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
This action is in reply to the amendment filed on 01/20/26.
Claims 1-6, 8-10 are amended and are hereby entered.
Claims 1-10 are currently pending and have been examined.
This action is made final.
Foreign Priority
Acknowledgment is made of Applicant's claim for foreign priority based on an application filed in Taiwan on 11/09/2023. A certified copy of the TW112143313 application as required by 37 CFR 1.55 was received on 09/18/24. Accordingly, a priority date of 11/09/23 has been given to this 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 1-10 are rejected under 35 U.S.C.101 because the claimed invention is directed to a judicial exception (an abstract idea) without significantly more.
Step 1
Claims 1-10 are drawn to a method, which is within the four statutory categories. Claims 1-10 are further directed to an abstract idea on the grounds set out in detail below.
Step 2A Prong 1
Claim 1 recites implementing the steps of:
converting biological data into a corresponding training parameter recommendation, including converting the biological data into a standardized score, forming an order list based on the standardized score and generating training parameters for the corresponding training parameter recommendation based on the order list, the standardized score being a distance between a raw value of the biological data and a normative mean represented in units of standard deviation
providing the training parameter recommendation for the subject to perform cognitive training
These steps amount to managing personal behavior or relationships or interactions between people and therefore recite certain methods of organizing human activity. Using biological data to determine a training parameter recommendation for a subject and subsequently provide the recommendation to the subject to perform the recommended cognitive training is a personal behavior that may be performed by a healthcare provider.
The above claims are therefore directed to an abstract idea.
Step 2A Prong 2
This judicial exception is not integrated into a practical application because the additional
elements within the claims only amount to:
A. Instructions to Implement the Judicial Exception. MPEP 2106.05(f)
The independent claims additionally recite:
a cognitive training system as a means of implementing a cognitive training program for a subject
a brainwave database as implementing the step of converting the biological data into a corresponding training parameter recommendation by the brainwave database
remote cloud system as implementing the steps of feeding back (providing) the training parameter recommendation
remote cloud system as implementing the step of feedback back a corresponding training parameter recommendation, converting biological data into a standardized score, forming an order list, and generating training parameters
remotely feeding back a training parameter recommendation, which is interpreted as indicating a computing system is used to remotely perform this step
a neurofeedback cognitive training module as a means of implementing the step of the subject performing cognitive training.
The broad recitation of general purpose computing elements at a high level of generality only amounts to mere instructions to implement the abstract idea using computing components as tools.
Regarding the cognitive training system, the specification does not appear to disclose this exact term, but it does disclose “cognitive training module” which is interpreted as being synonymous; the cognitive training module “includes a desktop computer, a notebook computer and/or smart mobile device” (para. [0013]). This element is therefore given its broadest reasonable interpretation as a general purpose computing device functioning in its ordinary capacity.
Regarding the “brainwave database”, no structural details are provided. Per para. [0027], this is understood to be a general purpose database functioning in its ordinary capacity, e.g., an electronic means of storing data, which only amounts to mere instructions to apply the abstract idea.
Regarding “remotely” feeding back a training parameter recommendation, per paras. [0013], [0027], this is understood to amount to using general purpose computing devices to provide feedback over a network, e.g., remotely, which only amounts to mere instructions to apply the abstract idea.
Regarding the remote cloud system, no particulars of this element are disclosed; the specification only reiterates the language “remote cloud system” (e.g., [0007], [0012], [0027]). Therefore, this element is given its broadest reasonable interpretation as a general purpose computing element functioning in its ordinary capacity.
Regarding “a neurofeedback cognitive training module”, this is understood to using a general purpose desktop, notebook and/or smart mobile device functioning in its ordinary capacity (para. [0013], [0031]) to apply the abstract idea.
B. Insignificant Extra-Solution Activity. MPEP 2106.05(g)
Claim 1 additionally recites
receiving biological data of a subject collected by a brainwave collection device
transmitting the biological data to a brainwave database of a remote cloud system through a network;
The step of receiving biological data of a subject collected by a brainwave collection device only amounts to insignificant extra-solution activity in the form of mere data gathering.
The step of transmitting the biological data to a brainwave database of a remote cloud system through a network only amounts to insignificant extra-solution activity. As stated in MPEP 2106.05(g), "[t]he term "extra-solution activity" can be understood as activities incidental to the primary process or product that are merely a nominal or tangential addition to the claim." In the present claim, the function of transmitting the biological data to a brainwave database of a remote cloud system through a network is only nominally or tangentially related to the process of using biological data to determine a training parameter recommendation for a subject and subsequently providing the recommendation to the subject to perform cognitive training, and accordingly constitutes insignificant extra-solution activity.
