Prosecution Insights
Last updated: April 19, 2026
Application No. 18/558,110

APPARATUS AND METHOD FOR CLASSIFYING HEART DISEASE USING MOBILENET

Non-Final OA §101§103§112
Filed
Oct 30, 2023
Examiner
LEVICKY, WILLIAM J
Art Unit
3796
Tech Center
3700 — Mechanical Engineering & Manufacturing
Assignee
Industry-Academic Cooperation Foundation Chosun University
OA Round
1 (Non-Final)
69%
Grant Probability
Favorable
1-2
OA Rounds
3y 5m
To Grant
98%
With Interview

Examiner Intelligence

Grants 69% — above average
69%
Career Allow Rate
397 granted / 572 resolved
-0.6% vs TC avg
Strong +29% interview lift
Without
With
+29.1%
Interview Lift
resolved cases with interview
Typical timeline
3y 5m
Avg Prosecution
56 currently pending
Career history
628
Total Applications
across all art units

Statute-Specific Performance

§101
7.8%
-32.2% vs TC avg
§103
38.1%
-1.9% vs TC avg
§102
21.2%
-18.8% vs TC avg
§112
24.3%
-15.7% vs TC avg
Black line = Tech Center average estimate • Based on career data from 572 resolved cases

Office Action

§101 §103 §112
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 . Information Disclosure Statement The information disclosure statement filed 6/16/2025 fails to comply with 37 CFR 1.98(a)(3)(i) because it does not include a concise explanation of the relevance, as it is presently understood by the individual designated in 37 CFR 1.56(c) most knowledgeable about the content of the information, of each reference listed that is not in the English language. It has been placed in the application file, but the information referred to therein has not been considered. The examiner notes this is regarding the NPL of the Korean office action which is not provided in English and does not have an English language summary. Drawings The drawings are objected to as failing to comply with 37 CFR 1.84(p)(5) because they include the following reference character(s) not mentioned in the description: Figure 1, Element 110. Corrected drawing sheets in compliance with 37 CFR 1.121(d), or amendment to the specification to add the reference character(s) in the description in compliance with 37 CFR 1.121(b) 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. 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. Claim Interpretation This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: input unit in claims 1 and 6; wavelet transformation unit in claims 1 and 6; filter unit in claims 2 and 7; and training dataset generation unit in claims 3-5 and 8-10. Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof. If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. 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 1-10 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 limitation “an input unit”; “a wavelet transformation unit”; a filter unit”; and “a training dataset generation unit” invokes 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed function and to clearly link the structure, material, or acts to the function. As best understood these units appear to be programs run on a computing device since Paragraph [0054] discloses a computer device to implement an apparatus for classifying heart disease using a MobileNet. Therefore, the claim is indefinite and is rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph. Applicant may: (a) Amend the claim so that the claim limitation will no longer be interpreted as a limitation under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph; (b) Amend the written description of the specification such that it expressly recites what structure, material, or acts perform the entire claimed function, without introducing any new matter (35 U.S.C. 132(a)); or (c) Amend the written description of the specification such that it clearly links the structure, material, or acts disclosed therein to the function recited in the claim, without introducing any new matter (35 U.S.C. 132(a)). If applicant is of the opinion that the written description of the specification already implicitly or inherently discloses the corresponding structure, material, or acts and clearly links them to the function so that one of ordinary skill in the art would recognize what structure, material, or acts perform the claimed function, applicant should clarify the record by either: (a) Amending the written description of the specification such that it expressly recites the corresponding structure, material, or acts for performing the claimed function and clearly links or associates the structure, material, or acts to the claimed function, without introducing any new matter (35 U.S.C. 132(a)); or (b) Stating on the record what the corresponding structure, material, or acts, which are implicitly or inherently set forth in the written description of the specification, perform the claimed function. For more information, see 37 CFR 1.75(d) and MPEP §§ 608.01(o) and 2181. 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 1-10 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim(s) recite(s) a mental process of classifying ECG signals in the frequency domain using a trained neural network. This judicial exception is not integrated into a practical application because as identified in the 112f/112b above all of the units are part of a computer device to receive ECG signals and using the processor transform them into the frequency domain and then classify the ECG signal using a neural network. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the steps are being performed on a general purpose computer. In light of Applicant’s specification, the claimed term computer is reasonably construed as a generic computing device. Like SAP America vs Investpic, LLC (Federal Circuit 2018), it is clear, from the claims themselves and the specification, that these limitations require no improved computer resources, just already available technology, with their already available basic functions, to use as tools in executing the claimed process. See MPEP 2106.05(f) 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. This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention. Claim(s) 1 and 6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Jang et al (Hyoung-Jong JANG et al, Detection of Premature Ventricular Contraction Using Discrete Wavelet Transform and Fuzzy Neural Network, Journal of Korea Multimedia Society Vol. 12, No. 3, March 2009 (pp. 451-459)), cited in IDS dated 10/30/2023, in view of Shin (KR 20210086778). Referring to Claims 1 and 6, Jang et al teaches an apparatus and method for classifying heart diseases using neural network, the apparatus comprising: an input unit configured to receive an electrocardiogram (ECG) signal in a time domain (e.g. Figure 6, input ECG and page 454, first paragraph under “3. Premature ventricular contraction diagnosis algorithm” discloses analyzing