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 .
Status of Claims
Claims 1-20 were previously pending and subject to a non-final Office Action having a notification date of November 19, 2025 (“non-final Office Action”). Following the non-final Office Action, Applicant filed an amendment on February 19, 2026 (the “Amendment”), amending claims 1, 14, and 18; canceling claim 5; and adding new claim 21.
The present Final Office Action addresses pending claims 1-4 and 6-21 in the Amendment.
Response to Arguments
Response to Applicant’s Arguments Regarding Claim Rejections Under 35 USC §101
On pages 9-10 of the Amendment, Applicant takes the position that the present claims do not recite "mental processes" because they now recite "automatically generating, based at least in part on the predicting of at least one of mental distress among the given dyad and social rhythm disruption among the given dyad, at least one control signal for controlling at least portions of one or more external physical robot-mediated interaction systems in connection with responding to the at least one of the predicted mental distress among the given dyad and the predicted social rhythm disruption among the given dyad" which is not performable in the human mind. The Examiner disagrees that the present claims do not recite "mental processes."
The courts consider a mental process (thinking) that "can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). As the Federal Circuit explained, "methods which can be performed mentally, or which are the equivalent of human mental work, are unpatentable abstract ideas the ‘basic tools of scientific and technological work’ that are open to all.’" 654 F.3d at 1371, 99 USPQ2d at 1694 (citing Gottschalk v. Benson, 409 U.S. 63, 175 USPQ 673 (1972)). MPEP 2106.05(III).
Claims do not recite a mental process when they do not contain limitations that can practically be performed in the human mind, for instance when the human mind is not equipped to perform the claim limitations. See SRI Int’l, Inc. v. Cisco Systems, Inc., 930 F.3d 1295, 1304 (Fed. Cir. 2019). MPEP 2106.05(III)(A).
However, claims can recite a mental process even if they are claimed as being performed on a computer. The Supreme Court recognized this in Benson, determining that a mathematical algorithm for converting binary coded decimal to pure binary within a computer’s shift register was an abstract idea. The Court concluded that the algorithm could be performed purely mentally even though the claimed procedures "can be carried out in existing computers long in use, no new machinery being necessary." 409 U.S at 67, 175 USPQ at 675. See also Mortgage Grader, 811 F.3d at 1324, 117 USPQ2d at 1699 (concluding that concept of "anonymous loan shopping" recited in a computer system claim is an abstract idea because it could be "performed by humans without a computer"). MPEP 2106.05(III)(C).
In the present case, the independent claims recite a mental process because a person could practically in their mind with pen and paper obtain biomarker data of a patient/caregiver dyad (e.g., by looking at it on a screen or paper), pre-process/adjust/normalize/segment/etc. the biomarker data to obtain indications of mental distress/social rhythm disruption (determine "data-based representations" of mental distress/social rhythm disruption in the biomarker data), and predict mental distress/social rhythm disruption among the dyad such as by analyzing the "data-based representations." These recitations, under their broadest reasonable interpretation, are similar to the concepts of collecting information, analyzing it and displaying certain results of the collection and analysis in Electric Power Group, LLC, v. Alstom (830 F.3d 1350, 119 USPQe2d 1739 (Fed. Cir. 2016)). MPEP 2106.04(a)(2)(III).
For instance, determining "data-based representations" of mental distress/social rhythm disruption based on obtained biomarkers of a patient/caregiver dyad and predicting mental distress/social rhythm disruption among the dyad using the data-based representations for use in performing actions (e.g., interventions to reduce predicted mental distress/social rhythm disruption in the dyad) amount to "certain methods of organizing human activity" because they are similar to a mental process that a neurologist should follow when testing a patient for nervous system malfunctions, In re Meyer, 688 F.2d 789, 791-93, 215 USPQ 193, 194-96 (CCPA 1982). MPEP 2106.04(a)(2)(II)(C).
The additional limitations of the performing the one or more automated actions including automatically generating, based at least in part on the predicting of at least one of mental distress among the given dyad and social rhythm disruption among the given dyad, at least one control signal for controlling at least portions of one or more external physical robot-mediated interaction systems in connection with responding to the at least one of the predicted mental distress among the given dyad and the predicted social rhythm disruption among the given dyad, the Examiner asserts that these limitations amount to merely reciting the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished (see MPEP § 2106.05(f)) and doing no more than generally linking use of the abstract idea to a particular technological environment or field of use without adding an inventive concept to the abstract idea (see MPEP § 2106.05(h)).
Response to Applicant’s Arguments Regarding Claim Rejections Under 35 USC §102/103
At page 10 of the Amendment, Applicant takes the position that Shamun does not teach predicting at least one of mental distress among a given dyad of at least one patient and at least one caregiver associated with the at least one patient and social rhythm disruption among the given dyad by processing input biomarker data, derived from the given dyad, using one or more artificial intelligence techniques in connection with at least a portion of the one or more data-based representations. The Examiner disagrees because Figure 1C, [0109], [0132], [0161], and [0296] of Shamun illustrates/discloses how the processed data (which includes the "data-based representations" based on input biomarker/physiological data per steps 130, 150 in Figure 1C and [0159]-[0161]) is sent 104B to database 160 and then to prediction model 600 (which includes a neural network/ML model (AI techniques) per [0031], [0129], [0189]-[0191], [0198]) for predicting a mental/emotional/stress/anxiety state of the user/patient and the therapist/caregiver of the dyad.
