U.S. patent application number 13/196701 was filed with the patent office on 2012-02-02 for noninvasive diagnostic system.
This patent application is currently assigned to Joint Vue, LLC. Invention is credited to Richard Komistek, Mohamed R. Mahfouz, Ray C. Wasielewski.
Application Number | 20120029345 13/196701 |
Document ID | / |
Family ID | 42396088 |
Filed Date | 2012-02-02 |
United States Patent
Application |
20120029345 |
Kind Code |
A1 |
Mahfouz; Mohamed R. ; et
al. |
February 2, 2012 |
NONINVASIVE DIAGNOSTIC SYSTEM
Abstract
A device for acquiring data and diagnosing a musculoskeletal
injury. The device includes a semi-flexible housing, at least one
ultrasonic transducer, a positional localizer, and a transmission
system. The semi-flexible housing is positioned proximate a portion
of the musculoskeletal system of a patient and supports the at
least one ultrasonic transducer and the positional localizer. The
at least one ultrasonic transducer is configured to acquire an
ultrasonic data indicative of a bone surface. The positional
localizer is positioned at a select location relative to the at
least one ultrasonic transducer and tracks movement of the housing.
The transmission system transmits the ultrasonic data of the at
least one ultrasonic transducer and the movement data of the
positional localizer to a data analyzer for analysis and
diagnosis.
Inventors: |
Mahfouz; Mohamed R.;
(Knoxville, TN) ; Wasielewski; Ray C.; (New
Albany, OH) ; Komistek; Richard; (Knoxville,
TN) |
Assignee: |
Joint Vue, LLC
Columbus
OH
|
Family ID: |
42396088 |
Appl. No.: |
13/196701 |
Filed: |
August 2, 2011 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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12364267 |
Feb 2, 2009 |
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13196701 |
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Current U.S.
Class: |
600/427 ;
600/300; 600/425; 600/437; 600/443; 600/587; 600/592; 600/595 |
Current CPC
Class: |
A61B 5/0002 20130101;
A61B 5/1036 20130101; A61B 8/5238 20130101; G16H 20/30 20180101;
A61B 2562/0247 20130101; A61B 2034/2051 20160201; A61B 5/1121
20130101; A61B 8/4227 20130101; A61B 8/4236 20130101; A61B 8/0875
20130101; A61B 8/466 20130101; A61B 5/6831 20130101; A61B 5/743
20130101; A61B 8/4472 20130101; A61B 8/4477 20130101; A61B 5/24
20210101; A61B 5/7435 20130101; G16H 40/63 20180101; A61B 5/0004
20130101; A61B 8/0858 20130101; A61B 2562/02 20130101; G06N 3/084
20130101; A61B 5/1114 20130101; A61B 8/4263 20130101; A61B 5/0059
20130101; A61B 5/1127 20130101; A61B 5/72 20130101; G16H 50/50
20180101; A61B 8/483 20130101; A61B 5/7267 20130101; A61B 5/002
20130101; A61B 8/4254 20130101; A61B 2034/2048 20160201; A61B 5/11
20130101; A61B 5/4533 20130101; A61B 8/5223 20130101; A61B 2034/105
20160201; A61B 2562/0204 20130101; A61B 5/6828 20130101; A61B
2562/0219 20130101; A61B 5/1038 20130101; A61B 5/112 20130101; A61B
8/467 20130101; A61B 2562/046 20130101; A61B 5/6807 20130101; A61B
5/389 20210101; A61B 5/4585 20130101; A61B 5/4528 20130101; A61B
34/20 20160201; A61B 5/6833 20130101 |
Class at
Publication: |
600/427 ;
600/437; 600/300; 600/443; 600/595; 600/587; 600/425; 600/592 |
International
Class: |
A61B 8/00 20060101
A61B008/00; A61B 6/03 20060101 A61B006/03; A61B 5/11 20060101
A61B005/11; A61B 5/103 20060101 A61B005/103; A61B 5/00 20060101
A61B005/00; A61B 8/13 20060101 A61B008/13 |
Foreign Application Data
Date |
Code |
Application Number |
Feb 2, 2010 |
WO |
US/PCT2010/022939 |
Claims
1. A device for acquiring data and diagnosing a musculoskeletal
injury, the device comprising: a semi-flexible housing configured
to be positioned proximate a portion of the musculoskeletal system
of a patient; at least one ultrasonic transducer operably coupled
to the housing and configured to acquire an ultrasonic data
indicative of a bone surface; a positional localizer operably
coupled to the housing at a select location relative to the at
least one ultrasonic transducer, the positional localizer
configured to track movement of the housing; and a transmission
system operably coupled to the housing and configured to transmit
the ultrasonic data from the at least one ultrasonic transducer and
the movement data from the positional localizer to a data analyzer
for analysis and diagnosis.
2. The device of claim 1, wherein the device is a brace configured
to surround the portion of the musculoskeletal system for
diagnosis.
3. The device of claim 2, wherein the brace is a knee brace for
diagnosing a knee injury, the knee brace further comprising: a
first ultrasonic transducer positioned proximate the distal femur;
and a second ultrasonic transducer positioned proximate the
proximal tibia.
4. The device of claim 3, wherein the first ultrasonic transducer,
the second ultrasonic transducer, or both is comprised of an
individual transducer tracking unit.
5. The device of claim 3, wherein the first ultrasonic transducer,
the second ultrasonic transducer, or both is comprised of an
inter-transducer mechanical link unit.
6. The device of claim 3, wherein the first ultrasonic transducer,
the second ultrasonic transducer, or both is comprised of a
rotating transducer unit.
7. The device of claim 1, wherein the positional localizer is an
optical sensor device, an inertial measurement unit device, an
ultra-wide band sensor device, or a combination thereof.
8. The device of claim 1, further comprising: a vibrational sensor
operably coupled to the housing and configured to acquire a
vibration signal generated during movement of the portion of the
musculoskeletal system.
9. The device of claim 8, wherein the vibrational sensor comprises
at least one accelerometer.
10. A method of diagnosing a musculoskeletal injury, the method
comprising: creating a 3D model of a portion of the musculoskeletal
system of a patient; acquiring a feature data with a sensor
positioned proximate the portion of the musculoskeletal system
while the portion is articulated; comparing, with a neural network,
the acquired feature data with a database of feature data, wherein
the database of feature data includes a dataset representative of
the musculoskeletal injury; and returning a diagnosis based on the
comparing.
11. The method of claim 10, further comprising: positioning a
sensor proximate the portion of the musculoskeletal system;
operating the sensor to acquire the feature data; and transferring
the acquired feature data to the neural network.
12. The method of claim 11, wherein the sensor is an ultrasound
transducer and the feature data includes an ultrasonic signal
indicative of a bone surface, the method further comprising:
tracking a position of the ultrasound transducer relative to the
portion of the musculoskeletal system.
13. The method of claim 10, where creating a 3D model further
comprises: acquiring structural data indicative of a surface of a
bone within the portion of the musculoskeletal system; and morphing
a general bone model in accordance with the structural data.
14. The method of claim 13, wherein the structural data includes an
ultrasonic signal, a computerized tomography data, a fluoroscopy
data, or a combination thereof.
15. The method of claim 10, wherein the feature data includes a
vibrational data, a kinematic data, a contact force data, or a
combination thereof.
16. The method of claim 15, wherein the feature data comprises the
vibrational data and the kinematic data, the vibrational data being
time-synchronized with the kinematic data.
17. The method of claim 10, wherein comparing the acquired feature
data further comprises: training the neural network with a
plurality of datasets, wherein at least one of the plurality of
datasets is the dataset representative of the musculoskeletal
injury.
18. The method of claim 10, wherein the feature data includes a
shear measurement, at least one Euler angle, a translational
component, a force data, or a combination thereof.
19. The method of claim 10, further comprising: displaying the
returned diagnosis, the 3D model, the acquired feature data, or a
combination thereof on a user interface.
20. A diagnostic system for diagnosing a musculoskeletal injury,
the diagnostic system comprising: a 3D model reconstruction module
configured to acquire a structural data indicative of a bone
surface within a portion of the musculoskeletal system of a patient
and to construct a patient-specific model from the structural data;
a kinematics tracking module configured to acquire a movement data
while the portion of the musculoskeletal system is articulated; a
vibroarthography module configured to acquire a vibration data
generated during the articulation; and an intelligent diagnosis
module configured to receive and analyze the structural data, the
movement data, and the vibration data and to determine an injury
type from the analysis.
21. The diagnostic system of claim 20, wherein the 3D model
reconstruction module further comprises: an ultrasound transducer
configured to acquire an ultrasonic signal indicative of the bone
surface; a position sensor having a select location relative to the
ultrasound transducer, the position sensor configured to track
movement of the portion of the musculoskeletal system; and a
statistical bone atlas comprising a plurality of bone models,
wherein at least one of the plurality of bone models is morphed in
accordance with the ultrasonic signal.
22. The diagnostic system of claim 20, wherein the kinematics
tracking module further comprises: a brace configured to be
positioned proximate the portion of the musculoskeletal system; at
least one ultrasonic transducer operably coupled to the brace and
configured to acquire an ultrasonic data indicative of the bone
surface; a positional localizer operably coupled to the brace at a
select location relative to the at least one ultrasonic transducer,
the positional localizer configured to track movement of the brace;
and a transmission system operably coupled to the brace and
configured to transmit the ultrasonic data from the at least one
ultrasonic transducer and the movement data from the positional
localizer to the intelligent diagnosis module.
