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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 05/26/2026 has been entered.
Claims 1-20 remain pending in this application.
Specification
New Matter
The amendment filed 05/26/2026 is objected to under 35 U.S.C. 132(a) because it introduces new matter into the disclosure. 35 U.S.C. 132(a) states that no amendment shall introduce new matter into the disclosure of the invention. The added material which is not supported by the original disclosure is as follows: “transforming, by the at least one processor, the first series of biosignal data and the first series of motion data into a first series of psychophysiological markers by segmenting the time-series physiological signals into a plurality of temporal segments; and for each temporal segment, extracting a plurality of signal features from the biosignal data to generate a psychophysiological marker representing an emotional state of the first user during the temporal segment;” and “wherein the calculating of the first time associated with the risk comprises inputting the extracted plurality of signal features of the psychophysiological markers into the depression model” within claims 1, 13 and 19.
Applicant is required to cancel the new matter in the reply to this Office Action.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-20 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
The amended claims recite “transforming, by the at least one processor, the first series of biosignal data and the first series of motion data into a first series of psychophysiological markers by segmenting the time-series physiological signals into a plurality of temporal segments; and for each temporal segment, extracting a plurality of signal features from the biosignal data to generate a psychophysiological marker representing an emotional state of the first user during the temporal segment;” and “wherein the calculating of the first time associated with the risk comprises inputting the extracted plurality of signal features of the psychophysiological markers into the depression model”, which is not described in the Applicant's specification. The specification recites “In one variation, the computer system can: transform the set of biosignal data into a set of psychophysiological markers, the set of psychophysiological markers representing emotions exhibited by the user in the population of users.” In [0044], however, there in no recitation of “segmenting the time-series physiological signals into a plurality of temporal segments”, “for each temporal segment, extracting a plurality of signal features from the biosignal data to generate a psychophysiological marker representing an emotional state of the first user during the temporal segment” and “the calculating of the first time associated with the risk comprises inputting the extracted plurality of signal features of the psychophysiological markers into the depression model”.
Independent claims 1, 13 and 19 recite limitations that are new matter, as discussed above.
Claims 2-12, 14-18, and 20 incorporate the deficiencies of independent claims 1, 13 and 19, through dependency, and are also rejected.
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.
Step 1:
Claims 1-20 are drawn to a method which is within the four statutory categories (i.e. process).
Step 2A, Prong 1:
The independent claims have been amended to recite “during a first time period: for each user in a population of users: accessing, by at least one processor of a computer system associated with the user, clinical assessment for depression in the user; accessing, by the at least one processor, a first set of biosignal data, of the user, preceding the clinical assessment for depression; accessing, by the at least one processor, a first set of motion data, of the user, preceding the clinical assessment for depression; transforming, by the at least one processor, the first set of biosignal data into a first set of psychophysiological markers, the first set of psychophysiological markers comprising emotions exhibited by the user; and deriving, by the at least one processor, a set of correlations between: the first set of psychophysiological markers and the clinical assessment for depression; and the first set of motion data and the clinical assessment for depression; and compiling, by the at least one processor, sets of correlations, derived for the population of users, into a depression model including a trained machine learning or artificial intelligence process configured to predict risk of future depression diagnosis based on historical psychophysiological markers and historical motion data; and during a second time period: accessing, by the at least one processor, a first series of biosignal data collected by a wearable device worn by a first user and communicatively coupled with the computer system; accessing, by the at least one processor, a first series of motion data of the first user; transforming, by the at least one processor, the first series of biosignal data into a first series of psychophysiological markers; accessing, by the at least one processor, a target time window; prior to presentation of a set of depression symptoms by the first user, calculating, by the at least one processor, a first risk score representing presentation of the set of depression symptoms by the first user within the target time window based on the first series of psychophysiological markers, the first series of motion data, and the depression model; in response to the first risk score exceeding a threshold risk, populating, by the at least one processor, a notification with: the first risk score; and a prompt to investigate the first user for prescription of a first dose of an pharmacological medication; and serving, by the at least one processor, the notification to a care provider associated with the first user”-claim 1, “…accessing, by the at least one processor, a risk threshold; prior to presentation of a set of depression symptoms by the first user: calculating, by the at least one processor, a first time associated with a risk of presentation of the set of depression symptoms by the first user based on the first series of psychophysiological markers and the depression model, the risk exceeding the risk threshold; and calculating, by the at least one processor, a first time duration between the first time and a current time; and in response to the first time duration falling below a threshold duration: populating, by the at least one processor, a notification with: the first time duration; and a prompt to investigate the first user for prescription of a first dose of an pharmacological medication;…”-claim 13, and claim 19 recites similar limitations.
