DETAILED ACTION
Status of Claims
This action is in reply to the communication filed on 20 January, 2026.
Claims 1, 19 and 20 have been amended.
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 Objections
Claims 1, 19 and 20 are objected to because of the following informalities: Claims 1, 19 and 20 recite “determining based at least in part on the adjusted physiological data . . .”; however, “adjusting” has been changed to “weighting”. Examiner assumes this is a typographical oversight. The claims should recite: “determining based at least in part on the weighted . Appropriate correction is required.
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), and does not include additional elements that either: 1) integrate the abstract idea into a practical application, or 2) that provide an inventive concept – i.e. element that amount to significantly more than the abstract idea. The Claims are directed to an abstract idea because, when considered as a whole, the plain focus of the claims is on an abstract idea.
Claim 1 is representative. Claim 1 recites:
A method at a user device, comprising:
receiving baseline physiological data associated with a user, the baseline physiological data measured by a wearable device throughout a first time interval, wherein the wearable device comprises a plurality of photoplethysmography (PPG) sensors configured to measure arterial blood flow at different locations on a finger of the user;
modifying weights of a baseline circadian rhythm adjustment model based at least in part on the baseline physiological data associated with the user to generate a modified circadian rhythm adjustment model that is individualized for the user, the modified circadian rhythm adjustment model associated with a circadian rhythm of the user;
receiving additional physiological data associated with the user, the additional physiological data measured by the wearable device during an additional time interval;
inputting the additional physiological data and the modified circadian rhythm adjustment model into a machine learning classifier;
weighting, by the machine learning classifier, the additional physiological data using the modified circadian rhythm adjustment model to generate weighted physiological data based at least in part on inputting the additional physiological data and the modified circadian rhythm adjustment model into the machine learning classifier;
determining, based at least in part on the adjusted physiological data, a plurality of contributing factors associated with a score for the user,
wherein a first contributing factor of the plurality of contributing factors is a quantity of rapid eye movement sleep; the quantity of rapid eye movement sleep determined based at least in part on one or more movements of the user, a heart rate of the user, a heart rate variability (HRV) of the user, a change in a temperature of the user, or any combination thereof;
calculating a value for the score for the user based at least in part on the plurality of contributing factors and a plurality of weights;
displaying, by a graphical user interface, a prompt for the user to provide a subjective assessment by the user regarding a state or an experience of the user;
receiving, based at least in part on displaying the prompt, input data from the user indicating the subjective assessment, the input data indicative of a range of values associated with the score for the user, the range of values corresponding to the state or the experience of the user;
adjusting a first weight of the plurality of weights based at least in part on the range of values indicated by the subjective assessment, the first weight corresponding to the first contributing factor; and
recalculating the value for the score for the user based at least in part on the adjusted first weight applied to the first contributing factor and based at least in part on the value for the score being outside of the range of values indicated by the subjective assessment.
Claim 20 recites medium with instructions executed by a processor, and Claim 19 recites an apparatus that executes the steps of the method recited in Claim 1.
STEP 1
The claims are directed to a device, a method and non-transitory computer readable medium which are included in the statutory categories of invention.
STEP 2A PRONG ONE
The claims, as illustrated by Claim 1, recite a sequence of steps including limitations that encompass a sequence of abstract ideas within the mathematical formula or relationship grouping, including:
receiving baseline physiological data associated with a user, the baseline physiological data measured throughout a first time interval; modifying weights of a baseline circadian rhythm adjustment model based at least in part on the baseline physiological data associated with the user to generate a modified circadian rhythm adjustment model that is individualized for the user, the modified circadian rhythm adjustment model associated with a circadian rhythm of the user;
receiving additional physiological data associated with the user, the additional physiological data measured during an additional time interval; weighting the additional physiological data to generate weighted physiological data based at least in part on the additional physiological data and the modified circadian rhythm adjustment model.
