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 .
Election/Restrictions
Applicant's election with traverse of Group I in the reply filed on 09/15/2025 is acknowledged. The traversal is on the grounds that Groups I and II do not illustrate mutually exclusive characteristics that would support a restriction of species and that the Examiner has not explained why the restriction is proper. This is not found persuasive because the restriction requirement of 08/01/2025 was not a species restriction. Groups I and II were restricted because the technical feature of identifying and communicating an intervention action does not make a contribution over the prior art, as explained in the 08/01/2025 restriction requirement.
Groups I and II lack unity of invention because even though the inventions of these groups require the technical feature of identifying and communicating an intervention action, this technical feature is not a special technical feature as it does not make a contribution over the prior art in view of Molina et al. (US 2018/0368755). Molina discloses methods and systems to detect sleep stages of a user including identifying and communicating an intervention action (e.g. Pars. [0044]-[0045]: determining likelihood of increasing probability of sleep stage detection and using different stimuli to increase the probability of accuracy).
The requirement is still deemed proper and is therefore made FINAL.
Claims 12-16 withdrawn from further consideration pursuant to 37 CFR 1.142(b), as being drawn to a nonelected invention, there being no allowable generic or linking claim. Applicant timely traversed the restriction (election) requirement in the reply filed on 09/15/2025.
Remarks
This action is in response to the Remarks filed 09/15/2025.
Claims 1-11 and 17-20 are examined below.
Claim Objections
Claims 2, 4-6, 8-11, 18, and 20 objected to because of the following informalities:
Claims 2, 4-6, 8-11, and 20 recites the phrase “circuitry is to” at the beginning of the claim. Examiner suggests using the phrase “circuitry is configured to”.
Claim 6, line 8, “and as associated with the detected pattern” is confusing and grammatically incorrect.
Claim 18, line 3, “publically” should be “publicly”.
Appropriate correction is required.
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.
Claim 18 is 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.
Claim 18 recites the limitation "respective feature sets" in line 5. There is insufficient antecedent basis for this limitation in the claim.
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 1-11 and 17-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claims recite a system for determining a probability a user will transition between sleep stages. To determine whether a claim satisfies the criteria for subject matter eligibility, the claim is evaluated according to a stepwise process as described in MPEP 2106(III) and 2106.03-2106.04. The instant claims are evaluated according to such analysis.
Step 1: Is the claim to a process, machine, manufacture or composition of matter?
Claims 1 and 17 are directed towards a system, and thus meet the requirements for step 1.
Step 2A (Prong 1): Does the claim recite an abstract idea, law of nature, or natural phenomenon?
Claims 1 and 17 recite a system for determining a probability a user will transition between sleep stages, comprising receiving data indicative of the user’s current psychophysiological state, storing a predictive data model, detecting a pattern from the user data that is indicative of a probability of a user transitioning from an awake to a sleep state, selecting an intervention action based on the detected pattern, and communicating a message of the intervention action to the user.
The limitation of determining a probability a user will transition between sleep stages, as drafted in claims 1-11 and 17-20, under its broadest reasonable interpretation, covers performance of the limitation in the mind or using pen and paper. For example, determining a probability a user will transition between sleep stages in the context of this claim encompasses a user collecting patient psychophysiological data, using a predictive data model to detect a pattern in the collected data, and based on the pattern, determining and communicating to the patient an intervention action that increases the probability of going from an awake to a sleep state.
Step 2A (Prong 2): Does the claim recite additional elements that integrate the judicial exception into a practical application?
As claimed and understood, the crux of the invention is the data analysis performed in order to select the intervention action. The steps of receiving patient data and storing a predictive data model are considered to be the pre-solution activity of data gathering by no more than routine means. The steps of detecting a pattern and selecting an intervention action based on the pattern are considered to be data analysis steps. The step of communicating a message to the user is considered to be a data output step.
The additional elements of the input circuitry, memory circuitry, and processing circuitry are recited at a high level of generality (i.e., as generic computer components for inputting, processing, and storing data). The wearable sensor in claim 10 is generic structure for the insignificant, extra-solution activity of data gathering. Specifically, these additional elements are generically recited computing elements that perform the steps of gathering, analyzing, and outputting data.
