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 .
Information Disclosure Statement
The information disclosure statements (IDS) submitted on August 25, 2023, December 21, 2023, and August 21, 2025 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements have been considered by the examiner.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Claims 1-20 are directed to a method of recommending meditation protocols using a computational algorithm, which is an abstract idea. Claims 1-20 do not include additional elements that integrate the exception into a practical application or that are sufficient to amount to significantly more than the judicial exception for the reasons provided below which are in line with the 2014 Interim Guidance on Patent Subject Matter Eligibility (Federal Register, Vol. 79, No. 241, p 74618, December 16, 2014), the July 2015 Update on Subject Matter Eligibility (Federal Register, Vol. 80, No. 146, p. 45429, July 30, 2015), the May 2016 Subject Matter Eligibility Update (Federal Register, Vol. 81, No. 88, p. 27381, May 6, 2016), and the 2019 Revised Patent Subject Matter Eligibility Guidance (Federal Register, Vol. 84, No. 4, page 50, January 7, 2019).
The analysis of claim 1 is as follows:
Step 1: Claim 1 is drawn to a process.
Step 2A – Prong One: Claim 1 recites an abstract idea. In particular, claim 1 recites the following limitations:
[A1] – “A method for generating personalized brain state protocol recommendations”;
[B1] – “accessing, at the protocol recommendation system, a plurality of meditation protocols including at least a first meditation protocol and a second meditation protocol, wherein each meditation protocol promotes a different type of meditation experience”; and
[C1] – “calculating, by the protocol recommendation system, at least a first depth score characterizing a performance of the dataset with respect to the first meditation protocol and a second depth score characterizing a performance of the dataset with respect to the second meditation protocol, wherein the first depth score is higher than the second depth score”.
These elements [A1]-[C1] of claim 1 are drawn to an abstract idea since they involve a mental process that can be practically performed in the human mind including observation, evaluation, judgment, and opinion and using pen and paper.
Step 2A – Prong Two: Claim 1 recites the following limitations that are beyond the judicial exception:
[A2] – “receiving, at a protocol recommendation system for a meditation application, a dataset representing brainwave activity for a first user in a meditative condition”; and
[B2] – “presenting, via a user interface for the meditation application and in response to the first depth score being higher than the second depth score, a recommendation to the first user to implement the first meditation protocol.”
These elements [A2]-[B2] of claim 1 do not integrate the exception into a practical application of the exception. In particular, the elements [A2]-[B2] are merely adding insignificant extra-solution activity to the judicial exception, i.e., mere data gathering and display of data at a higher level of generality - see MPEP 2106.04(d) and MPEP 2106.05(g). Furthermore, the elements [A2]-[B2] are merely instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.04(d) and MPEP 2106.05(f).
Step 2B: Claim 1 does not recite additional elements that amount to significantly more than the judicial exception itself. In particular, the recitation [B2] does not qualify as significantly more because this limitation merely describes the nature of the brainwave data and does not incorporate any particular machine or sensor as part of the claimed invention. Also, the recitations [A2]-[B2] are merely insignificant extrasolution activities to the judicial exception, e.g., mere data gathering in conjunction with the abstract idea that uses conventional, routine, and well known elements or simply displaying the results of the algorithm that uses conventional, routine, and well known elements. In particular, the meditation application is nothing more than a means for collecting and outputting data using generic computer components.
Claims 2-8 depend from claim 1, and recite the same abstract idea as claim 1. Furthermore, these claims only contain recitations that further limit the abstract idea (that is, the claims only recite limitations that further limit the algorithm). Each of these claim limitations do not integrate the exception into a practical application. In particular, the elements of claims 2-8 reciting the “user interface” and the “meditation application” are merely adding insignificant extra-solution activity to the judicial exception, i.e., mere display/output of data at a higher level of generality - see MPEP 2106.04(d) and MPEP 2106.05(g).
In view of the above, the additional elements individually do not integrate the exception into a practical application and do not amount to significantly more than the above-judicial exception (the abstract idea). Looking at the limitations of each claim as an ordered combination in conjunction with the claims from which they depend (that is, as a whole) 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, for example, or improves any other technology. There is no indication that the combination of elements permits automation of specific tasks that previously could not be automated. There is no indication that the combination of elements includes a particular solution to a computer-based problem or a particular way to achieve a desired computer-based outcome. Rather, the collective functions of the claimed invention merely provide conventional computer implementation, i.e., the computer is simply a tool to perform the process.
The analysis of claim 9 is as follows:
Step 1: Claim 9 is drawn to a process.
