DETAILED CORRESPONDENCE
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 .
Status of the Application
The Preliminary Amendment filed July 21, 2026 has been entered. Claims 1-20 were canceled; and new claims 21-40 were added. Claims 21-40 are pending and presented to be examined upon their merits. Claims 21-40 have been examined in the application. This communication is the first action on the merits.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on March 8, 2024 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
1-st Double Patenting Category: Claims 21, 23-25, 27, 29-34, 36, and 38 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-17 of U.S. Patent No. US 10,825,095 B1 to Bernico; Michael L. et al., (hereinafter "BERNICO-Claims").
Claim 21, EXAMINER's Analysis: Claim 21 is rejected as being anticipated by BERNICO-Claims. Claim 21 is an independent claim. BERNICO-Claims discloses the claimed subject matter of claim 21 as follows and as explained below.
Regarding and as per CLAIM 21, a system for evaluating an applicant to determine one or more terms of insurance coverage, comprising: Line Comment: (BERNICO-Claims: discloses "[a] system for evaluating an [] applicant [] to determine one or more terms of insurance coverage, [] comprising:" Claim 1)
• 21 ¶ 2 • a data receiving circuit configured to receive image data of the applicant; and Line Comment: (BERNICO-Claims: discloses "a data receiving circuit configured to receive [] image [] data of the insurance applicant; and" Claim 1)
• 21 ¶ 3 • a processor trained to correlate aspects of appearance with a personal and/or health-related characteristic by being provided with image data of individuals having known personal and/or health-related characteristics; Line Comment: (BERNICO-Claims: discloses "a processor [] trained to correlate aspects of appearance [] with a personal and/or health-related characteristic by being provided with [] image [] data of individuals having known personal and/or health-related characteristics" Claim 1)
• 21 ¶ 4 • wherein the processor analyzes the image data of the applicant to determine a personal and/or health-related characteristic of the applicant, and to suggest a term of insurance coverage based at least in part upon the determined personal and/or health-related characteristic. Line Comment: (BERNICO-Claims: discloses "processor [] to analyze the [] image [] data of the insurance applicant to determine the personal and/or health-related characteristic for the [] applicant, and to suggest a term of insurance coverage based at least in part on the determined personal and/or health-related characteristic" Claim 1)
Claim 23, EXAMINER's Analysis: Claim 23 is rejected as being anticipated by BERNICO-Claims. Claim 23 is a dependent claim that directly depends upon parent claim 21, which is an independent claim. Further to and in conjunction with the disclosures and teachings of the prior art recited in the parent as applied to the limitations of claim 21, BERNICO-Claims discloses the claimed subject matter of claim 23 as follows and as explained below.
Regarding and as per CLAIM 23, the system as set forth in claim 21,
• 23 ¶ 2 • wherein the term of insurance coverage includes an insurance premium or discount. Line Comment: (BERNICO-Claims: discloses "wherein the term of insurance coverage includes an insurance premium or discount" Claim 3)
Claim 24, EXAMINER's Analysis: Claim 24 is rejected as being anticipated by BERNICO-Claims. Claim 24 is a dependent claim that directly depends upon parent claim 21, which is an independent claim. Further to and in conjunction with the disclosures and teachings of the prior art recited in the parent as applied to the limitations of claim 21, BERNICO-Claims discloses the claimed subject matter of claim 24 as follows and as explained below.
Regarding and as per CLAIM 24, the system as set forth in claim 21,
• 24 ¶ 2 • wherein the image data of the applicant includes a digital image. Line Comment: (BERNICO-Claims: discloses "wherein the [] image data of the insurance applicant includes a digital image" Claim 4)
Claim 25, EXAMINER's Analysis: Claim 25 is rejected as being anticipated by BERNICO-Claims. Claim 25 is a dependent claim that directly depends upon parent claim 21, which is an independent claim. Further to and in conjunction with the disclosures and teachings of the prior art recited in the parent as applied to the limitations of claim 21, BERNICO-Claims discloses the claimed subject matter of claim 25 as follows and as explained below.
Regarding and as per CLAIM 25, the system as set forth in claim 21,
• 25 ¶ 2 • wherein the image data of the applicant includes a selfie. Line Comment: (BERNICO-Claims: discloses "image [] data of the insurance applicant" Claim 1 and "wherein the [] image of the insurance applicant is a selfie" Claim 8)
Claim 27, EXAMINER's Analysis: Claim 27 is rejected as being anticipated by BERNICO-Claims. Claim 27 is a dependent claim that directly depends upon parent claim 21, which is an independent claim. Further to and in conjunction with the disclosures and teachings of the prior art recited in the parent as applied to the limitations of claim 21, BERNICO-Claims discloses the claimed subject matter of claim 27 as follows and as explained below.
Regarding and as per CLAIM 27, the system as set forth in claim 21,
• 27 ¶ 2 • wherein the processor employs a deep learning neural network. Line Comment: (BERNICO-Claims: discloses "wherein the processor employs a neural network" Claim 11 and "[t]he system as set forth in claim 11, wherein the neural network is a deep learning neural network" Claim 13)
Claim 29, EXAMINER's Analysis: Claim 29 is rejected as being anticipated by BERNICO-Claims. Claim 29 is a dependent claim that directly depends upon parent claim 21, which is an independent claim. Further to and in conjunction with the disclosures and teachings of the prior art recited in the parent as applied to the limitations of claim 21, BERNICO-Claims discloses the claimed subject matter of claim 29 as follows and as explained below.
Regarding and as per CLAIM 29, the system as set forth in claim 21,
• 29 ¶ 2 • wherein the personal and/or health-related characteristic is at least one of age, sex, weight, height, ethnicity, lifespan, cause of death, tobacco use, alcohol use, drug use, diet, existing medical conditions, or risk factors for future medical conditions. Line Comment: (BERNICO-Claims: discloses "wherein the personal and/or health-related characteristic is selected from the group consisting of: age, sex, weight, height, ethnicity, lifespan, cause of death, tobacco use, alcohol use, drug use, diet, and existing medical conditions, risk factors for future medical conditions" Claim 14)
Claim 30, EXAMINER's Analysis: Claim 30 is rejected as being anticipated by BERNICO-Claims. Claim 30 is a dependent claim that directly depends upon parent claim 21, which is an independent claim. Further to and in conjunction with the disclosures and teachings of the prior art recited in the parent as applied to the limitations of claim 21, BERNICO-Claims discloses the claimed subject matter of claim 30 as follows and as explained below.
Regarding and as per CLAIM 30, the system as set forth in claim 21,
• 30 ¶ 2 • wherein the processor is further configured to use the determined personal and/or health-related characteristic to verify information provided by the applicant. Line Comment: (BERNICO-Claims: discloses "wherein the processor is further configured to use the determined personal and/or health-related characteristic to verify information provided by the [] applicant" Claim 15)
Claim 31, EXAMINER's Analysis: Claim 31 is rejected as being anticipated by BERNICO-Claims. Claim 31 is a dependent claim that directly depends upon parent claim 21, which is an independent claim. Further to and in conjunction with the disclosures and teachings of the prior art recited in the parent as applied to the limitations of claim 21, BERNICO-Claims discloses the claimed subject matter of claim 31 as follows and as explained below.
Regarding and as per CLAIM 31, the system as set forth in claim 21,
• 31 ¶ 2 • wherein the processor is further configured to use the determined personal and/or health-related characteristic to substantially automatically determine the term of insurance coverage. Line Comment: (BERNICO-Claims: discloses "wherein the processor is further configured to use the determined personal and/or health-related characteristic to substantially automatically determine the term of coverage" Claim 16)
Claim 32, EXAMINER's Analysis: Claim 32 is rejected as being anticipated by BERNICO-Claims. Claim 32 is an independent claim. BERNICO-Claims discloses the claimed subject matter of claim 32 as follows and as explained below.
Regarding and as per CLAIM 32, a system for evaluating an applicant to determine a life insurance premium, comprising: Line Comment: (BERNICO-Claims: discloses "[a] system for evaluating an [] applicant [] to determine a life insurance premium, [] comprising:" Claim 17)
• 32 ¶ 2 • a data receiving circuit configured to receive otherwise non-diagnostic conventional image data of the applicant; and Line Comment: (BERNICO-Claims: discloses "a data receiving circuit configured to receive otherwise non-diagnostic conventional [] image [] data of the [] applicant" Claim 17)
• 32 ¶ 3 • a processor employing a neural network and trained to correlate one or more aspects of appearance with a personal and/or health-related characteristic by being provided with otherwise non-diagnostic conventional image data of individuals having known personal and/or health-related characteristics; Line Comment: (BERNICO-Claims: discloses "a processor [] employing a neural network andG¦÷ trained to correlate one or more aspects of appearance [] with a personal and/or health-related characteristic by being provided with [] otherwise non-diagnostic conventional [] image [] data of individuals having known personal and/or health-related characteristics" Claim 17)
• 32 ¶ 4 • wherein the processor analyzes the otherwise non-diagnostic conventional image data of the applicant to determine a personal and/or health-related characteristic of the applicant, to use the determined personal and/or health-related characteristic to verify information provided by the applicant, and to substantially automatically determine the life insurance premium based at least in part upon the determined personal and/or health-related characteristic. Line Comment: (BERNICO-Claims: discloses “processor [] to analyze the otherwise non-diagnostic conventional [] image [] data of the insurance applicant to determine the personal and/or health-related characteristic for the insurance applicant, to use the determined personal and/or health-related characteristic to verify information provided by the insurance applicant, and the substantially automatically determine the life insurance premium based at least in part on the determined personal and/or health-related characteristic” Claim 17)
Claim 33, EXAMINER's Analysis: Claim 33 is rejected as being anticipated by BERNICO-Claims. Claim 33 is a dependent claim that directly depends upon parent claim 32, which is an independent claim. Further to and in conjunction with the disclosures and teachings of the prior art recited in the parent as applied to the limitations of claim 32, BERNICO-Claims discloses the claimed subject matter of claim 33 as follows and as explained below.
Regarding and as per CLAIM 33, the system as set forth in claim 32,
• 33 ¶ 2 • wherein the otherwise non-diagnostic conventional image data of the applicant includes a digital image. Line Comment: (BERNICO-Claims: discloses "otherwise non-diagnostic conventional [] image" Claims 7, 17 and "wherein the [] image data of the insurance applicant includes a digital image" Claim 4)
Claim 34, EXAMINER's Analysis: Claim 34 is rejected as being anticipated by BERNICO-Claims. Claim 34 is a dependent claim that directly depends upon parent claim 32, which is an independent claim. Further to and in conjunction with the disclosures and teachings of the prior art recited in the parent as applied to the limitations of claim 32, BERNICO-Claims discloses the claimed subject matter of claim 34 as follows and as explained below.
Regarding and as per CLAIM 34, the system as set forth in claim 32,
• 34 ¶ 2 • wherein the otherwise non-diagnostic conventional image data of the applicant includes a selfie. Line Comment: (BERNICO-Claims: discloses "otherwise non-diagnostic conventional [] image" Claims 7, 17 and "image [] data of the insurance applicant" Claim 1 and "wherein the [] image of the insurance applicant is a selfie" Claim 8)
Claim 36, EXAMINER's Analysis: Claim 36 is rejected as being anticipated by BERNICO-Claims. Claim 36 is a dependent claim that directly depends upon parent claim 32, which is an independent claim. Further to and in conjunction with the disclosures and teachings of the prior art recited in the parent as applied to the limitations of claim 32, BERNICO-Claims discloses the claimed subject matter of claim 36 as follows and as explained below.
Regarding and as per CLAIM 36, the system as set forth in claim 32,
• 36 ¶ 2 • wherein the neural network is a deep learning neural network. Line Comment: (BERNICO-Claims: discloses "employs a neural network" Claim 11 and "as set forth in claim 11, wherein the neural network is a deep learning neural network" Claim 13)
Claim 38, EXAMINER's Analysis: Claim 38 is rejected as being anticipated by BERNICO-Claims. Claim 38 is a dependent claim that directly depends upon parent claim 32, which is an independent claim. Further to and in conjunction with the disclosures and teachings of the prior art recited in the parent as applied to the limitations of claim 32, BERNICO-Claims discloses the claimed subject matter of claim 38 as follows and as explained below.
Regarding and as per CLAIM 38, the system as set forth in claim 32,
• 38 ¶ 2 • wherein the personal and/or health-related characteristic is at least one of age, sex, weight, height, ethnicity, lifespan, cause of death, tobacco use, alcohol use, drug use, diet, existing medical conditions, or risk factors for future medical conditions. Line Comment: (BERNICO-Claims: See Prior Comment at Claim 29 Par. 2)
2-nd Double Patenting Category: Claims 22, 26, 28, 35, 37, and 39-40 are rejected on the ground of nonstatutory double patenting as being unpatentable over BERNICO-Claims in view of U.S. Patent No. US 10,825,095 B1 to Bernico; Michael L. et al., (hereinafter "BERNICO-A").
Claim 22, EXAMINER's Analysis: Claim 22 is rejected as being unpatentable over BERNICO-Claims and BERNICO-A. Claim 22 is a dependent claim that directly depends upon parent claim 21, which is an independent claim. Further to and in conjunction with the disclosures and teachings of the prior art recited in the parent as applied to the limitations of claim 21, the combined disclosures and teachings of BERNICO-Claims and BERNICO-A taken together render obvious the claimed subject matter of claim 22 as follows and as explained below.
Regarding and as per CLAIM 22, the system as set forth in claim 21,
• 22 ¶ 2 • wherein the insurance coverage is health insurance. Line Comment: (BERNICO-Claims: doesn't expressly and explicitly recite wherein the insurance coverage is health insurance --- however BERNICO-A: clearly discloses, teaches, and/or suggests the feature -- "insurance coverage may be [] a proposed [] health insurance" col. 13 ln. 26 - col. 13 ln. 42); [See Remarks Below];
With respect to above-noted claimed element the above "wherein the insurance coverage..." line limitation which is disclosed by BERNICO-A: the teachings and/or suggestions within the disclosure of BERNICO-Claims thus far relied upon does not record within its explanations an explicit and express recital of the above "wherein the insurance coverage..." line limitation as required by the instant claim. Nevertheless, herein relied upon are portions of the disclosure of BERNICO-A which sufficiently teaches the feature appurtenant to the claimed invention as pointed out above with citation(s) to exemplary disclosures within BERNICO-A that teach and/or suggest the claimed feature. At the time of effective filing date, it would have been obvious for one of ordinary skill in the art to have modified the relied upon teachings of BERNICO-Claims by adding or substituting the feature the above "wherein the insurance coverage..." line limitation as taught and/or suggested by BERNICO-A, with a reasonable expectation of success of arriving at the claimed invention. The addition or substitution of this known feature by one of ordinary skill in the art at the time of the effective filing date would have yielded predictable results that were simply reckonable to that one person of ordinary skill in the art at that time. At the time of the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to have modified the teachings of BERNICO-Claims with these previously described teachings of the above "wherein the insurance coverage..." line limitation sufficiently taught, suggested, and/or disclosed in BERNICO-A because that one artisan of skill having ordinary skill in the art at the time of the effective filing date of the invention would have had a motivation of "[a]dvantages of these and other embodiments will become more apparent to those skilled in the art from the following description of the exemplary embodiments which have been shown and described by way of illustration[; a]s will be realized, the present embodiments described herein may be capable of other and different embodiments, and their details are capable of modification in various respects[; a]ccordingly, the drawings and description are to be regarded as illustrative in nature and not as restrictive" col. 3 ln. 29 - col. 3 ln. 39, or "[a]lthough the invention has been described with reference to the embodiments illustrated in the attached drawing figures, it is noted that equivalents may be employed and substitutions made herein without departing from the scope of the invention as recited in the claims". (BERNICO-A: col. 18 lns. 7-11).
Claim 26, EXAMINER's Analysis: Claim 26 is rejected as being unpatentable over BERNICO-Claims and BERNICO-A. Claim 26 is a dependent claim that directly depends upon parent claim 21, which is an independent claim. Further to and in conjunction with the disclosures and teachings of the prior art recited in the parent as applied to the limitations of claim 21, the combined disclosures and teachings of BERNICO-Claims and BERNICO-A taken together render obvious the claimed subject matter of claim 26 as follows and as explained below.
Regarding and as per CLAIM 26, the system as set forth in claim 21,
• 26 ¶ 2 • wherein the processor employs a convolutional neural network including a plurality of receptive fields which are tiled to overlap. Line Comment: (BERNICO-Claims: doesn't expressly and explicitly recite wherein the processor employs a convolutional neural network including a plurality of receptive fields which are tiled to overlap --- however BERNICO-A: clearly discloses, teaches, and/or suggests the feature -- "wherein the processor employs a neural network" Claim 11 and "[t]he system as set forth in claim 11, wherein the neural network is a convolutional neural network" Claim 13 and "employ a neural network, which may be a convolutional neural network (CNN)[; a] CNN is a type of feed-forward neural network often used in facial recognition systems, in which individual neurons may be tiled so as to respond to overlapping regions in the visual field[; a] CNN may include multiple layers of small neuron collections which examine small portions of an input image, called receptive fields[; t]he results of these collections may be tiled so that they overlap to better represent the original image, and this may be repeated for each layer" col. 5 ln. 22 - col. 5 ln. 40); [See Remarks Below];
With respect to above-noted claimed element the above "wherein the processor..." line limitation which is disclosed by BERNICO-A: the teachings and/or suggestions within the disclosure of BERNICO-Claims thus far relied upon fails to include within its writings an explicit and express recitation of the above "wherein the processor..." line limitation as recited in the claim under examination. However, herein relied upon are portions of the disclosure of BERNICO-A which sufficiently teaches the feature apposite to the claimed invention as commented about above with citation(s) to exemplary disclosures within BERNICO-A that teach and/or suggest the claimed feature. At the time of effective filing date, it would have been obvious for one of ordinary skill in the art to have modified the relied upon teachings of BERNICO-Claims by adding or substituting the feature the above "wherein the processor..." line limitation as taught and/or suggested by BERNICO-A, with a reasonable expectation of success of arriving at the claimed invention. The addition or substitution of this known feature by one of ordinary skill in the art at the time of the effective filing date would have yielded predictable results that were readily ascertainable to that one person of ordinary skill in the art at that time. At the time of the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to have modified the teachings of BERNICO-Claims with these aforementioned teachings of the above "wherein the processor..." line limitation sufficiently taught, suggested, and/or disclosed in BERNICO-A because that one artisan of skill having ordinary skill in the art at the time of the effective filing date of the invention would have had a motivation of "[a]dvantages of these and other embodiments will become more apparent to those skilled in the art from the following description of the exemplary embodiments which have been shown and described by way of illustration[; a]s will be realized, the present embodiments described herein may be capable of other and different embodiments, and their details are capable of modification in various respects[; a]ccordingly, the drawings and description are to be regarded as illustrative in nature and not as restrictive" col. 3 ln. 29 - col. 3 ln. 39, or "[a]lthough the invention has been described with reference to the embodiments illustrated in the attached drawing figures, it is noted that equivalents may be employed and substitutions made herein without departing from the scope of the invention as recited in the claims". (BERNICO-A: col. 18 lns. 7-11).
