DETAILED ACTION
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Continued Examination Under 37 CFR 1.114
2. A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant’s submission filed on 05/11/2026 has been entered.
3. Currently claims 1 and 21 have been amended; and claim 20 has been canceled. Thus, claims 1-19 and 21 are pending in this application.
Claim Rejections - 35 USC § 101
4. Non-Statutory (Directed to a Judicial Exception without an Inventive Concept/Significantly More)
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 1-19 and 21 are rejected under 35 U.S.C.101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1
The current claims fall within one of the four statutory categories of invention (MPEP 2106.03).
Step 2A [Wingdings font/0xE0] Prong One:
The claim(s) recite a judicial exception, namely an abstract idea, as shown below:
— Considering each of claims 1 and 21 as a representative claim, the following claimed limitations recite an abstract idea:
a) acquire data relating to a cognitive and/or physiological state and/or behavioral state of the at least one user, b)
determine based on the data acquired in step a) an indication of a predicted user performance score at the defined point in time, by calculating a numerical performance score,
c) compare the predicted user performance score to a desired user performance score, and
d) if the predicted user performance score indicates a predicted user performance falling short of a desired user performance indicated by the desired user performance score,
e) select, from a pool of activities based at least on the predicted user performance score, at least one activity and/or at least one time point or time range for performing an activity for adjusting the predicted user performance score to the desired user performance score or a tolerance range surrounding the desired user performance score, and
f) [present] at least one prompt to the user prompting the user to perform the at least one selected activity and/or to perform an activity at the at least selected one time point or time range,
g) wherein the user is continuously monitored with regard to their cognitive and/or physiological state and/or behavioral state and/or the completion of the selected activity and/or the performance of the activity at the at least one selected time point or time range, and
h) the selection in step e) is updated based on the monitoring data obtained in step g) to tailor the selection to the user's detected behavior.
Thus, the limitations identified above recite an abstract idea since the limitations correspond to certain methods of organizing human activity, and/or mental processes, which are part of the enumerated groupings of abstract ideas identified according to the current eligibility standard (see MPEP 2106.04(a)).
For instance, the current claims correspond to managing personal behavior; wherein, based on information gathered regarding the cognitive, physiological and/or behavioral state of a user, the user is provided with instruction that prompt the user to perform a selected activity in order to improve the user’s performance, etc.
Similarly, given the claimed limitations that recite the process of: determining an indication of a predicted user performance score at a defined point in time, based on the user’s cognitive, physiological and/or behavioral sate; comparing the user’s predicted performance score to a desired performance score; determining if the user’s predicted performance score is failing short of a desired user performance score, etc., the claims also overlap with the group mental processes; such as, an evaluation, an observation, and/or a judgment process, etc.
Step 2A [Wingdings font/0xE0] Prong Two:
The claims recite additional element(s), wherein computer system that implements computer components (a processor, a memory, etc.), including at least one sensor is utilized to facilitate the recited steps/functions regarding: collecting cognitive, physiological and/or behavioral data regarding a user (“a) acquiring data relating to a cognitive and/or physiological state and/or behavioral state of the at least one user via at least one sensor . . .”); analyzing the collected data using one or more algorithms (“b) determining based on the data acquired in step a) an indication of a predicted user performance score at the defined point in time, by calculating a numerical performance score, comparing the predicted user performance score to a desired user performance score, d) if the predicted user performance score indicates a predicted user performance falling short of a desired user performance indicated by the desired user performance score”); determining one or more results based on the analysis (“d) if the predicted user performance score indicates a predicted user performance falling short of a desired user performance indicated by the desired user performance score, e) selecting, from a pool of activities based at least on the predicted user performance score, at least one activity and/ or at least one time point or time range for performing an activity for adjusting the predicted user performance score to the desired user performance score or a tolerance range surrounding the desired user performance score”); generating pertinent information to the user based on the results obtained above (“f) outputting at least one prompt to the user prompting the user to perform the at least one selected activity and/or to perform an activity at the at least selected one time point or time range”); monitoring the user by gathering further data (“g) the user is continuously monitored via the at least one sensor with regard to their cognitive and/or physiological state and/or behavioral state and/or the completion of the selected activity and/or the performance of the activity at the at least one selected time point or time range”); updating one or more of the results based on the monitoring (“the selection in step e) is updated based on the monitoring data obtained in step g) to tailor the selection to the user's detected behavior”), etc.
