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 . Claims 1-20 have been reviewed and are under consideration by this office action.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 09/03/2026 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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 1-20 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.
Step One – Claim(s) 8-14 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claims do not fall within at least one of the four categories of patent eligible subject matter because the claims are directed to ineligible signals per se. “computer-readable medium” and the Original Specification does not provide a clear, deliberate and sufficient definition to exclude ineligible signals per se (Specification, [bullet pt. 6]; “storage medium may be any tangible medium”)(. The broadest reasonable interpretation of the above mentioned features include signals per se in view of their ordinary and customary meaning. As a result, claims 8-14 are rejected under 35 US.C. 101 for being directed to signals per se. Claim 1-7 and 15-20 are directed towards statutory categories. Claims 8-14 are being considered in the alternate form as a product for purposes of further analysis.
Step 2A, Prong One – The claims are found to recite limitations that set forth the abstract idea(s), namely in independent claims recite a series of steps for the abstract idea recited below.
Regarding independent claims, (additional elements bolded)
Regarding Claims 1, 8, and 15, A computer-implemented method comprising:/ A computer program product residing on a computer readable storage medium having a plurality of instructions stored thereon which, when executed across one or more processors, causes at least a portion of the one or more processors to perform operations comprising:/ A computing system including one or more processors and one or more memories configured to perform operations comprising:
receiving, by a computing device, input data from a user participating in a simulation scenario, wherein the input data includes biometric data;
receiving input data from the simulation scenario;
determining that the biometric data of the user is indicative of suboptimal performance in at least one parameter of the simulation scenario; and
triggering an intervention event in the simulation scenario based upon, at least in part, determining that the biometric data of the user is indicative of suboptimal performance in the at least one parameter of the simulation scenario.
As drafted, this is, under its broadest reasonable interpretation, within the Abstract idea groupings of “Mental processes—concepts performed in the human mind” (observation, evaluation, judgment, opinion) as the claims are directed towards receiving biometric data, determining biometric data is indicative of suboptimal performance, and triggering an event in a simulation scenario all of which are concepts capable of being performed in the human mind (i.e. via pen and paper).
Further the claims are directed towards the abstract idea grouping of “Certain methods of organizing human activity” — commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations) and/or managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions) as the claims are directed towards receiving biometric data, determining biometric data is indicative of suboptimal performance, and triggering an event in a simulation scenario
Step 2A, Prong Two - This judicial exception is not integrated into a practical application. The independent claims utilize at least the additional elements bolded above. The additional elements are performing the steps would be no more than mere instructions to apply the exception using a generic computer component. See MPEP 2106.05(f) and/or amounts to no more than generally linking the use of the judicial exception to a particular technological environment or field of use – see MPEP 2106.05(h).
Step 2B - The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements are just “apply it” on a computer. (See MPEP 2106.05(f) – Mere Instructions to Apply an Exception – “Thus, for example, claims that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not render an abstract idea eligible.” Alice Corp., 134 S. Ct. at 235) and/or amounts to no more than generally linking the use of the judicial exception to a particular technological environment or field of use – see MPEP 2106.05(h).
Regarding Claims 2-4, 6-7, 9-11, 13-14, 16-18, and 20, the claim further narrows the abstract idea or recite additional elements previously addressed in the independent claims.
Regarding Claims 5, 12, and 19, the claims recite the additional element of triggering an agent behavior. The additional element is performing the steps would be no more than mere instructions to apply the exception using a generic computer component. See MPEP 2106.05(f) and/or amounts to no more than generally linking the use of the judicial exception to a particular technological environment or field of use – see MPEP 2106.05(h).
Accordingly, the claim fails to recite any improvements to another technology or technical field, improvements to the functioning of the computer itself, use of a particular machine, effecting a transformation or reduction of a particular article to a different state or thing, adding unconventional steps that confine the claim to a particular useful application, and/or meaningful limitations beyond generally linking the use of an abstract idea to a particular environment. See 84 Fed. Reg. 55. Viewed individually or as a whole, these additional claim element(s) do not provide meaningful limitation(s) to transform the abstract idea into a patent eligible application of the abstract idea such that the claim(s) amounts to significantly more than the abstract idea itself.
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 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 set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied 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.
