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 .
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-20 rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
In claims 1, 17 it is unclear as to what is meant or how is performed the step of “identifying an individual with an unknown stress level”.
Claim Rejections - 35 USC § 102
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.
patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-4, 6-8, 10, 16-20 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Denison et al. (US 2014/0316230, hereinafter Denison).
With respect to claims 1, 17 Denison discloses a method and system comprising: identifying an individual with an unknown stress level; obtaining one or more electrical or optical signals associated with stress from the individual; (see para. 0015, “According to embodiments of the invention the inventors have established new technologies and solutions that address these limitations within the prior art and provide benefits including, but not limited to, global acquisition and storage of acquired EEG data and processed EEG data, development interfaces for expansion and re-analysis of acquired EEG data, long-term/continuous user wearability, detection of states of mental clarity, and improved detection of states of meditation.”, see para. 0070 “Mental states which the EEG waveform analysis roughly quantifies and displays to users in the form of a metric may include, but are not limited to, stress, relaxation, concentration, meditation, emotion and/or mood, valence (positiveness/negativeness of mood), arousal (intensity of mood), dominance (feeling of "control"), anxiety, drowsiness, state mental clarity/acute cognitive functioning (i.e. "mental fogginess" vs. "mental clarity", creativity, reasoning, memory), sleep, sleep quality (for example based on time spent in each stage of sleep as easily detected with EEG), amount of time asleep, presence of a seizure, presence of a seizure "prodromal stage" (indicative of an upcoming seizure), presence of stroke or impending stroke, presence of migraine or impending migraine, severity of migraine, heart rate, panic attack or impending panic attack.”
predicting a stress level of the individual based on the one or more electrical or optical signals obtained from the individual, wherein the stress level of the individual is predicted by a predictive model (see para. 0096, 0159, 0083 “Alternatively, linear time domain-based features, typically simple features, can be extracted from EEG data which have predictive value for some Neurometrics as well as disorders, stages of sleep, etc. particularly when used with other more complex feature analysis. Accordingly, through a combination of local algorithmic features, i.e. on the user's PED, and remote algorithmic features, i.e. those processing statistically or algorithmically extracted EEG data with machine learning classifiers running on remote servers, e.g. a cloud sourced backend, then these simpler features will essentially augment the more complex ones, to produce an overall greater classification accuracy.”
and generating a recommendation for the individual based on the predicted stress level, the recommendation including one or more mental exercises for relieving stress for the individual (see para. 0110, 0121, 0184, 0185, “Certain iterations of Introspect will also include cognitive "brain training" tasks intended to help users improve on a variety of mental skills/characteristics traits such as working memory and attention. These tasks will augment the built-in neurofeedback exercises that are also intended to improve these features--thus providing another avenue through which users can improve themselves on their mental characteristics of choice. Furthermore, cognitive tasks augmented by neurofeedback in a variety of ways--and neurofeedback augmented by cognitive tasks--are also aspects of "Introspect." This includes but is not limited to: 1) the recommendation of a cognitive task/mental activity or cognitive tasks/mental activities as methods for users to increase or decrease the amplitude of certain EEG wavebands; 2) sessions in which users concurrently perform a neurofeedback exercise and a cognitive task, and are scored on both--i.e. a conglomerate measure of the quality of the session is generated; 3) testing the efficacy of a neurofeedback session by the performance of a cognitive task directly prior and following a neurofeedback exercise; and/or 4) testing the efficacy of a cognitive task in changing user EEG band activity by having users perform a neurofeedback exercise directly prior and following a cognitive task--thus allowing the software to alter which exercises are recommended to the user in response to the prior impact various exercises have had on user mental state/EEG activity.”.
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With respect to claims 2, 18 Denison discloses wherein the one or more electrical or optical signals include one or more of an electroencephalogram (EEG) signal, a photoplethysmography (PPG) signal, or a remote PPG (rPPG) signal (see para. 0015).
With respect to claims 3, 19, Denison discloses wherein the one or more electrical or optical signals include one or more signals obtained from a wearable device, the wearable device including one or more sensors configured to measure the one or more signals (see Figs, 3A, 3B).
