juDETAILED 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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on January 22, 2026 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement has been considered by the examiner.
Response to Amendment
The amendment filed November 24, 2024 has been entered. Claims 1, 3-9, 11, and 14-24 remain pending in the application, and claims 2, 10, and 12-13 were cancelled. Applicant’s amendments to the claims have overcome each and every 102 rejection previously set forth in the Non-Final Office Action mailed July 23, 2025. Applicant’s amendments to the claims necessitate new grounds of rejection, as described in the Response to Arguments, 101, and 102 Rejections below.
Claim Rejections - 35 USC § 101
Claims 1, 3-9, 11, and 14-24 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Claims 1, 3-6, and 21 are directed to a computer program on a non-transitory computer readable medium for determining a likelihood of a respiratory infection of a user, which is an abstract idea. Claims 7-9, 11, 14-17 are directed to a method for determining a likelihood of a respiratory infection of a user using a computational algorithm, which is an abstract idea. Claims 18-20 and 23-24 are directed to a system for determining a likelihood of a respiratory infection using a computational algorithm, which is an abstract idea. Claims 1, 3-9, 11, and 14-24 do not include additional elements that integrate the exception into a practical application or that are sufficient to amount to significantly more than the judicial exception for the reasons provided below which are in line with the 2014 Interim Guidance on Patent Subject Matter Eligibility (Federal Register, Vol. 79, No. 241, p 74618, December 16, 2014), the July 2015 Update on Subject Matter Eligibility (Federal Register, Vol. 80, No. 146, p. 45429, July 30, 2015), the May 2016 Subject Matter Eligibility Update (Federal Register, Vol. 81, No. 88, p. 27381, May 6, 2016), and the 2019 Revised Patent Subject Matter Eligibility Guidance (Federal Register, Vol. 84, No. 4, page 50, January 7, 2019).
The analysis of claim 1 is as follows:
Step 1: Claim 1 is drawn to a machine.
Step 2A – Prong One: Claim 1 recites an abstract idea. In particular, claim 1 recites the following limitations:
[A1] – “evaluating the one or more features of the current respiratory rate pattern”;
[B1] – “comparing the one or more features of the current respiratory rate pattern to the one or more features of the historical respiratory rate pattern”; and
[C1] – “in response to a predetermined difference between the one or more features of the current respiratory rate pattern based on the heart rate data optically obtained during the predetermined stage of sleep within the current sleep interval and the one or more features of the historical respiratory rate pattern based on the heart rate data optically obtained during the predetermined stage of sleep within the one or more historical sleep intervals, creating an indicator of a likelihood of a respiratory infection of the user.”
These elements [A1]-[C1] of claim 1 are drawn to an abstract idea since they involve a mental process that can be practically performed in the human mind including observation, evaluation, judgment, and opinion and using pen and paper.
Step 2A – Prong Two: Claim 1 recites the following limitations that are beyond the judicial exception:
[A2] – “A computer program product comprising computer executable code embodied in a non-transitory computer readable medium”;
[B2] - “acquiring heart rate data from a user based on optical signals from a
wearable physiological monitor, the heart rate data including data acquired during one or
more historical sleep intervals and a current sleep interval”;
[C2] – “determining a historical respiratory rate pattern for the user at a first number of predetermined daily intervals based on the heart rate data obtained during a predetermined stage of sleep within the one or more historical sleep intervals, the historical respiratory rate pattern characterizing one or more features of a respiratory activity of the user during the first number of predetermined daily intervals”; and
[D2] – “determining a current respiratory rate pattern for the user during a second predetermined daily interval based on the heart rate data obtained during the predetermined stage of sleep within the current sleep interval”;
These elements [A2]-[D2] of claim 1 do not integrate the exception into a practical application of the exception. In particular, the element [A2] is merely an instruction to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.04(d) and MPEP 2106.05(f). Also, the elements [B2-D2] are merely adding insignificant extra-solution activity to the judicial exception, i.e., mere data gathering at a higher level of generality - see MPEP 2106.04(d) and MPEP 2106.05(g).
Step 2B: Claim 1 does not recite additional elements that amount to significantly more than the judicial exception itself. In particular, the recitation “acquiring heart rate data based on optical signals from a user with a wearable physiological monitor” is merely insignificant extrasolution activity to the judicial exception, e.g., mere data gathering in conjunction with the abstract idea that uses conventional, routine, and well known elements or simply displaying the results of the algorithm that uses conventional, routine, and well known elements. In particular, the physiological monitor is nothing more than a wearable optical sensor detecting heart rate. Such sensors are conventional as evidenced by:
U.S. Patent Application Publication No. 20180125418 A1 (Haakma et al.) ([0034] “a wearable device that can be worn during sleep”; [0078] “The device or apparatus of the present invention may be incorporated in the form of a device being included in a smartphone or a body-worn device such as a smart watch, a wristband or a heart rate belt etc.”; [0085] “wearable heart-rate variability based unobtrusive sleep staging system including a PPG sensor” (A PPG sensor is an optical sensor); [0090]).
Further, the element [A2] does not qualify as significantly more because this limitation is simply appending well-understood, routine and conventional activities previously known in the industry, specified at a high level of generality, to the judicial exception, e.g., a claim to an abstract idea requiring no more than a generic computer to perform generic computer functions that are well-understood, routine and conventional activities previously known in the industry (see Electric Power Group, 830 F.3d 1350 (Fed. Cir. 2016); Alice Corp. v. CLS Bank Int’l, 110 USPQ2d 1976 (2014)) and/or a claim to an abstract idea requiring no more than being stored on a computer readable medium which is a well-understood, routine and conventional activity previously known in the industry (see Electric Power Group, 830 F.3d 1350 (Fed. Cir. 2016); Alice Corp. v. CLS Bank Int’l, 110 USPQ2d 1976 (2014); SAP Am. v. InvestPic, 890 F.3d 1016 (Fed. Circ. 2018)).