These limitations correspond to an abstract idea of “certain methods of organizing human activity” with a recitation of generic processor. This is a method of managing interactions between people, such as user following rules and instructions. The mere nominal recitation of a generic processor, wearable device and a computing device does not take the claims out of the methods of organizing human interactions grouping. Thus, the claims recite an abstract idea.
The dependent claims also recite limitations that are directed to “certain methods of organizing human activities”, thus an abstract idea. The limitations corresponding to the abstract idea, such as user following rules and instructions are:
“Claim 2: “during the first time period: for each user in the population of users: accessing, by the at least one processor, a set of self-assessments of depression symptoms generated by the user; and extracting, by the at least one processor, a series of depression symptom severities from the set of self-assessments; wherein deriving the set of correlations comprises deriving, by the at least one processor, the set of correlations further between: the first set of psychophysiological markers and the series of depression symptom severities; and the first set of motion data and the series of depression symptom severities;…generating, by the at least one processor, the depression model configured to predict risk of future depression diagnosis and future depression symptom severity based on historical psychophysiological markers and historical motion data; further comprising accessing, by the at least one processor, a threshold depression symptom severity; and wherein calculating the first risk score comprises: prior to presentation of depression symptom severity, greater than the threshold depression symptom severity, by the first user: calculating, by the at least one processor, the first risk score representing presentation of the set of depression symptoms, approximating the threshold depression symptom severity, by the first user within the target time window”,
Claim 3: “wherein accessing a first set of biosignal data for each user in the population of users comprises: accessing, by the at least one processor, a first subset of biosignals of a user”,
Claim 4: “for each user in the population of users: accessing, by the at least one processor, a first set of text communications generated by the user; and extracting, by the at least one processor, a first set of language signals from the first set of text communications; wherein deriving the set of correlations comprises deriving, by the at least one processor, the set of correlations further between: the first set of language signals and the clinical assessment for depression; and further comprising, during the second time period: accessing, by the at least one processor, a first series of text communications generated by the first user; and extracting, by the at least one processor, a first series set of language signals from the first set of text communications; and wherein calculating the first risk score comprises calculating, by the at least one processor, the first risk score further based on the first series set of language signals”,
Claim 7: “accessing, by the at least one processor, an initial set of psychophysiological markers derived from a series of health evaluations executed by the care provider for the first user and representative of a set of health indicators for the first user; generating, by the at least one processor, a second emotion model linking biosignals to psychophysiological markers for the first user based on the initial set of biosignal data and the initial set of psychophysical markers”,
Claim 12: “wherein accessing the target time window comprises: setting the target time window based on: historic responsiveness of the first user to the pharmacological medication; and anticipated effective period of the first dose of the pharmacological medication”,
Claim 14: “during the first time period: for each user in the population of users: accessing, by the at least one processor, a set of self-assessments of depression symptoms generated by the user; and extracting, by the at least one processor, a series of depression symptom severities from the set of self-assessments; wherein deriving the set of correlations comprises deriving, by the at least one processor, the set of correlations further between the first set of psychophysiological markers and the series of depression symptom severities;…generating, by the at least one processor, the depression model configured to predict risk of future depression diagnosis and future depression symptom severity based on set of psychophysical markers; further comprising accessing, by the at least one processor, a threshold depression symptom severity; and wherein calculating the first time duration comprises: prior to presentation of depression symptom severity, greater than the threshold depression symptom severity, by the first user: calculating, by the at least one processor, the first time duration associated with risk of presentation of the set of depression symptoms, approximating the threshold depression symptom severity, by the first user within the first time duration”,
Claim 16: "further comprising: accessing, by the at least one processor, a first medical record of the first user, the first medical record specifying non-clinically significant depressive anxiety symptoms of the first user",
Claim 17: “further comprising accessing, by the at least one processor, a first medical record of the first user, the first medical record specifying: a chronic depression diagnosis of the first user; and a current dose of the pharmacological medication prescribed to the first user”
Claim 18: “wherein calculating the first time duration comprises calculating, by the at least one processor, the first time associated with the risk of presentation of the set of depression symptoms by the first user exceeding the risk threshold, the set of depression symptoms: indiscernible to a nominal practicing physician during the first time duration; and visible to the nominal practicing physician after the first time”,
Claim 20: " further comprising: during the first time period: for each user in the population of users: accessing, by the at least one processor, a set of self-assessments of depression symptoms generated by the user; and extracting, by the at least one processor, a series of depression symptom severities from the set of self-assessments; wherein deriving the set of correlations comprises deriving, by the at least one processor, the set of correlations further between: the first set of biosignal data, the first set of motion data and the series of depression symptom severities”.