Step 2A – Prong One: Claim 9 recites an abstract idea. In particular, claim 9 recites the following limitations:
[A1] – “calculating, by the brainwave guidance system, a first score characterizing a performance of the first dataset with respect to the first rule and a second score characterizing a performance of the first dataset with respect to the second rule”;
[B1] – “automatically creating, at the meditation application and in response to the first request, a second meditation protocol including only the first rule”; and
[C1] – “initiating, at the meditation application, a second guided meditation session for the first user that is implemented based on the second meditation protocol.”
These elements [A1]-[C1] of claim 9 are drawn to an abstract idea since (2) they involve a mental process that can be practically performed in the human mind including observation, evaluation, judgment, and opinion and using pen and paper.
Step 2A – Prong Two: Claim 9 recites the following limitations that are beyond the judicial exception:
[A2] – “receiving, at a brainwave guidance system for a meditation application, a first dataset representing brainwave activity for a first user during a first guided meditation session implemented based on a first meditation protocol, the first meditation protocol including at least a first rule and a second rule”;
[B2] – “presenting, via the meditation application, both the first score and the second score”; and
[C2] – “receiving, via a user interface for the meditation application, a first request to improve the first score”.
These elements [A2]-[C2] of claim 9 do not integrate the exception into a practical application of the exception. In particular, the elements [A2-C2] are merely adding insignificant extra-solution activity to the judicial exception, i.e., mere data gathering and display at a higher level of generality - see MPEP 2106.04(d) and MPEP 2106.05(g).
Step 2B: Claim 9 does not recite additional elements that amount to significantly more than the judicial exception itself. In particular, the recitation [A2] does not qualify as significantly more because this limitation merely describes the nature of the brainwave data and does not incorporate any particular machine or sensor as part of the claimed invention. Also, the limitations reciting a “user interface” are merely insignificant extrasolution activity to the judicial exception, e.g., mere data gathering in conjunction with the abstract idea that uses conventional, routine, and well known elements or simply displaying the results of the algorithm that uses conventional, routine, and well known elements.
Claims 10-15 depend from claim 9, and recite the same abstract idea as claim 9. Furthermore, these claims only contain recitations that further limit the abstract idea (that is, the claims only recite limitations that further limit the algorithm). Each of these claim limitations do not integrate the exception into a practical application. In particular, the elements of claims 10-15 reciting the “user interface” and the “meditation application” are merely adding insignificant extra-solution activity to the judicial exception, i.e., mere display/output of data at a higher level of generality - see MPEP 2106.04(d) and MPEP 2106.05(g).
In view of the above, the additional elements individually do not integrate the exception into a practical application and do not amount to significantly more than the above-judicial exception (the abstract idea). Looking at the limitations of each claim as an ordered combination in conjunction with the claims from which they depend (that is, as a whole) 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, for example, or improves any other technology. There is no indication that the combination of elements permits automation of specific tasks that previously could not be automated. There is no indication that the combination of elements includes a particular solution to a computer-based problem or a particular way to achieve a desired computer-based outcome. Rather, the collective functions of the claimed invention merely provide conventional computer implementation, i.e., the computer is simply a tool to perform the process.
The analysis of claim 16 is as follows:
Step 1: Claim 16 is drawn to a process.
Step 2A – Prong One: Claim 16 recites an abstract idea. In particular, claim 16 recites the following limitations:
[A1] – “calculating, by the brainwave feedback system, a first score characterizing a performance of the first meditation dataset with respect to the first rule and a second score characterizing a performance of the first meditation dataset with respect to the second rule”;
This element [A1] of claim 16 is drawn to an abstract idea since (2) it involves a mental process that can be practically performed in the human mind including observation, evaluation, judgment, and opinion and using pen and paper.
Step 2A – Prong Two: Claim 16 recites the following limitations that are beyond the judicial exception:
[A2] – “receiving, at a brainwave feedback system for a meditation application, a first meditation dataset representing brainwave activity for a first user during a first guided meditation session implemented based on a first meditation protocol, the first meditation protocol including at least a first rule and a second rule”; and
[B2] – “presenting, via the meditation application, a dashboard including: a description of the first rule accompanied by the first score, and a description of the second rule accompanied by the second score.”.
These elements [A2]-[B2] of claim 16 do not integrate the exception into a practical application of the exception. In particular, the elements [A2-B2] are merely adding insignificant extra-solution activity to the judicial exception, i.e., mere data gathering and display at a higher level of generality - see MPEP 2106.04(d) and MPEP 2106.05(g).
Step 2B: Claim 16 does not recite additional elements that amount to significantly more than the judicial exception itself. In particular, the recitation [A2] does not qualify as significantly more because this limitation merely describes the nature of the brainwave data and does not incorporate any particular machine or sensor as part of the claimed invention. Also, the limitations reciting a “dashboard” are merely insignificant extrasolution activity to the judicial exception, e.g., mere data gathering in conjunction with the abstract idea that uses conventional, routine, and well known elements or simply displaying the results of the algorithm that uses conventional, routine, and well known elements.
