DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claims Pending
Claims 1-19 are currently under examination.
Claim Objections
Claims 1-19 objected to because of the following informalities:
In Claim 1, “EI” (final line), should read -flexural rigidity (EI)- (Examiner's Note: Par. 4 of applicant’s spec.),
In Claim 12, “BM model” (line 1), should read -biomechanical model (BM)- (Examiner's Note: Par. 4 of applicant’s spec.),
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-19 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1 recites the limitation “the body part” in line 3. There is insufficient antecedent basis for this limitation in the claim. As such, the claim is indefinite as the applicant has failed to effectively define the metes and bounds of the claim. For examination purposes, this will be interpreted as -a body part-.
Claim 1 recites the limitation “the cortical bone of interest” in line 3. There is insufficient antecedent basis for this limitation in the claim. As such, the claim is indefinite as the applicant has failed to effectively define the metes and bounds of the claim. For examination purposes, this will be interpreted as -the cortical bone-.
Claim 1 recites the limitation “calculating EI, related output variables, or both”, which fails to effectively define the metes and bounds of the claim as it is unclear as to the manner in which the calculation is made. For example, what is the specific input that results in the calculation of EI? What are the “related output variables”, and from which equation or calculation are they output? As such, the claim is indefinite as the applicant has failed to effectively define the metes and bounds of the claim. For examination purposes, this will be interpreted as calculating flexural rigidity “using the formula EI=KbLb 3/48” (Par. 4 of applicant’s spec.).
Claim 3 recites the limitation “wherein the excitation stimulus is comprised of one or more swept sinusoids (“chirps”) with a frequency amplitude profile matched to the equipment to minimize spurious vibrations and to produce an adequate signal to noise ratio for the force and acceleration data”, which fails to effectively define the metes and bounds of the claim as it is unclear as to what is considered to be an “adequate” signal to noise ratio. As such, the claim is indefinite as the applicant has failed to effectively define the metes and bounds of the claim. For examination purposes, this will be interpreted as any ratio.
Claim 4 recites the limitation “a frequency amplitude profile matched to the equipment to minimize spurious vibrations and to produce an adequate signal to noise ratio for the force and acceleration data”, which fails to effectively define the metes and bounds of the claim as it is unclear as to what is considered to be an “adequate” signal to noise ratio. As such, the claim is indefinite as the applicant has failed to effectively define the metes and bounds of the claim. For examination purposes, this will be interpreted as any ratio.
The term “approximately” in claim 5 is a relative term which renders the claim indefinite. The term “approximately” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. For examination purposes, this will be interpreted as any level of mean and unit standard deviation.
The term “approximately” in claim 6 is a relative term which renders the claim indefinite. The term “approximately” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. For examination purposes, this will be interpreted as any level of mean and unit standard deviation.
Regarding claim 6, the phrase “can be” (line 2) renders the claim indefinite because it is unclear whether the limitation(s) following the phrase are part of the claimed invention. See MPEP § 2173.05(d). As such, the claim is indefinite as the applicant has failed to effectively define the metes and bounds of the claim. For examination purposes, “can be” will be interpreted as -is-.
Regarding claim 8, the phrase "such as" (line 3) renders the claim indefinite because it is unclear whether the limitations following the phrase are part of the claimed invention. See MPEP § 2173.05(d). As such, the claim is indefinite as the applicant has failed to effectively define the metes and bounds of the claim. For examination purposes, the limitations following the phrase will be interpreted as not required features of the claim.
Claim 10 recites the limitation “where the input to the model is the time domain displacement data xObs(t) calculated by twice integrating the observed time domain accelerance data”, which fails to effectively define the metes and bounds of the claim as it is unclear as to how the input to the model is “time domain displacement data xObs(t) calculated by twice integrating the observed time domain accelerance data”, when there is additional data that is present. For example, claim 7, which claim 10 is dependent on, recites “wherein the optimizer/solver minimizes a cost function comprised of (a) a weighted sum of squared residuals or a weighted sum of absolute values of residuals, and (b) a weighted sum of (i) one or more penalty functions, (ii) one or more Lagrange terms, or (iii) both one or more penalty functions and one or more Lagrange terms.”, and claim 1, which claim 7 is dependent on, recites “fitting a model to the processed data by applying an optimizer/solver that imposes one or more constraints on the estimated model parameters”, where Claims 1 and 7 each involve additional data types involved with the model. As such, the claim is indefinite as the applicant has failed to effectively define the metes and bounds of the claim. For examination purposes, “the input” will be interpreted as -an input-.
Claim 10 recites the limitation “the observed time domain accelerance data” in line 4. There is insufficient antecedent basis for this limitation in the claim. As such, the claim is indefinite as the applicant has failed to effectively define the metes and bounds of the claim. For examination purposes, this will be interpreted as -observed time domain accelerance data-.
Claim 10 recites the limitation “wherein the residuals are defined as the difference between the model's predicted time domain output force fpred(t) and the observed time domain output force data fobs(t), where the input to the model is the time domain displacement data xobs(t) calculated by twice integrating the observed time domain accelerance data”, which fails to effectively define the metes and bounds of the claim as it is unclear as to where “the output force fpred(t) and the observed time domain output force data fobs(t)” and “the observed time domain accelerance data” are acquired within the method. For example, claim 7, which claim 10 is dependent on, makes no indication as to the accelerance and force data. Claim 1, which claim 7 is dependent on, does recite “exciting the test probe unit with a stimulus while recording force f(t) and acceleration a(t)”. However, it is unclear as to where the claimed “the output force fpred(t) and the observed time domain output force data fobs(t)” and “the observed time domain accelerance data” originate. As such, the claim is indefinite as the applicant has failed to effectively define the metes and bounds of the claim. For examination purposes, the “the output force fpred(t) and the observed time domain output force data fobs(t)” will be interpreted as being the force data from claim 1. For examination purposes, “the observed time domain accelerance data” will be interpreted as accelerance from the acceleration data of claim 1.
Claim 11 recites the limitation “the input to the model is the time domain force data fobs(t).”, which fails to effectively define the metes and bounds of the claim as it is unclear as to how the input to the model is “the time domain force data fobs(t).”, when there is additional data that is present. For example, claim 7, which claim 11 is dependent on, recites “wherein the optimizer/solver minimizes a cost function comprised of (a) a weighted sum of squared residuals or a weighted sum of absolute values of residuals, and (b) a weighted sum of (i) one or more penalty functions, (ii) one or more Lagrange terms, or (iii) both one or more penalty functions and one or more Lagrange terms.”, and claim 1, which claim 7 is dependent on, recites “fitting a model to the processed data by applying an optimizer/solver that imposes one or more constraints on the estimated model parameters”, where Claims 1 and 7 each involve additional data types involved with the model. As such, the claim is indefinite as the applicant has failed to effectively define the metes and bounds of the claim. For examination purposes, “the input” will be interpreted as “an input”.