Claim 28, EXAMINER's Analysis: Claim 28 is rejected as being unpatentable over BERNICO-Claims and BERNICO-A. Claim 28 is a dependent claim that directly depends upon parent claim 21, which is an independent claim. Further to and in conjunction with the disclosures and teachings of the prior art recited in the parent as applied to the limitations of claim 21, the combined disclosures and teachings of BERNICO-Claims and BERNICO-A taken together render obvious the claimed subject matter of claim 28 as follows and as explained below.
Regarding and as per CLAIM 28, the system as set forth in claim 21,
• 28 ¶ 2 • wherein the image data of the applicant includes a video of the applicant, the processor being configured to determine at least one of a pulse, drug use, or a glucose level of the applicant by analyzing the video. Line Comment: (BERNICO-Claims: doesn't expressly and explicitly recite wherein the image data of the applicant includes a video of the applicant, the processor being configured to determine at least one of a pulse, drug use, or a glucose level of the applicant by analyzing the video --- however BERNICO-A: clearly discloses, teaches, and/or suggests the feature -- "the video may be used to calculate the applicant's pulse, and could evolve to detect medications or drug use through eye movements, and lead to other information such as glucose levels" col. 8 ln. 32 - col. 8 ln. 45 and "analyzing the [] video" col. 10 lns. 6-18, col. 10 ln. 37 - col. 10 ln. 45); [See Remarks Below];
With respect to above-noted claimed element the above "wherein the image data..." line limitation which is disclosed by BERNICO-A: the teachings and/or suggestions within the disclosure of BERNICO-Claims thus far relied upon does not mention within its descriptions an explicit and express recital of the above "wherein the image data..." line limitation as required by the claim being considered. Notwithstanding the foregoing, herein relied upon are portions of the disclosure of BERNICO-A which sufficiently teaches the feature applicable to the claimed invention as annotated above with citation(s) to exemplary disclosures within BERNICO-A that teach and/or suggest the claimed feature. At the time of effective filing date, it would have been obvious for one of ordinary skill in the art to have modified the relied upon teachings of BERNICO-Claims by adding or substituting the feature the above "wherein the image data..." line limitation as taught and/or suggested by BERNICO-A, with a reasonable expectation of success of arriving at the claimed invention. The addition or substitution of this known feature by one of ordinary skill in the art at the time of the effective filing date would have yielded predictable results that were easily discernable to that ordinarily skilled one person in the art at that time. At the time of the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to have modified the teachings of BERNICO-Claims with these previously described teachings of the above "wherein the image data..." line limitation sufficiently taught, suggested, and/or disclosed in BERNICO-A because that one skilled artisan having ordinary skill in the art at the time of the effective filing date of the invention would have had a motivation of "[a]dvantages of these and other embodiments will become more apparent to those skilled in the art from the following description of the exemplary embodiments which have been shown and described by way of illustration[; a]s will be realized, the present embodiments described herein may be capable of other and different embodiments, and their details are capable of modification in various respects[; a]ccordingly, the drawings and description are to be regarded as illustrative in nature and not as restrictive" col. 3 ln. 29 - col. 3 ln. 39, or "[a]lthough the invention has been described with reference to the embodiments illustrated in the attached drawing figures, it is noted that equivalents may be employed and substitutions made herein without departing from the scope of the invention as recited in the claims". (BERNICO-A: col. 18 lns. 7-11).
Claim 35, EXAMINER's Analysis: Claim 35 is rejected as being unpatentable over BERNICO-Claims and BERNICO-A. Claim 35 is a dependent claim that directly depends upon parent claim 32, which is an independent claim. Further to and in conjunction with the disclosures and teachings of the prior art recited in the parent as applied to the limitations of claim 32, the combined disclosures and teachings of BERNICO-Claims and BERNICO-A taken together render obvious the claimed subject matter of claim 35 as follows and as explained below.
Regarding and as per CLAIM 35, the system as set forth in claim 32
• 35 ¶ 2 • wherein the neural network is a convolutional neural network including a plurality of receptive fields which are tiled to overlap. Line Comment: (BERNICO-Claims: doesn't expressly and explicitly recite wherein the neural network is a convolutional neural network including a plurality of receptive fields which are tiled to overlap --- however BERNICO-A: clearly discloses, teaches, and/or suggests the feature -- "wherein the neural network is a convolutional neural network" Claim 13 and "employ a neural network, which may be a convolutional neural network (CNN)[; a] CNN is a type of feed-forward neural network often used in facial recognition systems, in which individual neurons may be tiled so as to respond to overlapping regions in the visual field[; a] CNN may include multiple layers of small neuron collections which examine small portions of an input image, called receptive fields[; t]he results of these collections may be tiled so that they overlap to better represent the original image, and this may be repeated for each layer" col. 5 ln. 22 - col. 5 ln. 40); [See Remarks Below];
With respect to above-noted claimed element the above "wherein the neural network..." line limitation which is disclosed by BERNICO-A: the teachings and/or suggestions within the disclosure of BERNICO-Claims thus far relied upon does not include within its writings the reciting explicitly and expressly of the above "wherein the neural network..." line limitation as presented within the claim being considered. Nonetheless, herein relied upon are portions of the disclosure of BERNICO-A which sufficiently teaches the feature apposite to the claimed invention as commented about above with reference(s) to exemplary disclosures within BERNICO-A that teach and/or suggest the claimed feature. At the time of effective filing date, it would have been obvious for one of ordinary skill in the art to have modified the relied upon teachings of BERNICO-Claims by adding or substituting the feature the above "wherein the neural network..." line limitation as taught and/or suggested by BERNICO-A, with a reasonable expectation of success of arriving at the claimed invention. The addition or substitution of this known feature by one of ordinary skill in the art at the time of the effective filing date would have yielded predictable results that were plainly ascertainable to that one person of ordinary skill in the art at that time. At the time of the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to have modified the teachings of BERNICO-Claims with these above-described teachings of the above "wherein the neural network..." line limitation sufficiently taught, suggested, and/or disclosed in BERNICO-A because that one skilled artisan having ordinary skill in the art at the time of the effective filing date of the invention would have had a motivation of "[a]dvantages of these and other embodiments will become more apparent to those skilled in the art from the following description of the exemplary embodiments which have been shown and described by way of illustration[; a]s will be realized, the present embodiments described herein may be capable of other and different embodiments, and their details are capable of modification in various respects[; a]ccordingly, the drawings and description are to be regarded as illustrative in nature and not as restrictive" col. 3 ln. 29 - col. 3 ln. 39, or "[a]lthough the invention has been described with reference to the embodiments illustrated in the attached drawing figures, it is noted that equivalents may be employed and substitutions made herein without departing from the scope of the invention as recited in the claims". (BERNICO-A: col. 18 lns. 7-11).
Claim 37, EXAMINER's Analysis: Claim 37 is rejected as being unpatentable over BERNICO-Claims and BERNICO-A. Claim 37 is a dependent claim that directly depends upon parent claim 32, which is an independent claim. Further to and in conjunction with the disclosures and teachings of the prior art recited in the parent as applied to the limitations of claim 32, the combined disclosures and teachings of BERNICO-Claims and BERNICO-A taken together render obvious the claimed subject matter of claim 37 as follows and as explained below.
Regarding and as per CLAIM 37, the system as set forth in claim 32
• 37 ¶ 2 • wherein the otherwise non-diagnostic conventional image data of the applicant includes a video of the applicant, the processor being configured to determine at least one of a pulse, drug use, or a glucose level of the applicant by analyzing the video. Line Comment: (BERNICO-Claims: doesn't expressly and explicitly recite wherein the otherwise non-diagnostic conventional image data of the applicant includes a video of the applicant, the processor being configured to determine at least one of a pulse, drug use, or a glucose level of the applicant by analyzing the video --- however BERNICO-A: clearly discloses, teaches, and/or suggests the feature -- "otherwise non-diagnostic conventional [] image" Claims 7, 17 and "the video may be used to calculate the applicant's pulse, and could evolve to detect medications or drug use through eye movements, and lead to other information such as glucose levels" col. 8 ln. 32 - col. 8 ln. 45 and "analyzing the [] video" col. 10 lns. 6-18, col. 10 ln. 37 - col. 10 ln. 45); [See Remarks Below];
With respect to above-noted claimed element the above "wherein the otherwise..." line limitation which is disclosed by BERNICO-A: the teachings and/or suggestions within the disclosure of BERNICO-Claims thus far relied upon omits to record within its explanations an explicit and express recitation of the above "wherein the otherwise..." line limitation as recited in the instant claim. However, herein relied upon are portions of the disclosure of BERNICO-A which sufficiently teaches the feature appurtenant to the claimed invention as annotated above with reference(s) to exemplary disclosures within BERNICO-A that teach and/or suggest the claimed feature. At the time of effective filing date, it would have been obvious for one of ordinary skill in the art to have modified the relied upon teachings of BERNICO-Claims by adding or substituting the feature the above "wherein the otherwise..." line limitation as taught and/or suggested by BERNICO-A, with a reasonable expectation of success of arriving at the claimed invention. The addition or substitution of this known feature by one of ordinary skill in the art at the time of the effective filing date would have yielded predictable results that were easily foreseeable to that one person of ordinary skill in the art at that time. At the time of the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to have modified the teachings of BERNICO-Claims with these above-described teachings of the above "wherein the otherwise..." line limitation sufficiently taught, suggested, and/or disclosed in BERNICO-A because that skilled one artisan having ordinary skill in the art at the time of the effective filing date of the invention would have had a motivation of "[a]dvantages of these and other embodiments will become more apparent to those skilled in the art from the following description of the exemplary embodiments which have been shown and described by way of illustration[; a]s will be realized, the present embodiments described herein may be capable of other and different embodiments, and their details are capable of modification in various respects[; a]ccordingly, the drawings and description are to be regarded as illustrative in nature and not as restrictive" col. 3 ln. 29 - col. 3 ln. 39, or "[a]lthough the invention has been described with reference to the embodiments illustrated in the attached drawing figures, it is noted that equivalents may be employed and substitutions made herein without departing from the scope of the invention as recited in the claims". (BERNICO-A: col. 18 lns. 7-11).
Claim 39, EXAMINER's Analysis: Claim 39 is rejected as being unpatentable over BERNICO-Claims and BERNICO-A. Claim 39 is an independent claim. The combined disclosures and teachings of BERNICO-Claims and BERNICO-A taken together render obvious the claimed subject matter of claim 39 as follows and as explained below.
Regarding and as per CLAIM 39, a method for evaluating an applicant to determine one or more terms of insurance coverage, comprising: Line Comment: (BERNICO-Claims: doesn't expressly and explicitly recite a method for evaluating an applicant to determine one or more terms of insurance coverage, comprising --- however BERNICO-A: clearly discloses, teaches, and/or suggests the feature -- "method for evaluating an [] applicant" Abstract, col. 2 lns. 12-31, col. 11 lns. 8-25, col. 11 ln. 34 - col. 11 ln. 57, and "for evaluating an [] applicant [] to determine one or more terms of insurance coverage, [] comprising:" Claim 1); [See Remarks Below];
With respect to above-noted claimed element the above "a method..." line limitation which is disclosed by BERNICO-A: the teachings and/or suggestions within the disclosure of BERNICO-Claims thus far relied upon omits to record within its writings an explicit and express recital of the above "a method..." line limitation as required by the instant claim. Notwithstanding the foregoing, herein relied upon are portions of the disclosure of BERNICO-A which sufficiently teaches the feature applicable to the claimed invention as pointed out above with quotation(s) of exemplary disclosures within BERNICO-A that teach and/or suggest the claimed feature. At the time of effective filing date, it would have been obvious for one of ordinary skill in the art to have modified the relied upon teachings of BERNICO-Claims by adding or substituting the feature the above "a method..." line limitation as taught and/or suggested by BERNICO-A, with a reasonable expectation of success of arriving at the claimed invention. The addition or substitution of this known feature by one of ordinary skill in the art at the time of the effective filing date would have yielded predictable results that were readily reckonable to that ordinarily skilled one person in the art at that time. At the time of the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to have modified the teachings of BERNICO-Claims with these previously described teachings of the above "a method..." line limitation sufficiently taught, suggested, and/or disclosed in BERNICO-A because that one artisan of skill having ordinary skill in the art at the time of the effective filing date of the invention would have had a motivation of "[a]dvantages of these and other embodiments will become more apparent to those skilled in the art from the following description of the exemplary embodiments which have been shown and described by way of illustration[; a]s will be realized, the present embodiments described herein may be capable of other and different embodiments, and their details are capable of modification in various respects[; a]ccordingly, the drawings and description are to be regarded as illustrative in nature and not as restrictive" col. 3 ln. 29 - col. 3 ln. 39, or "[a]lthough the invention has been described with reference to the embodiments illustrated in the attached drawing figures, it is noted that equivalents may be employed and substitutions made herein without departing from the scope of the invention as recited in the claims". (BERNICO-A: col. 18 lns. 7-11).
• 39 ¶ 2 • receiving, by a data receiving circuit, image data of the applicant; Line Comment: (BERNICO-Claims: discloses "a data receiving circuit configured to receive [] image [] data of the [] applicant" Claim 1)
• 39 ¶ 3 • training a processor to correlate aspects of appearance with a personal and/or health-related characteristic by providing the processor with image data of individuals having known personal and/or health-related characteristics; Line Comment: (BERNICO-Claims: discloses "trained to correlate aspects of appearance [] with a personal and/or health-related characteristic by being provided with [] moving image and audio data of individuals having known personal and/or health-related characteristics" Claim 1 and "wherein training the processor is trained" Claim 10)
• 39 ¶ 4 • analyzing, by the processor, the image data of the applicant to determine a personal and/or health-related characteristic of the applicant; and Line Comment: (BERNICO-Claims: discloses "processor [] to analyze the moving image and audio data of the insurance applicant to determine the personal and/or health-related characteristic for the insurance applicant" Claim 1)
• 39 ¶ 5 • suggesting, by the processor, a term of insurance coverage based at least in part upon the determined personal and/or health-related characteristic. Line Comment: (BERNICO-Claims: discloses "processor [] to suggest a term of insurance coverage based at least in part on the determined personal and/or health-related characteristic" Claim 1)
Claim 40, EXAMINER's Analysis: Claim 40 is rejected as being unpatentable over BERNICO-Claims and BERNICO-A. Claim 40 is a dependent claim that directly depends upon parent claim 39, which is an independent claim. Further to and in conjunction with the disclosures and teachings of the prior art recited in the parent as applied to the limitations of claim 39, BERNICO-Claims discloses the claimed subject matter of claim 40 as follows and as explained below.
Regarding and as per CLAIM 40, the method as set forth in claim 39,
• 40 ¶ 2 • wherein the term of insurance coverage includes an insurance premium or discount. Line Comment: (BERNICO-Claims: See Prior Comment at Claim 23 Par. 2)
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 21-40 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Claims 21-40 are directed to the abstract idea of: Claim 21 -: 21. A system for evaluating an applicant to determine one or more terms of insurance coverage, comprising: a receiving configured to receive image of the applicant; and a -processor trained to correlate aspects of appearance with a personal and/or health-related characteristic by being provided with image of individuals having known personal and/or health-related characteristics; wherein the -processor analyzes the image of the applicant to determine a personal and/or health-related characteristic of the applicant, and to suggest a term of insurance coverage based at least in part upon the determined personal and/or health-related characteristic. (fundamental economic principles or practices, commercial or legal interactions, managing personal behavior or relationships or interactions between people, concepts performed in the human mind, (including an observation, evaluation, judgment, opinion). ) Claim 22 -: 22. The system as set forth in claim 21, wherein the insurance coverage is health insurance. Claim 23 -: 23. The system as set forth in claim 21, wherein the term of insurance coverage includes an insurance premium or discount. Claim 24 -: 24. The system as set forth in claim 21, wherein the image of the applicant includes an image. Claim 25 -: 25. The system as set forth in claim 21, wherein the image of the applicant includes a selfie. Claim 26 -: 26. The system as set forth in claim 21, wherein the -processor employs neural receptive fields to overlap. Claim 27 -: 27. The system as set forth in claim 21, wherein the -processor employs a deep learning. Claim 28 -: 28. The system as set forth in claim 21, wherein the image of the applicant includes a -video of the applicant, the -processor being configured to determine at least one of a pulse, drug use, or a glucose level of the applicant by analyzing the -video. Claim 29 -: 29. The system as set forth in claim 21, wherein the personal and/or health-related characteristic is at least one of age, sex, weight, height, ethnicity, lifespan, cause of death, tobacco use, alcohol use, drug use, diet, existing medical conditions, or risk factors for future medical conditions. Claim 30 -: 30. The system as set forth in claim 21, wherein the -processor is further configured to use the determined personal and/or health-related characteristic to verify information provided by the applicant. Claim 31 -: 31. The system as set forth in claim 21, wherein the -processor is further configured to use the determined personal and/or health-related characteristic to substantially determine the term of insurance coverage. (fundamental economic principles or practices, commercial or legal interactions, managing personal behavior or relationships or interactions between people, concepts performed in the human mind, (including an observation, evaluation, judgment, opinion). ) Claim 32 -: 32. A system for evaluating an applicant to determine a life insurance premium, comprising: a receiving configured to receive otherwise non-diagnostic conventional image of the applicant; and a -processor employing and trained to correlate one or more aspects of appearance with a personal and/or health-related characteristic by being provided with otherwise non-diagnostic conventional image of individuals having known personal and/or health-related characteristics; wherein the -processor analyzes the otherwise non-diagnostic conventional image of the applicant to determine a personal and/or health-related characteristic of the applicant, to use the determined personal and/or health-related characteristic to verify information provided by the applicant, and to substantially determine the life insurance premium based at least in part upon the determined personal and/or health-related characteristic. (fundamental economic principles or practices, commercial or legal interactions, managing personal behavior or relationships or interactions between people, concepts performed in the human mind, (including an observation, evaluation, judgment, opinion). ) Claim 33 -: 33. The system as set forth in claim 32, wherein the otherwise non-diagnostic conventional image of the applicant includes an image. Claim 34 -: 34. The system as set forth in claim 32, wherein the otherwise non-diagnostic conventional image of the applicant includes a selfie. Claim 35 -: 35. The system as set forth in claim 32: wherein neural receptive fields to overlap. Claim 36 -: 36. The system as set forth in claim 32, wherein a deep learning. Claim 37 -: 37. The system as set forth in claim 32: wherein the otherwise non-diagnostic conventional image of the applicant includes a -video of the applicant, the -processor being configured to determine at least one of a pulse, drug use, or a glucose level of the applicant by analyzing the -video. Claim 38 -: 38. The system as set forth in claim 32, wherein the personal... [id. at 29], (fundamental economic principles or practices, commercial or legal interactions, managing personal behavior or relationships or interactions between people, concepts performed in the human mind, (including an observation, evaluation, judgment, opinion). ) Claim 39 -: 39. A method for evaluating an applicant to determine one or more terms of insurance coverage, comprising: receiving, by a receiving, image of the applicant; training a -processor to correlate aspects of appearance with a personal and/or health-related characteristic by providing the -processor with image of individuals having known personal and/or health-related characteristics; analyzing, by the -processor, the image of the applicant to determine a personal and/or health-related characteristic of the applicant; and suggesting, by the -processor, a term of insurance coverage based at least in part upon the determined personal and/or health-related characteristic. (fundamental economic principles or practices, commercial or legal interactions, managing personal behavior or relationships or interactions between people, concepts performed in the human mind, (including an observation, evaluation, judgment, opinion). ) Claim 40 -: 40. The method as set forth in claim 39, wherein the term... [id. at 23], (fundamental economic principles or practices, commercial or legal interactions, managing personal behavior or relationships or interactions between people, concepts performed in the human mind, (including an observation, evaluation, judgment, opinion). ) . The identified limitation(s) falls within the subject matter groupings of abstract ideas enumerated in Section I of the 2019 Revised Patent Subject Matter Eligibility Guidance: b) Certain methods of organizing human activity – fundamental economic principles or practices, commercial or legal interactions, managing personal behavior or relationships or interactions between people, c) Mental processes – concepts performed in the human mind, (including an observation, evaluation, judgment, opinion).