Claims 17-20 depend from claim 16, and recite the same abstract idea as claim 16. Furthermore, these claims only contain recitations that further limit the abstract idea (that is, the claims only recite limitations that further limit the algorithm). Each of these claim limitations do not integrate the exception into a practical application. In particular, the elements of claims 17-20 reciting the “user interface” and the “meditation application” are merely adding insignificant extra-solution activity to the judicial exception, i.e., mere display/output of data at a higher level of generality - see MPEP 2106.04(d) and MPEP 2106.05(g).
In view of the above, the additional elements individually do not integrate the exception into a practical application and do not amount to significantly more than the above-judicial exception (the abstract idea). Looking at the limitations of each claim as an ordered combination in conjunction with the claims from which they depend (that is, as a whole) 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, for example, or improves any other technology. There is no indication that the combination of elements permits automation of specific tasks that previously could not be automated. There is no indication that the combination of elements includes a particular solution to a computer-based problem or a particular way to achieve a desired computer-based outcome. Rather, the collective functions of the claimed invention merely provide conventional computer implementation, i.e., the computer is simply a tool to perform the process.
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by US 20150351655 A1 (Coleman, Trevor).
Regarding claim 1, Coleman teaches a method for generating personalized brain state protocol recommendations ([0376] “A recommendation of specific target brain state exercises based on previous performance and usage history may be provided by the system”), the method comprising:
receiving, at a protocol recommendation system for a meditation application, a dataset representing brainwave activity for a first user in a meditative condition ([0005] “These electrical patterns, or brainwaves, are measurable by devices such as and EEG”; [0008] “the received bio-signal data comprising at least brainwave data of the at least one user; measure performance of the at least one user relative to at least one brain state guidance objective corresponding to the at least one brain state guidance routine at least partly by analyzing the received bio-signal data”);
accessing, at the protocol recommendation system, a plurality of meditation protocols including at least a first meditation protocol and a second meditation protocol, wherein each meditation protocol promotes a different type of meditation experience ([0010] “a computer program that when executed runs one or more meditation routines that guide at least one user through at least one meditation exercise”; [0100] “a library of meditation exercises”; [0105] “Various types of brain state exercises, including various meditation exercises, are possible”);
calculating, by the protocol recommendation system, at least a first depth score characterizing a performance of the dataset with respect to the first meditation protocol and a second depth score characterizing a performance of the dataset with respect to the second meditation protocol, wherein the first depth score is higher than the second depth score ([0089] “The at least one computing device may be configured to receive brain state guidance proficiency information indicating the proficiency of the respective user in achieving brain state guidance objectives, and to select the brain state guidance routine for execution based at least partly on the received proficiency information.”; [0158] “a Busymind score. The 0 to 1 score produced is on a continuum from quiet-mind 0 to busy-mind 1”; [0254]); and
presenting, via a user interface for the meditation application and in response to the first depth score being higher than the second depth score, a recommendation to the first user to implement the first meditation protocol ([0126] “An application on the phone processes the brainwaves and gives them feedback about their brain state using neurofeedback to help them achieve deeply meditative states and to speed their learning of meditation states.”; [0259]; [0373] “The system may recommend a meditation exercise based on discovery stage or user choice, past performance, and other factors”; [0376]).
Regarding claim 2, Coleman teaches the method of claim 1, further comprising:
receiving, from the first user and via the user interface, a selection of the recommendation; and
providing, via the meditation application, a first guided meditation session that is implemented based on the first meditation protocol ([0258] “the mobile application may be configured to recommend training programs for the user to complete based on past performance”; [0373]; [0376] “A recommendation of specific target brain state exercises based on previous performance and usage history may be provided by the system.”).
Regarding claim 3, Coleman teaches the method of claim 1, further comprising:
presenting, via the meditation application and prior to presenting the recommendation, a first list of options including a first option representing the first meditation protocol and a second option representing the second meditation protocol ([0373] “The system may recommend a meditation exercise based on discovery stage or user choice, past performance, and other factors, including, for example, time and location data from GPS (e.g. on your morning commute to work it may recommend a “get up and go” training; at home at night it recommends the “unwind and relax” program). The recommendations may be organized in a manner similar to a play list that allows the user to either choose the recommended training, or optionally skip ahead in the play list, or choose something on their own.”);
presenting, via the meditation application, a third option for predicting a user’s optimal meditation protocol ([0258] “In one implementation the computer program may include a recommendation engine that based on variety of factors generates one or more suggested training programs, which may be organized in a manner similar to a play list, that allows the user to either choose the recommended training, or optionally skip ahead in the play list, or choose something on their own.”);
receiving, via the user interface and from the first user, a selection of the third option; and
initiating, via the meditation application and in response to the selection of the third option, a first brain activity collection session during which the dataset is obtained ([0124] “The embodiment comprises a mobile meditation solution including an EEG headset bundled with an application that measures a user's brainwaves while s/he meditates and tracks their progress over time.”; [0373-0374]).