These types of activities have been recognized by the courts as well-understood, routine and conventional activity when claimed as insignificant extra-solution activity. See MPEP 2106.05(d).
These elements in Sections A and B above are therefore not sufficient to integrate the abstract idea into a practical application. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually.
The above claims, as a whole, are therefore directed to an abstract idea.
Step 2B
The present claims do not include additional elements that are sufficient to amount to
more than the abstract idea because the additional elements or combination of elements amount to no more than a recitation of:
A. Instructions to Implement the Judicial Exception. MPEP 2106.05(f)
As explained above, claim 1 only recites the aforementioned computing elements as tools for performing the steps of the abstract idea, and mere instructions to perform the abstract idea using a computer is not sufficient to amount to significantly more than the abstract idea. MPEP 2106.05(f).
B. Insignificant Extra-Solution Activity. MPEP 2106.05(g)
Likewise, as explained above, the step of receiving biological data of a subject collected by a brainwave collection device, wherein the brainwave includes a brainwave collection device, only amounts insignificant extra-solution activity in the form of mere data gathering, and the step of transmitting the biological data to a brainwave database of a remote cloud system through a network only amounts to insignificant extra-solution activity.
C. Well-Understood, Routine and Conventional Activities. MPEP 2106.0S(d)
In addition to amounting to insignificant extra-solution activity the elements in Section B above constitute well-understood, routine and conventional activity.
The step of transmitting the biological data to a brainwave database of a remote cloud system through a network only amounts to receiving or transmitting data over a network, which has been previously held to be well-understood, routine and conventional when claimed at a high level of generality or as insignificant extra-solution activity. See MPEP 2106.05(d)(II).
As discussed above with respect to integration of the abstract idea into a practical application, the additional element of receiving biological data of a subject collected by a brainwave collection device was considered extra-solution activity. This has been re-evaluated under the “significantly more” analysis and determined to be well-understood, routine, conventional activity in the field. As evidenced by the prior art of record, receiving biological data of a subject collected by a brainwave collection device is well-understood, routine, and conventional activity in the field of computerized healthcare (see Sela reference at paras. [0027], [0044], [0048]; see Matthews reference at paras. [0002], [0024]; see McDonough reference at paras. [0020], [0099]). Well-understood, routine, conventional activity cannot provide an inventive concept (“significantly more”). As such the claim is not patent eligible.
Thus, taken alone, the additional elements do not amount to significantly more than the
above-identified judicial exception. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. Their
collective functions merely provide conventional computer implementation.
Depending Claims
Dependent claims recite additional subject matter which further narrows or defines the abstract idea embodied in the claims. For example, Claims 2, 3, 4, 5, 7, 8, 9 recite limitations which further narrow the scope of the independent claim. Claims 4, 6, 10 further recites limitations that are certain methods of organizing human activity as set out below:
Claim 4 also recites limitations pertaining to the biological data are converted into a standard score through at least one channel of the scalp electroencephalography (EEG) signals, and then presented in the order list according to a deviation mean, which is also certain methods of organizing human activity including managing personal behavior, as a healthcare provider could perform data analysis to convert data from scalp EEG signal from a channel into a standard score and present the results in an order list. The above limitations are therefore not sufficient to integrate the abstract idea into a practical application or to amount to significantly more than the abstract idea.
Claim 6 recites limitations pertaining to wherein after the step of feeding back the corresponding training parameter recommendation for cognitive training, the method further comprises providing an effect suggestion based on a result of the cognitive training, which is also certain methods of organizing human activity including managing personal behaviors, as a healthcare provider could provide an effect suggestion based on a cognitive training result after the subject has performed the cognitive training. Claim 6 also recites additional elements consistent with those addressed above with respect to independent claim 1, and recitation of these elements in claim 6 only amounts to mere instructions to apply the abstract idea. Claim 6 also recites limitations pertaining to transmitting the result of the cognitive training through the network back to the remote cloud system, which only amounts to insignificant extra-solution activity. In addition to amounting to insignificant extra-solution activity, the above limitations also constitute well-understood, routine and conventional activity in the form of transmitting data over a network, which has been recognized by the courts as well-understood, routine and conventional activity when claimed as insignificant extra-solution activity. See MPEP 2106.05(d). The above limitations are therefore not sufficient to integrate the abstract idea into a practical application or to amount to significantly more than the abstract idea.