In view of the above, the additional elements individually do not integrate the exception into a practical application and do not amount to significantly more than the above-judicial exception (the abstract idea). Looking at the limitations as an ordered combination (that is, as a whole) adds nothing that is not already present when looking at the elements taking individually. There is no indication that the combination of elements improves the functioning of a computer, for example, or improves any other technology. There is no indication that the combination of elements permits automation of specific tasks that previously could not be automated. There is no indication that the combination of elements includes a particular solution to a computer-based problem or a particular way to achieve a desired computer-based outcome. Rather, the collective functions of the claimed invention merely provide conventional computer implementation, i.e., the computer is simply a tool to perform the process.
Claims 3-6 and 21 depend from claim 1, and recite the same abstract idea as claim 1. Furthermore, these claims only contain recitations that further limit the abstract idea (that is, the claims only recite limitations that further limit the algorithm), with the following exceptions:
Claim 3: “the one or more features is performed on a remote server”;
Claim 4: “the indicator is transmitted from the remote server to a device associated with the user.; and
Claim 5: “the device is the wearable physiological monitor”;
Claim 6: “the device is at least one of a laptop computer, a tablet, or a cellular phone associated with the user”.
Each of these claim limitations does not integrate the exception into a practical application. In particular, the elements of claims 3-6 are merely adding insignificant extra-solution activity to the judicial exception, i.e., mere data gathering and transmission at a higher level of generality - see MPEP 2106.04(d) and MPEP 2106.05(g).
Also, each of these limitations of claims 3-6 do not recite additional elements that amount to significantly more than the judicial exception itself because they are merely insignificant extrasolution activity to the judicial exception, e.g., mere data gathering in conjunction with the abstract idea that uses conventional, routine, and well known elements or simply displaying the results of the algorithm that uses conventional, routine, and well known elements. Such devices are conventional as evidenced by Haakma (as provided above with respect to the rejection of claim 1).
Also, the limitation from claim 3 is simply appending well-understood, routine and conventional activities previously known in the industry, specified at a high level of generality, to the judicial exception, e.g., a claim to an abstract idea requiring no more than a generic computer to perform generic computer functions (that is, one of display) that are well-understood, routine and conventional activities previously known in the industry (see Electric Power Group, 830 F.3d 1350 (Fed. Cir. 2016); Alice Corp. v. CLS Bank Int'l, 110 USPQ2d 1976 (2014); SAP Am. v. InvestPic, 890 F.3d 1016 (Fed. Circ. 2018)).
In view of the above, the additional elements individually do not integrate the exception into a practical application and do not amount to significantly more than the above-judicial exception (the abstract idea). Looking at the limitations of each claim as an ordered combination in conjunction with the claims from which they depend (that is, as a whole) adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer, for example, or improves any other technology. There is no indication that the combination of elements permits automation of specific tasks that previously could not be automated. There is no indication that the combination of elements includes a particular solution to a computer-based problem or a particular way to achieve a desired computer-based outcome. Rather, the collective functions of the claimed invention merely provide conventional computer implementation, i.e., the computer is simply a tool to perform the process.
The analysis of claim 7 is as follows:
Step 1: Claim 7 is drawn to a process.
Step 2A – Prong One: Claim 7 recites an abstract idea. In particular, claim 7 recites the following limitations:
[A1] – “automatically generating an indicator for likelihood of an infection of the user with a respiratory illness at least once per day based on a comparison of one or more features of the physiological data signal during a particular stage of sleep within the recent sleep interval to the one or more features of the physiological data signal during the particular stage of sleep within the at least one historical sleep interval”
The element A1 of claim 7 is drawn to an abstract idea since they involve a mental process that can be practically performed in the human mind including observation, evaluation, judgment, and opinion and using pen and paper.
Step 2A – Prong Two: Claim 7 recites the following limitations that are beyond the judicial exception:
[A2] – “acquiring a physiological data signal from one or more optical sensors of a wearable device worn by a user, the physiological data signal including data acquired during a recent sleep interval and at least one historical sleep interval preceding the recent sleep interval”;
The element [A2] of claim 7 does not integrate the exception into a practical application of the exception. In particular, the element [A2] is merely adding insignificant extra-solution activity to the judicial exception, i.e., mere data gathering at a higher level of generality - see MPEP 2106.04(d) and MPEP 2106.05(g).
Step 2B: Claim 7 does not recite additional elements that amount to significantly more than the judicial exception itself. In particular, the recitation [A2] is merely insignificant extrasolution activity to the judicial exception, e.g., mere data gathering in conjunction with the abstract idea that uses conventional, routine, and well known elements or simply displaying the results of the algorithm that uses conventional, routine, and well known elements. In particular, the wearable device is nothing more than a wearable optical sensor detecting physiological data. Such devices are conventional as evidenced by Haakma (as provided above with respect to the rejection of claim 1).
In view of the above, the additional elements individually do not integrate the exception into a practical application and do not amount to significantly more than the above-judicial exception (the abstract idea). Looking at the limitations as an ordered combination (that is, as a whole) adds nothing that is not already present when looking at the elements taking individually. There is no indication that the combination of elements improves the functioning of a computer, for example, or improves any other technology. There is no indication that the combination of elements permits automation of specific tasks that previously could not be automated. There is no indication that the combination of elements includes a particular solution to a computer-based problem or a particular way to achieve a desired computer-based outcome. Rather, the collective functions of the claimed invention merely provide conventional computer implementation, i.e., the computer is simply a tool to perform the process.