These limitation excerpts, under their broadest reasonable interpretation, fall within the grouping(s) of abstract ideas of: Certain methods of organizing human activity – since: using images and voice recordings to facilitate underwriting life insurance as recited in the claim limitations, under their broadest reasonable interpretation, covers performance of the limitation(s) as fundamental economic principles or practices, (including hedging, insurance, mitigating risk); commercial or legal interactions, (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people, (including social activities, teaching, and following rules or instructions). Mental processes – since: the above-underlined as recited in the claim limitations, under their broadest reasonable interpretation, covers performance of the limitation(s) as concepts performed in the human mind, (including an observation, evaluation, judgment, opinion). Therefore, the limitations fall within the above-identified grouping(s) of abstract ideas.
While independent claims 21, 32, and 39 do not explicitly recite verbatim this identified abstract idea, the concept of this identified abstract idea is described by the steps of independent claim 21 and is described by the steps of independent claim 32 and is described by the steps of independent claim 39.
Claim 21: Specifically pertaining to the analysis under Step 2A of the Office's § 101 Subject Matter Eligibility Test for Products and Processes, independent claim 21 further to the abstract idea includes additional elements of "data", "circuit", "a processor", and "the processor". However, independent claim 21 does not include additional elements that are sufficient to integrate the exception into a practical application because "data", "circuit", "a processor", and "the processor" of independent claim 21 recite generic computer and/or field of use components pertaining to the particular technological environment that are recited a high-level of generality that perform functions ("A system for evaluating an … of insurance coverage, comprising", "a data receiving circuit configured … of the applicant; and", "a processor trained to correlate … personal and/or health-related characteristics" and "wherein the processor analyzes the … personal and/or health-related characteristic") that merely perform, conduct, carry out, implement, and/or narrow the abstract idea itself [Step 2A Prong I] (e.g. all or portion(s) of the noted recited steps) and/or that recite generic computer and/or field of use functions that are recited at a high-level of generality and/or because the additional method steps comprise or include: evaluated additional elements individually and in combination for which the courts have identified examples in which a judicial exception has not been integrated into a practical application, [Step 2A Prong II] adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea -- see MPEP 2106.05(f) (all or portions of the noted step(s)), and generally linking the use of the judicial exception to a particular technological environment or field of use -- see MPEP 2106.05(h) (all or portions of the noted step(s)). Regarding Step 2B treatment of the evaluated additional elements individually and in combination, the additional elements do not amount to more than a recitation of the words "apply it" (or an equivalent) or are not more than mere instructions to implement an abstract idea or other exception on a computer, and the additional elements do not amount to more than generally linking the use of a judicial exception to a particular technological environment or field of use. None of the additional elements taken individually or when taken as an ordered combination amount to significantly more than the abstract idea. Accordingly, independent claim 21 is ineligible.
Claim 32: Particularly regarding the analysis under Step 2A of the Office's § 101 Subject Matter Eligibility Test for Products and Processes, independent claim 32 further to the abstract idea includes additional elements of "data", "circuit", "a processor", "a neural network", "the processor", and "automatically". However, independent claim 32 does not include additional elements that are sufficient to integrate the exception into a practical application because "data", "circuit", "a processor", "a neural network", "the processor", and "automatically" of independent claim 32 recite generic computer and/or field of use components pertaining to the particular technological environment that are recited a high-level of generality that perform functions ("A system for evaluating an … life insurance premium, comprising", "a data receiving circuit configured … of the applicant; and", "a processor employing a neural … personal and/or health-related characteristics" and "wherein the processor analyzes the … personal and/or health-related characteristic") that merely perform, conduct, carry out, implement, and/or narrow the abstract idea itself (e.g. all or portion(s) of the noted recited steps) and/or that recite generic computer and/or field of use functions that are recited at a high-level of generality that include only steps narrowing the abstract idea [Step 2A Prong I] (e.g. all or portion(s) of the noted recited steps) and/or because the additional method steps comprise or include: evaluated additional elements individually and in combination for which the courts have identified examples in which a judicial exception has not been integrated into a practical application, [Step 2A Prong II] adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea -- see MPEP 2106.05(f) (all or portions of the noted step(s)), and adding insignificant extra-solution activity to the judicial exception -- see MPEP 2106.05(g) (all or portions of the "a processor employing a neural … personal and/or health-related characteristics", "wherein the processor analyzes the … personal and/or health-related characteristic" step(s)), and generally linking the use of the judicial exception to a particular technological environment or field of use -- see MPEP 2106.05(h) (all or portions of the noted step(s)). Regarding Step 2B treatment of the evaluated additional elements individually and in combination, the additional elements do not amount to more than a recitation of the words "apply it" (or an equivalent) or are not more than mere instructions to implement an abstract idea or other exception on a computer, and the additional elements do not add more than insignificant extra-solution activity to the judicial exception, and the additional elements do not amount to more than generally linking the use of a judicial exception to a particular technological environment or field of use. Moreover, the additional method steps comprise or include: reciting additional elements in implementing the abstract idea that do not constitute significantly more than the abstract idea because they comprise or include well-understood, routine, and conventional activities previously known to the industry (e.g. all or portion(s) of the "a processor employing a neural … personal and/or health-related characteristics", "wherein the processor analyzes the … personal and/or health-related characteristic", (insignificant extra-solution activity) steps), see Alice Corp., 134 S. Ct. at 2360, and/or that are otherwise not significant toward constituting any inventive concept beyond the abstract idea. (E.g. The above-italicized grounds of rejection apply at least to all or portion(s) of the noted recited steps.) For example regarding well-understood, routine, and conventional activities, the cited rationale have recognized the following computer function as well-understood, routine, and conventional functions when it is claimed or as insignificant extra-solution activity: receiving or transmitting data over a network, e.g., using the Internet to gather data, Intellectual Ventures I v. Symantec Corp., 838 F.3d at 1321, 120 USPQ2d at 1362 (2016) (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); and the cited rationale have found the following type of activity to be well-understood, routine, and conventional activity when it is claimed or as insignificant extra-solution activity: presenting offers and gathering statistics, OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d at 1362-63, 115 USPQ2d at 1092-93 (Fed. Cir. 2015), determining an estimated outcome and setting a price, OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d at 1362-63, 115 USPQ2d at 1092-93 (Fed. Cir. 2015), and arranging a hierarchy of groups, sorting information, eliminating less restrictive pricing information and determining the price, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1331, 115 USPQ2d 1681, 1699 (Fed. Cir. 2015). None of the additional elements taken individually or when taken as an ordered combination amount to significantly more than the abstract idea. Accordingly, independent claim 32 is ineligible.
Claim 39: Materially regarding the analysis under Step 2A of the Office's § 101 Subject Matter Eligibility Test for Products and Processes, independent claim 39 further to the abstract idea includes additional elements of "data", "circuit", "a processor", and "the processor". However, independent claim 39 does not include additional elements that are sufficient to integrate the exception into a practical application because "data", "circuit", "a processor", and "the processor" of independent claim 39 recite generic computer and/or field of use components pertaining to the particular technological environment that are recited a high-level of generality that perform functions ("A method for evaluating an … of insurance coverage, comprising", "receiving, by a data receiving … data of the applicant", "training a processor to correlate … personal and/or health-related characteristics", "analyzing, by the processor, the … of the applicant; and" and "suggesting, by the processor, a … personal and/or health-related characteristic") that merely perform, conduct, carry out, implement, and/or narrow the abstract idea itself [Step 2A Prong I] (e.g. all or portion(s) of the noted recited steps) and/or that recite generic computer and/or field of use functions that are recited at a high-level of generality and/or because the additional method steps comprise or include: evaluated additional elements individually and in combination for which the courts have identified examples in which a judicial exception has not been integrated into a practical application, [Step 2A Prong II] adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea -- see MPEP 2106.05(f) (all or portions of the noted step(s)), and generally linking the use of the judicial exception to a particular technological environment or field of use -- see MPEP 2106.05(h) (all or portions of the noted step(s)). Regarding Step 2B treatment of the evaluated additional elements individually and in combination, the same previously-stated legal authority and/or rationale supporting the grounds of rejection applied to the above Claim 21 also applies hereto. None of the additional elements taken individually or when taken as an ordered combination amount to significantly more than the abstract idea. Accordingly, independent claim 39 is ineligible.
Independent Claims: Nothing in independent claims 21, 32, and 39 improves another technology or technical field, improves the functioning of any claimed computer device itself, applies the abstract idea with any particular machine, solves any computer problem with a computer solution, or includes any element that may otherwise be considered to amount to significantly more than the abstract idea.
None of the dependent claims 22-31, 33-38, and 40 when separately considered with each dependent claim's corresponding parent claim overcomes the above analysis because none presents any method step not directed to the abstract idea that amounts to significantly more than the judicial exception or any physical structure that amounts to significantly more than the judicial exception.
Claims 24 and 33: Dependent claims 24 and 33 do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, "digital" of dependent claims 24 and 33 recite generic computer and/or field of use components pertaining to the particular technological environment that are recited a high-level of generality. No additional element introduced in these claims taken individually or when taken as an ordered combination amounts to significantly more than the abstract idea.
Claim 26: Dependent claim 26 does not include additional elements that are sufficient to amount to significantly more than the judicial exception because, "a convolutional neural network including a plurality of receptive fields which are tiled to overlap" of dependent claim 26 recite generic computer and/or field of use components pertaining to the particular technological environment that are recited a high-level of generality. No additional element introduced in this claim taken individually or when taken as an ordered combination amounts to significantly more than the abstract idea.
Claim 27: Dependent claim 27 does not include additional elements that are sufficient to amount to significantly more than the judicial exception because, "deep learning neural network" of dependent claim 27 recite generic computer and/or field of use components pertaining to the particular technological environment that are recited a high-level of generality. No additional element introduced in this claim taken individually or when taken as an ordered combination amounts to significantly more than the abstract idea.
Claims 28 and 37: Dependent claims 28 and 37 do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, "a video", and "the video" of dependent claims 28 and 37 recite generic computer and/or field of use components pertaining to the particular technological environment that are recited a high-level of generality. No additional element introduced in these claims taken individually or when taken as an ordered combination amounts to significantly more than the abstract idea.
Claim 31: Dependent claim 31 does not include additional elements that are sufficient to amount to significantly more than the judicial exception because, "automatically" of dependent claim 31 recite generic computer and/or field of use components pertaining to the particular technological environment that are recited a high-level of generality. No additional element introduced in this claim taken individually or when taken as an ordered combination amounts to significantly more than the abstract idea.
Claim 35: Dependent claim 35 does not include additional elements that are sufficient to amount to significantly more than the judicial exception because, "the neural network", and "a convolutional neural network including a plurality of receptive fields which are tiled to overlap" of dependent claim 35 recite generic computer and/or field of use components pertaining to the particular technological environment that are recited a high-level of generality. No additional element introduced in this claim taken individually or when taken as an ordered combination amounts to significantly more than the abstract idea.
Claim 36: Dependent claim 36 does not include additional elements that are sufficient to amount to significantly more than the judicial exception because, "the neural network", and "deep learning neural network" of dependent claim 36 recite generic computer and/or field of use components pertaining to the particular technological environment that are recited a high-level of generality. No additional element introduced in this claim taken individually or when taken as an ordered combination amounts to significantly more than the abstract idea.
Claim 22: Dependent claim 22 adds an additional method step of "wherein the insurance coverage is health insurance". However, the additional method step of dependent claims 22 is directed to the abstract idea noted above and does not otherwise alter the analysis presented above, and do not integrate the exception into a practical application, because the additional method step merely perform, conduct, carry out, and/or implement the abstract idea itself and/or only narrows the abstract idea (e.g. all or portion(s) of the noted recited step) and/or because the additional method step comprises or includes: evaluated additional elements individually and in combination for which the courts have identified examples in which a judicial exception has not been integrated into a practical application, as previously discussed regarding Claim 21 above. Regarding Step 2B treatment of the evaluated additional elements individually and in combination, the same previously-stated legal authority and/or rationale supporting the grounds of rejection applied to the above Claim 21 also applies hereto. (E.g. These previously-stated grounds of rejection that were italicized when applied to the referenced previous Claim(s) apply at least to all or portion(s) of the noted recited step.) No additional step introduced in this claim taken individually or when taken as an ordered combination amounts to significantly more than the abstract idea. Accordingly, dependent claim 22 is ineligible.
Claims 23 and 40: Dependent claims 23 and 40 add an additional method step of "wherein the term of insurance coverage includes an insurance premium or discount". However, the additional method step of dependent claim 23 and 40 is directed to the abstract idea noted above and does not otherwise alter the analysis presented above, and do not integrate the exception into a practical application, because the additional method step merely perform, conduct, carry out, and/or implement the abstract idea itself and/or only narrows the abstract idea (e.g. all or portion(s) of the noted recited step) and/or because the additional method step comprises or includes: evaluated additional elements individually and in combination for which the courts have identified examples in which a judicial exception has not been integrated into a practical application, as previously discussed regarding Claim 21 above. Regarding Step 2B treatment of the evaluated additional elements individually and in combination, the same previously-stated legal authority and/or rationale supporting the grounds of rejection applied to the above Claim 21 also applies hereto. (E.g. These previously-stated grounds of rejection that were italicized when applied to the referenced previous Claim(s) apply at least to all or portion(s) of the noted recited step.) No additional step introduced in this claim taken individually or when taken as an ordered combination amounts to significantly more than the abstract idea. Accordingly, dependent claims 23 and 40 are ineligible.
Claim 24: Dependent claim 24 adds an additional method step of "wherein the image data of the applicant includes a digital image". However, the additional method step of dependent claims 24 is directed to the abstract idea noted above and does not otherwise alter the analysis presented above, and do not integrate the exception into a practical application, because the additional method step merely perform, conduct, carry out, and/or implement the abstract idea itself and/or only narrows the abstract idea (e.g. all or portion(s) of the noted recited step) and/or because the additional method step comprises or includes: evaluated additional elements individually and in combination for which the courts have identified examples in which a judicial exception has not been integrated into a practical application, as previously discussed regarding Claim 21 above. Regarding Step 2B treatment of the evaluated additional elements individually and in combination, the same previously-stated legal authority and/or rationale supporting the grounds of rejection applied to the above Claim 21 also applies hereto. (E.g. These previously-stated grounds of rejection that were italicized when applied to the referenced previous Claim(s) apply at least to all or portion(s) of the noted recited step.) No additional step introduced in this claim taken individually or when taken as an ordered combination amounts to significantly more than the abstract idea. Accordingly, dependent claim 24 is ineligible.
Claim 25: Dependent claim 25 adds an additional method step of "wherein the image data of the applicant includes a selfie". However, the additional method step of dependent claims 25 is directed to the abstract idea noted above and does not otherwise alter the analysis presented above, and do not integrate the exception into a practical application, because the additional method step merely perform, conduct, carry out, and/or implement the abstract idea itself and/or only narrows the abstract idea (e.g. all or portion(s) of the noted recited step) and/or because the additional method step comprises or includes: evaluated additional elements individually and in combination for which the courts have identified examples in which a judicial exception has not been integrated into a practical application, as previously discussed regarding Claim 21 above. Regarding Step 2B treatment of the evaluated additional elements individually and in combination, the same previously-stated legal authority and/or rationale supporting the grounds of rejection applied to the above Claim 21 also applies hereto. (E.g. These previously-stated grounds of rejection that were italicized when applied to the referenced previous Claim(s) apply at least to all or portion(s) of the noted recited step.) No additional step introduced in this claim taken individually or when taken as an ordered combination amounts to significantly more than the abstract idea. Accordingly, dependent claim 25 is ineligible.