Claim 11 recites the limitation “the observed time domain accelerance data” in lines 3-4. There is insufficient antecedent basis for this limitation in the claim. As such, the claim is indefinite as the applicant has failed to effectively define the metes and bounds of the claim. For examination purposes, this will be interpreted as -observed time domain accelerance data-.
Claim 11 recites the limitation “wherein the residuals are defined as the difference between the model's predicted time domain output displacement xpred(t) and the observed time domain output displacement data xobs(t) calculated by twice integrating the observed time domain accelerance data, where the input to the model is the time domain force data fobs(t)”, which fails to effectively define the metes and bounds of the claim as it is unclear as to where “predicted time domain output displacement xpred(t) and the observed time domain output displacement data xobs(t) calculated by twice integrating the observed time domain accelerance data” and “the time domain force data fobs(t)” are acquired from. For example, claim 7, which claim 11 is dependent on, makes no indication as to the accelerance and force data. Claim 1, which claim 7 is dependent on, does recite “exciting the test probe unit with a stimulus while recording force f(t) and acceleration a(t)”. However, it is unclear as to where the claimed “the output force fpred(t) and the observed time domain output force data fobs(t)” and “the observed time domain accelerance data” originate. As such, the claim is indefinite as the applicant has failed to effectively define the metes and bounds of the claim. For examination purposes, “predicted time domain output displacement xpred(t) and the observed time domain output displacement data xobs(t) calculated by twice integrating the observed time domain accelerance data” will be interpreted as displacement from calculated from accelerance from the acceleration data of claim 1. For examination purposes, “the time domain force data fobs(t)” will be interpreted as being the force data from claim 1.
Claim 15 recites the limitation “the PZ model” in line 1. There is insufficient antecedent basis for this limitation in the claim. As such, the claim is indefinite as the applicant has failed to effectively define the metes and bounds of the claim. For examination purposes, this will be interpreted as -a PZ model-
Claim 15 recites the limitation “TF model” in line 1. There is insufficient antecedent basis for this limitation in the claim. As such, the claim is indefinite as the applicant has failed to effectively define the metes and bounds of the claim. For examination purposes, this will be interpreted as -a TF model-
Claim 17 recites the limitation “the range” in line 1. There is insufficient antecedent basis for this limitation in the claim. As such, the claim is indefinite as the applicant has failed to effectively define the metes and bounds of the claim. For examination purposes, this will be interpreted as -a range-.
Claim 18 recites the limitation “the sweet spot” in line 4. There is insufficient antecedent basis for this limitation in the claim. As such, the claim is indefinite as the applicant has failed to effectively define the metes and bounds of the claim. For examination purposes, this will be interpreted as -a sweet spot-.
Claim 19 recites the limitation “the sweet spot” in line 2. There is insufficient antecedent basis for this limitation in the claim. As such, the claim is indefinite as the applicant has failed to effectively define the metes and bounds of the claim. For examination purposes, this will be interpreted as -a sweet spot-.
The term “minimized” in claim 18 is a relative term which renders the claim indefinite. The term “minimized” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. For examination purposes, this will be interpreted as any level of reduction.
The term “minimized” in claim 19 is a relative term which renders the claim indefinite. The term “minimized” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. For examination purposes, this will be interpreted as any level of reduction.
Claims 2-19 are dependent on claim 1, and as such are also rejected.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The claims are generally directed towards a method for non-invasive measurement of mechanical properties of cortical bone. The method comprises positioning a body part on a mounting system, and placing a test probe against the body part. The test probe comprises one or more vibrator units, sensors, and controller. The test probe performs the functions of applying a static load to a test site, exciting the test probe with a stimulus, processing collected data, fitting a model to the processed data, and calculating El.
Claim(s) 1, 6, 12-14, and 16-19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Bowman (US Pub. No. 20190231250) hereinafter Bowman, and further in view of Bowman (US Pub. No. 20200146616) hereinafter Cotton (Examiner's Note: Referred to by the second named inventor of Cotton).
Regarding claim 1, Bowman discloses A method for non-invasive measurement of mechanical properties of a cortical bone of an individual (Abstract “Parametric model based computer implemented methods for determining the stiffness of a bone, systems for estimating the stiffness of a bone in vivo, and methods for determining the stiffness of a bone…”) (Par. 15, 48, 58 (method)), comprising:
placing a test probe unit against the region of the bone for determining the mechanical properties (Par. 48, “(1) positioning a force probe on the skin overlying the bone…”), wherein the test probe unit comprises one or more test probes (Abstract, “Parametric model based computer implemented methods for determining the stiffness of a bone, systems for estimating the stiffness of a bone in vivo, and methods for determining the stiffness of a bone”) (Par. 48, (force probe))(Par. 81 (system for estimating stiffness)) (Par. 81, “The mechanical force applicator 50 includes a force transducer 52 and a force probe 54 and is configured to apply static and oscillatory forces (F) to a region of the skin-bone complex…”) (Par. 58, “In embodiments of a parametric model based computer implemented method for determining the stiffness of a bone the method initially comprises applying a superposition of static and oscillatory forces…” “… controller comprises a processor and a storage medium containing computer readable and executable instructions which, when executed by the processor, cause the controller to automatically execute a series of analysis steps to determine the stiffness of the bone based on the measured oscillatory forces as functions of time F(t) and the resulting oscillatory accelerations as functions of time a(t).”), one or more vibrator units (Par. 81, “The mechanical force applicator 50 includes a force transducer 52 and a force probe 54 and is configured to apply static and oscillatory forces (F) to a region of the skin-bone complex. The static and oscillatory forces (F) applied to the skin-bone complex by the mechanical force applicator 50 include oscillatory forces (F) which in turn create oscillatory accelerations (a) of the skin-bone complex…”), one or more sensors (Par. 81, (transducer)) (Par. 48, “positioning a force probe on the skin overlying the bone, (2) applying both (i) a static force and (ii) oscillatory forces (F), (3) varying the frequency of the oscillatory forces (F) over a sub-range of the auditory frequency range, (4) measuring (i) the force applied through the force probe to the skin and (ii) the resulting acceleration of the force probe on the skin to obtain an oscillatory acceleration (a) of the skin-bone complex, and (5) calculating accelerance (i.e., acceleration divided by force) as a complex function of frequency, i.e., the complex accelerance frequency response function, A(f).”), multiple functions comprising (Par. 15, “ a system for estimating the stiffness of a bone in vivo is disclosed…”):
