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 was filed in this application after a decision by the Patent Trial and Appeal Board, but before the filing of a Notice of Appeal to the Court of Appeals for the Federal Circuit or the commencement of a civil action. 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examination under 37 CFR 1.114 and the fee set forth in 37 CFR 1.17(e) has been timely paid, the appeal has been withdrawn pursuant to 37 CFR 1.114 and prosecution in this application has been reopened pursuant to 37 CFR 1.114. Applicant’s submission filed on 11/12/2025 has been entered.
Notice to Applicant
This communication is in response to the amendment filed 11/12/2025. Claims 1, 11 have been amended. Claims 1-20 are presented for examination.
Subject Matter Free of Prior Art
Claim(s) 1-20 are allowable over prior art because the prior art of record fail to expressly teach or suggest, either alone or in combination, the features found within the independent claims, in particular: “obtain an activity profile, wherein the activity profile comprises at least an adjacent motion; identify a plurality of activity categories as a function of the activity profile, wherein identifying the plurality of activity categories further comprises: using an activity category classifier, wherein the activity category classifier is trained to categorize activities listed within the activity profile to categories of activities and add activity recommendations based on the categories of activities,” “output the circuit protocol as a function of the at least a change in mode, wherein the circuit protocol comprises altering a gut microbiome of a user, wherein the circuit protocol is further configured to reduce injury risk as a function of an injury forecaster, and wherein the injury forecaster is configured to assess a probability of musculoskeletal injury using historical activity and biometric data.” Because the prior art does not teach or disclose the above features in the specific manner and combinations recited in independent claims 1, 11, claims 1, 11 are hereby deemed to be allowable over prior art. Originally numbered dependent claims 2-10, 12-20 incorporate the allowable features of originally numbered independent claims 1, 11, through dependency, respectively.
However, the claims are still rejected under 101.
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 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. Based upon consideration of all of the relevant factors with respect to the claims as a whole, the claims are directed to non-statutory subject matter which do not include additional elements that are sufficient to amount to significantly more than the judicial exception because of the following analysis:
Claim 1 is drawn to an apparatus which is within the four statutory categories (i.e., machine). Claim 11 is drawn to a method which is within the four statutory categories (i.e., method).
Independent claim 1 (which is representative of independent claim 11) recites… receive at least a BMI representation and a circuit record comprising at least a digestion mode; generate, as a function of the circuit record, at least a change of mode, wherein generating the at least a change of mode further comprises: retrieving an activity baseline, wherein the activity baseline comprises an intensity baseline, a cardio baseline, and a muscularity baseline; receiving training data containing a plurality of data entries containing a plurality of inputs containing functional elements correlated to a plurality of outputs containing the at least a BMI representation…; calculate a desired BMI change as a function of the at least a BMI representation, wherein the desired BMI change comprises at least a change in insulin resistance; produce at least a change in mode as a function of the trained machine learning model, and the circuit record; obtain an activity profile, wherein the activity profile comprises at least an adjacent motion; identify a plurality of activity categories as a function of the activity profile, wherein identifying the plurality of activity categories further comprises: using an activity category [model], wherein the activity category [model]is trained to categorize activities listed within the activity profile to categories of activities and add activity recommendations based on the categories of activities; compute a desired increase in activity as a function of the activity baseline; establish an activity type as a function of a plurality of activity types, wherein identifying the activity type further comprises: using an activity type [model]; and output the circuit protocol as a function of the at least a change in mode, wherein the circuit protocol comprises altering a gut microbiome of a user, wherein the circuit protocol is further configured to reduce injury risk as a function of an injury forecaster, and wherein the injury forecaster is configured to assess a probability of musculoskeletal injury using historical activity and biometric data.
Under its broadest reasonable interpretation, the limitations noted above, as drafted, covers certain methods of organizing human activity (i.e., managing personal behavior or relationships or interactions between people…following rules or instructions), but for the recitation of generic computer components. That is, other than reciting a “computing device” (claim 1) and “processor” (claim 11), the claim encompasses rules or instructions followed to collect data, analyze the collected data, and output health recommendations for a user based on the analysis accordingly. If a claim limitation, under its broadest reasonable interpretation, covers managing personal behavior or relationships or interactions between people, but for the recitation of generic computer components, then it falls within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas. Accordingly, the claims recite an abstract idea.
Independent claim 1 further recites… training a machine learning model as a function of a machine learning algorithm and the training data.
Under the broadest reasonable interpretation, the limitations noted above, as drafted, covers mathematical relationships, but for the recitation of generic computer components. For example, with regards to training a machine learning model, the specification mentions: “Connections between nodes may be created via the process of "training" the network, in which elements from a training data 204 set are applied to the input nodes, a suitable training algorithm (such as Levenberg-Marquardt, conjugate gradient, simulated annealing, or other algorithms) is then used to adjust the connections and weights between nodes in adjacent layers of the neural network to produce the desired values at the output nodes. This process is sometimes referred to as deep learning” (¶ 0058; ¶ 0063). In light of the disclosure, the claims recite mathematical algorithms, which encompasses mathematical relationships between data in the manner described in the identified abstract idea, supra. If a claim limitation, under its broadest reasonable interpretation, covers mathematical relationships, but for the recitation of generic computer components, then it falls within the “Mathematical Concepts” grouping of abstract ideas. Accordingly, the claims recite an abstract idea.
For purposes of the following analysis, the aforementioned types of identified abstract ideas are considered together as a single abstract idea. See MPEP § 2106.04(II)(B).
