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 .
Drawings
The drawings are objected to because, Fig. 10 consists of a flow chart of numbers and empty boxes. The illustrations are not descriptive to the claimed invention as provided. The drawings are objected to because Fig. 10 is supposed to be a flowchart that depicts sequence of steps associated with the claimed invention. The flowchart does not provide enough information to understand the associated invention without having to reference the disclosure.
Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Specification
The abstract of the disclosure is objected to because legalese, claim language is used. A corrected abstract of the disclosure is required and must be presented on a separate sheet, apart from any other text. See MPEP § 608.01(b).
Claim Objections
Claims 4 and 23 are objected to because of the following informalities:
Claim 4 limitation “…course at at least two…” should recite “…course at least two…”.
Claim 23 is written as an independent claim that depends on claim 1 limitations. Claim 23 are best written as independent claims with the necessary claim limitations from claim 22. Appropriate correction is required.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-15,17,22-23,25 and 27 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Claim 27 is rejected under 35 U.S.C. 101 because “a computer-readable medium” should be “a non-transitory computer-readable recording medium”. Appropriate correction is required.
Independent claim 1 recites, for example, the following abstract idea: “…classifying a characteristic of the brain pressure…”, falls within mental process. There is no specific machine or device that is not known or generic recited in the claim limitations, see MPEP § 2106.05(b). The limitations have no specifics to the algorithmic foundation or dimensionality associated with the input characteristic and as such can be considered computations that can be performed in the mind using visual inspection or simple pen and paper. Further, limitations “…receiving data…” and “…outputting the classified…” are considered extra solution activity recited at a high level of generality with no specific machine or device disclosed that is not generic or known to perform the limitations.
The judicial exceptions are not integrated into a “practical application” as defined by the Subject Matter Eligibility Analysis documented in Federal Register 84(4), issued on 07 January 2019, and MPEP § 2106. The limitation of “…computer-implemented method…” in claim 1, simply represents implementing the abstract ideas with a computer. MPEP § 2106.05(f) notes that “using a computer as a tool to perform the abstract idea” is not sufficient to integrate a judicial exception into a practical application as interpreted by the court(s). Gottschalk v. Benson, 409 U.S. 63, 175 USPQ 673 (1972) “held that simply implementing a mathematical principle on a physical machine, namely a computer, was not a patentable application of that principle and Intellectual Ventures LLC v. Symantec Corp., 838 F.3d 1307, 1318 (Fed. Cir. 2016) established that mental processes encompass acts which, absent anything beyond generic computer components, may be “performed by a human, mentally or with pen and paper.” Intellectual Ventures additionally established that if a claim, under its broadest reasonable interpretation, covers performance in the mind but for the recitation of generic computer components, then it is still in the mental processes category of abstract ideas unless the step(s) cannot be practically performed in the mind. Therefore, a positive recitation of the associated computer would not necessarily result in patent eligible subject matter.
Independent claims 22 and 27 recite similar limitations of claim 1 and are rejected under the same rationale.
The dependent claims 2-15,17, 23 and 25 do not sufficiently link the subject matter to a practical application or recite element(s) which constitute significantly more than the abstract ideas identified. The depending claims are directed to additional limitations which encompass abstract ideas consistent with those identified above that are well-understood, routine and/or conventional activity. Further, dependent claims 2-15,17, 23 and 25 merely include limitations that either further define the abstract idea (and thus don’t make the abstract idea any less abstract) or amount to no more than generally linking the use of the abstract idea to a particular technological environment or field of use because they’re merely incidental or token additions to the claims that do not alter or affect how the process steps are performed.
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 14-15, 17 and 23 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 14, limitation “…the time course of the time-of-flight values in a segment” is unclear the connection to “the at least one segment” of claim 13. It is unclear if the segment in claim 14 are the same or different from that of claim 13.
Claim 15 recites the limitation "the maximum amplitudes" in line 2. There is insufficient antecedent basis for this limitation in the claim. Further, it is unclear the connection(s) of the dominant frequency component, further frequency components and evaluation of frequencies. It is unclear the distinctions of the various frequencies being utilized for the comparisons. It is unclear how or where the frequency information is obtained with relation to the quality criterion. The metes and bounds of the claim overall is unclear.
