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
Status of the Application
Claims 1-5, 8-12, and 15-24 are currently pending in this case and have been examined and addressed below. This communication is a Final Rejection in response to the Amendments to the Claims and Remarks filed on 10/27/2025.
Claim 1 is currently amended.
Claims 6-7 and 13-14 are cancelled and not considered at this time.
Claims 15-24 are newly added.
Claim Objections
Applicant is advised that should claim 12 be found allowable, claim 24 will be objected to under 37 CFR 1.75 as being a substantial duplicate thereof. When two claims in an application are duplicates or else are so close in content that they both cover the same thing, despite a slight difference in wording, it is proper after allowing one claim to object to the other as being a substantial duplicate of the allowed claim. See MPEP § 608.01(m).
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 1-5, 8-12, and 15-24 are rejected because the claimed invention is directed to an abstract idea without significantly more.
Step 1
Claims 1-5 and 8-11 fall within the statutory category of a process. Claims 15-23 fall within the statutory category of an apparatus. Claims 12 and 24 fall within the statutory category of an article of manufacture as a computer readable medium.
Step 2A, Prong One
As per Claims 1 and 15, the limitations of creating a current atrial tachycardia profile using set of data; analyzing the current data point using the current atrial tachycardia profile in order to determine whether said current data point is an outlier with respect to said current atrial tachycardia profile; analyzing the current data point using the current atrial tachycardia profile in order to determine whether the current data point is a persistent outlier; and updating the current atrial tachycardia profile in response to the change warning, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. The steps of creating a current atrial tachycardia profile, analyzing the current data point to determine whether the data point is an outlier with respect to the atrial tachycardia profile, analyzing the current data point to determine the data point is a persistent outlier, and updating the current profile are concepts performed including observation, evaluation, judgement and opinion in the human mind. If a claim limitation, under its broadest reasonable interpretation, covers the performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claims recite an abstract idea.
Step 2A, Prong Two
The judicial exception is not integrated into a practical application because the additional elements and combination of additional elements do not impose meaningful limits on the judicial exception. In particular, the Claim 1 recites the additional element – computer implemented method. No actual computing device is recited, but reciting steps implemented by a computer amounts to no more than mere instructions to apply the exception using a generic computer component. Claim 15 recites a system comprising an AT analysis module. The AT analysis module is described as a program module executed by a computer processor which is general purpose computer components used to execute the abstract idea that amounts to mere instructions to apply the exception. Accordingly, these additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claims also recites the additional elements of collecting a set of data which represent recordings of electrical activity of a human heart from at least one input source and collecting a current data point of an atrial tachycardia signal from at least one input source, which amount to insignificant extra-solution activity, as in MPEP 2106.05(g), because the steps of collecting a set of data and collecting a current data point are mere data gathering in conjunction with the abstract idea. The claims also recite the limitation of emitting a change warning indicating a change in the current atrial tachycardia profile upon determining that the current data point is a persistent outlier, which amounts to insignificant extra-solution activity, as in MPEP 2106.05(g), because the step of emitting a change warning based on the result of the abstract idea is mere data outputting. The limitations amount to necessary data gathering and outputting, (i.e., all uses of the recited judicial exception require such data gathering or data output). See Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015) (presenting offers and gathering statistics amounted to mere data gathering). Because the additional elements do not impose meaningful limitations on the judicial exception, the claim is directed to an abstract idea.
Step 2B
The claims do 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. As discussed above with the respect to integration of the abstract idea into a practical application, the recitation of a computer implemented method (claim 1) and an AT analysis module (Claim 15) amounts to no more than mere instructions to apply the exception using a generic computing component. The AT analysis module is described as a program module contained in a computer readable memory executed by a computer processor (Specification Page 12), which is disclosed as general purpose computer components used to execute the abstract idea. The claims also include the additional elements of collecting a set of data which represent recordings of electrical activity of a human heart from at least one input source and collecting a current data point of an atrial tachycardia signal from at least one input source, which are both elements that are well-understood, routine and conventional computer functions in the field of data management because they are claimed at a high level of generality and include receiving or transmitting data as well, which has been found to be well-understood, routine and conventional computer functions by the Court (MPEP 2106.05(d)(II)(i) Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014) ("Unlike the claims in Ultramercial, the claims at issue here specify how interactions with the Internet are manipulated to yield a desired result‐‐a result that overrides the routine and conventional sequence of events ordinarily triggered by the click of a hyperlink." (emphasis added). The limitation of emitting a change warning indicating a change in the current atrial tachycardia profile upon determining that the current data point is a persistent outlier amounts to mere data outputting and is found to be well-understood, routine, and conventional similar to activity the courts have found to be well-understood, routine, and conventional including Presenting offers and gathering statistics (OIP Techs., 788 F.3d at 1362-63, 115 USPQ2d at 1092-93). Looking at the limitations as an ordered combination 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 the computer or improves another technology. The claims do not amount to significantly more than the underlying abstract idea.
