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 .
Notice of Reply and Response to Arguments
This communication is responsive to the amendment(s) and/or argument(s) filed 11/20/25. The previous ground(s) of rejection is/are withdrawn and the following new and/or reiterated ground(s) of rejection is/are set forth hereinbelow.
Applicant’s arguments, see pages 7-9, filed 11/20/25, with respect to the rejection of the claims under 101 and 102(a)(2) have been fully considered and are persuasive. The 101 and 102(a)(2) rejections of the claims has/have been withdrawn.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-4, 6-15, and 17-20 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Leboeuf et al. (WO 2021/046237 A1, hereinafter Leboeuf).
For claim 1, Leboeuf discloses a system (Figs 3-6,16,18-21) (Pgs 15-83), comprising:
at least one programmable processor (Fig 3) ; and
a non-transitory machine-readable medium storing instructions which, when executed by the at least one programmable processor (Fig 3), cause the at least one programmable processor to perform operations comprising:
receiving patient data having one or more cardiovascular waveforms related to a cardiac cycle of a vasculature of a patient (310) (Figs 3-6,16,18-21) (Pgs 15-83, especially 29-37);
calculating, from the one or more cardiovascular waveforms, at least one output from a signal analysis method (320, 330) (Figs 3-6,16,18-21) (Pgs 15-83, especially 37-78);
inputting, into a trained artificial intelligence (Al) model, the one or more cardiovascular waveforms (Figs 3-6,16,18-21) (Pgs 15-83, especially 29-33, 41, 46, 54, 75, 79-82);
determining, utilizing the trained AI model, clinically relevant output parameters for the signal analysis method (especially in 320, 330) (Figs 3-6,16,18-21) (Pgs 15-83, especially 29-33, 41, 46, 54, 75, 79-82);
training the trained Al model to compute the clinically relevant output parameters (Figs 3-6,16,18-21) (Pgs 15-83, especially 29-33, 41, 46, 54, 75, 79-82) by at least:
inputting training data comprising first intrinsic phase training data, wherein the training data is from a subject that had a specific cardiovascular disease prior to collecting of the training data (Figs 3-6,16,18-21) (Pgs 15-83, especially 29-33, 41, 46, 54, 75, 79-82); and
in response to determining the output parameters, providing information about an underlying pathology to a user (340) (Figs 3-6,16,18-21) (Pgs 15-83).
For claim 2, Leboeuf discloses the system of claim 1, wherein the one or more cardiovascular waveforms are from a pulse pressure measurement or a pulse oximeter measurement (Figs 3-6,16,18-21) (Pgs 15-83).
For claim 3, Leboeuf discloses the system of claim 1, the operations further comprising:
calculating, from the one or more cardiovascular waveforms, a first intrinsic frequency and a first intrinsic phase associated with the cardiac cycle (especially in 320, 330) (Figs 3-6,16,18-21) (Pgs 15-83, especially 27-78); and
calculating, from the one or more cardiovascular waveforms, a second intrinsic frequency and a second intrinsic phase associated with the vasculature (especially in 320, 330) (Figs 3-6,16,18-21) (Pgs 15-83, especially 27-78),
wherein the clinically relevant output parameters comprise the first intrinsic frequency, the first intrinsic phase, the second intrinsic frequency, and the second intrinsic phase (Figs 3-6,16,18-21) (Pgs 15-83).
For claim 4, Leboeuf discloses the system of claim 3, the operations further comprising:
calculating, from the one or more cardiovascular waveforms, a diastolic intrinsic envelope, and a systolic intrinsic envelope, and relative height of a dicrotic notch (RHDN) (especially in 320, 330) (Figs 3-6,16,18-21) (Pgs 15-83, especially 27-78), and
wherein the calculating of the first intrinsic frequency, the first intrinsic phase, the second intrinsic frequency, and the second intrinsic phase comprises minimization of a function of the calculated frequencies, phases, and envelopes (especially in 320, 330) (Figs 3-6,16,18-21) (Pgs 15-83, especially 27-78).
