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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on December 30, 2025 has been entered.
Response to Amendment
In response to amendments, filed December 30, 2025, claims 1, 9-10, and 18 have been amended. Claims 3, 5-7, 12, and 14-16 have been cancelled. No claims have been added. Claims 1-2, 4, 8-11, 13, and 17-18 are pending.
Response to Arguments
Applicant’s arguments, see Remarks, filed December 30, 2025, with respect to the 35 U.S.C 101 rejections have been fully considered and are persuasive in view of the arguments. The present invention provides a significant improvement to the technology, supported by [0077] of the specification. The invention unconventionally applies each individual's characteristics to create a personalized temperature estimation model that improves estimation accuracy.
Applicant’s arguments with respect to prior art rejections have been considered but are moot because the new ground of rejection does not rely on the same reference combination applied in the prior rejection of record for any teaching or matter specifically challenged in the argument. A new ground(s) of rejection is made in view of the combinations of Uchiyama (WO 2017213011 A1)/St. Pierre (US 20110071420 A1)/Wang (CN113545757A)/Gelissen (US 20190209045 A1)/Gelissen (US 20170360299 A1).
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) 1-2, 4, 9-11, 13, and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Uchiyama (WO 2017213011 A1) in view of St. Pierre (US 20110071420 A1), Wang (CN113545757A), and Gelissen (US 20190209045 A1).
Regarding claim 1, Uchiyama teaches an apparatus for estimating body temperature (Fig. 5; deep body temperature estimation device 1), the apparatus comprising: a display configured to provide a user interface to receive health profile information that comprises a weight, a height, an age, and a temperature measurement site on a body (pg 5 [7] “The input unit 11 includes a numeric keypad, a mouse, or a touch panel that can input various types of information from the outside. The output unit 13 is provided as necessary, and is, for example, a display for displaying an image or a sound generator.” Fig. 5; pg 3 [5] “User information such as height and weight is used to estimate” pg 3 [7] “the metabolic fever M is estimated based on the user's heart rate, resting heart rate, weight, and age.” pg 2 [5] “In the aspect in which the wearable sensor 20 is equipped with a thermometer, the skin temperature may be measured using the thermometer, and the measurement result may be transmitted to the model via the communication unit 201 (see FIG. 5). However, instead of this, the temperature may be measured with a thermometer and input from the input unit 11.”). However, Uchiyama fails to disclose a plurality of temperature measurement sites or a PPG signal.
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 a temperature measurement site on a body selected by a user, from a plurality of temperature measurement sites displayed on the user interface ([0082] “The user can continue selecting the thermometry location control 328b until the thermometry location control 328b indicates a location where the thermometer is located on the patient's body or until the thermometry location control 328b indicates that measurements are to be obtained in direct mode. For example, in some embodiments, the PMP device 200 accepts readings from a thermometer when the thermometer is located in the patient's mouth, in an adult patient's armpit, or in a pediatric patient's armpit.” [0086] “The patient type button 316b indicates a value of a patient type parameter associated with the current patient.”).
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 apparatus of Uchiyama 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, 0086]).
While Uchiyama discloses measuring heart rate, the combination of Uchiyama/St. Pierre has no mention of PPG or more specifically AC/DC signals, or an abnormally low temperature threshold.
Wang teaches a core temperature measuring method using PPG. Wang discloses a photoplethysmogram (PPG) sensor configured to measure a PPG signal that comprises an alternating current (AC) signal and a direct current (DC) signal by emitting light onto the user and by detecting light scattered or reflected from the user (Fig. 4; Pg 2 [11] “obtaining the AC component and DC component of the initial PPG signal;” 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 (pg 9 [8] “As shown in FIG. 11, the computer device comprises a processor”) configured to:
estimate a cutaneous blood flow (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.”).
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 combination of Uchiyama/St. Pierre to include AC/DC PPG signals and measurement of cutaneous blood flow as disclosed in Wang to 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]).
However, the combination of Uchiyama/St. Pierre/Wang fails to particularly disclose area under a curve of the AC signal.