Dependent Claims 2-5, 8-12, and 16-24 add further limitations which are also directed to an abstract idea. For example, Claims 2 and 16 include extracting features chosen in a group comprising a cycle length feature, an electrode activation sequence feature, and/or a morphological feature of the activation sequence, and training a feature-based anomaly detection algorithm using at least one of said extracted features and/or combination thereof which fall into the abstract grouping of mathematical concepts. Extracting features and using these features to train an anomaly detection algorithm involves use of a mathematical relationship or calculations which fall into the mathematical concepts grouping.
Claims 3 and 17 include augmenting the data of the extracted features prior to training said feature-based anomaly detection algorithm which falls into the abstract grouping of a mental process because it can be performed using human mental observation, evaluation, judgement, and opinion.
Claims 4 and 19 include extracting from the current data point the features which have been used to train a one class support vector machine, feeding the extracted features to the feature-based anomaly detection algorithm, and receiving in return a value indicating whether said current data point is an outlier with respect to said current atrial tachycardia profile which fall into the abstract grouping of mathematical concepts. Extracting features from data and executing the algorithm using the features to receive an value are mathematical relationships.
Claims 5 and 18 include a description of the algorithm as a one class support vector machine which is a mathematical algorithm and therefore the claim falls into the grouping of mathematical concepts.
Claims 8 and 20 include creating a new current atrial tachycardia profile using the second set of data which falls into the abstract grouping of a mental process because it can be performed using human mental observation, evaluation, judgement, and opinion. The claim also includes collecting a new set of data which amounts to mere data gathering that is insignificant extra-solution activity. The collection of data from an input source is well-understood, routine, and conventional similar to receiving or transmitting data over a network, as per MPEP 2106.05(d)(II).
Claims 9 and 21 include adding the current data point to a memory buffer which is mere instructions to apply the exception because it is storing data to memory which is use of a computer for its ordinary purpose, as per MPEP 2106.05(f)(2).
Claims 10 and 22 include determining that a memory buffer threshold for data has been reached, and creating a new current atrial tachycardia profile using the stored data which fall into the abstract grouping of mental process because it can be performed using human mental observation, evaluation, judgement, and opinion.
Claims 11 and 23 includes determining that a memory buffer threshold for data has not been reached which falls into the abstract grouping of a mental process because it can be performed using human mental observation, evaluation, judgement, and opinion.
Claims 12 and 24 include all of the steps of claim 1 which falls into a mental process. The claims also include the use of a non-transitory computer readable medium storing a computer program comprising instructions to execute the steps of the claim. The non-transitory computer readable medium is recited at a high-level of generality such that it amounts to mere instructions to apply the exception, as per MPEP 2106.05(f)(2).
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 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.
Claim(s) 1-3, 8-9, 12, 15-17, and 20-24, are rejected under 35 U.S.C. 103 as being unpatentable over Braun et al. (US 2021/0369209 A1), hereinafter Braun, in view of Xi et al. (US 2009/0264783 A1), hereinafter Xi, in view of Zhang (US 2011/0166618 A1), hereinafter Zhang.
