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 .
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55. Acknowledgement is made of applicant’s claim for foreign priority to 25 August 2022 under 35 U.S.C. 119(a)-(d).
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 23 February 2026 has been entered.
Response to Amendment
Claims 1-12 & 14-16 were previously pending in this application. The amendment filed 23 February 2026 has been entered and the following has occurred: Claims 1, 6-12, & 16 have been amended. No claims have been added or cancelled.
Claims 1-12 & 14-16 remain pending in the 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 1-12 & 14-16 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 1-12 & 14), machine (claims 16), and manufacture (claims 15) (Subject Matter Eligibility (SME) Test Step 1: Yes) which recite steps of:
receiving an input from a user via a terminal to initiate an app;
outputting, via an output device of the terminal, an application algorithm of the app through based on the app being initiated, a cognitive function training algorithm of the cognitive function training app through an output device of the terminal based on the cognitive function training app being initiated, wherein the application algorithm comprises an output of one or more of a visual indication comprising one or more of a color, shape, pattern, text, or sparkle, or an audible indication comprising one or more of music or speech;
optimizing the application algorithm based on information of the user;
wherein the optimizing comprises calculating a fatigue level of the user based on a new input from the user, and adjusting a progress speed of the optimized cognitive function training algorithm based on the calculated fatigue level,
wherein the adjusting of the progress speed of the application algorithm is based on a fatigue level of the user being greater than a preset level and comprises stopping the application algorithm for a preset time period, or changing a training speed of the application algorithm;
receiving response inputs in response to the application algorithm;
generating a new application algorithm based on the response inputs, wherein
the new application algorithm comprises a new combination of terminal outputs comprising one or more of a visual indication comprising one or more of a color, shape, pattern, text, or sparkle, or an audible indication comprising one or more of music or speech;
sending, based on the response inputs or based on new response inputs associated with the new application algorithm, user state information to an electronic medical record or an external system device; and
outputting, via the output device, the user state information.
These steps of receiving a user input, outputting an application algorithm such as through an interface once an input from a user has been received, optimizing the cognitive function training format depending on information associated with the user by calculating a fatigue level of the user based on a new input/response inputs from the user, adjusting the progress speed of a therapy/application program based on fatigue level of the user, generating a new application algorithm/therapy based on said response inputs, sending user state information to an EMR, and outputting the user state information as drafted, under the broadest reasonable interpretation, includes methods of organizing human activity. MPEP 2106.04(a)(2)(II) describe certain methods of organizing human activity 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 above amount to methods or organizing human activity, at least by managing the typical behavior of a user regarding providing cognitive functioning training to the user based on user data. For instance, MPEP 2106.04(a)(2)(II)(C) specifically sets forth examples of managing personal behavior recited in a claim, such as filtering content, considering historical usage information while inputting data, and/or a mental process that a neurologist should follow when testing a patient for nervous system malfunctions. That is, the system performing general efforts of determining and providing cognitive function training depending on user input/information, such as fatigue level or inputs associated therewith, effectively manages person behavior of the user regarding the typical interaction or behavior when interacting with the cognitive therapy. Additionally, modifying content and therapy based on various aspects of the user’s interactions/behaviors, and therefore managing said user’s typical interaction or behavior when interacting with the cognitive therapy/system. Further, these limitations seem to highly relate to a “mental process that a neurologist should follow when testing a patient for nervous system malfunctions”, but recited for an electronic system, instead of a neurologist, which as detailed in MPEP 2106.04(a)(2)(II)(C), constitutes certain methods of organizing human activity in the form of managing personal behavior. Accordingly, the claim recites an abstract idea (SME Test Step 2A, Prong 1: Yes).
Dependent claims recite additional subject matter which further narrows or defines the abstract idea embodied in the claims (such as claims 2-12 & 14-15, reciting particular aspects of how user information may be collected, how to format 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 cognitive function training app/algorithm, an output device, a terminal, a processor, amounts to invoking computers as a tool to perform the abstract idea, see applicant’s specification [0048] for a cognitive function training app/algorithm; [0043] an output device; [0058]-[0059] for a terminal; [0054] for a processor/processing unit; see MPEP 2106.05(f));
add insignificant extra-solution activity to the abstract idea (such as recitation of as receiving user input/imitation from a user, such as to imitate a cognitive function training app, providing/receiving cognitive function training of the cognitive function training app through an output device/terminal, r receiving information relating to the user of the terminal, receiving response inputs, sending user state information to an EMR or an external system device, outputting user state information amounts to mere data gathering; recitation of outputting a cognitive function training algorithm based on said determining, changing a format of the training and/or adjusting a progress speed of the optimized cognitive function training based on information of the user of the terminal, such as calculated fatigue level amounts to selecting a particular data source or type of data to be manipulated, recitation of the training and/or adjusting a progress speed of the optimized cognitive function training based on information of the user of the terminal, such as calculated fatigue level, adjusting the progress speed of the application algorithm based on a fatigue level of the user, generating a new application based on the response inputs amounts to insignificant application, see MPEP 2106.05(g); outputting the user state information, i.e. to gathering and analyzing information using conventional techniques and displaying the result, see TLI Communications and MPEP 2106.05(a)(II)(iii));
generally link the abstract idea to a particular technological environment or field of use (such as recitation of an application or applied to the field of cognitive function training, recitation of the outputs comprising a visual indication of a color, shape, pattern, text, sparkle, or audible indication comprising one or more of music or speech, 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 2-12 & 14-15, which recite limitations relating to a sensor, a terminal, a cognitive function training app/algorithm, a non-transitory computer-readable recording medium, a program, and a computer, see applicant’s specification [0092] for a sensor; [0058]-[0059] for a terminal; [0048] for a cognitive function training app; [00138] for a non-transitory computer-readable recording medium; [00138] a program; [0043] for a computer, see MPEP 2106.05(f ), additional limitations which amount to invoking computers as a tool to perform the abstract idea; claims 2-6, which recite limitations relating to receiving user information, the type of user information being received, outputting one or more information, additional limitations which add insignificant extra-solution activity to the abstract idea which amounts to mere data gathering; claims 7-12 & 14, which recite limitations relating to further specifying optimizing the cognitive functioning training or the cognitive functioning training app, such as by making determinations on received information, 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 2-12 & 14-15, which recite limitations relating to the limitations being linked to a non-transitory computer-readable recording medium, or generally recited for use in an optimized cognitive function training app, 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 (SME Test Step 2A, Prong 2: No).
