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 .
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, 6, and 8 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.
Specifically, representative Claim 1 recites:
“An analysis device comprising: a waveform deformation unit configured to enlarge or reduce a target signal waveform obtained by analysis and indicating a change in signal intensity depending on a change in a value of a predetermined parameter by a scale factor of N (where N is a positive value other than 0 and 1) in the direction of the signal intensity axis and/or enlarge or reduce by a scale factor of M (where M may be a positive value other than 0 and 1 and may be a same value as N) in the direction of the predetermined parameter axis; a peak detection unit configured to use a learned model generated in advance by machine learning using, as teaching data, a signal waveform and a start point and an end point of a correct solution, and use, as an input, a signal waveform after deformation by the waveform deformation unit, and output, as a detection result, the start point and the end point of the peak; and a waveform inverse deformation unit configured to reduce or enlarge information on a start point and an end point of a peak, the information being output by the peak detection unit, by a scale factor of 1/N in the direction of the signal intensity axis and/or by a scale factor of 1/M in the direction of the predetermined parameter axis inverse to that at the time of deformation by the waveform deformation unit, and obtain a peak detection result for the target signal waveform, and a determination unit configured to determine a target parameter value range for which waveform enlargement or reduction is performed by the waveform deformation unit according to a predetermined reference, wherein the waveform deformation unit is configured to perform processing of enlarging or reducing the target signal waveform only for the target parameter value range determined by the determination unit.”
The claim limitations in the abstract idea have been highlighted in bold above; the remaining limitations are “additional elements”.
Under the Step 1 of the eligibility analysis, we determine whether the claims are to a statutory category by considering whether the claimed subject matter falls within the four statutory categories of patentable subject matter identified by 35 U.S.C. 101: Process, machine, manufacture, or composition of matter. The above claim is considered to be in a statutory category (machine).
Under the Step 2A, Prong One, we consider whether the claim recites train
a judicial exception (abstract idea). In the above claim, the highlighted portion constitutes an abstract idea because, under a broadest reasonable interpretation, it recites limitations that fall into/recite an abstract idea exceptions. Specifically, under the 2019 Revised Patent Subject matter Eligibility Guidance, it falls into the groupings of subject matter that covers mathematical concepts - mathematical relationships, mathematical formulas or equations, mathematical calculations. Additionally/alternatively, the limitation “determine a target parameter value range for which waveform enlargement or reduction is performed by the waveform deformation unit according to a predetermined reference”, under the BRI, falls into the mental process grouping (observation/evaluation/judgement).
Similar limitations comprise the abstract ideas of Claim 6.
Next, under the Step 2A, Prong Two, we consider whether the above claims that recites a judicial exception are integrated into a practical application.
The above claims comprise the following additional elements:
In Claim 1: An analysis device comprising: a waveform deformation unit, a peak detection unit, a waveform inverse deformation unit; a learned model generated in advance by machine learning using, as teaching data;
In Claim 6: A non-transitory computer-readable recording media, a computer; using a learned model generated in advance by machine learning using, as teaching data, a signal waveform
The additional elements in the preambles are recited in generality and represent insignificant extra-solution activity (field-of-use limitations) that is not meaningful to indicate a practical application.
The additional elements in the claims such as a non-transitory computer-readable medium and a computer (Claim 6) and functional units (Claim 1) are examples of generic computer equipment (components) that are generally recited and not meaningful and, therefore, are not qualified as particular machines to indicate a practical application. The limitations that generically recite obtaining a signal waveform (Claim 1) and a target signal waveform (Claim 6) represent insignificant extra-solution activity of mere data gathering. ”According to the October update on 2019 SME Guidance such steps are “performed in order to gather data for the mental analysis step, and is a necessary precursor for all uses of the recited exception. It is thus extra-solution activity, and does not integrate the judicial exception into a practical application”.
A step of performing processing of enlarging or reducing the target signal waveform only for the target parameter value range determined by the determination unit is not a meaningful limitations because it’s generically recited and represents insignificant extra-solution activity for all uses of the judicial exception.
The limitation that recite using a learned model generated in advance by machine learning using, as teaching data, a signal waveform are not meaningful to indicate a practical application (recited in generality).
Therefore, the claims are directed to a judicial exception and require further analysis under the Step 2B.
However, the above claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception (Step 2B analysis) because these additional elements/steps are well-understood and conventional in the relevant art based on the prior art of record. For example, Melnikov, Takeshi, and Taya disclose a learned model generated in advance by machine learning using, as teaching data, a signal waveform. A step of performing processing of enlarging or reducing the target signal waveform only for the target parameter value range is disclosed by Taya, Noda, and Takeshi.
The independent claims, therefore, are not patent eligible.
