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 .
Status of the Claims
Claims 1-20 are currently pending in the present application, with claims 1, 8, and 15 being independent.
Response to Amendments / Arguments
Applicant’s arguments, see Pg. 12-15, filed 02/18/2026, with respect to the rejection(s) of claim(s) 1-20 under 35 U.S.C § 103 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of newly found prior art.
Regarding the remaining arguments: Applicant argues with respect to the amended claim language, which is fully addressed in the prior art rejections set forth below.
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.
Claim(s) 1-6, 8-13, and 15-19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Jarvela et al. "Augmented virtual reality meditation: Shared dyadic biofeedback increases social presence via respiratory synchrony." ACM Transactions on Social Computing 4, no. 2 (2021): 1-19, hereinafter referred to as “Jarvela”, in view of Tadi et al. (US 20190155386), hereinafter referred to as “Tadi”, and in further view of Muller (US 20190201786).
Regarding claim 1, Jarvela discloses a computer-implemented method for managing a virtual environment context (DYNECOM), the method comprising:
analyzing, by a computing device (Section 3.1 Hardware and Setup…), a plurality of avatars associated with the virtual environment (Fig. 1 and Section 2.2; DYNECOM incorporates EEG-based neurofeedback but adds social dynamics to the environment by having multiple simultaneous users sharing the same VR space),
wherein grouping comprises determining, by the computing device, an affinity associated with the subset based on the scoring (Section 3.3, Pg. 6:7; When the measured EEG states of both users reach the limit of synchrony (within the same 1/10th of their individual current range)…as the system highlights dyadic synchrony, it is visualized even in low approach motivation (suggesting low empathy) cases…The adaptivity results in a system where users showing synchrony of color, meaning them being currently at the same respective percentage of their individual ranges at this moment in the session, even if the raw FA-values (frontal symmetry) differ…Section 4.1; …instructed to concentrate on empathetic, warm, and compassionate feelings and direct them at the statue representing their pair…Section 4.5; synchrony index within each dyad…); and
modifying, by the computing device (Section 3.1 Hardware and Setup…), the virtual environment for the subset in accordance with the virtual environment context based on the analysis (Fig. 1-2 and Section 3.2; Depending on the test condition, the bridge, the scene lights and the aura-like ring surrounding active statues show various visual effects or cues to inform the user of their current state. Scene layout is shown in Figure 1…Section 3.3, Pg. 6:7; In the environment different colors are used to represent the amount of empathy related approach motivation measured with the EEG…Colors are present in all of the lights in the scene…When the measured EEG states of both users reach the limit of synchrony (within the same 1/10th of their individual current range) the glowing effect visualizing this is activated. The glowing effect raises the intensity and brightness of the color…Section 4.1; the different visualizations and color coding in the environment mean (e.g., "When the EEG adaptation is turned on, the color of the bridge and the halo around the statue will change from green (= a little) to pink (= a lot) according to how strongly you are directing the feelings you are aiming to conjure in the exercise towards the opposite statue.") and instructed to concentrate on empathetic, warm, and compassionate feelings and direct them at the statue representing their pair. They were also encouraged to use the information provided by the VR environment to enhance their exercise);
wherein modifying comprises transitioning, by the computing device (Section 3.1 Hardware and Setup…), from a first virtual environment scene to a second virtual environment scene comprising a theme and a plurality of virtual objects reflecting the virtual environment context and the affinity (Fig. 1-2 and Section 4.2; experiment consisted of eight different conditions, each of which included a baseline measure, meditation, and a questionnaire about the meditation experience. The baseline measurement was conducted in a VR-room with an "X" on the wall…After two minutes the VR switched to the meditation environment. Condition scenarios differed based on which adaptions were being used (respiration, EEG, both, or no-biofeedback scenarios) …If the adaptions were active in the scenario, the environment started adapting to the participants' neurophysiological responses after the first 30 seconds. Section 3.2; This immersive setting provides several suitable aspects: It is a relaxed social situation with a shared activity, where nature provides a relaxing background, and the built-in elements balance the wilderness with familiarity. Each session starts by showing a minimalistic room for recording the participant’s baseline neurophysiological activation. It is followed by the meditation environment consisting of six stone statues sitting in a ring on a small shrine-like platform. The platform is surrounded by a short wall and a forest background lit by a cloudy evening sky. Dusk was chosen as scene lighting, as a dark ambience acts as a contrasting background in the visual hierarchy, guiding attention towards the neurofeedback cues and making them easily readable…).
