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 .
Response to Arguments
Applicant’s arguments, see Remarks page 7, filed 06/03/2026, with respect to the interpretations of claims 19, 20, and 31 under SuperGuide have been fully considered and are persuasive. The interpretations of claims 19, 20, and 31 have been withdrawn.
Applicant’s arguments, see Remarks pages 7-10, filed 06/03/2026, with respect to the rejections of claim(s) 16, 27, and 35 under 35 U.S.C. 103 have been fully considered, but are not persuasive.
On pages 8-9 of Remarks, Applicant argues:
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Examiner respectfully disagrees.
In response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986).
Paragraph 0030 of Hu discloses “In an embodiment, the system retains taken images of a user, analyzes the images by image recognition, and tags changes in areas of features identified from one image in a sequence image in the series as potential problem area. In the embodiment, the tagged area is checked in each new image to determine if the problem increases or worsens. If over time any problem area reaches a threshold level, the system (e.g., the server) generates an alert. In particular embodiments, the system is configured to instruct users to take an image of a particular part of body to have a closer and more precise monitoring. For example, if dark circles are developing under the eyes of the user, the system instructs the user to take detailed photos of the eyes on a regular basis with greater resolution to improve the accuracy of the image comparison and the recommendation. In one or more embodiments. The threshold is not predetermined for all clients but is instead calibrated and varied for each client using images taken by the client over time”. Wherein images captured by a user are stored as a time-series of images and compared to one another, until the differences are determined to reach a threshold level, indicating the detection of a health concern. The user is alerted of the health concern, and is instructed to take closer pictures of the detected problem area, and, as disclosed by paragraphs 0036 & 0039 of Hu, upon detection of a health concern, information from the user’s devices is acquired, with the user’s permission, in order to determine reasoning of the detected health concern.
Hu discloses, paragraph 0032, that its system comprises the functions: “the system detects certain changes on the face and body which indicate a potential health problem…some red spots detected on the skin might be an early symptom for a skin cancer if not treated early enough…In terms of changes of other parts of the body, such as hands, legs, neck, torso, back, another example is a detection of an early hunchback condition because of an incorrect posture when using computer…the system tracks the development of an injury, wound that is healing, skin condition, or other health condition on various parts of the body to determine through the time progression of images if the status is improving, deteriorating, or remains the same”, wherein the detection of early symptoms and early conditions, as well as the tracking of the improvement or deterioration of health conditions on the body, constitute “an early detection system for changes in patient health and compliance with a treatment regimen”.
Thus, Hu discloses the limitations: “wherein the user health survey comprises a requesting of further information relevant to a condition indicated by the determined differences between the reference facial properties and the subsequent facial properties and thereby provides an early detection system for changes in patient health and compliance with a treatment regimen.”
However, Hu fails to discloses the claim 16 limitations: “wherein the user health survey comprises one or more questions requesting further information relevant to a condition indicated by the determined differences between the reference facial properties and the subsequent facial properties and thereby provides an early detection system for changes in patient health and compliance with a treatment regimen”, wherein Hu fails to disclose the health survey comprising one or more questions.
Paragraph 00250 of Viklund, in reference to Figure 11, discloses “FIG. 11 illustrates methods of generating an alert based on a dynamic threshold. This dynamic threshold is optionally generated using Threshold Logic 750. The dynamic threshold can include multiple dimensions and may be different for each dimension. The dynamic threshold is used to determine if a deviation from expected activity is sufficient to generate an alert. Different dimensions of the dynamic threshold may change by different amounts and/or in different directions”. Viklund discloses a method comprising the detection and comparison of a person’s activity to an expected activity, which is compared to a dynamic threshold.
