Note: Descriptions are shown in the official language in which they were submitted.
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TITLE: APPARATUS AND METHOD FOR CHARACTERIZING
ADHESIVE BONDING AND OSSEOINTEGRATION
INVENTORS:
Mohamed Mahmoud Taher EL Gowini, Walled Ahmed Mohamed Moussa and
Edmond Hok Ming Lou
TECHNICAL FIELD:
The present disclosure is related to the field of apparatuses and
methods for characterizing adhesive bonding. In particular, the present
disclosure is related to the field of acoustic wave micro-electro-mechanical
systems ("MEMS") sensors for characterizing adhesive bonding and
osseointegration of man-made implants in a human body.
BACKGROUND:
Adhesives are widely used bonding materials that offer lightweight,
high strength load bearing structures and can be used with a wide range of
adherend materials such as metals, plastics, rubbers, composites and wood.
Adhesives' applications can include bone repair procedures in orthopedics,
bonded patch applications in airplanes, electronics packaging and building
materials. Monitoring the quality of an adhesive bond is an essential
procedure
to ensure the safety of components in service. There are various mechanisms
that lead to adhesive bonding degradation; such as moisture absorption,
cracks,
inclusions, wear, poor cure, and porosity. Numerous techniques exist for
monitoring the quality of an adhesive bond, such as acoustic emission [1,2],
radiography testing [3] and ultrasonic techniques. Ultrasonic techniques
include
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normal and/or oblique incidence [4,5] and guided wave techniques,[6,7]. Guided
wave techniques offer advantages such as confinement of the wave energy near
the adhesive-adherend interface, which makes the wave highly sensitive to the
interfacial mechanical properties and bonding conditions. In addition, guided
waves propagate along the interface and can inspect large components much
faster than with normal/oblique incidence methods.
Surgical implants play a major role in the lives of many people who
experience serious injuries. Implants are man made devices that are
"implanted"
in the human body to replace, support and/or enhance biological components or
structures in the body. Different kinds of implants can be inserted in the
human
body, which include knee, dental, hip and craniofacial implants such as nose,
ear
and eye. An important bonding process initiates at the prosthetic implant's
surface after insertion. The bone tissue develops to form a strong bond with
the
implant surface (usually Titanium Oxide) and prevents relative motion. This
process is called osseointegration and is an indicator of healing progression.
Osseointegration was discovered by Branemark in the 1950's, when he realized
that rabbit bone could be permanently attached to titanium implants. It is
defined
as the formation of a direct contact between living bone and implant. This
process allows the permanent fixation of the implant to the surrounding bone
tissue. While osseointegration occurs with various types of prostheses focus
will
be on osseointegration of hip implants.
Total hip replacement ("THR") is a surgical procedure adopted to
replace a dysfunctional hip joint assembly. This procedure helps to a great
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extent to restore normal gait conditions to the patient and alleviate the pain
due
to a failed hip joint assembly. The hip joint consists of the femoral head,
which is
attached to the acetabulum to form a ball and socket arrangement.
Deterioration
of the hip joint could be caused by arthritis, which occurs with age due to
degeneration of the articular cartilage. The wear of the articular cartilage
causes
bone to grind against bone; this causes severe pain, inhibits motion and
eventually leads to bone fracture. Another cause is the significant reduction
in
bone density that leads to bone fracture and damage of the blood vessels. A
common cause of hip joint deterioration among the young generation is injury
due to extreme exercise.
The THR procedure is an intensive procedure, where the patient
has to be completely sedated. The purpose of the operation is to replace a
damaged hip joint assembly with a prosthetic implant. There are two commonly
used approaches to ensure the formation of a strong bond between the implant
surface and the bone. Either to use bone cement to enhance implant fixation
i.e.
cemented implant, or to use an un-cemented implant. In the latter case, the
implant surface is coated with a porous layer to stimulate bone growth and the
formation of a strong bond.
Post surgical complications are very common in THR procedures
and patient follow-up is crucial. The most common type of complication is
implant loosening, which occurs due to the bone re-modeling process that takes
place after implant insertion. Remodeling takes place due to the changes in
the
loads transferred to the bone as a result of inserting an implant with a
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significantly different stiffness, which therefore shields the bone from the
stresses
normally transferred. This process leads to loss of bone mass and reduced bone
density, which ultimately leads to implant loosening.