Applicant’s arguments at pages 11-12 are moot in view of the new grounds of rejection as necessitated by the Amendment.
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 1-4 and 6-21 are rejected under 35 U.S.C. §101 because the claimed invention is directed to an abstract idea without significantly more:
Subject Matter Eligibility Criteria - Step 1:
Claims 1-4 and 6-13 are directed to a method (i.e., a process), claims 14-17 are directed to a non-transitory computer program product comprising a computer readable storage medium (i.e., a manufacture), and claims 18-21 are directed to a system (i.e., an apparatus). Accordingly, claims 1-4 and 6-21 are all within at least one of the four statutory categories. 35 USC §101.
Subject Matter Eligibility Criteria - Alice/Mayo Test: Step 2A - Prong One:
Regarding Prong One of Step 2A of the Alice/Mayo test (which collectively includes the guidance in the January 7, 2019 Federal Register notice and the October 2019 and July 2024 updates issued by the USPTO as incorporated into the MPEP, as supported by relevant case law), the claim limitations are to be analyzed to determine whether, under their broadest reasonable interpretation, they “recite” a judicial exception or in other words whether a judicial exception is “set forth” or “described” in the claims. MPEP 2106.04(II)(A)(1). An “abstract idea” judicial exception is subject matter that falls within at least one of the following groupings: a) certain methods of organizing human activity, b) mental processes, and/or c) mathematical concepts. MPEP 2106.04(a).
Representative independent claim 18 includes limitations that recite at least one abstract idea. Specifically, independent claim 18 recites:
A system comprising:
a memory configured to store program instructions; and
a processor operatively coupled to the memory to execute the program instructions to:
obtain biomarker data derived from a set of one or more dyads, each dyad comprising at least one patient and at least one caregiver associated with the at least one patient;
determine, based at least in part on processing at least a portion of the obtained biomarker data, one or more data-based representations of at least one of mental distress among at least one of the one or more dyads and social rhythm disruption among at least one of the one or more dyads;
predict at least one of mental distress among a given dyad of at least one patient and at least one caregiver associated with the at least one patient and social rhythm disruption among the given dyad by processing input biomarker data, derived from the given dyad, using one or more artificial intelligence techniques in connection with at least a portion of the one or more data-based representations; and
perform one or more automated actions based at least in part on the predicting step, wherein performing one or more automated actions comprises automatically generating, based at least in part on the predicting of at least one of mental distress among the given dyad and social rhythm disruption among the given dyad, at least one control signal for controlling at least portions of one or more external physical robot-mediated interaction systems in connection with responding to the at least one of the predicted mental distress among the given dyad and the predicted social rhythm disruption among the given dyad.
The Examiner submits that the foregoing underlined limitations constitute: (a) “certain
methods of organizing human activity” because they related to managing personal behavior or relationships or interactions between people (e.g., social activities, teaching, and following rules or instructions). For instance, determining "data-based representations" of mental distress/social rhythm disruption based on obtained biomarkers of a patient/caregiver dyad and predicting mental distress/social rhythm disruption among the dyad using the data-based representations for use in performing actions (e.g., interventions to reduce predicted mental distress/social rhythm disruption in the dyad) is similar to a mental process that a neurologist should follow when testing a patient for nervous system malfunctions, In re Meyer, 688 F.2d 789, 791-93, 215 USPQ 193, 194-96 (CCPA 1982). MPEP 2106.04(a)(2)(II)(C).
Furthermore, the foregoing underlined limitations constitute (b) “mental processes” because they are observations/evaluations/judgments/analyses that can, at the currently claimed high level of generality, be practically performed in the human mind (e.g., with pen and paper). For instance, a person could practically in their mind with pen and paper obtain biomarker data of a patient/caregiver dyad (e.g., by looking at it on a screen or paper), pre-process/adjust/normalize/segment/etc. the biomarker data to obtain indications of mental distress/social rhythm disruption (determine "data-based representations" of mental distress/social rhythm disruption in the biomarker data), and predict mental distress/social rhythm disruption among the dyad such as by analyzing the "data-based representations." These recitations, under their broadest reasonable interpretation, are similar to the concepts of collecting information, analyzing it and displaying certain results of the collection and analysis in Electric Power Group, LLC, v. Alstom (830 F.3d 1350, 119 USPQe2d 1739 (Fed. Cir. 2016)). MPEP 2106.04(a)(2)(III).
Claims “directed to collection of information, comprehending the meaning of that collected information, and indication of the results, all on a generic computer network operating in its normal, expected manner,” fail step one of the Alice framework. In re Killian, 45 F.4th 1373, 1380 (Fed. Cir. 2022). Claims directed to “collecting, analyzing, manipulating, and displaying data’’ are abstract. Univ. of Fla. Research Found., Inc. v. General Elec. Co., 916 F.3d 1363, 1368 (Fed. Cir. 2019). Claims directed to organizing, storing, and transmitting information determined to be directed to an abstract idea. Cyberfone Sys., L.L.C. v. CNN Interactive Grp., Inc., 558 F. App’x 988, 992 (Fed. Cir. 2014).
Accordingly, the claim recites at least one abstract idea.