Claim 10 recites limitations pertaining to wherein a corresponding training parameter recommendation further comprises recommending to refer to a priority order of execution of training after comparing surface brainwaves and brain area network according to a norm through a training protocol recommendation; and remotely feeding back based on the corresponding training parameter recommendation for a cognitive training step of neurophysiological feedback, and then comparing an outcome of the cognitive training step to the norm to evaluate whether brainwaves or brain areas are approaching balance to evaluate effectiveness of the corresponding training parameter recommendation, which are also certain methods of organizing human activity including managing personal behavior, as a healthcare provider could provide a recommendation for a priority order of training after performing a comparison analysis, provide feedback based on the training parameter recommendation, and performing an evaluation of training effectiveness. Claim 10 also recites additional elements consistent with those addressed above with respect to independent claim 1, and recitation of these elements in claim 6 only amounts to mere instructions to apply the abstract idea. The above limitations are therefore not sufficient to integrate the abstract idea into a practical application or to amount to significantly more than the abstract idea.
Dependent claims 2-10 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. 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.
The dependent claims have been given the full two-part analysis including analyzing the additional limitations both individually and in combination. The dependent claims, when analyzed individually, and in combination, are also held to be patent ineligible under 35 U.S.C. 101 as they include all of the limitations of claim 1. The additional recited limitations of the dependent claims fail to establish that the claims do not recite an abstract idea because the additional recited limitations of the dependent claims merely further narrow the abstract idea. Beyond the limitations which recite the abstract idea, the claims recite additional elements consistent with those identified above with respect to the independent claims which encompass adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f). 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.
Dependent claims 2-10 recite additional subject matter which amounts to additional elements consistent with those identified in the analysis of Claim 1 above. As discussed above with respect to Claim 1 and integration of the abstract idea into a practical application, recitation of these additional elements only amounts to invoking computers as a tool to perform the abstract idea. 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.
Dependent claims 2-10, when analyzed as a whole, are held to be patent ineligible under 35 U.S.C. 101 because the additional recited limitation(s) fail(s) to establish that the claim(s) is/are not directed to an abstract idea without significantly more. These claims fail to remedy the deficiencies of their parent claims above, and are therefore rejected for at least the same rationale as applied to their parent claims above, and incorporated herein.
For the reasons stated, Claims 1-10 fail the Subject Matter Eligibility Test and are consequently rejected under 35 U.S.C. 101.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1, 2, 4-7, 9-10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Sela (US Publication 20140163410A1) in view of Matthews (US Publication 20110015538A1), and further in view of May (US Publication 20190009133 A1).
Regarding Claim 1, Sela discloses:
receiving biological data of a subject by a brainwave collected by a brainwave collection device ([0027] teaches on securing electrodes to the head of a patient; the electrodes configured to measure electroencephalographic (EEG) brain activity; [0044] teaches on an embodiment of a neurofeedback system; data collection module is configured to receive EEG data associated with a patient (capturing biological data of a subject); [0048] teaches on an EEG reader device, such as a headset or individual electrodes placed on the head; the headset may be adapted so it is hidden by a frontal cap/hat – interpreted as “brainwave collection device”);
transmitting the biological data to a brainwave database of a remote cloud system through a network ([0027] teaches on using electrodes to capture EEG data; a central server is provided to store at least one treatment program algorithm – interpreted as a brainwave database; the measured EEG brain activity data is transmitted to a central server via the internet by way of a computer-based device; per [0014], the computer-based device is cloud-connectable and per [0052]-[0054], the servers will typically be cloud servers and the database on the internet will typically be Microsoft Azure SQL which is the database in Microsoft’s computing cloud);
converting the biological data into a corresponding training parameter recommendation using the remote cloud system according to the brainwave database ([0027] teaches on after the EEG data is transmitted to the central server, feedback is provided to the patient in accordance with the measured EEG brain activity data (quality/level of the activity); per [0052]-[0054], servers are cloud servers; [0182] provides specific details of the system providing feedback to the patient “in response to the electrical activity of the brain, measured during treatment”; feedback may be provided in various forms (blurring, darkening, changing font, sounds, etc. – all interpreted as “training parameters”) – if the system provides this type of feedback based on electrical activity of the patient’s brain, it is interpreted as “converting” the patient’s electrical brain data into corresponding training parameters for the patient, e.g., sound or screen effects such as darkening/blurring); and