However, the claimed additional element(s) fail to integrate the abstract idea into a practical application since the additional element(s) are utilized merely as a tool to facilitate the abstract idea. Thus, when each claim is considered as a whole, the additional element(s) fail to integrate the abstract idea into a practical application since they fail to impose meaningful limits on practicing the abstract idea. For instance, when each of the claims is considered as a whole, none of the claims provides a technological improvement over the relevant existing technology.
The observations above confirm that the claims are indeed directed to an abstract idea.
Step 2B
Accordingly, when the claim(s) is considered as a whole (i.e., considering all claim elements both individually and in combination), the claimed additional elements do not provide meaningful limitations 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 (also see MPEP 2106). The claimed additional elements are directed to conventional computer elements, which are serving merely to perform conventional computer functions. Accordingly, when each of the current claims is considered as a whole (e.g., see above the discussion under Prong Two regarding such consideration of the claim as a whole), none of the current claims is reciting any claim element—or a combination of claim elements—directed to an inventive concept.
It is also worth to note, per the original disclosure, that the claimed invention is directed to a conventional and generic arrangement of the additional elements. For instance, the original specification describes a computer system that utilizes one or more commercially available conventional computer devices (e.g., a smartphone, a tablet computer, etc.); and wherein, the computer system provides the user with one or more personalized recommendations, based on the analysis of data gathered regarding the user (e.g., data gathered via a sensor(s) and/or a manual input, etc.), in order to help the user achieve a desired goal, etc. (e.g., see [0168]; [0169], etc.).
Also see further sections from the specification (e.g., [0231] to [0241]) regarding the disclosed conventional hardware and software components.
In addition, the utilization of the conventional computer/network technology to facilitate the process of providing pertinent information/instruction to a user, based on collecting and analyzing data related to the user (e.g., cognitive data, physiological data, behavioral data, and/or activity data, etc.), is directed to a well-understood, routine, conventional activity in the art (e.g., see US 2016/0086500; US 2017/0132946; also see US 2008/0021287, etc.).
Note also that the process of selecting and presenting—from a database storing a plurality of exercises—one or more specific exercises to a user(s), based on one or more specific attributes of the user, is also part of the conventional computer/network technology (e.g., see US 2011/0004126; US 2006/0166737; etc.).
The observations above confirm that the current claimed invention fails to amount to “significantly more” than an abstract idea.
It is worth noting that the above analysis already encompasses each of the current dependent claims (i.e., claims 2-19). Particularly, each of the dependent claims also fails to amount to “significantly more” than the abstract idea since each dependent claim is directed to a further abstract idea, and/or a further conventional computer element/function utilized to facilitate the abstract idea.
Accordingly, the findings above demonstrate that none of the claims implements an element—or a combination of elements—directed to an inventive concept (e.g., none of the current claims is reciting an element—or a combination of elements—that provides a technological improvement over the existing/conventional technology).
