Patent Application 17953050 - APPARATUS AND METHOD FOR ESTIMATING BODY

Title: APPARATUS AND METHOD FOR ESTIMATING BODY TEMPERATURE
Application Information

Invention Title: APPARATUS AND METHOD FOR ESTIMATING BODY TEMPERATURE
Application Number: 17953050
Submission Date: 2025-05-14T00:00:00.000Z
Effective Filing Date: 2022-09-26T00:00:00.000Z
Filing Date: 2022-09-26T00:00:00.000Z
National Class: 600
National Sub-Class: 549000
Examiner Employee Number: 99955
Art Unit: 3791
Tech Center: 3700
Rejection Summary

102 Rejections: 0
103 Rejections: 4
Cited Patents

No patents were cited in this rejection.
Office Action Text


    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 Objections
Claims 1 and 20 are objected to because of the following informalities:
The claim 1 limitation “the core body temperature” should be “the estimated core body temperature” or “the core body temperature estimation.”  
The claim 19 limitation “based on the core body temperature, and the health profile information” should have the comma deleted to remove confusion.
The claim 20 limitation “measurement sites in a body of the user” should be “measurement sites on a body of the user.”
Appropriate correction is required.

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 20 is 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.
Regarding claim 20, it is unclear whether the “one of a plurality of temperature measurement sites” is part of the health profile information or not.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.


Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Under the two-step 101 analysis, the claims fail to satisfy the
criteria for subject matter eligibility.
Step 1: Claims 1-20 are within at least one of the four statutory categories.
Claim 1 and dependent claims 2-9 disclose an apparatus.
Claim 10 and dependent claims 11-18 disclose a method.
Claim 19 and dependent claim 20 disclose an apparatus.

