025$
DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
Claims 1-21 were previously pending in this application. The amendment filed 16 December 2025 has been entered and the following has occurred: Claims 1 & 12 have been amended. Claim 11 has been cancelled. No claims have been added.
Claims 1-10 & 12-21 remain pending in the application
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 1-10 & 12-21 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.
The claims recite subject matter within a statutory category as a process (claims 1-10), machine (claims 12-21) which recite steps of:
providing predefined targets for ABA programs, wherein each said predefined target comprises a skill to be addressed and one or more interventions for promoting mastery of said skill, and each said ABA program is a defined process for modifying one or more behaviors of an individual in relation to one or more of said predefined targets;
providing a template for structuring entry of target information by a user concerning one or more of said predefined targets, implementation of said one or more of predefined targets for a subject, and progress towards mastery of one of said predefined targets, wherein said template provides a standardized structure for said entry of target information;
receiving, at a network platform from multiple users, items of target information for multiple subjects, said items of target information provided using said predefined targets and said template;
establishing a collection of said target information, accessible via said network platform, based at least in part on said items of target information from said multiple users;
receiving, at said network platform, a query from a first user concerning a first ABA program for a first subject;
accessing said collection of said target information to generate a response to said query, said response free of protected information of other subjects; and
operating a processor of said network platform to predict a correlation between said predefined targets using said items of target information from said multiple users, wherein said correlation utilizes relationships between targets, wherein said relationships are determined by said processor, said relationships inform which targets will make learning other targets easier, and said relationships comprise one or more of a parent/child relationship between targets and a hierarchy of targets.
These steps of providing skills to be addressed and one or more interventions for promoting mastery of said skill in a user/individual with developmental disabilities by utilizing established applied behavioral analysis (ABA) programs in order to modify one or more behaviors of the individual/user, and predicting a correlation between said predefined targets using said items of target information from said multiple users, as drafted, under the broadest reasonable interpretation, includes methods of organizing human activity. MPEP 2106.04(a)(2)(II) describes various methods or organizing human activity, including fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts, legal obligations, advertising, marketing or sales activities or behaviors, and business relations); and/or managing personal behavior or relationships or interactions between people, (including social activities, teaching, and following rules or instructions). Further examples of “managing personal behavior or relationships or interactions between people” are given in MPEP 2106.04(a)(2)(II)(C), such as filtering content, considering historical usage information while inputting data, and/or a mental process that a neurologist should follow when testing a patient for nervous system malfunctions. The steps recited above relate heavily to the last-provided example of a mental process that a neurologist should follow when testing a patient for nervous system malfunctions. For instance, the steps recited effectively set forth a mental process (e.g., an ABA program which is set forth in the claim as a defined process for modifying one or more behaviors of an individual in relation to one or more of said predefined targets) that one or more entities should follow in order to promote mastery of a skill for individuals with developmental disabilities. The steps recited further in the independent claims of providing a template for structuring entry of target information by a user concerning one or more of said predefined targets, implementation of said one or more of predefined targets for a subject, and progress towards mastery of one of said predefined targets, wherein said template provides a standardized structure for said entry of target information; receiving items of target information for multiple subjects, said items of target information provided using said predefined targets and said template; establishing a collection of said target information, based at least in part on said items of target information from said multiple users; receiving a query from a first user concerning a first ABA program for a first subject; and accessing said collection of said target information to generate a response to said query, said response free of protected information of other subjects further specify the implementation of an ABA program, i.e. the identified abstract idea, by detailing the structuring of the program to be followed, how to tailor the program to the user/individual based on data of said user/individual and what benchmarks to set for accomplishing mastery of the skill, and basing said determinations based on, for instance, correlations between said predefined targets using said items of target information from said multiple users. At the least, the claim recites “modifying one or more behaviors of an individual in relation to one or more predefined targets (i.e. a skill to be addressed and one or more interventions for promoting mastery of said skill) and said recitation of “modifying one or more behaviors of an individual” alone substantially relates to the “managing personal behavior or relationships or interactions between people” of methods of organizing human activity. As such, under broadest reasonable interpretation, the independent claims, as drafted, include methods of organizing human activity.
Dependent claims recite additional subject matter which further narrows or defines the abstract idea embodied in the claims (such as claims 2-10 & 13-21, reciting particular aspects of how particulars of implementing the ABA program for the user may be performed in the mind, including aspects of identifying user behaviors/parameters, determinations of skill mastery, predictions of how long it will take to master a skill, etc., but for recitation of generic computer components).
This judicial exception is not integrated into a practical application. In particular, the additional elements do not integrate the abstract idea into a practical application, other than the abstract idea per se, because the additional elements amount to no more than limitations which:
amount to mere instructions to apply an exception (such as recitation of a network platform, a standardized structure, and a processor amounts to invoking computers as a tool to perform the abstract idea, see Applicant’s Specification [0029], [0046], & [0054] for a network platform; Spec. [0016] for a standardized (data) structure; Spec [0049] for a processor, see MPEP 2106.05(f));
add insignificant extra-solution activity to the abstract idea (such as recitation of providing targets for ABA program, providing a template for structuring entry of target information by a user concerning one or more of said predefined targets receiving items of target information for multiple subjects, receiving a query from a first user concerning a first ABA program for a first subject, accessing said collection of said target information amounts to mere data gathering; recitation of defining each target for an ABA program as a skill to be addressed and one or more interventions for promoting mastery of said skill by modifying one or more behaviors of an individual in relation to one or more of said predefined targets, specifying the items of target information provided using predefined targets and ABA program structuring template, specifying the response to be free of protected information of other subjects, predicting a correlation between predefined targets using items of target information from said multiple users, specifying the correlation and/or relationships comprising specific types of data or data manipulations/relationships amounts to selecting a particular data source or type of data to be manipulated; recitation of generating a response to said query, of the use of a template/standardized interface for entering data items of target information for ABA program(s), predicting a correlation between predefined targets using items of target information from said multiple users amounts to insignificant application, see MPEP 2106.05(g));
generally link the abstract idea to a particular technological environment or field of use (such as recitation of applying/implementing ABA programs and/or templates that define implementation of one or more of predefined targets for a subject, and progress towards mastery of one of said predefined targets, see MPEP 2106.05(h)).
