DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Arguments
Applicant’s arguments, see pg. 6 of Remarks, filed 06/04/2026, with respect to the Claim Objections to claim 1-15 have been fully considered and are persuasive. The Claim Objections of claims 1-15 have been withdrawn.
Applicant’s arguments, see pg. 6 of Remarks, filed 06/04/2026, with respect to the Claim Rejection under 35 USC 112(b) to claims 1-4, 6, 8, and 10-15 have been fully considered and are persuasive. The Examiner agrees that the amendments to claim 1, 4, and 10 overcome the rejections under 35 USC 112(b), as outline in the Non-Final Rejection filed on 03/05/2024. The rejection of claims 1-4, 6, 8 and 10-15 under USC 35 112(b) have been withdrawn.
Applicant's arguments on pg. 6 of Remarks filed 06/04/2026 have been fully considered but they are not persuasive regarding the rejection of claim 5 under 35 USC 112(b). Regarding the rejection of claim 5 under 35 USC 112(b), the Examiner disagrees that the amended claim overcomes the rejection under 35 USC 112(b). The Examiner maintains that the claim language reciting, “performing a sliding linear regression in a vicinity of a predetermined QRS peak” is indefinite. One of ordinary skill would not be able to determine what is “in a vicinity” or what is not “in a vicinity.” Therefore, the metes and bounds of the recited claim limitation are not defined. The rejection of claim 5 under 35 USC 112(b) is maintained.
Applicant's arguments on pg. 6 of Remarks filed 06/04/2026 have been fully considered but they are not persuasive regarding the rejection of claim 9 under 35 USC 112(b). Regarding the rejection of claim 9 under 35 USC 112(b), the Examiner disagrees that the amended claim overcomes the rejection under 35 USC 112(b). The Examiner maintains that the claim language reciting, “a pause associated with the asystole, high ventricular rate” is indefinite since the claim language of claim 9 necessitates an event type being an asystole or high ventricular rate, but claim 8 (which claim 9 is dependent from) gives the option of the event type being either an asystole, high ventricular rate, or bradycardia. In the event that the event type is a bradycardia, it would not be clear if a pause would be detected. Claim 8 gives an option for an event type, where claim 9 necessitates it to be 2 of the 3 options (high ventricular rate and asystole). It is not clear if, in the event that the event type is a bradycardia, if the limitations of claim 9 still apply. This is consistent with the rejection of claim 9 on pg. 6 of the Non-Final Rejection (filed 03/05/2026), which asserts that there is no antecedent basis for “the asystole” in claim 9, since asystole may not be the chosen event type in claim 8. The rejection of claim 9 under 35 USC 112(b) is maintained.
Applicant's arguments on pgs. 6-8 of Remarks filed 06/04/2026 filed have been fully considered but they are not persuasive regarding the rejection of claims 1-15 under 35 USC 101. Regarding the rejection of claims 1-15 under 35 USC 101, the Examiner respectfully disagrees that claim 1, as amended, overcomes the rejection by “concretely reciting structural features of a heart monitoring device.” The Applicant recites paragraphs from the instant specification in support of claim 1 overcoming the rejection of claim 1 under 35 USC 101. The Examiner respectfully reminds the applicant that the claims, not the specification, is what is evaluated for rejection under 35 USC 101. Additionally, as asserted on pg. 7 of Non-Final Rejection, filed 03/05/20206, the implantable device of claim 1 merely defines the field of use for the invention, and does not add significantly more or integrate the abstract idea into a practical application. Further, the methods described in para. [0016], [0019], [0022], [0031]-[0033]. [0046]-[0047], and [0081-0084] are merely signal processing methods based on mathematical concepts. The Examiner disagrees that the claims, as asserted on pg. 8 of Remarks, are directed integration of an abstract idea, or add significantly more than the abstract idea. The support for this assertion is made based on the details of the instant specification, not based on the language written in the claims. As claims 1-15 are written, the claimed language only recites abstract idea subject matter. The Examiner maintains that the dependent claims 2-15 do not add integration into a practical application or significantly more than the abstract ideas recited in claim 1. The Examiner maintains that dependent claim 15 does not recite patent eligible subject matter. Therefore, the Examiner maintains the rejection of claims under 35 USC 101. Further details regarding the rejection of the amended claim under 35 USC 101 are outlined below (see section titled, “Claim Rejections - 35 USC § 101”).
