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 .
Response to Amendment
Claims 1-20 were previously pending in this application. The amendment filed 10 April 2026 has been entered and the following has occurred: Claims 1, 12, & 19 have been amended. No claims have been cancelled or added.
Claims 1-20 remain pending in the application.
Affidavits/Declaration
The declarations under 37 CFR 1.132 filed 10 April 2026 are insufficient to overcome the rejections of claims 1-20 based upon the claims being directed towards patent-ineligible subject matter under 35 U.S.C. 101 as set forth in the last Office action because: While Applicant argues in view of new precedents set forth by Desjardins, i.e. “When viewed as a whole, the claims recite a specific machine architecture that senses physiological signals, maintains individualized neurophysiological response histories, and controls environment-embedded devices to deliver adaptive biofeedback. This is a technical system for controlling physical environments based on physiological state, not an abstract idea implemented on a computer. The Applicant submits that the specification and claims are an improvement to a “the functioning of a computer, or an improvement to other technology or a technical field.” MPEP § 2106,04(d)(1)(i.e., as revised post-Desjardins) Accordingly, the claims are patent-eligible under Section 101”. While Applicant argues that the claims recite a specific machine architecture that senses physiological signals, maintains individualized neurophysiological response histories, and controls environment-embedded devices to deliver adaptive biofeedback, Examiner argues that this is not necessarily an improvement over prior art systems that perform the same or similar functions. That is, while Examiner generally agrees that in light of Desjardins, that a software algorithm itself can constitute an improvement, the aspects claimed do not necessarily relate to an improvement over other software/algorithms that perform the same or substantially similar aspects described in prior art systems. For instance, Ashgar and Lake-Schaal disclose the described aspects of senses physiological signals, maintains individualized neurophysiological response histories, and controls environment-embedded devices to deliver adaptive biofeedback. There are no indications that the current steps go beyond the already-established software found in prior art systems, such as by Applicant’s purported “contextual training”, i.e. teaching physiological self-regulation of the user in the very context in which the self-regulated behavior is desired to take place. That is, while Applicant generally argues that the system delivering psychophysiological feedback is configured to train self-regulation improves biofeedback training technology itself by enabling pervasive, environment-integrated training, this does not necessarily reflect a technological improvement versus an improvement to the way that the user self-regulates based on outputs delivered by the system such as by adding context to said determinations. Therefore, the declarations are insufficient to overcome previous 35 U.S.C. 101 rejections of claims 1-20 based upon the claims still being directed towards patent-ineligible subject matter.
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.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
The claims recite subject matter within a statutory category as a process (claims 12-18), machine (claims 1-11 & 19-20) which recite steps of:
receive, from at least one electronic device of the plurality of electronic devices, a first signal associated with a first physiological response of the user;
determine, based on the first signal, an estimate of a state of the user by comparing the first signal to a historical record of the user's neurophysiological responses to cognitive and/or emotional state-inducing environmental stimuli or generic norm patterns for the group that the user belongs to; and
cause, based on the estimate of the state of the user, presentation of an electronic representation of a personalized psychophysiological stimuli via a second electronic device embedded in an environment local to the user and distinct from a wearable or handheld device used by the user, wherein the personalized psychophysiological stimuli comprises psychophysiological feedback configured to encourage neurophysiological self-regulation by the user and is personalized based on the historical record and real-time responses of the user or generic norm patterns for the group that the user belongs to.
These steps of receiving a first signal associated with a physiological response of the user, determining, based on the signal, an estimate of a state of the user such as by comparing signals to a historical record of the user, and causing, based on the estimate of the state of the user, presentation of a personalized psychophysiological stimuli, as drafted, under the broadest reasonable interpretation, includes performance of the limitation in the mind but for recitation of generic computer components. That is, other than reciting steps as performed by the generic computer components, nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the receiving a first signal associated with a physiological response of the user language, receiving a signal in the context of this claim encompasses a mental process of a person or entity either collecting physiological response data from the user, such as via observation, or receiving the data from a medium that the person or entity is using. Similarly, the limitation of determining an estimate of a state of the user based on the collected signal and comparing the first signal to a historical record of the user's neurophysiological responses to cognitive and/or emotional state-inducing environmental stimuli, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, such as a person or entity diagnosing the user based on the collected physiological response data and known patient/user historical data. For example, but for the causing presentation of representation of a personalized psychophysiological stimuli language, presentation of stimuli in the context of this claim encompasses a mental process of a human or entity choosing content to output to a user given the user’s psychological or physiological state. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
These steps of receiving a first signal associated with a physiological response of the user, determining, based on the signal, an estimate of a state of the user such as by comparing signals to a historical record of the user, and causing, based on the estimate of the state of the user, presentation of a personalized psychophysiological stimuli, as drafted, under the broadest reasonable interpretation, includes Methods of Organizing Human Activity (MOHA). MPEP 2106.04(a)(2)(II) sets forth various MOHA, including fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts, legal obligations, advertising, marketing or sales activities or behaviors, and business relations); and managing personal behavior or relationships or interactions between people, (including social activities, teaching, and following rules or instructions). The steps recited substantially relate to determining a state of a user, based on the state of the user, presenting certain content to the user, such as content that encourages neurophysiological self-regulation by the user and is personalized based on the historical record and real-time responses of the user. Therefore, the typical user behavior and/or interaction between the user and content/system that the user is interacting with is effectively being managed. At an even higher level, the steps recited at least relate to managing the activity of the user regarding the state of the user. That is, a certain amount or type of content is outputted to a user to either maintain or change a state of a user. Therefore, these aspects of managing the typical user behavior and/or interaction between the user and content/system and/or managing the activity of the user regarding the state of the user effectively amounts to MOHA. Accordingly, the claim recites an abstract idea.
Dependent claims recite additional subject matter which further narrows or defines the abstract idea embodied in the claims (such as claims 2-11, 13-18, & 20, reciting particular aspects of how the signal may be collected or how the representation may be outputted may be performed in the mind but for recitation of generic computer components).
This judicial exception is not integrated into a practical application. In particular, the additional elements do not integrate the abstract idea into a practical application, other than the abstract idea per se, because the additional elements amount to no more than limitations which:
amount to mere instructions to apply an exception (such as recitation of a one or more electronic devices, a processor, a memory, a physiological sensor, a smart watch, and a smart phone amounts to invoking computers as a tool to perform the abstract idea, see Applicant’s Specification [0007] for one or more electronic devices, [0054] for a processor, [0048] for a memory, [0014] for a physiological sensor, [0014] for a smart watch, [0042] for a smart phone, see MPEP 2106.05(f));
add insignificant extra-solution activity to the abstract idea (such as recitation of receiving, from at least one electronic device of the plurality of electronic devices amounts to mere data gathering, recitation of determine, based on the first signal, an estimate of a state of the state of the user, comparing the first signal to a historical record of the user's neurophysiological responses to cognitive and/or emotional state-inducing environmental stimuli or generic norm patterns for the group that the user belongs to, and personalizing psychophysiological stimuli according to historical records and real-time responses of the user amounts to selecting a particular data source or type of data to be manipulated, recitation of cause, based on the estimate of the state of the user, presentation of an electronic representation of a personalized psychophysiological stimuli via a second electronic device embedded in an environment local to the user, comparing the first signal to a historical record of the user's neurophysiological responses to cognitive and/or emotional state-inducing environmental stimuli or generic norm patterns for the group that the user belongs to amounts to insignificant application, see MPEP 2106.05(g));
generally link the abstract idea to a particular technological environment or field of use (such as recitation of a biocybernetics adaptation and biofeedback and/or encouraging neurophysiological self-regulation by the user, see MPEP 2106.05(h)).