Furthermore, dependent claims 2, 6-8, 11, 12, 15, and 19 further define the at least one abstract idea (and thus fail to make the abstract idea any less abstract) as set forth below:
-Claims 2, 15, and 19 recite how determining the one or more data-based representations includes performing phenotypic characterization which can be practically performed in the human mind ("mental processes") and relates to managing relations between people ("certain methods of organizing human activities").
-Claim 6 recites how performing the actions includes initiating human-mediated interactions within at least a portion of the given dyad which relates to managing relations between people ("certain methods of organizing human activities").
-Claim 7 recites how the predicting includes processing input biomarker data, derived from the given dyad, using one or more trajectory modeling techniques in connection with the at least a portion of the one or more data-based representations which can be practically performed in the human mind ("mental processes") and relates to managing relations between people ("certain methods of organizing human activities").
-Claim 8 recites how the predicting includes predicting one or more temporal state transitions associated with at least one of mental distress among the given dyad and social rhythm disruption among the given dyad which can be practically performed in the human mind ("mental processes") and relates to managing relations between people ("certain methods of organizing human activities").
-Claim 11 recites how obtaining the biomarker data includes obtaining it from an "isolation-related context" of the dyad which can be practically performed in the human mind ("mental processes") and relates to managing relations between people ("certain methods of organizing human activities").
-Claim 12 recites how processing input biomarker data includes processing it from an "isolation-related context" of the dyad which can be practically performed in the human mind ("mental processes") and relates to managing relations between people ("certain methods of organizing human activities").
Subject Matter Eligibility Criteria - Alice/Mayo Test: Step 2A - Prong Two:
Regarding Prong Two of Step 2A of the Alice/Mayo test, it must be determined whether the claim as a whole integrates the abstract idea into a practical application. As noted at MPEP §2106.04(II)(A)(2), it must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements such as merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.” MPEP §2106.05(I)(A).
In the present case, the additional limitations beyond the above-noted at least one abstract idea recited in the claim are as follows (where the bolded portions are the “additional limitations” while the underlined portions continue to represent the at least one “abstract idea”):
A system comprising (using computers or machinery as mere tools to perform the abstract idea as noted below, see MPEP § 2106.05(f)):
a memory configured to store program instructions (using computers or machinery as mere tools to perform the abstract idea as noted below, see MPEP § 2106.05(f)); and
a processor operatively coupled to the memory to execute the program instructions to (using computers or machinery as mere tools to perform the abstract idea as noted below, see MPEP § 2106.05(f)):
obtain biomarker data derived from a set of one or more dyads, each dyad comprising at least one patient and at least one caregiver associated with the at least one patient;
determine, based at least in part on processing at least a portion of the obtained biomarker data, one or more data-based representations of at least one of mental distress among at least one of the one or more dyads and social rhythm disruption among at least one of the one or more dyads;
predict at least one of mental distress among a given dyad of at least one patient and at least one caregiver associated with the at least one patient and social rhythm disruption among the given dyad by processing input biomarker data, derived from the given dyad, using one or more artificial intelligence techniques (merely reciting the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished, see MPEP § 2106.05(f)) in connection with at least a portion of the one or more data-based representations; and
perform one or more automated (using computers or machinery as mere tools to perform the abstract idea as noted below, see MPEP § 2106.05(f)) actions based at least in part on the predicting step, wherein performing one or more automated actions comprises automatically generating, based at least in part on the predicting of at least one of mental distress among the given dyad and social rhythm disruption among the given dyad, at least one control signal for controlling at least portions of one or more external physical robot-mediated interaction systems in connection with responding to the at least one of the predicted mental distress among the given dyad and the predicted social rhythm disruption among the given dyad (merely reciting the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished, see MPEP § 2106.05(f)); mere field of use limitation, see MPEP § 2106.05(h)).
For the following reasons, the Examiner submits that the above-identified additional limitations, when considered as a whole with the limitations reciting the at least one abstract idea, do not integrate the above-noted at least one abstract idea into a practical application.
Regarding the additional limitations of the system including memory including instructions, processor configured to execute the instructions, and "automated" actions, the Examiner submits that these limitations amount to merely using a computer or other machinery as tools performing their typical functionality in conjunction with performing the above-noted at least one abstract idea (see MPEP § 2106.05(f)).
Regarding the additional limitations of the prediction using "one or more artificial intelligence techniques," the Examiner submits that these limitations amount to merely reciting the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished which is equivalent to the words “apply it” (see MPEP § 2106.05(f)). Claims drafted using largely (if not entirely) result-focused functional language, containing no specificity about how the purported invention achieves those results, are almost always found to be ineligible for patenting under Section 101.” Beteiro, LLC v. DraftKings Inc., 104 F.4th 1350, 1356 (Fed. Cir. 2024). Claims that do no more than apply established methods of machine learning to a new data environment are not patent eligible. Recentive Analytics, Inc. v. Fox Corp., Fox Broadcasting Company, LLC, Fox Sports Productions, LLC, Case No. 23-2437, (Fed. Cir. 2025), pp. 10, 14. An abstract idea does not become nonabstract by limiting the invention to a particular field of use or technological environment. Id.