Applicant's arguments on pg. 10 of Remarks filed 06/04/2026 have been fully considered but they are not persuasive regarding the rejection of claims 1-15 under 35 USC 102 and 103. Regarding the rejection of claims 1-15 under 35 USC 102 and 103, the Examiner disagrees that amendment to the claims overcomes rejections in view of the prior art. The rejections of the amended claims 1-15 are detailed below.
Response to Amendment
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 1-15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1
Independent claim 1 is directed to a method, and dependent claims 13 and 14 are directed to an apparatus and system (i.e., a machine) for performing the method. Thus, the claims meet the requirements for step 1. However, regarding dependent claim 15, the claim is directed towards a computer program, which is not patent eligible subject matter and is therefore rejected under 35 USC § 101 step 1. See MPEP 2106.03 regarding signals per se.
Step 2A, prong 1
Claim 1 recites: “receiving a determination of a heart episode event based on an analysis of an electrocardiogram (ECG) signal… determining that a heart episode event is present in the reconstructed ECG signal; verifying the heart episode event from the reconstructed ECG signal is the heart episode event from the ECG signal based on a threshold comparison.” The recitation of determining a heart event, verifying a heart event from an ECG signal, and verifying a heart event from an ECG based on a threshold comparison is an abstract idea mental process. The claim includes subject matter that, as recited, could be performed by one of ordinary skill in the art, such as a cardiologist, in their own head. A cardiologist would be able to make determinations and verifications based on observations and judgements from an ECG signal (see MPEP 2106.04(a)(2)(III)) shown on a screen or printout.
Claim 1 further recites, “up-sampling the ECG signal to generate an up-sampled ECG signal; applying an anti-aliasing technique to the up-sampled ECG signal; generating a reconstructed ECG signal via an interpolation technique applied to the up- sampled ECG signal…”. The recited subject matter is a mathematical concept abstract idea related to mathematical principles of signal processing. Up-sampling, anti-aliasing, interpolation, and reconstruction (outputting a newly processed signal) are all based on mathematical principles. The recited concepts are defined by the relationships, equations, and formulas applied to signal (for example, is based entirely on a formula used to estimate unknown values). Therefore, the recited limitations are mathematical concept abstract ideas (see MPEP 2106.04(a)(2)(III)).
Step 2A, prong 2
Claim 1 recites the additional limitations: “receiving the ECG signal associated with the determined heart episode event.” The recited limitation is merely extra-solution activity data gathering. Collecting heart signals via an ECG is known in the art, and does not integrate the abstract ideas into a practical application. Further, the preamble of the claim recites, “A method for analyzing an event determined by an implantable device…”. The preamble merely defines the field of use for the method, and does not recite additional limitations that amount to integration into a practical application. In summary, the additional limitations (i.e., the claimed limitations that are not recited in step 2A, prong 1) do not integrate the abstract ideas into a practical application.
Step 2B
Claim 1 recites the additional limitations: “receiving the ECG signal associated with the determined heart episode event.” The recited limitation is merely extra-solution activity data gathering. Collecting heart signals via an ECG is known in the art, and does not add significantly more than the abstract idea. Further, the preamble of the claim recites, “A method for analyzing an event determined by an implantable device…”. The preamble merely defines the field of use for the method, and does not recite additional limitations add significantly more than the abstract idea. In summary, the additional limitations (i.e., the claimed limitations that are not recited in step 2A, prong 1) do not add significantly more than the abstract idea.
Dependent claims
Claims 2, 3, 6, 7, 8, 9, and 10 further define the abstract idea mental process of verifying.
Claim 4 recites extra-solution activity data gathering (“receiving information from the device”).
Claim 5 recites a mathematical concept abstract idea (“sliding linear regression”).
Claims 13 and 14 recite structures that are defined by the abstract ideas of claims 1-12 (an apparatus “configured to perform the methods of claim 1”).
