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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 11/17/2025 has been entered.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 1-4, 6-9, 11-14, and 16-19 is/are rejected under 35 U.S.C. 103 as being unpatentable over US2015/0265159 to Lane et al. “Lane”, in view of US20180242850 to Ellis et al. “Ellis”, and further in view of US2014/0149065 to Pompei et al. “Pompei”.
Regarding claim 1, Lane discloses a method (method for temperature detection, Paragraph 0001) comprising:
receiving a thermal image (temperature device 10 with an imaging device 16, Fig. 1, Paragraph 0017, wherein the imaging device is used to collect thermal image of the patient 14, Paragraph 0024);
processing the thermal image (controller includes an image processor and/or image processing software, Paragraph 0025) to detect a person's face (Paragraph 0027, image processor and other components of the controller determines a distance between different locations of the face, or other dimensions of the nose, eye, cheek, and chin; inferred that to determine the distances between different locations of the face, the face must be detected in the image; also see Paragraph 0053, “the imaging device 16 may be utilized to capture one or more images of the face of the patient…the image processors are able to identify one or more portions of the face...”); and
detecting a characteristic associated with the person based on at least one feature of the person's face (Paragraph 0027, determine a distance between a first location 36 a on the portion 34 of the face of the patient 14 and a second location 36 b on the portion 34, a distance between at least one of the first and second locations 36 a, 36 b and a third location 36 c on the face of the patient 14, a length, width, height, and/or other dimension related to an ear (such as the height H shown in FIG. 1), nose, eye, cheek, chin, and/or other body part of the patient 14, and/or other like attributes. One or more such attributes may be used to determine, for example, the age, gender, ethnicity, and/or other characteristics of the patient 14; wherein the age, gender, ethnicity would read on the characteristic associated with the person based on at least one feature of the person’s face),
extracting a temperature associated with the person’s face from the thermal image (thermal image provides temperature profile of the patient, Paragraph 0026, wherein the thermal image is of the measurement site, Paragraph 0024, i.e. the face, see Fig. 1), and
detecting an elevated body temperature condition (the determined temperature is used to determine an emerging fever, Paragraph 0020, which would read on elevated body temperature condition).
Lane additionally discloses selecting an operating mode may that includes selecting a set of temperature determination algorithms for use in core temperature determinations associated with the patient 14 (Paragraph 0028), wherein the algorithms are selected based on the one or more detected characteristics (Paragraph 0059, utilize one or more temperature determination algorithms tailored towards adults or pediatric patients, which would read on age, or also based on patient gender and/or ethnicity), wherein the algorithms could be a neural network, lookup table, or any other algorithm and/or components (Paragraph 0061).
However, Lane does not disclose wherein selecting the temperature determination algorithms includes selecting a circadian rhythm model based on the detected characteristic.
Ellis teaches in a similar field of endeavor, of determining core body temperature from collected temperature data from a temperature monitoring device and characterizing a user condition (e.g., fever) (Abstract).
Ellis teaches selecting a circadian rhythm model based on the a characteristic of the patient and determining an expected body temperature using the circadian rhythm model (Paragraph 0064, using reference profiles indicative of circadian affect on core body temperature, such as being lower in the hours before waking, higher in the later afternoon and/or early evening and using the profiles to normalize the core body temperatures by taking into account of the circadian affects as shown in Fig. 9; wherein the circadian rhythm influences are different for different profiles such as age, wherein for example a teenager can experience expected core body temperature fluctuations two hours later than adults, due to the teenager having a different circadian fluctuation than an adult, Paragraph 0064; using the profile specific to the patient, such as specific to the patients age range/group, i.e. teens, would read on selecting the circadian rhythm model based on a characteristic of the patient.
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have modified Lane’s invention, wherein selecting the temperature determination algorithms includes selecting a circadian rhythm model based on the detected characteristic, as taught by Ellis, in order to improve the suitability of the physiological metric for determining a user’s condition and avoiding false negatives or false positives (Ellis, Paragraph 0064).
However, the modifications of Lane and Ellis do not disclose determining an expected body temperature using the circadian rhythm model, and comparing the extracted temperature with the expected body temperature.
Pompei teaches in a similar field of endeavor of detecting a fever (Title and Abstract). Pompei teaches determining an expected body temperature using the circadian rhythm model (Paragraph 0053, using historical data of a plurality of individuals such as shown in Fig. 2, to determine a normal expected temperature as indicated by the global maximum, and a local maximum that would indicate a body temperature with a fever; wherein the historical data can be adjusted by a circadian filter, such as each hourly time window, to obtain a circadian filtered distribution, Paragraphs 0062; wherein the historical data can be different population sets, such as age group and sex, Paragraph 0068).
Pompei additionally teaches comparing the extracted temperature with the expected body temperature (Paragraph 0058, comparing the measured body temperature that is corrected, with the corresponding expected temperature that has been adjusted to an associated mean temperature, which is weighted based on the circadian cycle, Paragraph 0057, wherein the correspondence is based on the time of measurement, Paragraph 0058; As taught in Paragraph 0058, if a patient has normal temperature, the corrected temperature will be at the mean. However, in a patient who has a fever, the corrected temperature will be above the mean to indicate fever. This provides a time-dependent indication of fever).