Regarding claim 4, Coleman teaches the method of claim 3, further comprising:
presenting, via the user interface and prior to presenting the first list of options, a second list of options including a fourth option representing a first meditation style and a fifth option representing a second meditation style, wherein the first meditation style includes both the first meditation protocol and the second meditation protocol, and the second meditation style includes a third meditation protocol ([0247] “stage types: build; restore; release; relax; and refocus.”; [0248-0252]; [0292]); and
receiving, via the user interface and from the first user, a selection of the fourth option ([0258] “allows the user to either choose the recommended training, or optionally skip ahead in the play list, or choose something on their own.”),
wherein presentation of the first list of options is in response to the selection of the fourth option ([0253] “the meditation exercise may include a 3-5 minute guided practice/meditation based on visual and auditory prompts from the mobile application.”; [0373] “The system may recommend a meditation exercise based on discovery stage or user choice, past performance, and other factors, including, for example, time and location data from GPS (e.g. on your morning commute to work it may recommend a “get up and go” training; at home at night it recommends the “unwind and relax” program). The recommendations may be organized in a manner similar to a play list that allows the user to either choose the recommended training, or optionally skip ahead in the play list, or choose something on their own.).
Regarding claim 5, Coleman teaches the method of claim 4, wherein the first meditation style includes meditation protocols for different user experience levels ([0234]; [0276] “a series of graph modes fully engages users with their performance, as they remember the session in different ways. Having different data views allows different users with different experiences find data which connects with their experience.”), and the method further comprises:
calculating depth scores for each of the meditation protocols of the first meditation style ([0254] “This may be displayed for example in a graph or results screen that may provide the user feedback or insight on a number of matters relevant to meditation related objectives. For example, the graph may include information that indicates whether the user did well or badly and at what points and this may be brought to the next exercise to improve the results.”);
generating a first graph depicting the depth scores, the first graph indicating to which protocol and experience level each depth score corresponds ([0254] “graph”); and
presenting the first graph to a second user who is authorized to access additional data regarding the first user for purposes of coaching ([0125] “a second user may be notified when the first user is using the meditation application, and may enable the second user to access a dashboard that enables in real time or near real time to track the progress of the first user.”; [0260]; [0266] “The console view could also be used by doctors to monitor compliance with a prescribed training regimen”).
Regarding claim 6, Coleman teaches the method of claim 1, wherein the plurality of meditation protocols includes meditation protocols that each promote a different type of meditation experience for the same experience level ([0275] “multiple audio/visual environments within which to practice can help users experience more variety despite self-administering a fairly repetitive ABCN exercise.”), and the method further comprises:
calculating depth scores for each of the meditation protocols in the plurality of meditation protocols ([0254] “the graph may include information that indicates whether the user did well or badly and at what points and this may be brought to the next exercise to improve the results”; [0158] “a Busymind score. The 0 to 1 score produced is on a continuum from quiet-mind 0 to busy-mind 1; [0089]);
generating a first graph depicting all of the calculated depth scores ([0256] “The scores may be displayed in real time or at the end of the experience in the form of graphs”); and
presenting, via the meditation application, the first graph to the first user ([0254] “The computer system may track the user's interaction with the practice/meditation and based on this the analyzer may calculate results based on the user's brain data. This may be displayed for example in a graph or results screen that may provide the user feedback or insight on a number of matters relevant to meditation related objectives.”).
