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 .
Notice to Applicant
Claims 1-14 are pending and have been examined.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on February 4, 2025 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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 1-14 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.
Subject Matter Eligibility Criteria – Step 1:
The claims recite subject matter within a statutory category as a process and a machine (1-14). Accordingly, claims 1-14 are all within at least one of the four statutory categories.
Subject Matter Eligibility Criteria – Step 2A – Prong One:
Regarding Prong One of Step 2A of the Alice/Mayo test, the claim limitations are to be analyzed to determine whether, under their broadest reasonable interpretation they “recite” a judicial exception or in other words whether a judicial exception is “set forth” or “described” in the claims. MPEP §2106.04(II)(A)(1). An “abstract idea” judicial exception is subject matter that falls within at least one of the following groupings: a) certain methods of organizing human activity, b) mental processes, and /or c) mathematical concepts. MPEP §2106.04(a).
The Examiner has identified method Claim 1 as the claim that represents the claimed invention for analysis, and is similar to product claim 14.
Claim 1:
A method of implementing an application for maintaining a cognitive function and improving a decline in the cognitive function, the method comprising:
controlling a first training algorithm to be output to a user terminal in response to an input into the user terminal;
in a case where the first training algorithm is terminated, controlling a second training algorithm to be output to the user terminal;
in a case where the second training algorithm is terminated, evaluating user inputs into the first training algorithm and the second training algorithm; and
on the basis of a result of the evaluation, controlling a first visual display to be output to the user terminal.
These above limitations, not in bold, under their broadest reasonable interpretation, cover performance of the limitation as certain methods of organizing human activity. The claim elements are directed towards “controlling a first training algorithm to be output”, “in a case where the first training algorithm is terminated, controlling a second training algorithm to be output”, and “evaluating user inputs into the first training algorithm and the second training algorithm”. Providing/outputting training algorithms or cognitive exercises is a human activity typically performed by cognitive therapists or behavioural neurologists for their patients. It is important to note that the examples provided by the MPEP such as social activities, teaching, and following rules or instructions are provided as examples and not an exclusive listing and that MPEP 2106.04(a)(2)II states certain activity between a person and a computer may fall within the “certain methods of organizing human activity” grouping.
Accordingly, the claim recites an abstract idea.
Claim 14 is abstract for similar reasons.
Subject Matter Eligibility Criteria – Step 2A – Prong Two:
Regarding Prong Two of Step 2A of the Alice/Mayo test, it must be determined whether the claim as a whole integrates the idea into a practical application. As noted at MPEP §2106.04 (ID)(A)(2), it must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.” MPEP §2106.05(I)(A).
Additional Elements Cited in the claims:
Application (1,14); user terminal (1,4,7,8,10-11,14); first visual display (1,14); non-transitory computer-readable storage device (13); computer program (13); apparatus (14); first output controller (14); second output controller (14); training evaluation unit (14)
Any computing devices (user terminal, apparatus) and their associated components (non-transitory computer-readable storage device, computer program, application, first output controller, second output controller, training evaluation unit) that would be able to perform the method are taught at a high level of generality such that the claim elements amount's to no more than mere instructions to apply the exception using any generic component capable of performing the claim limitations. Pg. 14 of Applicant specification recites: “Referring to FIG. 3, the user terminal 110-1 is illustrated in the form of a smartphone, but the user terminal 110-1 when the present disclosure is implemented is not limited to the smartphone, and may include all of an apparatus installed at a fixed location such as a general personal computer (PC) and a portable terminal such as a tablet personal computer (PC) or a netbook.” Pg. 51 further recites: “The embodiments of the present disclosure described above may be implemented in the form of a computer program that may be executed through various components on a computer, and the computer program may be recorded on a computer-readable medium. Here, the medium may include magnetic media such as a hard disk, a floppy disk, and a magnetic tape, optical recording media such as CD-ROM and DVD, a magneto-optical medium such as a floptical disk, and a hardware device particularly configured to store and execute program instructions, such as ROM, RAM, and flash memory.” No specific, technical improvements are being made to the technology of computing devices as generic devices are applied to perform the abstract idea of providing mental exercises to a patient and evaluating patient state.
