CTNF 18/167,693 CTNF 94830 Detailed Notice Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. Continued Examination Under 37 CFR 1.114 07-42-04 AIA A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 12/29/2025 has been entered. Claim Rejections - 35 USC § 101 07-04-01 AIA 07-04 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 1-16 and 18-20 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. Step 1: In the instant case, claims 1-15 are directed toward a method (i.e., process) and claims 16 and 18-20 are directed toward an electrocardiogram (ECG) processing device (i.e., machine). Thus, each of the claims falls within one of the four statutory categories. Nevertheless, the claims fall within the judicial exception of an abstract idea. Step 2A—Prong 1: Independent claims 1, 10, and 16 recites steps that, under their broadest reasonable interpretations, cover performance of the limitations of a mental process, but for the recitation of generic computer components. Claim 1 recites: “A method comprising: selecting a first beat and a second beat; determining a dynamic time warping (DTW) distance between the first beat and the second beat; setting a similarity label for the first beat and the second beat based on the DTW distance; storing the first beat, the second beat, and the similarity label in a location of non- transitory memory as an electrocardiogram (ECG) training data triad; and training a machine learning model with the ECG training data triad to produce a trained machine learning model”. The limitations of selecting a first beat and a second beat; determining a dynamic time warping (DTW) distance between the first beat and the second beat; setting a similarity label for the first beat and the second beat based on the DTW distance; storing the first beat, the second beat, and the similarity label in a location… as an electrocardiogram (ECG) training data triad , given the broadest reasonable interpretation, cover the abstract idea of a mental process because they recite limitations that person can perform in the mind or via pen and paper—in this case the aforementioned steps recite a process of selecting, determining, setting, storing, training, and producing , but instead automates the process via a computer model, e.g. see MPEP 2106.04(a)(2). Any limitations not identified above as part of the abstract idea are deemed “additional elements”, and will be discussed in further detail below. Additionally, claim 10 recites: “A method comprising: selecting a first beat and a second beat; setting a similarity label for the first beat and the second beat based on a plurality of similarity metrics each received from a respective expert of a plurality of experts; storing the first beat, the second beat, and the similarity label in a location of non- transitory memory as a first electrocardiogram (ECG) training data triad; selecting a third beat and a fourth beat; determining a dynamic time warping (DTW) distance between the third beat and the fourth beat; setting a second similarity label for the third beat and the fourth beat based on the DTW distance; storing the third beat, the fourth beat, and the second similarity label in the location of non-transitory memory as a second ECG training data triad; and training a machine learning model with the first ECG training data triad and the second ECG training data triad to produce a trained machine learning model”. The limitations of selecting a first beat and a second beat; setting a similarity label for the first beat and the second beat based on a plurality of similarity metrics each received from a respective expert of a plurality of experts; storing the first beat, the second beat, and the similarity label in a location… as a first electrocardiogram (ECG) training data triad; selecting a third beat and a fourth beat; determining a dynamic time warping (DTW) distance between the third beat and the fourth beat; setting a second similarity label for the third beat and the fourth beat based on the DTW distance; storing the third beat, the fourth beat, and the second similarity label in the location… as a second ECG training data triad , given the broadest reasonable interpretation, cover the abstract idea of a mental process because they recite limitations that person can perform in the mind or via pen and paper—in this case the aforementioned steps recite a process of selecting, setting, storing, determining, training, and produce , but instead automates the process via a computer model or machine learning, e.g. see MPEP 2106.04(a)(2). Any limitations not identified above as part of the abstract idea are deemed “additional elements”, and will be discussed in further detail below. Additionally, claim 16 recites: “An electrocardiogram (ECG) processing device comprising: a display device; a memory storing a machine learning model and instructions; and a processor communicably coupled to the