Dependent claims recite additional subject matter which amount to limitations consistent with the additional elements in the independent claims (such as claims 2-11, 13-18, & 20, which recite one or more electronic devices, a vehicle, an electronic gaming system, virtual reality display, additional limitations which amount to invoking computers as a tool to perform the abstract idea; claims 2, 6, 12, & 16, which recite limitations relating to sending a signal with the estimate of the state of the user, generating a signal associated with a physiological state experienced by the user, additional limitations which add insignificant extra-solution activity to the abstract idea which amounts to mere data gathering; claims 3, 10, 13, 18, & 20, which recite limitations relating to generating or estimating the determined state and generating one or more feedbacks additional limitations which add insignificant extra-solution activity to the abstract idea by selecting a particular data source or type of data to be manipulated; claims 2-11, 13-18, & 20, which recite limitations relating to a particular cognitive state, emotional state, electronic systems, and/or devices to be used such as to display or present content, i.e. additional limitations which generally link the abstract idea to a particular technological environment or field of use). 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 and do not impose a meaningful limit to integrate the abstract idea into a practical application.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to discussion of integration of the abstract idea into a practical application, the additional elements amount to no more than mere instructions to apply an exception, add insignificant extra-solution activity to the abstract idea, and generally link the abstract idea to a particular technological environment or field of use. Additionally, the additional limitations, other than the abstract idea per se, amount to no more than limitations which:
amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields (such as receiving, from at least one electronic device of the plurality of electronic devices, e.g., receiving or transmitting data over a network, Symantec, MPEP 2106.05(d)(II)(i); determine, based on the first signal, an estimate of a state of the state of the user, presentation of an electronic representation of a personalized psychophysiological stimuli via a second electronic device embedded in an environment local to the user, comparing the first signal to a historical record of the user's neurophysiological responses to cognitive and/or emotional state-inducing environmental stimuli or generic norm patterns for the group that the user belongs to, e.g., performing repetitive calculations, Flook, MPEP 2106.05(d)(II)(ii); maintain one or more states of the user and associated electronic representations of personalized psychophysiological stimuli, e.g., electronic recordkeeping, Alice Corp., MPEP 2106.05(d)(II)(iii); storing computerized instructions for performance of the steps recited, e.g., storing and retrieving information in memory, Versata Dev. Group, MPEP 2106.05(d)(II)(iv); personalized psychophysiological stimuli comprises psychophysiological feedback configured to encourage neurophysiological self-regulation by the user and is personalized based on the historical record and real-time responses of the user or generic norm patterns for the group that the user belongs to, e.g. gathering and analyzing information using conventional techniques and displaying the result, TLI Communications, MPEP 2106.05(a)(II)).
Dependent claims recite additional subject matter which, as discussed above with respect to integration of the abstract idea into a practical application, amount to invoking computers as a tool to perform the abstract idea. Dependent claims recite additional subject matter which amount to limitations consistent with the additional elements in the independent claims (such as claims 2-11, 13-18, & 20, additional limitations which amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields, claims 2, 6, 12, & 16, which recite limitations relating to sending a signal with the estimate of the state of the user, generating a signal associated with a physiological state experienced by the user, e.g., receiving or transmitting data over a network, Symantec, MPEP 2106.05(d)(II)(i); claims 3, 10, 13, 18, & 20, which recite limitations relating to generating or estimating the determined state and generating one or more feedbacks, e.g., performing repetitive calculations, Flook, MPEP 2106.05(d)(II)(ii); claims 2-10, 13-18, & 20, which recites limitations relating to storing computerized instructions for performance of the steps recited, storing one or more psychophysiological states of the user, etc., e.g., storing and retrieving information in memory, Versata Dev. Group, MPEP 2106.05(d)(II)(iv); claims 2-11, 13-18, & 20, which recite limitations relating to a particular cognitive state, emotional state, electronic systems, and/or devices to be used such as to display or present content, gathering and analyzing information using conventional techniques and displaying the result, TLI Communications, MPEP 2106.05(a)(II)(iii)). 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.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable by Ashgar et al. (U.S. Patent Publication No. 2023/0106673), hereinafter “Ashgar”, in view of Lake-Schaal et al. (U.S. Patent Publication No. 2024/0335738), hereinafter “Lake-Schaal”.
Claim 1 –
Regarding Claim 1, Ashgar discloses a biocybernetics adaptation and biofeedback training system comprising:
a plurality of electronic devices associated with a user (See Ashgar Par [0013] which discloses one or more wearable devices and/or mobile devices that record one or more health measurements, i.e. physiological response of the user, thereby associated with the user), wherein
each electronic device of the plurality of electronic devices generate a signal associated with a physiological response of the user (See Ashgar Par [0013] which discloses one or more wearable devices and/or mobile devices that record one or more health measurements, i.e. physiological responses of the user, including heart rate, blood pressure, body temperature, galvanic skin response, a measurement of an electric signal from a heart of the occupant, a measurement of electrical activity of a brain of the occupant, etc. in order to determine a state of the occupant);
a computing device comprising:
at least one processor (See Ashgar Par [0110] which discloses the vehicle computing system including at least one processor);
memory storing instructions that, when executed by the at least one processor, cause the computing device (See Ashgar Par [0110] which discloses the vehicle computing system including at least one processor and instructions stored in or one at least one memory to perform one or more of the functions of operations described throughout Ashgar) to:
receive, from at least one electronic device of the plurality of electronic devices, a first signal associated with a first physiological response of the user (See Ashgar Par [0013] which discloses one or more wearable devices and/or mobile devices that record one or more health measurements, including heart rate, blood pressure, body temperature, galvanic skin response, a measurement of an electric signal from a heart of the occupant, a measurement of electrical activity of a brain of the occupant, etc. in order to determine a state of the occupant; See Ashgar Par [0121] which discloses a vehicle computing system obtaining, i.e. via sending or transmission, sensor data from the sensor systems on the vehicle or attached to the one or more occupants/mobile devices);
determine, based on the first signal, an estimate of a state of the user by comparing the first signal to a historical record of the user's neurophysiological responses to cognitive and/or emotional state-inducing environmental stimuli or generic norm patterns for the group that the user belongs to (See Ashgar Par [0010]-[0013] which discloses determining, i.e. determining an estimate, of a state of the user by receiving data associated with the one or more sensors of the vehicle and/or health sensors of the user; See Ashgar Par [0062] & [0068] which discloses the machine learning classifier being trained on positive and negative examples to determine a typical state of status of a vehicle, person, etc., albeit not recited for a “historical record” per se; See Ashgar Par [0154] which discloses determining state of the occupant a driving pattern of the occupant; See Ashgar Par [0147] which discloses monitoring an occupant associated with a mobile device and detecting a state of the occupant of a vehicle based on various aspects of occupant; See Ashgar Par [0044] which discloses one or more virtual reality systems facilitating interactions with VR environments and possibly combining real-world or physical environments and virtual environments to provide users with XR or VR experiences, and is thereby understood to constitute “embedding” said system; See Ashgar Par [0206] which discloses a machine learning classifier trained on positive and negative examples, i.e. historical data, including various cognitive, e.g. drowsiness, and/or emotional states, such that the state estimate would be determined based on comparison of current data to said historical data at least by the use of the learning model that is trained on said historical data, albeit not recited for a “historical record” per se); and
cause, based on the estimate of the state of the user, presentation of an electronic representation of a personalized psychophysiological stimuli via a second electronic device embedded in an environment local to the user and distinct from a wearable or handheld device used by the user (See Ashgar Par [0024] the apparatuses can include, be part of, and/or interfaced with a vehicle, a mobile device, a wearable device, a personal computer, a laptop computer, a tablet computer, a server computer, a robotics device or system, an aviation system, or other device, thereby pointing towards these apparatuses possibly being devices other than mobile devices, and in the case of the devices interfacing with a vehicle, would thereby include a second device embedded in an environment local to the user when said user is in the vehicle; While not “embedded” per se, see Ashgar Par [0044] which discloses one or more virtual reality systems facilitating interactions with VR environments and possibly combining real-world or physical environments and virtual environments to provide users with XR or VR experiences, and is thereby understood to constitute “embedding” said system; See Ashgar Par [0319] which discloses the associated output devices being one or more of a display, projector, television, speaker device, etc.; See Ashgar Par [0174]-[0175] which discloses an AR application modulating virtual content, i.e. psychophysiological stimuli under BRI, by controlling virtual content being presented, when the content is presented, where the content is presented, and one or more characteristics of the virtual content presented, based on the state of the occupant, which is understood by Examiner to constitute a “personalized” stimuli since the content presented is based on the determined state of the occupant which is based on a trained machine learning model using historical data, being compared to real-time responses of the user, albeit not recited for being based on a “historical record” per se), wherein the personalized psychophysiological stimuli comprises psychophysiological feedback configured to encourage neurophysiological self-regulation by the user and is personalized based on the historical record and real-time responses of the user or generic norm patterns for the group that the user belongs to (See Ashgar Par [0062] & [0068] which discloses the machine learning classifier being trained on positive and negative examples to determine a typical state of status of a vehicle, person, etc., albeit not recited for a “historical record” per se; See Ashgar Par [0154] which discloses determining state of the occupant a driving pattern of the occupant; See Ashgar Par [0174]-[0175] which discloses an AR application modulating virtual content, i.e. psychophysiological stimuli under BRI, by controlling virtual content being presented, when the content is presented, where the content is presented, and one or more characteristics of the virtual content presented, based on the state of the occupant, which is understood by Examiner to constitute a “personalized” stimuli since the content presented is based on the determined state of the occupant which is based on a trained machine learning model using historical data, being compared to real-time responses of the user, albeit not recited for being based on a “historical record” per se; additionally, “to encourage neurophysiological self-regulation by the user and is personalized based on the historical record and real-time responses of the user or generic norm patterns for the group that the user belongs to” effectively amounts to an intended result of a method step positively recited and does not hold patentable weight (See MPEP 2111.04(I))).