23. The diagnostic system of claim 20, wherein the vibroarthography
module further comprises: at least one vibrational sensor
positioned proximate the portion of the musculoskeletal system; and
a transmission system configured to transmit the vibration data
from the at least one vibrational sensor to the intelligent
diagnosis module.
24. The diagnostic system of claim 20, wherein the intelligent
diagnosis module further comprises: a neural network configured to
compare the movement data, the vibration data, or both to a
database comprising of movement, vibrational, and injury data,
wherein the database includes the movement data or the vibration
data and an associated musculoskeletal injury type; at least one
transformation configured to transfer an acquired data to a virtual
data; and a statistical atlas comprising a plurality of bone
models, wherein at least one of the plurality of bone models is
morphed in accordance with the structural data to construct the
patient-specific model.
25. The diagnostic system of claim 20, further comprising: a
contact force module configured to acquire a pressure data while
the portion of the musculoskeletal system is articulated.
26. The diagnostic system of claim 25, wherein the contract for
module comprises: a shoe insole configured to be positioned on a
foot of a patient; a plurality of pressure sensors operably coupled
to the shoe insole and arranged in a pattern; and a transmission
system operably coupled to the shoe insole and configured to
transmit the pressure data from the plurality of pressure sensors
to the intelligent diagnosis module.
Description
RELATED APPLICATIONS
[0001] The present application claims the filing benefit of
co-pending PCT Patent Application No. PCT/US2010/022939, filed on
Feb. 2, 2010, and is a Continuation-In-Part of co-pending U.S.
patent application Ser. No. 12/364,267, filed on Feb. 2, 2009, the
disclosures of both applications are hereby incorporated by
reference herein in their entirety.
FIELD OF THE INVENTION
[0002] The present invention relates to devices and methods for
evaluating a physiological condition of a musculoskeletal system
and, more particularly, to evaluating the physiological condition
of bodily joints.
BACKGROUND OF THE INVENTION
[0003] In humans, the knee joint 50, as shown in FIGS. 1, 2, and 3,
is functionally controlled by a mechanical system governed by three
unique types of forces: (1) active forces resulting from motion,
such as those resulting from a muscle flexing or relaxing; (2)
constraining forces that constrain motion, such as those resulting
from ligaments being in tension; and (3) interaction forces that
resist motion, such as those acting upon bones. In addition to
these three types of forces, the soft tissue in the knee joint 50
(e.g., cartilage and the meniscus) produce a dampening effect
distributing the compressive loads acting on the knee joint 50.
[0004] Knee joint motions are stabilized primarily by five
ligaments which restrict and regulate the relative motion between
the femur 52, the tibia 54, and the patella 56. These ligaments are
the anterior cruciate ligament ("ACL") 58, the posterior cruciate
ligament ("PCL") 60, the medial collateral ligament ("MCL") 62, the
lateral collateral ligament ("LCL") 64, and the patellar ligament
66. An injury to any one of these ligaments 58-66 or other
soft-tissue structures may cause detectable changes in knee
kinematics and the creation of detectable vibrations, each of which
may be representative of the type of knee joint injury and/or the
severity of the injury. These visual (knee kinematics) and auditory
(vibrations) changes are produced as the bones 52, 54, 56 move in a
distorted kinematic pattern and differ significantly from the look
and sound of a properly balanced knee joint 50 moving through the
same range and types of motion.
[0005] Conventionally, knee vibration has been detected using
microphones with or without stethoscope equipment and correlated
with clinical data regarding various joint problems. However,
microphones and stethoscopes cannot reliably detect frequencies,
especially those experiencing strong interference from noise. Also
the signal clearance can be substantially be influenced by skin
friction. It is desirable, therefore, to provide a diagnostic tool
that compares patient specific data with kinematic data while
providing visual feedback to clinicians.
SUMMARY OF THE INVENTION
[0006] While the present invention will be described in connection
with certain embodiments, it will be understood that the present
invention is not limited to these embodiments. To the contrary,
this invention includes all alternatives, modifications, and
equivalents as may be included within the spirit and scope of the
present invention.
[0007] A device for acquiring data and diagnosing a musculoskeletal
injury in accordance with one embodiment of the present invention
includes a semi-flexible housing, at least one ultrasonic
transducer, a positional localizer, and a transmission system. The
semi-flexible housing is positioned proximate a portion of the
musculoskeletal system of a patient and supports the at least one
ultrasonic transducer and the positional localizer. The at least
one ultrasonic transducer is configured to acquire an ultrasonic
data indicative of a bone surface. The positional localizer is
positioned at a select location relative to the at least one
ultrasonic transducer and tracks movement of the housing. The
transmission system transmits the ultrasonic data of the at least
one ultrasonic transducer and the movement data of the positional
localizer to a data analyzer for analysis and diagnosis.
[0008] Another embodiment of the present invention is directed to a
method of diagnosing a musculoskeletal injury. The method includes
creates a 3D model of a portion of the musculoskeletal system of a
patient. A feature data is acquires by a sensor that is positioned
proximate the portion of the musculoskeletal injury. The feature
data is compared, by a neural network, to a database of feature
data. A dataset within the database of feature data is
representative of the musculoskeletal injury. Then, based on the
comparing, a diagnosis is returned.
[0009] Still another embodiment of the present invention is
directed to a diagnostic system for diagnosing a musculoskeletal
injury. The system includes a 3D model reconstruction module that
acquires a structural data indicative of a bone surface. The bone
is within a portion of the musculoskeletal system of a patient. The
3D model reconstruction module constructs a patient-specific model
from the structural data. The system further includes a kinematic
tracking module that acquires movement data while the portion of
the musculoskeletal system is articulated. A vibroarthography model
acquires vibration data generated by the articulation. The
structural data, the movement data, and the vibration data are
received and analyzed by an intelligent diagnosis module in order
to determine injury type.
[0010] The above and other objects and advantages of the present
invention shall be made apparent from the accompanying drawings and
the description thereof.
BRIEF DESCRIPTION OF THE DRAWINGS
[0011] The accompanying drawings, which are incorporated in and
constitute a part of this specification, illustrate embodiments of
the present invention and, together with a general description of
the invention given above, and the detailed description of the
embodiments given below, serve to explain the principles of the
present invention.
[0012] FIG. 1 is a side elevational view of a posterior portion of
a knee joint with a 90.degree. flexion.
[0013] FIG. 2 is a side elevational view of the knee joint of FIG.
1 but with the knee joint fully extended.
[0014] FIG. 3 is a side elevational view of an anterior portion of
the knee joint in FIG. 1.
[0015] FIG. 4 is a flow chart illustrating a method of determining
a type of knee injury in accordance with one embodiment of the
present invention.
[0016] FIG. 5 is a schematic diagram of a diagnostic system in
accordance with one embodiment of the present invention.
[0017] FIG. 6 is another schematic diagram of the diagnostic system
of FIG. 5.
[0018] FIG. 7 is a schematic view of a knee brace in accordance
with one embodiment of the present invention.
[0019] FIG. 8 is a side elevational view of a vibration detection
module in accordance with one embodiment of the present
invention.
[0020] FIG. 9 is a side elevational view of an exemplary shoe
having a sensor array, for a shoe module, in accordance with one
embodiment of the present invention.
[0021] FIG. 9A is an exemplary wireless transmitter for use with
the shoe module of FIG. 9.
[0022] FIG. 9B is an enlarged view of one exemplary positional
sensor of the shoe module of FIG. 9.
[0023] FIG. 10 is a schematic view of an ultrasound transducer wand
for use with the diagnostic system in accordance with one
embodiment of the present invention.
[0024] FIG. 11 is a diagrammatic view of an ultra wide band
transmitter in accordance with one embodiment of the present
invention.
[0025] FIG. 12 is a diagrammatic view of an ultra wide band
receiver in accordance with one embodiment of the present
invention.
[0026] FIG. 13 is a Cartesian coordinate system depicting an ultra
wide band positioning system in accordance with one embodiment of
the present invention.
[0027] FIG. 14 is a diagrammatic view comparing one embodiment of
an ultra wide band positioning system to a global positioning
system.
[0028] FIG. 15 illustrates the error in detecting a position along
each of the x-, y-, and z-axes and with respect to a sequentially
acquired series of data points.
[0029] FIG. 16 is an exemplary screen capture of a user interface
of the diagnostic system of FIG. 5.
[0030] FIG. 17 is a side elevational view of a leg with a knee
brace in accordance with another embodiment of the present
invention.
[0031] FIG. 18 is a side elevational view of a leg with a knee
brace in accordance with another embodiment of the present
invention.
[0032] FIG. 19 is an individual transducer tracking sub-brace for
use with a knee brace in accordance with one embodiment of the
present invention.
[0033] FIG. 20 is an inter-transducers mechanical link sub-brace
for use with a knee brace in accordance with one embodiment of the
present invention.
[0034] FIG. 21 is a rotating transducer sub-brace for use with a
knee brace in accordance with one embodiment of the present
invention.
[0035] FIG. 22 is a diagrammatic representation of an inertia based
localizer circuit in accordance with one embodiment of the present
invention.
[0036] FIG. 23 is a diagrammatic representation of an alternate
individual transducer tracking sub-brace circuit architecture in
accordance with one embodiment of the present invention.
