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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 8/25/2026 has been entered.
Notice of Pre-AIA or AIA Status
This action is in response to the RCE filed 8/25/2026.
Claims 1, 3, 11 were amended 8/25/2026.
Claims 1-6 and 11-13 are currently pending and have been examined.
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 1-6 and 11-13 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) without significantly more.
Claims 1-6 and 11-13 are drawn to a method and an apparatus which are statutory categories of invention (Step 1: YES).
Independent claims 1 and 11 recite: predicting an occurrence of a mood episode using a digital phenotype, comprising: acquir[ing] by a target user log data associated with a circadian rhythm of the target user and disease information about a mood disorder type of the target user; wherein the log data acquired comprises at least physical activity related information and biometric signal information of the target user measured by; extract[ing] predetermined main feature information from the log data, wherein the physical activity related information includes step count information and the biometric signal information includes heart rate information, and wherein extracting the predetermined main feature information comprises; extracting sleep information comprising a sleep length, a sleep efficiency, a deviation of sleep onset, and a deviation of sleep offset form the physical activity related information or light exposure information; extracting the step count information divided into cumulative step counts for each of a plurality of daily timeslots comprising a morning timeslot, an afternoon timeslot, an evening timeslot, and a bedtime timeslot; and fitting the heart rate information to a cosine curve to estimate daily circadian rhythm parameters of the target user, the daily circadian rhythm parameters comprising a circadian rhythm (CR) amplitude, a CR acrophase, a CR mesor, and a CR goodness of fit measuring an R-squared value of the heart rate information not the fitted cosine curve; and deduc[ing] prediction information about the occurrence of the mood episode of the target user by inputting the predetermined main feature information and the disease information about the mood disorder type.
The recited limitations, as drafted, under their broadest reasonable interpretation, cover certain methods of organizing human activity between a user and medical staff, as reflected in the specification, which states that “medical staff terminal 300 refers to a device held by a doctor of the user 1, medical staff, or guardian to acquire prediction information for the occurrence of the mood episode of the user from the predicting apparatus 100 to identify a state of the user. When the occurrence of a specific type of mood episode (for example, a major depressive episode (MDE), a manic episode (ME), or a hypomanic episode (HME)) is predicted, the medical staff terminal generates and transmits guide information including an appropriate action to be taken by the user 1 to the user terminal 220 and/or the wearable device 210.” (see: specification paragraph 40). If a claim limitation, under its broadest reasonable interpretation, covers managing personal behavior or relationships or interactions between people, then it falls within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas. The present claims cover certain methods of organizing human activity because they address “for example, the predicting apparatus 100 provides predetermined questionnaire items with contents associated with a mood episode occurrence to the user terminal 220 of each of the plurality of users at every predetermined examination period and may acquire an input applied to each user terminal 220 in response to the predetermined questionnaire items as answer data.” (see: specification paragraph 71). Accordingly, the claims recite an abstract idea(s) (Step 2A Prong One: YES).
Further, the recited limitations, as drafted, under the broadest reasonable interpretation, cover mathematical relationships by calculating parameters using statistical analysis. If a claim limitation, under its broadest reasonable interpretation, covers mathematical relationships or mathematical calculations, then it falls within the “Mathematical Concepts” grouping of abstract ideas. Accordingly, the claims recite an abstract idea (Step 2A Prong One: YES).
The judicial exception is not integrated into a practical application. The claims are abstract but for the inclusion of the additional elements including “at least one wearable device worn by a target user”, “at least one user terminal”, and “previously trained artificial intelligence-based prediction model”, “apparatus”, “communication network”, “log collecting unit”, “feature extracting unit”, “analyzing unit” are recited at a high level of generality (e.g., that the acquiring and inputting is performed using generic computer components and a generic artificial intelligence model with instructions are executed to perform the claimed limitations). Such that they amount to no more than mere instructions to apply the exception using generic computer components. See: MPEP 2106.05(f).
Hence, the 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. Accordingly, the claims are directed to an abstract idea (Step 2A Prong Two: NO).
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, using the additional elements to perform the abstract idea amounts to no more than mere instructions to apply the exception using generic components. Mere instructions to apply an exception using a generic component cannot provide an inventive concept. See MPEP 2106.05(f).
Further, the claimed additional elements, identified above, are not sufficient to amount to significantly more than the judicial exception because they are generic components that are configured to perform well-understood, routine, and conventional activities previously known to the industry. See MPEP 2106.05(d). Said additional elements are recited at a high level of generality and provide conventional functions that do not add meaningful limits to practicing the abstract idea. The originally filed specification supports this conclusion at Figure 1, Figures 4A-4C, Figure 6 and
Paragraph 39, where “For example, the wearable device 210 may be a smart watch or a smart band which is worn on the wrist of a user to collect biometric information of the user, but is not limited thereto. As another example, the wearable device 210 may broadly refer to a device which is worn on various positions to acquire feature information of the user 1, such as a head-worn device, a strap type device, a garment-type device, or shoe-worn/foot pods device. Further, for example, the wearable device 210 may be Fitbit, Jawbone Up, Nike+ FuelBand, Apple Watch, or Samsung Gear. Further, the wearable device 210 and the user terminal 220 may be interlinked based on the same account information for one user 1. Further, according to an implemented example of the present disclosure, it may be understood that the wearable device 210 is included in the user terminal 220 in a broad sense.”
