DETAILED ACTION
Claims 1-20 are currently pending and have been examined.
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 § 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 an abstract idea without significantly more.
Subject Matter Eligibility Criteria - Step 1:
Claims 1-10 are directed to a system (i.e., a machine); Claims 11-19 are directed to a method (i.e., a process); and Claims 20 are directed to a CRM (i.e., a manufacture). Accordingly, claims 1-20 are all within at least one of the four statutory categories.
Subject Matter Eligibility Criteria - Alice/Mayo Test: Step 2A - Prong One:
Regarding Prong One of Step 2A, the claim limitations are to be analyzed to determine whether, under their broadest reasonable interpretation, they “recite” a judicial exception or in other words whether a judicial exception is “set forth” or “described” in the claims. MPEP 2106.04(II)(A)(1). An “abstract idea” judicial exception is subject matter that falls within at least one of the following groupings: a) certain methods of organizing human activity, b) mental processes, and/or c) mathematical concepts. MPEP 2106.04(a).
Representative independent claim 1 includes limitations that recite at least one abstract idea. Specifically, independent claim 1 recites:
1. A computing device, comprising:
one or more processors; and
one or more computer-readable media that store instructions that, when executed by the one or more processors, cause the computing device to perform operations, the operations comprising:
obtaining a plurality of sleep stages associated with a sleep session of a user, the sleep session at least partially defined by an estimated bedtime of the user;
identifying, in the plurality of sleep stages, one or more defined sleep stages indicative of a defined sleep state of the user;
calculating a time before sound sleep metric based at least in part on the estimated bedtime of the user and a start time of the one or more defined sleep stages; and
performing one or more operations based at least in part on the time before sound sleep metric.
The Examiner submits that the foregoing underlined limitations constitute “methods of organizing human activity” because obtaining sleep stage data of a user identifying sleep states of the user, calculating sleep metrics based on the user sleep data, and performing an action are associated with managing personal behavior or relationships or interactions between people. For example, but for the system, this claim encompasses a person facilitating data access, receiving data, and outputting data in the manner described in the identified abstract idea. The Examiner notes that “method of organizing human activity” includes a person’s interaction with a computer – see MPEP 2106.04(a)(2)(II)(C). If a claim limitation, under its broadest reasonable interpretation, covers managing personal behavior or interactions between people but for the recitation of generic computer components, then it falls within the “method of organizing human activity” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
Accordingly, independent claim 1 and analogous independent claims 11 & 20 recite at least one abstract idea.
Furthermore, dependent claims 2-10 & 12-19 further narrow the abstract idea described in the independent claims. Claims 2, 4, 12, & 14 recite determining the sleep metric, Claims 3 & 13 recite the sleep stage of the user, Claims 5-7 & 15-17 recite performing operations such as generating a notification to a user, sleep promoting features, Claims 8 & 18 recite performing an operation such as storing sleep data in a database, Claims 9 & 19 recite classifying a user in a sleep pattern category based on sleep metrics, and Claim 10 recites identifying a sleep pattern and determining a sleep diagnosis of the user. These limitations only serve to further limit the abstract idea and hence, are directed towards fundamentally the same abstract idea as independent claim 1 and analogous independent claims 11 & 20, even when considered individually and as an ordered combination.
Subject Matter Eligibility Criteria - Alice/Mayo Test: Step 2A - Prong Two:
Regarding Prong Two of Step 2A of the Alice/Mayo test, it must be determined whether the claim as a whole integrates the abstract idea into a practical application. As noted at MPEP §2106.04(II)(A)(2), it must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.” MPEP §2106.05(I)(A).
In the present case, the additional limitations beyond the above-noted at least one abstract idea recited in the claim are as follows (where the bolded portions are the “additional limitations” while the underlined portions continue to represent the at least one “abstract idea”):
1. A computing device, comprising:
one or more processors; and
one or more computer-readable media that store instructions that, when executed by the one or more processors, cause the computing device to perform operations, the operations comprising:
obtaining a plurality of sleep stages associated with a sleep session of a user, the sleep session at least partially defined by an estimated bedtime of the user;
identifying, in the plurality of sleep stages, one or more defined sleep stages indicative of a defined sleep state of the user;
calculating a time before sound sleep metric based at least in part on the estimated bedtime of the user and a start time of the one or more defined sleep stages; and
performing one or more operations based at least in part on the time before sound sleep metric.
For the following reasons, the Examiner submits that the above identified additional limitations do not integrate the above-noted at least one abstract idea into a practical application.
Regarding the additional limitations of the processor, memory, computing device; the Examiner submits that these limitations amount to merely using computers as tools to perform the above-noted at least one abstract idea (see MPEP § 2106.05(f)).
Thus, taken alone, the additional elements do not integrate the at least one abstract idea into a practical application.