As per Claims 1, 12, 15, and 24, Braun teaches a computer program product comprising a non-transitory computer readable medium storing a computer program comprising instructions to execute a computer implemented method for analyzing an atrial tachycardia signal ([0017] non-transitory computer readable medium storing a program causing a computer to execute the method) comprising the following operations:
a) collecting a set of data which represent recordings of electrical activity of a human heart from at least one input source ([0070] measuring an ECG signal synchronously with PPG signal);
b) creating a current atrial tachycardia profile using said set of data ([0041] pulse classifier is the trained classifying machine learning model, [0079] expert-labelled data obtained from a clinical device, [0081] build a dataset of signals with labeled attributes to each pulse);
c) collecting a current data point of an atrial tachycardia signal from at least one input source ([0083] pulse classifier receives each pulse as input, i.e. current data point of the signal); and
d) analyzing the current data point using the current atrial tachycardia profile in order to determine whether said current data point is an outlier with respect to said current atrial tachycardia profile ([0040] pulse class corresponds to resulting classification of the pulse when analyzed by the classifier as normal or not-normal/outlier which here is pathological or non-physiological, [0083] for each pulse inputted int the pulse classifier, output a pulse class from the classifier).
However, Braun may not explicitly disclose the following which is taught by Xi: e) analyzing the current data point using the current atrial tachycardia profile in order to determine whether the current data point is a persistent outlier ([0070] the set threshold related to atrial fibrillation is exceeded for a specified duration, i.e. persistent outlier data);
g) updating, in response to the change warning (determination of data point as an outlier), the current atrial tachycardia profile ([0062] adjustable detection threshold is increased or decreased based on the determination of whether the threshold is exceeded, Examiner interprets the profile to be the threshold value, where this is updated in the situation in which the current data point is an outlier because it exceeds the threshold).
Therefore, it would have been obvious to a person of ordinary skill in the art before the filing of the present application to combine the known concept of determining a current input is a persistent outlier from Xi with the known invention of a support vector machine which uses extracted features to determine if a current data point is an atrial tachycardia outlier from Braun in order to insure that the analysis does not lead to a false detection of atrial fibrillation or inappropriate diagnosis (Xi [0005]).
However, Braun and Xi may not explicitly disclose the following which is taught by Zhang: f) emitting a change warning indicating a change in the current atrial tachycardia profile upon determining that the current data point is a persistent outlier ([0018] alert message generated when signal data is determined to be an outlier from the comparator).
Therefore, it would have been obvious to a person of ordinary skill in the art before the filing of the present application to combine the known concept of generating an alert to indicate an outlier from Zhang with the known invention of a support vector machine which uses extracted features to determine if a current data point is an atrial tachycardia outlier from Braun in order to provide necessary care to a patient who is experiencing a cardiac anomaly situation.
As per Claims 2 and 16, Braun, Xi, and Zhang discloses the method of Claims 1 and 15. Braun also teaches extracting features chosen in a group comprising a cycle length feature, an electrode activation sequence feature, and/or a morphological feature of the activation sequence ([0012-0013] features used in the machine learning model include a time-related feature which is the time duration of the pulse cycle, i.e. cycle length), and
training a feature-based anomaly detection algorithm using at least one of said extracted features and/or a combination thereof ([0067] training the machine learning model using the expert-labelled data from the ECG signal).
As per Claims 3 and 17, Braun, Xi, and Zhang discloses the method of Claims 2 and 16. Braun also teaches augmenting the data of the extracted features prior to training said feature-based anomaly detection algorithm ([0063] normalizing feature data including a first augmentation index).
As per Claims 8 and 20, Braun, Xi, and Zhang discloses the method of Claims 3 and 17. However, Braun may not explicitly disclose the following which is taught by Xi: h) collecting a new set of data which represent recordings of electrical activity of a human heart from at least one input source; and i) creating a new current atrial tachycardia profile using the second set of data, and repeating steps c) and d) with said new current atrial tachycardia profile([0088] determining a threshold for the patient sensor data value is determined and periodically updated using sensor data which is collected over a period of time and updated when changes in patient’s condition occur, Examiner interprets this to be data collected after a change in patient condition is a second set of data and threshold is updated over time).
Therefore, it would have been obvious to a person of ordinary skill in the art before the filing of the present application to combine the known concept of collecting additional recordings of electrical activity and creating a new profile from the new data from Xi with the known invention of a support vector machine which uses extracted features to determine if a current data point is an atrial tachycardia outlier from Braun in order to insure that the analysis does not lead to a false detection of atrial fibrillation or inappropriate diagnosis (Xi [0005]).
