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 .
This is a corrected non-final rejection that takes place of the rejection mailed on 12/9/25.
Information Disclosure Statement
The information disclosure statement(s) (IDS) submitted on 4/29/24 has/have been acknowledged and is/are being considered by the Examiner.
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.
Claim(s) 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1- Claim 1
Claim 1 and dependent claims 2-20 are drawn to a method and thus meet the requirements for step 1.
Step 2a (prong 1) - Claim 1
Claims 1 recites the step of “determining … a depression score” Under the broadest reasonable interpretation, this step covers a concept capable of being performed in the human mind, and thus falls within the mental processes grouping of abstract ideas. Other than reciting the method is “computer-implemented” in the preamble, nothing in the claim precludes the step from practically being performed in the mind.
Accordingly, claim 1 recites an abstract idea.
Step 2a (prong 2) – Claim 1
The judicial exception is not integrated into a practical application. Claim 1 recites the additional elements of:
Retrieving, via one or more processors, blood pressure data and/or heart rate data of a patient is insignificant extra-solution activity (i.e., data gathering),
Receiving, via the one or more processors, from a patient user device corresponding to the patient, a plurality of answers corresponding to respective depression survey questions is insignificant extra-solution activity (i.e., data gathering), and
Presenting, via the one or more processors, to a clinician, blood pressure data, depression score and social determinants of health score is recited at a high level of generality (i.e., as generic devices, a “computer-implemented” method, performing generic computer functions like sending, receiving, and visually displaying data) is insignificant extra-solution activity (i.e., data output).
These steps do not integrate the abstract idea into a practical application because they are insignificant extra solution activity.
Step 2b- Claim 1
The additional elements when considered individually and in combination are not enough to qualify as significantly more than the abstract idea. As discussed above with respect to the integration of the abstract idea into a practical application, providing a (blood pressure data, depression score, social determinants of heath score) is recited at a high level of generality (i.e., as generic devices, a “computer-implemented” method, performing generic computer functions like sending, receiving, and visually displaying data). Further, retrieving data, receiving answers from surveys is considered data gathering. It is noted that the one or more processors are recited at a high level of generality.
The additional elements that were considered insignificant extra solution activity have been re-analyzed and do not amount to anything more than what is well-understood, routine and conventional when considered individually and in combination with evidence provided. Specifically:
Retrieving blood pressure/heart rate data of a patient is well understood, routine, and conventional (i.e., receiving data MPEP 2106.05(d)(II)).
Receiving answers from a survey is well understood, routine, and conventional (i.e., receiving data MPEP 2106.05(d)(II)).
Determining a depression score of the patient based on the received answers from the survey is well-understood routine and conventional (i.e., gathering data/statistics MPEP 2106.05(d)(II)).
Determining a social determinants score based on the received answers from the survey is well-understood routine and conventional (i.e., gathering data/statistics MPEP 2106.05(d)(II)).
Presenting data and scores to a clinician is considered to be well-understood, routine, and conventional (i.e., presenting data MPEP 2106.05(d)(II)).
Claim 1 is thus consider to be directed to an abstract idea without significantly more.
Claims 2-20 depend from claim 1. The devices utilized to collect the data as stated in claims 2-3 and 16 are stated at a high level of generality in applicant’s specification (“a smart watch; a touchpad device; a steering wheel; a smart handheld device; a waveform analysis kiosk; and a connected device”) and are merely used as a tool to carry out the data gathering. The type of data analyzed as stated in claims 4-5 and 14 are considered extra solution activity. Claims 6-11 and 16-17 are directed toward the extra solution activity of presenting data. Claims 12-13, 15 and 18 are directed to the extra solution activity of gathering data/statistics. Claims 19-20 are directed toward the extra solution activity of presenting/outputting data. Thus, the dependent claim do not change the overall analysis that claims 2-5, 12-16, and 18-20 are also directed to an abstract idea.
Claim Rejections - 35 USC § 112
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.
Claims 1-20 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.
Claim 1 recites the limitation "a patient" in line 5. This is vague as it is unclear if this is the same or different limitation as the “a perinatal patient” from line 1.
Claim 1 recites the limitation “from diagnosis through twelve months postpartum to a childbirth event”. This is vague as it is unclear if the claim limitations are from diagnosis through twelve months or diagnosis through childbirth event. Further it is unclear how the timeframe can be 12 months postpartum (child birth) to a child birth event which occurs before postpartum.
Claims 2-20 are rejected for inheriting the same deficiencies as claim 1.
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)(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, 4-8 and 10-20 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Conward et al. (U.S. Pub. 2024/0079145 – filed 1/15/22 with priority to 1/15/21 hereinafter “Conward”).
