’s modulus between
217 kPa and 341 kPa. Hendriks et al. (2003) found 10, skin
C to
be 9.4 ± 3.6 kPa and 11, skin
C to be 82 ± 60 kPa for a finite
element model exhibiting Mooney material behavior to account
for the non-linear stress-strain relationship. It is obvious that
results from different researchers are different. The main reason
might be that they modified the human skin’s natural state of
stress because the experimental devices had to be fixed to the
skin throughout the testing period. It is very difficult to control
the prestress introduced by the mechanical device. Therefore,
the measured values of mechanical properties might be
affected. Although not commonly used, the indentation method
can be used to measure the skin mechanical properties without
prestressing the skin specimen before the test (Bader and
Bowker, 1983). Furthermore, the indentation method can
determine the surface properties of the cutaneous surface,
which reflect the physic-chemical properties of the skin/
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indenter interface (Pailler-Mattei and Zahouani, 2004).
Pailler-Mattei et al. (2008) conducted experiments with an
original indentation device and obtained an average value of
Young’s modulus for the skin between 4.5 kPa and 8 kPa,
which are quite close to the results reported by Bader and
Bowker (1983) and Pailler-Mattei and Zahouani (2004). The
mechanical methods and imaging methods were combined by
most researchers to measure the skin mechanical properties in
literature. For example, ultrasound combined with indentation
(Zheng and Mak, 1996), MRI combined with indentation (Tran
et al., 2008), and suction combined with ultrasound and OCT
(Hendriks et al., 2003, 2006) have all been used. More recently,
some researchers have used airflow to measure the skin
mechanical properties (Boyer et al., 2012; Fleury et al., 2010;
Fugimura et al., 2008). The mechanical properties of skin
vary with the skin locations on body (Fung, 1993; Wilkes et al.,
1973). Staloff et al. (2008) claimed that the results of tests on
other parts of the human body such as the forearm cannot be
used to replace the results gained from facial skin because the
facial skin has a very complex underlying connective structure.
Thus, the studies on facial skin provide more accurate data on
facial skin mechanical properties (Barbarino et al., 2011; Barel
et al., 1998; Cua et al., 1990; Couturaud et al., 1995; Malm et
al., 1995; Ohshima et al., 2011; Tsukahara et al., 2004).
In literature, researchers have used linear and nonlinear skin
mechanical properties in skin simulations. Many skin models
claim skin as isotropic, linear elastic material (Diridollou et al.,
2000; Pailler-Mattei et al., 2008; Khatyr et al., 2006). Young’s
modulus and Poisson’s ratio can be used to define the linear
skin model. However, the linear elastic material models are
difficult to model the nonlinear properties of the skin in some
cases. Mooney-Rivlin strain energy function was employed by
Hendriks et al. (2006) to model skin.
The strain energy density function for an incompressible
Mooney-Rivlin material is:
11 22
33WCI CI 
where 1
C and 2
C are empirically determined material
constants, and 1
and 2
are the first and the second
invariant of the unimodular component of the left Cauchy-
Green tensor.
; 222
11 23
; 22 22 22
where F is the deformation gradient.
Evans (2009) used Odgen strain energy function with a pre-
strain parameter to simulate in-plane deformations of skin. The
Ogden strain energy for incompressible rubber-like material is
expressed in terms of the principal stretches i
where p
are constant shear moduli and
dimensionless constants. The principal stresses are found from:
ii i
 
Arruda-Boyce strain energy function was employed by
Bischoff et al. (2000) to model the nonlinear skin. The strain
energy density function for the incompressible Arruda-Boyce
model is given by: sinh
B chain
WNk n n
where n is the number of chain segments,
k is the
Boltzmann constant,
is the temperature in Kelvin, Nis the
number of chains in the network of a cross-linked polymer,
chain I
where 1
I is the first invariant of the left Cauchy-Green
deformation tensor, and
is the inverse Langevin
Devices measuring facial skin mechanical properties
Boyer et al. (2012) developed an air flow device called
Tonoderm which consists of an air compressor and an Air Mass
Flow Controller, 5851S (Brooks Instrument, Hatfield, PA,
USA). Fleury et al. (2010) developed an air puff that can
deform the skin surface and measure the mechanical properties.
The air puff developed by Fleury et al. (2010) mainly consists
of an air port (Porter Instruments, Hatfield, PA, USA), a
pressure gauge (Kelatron, Coporation, Ogden, UT, USA), and a
flux meter , GPE meterate 314 (GPE Scientific Ltd,
Bedfordshire, England). Fujimura et al. (2008) developed an air
flow system to measure the skin mechanical properties which
consists of an air reservoir and a displacement sensor. The
displacement of the skin was recorded by Fujimura et al.
(2008) using a displacement sensor, Z4W-V25R (Omron,
Kyoto, Japan). Staloff et al. (2007) used digital image speckle
correlation (DISC) to measure the skin mechanical properties.
