system

Abstract

Provide a system. A means for inputting a user's emotion; A means for analyzing input emotion data; means for generating artwork based on the analyzed emotion data; means for displaying the generated artwork to a user; A means for inputting user feedback; A means for analyzing the inputted impression data and providing mental care information; A system including:

Description

[Technical Field]

[0001] The technology of the present disclosure relates to a system. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] Modern society is extremely stressful, with many people suffering from negative emotions and stress. The contagious nature of these emotions, especially those that cause further mental strain, is a major problem. While art therapy is considered an effective way to express emotions and reduce stress, it requires drawing skills and artistic talent, making it a hurdle for people who do not normally draw. There is a need for a solution to this problem, one that allows individuals to easily express their emotions through art and reduce mental strain. [Means for solving the problem]

[0005] In order to solve the above problems, the present invention provides the following means. A means is provided for allowing a user to input, in text format, the negative emotions and stress factors they are currently experiencing. A means is then provided for analyzing this input emotional data using natural language processing technology and, based on the results, selecting appropriate colors and shapes to generate artwork. The generated artwork is displayed to the user, who then inputs their impressions of viewing it and any positive emotions they may have. By creating a system that includes a means for reanalyzing this impression data and providing the necessary mental care information, users can easily express their emotions and feel positive, even without specialized knowledge or skills.

[0006] "User's emotions" refers to the feelings and mental state that the user subjectively experiences, and in particular stress and negative emotions.

[0007] "Input means" refers to a device or interface that allows a user to provide specific information to a system, including a keyboard, touch screen, or voice recognition system.

[0008] "Means of analysis" refers to the techniques and algorithms used to interpret input data and classify it into specific meanings or categories.

[0009] "Emotional data" refers to text and numerical data that specifically expresses the emotional and stress information entered by the user into the system.

[0010] "Natural language processing technology" refers to the techniques and processes used to enable computers to understand and analyze human language.

[0011] "Artwork" refers to visual works such as designs and paintings that are generated based on the user's emotional data.

[0012] "Generative means" refers to technologies or algorithms that create new digital content or designs based on specific input data.

[0013] "Means for displaying" refers to a display device or other presentation technology for presenting the generated digital content or information to a user.

[0014] "Sentiments" refers to opinions or feelings that users have after viewing the displayed artwork, including positive or negative reactions.

[0015] "Mental care information" refers to specific advice and information to support users' mental health and stress management. [Brief explanation of the drawings]

[0016] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0017] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0018] First, the terms used in the following description will be explained.

[0019] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0020] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0021] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0022] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0024] [First embodiment]

[0025] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0026] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0027] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0029] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0032] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0036] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0037] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The following describes in detail the embodiments of the present invention.

[0038] This system generates artwork based on the user's emotional data to support mental care. The system mainly includes the following components: emotion input means, emotion analysis means, artwork generation means, artwork display means, impression input means, impression analysis means, and mental care information provision means.

[0039] System flow

[0040] 1. User emotion input

[0041] Users can input negative emotions and stress factors they are feeling at that time in text format into the device, for example, "I'm feeling stressed because of work pressure."

[0042] 2. Sending Emotional Data

[0043] The device sends the entered text data to the server, which receives the data and prepares it for analysis.

[0044] 3. Emotion analysis

[0045] The server passes the text data to a natural language processing (NLP) engine for analysis. The analysis extracts the main emotional categories and their intensity from the data. For example, if the data contains keywords such as "pressure" or "stress," an emotional score is calculated for each.

[0046] 4. Artwork generation

[0047] The server generates artwork based on the analysis results. It selects appropriate colors and shapes based on the emotion category and intensity, generating digital art. For example, if the user is feeling stressed, it selects bright red or yellow colors and sharp shapes to visualize the user's emotions.

[0048] 5. Artwork display

[0049] The generated artwork is sent from the server to the device, which displays it to the user, allowing the user to visually confirm their own emotions and record their reactions.

[0050] 6. User feedback

[0051] The user then inputs their impressions and positive feelings into the terminal after viewing the displayed artwork. For example, they might write something like, "Looking at this artwork helped me relax a little."

[0052] 7. Analysis of impressions and provision of mental health information

[0053] The device sends the user's impression data to the server. The server then analyzes the impression data again to understand the user's emotional state. The server then generates appropriate mental care information to help improve the user's emotions and sends it to the device. The device displays this information to the user to support further mental care.

[0054] Specific examples

[0055] For example, if a working user types, "I've been under a lot of pressure at work lately," this text data is sent from the device to the server, which uses an NLP engine to analyze the emotion keywords "pressure" and "stress" and calculates the corresponding emotion score.

[0056] The server then generates artwork based on the emotion score, choosing shades of red and yellow, sharp shapes, and applying design patterns, which are then sent to the user's device for viewing.

[0057] After viewing the artwork, the user inputs their impression, such as, "Looking at this artwork helped me relax a little." This impression data is sent back to the server, where it is analyzed and specific mental care information that will help them relax is generated and provided to the user.

[0058] In this way, users can easily express their feelings without any specialized knowledge or skills, and by obtaining appropriate mental care information, they can reduce stress and negative emotions.

[0059] The processing flow will be explained below.

[0060] Step 1:

[0061] The user enters their feelings and the causes of stress into the device in text format. For example, they might enter "I'm under a lot of pressure at work."

[0062] Step 2:

[0063] The terminal sends the entered text data to the server, using a communication protocol to ensure that the user's input is transmitted to the server accurately.

[0064] Step 3:

[0065] The server passes the received text data to a natural language processing (NLP) engine to begin analysis. The NLP engine extracts emotion categories (e.g., stress, pressure) and their intensity (numerical scores) from the text data.

[0066] Step 4:

[0067] The server then activates an artwork generation algorithm based on the emotion category and intensity obtained from the NLP engine. For example, if stress is detected as high, it will select stimulating colors like red and yellow and sharp shapes.

[0068] Step 5:

[0069] The server generates digital art using appropriate colors and shapes based on the emotion category and intensity, and the generated artwork is saved in image format.

[0070] Step 6:

[0071] The server transmits the generated artwork image data to the terminal and packages the data in a format that can be accessed by the user.

[0072] Step 7:

[0073] The device displays the received artwork to the user, who can then visually see the artwork that expresses their emotions.

[0074] Step 8:

[0075] The user then inputs their impressions and positive emotions after viewing the artwork into the device, for example, "Looking at this art made me feel a little relaxed."

[0076] Step 9:

[0077] The terminal transmits the user's impression data to the server using a communication protocol to ensure that the impression data is transmitted accurately.

[0078] Step 10:

[0079] The server analyzes the received data to identify changes in emotional state and trends in positive emotions, such as positive keywords like relaxation and a sense of security.

[0080] Step 11:

[0081] Based on the analysis results, the server generates useful mental care information for users (such as relaxation methods and stress management advice). The generated mental care information is stored in text format and link format.

[0082] Step 12:

[0083] The server transmits the generated mental care information to the terminal, packaging the data in a format that is easy for the user to access.