The claims recite a sequence of steps for calculating a value for a score for a user based on physiological data associated with the user. The physiological data may be weighted, and the weights may be adjusted based on an individualized circadian rhythm adjustment model and a subjective assessment provided by the user.
Initially, the claims require modifying a “baseline” circadian rhythm adjustment model using baseline user data to “generate tailored, individualized circadian rhythm adjustment models” (@ 0031). The modified circadian rhythm adjustment model represents weights to be applied to the physiological data of the user when calculating the score; as such, “modifying the model” involves “modifying the weights”. Here, Examiner notes that the specification does not disclose how to modify the weights based on a particular user’s baseline data. As such, the broadest reasonable interpretation of modifying the circadian rhythm adjustment model includes a user making a mental judgement as to what the weight should be and applying a correction factor to the baseline weight. Similarly, once the weights are adjusted, adjusting the physiological data by applying the adjusted weights to the data is a simple mathematical operation that can be performed mentally. Examiner notes that the above recited limitations may be reasonably construed as extra-solution data gathering steps.
The claims recite further processing of the received and adjusted additional physiological data, including the following limitations:
determining, based at least in part on the adjusted physiological data, a plurality of contributing factors associated with a score for the user,
wherein a first contributing factor of the plurality of contributing factors is a quantity of rapid eye movement sleep; the quantity of rapid eye movement sleep determined based at least in part on one or more movements of the user, a heart rate of the user, a heart rate variability (HRV) of the user, a change in a temperature of the user, or any combination thereof;
calculating a value for the score for the user based at least in part on the plurality of contributing factors and a plurality of weights;
receiving, based at least in part on displaying the prompt, input data from the user indicating the subjective assessment, the input data indicative of a range of values associated with the score for the user, the range of values corresponding to the state or the experience of the user; adjusting a first weight of the plurality of weights based at least in part on the range of values indicated by the subjective assessment, the first weight corresponding to the first contributing factor; and
recalculating the value for the score for the user based at least in part on the adjusted first weight applied to the first contributing factor and based at least in part on the value for the score being outside of the range of values indicated by the subjective assessment.
The claims calculate a plurality of contributing factors, including a quantity of REM sleep, based on physiological data; and a value for a score based on weighted contributing factors. The specification discloses that the “REM sleep” contributor is one factor used to calculate a “Sleep Score”. Other contributing factors for the Sleep Score may include “total sleep, efficiency, restfulness, deep sleep, latency, or timing”. (@ 0084) Each of these factors is calculated using a mathematical formula or relationship. For example, “total sleep” is a sum of all sleep periods in a day; “restfulness” may be a wake-up count, etc. In particular, the “quantity of REM sleep” is disclosed as “a sum total of REM sleep durations.” Here, Examiner notes that the claims do not require “determining or detecting the duration of periods of REM sleep”, only summing the durations of REM sleep obtained using other means. Technical details for determining a sleep stage and durations are limited to using a machine learning classifier, which is purely generic, configured to classify periods of time into different stages of sleep, including REM sleep, applied to the collected physiological data. Similarly, the value for the score, such as a Sleep Score, may be calculated as a summation of the weighted factors, including after the weights have been adjusted.
Weights may be adjusted based on a correlation between a contributing factor and a user’s subjective assessment. Weights may be increased or decreased by an amount determined through some unspecified means “so that the score more closely aligns with the subjective assessment of the user”. The broadest reasonable interpretation of adjusting factor weights, (i.e. increasing or decreasing), so that the calculated score and the subjective score match, includes a mathematical function. As such, the claims recite a mathematical formula or relationship.
The claims, as illustrated by Claim 1, also recite limitations that encompass an abstract idea within the “mental processes” grouping – concepts performed in the human mind including observation, evaluation, judgment and opinion.