Accordingly, these additional elements do no integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. See MPEP 2106.04(a)(2)(III)(C).
Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
The additional elements when considered individually and in combination is not enough to qualify as significantly more than the abstract idea. As discussed above with respect to the integration of the abstract idea into a practical application, the additional elements of input circuitry, memory circuitry, and processing circuitry amounts to no more than generically claimed computer components which enable the above-identified abstract idea to be conducted by performing the basic functions of automating mental tasks. The wearable sensor in claim 10 is generic structure for the insignificant, extra-solution activity of data gathering. Furthermore, the additional elements do not amount to more than generically linking the use of a judicial exception to a particular technological environment or field of use (see MPEP 2106.05(h)). Therefore, the claims are not patent eligible.
Claims 2-11 and 18-20 depend on claims 1 and 17 and recite the same abstract idea as claims 1 and 17 from which they depend. Further, these claims only contain recitations that further limit the abstract idea (that is, the claims only recite limitations that further limit the mental process). For example, the additional limitations recited in claims 2-9 and 18-20 (i.e. further defining the processing steps) are further data analysis steps. The additional limitations recited in claim 11 (i.e. receiving additional patient data) is a further data gathering step. The additional elements individually do not amount to significantly more than the judicial exception explained above (the abstract idea). Looking at the limitations 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 any technology or includes a particular solution to a computer-based problem or a particular way to achieve a computer-based outcome. Rather, the collective functions of the claimed invention merely provides a conventional computer implementation, i.e. the computer (processor) is simply a tool to perform the claimed invention.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-9, 11, and 17-20 are rejected under 35 U.S.C. 103 as being unpatentable over Chan et al. (US Patent Application Publication 2015/0190086 – APPLICANT CITED ON 09/19/2022 IDS), hereinafter Chan, further in view of Molina et al. (US Patent Application Publication 2018/0368755 – APPLICANT CITED ON 09/19/2022 IDS), hereinafter Molina.
Regarding claim 1, Chan discloses a system (e.g. Abstract) comprising:
memory circuitry to store a predictive data model indicative of different patterns and probabilities of a user transitioning from an awake state to a sleep state (e.g. Par. [0006]: memory; Pars. [0041]-[0042]: machine learning classifier and Hidden Markov Model used to determine probabilities of transitioning between sleep stages); and
processing circuitry (e.g. Par. [0018]: processor 104) to:
detect, using data indicative of a current psychophysiological state of the user, a pattern among the different patterns of the predictive data model that is indicative of a probability of the user transitioning from the awake state to the sleep state at a date and time (e.g. Pars. [0026]-[0027]: features determined for each epoch to classify the sleep stages; Pars. [0041]-[0043]: the hidden Markov model predicts the sequence of sleep stages, including going from awake to the first stage; Par. [0045]: graph 306 that shows the different sleep stages predicted by the model at different times; Fig. 3: graph 306).
However, Chan fails to disclose based on the detected pattern, select an intervention action predicted to increase the probability of the user transitioning to the sleep state at the date and time, and communicate a message indicative of the intervention action to the user.
Molina, in a similar field of endeavor, discloses systems and methods of detecting sleep stages. Molina discloses based on a pattern, selecting an intervention action predicted to increase the probability of the user transitioning to the sleep state at the date and time (e.g. Par. [0035]: sleep stage module that indicates probability of a transition from one sleep stage to another; Pars. [0044]-[0045]: determining stimuli to be provided to the patient), and communicate a message indicative of the intervention action to the user (e.g. Pars. [0044]-[0045]: auditory and visual stimuli are used to communicate with the patient; Par. [0027]: information and results communicated to the user).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Chan to include the selection and communication of the intervention action to the user as taught by Molina, because doing so would increase the probability of accuracy of determining sleep stages (e.g. Molina, par. [0045]).
