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 .
Status of Claims
Claims 1-10, 12-18, 20-22 has been considered and are addressed below. Claims 11 and 19 has been cancelled.
Response to Arguments/Amendments
Applicant’s amendments filed on 3-24-26 has been entered and are addressed below.
Applicant argues that the prior art does not teach ECG waveform and interval data are inputted in machine learning. Examiner respectfully disagrees. Paragraph 127 of Sullivan recites “acquiring a first set of physiological information of a subject received during a first period of time and based at least in part on a first ECG signal of the subject, and a second set of physiological information of the subject received during a second period of time; calculating first and second risk scores associated with estimating a risk of a potential cardiac arrhythmia event for the subject based on applying the first and second sets of physiological information to one or more machine learning classifier models trained on training metrics” which reads on ECG and interval data.
Applicant argues that in claim 9 the prior art does not teach an ensemble of boosted trees. Examiner respectfully disagrees. Sullivan paragraph 338 recites “a number of times the risk scores transgress the threshold may be noted and a trend of such transgressions can be extracted from such data. For a gradient boosting model, the resulting prediction score trend ranges in values given by the logit transformation of the underlying probability score, (e.g., values typically fall within the range of −4.5 to 4.5, where a logit value of 0 corresponds to a probability value of 0.5)”, which reads on boosted trees. Additionally paragraph 314 of Sullivan teaches “machine learning tool can include but is not limited to classification and regression tree decision models, such as random forest and gradient boosting, (e.g., implemented using R or any other statistical/mathematical programming language)”, which reads on the limitation.
Applicant argues that the amendments overcome the 101 rejection. Examiner respectfully disagrees. The amendments are addressed below.
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 1-10, 12-18, 20-22 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Claims 1-10, 12-18, 20-22 are drawn to a system and method which is/are statutory categories of invention (Step 1: YES).
Independent claims 1, and 15 recite “in response to input received from the user interface regarding a potential cardiac even, transmit a command”, “process electrocardiogram waveform associated with a potential cardiac event to extract interval data associated with potential cardiac event”, “input the ECG waveform and the interval data into a trained machine learning model”, “determine by the machine training model the potential cardiac event comprises a normal rhythm”.
If a claim limitation, under its broadest reasonable interpretation, covers managing personal behavior or relationships or interactions between people, then it falls within the “certain methods of organizing human activity” grouping of abstract ideas. Accordingly, the claims recite an abstract idea (Step 2A Prong One: YES).
This judicial exception is not integrated into a practical application. The claims are abstract but for the inclusion of the additional elements including, “mobile computing device comprising memory and one or more processors, “medical device”, wherein the memory stores instructions” which are additional elements that are recited at a high level of generality such that they amount to no more than mere instruction to apply the exception using generic computer components. See: MPEP 2106.05(f).
The additional elements are merely incidental or token additions to the claim that do not alter or affect how the process steps or functions in the abstract idea are performed (e.g., the “processor” language is incidental to what it is “configured” to perform). Therefore, the claimed additional elements do not add meaningful limitations to the indicated claims beyond a general linking to a technological environment. See: MPEP 2106.05(h).
The claims does not recite additional element which amounts to extra-solution activity concerning mere data gathering. The specification (e.g., as excerpted above) does not provide any indication that the additional elements are anything other than well‐understood, routine, and conventional functions when claimed in a merely generic manner (as they are here). See: MPEP 2106.05(g).
Further, the claimed additional elements, identified above, are not sufficient to amount to significantly more than the judicial exception because they are generic components that are not integrated into the claim because they are merely incidental or token additions to the claim that do not alter or affect how the process steps or functions in the abstract idea are performed. Therefore, the claimed additional elements do not add meaningful limitations to the indicated claims beyond a general linking to a technological environment. See: MPEP 2106.05(h).
The combination of these additional elements is no more than mere instructions to apply the exception using generic computer components. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
Hence, the additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Accordingly, the claims are directed to an abstract idea (Step 2A Prong Two: NO).
Step 2B:
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, using the additional elements to perform the abstract idea amounts to no more than mere instructions to apply the exception using generic components. Mere instructions to apply an exception using a generic components cannot provide an inventive concept. See: MPEP 2106.05(f).
Further, the claimed additional elements, identified above, are not sufficient to amount to significantly more than the judicial exception because they are generic components that are not integrated into the claim because they are merely incidental or token additions to the claim that do not alter or affect how the process steps or functions in the abstract idea are performed. Therefore, the claimed additional elements do not add meaningful limitations to the indicated claims beyond a general linking to a technological environment. See: MPEP 2106.05(h).