Regarding the additional limitations of the performing the one or more automated actions including automatically generating, based at least in part on the predicting of at least one of mental distress among the given dyad and social rhythm disruption among the given dyad, at least one control signal for controlling at least portions of one or more external physical robot-mediated interaction systems in connection with responding to the at least one of the predicted mental distress among the given dyad and the predicted social rhythm disruption among the given dyad, the Examiner asserts that these limitations amount to merely reciting the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished (see MPEP § 2106.05(f)) and doing no more than generally linking use of the abstract idea to a particular technological environment or field of use without adding an inventive concept to the abstract idea (see MPEP § 2106.05(h)).
Thus, taken alone, the additional elements do not integrate the at least one abstract idea into a practical application. Furthermore, looking at the additional limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. MPEP §2106.05(I)(A) and §2106.04(II)(A)(2).
For these reasons, representative independent claim 18 and analogous independent claims 1 and 14 do not recite additional elements that integrate the judicial exception into a practical application. Accordingly, representative independent claim 18 and analogous independent claims 1 and 14 are directed to at least one abstract idea.
The remaining dependent claim limitations not addressed above fail to integrate the abstract idea into a practical application as set forth below:
-Claims 2, 15, and 19 recite how the determination of the data-based representations uses one or more AI-based representation learning techniques which amounts to merely reciting the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished (see MPEP § 2106.05(f)). Claims that do no more than apply established methods of machine learning to a new data environment are not patent eligible. Recentive Analytics, Inc. v. Fox Corp., Fox Broadcasting Company, LLC, Fox Sports Productions, LLC, Case No. 23-2437, (Fed. Cir. 2025), pp. 10, 14. An abstract idea does not become nonabstract by limiting the invention to a particular field of use or technological environment. Id.
-Claims 3, 16, and 20 recite how the predicting uses one or more multivariate time series modeling techniques with one or more probabilistic transformers which does no more than generally link use of the abstract idea to a particular technological environment or field of use without adding an inventive concept to the abstract idea (see MPEP § 2106.05(h)) and also amounts to merely reciting the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished (see MPEP § 2106.05(f)).
-Claims 4, 17, and 21 recite how performing one or more automated actions includes automatically initiating one or more avatar-mediated interactions within at least a portion of the given dyad which does no more than generally link use of the abstract idea to a particular technological environment or field of use without adding an inventive concept to the abstract idea (see MPEP § 2106.05(h)) and also amounts to merely reciting the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished (see MPEP § 2106.05(f)).
-Claim 9 recites how performing one or more automated actions includes automatically training at least a portion of the one or more artificial intelligence techniques using feedback related to the predicting of at least one of mental distress among the given dyad and social rhythm disruption among the given dyad amounts to merely reciting the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished (see MPEP § 2106.05(f)). Requirements that the machine learning model be “iteratively trained” or dynamically adjusted do not represent a technological improvement because iterative training using selected training material and dynamic adjustments based on real-time changes are incident to the very nature of machine learning. Recentive Analytics, Inc. v. Fox Corp., Fox Broadcasting Company, LLC, Fox Sports Productions, LLC, Case No. 23-2437, (Fed. Cir. 2025), p. 12.
-Claim 10 recites how performing one or more automated actions includes generating and outputting, using one or more user interfaces, one or more visualizations pertaining to the predicting of at least one of mental distress among the given dyad and social rhythm disruption among the given dyad which amounts to merely using a computer or other machinery as tools performing their typical functionality in conjunction with performing the above-noted at least one abstract idea (see MPEP § 2106.05(f)).
-Claim 13 recites how software implementing the method is provided as a service in a cloud environment which amounts to merely using a computer or other machinery as tools performing their typical functionality in conjunction with performing the above-noted at least one abstract idea (see MPEP § 2106.05(f)).
When the above additional limitations are considered as a whole along with the limitations directed to the at least one abstract idea, the at least one abstract idea is not integrated into a practical application. Therefore, the claims are directed to at least one abstract idea.
Subject Matter Eligibility Criteria - Alice/Mayo Test: Step 2B:
Regarding Step 2B of the Alice/Mayo test, representative independent claim 18 does not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for reasons the same as those discussed above with respect to determining that the claim does not integrate the abstract idea into a practical application.
Regarding the additional limitations of the system including memory including instructions, processor configured to execute the instructions, and "automated" actions, the Examiner submits that these limitations amount to merely using a computer or other machinery as tools performing their typical functionality in conjunction with performing the above-noted at least one abstract idea (see MPEP § 2106.05(f)).
Regarding the additional limitations of the prediction using "one or more artificial intelligence techniques," the Examiner submits that these limitations amount to merely reciting the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished which is equivalent to the words “apply it” (see MPEP § 2106.05(f)). Claims drafted using largely (if not entirely) result-focused functional language, containing no specificity about how the purported invention achieves those results, are almost always found to be ineligible for patenting under Section 101.” Beteiro, LLC v. DraftKings Inc., 104 F.4th 1350, 1356 (Fed. Cir. 2024). Claims that do no more than apply established methods of machine learning to a new data environment are not patent eligible. Recentive Analytics, Inc. v. Fox Corp., Fox Broadcasting Company, LLC, Fox Sports Productions, LLC, Case No. 23-2437, (Fed. Cir. 2025), pp. 10, 14. An abstract idea does not become nonabstract by limiting the invention to a particular field of use or technological environment. Id.