display device and the memory, and when executing the instructions, configured to: receive Holter monitor data; separate the Holter monitor data into a plurality of beats; classify the plurality of beats to a plurality of classifications using the machine learning model, the machine learning model trained with a plurality of training data triads each comprising a respective first beat, a respective second beat, and a respective similarity label indicating if the respective first beat and the respective second beat are similar or dissimilar, a first portion of the similarity labels generated based on similarity metrics received from a plurality of experts and a second portion of the similarity labels generated based on, for each similarity label of the second portion of similarity labels, a dynamic time warping (DTW) distance between a respective first beat and a respective second beat of a training data triad including that similarity label; and display a plurality of representative beats corresponding to the plurality of classifications along with corresponding physiological labels via the display device”. The limitations of receive Holter monitor data; separate the Holter monitor data into a plurality of beats; classify the plurality of beats to a plurality of classifications… trained with a plurality of training data triads each comprising a respective first beat, a respective second beat, and a respective similarity label indicating if the respective first beat and the respective second beat are similar or dissimilar, a first portion of the similarity labels generated based on similarity metrics received from a plurality of experts and a second portion of the similarity labels generated based on, for each similarity label of the second portion of similarity labels, a dynamic time warping (DTW) distance between a respective first beat and a respective second beat of a training data triad including that similarity label; and display a plurality of representative beats corresponding to the plurality of classifications along with corresponding physiological labels via the display device , given the broadest reasonable interpretation, cover the abstract idea of a certain method of organizing human activity because they recite managing personal behavior or relationships or interactions between people (i.e. social activities, teaching, and following rules or instructions—in this case the aforementioned steps recite a process of receive, separate, classify, training, and display , which is properly interpreted as a “personal behavior”), but instead automates the process via a computer model or machine learning, e.g. see MPEP 2106.04(a)(2). Any limitations not identified above as part of the abstract idea are deemed “additional elements”, and will be discussed in further detail below. Dependent claims 2-9, 11-15, and 18-20 include other limitations, for example: Claims 4, 15, and 18 recite additional elements of “machine learning model comprises a deep learning network or a support vector machine”; Claim 19 recite additional elements of “the machine learning model comprises a classifier”; However, these only serve to further limit the abstract idea and hence are nonetheless directed towards fundamentally the same abstract idea as independent claims 1, 10, and 16. However, recitation of an abstract idea is not the end of the 35 U.S.C. 101 analysis. Each of the claims must be analyzed for additional elements that indicate the abstract idea is integrated into a practical application to determine whether the claim is considered to be “directed to” an abstract idea. Step 2A—Prong 2: Claims 1-16 and 18-20 are not integrated into a practical application because the additional elements (i.e. any limitations that are not identified as part of the abstract idea) amount to no more than limitations which: Amount to mere instructions to apply an exception—for example, the recitation of “non- transitory memory”, “machine learning model”, “display device”, “memory”, and “processor” , which amount to merely invoking a computer as a tool to perform the abstract idea, e.g. see FIG. 1-3 and [0006]-[0007], of the present specification, and see further MPEP 2106.05(f); Generally linking the abstract idea to a particular technological environment or field of use, for example, “of non- transitory memory”, “training a machine learning model with the ECG training data triad to produce a trained machine learning model”, “training a machine learning model with the first ECG training data triad and the second ECG training data triad to produce a trained machine learning model”, “display device; a memory storing a machine learning model and instructions; and a processor communicably coupled to the display device and the memory, and when executing the instructions, configured to”, and “using the machine learning model, the machine learning model” , which amounts to limiting the abstract