Looking at the additional limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. For instance, there is no indication that the additional elements, when considered as a whole with the abstract idea, reflect an improvement in the functioning of a computer or an improvement to another technology or technical field, apply or use the above-noted judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, implement/use the above-noted judicial exception with a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing, or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole does not integrate the abstract idea into a practical application of the abstract idea. MPEP §2106.05(I)(A) and §2106.04(II)(A)(2).
For these reasons, representative independent claim 1 and analogous independent claim 11 & 20 do not recite additional elements that integrate the judicial exception into a practical application.
Accordingly, the claims recites at least one abstract idea.
Thus, taken alone, any additional elements do not integrate the at least one abstract idea into a practical application. Therefore, the claims are directed to at least one abstract idea.
Subject Matter Eligibility Criteria - Alice/Mayo Test: Step 2B:
Regarding Step 2B of the Alice/Mayo test, representative independent claim 1 does not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for reasons the same as those discussed above with respect to determining that the claim does not integrate the abstract idea into a practical application.
As discussed above, regarding the additional limitations of the processor, memory, computing device; the Examiner submits that these limitations amount to merely using computers as tools to perform the above-noted at least one abstract idea (see MPEP § 2106.05(f)).
The dependent claims also do not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for the same reasons to those discussed above with respect to determining that the dependent claims do not integrate the at least one abstract idea into a practical application.
Therefore, claims 1-20 are ineligible under 35 USC §101.
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.
Claim(s) 1-8, 10-17, & 19-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Nachman (US20180279946).
As per claim 1, Nachman discloses a computing device (machine (e.g., computing system) 400; paragraph [0039]), comprising: one or more processors (hardware processor 402; paragraph [0039]); and one or more computer-readable media that store instructions that, when executed by the one or more processors, cause the computing device to perform operations (storage device 416 includes a machine readable medium 422 on which is stored one or more sets of instructions 424; paragraph [00401), the operations comprising:
obtaining a plurality of sleep stages associated with a sleep session of a user (instructions identify sleep data of the user during a sleep cycle; paragraph [00691), the sleep session at least partially defined by an estimated bedtime of the user (a sleep cycle includes time duration from beginning of sleep until the user gets up in the morning; paragraph [0034]);
identifying, in the plurality of sleep stages, one or more defined sleep stages indicative of a defined sleep state of the user (identifies a contextual factor of a user including sleep duration and amount of time in deep, light, and REM sleep; paragraph [00491);
calculating a time before sound sleep metric based at least in part on the
estimated bedtime of the user and a start time of the one or more defined sleep stages (a contextual factor including the offset of go to bed time from median of habitual go to bed time and time to sleep; paragraph [0049]); and
performing one or more operations based at least in part on the time before sound sleep metric (contextual factors including the offset of go to bed time from median and time to go to sleep that are correlated with audio events associated with sleep interrupt and light levels associated with sleep interrupt; paragraph [0049]).
As per claim 2, Nachman discloses the computing device of claim 1, wherein the time before sound sleep metric is indicative of a time period between the estimated bedtime of the user and a time when the user enters the defined sleep state (a contextual factor including the offset of go to bed time from median of habitual go to bed time and time to sleep; paragraph [0049]).
As per claim 3, Nachman discloses the computing device of claim 1, wherein the plurality of sleep stages comprises at least one of a wake stage, a light sleep stage, a deep sleep stage, or a rapid eye movement sleep stage (identifies a contextual factor of a user including sleep duration and amount of time in deep, light, and REM sleep; paragraph [00491), and
wherein the one or more defined sleep stages comprise a defined quantity of at least one of the light sleep stage, the deep sleep stage, or the rapid eye movement sleep stage (qualitative measure of sleep is derived from feature vectors describing the night's sleep, which includes "duration of time in deep sleep", "duration of time in light sleep", "duration of time in REM sleep"; paragraph [0030]).
As per claim 4, Nachman discloses the computing device of claim 1, wherein calculating the time before sound sleep metric based at least in part on the estimated bedtime of the user and the start time of the one or more defined sleep stages comprises:
calculating a difference in time between the estimated bedtime of the user and the start time of the one or more defined sleep stages (a contextual factor including
the offset of go to bed time from median of habitual go to bed time and time to sleep; paragraph [0049]).
As per claim 5, Nachman discloses the computing device of claim 1, wherein performing the one or more operations based at least in part on the time before sound sleep metric comprises:
generating an intelligent notification comprising the time before sound sleep metric (identifying in the correlated sleep data, combinations of contextual and environmental factors that affect the sleep quality of a user; paragraph [0060]); and
providing the intelligent notification to at least one of the user or a second computing device (providing a change recommendation to the user to a user behavior or static environment; paragraph [0060]).