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 user input/imitation from a user, such as to imitate a cognitive function training app, providing/receiving cognitive function training of the cognitive function training app through an output device/terminal, receiving information relating to the user of the terminal, receiving response inputs, sending user state information to an EMR or an external system device, outputting user state information, specifying outputted content, e.g., receiving or transmitting data over a network, Symantec, MPEP 2106.05(d)(II)(i); providing cognitive function training based on said determining, changing a format of the training based on information of the user of the terminal, calculating a fatigue level of the user based on a new input from the user, and adjusting a progress speed of the optimized cognitive function training algorithm based on the calculated fatigue level, adjusting the progress speed of the application algorithm based on a fatigue level of the user, generating a new application based on the response inputs, e.g., performing repetitive calculations, Flook, MPEP 2106.05(d)(II)(ii); optimizing the cognitive function training by changing a format according to user needs/preferences, such as in an electronic record, adjusting a progress speed which under BRI does not necessarily include physical parameters or associated medical treatment delivery parameters in particular, e.g. parameters or logs of the optimized cognitive function training algorithm or displayed content thereof, e.g., electronic recordkeeping, Alice Corp., MPEP 2106.05(d)(II)(iii); storing computerized program instructions to perform the steps recited, storing information about the user, storing interaction data, storing instructions for outputting means of the cognitive function training app, storing various physiological data/levels of the user, storing user state information, storing response inputs, e.g., storing and retrieving information in memory, Versata Dev. Group, MPEP 2106.05(d)(II)(iv); obtaining information relating to the user of the terminal, e.g., electronic scanning or extracting data from a physical document, Content Extraction, MPEP 2106.05(d)(II)(v); receiving user input and determinations relating to whether a user input has been received/initiated, receiving user response inputs e.g., a web browser’s back and forward button functionality, Internet Patent Corp., MPEP 2106.05(d)(II)(ii); presenting and/or outputting one or more visual indicia, such as the cognitive function training app, outputting the user state information, e.g. presenting offers and gathering statistics, OIP Techs, MPEP 2106.05(d)(II)(iv)).
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 2-12 & 14-15, additional limitations which amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields, e.g. claims 2-6, which recite limitations relating to receiving user information, the type of user information being received, outputting one or more information, e.g., receiving or transmitting data over a network, Symantec, MPEP 2106.05(d)(II)(i); claims 7-12 & 14, which recite limitations relating to further specifying optimizing the cognitive functioning training or the cognitive functioning training app, such as by making determinations on received information, e.g., performing repetitive calculations, Flook, MPEP 2106.05(d)(II)(ii); claims 7-12 & 14, which recite limitations relating to maintaining record or updating parameters relating to the cognitive function of the user or the user’s associated cognitive function training, e.g., electronic recordkeeping, Alice Corp., MPEP 2106.05(d)(II)(iii); claims 2-12 & 14-15, which generally recite limitations relating to performance of steps performed by a computer when a processor executes said computerized steps/instructions, storing of one or more received user information/outputted information e.g., storing and retrieving information in memory, Versata Dev. Group, MPEP 2106.05(d)(II)(iv); claim 3, which recites limitations relating to receiving information about the user, including a schedule of the user, which under BRI could include extraction from a physical or electronic document, e.g., electronic scanning or extracting data from a physical document, Content Extraction, MPEP 2106.05(d)(II)(v); claims 7-12 & 14, which recite limitations relating to receiving user input at the terminal, or information relating to said user input such as fatigue level, etc., e.g., a web browser’s back and forward button functionality, Internet Patent Corp., MPEP 2106.05(d)(II)(ii)). 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 (SME Test Step 2B: No).
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.
Claims 1-12 & 14-16 are rejected under 35 U.S.C. 103 as being unpatentable over Sachs et al. (U.S. Patent Publication No. 2020/0302825), hereinafter “Sachs”, in view of Ellison et al. (U.S. Patent Publication No. 2020/0253527), hereinafter “Ellison”, further in view of Oser et al. (U.S. Patent Publication No. 2020/0411185), hereinafter “Oser”.
Claim 1 –
Regarding Claim 1, Sachs discloses a method for controlling an improved cognitive function training app, the method comprising:
outputting, via an output device of the terminal, an application algorithm of the app through based on the app being initiated (See Sachs Par [0075] which discloses the delivery of content via the internet and/or mobile device applications; See Sachs Par [0086] which discloses a human subject utilizing a user interface in order to access and utilize, i.e. initiate, the therapy selection system and further discloses the therapy selection system providing relevant data outputs of therapy content (e.g., photos, audio, video, etc.) via the user interface, as the therapy selection system controls a progression and presentation of the exposure therapy content in a controlled manner; See Sachs Par [0177]-[0179] which discloses that the system does not have to just be used for exposure therapy or psychological reasons, and can be applied to nontherapeutic applications such as education, training, entertainment, or advertising, among other fields of use, such as the user being exposed to a certain scenario by an interactive or passive audiovisual display); wherein
the algorithm comprises an output of one or more of a visual indication comprising one or more of a color, shape, pattern, text, or sparkle or an audible indication comprising one or more of music or speech (See Sachs Par [0010] & [0012] & [0175] which discloses that the stimulation can comprise one or more of light, lighting, light patterns, flash, shade, darkness, colors, wavelengths, images, imagery, photos, video, videos, video clips, movies, optics, written material, internet content, or other visual or nonvisual stimuli of the visual system, including in connection with audio-visual content, virtual reality, and augmented reality and stimulation provided thereof);
wherein the optimizing the application algorithm based on information of the user (See Sachs Par [0086] & Fig. 6 which disclose the therapy selection system provides/controls relevant data outputs of therapy content via the user interface and obtains data from various physiological monitoring tools (e.g., sensors, medical devices) used to monitor the subject; See Sachs Par [0088]-[0089] & Fig. 6 which disclose the system selecting appropriate scenes or clips based upon desired anxiety levels as quantified by physiological responses to the scenes, such as those being captured by the physiological monitoring tools; See Sachs Par [0085] which discloses titrating and/or timing the content outputted to optimize the impact of the sensory stimulation, thereby constituting changing a “format” of the content under BRI since the timing and/or duration or intensity of the content is being optimized, and this optimization occurs in response to specific changes in body signals or changes that are measured with sensing, such as relative to electroencephalogram phase, brain or nerve signals, markers in blood or tissue fluids or gases, or relative to other sensed physiological signals at a specific phase or at specific phases of oscillations in sensed body signals to maximize the effectiveness of the desired outcome or for a specific disorder or unwanted condition) comprises calculating a fatigue level of the user based on a new input from the user (See Sachs Par [0119] which discloses changes in responsiveness (e.g. fatigue), over time will show effects of stimulation or