Prosecution Insights
Last updated: April 19, 2026
Application No. 18/455,597

METHODS AND APPARATUS FOR COACHING BASED ON NUTRITION

Final Rejection §101§DP
Filed
Aug 24, 2023
Examiner
UTAMA, ROBERT J
Art Unit
3715
Tech Center
3700 — Mechanical Engineering & Manufacturing
Assignee
Myfitnesspal Inc.
OA Round
2 (Final)
60%
Grant Probability
Moderate
3-4
OA Rounds
3y 6m
To Grant
90%
With Interview

Examiner Intelligence

Grants 60% of resolved cases
60%
Career Allow Rate
483 granted / 803 resolved
-9.9% vs TC avg
Strong +30% interview lift
Without
With
+30.0%
Interview Lift
resolved cases with interview
Typical timeline
3y 6m
Avg Prosecution
54 currently pending
Career history
857
Total Applications
across all art units

Statute-Specific Performance

§101
22.9%
-17.1% vs TC avg
§103
37.5%
-2.5% vs TC avg
§102
12.0%
-28.0% vs TC avg
§112
19.3%
-20.7% vs TC avg
Black line = Tech Center average estimate • Based on career data from 803 resolved cases

Office Action

§101 §DP
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 . 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 1-8, 10-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to judicial exception(s) without significantly more. [STEP 1] The claim recites at least one step. Thus, the claim is to a process, which is one of the statutory categories of invention (Step 1: YES). [STEP2A PRONG I] The claim(s) 1, 11 and 18 recite(s): generating a plurality of expected profiles for a plurality of data records within a user history database by: using a machine learning model to group users into the plurality of expected profiles; and using machine learning to generate heuristics and performance metrics for each of the plurality of expected profiles; associating a first user with a first expected profile of the plurality of expected profiles; receiving user input relating to nutrition consumption for the first user; in response to receiving the user input relating to nutrition consumption, identifying a caloric deficit or hydration deficit for the first user based on said nutrition consumption for the first user, and identifying one or more actionable items for the users to perform in response to determining the caloric defict or hydration deficit, wherein the one or more actionable items comprise at least a recommended workout recommending a workout for the first user based on the first expected profile, wherein the first expected profile includes at least one heuristic for generating dynamic feedback associated with the workout, wherein the at least one heuristic for generating the dynamic feedback comprises a rule for modifying the workout based on the nutrition consumption for the first user; and updating a user data record of the first user based on a logged performance corresponding to the workout. The non-highlighted aforementioned limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation between people but for the recitation of generic computer components. That is, other than reciting “database”, “processor”, “machine learning model” and “a client device” (see claim 11 and 18), nothing in the claim element precludes the step from practically being performed between people. For example, but for the recited language, the step in the context of this claim encompasses a doctor/nutritionist reviewing a user’s history, receiving a user’s consumption data, recommending workout based on the user and as well updating the user’s data record based on the user’s workout. If a claim limitation, under its broadest reasonable interpretation, covers observation, evaluation, judgment, opinion, then it falls within the “Mental Process” grouping of abstract ideas. Accordingly, the claim recites a judicial exception, and the analysis must therefore proceed to Step 2A Prong Two. [STEP2A PRONG II] This judicial exception is not integrated into a practical application. In particular, the claim only recites the additional element(s) – “database”, “processor”, “machine learning model” and “a client device”. The “database”, “processor”, “machine learning model” and “a client device” in the aforementioned steps are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer component. For example, paragraph 95-97 of the applicant’s specification only provides a generic mention of the use of the machine learning model to performed the claimed subject matter. Paragraph 70-71, 156 and 159 showing an implementation of the claimed subject matter using generic computer and database. Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea and the claim is therefore directed to the judicial exception. (Step 2A: YES). [STEP2B] The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a processor to perform the aforementioned steps amounts to no more than mere instructions to apply the exception using a generic computer component, which cannot provide an inventive concept. As noted previously, the claim as a whole merely describes how to generally “apply” the aforementioned concept in a computer environment. Thus, even when viewed as a whole, nothing in the claim adds significantly more (i.e., an inventive concept) to the abstract idea. The claim is not patent eligible. (Step 2B: NO). Claim(s) 2-10, 12-17 and 19-20 are dependent on supra claim(s) and includes all the limitations of the claim(s). Therefore, the dependent claim(s) recite(s) the same abstract idea. For example, claims 2-3 further defines the type of users of the system, claims 4-10, 12-17, 19-20 further defines the data that is used by the process. Thus, these claims recite no additional limitations. Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea and the claim is therefore directed to the judicial exception. Looking at the limitations as an ordered combination 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 or improves any other technology. Thus, even when viewed as a whole, nothing in the claim adds significantly more (i.e., an inventive concept) to the abstract idea. Response to Arguments Applicant terminal disclaimer submission has been accepted. As such, the obviousness double patenting rejection has been withdrawn With respect to applicant’s argument on the rejection under 35 U.S.C 101, the applicant provided the following argument: The abstract idea rejection is not valid since the claim is directed to the use of “machine learning model to group users into the plurality of expected profile” and using “machine learning to generate heuristics and performance metrics for each of the plurality of expected profiles”. The claim limitation is more similar to Enfish, McRO and are directed to the improvement of data retrieval functionality. The examiner notes that the use of “machine learning model” in the Applicant’s own specification seems to allow for the interpretation that the modelling includes the use of mental human assessment. For example, paragraph 40 of the Applicant’s specification shows that the in some embodiment the assessment include the use of a hybrid of human and machine learning assessment. Furthermore, the use of machine learning in this particular context are done in the generic fashion. A review of the specification paragraph 96 of the specification lists all the different type of machine learning currently used in the field. As such, the examiner takes the position the limitation of “ of “machine learning model to group users into the plurality of expected profile” and using “machine learning to generate heuristics and performance metrics for each of the plurality of expected profiles” are nothing more than mere instruction to apply an exception using generic computing technology (i.e. machine learning) since the applicant only recites a description of the solution to an using known machine learning methods with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result. Accordingly, the examiner concludes applicant argument are not sufficient to overcome the current rejection under 35 U.S.C 101. With respect to applicant’s argument that current claim limitation is similar to Enfish , McRO and is directed to an improvement to the data retrieval technology and/or the ability to make unique recommendation to the user. The examiner respectfully disagrees. In order to show an improvement: “the specification must be evaluated to determine if the disclosure provides sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. The specification need not explicitly set forth the improvement, but it must describe the invention such that the improvement would be apparent to one of ordinary skill in the art” [see MPEP 2106.04(d)(1)] A review of the specification does not show how one of ordinary skilled in the art would be able to recognize the current claim limitation to be an improvement in the data retrieval technology. However, the specification fails to provide any teaching that would provide an improvement to the data retrieval technology. The specification is clear that the invention is directed to an improvement of the providing workout recommendation and coaching (see Applicant’s specification paragraph 5-6, 154) or an improvement on how the user/consumer navigates their fitness journey (see Applicant’s specification paragraph 37). The examiner notes these disclosure are not sufficient evidence to show an improvement to computer technology or improvement to the technical field as the specification only shows improvement to the abstract idea itself. Accordingly, the examiner concludes applicant argument are not sufficient to overcome the current rejection under 35 U.S.C 101. 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 ROBERT J UTAMA whose telephone number is (571)272-1676. The examiner can normally be reached 9:00 - 17:30 Monday - Friday. 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, Kang Hu can be reached at (571)270-1344. 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. /ROBERT J UTAMA/Primary Examiner, Art Unit 3715
Read full office action