As per claim 6, Nachman discloses the computing device of claim 1, wherein performing the one or more operations based at least in part on the time before sound sleep metric comprises:
generating one or more sleep quality recommendations based at least in part on the time before sound sleep metric (identifying in the correlated sleep data, combinations of contextual and environmental factors that affect the sleep quality of a user; paragraph [0060]); and
providing an intelligent notification comprising at least one of the time before sound sleep metric or the one or more sleep quality recommendations to at least one of the user or a second computing device (providing a change recommendation to the user to a user behavior or static environment; paragraph [0060]).
As per claim 7, Nachman discloses the computing device of claim 1, wherein performing the one or more operations based at least in part on the time before sound sleep metric comprises:
implementing one or more sleep promoting features of at least one of the computing device or a second computing device based at least in part on the time before sound sleep metric (database 150 stores data from the sleep sensing, sleep environment interference and contextual interference logic components to mine for recommendations including specific window blinds associated with light rating of sleep interference for "natural light control" of the environment; paragraph [00251).
As per claim 8, Nachman discloses the computing device of claim 1, wherein performing the one or more operations based at least in part on the time before sound sleep metric comprises:
recording, in a database, at least one of the time before sound sleep metric or one or more additional time before sound sleep metrics corresponding to the user (database 150 stores data from the sleep sensing, sleep environment interference and contextual interference logic components to mine for recommendations; paragraph [0025]), the one or more additional time before sound sleep metrics being calculated based at least in part on at least one additional plurality of sleep stages associated with one or more additional sleep sessions of the user (correlation engine 140 in database 150 determines which environmental factors are likely to impact sleep most given different contextual factors that occurred outside of sleep; paragraph [00261).
As per claim 10, Nachman discloses the computing device of claim 1, wherein performing the one or more operations based at least in part on the time before sound sleep metric comprises:
identifying a defined sleep pattern of the user based at least in part on at least one of the time before sound sleep metric or one or more additional time before sound sleep metrics corresponding to the user (a set of sleep data is associated with a specific sleep cycle, where the includes a period immediately prior to sleep and immediately after waking up and the extension of time is user definable; paragraph [00341); and
determining at least one of a defined sleep condition diagnosis or a defined sleep condition prognosis associated with sleep quality of the user based at least in part on the defined sleep pattern (the recommendation engine includes a number of interference based learning that identifies factors that are modifiable such as sleep apnea in the user; paragraph (00361).
Claims 11-17 recite substantially similar limitations as those already addressed in claims 1-7, and, as such, are rejected for similar reasons as given above.
Claim 19 recites substantially similar limitations as those already addressed in claim 10, and, as such, is rejected for similar reasons as given above.
Claim 20 recites substantially similar limitations as those already addressed in claim 1, and, as such, is rejected for similar reasons as given above.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 9 & 18 are rejected under 35 U.S.C. 103 as being unpatentable over Nachman (US20180279946) in view of Carter (US20160367202)
As per claim 9, Nachman discloses the computing device of claim 8. Nachman fails to teach wherein performing the one or more operations
based at least in part on the time before sound sleep metric comprises:
comparing at least one of the time before sound sleep metric or the one or more additional time before sound sleep metrics to one or more second time before sound sleep metrics corresponding respectively to one or more second users; and
classifying the user in a defined sleep pattern category based at least in part on comparison of at least one of the time before sound sleep metric or the one or more additional time before sound sleep metrics to the one or more second time before sound sleep metrics.
Carter, however, teaches recording sleep data and sleep transition data, which includes awake-to-sleep transition record where once sleep is achieved, physiological data continues to be recorded during sleep period, are stored in a database for a user and other individuals (para. 85, 88-89). Carter also teaches to where the data records, including sleep data, sleep transition data, and awake activity data, comprise a multiplicity of records of third-party individuals, where the physiological cumulative data record of a user can be compared with third party individual trends (para. 89-91).
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the aforementioned features in Carter with Nachman based on the motivation of overcoming challenges with testing during sleep via providing wearable sensor management to optimize sensor energy efficiency and diagnostic efficacy (Carter – para. 3).
Claim 18 recites substantially similar limitations as those already addressed in claim 9, and, as such, is rejected for similar reasons as given above.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Viddam (US20230049849) teaches to patient sleep is staged using personalized circadian models built with data collected by wearable devices over daytime and nighttime hours, thus capturing a patient's personal circadian rhythms. The circadian model is used to identify sleep intervals in incoming nightly data for the patient. The identified sleep intervals are analyzed by the machine learning system which stages epochs of sleep.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Jonathan K Ng whose telephone number is (571)270-7941. The examiner can normally be reached M-F 8 AM - 5 PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Anita Coupe can be reached at 571-270-7949. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/Jonathan Ng/ Primary Examiner, Art Unit 3619
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