Claim 17, the n time-of flight-curves and time-of-flight value are unclear the connection/correlation with the representative curve and time-of-flight values of claim 1.
Regarding claim 23, it is unclear if the skull cross-section is the same or different from that of claim 22.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-13, 15, 17, 22-23 and 25 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Ragauskas et. al. (U.S. 5388583, February 14, 1995)(hereinafter, “Ragauskas”).
Regarding Claim 1, Ragauskas teaches: A computer-implemented method for classifying a brain pressure (“With reference to FIGS. 13a, 13b, 14, 15, and 16, a more detailed view of a system and method in accordance with the invention to measure and derive a value of a characteristic of the intracranium medium is shown.”), the method comprising:
receiving data comprising time-of-flight values, which are based on time-of-flight values measured at successive time points for one or more ultrasound signals through a cross-section of a skull (“At 64 the time for the acoustic pulse to traverse the axis or path in the brain is determined using a transit travel time measuring technique. The transit travel time, .tau.(t), then includes the variations encountered along the travel path in the brain.”; “Transit time or travel time, pulses or signals, as such terms are used herein thus include those signals as detected and received with the embodiments as long as such signals include detectable variations attributable to time-dependent changes in a physical body such as the intracranial medium.”);
classifying a characteristic of the brain pressure by means of one or more features of a representative curve of a time course of the time-of-flight values to obtain a classified characteristic of the brain pressure (“With reference to FIGS. 1-3 a system 20 is shown for deriving an indication of one or more dynamic characteristics of the intracranium medium 22.”;“The curves 82.1-82.3 in FIG. 11 illustrate the dependency of intracranium brain pressure P.sub.IC as a function of brain volume for different average pressures P.sub.0. At the higher brain pressures the brain volume remains substantially constant. The measurements of the variations in the acoustic travel times depend upon the changes in the brain pressure .DELTA..sub.P along the acoustic path.”; “FIG. 13b is illustrative of the averaging effect obtained by alternating the direction of the travel time measurements with the reversal switch 118. At 131.1 is a curve of each of the actual measurements of the velocity .DELTA..sub.C (t) in the opposite directions, while curve 131.2 shows the effect of averaging the measurements in curve 131.1.”); and
outputting the classified characteristic of the brain pressure (“With reference to FIGS. 1-3 a system 20 is shown for deriving an indication of one or more dynamic characteristics of the intracranium medium 22…The characteristic can be the time dependence of the intracranium pressure of brain tissue such as at 24 in FIGS. 4-6…”; “…the pressure of the brain tissue at 98 and the time dependency of the width of the spinal fluid ventricle at 100 can be obtained. These signals can then be indicated at 102 such as by displaying them on a video display or on a chart recorder or recorded in memory for further analysis or future display.”).
Regarding Claim 2, Ragauskas teaches the claim limitations as noted above.
Ragauskas further teaches: wherein the time course of the time- of-flight values correlates to a time course of the brain pressure within the skull (“These Figures show how the changes in the brain pressure, P.sub.IC, affect the velocities, c, and thus the travel times, .tau., of acoustic pulses along paths, d.sub.A, d.sub.B, d.sub.C, corresponding to paths 38, 40 and 42 in FIG. 3.”. see Fig. 3).
Regarding Claim 3, Ragauskas teaches the claim limitations as noted above.
Ragauskas further teaches: wherein the time course of the time-of-flight values comprises a plurality of peaks, which each correlate to an increase and a decrease of the brain pressure during a systolic and a diastolic phase (“In FIG. 10a, which shows the velocities, c.sub.t, curves 79.1, of acoustic pulses through primarily brain tissue, the slopes of the curves 79 1, c.sup.(i) during systolic events is higher than for curves, c.sup.(j), during diastolic events. The travel times .tau. vary correspondingly.”; “In FIG. 10b the acoustic velocity curve 79.2 is a combination of the velocity through brain tissue, segment 80.1, a basal artery having a diameter D.sub.CBA, segment 80.2, and another brain tissue segment 80.3. During a systolic event the slopes of the segments 80.1 and 80.3 are different from those during a diastolic event.”).
