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 Claims
In the reply filed 23 June 2026 the following changes have been made: amendments to claims 1, 8, 11, 14, and 17.
Claims 1-20 are currently pending and have been examined.
Priority
Applicant’s claim for the benefit of a prior-filed application under 35 U.S.C. 119(e) or under 35 U.S.C. 120, 121, 365(c), or 386(c) is acknowledged. Applicant has not complied with one or more conditions for receiving the benefit of an earlier filing date under 35 U.S.C. 119(e) as follows:
The later-filed application must be an application for a patent for an invention which is also disclosed in the prior application (the parent or original nonprovisional application or provisional application). The disclosure of the invention in the parent application and in the later-filed application must be sufficient to comply with the requirements of 35 U.S.C. 112(a) or the first paragraph of pre-AIA 35 U.S.C. 112, except for the best mode requirement. See Transco Products, Inc. v. Performance Contracting, Inc., 38 F.3d 551, 32 USPQ2d 1077 (Fed. Cir. 1994).
The disclosure of the prior-filed application, Application No. 63/520,989 fails to provide adequate support or enablement in the manner provided by 35 U.S.C. 112(a) or pre-AIA 35 U.S.C. 112, first paragraph for one or more claims of this application. For claim 16 the prior-filed application does not provide support for “wherein the device is a television.” Examiner cannot find disclosure that the device is a television in the prior filed application. For claim 18 the prior-filed application does not provide support for “wherein the therapeutic digital content is stored in association with a predicted impact score.” Examiner cannot find disclosure that the therapeutic digital content is stored in association with a predicted impact score. Accordingly, claims 16 and 18-19 are not entitled to the benefit of the prior application.
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 is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Step 1
The claim(s) recite(s) subject matter within a statutory category as a process (claims 1-10) and a machine (claims 11-20).
INDEPENDENT CLAIMS
Step 2A Prong 1
Claim 1 recites steps of
collecting, via a biometric tracker, a first biometric data of the user, wherein the biometric tracker includes at least one sensing device;
processing the first biometric data to establish a baseline dataset for the user, exposing the user to the digital content;
extracting at least one feature parameter from the digital content;
collecting, via the biometric tracker, a second biometric data of the user while the user is exposed to the digital content;
generating, via an iteratively trained training model, a model output based on the second biometric data and the at least one feature parameter; the model output indicative of a correlation between the at least one feature parameter and a change in a biometric parameter of the user;
determining an impact score for the digital content based on the baseline dataset and the model output, the impact score quantifying an impact of the digital content on a state of the user; and
presenting, via a display device, the impact score to the user;
updating the iteratively trained training model based on the impact score and the at least one feature parameter;
receiving, from the user, a target state, the target state being a target physiological state or a target psychological state;
generating, based on the impact score and the target state, a modified version of the digital content; and
presenting, via the display device, the modified version of the digital content to the user.
Claim 11 recites steps of
a biometric tracker including a sensor, wherein the biometric tracker is designed to collect biometric data of the user;
a device adapted to present the digital content to the user; and
a controller including a processor configured to:
process a first biometric data of the user collected by the biometric tracker to establish a baseline dataset for the user;
expose the user to the digital content;
extract at least one feature parameter from the digital content;
receive a second biometric data of the user collected by the biometric tracker while the user is exposed to the digital content;
generate, using an iteratively trained training model, a model output based on the second biometric data and the at least one feature parameter, the model
output indicative of a correlation between the at least one feature parameter and a
change in a biometric parameter of the user;
determine an impact score for the digital content based on the baseline dataset and the model output, the impact score quantifying an impact of the digital content on a state
of the user an output of the iteratively trained training model; and
present, via the device, the impact score to the user;
update the iteratively trained training model based on the impact score and the at
least one feature parameter;
receive, from the user, a target state, the target state being a target physiological
state or a target psychological state;
generate, based on the impact score and the target state, a modified version of the
digital content; and
present, via the device, the modified version of the digital content to the user.
These steps for evaluating a biometric response of a user to digital content, as drafted, under the broadest reasonable interpretation, includes methods of organizing human activity. That is, nothing in the claim element precludes the italicized portions from managing personal behavior or relationships or interactions between people through organizing the activity around collection and processing biometric data to present an impact score to the user. This could be analogized to considering historical usage information while inputting data. The italicized portion containing the recitation of updating the iteratively trained training model at a high level of generality has been treated as part of the abstract idea, specifically as mathematical calculations which falls within the abstract idea of mathematical concepts, in light of the 2024 USPTO AI Guidance. If a claim limitation, under its broadest reasonable interpretation, covers performance as organizing human activity and mathematical calculations but for the recitation of generic computer components, then it falls within the “Methods of Organizing Human Activity” and “Mathematical Concepts” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
Step 2A Prong 2
This judicial exception is not integrated into a practical application. In particular, the additional elements non-italicized portions identified above for claims 1 and 11, does 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 via a biometric tracker; wherein the biometric tracker includes at least one sensing device; exposing the user to the digital content; via an iteratively trained training model; via a display device; generating […] a modified version of the digital content; and presenting, via the display device, the modified version of the digital content to the user a device adapted to present the digital content to the user; and, a controller including a processor configured amounts to invoking computers as a tool to perform the abstract idea, see MPEP 2106.05(f))
add insignificant extra-solution activity to the abstract idea (such as recitation of collecting […] a first biometric data of the user; collecting […] a second biometric data of the user while the user is exposed to the digital content; and, receiving, from the user, a target state, the target state being a target physiological state or a target psychological state amounts to mere data gathering since it does not add meaningful limitations to the collecting actions performed, see MPEP 2106.05(g))
Each of the above additional elements therefore only amounts to mere instructions to implement functions within the abstract idea using generic computer components or other machines within their ordinary capacity; and, add insignificant extra-solution activity to the abstract idea. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. These elements are therefore not sufficient to integrate the abstract idea into a practical application. Therefore, the above claims, as a whole, are directed to an abstract idea.
