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 .
Claim Status: Claims 1-20 are pending.
Claim Rejections - 35 USC § 102
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 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.
Claims 1, 7-15, and 17-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Bhushan (US 2017/0347894).
Re Claim 1, Bhushan discloses a system comprising:
a body-worn patch to be worn by a patient (fig. 5, Biostrip device), wherein the body-worn patch comprises a plurality of sensors (fig. 5),
wherein the plurality of sensors comprises: a biopotential sensor capable of measuring an electrocardiogram (ECG) signal (para. [0051], fig. 5, ECG from 1st Biostrip device on sternum), an inertial measurement unit capable of measuring a seismocardiogram (SCG) signal (para. [0051], fig. 5, SCG from 1st Biostrip device on sternum), an optical sensor capable of measuring a photoplethysmography (PPG) signal (para. [0051], fig. 5, PPG from 1st Biostrip device on sternum); and
a controller (para. [0038], fig. 1, a processor or microcontroller, “MCU”) in signal communication with the plurality of sensors and the controller is capable of receiving the ECG signal, the SCG signal, and the PPG signal (fig. 1, para. [0039], EXG 101, PPG 103),
wherein the controller is capable of determining a physiological property of the patient based on the ECG signal, the SCG signal, and the PPG signal (para. [0047], blood pressure derived from ECG, SCG, and PPG signals).
Re Claim 7, Bhushan discloses that the controller is capable of determining the physiological property of the patient using a machine-learning model (para. [0051]-[0053], a Linear Regression Machine Learning algorithm is used with a training set containing data for over 100 patients with data recorded for ECG, PPG, SCG and SBP and DBP, over a 1-4 hour interval to derive systolic and diastolic central BP).
Re Claim 8, Bhushan discloses that the machine-learning model comprises at least one model selected from the group consisting of linear regression, decision tree, gradient boosted machine, ensemble method, and a deep learning based neural network (para. [0051]-[0053], a Linear Regression Machine Learning algorithm is used with a training set containing data for over 100 patients with data recorded for ECG, PPG, SCG and SBP and DBP, over a 1-4 hour interval to derive systolic and diastolic central BP).
Re Claim 9, Bhushan discloses that the biopotential sensor comprises at least two electrodes removably connected to the body-worn patch (para. [0025], [0037], Biostrip device includes an electronic module or a component that is reusable and rechargeable (via micro-USB or wirelessly or both) and is stuck on one side with a two-sided adhesive tape, which is meant for a single use only), wherein the electrodes contact a skin of the patient to make an electrical connection between the patient and the body-worn patch (para. [0025], [0039], two or more electrodes which measure an electrical signal of the Electro Cardio Gram (ECG) when stuck on the chest).
Re Claim 10, Bhushan discloses that the plurality of sensors further comprises a temperature sensor (para. [0010], [0026], [0101], fig. 1, skin temperature 104).
Re Claim 11, Bhushan discloses that at least one of the optical sensor and the temperature sensor contacts a skin of the patient (para. [0010], [0026], [0101], fig. 1, skin temperature 104; para. [0040], The Biostrip device includes a reflective Photoplethysmograph (“PPG”) module attached to the underside of the device, and in direct visual contact with the skin on the chest/wrist/forehead or other location where the device adheres).
Re Claim 12, Bhushan discloses that the body-worn patch further comprises a wireless communication circuit capable of wirelessly transmitting the ECG signal, the SCG signal, and the PPG signal to the controller, a secondary controller, or a combination thereof (para. [0044], The Biostrip also contains an integrated circuit for wireless data communication that enables it to connect and communicate, and send to and receive data from, a smartphone/smartwatch or another gateway device such as a wifi router; para. [0101]).
Re Claim 13, Bhushan discloses that the wireless communication circuit transmits the ECG signal, the SCG signal, and the PPG signal using Bluetooth (para. [0101], A plurality of sensors 101,102,103,104 record data, and transmit the data to a microcontroller 105. The data is processed by the microprocessor 105 and then sent for transmission to the Bluetooth low energy (“BLE”)/Wireless transmission module 106. Module 106 communicates the data to a smartphone or another gateway device).
Re Claim 14, Bhushan discloses that the controller is further capable of receiving characteristics of the patient, wherein the controller determines the physiological property based on the ECG signal, the SCG signal, the PPG signal, and the characteristics of the patient (para. [0047], blood pressure is calculated from disclosed physiological metrics from ECG, SCG, and PPG signals combined with individual factors such as age, sex, height, weight and medical conditions of the user).