Regarding claim 7, Coleman teaches the method of claim 2, wherein the first meditation protocol includes at least a first rule and a second rule ([0140] “User annotation may be used to label time segments of the data to supervise machine learning to develop models and rules for brainstate estimation.”; [0148] “Some changes in Brainstate may not meaningful or useful for the user to receive notification, or the changes in brainstate need to be processed through rules that can send notifications that are effective in helping a user achieve their goal”), and the method further comprises:
receiving, at the protocol recommendation system, a guided meditation dataset representing brainwave activity for the first user during the first guided meditation session ([0005] “These electrical patterns, or brainwaves, are measurable by devices such as and EEG”; [0008] “the received bio-signal data comprising at least brainwave data of the at least one user; measure performance of the at least one user relative to at least one brain state guidance objective corresponding to the at least one brain state guidance routine at least partly by analyzing the received bio-signal data”);
calculating, by the protocol recommendation system, a first score characterizing a performance of the guided meditation dataset with respect to the first rule and a second score characterizing a performance of the guided meditation dataset with respect to the second rule ([0073] “The at least one brain state guidance objective may comprise the estimated busy-mind score indicative of a quiet-mind on the continuum”; [0148] “Notification Rules can use, as an example an integrator that counts the number of events that are indicative of the target state until a threshold is reached and then a notification is sent to the user”);
presenting, via the meditation application, both the first score and the second score ([0126] “An application on the phone processes the brainwaves and gives them feedback about their brain state using neurofeedback to help them achieve deeply meditative states and to speed their learning of meditation states.”; [0259]; [0373] “The system may recommend a meditation exercise based on discovery stage or user choice, past performance, and other factors”; [0376]);
receiving, via the user interface, a request to improve the first score ([0143]; [0148] “Some changes in Brainstate may not meaningful or useful for the user to receive notification, or the changes in brainstate need to be processed through rules that can send notifications that are effective in helping a user achieve their goal”); and
automatically creating, at the meditation application and in response to the request, a second meditation protocol including only the first rule ([0150] “Notification Rules may decide what events or brainstates are interesting to the user. The rules consider the type of video game or exercise the user is engaged and the goal that user is trying to achieve”; [0258]).
Regarding claim 8, Coleman teaches the method of claim 2, wherein the first meditation protocol includes at least a first rule and a second rule ([0140]; [0148] “Some changes in Brainstate may not meaningful or useful for the user to receive notification, or the changes in brainstate need to be processed through rules that can send notifications that are effective in helping a user achieve their goal”), and the method further comprises:
receiving, at the protocol recommendation system, a guided meditation dataset representing brainwave activity for the first user during the first guided meditation session ([0005] “These electrical patterns, or brainwaves, are measurable by devices such as and EEG”; [0008] “the received bio-signal data comprising at least brainwave data of the at least one user; measure performance of the at least one user relative to at least one brain state guidance objective corresponding to the at least one brain state guidance routine at least partly by analyzing the received bio-signal data”);
calculating, by the protocol recommendation system, a first score characterizing a performance of the guided meditation dataset with respect to the first rule and a second score characterizing a performance of the guided meditation dataset with respect to the second rule ([0073] “The at least one brain state guidance objective may comprise the estimated busy-mind score indicative of a quiet-mind on the continuum”; [0148] “Notification Rules can use, as an example an integrator that counts the number of events that are indicative of the target state until a threshold is reached and then a notification is sent to the user”);
presenting, via the meditation application, both the first score and the second score ([0126] “An application on the phone processes the brainwaves and gives them feedback about their brain state using neurofeedback to help them achieve deeply meditative states and to speed their learning of meditation states.”; [0259]; [0373] “The system may recommend a meditation exercise based on discovery stage or user choice, past performance, and other factors”; [0376]); and
presenting, via the meditation application ([0282] “The system may employ the typical gamification technique of “badges” or “achievements” with self-administered neurofeedback”), a dashboard including:
a description of the first rule accompanied by the first score ([0254] “the graph may include information that indicates whether the user did well or badly and at what points and this may be brought to the next exercise to improve the results.”; [0284] “The screen presented to users directly after their session should provide clear guidance as to the purpose of that unlock. Showing users the average score, current score, and total score can help provide context. Visually showing the progress toward a goal is critical, and the labelling of that goal needs to be a clear and engaging communication of how the system will respond at the unlock point.”), and
a description of the second rule accompanied by the second score ([0285] “Some examples of goals may include: achieving the opposite end of the spectrum for a certain period of time; achieving a certain level of volatility; achieving a certain amount of continuous “bonus” points; and achieving a certain overall score.”).