Jarvela does not disclose wherein analyzing the plurality of avatars comprises utilizing electromyography to ascertain a plurality of attributes, wherein electromyography comprises analyzing a plurality of facial muscles derived from at least one computer-mediated reality device associated with the virtual environment and utilizing one or more machine learning models to ascertain the virtual environment context;
ranking, by the computing device, each avatar of the plurality of avatars based on the analysis;
grouping, by the computing device, at least a subset of the avatars based on a scoring of each avatar associated with the ranking;
In the same art of multi-user virtual environment context, Tadi discloses wherein analyzing the plurality of avatars comprises utilizing electromyography to ascertain a plurality of attributes (Par. 0006; facial expression detection according to electromyography (EMG) signals), wherein electromyography comprises analyzing a plurality of facial muscles (Par. 0022; a facial expression determination system for determining a facial expression on a face of a user, comprising an apparatus comprising a plurality of EMG (electromyography) electrodes in contact with the face of the user; a computational device in communication with said electrodes and configured for receiving a plurality of EMG signals from said EMG electrodes, said computational device including a signal processing abstraction layer configured to preprocess said EMG signals to form preprocessed EMG signals; and a classifier configured to receive said preprocessed EMG signals and for classifying the facial expression according to said preprocessed EMG signals; and a training system configured to train said classifier, said training system configured to receive a plurality of sets of preprocessed EMG signals from a plurality of training users, wherein: each set comprising a plurality of groups of preprocessed EMG signals from each training user, each group of preprocessed EMG signals corresponding to a previously classified facial expression of said training user; determine a pattern of variance of for each of said groups of preprocessed EMG signals across said plurality of training users corresponding to each classified facial expression; and compare said preprocessed EMG signals of the user to said patterns of variance to classify the facial expression of the user) derived from at least one computer-mediated reality device associated with the virtual environment (Par. 0349; Computational device 1804 can then be configured so as to provide the classified facial expression, and optionally the video data, to a VR application 1818) and utilizing one or more machine learning models (Par. 0100; neural network and/or machine learning classifiers including but not limited to Bagging classifier, SVM (support vector machine) classifier, NC (node classifier), NCS (neural classifier system), SCRLDA (Shrunken Centroid Regularized Linear Discriminate and Analysis), Random Forest…Par. 0215; At 1004, a machine learning classifier is constructed for training…The classification is matched to the known expressions so as to train the classifier. In some implementations, the determination of what constitutes a neutral expression is also determined. As previously described, before facial expression determination begins, the user is asked to maintain a deliberately neutral expression, which is then analyzed) to ascertain the virtual environment context (Fig. 27 and Par. 0429; playing a game between a plurality of users in a VR environment according to at least some embodiments of the present disclosure. Accordingly, at 2702, the VR game starts, and at 2704, each user makes a facial expression, which is optionally classified (see, e.g., classification methods described herein), and/or a gesture, which is optionally tracked as described herein. At 2706, the facial expression may be used to manipulate one or more game controls, such that the VR application providing the VR environment responds to each facial expression by advancing game play according to the expression that is classified. At 2708, the gesture may be used to manipulate one or more game controls, such that the VR application providing the VR environment responds to each gesture by advancing game play according to the gesture that is tracked).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to combine Jarvela’s DYNECOM system for users in a VR space with Tadi's EMG-based attribute analysis system. The motivation lies in the advantage of improving accuracy of user attribute detection (Tadi Par. 0002; AR/VR hardware (such as AR/VR helmets, headsets, and/or other apparatuses) can obscure portions of a user's face, making it difficult to detect a user's facial expressions while using the AR/VR hardware. Par. 0006; rapid, efficient mechanism for facial expression detection according to electromyography (EMG) signals), allowing more context-aware modification of multi-user virtual environments (Tadi Par. 0432; if the user is showing fatigue in a facial expression, then optionally, VR environment is altered to induce a feeling of greater energy in the user. Par. 0435; game play may be adjusted according to the emotion of the user, for example, by increasing the speed and/or difficulty of game play in response to boredom by the user. At 2914, the effect of the adjustment of game play on the emotion of the user may be monitored. At 2916, the user optionally receives feedback on game play, for example, by indicating that the user was bored at one or more times during game play), enhancing user gameplay (Tadi Par. 0429; advancing game play according to the expression. Par. 0451; the ability of the user to perform such actions may be optionally scored, such scoring may include separate scores for body actions and facial expressions), and overall improving multi-user virtual environments through analysis of user-specific characteristics. While Jarvela adapts the virtual environment based on user state, it relies on indirect physiological signals (e.g., EEG, respiration), which are limited in capturing explicit user expressions, while Tadi’s EMG-based analysis provides a more direct and reliable mechanism for detecting user attributes such as facial expressions and emotional states, particularly in AR/VR environments. Therefore, incorporating Tadi’s EMG-based attribute detection into Jarvela’s neurofeedback techniques would have predictably improved the system’s ability to accurately determine user context and responsively adapt the virtual environment, thereby enhancing user interaction and constitutes a simple substitution of known techniques to obtain more reliable or expressive attributes.