Paragraphs 00254-00255 of Viklund further disclose “In a Determine Deviation Step 1120 it is determined that activity level of the user received in Receive Activity Step 1110 represents a deviation from the expected activity of the user as received in Receive Expected Activity Step 1115…In a Determine Threshold Step 1125 a threshold for the deviation is determined. The threshold typically different for different dimensions of activity, and is dynamic. A dynamic threshold is one that may vary depending on different criteria…Determination of a threshold is optionally responsive to answers to questions selected using Question Logic 195. For example, an answer to a question may explain a deviation or indicate that a deviation is likely to indicate a health problem”. Wherein, upon determination that a difference between a user’s activity level and an expected activity level is significant enough to be classified as a deviation, the user is asked questions regarding the deviation in order to determine whether they indicate a health problem. The questions sent to a user, in response to the deviation determination, constitute a user health survey, wherein the questions are relevant to the deviation between the user’s activity level and the expect activity level.
Given the teachings above, one of ordinary skill in the art would have been motivated to implement the known technique of providing questions to a user based on detected deviations disclosed by Viklund by sending questions to a user based on the detected health concerns disclosed by Hu.
In response to applicant’s argument that there is no teaching, suggestion, or motivation to combine the references, the examiner recognizes that obviousness may be established by combining or modifying the teachings of the prior art to produce the claimed invention where there is some teaching, suggestion, or motivation to do so found either in the references themselves or in the knowledge generally available to one of ordinary skill in the art. See In re Fine, 837 F.2d 1071, 5 USPQ2d 1596 (Fed. Cir. 1988), In re Jones, 958 F.2d 347, 21 USPQ2d 1941 (Fed. Cir. 1992), and KSR International Co. v. Teleflex, Inc., 550 U.S. 398, 82 USPQ2d 1385 (2007). In this case, paragraph 00255 of Viklund discloses “an answer to a question may explain a deviation or indicate that a deviation is likely to indicate a health problem. In an illustrative example, if a monitored user is detected getting up several times at night, then a question about how well the user slept may be selected. An answer to that question of "there was a party next door" may be indicative that getting up is not the result of an undesirable health state, while an answer "I keep feeling like I have to pee, but cannot" may be indicative of the likelihood of a health problem that warrants an alert be sent”. Thus, one of ordinary skill in the art would have been motivated to combine the teachings of Viklund with Hu because the questions provide further information from the user regarding any detected deviations, or differences. The determined questions are further analyzed for further determination of health concerns and their severity.
Therefore, the rejection of claim 16 under 35 U.S.C. 103, as further disclosed below, is maintained.
As per claim(s) 27 and 35, arguments made in rejecting claim(s) 16 are analogous.
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) 16-17, 21-22, 26-29, 32, and 34-37 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hu et al. (US 20190214127 A1) hereinafter referenced as Hu, in view of Viklund et al. (WO2019070763A1) hereinafter referenced as Viklund.
Regarding claim 16, Hu discloses: A non-transitory computer-readable medium storing machine-readable instructions that when executed by a processor, causes the processor to (Hu: 0089-0090):
control a camera to capture a reference image of a user's face and a subsequent image of the user's face (Hu: 0077: “In 504, client device 132 captures one or more images of a face or other body part of the user over a period of time.”; 0078: “In 512, image comparison module 320 determines a time series of images previously captured over a predetermined period of time to compare to the most recently received image.”; Wherein the reference image was previously captured and the subsequent image was captured in step 504);
determine reference facial properties of the user from the reference image, and subsequent facial properties of the user from the subsequent image (Hu: 0078: “…recognition module 318 within application 107 of server 104 extracts one or more facial features (or other body features) from the image(s) after receiving the image(s)… image comparison module 320 determines a time series of images previously captured over a predetermined period of time to compare to the most recently received image.”; Wherein the subsequent image’s facial features are extracted and compared to the features of the reference image);
determine any differences between the reference facial properties and the subsequent facial properties (Hu: 0078: “In 512, image comparison module 320 determines a time series of images previously captured over a predetermined period of time to compare to the most recently received image. In 514, image comparison module 320 compares the image series using a knowledge base to determine differences between one or more facial features (or other body features) that are indicative of a sub-optimal health condition of the user.”);