time-linked changes in the severity of the disorder, such that a therapy approach can be modified based on said reactivities or sensitivities to media content; See Sachs Par [0157] which discloses charting responses of the user, such as depicting how a total session’s responses vary and change over time with each successive, i.e. new, input of the user, allowing for responsiveness to be determined over time, such as a generally decreasing responsiveness, etc.; See Sachs Par [0158] which specifically discloses slope or ramping levels/rate of change in responsiveness, i.e. calculating a level of responsiveness, such as based on the charted responses described in Sachs Par [0157]), and adjusting a progress speed of the optimized cognitive function training algorithm based on the calculated fatigue level (See Sachs Par [0174] which discloses depending on various scores or levels, such as responsiveness, e.g. fatigue as described in Sachs Par [0119], the time course of response and responsiveness to anxiety stimulation can be used to modify the time course for reduction, such that the timing/progress of the session can be changed to rapid or slow; See Sachs Par [0085] which discloses titrating and/or timing the content outputted to optimize the impact of the sensory stimulation, thereby constituting changing a format in the form of “progress speed” of the content under BRI since the timing and/or duration or intensity of the content is being optimized, and this optimization occurs in response to specific changes in body signals or changes that are measured with sensing, such as relative to electroencephalogram phase, brain or nerve signals, markers in blood or tissue fluids or gases, or relative to other sensed physiological signals at a specific phase or at specific phases of oscillations in sensed body signals to maximize the effectiveness of the desired outcome or for a specific disorder or unwanted condition), wherein
the adjusting of the progress speed of the application algorithm is based on a fatigue level of the user being greater than a preset level and comprises stopping the application algorithm for a preset time period, or changing a training speed of the application algorithm (See Sachs Par [0081] which discloses the level of distress induced by sensory stimulation is gradually increased until the target threshold of net sympathetic-parasympathetic drive or distress or anxiety for that session is reached; See Sachs Par [0119] which discloses determining changes in responsiveness, e.g. net sympathetic-parasympathetic drive or distress or anxiety, over time showing effects of stimulation or time-lined changes in severity of disorder/sensory stimulation, e.g. in relation to time of day, fatigue, distractions, emotional states, comorbidities, or medication use) and can modify a therapy approach during a session or across multiple sessions over the course of therapy in accordance with said changes; See Sachs Par [0085] which discloses titrating and/or timing the content outputted to optimize the impact of the sensory stimulation, thereby constituting changing a format in the form of “progress speed” of the content under BRI since the timing and/or duration or intensity of the content is being optimized, and this optimization occurs in response to specific changes in body signals or changes that are measured with sensing, such as relative to electroencephalogram phase, brain or nerve signals, markers in blood or tissue fluids or gases, or relative to other sensed physiological signals at a specific phase or at specific phases of oscillations in sensed body signals to maximize the effectiveness of the desired outcome or for a specific disorder or unwanted condition);
receiving response inputs in response to the application algorithm (See Sachs Par [0119] which discloses determining changes in responsiveness over time showing effects of stimulation or time-lined changes in severity of disorder/sensory stimulation, i.e. response inputs under BRI, and can modify a therapy approach during a session or across multiple sessions over the course of therapy in accordance with said changes);
generating a new application algorithm based on the response inputs (See Sachs Par [0119] which discloses determining changes in responsiveness over time showing effects of stimulation or time-lined changes in severity of disorder/sensory stimulation and can modify a therapy approach, i.e. generate a new algorithm, during a session or across multiple sessions over the course of therapy in accordance with said changes; See Sachs Par [0096] which specifically discloses the resulting physiological signals being used as feedback to modify the therapy session (or start a new session, i.e. new algorithm) or to provide model training, reinforcement, or modification), wherein
the new application algorithm comprises a new combination of terminal outputs comprising one or more of a visual indication comprising one or more of a color, shape, pattern, text, or sparkle, or an audible indication comprising one or more of music or speech (See Sachs Par [0010] & [0012] & [0175] which discloses that the stimulation can comprise one or more of light, lighting, light patterns, flash, shade, darkness, colors, wavelengths, images, imagery, photos, video, videos, video clips, movies, optics, written material, internet content, or other visual or nonvisual stimuli of the visual system, including in connection with audio-visual content, virtual reality, and augmented reality and stimulation provided thereof);
sending, based on the response inputs or based on new response inputs associated with the new application algorithm, user state information to an electronic medical record or an external system device (See Sachs Par [0104]-[0105] which discloses calculating states of the patient relevant physiological responses and may be recorded and displayed, albeit not explicitly recited for being recorded in an EMR or externals system device; See Sachs Par [0125] which discloses patients and subjects can be monitored using multiple measurement systems to quantify physiological measures of anxiety, physiological stress and state of autonomic activation); and
outputting, via the output device, the user state information (See Sachs Par [0104]-[0105] which discloses calculating states of the patient relevant physiological responses and may be recorded and displayed).
While Sachs generally discloses a cognitive function training application and associated algorithm, Sachs does not seem to explicitly disclose a user initiating said training session/software as given by the limitation:
receiving an input from a user via a terminal to initiate an app.
However, Ellison discloses receiving an input from a user via a terminal to initiate an app (See Ellison Par [0329]-[0330] which discloses a user interacting with an application/software such that assessment assessments of speed and accuracy, and movement mapping can be made depending on the user interactions; See Ellison Par [0332]-[0333] which discloses a user interactive workspace wherein the interactivity exercise is started by the user clicking the start button when he or she is ready; See Ellison Par [0338] which discloses upon the user clicking the start button, time information and an associated time stamp is recorded, therefore allowing for time tracking of user’s interaction sessions). The disclosure of Ellison is directly applicable to the disclosure of Sachs because both disclosures share limitations and capabilities, such as being directed towards an interactive software for increasing mental capabilities of a user.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the disclosure of Sachs, which already discloses a cognitive function training application and associated algorithm to further include receiving an input from a user via a terminal to initiate said cognitive function training app, as disclosed by Sachs, because this allows for time information and an associated time stamp to be recorded upon the start button being clicked, allowing for time tracking of user’s interaction sessions (See Ellison Par [0338]).
While Sachs and Ellison generally disclose sending user state information to a database/system, Sachs and Ellison are relatively silent on said database/system specifically being an EMR.
sending, based on the response inputs or based on new response inputs associated with the new application algorithm, user state information to an electronic medical record or an external system device.