As per Claims 9 and 21, Braun, Xi, and Zhang discloses the method of Claims 1 and 15. Braun also teaches d1) adding the current data point to a memory buffer ([0083] pulses can be a time series of pulses inputted into the classifier/model, [0069] training data of pulses are received and stored in a created database to create a training dataset).
As per Claim 22, Braun, Xi, and Zhang discloses the limitations of Claim 21. However, Braun may not explicitly disclose the following which is taught by Xi: d2) determining that a memory buffer threshold for data has been reached ([0089] the time period is divided into sub-time periods to conserve memory space, therefore memory is available and the threshold has not been reached); and
j) creating a new current atrial tachycardia profile using the data stored in the memory buffer ([0089] collection and analysis of patient data for a time period which saves memory space, Examiner interprets this to inherently teach the data is stored in memory that is temporary as the space would not be relevant if the data was not stored and removed for the next time period, [0088] updating the threshold periodically based on the time periods from the collected data) and
repeating steps c) and d) with said new current atrial tachycardia profile ([0088] determining a threshold for the patient sensor data value is determined and periodically updated using sensor data which is collected over a period of time and updated when changes in patient’s condition occur, Examiner interprets this to be data collected after a change in patient condition is a second set of data and threshold is updated over time).
Therefore, it would have been obvious to a person of ordinary skill in the art before the filing of the present application to combine the known concept of collecting additional recordings of electrical activity and creating a new profile from the new data from Xi with the known invention of a support vector machine which uses extracted features to determine if a current data point is an atrial tachycardia outlier from Braun in order to insure that the analysis does not lead to a false detection of atrial fibrillation or inappropriate diagnosis (Xi [0005]).
As per Claim 23, Braun, Xi, and Zhang discloses the limitations of Claim 21. However, Braun may not explicitly disclose the following which is taught by Xi: d3) determining that a memory buffer threshold for data has not been reached ([0089] the time period is divided into sub-time periods to conserve memory space, therefore memory is available and the threshold has not been reached), and
repeating steps c) and d) with said current atrial tachycardia profile ([0088] determining a threshold for the patient sensor data value is determined and periodically updated using sensor data which is collected over a period of time and updated when changes in patient’s condition occur, Examiner interprets this to be data collected after a change in patient condition is a second set of data and threshold is updated over time).
Therefore, it would have been obvious to a person of ordinary skill in the art before the filing of the present application to combine the known concept of collecting additional recordings of electrical activity and creating a new profile from the new data from Xi with the known invention of a support vector machine which uses extracted features to determine if a current data point is an atrial tachycardia outlier from Braun in order to insure that the analysis does not lead to a false detection of atrial fibrillation or inappropriate diagnosis (Xi [0005]).
Claim(s) 4-5, 10-11, and 18-19, are rejected under 35 U.S.C. 103 as being unpatentable over Braun (US 2021/0369209 A1), in view of Ukil et al. (US 2019/0050690 A1), hereinafter Ukil.
As per Claims 4 and 19, Braun, Xi, and Zhang discloses the method of Claims 2 and 18. Braun also teaches extracting from said current data point the features which have been used to train a support vector machine ([0023] features are extracted from the PPG pulse, i.e. data point, [0074] training the machine learning model using the feature, which here is the SNR characteristics from the PPG pulse, [0068] the machine learning model is a support vector machine),
feeding said extracted features to said feature-based anomaly detection algorithm ([0065-0066] inputting the extracted features into the machine learning model, [0082-0083] classify each pulse by inputting features into the trained model), and
receiving in return a value indicating whether said current data point is an outlier with respect to said current atrial tachycardia profile ([0083] output a pulse class value for each pulse feature which is input into the model, [0096-0097] model classifies the pulse as normal or not (“pathological and non-physiological”) which are outliers that are not included in the data set moving forward).
However, Braun, Xi, and Zhang may not explicitly disclose the following which is taught by Ukil: the use of a one class support vector machine (Abstract one class support vector machine used to detect cardiac abnormality; [0027-0028] anomaly detection algorithm using OC-SVM).
Therefore, it would have been obvious to a person of ordinary skill in the art before the filing of the present application to combine the known concept of a one class support vector machine to determine an outlier from Ukil with the known invention of a support vector machine which uses extracted features to determine if a current data point is an atrial tachycardia outlier from Braun, Xi, and Zhang in order to provide a binary classification of the data because anomaly detection is a vital analytics decision (Ukil [0002]/[0004]).