Paragraph 41, where “For example, the user terminal 220 and/or the medical staff terminal 300 may include a smart phone, a smart pad, and a tablet PC, and terminals of all kinds of wireless communications such as personal communication system (PCS), global system for mobile communication (GSM), personal digital cellular (PDC), personal handy phone system (PHS), personal digital assistant (PDA), international mobile communication (IMT)-2000, code division multiple access (CDMA)-2000, W-code division multiple access (W-CDMA), and wireless broadband internet (Wibro).”
Paragraph 115, “The method for predicting an occurrence of a mood episode using a digital phenotype and the training method of an artificial intelligence-based prediction model for predicting a mood episode relapse using a digital phenotype according to the exemplary embodiment of the present disclosure are implemented in the form of a program instruction to be performed by various computer means to be recorded in a computer readable medium. The computer readable medium may include solely a program command, a data file, and a data structure or a combination thereof. The program instruction recorded in the medium may be specifically designed or constructed for the present disclosure or known to those skilled in the art of a computer software to be used. Examples of the computer readable recording medium include a magnetic media such as a hard disk, a floppy disk, or a magnetic tape, an optical media such as a CD-ROM or a DVD, a magneto-optical media such as a floptical disk, and a hardware device which is specifically configured to store and execute the program command such as a ROM, a RAM, and a flash memory. Examples of the program command include not only a machine language code which is created by a compiler but also a high level language code which may be executed by a computer using an interpreter. The hardware device may operate as one or more software modules in order to perform the operation of the present disclosure, and vice versa.”
Paragraph 37, where “Referring to FIG. 1, a digital health care system according to an exemplary embodiment of the present disclosure may include an apparatus 100 for predicting (hereinafter, referred to as a "predicting apparatus 100") an occurrence of a mood episode using a digital phenotype according to an exemplary embodiment of the present disclosure, a wearable device 210, a user terminal 220, and a medical staff terminal 300.”
Paragraph 38, where “the medical staff terminal 300 may communicate with each other by means of a network 20. The network 20 means a connection structure which allows information exchange between nodes such as terminals or servers. Examples of the network 20 include a 3rd generation partnership project (3GPP) network, a long term evolution (LTE) network, a 5G network, a world interoperability for microwave access (WIMAX) network, Internet, a local area network (LAN), a personal area network (PAN), a Wi-Fi network, a Bluetooth network, a satellite broadcasting network, an analog broadcasting network, and a digital multimedia broadcasting (DMB) network, but are not limited thereto.”
Paragraph 90, where “The log collecting unit 140 may acquire log data related to a circadian rhythm of the target user 1 from at least one of the user terminal 220 of the target user 1 and a wearable device 210 which is attached to or worn on a body of the target user 1. Further, the log collecting unit 140 may acquire user information including disease information about the mood disorder type of the target user 1.”
Paragraph 91, where “The feature extracting unit 150 may extract predetermined main feature information from the log data. Specifically, the feature extracting unit 150 may deduce main feature information which is set in advance so as to correspond to the disease information of the target user 1 from the log data.”
Paragraph 92, where “The analysis unit 160 may deduce prediction information about the mood episode occurrence of the target user 1 by inputting the extracted main feature information to a previously trained artificial intelligence-based prediction model. Specifically, the analysis unit 160 may calculate information about the occurrence possibility of at least one of the major depressive episode (MDE), the manic episode (ME), and the hypomanic episode (HME) of the target user 1 within a predetermined analysis period as prediction information.”
Viewing the limitations as an ordered combination, the claims simply instruct the additional elements to implement the concept described above in the identification of abstract idea with route, conventional activity specified at a high level of generality in a particular technological environment.
Hence, the claims as a whole, considering the additional elements individually and as an ordered combination, do not amount to significantly more than the abstract idea (Step 2B: NO).
Dependent claims 2-6, 12-13 when analyzed as a whole, considering the additional elements individually and/or as an ordered combination, are held to be patent ineligible under 35 U.S.C. 101 because the additional recited limitations fail to establish that the claims are directed to an abstract idea without significantly more. Claim 2, 4, 6 and 12 recite deducing and including healthcare data on the generically recited computing components and generically recited artificial intelligence model as shown in the parent claims above.
Claims 3 and 13 further recite “a target prediction model” and “a plurality of previously trained prediction models” which is recited at a high level of generality (e.g., that the associating and correlating are performed using generic computer components with instructions are executed to perform the claimed limitations) as shown in the specification paragraphs 50 and 21. Such that they amount to no more than mere instructions to apply the exception using generic computer components. See: MPEP 2106.05(f).