Dependent claims recite additional subject matter which amount to limitations consistent with the additional elements in the independent claims (such as claims 2-10 & 13-21, which recite limitations relating to a network platform, a data structure, additional limitations which amount to invoking computers as a tool to perform the abstract idea, see Applicant’s Specification [0029], [0046], & [0054] for a network platform; Spec. [0016] for a standardized (data) structure; see MPEP 2106.05(f); claims 9-10 & 20-21, which recite limitations relating to receiving information from one of said multiple users for defining a new target and making said new target available, i.e. transmitting, to others of said multiple users, receiving, in said standardized structure, result information for an implemented target, additional limitations which add insignificant extra-solution activity to the abstract idea which amounts to mere data gathering; claims 2-6, 9, 13-17, & 20, which recite limitations relating to specifying the skill to be reduction of a behavior associated with developmental disability or learning a behavior that is suppressed due to a developmental disability, identifying an appropriate target for said first subject, identifying a first behavior based on said query and matching said first behavior to one or more candidate targets, one or more candidate targets associated with said first behavior and comparing said plurality of said one or more candidate targets based on a likelihood of success in promoting mastery of an associated skill, defining a new target based on received information from one of said multiple users, additional limitations which add insignificant extra-solution activity to the abstract idea by selecting a particular data source or type of data to be manipulated; claims 7-8 & 18-19, which recite limitations relating to ranking one or more candidate targets based on various aspects, e.g. how many times the plurality of candidate targets has been implemented, how long each of the plurality of candidate targets has been in existence, etc., evaluating said likelihood of success for a first candidate target by considering a relationship between mastery of said first candidate target and mastery of another target, predicting how long it will take a first subject to master a skill, additional limitations which amount to insignificant application, see MPEP 2106.05(g); claims 2-10 & 13-21, which generally recite limitations further specifying the implementation of the ABA program or parameterization of said program, additional limitations which generally link the abstract idea to a particular technological environment or field of use). 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. Their collective functions merely provide conventional computer implementation and do not impose a meaningful limit to integrate the abstract idea into a practical application.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to discussion of integration of the abstract idea into a practical application, the additional elements amount to no more than mere instructions to apply an exception, add insignificant extra-solution activity to the abstract idea, and generally link the abstract idea to a particular technological environment or field of use. Additionally, the additional limitations, other than the abstract idea per se, amount to no more than limitations which:
amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields (such as providing targets for ABA program, providing a template for structuring entry of target information by a user concerning one or more of said predefined targets receiving items of target information for multiple subjects, receiving a query from a first user concerning a first ABA program for a first subject, accessing said collection of said target information, e.g., receiving or transmitting data over a network, Symantec, MPEP 2106.05(d)(II)(i); generating a response to said query based on accessed target information, predicting a correlation between predefined targets using items of target information from said multiple users, said correlation utilizing relationships between targets, wherein said relations inform which targets will make learning other targets easier, e.g., performing repetitive calculations, Flook, MPEP 2106.05(d)(II)(ii); establishing a collection of said target information, accessible via said network platform, based at least in part on said items of target information from said multiple users, e.g., electronic recordkeeping, Alice Corp., MPEP 2106.05(d)(II)(iii); storing computerized instructions for performance of the steps recited in the independent claims, providing a standardized structure for entry and storage of target information concerning one or more of said predefined targets, implementation of said one or more of predefined targets for a subject, and progress towards mastery of one of said predefined targets, establishing a collection, i.e. storage or record, of said target information, e.g., storing and retrieving information in memory, Versata Dev. Group, MPEP 2106.05(d)(II)(iv); populating a standardized structure/template based on received content from one or more documents containing information of an individual/user, e.g., electronic scanning or extracting data from a physical document, Content Extraction, MPEP 2106.05(d)(II)(v); receiving a query from a first user concerning a first ABA program for a first subject, which under BRI, includes input/querying via an input device or interface by the individual/user, e.g., a web browser’s back and forward button functionality, Internet Patent Corp., MPEP 2106.05(d)(II)(ii); utilizing a template or data structure for recording/inputting data items of target information; see Thomas Par [0046] which disclose the use of templates to enable a therapist to record observations to generate special needs assessment test and see Barry Par [0096] & Fig. 18 which discloses a “programs” tab which is associated with a particular client or subject, including target information, and including varying criteria, such as the target, the data started, mastery of the target, % correctness of the target, etc. to be populated or input by a user, thereby providing the generally well-known nature of the use of a template/standardized interface for entering data items of target information for ABA program(s))
Dependent claims recite additional subject matter which, as discussed above with respect to integration of the abstract idea into a practical application, amount to invoking computers as a tool to perform the abstract idea. Dependent claims recite additional subject matter which amount to limitations consistent with the additional elements in the independent claims (such as claims 2-10 & 13-21, additional limitations which amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields, claims 9-10 & 20-21, which recite limitations relating to receiving information from one of said multiple users for defining a new target and making said new target available, i.e. transmitting, to others of said multiple users, receiving, in said standardized structure, result information for an implemented target, e.g., receiving or transmitting data over a network, Symantec, MPEP 2106.05(d)(II)(i); claims 7-8, & 18-19, which recite limitations relating to ranking one or more candidate targets based on various aspects, e.g. how many times the plurality of candidate targets has been implemented, how long each of the plurality of candidate targets has been in existence, etc., evaluating said likelihood of success for a first candidate target by considering a relationship between mastery of said first candidate target and mastery of another target, predicting how long it will take a first subject to master a skill, e.g., performing repetitive calculations, Flook, MPEP 2106.05(d)(II)(ii); claims 2-10 & 13-21, which recite limitations generally relating to storing various user data, storing various ABA program data, storing various predefined target data, storing computerized instructions for performance of the steps recited on a computer or network platform, e.g., storing and retrieving information in memory, Versata Dev. Group, MPEP 2106.05(d)(II)(iv). 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. Their collective functions merely provide conventional computer implementation.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-10 & 12-21 are rejected under 35 U.S.C. 103 as being unpatentable over Barry et al. (U.S. Patent Publication No. 2018/0174677), hereinafter “Barry”, in view of Etra et al. (U.S. Patent Publication No. 2021/0257081), hereinafter “Etra”.