generate a record of the reference and the subsequent facial properties (Hu: 0024: “the one or more databases store the time series of images as well as health information regarding the user's health information. In particular embodiments, the user's health information includes quantitative measurements for determining differences between time-series image data (e.g., “selfies” taken over a period of time).”; Wherein the health information includes the facial properties);
generate a warning when the differences between the reference facial properties and the subsequent facial properties are determined (Hu: Figure 5; 0078: “In 516, image sub-health detection module 322 determines whether a difference in the facial or body features in the series of images exceed a predetermined threshold value.”; 0079: “In 520, alert/notification module 324 creates an alert for close monitoring of the health condition and sends the alert to the user.”; Wherein an alert is created when the differences exceed a threshold value), wherein the warning includes a user health survey (Hu: 0030: “ If over time any problem area reaches a threshold level, the system (e.g., the server) generates an alert. In particular embodiments, the system is configured to instruct users to take an image of a particular part of body to have a closer and more precise monitoring. For example, if dark circles are developing under the eyes of the user, the system instructs the user to take detailed photos of the eyes on a regular basis with greater resolution to improve the accuracy of the image comparison and the recommendation.”;
0036-0039: “the system acquires information from wearable devices to analyze the user's activities to facilitate determining a reason for a detected health concern…the system connects with a user's calendar to detect whether the user is under pressure and working too hard which might lead to sub-healthy status of the user. In another particular embodiment, the system acquires information from a personal health tracking system (e.g., a smart watch or fitness tracker) with the user's permission to reevaluate activity goals if some anomalies are detected.”; Wherein the requests for further imaging of a particular body part and for personal health tracking system information constitute a health survey.);
control a display to display the warning including the user health survey (Hu: 0028: “the system generates an alert to the user such as creating a notification on a mobile phone, sending an email, sending a text message or some other preferred methods of contact that includes an indication to a user that an image should be taken.”; Wherein the alert via notification, email, or text message constitutes an alert being displayed.);
control a communication unit to transmit the user health survey to an external device when the user health survey is completed (Hu: 0029-0030: “ a smart phone is used as the client device for taking daily photos of a user…the system retains taken images of a user, analyzes the images by image recognition, and tags changes in areas of features identified from one image in a sequence image in the series as potential problem area. In the embodiment, the tagged area is checked in each new image to determine if the problem increases or worsens. If over time any problem area reaches a threshold level, the system (e.g., the server) generates an alert. In particular embodiments, the system is configured to instruct users to take an image of a particular part of body to have a closer and more precise monitoring.”; 0036-0039: “the system acquires information from wearable devices to analyze the user's activities to facilitate determining a reason for a detected health concern…the system connects with a user's calendar to detect whether the user is under pressure and working too hard which might lead to sub-healthy status of the user. In another particular embodiment, the system acquires information from a personal health tracking system (e.g., a smart watch or fitness tracker) with the user's permission to reevaluate activity goals if some anomalies are detected.”);
and store the record in a memory (Hu: 0024: “the one or more databases store the time series of images as well as health information regarding the user's health information.”; 0054: “Database(s) 109, such as a user profile database, an image database, and/or a feature/symptom correlation database may be stored in storage 108 as shown or supplied by another source (not shown).”).,
wherein the user health survey comprises a requesting of further information relevant to a condition indicated by the determined differences between the reference facial properties and the subsequent facial properties (Hu: 0030: “ If over time any problem area reaches a threshold level…the system is configured to instruct users to take an image of a particular part of body to have a closer and more precise monitoring. For example, if dark circles are developing under the eyes of the user, the system instructs the user to take detailed photos of the eyes on a regular basis with greater resolution to improve the accuracy of the image comparison and the recommendation.”;