Step 2B
The claim(s) 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, and add insignificant extra-solution activity to the abstract idea. Additionally, the additional limitations, other than the abstract idea per se, amount to no more than limitations which:
amount to mere instructions to apply an exception in particular fields such as recitation of via a biometric tracker; wherein the biometric tracker includes at least one sensing device; exposing the user to the digital content; via an iteratively trained training model; via a display device; generating […] a modified version of the digital content; and presenting, via the display device, the modified version of the digital content to the user a device adapted to present the digital content to the user; and, a controller including a processor configured, e.g., a commonplace business method or mathematical algorithm being applied on a general-purpose computer, Alice Corp. v. CLS Bank, MPEP 2106.05(f).
amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields such as recitation of collecting […] a first biometric data of the user; collecting […] a second biometric data of the user while the user is exposed to the digital content; and, receiving, from the user, a target state, the target state being a target physiological state or a target psychological state, e.g., receiving or transmitting data over a network, Symantec, MPEP 2106.05(d)(II)(i).
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 generic computer implementation.
DEPENDENT CLAIMS
Step 2A Prong 1
Dependent claims recite additional subject matter which further narrows or defines the abstract idea embodied in the claims (such as claims 2-10, and 12-20 reciting particular aspects for evaluating a biometric response of a user to digital content such as
[Claim 2] wherein the first biometric data and the second biometric data includes electroencephalogram (EEG) data;
[Claim 3] wherein the first biometric data and the second biometric data includes heart rate data;
[Claim 4] wherein the digital content comprises at least one selected from the group consisting of virtual reality content, augmented reality content, mixed reality content, audio content, spatial content, video content, and/or audiovisual content digital content;
[Claim 5] wherein the display device is a virtual reality device;
[Claim 6] wherein the at least one feature parameter can include one or more of a color, a texture, a shape, a lighting feature, a volume, a speed, a proximity, a location, or a sound of the digital content;
[Claim 7] wherein the impact score for the digital content is unique to the user;
[Claim 8] receiving third-party digital content from a content database;
generating, via the iteratively trained training model, a predicted impact score for the third-party digital content; and
recommending the third-party digital content to the user based on the predicted impact score and the second biometric data;
[Claim 9] generating a modified version of the third-party digital content based on the predicted impact score; and
presenting, via the display device, the modified version of the third-party digital content based on the predicted impact score;
[Claim 10] wherein generating the modified version of the third-party digital content includes altering a story arc of the third-party digital content;
[Claim 12] wherein the biometric data includes one or more of EEG data, heart rate data, respiratory data, blood pressure data, functional magnetic resonance imaging data, near-infrared spectroscopy data, or skin temperature data;
[Claim 13] wherein the biometric tracker includes one or more of an EEG monitor, a heart rate monitor, a respiratory monitor, a blood pressure monitor, or a skin temperature monitor;
[Claim 14] wherein the target state corresponds to a reduction in a blood pressure of the user or a reduction in heart rate of the user;
[Claim 15] wherein the at least one feature parameter can include one or more of a color, a texture, a shape, a lighting feature, a volume, a speed, a proximity, a location, or a sound of the content;
[Claim 16] wherein the digital content is two-dimensional video content; and
wherein the device is a television;
[Claim 17] wherein the processor is further configured to:
receive, from the user, a target psychological state;
determine a difference between a current psychological state of the user and the target psychological state based on the second biometric data;
retrieve, from a digital content database, therapeutic digital content based on the difference between the current psychological state of the user and the target psychological state; and
recommend the therapeutic digital content to the user;
[Claim 18] wherein the therapeutic digital content is stored in association with a predicted impact score;
[Claim 19] wherein the processor is further configured to determine the predicted impact score for the therapeutic digital content based on historical biometric data associated with the user;
[Claim 20] wherein the impact score for the digital content is unique to the user;
these italicized portions are methods of organizing human activity since they merely describe types of data and determinations that can be performed by humans.
Step 2A Prong 2
Dependent claims 4-5, 8-10, 13, and 16-19 recite additional subject matter which amount to limitations consistent with the additional elements in the independent claims (the additional limitations in claim 4 (virtual reality content, augmented reality content, mixed reality content, audio content, spatial content, video content, and/or audiovisual content digital content); claim 5 (wherein the display device is a virtual reality device); claim 8 (via the iteratively trained training model); claim 9 (generating a modified version of the third-party digital content; and, presenting, via the display device, the modified version of the third-party digital content); claim 10 (wherein generating the modified version of the third-party digital content includes altering a story arc of the third-party digital content); claim 13 (includes one or more of an EEG monitor, a heart rate monitor, a respiratory monitor, a blood pressure monitor, or a skin temperature monitor); claim 16 (wherein the digital content is two-dimensional video content; and wherein the device is a television); and, claim 19 (the processor is further configured) amounts to invoking computers as a tool to perform the abstract idea, see MPEP 2106.05(f)); and, claim 8 (receiving third-party digital content from a content database); claim 14 (receive, from the user, a target physiological state); claim 17 (receive, from the user, a target psychological state; and, retrieve, from a digital content database, therapeutic digital content); and, claims 18 (wherein the therapeutic digital content is stored in association with a predicted impact score) amounts to mere data gathering and storage since it does not add meaningful limitations to the receiving, retrieving, and storing, actions performed, see MPEP 2106.05(g))). Accordingly, these additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
Step 2B
Dependent claims 4-5, 8-10, 13, 16, and 19 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, e.g., a commonplace business method or mathematical algorithm being applied on a general-purpose computer, Alice Corp. v. CLS Bank, MPEP 2106.05(f). Also, [0025], [0028], and [0039]-[0040] which disclose off-the-shelf devices. Dependent claims 8, 14, and 17 recite additional subject matter which amounts to elements that have been recognized as well-understood, routine, and conventional activity in particular fields, e.g., receiving or transmitting data over a network, Symantec, MPEP 2106.05(d)(II)(i); Dependent claim 18 amounts to elements that have been recognized as well-understood, routine, and conventional activity in particular fields, e.g., storing and retrieving information in memory, Versata Dev. Group, Inc., MPEP 2106.05(d)(II)(iv). There is no indication that these additional elements improve the functioning of a computer or improves any other technology. Their collective functions merely provide generic computer implementation.