Claims 8-9, 11, 14-17, and 22 depend from claim 7, and recite the same abstract idea as claim 7. Furthermore, these claims only contain recitations that further limit the abstract idea (that is, the claims only recite limitations that further limit the algorithm), with the following exceptions:
Claim 8: “transmitting the physiological data signal to a server; automatically generating the indicator at the server; and transmitting the indicator to a device associated with the user for display.”;
Claim 9: “automatically generating the indicator on the wearable device and transmitting the indicator to a device associated with the user”
Each of these claim limitations does not integrate the exception into a practical application. In particular, the elements of claims 8-9 are merely adding insignificant extra-solution activity to the judicial exception, i.e., mere data gathering, transmission, and display at a higher level of generality - see MPEP 2106.04(d) and MPEP 2106.05(g). Also, each of these limitations do not recite additional elements that amount to significantly more than the judicial exception itself because they are merely insignificant extrasolution activity to the judicial exception, e.g., mere data gathering in conjunction with the abstract idea that uses conventional, routine, and well known elements or simply displaying the results of the algorithm that uses conventional, routine, and well known elements. Such devices are conventional as evidenced by Haakma (as provided above with respect to the rejection of claim 1).
In view of the above, the additional elements individually do not integrate the exception into a practical application and do not amount to significantly more than the above-judicial exception (the abstract idea). Looking at the limitations of each claim as an ordered combination in conjunction with the claims from which they depend (that is, as a whole) adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer, for example, or improves any other technology. There is no indication that the combination of elements permits automation of specific tasks that previously could not be automated. There is no indication that the combination of elements includes a particular solution to a computer-based problem or a particular way to achieve a desired computer-based outcome. Rather, the collective functions of the claimed invention merely provide conventional computer implementation, i.e., the computer is simply a tool to perform the process.
The analysis of claim 18 is as follows:
Step 1: Claim 18 is drawn to a machine.
Step 2A – Prong One: Claim 18 recites an abstract idea. In particular, claim 18 recites the following limitations:
[A1] – “evaluating the one or more features of the current respiratory rate pattern”;
[B1] – “comparing the one or more features of the current respiratory rate pattern to the one or more features of the historical respiratory rate pattern”; and
[C1] – “in response to a predetermined difference between the one or more features of the current respiratory rate pattern determined for the user at the predetermined sleep stage during the current sleep interval and the one or more features of the historical respiratory rate pattern determined for the user at the predetermined sleep stage during the first number of historical sleep intervals, creating an indicator of a likelihood of a respiratory infection of the user.”
These elements [A1]-[C1] of claim 18 are drawn to an abstract idea since they involve a mental process that can be practically performed in the human mind including observation, evaluation, judgment, and opinion and using pen and paper.
Step 2A – Prong Two: Claim 18 recites the following limitations that are beyond the judicial exception:
[A2] – “a server configured to receive heart rate data and to evaluate a respiratory health of a user based on the heart rate data”;
[B2] – “determining a historical respiratory rate pattern for the user at a predetermined sleep stage during a first number of historical sleep intervals based on the heart rate data, the historical respiratory rate pattern characterizing one or more features of a typical respiratory rate pattern during the predetermined sleep stage”; and
[C2] – “determining a current respiratory rate pattern for the user at the predetermined sleep stage during a current sleep interval based on the heart rate data”;
These elements [A2]-[C2] of claim 18 do not integrate the exception into a practical application of the exception. In particular, the element [A2] is merely an instruction to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.04(d) and MPEP 2106.05(f). Also, the elements [B2-C2] are merely adding insignificant extra-solution activity to the judicial exception, i.e., mere data gathering at a higher level of generality - see MPEP 2106.04(d) and MPEP 2106.05(g).
Step 2B: Claim 18 does not recite additional elements that amount to significantly more than the judicial exception itself. In particular, the recitation “receive heart rate data” is merely insignificant extrasolution activity to the judicial exception, e.g., mere data gathering in conjunction with the abstract idea that uses conventional, routine, and well known elements or simply displaying the results of the algorithm that uses conventional, routine, and well known elements. In particular, the data acquirer is nothing more than a wearable sensor detecting heart rate. Such devices are conventional as evidenced by Haakma (as provided above with respect to the rejection of claim 1).
Further, the element [A2] does not qualify as significantly more because this limitation is simply appending well-understood, routine and conventional activities previously known in the industry, specified at a high level of generality, to the judicial exception, e.g., a claim to an abstract idea requiring no more than a generic computer to perform generic computer functions that are well-understood, routine and conventional activities previously known in the industry (see Electric Power Group, 830 F.3d 1350 (Fed. Cir. 2016); Alice Corp. v. CLS Bank Int’l, 110 USPQ2d 1976 (2014)) and/or a claim to an abstract idea requiring no more than being stored on a computer readable medium which is a well-understood, routine and conventional activity previously known in the industry (see Electric Power Group, 830 F.3d 1350 (Fed. Cir. 2016); Alice Corp. v. CLS Bank Int’l, 110 USPQ2d 1976 (2014); SAP Am. v. InvestPic, 890 F.3d 1016 (Fed. Circ. 2018)).
In view of the above, the additional elements individually do not integrate the exception into a practical application and do not amount to significantly more than the above-judicial exception (the abstract idea). Looking at the limitations as an ordered combination (that is, as a whole) adds nothing that is not already present when looking at the elements taking individually. There is no indication that the combination of elements improves the functioning of a computer, for example, or improves any other technology. There is no indication that the combination of elements permits automation of specific tasks that previously could not be automated. There is no indication that the combination of elements includes a particular solution to a computer-based problem or a particular way to achieve a desired computer-based outcome. Rather, the collective functions of the claimed invention merely provide conventional computer implementation, i.e., the computer is simply a tool to perform the process.
