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 .
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
Claim Status
Claims 1-14 are pending.
Claim 6 is objected to.
Claims 1-14 are rejected.
Priority
Applicant's claim for the benefit of a prior-filed application, PCT/KR2022/002747, filed 02/24/2022 and applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d) to App. No.10-2021-0024707 filed 02/24/2021. Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Information Disclosure Statement
The information disclosure statements (IDS) filed on 06/22/2023 and 10/15/2024 are in compliance with the provisions of 37 CFR 1.97 and have therefore been considered. A signed copy of the IDS document is included with this Office Action.
Drawings
The Drawings submitted 06/22/2023 are accepted.
Specification
The disclosure is objected to for the following informalities. It is noted that for purposes of the instant Office Action, any reference to the specification pertains to the clean copy of the substitute specification as originally filed on 06/23/2023.
Trade Names
The use of the terms Apple Watch and Galaxy Watch, as example, which are trade names or marks used in commerce, have been noted in this application. Each term should be accompanied by corresponding generic terminology; furthermore the terms should be capitalized wherever they appear or, where appropriate, include a proper symbol indicating use in commerce such as ™, ™, or ® following the terms. Applicant is requested to review the Specification and Drawings for all instances.
Although the use of trade names and marks used in commerce (i.e., trademarks, service marks, certification marks, and collective marks) is permissible in patent applications, the proprietary nature of the marks should be respected and every effort made to prevent their use in any manner which might adversely affect their validity as commercial marks.
Appropriate correction for all objections to the specification is required.
Claim Interpretation
35 U.S.C. 112(f)
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
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: “a data input unit”, “a data extraction unit”, “a training unit”, “an electrocardiogram generation unit” and “a control unit” in claim 1.
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.
The three-prong test: (A) “unit” is a substitute for “means” that is a generic placeholder; (B) unit is modified by the functional language “configured to”; (C) unit is modified by “data input”, which does not provide sufficient structure for performing the step of receive 12-lead electrocardiograms measured by a plurality of patients. The specification discloses a data input unit with no description. See below regarding issues under 112(a) and 112(b) arising from this claim interpretation.
The three-prong test: (A) “unit” is a substitute for “means” that is a generic placeholder; (B) unit is modified by the functional language “configured to”; (C) segmenter is modified by “data extraction” but does not provide sufficient structure for performing the step to extract training data from the input 12-lead electrocardiograms. The specification discloses a data extraction unit, but does not disclose adequate structure to perform the claimed function. See below regarding issues under 112(a) and 112(b) arising from this claim interpretation.
The three-prong test: (A) “a unit” is a substitute for “means” that is a generic placeholder; (B) unit is modified by the functional language “configured to”; (C) unit is modified by “training” but does not provide sufficient structure for performing the step to train a plurality of training models on a characteristic of the electrocardiograms. The specification discloses a training unit, but does not disclose adequate structure to perform the claimed function . See below regarding issues under 112(a) and 112(b) arising from this claim interpretation.
The three-prong test: (A) “unit” is a substitute for “means” that is a generic placeholder; (B) unit is modified by the functional language “configured to”; (C) unit is modified by “electrocardiogram generation “ but does not provide sufficient structure for performing the step to receive at least one reference electrocardiogram from a subject to be measured, and to generate one or more virtual electrocardiograms by inputting the input reference electrocardiogram into the plurality of trained training models. The specification discloses electrocardiogram generation unit but does not disclose adequate structure to perform the claimed function. See below regarding issues under 112(a) and 112(b) arising from this claim interpretation.
The three-prong test: (A) “unit” is a substitute for “means” that is a generic placeholder; (B) unit is modified by the functional language “configured to”; (C) unit is modified by “control” but does not provide sufficient structure for performing the step to synchronize the reference electrocardiogram and the generated virtual electrocardiograms with each other, and to output waveforms for the synchronized reference electrocardiogram and virtual electrocardiograms. The specification discloses control unit but does not disclose adequate structure to perform the claimed function. See below regarding issues under 112(a) and 112(b) arising from this claim interpretation.
