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 .
Response to Arguments
Applicant’s arguments in combination with amendments, see Remarks and claims, filed 11/03/2025, with respect to 35 USC 101 rejections have been fully considered but are they are not persuasive. Beginning on page 2, the applicant argues that the independent claims recite various limitations such as, “one or more leads of an ECG device for acquiring electrical signals, and a digital connection between the ECG device and a computational processor [] to generate the ECG data and waveforms, and to computer []”. These arguments are fully considered but are not persuasive. Under the broadest reasonable interpretation, the claim as recited requires “computing, a risk that the individual will experience a cardiovascular disease event in the future”. The claim recites concepts performed in the human mind (including an observation, evaluation, judgment, opinion). Thus, an abstract idea is involved.
The applicant argues that the risk that the individual will experience […] cannot be performed without acquisition of the electrical signal. This argument is fully considered but is not persuasive. The 101 analysis is performed by first determining whether an abstract idea is recited, then the additional elements are considered to determine whether they amount to significantly more than the abstract idea. Here, the mentioned limitations are considered to be recited at a high level of generality and are merely data gathering/processing which are considered to be mere extra-solution activity. The limitations considered both individually and as an ordered combination do not amount to significantly more than the abstract idea. In other words, a doctor can view the data collected using any generic device to determine a risk of a cardiovascular disease event in the future. This is the definition of an observation, evaluation, judgment, opinion which is an abstract idea. The claim does not provide any details regarding ECG device, computational processing system, one or more leads that would suggest these limitations are the novelty of the system or in any way unique. Therefore, the mentioned limitations are simply appending well-understood, routine and conventional activities previously known in the industry, specified at a high level of generality, to the judicial exception, e.g., a claim to an abstract idea requiring no more than a generic computer to perform generic computer functions that are well-understood, routine and conventional activities previously known in the industry (see Electric Power Group, 830 F.3d 1350 (Fed. Cir. 2016); Alice Corp. v. CLS Bank Int’I, 110 USPQ2d 1976 (2014)).
The claim recites using a “trained computational model” without providing any details regarding the model is created or operated. Under its broadest reasonable interpretation, the plain meaning of “utilizes” and “compute” as recited in “utilizes the one or more electrocardiogram waveforms to compute the risk of the cardiovascular disease event” []” merely encompasses mental observation or evaluation and to continue the observation and/or evaluation as mentioned above. Furthermore, should the model require further training the model, such would represent mathematical calculations for iteratively adjusting the model.
The applicant argues the improvement of the recited system. This argument is fully considered but is not persuasive. To have a technological improvement, the additional elements need to be improved. Here, the improvement is provided in the abstract idea. The court in, Genetic Technologies Limited v. Merial LLC (Fed Cir., 2016) tells us that the inventive concept of step 2 of the Alice/Mayo analysis cannot be supplied by the abstract idea.
For at least the reasons recited above, the 101 rejection is maintained.
Applicant’s arguments in combination with amendments, see Remarks and claims, filed 11/03/2025, with respect to 35 USC 101 rejections have been fully considered and are persuasive. Beginning on page 4, the applicant argues that Victor does not provide a predicting a risk of a future cardiovascular event. This argument is fully considered. However, Victor in paragraph 0032 discloses that the computerized system can further analyze the ECG data to determine a risk score indicative of future risk to the cardiac event for display. However, to expedite prosecution, the applicant’s arguments are considered persuasive. Therefore, the 102 rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Victor (previously presented) in view of US Pat Pub 20210076960 to Fornwalt et al.
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 1-20 are rejected under 35 U.S.C. 101 because of the following analysis:
1 – statutory category: Claims 1-12 recite a series of steps and therefore, falls under the statutory category of being a process. See MPEP 2106.03. Claims 13-20 recite a system, and therefore, falls under the statutory category of being a thing or products. See MPEP 2106.03.
2A – Prong 1: The independent claims 1 and 13 recite a judicial exception by reciting the limitations of “obtain electrocardiogram data”, “predict a risk that the individual will experience a cardiovascular disease event in the future”, “compute the risk of the cardiovascular disease event, wherein the risk to be computed is a percent likelihood that the individual will experience the cardiovascular disease event within a future timeframe”. These limitations, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in mind or by a person using a pen and paper and mathematics. Therefore, an abstract idea is involved.