Therefore, in consideration of all the facts, this is a textbook USC 101 where the present invention is clearly not patent-eligible under USC 101. Additionally, it is evident that the present claims monopolize the fundamental concept of feedback adaptation, restricting further innovation in this area without offering a specific, technical improvement to how the computer actually operates; “monopolization of those tools through the grant of a patent might tend to impede innovation more than it would tend to promote it.” Alice Corp., 573 U.S. at 216, 110 USPQ2d at 1980 (quoting Myriad, 569 U.S. at 589, 106 USPQ2d at 1978 and Mayo Collaborative Servs. v. Prometheus Labs. Inc., 566 U.S. 66, 71, 101 USPQ2d 1961, 1965 (2012)).
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 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 set forth in Graham v. John Deere Co., 383 U.S. 1, 148
USPQ 459 (1966), that are applied 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.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Hill et al. (US20190198153A1) in view of Krishnan (US20230012960A1).
Regarding claim 1, Hill discloses collecting, via a biometric tracker, a first biometric data of the user, wherein the biometric tracker includes at least one sensing device ([0036] “Sensors or monitors 22-30 can be configured to monitor, record and/or collect certain types of biometric data of a patient or user before, during and after the user engages with selected VR content through system 10.” Also, see Figure 2)
processing the first biometric data to establish a baseline dataset for the user ([0033] “Processor 12 can also be configured to receive and process biometric data from monitors 22-30 and associated with a patient or user.” [0040] “At step 104, a baseline biometric dataset can be created for the patient based on the initial biometric data recorded at step 102.”)
exposing the user to the digital content ([0010] “expose the user to a first VR environment and experience”)
extracting at least one feature parameter from the digital content ([0033] “Processor 12 can be configured to communicate with VR content database module 16 in order to access and transmit VR content based on determined parameters or instructions associated with a patient or user.” [0041] “The VR content can include any number of different components or features, including but not limited to visual stimuli, color, lighting, movement, camera angle, sound, music, voice, pacing, timing, characters, story arc, and script, aimed at influencing a patient's emotional, psychological and/or psychiatric state.”)
collecting, via the biometric tracker, a second biometric data of the user while the user is exposed to the digital content ([0106] “with biometric devices (such as monitors 22-30 in system 10)" [0044] “At step 116, the patient's biometrics may be measured and recorded during and/or after exposure to the second VR content in a similar manner to steps 102 and 108. At step 118, a second biometric dataset for the patient can be created based on the patient's biometric data measured during step 116.”)
determining an impact score for the digital content based on the baseline dataset and the model output ([0008] “The user's EEG-type biometric data may be measured during and/or after exposure to certain VR content and compared to previously measured EEG-type biometric data of the user to produce z-scores of change for specific brainwave types (i.e., alpha, delta, theta, etc.) in certain regions of the user's brain. The z-scores may then be used to identify statistically significant changes in the user's EEG-type biometric data (such as by identifying z-scores greater than or equal to 1.0”)
the impact score quantifying an impact of the digital content on a state of the user ([0059] “The creation of z-scores for the various Qeeg types of brainwave data (i.e., alpha, delta, theta, etc.) can then be used to quantitatively identify meaningful changes in the user's EEG biometric data.” [0060] “According to one embodiment, the z-score changes identified in the user's biometric data as a result of exposure to selected VR content may be used to determine whether the selected VR content is having a positive effect on the user's emotional, psychological or psychiatric state.”)
receiving, from the user, a target state, the target state being a target physiological state or a target psychological state ([0104] “According to one embodiment of the present invention, a user may begin by taking a questionnaire and/or symptom checklist configured to determine the user's specific goals/needs (such as stress reduction, improving focus, etc.)”)
generating, based on the impact score and the target state, a modified version of the digital content ([0059] “identify statistically significant z-score changes in a user's biometric data resulting from exposure to selected VR content.” [0105] “the user may be presented with a library of VR content designed to address the user's specific goals/needs.”)
and presenting, via the display device, the modified version of the digital content to the user ([0108] “Based on the results of […] biometric data analysis, additional VR content options may be offered to further achieve the desired effect.”)