Step 2A, Prong One: The independent claims 1, 10, and 19 recite limitations directed to an abstract idea that is part of the Mathematical Concepts and/or Mental Processes group identified in the 2019 Revised Patent Subject Matter Eligibility Guidance published in the Federal Register (84 FR 50) on January 7, 2019.
	Mathematical Concepts: “A mathematical relationship is a relationship between variables or numbers. A mathematical relationship may be expressed in words ….” October 2019 Update: Subject Matter Eligibility, II. A. i. “[T]here are instances where a formula or equation is written in text format that should also be considered as falling within this grouping.” Id. at II. A. ii. “[A] claim does not have to recite the word “calculating” in order to be considered a mathematical calculation.” Id. at II. A. iii. See for example, SAP Am., Inc. v. InvestPic, LLC, 898 F.3d 1161, 1163-65 (Fed. Cir. 2018) (performing a resampled statistical analysis to generate a resampled distribution).
Mental Processes: Mental Processes can be practically performed in the human mind using mental steps, a pen and paper, or basic critical thinking/judgement -- types of activities that have been found by the courts to represent abstract ideas. See p. 7-8 of October 2019 Update: 2019 Revised Patent Subject Matter Eligibility Guidance published in the Federal Register (84 FR 50) for examples of ineligible claims that recite mental processes.
	Claims 1, 10, and 19 recite the follow abstract ideas:
“estimate[e]/[ing] a cutaneous blood flow and an energy metabolism of the object based on the PPG signal”
[0042] “the processor 120 may extract a feature from the PPG signal, and may estimate the cutaneous blood flow based on the extracted feature by using a model that defines a correlation between the feature and the cutaneous blood flow.” [0044] “the processor 120 may extract, as a feature of the PPG signal, an area under curve (AUC) which is an area 210 of an AC component the PPG signal, and may estimate the cutaneous blood flow by using the extracted AUC. In this case, the processor 120 may obtain the cutaneous blood flow based on the extracted AUC by using a blood flow estimation model that defines a correlation between the AUC and the cutaneous blood flow.” [0045] “the processor 12 may extract, as a feature of the PPG signal, a Perfusion Index that indicates a ratio of the AC signal to the DC signal of the PPG signal, and may estimate the cutaneous blood flow by using the obtained Perfusion Index. For example, the processor 120 may obtain the cutaneous blood flow based on the obtained Perfusion Index by using a blood flow estimation model that defines a correlation between the Perfusion Index and the cutaneous blood flow.” [0046] “[Equation 1] PI(Perfusion Index) = AC/DC”
[0049] “the processor 120 may estimate the energy metabolism based on the obtained heart rate. In particular, the processor 120 may continuously output an estimation of the energy metabolism which is updated in real time as the PPG signal and the heart rate are continuously measured over time. For example, the processor 120 may estimate the energy metabolism MHR based on the obtained heart rate (HR) by using the following Equations 2 to 5.”
“estimate[e]/[ing] a core body temperature of the object based on the cutaneous blood flow and the energy metabolism”
[0058] “the processor 120 may estimate core body temperature of the object by applying the estimated cutaneous blood flow and energy metabolism to a predetermined core body temperature estimation model. In this case, the predetermined core body temperature estimation model may be represented by the following Equation 7.”
These limitations describe a mathematical calculation and/or a mental process as the skilled artisan is capable of performing the recited limitations and making a mental assessment thereafter. Estimating a cutaneous blood flow, an energy metabolism, and a core body temperature by evaluating area under a curve and/or via equations 1-7 can be performed through an individual’s mental process and judgement, as well as are mathematical concepts that can be determined mentally or with the aid of pen and paper.
Regarding the dependent claims, they are directed to either 1) steps that are also abstract or 2) additional data output that is well-understood, routine, and previously known to the industry:
Claims 2-4, 6, 11-13, and 15 further limit the calculations and mathematical relationships for the cutaneous blood flow, metabolic energy, and core body temperature via weights within models
Claims 5 and 14 further limit the estimation of metabolic energy to be based on heart rate determined from the PPG signal
Claims 7-8 and 16-17 further limit outputting notification information based on a temperature threshold/range
Claims 9 and 18 further limit the estimation of core body temperature to include a user’s motion and temperature
Claim 20 further limits health profile information and the selection of measurement sites
The dependent claims further limit the abstract ideas of independent claims 1, 10, and 19 and do not recite significantly more than the abstract ideas.
Step 2A, Prong Two: The judicial exceptions (abstract ideas) in claims 1-20 are not integrated into a practical application because:
The abstract idea amounts to simply implementing the abstract idea on a computer. For example, the recitations regarding the generic computing components for receiving measurement data and outputting results merely invoke a computer as a tool.
The data-gathering step (measuring PPG data) and the data-output step (providing the notification information on the risk of abnormal body temperature) do not add a meaningful limitation to the method as they are insignificant extra-solution activity.
There is no improvement to a computer or other technology. “The McRO court indicated that it was the incorporation of the particular claimed rules in computer animation that "improved [the] existing technological process", unlike cases such as Alice where a computer was merely used as a tool to perform an existing process.” MPEP 2106.05(a) II.
The claims recite a computer/processor that is used as a tool for obtaining measurement data and outputting results.
The claims do not apply the abstract idea to affect a particular treatment or prophylaxis for a disease or medical condition. Rather, the abstract idea is utilized to measure PPG data to output the notification information on the risk of abnormal body temperature.
The claims do not apply the abstract idea to a particular machine. “Integral use of a machine to achieve performance of a method may provide significantly more, in contrast to where the machine is merely an object on which the method operates, which does not provide significantly more.” MPEP 2106.05(b). II. “Use of a machine that contributes only nominally or insignificantly to the execution of the claimed method (e.g., in a data gathering step or in a field-of-use limitation) would not provide significantly more.” MPEP 2106.05(b) III. The pending claims utilize a computer/processor for receiving measurement data and outputting results.
The additional elements are identified as follows:
Claims 1-9 and 19-20 –  apparatus/device
Claims 1, 6, 9-10, 15, and 18 – object
Claims 1, 2, and 19 – PPG sensor
Claims 7,  16, and 19– output interface/display/user interface
Claims 1-9 and 19 – processor
Step 2B: Claims 1-20 do not include additional elements that are sufficient to provide for an inventive concept nor amount to significantly more than the judicial exception.
Those in the relevant field of art would recognize the above-identified additional elements as being well-understood, routine, and conventional means for receiving measurement data and outputting results as demonstrated by the specification. The applicant discloses nothing unique about the apparatus/device (Specification [0037, 0094, 0108]), object (Specification [0039]), PPG sensor (Specification [0040]), output interface/display/user interface (Specification [0082, 0105]]), processor (Specification [0100 0106 0110]), configured to perform the generic computer functions (e.g., receiving measurement data and outputting results) that are well-understood, routine, and conventional activities previously known to the pertinent industry.
Thus, the claimed additional elements “are so well-known that they do not need to be described in detail in a patent application to satisfy 35 U.S.C. § 112(a).” Berkheimer Memorandum, III. A. 3. Furthermore, the court decisions discussed in MPEP § 2106.05(d)(lI) note the well-understood, routine and conventional nature of such additional generic computer components as those claimed. See option III. A. 2. in the Berkheimer memorandum.
When considered in combination, the additional elements (i.e., the generic computer functions and conventional equipment/steps) do not amount to significantly more than the abstract idea. Looking at the claim limitations 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 the apparatus/device, object, PPG sensor, output interface/display, processor, or any other technology. Their collective functions
merely provide conventional computer implementation.
Therefore, claims 1-20 are directed to patent ineligible subject matter.

Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.