Claim 26: Dependent claim 26 adds an additional method step of "wherein the processor employs a convolutional neural network including a plurality of receptive fields which are tiled to overlap". However, the additional method step of dependent claims 26 is directed to the abstract idea noted above and does not otherwise alter the analysis presented above, and do not integrate the exception into a practical application, because the additional method step merely perform, conduct, carry out, and/or implement the abstract idea itself and/or only narrows the abstract idea (e.g. all or portion(s) of the noted recited step) and/or because the additional method step comprises or includes: evaluated additional elements individually and in combination for which the courts have identified examples in which a judicial exception has not been integrated into a practical application, as previously discussed regarding Claim 32 above. Regarding Step 2B, the additional elements do not amount to more than a recitation of the words "apply it" (or an equivalent) or are not more than mere instructions to implement an abstract idea or other exception on a computer, and the additional elements do not add more than insignificant extra-solution activity to the judicial exception, and the additional elements do not amount to more than generally linking the use of a judicial exception to a particular technological environment or field of use. (E.g. The above-italicized grounds of rejection apply at least to all or portion(s) of the noted recited step.) For example regarding well-understood, routine, and conventional activities, the cited rationale have recognized the following computer function as well-understood, routine, and conventional functions when it is claimed or as insignificant extra-solution activity: receiving or transmitting data over a network, Intellectual Ventures I v. Symantec Corp., (2016); TLI Communications LLC v. AV Auto. LLC, (Fed. Cir. 2016); OIP Techs., Inc., v. Amazon.com, Inc., (Fed. Cir. 2015); buySAFE, Inc. v. Google, Inc., (Fed. Cir. 2014), see previous legal citations herein Re: Claim 32, and electronically scanning or extracting data from a physical document, Content Extraction and Transmission, LLC v. Wells Fargo Bank, 776 F.3d 1343, 1348, 113 USPQ2d 1354, 1358 (Fed. Cir. 2014) (optical character recognition); and the cited rationale have found the following type of activity to be well-understood, routine, and conventional activity when it is claimed or as insignificant extra-solution activity: identifying undeliverable mail items, decoding data on those mail items, and creating output data, Return Mail, Inc. v. U.S. Postal Service, -- F.3d --, -- USPQ2d --, slip op. at 32 (Fed. Cir. August 28, 2017), pertaining to all or portion(s) of the noted recited step. No additional step introduced in this claim taken individually or when taken as an ordered combination amounts to significantly more than the abstract idea. Accordingly, dependent claim 26 is ineligible.
Claim 27: Dependent claim 27 adds an additional method step of "wherein the processor employs a deep learning neural network". However, the additional method step of dependent claims 27 is directed to the abstract idea noted above and does not otherwise alter the analysis presented above, and do not integrate the exception into a practical application, because the additional method step merely perform, conduct, carry out, and/or implement the abstract idea itself and/or only narrows the abstract idea (e.g. all or portion(s) of the noted recited step) and/or because the additional method step comprises or includes: evaluated additional elements individually and in combination for which the courts have identified examples in which a judicial exception has not been integrated into a practical application, as previously discussed regarding Claim 32 above. Regarding Step 2B, the additional elements do not amount to more than a recitation of the words "apply it" (or an equivalent) or are not more than mere instructions to implement an abstract idea or other exception on a computer, and the additional elements do not add more than insignificant extra-solution activity to the judicial exception, and the additional elements do not amount to more than generally linking the use of a judicial exception to a particular technological environment or field of use. (E.g. The above-italicized grounds of rejection apply at least to all or portion(s) of the noted recited step.) For example regarding well-understood, routine, and conventional activities, the cited rationale have recognized the following computer function as well-understood, routine, and conventional functions when it is claimed or as insignificant extra-solution activity: receiving or transmitting data over a network, Intellectual Ventures I v. Symantec Corp., (2016); TLI Communications LLC v. AV Auto. LLC, (Fed. Cir. 2016); OIP Techs., Inc., v. Amazon.com, Inc., (Fed. Cir. 2015); buySAFE, Inc. v. Google, Inc., (Fed. Cir. 2014), see previous legal citations herein Re: Claim 32, pertaining to all or portion(s) of the noted recited step. No additional step introduced in this claim taken individually or when taken as an ordered combination amounts to significantly more than the abstract idea. Accordingly, dependent claim 27 is ineligible.
Claim 28: Dependent claim 28 adds an additional method step of "wherein the image data of the applicant includes a video of the applicant, the … drug use, or a glucose level of the applicant by analyzing the video". However, the additional method step of dependent claims 28 is directed to the abstract idea noted above and does not otherwise alter the analysis presented above, and do not integrate the exception into a practical application, because the additional method step merely perform, conduct, carry out, and/or implement the abstract idea itself and/or only narrows the abstract idea (e.g. all or portion(s) of the noted recited steps) and/or because the additional method step comprises or includes: evaluated additional elements individually and in combination for which the courts have identified examples in which a judicial exception has not been integrated into a practical application, as previously discussed regarding Claim 32 above. Regarding Step 2B, the additional elements do not amount to more than a recitation of the words "apply it" (or an equivalent) or are not more than mere instructions to implement an abstract idea or other exception on a computer, and the additional elements do not add more than insignificant extra-solution activity to the judicial exception, and the additional elements do not amount to more than generally linking the use of a judicial exception to a particular technological environment or field of use. (E.g. The above-italicized grounds of rejection apply at least to all or portion(s) of the noted recited steps.) For example regarding well-understood, routine, and conventional activities, the cited rationale have recognized the following computer function as well-understood, routine, and conventional functions when it is claimed or as insignificant extra-solution activity: electronic recordkeeping, Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 134 S. Ct. at 2359, 110 USPQ2d at 1984 (2014) (creating and maintaining "shadow accounts"); Ultramercial, Inc. v. Hulu, LLC, 772 F.3d at 716, 112 USPQ2d at 1755 (Fed. Cir. 2014) (updating an activity log); and the cited rationale have found the following type of activity to be well-understood, routine, and conventional activity when it is claimed or as insignificant extra-solution activity: recording a customer's order, Apple, Inc. v. Ameranth, Inc., 842 F.3d 1229, 1244, 120 USPQ2d 1844, 1856 (Fed. Cir. 2016), identifying undeliverable mail items, decoding data on those mail items, and creating output data, Return Mail, Inc. v. U.S. Postal Service, (Fed. Cir. 2017), see previous legal citation herein Re: Claim 26, and arranging a hierarchy of groups, sorting information, eliminating less restrictive pricing information and determining the price, Versata Dev. Group, Inc. v. SAP Am., Inc., (Fed. Cir. 2015), see previous legal citation herein Re: Claim 32, pertaining to all or portion(s) of the noted recited steps. No additional step introduced in this claim taken individually or when taken as an ordered combination amounts to significantly more than the abstract idea. Accordingly, dependent claim 28 is ineligible.
Claims 29 and 38: Dependent claims 29 and 38 add an additional method step of "wherein the personal and/or health-related characteristic is at least one of age, sex, weight, … drug use, diet, existing medical conditions, or risk factors for future medical conditions". However, the additional method step of dependent claim 29 and 38 is directed to the abstract idea noted above and does not otherwise alter the analysis presented above, and do not integrate the exception into a practical application, because the additional method step merely perform, conduct, carry out, and/or implement the abstract idea itself and/or only narrows the abstract idea (e.g. all or portion(s) of the noted recited steps) and/or because the additional method step comprises or includes: evaluated additional elements individually and in combination for which the courts have identified examples in which a judicial exception has not been integrated into a practical application, as previously discussed regarding Claim 21 above. Regarding Step 2B treatment of the evaluated additional elements individually and in combination, the same previously-stated legal authority and/or rationale supporting the grounds of rejection applied to the above Claim 21 also applies hereto. (E.g. These previously-stated grounds of rejection that were italicized when applied to the referenced previous Claim(s) apply at least to all or portion(s) of the noted recited steps.) No additional step introduced in this claim taken individually or when taken as an ordered combination amounts to significantly more than the abstract idea. Accordingly, dependent claims 29 and 38 are ineligible.
Claim 30: Dependent claim 30 adds an additional method step of "wherein the processor is further configured to use the determined personal and/or health-related characteristic to verify information provided by the applicant". However, the additional method step of dependent claims 30 is directed to the abstract idea noted above and does not otherwise alter the analysis presented above, and do not integrate the exception into a practical application, because the additional method step merely perform, conduct, carry out, and/or implement the abstract idea itself and/or only narrows the abstract idea (e.g. all or portion(s) of the noted recited step) and/or because the additional method step comprises or includes: evaluated additional elements individually and in combination for which the courts have identified examples in which a judicial exception has not been integrated into a practical application, as previously discussed regarding Claim 21 above. Regarding Step 2B treatment of the evaluated additional elements individually and in combination, the same previously-stated legal authority and/or rationale supporting the grounds of rejection applied to the above Claim 21 also applies hereto. (E.g. These previously-stated grounds of rejection that were italicized when applied to the referenced previous Claim(s) apply at least to all or portion(s) of the noted recited step.) No additional step introduced in this claim taken individually or when taken as an ordered combination amounts to significantly more than the abstract idea. Accordingly, dependent claim 30 is ineligible.
Claim 31: Dependent claim 31 adds an additional method step of "wherein the processor is further configured to use the determined personal and/or health-related characteristic to substantially automatically determine the term of insurance coverage". However, the additional method step of dependent claims 31 is directed to the abstract idea noted above and does not otherwise alter the analysis presented above, and do not integrate the exception into a practical application, because the additional method step merely perform, conduct, carry out, and/or implement the abstract idea itself and/or only narrows the abstract idea (e.g. all or portion(s) of the noted recited step) and/or because the additional method step comprises or includes: evaluated additional elements individually and in combination for which the courts have identified examples in which a judicial exception has not been integrated into a practical application, as previously discussed regarding Claim 21 above. Regarding Step 2B treatment of the evaluated additional elements individually and in combination, the same previously-stated legal authority and/or rationale supporting the grounds of rejection applied to the above Claim 21 also applies hereto. (E.g. These previously-stated grounds of rejection that were italicized when applied to the referenced previous Claim(s) apply at least to all or portion(s) of the noted recited step.) No additional step introduced in this claim taken individually or when taken as an ordered combination amounts to significantly more than the abstract idea. Accordingly, dependent claim 31 is ineligible.
Claim 33: Dependent claim 33 adds an additional method step of "wherein the otherwise non-diagnostic conventional image data of the applicant includes a digital image". However, the additional method step of dependent claims 33 is directed to the abstract idea noted above and does not otherwise alter the analysis presented above, and do not integrate the exception into a practical application, because the additional method step merely perform, conduct, carry out, and/or implement the abstract idea itself and/or only narrows the abstract idea (e.g. all or portion(s) of the noted recited step) and/or because the additional method step comprises or includes: evaluated additional elements individually and in combination for which the courts have identified examples in which a judicial exception has not been integrated into a practical application, as previously discussed regarding Claim 21 above. Regarding Step 2B treatment of the evaluated additional elements individually and in combination, the same previously-stated legal authority and/or rationale supporting the grounds of rejection applied to the above Claim 21 also applies hereto. (E.g. These previously-stated grounds of rejection that were italicized when applied to the referenced previous Claim(s) apply at least to all or portion(s) of the noted recited step.) No additional step introduced in this claim taken individually or when taken as an ordered combination amounts to significantly more than the abstract idea. Accordingly, dependent claim 33 is ineligible.
Claim 34: Dependent claim 34 adds an additional method step of "wherein the otherwise non-diagnostic conventional image data of the applicant includes a selfie". However, the additional method step of dependent claims 34 is directed to the abstract idea noted above and does not otherwise alter the analysis presented above, and do not integrate the exception into a practical application, because the additional method step merely perform, conduct, carry out, and/or implement the abstract idea itself and/or only narrows the abstract idea (e.g. all or portion(s) of the noted recited step) and/or because the additional method step comprises or includes: evaluated additional elements individually and in combination for which the courts have identified examples in which a judicial exception has not been integrated into a practical application, as previously discussed regarding Claim 21 above. Regarding Step 2B treatment of the evaluated additional elements individually and in combination, the same previously-stated legal authority and/or rationale supporting the grounds of rejection applied to the above Claim 21 also applies hereto. (E.g. These previously-stated grounds of rejection that were italicized when applied to the referenced previous Claim(s) apply at least to all or portion(s) of the noted recited step.) No additional step introduced in this claim taken individually or when taken as an ordered combination amounts to significantly more than the abstract idea. Accordingly, dependent claim 34 is ineligible.
Claim 35: Dependent claim 35 adds an additional method step of "wherein the neural network is a convolutional neural network including a plurality of receptive fields which are tiled to overlap". However, the additional method step of dependent claims 35 is directed to the abstract idea noted above and does not otherwise alter the analysis presented above, and do not integrate the exception into a practical application, because the additional method step merely perform, conduct, carry out, and/or implement the abstract idea itself and/or only narrows the abstract idea (e.g. all or portion(s) of the noted recited step) and/or because the additional method step comprises or includes: evaluated additional elements individually and in combination for which the courts have identified examples in which a judicial exception has not been integrated into a practical application, as previously discussed regarding Claim 32 above. Regarding Step 2B treatment of the evaluated additional elements individually and in combination, the same previously-stated legal authority and/or rationale supporting the grounds of rejection applied to the above Claim 26 also applies hereto. (E.g. These previously-stated grounds of rejection that were italicized when applied to the referenced previous Claim(s) apply at least to all or portion(s) of the noted recited step.) See discussion above regarding Claim 26 for pertinent previously cited rationale finding well-understood, routine, and conventional activities, pertaining to all or portion(s) of the noted recited step. No additional step introduced in this claim taken individually or when taken as an ordered combination amounts to significantly more than the abstract idea. Accordingly, dependent claim 35 is ineligible.
Claim 36: Dependent claim 36 adds an additional method step of "wherein the neural network is a deep learning neural network". However, the additional method step of dependent claims 36 is directed to the abstract idea noted above and does not otherwise alter the analysis presented above, and do not integrate the exception into a practical application, because the additional method step merely perform, conduct, carry out, and/or implement the abstract idea itself and/or only narrows the abstract idea (e.g. all or portion(s) of the noted recited step) and/or because the additional method step comprises or includes: evaluated additional elements individually and in combination for which the courts have identified examples in which a judicial exception has not been integrated into a practical application, as previously discussed regarding Claim 32 above. Regarding Step 2B treatment of the evaluated additional elements individually and in combination, the same previously-stated legal authority and/or rationale supporting the grounds of rejection applied to the above Claim 27 also applies hereto. (E.g. These previously-stated grounds of rejection that were italicized when applied to the referenced previous Claim(s) apply at least to all or portion(s) of the noted recited step.) See discussion above regarding Claim 27 for pertinent previously cited rationale finding well-understood, routine, and conventional activities, pertaining to all or portion(s) of the noted recited step. No additional step introduced in this claim taken individually or when taken as an ordered combination amounts to significantly more than the abstract idea. Accordingly, dependent claim 36 is ineligible.
Claim 37: Dependent claim 37 adds an additional method step of "wherein the otherwise non-diagnostic conventional image data of the applicant includes a video of … drug use, or a glucose level of the applicant by analyzing the video". However, the additional method step of dependent claims 37 is directed to the abstract idea noted above and does not otherwise alter the analysis presented above, and do not integrate the exception into a practical application, because the additional method step merely perform, conduct, carry out, and/or implement the abstract idea itself and/or only narrows the abstract idea (e.g. all or portion(s) of the noted recited steps) and/or because the additional method step comprises or includes: evaluated additional elements individually and in combination for which the courts have identified examples in which a judicial exception has not been integrated into a practical application, as previously discussed regarding Claim 32 above. Regarding Step 2B treatment of the evaluated additional elements individually and in combination, the same previously-stated legal authority and/or rationale supporting the grounds of rejection applied to the above Claim 28 also applies hereto. (E.g. These previously-stated grounds of rejection that were italicized when applied to the referenced previous Claim(s) apply at least to all or portion(s) of the noted recited steps.) See discussion above regarding Claim 28 for pertinent previously cited rationale finding well-understood, routine, and conventional activities, pertaining to all or portion(s) of the noted recited steps. No additional step introduced in this claim taken individually or when taken as an ordered combination amounts to significantly more than the abstract idea. Accordingly, dependent claim 37 is ineligible.
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§101 Subject Matter Eligibility Test for Products and Processes
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 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 set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
Determining the scope and contents of the prior art.
Ascertaining the differences between the prior art and the claims at issue.
Resolving the level of ordinary skill in the pertinent art.
Considering objective evidence present in the application indicating obviousness or nonobviousness.
1-st Prior Art Category: Claims 21-24 and 28-31 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Application Publication No. US 2015/0025917 A1 of Stempora; Jeffrey, (hereinafter "STEMPORA") in view of U.S. Patent Application Publication No. US 2001/0043729 A1 of Giger, Maryellen L. et al., (hereinafter "GIGER").
Claim 21, EXAMINER's Analysis: Claim 21 is rejected as being unpatentable over STEMPORA and GIGER. Claim 21 is an independent claim. The combined disclosures and teachings of STEMPORA and GIGER taken together render obvious the claimed subject matter of claim 21 as follows and as explained below.