Visual displays are also taught at a high level of generality. Pg. 19 recites: “The visual display controller 257 may control a first visual display to be output to the user terminal 110-1, on the basis of the result evaluated by the training evaluation unit 255. Here, the first visual display may be output through a display of the user terminal 110-1, and visual effects (a color, a shape, a pattern, a sparkle, and the like) of the first visual display may vary according to training fidelity and training performance for a training algorithm performed by the user. As an example, the first visual display may be a flower of memory.” No specific, technical improvements are being made to the technology of display devices as they are only applied to perform an insignificant extra-solution activity of outputting data for display
Looking at the additional elements as an ordered combination adds nothing that is not already present when looking at the elements taken individually. For instance, there is no indication that the additional elements, when considered as a whole with the limitations reciting the at least one abstract idea, reflect an improvement in the functioning of a computer or an improvement to another technology or technical field, apply or use the above-noted judicial exception with a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing, or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole does not integrate the abstract idea into a practical application of the abstract idea. MPEP §2106.05(I)(A) and §2106.04(IID)(A)(2).
The remaining dependent claim limitations not addressed above fail to integrate the abstract idea into a practical application as set forth below:
Claim 2: This claim recites wherein the first training algorithm comprises a fixed first number of detailed training algorithms; which only serves to further limit the first training exercise.
Claim 3: This claim recites wherein the first training algorithm comprises a detailed training algorithm for a focusing functional area; which only serves to further limit the first training exercise.
Claim 4: This claim recites wherein the detailed training algorithm for the focusing functional area comprises an algorithm configured to receive and evaluate speech of a user using the user terminal; which only serves to further limit the type of training exercise.
Claim 5: This claim recites wherein the detailed training algorithm for the focusing functional areas comprises: providing a guidance message to a user through the user terminal; and receiving speech of the user having at least one of a pitch and a speed changed according to the guidance message, comparing the speech of the user with a stored value, and evaluating the speech of the user; which teaches an abstract idea of certain methods of organizing human activity by guiding a user to perform a task and evaluating the speech of the user, which is a human activity typically performed by speech pathologists for their patients. This claim further serves to limit the type of training exercise.
Claim 6: This claim recites wherein the first training algorithm comprises a detailed training algorithm for a visualization functional area; which only serves to further limit the type of training exercise.
Claim 7: This claim recites wherein the detailed training algorithm for the visualization functional area comprises an algorithm configured to receive speech of a user using the user terminal and evaluate a number of syllables of a word included in the speech; which only serves to further limit the type of training exercise.
Claim 8: This claim recites; wherein the detailed training algorithm for the visualization functional area comprises: providing a guidance message to a user through the user terminal; and receiving speech of the user for a certain period of time in response to the guidance message, detecting a number of syllables, comparing the detected number of syllables with a preset value, and evaluating the speech of the user; which teaches an abstract idea of certain methods of organizing human activity by guiding a user to perform a task and evaluating the speech of the user, which is a human activity typically performed by speech pathologists for their patients. This claim further serves to limit the type of training exercise.
Claim 9: This claim recites wherein the first training algorithm comprises a detailed training algorithm for a fusion functional area; which only serves to further limit the type of training exercise.
Claim 10: This claim recites wherein the detailed training algorithm for the fusion functional area comprises an algorithm configured to receive a story created by the user using the user terminal and determine whether or not the story meets a condition; which only serves to further limit the type of training exercise.
Claim 11: This claim recites wherein the detailed training algorithm for the fusion functional area comprises: providing a story creation condition to the user through the user terminal; and in a case where the story created by the user is received, determining whether or not the story is a story corresponding to a number of words and emotional modifiers included in the story creation condition; which teaches an abstract idea of certain methods of organizing human activity by instructing a user of conditions for creating story and evaluating the story of the user, which is a human activity typically performed by speech pathologists for their patients. This claim further serves to limit the type of training exercise.
Claim 12: This claim recites wherein the first training algorithm comprises at least two of detailed training algorithms for focusing, visualization, and fusion functional areas; which only serves to further limit the types of training exercises.