Claims 1-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Al Zahrani et al. (US 20240338639 A1) (herein after referred to as “Zahr”) in view of Haluck et al. (US 20050181340 A1).
Regarding Claims 1, 8, and 15, Zahr teaches: A computer-implemented method comprising:/ A computer program product residing on a computer readable storage medium having a plurality of instructions stored thereon which, when executed across one or more processors, causes at least a portion of the one or more processors to perform operations comprising:/ A computing system including one or more processors and one or more memories configured to perform operations comprising: (Zahr, [05-06]; The method further includes applying an AI model using natural language and decision tree processing to the received input, and reporting a worker fitness assessment based on the AI model…a system includes memory to store computer executable instructions, and one or more processors, operatively coupled to the memory, that execute the computer executable instructions to implement and Zahr, [29]; n some examples, one or more portions of the system 200 can be implemented as machine readable instructions for execution on a computing platform 202 having a processor 204 and a memory 206).
receiving, by a computing device, input data from a user participating in a simulation scenario, wherein the input data includes biometric data; (Zahr, [30]; The system 200 includes an analyzer 208 that is operable to provide an assessment report 210 based on received data inputs 212. The inputs 212 may correspond to the discrete data 102 and live (real-time or wearable) data 104 described above, and the assessment report 210 may correspond to the output 105 relating to the one or more of classification of worker stress level, overall fitness of the worker and/or fitness for particular tasks, and advisories on recommended actions, warnings, or remediations also described above. The advisories can be qualifications or disqualifications from tasks or work shifts, and in certain embodiments may include indications of stress level and risk level. In certain embodiments, they can include work environment improvement suggestions, such as more training, operator simulation training (OTS), which is an operations simulator that includes various what-if scenarios and measures how the worker addresses each and is based on process simulation models, or conducting more or frequent drills).
receiving input data from the simulation scenario; (Zahr, [30]; The system 200 includes an analyzer 208 that is operable to provide an assessment report 210 based on received data inputs 212. The inputs 212 may correspond to the discrete data 102 and live (real-time or wearable) data 104 described above, and the assessment report 210 may correspond to the output 105 relating to the one or more of classification of worker stress level, overall fitness of the worker and/or fitness for particular tasks, and advisories on recommended actions, warnings, or remediations also described above. The advisories can be qualifications or disqualifications from tasks or work shifts, and in certain embodiments may include indications of stress level and risk level. In certain embodiments, they can include work environment improvement suggestions, such as more training, operator simulation training (OTS), which is an operations simulator that includes various what-if scenarios and measures how the worker addresses each and is based on process simulation models, or conducting more or frequent drills.
determining that the biometric data of the user is indicative of suboptimal performance in at least one parameter of the simulation scenario; and (Zahr, [14]; Live data 104 relates to the worker's real-time physiological condition, as gleaned for example from a wearable device (not shown) or the like that can for instance provide pulse rate and cardio rhythms and patterns and other heart information, worker temperature, blood glucose level, skin moisture and hydration, sleep time, exercise time and level, and any other parameters that may be monitored in real-time and that may be relevant for determining that particular worker's physical and/or mental state, and fitness for a particular task or tasks and Zahr, [12]; The discrete data can include results from medical health checks, medical history, workload, years of experience, etc. The output of the model can include a stress level indicator and a risk level that can be used for example to qualify or disqualify the worker from conducting certain high risk and extremely demanding tasks).
