3DETAILED 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 .
Status of Amendments
Claim 1 has been amended.
Claims 2 – 15 have been cancelled.
Claims 16 – 34 have been newly added.
Claims 1 and 16 – 34 are pending.
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.
This subject matter eligibility analysis follows the latest guidance for Patent Subject Matter Eligibility Guidance.
Claims 1 and 15 - 34 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter.
Step 1:
Claims 1 and 16 – 23 are drawn to a method.
Claims 26 – 33 are drawn to a system.
Claim 34 are drawn to a CRM
Thus, initially, under Step 1 of the analysis, it is noted that the claims are directed towards eligible categories of subject matter.
Step 2A:
Prong 1: Does the Claim recite an Abstract idea, Law of Nature, or Natural Phenomenon?
Claims 26 - 33 are exemplary because they require substantially the same operative limitations of the remaining claims (reproduced below.) Examiner has underlined the claim limitations which recite the abstract idea, discussed in detail in the paragraphs that follow.
26. (New) A system comprising:
one or more processors, and
one or more non-transitory computer readable media storing computer instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising:
determining one or more measurements of a current user's interaction with an application, the measurements specifying changes in response time or accuracy for different levels of visual or audio output of the application for the current user;
comparing the one or more measurements with expectations derived from measurements from a first corpus of users, comprising comparing (i) one or more of the changes in response time or accuracy for the different levels of visual or audio output of the application for the current user with (ii) one or more representative changes in response time or accuracy for the different levels of visual or audio output of the application for one or more other users;
identifying one or more capabilities of the current user based upon comparing (i) the one or more of the changes in response time or accuracy for the different levels of visual or audio output of the application for the current user with (ii) the one or more representative changes in response time or accuracy for the different levels of visual or audio output of the application for one or more other users; and
in response to identifying the one or more capabilities of the current user,
modifying at least a first property of the application, comprising selecting an adjusted level of visual or audio output of the application.
The claims recite italicized limitations that fall within at least one of the groupings of abstract ideas enumerated in the 2019 PEG, namely, Certain Methods of Organizing Human Activity and Mental Processes.
More specifically, under this grouping, the italicized limitations represent concepts performed in the human mind (including an observation, evaluation, judgment, opinion) and managing interactions between people. For example, the italicized limitations are directed towards the collection of user interaction data, analyzing it by comparing the user interaction data to group of users, classifying the data and modifying the behavior of and application based on the characterization. These are steps or concepts that can be performed in the human mind or using pencil and paper.
Prong 2: Does the Claim recite additional elements that integrate the exception in to a practical application of the exception?
Although the claims recite additional limitations, these limitations do not integrate the exception into a practical application of the exception. For example, the claims require additional limitations as follow, (emphasis added): computer applications, processors, computers.
These additional limitations do not represent an improvement to the functioning of a computer, or to any other technology or technical field, (MPEP 2106.05(a)). Nor do they apply the exception using a particular machine, (MPEP 2106.05(b)). Furthermore, they do not effect a transformation. (MPEP 2106.05(c)). Rather, these additional limitations amount to an instruction to “apply” the judicial exception using a computer as a tool to perform the abstract idea. Therefore, since the additional limitations, individually or in combination, are indistinguishable from a computer used as a tool to perform the abstract idea, the analysis continues to Step 2B, below.
Step 2B:
Under Step 2B, the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because they amount to conventional and routine computer implementation and mere instructions for implementing the abstract idea on generic computing devices.
For example, as pointed out above, the claimed invention recites additional elements facilitating implementation of the abstract idea. Applicant has claimed computer applications and processors. However, all of these elements viewed individually and as a whole, are indistinguishable from conventional computing elements known in the art. Therefore, the additional elements fail to supply additional elements that yield significantly more than the underlying abstract idea.
As the Alice court cautioned, citing Flook, patent eligibility cannot depend simply on the draftsman’s art. Here, amending the claims with generic computing elements does not (in this Examiner’s opinion), confer eligibility.
