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 1-7, 9-12, 14, 16-18, & 21-25 were previously pending in this application. The amendment filed 22 April 2026 has been entered and the following has occurred: Claims 1-3, 5-7, 9-12, 14, 16-18, 21, 22, 24, & 25 have been amended. No claims have been added or cancelled.
Claims 1-7, 9-12, 14, 16-18, & 21-25 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 1-7, 9-12, 14, 16-18, & 21-25 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 1-7, 9-12, 14, 16, & 21-24) and a machine (claims 17-18 & 25) which recite steps of (Subject Matter Eligibility (SME) Test Step 1: Yes):
receiving peripheral navigational input data from a user interacting with the non-wearable computing device from at least one peripheral input navigation device, the peripheral navigational input data being generated by the at least one peripheral input navigation device when the suer interacts with the non-wearable computing device
executing, locally on the non-wearable computing device and without reliance on wearable sensor data, a machine learning architecture that
receives the peripheral navigational input data and one or more of environmental data and contextual data associated with the user; and
processes the peripheral navigational input data and the one or more of environmental data and the contextual data associated with the user to identify potential stress indicator data representing inferred physiological and behavioral signals of the user;
extracting from the potential stress indicator data a metric corresponding to at least one of physiological and behavioral features so as to passively infer physiological and behavioral signals of the user while the user interacts with the computing device;
generate, based on the generated metric, an estimated stress state of the user;
modifies, by the non-wearable computing device, a workspace of a graphical user interface to include a wellness widget that presents the one or more stress interventions in conjunction with the suite of productivity tools;
receiving user feedback via the wellness widget as additions to the potential stress indicator data;
personalizing the machine learning architecture based on the received user feedback and the potential stress indicator data to improve stress estimation accuracy and intervention strategies.
These steps of receiving/extracting potential stress indicator data from the user interacting with a peripheral input navigation device, estimating, based on the potential stress indicator data, the stress level of the user, receiving used feedback, and personalizing an algorithm based on said user feedback, potential stress indicator data, etc., as drafted, under the broadest reasonable interpretation, includes methods of organizing human activity MPEP 2106.04(a)(2)(II) describes certain Methods of Organizing Human Activity relating to managing personal behavior and/or relationships or interactions between people. For instance, the instant set of Claims recite limitations relating to receiving and organizing human data in the form of potential stress indicator data and peripheral input navigation device interaction data, receiving raw input from a peripheral input device that is non-physiological input produced to navigate a suite of productivity software analyzing said data, processing said raw input to determine/estimate stress levels of a user and/or whether a stress mitigation intervention should be presented, presenting said intervention to the user on a user interface if the system determines the intervention needs to be presented, further providing feedback to the system by the user regarding efficacy of the intervention, and tailoring future interventions based on said feedback. Therefore, the instant set of claims recite limitations relating to managing personal behavior of the user, in the form of managing the user’s interaction with productivity software and/or interaction with a wellness widget/GUI, via the user’s input data captured at a peripheral input navigation device and based on the system’s perceived stress levels assigned to the user. That is, under broadest reasonable interpretation, the user’s typical behavior, i.e. interaction with a computer, associated peripheral input navigation device(s) and productivity software, is essentially being managed by the system based on the user/human’s activity data. These aspects fall within the “Methods of Organizing Human Activity” grouping of abstract ideas in the form of managing personal behavior. Accordingly, the claims recite an abstract idea.
Dependent claims recite additional subject matter which further narrows or defines the abstract idea embodied in the claims (such as claims 2-7, 9-11, 14, 16, 18, & 21-25, reciting particular aspects of how perceiving stress levels/indicators of a user or determining optimal content/intervention for said user, and delivering said content/intervention may be performed but for recitation of generic computer components) (SME Test Step 2A, Prong 1: Yes).
