DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on February 17, 2026 has been entered.
Notice to Applicant
Claims 1, 8, and 15 have been amended. Now, claims 1-20 remain pending and will be examined herein.
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.
3. Claims 1-20 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.
4. Claims 1-20 are directed to computing a quality of life metric, which is considered managing personal behavior. Managing personal behavior fall within a subject matter grouping of abstract ideas which the Courts have considered ineligible (Certain methods of organizing human activity). The claims do not integrate the abstract idea into a practical application, and do not include additional elements that provide an inventive concept (are sufficient to amount to significantly more than the abstract idea).
Under step 1 of the Alice/Mayo framework, it must be considered whether the claims are directed to one of the four statutory classes of invention. In the instant case, claim 1-7 recite a method and at least one step. Claims 8-14 recite a system comprising a memory and processor. Claims 15-20 recite a non-transitory computer-readable storage media. Therefore, the claims are each directed to one of the four statutory categories of invention (process, manufacture, apparatus).
Under step 2A of the Alice/Mayo framework, it must be considered whether the claims are “directed to” an abstract idea. That is, whether the claims recite an abstract idea and fail to integrate the abstract idea into a practical application.
Regarding independent claim 1, the claim sets forth a process in which computing a quality of life metric is performed for improving a quality of life of an individual or group of individuals, including through the facilitation of managing personal behavior, in the following limitations:
receiving a dataset comprising time-series data pertaining to a QOL factor for the individual or group of individuals;
determining a relative importance of the QOL factor for the individual or group of individuals and filtering the dataset based on the relative importance;
computing a QOL metric associated with the individual or group of individuals;
determining an intervening measure based on the QOL metric;
requesting an application of the intervening measure based on the QOL metric;
wherein the application of the intervening measure comprises inserting the intervening measure and analyzing, the QOL factor to determine a level of efficacy of the intervening measure based on the relative importance;
wherein the application of the intervening measure further comprising determining, one ore more gaps associated with the QOL factor and filling the one or more gaps based on a plurality of user inputs associated with the QOL factor; and
modifying the QOL metric based on a plurality of intervening measure data comprising the level of efficacy derived from the application of the intervening measure and reflecting the modified QOL metrics on a chart.
The above-recited limitations are directed to computing a quality of life metric for improving a quality of life of an individual or group of individuals. This arrangement amounts to managing personal behavior. Such concepts have been considered ineligible certain methods of organizing human activity by the Courts (See MPEP 2106.04(a)).
Claim 1 does recite additional elements:
Via a computing device;
One or more machine learning models.
These additional elements merely amount to the general application of the abstract idea to a technological environment (“via a computing device”, “one or more machine learning models”) and insignificant pre-and-post solution activity (receiving, determining, computing, requesting, inserting, and modifying). The specification makes clear the general-purpose nature of the technological environment. Paragraphs 21, 22, 25, and 35 indicate that while exemplary general purpose systems may be specific for descriptive purposes, any elements or combinations of elements capable of implementing the claimed invention are acceptable. That is, the technology used to implement the invention is not specific or integral to the claim.
Therefore, considered both individually and as an ordered combination, the additional elements do no more than generally link the use of the abstract idea to a particular technological environment or field of use. That is, given the generality with which the additional limitations are recited, the limitations do not implement the abstract idea with, or use the abstract idea in conjunction with, a particular machine or manufacture that is integral to the claim. Additionally, the claims do not reflect an improvement in the functioning of a computer, or an improvement to other technology or technical field, do not apply or use the abstract idea to effect a particular treatment or prophylaxis for a disease or medical condition, do not effect a transformation or reduction of a particular article to a different state or thing; and do not apply or use the abstract idea in some other meaningful way beyond generally linking the use of the abstract idea to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the abstract idea. Accordingly, the Examiner concludes that the claim fails to integrate the abstract idea into a practical application, and is therefore “directed to” the abstract idea.
Under step 2B of the Alice/Mayo framework, it must finally be considered whether the claim includes any additional element or combination of elements that provide an inventive concept (i.e., whether the additional element or elements are sufficient to amount to significantly more than the abstract idea). As indicated above, considered both individually and as an ordered combination, the additional elements do not implement the abstract idea with, or use the abstract idea in conjunction with, a particular machine or manufacture that is integral to the claim, do not reflect an improvement in the functioning of a computer, or an improvement to other technology or technical field, do not apply or use the abstract idea to effect a particular treatment or prophylaxis for a disease or medical condition, do not effect a transformation or reduction of a particular article to a different state or thing, and do not apply or use the abstract idea in some other meaningful way beyond generally linking the use of the abstract idea to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the abstract idea
Further, the additional elements (recited above) simply append well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception. Communicating information (i.e., receiving or transmitting data over a network) has been repeatedly considered well-understood, routine, and conventional activity by the Courts (See MPEP 2106.05(d)). Accordingly, the Examiner asserts that the additional elements, considered both individually, and as an ordered combination, do not provide an inventive concept, and the claim is ineligible for patent.