Gelissen_045 teaches a sensor system is for monitoring respiratory signals using PPG. The combination of Uchiyama/St. Pierre/Wang/Gelissen_045 discloses:
estimate a cutaneous blood flow of the user based on an area under a curve of the AC signal of the PPG signal (Gelissen_045: [0004] “a PPG-based sensor… detects changes in blood volume in the skin;” [0089] “The PPG amplitude (AC amplitude) as well as DC values (area under the curve of the AC signal) varies depending on body site;” 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”).
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 combination of Uchiyama/St. Pierre/Wang to include area under the curve of the AC signal as disclosed in Gelissen_045 as a means to normalize the physiological signal to the particular body location where the PPG signal is measured for more accurate readings (Gelissen_045 [0089]).
The combination of Uchiyama/St. Pierre/Wang/Gelissen_045 further discloses:
estimate an energy metabolism of the user based on a resting metabolic rate Mo, a difference between a resting heart rate HRo and a PPG-based heart rate HR obtained from the PPG signal, a difference between the resting metabolic rate Mo and a maximum work capacity (MWC), wherein the MWC is obtained based on the age and a lean body mass (LBM), and the LBM is obtained based on the weight and the height, and a difference between the resting heart rate HRo and a maximum heart rate (HRmax) that is obtained based on the age (Wang: pg 6 [5] “extracting the heart rate from the sample PPG signal;” Uchiyama: pg 3 [4] "The body temperature simulation using the two-node model described in the previous chapter requires four types of input: (1) user information such as weight, (2) initial body temperature, (3) metabolic rate, and (4) environmental conditions;” pg 4 [12] “the thermal calculation in the two-node model is delayed by two types of delay parameters β1 and β2. β1 controls the propagation speed of heat M generated by metabolism to take into account the initial drop in deep body temperature, and further delays the decrease in body temperature during a break. β1 is incorporated into the model as the size of the sliding window. The larger the β1, the lower the heat propagation rate due to metabolism. β2 represents a delay in the thermoregulatory response to an increase in body temperature;” pg 3 [6] “The total metabolic heat M in the model is estimated based on oxygen consumption. As shown by the equation (4), the metabolic fever is considered as the sum of resting metabolic fever (basal metabolism) M .sub.rest and metabolic fever M .sub.ex by exercise. Each metabolic fever [W] is calculated by equations (5) and (6). The terms 3.5 .Math. weight and (VO2−3.5) .Math. weight in these equations represent the resting state and oxygen consumption [ml / min] due to exercise, respectively." pg 3 [7] "VO2max is obtained from the user's maximum heart rate maxHR and resting heart rate restHR (formula (8)). Further, in order to estimate% VO2R from the heart rate, the current heart rate% HRR with respect to the reserve heart rate (how much it rises with respect to the maximum heart rate) is used to convert according to the equation (9). % HRR is calculated by the carbonnene method shown by Formula (10). The maximum heart rate is estimated based on the age of the user (formula (11)). By the above method, the metabolic fever M is estimated based on the user's heart rate, resting heart rate, weight, and age"),
estimate a core body temperature of the user based on an equation expressed as: Tc = α x SBFa + β x EEb, wherein Tc, denotes the core body temperature, SBF denotes the cutaneous blood flow, EE denotes the energy metabolism, α denotes a first weight for the cutaneous blood flow based on heat generated from an external heat source, and β denotes a second weight for the energy metabolism based on an internally generated heat (Uchiyama: pg 4 [3] "In the outdoor environment, the skin receives strong heat energy due to solar radiation, and the skin temperature rises. However, the conventional two-node model does not consider the influence of solar heat. Here, as shown in FIG. 2, the measurement value of the pyranometer included in the environmental sensor 12 installed in the environment, the user's total skin area, and clothes are used as inputs, and the direct solar radiation heat qdn received by the user is estimated. Was incorporated into the heat balance calculation. qdn is obtained by the following equation (E)." pg 3 [8] "the energy loss W due to external work is obtained by multiplying the exercise metabolism by the coefficient Δeff as shown in the equation (12). Δeff