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 .
Continued Examination Under 37 CFR 1.114
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 6/10/2026 has been entered.
Status of Claims
Claims 9, 14 has been canceled.
Claims 1, 3, 12, 13 have been amended
Claims 1- 8, 10 – 13 and 15 – 22 are presently pending
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- 8, 10 – 13 and 15 – 22 is/are rejected under 35 U.S.C. 103 as being unpatentable over Sumant et al (US 2020/0206631) in view of Estanislao (US 2020/0406144)
As per claim 1, Sumant discloses:
one or more processors; and (Sumant 0126, 0127)
one or more non-transitory machine-readable media storing instructions that, when executed by the one or more processors, cause the affective gaming system to: (Sumant 0126, 0127)
execute a session of a video game on an entertainment device for a first user…(Sumant discloses a unit that hosts a video game session) (Sumant 0031, 0096)
receive, during gameplay of the session, biometric data associated with the first user (Sumant discloses the biometric data from a first user that is participating in the session of a video game) (Sumant 0025, 00350096, 0097)
generate, based on at least part of the biometric data, current emotion data associated with the first user; (Sumant discloses the determination of a current or predicted emotion of the user based upon the current biometrics) (Sumant 0099)
(Sumant discloses the determination of a desired emotional state based upon the current or predicted emotional state) (Suman 0099)
determine a difference between the target emotion data associated with the first user and the current emotion data associated with the first user to evaluate whether the difference meets or exceeds a threshold difference; (Sumant discloses the modification of a video game play or data based upon the difference of the predicted emotion state and desired emotional state (Sumant 0100 – 0102). Sumant discloses the conversion of the desired emotional state and the predicted emotion state to a numerical value to determine a degree of difference when compared to a threshold (i.e. does it match or do the numerical values representing states match) (Sumant 0100)
modify, responsive to the difference meeting or exceeding the threshold difference, one or more aspects of the video game that are specific to the first user…; (Sumant discloses the modification of a video game play or data based upon the difference of the predicted emotion state and desired emotional state) (Sumant 0100 – 0102)
iteratively perform during the gameplay of the session, the generation of the current emotion data and the target emotion data, the determination of the difference, and the cause of the rendering until the difference does not meet or exceed the threshold difference; and cease the modification of the one or more aspects of the video game that are specific to the first user. (Sumant discloses that the process occurs in real time and is iterative wherein game modifications occur repeatedly) Sumant states: “ Further, it should be understood that the process 400 may be updated or performed repeatedly over time. For example, the process 400 may be repeated for each play session of a video game 112, for each round of the video game 112, each week, each month, for every threshold number of play sessions, for every threshold number of times a user loses or fails to complete an objective, each time a win ratio drops below a threshold level, and the like. However, the process 400 may be performed more or less frequently. It should also be understood that the process 400 may be performed in real-time, or substantially close to real-time, enabling the video game 112 to be modified while the user is playing the video game 112. Thus, the process 400 can make for a dynamic gaming experience.” (Sumant 0096)
Sumant fails to disclose:
of a plurality of users participating in the session of the video game, wherein the video game is a multi-player video game;
…without impacting mechanics of interactions between the first user and other users participating in the session of the video game during the gameplay, and wherein the modification is performed by adjusting an in-game display setting or an in-game audio setting specific to the first user to provide alternative graphics or alternative sounds for a virtual object or an environmental element;
cause the entertainment device to process the alternative graphics of the alternative sounds to generate a modified video frame or a modified audio output to render the modified one or more aspects of the video game to the first user, wherein the modified one or more aspects of the video game is not rendered to the other users;
However in a similar field of endeavor wherein a video game is customized for an individual player, Estanislao teaches a multiplayer game system comprising multiple clients connecting to a game server wherein based upon the players interactions in the game and performance in the game the system dynamically modifies in-game music to provide to a single game player utilizing a client individualized music to that client only and not other player clients in the multiplayer game session (Etanislao 0037, 0047, 0099, 0104 – 0110, 0119). This dynamic music modification is done iteratively while playing the game (Etanislao 0099)
It would be obvious to one of ordinary skill in the art, at the time of filing, to modify Sumant in view of Etanislao to provide a multiplayer game system that modifies the game multiplayer game session experience wherein the modifications are unique to each particular game player in the session and not rendered or executed for everyone in the game session. Etanislao teaches that “By automating the process of what kind of music is being played and how the music is modulated, the video game may become more immersive, become more enjoyable and provide players with a wide variety of customizable features in order to enhance the overall user experience. (Etanislao 0005)
As per claim 2, Sumant discloses:
determine an expected range of values that the current emotion data associated with the first user is expected to fall within, (Sumant discloses the determination of a range of a degree threshold) (Sumant 0100)
wherein the target emotion data associated with the first user if the current emotion data associated with the first user does not fall within the expected range of values. (Sumant discloses the determination of a target or desired emotion based upon values that correspond (i.e. “These values may be compared separately to corresponding values of the desired emotional state )(Sumant 0100)
As per claim 3, Sumant discloses:
Wherein the expected range of values is determined based on a predetermined range of values. (Sumant discloses the determination of a target or desired emotion based upon values that correspond (i.e. “These values may be compared separately to corresponding values of the desired emotional state )(Sumant 0100), the values being predetermined ranges.