[0084] Step 13:

[0085] The device displays the received mental care information to the user, who can then practice further relaxation and stress management based on the mental care information.

[0086] Example 1

[0087] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0088] In modern society, the increase in stress and negative emotions caused by daily life and work has become a problem. This has led to a growing need for mental health care, but the difficulty of self-awareness and emotional expression makes effective care difficult. In particular, there are few systems that allow users to visually check their own emotions and obtain appropriate mental health care information. Safe handling of emotional and impression data is also an important issue.

[0089] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0090] In this invention, the server includes means for inputting a user's emotions in text format, means for securely transmitting the input emotion data to the server, means for analyzing the transmitted emotion data using natural language processing technology, means for generating artwork using a generative AI model based on the analyzed emotion data, means for displaying the generated artwork to the user, means for inputting the user's impressions, and means for re-analyzing the input emotion data and providing mental care information, thereby enabling the user to visually confirm their own emotions and obtain appropriate mental care information.

[0091] A "user" is someone who uses the system to input their own emotions and receive artwork and mental care information.

[0092] The "means for inputting emotions in text format" is an interface that allows a user to input their own emotions and stress factors as text information.

[0093] "Means for securely transmitting input emotion data to a server" refers to a function that transmits the emotion text data input by the user to a server using a secure communication method (e.g., HTTPS).

[0094] "Means for analyzing using natural language processing technology" refers to technology (e.g., a natural language processing engine) used to analyze the text data received by the server and extract the main emotional categories and intensity of the emotions.

[0095] "Means for generating artwork using a generative AI model" refers to an artificial intelligence model (e.g., image generation AI) for automatically generating digital art based on the results of sentiment analysis.

[0096] The "means for displaying the generated artwork to the user" is a function for displaying the artwork sent from the server on the user terminal.

[0097] The "means for inputting user's impressions" is an interface that allows the user to re-input their impressions and feelings about the displayed artwork.

[0098] The "means for re-analyzing input impression data and providing mental care information" is a function that analyzes the impression data input by the user again, grasps the user's emotional state, and then generates and provides appropriate mental care information.

[0099] An "emotion category" is a category for classifying the user's emotions (e.g., pressure, stress).

[0100] "Emotion Intensity" is a score that quantifies the strength of the emotion the user is feeling.

[0101] A "secure connection" is an encrypted communication method used to securely send and receive data between a device and a server.

[0102] The present invention provides a system for supporting mental health care by generating artwork based on a user's emotional data. The system mainly includes the following components: an emotion input means, an emotion analysis means, an artwork generation means, an artwork display means, an impression input means, an impression analysis means, and a mental health care information provision means.

[0103] System Configuration

[0104] The hardware required to implement the system includes the device used by the user (e.g., smartphone, PC) and the server that processes and manages the data. The software uses a natural language processing engine (e.g., Google® NLP API) and a generative AI model (e.g., DALL-E).

[0105] Processing flow

[0106] First, the user enters the negative emotions or stressors they are currently experiencing into the device in text format. For example, they might enter, "I'm feeling stressed because of work pressure."

[0107] The device then sends the entered text data to the server using a secure connection (e.g., HTTPS), and notifies the user whether the transmission was successful.

[0108] The server cleans the received text data and passes it to a natural language processing engine for analysis, which extracts major emotional categories (e.g., pressure, stress) and emotional intensities (scores) from the data.

[0109] The server then uses a generative AI model to generate artwork based on the emotion analysis—for example, choosing vibrant colors like red and yellow and sharp shapes when stress levels are high—and the artwork is generated digitally.

[0110] The generated artwork is sent from the server to the device, which then displays it to the user. After viewing the artwork, the user can input their impressions and positive emotions into the device. For example, they can input a comment like, "Looking at this art made me feel a little more relaxed."

[0111] The user's impression data is sent back to the server, which analyzes it again. This analysis allows the server to understand the user's emotional state and generate appropriate mental care information. The generated mental care information is then sent to the user's device and displayed to the user.

[0112] Specific examples

[0113] A working user types, "I've been under a lot of pressure at work lately." This text data is sent from the device to a server, which uses a natural language processing engine to analyze the emotion keywords "pressure" and "stress" and calculates an emotion score.

[0114] The server then uses a generative AI model to generate artwork with sharp shapes in red and yellow tones based on the emotion scores, and the artwork is sent to the user's device for viewing.

[0115] The user inputs their impression, such as, "Looking at this art helped me relax a little." This impression data is sent back to the server, where it is analyzed and specific advice on how to relax is generated and provided to the user's device.

[0116] Prompt Sentence Examples

[0117] "I'm feeling the pressure. Visualize how it feels."

[0118] "Look at this art and tell us how it makes you feel so we can provide you with helpful care information for next time."

[0119] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0120] Step 1:

[0121] The user inputs their emotions in text format. For example, they input a sentence such as "I feel stressed because of work pressure" into the device interface. Input: User's emotion text data. Output: Emotion text data saved on the device.

[0122] Step 2:

[0123] The device sends the entered text data to the server using a secure connection. HTTPS is used to protect the data when it is sent. Input: Emotion text data stored on the device. Output: Emotion text data sent to the server.

[0124] Step 3:

[0125] The server stores the received text data and performs data cleaning. Preprocessing is performed to remove unnecessary spaces and special characters. Input: Emotion text data sent to the server. Output: Cleaned emotion text data stored on the server.

[0126] Step 4:

[0127] The server passes the cleaned text data to a natural language processing engine for sentiment analysis. The analysis extracts the main sentiment categories and their numerical values ​​of sentiment intensity. Input: Cleaned sentiment text data. Output: Sentiment categories and sentiment intensity as analysis results.

[0128] Step 5:

[0129] The server uses a generative AI model based on the results of emotion analysis to generate artwork. For example, if the emotion intensity is high, it will use red and yellow colors and generate artwork with sharp shapes. Input: Emotion category and emotion intensity. Output: Generated digital artwork.

[0130] Step 6:

[0131] The server sends the generated artwork to the device. The device displays the received artwork to the user in a dedicated viewer. Input: Generated digital artwork. Output: Artwork displayed on the device.

[0132] Step 7:

[0133] The user inputs their impressions after viewing the artwork in text format into the device. For example, they might input "Looking at this art made me feel a little relaxed." Input: User's impression text data. Output: Impression text data saved on the device.

[0134] Step 8:

[0135] The device sends the user's feedback data to the server using a secure connection. Input: Feedback text data stored on the device. Output: Feedback text data sent to the server.

[0136] Step 9:

[0137] The server passes the received sentiment data to the natural language processing engine for further analysis. Emotion categories and emotional intensities are extracted to understand the user's current emotional state. Input: sentiment text data sent to the server. Output: Emotional state as the analysis result.

[0138] Step 10:

[0139] The server generates appropriate mental care information based on the analysis results and sends it to the device. The device displays the received mental care information to the user. Input: Emotional state as the analysis result. Output: Mental care information displayed on the device.

