DETAILED ACTION
This communication is in response to the Arguments and Remarks filed on 3/25/2026. Claims 10-20 are pending and have been examined. Hence, this Action has been made FINAL.
Any previous objection/rejection not mentioned in this Office Action has been withdrawn by the examiner.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 13, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 5/18/2026 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed in parent Application No. KR 10-2024-0007767, filed on 1/18/2024.
Response to Arguments
Applicant's arguments filed 3/25/2026 have been fully considered but they are not persuasive.
With respect to the 35 U.S.C. 101 rejections, the applicant asserts that Claim 10 has been amended to recite that the constituent elements of the claim are performed "by a device" which is a machine or a component of the machine.
Examiner respectfully disagrees, the device in these claims is merely used to apply a mental a process via a computing device. Furthermore, the device is general purpose/ generic with no specific design or implementation that integrates within the claim language.
With respect to the 35 U.S.C. 103 rejections, the applicant asserts that Claim 10 has been amended to more clearly define a feature of the presently claimed embodiment and to more clearly distinguish over the applied prior art references
This argument is considered moot in view of an updated prior art search necessitated by the amendments to the claims. An updated prior art rejection is detailed below.
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 10-20 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claim 10 recites A method for supporting a prediction for a degenerative brain function decline of a user, the method comprising: outputting, by a [device], to the user, through a user interface device, a first reference content, and at least one system conversation triggering at least one user conversation related to the first reference content; receiving, by the device, from the user, through the user interface device, at least one user conversation for the first reference content; and based on a first generated content generated based on the at least one user conversation for the first reference content, acquiring, by the device, a first prediction result for the degenerative brain function decline of the user, wherein, using first situation description information of the user regarding a situation represented in the first reference content, the first generated content is generated to represent, in the first generated content, a situation corresponding to the first situation description information of the user.
The limitations in this claim, as drafted, is a process that, under broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. The human mind is capable of performing this method. As an example, this could be done by a doctor examining a patient for degenerative brain function decline. The doctor could show the patient content like a photograph and ask them to describe the picture (system conversation). The patient could then describe what they see (user conversation). Then, the doctor could have the patient draw the picture for themselves (generated content). Next, based on the drawing, the doctor could make a prediction on if they are experiencing any degenerative brain function decline. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim lists the additional component of a user interface and a device. The user interface device is described in paragraphs 58-59 of the specification with a generic description of the component. The device is merely being used to apply a mental process via a computing device. The device is described in paragraph 58 of the specification and is described as a generic computing device. Accordingly, the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The claim is not patent eligible.
Claim 11 recites wherein the method further includes providing, by the device, the first prediction result to the user through the user interface device.
The limitations in this claim, as drafted, is a process that, under broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. From the independent claim example, the doctor can present the prediction to the patient by writing it on a paper and giving it to them. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. The claim does not list any additional components that were not present in the independent claim. Accordingly, the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The claim is not patent eligible.
Claim 12 recites wherein: a first user conversation of the at least one user conversation is associated with a first system conversation of the at least one system conversation, a second system conversation of the at least one system conversation is generated or selected based on the first user conversation.
The limitations in this claim, as drafted, is a process that, under broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. From the independent claim example, the patient's description of the picture would be associated with the initial question asked by the doctor. The doctor could then respond to their description by for example, saying a follow up question or letting them know they did a good job. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. The claim does not list any additional components that were not present in the independent claim. Accordingly, the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The claim is not patent eligible.
Claim 13 recites wherein the at least one system conversation is generated or selected based on an understanding-based conversation task for the first reference content.
The limitations in this claim, as drafted, is a process that, under broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. From the independent claim example, the doctor could create a question based on understanding of the content (Ex: show them a picture, ask them to describe the picture). If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. The claim does not list any additional components that were not present in the independent claim. Accordingly, the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The claim is not patent eligible.
Claim 14 recites wherein the method further includes outputting, to the user, through the user interface device, the first generated content generated based on the at least one user conversation for the first reference content.
The limitations in this claim, as drafted, is a process that, under broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. From the independent claim example, the doctor can present an image drawn based on the patient’s description to the patient by drawing it on paper and giving it to them. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. The claim does not list any additional components that were not present in the independent claim. Accordingly, the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The claim is not patent eligible.
Claim 15 recites wherein the first prediction result is acquired through an application of a patient group model and a normal group model learned based on content data to the first reference content, and the first generated content generated based on the at least one user conversation for the first reference content.