The claims recite receiving and adjusting physiological data associated with a user based on weights related to the user’s circadian rhythm, and calculating contributing factors associated with a score for the user based on the received and adjusted physiological data. Contributing factors are calculated, and a value for the score is calculated using a combination of weighted, score contributing factors. Receiving and analyzing data is an abstract mental process. (Electric Power Group.) The specification discloses that a score may be calculated including percentages, total counts of events, etc.. The broadest reasonable interpretation of “calculating” includes performing this calculation in the human mind, or with the aid of pen and paper. For example, one of ordinary skill can sum up the duration of time periods classified as “REM” sleep for a day either mentally, or with the aid of pen and paper. Calculating and recalculating a score by combining weighted values for relevant factors, is a process that, except for generic computer implementation steps, can be performed in the human mind. As such, the claims recite an abstract idea within the mental process grouping.
STEP 2A PRONG TWO
The claims recite limitations that include additional elements beyond those that encompass the abstract idea above including:
a user device;
a wearable device; wherein the wearable device comprises a plurality of photoplethysmography (PPG) sensors configured to measure arterial blood flow at different locations on a finger of the user;
inputting the additional physiological data and the modified circadian rhythm adjustment model into a machine learning classifier; weighting, by the machine learning classifier based at least in part on inputting the additional physiological data and the modified circadian rhythm adjustment model into the machine learning classifier;
displaying, by a graphical user interface, a prompt for the user to provide a subjective assessment by the user regarding a state or an experience of the user;
However, these additional elements do not integrate the abstract idea into a practical application of that idea in accordance with the MPEP. (see MPEP 2106.05)
The user device, wearable device and graphical user interface are recited at a high level of generality such that it amounts to no more than instructions to apply the abstract idea using a generic computer component. These elements merely add instructions to implement the abstract idea on a computer, and generally link the abstract idea to a particular technological environment. For example, the specification discloses that the user device and the wearable device are known in the art
With respect to weighting data using a classifier, the claims merely apply established methods of machine learning to an abstract scoring process in a new data environment – i.e. applying a model to the user’s physiological data and modified circadian rhythm. The specification teaches that the learning model may be configured to weight the data and output a classification using the physiological data; using a generic machine learning model (@ 0030, 0031). Machine learning limitations reciting broad, functionally described, well-known techniques executed by generic and conventional computing devices does not provide a practical application of the abstract diagnostic process. “Today we hold only that patents that do no more than claim the application of generic machine learning to new data environments, without disclosing improvements to the machine learning models to be applied, are patent ineligible under §101.” (Recentive Analytics, Inc. v. Fox Corp. (Fed. Cir. 2025)).
Receiving baseline and additional physiological data and a subjective assessment, in response to a prompt, are also insignificant extra-solution activities – i.e. a data gathering steps. Nothing in the claim recites specific limitations directed to an improved technology or technological process. Similarly, the specification is silent with respect to these kinds of improvements. A general purpose computer that applies a judicial exception by use of conventional computer functions, as is the case here, does not qualify as a particular machine, nor does the recitation of a generic computer impose meaningful limits in the claimed process. (see Ultramercial, Inc. v. Hulu, LLC, 772 F.3d 709, 716-17 (Fed. Cir. 2014)). As such, the additional elements recited in the claim do not integrate the abstract scoring process into a practical application of that process.
STEP 2B
The additional elements identified above do not amount to significantly more than the abstract scoring process. Receiving information and requesting information (i.e. displaying prompts), for example over a network, is a well-understood, routine and conventional computer function – i.e. receiving or transmitting data over a network as in Symantec, TLI, OIP and buySAFE.
The additional structural elements or combination of elements in the claims, other than the abstract idea per se, amount to no more than a recitation of generic computer structure (i.e. a processor, user device, wearable device, graphical user interface, and computer-readable medium). Each of the above components are disclosed in the specification as being purely conventional and/or known in the industry. Because the specification describes these additional elements in general terms, without describing particulars, Examiner concludes that the claim limitations may be broadly, but reasonably construed, as reciting well-understood, routine and conventional computer components and techniques. The specification describes the elements in a manner that indicates that they are sufficiently well-known that the specification does not need to describe the particulars in order to satisfy U.S.C. 112. Considered as an ordered combination the limitations recited in the claims add nothing that is not already present when the steps are considered individually. As such, the additional elements recited in the claim do not provide significantly more than the abstract scoring process, or an inventive concept.