Claim 13: This claim recites a non-transitory computer-readable storage device storing a computer program for executing the method of claim 1; which teaches a non-transitory computer-readable storage device at a high level of generality, such that no specific, technical improvements are made to storage device technologies.
Subject Matter Eligibility Criteria – Step 2B:
Regarding Step 2B of the Alice/Mayo test, representative independent claims do not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for reasons the same as those discussed above with respect to determining that the claim does not integrate the abstract idea into a practical application.
These claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to discussion of integration of the abstract idea into a practical application, the additional elements amount to no more than mere instructions to apply an exception, add insignificant extra-solution activity to the abstract idea, and generally link the abstract idea to a particular technological environment or field use. Additionally, the additional limitations, other than the abstract idea per se, amount to no more than limitations which:
Amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields (such as determining the wellness categories of a person based on tested blood, e.g., storing and retrieving information in memory, Versata Dev. Group, MPEP §2106.05(d)(II)(iv); providing a credit offset for the deductible, e.g., performing repetitive calculations, Flook, MPEP §2106.05(d)(II)(ii).
Dependent claims recite additional subject matter which, as discussed above with respect to integration of the abstract idea into a practical application, amount to invoking computers as a tool to perform the abstract idea. Dependent claims recite additional subject matter which amount to limitations consistent additional subject matter which amount to limitations consistent with the additional elements in the independent claims (such as claims 2-13, additional limitations which amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields, claims 2-13, e.g., performing repetitive calculations, Flook, MPEP §2106.05(d)(II)(ii); claims 2-13, e.g., storing and retrieving information in memory, Versata Dev. Group, MPEP §2106.05(d)(II)(iv). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation.
Therefore, whether taken individually or as an ordered combination, claims 1-14 are nonetheless rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Kim (US 11759145).
Regarding claim 1, Kim teaches a method of implementing an application for maintaining a cognitive function and improving a decline in the cognitive function, the method comprising:
[Examiner notes that the intended use of “for maintaining a cognitive function and improving a decline in the cognitive” carries no significance to claim construction; see MPEP 2111.02 II]
controlling a first training algorithm to be output to a user terminal in response to an input into the user terminal (col. 14, lines 17-26, “Referring to FIG. 2, the processor 210 of the user terminal 200 may perform a first task for obtaining a plurality of first voice data related to a plurality of images, respectively, while operating in conjunction with the sequential displaying of the plurality of images (S110). In this case, the plurality of first voice data may include voice data that is obtained from timing at which a first touch input is input to timing at which a second touch input is input when an N (N is a natural number equal to or greater than 1)-th image, among the plurality of images, is displayed.”). Examiner interprets the task of Kim to encompass an algorithm, as it follows the same functional steps of an algorithm (as noted by dependent claims 5, 7-8, and 10-11) providing a guidance message, obtaining speech data, and evaluating the received speech data, as evidenced by Fig. 3 and the remaining recitations below. The term “training” does not provide a functional limitation, as it is an intended use of the algorithm.
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in a case where the first training algorithm is terminated, controlling a second training algorithm to be output to the user terminal (col. 19-20, lines 66-4, “The plurality of tasks may include a first task for obtaining the plurality of first voice data related to a plurality of images, respectively, while operating in conjunction with the sequential displaying of the plurality of images and a second task for obtaining the second voice data without displaying an image.” col. 18, lines 58-64, “before the second task is performed after all of the plurality of first voice data is obtained through the first task, the processor 210 may control the communication unit 230 so that the communication unit 230 first transmits the plurality of first voice data to the device 100 and then transmits the second voice data to the device 100.”);
[Examiner notes that the contingent clause of “in a case where the first training algorithm is terminated,…” has no patentable weight as the following contingent limitation is not required to be performed; see MPEP 2111.04 II. However, art is provided in the interest of compact prosecution]
in a case where the second training algorithm is terminated, evaluating user inputs into the first training algorithm and the second training algorithm (col. 19, lines 6-9, “After receiving all of the plurality of first voice data and the second voice data, the processor 110 of the device 100 may identify whether a user of the user terminal 200 has dementia.”); and
on the basis of a result of the evaluation, controlling a first visual display to be output to the user terminal (col. 13, lines 28-33, “The display unit 250 may display (output) information processed by the user terminal 200. For example, the display unit 250 may display execution screen information of an application program that is driven in the user terminal 200, or user interface (UI) and graphic user interface (GUI) information according to the execution screen information.”).