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
35 U.S.C. 112(a)
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
Claim(s) 1-7 is/are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claim 1 and those dependent therefrom is/are rejected because, as outlined above under 35 USC 112(f), the disclosure does not contain adequate structure for “a data input unit, a data extraction unit, a training unit, an electrocardiogram generation unit, and a control unit” to perform the claimed functions. The specification as published mentions these unit without any structure. Therefore, there is insufficient disclosure as to necessary structure, steps explained in prose, or any mathematical expression necessary to carry out the above recited function.
With respect to the above limitations, adequate written description for specific programming to carry out said functions in computer-related inventions requires disclosure of the algorithm by which to perform said function. Without the algorithm disclosed, it is unclear as to the exact structure that performs said function (see Finisar Corp. v. DirecTV Group Inc., 86 USPQ2d 1609, 1623 (Fed. Cir. 2008); Halliburton Energy Services v. M-I LLC 514 F.3d 1244, 1256 n.7 (Fed. Cir. 2008)). This raises issues under 112(a) because without the respective algorithms disclosed, one is not apprised of the inventor or joint inventor having possession of the claimed invention.
35 U.S.C. 112(b)
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.
Claims 1-14 are rejected under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention.
Claims 1 and those dependent therefrom limitation “a data input unit, a data extraction unit, a training unit, an electrocardiogram generation unit, and a control unit” invoke 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. (i) the disclosure is devoid of any structure that performs the function in the claim. Therefore, the claims are 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 1: It is clear from the description on pages (see also independent claim 8) that receiving as well patient information corresponding to the 12-lead electrocardiograms and classifying and storing the input 12-lead electrocardiograms according to this patient information, is essential to the definition of the invention. More specifically, claim 2 states that “the patient information includes at least one of gender, age, whether there is a heart disease, and a potential vector of each of the measured electrocardiograms". However, it is not clear how the claimed model can be realistically trained without including specifically the potential vector (lead type) as training data; it would be fed with n times 12 electrocardiogram waveforms without knowing which waveform relates to which lead. Claim(s) 2-7 is/are rejected for the same reason because they depend from claims 1, respectively, and do not resolve the indefiniteness issue in those claims.
Claims 1 and 8: “a control unit configured to synchronize the reference electrocardiogram and the generated virtual electrocardiograms with each other, and to output waveforms for the synchronized reference electrocardiogram and virtual electrocardiograms”. It becomes unclear which "generated virtual electrograms" are precisely meant all generated virtual waveforms, the virtual waveforms as output of the 2nd training model, or the virtual waveforms as output of the 1st training model. The applicant is requested to clarify this ambiguity. Claim(s) 2-7 and 9-14 is/are rejected for the same reason because they depend from claims 1 and 8, respectively, and do not resolve the indefiniteness issue in those claims.
Claims 2 and 9 limitation recites, “the patient information”, There is insufficient antecedent basis for this limitation in the claim as there is no previous recitation of patient information. Claim(s) 3-7 and 10-14 is/are rejected for the same reason because they depend from claims 2 and 9, respectively, and do not resolve the indefiniteness issue in those claims.
Claim 4: limitation recites “constructs a first training model and second training models for 6-lead limb electrocardiograms and 6-lead chest electrocardiograms; and trains the constructed first and second training models to, when inputting one or more reference lead electrocardiograms to the first and second training models”. It is unclear if this is a new first training model separate from the first training model of claim 3 or is the first training model trained twice. The corresponding method claim does not include a first training model, it is being interpreted as not requiring a second first training model or for the model to be trained twice. Claim(s) 5-7 is/are rejected for the same reason because they depend from claim 2, respectively, and do not resolve the indefiniteness issue in those claims.
Claims 5 and 11 limitation recites “wherein … second training models”. There is insufficient antecedent basis for this limitation in the claim as there is no previous recitation of a second training model. Claim(s) 6-7 and 12-13 is/are rejected for the same reason because they depend from claims 5 and 11, respectively, and do not resolve the indefiniteness issue in those claims.