Regarding claim 2, Chan further discloses wherein the processing circuitry is to detect the pattern by identifying, in the data, a feature set from among a plurality of feature sets and selecting a sub-model of the predictive data model using the feature set, the predictive data model including a plurality of sub-models (e.g. Par. [0024]: machine learning classifier used to determine sleep stage probabilities which is then input into another algorithm; Par. [0027]: multiple epochs have features calculated; Pars. [0034]-[0035]: each epoch is associated with a certain sleep stage).
However, Chan fails to specifically disclose the plurality of sub-models that indicate the probability of the user transitioning to the sleep state in response to different intervention actions, and the plurality of sub-models being associated with a particular feature set of the plurality of feature sets. Molina, in a similar field of endeavor, discloses systems and methods of detecting sleep stages. Molina discloses indicating the probability of the user transitioning to the sleep state in response to different intervention actions, and a plurality of sub-models being associated with a particular feature set of the plurality of feature sets (e.g. Pars. [0044]-[0045]: auditory and visual stimuli are used to communicate with the patient; Par. [0035]: each sleep stage has its own neuron with its own activation function to determine probability of that sleep stage).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Chan in view of Molina to include the probability of the user transitioning to the sleep state in response to different intervention actions and the plurality of sub-models being associated with a particular feature set as taught by Molina, because doing so would increase accuracy of the prediction of probability of the sleep stage (e.g. Molina, par. [0045]).
Regarding claim 3, Chan further discloses wherein the plurality of sub-models are associated with different time frames, and each feature of the feature set has a weight associated with the probability of the user transitioning to the sleep state (e.g. Pars. [0043]-[0044]: prior probabilities and time varying matrices used to predict the sequence of sleep stages).
Regarding claim 4, Chan further discloses training the classifier using initial data (e.g. Pars. [0049]-[0050]). However, Chan fails to specifically disclose wherein the processing circuitry is to revise the predictive data model based on feedback data which is indicative of whether the user transitions to the sleep state responsive to the intervention action. Molina, in a similar field of endeavor, discloses systems and methods of detecting sleep stages. Molina discloses wherein the processing circuitry is to revise the predictive data model based on feedback data which is indicative of whether the user transitions to the sleep state responsive to the intervention action (e.g. Pars. [0039]-[0040]: the sleep stage module is configured to refine the sleep stage estimation and probability based on the reassessment stimuli).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Chan in view of Molina to include refining the model based on feedback as taught by Molina, because doing so would allow increased accuracy in determining the sleep stages and the transition between sleep stages.
Regarding claim 5, Chan fails to disclose wherein the processing circuitry is to receive the feedback data in real time, and in response to the feedback data and the revised predictive data model, to communicate another message indicative of a revised intervention action. Molina, in a similar field of endeavor, discloses systems and methods of detecting sleep stages. Molina discloses wherein the processing circuitry is to receive the feedback data in real time, and in response to the feedback data and the revised predictive data model, to communicate another message indicative of a revised intervention action (e.g. Pars. [0039]-[0040]: the sleep stage module is configured to refine the sleep stage estimation and probability based on the reassessment stimuli, and the updated stimuli is provided to the user).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Chan in view of Molina to include refining the model based on feedback and communicating an updated message as taught by Molina, because doing so would allow increased accuracy in determining the sleep stages and the transition between sleep stages.
Regarding claim 6, Chan fails to disclose wherein the processing circuitry is to receive the feedback data, and in response to the received feedback data: identify features from the feedback data; identify whether the user exhibits a response to the intervention action that is anticipated by the predictive data model to increase the probability based on the identified features; and in response to an unexpected response, revise the predictive data model for the user and as associated with the detected pattern. Molina, in a similar field of endeavor, discloses systems and methods of detecting sleep stages. Molina discloses wherein the processing circuitry is to receive the feedback data, and in response to the received feedback data: identify features from the feedback data, identify whether the user exhibits a response to the intervention action that is anticipated by the predictive data model to increase the probability based on the identified features, and in response to an unexpected response, revise the predictive data model for the user and as associated with the detected pattern (e.g. Pars. [0039]-[0040]: the sleep stage module is configured to refine the sleep stage estimation and probability based on the reassessment stimuli, and the updated stimuli is provided to the user).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Chan in view of Molina to include refining the model based on feedback as taught by Molina, because doing so would allow increased accuracy in determining the sleep stages and the transition between sleep stages.
