DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Arguments
Applicant’s arguments in combination with amendments, See remarks and claims, filed 11/10/2025, with respect to the rejection(s) of claim(s) 1-20 under 35 USC 101 have been fully considered but are not persuasive. Beginning on page 9, the applicant argues that the independent claims as amended recite limitations which amount to significantly more than the abstract idea and cannot be performed within a human’s mind [], the claim recite a “specific real time feedback loop integrated into the operation of a computer implemented system. This argument is fully considered but is not persuasive. The claim as recited does not provide any details regarding the number of data points or how fast the calculation needs to be done. The recitation of “dynamically adjusting []”, under its broadest reasonable interpretation only requires the values to be adjustable over time.
The applicant argues that the system modifies its prediction model and prioritizes subsequent recommendations towards historically effective intervention []. This argument is fully considered but is not persuasive. The claim as recited does not provide any specific treatment because the claim merely requires “adjusting at least one recommendation [], prioritizing at least one subsequent recommendation for the user toward content, activities or resources”.
Beginning on page 10, the applicant argues that the claim do not cover performance “purely in mind”, and do not amount to mere extra-solution activity. This argument is fully considered but is not persuasive. The claims as presented, recites an step that can be performed in mind, or by using a pen and paper, and therefore an abstract idea is involved. The additional limitations provided are provided at a high level of generality and is recited as performing generic computer functions. i.e., data gathering/processing and are mere extra-solution activity. For at least the reasons recited above, the 101 rejection is maintained. See detailed rejection below.
Applicant’s arguments in combination with amendments, See remarks and claims, filed 11/10/2025, with respect to the rejection(s) of claim(s) 1-20 under 35 USC 103 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Alailima (20200114115) in view of US 20150140527 to Gilad et al.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because of the following analysis:
1 – statutory category: Claims 1-12 and 20 recite a system/device, and therefore, falls under the statutory category of being a thing or products. See MPEP 2106.03. Claims 13-19 recite a series of steps and therefore, falls under the statutory category of being a process. See MPEP 2106.03.
2A – Prong 1: The independent claims 1, 13 and 20 recite a judicial exception by reciting the limitations of “capturing a plurality of signals associated with a mood, a mental state, or a combination thereof, associated with a user, interaction data associated with the user, or a combination thereof; labeling the plurality of signals based on an assessment of how engagement with content is to be interpreted; assigning, based on the plurality of signals, a score value relating to a mental health of the user; determining, based on the score value, the plurality of signals, or a combination thereof, a deficit or need of the user relating to the mental health of the user; determining a prediction relating to content, activities, resources, or a combination thereof, to be presented or delivered for interaction with the user to enhance the score value relating to the mental health of the user; providing access to the content, activities, resources, or a combination thereof; and dynamically adjusting the score value relating to the mental health of the user in real-time as the user interacts with the content, activities, resources, or a combination thereof, to provide an adjusted score value, dynamically adjusting at least one recommendation for the user based on the adjusted score value and other data associated with the user”. These limitations, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in mind or by a person using a pen and paper. The abstract idea here is related to the concepts performed in the human mind including an observation, evaluation, judgment, opinion, etc. Therefore, an abstract idea is involved.
It is noted that generally stating using and training an artificial intelligence model falls under the judicial exception, e.g., abstract ideas. The claim recites “determining by utilizing an artificial intelligence model” and “updating a prediction model”. The claim does not provide any detail about how the models are created or operated, and the plain meaning of “determining” and “updating” encompasses mental observation or evaluation and to continue the observation and/or evaluation. Furthermore, should the updating include training the models, such would represent mathematical calculations for iteratively adjusting the model.
2A – Prong 2: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements when considered both individually and as an ordered combination do not amount to significantly more than the abstract idea. The independent claims 1, 13, and 20 recite the additional limitations of “memory”, “application”, “processor”, “device of the user”, etc. The mentioned limitations are recited at a high level of generality and is recited as performing generic computer functions. i.e., data gathering/processing and are mere extra-solution activity. The elements amount to 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 2106.04(d) and 2106.05(f)). Accordingly, each of the additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limitations on practicing the abstract idea.