Regarding the Berkheimer decision, Applicant’s specification establishes that these additional elements are generic:
[0016] Referring now to the drawings, wherein like reference numerals designate identical or corresponding parts throughout the several views, in Figure 1 an example of an entertainment system 10 is a computer or console such as the Sony® PlayStation 5® (PS5).
[0017] The entertainment system 10 comprises a central processor 20. This may be a single or multi core processor, for example comprising eight cores as in the PS5. The entertainment system also comprises a graphical processing unit or GPU 30. The GPU can be physically separate to the CPU, or integrated with the CPU as a system on a chip (SoC) as in the PS5.
[0018] The entertainment device also comprises RAM 40, and may either have separate RAM for each of the CPU and GPU, or shared RAM as in the PS5. The or each RAM can be physically separate, or integrated as part of an SoC as in the PS5. Further storage is provided by a disk 50, either as an external or internal hard drive, or as an external solid state drive, or an internal solid state drive as in the PS5.
[0019] The entertainment device may transmit or receive data via one or more data ports 60, such as a USB port, Ethernet® port, Wi-Fi® port, Bluetooth® port or similar, as appropriate. It may also optionally receive data via an optical drive 70.
[0020] Interaction with the system is typically provided using one or more handheld controllers 80, such as the DualSense® controller in the case of the PS5.
[0021] Audio/visual outputs from the entertainment device are typically provided through one or more A/V ports 90, or through one or more of the wired or wireless data ports 60.
[0022] Where components are not integrated, they may be connected as appropriate either by a dedicated data link or via a bus 100.
[0023] An example of a device for displaying images output by the entertainment system is a head mounted display ‘HMD’ 95, worn by a user 1.
Therefore, these elements fail to supply additional elements that yield significantly more than the underlying abstract idea. Thus, taken alone, the additional elements do not amount to significantly more than the above-identified judicial exception (the abstract idea).
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.
Moreover, the claims do not recite improvements to another technology or technical field. Nor, do the claims improve the functioning of the underlying computer itself -- they merely recite generic computing elements. Furthermore, they do not effect a transformation of a particular article to a different state or thing: the underlying computing elements remain the same.
Concerning preemption, the Federal Circuit has said in Ariosa Diagnostics, Inc., V. Sequenom, Inc., (Fed Cir. June 12, 2015):
The Supreme Court has made clear that the principle of preemption is the basis for the judicial exceptions to patentability. Alice, 134 S. Ct at 2354 (“We have described the concern that drives this exclusionary principal as one of pre-emption”). For this reason, questions on preemption are inherent in and resolved by the § 101 analysis. The concern is that “patent law not inhibit further discovery by improperly tying up the future use of these building blocks of human ingenuity.” Id. (internal quotations omitted). In other words, patent claims should not prevent the use of the basic building blocks of technology—abstract ideas, naturally occurring phenomena, and natural laws. While preemption may signal patent ineligible subject matter, the absence of complete preemption does not demonstrate patent eligibility. In this case, Sequenom’s attempt to limit the breadth of the claims by showing alternative uses of cffDNA outside of the scope of the claims does not change the conclusion that the claims are directed to patent ineligible subject matter. Where a patent’s claims are deemed only to disclose patent ineligible subject matter under the Mayo framework, as they are in this case, preemption concerns are fully addressed and made moot. (Emphasis added.)
For these reasons, it appears that the claims are not patent-eligible under 35 USC §101.
Claim Rejections - 35 USC § 103
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.
Claim(s) 1, 16 – 18, 21 – 29 and 32 - 34 is/are rejected under 35 U.S.C. 103 as being unpatentable over Gould (US 2019/0182071) in view of Aghdaie (US 2018/0243656).
