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 .
Election/Restrictions
Claims 10-20 are withdrawn from further consideration pursuant to 37 CFR 1.142(b) as being drawn to a nonelected species, there being no allowable generic or linking claim. Election was made without traverse in the reply filed on 9/28/2026.
Applicant’s election without traverse of species A, claims 1-9 in the reply filed on 9/28/2026 is acknowledged.
This office action is responsive to the amendment filed on 9/28/2026. As directed by the amendment, the status of the claim(s) are:
Claim(s) 1-20 is/are presently pending;
Claim(s) 10-20 is/are withdrawn;
Claim(s) 1-9 is/are examined on the merits.
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.
Claim(s) 2 is/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 2 recites the limitation "the first extracted features, the second extracted features, and the third extracted features". There is insufficient antecedent basis for this limitation in the claim. Note that claim 1 on which the instant claim depends recites the singular form “a first feature…a second feature…a third feature”; feature vs features, this inconsistency makes the instant claim indefinite since it is unclear whether the instant limitations refer to the same recitations of claim 1.
Claim Rejections - 35 USC § 103
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 (i.e., changing from AIA to pre-AIA ) 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.
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) 1-2, 5, 7-9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Atallah (US 20210186347 A1; 6/24/2021) in view of Sohn (US 20230218240 A1; 7/23/2023).
Regarding claim 1, Atallah teaches a system for predicting a characteristic of a neonate (Fig. 2) comprising:
a ballistographic monitoring device configured to measure movement of the neonate and create a ballistographic signal from the measured movement ([0031] “motion…ballistocardiography”; [0056] “ballistocardiography”);
a vital measurement device configured to measure a vitals measurement of the neonate and create a vital signal from the vitals measurement ([0014] “body temperature of the infant”; [0041]; [0042] “body temperature”);
a camera configured to capture an image of the neonate and create a camera signal from the image ([0035]);
a memory including instructions ([0015]; [0032]); and
at least one processor to execute the instructions to ([0015]; [0032]):
extract a first feature from the ballistographic signal ([0031]; [0033] “heart rate variability features”; [0056]);
extract a second feature from the vital signal ([0042]; [0044]);
extract a third feature from the camera signal ([0035]; [0042]; [0044]);
process the first feature, the second feature, and the third feature using a learning model trained for a characteristic of the neonate ([0059] “neural network”; [0075] “machine learning algorithm to automatically determine the infant health status”; claim 1); and
display from the learning model on a user interface ([0046] “control a user interface 112 to render (or output or provide) the determined heart rate variability feature, the determined health status of the infant, both the determined heart rate variability feature and the determined health status of the infant, or any other information, or any combination of information, resulting from the method disclosed herein”).
Atallah does not teach learning model trained to generate a prediction and display the prediction. However, Sohn teaches in the same field of endeavor (Abstract; Fig. 4; [0004] “infant”) learning model trained to generate a prediction and display the prediction ([0031]; [0039] “predicting…using a predetermined trained algorithm model”; [0067]-[0068] “output heart rate…stress index”). Thus it would have been obvious to a person of ordinary skill in the art before the effective filing date of the invention to modify the teaching of Atallah to include these features as taught by Sohn because this enables predicting using artificial intelligence in a contactless manner ([0002]).
Regarding claim 2, the combination of Atallah and Sohn teaches wherein the first extracted features, the second extracted features, and the third extracted features include the heart rate of the neonate (Atallah [0014] “heart rate of the infant”; Sohn [0011] “heart rate”), the breathing rate of the neonate (Atallah [0014] “respiration rate of the infant”; Sohn [0011] “respiratory rate”), or the movement pattern of the neonate (Atallah [0014] “a movement of the infant, an activity level of the infant”), the oxygenation level of the neonate (Atallah [0041] “blood oxygen saturation”; Sohn [0055] “remote PPG”), or the oxygen absorption value of the neonate (Atallah [0041] “blood oxygen saturation”; Sohn [0055] “remote PPG”; inherent to blood oxygen measurements). Thus it would have been obvious to a person of ordinary skill in the art before the effective filing date of the invention to modify the teaching of Atallah to include these features as taught by Sohn because this enables predicting using artificial intelligence in a contactless manner ([0002]).
Regarding claim 5, in the combination of Atallah and Sohn, Sohn teaches wherein the image defines an infrared (IR) image ([0056]) and a red image ([0047]). Thus it would have been obvious to a person of ordinary skill in the art before the effective filing date of the invention to modify the teaching of Atallah to include these features as taught by Sohn because this enables predicting using artificial intelligence in a contactless manner ([0002]).
Regarding claim 7, in the combination of Atallah and Sohn, Sohn teaches wherein the red image and the IR image comprise imaging data obtained from one or more regions of skin of the patient (Fig. 3; Fig. 5; [0047]; [0056]; claim 19). Thus it would have been obvious to a person of ordinary skill in the art before the effective filing date of the invention to modify the teaching of Atallah to include these features as taught by Sohn because this enables predicting using artificial intelligence in a contactless manner ([0002]).