Regarding claim 1, Conward discloses a computer-implemented method for monitoring a perinatal patient from diagnosis through twelve months postpartum to a childbirth event via real time patient data and alerts (e.g. Fig. 9; Paragraph 25), the method comprising: retrieving, via one or more processors (e.g. 150), blood pressure data and/or heart rate data of a patient from one or more electronic medical devices (e.g. 810; ¶¶37, 53); receiving, via the one or more processors (e.g. 150), from a patient user device corresponding to the patient, a plurality of answers corresponding to respective depression survey questions (e.g. 810; ¶¶16,20, 27); determining, via the one or more processors (e.g. 150), a depression score of the patient based on the received plurality of answers corresponding to respective depression survey questions (e.g. 820); receiving, via the one or more processors (e.g. 150), from the patient user device, a plurality of answers corresponding to social determinants of health survey questions (e.g. 810; ¶¶16, 2); determining, via the one or more processors (e.g. 150), a social determinants of health score of the patient based on the received plurality of answers corresponding to respective social determinants of health survey questions (e.g. 820; ¶¶100, 110); presenting, via the one or more processors (e.g. 150), to a clinician: (i) the blood pressure data and/or heart rate data of the patient, (ii) the depression score of the patient, and (iii) the social determinants of health score of the patient (e.g. 830).
Regarding claim 4, Conward further discloses wherein the blood pressure data and/or heart rate data comprises systolic blood pressure data, and diastolic blood pressure data (e.g. ¶37; “Blood pressure”).
Regarding claim 5, Conward further discloses wherein the blood pressure data and/or heart rate data include time stamps indicating when the blood pressure data and/or heart rate data was measured (e.g. ¶53).
Regarding claim 6, Conward further discloses determining, via the one or more processors, a recommendation for the patient based on (i) the blood pressure data and/or heart rate data of the patient, (ii) the depression score of the patient, and/or (iii) the social determinants of health score of the patient; and presenting, via the one or more processors, the recommendation to the clinician (e.g. ¶¶17, 45).
Regarding claim 7, Conward further discloses wherein the recommendation comprises a recommended treatment or a recommendation for an appointment with a clinician (e.g. ¶45).
Regarding claim 8, Conward further discloses wherein the clinician is a physician or a social worker (e.g. ¶45).
Regarding claim 10, Conward further discloses wherein the blood pressure data and/or heart rate data include time stamps indicating when the blood pressure data and/or heart rate data was measured; the received plurality of answers corresponding to respective depression survey questions include time stamps indicating when the patient answered the depression survey questions (e.g. ¶75); the received plurality of answers corresponding to respective social determinants of health survey questions include time stamps indicating when the patient answered the social health survey questions (e.g. ¶75); and the determination of the recommendation for the patient is further based on correlations between any of: (i) the time stamps indicating when the blood pressure data and/or heart rate data was measured, (ii) the time stamps indicating when the patient answered the depression survey questions, and/or (iii) the time stamps indicating when the patient answered the social determinants of health survey questions (e.g. ¶75).
Regarding claim 11, Conward further discloses wherein the determining the recommendation comprises routing, to a trained machine learning algorithm: (i) the blood pressure data and/or heart rate data of the patient, (ii) the depression score of the patient, and/or (iii) the social determinants of health score of the patient (e.g. ¶20).
Regarding claim 12, Conward further discloses training, via the one or more processors, a machine learning algorithm to determine recommended treatments by routing historical data into the machine learning algorithm; and wherein the historical data comprises historical: (i) blood pressure data and/or heart rate data of patients, (ii) depression scores of patients, (iii) social health scores of patients, (iv) treatments of patients, and/or (v) outcomes of treatments of the patients (e.g. ¶¶20, 45).
Regarding claim 13, Conward further discloses receiving, via the one or more processors, historical data; determining, via the one or more processors, a subset of the historical data corresponding to a particular racial group (e.g. ¶75); and training, via the one or more processors, a machine learning algorithm to determine recommendations by routing the subset of historical data into the machine learning algorithm (e.g. ¶75); and wherein the historical data comprises historical: (i) blood pressure data and/or heart rate data of patients, (ii) depression scores of patients, (iii) social health scores of patients, (iv) treatments of patients, and/or (v) outcomes of treatments of the patients (e.g. ¶75).
Regarding claim 14, Conward further discloses wherein the patient is a prenatal patient; the blood pressure data and/or heart rate data is prenatal blood pressure and/or prenatal heartrate data; the depression score is a prenatal depression score; and the social determinants of health score is a prenatal determinants of social health score (e.g. ¶¶20, 24).
Regarding claim 15, Conward further discloses determining, via the one or more processors, subscores of the social determinants of health score; andwherein the presenting comprises presenting, via the one or more processors, the social determinants of health score as a numerical value, and presenting, via the one or more processors, the subscores in graphical form (e.g. see Figs. 4-6; ¶¶49, 51, 74).
