DETAILED ACTION
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, 3, and 5-8 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claims recite an abstract idea as discussed below. This abstract idea is not integrated into a practical application for the reasons discussed below. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception for the reasons discussed below.
Step 1 of the 2019 Guidance requires the examiner to determine if the claims are to one of the statutory categories of invention. Applied to the present application, the claims belong to one of the statutory classes of a process or product as a computer implemented method or a computer system/product.
Step 2A of the 2019 Guidance is divided into two Prongs. Prong 1 requires the examiner to determine if the claims recite an abstract idea, and further requires that the abstract idea belong to one of three enumerated groupings: mathematical concepts, mental processes, and certain methods of organizing human activity.
Claim 1 is copied below, with the limitations belonging to an abstract idea being underlined.
1. A peak shape estimation device comprising a processor, said processor configured to process measurement data acquired from a mass spectrometer or chromatograph, and memory storing computer executable instructions that, when executed by the processor, cause the peak shape estimation device to:
acquire measurement waveform data based on measurement data acquired over time, by said mass spectrometer or chromatograph, the measurement waveform data representing a change in signal intensity versus time in the measurement data; and
acquire estimation waveform data by estimating a peak shape included in the measurement waveform data by fitting a peak waveform model to the measurement waveform data, wherein an error term having a correlation to time is added to the peak waveform model before fitting the peak waveform model to the measurement waveform data to represent noise data;
calculate a peak area with use of the estimation waveform data,
wherein the error term is modeled as a time-series model.
Claim 6 is copied below, with the limitations belonging to an abstract idea being underlined.
6. A peak shape estimation device comprising a processor and memory storing computer executable instructions that, when executed by the processor, cause the peak shape estimation device to:
acquire measurement waveform data based on measurement data acquired over time by an analysis device the measurement data representing a change in signal intensity versus time in the measurement data;
estimate noise data included in the measurement waveform data and determine a correlation coefficient for the estimate of the noise data;
calculate a peak area with use of estimation waveform data; and
output an indication of a detection of an abnormality in response to the correlation coefficient exceeding a predetermined threshold value.
Claim 7 is copied below, with the limitations belonging to an abstract idea being underlined.
7. A peak shape estimation method comprising:
acquiring measurement waveform data based on measurement data acquired over time by an analysis device, the measurement waveform data representing a change in signal intensity versus time in the measurement data; and
acquiring estimation waveform data by estimating a peak shape included in the measurement waveform data by fitting a peak waveform model to the measurement waveform data, wherein an error term having a correlation to time is added to the peak waveform model before fitting the peak waveform model to the measurement waveform data to represent noise data; and
calculating a peak area with use of the estimation waveform data;
wherein the error term is modeled as a time-series model.
Claim 8 is copied below, with the limitations belonging to an abstract idea being underlined.
8. A peak shape estimation abnormality detection method including:
acquiring measurement waveform data based on measurement data acquired over time by an analysis device, the measurement waveform data representing a change in signal intensity versus time in the measurement data;
estimating noise data included in the measurement waveform data and determining a correlation coefficient for the estimate of the noise data;
calculating a peak area with use of estimation waveform data; and
output an indication of a detection of an abnormality in response to the correlation coefficient exceeding a predetermined threshold value.
The limitations underlined can be considered to describe a mathematical concept, namely a series of calculations leading to one or more numerical results or answers, obtained by a sequence of mathematical operations on numbers and/or mental steps. The lack of a specific equation in the claim merely points out that the claim would monopolize all possible appropriate equations for accomplishing this purpose in all possible systems. These steps recited by the claim therefore amount to a series of mental and/or mathematical steps, making these limitations amount to an abstract idea.
In summary, the highlighted steps in the claim above therefore recite an abstract idea at Prong 1 of the 101 analysis.
The additional elements in the claim have been left in normal font.
The additional limitations in relation to the computer, computer product, or computer system, i.e. processor and memory storing executable instructions, does not offer a meaningful limitation beyond generally linking the use of the method to a computer (see ALICE CORP. v. CLS BANK INT’L 573 U. S. 208 (2014)). The claim does not recite a particular machine applying or being used by the abstract idea. As discussed above, the recited means plus function limitations equate to software instructions/algorithm implement on a computer and are treated as part of the abstract idea/data processing algorithm.
The additional limitation of acquiring the measurement waveform data equates to extrasolution data activity, i.e. data gathering (see MPEP 2106.05(g)).