f) applying a static load to a test site (Par. 58, “In embodiments of a parametric model based computer implemented method for determining the stiffness of a bone the method initially comprises applying a superposition of static and oscillatory forces (F) over a range of frequencies (f), i.e. vibrations, to a region of the skin-bone complex of a bone of interest, e.g., the ulna”) (Par. 48, “(2) applying both (i) a static force and (ii) oscillatory forces (F)”) (Par. 15, “mechanical force applicator includes a force transducer and a force probe and is configured to apply a superposition of static and oscillatory forces (F) over a range of frequencies (f) to a region of the skin-bone complex”);
g) exciting the test probe unit with a stimulus while recording force f(t) and acceleration a(t) (Par. 15, “The mechanical force applicator includes a force transducer and a force probe and is configured to apply a superposition of static and oscillatory forces (F) over a range of frequencies (f) to a region of the skin-bone complex, wherein the oscillatory forces (F) excite oscillatory accelerations (a) of the skin-bone complex. The frequency response recorder is configured to measure and transmit to the data analyzer the oscillatory forces as functions of time F(t) and the oscillatory accelerations as functions of time a(t).”) (Par. 58, “…The oscillatory forces (F) applied to the skin-bone complex induce corresponding oscillatory accelerations (a) over the range of frequencies (f) of the skin-bone complex. Further, a data receiver receives measurement of the oscillatory forces as functions of time F(t) and the resulting oscillatory accelerations (a) as functions of time a(t).”) (Par. 48, (force probe));
h) processing the collected force and acceleration data (Par. 59, “…With reference to FIGS. 3 and 4, the controller, in accordance with the executable instructions on the storage medium containing computer readable and executable instructions, automatically determines the oscillatory acceleration (a) and oscillatory forces (F) as functions of frequency, a(f) and F(f) respectively by performing Fourier transformations to convert a(t) and F(t) to a(f) and F(f) respectively.”) (Par. 63, “he controller, in accordance with the executable instructions on the storage medium containing computer readable and executable instructions, automatically determines the oscillatory acceleration (a) and oscillatory forces (F) as functions of frequency, a(f) and F(f) respectively by performing Fourier transformations to convert a(t) and F(t) to a(f) and F(f) respectively for the shifted region”) (Par. 68, “Upon determination of the overall optimized data set, the stiffness of the bone can be determined. Additionally, in various embodiments, each of the individual optimized data sets may be used to determine the stiffness of the bone”);
j) calculating El, related output variables, or both (Par. 68, “Upon determination of the overall optimized data set, the stiffness of the bone can be determined. Additionally, in various embodiments, each of the individual optimized data sets may be used to determine the stiffness of the bone”) (Par. 69, “Additionally, in multiple embodiments, the determined stiffness of bone in the method is flexural rigidity, EI, and may be calculated based on the determined transverse bending stiffness 6 (K.sub.B) of the bone. Specifically, EI=K.sub.BL.sup.3/48, wherein L is the length of the bone.”).
Bowman highly suggests but fails to explicitly disclose positioning the body part of the individual containing the cortical bone of interest on a mounting system and applying restraints (Examiner's Note: Bowman fails to explicitly state the exact method step).
Bowman does teach in an exemplary embodiment positioning the body part of the individual containing the cortical bone of interest on a mounting system and applying restraints (Par. 81, “The bone positioning support 40 is configured to position and support the skin-bone complex in an orientation and position for measurement. The mechanical force applicator 50 includes a force transducer 52 and a force probe 54 and is configured to apply static and oscillatory forces (F) to a region of the skin-bone complex…”) (Par. 82, “In some embodiments the bone positioning support 40 includes a bone positioning harness 170. The bone positioning harness 170 is an adjustable and flexible but inelastic tensile sling….”).
Therefore, it would have been obvious to a person of ordinary skill in the art to modify the method of Bowman with an embodiment of Bowman to explicitly include positioning the body part of the individual containing the cortical bone of interest on a mounting system and applying restraints through the combination of embodiments as it would have yielded the predictable result of securing the body part at a desired position for measurement (Bowman (Par. 81)).
Modified Bowman fails to explicitly disclose a controller having one or more processors and a memory containing computer readable and executable instructions which, when executed by a processor, allows the controller to perform multiple functions. (Examiner's Note: The above indicated embodiment fails to explicitly state computer implementation for the entirety of the method)
However, Bowman does teach in an exemplary method a controller having one or more processors and a memory containing computer readable and executable instructions which, when executed by a processor, allows the controller to perform multiple functions (Par. 14, “The computer implemented method includes (1) applying a superposition of static and oscillatory forces (F) over a range of frequencies (f) to a region of a skin-bone complex thereby exciting oscillatory accelerations (a) over the range of frequencies (f) of the skin-bone complex; (2) receiving measurements of the oscillatory forces (F) as functions of time F(t) and the resulting oscillatory accelerations (a) as functions of time a(t) with a data receiver communicatively coupled to a controller including a processor and a storage medium containing computer readable and executable instructions…”) (Par. 58, “The controller comprises a processor and a storage medium containing computer readable and executable instructions which, when executed by the processor, cause the controller to automatically execute a series of analysis steps to determine the stiffness of the bone based on the measured oscillatory forces as functions of time F(t) and the resulting oscillatory accelerations as functions of time a(t).”).
Therefore, it would have been obvious to a person of ordinary skill in the art to modify the method of Bowman with that of Bowman to explicitly include a controller having one or more processors and a memory containing computer readable and executable instructions which, when executed by a processor, allows the controller to perform multiple functions through the combination of embodiments as it would have yielded the predictable result of explicitly implementing the method on a computational device (Bowman (Par. 14, 58)).
Modified Bowman fails to explicitly disclose fitting a model to the processed data by applying an optimizer/solver that imposes one or more constraints on the estimated model parameters.
However, Cotton teaches fitting a model to the processed data by applying an optimizer/solver that imposes one or more constraints on the estimated model parameters (Par. 54, “mechanical models may include 3-dimensional FEA for example, to provide patient-specific estimations of strength of the bone specimen…” “…allows a generated mechanical model to render estimations of strength of the bone specimen throughout the bone specimen…”) (Par. 48, “It will be appreciated that the initial assigned value for the elastic modulus may also be obtained, for example, from a look-up table or database based on the species of patient, the mass of the patient, the height or length of the patient, or other physiological attributes of the patient.”) (Par. 14 (patient specific E)).
Bowman and Cotton are considered to be analogous art to the claimed invention as they are involved with bone measurements.
Therefore, it would have been obvious to a person of ordinary skill in the art to modify the method of Bowman with that of Cotton to include fitting a model to the processed data by applying an optimizer/solver that imposes one or more constraints on the estimated model parameters through the combination of references as it would have yielded the predictable result of allowing for the assessment of bone parameters under differing conditions (Cotton (Par. 54)).
Regarding claim 6, modified Bowman fails to explicitly disclose the limitations of the claim.