is known for basic types of exercise such as walking, running, and cycling." pg 4 [12] "the thermal calculation in the two-node model is delayed by two types of delay parameters β1 and β2. β1 controls the propagation speed of heat M generated by metabolism to take into account the initial drop in deep body temperature, and further delays the decrease in body temperature during a break. β1 is incorporated into the model as the size of the sliding window. The larger the β1, the lower the heat propagation rate due to metabolism. β2 represents a delay in the thermoregulatory response to an increase in body temperature." pg 2 [8] "In the two-node model, the body temperature change from time t to t + 1 is determined based on the deep body temperature T .sub.core .sup.t at time .sup.t , the skin temperature T .sub.skin .sup.t [incorporating 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;” for skin temperature estimations], and the input value from the wearable sensor 20 obtained at time t. By calculating the heat exchange during this time, the deep body temperature T .sub.core .sup.t and the changes ΔT .sub.core .sup.t and ΔT .sub.skin .sup.t of the skin temperature T .sub.skin .sup.t at time t are obtained, respectively. Based on the obtained change amount, the body temperature at time t + 1 is calculated by the following equation (A).");
set an abnormal body temperature range corresponding to the selected temperature measurement site, from among a plurality of abnormal body temperature ranges that are set differently for the plurality of temperature measurement sites (St. Pierre: [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 or whether the PMP device 200 is to obtain measurements of the patient's temperature in direct mode.” [0079] “A temperature alarm status area 328a is located at the right side of the temperature frame 314d. The temperature alarm status area 328a specifies an upper alarm limit and a lower alarm limit. The upper alarm limit and the lower alarm limit define a temperature alarm range. An alarm associated with the patient's temperature is active when the patient's temperature level is outside the temperature alarm range.” [0086] “by using the patient type button 316b to change the patient type parameter, the user can automatically change the alarm limits for the patient's physiological parameters. As described elsewhere in this document, the user can also manually set the alarm limits for physiological parameters.” Gelissen_045: [0089] “The PPG amplitude (AC amplitude) as well as DC values (area under the curve of the AC signal) varies depending on body site, which is why the normalization mentioned above is desired to compensate for this. The respiratory signal is for example normalized by the amplitude of the pulse signal. In this way, the baseline variation is expressed in relation to the magnitude of the pulse signal as seen in the PPG signal at that particular body location.”);
based on the estimated core body temperature being greater than or equal to a predetermined upper threshold of the abnormal body temperature range, control the display to output a high body temperature risk message along with a user guidance to lower the core body temperature; and based on the estimated core body temperature being less than or equal to a predetermined lower threshold of the abnormal body temperature range, control the display to output a low body temperature risk message along with a user guidance to increase the core body temperature (Uchiyama: pg 5 [14] “The warning processing unit 105 outputs a warning (display, warning sound, guide, etc.) and outputs a warning (eg, display, warning sound, guide, etc.) during the exercise after the warm-up is completed, for example, when the deep body temperature being calculated rises to the threshold value for determining heat stroke. To inform. The threshold value may be a fixed value, or may be set in consideration of a delay according to a set delay parameter, or may be set in consideration of a change gradient of the deep body temperature. Good.” pg 6 [2] “On the other hand, if the deep body temperature exceeds the threshold, a warning is issued (step S21). The monitoring process continues in the same manner when the estimated deep body temperature is removed from the warning state (decreased) due to a break after the warning and returns to the exercise again (No in steps S15 to S19).” St. Pierre: [0079] “The upper alarm limit and the lower alarm limit define a temperature alarm range. An alarm associated with the patient's temperature is active when the patient's temperature level is outside the temperature alarm range.”).