Claim(s) 1-7, 9-16, and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Reifman (US 20190192009 A1) in view of Wang (CN113545757A).
Regarding claim 1, Reifman teaches an apparatus for estimating body temperature (Fig. 1. [0052] “A system and method of estimating a body temperature of an individual is provided”). While, Reifman discloses in [0014] a “fitness-tracking device 110 includes a chest strap or a wrist watch, which continually collects an individual's heart rate, activity (e.g., via a 3 axis accelerometer), and skin temperature,” Reifman fails to specifically disclose PPG.
Wang teaches a core temperature measuring method using PPG. The combination of Reifman/Wang teaches the apparatus comprising:
a photoplethysmogram (PPG) sensor configured to measure a PPG signal by emitting light onto an object and by detecting light scattered or reflected from the object (Wang: Fig. 4; Pg 4 [5] “The measuring method of the core temperature combines the environment temperature value to adjust and correct the PPG signal”);
and a processor (Reifman: processor 520, controller 530) configured to estimate a cutaneous blood flow (Wang: Pg 4 [10] “because the PPG signal generated in the process of toggling along the arterial blood vessel and blood flow to the periphery, and the human body blood flow is often associated with the temperature in the environment, based on this, the embodiment by obtaining and PI data to reflect the blood flow in the target object.”) and an energy metabolism of the object based on the PPG signal (Reifman: [0017] “account for features such as the rate of heat gain due to metabolic activity… after measurements of heart rate;” Wang: Pg 6 [5] “extracting the heart rate from the sample PPG signal”),
estimate a core body temperature of the object based on the cutaneous blood flow and the energy metabolism (Wang: Pg 2 [2-3] “a core temperature measuring method, comprising: collecting the initial PPG (Photo Plethysmo Graphy, photoelectric volume pulse wave) signal of the target object; according to the initial PPG signal, determining the PI (Perfusion Index, blood flow perfusion index) data of the target object;” Reifman: [0017] “The algorithm can repeat this procedure after measurements of heart rate [energy metabolism], activity, and skin temperature [related to cutaneous blood flow and Perfusion Index per Wang] every minute to update the model parameters, individualize the model, and provide new estimates of core body temperature”),
and provide notification information on a risk of abnormal body temperature based on the core body temperature (Reifman: [0020] In at least one embodiment, the system can also be used to predict core body temperature (e.g., 20 minutes in advance) and provide ample time to intervene and prevent an impending heat injury. This can be achieved by coupling a series of estimated core body temperatures with a predictive model in the development of a real-time, heat-injury warning system.”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system of Reifman to include PPG and measurement of cutaneous blood flow as disclosed in Wang to adjust and correct the PPG signal according to the PI data to ensure the PPG signal can accurately reflect the core temperature value of the human body and improve overall measuring precision of the core temperature value (Wang Pg 4 [5-6]). 

Regarding claim 2, the combination of Reifman/Wang discloses the apparatus of claim 1:
wherein the processor (Reifman: processor 520, controller 530) is further configured to obtain a reference cutaneous blood flow and a reference energy metabolism based on a calibration PPG signal measured by the PPG sensor at a calibration time (Wang: Pg 8 [2-3] “Step S60: obtaining all PI data corresponding to the current environment temperature value… because of different environmental temperature values, having different initial PPG signal, and the ratio of initial PPG signal alternating component and direct current component can be used for representing the PI data; therefore, it only needs to obtain the initial PPG signal corresponding to different environment temperature values according to the above steps; to determine the corresponding PI data, will not be repeated here, parameter can be the corresponding content.” Pg 6 [5] “wherein the first corresponding relationship is determined based on a large number of sample temperature values and a sample PPG signal; Specifically, the sample PPG signal from extracting a characteristic data capable of reflecting the sample PPG signal, for directly representing the first corresponding relation, for example, extracting the heart rate from the sample PPG signal, then obtaining the corresponding relation between the heart rate and the sample temperature value;” Reifman: [0017] “rate of heat gain due to metabolic activity;”),
determine weights to be applied to the reference cutaneous blood flow and the reference energy metabolism, respectively, and generate a core body temperature estimation model for estimating the core body temperature based on a weighted sum of the reference cutaneous blood flow and the reference energy metabolism (Reifman: [0017] “In at least one embodiment, the Kalman filter considers the errors between the estimates provided by the mathematical model and the actual measured heart rate and skin temperature of the individual, and can provide corrections by adjusting up to seven parameters in the mathematical model” [0030] “A controller connected to the processor can modify one or more parameters in the model when the difference between the estimated physiological condition and the measured physiological condition is above a threshold 450. The modifying of the parameter(s) in the model can include modifying a rate constant for the heart rate signal (α.sub.1), a thermoregulatory rate constant for the core temperature signal (α.sub.2), a rate of convective heat loss/gain from the skin to the environment (α.sub.3) , a rate of heat loss to the environment due to sweat evaporation (α.sub.4), a gain in heart rate due to physical activity (β), a rate of heat gain due to metabolic activity (γ.sub.1), and/or a rate of heat loss/gain from the core to the skin (γ.sub.2).” Wang: Pg 2 [2-3] “according to the initial PPG signal, determining the PI (Perfusion Index, blood flow perfusion index) data of the target object”).