Regarding claim 2, Kim teaches the method of claim 1, as described above. Kim further teaches wherein the first training algorithm comprises a fixed first number of detailed training algorithms (col. 2, lines 35-41, “According to some embodiments of the present disclosure, the plurality of tasks may include a first task for obtaining the plurality of first voice data related to the plurality of images, respectively, while operating in conjunction with the sequential displaying of the plurality of images, and a second task for obtaining the second voice data without displaying an image.” Col. 2, lines 48-54, “Terms including an ordinal number, such as first, second, etc., may be used to describe various elements, but the elements are not limited by the terms. The above terms are used only for the purpose of distinguishing one component from another component. Therefore, a first component mentioned below may be a second component within the spirit of the present description.”). Examiner notes that the first task may be a first or second task, which indicates that the first algorithm comprises a fixed number of two algorithms.
Regarding claim 3, Kim teaches the method of claim 1, as described above. Kim further teaches wherein the first training algorithm comprises a detailed training algorithm for a focusing functional area (col. 14, lines 17-21, “The voice activity analysis information may mean information indicative of a speech rate or response time of a user of the user terminal 200.”).
[Examiner notes that the intended use of “for a focusing functional area” carries no significance to claim construction; see MPEP 2111.02 II]
Regarding claim 4, Kim teaches the method of claims 1 and 3, as described above. Kim further teaches wherein the detailed training algorithm for the focusing functional area comprises an algorithm configured to receive and evaluate speech of a user using the user terminal (col. 21, lines 11-16, “Specifically, the processor 110 may calculate a score value by inputting the content analysis information and the voice activity analysis information to the dementia identification model. Furthermore, the processor 110 may identify dementia based on the score value.”).
Regarding claim 5, Kim teaches the method of claims 1 and 3, as described above. Kim further teaches wherein the detailed training algorithm for the focusing functional areas comprises:
providing a guidance message to a user through the user terminal (col. 13, lines 52-58, “According to some embodiments of the present disclosure, the sound output unit 260 may output a preset sound (e.g., a voice that describes a task that needs to be performed by a user), while operating in conjunction with the output of a screen including a message that describes a task that needs to be performed by a user, before a plurality of images is displayed,...”); and
receiving speech of the user having at least one of a pitch and a speed changed according to the guidance message (col. 19, lines 29-32, “The voice activity analysis information may mean information indicative of a speech rate or response time of a user of the user terminal 200”),
comparing the speech of the user with a stored value, and evaluating the speech of the user (col. 21, lines 11-16, “Specifically, the processor 110 may calculate a score value by inputting the content analysis information and the voice activity analysis information to the dementia identification model. Furthermore, the processor 110 may identify dementia based on the score value.” Col. 21, lines 17-22, “For example, the processor 110 may determine whether a user of the user terminal 200 has dementia based on whether the score value is greater than a preset threshold. That is, when recognizing that the score value output by the dementia identification model is greater than the preset threshold, the processor 110 may determine that the user has dementia.”).
Regarding claim 6, Kim teaches the method of claim 1, as described above. Kim further teaches wherein the first training algorithm comprises a detailed training algorithm for a visualization functional area (col. 2, lines 2-10, “the obtaining of the content analysis information and the voice activity analysis information by using the plurality of first voice data and the second voice data which have been obtained by performing the plurality of tasks in the user terminal may include changing the plurality of first voice data into a plurality of first text data, converting the second voice data into second text data, and obtaining the content analysis information by using the plurality of first text data and the second text data.” col. 19, lines 36-40, “The speech rate information may be calculated based on the number of syllables included in each of the plurality of first voice data and the second voice data and a total time for which a voice of the user is present in each of the plurality of first voice data and the second voice data.”).