Hill does not explicitly disclose however Krishnan teaches generating, via an iteratively trained training model, a model output based on the second biometric data and the at least one feature parameter ([0066] “In some implementations, the score generator 143 (e.g., a deep learning model or an XGBoost model) can be configured to iteratively receive a subset of user data from the set of past user data, a subset of setting data from the set of past setting data, and/or a subset of drug data from the set of past drug data described above and generate an output.”)
the model output indicative of a correlation between the at least one feature parameter and a change in a biometric parameter of the user ([0120] “input the user data into the model, which can generate an output that is or is indicative of the score of the user. […] The score can be based on or indicative of a measure of focus and relaxation of the user, e.g., as determined based on the user's EEG data, HRV data, and/or other data”)
and presenting, via a display device, the impact score to the user ([0079] “an indication of state of the user (e.g., a score) […] Therefore, in some instances, the score generator 143 can determine whether a current state of the adaptive setting is successful in inducing or maintaining an optimal set. In some implementations, the therapy device 110 can include a feedback system indicator to display, to the use.”)
updating the iteratively trained training model based on the impact score and the at least one feature parameter ([0066] “(e.g., a deep learning model or an XGBoost model) can be configured to iteratively” [0117] “As the user proceeds through the induction process, the user's EEG data and other data can be collected and used to update the global classifier. The calibration phase can continue and be repeated before beginning a gameplay.” [0144] “In some implementations, a machine learning model (e.g., similar to the score generator 143 as shown and described with respect to FIG. 1 ) can be used to generate a score to estimate a progression (e.g., a completeness) of the digital therapy 503. Thereafter, the closed-loop 500 can adaptively change the digital therapy based on the estimated score.”)
Therefore, it would have obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to include in the virtual reality therapy system of Hill generating, via an iteratively trained training model, a model output based on the second biometric data and the at least one feature parameter, the model output indicative of a correlation between the at least one feature parameter and a change in a biometric parameter of the user; presenting, via a display device, the impact score to the user; and, updating the iteratively trained training model based on the impact score and the at least one feature parameter as taught by Krishnan since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art.
Regarding claim 2, Hill discloses wherein the first biometric data and the second biometric data includes electroencephalogram (EEG) data ([0040] “the biometrics recorded for the patient may include EEG readings, heart rate, blood pressure, respiratory rate, and skin temperature).”)
Regarding claim 3, Hill discloses wherein the first biometric data and the second biometric data includes heart rate data ([0040] “the biometrics recorded for the patient may include EEG readings, heart rate, blood pressure, respiratory rate, and skin temperature).”)
Regarding claim 4, Hill discloses wherein the digital content comprises at least one selected from the group consisting of virtual reality content, augmented reality content, mixed reality content, audio content, spatial content, video content, and/or audiovisual content digital content ([0006] “The present invention is directed generally to systems and methods for using virtual reality ("VR"), augmented reality ("AR") and/or mixed reality ("MR") content in the therapeutic treatment of psychological, psychiatric or other medical conditions in patients).”)
Regarding claim 5, Hill discloses wherein the display device is a virtual reality device ([0032] “As shown in FIG. 1, system 10 may include a processor 12, a VR device 14”)
Regarding claim 6, Hill discloses wherein the at least one feature parameter can include one or more of a color, a texture, a shape, a lighting feature, a volume, a speed, a proximity, a location, or a sound of the digital content ([0041] “The VR content can include any number of different components or features, including but not limited to visual stimuli, color, lighting, movement, camera angle, sound, music, voice, pacing, timing, characters, story arc, and script, aimed at influencing a patient's emotional, psychological and/or psychiatric state).”)
Regarding claim 7, Hill discloses wherein the impact score for the digital content is unique to the user ([0059] “the EEG biometric data of the user may be measured during and/or after exposure to the VR content and compared to previously measured EEG biometric data of the user to produce z-scores of change for specific brainwave types (alpha, delta, theta, etc.) in certain regions of the brain” [0101] The BRAlNAVATAR® system has a feature called Z-builder which allows for the conversion of a raw EEG file into a quantitative reference file. Post-VR (or During-VR) EEG data can be compared to the Pre-VR reference file producing z scores of change for each variable at each region of interest for each subject).”)
Regarding claim 8, Hill discloses receiving third-party digital content from a content database ([0033] Processor 12 can be configured to communicate with VR content database module 16 in order to access and transmit VR content based on determined parameters or instructions associated with a patient or user.” [0035] “VR content database module 16 may comprise a reference library containing a plurality of categorized VR content”)
generating, […], a predicted impact score for the third-party digital content ([0033] “Processor 12 can be configured to communicate with biometric reference database module 18 in order to access and utilize and biometric data and algorithms for analyzing and processing a patient's biometric data received by system 10.” [0100] specific VR content experiences have been shown to result in predictable changes in biometric and brainwave patterns. As also described above, this may be assessed by comparing pre-VR biometric data to post-VR biometric data”)
and recommending the third-party digital content to the user based on the predicted impact score and the second biometric data ([0101] “Post-VR (or During-VR) EEG data can be compared to the Pre-VR reference file producing z scores of change for each variable at each region of interest for each subject.” [0103] “a user's biometrics can be assessed for patterns associated with specific concerns (anxiety, depression, pain, etc.). Based on these results, the user may be offered a selection of experiences specifically designed to address areas of concern/biometric patterns. For example, users demonstrating the certain types of profiles (such as stress reduction/pain reduction 300, mindfulness 302, focus 304, quiet mind 306 and open heart 308) will be recommended the VR content specific to such profiles.”)
Hill does not explicitly disclose however Krishnan teaches via the iteratively trained training model ([0066] “In some implementations, the score generator 143 (e.g., a deep learning model or an XGBoost model) can be configured to iteratively
Therefore, it would have obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to include in the virtual reality therapy system of Hill via the iteratively trained training module as taught by Krishnan since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art.