Regarding Claim 4, Ragauskas teaches the claim limitations as noted above.
Ragauskas further teaches: wherein a change between time-of-flight values in the time course at least two successive time points correlates directly to a change of the brain pressure at the at least two successive time points (“These Figures show how the changes in the brain pressure, P.sub.IC, affect the velocities, c, and thus the travel times, .tau., of acoustic pulses along paths, d.sub.A, d.sub.B, d.sub.C, corresponding to paths 38, 40 and 42 in FIG. 3.”. see Fig. 3).
Regarding Claim 5, Ragauskas teaches the claim limitations as noted above.
wherein the classified characteristic of the brain pressure indicates a normal brain pressure, or indicates an abnormal brain pressure (“The curves 82.1-82.3 in FIG. 11 illustrate the dependency of intracranium brain pressure P.sub.IC as a function of brain volume for different average pressures P.sub.0. At the higher brain pressures the brain volume remains substantially constant. The measurements of the variations in the acoustic travel times depend upon the changes in the brain pressure .DELTA..sub.P along the acoustic path.”. see Fig. 11)
Regarding Claim 6, Ragauskas teaches the claim limitations as noted above.
Ragauskas further teaches: wherein the representative curve comprises at least one characteristic peak (“With reference to FIGS. 1-3 a system 20 is shown for deriving an indication of one or more dynamic characteristics of the intracranium medium 22.”;“The curves 82.1-82.3 in FIG. 11 illustrate the dependency of intracranium brain pressure P.sub.IC as a function of brain volume for different average pressures P.sub.0. At the higher brain pressures the brain volume remains substantially constant. The measurements of the variations in the acoustic travel times depend upon the changes in the brain pressure .DELTA..sub.P along the acoustic path.”; “FIG. 13b is illustrative of the averaging effect obtained by alternating the direction of the travel time measurements with the reversal switch 118. At 131.1 is a curve of each of the actual measurements of the velocity .DELTA..sub.C (t) in the opposite directions, while curve 131.2 shows the effect of averaging the measurements in curve 131.1.”).
Regarding Claim 7, Ragauskas teaches the claim limitations as noted above.
Ragauskas further teaches: wherein the characteristic of the brain pressure is determined by the computer by extracting the one or more features of the curve of the at least one characteristic peak (“With reference to FIGS. 1-3 a system 20 is shown for deriving an indication of one or more dynamic characteristics of the intracranium medium 22.”;“The curves 82.1-82.3 in FIG. 11 illustrate the dependency of intracranium brain pressure P.sub.IC as a function of brain volume for different average pressures P.sub.0. At the higher brain pressures the brain volume remains substantially constant. The measurements of the variations in the acoustic travel times depend upon the changes in the brain pressure .DELTA..sub.P along the acoustic path.”; “FIG. 13b is illustrative of the averaging effect obtained by alternating the direction of the travel time measurements with the reversal switch 118. At 131.1 is a curve of each of the actual measurements of the velocity .DELTA..sub.C (t) in the opposite directions, while curve 131.2 shows the effect of averaging the measurements in curve 131.1.”. See Fig. 13).
Regarding Claim 8, Ragauskas teaches the claim limitations as noted above.
Ragauskas further teaches: wherein a first characteristic feature of the one or more features is a peak width of the at least one characteristic peak at a certain percentage of the maximum amplitude of the at least one characteristic peak (“Because of the brief nature of the travel time pulses on line 132, they contain many higher harmonics. These harmonics extend very high in frequency and their amplitudes fall off with frequency at a typical rate determined by the function sinx/z until the amplitudes approach a first minimum level at about one gigahertz if the width of pulses 126 on line 132, see FIG. 16, is about one nanosecond.”; “The travel time signals on line 132 are applied to a mixer 136 to amplitude modulate a coherent frequency signal f.sub.1 of the order of about 8 MHz on line 138 from a frequency signal generator 140. The output 142 from mixer 136 then includes the higher harmonics 143.1-143.J, but centered at elevated frequencies at intervals separated by whole integer multiples of the average frequency f.sub..phi..”).