Claim 15 recites subject matter that is not patent eligible (a computer program).
Claim Rejections - 35 USC § 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.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 5 and 9 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Regarding claim 5, the claim recites “determining a sliding linear regression in a vicinity of a predetermined QRS peak” (ln. 3-4). The use of “vicinity” is so broad that it is unclear what is considered to be in the vicinity. More specificity is required to understand the metes and bounds of the limitation.
Regarding claim 9, the claim recites “a pause associated with the asystole, high ventricular rate...” (line 3). However, claim 8 recites the option for event types as being “an asystole, high ventricular rate, and/or a bradycardia”. There is insufficient antecedent basis for “the asystole” since it is referred to in the optional case in claim 8 (by reciting the option “and/or”). Even with the amendment “high ventricular rate,” claim 8 still provides the option of “a bradycardia” (line2). It is unclear if the step is performed if a bradycardia is detected (and not the asystole or high ventricular rate.”).
Claim Rejections - 35 USC § 112(d)
The following is a quotation of 35 U.S.C. 112(d):
(d) REFERENCE IN DEPENDENT FORMS.—Subject to subsection (e), a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
The following is a quotation of pre-AIA 35 U.S.C. 112, fourth paragraph:
Subject to the following paragraph [i.e., the fifth paragraph of pre-AIA 35 U.S.C. 112], a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
Claim 4 is rejected under 35 U.S.C. 112(d) or pre-AIA 35 U.S.C. 112, 4th paragraph, as being of improper dependent form for failing to further limit the subject matter of the claim upon which it depends, or for failing to include all the limitations of the claim upon which it depends. Claim 4 does not further limit the subject matter from claim 1. Claim 1 recites, “receiving the ECG signal associated with the determined heart episode event” and “a method for analyzing an event determined by an implantable device.”. The method step recited in claim 4 does not further narrow the scope of the subject matter of claim 1. Applicant may cancel the claim(s), amend the claim(s) to place the claim(s) in proper dependent form, rewrite the claim(s) in independent form, or present a sufficient showing that the dependent claim(s) complies with the statutory requirements.
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.
Claims 1-4, 8, and 13-15 is/are rejected under 35 U.S.C. 102(a)(1)/(a)(2) as being anticipated by Dawoud et al. (US 20190336026 A1, “Dawoud”) (cited previously).
Regarding claim 1, Dawoud teaches a method for analyzing an event determined by an implantable device (Fig. 1; para. [0076]: "FIG. 1 illustrates an implantable cardiac monitoring device (ICM) 100 intended for subcutaneous implantation at a site near the heart."), the method comprising: receiving a determination of a heart episode event (para. [0164]: "At 902, one or more processors determine that the ICM device documented bradycardia episode or asystole episode based on cardiac activity signals detected in the primary sensing channel 801.") based on an analysis of an electrocardiogram (ECG) signal (para. [0093]: " The data acquisition system 150 is configured to acquire cardiac electrogram (EGM) signals as CA signals."; This shows the CA signals are ECG signals); receiving the ECG signal associated with the determined heart episode event (para. [0164]: "At 902, one or more processors determine that the ICM device documented bradycardia episode or asystole episode based on cardiac activity signals detected in the primary sensing channel 801."); up-sampling the ECG signal to generate an up-sampled ECG signal (para. [0165]: "At 904, the one or more processors resample the CA signal (e.g., utilizing interpolation) to increase a resolution of the data samples within the CA data set for the CA signal. Resampling the CA signals allows relatively more precise settings of thresholds and more detailed sensing operations to be performed at later operations in FIG. 9A. By way of example, the original CA signals (e.g., VEGM signals) may be defined by a CA data set that has a sample frequency of 128 Hz, whereas the resampling and interpolation increase the sample resolution to 512 Hz. Various types of interpolation may be applied, such as linear interpolation or Shannon interpolation, in which zeros are added between points and the signal is digitally low-pass filtered and multiplied by the reciprocal of the up-sampled ratio."); applying an anti-aliasing technique to the up-sampled ECG signal (para. [0165]: " the signal is digitally low-pass filtered and multiplied by the reciprocal of the up-sampled ratio."; applying a low-pass filter is an anti-aliasing technique; Additionally, [0168] describes a high-pass filter applied to the signal in step 906); generating a reconstructed ECG signal via an interpolation technique applied to the up- sampled