With respect to claim 4 Denison discloses wherein the wearable device is a virtual reality (VR) device (see Figs. 3A, 3B).
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With respect to claim 6 Denison discloses wherein the one or more mental exercises include one or more of an image, an audio, or a video (see para. 185).
With respect to claim 7 Denison discloses wherein the one or more mental exercises are played in a two-dimensional environment when the individual practices the one or more mental exercises. (see para. 0185, 0186).
With respect to claim 8 Denison discloses wherein the one or more mental exercises are played in a virtual reality environment when the individual practices the one or more mental exercises (see para. 0185, 0186).
With respect to claims 10, 20 Denison discloses further comprising: obtaining one or more tasks to be performed by the individual; assessing complexity of the one or more tasks to be performed by the individual; and creating a schedule for performing the one or more tasks by the individual based on the determined complexity of the one or more tasks and the determined stress level of the individual (see para. 0185)
With respect to claim 16 Denison discloses wherein the one or more recommendations include one or more classes for the individual, the one or more classes being arranged in sequence when more than one class is included in the recommendations (see para. 0185, sessions).
Claim Rejections - 35 USC § 103
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.
Claim(s) 9, 11-15, are rejected under 35 U.S.C. 103 as being unpatentable over Denison (US 2014/0316230) in view of Sinha et al. (US 2023/0335258, hereinafter Sinha).
With respect to claim 9, Denison discloses the system and method as set forth above, but fails to explicitly teach wherein the one or more mental exercises include a mental exercise generated by a generative artificial intelligence (AI).
In the same field of endeavor in the subject of method and system for generating personalized intervention plans based on mental health and other aspect of the subject as part of a training model, Sinha discloses a generative AI model by a large language model (LLM) for providing personal intervention plans to treat the subject (see para. 0151, 0152).
It would have been obvious to one skilled in the art before the effective filling date to teach wherein the one or more mental exercises include a mental exercise generated by a generative artificial intelligence (AI) as disclosed by Denison in order to improve patient diagnostic and treatment (see para. 0002).
With respect to claim 11 Sinha discloses further comprising: creating one or more large language models (LLMs), the LLMs configured to automatically output breakdowns for the one or more tasks based on the determined complexity of the one or more tasks and the determined stress level of the individual (see para. 0151).
With respect to claim 12 Sinha discloses wherein the one or more LLMs are configured to automatically generate a summary for the output breakdowns (para. 0167) .
With respect to claim 13 Sinha discloses wherein the predictive model is further trained to predict one or more of a focus level, a cognitive ability, an attention level, or an alertness level for the individual (see para. 0140).
With respect to claim 14 Sinha discloses wherein the schedule of the individual is created based on the predicted one or more of the stress level, focus level, cognitive ability, attention level, or alertness level for the individual (see para. 0140).
With respect to claim 15 Sinha discloses wherein the one or more recommendations include one or more physical exercises, diet, or nutrition for the individua (see para. 0161).
Claim(s) 5 is/are rejected under 35 U.S.C. 103 as being unpatentable over in Denison (US 2014/0316230) in view of Kodra (US 2015/0313530).
With respect to claim 5 Denison discloses the method as set forth above, but fails to explicitly disclose wherein the one or more electrical or optical signals includes a signal obtained from a camera, the camera performing a face scan of the individual to obtain the signal.
Kodra in the same field of invention in the subject of mental state event generation acquisition discloses using a video camera to acquire face pictures (see para. 0007).
It would have been obvious to one skilled in the art before the effective filling date to wherein the one or more electrical or optical signals includes a signal obtained from a camera, the camera performing a face scan of the individual to obtain the signal because doing so will allow to further obtain individual characteristics for stress of the subject.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOSEPH M SANTOS RODRIGUEZ whose telephone number is (571)270-7782. The examiner can normally be reached Monday-Friday 8:30am to 5:30pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Anne M. Kozak can be reached at 571-270-0552. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/JOSEPH M SANTOS RODRIGUEZ/Primary Examiner, Art Unit 3797