► Applicant’s arguments directed to section §101 have been fully considered (the arguments filed on 05/11/2026). However, the arguments are not persuasive at least for the following reasons:
Firstly, regarding Prong Two of Step 2A, Applicant is asserting that “claim 1 recites, in part, ‘selecting, from a pool of activities based at least on the predicted user performance score, at least one activity . . . amended claim 1 is allowable under 35 U.S.C. § 101 at least because amended claim 1 ‘as a whole integrates the judicial exception into a practical application.’ MPEP § 2106.04(d) . . . the claim as a whole successfully integrates the judicial exception . . . amended claim 1 at least provides an ‘improvement in the functioning of a computer, or an improvement to other technology or technical field.’ . . . by ‘selecting, from a pool of activities based at least on the predicted user performance score, at least one activity and/or at least one time point or time range ... ‘ the claimed techniques narrow the selection to activities that are closely related to the user's current state data . . . ‘[i]f multiple activities or course of activities/actions are available, the selection unit preferably bases the selection on a trade-off between adjusting the predicted user performance score to the desired user performance score or a tolerance range and causing minimal disruption to a user's planned or scheduled events.’ Present Application, para. [0177]. Because the pool of activities is tied at least to the predicted user performance score, which is itself derived from current sensor data for this particular user, the selection is made within a smaller, more relevant range. As such, the claimed techniques reduce the computational search space and improve processing efficiency by avoiding the need to evaluate activities that are not relevant to the user's current predicted performance state” (emphasis added).
However, the process of selecting—from a database of items—one or more specific items (e.g., one relevant activity) based on one or more conditions (e.g., a predicted performance score) has nothing to do with a technological improvement. In particular, regardless of whether the claimed method/system is narrowing the selection of activities, it is merely performing basic or existing computer functions. Thus, the above does not achieve any improvement in the functioning of the computer, regardless of whether the alleged improvement relates to processing efficiency and/or reduction of a memory space, etc. Consequently, Applicant’s attempt to portray an alleged technological improvement, namely the alleged techniques that supposedly “reduce the computational search space and improve processing efficiency”, is not persuasive.
Moreover, Applicant appears to make contradictory assertions. For instance, per Applicant’s theory, the claimed techniques “reduce the computational search space and improve processing efficiency by avoiding the need to evaluate activities that are not relevant to the user's current predicted performance state” (emphasis added). However, if the claimed (and the disclosed) method/system is assumed to reduce computational search “by avoiding the need to evaluate activities that are not relevant to the user's current predicted performance state”, it is unclear how the method/system is assumed to identify—from a plurality of activities in the pool—the at least one activity that is relevant to the user? So far, Applicant fails to address the above critical finding. Of course, the above inconsistency further confirms that neither the current claims nor the original disclosure as a whole implements any technological improvement over the relevant existing technology.
Although a reference is not necessarily required, one or more of the references cited as part of the analysis under Step 2B already confirm the existing technology that Applicant’s claimed (and disclosed) method/system is implementing. For instance, Einav (US 2011/0004126), which is a publication available to the public for more than a decade prior to Applicant’s claimed (and disclosed) method/system, already teaches such conventional system. In particular, besides evaluating and scoring the abilities of the user to perform one or more activities (e.g., see [0077] to [0089]), Einav’s system also selects, based on the evaluation above, one or more relevant exercises to the user from a database that stores a plurality of activities ([0129]).
The fact above effectively invalidates Applicant’s assertion regarding the alleged technological improvement. In particular, despite relying on the such features of the existing computer/network technology, Applicant is attempting to portray an alleged technological improvement while depicting one of the existing computer functions as the alleged technological improvement. Thus, neither the current claims nor the original disclosure implements an element—or a combination of elements—that integrates the abstract idea into a patent-eligible practical application.
Applicant further asserts, “the predicted user performance score is a numerical score calculated in previous step (b), which allows the claimed steps to perform the selection without re-analyzing the underlying raw sensor data. As described in the Present Application, the claimed invention ‘provides a quantified output of this state (an integer number, e.g. a user performance score) and it can be used to estimate the value of [the state] in the future (e.g. a predicted user performance score).’ Present Application, para. [0250]. The numerical score encapsulates the user's cognitive, physiological, and behavioral state data into a single quantified value, so the selection step can operate directly on the quantified value rather than processing the raw data again. As such, the claimed techniques further reduce system complexity by avoiding redundant processing of the same data across multiple steps” (emphasis added).