Claim 1 –
Regarding Claim 1, Barry discloses a method for use in developing and implementing programs of Applied Behavior Analysis (ABA) for individuals with developmental disabilities, comprising:
providing predefined targets for ABA programs (See Barry Par [0044] which discloses creation of a therapy plan including identification of a skill or skills that the subject is required to master, and the creation of a program for each of these skills, and each of these programs can be created by creating or identifying goals, targets, instructions and mastery criteria; See Barry Par [0005] which discloses one example of therapy including Applied Behavior Analysis (ABA) therapy to teach communication skills, teach life skills, and/or modify problem behavior), wherein
each said predefined target comprises a skill to be addressed and one or more interventions for promoting mastery of said skill, and each said ABA program is a defined process for modifying one or more behaviors of an individual in relation to one or more of said predefined targets (See Barry Par [0006] which discloses during ABA therapy, data may be collected on an ongoing basis to measure progress, and the data may then be used to modify a therapy plan for the subject or to create a new therapy plan; See Barry Par [0011] which discloses selecting a program and selecting a target; See Barry Par [0044] which discloses identification of a skill or skills that the subject is required to master and the creation of a program for each of these skills, each of the programs being created by creating or identifying goals, targets, instructions, and mastery criteria);
providing a template for structuring entry of target information by a user concerning one or more of said predefined targets, implementation of said one or more of predefined targets for a subject, and progress towards mastery of one of said predefined targets (See Barry Par [0088]-[0093] and Fig. 10-15 which discloses an interface for inputting information such as the BIP name, behavior goals, functions, measurement type, operational definitions, antecedent modifications, replacement, behavior, and consequence manipulation, behaviors, events and event information, measurement type, goals, and program instructions associated with the goals; See Barry Par [0096] & Fig. 18 which discloses a “programs” tab which is associated with a particular client or subject, including target information, and including varying criteria, such as the target, the data started, mastery of the target, % correctness of the target, etc. to be populated or input by a user), wherein
said template provides a standardized structure for said entry of target information (See Barry Par [0088]-[0093] and Fig. 10-15 which discloses an interface for inputting information such as the BIP name, behavior goals, functions, measurement type, operational definitions, antecedent modifications, replacement, behavior, and consequence manipulation, behaviors, events and event information, measurement type, goals, and program instructions associated with the goals; See Figs. 12-14 which display or provide a standardized structure for entry of target information);
receiving, at a network platform from multiple users, items of target information for multiple subjects, said items of target information provided using said predefined targets and said template (See Barry Par [0093] & Fig. 15 providing a collection of said information in the form dashboard or user interface for access by one or more users; See Barry Par [0096] & Fig. 18 which discloses a “programs” tab which is associated with a particular client or subject, including target information, such as a list of programs, a list of goals, a field containing directions, and a grid containing information relating to targets such as names, date started, and percentage correct; See Barry Par [0096] & Fig. 18 which discloses a “programs” tab which is associated with a particular client or subject, including target information, and including varying criteria, such as the target, the data started, mastery of the target, % correctness of the target, etc. to be populated or input by a user);
establishing a collection of said target information, accessible via said network platform, based at least in part on said items of target information from said multiple users (See Barry Par [0093] & Fig. 15 providing a collection of said information in the form dashboard or user interface for access by one or more users; See Barry Par [0096] & Fig. 18 which discloses a “programs” tab which is associated with a particular client or subject, including target information, such as a list of programs, a list of goals, a field containing directions, and a grid containing information relating to targets such as names, date started, and percentage correct; See Barry Par [0096] & Fig. 18 which discloses a “programs” tab which is associated with a particular client or subject, including target information, and including varying criteria, such as the target, the data started, mastery of the target, % correctness of the target, etc. to be populated or input by a user; See Barry Par [0087] & Fig. 9 which discloses the interface tracking target information for multiple clients, and varying criteria related to each of the clients, including start of care, initial assessment, ABA status, etc.);
receiving, at said network platform, a query from a first user concerning a first ABA program for a first subject (See Barry Par [0087] & Fig. 9 which discloses the interface tracking target information for multiple clients, and varying criteria related to each of the clients, including start of care, initial assessment, ABA status, etc.; See Barry Par [0088] & Figs. 9-12 & 15 which discloses the management of a particular client from each of the clients listed in Fig. 9, i.e. upon selection (i.e. query) of a particular client, ABA program information and targets for the subject are presented/populated); and
accessing said collection of said target information to generate a response to said query, said response free of protected information of other subjects (See Barry Par [0087] & Fig. 9 which discloses the interface tracking target information for multiple clients, and varying criteria related to each of the clients, including start of care, initial assessment, ABA status, etc.; See Barry Par [0088] & Figs. 9-12 & 15 which discloses the management of a particular client from each of the clients listed in Fig. 9, i.e. upon selection (i.e. query) of a particular client, ABA program information and targets for the subject are presented/populated; See Barry Par [0096] & Fig. 18 which discloses a “programs” tab, i.e. standardized structure, which is associated with a particular client or subject, including target information, and including varying criteria, such as the target, the data started, mastery of the target, % correctness of the target, etc. to be populated or input by a user); and
said correlation utilizes relationships between targets (See Barry Par [0049] which discloses a program may have a hierarchy that deconstructs to a set of goals, which in turn deconstruct to a set of targets), wherein
said relationships are determined by said processor (See Barry Par [0106]-[0107] which discloses one or more processors or computers/computer systems for performing and/or automatically conducting tasks),
said relationships comprise one or more of a parent/child relationship between targets and a hierarchy of targets (See Barry Par [0049] which discloses a program may have a hierarchy that deconstructs to a set of goals, which in turn deconstruct to a set of targets, , thereby constituting parent/child relationships at least by a broader “parent” goal deconstructing into children “targets”).