Regarding claim 9, Coleman teaches a method of providing personalized brain state guidance ([0376] “A recommendation of specific target brain state exercises based on previous performance and usage history may be provided by the system”), the method comprising:
receiving, at a brainwave guidance system for a meditation application, a first dataset representing brainwave activity for a first user during a first guided meditation session implemented based on a first meditation protocol, the first meditation protocol including at least a first rule and a second rule ([0005] “These electrical patterns, or brainwaves, are measurable by devices such as and EEG”; [0008] “the received bio-signal data comprising at least brainwave data of the at least one user; measure performance of the at least one user relative to at least one brain state guidance objective corresponding to the at least one brain state guidance routine at least partly by analyzing the received bio-signal data”; [0140]; [0148] “Some changes in Brainstate may not meaningful or useful for the user to receive notification, or the changes in brainstate need to be processed through rules that can send notifications that are effective in helping a user achieve their goal”);
calculating, by the brainwave guidance system, a first score characterizing a performance of the first dataset with respect to the first rule and a second score characterizing a performance of the first dataset with respect to the second rule ([0073] “The at least one brain state guidance objective may comprise the estimated busy-mind score indicative of a quiet-mind on the continuum”; [0148] “Notification Rules can use, as an example an integrator that counts the number of events that are indicative of the target state until a threshold is reached and then a notification is sent to the user”);
presenting, via the meditation application, both the first score and the second score ([0126] “An application on the phone processes the brainwaves and gives them feedback about their brain state using neurofeedback to help them achieve deeply meditative states and to speed their learning of meditation states.”; [0259] “the computer program scores the user for performance in a variety of ways. In one aspect, the user receives for example points for different positive actions of the user in relation to one or more exercises.”; [0373] “The system may recommend a meditation exercise based on discovery stage or user choice, past performance, and other factors”; [0376]);
receiving, via a user interface for the meditation application, a first request to improve the first score ([0143]; [0148] “Some changes in Brainstate may not meaningful or useful for the user to receive notification, or the changes in brainstate need to be processed through rules that can send notifications that are effective in helping a user achieve their goal”);
automatically creating, at the meditation application and in response to the first request, a second meditation protocol including only the first rule ([0150] “Notification Rules may decide what events or brainstates are interesting to the user. The rules consider the type of video game or exercise the user is engaged and the goal that user is trying to achieve”; [0258]); and
initiating, at the meditation application, a second guided meditation session for the first user that is implemented based on the second meditation protocol ([0293] “The present system may detect changes in the user's brain state and classify the new brain state and present a notification that is meaningful and relevant to the user's goal brain state. The app/system of the present invention may have built-in scripts that embody the instructions that has a voice actor to provide the instructions for the user to complete the exercise.”).
Regarding claim 10, Coleman teaches the method of claim 9, further comprising:
determining, at the meditation application, the first score falls below a predesignated threshold ([0153] “Conventional systems provide fixed thresholds that are set prior to the start of a session based on the user's previous sessions or a database of normative data. The present system may adapt a session as shown.”; [0280]); and
presenting to the first user, in response to the first score falling below the predesignated threshold, a message recommending the creation of the second meditation protocol in order to improve their performance for the first meditation protocol ([0254] “the graph may include information that indicates whether the user did well or badly and at what points and this may be brought to the next exercise to improve the results.”; [0256] “The scores may be displayed in real time or at the end of the experience in the form of graphs, raw data, interpretive visualizations (a tree that blossoms or wilts.) Feedback can be positive (rings a bell when you're in the right state) or negative (you hear thunder when your mind wanders).”).
Regarding claim 11, Coleman teaches the method of claim 9, wherein the first rule is directed to brain activity promoting a first metric and the second rule is directed to brain activity promoting a different, second metric ([0059] “Goal states may include: mindfulness, focused attention, open presence (open monitoring), positive emotions, and visualization, among others. Each of these goal states may be referred to as a meditative brain state, but the present invention is not limited only to meditative brain states.”; [0139]; [0146];[0151] “Notification Rules Types may include: Continuous Feedback (proportional), where feedback received is usually linear and proportional to a measure of a signal (e.g. speed of a race car is linearly proportional to alpha power) Continuous Feedback (integral), where feedback is proportional to how long user maintains a measure usually above a threshold (e.g. Speed of race increases as user maintains alpha power above a threshold); and Discrete Feedback, where Reward or penalty is a discrete event like a bell ding.”).
Regarding claim 12, Coleman teaches the method of claim 11, wherein the first metric represents one of power, percent of total power, power ratio, coherence, connectivity, minimum frequency, maximum frequency, phase synchrony, complexity, brain location, and target brainwave direction ([0139] “The system can derive feedback by frequency of changes plus direction of change.”; [0434] “Power spectrum of EEG signals from electrodes may be computed by the system of the present invention in real time … The coherence of two EEG signals are measured and their coherence is rewarded”).