For claim 6, Leboeuf discloses the system of claim 1, the operations further comprising: obtaining a pulse pressure waveform measurement (via 110) (Figs 3-6,16,18-21) (Pgs 15-83), wherein the calculating of the at least one output from the signal analysis method is based on the pulse pressure waveform measurement which is one or more of a carotid pressure waveform, an aortic wall waveform, a carotid vessel wall waveform, a radial pressure waveform, a radial vessel wall waveform, a brachial pressure waveform, a brachial vessel wall waveform, a femoral pressure waveform, a femoral vessel wall waveform, or a pulse-ox waveform (especially in 320, 330) (Figs 3-6,16,18-21) (Pgs 15-83, especially 27-78).
For claim 7, Leboeuf discloses the system of claim 1, wherein the calculating of the at least one output from the signal analysis method is based on a measurement of blood flow (320, 330) (Figs 3-6,16,18-21) (Pgs 15-83, especially 37-78).
For claim 8, Leboeuf discloses the system of claim 1, further comprising a client device (1200) (Figs 3-6,16,18-21) (Pgs 15-83, especially 37-78) having a diagnosis module that includes the trained Al model and provides the information about the underlying pathology to a user as a determination of a specific cardiovascular disease (Figs 3-6,16,18-21) (Pgs 15-83, especially 37-78).
For claim 9, Leboeuf discloses the system of claim 8, wherein the client device is a smartphone or a wearable device (1200).
For claim 10, Leboeuf discloses the system of claim 1, the operations further comprising: calculating, from the one or more cardiovascular waveforms, a Fourier transform harmonic information truncated by any number of frequency of any cardiovascular waveform (especially in 320, 330) (Figs 3-6,16,18-21, especially Fig 3) (Pgs 15-83, especially 37-78).
For claim 11, Leboeuf discloses the system of claim 1, the operations further comprising: calculating, from the one or more cardiovascular waveforms, a basis function expansion extracted from a cardiovascular waveform (especially in 320, 330) (Figs 3-6,16,18-21, especially Fig 3) (Pgs 15-83, especially 37-78).
For claim 12, Leboeuf discloses a non-transitory, machine-readable medium (Fig 3) storing instructions (Fig 3) (Pgs 15-83, especially 37-78) which, when executed by at least one programmable processor, cause the at least one programmable processor to perform operations comprising:
receiving patient data having one or more waveforms related to a cardiac cycle or a vasculature of a patient (310) (Figs 3-6,16,18-21) (Pgs 15-83, especially 29-37);
calculating, from the one or more waveforms, at least one clinically relevant parameter from a signal analysis method (320, 330) (Figs 3-6,16,18-21) (Pgs 15-83, especially 37-78);
inputting, into a trained artificial intelligence (Al) model, the one or more waveforms (Figs 3-6,16,18-21) (Pgs 15-83, especially 29-33, 41, 46, 54, 75, 79-82), the AI model comprising a neural network (Figs 3-6,16,18-21) (Pgs 15-83, especially 29-33, 41, 46, 54, 75, 79-82);
determining, utilizing the trained Al model, a physiological parameter (Figs 3-6,16,18-21) (Pgs 15-83, especially 29-33, 41, 46, 54, 75, 79-82);
training the neural network to detect signal analysis outputs or clinical or physiological indices directly (Figs 3-6,16,18-21) (Pgs 15-83, especially 29-33, 41, 46, 54, 75, 79-82) by at least:
inputting training data comprising first intrinsic phase training data (Figs 3-6,16,18-21) (Pgs 15-83, especially 29-33, 41, 46, 54, 75, 79-82), wherein the training data is from a patient with a specific cardiovascular disease which is a target for diagnosis (Figs 3-6,16,18-21) (Pgs 15-83, especially 29-33, 41, 46, 54, 75, 79-82); and
in response to determining the physiological parameter, providing an indication of a cardiac risk to the patient (340) (Figs 3-6,16,18-21) (Pgs 15-83).
