DETAILED ACTION
Applicant's Submission of a Response
Applicant’s submission of a response on 7/14/2026 has been received and fully considered. In the response, claims 1, 17, 21, and 22 have been amended. Claim 20 was previously canceled. Therefore, claims 1-19, 21, and 22 are 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.
Claims 1-19, 21, and 22 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Application Publication No. 2022/0057865 to Ballagas (Fig. 5 shows below for convenience, but entire reference is relevant as cited) in view of U.S. Patent No. 10,552,752 to Kashyap.
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With regard to claim 1, Ballagas discloses With regard to claim 1, Ballagas discloses a computer-implemented method comprising a user input device (e.g., see Fig. 3A for exemplary user input device; see also paragraph 19 for discussion of various types of input de3vcies, including handheld controllers), the method comprising: determining movement of a user using one or more sensors (e.g., see at least Fig. 5, steps 502 and 504 for using a sensor to determine user movement; see also paragraph 30 for discussion of detecting finger position); predicting an actuation of a user input device that triggers a game event based on the determined movement (e.g., see Fig. 5, step 508 for predicting actuation an input device; see also paragraph 32 for discussion of input device actuation prediction); and outputting an effect that is associated with the predicted actuation of the user input device (e.g., see Fig. 5, step 510 for preemptively propagating selectable option event; see also paragraph 33 for discussion of outputting an effect that associated with the predicted actuation of the user input device);
[claim 2] wherein: the user input device comprises a controller that includes an input element (e.g., see Fig. 3A that shows controller 204 includes input element/selectable options 220; see also paragraph 22 for discussion a controller 204 with input elements 220), and the one or more sensors are configured to determine the movement of the user relative to the input element of the controller (e.g., see Fig. 5, step 508 for predicting actuation an input device; see also paragraph 32 for discussion of input device actuation prediction);
[claim 3] wherein determining the movement of the user relative to the controller comprises determining a movement of a hand of the user relative to the input element (e.g., see at least Fig. 5, steps 502 and 504 for using a sensor to determine user movement; see also paragraph 30 for discussion of detecting finger position);
[claim 4] wherein the one or more sensors comprise at least one of a proximity sensor (e.g., see at least paragraph 12 that discusses that “proximity sensors can be placed on the selectable buttons and/or near the selectable buttons to detect finger or hand position”), a pressure sensor, a motion detector, a capacitive touch sensor, or a galvanic skin response sensor;
[claim 5] wherein the one or more sensors comprise a pressure sensor that is disposed on the controller and that is configured to determine an amount of pressure applied to the input element by the user (e.g., see at least paragraphs 22-23, 30, and 41-42 that discuss sensing a user touching a button, but not yet pressing enough to trigger a direct input; the Examiner notes that Ballagas does not use the term “pressure” but does distinguish between a touch and a press, which defines a difference in force/pressure);
[claim 6] wherein the one or more sensors comprise a proximity sensor or a motion detector that is disposed in an interior of the controller and that is adjacent and transparent to the input element (e.g., see at least paragraph 12 that discusses that “proximity sensors can be placed on the selectable buttons and/or near the selectable buttons to detect finger or hand position”);
[claim 7] wherein the input element is at least one of a button (e.g., see at least paragraph 12 that discusses that “proximity sensors can be placed on the selectable buttons and/or near the selectable buttons to detect finger or hand position”), a trigger, or an analog stick;
[claim 8] wherein: the user input device comprises a user-tracking module that is configured to receive an actuation input when the user is located at a target location (e.g., see at least paragraph 12 that discusses that “proximity sensors can be placed on the selectable buttons and/or near the selectable buttons to detect finger or hand position” which touching the button is a target location); and the sensor is configured to determine the movement of the user to predict the user being located at the target location at a future time (e.g., see Fig. 5, step 508 for predicting actuation an input device; see also paragraph 32 for discussion of input device actuation prediction);
[claim 9] wherein: the user input device comprises an eye-tracking module configured to receive an actuation input when the user looks at a target location (e.g., see at least paragraphs 19 and 23 that discuss the use of “eye-tracking devices”); and the sensor is configured to determine the movement of an eye of the user to predict the user looking at the target location at a future time (e.g., see at least paragraphs 19 and 23 that discuss the use of “eye-tracking devices”);
[claim 10] wherein outputting the effect comprises outputting a pre-emptive effect, prior to actuation of the user input device, based on the predicted actuation of the user input device (e.g., see Fig. 5, step 510 for preemptively propagating selectable option event; see also paragraph 33 for discussion of outputting an effect that associated with the predicted actuation of the user input device);
[claim 11] wherein a magnitude of the pre-emptive effect is based on the determined movement of the user (e.g., see at least paragraphs 14 and 15 that discuss tuning the model to preemptively actuation inputs on different controllers based on various types of sensed activities, which equates to implementing a “magnitude” of the preemptive effect);