Re Claim 15, Bhushan discloses that the characteristics of the patient comprise at least one of an age of the patient, a gender of the patient, a height of the patient, and a weight of the patient (para. [0047], blood pressure is calculated from disclosed physiological metrics from ECG, SCG, and PPG signals combined with individual factors such as age, sex, height, weight and medical conditions of the user).
Re Claim 17, Bhushan discloses that the controller selects a machine-learning model from a data store based on the characteristics of the patient and the controller determine the physiological property of the patient based on the machine-learning model (para. [0050]-[0068] shows examples of a machine learning model with a training set with individual factors such as age, sex, height, weight).
Re Claim 18, Bhushan discloses a method for determining a physiological property of a patient with a body-worn patch (fig. 5, Biostrip device), the method comprising:
measuring, by a biopotential sensor of a body-worn patch device, an ECG signal of the patient (para. [0051], fig. 5, ECG from 1st Biostrip device on sternum);
measuring, by an inertial measurement unit of the body-worn patch device, an SCG signal of the patient (para. [0051], fig. 5, SCG from 1st Biostrip device on sternum);
measuring, by an optical sensor of the body-worn patch device, a PPG signal of the patient (para. [0051], fig. 5, PPG from 1st Biostrip device on sternum);
receiving, by a controller (para. [0038], fig. 1, a processor or microcontroller, “MCU”), the ECG signal, the SCG signal, and the PPG signal (fig. 1, para. [0039], EXG 101, PPG 103); and
determining, by the controller, a physiological property of the patient based on the ECG signal, the SCG signal, and the PPG signal (para. [0047], blood pressure derived from ECG, SCG, and PPG signals).
Re Claim 19, Bhushan discloses that the method further comprises:
measuring, by a temperature sensor of the body-worn patch device, a temperature of the patient (para. [0010], [0026], [0101], fig. 1, skin temperature 104);
receiving, by the controller, the temperature of the temperature of the patient (para. [0026], [0046], system records skin temperature); and
determining, by the controller, the physiological property of the patient further based on the temperature of the patient (para. [0018], [0026], [0046], the system records skin temperature, blood oxygenation, CO2 levels in the blood, haemoglobin levels in the blood, blood glucose, in order to provide the user with more detailed information on the blood pressure levels are varying with detailed inputs on how the BP levels are varying with respect to the other physiological parameters mentioned above).
Re Claim 20, Bhushan discloses that the method further comprises:
receiving, by the controller, characteristics of the patient, wherein the characteristics of the patient comprise at least one of an age of the patient, a gender of the patient, a height of the patient, and a weight of the patient (para. [0047], blood pressure is calculated from disclosed physiological metrics from ECG, SCG, and PPG signals combined with individual factors such as age, sex, height, weight and medical conditions of the user);
selecting, by the controller, a machine learning model from a data store based on the characteristics of the patient; and determining, by the controller, the physiological property of the patient based further on the machine learning model (para. [0050]-[0068] shows examples of a machine learning model, with a training set with individual factors such as age, sex, height, weight, to obtain a value for systolic and diastolic blood pressure).
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.
Claims 2-6 are rejected under 35 U.S.C. 103 as being unpatentable over Bhushan (US 2017/0347894) in view of Bhushan et al. (US 2017/0347899A1), hereinafter “Sibal”.
Re Claim 2, Bhushan discloses the claimed invention substantially as set forth in claim 1.
Bhushan discloses that the controller is capable of determining the physiological property of the patient based on a plurality of characteristics from the aligned ECG signal, SCG signal, and PPG signal (para. [0047], blood pressure derived from ECG, SCG, and PPG signals, wherein blood pressure reads on physiological property. Para. [0047] discloses a plurality of characteristics of PTT, pulse wave velocity, PEP, the time delay between the R-peak as measured from the ECG, and the peak measured from the IPG, and time delays between the opening and closing of the valves, as measured from the SCG, and time-lag between the valve opening and the R-peak as measured from the ECG, and the peak of the Pulse wave, as measured from the PPG).
Bhushan discloses aligning the ECG signal, the SCG signal, and the PPG signal based on time on a smartphone (claim 19, synchronizing all signals on the smartphone), but is silent regarding the controller being capable of aligning the ECG signal, the SCG signal, and the PPG signal based on time.
However, Sibal discloses method and system for continuous monitoring of cardiovascular health (abstract) and teaches the controller being capable of aligning the ECG signal, the SCG signal, and the PPG signal based on time (para. [0038]-[0042], The Biostrip devices first sync their internal clocks with the real time clock (RTC) of the gateway device—smartphone/smartwatch, other gateway device—so that the internal clocks of the Biostrips are aligned with the clock of the gateway device, as well as with each other).