ECG signal (para. [0165]: "For example, the operations at 904-910 may be implemented by the feature enhancement process 815 (FIG. 8A). At 904, the one or more processors resample the CA signal (e.g., utilizing interpolation) to increase a resolution."; Additionally, in Fig. 9A, step 922, an R-wave is being detected from a signal, meaning the ECG signal is reconstructed); determining that a heart episode event is present in the reconstructed ECG signal (Fig. 9A; Step 930 (which is after resampling at 904)para. [0187]: "At 930, the one or more processors analyze the beat segment of interest to detect whether an arrhythmia is present. The detection of the arrhythmia is based at least in part on a presence or absence of one or more R-waves within the beat segment of interest. For example, the processors may confirm or deny the presence of a bradycardia episode and/or in asystole episode within one or more beat segment of interests."); verifying the heart episode event from the reconstructed ECG signal is the heart episode event from the ECG signal based on a threshold comparison (para. [0187]: "At 930, the one or more processors analyze the beat segment of interest to detect whether an arrhythmia is present. The detection of the arrhythmia is based at least in part on a presence or absence of one or more R-waves within the beat segment of interest. For example, the processors may confirm or deny the presence of a bradycardia episode and/or in asystole episode within one or more beat segment of interests. In connection with bradycardia episodes, the processors may maintain a running count of a number of beats having RR intervals that are sufficiently long (exceed a bradycardia RR interval threshold) to be indicative of a bradycardia episode.").
Regarding claim 2, Dawoud teaches method according to claim 1 (see rejection above), wherein verifying the event type is based in part on the type of heart episode event (para. [0018]: “The first pass arrhythmia detection algorithm may declare the arrhythmia episode to be one of a bradycardia, asystole or atrial fibrillation episode.), wherein the heart episode event type comprises at least one of the following: an atrial fibrillation onset, an asystole, a high ventricular rate, and a bradycardia (para. [0018]; “The first pass arrhythmia detection algorithm may declare the arrhythmia episode to be one of a bradycardia, asystole or atrial fibrillation episode.”; para. [0086]; “The arrhythmia detector 134 of the microcontroller 121 includes an on-board R-R interval irregularity (ORI) process 136 that detects AF episodes using an automatic detection algorithm that monitors for irregular ventricular rhythms that are commonly known to occur during AF.”).
Regarding claim 3, Dawoud teaches the method according to claim 1 (see above), wherein the verifying comprises determining whether the event is true positive and/or whether the heart episode event is false positive. (para. [0160]; “The adaptive sensitivity threshold changes between events and/or episodes. The detection algorithm 813 provides a reduction in false declaration of bradycardia and asystole episodes by the ORI process 809, while maintaining the sensitivity in detecting true bradycardia and asystole episodes.”; para. [0108]; “For example, a 30-45 second strip of EGM signals may include one or more PVC events that cause the AF detection algorithm of an IMD to designate a false R-wave marker. Based on the number of false R-wave markers in the EGM strip, the AF detection algorithm may determine that no arrhythmia episode is present or a false arrhythmia episode is present.”)
Regarding claim 4, Dawoud teaches the method according to claim 1 (see above), further comprising receiving the ECG signal associated with the heart episode from the implantable device event (para. [0164]: "At 902, one or more processors determine that the ICM device documented bradycardia episode or asystole episode based on cardiac activity signals detected in the primary sensing channel 801.").
Regarding claim 8, Dawoud teaches the method of claim 1 (see 102 rejection above), wherein if the type comprises an asystole, high ventricular rate and/or a bradycardia , the verifying comprises eliminating RR intervals from the heart episode (para. [0116]: “At 304, the one or more processors analyze the CA data for noise and pass or remove segments of the CA signal for select cardiac events based on a noise level within the corresponding segment of the CA signal… The software based evaluation can be developed in a manner that is tailored to AF detection such that the software-based noise rejection is more sensitive in connection with identifying or removing unduly noisy CA signal segments that in turn give rise to inappropriate R-wave detection.”; para. [0117]: “Optionally, as explained below in connection with FIG. 11, embodiments herein may declare a segment of the CA signals to represent a noisy segment, and remove the noisy segment to form noise corrected CA signals.” The segment removed is determined by inappropriate R-waves.).