Jarvela in view of Tadi does not disclose ranking, by the computing device, each avatar of the plurality of avatars based on the analysis, and grouping, by the computing device, at least a subset of the avatars based on a scoring of each avatar associated with the ranking.
In the same art of avatar analysis, Muller discloses ranking, by the computing device (Fig. 1B), each avatar of the plurality of avatars based on the analysis (Par. 0142; the system may track character attributes of other characters as well and generate one or more rankings for the characters based on the character attributes. Par. 0230; the system develops rankings of characterizations for players and stores such data…),
grouping, by the computing device (Fig. 1B), at least a subset of the avatars (Fig. 3; group 325. Par. 0142; the system may attempt to identify complementary, for example similar or like-minded characters and/or players or characters or players that otherwise likely enhance the collective gaming experience) based on a scoring of each avatar associated with the ranking (see Par. 0281 on “bonding metric” and Par. 0132; The threshold can represent a statistically determined dividing line between an average among all players, and those players within a predefined category or characterization of players who are statistically more likely than the rest of the players to perform certain actions) based on the plurality of attributes (Par. 0058; the system identifies, determines, analyzes, and/or performs calculations regarding various items of information and/or data associated with users and user characters including characteristics, metrics, criteria, classifications, attributes, etc.).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to incorporate Muller’s ranking and grouping techniques into the combined system of Jarvela and Tadi. Doing so enables structured differentiation and organization of multiple avatars based on their analyzed attributes, yielding predictable results in improved tailoring to virtual environment modifications to specific subsets of users, therefore, providing more efficient and contextually relevant multi-user interactions within the virtual environment.
Regarding claim 2, Jarvela in view of Tadi in further view of Muller discloses the computer-implemented method of claim 1, and further discloses wherein analyzing the plurality of avatars comprises: determining, by the computing device, a sentiment of each avatar of the plurality of avatars (Jarvela Section 3.3, Pg. 6:7; In the environment different colors are used to represent the amount of empathy related approach motivation measured with the EEG…Individual minimum and maximum values of the monitored bio signals are tracked during the session and are used to define the individual's range…Section 4.1; EEG, electrocardiogram (ECG), EDA, and respiration were measured…The experiment consisted of baseline measurement session, meditation activity, and self-reporting. Fig. 3-4 and Section 4.4; To assess their subjective experiences, the participants also rated the three-dimensional emotion scale Valence (how positive or negative the experience was). Arousal (how intense the experience was), and Dominance (how in control they felt) using Self-Assessment Manakins (SAM)…These bi-directional scores were used to calculate empathic accuracy scores, and intersubjective symmetries (ISS) from Social Presence scales); and
scoring, by the computing device, a compatibility of each avatar with the plurality of avatars based on the sentiment (Jarvela Section 3.3, Pg. 6:7; When the measured EEG states of both users reach the limit of synchrony (within the same 1/10th of their individual current range) the glowing effect visualizing this is activated. The glowing effect raises the intensity and brightness of the color…as the system highlights dyadic synchrony, it is visualized even in low approach motivation (suggesting low empathy) cases…The adaptivity results in a system where users showing synchrony of color, meaning them being currently at the same respective percentage of their individual ranges at this moment in the session, even if the raw FA-values (frontal symmetry) differ…Section 4.1; the different visualizations and color coding in the environment mean (e.g., "When the EEG adaptation is turned on, the color of the bridge and the halo around the statue will change from green (= a little) to pink (= a lot) according to how strongly you are directing the feelings you are aiming to conjure in the exercise towards the opposite statue.") and instructed to concentrate on empathetic, warm, and compassionate feelings and direct them at the statue representing their pair. They were also encouraged to use the information provided by the VR environment to enhance their exercise…Section 4.5; synchrony index within each dyad…).
Jarvela, Tadi, and Muller are combined for the reasons set forth above with respect to claim 1.