Regarding claim 9, Hill discloses generating a modified version of the third-party digital content based on the predicted impact score ([0050] “If, however, it is determined at step 210 that the changes in the user's biometric data corresponding to the currently selected VR content do not exceed the threshold requirements, the method proceeds to step 214. At step 214, a modified selected VR content is provided to the user in place of the previously selected VR content.” [0058] “As further provided in method 200 at steps 212-214, when it is determined by analyzing the user's biometric data that the VR content is not providing the desired changes in the user's biometric data, the VR content can be modified or altered to provide a more suitable VR content.”)
and presenting, via the display device, the modified version of the third-party digital content based on the predicted impact score ([0048] “Then at step 210, it is determined whether the changes in the user's biometric data as calculated at step 208 exceed specific threshold requirements.” [0050] “At step 214, a modified selected VR content is provided to the user in place of the previously selected VR content.” [0051] A notification may be generated and provided to the user within the currently selected VR content.”)
Regarding claim 10, Hill discloses wherein generating the modified version of the third-party digital content includes altering a story arc of the third-party digital content ([0053] the adjustments to the VR content may be configured to vary the […] story arc)
Regarding claim 11, Hill discloses a biometric tracker including a sensor, wherein the biometric tracker is designed to collect biometric data of the user ([0036] Sensors or monitors 22-30 can be configured to monitor, record and/or collect certain types of biometric data of a patient or user before, during and after the user engages with selected VR content through system 10.”)
a device adapted to present the digital content to the user ([0034] “According to one embodiment, VR device 14 can be configured as a headset that is worn over a user's eyes like a pair of googles.”)
and a controller including a processor configured to: process a first biometric data of the user collected by the biometric tracker to establish a baseline dataset for the user ([0033] “Processor 12 can also be configured to receive and process biometric data from monitors 22-30 and associated with a patient or user.” [0040] “At step 104, a baseline biometric dataset can be created for the patient based on the initial biometric data recorded at step 102.”)
expose the user to the digital content ([0010] “expose the user to a first VR environment and experience”)
extract at least one feature parameter from the digital content ([0033] “Processor 12 can be configured to communicate with VR content database module 16 in order to access and transmit VR content based on determined parameters or instructions associated with a patient or user.” [0041] “The VR content can include any number of different components or features, including but not limited to visual stimuli, color, lighting, movement, camera angle, sound, music, voice, pacing, timing, characters, story arc, and script, aimed at influencing a patient's emotional, psychological and/or psychiatric state.”)
receive a second biometric data of the user collected by the biometric tracker while the user is exposed to the digital content ([0044] “At step 116, the patient's biometrics may be measured and recorded during and/or after exposure to the second VR content in a similar manner to steps 102 and 108. At step 118, a second biometric dataset for the patient can be created based on the patient's biometric data measured during step 116.”)
determine an impact score for the digital content based on the baseline dataset and an output of the iteratively trained training module ([0008] “The user's EEG-type biometric data may be measured during and/or after exposure to certain VR content and compared to previously measured EEG-type biometric data of the user to produce z-scores of change for specific brainwave types (i.e., alpha, delta, theta, etc.) in certain regions of the user's brain. The z-scores may then be used to identify statistically significant changes in the user's EEG-type biometric data (such as by identifying z-scores greater than or equal to 1.0”)
receive, from the user, a target state, the target state being a target physiological state or a target psychological state ([0104] “According to one embodiment of the present invention, a user may begin by taking a questionnaire and/or symptom checklist configured to determine the user's specific goals/needs (such as stress reduction, improving focus, etc.)”)
generate, based on the impact score and the target state, a modified version of the digital content ([0059] “identify statistically significant z-score changes in a user's biometric data resulting from exposure to selected VR content.” [0105] “the user may be presented with a library of VR content designed to address the user's specific goals/needs.”)
and present, via the display device, the modified version of the digital content to the user ([0108] “Based on the results of […] biometric data analysis, additional VR content options may be offered to further achieve the desired effect.”)
Hill does not explicitly disclose however Krishnan teaches generating, via an iteratively trained training model, a model output based on the second biometric data and the at least one feature parameter ([0066] “In some implementations, the score generator 143 (e.g., a deep learning model or an XGBoost model) can be configured to iteratively receive a subset of user data from the set of past user data, a subset of setting data from the set of past setting data, and/or a subset of drug data from the set of past drug data described above and generate an output.”)
the model output indicative of a correlation between the at least one feature parameter and a change in a biometric parameter of the user ([0120] “input the user data into the model, which can generate an output that is or is indicative of the score of the user. […] The score can be based on or indicative of a measure of focus and relaxation of the user, e.g., as determined based on the user's EEG data, HRV data, and/or other data”)
present, via the device, the impact score to the user ([0079] “an indication of state of the user (e.g., a score) […] Therefore, in some instances, the score generator 143 can determine whether a current state of the adaptive setting is successful in inducing or maintaining an optimal set. In some implementations, the therapy device 110 can include a feedback system indicator to display, to the use.”)
update the iteratively trained training model based on the impact score and the at least one feature parameter ([0066] “(e.g., a deep learning model or an XGBoost model) can be configured to iteratively” [0117] “As the user proceeds through the induction process, the user's EEG data and other data can be collected and used to update the global classifier. The calibration phase can continue and be repeated before beginning a gameplay.” [0144] “In some implementations, a machine learning model (e.g., similar to the score generator 143 as shown and described with respect to FIG. 1 ) can be used to generate a score to estimate a progression (e.g., a completeness) of the digital therapy 503. Thereafter, the closed-loop 500 can adaptively change the digital therapy based on the estimated score.”)