Further, the claimed additional elements, identified above, are not sufficient to amount to significantly more than the judicial exception because they are generic components that are configured to perform well-understood, routine, and conventional activities previously known to the industry. See: MPEP 2106.05(d). Said additional elements are recited at a high level of generality and provide conventional functions that do not add meaningful limits to practicing the abstract idea. The originally filed specification supports this conclusion at Figure 1, and
Paragraph 75 recite “computing device 300 includes a bus 310 that, directly and/or indirectly, couples one or more of the following devices: a processor 320, a memory 330, an input/output (I/O) port 340, an I/O component 350, and a power supply 360. Any number of additional components, different components, and/or combinations of components may also be included in the computing device 300.”
Paragraph 80 recite “a presentation component configured to present information to a user such as, for example, a display device, a speaker, and/or the like, and/or an input component such as, for example, a microphone, a joystick, a wireless device, a keyboard, a pen, a voice input device, a touch input device, a touch-screen device, an interactive display device, a mouse, and/or the like”.
Paragraph 47 recite “Medical devices can be equipped with one or more sensing devices (e.g., sensors, electrodes) and programmed to sense physiological data such as electrocardiogram (ECG) data”.
The claims does not recite additional element which amounts to extra-solution activity concerning mere data gathering. The specification (e.g., as excerpted above) does not provide any indication that the additional elements are anything other than well‐understood, routine, and conventional functions when claimed in a merely generic manner (as they are here). See: MPEP 2106.05(g).
Viewing the limitations as an ordered combination, the claims simply instruct the additional elements to implement the concept described above in the identification of abstract idea with routine, conventional activity specified at a high level of generality in a particular technological environment.
Hence, the claims as a whole, considering the additional elements individually and as an ordered combination, do not amount to significantly more than the abstract idea (Step 2B: NO).
Dependent claim(s) 2-10, 12-14, 16-18, 20-22 when analyzed as a whole, considering the additional elements individually and/or as an ordered combination, are held to be patent ineligible under 35 U.S.C. 101 because the additional recited limitation(s) fail(s) to establish that the claim(s) is/are not directed to an abstract idea without significantly more. These claims fail to remedy the deficiencies of their parent claims above, and are therefore rejected for at least the same rationale as applied to their parent claims above, and incorporated herein. Additionally, the devices mentioned in dependents claim are used as input devices.
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.
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claim(s) 1-10, 12-18, 20-22 is/are rejected under 35 U.S.C. 103 as being unpatentable over Sullivan (US 2016/0135706) in view of Esboldt (US 2025/0017537).
With respect to claim 1 Sullivan teaches A system comprising: a user interface, a mobile computing device comprising memory and one or more processors, wherein the memory stores instructions that, when executed, cause the mobile computing device (Sullivan paragraph 260) to:
In response to input received from the user interface regarding a potential cardiac event, transmit a command to medical device (Sullivan teaches 507 “processing of data may occur at various locations (e.g., on various devices) of the early warning system (10 of FIG. 5). For example, at least some of the data (e.g., ECG data received by the medical device, data input via the application, etc.) may be processed on any combination of the computing device (e.g., the mobile device), the medical device, the base unit, a server, the internet, a cloud hosted server, and/or a second medical device (e.g., a second medical device such as a defibrillator or a cardiac monitor that may be in communication with the medical device). In some implementations, patient data (e.g., ECG data) is transmitted to the mobile device, and at least some of the processing of the patient data is performed on the mobile device”)
Process an electrocardiogram (ECG) waveform generated by the medical device and associated with a potential cardiac event to extract interval data associated with the potential cardiac event (Sullivan paragraph 371 “electrophysiologic data can include electrocardiogram recordings of varying time length. For example, recordings of 45 to 60 seconds in length can be obtained once per subject and/or at time intervals” and 409 “”Patient data may be used in conjunction with patient-specific ECG data for data processing and display, or it may be used to correlate information extracted from the ECG data. At stage 774, a VCG signal is determined (e.g., generated) based on the received ECG signal. ECG data provides a time-dependent voltage that describes the electrical activity of the heart, which is treated like a dipole having an origin at the center of the patient's heart),
input the ECG waveform and the interval data into a trained machine learning model (Sullivan paragraph 127 “A medical premonitory event estimation system, comprising: a nontransitory computer-readable storage medium in communication with one or more processors and having instructions stored thereon which, when executed by the one or more processors, cause the one or more processors to perform operations comprising: acquiring a first set of physiological information of a subject received during a first period of time and based at least in part on a first ECG signal of the subject, and a second set of physiological information of the subject received during a second period of time; calculating first and second risk scores associated with estimating a risk of a potential cardiac arrhythmia event for the subject based on applying the first and second sets of physiological information to one or more machine learning classifier models trained on training metrics comprising at least one of i) cardiac electrophysiology metrics of a first plurality of subjects, and ii) at least one of demographic metrics and medical history metrics of the first plurality of subjects, wherein the one or more machine learning classifier models is validated on validation metrics of a second plurality of subjects, and wherein one or more thresholds of the one or more machine learning classifier models is set based on the validation; providing at least the first and second risk scores associated with the potential cardiac arrhythmia event as a time changing series of risk scores; and classifying the first and second risk scores associated with estimating the risk of the potential cardiac arrhythmia event for the subject based on the one or more thresholds”), and
determine, by the trained machine learning model, that the potential cardiac event comprises a normal rhythm (Sullivan paragraph 348 “Heart rate, heart rate variability, and heart rate irregularities metrics include metrics that are derived from estimation of RR (R-wave to R-wave) intervals as detected by a QRS detector. In some implementations, evaluation of these metrics includes discriminating between normal beats (N) and ectopic beats (e.g. PVC). For example, a PVC detector can be used to identify PVCs. Intervals between two normal beats are called NN intervals”).