0036-0039: “the system acquires information from wearable devices to analyze the user's activities to facilitate determining a reason for a detected health concern…the system connects with a user's calendar to detect whether the user is under pressure and working too hard which might lead to sub-healthy status of the user. In another particular embodiment, the system acquires information from a personal health tracking system (e.g., a smart watch or fitness tracker) with the user's permission to reevaluate activity goals if some anomalies are detected.”) and thereby provides an early detection system for changes in patient health and compliance with a treatment regimen (Hu: 0031-0033: “a system database or cloud storage system records possible problems which can be noticed on the skin, the face or the body of a user…and compares a knowledge base including an image database for certain health issues available and provided by a medical agency with the user's daily images to provide further information to the user about the user's health status…
In another example, some red spots detected on the skin might be an early symptom for a skin cancer if not treated early enough…In other particular example, the system tracks the development of an injury, wound that is healing, skin condition, or other health condition on various parts of the body to determine through the time progression of images if the status is improving, deteriorating, or remains the same…
the system receives health monitoring information from a user's health monitoring devices such as a smart watch or fitness tracker device to detect changes of life style of the user and learn a correlation between detected facial and body changes and changes of living style or habit.”;
Wherein all the collected information is processed by the system in order to detect the user’s current health status allowing for the early detection of health issues and the tracking of whether health conditions, such as wounds, are improving.).
Hu does not disclose expressly: wherein the user health survey comprises one or more questions requesting further information relevant to a condition indicated by the determined differences between the reference facial properties and the subsequent facial properties.
Viklund discloses: a system for analyzing the activities of a user for the purposes of diagnosing the user’s health issues and reporting activity deviations determined to be concerning, wherein for the process of reporting health deviations, a health survey, used to determine whether the activity deviation is urgent, is generated comprises one or more questions requesting further information relevant to a condition indicated by the determined differences between a reference activity and a subsequent received activity (Viklund: Figure 11; 0250: “FIG. 11 illustrates methods of generating an alert based on a dynamic threshold…The dynamic threshold is used to determine if a deviation from expected activity is sufficient to generate an alert.”;
0252-0254: “In a Receive Activity Step 1110 an activity level of a user is received…In a Receive Expected Activity Step 1115 an expected activity is received...In a Determine Deviation Step 1120 it is determined that activity level of the user received in Receive Activity Step 1110 represents a deviation from the expected activity of the user as received in Receive Expected Activity Step 1115.”;
0256: “In a Determine Threshold Step 1125 a threshold for the deviation is determined…Determination of a threshold is optionally responsive to answers to questions selected using Question Logic 195. For example, an answer to a question may explain a deviation or indicate that a deviation is likely to indicate a health problem. In an illustrative example, if a monitored user is detected getting up several times at night, then a question about how well the user slept may be selected. An answer to that question of "there was a party next door" may be indicative that getting up is not the result of an undesirable health state, while an answer "I keep feeling like I have to pee, but cannot" may be indicative of the likelihood of a health problem that warrants an alert be sent. Thresholds determined in Determine Threshold Step 1125 may, therefore, be based on responses to selected questions.”), wherein the user activity also includes user properties extracted from captured images (Viklund: 0194: “All or part of Machine Learning System 735 is optionally disposed on members of Monitored Devices 110. For example, acceleration data generated by Sensor 715A on Monitored Device 110A may be processed by Machine Learning System 735 to produce a preliminary result indicative of an activity…Machine Learning System 735, Machine Learning System 745, and/or Rule Logic are optionally configured to analyze images or a series of images. For example, Machine Learning System 735 may be configured to analyze an image of a wound for signs of infection or to analyze one or more images for indications of skin cancer, and/or other uses of image analysis discussed herein.”).