While Zahr teaches parameters indicative of sub-optimal performance (i.e. disqualifying tasks), Zahr does not appear to explicitly teach triggering an intervention. However, Zahr in view of the analogous art of Haluck (i.e. performance modeling) does teach: triggering an intervention event in the simulation scenario based upon, at least in part, determining that the biometric data of the user is indicative of suboptimal performance in the at least one parameter of the simulation scenario. (Haluck, [02]; invention relates generally to computer-based simulators and, in particular, to an adaptive simulation environment that automatically facilitates real-time adjustments based on the user's performance to achieve an optimal learning "zone" involving moderate stress, and further including the ability to change the training environment in real-time to optimize motor-skill learning and Haluck, [09]; the step of modifying the display includes changing the size of the object as a function of the user's ability to complete the task in the predetermined period of time. For example, the size of the object may be increased (easier) if the user is unable to complete the task in the predetermined period of time, or the size may be decreased (more difficult) if the user is able to complete the task in the predetermined period of time and Haluck, [22-24]; one of these algorithms 106 measures the speed of the user in terms of task completion, and then modifies the speed of subsequent tasks. These are called RF 1,2,3. A second ST algorithm 108 in FIG. 1B (RF 4,5,6) measures the speed of task completion, but then modifies the environment to emphasize the accuracy of subsequent tasks. All RF/ST tasks "train up" the weaker hand, that is if the task is not completed, the task is repeated for the same hand, but may be adjusted in terms of level of difficulty… basis for the ST algorithms of RF 1,2,3 is that the target object appears for a preset amount of time, starting at about 2 seconds, for example (though the amount of time may be varied according to the invention depending upon the procedure. See FIG. 1A, decision block 110). If the task in not completed in 2 seconds, the target changes color for a fraction of a second 116 and an auditory signal is generated at 118, signifying failure of that task… if the task is completed in the time the target is present, another visual and/or auditory signal for task completion is given, and the next target time of presence or availability for task completion is reduced by an amount of time at 114, preferably 15-20 percent, making the task more difficult. For a task failure, the duration that the next target is available for task completion by an increase of time at 120 by about 15-20 percent, thus making the task easier).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the disclosed invention to have combined the teachings of Zahr teaches parameters indicative of sub-optimal performance with the teachings of Haluck including simulation interventions based on biometrics in order to optimize tasks for users to enhance training, optimize worker abilities, and worker quality (Haluck, [10]; if the user is unable to complete the task in the predetermined period of time, and an audible signal may be generated as a function of the user's ability or inability to complete the task in the predetermined period of time. If the user uses both hands and the task is not completed, the task is repeated for the same hand, and the task may optionally be adjusted in terms of level of difficulty. If the environment involves a laparoscopic surgical procedure, the task may include grasping, moving, cutting or otherwise manipulating the object).
Regarding Claims 2, 9, and 16, While Zahr teaches applying decision criteria to biometric data(Zahr, [25]; analysis module 112 can build an AI (artificial intelligence) model implementing an AI classification algorithm such as a decision tree algorithm or other AI techniques for facilitating the decision process about the worker's stress level, fitness and remediation), Haluck is relied upon to teach simulation side inputs: The computer-implemented method of claim 1, wherein determining that the biometric data of the user is indicative of suboptimal performance in the at least one parameter of the simulation scenario includes matching the biometric data from the user participating in the simulation scenario and the input data from the simulation scenario to a rule of a plurality of rules. (Haluck, [17-18]; Parameters to be governed by ST may include, but are not limited to, object size, color, speed of motion, timing and frequency or appearance, graphic clarity, haptics, level and types of haptic information, levels of stress to a user of the system, control over which levels, tasks, and scenarios are introduced… measure user abilities, skill, performance, and proficiency. The system also incorporates various methods of training enhancement such as recognizing saturation effects, plateau effects, after effect, introducing chaining of training tasks, introducing intermittent-type training. Near real-time adjustments are be made and Haluck, [22-25]; cited above).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the disclosed invention to have combined the teachings of Zahr teaches parameters indicative of sub-optimal performance with the teachings of Haluck including simulation interventions based on biometrics in order to optimize tasks for users to enhance training, optimize worker abilities, and worker quality (Haluck, [10]; if the user is unable to complete the task in the predetermined period of time, and an audible signal may be generated as a function of the user's ability or inability to complete the task in the predetermined period of time. If the user uses both hands and the task is not completed, the task is repeated for the same hand, and the task may optionally be adjusted in terms of level of difficulty. If the environment involves a laparoscopic surgical procedure, the task may include grasping, moving, cutting or otherwise manipulating the object).