Therefore, It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have modified the system as described by Lane and Pompei, wherein the method includes determining an expected body temperature using the circadian rhythm model, and comparing the extracted temperature with the expected body temperature, as taught by Pompei, in order to provide a time-dependent indication of fever (Paragraph 0058) that adjusts the temperature measurements to establish accurate detection of fever (Paragraph 0006), and take into account the variations of body temperature during the day based on the circadian cycle (Paragraph 0004).
Regarding claim 2, the modifications of Lane, Ellis, and Pompei disclose all the features of claim 1 above.
Pompei discloses receiving a time (Paragraph 0037, receive and label (time/date stamp) the temperature measurements) and using the time to identify a phase of the circadian rhythm model (using the time of measurement to determine the corresponding point on the circadian cycle plot, Paragraph 0058, Fig. 3).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have modified the system as described by Lane and Pompei, wherein the method includes receiving a time and using the time to identify a phase of the circadian rhythm model, as further taught by Pompei, in order to adjusts the temperature measurements based on the circadian cycle, Paragraph 0057-58) to establish accurate detection of fever (Paragraph 0006).
However, the modifications of Lane, Ellis, and Pompei do not explicitly disclose wherein the time is associated with the thermal image.
However, It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have modified the system as described by Lane and Ellis, wherein the time is associated with the thermal image since Pompei teaches that the time is associated with the temperature measurement (Pompei, Paragraph 0037) and Lane teaches the temperature measurements are obtained from the thermal images (Lane, Paragraph 0024).
Regarding claim 3 and 4, the modifications of Lane, Ellis, and Pompei disclose all the features of claim 2 above.
Pompei teaches selecting the expected body temperature corresponding to the phase from a plurality of expected body temperatures corresponding to a plurality of phases of the circadian rhythm model (see Fig. 3, determining the expected temperature, such as Te, corresponding to the measured time point, amongst the plurality of expected temperatures, located at different phases of the circadian cycle plot of Fig. 3.; See also Paragraphs 0056-0058). Pompei further discloses adjusting the expected body temperature in response to the identified phase (Paragraph 0058, adjusting the expected temperature Te, to the mean temperature TM corresponding to the measured time point).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have modified the system as described by Lane, Ellis, and Pompei, wherein the method includes selecting the expected body temperature corresponding to the phase from a plurality of expected body temperatures corresponding to a plurality of phases of the circadian rhythm model, and adjusting the expected body temperature in response to the identified phase, as taught by Pompei, in order to take into the account the time of day and the effects of the circadian cycle according to time, on the temperature (Paragraph 0056).
Regarding claim 6, the modifications of Lane, Ellis, and Pompei disclose all the features of claim 1 above.
As disclosed in the claim 1 rejection above, Lane discloses obtaining a thermal image of the face with a temperature gradient/profile of the patient (Paragraph 0026), and Pompei teaches comparing the combined extracted temperature with the expected body temperature to detect the elevated body temperature condition (comparing the extracted temperature with the expected body temperature (comparing the measured body temperature that is corrected, with the corresponding expected temperature that has been adjusted to an associated mean temperature, wherein the correspondence is based on the time of measurement, Paragraph 0058. As taught in Paragraph 0058, if a patient has normal temperature, the corrected temperature will be at the mean. However, in a patient who has a fever, the corrected temperature will be above the mean to indicate fever. This provides a time-dependent indication of fever).
Lane further discloses wherein the extracted temperature comprises a first extracted temperature associated with a first location of the person's face (first temperature corresponding to the first location 36a on the portion 34 of the face of the patient, Paragraph 0060) from the thermal image;
the method further comprises:
extracting a second temperature and a third temperature associated with a second location and a third location of the person's face (second temperature corresponding to the second location 36 b on the portion 34 of the face of the patient 14, Paragraph 0060; location 36 c, Paragraph 0028, and Lane discloses in Paragraph 0017, determining respective temperatures of locations 36 a . . . 36 n (collectively, “locations 36”) on the portion 34 of the face and/or any of the other measurement sites described herein), respectively, from the thermal image; and
wherein the first, second, and third extracted temperatures comprise at least a temperature of an inner canthus of the person, and a temperature of an oral region of the person (Paragraph 0008, determining, with the device, a temperature from an inner-canthal region of the patient; Paragraph 0016, “ an external surface of the patient's skin, such as the face, forehead, temple, ears (such as the outer or inner ear), eyes, nose, lips, neck, wrist, chin, open mouth, and/or other like skin surfaces”; wherein the measurement sites can be Paragraph 0060, the temperature measurement can be from the right or left inner-canthal region of the patient).
However, Lane does not disclose the plurality of temperatures are extracted from the thermal image.
However, Lane does disclose obtaining temperature measurements at the left and right inner canthal regions using sensors 18 that are also located on the temperature measurement device (Paragraph 0060) wherein sensor 18 is an infrared sensor (Paragraph 0030). Lane also discloses generating a temperature profile from the thermal image of the patient (Paragraph 0026), wherein the thermal image is of the measurement site, which is the face (See Fig. 1). Lane additionally discloses that sensor 16, for obtaining the thermal image is also an infrared sensor (Paragraph 0024).