The dependent claims add additional features including:
those that merely serve to further narrow the abstract idea above such as:
further limiting the state of the user to a particular type (Claim 3);
further limiting the type of score (Claim 4);
further limiting the type of wearable device (Claims 18);
those that recite additional abstract ideas such as:
determining that the user has awakened (Claim 5);
determining that a threshold time has elapsed (Claims 6, 8);
receiving updated input, recalculating the value, and displaying results (Claim 7);
calculating an initial value, the value is calculated based on the initial value and subjective assessment; (Claim 9);
increasing/decreasing the initial score by an amount based on the subjective assessment (Claim 11 - 14);
adjusting weights applied to a factor of the score based on determining correlations between factors and the subjective assessment (Claim 15, 16);
those that recite well-understood, routine and conventional activity or computer functions such as:
displaying results on a GUI (Claim 2);
displaying a prompt, a second prompt, (Claims 5, 6, 8, 10);
displaying recommendations, (Claim 17).
The limitations recited in the dependent claims, in combination with those recited in the independent claims add nothing that integrates the abstract idea into a practical application, or that amounts to significantly more. As such, the additional element do not integrate the abstract idea into a practical application, or provide an inventive concept that transforms the claims into a patent eligible invention.
The apparatus claims are no different from the method claims in substance. “The equivalence of the method, system and media claims is readily apparent.” “The only difference between the claims is the form in which they were drafted.” (Bancorp). The method claims recite the abstract idea implemented on a generic computer, while the apparatus claims recite generic computer components configured to implement the same idea. Specifically, Claims 19 and 20 merely add the generic hardware noted above that nearly every computer will include. The apparatus claim’s requirement that the same method be performed with a programmed computer does not alter the method’s patentability under U.S.C. 101 (In re Grams). Therefore, the claims are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
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.
Claims 1 – 11, 13 and 15 - 20 are rejected under 35 U.S.C. 103 as being unpatentable over Pho et al.: (US PGPUB 2021/0407684 A1) in view of Molony et al.: (US PGPUB 2023/0245780 A1) in view of Bordia et al.: (US PGPUB 2020/0366747).
Examiner notes that Pho et al. has a common assignee with the present application; however based on the earliest effective filing date, Pho qualifies as prior art under U.S.C. 102 (a)(1), and does not meet any of the exceptions.
CLAIMS 1, 19 and 20
Pho discloses an illness detection system that includes following limitations:
receiving baseline physiological data associated with a user, the baseline physiological data measured by a wearable device throughout a first time interval, wherein the wearable device comprises a plurality of photoplethysmography (PPG) sensors configured to measure arterial blood flow at different locations on a finger of the user; (Pho 0019, 0025 – 0027, 0038, 0042, 0059, 0060, 0085 - 0088, 0111);
modifying weights of a baseline circadian rhythm adjustment model based at least in part on the baseline physiological data associated with the user to generate a modified circadian rhythm adjustment model that is individualized for the user, the modified circadian rhythm adjustment model associated with a circadian rhythm of the user; (Pho 0025, 0042 – 0045).
