DETAILED ACTION
This Office Action is in response to the communication dated 12 January 2026 concerning Application No. 18/419,977 filed on 23 January 2024.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
Status of Claims
Claims 1-20 are pending and currently under consideration for patentability; claims 1, 10, 11, and 20 have been amended.
Response to Arguments
Applicant's arguments filed 12 January 2026 have been fully considered but they are not persuasive.
Applicant argues that “Bogun discloses training a model to "to identify the site of origin of ventricular arrhythmias including VT exit sites and other sites resulting in ventricular arrhythmias,"…but does not disclose "training the ML algorithm to detect an arrythmia," as recited in claim 1” (Arguments, p. 7). The Examiner respectfully disagrees and maintains that Bogun’s disclosure of identifying the origin site of a ventricular arrhythmia is analogous to Applicant’s recitation of detecting an arrhythmia. For example, if one identifies the site of origin of a ventricular arrhythmia, as directed by Bogun, then one necessarily has detected an arrhythmia, as recited by Applicant. It is not possible to identify where an arrhythmia originated without first identifying that there was an arrhythmia. Therefore, the Examiner respectfully maintains that Bogun describes detecting an arrhythmia.
Applicant argues that Bogun is silent on "storing the activity level and the one or more heart rate parameters as part of a historical set of training data, the historical set of training data including previously recorded activity levels and previously recorded heart rate parameters," as recited in claim 1” (Arguments, p. 8). In support of this, Applicant argues that “Bogun discloses a "stored database of historical ECG signals," which may correspond to the claimed "historical set of ECG data," as recited in claim 1, but is silent on storing the activity level and the one or more heart rate parameters as part of a historical set of training data, the historical set of training data including previously recorded activity levels and previously recorded heart rate parameters," as recited in claim 1 (Arguments, p. 9, Applicant’s emphasis maintained). The Examiner respectfully disagrees, as Bogun describes “performing signal analysis on collected ECG signals, such as noise filtering, signal averaging, etc., and storing (and/or buffering) those ECG signals and transmitting the same to the computer 312 for further analysis and pace mapping” (Bogun, [0063]), which the Examiner respectfully submits is analogous to “storing…one or more heart rate parameters” as recited. As agreed by Applicant, Bogun also describes using “a stored database of historical ECG signals,” which the Examiner respectfully submits is analogous to using “previously recorded” parameters. Therefore, the Examiner respectfully maintains that Bogun describes “storing the activity level and the one or more heart rate parameters as part of a historical set of training data, the historical set of training data including previously recorded activity levels and previously recorded heart rate parameters” as recited.
Applicant’s Terminal Disclaimer dated 12 January 2026 has been accepted, rendering moot the rejections of claims 1-20 on the grounds of obviousness-type double patenting.
Claim Rejections - 35 USC § 103
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Bogun et al. (US 2014/0107510 A1) in view of Osorio (US 2014/0275840 A1) and Shmueli (WO 2012/140559 A1).
Regarding claims 1 and 11, Bogun describes a method and system comprising
determining, using a machine learning algorithm ([0030] - [0031]), one or more heart rate parameters of a user ([0030])
training the ML algorithm to detect an arrythmia ([0006], [0053]) by
storing the one or more heart rate parameters as part of a historical set of training data, the historical set of training data including previously recorded heart rate parameters ([0053], [0060], [0063])
storing the ECG data as part of a historical set of ECG data comprising previously recorded ECG data ([0053], [0060], [0063])
training the ML algorithm to detect an arrythmia using the historical set of training data and the historical set of ECG data ([0020], [0032], [0058])
Specifically regarding claim 11, Bogun describes a set of sensors configured to sense the one or more heart rate parameters and a computing device communicatively coupled to the set of sensors ([0063]).