Regarding claim 8, in the combination of Atallah and Sohn, Atallah teaches wherein the vital measurement device defines a heart rate monitor ([0014] “heart rate of the infant”), a blood pressure monitor, a pulse oximeter ([0041] “pulse oximeter”), a temperature probe ([0014] “body temperature of the infant”; [0041]; [0042] “body temperature”), or a respiratory ventilator.
Regarding claim 9, the combination of Atallah and Sohn teaches wherein the learning model is a machine learning model trained on historical and patient data (Atallah [0059]-[0060]; [0067]-[0068]; Sohn Fig. 1; [0039] “predicting…using a predetermined trained algorithm model”; [0048]; [0053] “learn a pattern..train the model”). Thus it would have been obvious to a person of ordinary skill in the art before the effective filing date of the invention to modify the teaching of Atallah to include these features as taught by Sohn because this enables predicting using artificial intelligence in a contactless manner ([0002]).
Claim(s) 3-4 is/are rejected under 35 U.S.C. 103 as being unpatentable over Atallah and Sohn as applied to claim 1 above, and further in view of Halperin (US 20080275349 A1; 11/6/2008).
Regarding claim 3, the combination of Atallah and Sohn does not teach wherein the prediction includes sepsis, meningitis, hypoxemia, radiologically proven pneumonia, or early infantile cerebral palsy. Note that Atallah teaches outputting alert if signs of sepsis occurs ([0064]). However, Halperin teaches in the same field of endeavor (Abstract; Fig. 2; [0011]; [0019]) wherein the prediction includes sepsis ([0495]-[0505]; “sepsis risk score”; [0860] “sepsis score”), meningitis, hypoxemia, radiologically proven pneumonia, or early infantile cerebral palsy. Thus it would have been obvious to a person of ordinary skill in the art before the effective filing date of the invention to modify the teaching of Atallah and Sohn to include this feature as taught by Halperin because this enables contactless monitoring and predicting of abnormal conditions as needed ([0011]; [0798]).
Regarding claim 4, the combination of Atallah and Sohn does not explicitly teach wherein the processor is further configured to:
process the first feature, the second feature, and the third feature using the learning model trained to generate a score indicating a severity of the prediction;
display the score from the learning model on the user interface.
Note that Sohn teaches generating prediction and displaying ([0031]; [0039] “predicting…using a predetermined trained algorithm model”; [0067]-[0068] “output heart rate…stress index”). However, Halperin teaches in the same field of endeavor (Abstract; Fig. 2; [0011]; [0019]) process the first feature, the second feature, and the third feature using the learning model trained to generate a score indicating a severity of the prediction (Fig. 2; [0495]-[0505]; “sepsis risk score”; [0860] “sepsis score”);
display the score from the learning model on the user interface ([0495]-[0505]; “sepsis risk score”; [0860] “sepsis score”). Thus it would have been obvious to a person of ordinary skill in the art before the effective filing date of the invention to modify the teaching of Atallah and Sohn to include this feature as taught by Halperin because this enables contactless monitoring and predicting of abnormal conditions as needed ([0011]; [0798]).
Claim(s) 6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Atallah and Sohn as applied to claim 5 above, and further in view of Verkruijsse (US 20170014087 A1; 1/19/2017; cited in IDS).
Regarding claim 6, in the combination of Atallah and Sohn, Sohn teaches wherein the extracting the third feature comprises:
creating a first red plethysmograph waveform from a red image ([0047]);
creating a second infrared (IR) plethysmograph waveform from an infrared (IR) image ([0056]).
The combination of Atallah and Sohn does not teach calculating the third feature using the first red plethysmograph waveform and the second IR plethysmograph waveform. However, Verkruijsse teaches in the same field of endeavor (Abstract; Fig. 1) teach calculating the third feature using the first red plethysmograph waveform and the second IR plethysmograph waveform (Fig. 3A-3C; [0042]; [0045]-[0047]; [0049]). Thus it would have been obvious to a person of ordinary skill in the art before the effective filing date of the invention to modify the teaching of Atallah and Sohn to include these features as taught by Verkruijsse because this enables obtaining the needed contrast for remote PPG measurement ([0046]-[0047]).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Halperin (US 20080275349 A1; 11/6/2008) cited above also teaches claim 9’s wherein the learning model is a machine learning model trained on historical and patient data ([0608] “for specific patient or based on population averages”).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Jonathan T Kuo whose telephone number is (408)918-7534. The examiner can normally be reached M-F 10 a.m. - 6 p.m. PT.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Niketa Patel can be reached at 571-272-4156. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/JONATHAN T KUO/Primary Examiner, Art Unit 3792
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