The bones in the wrists and ankles are considered to be short
bones, while bones in the arms and legs, such as the femur are considered to
be
long bone. Bone is a complex structure. On the macroscopic scale it consists
of
two main layers; cortical and cancellous. Cortical bone is the compact outer
layer that acts as a protective layer. Cancellous bone is the inner softer
layer,
which exists mainly in the end of long bone and within vertebrae. It is a
porous
structure formed of trabecular tissue. Although the cancellous bone is a soft
tissue, the individual trabeculae are much stiffer than the bulk.
A wide range of values for the elastic modulus of single trabeculae
have been determined. This variability is due to the differences and
limitations in
measurement techniques. The range of elastic modulus for single trabeculae is
1-20GPa and the density is in the range of 1,600-2,600kg/m3. The size of
single
trabeculae is in the range of 100-500pm. On the other hand, the stiffness of
the
cancellous bone is lower than for single trabeculae. The range of values for
the
elastic modulus is 10-4,000MPa and the density is 150-1,000 kg/m3. The elastic
modulus is related to the apparent density (density of the trabecular
structure and
pores) through an empirically determined power law.
Various mechanisms exist for detecting osseointegration of hip
implants. Imaging techniques such as X-Ray imaging, Dual Energy X-Ray
Absorptiometry ("DEXA") and Quantitative Computed Tomography ("q-CT") are
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commonly used. Plain radiographs are widely used but have been shown to be
highly inaccurate. It has been shown that unless a significant level of bone
mineral density occurs; up to 70%, radiological signs will not be conclusive.
DEXA, on the other hand, can provide a quantitative assessment of the bone
5 mineral density; however, some unreliability exists since it depends on the
exact
positioning of the patients and errors would be introduced by patient
movements.
Quantitative CT-scans are widely used since they provide an accurate
quantitative assessment of the bone mineral content; however its major
drawback is the high radiation exposure.
Another approach is using vibration techniques. This approach can
use sound waves in the audio range to excite femoral hip-implant assembly in
vitro at different stages of cement curing. The results indicated that there
was
indeed an upward shift in the frequency response of the entire assembly. This
approach has also been used to demonstrate that there is a shift in the
natural
frequency measurements of femurs with fixed and loose prostheses. Clinical
studies have found that when loosening of the implant occurs, it can be
detected
by changes in the output signal. However, in an attempt to detect early stages
of
implant loosening, a study conducted on cadaver femora by simulating different
stages of implant loosening and exciting the system with a sinusoidal force
indicated that the system was performing well in detecting late stages of
implant
loosening but failed to identify early stages of implant loosening.
Further studies have investigated the accuracy of vibration
detection techniques. Results were collected from vibration tests on a group
of
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patients, as well as x-ray data for the same patients and were compared with
each other. The results concluded that vibration testing was 20% more
sensitive
and diagnosed 13% more patients when compared with x-ray data.
A new generation of bio-implantable sensors is gaining momentum
due to the major advances in the field of Micro-electro-mechanical Systems
(MEMS). Implanting miniature sensors in the human body can be a major
achievement. This would allow surgeons to monitor all parameters of interest
in-
vivo, which would lead to more tailored prescriptions, accurate assessments
and
early prediction of possible complications. In essence, each patient could
become a biomechanics laboratory.
Various researchers have utilized bio-implantable MEMS sensors
for in-vivo analyses. One has investigated the biocompatibility and wound
healing behavior of bone tissue due to implanting a piezoresistive MEMS sensor
in an animal spine. Results indicated healthy bone remodeling and no signs of
inflammation or bone abnormalities. Another discussed the possibilities of
using
MEMS sensors in the spine and femur to measure fluid pressure.
The potential of bio-implantable sensors was also extended to the
problem of implant loosening. Piezoresistive MEMS sensors have been utilized
to measure the stresses at the bone implant interface in hip and knee implants
respectively. Both approaches infer healing progression from the stress
measurements since it is expected that the loads measured by the sensor will
increase as healing progresses. In these approaches, values were assumed for
the bone properties and the stresses were calculated accordingly.