These limitations correspond to “certain methods of organizing human activity” (method of managing interactions between people, such as user following rules and instructions) with a recitation of generic computing devices, such at least one processor, a wearable device worn by a first user and a computing/mobile device carried by the first user. These devices are described in the current specification as generic computing devices (current specification; [0017]).
Claim have been amended to recite “compiling, by the at least one processor, sets of correlations, derived for the population of users, into a depression model including a trained machine learning or artificial intelligence process configured to predict risk of future depression diagnosis based on historical psychophysiological markers and historical motion data” in claims 1, 13, 19, “generating, by the at least one processor, an emotion model including a trained machine learning or artificial intelligence process linking biosignals to psychophysiological markers for the first user based on the emotion- labeled set of biosignal data” and “predicting risk of future depression diagnosis using a trained machine learning model” and “segmenting the time-series physiological signals into a plurality of temporal segments; and for each temporal segment, extracting a plurality of signal features from the biosignal data to generate a psychophysiological marker representing an emotional state of the first user during the temporal segment;” and “wherein the calculating of the first time associated with the risk comprises inputting the extracted plurality of signal features of the psychophysiological markers into the depression model” correspond to mathematical relationships, which falls within the “mathematical concepts” grouping of abstract ideas. The current specification recites “Then, the computer system can train a depression model (e.g., transformer deep neural network) to identify correlations (e.g., patterns) between user data - including the set of physiological biosignal data, the set of motion data, and the set of communication data - and the set of clinical evaluations. Therefore, the computer system can train the depression model to identify patterns in the user data that are correlated with clinical evaluations, which are indicative of the severity and quantity of depression symptoms exhibited by the user and observed by the care provider.” in [0023].
After considering all claim elements, both individually and in combination and in ordered combination, it has been determined that the claims do not amount to significantly more than the abstract idea itself.
Claims 2-12, 14-18 and 20 are ultimately dependent from claims 1, 13, 19 and include all the limitations of claims 1, 13, 19. Therefore, claims 2-12, 14-18 and 20 recite the same abstract idea. Claims 2-12, 14-18 and 20 describe a further limitation regarding the basis for determining the risk score for the user based on the collected data and the depression model. These are all just further describing the abstract idea recited in claims 1, 13, 19, without adding significantly more.
Step 2A, Prong 2:
This judicial exception is not integrated into a practical application. In particular, claims recite the additional elements of: “at least one processor”, using the at least one processor to perform the accessing, transforming, deriving, compiling, converting, calculating, prompting, extracting, recording, labeling, generating, encrypting, setting, populating and serving steps.
These additional elements are directed to hardware and software elements, these limitations are not enough to qualify as “practical application” being recited in the claims along with the abstract idea since these elements are merely invoked as a tool to apply instructions of the abstract idea in a particular technological environment, and mere instructions to apply/implement/automate an abstract idea in a particular technological environment and merely limiting the use of an abstract idea to a particular field or technological environment do not provide practical application for an abstract idea (MPEP 2106.05(f) & (h)). The additional elements amount no more than mere instructions to apply the exception using a generic computer component (the at least one processor).
Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea.
Step 2B:
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a computing device to perform accessing, transforming, compiling, calculating and serving notifications steps amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept.
The claims are not patent eligible.
