DETAILED ACTION
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 11/19/2025 has been entered.
Status of Claims
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This action is in reply to the RCE filed on 11/19/2025.
Claims 1, 3, 4, 6, 8-10, 12, 15, 19, and 20 have been amended
Claims 2, 5, 7, 11, 14, 16-18 have been canceled.
Claims 21-28 have been added.
Claims 1, 3, 4, 6, 8-10, 12, 13, 15, and 19-28 are currently pending and have been examined.
The previous objections and 112(f) interpretations are withdrawn due to amendments to the claim.
Response to Arguments
Applicant's arguments filed 10/17/2025 with respect to the 101 rejection have been fully considered but they are not persuasive.
Applicant argues #1:
The Patent Office has the initial burden of presenting a prima facie case that the claims are directed to patent-ineligible subject matter. See MPEP § 2106 (III) (“The Examiner bears the initial burden . . . of presenting a prima facie case of unpatentability.”) (quoting In re Oetiker, 977 F.2d 1443, 1445, (Fed. Cir. 1992)). In order to preserve Applicant’s rights on appeal and ensure that the rejections are fully documented on the record, Applicant asserts that the Office Action has failed to establish a prima facie case that the claims are directed to patent-ineligible subject matter as set forth below.
a.Step 2A Prong One under USPTO SME Guidance:
…
Applicant respectfully submits that the independent claims presented herewith do not recite a judicial exception, per se, and there is no need to evaluate the independent claims further to determine whether such claims integrate a judicial exception into a practical application.
… In reviewing the Office Action under Step 2A – Prong One, the Examiner highlights certain claim elements and indicates that such claim elements “covers commercial or legal interactions for determining the financial wellness of a person and recommending products/services based on the score but for the recitation of generic computer components.”
Applicant respectfully submit that Step 2A – Prong One is a threshold question and analysis of whether any computer components are generic is not part of the analysis under step 2A – Prong One. Rather, the inquiry under Step 2A – Prong One is whether the claim recites a judicial exception. As indicated above, the Memorandum instructs examiners to distinguish between claims that merely “involve” or cover a judicial exception from those that actually “recite” a judicial exception. Here, the Office Action indicates the claim “covers commercial or legal interactions” and that the claim recites certain methods of organizing human activity. Applicant respectfully disagrees as the claim itself does not recite, per se, a method of organizing human activity nor does it recite, per se, commercial or legal interactions. Rather, it trains a model, collects data, and uses that data to make a prediction to generate a score, and assigns the score to a profile. That process is not, in and of itself, a commercial interaction or a legal interaction. Rather, any commercial interaction would be performed downstream from the process of predicting the financial wellness score.
Examiners response:
The Examiner respectfully disagrees, training a model, collecting data, and using that data to make a prediction to generate a score, and assigning the score to a profile does not render the claims eligible, and regardless of where the predicting of the wellness score is performed, it is claimed and therefor the claims do recite an abstract idea. Additionally, the training a model, collecting data, and using that data to make a prediction to generate a score, and assigning the score to a profile is part of the abstract idea akin to ineligible Claim 2 of Example 47 of the USPTO’s July 2024 Subject Matter Eligibility Examples. Similar to claim 2, where the training steps were found to fall within the mathematical concepts grouping of abstract ideas, the training of the instant application is recited and described in the specification in a highly generic manner such that it could be interpreted as performing repetitive calculations and therefor is abstract (see [0062] describing several generic machine learning methods to be used which are rooted in mathematical concepts).
Applicant argues #2:
Under Step 2A – Prong One, Applicant references Example 39 – Method for Training a Neural Network for Facial Detection of the USPTO Subject Matter Eligibility Examples: Business Methods (hereinafter “Example 39”), which evaluates a claim under 35 U.S.C. § 101. The claim evaluated in Example 39 is as follows…
The claim in Example 39 relates to the collection of data, the creation of two training data sets, and an iterative training process with two training processes using the two training data sets. The analysis of the claim of Example 39 is reproduced hereinbelow with respect to whether the claim recites patent eligible subject matter.
In identical fashion to the above example, amended claims 1, 19, and 23 do not recite, per se, any method of organizing human activity as the claims do not recite a fundamental economic concept or manage interactions between people. Rather, the claims trains a model, collects data, and performs a prediction. Performing the exact same analysis set forth by Example 39, even if some of the limitations “may be based on” methods of organizing human activity, this is not the relevant inquiry as the inquiry at this stage of the 35 U.S.C. § 101 analysis is whether the claims recite, per se, a judicial exception. In reviewing Applicant’s amended claims 1, 19, and 23, no per se recitation of a judicial exception is included in amended claims 1, 19, and 23.