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It is, therefore, desirable, to provide an apparatus and method for
characterizing adhesive bonding and osseointegration that overcomes the
shortcomings in the prior art.
SUMMARY:
An apparatus and method for characterizing adhesive bonding is
provided. In some embodiments, the apparatus and method can allow
monitoring of osseointegration of a man-made implant inserted into a human
body and predict whether implant loosening would occur. In so doing, the
apparatus and method can alleviate the severe pain suffered by patients due to
implant loosening and prevent having to do re-correction surgeries. While this
disclosure discusses apparatuses and methods for characterizing adhesive
bonding and osseointegration of man-made implants for insertion in human
bodies, it is obvious to those skilled in the art that the apparatuses and
methods
described herein can be adapted and configured to characterize adhesive
bonding between two surfaces or materials in general, and are not limited to
characterizing adhesive bonding and osseointegration of man-made implants.
In some embodiments, the apparatus and method can predict
implant loosening directly by monitoring two properties at the interface
between
the implant and the bone: a) the stiffness of the bone layer; and b) the
stiffness of
the interface wherein the implant comprises an acoustic wave MEMS sensor
disposed therein. In other embodiments, the apparatus and method can allow
healthcare providers to identify the location where loosening of the implant
is
occurring.
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In some embodiments, the apparatus and method can: a)
characterize the curing process of an interfacial layer; b) characterize the
change
in stiffness of the adjacent bone layer; c) characterize the change in
stiffness of
the interface in the location of the sensor; d) allow healthcare providers to
predict
early stages of implant loosening; and e) allows healthcare providers to
determine where implant loosening is occurring.
Incorporated by reference into this application in its entirety is a
paper written by the within inventors entitled, "ADHESIVE BONDING
CHARACTERIZATION USING AN ACOUSTIC WAVE MEMS SENSOR",
submitted for publication in the Proceedings of the 23rd CANCAM 2011
conference to be held in Vancouver, British Columbia, Canada on June 5-9,
2011. A copy of this paper is attached to this application as Appendix "A".
All of
the reference documents listed in this paper are also incorporated by
reference
into this application in their entirety.
Broadly stated, in some embodiments, an acoustic wave sensor is
provided, comprising: a semiconductor substrate; a piezoelectric layer
disposed
on the substrate; a metallic layer disposed on the piezoelectric layer; and an
input electrode and an output electrode disposed on the substrate, the
electrodes
disposed between the substrate and the piezoelectric layer.
Broadly stated, in some embodiments, an apparatus is provided for
characterizing adhesive bonding, comprising an acoustic wave sensor
comprising: a semiconductor substrate; a piezoelectric layer disposed on the
substrate; a metallic layer disposed on the piezoelectric layer; and an input
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electrode and an output electrode disposed on the substrate, the electrodes
disposed between the substrate and the piezoelectric layer.
Broadly stated, in some embodiments, a method is provided for
characterizing adhesive bonding, the method comprising the steps of: providing
an acoustic wave sensor, comprising: a semiconductor substrate, a
piezoelectric
layer disposed on the substrate, a metallic layer disposed on the
piezoelectric
layer, and an input electrode and an output electrode disposed on the
substrate,
the electrodes disposed between the substrate and the piezoelectric layer;
placing the sensor between two surfaces or two materials to be adhered
together; placing an adhesive layer between the two surfaces or two materials
wherein an adhesive bond is formed between the two surfaces or two materials;
exciting the sensor wherein the sensor generates acoustic waves wherein the
acoustic waves propagate through the sensor and the adhesive layer; and
monitoring the acoustic waves; and determining the strength of the adhesive
bond from the monitored acoustic waves.
BRIEF DESCRIPTION OF THE DRAWINGS:
Figure 1 is a perspective view depicting one embodiment of an
acoustic wave sensor comprising slanted finger interdigital ("SFIT")
electrodes.
Figure 2a) is a cross-section view depicting an Au-AIN-Si (no-bond)
configuration.
Figure 2b) is a cross-section view depicting an IHS-Au-AIN-Si
(perfect-bond) configuration.