For claim 13, Leboeuf discloses the medium of claim 12, wherein the one or more waveforms are from a pulse pressure measurement or a pulse oximeter measurement (Figs 3-6,16,18-21) (Pgs 15-83).
For claim 14, Leboeuf discloses the medium of claim 12, the operations further comprising:
calculating, from the one or more waveforms, a first intrinsic frequency and a first intrinsic phase associated with the cardiac cycle (especially in 320, 330) (Figs 3-6,16,18-21) (Pgs 15-83, especially 27-78); and
calculating, from the one or more waveforms, a second intrinsic frequency and a second intrinsic phase associated with the vasculature (especially in 320, 330) (Figs 3-6,16,18-21) (Pgs 15-83, especially 27-78),
wherein the physiological parameter comprises myocardial parameters, and the myocardial parameters comprise the first intrinsic frequency, the first intrinsic phase, the second intrinsic frequency, and the second intrinsic phase (Figs 3-6,16,18-21) (Pgs 15-83, especially 27-78).
For claim 15, Leboeuf discloses the medium of claim 14, the operations further comprising:
calculating, from the one or more waveforms, a diastolic intrinsic envelope, and a systolic intrinsic envelope (especially in 320, 330) (Figs 3-6,16,18-21) (Pgs 15-83, especially 27-78),
wherein the calculating of the first intrinsic frequency, the first intrinsic phase, the second intrinsic frequency, and the second intrinsic phase comprises minimization of a function of calculated frequencies, phases, and envelopes (Figs 3-6,16,18-21) (Pgs 15-83, especially 27-78).
For claim 17, Leboeuf discloses the medium of claim 12, the operations further comprising:
obtaining a pulse pressure waveform measurement (via 110) (Figs 3-6,16,18-21) (Pgs 15-83), wherein the calculating of the clinically relevant or physiological parameters are based on the pulse pressure waveform measurement, which is one or more of a carotid pressure waveform, an aortic wall waveform, a carotid vessel wall waveform, a radial pressure waveform, a radial vessel wall waveform, a brachial pressure waveform, a brachial vessel wall waveform, a femoral pressure waveform, a femoral vessel wall waveform, pulmonary vessel wall waveform, pulmonary pressure waveform, or a pulse-ox waveform (especially in 320, 330) (Figs 3-6,16,18-21) (Pgs 15-83, especially 27-78).
For claim 18, Leboeuf discloses the medium of claim 12, wherein the calculating of the clinically relevant or physiological parameters is based on a measurement of blood flow (320, 330) (Figs 3-6,16,18-21) (Pgs 15-83, especially 37-78).
For claim 19, Leboeuf discloses the medium of claim 12, wherein the medium and the processor reside on a client device (1200) having a diagnosis module that includes the trained Al model and provides the indication of the cardiac risk to the patient for a cardiovascular disease (Figs 3-6,16,18-21) (Pgs 15-83, especially 37-78).
For claim 20, Leboeuf discloses the medium of claim 19, wherein the client device is a smartphone or a wearable device (1200).
Conclusion
The cited prior art made of record on the accompanying PTO-892 and not relied upon is considered pertinent to applicant's disclosure, relating to means and methods for configuring AI to indicate cardiac risk based on sensed cardiovascular waveforms.
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 Jeffrey G. Hoekstra whose telephone number is (571)272-7232. The examiner can normally be reached Monday through Thursday from 5am-3pm 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, Charles A. Marmor II can be reached at (571)272-4730. 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 (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.
Jeffrey G. Hoekstra
Primary Examiner
Art Unit 3791
/JEFFREY G. HOEKSTRA/ Primary Examiner, Art Unit 3791