Claims 19-20 and 23-24 depend from claim 18, and recite the same abstract idea as claim 18. Furthermore, these claims only contain recitations that further limit the abstract idea (that is, the claims only recite limitations that further limit the algorithm), with the following exceptions:
Claim 19: “wearable physiological monitor configured to continuously acquire heart rate data from the user and transmit the heart rate data to the server.”;
Claim 20: “a user device configured to receive an alert from the server and display the alert to the user when the likelihood of the respiratory infection is above a predetermined threshold”.
Each of these claim limitations does not integrate the exception into a practical application. In particular, the elements of claims 19-20 are merely adding insignificant extra-solution activity to the judicial exception, i.e., mere data gathering, transmission, and display at a higher level of generality - see MPEP 2106.04(d) and MPEP 2106.05(g).
Also, each of these limitations of claims 19-20 do not recite additional elements that amount to significantly more than the judicial exception itself because they are merely insignificant extrasolution activity to the judicial exception, e.g., mere data gathering in conjunction with the abstract idea that uses conventional, routine, and well known elements or simply displaying the results of the algorithm that uses conventional, routine, and well known elements. Such devices are conventional as evidenced by Haakma (as provided above with respect to the rejection of claim 1).
Also, the limitation from claim 20 is simply appending well-understood, routine and conventional activities previously known in the industry, specified at a high level of generality, to the judicial exception, e.g., a claim to an abstract idea requiring no more than a generic computer to perform generic computer functions (that is, one of display) that are well-understood, routine and conventional activities previously known in the industry (see Electric Power Group, 830 F.3d 1350 (Fed. Cir. 2016); Alice Corp. v. CLS Bank Int'l, 110 USPQ2d 1976 (2014); SAP Am. v. InvestPic, 890 F.3d 1016 (Fed. Circ. 2018)).
In view of the above, the additional elements individually do not integrate the exception into a practical application and do not amount to significantly more than the above-judicial exception (the abstract idea). Looking at the limitations of each claim as an ordered combination in conjunction with the claims from which they depend (that is, as a whole) adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer, for example, or improves any other technology. There is no indication that the combination of elements permits automation of specific tasks that previously could not be automated. There is no indication that the combination of elements includes a particular solution to a computer-based problem or a particular way to achieve a desired computer-based outcome. Rather, the collective functions of the claimed invention merely provide conventional computer implementation, i.e., the computer is simply a tool to perform the process.
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)(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 1, 3-9, 11, and 14-24 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by US 20230190140 A1 (Tiron et al.).
Regarding claim 1, Tiron teaches a computer program product comprising computer executable code embodied in a non-transitory computer readable medium that, when executing on one or more computing devices ([0251]), performs the steps of:
acquiring heart rate data from a user based on optical signals from a wearable physiological monitor, the heart rate data including data acquired during one or more historical sleep intervals and a current sleep interval ([0040] “a heart rate sensor” … “The one or more sensors may be or include, for example, a wearable sensor device.”; [0054] “The PPG sensor outputs physiological data associated with the user that can be used to determine one or more cough events, one or more physiological parameters and/or one or more sleep-related parameters, such as, for example, a heart rate, a heart rate pattern, and a heart rate variability, thus acting as a heart rate sensor”; [0496] “In some instances, the tracking of the signal may be conducted during a detected sleep stage including any one of light sleep, deep sleep and REM sleep.”; [0499] “the heart rate features including one or more of heart rate variability and comparison to personalised baseline measures related to heart rate”; [0501] “Some or all of the extracted respiration, heart rate, movement, and coughing and snoring parameters may be utilized to estimate the number of apneas and hypopneas occurring during a sleeping period.”; [0504] “If a cough occurs at night while the subject is trying to sleep, the cough may be detected by any one or combination of a disturbance in the breathing signal, a change in heart rate from a cardiac signal (typically detected by the system as an increase sustained for a period after the cough, primarily during exhalation)”; [0526] “a change in heart rate (typically detected by the system as an increase from baseline heart rate in, for example, the preceding 10 mins, which is sustained for a period of several minutes after the cough, primarily during exhalation)”);
determining a historical respiratory rate pattern for the user at a first number of predetermined daily intervals based on the heart rate data obtained during a predetermined stage of sleep within the one or more historical sleep intervals, the historical respiratory rate pattern characterizing one or more features of a respiratory activity of the user during the first number of predetermined daily intervals ([0030] “The accessed data may be current and/or historical physiological data, thus corresponding to the person's current and/or a previous physiological condition”; [0499] “The method and system may include tracking a breathing pattern of the user based on combining data associated with a determined cough signature and at least one of a breathing signal, heart rate data”; [0504]; [0515] “predetermined time periods, e.g. every second over a monitoring period (e.g. a sleep session)”; [0526]);
determining a current respiratory rate pattern for the user during a second predetermined daily interval based on the heart rate data obtained during the predetermined stage of sleep within the current sleep interval ([0030] “The accessed data may be current and/or historical physiological data, thus corresponding to the person's current and/or a previous physiological condition.”; [0499] “The method and system may include tracking a breathing pattern of the user based on combining data associated with a determined cough signature and at least one of a breathing signal, heart rate data”);
evaluating the one or more features of the current respiratory rate pattern ([0504] “in addition to estimating breathing rate, the waveform in the breathing signal may be analysed by processing local changes in breathing amplitude changes via estimation of the envelope of the breathing signal, and tracking individual parts of the inspiration/expiration waveform morphology”);
comparing the one or more features of the current respiratory rate pattern to the one or more features of the historical respiratory rate pattern ([0138] “The device or system may then apply the monitoring/classification methodology described herein, which may include comparing cough sound(s) or feature(s) from such sounds to a personal cough signature, such as if existing cough data has previously been stored. Such comparisons may be applied to detect, one or more changes in tonal quality, duration, and/or frequency of the newer cough relative to the cough signature. Optionally, such detections may be applied over time such as to analyse trends of cough changes over time.”; [0504] “the cough may be detected by any one or combination of a disturbance in the breathing signal, a change in heart rate from a cardiac signal (typically detected by the system as an increase sustained for a period after the cough, primarily during exhalation)”; “in addition to estimating breathing rate, the waveform in the breathing signal may be analysed by processing local changes in breathing amplitude changes via estimation of the envelope of the breathing signal, and tracking individual parts of the inspiration/expiration waveform morphology”; [0526]); and