While Barry generally discloses a hierarchy of targets and parent/child relationships between said targets, Barry is relatively silent on operating a processor to automatically perform correlations of targets from multiple users, informing which targets will make learning easier, as given by the following limitations:
operating a processor of said network platform to predict a correlation between said predefined targets using said items of target information from said multiple users,
wherein said relationships inform which targets will make learning other targets easier (See Etra Par [0043], [0055], [0049], & [0095 which discloses fine-tuning hours recommendations for different skills/behaviors categories based on applied learning models optimizing said treatment plan parameters based on historical data from multiple users, such that said skills/behaviors are optimized based on which skills the current patient’s cohort matches).
However, Etra discloses operating a processor of said network platform (See Etra Par [0043], [0049], & [0095] which discloses a machine learning algorithm for optimizing ABA treatment plans, i.e. utilizing a processor) to predict a correlation between said predefined targets using said items of target information from said multiple users (See Etra Par [0043], [0049], & [0095] which discloses a machine learning algorithm for optimizing ABA treatment plans, such that quantifiable criteria for progress are established, describing behavioral intervention techniques appropriate to the target behavior, reinforcers selected, and strategies for generalization of learned skills based on historical data of ABA treatments from multiple patients, to produce patient cohorts), wherein said relationships inform which targets will make learning other targets easier (See Etra Par [0043], [0055], [0049], & [0095] which discloses fine-tuning hours recommendations for different skills/behaviors categories based on applied learning models optimizing said treatment plan parameters based on historical data from multiple users, such that said skills/behaviors are optimized based on which skills the current patient’s cohort matches). The disclosure of Etra is directly applicable to the disclosure of Barry, because both disclosures share limitations and capabilities, such as being directed towards optimizing ABA treatments for one or more patients.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the disclosure of Barry, which already discloses a hierarchy of targets and parent/child relationships between said targets, to further include processor to automatically perform correlations of targets from multiple users, informing which targets will make learning easier, as disclosed by Etra, because this allows for automated algorithms to optimize ABA Treatment plans by producing patient cohorts based on quantifiable criteria, and thereby optimizing which skills/behaviors to learn based on which patient cohort the current patient falls into (See Etra Par [0043], [0055], [0049], & [0095]).
Claim 2 -
Regarding Claim 2, Barry and Etra disclose the method of claim 1 in its entirety. Barry further discloses a method, wherein:
said skill involves reducing a behavior associated with a developmental disability (See Barry Par [0005] which discloses one example of autism therapy including Applied Behavior Analysis (ABA) therapy to teach communication skills, teach life skills, and/or modify problem behavior, i.e. reduce problem behavior associated with autism).
Claim 3 –
Regarding Claim 3, Barry and Etra disclose the method of claim 1 in its entirety. Barry further discloses a method, wherein:
said skill is associated with learning a behavior that is suppressed due to developmental disability (See Barry Par [0005] which discloses one example of autism therapy including Applied Behavior Analysis (ABA) therapy to teach communication skills, teach life skills, i.e. learning behaviors that are suppressed by autism).
Claim 4 –
Regarding Claim 4, Barry and Etra disclose the method of claim 1 in its entirety. Barry further discloses a method, wherein:
said query concerns identifying an appropriate target for said first subject (See Barry Par [0006] which discloses during ABA therapy, data may be collected on an ongoing basis to measure progress, and the data may then be used to modify a therapy plan for the subject or to create a new therapy plan; See Barry Par [0011] which discloses selecting a program and selecting a target; See Barry Par [0044] which discloses identification of a skill or skills that the subject is required to master and the creation of a program for each of these skills, each of the programs being created by creating or identifying goals, targets, instructions, and mastery criteria).
Claim 5 –
Regarding Claim 5, Barry and Etra disclose the method of claim 4 in its entirety. Barry further discloses a method, wherein:
said network platform is operative for identifying a first behavior based on said query and matching said first behavior to one or more candidate targets (See Barry Par [0005] which discloses one example of autism therapy including Applied Behavior Analysis (ABA) therapy to teach communication skills, teach life skills, and/or modify problem behavior; See Barry Par [0044] which discloses identification of a skill or skills that the subject is required to master and the creation of a program for each of these skills, each of the programs being created by creating or identifying goals, targets, instructions, and mastery criteria).
Claim 6 –
Regarding Claim 6, Barry and Etra disclose s the method of claim 5 in its entirety. Barry further discloses a method, wherein:
said matching comprises identifying a plurality of said one or more candidate targets associated with said first behavior and comparing said plurality of said one or more candidate targets based on a likelihood of success in promoting mastery of an associated skill (See Barry Par [0005] which discloses one example of autism therapy including Applied Behavior Analysis (ABA) therapy to teach communication skills, teach life skills, and/or modify problem behavior; See Barry Par [0044] which discloses identification of a skill or skills that the subject is required to master and the creation of a program for each of these skills, each of the programs being created by creating or identifying goals, targets, instructions, and mastery criteria; See Barry Par [0043] , [0045], & [0057] which discloses inputting data into a mathematical model for revising or generating an autism therapy plan, and while not “calculations” per se, the model includes “calculations” of new programs, new targets, etc. for a client accomplishing said autism therapy).