With regards to the dependent claims, claims 2-3 and 8 provide additional features/steps which are part of an expanded abstract idea of the independent claims (additionally comprising abstract idea steps) and, therefore, these claims are not eligible without meaningful additional elements that reflect a practical application and/or additional elements that qualify for significantly more for substantially similar reasons as discussed with regards to Claim 1.
For example, additional elements in Claims 2 and 3 (chromatogram waveform and deep learning) are all recited in generality and not meaningful to indicate a practical application and/or qualify for significantly more.
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 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.
Claims 1-3 and 6 are rejected under 35 U.S.C. 103 as being unpatentable over Arsenty D. Melnikov et al., “Deep Learning for the Precise Peak Detection in High-Resolution LC−MS Data”, Anal. Chem. 2020, 92, pp. 588−592, hereinafter “Melnikov’ and supplementary information to this article, “Supplementary information for “Deep learning for the precise peak detection in high-resolution LC-MS data"' (27 pages), hereinafter ‘Supplementary’ (submitted in IDS dated 6/24/2024) in view of Osoekawa Takeshi (US 20200279408), hereinafter ‘Takeshi’, in view of Akihiroa Taya et al. (US 12105068), hereinafter ‘Taya’.
With regards to Claim 1, Melnikov discloses
An analysis device (CNN for ROI Classification, p.589) comprising: a waveform deformation unit configured to enlarge or reduce a target signal waveform obtained by analysis and indicating a change in signal intensity depending on a change in a value of a predetermined parameter by a scale factor of N (where N is a positive value other than 0 and 1) in the direction of the signal intensity axis and/or enlarge or reduce by a scale factor of M (where M may be a positive value other than 0 and 1 and may be a same value as N) in the direction of the predetermined parameter axis (The signal intensities in ROIs were scaled to unity at the maximum, p.590); a peak detection unit (CNN for Peak Integration, p.590) configured to use a learned model (Authors applied CNN, p.588) generated in advance by machine learning using, as teaching data, a signal waveform and a start point and an end point of a correct solution (Section “Data Mining”, p.589), and output, as a detection result, the start point and the end point of the peak (Peak boundaries, p.590), a waveform inverse deformation unit (CNN for Peak Integration, p.590), and reducing or enlarging (scaling) information (p. 590, left column) and calculating an integrated area for measured peaks (p.590, Left Column: The length of each ROI was linearly interpolated, transforming the ROI size to 256 points. The signal intensities in ROIs were scaled to unity at the maximum; additionally, “Evaluation of the algorithm” section) that implies reducing or enlarging information on a start point and an end point of a peak, the information being output by the peak detection unit, by a scale factor of 1/N in the direction of the signal intensity axis and/or by a scale factor of 1/M in the direction of the predetermined parameter axis inverse to that at the time of deformation by the waveform deformation unit, and obtain a peak detection result for the target signal waveform.
“Supplementary” also discloses generated in advance by machine learning using, as teaching data, a signal waveform and a start point and an end point of a correct solution (Fig. S2, p.5) and further discloses use, as an input, a signal waveform after deformation by the waveform deformation unit (CNN for peak integration, last paragraph on p.6), and output, as a detection result, the start point and the end point of the peak (Table S1, p.10);
However, Melnikov does not specifically disclose reducing or enlarging information on a start point and an end point of a peak, the information being output by the peak detection unit, by a scale factor of 1/N in the direction of the signal intensity axis and/or by a scale factor of 1/M in the direction of the predetermined parameter axis inverse to that at the time of deformation by the waveform deformation unit, and obtain a peak detection result for the target signal waveform.
Takeshi discloses a waveform deformation unit [0070, 0055] that describes waveform scaling in both intensity and tine axis, a peak detection unit [0071-0072] that discloses converting pixel positions of the start/end points of peak back to time and intensity and outputting results (Fig.7).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Melnikov/Supplemental in view of Takeshi to obtain a peak detection result for the target signal waveform by reducing or enlarging information on a start point and an end point of a peak, the information being output by the peak detection unit, by a scale factor of 1/N in the direction of the signal intensity axis and/or by a scale factor of 1/M in the direction of the predetermined parameter axis inverse to that at the time of deformation by the waveform deformation unit as known in art techniques of scaling/zooming in/out using specific magnification factors as discussed in Takeshi above.
Melnikov does not specifically disclose
a determination unit configured to determine a target parameter value range for which waveform enlargement or reduction is performed by the waveform deformation unit according to a predetermined reference, wherein the waveform deformation unit is configured to perform processing of enlarging or reducing the target signal waveform only for the target parameter value range determined by the determination unit.