Regarding claim 16, Conward further discloses wherein: the patient is a postpartum patient; the blood pressure data and/or heart rate data is postpartum blood pressure and/or postpartum heartrate data (e.g. ¶24); the depression score is a postpartum depression score (e.g. see Fig. 8); the social determinants of health score is a postpartum determinants of social health score (e.g. see Fig. 8); and the method further comprises: receiving, via one or more processors, prenatal blood pressure data and/or prenatal heart rate data of the postpartum patient; receiving, via the one or more processors, from the patient user device corresponding to the postpartum patient, a plurality of prenatal answers corresponding to respective depression survey questions (e.g. see Fig. 8); determining, via the one or more processors, a prenatal depression score of the postpartum patient based on the received plurality of prenatal answers corresponding to respective depression survey questions (e.g. see Fig. 8); receiving, via the one or more processors, from the patient user device, a plurality of prenatal answers corresponding to social determinants of health survey questions (e.g. ¶75); determining, via the one or more processors, a prenatal social determinants of health score of the postpartum patient based on the received plurality of prenatal answers corresponding to respective social determinants of health survey questions (e.g. ¶75); and presenting, via the one or more processors, to a clinician: (i) the prenatal blood pressure data and/or prenatal heart rate data of the postpartum patient, (ii) the prenatal depression score of the postpartum patient, and (iii) the prenatal social determinants of health score of the postpartum patient (e.g. ¶75).
Regarding claim 17, Conward further discloses determining, via the one or more processors, a recommendation for the postpartum patient based on (i) the postpartum blood pressure data and/or postpartum heart rate data of the postpartum patient, (ii) the depression score of the postpartum patient, (iii) the social determinants of health score of the postpartum patient, (iv) the prenatal blood pressure data and/or prenatal heart rate data of the postpartum patient, (v) the prenatal depression score of the postpartum patient, and/or (vi) prenatal the social determinants of health score of the postpartum patient (e.g. ¶75); and presenting, via the one or more processors, the recommendation to the clinician (e.g. ¶¶75, 99, 109, 119, 131, 138).
Regarding claim 18, Conward further discloses training, via the one or more processors, a machine learning algorithm to determine recommendations by routing historical data into the machine learning algorithm; and wherein the historical data comprises historical: (i) prenatal and/or postpartum blood pressure data and/or prenatal and/or postpartum heart rate data of patients, (ii) prenatal and/or postpartum depression scores of patients, (iii) prenatal and/or postpartum social health scores of patients, (iv) treatments of patients, and/or (v) outcomes of treatments of the patients (e.g. see Fig. 2; ¶¶41-43).
Regarding claim 19, Conward further discloses if the depression score is below a depression score threshold value, alerting, via the one or more processors, the clinician (¶¶15, 52).
Regarding claim 20, Conward further discloses if the social determinants of health score is below a social determinants of health score threshold value, alerting, via the one or more processors, the clinician (¶¶15, 52).
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.
Claim(s) 2-3 is/are rejected under 35 U.S.C. 103 as being unpatentable over Conward as applied to claims 1, 4-8 and 10-20 above, and further in view of Yuasa et al. (U.S. Pub. 2014/0236028 hereinafter “Yuasa”).
Regarding claims 2-3, Conward discloses the claimed invention as disclosed in detail above, but is silent as to the type of blood pressure sensor used to collect the data that is inputted into the processor. However, Yuasa teaches that it is known in the art to use MEMs sensors as disclosed in Paragraph 62, Claims 2 and 18 to provide a known pressure sensor that senses the change in the tensile stress of the skin above the blood vessel, thereby producing a blood pressure without optical sensing. It would have been obvious to one having ordinary skill in the art at the time the invention was made to modify the system as taught by Conward, with the well known MEMs sensor as taught by Yuasa, since such a modification would provide the predictable results of using well known MEMs sensors, that sense the change in the tensile stress of the skin above the blood vessel, thereby producing a blood pressure.
Claim(s) 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Conward as applied to claims 1, 4-8 and 10-20 above, and further in view of Ozen Irmak et al. (U.S. Pub. 2022/0130518 hereinafter “Ozen”).
Regarding claims 2-3, Conward discloses the claimed invention as disclosed in detail above, but is silent as to the system recommending a time period to complete the recommendation. However, Ozen teaches that it is known in the art to output a time recommendation in Paragraph 71 to provide a set time for the recommendation to be completed thereby easing the burden from the patient. It would have been obvious to one having ordinary skill in the art at the time the invention was made to modify the system as taught by Conward, with the time recommendation as taught by Ozen, since such a modification would provide the predictable results of providing a set time for the recommendation to be completed thereby easing the burden from the patient.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to REX R HOLMES whose telephone number is (571)272-8827. The examiner can normally be reached Monday-Thursday 7:00AM-5:30PM.
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/REX R HOLMES/ Primary Examiner, Art Unit 3796