The limitations in this claim, as drafted, is a process that, under broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. From the independent claim example, the doctor could base their prediction off of known results they’ve studied from patients with and without degenerative brain function decline. The doctor could build their prior knowledge based on pictures created from a patient’s description of an initial picture. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. The claim lists the additional components of a patient group model and normal group model. These models are described as VLM’s in paragraph 102 of the specification and the VLM’s are said to be general purpose models in paragraph 89 of the specification. Accordingly, the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The claim is not patent eligible.
Claim 16 recites wherein the method further includes: outputting, by the device, to the user, through the user interface device, a second reference content selected based on the first prediction result for the degenerative brain function decline of the user, and at least one system conversation triggering at least one user conversation related to the second reference content; receiving, by the device, from the user, through the user interface device, at least one user conversation for the second reference content; and based on a second generated content generated based on the at least one user conversation for the second reference content, acquiring, by the device, a second prediction result for the degenerative brain function decline of the user. wherein, using second situation description information of the user regarding a situation represented in the second reference content, the second generated content is generated to represent, in the second generated content, a situation corresponding to the second situation description information of the user.
The limitations in this claim, as drafted, is a process that, under broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. From the independent claim example, the doctor could repeat this process and give the patient another result. They would show them another photo, ask a question, receive a response, draw a picture based on that response, and then provide another prediction of degenerative brain function decline based on that picture. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. The claim does not list any additional components that were not present in the independent claim. Accordingly, the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The claim is not patent eligible.
Claim 17 recites wherein the method further includes providing the second prediction result to the user through the user interface device.
The limitations in this claim, as drafted, is a process that, under broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. From the independent claim example, the doctor can present the new prediction to the patient by writing it on a paper and giving it to them. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. The claim does not list any additional components that were not present in the independent claim. Accordingly, the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The claim is not patent eligible.
Claim 18 recites wherein the method further includes outputting, by the device, to the user, through the user interface device, the second generated content generated based on the at least one user conversation for the second reference content.
The limitations in this claim, as drafted, is a process that, under broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. From the independent claim example, the doctor can present the new second drawn picture based on their response to the patient by drawing it on a paper and giving it to them. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. The claim does not list any additional components that were not present in the independent claim. Accordingly, the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The claim is not patent eligible.
Claim 19 recites wherein the content includes at least one of an image, a video, a text, a voice, or a sound.
The limitations in this claim, as drafted, is a process that, under broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. From the independent claim example, the doctor could give the patient an image, video, text, voice, or sound as the content they will ask them a question about. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. The claim does not list any additional components that were not present in the independent claim. Accordingly, the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The claim is not patent eligible.
Claim 20 recites A device for supporting a prediction for a degenerative brain function decline of a user, the device comprising: a memory; a transceiver; and a processor, wherein the processor is configured to perform the method according to claim 10.
The limitations in this claim, as drafted, is a process that, under broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. The device performs the same method as claim 10, thus is rejected on the same grounds. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. The claim lists the additional components of a memory, a transceiver, and a processor. The memory is detailed in paragraph 55 of the specification with a generic description of the component. The transceiver is detailed in paragraph 55 of the specification with a generic description of the component. The processor is detailed in paragraph 134 of the specification with a generic description of the component. Accordingly, the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The claim is not patent eligible.
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 (i.e., changing from AIA to pre-AIA ) 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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 10-20 are rejected under 35 U.S.C. 103 as being unpatentable over US Patent Publication US 11631395 B2 (Vairavan et al.) in view of KR Patent Publication KR 20200012120 A (Jeong) and “A Portrait of Emotion: Empowering Self-Expression through AI-Generated Art” (Lee et al.).
Regarding Claim 10, Vairavan et al. teaches A method for supporting a prediction for a degenerative brain function decline of a user, the method comprising:
(The present application relates to devices and methods for detecting and/or predicting cognitive decline) (Col. 4, Lines 27-28).
outputting, by a device, to the user, through a user interface device, a first reference content, and at least one system conversation triggering at least one user conversation related to the first reference content;
(In step 602, the subject is provided with a first set of instructions a plurality of times by a clinician operating the device 500 or by the processor 502 directing the audio output arrangement 506 to audibly provide the first set of instructions to the patient) (Col. 11, Lines 27-31).