However, Bowman does disclose wherein the processed data are further processed to calculate an observed impedance function Hobs(jw), which can be the complex stiffness frequency response function or the complex compliance frequency response function (Bowman (Par. 54, “Inverting the associated complex stiffness frequency response function, H(f), generates complex compliance frequency response function, Y(f).”))(Bowman (Par. 51, “Therefore, before the parametric model can be fitted, A(f) is first converted to a form in which the lowest power of frequency in the numerator polynomial is zero. Such a form is obtained by integrating A(f) twice with respect to frequency yielding a complex compliance frequency response function, Y(f)=x(f)/F(f) in which “x” is displacement. Such a form can also be obtained by inverting Y(f) to obtain the associated complex stiffness frequency response function, H(f)=F(f)/x(f).”)(Par. 52-56)).
(Examiner's Note: calculations interpreted as “Furthermore, H(jw) is a generalized impedance function that can be either the complex stiffness F(jw)/X(jw) or the complex compliance X(jw)/F(jw), where F(jw) is the Fourier transform of force f(t) and X(jw) is 1/(jw) 2 times the Fourier transform of acceleration a(t). In practice, H(jw) is often calculated using Fourier power spectral densities and its variants (see, for example, Vold et al., 1984).” (Par. 70 of applicants spec.))
However, Bowman does teach data normalized to be approximately zero mean and unit standard deviation (Bowman (Par. 99, “Ulnas were supported in the same orientation for MRTA and QMT stiffness tests. In QMT stiffness tests, repeated measurements of stiffness were collected until the internal coefficient of variation (standard deviation/mean) was less than or equal to 1.0% for five measurements taken consecutively.”)).
Therefore, it would have been obvious to a person of ordinary skill in the art to modify the method of Bowman and Cotton with that of Bowman to include wherein the processed data are further processed to calculate an observed impedance function Hobs(jw), which can be the complex stiffness frequency response function or the complex compliance frequency response function, which is then normalized to be approximately zero mean and unit standard deviation through the combination of embodiments as it would have yielded the predictable result of improving data quality.
Regarding claim 12, modified Bowman fails to explicitly disclose the limitations of the claim.
However, Cotton further teaches wherein the model is a BM model (Cotton (Par. 54, “mechanical models may include 3-dimensional FEA for example, to provide patient-specific estimations of strength of the bone specimen…” “…allows a generated mechanical model to render estimations of strength of the bone specimen throughout the bone specimen…”) (Par. 48, “It will be appreciated that the initial assigned value for the elastic modulus may also be obtained, for example, from a look-up table or database based on the species of patient, the mass of the patient, the height or length of the patient, or other physiological attributes of the patient.”) (Par. 14 (patient specific E))).
Therefore, it would have been obvious to a person of ordinary skill in the art to modify the method of Bowman and Cotton with that of Cotton to include wherein the model is a BM model for the reasoning as indicated in claim 1 above.
Regarding claim 13, modified Bowman fails to explicitly disclose the limitations of the claim.
However, Bowman does disclose wherein the model is a 6, 7, 8, 9, or 12 Parameter Model or a variant of the 6, 7, 8, 9, or 12 Parameter Model (Bowman (Par. 50 (7 parameter model))(Par. 52-56 (7 parameter model))).
Cotton further teaches wherein the model is a BM model (Cotton (Par. 54, “mechanical models may include 3-dimensional FEA for example, to provide patient-specific estimations of strength of the bone specimen…” “…allows a generated mechanical model to render estimations of strength of the bone specimen throughout the bone specimen…”) (Par. 48, “It will be appreciated that the initial assigned value for the elastic modulus may also be obtained, for example, from a look-up table or database based on the species of patient, the mass of the patient, the height or length of the patient, or other physiological attributes of the patient.”) (Par. 14 (patient specific E))).
Therefore, it would have been obvious to a person of ordinary skill in the art to modify the method of Bowman and Cotton with that of Bowman and Cotton to include wherein the BM model of Cotton is a 6, 7, 8, 9, or 12 Parameter BM Model or a variant of the 6, 7, 8, 9, or 12 Parameter BM Model through the combination of references for the reasoning as indicated in claim 1 above and it would have yielded the predictable result of factoring in additional features and improving overall accuracy (Bowman (Par. 50)).
Regarding claim 14, modified Bowman fails to explicitly disclose the limitations of the claim.
However, Bowman does disclose wherein the model is a finite element model of the body part that has been parameterized to 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or more parameters (Bowman (Par. 50 (7 parameter model))(Par. 52-56 (7 parameter model))).
Cotton further teaches wherein the model is a BM model (Cotton (Par. 54, “mechanical models may include 3-dimensional FEA for example, to provide patient-specific estimations of strength of the bone specimen…” “…allows a generated mechanical model to render estimations of strength of the bone specimen throughout the bone specimen…”) (Par. 48, “It will be appreciated that the initial assigned value for the elastic modulus may also be obtained, for example, from a look-up table or database based on the species of patient, the mass of the patient, the height or length of the patient, or other physiological attributes of the patient.”) (Par. 14 (patient specific E))).
Therefore, it would have been obvious to a person of ordinary skill in the art to modify the method of Bowman and Cotton with that of Bowman and Cotton to include wherein the BM model is a finite element model of the body part that has been parameterized to 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or more parameters through the combination of references for the reasoning as indicated in claim 1 above and it would have yielded the predictable result of factoring in additional features and improving overall accuracy (Bowman (Par. 50)).
Regarding claim 16, modified Bowman further discloses wherein the imposed constraints include at least one constraint selected from the group consisting of: minimum and maximum system gain, system stability, minimum and maximum damping/settling time, non-negativity of physical parameters (Bowman (Par. 50, “Specifically, the 7-parameter model accounts for mass of the skin 8 (M.sub.S), transverse bending stiffness of the skin 2 (K.sub.S), damping coefficient of the skin 12 (B.sub.S), mass of the bone 10 (M.sub.B), transverse bending stiffness of the bone 6 (K.sub.B), damping coefficient of the bone 14 (B.sub.B), and damping coefficient of the surrounding soft tissue 4 (B.sub.P)”)), minimum and maximum model parameter values, minimum and maximum peak frequencies, relative peak frequencies, minimum and maximum flexural rigidity, non-negativity of the quadratic radicals in Ks, and non-vanishing denominator in the quadratic formula for Ks (Bowman (Par. 50 (7 parameter model))(Par. 52-56 (7 parameter model))).
Regarding claim 17, modified Bowman fails to explicitly disclose the limitations of the claim.
However, Bowman does teach in an example wherein a limited number of subjects spanning the range of BMIs and muscularities are tested to determine approximate population norms for defining constraint bounds (Bowman (Par. 105, “The test specimens used for this system validation consisted of 20 fresh-frozen cadaveric human arms. To maximize the likelihood that the tested specimens would exhibit a wide range of EI values, cadaveric human arms from twelve small women and eight large men of various ages (women=66-90 yrs, men=48-96 yrs) and body mass indices (BMI) (women=13.7-22.9 kg/m.sup.2, men=25.0-39.7 kg/m.sup.2) were acquired.”) (Par. 103, 110-111(experimental results)).