Regarding claim 7, Chan fails to disclose wherein the intervention action is part of a sleep intervention strategy that includes a plurality of intervention actions, the plurality of intervention actions being selected from a group consisting of: a behavioral intervention action, a cognitive intervention action, a neuromodulation action, an environmental change, a sensory action, and combinations thereof. Molina, in a similar field of endeavor, discloses systems and methods of detecting sleep stages. Molina discloses wherein the intervention action consists of a sensory action (e.g. Par. [0043]: visual and auditory stimulus are types of stimuli presented).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Chan in view of Molina to include the sensory intervention action as taught by Molina to determine the most effective stimuli to provide.
Regarding claim 8, Chan fails to disclose wherein the processing circuitry is to communicate the message indicative of the sleep intervention strategy and which includes an order of the plurality of intervention actions. Molina, in a similar field of endeavor, discloses systems and methods of detecting sleep stages. Molina discloses wherein the processing circuitry is to communicate the message indicative of the sleep intervention strategy and which includes an order of the plurality of intervention actions (e.g. Par. [0043]: the first stimuli provided is visual, then auditory).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Chan in view of Molina to include the order of intervention actions as taught by Molina to determine the most effective stimuli to provide.
Regarding claim 9, Chan fails to disclose wherein the processing circuitry is to communicate a plurality of messages, including the message, that are indicative of the plurality of intervention actions, each of the plurality of messages being selected from a group consisting of: a message displayed to the user that instructs the user to take a respective intervention action, and a message to another device to automatically cause a respective intervention action to occur at a particular time in accordance with the sleep intervention strategy. Molina, in a similar field of endeavor, discloses systems and methods of detecting sleep stages. Molina discloses wherein the processing circuitry is to communicate a plurality of messages, including the message, that are indicative of the plurality of intervention actions, each of the plurality of messages being a message displayed to the user that instructs the user to take a respective intervention action (e.g. Par. [0043]: a visual stimuli is provided).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Chan in view of Molina to include the message being displayed to the user as taught by Molina because doing so would allow measurement of the user’s reaction.
Regarding claim 11, Chan further discloses input circuitry to receive the data indicative of the current psychophysiological state of the user, wherein the data received is selected from a group consisting of: schedule or calendar data, stress level, general mood, dietary data, health information, exercise data, sleep data, and a combination thereof (e.g. Par. [0016]0, [0018]: health information of the user is measured).
Regarding claim 17, Chan discloses a system (e.g. Abstract) comprising:
input circuitry to receive data indicative of a current psychophysiological state of a user (e.g. Par. [0016]);
memory circuitry to store a predictive data model indicative of different patterns and probabilities of a user transitioning from an awake state to a sleep state (e.g. Par. [0006]: memory; Pars. [0041]-[0042]: machine learning classifier and Hidden Markov Model used to determine probabilities of transitioning between sleep stages); and
processing circuitry (e.g. Par. [0018]: processor 104) to:
detect, using data indicative of a current psychophysiological state of the user, a pattern among the different patterns of the predictive data model that is indicative of a probability of the user transitioning from the awake state to the sleep state at a date and time (e.g. Pars. [0026]-[0027]: features determined for each epoch to classify the sleep stages; Pars. [0041]-[0043]: the hidden Markov model predicts the sequence of sleep stages, including going from awake to the first stage).
However, Chan fails to disclose based on the detected pattern, select an intervention action predicted to increase the probability of the user transitioning to the sleep state at the date and time, and communicate a message indicative of the intervention action to the user.
Molina, in a similar field of endeavor, discloses systems and methods of detecting sleep stages. Molina discloses based on a pattern, selecting an intervention action predicted to increase the probability of the user transitioning to the sleep state at the date and time (e.g. Par. [0035]: sleep stage module that indicates probability of a transition from one sleep stage to another; Pars. [0044]-[0045]: determining stimuli to be provided to the patient), and communicate a message indicative of the intervention action to the user (e.g. Pars. [0044]-[0045]: auditory and visual stimuli are used to communicate with the patient; Par. [0027]: information and results communicated to the user).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Chan to include the selection and communication of the intervention action to the user as taught by Molina, because doing so would increase the probability of accuracy of determining sleep stages (e.g. Molina, par. [0045]).