[0140] (Application example 1)

[0141] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0142] There is a need for a method to effectively alleviate users' stress and negative emotions and support their mental health. However, current mental health services lack a mechanism for providing instant and personalized care based on a user's emotional analysis. They also lack a method for visually expressing emotions and thereby improving the user's psychological state. Furthermore, there is a need for an efficient means for providing such care to multiple users individually.

[0143] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0144] In this invention, the server includes a means for inputting a user's emotions, a means for analyzing the input emotion data, and a means for generating artwork based on the analyzed emotion data. This allows users to visually check their own emotions in real time and instantly obtain optimal mental care information based on the results. Furthermore, by including a means for distributing the artwork and mental care information generated based on the emotion data, it becomes possible to provide care efficiently and individually to multiple users.

[0145] The "means for inputting user's emotions" is an interface that allows the user to input their own emotions and situations into the system in text format.

[0146] The "means for analyzing input emotional data" is a mechanism for analyzing the emotional data input by the user using natural language processing and machine learning techniques, and extracting emotional categories and their intensities.

[0147] The "means for generating artwork based on analyzed emotional data" refers to an algorithm or program that selects appropriate colors and shapes based on emotional analysis and generates digital art.

[0148] The "means for displaying the generated artwork to the user" refers to a display device or software that displays the generated digital art on the user's terminal, allowing the user to visually confirm it.

[0149] The "means for inputting user impressions" is an interface that allows the user to re-input impressions and feelings that they had after viewing the displayed artwork.

[0150] The "means for analyzing inputted impression data and providing mental care information" is a system that analyzes the user's impression data to re-understand the emotional state, and generates and provides appropriate mental care information.

[0151] "Means for distributing artwork and mental care information generated based on emotional data" refers to a network or communication means for distributing the generated digital art and mental care information to users and providing care individually to multiple users.

[0152] "Natural language processing technology" is a technology for mechanically analyzing text data and extracting structured information.

[0153] An "emotion category" is a type of emotion classified based on analyzed emotion data.

[0154] "Emotion intensity" is an index that indicates the strength or degree of an emotion in the analyzed emotion category.

[0155] The present invention provides details of a system for supporting mental care by generating artwork based on a user's emotional data. An embodiment of the system will be described below.

[0156] Overall system configuration

[0157] The system mainly consists of the following components:

[0158] 1. A way to input user emotions

[0159] Users use a device such as a smartphone to input their feelings into the system in text format, such as "I've been feeling a lot of pressure at work lately."

[0160] 2. A method for analyzing input emotion data

[0161] Emotional text data sent from the device is passed to a server, where it is analyzed for emotional category and intensity using natural language processing (NLP) technology.

[0162] 3. A method for generating artwork based on analyzed emotion data

[0163] Based on the analysis of emotional data, appropriate colors and shapes are selected and digital art is generated using a generative AI model.

[0164] 4. A means of displaying the generated artwork to the user

[0165] The generated digital art is sent from the server to the terminal and displayed on the user's visual display device (smartphone display).

[0166] 5. A way to input user feedback

[0167] The user then enters their thoughts after viewing the displayed artwork in text format, for example, "Looking at this art made me feel a little relaxed."

[0168] 6. A means of analyzing inputted impression data and providing mental care information

[0169] The retransmitted impression data is analyzed by the server, and optimal mental care information is generated. This information is then sent to the user and displayed on their device.

[0170] 7. A means of delivering artwork and mental health information generated based on emotional data

[0171] The generated digital art and mental care information are distributed individually to multiple users.

[0172] Hardware and software used

[0173] Server: A server with high-performance computing power is used. This server is responsible for analyzing data and generating artwork.

[0174] Natural Language Processing (NLP) engine: For example, the Transformers library from Hugging Face is used.

[0175] Generative AI models: Built using machine learning frameworks such as TENSORFLOW (registered trademark) and PyTorch.

[0176] Smartphones: Used for users to input emotional data and display generated digital art and mental health information.

[0177] Data processing and calculation

[0178] 1. Emotion data analysis: The server uses a natural language processing engine to analyze the input text data and extract emotion categories and intensities.

[0179] 2. Artwork generation: Select colors and shapes based on the analysis results and generate appropriate digital art using a generative AI model.

[0180] 3. Analysis of impression data: The re-entered impression data is analyzed to understand the user's latest emotional state and provide appropriate mental care information.

[0181] Specific examples

[0182] If a user types, "I've been under a lot of pressure at work lately," this text data is sent from the device to the server. The NLP engine analyzes the emotional category of "stress" and extracts the corresponding intensity. The server selects red and sharp shapes and generates digital art using a generative AI model. The generated artwork is displayed on the smartphone for the user to visually confirm. If the user types, "Looking at this art helped me relax a bit," the impression data is sent again to the server, and appropriate mental care information is generated and displayed.

[0183] Prompt Sentence Examples

[0184] "The user has mentioned feeling stressed at work recently. Generate colorful, vivid digital art to visualize this emotion and provide appropriate mental health information."

[0185] In this way, users can receive help in effectively managing their emotions and relaxing through their smartphones.

[0186] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0187] Step 1:

[0188] The user inputs emotion data

[0189] The user uses a smartphone to input the emotions and stress factors they are feeling at that time in text format. For example, they might enter a sentence such as "I've been feeling a lot of pressure at work lately" into the smartphone's input form. This data is temporarily stored as text data on the device.

[0190] Input: Emotion text data entered by the user

[0191] Output: Emotion text data temporarily stored on the smartphone

[0192] Step 2:

[0193] Send emotion data to the server

[0194] The device sends the input emotion text data to a server via the Internet using a network protocol such as an HTTP POST request.

[0195] Input: Emotion text data sent from the device

[0196] Output: Emotion text data received by the server

[0197] Step 3:

[0198] The server analyzes the emotional data

[0199] The server passes the received emotion text data to a natural language processing (NLP) engine for analysis, specifically using Hugging Face's Transformers library to extract emotion categories (e.g., stress) and their intensity.

[0200] Input: Emotion text data received by the server

[0201] Output: Parsed emotion categories and their intensities

[0202] Step 4:

[0203] Generate artwork

[0204] The server generates digital art using a generative AI model (e.g., TensorFlow or PyTorch) based on the emotion category and its intensity obtained by the NLP engine, with color and shape determined by the emotion category.

[0205] Input: Parsed emotion category and its intensity

[0206] Output: Generated digital art data

[0207] Step 5:

[0208] Send the generated artwork to your device

[0209] The server then transmits the generated digital art data to the user's device via the Internet, again using the HTTP protocol.

[0210] Input: Generated digital art data

[0211] Output: Digital art data received on the device

[0212] Step 6:

[0213] View user-generated artwork

[0214] The user then views the digital art received on the device on a visual display device (smartphone display), thereby confirming the visualization of their own emotions.