It is further noted that the act of inputting training data into a learning model, to train or use a model, falls under the judicial exception of mathematical calculations. Additionally or alternatively, the training of the learning model by inputting training data (see claim 2), and adjusting the model accordingly additionally represents mathematical calculations or mental observations or evaluation to iteratively adjust the model.
2A – Prong 2: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements when considered both individually and as an ordered combination do not amount to significantly more than the abstract idea. The independent claims 1 and 13 recite the additional limitations of “computational processing system”, “electrocardiogram device”, “one or more leads”, “memory”, “processor”, etc. The mentioned limitations are recited at a high level of generality and is recited as performing generic computer functions. i.e., data gathering/processing and are extra-solution activity. The elements amount to mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.04(d) and 2106.05(f)). Accordingly, each of the additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limitations on practicing the abstract idea.
2B: The emphasized elements cited above do not amount to significantly more than the judicial exception because these limitations are simply appending well-understood, routine and conventional activities previously known in the industry, specified at a high level of generality, to the judicial exception, e.g., a claim to an abstract idea requiring no more than a generic computer to perform generic computer functions that are well-understood, routine and conventional activities previously known in the industry (see Electric Power Group, 830 F.3d 1350 (Fed. Cir. 2016); Alice Corp. v. CLS Bank Int’I, 110 USPQ2d 1976 (2014)).
In view of the above, the additional elements individually do not amount to significantly more than the above-judicial exception (the abstract idea). Looking at the limitations as an ordered combination (that is, as a whole) adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer, for example, or improves any other technology. There is no indication that the combination of elements permits automation of specific tasks that previously could not be automated. There is no indication that the combination of elements includes a particular solution to a computer-based problem or a particular way to achieve a desired computer-based outcome. Rather, the collective functions of the claimed invention merely provide conventional computer implementation, i.e., the computer is simply a tool to perform the process. Simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, e.g., a claim to an abstract idea requiring no more than a generic computer to perform generic computer functions that are well-understood, routine and conventional activities previously known to the industry, as discussed in Alice Corp., 573 U.S. at 225, 110 USPQ2d at 1984 (see MPEP § 2106.05(d)).
Claims 2-12 and 14-20 depend on claims 1 and 13. The mentioned dependent claims recite the same abstract idea as the independent claims. Furthermore, these claims only contain recitations that further limit the abstract idea (that is, the claims only recite limitations that further limit the mental process). For example, the dependent claim recites the limitations “estimating a risk [] combining the estimated risk”, “administering a statin”, “halting administering a statin”, “performing a clinical intervention”, etc., are recited at a high level of generality and is recited as performing generic computer functions. i.e., data processing and/or acts performed by a medical care taker based on the results of an abstract idea. The elements amount to mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.04(d) and 2106.05(f)).
The additional elements individually do not amount to significantly more than the above-judicial exception (the abstract idea). Looking at the limitations as an ordered combination (that is, as a whole) adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer, for example, or improves any other technology. There is no indication that the combination of elements permits automation of specific tasks that previously could not be automated. There is no indication that the combination of elements includes a particular solution to a computer-based problem or a particular way to achieve a desired computer-based outcome. Rather, the collective functions of the claimed invention merely provide conventional computer implementation, i.e., the computer is simply a tool to perform the process.
Thus, claims 1-20 are directed to an abstract idea and are therefore rejected.
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.
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
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) 1-7, 11, 13—20 is/are rejected under 35 U.S.C. 103 as being unpatentable over US pat pub no. 20220095982 granted to Victor et al. (hereinafter “Victor”) in view of 20210076960 to Fornwalt et al. (hereinafter “Fornwalt”).