While Ashgar Par [0062] & [0068] discloses the machine learning classifier being trained on positive and negative examples to determine a typical state of status of a vehicle, person, etc., Ashgar does not explicitly recite said data/statuses in the form of a “historical record” per se as given by the following limitations:
comparing the first signal to a historical record of the user's neurophysiological responses to cognitive and/or emotional state-inducing environmental stimuli or generic norm patterns for the group that the user belongs to
the personalized psychophysiological stimuli comprises psychophysiological feedback configured to encourage neurophysiological self-regulation by the user and is personalized based on the historical record and real-time responses of the user or generic norm patterns for the group that the user belongs to
However, Lake-Schaal discloses comparing the first signal to a historical record of the user's neurophysiological responses to cognitive and/or emotional state-inducing environmental stimuli and the personalized psychophysiological stimuli comprises psychophysiological feedback configured to encourage neurophysiological self-regulation by the user and is personalized based on the historical record (See Lake-Schaal Par [0078] which discloses application state data including records of user interactions with an application or other application inputs, outputs, or internal states of the user; See Lake-Schaal Par [0103] which discloses storing data structures of self-associated records each including a unique identifier, duration value of a content segment, one or more semantic tags relevant to passenger profile or user profile data, technical metadata as needed to select, configure or produce an interactive media content or a video that includes the content component or video clips identified by the identifier). The disclosure of Lake-Schaal is directly applicable to the disclosure of Ashgar, because the disclosures share limitations and capabilities, such as being directed towards delivery of content to one or more users based on the states of the user, especially in vehicular environments.
It would have been obvious to one of ordinary skill in the effective filing date of the claimed invention to modify the disclosure of Ashgar which already discloses the machine learning classifier being trained on positive and negative examples to determine a typical state of status of a vehicle, person, etc. to further specifically include the data that the learning algorithm is trained on is a historical record, per se, as disclosed by Lake-Schaal, because maintaining one or more data structures of self-associated records each including a unique identifier, duration value of a content segment, one or more semantic tags relevant to passenger profile or user profile data allows for selection, configuration or production an interactive media content or a video that includes the content component or video clips based on the maintained record (See Lake-Schaal Par [0103]).
Claim 2 –
Regarding Claim 2, Ashgar and Lake-Schaal disclose the system of claim 1 in its entirety. Ashgar further discloses a system, wherein:
the state of the user comprises one or both of a cognitive state and emotional state (See Ashgar Par [0148] which discloses the state of the user comprising one or more cognitive states and/or emotional states).
Claim 3 –
Regarding Claim 3, Ashgar and Lake-Schaal disclose the system of claim 1 in its entirety. Ashgar further discloses a system, wherein:
the instructions further cause the computing device to send, to the second electronic device embedded in the environment local to the user, a signal associated with the estimate of the state of the user (See Ashgar Par [0110] which discloses the vehicle computing system including at least one processor and instructions stored in or one at least one memory to perform one or more of the functions of operations described throughout Ashgar; While not “embedded” per se, see Ashgar Par [0121] which discloses a vehicle computing system obtaining, i.e. via sending or transmission, sensor data from the sensor systems on the vehicle or attached to the one or more occupants/mobile devices. such that these systems or devices are understood to be “embedded”; See Ashgar Par [0125] which discloses a vehicle computing system that includes any of the sensor data and/or data generated based on the sensor data, such that a description of information in the sensor data can be generated by the vehicle computing system).
Claim 4 –
Regarding Claim 4, Ashgar and Lake-Schaal disclose the system of claim 1 in its entirety. Ashgar further discloses a system, wherein:
the plurality of electronic devices associated with the user comprises a smart phone (See Ashgar Par [0024] & [0073] which discloses one or more sensor systems and/or devices, such as a smart phone, smart watch, or the like, for collecting and/or outputting data/content associated with a user).
Claim 5 –
Regarding Claim 5, Ashgar and Lake-Schaal disclose the system of claim 1 in its entirety. Ashgar further discloses a system, wherein:
the plurality of electronic devices associated with the user comprises a one or more physiological sensor devices (See Ashgar Par [0013] which discloses one or more wearable devices and/or mobile devices that record one or more health measurements, including heart rate, blood pressure, body temperature, galvanic skin response, a measurement of an electric signal from a heart of the occupant, a measurement of electrical activity of a brain of the occupant, etc. in order to determine a state of the occupant; See Ashgar Par [0110] which discloses the vehicle computing system including at least one processor and instructions stored in or one at least one memory to perform one or more of the functions of operations described throughout Ashgar; See Ashgar Par [0121] which discloses a vehicle computing system obtaining, i.e. via sending or transmission, sensor data from the sensor systems on the vehicle or attached to the one or more occupants/mobile devices; See Ashgar Par [0125] which discloses a vehicle computing system that includes any of the sensor data and/or data generated based on the sensor data, such that a description of information in the sensor data can be generated by the vehicle computing system).
Claim 6 –
Regarding Claim 6, Ashgar and Lake-Schaal disclose the system of claim 5 in its entirety. Ashgar further discloses a system, wherein:
at least one physiological sensor device generates a signal associated with a physiological state experienced by the user (See Ashgar Par [0013] which discloses one or more wearable devices and/or mobile devices that record one or more health measurements, including heart rate, blood pressure, body temperature, galvanic skin response, a measurement of an electric signal from a heart of the occupant, a measurement of electrical activity of a brain of the occupant, etc. in order to determine a state of the occupant; See Ashgar Par [0110] which discloses the vehicle computing system including at least one processor and instructions stored in or one at least one memory to perform one or more of the functions of operations described throughout Ashgar; See Ashgar Par [0121] which discloses a vehicle computing system obtaining, i.e. via sending or transmission, sensor data from the sensor systems on the vehicle or attached to the one or more occupants/mobile devices; See Ashgar Par [0125] which discloses a vehicle computing system that includes any of the sensor data and/or data generated based on the sensor data, such that a description of information in the sensor data can be generated by the vehicle computing system).
Claim 7 –
Regarding Claim 7, Ashgar and Lake-Schaal disclose the system of claim 1 in its entirety. Ashgar further discloses a system, wherein:
the environment local to the user comprises a vehicle interior (See Ashgar Par [0044] which discloses one or more virtual reality systems facilitating interactions with VR environments and possibly combining real-world or physical environments and virtual environments to provide users with XR or VR experiences; See Ashgar Par [0004] which discloses the method including one or more images of an interior portion of a vehicle, such as to determine a state of an occupant of the vehicle; See Ashgar Par [0175] which discloses an AR application modulating virtual content, i.e. psychophysiological stimuli under BRI, by controlling virtual content being presented, when the content is presented, where the content is presented, and one or more characteristics of the virtual content presented, based on the state of the occupant).
