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
Continued Examination Under 37 CFR 1.114
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 7/14/2025 has been entered. Claims 1-3, 5-9 and 11-20 are currently pending and under examination.
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, 5-9 and 11-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Claims 1-3, 5-9 and 11-20 is/are drawn a method and an apparatus which is/are a statutory category of invention (Step 1: YES). The claim limitations within independent claims 1 and 16-20 that set forth or describe the abstract idea is/are: “obtaining multiple ECG signals from the multiple ECG signals including digital processing the multiple ECG signals using signal processing to remove interferences including maternal ECG, powerline, and electromyographic signals from within the pregnant woman”, “detect/detecting fetal QRS complexes in the multiple fetal ECG signals”, “calculating at least one fetal vector cardiogram from said multiple fetal ECG signals using the detected fetal QRS complexes”, “provide/providing the fetal vector cardiogram as input to the machine learning classifier configured with the trained parameters, and obtaining a classification for the fetal vector cardiogram, the fetal vector cardiogram being resampled before providing as an input to the machine learning classifier..wherein computing the fetal VCG is preformed….as an input to the machine learning classifier”, “communicating the classification to an operator of the device”, “providing the first and second training set to a machine learning algorithm to obtain trained parameters for the machine learning classifier” and “augmenting the first training set by randomly rotating fetal vector cardiogram…”. The reasons that the limitations is/are considered an abstract idea is/are the following: The limitations of “detecting fetal QRS complexes in the multiple fetal ECG signals”, “calculating at least one vector cardiogram from said multiple fetal ECG signals using the detected fetal QRS complexes”, “obtaining a classification for the fetal vector cardiogram” and “communicating the classification to an operator of the device” is a process directed to a concept relating to organizing or analyzing information in a way that can be performed in human mental work, i.e. under its broadest reasonable interpretation covers performance of the limitation in the mind with the aid of pen and paper but for the recitation of generic computer components. That is, other than reciting “processor configured to” (claims 1 and 19) nothing in the claim element precludes the steps from practically being performed in the mind with the aid of pen and paper. For example but for the “processor configured to” (claims 1 and 19), “detecting fetal QRS complexes in the multiple fetal ECG signals”, “calculating at least one fetal vector cardiogram from said multiple fetal ECG signals using the detected fetal QRS complexes”, “obtaining a classification for the fetal vector cardiogram” and “communicating the classification to an operator of the device” in the context of this claim encompasses the user, with the aid of pen and paper, detecting fetal QRS complexes in the multiple fetal ECG signals, calculating a fetal vector cardiogram and using the fetal vector cardiogram to classify whether congenital heart disease exists and communicating the classification. There is nothing to suggest an undue level of complexity in the detecting, calculating and communicating steps. The specification indicates that a trained sonographer can look for indication of CHD during ultrasound screening using image data and ECG recordings (para. [0004], [0111] of published application US 2020/0214618), therefore a trained person can classify CHD using provided image data and ECG recordings. A human in their mind can make a congenital heart disease determination based on input data including mentally determining if an anomaly is present using input data such image data and ECG recordings. If a claim limitation, under its broadest reasonable interpretation covers a metal process, i.e. performance of the limitation in the mind, but for the recitation of generic computer components, then it falls with the “Mental Processes” grouping of abstract ideas. Accordingly the claims recite an abstract idea. Although not drawn to the same subject matter, the claimed limitation(s) is/are similar to concepts that have been identified as abstract by the courts, such as: collecting information, analyzing it, and reporting certain results of the collection and analysis in Electric Power Group, LLC, v. Alstom, 830 F.3d 1350, 119 U.S.P.Q.2d 