As per Claims 5 and 18, Braun, Xi, and Zhang discloses the method of Claims 2 and 16. However, Braun, Xi, and Zhang may not explicitly disclose the following which is taught by Ukil: feature-based anomaly detection algorithm is a one class support vector machine (Abstract one class support vector machine used to detect cardiac abnormality; [0027-0028] anomaly detection algorithm using OC-SVM).
Therefore, it would have been obvious to a person of ordinary skill in the art before the filing of the present application to combine the known concept of a one class support vector machine to determine an outlier from Ukil with the known invention of a support vector machine which uses extracted features to determine if a current data point is an atrial tachycardia outlier from Braun, Xi, and Zhang in order to provide a binary classification of the data because anomaly detection is a vital analytics decision (Ukil [0002]/[0004]).
As per Claim 10, Braun, Xi, Zhang and Ukil discloses the method of Claim 5. However, Braun may not explicitly disclose the following which is taught by Xi: d2) determining that a memory buffer threshold for data has been reached ([0089] the time period is divided into sub-time periods to conserve memory space, therefore memory is available and the threshold has not been reached); and
j) creating a new current atrial tachycardia profile using the data stored in the memory buffer ([0089] collection and analysis of patient data for a time period which saves memory space, Examiner interprets this to inherently teach the data is stored in memory that is temporary as the space would not be relevant if the data was not stored and removed for the next time period, [0088] updating the threshold periodically based on the time periods from the collected data) and
repeating steps c) and d) with said new current atrial tachycardia profile ([0088] determining a threshold for the patient sensor data value is determined and periodically updated using sensor data which is collected over a period of time and updated when changes in patient’s condition occur, Examiner interprets this to be data collected after a change in patient condition is a second set of data and threshold is updated over time).
Therefore, it would have been obvious to a person of ordinary skill in the art before the filing of the present application to combine the known concept of collecting additional recordings of electrical activity and creating a new profile from the new data from Xi with the known invention of a support vector machine which uses extracted features to determine if a current data point is an atrial tachycardia outlier from Braun in order to insure that the analysis does not lead to a false detection of atrial fibrillation or inappropriate diagnosis (Xi [0005]).
As per Claim 11, Braun, Xi, Zhang, and Ukil discloses the method of Claim 5. However, Braun may not explicitly disclose the following which is taught by Xi: d3) determining that a memory buffer threshold for data has not been reached ([0089] the time period is divided into sub-time periods to conserve memory space, therefore memory is available and the threshold has not been reached), and
repeating steps c) and d) with said current atrial tachycardia profile ([0088] determining a threshold for the patient sensor data value is determined and periodically updated using sensor data which is collected over a period of time and updated when changes in patient’s condition occur, Examiner interprets this to be data collected after a change in patient condition is a second set of data and threshold is updated over time).
Therefore, it would have been obvious to a person of ordinary skill in the art before the filing of the present application to combine the known concept of collecting additional recordings of electrical activity and creating a new profile from the new data from Xi with the known invention of a support vector machine which uses extracted features to determine if a current data point is an atrial tachycardia outlier from Braun in order to insure that the analysis does not lead to a false detection of atrial fibrillation or inappropriate diagnosis (Xi [0005]).
Response to Arguments
Applicant’s arguments, see Pages 8-17, “Claim Rejections Under 35 U.S.C. §101”, filed 10/27/2025 with respect to claims 1-5, 8-12, and 15-24 have been fully considered but they are not persuasive.