Regarding the additional limitations of the performing the one or more automated actions including automatically generating, based at least in part on the predicting of at least one of mental distress among the given dyad and social rhythm disruption among the given dyad, at least one control signal for controlling at least portions of one or more external physical robot-mediated interaction systems in connection with responding to the at least one of the predicted mental distress among the given dyad and the predicted social rhythm disruption among the given dyad, the Examiner asserts that these limitations amount to merely reciting the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished (see MPEP § 2106.05(f)) and doing no more than generally linking use of the abstract idea to a particular technological environment or field of use without adding an inventive concept to the abstract idea (see MPEP § 2106.05(h)).
The dependent claims also do not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for the same reasons to those discussed above with respect to determining that the dependent claims do not integrate the at least one abstract idea into a practical application.
-Claims 2, 15, and 19 recite how the determination of the data-based representations uses one or more AI-based representation learning techniques which amounts to merely reciting the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished (see MPEP § 2106.05(f)). Claims that do no more than apply established methods of machine learning to a new data environment are not patent eligible. Recentive Analytics, Inc. v. Fox Corp., Fox Broadcasting Company, LLC, Fox Sports Productions, LLC, Case No. 23-2437, (Fed. Cir. 2025), pp. 10, 14. An abstract idea does not become nonabstract by limiting the invention to a particular field of use or technological environment. Id.
-Claims 3, 16, and 20 recite how the predicting uses one or more multivariate time series modeling techniques with one or more probabilistic transformers which does no more than generally link use of the abstract idea to a particular technological environment or field of use without adding an inventive concept to the abstract idea (see MPEP § 2106.05(h)) and also amounts to merely reciting the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished (see MPEP § 2106.05(f)).
-Claims 4, 17, and 21 recite how performing one or more automated actions includes automatically initiating one or more avatar-mediated interactions within at least a portion of the given dyad which does no more than generally link use of the abstract idea to a particular technological environment or field of use without adding an inventive concept to the abstract idea (see MPEP § 2106.05(h)) and also amounts to merely reciting the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished (see MPEP § 2106.05(f)).
-Claim 5 recites how performing one or more automated actions includes automatically initiating one or more robot-mediated interactions within at least a portion of the given dyad which does no more than generally link use of the abstract idea to a particular technological environment or field of use without adding an inventive concept to the abstract idea (see MPEP § 2106.05(h)) and also amounts to merely reciting the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished (see MPEP § 2106.05(f)).
-Claim 9 recites how performing one or more automated actions includes automatically training at least a portion of the one or more artificial intelligence techniques using feedback related to the predicting of at least one of mental distress among the given dyad and social rhythm disruption among the given dyad amounts to merely reciting the idea of a solution or outcome without reciting details of how a solution to a problem is accomplished (see MPEP § 2106.05(f)). Requirements that the machine learning model be “iteratively trained” or dynamically adjusted do not represent a technological improvement because iterative training using selected training material and dynamic adjustments based on real-time changes are incident to the very nature of machine learning. Recentive Analytics, Inc. v. Fox Corp., Fox Broadcasting Company, LLC, Fox Sports Productions, LLC, Case No. 23-2437, (Fed. Cir. 2025), p. 12.
-Claim 10 recites how performing one or more automated actions includes generating and outputting, using one or more user interfaces, one or more visualizations pertaining to the predicting of at least one of mental distress among the given dyad and social rhythm disruption among the given dyad which amounts to merely using a computer or other machinery as tools performing their typical functionality in conjunction with performing the above-noted at least one abstract idea (see MPEP § 2106.05(f)).
-Claim 13 recites how software implementing the method is provided as a service in a cloud environment which amounts to merely using a computer or other machinery as tools performing their typical functionality in conjunction with performing the above-noted at least one abstract idea (see MPEP § 2106.05(f)).
Therefore, claims 1-4 and 6-21 are ineligible under 35 USC §101.
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, 7-9, 11-14, and 18 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent App. Pub. No. 2020/0320335 to Shamun et al. ("Shamun") in view of U.S. Patent App. Pub. No. 2020/0110890 to Woo et al. ("Woo"):
Regarding claim 1, Shamun discloses a computer-implemented method comprising:
obtaining biomarker data derived from a set of one or more dyads, each dyad comprising at least one patient and at least one caregiver associated with the at least one patient (Figure 1C, [0156]-[0158] illustrate/disclose obtaining physiological data (biomarker data) from a user while [0296] discloses collecting physiological data from both a patient and therapist/caregiver (dyad));
determining, based at least in part on processing at least a portion of the obtained biomarker data, one or more data-based representations of at least one of mental distress among at least one of the one or more dyads and social rhythm disruption among at least one of the one or more dyads (steps 130, 150 in Figure 1C and [0159]-[0161] illustrate/discuss processing the data from the sensing unit (i.e., the physiological/biomarker data) which would result in "data-based representations"; furthermore, [0004], [0100, [0101] disclose how there is a correlation between physiological response and mental/emotional/stress state of a user; accordingly, the above-noted "data-based representations" are indicative of a mental/emotional/stress state ("mental distress") of least one of the members of the dyad);
predicting at least one of mental distress among a given dyad of at least one patient and at least one caregiver associated with the at least one patient and social rhythm disruption among the given dyad by processing input biomarker data, derived from the given dyad, using one or more artificial intelligence techniques in connection with at least a portion of the one or more data-based representations (Figure 1C, [0109], [0132], [0161], [0296] illustrates/discloses how the processed data (which includes the "data-based representations" based on input biomarker/physiological data) is sent 104B to database 160 and then to prediction model 600 (which includes a neural network/ML model (AI techniques) per [0031], [0129], [0189]-[0191], [0198]) for predicting a mental/emotional/stress/anxiety state of the user/patient and the therapist/caregiver of the dyad); and
performing one or more automated actions based at least in part on the predicting step ([0242] discloses providing an alert/notification/feedback based on the predicted mental/emotional state), …;
wherein the method is carried out by at least one computing device ([0300]-[0303] discloses one or more computing devices including processor(s), memory(ies), etc.).