(Each of the patients was provided with a first set of instructions for listening to a first word list and immediately recalling and speaking the first word list.) (Col. 13, Lines 51-53)
The user is provided a list of words (first reference content) through an audio user interface. Furthermore, the user is given the instruction (system conversation) to read the list of words allowed for recording (user conversation).
receiving, by the device, from the user, through the user interface device, at least one user conversation for the first reference content;
(In step 602, the subject is provided with a first set of instructions a plurality of times by a clinician operating the device 500 or by the processor 502 directing the audio output arrangement 506 to audibly provide the first set of instructions to the patient, and the processor 502 receives from the audio input arrangement 506 subject baseline speech data corresponding to a plurality of audio recordings of speech of a subject in response to the first set of instructions.) (Col. 11, Lines 27-35).
The patient (user) repeats the words into an audio recording; thus, the system receives the user conversation.
Vairavan et al. does not explicitly teach: and based on a first generated content generated based on the at least one user conversation for the first reference content, acquiring, by the device, a first prediction result for the degenerative brain function decline of the user. wherein, using first situation description information of the user regarding a situation represented in the first reference content, the first generated content is generated to represent, in the first generated content, a situation corresponding to the first situation description information of the user.
However, Jeong et al. teaches and based on a first generated content generated based on the at least one user conversation for the first reference content, acquiring, by the device, a first prediction result for the degenerative brain function decline of the user.
(The cognitive impairment prevention conversation service apparatus 120 generates a questionnaire (or query content) to be provided to the subject based on the received related information and data, and responds to the questionnaire provided by the subject's user device. Based on the prediction of the subject's dementia potential (S610). Of course, since the prediction is based on the analysis result of the response of the subject accumulated over time, when the prediction is made, the cognitive impairment prevention conversation service device 120 is stored in advance for more accurate evaluation or After generating some additional questions automatically and automatically transmitting to the user device of the second user without the intervention of the first user, more accurate judgment can be made based on the answers) (Page 10, Paragraphs 5-6).
The system of Jeong is designed to detect signs of degenerative brain function decline in a patient (second user in the spec) by having another user (first user in spec) message them while allowing the system to monitor the messages. Its initial steps will have the first user provide information, content, and questions for the conversation. As the system gathers information from the second users’ responses it will begin to generate its own question for the second user in order to better detect cognitive decline. In this sense, the system is generating content based on the user conversation and using that content to evaluate for cognitive decline.
It would have been obvious to a person having ordinary skill in the art before the time of the effective filing date of the claimed invention of the instant application to modify the method of evaluating cognitive decline as taught by Vairavan et al. to generate content to evaluate for degenerative brain function decline as taught by Jeong. This would have been an obvious improvement as a user’s response to an initial test can provide added context for which an evaluation can be made (Jeong, Page 10, Paragraph 6).
Vairavan et al. in view Jeong does not explicitly teach: wherein, using first situation description information of the user regarding a situation represented in the first reference content, the first generated content is generated to represent, in the first generated content, a situation corresponding to the first situation description information of the user.
However, Lee et al. teaches wherein, using first situation description information of the user regarding a situation represented in the first reference content, the first generated content is generated to represent, in the first generated content, a situation corresponding to the first situation description information of the user.
(Figure 1 illustrates overall process. We used diary entries released from the previous study1, annotated with emotion categories. Each diary entry was self-annotated with one or two emotion categories by diary authors (happy, sad, angry, neutral, disgust, surprise, calm, fear, and others; Ekman, 1992).) (Section: Emotion Diary Entries, Paragraph 1)
(We used DALL-E 25 and StableDiffusion6 interchangeably to generate images using the same prompt to select the most appropriate images per diary to ensure that its main events and emotions are represented in their drawings.) (Section: AI Art Generation, Paragraph 1).
Lee et al. shows generating content based off a user’s description of an event with the goal of the images being to determine something about the user’s mental state (emotions in this case). The initial diary entries are meant to describe emotions felt during the pandemic and the generated images are supposed to depict those same emotions. Since Vairavan et al. in view of Jeong already teaches presenting a first reference content and generating content from that, this is meant to show that the generation of content can come from a user’s description of something.
It would have been obvious to a person having ordinary skill in the art before the time of the effective filing date of the claimed invention of the instant application to modify the method of evaluating cognitive decline as taught by Vairavan et al. in view of Jeong to generate content based off of a user’s description of related content as taught by Lee et al. This would have been an obvious improvement as the method can accurately generate art that reflects a user’s emotions which is a form of representing a user’s cognitive state (Jeong, Section: The Present Study, Paragraph 3).
Regarding Claim 11, Vairavan et al. in view of Jeong and Lee et al. teaches the system of claim 10.