Regarding claim 1. Victor discloses a computational method for predicting a future cardiovascular event (abstract, para 0017, 0085, etc.), using an electrocardiogram system comprising an electrocardiogram device and a computational processing system (para 0087-0088 “system device 14”) comprising: acquiring electrical signals of an individual using a set of one or more leads of the electrocardiogram device (para 0088 “sensing device 13 may be one or more electrodes that may be disposed on one or more leads [] 12-lead arrangement”); receiving, using the computational processing system, the electrical signals of the individual, wherein the computational processing system is in communication with the electrocardiogram device (para 0087-0088 “Sensing device 13 may be in electrical communication with system device 14 running the ECG application 29”, figs 2-3); generating, using the computational processing system, electrocardiogram data from the electrical signal of the individual (e.g., para 0088, “ECG sensing device 13 is designed to sense the electrical activity of the heart for generating ECG data”), wherein the electrocardiogram data comprises one or more electrocardiogram waveforms (e.g., para 0088 “ECG data”, para 0101, 0111-0120 discussing various waves of the ECG data, fig 5a-6b); and computing, using the computational processing system and a trained computational model, a risk that the individual will experience a cardiovascular disease event in the future (e.g., para 0032, 0085 “analyzing the ECG data using machine learning algorithms to detect and/or predict cardiac events”, 0086), wherein the trained computational model utilizes the one or more electrocardiogram waveforms to predict a likelihood of the cardiovascular disease event (para 0032, 0037-0038 “determine a probability” and “confidence score”) but fails to explicitly disclose wherein the electrocardiogram data is utilized as input into the trained computational model, wherein the trained computational model []compute the risk of the cardiovascular disease event, wherein the risk to be computed is a percent likelihood that the individual will experience the cardiovascular disease event within a future timeframe.
Fornwalt, from a similar field of endeavor, teaches generating a model to predict future cardiovascular risk based on collected ECG data to help prevent the future adverse condition (abstract, para 0012-0014, 0186, 0196-0197 etc.). It would have been obvious before the effective filing date of the claimed invention to modify the disclosure of Victor with the teachings of Fornwalt, because doing so would allow for using the details of the model to provide the predictable result of predicting future risk (abstract, para 0011-0014).
Regarding claim 2. Victor as modified by Fornwalt renders obvious the method of claim 1, wherein the trained computational model is trained from electrocardiogram data obtained from a cohort of individuals having cardiovascular health records that include a timeline of cardiovascular events after collection of each individual’s electrocardiogram data (para 0024 “algorithm trained from a plurality of ECG data sets from different patients”).
Regarding claim 3. Victor as modified by Fornwalt renders obvious the method of claim 1, wherein the computational model is a deep neural network (DNN), a convolutional neural network (CNN), a recurrent neural network, a long short-term memory (LSTM) network, a kernel ridge regression, or a gradient-boosted random forest decision tree (para 0110, 0125 “neural network may be a convolutional neural network”).
Regarding claim 4. (Currently Amended) Victor as modified by Fornwalt renders obvious the method of claim 1, wherein the future timeframe is trained computational model predicts the risk that the individual will experience a cardiovascular disease event that will occur in more than one year after the acquisition of the electrical signals (Victor para 0032, Fornwalt, para 0015-0016, 0060, 0091, etc.).
Regarding claim 5. (Currently Amended) Victor as modified by Fornwalt renders obvious the method of claim 1, wherein the future timeframe is trained computational model predicts the risk that the individual will experience a cardiovascular disease event that will occur within five years after the acquisition of the electrical signals (Victor para 0032, Fornwalt, para 0015-0016, 0060, 0091, etc.).
Regarding claim 6. (Currently Amended) Victor as modified by Fornwalt renders obvious the method of claim 1, wherein the future timeframe is trained computational model predicts the risk that the individual will experience [[a]] the cardiovascular disease event that will occur within ten years after the acquisition of the electrical signals (Victor para 0032, Fornwalt, para 0015-0016, 0060, 0091, etc.).
Regarding claim 7. Victor as modified by Fornwalt renders obvious the method of claim 1, wherein the cardiovascular event is development of atherosclerotic cardiovascular disease (ASCVD), infarction, heart failure, non-lethal heart attack, lethal heart attack, stroke, sudden cardiac death, or a combination thereof (para 0123 “infarction”, 0194, 0212 “cardiac events”).