Therefore, it would have been obvious to one of ordinary skill in the art, at the time of filing, to modify Bhushan, by configuring the controller to be capable of aligning the ECG signal, the SCG signal, and the PPG signal based on time, as taught by Sibal, for the purpose of calculating the plurality of characteristics (para. [0038]-[0042]).
Re Claim 3, Bhushan discloses that the plurality of characteristics comprises a pre-ejection period based on an R-wave of the ECG signal and an AO peak of the SCG signal (para. [0052], PEP refers to the Pre-Ejection Period, or the time interval between the R-peak of the ECG and the AO opening peak of the SCG).
Re Claim 5, Bhushan discloses that the plurality of characteristics comprises a pulse arrival time based on an R-wave of the ECG signal and a PPG onset of the PPG signal (claim 10, combine information from the ECG sensor and the PPG sensor to calculate PATfoot).
Re Claims 4 and 6, Bhushan as modified by Sibal discloses the claimed invention substantially as set forth in claims 1 and 2.
Bhushan discloses the plurality of characteristics comprise: a pre-ejection period based on an R-wave of the ECG signal and an AO peak of the SCG signal (para. [0052], PEP refers to the Pre-Ejection Period, or the time interval between the R-peak of the ECG and the AO opening peak of the SCG); a pulse arrival time based on the R-wave of the ECG signal and the PPG onset of the PPG signal (claim 10, combine information from the ECG sensor and the PPG sensor to calculate PATfoot).
Bhushan discloses the plurality of characteristics comprises a pulse transit time based on the R-peak and Aortic Valve opening measured on the Biostrip, and the foot and peak of the PPG curve (para. [0075]).
Bhushan is silent regarding a pulse transit time based on an AO peak of the SCG signal and a PPG onset of the PPG signal.
However, Sibal discloses method and system for continuous monitoring of cardiovascular health (abstract) and teaches calculating a pulse transit time based on R-peak of the ECG or an AO peak of the SCG signal till a PPG onset of the PPG signal (para. [0037], calculate a value of Pulse Transit Time (PTT) from the R-peak of the ECG or the aortic valve opening (AO) peak of the SCG, till the foot/peak/dichrotic notch of the PPG curve).
Therefore, it would have been obvious to one of ordinary skill in the art, at the time of filing, to modify Bhushan as modified by Sibal, by calculating a pulse transit time based on an AO peak of the SCG signal and a PPG onset of the PPG signal, as taught by Sibal, because such a modification is the result of simple substitution of one known element for another producing a predictable result. More specifically, Bhushan’s method of calculating PTT and Sibal’s method of calculating PTT perform the same general and predictable function, the predictable function being measuring a blood pressure. Since each individual element and its function are shown in the prior art, albeit shown in separate references, the difference between the claimed subject matter and the prior art rests not on any individual element or function but in the very combination itself - that is in the substitution of Bhushan’s method of calculating PTT by replacing it with Sibal’s method of calculating PTT. Thus, the simple substitution of one known element for another producing a predictable result renders the claim obvious.
Claim 16 is rejected under 35 U.S.C. 103 as being unpatentable over Bhushan (US 2017/0347894) in view of Goldberg (US 2005/0071197 A1).
Re Claim 16, Bhushan discloses the claimed invention substantially as set forth in claims 1, 14, and 15.
Bhushan is silent regarding wherein the characteristics of the patient are determined based on a manual input by a user to the controller, a first scan of an identification card of the patient, a second scan of the patient by a camera connected to the controller, an automatic retrieval from a medical database wherein the medical database comprises medical data of the patient, or a combination thereof.
However, Goldberg discloses personal health management device (abstract) and teaches characteristics of the patient are determined based on a manual input by a user to the controller, a first scan of an identification card of the patient, a second scan of the patient by a camera connected to the controller, an automatic retrieval from a medical database wherein the medical database comprises medical data of the patient, or a combination thereof (para. [0024], user manually inputs age, height, and weight).
Therefore, it would have been obvious to one of ordinary skill in the art, at the time of filing, to modify Bhushan, by configuring the characteristics of the patient to be determined based on a manual input by a user to the controller, a first scan of an identification card of the patient, a second scan of the patient by a camera connected to the controller, an automatic retrieval from a medical database wherein the medical database comprises medical data of the patient, or a combination thereof, as taught by Goldberg, for the purpose of obtaining user information (para. [0024]).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to VYNN V HUH whose telephone number is (571)272-4684. The examiner can normally be reached Monday to Friday from 9 am to 5 pm.
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/Benjamin J Klein/Supervisory Patent Examiner, Art Unit 3792
/V.V.H./
Vynn Huh, December 13, 2025Examiner, Art Unit 3792