Examiners response:
The Examiner respectfully disagrees, with respect to Example 39, the claims of Example 39 were found to be eligible because the claims did not recite any of the judicial exceptions enumerated in the 2019 PEG. Unlike Example 39, the claims of the instant application do recite abstract ideas for training a neural network to predict a financial stress level, collect and analyze data relating to the financial and physical well-being to generate a financial wellness score of a person, this process clearly falls within several of the enumerated categories, and while the idea may have shifted categories due to the substantial amendments, the training and generating scores are akin to performing repetitive calculations (mathematical relationships with the respect to the training the neural network and generating scores), and mental processes (including observations and evaluations performing in the human mind) of analyzing data relating to the financial and physical well-being to generate a financial wellness score of a person. Further, while not recited in the independent claims, the dependent claims do recite commercial and legal interactions for providing recommendations for bank products based on the score, as in claim 12.
Applicant argues #3:
a.Step 2A Prong Two under USPTO SME Guidance:
… Applicant respectfully submits that the amended claims presented herewith recite additional elements that integrate the judicial exception into a practical application of that judicial exception.
In particular, under Step 2A Prong Two, the claim should be evaluated to determine whether the claim, as a whole, integrates the recited judicial exception into a practical application by applying, relying on, or using the judicial exception in a manner that imposes meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception. Under step 2A Prong Two, the guidance instructs Examiners to evaluate integration into a practical application by: a) identifying whether there are any additional elements recited in the claim beyond the judicial exception(s); and b) evaluating these additional elements individually and in combination to determine whether they integrate the exception into a practical application, using one or more considerations laid out by the Supreme Court and the Federal Circuit…
Applying the guidelines established by the Memorandum to the independent claims, Applicant respectfully submits that the claims are not directed to an abstract idea. Instead, the amended claims provide details of how a solution to a particular problem in existing technology is accomplished.
As a threshold matter, amended claim 1 recites additional elements that include: at least one processor, a communications interface, a memory device, training test data, a neural network, a target variable, a target variable, weights, nodes, and one or more devices.
Setting aside any analysis of whether these additional elements are well-understood, routine, or conventional activity, as such factors are irrelevant as part of the Step 2A Prong Two analysis, Applicant respectfully submits that the additional elements, when evaluated individually and in combination, integrate any recited judicial exception into a practical application by (1) reflecting an improvement in the functioning of a technology or technical field, (2) implementing any recited judicial exception in conjunction with a particular machine or manufacture that is integral to the claim, and (3) using the judicial exception in some other meaningful way beyond general linking the use of any recited judicial exception to a technological environment.
In particular, Applicant respectfully submits that when evaluating amended claim 1, as a whole, these recited additional elements outlined above integrate any recited judicial exception into a practical application because they (1) reflect an improvement in the functioning of a technology or technical field by improving predictability of the target variable and functionality of the neural network. By making this adjustment to the weights, the error amount is reduced and the predictability of the target variable becomes more accurate. This improved accuracy and reduction in error is necessarily an improvement on the computing system, the neural network, and to the nodes (i.e., the underlying machines/computers) of the neural network. Specifically, the underlying machine/computer is improved with each iteration of the iterative training and testing loop to make more accurate predictions of a likely future outcome. The improvements to the accuracy and predictive processes provided by the recited computing system address deficiencies in existing data analysis processes. Further, this process covers a particular solution to a particular problem arising in the field of data analytics and statistical analysis. As stated by the Memorandum, “[t]he specification does not need to 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.” Thus, the claim recitations reflect an improvement in the functioning of a technology or technical field of data analytics and statistical analysis.