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 computing device (i.e. non-wearable computer device), a graphical user interface (GUI), a workspace, a widget, machine learning architecture, & peripheral input navigation device amounts to invoking computers as a tool to perform the abstract idea, see Applicant’s specification [0067], [0068], [0053], [0053]-[0054], [0027], & [0030], respectively, see MPEP 2106.05(f));
add insignificant extra-solution activity to the abstract idea (such as receiving peripheral navigational input data, receiving peripheral navigational input data and one or more of environmental data and contextual data comprising one or more of environmental and contextual data and/or peripheral interaction input navigation data, receiving raw input data, i.e. non-physiological input, that is produced to navigate a suite of productivity software running on the computing device, selecting a baseline stress level of a user, receiving an indication that mitigation of the stress level of the user is recommended, receiving user feedback and providing said feedback to machine learning architecture, receiving peripheral interaction input data amounts to mere data gathering; recitation of processing the raw input to extract physiological and behavioral features for estimating the stress level of the user based on the inferred metrics and estimating the stress level of the user, based on the inferred metric, processing the peripheral navigational input data and the one or more of environmental data and the contextual data associated with the user to identify potential stress indicator data representing inferred physiological and behavioral signals of the user amounts to selecting a particular data source or type of data to be manipulated; recitation of facilitating navigation through a suite of productivity tools in a workspace that is modifiable, and modifying a workspace to include a wellness widget that provides one or more stress interventions on the productivity tools generating peripheral interaction input data from the user interacting with at least one peripheral input navigation device, personalizing the machine learning architecture based on the received user feedback and the potential stress indicator data to improve stress estimation accuracy and intervention strategies, processing the peripheral navigational input data and the one or more of environmental data and the contextual data associated with the user to identify potential stress indicator data representing inferred physiological and behavioral signals of the user 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 stress mitigation intervention and/or user feedback regarding said intervention being presented via a graphical user interface/wellness widget, 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 2-7, 9-11, 14, 16, 18, & 21-25, which recite limitations relating to a personal computer, machine learning stress mitigation architecture, a stress predictor/estimator/intervention model, a GUI, a workspace, a widget, a computer application/underlying application, a computing device, additional limitations which amount to invoking computers as a tool to perform the abstract idea, see applicant’s specification [0076], [0077], [0077], [0053], [0053]-[0054], [0077], & [0067], respectively, see MPEP 2106.05(f)); claims 2-6, 11, 14, 18, 21, & 23 which recite limitations relating to receiving potential stress indicator associated with at least one input device, the input device data including pointer activity, mouse activity, keyboard activity, personal information activity, the environmental data comprising physiological and behavioral activity of the user, identifying and aggregating actual stress indicator data, aggregating the future stress level of the user, provide indication of an actual stress level of the user, providing the one or more stress mitigation interventions, providing one or more widgets/workspaces, receiving user feedback captured via the wellness widget, storing user interaction and stress indicator data, additional limitations which add insignificant extra-solution activity to the abstract idea which amounts to mere data gathering, claims 2, 5-7, 9-10, 14, 16, 18, & 21-22, which recite limitations relating to presenting one or more stress mitigation interventions, estimating the stress level of the user based on received data, predicting the future stress level of the user based on received data, determining a sentiment of stress indicator data, calibrating the stress estimator model, determining one or more of an efficacy of the intervention on the user’s stress level, varying the complexity an type of the stress mitigation intervention based on efficacy, refining the inferred metric to contextualize the estimated stress level based on historical stress levels of the user and task context to facilitate adaptive functionality of the suite of productivity software based on the estimated stress level, 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 5-6, 9-11, 14, 18, 24-25, which recite limitations relating to a stress predictor/estimator/intervention model modifying the workspace to include a widget, e.g. wellness widget, and/or outputting varying data, interventions, and/or graphs on an interface means 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 (SME Test Step 2A, Prong 2: No).
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 receiving peripheral navigational input data, receiving peripheral navigational input data and one or more of environmental data and contextual data comprising one or more of environmental and contextual data and/or peripheral interaction input navigation data, receiving raw input data, i.e. non-physiological input, that is produced to navigate a suite of productivity software running on the computing device, selecting a baseline stress level of a user, receiving an indication that mitigation of the stress level of the user is recommended, receiving user feedback and providing said feedback to machine learning architecture, receiving peripheral interaction input data, e.g., receiving or transmitting data over a network, Symantec, MPEP 2106.05(d)(II)(i); processing the raw input to extract physiological and behavioral features for estimating the stress level of the user based on the inferred metrics and performing an evaluation of whether to mitigate the stress level of the user, estimating the stress level of the user, based on the extracted metric, applying closed-loop machine learning efforts for performing said calculations, modifying a workspace to include a wellness widget that provides one or more stress interventions on the productivity tools generating peripheral interaction input data from the user interacting with at least one peripheral input navigation device, personalizing the machine learning architecture based on the received user feedback and the potential stress indicator data to improve stress estimation accuracy and intervention strategies, processing the peripheral navigational input data and the one or more of environmental data and the contextual data associated with the user to identify potential stress indicator data representing inferred physiological and behavioral signals of the user, e.g., performing repetitive calculations, Flook, MPEP 2106.05(d)(II)(ii); storing the various collected user data, storing computerized instructions for performing the steps recited, storing instructions for producing an interface/display/content on a workspace/screen, storing instructions for producing an application and/or wellness widget, e.g., storing and retrieving information in memory, Versata Dev. Group, MPEP 2106.05(d)(II)(iv); collecting/observing data associated with a user as it relates to interaction with a remote mobile device, including user feedback based on user input to a GUI, i.e. pointer data/mouse data, facilitating navigation through a suite of productivity tools in a workspace that is modifiable to include a wellness widget to provide one or more stress interventions which under BRI includes a user interacting with a GUI for performing the stress intervention via button mechanisms, etc., e.g., a web browser’s back and forward button functionality, Internet Patent Corp., MPEP 2106.05(d)(II)(ii); receiving peripheral interaction input data generated by the user for interacting with the at least one peripheral input navigation device and modifying learning algorithm, see Horseman et al. (U.S. Patent Publication No. 2019/0090816) Par [0163] describing it to be traditional, i.e. WURC, to collect data reflecting user navigation device activity/behavior for aspects of monitoring stress of the user and modifying learning algorithms);