Staloff et al. (2007) took images in rapid succession using a
five megapixel camera, Canon D60 and Canon Powershot Pro1
(Lake Success, NY, USA). Mahmud et al. (2010) used a 3-
camera optial motion analysis system, Qualisys Proflex-
MCU1000 (Qualisys, Gothenburg, Sweden) with 50mm focal
length lenses. Hendriks et al. (2004) performed suction
measurements and obtained elevation and thickness of the skin
with OCT. The OCT device and suction device used by
Hendriks et al. (2004) were customized. Li et al. (2012) used a
home-made surface wave generator with an OCT system, SD-
OCT (DenseLight Semiconductors Ltd, Singapore) to observe
the deformation and mechanical properties of the skin. Liang
and Boppart (2010) used an OCT system and observed the skin
deformation with a mechanical wave driver, SF-9324 (PASCO
scientific, Roseville, CA). Liang and Boppart (2010) also
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verified their results for mechanical properties of the skin with
a commercial instrument, Custometer MPA 580 (Courage
Khazaka Electronic, Koln, Germany). Gahagnon et al. (2009)
used a high frequency ultrasound scanner (Dermcup 2020, Atys
Medical, Soucieu en Jarrest, France) and an extensiometer
developed in LMARC laboratory and P. Fabre Research
Institute in France to develop skin imaging. Gennisson et al.
(2004) used a 50 MHz ultrasound probe (Panametrics, La
Garenne Colombe, France) with a vibrator, Brüel & Kjær 4810
(Brüel & Kjær Sound & Vibration, Nærum, Denmark). Lapeer
et al. (2010) used the Stable Micro System TA.XT2 texture
analysis machine (Stable Micro Systems Ltd., Godalming, UK)
to measure the human skin mechanical properties in vitro.
Khatyr et al. (2004) developed an extensometer which provides
a non-invasive measurement of the skin mechanical properties
on different parts of the body and in different directions at each
point. Lim et al. (2008) designed an extensometer to measure
the mechanical properties of skin. Wang and Hayward (2007)
developed an apparatus that can deform the skin in the large
deformation range with traction and measure the skin
properties. Pailler-Mattei and Zahouani (2004; 2008)
developed an experimental device which can study the
adhesion forces and mechanical properties of human skin in
vivo with an indentation test. Diridollou et al. (2000) developed
a suction test device which consists of a pressure control
system that can apply increasing and decreasing suction to the
skin, an electronic circuit that detects the displacement of the
skin and an ultrasound device. Hendriks et al. (2003) attached
an ultrasound system (DUB 20, Taberna Pro Medicum,
Germany) to a self-developed suction device to perform the
suction test in vivo and measured the mechanical properties of
the skin. Agache et al. (1980) introduced a torsional device
which contains a torque-motor and a rotational detector which
can provide voltage proportional to the rotational angle.
Facial muscle thickness
As mentioned in the Human Anatomy section, the major facial
muscles include masseter, levator labii superioris and
zygomaticus major muscles. The major facial muscles
thicknesses are most commonly measured by several in vivo
imaging techniques: ultrasound scanning, computerized
tomography (CT) and magnetic resonance imaging (MRI). CT
was used to measure the facial muscle thickness by several
researchers (Chabanas et al., 2003; Weijs and Hillen, 1984; Van
Spronsen et al., 1989; Katsumata et al., 2004). The results
provided by CT are considered to be reliable (Satiroglu et al.,
2005). However, the CT can unavoidably bring radiographic
exposure to the subjects (Satiroglu et al., 2005), which is a
known cumulative biological effect. MRI is a method that
received relatively little attention by researchers in literature
(Farrugia et al., 2007; Fischbein et al., 2001; Kaylie et al.,
2003; Von Sponsen et al., 1991; Hannam and Wood, 1989).
MRI was found to be accurate (Hannam and Wood, 1989);
however, the relatively high cost of MRI reduces its clinical
availability. In literature, the ultrasonography method has been
used by most of the researchers for measuring the facial muscle
thickness (Satiroglu et al., 2005; Castelo et al., 2007;
Gergiakaki et al., 2007; Kiliaridis and Kalebo, 1991; Kiliaridis
et al., 2003, 2007; Kubota et al., 1998; Muller et al., 2012;
Palinkas et al., 2010; Raadsheer et al., 1996). The
ultrasonography has been proved to be a simple, inexpensive
and accurate method to measure the muscle thickness
(Satiroglu et al., 2005) and it is applicable for large scale
studies (Radsheer et al., 1994). Also, ultrasonography does not
have known cumulative biological effects. Satiroglu et al.
(2005) used the ultrasonography method to measure the
thickness of the major facial muscles in adults, and results are
shown in Table 2. The influence of age and gender on the
thickness of human facial muscles was studied by Palinkas et
al. (2010), and the results are shown in Table 3.
Table 2 Mean and standard deviation of muscle thickness on
different facial sites for adults (Satiroglu et al., 2005)
Muscles Me an and SD (mm)
Masseter (relaxed) Males 14.92 (1.59)
Females 12.74 (1.69)
Combined 13.56 (1.95)
Masseter (clenching) Males 15.92 (1.89)
Females 13.76 (1.24)
Combined 14.57 (1.83)
Levator labii superioris Males 3.60 (0.49)
Females 3.41 (0.44)
Combined 3.48 (0.46)
Zygomaticus major Males 3.62 (0.38)
Females 3.33 (0.39)
Combined 3.44 (0.40)
Devices measuring muscle thickness
CT machines used by Katsumata et al. (2004) were the high
speed advantage (General Electronic, New York, NY, USA)
and the X-Vision (Toshiba, Otawara, Japan). Farrugia et al.