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 1-14 are rejected under 35 U.S.C. 101 because the claimed invention is directed to one or more judicial exceptions without significantly more.
MPEP 2106 organizes judicial exception analysis into Steps 1, 2A (Prongs One and Two) and 2B as follows below. MPEP 2106 and the following USPTO website provide further explanation and case law citations: uspto.gov/patent/laws-and-regulations/examination-policy/examination-guidance-and-training-materials.
Framework with which to Evaluate Subject Matter Eligibility:
Step 1: Are the claims directed to a process, machine, manufacture, or composition of matter;
Step 2A, Prong One: Do the claims recite a judicially recognized exception, i.e. a law of nature, a natural phenomenon, or an abstract idea;
Step 2A, Prong Two: If the claims recite a judicial exception under Prong One, then is the judicial exception integrated into a practical application (Prong Two); and
Step 2B: If the claims do not integrate the judicial exception, do the claims provide an inventive concept.
Framework Analysis as Pertains to the Instant Claims:
Step 1
With respect to Step 1: yes, the claims are directed to a method and system, i.e., a process, machine, or manufacture within the above 101 categories [Step 1: YES; See MPEP § 2106.03].
Step 2A, Prong One
With respect to Step 2A, Prong One, the claims recite judicial exceptions in the form of abstract ideas. The MPEP at 2106.04(a)(2) further explains that abstract ideas are defined as:
mathematical concepts (mathematical formulas or equations, mathematical relationships and mathematical calculations);
certain methods of organizing human activity (fundamental economic practices or principles, managing personal behavior or relationships or interactions between people); and/or
mental processes (procedures for observing, evaluating, analyzing/ judging and organizing information).
With respect to the instant claims, under the Step 2A, Prong One evaluation, the claims are found to recite abstract ideas that fall into the grouping of mental processes (in particular procedures for observing, analyzing and organizing information) and mathematical concepts (in particular mathematical relationships and formulas) are as follows:
Independent claim 8:
classifying … the input 12-lead electrocardiograms according to the patient information
extracting training data from the stored 12-lead electrocardiograms;
training a plurality of training models on a characteristic of the electrocardiograms by inputting the extracted training data to the plurality of training models;
synchronizing the reference electrocardiogram and the generated virtual electrocardiograms with each other, and
Dependent claim 10:
training a first training model to determine a potential vector for each of the input electrocardiograms and
generate a first virtual electrocardiogram by inputting 6-lead limb electrocardiograms and 6-lead chest electrocardiograms to the first training model.
Dependent claim 11:
constructing second training models trained for styles based on the first virtual electrocardiogram; and
training the constructed second training models to, when inputting the first virtual electrocardiogram to the second training models, convert the input lead electrocardiograms into styles each having a corresponding potential vector and output them as second virtual electrocardiograms.
Dependent claim 12:
constructed by mixing a generative adversarial network and an autoencoder method or using each of them.
Dependent claim 13:
extracting a potential vector for the reference electrocardiogram and generating a first virtual electrocardiogram by inputting the input reference electrocardiogram to the first training model; and
generating second virtual electrocardiograms by inputting the first virtual electrocardiogram to the second training models that have been trained on the extracted potential vector.
Dependent claim 14:
synchronizing the reference electrocardiogram and the plurality of virtual electrocardiograms by matching them
determining whether there is an abnormality in health of the subject to be measured by using at least one of an amplitude, gradient, and electrode position of each of the output waveforms for the reference electrocardiogram and virtual electrocardiograms.
Dependent claims 9 recite further steps that limit the judicial exceptions in independent claim 8 and, as such, also are directed to those abstract ideas. For example, claim 9 further limits patient information of claim 8;
Under the BRI, the instant claims recite judicial exceptions that are an abstract idea of the type that is in the grouping of a “mental process”, such as procedures for evaluating, analyzing or organizing information, and forming judgement or an opinion. The instant claims further recite judicial exceptions that are an abstract idea of the type that is in the grouping of a “mathematical concept”, such as mathematical relationships and mathematical equations.