in response to a predetermined difference between the one or more features of the current respiratory rate pattern based on the heart rate data optically obtained during the predetermined stage of sleep within the current sleep interval and the one or more features of the historical respiratory rate pattern based on the heart rate data optically obtained during the predetermined stage of sleep within the one or more historical sleep intervals, creating an indicator of a likelihood of a respiratory infection of the user ([0038] “heart rate”; [0039] “Use of cough indication data as well as physiological data associated with one or more physiological parameters of the person provides a more insightful monitoring of the health of the person, and in particular, the health of a person suffering, or recovering from, a respiratory condition associated with an infectious disease(s) such as COVID-19”; [0054] “The PPG sensor outputs physiological data associated with the user that can be used to determine one or more cough events, one or more physiological parameters and/or one or more sleep-related parameters, such as, for example, a heart rate, a heart rate pattern, and a heart rate variability, thus acting as a heart rate sensor, as well as a cardiac cycle, respiration rate, an inspiration amplitude, an expiration amplitude, an inspiration-expiration ratio, estimated blood pressure parameter(s), or any combination thereof.”; [0087] “present technology can rely on different physiological characteristics to identify possible symptoms or characteristics of respiratory conditions associated with an infectious disease(s) such as COVID-19”; [0137]; [0499] “any one or combination of breathing features and heart rate features; the breathing features including one or more of breathing rate, inspiration to expiration time, breathing amplitude as assessed by local amplitude detection, and comparison to personalised baseline measures related to breathing rate; and the heart rate features including one or more of heart rate variability and comparison to personalised baseline measures related to heart rate.”).
Regarding claim 3, Tiron teaches the computer program product of claim 1, wherein comparing the one or more features is performed on a remote server ([0598] “The fact that the data does not have to be processed in real or near real time permits a transmission of data to a remote server”; [0067]).
Regarding claim 4, Tiron teaches the computer program product of claim 3, wherein the indicator is transmitted from the remote server to a device associated with the user ([0075] “where at least some of the processing is performed on one or more remote device(s), the method may further include, in the one or more processors, receiving back from the remote device(s) the generated one or more measures of sleep disordered breathing. The method may further include (a) displaying the received one or more measures of sleep disordered breathing on a display, or (b) transmitting, via data communications transmission, the received one or more measures of sleep disordered breathing to a local processing/displaying device.”).
Regarding claim 5, Tiron teaches the computer program product of claim 4, wherein the device is the wearable physiological monitor ([0064] “smart watch”).
Regarding claim 6, Tiron teaches the computer program product of claim 4, wherein the device is at least one of a laptop computer, a tablet, or a cellular phone associated with the user ([0064] “a smart phone, a tablet computer, a general computing device”).
Regarding claim 7, Tiron teaches a method, comprising:
acquiring a physiological data signal from one or more optical sensors of a wearable device worn by a user, the physiological data signal including data acquired during a recent sleep interval and at least one historical sleep interval preceding the recent sleep interval ([0040] “a heart rate sensor” … “The one or more sensors may be or include, for example, a wearable sensor device.”; [0054] “The PPG sensor outputs physiological data associated with the user that can be used to determine one or more cough events, one or more physiological parameters and/or one or more sleep-related parameters, such as, for example, a heart rate, a heart rate pattern, and a heart rate variability, thus acting as a heart rate sensor”; [0496] “In some instances, the tracking of the signal may be conducted during a detected sleep stage including any one of light sleep, deep sleep and REM sleep.”; [0499] “the heart rate features including one or more of heart rate variability and comparison to personalised baseline measures related to heart rate”; [0501] “Some or all of the extracted respiration, heart rate, movement, and coughing and snoring parameters may be utilized to estimate the number of apneas and hypopneas occurring during a sleeping period.”; [0504] “If a cough occurs at night while the subject is trying to sleep, the cough may be detected by any one or combination of a disturbance in the breathing signal, a change in heart rate from a cardiac signal (typically detected by the system as an increase sustained for a period after the cough, primarily during exhalation)”; [0526] “a change in heart rate (typically detected by the system as an increase from baseline heart rate in, for example, the preceding 10 mins, which is sustained for a period of several minutes after the cough, primarily during exhalation)”); and
automatically generating an indicator for likelihood of an infection of the user with a respiratory illness at least once per day based on a comparison of one or more features of the physiological data signal during a particular stage of sleep within the recent sleep interval to the one or more features of the physiological data signal during the particular stage of sleep within at least one historical sleep interval (Abstract – “The processor may evaluate sensing signal(s) to generate indication(s) of cough event(s) and/or cough type which may include generating an indication of a coronavirus disease or a coronavirus disease cough type.”; [0028] “The physiological data may be used in the classifying, or transmitting for classification, with the one or more cough related features to generate the indication of one or more events of coughing or coughing type”; [0138] “The device or system may then apply the monitoring/classification methodology described herein, which may include comparing cough sound(s) or feature(s) from such sounds to a personal cough signature, such as if existing cough data has previously been stored. Such comparisons may be applied to detect, one or more changes in tonal quality, duration, and/or frequency of the newer cough relative to the cough signature. Optionally, such detections may be applied over time such as to analyse trends of cough changes over time.”; [0495] “the system may determine a probability of the cough(s) being related to any one or more of any particular disease(s) such as COPD, asthma, gastroesophageal reflux disease (GERD), and upper airway cough syndrome, COVID-19 etc.”; [0515] “The real-time block 9010 may be executed at predetermined time periods, e.g. every second over a monitoring period (e.g. a sleep session), and returns a probability of cough for a portion (e.g. half) of each of the predetermined time periods, e.g. each half of each given second.”).