Regarding claim 13, Coleman teaches the method of claim 9, further comprising:
receiving, at the brainwave guidance system, a second dataset representing brainwave activity for the first user during a second guided meditation session implemented based on a third meditation protocol, the third meditation protocol including at least a third rule, fourth rule, and a fifth rule ([0297] “focused attention exercise”; [0062] “the user may have selected a target brain state and is therefore consciously aware of the goal that the user is trying to achieve. Through the updated brain state guidance indications, the user may also achieve a meta-awareness of the state that the user is in. The feedback that the system provides to the user can be modified by notification rules, and the system's estimates of the user's brain state may be actively adapted. This differs with conventional methods that use fixed thresholds, and are not adaptive, instead using simple rules to provide feedback.”);
calculating, by the brainwave guidance system, a third score characterizing a performance of the second dataset with respect to the third rule, a fourth score characterizing a performance of the second dataset with respect to the fourth rule, and a fifth score characterizing a performance of the second dataset with respect to the fifth rule ([0067] “The at least one computing device may be configured to calibrate the at least one brain state stability threshold at least partly by: analyzing fixed time segments of the brainwave data in real-time; calculating an alpha power value for each time segment; calculating a statistical distribution of the alpha power values over a predetermined calibration time segment, the predetermined calibration time segment comprising a longer duration than each of the fixed time segments; and determining a statistical distribution of alpha variability based at least partly on instantaneous alpha variability of the statistical distribution of the alpha power values”);
presenting, via the meditation application, the third score, fourth score, and the fifth score ([0061] “The continuum may be quantized into a number of segments and the system may vary the UI element or scene for the brain state guidance exercise based on the quantization segment, thereby providing a real-time brain state guidance indication to the use”; [0063] “update the presented at least one brain state guidance indication based at least partly on the measured performance”; [0117]);
receiving, via the user interface, a second request to improve both the fourth score and the fifth score ([0295] “] In a Focused Attention Method of brain training, the user sets the intention to sustain attention upon an object with the goal to cultivate relaxation, stability and vividness of attention”); and
automatically creating, at the meditation application and in response to the second request, a fourth meditation protocol including only the fourth rule and the fifth rule ([0297] “An example of a focused attention exercise which may be employed by the present system”).
Regarding claim 14, Coleman teaches the method of claim 9, further comprising:
receiving, at the brainwave guidance system, a second dataset representing brainwave activity for the first user during a second guided meditation session implemented based on a third meditation protocol, the third meditation protocol including at least a third rule, fourth rule, and a fifth rule ([0297] “focused attention exercise”; [0062] “the user may have selected a target brain state and is therefore consciously aware of the goal that the user is trying to achieve. Through the updated brain state guidance indications, the user may also achieve a meta-awareness of the state that the user is in. The feedback that the system provides to the user can be modified by notification rules, and the system's estimates of the user's brain state may be actively adapted. This differs with conventional methods that use fixed thresholds, and are not adaptive, instead using simple rules to provide feedback.”);
calculating, by the brainwave guidance system, a third score characterizing a performance of the second dataset with respect to the third rule, a fourth score characterizing a performance of the second dataset with respect to the fourth rule, and a fifth score characterizing a performance of the second dataset with respect to the fifth rule ([0067] “The at least one computing device may be configured to calibrate the at least one brain state stability threshold at least partly by: analyzing fixed time segments of the brainwave data in real-time; calculating an alpha power value for each time segment; calculating a statistical distribution of the alpha power values over a predetermined calibration time segment, the predetermined calibration time segment comprising a longer duration than each of the fixed time segments; and determining a statistical distribution of alpha variability based at least partly on instantaneous alpha variability of the statistical distribution of the alpha power values”);
determining, at the meditation application, both the third score and the fourth score fall below a predesignated threshold, while the fifth score is above the predesignated threshold ([0061] “the system may determine the stability of the user's brain waves against a brain state stability threshold for the target brain state.”); and
automatically creating, at the meditation application and in response to the third score and the fourth score falling below the predesignated threshold, a fourth meditation protocol including only the third rule and the fourth rule ([0067] “wherein the at least one brain state guidance indication updating is based at least partly on the estimated busy-mind score.”).
Regarding claim 15, Coleman teaches the method of claim 9, wherein presentation of the first score is accompanied by a language-based descriptor (Fig. 52G “You’ve reached milestone”).