As per claim 4, Sumant discloses:
wherein the expected range of values is determined based on at least one of a genre of the video game and an in-game context of the video game. (Sumant discloses the selecting of a video game configuration based upon the genre of the game such as a horror game and the context wherein it attempts to make the game even scarier for an adult by selecting a predetermined game configuration based upon the desired emotional state)( Sumant 0102).
As per claim 5, Sumant discloses:
receive biometric data associated with two or more other
users of the plurality of users, the two or more other users being different from the first user; generate, based on at least part of the biometric data associated with the two or more other users, current emotion data associated with each of the two or more other users; and determine the expected range of values by performing a statistical analysis on the current emotion data. (Sumant discloses “In some embodiments, a user may play the video game 112 with other users who are in the room or who are elsewhere in the case of network-based multiplayer. In some such embodiments, the processes 300 and/or 400 may determine an aggregate predicted emotional state for the users playing the video game 112. The determination of whether or not to modify the video game 112 may be based at least in part on the aggregate predicted emotional state for the users. Alternatively, or in addition, the determination of whether or not to modify the video game 112 may be based on a majority of the users playing the video game 112. For example, if it is determined that four of six players playing the video game 112 are associated with a negative emotional state, the game configuration system 134 may modify a state or configuration of the video game 112. If on the other hand it is determined, for example, that only one of the six players is associated with a negative emotional state, the game configuration system 134 may determine to not make any changes to the video game 112.” (Sumant 0105)
As per claim 6, Sumant discloses:
wherein the target emotion data associated with the first user is generated based on the expected range of values. (Sumant discloses the selecting of a video game configuration based upon the genre of the game such as a horror game and the context wherein it attempts to make the game even scarier for an adult by selecting a predetermined game configuration based upon the desired emotional state) ( Sumant 0102).
As per claim 7, Sumant discloses:
wherein the determining unit comprises one or more trained determining models that are trained to determine the expected range of values. (Sumant discloses machine learning models that are trained to determine the current emotion state of the user such as if they are happy, sad, frustrated, disgusted, scared or the like (i.e. expected range of values))(Sumant 0064)
As per claim 8, Sumant discloses:
wherein a first trained generating model is trained to generate the current emotion data, and a trained generating model is trained to generate the target emotion data. (Sumant discloses a trained model to determine current emotion data (Suman 0064) and the trained model to determine target emotion data in that it determines if the user is likely to keep playing the game or to “churn” (i.e. stop playing the game) (Sumant 0065).
As per claim 10, Sumant discloses:
wherein the biometric data comprises one or more selected from the list consisting of: i. a galvanic skin response; ii. a heart rate; iii. a breathing rate; iv. a blink rate; v. a metabolic rate; vi. video data; vii. audio data; and viii. one or more input signals. (Sumant 0025)
As per claim 11, Sumant discloses:
wherein the biometric data is received from one or more of: i. a fitness tracking device; ii. a user input device; iii. a camera; and iv. a microphone. (Sumant 0025)
Dependent claim(s) 12 and 13 is/are obvious over Sumant and Etanislao based on the same analysis set forth for claim(s) 1, which are similar in claim scope.