Claim 1 recites additional elements (i.e., An apparatus…comprising a computing device; machine learning). Claim 11 recites additional elements (i.e., a processor; machine learning). Looking to the specifications, a computing device having a processor is described at a high level of generality (¶ 0011; ¶ 0081-0083), such that it amounts to no more than mere instructions to apply the exception using generic computer components. Also, “machine learning” is described as “a process that automatedly uses training data 204 to generate an algorithm that will be performed by a computing device/module to produce outputs 208 given data provided as inputs 212” (¶ 0053) and “classifier” is described as “a machine- learning model as defined below, such as a mathematical model, neural net, or program generated by a machine learning algorithm known as a "classification algorithm"…that sorts inputs into categories or bins of data, outputting the categories or bins of data and/or labels associated therewith” (¶ 0056), which is described at a high level of generality (i.e., no description of the mechanism for accomplishing the result), such that using machine learning amounts to no more than a recitation of the words "apply it" (or an equivalent), such as mere instructions to implement an abstract idea on a computer, and only generally links the use of a judicial exception to a particular technological environment or field of use (i.e., computer technology), which does not impose meaningful limits on the scope of the claim. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements individually. The additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Accordingly, the claims are directed to an abstract idea.
Reevaluated under step 2B, the additional elements noted above do not provide “significantly more” when taken either individually or as an ordered combination. The use of a general purpose computer or computers (i.e., a computing device having a processor) amounts to no more than mere instructions to apply the exception using generic computer components and does not impose any meaningful limitation on the computer implementation of the abstract idea, so it does not amount to significantly more than the abstract idea. Also, “machine learning” and “classifier” is described at a high level of generality (i.e., no description of the mechanism for accomplishing the result), such that using machine learning amounts to no more than a recitation of the words "apply it" (or an equivalent), such as mere instructions to implement an abstract idea on a computer, and only generally links the use of a judicial exception to a particular technological environment or field of use (i.e., computer technology), which does not impose meaningful limits on the scope of the claim. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements individually. The combination of elements does not indicate a significant improvement to the functioning of a computer or any other technology and their collective functions merely provide a conventional computer implementation of the abstract idea. Furthermore, the additional elements or combination of elements in the claims, other than the abstract idea per se, amount to no more than a recitation of generally linking the abstract idea to a particular technological environment or field of use, as the courts have found in Parker v. Flook; similarly, the current invention merely limits the claimed calculations to the healthcare industry which does not impose meaningful limits on the scope of the claim. Therefore, there are no limitations in the claims that transform the judicial exception into a patent eligible application such that the claims amount to significantly more than the judicial exception.
Dependent claims 2-10, 12-20 include all the limitations of the parent claims and further elaborate on the abstract idea discussed above and incorporated herein.
Claims 2, 5-10, 12, 15-20 further define the analysis and organization of data for the performance of the abstract idea and do not recite any additional elements. Thus, the claims do not integrate the abstract idea into a practical application and do not provide “significantly more.”
Claims 3, 13 further recites the additional elements of “wearable devices” and claims 4, 14 recites the additional elements of “computer system monitoring,” which are only invoked merely as a tool in its ordinary capacity to perform an existing process (i.e., collecting data), which does not impose meaningful limits on the scope of the claim and amounts to no more than a recitation of the words "apply it" (or an equivalent), and only generally links the claimed invention to a particular technological environment or field of use (i.e., computer technology), which does not impose meaningful limits on the scope of the claim. Also, functional limitations further define the analysis and organization of data for the performance of the abstract idea. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements individually. Thus, the claims as a whole do not integrate the abstract idea into a practical application and do not provide “significantly more.”
Although the dependent claims add additional limitations, they only serve to further limit the abstract idea by reciting limitations on what the information is and how it is received and used. These information characteristics do not change the fundamental analogy to the abstract idea groupings, and when viewed individually or as a whole, they do not add anything substantial beyond the abstract idea. Furthermore, the combination of elements does not indicate a significant improvement to the functioning of a computer or any other technology. Therefore, the claims when taken as a whole are ineligible for the same reasons as the independent claims.
Response to Arguments
Applicant's arguments filed 11/12/2025 have been fully considered but they are not persuasive. Applicant’s arguments will be addressed hereinbelow in the order in which they appear in the response filed 11/12/2025.
In the remarks, Applicant argues in substance that:
Regarding the 103 rejections, the cited prior art reference(s) fails to teach the amended claim limitations.
It is respectfully submitted that Examiner has considered Applicant’s arguments and does not find them persuasive. Examiner has attempted to address all of the arguments presented by Applicant; however, any arguments inadvertently not addressed are not persuasive for at least the following reasons:
In response to Applicant’s argument that (a) regarding the 103 rejections, the cited prior art reference(s) fails to teach the amended claim limitations:
It is respectfully submitted that the amendments have rendered the rejections moot and amended claims 1-20 recite subject matter free of prior art because the prior art does not teach or disclose the amended features in the specific manner and combinations recited. Thus, the claims are now allowable over prior art. Originally numbered dependent claims 2-10, 12-20 incorporate the allowable features of originally numbered independent claims 1, 11 through dependency, respectively.
However, the claims are still rejected under 101.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Emily Huynh whose telephone number is (571)272-8317. The examiner can normally be reached on M-Th 8-5 PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Robert Morgan can be reached on (571) 272-6773.The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/EMILY HUYNH/Primary Examiner, Art Unit 3683