[0037] FIG. 24 is a diagrammatic representation of a high voltage
circuit for use with a knee brace in accordance with one embodiment
of the present invention.
[0038] FIG. 25 is a diagrammatic representation of the circuit
layout of the high voltage circuit of FIG. 24.
[0039] FIG. 26 is a diagrammatic representation of a high voltage
multiplexer for use with a sub-brace of a knee brace in accordance
with one embodiment of the present invention.
[0040] FIG. 27 a diagrammatic representation of a receiving circuit
for use with a sub-brace of a knee brace in accordance with one
embodiment of the present invention.
[0041] FIG. 28 is a diagrammatic representation of a diagnostic
system in accordance with an embodiment of the present
invention.
[0042] FIG. 29 is a flow chart illustrating one method of using the
diagnostic system of FIG. 28.
[0043] FIGS. 30A-30C illustrate various kinematic feature vectors
acquired from a knee joint moving through a range of motion.
[0044] FIGS. 31A-31C illustrate feature vectors of a femoral
position with respect to the tibia.
[0045] FIG. 32 illustrates average medial and lateral femoral
condyle positions during a deep knee bend of a patient having an
anterior cruciate ligament deficit.
[0046] FIG. 33 is a diagrammatic representation of a neural network
classifier in accordance with one embodiment of the present
invention.
[0047] FIG. 34 is a diagrammatic representation of a construction
of a neural network.
DETAILED DESCRIPTION OF THE INVENTION
[0048] The exemplary embodiments of the present invention are
illustrated and described below to encompass diagnosis of bodily
abnormalities and, more particularly, devices and methods for
evaluating the physiological condition of the musculoskeletal
system (such as joints) to discern whether abnormalities exist and
the extent of any abnormalities. Of course, it will be apparent to
those of ordinary skill in the art that the exemplary embodiments
discussed below are merely examples and may be reconfigured without
departing from the scope and spirit of the present invention.
However, for clarity and precision, the exemplary embodiments, as
discussed below, may include optional steps, methods, and features
that one of ordinary skill should recognize as not being a
requisite to fall within the scope of the present invention. By way
of example, the exemplary embodiments disclosed herein are
described with respect to diagnosing a knee joint injury.
Nevertheless, the exemplary embodiments may be utilized to diagnose
other injuries of the musculoskeletal system (such as a hip joint
injury or a bone fracture), as the knee joint 50 (FIG. 1) is merely
exemplary to facilitate an understanding of the embodiments
disclosed.
[0049] Turning now to the figures and in particular to FIG. 4, with
reference also to FIG. 1, a low level exemplary process flow for a
method 70 of determining a type of knee joint injury in accordance
with one embodiment of the present invention is described. Still
more particularly, the method 70 includes constructing a 3D model
of the knee joint 50 (Block 72), which may include the detection of
motion sound (Block 74) as well as tracking the kinematics (Block
76). The detected sound and tracked kinematics are automatically
analyzed (Block 78) and the knee injury recognized based upon the
analysis (Block 80).
[0050] FIG. 5 illustrates a first exemplary diagnostic system 82
for implementing the method 70 of FIG. 3. The diagnostic system 82
includes four modules: (1) a pulse echo A-mode ultrasound based 3D
model reconstruction ("PEAUMR") module 84 (FIG. 6) for constructing
a patient-specific 3D-model of the patient's knee joint 50 (FIG.
1); (2) a joint kinematics tracking ("JKT") module 86 for tracking
the kinematics of the knee joint 50 (FIG. 1) using the
patient-specific 3D model of the knee joint 50 (FIG. 1) from the
PEAUMR module 84; (3) vibroarthography ("VA") module 88 for
capturing sounds emanating from the knee joint 50 (FIG. 1) while in
motion; and (4) an intelligent diagnosis ("ID") module 90 for
identifying a likely diagnosis of the knee joint 50 (FIG. 1) using
the kinematic data and the vibration data. Each of these four
modules 84-90 is described in further detail below. If desired, a
foot module 92 (FIG. 6) may be included with the JKT module 86 for
providing dynamic force data, also described in detail below.
[0051] It will be understood by those of skill in the art that the
diagnosis system 82 is usable with or without the use of the VA
module 88. For example, the present invention may be used to
mathematically describe the relative motion of the bones 52, 54, 56
in the patient's knee joint 50 as such motion is tracked on a
3D-patient specific bone model. The bone model and motion may be
compared with a database of mathematical descriptions of joint
motion. The database could contain mathematical descriptions of
healthy or clinically undesirable joint motion.
As will be discussed in more detail hereafter, the interaction
between bodily tissue (e.g., bone against cartilage or bone against
bone) in a dynamic environment creates certain vibrations that are
indicative of the condition or state of health of the joint. Even
the healthiest and youngest joints create vibrations. However,
joints that exhibit degradation, whether through wear or injury,
will exhibit vibrations that are much more pronounced and amplified
as compared to those of a healthy joint. The VA module 88 with the
diagnostic system 82 utilizes those sounds, such as vibrations,
exhibited by the joint during a range of motion to diagnose the
condition of the joint without requiring an invasive procedure or
subjecting the patient to radiation.
[0052] FIG. 6 provides still further details of the diagnostic
system 82. The modules 84-92 may output the acquired data to a
computer 96 for data processing by way of, for example, a neural
network 98. The data processing, as will be discussed in more
detail below, may provide one or more of a visual output, an
audible output, and a diagnosis by way of a visual display 100.
[0053] Referring still to FIGS. 4-6, and now also FIG. 7, the VA
module 88 is shown and comprises a plurality of accelerometers
(three are shown 120a, 120b, 120c) that are utilized to detect
sound, specifically, vibrations occurring as a result of motion of
the knee joint 50. In this exemplary VA module 88, the
accelerometers 120a, 120b, 120c are mounted directly to the skin or
external tissue surface of the patient, as skin-mounted sensor
119s, in order to detect sounds from bone and soft tissue
interaction. An intervening adhesive may be utilized between the
accelerometers 120a, 120b, 120c. In the context of the knee joint
50, the VA module 88 includes one accelerometer 120a mounted on the
medial side of the knee joint 50, a second accelerometer 120b
mounted on the lateral side of the knee joint 50, and a third
accelerometer 120c mounted on the front side of the knee joint 50,
proximate the patella 56 (FIG. 3). As illustrated, the
accelerometers 120a, 120b, 120c are mounted to the patient so that
each lies along a common plane 121, though this is not required. It
should also be understood, however, that any number of
accelerometers 120a, 120b, 120c may be utilized to detect sounds
generated by the patient's knee joint 50.
[0054] Each accelerometer 120a, 120b, 120c is in communication with
one or more signal conditioning circuits or electronics 122. The
accelerometers 120a, 120b, 120c are operative to detect sound,
specifically vibrations, and output the sound detected in the form
of frequency data (measured in Hertz) to the conditioning circuits
122. This frequency data is processed by the conditioning circuits
122 and communicated to the computer 96 as digital frequency data.
While the accelerometers 120a, 120b, 120c are generating frequency
data, the conditioning circuits 122 may include a clock 123 to time
stamp the frequency data generated. As will be discussed in more
detail below, correlating the frequency data with the time stamp
provides a constant against which all of the detected data can be
compared on a relative scale.
[0055] The first accelerometer 120a on the medial side of the knee
joint 50 detects vibrations generated primarily by the interactions
between the medial condyle 110 (FIG. 1) of the femur 52 against the
medial cartilage 112 (FIG. 1) on top of the medial portion of the
tibia 54. Similarly, the second accelerometer 120b on the lateral
side of the knee joint 50 detects vibrations generated primarily by
the interactions between the lateral condyle 114 (FIG. 1) of the
femur 52 against the lateral cartilage 116 (FIG. 1) on top of the
lateral portion of the tibia 54. The third accelerometer 120c on
the front of the knee joint 50, proximate the patella 56 (FIG. 3),
detects vibrations generated primarily by the interactions between
the femur 52 against the patella 56 (FIG. 3). The resulting data
output by the accelerometers 120a, 120b, 120c may then be
wirelessly transmitted to the computer 96 via a wireless
transmitter 124, such as an ultra-wide band transmitter, and
utilized in combination with data from the other modules to
ascertain the appropriate diagnosis.
[0056] FIG. 8 illustrates one example of a plurality of thin film
accelerometers (four are shown, 120a, 120b, 120c, 120d) that are
suitable for detecting the vibrations produced by motion of the
knee joint 50. Thin film accelerometers 120a, 120b, 120c, 120d may
be used in lieu of sound sensors because of better performance and
less noise susceptibility. The thin film accelerometers 120a, 120b,
120c, 120d may also be used as a localizer and include the same
circuitry. The accelerometers 120a, 120b, 120c, 120d are attached
to the patients so the outputs may be amplified, digitized, and
sent wirelessly to the computer 96 as described below.
[0057] With reference now to FIGS. 4-6 and 9, the foot module 92
(also referred to as the contact force module ("CFM")) is shown and
includes a plurality of pressure sensors 130 that are utilized to
detect pressure or a contact force occurring at the bottom of the
foot (not shown) when the knee joint 50 (FIG. 1) is moved through a
range of motion under a loaded condition. In other words, as the
patient walks, jogs, runs, etc., the foot module 92 detects
pressure data at the bottom of the foot when the foot is partially
or fully in contact with the ground. In exemplary form, the
pressure sensors 130 are incorporated into an insole 132 of a shoe
134 that conforms to the general shape of a patient's foot. Because
humans have different sized feet, the insoles 132 may be
incrementally sized to accommodate humans with differently sized
feet or to accommodate a particular type of shoe 134 (or lack
thereof) needed for a particular activity.