Therefore, it would have been obvious to a person of ordinary skill in the art to modify the method of Bowman and Cotton with that of Bowman and Cotton to include wherein a limited number of subjects spanning the range of BMIs and muscularities are tested to determine approximate population norms for defining constraint bounds through the combination of references as it would have yielded the predictable result of validating the model and data (Bowman (Par. 103)).
Regarding claim 18, modified Bowman fails to explicitly disclose the limitations of the claim.
However, Bowman does teach in examples wherein (a) the subject is measured repeatedly at two or more points along one or more of a transit line in the transverse plane, a line in the longitudinal direction within the sagittal plane (Bowman (Par. 66, “For example, the superposition of static and oscillatory forces (F) over a range of frequencies (f) may be initially applied to a region of the skin-bone complex medial of the centerline of the ulna, then the static and oscillatory forces (F) over a range of frequencies (f) are applied to a shifted region lateral of the initial region of the skin-bone complex, then the static and oscillatory forces (F) over a range of frequencies (f) are applied to a further shifted region further lateral of the initial region of the skin-bone complex. The measure of conformity improves upon each further lateral shift of the application of the static and oscillatory forces (F) until the optimum location for data collection is passed by. When the optimum location for data collection is passed by, the measure of conformity will worsen. The optimized data set with respect to medial to lateral shifting of the region is represented by the best measure of conformity of the saved data sets”), different angles of the test probe relative to the cortical bone of interest and combinations therein (Bowman (Par. 79, “with reference to FIGS. 2 and 3, the threshold minimum and threshold maximum frequencies are selected such that the bone peak 20 of Y(f) and the skin peak 22 of Y(f) are contained within the frequency range enclosed by the threshold minimum frequency and the threshold maximum frequency. Typically, the bone peak 20 of Y(f) is centered at approximately 150-250 Hz and the skin peak of Y(f) is centered at approximately 500-800 Hz. In a further embodiment, the threshold minimum frequency is selected as the resonant frequency representing the bone peak and the threshold maximum frequency is selected as the resonant frequency representing the skin peak.) (Par. 80, “The static and oscillatory forces (F) are then applied to the shifted region and a revised stiffness of bone is generated along with a revised measure of conformity...”)) and (b) the results from the sweet spot, where the spurious modes of vibration are eliminated or minimized, are displayed and stored (Bowman (Par. 91, “n further embodiments of a system for estimating the stiffness of a bone in vivo, the processor is connected to a visual subsystem with a graphical user interface (GUI). ….”)) (Bowman (Par. 79, “with reference to FIGS. 2 and 3, the threshold minimum and threshold maximum frequencies are selected such that the bone peak 20 of Y(f) and the skin peak 22 of Y(f) are contained within the frequency range enclosed by the threshold minimum frequency and the threshold maximum frequency. Typically, the bone peak 20 of Y(f) is centered at approximately 150-250 Hz and the skin peak of Y(f) is centered at approximately 500-800 Hz. In a further embodiment, the threshold minimum frequency is selected as the resonant frequency representing the bone peak and the threshold maximum frequency is selected as the resonant frequency representing the skin peak.) (Par. 80, “The static and oscillatory forces (F) are then applied to the shifted region and a revised stiffness of bone is generated along with a revised measure of conformity...”)).
Therefore, it would have been obvious to a person of ordinary skill in the art to modify the method of Bowman and Cotton with that of Bowman to include wherein (a) the subject is measured repeatedly at two or more points along one or more of a transit line in the transverse plane, a line in the longitudinal direction within the sagittal plane, different angles of the test probe relative to the cortical bone of interest and combinations therein, and (b) the results from the sweet spot, where the spurious modes of vibration are eliminated or minimized, are displayed and stored through the combination of references as it would have yielded the predictable result of providing direct feedback to the user and acquiring measurement data from multiple points, optimizing the data (Bowman (Par. 66)).
Regarding claim 19, modified Bowman fails to explicitly disclose the limitations of the claim.
However, Bowman does teach in examples wherein (a) the subject is measured repeatedly at different points along a transit line in the transverse plane, (Bowman (Par. 66, “For example, the superposition of static and oscillatory forces (F) over a range of frequencies (f) may be initially applied to a region of the skin-bone complex medial of the centerline of the ulna, then the static and oscillatory forces (F) over a range of frequencies (f) are applied to a shifted region lateral of the initial region of the skin-bone complex, then the static and oscillatory forces (F) over a range of frequencies (f) are applied to a further shifted region further lateral of the initial region of the skin-bone complex. The measure of conformity improves upon each further lateral shift of the application of the static and oscillatory forces (F) until the optimum location for data collection is passed by. When the optimum location for data collection is passed by, the measure of conformity will worsen. The optimized data set with respect to medial to lateral shifting of the region is represented by the best measure of conformity of the saved data sets”))(Bowman (Par. 79, “with reference to FIGS. 2 and 3, the threshold minimum and threshold maximum frequencies are selected such that the bone peak 20 of Y(f) and the skin peak 22 of Y(f) are contained within the frequency range enclosed by the threshold minimum frequency and the threshold maximum frequency. Typically, the bone peak 20 of Y(f) is centered at approximately 150-250 Hz and the skin peak of Y(f) is centered at approximately 500-800 Hz. In a further embodiment, the threshold minimum frequency is selected as the resonant frequency representing the bone peak and the threshold maximum frequency is selected as the resonant frequency representing the skin peak.) (Par. 80, “The static and oscillatory forces (F) are then applied to the shifted region and a revised stiffness of bone is generated along with a revised measure of conformity...”)) and (b) the results from the sweet spot, where the spurious modes of vibration are eliminated or minimized, are displayed and stored (Bowman (Par. 91, “n further embodiments of a system for estimating the stiffness of a bone in vivo, the processor is connected to a visual subsystem with a graphical user interface (GUI). ….”)) (Bowman (Par. 79, “with reference to FIGS. 2 and 3, the threshold minimum and threshold maximum frequencies are selected such that the bone peak 20 of Y(f) and the skin peak 22 of Y(f) are contained within the frequency range enclosed by the threshold minimum frequency and the threshold maximum frequency. Typically, the bone peak 20 of Y(f) is centered at approximately 150-250 Hz and the skin peak of Y(f) is centered at approximately 500-800 Hz. In a further embodiment, the threshold minimum frequency is selected as the resonant frequency representing the bone peak and the threshold maximum frequency is selected as the resonant frequency representing the skin peak.) (Par. 80, “The static and oscillatory forces (F) are then applied to the shifted region and a revised stiffness of bone is generated along with a revised measure of conformity...”)).