Regarding claim 16, Coleman teaches a method of providing personalized meditation feedback, the method comprising:
receiving, at a brainwave feedback system for a meditation application, a first meditation dataset representing brainwave activity for a first user during a first guided meditation session implemented based on a first meditation protocol, the first meditation protocol including at least a first rule and a second rule ([0005] “These electrical patterns, or brainwaves, are measurable by devices such as and EEG”; [0008] “the received bio-signal data comprising at least brainwave data of the at least one user; measure performance of the at least one user relative to at least one brain state guidance objective corresponding to the at least one brain state guidance routine at least partly by analyzing the received bio-signal data”; [0140]; [0148] “Some changes in Brainstate may not meaningful or useful for the user to receive notification, or the changes in brainstate need to be processed through rules that can send notifications that are effective in helping a user achieve their goal”);
calculating, by the brainwave feedback system, a first score characterizing a performance of the first meditation dataset with respect to the first rule and a second score characterizing a performance of the first meditation dataset with respect to the second rule ([0073] “The at least one brain state guidance objective may comprise the estimated busy-mind score indicative of a quiet-mind on the continuum”; [0148] “Notification Rules can use, as an example an integrator that counts the number of events that are indicative of the target state until a threshold is reached and then a notification is sent to the user”);
presenting, via the meditation application ([0282] “The system may employ the typical gamification technique of “badges” or “achievements” with self-administered neurofeedback”), a dashboard including:
a description of the first rule accompanied by the first score ([0254] “the graph may include information that indicates whether the user did well or badly and at what points and this may be brought to the next exercise to improve the results.”; [0284] “The screen presented to users directly after their session should provide clear guidance as to the purpose of that unlock. Showing users the average score, current score, and total score can help provide context. Visually showing the progress toward a goal is critical, and the labelling of that goal needs to be a clear and engaging communication of how the system will respond at the unlock point.”), and
a description of the second rule accompanied by the second score ([0285] “Some examples of goals may include: achieving the opposite end of the spectrum for a certain period of time; achieving a certain level of volatility; achieving a certain amount of continuous “bonus” points; and achieving a certain overall score.”).
Regarding claim 17, Coleman teaches the method of claim 16, wherein the dashboard further includes a first text-based descriptor accompanying the first score and a second text-based descriptor accompanying the second score (Fig. 52A depicts the scores of calm and neutral brain state scores described by text.).
Regarding claim 18, Coleman teaches the method of claim 16, wherein the first rule is directed to brain activity promoting a first metric and the second rule is directed to brain activity promoting a different, second metric ([0059] “Goal states may include: mindfulness, focused attention, open presence (open monitoring), positive emotions, and visualization, among others. Each of these goal states may be referred to as a meditative brain state, but the present invention is not limited only to meditative brain states.”; [0139]; [0146];[0151] “Notification Rules Types may include: Continuous Feedback (proportional), where feedback received is usually linear and proportional to a measure of a signal (e.g. speed of a race car is linearly proportional to alpha power) Continuous Feedback (integral), where feedback is proportional to how long user maintains a measure usually above a threshold (e.g. Speed of race increases as user maintains alpha power above a threshold); and Discrete Feedback, where Reward or penalty is a discrete event like a bell ding.”).
Regarding claim 19, Coleman teaches the method of claim 18, further comprising:
accessing, at the meditation application, a frequency band power database that includes a first set of text-based descriptions interpreting a range of scores possible for the first metric, and a second set of text-based descriptions interpreting a range of scores possible for the second metric ([0102] “The brain state information and optionally other bio-feedback or non-bio-feedback information may be used to assess whether the user is achieving “mindfulness of breath” or “mindfulness of sound” objectives. These objectives may be associated with one or more thresholds to determine not only whether a user is for example attempting to meet these objectives, but possibly also the particular region achieved by a user performing a mental exercise of the present invention, where a region is defined by a range of brain state values, or values based on other bio-signal or non-bio-signal data.”);
selecting a first text-based description linked to the first score from the first set and selecting a second text-based description linked to the second score from the second set ([0102] “assess whether the user is achieving “mindfulness of breath” or “mindfulness of sound” objectives”); and
presenting, via the meditation application, both the first text-based description and the second text-based description ([0109] “A stable brain state within particular brain wave power level regions may indicate different meditative states such as for example “mindfulness of breath” or “mindfulness of sound” or “concentration”. The system may provide a way to capture information related to these states of meditation.”; Fig. 52A depicts the scores of calm and neutral brain state scores described by text indicating a stable brain state).
Regarding claim 20, Coleman teaches the method of claim 16, further comprising:
receiving, via a user interface for the meditation application, a first request to improve the first score ([0143]; [0148] “Some changes in Brainstate may not meaningful or useful for the user to receive notification, or the changes in brainstate need to be processed through rules that can send notifications that are effective in helping a user achieve their goal”);
automatically creating, at the meditation application and in response to the first request, a second meditation protocol including only the first rule ([0150] “Notification Rules may decide what events or brainstates are interesting to the user. The rules consider the type of video game or exercise the user is engaged and the goal that user is trying to achieve”; [0258]); and
initiating, at the meditation application, a second guided meditation session for the first user that is implemented based on the second meditation protocol ([0293] “The present system may detect changes in the user's brain state and classify the new brain state and present a notification that is meaningful and relevant to the user's goal brain state. The app/system of the present invention may have built-in scripts that embody the instructions that has a voice actor to provide the instructions for the user to complete the exercise.”).
Conclusion
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/EVELYN GRACE PARK/Examiner, Art Unit 3791 /TSE W CHEN/Supervisory Patent Examiner, Art Unit 3791