Claim 7 –
Regarding Claim 7, Barry and Etra disclose the method of claim 6 in its entirety. Barry further discloses a method, wherein:
said network platform is operative for ranking said one or more candidate targets based on one or more of (While not “ranking” per se, see Barry Par [0096] & Fig. 18 which discloses a “programs” tab which is associated with a particular client or subject, including target information, and ordering, i.e. ranking, the entries according to varying criteria, such as the target, the data started, mastery of the target, % correctness of the target, etc.; it is furthermore understood that only one of the following criteria has to be disclosed since the verbiage “one or more of” is present) a number of times each of said candidate targets has been implemented, how long each of said one or more candidate targets has been in existence (See Barry Par [0096] & Fig. 18 which discloses a “programs” tab which is associated with a particular client or subject, including target information, such as date started, i.e. how long the targets have been in existence), a ratio of the number of times each of said one or more candidate targets was successfully mastered to times it was implemented (See Barry Par [0096] & Fig. 18 which discloses a “programs” tab which is associated with a particular client or subject, including target information, such as which programs have been mastered, and would therefore also include a “ratio” of successfully mastered targets), a geographical extent over which each of said one or more candidate targets was implemented, and statistical characteristics concerning previous mastery of each of said one or more candidate targets (See Barry Par [0096] & Fig. 18 which discloses a “programs” tab which is associated with a particular client or subject, including target information, mastery of the target, % correctness of the target, etc. which is understood to include “statistical characteristics concerning previous mastery of each of said one or more candidate targets”).
Claim 8 –
Regarding Claim 8, Barry and Etra disclose the method of claim 6 in its entirety. Barry further discloses a method, wherein:
said network platform is operative for evaluating said likelihood of success for a first candidate target by considering a relationship between mastery of said first candidate target and mastery of another target (See Barry Par [0043] , [0045], & [0057] which discloses inputting data into a mathematical model for revising or generating an autism therapy plan, i.e. current programs/targets, and while not “calculations” per se, the model includes “calculations” of new programs, new targets, etc. for a client accomplishing said autism therapy, (i.e. Barry Par [0044] discloses identification of a skill or skills that the subject is required to master and the creation of a program for each of these skills, each of the programs being created by creating or identifying goals, targets, instructions, and mastery criteria) thereby considering a relationship between mastery of a first candidate target and mastery of another target).
Claim 9 –
Regarding Claim 9, Barry and Etra disclose the method of claim 1 in its entirety. Barry further discloses a method, wherein:
said network platform is operative for receiving information from one of said multiple users for defining a new target and making said new target available to others of said multiple users (See Barry Par [0043] , [0045], & [0057] which discloses inputting data into a mathematical model for revising or generating an autism therapy plan; See Barry Par [0093] & Fig. 15 providing a collection of said information in the form dashboard or user interface for access by one or more users; See Barry Par [0096] & Fig. 18 which discloses a “programs” tab which is associated with a particular client or subject, including target information, such as a list of programs, a list of goals, a field containing directions, and a grid containing information relating to targets such as names, date started, and percentage correct; See Barry Par [0096] & Fig. 18 which discloses a “programs” tab which is associated with a particular client or subject, including target information, and including varying criteria, such as the target, the data started, mastery of the target, % correctness of the target, etc. to be populated or input by a user).
Claim 10 –
Regarding Claim 10, Barry and Etra disclose the method of claim 1 in its entirety. Barry further discloses a method, wherein:
said network platform is operative for receiving, in said standardized structure, result information for an implemented target (See Barry Par [0087] & Fig. 9 which discloses the interface tracking target information for multiple clients, and varying criteria related to each of the clients, including start of care, initial assessment, ABA status, etc.; See Barry Par [0088] & Figs. 9-12 & 15 which discloses the management of a particular client from each of the clients listed in Fig. 9, i.e. upon selection of a particular client, ABA program information and targets for the subject are presented/populated; See Barry Par [0096] & Fig. 18 which discloses a “programs” tab, i.e. standardized structure, which is associated with a particular client or subject, including target information, and including varying criteria, such as the target, the data started, mastery of the target, % correctness of the target, etc. to be populated or input by a user).