Regarding claim 11. Victor as modified by Fornwalt renders obvious the method of claim 1 further comprising: performing a clinical intervention, clinical monitoring, or a treatment based on a future cardiovascular disease event prediction (para 0192 “a notification may include a treatment recommendation Information displayed and provided by the ECG platform may have to be reviewed and/or released by a healthcare professional”).
Regarding claim 13. Victor discloses an electrocardiogram system for predicting future cardiovascular events of patients (abstract, para 0017, 0085, etc.), the system comprising: an electrocardiogram device comprising a set of one or more leads capable of acquiring electrical signals of an individual (para 0017, 0036, 0088, 0105, 0108-0109, etc., “one or more ECG leads”); and a computational processing system in communication with the electrocardiogram device (para 0088-0089, fig. 2), the computational processing system comprising: a memory (para 0099 “memory”) comprising: an application for performing an electrocardiogram (para 0088-0089, fig. 3A); and an application comprising a trained computational model for predicting future cardiovascular events (para 0101); and a processor (para 0094), wherein the application for performing an electrocardiogram directs the processor to: collect electrical signals of an individual (e.g., para 0088, “ECG sensing device 13 is designed to sense the electrical activity of the heart for generating ECG data”); and generate electrocardiogram data, wherein the electrocardiogram data comprises a set of one or more electrocardiogram waveforms (e.g., para 0088 “ECG data”, para 0101, 0111-0120 discussing various waves of the ECG data, fig 5a-6b); wherein the application comprising a trained computational model for predicting future cardiovascular events directs the processor to: obtain the electrocardiogram data; and predict a risk that an individual will experience a cardiovascular disease event in the future utilizing the set of one or more electrocardiogram waveforms (e.g., para 0085 “analyzing the ECG data using machine learning algorithms to detect and/or predict cardiac events”, 0086; para 0037-0038 “determine a probability” and “confidence score”) but fails to explicitly disclose wherein the electrocardiogram data is utilized as input into the trained computational model, wherein the trained computational model []compute the risk of the cardiovascular disease event, wherein the risk to be computed is a percent likelihood that the individual will experience the cardiovascular disease event within a future timeframe.
Fornwalt, from a similar field of endeavor, teaches generating a model to predict future cardiovascular risk based on collected ECG data to help prevent the future adverse condition (abstract, para 0012-0014, 0186, 0196-0197 etc.). It would have been obvious before the effective filing date of the claimed invention to modify the disclosure of Victor with the teachings of Fornwalt, because doing so would allow for using the details of the model to provide the predictable result of predicting future risk (abstract, para 0011-0014).
Regarding claim 14. Victor as modified by Fornwalt renders obvious the system of claim 13, wherein the trained computational model is trained from electrocardiogram data obtained from a cohort of individuals having cardiovascular health records that include a timeline of cardiovascular events after collection of each individual’s electrocardiogram data (para 0024 “algorithm trained from a plurality of ECG data sets from different patients”).
Regarding claim 15. (Currently Amended) Victor as modified by Fornwalt renders obvious the system of claim 13, wherein the future timeframe is trained computational model predicts the risk that the individual will experience a cardiovascular disease event that will occur in more than one year after the acquisition of the electrical signals (Victor para 0032, Fornwalt, para 0015-0016, 0060, 0091, etc.).
Regarding claim 16. (Currently Amended) Victor as modified by Fornwalt renders obvious the system of claim 13, wherein the future timeframe is trained computational model predicts the risk that the individual will experience a cardiovascular disease event that will occur within five years after the acquisition of the electrical signals (Victor para 0032, Fornwalt, para 0015-0016, 0060, 0091, etc.).
Regarding claim 17. Victor as modified by Fornwalt renders obvious the system of claim 13, wherein the cardiovascular event is development of atherosclerotic cardiovascular disease (ASCVD), infarction, heart failure, non-lethal heart attack, lethal heart attack, stroke, sudden cardiac death, or a combination thereof (para 0123 “infarction”, 0194, 0212 “cardiac events”).