As per claim 15, receiving biometric data associated with two or more other users of the plurality of users, the two or more other users being different from the first user; generating, based on at least part of the biometric data associated with the two or more other users, current emotion data associated with each of the two or more other users; and determining an expected range of values by performing a statistical analysis on the current emotion data, wherein the target emotion data associated with the first user is generated when the current emotion data associated with the first user does not fall within the expected range of values. (Combination of Sumant and Etanislao, wherein Sumant discloses the determination of a target or desired emotion based upon values that correspond (i.e. “These values may be compared separately to corresponding values of the desired emotional state )(Sumant 0100), to corresponding values of desired emotion to the desired emotion data) (Sumant 0100) (Etanislao teaches the use of determining player profiles of multiple players in a multiplayer game session) (Etanislao 0037, 0047, 0099, 0104 – 0110, 0119).
As per claim 16, wherein the biometric data comprises one or more of.i. a galvanic skin response; ii. a heart rate; iii. a breathing rate; iv. a blink rate; v. a metabolic rate; vi. video data; vii. audio data; and viii. one or more input signals. (Sumant 0025)
As per claim 17, wherein the generation of the current emotion data or target emotion data is performed using one or more machine learning models trained on biometric data collected during one or more previously hosted sessions of the video game. (Sumant discloses machine learning models that are trained to determine the current emotion state of the user such as if they are happy, sad, frustrated, disgusted, scared or the like (i.e. expected range of values))(Sumant 0064) Sumant further discloses that the models may be trained on historical data from past plays of the user of the video game) (Sumant 0062 -0063)
As per claim 18, wherein a first trained generating model is trained to generate the current emotion data, and a second trained generating model is trained to generate the target emotion data. (Sumant discloses the using trained models to determine the churn rate and/or the emotional state of the user) (Suman 0065)
As per claim 19, receiving biometric data associated with two or more other users of the plurality of users, the two or more other users being different from the first user; generating, based on at least part of the biometric data associated with the two or more other users, current emotion data associated with each of the two or more other users; and determining an expected range of values by performing a statistical analysis on the current emotion data, wherein the target emotion data associated with the first user is generated when the current emotion data associated with the first user does not fall within the expected range of values. (Combination of Sumant and Stein, wherein Sumant discloses the determination of a target or desired emotion based upon values that correspond (i.e. “These values may be compared separately to corresponding values of the desired emotional state )(Sumant 0100), to corresponding values of desired emotion to the desired emotion data) (Sumant 0100) and Etanislao teaches the use of determining player profiles of multiple players in a multiplayer game session) (Etanislao 0037, 0047, 0099, 0104 – 0110, 0119).
As per claim 20, wherein the biometric data comprises one or more of:i. a galvanic skin response; ii. a heart rate; iii. a breathing rate; iv. a blink rate; v. a metabolic rate; vi. video data; vii. audio data; and viii. one or more input signals. (Sumant 0025)
As per claim 21, wherein the generation of the current emotion data or target emotion data is performed using one or more machine learning models trained on biometric data collected during one or more previously hosted sessions of the video game. (Sumant discloses machine learning models that are trained to determine the current emotion state of the user such as if they are happy, sad, frustrated, disgusted, scared or the like (i.e. expected range of values))(Sumant 0064) Sumant further discloses that the models may be trained on historical data from past plays of the user of the video game) (Sumant 0062 -0063)
As per claim 22, wherein a first trained generating model is trained to generate the current emotion data, and a second trained generating model is trained to generate the target emotion data. (Sumant discloses the using trained models to determine the churn rate and/or the emotional state of the user) (Suman 0065)
Response to Arguments
Applicant’s arguments with respect to claim(s) 1- 8, 10 – 13 and 15 – 22 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 in view of Etanislao.
Applicant’s arguments and corresponding amendments with respect to claim(s) 1- 8, 10 – 13 and 15 – 22 regarding the rejection under 35 U.S.C. 101, has been considered and are persuasive. The rejection has been withdrawn.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ROSS A WILLIAMS whose telephone number is (571)272-5911. The examiner can normally be reached Mon-Fri 8am - 4pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kang Hu can be reached at (571)270-1344. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/RAW/ Examiner, Art Unit 3715
8/20/2026
/KANG HU/ Supervisory Patent Examiner, Art Unit 3715
Prosecution Insights