2B: The emphasized elements cited above do not amount to significantly more than the judicial exception because these limitations are simply appending well-understood, routine and conventional activities previously known in the industry, specified at a high level of generality, to the judicial exception, e.g., a claim to an abstract idea requiring no more than a generic computer to perform generic computer functions that are well-understood, routine and conventional activities previously known in the industry (see Electric Power Group, 830 F.3d 1350 (Fed. Cir. 2016); Alice Corp. v. CLS Bank Int’I, 110 USPQ2d 1976 (2014)).
In view of the above, the additional elements individually do not amount to significantly more than the above-judicial exception (the abstract idea). Looking at the limitations as an ordered combination (that is, as a whole) adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer, for example, or improves any other technology. There is no indication that the combination of elements permits automation of specific tasks that previously could not be automated. There is no indication that the combination of elements includes a particular solution to a computer-based problem or a particular way to achieve a desired computer-based outcome. Rather, the collective functions of the claimed invention merely provide conventional computer implementation, i.e., the computer is simply a tool to perform the process. Simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, e.g., a claim to an abstract idea requiring no more than a generic computer to perform generic computer functions that are well-understood, routine and conventional activities previously known to the industry, as discussed in Alice Corp., 573 U.S. at 225, 110 USPQ2d at 1984 (see MPEP § 2106.05(d)).
Claims 2-12 and 14-19 depend on claims 1 and 13, respectively. The mentioned dependent claims recite the same abstract idea as the independent claims. Furthermore, these claims only contain recitations that further limit the abstract idea (that is, the claims only recite limitations that further limit the mental process). For example, the dependent claim recites the limitations “device of the user”, “visually rendering the score value”, “user interface”, etc., are recited at a high level of generality and is recited as performing generic computer functions. i.e., data processing. The elements amount to 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 2106.04(d) and 2106.05(f)).
The additional elements individually do not amount to significantly more than the above-judicial exception (the abstract idea). Looking at the limitations as an ordered combination (that is, as a whole) adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer, for example, or improves any other technology. There is no indication that the combination of elements permits automation of specific tasks that previously could not be automated. There is no indication that the combination of elements includes a particular solution to a computer-based problem or a particular way to achieve a desired computer-based outcome. Rather, the collective functions of the claimed invention merely provide conventional computer implementation, i.e., the computer is simply a tool to perform the process.
Claim 8 is further directed toward an abstract idea for including mathematical calculations. Claim 8 recites the limitations of “training the artificial intelligence model based on []”. It is noted that the act of inputting training data into an intelligence model falls under the judicial exception of mathematical calculations. Additionally or alternatively, the training of the learning model by inputting training data, and adjusting the model accordingly additionally represents mathematical calculations or mental observations or evaluation to iteratively adjust the model.
Thus, claims 1-20 are directed to an abstract idea and are therefore rejected.
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 (i.e., changing from AIA to pre-AIA ) 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 text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over US Pat Pub No. 20200114115 granted to Titiimaea Alailima (hereinafter “Alailima”) in view of US 20150140527 to Gilad et al. (hereinafter “Gilad”).