Claim 8 –
Regarding Claim 8, Ashgar and Lake-Schaal disclose the system of claim 1 in its entirety. Ashgar further discloses a system, wherein:
the environment local to the user comprises a portion of an electronic gaming system (See Ashgar Par [0044] which discloses one or more virtual reality systems facilitating interactions with VR environments and possibly combining real-world or physical environments and virtual environments to provide users with XR or VR experiences; See Ashgar Par [0045] & [0048] which discloses one or more AR or VR systems or content being used for gaming, entertainment, and/or other applications, i.e. gaming system; See Ashgar Par [0160] which discloses the content filtering engine filtering any virtual content distracting the occupant or determined to distract the occupant, e.g. based on the state of the occupant, such that the content filtering engine can determine various video game content to output or attenuate for the occupant(s)).
Claim 9 –
Regarding Claim 9, Ashgar and Lake-Schaal disclose the system of claim 1 in its entirety. Asghar further discloses a system, wherein:
the second electronic device embedded in the environment local to the user comprises a virtual reality display (While not “embedded” per se, see Ashgar Par [0044] which discloses one or more virtual reality systems facilitating interactions with VR environments and possibly combining real-world or physical environments and virtual environments to provide users with XR or VR experiences, and is thereby understood to constitute “embedding” said system).
Claim 10 –
Regarding Claim 10, Ashgar and Lake-Schaal disclose the system of claim 1 in its entirety. Ashgar further discloses a system, wherein:
the instructions further cause the computing device to cause the virtual reality display to display a visual representation of a locality external to the environment local to the user (Ashgar Par [0110] which discloses the vehicle computing system including at least one processor and instructions stored in or one at least one memory to perform one or more of the functions of operations described throughout Ashgar; See Ashgar Par [0171] which discloses a portion of an environment outside of the vehicle are captured by one or more image sensors of the sensor system; See Ashgar Par [0158] which discloses the content filtering engine filtering/blocking certain content that may distract the occupants including a certain region outside of the vehicle that the content filtering engine determines should remain visible to the occupant or replace virtual content rendered by the mobile device with live content that may not obstruct a view of the occupant to a vehicle event or an environment outside of the vehicle).
Claim 11 –
Regarding Claim 11, Ashgar and Lake-Schaal disclose the system of claim 10 in its entirety. Ashgar further discloses a system, wherein:
the environment local to the user comprises an interior space of a vehicle and the locality external to the environment local to the user comprises a space external to the vehicle (See Ashgar Par [0044] which discloses one or more virtual reality systems facilitating interactions with VR environments and possibly combining real-world or physical environments and virtual environments to provide users with XR or VR experiences; See Ashgar Par [0004] which discloses the method including one or more images of an interior portion of a vehicle, such as to determine a state of an occupant of the vehicle; See Ashgar Par [0175] which discloses an AR application modulating virtual content, i.e. psychophysiological stimuli under BRI, by controlling virtual content being presented, when the content is presented, where the content is presented, and one or more characteristics of the virtual content presented, based on the state of the occupant; See Ashgar Par [0171] which discloses a portion of an environment outside of the vehicle are captured by one or more image sensors of the sensor system; See Ashgar Par [0158] which discloses the content filtering engine filtering/blocking certain content that may distract the occupants including a certain region outside of the vehicle that the content filtering engine determines should remain visible to the occupant or replace virtual content rendered by the mobile device with live content that may not obstruct a view of the occupant to a vehicle event or an environment outside of the vehicle).
Claim 12 –
Regarding Claim 12, Ashgar discloses a method comprising:
receiving, from at least electronic device of a plurality of electronic devices associated with a user, a first signal associated with a first physiological response of the user (See Ashgar Par [0013] which discloses one or more wearable devices and/or mobile devices that record one or more health measurements, including heart rate, blood pressure, body temperature, galvanic skin response, a measurement of an electric signal from a heart of the occupant, a measurement of electrical activity of a brain of the occupant, etc. in order to determine a state of the occupant; See Ashgar Par [0121] which discloses a vehicle computing system obtaining, i.e. via sending or transmission, sensor data from the sensor systems on the vehicle or attached to the one or more occupants/mobile devices);
determining, based on the first signal, an estimate of a state of the user comprising one or both of a cognitive state of the user and an emotional state of the user (See Ashgar Par [0010]-[0013] which discloses determining, i.e. determining an estimate, of a state of the user by receiving data associated with the one or more sensors of the vehicle and/or health sensors of the user; See Ashgar Par [0147] which discloses monitoring an occupant associated with a mobile device and detecting a state of the occupant of a vehicle based on various aspects of occupant); wherein
determining the estimate comprises comparing the first signal to a historical record of the user's neurophysiological responses to cognitive and/or emotional state-inducing environmental stimuli or generic norm patterns for the group that the user belongs to (See Ashgar Par [0010]-[0013] which discloses determining, i.e. determining an estimate, of a state of the user by receiving data associated with the one or more sensors of the vehicle and/or health sensors of the user; See Ashgar Par [0062] & [0068] which discloses the machine learning classifier being trained on positive and negative examples to determine a typical state of status of a vehicle, person, etc., albeit not recited for a “historical record” per se; See Ashgar Par [0154] which discloses determining state of the occupant a driving pattern of the occupant; See Ashgar Par [0147] which discloses monitoring an occupant associated with a mobile device and detecting a state of the occupant of a vehicle based on various aspects of occupant; See Ashgar Par [0044] which discloses one or more virtual reality systems facilitating interactions with VR environments and possibly combining real-world or physical environments and virtual environments to provide users with XR or VR experiences, and is thereby understood to constitute “embedding” said system; See Ashgar Par [0206] which discloses a machine learning classifier trained on positive and negative examples, i.e. historical data, including various cognitive, e.g. drowsiness, and/or emotional states, such that the state estimate would be determined based on comparison of current data to said historical data at least by the use of the learning model that is trained on said historical data, albeit not recited for a “historical record” per se);
causing, based on the estimate of the state of the user, presentation of an electronic representation of a personalized psychophysiological stimuli via a second electronic device embedded in an environment local to the user (While not “embedded” per se, see Ashgar Par [0044] which discloses one or more virtual reality systems facilitating interactions with VR environments and possibly combining real-world or physical environments and virtual environments to provide users with XR or VR experiences, and is thereby understood to constitute “embedding” said system; See Ashgar Par [0174]-[0175]which discloses an AR application modulating virtual content, i.e. psychophysiological stimuli under BRI, by controlling virtual content being presented, when the content is presented, where the content is presented, and one or more characteristics of the virtual content presented, based on the state of the occupant, which is understood by Examiner to constitute a “personalized” stimuli since the content presented is based on the state of the occupant) and distinct from a wearable or handheld device used by the user (See Ashgar Par [0024] the apparatuses can include, be part of, and/or interfaced with a vehicle, a mobile device, a wearable device, a personal computer, a laptop computer, a tablet computer, a server computer, a robotics device or system, an aviation system, or other device, thereby pointing towards these apparatuses possibly being devices other than mobile devices, and in the case of the devices interfacing with a vehicle, would thereby include a second device embedded in an environment local to the user when said user is in the vehicle; While not “embedded” per se, see Ashgar Par [0044] which discloses one or more virtual reality systems facilitating interactions with VR environments and possibly combining real-world or physical environments and virtual environments to provide users with XR or VR experiences, and is thereby understood to constitute “embedding” said system; See Ashgar Par [0319] which discloses the associated output devices being one or more of a display, projector, television, speaker device, etc.), wherein the personalized psychophysiological stimuli comprises psychophysiological feedback configured to encourage neurophysiological self-regulation by the user and is personalized based on the historical record and real-time responses of the user or generic norm patterns for the group that the user belongs to (See Ashgar Par [0062] & [0068] which discloses the machine learning classifier being trained on positive and negative examples to determine a typical state of status of a vehicle, person, etc., albeit not recited for a “historical record” per se; See Ashgar Par [0154] which discloses determining state of the occupant a driving pattern of the occupant; See Ashgar Par [0174]-[0175] which discloses an AR application modulating virtual content, i.e. psychophysiological stimuli under BRI, by controlling virtual content being presented, when the content is presented, where the content is presented, and one or more characteristics of the virtual content presented, based on the state of the occupant, which is understood by Examiner to constitute a “personalized” stimuli since the content presented is based on the determined state of the occupant which is based on a trained machine learning model using historical data, being compared to real-time responses of the user, albeit not recited for being based on a “historical record” per se; additionally, “to encourage neurophysiological self-regulation by the user and is personalized based on the historical record and real-time responses of the user or generic norm patterns for the group that the user belongs to” effectively amounts to an intended result of a method step positively recited and does not hold patentable weight (See MPEP 2111.04(I))).