Regarding Claims 3, 10, and 17, Zahr/Haluck teaches: The computer-implemented method of claim 1 further comprising determining a time when the intervention is to be triggered during the simulation. (Haluck, [23-25]; The basis for the ST algorithms of RF 1,2,3 is that the target object appears for a preset amount of time, starting at about 2 seconds, for example (though the amount of time may be varied according to the invention depending upon the procedure. See FIG. 1A, decision block 110). If the task in not completed in 2 seconds, the target changes color for a fraction of a second 116 and an auditory signal is generated at 118, signifying failure of that task… The time that the target is present before the failure signal(s) is then adjusted. For example, if the task is completed in the time the target is present, another visual and/or auditory signal for task completion is given, and the next target time of presence or availability for task completion is reduced by an amount of time at 114, preferably 15-20 percent… f the user can complete the task at block 122 in a time between 1 and 2 seconds (or thereabouts), the size of the target(s) remains the same at 132 for the next trial. As with all task completion and failure modes, optional visual and/or audible alerts may be generated. If the task is completed quickly at 130, in less than one second or shorter allotted time).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the disclosed invention to have combined the teachings of Zahr teaches parameters indicative of sub-optimal performance with the teachings of Haluck including simulation interventions times in order to determine the abilities of worker to complete a task or if auser can progress to harder tasks (Haluck, [25]; If the user can complete the task at block 122 in a time between 1 and 2 seconds (or thereabouts), the size of the target(s) remains the same at 132 for the next trial. As with all task completion and failure modes, optional visual and/or audible alerts may be generated. If the task is completed quickly at 130, in less than one second or shorter allotted time, the targets become smaller at 134 by a certain percent, making the task more difficult. If the user requires more than 2 second to complete the task, the targets become larger at 124, making the tasks easier).
Regarding Claims 4, 11, and 18, Zahr/Haluck teaches: The computer-implemented method of claim 1, wherein determining the time when the intervention is to be triggered during the simulation is determined based upon, at least in part, monitoring the simulation scenario for one of a predicted performance of the user, the input data from the user participating in the simulation scenario, and the input data from the simulation scenario. (Haluck, [23-25]; The basis for the ST algorithms of RF 1,2,3 is that the target object appears for a preset amount of time, starting at about 2 seconds, for example (though the amount of time may be varied according to the invention depending upon the procedure. See FIG. 1A, decision block 110). If the task in not completed in 2 seconds, the target changes color for a fraction of a second 116 and an auditory signal is generated at 118, signifying failure of that task… The time that the target is present before the failure signal(s) is then adjusted. For example, if the task is completed in the time the target is present, another visual and/or auditory signal for task completion is given, and the next target time of presence or availability for task completion is reduced by an amount of time at 114, preferably 15-20 percent… f the user can complete the task at block 122 in a time between 1 and 2 seconds (or thereabouts), the size of the target(s) remains the same at 132 for the next trial. As with all task completion and failure modes, optional visual and/or audible alerts may be generated. If the task is completed quickly at 130, in less than one second or shorter allotted time).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the disclosed invention to have combined the teachings of Zahr teaches parameters indicative of sub-optimal performance with the teachings of Haluck including simulation interventions times in order to determine the abilities of worker to complete a task or if a user can progress to harder tasks (Haluck, [25]; If the user can complete the task at block 122 in a time between 1 and 2 seconds (or thereabouts), the size of the target(s) remains the same at 132 for the next trial. As with all task completion and failure modes, optional visual and/or audible alerts may be generated. If the task is completed quickly at 130, in less than one second or shorter allotted time, the targets become smaller at 134 by a certain percent, making the task more difficult. If the user requires more than 2 second to complete the task, the targets become larger at 124, making the tasks easier).
Regarding Claims 5, 12, and 19, While Zahr teaches determining conditions of a user based on biometric data and generating a responsive action/intervention. Examiner relies on Haluck to teach implementing performance responsive interventions in simulations and altering agent behavior. The computer-implemented method of claim 1, wherein triggering the intervention event in the simulation scenario includes triggering an agent behavior in the simulation scenario. (Haluck, [23-25]; the ST algorithms of RF 1,2,3 is that the target object appears for a preset amount of time, starting at about 2 seconds, for example (though the amount of time may be varied according to the invention depending upon the procedure. See FIG. 1A, decision block 110). If the task in not completed in 2 seconds, the target changes color for a fraction of a second 116 and an auditory signal is generated at 118, signifying failure of that task…if the task is completed in the time the target is present, another visual and/or auditory signal for task completion is given, and the next target time of presence or availability for task completion is reduced by an amount of time at 114, preferably 15-20 percent, making the task more difficult. For a task failure, the duration that the next target is available for task completion by an increase of time at 120 by about 15-20 percent, thus making the task easier. The auditory signals provide immediate (proximate) feedback to help the learner to distinguish between a successfully completed or failed task and are included to assist in learning… As with all task completion and failure modes, optional visual and/or audible alerts may be generated. If the task is completed quickly at 130, in less than one second or shorter allotted time, the targets become smaller at 134 by a certain percent, making the task more difficult. If the user requires more than 2 second to complete the task, the targets become larger at 124, making the tasks easier).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the disclosed invention to have combined the teachings of Zahr teaches parameters indicative of sub-optimal performance with the teachings of Haluck including simulation interventions times in order to determine the abilities of worker to complete a task or if a user can progress to harder tasks (Haluck, [25]; If the user can complete the task at block 122 in a time between 1 and 2 seconds (or thereabouts), the size of the target(s) remains the same at 132 for the next trial. As with all task completion and failure modes, optional visual and/or audible alerts may be generated. If the task is completed quickly at 130, in less than one second or shorter allotted time, the targets become smaller at 134 by a certain percent, making the task more difficult. If the user requires more than 2 second to complete the task, the targets become larger at 124, making the tasks easier).