Examiners response:
The Examiner respectfully disagrees, the Examiner fails to see how the claims amount to an improvement in technology of data analytics and statistical analysis as MPEP 2106.05(d) provides it’s WURC to use a computer for Performing repetitive calculations, see Flook, 437 U.S. at 594, 198 USPQ2d at 199 (recomputing or readjusting alarm limit values); Bancorp Services v. Sun Life, 687 F.3d 1266, 1278, 103 USPQ2d 1425, 1433 (Fed. Cir. 2012) ("The computer required by some of Bancorp’s claims is employed only for its most basic function, the performance of repetitive calculations, and as such does not impose meaningful limits on the scope of those claims."); as is here with using the computer to perform repetitive calculations for training the neural network and calculating the scores. Further, iteratively training, and adjusting weights of the network are incident to the very nature of machine learning similar to the findings of the Recentive Analytics, Inc. v. Fox Corp., Case No. 2023-2437 (Fed. Cir. Apr. 18, 2025) decision, where the Courts found that the requirements that the machine learning model be “iteratively trained” or dynamically adjusted in the Machine Learning Training patents did not represent a technological improvement. As Recentive’s own representations about the nature of machine learning vitiate this argument: Iterative training using selected training material and dynamic adjustments based on real-time changes are incident to the very nature of machine learning. See, e.g., Opposition Br. 9 (“[U]sing a machine learning technique[] . . . necessarily includes [an] iterative[] training step . . . .” internal quotation marks and citation omitted)); Transcript at 26:21–24 (“[T]he way machine learning works is the inputs are defined, the model is trained, and then the algorithm is actually updated and improved over time based on the input”). For these reasons, applicant’s arguments are not persuasive.
Applicant argues #4:
In this regard, Applicant references Claim 3 of Example 47 – Anomaly Detection of the USPTO Subject Matter Eligibility Examples (hereinafter “Example 47”), which evaluates a claim under 35 U.S.C. § 101. The claim evaluated in Example 47 is as follows:…
Under the Step 2A, Prong Two analysis of Claim 3 of Example 47, the example identifies additional elements of “(d) detecting a source address associated with the one or more malicious network packets,” “(e) dropping the one or more malicious network packets in real time, and “(f) blocking future traffic from the source address” while noting that limitation (a) is performed by a computer. In looking at the additional elements as a whole to evaluate whether the claim includes an improvement to a computer or a technological field, the example determined that “the disclosed system enhances security by acting in real time to proactively prevent network intrusions.” Based on identifying the improvement, the example reviews whether the claim reflects the improvement in the technical field of network intrusion detection. In this regard, the example asserts that steps (d)-(f) provide for “improved network security using the information from the detection to enhance security by taking proactive measures to remediate the danger by detecting the source address associated with the potentially malicious packets.” Because steps (d)-(f) reflect the improvement, the claim as a whole was found to integrate the practical application such that the claim is not directed to the judicial exception and provides an improvement in the functioning of a computer or technical field of network intrusion detection. Similarly, Applicant recites steps for an improvement associated with data analysis to provide a more comprehensive view of a person’s financial wellbeing, economic health, physical, and emotional wellness, as indicated by paragraph [0093], which is an improvement over existing data analytics and statistical analysis…
Respectfully, the Examiner is reminded that the Memorandum also indicates, “if it is a ‘close call’ as to whether a claim is eligible, they should only make a rejection when it is more likely than not (i.e., more than 50%) that the claim is ineligible under 35 U.S.C. 101.” Thus, if it is unclear whether or not there is an improvement to technology or a technical field, the rejection should only be made if it is more likely than not that there is an improvement to technology or the technical field.
Applying the revised standards of Prong Two of Step 2A to amended claims 1 19, and 23, Applicant respectfully submits that the claim recites additional elements that integrate the recited judicial exception into a practical application of that exception and is, therefore, patent eligible under Prong Two of Step 2A.
Examiners response:
The Examiner respectfully disagrees, unlike claim 3 of Example 47, the claims are not directed towards a practical application (as claim 3 was found to be eligible in that the claims provide for improved network security using the information from the detection to enhance security by taking proactive measures to remediate the danger by detecting the source address associated with the potentially malicious packets), that is to say in claim 3 of the Example there is an improvement to the network and network security unlike the instant applications which at most could be considered an improvement to the abstract idea for generating a financial wellness of a user based on financial and physical health data. Further, similar to Claim 2 of Example 47 in the July 2024 Subject Matter Eligibility Examples, the training is recited at high level of generality such that it amounts to using a generic computer to perform generic computer functions, akin to using a computer to perform repetitive calculations (See MPEP 2106.05(d)), and therefore amounts to no more than mere instructions to apply the exception using a generic computer (See MPEP 2106.05(f)).