[claim 12] wherein a type of the pre-emptive effect is based on the determined movement of the user (e.g., see at least paragraphs 15-16 and 28 that discusses the type of sensed movement);
[claim 13] wherein: the user input device comprises a controller comprising an input element; and a magnitude of the pre-emptive effect varies based on the distance between the user and the input element of the controller (e.g., see at least paragraphs 14 and 15 that discuss tuning the model to preemptively actuation inputs on different controllers based on various types of sensed activities, which equates to implementing a “magnitude” of the preemptive effect);
[claim 14] wherein: the user input device comprises a controller that includes an input element; and a magnitude of the pre-emptive effect varies based on a length of time the user has been within a proximity threshold around the input element of the controller (e.g., see at least paragraph 17 that discusses a time-based weighting for the predictive model);
[claim 15] wherein: the user input device comprises a controller that includes an input element; and the pre-emptive effect is output by the controller (e.g., see Fig. 5, step 510 for preemptively propagating selectable option event; see also paragraph 33 for discussion of outputting an effect that associated with the predicted actuation of the user input device);
[claim 16] wherein: the user input device comprises a user-tracking module that is configured to receive an actuation input when a user is located at a target location; the sensor is configured to determine the movement of the user to predict the user being located at the target location at a future time (e.g., see at least paragraph 12 that discusses that “proximity sensors can be placed on the selectable buttons and/or near the selectable buttons to detect finger or hand position” which touching the button is a target location); and a magnitude of the pre-emptive effect increases as the user moves closer to the target location (e.g., see at least paragraphs 14 and 15 that discuss tuning the model to preemptively actuation inputs on different controllers based on various types of sensed activities, which equates to implementing a “magnitude” of the preemptive effect);
[claim 17] wherein: the user input device comprises an eye-tracking module that is configured to receive an actuation input when a user looks at a target location; the sensor is configured to determine the movement of an eye of the user to predict the user looking at the target location at a future time (e.g., see at least paragraphs 19 and 23 that discuss the use of “eye-tracking devices”); and a magnitude of the pre-emptive effect increases as the eye of the user moves closer to the target location (e.g., see at least paragraphs 14 and 15 that discuss tuning the model to preemptively actuation inputs on different controllers based on various types of sensed activities, which equates to implementing a “magnitude” of the preemptive effect);
[claim 18] wherein outputting the effect comprises: caching the effect prior to actuation of the user input device; and providing, for output, the cached outputting the actuation effect after actuation of the user input device (e.g., see Fig. 5, step 516 that provides outputting the actuation effect after actuation of the user input device; see also paragraph 47 that generally discusses cache memory for temporary storage, which would also be available for preemptive input); and
[claim 19] wherein predicting the future actuation of the user input device based on the determined movement comprises applying a trained machine learning model to the determined movement, wherein the trained machine learning model is configured to output the predicted future actuation from the determined movement (e.g., see at least Fig. 5, step 508 that utilizes a predicts the targeted selectable options(s); see also paragraph 32 that discusses the use of a “machine learning model”).
With regard to claim 1, Ballagas is silent with respect to the type of game output that is associated with the predicted actuation of the user input device. Despite the Examiner’s position that Ballagas’ video game output is very likely, one or more of audio, visual, smell, taste, or haptic feedback, there is a possibility that Ballagas’ game output could be could be temperature, sense of balance, or some other human perceptions. Therefore, the Examiner relies upon a secondary reference to teach what is otherwise typical game play output (e.g., audio, visual, and haptic).
In the same field of endeavor, Kashyap teaches a perceived game play input device that outputs visual and haptic feedback (e.g., see column 10, lines 49-64); visual alerts, audio components, video output, and haptic feedback (e.g., see column 11, lines 41-53); and conventional computer output devices including display output devices, audio output devices, video output devices (e.g., see the paragraph bridging columns 17 and 18).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the current invention to modify Ballagas with audio/video/haptic output as taught by Kashyap in order to use a known technique to improve similar devices (methods, or products) in the same way. In this case, audio/video/haptic output are very commonly used in a wide range of video games, which aids the user in playing the game.
With regard to claims 21 and 22, Ballagas in view of Kashyap make obvious a system and one or more non-transitory computer-readable media that stores instructions to perform the steps analyzed above for claim 1, which is similar in claim scope.
Response to Arguments
Applicant’s arguments with respect to claims 1-19, 21, and 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.
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JAMES S MCCLELLAN whose telephone number is (571)272-7167. The examiner can normally be reached Monday-Friday (8:30AM-5:00PM).
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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.
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/James S. McClellan/Primary Examiner, Art Unit 3715
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