Regarding claim 3, the combination of Reifman/Wang discloses the apparatus of claim 2, wherein the processor is further configured to determine a first weight for the cutaneous blood flow based on heat generated from an external heat source, and determine a second weight for the energy metabolism based on an internally generated heat (Reifman: [0030] “A controller connected to the processor can modify one or more parameters in the model when the difference between the estimated physiological condition and the measured physiological condition is above a threshold 450. The modifying of the parameter(s) in the model can include modifying a rate constant for the heart rate signal (α.sub.1), a thermoregulatory rate constant for the core temperature signal (α.sub.2), a rate of convective heat loss/gain from the skin to the environment (α.sub.3) [with the cutaneous blood flow and Perfusion Index of Wang Pg 2 [2-3], inherently due to external heat source], a rate of heat loss to the environment due to sweat evaporation (α.sub.4), a gain in heart rate due to physical activity (β), a rate of heat gain due to metabolic activity (γ.sub.1) [inherently internally generated heat], and/or a rate of heat loss/gain from the core to the skin (γ.sub.2).”). 

Regarding claim 4, the combination of Reifman/Wang discloses the apparatus of claim 1, wherein the processor (Reifman: processor 520, controller 530) is configured to extract a feature from the PPG signal, and estimate the cutaneous blood flow based on the extracted feature by using a model that defines a correlation between the feature and the cutaneous blood flow (Wang: Pg 8 [8] “Specifically, because the initial PPG signal with the current environment temperature value corresponding to the first corresponding relation, and PI [Perfusion Index, blood flow perfusion index] data based on the initial PPG signal AC component and direct current component ratio to obtain, therefore, correspondingly obtaining the PI data corresponding to the current environment temperature value of the second corresponding relation; obtaining the second corresponding relation between the PI data and the initial PPG signal; so that it can be input any current environment temperature value or initial PPG signal, it can determine a corresponding PI data; wherein the second corresponding relation can be determined by means of linear regression, namely determining the PI data corresponding to the initial PPG signal or the current environmental temperature value corresponding to the linear regression equation by the least square method.”).  
Regarding claim 5, the combination of Reifman/Wang discloses the apparatus of claim 1, wherein the processor (Reifman: processor 520, controller 530) is further configured to obtain a heart rate from the PPG signal (Wang: Pg 6 [5] “extracting the heart rate from the sample PPG signal, then obtaining the corresponding relation between the heart rate and the sample temperature value”), and estimate the energy metabolism based on the heart rate (Reifman: [0017] “In at least one embodiment, the Kalman filter considers the errors between the estimates provided by the mathematical model and the actual measured heart rate and skin temperature of the individual, and can provide corrections by adjusting up to seven parameters in the mathematical model. In at least one embodiment, the seven parameters, which may be continually adjusted and updated, account for features such as the rate of heat gain due to metabolic activity…”).  
Regarding claim 6, the combination of Reifman/Wang discloses the apparatus of claim 1, wherein the processor (Reifman: processor 520, controller 530) is further configured to estimate the core body temperature of the object by applying the cutaneous blood flow and the energy metabolism to a predetermined core body temperature estimation model (Reifman: [0017] “In at least one embodiment, the Kalman filter considers the errors between the estimates provided by the mathematical model and the actual measured heart rate and skin temperature [using the cutaneous blood flow and Perfusion Index of Wang Pg 2 [2-3]], of the individual, and can provide corrections by adjusting up to seven parameters in the mathematical model. In at least one embodiment, the seven parameters, which may be continually adjusted and updated, account for features such as the rate of heat gain due to metabolic activity, the rate of convective heat loss or gain from the skin surface to the environment, and the rate of heat loss to the environment due to sweat evaporation, among others. The algorithm can repeat this procedure after measurements of heart rate, activity, and skin temperature every minute to update the model parameters, individualize the model, and provide new estimates of core body temperature”).  
Regarding claim 7, the combination of Reifman/Wang discloses the apparatus of claim 1, further comprising an output interface, wherein in response to the estimated core body temperature falling outside a predetermined threshold range, the processor is further configured to provide the notification information on the risk of abnormal body temperature through the output interface (Wang: Pg 5 [9] “it also can realize the prompting function by sending the prompting message to the intelligent watch display screen; or by means of the intelligent watch sending different voice information.” Reifman: [0020] “In at least one embodiment, the system can also be used to predict core body temperature (e.g., 20 minutes in advance) and provide ample time to intervene and prevent an impending heat injury. This can be achieved by coupling a series of estimated core body temperatures with a predictive model in the development of a real-time, heat-injury warning system.”).  

Regarding claim 9, the combination of Reifman/Wang discloses the apparatus of claim 1, wherein the processor is further configured to estimate the core body temperature of the object based further on at least one of a user's motion and temperature while the PPG signal is measured (Reifman: processor 520, controller 530; [0023] “FIG. 4 illustrating a method for estimating a body temperature of an individual according to an embodiment of the invention (e.g., using the system 400). A processor can receive physiological data from a sensor in a wearable measuring device (a wearable accelerometer) 410. The processor can be in the wearable measuring device or in wireless communication with the wearable measuring device. The physiological data can include the heart rate, the skin temperature, and/or activity data of the individual. The physiological data can be from different body locations. The activity data can include the running speed of the individual and/or an activity score of the individual (e.g., low, moderate, high, and very high). In at least one embodiment, the processor receives the 3-D body acceleration of the individual from the wearable measuring device and maps the body acceleration into Metabolic Equivalent (MET, amount of energy burned during exercise) units to determine the activity score of the individual.”). 