Additionally similar to Recentive Analytics, Inc. v. Fox Corp., Case No. 2023-2437 (Fed. Cir. Apr. 18, 2025), the claims are directed to the abstract idea of using a generic machine learning technique in a particular environment, with no inventive concept. Instead of disclosing “a specific implementation of a solution to a problem in the software arts,” Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1339 (Fed. Cir. 2016), or “a specific means or method that solves a problem in an existing technological process,” Koninklijke, 942 F.3d at 1150, the only thing the claims disclose about the use of machine learning is that machine learning is used in a new environment. The use of the Machine Learning does not represent a technological improvement. (see Recentive Analytics, Inc. v. Fox Corp., Case No. 2023-2437 (Fed. Cir. Apr. 18, 2025)).
Applicant argues #5:
b.Step 2B under USPTO SME Guidance:
Specifically, the guidance specifies that the focus of Step 2B is to consider whether an additional element or combination of elements adds a specific limitation or combination of limitations that are not well-understood, routine, or conventional activity in the field, which is indicative that an inventive concept may be present, or simply appends well-understood routine, conventional activities previously known in the industry, specified at a high level of generality, to the judicial exception, which is indicative that an inventive concept may not be present. As indicated by the Federal Circuit in Bascom Global Internet Services, Inc. v. AT&T Mobility LLC, 827 F.3d 1341 (Fed. Cir. 2016), “an inventive concept can be found in the non-conventional and non-generic arrangement of known, conventional pieces.” Applying Step 2B of the guidance to the claims recited herewith, Applicant respectfully submits that claims 1, 16 and 19 include a specific limitation or combination of limitations that are not well-understood, routine, or conventional activity in the field, and, therefore, recite an inventive concept and are patent eligible under Step 2B.
The 2019 Revised Patent Subject Matter Eligibility Guidance gives an example that if a combination of steps used to gather data is found to be insignificant extra-solution activity under Step 2A, the examiner could determine the combination of steps to gather data is in an unconventional way and therefore includes an “inventive concept” rendering the claim eligible under Step 2B.
It is respectfully submitted that Applicant’s recited computing system adds a specific limitation or combination of limitations that are not well-understood, routine, or conventional activity in the field and do not simply append well-understood routine, or conventional activities previously known to the industry, specified at a high level of generality, to the exception. For example, amended claims 1, 19, and 23 recite “predict, via the deployed neural network and based on the first score and the second score, the person’s financial stress level, the predicted financial stress level being a financial wellness score” and “assign the financial wellness score to the user profile.” Applicant respectfully submits that these specific limitations or combination of limitations are not well-understood, routine, or generic. Because the recitations predict the person’s financial stress level in an unconventional way, the claims recite significantly more than the judicial exception and are, therefore, patent eligible under Step 2B.
Thus, Applicant respectfully submits that amended claims 1, 19, and 23 recite significantly more than a judicial exception since, at the very least, additional elements provide an inventive concept and is, therefore, patent eligible under Step 2B.
Therefore, Applicant respectfully requests that the rejection under 35 U.S.C. § 101 be withdrawn.
Examiners response:
The Examiner respectfully disagrees, similar to Recentive Analytics, Inc. v. Fox Corp., Case No. 2023-2437 (Fed. Cir. Apr. 18, 2025), the claims are directed to the abstract idea of using a generic machine learning technique in a particular environment, with no inventive concept. Instead of disclosing “a specific implementation of a solution to a problem in the software arts,” Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1339 (Fed. Cir. 2016), or “a specific means or method that solves a problem in an existing technological process,” Koninklijke, 942 F.3d at 1150, the only thing the claims disclose about the use of machine learning is that machine learning is used in a new environment. The use of the Machine Learning does not represent a technological improvement. (see Recentive Analytics, Inc. v. Fox Corp., Case No. 2023-2437 (Fed. Cir. Apr. 18, 2025)). Further, the claims here are not like those the Court found patent eligible in Bascom, in which the inventive concept was the unconventional arrangement of the installation of a filtering tool at a specific location, remote from the end-users, with customizable filtering features specific to each end user, this design permitted the filtering tool to have both the benefits of a filter on a local computer and the benefits of a filter on the [Internet Service Provider] server and was not conventional or generic, instead, the patent claimed and explained how a particular arrangement of elements was “a technical improvement over prior art ways of filtering such content.” (BASCOM, 827 F.3d at 1345.). In the instant application the claims do not have an inventive concept found in the non-conventional and non-generic arrangement of the additional elements.
For the reasons above, the 101 rejection is hereby maintained.
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, 3, 4, 6, 8-10, 12, 13, 15, and 19-28 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more, and fails step 2 of the analysis because the focus of the claims is not on the devices themselves or a practical application but rather directed towards an abstract idea, the analysis is provided below.