remotely feeding back the corresponding training parameter recommendation using the remote cloud system to a neurofeedback cognitive training module in the cognitive training system in real time for cognitive training ([0027] teaches on providing feedback to the patient in accordance with their measured EEG activity; the patient “receives a treatment protocol” from the central server via the internet by way of the computer-based device (synonymous with “remotely feedback back” a recommendation); [0048] teaches on the patient using a “patient application” installed on the patient’s home computer to perform treatment procedures (synonymous with neurofeedback cognitive training module); [0182] provides specific details of the system providing feedback to the patient “in response to the electrical activity of the brain, measured during treatment”; feedback may be provided in various forms (blurring, darkening, changing font, sounds, etc. – all interpreted as “training parameter”; [0003]-[0004] teach on the system/method providing real-time feedback to the patient based on the EEG of the brain to train and condition the patient’s brain),
wherein the remote cloud system is configured for converting the biological data into the corresponding training parameter recommendation ([0182] provides specific details of the system providing feedback to the patient “in response to the electrical activity of the brain, measured during treatment”; feedback may be provided in various forms (blurring, darkening, changing font, sounds, etc. – all interpreted as “training parameters”) – if the system provides this type of feedback based on electrical activity of the patient’s brain, it is interpreted as “converting” the patient’s electrical brain data into corresponding training parameters for the patient, e.g., sound or screen effects such as darkening/blurring),
includinggenerating training parameters for the corresponding training parameter recommendation ([0182] provides specific details of the system providing feedback to the patient “in response to the electrical activity of the brain, measured during treatment”; feedback may be provided in various forms (blurring, darkening, changing font, sounds, etc. – all interpreted as generating training parameters for a corresponding recommendation)
Sela does not teach the following, but Matthews, which is directed to a system and method for analyzing EEG data, teaches:
converting the biological data into a standardized score ([0001] teaches on collecting EEG data from 1 to 19 or more scalp sites; a single score for each site may be produced; a single score for each scalp-site pair may be produced; a single combined score for all measured site and site-pairs may be produced – biological data; [0007] teaching on the invention receives as input the output of EEG acquisition software converted to z-score tables after which a set of transformations is conducted; [0009] teaches on receiving EEG data as z-score tables, and transforming the z-scores by calculating deviance scores for single-sites and site-pairs (deviance scores are interpreted as a standardized score); [0010] teaches on receiving qEEG data (“biological data”) that have been converted to z-scores, and converting the z-scores to deviance scores – interpreted as a standardized score), forming an order list based on the standardized score [0010] teaches on receiving qEEG data (“biological data”) that have been converted to z-scores, and converting the z-scores to deviance scores (standardized score); a “ranked list” is presented on a display – interpreted as an “order list” based on the standardized score”), the standardized score being a distance between a raw value of the biological data and a normative mean in the brainwave database represented in units of standard deviation ([0010] teaches on receiving qEEG data converted to z-scores, and subsequently converting the z-scores to deviance scores, and then computing “hit rates, means, and other summary measures (median, standard deviation) of appropriate output sets of scores; Examiner interprets a standard deviation as being indicative of the distance between the biological data value and a mean).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to modify Sela with these teachings of Matthews to convert EEG data into a standardized score and form an order list based on the standardized score, where the standardized score is a distance between a raw value of the EEG data and a mean represented in units of standard deviation, with the motivation of using a standardized score to determine how normal or abnormal a measurement is in comparison to an expected score (Matthews [0004]), and to present a ranked (order) list so that a user is able to quickly identify which site is most abnormal/most deviant (Matthews [0010]).
Sela/Matthews do not teach the following, but May, which is directed to methods and systems for data-driven movement skill training, teaches:
generating [a training recommendation] based on the order list ([0692] teaches on providing an active training list in order of importance).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to further modify the teachings of Sela/Matthews with these teachings of May, to generate the neurofeedback training parameters for a corresponding training parameter recommendation of Sela/Matthews based on an order list as taught by May, with the motivation of providing a list of training goals based on which elements should be focused on and representing the most significant training goal (May [0692]).
Regarding Claim 2, Sela/Matthews/May teach the limitations of Claim1. Sela further discloses wherein the brainwave collection device is an electroencephalography (EEG) cap or a heart rate variability cap (HRV Cap) ([0048] teaches on an EEG reader device in a “headset” implementation which may be adapted into a frontal cap).