While Ashgar Par [0062] & [0068] discloses the machine learning classifier being trained on positive and negative examples to determine a typical state of status of a vehicle, person, etc., Ashgar does not explicitly recite said data/statuses in the form of a “historical record” per se as given by the following limitations:
comparing the first signal to a historical record of the user's neurophysiological responses to cognitive and/or emotional state-inducing environmental stimuli or generic norm patterns for the group that the user belongs to
the personalized psychophysiological stimuli comprises psychophysiological feedback configured to encourage neurophysiological self-regulation by the user and is personalized based on the historical record and real-time responses of the user or generic norm patterns for the group that the user belongs to
However, Lake-Schaal discloses comparing the first signal to a historical record of the user's neurophysiological responses to cognitive and/or emotional state-inducing environmental stimuli and the personalized psychophysiological stimuli comprises psychophysiological feedback configured to encourage neurophysiological self-regulation by the user and is personalized based on the historical record (See Lake-Schaal Par [0078] which discloses application state data including records of user interactions with an application or other application inputs, outputs, or internal states of the user; See Lake-Schaal Par [0103] which discloses storing data structures of self-associated records each including a unique identifier, duration value of a content segment, one or more semantic tags relevant to passenger profile or user profile data, technical metadata as needed to select, configure or produce an interactive media content or a video that includes the content component or video clips identified by the identifier). The disclosure of Lake-Schaal is directly applicable to the disclosure of Ashgar, because the disclosures share limitations and capabilities, such as being directed towards delivery of content to one or more users based on the states of the user, especially in vehicular environments.
It would have been obvious to one of ordinary skill in the effective filing date of the claimed invention to modify the disclosure of Ashgar which already discloses the machine learning classifier being trained on positive and negative examples to determine a typical state of status of a vehicle, person, etc. to further specifically include the data that the learning algorithm is trained on is a historical record, per se, as disclosed by Lake-Schaal, because maintaining one or more data structures of self-associated records each including a unique identifier, duration value of a content segment, one or more semantic tags relevant to passenger profile or user profile data allows for selection, configuration or production an interactive media content or a video that includes the content component or video clips based on the maintained record (See Lake-Schaal Par [0103]).
Claim 13 –
Regarding Claim 13, Ashgar and Lake-Schaal disclose the method of claim 12 in its entirety. Ashgar further discloses a method, further comprising:
sending, to the second electronic device embedded in the environment local to the user, a signal associated with the estimate of the state of the user (While not “embedded” per se, see Ashgar Par [0044] which discloses one or more virtual reality systems facilitating interactions with VR environments and possibly combining real-world or physical environments and virtual environments to provide users with XR or VR experiences, and is thereby understood to constitute “embedding” said system).
Claim 14 –
Regarding Claim 14, Ashgar and Lake-Schaal disclose the method of claim 12 in its entirety. Ashgar further discloses a method, wherein:
the plurality of electronic devices associated with the user comprises a smart phone (See Ashgar Par [0024] & [0073] which discloses one or more sensor systems and/or devices, such as a smart phone, smart watch, or the like, for collecting and/or outputting data/content associated with a user).
Claim 15 –
Regarding Claim 15, Ashgar and Lake-Schaal disclose the method of claim 13 in its entirety. Ashgar further discloses a method, wherein:
the plurality of electronic devices associated with the user comprises at least one physiological sensor device (See Ashgar Par [0013] which discloses one or more wearable devices and/or mobile devices that record one or more health measurements, including heart rate, blood pressure, body temperature, galvanic skin response, a measurement of an electric signal from a heart of the occupant, a measurement of electrical activity of a brain of the occupant, etc. in order to determine a state of the occupant; See Ashgar Par [0110] which discloses the vehicle computing system including at least one processor and instructions stored in or one at least one memory to perform one or more of the functions of operations described throughout Ashgar; See Ashgar Par [0121] which discloses a vehicle computing system obtaining, i.e. via sending or transmission, sensor data from the sensor systems on the vehicle or attached to the one or more occupants/mobile devices; See Ashgar Par [0125] which discloses a vehicle computing system that includes any of the sensor data and/or data generated based on the sensor data, such that a description of information in the sensor data can be generated by the vehicle computing system).
Claim 16 –
Regarding Claim 16, Ashgar and Lake-Schaal disclose the method of claim 15 in its entirety. Ashgar further discloses a method, wherein:
the at least one physiological sensor device generates a signal associated with a physiological state experienced by the user (See Ashgar Par [0013] which discloses one or more wearable devices and/or mobile devices that record one or more health measurements, including heart rate, blood pressure, body temperature, galvanic skin response, a measurement of an electric signal from a heart of the occupant, a measurement of electrical activity of a brain of the occupant, etc. in order to determine a state of the occupant; See Ashgar Par [0110] which discloses the vehicle computing system including at least one processor and instructions stored in or one at least one memory to perform one or more of the functions of operations described throughout Ashgar; See Ashgar Par [0121] which discloses a vehicle computing system obtaining, i.e. via sending or transmission, sensor data from the sensor systems on the vehicle or attached to the one or more occupants/mobile devices; See Ashgar Par [0125] which discloses a vehicle computing system that includes any of the sensor data and/or data generated based on the sensor data, such that a description of information in the sensor data can be generated by the vehicle computing system).
Claim 17 –
Regarding Claim 17, Ashgar and Lake-Schaal disclose the method of claim 12 in its entirety. Ashgar further discloses a method, wherein:
the second electronic device embedded in an environment local to the user comprises a virtual reality device associated with a gaming system (While not “embedded” per se, see Ashgar Par [0044] which discloses one or more virtual reality systems facilitating interactions with VR environments and possibly combining real-world or physical environments and virtual environments to provide users with XR or VR experiences, and is thereby understood to constitute “embedding” said system; See Ashgar Par [0045] & [0048] which discloses one or more AR or VR systems or content being used for gaming, entertainment, and/or other applications, i.e. gaming system; See Ashgar Par [0160] which discloses the content filtering engine filtering any virtual content distracting the occupant or determined to distract the occupant, e.g. based on the state of the occupant, such that the content filtering engine can determine various video game content to output or attenuate for the occupant(s)).
Claim 18 –
Regarding Claim 18, Ashgar and Lake-Schaal disclose the method of claim 17 in its entirety. Ashgar further discloses a method, wherein:
the virtual reality device generates one or more of visual feedback, haptic feedback, and audio feedback (see Ashgar Par [0044] which discloses one or more virtual reality systems facilitating interactions with VR environments and possibly combining real-world or physical environments and virtual environments to provide users with XR or VR experiences; See Ashgar Par [0101] which discloses one or more haptic feedback devices or other output devices being controlled by the vehicle computing system).