[0058] The pressure sensors 130 may be arranged in a grid-shaped
pattern on the insole 132, which may include a series of rows and
columns. The pressure sensors 130 are exposed to the underside of a
patient's foot so that the location and amplitude (or amount) of
the contact forces applied by the foot to the shoe 134, by way of
the insole 132, may be measured. As will be discussed in more
detail hereafter, the location of the pressures and the relative
amount of pressures provides information relevant to diagnosis of
injury. For example, the detected pressures of a patient with a
limp caused by a knee joint injury would differ from the detected
pressures of a patient with a healthy knee joint and a normal
gait.
[0059] In one embodiment, each sensor 130 may include a capacitor
having a deformable dielectric between two electrode plates.
Changes in the pressure applied to the plates cause a strain, or
deformation, of the dielectric medium. Thus, a pressure applied to
the capacitive sensor 130 changes the spacing between the plates
and the measured capacitance. The capacitive sensors 130 are
arrayed across the area of pressure measurement to provide discrete
pressure data points corresponding to strains/deformation at the
various locations of the array. These strains/deformations are used
to find the stresses and thus the compressive forces and to
calculate the output of pressure data having units of force per
unit area and time (i.e., N/m sec).
[0060] The sensors 130 in the grid-shape enable positioning of each
detected pressure from each of the sensors 130 relative to another
sensor 130. The resultant data, which includes a two-dimensional
map of the pressure sensors 130, is either stored on the computer
96 or stored locally with the sensors 130. The resulting data may
be wirelessly transmitted to the computer 96 via a wireless
transmitter 136, such as an ultra-wide band transmitter. Using the
2D map of the sensors 130 stored on the computer 96 in combination
with the received sensor pressure data, the computer 96 is
operative to generate data tying detected pressure to position,
specifically the position of one pressure sensor 130 with respect
to another.
[0061] By tying amounts of compressive force to its applied
position, the foot module 92 provides data reflecting precisely
what pressures are exerted at what location. In addition, the
computer 96 may include an internal clock 97 to associate a time of
which the pressure is applied with the pressure data generated by
the pressure sensors 130. Accordingly, the diagnostic system 82 not
only knows how much pressure was exerted and the location where the
pressure was applied, but also has time data indicating the
duration of the applied pressures. Again, by tying the pressure
data generated by the pressure sensors 130 to time, the pressure
data can be correlated with the sound data generated by the VA
module 88 using a common time scale. As a result, the diagnostic
system 82 may evaluate how pressures exhibited at the bottom of the
foot change as a function of time, along with how the vibrational
data changes during the same time.
[0062] FIGS. 4-6 and 10 illustrate the details of the JKT module
86, which comprises an ultrasound creation and positioning
submodule 140, an ultrasound registration submodule 142, and an
ultrasound dynamic movement submodule 144. Specifically, each
submodule 140, 142, 144 includes an A-mode ultrasound transducer to
generate sound and to detect reflected sound, wherein the reflected
sound is representative of the structure, position, and acoustical
impedance of the knee joint 50 (FIG. 1). Commercially-available
transducers may include, for example, an immersion unfocused 3.5
MHz transducer, such as those that are available from Olympus Corp.
(Tokyo, Japan). Those skilled in the art are familiar with the
operation of ultrasound transducers generally and, more
specifically, an A-mode ultrasound transducer that generates sound
pulses and detects sound that is reflected at tissue boundaries of
tissues having different acoustic impedances. The magnitude of the
reflected sound and the time delay are utilized to determine the
distance between the ultrasound transducer and the tissue
interface.
[0063] In the illustrated embodiment, the A-mode ultrasound
transducers are utilized to detect the interface between bone and
the surrounding soft tissue so that the location of the bone
surface may be determined. Because the operation of ultrasound
transducers (including the A-mode ultrasound transducers) is well
known to those skilled in the art, a detailed discussion of the
operation of ultrasound transducers in general, and A-mode
ultrasound transducers specifically, has been omitted only for
purposes of brevity.
[0064] The ultrasound creation and positioning submodule 140 as
shown in FIG. 10 comprises one or more A-mode ultrasound
transducers 150 fixedly mounted to a wand 152. The wand 152 further
includes at least one positioning device 170. In this exemplary
embodiment, the ultrasound creation and positioning submodule 140
is physically separate from the ultrasound registration submodule
142 (FIG. 6) and the ultrasound dynamic movement submodule 144
(FIG. 6), the latter two of which are mounted to a rigid knee brace
220 schematically illustrated in FIG. 17. In this fashion, the
ultrasound creation and positioning submodule 140 is repositionable
with respect to the rigid knee brace 220 (FIG. 17) and adapted to
place one or more of its A-mode ultrasound transducers 150 in
contact with the patient's epidermis, proximate the knee joint 50
(FIG. 1). It should be noted, however, that the knee brace 220
(FIG. 17) does not have to be rigid, other than the linkages
between certain components. Moreover, the knee joint 50 (FIG. 1)
may be scanned by the ultrasound wand 152 before positioning the
brace 220 (FIG. 17) thereon.
[0065] One of the functions of the ultrasound creation and
positioning submodule 140 is to generate an electrical signal that
is representative of the ultrasonic wave detected by the
transducers 150 as the wand 152 moves over the patient's epidermis,
proximate the knee joint 50 (FIG. 1). The ultrasound transducers
150 receive the ultrasonic wave based upon the magnitude of the
reflected ultrasonic wave from the bone-tissue interface. As
discussed previously, the magnitude of the electrical signal and
the delay between the generation of the ultrasonic wave by the
ultrasound transducer 150 to detection of the reflected ultrasonic
wave by the ultrasound transducer 150 is indicative of the distance
to the bone underneath the transducer 150. But, distance data alone
is not particularly useful; therefore, one or more positioning
devices 170 are used to provide a 3D coordinate system, one example
of which is shown in FIG. 11.
[0066] The positioning devices 170 of the ultrasound creation and
positioning submodule 140 are fixedly mounted to the wand 152 and
may include any of a number of positioning devices 170. For
example, the wand 152 may include one or more optical devices (as
the positioning devices 170) that are configured to generate,
detect, and/or reflect pulses of light. These pulses of light
interact with a corresponding detector or light generator to
discern the position of the wand 152, in 3D space, and with respect
to a fixed or reference position. One such device includes a light
detector configured to detect pulses of light emitted from light
emitters having known positions. The light detector detects the
light and sends a representative signal to the computer 96 or
otherwise a controller (not shown) of the light detector. The
computer 96 is also provided the time at which the light pulses
were emitted by the optical devices 170. In this matter, the
computer 96 determines the position of the wand 152 relative to the
known positions of the detectors. Because the ultrasound transducer
150 and the optical devices 170 are fixedly mounted to the wand
152, the position of the ultrasound transducers 150 with respect to
the position of the optical devices 170 is known. Similarly,
because the ultrasound transducers 150 are generating signals
representative of the straight line distance between the
transducers 150 and the bone-tissue interface, and the position of
the transducers 150 with respect to the optical devices 170 is
known, the position of the bone-tissue interface with respect to
the optical devices 170 may be determined. In other words, as the
wand 152 moves over the patient's epidermis, the optical devices
170 generate data that is determined, by the computer 96, to
represent that the relative position of the optical devices 170
with respect to the light detectors has changed in the 3D
coordinate system. This change in the position of the optical
devices 170 may be easily correlated to the position of the
bone-tissue interface, in 3D, because the position of the
bone-tissue interface relative to the ultrasound transducers 150,
as well as the position of the optical devices 170 with respect to
the ultrasound transducers 150 are known. Accordingly, the 3D
position data may be used in combination with the fixed position
data (distance data for the position of the ultrasound transducers
150 with respect to the optical devices 170) for the ultrasound
transducers 150 in combination with the distance data generated in
response to the signals received from the ultrasound transducers
150 to generate composite data. The composite data may, in turn, be
used to create a plurality of 3D points representing a plurality of
distinct points on the surface of the bone, along the bone-tissue
interface. As will be discussed in more detail below, these 3D
points are utilized in conjunction with a default bone model to
generate a virtual, 3D representation of the patient's bone.
[0067] Alternatively, the positioning devices 170 may comprise one
or more inertial measurement units ("IMUs"). IMUs are known to
those skilled in the art and include accelerometers, gyroscopes,
and magnetometers that work together to determine the position of
the IMUs in a 3D coordinate system. Because the A-mode ultrasound
transducer 150 and the IMUs 170 are fixedly mounted to the wand
152, the position of the ultrasound transducers 150 with respect to
the position of the IMUs 170 is known. Similarly, because the
ultrasound transducers 150 are generating signals representative of
the straight line distance between the transducers 150 and the
bone-tissue interface and the position of the transducers 150 with
respect to the IMUs 170 is known, the position of the bone-tissue
interface with respect of the IMUs 170 may be determined. In other
words, as the wand 152 moves over the patient's epidermis, the IMUs
170 generate data that is determined, by the computer 96, to
represent that the relative position of the IMUs 170 has changed in
the 3D coordinate system. This change in the position of the IMUs
170 may be easily correlated to the position of the bone-tissue
interface in 3D because the position of the bone tissue interface
relative to the ultrasound transducer 150 is known, as is also the
position of the IMUs 170 with respect to the ultrasound transducers
150. Accordingly, the 3D position data may be used in combination
with the fixed position data (distance data for the position of the
ultrasound transducers 150 with respect to the IMUs 170) for the
ultrasound transducers 150 in combination with the distance data
generated in response to the signals received from the ultrasound
transducers 150 to generate the composite data as described
above.