Therefore, It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have modified the system as described by Lane, Ellis, and Pompei, wherein the measured temperature is extracted from the thermal image with the thermal profile of the patient, since Lane teaches that both the imaging sensor 16 and the sensor 18 are both infrared sensors, and both are used to obtain temperature data of the patient (temperature profile extracted from the thermal image obtained using sensor 16, and direct temperature measurements obtained using sensor 18). It would be obvious that the temperature at specific regions within the image can be extracted from the thermal image with the temperature profile, and that these regions can be the right and/or left inner canthal regions.
However, Lane does not disclose calculating a combined extracted temperature, wherein calculating the combined extracted temperature comprises determining a median of the first, second, and third extracted temperatures.
Ellis teaches (Paragraph 0026) wherein the collected temperature data from the temperature sensors (Fig. 1A, step S110) is an aggregate temperature data (e.g., average temperature, median temperature), wherein the temperature data is from a plurality of heat flux channels associated with different measurement sites (e.g. at different exterior skin regions). Therefore, the aggregate temperature data, such as the median temperature of the collected temperature data, would read on the combined extracted temperature as the median of the plurality of temperatures.
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have modified the system as described by Lane, Ellis, and Pompei, wherein the method includes calculating a combined extracted temperature, wherein calculating the combined extracted temperature comprises determining a median of the first, second, and third extracted temperatures of Lane, as taught by Ellis, in order to account for variability and perform adjustments such as normalization (Ellis, Paragraph 0026).
Regarding claim 7, the modifications of Lane, Ellis, and Pompei disclose all the features of claim 6 above.
Lane disclose generating a notification of the elevated body temperature condition and/or the fever condition (Paragraph 0044, generating an audible and/or visible alarm by the controller 30 when a temperature determined by the device 10 meets or exceeds a threshold temperature; wherein the temperature measurement device is used in the context of indicating emerging fever, Paragraph 0019).
Regarding claims 8 and 9, the modifications of Lane, Ellis, and Pompei disclose all the features of claim 1 above.
Lane discloses processing the thermal image and visible light image to detect the characteristic (Paragraph 0024, the imaging device 16 is a digital camera that can obtain images, which would read on visible light images, and also device 16 can in additional collect thermal radiation to form thermal images; Paragraph 0027, wherein the one or more images, which the examiner interprets as more and would read on the digital camera image and thermal image, are used to determine a distance between different locations of the face), wherein the characteristic is a first characteristic comprising an age associated with the person, a second characteristic comprising a gender associated with the person (Paragraph 0027, image processor and other components of the controller determines a distance between different locations of the face, or other dimensions of the nose, eye, cheek, and chin, which is further used to determine the age, gender, ethnicity, and/or other characteristics of the patient; the examiner interprets Paragraph 0027 using the “and” condition, which would read on determining both an age and gender associated with the determined distance).
Regarding claim 11, Lane discloses a system (system for temperature detection, Paragraph 0001) comprising:
a thermal imager (temperature device 10 with an imaging device 16, Fig. 1, Paragraph 0017, wherein the imaging device is used to collect thermal image of the patient 14, Paragraph 0024); and
a logic device (controller 30, Fig. 1, Paragraph 0024) configured to:
operate the thermal imager to capture a thermal image (Paragraph 0049, controller 30 operably connected to imaging device 16, and configured to control the operation of such components, wherein the operation of the imaging device is to collect thermal images, Paragraph 0024),
process the thermal image (controller includes an image processor and/or image processing software, Paragraph 0025) to detect a person’s face and a characteristic associated with the person (Paragraph 0027, image processor and other components of the controller determines a distance between different locations of the face, or other dimensions of the nose, eye, cheek, and chin; inferred that to determine the distances between different locations of the face, the face must be detected in the image; also see Paragraph 0053, “the imaging device 16 may be utilized to capture one or more images of the face of the patient…the image processors are able to identify one or more portions of the face...”); and
detecting a characteristic associated with the person based on at least one feature of the person's face (Paragraph 0027, determine a distance between a first location 36 a on the portion 34 of the face of the patient 14 and a second location 36 b on the portion 34, a distance between at least one of the first and second locations 36 a, 36 b and a third location 36 c on the face of the patient 14, a length, width, height, and/or other dimension related to an ear (such as the height H shown in FIG. 1), nose, eye, cheek, chin, and/or other body part of the patient 14, and/or other like attributes. One or more such attributes may be used to determine, for example, the age, gender, ethnicity, and/or other characteristics of the patient 14; wherein the age, gender, ethnicity would read on the characteristic associated with the person based on at least one feature of the person’s face),
extract a temperature associated with the person’s face from the thermal image (thermal image provides temperature profile of the patient, Paragraph 0026, wherein the thermal image is of the measurement site, Paragraph 0024, i.e. the face, see Fig. 1), and
detect an elevated body temperature condition (the determined temperature is used to determine an emerging fever, Paragraph 0020, which would read on elevated body temperature condition).