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Figure 3 is an X-Y graph depicting dispersion profiles of the first
three modes of wave propagation in the no-bond and perfect-bond cases.
Figure 4 is a cross-section view depicting a four-layer configuration
(IHS-Au-AIN-Si) with a spring boundary at the IHS-Au interface.
5 Figure 5 is an X-Y graph depicting the shift in the wave dispersion
profile of the Mo mode of the HIS-Au-AIN-Si configuration due to changing
interface stiffness (K).
Figure 6 is an X-Y graph depicting the percentage increase in wave
velocity (%) for different h/A configurations as the interface stiffness
increases.
10 DETAILED DESCRIPTION OF EMBODIMENTS:
An apparatus and method is provided utilizing an acoustic wave
sensor for characterizing adhesive bonding integrity and osseointegration. One
embodiment of an acoustic wave sensor is illustrated in Figure 1. In some
embodiments, the sensor can comprise of a silicon ("Si") (100) substrate, an
aluminum nitride ("AIN") film deposited on the surface of the Si substrate,
two
sets of electrodes (input and output) patterned at the AIN-Si interface and a
thin
gold ("Au") film deposited on the surface of the AIN film. The AIN film is
piezoelectric and can allow electrical excitation of acoustic waves.
In some embodiments, the AIN and Au films can be guiding layers
and can confine the wave near the interface, which can increase its
sensitivity to
changes in the adjacent environment. A wide band acoustic wave signal can be
generated using the Slanted Finger Interdigital ("SFIT") electrode
configuration
as illustrated in Figure 1. In the slanted geometry the electrode period
(distance
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between two similarly charged electrode fingers) can vary linearly along the
length of the fingers. The narrow periods can excite higher frequency waves,
while the wider periods can excite lower frequency waves. The wide band
acoustic signal can facilitate generation of a wave dispersion profile.
In some embodiments, there are can be a number of features that
an acoustic wave MEMS sensor can provide for adhesive bonding
characterization that can include quantification of interfacial imperfections
and
degradation in bonding strength, which can be related directly to the wave
dispersion characteristics. The reduced size of the sensor can allow it to be
embedded along the adhesive-adherend interface to provide a localized
diagnosis of interface properties. In addition, the proposed sensor
configuration
can facilitate the propagation of an interface wave that can be highly
sensitive to
interfacial properties.
In some embodiments, a wave dispersion model is provided that
can generate a dispersion profile of a wave propagating in the multi-layered
configuration and monitor the shift in the wave dispersion profile due to
adhesive
bonding degradation. Using this information, the sensitivity of different
sensor
configurations can be examined to select the configuration with highest
sensitivity
for device fabrication.
Wave Dispersion Model
A. Generating the Au A/N-Si Dispersion Curve
In order to be able to generate the dispersion profile for a multi-
layered configuration, it is essential to solve the wave equation in each
layer.
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The Au and AIN films on top of the silicon substrate can act as guiding layers
and
their thicknesses comprise characteristic dimensions that can lead to wave
dispersion. The wave equation can be written as:
[Fpq g "'DV2 I [a,] = 0 (1)
(I'pq - Spq pv2= 0 (2)
where rpq refers to the Christoffel stiffness constants, which are
functions of the material properties and the decay parameter b. The subscripts
p
and q can have the values 1, 3 and 4, which correspond to the displacement
components u1, u3 and the electric potential 0, respectively; sP4 is the
Kronecker
delta function, p is the density of the medium in kg/m3, v is the phase
velocity in
m/s, ap is the relative wave amplitude vector. Mason [8] provides a detailed
derivation of the Christoffel equation and the expressions for the Christoffel
constants. By solving the secular equation (2) for a given phase velocity v,
the
decay parameter b and the relative wave amplitude vector ap can be determined.
The plane wave solutions for a given medium in the sagittal plane (xi-x3) can
be
written as a summation of partial wave solution as follows:
ui C,, d. exp(ikbnx3)exp[ik(x,-vt)]; >=1, 3 (3)
n
o=l Cn t ' exp(ikbnx3) exp[ik(x1-vt)] (4)
n
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where k is the wave number and the Cõ are weighting factors. In the
piezoelectric AIN film the wave solutions are the coupled mechanical
displacements uj and the electric potential 0 given in (3) and (4),
respectively.