[0068] Referring now also to FIGS. 11-12, the positioning devices
170 may still alternatively comprise one or more ultra-wide band
(UWB) transmitters. UWB transmitters are known to those skilled in
the art, but the use of UWB transmitters and receivers for
millimeter resolution 3D positioning is novel. In that regard, one
or more UWB transmitters 170 are fixedly mounted to the wand 152
and configured to sequentially transmit UWB signals to three or
more UWB receivers 172 having known positions in a 3D coordinate
system. This embodiment of the positioning device 170 is comprised
of active tags or transmitters 170 that are tracked by the UWB
receivers 172. The system architecture of the UWB transmitter 170
is shown in FIG. 11 where a low noise system clock ("crystal
clock") 174 triggers a baseband UWB pulse generator 176 (for
instance a step recovery diode ("SRD") pulse generator). The
baseband pulse from the baseband UWB pulse generator 176 is
upconverted by a local oscillator 178 via a double balanced
wideband mixer (not shown). The upconverted signal is amplified and
filtered ("bandpass filter" 180). Finally the signal is
transmitted, via an omnidirectional antenna 182, to the computer 96
(FIG. 6). The UWB signal may travel through an indoor channel where
significant multipath and pathless effects cause noticeable signal
degradation.
[0069] The UWB receiver 172 architecture in accordance with one
embodiment is shown in FIG. 12. The signal is received via a
directional UWB antenna 184 and is filtered and amplified
("bandpass filter" 186), downconverted by a local oscillator 187,
and low-pass filtered ("LPF") 188. A sub-sampling mixer 190
triggered by a second low noise system clock ("crystal clock") 192
is used to tune extend the pulse by about 1,000 to about 100,000
times. This effectively reduces the bandwidth of the UWB pulse and
allows sampling by a conventional analog-to-digital converter
("ADC") 194.
[0070] Each UWB transmitter 170 and receiver 172 is in
communication with the computer 96. Accordingly, the computer 96
detects each time the UWB transmitter 170 transmits a UWB signal,
as well as the time at which the UWB signal was transmitted.
Similarly, the computer 96 detects the position of each of the UWB
receivers 172 in the 3D coordinate system, as well as the time at
which the UWB signal was received. The final
time-difference-of-arrival ("TDOA") calculation, via a UWB
positioning system 183, is shown in FIG. 13.
[0071] Referring now to FIG. 13, for the TDOA calculation, at least
four base receivers 172 (Rx1, Rx2, Rx3, Rx4) are needed to localize
the 3D position of the UWB transmitter 170 ("Tag"). The geometry of
the receivers Rx1, Rx2, Rx3, Rx4 has important ramifications on the
achievable 3D accuracy through what is known as geometric position
dilution of precision ("PDOP"). A combination of novel filtering
techniques, high sample rates, robustness to multipath
interference, accurate digital ranging algorithms, low phase noise
local oscillators, and high integrity microwave hardware are needed
to achieve millimeter range accuracy (e.g. ranging from about 5 mm
to about 7 mm in 3D real-time). An analogy of the UWB positioning
system 183 to a GPS system 185 is shown in FIG. 14.
[0072] FIG. 15 shows actual experimental errors in each of the x-,
y-, and z-coordinates for detecting the position of the UWB
transmitter 170 in 3D space and in real-time for over 1000 samples
while the transmitter 170 is moving freely within the 3D space.
[0073] Because the A-mode ultrasound transducers 150 and the UWB
transmitters 170 are fixedly mounted to the wand 152, the position
of the ultrasound transducers 150 with respect to the position of
the UWB transmitters 170 is known. Similarly, because the
ultrasound transducers 150 are generating signals representative of
the straight line distance between the ultrasound transducers 150
and the bone-tissue interface and the position of the ultrasound
transducers 150 with respect to the UWB transmitters 170 is known,
the position of the bone-tissue interface with respect to the UWB
transmitter 170 may be determined. In other words, as wand 152
moves over the patient's epidermis, the UWB transmitters 170
transmit UWB signals that are correspondingly received by the UWB
receivers 172. These UWB signals are processed by the computer 96
in order to discern whether the relative position of the UWB
transmitters 170 has changed in the 3D coordinate systems, as well
as the extent of such a change. This change in 3D position of the
UWB transmitters 170 can be easily correlated to the position of
the bone-tissue interface in 3D because the position of the bone
relative to the ultrasound transducer 150 and the position of the
UWB transmitters 170 with respect to the ultrasound transducer 150
are known. Accordingly, the UWB 3D position data may be used in
combination with the fixed position data (distance data for the
position of the ultrasound transducers 150) to generate the
composite data as described above.
[0074] Regardless of the positioning device 170 utilized with the
ultrasound creation and positioning submodule 140, the wand 152 is
repositioned over the skin of the patient, proximate to the knee
joint 50 (FIG. 1) while the knee joint 50 (FIG. 1) is bent. Bending
the patient's knee joint 50 (FIG. 1) during data acquisition
enables the creation of a 3D series of points for each of the bones
of the knee joint 50 (FIG. 1) (the distal femur 52, the proximal
tibia 54, and the patella 56). Thus, as the wand 152 is
repositioned, the data from the transducer 150 is transmitted to a
wireless transmitter 200 mounted to the wand 152. When the wireless
transmitter 200 receives the data from the transducers 150, the
transmitter 200 transmits the data via a wireless link to the
computer 96.
[0075] In order to power the devices on-board the wand 152, an
internal power supply (not shown) may be provided. In one
embodiment, the internal power supply comprises one or more
rechargeable batteries.
[0076] Transformation is needed for transforming the position data
from a reference coordinate frame of reference to a world frame of
reference. According to one embodiment of the present invention, a
linear movement of the ultrasound transducer 150 may be
described:
v(n+1)=v(n)+a(n)dt Equation 1
s(n+t)=s(n)+v(n)dt=0.5a(n)dt.sup.2 Equation 2
where s(n+1) is the position of the ultrasound transducer 150 at a
current state, s(n) is the position from a previous state, v(n+1)
is the instantaneous velocity of the current state, v(n) is the
velocity from previous state, a(n) is the detected acceleration,
and dt is the sampling time interval. The previous equations
describe the dynamic motion and positioning of a point in 3D
Euclidean space. Additional information is needed to describe 3D
orientation and motion.
[0077] The orientation of the ultrasound transducer 150 may be
described by using a gravity-based accelerometer (for example
ADXL-330, analog device) and extracting the tilting information
from each of a pair of orthogonal axes. The acceleration output on
each of the x-, y-, or z-axes is due to gravity and is equal to the
following:
A.sub.i=(V.sub.outx-V.sub.off)=S Equation 3
where A.sub.i is the acceleration of the ultrasound transducer 150
along each of the x-, y-, or z-axes, V.sub.outx is the voltage
output on each of the x-, y-, or z-axes, V.sub.off is the offset
voltage, and S is the sensitivity of the accelerometer. The yaw,
pitch, and roll may be thus calculated as:
.rho. = arctan ( A x A y 2 + A z 2 ) Equation 4 .PHI. = arctan ( A
y A x 2 + A z 2 ) Equation 5 .theta. = arctan ( A y 2 + A x 2 A z )
Equation 6 ##EQU00001##
where pitch is .rho. (the x-axis relative to the ground), roll is
.phi. (the y-axis relative to the ground) and roll is .theta. (the
z-axis relative to the ground). Since the accelerometer is
gravity-based, the orientation does not require information from
the previous state once the accelerometer is calibrated. The static
calibration requires the resultant sum of accelerations from each
of the three axes to equal 1-g (where g is the nominal acceleration
due to gravity at the Earth's surface at sea level, defined to be
precisely 9.80665 m/s.sup.2 (approximately 32,174 ft/s.sup.2)).
Alternatively, an orientation sensor that provides yaw, pitch and
roll information of the bodily tissue in question may be used. One
such orientation sensor may be the commercially-available model
IDG-300 from InvenSense (Sunnyvale, Calif.). The orientation of the
ultrasound transducer 150 may then be resolved by using, for
example, a direction cosine matrix transformation:
X.sub.2C.theta.C.phi.C.theta.C.phi.S.sub.p-S.theta.C.sub.pC.theta.S.phi.-
C.sub.p-S.theta.S.sub.pX.sub.1
Y.sub.2=S.theta.C.phi.S.theta.S.phi.S.sub.p-C.theta.C.sub.pS.theta.S.phi-
.C.sub.p-C.theta.S.sub.pY.sub.1 Equation 7
Z.sub.2-S.phi.C.phi.S.sub.pC.theta.C.sub.p
where C represents cosine and S represents sine.