idea to the field of technology/the environment of computers, see MPEP 2106.05(h); and/or Merely acquiring information for further analysis by the system and the particular manner of acquisition is not described or shown to be important, for example, “receive Holter monitor data” , which amounts to insignificant extra-solution activity in the form of mere data gathering because it merely functions tangentially to the main idea of the invention and serves only to bring in the data necessary for the inventions main analysis, see MPEP 2106.05(g). Additionally, dependent claims 2-9, 11-15, and 18-20 include other limitations, but as stated above, the limitations recited by these claims do not include any additional elements beyond those already recited in independent claims 1, 10, and 16, and hence also do not integrate the aforementioned abstract idea into a practical application. Step 2B: The claims do not include additional elements (i.e., “non- transitory memory”, “machine learning model”, “display device”, “memory” ) that are sufficient to amount to “significantly more” than the judicial exception because the additional elements (i.e. the elements other than the abstract idea), as stated above, are directed towards no more than limitations that amount to mere instructions to apply the exception, and/or generally link the abstract idea to a particular technological environment or field of use, which even when reevaluated under the considerations of Step 2B of the analysis, do not amount to “significantly more” than the abstract idea. Dependent claims 2-9, 11-15, and 18-20 include other limitations, but none of these limitations are deemed significantly more than the abstract idea because, as stated above, the aforementioned dependent claims do not recite any additional elements not already recited in independent claims 1, 10, and 16, and hence do not amount to “significantly more” than the abstract idea. Additionally, the additional elements (i.e., “receive Holter monitor data” ), add extra solution activity, which comprises limitations which amount to elements that have been recognized as well-understood, routine, and conventional activity in a particular field as demonstrated by: Relevant court decisions (See MPEP 2106.05(d)(II)): Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014) (“Unlike the claims in Ultramercial, the claims at issue here specify how interactions with the Internet are manipulated to yield a desired result‐‐a result that overrides the routine and conventional sequence of events ordinarily triggered by the click of a hyperlink.” (emphasis added)). Thus, taken alone, the additional elements do not amount to significantly more than the abstract idea identified above. Furthermore, looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually, and there is no indication that the combination of elements improves the functioning of a computer or improves any other technology, and their collective functions merely provide conventional computer implementation. Therefore, whether taken individually or as an ordered combination, claims 1-16 and 18-20 are nonetheless rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter. Response to Arguments 07-37 AIA Applicant's arguments filed 12/29/2025 have been fully considered but they are not persuasive. Regarding the 35 U.S.C. 101 Rejection, Applicant argues the claims are not directed to an abstract idea because claim 1 provides a technical improvement in the field of cardiac monitoring by analyzing large quantities of data (i.e., heartbeats). Examiner respectfully disagrees. MPEP 2106.02(a)(2) ascertains that data processing or analysis, regardless of the quantity of data still recites an abstract idea (See also Electric Power Group v. Alstom, S.A., 830 F.3d 1350, 1353-54, 119 USPQ2d 1739, 1741-42 (Fed. Cir. 2016)) . Applicant also argues the limitations of “training a machine learning model with the ECG training data triad comprising a first beat, a second beat, and a similarity label for the first beat and the second beat that is set based on the DTW distance between the first beat and the second beat to produce a trained machine learning model” provides a technological improvement by its ability to cluster large amount of data (ECG beats). Examiner respectfully disagrees. As stated above the MPEP is clear in that using computer tools (i.e., a machine learning model) to analyze data (i.e., ECG heartbeats), again regardless of amount of data, is not a technological improvement (See MPEP 2106.05(f) “The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words “apply it”. See Electric Power Group, LLC v. Alstom, S.A., 830 F.3d 1350, 1356, 119 USPQ2d 1739, 1743-44 (Fed. Cir. 2016); Intellectual Ventures I v. Symantec, 838 F.3d 1307, 1327, 120 USPQ2d 1353, 1366 (Fed. Cir. 2016); Internet Patents Corp. v. Active Network, Inc., 790 F.3d 1343, 1348, 115 USPQ2d 1414, 1417 (Fed. Cir. 2015)”. Applicant’s supposed technological improvement is not eligible for the same reasons as Intellectual Ventures I v. Capital One Fin. Corp., 850 F.3d 1332, 121 USPQ2d 1940 (Fed. Cir. 2017). It was stated that “the steps in the claims described “the creation of a dynamic document based upon ‘management record types’ and ‘primary record types.’” 