Regarding claim 2, the combination of Uchiyama/St. Pierre/Wang/Gelissen_045 discloses the apparatus of claim 1:
wherein the processor (Uchiyama: control unit 10; Wang: pg 9 [8] “As shown in FIG. 11, the computer device comprises a processor”) 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] “obtain the initial PPG signal corresponding to different environment temperature values according to the above steps; to determine the corresponding PI data” 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;” Uchiyama: pg 2 [8] “the initial deep body temperature T .sub.core .sup.0 and the initial skin temperature T .sub.skin .sup.0 are obtained;” pg 3 [6] “The total metabolic heat M in the model is estimated based on oxygen consumption. As shown by the equation (4), the metabolic fever is considered as the sum of resting metabolic fever (basal metabolism) M .sub.rest and metabolic fever M .sub.ex by exercise. Each metabolic fever [W] is calculated by equations (5) and (6).”),
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 (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;” Uchiyama: pg 4 [3] "In the outdoor environment, the skin receives strong heat energy due to solar radiation, and the skin temperature rises. However, the conventional two-node model does not consider the influence of solar heat. Here, as shown in FIG. 2, the measurement value of the pyranometer included in the environmental sensor 12 installed in the environment, the user's total skin area, and clothes are used as inputs, and the direct solar radiation heat qdn received by the user is estimated. Was incorporated into the heat balance calculation. qdn is obtained by the following equation (E)." pg 3 [8] "the energy loss W due to external work is obtained by multiplying the exercise metabolism by the coefficient Δeff as shown in the equation (12). Δeff is known for basic types of exercise such as walking, running, and cycling." pg 4 [12] "the thermal calculation in the two-node model is delayed by two types of delay parameters β1 and β2. β1 controls the propagation speed of heat M generated by metabolism to take into account the initial drop in deep body temperature, and further delays the decrease in body temperature during a break. β1 is incorporated into the model as the size of the sliding window. The larger the β1, the lower the heat propagation rate due to metabolism. β2 represents a delay in the thermoregulatory response to an increase in body temperature." pg 2 [8] "In the two-node model, the body temperature change from time t to t + 1 is determined based on the deep body temperature T .sub.core .sup.t at time .sup.t , the skin temperature T .sub.skin .sup.t [incorporating 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;” for skin temperature estimations], and the input value from the wearable sensor 20 obtained at time t. By calculating the heat exchange during this time, the deep body temperature T .sub.core .sup.t and the changes ΔT .sub.core .sup.t and ΔT .sub.skin .sup.t of the skin temperature T .sub.skin .sup.t at time t are obtained, respectively. Based on the obtained change amount, the body temperature at time t + 1 is calculated by the following equation (A).").
Regarding claim 4, the combination of Uchiyama/St. Pierre/Wang/Gelissen_045 discloses the apparatus of claim 1, wherein the processor (Uchiyama: control unit 10; Wang: pg 9 [8] “As shown in FIG. 11, the computer device comprises a processor”) 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.” Gelissen_045: [00899] “area under the curve of the AC signal”).
Regarding claim 9, the combination of Uchiyama/St. Pierre/Wang/Gelissen_045 discloses the apparatus of claim 1, wherein the processor (Uchiyama: control unit 10; Wang: pg 9 [8] “As shown in FIG. 11, the computer device comprises a processor”) is further configured to estimate the core body temperature of the user based further on a user's motion while the PPG signal is measured (Uchiyama: pg 3 [8] “the energy loss W due to external work is obtained by multiplying the exercise metabolism by the coefficient Δeff as shown in the equation (12). Δeff is known for basic types of exercise such as walking, running, and cycling. Therefore, Δeff = 0.40 (during walking), Δeff = 0.44 to 0.54 (during running), and Δeff = 0.23 (during bicycle exercise), respectively. Since energy efficiency changes depending on the speed when traveling, a value of 0.44 to 0.54 is given according to the speed of the user.” 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.”).