Regarding Claim 9, Ragauskas teaches the claim limitations as noted above.
Ragauskas further teaches: wherein a second characteristic feature of the one or more features is a similarity of the curve shape of the at least one characteristic peak to a synthetic function (“With reference to FIGS. 1-3 a system 20 is shown for deriving an indication of one or more dynamic characteristics of the intracranium medium 22.”;“The curves 82.1-82.3 in FIG. 11 illustrate the dependency of intracranium brain pressure P.sub.IC as a function of brain volume for different average pressures P.sub.0. At the higher brain pressures the brain volume remains substantially constant. The measurements of the variations in the acoustic travel times depend upon the changes in the brain pressure .DELTA..sub.P along the acoustic path.”; “FIG. 13b is illustrative of the averaging effect obtained by alternating the direction of the travel time measurements with the reversal switch 118. At 131.1 is a curve of each of the actual measurements of the velocity .DELTA..sub.C (t) in the opposite directions, while curve 131.2 shows the effect of averaging the measurements in curve 131.1.”. See Fig. 13).
Regarding Claim 10, Ragauskas teaches the claim limitations as noted above.
Ragauskas further teaches: wherein the at least one characteristic peak is characteristic for a plurality of peaks in at least one time segment of the time course of the time-of-flight values (“With reference to FIGS. 1-3 a system 20 is shown for deriving an indication of one or more dynamic characteristics of the intracranium medium 22.”;“The curves 82.1-82.3 in FIG. 11 illustrate the dependency of intracranium brain pressure P.sub.IC as a function of brain volume for different average pressures P.sub.0. At the higher brain pressures the brain volume remains substantially constant. The measurements of the variations in the acoustic travel times depend upon the changes in the brain pressure .DELTA..sub.P along the acoustic path.”; “FIG. 13b is illustrative of the averaging effect obtained by alternating the direction of the travel time measurements with the reversal switch 118. At 131.1 is a curve of each of the actual measurements of the velocity .DELTA..sub.C (t) in the opposite directions, while curve 131.2 shows the effect of averaging the measurements in curve 131.1.”. See Fig. 13).
Regarding Claim 11, Ragauskas teaches the claim limitations as noted above.
Ragauskas further teaches: wherein the at least one characteristic peak is determined by the following steps: extracting a plurality of individual peaks from the at least one time segment of the time course of the time-of-flight values, normalizing time points of the time-of-flight values in the individual peaks, grouping the individual peaks by applying a similarity criterion for the individual peaks, identifying the group with the largest number of peaks, and forming the at least one characteristic peak from the peaks in the identified group of peaks (“Since the intracranium pressure P.sub.IC (t) can be expressed as the sum of an average component, P.sup.(.phi.).sub.IC, and a variable component .DELTA..sub.P (t), then it can be shown that by measuring the travel time accurately one can obtain an evaluation of the change in the intracranium pressure. Thus by obtaining a measurement of the changes in the travel time due to the effect of cardiac pulses on different portions of the brain, an indication of the pressure changes in that portion can be determined.”; “With reference to FIGS. 1-3 a system 20 is shown for deriving an indication of one or more dynamic characteristics of the intracranium medium 22.”;“The curves 82.1-82.3 in FIG. 11 illustrate the dependency of intracranium brain pressure P.sub.IC as a function of brain volume for different average pressures P.sub.0. At the higher brain pressures the brain volume remains substantially constant. The measurements of the variations in the acoustic travel times depend upon the changes in the brain pressure .DELTA..sub.P along the acoustic path.”; “FIG. 13b is illustrative of the averaging effect obtained by alternating the direction of the travel time measurements with the reversal switch 118. At 131.1 is a curve of each of the actual measurements of the velocity .DELTA..sub.C (t) in the opposite directions, while curve 131.2 shows the effect of averaging the measurements in curve 131.1.”. See Fig. 13).
Regarding Claim 12, Ragauskas teaches the claim limitations as noted above.