Regarding claim 18. Victor as modified by Fornwalt renders obvious the system of claim 13, wherein the computational processing system is housed within a computing device that is in direct association the electrocardiogram device (para 0088 “Sensing device 13 may be placed on the surface of the chest of a patient and/or limbs of a patient and is in electrical communication with system device 14; “ECG generation such as the Apple Watch available from Apple”, and “system device 14 is one or more computing device (e.g., laptop, desktop, tablet, smartphone, smartwatch, etc.); it is understood that the ECG device and the device 14 are both the smartwatch; it is further noted that the claim only requires the parts to be “in direct association”, under its BRI, that could include mere electrical communication). It is also noted that mere making parts integral would be a matter of design choice where there is a lack of criticality. See In re Larson, 340 F.2d 965, 968, 144 USPQ 347, 349 (CCPA 1965) wherein the court has held that the use of a one piece construction instead of the structure disclosed in [the prior art] would be merely a matter of obvious engineering choice.
Regarding claim 19. Victor as modified by Fornwalt renders obvious the system of claim 13, wherein the computational processing system is housed within a computing device that is separate of the electrocardiogram device and obtains the electrocardiogram data via a wireless connection (para 0088 “Sensing device 13 may be placed on the surface of the chest of a patient and/or limbs of a patient and is in electrical communication with system device 14; “ECG generation such as the Apple Watch available from Apple”, and “system device 14 is one or more computing device (e.g., laptop, desktop, tablet, smartphone, smartwatch, etc.); it is understood that the ECG device could be the apple watch while the device 14 is the computer).
It is also noted that mere making parts separate would be a matter of design choice where there is a lack of criticality. See In re Dulberg, 289 F.2d 522, 523, 129 USPQ 348, 349 (CCPA 1961).
Regarding claim 20. Victor as modified by Fornwalt renders obvious the system of claim 13, wherein the electrocardiogram device and the computational processing system is housed within a wearable device (para 0087-0090). It is also noted that mere making parts integral would be a matter of design choice where there is a lack of criticality. See In re Larson, 340 F.2d 965, 968, 144 USPQ 347, 349 (CCPA 1965) wherein the court has held that the use of a one piece construction instead of the structure disclosed in [the prior art] would be merely a matter of obvious engineering choice.
Claim(s) 8-10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Victor as modified by Fornwalt as applied to claims 1-7, 11, 13—20 above, and further in view of US pat pub no. 20200147051 to Oshima et al. (“Oshima”).
Regarding claim 8. (Currently Amended) Victor as modified by Fornwalt renders obvious the method of claim 1, but fails to disclose wherein the cardiovascular event is development of atherosclerotic cardiovascular disease (ASCVD); the method further comprising: estimating, using the computational processing system, a risk of ASCVD of the individual via [[the]] a pooled cohort equation (PCE); and combining, using the computational processor, the estimated risk of ASCVD as estimated by PCE risk with the predicted likelihood that the individual is to develop ASCVD as determined by the trained computational model to yield a combined risk assessment.
Oshima, from a similar field of endeavor, teaches that it is known to use the pooled cohorts equation for determining various risks including atherosclerotic cardiovascular disease (para 0027, 0072, 0188, etc.). It would have been obvious before the effective filing date of the claimed invention to modify the disclosure of Victor as modified by Fornwalt with the known teachings of Oshima, because doing so would allow for the predictable result of estimating future risks (para 0027).
Regarding claim 9. (Original) Victor as modified by Fornwalt and Oshima renders obvious the method of claim 8 further comprising administering a statin to the individual, wherein the individual was estimated to be a low risk of developing ASCVD by PCE and high risk of developing ASCVD by the trained computational model (Oshima, para 0024, etc.).
Regarding claim 10. (Original) The method of claim 8 further comprising halting administering of a statin to the individual, wherein the individual was estimated to be a high risk of developing ASCVD by PCE and low risk of developing ASCVD by the trained computational model (Oshima, para 0029, etc.).
Conclusion
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 nonprovisional extension fee (37 CFR 1.17(a)) 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 mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SANA SAHAND whose telephone number is (571)272-6842. The examiner can normally be reached M-Th 8:30 am -5:30 pm; F 9 am-3 pm.
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, Jennifer S McDonald can be reached at (571) 270- 3061. 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.
/SANA SAHAND/Examiner, Art Unit 3796