Regarding claim 10, Uchiyama teaches a method of estimating body temperature (pg 7 [9] “A depth body temperature estimation method comprising: a monitor calculation step of executing the heat balance calculation formula by applying the optimal parameter set and calculating the depth body temperature.”), the method comprising: providing, through a display, a user interface to receive health profile information that comprises a weight, a height, an age, and a temperature measurement site on a body (pg 5 [7] “The input unit 11 includes a numeric keypad, a mouse, or a touch panel that can input various types of information from the outside. The output unit 13 is provided as necessary, and is, for example, a display for displaying an image or a sound generator.” Fig. 5; “User information such as height and weight is used to estimate” pg 3 [7] “the metabolic fever M is estimated based on the user's heart rate, resting heart rate, weight, and age.” pg 2 [5] “In the aspect in which the wearable sensor 20 is equipped with a thermometer, the skin temperature may be measured using the thermometer, and the measurement result may be transmitted to the model via the communication unit 201 (see FIG. 5). However, instead of this, the temperature may be measured with a thermometer and input from the input unit 11.”). However, Uchiyama fails to disclose a plurality of temperature measurement sites or a PPG signal.
St. Pierre discloses a temperature measurement site on a body selected by a user, from a plurality of temperature measurement sites displayed on the user interface ([0082] “The user can continue selecting the thermometry location control 328b until the thermometry location control 328b indicates a location where the thermometer is located on the patient's body or until the thermometry location control 328b indicates that measurements are to be obtained in direct mode. For example, in some embodiments, the PMP device 200 accepts readings from a thermometer when the thermometer is located in the patient's mouth, in an adult patient's armpit, or in a pediatric patient's armpit.” [0086] “The patient type button 316b indicates a value of a patient type parameter associated with the current patient.”).
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 method of Uchiyama 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, 0086]).
While Uchiyama discloses measuring heart rate, combination of Uchiyama/St. Pierre has no mention of PPG or more specifically AC/DC signals, or an abnormally low temperature threshold.
Wang discloses:
measuring a photoplethysmogram (PPG) signal that comprises an alternating current (AC) signal and a direct current (DC) signal by emitting light onto a user and by detecting light scattered or reflected from the user (Wang: Fig. 4; “obtaining the AC component and DC component of the initial PPG signal;” 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.”).
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 combination of Uchiyama/St. Pierre to include AC/DC PPG signals and measurement of cutaneous blood flow as disclosed in Wang to 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]). However, the combination of Uchiyama/St. Pierre/Wang fails to disclose area under a curve of the AC signal.
The combination of Uchiyama/St. Pierre/Wang/Gelissen_045 discloses:
estimating cutaneous blood flow of the user based on an area under a curve of the AC signal of the PPG signal (Gelissen_045: [0004] “a PPG-based sensor. While the purpose of such a sensor is to obtain a measure of blood oxygen saturation, it also detects changes in blood volume in the skin;” [0089] “The PPG amplitude (AC amplitude) as well as DC values (area under the curve of the AC signal) varies depending on body site;” 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”).
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 combination of Uchiyama/St. Pierre/Wang to include area under the curve of the AC signal as disclosed in Gelissen_045 as a means to normalize the physiological signal to the particular body location where the PPG signal is measured for more accurate readings (Gelissen_045 [0089]).