(2007) gained MRI with a 1.5T Siemens Sonata (Siemens
Medical Solutions, Erlangen, Germany). Castelo et al. (2007)
used the ultrasound system, Just Vision Toshiba (Toshiba,
Otawara, Japan) with a 10-MHz linear transducer. Gergiakaki
et al. (2007), Kiliaridis et al. (2003, 2007) and Raadsheer et al.
(1994) used real time ultrasound scanner, Pie Medical Scanner
480 (Pie Medical, Maastricht, The Netherlands) with a 7.5-
MHz linear array transducer. Kubota et al. (1998) used
ultrasonographic scanning system, SSD-500 (Aloka Co., Ltd,
Tokyo, Japan) with a 7.5 MHz linear type scanning probe.
Muller et al. (2012) used the real time ultrasound scanners,
FALCO I00, (Pie Medical, Maastricht, The Netherlands) and
MyLab25 (Esaote, Genova, Italy) with linear array transducers
(6-8 MHz, 4-13 MHz). Palinkas et al. (2010) used SonoSite
Titan ultrasound tool (Duluth, Georgia, USA) with a 56mm/10
MHz linear-array transducer. Satiroglu et al. (2005) used a real-
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time ultrasound scanner, Siemens Elegra (Siemens, Erlangen,
Germany) with a 7.5-9 MHz broadhand transducer.
Table 3 Means and standard deviations of the thickness (cm) of
the right masseter (RM), left masseter (LM), right temporal
(RT), and left temporal (LT) in the five age groups in relation to
gender-male (M) and female (F) –in the clinical condition of
rest (Palinkas et al., 2010).
Age Groups Gender Muscles
07-12 M 0.78 (0.04) 0.77 (0.03) 0.51 (0.03) 0.49 (0.03)
F 0.73 (0.04) 0.73 (0.03) 0.44 (0.03) 0.43 (0.03)
13-20 M 0.94 (0.04) 0.95 (0.03) 0.62 (0.03) 0.63 (0.03)
F 0.92 (0.04) 0.92 (0.04) 0.65 (0.03) 0.63 (0.03)
21-40 M 1.02 (0.04) 1.06 (0.04) 0.67 (0.03) 0.68 (0.03)
F 0.82 (0.04) 0.84 (0.04) 0.56 (0.03) 0.59 (0.03)
41-60 M 1.16 (0.04) 1.14 (0.03) 0.74 (0.03) 0.71 (0.03)
F 0.93 (0.04) 0.94 (0.03) 0.59 (0.03) 0.59 (0.03)
61-80 M 1.10 (0.06) 1.07 (0.06) 0.65 (0.05) 0.66 (0.05)
F 0.90 (0.06) 0.89 (0.05) 0.47 (0.04) 0.46 (0.04)
Facial Muscle Mechanical Properties
In the literature, there is no direct experimental data available
for human facial muscle mechanical properties. However, the
mechanical properties of human muscle on other sites of human
bodies and on animal (Linder-Ganz and Gefen, 2003) have
been studied by previous researchers. Several testing
techniques have been used to measure the mechanical behavior
of the human muscles. Compression tests were used to invest
the mechanical properties of skeletal muscles (Aritan et al.,
2008; Bosboom et al., 2001; Linder-Ganz and Gefen, 2004;
Livarinen et al., 2011; Van Loocke et al., 2006; Van Loocke et
al., 2008). Some researchers performed indentation tests on
skeletal muscles (Gefen et al., 2005; Livarinen, et al., 2014;
Palevski et al., 2006; Zheng et al., 1999). Some other
researchers use ultrasound (Blackburn et al., 2009; Gennisson
et al., 2010, 2005; Nordez et al., 2008; Nordez and Hug, 2010)
to measure the muscle mechanical properties. Some researchers
(Chabanas and Payan, 2000; Chabanas et al., 2003; Gladilin et
al., 2004) used the Young’s modulus values reported by Duck
(1990) in their linear elastic FEM facial muscle simulation
models. Duck (1990) reported 6.2 kPa for a human muscle in
its rest position and 110 kPa for the same muscle, which are
close with the measurements reported by Ohayon et al. (1999)
on cardiac muscles. Some researchers developed non-linear
models for muscle tissues. Hyperelastic muscle models were
performed by Cox et al. (2007), Jia et al. (2006) and Linder-
Ganz and Gefen (2004). Viscoelastic muscle models were used
by Aritan et al. (2008), Best et al. (1994), Bosboom et al.
(2001) and Van Loocke et al. (2008). The detailed parameters
for the mechanical properties of muscle in those models are
measured and reported.
Devices measuring muscle mechanical properties
Aritan et al. (2008) designed a creep testing machine to
quantify the non-linear viscoelastic behavior of muscular bulk
tissue, which consist of a main frame, a squeezing chamber, a
tensional load cell and a data collection unit. Bosboom et al.