Regarding claim 18, Chan further discloses wherein the memory circuitry includes instructions that when executed cause the processing circuitry to generate the predictive data model based on general population trends and publicly available information (e.g. Pars. [0049-[0050]).
However, Chan fails to specifically disclose revising the predictive data model for the user over time using feedback data indicative of success of different sleep intervention strategies for respective feature sets. Molina, in a similar field of endeavor, discloses systems and methods of detecting sleep stages. Molina discloses revising the predictive data model for the user over time using feedback data indicative of success of different sleep intervention strategies for respective feature sets (e.g. Pars. [0039]-[0040]: the sleep stage module is configured to refine the sleep stage estimation and probability based on the reassessment stimuli, and the updated stimuli is provided to the user).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Chan in view of Molina to include refining the model based on feedback as taught by Molina, because doing so would allow increased accuracy in determining the sleep stages and the transition between sleep stages.
Regarding claim 19, Chan fails to disclose wherein the at least one message indicative of the at least one intervention action further includes an indication of an order and timing of the at least one intervention action. Molina, in a similar field of endeavor, discloses systems and methods of detecting sleep stages. Molina discloses wherein the at least one message indicative of the at least one intervention action further includes an indication of an order and timing of the at least one intervention action (e.g. Par. [0043]: the first stimuli provided is visual, then auditory).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Chan in view of Molina to include the order of intervention actions as taught by Molina to determine the most effective stimuli to provide.
Regarding claim 20, Chan fails to disclose wherein the processing circuitry is to communicate the at least one message to another device to automatically cause the at least one intervention action to occur at a particular time in accordance with the sleep intervention strategy. Molina, in a similar field of endeavor, discloses systems and methods of detecting sleep stages. Molina discloses wherein the processing circuitry is to communicate the at least one message to another device to automatically cause the at least one intervention action to occur at a particular time in accordance with the sleep intervention strategy (e.g. Par. [0027]: a user interface that outputs results, data, and instructions to the user).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Chan in view of Molina to include outputting the message to another device as taught by Molina because doing so would allow the user to be notifies of the message and intervention action.
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Chan et al. (US Patent Application Publication 2015/0190086 – APPLICANT CITED ON 09/19/2022 IDS), hereinafter Chan, further in view of Molina et al. (US Patent Application Publication 2018/0368755 – APPLICANT CITED ON 09/19/2022 IDS), hereinafter Molina, as applied to claim 1 above, and further in view of Wright et al. (US Patent Application Publication 2020/0121248), hereinafter Wright.
Regarding claim 10, Chan further discloses input circuitry to receive the data indicative of the current psychophysiological state of the user, the input circuitry including a wearable physiological sensor to sense a physiological signal from the user (e.g. Par. [0016]). However, Chan fails to specifically disclose another sensor to sense an atmospheric measurement. Wright, in a similar field of endeavor, is directed towards determining sleep states of the user. Wright discloses an additional sensor to sense an atmospheric measurement (e.g. Par. [0065]: environmental sensors to measure data relating to temperature).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Chan in view of Molina to include the environmental sensor as taught by Wright to determine environmental factors that disturb sleep.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Kinnunen et al. (US 2022/0375590) is directed towards a sleep staging algorithm.
Kahn et al. (US 11,766,213) is directed towards sleep monitoring.
Aoyama et al. (US 2015/0029030) is directed towards sleep state management.
Rubin et al. (US 2007/0249952) is directed towards sleep monitoring.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SHREYA P ANJARIA whose telephone number is (571)272-9083. The examiner can normally be reached M-F: 8:00-5:00 EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jennifer McDonald can be reached at 571-270-3061. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/SHREYA ANJARIA/Examiner, Art Unit 3796
/ALLEN PORTER/Primary Examiner, Art Unit 3796