Bogun does not explicitly disclose
comparing an activity level of a user with one or more heart rate parameters of the user to determine whether a discordance is present between the activity level and the one or more heart rate parameters
in response to detecting that the discordance is present between the activity level and the one or more heart rate parameters, performing an electrocardiogram of the user to obtain ECG data of the user
However, Osorio also describes a method for monitoring a patient, including comparing an activity level of a user with one or more heart rate parameters of the user ([0057] - [0058], [0071], [0074]) to determine whether a discordance is present between the activity level and the one or more heart rate parameters ([0029], [0044] - [0045]) and, in response to determining that the discordance is present between the activity level and the one or more heart rate parameters, indicating the possibility of a pathological body state ([0003]) such as an arrhythmia ([0071]). Similarly, Shmueli also describes a method for monitoring a patient, including, upon initially being alerted to a possible pathological state such as a possible arrhythmia, performing an electrocardiogram of the user to obtain ECG data of the user (p 12:14-32). As Osorio and Shmueli are also directed towards patient monitoring and are in a similar field of endeavor, it would have been obvious to a person having ordinary skill in the art at the time the invention was filed to incorporate discordance monitoring and ECG triggering steps similar to those described by Osorio and Shmueli into the method described by Bogun, as doing so advantageously allows for an overall machine learning model which can screen for arrhythmia events by monitoring a patient’s cardiac parameters and activity.
Regarding claims 2 and 12, Osorio describes wherein the activity level of the user and the one or more heart rate parameters of the user are sensed within a threshold amount of time of each other ([0029], in order to determine if a heart rate increase is commensurate with an activity level, it would have been obvious to a person having ordinary skill in the art at the time the invention was filed to measure the two quantities within a threshold amount of time, as doing so allows for such a correlation).
Regarding claims 3 and 13, Osorio describes wherein the one or more heart rate parameters comprise a heart rate of the user ([0042]).
Regarding claims 4 and 14, Osorio describes wherein the one or more heart rate parameters comprise a heart rate of the user and a heart rate variability of the user ([0042]).
Regarding claims 5, 6, 15, and 16, although Bogun, Osorio, and Shmueli do not explicitly disclose the two discordance scenarios recited in the claims (heart rate increase, HRV increase, activity at rest; heart rate increase, HRV decrease, activity at rest), the Examiner respectfully directs Applicant to Osorio’s figure 8 and corresponding description in paragraphs [0077] - [0080], which describe monitoring for discordance between the user’s activity level and body data such as heart rate and HRV. Based on this, the Examiner respectfully submits that it would have been obvious to a person having ordinary skill in the art at the time the invention was filed to use any combination of changes in body parameters and activity level values as would be relevant for monitoring the patient, as doing so advantageously allows the resulting method to accurately determine discordances between the body data and the activity level.
Regarding claims 7 and 17, Bogun describes the use of the machine learning algorithm ([0030] - [0031]), and Osorio describes wherein the method uses biometric data of the user to detect whether a discordance is present between the activity level and the one or more heart rate parameters ([0029]).
Regarding claims 8 and 18, Osorio describes wherein the activity level of the user and each of the one or more heart rate parameters of the user comprise a range of values ([0029] - [0030]).
Regarding claims 9 and 19, Osorio describes wherein the range of values for each of the activity level of the user and the one or more heart rate parameters is based on biometric data of the user ([0029] - [0030]).
Regarding claims 10 and 20, Bogun describes wherein the arrhythmia is ventricular tachycardia ([0016]).
Statement on Communication via Internet
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“Recognizing that Internet communications are not secure, I hereby authorize the USPTO to communicate with the undersigned and practitioners in accordance with 37 CFR 1.33 and 37 CFR 1.34 concerning any subject matter of this application by video conferencing, instant messaging, or electronic mail. I understand that a copy of these communications will be made of record in the application file.”
Please refer to MPEP 502.03 for guidance on Communications via Internet.
Conclusion
THIS ACTION IS MADE FINAL. 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 Ankit D. Tejani, whose telephone number is 571-272-5140. The Examiner may normally be reached on Monday through Friday, 8:30AM through 5:00PM EST. 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, Carl Layno, can be reached by telephone at 571-272-4949. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. 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 at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (in USA or Canada) or 571-272-1000.
/Ankit D Tejani/
Primary Examiner, Art Unit 3792