1739 (Fed. Cir. 2016), selecting certain information, analyzing it using mathematical techniques, and reporting or displaying the results of the analysis in SAP America Inc. v. Investpic, LLC, 890 F.3d 1016, 126 USPQ2d 1638 (Fed Cir. 2018). Additionally, the limitations of, “obtaining multiple ECG signals from the multiple ECG signals including digital processing the multiple ECG signals using signal processing to remove interferences including maternal ECG, powerline, and electromyographic signals from within the pregnant woman”, “detect/detecting fetal QRS complexes in the multiple fetal ECG signals”, “calculating at least one fetal vector cardiogram from said multiple fetal ECG signals using the detected fetal QRS complexes”, “provide/providing the fetal vector cardiogram as input to the machine learning classifier configured with the trained parameters, and “obtaining a classification for the fetal vector cardiogram, the fetal vector cardiogram being resampled before providing as an input to the machine learning classifier, wherein computing the fetal VCG is preformed….as an input to the machine learning classifier”, “providing the first and second training set to a machine learning algorithm to obtain trained parameters for the machine learning classifier” (claim 18) and “augmenting the first training set by randomly rotating fetal vector cardiogram…”, cover an abstract idea that is part of mathematical concepts. “A mathematical formula or equation will be considered as falling with the ‘mathematical concepts” grouping....”. October 2019 Update: Subject Matter Eligibility, “[T]here are instances where a formula or equation is written in text format that should also be considered as falling within this grouping.” /d. at Il. A. ii. See for example, Diamond v. Diehr, 450 U.S. 175, 177 n.2, 179 n.5, 191-92 (1981) or Parker v. Flook 437 U.S. 584, 585, 198 USPQ 193, 195 (1978) (calculating a number representing an alarm limit using a mathematical formula). The claimed steps of “obtaining multiple ECG signals from the multiple ECG signals including digital processing the multiple ECG signals using signal processing to remove interferences including maternal ECG, powerline, and electromyographic signals from within the pregnant woman”, “detect/detecting fetal QRS complexes in the multiple fetal ECG signals”, “calculating at least one fetal vector cardiogram from said multiple fetal ECG signals using the detected fetal QRS complexes”, “provide/providing the fetal vector cardiogram as input to the machine learning classifier configured with the trained parameters, and obtaining a classification for the fetal vector cardiogram, the fetal vector cardiogram being resampled before providing as an input to the machine learning classifier, wherein computing the fetal VCG is preformed….as an input to the machine learning classifier”, “providing the first and second training set to a machine learning algorithm to obtain trained parameters for the machine learning classifier” (claim 18) and “augmenting the first training set by randomly rotating fetal vector cardiogram…” recite a mathematical concept (i.e., mathematical formulas or equations, and mathematical calculations). The claimed steps recite performing a mathematical formula or equation, i.e. a machine learning classifier trained using trained parameters obtained using a machine learning algorithm to determine the classification of congestive heart failure, augmenting the first training set by randomly rotating fetal vector cardiogram which can be performed by introducing Gaussian-distributed noise as disclosed within the specification (e.g. para. [0162] of published application US 2020/0214618) and/or using a machine learning algorithm “a series of mathematical calculations” to obtain trained parameters for a machine learning classifier. If a claim limitation, under its broadest reasonable interpretation covers a mathematical formula or equation but for the recitation of generic computer components, then it falls within the “Mathematical Concepts” grouping of abstract ideas. Accordingly the claims recite an abstract idea. Although not drawn to the same subject matter, the claimed limitation(s) is/are similar to concepts that have been identified as abstract by the courts, such as: a formula for computing an alarm limit in Parker v. Flook 487 U.S. 584, 585, 198 USPQ 193, 195 (1978), the Arrhenius equation in Diamond v. Diehr, 450 U.S. 175, 177 n.2, 179 n.5, 191-92 (1981). Thus, the claim(s) are directed to a judicial exception and fall squarely within the realm of "abstract ideas," which is a patent-ineligible concept. (Step 2A: Prong One YES).
