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 1-20 were previously pending in this application. The amendment filed 10 July 2025 has been entered and the following has occurred: Claims 1-2, 9, 11-12, 14, 16-18, have been amended. Claims 21-25 have been added. Claims 8, 13, 15, & 19- 20 have been 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 potential stress indicator data from the user interacting with a computing device from at least one peripheral input navigation device, the potential stress indicator data comprising peripheral interaction input data generated by the user for interacting with the at least one peripheral input navigation device and one or more of environmental data and contextual data associated with the user, the computing device being a non-wearable computer device that is configured to
executing, locally on the computing device, a machine learning architecture that receives the potential stress indicator data; and
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;
estimating, based on the extracted metric, the stress level of the user;
performing an evaluation of whether to mitigate, via one or more stress mitigation interventions, the stress level of the user; and
presenting the one or more stress mitigation interventions to the user via a graphical user interface when the evaluation indicates that the stress level is mitigable,
facilitating, via the graphical user interface, navigation through a suite of productivity tools in a workspace;
modifying the workspace 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, performing an evaluation of whether to mitigate, via one or more stress mitigation interventions, the stress level of the user, presenting the one or more stress mitigation interventions to the user via a graphical user interface when the evaluation indicates that the stress level should be mitigated, 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 recitation of receiving stress indicator 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, 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 performing an evaluation of whether to mitigate the stress level of the user, and estimating the stress level of the user, based on the inferred metric, amounts to selecting a particular data source or type of data to be manipulated; recitation of presenting one or more stress interventions via a graphical user interface and/or facilitating navigation through a suite of productivity tools in a workspace that is modifiable 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 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 stress indicator 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, 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, 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, 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);
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 10 July 2025 have been fully considered but they are not persuasive:
Regarding 35 U.S.C. 101 rejections of claims 1-20, Applicant argues on p. 10-11 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 solution to a recognized computing problem, i.e. detecting and mitigating user stress within the constrained context of standard computing environments (e.g. personal computers running productivity tools) without requiring physiological sensors, at least by the recitation of the closed-loop technical system modifying layouts in real time to display stress interventions, and user feedback being looped back into the system to refine future outputs. Examiner respectfully disagrees with Applicant’s arguments. While Applicant argues that the claims solve the “computing problem” of . detecting and mitigating user stress within the constrained context of standard computing environments (e.g. personal computers running productivity tools) without requiring physiological sensors, Applicant’s disclosure does not necessarily support said “computer problem”. That is, this shortcoming is 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. 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, 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, currently pending 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 1-20, Applicant argues on p. 11-13 of Arguments/Remarks that Applicant’s amended claims do not recite a judicial exception under Step 2B. More specifically, Applicant argues that the features recited at the top of p. 12 of Arguments/Remarks are substantially similar to features found in Example 48 for at least 3 provided arguments found on p. 12-13 of Argument/Remarks. Examiner respectfully disagrees with Applicant’s Arguments. Regarding Applicant’s first argument that the claims do not recite mere data receipt and display, and instead require specific technical mechanisms and operations for receiving navigational input from peripheral input devices… 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”. That is, while the claims recite said technological components, these technological components merely implement the abstract idea at hand and/or are merely used as a tool to perform/accomplish the characterized abstraction of detecting and mitigating stress of a user that is making use of productivity tools on a computer with an associated interface. Furthermore, these efforts amount to merely links the use of the judicial exception to a particular technological environment of productivity tools/computer productivity software, instead of applying or using the judicial exception in some other meaningful way. Regarding Applicant’s second argument that the claims improve user experience and mental wellness support within computing environments, Examiner contends that this reads as improving said aspects of “detecting and mitigating user stress” which represents improvements to the abstraction at-hand instead of improvements to the technology that applies said abstraction. That is, the judicial exception alone cannot provide the improvement and a mere improvement to the abstraction alone does not constitute a technological improvement in view of the Alice/Mayo framework. Regarding Applicant’s third argument that the claimed GUI goes well beyond generic displays and instead constitutes a closed-loop, interactive interface responsive to inferred behavioral metrics, Examiner contends that the mere organization of data and/or receiving data, analyzing data, and reorganization or said data in a user interface, especially based on user interaction represents both insignificant, extra-solution activity and/or well-understood, routine, and/or conventional activity found in prior art systems. For instance, mere outputting of data in an interface and modifying said outputs based on user behavior represents efforts of data gathering, data manipulation, data output, and/or display content on an interface, i.e. insignificant, extra-solution activity. Furthermore, these aspects represent efforts of transmitting data/information over network means, performing repetitive calculations, outputting content in a user interface that is modified based on user data, all of which constituted well-understood, routine, and/or conventional activity found in prior art systems. While the claims may specify the type of user data received, e.g. peripheral input navigation data and/or stress indication data, the type of analysis performed, e.g. closed-loop machine learning, and/or the content being outputted on the interface, e.g. stress mitigation intervention and/or data, it is clear that a high-level, the claims amount to no more than data gathering, analysis, and/or outputting a result. As such, currently pending claims 1-7, 9-12, 14, 16-18, & 21-25 are not substantially similar to Example 48 and therefore remain rejected under 35 U.S.C. 101.
Regarding 35 U.S.C. 103 rejections of claims 1-20, Applicant argues on p. 13-20 that the claims are nonobvious over previously reasoned/cited portions of Lassoued, Horseman, and Lundin due to technical innovations over the cited references, such as GUI integration with a wellness widget providing mitigation interventions and user feedback loops in a singular interface/suite of productivity tools operated by the user. Examiner agrees with Applicant’s arguments. Therefore, the previous 35 U.S.C. 103 rejections for claims 1-20 have been withdrawn. Furthermore, after thorough search and consideration of the prior art, the claims seem to be allowable over the prior art, at least by the recited embedding of the wellness widget in combination with the stress mitigation intervention in conjunction with the suite of productivity tools in the same interface. That is, while the prior art generally discloses each portion of this embodiment individually, e.g. a stand-alone wellness widget, issuing stress mitigation interventions via a GUI, and/or observing a user’s behaviors during use of productivity tools to determine stress levels of the user, it is the combination, i.e. all things being performed “in conjunction with” the suite of productivity tools on a singular user interface that presents a novel combination over the prior art. Even further, the prior art also does not necessarily disclose personalizing machine learning architecture according to received user feedback and potential stress indicator data in the form of user peripheral input navigation device interaction data. That is, Applicant’s arguments found on p. 15-17 are found persuasive in arguing against prior art references teaching these limitations. As such, currently pending claims 1-7, 9-12, 14, 16-18, & 21-25 overcome art-based rejections. However, it should be noted that these claims remain rejected under 35 U.S.C. 101, as discussed above.
Conclusion
The prior art made of record and not relied upon is considered pertinent to Applicant's disclosure:
Horseman et al. (U.S. Patent Publication No. 2019/0090816) discloses a system for monitoring and improving health, i.e. anxiety, and productivity of employees for use in computer environments operated by said employees;
Ni et al. (U.S. Patent Publication No. 2018/0101807) discloses a system for tracking behaviors and activities over time for a user to determine stress, health, and/or productivity metrics for said user;
Boudreau et al. (U.S. Patent Publication No. 2021/0235641) discloses a system or monitoring and regulating productivity of one or more employees/workers based on various collected employee data/metrics.
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/H.R./Examiner, Art Unit 3684
/Shahid Merchant/Supervisory Patent Examiner, Art Unit 3684