Regarding claim 10, Reifman teaches a method of estimating body temperature (Fig. 1. [0052] “A system and method of estimating a body temperature of an individual is provided”). While, Reifman discloses in [0014] a “fitness-tracking device 110 includes a chest strap or a wrist watch, which continually collects an individual's heart rate, activity (e.g., via a 3 axis accelerometer), and skin temperature,” Reifman fails to specifically disclose PPG.
The combination of Reifman/Wang teaches the method comprising:
measuring a photoplethysmogram (PPG) signal by emitting light onto an object and by detecting light scattered or reflected from the object (Wang: Fig. 4; Pg 4 [5] “The measuring method of the core temperature combines the environment temperature value to adjust and correct the PPG signal”);
estimating cutaneous blood flow (Wang: Pg 4 [10] “because the PPG signal generated in the process of toggling along the arterial blood vessel and blood flow to the periphery, and the human body blood flow is often associated with the temperature in the environment, based on this, the embodiment by obtaining and PI data to reflect the blood flow in the target object.”) and energy metabolism based on the PPG signal (Reifman: [0017] “account for features such as the rate of heat gain due to metabolic activity… after measurements of heart rate;” Wang: Pg 6 [5] “extracting the heart rate from the sample PPG signal”);
estimating core body temperature of the object based on the cutaneous blood flow and the energy metabolism (Wang: Pg 2 [2-3] “a core temperature measuring method, comprising: collecting the initial PPG (Photo Plethysmo Graphy, photoelectric volume pulse wave) signal of the target object; according to the initial PPG signal, determining the PI (Perfusion Index, blood flow perfusion index) data of the target object;” Reifman: [0017] “The algorithm can repeat this procedure after measurements of heart rate [energy metabolism], activity, and skin temperature [related to cutaneous blood flow and Perfusion Index per Wang] every minute to update the model parameters, individualize the model, and provide new estimates of core body temperature”);
and providing notification information on a risk of abnormal body temperature based on the estimated core body temperature (Reifman: [0020] In at least one embodiment, the system can also be used to predict core body temperature (e.g., 20 minutes in advance) and provide ample time to intervene and prevent an impending heat injury. This can be achieved by coupling a series of estimated core body temperatures with a predictive model in the development of a real-time, heat-injury warning system.”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system of Reifman to include PPG and measurement of cutaneous blood flow as disclosed in Wang to adjust and correct the PPG signal according to the PI data to ensure the PPG signal can accurately reflect the core temperature value of the human body and improve overall measuring precision of the core temperature value (Wang Pg 4 [5-6]). 
  