Furthermore, Vairavan et al. teaches wherein the method further includes providing, by the device, the first prediction result to the user through the user interface device.
(The processor 502 may also generate an output indicating whether the subject has an increased risk for neurodegeneration and/or likely suffers from cognitive decline based on the ensemble output generated by the trained ensemble classifier 516 from analyzing the subject test data. The output may indicate that the subject has an increased risk for neurodegeneration and/or likely suffers from cognitive decline when the ensemble output identifies the subject test data as corresponding to the cognitive decline patient. In contrast, the output may indicate that the subject does not have an increased risk for neurodegeneration and/or is not likely to suffer from cognitive decline when the ensemble output identifies the subject test data as corresponding to the normal patient. In step 610, the processor 502 directs the display 512 to provide a visual display showing the output.) (Col. 12, Lines 7-21).
The output is displayed to the patient.
Regarding Claim 12, Vairavan et al. in view of Jeong and Lee et al. teaches the system of claim 10.
Furthermore, Vairavan et al. teaches wherein: a first user conversation of the at least one user conversation is associated with a first system conversation of the at least one system conversation,
(Each of the patients was provided with a first set of instructions for listening to a first word list and immediately recalling and speaking the first word list.) (Col. 13, Lines 51-53).
In an example presented by Vairavan et al. it can be clearly stated that the patient’s response is directly related to the system conversation provided to them.
a second system conversation of the at least one system conversation is generated or selected based on the first user conversation.
(The patients were then subject to a distraction task. In particular, each of the patients was subsequently provided with a second set of instructions for listening to a second word list and recalling and speaking the second word list. The second word list includes the following words: desk, ranger, bird, shoe, stove, mountain, glasses, towel, cloud, boat, lamb, bell, pencil, church, fish. The speech was recorded for each patient to generate a set of trial speech data corresponding to the speech recordings for a Distractor Trial. After the distraction task, the patients were then asked to recall and speak the first word list. The speech was recorded for each patient to generate a set of trial speech data corresponding to the speech recordings for a Post Distraction Trial. After a 20-minute delay, the patients were then asked again to recall and speak the first word list. The speech was recorded for each patient to generate a set of trial speech data corresponding to the speech recordings for a Delayed Recall Trial.) (Col. 13 Lines 62-67 to Col.14, Lines 1-12).
Second system conversation related to the user conversation can be seen in this example where they are asked to recall their answer to a previous test.
Regarding Claim 13, Vairavan et al. in view of Jeong and Lee et al. teaches the system of claim 10.
Furthermore, Vairavan et al. teaches wherein the at least one system conversation is generated or selected based on an understanding-based conversation task for the first reference content.
(The present application relates to devices and methods for detecting and/or predicting cognitive decline, in particular, MCI, by analyzing data corresponding to a speech sample of a subject or patient obtained from a neuropsychological test, such as a word list recall (WLR) test using a computer-implemented method.) (Col. 4 Lines 27-32).
(Each of the patients was provided with a first set of instructions for listening to a first word list and immediately recalling and speaking the first word list.) (Col. 13, Lines 51-53).
The system conversation is the request to verbally recall the list of words provided in the first content. This is an understanding-based conversation task as it tests the users understanding of the question, ability to remember words, and ability to pronounce words.
Regarding Claim 14, Vairavan et al. in view of Jeong and Lee et al. teaches the system of claim 10.
Furthermore, Jeong teaches wherein the method further includes outputting, to the user, through the user interface device, the first generated content generated based on the at least one user conversation for the first reference content.
(Accordingly, the cognitive impairment prevention conversation service apparatus 120 may generate a questionnaire for a specific person of user 1 received through a query format and process the same (S530). In this case, the processing includes, for example, displaying a standardized question on a screen, and being edited by the user and provided to the second user) (Page 9, Paragraph 8).
The content generated in the method of Jeong is displayed to the user/patient.
Regarding Claim 15, Vairavan et al. in view of Jeong and Lee et al. teaches the method of claim 10,
Furthermore, Jeong teaches wherein the first prediction result is acquired through an application of a patient group model and a normal group model learned based on content data to the first reference content, and the first generated content generated based on the at least one user conversation for the first reference content.
(When the cognitive impairment prevention conversation service device 120 receives an answer, it stores the corresponding answer and performs analysis (S550). For example, if there is an answer provided by the second user in relation to the photograph, the accuracy is evaluated by comparison. In this way, the same content, such as the same picture, is periodically equated to the same repetition with time, or the style or question is changed little by little. Based on the answers, the possibility of dementia of the second user is analyzed more precisely. Predictive.) (Jeong, Page 9, Paragraph 10).