Regarding claims 1, 13 and 20. Alailima discloses a system/method/computer readable device (e.g., para 0005, 0165 “a cognitive platform comprises the apparatus and/or system”), comprising: a memory that stores instructions (para 0165 “memory device”); and a processor that executes the instructions to perform operations (para 0005, 0165 “processor”), the operations comprising: capturing, via an application, a plurality of signals associated with a mood, a mental state, or a combination thereof, associated with a user, interaction data associated with the user, or a combination thereof (e.g., para 0165-0166 “receive plurality of user data [] user-generated input in response to a first/second instance”, and “one or more sensor inputs”, see step 1402 or 1406); labeling the plurality of signals based on an assessment of how engagement with content is to be interpreted (para 0165-0166 “compute, with the processor, the first/second plurality of user data [] to derive an effort metric based”, see step 404 or 1408); assigning, based on the plurality of signals, a score value relating to a mental health of the user (para 0166 “determine a quantified measure of user engagement associated with the second instance of the computerized stimuli or interaction based on the effort metric 1408” and “determine the measure of user engagement”; or see para 0109, 0119 for “user’s score”); determining, based on the score value, the plurality of signals, or a combination thereof, a deficit or need of the user relating to the mental health of the user (para 0166 “analyze or apply the quantified measure of user engagement to a specified engagement/effort threshold or trigger value or a pre-determined or adaptive range or spectrum of values corresponding to a characterization of measure of user engagement (e.g., insufficient effort, sufficient effort, optimal effort)” – which allows for determining the “deficiency” and/or “need”); determining, by utilizing an artificial intelligence model (para 0067-0070, 0165-0166 “the non-linear computational framework may comprise an artificial neural network; for example, a convolutional neural network or a recurrent neural network”), a prediction relating to content, activities, resources, or a combination thereof, to be presented or delivered for interaction with the user to enhance the score value relating to the mental health of the user; providing access to the content, activities, resources, or a combination thereof, to a device of the user (para 0166 “modify, adapt or deliver at least one user interface element or user prompt 1410 in response to the quantified measure of user engagement being below the specified threshold or trigger value and/or in accordance with the adaptive range or spectrum of effort/engagement characterization(s)”); and dynamically adjusting the score value relating to the mental health of the user in real-time as the user interacts with the content, activities, resources, or a combination thereof (para 0166 “analyzed in real-time”), to provide an adjusted score value, dynamically adjusting at least one recommendation for the user based on the adjusted score value and other data associated with the user, updating a prediction model associated with the prediction based on a measured change to the adjusted score value; and (para 0064 “feedback [] to adjust the difficulty level of the task, adjust types of tasks, and/or as feedback to the individual concerning the user's interaction with the computing device”) But fails to disclose prioritizing at least one subsequent recommendation for the user toward content, activities, or resources associated with greater score improvement.
Gilad, from a similar field of endeavor, teaches that it is known to have an interventions selection module that maps the context information to one or more recommended interventions and ranks the recommended interventions by relevance, and/or by conveying relevance in some other manner (para 0082). It would have been obvious before the effective filing date of the claimed invention to modify the disclosure of Alailima with the teachings of Gilad, because doing so would allow for ranking information as desired and provide the predictable result of mapping the context information to one or more recommended interventions.
Regarding claim 2. Alailima as modified by Gilad renders obvious the system of claim 1, wherein the operations further comprise dynamically adjusting recommendations for content, activities, resources, or a combination thereof, in real-time as the score value is adjusted, as the user interacts with the content, activities, or resources, as circumstances relating to the user change, or a combination thereof (see rejection of claim 1, para 0165-0166 “real time”, step 1410, 1506).
Regarding claim 3. Alailima as modified by Gilad renders obvious the system of claim 1, wherein the content, activities, or resources comprise one or more of a coaching session, a crisis resource, a community resource, a care activity, a therapy session, video content, gaming content, audio content, virtual reality content, augmented reality content, medical content, medical therapy sessions, surveys, mental health content, training content, or a combination thereof (para 0008 “the at least one user interface element or user prompt comprising a task or instruction associated with the computerized therapeutic treatment regimen”).
Regarding claim 4. Alailima as modified by Gilad renders obvious the system of claim 1, wherein the score value is comprised of score values relating to a plurality of variables utilized in determining the mental health of the user, and wherein the plurality of variables comprises one or more of a relationship variable, a physical variable, a mind variable, a positivity variable, an engagement variable, a mood tracker variable, a mental state variable, or a combination thereof (para 0083, 0150, etc.).
Regarding claim 5. Alailima as modified by Gilad renders obvious the system of claim 1, wherein the operations further comprise capturing the plurality of signals from the device of the user as the user interacts with the application (para 0165-0166 “computerized stimuli or interaction may comprise one or more user tasks being displayed via a graphical user interface”).
Regarding claim 6. Alailima as modified by Gilad renders obvious the system of claim 1, wherein the operations further comprise generating the content, activities, resources, or a combination thereof, such that the content, resources, or a combination thereof, are tailored to improving the mental health of the user (para 0166-0167 “the at least one user interface element or user prompt comprising a task or instruction associated with the computerized therapeutic treatment regimen”).