Regarding Claim 4, Sela/Matthews/May teach the limitations of claim 1. Sela does not disclose the following but Matthews further teaches: wherein the biological data are scalp electroencephalography (EEG) signals from one or more channels ([0001] teaches on collecting EEG data from 1 to 19 or more scalp sites; a single score for each site may be produced; a single score for each scalp-site pair may be produced; a single combined score for all measured site and site-pairs may be produced – biological data; 1 to 19 or more “scalp sites” are interpreted as “one or more channels” from which the EEG data is received), the biological data are converted into a standard score through at least one channel of the scalp electroencephalography (EEG) signals ([0001] teaches on collecting EEG data from 1 to 19 or more scalp sites (channels) – biological data; [0007] teaching on the invention receives as input the output of EEG acquisition software converted to z-score tables after which a set of transformations is conducted; [0009] teaches on receiving EEG data as z-score tables, and transforming the z-scores by calculating deviance scores for single-sites and site-pairs (deviance scores are interpreted as a standardized score); [0010] teaches on receiving qEEG data (“biological data”) that have been converted to z-scores, and converting the z-scores to deviance scores – interpreted as a standardized score), and then presented in the order list according to a deviation mean ([0061] teaches on the system calculating a mean across frequency bins; for site-pairs found, the power deviance score is calculated; then the system computes a mean of means for each site; the Planner ranks the sites in order from high to low mean deviance – Examiner interprets “mean deviance” is interpreted as being the same as “deviation mean”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to modify Sela/Matthews/May with these teachings of Matthews to collect scalp EEG signals from one or more channels and convert data from at least one channel into a standard score to determine a training parameter recommendation, with the motivation of using a standard score to determine how normal or abnormal a measurement is in comparison to an expected score (Matthews [0004]), and to present a ranked (order) list so that a user is able to quickly identify which site is most abnormal (Matthews [0061]).
Regarding Claim 5, Sela/Matthews/May teach the limitations of Claim 4. Sela further discloses wherein the brainwave data include amplitudes ([0175] teaches on the system facilitating patient treatment progress reports including progress measured in terms of “amplitude” level of brain waves]), frequencies ([0197] teaches on the system checking electrical activity of patient and calculating a number of parameters of this electrical activity; the parameters considered are based on the relationship between the various frequencies of different brain regions – understood to teach that “frequencies” are known), sites ([0197] teaches on the system checking electrical activity of patient and calculating a number of parameters of this electrical activity; the parameters considered are based on the relationship between the various frequencies of different brain regions – understood to teach that “sites” (brain region) data is known) and pattern characteristics (([0197] teaches on the system checking electrical activity of patient and calculating a number of parameters of this electrical activity; the system “checks various correlations existing between the electrical activity in one location relative to another location” – “correlations” between locations are interpreted as reading on broadest reasonable interpretation of “pattern characteristics”).
Regarding Claim 6, Sela/Matthews/May teach the limitations of Claim 1. Sela further discloses wherein after the step of remotely feeding back the corresponding training parameter recommendation to the neurofeedback cognitive training module for cognitive training, the method further comprises providing an effect suggestion based on a result of the cognitive training ([0182] teaches on the system providing feedback (disturbance) to the patient by blurring, darkening, fading screen color or playing sounds – interpreted as remotely feeding back the training parameter recommendation to the training module; as the distance/difference from target result increases, the screen feedback disturbances increase; the closer the patient is to meeting the desired treatment protocol values, the less will be the feedback disturbance – interpreted as “providing an effect suggestion based on the result of cognitive training”, e.g., as patient’s result gets further from target, effects increase; as patient’s results get closer to garget, effects decrease), and transmitting the result of the cognitive training through the network back to the remote cloud system ([0183] teaches on, at the end of the treatment, the system stops the operation, stores the accumulated/collected information and sends the information through the wireless network to the company organization center; [0129]-[0132] also teach on the interface between the cloud and patient system, at the end of each treatment session, the system tries to transfer treatment results to the cloud and send data created when there is communication).
Regarding Claim 7, Sela/Matthews/May teach the limitations of Claim 1. Sela further discloses wherein the neurofeedback cognitive training module includes a desktop computer, a notebook computer and/or a smart mobile device ([0206] teaches on the computer based device used by the patient as being a mobile device, for example, a laptop, smartphone, tablet/iPad or the like).
Regarding Claim 9, Sela/Matthews/May teach the limitations of claim 5. Sela does not disclose, but Matthews further teaches wherein a brain activity area is predicted back as the training parameters based on sites of the one or more channels ([0010] teaches on receiving qEEG results converted to z-scores; deviance and mean are calculated for all z-scores associated with a given site (interpreted as site of a channel – per [0029] teaching on a 19 channel full-head EEG); a ranked list is presented on a display to provide a report with the most deviant sites, site-pairs and other combinations of sites; such analysis is used to identify scalp sites (e.g., channels) and interrelationships that are most abnormal; such data can be provided in real-time; Examiner interprets identification of “scalp sites” that are “most abnormal” to read on broadest reasonable interpretation of “brain activity area” that is “predicted back through the brainwave characteristics” (EEG data); [0032] in order to conduct appropriate training for a client’s needs, NFB is designed based on factors including, qEEG findings that localize actual brain function deficits; [0035] teaches on comparing EEG voltages in NFB to appropriate database in real-time so that z-scores can be used for training purposes; continues flow of information is compared to a set of “training” criteria designed to shift brain function by operant conditioning).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to further modify the combined teachings of Sela/Matthews/May with these teachings of Matthews to predict a brain area as recommended training parameters based on the sites of one or more channels, with the motivation of identifying sites of the brain (via EEG channels) that are most abnormal (Matthews [0061]) and to address specific needs of the user (Matthews [0008]).