[0215] Input: Digital art data displayed on the device

[0216] Output: Visual confirmation for the user

[0217] Step 7:

[0218] The user enters their feedback

[0219] After viewing the generated artwork, the user again enters their impressions in text format. For example, they might enter a comment like, "Looking at this art made me feel a little relaxed." This data is also temporarily stored on the device.

[0220] Input: User-entered text data

[0221] Output: Impression text data temporarily saved on the smartphone

[0222] Step 8:

[0223] Send the feedback data to the server

[0224] The terminal again transmits the input impression text data to the server via the Internet.

[0225] Input: Text data of impressions sent from the device

[0226] Output: Text data of the impressions received by the server

[0227] Step 9:

[0228] The server analyzes the opinion data

[0229] The server then passes the received impression text data back to the natural language processing (NLP) engine for analysis to grasp the user's latest emotional state.

[0230] Input: Text data of impressions received by the server

[0231] Output: Latest analyzed emotional state

[0232] Step 10:

[0233] Generates mental health information and provides it to users

[0234] The server generates appropriate mental care information based on the analyzed latest emotional state. This information is generated using a mental care database prepared in advance. The generated information is sent to the terminal via the Internet. The terminal receives this information and displays it to the user.

[0235] Input: Analyzed latest emotional state and mental care database

[0236] Output: Generated mental health information and its display

[0237] This allows users to effectively manage their emotions and receive appropriate mental health information.

[0238] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0239] The following describes in detail the embodiments of the present invention. The present invention is a system that recognizes and analyzes a user's emotions, generates artwork based on the analysis, and provides mental care information. In particular, the system is configured to incorporate an emotion engine for recognizing a user's emotions in real time.

[0240] The system includes the following main components:

[0241] Emotion input method

[0242] Emotion analysis means

[0243] Emotion Engine

[0244] Artwork Generation Method

[0245] Artwork display method

[0246] Comment input method

[0247] Impression analysis means

[0248] Means of providing mental health information

[0249] System flow

[0250] 1. User emotion input

[0251] The user inputs their feelings and stressors into the device in text format, for example, "I feel a lot of pressure at work."

[0252] 2. Sending Emotional Data

[0253] The device sends the input text data to the server, and the emotion engine uses this data to recognize emotions.

[0254] 3. Emotion Recognition by Emotion Engine

[0255] The server's emotion engine analyzes the transmitted text, voice, and even the user's facial expression data to recognize the emotion category (e.g., stress, pressure) and its intensity (numerical score) in real time. For example, if the user enters "tired," it will recognize the emotion as "fatigue." It also obtains complementary emotion data from the user's voice and facial expressions.

[0256] 4. Emotion analysis

[0257] The emotion data recognized by the emotion engine is further analyzed in detail by the server to identify the user's current emotional state.

[0258] 5. Artwork generation

[0259] The server then activates an artwork generation algorithm based on the emotion analysis results. For example, if the intensity of "stress" is high, it will select stimulating colors like red and yellow and sharp shapes to generate digital art.

[0260] 6. Artwork display

[0261] The server sends image data of the generated artwork to the device, which then displays the received artwork to the user, allowing the user to visually view the artwork that expresses their own emotions.

[0262] 7. User feedback

[0263] The user then inputs their impressions and positive emotions into the device after viewing the artwork. For example, they might input, "Looking at this art made me feel a little relaxed."

[0264] 8. Sending and analyzing feedback data

[0265] The device sends the user's impression data to the server, which then analyzes the received impression data to identify changes in the user's emotional state and trends in positive emotions. For example, it analyzes the keyword "relaxation."

[0266] 9. Providing mental health care information

[0267] Based on the analysis results, the server generates useful mental care information for the user (advice on relaxation methods and stress management). The generated mental care information is sent to the user's device and displayed to the user. Based on this, the user can practice further relaxation and stress management.

[0268] Specific examples

[0269] For example, if a user types "I've been feeling a lot of pressure at work lately," this text data is sent from the device to the server. The emotion engine then recognizes emotions such as "pressure" and "stress" in real time and evaluates their intensity. Furthermore, the user's facial expressions and voice data are also used for analysis.

[0270] The server generates digital art using colors such as red and yellow and sharp shapes based on the obtained emotional data, and sends this artwork to the user's device. The user looks at the displayed artwork and inputs their impression, such as "Looking at this art made me feel a little relaxed."

[0271] Finally, the server analyzes this data again to generate mental care information that will help users relax and send it to their device. In this way, users can easily express their feelings and obtain appropriate mental care information to maintain their mental health, even without specialized knowledge or skills.

[0272] The processing flow will be explained below.

[0273] Step 1:

[0274] The user enters their feelings and the causes of stress into the device in text format. For example, they might enter "I'm under a lot of pressure at work."

[0275] Step 2:

[0276] The terminal sends the entered text data to the server, using a communication protocol to ensure the data is sent reliably.

[0277] Step 3:

[0278] The server passes the received text data to the emotion engine and begins analysis. The emotion engine uses natural language processing technology to analyze the input text and recognize emotion categories (e.g., "stress") and their intensity (numerical score).

[0279] Step 4:

[0280] The emotion engine simultaneously analyzes the user's facial expression and voice data and recognizes emotions from these data, improving the accuracy of emotion category and intensity recognition.

[0281] Step 5:

[0282] The server uses the emotion data obtained from the emotion engine to activate an artwork generation algorithm. Based on the analysis results, it selects appropriate colors and shapes to generate digital art. For example, if the intensity of "stress" is high, it selects stimulating colors like red and yellow and sharp shapes.

[0283] Step 6:

[0284] The server saves the generated artwork in image format and sends the data to the terminal, using a communication protocol to ensure that the image data is transferred accurately.

[0285] Step 7:

[0286] The device displays the received artwork to the user, allowing the user to visually confirm the artwork that expresses their emotions.

[0287] Step 8:

[0288] After viewing the artwork, the user again inputs their impressions and positive emotions into the device, for example, "Looking at this art made me feel a little relaxed."

[0289] Step 9:

[0290] The terminal transmits the user's impression data to the server using a communication protocol to ensure that the impression data is transmitted accurately.

[0291] Step 10:

[0292] The server then passes the received impression data back to the emotion engine, which analyzes changes in the emotional state and trends in positive emotions. For example, it checks whether the keyword "relaxed" is included.

[0293] Step 11:

[0294] Based on the analysis results, the server generates useful mental care information for the user, such as advice on relaxation techniques and stress management.

[0295] Step 12:

[0296] The server transmits the generated mental care information to the terminal, using a communication protocol to ensure reliable data transfer.

[0297] Step 13:

[0298] The device then displays the received mental care information to the user, who can then use the information to further relax and manage stress.

[0299] Example 2

[0300] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0301] In modern society, many people suffer from stress and emotional burdens, and managing and caring for these stressors is becoming increasingly important. However, there are few systems that can accurately recognize these emotions in real time and provide appropriate mental care information based on that information. Therefore, there is a need for a system that allows users to easily input their own emotional state, have it analyzed, and provide appropriate coping strategies. Furthermore, expressing emotions through visual means and receiving feedback based on those emotions is expected to lead to more effective mental care.