However, the argument above is not even logically sound, much less persuasive. This is because it is relying on an invalid assumption that has nothing to do with any technology, much less a technological improvement. For instance, if the so-called “predicted user performance score” is already determined in step (b), based on the analysis of the sensor data, then step (c) is merely required to compare the above already determined result to the so-called “desired user performance score”. This is because step (c) already has the two parameters needed to perform the comparison. In particular, once the execution process reaches step (c), it is illogical to simply repeat the process of step (a)—i.e., the process of analyzing the sensor data—since step (c) already has the result needed to perform the comparison. Accordingly, it does not appear to be a valid argument to simply allege a technological improvement just because step (c)—and/or any of steps (c) to (h)—does not repeat the task of step (a). Consequently, Applicant’s alleged technological improvement, namely the alleged capability to “reduce system complexity by avoiding redundant processing of the same data across multiple steps”, is not even logical, much less persuasive.
Applicant further asserts that “claim 1 further recites that ‘the selection in step e) is updated based on the monitoring data obtained in step g) to tailor the selection to the user's detected behavior.’ . . . ‘[t]he recommendations output by the system or method according to the present invention (e.g. the activities selected to be performed or skipped at selected time points or ranges) are preferably also updated based on the monitoring data capturing the actual user behaviour in the fashion of a closed-loop operation.’ Present Application, para. [0102] . . . ‘using a sensor or multiple sensors for monitoring user behaviour can resolve user behaviour differing from recommended behaviour.’ Id., para. [0240]. Accordingly, this closed-loop operation provides improvements to the prompt generation process by avoiding unnecessary prompts, as the system does not need to run as frequently at least because the system tailors recommendations based on actual detected behavior rather than generating repeated prompts based on expected incomplete and/or inaccurate data” (emphasis added).
However, Applicant appears to rely on subjective speculations, as opposed to factual findings, to substantiate the alleged technological improvement. For instance, unlike Applicant’s speculative assertion above, the so-called “closed loop”, which the system supposedly implements to monitor the user, appears to be performed continuously. For instance, the specification describes (see [0099], emphasis added),
“For example, it is monitored whether the user completes the activity "Sleeping 2 hours from 12:00 to 14:00 pm" fully (2 hours), partially (e.g. 1 hour) or not at all (0 hour, 0 min) and whether the user performs the task at the at least one selected time point or time range, e.g. sleeps 2 hours from 11 :00 am to 13:00 pm (the user has partially completed the activity at the selected time range), sleeps 2 hours from 12:00 am to 14:00 pm (the user has fully completed the activity at the selected time range) etc. The monitoring can rely on sensor data, but can also comprise manual input from the user, prompting the user to provide manual input or inferred data inferred e.g. from the user's habits or a recommendation output by the method or system”
Accordingly, Applicant’s new theory, “the system does not need to run as frequently at least because the system tailors recommendations based on actual detected behavior”, appears to completely contradict the facts described in the speciation. This is because the disclosed system/method appears to continuously monitor the user (e.g., monitoring the user continuously in order to determine whether the user has slept for full 2 hours or not, etc.). Of course, such continuous monitoring process does drain system resources. Moreover, per the excerpt above, the disclosed system/method alternatively relies on a manual process—i.e., instead of relying on a sensor, the system prompts the user to provide a manual input. In fact, such manual implementation does not appear to be a resource-intensive process since it does not require the continuous use of sensor to monitor the user. Thus, even the specification itself effectively invalidates Applicant’s theory regarding the alleged technological improvement.