Analyzing the claim as whole for an inventive concept, the claim does not include additional elements/steps that are sufficient to amount to significantly more than the judicial exception. The additionally recited element(s) appended to the abstract idea in claims 1 and 16-20 include: “a signal input configured to receive multiple ECG signals from multiple electrodes, said electrodes being arranged on the abdomen of a pregnant woman”, “receiving a first training set…and a corresponding second training set…” (claims 16,18 and 20), “a storage for storing trained parameters for a machine learning classifier for classifying a fetal vector cardiogram as having a CHD or not….”, “a processor configured to”, “CRM…to cause a processor system” (claims 19-20). The additional elements of “a signal input configured to receive/receiving multiple ECG signal from multiple electrodes, said electrodes arranged on the abdomen of a pregnant woman”, “receiving a first training set…and a corresponding second training set…”, merely: add insignificant extra-solution activity, reciting “a signal input configured to receive multiple ECG signal from multiple electrodes, said electrodes arranged on the abdomen of a pregnant woman”, “receiving a first training set…and a corresponding second training set…”,,is recited at a high level of generality (i.e. as a general means of receiving electrocardiogram signals) and is merely nominally, insignificantly or tangentially related to the performance of the steps, i.e. amounts to mere data gathering, which is a form of insignificant extra-solution activity (pre-solution activity. All uses of the recited judicial exception require the pre-solution activity of data gathering. As discussed above with respect to integration of abstract idea into a practical, the additional element of “a storage for storing trained parameters for a machine learning classifier for classifying a fetal vector cardiogram as having a CHD or not….”, using “a processor configured to” perform the “obtain”, “provide” and “communicate” steps and [CRM] representing instructions to cause a processor system” amount to no more than mere instruction to apply the exception using generic computer components. The “storage”, “processor” and [CRM] representing instructions to cause a processor system…” are purely general-purpose computer components recited as carrying out the general-purpose computer functions of storing data, processing data and displaying to enable the abstract process. As such, this/these recitation(s) is/are nothing more than nominal recitation(s) of a computer covering an abstract concept. See Bancorp Servs. v. Sun Life Assurance Co., 687 F.3d 1266, 103 USPQ2d 1425 (Fed. Circ. 2012). See also Mayo Collaborative Services v. Prometheus Laboratories Inc., 101 USPQ2d 1961 (U.S. 2012), which establishes that a claim cannot simply state the abstract idea and add the words "apply it”. Therefore, the additional elements, alone or in combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea (Step 2A, Prong Two, NO).
Claims 1 and 16-20 do not include additional elements, alone or in combination, that are sufficient to amount to significantly more than the judicial exception (i.e., an inventive concept) for the same reasons as described above. e.g., all elements are directed to pre-solution activity carried out using well-understood routine, conventional activities previously known to the industry and amount to elements that have been recognized as well-understood, routine and conventional activity in particular fields, e.g. receiving or transmitting data over a network, Symantec, see MPEP 2106.05(d)(II) or purely general-purpose computer components recited as carrying out the general-purpose computer functions of storing data, processing data and displaying to enable the abstract process, the additional elements do not amount to significantly more than the above-identified judicial exception(s). Further, utilizing multiple electrodes arranged on an abdomen of a pregnant women for obtaining multiple ECG signals was well- understood routine, conventional activities previously known to the industry and amount to elements that have been recognized as well-understood, routine and conventional activity in particular fields as evidence by US 2017/0055866 to Vullings et al. (e.g. para. [0015], [0019], [0040]) or US 2016/0270670 to Oz et al. (e.g. Fig. 4 para. [0004], [0008]). Further, regarding the processor, applicant discloses that the method may be implemented on a computer as a computer implemented method or in dedicated hardware or in a combination of both (e.g. para. [0043]-[0044], [0187]-[0188] of published application US 2020/0214618), therefore the recited “storage”, “processor” and “[CRM] representing instructions to cause a processor system..” are nothing more than purely general-purpose computer components recited as carrying out the general-purpose computer functions of storing data, processing data and displaying to enable the abstract process, Similarly, when considered as an ordered combination, the additional components/steps of the claim(s) add nothing that is not already present when the steps are considered separately (Step 2B: NO). The claims are not patent eligible.