Independent Claims 8 and 15 are parallel in scope to claim 1 and ineligible for similar reasons.
Regarding Claims 2, 9, and 16
Claims 2, 9, and 16 sets forth:
correlating the QOL metric to at least one QOL value associated with a questionnaire presented to a user.
Such a recitation merely embellishes the abstract idea of computing a quality of life metric, which is considered managing personal behavior. While the claim does set forth the additional limitation of “via the computing device”, this recitation is similar to the additional limitations in claim 1, as it does no more than generally link the use of the abstract idea to a particular technological environment. As such, it does not integrate the abstract idea into a practical application, and does not provide an inventive concept. Accordingly, the claim does not confer eligibility on the claimed invention and is ineligible for similar reasons to claim 1.
Each of these steps of the dependent claims 2-7, 9-14, and 16-20 only serve to further limit or specify the features of independent claims 1, 8, and 15 accordingly, and hence are nonetheless directed towards fundamentally the same abstract idea as the independent claim and utilize the additional elements already analyzed in the expected manner.
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.
5. 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.
6. Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over United States Patent Application Publication Number 2014/0156308, Ohnemus, et al., hereinafter Ohnemus in view of United States Patent Application Number 2011/0105852, Morris, et al., hereinafter Morris.
7. Regarding claim 1, Ohnemus discloses a computer-implemented method for improving a quality of life (QOL) of an individual or a group of individuals, the method comprising:
receiving, via a computing device, a dataset comprising time-series data pertaining to a QOL factor for the individual or group of individuals, (para. 60, The scores can be combined using a dynamic weighing scheme based on the relevance of each for a given user and at a given time, and para. 62, The input data for these models can include several sources, including inputs associated with family, demographics and metabolism, as well as other user inputs and parameters derived by internal models that use the inputs, data derived from the Quality of Life model, and data collected from one or more processes, substantially as shown and described herein);
determining, via the computing device, a relative importance of the QOL factor for the individual or group of individuals and filtering the dataset based on the relative importance, (para. 142, Filtering (such as by risk and alert state), and para. 145, The feedback loop engine of the present application can learn and store important statistical lifestyle data of the user that helps the user to navigate through the complexity of life);
computing, via the computing device, a QOL metric associated with the individual or group of individuals, (para. 178, The Metric Health Model score can be based on medical parameter information of a user, such as their medical history information, attributes, physiological metrics, and lifestyle information to the system.);
determining, via the computing device, an intervening measure based on the QOL metric, (para. 140, inspire users to improve their health score and overall life quality, and provide intelligent suggestions based on a user's data input on the system);
requesting, via the computing device, an application of the intervening measure based on the QOL metric, (para. 141, The avatar "Q" can appear on both a web platform and in a mobile app and can communicate with users in various ways, including but not limited to speech bubbles. In one or more implementations, the avatar will access content from the various trackers and situations on the platform to allow intelligent interactions with the user. The avatar "Q" can function as a coach to regular users and assist them in their training by providing training plans);
wherein the application of the intervening measure comprises inserting the intervening measure into one or more machine learning models and analyzing, via the one or more machine learning models, the QOL factor to determine a level of efficacy of the intervening measure based on the relative importance of the QOL factor, (para. 62, These risk factors may be not directly included in the core risk models that are quantified using models and data from studies and para. 67, The effect of changing any particular MRF from a current value to an ideal, best value can be quantified by determining the difference between the corresponding two metric health scores, thus producing a first recommendation, namely to focus on the MRF that produces the largest effect and para. 68, values can be a ranking of the lifestyle components by their effect on each of the MRF); and
modifying, via the computing device, the QOL metric based on a plurality of intervening measure data comprising the level of efficacy derived from application of the intervening measure and reflecting the modified QOL metric on a chart, (para. 68, values can be a ranking of the lifestyle components by their effect on each of the MRF, para. 145, the components of the health score Platform are interlinked so as to suggest ways for users to improve their health and their health score, based on an intimate knowledge of the health score and para. 171, the system can provide encouragement to the user to maintain a course of activity or modify behavior. For example, the system can send a message to the user indicating that if the user increased fitness activity by a certain amount of time, the health score would go up by a certain amount and para. 173, Charts can be generated in order for a user to track progress and analyze where there can be improvement in behavior).
Ohnemus does not teach wherein the application of the intervening measure further comprises determining, via the computing device, one or more gaps associated with the QOL factor and filling the one or more gaps based on a plurality of user inputs associated with the QOL factor.