Regarding claim 3, Jarvela in view of Tadi in further view of Muller discloses the computer-implemented method of claim 1, and further discloses wherein the affinity is derived from an emotional analysis of each avatar in the subset (Jarvela Section 3.3, Pg. 6:7; In the environment different colors are used to represent the amount of empathy related approach motivation measured with the EEG…Individual minimum and maximum values of the monitored bio signals are tracked during the session and are used to define the individual's range…Section 4.1; EEG, electrocardiogram (ECG), EDA, and respiration were measured…The experiment consisted of baseline measurement session, meditation activity, and self-reporting. Fig. 3-4 and Section 4.4; …These bi-directional scores were used to calculate empathic accuracy scores, and intersubjective symmetries (ISS) from Social Presence scales).
Jarvela, Tadi, and Muller are combined for the reasons set forth above with respect to claim 1.
Regarding claim 4, Jarvela in view of Tadi in further view of Muller discloses the computer-implemented method of claim 1, but Jarvela in view of Tadi does not disclose wherein the scoring comprises a threshold correlated to the ranking of each avatar of the plurality of avatars, and the grouping is determined based on a score exceeding the threshold.
In the same art of avatar analysis, Muller discloses wherein the scoring comprises a threshold correlated to the ranking of each avatar of the plurality of avatars (Muller Par. 0132; The threshold can represent a statistically determined dividing line between an average among all players, and those players within a predefined category or characterization of players who are statistically more likely than the rest of the players to perform certain actions…) and the grouping is determined based on a score exceeding the threshold (Muller Par. 0281; analyze which fellow players a given player frequently plays with, the number of communications with particular players, and so forth, to thereby determine whether the given player likes to play only with a certain group of other players or that their play with a certain group of players exceeds a given threshold, communicate with those players beyond a threshold, and so forth…).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to incorporate Muller’s threshold-based scoring into the system of Jarvela and Tadi. Doing so provides a clear and objective criterion for distinguishing between avatars when performing grouping operations. Utilizing a threshold to allow the system to efficiently identify whether objects exceed a defined level is a common technique in the art, therefore using a known technique in the context of identifying subsets of avatars scores enables consistent and scalable grouping decisions based on quantitative measures of user attributes. Such implementation yields predictable results in improved system’s ability to selectively group avatars in a multi-user virtual environment and apply necessary post calculation context-specific modifications.
Regarding claim 5, Jarvela in view of Tadi in further view of Muller discloses the computer-implemented method of claim 3, and further discloses wherein modifying the virtual environment comprises: transitioning, by the computing device, from a first virtual environment scene to a second virtual environment scene based on the analysis (Jarvela Fig. 1-2 and Section 4.2; experiment consisted of eight different conditions, each of which included a baseline measure, meditation, and a questionnaire about the meditation experience. The baseline measurement was conducted in a VR-room with an "X" on the wall…After two minutes the VR switched to the meditation environment. Condition scenarios differed based on which adaptions were being used (respiration, EEG, both, or no-biofeedback scenarios) …If the adaptions were active in the scenario, the environment started adapting to the participants' neurophysiological responses after the first 30 seconds).
wherein the second virtual environment scene is rendered based on the affinity associated with the subset (Jarvela Fig. 1-2 and Section 4.2; Condition scenarios differed based on which adaptions were being used (respiration, EEG, both, or no-biofeedback scenarios) …If the adaptions were active in the scenario, the environment started adapting to the participants' neurophysiological responses after the first 30 seconds. Section 3.2; Each session starts by showing a minimalistic room for recording the participant’s baseline neurophysiological activation. It is followed by the meditation environment consisting of six stone statues sitting in a ring on a small shrine-like platform…guiding attention towards the neurofeedback cues and making them easily readable…).
Jarvela, Tadi, and Muller are combined for the reasons set forth above with respect to claim 1.
Regarding claim 6, Jarvela in view of Tadi in further view of Muller discloses the computer-implemented method of claim 5, and further discloses wherein the second virtual environment scene comprises a shared theme for the avatars of the subset in accordance with the affinity (Jarvela Section 4.1; the different visualizations and color coding in the environment mean (e.g., "When the EEG adaptation is turned on, the color of the bridge and the halo around the statue will change from green (= a little) to pink (= a lot) according to how strongly you are directing the feelings you are aiming to conjure in the exercise towards the opposite statue.") and instructed to concentrate on empathetic, warm, and compassionate feelings and direct them at the statue representing their pair. They were also encouraged to use the information provided by the VR environment to enhance their exercise. Examiner's note: shared theme is the meditation environment color visualization).
Jarvela, Tadi, and Muller are combined for the reasons set forth above with respect to claim 1.
Regarding claims 8 and 15, claim 8 is the CRM claim (Jarvela Section 3.1 Hardware and Setup…) and claim 15 is the system claim (Jarvela Section 3.1 Hardware and Setup…) of method claim 1, and is accordingly rejected using substantially similar rationale as to that which is set for with respect to claim 1.