Pho discloses a system and method for monitoring the sleeping patterns of a user at a user device, including a wearable device configured to collect physiological data from a user using a plurality of PPG sensors measuring blood flow at different locations of the user’s finger. Initially, baseline physiological data is collected and applied to a baseline circadian rhythm adjustment model to generate a modified circadian rhythm adjustment model that is tailored, individualized and specific to each respective user. The modified model is used to weight or adjust physiological data collect during sleep. Pho also discloses the following limitations:
receiving additional physiological data associated with the user, the additional physiological data measured by the wearable device during an additional time interval; inputting the additional physiological data and the modified circadian rhythm adjustment model into a machine learning classifier; weighting, by the machine learning classifier, the additional physiological data using the modified circadian rhythm adjustment model to generate weighted physiological data based at least in part on inputting the additional physiological data and the modified circadian rhythm adjustment model into the machine learning classifier; (Pho 0019, 0025 – 0028, 0042 – 0045);
calculating, based at least in part on the physiological data, a plurality of contributing factors associated with a score for the user, wherein a first contributing factor of the plurality of contributing factors is a quantity of rapid eye movement sleep; the quantity of rapid eye movement sleep determined based at least in part on one or more movements of the user, a heart rate of the user, a heart rate variability (HRV) of the user, a change in a temperature of the user, or any combination thereof; calculating a value for the score for the user based at least in part on the plurality of contributing factors and a plurality of weights; (Pho 0042, 0104 - 0109, 0128, 0137).
Pho receives additional physiological data over multiple time periods and weights the data using the modified circadian rhythm model and a machine learning model. The system determines factors that are contributing factors, including REM sleep and calculates a sleep score based on the factors.
With respect to the following limitations:
displaying, by a graphical user interface, a prompt for the user to provide a subjective assessment by the user regarding a state or an experience of the user; (Molony 0084, 0166, 0167, 0170);
receiving, based at least in part on displaying the prompt, input data from the user indicating the subjective assessment, the input data indicative of a range of values associated with the score for the user, the range of values corresponding to the state or the experience of the user; (Molony 0004, 0005, 0044, 0166 – 0170); and
adjusting a first weight of the plurality of weights based at least in part on the range of values indicated by the subjective assessment, the first weight corresponding to the first contributing factor; (Molony 0184, 0191, 0193 – 0195);
recalculating the value for the score for the user based at least in part on the adjusted first weight applied to the first contributing factor and based at least in part on the value for the score being outside of the range of values indicated by the subjective assessment; (Molony 0005, 0191).
Pho teaches receiving a subjective assessment, such as symptoms, but not a process for prompting a user to provide a subjective assessment, adjusting weights for score factors, and recalculating the score based on the adjusted weights. Molony teaches a health scoring system that receives physiological data associated with a sleep session (i.e. a time interval) using sensors of a wearable device, and generates component scores (i.e. scores for contributing factors) from the physiological data. Component scores includes sleep parameters associated with the user that are indicative of sleep states, including a REM sleep state. The component scores may be weights and used to calculate a total score for the user.
The user is prompted, on the GUI of a user device, to input a value for subjective feedback related to the sleep session, in response to a specific request. The subjective feedback includes information indicative of a self-reported subjective sleep score – i.e. a value for a perceived rating or measurement having a range of values. The physiological data and subjective feedback are used to calculate component scores for calculating a value for total health score based on their respective weights. Component scores and the total score displayed to the user on a GUI of a user device. Further, component scores may be updated repeatedly/periodically as subjective data is received, and thereby update the total score. Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing data of the claimed invention, to have modified the health scoring system of Pho so as to have included prompting for subjective feedback and adjusting an objective score using a self-reported score, in accordance with the teachings of Molony, in order to correlate a calculated score with a user-selected score.
The claims require calculating/recalculating, a value for a score based “at least in part on” contributing factors and weights/adjusted weights, allowing additional elements to be considered in the score. For example, the claims allow a score to be calculated based on weighted contributing factors including a subjective rating; then adjusting the score as new subjective rating data is received. Examiner asserts that Pho/Molony teaches this process.
Nonetheless, Examiner understands that the claims intend to recite a two-step process – i.e. first, to calculate a score without using any subjective feedback, and then, to adjust the weights/component score based on the feedback. In an effort to advance prosecution, Examiner offers Bordia et al.