However, Oser discloses sending, based on the response inputs or based on new response inputs associated with the new application algorithm, user state information to an electronic medical record or an external system device (See Oser Par [0129] & [0133] which discloses adjusting order of and/or content of intervention modules provided, where intervention types and content are described above and updating electronic health records by writing or modifying records whenever new information is generated regarding the user/subject/patient, and can include patient health behavior or health statuses and changes thereof). The disclosure of Oser is directly applicable to the disclosure of Sachs and Ellison, because the disclosures share limitations and capabilities, such as being directed towards developing one or more interventions for a patient/user of a user interface, such that content of the intervention can be modified based on user status.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the disclosure of Sachs and Ellison, which already discloses sending user state information to a database/system, to further specifically include said database/system specifically being an electronic medical record system, because this allows for the system being configured to transmit a notification providing information regarding the type of care, content of intervention, intervention types, etc. the subject has received, and to use this data for monitoring statuses of the subject over time in the electronic health record (See Oser Par [0129] & [0133]).
Claim 2 –
Regarding Claim 2, Sachs, Ellison, and Oser disclose the method of claim 1 in its entirety. Sachs further discloses a method, wherein:
the information of the user is information that is previously collected by a sensor of the terminal (See Sachs Par [0088]-[0089] & Fig. 6 which disclose the system selecting appropriate scenes or clips based upon desired anxiety levels as quantified by physiological responses to the scenes, such as those being captured by the physiological monitoring tools, including implanted devices, percutaneously inserted devices, minimally invasive devices, wearable devices, noninvasive devices such as handheld personal devices, or non-contact methods such as a camera or infrared sensor, or specific devices such as smart watch, fitness tracker, chest belt, smart bra or other clothing with sensors, disposable patches, tattoos, electrode tattoos, ear buds or headphones).
Claim 3 –
Regarding Claim 3, Sachs, Ellison, and Oser disclose the method of claim 1 in its entirety. Sachs further discloses a method, wherein:
the information of the user is information about a biosignal-based circadian rhythm of the user collected by a sensor of the terminal, and a schedule of the user (See Sachs Par [0088]-[0089] & Fig. 6 which disclose the system selecting appropriate scenes or clips based upon desired anxiety levels as quantified by physiological responses to the scenes, such as those being captured by the physiological monitoring tools, including implanted devices, percutaneously inserted devices, minimally invasive devices, wearable devices, noninvasive devices such as handheld personal devices, or non-contact methods such as a camera or infrared sensor, or specific devices such as smart watch, fitness tracker, chest belt, smart bra or other clothing with sensors, disposable patches, tattoos, electrode tattoos, ear buds or headphones; See Sachs Par [0085] which discloses consideration of biological rhythms including circadian, diurnal, ultradian, or infradian rhythms and that sensory stimulation patterns could be delivered relative to sleep phase, sleep schedule, appetite, body temperature, hormone levels, alertness, blood pressure, or reaction times, and the sensory stimulation patterns could be delivered relative to specific changes in body signals or changes that are measured with sensing, such as relative to electroencephalogram phase, brain or nerve signals, markers in blood or tissue fluids or gases, or relative to other sensed physiological signals at a specific phase or at specific phases of oscillations in sensed body signals to maximize the effectiveness of the desired outcome or for a specific disorder or unwanted condition).
Claim 4 –
Regarding Claim 4, Sachs, Ellison, and Oser disclose the method of claim 1 in its entirety. Sachs further discloses a method, wherein:
the information of the user is at least one of a sleeping time of the user, a number of housemates of the user, an outdoor activity level of the user, and a depression level of the user, which are input after the app is first executed (See Sachs Par [0085] which discloses consideration of biological rhythms including circadian, diurnal, ultradian, or infradian rhythms and that sensory stimulation patterns could be delivered relative to sleep phase, sleep schedule, appetite, body temperature, hormone levels, alertness, blood pressure, or reaction times, and the sensory stimulation patterns could be delivered relative to specific changes in body signals or changes that are measured with sensing, such as relative to electroencephalogram phase, brain or nerve signals, markers in blood or tissue fluids or gases, or relative to other sensed physiological signals at a specific phase or at specific phases of oscillations in sensed body signals to maximize the effectiveness of the desired outcome or for a specific disorder or unwanted condition; See Sachs Par [0104]-[0105] which discloses that the physiological responses and/or cognitive of the patient are observed in real-time or after playback of the media content and the states or measurements may be used to calculate physiological response progress between sessions, scenes, or other observations, i.e. after the cognitive function training app is first executed; See Sachs Par [0014] which discloses a wide range of physiological parameters that can be collected by the system including, sleep quality, disturbances, changes, schedule, and sadness, i.e. depression, levels).
Claim 5 –
Regarding Claim 5, Sachs, Ellison, and Oser disclose the method of claim 1 in its entirety. Sachs further discloses a method, wherein:
the optimizing comprises visually or aurally outputting a training time range of day that is most appropriate for the user (See Sachs Par [0085] which discloses consideration of biological rhythms including circadian, diurnal, ultradian, or infradian rhythms and that sensory stimulation patterns could be delivered relative to sleep phase, sleep schedule, appetite, body temperature, hormone levels, alertness, blood pressure, or reaction times, and the sensory stimulation patterns could be delivered relative to specific changes in body signals or changes that are measured with sensing, such as relative to electroencephalogram phase, brain or nerve signals, markers in blood or tissue fluids or gases, or relative to other sensed physiological signals at a specific phase or at specific phases of oscillations in sensed body signals to maximize the effectiveness of the desired outcome or for a specific disorder or unwanted condition; See Sachs Par [0177]-[0179] which discloses that the system does not have to just be used for exposure therapy or psychological reasons, and can be applied to nontherapeutic applications such as education, training, entertainment, or advertising, among other fields of use, such as the user being exposed to a certain scenario by an interactive or passive audiovisual display, i.e. visual or aural output).
Claim 6 –
Regarding Claim 6, Sachs, Ellison, and Oser disclose the method of claim 1 in its entirety. Sachs further discloses a method, wherein:
the information of the user is external information about a day on which the app provides the application algorithm, and personal information of the user on the day (See Sachs Par [0104]-[0105] which discloses that the physiological responses and/or cognitive of the patient are observed in real-time or after playback of the media content and the states or measurements may be used to calculate physiological response progress between sessions, scenes, or other observations, i.e. after the cognitive function training app is first executed; See Sachs Par [0085] which discloses consideration of biological rhythms including circadian, diurnal, ultradian, or infradian rhythms, i.e. daily, within a day, between days, or slightly more than a day rhythms, constituting external information about a day, between days, within a day, or slightly more than a day, and that sensory stimulation patterns could be delivered relative to sleep phase, sleep schedule, appetite, body temperature, hormone levels, alertness, blood pressure, or reaction times, and the sensory stimulation patterns could be delivered relative to specific changes in body signals or changes that are measured with sensing, such as relative to electroencephalogram phase, brain or nerve signals, markers in blood or tissue fluids or gases, or relative to other sensed physiological signals at a specific phase or at specific phases of oscillations in sensed body signals to maximize the effectiveness of the desired outcome or for a specific disorder or unwanted condition).