Prosecution Timeline

Aug 24, 2023
Application Filed
Feb 06, 2025
Non-Final Rejection — §101, §DP
Jun 11, 2025
Response after Non-Final Action
Jun 11, 2025
Response Filed
Jul 02, 2025
Response Filed
Jul 02, 2025
Response after Non-Final Action
Mar 11, 2026
Final Rejection — §101, §DP (current)

Precedent Cases

Applications granted by this same examiner with similar technology

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WEARABLE TERMINAL, PRESENTATION METHOD, AND RECORDING MEDIUM
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Patent 12562072
ADAPTIVE AUDIO AND AUDIOVISUAL RECURSIVE SELF-FEEDBACK FOR SPEECH THERAPY
2y 5m to grant Granted Feb 24, 2026
Patent 12548457
METHOD AND ARRANGEMENT FOR ASSISTED EXECUTION OF AN ACTIVITY
2y 5m to grant Granted Feb 10, 2026
Patent 12542070
TEACHING AID
2y 5m to grant Granted Feb 03, 2026
Patent 12536788
TRACKING DIET AND NUTRITION USING WEARABLE BIOLOGICAL INTERNET-OF-THINGS
2y 5m to grant Granted Jan 27, 2026
Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

3-4
Expected OA Rounds
60%
Grant Probability
90%
With Interview (+30.0%)
3y 6m
Median Time to Grant
Moderate
PTA Risk
Based on 803 resolved cases by this examiner. Grant probability derived from career allow rate.

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