Claim(s) 2-3, 5-9 and 11-15 depend directly or indirectly from claim(s) 1. Therefore, the dependent claims rely upon the same abstract idea as the independent claim(s), as set forth above. Additionally, the dependent claims do nothing more than further limiting the abstract idea while failing to qualify as "significantly more", and the specificity of an abstract idea does not make it any "less abstract” as it is still directed to concepts relating to organizing or analyzing information in a way that can be performed mentally or is analogous to human mental work subject matter. Therefore, the dependent claim(s) are also not patent eligible for the reasons discussed above. Claim(s) 2-3, 5-9,12-14 fail(s) to provide significantly more, when considered as an ordered combination, as it/they merely provide further limitation regarding the abstract idea, which can still nonetheless be considered mental processes, i.e. performed in the mind with the aid of pen and paper and/or mathematical concepts. Claim(s) 11, 15 fail(s) to provide significantly more, when considered as an ordered combination, as it/they merely provide further limitations regarding data that is received, which is merely nominally, insignificantly or tangentially related to the performance of the steps, i.e. amounts to mere data gathering, which is a form of insignificant extra-solution activity (pre-solution activity. All uses of the recited judicial exception require the pre-solution activity of data gathering.
The instantly rejected claim(s) are therefore not drawn to eligible subject matter as they are directed to an abstract idea without significantly more. In the interest of advancing prosecution, the examiner suggests: providing evidence, for example, delineating how the abstract idea and/or additional elements appended to the abstract idea results in an improvement to the technology/technical field, which can show eligibility and/or adding a practical application of the claimed method outside of the computer (e.g. treating a patient). See MPEP § 716.01(c) for examples of providing evidence supported by an appropriate affidavit or declaration. For additional guidance, applicant is directed generally to MPEP §2106.
Response to Arguments
Applicant's arguments filed 7/14/2025 have been fully considered but they are not persuasive. It is noted that the rejection has been updated to show how the amended claim language is being rejected.
3.1 The Claims are not Directed to a Judicial Exception (p. 9-13 of response filed 7/14/2025).
Applicant argues that “linking the abstract qualities of how Congenital Heart Disease affects changes in fetal electrocardiograms to a practical device that processes a maternal electrocardiogram into actionable information ensures the patent-eligibility of the claimed subject matter. This position is supported both by the MPEP and the courts. As noted by MPEP § 2107.01(I)(A), when an applicant correlates a “specific biological activity” (aberrant electrocardiac activity) to a “disease condition” (Congenital Heart Disease), then this is sufficient to find that the claim has specific utility and thus is a practical application.”, see p. 9-10. This is not persuasive. Applicant points to MPEP 2107.04(I)(A) which provides compliance with the utility requirement of 35 USC 101 not subject matter eligibility which is provided within MPEP 2106. As stated within MPEP 2106 (I) “Lastly, eligibility should not be evaluated based on whether the claimed invention has utility, because “[u]tility is not the test for patent-eligible subject matter.” Genetic Techs. Ltd. v. Merial LLC, 818 F.3d 1369, 1380, 118 USPQ2d 1541, 1548 (Fed. Cir. 2016).”