Bordia discloses a system and method for the computation of a user experience score. A user experience score is calculated based on various objective factors related to a session. The calculation uses end-user feedback such that the score is strongly correlated with the feedback (@ 0005). Values for experience metrics are weighted and an aggregate score is computed from the scores and weights. (@ 0006) The score may be adjusted based on a “user-selected score”, and at least one weight of the plurality of weights is adjusted based on a difference between the user-selected score and the calculated score, and reported to the user. (@ 0008, 0120 - 0122). Although the scoring in Bordia is related to a user’s experience with a web-based application, the techniques in Bordia are equally applicable to adjusting a sleep score – i.e. a user experience sleeping. Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing data of the claimed invention, to have modified the health scoring system of Pho/Molony so as to have included a two-step scoring process based on adjusting an objective score using a self-reported score, in accordance with the teachings of Bordia, in order to correlate a calculated score with a user-selected score.
CLAIMS 2 - 4
The combination of Pho/Molony/Bordia discloses the limitations above relative to Claim 1. Additionally, Pho discloses the following limitations:
displaying, by the graphical user interface, the value for the score; (Pho 0043, 0117).
Pho displays the health score on a display of a user device.
wherein the state of the user comprises a physiological state of the user, a mental state of the user, or both; (Pho 0280).
Pho discloses physiological or mental health states.
wherein the score comprises a Sleep Score that indicates a quality of sleep for the user, comprises a Readiness Score that indicates a level of recovery for the user, or comprises a Stress Score that indicates stress level for the user; (Pho 0043, 0096, ).
Pho discloses sleep scores and readiness scores.
CLAIMS 15 - 17
The combination of Pho/Molony/Bordia discloses the limitations above relative to Claim 1. Additionally, Molony discloses the following limitations:
adjusting a weight applied to a factor of the score based at least in part on the input data indicative the subjective assessment; (Molony 0124, 0184, 0193 – 0195);
determining, based at least in part on the input data indicative of the subjective assessment, a correlation between the factor and the subjective assessment, wherein the weight applied to the factor is adjusted based at least in part on the determination; (Molony 0143, 0217);
displaying, by the graphical user interface, a recommendation for the user based at least in part on the correlation between the factor and the subjective assessment; (Molony 0090, 0224).
Molony teaches adjusting factor weights based on the input data including subjective data; determining correlations between factors and assessments; and displaying recommendations. Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing data of the claimed invention, to have modified the health scoring system of Pho so as to have included prompting for subjective feedback and adjusting an objective score using a self-reported score, in accordance with the teachings of Molony, in order to correlate a calculated score with a user-selected score.
CLAIM 18
The combination of Pho/Molony/Bordia discloses the limitations above relative to Claim 1. Additionally, Pho discloses the following limitations:
wherein the wearable device comprises a wearable ring device, and wherein the physiological data is collected from the user based on arterial blood flow; (Pho 0111).
Pho discloses blood flow sensors in a ring.
CLAIMS 5 and 8
The combination of Pho/Molony/Bordia discloses the limitations above relative to Claim 1. Additionally, Molony discloses the following limitations:
determining that the user has awakened from sleep; wherein the prompt is displayed based at least in part on the determination; (Molony 0097, 0166, 0167);
determining that a threshold amount of time has elapsed since the user has awakened from sleep, wherein the prompt is displayed based at least in part on the determination; (Molony 0097, 0163, 0166, 0167).
Molony discloses determining when the user awakens, and can determine a predetermined amount of time after the user awakens. Molony subsequently requests subjective assessment data. Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing data of the claimed invention, to have modified the health scoring system of Pho so as to have included prompting for subjective feedback based on a user awakening, in accordance with the teachings of Molony, in order to collect data while it is fresh in the mind.
CLAIMS 9 and 10
The combination of Pho/Molony/Bordia discloses the limitations above relative to Claim 1. Additionally, Molony discloses the following limitations:
calculating an initial value for the score based at least in part on the additional physiological data, wherein the value for the score is calculated based at least in part on the initial value and the input data from the user indicating the subjective assessment; (Molony 0005, 0191);
wherein the prompt is displayed based at least in part on calculating the initial value for the score; (Molony 0166, 0167).