Sullivan does not teach normal sinus rhythm.
Esboldt teaches labeled ECG data may identify a particular cardiac event, including but not limited to ventricular tachycardia, bradycardia, atrial fibrillation, pause, normal sinus rhythm, or artifact/noise (Esboldt paragraph 54).
One of ordinary skill in the art would have found it obvious to combine the teachings of Sullivan with Esboldt at the time of filing with the motivation of assisting with processing and analyzing thousands and thousands of cardiac events and identifying which cardiac events ultimately warrant review by a patient care group (Esboldt paragraph 73).
Claim 15 is rejected as above.
With respect to claim 2 Sullivan teaches the system of claim 1, wherein the instructions, when executed, further cause the mobile computing device to: generate an alert in response to the determining that the potential cardiac event contains the normal cardiac rhythm (Sullivan paragraph 380).
With respect to claim 3 Sullivan teaches the system of claim 2, wherein the instructions, when executed, further cause the mobile computing device to: display the alert and the ECG waveform on the user interface (Sullivan paragraph 241).
Claim 16 is rejected as above.
With respect to claim 4 Sullivan teaches the system of claim 1, wherein the interval data comprises data relating to peaks of R waves (Sullivan paragraph 242).
Claim 17 is rejected as above.
With respect to claim 5 Sullivan teaches the system of claim 4, wherein the data relating to peaks of R waves includes a time interval between successive R waves (Sullivan paragraph 242).
With respect to claim 6 Sullivan teaches the system of claim 1, wherein the instructions, when executed, further cause the mobile computing device to: process the ECG waveform to generate non-linear features, and input the non-linear features into the trained machine learning mode (Sullivan paragraph 464).
With respect to claim 7 Sullivan teaches the system of claim 1, wherein the instructions, when executed, further cause the mobile computing device to: prevent the potential cardiac event from being forwarded to a physician (Sullivan paragraph 380).
Claim 18 is rejected as above.
With respect to 8 Sullivan teaches the system of claim 1, wherein the trained machine learning model comprises classification model (Sullivan paragraph 127).
With respect to claim 9 Sullivan teaches the system of claim 1, wherein the trained machine learning model comprises an ensemble of boosted trees (Sullivan paragraph 466 and 338).
With respect to claim 10 Sullivan teaches the system of claim 1, wherein the instructions, when executed, further cause the mobile computing device to: determine, based on sensor data other than the ECG waveform, that a condition of a patient is worsening, and generate an alert in response to the condition worsening (Sullivan paragraph 380).
With respect to claim 12 Sullivan teaches the system of claim 11, wherein the mobile computing device includes a display configured to display a user interface, wherein the input is a selection of an icon on the user interface (Sullivan paragraph 241).
With respect to claim 13 Sullivan teaches the system of claim 11, further comprising: the medical device communicatively coupled to the mobile computing device, wherein the medical device is programmed to record the ECG waveform in response to the medical device receiving the command wherein the medical device is an implantable medical device (Sullivan paragraph 466 and 257).
Claim 20 is rejected as above.
With respect to claim 14 Sullivan teaches the system of claim 1, wherein the mobile computing device is programmed to determine, via the trained machine learning model, that the potential cardiac event is only either an abnormal cardiac event or a normal cardiac event (Sullivan paragraph 380).
With respect to claim 21, Sullivan in view of Esboldt teaches the method of claim 15, wherein the trained machine learning model is programed to make a binary decision regarding whether the potential cardiac even is normal sinus rhythm or abnormal rhythm (Sullivan paragraph 241).
Claim 22 is rejected as above.
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 REGINALD R REYES whose telephone number is (571)270-5212. The examiner can normally be reached 8:00-4:30 M-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, Shahid R. Merchant can be reached at (571) 270-1360. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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REGINALD R. REYES
Primary Examiner
Art Unit 3684
/REGINALD R REYES/Primary Examiner, Art Unit 3684
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