Applicant argues “Analogous to the claims at issue in Cardionet, the present claims recite a structured arrangement comprising: ° Signal-acquisition hardware (multiple electrodes on the maternal abdomen), ° Advanced signal processing techniques (removing interferences from maternal ECG, fetal QRS detection, down sampling of fetal VCG), ° Machine learning classifier employing specifically trained parameters to classify fetal heart conditions, and ° Communication of the clinical diagnosis to the operator. As in Cardionet, the present claims should be viewed as an ‘improved cardiac monitoring’, i.e., a practical application, satisfying Alice’s first prong. Critically, the present claim explicitly recites that computing the fetal VCG is performed on a higher sample-rate, while the fetal vector cardiogram is down-sampled to a lower sample-rate before providing it as an input to the machine learning classifier. These specific processing steps demonstrate integration of the claimed invention into a practical and technologically meaningful application.”, see pgs. 10-12. This is not persuasive. Applicant argues that the signal acquisition hardware, advanced signal processing techniques, machine learning classifier and communicating results back to the operator add “significantly more”. As stated above within the rejection, the signal processing, machine learning classifier and communicating results back to the operator are all part of the judicial exception itself they are not “additional elements”. As stated in the MPEP “An inventive concept “cannot be furnished by the unpatentable law of nature (or natural phenomenon or abstract idea) itself.” It is “additional elements” that are evaluated to determine whether the judicial exception amount to an inventive concept, see MPEP 2106.05. Regarding the signal input, “a signal input configured to receive/receiving multiple ECG signal from multiple electrodes, said electrodes arranged on the abdomen of a pregnant woman”, merely: add insignificant extra-solution activity, reciting “a signal input configured to receive multiple ECG signal from multiple electrodes, said electrodes arranged on the abdomen of a pregnant woman”, is recited at a high level of generality (i.e. as a general means of receiving electrocardiogram signals) and is merely nominally, insignificantly or tangentially related to the performance of the steps, i.e. amounts to mere data gathering, which is a form of insignificant extra-solution activity (pre-solution activity. All uses of the recited judicial exception require the pre-solution activity of data gathering. Further, utilizing multiple electrodes arranged on an abdomen of a pregnant women for obtaining multiple ECG signals was well- understood routine, conventional activities previously known to the industry and amount to elements that have been recognized as well-understood, routine and conventional activity in particular fields as evidence by US 2017/0055866 to Vullings et al. (e.g. para. [0015], [0019], [0040]) or US 2016/0270670 to Oz et al. (e.g. Fig. 4 para. [0004], [0008]). The instant claims do not provide improvements to any other technology or technical field as discussed in Diamond v. Diehr, 450 U.S. 175, 191-92, 209 USPQ 1, 10 (1981), the instant claims do not show an improvement in existing technology by reciting a particular configuration and a particular method of using the data from the particular configuration as discussed in Thales Visionix, Inc. v. United States, 850 F.3d 1343, 1348-49, 121 USPQ2d 1898, 1902 (Fed. Cir. 2017) and the claims do not improve an existing technological process as discussed in McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1315, 120 USPQ2d 1091, 1102 (Fed. Cir. 2016).
Applicant argues “The situation is similar here. The way a device according to the pending claims diagnoses Congenital Heart Disease is different from what doctors do—moreover there are no documents on record that suggest otherwise. Specifically, doctors do not mentally perform digital signal processing, such as separating fetal ECG signals from other signals, detecting QRS complexes, calculating VCGs, etc.. Crucially, doctors do not apply a machine learning classifier. A device according to the claims employs a machine learning model trained on a dataset specifically to discriminate between CHD and non-CHD conditions. This statistical and computational approach is fundamentally different from clinical diagnostic procedures, which do not depend on algorithmic inference from extensive datasets. By employing a trained classifier and standardized computational methods, the described system provides consistent, reproducible outcomes, free from subjective interpretation variability inherent in conventional clinical assessments. In particular, the newly recited feature of downsizing a VCG before applying a trained classifier is not possible to perform mentally and is not a standard medical procedure currently practiced by doctors in this field.”, see p. 12-13. This is not persuasive. MPEP 2106 (I) recites “The Supreme Court’s decisions make it clear that judicial exceptions need not be old or long-prevalent, and that even newly discovered or novel judicial exceptions are still exceptions.”, therefore there is no requirement that the judicial exception is old or long-prevalent and can include those which are newly discovered or novel. The 101 rejection does not state that the digital signal processing, machine learning classifier and downsizing of the VCG before applying a trained classifier are being performed mentally. Regarding the digital signal processing, machine learning classifier and downsizing of the VCG before applying a trained classifier, all these elements have been stated as being part of mathematical concepts. The claimed steps recite performing a mathematical formula or equation, i.e. a machine learning classifier trained using trained parameters obtained using a machine learning algorithm to determine the classification of congestive heart failure, augmenting the first training set by randomly rotating fetal vector cardiogram which can be performed by introducing Gaussian-distributed noise as disclosed within the specification (e.g. para. [0162] of published application US 2020/0214618) and/ or using a machine learning algorithm “a series of mathematical calculations” to obtain trained parameters for a machine learning classifier. If a claim limitation, under its broadest reasonable interpretation covers a mathematical formula or equation but for the recitation of generic computer components, then it falls within the “Mathematical Concepts” grouping of abstract ideas. Accordingly the claims recite an abstract idea. Producing a trained machine learning classifier through training a model does not recite a specific, technical improvement to a technical field. The trained model of the instant application is used to generally apply the abstract idea without placing limits on how the trained model functions. Rather, the only outcome is to determine a classification based on fetal vector cardiogram data without any details on how the model uses the fetal vector cardiogram data to produce the classification. As such, the claims do not recite additional elements that integrate the judicial exception into a practical application, see MPEP 2106.04(d).