However, Shamun appears to be silent regarding wherein performing one or more automated actions comprises automatically generating, based at least in part on the predicting of at least one of mental distress among the given dyad and social rhythm disruption among the given dyad, at least one control signal for controlling at least portions of one or more external physical robot-mediated interaction systems in connection with responding to the at least one of the predicted mental distress among the given dyad and the predicted social rhythm disruption among the given dyad.
Nevertheless, Woo teaches ([0051], [0055], [0056] and Figure 2) that it was known in the healthcare informatics art for a user terminal 200 to obtain a user's emotional information from a bio-sensor/camera and then generate and transmit feedback/functional information (control signal) to an electronic device/robot 300 (external physical robot-mediated interaction system) that can be executed by the electronic device/robot 300 to improve the user's emotion from a negative emotion such as anger or sadness (responding to mental distress/social rhythm disruption).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention for performing the one or more automated actions of Shamun to include automatically generating, based at least in part on the predicting of at least one of mental distress among the given dyad and social rhythm disruption among the given dyad, at least one control signal for controlling at least portions of one or more external physical robot-mediated interaction systems in connection with responding to the at least one of the predicted mental distress among the given dyad and the predicted social rhythm disruption among the given dyad similar to as taught by Woo to advantageously improve the emotional state of one or more members of the dyad. A person of ordinary skill in the art would have been motivated to combine the prior art to achieve the claimed invention and there would have been a reasonable expectation of success in doing so. KSR Int'l Co. v. Teleflex Inc., 550 U.S. 398 (2007). Furthermore, all the claimed elements were known in the prior art and one skilled in the art could have combined the elements as claimed by known methods with no change in their respective functions, and the combination yielded nothing more than predictable results to one of ordinary skill in the art. Id.
Regarding claim 7, the Shamun/Woo combination discloses the computer-implemented method of claim 1, further including wherein predicting comprises processing input biomarker data, derived from the given dyad, using one or more trajectory modeling techniques in connection with the at least a portion of the one or more data-based representations ([0227]-[0228] of Shamun discusses how after a certain period of time in which physiological data of a user was gathered, the user may be associated with an existing prediction model associated with a particular cluster of users based on similarities in physiological data while [0136]-[0139] of Shamun discusses how each cluster of users having similarities in physiological patterns (trajectories) can be associated with a different respective predictive model; accordingly, associating the user (e.g., the user of the dyad of [0296] of Shamun) with a model of a particular cluster to generate a corresponding prediction (based on the "data-based representations as discussed in relation to claim 1) amounts to using one or more "trajectory modeling techniques").
Regarding claim 8, the Shamun/Woo combination discloses the computer-implemented method of claim 1, further including wherein predicting comprises predicting one or more temporal state transitions associated with at least one of mental distress among the given dyad and social rhythm disruption among the given dyad (Figure 10 and [0297] of Shamun illustrates/discloses predicting state transitions of relaxation/stress over various states (temporal state transitions)).
Regarding claim 9, the Shamun/Woo combination discloses the computer-implemented method of claim 1, further including wherein performing one or more automated actions comprises automatically training at least a portion of the one or more artificial intelligence techniques using feedback related to the predicting of at least one of mental distress among the given dyad and social rhythm disruption among the given dyad ([0134], [140], [0173]-[0174], [205] of Shamun discuss receiving feedback from users regarding predicted emotional states and training/retraining the prediction model based on the same).
Regarding claim 11, the Shamun/Woo combination discloses the computer-implemented method of claim 1, further including wherein obtaining biomarker data comprises obtaining biomarker data from the set of one or more dyads, wherein at least a portion of each dyad comprises at least one isolation-related context ([0295]-[0296] of Shamun discloses obtaining physiological data (biomarker data) from the patient and therapist/caregiver (dyad) during a psychotherapeutic session which is interpreted to be an "isolation-related context" as one of ordinary skill in the art would understand a psychotherapeutic session to be closed/isolated relative to the public).
Regarding claim 12, the Shamun/Woo combination discloses the computer-implemented method of claim 1, further including wherein processing input biomarker data comprises processing input biomarker data derived from the given dyad, and wherein at least a portion of the given dyad comprises at least one isolation-related context ([0295]-[0296] of Shamun discloses obtaining and processing physiological data (biomarker data) from the patient and therapist/caregiver (dyad) during a psychotherapeutic session which is interpreted to be an "isolation-related context" as one of ordinary skill in the art would understand a psychotherapeutic session to be closed/isolated relative to the public).
Regarding claim 13, the Shamun/Woo combination discloses the computer-implemented method of claim 1, further including wherein software implementing the method is provided as a service in a cloud environment ([0163], [0232] of Shamun disclose how many of the functionalities can be provided in cloud-based components which would necessarily involve services provided by software).