Regarding claim 7. Alailima as modified by Gilad renders obvious the system of claim 1, wherein the operations further comprise capturing the plurality of signals on a continuous basis or while the user is utilizing the application (para 0096, 0101 “to promote continued user interaction”, 0163).
Regarding claim 8. Alailima as modified by Gilad renders obvious the system of claim 1, wherein the operations further comprise training the artificial intelligence model based on information associated with the user and other users, information known to be associated with mental health, patterns associated with generating mental health diagnoses, information associated types of content to enhance mental health, or a combination thereof (para 0007, 0068, 0108-0110, etc., “training dataset []”).
Regarding claim 9. Alailima as modified by Gilad renders obvious the system of claim 1, wherein the operations further comprise adjusting a confidence score for the prediction based on whether the content, the activities, or the resources, affected the mental health of the user in a manner as predicted (para 0167 “outputs comprising one or more usage insights, graphical reports, and/or data visualizations corresponding to user trends, therapeutic efficacy [] view treatment adherence, treatment efficacy, and treatment outcomes for the patient-user”).
Regarding claim 10. Alailima as modified by Gilad renders obvious the system of claim 1, wherein the operations further comprise visually rendering the score value in a graph on a user interface of the device of the user, and wherein the operations further comprise visually rendering sub-scores of variables utilized in determining the score in the graph (para 0167 “outputs comprising one or more [] graphical reports, and/or data visualizations corresponding to user trends”).
Regarding claim 11. Alailima as modified by Gilad renders obvious the system of claim 1, wherein the operations further comprise determining which content, activities, or resources generated the highest improvement to the score value relating to the mental health of the user (para 0167 “therapeutic efficacy”, “outputs to one or more external or third-party user devices “ – would allow the viewer to determine which treatment has the highest efficacy).
Regarding claim 12. Alailima as modified by Gilad renders obvious the system of claim 11, wherein the operations further comprise providing a higher weight to the content, the activities, or the resources that generated the highest improvement to the score value in comparison to other content, other activities, or other resources (para 0057 “apply a weighting factor”).
Regarding claim 14. Alailima as modified by Gilad renders obvious the method of claim 13, further comprising training the artificial intelligence model based on interactions with the content, the activities, the resources, or a combination thereof (para 0007, 0068, 0108-0110, etc., “training dataset []”).
Regarding claim 15. Alailima as modified by Gilad renders obvious the method of claim 13, further comprising providing access to the content, activities, resources, or a combination thereof, to the device of the user via a user interface of the application (para 0156 “device 1004”).
Regarding claim 16. Alailima as modified by Gilad renders obvious the method of claim 13, further comprising recommending content, activities, resources, or a combination thereof, to the user based on the user having a threshold correlation with characteristics of another user (para 0166 “threshold”).
Regarding claim 17. Alailima as modified by Gilad renders obvious the method of claim 13, further comprising updating the adjusting a predictive capability of the artificial intelligence model based on interactions conducted by the user with respect to the content, activities, resources, or a combination thereof (para 0007, 0068, 0108-0110, etc., “training dataset []” para 0165-0166 “real time analyses”).
Regarding claim 18. Alailima as modified by Gilad renders obvious the method of claim 14, further comprising capturing sensor data including biometric data, visual content of the user, audio content associated with the user, virtual reality content associated with the user, augmented reality content associated with the user, or a combination thereof (para 0158 “measured sensor data (such as but not limited to accelerometer measurement data and/or touch screen measurement data”).
Regarding claim 19. Alailima as modified by Gilad renders obvious the method of claim 14, further comprising visually rendering adjustments to the score value to a user interface of the device of the user in real-time to advise the user to the adjustments to the score value based on interactions with the content, the activities, the resources, or a combination thereof (para 0165-0166 “real time”, “presented or rendered on graphical user interface []”).
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SANA SAHAND whose telephone number is (571)272-6842. The examiner can normally be reached M-Th 8:30 am -5:30 pm; F 9 am-3 pm.
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/SANA SAHAND/Examiner, Art Unit 3796