Regarding Claim 10, Sela/Matthews/May teach the limitations of Claim 1. Sela does not disclose, but Matthews, which is directed to a system and method for analyzing EEG data, teaches: wherein the corresponding training parameter recommendation comprises recommending training after comparing surface brainwaves and brain area network according to a norm through a training protocol recommendation ([0004] teaches on using a z-score with NFB EEG measurements; the z-score indicates a measure of how normal/abnormal a measurement is in comparison to a value in a database containing expected scores (an expected score is interpreted as synonymous with “a norm”; [0032] teaches on, in order to conduct appropriate training for a client’s needs, NFB is designed based on factors including, qEEG findings that localize actual brain function deficits; [0035] teaches on comparing EEG voltages in NFB to appropriate database in real-time so that z-scores can be used for training purposes; continues flow of information is compared to a set of “training” criteria designed to shift brain function by operant conditioning; [0130] teaches on using data from 19 channels NFB to define empirically based rules; the system may use the results to recommend protocols, protocol taper, protocol reinstatement, or termination); and remotely feeding back to the neurofeedback cognitive training module based on the training parameter recommendation for a cognitive training step of neurophysiological feedback ([0005] teaches on using EEG in real-time in NFB; NFB uses the EEG data immediately and continuously to conduct real-time training (interpreted as feedback back to a training module the training parameter recommendation for a subject to perform a cognitive training step) [0010] teaches on receiving qEEG results converted to z-scores; deviance and mean are calculated for all z-scores associated with a given site; a ranked list is presented on a display to provide a report with the most deviant sites, site-pairs and other combinations of sites; such analysis is used to identify scalp sites and interrelationships that are most abnormal; [0032] teaches on, in order to conduct appropriate training for a client’s needs, NFB is designed based on factors including, qEEG findings that localize actual brain function deficits; [0035] teaches on comparing EEG voltages in NFB to appropriate database in real-time so that z-scores can be used for training purposes; continues flow of information is compared to a set of “training” criteria designed to shift brain function by operant conditioning), and then comparing an outcome of the cognitive training step to the norm to evaluate whether brainwaves or brain areas are approaching balance to evaluate effectiveness of the corresponding training parameter recommendation ([0035] teaches on comparing EEG voltages to an appropriate database in real-time so that Z-scores can be used for training purposes; EEG voltages or z-scores may be used for NFB; the continuous flow of information is compared to training criteria designed to shift brain function by operant conditioning; continuous feedback about success in meeting training criteria is displayed to the client in a way to reward success; continuous feedback about success in meeting training criteria is interpreted as reading on broadest reasonable interpretation of evaluating whether brain waves/areas are approaching balance to evaluate effectiveness per [0004] (z-score measures how normal/abnormal a measurement is compared to database containing expected scores, e.g., the norm)).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to further modify the teachings of Sela/Matthews/May with these teachings of Matthews to recommend training after comparing brainwaves and brain area network according to a norm through protocol recommendation after a calculation, remotely providing the cognitive training back to a neurofeedback cognitive training module for the subject to perform, and evaluating effectiveness, with the motivation of identifying sites of the brain that are most abnormal (Matthews [0061]), addressing the specific needs of the subject (Matthews [0008]), and using NFB as a needs-assessment to use an individual’s EEG findings to localize areas of function within the brain, in order to conduct appropriate training for the client’s needs (Matthews [0032]).
Sela/Matthews do not teach that the training recommended refers to a priority order of execution of training, but May, which is directed to methods and systems for data-driven movement skill training, teaches that training recommended refers to a priority order of execution of training ([0692] teaches on providing an active training list in an order of importance).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to further modify the teachings of Sela/Matthews/May with these teachings of May, to provide the recommended NFB training to an individual in a priority order for execution, with the motivation of providing a list of training goals where the most significant training goal is represented (May [0692]).
Claim(s) 3 is/are rejected under 35 U.S.C. 103 as being unpatentable over Sela (US Publication 20140163410A1) in view of Matthews (US Publication 20110015538A1), and further in view of May (US Publication 20190009133 A1) as applied to Claim 1 above, and further in view of Wikipedia article “Wireless ad hoc network”.