Ragauskas further teaches: wherein forming the at least one characteristic peak comprises: for each time point, forming a median of the time-of-flight values of the peaks from the identified group (“Since the intracranium pressure P.sub.IC (t) can be expressed as the sum of an average component, P.sup.(.phi.).sub.IC, and a variable component .DELTA..sub.P (t), then it can be shown that by measuring the travel time accurately one can obtain an evaluation of the change in the intracranium pressure. Thus by obtaining a measurement of the changes in the travel time due to the effect of cardiac pulses on different portions of the brain, an indication of the pressure changes in that portion can be determined.”; “With reference to FIGS. 1-3 a system 20 is shown for deriving an indication of one or more dynamic characteristics of the intracranium medium 22.”;“The curves 82.1-82.3 in FIG. 11 illustrate the dependency of intracranium brain pressure P.sub.IC as a function of brain volume for different average pressures P.sub.0. At the higher brain pressures the brain volume remains substantially constant. The measurements of the variations in the acoustic travel times depend upon the changes in the brain pressure .DELTA..sub.P along the acoustic path.”; “FIG. 13b is illustrative of the averaging effect obtained by alternating the direction of the travel time measurements with the reversal switch 118. At 131.1 is a curve of each of the actual measurements of the velocity .DELTA..sub.C (t) in the opposite directions, while curve 131.2 shows the effect of averaging the measurements in curve 131.1.”. See Fig. 13).
Regarding Claim 13, Ragauskas teaches the claim limitations as noted above.
Ragauskas further teaches: wherein the at least one segment is determined by the following steps: extracting one or more time segments from the time course of the time-of-flight values, wherein a segment comprises a plurality of peaks in the time-of-flight values, determining the at least one time segment by selecting one or more time segments in which the peaks meet a quality criterion (“Since the intracranium pressure P.sub.IC (t) can be expressed as the sum of an average component, P.sup.(.phi.).sub.IC, and a variable component .DELTA..sub.P (t), then it can be shown that by measuring the travel time accurately one can obtain an evaluation of the change in the intracranium pressure. Thus by obtaining a measurement of the changes in the travel time due to the effect of cardiac pulses on different portions of the brain, an indication of the pressure changes in that portion can be determined.”; “With reference to FIGS. 1-3 a system 20 is shown for deriving an indication of one or more dynamic characteristics of the intracranium medium 22.”;“The curves 82.1-82.3 in FIG. 11 illustrate the dependency of intracranium brain pressure P.sub.IC as a function of brain volume for different average pressures P.sub.0. At the higher brain pressures the brain volume remains substantially constant. The measurements of the variations in the acoustic travel times depend upon the changes in the brain pressure .DELTA..sub.P along the acoustic path.”; “FIG. 13b is illustrative of the averaging effect obtained by alternating the direction of the travel time measurements with the reversal switch 118. At 131.1 is a curve of each of the actual measurements of the velocity .DELTA..sub.C (t) in the opposite directions, while curve 131.2 shows the effect of averaging the measurements in curve 131.1.”. See Fig. 13).
Regarding Claim 15, Ragauskas teaches the claim limitations as noted above.
Ragauskas further teaches: wherein the quality criterion is formed by a comparison of the maximum amplitudes of the most dominant frequency component with amplitudes of further frequency components in the time course of the time-of-flight values in a segment, or wherein the quality criterion is formed by an evaluation of frequencies in the time course of the time-of-flight values in a segment (“Since the intracranium pressure P.sub.IC (t) can be expressed as the sum of an average component, P.sup.(.phi.).sub.IC, and a variable component .DELTA..sub.P (t), then it can be shown that by measuring the travel time accurately one can obtain an evaluation of the change in the intracranium pressure. Thus by obtaining a measurement of the changes in the travel time due to the effect of cardiac pulses on different portions of the brain, an indication of the pressure changes in that portion can be determined.”; “With reference to FIGS. 1-3 a system 20 is shown for deriving an indication of one or more dynamic characteristics of the intracranium medium 22.”;“The curves 82.1-82.3 in FIG. 11 illustrate the dependency of intracranium brain pressure P.sub.IC as a function of brain volume for different average pressures P.sub.0. At the higher brain pressures the brain volume remains substantially constant. The measurements of the variations in the acoustic travel times depend upon the changes in the brain pressure .DELTA..sub.P along the acoustic path.”; “FIG. 13b is illustrative of the averaging effect obtained by alternating the direction of the travel time measurements with the reversal switch 118. At 131.1 is a curve of each of the actual measurements of the velocity .DELTA..sub.C (t) in the opposite directions, while curve 131.2 shows the effect of averaging the measurements in curve 131.1.”. See Fig. 13).