The answer provided by the outside user (first user) can be considered the “normal” group answer for which the answer provided by the patient is compared to in order to evaluate their replies to questions.
Furthermore, Vairavan teaches the specific limitation of wherein the first prediction result is acquired through an application of a patient group model and a normal group model learned based on content data to the first reference content
(In step 202, the computing device 110 receives from the database 110 a plurality of sets of training baseline speech data 112 corresponding to a plurality of sets of prior audio recordings of speech of a group of normal and cognitive decline patients. Each set of the training baseline speech data 112 corresponds to speech of the group of normal and cognitive decline patients in response to a same set of instructions for listening to a word list and recalling and speaking the same word list.) (Vairavan et al. Col. 5, Lines 39-47).
(The computing device 110 may extract as speech features from the sets of speech data any suitable type of acoustics properties for analyzing audio recordings of spoken speech, including mean and standard deviation data values corresponding to such acoustic properties.) (Vairavan et al. Col. 6, Lines 55-60).
Vairavan et al. trains models based on data gathered from normal and cognitive decline patients.
Regarding Claim 16, Vairavan et al. in view of Jeong and Lee et al. teaches the system of claim 10.
Furthermore, Vairavan et al. teaches wherein the method further includes: outputting, by the device, to the user, through the user interface device, a second reference content selected based on the first prediction result for the degenerative brain function decline of the user, and at least one system conversation triggering at least one user conversation related to the second reference content;
(The patients were then subject to a distraction task. In particular, each of the patients was subsequently provided with a second set of instructions for listening to a second word list and recalling and speaking the second word list.) (Vairavan et al. Col. 13, Lines 62-65).
The example provided by Vairavan et al. states following up with a second set of words for the user to repeat. This set is based on the first prediction as it is a completely new set of words meant to act as a distraction for when the user is asked to repeat the first set of words again.
receiving, by the device, from the user, through the user interface device, at least one user conversation for the second reference content;
(In step 602, the subject is provided with a first set of instructions a plurality of times by a clinician operating the device 500 or by the processor 502 directing the audio output arrangement 506 to audibly provide the first set of instructions to the patient, and the processor 502 receives from the audio input arrangement 506 subject baseline speech data corresponding to a plurality of audio recordings of speech of a subject in response to the first set of instructions.) (Vairavan et al. Col. 11, Lines 27-35).
(The patients were then subject to a distraction task. In particular, each of the patients was subsequently provided with a second set of instructions for listening to a second word list and recalling and speaking the second word list.) (Col. 13, Lines 62-65).
Just like with the first set of words, the patient is instructed to recall them aloud.
Furthermore, Jeong teaches and based on a second generated content generated based on the at least one user conversation for the second reference content, acquiring, by the device, a second prediction result for the degenerative brain function decline of the user.
(The cognitive impairment prevention conversation service apparatus 120 generates a questionnaire (or query content) to be provided to the subject based on the received related information and data, and responds to the questionnaire provided by the subject's user device. Based on the prediction of the subject's dementia potential (S610). Of course, since the prediction is based on the analysis result of the response of the subject accumulated over time, when the prediction is made, the cognitive impairment prevention conversation service device 120 is stored in advance for more accurate evaluation or After generating some additional questions automatically and automatically transmitting to the user device of the second user without the intervention of the first user, more accurate judgment can be made based on the answers) (Jeong, Page 10, Paragraphs 5-6).
The system of Jeong stores predictions made in order to create new generated content that will be used to make more accurate evaluations. Where an updated question is a second generated content based on the user conversation and the user reply provides a second prediction.
Furthermore, Lee et al. teaches wherein, using second situation description information of the user regarding a situation represented in the second reference content, the second generated content is generated to represent, in the second generated content, a situation corresponding to the first situation description information of the user.
(Figure 1 illustrates overall process. We used diary entries released from the previous study1, annotated with emotion categories. Each diary entry was self-annotated with one or two emotion categories by diary authors (happy, sad, angry, neutral, disgust, surprise, calm, fear, and others; Ekman, 1992).) (Section: Emotion Diary Entries, Paragraph 1)
(We used DALL-E 25 and StableDiffusion6 interchangeably to generate images using the same prompt to select the most appropriate images per diary to ensure that its main events and emotions are represented in their drawings.) (Section: AI Art Generation, Paragraph 1).