Claim 19 –
Regarding Claim 19, Ashgar discloses a computing device comprising:
at least one processor (See Ashgar Par [0110] which discloses the vehicle computing system including at least one processor);
memory storing instructions that, when executed by the at least one processor, cause the computing device (See Ashgar Par [0110] which discloses the vehicle computing system including at least one processor and instructions stored in or one at least one memory to perform one or more of the functions of operations described throughout Ashgar) to:
receive, from at least one electronic device of a plurality of electronic devices, a first signal associated with a first physiological response of a user, wherein the plurality of electronic devices comprises one or more of a physiological sensor, a smart watch, and a smart phone (See Ashgar Par [0013] which discloses one or more wearable devices and/or mobile devices that record one or more health measurements, including heart rate, blood pressure, body temperature, galvanic skin response, a measurement of an electric signal from a heart of the occupant, a measurement of electrical activity of a brain of the occupant, etc. in order to determine a state of the occupant; See Ashgar Par [0121] which discloses a vehicle computing system obtaining, i.e. via sending or transmission, sensor data from the sensor systems on the vehicle or attached to the one or more occupants/mobile devices; See Ashgar Par [0024] & [0073] which discloses one or more sensor systems and/or devices, such as a smart phone, smart watch, or the like, for collecting and/or outputting data/content associated with a user);
determine, based on the first signal, an estimate of a state of the user by comparing the first signal to a historical record of the user's neurophysiological responses to cognitive and/or emotional state-inducing environmental stimuli or generic norm patterns for the group that the user belongs to (See Ashgar Par [0010]-[0013] which discloses determining, i.e. determining an estimate, of a state of the user by receiving data associated with the one or more sensors of the vehicle and/or health sensors of the user; See Ashgar Par [0062] & [0068] which discloses the machine learning classifier being trained on positive and negative examples to determine a typical state of status of a vehicle, person, etc., albeit not recited for a “historical record” per se; See Ashgar Par [0154] which discloses determining state of the occupant a driving pattern of the occupant; See Ashgar Par [0147] which discloses monitoring an occupant associated with a mobile device and detecting a state of the occupant of a vehicle based on various aspects of occupant; See Ashgar Par [0044] which discloses one or more virtual reality systems facilitating interactions with VR environments and possibly combining real-world or physical environments and virtual environments to provide users with XR or VR experiences, and is thereby understood to constitute “embedding” said system; See Ashgar Par [0206] which discloses a machine learning classifier trained on positive and negative examples, i.e. historical data, including various cognitive, e.g. drowsiness, and/or emotional states, such that the state estimate would be determined based on comparison of current data to said historical data at least by the use of the learning model that is trained on said historical data, albeit not recited for a “historical record” per se); and
cause, based on the estimate of the state of the user, presentation of an electronic representation of a personalized psychophysiological stimuli via a second electronic device embedded in an environment local to the user (While not “embedded” per se, see Ashgar Par [0044] which discloses one or more virtual reality systems facilitating interactions with VR environments and possibly combining real-world or physical environments and virtual environments to provide users with XR or VR experiences, and is thereby understood to constitute “embedding” said system; See Ashgar Par [0174]-[0175] which discloses an AR application modulating virtual content, i.e. psychophysiological stimuli under BRI, by controlling virtual content being presented, when the content is presented, where the content is presented, and one or more characteristics of the virtual content presented, based on the state of the occupant, which is understood by Examiner to constitute a “personalized” stimuli since the content presented is based on the state of the occupant) and distinct from a wearable or handheld device used by the user (See Ashgar Par [0024] the apparatuses can include, be part of, and/or interfaced with a vehicle, a mobile device, a wearable device, a personal computer, a laptop computer, a tablet computer, a server computer, a robotics device or system, an aviation system, or other device, thereby pointing towards these apparatuses possibly being devices other than mobile devices, and in the case of the devices interfacing with a vehicle, would thereby include a second device embedded in an environment local to the user when said user is in the vehicle; While not “embedded” per se, see Ashgar Par [0044] which discloses one or more virtual reality systems facilitating interactions with VR environments and possibly combining real-world or physical environments and virtual environments to provide users with XR or VR experiences, and is thereby understood to constitute “embedding” said system; See Ashgar Par [0319] which discloses the associated output devices being one or more of a display, projector, television, speaker device, etc.), wherein
the personalized psychophysiological stimuli comprises psychophysiological feedback configured to encourage neurophysiological self-regulation by the user and is personalized based on the historical record and real-time responses of the user or generic norm patterns for the group that the user belongs to (See Ashgar Par [0062] & [0068] which discloses the machine learning classifier being trained on positive and negative examples to determine a typical state of status of a vehicle, person, etc., albeit not recited for a “historical record” per se; See Ashgar Par [0154] which discloses determining state of the occupant a driving pattern of the occupant; See Ashgar Par [0174]-[0175] which discloses an AR application modulating virtual content, i.e. psychophysiological stimuli under BRI, by controlling virtual content being presented, when the content is presented, where the content is presented, and one or more characteristics of the virtual content presented, based on the state of the occupant, which is understood by Examiner to constitute a “personalized” stimuli since the content presented is based on the determined state of the occupant which is based on a trained machine learning model using historical data, being compared to real-time responses of the user, albeit not recited for being based on a “historical record” per se; additionally, “to encourage neurophysiological self-regulation by the user and is personalized based on the historical record and real-time responses of the user or generic norm patterns for the group that the user belongs to” effectively amounts to an intended result of a method step positively recited and does not hold patentable weight (See MPEP 2111.04(I))).
While Ashgar Par [0062] & [0068] discloses the machine learning classifier being trained on positive and negative examples to determine a typical state of status of a vehicle, person, etc., Ashgar does not explicitly recite said data/statuses in the form of a “historical record” per se as given by the following limitations:
comparing the first signal to a historical record of the user's neurophysiological responses to cognitive and/or emotional state-inducing environmental stimuli or generic norm patterns for the group that the user belongs to
the personalized psychophysiological stimuli comprises psychophysiological feedback configured to encourage neurophysiological self-regulation by the user and is personalized based on the historical record and real-time responses of the user or generic norm patterns for the group that the user belongs to
However, Lake-Schaal discloses comparing the first signal to a historical record of the user's neurophysiological responses to cognitive and/or emotional state-inducing environmental stimuli and the personalized psychophysiological stimuli comprises psychophysiological feedback configured to encourage neurophysiological self-regulation by the user and is personalized based on the historical record (See Lake-Schaal Par [0078] which discloses application state data including records of user interactions with an application or other application inputs, outputs, or internal states of the user; See Lake-Schaal Par [0103] which discloses storing data structures of self-associated records each including a unique identifier, duration value of a content segment, one or more semantic tags relevant to passenger profile or user profile data, technical metadata as needed to select, configure or produce an interactive media content or a video that includes the content component or video clips identified by the identifier). The disclosure of Lake-Schaal is directly applicable to the disclosure of Ashgar, because the disclosures share limitations and capabilities, such as being directed towards delivery of content to one or more users based on the states of the user, especially in vehicular environments.
It would have been obvious to one of ordinary skill in the effective filing date of the claimed invention to modify the disclosure of Ashgar which already discloses the machine learning classifier being trained on positive and negative examples to determine a typical state of status of a vehicle, person, etc. to further specifically include the data that the learning algorithm is trained on is a historical record, per se, as disclosed by Lake-Schaal, because maintaining one or more data structures of self-associated records each including a unique identifier, duration value of a content segment, one or more semantic tags relevant to passenger profile or user profile data allows for selection, configuration or production an interactive media content or a video that includes the content component or video clips based on the maintained record (See Lake-Schaal Par [0103]).
Claim 20 –
Regarding Claim 20, Ashgar and Lake-Schaal disclose the computing device of claim 19 in its entirety. Ashgar further discloses a computing device, wherein:
the second electronic device embedded in an environment local to the user comprises a virtual reality device associated with a gaming system (See Ashgar Par [0044] which discloses one or more virtual reality systems facilitating interactions with VR environments and possibly combining real-world or physical environments and virtual environments to provide users with XR or VR experiences; See Ashgar Par [0045] & [0048] which discloses one or more AR or VR systems or content being used for gaming, entertainment, and/or other applications, i.e. gaming system; See Ashgar Par [0160] which discloses the content filtering engine filtering any virtual content distracting the occupant or determined to distract the occupant, e.g. based on the state of the occupant, such that the content filtering engine can determine various video game content to output or attenuate for the occupant(s)) and the virtual reality device generates one or more of visual feedback, haptic feedback, and audio feedback (see Ashgar Par [0044] which discloses one or more virtual reality systems facilitating interactions with VR environments and possibly combining real-world or physical environments and virtual environments to provide users with XR or VR experiences; See Ashgar Par [0101] which discloses one or more haptic feedback devices or other output devices being controlled by the vehicle computing system).