Step 1 (Statutory Categories) - The claims pass step 1 of the subject matter eligibility test (see MPEP 2106(III)) as the claims are directed towards a system, non-transitory computer-readable medium, and method.
Step 2A – Prong One (Do the claims recite an abstract idea?)
The idea is recited in the claims, in part, by:
train, using training test data, a neural network to predict factors indicative of a financial stress level, the training including:
iteratively predicting the factors from the training test data that correlate to the financial stress, the predicting generating a prediction;
testing and comparing, during each iteration, the prediction to a target variable; and
indicating, for each iteration and via a feedback loop, modifications to weights assigned to nodes of the neural network to improve the neural network’s ability to predict the target variable and reduce error of the prediction;
collect financial data about a first factor of a person, the first factor being indicative of the person’s financial wellbeing;
generate, from the financial data, a first score associated with the first factor, the first score being correlated to a user profile of the person;
collect, from one or more devices, data indicative of a second factor of the person, the second factor being indicative of the person’s physical wellbeing, the one or more devices including at least one of (a) a wearable device worn by the person, and (b) an imaging device that provides one or more images of the person;
generate, from the data indicative of the financial stress, a second score associated with the second factor, second score being correlated to the user profile of the person;
predict based on the first score and the second score, the person’s financial stress level, the predicted financial stress level being a financial wellness score; and
assign the financial wellness score to the user profile;
wherein the user profile is associated with a banking system of a bank based on the person being a client of the bank, and
wherein at least some of the financial data is obtained from a financial monitoring source that provides information associated with one or more of (i) credit score changes, (ii) changes in direct deposit patterns or income changes including loss of employment and reduction in work hours, (iii) changes in transaction and account patterns including account closures, (iv) overdrafts, late payments and an increase in debt-related transactions, (v) changes in credit card patterns including increased transaction frequency for basic needs with decreased spending in dining out and entertainment, (vi) sale of investments or assets, (vii) requests for payment extensions or loan modifications, and (viii) payday loans or cash advances.
The steps recited above under Step 2A Prong One of the analysis under the broadest reasonable interpretation covers two groupings of abstract ideas, mathematical concepts with respect to training of the neural network in that the training is based on mathematical calculations as the specification describes several training techniques which may be utilized rooted in mathematics (see [0061-0062] for example) and mental processes, in which the generic computer is being used as a tool for performing the mental processes of generating scores relating a person’s financial stress and physical well-being to generate a financial wellness scores, which can be performed mentally. Additionally, the dependent claims recite commercial or legal interactions (including marketing or sales activities or behaviors; business relations) for recommending products/services based on the score but for the recitation of generic computer components. That is other than reciting a non-transitory computer-readable medium, a computer system comprising at least one processor, a communications interface, memory, a client central database, a client interaction and transaction source, a financial monitoring source, one or more devices comprising a wearable device (which is one of a fitness tracker, a smart watch, a connected headset, smart glasses or a wrist band), an imaging device, and a deployed neural network nothing in the claim elements are directed towards anything other than mathematical concepts and mental processes as described above for analyzing information about the financial and physical well-being of a person in order assign a financial wellness score, subsequently used to recommend a product or service based on the analysis. If a claim limitation, under its broadest reasonable interpretation, uses a computer to perform mental processes and mathematical calculations, then it falls within the “Mental Processes” and “Mathematical Concepts” groupings of abstract ideas. Accordingly, the claims recite an abstract idea.