Applicant argues that the claim 1 does not recite an abstract idea because it contains features that cannot practically be performed in the human mind. Specifically, applicant argues that the human mind cannot perform the steps of analyzing the current data point using the current atrial tachycardia profile in order to determine whether the current data point is a persistent outlier, emitting a change warning, and updating the current atrial tachycardia profile, similar to SRI Int’l, inc. v. Cisco Sys., Inc. Examiner respectfully disagrees that an abstract idea is not recited in the claims. The claims include steps such as creating a current atrial tachycardia profile, analyzing the current data point to determine whether said current data point is an outlier, analyzing the current data point to determine whether the current data point is a persistent outlier, and updating the current atrial tachycardia profile, which can be performed using human mental processing. The analyzing steps do not limit the type of analysis to that which cannot be performed mentally. The cited example, SRI Int’l, includes analysis of a specific type of data, network packets, that is not possible to be analyzed in the human mind. In the present claims, the data which is analyzed is not specified beyond data which represents recordings of electrical activity and a current data point of an atrial tachycardia signal. This data could be any type and thus, under BRI, can be data which could be processed using human mental processing. Human mental observation, evaluation, judgment, and opinion can be used to analyze a “data point” and “set of data” which represents recordings. The step of emitting a change warning is not identified as part of the abstract idea, but rather is an additional element which is mere data outputting that amounts to insignificant extra-solution activity, as per the rejection above.
Applicant argues that the claim recites additional elements that integrate the abstract idea into a practical application. Specifically, Applicant argues that claim provides an improvement to the technology or technical field by providing a method for automatically generating and updating an atrial tachycardia profile based on analyzing an atrial tachycardia signal collected in real-time during a catheter ablation procedure. Examiner respectfully disagrees. The additional elements of the claims include the implementation using a computer, collecting a set of data, collecting a current data point, and emitting a change warning indicating a change in current atrial tachycardia profile. The computer elements amount to mere instructions to apply the judicial exception, and the collection of data and emitting a warning amount to insignificant extra-solution activity because it describes mere data gathering and outputting. These additional elements do not integrate the abstract idea into a practical application by providing a technical improvement. Any improvement to automatically generating and updating an atrial tachycardia profile based on analyzing an atrial tachycardia signal collected in real-time during a catheter ablation procedure is an improvement to the abstract idea itself. No matter how much of an advance in the field the claims recite, the advance lies entirely in the realm of abstract ideas, with no plausibly alleged innovation in the nonabstract application realm. An advance of that nature is ineligible for patenting.
Applicant argues that the claim includes an inventive concept which provides significantly more than the abstract idea because the claimed features are not well-understood, routine, and conventional activity in the field. Examiner respectfully disagrees. The additional elements of the claims, which have been identified above as insignificant extra-solution activity include collecting a set of data, collecting a current data point, and emitting a change warning indicating a change in current atrial tachycardia profile. These elements are shown to be well-understood, routine, and conventional based on similarity to elements found to be recognized as well-understood, routine, and conventional by the courts, as per MPEP 2106.05(d)(II). The collection of data from an input source is similar to receiving or transmitting data over a network. The emitting of a change warning indicating a change in current atrial tachycardia profile is merely the outputting of a notification, based on BRI of the claims. The claim does not specify details about how the warning is emitted, therefore, the claim is similar to presenting offers and gathering statistics (OIP Techs). The combination of elements does not provide any particular inventive concept. Therefore, the claim does not provide significantly more than the abstract idea and the rejection is maintained.
Applicant’s arguments, see Pages 17-21, “Claim Rejections Under 35 U.S.C. §102”, filed 10/27/2025 with respect to claims 1-3, 9, and 12 have been fully considered.
With regard to Claim 1, Applicant argues that Braun does not teach a current atrial tachycardia profile. Examiner respectfully disagrees. Braun teaches creating a current atrial tachycardia profile from the collected data, as [0040-0041] describes a classifier which determines a pulse class for the collected signal data. Interpretation of the claim language as recited, under BRI, does not limit a current atrial tachycardia profile in such as a way that the classifier of Braun which determines a pulse class for the data does not read on the claim language. The claims do not specify what the profile includes or how it is determined.
Applicant additionally argues that Braun does not teach “in order to obtain another current atrial tachycardia profile, the whole training would have to be redone with new data, which neither described nor suggested as being available”. With regard to obtaining another current atrial tachycardia profile, the claims do not limit as to how this is performed. The claim language as recited is updating, in response to the change warning, the current atrial tachycardia profile. This could be performed in any fashion. However, the argument that this is not taught explicitly by Braun is persuasive. Therefore, the 102 rejection has been withdrawn. However, after further consideration, a new grounds of rejection is made over 35 USC 103 in view of Xi and Zhang.
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.
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/EVANGELINE BARR/Primary Examiner, Art Unit 3682