Therefore, it would have obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to include in the virtual reality therapy system of Hill generating, via an iteratively trained training model, a model output based on the second biometric data and the at least one feature parameter, the model output indicative of a correlation between the at least one feature parameter and a change in a biometric parameter of the user; presenting, via a display device, the impact score to the user; and, updating the iteratively trained training model based on the impact score and the at least one feature parameter as taught by Krishnan since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art.
Regarding claim 12, Hill discloses wherein the biometric data includes one or more of EEG data, heart rate data, respiratory data, blood pressure data, functional magnetic resonance imaging data, near-infrared spectroscopy data, or skin temperature data ([0040] “the biometrics recorded for the patient may include EEG readings, heart rate, blood pressure, respiratory rate, and skin temperature).”)
Regarding claim 13, Hill discloses wherein the biometric tracker includes one or more of an EEG monitor, a heart rate monitor, a respiratory monitor, a blood pressure monitor, or a skin temperature monitor ([0036] “According to one embodiment, system 10 includes an electroencephalogram (EEG) monitor 22 to monitor the EEG activity of a user.”)
Regarding claim 14, Hill discloses wherein the target state corresponds to a reduction in a blood pressure of the user or a reduction in heart rate of the user ([0060] “decreased blood pressure, heart rate and respiratory rate levels are also linked to a more calm and relaxed state. Accordingly, when the desired effect of the selected VR content is to place the user in a relaxed or stress-reduced state”)
Regarding claim 15, Hill discloses wherein the at least one feature parameter can include one or more of a color, a texture, a shape, a lighting feature, a volume, a speed, a proximity, a location, or a sound of the content ([0041] “The VR content can include any number of different components or features, including but not limited to visual stimuli, color, lighting, movement, camera angle, sound, music, voice, pacing, timing, characters, story arc, and script, aimed at influencing a patient's emotional, psychological and/or psychiatric state.”)
Regarding claim 16, Hill discloses wherein the digital content is two-dimensional video content ([0034] “VR content can be monoscopic”)
Hill does not explicitly disclose however Krishnan teaches wherein the device is a television ([0075] “a display device (e.g., a television screen)”)
Therefore, it would have obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to include in the virtual reality therapy system of Hill the device is a television as taught by Krishnan since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art.
Regarding claim 17, Hill discloses wherein the processor is further configured to: determine the difference between the state of the user and the target state based on the second biometric data ([0044] “After the second biometric dataset is created, it can be analyzed and compared to the patient's first biometric dataset and/or the patient's baseline biometric dataset at step 120 to determine the effect the second VR content had on the patient's biometrics associated with psychological, psychiatric or other medical conditions.”)
retrieve, from a digital content database, therapeutic digital content based on the difference between the state of the user and the target state ([0046] “The selected VR content may be chosen based on the specific type of emotional, psychological and/or psychiatric state to be addressed for the user. According to one embodiment, the selected VR content is chosen from a library database containing a plurality of VR content categorized based on the content's ability to influence positive change in certain types of emotional, psychological and/or psychiatric states.”)
and recommend the therapeutic digital content to the user ([0046] “providing VR content to a user as therapeutic content” Also, see Figure 4)
Regarding claim 18, Hill does not explicitly disclose however Krishnan teaches wherein the therapeutic digital content is stored in association with a predicted impact score ([0080] “In some instances, the adaptive setting model can guide or actively induce/maintain optimal set in the user during a digital therapy” [0082] “The profile updater 144 can then receive an indication of state of the user (e.g., the score) from the score generator 143 and in response to various states of the adaptive setting. and update a user profile of the user to generate an updated user profile. The updated user profile can be stored in the memory 131.”)
Therefore, it would have obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to include in the virtual reality therapy system of Hill the therapeutic digital content stored in association with a predicted impact score as taught by Krishnan since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art.
Regarding claim 19, Hill discloses wherein the processor is further configured to determine the predicted impact score for the therapeutic digital content based on historical biometric data associated with the user ([0100] “specific VR content experiences have been shown to result in predictable changes in biometric and brainwave patterns. As also described above, this may be assessed by comparing pre-VR biometric data to post-VR biometric data).”)
Regarding claim 20, Hill discloses wherein the impact score for the digital content is unique to the user ([0059] “the EEG biometric data of the user may be measured during and/or after exposure to the VR content and compared to previously measured EEG biometric data of the user to produce z-scores of change for specific brainwave types (alpha, delta, theta, etc.) in certain regions of the brain” [0101] The BRAlNAVATAR® system has a feature called Z-builder which allows for the conversion of a raw EEG file into a quantitative reference file. Post-VR (or During-VR) EEG data can be compared to the Pre-VR reference file producing z scores of change for each variable at each region of interest for each subject).”)
Response to Arguments
Applicant’s arguments filed on 22 June 2026 have been considered but are not fully persuasive.
Regarding the double patenting rejection, applicant has filed a terminal disclaimer which has been approved by the USPTO. Therefore, the double patenting rejection has been withdrawn.