Regarding claim 14, Shamun discloses a computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a computing device ([0300]-[0303] of Shamun discloses one or more computing devices including a non-transitory computer-readable storage medium/memory with instructions, processor(s), etc.).
The remaining limitations of claim 14 are disclosed by the Shamun/Woo combination as discussed above in relation to claim
Claim 18 is rejected in view of the Shamun/Woo combination as discussed above in relation to claim 14.
Claims 2, 15, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent App. Pub. No. 2020/0320335 to Shamun et al. ("Shamun") in view of U.S. Patent App. Pub. No. 2020/0110890 to Woo et al. ("Woo"), and further in view of U.S. Patent App. Pub. No. 2025/0266162 to Rafikov et al. ("Rafikov"):
Regarding claim 2, the Shamun/Woo combination discloses the computer-implemented method of claim 1, but appears to be silent regarding wherein determining the one or more data-based representations comprises performing phenotypic characterization by processing the at least a portion of the obtained biomarker data using one or more artificial intelligence-based representation learning techniques.
Nevertheless, Rafikov teaches ([0005], [0009], [0026]) that it was known in the healthcare informatics art to sub-phenotype a disease of a patient based on a biomarker panel using ML and DL algorithms to advantageously facilitate prediction of disease risk scores for the patient and evaluation of therapy effectiveness ([0007]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention for determining the one or more data-based representations in the system of Shamun to include performing phenotypic characterization by processing the at least a portion of the obtained biomarker data using one or more artificial intelligence-based representation learning techniques as taught by Rafikov to advantageously facilitate prediction of disease risk scores for the patient and evaluation of therapy effectiveness. A person of ordinary skill in the art would have been motivated to combine the prior art to achieve the claimed invention and there would have been a reasonable expectation of success in doing so. KSR Int'l Co. v. Teleflex Inc., 550 U.S. 398 (2007). Furthermore, all the claimed elements were known in the prior art and one skilled in the art could have combined the elements as claimed by known methods with no change in their respective functions, and the combination yielded nothing more than predictable results to one of ordinary skill in the art. Id.
Claims 15 and 19 are rejected in view of the Shamun/Woo/Rafikov combination as discussed above in relation to claim 2
Claims 3, 16, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent App. Pub. No. 2020/0320335 to Shamun et al. ("Shamun") in view of U.S. Patent App. Pub. No. 2020/0110890 to Woo et al. ("Woo"), and further in view of U.S. Patent App. Pub. No. 2022/0392637 to Kollada et al. ("Kollada"):
Regarding claim 3, the Shamun/Woo combination discloses the computer-implemented method of claim 1, further including wherein the obtained biomarker data and therefore the above-noted data-based representations are "multivariate time series data" because there are various types of biomarkers ([0157] of Shamun) which are obtained over time and timestamped ([0058], [0178], [0182] of Shamun) for use in predicting the mental/emotional state of the user over time using ML ([0132], [0146], Figure 10 of Shamun).
However, the Shamun/Woo combination appears to be silent regarding wherein predicting comprises processing input biomarker data, derived from the given dyad, using one or more multivariate time series modeling techniques with one or more probabilistic transformers, in connection with the at least a portion of the one or more data-based representations.
Nevertheless, Kollada teaches ([0011], [0053]-[0055]) that it was known in the healthcare informatics art to process dynamic data representations from at least two types of sensors over time (multivariate time series data) using an ML model to generate mental health conditions predictions of a user, where the ML model utilizes a transformer encoder implementing a multi-head attention mechanism to learn the multimodal representation for mental health classification ([0065], [0118]-[0121], [0137]) across a quantitative severity scale ([0051], [0187], such that the transformer encoder is a "probabilistic transformer" because an output severity scale is a probability of the mental health disorder being severe). Use of such a transformer advantageously integrates information across modalities within a temporal context through dynamic embeddings to form a multimodal sequence (multivariate time series modeling techniques) that is efficiently processed resulting in improved classification performance. This is very advantageous for diagnosing mental health disorders, because they are exhibited as a complex constellation of symptoms, that are not captured by systems that process modality by modality or by approaches that do not obtain and/or maintain the temporal information ([0047]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention for the predicting to include processing input biomarker data, derived from the given dyad, using one or more multivariate time series modeling techniques with one or more probabilistic transformers, in connection with the at least a portion of the one or more data-based representations in the system of the Shamun/Woo combination as taught by Kollada to advantageously integrate information across modalities within a temporal context through dynamic embeddings to form a multimodal sequence (multivariate time series modeling techniques) that is efficiently processed resulting in improved classification performance. This is very advantageous for diagnosing mental health disorders, because they are exhibited as a complex constellation of symptoms, that are not captured by systems that process modality by modality or by approaches that do not obtain and/or maintain the temporal information. A person of ordinary skill in the art would have been motivated to combine the prior art to achieve the claimed invention and there would have been a reasonable expectation of success in doing so. KSR Int'l Co. v. Teleflex Inc., 550 U.S. 398 (2007). Furthermore, all the claimed elements were known in the prior art and one skilled in the art could have combined the elements as claimed by known methods with no change in their respective functions, and the combination yielded nothing more than predictable results to one of ordinary skill in the art. Id.
Claims 16 and 20 are rejected in view of the Shamun/Woo/Kollada combination as discussed above in relation to claim 3.