Regarding Claim 17, Ragauskas teaches the claim limitations as noted above.
Ragauskas further teaches: wherein receiving data with time-of-flight values comprises: receiving a number of n time-of-flight curves, wherein in each of the n time-of-flight curves a time-of-flight value is assigned to one of the successive time points, for each of the n time-of-flight curves, subtracting an offset from the time-of-flight values in the time-of-flight curve, forming an averaged time-of-flight curve by averaging the time-of-flight values of each of the n time-of-flight curves at one of the successive time points (“FIG. 10c illustrates velocity curves 81.1 and 81.3 with a similar behavior as the curves 79.1 and 79.2 in FIG. 10b and illustrate that when the acoustic paths intersect either a basal artery or a ventricle, acoustic travel times vary primarily as a function of the changes in pressure brought on from cardiac pulses.”; “The curves 82.1-82.3 in FIG. 11 illustrate the dependency of intracranium brain pressure P.sub.IC as a function of brain volume for different average pressures P.sub.0. At the higher brain pressures the brain volume remains substantially constant. The measurements of the variations in the acoustic travel times depend upon the changes in the brain pressure .DELTA..sub.P along the acoustic path.”; “The frequency band .DELTA.f.sub.(BPF) of bandpass filter 148 is chosen so as to select a desired frequency modulated harmonic 143.J without distortion. This implies a frequency pass band for .DELTA.f.sub.BFP that is equal to or greater than 2F.sub.max where F.sub.max is the frequency band of the spectrum of the selected harmonic 143.J.”; “FIG. 13b is illustrative of the averaging effect obtained by alternating the direction of the travel time measurements with the reversal switch 118. At 131.1 is a curve of each of the actual measurements of the velocity .DELTA..sub.C (t) in the opposite directions, while curve 131.2 shows the effect of averaging the measurements in curve 131.1.”. See Fig. 13).
Regarding Claim 22, Ragauskas teaches: A computer configured to carry out a method for classifying a brain pressure (“With reference to FIGS. 13a, 13b, 14, 15, and 16, a more detailed view of a system and method in accordance with the invention to measure and derive a value of a characteristic of the intracranium medium is shown.”), the method comprising:
receiving data comprising time-of-flight values, which are based on time-of-flight values measured at successive time points for one or more ultrasound signals through a cross-section of a skull (“At 64 the time for the acoustic pulse to traverse the axis or path in the brain is determined using a transit travel time measuring technique. The transit travel time, .tau.(t), then includes the variations encountered along the travel path in the brain.”; “Transit time or travel time, pulses or signals, as such terms are used herein thus include those signals as detected and received with the embodiments as long as such signals include detectable variations attributable to time-dependent changes in a physical body such as the intracranial medium.”);
classifying a characteristic of the brain pressure by means of one or more features of a representative curve of a time course of the time-of-flight values to obtain a classified characteristic of the brain pressure (“With reference to FIGS. 1-3 a system 20 is shown for deriving an indication of one or more dynamic characteristics of the intracranium medium 22.”;“The curves 82.1-82.3 in FIG. 11 illustrate the dependency of intracranium brain pressure P.sub.IC as a function of brain volume for different average pressures P.sub.0. At the higher brain pressures the brain volume remains substantially constant. The measurements of the variations in the acoustic travel times depend upon the changes in the brain pressure .DELTA..sub.P along the acoustic path.”; “FIG. 13b is illustrative of the averaging effect obtained by alternating the direction of the travel time measurements with the reversal switch 118. At 131.1 is a curve of each of the actual measurements of the velocity .DELTA..sub.C (t) in the opposite directions, while curve 131.2 shows the effect of averaging the measurements in curve 131.1.”); and
outputting the classified characteristic of the brain pressure (“With reference to FIGS. 1-3 a system 20 is shown for deriving an indication of one or more dynamic characteristics of the intracranium medium 22…The characteristic can be the time dependence of the intracranium pressure of brain tissue such as at 24 in FIGS. 4-6…”; “…the pressure of the brain tissue at 98 and the time dependency of the width of the spinal fluid ventricle at 100 can be obtained. These signals can then be indicated at 102 such as by displaying them on a video display or on a chart recorder or recorded in memory for further analysis or future display.”).