The claim recites classifying and determining. The human mind is capable of classifying the input 12-lead electrocardiograms according to the patient information and determining whether there is an abnormality in health of the subject to be measured by using at least one of an amplitude, gradient, and electrode position of each of the output waveforms for the reference electrocardiogram and virtual electrocardiograms. The claims recite mathematical concepts of extracting training data, training a plurality of training models, synchronizing the reference electrocardiogram and the generated virtual electrocardiograms, training a first training model, generate a first virtual electrocardiogram, constructing second training, training the constructed second training models, constructed by mixing a generative adversarial network and an autoencoder, extracting a potential vector, synchronizing the reference electrocardiogram and the generated virtual electrocardiograms, and generating second virtual electrocardiograms,
Therefore, claim 8 and those claims dependent therefrom recite an abstract idea [Step 2A, Prong 1: YES; See MPEP § 2106.04].
Step 2A, Prong Two
Because the claims do recite judicial exceptions, direction under Step 2A, Prong Two, provides that the claims must be examined further to determine whether they integrate the judicial exceptions into a practical application (MPEP 2106.04(d)). A claim can be said to integrate a judicial exception into a practical application when it applies, relies on, or uses the judicial exception in a manner that imposes a meaningful limit on the judicial exception. This is performed by analyzing the additional elements of the claim to determine if the judicial exceptions are integrated into a practical application (MPEP 2106.04(d).I.; MPEP 2106.05(a-h)). If the claim contains no additional elements beyond the judicial exceptions, the claim is said to fail to integrate the judicial exceptions into a practical application (MPEP 2106.04(d).III).
Additional elements, Step 2A, Prong Two
With respect to the instant recitations, the claims recite the following additional elements:
Independent claim 8:
receiving 12-lead electrocardiograms measured by a plurality of patients and patient information corresponding to the 12-lead electrocardiograms
storing the input 12-lead electrocardiograms according to the patient information
receiving at least one reference electrocardiogram from the subject to be measured, and generating one or more virtual electrocardiograms by inputting the input reference electrocardiogram into the plurality of trained training models
outputting waveforms for the synchronized reference electrocardiogram and virtual electrocardiograms and information about whether there has occurred an abnormality in health of the subject to be measured.
Dependent claim 14:
outputting the plurality of synchronized electrocardiograms
The claims also include non-abstract computing elements. For example, independent claim 14 includes a monitor.
Considerations under Step 2A, Prong Two
With respect to Step 2A, Prong Two, the additional elements of the claims do not integrate the judicial exceptions into a practical application for the following reasons. Those steps directed to data gathering, such as “receiving”, and to data outputting, such as “store” and “outputting” , perform functions of collecting the data needed to carry out the judicial exceptions. Data gathering and outputting do not impose any meaningful limitation on the judicial exceptions, or on how the judicial exceptions are performed. Data gathering and outputting steps are not sufficient to integrate judicial exceptions into a practical application (MPEP 2106.05(g)).
Further steps directed to additional non-abstract elements of “a monitor” do not describe any specific computational steps by which the “computer parts” perform or carry out the judicial exceptions, nor do they provide any details of how specific structures of the computer, such as the computer-readable recording media, are used to implement these functions. The claims state nothing more than a generic computer which performs the functions that constitute the judicial exceptions. Hence, these are mere instructions to apply the judicial exceptions using a computer, and therefore the claim does not integrate that judicial exceptions into a practical application. The courts have weighed in and consistently maintained that when, for example, a memory, display, processor, machine, etc.… are recited so generically (i.e., no details are provided) that they represent no more than mere instructions to apply the judicial exception on a computer, and these limitations may be viewed as nothing more than generally linking the use of the judicial exception to the technological environment of a computer (MPEP 2106.05(f)).
Thus, none of the claims recite additional elements which would integrate a judicial exception into a practical application, and the claims are directed to one or more judicial exceptions [Step 2A, Prong 2: NO; See MPEP § 2106.04(d)].