[0302] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0303] In this invention, the server includes a means for transmitting user emotion data to the server, a means for analyzing the emotion data received by the server using a natural language processing algorithm, and a means for generating artwork based on the analyzed emotion data. This allows the emotion data input by the user to be analyzed, and artwork generated based on the analysis results to be quickly provided to the user. As a result, the user can visually understand their own emotions and receive individually customized mental care information.

[0304] "User" refers to a person who uses this system to input emotion data and impression data.

[0305] "Terminal" refers to the electronic device used by the User to input emotional and / or impression data and to receive and display artwork and mental health information.

[0306] The term "server" refers to a remote computer system that analyzes the received emotional and impression data and generates artwork and mental care information.

[0307] "Emotion data" refers to data entered by a user in text format about their emotions and the causes of stress.

[0308] A "natural language processing algorithm" refers to a computational method for analyzing emotional data and recognizing the emotional categories and intensity contained within it.

[0309] "Emotion category" refers to the type of emotion (e.g., "stress" or "pressure") classified as a result of analyzing emotion data.

[0310] "Intensity" refers to a numerical representation of the strength of an emotion for a particular emotion category.

[0311] "Artwork" refers to visual content (images) generated based on analyzed emotional data.

[0312] "Opinion data" refers to data entered by a user in text format as their impressions or feedback on the displayed artwork.

[0313] "Mental care information" refers to information such as advice on relaxation methods and stress management that is generated based on the analyzed impression data and provided to the user.

[0314] The system of the present invention recognizes and analyzes the user's emotions in real time, and generates artwork based on the results to provide mental care information. This system is implemented mainly using the following hardware and software.

[0315] Hardware and software used

[0316] Device: Used by users to input and send emotional and sentiment data, and to receive and display artwork and mental health information. Examples include smartphones, tablets, and PCs.

[0317] Server: A computer system that receives and analyzes emotional and impression data, and generates and transmits artwork and mental care information.

[0318] Natural language processing algorithms: Software techniques used to analyze user sentiment data, for example, NLP libraries implemented in Python.

[0319] Generative AI model: An algorithm that uses machine learning techniques to generate artwork based on sentiment analysis results.

[0320] Example of a system

[0321] For example, if a user types "I've been under a lot of pressure at work lately," this text data is sent from the device to the server. The server then uses an emotion engine to recognize emotions such as "pressure" and "stress" in real time and evaluate their intensity. Furthermore, the user's facial expressions and voice data are also used for analysis.

[0322] The server generates digital art using colors such as red and yellow and sharp shapes based on the obtained emotional data, and sends this artwork to the user's device. The user looks at the displayed artwork and inputs their impression, such as "Looking at this art made me feel a little relaxed."

[0323] Finally, the server analyzes this feedback data, generates mental care information that will help users relax, and sends it to the user's device. Based on the displayed advice, users can practice further relaxation and stress management.

[0324] Prompt Sentence Examples

[0325] "Describe a system that recognizes and analyzes a user's emotions, generates artwork based on the user's emotional state, and displays the results to the user."

[0326] The system of the present invention allows users to easily express their feelings and obtain appropriate mental care information to maintain their mental health, even without specialized knowledge or skills.

[0327] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0328] Step 1:

[0329] The user inputs emotion data into the terminal. Specifically, the user inputs emotion or stress factors such as "I've been under a lot of pressure at work lately" into a text input field on the terminal.

[0330] Input: User's text data

[0331] Output: Text information entered into the terminal

[0332] Step 2:

[0333] The device sends the input emotion data to the server. When the user taps the "Send" button, the device generates an HTTP request and sends the text data to the server.

[0334] Input: Text information entered into the device

[0335] Output: Text data sent to the server

[0336] Step 3:

[0337] The server analyzes the received text data using a natural language processing algorithm. The server uses an NLP library to analyze the text and calculates an emotion category (e.g., "stress" or "pressure") and its intensity score.

[0338] Input: Text data sent

[0339] Output: Emotion category and its intensity score

[0340] Step 4:

[0341] The server performs a detailed analysis of the acquired emotional data. It compares it with past emotional data and analyzes changes and patterns in the user's emotions. For example, it evaluates whether the intensity of pressure has increased over the past few days.

[0342] Input: Emotion categories and their intensity scores

[0343] Output: Detailed analysis results

[0344] Step 5:

[0345] The server then uses a generative AI model to generate artwork based on the analysis results. Based on the emotion category and its intensity, the generative AI model selects colors and shapes to generate digital art. For example, if the intensity of stress is high, stimulating colors like red and yellow will be used, and sharp shapes will be created.

[0346] Input: Detailed analysis results

[0347] Output: Image data of the generated artwork

[0348] Step 6:

[0349] The server sends the image data of the generated artwork to the terminal, and information including the image data is sent as an HTTP response.

[0350] Input: Image data of the generated artwork

[0351] Output: Image data sent to the device

[0352] Step 7:

[0353] The terminal displays the received artwork to the user. Specifically, the artwork is displayed full-screen on the terminal screen, allowing the user to enjoy it visually.

[0354] Input: Image data

[0355] Output: Artwork displayed on screen

[0356] Step 8:

[0357] The user inputs their thoughts after viewing the artwork into the device, for example, by typing "This art made me feel a little relaxed" into the text input field.

[0358] Input: User testimonial text

[0359] Output: Impression data entered into the terminal

[0360] Step 9:

[0361] The device sends the impression data to the server. When you enter your impression and tap the "Send" button, an HTTP request is generated and sent to the server.

[0362] Input: Impression data entered into the terminal

[0363] Output: Feedback data sent to the server

[0364] Step 10:

[0365] The server analyzes the sentiment data using a natural language processing algorithm to extract positive emotions and keywords, and evaluates changes in the user's emotional state.

[0366] Input: Impression data

[0367] Output: Changes in emotional state and evaluation results

[0368] Step 11:

[0369] The server generates mental care information based on the analysis results. Based on changes in emotional state and the evaluation results, it generates advice on relaxation methods and stress management, and creates mental care information to provide to the user.

[0370] Input: Emotional state changes and evaluation results

[0371] Output: Generated mental health information

[0372] Step 12:

[0373] The server sends the generated mental care information to the terminal, and data including the mental care information is sent as an HTTP response.

[0374] Input: Generated mental health information

[0375] Output: Mental health information sent to the device

[0376] Step 13:

[0377] The mental care information received by the device is displayed to the user. The mental care information is displayed on the device screen in the form of a dedicated widget or notification.

[0378] Input: Mental care information

[0379] Output: Mental health information displayed on the screen

[0380] (Application example 2)

[0381] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0382] In modern society, stress and pressure affect many people. However, there are limited systems that can identify an individual's emotional state in real time and provide appropriate mental health care information based on that information. Even if emotion recognition systems exist, there is a lack of a way to input emotions without requiring the user's effort or to provide visual feedback of emotions.