850 F.3d at 1339-40; 121 USPQ2d at 1945-46. The claims were found to be directed to the abstract idea of “collecting, displaying, and manipulating data.” 850 F.3d at 1340; 121 USPQ2d at 1946. In addition to the abstract idea, the claims also recited the additional element of modifying the underlying XML document in response to modifications made in the dynamic document. 850 F.3d at 1342; 121 USPQ2d at 1947-48. Although the claims purported to modify the underlying XML document in response to modifications made in the dynamic document, nothing in the claims indicated what specific steps were undertaken other than merely using the abstract idea in the context of XML documents. The court thus held the claims ineligible, because the additional limitations provided only a result-oriented solution and lacked details as to how the computer performed the modificati ons, which was equivalent to the words “apply it”. 850 F.3d at 1341-42; 121 USPQ2d at 1947-48 (citing Electric Power Group., 830 F.3d at 1356, 1356, USPQ2d at 1743-44 (cautioning against claims “so result focused, so functional, as to effectively cover any solution to an identified problem”))”. Applicant also argues the technological improvement is analogous to the patent-eligible improvement recognized in the recent Appeals Review Panel Decision on Request for Rehearing in U.S. Patent No. 16/319,040 (hereinafter 16/319,040). Examiner respectfully disagrees. The current application is very high level and does not perform the same functions as recited in 16/319,040. The claims in 16/319,040 had a method for continual learning, more specifically update a model while still preserving prior parameters/learned tasks. This was shown to be a technical improvement to machine learning. Additionally, although both Desjardin and the current application both recite training a machine learning model, Desjardin addresses “catastrophic forgetting”. The current application does not perform these same functions and is recited a high level that it amounts to applying the abstract idea to the additional elements. Applicant argues the previous Office Action did not properly evaluate claim 1 because the “training a machine learning model with the ECG training data triad to produce a trained machine learning model”, which allegedly recited an abstract idea, was not analyzed under Prong 2A by being incorporated into a practical application. Additionally, Applicant argues these limitations as not properly analyzed under Step 2B in order to determine if this limitation amounted to significantly more than the abstract idea. Examiner respectfully disagrees. As shown above, the additional elements are recited a high level and amount to generic computer tools. The additional elements also are being applied to the abstract idea, which is shown to not be an improvement (See MPEP 2106.05(b): “Merely adding a generic computer, generic computer components, or a programmed computer to perform generic computer functions does not automatically overcome an eligibility rejection. Alice Corp. Pty. Ltd. v. CLS Bank Int’l, 573 U.S. 208, 223-24, 110 USPQ2d 1976, 1983-84 (2014). See In re Alappat , 33 F.3d 1526, 1545, 31 USPQ2d 1545, 1558 (Fed. Cir. 1994); In re Bilski , 545 F.3d 943, 88 USPQ2d 1385 (Fed. Cir. 2008)” and MPEP 2106.05(f): “The Court found that the recitation of the computer in the claim amounted to mere instructions to apply the abstract idea on a generic computer. 573 U.S. at 225-26, 110 USPQ2d at 1984”). Even under Step 2B, the additional elements alone or in combination do not amount to significantly more (see MPEP 2106.05(f): “implementing an abstract idea on a generic computer, does not integrate the abstract idea into a practical application in Step 2A Prong Two or add significantly more in Step 2B, similar to how the recitation of the computer in the claim in Alice amounted to mere instructions to apply the abstract idea of intermediated settlement on a generic computer. For more information on formulating a subject matter eligibility rejection. See MPEP § 2106.07(a) ”). Applicant argues the claims should be evaluated under the guidelines set for in the USPTO memorandum issued on 08/04/2025 by Charles Kim, Deputy Commissioner for Patents (hereinafter the Memo). Examiner respectfully disagrees. Even though the Memo is not law, under its recommendations, the claims still recite an abstract idea, as person, persons, or person with computer tools can perform the functions of selecting, setting, storing, determining, training, produce, receive, classify, and display (see MPEP 