Regarding claim 8, Tiron teaches the method of claim 7, further comprising:
transmitting the physiological data signal to a server ([0198] “transmit data (e.g., sensing signals) to remote processing device(s) (e.g., one or more servers) so that the processing and detections may be performed remotely”);
automatically generating the indicator at the server (Abstract – “The processor may evaluate sensing signal(s) to generate indication(s) of cough event(s) and/or cough type which may include generating an indication of a coronavirus disease or a coronavirus disease cough type.”; [0028] “The physiological data may be used in the classifying, or transmitting for classification, with the one or more cough related features to generate the indication of one or more events of coughing or coughing type”; [0067] “Any one of the classification of features and the generation of measures of sleep disorder breathing, can be generated or processed remotely—by one or more remote processing device(s) or server(s). Thus, in some embodiments, the method may include transmitting to remote device/s or server/s either data for classification or classified features for generation of measure/s of sleep disorder breathing”); and
transmitting the indicator to a device associated with the user for display ([0066] “The processors may be further arranged to display the generated event indicator(s) on a display of the device, or to forward the generated event indicator(s) to an external processing/displaying device.”; [0198] “a processing device (e.g., a smart phone), may be configured to transmit data (e.g., sensing signals) to remote processing device(s) (e.g., one or more servers) so that the processing and detections may be performed remotely. In such a case, the remote processing device(s) may transmit the results back to the local processing device for display on the local processing device or on another device associated with it.”).
Regarding claim 9, Tiron teaches the method of claim 7, further comprising automatically generating the indicator on the wearable device and transmitting the indicator to a device associated with the user ([0064] “smart watch”; [0066] “The processors may be further arranged to display the generated event indicator(s) on a display of the device, or to forward the generated event indicator(s) to an external processing/displaying device.”).
Regarding claim 11, Tiron teaches the method of claim 7, wherein the infection is a Covid-19 infection ([0087] “present technology can rely on different physiological characteristics to identify possible symptoms or characteristics of respiratory conditions associated with an infectious disease(s) such as COVID-19”; [0137]).
Regarding claim 14, Tiron teaches the method of claim 7, wherein the at least one historical sleep interval includes a number of intervals sufficient to establish a pre-infection baseline for a health respiratory pattern ([0033] “The present technology may be used in pre-screening of individuals, such as suspected or presumed COVID-19 patients. The disclosed methods and systems can process subtle changes in respiratory inspiration/expiration ratio and/or rate such as changes from personal baseline or pre-determined baseline”; [0281] “it is possible to classify the event type by assessing whether an it has an associated increase or decrease in effort, (also shape of modulation and amplitude change) versus recent history baseline.”; [0499] “the heart rate features including one or more of heart rate variability and comparison to personalised baseline measures related to heart rate.”).
Regarding claim 15, Tiron the method of claim 7, wherein the physiological data signal includes heart rate data for the user ([0526] “heart rate”).
Regarding claim 16, Tiron teaches the method of claim 7, wherein the physiological data signal provides a proxy for a respiratory pattern of the user ([0499] “The method and system may include tracking a breathing pattern of the user based on combining data associated with a determined cough signature and at least one of a breathing signal, heart rate data, blood pressure data, and motion sensing data”).
Regarding claim 17, Tiron teaches the method of claim 7, further comprising training a machine classifier to return a probability that a set of values for the one or more features is indicative of the infection, and applying the machine classifier to the one or more features of the physiological data signal during the recent sleep interval ([0596] “Machine learned features may also be extracted for such classifications in the module 8916. Thus, with such features a snore classification process/module 8920 and a cough related fingerprinting process/module 8918 may classify the passive stream respectively to produce outputs 8928 such as cough events, snore, wheeze, gasp etc”).