[0383] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for inputting a user's emotions in voice or text format, means for analyzing the input emotional data, means for generating artwork based on the analyzed emotional data, means installed in the smart device for displaying the generated artwork to the user, means for inputting the user's impressions, and means for analyzing the input impression data and providing mental care information. This allows the user to easily input their emotional state via the smart device and receive appropriate mental care information in real time based on the analysis results.

[0384] "A means for inputting emotions in voice or text format" refers to a device or software that has the function of allowing a user to input emotions as voice or text data.

[0385] "Means for analyzing emotional data" refers to devices or software that have the function of analyzing input emotional data using algorithms or AI models and identifying the type and intensity of emotions.

[0386] "Means for generating artwork" refers to devices or software that have the function of creating digital art using specific colors and shapes based on analyzed emotional data.

[0387] "Means installed on a smart device" means a device or software installed on smart glasses or other wearable devices that has the ability to display generated artwork or mental health information to the user.

[0388] The "means for inputting user's impressions" refers to a device or software that has a function that allows the user to re-input impressions or genetic emotions after viewing the generated artwork.

[0389] "Means for analyzing input impression data and providing mental care information" refers to a device or software that has the function of analyzing the user's impression data and generating and providing useful mental care information to the user based on the results.

[0390] The "means for converting voice input into text format" refers to a device or software that has the function of automatically converting a user's voice data into text data.

[0391] A "cloud-based AI model" is an algorithm or software that accesses a cloud server via the internet and uses artificial intelligence technology to perform data analysis and emotion recognition.

[0392] A "means for generating prompt sentences" is a device or software that has the function of enabling an AI model to generate appropriate prompt sentences or responses based on input data from a user.

[0393] The present invention will be described in detail below with reference to an embodiment thereof. This system allows a user to input their emotions in the form of voice or text, analyzes the data in real time, generates artwork, and provides mental health information to the user.

[0394] Hardware and software used

[0395] The system includes the following hardware and software:

[0396] Smart devices (smart glasses, smartphones, etc.)

[0397] Voice Recognition Software

[0398] Text Analysis Software

[0399] Cloud Server

[0400] AI model (generative AI model)

[0401] Digital Art Generation Software

[0402] Display

[0403] System flow

[0404] 1. Emotion Input

[0405] Users can input their emotions using the voice input function of their smart device, for example, by speaking, "I've been feeling pressure at work lately," or by typing in text, "I've been feeling stressed lately."

[0406] 2. Speech-to-text conversion

[0407] When voice input is performed, the voice recognition software in the device converts the voice data into text data, which is then sent to a cloud server.

[0408] 3. Emotion analysis

[0409] The cloud server analyzes the received text data and uses a generative AI model to identify the type of emotion (e.g., stress, pressure) and its intensity. The analyzed emotion data is then sent back to the smart device.

[0410] 4. Artwork generation

[0411] The smart device generates digital art based on the emotion analysis results. For example, if the stress level is high, artwork using red and yellow colors and sharp shapes will be generated. This artwork visually represents the user's emotions.

[0412] 5. Artwork display

[0413] The generated digital art is displayed on the smart device's display, allowing the user to visually appreciate the artwork.

[0414] 6. Input your thoughts

[0415] The user then re-enters their thoughts and positive emotions after viewing the displayed artwork. For example, they might enter text such as, "Looking at this art made me feel a little relaxed."

[0416] 7. Analysis of impressions and provision of mental health information

[0417] The cloud server then analyzes the sentiment data again to identify changes in the user's emotional state and trends in positive emotions. This information is then used to generate useful mental health information for the user, which is then sent to the user's smart device. For example, advice such as "Take a deep breath. It's important to take time to relax" is provided.

[0418] Specific examples

[0419] For example, if a user types, "I've been feeling pressure at work lately," the speech is converted into text, and the cloud server identifies emotions such as "pressure" and "stress" and evaluates their intensity. Based on this data, the smart device generates digital art with red and yellow colors and sharp shapes and displays it to the user. The user then types their impression, such as "Looking at this art made me feel a little more relaxed," and the cloud server analyzes the data and provides mental care information such as "Take a deep breath."

[0420] Example prompt sentence:

[0421] "I've been feeling a lot of pressure at work lately. I'd like to relax a bit."

[0422] In this way, this system allows users to effectively express their emotions and provides appropriate mental care information based on those emotions.

[0423] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0424] Step 1:

[0425] A user inputs their emotions in the form of voice or text using a smart device. For example, they can say or type, "I've been feeling pressure at work lately." This is input data, which is collected as voice data or text data.

[0426] Step 2:

[0427] The device's voice recognition software converts voice data into text data. If the input is voice, the voice recognition software analyzes the voice and outputs it as text data. In this case, the input is voice data and the output is text data.

[0428] Step 3:

[0429] The device sends the converted text data to the cloud server using a data communication protocol. The input is text data, and the output is data sent to the server.

[0430] Step 4:

[0431] The cloud server performs emotion analysis on the received text data using a generative AI model. The generative AI model analyzes the text and identifies the type of emotion (e.g., stress, pressure) and its intensity. The input is text data, and the output is emotion data (type and intensity of emotion).

[0432] Step 5:

[0433] The server sends the analyzed emotion data to the smart device using a data communication protocol. The input is emotion data, and the output is data sent to the device.

[0434] Step 6:

[0435] The device generates digital art based on the emotion analysis results. Digital art generation software analyzes the emotion data and generates artwork with appropriate colors and shapes. The input is emotion data, and the output is digital art data.

[0436] Step 7:

[0437] The terminal displays the generated digital art on a display, allowing the user to visually appreciate the artwork. The input is digital art data, and the output is a display of the artwork.

[0438] Step 8:

[0439] The user then inputs his or her impressions after viewing the displayed artwork. For example, the user may input text such as "Looking at this artwork helped me to relax a little." This is the input of new impression data.

[0440] Step 9:

[0441] The device sends user feedback data to the cloud server. The input is the feedback data, and the output is the data sent to the server.

[0442] Step 10:

[0443] The cloud server analyzes the input impression data and analyzes changes in emotional state and trends in positive emotions. The generative AI model analyzes the impression data and generates mental care information. The input is impression data, and the output is mental care information.

[0444] Step 11:

[0445] The server sends the generated mental care information to the smart device and displays it to the user. For example, advice such as "Take a deep breath. It's important to take time to relax" is displayed. The input is the mental care information, and the output is the display to the user.

[0446] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0447] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0448] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0449] [Second embodiment]

[0450] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0451] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0452] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0453] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0454] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0455] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0456] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0457] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0458] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0459] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0460] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0461] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0462] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The following describes in detail the embodiments of the present invention.

[0463] This system generates artwork based on the user's emotional data to support mental care. The system mainly includes the following components: emotion input means, emotion analysis means, artwork generation means, artwork display means, impression input means, impression analysis means, and mental care information provision means.

[0464] System flow

[0465] 1. User emotion input

[0466] Users can input negative emotions and stress factors they are feeling at that time in text format into the device, for example, "I'm feeling stressed because of work pressure."