Before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to implement the known technique of providing questions to a user based on detected deviations disclosed by Viklund by sending questions to a user based on the detected anomalies disclosed by Hu. The suggestion/motivation for doing so would have been “an answer to a question may explain a deviation or indicate that a deviation is likely to indicate a health problem… if a monitored user is detected getting up several times at night, then a question about how well the user slept may be selected. An answer to that question of "there was a party next door" may be indicative that getting up is not the result of an undesirable health state, while an answer "I keep feeling like I have to pee, but cannot" may be indicative of the likelihood of a health problem that warrants an alert be sent” (Viklund:0255). Further, one skilled in the art could have combined the elements as described above by known methods with no change in their respective functions, and the combination would have yielded nothing more than predictable results. Therefore, it would have been obvious to combine Hu with Viklund to obtain the invention as specified in claim 16.
Regarding claim 17, Hu in view of Viklund discloses: The non-transitory computer-readable medium according to claim 16, wherein each of the reference facial properties and the subsequent facial properties relate to at least one of eyes, skin, hair, or facial impression of the user as depicted in a respective one of the reference image and the subsequent image (Hu: 0036: “…tracked facial characteristics include, but are not limited to, dark circles around the eyes, eyes that bulge out, dull complexion, unhealthy color of teeth, dark spots on the skin, skin inflammations, change of shape of face, changes in eyeball shape/color, and acne.”).
Regarding claim 21, Hu in view of Viklund discloses: The non-transitory computer-readable medium according to claim 17, wherein the instructions cause the processor to determine at least one of a respective color or clarity of an eye from each of the reference image and the subsequent image (Hu: 0036: “tracked facial characteristics include, but are not limited to, dark circles around the eyes, eyes that bulge out, dull complexion, unhealthy color of teeth, dark spots on the skin, skin inflammations, change of shape of face, changes in eyeball shape/color, and acne.”).
Regarding claim 22, Hu in view of Viklund discloses: The non-transitory computer-readable medium according to claim 17, wherein the instructions cause the processor to determine at least one of a respective skin color, skin tone, or skin moisture from each of the reference image and the subsequent image (Hu: 0036: “tracked facial characteristics include, but are not limited to, dark circles around the eyes, eyes that bulge out, dull complexion, unhealthy color of teeth, dark spots on the skin, skin inflammations, change of shape of face, changes in eyeball shape/color, and acne.”).
Regarding claim 26, Hu in view of Viklund discloses: The non-transitory computer-readable medium according to claim 16, wherein prior to capturing the reference image and/or the subsequent image, the instructions cause the processor to: generate an input window requesting the reference image or the subsequent image to be taken, and control a display to display the input window (The recited “and/or” is interpreted as “or”) (Hu: 0028: “…capturing an image on an individual day could be skipped and if too many days are skipped in a row, the system generates an alert to the user such as creating a notification on a mobile phone, sending an email, sending a text message or some other preferred methods of contact that includes an indication to a user that an image should be taken.”; Wherein the alert/notification to the user requesting for them to take an image constitutes the input window).
As per claim(s) 27, arguments made in rejecting claim(s) 16 are analogous.
Regarding claim 28, Hu in view of Viklund discloses: The apparatus according to claim 27, wherein the apparatus is a mobile device (Hu: 0024: “In particular embodiments, the client device includes a mobile phone or a camera or other imaging device installed at a user location.”).
As per claim(s) 29, arguments made in rejecting claim(s) 17 are analogous.
Regarding claim 32, Hu in view of Viklund discloses: The apparatus according to claim 27, wherein the processor is configured to determine at least one of a respective skin color, skin tone, skin moisture, hair distribution, hair volume, eye color, and/or clarity of an eye from each of the reference image and the subsequent image (The recited “and/or” is interpreted as “or”) (Hu: 0036: “tracked facial characteristics include, but are not limited to, dark circles around the eyes, eyes that bulge out, dull complexion, unhealthy color of teeth, dark spots on the skin, skin inflammations, change of shape of face, changes in eyeball shape/color, and acne.”).