Regarding and as per CLAIM 21, a system for evaluating an applicant to determine one or more terms of insurance coverage, comprising: Reference (STEMPORA: discloses e.g. "[i]n one embodiment a system for determining a level of risk associated with an individual for underwriting purposes comprises at least one sensor that provides information, such as a camera providing one or more images or video for example, used to determine one or more properties of the individual[; t]he individual information, such as eye related information, can be processed to generate cognitive information for the individual, which can be used to determine the level of risk associated with the individual[; t]he cognitive information can be compared to baseline cognitive information for the individual to determine the level of risk[; i]n another embodiment, a method for determining a level of risk or price of insurance includes obtaining information from a sensor, generating cognitive information from the sensor information, and generating a level of risk or price of insurance using at least the first cognitive information" Abstract)
• 21 ¶ 2 • a data receiving circuit configured to receive image data of the applicant; and Reference (STEMPORA: discloses e.g. "[i]n one embodiment a system for determining a level of risk associated with an individual for underwriting purposes comprises at least one sensor that provides information, such as a camera providing one or more images or video for example, used to determine one or more properties of the individual[; t]he individual information, such as eye related information, can be processed to generate cognitive information for the individual, which can be used to determine the level of risk associated with the individual[; t]he cognitive information can be compared to baseline cognitive information for the individual to determine the level of risk[; i]n another embodiment, a method for determining a level of risk or price of insurance includes obtaining information from a sensor, generating cognitive information from the sensor information, and generating a level of risk or price of insurance using at least the first cognitive information" Abstract)
• 21 ¶ 3 • a processor trained to correlate aspects of appearance with a personal and/or health-related characteristic by being provided with image data of individuals having known personal and/or health-related characteristics; Reference (STEMPORA: discloses "a decision-making process algorithm is executed on one or more processors in a system to determine or process decision information for determining the risk assessment, the risk score, the underwriting, or the cost of insurance for an individual[; i]n one embodiment, the decision-making algorithm performs one or more of the tasks selected from the group identifies a risk-related decision; determines decision information; determines (with or without a degree of certainty or probability) contextual decision related information (such as the framework for the decision); determines (with or without a degree of certainty or probability) risk exposure information; determines (with or without a degree of certainty or probability) the use of one or more decision-making processes by the individual; determines (with or without a degree of certainty or probability) the use of one or more heuristic decision-making processes by the individual; determines the decision outcome; determines whether it is a negative, positive, or neutral decision outcome; correlates the actual or perceived risk exposure information with one or more decision-making processes (such as a heuristic); identifies the decision andor the individual on a scale from risk-seeking to risk-avoiding; analyzes historical decision information to provide decision information for a subsequent decision (such as a vehicle operator frequently choosing a particular decision-making process under a particular set of conditions); compares decision information for an individual with collective decision information from a plurality of individuals; identifies one or more patterns in decision information from a plurality of individuals; applies an identified pattern of decision related information from a plurality of individuals to determine, predict, or estimate the decision information for individual (including an individual within or not within the plurality of individuals)" par. [0046] and e.g. "[i]n one embodiment a system for determining a level of risk associated with an individual for underwriting purposes comprises at least one sensor that provides information, such as a camera providing one or more images or video for example, used to determine one or more properties of the individual[; t]he individual information, such as eye related information, can be processed to generate cognitive information for the individual, which can be used to determine the level of risk associated with the individual[; t]he cognitive information can be compared to baseline cognitive information for the individual to determine the level of risk[; i]n another embodiment, a method for determining a level of risk or price of insurance includes obtaining information from a sensor, generating cognitive information from the sensor information, and generating a level of risk or price of insurance using at least the first cognitive information" Abstract); (STEMPORA: doesn't expressly and explicitly recite by being provided with image data --- however GIGER: clearly discloses, teaches, and/or suggests the feature -- "obtaining image data representative of a medical image; computing at least one feature characteristic of the image data; comparing the computed feature characteristic to corresponding computed feature characteristics derived from images in a known image data set; selecting image data from images of the known image data set having corresponding computed feature characteristics similar to the feature characteristics computed in the computing step" par. [0011], Claim 1 or "an initial acquisition of a set of known medical images that comprise a database, and presentation of the images in digital format[; t]he lesion location in terms of estimated center is input from either a human or computer[; t]he method, system and computer readable medium that employs an intelligent search workstation for the computer assisted interpretation of medical images consists of the following stages: access to a database of known medical images with known/confirmed diagnoses of pathological state (step 112), computer-extraction of features of lesions within the known database (step 104), input method for an unknown case (step 102), computer-extraction of features of lesion of the unknown case (step 104), calculation of likelihood of pathological state (e.g., likelihood of malignancy) for the known and unknown cases (step 108), calculation of similarity indices for the unknown cases relative to each of the known cases (step 110), search among the known database based on the calculated similarity indices (step 114) and presentation of the "similar" cases and/or the computer-estimated features and/or likelihood of pathological state (step 116)[; a] specific example of the system is given for mass lesions in mammographic images in which the computer extracts features (step 104) and estimates the likelihood of malignancy for the known and the unknown cases (step 108), computes the similarity indices for each pair (step 110), and output cases that are similar in terms of individual features, combination of features, and/or computer-estimated likelihood of malignancy (step 116)" par. [0030] or "inputting of digital images" par. [0034]), [See Remarks Below]; (STEMPORA: discloses as described previously in this paragraph); (STEMPORA: doesn't expressly and explicitly recite known --- however GIGER: clearly discloses, teaches, and/or suggests the feature -- as described previously in this paragraph); (STEMPORA: discloses as described previously in this paragraph)
With respect to above-noted claimed elements [1] "by being provided with image data" and [2] "known" which are disclosed by GIGER: the teachings and/or suggestions within the disclosure of STEMPORA thus far relied upon does not mention within its descriptions an explicit and express recitation of [1] "by being provided with image data" and [2] "known" as recited in the instant claim. Nonetheless, herein relied upon are portions of the disclosure of GIGER which sufficiently teaches the features apposite to the claimed invention as commented about above with quotation(s) of exemplary disclosures within GIGER that teach and/or suggest the claimed features. At the time of effective filing date, it would have been obvious for one of ordinary skill in the art to have modified the relied upon teachings of STEMPORA by adding or substituting the features [1] "by being provided with image data" and [2] "known" as taught and/or suggested by GIGER, with a reasonable expectation of success of arriving at the claimed invention. The addition or substitution of these known features by one of ordinary skill in the art at the time of the effective filing date would have yielded predictable results that were readily reckonable to that one person of ordinary skill in the art at that time. At the time of the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to have modified the teachings of STEMPORA with these aforementioned teachings of [1] "by being provided with image data" and [2] "known" sufficiently taught, suggested, and/or disclosed in GIGER because that one artisan of skill having ordinary skill in the art at the time of the effective filing date of the invention would have had a motivation of "combines the benefit of computer-aided diagnosis with prior knowledge obtained via confirmed cases". (GIGER: par. [0013]).
• 21 ¶ 4 • wherein the processor analyzes the image data of the applicant to determine a personal and/or health-related characteristic of the applicant, and to suggest a term of insurance coverage based at least in part upon the determined personal and/or health-related characteristic. Reference (STEMPORA: discloses e.g. "[i]n one embodiment a system for determining a level of risk associated with an individual for underwriting purposes comprises at least one sensor that provides information, such as a camera providing one or more images or video for example, used to determine one or more properties of the individual[; t]he individual information, such as eye related information, can be processed to generate cognitive information for the individual, which can be used to determine the level of risk associated with the individual[; t]he cognitive information can be compared to baseline cognitive information for the individual to determine the level of risk[; i]n another embodiment, a method for determining a level of risk or price of insurance includes obtaining information from a sensor, generating cognitive information from the sensor information, and generating a level of risk or price of insurance using at least the first cognitive information" Abstract)
Claim 22, EXAMINER's Analysis: Claim 22 is rejected as being unpatentable over STEMPORA and GIGER. Claim 22 is a dependent claim that directly depends upon parent claim 21, which is an independent claim. Further to and in conjunction with the disclosures and teachings of the prior art recited in the parent as applied to the limitations of claim 21, STEMPORA discloses the claimed subject matter of claim 22 as follows and as explained below.
Regarding and as per CLAIM 22, the system as set forth in claim 21, Reference (STEMPORA: discloses e.g. "[i]n one embodiment a system for determining a level of risk associated with an individual for underwriting purposes comprises at least one sensor that provides information, such as a camera providing one or more images or video for example, used to determine one or more properties of the individual[; t]he individual information, such as eye related information, can be processed to generate cognitive information for the individual, which can be used to determine the level of risk associated with the individual[; t]he cognitive information can be compared to baseline cognitive information for the individual to determine the level of risk[; i]n another embodiment, a method for determining a level of risk or price of insurance includes obtaining information from a sensor, generating cognitive information from the sensor information, and generating a level of risk or price of insurance using at least the first cognitive information" Abstract)
• 22 ¶ 2 • wherein the insurance coverage is health insurance. Reference (STEMPORA: discloses e.g. "[i]n one embodiment a system for determining a level of risk associated with an individual for underwriting purposes comprises at least one sensor that provides information, such as a camera providing one or more images or video for example, used to determine one or more properties of the individual[; t]he individual information, such as eye related information, can be processed to generate cognitive information for the individual, which can be used to determine the level of risk associated with the individual[; t]he cognitive information can be compared to baseline cognitive information for the individual to determine the level of risk[; i]n another embodiment, a method for determining a level of risk or price of insurance includes obtaining information from a sensor, generating cognitive information from the sensor information, and generating a level of risk or price of insurance using at least the first cognitive information" Abstract and "the risk assessment, risk score, underwriting or cost of insurance is for one or more insurance products selected from the group casualty insurance, automobile or craft insurance, life insurance, health or medical insurance, property insurance, liability insurance, financial instrument insurance, and law enforcement risk assessment or regulation" par. [0228])
Claim 23, EXAMINER's Analysis: Claim 23 is rejected as being unpatentable over STEMPORA and GIGER. Claim 23 is a dependent claim that directly depends upon parent claim 21, which is an independent claim. Further to and in conjunction with the disclosures and teachings of the prior art recited in the parent as applied to the limitations of claim 21, STEMPORA discloses the claimed subject matter of claim 23 as follows and as explained below.
Regarding and as per CLAIM 23, the system as set forth in claim 21, See Prior Comment(s) at Claim 22 Par. 1;
• 23 ¶ 2 • wherein the term of insurance coverage includes an insurance premium or discount. Reference (STEMPORA: discloses e.g. "[i]n one embodiment a system for determining a level of risk associated with an individual for underwriting purposes comprises at least one sensor that provides information, such as a camera providing one or more images or video for example, used to determine one or more properties of the individual[; t]he individual information, such as eye related information, can be processed to generate cognitive information for the individual, which can be used to determine the level of risk associated with the individual[; t]he cognitive information can be compared to baseline cognitive information for the individual to determine the level of risk[; i]n another embodiment, a method for determining a level of risk or price of insurance includes obtaining information from a sensor, generating cognitive information from the sensor information, and generating a level of risk or price of insurance using at least the first cognitive information" Abstract)
Claim 24, EXAMINER's Analysis: Claim 24 is rejected as being unpatentable over STEMPORA and GIGER. Claim 24 is a dependent claim that directly depends upon parent claim 21, which is an independent claim. Further to and in conjunction with the disclosures and teachings of the prior art recited in the parent as applied to the limitations of claim 21, the combined disclosures and teachings of STEMPORA and GIGER taken together render obvious the claimed subject matter of claim 24 as follows and as explained below.
Regarding and as per CLAIM 24, the system as set forth in claim 21, See Prior Comment(s) at Claim 22 Par. 1;
• 24 ¶ 2 • wherein the image data of the applicant includes a digital image. Reference (STEMPORA: discloses e.g. "[i]n one embodiment a system for determining a level of risk associated with an individual for underwriting purposes comprises at least one sensor that provides information, such as a camera providing one or more images or video for example, used to determine one or more properties of the individual[; t]he individual information, such as eye related information, can be processed to generate cognitive information for the individual, which can be used to determine the level of risk associated with the individual[; t]he cognitive information can be compared to baseline cognitive information for the individual to determine the level of risk[; i]n another embodiment, a method for determining a level of risk or price of insurance includes obtaining information from a sensor, generating cognitive information from the sensor information, and generating a level of risk or price of insurance using at least the first cognitive information" Abstract); (STEMPORA: doesn't expressly and explicitly recite a digital image. --- however GIGER: clearly discloses, teaches, and/or suggests the feature -- "automated analysis of digital images" par. [0003] or "inputting of digital images" par. [0034] or "digitizing and storing images obtained from an image acquisition device[; a]lternatively, the present invention can also be implemented to process digital data derived from images obtained by other means, such as a picture archive communication system (PACS)[; i]n other words, often the digital images being processed will be in existence in digital form and need not be converted to digital form in practicing the invention" par. [0066]), [See Remarks Below]
With respect to above-noted claimed element "a digital image" which is disclosed by GIGER: the teachings and/or suggestions within the disclosure of STEMPORA thus far relied upon omits to record within its explanations the reciting explicitly and expressly of a digital image as recited in the claim under examination. Nonetheless, herein relied upon are portions of the disclosure of GIGER which sufficiently teaches the feature appurtenant to the claimed invention as pointed out above with quotation(s) of exemplary disclosures within GIGER that teach and/or suggest the claimed feature. At the time of effective filing date, it would have been obvious for one of ordinary skill in the art to have modified the relied upon teachings of STEMPORA by adding or substituting the feature a digital image as taught and/or suggested by GIGER, with a reasonable expectation of success of arriving at the claimed invention. The addition or substitution of this known feature by one of ordinary skill in the art at the time of the effective filing date would have yielded predictable results that were plainly foreseeable to that ordinarily skilled one person in the art at that time. At the time of the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to have modified the teachings of STEMPORA with these previously described teachings of "a digital image" sufficiently taught, suggested, and/or disclosed in GIGER because that one artisan of skill having ordinary skill in the art at the time of the effective filing date of the invention would have had a motivation of "combines the benefit of computer-aided diagnosis with prior knowledge obtained via confirmed cases". (GIGER: par. [0013]).
Claim 28, EXAMINER's Analysis: Claim 28 is rejected as being unpatentable over STEMPORA and GIGER. Claim 28 is a dependent claim that directly depends upon parent claim 21, which is an independent claim. Further to and in conjunction with the disclosures and teachings of the prior art recited in the parent as applied to the limitations of claim 21, STEMPORA discloses the claimed subject matter of claim 28 as follows and as explained below.
Regarding and as per CLAIM 28, the system as set forth in claim 21, See Prior Comment(s) at Claim 22 Par. 1;
• 28 ¶ 2 • wherein the image data of the applicant includes a video of the applicant, the processor being configured to determine at least one of a pulse, drug use, or a glucose level of the applicant by analyzing the video. Reference (STEMPORA: discloses "a camera providing one or more images or video used to determine one or more properties of the individual, such as the properties of one or more eyes of the individual (and optionally identification information) that is used to help determine risk[; i]n another example, the system comprises one or more sensors that determine facial or heart rate or circadian rhythm information[; t]he system may comprise one or more combinations of sensors andor cameras[; t]he sensor (such as a camera) may be mounted or built into a vehicle, a portable device, or an accessory for the vehicle or portable device, or worn by the individual[; t]he properties related to one or more eyes include one or more selected from the group pupil size or dilation, eyelid statemotion (incl. sleepy eyelid movement, blinking rate, closed eyelids, etc.), microsaccade amplitude, frequency or orientation, vergence, eye orientation, eye movement or fixation, gaze direction, gaze duration, details of the iris, symptoms of eye fatigue, and details of the retina[; t]he details of the iris or retina (andor information from an image of the face of the individual) may be used to provide operator identification information[; t]he eye related information can be processed to generate first cognitive information for individual, which can be used at least in part to generate the level of risk associated with the individual performing the activity[; f]acial andor hear rate andor circadian rhythm information, separately or used in combination with one or more other sensors, may be used to improve identification of cognitive states in some instances" par. [0004])
Claim 29, EXAMINER's Analysis: Claim 29 is rejected as being unpatentable over STEMPORA and GIGER. Claim 29 is a dependent claim that directly depends upon parent claim 21, which is an independent claim. Further to and in conjunction with the disclosures and teachings of the prior art recited in the parent as applied to the limitations of claim 21, STEMPORA discloses the claimed subject matter of claim 29 as follows and as explained below.
Regarding and as per CLAIM 29, the system as set forth in claim 21, See Prior Comment(s) at Claim 22 Par. 1;
• 29 ¶ 2 • wherein the personal and/or health-related characteristic is at least one of age, sex, weight, height, ethnicity, lifespan, cause of death, tobacco use, alcohol use, drug use, diet, existing medical conditions, or risk factors for future medical conditions. Reference (STEMPORA: discloses e.g. "[i]n one embodiment a system for determining a level of risk associated with an individual for underwriting purposes comprises at least one sensor that provides information, such as a camera providing one or more images or video for example, used to determine one or more properties of the individual[; t]he individual information, such as eye related information, can be processed to generate cognitive information for the individual, which can be used to determine the level of risk associated with the individual[; t]he cognitive information can be compared to baseline cognitive information for the individual to determine the level of risk[; i]n another embodiment, a method for determining a level of risk or price of insurance includes obtaining information from a sensor, generating cognitive information from the sensor information, and generating a level of risk or price of insurance using at least the first cognitive information" Abstract and "a camera providing one or more images or video used to determine one or more properties of the individual, such as the properties of one or more eyes of the individual (and optionally identification information) that is used to help determine risk[; i]n another example, the system comprises one or more sensors that determine facial or heart rate or circadian rhythm information[; t]he system may comprise one or more combinations of sensors andor cameras[; t]he sensor (such as a camera) may be mounted or built into a vehicle, a portable device, or an accessory for the vehicle or portable device, or worn by the individual[; t]he properties related to one or more eyes include one or more selected from the group pupil size or dilation, eyelid statemotion (incl. sleepy eyelid movement, blinking rate, closed eyelids, etc.), microsaccade amplitude, frequency or orientation, vergence, eye orientation, eye movement or fixation, gaze direction, gaze duration, details of the iris, symptoms of eye fatigue, and details of the retina[; t]he details of the iris or retina (andor information from an image of the face of the individual) may be used to provide operator identification information[; t]he eye related information can be processed to generate first cognitive information for individual, which can be used at least in part to generate the level of risk associated with the individual performing the activity[; f]acial andor hear rate andor circadian rhythm information, separately or used in combination with one or more other sensors, may be used to improve identification of cognitive states in some instances" par. [0004])
Claim 30, EXAMINER's Analysis: Claim 30 is rejected as being unpatentable over STEMPORA and GIGER. Claim 30 is a dependent claim that directly depends upon parent claim 21, which is an independent claim. Further to and in conjunction with the disclosures and teachings of the prior art recited in the parent as applied to the limitations of claim 21, STEMPORA discloses the claimed subject matter of claim 30 as follows and as explained below.
Regarding and as per CLAIM 30, the system as set forth in claim 21, See Prior Comment(s) at Claim 22 Par. 1;
• 30 ¶ 2 • wherein the processor is further configured to use the determined personal and/or health-related characteristic to verify information provided by the applicant. Reference (STEMPORA: discloses "an insurance underwriter may set-up an award or discount program for the cost of automobile insurance for individuals who improve their performance in a specific discipline or skill (such as an improvement cognitive capacity through the use of cognitive enhancement games or puzzles) and expect to see an improvement in safe vehicle operation by the individual over time[; i]n one embodiment, a resource may be provided to the individual to help modify their behavior andor improve their cognitive ability[; t]he resource may include training (such as risk avoidance training, for example), an application, seminar, instructional media, a game, a puzzle, cognitive enhancement application or tool, behavior modification application or tool, or other resource known to modify behavior andor facilitate enhancement of cognitive ability[; f]or example, a free mathematical puzzle application for a smartphone (such as a Sudoku application) may be offered to the individual and after installing opening the application, the individual's identity is verified (such as by using the built-in camera and facial recognition), and improved puzzle performance is rewarded by discounts to their automobile insurance" par. [0189])
Claim 31, EXAMINER's Analysis: Claim 31 is rejected as being unpatentable over STEMPORA and GIGER. Claim 31 is a dependent claim that directly depends upon parent claim 21, which is an independent claim. Further to and in conjunction with the disclosures and teachings of the prior art recited in the parent as applied to the limitations of claim 21, STEMPORA discloses the claimed subject matter of claim 31 as follows and as explained below.