(2001) performed compression test with Zwick 1445 machine
(Zwick Roell, Ulm, Germany). Linder-Ganz and Gefen (2004)
used compression test with a testing machine, INSTRON 5544
(Instron, Norwood, Massachusetts, USA). Van Loocke et al.
(2006, 2008) performed compression tests with a uniaxial test
machine, Zwick Z005 (Zwick Roell, Ulm, Germany). Nordez
and Hug (2010) used an AixPlorer ultrasonic scanner
(Supersonic Imagine, Aix en Provence, France), coupled with a
linear transducer array (4-15 MHz, SuperLinear 15-4, Vermon,
Tours, France) in their test. Gefen et al. (2005) developed an
electromechanical, computer-controlled and precalibrated
indentor with a miniature linear stepper motor, force transducer
and a linear variable displacement transducer to measure the
indentation force and material displacement. Livarinen et al.
(2014) developed a hand-held indentation device to measure
the muscle mechanical properties, which consist of two load
cells: 10 kg Honeywell Sensotec load cell 31/1430-04 Mid
(Honeywell Sensotec, Columbus, OH, USA) and 1000 g
Honeywell Sentec load cell 31/ 1426-02 Mid (Honeywell
Sensotec, Columbus, OH, USA). Palevski et al. (2006)
developed a pneumatic indentation testing device which can
have an indentation speed of 2000 mm/s during the ramp
phase. Gennisson et al. (2005) developed an ultrasound
indentation vibrator with a measuring excitor, Brüel & Kjær
4810 (Brüel & Kjær Sound & Vibration, Nærum, Denmark) to
measure the hardness of the muscle in vivo. Nordez et al.
(2008) used a shear elasticity probe which is composed of an
ultrasonic 5 MHz transducer and a vibrator, Brüel & Kjær 4810
(Brüel & Kjær Sound & Vibration, Nærum, Denmark) to
measure the hardness of the muscle in vivo. Blackburn et al.
(2009) used B-mode ultrasound device, LOGIQe (General
Electronic, Milwaukee, WI, USA) with a 7 MHz linear-array
transducer. Livarinen et al. (2013) used a suction device made
of thermoplastic elastomer SEBS, Thermolast (Kraiburg TPE
GmbH & Co. KG, Waldkraiburg, Germany) to measure the
forearm muscle mechanical properties.
Adipose tissue thickness
In literature, there is no direct data about the subcutaneous
layer thickness on healthy human face. However,
subcutaneous tissue thickness on other sites of human body
have been measured by researchers using computed
tomography (CT) (Burbridge et al., 2007) and ultrasound
method (Gibney et al., 2010; Guaraldi et al., 2005; Nordander
et al., 2003; Presti et al., 2012; Rolfe et al., 2010; Smith et al.,
1991). As mentioned in the former chapters in this paper, CT
has potential biomedical hazard because of the radiation
exposure. Most of the researchers in literature chose ultrasound
to measure the subcutaneous tissue thickness under skin
Copyright © 2015 by ASME
because of the effectiveness and accuracy of ultrasound.
Guaraldi et al. (2005) measured the facial subcutaneous
thickness change on HIV patients using ultrasound device.
Presti et al. (2012) performed ultrasound measurement of
subcutaneous thickness at the insulin injection sites on
Devices measuring subcutaneous tissue thickness
Gibney et al. (2010) used high frequency Cortex Dermascan C
ultrasound unit with a 20 MHz probe and a GE LOGIQ e
ultrasound unit (General Electric Healthcare, Little Chalfont,
Buckinghamshire, United Kingdom) with a 4.5-13.0 MHz
probe. Nordander et al. (2003) used ultrasound equipment with
a linear array probe and a frequency of 12 MHz (Logiq 700,
General Electric OEC Medical Systems, Salt Lake City, Utah,
USA) to measure the distance between skin surface and muscle
belly. The thickness of the subcutaneous tissue was measureb
by Nordander et al. (2003) using a skinfold caliper (Harpenden,
British Indicators, West Sussex, UK). Presti et al. (2012)
measured the thickness of subcutaneous tissue using the
MyLabTouch portable US unit with a 33-mm, 13.6-MHz
transducer/probe (ESAOTE Biomedica Deutschland GmbH,
Koln, Germany). Rolfe et al. (2010) measured the visceral and
subcutaneous abdominal fat thickness with a Logic Book XP
ultrasound device and a 3C MHz-RS abdominal curved array
transducer (General Electric Healthcare, Little Chalfont,
Buckinghamshire, United Kingdom). Smith et al. (1991) used a
Harpenden stadiometer (Harpenden, British Indicators, West
Sussex, UK) to measure the thickness of subcutaneous tissue.
Smith et al. (1991) measured the distances from skin to muscle
fascia using high resolution real time ultrasonography with an
electronically focused 5 MHz linear array transducer.
Subcutaneous tissue mechanical properties
No facial subcutaneous tissue mechanical properties were
reported in literature. However, the mechanical properties of
subcutaneous tissue tested on other sites of human body, like
breast (Chung et al., 2007; Samani et al., 2001; Samani and
Plewes, 2004; Wang et al., 2009), heel (Miller-Young et al.,
2002), fingertip (Wu et al., 2003), porcine tissue (Zheng and
Mak, 1996) or animals (Wu et al., 2004, 2007) were published.