Regarding the USC 101 rejection, applicant argues that the claims do not recite an abstract idea and do not recite any limitations falling within any of the enumerated groupings. In addition, applicant asserts that the amended claims are not directed towards mental processes because they recite limitations which cannot be practically performed in the human mind. That the claimed steps quite clearly require the use of a computing system. Under Step 2A Prong 2, applicant argues that the claims integrate the abstract idea into a practical application because the claimed approach is directed to the practical application of providing specific digital content. That is, the claimed approach imparts the improvement of advanced data processing techniques to analyze biometric data indicative of the response of a user to specific aspects of digital content, develops a predictive model (i.e., the iteratively trained training module) to score content watched by the user, wherein the score is developed based on the user's physiological response as determined by comparing the user's biometric data to the user's historical biometric data and baseline biometric data insights from a population of users and digital content. Applicant also states that the claimed approach provides greater access to treatment and therapeutic intervention without face-to-face treatment by a clinician, which requires transportation, financial resources, time, and an associated provider. Under Step 2B, applicant argues that each claim recites features in a particularly-claimed order and combination that involves an inventive concept and is not well-understood, routine, or conventional. At least due to also the fact that the claims are patentable over the prior art. Applicant states that claim 11 recites similar language as claim 1 and is also patent-eligible. Applicant requests withdrawal of the USC 101 rejection.
Examiner disagrees with the applicant’s arguments. Applicant’s claims are clearly directed to an abstract idea. The invention measures a user's physical or mental reactions to digital media, scores that impact using machine learning, and then actively modifies the digital content to help the user reach a desired mental or physical state. The claimed limitations are tasks that doctors, researchers, and psychologists have manually performed for decades. The MPEP makes it clear that claims can recite an abstract idea even if they are claimed as being performed on a computer. The courts have also found claims requiring a generic computer or nominally reciting a generic computer may still recite abstract idea even though the claim limitations are not performed entirely by a human. The limitations identified as abstract in the present application are very outcome-based or result-focused and don’t give much technical detail that goes beyond what a human can do. Merely adding a generic computer, generic computer components, or a programmed computer to perform generic computer functions does not automatically overcome an eligibility rejection. Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 224, 110 USPQ2d 1976, 1984 (2014). See also OIP Techs. v. Amazon.com, 788 F.3d 1359, 1364, 115 USPQ2d 1090, 1093-94 (Fed. Cir. 2015) ("Just as Diehr could not save the claims in Alice, which were directed to ‘implement[ing] the abstract idea of intermediated settlement on a generic computer’, it cannot save OIP's claims directed to implementing the abstract idea of price optimization on a generic computer.") (citations omitted). The present model claimed is a black box algorithm with no clarity on the actual computer processing or how the computer is programmed to achieve the results in a non-abstract way different from how humans analyze/process data. Despite the applicant’s assertions, examiner asserts that the claim still puts no limit on how the computer actually performs the argued limitations (i.e., computer-focused operations) such they cannot be considered an abstract idea. Even if the claims nominally recite computer components that are rooted in technology, there is no recitation of how the computer components are specifically programmed to distinguish from generic computer processes.
Under Step 2A Prong 2, the amendments do not do much to advance prosecution because the present specification provides a bare assertion of an improvement without the detail necessary to be apparent to a person of ordinary skill in the art. The MPEP provides that improvements to the functioning of a computer or to any other technology or technical field can signal eligibility, see MPEP 2106.05(a), and provides examples of improvements to computer functionality, MPEP 2106.05(a)(I), and improvements to any other technology of technical field, MPEP 2106.05(a)(I). “In computer-related technologies, the examiner should determine whether the claim purports to improve computer capabilities or, instead, invokes computers merely as a tool”. Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1336, 118 USPQ2d 1684, 1689 (Fed. Cir. 2016). In Enfish, the court evaluated the patent eligibility of claims related to a self-referential database. Id. The court concluded the claims were not directed to an abstract idea, but rather to an improvement to computer functionality. Id. It was the specification' s discussion of the prior art and how the invention improved the way the computer stores and retrieves data in memory in combination with the specific data structure recited in the claims that demonstrated eligibility. 822 F.3d at 1339, 118 USPQ2d at 1691. The claim was not simply the addition of general-purpose computers added post-hoc to an abstract idea, but a specific implementation of a solution to a problem in the software arts. 822 F.3d at 1339, 118 USPQ2d at 1691. Unlike Enfish, the instant claimed invention appears to improve upon a judicial exception rather than a problem in the software arts. Rather than improving a computer's algorithm (i.e., solving a technically based problem), the claimed invention purports to solve the non-technological problem of lack of objective physiological data on how digital content impacts viewers ([0003] of specification) by using computers to perform data processing/manipulation rather than a concrete technical improvement (also see page 13 of applicant’s arguments of record). In other words, one of the main/glaring issues with the present invention is that the problems solved by the applicant is not technological problem. Applicant themselves have clarified the record by indicating the invention performs advanced data processing techniques and also provides greater access to treatment and therapeutic intervention without face-to-face treatment by a clinician, which requires transportation, financial resources, time, and an associated provider. This asserted improvement by the applicant is not an improvement to computer technology and is not considered patent eligible by the USPTO (see MPEP 2106). All the applicant is doing is applying known technology for their intended benefit(s) to a new data environment and calling it an improvement (see Customedia Techs., LLC v. Dish Network Corp., Case No.18-2239 (Fed. Cir. Mar. 6, 2020).
The examiner asserts the following facts which the applicant will not be able to dispute:
1) the invention does NOT involve a novel algorithm or data structure that significantly improves the computer's functionality,
2) the invention does NOT involve a new hardware component or configuration that works with the computer to achieve a specific technical benefit, and
3) the computer is NOT used in a completely new way demonstrating a significant technical advancement.