Claim 7 –
Regarding Claim 7, Sachs, Ellison, and Oser disclose the method of claim 1 in its entirety. Sachs further discloses a method, wherein:
the optimizing comprises, after determining that the app has been initiated, optimizing the application algorithm in real time by considering collected inputs from the user (See Sachs Par [0104]-[0105] which discloses that the physiological responses and/or cognitive of the patient are observed in real-time or after playback of the media content and the states or measurements may be used to calculate physiological response progress between sessions, scenes, or other observations, i.e. after the cognitive function training app is first execute).
Claim 8 –
Regarding Claim 8, Sachs, Ellison, and Oser disclose the method of claim 7 in its entirety. Sachs further discloses a method, wherein:
the optimizing further comprises, based on the inputs from the user being greater than a preset level, stopping the application algorithm for a preset time period, or changing a training speed of the application algorithm (See Sachs Par [0115] which discloses the measurement of a physiological response measurement between the second measurement and the first measurement, followed by a series of evaluations relative to scene targets. e.g. evaluations may include, a first evaluation based on whether a peak physiological response magnitude for a scene is met or exceeded, i.e. greater than a preset level; a second evaluation based on whether a physiological response target reduction in anxiety over time also referred to as decay for a scene is met or exceeded; and a third evaluation based on whether response target totals for a scene is met or exceeded, i.e. greater than a preset level, and subsequently changing; subject; See Sachs Par [0088]-[0089] & Fig. 6 which disclose the system selecting appropriate scenes or clips based upon desired anxiety levels as quantified by physiological responses to the scenes, such as those being captured by the physiological monitoring tools or by physiological response measurement described in Sachs Par [0115]).
Claim 9 –
Regarding Claim 9, Sachs, Ellison, and Oser disclose the method of claim 7 in its entirety. Sachs further discloses a method, wherein:
the optimizing further comprises, based on the inputs from the user being less than or equal to a preset level, stopping the application algorithm for a preset time period, or changing a training speed of the application algorithm (See Sachs Par [0115] which discloses the measurement of a physiological response measurement between the second measurement and the first measurement, followed by a series of evaluations relative to scene targets. e.g. evaluations may include, a first evaluation based on whether a peak physiological response magnitude for a scene is met or exceeded, i.e. greater than a preset level; a second evaluation based on whether a physiological response target reduction in anxiety over time also referred to as decay for a scene is met or exceeded; and a third evaluation based on whether response target totals for a scene is met or exceeded, i.e. greater than a preset level, and subsequently changing; subject; See Sachs Par [0088]-[0089] & Fig. 6 which disclose the system selecting appropriate scenes or clips based upon desired anxiety levels as quantified by physiological responses to the scenes, such as those being captured by the physiological monitoring tools or by physiological response measurement described in Sachs Par [0115]; See Sachs Par [0121] which discloses when a subject becomes less attentive, i.e. attention less than or equal to a preset level, media content of increasing distress could be titrated to establish the level of content distress that causes the subject to look away or subsequent content could then be selected so that the subject would tolerate viewing the content without looking away).
Claim 10 –
Regarding Claim 10, Sachs, Ellison, and Oser disclose the method of claim 7 in its entirety. Sachs further discloses a method, wherein:
the optimizing further comprises collecting inputs irrelevant to the user in addition to the inputs from the user, and based on the collected inputs irrelevant to the user being greater than a preset level, stopping the application algorithm (See Sachs Par [0124] which discloses collecting inputs relating to signal capture quality and/or tracking adequacy, i.e. whether signals are being successfully captured, and if a threshold number of signals lose concordance the signal capture can be discontinued or an alert could indicate loss of concordance, i.e. the cognitive function process stopping if a sensor reading becomes unavailable, constituting inputs irrelevant to the user and upon the collected inputs irrelevant to the user being greater than a preset level, stopping the training/recording session; See Sachs Par [0115] which discloses the measurement of a physiological response measurement between the second measurement and the first measurement, followed by a series of evaluations relative to scene targets. e.g. evaluations may include, a first evaluation based on whether a peak physiological response magnitude for a scene is met or exceeded, i.e. greater than a preset level; a second evaluation based on whether a physiological response target reduction in anxiety over time also referred to as decay for a scene is met or exceeded; and a third evaluation based on whether response target totals for a scene is met or exceeded, i.e. greater than a preset level, and subsequently changing; subject; See Sachs Par [0088]-[0089] & Fig. 6 which disclose the system selecting appropriate scenes or clips based upon desired anxiety levels as quantified by physiological responses to the scenes, such as those being captured by the physiological monitoring tools or by physiological response measurement described in Sachs Par [0115]).
Claim 11 –
Regarding Claim 11, Sachs, Ellison, and Oser disclose the method of claim 10 in its entirety. Sachs further discloses a method, wherein:
the providing of the optimized application algorithm through the terminal comprises stopping the application algorithm until the inputs from the user fall below a certain level (See Sachs Par [0121] which discloses when a subject becomes less attentive, i.e. attention less than or equal to a preset level, media content of increasing distress could be titrated to establish the level of content distress that causes the subject to look away, i.e. attentiveness falls below a certain level, or subsequent content could then be selected so that the subject would tolerate viewing the content without looking away).
Claim 12 –
Regarding Claim 12, Sachs, Ellison, and Oser disclose the method of claim 1 in its entirety. Sachs further discloses a method, wherein:
the providing of the optimized application algorithm through the terminal comprises, based on the input from the user satisfying a preset condition, outputting at least one of visual guide information and auditory guide information through the terminal (See Sachs Par [0177]-[0179] which discloses that the system does not have to just be used for exposure therapy or psychological reasons, and can be applied to nontherapeutic applications such as education, training, entertainment, or advertising, among other fields of use, such as the user being exposed to a certain scenario by an interactive or passive audiovisual display, i.e. visual or aural output; See Sachs Par [0115] which discloses the measurement of a physiological response measurement between the second measurement and the first measurement, followed by a series of evaluations relative to scene targets. e.g. evaluations may include, a first evaluation based on whether a peak physiological response magnitude for a scene is met or exceeded, i.e. greater than a preset level; a second evaluation based on whether a physiological response target reduction in anxiety over time also referred to as decay for a scene is met or exceeded; and a third evaluation based on whether response target totals for a scene is met or exceeded, i.e. greater than a preset level, and subsequently changing).