The subcutaneous mechanical properties were tested either in
vitro or in vivo. Wu et al. (2004, 2007) conducted in vitro tests
on pig subcutaneous tissues and created nonlinear-elasticity
models to describe the mechanical behavior of the tissues.
Miller-Young et al. (2002) used specimen from human
cadaveric feet to test the fat pad on heel. The in vivo methods
include compression method (Wang et al., 2009; Wu et al.,
2007), tensile method (Chung et al., 2008), indentation method
(Samani and Plewes, 2004; Zheng and Mak, 1996) ultrasound
(Zheng and Mak, 1996) and MRI (Samani et al., 2001). The
subcutaneous tissue is believed to behave nonlinear elastic
mechanical properties (Wu et al., 2007). Several non-linear
models were introduced in literature. Miller –Young introduced
a nonlinear viscoelastic model for the fat pad on human heel
and specified parameters for the Mooney-Rivlin material
equations. Chung et al. (2008) specified the parameters for neo-
Hookean equation used for a non-linear elastic model of human
breast. Samani et al. (2001) and Samani and Plewes (2004)
introduced hyperelastic models for the human breast and
provided the parameters.
Devices measuring subcutaneous tissue mechanical
Chung et al., (2008) developed a tensile testing device which
consisted of a force transducer coupled to a displacement
actuator. Samani and Plewes developed an indentation
measuring system which consists of a programmable high
resolution linear servo actuator LAL30 (SMAC, Carlsbad, CA,
USA). Samani et al. (2001) used GE SIGNA 1.5-T scanner (GE
Medical Systems, Milwakee, WI) for the MRI. Wu et al.(2007)
performed compression tests with a universal micro-mechanical
testing mashine (Model Mach-I, Biosyntech, Montreal,
Canada). Zheng and Mak (1996) used Panametrics model
5052UA ultrasound (General Electric Healthcare, Little
Chalfont, Buckinghamshire, UK) pulser/receiver as both an
ultrasound source and indenter.
A detailed overview of various study of the thickness and
mechanical properties of human facial soft tissues and the
models for the facial soft tissues are presented in this paper.
The human facial soft tissues are believed to have non-linear
elastic, anisotropic and multi-layer structures. The measuring
methods and devices for the thickness and mechanical
properties of different layers of the human soft tissues were
overviewed in this paper. The measuring methods are either in
vivo or in vitro. Several finite element models were created for
different layers for the facial soft tissues. More detailed and
accurate measurement for the thickness and mechanical
properties of each layers of human facial soft tissues are still
needed in the future. Future work is needed to create a non-
linear elastic finite element model that can precisely describe
the mechanical behavior of each layer of human facial soft
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... The proper mesh configuration, one of the important factors affecting accuracy, has been generated by TMR in this study. A Young's modulus of 0.03 MPa and a Poisson's ratio of 0.49 are used as material properties of soft tissue in this study by referring to previous studies [27,[31][32][33][34][35][36][37]. The thickness of the shell element was defined as 2 mm. ...
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A novel contact model is presented to efficiently solve a face-mask contact problem by using the finite element (FE) method for the optimized design of a custom facial mask. Simulation of contact pressure for various mask designs considering material properties of the face allows virtual evaluation of the suitability of a mask design for a person's face without conducting empirical measurement of the face-mask contact pressure. The proposed contact model is accomplished by combining three approaches to reduce the calculation cost of simulating the face-mask contact: (1) use of a simplified and modifiable mask model that applies a spline curve to design points; (2) reduction of the FE model of the face by applying static condensation; and (3) application of a contact assumption that uses the Lagrange multiplier method. A numerical case study of a medical mask design showed that the proposed model could calculate the face-mask contact pressure efficiently (0.0448 sec per design). In a pilot usability experiment, the measured contact pressure was found similar values (range of mean contact pressure: 0.0093~0.0150 MPa) to the estimated values (range of mean contact pressure: 0.0097~0.0116 MPa).
... This system is supported by a 1 mm subcutaneous tissue layer that provides a compliant boundary condition for the dermis by representing underlying tissue. The model was given material and geometric properties from literature [58][59][60][61] , listed in Table 2. Data on facial skin was used where available, complemented with properties of volar forearm skin, as research suggests there is no significant difference in thicknesses, stiffness, Poisson's ratios and frictional behaviour 62,63 . ...
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The use of close-fitting PPE is essential to prevent exposure to dispersed airborne matter, including the COVID-19 virus. The current pandemic has increased pressure on healthcare systems around the world, leading to medical professionals using high-grade PPE for prolonged durations, resulting in device-induced skin injuries. This study focuses on computationally improving the interaction between skin and PPE to reduce the likelihood of discomfort and tissue damage. A finite element model is developed to simulate the movement of PPE against the face during day-to-day tasks. Due to limited available data on skin characteristics and how these vary interpersonally between sexes, races and ages, the main objective of this study was to establish the effects and trends that mask modifications have on the resulting subsurface strain energy density distribution in the skin. These modifications include the material, geometric and interfacial properties. Overall, the results show that skin injury can be reduced by using softer mask materials, whilst friction against the skin should be minimised, e.g. through use of micro-textures, humidity control and topical creams. Furthermore, the contact area between the mask and skin should be maximised, whilst the use of soft materials with incompressible behaviour (e.g. many elastomers) should be avoided.