Regarding claim 34, Hu in view of Viklund discloses: The apparatus according to claim 27, wherein the user interface is further configured to receive user inputs for the user health survey (Hu: 0033: “a user's health profile stored in the database is used to provide information regarding the user's family medical history and personal medical history to determine if the person has predisposition to certain conditions…the system receives health monitoring information from a user's health monitoring devices such as a smart watch or fitness tracker device to detect changes of life style of the user and learn a correlation between detected facial and body changes and changes of living style or habit.”)
(Viklund: 0101: “Caregivers can report/provide answers to the questions via Caregiver Interface 158 via, typing, speaking into a microphone, or checking boxes. The answers can be provided by the user in response to the caregiver asking the user a question, or may be based on observations of the user by the caregiver. ”;
0255: “Determination of a threshold is optionally responsive to answers to questions selected using Question Logic 195. For example, an answer to a question may explain a deviation or indicate that a deviation is likely to indicate a health problem. In an illustrative example, if a monitored user is detected getting up several times at night, then a question about how well the user slept may be selected. An answer to that question of "there was a party next door" may be indicative that getting up is not the result of an undesirable health state, while an answer "I keep feeling like I have to pee, but cannot" may be indicative of the likelihood of a health problem that warrants an alert be sent.”).
As per claim(s) 35, arguments made in rejecting claim(s) 16 are analogous.
Regarding claim 36, Hu in view of Viklund discloses: The non-transitory computer-readable medium according to claim 16, wherein to determine any differences between the reference facial properties and the subsequent facial properties, the instructions cause the processor to analyze characteristics of the user's face against pre-stored information detailing pre-defined facial characteristics (Hu: 0031: “In particular embodiments, a system database or cloud storage system records possible problems which can be noticed on the skin, the face or the body of a user. In a particular example, the system keeps records of various images of melanoma progression over time, such as dark or red spots on the skin, and compares a knowledge base including an image database for certain health issues available and provided by a medical agency with the user's daily images to provide further information to the user about the user's health status.”; 0036: “a system tracks a history of user images taken over a period of time, conducts facial recognition to compare historical images to characteristics of a healthy face or from a medical image database for a specific health concern, detects a health concern based upon the comparison, and alerts the user based upon the detected health concern.”).
Regarding claim 37, Hu in view of Viklund discloses: The non-transitory computer-readable medium according to claim 36, wherein the pre-defined facial characteristics represent facial indicators that are indicative of diseases, disorders, or drug side-effects (Hu: 0031: “a system database or cloud storage system records possible problems which can be noticed on the skin, the face or the body of a user. In a particular example, the system keeps records of various images of melanoma progression over time, such as dark or red spots on the skin, and compares a knowledge base including an image database for certain health issues available and provided by a medical agency with the user's daily images to provide further information to the user about the user's health status.”).
Claim(s) 18-20, and 30-31 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hu in view of Viklund, and further in view of Mursel et al. (TR 201723564 A2) hereinafter referenced as Mursel.
Regarding claim 18, Hu in view of Viklund discloses: The non-transitory computer-readable medium according to claim 17.
Hu in view of Viklund does not disclose expressly: wherein the instructions cause the processor to determine a respective facial impression from each of the reference image and the subsequent image based on a respective distance measured between a fixed face point and a variable face point depicted in the corresponding image.
Mursel discloses: determination of a facial impression based on a respective distance measured between a fixed face point and a variable face point depicted (Mursel: Page 3-4: Paragraph: 5: “The information acquired is processed into the database of the processor (3) automated by the deep learning system. such as mouth distance, depth of eye, nose, distance and position relation between cue points”; Wherein the distance between cue points constitutes the distance measured between a fixed and variable face point.).
Before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to incorporate the known technique taught by Mursel of measuring the distance between cue points into Hu in view of Viklund by measuring points on the reference and subsequent images. The suggestion/motivation for doing so would have been “…the automated processor (3) with the deep learning system provides a list of possible physical and mental illnesses where these measures and characteristics match.” (Mursel: Page 4: Paragraph 1). Further, one skilled in the art could have combined the elements as described above by known methods with no change in their respective functions, and the combination would have yielded nothing more than predictable results. Therefore, it would have been obvious to combine Hu in view of Viklund with Mursel to obtain the invention as specified in claim 18.