Claim 14 –
Regarding Claim 14, Sachs, Ellison, and Oser disclose the method of claim 1 in its entirety. Sachs further discloses a method, wherein:
the optimizing comprises calculating a fatigue level of the user based on the input from the user, and determining whether to proceed with the optimized application algorithm, based on the calculated fatigue level (See Sachs Par [0119] which discloses monitoring of responsiveness in the user, such as relation to time of day, fatigue, distractions, emotional states, comorbidities, or medication use; See Sachs Par [0085] which discloses titrating and/or timing the content outputted to optimize the impact of the sensory stimulation, thereby constituting changing a format in the form of “progress speed” of the content under BRI since the timing and/or duration or intensity of the content is being optimized, and this optimization occurs in response to specific changes in body signals or changes that are measured with sensing, such as relative to electroencephalogram phase, brain or nerve signals, markers in blood or tissue fluids or gases, or relative to other sensed physiological signals at a specific phase or at specific phases of oscillations in sensed body signals to maximize the effectiveness of the desired outcome or for a specific disorder or unwanted condition).
Claim 15 –
Regarding Claim 15, Sachs, Ellison, and Oser disclose a non-transitory computer-readable recording medium having recorded thereon a program for causing a computer to execute the method of claim 1 (See Sachs Par [0225]-[0226] for a machine-readable storage medium and 35 U.S.C. 103 rejection of claim 1 above).
Claim 16 –
Regarding Claim 16, Sachs discloses a device for controlling an improved cognitive function training app, the device comprising:
a processor programmed to (See Sachs Par [0224] which discloses a processor or CPU for performing steps recited):
output, via an output device of the terminal, an application algorithm of the app through an output device of the terminal based on the app being initiated (See Sachs Par [0086] which discloses a human subject utilizing a user interface in order to access and utilize, i.e. initiate, the therapy selection system and further discloses the therapy selection system providing relevant data outputs of therapy content (e.g., photos, audio, video, etc.) via the user interface, as the therapy selection system controls a progression and presentation of the exposure therapy content in a controlled manner; See Sachs Par [0177]-[0179] which discloses that the system does not have to just be used for exposure therapy or psychological reasons, and can be applied to nontherapeutic applications such as education, training, entertainment, or advertising, among other fields of use, such as the user being exposed to a certain scenario by an interactive or passive audiovisual display, and therefore is understood to read on “cognitive function training” hereinafter);
optimize the application algorithm by changing a format in which the app outputs the application algorithm based on information of the user of the terminal of the terminal (See Sachs Par [0086] & Fig. 6 which disclose the therapy selection system provides/controls relevant data outputs of therapy content via the user interface and obtains data from various physiological monitoring tools (e.g., sensors, medical devices) used to monitor the subject; See Sachs Par [0088]-[0089] & Fig. 6 which disclose the system selecting appropriate scenes or clips based upon desired anxiety levels as quantified by physiological responses to the scenes, such as those being captured by the physiological monitoring tools; See Sachs Par [0085] which discloses titrating and/or timing the content outputted to optimize the impact of the sensory stimulation, thereby constituting changing a “format” of the content under BRI since the timing and/or duration or intensity of the content is being optimized, and this optimization occurs in response to specific changes in body signals or changes that are measured with sensing, such as relative to electroencephalogram phase, brain or nerve signals, markers in blood or tissue fluids or gases, or relative to other sensed physiological signals at a specific phase or at specific phases of oscillations in sensed body signals to maximize the effectiveness of the desired outcome or for a specific disorder or unwanted condition); and
based on the app being initiated or resumed (See Sachs Par [0086] which discloses a human subject utilizing a user interface in order to access and utilize, i.e. initiate, the therapy selection system; See Sachs Par [0086] & Fig. 6 which disclose the therapy selection system provides/controls relevant data outputs of therapy content via the user interface and obtains data from various physiological monitoring tools (e.g., sensors, medical devices) used to monitor the subject; See Sachs Par [0088]-[0089] & Fig. 6 which disclose the system selecting appropriate scenes or clips based upon desired anxiety levels as quantified by physiological responses to the scenes, such as those being captured by the physiological monitoring tools), wherein
the optimization of the application algorithm is based on a fatigue level of the user based on a fatigue level of the user based on a new input from the user (See Sachs Par [0119] which discloses changes in responsiveness (e.g. fatigue), over time will show effects of stimulation or time-linked changes in the severity of the disorder, such that a therapy approach can be modified based on said reactivities or sensitivities to media content; See Sachs Par [0157] which discloses charting responses of the user, such as depicting how a total session’s responses vary and change over time with each successive, i.e. new, input of the user, allowing for responsiveness to be determined over time, such as a generally decreasing responsiveness, etc.; See Sachs Par [0158] which specifically discloses slope or ramping levels/rate of change in responsiveness, i.e. calculating a level of responsiveness, such as based on the charted responses described in Sachs Par [0157]) and comprises adjustment of a progress speed of the optimized cognitive function training based on the calculated fatigue level (See Sachs Par [0174] which discloses depending on various scores or levels, such as responsiveness, e.g. fatigue as described in Sachs Par [0019], the time course of response and responsiveness to anxiety stimulation can be used to modify the time course for reduction, such that the timing/progress of the session can be changed to rapid or slow); wherein
the adjustment of the progress speed of the application algorithm is based on a fatigue level of the user being greater than a preset level and comprises stopping the application algorithm for a preset time period, or changing a training speed of the application algorithm (See Sachs Par [0081] which discloses the level of distress induced by sensory stimulation is gradually increased until the target threshold of net sympathetic-parasympathetic drive or distress or anxiety for that session is reached; See Sachs Par [0119] which discloses determining changes in responsiveness, e.g. net sympathetic-parasympathetic drive or distress or anxiety, over time showing effects of stimulation or time-lined changes in severity of disorder/sensory stimulation, e.g. in relation to time of day, fatigue, distractions, emotional states, comorbidities, or medication use) and can modify a therapy approach during a session or across multiple sessions over the course of therapy in accordance with said changes; See Sachs Par [0085] which discloses titrating and/or timing the content outputted to optimize the impact of the sensory stimulation, thereby constituting changing a format in the form of “progress speed” of the content under BRI since the timing and/or duration or intensity of the content is being optimized, and this optimization occurs in response to specific changes in body signals or changes that are measured with sensing, such as relative to electroencephalogram phase, brain or nerve signals, markers in blood or tissue fluids or gases, or relative to other sensed physiological signals at a specific phase or at specific phases of oscillations in sensed body signals to maximize the effectiveness of the desired outcome or for a specific disorder or unwanted condition);
receive response inputs in response to the application algorithm (See Sachs Par [0119] which discloses determining changes in responsiveness over time showing effects of stimulation or time-lined changes in severity of disorder/sensory stimulation, i.e. response inputs under BRI, and can modify a therapy approach during a session or across multiple sessions over the course of therapy in accordance with said changes);