Claim 12 –
Regarding Claim 12, Barry discloses a system for use in developing and implementing programs of Applied Behavior Analysis (ABA) for individuals with developmental disabilities, comprising:
a network platform operative (See Barry Par [0107]-[0108] which discloses the use of multimedia devices, desktop computer devices, one or more autism therapy session platforms optionally configured in network communication for carrying out elements of the autism therapy sessions platform) for:
providing predefined targets for said ABA programs (See Barry Par [0044] which discloses creation of a therapy plan including identification of a skill or skills that the subject is required to master, and the creation of a program for each of these skills, and each of these programs can be created by creating or identifying goals, targets, instructions and mastery criteria; See Barry Par [0005] which discloses one example of therapy including Applied Behavior Analysis (ABA) therapy to teach communication skills, teach life skills, and/or modify problem behavior), wherein
each said predefined target comprises a skill to be addressed and one or more interventions for promoting mastery of said skill, and each said ABA program is a defined process for modifying one or more behaviors of an individual in relation to one or more of said predefined targets (See Barry Par [0006] which discloses during ABA therapy, data may be collected on an ongoing basis to measure progress, and the data may then be used to modify a therapy plan for the subject or to create a new therapy plan; See Barry Par [0011] which discloses selecting a program and selecting a target; See Barry Par [0044] which discloses identification of a skill or skills that the subject is required to master and the creation of a program for each of these skills, each of the programs being created by creating or identifying goals, targets, instructions, and mastery criteria);
providing a template for structuring entry of target information by a user concerning said one or more predefined targets, implementation of said one or more predefined targets for a subject, and progress towards mastery of said one or more predefined targets (See Barry Par [0088]-[0093] and Fig. 10-15 which discloses an interface for inputting information such as the BIP name, behavior goals, functions, measurement type, operational definitions, antecedent modifications, replacement, behavior, and consequence manipulation, behaviors, events and event information, measurement type, goals, and program instructions associated with the goals; See Barry Par [0096] & Fig. 18 which discloses a “programs” tab which is associated with a particular client or subject, including target information, and including varying criteria, such as the target, the data started, mastery of the target, % correctness of the target, etc. to be populated or input by a user), wherein
said template provides a standardized structure for said entry of target information (See Barry Par [0088]-[0093] and Fig. 10-15 which discloses an interface for inputting information such as the BIP name, behavior goals, functions, measurement type, operational definitions, antecedent modifications, replacement, behavior, and consequence manipulation, behaviors, events and event information, measurement type, goals, and program instructions associated with the goals; See Figs. 12-14 which display or provide a standardized structure for entry of target information);
receiving items of said target information for multiple subjects, said items of target information provided using said one or more predefined targets and said template (See Barry Par [0093] & Fig. 15 providing a collection of said information in the form dashboard or user interface for access by one or more users; See Barry Par [0096] & Fig. 18 which discloses a “programs” tab which is associated with a particular client or subject, including target information, such as a list of programs, a list of goals, a field containing directions, and a grid containing information relating to targets such as names, date started, and percentage correct; See Barry Par [0096] & Fig. 18 which discloses a “programs” tab which is associated with a particular client or subject, including target information, and including varying criteria, such as the target, the data started, mastery of the target, % correctness of the target, etc. to be populated or input by a user);
providing access to a collection of said target information, said target information based at least in part on said items of target information from said multiple subjects (See Barry Par [0093] & Fig. 15 providing a collection of said information in the form dashboard or user interface for access by one or more users; See Barry Par [0096] & Fig. 18 which discloses a “programs” tab which is associated with a particular client or subject, including target information, such as a list of programs, a list of goals, a field containing directions, and a grid containing information relating to targets such as names, date started, and percentage correct; See Barry Par [0096] & Fig. 18 which discloses a “programs” tab which is associated with a particular client or subject, including target information, and including varying criteria, such as the target, the data started, mastery of the target, % correctness of the target, etc. to be populated or input by a user; See Barry Par [0087] & Fig. 9 which discloses the interface tracking target information for multiple clients, and varying criteria related to each of the clients, including start of care, initial assessment, ABA status, etc.);
receiving a query from a first user concerning a first ABA program for a first subject (See Barry Par [0087] & Fig. 9 which discloses the interface tracking target information for multiple clients, and varying criteria related to each of the clients, including start of care, initial assessment, ABA status, etc.; See Barry Par [0088] & Figs. 9-12 & 15 which discloses the management of a particular client from each of the clients listed in Fig. 9, i.e. upon selection (i.e. query) of a particular client, ABA program information and targets for the subject are presented/populated); and
accessing said collection of said target information to generate a response to said query, said response free of protected information of other subjects (See Barry Par [0087] & Fig. 9 which discloses the interface tracking target information for multiple clients, and varying criteria related to each of the clients, including start of care, initial assessment, ABA status, etc.; See Barry Par [0088] & Figs. 9-12 & 15 which discloses the management of a particular client from each of the clients listed in Fig. 9, i.e. upon selection (i.e. query) of a particular client, ABA program information and targets for the subject are presented/populated; See Barry Par [0096] & Fig. 18 which discloses a “programs” tab, i.e. standardized structure, which is associated with a particular client or subject, including target information, and including varying criteria, such as the target, the data started, mastery of the target, % correctness of the target, etc. to be populated or input by a user);
said correlation utilizes relationships between targets (See Barry Par [0049] which discloses a program may have a hierarchy that deconstructs to a set of goals, which in turn deconstruct to a set of targets), wherein
said relationships are determined by said processor (See Barry Par [0106]-[0107] which discloses one or more processors or computers/computer systems for performing and/or automatically conducting tasks),
said relationships comprise one or more of a parent/child relationship between targets and a hierarchy of targets (See Barry Par [0049] which discloses a program may have a hierarchy that deconstructs to a set of goals, which in turn deconstruct to a set of targets, , thereby constituting parent/child relationships at least by a broader “parent” goal deconstructing into children “targets”).
While Barry generally discloses a hierarchy of targets and parent/child relationships between said targets, Barry is relatively silent on operating a processor to automatically perform correlations of targets from multiple users, informing which targets will make learning easier, as given by the following limitations:
operating a processor of said network platform to predict a correlation between said predefined targets using said items of target information from said multiple users,
wherein said relationships inform which targets will make learning other targets easier (See Etra Par [0043], [0055], [0049], & [0095 which discloses fine-tuning hours recommendations for different skills/behaviors categories based on applied learning models optimizing said treatment plan parameters based on historical data from multiple users, such that said skills/behaviors are optimized based on which skills the current patient’s cohort matches).