[0078] Referring again to FIGS. 4-6, and now also to FIG. 16, the
PEAUMR module 84 is described in greater detail. The PEAUMR module
84 constructs a 3D model of the patient's knee joint 50 (FIG. 6) by
converting the transcutaneously acquired a set of 3D data points
(using the tracked pulse echo A-mode ultrasound transducer 150),
that, in total, are representative of the shape of the bone-tissue
interface and therefore each bones' surface.
[0079] Before the patient data is acquired, software residing on
the computer 96 may request a series of inputs from the user to
adapt the diagnostic system 82 to equipment specific devices and
the particular portion of the musculoskeletal anatomy to be
modeled. For example, a menu 204 on a user interface 206 may be
presented for the user to select the type of digitizer, which may
include, without limitation, ultrasound. After the type of
digitizer is selected, the user may actuate buttons 205a, 205b to
connect to or disconnect from the digitizer, respectively.
[0080] As wand 152 moves over the patient's epidermis, the set of
points is generated, numerically recorded, viewable in a data
window 210, and ultimately utilized by the software to conform a
selected bone model to the patient's actual bone shape.
Consequently, the wand 152 is repositioned over the bones (the
distal femur 52, the patella 56, the proximal tibia 54) for
approximately 30 seconds so that the discrete points to typify the
topography of the bone. Repositioning the wand 152 over the bone in
question for a longer duration results in more 3D points being
generated increases the resolution and improves the accuracy of the
patient-specific bone model. A partial range of motion of the knee
joint 50 (FIG. 1) while repositioning the wand 152 over the knee
joint (FIG. 1) aids in scanning additional portions of the bone in
question for new 3D points that may have been obscured by other
bones in another range of motion position.
[0081] Before, during, or after the ultrasound data is acquired,
the software provides various drop-down menus allowing the software
to load a bone model 208 that is roughly the same shape as the
patient's bone. The computer 96 receives the ultrasound data, the
computer 96 includes software that interprets the A-mode ultrasound
transducer data and constructs a 3D map having discrete 3D points
corresponding to points on the surface of the scanned bone. That
is, the shape of the patient's bone is reconstructed in virtual
space, using a set of points outlining the surface of the patient's
bone as acquired by the tracked ultrasound transducer 150 (FIG.
10). The set of points is applied to an atlas-based deformable
model software to reconstruct the patient-specific 3-D model.
[0082] More specifically, the computer 96 may include a database
having a plurality of bone models of various portions of the
musculoskeletal system, for example, the femur 52, the tibia, 54,
and the patella 56, that are classified and selectable in a menu
212, for example based upon ethnicity, gender, height ranges, the
side of the body, and so forth. Each of these classifications is
accounted for in a drop-down menu of the software so that the model
initially chose by the software most closely approximates the body
of the patient.
[0083] For mapping each bone, the computer 96 uses either a default
bone model or the selected bone model as a starting point to
construction of the ultimate patient-specific, virtual bone model.
The default bone model may be a generalized average, as the
morphing algorithms use statistical knowledge of a wide database
population of bones for a very accurate model. The selected bone
model expedites computation. For example, in the case of generating
a patient-specific model of the femur 52 where the patient is a 53
year old, Caucasian male, who is six feet tall, a default femoral
bone model is selected based upon the classification of Caucasian
males having an age between 50-60, and a height ranging from 5'10''
to 6'2''. In this manner, selection of the appropriate default bone
model more quickly achieves an accurate patient-specific, virtual
bone model because of the number of iterations between the
patient's actual bone (typified by the 3D map of bone points) and
the default bone model are reduced. Nevertheless, in view of the
model bones taking into account numerous traits of the patient
(ethnicity, gender, bone modeled, and body side of the bone), it is
quite possible to construct an accurate patient-specific 3D model
with as few as 150 data points comprising the set which typically
may be acquired by repositioning the wand 152 over the bone for 30
seconds for each bone. Ultrasound will not be affected whether the
patient has a prosthetic implant.
[0084] After the appropriate bone model is selected, the computer
96 superimposes the 3D points onto the default bone model and,
thereafter, carries out a deformation process so that the bone
model exhibits the 3D bone points detected during the signal
acquisition. The deformation process also makes use of statistical
knowledge of the bone shape based upon reference bones of a wide
population. After the deformation process is complete, the
resulting bone model is a patient-specific, virtual 3D model of the
patient's actual bone. The foregoing process is repeated for each
bone comprising the specific joint to create patient-specific,
virtual 3D models of the patient's anatomy.
[0085] Referring back to FIGS. 4-7, and now also FIG. 17, the JKT
module 86 may be configured to track the kinematics of the knee
joint 50 (FIG. 1) and display the kinematics on the
patient-specific 3D bone model generated by the PEAUMR module 84
using, for example, one or more bone motion tracking braces 220.
Generally, the bone motion tracking brace 220 includes pulse echo
A-mode ultrasound transducers 222 to transcutaneously localize the
bone-tissue interface and derive a set of points outlining each
bone's surface.
[0086] Turning specifically to FIG. 17, the brace 220 includes a
plurality of A-mode ultrasound transducers 222 fixedly mounted to
the knee brace 220. Specifically, in the context of a knee joint
50, there are at least two A-mode ultrasound transducers 222 (i.e.,
"a transducer group" 222a, 222b) fixedly mounted to the knee brace
220 for tracking of the tibia 54 (FIG. 1) and the femur 52 (FIG.
1). In other words, the knee brace 220 includes at least six
ultrasound transducers 222 in order to track the two primary bones
52, 54 (FIG. 1) of the knee joint 50. Each transducer group 222a,
222b includes a rigid, mechanical connection linking the
transducers 222 and the positioning devices 224 to the knee brace
220. In this manner, the relative positions of the transducers 222
with respect to one another do not change. A first transducer group
222a at least partially circumscribes a distal portion of the femur
52 (FIG. 1); while a second transducer group 222b at least
partially circumscribes a proximal portion of the tibia 54 (FIG.
1); and an optional third transducer group (not shown) overlies the
patella 56 (FIG. 3) if patella kinematics are desired. The
ultrasound registration submodule 142 is accordingly configured to
provide a plurality of static reference points for each bone as the
bone is moved through a range of motion.
[0087] Each ultrasound transducer 222 is tracked using an
accelerometer or a sensor-specific localizer (or any other
appropriate inertial sensor). The tracking may then be used to
generate localized bone points from the outputs of the ultrasound
transducers 222 and to virtually display bone movement on the 3D
model while the knee joint 50 (FIG. 1) is taken through the range
of motion.
[0088] Referring to FIGS. 6 and 17, the ultrasound dynamic movement
submodule 144 comprises a plurality of positioning devices 224 that
is configured to feed information to the computer 96 regarding the
3D position of each transducer group 222a, 222b of the ultrasound
registration submodule 142. In exemplary form, the position devices
224 may comprise light detectors operative to detect pulses of
light emitted from light emitters having known positions. The light
detectors 224 detect the light and transmit representative signals
to a control circuitry (not shown) associated with the knee brace
220. The knee brace 220 transmits this information to the computer
96, which also knows when the light pulses were emitted as a
function of time and position. In this manner, the computer 96 may
determine the position of the transducers 222 in the 3D coordinate
system. Because the ultrasound transducers 222 and the optical
devices 224 are fixedly mounted to the knee brace 220, the position
of the ultrasound transducers 222 with respect to the position of
the optical devices 224 is known. Similarly, because the ultrasound
transducers 222 are generating signals representative of the
straight line distance between each of the ultrasound transducers
222 and the bone-tissue interface beneath, and the position of the
ultrasound transducers 222 with respect to the optical devices 224
is known, the position of the bone-tissue interface with respect to
the optical devices 224 may be easily determined. In other words,
as the knee joint 50 (FIG. 1) is moved, and correspondingly so too
is the knee brace 220, the optical devices 224 generate data that
is determined by the computer 96 that the relative position of the
optical devices 224 has changed in the 3D coordinate system. This
change in the position of the optical devices 224 may be easily
correlated to the position of the bone in question in 3D because
the position of the bone relative to the ultrasound transducer
groups 222a, 222b is known, as is the position of the optical
devices 224 with respect to the ultrasound transducer groups 222a,
222b. Accordingly, the optical devices 224 generate data that is
used in combination with the fixed position data (distance data for
the position of the ultrasound transducers 222) to generate the
composite data. The composite data may, in turn, be used to create
dynamically moving map of the bone on the patient-specific 3D
model.
[0089] Alternatively, the positioning devices 224 may be comprised
of one or more IMUs. Because the ultrasound transducers 222 and the
IMUs 224 are fixedly mounted to the knee brace 220, the relative
positions between the ultrasound transducers 222 and the IMUs 224
are known. Similarly, because the ultrasound transducers 222 are
generating signals representative of the straight line distance
between the transducer 222 and the bone-tissue interface, and the
position of the transducers 222 with respect to the IMUs 224 is
known, the position of the bone with respect to the IMUs 224 may be
easily determined. In other words, as the knee joint 50 (FIG. 1)
with the knee brace 220 moves, the IMUs 224 generate data that is
determined, by the computer 96, as a change in the position of the
IMUs 224. This change in the position of the IMUs 224 may be easily
correlated to the position of the bone in 3D because the position
of the bone relative to the ultrasound transducer groups 222a, 222b
is known, as well as the position of the IMUs 224 with respect to
the ultrasound transducer groups 222a, 222b. By way of example,
because the ultrasound transducers 222 do not move with respect to
the knee brace 220, any movement of the IMUs 224 in space means
that the knee brace 220 has also moved in space, and by continuing
to track the distance data provided by each IMU 224, the movement
of the bone may be correspondingly tracked. IMU tracking of the
bone movements requires a static registration between the IMUs 224
and an initial known body position (such as standing). The IMUs 224
enable measurement of the relative motion between different bones
via their corresponding ultrasound transducer group data and the
IMU data. The IMUs 224 may be used alone or in conjunction with
other positioning devices 170 (FIG. 10), such as those described in
detail above. In this scenario, the IMU position is updated at a
certain interval with the absolute position provided by the
additional positioning system to minimize error. Therefore the two
positioning systems act together as one positioning system.