As per claim 1,
determining one or more measurements of a current user's interaction with an application, the measurements specifying changes in response time or accuracy for different levels of visual or audio output of the application for the current user; (Gould discloses the determination of a user’s interactions with a UI, wherein the interactions are analyzed to measure the users typing or input speed (i.e. response time) (Gould 0033). Gould discloses a cloud server determining the users cognitive level based upon changes in the measured interactions with the UI) (Gould 0030, 0031)
in response to identifying the one or more capabilities of the current user, modifying at least a first property of the application, comprising selecting an adjusted level of visual or audio output of the application (Gould discloses the modification of a user interface based upon the identified cognitive level (increase or decrease in cognitive level), wherein the modification may be a graphical modification) (Gould 0033)
Gould fails to disclose:
comparing the one or more measurements with expectations derived from measurements from a first corpus of users, comprising comparing (i) one or more of the changes in response time or accuracy for the different levels of visual or audio output of the application for the current user with (ii) one or more representative changes in response time or accuracy for the different levels of visual or audio output of the application for one or more other users;
identifying one or more capabilities of the current user based upon comparing (i) the one or more of the changes in response time or accuracy for the different levels of visual or audio output of the application for the current user with (ii) the one or more representative changes in response time or accuracy for the different levels of visual or audio output of the application for one or more other users; and
However, in a similar field of endeavor, Aghdaie discloses a system that Aghdaie discloses the comparing of the monitored measurements found in a user profile, wherein the attributes correspond to statistical values, and comparing all the attributes of a single user with that of multiple users by means of a prediction model to generate a determination such as predicted churn rate of a user, Aghdaie discloses the characterizing of a player as likely to churn based upon the comparison ) (Aghdaie 0091 - 0093).
It would be obvious to one of ordinary skill in the art, at the time of filing, to modify Gould in view of Aghdaie to use a known technique to improve similar devices in the same way, by comparing a single user’s cognitive measurements to a corpus of user cognitive measurements to aid in the determination of when to make changes to an application’s interface. This would provide a greater amount of accuracy as the system would have more data points to compare a singular users measurements with in order to determine the amount of cognitive decline the user is experiencing
As per claim 16, wherein determining the one or more measurements comprises performing the one or more measurements of the current user's interaction using the application or a calibration application. (Gould discloses the determination of the current user interactions while utilizing the application) (Gould 0033)
As per claim 17, wherein identifying the one or more capabilities of the current user comprises: classifying the one or more capabilities of the current user based on a closest match between the one or more measurements and a respective measurement profile derived from a second corpus of users with one or more respective known capabilities. (Combination of Gould in view of Aghdaie, wherein Aghdaie teaches the determination of a user’s difficulty level (i.e. capability) based upon how they compare to a user pool or group comprising a plurality of user of similar attributes wherein the modification made to the game is based on how close the they align with a challenge level of the users of the pool) (Aghdaie 0095)
As per claim 18, comprising: estimating a fatigue level of the current user; and modifying at least the first property of the application based on the estimated fatigue level of the current user. (Aghdaie discloses the estimation of how likely the user is to churn or stop playing a game (i.e. game fatigue) (Aghdaie 0091, 0092), (Aghdaie discloses the comparing of the monitored measurements found in a user profile, wherein the
attributes correspond to statistical values, and comparing all the attributes of a single user with that of multiple users by means of a prediction model to generate a determination such as predicted churn rate of a user, (Aghdaie 0091 - 0093), wherein the system determines that the user needs more of a challenge or difficulty (Aghdaie 0093, 0094) and makes a modification to the game based upon that need) (0097, 0098).
As per claim 21, wherein the one or more capabilities of the user comprise at least one of a reaction time or a dexterity of the current user. (Gould discloses a reaction time in reference to typing speed) (Gould 0033)
As per claim 22, wherein the one or more capabilities of the current user are based on at least one of a sensory processing cognitive load, a memory cognitive load, a problem solving cognitive load, or an executive function cognitive load of the current user. (Gould discloses the capabilities based on a sensory processing cognitive load (i.e. typing)) (Gould 0033).