... Data were extracted from the acquired CT data using Mimics 20.0 software (Materialise Co., Leuven, Belgium), focussing on craniofacial soft tissues and the skull and excluding brain tissue. Facial soft tissue has a complex structure consisting of skin, fat and muscle (Xu and Yang 2015), with three main layers, i.e. the epidermis, the dermis and subcutaneous tissue. The epidermis is approximately 0.1 mm thick and is mainly composed of keratinocytes; the underlying dermis is approximately 0.6-3.5 mm thick and is mainly composed of elastic fibres; and the subcutaneous layer is mainly composed of fat, muscle fibres and mucous membranes (Yin 2012). ...
In this study, an accurate finite element (FE) stress analysis of head-mounted products for Chinese users was performed. Using craniofacial computed tomography scans of 280 Chinese individuals, the total soft tissue thickness and thickness of the fat and muscle layers for 41 landmarks were measured. The data were used to construct FE head models (FEH). An FE stress test was conducted to analyse the wearing of medical goggles using two FE models based on one-layer (FEH 1) and three-layer (FEH 3) soft tissue material parameters. When compared with the experimental results, the modelling results for FEH 3 were more realistic than those for FEH 1. Wearing medical goggles led to stress concentration over five landmark areas, A: upper medial forehead, B: temporal, C: zygion, D: infraorbital fossa and E: rhinion, of which B, C and D caused the most discomfort during long-term goggle wear. Practitioner Summary: A precise FE head model can reflect the complex contact pressure of a head-related product. Two FE models based on one- and three-layer soft tissue material parameters were established and tested separately with medical goggles. The model can be used to improve the comfort of head-related products.
... Craniofacial soft tissue is formed by muscles, fat, and skin. 31 Different colors and thresholds distinguished different soft tissues during the measurements. Fat tissue Hounsfield units range from À50 to À200 32,33 ( Fig. 1). ...
In this study, data related to the total soft tissue thickness and fat layer thickness of 41 anatomical landmarks were extracted from the craniofacial computerized tomography data of 280 Chinese individuals (160 males and 120 females). The measurements were assessed according to the following factors: a. sex, b. age, and c. sex × age. Descriptive statistics and a differential analysis were carried out in each group to analyze both the total soft tissue thickness and fat layer thickness. The results showed the following. 1. The results showed that the greater the total thickness of the soft tissue, the thicker the fat layer. 2. The thicknesses of the head and face soft tissues are strongly affected by sex. The total thickness of all landmark points in the men, except for the zygomatic points, was on average greater than that in the women. In contrast to the total thickness, the fat layer, except for the point of rhinion, in the women was larger than that in the men. 3. In the comparison of the 4 age groups, most feature points did not show an evident increasing or decreasing trend with age in the total thickness of the soft tissue. However, regarding the thickness of fat, the thickness at the other points, except for the feature infraorbital fossa point, decreased with age. 4. In the analysis of the sex × age group, no statistically significant differences were found at any landmark points. This paper is significant for facial reconstruction and cosmetic surgery in the Chinese population.
... 5 Over the years, different techniques have been developed in order to achieve increasingly precise STT measurements based on medical imaging, including radiography, ultrasound, magnetic resonance imaging, computed tomography (CT) and cone beam CT (CBCT). 6 Although in the literature there are reviews of different techniques for STT measurement, 7,8 no reviews have been carried out on CBCT. CBCT is a potentially low-dose imaging technique in which cone-shaped X-ray beam moves in a helical progression to acquire multiple image slices, while the detector makes a circle around the patient. ...
When human remains are found, with no evidence of identity, facial approximation can be a useful technique to employ. The reconstruction of the ante-mortem appearance can reproduce the likely features of the face, starting from the skull, based on the overlying soft-tissue thickness. Over the years, many techniques have been developed to achieve soft-tissue thickness measurements, one of which is based on the use of cone beam computed tomography. This study aimed to review the status of this technique and to evaluate heterogeneity among studies undertaken in this field, with particular regard to determination of landmarks, sex and body mass index.
... Since the electrodes interface with the skin in the forehead area, the statistical variations of this region were identified assuming that male skin (δs) is 1 mm thicker than female [29]. There is no direct data about the subcutaneous layer thickness (δf) on the healthy human face in the literature [30] as the subcutaneous tissue is anatomically placed between skin and muscle layers. The average thickness of this tissue was calculated from the difference between the average thickness of the skin and the average depth of the frontalis muscle. ...