Regarding Claims 6, 13, and 20, Zahr/Haluck teaches: The computer-implemented method of claim 1, wherein triggering the intervention event in the simulation scenario includes adjusting a difficulty level of the simulation scenario. (Haluck, [09]; step of modifying the display includes changing the size of the object as a function of the user's ability to complete the task in the predetermined period of time. For example, the size of the object may be increased (easier) if the user is unable to complete the task in the predetermined period of time, or the size may be decreased (more difficult) if the user is able to complete the task in the predetermined period of time and Haluck, [25]; As with all task completion and failure modes, optional visual and/or audible alerts may be generated. If the task is completed quickly at 130, in less than one second or shorter allotted time, the targets become smaller at 134 by a certain percent, making the task more difficult. If the user requires more than 2 second to complete the task, the targets become larger at 124, making the tasks easier)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the disclosed invention to have combined the teachings of Zahr teaches parameters indicative of sub-optimal performance with the teachings of Haluck including simulation interventions times in order to determine the abilities of worker to complete a task or if a user can progress to harder tasks (Haluck, [25]; If the user can complete the task at block 122 in a time between 1 and 2 seconds (or thereabouts), the size of the target(s) remains the same at 132 for the next trial. As with all task completion and failure modes, optional visual and/or audible alerts may be generated. If the task is completed quickly at 130, in less than one second or shorter allotted time, the targets become smaller at 134 by a certain percent, making the task more difficult. If the user requires more than 2 second to complete the task, the targets become larger at 124, making the tasks easier).
Regarding Claims 7 and 14 Zahr/Haluck teaches: The computer-implemented method of claim 1, wherein the input data from the user participating in the simulation scenario further includes at least one of user performance data and game state data. (Haluck, [22-25]; Two different types of ST algorithms are disclosed herein, resulting in six RF/ST tasks in combination. Referring to FIG. 1A, one of these algorithms 106 measures the speed of the user in terms of task completion, and then modifies the speed of subsequent tasks. These are called RF 1,2,3. A second ST algorithm 108 in FIG. 1B (RF 4,5,6) measures the speed of task completion, but then modifies the environment to emphasize the accuracy of subsequent tasks. All RF/ST tasks "train up" the weaker hand, that is if the task is not completed, the task is repeated for the same hand, but may be adjusted in terms of level of difficulty… remaining citations can be seen above).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the disclosed invention to have combined the teachings of Zahr teaches parameters indicative of sub-optimal performance with the teachings of Haluck including simulation interventions times in order to determine the abilities of worker to complete a task or if a user can progress to harder tasks (Haluck, [25]; If the user can complete the task at block 122 in a time between 1 and 2 seconds (or thereabouts), the size of the target(s) remains the same at 132 for the next trial. As with all task completion and failure modes, optional visual and/or audible alerts may be generated. If the task is completed quickly at 130, in less than one second or shorter allotted time, the targets become smaller at 134 by a certain percent, making the task more difficult. If the user requires more than 2 second to complete the task, the targets become larger at 124, making the tasks easier).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JEREMY L GUNN whose telephone number is (571)270-1728. The examiner can normally be reached Monday - Friday 6:30-4:30.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jerry O'Connor can be reached on (571) 272-6787. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/JEREMY L GUNN/ Primary Examiner, Art Unit 3624