Regarding Claim 23, Ragauskas teaches the claim limitations as noted above.
Ragauskas further teaches: An apparatus arrangement, comprising the computer according to claim 22 and at least two probes, for determining the time-of-flight values of the one or more ultrasound signals through a cross-section of a skull, wherein the at least two probes comprise at least one emitter for outputting the one or more ultrasound signals and at least one corresponding detector for detecting the output one or more ultrasound signals (“FIG. 1 a single pair of ultrasonic transducers 32,34 is used to investigate, for example either one or successively one of the brain paths 38, 40, or 42. This involves the appropriate alignment, see FIGS. 2 and 3, of the transducers 32, 34 to determine, for example, pulsations in the brain tissue pressure, path 38, or pulsatility of spinal fluid in a brain ventricle, path 42, or the pulsations in a basal artery, path 40. Alternatively a multiple of transducer pairs 32-34, 32'-34', 32"-34" could be simultaneously employed and aligned along these respective or other brain paths.”; “ One ultrasonic transducer is driven by an electric pulse to generate an acoustic pulse that is transmitted into the brain, while the other transducer serves as the detector of an incident acoustic pulse after it has traversed a path in the brain.”).
Regarding Claim 25, Ragauskas teaches the claim limitations as noted above.
Ragauskas further teaches: wherein the at least two probes are configured to output a plurality of wave packets each having an n-periodic signal of constant frequency at respective one of the successive time points, to detect time-of-flight values through the cross-section of the skull for each of the n-periods of the periodic signal at each of the plurality of wave packets (“FIG. 1 a single pair of ultrasonic transducers 32,34 is used to investigate, for example either one or successively one of the brain paths 38, 40, or 42. This involves the appropriate alignment, see FIGS. 2 and 3, of the transducers 32, 34 to determine, for example, pulsations in the brain tissue pressure, path 38, or pulsatility of spinal fluid in a brain ventricle, path 42, or the pulsations in a basal artery, path 40. Alternatively a multiple of transducer pairs 32-34, 32'-34', 32"-34" could be simultaneously employed and aligned along these respective or other brain paths.”; “FIG. 10c illustrates velocity curves 81.1 and 81.3 with a similar behavior as the curves 79.1 and 79.2 in FIG. 10b and illustrate that when the acoustic paths intersect either a basal artery or a ventricle, acoustic travel times vary primarily as a function of the changes in pressure brought on from cardiac pulses.”; “The curves 82.1-82.3 in FIG. 11 illustrate the dependency of intracranium brain pressure P.sub.IC as a function of brain volume for different average pressures P.sub.0. At the higher brain pressures the brain volume remains substantially constant. The measurements of the variations in the acoustic travel times depend upon the changes in the brain pressure .DELTA..sub.P along the acoustic path.”; “The frequency band .DELTA.f.sub.(BPF) of bandpass filter 148 is chosen so as to select a desired frequency modulated harmonic 143.J without distortion. This implies a frequency pass band for .DELTA.f.sub.BFP that is equal to or greater than 2F.sub.max where F.sub.max is the frequency band of the spectrum of the selected harmonic 143.J.”; “FIG. 13b is illustrative of the averaging effect obtained by alternating the direction of the travel time measurements with the reversal switch 118. At 131.1 is a curve of each of the actual measurements of the velocity .DELTA..sub.C (t) in the opposite directions, while curve 131.2 shows the effect of averaging the measurements in curve 131.1.”. See Fig. 13).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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.