[0090] As was described previously with respect to the wand 152,
the positioning devices 224 of the brace 220 may alternatively be
comprised of one or more ultra wide band (UWB) transmitters. In
that regard, one or more UWB transmitters 224 are fixedly mounted
to the brace 220 and operable to transmit sequential UWB signals to
three or more UWB receivers (not shown) having known positions in
the 3D coordinate system. Each UWB transmitter 224 is in
communication with the computer 96, as are the plurality of UWB
receivers (not shown). Accordingly, the computer 96 detects each
time the UWB transmitter transmits a UWB signal, as well as the
time at which the UWB signal was transmitted. Similarly, the
computer 96 detects the position of each of the UWB receivers (not
shown) in the 3D coordinate system, as well as the time at which
the UWB signal was received. The computer 96 may then use the
custom digital signal processing algorithms to accurately locate
the leading-edge of the received UWB pulse based on the position of
each UWB receiver (not shown), the time when each UWB signal was
received, and the time that the UWB signal was transmitted. The
position may then be determined by the TDOA calculation as was
described with reference to FIG. 11). Again, because the ultrasound
transducers 222 do not move with respect to the knee brace 220, any
movement of the transducers 222 in space means that the brace 220
has moved. The movement of the knee brace 220 is tracked using the
computer 96 in combination with the UWB transmitters 224 and the
UWB receivers (not shown). Similarly, because the fixed orientation
between the UWB transmitters 224 and the ultrasound transducers 222
changes in position in the 3D coordinate system, the UWB
transmitter 224 may correspondingly be used to track movement of
each bone.
[0091] In order to communicate information from the submodules 142,
144 to the computer 96, the brace 220 may include a transmitter
228, such as a UWB transmitter, in communication with the
ultrasound transducer 222 to facilitate wireless communication of
data to the computer 96. It should be noted that if UWB transmitter
228 is also utilized as the positioning devices 224, a dedicated
transmitter 228 is unnecessary as the UWB transmitters 224 could
function to also send ultrasound data directly to the computer 96
over a wireless link.
[0092] It should be understood that use of the transmitter 228 and
a field programmable gate array design enables the computations to
be cammed out on a real-time basis. For example, as patient's knee
joint 50 (FIG. 1) is bent while wearing the brace 220, the
ultrasound data is immediately transmitted to the computer 96,
which in real-time, calculates and displays the position and
movement of each bone with the 3D patient-specific bone model.
[0093] FIG. 18 illustrates a knee brace 230 in accordance with
another embodiment of the present invention. The knee brace 230 has
a first sub-brace 232 positioned at the distal portion of the femur
52, a second sub-brace 234 positioned at the proximal end of the
tibia 54, and a third sub-brace 236 positioned at the patella 56
(FIG. 3). The sub-braces 232, 234, 236 include a plurality of
transducers mounted thereto. Each transducer is responsible for
determining the location of a point on the surface of the bone
during movement of the knee joint 50. The sub-braces 232, 234, 236
reduce the occurrence of problems of locating and tracking the bone
using ultrasound data when the motion of the bone relative to the
skin is small compared to the gross joint motion. There are at
least three approaches disclosed herein for tracking the motion of
the ultrasound transducers themselves.
[0094] FIG. 19 illustrates the first approach commonly referred to
herein as an "ITT" (individual transducer tracking) approach. In
FIG. 19, each transducer 238 in the sub-brace 232 has an associated
tracking module 240 to individually track each transducer 238.
Using the ITT approach, the transducers 238 may be supported by a
flexible length of strap.
[0095] Referencing FIG. 20, a sub-brace 241 according to the second
approach is shown. The second approach, commonly referred to herein
as an "ITML" (Inter-Transducers Mechanical Links) approach,
involves the transducers 242 being connected to each other by
movable mechanical links 244. Each mechanical link 244 includes
length and angle sensors 246 that allow for detection of the
movement of the transducers 242 relative to one another and the
relative translational motions of the links 244. Every two links
244 are connected by a pivot pin 248 that allows rotation and
translation of the links 244 relative to each other. The length and
angle sensors 246 are mounted to at least one link 244 and
proximate to the pivot pin 248 to allow for detection of the angle
between adjacent 244 links. The ITML approach features a fewer
number of localizers than the ITT approach of FIG. 19.
[0096] Referring now to FIG. 21, a sub-brace 249 according to the
third approach is shown. The third approach, commonly referred to
herein as a "RT" (Rotating Transducer) approach, involves using a
single ultrasound transducer 250 that is mounted to a carriage 252.
The carriage 252 traverses along a track 254, located on the inner
circumference 256 of the sub-brace 249. For example, the carriage
252 may be moved along the track 254 by a string loop 258 that is
wrapped around the drive shaft (not shown) of a motor 260. When the
transducer 250 reaches the motor 260, the rotation direction of the
motor 260 is changed and the transducer 250 moves in the opposite
direction.
[0097] A tracking module 262 such as an inertia-based localizer is
mounted to the transducer 250 to track its motion. As the
transducer 250 rotates within the inner circumference 256 of the
sub-brace 249, it collects data as to the bone-tissue interface. By
using a single transducer 250, the RT approach includes the
advantage of lower cost than the stationary transducer designs and
higher accuracy due to the greater number of localized bone surface
points for each tracking step, while maintain a mechanical
flexibility.
[0098] Referring to FIG. 22, a localizer 270 of tracking each
ultrasound transducer 238 (FIG. 19) mounted to the sub-brace 232
(FIG. 19) is shown. The localizer 270 comprises a plurality of
nodes 272 with each node 272 comprising a CMOS accelerometer and a
temperature sensor (not shown) for thermal drive comparison. Each
node 272 is integrated to minimize noise and distortion. The
outputs of the accelerometers 272 regarding the x-, y-, and
z-coordinates and the temperature sensors (not shown) are directed
to a multiplexer 274 ("MUX") that multiplexes the signals.
Multiplexed outputs are amplified by an amplifier 276 ("AMP"), and
then directed to an ADC 278. The digital conversion of the signal
may be performed within or outside the accelerometers 272.
Outputting digital signals may then be directed to a wireless
transmitter 280 by way of a parallel input/serial output device
282.
[0099] In FIG. 23 a design alternative for the sub-brace 232 is
shown. The electronic architecture includes a high voltage
amplifier circuit 286 ("HV IX AMP") feeding a voltage multiplex
circuit ("HV MUX") 288 to excite each ultrasound transducer 238 and
thereby acts as an analog switch. The echo signals from each
transducer 238 are multiplexed pursuant to a logic control
directing the opening of the switches in the MUX 290 at precise
intervals. An exemplary logic control is the MSP430, available from
Texas Instruments, Inc. (Dallas, Tex.). The output from the MUX 290
is I amplified by a low noise AMP 292 ("LNA") and the signal is
conditioned using a conditioning circuit (for example, a
time-gain-control ("TGC") circuit 294 and a band-pass filter
("BPF") 296, and digitized using an ACS 298. Electric power to the
foregoing components is supplied by way of a battery 300, which
also supplies power to a wireless transmitter module 302. In
exemplary form, the wireless transmitter module 302 utilizes a
universe asynchronous receiver/transmitter ("UART") protocol. The
wireless transmitter module 302 includes a wireless transmitter
circuit 304 receiving the output from a first in-first out ("FIFO")
buffer (not shown) of the ADS 298 by way of a serial interface 306.
An output from the wireless transmitter circuit 304 is conveyed
using a serial link coupled to an antenna 308. Signals conveyed
through the antenna 308 are broadcast for reception by a wireless
receiver (not shown) coupled to a controller (not shown) or the
computer 96 (FIG. 6).
[0100] Referring now to FIGS. 24 and 25, an exemplary high voltage
circuit 310 is shown and may be used to trigger and generate the
excitation energy for a piezoelectric crystal in the ultrasound
transducer 238 (FIG. 19). Exemplary high voltage circuits 10 for
use in this embodiment may include, without limitation, the pulsar
integrated circuit (HV379) available from Supertex, Inc (Sunnyvale,
Calif.).
[0101] Referencing FIG. 26, an exemplary high voltage multiplexer
312 is shown and may be used to trigger and excite multiple
piezoelectric transducers 238 (FIG. 19) without increasing the
number of high voltage circuits 310 (FIG. 24). Exemplary high
voltage multiplexer 312 for use in this embodiment may include,
without limitation, the high voltage multiplexer (HV2221) available
from Supertex, Inc (Sunnyvale, Calif.). The advantage of using a
high voltage multiplexer 312 is the ability to use CMOS level
control circuitry, thereby making the control logic compatible with
virtually any microcontroller or field programmable gate array that
is commercially-available.