Regarding and as per CLAIM 31, the system as set forth in claim 21, See Prior Comment(s) at Claim 22 Par. 1;
• 31 ¶ 2 • wherein the processor is further configured to use the determined personal and/or health-related characteristic to substantially automatically determine the term of insurance coverage. Reference (STEMPORA: discloses e.g. "[i]n one embodiment a system for determining a level of risk associated with an individual for underwriting purposes comprises at least one sensor that provides information, such as a camera providing one or more images or video for example, used to determine one or more properties of the individual[; t]he individual information, such as eye related information, can be processed to generate cognitive information for the individual, which can be used to determine the level of risk associated with the individual[; t]he cognitive information can be compared to baseline cognitive information for the individual to determine the level of risk[; i]n another embodiment, a method for determining a level of risk or price of insurance includes obtaining information from a sensor, generating cognitive information from the sensor information, and generating a level of risk or price of insurance using at least the first cognitive information" Abstract and "portable device functions or portable device software restrictions are controlled at least in part by a third party such as a parent, guardian, insurer, or employer[; i]n this embodiment, the third party may manage the portable device functions or software restrictions directly, indirectly, or using a risk analysis that may utilize a cognitive analysis[; t]he management may be performed directly on the device, remotely through wired or wireless communication, using a web or software application interface, in real-time, automatically, manually, or using instructions, conditions, settings, or algorithms pre-loaded onto the device or transmitted remotely" par. [0205])
2-nd Prior Art Category: Claim 25 is rejected under 35 U.S.C. 103 as being unpatentable over STEMPORA in view of GIGER in further view of U.S. Patent Application Publication No. US 2011/0161100 A1 of Peak; David F. et al., (hereinafter "PEAK").
Claim 25, EXAMINER's Analysis: Claim 25 is rejected as being unpatentable over STEMPORA and GIGER and PEAK. Claim 25 is a dependent claim that directly depends upon parent claim 21, which is an independent claim. Further to and in conjunction with the disclosures and teachings of the prior art recited in the parent as applied to the limitations of claim 21, the combined disclosures and teachings of STEMPORA and PEAK taken together render obvious the claimed subject matter of claim 25 as follows and as explained below.
Regarding and as per CLAIM 25, the system as set forth in claim 21, See Prior Comment(s) at Claim 22 Par. 1;
• 25 ¶ 2 • wherein the image data of the applicant includes a selfie. Reference (STEMPORA: discloses e.g. "[i]n one embodiment a system for determining a level of risk associated with an individual for underwriting purposes comprises at least one sensor that provides information, such as a camera providing one or more images or video for example, used to determine one or more properties of the individual[; t]he individual information, such as eye related information, can be processed to generate cognitive information for the individual, which can be used to determine the level of risk associated with the individual[; t]he cognitive information can be compared to baseline cognitive information for the individual to determine the level of risk[; i]n another embodiment, a method for determining a level of risk or price of insurance includes obtaining information from a sensor, generating cognitive information from the sensor information, and generating a level of risk or price of insurance using at least the first cognitive information" Abstract); (STEMPORA: doesn't expressly and explicitly recite a selfie. --- however PEAK: clearly discloses, teaches, and/or suggests the feature -- e.g. "a user who is operating the medical monitoring application may be prompted to take a photo of themselves with the sensor(s) installed and attached to their body as proof that the medical or health status-related information was collected from the correct individual" par. [0075]); see also (STEMPORA: "a self-reporting mechanism, historical cognitive load measurements performing one or more physical andor mental activities, or using cognitive map information, and the cognitive load is evaluated using eye related information (and optionally facial information) obtained from a camera while the individual is performing a primary or goal state activity such as operating a vehicle" par. [0142]), [See Remarks Below]
With respect to above-noted claimed element "a selfie" which is disclosed by PEAK: the teachings and/or suggestions within the disclosure of STEMPORA thus far relied upon fails to mention within its writings an explicit and express recital of a selfie as required by the instant claim. Nonetheless, herein relied upon are portions of the disclosure of PEAK which sufficiently teaches the feature appurtenant to the claimed invention as commented about above with quotation(s) of exemplary disclosures within PEAK that teach and/or suggest the claimed feature. At the time of effective filing date, it would have been obvious for one of ordinary skill in the art to have modified the relied upon teachings of STEMPORA by adding or substituting the feature a selfie as taught and/or suggested by PEAK, with a reasonable expectation of success of arriving at the claimed invention. The addition or substitution of this known feature by one of ordinary skill in the art at the time of the effective filing date would have yielded predictable results that were simply reckonable to that ordinarily skilled one person in the art at that time. At the time of the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to have modified the teachings of STEMPORA with these above-described teachings of "a selfie" sufficiently taught, suggested, and/or disclosed in PEAK because that one skilled artisan having ordinary skill in the art at the time of the effective filing date of the invention would have had a motivation of "to provide systems and methods which allow medical and health related data to be collected by an individual and transmitted to insurers and other benefits providers for use in pricing, underwriting and managing insurance and benefits policies". (PEAK: par. [0006]).
3-rd Prior Art Category: Claim 26 is rejected under 35 U.S.C. 103 as being unpatentable over STEMPORA in view of GIGER in further view of U.S. Patent Application Publication No. US 2015/0193718 A1 of Shaburov; Victor et al., (hereinafter "SHABUROV").
Claim 26, EXAMINER's Analysis: Claim 26 is rejected as being unpatentable over STEMPORA and GIGER and SHABUROV. Claim 26 is a dependent claim that directly depends upon parent claim 21, which is an independent claim. Further to and in conjunction with the disclosures and teachings of the prior art recited in the parent as applied to the limitations of claim 21, the combined disclosures and teachings of STEMPORA and SHABUROV taken together render obvious the claimed subject matter of claim 26 as follows and as explained below.
Regarding and as per CLAIM 26, the system as set forth in claim 21, See Prior Comment(s) at Claim 22 Par. 1;
• 26 ¶ 2 • wherein the processor employs a convolutional neural network including a plurality of receptive fields which are tiled to overlap. Reference (STEMPORA: doesn't expressly and explicitly recite a convolutional neural network including a plurality...receptive fields which are tiled to overlap. --- however SHABUROV: clearly discloses, teaches, and/or suggests the feature -- "[t]he step 940 of comparing may include applying at least one machine-learning algorithm such as a convolution neural network (CNN) and/or a state vector machine (SVM)[; g]enerally, CNN is a type of feed-forward artificial neural network where the individual neurons are tiled in such a way that they respond to overlapping regions in the visual field[; c]NNs consist of multiple layers of small neuron collections, which look at small portions of the input image, called receptive fields[; t]he results of these collections are then tiled so that they overlap to obtain a better representation of the original image; this is repeated for every such layer[; c]onvolutional networks may include local or global pooling layers, which combine the outputs of neuron clusters[; t]hey also consist of various combinations of convolutional layers and fully connected layers, with pointwise nonlinearity applied at the end of or after each layer[; t]o avoid the situation that there exist billions of parameters if all layers are fully connected, the idea of using a convolution operation on small regions, has been introduced[; o]ne major advantage of convolutional networks is the use of shared weight in convolutional layers, which means that the same filter (weights bank) is used for each pixel in the layer; this both reduces required memory size and improves performance" par. [0100]), [See Remarks Below]
With respect to above-noted claimed element "a convolutional neural network including a plurality of receptive fields which are tiled to overlap" which is disclosed by SHABUROV: the teachings and/or suggestions within the disclosure of STEMPORA thus far relied upon fails to record within its descriptions an explicit and express recitation of a convolutional neural network including a plurality of receptive fields which are tiled to overlap as required by the claim under examination. However, herein relied upon are portions of the disclosure of SHABUROV which sufficiently teaches the feature apposite to the claimed invention as commented about above with reference(s) to exemplary disclosures within SHABUROV that teach and/or suggest the claimed feature. At the time of effective filing date, it would have been obvious for one of ordinary skill in the art to have modified the relied upon teachings of STEMPORA by adding or substituting the feature a convolutional neural network including a plurality of receptive fields which are tiled to overlap as taught and/or suggested by SHABUROV, with a reasonable expectation of success of arriving at the claimed invention. The addition or substitution of this known feature by one of ordinary skill in the art at the time of the effective filing date would have yielded predictable results that were easily foreseeable to that one person of ordinary skill in the art at that time. At the time of the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to have modified the teachings of STEMPORA with these previously described teachings of "a convolutional neural network including a plurality of receptive fields which are tiled to overlap" sufficiently taught, suggested, and/or disclosed in SHABUROV because that one artisan of skill having ordinary skill in the art at the time of the effective filing date of the invention would have had a motivation of "analytics in video conferencing and, more particularly, to systems and methods for recognizing emotions of individuals, such as customer call center employees or agents, and aggregating related work quality metrics of the individuals when they interact with customers via a video conference", (SHABUROV: par. [0001]); or "technology for video-based workforce analytics, in which an emotional status of individuals, such as customer center employees and agents, can be recognized, recorded, and analyzed[; i]n particular, this technology allows for video monitoring of the individuals when they video chat with customers[; t]he video is processed in real time to determine an emotional status of an individual by identifying and tracking facial mimics[; t]he present technology can recognize facial mimics by locating feature reference points (e.g., facial landmarks) on the video, aligning a virtual face mesh to the feature reference points, and determining mesh deformations that reflect face mimics of the individual[; i]n some embodiments, audio can also be processed to determine speech or voice characteristics to improve emotion recognition[; o]nce the emotional status of the individual is determined, the present technology allows for providing one or more work quality parameters such as employee tiredness, negative attitude to work, stress, anger, disrespect, and so forth", (SHABUROV: par. [0005).
4-th Prior Art Category: Claims 27, 32-33, and 36-40 are rejected under 35 U.S.C. 103 as being unpatentable over STEMPORA in view of GIGER in further view of U.S. Patent Application Publication No. US 2016/0259994 A1 of Ravindran; Arun et al., (hereinafter "RAVINDRAN").
Claim 27, EXAMINER's Analysis: Claim 27 is rejected as being unpatentable over STEMPORA and GIGER and RAVINDRAN. Claim 27 is a dependent claim that directly depends upon parent claim 21, which is an independent claim. Further to and in conjunction with the disclosures and teachings of the prior art recited in the parent as applied to the limitations of claim 21, the combined disclosures and teachings of STEMPORA and RAVINDRAN taken together render obvious the claimed subject matter of claim 27 as follows and as explained below.
Regarding and as per CLAIM 27, the system as set forth in claim 21, See Prior Comment(s) at Claim 22 Par. 1;
• 27 ¶ 2 • wherein the processor employs a deep learning neural network. Reference (STEMPORA: discloses "a decision-making process algorithm is executed on one or more processors in a system to determine or process decision information for determining the risk assessment, the risk score, the underwriting, or the cost of insurance for an individual[; i]n one embodiment, the decision-making algorithm performs one or more of the tasks selected from the group identifies a risk-related decision; determines decision information; determines (with or without a degree of certainty or probability) contextual decision related information (such as the framework for the decision); determines (with or without a degree of certainty or probability) risk exposure information; determines (with or without a degree of certainty or probability) the use of one or more decision-making processes by the individual; determines (with or without a degree of certainty or probability) the use of one or more heuristic decision-making processes by the individual; determines the decision outcome; determines whether it is a negative, positive, or neutral decision outcome; correlates the actual or perceived risk exposure information with one or more decision-making processes (such as a heuristic); identifies the decision andor the individual on a scale from risk-seeking to risk-avoiding; analyzes historical decision information to provide decision information for a subsequent decision (such as a vehicle operator frequently choosing a particular decision-making process under a particular set of conditions); compares decision information for an individual with collective decision information from a plurality of individuals; identifies one or more patterns in decision information from a plurality of individuals; applies an identified pattern of decision related information from a plurality of individuals to determine, predict, or estimate the decision information for individual (including an individual within or not within the plurality of individuals)" par. [0046]); (STEMPORA: doesn't expressly and explicitly recite a deep learning neural network. --- however RAVINDRAN: clearly discloses, teaches, and/or suggests the feature -- "deep learning models, such as convolutional neural networks (CNNs)" par. [0010] or "providing an advanced deep learning architecture that exhibits superior classification accuracy to assess property damage and an iterative image processing system that determines that advanced deep learning architecture" par. [0012], [See Remarks Below] and e.g. "a digital image may be processed by an ensemble of convolutional neural networks (CNNs) to classify objects in the digital image" Abstract or "classifying objects in a digital image using convolutional neural networks (CNNs)" par. [0006] or "[a]n image processing system, according to an example, builds and trains an ensemble of deep learning models, such as convolutional neural networks (CNNs), to accurately and automatically perform image processing to detect particular attributes of objects in a digital image, and to classify the objects according to the detected attributes" par. [0010] or "image processing using convolutional neural networks (CNNs)" par. [0022] or "[f]IG. 6 shows a flow chart diagram of an optimized convolutional neural network (CNN) 600" par. [0044]), [See Remarks Below]
With respect to above-noted claimed element "a deep learning neural network" which is disclosed by RAVINDRAN: the teachings and/or suggestions within the disclosure of STEMPORA thus far relied upon fails to record within its explanations an explicit and express recitation of a deep learning neural network as presented within the instant claim. However, herein relied upon are portions of the disclosure of RAVINDRAN which sufficiently teaches the feature applicable to the claimed invention as commented about above with citation(s) to exemplary disclosures within RAVINDRAN that teach and/or suggest the claimed feature. At the time of effective filing date, it would have been obvious for one of ordinary skill in the art to have modified the relied upon teachings of STEMPORA by adding or substituting the feature a deep learning neural network as taught and/or suggested by RAVINDRAN, with a reasonable expectation of success of arriving at the claimed invention. The addition or substitution of this known feature by one of ordinary skill in the art at the time of the effective filing date would have yielded predictable results that were readily reckonable to that ordinarily skilled one person in the art at that time. At the time of the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to have modified the teachings of STEMPORA with these previously described teachings of "a deep learning neural network" sufficiently taught, suggested, and/or disclosed in RAVINDRAN because that one artisan of skill having ordinary skill in the art at the time of the effective filing date of the invention would have had a motivation of "to accurately classify the objects in the digital image". (RAVINDRAN: Abstract).
Claim 32, EXAMINER's Analysis: Claim 32 is rejected as being unpatentable over STEMPORA and GIGER and RAVINDRAN. Claim 32 is an independent claim. The combined disclosures and teachings of STEMPORA and GIGER and RAVINDRAN taken together render obvious the claimed subject matter of claim 32 as follows and as explained below.