generate a new application algorithm based on the response inputs (See Sachs Par [0119] which discloses determining changes in responsiveness over time showing effects of stimulation or time-lined changes in severity of disorder/sensory stimulation and can modify a therapy approach, i.e. generate a new algorithm, during a session or across multiple sessions over the course of therapy in accordance with said changes; See Sachs Par [0096] which specifically discloses the resulting physiological signals being used as feedback to modify the therapy session (or start a new session, i.e. new algorithm) or to provide model training, reinforcement, or modification), wherein
the new application algorithm comprises a new combination of terminal outputs comprising one or more of a visual indication comprising one or more of a color, shape, pattern, text, or sparkle, or an audible indication comprising one or more of music or speech (See Sachs Par [0010] & [0012] & [0175] which discloses that the stimulation can comprise one or more of light, lighting, light patterns, flash, shade, darkness, colors, wavelengths, images, imagery, photos, video, videos, video clips, movies, optics, written material, internet content, or other visual or nonvisual stimuli of the visual system, including in connection with audio-visual content, virtual reality, and augmented reality and stimulation provided thereof);
send, based on the response inputs or based on new response inputs associated with the new application algorithm, user state information to an electronic medical record or an external system device (See Sachs Par [0104]-[0105] which discloses calculating states of the patient relevant physiological responses and may be recorded and displayed, albeit not explicitly recited for being recorded in an EMR or externals system device; See Sachs Par [0125] which discloses patients and subjects can be monitored using multiple measurement systems to quantify physiological measures of anxiety, physiological stress and state of autonomic activation); and
output, via the output device, the user state information (See Sachs Par [0104]-[0105] which discloses calculating states of the patient relevant physiological responses and may be recorded and displayed).
While Sachs generally discloses a cognitive function training application and associated algorithm, Sachs does not seem to explicitly disclose a user initiating said training session/software as given by the limitation:
receive an input from a user via a terminal to initiate a cognitive function training app.
However, Ellison discloses receive an input from a user via a terminal to initiate a cognitive function training app (See Ellison Par [0329]-[0330] which discloses a user interacting with an application/software such that assessment assessments of speed and accuracy, and movement mapping can be made depending on the user interactions; See Ellison Par [0332]-[0333] which discloses a user interactive workspace wherein the interactivity exercise is started by the user clicking the start button when he or she is ready; See Ellison Par [0338] which discloses upon the user clicking the start button, time information and an associated time stamp is recorded, therefore allowing for time tracking of user’s interaction sessions).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the disclosure of Sachs, which already discloses a cognitive function training application and associated algorithm to further include receiving an input from a user via a terminal to initiate said cognitive function training app, as disclosed by Sachs, because this allows for time information and an associated time stamp to be recorded upon the start button being clicked, allowing for time tracking of user’s interaction sessions (See Ellison Par [0338]).
While Sachs and Ellison generally disclose sending user state information to a database/system, Sachs and Ellison are relatively silent on said database/system specifically being an EMR.
sending, based on the response inputs or based on new response inputs associated with the new application algorithm, user state information to an electronic medical record or an external system device.
However, Oser discloses sending, based on the response inputs or based on new response inputs associated with the new application algorithm, user state information to an electronic medical record or an external system device (See Oser Par [0129] & [0133] which discloses adjusting order of and/or content of intervention modules provided, where intervention types and content are described above and updating electronic health records by writing or modifying records whenever new information is generated regarding the user/subject/patient, and can include patient health behavior or health statuses and changes thereof).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the disclosure of Sachs and Ellison, which already discloses sending user state information to a database/system, to further specifically include said database/system specifically being an electronic medical record system, because this allows for the system being configured to transmit a notification providing information regarding the type of care, content of intervention, intervention types, etc. the subject has received, and to use this data for monitoring statuses of the subject over time in the electronic health record (See Oser Par [0129] & [0133]).
Response to Arguments
Applicant's arguments filed 12 June 2025 have been fully considered but they are not persuasive:
Regarding 35 U.S.C. 101 rejections of Claims 1-12 & 14-16, Applicant argues on p. 6-10 of Arguments/Remarks that the claims, as amended, do not recite a judicial exception, but instead recite features not practically performed in a human mind, similar to Example 39 reciting training a neural network for facial detection, and therefore 35 U.S.C. 101 rejections of claims 1-16 should be withdrawn in view of the newly amended limitations, and further argues that the amendments integrate any judicial exception into a practical application. Examiner respectfully disagrees with Applicant’s arguments. While Applicant generally argues against each grouping of abstract idea, Applicant seems to focus on the mental processes grouping of abstract ideas as given by the language “the recitations include features not practically performed in a human mind, similar to Example 39 reciting training a neural network for facial detection”. However, if a computer is performing the method of organizing human activity, the claim under BRI still recites methods of organizing human activity, albeit recited for operation by computer technology instead of humans. That is, if a computer is performing the steps of filtering content based on user interaction with content and/or therapy and/or recites a mental process that should be followed when testing a patient for nervous system malfunctions, then the claims still contain efforts of organizing human activity but merely recited for an electronic system performing the actions, instead of a neurologist, and reads as mere instructions to apply an exception using generic computer technology/components. Therefore the claims wholly differ from Example 39 which did not utilize generic computer technology to merely accomplish or perform a judicial exception. Furthermore, regarding methods of organizing human activity, Applicant argues against the aspects managing interactions between people, but the steps recited clearly relate to a therapy applied to a patient by one or more providers via a computer system, and optimization/modification of said therapy based on patient physiological responses and inputs/feedbacks. While Applicant further argues on p. 9-10 of Arguments/Remarks that the limitations recited in claims 1 & 16 amount to efforts that integrate any judicial exception into a practical application, this reads as mere restatements of subject matter eligibility patentability instead of additional proof/evidence pointing to said practical application, because no additional substantiation. While Examiner notes recent guidance regarding Desjardins and optimization or learning algorithms and parameters thereof, which may be similar to the instant disclosure, Examiner also identifies that the instant claims merely elect the aspects of the application algorithm being generated or optimized is the one or more content and/or visual indications comprising one or more of a color, shape pattern, text, or sparkle or an audible indication comprising one or more of a music or speech As such, claims 1-12 & 14-16 remain rejected under 35 U.S.C. 101.