The combination of Uchiyama/St. Pierre/Wang/Gelissen_045 further discloses:
estimating energy metabolism of the user based on a resting metabolic rate Mo, a difference between a resting heart rate HRo and a PPG-based heart rate HR obtained from the PPG signal, a difference between the resting metabolic rate Mo and a maximum work capacity (MWC), wherein the MWC is obtained based on the age and a lean body mass (LBM), and the LBM is obtained based on the weight and the height, and a difference between the resting heart rate HRo and a maximum heart rate (HRmax) that is obtained based on the age (Wang: pg 6 [5] “extracting the heart rate from the sample PPG signal;” Uchiyama: pg 3 [4] "The body temperature simulation using the two-node model described in the previous chapter requires four types of input: (1) user information such as weight, (2) initial body temperature, (3) metabolic rate, and (4) environmental conditions;” pg 4 [12] “the thermal calculation in the two-node model is delayed by two types of delay parameters β1 and β2. β1 controls the propagation speed of heat M generated by metabolism to take into account the initial drop in deep body temperature, and further delays the decrease in body temperature during a break. β1 is incorporated into the model as the size of the sliding window. The larger the β1, the lower the heat propagation rate due to metabolism. β2 represents a delay in the thermoregulatory response to an increase in body temperature;” pg 3 [6] “The total metabolic heat M in the model is estimated based on oxygen consumption. As shown by the equation (4), the metabolic fever is considered as the sum of resting metabolic fever (basal metabolism) M .sub.rest and metabolic fever M .sub.ex by exercise. Each metabolic fever [W] is calculated by equations (5) and (6). The terms 3.5 .Math. weight and (VO2−3.5) .Math. weight in these equations represent the resting state and oxygen consumption [ml / min] due to exercise, respectively." pg 3 [7] "VO2max is obtained from the user's maximum heart rate maxHR and resting heart rate restHR (formula (8)). Further, in order to estimate% VO2R from the heart rate, the current heart rate% HRR with respect to the reserve heart rate (how much it rises with respect to the maximum heart rate) is used to convert according to the equation (9). % HRR is calculated by the carbonnene method shown by Formula (10). The maximum heart rate is estimated based on the age of the user (formula (11)). By the above method, the metabolic fever M is estimated based on the user's heart rate, resting heart rate, weight, and age");
estimating a core body temperature of the user based on an equation expressed as: Tc = α x SBFa + β x EEb, wherein Tc, denotes the core body temperature, SBF denotes the cutaneous blood flow, EE denotes the energy metabolism, α denotes a first weight for the cutaneous blood flow based on heat generated from an external heat source, and β denotes a second weight for the energy metabolism based on an internally generated heat (Uchiyama: pg 4 [3] "In the outdoor environment, the skin receives strong heat energy due to solar radiation, and the skin temperature rises. However, the conventional two-node model does not consider the influence of solar heat. Here, as shown in FIG. 2, the measurement value of the pyranometer included in the environmental sensor 12 installed in the environment, the user's total skin area, and clothes are used as inputs, and the direct solar radiation heat qdn received by the user is estimated. Was incorporated into the heat balance calculation. qdn is obtained by the following equation (E)." pg 3 [8] "the energy loss W due to external work is obtained by multiplying the exercise metabolism by the coefficient Δeff as shown in the equation (12). Δeff is known for basic types of exercise such as walking, running, and cycling." pg 4 [12] "the thermal calculation in the two-node model is delayed by two types of delay parameters β1 and β2. β1 controls the propagation speed of heat M generated by metabolism to take into account the initial drop in deep body temperature, and further delays the decrease in body temperature during a break. β1 is incorporated into the model as the size of the sliding window. The larger the β1, the lower the heat propagation rate due to metabolism. β2 represents a delay in the thermoregulatory response to an increase in body temperature." pg 2 [8] "In the two-node model, the body temperature change from time t to t + 1 is determined based on the deep body temperature T .sub.core .sup.t at time .sup.t , the skin temperature T .sub.skin .sup.t [incorporating 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;” for skin temperature estimations], and the input value from the wearable sensor 20 obtained at time t. By calculating the heat exchange during this time, the deep body temperature T .sub.core .sup.t and the changes ΔT .sub.core .sup.t and ΔT .sub.skin .sup.t of the skin temperature T .sub.skin .sup.t at time t are obtained, respectively. Based on the obtained change amount, the body temperature at time t + 1 is calculated by the following equation (A).");