Moreover, the process of monitoring a user based on data gathered from one or more sensors, while managing the frequency of the monitoring process to conserve computational resources, is already part of the existing computer/network technology. Although a reference is not necessarily required to demonstrate the fact above, at least one of the references cited as part of the Step 2B analysis already teaches such existing technology. In particular, Woellenstein (US 2008/0021287), which is a publication available to the public for more than a decade prior to Applicant’s claimed (and disclosed) method/system, describes such a computer-based system that monitors—based on one or more sensors—the state of a patient ([0021]; [0023]). Accordingly, when the patient’s health condition is stable, Woellenstein performs the monitoring process less frequently—such as, collecting one sample per day; however, when the patient’s health condition is worsening, Woellenstein increases the frequency of gathering sensor data—such as, one sample every four hours or one sample every thirty minutes, etc. (see [0028]). Thus, even common sense dictates that Woellenstein does conserve computational resources since it does not continuously gather sensor data when the patient’s health condition is stable. Instead, the frequency of gathering sensor data increases only when the patient’s health condition is deteriorating.
The above demonstrates the robustness of the existing computer/network technology to efficiently manage computational resources while dynamically adapting to the specific scenario. In contrast, Applicant’s claimed (and disclosed) method/system does not even appear to have such a feature, much less an advanced one. Thus, neither the sections that Applicant cited from the specification, nor Applicant’s assertion regarding the claimed (or disclosed) features, demonstrates the alleged technological improvement that Applicant is implying.
Secondly, while referring to the USPTO memorandum (the memorandum dated December 5, 2025), Applicant asserts that “by selecting from a pool of activities based on the predicted user performance score, the system performs selection within a smaller, more relevant range using a numerical score that encapsulates the user's cognitive, physiological, and behavioral state data, thereby avoiding redundant processing of the same data across multiple steps and reducing computational resources. Further, via the closed-loop operation, the claimed process tailors recommendations based on actual detected behavior to avoid unnecessary prompts. As such, the claimed techniques at least provide ‘credited benefits’ of ‘reduced system complexity and streamlining’ and ‘preservation of performance attributes associated with earlier tasks during subsequent computational tasks’ that integrate the claims ‘as a whole ... into a practical application.’ Id. Accordingly, ‘the [claimed] invention improves upon conventional functioning of a computer, or upon conventional technology or technological processes’ where ‘a technical explanation of the asserted improvement is present in the specification, and that the claim reflects the asserted improvement.’ MPEP § 2106.05(a)” (emphasis added).
However, neither the memorandum (the December 5, 2025 memorandum) nor any of the sections from the MPEP even remotely supports Applicant’s alleged technological improvement. This is because Applicant’s alleged technological improvement has nothing to do with a specific technology, much less a technological improvement. Instead, it appears to rely on unsound speculative assertions, as opposed to factual findings. In particular, per Applicant’s theory, the claimed method/system provides an alleged technological improvement since step (c)—or any of steps (c) to (h)—does not repeat the process of step (a). However, as already demonstrated above, such speculative assertion is logically flawed. This is because step (c) is assigned a task of comparing two results—namely, comparing “predicted user performance score”, which is obtained from step (a), to the so-called “desired user performance score”. Accordingly, step (c) is not even expected to repeat the same process of step (a) since it already has the value it needs to perform its assigned task (i.e., the task of comparing the value already obtained from step (a) to a predetermined value). Accordingly, once again it is not logically sound to allege a technological improvement just because step (c) does not repeat the task of step (a). Consequently, Applicant’s alleged technological improvement, namely the alleged capability to “reduc[e] computational resources” by supposedly “avoiding redundant processing of the same data across multiple steps”, is once again not persuasive. In particular, while repeatedly relying on speculative assertions, Applicant is attempting to substantiate an alleged technological improvement.
Of course, the same is true regarding Applicant’s so-called “closed loop” operation, which allegedly reduces “system complexity . . . tailors recommendations based on actual detected behavior to avoid unnecessary prompts”. In particular, while misapplying the revised section of the MPEP—i.e., MPEP 2106.04(d), Applicant is attempting to support the alleged technological improvement while simply emphasizing the same subjective theories noted above. In contrast, the Office’s analysis above already demonstrates the reason why none of Applicant’s assertions is valid to substantiate Applicant’s alleged technological improvement. For instance, as already pointed out above, the process of assigning a specific task to each step, as opposed to requiring each step to repeat a task that a preceding step has already performed, has nothing to do with a technological improvement. Instead, the above is merely a routine or existing programming procedure. Consequently, Applicant’s arguments are not even relevant to challenge—much less negate—the Office’s findings.