Therefore, it would have been obvious to a person of ordinary skill in the art to modify the method of Bowman and Cotton with that of Bowman to include wherein (a) the subject is measured repeatedly at different points along a transit line in the transverse plane, and (b) the results from the sweet spot, where the spurious modes of vibration are eliminated or minimized, are displayed and stored through the combination of references as it would have yielded the predictable result of providing direct feedback to the user and acquiring measurement data from multiple points, optimizing the data (Bowman (Par. 66)).
Claim(s) 2 is/are rejected under 35 U.S.C. 103 as being unpatentable over Bowman in view of Cotton as applied to claim 1 above, and further in view of Dyer (US Pub. No. 20040098168) hereinafter Dyer.
Bowman and Cotton teach the method of claim 1 above.
Regarding claim 2, modified Bowman fails to explicitly disclose the limitations of the claim.
However, Dyer teaches wherein a dither signal is added to the static load to keep the vibration motor active throughout testing such that startup transients are avoided or minimized when the excitation stimulus begins (Par. 65, “FIG. 3.7 shows that vibration was controlled to below the low limit in two balance correction iterations the time required for the vibration data sampling, estimation, and control computation is evident by noting the time between the end of the first balance iteration and the start of the second (observable when the vibration again begins to decrease again just before one second). A portion of this time between balance weight positioning was allotted as a fixed delay to allow the transient vibration to settle.”) (Par. 167-169, “control must be "dithered" somehow to provide m independent correction vectors. The simplest way to accomplish this would be to. move the correction weights only one balance plane at a time (while recording the error signal vectors after each balance weight movement)…” “…To ensure that all error sensor output amplitudes decrease, all correction weights could be moved simultaneously…”).
Bowman, Cotton, and Dyer are considered to be analogous art to the claimed invention as they are involved with vibrational measurements.
Therefore, it would have been obvious to a person of ordinary skill in the art to modify the method of Bowman and Cotton with that of Dyer to include wherein a dither signal is added to the static load to keep the vibration motor active throughout testing such that startup transients are avoided or minimized when the excitation stimulus begins through the combination of references as error signals due to vibrations are a known issue with vibrational devices (Dyer (Par. 24)) and it would have yielded the predictable result of reducing error (Dyer (Par. 169)).
Claim(s) 3-5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Bowman in view of Cotton as applied to claim 1 above, and further in view of Krah (US Pub. No. 20080157893) hereinafter Krah.
Bowman and Cotton teach the method of claim 1 above.
Regarding claim 3, modified Bowman fails to explicitly disclose the limitations of the claim.
However, Bowman does disclose wherein the excitation stimulus is comprised of one or more swept sinusoids (“chirps”) (Bowman (Par. 75, “In various embodiments, the oscillatory forces (F) are applied over the excitation frequency range in a swept sine waveform, a pseudorandom waveform, a shaped random waveform, a chirp waveform, a burst waveform, a burst random waveform, a shaped burst random waveform, a white noise waveform, a pink noise waveform, or other standard waveforms known to one of ordinary skill in the art.”)).
Krah teaches a frequency amplitude profile matched to the equipment to minimize spurious vibrations and to produce an adequate signal to noise ratio for the force and acceleration data (Par. 123, “Because Vstim can create undesirable harmonics, especially if comprised of square waves, the demodulation waveform Vdem 816 can be a Gaussian sine wave in an otherwise DC signal…” “…Thus, mixing Vdem with that output signal can ensure optimal results.”)(Par. 135, “This tuning value may the lowest available tuning value (i.e., 0). At step 1002, the phase of the demodulation signal Vdem is adjusted so that it matches the phase of signal 810 (i.e., the signal output from the amplifier circuit). See FIG. 8a for more details regarding the demodulation signal. Adjusting the phase of the demodulation signal may assist in ensuring better noise rejection at signal mixer 804 and a higher result signal 824. It can be beneficial to adjust the phase of Vdem after every modification of the tuning value, because the tuning value causes different stimulation frequencies and different stimulation frequencies can cause different phases of signal 810....”).
Bowman, Cotton, and Krah are considered to be analogous art to the claimed invention as they are involved with vibrational measurements.
Therefore, it would have been obvious to a person of ordinary skill in the art to modify the method of Bowman and Cotton with that of Krah to include wherein the excitation stimulus of Bowman is comprised of one or more swept sinusoids (“chirps”) with a frequency amplitude profile matched to the equipment to minimize spurious vibrations and to produce an adequate signal to noise ratio for the force and acceleration data through the combination of references as differing waveforms are known in the art (Bowman (Par. 75)) and it would have yielded the predictable result of improving signal quality and reducing noise (Krah (Par. 123, 135)).
Regarding claim 4, modified Bowman fails to explicitly disclose the limitations of the claim.
However, Bowman does disclose wherein the excitation stimulus is a white, pink, or other noise signal that is uniform, Gaussian, or other shape (Bowman (Par. 75, “In various embodiments, the oscillatory forces (F) are applied over the excitation frequency range in a swept sine waveform, a pseudorandom waveform, a shaped random waveform, a chirp waveform, a burst waveform, a burst random waveform, a shaped burst random waveform, a white noise waveform, a pink noise waveform, or other standard waveforms known to one of ordinary skill in the art.”)).
Krah teaches a frequency amplitude profile matched to the equipment to minimize spurious vibrations and to produce an adequate signal to noise ratio for the force and acceleration data (Par. 123, “Because Vstim can create undesirable harmonics, especially if comprised of square waves, the demodulation waveform Vdem 816 can be a Gaussian sine wave in an otherwise DC signal…” “…Thus, mixing Vdem with that output signal can ensure optimal results.”)(Par. 135, “This tuning value may the lowest available tuning value (i.e., 0). At step 1002, the phase of the demodulation signal Vdem is adjusted so that it matches the phase of signal 810 (i.e., the signal output from the amplifier circuit). See FIG. 8a for more details regarding the demodulation signal. Adjusting the phase of the demodulation signal may assist in ensuring better noise rejection at signal mixer 804 and a higher result signal 824. It can be beneficial to adjust the phase of Vdem after every modification of the tuning value, because the tuning value causes different stimulation frequencies and different stimulation frequencies can cause different phases of signal 810....”).
Bowman, Cotton, and Krah are considered to be analogous art to the claimed invention as they are involved with vibrational measurements.
Therefore, it would have been obvious to a person of ordinary skill in the art to modify the method of Bowman and Cotton with that of Krah to include wherein the excitation stimulus of Bowman is a white, pink, or other noise signal that is uniform, Gaussian, or other shape, with a frequency amplitude profile matched to the equipment to minimize spurious vibrations and to produce an adequate signal to noise ratio for the force and acceleration data through the combination of references as differing waveforms are known in the art (Bowman (Par. 75)) and it would have yielded the predictable result of improving signal quality and reducing noise (Krah (Par. 123, 135)).