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 2-7, 9-11, 14, 16, 18, & 21-25 additional limitations which amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields, claims 2-6, 11, 14, 18, & 21, which recite limitations relating to a mobile operating environment such as receiving potential stress indicator associated with at least one input device, the input device data including pointer activity, mouse activity, keyboard activity, personal information activity, the environmental data comprising physiological and behavioral activity of the user, identifying and aggregating actual stress indicator data, aggregating the future stress level of the user, provide indication of an actual stress level of the user, providing the one or more stress mitigation interventions, providing one or more widgets/workspaces, capturing user feedback via the wellness widget, e.g., receiving or transmitting data over a network, Symantec, MPEP 2106.05(d)(II)(i); claims 2, 5-7, 9-10, 14, 16, 18, 21-22, which recite limitations relating to presenting one or more stress mitigation interventions, estimating the stress level of the user based on received data, predicting the future stress level of the user based on received data, determining a sentiment of stress indicator data, calibrating the stress estimator model, determining one or more of an efficacy of the intervention on the user’s stress level, varying the complexity an type of the stress mitigation intervention based on efficacy, refining the inferred metric to contextualize the estimated stress level based on historical stress levels of the user and task context to facilitate adaptive functionality of the suite of productivity software based on the estimated stress level, refining the machine learning architecture based on user feedback and after completion of the one or more stress mitigation interventions, e.g., performing repetitive calculations, Flook, MPEP 2106.05(d)(II)(ii); claims 2-7, 9-11, 14, 16, 18, & 23, which recite limitations relating to storing instructions for performing the steps recited, storing various received/aggregated data, storing stress mitigation content, storing instructions for populating a user interface, such as with a workspace/widget, storing user interaction and stress indicator data in local memory, etc. e.g., storing and retrieving information in memory, Versata Dev. Group, MPEP 2106.05(d)(II)(iv); claims 2-6, 11, 14, 18, 24-25, which recite limitations relating to input device data including pointer activity, mouse activity, keyboard activity, personal information activity, the environmental data comprising physiological and behavioral activity of the user, such as in a computerized interface, providing one or more GUI’s/widgets/workspaces for interaction by the user, outputting varying data, interventions, and/or graphs on an interface means, e.g., a web browser’s back and forward button functionality, Internet Patent Corp., MPEP 2106.05(d)(II)(ii); claim 21 reciting limitations relating to receiving peripheral interaction input data generated by the user for interacting with the at least one peripheral input navigation device, see Horseman et al. (U.S. Patent Publication No. 2019/0090816) Par [0163] describing it to be traditional, i.e. WURC, to collect data reflecting user navigation device activity/behavior for aspects of monitoring stress of the user). 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 (SME Test Step 2B: No).
Response to Arguments
Applicant's arguments filed 22 April 2026 have been fully considered but they are not persuasive:
Regarding 35 U.S.C. 101 rejections of claims 1-7, 9-12, 14, 16-18, & 21-25, Applicant argues on p. 13-16 of Arguments/Remarks that any alleged abstract idea is integrated into a practical application. More specifically, Applicant argues that the claims are directed towards a specific, technical mechanism for non-wearable physiological inference and interface reconfiguration, rather than abstract stress management implemented on generic hardware. Examiner respectfully disagrees with Applicant’s arguments. While Applicant argues that the claims are directed towards a specific, technical mechanism for non-wearable physiological inference and interface reconfiguration. While Examiner notes the structural components and additional limitations, such as a computer, a non-wearable computing device, or other devices, such as machine learning techniques for automated performance of the steps recited. However, Examiner points to MPEP 2106.05(a)(I) which discloses that mere automation of manual processes, is not sufficient to show an improvement in computer-functionality. Furthermore, Examiner contends that these aspects of utilizing peripheral input devices and/or machine learning architecture and/or a graphical user interface read as mere efforts to “apply it”. Additionally, the purported shortcomings are not substantially described in Applicant’s Specification so as to reasonably confer to one of ordinary skill in the art before the effective filing date of the claimed invention that the claims are indeed solving said shortcoming. Furthermore, the inventive concept of the instantly-claimed system is directed towards mitigating stress of a user that is making use of productivity tools on a computer. The inventive concept is not directed towards improved computing environments and/or making more convenient aspects of computing environments regarding physiological sensors and/or an improved learning algorithm, but rather the mere application of said components. While these computing devices may be employed to accomplish said inventive concept of detecting and mitigating stress of a user that is making use of productivity tools on a computer, this wholly differs from the disclosure being directed towards improvements of said computing devices regarding “the constrained context of standard computing environments without requiring physiological sensors”. Therefore, because the system is directed towards improvements of detecting and mitigating user stress, and optimizing determining these efforts present as an improvement to the abstraction at-hand instead of the computing devices and/or technology implementing said abstraction. According to MPEP 2106.05(a) specifically mentions that “the judicial exception alone cannot provide the improvement”. Therefore, improving said aspects of “detecting and mitigating user stress” represents improvements to the abstraction at-hand instead of improvements to the technology that applies said abstraction. As such, the claims do not recite an improvement to computer technology and/or a practical application. Therefore, claims 1-7, 9-12, 14, 16-18, & 21-25 remain rejected under 35 U.S.C. 101.