Regarding and as per CLAIM 32, a system for evaluating an applicant to determine a life insurance premium, comprising: Reference (STEMPORA: discloses e.g. "[i]n one embodiment a system for determining a level of risk associated with an individual for underwriting purposes comprises at least one sensor that provides information, such as a camera providing one or more images or video for example, used to determine one or more properties of the individual[; t]he individual information, such as eye related information, can be processed to generate cognitive information for the individual, which can be used to determine the level of risk associated with the individual[; t]he cognitive information can be compared to baseline cognitive information for the individual to determine the level of risk[; i]n another embodiment, a method for determining a level of risk or price of insurance includes obtaining information from a sensor, generating cognitive information from the sensor information, and generating a level of risk or price of insurance using at least the first cognitive information" Abstract and "the risk assessment, risk score, underwriting or cost of insurance is for one or more insurance products selected from the group casualty insurance, automobile or craft insurance, life insurance, health or medical insurance, property insurance, liability insurance, financial instrument insurance, and law enforcement risk assessment or regulation" par. [0228])
• 32 ¶ 2 • a data receiving circuit configured to receive otherwise non-diagnostic conventional image data of the applicant; and Reference (STEMPORA: discloses e.g. "[i]n one embodiment a system for determining a level of risk associated with an individual for underwriting purposes comprises at least one sensor that provides information, such as a camera providing one or more images or video for example, used to determine one or more properties of the individual[; t]he individual information, such as eye related information, can be processed to generate cognitive information for the individual, which can be used to determine the level of risk associated with the individual[; t]he cognitive information can be compared to baseline cognitive information for the individual to determine the level of risk[; i]n another embodiment, a method for determining a level of risk or price of insurance includes obtaining information from a sensor, generating cognitive information from the sensor information, and generating a level of risk or price of insurance using at least the first cognitive information" Abstract and "the system comprises a camera providing one or more images or video used to determine one or more properties of the individual, such as the properties of one or more eyes of the individual (and optionally identification information) that is used to help determine risk[; i]n another example, the system comprises one or more sensors that determine facial or heart rate or circadian rhythm information[; t]he system may comprise one or more combinations of sensors andor cameras[; t]he sensor (such as a camera) may be mounted or built into a vehicle, a portable device, or an accessory for the vehicle or portable device, or worn by the individual[; t]he properties related to one or more eyes include one or more selected from the group pupil size or dilation, eyelid statemotion (incl. sleepy eyelid movement, blinking rate, closed eyelids, etc.), microsaccade amplitude, frequency or orientation, vergence, eye orientation, eye movement or fixation, gaze direction, gaze duration, details of the iris, symptoms of eye fatigue, and details of the retina[; t]he details of the iris or retina (andor information from an image of the face of the individual) may be used to provide operator identification information" par. [0004])
• 32 ¶ 3 • a processor employing a neural network and trained to correlate one or more aspects of appearance with a personal and/or health-related characteristic by being provided with otherwise non-diagnostic conventional image data of individuals having known personal and/or health-related characteristics; Reference (STEMPORA: discloses "a decision-making process algorithm is executed on one or more processors in a system to determine or process decision information for determining the risk assessment, the risk score, the underwriting, or the cost of insurance for an individual[; i]n one embodiment, the decision-making algorithm performs one or more of the tasks selected from the group identifies a risk-related decision; determines decision information; determines (with or without a degree of certainty or probability) contextual decision related information (such as the framework for the decision); determines (with or without a degree of certainty or probability) risk exposure information; determines (with or without a degree of certainty or probability) the use of one or more decision-making processes by the individual; determines (with or without a degree of certainty or probability) the use of one or more heuristic decision-making processes by the individual; determines the decision outcome; determines whether it is a negative, positive, or neutral decision outcome; correlates the actual or perceived risk exposure information with one or more decision-making processes (such as a heuristic); identifies the decision andor the individual on a scale from risk-seeking to risk-avoiding; analyzes historical decision information to provide decision information for a subsequent decision (such as a vehicle operator frequently choosing a particular decision-making process under a particular set of conditions); compares decision information for an individual with collective decision information from a plurality of individuals; identifies one or more patterns in decision information from a plurality of individuals; applies an identified pattern of decision related information from a plurality of individuals to determine, predict, or estimate the decision information for individual (including an individual within or not within the plurality of individuals)" par. [0046]); (STEMPORA: doesn't expressly and explicitly recite employing a neural network --- however RAVINDRAN: clearly discloses, teaches, and/or suggests the feature -- e.g. "a digital image may be processed by an ensemble of convolutional neural networks (CNNs) to classify objects in the digital image" Abstract or "classifying objects in a digital image using convolutional neural networks (CNNs)" par. [0006] or "[a]n image processing system, according to an example, builds and trains an ensemble of deep learning models, such as convolutional neural networks (CNNs), to accurately and automatically perform image processing to detect particular attributes of objects in a digital image, and to classify the objects according to the detected attributes" par. [0010] or "image processing using convolutional neural networks (CNNs)" par. [0022] or "[f]IG. 6 shows a flow chart diagram of an optimized convolutional neural network (CNN) 600" par. [0044]), [See Remarks Below]; (STEMPORA: discloses as described previously in this paragraph and e.g. "[i]n one embodiment a system for determining a level of risk associated with an individual for underwriting purposes comprises at least one sensor that provides information, such as a camera providing one or more images or video for example, used to determine one or more properties of the individual[; t]he individual information, such as eye related information, can be processed to generate cognitive information for the individual, which can be used to determine the level of risk associated with the individual[; t]he cognitive information can be compared to baseline cognitive information for the individual to determine the level of risk[; i]n another embodiment, a method for determining a level of risk or price of insurance includes obtaining information from a sensor, generating cognitive information from the sensor information, and generating a level of risk or price of insurance using at least the first cognitive information" Abstract); (STEMPORA: doesn't expressly and explicitly recite by being provided with --- however GIGER: clearly discloses, teaches, and/or suggests the feature -- "obtaining image data representative of a medical image; computing at least one feature characteristic of the image data; comparing the computed feature characteristic to corresponding computed feature characteristics derived from images in a known image data set; selecting image data from images of the known image data set having corresponding computed feature characteristics similar to the feature characteristics computed in the computing step" par. [0011], Claim 1 or "an initial acquisition of a set of known medical images that comprise a database, and presentation of the images in digital format[; t]he lesion location in terms of estimated center is input from either a human or computer[; t]he method, system and computer readable medium that employs an intelligent search workstation for the computer assisted interpretation of medical images consists of the following stages: access to a database of known medical images with known/confirmed diagnoses of pathological state (step 112), computer-extraction of features of lesions within the known database (step 104), input method for an unknown case (step 102), computer-extraction of features of lesion of the unknown case (step 104), calculation of likelihood of pathological state (e.g., likelihood of malignancy) for the known and unknown cases (step 108), calculation of similarity indices for the unknown cases relative to each of the known cases (step 110), search among the known database based on the calculated similarity indices (step 114) and presentation of the "similar" cases and/or the computer-estimated features and/or likelihood of pathological state (step 116)[; a] specific example of the system is given for mass lesions in mammographic images in which the computer extracts features (step 104) and estimates the likelihood of malignancy for the known and the unknown cases (step 108), computes the similarity indices for each pair (step 110), and output cases that are similar in terms of individual features, combination of features, and/or computer-estimated likelihood of malignancy (step 116)" par. [0030] or "inputting of digital images" par. [0034]), [See Remarks after Claim 21 Par. 3 herein for previously explained rationale or reasoned explanation supporting the finding of obviousness regarding the above-identified combination]; (STEMPORA: discloses as described previously in this paragraph and as already cited in this par.); (STEMPORA: doesn't expressly and explicitly recite known --- however GIGER: clearly discloses, teaches, and/or suggests the feature -- as described previously in this paragraph); (STEMPORA: discloses as described previously in this paragraph)
With respect to above-noted claimed element "employing a neural network" which is disclosed by RAVINDRAN: the teachings and/or suggestions within the disclosures of STEMPORA and GIGER thus far relied upon do not mention within the authors' descriptions an explicit and express recital of employing a neural network as required by the claim being considered. Nonetheless, herein relied upon are portions of the disclosure of RAVINDRAN which sufficiently teaches the feature appurtenant to the claimed invention as pointed out above with citation(s) to exemplary disclosures within RAVINDRAN that teach and/or suggest the claimed feature. At the time of effective filing date, it would have been obvious for one of ordinary skill in the art to have modified the combined and herein relied upon teachings of STEMPORA and GIGER by adding or substituting the feature employing a neural network as taught and/or suggested by RAVINDRAN, with a reasonable expectation of success of arriving at the claimed invention. The addition or substitution of this known feature by one of ordinary skill in the art at the time of the effective filing date would have yielded predictable results that were plainly ascertainable to that one person of ordinary skill in the art at that time. At the time of the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to have modified the teachings of STEMPORA and GIGER with these aforementioned teachings of "employing a neural network" sufficiently taught, suggested, and/or disclosed in RAVINDRAN because that skilled one artisan having ordinary skill in the art at the time of the effective filing date of the invention would have had a motivation of "to accurately classify the objects in the digital image". (RAVINDRAN: Abstract).
• 32 ¶ 4 • wherein the processor analyzes the otherwise non-diagnostic conventional image data of the applicant to determine a personal and/or health-related characteristic of the applicant, to use the determined personal and/or health-related characteristic to verify information provided by the applicant, and to substantially automatically determine the life insurance premium based at least in part upon the determined personal and/or health-related characteristic. Reference (STEMPORA: discloses e.g. "[i]n one embodiment a system for determining a level of risk associated with an individual for underwriting purposes comprises at least one sensor that provides information, such as a camera providing one or more images or video for example, used to determine one or more properties of the individual[; t]he individual information, such as eye related information, can be processed to generate cognitive information for the individual, which can be used to determine the level of risk associated with the individual[; t]he cognitive information can be compared to baseline cognitive information for the individual to determine the level of risk[; i]n another embodiment, a method for determining a level of risk or price of insurance includes obtaining information from a sensor, generating cognitive information from the sensor information, and generating a level of risk or price of insurance using at least the first cognitive information" Abstract and "an insurance underwriter may set-up an award or discount program for the cost of automobile insurance for individuals who improve their performance in a specific discipline or skill (such as an improvement cognitive capacity through the use of cognitive enhancement games or puzzles) and expect to see an improvement in safe vehicle operation by the individual over time[; i]n one embodiment, a resource may be provided to the individual to help modify their behavior andor improve their cognitive ability[; t]he resource may include training (such as risk avoidance training, for example), an application, seminar, instructional media, a game, a puzzle, cognitive enhancement application or tool, behavior modification application or tool, or other resource known to modify behavior andor facilitate enhancement of cognitive ability[; f]or example, a free mathematical puzzle application for a smartphone (such as a Sudoku application) may be offered to the individual and after installing opening the application, the individual's identity is verified (such as by using the built-in camera and facial recognition), and improved puzzle performance is rewarded by discounts to their automobile insurance" par. [0189] and "portable device functions or portable device software restrictions are controlled at least in part by a third party such as a parent, guardian, insurer, or employer[; i]n this embodiment, the third party may manage the portable device functions or software restrictions directly, indirectly, or using a risk analysis that may utilize a cognitive analysis[; t]he management may be performed directly on the device, remotely through wired or wireless communication, using a web or software application interface, in real-time, automatically, manually, or using instructions, conditions, settings, or algorithms pre-loaded onto the device or transmitted remotely" par. [0205])
Claim 33, EXAMINER's Analysis: Claim 33 is rejected as being unpatentable over STEMPORA and GIGER and RAVINDRAN. Claim 33 is a dependent claim that directly depends upon parent claim 32, which is an independent claim. Further to and in conjunction with the disclosures and teachings of the prior art recited in the parent as applied to the limitations of claim 32, STEMPORA and GIGER disclose and render obvious as previously combined the claimed subject matter of claim 33 as follows and as explained below.
Regarding and as per CLAIM 33, the system as set forth in claim 32, Reference (STEMPORA: discloses e.g. "[i]n one embodiment a system for determining a level of risk associated with an individual for underwriting purposes comprises at least one sensor that provides information, such as a camera providing one or more images or video for example, used to determine one or more properties of the individual[; t]he individual information, such as eye related information, can be processed to generate cognitive information for the individual, which can be used to determine the level of risk associated with the individual[; t]he cognitive information can be compared to baseline cognitive information for the individual to determine the level of risk[; i]n another embodiment, a method for determining a level of risk or price of insurance includes obtaining information from a sensor, generating cognitive information from the sensor information, and generating a level of risk or price of insurance using at least the first cognitive information" Abstract)
• 33 ¶ 2 • wherein the otherwise non-diagnostic conventional image data of the applicant includes a digital image. Reference (STEMPORA: discloses "the system comprises a camera providing one or more images or video used to determine one or more properties of the individual, such as the properties of one or more eyes of the individual (and optionally identification information) that is used to help determine risk[; i]n another example, the system comprises one or more sensors that determine facial or heart rate or circadian rhythm information[; t]he system may comprise one or more combinations of sensors andor cameras[; t]he sensor (such as a camera) may be mounted or built into a vehicle, a portable device, or an accessory for the vehicle or portable device, or worn by the individual[; t]he properties related to one or more eyes include one or more selected from the group pupil size or dilation, eyelid statemotion (incl. sleepy eyelid movement, blinking rate, closed eyelids, etc.), microsaccade amplitude, frequency or orientation, vergence, eye orientation, eye movement or fixation, gaze direction, gaze duration, details of the iris, symptoms of eye fatigue, and details of the retina[; t]he details of the iris or retina (andor information from an image of the face of the individual) may be used to provide operator identification information" par. [0004] and e.g. "[i]n one embodiment a system for determining a level of risk associated with an individual for underwriting purposes comprises at least one sensor that provides information, such as a camera providing one or more images or video for example, used to determine one or more properties of the individual[; t]he individual information, such as eye related information, can be processed to generate cognitive information for the individual, which can be used to determine the level of risk associated with the individual[; t]he cognitive information can be compared to baseline cognitive information for the individual to determine the level of risk[; i]n another embodiment, a method for determining a level of risk or price of insurance includes obtaining information from a sensor, generating cognitive information from the sensor information, and generating a level of risk or price of insurance using at least the first cognitive information" Abstract); (STEMPORA: doesn't expressly and explicitly recite a digital image. --- however GIGER: clearly discloses, teaches, and/or suggests the feature -- "automated analysis of digital images" par. [0003] or "inputting of digital images" par. [0034] or "digitizing and storing images obtained from an image acquisition device[; a]lternatively, the present invention can also be implemented to process digital data derived from images obtained by other means, such as a picture archive communication system (PACS)[; i]n other words, often the digital images being processed will be in existence in digital form and need not be converted to digital form in practicing the invention" par. [0066]), [See Remarks after Claim 24 Par. 2 herein for previously explained rationale or reasoned explanation supporting the finding of obviousness regarding the above-identified combination]
Claim 36, EXAMINER's Analysis: Claim 36 is rejected as being unpatentable over STEMPORA and GIGER and RAVINDRAN. Claim 36 is a dependent claim that directly depends upon parent claim 32, which is an independent claim. Further to and in conjunction with the disclosures and teachings of the prior art recited in the parent as applied to the limitations of claim 32, STEMPORA and RAVINDRAN disclose and render obvious as previously combined the claimed subject matter of claim 36 as follows and as explained below.
Regarding and as per CLAIM 36, the system as set forth in claim 32, Reference (STEMPORA: discloses e.g. "[i]n one embodiment a system for determining a level of risk associated with an individual for underwriting purposes comprises at least one sensor that provides information, such as a camera providing one or more images or video for example, used to determine one or more properties of the individual[; t]he individual information, such as eye related information, can be processed to generate cognitive information for the individual, which can be used to determine the level of risk associated with the individual[; t]he cognitive information can be compared to baseline cognitive information for the individual to determine the level of risk[; i]n another embodiment, a method for determining a level of risk or price of insurance includes obtaining information from a sensor, generating cognitive information from the sensor information, and generating a level of risk or price of insurance using at least the first cognitive information" Abstract)
• 36 ¶ 2 • wherein the neural network is a deep learning neural network. Reference (STEMPORA: doesn't expressly and explicitly recite wherein the neural network is a deep learning neural network. --- however RAVINDRAN: clearly discloses, teaches, and/or suggests the feature -- e.g. "a digital image may be processed by an ensemble of convolutional neural networks (CNNs) to classify objects in the digital image" Abstract or "classifying objects in a digital image using convolutional neural networks (CNNs)" par. [0006] or "[a]n image processing system, according to an example, builds and trains an ensemble of deep learning models, such as convolutional neural networks (CNNs), to accurately and automatically perform image processing to detect particular attributes of objects in a digital image, and to classify the objects according to the detected attributes" par. [0010] or "image processing using convolutional neural networks (CNNs)" par. [0022] or "[f]IG. 6 shows a flow chart diagram of an optimized convolutional neural network (CNN) 600" par. [0044]), [See Remarks after Claim 35 Par. 2 herein] and ("deep learning models, such as convolutional neural networks (CNNs)" par. [0010] or "providing an advanced deep learning architecture that exhibits superior classification accuracy to assess property damage and an iterative image processing system that determines that advanced deep learning architecture" par. [0012]), [See Remarks after Claim 27 Par. 2 herein] and [See Remarks after Claim 27 Par. 2 herein for previously explained rationale or reasoned explanation supporting the finding of obviousness regarding the above-identified combination]
Claim 37, EXAMINER's Analysis: Claim 37 is rejected as being unpatentable over STEMPORA and GIGER and RAVINDRAN. Claim 37 is a dependent claim that directly depends upon parent claim 32, which is an independent claim. Further to and in conjunction with the disclosures and teachings of the prior art recited in the parent as applied to the limitations of claim 32, STEMPORA discloses the claimed subject matter of claim 37 as follows and as explained below.
Regarding and as per CLAIM 37, the system as set forth in claim 32 See Prior Comment(s) at Claim 35 Par. 1;
• 37 ¶ 2 • wherein the otherwise non-diagnostic conventional image data of the applicant includes a video of the applicant, the processor being configured to determine at least one of a pulse, drug use, or a glucose level of the applicant by analyzing the video. Reference (STEMPORA: discloses "a camera providing one or more images or video used to determine one or more properties of the individual, such as the properties of one or more eyes of the individual (and optionally identification information) that is used to help determine risk[; i]n another example, the system comprises one or more sensors that determine facial or heart rate or circadian rhythm information[; t]he system may comprise one or more combinations of sensors andor cameras[; t]he sensor (such as a camera) may be mounted or built into a vehicle, a portable device, or an accessory for the vehicle or portable device, or worn by the individual[; t]he properties related to one or more eyes include one or more selected from the group pupil size or dilation, eyelid statemotion (incl. sleepy eyelid movement, blinking rate, closed eyelids, etc.), microsaccade amplitude, frequency or orientation, vergence, eye orientation, eye movement or fixation, gaze direction, gaze duration, details of the iris, symptoms of eye fatigue, and details of the retina[; t]he details of the iris or retina (andor information from an image of the face of the individual) may be used to provide operator identification information[; t]he eye related information can be processed to generate first cognitive information for individual, which can be used at least in part to generate the level of risk associated with the individual performing the activity[; f]acial andor hear rate andor circadian rhythm information, separately or used in combination with one or more other sensors, may be used to improve identification of cognitive states in some instances" par. [0004])
Claim 38, EXAMINER's Analysis: Claim 38 is rejected as being unpatentable over STEMPORA and GIGER and RAVINDRAN. Claim 38 is a dependent claim that directly depends upon parent claim 32, which is an independent claim. Further to and in conjunction with the disclosures and teachings of the prior art recited in the parent as applied to the limitations of claim 32, STEMPORA discloses the claimed subject matter of claim 38 as follows and as explained below.
Regarding and as per CLAIM 38, the system as set forth in claim 32, Reference (STEMPORA: discloses e.g. "[i]n one embodiment a system for determining a level of risk associated with an individual for underwriting purposes comprises at least one sensor that provides information, such as a camera providing one or more images or video for example, used to determine one or more properties of the individual[; t]he individual information, such as eye related information, can be processed to generate cognitive information for the individual, which can be used to determine the level of risk associated with the individual[; t]he cognitive information can be compared to baseline cognitive information for the individual to determine the level of risk[; i]n another embodiment, a method for determining a level of risk or price of insurance includes obtaining information from a sensor, generating cognitive information from the sensor information, and generating a level of risk or price of insurance using at least the first cognitive information" Abstract)
• 38 ¶ 2 • wherein the personal and/or health-related characteristic is at least one of age, sex, weight, height, ethnicity, lifespan, cause of death, tobacco use, alcohol use, drug use, diet, existing medical conditions, or risk factors for future medical conditions. See Prior Comment(s) at Claim 29 Par. 2;
Claim 39, EXAMINER's Analysis: Claim 39 is rejected as being unpatentable over STEMPORA and GIGER and RAVINDRAN. Claim 39 is an independent claim. The combined disclosures and teachings of STEMPORA and GIGER and RAVINDRAN taken together render obvious the claimed subject matter of claim 39 as follows and as explained below.