Lee et al. shows generating content based off a user’s description of an event with the goal of the images being to determine something about the user’s mental state (emotions in this case). The initial diary entries are meant to describe emotions felt during the pandemic and the generated images are supposed to depict those same emotions. Since Vairavan et al. in view of Jeong already teaches presenting a first reference content and generating content from that, this is meant to show that the generation of content can come from a user’s description of something.
Regarding Claim 17, Vairavan et al. in view of Jeong and Lee et al. teaches the system of claim 16.
Furthermore, Vairavan et al. teaches wherein the method further includes providing the second prediction result to the user through the user interface device.
(The processor 502 may also generate an output indicating whether the subject has an increased risk for neurodegeneration and/or likely suffers from cognitive decline based on the ensemble output generated by the trained ensemble classifier 516 from analyzing the subject test data. The output may indicate that the subject has an increased risk for neurodegeneration and/or likely suffers from cognitive decline when the ensemble output identifies the subject test data as corresponding to the cognitive decline patient. In contrast, the output may indicate that the subject does not have an increased risk for neurodegeneration and/or is not likely to suffer from cognitive decline when the ensemble output identifies the subject test data as corresponding to the normal patient. In step 610, the processor 502 directs the display 512 to provide a visual display showing the output.) (Col. 12, Lines 7-21).
The cognitive decline assessments are output to the user. Once again, Fig. 8 shows this assessment being done for multiple tests done the provided example.
Regarding Claim 18, Vairavan et al. in view of Jeong and Lee et al. teaches the system of claim 16.
Furthermore, Jeong teaches wherein the method further includes outputting, by the device, to the user, through the user interface device, the first generated content generated based on the at least one user conversation for the first reference content.
(Accordingly, the cognitive impairment prevention conversation service apparatus 120 may generate a questionnaire for a specific person of user 1 received through a query format and process the same (S530). In this case, the processing includes, for example, displaying a standardized question on a screen, and being edited by the user and provided to the second user) (Page 9, Paragraph 8).
The “second” content generated in the method of Jeong is displayed to the user/patient.
Regarding Claim 19, Vairavan et al. in view of Jeong and Lee et al. teaches the system of claim 10.
Furthermore, Vairavan et al. teaches wherein the content includes at least one of an image, a video, a text, a voice, or a sound.
(Each set of the training baseline speech data 112 corresponds to speech of the group of normal and cognitive decline patients in response to a same set of instructions for listening to a word list and recalling and speaking the same word list.) (Col. 5, Lines 43-47).
(In step 602, the subject is provided with a first set of instructions a plurality of times by a clinician operating the device 500 or by the processor 502 directing the audio output arrangement 506 to audibly provide the first set of instructions to the patient) (Vairavan et al. Col. 11, Lines 27-31).
In Vairavan et al. the content is in the form of voice and sound content as it is a list of English words output audibly to the user.
Furthermore, Jeong teaches wherein the content includes at least one of an image, a video, a text, a voice, or a sound.
(Accordingly, the cognitive impairment prevention conversation service apparatus 120 may generate a questionnaire for a specific person of user 1 received through a query format and process the same (S530). In this case, the processing includes, for example, displaying a standardized question on a screen, and being edited by the user and provided to the second user) (Jeong, Page 9, Paragraph 8).
Jeong teaches producing content in the form of text.
Regarding Claim 20, Vairavan et al. teaches A device for supporting a prediction for a degenerative brain function decline of a user, the device comprising: a memory; a transceiver; and a processor,
(The computing device 120 in this embodiment comprises a processor 122, a computer accessible medium 124, and an input/output device 126 for receiving and/or transmitting data and/or instructions to and/or from the computing device 120. The processor 122 can include, e.g., one or more microprocessors, and use instructions stored on the computer-accessible medium 124 (e.g., memory storage device).) (Col. 4, Lines 62-67 to Col. 5, Lines 1-2).
wherein the processor is configured to perform the method according to claim 1.
Vairavan et al. in view of Jeong and Lee et al. teaches the method of claim 10, see the details of this rejection above.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to NICHOLAS DANIEL LOWEN whose telephone number is (571)272-5828. The examiner can normally be reached Mon-Fri 8:00am - 4:00pm.
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, Paras D Shah can be reached at (571) 270-1650. 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.
/NICHOLAS D LOWEN/Examiner, Art Unit 2653
/Paras D Shah/Supervisory Patent Examiner, Art Unit 2653
06/27/2026
Prosecution Insights