Regarding claim 5, modified Bowman fails to explicitly disclose the limitations of the claim.
However, Bowman does teach wherein the processed data are conditioned to be approximately zero mean and unit standard deviation (Bowman (Par. 99, “Ulnas were supported in the same orientation for MRTA and QMT stiffness tests. In QMT stiffness tests, repeated measurements of stiffness were collected until the internal coefficient of variation (standard deviation/mean) was less than or equal to 1.0% for five measurements taken consecutively.”)).
Krah teaches wherein the processed data are data that have been trimmed to remove unwanted transients (Par. 83-86 (band-pass filter)).
Bowman, Cotton, and Krah are considered to be analogous art to the claimed invention as they are involved with vibrational measurements.
Therefore, it would have been obvious to a person of ordinary skill in the art to modify the method of Bowman and Cotton with that of Bowman and Krah to include wherein the processed data are data that have been trimmed to remove unwanted transients and wherein the processed data are conditioned to be approximately zero mean and unit standard deviation through the combination of references as it would have yielded the predictable result of improving data quality and reducing noise.
Claim(s) 7-11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Bowman in view of Cotton as applied to claim 1 above, and further in view of Dimarogonas (US Pat. No. 5836876) hereinafter Dimarogonas.
Bowman and Cotton teach the method of claim 1 above.
Regarding claim 7, modified Bowman fails to explicitly disclose the limitations of the claim.
Bowman does teach residuals ( Bowman (Par. 54, “Inverting the associated complex stiffness frequency response function, H(f), generates complex compliance frequency response function, Y(f).”))(Bowman (Par. 51, “Therefore, before the parametric model can be fitted, A(f) is first converted to a form in which the lowest power of frequency in the numerator polynomial is zero. Such a form is obtained by integrating A(f) twice with respect to frequency yielding a complex compliance frequency response function, Y(f)=x(f)/F(f) in which “x” is displacement. Such a form can also be obtained by inverting Y(f) to obtain the associated complex stiffness frequency response function, H(f)=F(f)/x(f).”)(Par. 52-56)).
However, Dimarogonas teaches wherein the optimizer/solver minimizes a cost function comprised of (a) a weighted sum of squared residuals or a weighted sum of absolute values of residuals, and (b) a weighted sum of (i) one or more penalty functions, (ii) one or more Lagrange terms, or (iii) both one or more penalty functions and one or more Lagrange terms (Col. 10-11, lines 58-6, “In the second do-loop, the Newton-Raphson method is again used; however, this time the modal damping factor, natural frequency and maximum amplitude are each varied and a separate value for the error and the change in error with respect to the change in each of the three parameters is calculated. The parameters are varied until the sum of the squares of the differences of the errors is minimized...”).
Bowman, Cotton, and Dimarogonas are considered to be analogous art to the claimed invention as they are involved with vibrational measurements.
Therefore, it would have been obvious to a person of ordinary skill in the art to modify the method of Bowman and Cotton with that of Dimarogonas to include wherein the optimizer/solver minimizes a cost function comprised of (a) a weighted sum of squared residuals or a weighted sum of absolute values of residuals, and (b) a weighted sum of (i) one or more penalty functions, (ii) one or more Lagrange terms, or (iii) both one or more penalty functions and one or more Lagrange terms through the combination of references as it would have yielded the predictable result of improving measurement accuracy (Dimarogonas (Col. 10-11, lines 58-6)).
Regarding claim 8, modified Bowman fails to explicitly disclose the limitations of the claim.
However, Dimarogonas further teaches wherein the optimizer/solver is an optimizer/solver capable of minimizing or maximizing nonlinear cost functions subject to one or more constraints (Col. 10-11, lines 58-6, “In the second do-loop, the Newton-Raphson method is again used; however, this time the modal damping factor, natural frequency and maximum amplitude are each varied and a separate value for the error and the change in error with respect to the change in each of the three parameters is calculated. The parameters are varied until the sum of the squares of the differences of the errors is minimized...”).
Therefore, it would have been obvious to a person of ordinary skill in the art to modify the method of Bowman, Cotton, and Dimarogonas with that of Dimarogonas to include wherein the optimizer/solver is an optimizer/solver capable of minimizing or maximizing nonlinear cost functions subject to one or more constraints, such as a Levenberg-Marquardt optimizer/solver, a Nelder-Mead simplex optimizer/solver, a conjugant gradients optimizer/solver, a Gauss-Newton optimizer/solver, a Broyden-Fletcher-Goldfarb-Shanno (BFGS) optimizer/solver, a Davidon-Fletcher-Powell (DFP) optimizer/solver, a steepest descent optimizer/solver, a bisection optimizer/solver, and, when the constraints are only linear, a quadratic program solver through the combination of references as it would have yielded the predictable result of improving measurement accuracy (Dimarogonas (Col. 10-11, lines 58-6)).
Regarding claim 9, modified Bowman fails to explicitly disclose the limitations of the claim.
However, Bowman does teach in an example wherein the residuals are defined as the complex valued difference between the model's predicted complex valued frequency response function Hpred(jw) and the observed complex valued frequency response function Hobs(jw) (Bowman (Par. 113, “fit a parametric mathematical model to Y(f) to obtain a first set of parameters of the parametric mathematical model, including the stiffness of the bone (K.sub.B), (v) fit the parametric mathematical model to H(f) to obtain a second set of parameters of the parametric mathematical model, including the stiffness of the bone (K.sub.B), (vi) determine discrepancies between the first set of parameters and the second set of parameters as a measure of conformity thereof to the parametric mathematical model, and (vii) save the measure of conformity, the first set of parameters, and the second set of parameters as a data set.”)) (Bowman (Par. 54, “Inverting the associated complex stiffness frequency response function, H(f), generates complex compliance frequency response function, Y(f).”))(Bowman (Par. 51, “Therefore, before the parametric model can be fitted, A(f) is first converted to a form in which the lowest power of frequency in the numerator polynomial is zero. Such a form is obtained by integrating A(f) twice with respect to frequency yielding a complex compliance frequency response function, Y(f)=x(f)/F(f) in which “x” is displacement. Such a form can also be obtained by inverting Y(f) to obtain the associated complex stiffness frequency response function, H(f)=F(f)/x(f).”)(Par. 52-56)).
Therefore, it would have been obvious to a person of ordinary skill in the art to modify the method of Bowman, Cotton, and Dimarogonas with that of Bowman to include wherein the residuals are defined as the complex valued difference between the model's predicted complex valued frequency response function Hpred(jw) and the observed complex valued frequency response function Hobs(jw) through the combination of embodiments as it would have yielded the predictable result of monitoring for discrepancies between parameters (Bowman (Par. 113)).