setting an abnormal body temperature range corresponding to the selected temperature measurement site, from among a plurality of abnormal body temperature ranges that are set differently for the plurality of temperature measurement sites (St. Pierre: [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 or whether the PMP device 200 is to obtain measurements of the patient's temperature in direct mode.” [0079] “A temperature alarm status area 328a is located at the right side of the temperature frame 314d. The temperature alarm status area 328a specifies an upper alarm limit and a lower alarm limit. The upper alarm limit and the lower alarm limit define a temperature alarm range. An alarm associated with the patient's temperature is active when the patient's temperature level is outside the temperature alarm range.” [0086] “by using the patient type button 316b to change the patient type parameter, the user can automatically change the alarm limits for the patient's physiological parameters. As described elsewhere in this document, the user can also manually set the alarm limits for physiological parameters.” Gelissen_045: [0089] “The PPG amplitude (AC amplitude) as well as DC values (area under the curve of the AC signal) varies depending on body site, which is why the normalization mentioned above is desired to compensate for this. The respiratory signal is for example normalized by the amplitude of the pulse signal. In this way, the baseline variation is expressed in relation to the magnitude of the pulse signal as seen in the PPG signal at that particular body location.”);
based on the estimated core body temperature being greater than or equal to a predetermined upper threshold of the abnormal body temperature range, control the display to output a high body temperature risk message along with a user guidance to lower the core body temperature and based on the estimated core body temperature being less than or equal to a predetermined lower threshold of the abnormal body temperature range, control the display to output a low body temperature risk message along with a user guidance to increase the core body temperature (Uchiyama: pg 5 [14] “The warning processing unit 105 outputs a warning (display, warning sound, guide, etc.) and outputs a warning (eg, display, warning sound, guide, etc.) during the exercise after the warm-up is completed, for example, when the deep body temperature being calculated rises to the threshold value for determining heat stroke. To inform. The threshold value may be a fixed value, or may be set in consideration of a delay according to a set delay parameter, or may be set in consideration of a change gradient of the deep body temperature. Good.” pg 6 [2] “On the other hand, if the deep body temperature exceeds the threshold, a warning is issued (step S21). The monitoring process continues in the same manner when the estimated deep body temperature is removed from the warning state (decreased) due to a break after the warning and returns to the exercise again (No in steps S15 to S19).” St. Pierre: [0079] “The upper alarm limit and the lower alarm limit define a temperature alarm range. An alarm associated with the patient's temperature is active when the patient's temperature level is outside the temperature alarm range.”).
Regarding claim 11, the combination of Uchiyama/St. Pierre/Wang/Gelissen_045 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] “obtain the initial PPG signal corresponding to different environment temperature values according to the above steps; to determine the corresponding PI data” 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;” Uchiyama: pg 2 [8] “the initial deep body temperature T .sub.core .sup.0 and the initial skin temperature T .sub.skin .sup.0 are obtained;” pg 3 [6] “The total metabolic heat M in the model is estimated based on oxygen consumption. As shown by the equation (4), the metabolic fever is considered as the sum of resting metabolic fever (basal metabolism) M .sub.rest and metabolic fever M .sub.ex by exercise. Each metabolic fever [W] is calculated by equations (5) and (6).”),
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 (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;” Uchiyama: pg 4 [3] "In the outdoor environment, the skin receives strong heat energy due to solar radiation, and the skin temperature rises. However, the conventional two-node model does not consider the influence of solar heat. Here, as shown in FIG. 2, the measurement value of the pyranometer included in the environmental sensor 12 installed in the environment, the user's total skin area, and clothes are used as inputs, and the direct solar radiation heat qdn received by the user is estimated. Was incorporated into the heat balance calculation. qdn is obtained by the following equation (E)." pg 3 [8] "the energy loss W due to external work is obtained by multiplying the exercise metabolism by the coefficient Δeff as shown in the equation (12). Δeff is known for basic types of exercise such as walking, running, and cycling." pg 4 [12] "the thermal calculation in the two-node model is delayed by two types of delay parameters β1 and β2. β1 controls the propagation speed of heat M generated by metabolism to take into account the initial drop in deep body temperature, and further delays the decrease in body temperature during a break. β1 is incorporated into the model as the size of the sliding window. The larger the β1, the lower the heat propagation rate due to metabolism. β2 represents a delay in the thermoregulatory response to an increase in body temperature." pg 2 [8] "In the two-node model, the body temperature change from time t to t + 1 is determined based on the deep body temperature T .sub.core .sup.t at time .sup.t , the skin temperature T .sub.skin .sup.t [incorporating 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;” for skin temperature estimations], and the input value from the wearable sensor 20 obtained at time t. By calculating the heat exchange during this time, the deep body temperature T .sub.core .sup.t and the changes ΔT .sub.core .sup.t and ΔT .sub.skin .sup.t of the skin temperature T .sub.skin .sup.t at time t are obtained, respectively. Based on the obtained change amount, the body temperature at time t + 1 is calculated by the following equation (A).").