Step 2B (MPEP 2106.05.A i-vi)
According to analysis so far, the additional elements described above do not provide significantly more than the judicial exception. A determination of whether additional elements provide significantly more also rests on whether the additional elements or a combination of elements represents other than what is well-understood, routine, and conventional. Conventionality is a question of fact and may be evidenced as: a citation to an express statement in the specification or to a statement made by an applicant during prosecution that demonstrates a well-understood, routine or conventional nature of the additional element(s); a citation to one or more of the court decisions as discussed in MPEP 2106(d)(II) as noting the well-understood, routine, conventional nature of the additional element(s); a citation to a publication that demonstrates the well-understood, routine, conventional nature of the additional element(s); and/or a statement that the examiner is taking official notice with respect to the well-understood, routine, conventional nature of the additional element(s).
With respect to the instant claims, the courts have found that receiving and outputting data are well-understood, routine, and conventional functions of a computer when claimed in a merely generic manner or as insignificant extra-solution activity (see Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information), 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), Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015), and OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93, as discussed in MPEP 2106.05(d)(II)(i)).
As such, the claims simply append well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception (MPEP2106.05(d)). The data gathering steps as recited in the instant claims constitute a general link to a technological environment which is insufficient to constitute an inventive concept which would render the claims significantly more than the judicial exception (MPEP2106.05(g)&(h)).
With respect to claim 8 and those claims dependent therefrom, the computer-related elements do not rise to the level of significantly more than the judicial exception. The claims state nothing more than a generic monitor which performs the functions that constitute judicial exceptions. Hence, these are mere instructions to apply the judicial exceptions using a computer element, which the courts have found to not provide significantly more when recited in a claim with a judicial exception (see MPEP 2106.06(A)). The additional elements are set forth at such a high level of generality that they can be met by a general-purpose monitor. Therefore, the computer components constitute no more than a general link to a technological environment, which is insufficient to constitute an inventive concept that would render the claims significantly more than the judicial exceptions (see MPEP 2106.05(b)I-III).
Taken alone, the additional elements do not amount to significantly more than the above-identified judicial exception(s). Even when viewed as a combination, the additional elements fail to transform the exception into a patent-eligible application of that exception. Thus, the claims as a whole do not amount to significantly more than the exception itself [Step 2B: NO; See MPEP § 2106.05].
Therefore, the instant claims are not drawn to eligible subject matter as they are directed to one or more judicial exceptions without significantly more. For additional guidance, applicant is directed generally to the MPEP § 2106.
2. With respect to claims 1-7, the claimed invention is further directed to non-statutory subject matter. The claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter because they recite a system claim to a software program that does not also contain at least one structural limitation (such as a "means plus function" limitation) has no physical or tangible form and thus does not fall within any statutory category.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-14 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Lee et al. (Lee, JeeEun, et al. "Synthesis of electrocardiogram V-lead signals from limb-lead measurement using R-peak aligned generative adversarial network." IEEE journal of biomedical and health informatics 24.5 (2019): 1265-1275, cited on IDS dated 10/15/2024.
Claim 1 is directed to a system for generating electrocardiograms based on a deep learning algorithm, the system comprising:
Lee discloses synthesis of electrocardiogram v-lead signals from limb-lead measurement using r-peak aligned generative adversarial network [title]. Lee further discloses in this study, V-lead ECG signals were synthesized from limb leads using an R-peak aligned generative adversarial network (GAN) [abstract].
a data input unit configured to receive 12-lead electrocardiograms measured by a plurality of patients;
Lee discloses the data used in the present study were the data of 52 healthy individuals obtained from the Physikalisch-Technische Bundesanstalt (PTB) dataset provided by PhysioNetthe where the PTB dataset is an ECG dataset of less than two minutes, including both the standard limb-lead and chest-lead ECG data [p. 1266, col. 1, par. 2].
a data extraction unit configured to extract training data from the input 12-lead electrocardiograms;
Lee discloses the total, 70% of the data was used for the training set, 20% for the validation set, and 10% for the testing set. [p. 1266, col. 1, par. 2].