Regarding claim 10, modified Bowman further discloses wherein the residuals are defined as the difference between the model's predicted time domain output force fpred(t) and the observed time domain output force data fobs(t) (Bowman (Par. 59, “In embodiments Y(f) and H(f) are determined by reducing a(f) and F(f) to the complex accelerance frequency response function A(f) and integrating A(f) twice in accordance with the mathematical manipulation previously discussed. Additionally, the controller automatically fits a parametric mathematical model to Y(f) to obtain a first set of parameters of the parametric mathematical model, including the stiffness of the bone (K.sub.B), as well as fits the parametric mathematical model to H(f) to obtain a second set of parameters of the parametric mathematical model, including the stiffness of the bone (K.sub.B). The parametric mathematical model may also be as previously discussed. The controller further automatically determines discrepancies between the first set of parameters and the second set of parameters as a measure of conformity thereof to the parametric mathematical model and saves the measure of conformity, the first set of parameters, and the second set of parameters as a data set..”) (Par. 63, “In embodiments Y(f) and H(f) are determined by reducing a(f) and F(f) to the complex accelerance frequency response function A(f) and integrating A(f) twice in accordance with the mathematical manipulation previously discussed…”)), where the input to the model is the time domain displacement data xobs(t) calculated by twice integrating the observed time domain accelerance data (Bowman (Par. 59, “In embodiments Y(f) and H(f) are determined by reducing a(f) and F(f) to the complex accelerance frequency response function A(f) and integrating A(f) twice in accordance with the mathematical manipulation previously discussed. Additionally, the controller automatically fits a parametric mathematical model to Y(f) to obtain a first set of parameters of the parametric mathematical model, including the stiffness of the bone (K.sub.B), as well as fits the parametric mathematical model to H(f) to obtain a second set of parameters of the parametric mathematical model, including the stiffness of the bone (K.sub.B). The parametric mathematical model may also be as previously discussed. The controller further automatically determines discrepancies between the first set of parameters and the second set of parameters as a measure of conformity thereof to the parametric mathematical model and saves the measure of conformity, the first set of parameters, and the second set of parameters as a data set..”) (Par. 63, “In embodiments Y(f) and H(f) are determined by reducing a(f) and F(f) to the complex accelerance frequency response function A(f) and integrating A(f) twice in accordance with the mathematical manipulation previously discussed…”)).
Regarding claim 11, modified Bowman further discloses wherein the residuals are defined as the difference between the model's predicted time domain output displacement xpred(t) and the observed time domain output displacement data xobs(t) calculated by twice integrating the observed time domain accelerance data (Bowman (Par. 59, “In embodiments Y(f) and H(f) are determined by reducing a(f) and F(f) to the complex accelerance frequency response function A(f) and integrating A(f) twice in accordance with the mathematical manipulation previously discussed. Additionally, the controller automatically fits a parametric mathematical model to Y(f) to obtain a first set of parameters of the parametric mathematical model, including the stiffness of the bone (K.sub.B), as well as fits the parametric mathematical model to H(f) to obtain a second set of parameters of the parametric mathematical model, including the stiffness of the bone (K.sub.B). The parametric mathematical model may also be as previously discussed. The controller further automatically determines discrepancies between the first set of parameters and the second set of parameters as a measure of conformity thereof to the parametric mathematical model and saves the measure of conformity, the first set of parameters, and the second set of parameters as a data set..”) (Par. 63, “In embodiments Y(f) and H(f) are determined by reducing a(f) and F(f) to the complex accelerance frequency response function A(f) and integrating A(f) twice in accordance with the mathematical manipulation previously discussed…”)), where the input to the model is the time domain force data fobs(t) (Bowman (Par. 59, “In embodiments Y(f) and H(f) are determined by reducing a(f) and F(f) to the complex accelerance frequency response function A(f) and integrating A(f) twice in accordance with the mathematical manipulation previously discussed. Additionally, the controller automatically fits a parametric mathematical model to Y(f) to obtain a first set of parameters of the parametric mathematical model, including the stiffness of the bone (K.sub.B), as well as fits the parametric mathematical model to H(f) to obtain a second set of parameters of the parametric mathematical model, including the stiffness of the bone (K.sub.B). The parametric mathematical model may also be as previously discussed. The controller further automatically determines discrepancies between the first set of parameters and the second set of parameters as a measure of conformity thereof to the parametric mathematical model and saves the measure of conformity, the first set of parameters, and the second set of parameters as a data set..”) (Par. 63, “In embodiments Y(f) and H(f) are determined by reducing a(f) and F(f) to the complex accelerance frequency response function A(f) and integrating A(f) twice in accordance with the mathematical manipulation previously discussed…”)).
Claim(s) 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Bowman in view of Cotton as applied to claim 1 above, and further in view of Luo (US Pub. No. 20050197576) hereinafter Luo.
Bowman and Cotton teach the method of claim 1 above.
Regarding claim 15, modified Bowman fails to explicitly disclose the limitations of the claim.
However, Luo teaches wherein the model is the PZ model or TF model (Par. 46, “computation of one or more of said quantities BMD, bone strength, bone fracture risk, bone architecture and bone quality may be derived using at least one parameter as may be derived from the acoustic bone transfer function (in either the frequency and time-domains, or in both)…”) (Par. 53, “In this case, an overall transfer function is derived relating the input waveform to the received (reflected) waveform. The transfer function depends on the acoustic properties and thicknesses associated with the soft tissue, cortical bone and trabecular bone, respectively…”).
(Examiner's Note: PZ and TF models interpreted as indicated in Par. 3 of the applicant’s spec. “The poles and zeros of a generalized transfer function PZ(jw) (the PZ model) are fit to H(jw) in some embodiments of MRTA (for example, by using a system analyzer such as the HP3562A), while in other embodiments the coefficients of a generalized transfer function TF(jw) (the TF model)…”)
Bowman, Cotton, and Luo are considered to be analogous art to the claimed invention as they are involved with Bone measurements.
Therefore, it would have been obvious to a person of ordinary skill in the art to modify the method of Bowman and Cotton with that of Luo to include wherein the model is the PZ model or TF model through the combination of references as differing analysis types are known in the art (Luo (Par. 46)) and it would have yielded the predictable result of improving model accuracy by factoring in additional parameters (Luo (Par. 46)).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure: Mueller (US Pub. No. 20200249069) and Boelitz (US Pub. No. 20030150961).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ARI SINGH KANE PADDA whose telephone number is (571)272-7228. The examiner can normally be reached Monday - Friday 8:00 am - 5:00 pm.
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/ARI S PADDA/Examiner, Art Unit 3791
/JASON M SIMS/Supervisory Patent Examiner, Art Unit 3791
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