It is evident from the specification and claims that the applicant is not improving computer technology, and instead providing an improvement to the abstract idea. An improvement to the abstract idea is not an improvement to computer technology. Thus, examiner does not see how the present claims improve the functioning of a computer or provide improvements to any other technology or technical field. The claimed invention appears similar to the example of improvements that are insufficient to show an improvement in computer-functionality such as arranging transactional information on a graphical user interface in a manner that assists traders in processing information more quickly, Trading Technologies v. IBG LLC, 921 F.3d 1084, 1093-94, 2019 USPQ2d 138290 (Fed. Cir. 2019). See MPEP 2106.05(a)(I)(viii). The broad claims are lacking concrete limitations to integrate the abstract idea into a practical application. Examiner points out that the claimed limitations have no indication in the specification that the operations recited invoke any inventive programming, require any specialized computer hardware or other inventive computer components, i.e., a particular machine, or that the claimed invention is implemented using other than generic computer components to perform generic computer functions. See DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1256 (fed Cir. 2014) (“[A]fter Alice, there can remain no doubt: recitation of generic computer limitations does not make an otherwise ineligible claim patent-eligible.”). Most importantly, in DDR Holdings & unlike the present claims, the claims at issue specified how interactions with the Internet were manipulated to yield a desired result—a result that overrode the routine and conventional sequence of events ordinarily triggered by the click of a hyperlink. 773 F.3d at 1258; 113 USPQ2d at 1106. The examiner also points out that there is no indication in the specification that the claimed invention affects a transformation or reduction of a particular article to a different state or thing. Examiner points to the recitation of model in the claim(s) as generic. "[T]he mere recitation of a generic computer cannot transform a patent-ineligible abstract idea into a patent-eligible invention." Alice Corp. v. CLS Banklnt'l, 573 U.S. 208 223 (2014). Applicant does not and cannot contend they invented the concept of training a model, nor does the specification disclose any new training technique. The alleged improvement of using a trained model lies in the abstract idea itself, not to any technological improvement nor to any improvement to the functioning of a computer. See BSG Tech LLC v. Buyseasons, Inc., 899 F.3d 1281, 1287-88 (Fed. Cir. 2018). The fact pattern of the applicant’s claims is congruent to the Recentive Analytics, Inc. v. Fox Corp., 2025 U.S.P.Q.2d 628 (Fed. Cir. 2025) decision by the Federal Circuit. Just like in Recentive, the present claims do not delineate steps through which the trained model achieves an improvement. See, e.g., IBM v. Zillow Grp., Inc., 50 F.4th 1371, 1381 (Fed. Cir. 2022) (holding abstract a claim that "d[id] not sufficiently describe how to achieve [its stated] results in a non-abstract way," because "[s]uch functional claim language, without more, is insufficient for patentability under our law." (quoting Two-Way Media Ltd v. Comcast Cable Commc'ns, LLC, 874 F.3d 1329, 1337 (Fed. Cir. 2017))); see also Intell. Ventures I LLC v. Capital One Fin. Corp., 850 F.3d 1332, 1342 (Fed. Cir. 2017) (similar); Elec. Power Grp., LLC v. Alstom S.A., 830 F.3d 1350, 1356 (Fed. Cir. 2016) (similar). Claiming a mere concept or functional result without disclosing the implementation details does not overcome USC 101. Applying an established technique to a new field or data set is insufficient for patent eligibility. To show an involvement of a computer assists in improving technology, the claims must recite details regarding how a computer aids the method, the extent to which the computer aids the method, or the significance of a computer to the performance of the method. Merely adding generic computer components to perform the method is not sufficient. Thus, the claim must include more than mere instructions to perform the method on a generic component or machinery to qualify as an improvement to an existing technology (MPEP 2106.05(a)(II)). In Finjan, Inc. v. Blue Coat Systems the courts found that the claims were “directed to a non-abstract improvement in computer functionality…” (MPEP 2106.04(d)). The present invention clearly does not meet the condition set forth by the courts and thus is not integrated into a practical application.
An analysis was performed under Step 2B, with court case citations, which didn’t result in the claim being eligible under USC 101. In comparison to Bascom, examiner points out that Bascom is not similar to the present application because Bascom claimed a technical improvement in the art i.e., a technology-based solution to filter content on the internet while the present application is not presenting an improvement (as indicated above). There is nothing specialized about using off-the-shelf computers on new data. The use of a computer or other machinery in its ordinary capacity for economic or other tasks or simply adding a general-purpose computer or computer components after the fact to an abstract idea does not provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). The applicant has not demonstrated that their invention is inventive. There is no justification to withdraw the USC 101. Therefore, the USC 101 rejection is strongly maintained
Regarding the USC 103 rejection, applicant’s arguments have been considered, but in light of the amendments new paragraphs from Hill and Krishnan have been cited to teach the claimed limitations. Therefore, the USC 103 rejection has been maintained.
Prior Art Cited but Not Relied Upon
Wu, J. Y., Tsai, Y. Y., Chen, Y. J., Hsiao, F. C., Hsu, C. H., Lin, Y. F., & Liao, L. D. (2025). Digital transformation of mental health therapy by integrating digitalized cognitive behavioral therapy and eye movement desensitization and reprocessing. Medical & Biological Engineering & Computing, 63(2), 339-354.
This reference is relevant because it discloses recommending and generating digital behavior therapy content based on biometric data.
US20220061757A1
This reference is relevant because it discloses collecting biometric data and generating a score to help adjust the digital content.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to WINSTON FURTADO whose telephone number is (571)272-5349. The examiner can normally be reached Monday-Friday 8:00 AM to 4:00 PM EST.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Mamon Obeid can be reached at (571) 270-1813. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/WINSTON R FURTADO/Primary Examiner, Art Unit 3687
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