As per claim 23, wherein modifying at least the first property of the application comprises changing an in-application rate of time. (Combination of Gould and Aghdaie, Aghdaie discloses the difficultly level being changed with respect to the users reaction time such as "adjusting responsiveness") (Aghdaie 0030)
As per claim 24, comprising determining a degree of change to the in- application rate of time based on the one or more capabilities of the current user. (Combination of Gould and Aghdaie, Aghdaie discloses the difficultly level being changed with respect to the users reaction time such as "adjusting responsiveness") (Aghdaie 0030)
As per claim 25, comprising determining when to change the in-application rate of time based on the one or more capabilities of the current user. (Combination of Gould and Aghdaie, Aghdaie discloses the difficultly level being changed with respect to the users reaction time such as "adjusting responsiveness" at some point in time during application use) (Aghdaie 0030)
Independent claim(s) 26 and 34 is/are made obvious by the combination of Gould and Aghdaie based on the same analysis set forth for claim(s) 1, which are similar in claim scope.
Dependent claim(s) 27-29, 32 and 33 is/are made obvious by the combination of Gould and Aghdaie based on the same analysis set forth for claim(s) 16-18, 21 and 22, which are similar in claim scope.
Claim(s) 19 and 30 is/are rejected under 35 U.S.C. 103 as being unpatentable over Gould (US 2019/0182071) in view of Aghdaie (US 2018/0243656) in view of Kayama (US 2023/0118151).
As per claim 19, Aghdaie fails to disclose:
correlating estimated levels of fatigue with changes to other measurements; and modifying at least the first property of the application based on the correlation between estimated levels of fatigue and the other measurements.
However, in a similar field of endeavor, Kayama discloses a game system wherein fatigue levels and other measurements such as stress levels of a game player a continuously monitored and the game difficultly level is changed in response to how the fatigue level affects the stress level, wherein the fatigue and stress level is continuously monitored and thus the game is continuously adapting the game difficulty (Kayama 0002)
It would be obvious to one of ordinary skill in the art, at the time of filing, to modify Aghdaie in view of Kayama to use a known technique to improve similar devices in the same way by correlating fatigue levels to another measurement such as stress to determine the needs of a user. This would enable the system to more accurately determine the current mood of the player and adapt the game to better suit the play style of the player.
Dependent claim(s) 30 is/are made obvious by the combination of Gould, Aghdaie and Kayama based on the same analysis set forth for claim(s) 19, which are similar in claim scope.
Claim(s) 20 and 31 is/are rejected under 35 U.S.C. 103 as being unpatentable over Gould (US 2019/0182071) in view of Aghdaie (US 2018/0243656) in view of Kwatra et al (US 2022/0139375).
As per claim 20, Gould fails to disclose:
wherein comparing the one or more measurements comprises comparing the one or more measurements with data from the first corpus of users to determine a difference between the one or more measurements and an average measurement value, or a position within a distribution of measurement values.
However, in a similar field of endeavor, wherein a cognitive function is determined, Kwatra teaches “ Corpus generator 202 in some embodiments uses crowdsourcing to populate the utterance corpus 214. Various statistical analyses can be performed based on the population comprising the corpus and used as a benchmark for classifying whether a user's change in memory functioning is likely due to memory impairment (e.g., whether the change deviates by more than a predetermined number of standard deviations from the population norm). A machine learning classification model can be generated using iterative reinforcement learning whereby the model is iteratively refined with increases in the size of the population of utterance corpus 214.” (Kwatra 0048). Thus as can be seen the comparison of a difference of the user’s measurements to a standard deviation.
It would be obvious to one of ordinary skill in the art, at the time of filing, to modify Gould in view of Kwatra to use a known technique to modify similar systems in the same way by making a statistical comparison of a user’s measurements to determine a difference with respect to a groups distribution of values. In this way a system can readily determine if the measured cognitive measurement is an outlier or abnormality.
Dependent claim(s) 31 is/are made obvious by the combination of Gould, Aghdaie and Kwatra based on the same analysis set forth for claim(s) 20, which are similar in claim scope.
Response to Arguments
Applicant’s arguments with respect to claim(s) 1 and 16 – 34 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument. Please see above rejection addressing the newly amended claims in view of Gould, Aghdaie, Katwra and Kayama.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/RAW/ Examiner, Art Unit 3715
2/21/2026
/KANG HU/ Supervisory Patent Examiner, Art Unit 3715