Regarding 35 U.S.C. 103 rejections of Claims 1-12 & 14-16, Applicant argues on p. 10-15 of Arguments/Remarks that Sachs and Ellison do not disclose all the newly amended elements found in independent claims 1 & 16 and therefore fails to anticipate independent claims 1 & 16. Examiner agrees with Applicant’s arguments. More specifically, Examiner agrees that Sachs and Ellison do not disclose the newly amended limitation regarding “sending, based on the response inputs or based on new response inputs associated with the new application algorithm, user state information to an electronic medical record or an external system device”. Therefore, the 35 U.S.C. 103 rejections for claims 1-12 & 14-16 have been withdrawn. However, upon further consideration, a new ground of rejection has been made under 35 U.S.C. 103 over Sachs, in view of Ellison, further in view of Oser. Oser, which was not previously relied upon fully discloses the limitation regarding “sending, based on the response inputs or based on new response inputs associated with the new application algorithm, user state information to an electronic medical record or an external system device”. Additionally, while Applicant generally argues on p. 10-11 of Arguments/Remarks that Sachs “only specifies fatigue as an example of the cause of the user’s decreased responsiveness and does not directly calculate the fatigue level using the user’s response to sensory stimulation” (See p. 11 of Arguments/Remarks), Examiner maintains that Sachs indeed discloses said aspects and points to Sachs Par [0119] which discloses changes in responsiveness (e.g. fatigue), over time to show effects of stimulation or time-linked changes in the severity of the disorder, such that a therapy approach can be modified based on said reactivities or sensitivities to media content. Further, Sachs Par [0158] specifically discloses slope or ramping levels/rate of change in responsiveness, i.e. calculating a level of responsiveness, (e.g. fatigue as in Sachs Par [0119]). Following this, Sachs Par [0174] discloses depending on various scores or levels, such as responsiveness, e.g. fatigue as described in Sachs Par [0119], the time course of response and responsiveness to anxiety stimulation can be used to modify the time course for reduction, such that the timing/progress of the session can be changed to rapid or slow and/or Sachs Par [0085] discloses titrating and/or timing the content outputted to optimize the impact of the sensory stimulation, thereby constituting changing a format in the form of “progress speed” of the content under BRI since the timing and/or duration or intensity of the content is being optimized, and this optimization occurs in response to specific changes in body signals or changes that are measured with sensing. While Applicant further argues that “…since Sachs does not calculate the user’s fatigue level, the provision of treatment or training may not be stopped or the progression speed may not be adjusted according to the user’s fatigue level as in the present invention”, it remains clear that Sachs Par [0174] discloses depending on various scores or levels, such as responsiveness, e.g. fatigue as described in Sachs Par [0119], the time course of response and responsiveness to anxiety stimulation can be used to modify the time course for reduction, such that the timing/progress of the session can be changed to rapid or slow and/or Sachs Par [0085] discloses titrating and/or timing the content outputted to optimize the impact of the sensory stimulation. As such, it is understood by Examiner that Sachs effectively discloses “directly calculate[ing] the fatigue level using the user’s response to sensory stimulation”, as argued by Applicant. Applicant further argues that “there is a specific difference between the content of adjusting the interval between providing the sensory stimulation of Sachs and the content of stopping the cognitive function training of the present invention or adjusting the progress speed of the cognitive function training of the present invention” (See Arguments/Remarks p. 13). However, Examiner maintains that adjusting the interval between providing sensory stimulation is the same or substantially similar to “adjusting the progress speed of the cognitive function training”, without said adjustments to progress speed being further specified. That is, under BRI “progress speed” of the cognitive function training could relate to multiple aspects of content found in said cognitive function training course/content, such as duration of content, how often content is delivered, how long content remains on a screen, or other embodiments thereof. Therefore, Sachs disclosing adjusting the interval between providing the sensory stimulation substantially reads on adjusting the progress speed of the cognitive function training. While Examiner generally agrees with Applicant that Sachs does not disclose “stopping” said cognitive training, under BRI, this alternative embodiment does not necessarily have to be met because the claim requires “stopping the cognitive function training of the present invention or adjusting the progress speed of the cognitive function training of the present invention”. Applicant argues that Ellison does not remedy the above-argued deficiencies of Sachs , i.e. because Ellison cannot provide customized cognitive function raining to the user according to the user’s current sate (see p. 14-15 of Arguments/Remarks). Examiner argues that Ellison does not need to remedy said aspects of controlling progress of the cognitive function training, because Sachs discloses said aspects in their entirety aside from “sending, based on the response inputs or based on new response inputs associated with the new application algorithm, user state information to an electronic medical record or an external system device”, which is instead met by Oser. As such, independent claims 1 & 16 and claims dependent therefrom remain rejected under 35 U.S.C. 103 over Sachs in view of Ellison, further in view of Oser.
Regarding 35 U.S.C. 103 rejections of Claims 1-16, Applicant argues on p. 15-16 of Arguments/Remarks that because independent claims 1 & 16 are purportedly allowable over the prior art, dependent claims 2-12 & 14-15 which depend from independent claim 1 are also purportedly allowable over the prior art. Examiner respectfully disagrees with Applicant’s arguments. As discussed above, independent claims 1 & 16 remain rejected under a new ground of rejection made under 35 U.S.C. 103 over Sachs, in view of Ellison, further in view of Oser. Therefore, Applicant’s arguments regarding independent claims 1 & 16 being allowable over the prior art are rendered moot by the new ground of rejection. As such, dependent claims 2-12 & 14-15 also 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:
Ozen et al. (U.S. Patent Publication No. 2022/0130518) discloses aspects of receiving affective state of a subject by collecting questionnaire data and/or physiological data, such that subsequently issued mental therapies are based on said affective state of the subject;
Feurerstein et al. (U.S. Patent Publication No. 2022/0319705) discloses a system for accessing electronic health records of the patient and adapt the list of treatment activities based on the electronic health records, such that the electronic health records may indicate the patient's response to previous treatments or lack of previous treatments such that appropriate care and/or precautions may be taken when generating the list of treatments;
Orr et al. (U.S. Patent Publication No. 2020/0178885) discloses a system for adjustment of training protocols in virtual reality (VR) or augmented reality (AR) environments based on biofeedback, such as motion data and biometric measurement, such that the adjustment, the motion data, and/or the biometric measurement may be logged in an electronic health record.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to HUNTER J RASNIC whose telephone number is (571)270-5801. The examiner can normally be reached M-F 8am-5:30pm.
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/H.R./Examiner, Art Unit 3684
/Shahid Merchant/Supervisory Patent Examiner, Art Unit 3684
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