Lane additionally discloses the logic device is configured to select an operating mode may that includes selecting a set of temperature determination algorithms for use in core temperature determinations associated with the patient 14 (Paragraph 0028), wherein the algorithms are selected based on the one or more detected characteristics (Paragraph 0059, utilize one or more temperature determination algorithms tailored towards adults or pediatric patients, which would read on age, or also based on patient gender and/or ethnicity), wherein the algorithms could be a neural network, lookup table, or any other algorithm and/or components (Paragraph 0061).
However, Lane does not disclose wherein selecting the temperature determination algorithms includes selecting a circadian rhythm model based on the detected characteristic.
Ellis teaches in a similar field of endeavor, of determining core body temperature from collected temperature data from a temperature monitoring device and characterizing a user condition (e.g., fever) (Abstract).
Ellis teaches selecting a circadian rhythm model based on the a characteristic of the patient and determining a body temperature using the circadian rhythm model (Paragraph 0064, using reference profiles indicative of circadian affect on core body temperature, such as being lower in the hours before waking, higher in the later afternoon and/or early evening and using the profiles to normalize the core body temperatures by taking into account of the circadian affects as shown in Fig. 9; wherein the circadian rhythm influences are different for different profiles such as age, wherein for example a teenager can experience expected core body temperature fluctuations two hours later than adults, due to the teenager having a different circadian fluctuation than an adult, Paragraph 0064; using the profile specific to the patient, such as specific to the patients age range/group, i.e. teens, would read on selecting the circadian rhythm model based on a characteristic of the patient.
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have modified Lane’s invention, wherein selecting the temperature determination algorithms includes selecting a circadian rhythm model based on the detected characteristic, as taught by Ellis, in order to improve the suitability of the physiological metric for determining a user’s condition and avoiding false negatives or false positives (Ellis, Paragraph 0064).
However, the modifications of Lane and Ellis do not disclose determining an expected body temperature using the circadian rhythm model, and comparing the extracted temperature with the expected body temperature.
Pompei teaches in a similar field of endeavor of detecting a fever (Title and Abstract). Pompei teaches determining an expected body temperature using the circadian rhythm model (Paragraph 0053, using historical data of a plurality of individuals such as shown in Fig. 2, to determine a normal expected temperature as indicated by the global maximum, and a local maximum that would indicate a body temperature with a fever; wherein the historical data can be adjusted by a circadian filter, such as each hourly time window, to obtain a circadian filtered distribution, Paragraphs 0062; wherein the historical data can be different population sets, such as age group and sex, Paragraph 0068).
Pompei additionally teaches comparing the extracted temperature with the expected body temperature (Paragraph 0058, comparing the measured body temperature that is corrected, with the corresponding expected temperature that has been adjusted to an associated mean temperature, which is weighted based on the circadian cycle, Paragraph 0057, wherein the correspondence is based on the time of measurement, Paragraph 0058; As taught in Paragraph 0058, if a patient has normal temperature, the corrected temperature will be at the mean. However, in a patient who has a fever, the corrected temperature will be above the mean to indicate fever. This provides a time-dependent indication of fever).
Therefore, It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have modified the system as described by Lane and Ellis, wherein the logic device is further configured to determine an expected body temperature using the circadian rhythm model, and compare the extracted temperature with the expected body temperature, as taught by Pompei, in order to provide a time-dependent indication of fever (Paragraph 0058) that adjusts the temperature measurements to establish accurate detection of fever (Paragraph 0006), and take into account the variations of body temperature during the day based on the circadian cycle (Paragraph 0004).
Regarding claim 12, the modifications of Lane, Ellis, and Pompei disclose all the all the features of claim 11 above.
Pompei discloses wherein the logic device is configured to receive a time (Paragraph 0037, receive and label (time/date stamp) the temperature measurements) and use the time to identify a phase of the circadian rhythm model (using the time of measurement to determine the corresponding point on the circadian cycle plot, Paragraph 0058, Fig. 3).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have modified the system as described by Lane, Ellis, and Pompei, wherein the logic device is configured to receive a time and use the time to identify a phase of the circadian rhythm model, as further taught by Pompei, in order to adjusts the temperature measurements based on the circadian cycle, Paragraph 0057-58) to establish accurate detection of fever (Paragraph 0006)
However, the modifications of Lane, Ellis, and Pompei do not explicitly disclose wherein the time is associated with the thermal image.
However, It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have modified the system as described by Lane and Pompei, wherein the time is associated with the thermal image since Pompei teaches that the time is associated with the temperature measurement (Pompei, Paragraph 0037) and Lane teaches the temperature measurements are obtained from the thermal images (Lane, Paragraph 0024).
Regarding claim 13 and 14, the modifications of Lane, Ellis, and Pompei disclose all the features of claim 12 above.