[Examiner notes that the intended use of “for a visualization functional area” carries no significance to claim construction; see MPEP 2111.02 II]
Regarding claim 7, Kim teaches the method of claims 1 and 6, as described above. Kim further teaches wherein the detailed training algorithm for the visualization functional area comprises an algorithm configured to receive speech of a user using the user terminal and evaluate a number of syllables of a word included in the speech (col. 19, lines 36-40, “The speech rate information may be calculated based on the number of syllables included in each of the plurality of first voice data and the second voice data and a total time for which a voice of the user is present in each of the plurality of first voice data and the second voice data.”).
Regarding claim 9, Kim teaches the method of claims 1 and 6, as described above. Kim further teaches wherein the first training algorithm comprises a detailed training algorithm for a fusion functional area (Fig. 7). Examiner interprets receiving a story from the user and analyzing the story by the processor of the device to encompass the first training algorithm, with respect to the rejection to claim 10, below.
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Regarding claim 10, Kim teaches the method of claims 1 and 9, as described above. Kim further teaches wherein the detailed training algorithm for the fusion functional area comprises an algorithm configured to receive a story created by the user using the user terminal (Fig. 7).
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And determine whether or not the story meets a condition (col. 21, lines 12-22, “Specifically, the processor 110 may calculate a score value by inputting the content analysis information and the voice activity analysis information to the dementia identification model. Furthermore, the processor 110 may identify dementia based on the score value. For example, the processor 110 may determine whether a user of the user terminal 200 has dementia based on whether the score value is greater than a preset threshold. That is, when recognizing that the score value output by the dementia identification model is greater than the preset threshold, the processor 110 may determine that the user has dementia.”). Under the broadest reasonable interpretation, determining if the content of the story received from the user/patient meets a threshold condition for dementia diagnosis encompasses a determining whether or not the story meets a condition.
Regarding claim 12, Kim teaches the method of claim 1, as described above. Kim further teaches wherein the first training algorithm comprises at least two of detailed training algorithms for focusing, visualization, and fusion functional areas (col. 14, lines 17-21, “The voice activity analysis information may mean information indicative of a speech rate or response time of a user of the user terminal 200.” col. 2, lines 2-10, “the obtaining of the content analysis information and the voice activity analysis information by using the plurality of first voice data and the second voice data which have been obtained by performing the plurality of tasks in the user terminal may include changing the plurality of first voice data into a plurality of first text data, converting the second voice data into second text data, and obtaining the content analysis information by using the plurality of first text data and the second text data.” col. 19, lines 36-40, “The speech rate information may be calculated based on the number of syllables included in each of the plurality of first voice data and the second voice data and a total time for which a voice of the user is present in each of the plurality of first voice data and the second voice data.”). Examiner notes that the first task encompasses both speech rate (speed/focusing) and syllable analysis (visualization).
[Examiner notes that the intended use of “for focusing, visualization, and fusion functional areas” carries no significance to claim construction; see MPEP 2111.02 II]
Regarding claim 13, Kim teaches a non-transitory computer-readable storage device storing a computer program for executing the method of claim 1 (col. 7, lines 8-12, “The storage 120 may store data supporting various functions of the device 100. The storage 120 may store a plurality of application programs (or applications) driven in the device 100, and data, commands, and at least one program command for the operation of the device 100.” col. 7, lines 26-37, “The storage 120 may include at least one type of storage medium of a flash memory type, a hard disk type, a solid state disk (SSD) type, a silicon disk drive (SDD) type, a multimedia card micro type, a card-type memory (e.g., SD memory and XD memory), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, a magnetic disk, and an optical disk. The device 100 may be operated in relation to a web storage that performs a storage function of the storage 120 on the Internet.”). Examiner notes that the first task encompasses both speech rate (speed/focusing) and syllable analysis (visualization).