[0467] 2. Sending Emotional Data

[0468] The device sends the entered text data to the server, which receives the data and prepares it for analysis.

[0469] 3. Emotion analysis

[0470] The server passes the text data to a natural language processing (NLP) engine for analysis. The analysis extracts the main emotional categories and their intensity from the data. For example, if the data contains keywords such as "pressure" or "stress," an emotional score is calculated for each.

[0471] 4. Artwork generation

[0472] The server generates artwork based on the analysis results. It selects appropriate colors and shapes based on the emotion category and intensity, generating digital art. For example, if the user is feeling stressed, it selects bright red or yellow colors and sharp shapes to visualize the user's emotions.

[0473] 5. Artwork display

[0474] The generated artwork is sent from the server to the device, which displays it to the user, allowing the user to visually confirm their own emotions and record their reactions.

[0475] 6. User feedback

[0476] The user then inputs their impressions and positive feelings into the terminal after viewing the displayed artwork. For example, they might write something like, "Looking at this artwork helped me relax a little."

[0477] 7. Analysis of impressions and provision of mental health information

[0478] The device sends the user's impression data to the server. The server then analyzes the impression data again to understand the user's emotional state. The server then generates appropriate mental care information to help improve the user's emotions and sends it to the device. The device displays this information to the user to support further mental care.

[0479] Specific examples

[0480] For example, if a working user types, "I've been under a lot of pressure at work lately," this text data is sent from the device to the server, which uses an NLP engine to analyze the emotion keywords "pressure" and "stress" and calculates the corresponding emotion score.

[0481] The server then generates artwork based on the emotion score, choosing shades of red and yellow, sharp shapes, and applying design patterns, which are then sent to the user's device for viewing.

[0482] After viewing the artwork, the user inputs their impression, such as, "Looking at this artwork helped me relax a little." This impression data is sent back to the server, where it is analyzed and specific mental care information that will help them relax is generated and provided to the user.

[0483] In this way, users can easily express their feelings without any specialized knowledge or skills, and by obtaining appropriate mental care information, they can reduce stress and negative emotions.

[0484] The processing flow will be explained below.

[0485] Step 1:

[0486] The user enters their feelings and the causes of stress into the device in text format. For example, they might enter "I'm under a lot of pressure at work."

[0487] Step 2:

[0488] The terminal sends the entered text data to the server, using a communication protocol to ensure that the user's input is transmitted to the server accurately.

[0489] Step 3:

[0490] The server passes the received text data to a natural language processing (NLP) engine to begin analysis. The NLP engine extracts emotion categories (e.g., stress, pressure) and their intensity (numerical scores) from the text data.

[0491] Step 4:

[0492] The server then activates an artwork generation algorithm based on the emotion category and intensity obtained from the NLP engine. For example, if stress is detected as high, it will select stimulating colors like red and yellow and sharp shapes.

[0493] Step 5:

[0494] The server generates digital art using appropriate colors and shapes based on the emotion category and intensity, and the generated artwork is saved in image format.

[0495] Step 6:

[0496] The server transmits the generated artwork image data to the terminal and packages the data in a format that can be accessed by the user.

[0497] Step 7:

[0498] The device displays the received artwork to the user, who can then visually see the artwork that expresses their emotions.

[0499] Step 8:

[0500] The user then inputs their impressions and positive emotions after viewing the artwork into the device, for example, "Looking at this art made me feel a little relaxed."

[0501] Step 9:

[0502] The terminal transmits the user's impression data to the server using a communication protocol to ensure that the impression data is transmitted accurately.

[0503] Step 10:

[0504] The server analyzes the received data to identify changes in emotional state and trends in positive emotions, such as positive keywords like relaxation and a sense of security.

[0505] Step 11:

[0506] Based on the analysis results, the server generates useful mental care information for users (such as relaxation methods and stress management advice). The generated mental care information is stored in text format and link format.

[0507] Step 12:

[0508] The server transmits the generated mental care information to the terminal, packaging the data in a format that is easy for the user to access.

[0509] Step 13:

[0510] The device displays the received mental care information to the user, who can then practice further relaxation and stress management based on the mental care information.

[0511] Example 1

[0512] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0513] In modern society, the increase in stress and negative emotions caused by daily life and work has become a problem. This has led to a growing need for mental health care, but the difficulty of self-awareness and emotional expression makes effective care difficult. In particular, there are few systems that allow users to visually check their own emotions and obtain appropriate mental health care information. Safe handling of emotional and impression data is also an important issue.

[0514] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0515] In this invention, the server includes means for inputting a user's emotions in text format, means for securely transmitting the input emotion data to the server, means for analyzing the transmitted emotion data using natural language processing technology, means for generating artwork using a generative AI model based on the analyzed emotion data, means for displaying the generated artwork to the user, means for inputting the user's impressions, and means for re-analyzing the input emotion data and providing mental care information, thereby enabling the user to visually confirm their own emotions and obtain appropriate mental care information.

[0516] A "user" is someone who uses the system to input their own emotions and receive artwork and mental care information.

[0517] The "means for inputting emotions in text format" is an interface that allows a user to input their own emotions and stress factors as text information.

[0518] "Means for securely transmitting input emotion data to a server" refers to a function that transmits the emotion text data input by the user to a server using a secure communication method (e.g., HTTPS).

[0519] "Means for analyzing using natural language processing technology" refers to technology (e.g., a natural language processing engine) used to analyze the text data received by the server and extract the main emotional categories and intensity of the emotions.

[0520] "Means for generating artwork using a generative AI model" refers to an artificial intelligence model (e.g., image generation AI) for automatically generating digital art based on the results of sentiment analysis.

[0521] The "means for displaying the generated artwork to the user" is a function for displaying the artwork sent from the server on the user terminal.

[0522] The "means for inputting user's impressions" is an interface that allows the user to re-input their impressions and feelings about the displayed artwork.

[0523] The "means for re-analyzing input impression data and providing mental care information" is a function that analyzes the impression data input by the user again, grasps the user's emotional state, and then generates and provides appropriate mental care information.

[0524] An "emotion category" is a category for classifying the user's emotions (e.g., pressure, stress).

[0525] "Emotion Intensity" is a score that quantifies the strength of the emotion the user is feeling.

[0526] A "secure connection" is an encrypted communication method used to securely send and receive data between a device and a server.

[0527] The present invention provides a system for supporting mental health care by generating artwork based on a user's emotional data. The system mainly includes the following components: an emotion input means, an emotion analysis means, an artwork generation means, an artwork display means, an impression input means, an impression analysis means, and a mental health care information provision means.

[0528] System Configuration

[0529] The hardware required to implement the system includes the devices used by users (e.g., smartphones, PCs) and the server that processes and manages the data. The software uses a natural language processing engine (e.g., Google NLP API) and a generative AI model (e.g., DALL-E).

[0530] Processing flow

[0531] First, the user enters the negative emotions or stressors they are currently experiencing into the device in text format. For example, they might enter, "I'm feeling stressed because of work pressure."