Pompei teaches wherein the logic device (processor, Paragraph 0012) is configured to select the expected body temperature corresponding to the phase from a plurality of expected body temperatures corresponding to a plurality of phases of the circadian rhythm model (see Fig. 3, determining the expected temperature, such as Te, corresponding to the measured time point, amongst the plurality of expected temperatures, located at different phases of the circadian cycle plot of Fig. 3.; See also Paragraphs 0056-0058). Pompei further discloses adjusting the expected body temperature in response to the identified phase (Paragraph 0058, adjusting the expected temperature Te, to the mean temperature TM corresponding to the measured time point).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have modified the system as described by Lane, Ellis, and Pompei, wherein the logic device is configured to select the expected body temperature corresponding to the phase from a plurality of expected body temperatures corresponding to a plurality of phases of the circadian rhythm model, and adjust the expected body temperature in response to the identified phase, as taught by Pompei, in order to take into the account the time of day and the effects of the circadian cycle according to time, on the temperature (Paragraph 0056).
Regarding claim 16, the modifications of Lane, Ellis, and Pompei disclose all the features of claim 11 above.
As disclosed in the claim 11 rejection above, Lane discloses obtaining a thermal image of the face with a temperature gradient/profile of the patient (Paragraph 0026), and Pompei teaches comparing the combined extracted temperature with the expected body temperature to detect the elevated body temperature condition (comparing the extracted temperature with the expected body temperature (comparing the measured body temperature that is corrected, with the corresponding expected temperature that has been adjusted to an associated mean temperature, wherein the correspondence is based on the time of measurement, Paragraph 0058. As taught in Paragraph 0058, if a patient has normal temperature, the corrected temperature will be at the mean. However, in a patient who has a fever, the corrected temperature will be above the mean to indicate fever. This provides a time-dependent indication of fever).
Lane further discloses wherein the extracted temperature comprises a first extracted temperature associated with a first location of the person's face (first temperature corresponding to the first location 36a on the portion 34 of the face of the patient, Paragraph 0060) from the thermal image;
wherein the logic device is configured to:
extract a second temperature and a third temperature associated with a second location and a third location of the person's face (second temperature corresponding to the second location 36 b on the portion 34 of the face of the patient 14, Paragraph 0060; location 36 c, Paragraph 0028, and Lane discloses in Paragraph 0017, determining respective temperatures of locations 36 a . . . 36 n (collectively, “locations 36”) on the portion 34 of the face and/or any of the other measurement sites described herein), respectively, from the thermal image; and
wherein the first, second, and third extracted temperatures comprise at least a temperature of an inner canthus of the person, and a temperature of an oral region of the person (Paragraph 0008, determining, with the device, a temperature from an inner-canthal region of the patient; Paragraph 0016, “ an external surface of the patient's skin, such as the face, forehead, temple, ears (such as the outer or inner ear), eyes, nose, lips, neck, wrist, chin, open mouth, and/or other like skin surfaces”; wherein the measurement sites can be Paragraph 0060, the temperature measurement can be from the right or left inner-canthal region of the patient).
However, Lane does not disclose the plurality of temperatures are extracted from the thermal image.
However, Lane does disclose obtaining temperature measurements at the left and right inner canthal regions using sensors 18 that are also located on the temperature measurement device (Paragraph 0060) wherein sensor 18 is an infrared sensor (Paragraph 0030). Lane also discloses generating a temperature profile from the thermal image of the patient (Paragraph 0026), wherein the thermal image is of the measurement site, which is the face (See Fig. 1). Lane additionally discloses that sensor 16, for obtaining the thermal image is also an infrared sensor (Paragraph 0024).
Therefore, It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have modified the system as described by Lane, Ellis, and Pompei, wherein the measured temperature is extracted from the thermal image with the thermal profile of the patient, since Lane teaches that both the imaging sensor 16 and the sensor 18 are both infrared sensors, and both are used to obtain temperature data of the patient (temperature profile extracted from the thermal image obtained using sensor 16, and direct temperature measurements obtained using sensor 18). It would be obvious that the temperature at specific regions within the image can be extracted from the thermal image with the temperature profile, and that these regions can be the right and/or left inner canthal regions.
However, Lane does not disclose calculating a combined extracted temperature, wherein calculating the combined extracted temperature comprises determining a median of the first, second, and third extracted temperatures.
Ellis teaches (Paragraph 0026) wherein the collected temperature data from the temperature sensors (Fig. 1A, step S110) is an aggregate temperature data (e.g., average temperature, median temperature), wherein the temperature data is from a plurality of heat flux channels associated with different measurement sites (e.g. at different exterior skin regions). Therefore, the aggregate temperature data, such as the median temperature of the collected temperature data, would read on the combined extracted temperature as the median of the plurality of temperatures.
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have modified the system as described by Lane, Ellis, and Pompei, wherein the logic device is configured to calculate a combined extracted temperature, wherein calculating the combined extracted temperature comprises determining a median of the first, second, and third extracted temperatures of Lane, as taught by Ellis, in order to account for variability and perform adjustments such as normalization (Ellis, Paragraph 0026).
Regarding claim 17, the modifications of Lane, Ellis, and Pompei disclose all the features of claim 16 above.
Lane disclose generating a notification of the elevated body temperature condition and/or the fever condition (Paragraph 0044, generating an audible and/or visible alarm by the controller 30 when a temperature determined by the device 10 meets or exceeds a threshold temperature; wherein the temperature measurement device is used in the context of indicating emerging fever, Paragraph 0019).