Regarding claim 13, Dawoud teaches an apparatus (abstract; “Computer implemented methods and systems for detecting arrhythmias in cardiac activity are provided. The method is under control of one or more processors configured with specific executable instructions.”) for analyzing an event determined by an implantable device (Fig. 1; para. [0076]; “implantable cardiac monitoring device (ICM) 100.”), wherein the apparatus is configured to perform a method of claim 1 (see above).
Regarding claim 14, Dawoud teaches a system (abstract; “Computer implemented methods and systems for detecting arrhythmias in cardiac activity are provided”) for analyzing an event determined by an implantable device comprising: an apparatus according to claim 13 (see above); and the implantable device (Fig. 1; para. [0076]; “implantable cardiac monitoring device (ICM) 100.”).
Regarding claim 15, Dawoud teaches a computer program comprising instructions to perform a method of any of claim 1 when the instructions are executed (Abstract; “The method is under control of one or more processors configured with specific executable instructions.”).
Claim Rejections - 35 USC § 103
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.
24. Claims 5 and 6 are rejected under 35 U.S.C. 103 as being unpatentable over Dawoud et al. (US 20190336026 A1, “Dawoud”), Aspuru et al. (“Segmentation of the ECG Signal by Means of a Linear Regression Algorithm”; Pub. Feb. 14, 2019, “Aspuru”), and Mena et al. (“Mobile Personal Health Monitoring for Automated Classification of Electrocardiogram Signals in Elderly”; Pub. May 29, 2018, “Mena”) (all references cited previously).
Regarding claim 5, Dawoud teaches a method according to claim 1 (see 102 rejection above). However, Dawoud does not teach wherein determining that a heart episode event is present in the reconstructed ECG signal involves performing a sliding linear regression in a vicinity of a predetermined QRS peak.
Aspuru, in the same field of endeavor of detecting cardiac events and anomalies from ECG signals, discloses a method for performing a linear regression to a segment of an ECG signal to detect a peak. Aspuru discloses wherein determining that a heart episode event is present in the reconstructed ECG signal involves performing a sliding linear regression in a vicinity of a predetermined QRS peak. (Abstract; “Our approach is based on the use of linear regression to segment the signal, with the goal of detecting the R point of the ECG wave and later, to separate the signal in periods for detecting P, Q, S, and T peaks. After pre-processing of ECG signal to reduce the noise, the algorithm was able to efficiently detect fiducial points, information that is transcendental for diagnosis of heart conditions using machine learning classifiers.”; In the case of Aspuru, sliding is not used to describe the linear regression. However, sliding linear regression is considered performing linear regression to data in a window that is changing over time (as opposed to a set number of data points). Thus, Aspuru discloses an example of a sliding linear regression in that it is performed on a window of ECG data recorded over time.)
Aspuru does not specifically disclose performing the linear regression for the atrial fibrillation event type. However, Aspuru discloses that the method is used to detect each section of an ECG signal for diagnosis of several heart conditions (introduction; para. 1), and references Mena et al. (“Mobile Personal Health Monitoring for Automated Classification of Electrocardiogram Signals in Elderly”). Mena discloses classifying ECG signals for specificity in detecting atrial fibrillation (Discussion; para. 1). Thus, atrial fibrillation is considered one of the heart conditions where the sliding linear regression method can be used to detect P waves.
It would have been obvious to one of ordinary skill in the art before the effective filing date to combine the methods of claim 1, as disclosed by Dawoud, with the technique of identifying P-wave peaks with a sliding linear regression as disclosed by Aspuru. Aspuru discloses the known technique of performing a sliding linear regression on segments of an ECG, and uses this technique to diagnose heart conditions. It would have been obvious to incorporate this into the method of claim 1, which is directed towards a method of diagnosing heart conditions, since it would improve the method of detecting P-wave peaks. In doing so, the technique would have yielded predictable results of improved accuracy in verifying heart conditions.