Regarding claim 13, the combination of Uchiyama/St. Pierre/Wang/Gelissen_045 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.” Gelissen_045: [00899] “area under the curve of the AC signal”).
Regarding claim 18, the combination of Uchiyama/St. Pierre/Wang/Gelissen_045 discloses the method of claim 10, wherein the estimating of the core body temperature of the user comprises estimating the core body temperature of the user based further on a user's motion while the PPG signal is measured (Uchiyama: pg 3 [8] “the energy loss W due to external work is obtained by multiplying the exercise metabolism by the coefficient Δeff as shown in the equation (12). Δeff is known for basic types of exercise such as walking, running, and cycling. Therefore, Δeff = 0.40 (during walking), Δeff = 0.44 to 0.54 (during running), and Δeff = 0.23 (during bicycle exercise), respectively. Since energy efficiency changes depending on the speed when traveling, a value of 0.44 to 0.54 is given according to the speed of the user.” 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.”).
Claim(s) 8 and 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Uchiyama (WO 2017213011 A1) in view of St. Pierre (US 20110071420 A1), Wang (CN113545757A), and Gelissen (US 20190209045 A1), and in further view of Gelissen (US 20170360299 A1).
Regarding claim 8, the combination of Uchiyama/St. Pierre/Wang/Gelissen_045 discloses the apparatus of claim 1, wherein in response to the estimated core body temperature falling within the set abnormal body 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.” Uchiyama: pg 5 [14] “The warning processing unit 105 outputs a warning (display, warning sound, guide, etc.) and outputs a warning (eg, display, warning sound, guide, etc.) during the exercise after the warm-up is completed, for example, when the deep body temperature being calculated rises to the threshold value for determining heat stroke.” St. Pierre: [0079] “The upper alarm limit and the lower alarm limit define a temperature alarm range. An alarm associated with the patient's temperature is active when the patient's temperature level is outside the temperature alarm range.”). However, the combination of Uchiyama/St. Pierre/Wang/Gelissen_045 fails to disclose a recommendation to stop outdoor activities.
Gelissen_299 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_299 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 Uchiyama/St. Pierre/Wang/Gelissen_045 to include recommending stopping outdoor activities as disclosed in Gelissen_299 to remedy an issue that the user is facing and improve the user’s calculated health parameter (Gelissen_299 [0069 and 0143]).
Regarding claim 17, the combination of Uchiyama/St. Pierre/Wang/Gelissen_045 discloses the method of claim 10, further comprising, in response to the core body temperature falling within the set abnormal body temperature 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.” Uchiyama: pg 5 [14] “The warning processing unit 105 outputs a warning (display, warning sound, guide, etc.) and outputs a warning (eg, display, warning sound, guide, etc.) during the exercise after the warm-up is completed, for example, when the deep body temperature being calculated rises to the threshold value for determining heat stroke.” St. Pierre: [0079] “The upper alarm limit and the lower alarm limit define a temperature alarm range. An alarm associated with the patient's temperature is active when the patient's temperature level is outside the temperature alarm range.”). However, the combination of Uchiyama/St. Pierre/Wang/Gelissen_045 fails to disclose a recommendation to stop outdoor activities.
Gelissen_299 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 Uchiyama/St. Pierre/Wang/Gelissen_045 to include recommending stopping outdoor activities as disclosed in Gelissen_299 to remedy an issue that the user is facing and improve the user’s calculated health parameter (Gelissen_299 [0069 and 0143]).
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.
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/M.H./Examiner, Art Unit 3791
/DEVIN B HENSON/Primary Examiner, Art Unit 3791
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