Regarding claim 11, the combination of Reifman/Wang discloses the method of claim 10,
further comprising obtaining a reference cutaneous blood flow and a reference energy metabolism based on a calibration PPG signal at a calibration time (Wang: Pg 8 [2-3] “Step S60: obtaining all PI data corresponding to the current environment temperature value … because of different environmental temperature values, having different initial PPG signal, and the ratio of initial PPG signal alternating component and direct current component can be used for representing the PI data; therefore, it only needs to obtain the initial PPG signal corresponding to different environment temperature values according to the above steps; to determine the corresponding PI data, will not be repeated here, parameter can be the corresponding content.” Pg 6 [5] “wherein the first corresponding relationship is determined based on a large number of sample temperature values and a sample PPG signal; Specifically, the sample PPG signal from extracting a characteristic data capable of reflecting the sample PPG signal, for directly representing the first corresponding relation, for example, extracting the heart rate from the sample PPG signal, then obtaining the corresponding relation between the heart rate and the sample temperature value;” Reifman: [0017] “rate of heat gain due to metabolic activity;”),
determining weights to be applied to the reference cutaneous blood flow and the reference energy metabolism, respectively, and generating a core body temperature estimation model for estimating the core body temperature based on a weighted sum of the reference cutaneous blood flow and the reference energy metabolism (Reifman: [0017] “In at least one embodiment, the Kalman filter considers the errors between the estimates provided by the mathematical model and the actual measured heart rate and skin temperature of the individual, and can provide corrections by adjusting up to seven parameters in the mathematical model” [0030] “A controller connected to the processor can modify one or more parameters in the model when the difference between the estimated physiological condition and the measured physiological condition is above a threshold 450. The modifying of the parameter(s) in the model can include modifying a rate constant for the heart rate signal (α.sub.1), a thermoregulatory rate constant for the core temperature signal (α.sub.2), a rate of convective heat loss/gain from the skin to the environment (α.sub.3) , a rate of heat loss to the environment due to sweat evaporation (α.sub.4), a gain in heart rate due to physical activity (β), a rate of heat gain due to metabolic activity (γ.sub.1), and/or a rate of heat loss/gain from the core to the skin (γ.sub.2).” Wang: Pg 2 [2-3] “according to the initial PPG signal, determining the PI (Perfusion Index, blood flow perfusion index) data of the target object”).  
Regarding claim 12, the combination of Reifman/Wang discloses the method of claim 11, wherein the generating of the core body temperature estimation model comprises determining a first weight for the cutaneous blood flow based on heat generated from an external heat source, and determining a second weight for the energy metabolism based on an internally generated heat (Reifman: [0030] “A controller connected to the processor can modify one or more parameters in the model when the difference between the estimated physiological condition and the measured physiological condition is above a threshold 450. The modifying of the parameter(s) in the model can include modifying a rate constant for the heart rate signal (α.sub.1), a thermoregulatory rate constant for the core temperature signal (α.sub.2), a rate of convective heat loss/gain from the skin to the environment (α.sub.3) [with the cutaneous blood flow and Perfusion Index of Wang Pg 2 [2-3], inherently due to external heat source], a rate of heat loss to the environment due to sweat evaporation (α.sub.4), a gain in heart rate due to physical activity (β), a rate of heat gain due to metabolic activity (γ.sub.1) [inherently internally generated heat], and/or a rate of heat loss/gain from the core to the skin (γ.sub.2).”).
Regarding claim 13, the combination of Reifman/Wang discloses the method of claim 10, wherein the estimating of the cutaneous blood flow comprises extracting a feature from the PPG signal, and estimating the cutaneous blood flow based on the extracted feature by using a model that defines a correlation between the feature and the cutaneous blood flow (Wang: Pg 8 [8] “Specifically, because the initial PPG signal with the current environment temperature value corresponding to the first corresponding relation, and PI [Perfusion Index, blood flow perfusion index] data based on the initial PPG signal AC component and direct current component ratio to obtain, therefore, correspondingly obtaining the PI data corresponding to the current environment temperature value of the second corresponding relation; obtaining the second corresponding relation between the PI data and the initial PPG signal; so that it can be input any current environment temperature value or initial PPG signal, it can determine a corresponding PI data; wherein the second corresponding relation can be determined by means of linear regression, namely determining the PI data corresponding to the initial PPG signal or the current environmental temperature value corresponding to the linear regression equation by the least square method.”).
Regarding claim 14, the combination of Reifman/Wang discloses the method of claim 10, wherein the estimating of the energy metabolism comprises obtaining a heart rate from the PPG signal (Wang: Wang: Pg 6 [5] “extracting the heart rate from the sample PPG signal, then obtaining the corresponding relation between the heart rate and the sample temperature value”), and estimating the energy metabolism based on the heart rate (Reifman: [0017] “In at least one embodiment, the Kalman filter considers the errors between the estimates provided by the mathematical model and the actual measured heart rate and skin temperature of the individual, and can provide corrections by adjusting up to seven parameters in the mathematical model. In at least one embodiment, the seven parameters, which may be continually adjusted and updated, account for features such as the rate of heat gain due to metabolic activity…”).  
Regarding claim 15, the combination of Reifman/Wang discloses the method of claim 10, wherein the estimating of the core body temperature of the object comprises estimating the core body temperature of the object by applying the cutaneous blood flow and the energy metabolism to a predetermined core body temperature estimation model (Reifman: [0017] “In at least one embodiment, the Kalman filter considers the errors between the estimates provided by the mathematical model and the actual measured heart rate and skin temperature [using the cutaneous blood flow and Perfusion Index of Wang Pg 2 [2-3]], of the individual, and can provide corrections by adjusting up to seven parameters in the mathematical model. In at least one embodiment, the seven parameters, which may be continually adjusted and updated, account for features such as the rate of heat gain due to metabolic activity, the rate of convective heat loss or gain from the skin surface to the environment, and the rate of heat loss to the environment due to sweat evaporation, among others. The algorithm can repeat this procedure after measurements of heart rate, activity, and skin temperature every minute to update the model parameters, individualize the model, and provide new estimates of core body temperature”).  
Regarding claim 16, the combination of Reifman/Wang discloses the method of claim 10, wherein the providing of the notification information on the risk of abnormal body temperature comprises, in response to the estimated core body temperature falling outside a predetermined threshold range, providing the notification information on the risk of abnormal body temperature through an output interface (Wang: Pg 5 [9] “it also can realize the prompting function by sending the prompting message to the intelligent watch display screen; or by means of the intelligent watch sending different voice information.” Reifman: [0020] “In at least one embodiment, the system can also be used to predict core body temperature (e.g., 20 minutes in advance) and provide ample time to intervene and prevent an impending heat injury. This can be achieved by coupling a series of estimated core body temperatures with a predictive model in the development of a real-time, heat-injury warning system.”).  
Regarding claim 18, the combination of Reifman/Wang discloses the method of claim 10, wherein the estimating of the core body temperature of the object comprises estimating the core body temperature of the object based further on at least one of a user's motion and temperature while the PPG signal is measured (Reifman: processor 520, controller 530; [0023] “FIG. 4 illustrating a method for estimating a body temperature of an individual according to an embodiment of the invention (e.g., using the system 400). A processor can receive physiological data from a sensor in a wearable measuring device (a wearable accelerometer) 410. The processor can be in the wearable measuring device or in wireless communication with the wearable measuring device. The physiological data can include the heart rate, the skin temperature, and/or activity data of the individual. The physiological data can be from different body locations. The activity data can include the running speed of the individual and/or an activity score of the individual (e.g., low, moderate, high, and very high). In at least one embodiment, the processor receives the 3-D body acceleration of the individual from the wearable measuring device and maps the body acceleration into Metabolic Equivalent (MET, amount of energy burned during exercise) units to determine the activity score of the individual.”). 