Applicant argues “The situation is similar here—an improved cardiac monitoring device is a practical application and passes Alice step one. Nevertheless, the claims also pass Alice step two, as previously explained in the Applicant responses filed to date in the subject application. Specifically, the claims recite additional inventive elements that go beyond the judicial exception, notably the detailed technical steps including adaptive interference removal, VCG down-sampling, and machine-learning-based classification methods.”, see p. 12-13. This is not persuasive. As stated above, the digital signal processing, machine learning classifier and downsizing of the VCG before applying a trained classifier, all these elements have been stated as being part of mathematical concepts. Further, as stated above, producing a trained machine learning classifier through training a model does not recite a specific, technical improvement to a technical field. The trained model of the instant application is used to generally apply the abstract idea without placing limits on how the trained model functions, see para. [0094] of published application US 2020/0214618 which recites that the machine learning classifier can be a deep neural network or support vector machine without placing limits on how the trained model functions. Rather, the only outcome is to determine a classification based on fetal vector cardiogram data without any details on how the model uses the fetal vector cardiogram data to produce the classification. As previously stated, the claims do not recite additional elements that integrate the judicial exception into a practical application, see MPEP 2106.04(d).
3.2 The Claims provide Concrete Advantages Supported by the Specification (p. 13-14 of response filed 7/14/2025).
Applicant argues “The specification enumerates clear and substantial advantages that underline the practical application: ° CHD detection around 20 weeks gestation with sensitivity and specificity of 77.6% and 74.0%, respectively. These performance metrics are robust, operator-independent, and substantially improve upon conventional methods reliant on ultrasound expertise (p.24, 1.109 - p.25, 1.115).° Improved classification metrics are achievable when classifying CHD upon detection of at least one abnormal fetal VCG, reaching sensitivity of 87.8%, specificity of 56.0%, accuracy of 71.7%, and an F1-score of 75.4% (p.25, 1.19-21). ° Concrete clinical benefits, including facilitating intra-uterine therapy, planning deliveries at facilities with appropriate neonatal and cardiothoracic surgical capabilities, and timely post-birth treatments, substantially reducing morbidity and improving survival rates for CHD- diagnosed fetuses (p.1, 1.24-29).”, see p. 13-14. This is not persuasive. As stated above, MPEP 2106 (I) recites “The Supreme Court’s decisions make it clear that judicial exceptions need not be old or long-prevalent, and that even newly discovered or novel judicial exceptions are still exceptions.”, therefore there is no requirement that the judicial exception is old or long-prevalent and can include those which are newly discovered or novel. The instant claims do not provide improvements to any other technology or technical field as discussed in Diamond v. Diehr, 450 U.S. 175, 191-92, 209 USPQ 1, 10 (1981), the instant claims do not show an improvement in existing technology by reciting a particular configuration and a particular method of using the data from the particular configuration as discussed in Thales Visionix, Inc. v. United States, 850 F.3d 1343, 1348-49, 121 USPQ2d 1898, 1902 (Fed. Cir. 2017) and the claims do not improve an existing technological process as discussed in McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1315, 120 USPQ2d 1091, 1102 (Fed. Cir. 2016). The claims do not recite additional elements that integrate the judicial exception into a practical application, see MPEP 2106.04(d).
Conclusion
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/JENNIFER L GHAND/Examiner, Art Unit 3796
Prosecution Insights