Molony discloses updating an initial score based on the subjective assessment. Molony discloses prompting for subjective data based on an analysis of the physiological data. Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing data of the claimed invention, to have modified the health scoring system of Pho so as to have included updating an initial score based on subjective feedback, in accordance with the teachings of Molony, in order to correlate a calculated score with a user-selected score.
CLAIMS 11 and 13
The combination of Pho/Molony/Bordia discloses the limitations above relative to Claim 9. Additionally, Molony discloses the following limitations:
increasing the initial value by an amount that is based at least in part on the subjective assessment by the user; decreasing the initial value by an amount that is based at least in part on the subjective assessment by the user; (Molony 0194 – 0198).
Molony discloses increasing or decreasing an initial score based on the subjective input. Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing data of the claimed invention, to have modified the health scoring system of Pho so as to have included increasing or decreasing an initial score based on subjective feedback, in accordance with the teachings of Molony, in order to correlate a calculated score with a user-selected score.
CLAIMS 6 and 7
The combination of Pho/Molony/Bordia discloses the limitations above relative to Claim 5. Additionally, Molony discloses the following limitations:
determining that a threshold amount of time has elapsed since the user has awakened from sleep; (Molony 0097, 0163);
displaying, by the graphical user interface and based at least in part on determining that the threshold amount of time has elapsed, a second prompt for the user to provide an updated subjective assessment by the user; (Molony 0097, 0163, 0166, 0167);
receiving updated input data from the user indicating the updated subjective assessment; recalculating the value for the score based at least in part on the updated input data; and displaying, by the graphical user interface, the recalculated value for the score; (Molony 0005, 0191).
Molony discloses determining when the user awakens, and can determine a predetermined amount of time after the user awakens. Molony subsequently requests subjective assessment data. Additionally, Molony teaches repeatedly updating the score as physiological or subjective data is received. Molony does not expressly disclose a second prompt to update the input; nonetheless, it would be obvious to one of ordinary skill to prompt for updated input for repeated calculations in a similar manner to prompting for the initial subjective input. Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing data of the claimed invention, to have modified the health scoring system of Pho/Molony so as to have included prompting for input at each repetition of the calculation, and receive updated inputs based at least in part on displaying the second prompt, merely as a matter of design choice – i.e. a choice of when to prompt for input, in order to obtain updated results in a timely manner.
Claims 12 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Pho et al.: (US PGPUB 2021/0407684 A1) in view of Molony et al.: (US PGPUB 2023/0245780 A1) in view of Bordia et al.: (US PGPUB 2020/0366747) in view of Gonier et al.: (US PGPUB 2020/0193355 A1.
CLAIMS 12 and 14
The combination of Pho/Molony/Bordia discloses the limitations above relative to Claims 11 and 13. With respect to the following limitations:
determining, based at least in part on the input data indicating the subjective assessment of the user, that the initial value of the score is lower than indicated by the subjective assessment by the user, wherein the initial value is increased by the amount based at least in part on the determination; (Gonier 0003, 0008, 0024, 0031 – 0034);
determining, based at least in part on the input data indicating the subjective assessment of the user, that the initial value of the score is higher than indicated by the subjective assessment by the user, wherein the initial value is decreased by the amount based at least in part on the determination; (Gonier 0003, 0008, 0024, 0031 – 0034).
Pho/Molony teaches repeatedly adjusting the score as physiological or subjective data is received, and Bordia discloses adjusting weights responsive to a difference between the values. Pho/Molony/Bordia does not expressly disclose increasing (or decreasing) an initial value based on determining that the initial score is lower than (or higher than) indicated by the subjective assessment. The specification discloses that a range of scores may be indicated by a subjective assessment – i.e. a range of scores expected by the user. Gonier discloses a scoring system that repetitively collects and analyzes user data to provide objective metrics, or scores, about the user, using an algorithm or formula. The score may also be based on subjective ratings from the user, where the calculated score is increased or decreased depending on the particular formula and the subjective rating. Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing data of the claimed invention, to have modified the health scoring system of Pho/Molony so as to have included increasing the score when the user perceives it being too low; and decreasing the score when the user perceives the score a being too high, in accordance with the teachings of Gonier, in order to user feedback in updating health scores.