Response to Arguments
Applicant's arguments filed 10 April 2026 have been fully considered but they are not persuasive:
Regarding 35 U.S.C. 101 rejections of claims 1-20, Applicant argues on p. Applicant argues on p. 8-9 in view of the Declarations filed 10 April 2026. More specifically Applicant argues in view of the Declarations and Desjardins regarding “When viewed as a whole, the claims recite a specific machine architecture that senses physiological signals, maintains individualized neurophysiological response histories, and controls environment-embedded devices to deliver adaptive biofeedback. This is a technical system for controlling physical environments based on physiological state, not an abstract idea implemented on a computer. The Applicant submits that the specification and claims are an improvement to a “the functioning of a computer, or an improvement to other technology or a technical field.” MPEP § 2106,04(d)(1)(i.e., as revised post-Desjardins) Accordingly, the claims are patent-eligible under Section 101”. Examiner respectfully disagrees with Applicant’s arguments. While Applicant argues that the claims recite a specific machine architecture that senses physiological signals, maintains individualized neurophysiological response histories, and controls environment-embedded devices to deliver adaptive biofeedback, Examiner argues that this is not necessarily an improvement over prior art systems that perform the same or similar functions. That is, while Examiner generally agrees that in light of Desjardins, that a software algorithm itself can constitute an improvement, the aspects claimed do not necessarily relate to an improvement over other software/algorithms that perform the same or substantially similar aspects described in prior art systems. For instance, Ashgar and Lake-Schaal disclose the described aspects of senses physiological signals, maintains individualized neurophysiological response histories, and controls environment-embedded devices to deliver adaptive biofeedback. There are no indications that the current steps go beyond the already-established software found in prior art systems, such as by Applicant’s purported “contextual training”, i.e. teaching physiological self-regulation of the user in the very context in which the self-regulated behavior is desired to take place. That is, while Applicant generally argues that the system delivering psychophysiological feedback is configured to train self-regulation improves biofeedback training technology itself by enabling pervasive, environment-integrated training, this does not necessarily reflect a technological improvement versus an improvement to the way that the user self-regulates based on outputs delivered by the system such as by adding context to said determinations. Therefore, the declarations are insufficient to overcome previous 35 U.S.C. 101 rejections of claims 1-20 based upon the claims still being directed towards patent-ineligible subject matter. As such, claims 1-20 remain rejected under 35 U.S.C. 101.
Regarding 35 U.S.C. 101 rejections of claims 1-20, Applicant argues on p. 9-10 of Arguments/Remarks that the generalization of the presentation of a psychophysiological stimuli on a second electronic device embedded in an environment local to the user is also “a mental process of a human or entity choosing content to output to a user the user’s psychological or physiological state” ignores limitation in the claim including the physical electronic device generating the signals associated with a physiological response of the user. And as such, the physical structures, such as the machine-implemented signal-processing components and steps recited in the claims that are do not describe an abstract concept or a mental process. Examiner respectfully disagrees with Applicant’s arguments. The physical structures and/or steps that fall outside of being reasonably performed in the mind are/were considered under step 2A/2B of the Alice/Mayo framework for determining patent-eligibility as additional elements. Each of these limitations were determined to represent insignificant, extra-solution activity and/or well-understood, routine, conventional activity in prior art systems. While Applicant states that it’s not clear how the human mind can generate electronic signals based on physiological responses of a user or how the human mind could process signals generated by electronic devices, MPEP 2106.04(a)(2)(III)(C) states that performing a mental process using a generic computer or simply using a computer as a tool to perform a mental process still constitutes the mental process itself. For instance, Examiner generally concedes that these aspects may not be reasonably performed in the human mind itself, but the general electronic signals and/or signals generated by electronic devices can easily be processed by generic computers, especially given the generic nature of the aspects described, and in view of the above-mentioned MPEP 2106.04(a)(2)(III)(C), would still constitute the characterized abstraction itself. While Applicant likens the example (iii) provided in MPEP 2106.04(a)(1) regarding an “earring comprising a sensor for taking period blood glucose measurements and a memory for storing measurement data from the sensor”, there are additional steps recited in the pending claims that amount to an abstract idea. That is, while there may be additional elements in the claims that may not represent abstract concepts, there are additional steps that fall outside of the specific example of “an earring comprising a sensor for taking period blood glucose measurements and a memory for storing measurement data from the sensor”. Additionally, the example provided does not recite abstract steps, versus simple structural elements that are recited for an intended purpose of performing various steps, versus the instantly pending claims which recite standalone abstract concepts. As such, claims 1-20 remain rejected under 35 U.S.C. 101.
Regarding 35 U.S.C. 101 rejections of claims 1-20, Applicant argues on p. 10-11 of Arguments/Remarks that the claims constitute a practical application because the claims change how a physical environment operates in response to measured physiological conditions and thereby use sensed physiological data to control physical systems in real time. Examiner respectfully disagrees with Applicant’s arguments. While the claims generally recite presentation of an electronic representation of a personalized psychophysiological stimuli via a second electronic device embedded in an environment local to the user, this does not necessarily relate to “controlling physical systems in real time”. That is, there is no indication that there are efforts beyond receiving data, analyzing data, and outputting results. That is, once these analyses are performed by the systems, there are no back-end implementations of said results, such as by controlling or outputting a response or effectuating a response by a physical device/component. Therefore, while Applicant may be using general language regarding “changing” how a system or component may perform based on data gathered or analyzed, these changes merely relate to the content being outputted to the user via the system. That is, these aspects do not amount to a practical application or back-end functionality beyond further limiting the already-established abstraction at-hand of receiving data, analyzing data, and outputting results. While Applicant argues that the claims do not merely select or present informational content, and instead modify characteristics of the surrounding environment itself in response to measured physiological conditions, such as environment-level actuation, these activities are not reflected in the claims under broadest reasonable interpretation. As such, claims 1-20 remain rejected under 35 U.S.C. 101.
Regarding 35 U.S.C. 101 rejections of claims 1-20, Applicant argues on p. 10-11 of Arguments/Remarks that the claims recite significantly more than the judicial exception recited, because the claims provide a specific technological solution to a technological problem identified, such as conventional biofeedback systems being limited to particular settings and fail to provide continuous, pervasive training across a user’s daily environments. That is, the introduction of a “distributed, environment-integrated biofeedback architecture” that enables persistent neurophysiological training across heterogeneous physical spaces. Examiner respectfully disagrees with Applicant’s arguments. The argued problem is not necessarily a technological problem, but rather a generalized or abstract problem. That is, a lack of providing continuous, pervasive training across a user’s daily environments is a problem that is wholly abstract at least by representing a mental process and/or method of organizing human activity. While Applicant further argues that the systems allow for coordinating physiological sensing, historical modeling, and environment-embedded actuation, these aspects do not necessarily represent a technological improvement versus an improvement in collecting data and outputting results of analysis performed on said collected data. Therefore, the aspect of producing an improved pervasive training across a user’s daily environments and/or collecting certain contexts/settings amount to efforts of improving an abstraction, not improving the technology or technical field at-hand. As such, claims 1-20 remain rejected under 35 U.S.C. 101.
Regarding 35 U.S.C. 102 rejections of Claims 1-20, Applicant argues on p. 12-13 of Arguments/Remarks that Ashgar fails to teach the newly amended limitations found in independent claims 1, 12, & 19. Examiner agrees with Applicant’s arguments. Therefore, the previous 35 U.S.C. 102 rejections have been withdrawn. However, upon further consideration, a new ground of rejection under 35 U.S.C. 103 has been made over Ashgar in view of Lake-Schaal. That is, the newly cited Lake-Schaal reads on the newly amended limitations found in independent claims 1, 12, & 19 regarding the use of a historical record for training purposes of a learning algorithm. As such, claims 1, 12, & 19 remain rejected under 35 U.S.C. 103.