Regarding claims 9 and 16, claims 9 and 16 has similar limitations as of claim 2, except claim 9 is the computer program product comprising a CRM claim (Jarvela Section 3.1 Hardware and Setup…) and claim 16 is the system claim (Jarvela Section 3.1 Hardware and Setup…) to the method claim 2, therefore it is rejected under the same rationale as claim 2.
Regarding claims 11 and 18, claims 11 and 18 has similar limitations as of claim 4, except claim 11 is the computer program product comprising a CRM claim (Jarvela Section 3.1 Hardware and Setup…) and claim 18 is the system claim (Jarvela Section 3.1 Hardware and Setup…) to the method claim 4, therefore it is rejected under the same rationale as claim 4.
Regarding claims 10 and 17, claims 10 and 17 has similar limitations as of claim 3, except claim 10 is the computer program product comprising a CRM claim (Jarvela Section 3.1 Hardware and Setup…) and claim 17 is the system claim (Jarvela Section 3.1 Hardware and Setup…) to the method claim 3, therefore it is rejected under the same rationale as claim 3.
Regarding claims 12 and 19, claims 12 and 19 has similar limitations as of claim 5, except claim 12 is the computer program product comprising a CRM claim (Jarvela Section 3.1 Hardware and Setup…) and claim 19 is the system claim (Jarvela Section 3.1 Hardware and Setup…) to the method claim 5, therefore it is rejected under the same rationale as claim 5.
Regarding claim 13, claims 13 has similar limitations as of claim 6, except claim 13 is the computer program product comprising a CRM claim (Jarvela Section 3.1 Hardware and Setup…) to the method claim 6, therefore it is rejected under the same rationale as claim 6.
Claim(s) 7, 14, and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Jarvela et al. "Augmented virtual reality meditation: Shared dyadic biofeedback increases social presence via respiratory synchrony." ACM Transactions on Social Computing 4, no. 2 (2021): 1-19, hereinafter referred to as “Jarvela”, in view of Tadi et al. (US 20190155386), hereinafter referred to as “Tadi”, in further view of Muller (US 20190201786), and in further view of Allen et. al. (US 9779327), hereinafter referred to as “Allen”.
Regarding claim 7, Jarvela in view of Tadi in further view of Muller discloses the computer-implemented method of claim 1, but does not disclose analyzing, by the computing device, a plurality of social media profiles of a plurality of users associated with the plurality of avatars, and extracting, by the computing device, social media characteristics of the plurality of users from the plurality of social media profiles.
In the same art of avatar similarity matching, Allen discloses analyzing, by the computing device (Computing devices 104), a plurality of social media profiles of a plurality of users associated with the plurality of avatars (Column 14, lines 28-35; The cognitive traits avatar system 150 generates a dynamically changing cognitive trait avatar which provides an intuitive and elegant visualization of a person's personality trait-balance versus personality trait-dominance. In one illustrative embodiment, this visualization is dynamically adjusted based on a user's social media presence as the user's social media presence changes over time) and
extracting, by the computing device (Computing devices 104), social media characteristics of the plurality of users from the plurality of social media profiles. (Column 15, lines 2-12; Through analysis of current interactions (i.e. within a defined moving window of text or number of interactions) and/or a history of interactions with a social networking website, or plurality of social networking websites, or other systems/services that provide electronic communication in a textual format, voice-to-text format, or the like, the cognitive traits avatar system 150 is configured to extract features from these interactions and correlate the features with cognitive traits to help define a representation of the user's personality, i.e. the collection of cognitive traits).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to incorporate the social-media based avatar analysis, as taught by Allen, into the combined augmented reality system of Jarvela, Tadi, and Muller. The motivation lies in the advantage of providing relevant attributes to an avatar’s character for further improved ranking and grouping accuracy. Because social media presence and activity is very prevalent, integrating social media profile data into avatar systems yields predictable improvement in avatar personalization and scoring.
Regarding claims 14 and 20, claims 14 and 20 has similar limitations as of claim 7, except claim 14 is the computer program product comprising a CRM claim (Jarvela Section 3.1 Hardware and Setup…) and claim 20 is the system claim (Jarvela Section 3.1 Hardware and Setup…) to the method claim 7, therefore it is rejected under the same rationale as claim 7.
Conclusion
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/JENNY N TRAN/Examiner, Art Unit 2615 /ALICIA M HARRINGTON/Supervisory Patent Examiner, Art Unit 2615
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