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Objective: Conventional treatment methods for migraine often have side effects. One treatment involves a wearable neuromodulator targeting frontal nerves. Studies based on this technique have shown limited efficacy and the existing setting can cause pain. These may be associated with neuroanatomical variations which lead to high levels of required stimulus current. The aim of this paper is to study the effect of such variations on the activation currents of the Cefaly neuromodulator. Also, using a different electrode orientation, the possibility of reducing activation current levels to avoid painful side-effects and improve efficacy, is explored. Approach: This paper investigates the effect of neuroanatomical variations and electrode orientation on the stimulus current thresholds using a computational hybrid model involving a volume conductor and an advanced nerve model. Ten human head models are developed considering statistical variations of key neuroanatomical features, to model a representative population. Main results: By simulating the required stimulus current level in the head models, it is shown that neuroanatomical variations have a significant impact on the outcome, which is not solely a function of one specific neuroanatomical feature. The stimulus current thresholds based on the conventional Cefaly system vary from 4.4 mA to 25.1 mA across all head models. By altering the electrode orientation to align with the nerve branches, the stimulus current thresholds are substantially reduced to between 0.28 mA and 15 mA, reducing current density near pain-sensitive structures which may lead to a higher level of patient acceptance, further improving the efficacy. Significance: Computational modeling based on statistically valid neuroanatomical parameters, covering a representative adult population, offers a powerful tool for quantitative comparison of the effect of the position of stimulating electrodes which is otherwise not possible in clinical studies.
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Background In vivo mechanical characterisation of biological soft tissue is challenging, even under moderate quasi-static loading. Clinical application of suction-based methods is hindered by usual assumptions of tissues homogeneity and/or time-consuming acquisitions/postprocessingObjective Provide practical and unexpensive suction-based mechanical characterisation of soft tissues considered as bilayered structures. Inverse identification of the bilayers’ Young’s moduli should be performed in almost real-time.Methods An original suction system is proposed based on volume measurements. Cyclic partial vacuum is applied under small deformation using suction cups of aperture diameters ranging from 4 to 30 mm. An inverse methodology provides both bilayer elastic stiffnesses, and optionally the upper layer thickness, based on the interpolation of an off-line finite element database. The setup is validated on silicone bilayer phantoms, then tested in vivo on the abdomen skin of one healthy volunteer.ResultsOn bilayer silicone phantoms, Young’s moduli identified by suction or uniaxial tension presented a relative difference lower than 10 % (upper layer thickness of 3 mm). Preliminary tests on in vivo abdomen tissue provided skin and underlying adipose tissue Young’s Moduli at 54 kPa and 4.8 kPa respectively. Inverse identification process was performed in less than one minute.Conclusions This approach is promising to evaluate elastic moduli in vivo at small strain of bilayered tissues.
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The use of close-fitting PPE is essential to prevent exposure to dispersed airborne matter, including the COVID-19 virus. The current pandemic has increased pressure on the healthcare system, leading to medical professionals using high-grade PPE for prolonged times, resulting in device-insduced skin injuries. This study focuses on computationally improving the interaction between skin and PPE to reduce the likelihood of discomfort and tissue damage. A finite element model is developed to simulate the movement of PPE against the face during day-to-day tasks. Due to limited available data on skin characteristics and how these vary interpersonally between sexes, races and ages, the main objective of this study was to establish the effects and trends that mask modifications have on the resulting subsurface strain energy density distribution in the skin. These modifications include the material, geometry and interfacial properties. Overall, the results show that skin injury can be reduced by using softer mask materials, whilst friction against the skin should be minimised, e.g. through use of micro-textures, humidity control and topical creams. Furthermore, the contact area between the mask and skin should be maximised, whilst the use of soft materials with incompressible behaviours (e.g. most elastomers) should be avoided.
Facial soft tissue thickness (FSTT) is essential to forensic anthropologists for facial reconstruction- recreating a recognizable face from an unidentified skull and to plastic surgeons for treatment planning. Together with the age and sex of a person, the facial profile is related to facial soft tissue thickness, which is required for accurate facial reconstruction and recognition. Having such a facial profile in the national level is very important for a country since FSTT changes according to the geographical factors. In this paper we are presenting a review on literature associated with this topic describing the methods used for data collection, measuring FSTT and analyzing those values along with the method we are proposing to be followed in the research we are to conduct in the Sri Lankan context.
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The scattering of ultrasonic waves depends on the size, shape, acoustical properties and concentration of scatterers in the tissue. The spectrum of the ultrasonic backscatter can be used to characterize non-invasively the structural and mechanical properties of tissue. We intend to apply the custom-designed high-frequency ultrasonic scanner for the skin and cutaneous lesions characterization by evaluating their attenuating and scattering properties. In this pilot study, we have explored the possibility of extracting the human skin backscattering coefficient (BC) from the ultrasonic B-scans obtained in vivo at 20-30 MHz. The measured BC values of normal skin (dermis) agree well with the published data. We have found also that the spatial resolution of the BC determination using our scanner is sufficient (aprox. 1 mm2) to characterize small skin lesions and assess their penetration depth.
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This paper will present our work on the simulation of soft tissue deformation within the con-text of maxillofacial surgery. Our approach is based on finite element methods on tetrahedral grids. These grids represent different tissue regions and are automatically generated with guaranteed topological correctness and scalable resolution from segmented 3D tomographic data.We describe the complete pipeline from creating 3D models of the patients’ anatomy, the surgical planning, and the numerical simulation of soft tissue deformation. As a result of our investigation we will assess our approach with a view to providing a complete planning and simulation system for clinical use.