However, Etra discloses operating a processor of said network platform (See Etra Par [0043], [0049], & [0095] which discloses a machine learning algorithm for optimizing ABA treatment plans, i.e. utilizing a processor) to predict a correlation between said predefined targets using said items of target information from said multiple users (See Etra Par [0043], [0049], & [0095] which discloses a machine learning algorithm for optimizing ABA treatment plans, such that quantifiable criteria for progress are established, describing behavioral intervention techniques appropriate to the target behavior, reinforcers selected, and strategies for generalization of learned skills based on historical data of ABA treatments from multiple patients, to produce patient cohorts), wherein said relationships inform which targets will make learning other targets easier (See Etra Par [0043], [0055], [0049], & [0095] which discloses fine-tuning hours recommendations for different skills/behaviors categories based on applied learning models optimizing said treatment plan parameters based on historical data from multiple users, such that said skills/behaviors are optimized based on which skills the current patient’s cohort matches). The disclosure of Etra is directly applicable to the disclosure of Barry, because both disclosures share limitations and capabilities, such as being directed towards optimizing ABA treatments for one or more patients.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the disclosure of Barry, which already discloses a hierarchy of targets and parent/child relationships between said targets, to further include processor to automatically perform correlations of targets from multiple users, informing which targets will make learning easier, as disclosed by Etra, because this allows for automated algorithms to optimize ABA Treatment plans by producing patient cohorts based on quantifiable criteria, and thereby optimizing which skills/behaviors to learn based on which patient cohort the current patient falls into (See Etra Par [0043], [0055], [0049], & [0095]).
Claims 13-21 –
Regarding Claims 13-21, claims 13-21 are substantially similar or the same as claims 2-10, respectively, but for recitation of the system implementation of independent claim 12 rather than the computerized method implementation of independent claim 1. Because Barry and Etra effectively disclose the system of claim 12 in its entirety and claims 2-10, as presented above, claims 13-21 are rejected under 35 U.S.C. 103 over Barry in view of Etra for substantially similar or the same reasonings as presented above for claims 2-10, respectively, but applied to the system implementation including a network platform for performance of the steps or embodiments recited, as recited in independent claim 12.
Response to Arguments
Applicant's arguments filed 16 December 2025 have been fully considered but they are not persuasive:
Regarding 35 U.S.C. 101 rejections of claims 1-21, Applicant argues on p. 8-10 of Arguments/Remarks in view of Enfish, LLC v. Microsoft Corp., stating that improvements in computer science are not always abstract, and that it was determined that implementations of a solution to a problem in the software arts that are more than simple recitations of well-known processes executed by a computer are patent eligible. As such, Applicant argues that the implementations of claim 1 and claim 12 solve current issues in the field of ABA therapy program development and implementation, because the current state of the field of ABA therapy program development and implementation only recreates what would be done on paper in an automated fashion, versus the currently claimed invention, which provides predefined targets and accessing target information to generate a response to a query, such that the efficacy of certain ABA programs can be tracked and better studied, therefore constituting an improvement over prior art systems. Examiner respectfully disagrees with Applicant’s arguments. While Examiner does not necessarily argue against improvements to ABA program tracking/being studied, Examiner does content that does not represent at technical improvement as defined by the Alice/Mayo framework for determining patent-eligible subject matter. That is, improvements to ABA program tracking/being studied merely represents an improvement to the already-characterized abstraction of ABA program tracking/being studied. That is, ABA program tracking/being studied substantially relates to human-performed activities, behaviors, and/or learning of skills. Therefore, tracking/studying of said activities, behaviors, and/or learning of skills also substantially relates to the abstract idea grouping of “Methods of organizing human activity”. That is, an improvement to the already-characterized abstraction still constitutes the abstraction itself, and as stated in MPEP 2106.05(a), that the judicial exception alone cannot provide the improvement. Therefore, improved aspects of tracking and/or studying ABA programs cannot alone provide the technical improvement and/or constitute a practical application to overcome 35 U.S.C. 101 rejections. While Applicant further argues on p. 9-10 of Arguments/Remarks that the invention provides an advancement to current systems in the software arts for ABA therapy, because predictions can be complex and take into account information that could not be done through a simple mental process, MPEP 2106.05(a)(I) states that mere automation of manual processes and/or processes that are manually performed on a computer does not constitute a practical application/improvement to the technology. Therefore, even if “predictions can be complex” and utilize a computer for known processing efforts to account for complex/multitudes of information, this does not necessarily represent a practical application and/or significantly more than the recited abstract idea. Applicant also argues various aspects of advancements and improvements, including real-world effects/tangible outcomes and/or transformative steps. However, Examiner contends that merely outputting a computerized result of analyses performed does not represent a tangible outcome, but rather an abstract outcome. That is, said output is not integrated into a physical, concrete or tangible result, such as the result that can be found in Diamond v. Diehr. Furthermore, Examiner contends that “transformative steps” or transformative actions that relate to mere manipulation and/or analyses of data is insufficient to meet the transformation prong of the “machine-or-transformation” test for constituting a practical application, see Cybersource Corp v. Retail Decisions, Inc. As such, claims 1-21 remain rejected under 35 U.S.C. 101.
Regarding 35 U.S.C. 102 rejections of claims 1-21, Applicant generally argues on p. 11-14 of Arguments/Remarks against previous 35 U.S.C. 102 rejections made in view of Barry for claims 1-21. That is, Applicant generally argues that Barry does not read on each and every limitation found in amended independent claims 1 & 12. More specifically, Applicant argues on p. 13-14 of Arguments/Remarks that Barry does not disclose predicting a correlation between predefined targets and/or correlations based on target information specifically from multiple users. Applicant further argues, therefore, that the 35 U.S.C. 102 rejections for claims 1 & 12 should be withdrawn. Examiner agrees with Applicant’s arguments. Therefore, the 35 U.S.C. 102 rejections made in view of Barry for claims 1-21 have been withdrawn. However upon further consideration, a new ground of rejection has been made under 35 U.S.C. 103 over Barry in view of Etra. This new ground of rejection relies on Etra to read on predicting correlations between predefined targets, i.e. relationships between targets defining which targets will make learning other targets easier and/or correlations based on target information from multiple users. That is, Etra discloses machine learning methodologies to improve ABA results at least by improving recommendations for patients that fall in to defined cohorts, at least by predicting a correlation between predefined targets and/or correlations based on target information, i.e. ABA treatments, treatment variables, demographics of the patients, demographics of the patients’ parents, etc. specifically from multiple users, such as at Etra Par [0043], [0049], & [0095]. It should be noted, however that Barry effectively discloses use in sharing predefined targets and tracking progress towards hitting those targets by multiple different individuals, as further explained in the arguments below. As such, claims 1-21 remain rejected under 35 U.S.C. 103.