Response to Arguments
Applicant's arguments filed 05/26/2026 have been fully considered but they are not persuasive. Applicant’s arguments will be addressed below in the order in which they appear.
Applicant argues that claim 1 does not recite an abstract idea, since claim 1 is specifically directed to and rooted in technology used to improve a computer’s ability to interpret and utilize wearable sensor data by converting unprocessed physiological measurements, which are directly usable for predictive modeling, into intermediate feature-based, machine-interpretable representations that enable downstream computation.
In response, Examiner submits that the current specification recites and mentions “converting data” in one section, which is: “In one implementation, the computer system can: access a first subset of biosignals of a user; convert the first subset of biosignals of the user into a first emotion; in response to the first emotion of the user comprising a target emotion, prompt the user to supply a first current personal depression symptom severity; and store the first current personal depression symptom severity in a first self-assessment in the set of self- assessments. Then, the computer system can: extract a first depression symptom severity, in the series of depression symptom severities, from the first self-assessment. Therefore, the computer system can prompt the user in the population of users to respond to a questionnaire (e.g., PHQ-9) of depression symptom severity in response to detecting the first emotion (e.g., sadness) based on the subset of biosignal.” in [0055].
The current specification also recites : “In one implementation, as described in U.S. Patent Application No. 16/460,105, during an initial time period preceding the second time period, the computer system can: prompt the first user to orally recite a story associated with a first target emotion (e.g., sadness); record a voice recording of the first user reciting the story; record an initial set of biosignal data via the wearable device worn by the first user; extract an initial set of psychophysiological markers from the voice recording, the initial set of psychophysiological markers including a first emotion marker for a first instance of the first target emotion exhibited by the first user during the first time period; label the initial set of biosignal data according to the initial set of psychophysiological markers to generate an emotion-labeled set of biosignal data; and generate a first emotion model linking biosignals to psychophysiological markers for the first user based on the emotion-labeled set of biosignal data. In particular, the computer system can: extract a series of pitch, voice speed, voice volume, tone, and/or other characteristics of voice of the first user from the voice recording; and transform this series into timestamped instances (and magnitudes) of the target emotion exhibited by the first user while reciting the story. The remote computer system can then: synchronize the series of biosignal data and series of instances of the target emotion; and implement machine learning, and/or other techniques to derive the first emotion model. Therefore, the computer system can generate the first emotion model configured to transform the series of biosignal data into the series of psychophysiological markers, the series of psychophysiological markers representing instances of the first target emotion (e.g., sadness) experienced by the first user. In this implementation, the computer system can transform the series of biosignal data into the series of psychophysiological markers based on the first emotion model.” in [0062].
Therefore, the limitations of “converting, by the at least one processor, the first subset of biosignals of the user into a first emotion” and “generating, by the at least one processor, the depression model configured to predict risk of future depression diagnosis and future depression symptom severity based on historical psychophysiological markers and historical motion data” correspond to mere instructions to apply the exception using a generic computer component.
Applicant argues that claim 1 recites significantly more than the alleged abstract idea, since claim 1 recites additional elements that recite an ordered combination of technical signal-processing steps, and that goes beyond generic data analysis.
In response, Examiner submits that, as indicated in the section above, neither the current claims nor the current specification recites any improvement in the technology. The current claims and the current specification recites “transforming, by the ate least one processor, the first set of biosignal data into a first set of psychophysiological markers” and “Generally, Block S116 of the method S1oo recites: transforming the set of biosignal data into a set of psychophysiological markers, the set of psychophysiological markers representing metrics associated with mental health of the user in the population of users. Generally, in Block S116, the computer system can transform the set of biosignal data, such as heart rate variability data, skin temperature data, and/or respiratory rate data, into the set of psychophysiological markers representing various metrics indicative of the mental health of the user, such as instances of target emotion (e.g., sadness), sleep quality, social activity level, psychomotor activity level.”. There is no indication of a technological improvement neither in the claims nor in the current specification.
Therefore, Applicant’s arguments are not persuasive and claims are rejected under 35 U.S.C. §101 as being directed to non-statutory subject matter.
Conclusion
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/DILEK B COBANOGLU/Primary Examiner, Art Unit 3687
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