Regarding claim 18, Tiron teaches a system, comprising:
a server configured to receive heart rate data ([0040] “a heart rate sensor”; [0198] “transmit data (e.g., sensing signals) to remote processing device(s) (e.g., one or more servers)”) and to evaluate a respiratory health of a user based on the heart rate data ([0499] “tracking a breathing pattern of the user based on combining data associated with a determined cough signature and at least one of a breathing signal, heart rate data”) by performing the steps of:
determining a historical respiratory rate pattern for the user at a predetermined sleep stage during a first number of historical sleep intervals based on the heart rate data, the historical respiratory rate pattern characterizing one or more features of a typical respiratory rate pattern during the predetermined sleep stage ([0030] “The accessed data may be current and/or historical physiological data, thus corresponding to the person's current and/or a previous physiological condition”; [0499] “The method and system may include tracking a breathing pattern of the user based on combining data associated with a determined cough signature and at least one of a breathing signal, heart rate data”);
determining a current respiratory rate pattern for the user at the predetermined sleep stage during a current sleep interval based on the heart rate data ([0030] “The accessed data may be current and/or historical physiological data, thus corresponding to the person's current and/or a previous physiological condition.”; [0499] “The method and system may include tracking a breathing pattern of the user based on combining data associated with a determined cough signature and at least one of a breathing signal, heart rate data”; [0515] “predetermined time periods, e.g. every second over a monitoring period (e.g. a sleep session)”);
evaluating the one or more features of the current respiratory rate pattern ([0504] “in addition to estimating breathing rate, the waveform in the breathing signal may be analysed by processing local changes in breathing amplitude changes via estimation of the envelope of the breathing signal, and tracking individual parts of the inspiration/expiration waveform morphology”);
comparing the one or more features of the current respiratory rate pattern to the one or more features of the historical respiratory rate pattern ([0138] “The device or system may then apply the monitoring/classification methodology described herein, which may include comparing cough sound(s) or feature(s) from such sounds to a personal cough signature, such as if existing cough data has previously been stored. Such comparisons may be applied to detect, one or more changes in tonal quality, duration, and/or frequency of the newer cough relative to the cough signature. Optionally, such detections may be applied over time such as to analyse trends of cough changes over time.”; [0504] “the cough may be detected by any one or combination of a disturbance in the breathing signal, a change in heart rate from a cardiac signal (typically detected by the system as an increase sustained for a period after the cough, primarily during exhalation)”; “in addition to estimating breathing rate, the waveform in the breathing signal may be analysed by processing local changes in breathing amplitude changes via estimation of the envelope of the breathing signal, and tracking individual parts of the inspiration/expiration waveform morphology”; [0526]); and
in response to a predetermined difference between the one or more features of the current respiratory rate pattern determined for the user at the predetermined sleep stage during the current sleep interval and the one or more features of the historical respiratory rate pattern determined for the user at the predetermined sleep stage during the first number of historical sleep intervals, creating an indicator of a likelihood of a respiratory infection of the user ([0038] “heart rate”; [0039] “Use of cough indication data as well as physiological data associated with one or more physiological parameters of the person provides a more insightful monitoring of the health of the person, and in particular, the health of a person suffering, or recovering from, a respiratory condition associated with an infectious disease(s) such as COVID-19”; [0054] “The PPG sensor outputs physiological data associated with the user that can be used to determine one or more cough events, one or more physiological parameters and/or one or more sleep-related parameters, such as, for example, a heart rate, a heart rate pattern, and a heart rate variability, thus acting as a heart rate sensor, as well as a cardiac cycle, respiration rate, an inspiration amplitude, an expiration amplitude, an inspiration-expiration ratio, estimated blood pressure parameter(s), or any combination thereof.”; [0087] “present technology can rely on different physiological characteristics to identify possible symptoms or characteristics of respiratory conditions associated with an infectious disease(s) such as COVID-19”; [0137]; [0499] “any one or combination of breathing features and heart rate features; the breathing features including one or more of breathing rate, inspiration to expiration time, breathing amplitude as assessed by local amplitude detection, and comparison to personalised baseline measures related to breathing rate; and the heart rate features including one or more of heart rate variability and comparison to personalised baseline measures related to heart rate.”).
Regarding claim 19, Tiron teaches the system of claim 18, further comprising a wearable physiological monitor configured to continuously acquire the heart rate data from the user and transmit the heart rate data to the server ([0040] “heart rate sensor”; “The one or more sensors may be or include, for example, a wearable sensor device.”).
Regarding claim 20, Tiron teaches the system of claim 18, further comprising a user device configured to receive an alert from the server and display the alert to the user when the likelihood of the respiratory infection is above a predetermined threshold ([0012]; [0048]; [0232]; [0324] “The process(es) may be configured to generate an SDB risk indication such as to provide any one or more of: [0325] (1) a binary classification flag (true or false) for exceedance of a clinical threshold of SDB events (e.g., AHI greater than a threshold such as 15).”; [0462] “The factor, such as in the presence of SDB probability risk, can then serve to penalize a reported sleep score”; [0470]; [0506]; [0568] “Analysis of a reduction in sleep score due to cough (with wakefulness) or snoring, along with a rise in resting breathing rate and/or change in inspiration/expiration ratio can be indicative of a worsening respiratory infection, and in turn an increased risk of the subject's condition worsening”; [0674] “a user interface display is shown in FIG. 35 in association with snore information data and a sleep score of a sleep session.”; [0730-0731] “the classifying comprises identifying one of an affirmation and a negation of a presence of a number of sleep disordered breathing events exceeding a threshold for a sleep session, and wherein the one or more measures of sleep disordered breathing comprises a binary flag representing a result of the identifying”; [0744]; [0915]).
Regarding claim 21, Tiron teaches the computer program product of claim 1, wherein the predetermined stage of sleep of at least one of the one or more historical sleep intervals and the current sleep interval is selected based on a consistency of the heart rate data ([0042] “a heart rate variation”; [0054]; [0087]; [0111-0128]; [0496] “The system, such as with an application running on a processing device (e.g., a smartphone), may access different sensors in order to estimate physiological signals relating to respiratory conditions both during sleep stages and during wake. In some instances, the tracking of the signal may be conducted during a detected sleep stage including any one of light sleep, deep sleep and REM sleep. Thus, the sleep stage may be assessed in determining information about a cough (e.g., cough type and/or cause).”; [0498] “the physiological parameter may comprise heart rate, and, the trend monitoring of heart rate variability (HRV) may be applied.”; [0499]).