Regarding Claim 3, Sela/Matthews/May teach the limitations of Claim 1. Sela discloses wherein the network is the internet ([0015], [0027]) and wherein the network is a wireless network ([0183]). But does not disclose the network is an ad-hoc network (Wikipedia article “Wireless ad hoc network” (Para. 1) teaches on an ad hoc network being a decentralized type of wireless network; the network is “ad hoc” because it does not rely on pre-existing infrastructure such as routers or wireless access points).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to modify Sela/Matthews/May to use an ad-hoc network as taught by Wikipedia article “Wireless ad hoc network” for transmitting biological data to the remove cloud system, to allow devices to communicate directly with each other without a router, and because ad hock networks lack the complexities of infrastructure setup and administration and enable user devices to join networks on the fly (Paras. 2-3).
Response to Applicant’s Remarks/Arguments
Please note: When referencing page numbers of Applicant’s response, references are to page numbers as printed.
Claim Objections
The objections to Claim 3 are withdrawn in view of Applicant’s amendment.
Rejections under 35 USC 112(a)
The rejections of Claims 1-10 are withdrawn in view of Applicant’s amendments to the claims, particularly Claim 1; Applicant’s remarks directed to paras. [0036]-[0037]; and para. [0038].
Rejections under 35 USC 112(b)
The rejection of Claim 1 detailed at page 5 is withdrawn in view of Applicant’s amendments to Claim 1 and remarks directed to paras. [0036]-[0037] at pages 14-15. The rejections of Claim 4 for lack of antecedent basis and indefinite issues are withdrawn in view of Applicant’s amendment to Claim 4. The rejections of Claim 10 for lack of antecedent basis and indefinite issues are withdrawn in view of Applicant’s amendment to Claim 10.
35 USC 101 Rejections
Applicant’s remarks have been fully considered but are not persuasive. The 101 section above has been updated to reflect amended claim language. Regarding amendment “receiving biological data…” this is identified as insignificant extra-solution activity in the form of mere data gathering. Regarding amendment presented at pages 11-12 regarding “transmitting the biological data to a brainwave database of a remote cloud system through a network”, this has been identified as extra-solution activity in the form of transmitting data over a network, which the courts have found to be well understood, routine and conventional when claimed at a high level. Regarding recitation of “using the remote cloud system” in “converting” and “feeding back” limitations, the remote cloud system is understood to be a general purpose computing element functioning in its normal capacity, which only amounts to mere instructions to apply the abstract idea. MPEP 2106.05(f). Using general purpose computing elements to implement the abstract idea is not sufficient to integrate the judicial exception into a practical application or amount to significantly more. This argument is not persuasive.
Regarding remarks at page 12 pertaining to an “automated way without human interaction”, Examiner submits that merely automating a process using a computer does not automatically confer subject matter eligibility. (See MPEP 2106.05(a)(I), example (iii) under “Examples that the courts have indicated may not be sufficient to show an improvement in computer-functionality”). The computing elements, e.g., as stated by Applicant at page 14, “the method is executed in a cognitive training system and performed by various hardware modules or programs”, are only being used to apply the steps of the abstract idea. This is not persuasive.
Regarding remarks, “the amended claim language neither interacts with people nor manages human activity”, Examiner respectfully disagrees that the claims as presented render the claim subject-matter eligible. Multiple CAFC decisions that the Office has characterized as Certain Method of Organizing Human Activity did not actively recite a person or persons performing the steps of the claims (see, e.g., EPG, TLI communications, Ultramercial). Because whether a human is required to perform the step of the claim is not a requirement for claims to encompass certain method of organizing human activity, this argument is not persuasive. The Examiner further notes: MPEP 2106. 04(a)(2)(II) states that a claimed invention is directed to certain methods of organizing human activity if the identified claim elements contain limitations that encompass fundamental economic principles or practices, commercial or legal interactions, or managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions). The Examiner submits that the identified claim elements in 101 section above represent a series of personal behaviors that a person or persons, with or without the aid of a computer, would follow to determine a training parameter recommendation for a subject and subsequently provide the recommendation to the subject to perform cognitive training. Applicant has not pointed to anything in the claims that fall outside of this characterization. The elements cited by Applicant at page 12 only amount to mere instructions to apply the abstract idea on a computer. Because the claim elements fall under a series of personal behaviors that a person or persons would follow to determine a training parameter recommendation for a subject and subsequently provide the recommendation to the subject to perform cognitive training, the claimed invention is directed to an abstract idea. This argument is not persuasive.