Regarding 35 U.S.C. 102 rejections of Claims 1-20, Applicant argues on p. 13-15 of Arguments/Remarks that Ashgar does not disclose distinct “second electronic device embedded in an environment local to the user” separate from the device(s) generating the physiological signal nor presentation of a “psychophysiological stimulus” via this environmental device. Applicant further argues in view of Claim 3, Claim 6, Claim 8, Claim 9, Claim 11, and Claim 18 being allowable over the prior art. Examiner respectfully disagrees with Applicant’s arguments. While Examiner generally concedes that Ashgar does not disclose a “an electronic record” being used for training a learning algorithm this is effectively met by newly cited Lake-Schaal instead. However, Ashgar Par [0174]-[0175] which discloses an AR application modulating virtual content, i.e. psychophysiological stimuli under BRI, by controlling virtual content being presented, when the content is presented, where the content is presented, and one or more characteristics of the virtual content presented, based on the state of the occupant, which is understood by Examiner to constitute a “personalized” stimuli since the content presented is based on the determined state of the occupant which is based on a trained machine learning model using historical data, being compared to real-time responses of the user, and thereby constitutes presentation of a “psychophysiological stimulus”. Asghar Par [0024] & [0044] effectively discloses “second electronic device embedded in an environment local to the user”, respectively, at least by describing that the back-end apparatuses can include, be part of, and/or interfaced with a vehicle, a mobile device, a wearable device, a personal computer, a laptop computer, a tablet computer, a server computer, a robotics device or system, an aviation system, or other device, thereby pointing towards these apparatuses possibly being devices other than mobile devices, and in the case of the devices interfacing with a vehicle, would thereby include a second device embedded in an environment local to the user when said user is in the vehicle and one or more virtual reality systems facilitating interactions with VR environments and possibly combining real-world or physical environments and virtual environments to provide users with XR or VR experiences, and is thereby understood to constitute “embedding” said system. Therefore, Ashgar and Lake-Schaal effectively disclose the entirety of the limitations argued by Applicant. Regarding Claim 3, Applicant argues because Ashgar does not disclose a second device embedded in an environment local to the user separate from the device(s) generating the physiological signal. However, Examiner argues that Asghar Par [0024] & [0044] effectively discloses “second electronic device embedded in an environment local to the user” as explained above. As such, claim 3 is effectively met by Ashgar and Lake-Schaal. Regarding Claim 6, Applicant argues that Ashgar does not disclose at least one physiological sensor device that "generates a signal associated with a physiological state experienced by the user, because this requires direct human physiological signals as input”. However, Ashgar Par [0013] discloses one or more wearable devices and/or mobile devices that record one or more health measurements, including heart rate, blood pressure, body temperature, galvanic skin response, a measurement of an electric signal from a heart of the occupant, a measurement of electrical activity of a brain of the occupant, etc. in order to determine a state of the occupant, which would require direct human physiological signals as input. As such, claim 6 is effectively met by Ashgar and Lake-Schaal. Regarding Claim 8, Applicant argues that Ashgar does not disclose an “environment local to the user comprises a portion of an electronic gaming system”. However, Examiner points to Ashgar Par [0045] & [0048] which discloses one or more AR or VR systems or content being used for gaming, entertainment, and/or other applications, i.e. gaming system; . As such, claim 8 is effectively met by Ashgar and Lake-Schaal. Regarding Claim 9, Applicant argues that Ashgar does not disclose a virtual reality display. However, Examiner points to Ashgar Par [0044] which discloses one or more virtual reality systems facilitating interactions with VR environments and possibly combining real-world or physical environments and virtual environments to provide users with XR or VR experiences, and is thereby understood to constitute “embedding” said system. As such, claim 9 is effectively met by Ashgar and Lake-Schaal. Regarding Claim 11, Applicant argues that Ashgar does not disclose “an interior space of a vehicle” as the environment for the embedded device. However, Examiner points to Ashgar Par [0044] which discloses one or more virtual reality systems facilitating interactions with VR environments and possibly combining real-world or physical environments and virtual environments to provide users with XR or VR experiences; See Ashgar Par [0004] which discloses the method including one or more images of an interior portion of a vehicle, such as to determine a state of an occupant of the vehicle. As such, claim 11 is effectively met by Ashgar and Lake-Schaal. Regarding Claim 18, Applicant argues that Ashgar does not disclose the VR device “generating one or more of visual feedback, haptic feedback, and audio feedback”. However, Examiner points to Ashgar Par [0044] which discloses one or more virtual reality systems facilitating interactions with VR environments and possibly combining real-world or physical environments and virtual environments to provide users with XR or VR experiences; See Ashgar Par [0101] which discloses one or more haptic feedback devices or other output devices being controlled by the vehicle computing system. As such, claim 18 is effectively met by Ashgar and Lake-Schaal. As such, claims 1, 12, & 19 and claims dependent therefrom remain rejected under 35 U.S.C. 103.
Regarding 35 U.S.C. 102 rejections of claims 1-20, Applicant argues on p. 15 of Arguments/Remarks that Ashgar does not disclose “historical record based state estimation”. Examiner agrees with Applicant’s arguments. However, Lake-Schaal discloses the use of historical records under the new ground of rejection issued for independent claims 1, 12, & 19. As such, claims 1, 12, & 19 and claims dependent therefrom remain rejected under 35 U.S.C. 103.
Regarding 35 U.S.C. 102 rejections of claims 1-20, Applicant argues on p. 15 of Arguments/Remarks that Ashgar does not disclose “psychophysiological feedback configured to encourage neurophysiological self-regulation and personalized based on both (i) the historical record and (ii) real-time responses” as in claims 1, 12, & 19. Examiner agrees with Applicant’s arguments. However, Lake-Schaal discloses the use of historical records under the new ground of rejection issued for independent claims 1, 12, & 19, and this combination of Ashgar and Lake-Schaal does effectively disclose “psychophysiological feedback configured to encourage neurophysiological self-regulation and personalized based on both (i) the historical record and (ii) real-time responses” as in claims 1, 12, & 19. As such, claims 1, 12, & 19 and claims dependent therefrom remain rejected under 35 U.S.C. 103.
Regarding 35 U.S.C. 102 rejections of claims 1-20, Applicant argues on p. 16 of Arguments/Remarks that Ashgar does not disclose “historical record based state estimation”. Examiner respectfully disagrees with Applicant’s arguments. Examiner points to Asghar Par [0024] & [0044] which effectively discloses “second electronic device embedded in an environment local to the user”, respectively, at least by describing that the back-end apparatuses can include, be part of, and/or interfaced with a vehicle, a mobile device, a wearable device, a personal computer, a laptop computer, a tablet computer, a server computer, a robotics device or system, an aviation system, or other device, thereby pointing towards these apparatuses possibly being devices other than mobile devices, and in the case of the devices interfacing with a vehicle, would thereby include a second device embedded in an environment local to the user when said user is in the vehicle and one or more virtual reality systems facilitating interactions with VR environments and possibly combining real-world or physical environments and virtual environments to provide users with XR or VR experiences, and is thereby understood to constitute “embedding” said system. As such, claims 1, 12, & 19 and claims dependent therefrom remain rejected under 35 U.S.C. 103.
Regarding 35 U.S.C. 102 rejections of claims 1-20, Applicant argues on p. 16 of Arguments/Remarks that because independent claims 1, 12, & 19 are purportedly allowable over the prior art, claims dependent from said independent claims should also be allowable over the prior art. Examiner respectfully disagrees with Applicant’s arguments. As discussed above, a new ground of rejection has been issued for claims 1, 12, & 19. Therefore, Applicant’s arguments regarding independent claims 1, 12, & 19 being allowable over the prior art and therefore claims dependent therefrom being allowable over the prior art are rendered moot, because claims 1, 12, & 19 are not allowable over the prior art. As such, claims 1, 12, & 19 and claims dependent therefrom remain rejected under 35 U.S.C. 103.
Conclusion
The prior art made of record and not relied upon is considered pertinent to Applicant's disclosure:
Zohni et al. (U.S. Patent Publication No. 2023/0334788) discloses a Mixed-Reality visor (MR-visor) system and method utilizing environmental sensor feedback for replicating restricted external visibility during operation of manned vehicles, such as based on user physiological inputs and other environmental factors;
Madison et al. (U.S. Patent No. 10,977,956) discloses providing driver training in a virtual reality environment and augmentation of said virtual reality environment based on user performance, feedback, state, and other factors;
Xiong et al. (U.S. Patent Publication No. 2015/0197205) discloses a system for changing or controlling a computer simulation regarding an internal environment of a vehicle.
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/H.R./Examiner, Art Unit 3684
/Shahid Merchant/Supervisory Patent Examiner, Art Unit 3684
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