Regarding claims 18 and 19, the modifications of Lane, Ellis, and Pompei disclose all the features of claim 11 above.
Lane discloses wherein the logic device is configured to process the thermal image and visible light image to detect the characteristic (Paragraph 0024, the imaging device 16 is a digital camera that can obtain images, which would read on visible light images, and also device 16 can in additional collect thermal radiation to form thermal images; Paragraph 0027, wherein the one or more images, which the examiner interprets as more and would read on the digital camera image and thermal image, are used to determine a distance between different locations of the face), wherein the characteristic is a first characteristic comprising an age associated with the person, a second characteristic comprising a gender associated with the person (Paragraph 0027, image processor and other components of the controller determines a distance between different locations of the face, or other dimensions of the nose, eye, cheek, and chin, which is further used to determine the age, gender, ethnicity, and/or other characteristics of the patient; the examiner interprets Paragraph 0027 using the “and” condition, which would read on determining both an age and gender associated with the determined distance).
Claim(s) 5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lane, in view of Ellis, and further in view of Pompei, as applied to claim 1 above, and further in view of US2017/0238868 to Kenyon et al. “Kenyon”.
Regarding claim 5, the modifications of Lane, Ellis, and Pompei disclose all the features of claim 1 above.
As disclosed in the claim 1 rejection above, Ellis teaches wherein the circadian rhythm model corresponds to a sub-class associated with the characteristic (Paragraph 0064, using reference profiles indicative of circadian affect specific to a patient’s age range/group).
However, the modification of Lane, Ellis, and Pompei do not disclose updating the circadian rhythm model corresponding to the sub-class using the extracted temperature to improve accuracy of the circadian rhythm model.
Kenyon teaches a generalized default estimation of circadian rhythm derived from a sample of a general population of people, and over time adjusts the generalized default estimation of circadian rhythm using the measurements of the individual, wherein the measurements include skin temperature (Paragraph 0032). Kenyon teaches by adjusting the generalized default estimation using the individual's measurements, the estimation/model would become more of the individual's actual circadian rhythm (Paragraph 0032). This reads on the claimed updating the circadian rhythm model corresponding to the sub-class using the extracted temperature.
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have modified the system as described by Lane, Ellis, and Pompei, wherein the method includes updating the circadian rhythm model corresponding to the sub-class using the extracted temperature, as taught by Kenyon, in order to adjust the estimation/model to resemble more of the individual's circadian rhythm (Kenyon, Paragraph 0032). By adjusting the estimation/model to be more of the individual's circadian rhythm, it would be obvious that the accuracy of the estimation/model would improve for the individual.
Claim(s) 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lane, in view of Ellis, further in view of Pompei, as applied to claim 1 above, further in view of US2018/0303397 to Krupa et al. “Krupa”, further in view of US2012/0289850 to Xu et al. “Xu”, and further in view of US2011/0205367 to Brown et al. “Brown”.
Regarding claim 10, the modifications of Lane, Ellis, and Pompei disclose all the features of claim 1 above.
Lane discloses wherein the method is performed by a portable thermal camera (temperature measurement device 10 is a hand-held device, Paragraph 0020, with an imaging device 16, that can obtain thermal image of the patient, Paragraph 0024, and also visible light images, Paragraph 0024, i.e. images from a digital camera);
the processing is performed by a neural network (controller 30 selects a neural network, Paragraph 0027 for use in determination of the temperature); and
wherein the temperature is associated with an inner canthus of the person’s face (Paragraph 0008, determining, with the device, a temperature from an inner-canthal region of the patient; Paragraph 0060, the temperature measurement can be from the right or left inner-canthal region of the patient).
However, Lane does not disclose wherein the measured temperatures are extracted from the thermal image.
However, Lane does disclose obtaining temperature measurements using sensors 18 that are also located on the temperature measurement device (Paragraph 0060) wherein sensor 18 is an infrared sensor (Paragraph 0030). Lane also discloses generating a temperature profile from the thermal image of the patient (Paragraph 0026), wherein the thermal image is of the measurement site, which is the face (See Fig. 1). Lane additionally discloses that sensor 16, for obtaining the thermal image is also an infrared sensor (Paragraph 0024).
Therefore, It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have modified the system as described by Lane, Ellis, and Pompei, wherein the measured temperatures are extracted from the thermal image with the thermal profile of the patient, since Lane teaches that both the imaging sensor 16 and the sensor 18 are both infrared sensors, and both are used to obtain temperature data of the patient (temperature profile extracted from the thermal image obtained using sensor 16, and direct temperature measurements obtained using sensor 18). It would be obvious that the temperature at specific regions within the image can be extracted from the thermal image with the temperature profile.
However, the modifications of Lane, Ellis, and Pompei do not disclose wherein the neural network is configured to process the images to detect the person’s face and the characteristic and includes training the neural network to detect the face and the characteristic.