Yasufumi discloses a signal processing system [0002] with a determination unit (Comparator 31, Abstract) that determine whether a signal strength (strength of fluctuations in signal intensity) is high or low compared to specified value such as a reference value [0004, 0011, 0012].
Taya discloses target parameter value range determined by the determination unit (a method of splitting spectral information on the sample into a plurality of pieces of spectral information is a method of specifying, by the user, splitting locations of the spectral information. For example, there exist a method of specifying a range of a spectrum for each test substance, and a method of specifying a center of the spectrum for each test substance, to thereby extract a certain range before and after the center. The method of specifying the center includes a method of setting the range to be extracted in advance and a method of automatically determining the range to be extracted, Col.7, Lines 32-42]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Melnikov/Supplemental in view of Takeshi, Yasufumi, and Taya to perform processing of enlarging or reducing a signal waveform according to a predetermined reference (ensures a wide dynamic range while preventing a decrease in the S / N ratio, Yasufumi [0008]) while performing it for a limited (“target parameter value”) spectral range as determined by the determination unit (only required to extend a range for the extraction, Taya, Col.7, Line 48-49) to increase efficiency of processing.
With regards to Claims 2 and 3, Melnikov/Supplemental in view of Takeshi, Yasufumi, and Taya discloses the claim limitations as discussed in regards to Claim 1.
Melnikov/Supplemental additionally discloses he predetermined parameter is time, and the signal waveform is a chromatogram waveform, wherein the machine learning is deep learning (Melnikov, Title and Abstract) and so does Takeshi [0049].
With regards to Claim 6, Melnikov/Supplemental in view of Takeshi, Yasufumi, and Taya discloses the claim limitations as discussed in regards to Claim 1.
In addition, Melnikov/Supplemental disclose a non-transitory computer-readable recording media recording a waveform processing program for an analysis device, the program configured to process, on a computer, a target signal waveform (p.588).
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Melnikov/Supplemental in view of Takeshi, Yasufumi, and Taya, in further view of Akira Noda (US 20190011408), hereinafter ‘Noda’.
Melnikov/Supplemental in view of Takeshi, Yasufumi, and Taya discloses the claim limitations as discussed in regards to Claim 1.
However, Melnikov/Supplemental does not specifically disclose wherein the value of N and/or the value of M is a predetermined value or a value selected by a user.
Noda discloses the value of N and/or the value of M is a predetermined value (a scale factor changed within a predetermined range [0018]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Melnikov/Supplemental in view of Takeshi, Yasufumi, Taya, and Noda to use a value of N and/or the value of M as a predetermined value to ensure true (noise-free) picks (Noda [0040]).
Response to Arguments
35 U.S.C. 101
Applicant's arguments filed 5/27/2026 have been fully considered but they are not persuasive.
The Applicant argues (p.4): Notably, claim 1 recites enlarging or reducing the target signal waveform only for the target parameter value range …
Thus, at least the above-noted claim features improve the technology of liquid and gas chromatography and therefore, when viewed as a whole, integrate any alleged abstract idea into a practical application thereof.
The Examiner submits that the entire improvement (“enlarging or reducing the target signal waveform only for the target parameter value range”) is in the abstract idea. However, according to MPEP 2106.05(a).II: “it is important to keep in mind that an improvement in the abstract idea itself (e.g. a recited fundamental economic concept) is not an improvement in technology … the claim must include more than mere instructions to perform the method on a generic component or machinery to qualify as an improvement to an existing technology”.
The Examiner additionally notes that no meaningful additional elements related to technology of liquid and gas chromatography that may indicate a practical application are recited in addition to the abstract idea.
The Applicant argues (p.4):
Further, the present claims are similar to subject-matter eligibility Example 40 (claim 1) and Example 47 (claim 3), which are directed to a practical application of the respective abstract ideas recited therein.
The Examiner respectfully disagrees.
With regards to Example 40, its Claim 1 recites meaningful additional elements that indicate a practical application (“the traffic data comprising at least one of network delay, packet loss, or jitter …collecting additional traffic data relating to the network traffic when the collected traffic data is greater than the predefined threshold, the additional traffic data comprising Netflow protocol data”). The Claim also recites “a network appliance connected between computing devices in a network”. The instant claim only recites the abstract idea steps.
With regards to Example 47, its Claim 1 is found eligible because it does not recite an abstract idea unlike the instant claim (“There is no judicial exception recited in the claim.”)
35 U.S.C. 103
Applicant’s arguments with respect to claim(s)1 and 6 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ALEXANDER SATANOVSKY whose telephone number is (571)270-5819. The examiner can normally be reached on M-F: 9 am-5 pm.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Catherine Rastovski can be reached on (571) 270-0349. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ALEXANDER SATANOVSKY/
Primary Examiner, Art Unit 2857
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