Regarding claim 6, Dawould, in combination with Aspuru, disclose the method according to claim 5 (see above). Dawoud further discloses wherein the verifying is further based at least in part on one of the following: an RR interval, a PP interval, an RP interval, a correlation of a QRS complex morphology and/or on an ectopy probability, in the heart episode event (para. [0078]; “The ICM 100 includes one or more processors and memory that stores program instructions directing the processors to implement AF detection utilizing an on-board R-R interval irregularity (ORI) process that analyzes cardiac activity signals collected over one or more sensing channels.”; para. [0125]; “For example, at 318, the one or more processors may implement the QRS complex morphology based PVC detection process described in one or more of the Co-Pending Related Applications referred to above, and filed concurrently on the same day as the present application. The processors determine whether a QRS complex morphology has varied beyond a morphology variation threshold. Variation in the R-wave morphology beyond the morphology variation threshold provides a good indicator that the cardiac events include one or more PVC. When the cardiac events include a sufficient number of PVCs, the process may attribute an R-R interval variation to (and indicative of) PVCs or non-atrial originated beats that lead to significantly different R-R intervals, and not due to (or indicative of) an AF episode.”; The morphological differences are indicative of a PVC episode and are used to detect false positives.)
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Dawoud et al. (US 20190336026 A1, “Dawoud”) in view of Cao et al. (US 20200305799 A1, “Cao”) (cited previously).
Regarding claim 7, Dawoud discloses the method according to claim 1 (see 102 rejection). However, Dawoud does not expressly disclose wherein the verifying is performed by an artificial intelligence system and/or a machine learning system that has been trained with events that were verified via manual inspection of heart episodes.
Cao, in the same field of processing ECG data to diagnose cardiac events, discloses a method based on machine learning artificial intelligence. Cao discloses wherein the verifying is performed by an artificial intelligence system and/or a machine learning system (para. [0043]; " The ECG automatic analysis method based on artificial intelligence self-learning according to the embodiments of the present disclosure includes data preprocessing, heart beat feature detection, interference signal detection and heart beat classification based on deep learning methods, signal quality evaluation and lead combination, heart beat verifying, and analysis and calculation of ECG events and parameters.") that has been trained with events that were verified via manual inspection of heart episodes (para. [0005]; "Specifically, training data came from 64,121 samples of 29,163 patients. Each sample was single-lead data with a length of 30 seconds and a sample rate of 200 Hz. Each second of data corresponds to the Rhythm Type labeled and reviewed by qualified ECG experts, with a total of 14 labeled types, including 12 common arrhythmia events, a normal sinus rhythm and a noise type. The trained model labeled data by using a single-lead gold standard with a same sample rate to perform 14 types of events identification on each second of input data").
It would have been obvious to one of ordinary skill in the art before the effective filing date to combine the method of claim 1, as disclosed by the Dawoud, with the method of using artificial intelligence as disclosed by Cao. Doing so would have been an obvious improvement of the ECG analysis for detecting cardiac events that would yield the predictable result of further increasing the accuracy of detecting cardiac events. Further, it would have been obvious to train the AI algorithm with confirmed events labeled by ECG experts since doing so would provide a baseline accuracy for the algorithm to compare with the output calculations. Using this known technique would have yielded predictable results for an improving the accuracy of verifying heart events.
Claims 9 and 10 are rejected under 35 U.S.C. 103 as being unpatentable over Dawoud et al. (US 20190336026 A1, “Dawoud”) in view of Ghanem et al. (US 7734336 B2, “Ghanem”) (cited previously).
Regarding claim 9, Dawoud teaches the method according to claim 8 (see 102 rejection above). However, Dawoud does not expressly teach wherein the verifying further comprises: detecting whether a pause associated with the asystole, high ventricular rate is present between subsequent QRS peaks, corresponds to an RR interval that has not been eliminated.