Krupa teaches wherein the neural network (Paragraphs 0080, 0120) is configured to process the images to detect the person’s face and the characteristic (Paragraph 0120, deep learning accomplished using a convolution neural network for facial recognition and analysis tasks, where the input layer receives image data, such as from a thermal imager, Paragraphs 0048, 0100; and the analysis include facial features, Paragraphs 0101-0103, used to determine demographic data such as gender and age, Paragraph 0101), and training the neural network to detect the face and the characteristic (training using image samples, Paragraphs 0076, 0106, to detect the face and facial features, Paragraph 0107, and to determine demographic data such as age and gender, Paragraphs 0076, 0102).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have modified the system as described by Lane, Ellis, and Pompei, wherein the neural network is configured to process the images to detect the person’s face and the characteristic and include training the neural network to detect the face and the characteristic, as taught by Krupa, in order to perform facial recognition, facial feature determination, Paragraph 0120, and classifying the results by demographic, Paragraph 0112. Further, the use of a neural network is a simple substitution of one known image processing algorithm for facial detection and facial feature extraction, such as the one used by Lane, for another, such as the neural network used by Krupa, to obtain predictable results, i.e. detecting the face in images, and facial feature extraction. (See MPEP 2143).
However, the modifications of Lane, Ellis, Pompei, and Krupa do not disclose stabilizing the thermal image.
Xu teaches a similar thermal imaging system that obtains temperature of the facial region of a person (Abstract). Xu teaches the system is configured to stabilize the thermal image (image stabilizer 710 is provide for the system, wherein the image stabilizer is for the obtained thermal image video sequence captured by the thermal camera 702, Paragraph 0045).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have modified the system as described by Lane, Ellis, Pompei, and Krupa, wherein the method includes stabilizing the thermal image, as taught by Xu, in order to compensate for noise in the thermal image video sequence, motion of the camera, or movement of the subject (Paragraph 0045).
However, the modifications of Lane, Ellis, Pompei, Krupa, and Xu do not disclose averaging spatial and temporal pixel values of a plurality of thermal images to improve accuracy of the extracted temperature.
Brown teaches a similar system of obtaining infrared images using an infrared sensor (Abstract) and obtaining a temperature measurement from the infrared images (Abstract). Brown teaches the system is configured to average spatial and temporal pixel values of a plurality of thermal images (Paragraph 0055, “The temperature estimator 772 may use spatial filtering (for example, averaging pixels within an image) and temporal filtering (for example, averaging time-sequential images) if needed to minimize the effects of noise in the infrared images.”).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have modified the system as described Lane, Ellis, Pompei, Krupa, and Xu, wherein the method includes averaging spatial and temporal pixel values of a plurality of thermal images to improve accuracy of the extracted temperature, as taught by Brown, in order to minimize the noise in the infrared images (Paragraph 0055). Therefore, in minimizing the noise in the images, it would be obvious that measurements obtained from the improved images, such as temperature would have improved accuracy.
Claim(s) 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lane, in view of Ellis, further in view of Pompei, as applied to claim 11 above, and further in view of Kenyon.
Regarding claim 15, the modifications of Lane, Ellis, and Pompei disclose all the features of claim 11 above.
As disclosed in the claim 11 rejection above, Ellis teaches wherein the circadian rhythm model corresponds to a sub-class associated with the characteristic (Paragraph 0064, using reference profiles indicative of circadian affect specific to a patient’s age range/group).
However, the modification of Lane, Ellis, and Pompei do not disclose wherein the logic device is configured to update the circadian rhythm model corresponding to the sub-class using the extracted temperature to improve accuracy of the circadian rhythm model.
Kenyon teaches a generalized default estimation of circadian rhythm derived from a sample of a general population of people, and over time adjusts the generalized default estimation of circadian rhythm using the measurements of the individual, wherein the measurements include skin temperature (Paragraph 0032). Kenyon teaches by adjusting the generalized default estimation using the individual's measurements, the estimation/model would become more of the individual's actual circadian rhythm (Paragraph 0032). This reads on the claimed updating the circadian rhythm model corresponding to the sub-class using the extracted temperature.
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have modified the system as described by Lane, Ellis, and Pompei, wherein the logic device is configured to update the circadian rhythm model corresponding to the sub-class using the extracted temperature, as taught by Kenyon, in order to adjust the estimation/model to resemble more of the individual's circadian rhythm (Kenyon, Paragraph 0032). By adjusting the estimation/model to be more of the individual's circadian rhythm, it would be obvious that the accuracy of the estimation/model would improve for the individual.
Claim(s) 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lane, in view of Ellis, further in view of Pompei, as applied to claim 11 above, further in view of Krupa, further in view of Xu, and further in view of Brown.
Regarding claim 20, the modifications of Lane, Ellis, and Pompei disclose all the features of claim 11 above.
Lane discloses wherein the system is a portable thermal camera (temperature measurement device 10 is a hand-held device, Paragraph 0020, with an imaging device 16, that can obtain thermal image of the patient, Paragraph 0024, and also visible light images, Paragraph 0024, i.e. images from a digital camera);
the logic device (controller 30) comprises a neural network (controller 30 selects a neural network, Paragraph 0027 for use in determination of the temperature); and
wherein the temperature is associated with an inner canthus of the person’s face (Paragraph 0008, determining, with the device, a temperature from an inner-canthal region of the patient; Paragraph 0060, the temperature measurement can be from the right or left inner-canthal region of the patient).