Regarding and as per CLAIM 39, a method for evaluating an applicant to determine one or more terms of insurance coverage, comprising: Reference (STEMPORA: discloses e.g. "method for determining an underwriting risk, risk score, or price of insurance" Title and e.g. "[i]n one embodiment a system for determining a level of risk associated with an individual for underwriting purposes comprises at least one sensor that provides information, such as a camera providing one or more images or video for example, used to determine one or more properties of the individual[; t]he individual information, such as eye related information, can be processed to generate cognitive information for the individual, which can be used to determine the level of risk associated with the individual[; t]he cognitive information can be compared to baseline cognitive information for the individual to determine the level of risk[; i]n another embodiment, a method for determining a level of risk or price of insurance includes obtaining information from a sensor, generating cognitive information from the sensor information, and generating a level of risk or price of insurance using at least the first cognitive information" Abstract)
• 39 ¶ 2 • receiving, by a data receiving circuit, image data of the applicant; Reference (STEMPORA: discloses e.g. "[i]n one embodiment a system for determining a level of risk associated with an individual for underwriting purposes comprises at least one sensor that provides information, such as a camera providing one or more images or video for example, used to determine one or more properties of the individual[; t]he individual information, such as eye related information, can be processed to generate cognitive information for the individual, which can be used to determine the level of risk associated with the individual[; t]he cognitive information can be compared to baseline cognitive information for the individual to determine the level of risk[; i]n another embodiment, a method for determining a level of risk or price of insurance includes obtaining information from a sensor, generating cognitive information from the sensor information, and generating a level of risk or price of insurance using at least the first cognitive information" Abstract)
• 39 ¶ 3 • training a processor to correlate aspects of appearance with a personal and/or health-related characteristic by providing the processor with image data of individuals having known personal and/or health-related characteristics; Reference (STEMPORA: doesn't expressly and explicitly recite training --- however RAVINDRAN: clearly discloses, teaches, and/or suggests the feature -- "[a]n image processing system, according to an example, builds and trains an ensemble of deep learning models, such as convolutional neural networks (CNNs), to accurately and automatically perform image processing to detect particular attributes of objects in a digital image, and to classify the objects according to the detected attributes" par. [0010]), [See Remarks Below]; (STEMPORA: discloses "a decision-making process algorithm is executed on one or more processors in a system to determine or process decision information for determining the risk assessment, the risk score, the underwriting, or the cost of insurance for an individual[; i]n one embodiment, the decision-making algorithm performs one or more of the tasks selected from the group identifies a risk-related decision; determines decision information; determines (with or without a degree of certainty or probability) contextual decision related information (such as the framework for the decision); determines (with or without a degree of certainty or probability) risk exposure information; determines (with or without a degree of certainty or probability) the use of one or more decision-making processes by the individual; determines (with or without a degree of certainty or probability) the use of one or more heuristic decision-making processes by the individual; determines the decision outcome; determines whether it is a negative, positive, or neutral decision outcome; correlates the actual or perceived risk exposure information with one or more decision-making processes (such as a heuristic); identifies the decision andor the individual on a scale from risk-seeking to risk-avoiding; analyzes historical decision information to provide decision information for a subsequent decision (such as a vehicle operator frequently choosing a particular decision-making process under a particular set of conditions); compares decision information for an individual with collective decision information from a plurality of individuals; identifies one or more patterns in decision information from a plurality of individuals; applies an identified pattern of decision related information from a plurality of individuals to determine, predict, or estimate the decision information for individual (including an individual within or not within the plurality of individuals)" par. [0046] and e.g. "[i]n one embodiment a system for determining a level of risk associated with an individual for underwriting purposes comprises at least one sensor that provides information, such as a camera providing one or more images or video for example, used to determine one or more properties of the individual[; t]he individual information, such as eye related information, can be processed to generate cognitive information for the individual, which can be used to determine the level of risk associated with the individual[; t]he cognitive information can be compared to baseline cognitive information for the individual to determine the level of risk[; i]n another embodiment, a method for determining a level of risk or price of insurance includes obtaining information from a sensor, generating cognitive information from the sensor information, and generating a level of risk or price of insurance using at least the first cognitive information" Abstract); (STEMPORA: doesn't expressly and explicitly recite by providing the processor with image data --- however GIGER: clearly discloses, teaches, and/or suggests the feature -- "obtaining image data representative of a medical image; computing at least one feature characteristic of the image data; comparing the computed feature characteristic to corresponding computed feature characteristics derived from images in a known image data set; selecting image data from images of the known image data set having corresponding computed feature characteristics similar to the feature characteristics computed in the computing step" par. [0011], Claim 1 or "an initial acquisition of a set of known medical images that comprise a database, and presentation of the images in digital format[; t]he lesion location in terms of estimated center is input from either a human or computer[; t]he method, system and computer readable medium that employs an intelligent search workstation for the computer assisted interpretation of medical images consists of the following stages: access to a database of known medical images with known/confirmed diagnoses of pathological state (step 112), computer-extraction of features of lesions within the known database (step 104), input method for an unknown case (step 102), computer-extraction of features of lesion of the unknown case (step 104), calculation of likelihood of pathological state (e.g., likelihood of malignancy) for the known and unknown cases (step 108), calculation of similarity indices for the unknown cases relative to each of the known cases (step 110), search among the known database based on the calculated similarity indices (step 114) and presentation of the "similar" cases and/or the computer-estimated features and/or likelihood of pathological state (step 116)[; a] specific example of the system is given for mass lesions in mammographic images in which the computer extracts features (step 104) and estimates the likelihood of malignancy for the known and the unknown cases (step 108), computes the similarity indices for each pair (step 110), and output cases that are similar in terms of individual features, combination of features, and/or computer-estimated likelihood of malignancy (step 116)" par. [0030] or "inputting of digital images" par. [0034], [See Remarks Below] and as already described in previous citation to this secondary disclosure within this same paragraph), [See Remarks after Claim 21 Par. 3 herein for previously explained rationale or reasoned explanation supporting the finding of obviousness regarding the above-identified combination]; (STEMPORA: discloses as described previously in this paragraph); (STEMPORA: doesn't expressly and explicitly recite known --- however GIGER: clearly discloses, teaches, and/or suggests the feature -- as described previously in this paragraph); (STEMPORA: discloses as described previously in this paragraph)
With respect to above-noted claimed element [2] "by providing" which is disclosed by GIGER: the teachings and/or suggestions within the disclosure of STEMPORA thus far relied upon fails to include within its descriptions an explicit and express recitation of [2] "by providing" as required by the instant claim. Notwithstanding the foregoing, herein relied upon are portions of the disclosure of GIGER which sufficiently teaches the feature applicable to the claimed invention as commented about above with reference(s) to exemplary disclosures within GIGER that teach and/or suggest the claimed feature. At the time of effective filing date, it would have been obvious for one of ordinary skill in the art to have modified the relied upon teachings of STEMPORA by adding or substituting the feature [2] "by providing" as taught and/or suggested by GIGER, with a reasonable expectation of success of arriving at the claimed invention. The addition or substitution of this known feature by one of ordinary skill in the art at the time of the effective filing date would have yielded predictable results that were readily foreseeable to that one person of ordinary skill in the art at that time. At the time of the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to have modified the teachings of STEMPORA with these previously described teachings of [2] "by providing" sufficiently taught, suggested, and/or disclosed in GIGER because that one skilled artisan having ordinary skill in the art at the time of the effective filing date of the invention would have had a motivation of "combines the benefit of computer-aided diagnosis with prior knowledge obtained via confirmed cases". (GIGER: par. [0013]).
With respect to above-noted claimed element [1] "training" which is disclosed by RAVINDRAN: the teachings and/or suggestions within the disclosures of STEMPORA and GIGER thus far relied upon do not record within the authors' writings the reciting explicitly and expressly of [1] "training" as required by the claim under examination. Notwithstanding the foregoing, herein relied upon are portions of the disclosure of RAVINDRAN which sufficiently teaches the feature applicable to the claimed invention as commented about above with citation(s) to exemplary disclosures within RAVINDRAN that teach and/or suggest the claimed feature. At the time of effective filing date, it would have been obvious for one of ordinary skill in the art to have modified the combined and herein relied upon teachings of STEMPORA and GIGER by adding or substituting the feature [1] "training" as taught and/or suggested by RAVINDRAN, with a reasonable expectation of success of arriving at the claimed invention. The addition or substitution of this known feature by one of ordinary skill in the art at the time of the effective filing date would have yielded predictable results that were readily ascertainable to that one person of ordinary skill in the art at that time. At the time of the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to have modified the teachings of STEMPORA and GIGER with these previously described teachings of [1] "training" sufficiently taught, suggested, and/or disclosed in RAVINDRAN because that skilled one artisan having ordinary skill in the art at the time of the effective filing date of the invention would have had a motivation of "to accurately classify the objects in the digital image". (RAVINDRAN: Abstract).
• 39 ¶ 4 • analyzing, by the processor, the image data of the applicant to determine a personal and/or health-related characteristic of the applicant; and Reference (STEMPORA: discloses e.g. "[i]n one embodiment a system for determining a level of risk associated with an individual for underwriting purposes comprises at least one sensor that provides information, such as a camera providing one or more images or video for example, used to determine one or more properties of the individual[; t]he individual information, such as eye related information, can be processed to generate cognitive information for the individual, which can be used to determine the level of risk associated with the individual[; t]he cognitive information can be compared to baseline cognitive information for the individual to determine the level of risk[; i]n another embodiment, a method for determining a level of risk or price of insurance includes obtaining information from a sensor, generating cognitive information from the sensor information, and generating a level of risk or price of insurance using at least the first cognitive information" Abstract)
• 39 ¶ 5 • suggesting, by the processor, a term of insurance coverage based at least in part upon the determined personal and/or health-related characteristic. Reference (STEMPORA: discloses e.g. "[i]n one embodiment a system for determining a level of risk associated with an individual for underwriting purposes comprises at least one sensor that provides information, such as a camera providing one or more images or video for example, used to determine one or more properties of the individual[; t]he individual information, such as eye related information, can be processed to generate cognitive information for the individual, which can be used to determine the level of risk associated with the individual[; t]he cognitive information can be compared to baseline cognitive information for the individual to determine the level of risk[; i]n another embodiment, a method for determining a level of risk or price of insurance includes obtaining information from a sensor, generating cognitive information from the sensor information, and generating a level of risk or price of insurance using at least the first cognitive information" Abstract)
Claim 40, EXAMINER's Analysis: Claim 40 is rejected as being unpatentable over STEMPORA and GIGER and RAVINDRAN. Claim 40 is a dependent claim that directly depends upon parent claim 39, which is an independent claim. Further to and in conjunction with the disclosures and teachings of the prior art recited in the parent as applied to the limitations of claim 39, STEMPORA discloses the claimed subject matter of claim 40 as follows and as explained below.
Regarding and as per CLAIM 40, the method as set forth in claim 39, Reference (STEMPORA: discloses e.g. "method for determining an underwriting risk, risk score, or price of insurance" Title)
• 40 ¶ 2 • wherein the term of insurance coverage includes an insurance premium or discount. See Prior Comment(s) at Claim 23 Par. 2;
5-th Prior Art Category: Claim 34 is rejected under 35 U.S.C. 103 as being unpatentable over STEMPORA in view of GIGER in further view of PEAK in even further view of RAVINDRAN.
Claim 34, EXAMINER's Analysis: Claim 34 is rejected as being unpatentable over STEMPORA and GIGER and PEAK and RAVINDRAN. Claim 34 is a dependent claim that directly depends upon parent claim 32, which is an independent claim. Further to and in conjunction with the disclosures and teachings of the prior art recited in the parent as applied to the limitations of claim 32, STEMPORA and PEAK disclose and render obvious as previously combined the claimed subject matter of claim 34 as follows and as explained below.
Regarding and as per CLAIM 34, the system as set forth in claim 32, Reference (STEMPORA: discloses e.g. "[i]n one embodiment a system for determining a level of risk associated with an individual for underwriting purposes comprises at least one sensor that provides information, such as a camera providing one or more images or video for example, used to determine one or more properties of the individual[; t]he individual information, such as eye related information, can be processed to generate cognitive information for the individual, which can be used to determine the level of risk associated with the individual[; t]he cognitive information can be compared to baseline cognitive information for the individual to determine the level of risk[; i]n another embodiment, a method for determining a level of risk or price of insurance includes obtaining information from a sensor, generating cognitive information from the sensor information, and generating a level of risk or price of insurance using at least the first cognitive information" Abstract)
• 34 ¶ 2 • wherein the otherwise non-diagnostic conventional image data of the applicant includes a selfie. Reference (STEMPORA: discloses "the system comprises a camera providing one or more images or video used to determine one or more properties of the individual, such as the properties of one or more eyes of the individual (and optionally identification information) that is used to help determine risk[; i]n another example, the system comprises one or more sensors that determine facial or heart rate or circadian rhythm information[; t]he system may comprise one or more combinations of sensors andor cameras[; t]he sensor (such as a camera) may be mounted or built into a vehicle, a portable device, or an accessory for the vehicle or portable device, or worn by the individual[; t]he properties related to one or more eyes include one or more selected from the group pupil size or dilation, eyelid statemotion (incl. sleepy eyelid movement, blinking rate, closed eyelids, etc.), microsaccade amplitude, frequency or orientation, vergence, eye orientation, eye movement or fixation, gaze direction, gaze duration, details of the iris, symptoms of eye fatigue, and details of the retina[; t]he details of the iris or retina (andor information from an image of the face of the individual) may be used to provide operator identification information" par. [0004] and e.g. "[i]n one embodiment a system for determining a level of risk associated with an individual for underwriting purposes comprises at least one sensor that provides information, such as a camera providing one or more images or video for example, used to determine one or more properties of the individual[; t]he individual information, such as eye related information, can be processed to generate cognitive information for the individual, which can be used to determine the level of risk associated with the individual[; t]he cognitive information can be compared to baseline cognitive information for the individual to determine the level of risk[; i]n another embodiment, a method for determining a level of risk or price of insurance includes obtaining information from a sensor, generating cognitive information from the sensor information, and generating a level of risk or price of insurance using at least the first cognitive information" Abstract); (STEMPORA: doesn't expressly and explicitly recite a selfie. --- however PEAK: clearly discloses, teaches, and/or suggests the feature -- e.g. "a user who is operating the medical monitoring application may be prompted to take a photo of themselves with the sensor(s) installed and attached to their body as proof that the medical or health status-related information was collected from the correct individual" par. [0075]); see also (STEMPORA: "a self-reporting mechanism, historical cognitive load measurements performing one or more physical andor mental activities, or using cognitive map information, and the cognitive load is evaluated using eye related information (and optionally facial information) obtained from a camera while the individual is performing a primary or goal state activity such as operating a vehicle" par. [0142]), [See Remarks after Claim 25 Par. 2 herein for previously explained rationale or reasoned explanation supporting the finding of obviousness regarding the above-identified combination]
6-th Prior Art Category: Claim 35 is rejected under 35 U.S.C. 103 as being unpatentable over STEMPORA in view of GIGER in further view of SHABUROV in even further view of RAVINDRAN.
Claim 35, EXAMINER's Analysis: Claim 35 is rejected as being unpatentable over STEMPORA and GIGER and SHABUROV and RAVINDRAN. Claim 35 is a dependent claim that directly depends upon parent claim 32, which is an independent claim. Further to and in conjunction with the disclosures and teachings of the prior art recited in the parent as applied to the limitations of claim 32, the combined disclosures and teachings of STEMPORA and SHABUROV and RAVINDRAN taken together render obvious the claimed subject matter of claim 35 as follows and as explained below.
Regarding and as per CLAIM 35, the system as set forth in claim 32 Reference (STEMPORA: discloses e.g. "[i]n one embodiment a system for determining a level of risk associated with an individual for underwriting purposes comprises at least one sensor that provides information, such as a camera providing one or more images or video for example, used to determine one or more properties of the individual[; t]he individual information, such as eye related information, can be processed to generate cognitive information for the individual, which can be used to determine the level of risk associated with the individual[; t]he cognitive information can be compared to baseline cognitive information for the individual to determine the level of risk[; i]n another embodiment, a method for determining a level of risk or price of insurance includes obtaining information from a sensor, generating cognitive information from the sensor information, and generating a level of risk or price of insurance using at least the first cognitive information" Abstract)
• 35 ¶ 2 • wherein the neural network is a convolutional neural network including a plurality of receptive fields which are tiled to overlap. Reference (STEMPORA: doesn't expressly and explicitly recite wherein the neural network --- however RAVINDRAN: clearly discloses, teaches, and/or suggests the feature -- e.g. "a digital image may be processed by an ensemble of convolutional neural networks (CNNs) to classify objects in the digital image" Abstract or "classifying objects in a digital image using convolutional neural networks (CNNs)" par. [0006] or "[a]n image processing system, according to an example, builds and trains an ensemble of deep learning models, such as convolutional neural networks (CNNs), to accurately and automatically perform image processing to detect particular attributes of objects in a digital image, and to classify the objects according to the detected attributes" par. [0010] or "image processing using convolutional neural networks (CNNs)" par. [0022] or "[f]IG. 6 shows a flow chart diagram of an optimized convolutional neural network (CNN) 600" par. [0044]), [See Remarks Below]; (STEMPORA: doesn't expressly and explicitly recite is a convolutional neural network including a plurality...receptive fields which are tiled to overlap. --- however SHABUROV: clearly discloses, teaches, and/or suggests the feature -- "[t]he step 940 of comparing may include applying at least one machine-learning algorithm such as a convolution neural network (CNN) and/or a state vector machine (SVM)[; g]enerally, CNN is a type of feed-forward artificial neural network where the individual neurons are tiled in such a way that they respond to overlapping regions in the visual field[; c]NNs consist of multiple layers of small neuron collections, which look at small portions of the input image, called receptive fields[; t]he results of these collections are then tiled so that they overlap to obtain a better representation of the original image; this is repeated for every such layer[; c]onvolutional networks may include local or global pooling layers, which combine the outputs of neuron clusters[; t]hey also consist of various combinations of convolutional layers and fully connected layers, with pointwise nonlinearity applied at the end of or after each layer[; t]o avoid the situation that there exist billions of parameters if all layers are fully connected, the idea of using a convolution operation on small regions, has been introduced[; o]ne major advantage of convolutional networks is the use of shared weight in convolutional layers, which means that the same filter (weights bank) is used for each pixel in the layer; this both reduces required memory size and improves performance" par. [0100]), [See Remarks after Claim 26 Par. 2 herein]
With respect to above-noted claimed element "wherein the neural network" which is disclosed by RAVINDRAN: the teachings and/or suggestions within the disclosures of STEMPORA and SHABUROV thus far relied upon omit to mention within the authors' explanations the reciting explicitly and expressly of wherein the neural network as recited in the claim under examination. Nevertheless, herein relied upon are portions of the disclosure of RAVINDRAN which sufficiently teaches the feature appurtenant to the claimed invention as commented about above with reference(s) to exemplary disclosures within RAVINDRAN that teach and/or suggest the claimed feature. At the time of effective filing date, it would have been obvious for one of ordinary skill in the art to have modified the combined and herein relied upon teachings of STEMPORA and SHABUROV by adding or substituting the feature wherein the neural network as taught and/or suggested by RAVINDRAN, with a reasonable expectation of success of arriving at the claimed invention. The addition or substitution of this known feature by one of ordinary skill in the art at the time of the effective filing date would have yielded predictable results that were plainly foreseeable to that one person of ordinary skill in the art at that time. At the time of the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to have modified the teachings of STEMPORA and SHABUROV with these previously described teachings of "wherein the neural network" sufficiently taught, suggested, and/or disclosed in RAVINDRAN because that one artisan of skill having ordinary skill in the art at the time of the effective filing date of the invention would have had a motivation of "to accurately classify the objects in the digital image". (RAVINDRAN: Abstract).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
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Sincerely,
/SLADE E SMITH/Primary Examiner, Art Unit 3696 01/30/2026