Claim 14 and 27 are rejected under 35 U.S.C. 103 as being unpatentable over Ragauskas in view of Kassem et. al. (U.S. 20140275818, September 18, 2014)(hereinafter, “Kassem”).
Regarding Claim 14, Ragauskas teaches the claim limitations as noted above.
Ragauskas does not teach: wherein the quality criterion is formed by an autocorrelation function which evaluates a self-similarity of the time course of the time-of-flight values in a segment.
Kassem in the field of intracranial pressure systems and methods teaches “…a display screen that includes information related to a physiological parameter being measured from a patient. The information can include a current value based on values of the physiological parameter gathered from the patient over a period of time…a median of gathered values, a rate of change of gathered values, a correlation (e.g., PRx, RAP index, autocorrelation, an average of autocorrelation, etc.), a maximum value among the gathered values…”
Therefore, it would be obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the quality criterion in Ragauskas to be formed by autocorrelation function as taught in Kassem to “…allow the displaying and monitoring of one or more physiological parameters of the patient. This monitoring and display can facilitate identification of changes in the patient's condition that may require a doctor's assessment and/or may require an adjustment of the patient's treatment…” (Kassem, [0039]).
Regarding Claim 27, Ragauskas teaches: A method executed by a computer for classifying a brain pressure (“With reference to FIGS. 13a, 13b, 14, 15, and 16, a more detailed view of a system and method in accordance with the invention to measure and derive a value of a characteristic of the intracranium medium is shown.”), the method comprising:
receiving data comprising time-of-flight values, which are based on time-of-flight values measured at successive time points for one or more ultrasound signals through a cross-section of a skull (“At 64 the time for the acoustic pulse to traverse the axis or path in the brain is determined using a transit travel time measuring technique. The transit travel time, .tau.(t), then includes the variations encountered along the travel path in the brain.”; “Transit time or travel time, pulses or signals, as such terms are used herein thus include those signals as detected and received with the embodiments as long as such signals include detectable variations attributable to time-dependent changes in a physical body such as the intracranial medium.”);
classifying a characteristic of the brain pressure by means of one or more features of a representative curve of a time course of the time-of-flight values to obtain a classified characteristic of the brain pressure (“With reference to FIGS. 1-3 a system 20 is shown for deriving an indication of one or more dynamic characteristics of the intracranium medium 22.”;“The curves 82.1-82.3 in FIG. 11 illustrate the dependency of intracranium brain pressure P.sub.IC as a function of brain volume for different average pressures P.sub.0. At the higher brain pressures the brain volume remains substantially constant. The measurements of the variations in the acoustic travel times depend upon the changes in the brain pressure .DELTA..sub.P along the acoustic path.”; “FIG. 13b is illustrative of the averaging effect obtained by alternating the direction of the travel time measurements with the reversal switch 118. At 131.1 is a curve of each of the actual measurements of the velocity .DELTA..sub.C (t) in the opposite directions, while curve 131.2 shows the effect of averaging the measurements in curve 131.1.”); and
outputting the classified characteristic of the brain pressure (“With reference to FIGS. 1-3 a system 20 is shown for deriving an indication of one or more dynamic characteristics of the intracranium medium 22…The characteristic can be the time dependence of the intracranium pressure of brain tissue such as at 24 in FIGS. 4-6…”; “…the pressure of the brain tissue at 98 and the time dependency of the width of the spinal fluid ventricle at 100 can be obtained. These signals can then be indicated at 102 such as by displaying them on a video display or on a chart recorder or recorded in memory for further analysis or future display.”).
Ragauskas does not explicitly teach a computer-readable medium.
Kassem in the field of intracranial pressure systems and methods teaches: “A computer readable medium can be provided that has stored thereon a program, that when executed, can perform the method.” [0011].
Therefore, it would be obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Ragauskas to include a computer-readable medium as taught in Kassem to perform the method with minimal human interaction, increasing speed and accuracy of a processed method.
Conclusion
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/AMAL ALY FARAG/Primary Examiner, Art Unit 3798
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