However, Lane does not disclose wherein the measured temperatures are extracted from the thermal image.
However, Lane does disclose obtaining temperature measurements using sensors 18 that are also located on the temperature measurement device (Paragraph 0060) wherein sensor 18 is an infrared sensor (Paragraph 0030). Lane also discloses generating a temperature profile from the thermal image of the patient (Paragraph 0026), wherein the thermal image is of the measurement site, which is the face (See Fig. 1). Lane additionally discloses that sensor 16, for obtaining the thermal image is also an infrared sensor (Paragraph 0024).
Therefore, It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have modified the system as described by Lane, Ellis, and Pompei, wherein the measured temperature is extracted from the thermal image with the thermal profile of the patient, since Lane teaches that both the imaging sensor 16 and the sensor 18 are both infrared sensors, and both are used to obtain temperature data of the patient (temperature profile extracted from the thermal image obtained using sensor 16, and direct temperature measurements obtained using sensor 18). It would be obvious that the temperature at specific regions within the image can be extracted from the thermal image with the temperature profile.
However, the modifications of Lane. Ellis, and Pompei do not disclose wherein the neural network is configured to process the images to detect the person’s face and the characteristic and the neural network is configured to be trained to detect the face and the characteristic.
Krupa teaches wherein the neural network (Paragraphs 0080, 0120) is configured to process the images to detect the person’s face and the characteristic (Paragraph 0120, deep learning accomplished using a convolution neural network for facial recognition and analysis tasks, where the input layer receives image data, such as from a thermal imager, Paragraphs 0048, 0100; and the analysis include facial features, Paragraphs 0101-0103, used to determine demographic data such as gender and age, Paragraph 0101), and the neural network is configured to be trained to detect the face and the characteristic (training using image samples, Paragraphs 0076, 0106, to detect the face and facial features, Paragraph 0107, and to determine demographic data such as age and gender, Paragraphs 0076, 0102).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have modified the system as described by Lane, Ellis, and Pompei, wherein the neural network is configured to process the images to detect the person’s face and the characteristic and the neural network is configured to be trained to detect the face and the characteristic, as taught by Krupa, in order to perform facial recognition, facial feature determination, Paragraph 0120, and classifying the results by demographic, Paragraph 0112. Further, the use of a neural network is a simple substitution of one known image processing algorithm for facial detection and facial feature extraction, such as the one used by Lane, for another, such as the neural network used by Krupa, to obtain predictable results, i.e. detecting the face in images, and facial feature extraction. (See MPEP 2143).
However, the modifications of Lane, Ellis, Pompei, and Krupa do not disclose the system is configured to stabilize the thermal image.
Xu teaches a similar thermal imaging system that obtains temperature of the facial region of a person (Abstract). Xu teaches the system is configured to stabilize the thermal image (image stabilizer 710 is provide for the system, wherein the image stabilizer is for the obtained thermal image video sequence captured by the thermal camera 702, Paragraph 0045).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have modified the system as described by Lane, Pompei, and Krupa, wherein the system is configured to stabilize the thermal image, as taught by Xu, in order to compensate for noise in the thermal image video sequence, motion of the camera, or movement of the subject (Paragraph 0045).
However, the modifications of Lane, Ellis, Pompei, Krupa, and Xu do not disclose the system is configured to average spatial and temporal pixel values of a plurality of thermal images to improve accuracy of the extracted temperature.
Brown teaches a similar system of obtaining infrared images using an infrared sensor (Abstract) and obtaining a temperature measurement from the infrared images (Abstract). Brown teaches the system is configured to average spatial and temporal pixel values of a plurality of thermal images (Paragraph 0055, “The temperature estimator 772 may use spatial filtering (for example, averaging pixels within an image) and temporal filtering (for example, averaging time-sequential images) if needed to minimize the effects of noise in the infrared images.”).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have modified the system as described Lane, Ellis, Pompei, Krupa, and Xu, wherein the system is configured to average spatial and temporal pixel values of a plurality of thermal images to improve accuracy of the extracted temperature, as taught by Brown, in order to minimize the noise in the infrared images (Paragraph 0055). Therefore, in minimizing the noise in the images, it would be obvious that measurements obtained from the improved images, such as temperature would have improved accuracy.
Response to Arguments
Applicant’s arguments with respect to claim(s) 1-20 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument. Applicant argues in Arguments filed on 11/17/2025 that Lane or Pompei teaches selecting a circadian rhythm model based on the detected characteristic. This limitation is a newly amended limitation, and newly applied prior art to Ellis is used to address the limitation in combination with Lane and Pompei.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Milton Truong whose telephone number is (571)272-2158. The examiner can normally be reached 9AM - 5PM, MON-FRI.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Keith Raymond can be reached at (571) 270-1790. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/MT/Examiner, Art Unit 3798
/KEITH M RAYMOND/Supervisory Patent Examiner, Art Unit 3798