[0102] Referring to FIGS. 23 and 27, an exemplary receiving circuit
314, which comprises the MUX 290, the LNA 292, the TGC 294, the BPF
296, and the ADC 298 is shown and may be utilized to receive the
echo signals from each transducer 238. Exemplary receiving circuits
314 for use in the this embodiment include, without limitation, the
AD9271 8-channel ultrasound receiving integrated circuits,
available from Analog Devices, Inc. (Norwood, Mass.).
[0103] With reference now to FIGS. 28 and 29, one method 316 of
using X-ray fluoroscopy and in-vivo measurements of dynamic knee
kinematics, as described above, for understanding the effects of
joint injuries, diseases, and evaluating the outcome of surgical
procedures is described. In the particular illustrated embodiment,
and using the two aforementioned techniques, six degrees of freedom
("DOF") are determined for the knee joint 50 (FIG. 1) and include
the position and orientation of each bone comprising the knee joint
50 (FIG. 1). The accuracy of this method 316 is within 1.degree. of
rotation and 1 mm of translation (except for translations that are
parallel to the viewing plane).
[0104] Implementation of the method 316 includes joint movement
visualization via the 3D model reconstruction with A-mode
ultrasound system, as described previously. The method 316 also
measures the vibrations produced to accurately localize the
vibrational center and to determine the cause of the vibrations'
occurrence.
[0105] Interpretation of the vibration and kinematic data is a
complicated task involving an in-depth understanding of data
acquisition, training data sets, signal analysis, as well as the
mechanical system characteristics. Vibrations generated through the
interactions of implant components, bones, and/or soft tissues
result from induced by driving force leading to a dynamic response.
The driving force may be associated with knee-ligament instability,
bone properties, and conditions. A normal intact knee joint 50
(FIG. 1) will have a distinct pattern of motion and vibrational
characteristics. Once degeneration or damage occurs to the knee
joint 50 (FIG. 1), both the kinematic and vibrational
characteristics change. This altering, for each type of injury or
degeneration, leads to distinct changes (or signature) that may be
captured by the kinematic and vibration methods described
herein.
[0106] FIGS. 28-34 illustrate a diagnostic system 320 configured to
perform the method 316 in accordance with one embodiment of the
present invention. The diagnostic system 320 includes the ID module
90 configured to diagnose soft tissue and bone injuries. For
example, a first patient having a normal knee joint and a second
patient having an anterior cruciate ligament deficit ("ACLD") may
exhibit a similar pattern of posterior femoral translation during
progressive knee flexion; however, the first and second patients
exhibit different axial rotation patterns of 30.degree. of knee
flexion. Accordingly, the ID module 90 includes three stages: (1) a
first stage that involves data analysis, (2) a second stage that
includes sending the data to a neural network for detecting an
injury, and (3) a third stage that classifies or determines
severity of a detected injury.
[0107] The first stage includes acquisition of kinematic feature
vectors, using multiple physiological measurements taken from the
patient while the patient moves the knee joint 50 (FIG. 1) through
a range of motion. Exemplary measurements may include, without
limitation, medial condyle anteroposterior ("MAP") motion and
lateral condyle anteroposterior ("LAP") motion. The LAP motion
pertains to the anterior-posterior ("AP") distance of the medial
and lateral condyle points 110, 114 (FIG. 1) relative to a tibia
geometric center. Other exemplary measurements may include lateral
shear interferometer ("LSI") measurement of the distance between
the lateral femoral condyle 114 (FIG. 1) and the lateral tibial
plateau 321 (FIG. 3), and medial shear interferometer ("MSI")
measurement of the distance between the medial, femoral condyle 310
(FIG. 1) and the medial tibial plateau 321 (FIG. 3) which includes
the superior/inferior ("S/I") distance of the lateral and medial
condoyle points 114, 110 (FIG. 1) to a tibial plane, as shown in
FIGS. 30A-30C.
[0108] Feature vectors may also include the femoral position with
respect to the tibia which is defined by three Euler angles 340,
three translation components with the vibrational signal 342, and
force data 344. Examples of these vectors are shown in FIGS.
31A-31C, respectively. FIG. 32 is a graphical representation 346
showing the average medial and lateral condyle positions during a
deep knee bend activity for the second patient having ACLD. The
feature vectors that are extracted from the kinematic and vibration
analyses are output to the neural network 98 (FIG. 6) for
determining the injury, as described in greater detail below.
[0109] FIG. 33 illustrates one embodiment of a neural network
classifier 322 having multiple binary outputs 323a, 323b, 323c,
323d, i.e., each output is either a "1" or "0," wherein the "1"
corresponding to "yes" and the "0" corresponding to "no." In this
neural network classifier 322, each output 323a, 323b, 323c, 323d
represents the response of the neural network 98 (FIG. 1) to a
particular injury type. For example, one output 323b may represent
the response for ACLD, wherein its state will be "1" if an ACL
injury is detected, and "0" otherwise. Obviously, the neural
network 98 (FIG. 1) and the classifier 322 may be significantly
more or less sophisticated, depending on the underlying model of
the joint in question.
[0110] FIG. 34 illustrates one embodiment of a construction 325 of
the neural network 98 (FIG. 6). The construction 325 includes
formulating a supervised classifier using a training set 324 of the
kinematic and vibration data corresponding to a dataset 326 of
normal and injured knee joints. The neural network 98 (FIG. 6) is
trained with the training set 324 of vectors, wherein each vector
consists of data (sound 328, kinematic 330, and force 332)
collected from the knee joint 50 (FIG. 1).
[0111] Fluoroscopy data 333 may be used to calculate the
kinematics. While fluoroscopy data 333 is highly accurate, it
requires the patient to remain within the small working volume of
the fluoroscope unit and subjects the patient to ionizing radiation
for a prolonged period of time. For most dynamic activities where
the joints are loaded, such as running, jumping, or other dynamic
activities, fluoroscopy is an unacceptable alternative. Therefore,
use of fluoroscopy data 333 is not required.
[0112] It should further be noted that electromyography ("EMG")
electrodes 337 (FIG. 6) may also be utilized as a data input for
the computer 96 (FIG. 6) and the neural network 98 (FIG. 6). In
this fashion, one or more EMG electrodes 337 (FIG. 6) are mounted
to the surface of the skin proximate the muscles adjacent the knee
joint 50 (FIG. 1) to monitor the electrical signal transmitted to
the muscles in order to provide relevant data of a muscle injury or
disorder.
[0113] Once the neural network 98 (FIG. 6) is trained, it may be
used to classify new cases and categorize an injury type using
these kinematic 330, vibration 328, and force 332 data. Those
skilled in the art will readily understand that the types and
classifications desired to be accommodated by the neural network 98
(FIG. 6) necessarily include training the neural network 98 (FIG.
6) on these very types of classifications. Exemplary types and
classifications of injuries to mammalian knee joints include,
without limitation, osteoarthritic conditions, soft tissue damage,
and abnormal growths. Likewise, the neural network 98 (FIG. 6)
needs to be trained to differentiate between and normal and
abnormal knee conditions.
[0114] Referring again to FIG. 29, for a new patient 326, acquired
vibrational, kinematic, and force features 328, 330, 332 the knee
joint 50 (FIG. 1) are compiled and input as a testing set 327 to
the trained neural network 334. The trained neural network 334 then
diagnoses the condition of the knee joint 50 (FIG. 1), and returns
one of the outputs 323a, 323b, 323c, 323d.
[0115] Although now shown, some embodiments of the method may be
adapted so that the testing set 327 is acquired outside of a
clinical setting. For example, a knee brace in accordance with an
embodiment of the present invention may be worn by a patient for an
extended period of time while performing normal activities. For
example, the patient may wear a device incorporating components of
at least one of the JKT module 86 (FIG. 6), the VA module 88 (FIG.
6), and the foot module 92 (FIG. 6) during activities that are not
reproducible in the office (for example, weight lifting, racquet
ball, etc.) and that elicit the pain or patient's symptoms. In some
embodiments, the patient may turn the device on immediately prior
to the activity and/or the patient may mark onset of the pain or
symptoms when it occurs. This enables analysis of the data range
from few seconds before the marked time to see what abnormal sounds
or joint kinematic were occurring.
[0116] Data may be stored on a portable hard drive (or any other
portable storage device) and then may be downloaded to exemplary
systems for analysis. The data can be wirelessly transmitted and
stored in a computer. It can also be stored with a miniature memory
drive if field data is desired. If the occurrence of the pain is
more random, some embodiments of the devices may continuously
acquire data. Although, continuously monitoring devices may require
a larger data storage capacity.
[0117] It is understood that while the exemplary embodiments have
been described herein with respect to the knee joint 50 (FIG. 1),
those skilled in the art will readily understand that the
aforementioned embodiments may be easily adapted to other joints of
the musculoskeletal system of a mammalian animal. For example,
embodiments may be adapted for use on hips, ankles, toes, spines,
shoulders, elbows, wrists, fingers, and temporomandibular
joints.
[0118] While the present invention has been illustrated by a
description of various embodiments, and while these embodiments
have been described in some detail, they are not intended to
restrict or in any way limit the scope of the disclosed invention.
Additional advantages and modifications will readily appear to
those skilled in the art. The various features of the present
invention may be used alone or in any combination depending on the
needs and preferences of the user. This has been a description of
the present invention, along with methods of practicing the present
invention as currently known.
* * * * *