For the Au film and Si substrate, which are non-piezoelectric, the potential
and
the displacement solutions can be de-coupled.
In some embodiments, when the wave solutions for each medium
are generated, it is essential to find the value of the phase velocity that
sets the
determinant of the boundary condition matrix to zero. The dispersion profile
can
then be obtained by finding the velocity values that satisfy the boundary
condition
matrix at different frequencies.
A schematic of the three layer configuration (Au-AIN-Si) of the
sensor is shown in Figure 2a). This configuration is referred to in this
disclosure
as the no-bond case because the top surface of the Au film is a free surface.
To study the effect of changing interface properties on the wave
dispersion profile, an adhesive layer can be added on top of the sensor as
illustrated in Figure 2b). The wave solutions in the adhesive layer can be
taken
into account in addition to the boundary conditions at the adhesive-gold
interface.
Adhesives can have numerous applications and their material properties can
vary significantly, the elastic modulus of structural adhesives can be as high
as
10 GPa [9]. The adhesive layer can be modeled as an isotropic half space
("HIS") with an elastic modulus of 8 GPa and it is assumed to be perfectly
bonded to the Au film, that is, continuity of displacement and stresses in the
sagittal plane. This configuration is referred to as the perfect-bond case in
this
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disclosure. The dispersion profiles showing the first three modes of wave
propagation for the no-bond and perfect-bond cases are shown in Figure 3.
The dispersion curves illustrate the variation in wave velocity with
the dimensionless parameter h1A. The parameter h refers to the thicknesses of
the Au and AIN films, and A refers to the distance between two similarly
charged
electrode fingers. As the value of h/A increases, the wave can be more
confined
near the interface and can propagate with a higher frequency.
B. Spring Boundary Model
In some embodiments, interfacial imperfections along the adhesive
bond line can often be confined to a very thin layer near the interface. The
overall effect of these imperfections can reduce the interface stiffness,
which can
lead to an increase in the far-field displacement at a given load as a result
of
bond degradation. To account for the reduction in interface stiffness at the
adhesive bond line, the interface can be modeled as a layer of distributed
mass-
less springs with spring stiffness K (N/m3). This is known as the spring
boundary
model, and has been frequently used to study the effect of interface
imperfections on wave propagation characteristics [10-12]. Figure 4 shows a
schematic of the IHS-Au-AIN-Si configuration with the spring boundary at the
IHS-Au interface.
When a load is applied, the interfacial springs can be distorted
leading to a discontinuous displacement field across the interface. The
stresses,
on the other hand, can be continuous across the interface to keep the layers
intact and can be proportional to the discontinuous displacement field.
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The boundary conditions for the IHS-Au-AIN-Si configuration with
the spring boundary are shown in Table 1 as shown below:
Table 1: Boundary Conditions for the Different Interface Conditions
Boundary Conditions AIN-Si AIN-Au Au-IHS
u3 = 3 / /
ut = ~~ / /
T3 = Y13 / /
T33 ~33 / /
D3 = b3 / /
0_~ /
/
0=0
T33 =t=K[W3-u3] /
T3 =t= K[W, -u, J /
5 where ul and u3 refer to the displacements (m) in the 1 and 3
directions, respectively. T13 and T33 refer to the normal and shear stresses
(N/m2) in the sagittal plane, respectively. D3 is the electric displacement
component (C/m2). 0 is the electric potential (V). K is the interface
stiffness
(N/m3). There are three interfaces in this configuration (AIN-Si, AIN-Au and
Au-
10 IHS), which are listed in the top row of Table 1. When a boundary condition
is
applied at an interface, the interface is marked with (/).
Results
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The effect of changing the interface stiffness on the fundamental
mode (Mo) of the wave dispersion profile of the IHS-Au-AIN-Si configuration
shown in Figure 3 can be investigated using the wave dispersion model. The
shift in the fundamental mode of the dispersion profile at different interface
stiffness values is shown in Figure 5. The inset provides a better
illustration of
the shift in the dispersion profile.