Regarding 35 U.S.C. 101 rejections of claims 1-7, 9-12, 14, 16-18, & 21-25, Applicant argues on p. 15-16 of Arguments/Remarks that Applicant’s amended claims do not recite a judicial exception under Step 2B. More specifically, Applicant argues that the steps recited define a computational transformation pipeline that enables physiological and behavioral inference from peripheral input signals in a non-wearable environment. Examiner respectfully disagrees with Applicant’s Arguments. In re Cybersource Corp. v. Retail Decisions, Inc. states that “the mere manipulation or reorganization of data, however, does not satisfy the transformation prong” and that “the "incidental use" of a computer did not allow the claim to meet the machine portion of the test”. That is, merely reciting the use of computer components as a tool for transforming data inputs into data outputs based on applied learning/computational models, is not enough to constitute an effective transformation under the machine-or-transformation test. Therefore, this computational pipeline that enables physiological and behavioral inference from peripheral input signals into outputted intervention strategies. It should be further noted that said intervention strategies are not necessarily elected or recited to be physical or practical applications of the recited abstract idea. That is, there is no effectuation or concrete effects on the back-end of the system being applied to constitute a practical application or significantly more than the recited abstract idea. Therefore, claims 1-7, 9-12, 14, 16-18, & 21-25 remain rejected under 35 U.S.C. 101.
Regarding 35 U.S.C. 101 rejections of claims 1-7, 9-12, 14, 16-18, & 21-25, Applicant argues on p. 16 of Arguments/Remarks that because independent claim 1 purportedly represents patent-eligible subject matter that independent claims 12 & 17 also represent patent-eligible subject matter by being substantially similar to independent claim 1. Examiner respectfully disagrees with Applicant’s Arguments. Independent claim 1 was determined to still represent patent-ineligible subject matter as discussed above. As such, Applicant’s arguments regarding independent claims 1 purportedly representing patent-eligible subject matter are rendered moot and independent claims 12 & 17 represent patent-ineligible subject matter. Therefore, claims 1-7, 9-12, 14, 16-18, & 21-25 remain rejected under 35 U.S.C. 101
Regarding 35 U.S.C. 101 rejections of claims 1-7, 9-12, 14, 16-18, & 21-25, Applicant argues on p. 16 of Arguments/Remarks that because independent claims 1, 12, & 17 purportedly represent patent-eligible subject matter that dependent claims 2-7, 9-11, 14, 16, 18, & 21-25 also represent patent-eligible subject matter by virtue of dependency. Examiner respectfully disagrees with Applicant’s Arguments. Independent claims 1, 12, & 17 were determined to still represent patent-ineligible subject matter as discussed above. As such, Applicant’s arguments regarding independent claims 1, 12, & 17 purportedly representing patent-eligible subject matter are rendered moot and dependent claims 2-7, 9-11, 14, 16, 18, & 21-25 do not represent patent-eligible subject matter. Therefore, claims 1-7, 9-12, 14, 16-18, & 21-25 remain rejected under 35 U.S.C. 101.
Conclusion
The prior art made of record and not relied upon is considered pertinent to Applicant's disclosure:
Giftakis et al. (U.S. Patent Publication No. 2010/0280336) discloses a system for detecting patient anxiety, particular regarding one or more anxiety events or anxiety disorders ,such that a mood state transition is detected based on patient activity information and therapy delivery is controlled based on the detection of the mood state transition, such as by using machine learning efforts;
Jain et al. (U.S. Patent Publication No. 2012/0130196) discloses a system for automatically receiving patient data, stimuli, etc., over sensors and determining patient stress, anxiety or mood.
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
/Shahid Merchant/Supervisory Patent Examiner, Art Unit 3684
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