Claim(s) 8 and 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Reifman (US 20190192009 A1) in view of Wang (CN113545757A), and in further view of Gelissen (US 20170360299 A1).
Regarding claim 8, the combination of Reifman/Wang discloses the apparatus of claim 1, wherein in response to the estimated core body temperature falling outside a predetermined temperature range, the processor is further configured to provide a text message or a voice message (Wang: Pg 5 [9] “it also can realize the prompting function by sending the prompting message to the intelligent watch display screen; or by means of the intelligent watch sending different voice information.” Reifman: [0020] “In at least one embodiment, the system can also be used to predict core body temperature (e.g., 20 minutes in advance) and provide ample time to intervene and prevent an impending heat injury. This can be achieved by coupling a series of estimated core body temperatures with a predictive model in the development of a real-time, heat-injury warning system.”). However, the combination of Reifman/Wang fails to disclose a recommendation to stop outdoor activities.
Gelissen teaches a wearable device that uses health inputs from embedded body sensors for the duration of an activity performed by a user of the wearable device to calculate a health parameter. Gelissen discloses that recommends stopping outdoor activities ([0143] 18A illustrates an exemplary health database 272 of the health network 270. The information from the health database 272 may include temperatures (column 1805) ranging from 70° F. down to minus 10° F., health summaries (column 1810) indicating that a user BP is high, and various recommendations (1815) from the health network 270. The recommendations in FIG. 18A may include notifications to see physician, spend more time indoors, see physician, spend more time indoors to lower BP, and stay indoors, see physician, or other recommended actions.). 
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combination of Reifman/Wang to include recommending stopping outdoor activities as disclosed in Gelissen to remedy an issue that the user is facing and improve the user’s calculated health parameter (Gelissen [0069 and 0143]).

Regarding claim 17, the combination of Reifman/Wang discloses the method of claim 10, further comprising, in response to the core body temperature falling outside a predetermined threshold range, providing a text message or a voice message (Wang: Pg 5 [9] “it also can realize the prompting function by sending the prompting message to the intelligent watch display screen; or by means of the intelligent watch sending different voice information.” Reifman: [0020] “In at least one embodiment, the system can also be used to predict core body temperature (e.g., 20 minutes in advance) and provide ample time to intervene and prevent an impending heat injury. This can be achieved by coupling a series of estimated core body temperatures with a predictive model in the development of a real-time, heat-injury warning system.”). However, the combination of Reifman/Wang fails to disclose a recommendation to stop outdoor activities.
Gelissen discloses that recommends stopping outdoor activities ([0143] 18A illustrates an exemplary health database 272 of the health network 270. The information from the health database 272 may include temperatures (column 1805) ranging from 70° F. down to minus 10° F., health summaries (column 1810) indicating that a user BP is high, and various recommendations (1815) from the health network 270. The recommendations in FIG. 18A may include notifications to see physician, spend more time indoors, see physician, spend more time indoors to lower BP, and stay indoors, see physician, or other recommended actions.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combination of Reifman/Wang to include recommending stopping outdoor activities as disclosed in Gelissen to remedy an issue that the user is facing and improve the user’s calculated health parameter (Gelissen [0069 and 0143]).