Regarding claim 14, this claim is rejected for the same reasons as claim 1. Kim further teaches a first output controller (col. 6, lines 51-55, “The processor 110 may provide or process appropriate information or functions by processing signals, data, or information that is input or output through the components of the device 100 or driving an application program stored in the storage 120.” Col. 2, lines 36-40, “the plurality of tasks may include a first task for obtaining the plurality of first voice data related to the plurality of images, respectively, while operating in conjunction with the sequential displaying of the plurality of images”);
a second output controller (col. 6, lines 51-55, “The processor 110 may provide or process appropriate information or functions by processing signals, data, or information that is input or output through the components of the device 100 or driving an application program stored in the storage 120.” Col. 17, lines 48-50, “the processor 210 of the user terminal 200 may perform a second task for obtaining second voice data without displaying an image (S120).”);
a training evaluation unit (col. 21, lines 12-15, “the processor 110 may calculate a score value by inputting the content analysis information and the voice activity analysis information to the dementia identification model”); and
a visual display controller (col. 13, lines 28-33, “The display unit 250 may display (output) information processed by the user terminal 200. For example, the display unit 250 may display execution screen information of an application program that is driven in the user terminal 200, or user interface (UI) and graphic user interface (GUI) information according to the execution screen information.”).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Kim (US 11759145) in view of Gomory (US 20160117940).
Regarding claim 8, Kim teaches the method of claims 1 and 6, as described above. Kim further teaches wherein the detailed training algorithm for the visualization functional area comprises:
providing a guidance message to a user through the user terminal (col. 13, lines 52-58, “According to some embodiments of the present disclosure, the sound output unit 260 may output a preset sound (e.g., a voice that describes a task that needs to be performed by a user), while operating in conjunction with the output of a screen including a message that describes a task that needs to be performed by a user, before a plurality of images is displayed,...”); and
receiving speech of the user for a certain period of time in response to the guidance message (col. , lines , “In this case, the description screen S1 may include a message M1 that describes the task that needs to be performed by the user and a start button 401 that enables the first task for obtaining the plurality of first voice data to be started.”),
detecting a number of syllables (col. 19, lines 36-40, “The speech rate information may be calculated based on the number of syllables included in each of the plurality of first voice data and the second voice data and a total time for which a voice of the user is present in each of the plurality of first voice data and the second voice data.”), and
evaluating the speech of the user (col. 21, lines 11-16, “Specifically, the processor 110 may calculate a score value by inputting the content analysis information and the voice activity analysis information to the dementia identification model. Furthermore, the processor 110 may identify dementia based on the score value.” Col. 21, lines 17-22, “For example, the processor 110 may determine whether a user of the user terminal 200 has dementia based on whether the score value is greater than a preset threshold. That is, when recognizing that the score value output by the dementia identification model is greater than the preset threshold, the processor 110 may determine that the user has dementia.”).
Kim does not teach comparing the detected number of syllables with a preset value.
However, Gomory does teach comparing the detected number of syllables with a preset value ([0037], “In some embodiments, the system further comprises a therapy application, where the threshold algorithm can be constructed and arranged to cause the system to modify the therapy application if one or more parameters fall outside a threshold. The threshold algorithm can be constructed and arranged to compare a parameter to a threshold wherein the parameter is selected from the group consisting of: lexical parameters such as word length, number of syllables,…” [0062], “The input data can comprise at least recorded speech, for example where the speech represents at least one of: a sentence; a word; a partial word; a phonetic sound such as a diphone, a triphone or a blend; a phoneme; or a syllable.”).
Kim in view of Gomory are considered analogous to the claimed invention because they are in the field of speech analysis. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Kim with Gomory for the advantage of providing a system “to assist, motivate, evaluate, and/or monitor the patient in his or her performance of the therapy application” (Gomory; [0134]).
Claim 11 is rejected under 35 U.S.C. 103 as being unpatentable over Kim (US 11759145) in view of Maurya (US 20230133843) further in view of Eleftheriou (US 20200075039).
Regarding claim 11, Kim teaches the method of claims 1 and 9, as described above. Kim further teaches wherein the detailed training algorithm for the fusion functional area comprises: providing a story creation condition to the user through the user terminal (Fig. 7). Under the broadest reasonable interpretation, providing a prompt such as telling the story of “Rabbit and Turtle” encompasses a condition for the story creation, as it provides a guideline for how the story should be created.
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Kim does not teach wherein the detailed training algorithm for the fusion functional area comprises: in a case where the story created by the user is received, determining whether or not the story is a story corresponding to a number of words and emotional modifiers included in the story creation condition.