However, Morris teaches wherein the application of the intervening measure further comprises determining, via the computing device, one or more gaps associated with the QOL factor and filling the one or more gaps based on a plurality of user inputs associated with the QOL factor, (para. 31, the use of imputation enables the approaches herein the determine how different a first person, for whom data is missing data, is from other persons who have similar characteristics, as determined by weights in regression equations. In one embodiment, the Archimedes Optimizer can calculate risk regardless of the number of missing data values or the nature of the missing data values. In an embodiment, the Archimedes Optimizer only requires an age value and a gender value for a patient, and uses imputation techniques to fill in gaps in data).
At the time of Applicant's filed invention, it would have been obvious to one of ordinary skill in the art to modify the method of Ohnemus with the teaching of Morris. As suggested by Morris, one would have been motivated to include this feature to allow the use of imputation to supply missing data values, (Morris [0001]), to modify the method of Ohnemus with the teaching of Morris.
8. Regarding claim 2, Ohnemus discloses the method of claim 1 as described above. Ohnemus further discloses correlating, via the computing device, the QOL metric to at least one QOL value associated with a questionnaire presented to a user, (para. 106, The food/nutrition tracker feature can target sustainable lifestyle changes by using more specific questions and tailored, practical prompts).
9. Regarding claim 3, Ohnemus discloses the method of claim 1 as described above. Ohnemus further discloses wherein the QOL factor includes at least one of a mood, a sleep quality, an amount of sleep, a level of mobility, a pain frequency, a pain intensity, or a daily activity associated with the individual or group of individuals, (para. 98, The domains include 1) physical activity, 2) stress, 3) sleep and 4) diet).
10. Regarding claim 4, Ohnemus discloses the method of claim 1 as described above. Ohnemus further discloses
generating, via the computing device, training data from the time-series data, (para. 121, The health score in accordance with the present application can represent a "living score," one that is dynamic and learning over time. With the introduction of new information from the user, and new medical breakthroughs and developments, the algorithm can be optimized over time);
generating, via the computing device, a machine-learned output from a machine learning model trained with the training data, (para. 53, three interrelated components can be included in calculating the user's health score: a metric health model ("MHM"), which includes subjective information from the user about who the user is; a quality of life model ("QLM"), which includes subjective information from the user about how the user feels; and a lifestyle model ("LSM") which includes subjective information from the user about the user lives. three interrelated components can be included in calculating the user's health score: a metric health model ("MHM"), which includes subjective information from the user about who the user is; a quality of life model ("QLM"), which includes subjective information from the user about how the user feels; and a lifestyle model ("LSM") which includes subjective information from the user about the user lives, and para. 121, The health score in accordance with the present application can represent a "living score," one that is dynamic and learning over time. With the introduction of new information from the user, and new medical breakthroughs and developments, the algorithm can be optimized over time); and
assigning, via the computing device, a plurality of weights to the machine-learned output based on the relative importance of the QOL factor, (para. 51, Predetermined weighting factors can be used to assign a relative value of each of the parameters that are used to calculate the health score. The user's health score can be then calculated by combining the weighted parameters in accordance with an algorithm).
11. Regarding claim 5, Ohnemus discloses the method of claim 1 as described above. Ohnemus further discloses wherein a machine-learned model associated with the machine-learned output is configured to linearly combine the machine-learned output based on the plurality of weights, (para. 51, Predetermined weighting factors can be used to assign a relative value of each of the parameters that are used to calculate the health score. The user's health score can be then calculated by combining the weighted parameters in accordance with an algorithm and para. 70, The individual weighted scores, when summed and linearly normalized into the 0-1,1000 interval, define the overall Lifestyle Score, and 45% of the overall health score).
12. Regarding claim 6, Ohnemus discloses the method of claim 1 as described above. Ohnemus further discloses wherein the intervening measure is configured to improve the QOL of the individual or group of individuals based on the QOL metric exceeding a threshold value established, via the computing device, based on the time-series data, (para. 169, feedback can be provided to an administrator such as a gym staff member where it is determined that a user is exceeding a predetermined threshold (which due to knowledge of their health can be varied respective to their health score or other recorded data)).
13. Regarding claim 7, Ohnemus discloses the method of claim 1 as described above. Ohnemus further discloses wherein the QOL metric is configured to be utilized, via the computing device, to determine the level of efficacy of the intervening measure, (para. 67, The effect of changing any particular MRF from a current value to an ideal, best value can be quantified by determining the difference between the corresponding two metric health scores, thus producing a first recommendation, namely to focus on the MRF that produces the largest effect).
14. Regarding claims 8-14, these claims are rejected for the same reasons as set forth above with regard to claims 1-7. Ohnemus discloses one or more processors, one or more computer-readable memories, and program instructions stored on at least one of the one or more computer-readable memories for execution by at least one of the one or more processors to cause the computer system to perform a series of steps, (para. 7).