electrocardiogram signals); a wavelet transformation unit configured to transform the ECG signal in the time domain into an ECG signal in a frequency domain (e.g. Figure 6 wavelet and page 454, first paragraph under “3. Premature ventricular contraction diagnosis algorithm” discloses features are extracted using wavelet transform); a neural network configured to classify the ECG signal in the frequency domain as one of atrial fibrillation (AFIB), left bundle branch block beat (LBBB), normal sinus rhythm (NSR), and premature ventricular contraction (PVC), wherein the neural network is trained using a training dataset (e.g. Figure 6 NEWFM and page 454, first paragraph under “3. Premature ventricular contraction diagnosis algorithm” discloses using a neural network based on weighted fuzzy membership). However, Jang et al does not explicitly disclose the neural network is a MobileNet trained using a training data set. Shin teaches that it is known to use MobileNet neural network (well known technology) and data set for training a neural network as set forth in Page 8 paragraph 5 of the translation and page 8 line 9 of the translation to provide adjustment of parameters to improve detection accuracy and the simple substitution of one neural network for another. It would have been obvious before the effective filing date of the claimed invention to one having ordinary skill in the art to modify the system/method as taught by Jang et al, with data set for MobileNet neural network (well known technology) and data set for training a neural network as taught by Shin, since such a modification would provide the predictable results of adjustment of parameters to improve detection accuracy and the simple substitution of one neural network for another. Claim(s) 2 and 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Jang et al (Hyoung-Jong JANG et al, Detection of Premature Ventricular Contraction Using Discrete Wavelet Transform and Fuzzy Neural Network, Journal of Korea Multimedia Society Vol. 12, No. 3, March 2009 (pp. 451-459)) in view of Shin (KR 20210086778) as applied above, and further in view of Chen et al (US Publication 2020/0229756). Referring to Claims 2 and 7, Jang et al in view of Shin teaches the claimed invention, further comprising: a filter unit configured to perform low-pass filtering on the ECG signal in the time domain (e.g. Page 452, right column, last line). However, Jang et al does not explicitly disclose wherein a cutoff frequency of the low-pass filtering is 130 Hz. Chen et al teaches that it is known to use with a low pass filter with a cutoff frequency between 0.5Hz and 150Hz (thereby including 130 Hz as a cutoff frequency) as set forth in Paragraph [0042] to provide improving detection of cardiac activity while reducing high frequency noise. It would have been obvious before the effective filing date of the claimed invention to one having ordinary skill in the art to modify the system/method as taught by Jang et al, with a low pass filter with a cutoff frequency is 130Hz as taught by Chen et al, since such a modification would provide the predictable results of improving detection of cardiac activity while reducing high frequency noise. Claim(s) 3-5 and 8-10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Jang et al (Hyoung-Jong JANG et al, Detection of Premature Ventricular Contraction Using Discrete Wavelet Transform and Fuzzy Neural Network, Journal of Korea Multimedia Society Vol. 12, No. 3, March 2009 (pp. 451-459)) in view of Shin (KR 20210086778) as applied above, and further in view of Blake et al (US Publication 2021/0193291). Referring to Claims 3-5 and 8-10, Jang et al in view of Shin teaches the claimed invention, further comprising: a training dataset generation unit configured to generate the training dataset, wherein the MobileNet performs training using the training dataset; wherein the training dataset generation unit increases the number of pieces of data by generating a second number of ECG signals in the time domain from a first number of ECG signals in the time domain, the second number being greater than the first number, and the second number of ECG signals in the time domain are transformed into ECG signals in the frequency domain using wavelet transformation; wherein the training dataset generation unit increases the number of pieces of data by using a matching pursuit algorithm or by rotating each of the first number of ECG signals in the time domain. Blake et al teaches that it is known to use generation of simulation training data and actual data for training the neural network model with the actual data having greater weight as set forth in Figure 1 and Paragraph [0028] to provide training of the neural network model to reconstruct or predict electrical behavior from electrocardiogram (ECG) data. It would have been obvious before the effective filing date of the claimed invention to one having ordinary skill in the art to modify the system/method as taught by Jang et al, with a training dataset generation unit configured to generate the training dataset, wherein the MobileNet performs training using the training dataset; wherein the training dataset generation unit increases the number of pieces of data by generating a second number of ECG signals in the time domain from a first number of ECG signals in the time domain, the second number being greater than the first number, and the second number of ECG signals in the time domain are transformed into ECG signals in the frequency domain using wavelet transformation; wherein the training dataset generation unit increases the number of pieces of data by using a matching pursuit algorithm or by rotating each of the first number of ECG signals in the time domain as taught by Blake et al, since such a modification would provide the predictable results of raining of the neural network model to reconstruct or predict electrical behavior from electrocardiogram (ECG) data. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to William J Levicky whose telephone number is (571)270-3983. The examiner can normally be reached Monday-Thursday 8AM-5PM EST. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, David Hamaoui can be reached at (571)270-5625. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /WILLIAM J LEVICKY/Primary Examiner, Art Unit 3796
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Prosecution Timeline

Oct 30, 2023
Application Filed
Sep 10, 2025
Non-Final Rejection — §101, §103, §112 (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

1-2
Expected OA Rounds
69%
Grant Probability
98%
With Interview (+29.1%)
3y 5m
Median Time to Grant
Low
PTA Risk
Based on 572 resolved cases by this examiner. Grant probability derived from career allow rate.

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