Regarding 35 U.S.C. 102 rejections of claims 1-21, Applicant argues on p. 11-12 of Arguments/Remarks that the system of Barry is for individualized program management, and is not for use in sharing predefined targets and tracking progress towards hitting those targets by multiple different individuals. Examiner respectfully disagrees with Applicant’s arguments. Assuming arguendo that Barry does not disclose sharing predefined targets and tracking progress towards hitting those targets by multiple different individuals, Examiner contends that the claim language does not necessarily require these aspects for multiple different individuals. That is, beyond recitation of multiple individuals in the preamble of the claim, merely limiting the scope/field of endeavor of the claims and stating that data is used from multiple users to define target information. For instance, the first limitation found in independent claims 1 & 12 recite “a defined process for modifying one or more behaviors of an individual in relation to one or more of said predefined targets,” not multiple individuals. While Applicant may be arguing in view of the “multiple subjects” language, a “subject” does not necessarily constitute a human entity unless specified in the claims. That is, under broadest reasonable interpretation, “target information for multiple subjects,” for example, could simply constitute targets defined for multiple areas or topics. While Applicant may intend for a more specific interpretation of “subject”, such as one defining a human entity, under the broadest reasonable interpretation, “subject” can merely include areas or topics to be achieved by the singular individual established in “a defined process for modifying one or more behaviors of an individual in relation to one or more of said predefined targets.” While the above assumed arguendo that Barry does not disclose sharing predefined targets and tracking progress towards hitting those targets by multiple different individuals, Examiner purports that Barry Par [0093] & Fig. 15 providing a collection of said information in the form dashboard or user interface for access by one or more users and Barry Par [0087] & Fig. 9 discloses the interface tracking target information for multiple clients, and varying criteria related to each of the clients, including start of care, initial assessment, ABA status, etc. Furthermore, the disclosure of Barry is directed towards a mathematical model That is, Barry effectively discloses “sharing predefined targets and tracking progress towards hitting those targets by multiple different individuals” in said interface implementation described by Barry at these cited portions. As such, Barry still reads on independent claims 1 & 12. As such, claims 1-21 remain rejected under 35 U.S.C. 103.
Regarding 35 U.S.C. 102 rejections of claims 1-21, Applicant argues on p. 12-13 of Arguments/Remarks that Barry does not disclose “predefined” targets, stating that Barry specifically describes that there is a creation of a program for each of these skills, meaning that the targets are not predefined as claimed in the present application. Examiner respectfully disagrees with Applicant’s arguments. While Applicant argues that Barry describes “creation of a program for each of these skills”, and therefore, these targets are not “predefined, Examiner argues that Applicant’s claims do not specify the time period that constitutes “predefined”. That is, Barry effectively discloses an initial establishing/creation of targets for a user, i.e. before the plan is actually implemented, and following implementation of the plan, subsequent updating of said targets based on received data. Therefore, said initial establishing/creation of targets for a user, which occurs before the plan is actually implemented, could effectively constitute “predefined” targets for a user under broadest reasonable interpretation, since these targets are determined before a defined treatment plan has been implemented for the user. That is, without specifying the particular time-frame for said “predefined” targets, Barry defining said targets before the implementation of the defined treatment plan effectively reads on “predefined” targets. Therefore, it is determined that Barry does disclose “predefined” targets, under broadest reasonable interpretation, without specifying the particular time-frame for said “predefined” targets. As such, Barry still reads on independent claims 1 & 12. As such, claims 1-21 remain rejected under 35 U.S.C. 103.
Regarding 35 U.S.C. 102 rejections of claims 1-21, Applicant argues on p. 14 of Arguments/Remarks that because claims 2-10 and 13-21 depend from independent claims 1 & 12, Barry no longer anticipates claims 2-10 & 13-21 under 35 U.S.C. 102, by virtue of dependency. Examiner agrees with Applicant’s arguments. However, a new ground of rejection has been made under 35 U.S.C. 103 over Barry in view of Etra. Therefore, independent claims 1 & 12 and claims dependent therefrom (claims 2-10 and 13-21) remain rejected under 35 U.S.C. 103. As such, claims 1-21 remain rejected under 35 U.S.C. 103.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Kohli et al. (“Machine learning-based ABA treatment recommendation and personalization for autism spectrum disorder: an exploratory study” – NPL – 25 July 2022) discloses applying two machine learning algorithms to recommend and personalize ABA treatment goals for study participants with ASD;
Bradley et al. (U.S. Patent Publication No. 2019/0034494) discloses a system for automatically tracking goal procession and determinations of whether thresholds associated with goals are being met based on compiled data;
Bindler et al. (U.S. Patent Publication No. 2003/0059750) discloses a system or implementing an online psychological service, including various learning and/or skill development, and further specifically describes a client can monitor their activity to ensure they are performing a behavior pattern correctly, such that once simpler forms of behaviors are mastered, they are linked or chained together, i.e. determining which behaviors to perform in an order that are optimal for development of more complex behaviors.
Applicant's amendment necessitated the new ground 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.
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/H.R./Examiner, Art Unit 3684
/KENNETH BARTLEY/Primary Examiner, Art Unit 3684