15. Regarding claims 15-20, these claims are rejected for the same reasons as set forth above with regard to claims 1, 2, 4, 6 and 7. Ohnemus discloses one or more non-transitory computer-readable storage media and program instructions stored on the one or more non-transitory computer-readable storage media, the program instructions, when executed by the computing device, cause the computing device to perform a series of steps, (para. 7).
Response to Arguments
16. Applicant's arguments filed January 21, 2026 (RCE filed February 17, 2026) have been fully considered but they are not persuasive.
A. Applicant argues that the claimed invention is analogous to Example 48 of the 2019 PEG, and that the claims are eligible as they do not recite a judicial exception and that the human mind along cannot practically perform the features of Applicant’s amended claim 1.
In response, Examiner respectfully disagrees. The claims do not integrate the abstract idea into a practical application, and do not include additional elements that provide an inventive concept (are sufficient to amount to significantly more than the abstract idea). (Digitech Image Tech., LLC v. Electronics for Imaging, Inc. (Fed. Cir. 2014)). This judicial exception is not integrated into a practical application. In particular, the claim only recites additional elements of a computing device and a machine learning model. The elements in each of these independent claims are recited at a high-level of generality (i.e., a computing device, a machine learning model, one or more processors, one or more computer-readable memories, and one or more non-transitory computer-readable storage media and program instructions stored on the one or more non-transitory computer-readable storage media), such that the claims are directed to utilizing general purpose computer components (Application Specification [0021], [0035], [0040], and [0041])). As such, the limitations amount to no more than 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).
As a result, there are no meaningful limitations in the claim that transform the exception into a patent eligible application such that the claim amounts to significantly more than the exception itself, and the claims are properly rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter. Thus, the claims do not recite additional limitations that integrate the exception into a Practical Application.
With regard to Example 48, the claims in the instant application and the claims in Example 48 follow a completely different fact pattern. The eligible claims in Example 48 are directed to an improvement to existing computer technology or to the technology of speech separation and an improvement to existing speech-to-text technology. The present claims are directed to receiving data with regard to a Quality of Life (QOL) factor for an individual or group, determining a relative importance of the QOL factor, computing a metric, determining an intervening measure, requesting an application of the intervening measure, analyzing the QOL factor to determine a level of efficacy of the intervening measure, determining one or more gaps associated with the QOL factor, and modifying the QOL metric, in the same manner a computer would be used to process data, it is not transforming anything in the manner in which Example 48 is performing a transformation. In Example 48, “the claim reflects these technical improvements discussed in the disclosure by reciting details of how the DNN trained on source separation aids in the cluster assignments to correspond to the sources identified in the mixed speech signal, which are then converted into separate speech signals in the time domain to generate a sequence of words from the spectral features, thereby making individual transcription of each separated speech signal possible”. Therefore, the claims in the instant application are in no way analogous to Example 48.
As recited above, the above-recited limitations are directed to computing a quality of life metric for improving a quality of life of an individual or group of individuals. This arrangement amounts to managing personal behavior. Such concepts have been considered ineligible certain methods of organizing human activity by the Courts (See MPEP 2106.04(a)). Examiner submits that the abstract idea does not read on the entirety of the inventive concept — specifically on the computing device, a machine learning model, one or more processors, one or more computer-readable memories, and one or more non-transitory computer-readable storage media and program instructions stored on the one or more non-transitory computer-readable storage media. However, the use of electronic means for performing the abstract idea is not enough to overcome Step 2A Prong 1 (2019 Revised Patent Subject Matter Eligibility Guidance, 84 FED. REG. 4 (January 7, 2019) at p. 8 footnote 54 further citing Intellectual Ventures | LLC v. Symantec Corp., 838 F.3d 1307, 1316-18 (Fed. Cir. 2016) where the electronic implementation of human activity was not adequate to overcome Step 2A Prong 1). Examiner agrees that the additional elements that the applicant asserts are not a method of organizing human activity and are instead analyzed under prong 2 and step 2B as additional elements to the abstract idea.
Accordingly, it does not amount to significantly more, and the application of the abstract idea is therefore not eligible.
B. Applicant argues that Ohnemus fails to teach " wherein the application of the intervening measure further comprises determining, via the computing device, one or more gaps associated with the QOL factor and filling the one or more gaps based on a plurality of user inputs associated with the QOL factor".
Applicant’s arguments with respect to claim 1 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
METHODS FOR DATA COLLECTION AND DISTRIBUTION (US 20130185096 A1) teaches performing research in which participation is incentivized by early access to the data and samples collected. Also provided are methods for distributing research data.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to AMBER ALTSCHUL MISIASZEK whose telephone number is (571)270-1362. The examiner can normally be reached M-F 9AM-5PM.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Fonya Long can be reached at 571-270-5096. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/AMBER A MISIASZEK/Primary Examiner, Art Unit 3682