Both reflectance spectroscopy and the determination Young's Modulus of skin have shown promise for identifying skin pathology. At present, these determinations are carried out using separate methodologies. This study demonstrates a new technology combining digital UV/VIS reflectance spectroscopy and vacuum aspiration for simultaneously determining the reflectance spectrum and mechanical properties of human skin tissue. A small hand held prototype device incorporating fiber-optic light guides into a vacuum channel was calibrated using various elastic materials subjected to increments of stress by vacuum from 0 to 25 in Hg. The intensity of a UV/VIS light beam reflected from the material at each vacuum increment was compared to the resulting material strain. The reflected beam was also spectrophotometrically analyzed. Skin types were similarly evaluated comparing normal and scar tissue and skin of various ages and coloration. An exponential relationship between reflected beam intensity and the amount of strain resulting from vacuum increments was observed. Young's Modulus (calculated from Aoki et. al equation) and spectra from normal skin and scar tissue were in agreement with previously published observations. Age related decreases in skin elasticity were also demonstrated. In the reflectance spectra, oxy and deoxy-hemoglobin absorbance bands were detected, becoming significantly enhanced at increased levels of vacuum. Melanin absorbance was also easily detected and appeared to correlate with skin coloration. Since superficial skin pathologies have characteristic spectroscopic and mechanical properties, this technique may provide a promising new approach for rapid, non-invasive method for the evaluation of skin lesions.
The purpose of the present study was to compare mechanical properties of healthy and diseased human skins. We used an elastographic imaging system described and validated in a previous work (Gahagnon, 2006). This system was based on combination of two devices: an extensiometer that submitted the skin to an uniaxial stress cycle of ten seconds and a high resolution echographic system with an axial resolution of 150 ¿m (20 MHz) and a frame rate of 10 images per second. Thickness of the skin, efforts applied and kinetics of the axial strain were compared between healthy subjects and patients with Marfan syndrome. Children with Marfan syndrome showed significant differences compared with the healthy children.
In order to evaluate the mechanical properties of the human skeletal muscles, the elasticity and viscosity of the human calf muscles were measured with Magnetic Resonance Elastography (MRE). MRE is a novel method to measure the mechanical properties of living soft tissues in vivo quantitatively by observing the strain waves propagated in the object. In this study, the shear modulus and viscosity coefficient were measured with MRE. The shear modulus was 3.7 kPa in relaxed state, and increased with increasing the muscle forces. Interestingly, the viscosity was changed with the vibration frequency applied to the muscles, that was 4.5 Pa·s at 100Hz vibration and 2.4 Pa·s at 200Hz vibration. This shows clearly the visco-elastic property.
Publisher Summary This chapter reviews the mechanical properties of tissues, including their densities, moduli of elasticity, and ultimate strengths. The density of tissue may be measured by comparing the mass of a sample in air with the apparent mass measured in water. The density is calculated from the ratio of the apparent masses and knowledge of the density of water at the measurement temperature. Density varies as a function of temperature. The factors affecting elasticity in a tissue can be humidity, tissue composition—either collagen or elastin—and the viscoelasticity of the tissue. Thereafter, the ultimate tensile strength of soft tissue is more amenable to simple numeric evaluation than is the general nonlinear stress–strain relationship. A number of factors may affect this soft tissue property such as age of the tissue, humidity, and the shear and bursting strength of the tissue. The viscosity of a fluid may be measured either by observing its flow along a capillary tube or by the use of a rotational viscometer. The viscometer applies an almost uniform shear rate across the fluid and can be used to investigate the variation of viscosity with velocity gradient. Subsequently, it has been noticed that blood viscosity increases with hematocrit and decreases with temperature.
Acknowledgments First, I would like to thank Peter Deuflhard for inviting me to Zuse-Institute- Berlin (ZIB) to participate on the computer,assisted surgery (CAS) project that has been originated with his vision of the realistic modeling of the human,face on the basis of consistent numerical methods. I am indebted to him for his guidance of my work and for giving me the freedom to go my own, often only intuitively approachable ways to achieve research goals. Such multi-disciplinary work would be unimaginable,without the cooperation with many people directly or indirectly contributing and supporting it. I thank my colleague within the CAS-project, Stefan Zachow, for providing geometri- cal models of human anatomy, which essentially helped this work to become an application-oriented effort. I thank Martin Seebass for discussions around the top- ics of geometrical modeling,and visualization. I am grateful to Hans-Christian Hege for his personal engagement,and many-sided support of this fascinating project from its very beginning on. My thanks go to my,colleagues from Sci- entific Computing Department of ZIB and Free University of Berlin: Bodo Erd- mann, Jens Lang, Rainer Roitzsch and Rolf Krause for their assistance and many practical advices w.r.t. the structural mechanics,modeling,and the finite element programming, especially at the beginning of this work. I would like to express my great thanks to Martin Weiser for many helpful discussions across the field of
In this work we have studied the effect of adhesion forces on the mechanical parameters between a spherical indenter and human skin surface with an indentation test. To take into account the effect of adhesion on Hertzian contact radius, pressure and strain, a theory of adhesion contact, like that of Johnson, Kendall and Roberts (JKR) or Derjaguin, Muller and Toporov (DMT) must be used. These theories correct the errors induced by the adhesion forces on contact parameters. The change in skin surface lipid film during hydration by water is assessed by analyzing the evolution of the adhesion energy and skin stiffness.