Ghanem, in the same field of endeavor of detecting arrythmia, discloses a method for detecting cardiac events from an ECG. Ghanem discloses wherein the verifying further comprises: detecting whether a pause associated with the asystole, high ventricular rate is present between subsequent QRS peaks (para. (63); “Once the heart rate estimate is obtained using the heart rate metric, a determination is made as to whether asystole is detected for either channel, ECG1 or ECG 2, Block 324. According to an embodiment of the present invention, asystole is detected for the channel, for example, either by determining whether one of the 12 R-R intervals is greater than a predetermined time period, such as three seconds, for example, or if the time since the most recently sensed R wave exceeds a predetermined time period, such as three seconds, for example.”), corresponds to an RR interval that has not been eliminated (para. (63): “The latter can occur if an R-wave is sensed, for example, in one channel ECG1, but the other channel ECG2 has not had an R-wave sense in three or more seconds. If asystole is detected for either of the two channels ECG1 or ECG2, the current 12 R-R intervals for channels that are determined to be in asystole are cleared from the buffers, Block 325, and the process continues by determining whether the current heart rate estimate is reliable for both channels ECG1 and ECG2, Block 328, described below.”; “Current 12 R-R intervals” implies the RR intervals have not been eliminated yet.) Ghanem does not explicitly disclose the limitation as a “pause” between peaks. However, as described, a prolonged interval, or an “interval longer than a time period”, can be considered to be a pause.
It would have been obvious to combine the method of claim 8, as disclosed by Dawoud, with the methods of detecting a pause associated with asystole between QRS peaks as disclosed by Ghanem. Detecting a pause between peaks is a technique for indicating asystole, as disclosed in Ghanem. It would have been obvious to include this technique with the method of claim 8 since it improves the process of verifying asystole events. One of ordinary skill in the art would have recognized that the method of Ghanem would be effective in rejecting noise (see Ghanem para. (11)). Therefore, it would have been desirable to include this technique in the device of Dawoud.
Regarding claim 10, Dawoud, in combination with Ghanem, discloses the method according to claim 9 (see above). Dawoud further discloses that the heart episode event from the ECG signal is a (para. [0164]: "At 902, one or more processors determine that the ICM device documented bradycardia episode or asystole episode based on cardiac activity signals detected in the primary sensing channel 801.") true positive (TP) otherwise determining that the event is false positive (Fig. 3; 316 and 320 show “Declare False Arrythmia Detection” (False Positive) and “Confirm Original Arrythmia Detection” (True positive), respectively.). However, Dawoud does not expressly teach that the determination of a false or true positive is contingent upon a detection of a pause.
Ghanem discloses that a pause is detected (para. (63); “Once the heart rate estimate is obtained using the heart rate metric, a determination is made as to whether asystole is detected for either channel, ECG1 or ECG 2, Block 324. According to an embodiment of the present invention, asystole is detected for the channel, for example, either by determining whether one of the 12 R-R intervals is greater than a predetermined time period, such as three seconds, for example, or if the time since the most recently sensed R wave exceeds a predetermined time period, such as three seconds, for example.”), and that when the pause is detected (para. (63): “ According to an embodiment of the present invention, asystole is detected for the channel, for example, either by determining whether one of the 12 R-R intervals is greater than a predetermined time period, such as three seconds, for example, or if the time since the most recently sensed R wave exceeds a predetermined time period, such as three seconds, for example.”).
It would have been obvious to combine the true positive determination, as disclosed by Dawoud, with the methods of detecting a pause associated with asystole between QRS peaks as disclosed by Ghanem. Detecting a pause between peaks is a technique for indicating asystole, as disclosed in Ghanem. Additionally, one of ordinary skill in the art would recognize that a pause is confirmation of asystole, and that a true positive would be determined from a pause, as Ghanem discloses that asystole can be detected this way. Therefore, it would have been obvious to implement the technique for confirming asystole in the method of Dawoud.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to OWEN LEWIS MARSH whose telephone number is (571)272-8584. The examiner can normally be reached 7:30am – 5pm (M-Th), and 8am – noon (F).
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jennifer McDonald can be reached at (571) 270-3061. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Additionally, SPE Carl Layno may be reached at (571) 272-4949.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/O.L.M./Examiner, Art Unit 3796
/CARL H LAYNO/Supervisory Patent Examiner, Art Unit 3796
Prosecution Insights