a training unit configured to train a plurality of training models on a characteristic of the electrocardiograms by inputting the extracted training data to the plurality of training models;
Lee discloses for the R-peak aligned GAN training, we set the batch size to 1 and used the minibatch stochastic gradient descent (SGD) [p. 1267, col. 1, par. 3]. Lee further discloses the learning rate was set to 0.0002 and the hyper parameter optimization was performed through adaptive moment estimation (Adam) [p. 1267, col. 1, par. 3].
an electrocardiogram generation unit configured to receive at least one reference electrocardiogram from a subject to be measured, and to generate one or more virtual electrocardiograms by inputting the input reference electrocardiogram into the plurality of trained training models; and
Lee discloses the GAN consisted of a generator synthesizing the V leads as well as a discriminator that distinguished a true signal from a false signal and underwent learning through the pair dataset [p. 1267, col. 1, par. 2]. Lee further discloses for the R-peak aligned GAN training, we set the batch size to 1 and used the minibatch stochastic gradient descent (SGD) [p. 1267, col. 1, par. 3]. Lee further discloses the learning rate was set to 0.0002 and the hyper parameter optimization was performed through adaptive moment estimation (Adam) [p. 1267, col. 1, par. 3].
a control unit configured to synchronize the reference electrocardiogram and the generated virtual electrocardiograms with each other, and to output waveforms for the synchronized reference electrocardiogram and virtual electrocardiograms.
Lee discloses comparing the real signal to the generated signal that will output the waveforms of each [p. 1272, fig. 4].
Claims 2 and 9 are directed to wherein the patient information includes at least one of gender, age, whether there is a heart disease, and a potential vector of each of the measured electrocardiograms.
Lee discloses for clinical validation, anomaly cases were analyzed using myocardial infraction, bundle branch block, and cardiomyopathy dataset according to the diagnostic class of PTB database [p. 1272, col. 1, par. 2].
Claims 3 and 10 are directed to wherein the training unit trains a first training model to determine a potential vector for each of the input electrocardiograms by inputting 6-lead limb electrocardiograms and 6-lead chest electrocardiograms to the first training model.
Lee discloses the PTB dataset is an ECG dataset of less than two minutes, including both the standard limb-lead and chest-lead ECG data where of the total, 70% of the data was used for the training set, 20% for the validation set, and 10% for the testing set. [p. 1266, col. 1, par. 2]. Lee further discloses for the R-peak aligned GAN training, we set the batch size to 1 and used the minibatch stochastic gradient descent (SGD) [p. 1267, col. 1, par. 3].
Claims 4 and 11 are directed to wherein the training unit: constructs a first training model and second training models for 6-lead limb electrocardiograms and 6-lead chest electrocardiograms; and trains the constructed first and second training models to, when inputting one or more reference lead electrocardiograms to the first and second training models, convert the input reference lead electrocardiograms into styles each having a corresponding potential vector and output them as virtual electrocardiograms.
With respect to claims 4 and 11 that requires a particular style. The specification doesn’t specifically define this, nor does the art of record. It appears from the specification to be possibly associated with trends that might be seen with age, gender, or certain conditions. Lee discloses a V leads ECG result generated from two data cases for each diagnostic class showing the cases of myocardial infraction case, bundle branch block and cardiomyopathy, respectively [p. 1272, col. 1, par. 3]. Lee further discloses as a result of visual inspection of the synthesized signals through RATE, even in anomaly cases according to each diagnostic class, the actual signal and the generated signal are generated without a big difference [p. 1272, col. 1, par. 3] which reads on a trend or style of electrocardiogram.
Claims 5 and 12 are directed to wherein the first and second training models are each constructed by mixing a generative adversarial network and an autoencoder method or using each of them.
Lee discloses synthesis of electrocardiogram v-lead signals from limb-lead measurement using r-peak aligned generative adversarial network [title].
Claims 6 and 13 are directed to wherein the electrocardiogram generation unit: extracts a potential vector for the reference electrocardiogram and generates a first virtual electrocardiogram by inputting the input reference electrocardiogram to the first training model; and
Lee discloses R-peaks were extracted based on the Pan-Tompkins algorithm [p. 1266, col. 1, par. 3]. Lee further discloses the reference ML II lead as a reference and generating the signal for V1 from that reference [p. 1273, fig. 5].
generates second virtual electrocardiograms by inputting the first virtual electrocardiogram to the second training models.