Regarding remarks at bottom of page 12-top of page 13 pertaining to amended limitation “remote cloud system is configured for…converting the biological data into a standardized score”, Examiner respectfully submits that this only amounts to mere instructions to apply the abstract idea on a computer, e.g., using a computer (remote cloud system) to convert biological data into a standardized score. Applicant argues at top of page 13 “it should be noted that computing the standardized score from the biological data…”; however, the claim recites “converting the biological data into a standardized score”; no particulars of a calculation are recited. Regardless, Examiner submits that a real-time computational processing of high dimensional data (as mentioned by Applicant at page 13) only amounts to mere instructions to apply the abstract idea on a computer. Further, Examiner submits that certain methods of organizing activity may include a human interacting with a computer (MPEP 2106.04(a)(2)(II)). Examiner respectfully disagrees that this computation is “significantly more” than an abstract idea or that it “provides significant extra-solution activity”. Examiner submits that a person, with or without a computer, could convert biological data into a corresponding training parameter recommendation, and as such, this limitation has been included in the scope of the abstract idea. As the computation step falls within the scope of the abstract idea, it does not amount to a practical application. This argument is not persuasive.
Regarding remarks at page 13 pertaining to “remotely feeding back the corresponding training parameter recommendation”, Examiner respectfully disagrees that this provides a practical application. Applicant argues that “the method significantly improves the effectiveness and efficiency of cognitive training by providing real time recommendations”. Examiner respectfully submits that providing real time recommendations to improve effectiveness/efficiency of cognitive training may be an improvement to the abstract idea, however this is not sufficient to integrate the judicial exception into a practical application. Please see MPEP 2106.05(a) which states, “It is important to note, the judicial exception alone cannot provide the improvement. The improvement can be provided by one or more additional elements.” Applicant has not provided, nor can Examiner find evidence of, how any of the additional elements identified above in main 101 analysis section are providing an improvement over prior art systems. This argument is not persuasive.
For all of the above reasons, Applicant’s remarks are not persuasive and the rejections of Claims 1-10 under 35 USC 101 are maintained.
35 USC 102/103 Rejections
Applicant’s remarks have been fully considered but are not persuasive. Regarding remarks at bottom of page 16 continuing to page 17, Examiner respectfully submits that while Sela considered alone may not teach on the amended features, the combination of Sela with Matthews and May teach on “automatically” converting physiological signals into training parameter recommendations with ordering and priority. This argument is not persuasive.
Regarding remarks in second paragraph at page 17, Examiner respectfully submits that Applicant appears to be arguing a particular embodiment of Sela. Examiner notes that para. [0009] further discloses “It is a particular feature of the present system and method that they are adapted to perform an automatic or semi-automatic neurofeedback treatment. The adaptation includes that the system can automatically make a neurofeedback treatment protocol” (emphasis Examiner). Further, Para. [0010] further discloses "the system itself, can provide a treatment plan or so-called “protocol” remotely”. Regarding remarks to “real time” training recommendation, Examiner submits that para. [0004] of Sela teaches real-time aspects of their invention. These arguments are not persuasive.
Regarding remarks at page 17, third paragraph pertaining to standardizing data and forming an order list, Examiner submits that while Sela does not disclose these amended features, Matthews and May have been introduced to teach on the broadest reasonable limitation of these features. This argument is not persuasive.
Regarding remarks directed to Matthews at pages 17-18, Examiner submits that the May reference has been introduced to teach on the limitations pertaining to using an order list to generate training parameter recommendations. These arguments are not persuasive.
Regarding Applicant’s closing statement at page 18, Examiner submits that this has been covered in preceding paragraphs and claim mappings provided in 103 section above; the combination of Sela, Matthews and May teach on the limitations of Claim 1.
Regarding remarks directed to Claim 8, Applicant’s remarks have been considered and are persuasive. A search of publicly available prior art fails to yield a reference or combination of references that would make the claimed combination of amended claim 8 obvious when considered as a whole. The rejection of Claim 8 under 35 USC 103 is withdrawn.
The rejections of Claims 1-8, 9-10 under 35 USC 103 are maintained.
Conclusion
In the interest of expediting prosecution, Examiner respectfully requests that Applicant provides citations to relevant paragraphs of specification for support for amendments in future correspondence.
The following relevant prior art not cited is made of record:
US Publication 20210259615 A1 teaching on using neurofeedback training for resilience training in which the protocol is personalized to each trainee
US Publication 20220101981 A1, teaching on a method and system for neuromodulation using principles of neurofeedback training
US Publication 20190200888 A1, teaching on a method and apparatus for neuroenhancement using LORETA
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 extension fee 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 date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ANNE-MARIE K ALDERSON whose telephone number is (571)272-3370. The examiner can normally be reached on Mon-Fri 9:00am-5:00pm EST, and generally schedules interviews in the timeframe of 2:00-5:00pm EST.
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/ANNE-MARIE K ALDERSON/Primary Examiner, Art Unit 3682