Step 2A – Prong Two (Does the claim recite additional elements that integrate the judicial exception into a practical application?) - This judicial exception is not integrated into a practical application. In particular, the claims only recite the additional elements of a non-transitory computer-readable medium, a computer system comprising at least one processor, a communications interface, memory, a client central database, a client interaction and transaction source, a financial monitoring source, one or more devices comprising a wearable device (which is one of a fitness tracker, a smart watch, a connected headset, smart glasses or a wrist band), an imaging device, and a deployed neural network. As discussed in MPEP 2106.04(d)(i), under Step 2A Prong Two, the Courts have identified and indicated limitations directed towards using a computer as a tool to perform an abstract idea, and adding insignificant extra-solution activity does not integrate a judicial exception into a practical application, as is the case here, with respect to assigning the scores and combining them to provide a recommendation to assign a financial wellness score (using the computer as tool to perform the abstract idea), and with respect to the data collection steps from the imaging device and/or wearable device, this amounts to adding insignificant extra-solution activity similar to Selecting information, based on types of information and availability of information in a power-grid environment, for collection, analysis and display, Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354-55, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016);. See also, 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). Mere instructions to apply the judicial exception using generic computer components, adding insignificant extra-solution activity and limiting the judicial exception to a particular environment are not indicative of a practical application (see MPEP 2106.04(d)(i)). With respect to the neural network model and deploying using the model to generate the score, in view of the new July 2024 Subject Matter Eligibility Examples, which provides additional guidance on Patent Subject Matter Eligibility, including artificial intelligence, the Examiner finds the claims do not integrate the judicial into a practical application. Similar to Claim 2 of Example 47 in the July 2024 Subject Matter Eligibility Examples, the neural network is recited at high level of generality such that it amounts to using a generic computer to perform generic computer functions, akin to using a computer to perform repetitive calculations (See MPEP 2106.05(d)), and therefore amounts to no more than mere instructions to apply the exception using a generic computer (See MPEP 2106.05(f). Accordingly, these 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. The claims are directed towards an abstract idea.
Step 2B (Does the claim recite additional elements that amount to significantly more than the judicial exception?) - The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, as discussed above, with respect to integration of the abstract idea into a practical application, using the additional elements of a non-transitory computer-readable medium, a computer system comprising at least one processor, a communications interface, memory, a client central database, a client interaction and transaction source, a financial monitoring source, one or more devices comprising a wearable device (which is one of a fitness tracker, a smart watch, a connected headset, smart glasses or a wrist band), an imaging device, and a deployed neural network to perform the steps recited in Step 2A Prong One of the analysis amounts to no more than mere instructions to apply the exception using generic computer components, adding insignificant extra solution activity and limits the judicial exception to the particular environment which does not provide an inventive concept. The additional elements have been considered separately, and as an ordered combination, and do not add significantly more (also known as an “inventive concept”) to the judicial exception. Further, MPEP 2106.05(d)(ii) provides that receiving and transmitting data over a network (see 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), Performing repetitive calculations, Flook, 437 U.S. at 594, 198 USPQ2d at 199 (recomputing or readjusting alarm limit values); Bancorp Services v. Sun Life, 687 F.3d 1266, 1278, 103 USPQ2d 1425, 1433 (Fed. Cir. 2012); Ultramercial, 772 F.3d at 716, 112 USPQ2d at 1755 (updating an activity log); and Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93; are well-understood routine and conventional, similar to the instant application claims which recites and sending and receiving data over network, and storing and retrieving information from the data sources and wearable device pertaining to financial and physical data about the user. With respect to the imaging device and wearable device, as per MPEP 2106.05(f) use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more. Additionally, with respect to the wearable device and the imaging device, this is akin to Selecting information, based on types of information and availability of information in a power-grid environment, for collection, analysis and display, Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354-55, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016), and using fitness devices to track health and fitness metrics is well-known as evident in the prior art1. Thus, the claims are not patent eligible.
The dependent claims have been given the full analysis including analyzing the additional limitations both individually and in combination as a whole. For instance, claims 12 and 13 further define the abstract idea, claims 3, 4, 6, and 8 further define insignificant extra solutions activities and claim 9-10 further define the technical environment similar to Selecting information, based on types of information and availability of information in a power-grid environment, for collection, analysis and display, Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354-55, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016). With respect to further limiting the neural network to be a CNN and RNN neural network in claim 15, as discussed above, this is recited at high level of generality such that it amounts to using a generic computer to perform generic computer functions, akin to using a computer to perform repetitive calculations (See MPEP 2106.05(d)) as both these networks are rooted in mathematics similar to ineligible claim 2 of Example 47. The Dependent claims when analyzed both individually and in combination are also held to be patent ineligible under 35 U.S.C. 101 for the same reasoning as above and the additional recited limitations fail to establish that the claims are not directed to an abstract idea. The additional limitations of the dependent claims when considered individually and as an ordered combination do not amount to significantly more than the abstract idea.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to GREGORY S CUNNINGHAM II whose telephone number is (313)446-6564. The examiner can normally be reached Mon-Fri 8:30am-4pm.
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, Bennett Sigmond can be reached at 303-297-4411. 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.
GREGORY S. CUNNINGHAM II
Primary Examiner
Art Unit 3694
/GREGORY S CUNNINGHAM II/Primary Examiner, Art Unit 3694
1 See NPL Facts About Fitness Trackers and Which One is Right for You