Claim 4, 10, 17, and 21 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent App. Pub. No. 2020/0320335 to Shamun et al. ("Shamun") in view of U.S. Patent App. Pub. No. 2020/0110890 to Woo et al. ("Woo"), and further in view of U.S. Patent App. Pub. No. 2019/0038180 to Tzvieli et al. ("Tzvieli"):
Regarding claim 4, the Shamun/Woo combination discloses the computer-implemented method of claim 1, but appears to be silent regarding wherein performing one or more automated actions comprises automatically initiating, based at least in part on the predicting of at least one of mental distress among the given dyad and social rhythm disruption among the given dyad, one or more avatar-mediated interactions within at least a portion of the given dyad.
Nevertheless, Tzvieli teaches ([0107]) that it was known in the healthcare informatics art to process thermal (physiological) data of a user with an ML model to predict a physiological response of the user including stress ([0096]) and utilize a virtual robot ([0167] and Figure 30) to urge the user to increase the ratio between the duration of the user's exhales and inhales ("avatar-mediated interactions" with the user) in order to alleviate the stress that builds up.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention for the performing one or more automated actions to include automatically initiating, based at least in part on the predicting of at least one of mental distress among the given dyad and social rhythm disruption among the given dyad, one or more avatar-mediated interactions within at least a portion of the given dyad in the system of the Shamun/Woo combination similar to as taught by Tzvieli to advantageously alleviate stress that builds up in the user. A person of ordinary skill in the art would have been motivated to combine the prior art to achieve the claimed invention and there would have been a reasonable expectation of success in doing so. KSR Int'l Co. v. Teleflex Inc., 550 U.S. 398 (2007). Furthermore, all the claimed elements were known in the prior art and one skilled in the art could have combined the elements as claimed by known methods with no change in their respective functions, and the combination yielded nothing more than predictable results to one of ordinary skill in the art. Id.
Regarding claim 10, the Shamun/Woo combination discloses the computer-implemented method of claim 1, but appears to be silent regarding wherein performing one or more automated actions comprises generating and outputting, using one or more user interfaces, one or more visualizations pertaining to the predicting of at least one of mental distress among the given dyad and social rhythm disruption among the given dyad.
Nevertheless, Tzvieli teaches ([0107]) that it was known in the healthcare informatics art to process thermal (physiological) data of a user with an ML model to predict a physiological response of the user including stress ([0096]) and generate and output an alert to a user interface (a visualization) ([0067], [0456] and Figure 47) notifying a user when the stress level reaches a predetermined threshold and encouraging the user to avoid stress-inducing behavior to make the user aware of the stress thereby allowing the user to take actions to improve the user's stress level.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention for the performing one or more automated actions to include generating and outputting, using one or more user interfaces, one or more visualizations pertaining to the predicting of at least one of mental distress among the given dyad and social rhythm disruption among the given dyad in the system of the Shamun/Woo combination similar to as taught by Tzvieli to make the user aware of the stress thereby allowing the user to take actions to improve the user's stress level. A person of ordinary skill in the art would have been motivated to combine the prior art to achieve the claimed invention and there would have been a reasonable expectation of success in doing so. KSR Int'l Co. v. Teleflex Inc., 550 U.S. 398 (2007). Furthermore, all the claimed elements were known in the prior art and one skilled in the art could have combined the elements as claimed by known methods with no change in their respective functions, and the combination yielded nothing more than predictable results to one of ordinary skill in the art. Id.
Claims 17 and 21 are rejected in view of the Shamun/Woo/Tzvieli combination as discussed above in relation to claim 4.
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent App. Pub. No. 2020/0320335 to Shamun et al. ("Shamun") in view of U.S. Patent App. Pub. No. 2020/0110890 to Woo et al. ("Woo"), and further in view of U.S. Patent App. Pub. No. 2020/0126670 to Bender et al. ("Bender"):
Regarding claim 6, the Shamun/Woo combination discloses the computer-implemented method of claim 1, but appears to be silent regarding wherein performing one or more automated actions comprises automatically initiating, based at least in part on the predicting of at least one of mental distress among the given dyad and social rhythm disruption among the given dyad, one or more human-mediated interactions within at least a portion of the given dyad.
Nevertheless, Bender teaches ([0048]) that it was known in the healthcare informatics art to utilize an ML process to predict a user's/care recipient's stress level and send text/voice-based prompt feedback to a caregiver and/or the care recipient ([0083]) to initiate activity to change a current location (initiate human-mediated interaction) to advantageously improve the health and welfare of the recipient ([0107])
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention for the performing one or more automated actions to include automatically initiating, based at least in part on the predicting of at least one of mental distress among the given dyad and social rhythm disruption among the given dyad, one or more human-mediated interactions within at least a portion of the given dyad in the system of the Shamun/Woo combination similar to as taught by Bender to advantageously improve the health and welfare of the recipient/user. A person of ordinary skill in the art would have been motivated to combine the prior art to achieve the claimed invention and there would have been a reasonable expectation of success in doing so. KSR Int'l Co. v. Teleflex Inc., 550 U.S. 398 (2007). Furthermore, all the claimed elements were known in the prior art and one skilled in the art could have combined the elements as claimed by known methods with no change in their respective functions, and the combination yielded nothing more than predictable results to one of ordinary skill in the art. Id.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/JONATHON A. SZUMNY/Primary Examiner, Art Unit 3686