Regarding claim 22, Tiron teaches the method of claim 7, wherein the particular stage of sleep of the at least one historical sleep interval and the recent sleep interval is selected based on a consistency of the physiological data signal ([0087]; [0111-0128]; [0496] “The system, such as with an application running on a processing device (e.g., a smartphone), may access different sensors in order to estimate physiological signals relating to respiratory conditions both during sleep stages and during wake. In some instances, the tracking of the signal may be conducted during a detected sleep stage including any one of light sleep, deep sleep and REM sleep. Thus, the sleep stage may be assessed in determining information about a cough (e.g., cough type and/or cause).”; [0498] “the physiological parameter may comprise heart rate, and, the trend monitoring of heart rate variability (HRV) may be applied.”).
Regarding claim 23, Tiron teaches the system of claim 18, wherein the predetermined sleep stage of at least one of the historical sleep intervals and the current sleep interval is selected based on a consistency of the heart rate data ([0042] “a heart rate variation”; [0054]; [0087]; [0111-0128]; [0496] “The system, such as with an application running on a processing device (e.g., a smartphone), may access different sensors in order to estimate physiological signals relating to respiratory conditions both during sleep stages and during wake. In some instances, the tracking of the signal may be conducted during a detected sleep stage including any one of light sleep, deep sleep and REM sleep. Thus, the sleep stage may be assessed in determining information about a cough (e.g., cough type and/or cause).”; [0498] “the physiological parameter may comprise heart rate, and, the trend monitoring of heart rate variability (HRV) may be applied.”; [0499]).
Regarding claim 24, Tiron teaches the system of claim 18, wherein the predetermined sleep stage of at least one of the historical sleep intervals and the current sleep interval includes a period of deep sleep most immediately preceding an end of a nightly sleep event ([0441] “The hypnogram as determined by the sleep staging process identifies different stages of sleep (e.g., deep, light, REM) or wake over the course of the recording session. The sleep-wake correction mask is a time series of indicators for the recording session that represents either sleep or wake in a particular time sub-interval of the time series. Thus, the sleep indicator of the mask summarizes any of deep, light or REM, etc. as a sleep interval”).
Response to Arguments
Applicant's arguments filed November 24, 2025 have been fully considered but they are not persuasive. With respect to the 101 Rejections in the Non-Final Office Action (See Pages 8-9 of Applicant’s Response “Claim Rejections – 35 U.S.C. § 101”), Applicant argues that the amended limitations integrate the inventive concept into practical application. With respect to the 102 Rejections in the Non-Final Office Action (See Pages 9-10 of Applicant’s Response “Claim Rejections – 35 U.S.C. § 102”), Applicant argues that Tiron does not teach “in response to a predetermined-difference between the one or more features of the current respiratory rate pattern based on the heart rate data optically obtained during the predetermined state of sleep within the current sleep interval and the one or more features of the historical respiratory rate pattern based on the heart rate data optically obtained during the predetermined stage of sleep within the one or more historical sleep intervals, creating an indicator of a likelihood of a respiratory infection of the user”, as recited in claim 1 and claim 18. Applicant also argues that Tiron does not teach “automatically generating an indicator for likelihood of an infection of the user with a respiratory illness at least once per day based on a comparison of one or more features of the physiological data signal during a particular stage of sleep within the recent sleep interval to the one or more features of the physiological data signals during the particular stage of sleep within the at least one historical sleep interval”, as recited in claim 7.
MPEP § 2111 discusses proper claim interpretation, including giving claims their broadest reasonable interpretation in light of the specification during examination. Under broadest reasonable interpretation (BRI), the words of a claim must be given their plain meaning unless such meaning is inconsistent with the specification, and it is improper to import claim limitations from the specification into the claim. The requirements for anticipation are discussed in MPEP § 2131. MPEP § 2131 notes that “To reject a claim as anticipated by a reference, the disclosure must teach every element required by the claim under its broadest reasonable interpretation.”
The claims, as written, do not integrate the inventive concept into practical application under BRI. Claims 1, 7, and 18 recite creating/generating an indicator of a likelihood of a respiratory infection of a user, which is an abstract idea of a mental process performed using generic computers and sensors as described above. The indicator is not being used to develop or inform any type of treatment, test, or diagnosis corresponding to the indicator of likelihood. As written, this indicator of likelihood could be determined in a person’s mind as “likely” or “not likely” after looking at the data collected by the generic optical sensor. Therefore, the likelihood is not a practical application and is merely being indicated using generic computers and sensors to acquire and output data.
There are new grounds of claim rejections that were necessitated by the claim amendments.
The amended limitations of claims 1, 7, and 18 are taught by Tiron, as described above. Under BRI, the “one or more features” may be any feature associated with the respiratory rate pattern and the optically obtained heart rate data, such as coughing events taught by Tiron [0504]. Tiron teaches optical PPG sensors being used to determine respiratory and heart rate data in [0054]. Comparison of these data to baseline measures [0499] in combination with classification of coughing events [0515] during sleep stages [0505] can be used to indicate a respiratory infection [0039]. Tiron also teaches the data being collected and compared at present and previous time periods during sleep sessions [0030, 0042, 0068, 0504].
Claims 3-6, 8-9, 11, 14-17, and 19-24 are rejected because the rejection of claims 1, 7, and 18 are proper and the prior art teaches or suggests all the features of these claims for the reasons described in the 102.
Conclusion
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 EVELYN GRACE PARK whose telephone number is (571)272-0651. The examiner can normally be reached Monday - Friday, 9AM - 5:00PM.
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, Robert (Tse) Chen can be reached at (571)272-3672. 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.
/EVELYN GRACE PARK/Examiner, Art Unit 3791
/TSE W CHEN/Supervisory Patent Examiner, Art Unit 3791