Claim(s) 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Reifman (US 20190192009 A1) in view of Nielson (US 20200405160 A1), and in further view of Wang (CN113545757A).
Regarding claim 19, Reifman teaches an electronic device comprising: a display configured to provide a user interface (Reifman: [0049] “The system further includes a user interface adapter 19 that connects a keyboard 15, mouse 17, speaker 24, microphone 22, and/or other user interface devices such as a touch screen device (not shown) to the bus 12 to gather user input. Additionally, a communication adapter 20 connects the bus 12 to a data processing network 25, and a display adapter 21 connects the bus 12 to a display device 23 which may be embodied as an output device such as a monitor, printer, or transmitter, for example.”). However, Reifman fails to specifically disclose to receive healthy profile information, a PPG signal, or cutaneous blood flow.
Nielson teaches a wellness tracking device that includes PPG and temperature sensing. Nielson discloses
to receive health profile information (Nielson: [0021] “the user may input their height, weight, age, stride, or other data in a user profile on a fitness-tracking website or application”);
a PPG sensor configured to measure a PPG signal by emitting light onto a user and by detecting light scattered or reflected from the user ([0046] “the sensors 602 may include a plurality of different sensors, such as SpO2 sensors, PPG (photoplethysmography) sensors, ECG (electrocardiography) sensors, temperature sensors, and the like.”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the device of Reifman to include receiving health profile information and PPG as disclosed in Nielson as the health profile information and PPG signals may be used in combination to more accurately evaluate user physiological parameters and behaviors, and the PPG adjust and correct the PPG signal according to the PI data to ensure the PPG signal can accurately reflect the core temperature value of the human body and improve overall measuring precision of the core temperature value (Nielson [0021]). 
However the combination of Reifman/Nielson fails to disclose cutaneous blood flow.
The combination of Reifman/Nielson/Wang discloses:
and a processor configured to estimate a cutaneous blood flow (Wang: Pg 4 [10] “because the PPG signal generated in the process of toggling along the arterial blood vessel and blood flow to the periphery, and the human body blood flow is often associated with the temperature in the environment, based on this, the embodiment by obtaining and PI data to reflect the blood flow in the target object.”) and an energy metabolism of the user based on the PPG signal (Reifman: [0017] “account for features such as the rate of heat gain due to metabolic activity… after measurements of heart rate;” Nielson: [0021] “The user monitoring device 102 may collectively or respectively capture data related to any one or more of caloric energy expenditure, floors climbed or descended, heart rate, heart rate variability, heart rate recovery;” [0046] “PPG (photoplethysmography) sensors”),
estimate a core body temperature of the user based on the cutaneous blood flow and the energy metabolism (Wang: Pg 2 [2-3] “a core temperature measuring method, comprising: collecting the initial PPG (Photo Plethysmo Graphy, photoelectric volume pulse wave) signal of the target object; according to the initial PPG signal, determining the PI (Perfusion Index, blood flow perfusion index) data of the target object;” Reifman: [0017] “The algorithm can repeat this procedure after measurements of heart rate [regarding energy metabolism], activity, and skin temperature [related to cutaneous blood flow and Perfusion Index per Wang] every minute to update the model parameters, individualize the model, and provide new estimates of core body temperature”),
and provide notification information on a risk of abnormal body temperature based on the core body temperature, and the health profile information (Nielson: [0021] “The user monitoring device 102 may collectively or respectively capture data related to any one or more of caloric energy expenditure, floors climbed or descended, heart rate, heart rate variability, heart rate recovery, location and/or heading (e.g., through GPS), elevation, ambulatory speed and/or distance traveled, swimming lap count, bicycle distance and/or speed, blood pressure, blood glucose, skin conduction, skin and/or body temperature, electromyography data, electroencephalographic data, weight, body fat, respiration rate and patterns, various body movements, among others. Additional data may be provided from an external source, e.g., the user may input their height, weight, age, stride, or other data in a user profile on a fitness-tracking website or application and such information may be used in combination with some of the above-described data to make certain evaluation or in determining user behaviors;” Reifman: [0020] “In at least one embodiment, the system can also be used to predict core body temperature (e.g., 20 minutes in advance) and provide ample time to intervene and prevent an impending heat injury. This can be achieved by coupling a series of estimated core body temperatures with a predictive model in the development of a real-time, heat-injury warning system.”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combination of Reifman/Nielson to include estimate of cutaneous blood flow as disclosed in Wang to adjust and correct the PPG signal according to the PI data to ensure the PPG signal can accurately reflect the core temperature value of the human body and improve overall measuring precision of the core temperature value (Wang Pg 4 [5-6]). 

Claim(s) 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Reifman (US 20190192009 A1) in view of Nielson (US 20200405160 A1) and Wang (CN113545757A), and in further view of St. Pierre (US 20110071420 A1).
Regarding claim 20, the combination of Reifman/Nielson/Wang discloses the electronic device of claim 19, wherein the health profile information comprises a weight, a height, and an age of the user (Nielson: [0021] “Additional data may be provided from an external source, e.g., the user may input their height, weight, age, stride, or other data in a user profile on a fitness-tracking website or application”). However, the combination of Reifman/Nielson/Wang fails to disclose a user selecting a temperature measurement site.
St. Pierre teaches a device that obtains a series of measurements of a physiological parameter such as temperature measurements of a monitored patient. St. Pierre discloses and one of a plurality of temperature measurement sites in a body of the user which is selected by the user ([0081] “ When the PMP device 200 measures the patient's temperature in the predictive mode, the thermometer can be located at various places on the patient's body. Example locations on the patient's body where the thermometer can be located include in the patient's mouth, on the patient's thigh, in the patient's armpit, in the patient's rectum, and other locations. The temperature frame 314d includes a thermometry location control 328b.”[0082] “When a user selects the thermometry location control 328b, the PMP device 200 updates the thermometry location control 328b such that the thermometry location control 328b indicates a different location on the patient's body”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combination of Reifman/Nielson/Wang to include a user selecting a temperature measurement site as disclosed in St. Pierre to accurately read and predict the patient’s temperature based on the periodic reading of the patient’s temperature from a selected location (St. Pierre [0080, 0081]).

Conclusion
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/M.H./Examiner, Art Unit 3791                                                                                                                                                                                                        

/DEVIN B HENSON/Primary Examiner, Art Unit 3791