2106.04(a)(2) “the sub-groupings encompass both activity of a single person (for example, a person following a set of instructions or a person signing a contract online) and activity that involves multiple people (such as a commercial interaction), and thus, certain activity between a person and a computer (for example a method of anonymous loan shopping that a person conducts using a mobile phone) may fall within the “certain methods of organizing human activity” grouping”). As stated above the addition elements (i.e., machine learning model, processor, memory, etc.) are recite a high level and are being applied to the abstract idea., which does not integrate the abstract idea into a practical application under Prong 2 or amount to significantly more under Step 2B. Applicant argues the claims recite a particular solution by improving cardiac monitoring via ECG similarity analysis. Examiner respectfully disagrees. MPEP 2106.05(f) states “Use of a computer or other machinery in its ordinary capacity for economic or other tasks ( e.g., to receive, store, or transmit data) or simply adding a general-purpose computer or computer components after the fact to an abstract idea ( e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Similarly, “claiming the improved speed or efficiency inherent with applying the abstract idea on a computer” does not integrate a judicial exception into a practical application or provide an inventive concept. Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015)”. Using the machine learning model to perform the ECG analysis is recited a high level and does not integrate the abstract idea into a practical application or provide significantly more. Applicant argue the claims are similar to Example #39 and #47. Examiner respectfully disagrees. Example #39 is directed to a method of training a neural network for facial detection, which is not the same as the instant application’s technology of monitoring ECG data. Even more, Example #39 was not eligible because it recited “training the neural network in a first stage using the first training set”, but because the claim did not recite an abstract idea. The current application does recite an abstract idea. Additionally, the claims are not similar to the claims in Example #47. It is not similar to claim 1 of Example #47 because Example claim 1 does not recite an abstract idea because it is directed to an artificial neural network comprising a plurality of neurons and synaptic circuits. The application claims are also not similar to claim 3 of Example #47 because while the claim recites an abstract idea, “the disclosed system detects network intrusions and takes real-time remedial actions, including dropping suspicious packets and blocking traffic from suspicious source addresses. The background section further explains that the disclosed system enhances security by acting in real time to proactively prevent network intrusions. The claimed invention in the example reflects this improvement in the technical field of network intrusion detection. Steps (d)-(f) provide for improved network security using the information from the detection to enhance security by taking proactive measures to remediate the danger by detecting the source address associated with the potentially malicious packets. Specifically, the claim reflects the improvement in step (d), dropping potentially malicious packets in step (e), and blocking future traffic from the source address in step (f)”. These features are not similar to the instant application’s claims in any way. Therefore, the claims are not 101 eligible. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to RACHAEL SOJIN STONE whose telephone number is (571)272-8798. The examiner can normally be reached Monday-Friday 7 AM - 7 PM (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, Peter Choi can be reached at (469) 295-9171. 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. 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If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /R.S.S./Examiner, Art Unit 3681 /PETER H CHOI/Supervisory Patent Examiner, Art Unit 3681 Application/Control Number: 18/167,693 Page 2 Art Unit: 3681 Application/Control Number: 18/167,693 Page 3 Art Unit: 3681 Application/Control Number: 18/167,693 Page 4 Art Unit: 3681 Application/Control Number: 18/167,693 Page 5 Art Unit: 3681 Application/Control Number: 18/167,693 Page 6 Art Unit: 3681 Application/Control Number: 18/167,693 Page 7 Art Unit: 3681 Application/Control Number: 18/167,693 Page 8 Art Unit: 3681 Application/Control Number: 18/167,693 Page 9 Art Unit: 3681 Application/Control Number: 18/167,693 Page 10 Art Unit: 3681 Application/Control Number: 18/167,693 Page 11 Art Unit: 3681 Application/Control Number: 18/167,693 Page 12 Art Unit: 3681 Application/Control Number: 18/167,693 Page 13 Art Unit: 3681
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