The results in Figure 5 can provide sufficient information to
calculate the change in wave velocity at various interface stiffness values to
examine the sensitivity of the different h1A configurations. Figure 6
illustrates the
change in wave velocity (%) as the interface stiffness changes from the no
bond
case to the perfect bond case.
Discussion
The effect of adhesive bonding degradation has been investigated
using the shift in the fundamental mode of the wave dispersion profile of the
interface wave generated in the multi-layered configuration. In some
embodiments, it was found that when the interface stiffness K= 2x10" N/m3, the
dispersion profile can matche that of the "perfect bond" case, and when
K=1x108
N/m3, the dispersion profile can match that of the "no bond" configuration.
Figure
5 shows the shift in the MO mode of the wave dispersion profile as the
interface
stiffness values are reduced. The results indicate that for a given h1A
configuration as the interface stiffness decreases, the wave velocity can also
decrease until it reaches that of the no-bond case. Using the shift in the
wave
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dispersion profiles, the sensitivity of different sensor configurations has
been
investigated.
Figure 6 illustrates the change in wave velocity as the interface
stiffness values change from K=1x108 N/m3 to K=2 x1012 N/m3. The results
indicate that at K=1 x108 N/m3, the change in wave velocity can be almost
negligible for all configurations since this interface stiffness value is
equivalent to
the "no-bond" case. At the low stiffness values where K=8x108 N/m3, the low
h/A
configurations can have the highest sensitivity. This trend also occurs at
K=2x109 N/m3 except that the sensitivity of hlA=0.25 drops. This behaviour
occurs because up to K=2x109 N/m3, the interface stiffness is weak and at a
given stress level, the interface discontinuity can be high. At low h/A
values, the
wave penetrates deeper; therefore, the wave can be more sensitive to the
larger
displacement discontinuities at the interface. As the interface stiffness
reaches
K=8x109 N/m3 and continues to increase, the displacement discontinuity can
decrease due to the increased interfacial stiffness. In these cases, the
sensitivity
can increase with increasing h/A values because the wave can become more
confined near the interface and, therefore, more sensitive to changes in
interface
stiffness K. In some embodiments, the interface stiffness value was increased
to
K=2x1012 N/m3 and it was found that the change in wave velocity was
negligible.
This is because K=2x1011 N/m3 can be equivalent to the "perfect bond" case,
and
any further increase in interface stiffness can lead to negligible changes in
wave
velocity.
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From the results in Figure 6, the range of h/A = 0.3 - 0.4 appears to
be appropriate for designing the sensor due to its high sensitivity throughout
the
entire range. Configurations with higher h/A values can have low sensitivity
up to
K=2x109 N/m3 and could require higher precision during electrode fabrication
and
a higher operating frequency range.
Conclusion
A new approach for monitoring adhesive bonding degradation using
an acoustic wave MEMS sensor has been provided herein. In some
embodiments, the approach can be based on examining the shift in the wave
dispersion profile due to changing interface stiffness. A wave dispersion
model
has been developed and can be used to study the effect of changing the
interface stiffness on the wave dispersion profile. The results show that as
the
interface stiffness decreases, there can be a reduction in the wave velocity.
In
addition, the sensitivity of different sensor configurations has been
investigated
and the results indicate that the range of h/A=0.3-0.4 appears to be a choice
for
sensor fabrication in some embodiments.
In some embodiments, an array of acoustic wave MEMS sensors
can be assembled comprising wireless communication means, such as Wi-Fi,
Bluetooth or any other functionally equivalent means as well known to those
skilled in the art, with an antenna and a power supply that can be attached to
an
implant before being insertion into a femur during a hip replacement
procedure.
Although a few embodiments have been shown and described, it
will be appreciated by those skilled in the art that various changes and
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modifications might be made without departing from the scope of the invention.
The terms and expressions used in the preceding specification have been used
herein as terms of description and not of limitation, and there is no
intention in
the use of such terms and expressions of excluding equivalents of the features
shown and described or portions thereof, it being recognized that the
invention is
defined and limited only by the claims that follow.
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The following documents are incorporated into this application by
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