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 .
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 (i.e., changing from AIA to pre-AIA ) 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 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.
Claim(s) 1-7 and 9-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kwatra (US 2022.0001238).
Regarding claim 1, Kwatra disclose:
A computer-implemented method comprising: determining, by a collaboration mode transition engine, based on biometrics data and behavioral data, a cognitive level of a user associated with a first collaboration mode in a plurality of collaboration modes; determining, by the collaboration mode transition engine, based on collaboration mode usage data associated with the first collaboration mode, a cognitive level threshold of the user for the first collaboration mode (see Fig 2-3; [0026, 0048-0061]; a reactive performance of method 200 with user indication of an AR workout (e.g., first collaboration mode); determine the cognition level of user based on biometric and behavioral l data; determine (scoring) cognitive level associated with ‘first’ area workout at S206).
While in method 200 the determined cognitive level determines the first collaboration mode, it is not explicit as the transition to the second collaboration mode. However, Fig. 3 of Kwatra discloses:
selecting, by the collaboration mode transition engine, responsive to a determination that the cognitive level exceeds the cognitive level threshold, a second collaboration mode in the plurality of collaboration modes; and transitioning, by the collaboration mode transition engine, to the second collaboration mode (see Fig. 3; changes during first collaboration mode to cognitive score indicate a threshold has been exceed. Thus the change triggers a transition to a second (modified) workout (e.g., second collaborative mode).
Therefore, it would have been obvious to one of ordinary skill in the art, prior to the effective filing date of applicant’s invention, to combine the known techniques of Kwarta of Fig. 3’s embodiment to that of Fig. 2’s embodiment, to predictably provide a device to automatically keep the user focused ([0058]).
Regarding claim 2, the rejection of claim 1 is incorporated herein. Kwarta further disclose:
the collaboration mode transition engine comprises a machine learning model trained to determine the cognitive level threshold based on a plurality of cognitive level thresholds from a plurality of users and trained to determine the cognitive level based on a plurality of cognitive levels from the plurality of users, further comprising: applying the machine learning model to the collaboration mode usage data to determine the cognitive level threshold of the user; and applying the machine learning model to the biometrics data and behavioral data to determine the cognitive level of the user (see [0051]).
Regarding claim 3, the rejection of claim 1 is incorporated herein. Kwarta further disclose:
translating a user interaction of a second user to the second collaboration mode (see [0073, 0078]).
Regarding claim 4, the rejection of claim 1 is incorporated herein. Kwarta further disclose:
the second collaboration mode is a virtual reality collaboration mode, and wherein transitioning to the second collaboration mode further comprises: creating a virtual reality collaboration environment; and initiating a virtual reality collaboration in the virtual reality collaboration environment (see [0027]).
Regarding claim 5, the rejection of claim 4 is incorporated herein. Kwarta further disclose:
generating a virtual reality avatar associated with a second user interacting with a third collaboration mode; translating a user interaction of the second user in the third collaboration mode to the virtual reality collaboration environment; and updating, based on the translating, the virtual reality avatar of the second user (see [0073]; avatars of other users in VR space where this is the ‘third’ collaboration mode; and where the translation is the emulation of user movements).
Regarding claim 6, the rejection of claim 1 is incorporated herein. Kwarta further disclose:
predicting a recovery time for the user; and remaining in the second collaboration mode for at least the recovery time (see [0059-0061] where the recovery time is where system predicts a modification is necessary and shifts to a ‘second’ (modified) collaboration mode).
Regarding claim 7, the rejection of claim 1 is incorporated herein. Kwarta further disclose:
identifying a plurality of devices associated with the user; identifying a plurality of collaboration applications from the plurality of devices; and identifying the plurality of collaboration modes from the plurality of collaboration applications (see [0068]; varying equipment (devices) can be used when presenting or modifying the workouts (collaborations)).
Regarding claim 9, the rejection of claim 1 is incorporated herein. Kwarta further disclose:
the biometrics data includes at least one of heart rate data, breathing rate data, and facial expression data (see [0026]).
Regarding claim 10, claim 10 is rejected under the same rationale as claim 1, where Kwara further disclose: A computer program product comprising one or more computer readable storage media, and program instructions collectively stored on the one or more computer readable storage media, the program instructions executable by a processor to cause the processor to perform operations (see Fig. 4; [0081-0083]; *note claim 10 and similarly claim 16 are being read in light [0056] of applicant’s PG Pub with respect to 35 USC 101 – such that it is clear the storage media cannot be described as transitory).
Regarding claims 11-20, claims 11-20 are rejected under the same rationale as claims 2-7, 10, and 2-6, respectively.
Claim(s) 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kwarta in view of Yildiz (US 2021.0096646).
Regarding claim 8, the rejection of claim 1 is incorporated herein. Kwarta is not explicit as to, but Yildiz disclose:
the behavioral data includes at least one of response time data, response accuracy data, and distraction data (see [0055]; behavioral data to include distractions).
Therefore, it would have been obvious to one of ordinary skill in the art, prior to the effective filing date of applicant’s invention, to combine the known techniques of Yildiz to that of Kwarta to predictably allow the system to recommend breaks or detect fatigue of the user ([0054]).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KENNETH BUKOWSKI whose telephone number is (571)270-7913. The examiner can normally be reached Monday - Friday // 0730-1530.
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/kenneth bukowski/ Primary Examiner, Art Unit 2621
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