The additional limitation outputting the indication of a detection of an abnormality based on the value of correlation coefficient equates to extrasolution data activity, i.e. data reporting (see MPEP 2106.05(g)).
The claims do not integrate the abstract idea into a practical application. Various considerations are used to determine whether the additional elements are sufficient to integrate the abstract idea into a practical application. The claim does not recite a particular machine applying or being used by the abstract idea. The claim does not effect a real-world transformation or reduction of any particular article to a different state or thing. (Manipulating data from one form to another or obtaining a mathematical answer using input data does not qualify as a transformation in the sense of Prong 2.)
The claim does not contain additional elements which describe the functioning of a computer, or which describe a particular technology or technical field, being improved by the use of the abstract idea. (This is understood in the sense of the claimed invention from Diamond v Diehr, in which the claim as a whole recited a complete rubber-curing process including a rubber-molding press, a timer, a temperature sensor adjacent the mold cavity, and the steps of closing and opening the press, in which the recited use of a mathematical calculation served to improve that particular technology by providing a better estimate of the time when curing was complete. Here, the claim does not recite carrying out any comparable particular technological process.) In all of these respects, the claim fails to recite additional elements which might possibly integrate the claim into a particular practical application. Instead, based on the above considerations, the claim would tend to monopolize the abstract idea itself, rather than integrate the abstract idea into a practical application.
Step 2b of the 2019 Guidance requires the examiner to determine whether the additional elements cause the claim to amount to significantly more than the abstract idea itself. The considerations for this particular claim are essentially the same as the considerations for Prong 2 of Step 2a, and the same analysis leads to the conclusion that the claim does not amount to significantly more than the abstract idea.
Therefore, claims 1, 6, 7, and 8 are rejected under 35 U.S.C. 101 as directed to an abstract idea without significantly more.
Dependent claims 3 and 5 are similarly ineligible. The dependent claims merely add limitations which further detail the abstract idea, namely further mathematical/mental steps detailing how the data processing algorithm is implemented, i.e. additional software limitations. These do not help to integrate the claim into a practical application or make it significantly more than the abstract idea (which is recited in slightly more detail, but not in enough detail to be considered to narrow the claim to a particular practical application itself).
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.
Claims 6 and 8 are rejected under 35 U.S.C. 103 as being unpatentable over Gupta (US 20190271295) in view of Nakamura (US 20200239136).
Regarding claim 6, Gupta discloses a peak shape estimation device comprising a computer, i.e. computers obviously comprise a processor and memory storing computer executable instructions that are executed by the processor, the computer causing the peak shape estimation device to (see paragraphs 0026 and 0046: computer for data analysis; analyses noise peak, including width, i.e. shape):
acquire measurement waveform data based on measurement data acquired over time by an analysis device the measurement data representing a change in signal intensity versus time in the measurement data (see Abstract and paragraph 0025-0026 and 0046: computer receives noise data captured by microphone, noise data captured over time period, noise data contains peaks, i.e. must contain a change in signal intensity versus time);
estimate noise data included in the measurement waveform data and determine a correlation coefficient for the estimate of the noise data (see paragraph 0013 and claims 1 and 6: determines a correlation coefficient with respect to the noise data to see if signal contains tonal noise);
calculate a peak width with use of estimation waveform data (see paragraph 0089-0090: width of the identified peak is analyzed); and
determine an indication of a detection of an abnormality in response to the correlation coefficient exceeding a predetermined threshold value (see paragraph 0013 and claim 6: determining presence of tonal noise if a correlation coefficient exceeds a threshold).
Gupta does not expressly disclose calculating a peak area with use of estimation waveform data; and
outputting an indication of the detection abnormality.
Nakamura discloses calculating a peak area with use of estimation waveform data (see Figs 4a and 4b and paragraph 0011-0012: discloses calculating peak area of acquired peak data as well as peak width); and
outputting an indication of a detection abnormality (see Abstract and paragraph 0038: outputting an abnormal signal in response to identifying an abnormality).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Gupta with the teachings of Nakamura, i.e. calculating a peak area and outputting an indication of the identified abnormality, for the advantageous benefit of using an alternative parameter to represent the size/shape of the identify peak and alerting one of the identified abnormalities.