Claim 4 further recites “the target predication model” which is recited at a high level of generality (e.g., that the associating and correlating are performed using generic computer components with instructions are executed to perform the claimed limitations) as shown in the specification paragraph 50. Such that they amount to no more than mere instructions to apply the exception using generic computer components. See: MPEP 2106.05(f).
These claims fail to remedy the deficiencies of their parent claims above, and therefore rejected for at least the same rationale as applied to their parent claims above, and incorporated herein.
Response to Arguments
The arguments filed 8/25/2026 have been fully considered.
Regarding the arguments pertaining to the 101 rejection are not persuasive. Applicant argues that the claimed invention provides a highly advanced, automated, and non-invasive clinical predictive system that utilizes a target user’s “digital phenotype” to model and predict the occurrence of imminent mood episodes and as an improvement by analyzing objective continuous biometric and behavioral data associated with the user’s circadian rhythm. However, this is an improvement to the medical field of analyzing a user by medical staff as shown in the specification and does not create an improvement to technology. The “medical field” is not necessarily a “technical field”, nor is a treatment effected. Classen is an example of adding a meaningful limitation to the claims that create a practical application, however Classen integrated the results of the analysis into a specific and tangible method that resulted in the method “moving from abstract scientific principle to specific application” (Classen Immunotherapies Inc. v. Biogen IDEC). The current claimed limitations fail to provide this practical application.
Applicant further argues that the claimed invention recites a specific, integrated combination of hardware data collection, mathematical and behavioral signal processing and dynamic AI model selection. Examiner respectfully disagrees. The functions argued are representative of the abstract idea. The claims here are not directed to a specific improvement to computer functionality that amount to a practical application. Rather, they are directed to the use of conventional or generic technology in a well-known environment, without any claim that the invention reflects an inventive solution to a technical problem presented by combining the two. In the present case, the claims fail to recite any elements that individually or as an ordered combination transform the identified abstract idea(s) in the rejection into a patent-eligible application of that idea.
Further, not every claim that recites concrete, tangible components escapes the reach of the abstract-idea inquiry. (See, e.g., Alice, 134). It is well-settled that mere recitation of concrete, tangible components that are generic is insufficient to confer patent eligibility to an otherwise abstract idea. In order to amount to an inventive concept, the components must involve more than performance of “’well-understood, routine, conventional activities’ previously known to the industry.” (Alice, 134 S. Ct. at 2359 (quoting Mayo, 132 S.Ct. at 1294)). The originally filed specification was investigated and found to support this conclusion as the technology recited is generic and does not show an improvement to technology.
Applicant further argues that the independent claims do not recite an abstract idea because the claim limitations do not explicitly recite “medical staff” and that it doesn’t apply under broadest reasonable interpretation. Examiner respectfully disagrees. The claimed invention, under broadest reasonable interpretation, is directed towards Certain Methods of Organizing Human Activity as the claimed invention as shown in the specification is directed towards a user interacting with medical staff through the generic computer components claimed. The claimed invention is directed towards a user interacting with medical staff to determine mood disorder type falls under an abstract idea. Further, the mathematical calculations are statistical processes implemented on the input/output of data using the generic computer components as recited above and are directed towards Mathematical Concepts.
Applicant further argues that the claims improve the functioning of a computer or other technology or technological field and is similar to Diamond v Diehr, Enfish, and McRo. Applicant further argues that the claim amendments provide significantly more to the technical field as the combination of features which improve upon the well-understood, routine, conventional bio-measurement technology. Examiner respectfully disagrees. The functions argued are representative of the abstract idea and the addition of mathematical calculations of data are implementations on the data itself rather than on a specific functionality of technology of the computing device.
Applicant further argues that due to the 103 rejection being overcome, the 101 rejection should be withdrawn. Applicant further argues that a reference must be cited in accordance with Berkheimer, which establishes evidentiary standards for Step 2B only with regard as to what is well-understood, routine, and conventional as per MPEP 2106.05(d). The first criteria set forth in the Berkheimer memo is a “citation to an express statement in the specification or to a statement made by an applicant during prosecution that demonstrates the well-understood, routine, conventional nature of the additional element(s)…” As shown in the 101 rejection as written above, the specification is cited in Figures 1, 4A-4C, 6 and their associated citations in the body of the specification as having computer elements that are well-understood, routine, and conventional without significantly more than the abstract idea.
The dependent claims rely on the arguments of the independent claims and are rejected upon the same reasons as the independent claims above.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KIMBERLY A SASS whose telephone number is (571)272-4774. The examiner can normally be reached 7AM-5PM (EST).
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, JASON DUNHAM can be reached at 571-272-8109. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/KIMBERLY A. SASS/Examiner, Art Unit 3686
Prosecution Insights