Regarding claim 19, Hu in view of Viklund and Mursel discloses: The non-transitory computer-readable medium according to claim 18, wherein the fixed face point comprises at least one of a bridge of a nose or an outer edge of a nostril (Mursel: Page 3-4: Paragraph: 5: “The information acquired is processed into the database of the processor (3) automated by the deep learning system. such as mouth distance, depth of eye, nose, distance and position relation between cue points”; Wherein the nose constitutes the bridge and the outer edge of a nostril).
Regarding claim 20, Hu in view of Viklund and Mursel discloses: The non-transitory computer-readable medium according to claim 18, wherein the variable face point comprises at least one of an outer edge of an eyelid or a corner of a mouth (Mursel: Page 3-4: Paragraph: 5: “The information acquired is processed into the database of the processor (3) automated by the deep learning system. such as mouth distance, depth of eye, nose, distance and position relation between cue points”; Wherein the eye comprises at least one outer edge of an eyelid).
As per claim(s) 30, arguments made in rejecting claim(s) 18 are analogous.
Regarding claim 31, Hu in view of Viklund and Mursel discloses: The apparatus according to claim 30, wherein the fixed face point comprises at least one of a bridge of a nose or an outer edge of a nostril (Mursel: Page 3-4: Paragraph: 5: “The information acquired is processed into the database of the processor (3) automated by the deep learning system. such as mouth distance, depth of eye, nose, distance and position relation between cue points”; Wherein the nose constitutes the bridge and the outer edge of a nostril), and wherein the variable face point comprises at least one of an outer edge of an eyelid or a corner of a mouth (Mursel: Page 3-4: Paragraph: 5: “The information acquired is processed into the database of the processor (3) automated by the deep learning system. such as mouth distance, depth of eye, nose, distance and position relation between cue points”; Wherein the eye comprises at least one outer edge of an eyelid).
Claim(s) 23 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hu in view of Viklund, and further in view of Bhalotia (US 20200312455 A1).
Regarding claim 23, Hu in view of Viklund discloses: The non-transitory computer-readable medium according to claim 16.
Hu in view of Viklund does not disclose expressly: wherein the instructions cause the processor to determine at least one of a respective hair distribution, or hair volume from each of the reference and the subsequent images.
Bhalotia discloses: determining at least one of a respective hair distribution, or hair volume from an image (Bhalotia: 0043: “The processing unit 102 may be configured to process at least an image to determine different patterns/colors/shades/texture of eyes, hair, nails, or the skin of face or other body parts.”).
Before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to incorporate the algorithms for analyzing hair visual markers disclosed by Bhalotia into the feature extraction process disclosed by Hu in view of Viklund. The suggestion/motivation for doing so would have been “At step 306, the captured image of visual markers is analyzed by the processing unit 102 to determine the health condition of the individual. The determination of the health condition of an individual comprises determination of one or more of a constitution type, a disease type…symptoms of a disease, susceptibility to a disease, tendency to develop illness...” (Bhalotia: 0058; Wherein more visual features allow for more accurate determinations.). Further, one skilled in the art could have combined the elements as described above by known methods with no change in their respective functions, and the combination would have yielded nothing more than predictable results. Therefore, it would have been obvious to combine Hu in view of Viklund with Bhalotia to obtain the invention as specified in claim 23.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ANTHONY J RODRIGUEZ whose telephone number is (703)756-5821. The examiner can normally be reached Monday-Friday 10am-7pm.
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/ANTHONY J RODRIGUEZ/Examiner, Art Unit 2672
/SUMATI LEFKOWITZ/Supervisory Patent Examiner, Art Unit 2672
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