Regarding claim 8, Gupta discloses a peak shape estimation abnormality detection method (see Abstract, paragraph 0017, and claim 6: determining presence of tonal noise if a correlation coefficient exceeds a threshold) including:
acquiring measurement waveform data based on measurement data acquired over time by an analysis device, the measurement waveform data representing a change in signal intensity versus time in the measurement data (see Abstract and paragraph 0025-0026 and 0046: computer receives noise data captured by microphone, noise data captured over time period, noise data contains peaks, i.e. must contain a change in signal intensity versus time);
estimating noise data included in the measurement waveform data and determining a correlation coefficient for the estimate of the noise data (see paragraph 0013 and claims 1 and 6: determines a correlation coefficient with respect to the noise data to see if signal contains tonal noise);
calculating a peak width with use of estimation waveform data (see paragraph 0089-0090: width of the identified peak is analyzed); and
determine an indication of a detection of an abnormality in response to the correlation coefficient exceeding a predetermined threshold value (see paragraph 0013 and claim 6: determining presence of tonal noise if a correlation coefficient exceeds a threshold).
Gupta does not expressly disclose calculating a peak area with use of estimation waveform data; and
outputting an indication of the detection of an abnormality.
Nakamura discloses calculating a peak area with use of estimation waveform data (see Figs 4a and 4b and paragraph 0011-0012: discloses calculating peak area of acquired peak data as well as peak width); and
outputting an indication of a detection abnormality (see Abstract and paragraph 0038: outputting an abnormal signal in response to identifying an abnormality).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Gupta with the teachings of Nakamura, i.e. calculating a peak area and outputting an indication of the identified abnormality, for the advantageous benefit of using an alternative parameter to represent the size/shape of the identify peak and alerting one of the identified abnormalities.
Response to Arguments
Applicant's arguments filed have been fully considered.
Applicant argues that the claim amendments overcome the prior Claim Objections. The examiner agrees, the prior Claim Objections have been withdrawn.
Applicant argues that the claim amendments overcome the prior 112 Claim Rejections. The examiner agrees, the prior 112 Claim Rejections have been withdrawn.
Applicant argues that the claims are patent eligible under 35 USC 101.
Applicant argues that the claims are not directed to a mathematical concept standing along, but are directed to a physical device having tangible components. The examiner respectfully disagrees as the argued physical components represent a computer. The additional limitations in relation to the computer, computer product, or computer system, i.e. processor and memory storing executable instructions, does not offer a meaningful limitation beyond generally linking the use of the method to a computer (see ALICE CORP. v. CLS BANK INT’L 573 U. S. 208 (2014)).
Applicant argues that the claims is integrated into a practical application as the performance of peak shape estimation device is being improved. The examiner respectfully disagrees. A novel abstract idea is still an abstract idea. Synopsys v Mentor Graphics held that a claim for a new abstract idea is still an abstract idea and that the search for a 101 inventive concept is thus distinct from demonstrating 102 novelty (SYNOPSYS, INC. v. 2 MENTOR GRAPHICS CORPORATION (CAFC Decided October 17, 2016). Furthermore, the claims do not expressly recite any limitation in relation to performing any of the argued analytical measurements. The claim only requires acquiring, i.e. receiving such data, and receiving data equates to extrasolution data activity, not a practical application.
Applicant argues that the pending claims are like patent eligible examples 40 and 41. The examiner respectfully disagrees as neither example relates to peak identification. Furthermore, example 40, claim 1 includes a response of collecting additional data upon a predetermined condition. Example 40, claim 2 collects data and compares the data to a threshold was found to be patent ineligible. Similar to the threshold comparison in independent claim 6 and 8 of the applicant’s invention.
Applicant argues that the claims are directed to a patent eligible improvement under step 2B as the limitation are not well-understood, routine or conventional. The examiner respectfully disagrees. A novel abstract idea is still an abstract idea. Synopsys v Mentor Graphics held that a claim for a new abstract idea is still an abstract idea and that the search for a 101 inventive concept is thus distinct from demonstrating 102 novelty (SYNOPSYS, INC. v. 2 MENTOR GRAPHICS CORPORATION (CAFC Decided October 17, 2016).
Applicant argues that the claims are patentable over the prior 103 Claim Rejections. The examiner agrees. However, upon further search and consideration, new 103 Claim Rejections have been presented above.
Relevant Prior Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Grosman (US 20210178069) discloses time series analysis of data using autoregressive moving average models.
Zhang CN-108564254, see English Translation, discloses analyzing chromatogram data using an autoregressive moving average model.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MICHAEL J DALBO whose telephone number is (571)270-3727. The examiner can normally be reached M-F 9AM - 5PM.
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/MICHAEL J DALBO/ Primary Examiner, Art Unit 2857
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