Response to Arguments
Applicant's arguments filed 20 January, 2026 have been fully considered but they are not persuasive.
The U.S.C. §101 Rejection
Applicant asserts that the claims do not recite a judicial exception, and recite features that integrate any exception into a practical application. In particular, Applicant correctly identifies the Office’s alleged abstract idea as being “within the mathematical formula or relationship grouping. However, Applicant then asserts that the claims contain limitation that cannot be performed mentally. Mathematical formula or relationships are not required to be performed mentally. Applicant’s argument does not apply to the mathematical formula or relationship grouping. While machine learning analysis may not be reasonably performed mentally, calculating a value for a score based on a plurality of factors and weights, adjusting weights, and recalculating the score can be performed mentally, or with the aid of pen and paper. These are simple additions and multiplications.
Examiner further asserts that modifying a circadian rhythm adjustment model can be performed mentally, especially given that the specification fails to disclose how this function is performed. The broadest interpretation of this step includes modifying weights of a baseline model based on user data. Examiner asserts that adjusting the weights for the data based on the modified model is a simple mathematical operation – applying the modified weight to the data - that can be performed mentally, especially given that the specification limits technical details as to how this function is performed to “adjusting by a machine learning classifier”, without any further explanation.
Applicant does not address Examiner’s rejection based on the claims being directed to a mathematical relationship.
The claims recite calculating a value for a score using weighted contributing factors, such as a quantity of REM Sleep. The quantity of Rem sleep is a summation of all of the time periods in a day where REM sleep state was determined. Examiner asserts that a human can add time periods of REM sleep mentally or with the aid of pen and paper.
Applicant asserts a practical application because the claims “improve the functioning of a “computational algorithm for health scores” by tailoring a circadian rhythm model to the user. However, improving an algorithm that is representative of an abstract idea “to provide accurate heath scores” does not improve the functioning of the processor; rather the improvement is to the abstract idea itself.
The U.S.C. §103 Rejection
Applicant asserts that Pho does not disclose features related to PPG sensors, or modifying weights of a baseline circadian rhythm adjustment model to generate an individualized model. Examiner disagrees. Pho, as shown above, teaches exactly those features.
CONCLUSION
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US PGPUB 2019/0380871 to Gutierrz discloses a system and method for determining a physiological state of a user, including weighting physiological characteristics of the user based on a circadian rhythm.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry of a general nature or relating to the status of this application or concerning this communication or earlier communications from the Examiner should be directed to John A. Pauls whose telephone number is (571) 270-5557. The Examiner can normally be reached on Mon. - Fri. 8:00 - 5:00 Eastern. If attempts to reach the examiner by telephone are unsuccessful, the Examiner’s supervisor, Robert Morgan can be reached at (571) 272-6773.
Official replies to this Office action may now be submitted electronically by registered users of the EFS-Web system. Information on EFS-Web tools is available on the Internet at: http://www.uspto.gov/patents/process/file/efs/guidance/index.jsp. An EFS-Web Quick-Start Guide is available at: http://www.uspto.gov/ebc/portal/efs/quick-start.pdf.
Alternatively, official replies to this Office action may still be submitted by any one of fax, mail, or hand delivery. Faxed replies should be directed to the central fax at (571) 273-8300. Mailed replies should be addressed to “Commissioner for Patents, PO Box 1450, Alexandria, VA 22313-1450.” Hand delivered replies should be delivered to the “Customer Service Window, Randolph Building, 401 Dulany Street, Alexandria, VA 22314.”
/JOHN A PAULS/Primary Examiner, Art Unit 3683
Date: 12 February, 2026