Lee discloses the generator generates the virtual electrocardiogram and that is input into a discriminator that compares it to the reference signal [p. 1273, fig. 5] which reads on a second model.
Claims 7 and 14 are directed to wherein the control unit: synchronizes the reference electrocardiogram and the plurality of virtual electrocardiograms by matching them; outputs the plurality of synchronized electrocardiograms through a monitor; and determines whether there is an abnormality in health of the subject to be measured by using at least one of an amplitude, gradient, and electrode position of each of the output waveforms for the reference electrocardiogram and virtual electrocardiograms.
Lee discloses the result of V1 lead ECG generated from four data cases. The (a) is a case of premature ventricular contraction, the (b) is a case of fusion of ventricular and normal beat, the (c) is a case of left bundle branch block beat, and the (d) is a case of atrial premature beat. Blue is the actual measured signal and green indicates the generated signal [p. 1272, col. 2, par. 2]. Lee further discloses as a result of visual inspection of the generated signal, it was confirmed that there is no significant difference between actual and generated signals in various anomaly cases of MIT-BIH arrhythmia dataset [p. 1272, col. 2, par. 2].
Claim 8 is directed to a method for generating electrocardiograms using a system for generating electrocardiograms, the method comprising:
Lee discloses synthesis of electrocardiogram v-lead signals from limb-lead measurement using r-peak aligned generative adversarial network [title]. Lee further discloses in this study, V-lead ECG signals were synthesized from limb leads using an R-peak aligned generative adversarial network (GAN) [abstract].
receiving 12-lead electrocardiograms measured by a plurality of patients and patient information corresponding to the 12-lead electrocardiograms;
Lee discloses the data used in the present study were the data of 52 healthy individuals obtained from the Physikalisch-Technische Bundesanstalt (PTB) dataset provided by PhysioNetthe where the PTB dataset is an ECG dataset of less than two minutes, including both the standard limb-lead and chest-lead ECG data [p. 1266, col. 1, par. 2].
classifying and storing the input 12-lead electrocardiograms according to the patient information, and extracting training data from the stored 12-lead electrocardiograms;
Lee discloses the total, 70% of the data was used for the training set, 20% for the validation set, and 10% for the testing set. [p. 1266, col. 1, par. 2].
training a plurality of training models on a characteristic of the electrocardiograms by inputting the extracted training data to the plurality of training models;
Lee discloses for the R-peak aligned GAN training, we set the batch size to 1 and used the minibatch stochastic gradient descent (SGD) [p. 1267, col. 1, par. 3]. Lee further discloses the learning rate was set to 0.0002 and the hyper parameter optimization was performed through adaptive moment estimation (Adam) [p. 1267, col. 1, par. 3].
receiving at least one reference electrocardiogram from the subject to be measured, and generating one or more virtual electrocardiograms by inputting the input reference electrocardiogram into the plurality of trained training models; and
Lee discloses the GAN consisted of a generator synthesizing the V leads as well as a discriminator that distinguished a true signal from a false signal and underwent learning through the pair dataset [p. 1267, col. 1, par. 2]. Lee further discloses for the R-peak aligned GAN training, we set the batch size to 1 and used the minibatch stochastic gradient descent (SGD) [p. 1267, col. 1, par. 3]. Lee further discloses the learning rate was set to 0.0002 and the hyper parameter optimization was performed through adaptive moment estimation (Adam) [p. 1267, col. 1, par. 3].
synchronizing the reference electrocardiogram and the generated virtual electrocardiograms with each other, and outputting waveforms for the synchronized reference electrocardiogram and virtual electrocardiograms and information about whether there has occurred an abnormality in health of the subject to be measured.
Lee discloses comparing the real signal to the generated signal that will output the waveforms of each [p. 1272, fig. 4].
Conclusion
No claims are allowed.
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/D.M.B./Examiner, Art Unit 1685
/Soren Harward/Primary Examiner, TC 1600
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