However, Maurya does teach wherein the detailed training algorithm for the fusion functional area comprises:
in a case where the story created by the user is received, determining whether or not the story is a story corresponding to a number of words included in the story creation condition ([0064], “The Essay Analyzer may advantageously track the distribution of these compositions across classes from the database for various essays, and in conjunction with the associated profile, provide feedback that helps the author tailor the content of the essay for better effect or to meet specific requirements, such as omitting some details to ensure the essay is within a word limit.” ).
Kim in view of Maurya are considered analogous to the claimed invention because they are in the field of story analysis. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Kim with Maurya for the advantage of providing a system that flags when “a paragraph length exceeds […] recommended range” (Maurya; [0172]).
Kim in view of Maurya does teach wherein the detailed training algorithm for the fusion functional area comprises:
in a case where the story created by the user is received, determining whether or not the story is a story corresponding to emotional modifiers included in the story creation condition.
However, Maurya in view of Eleftheriou does teach wherein the detailed training algorithm for the fusion functional area comprises:
in a case where the story created by the user is received, determining whether or not the story is a story corresponding to emotional modifiers included in the story creation condition (Maurya, [0021], “The framework analyzes the language, relevance, structure, and flows for an overall impactful essay. Essay content is checked to evaluate whether the author has covered essential aspects regarded primary to the essay that are pre-identified in the framework.” Eleftheriou, [0012], “the companion application can: prompt the user to recount a story associated with a target emotion (e.g., happy, sad, stressed, distressed, etc.); and capture a voice recording of the user orally reciting this story.”). It would be obvious to one of ordinary skill in the art that combining a text content analyzer that analyzes text for relevance and covering of essential aspects with a prompt for a target emotion would encompass determining whether or not the story corresponds to an emotional modifier, as the emotional modifier is the prompt that the analyzer would assess for.
Kim in view of Maurya further in view of Eleftheriou are considered analogous to the claimed invention because they are in the field of story analysis. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Kim in view of Maurya with Eleftheriou for the advantage of “prompt[ing] the user to complete the emotion-specific coaching activity via the mobile device” (Eleftheriou; [0017]).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Method And Systems For Treating Health Conditions Using Prescription Digital Therapeutics (US 20220028528) teaches a prescription digital therapeutic (PDT) system provided to patients/users, wherein the PDT system allows guided behavioral therapy and skills training to be administered in a convenient and flexible, yet structured fashion, via a system associated with an application such as a mobile application. Guided behavioral therapy technologies may be based at least in part on cognitive behavioral therapy (CBT) techniques to allow for development of a skillset for treating a physiological disease, disorder and/or condition, and for managing stress and/or other psychological symptoms associated with such disease, disorder and/or condition. Patient interactions with the PDT system are monitored to control progression through the system content and to continually refine one or more personalized intervention regimens associated with the guided behavioral therapy.
Method and System for Estimating a Demand or an Attentional Cost Associated with the Execution of a Task or Attention Sharing Strategies Developed by an Individual (US 20190172367) which teaches a method for estimating the attentional resources invoked for the execution of a primary task and/or attention sharing strategies developed by an individual, said method being implemented in a mobile terminal and being based on the utilization of the dual-task paradigm, noteworthy in that it comprises the following steps: —Evaluation (10) of first performance ratings of the individual during the execution of a primary task alone, —Evaluation (20) of second performance ratings of the individual during the execution of a secondary task alone, —Evaluation (30) of third performance ratings of the individual during the simultaneous execution of the primary and secondary tasks, —Estimation (40) of the attentional demand required for the execution of the primary task and/or of the effect (beneficial or negative) of a secondary task on the control mechanisms involved in the execution of the primary task and/or attention sharing strategies developed by an individual by comparing the first, second and third performance ratings evaluated during the previous steps.
Determining A Demographic Characteristic Based On Computational User-health Testing Of A User Interaction With Advertiser-specified Content (US 20120164613), which teaches methods, apparatuses, computer program products, devices and systems are described that carry out specifying at least one of a plurality of user-health test functions responsive to an interaction between a user and at least one advertiser-specified attribute; and transmitting at least one demographic characteristic of the user based on at least one output of the at least one of a plurality of user-health test functions.
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/D.C./Examiner, Art Unit 3684
/Shahid Merchant/Supervisory Patent Examiner, Art Unit 3684
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