Of course, the same is true regarding Applicant’s theory about the so-called “closed-loop” operation, which supposedly “provides improvements to the prompt generation process by avoiding unnecessary prompts as the system does not need to run as frequently” since it supposedly “tailors recommendations based on actual detected behavior rather than generating repeated prompts based on expected incomplete and/or inaccurate data” (emphasis added). In particular, even the specification itself invalidates Applicant’s theory since the system is continuously running in order to monitor the activities that the user is performing—such as, monitoring whether the user has slept for two full hours, etc. (see discussion above). In this regard, Applicant justification does not appear to be relevant since it is immaterial whether the system is tailoring the recommendation “based on actual detected behavior rather than generating repeated prompts based on expected incomplete and/or inaccurate data”. This is because the system is still required to continuously monitor the user if the objective is to accurately determine whether user has slept for two full hours or not. Of course, if the required sleep duration is eight hours, as opposed to just two hours, the system is expected to monitor the user continuously for eight hours. Otherwise, it cannot accurately determine whether the user has slept for full eight hours or just for three hours, etc.
Moreover, again as already pointed out above, it is already part of the existing computer/network technology to implement a computer-based system, which dynamically adapts the frequency of monitoring a user based on the status of the user. Of course, the exemplary reference (Woellenstein) cited above already confirms the fact above. Accordingly, the finding above further invalidates Applicant’s core argument regarding the alleged technological improvement.
Thus, at least for the reasons discussed above, the Office concludes that none of the current claims implements an element—or a combination of elements—that amounts to “significantly more” than an abstract idea.
Claim Rejections - 35 USC § 112
5. The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
● Claims 8 and 10 are rejected under 35 U.S.C.112(b), or second paragraph (pre-AIA ), as being indefinite for failing to particularly point out and distinctly claim the subject matter which applicant regards as the invention.
(a) Claim 8 recites, “step e) comprises selecting from a pool of activities, such as resting, physical activity, sleeping or cognitive exercise, an activity or course of activities predicted to adjust the predicted user performance score to the desired user performance score or a tolerance range surrounding the desired user performance score” (emphasis added).
However, it is unclear whether the term “a pool of activities” is referring to a further pool or the same pool that claim 1 is reciting. Given its dependency on claim 1, it is worth noting that claim 8 includes all the limitations of claim 1.
In addition, given the context of the term, “such as”, as used in the claim , it is unclear whether the claim is attempting to limit the “pool of activities” to the listed activities, or whether the listed activities are part of the claimed method.
Consequently, claim 8 is ambiguous or indefinite at least for the reasons pointed out above.
(b) Claim 10 recites, “. . . wherein the user can preferably define the desired
user performance score as a desired minimal numerical performance score at a single point in time or as a desired minimal cumulative numerical performance score summed over or averaged over multiple points of time” (emphasis added).
However, given the context of the term, “preferably”, as used above, it is unclear whether the claim is attempting to limit the “user performance score” to the listed options only. Accordingly, claim 10 is ambiguous or indefinite at least for the reason above.
Applicant is further advised to reevaluate each of the current claims and make appropriate corrections if additional discrepancies are discovered.
Prior Art
6. Considering each of claims 1 and 21 as a whole (including the dependent claims), the prior art does not teach or suggest the claims as currently presented (regarding the state of the prior art, see the office action dated 06/18/2025).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to BRUK A GEBREMICHAEL whose telephone number is (571) 270-3079. The examiner can normally be reached from 7:00 AM - 3:00 PM.
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/BRUK A GEBREMICHAEL/Primary Examiner, Art Unit 3715
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