[0532] The device then sends the entered text data to the server using a secure connection (e.g., HTTPS), and notifies the user whether the transmission was successful.

[0533] The server cleans the received text data and passes it to a natural language processing engine for analysis, which extracts major emotional categories (e.g., pressure, stress) and emotional intensities (scores) from the data.

[0534] The server then uses a generative AI model to generate artwork based on the emotion analysis—for example, choosing vibrant colors like red and yellow and sharp shapes when stress levels are high—and the artwork is generated digitally.

[0535] The generated artwork is sent from the server to the device, which then displays it to the user. After viewing the artwork, the user can input their impressions and positive emotions into the device. For example, they can input a comment like, "Looking at this art made me feel a little more relaxed."

[0536] The user's impression data is sent back to the server, which analyzes it again. This analysis allows the server to understand the user's emotional state and generate appropriate mental care information. The generated mental care information is then sent to the user's device and displayed to the user.

[0537] Specific examples

[0538] A working user types, "I've been under a lot of pressure at work lately." This text data is sent from the device to a server, which uses a natural language processing engine to analyze the emotion keywords "pressure" and "stress" and calculates an emotion score.

[0539] The server then uses a generative AI model to generate artwork with sharp shapes in red and yellow tones based on the emotion scores, and the artwork is sent to the user's device for viewing.

[0540] The user inputs their impression, such as, "Looking at this art helped me relax a little." This impression data is sent back to the server, where it is analyzed and specific advice on how to relax is generated and provided to the user's device.

[0541] Prompt Sentence Examples

[0542] "I'm feeling the pressure. Visualize how it feels."

[0543] "Look at this art and tell us how it makes you feel so we can provide you with helpful care information for next time."

[0544] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0545] Step 1:

[0546] The user inputs their emotions in text format. For example, they input a sentence such as "I feel stressed because of work pressure" into the device interface. Input: User's emotion text data. Output: Emotion text data saved on the device.

[0547] Step 2:

[0548] The device sends the entered text data to the server using a secure connection. HTTPS is used to protect the data when it is sent. Input: Emotion text data stored on the device. Output: Emotion text data sent to the server.

[0549] Step 3:

[0550] The server stores the received text data and performs data cleaning. Preprocessing is performed to remove unnecessary spaces and special characters. Input: Emotion text data sent to the server. Output: Cleaned emotion text data stored on the server.

[0551] Step 4:

[0552] The server passes the cleaned text data to a natural language processing engine for sentiment analysis. The analysis extracts the main sentiment categories and their numerical values ​​of sentiment intensity. Input: Cleaned sentiment text data. Output: Sentiment categories and sentiment intensity as analysis results.

[0553] Step 5:

[0554] The server uses a generative AI model based on the results of emotion analysis to generate artwork. For example, if the emotion intensity is high, it will use red and yellow colors and generate artwork with sharp shapes. Input: Emotion category and emotion intensity. Output: Generated digital artwork.

[0555] Step 6:

[0556] The server sends the generated artwork to the device. The device displays the received artwork to the user in a dedicated viewer. Input: Generated digital artwork. Output: Artwork displayed on the device.

[0557] Step 7:

[0558] The user inputs their impressions after viewing the artwork in text format into the device. For example, they might input "Looking at this art made me feel a little relaxed." Input: User's impression text data. Output: Impression text data saved on the device.

[0559] Step 8:

[0560] The device sends the user's feedback data to the server using a secure connection. Input: Feedback text data stored on the device. Output: Feedback text data sent to the server.

[0561] Step 9:

[0562] The server passes the received sentiment data to the natural language processing engine for further analysis. Emotion categories and emotional intensities are extracted to understand the user's current emotional state. Input: sentiment text data sent to the server. Output: Emotional state as the analysis result.

[0563] Step 10:

[0564] The server generates appropriate mental care information based on the analysis results and sends it to the device. The device displays the received mental care information to the user. Input: Emotional state as the analysis result. Output: Mental care information displayed on the device.

[0565] (Application example 1)

[0566] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0567] There is a need for a method to effectively alleviate users' stress and negative emotions and support their mental health. However, current mental health services lack a mechanism for providing instant and personalized care based on a user's emotional analysis. They also lack a method for visually expressing emotions and thereby improving the user's psychological state. Furthermore, there is a need for an efficient means for providing such care to multiple users individually.

[0568] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0569] In this invention, the server includes a means for inputting a user's emotions, a means for analyzing the input emotion data, and a means for generating artwork based on the analyzed emotion data. This allows users to visually check their own emotions in real time and instantly obtain optimal mental care information based on the results. Furthermore, by including a means for distributing the artwork and mental care information generated based on the emotion data, it becomes possible to provide care efficiently and individually to multiple users.

[0570] The "means for inputting user's emotions" is an interface that allows the user to input their own emotions and situations into the system in text format.

[0571] The "means for analyzing input emotional data" is a mechanism for analyzing the emotional data input by the user using natural language processing and machine learning techniques, and extracting emotional categories and their intensities.

[0572] The "means for generating artwork based on analyzed emotional data" refers to an algorithm or program that selects appropriate colors and shapes based on emotional analysis and generates digital art.

[0573] The "means for displaying the generated artwork to the user" refers to a display device or software that displays the generated digital art on the user's terminal, allowing the user to visually confirm it.

[0574] The "means for inputting user impressions" is an interface that allows the user to re-input impressions and feelings that they had after viewing the displayed artwork.

[0575] The "means for analyzing inputted impression data and providing mental care information" is a system that analyzes the user's impression data to re-understand the emotional state, and generates and provides appropriate mental care information.

[0576] "Means for distributing artwork and mental care information generated based on emotional data" refers to a network or communication means for distributing the generated digital art and mental care information to users and providing care individually to multiple users.

[0577] "Natural language processing technology" is a technology for mechanically analyzing text data and extracting structured information.

[0578] An "emotion category" is a type of emotion classified based on analyzed emotion data.

[0579] "Emotion intensity" is an index that indicates the strength or degree of an emotion in the analyzed emotion category.

[0580] The present invention provides details of a system for supporting mental care by generating artwork based on a user's emotional data. An embodiment of the system will be described below.

[0581] Overall system configuration

[0582] The system mainly consists of the following components:

[0583] 1. A way to input user emotions

[0584] Users use a device such as a smartphone to input their feelings into the system in text format, such as "I've been feeling a lot of pressure at work lately."

[0585] 2. A method for analyzing input emotion data

[0586] Emotional text data sent from the device is passed to a server, where it is analyzed for emotional category and intensity using natural language processing (NLP) technology.

[0587] 3. A method for generating artwork based on analyzed emotion data

[0588] Based on the analysis of emotional data, appropriate colors and shapes are selected and digital art is generated using a generative AI model.

[0589] 4. A means of displaying the generated artwork to the user

[0590] The generated digital art is sent from the server to the terminal and displayed on the user's visual display device (smartphone display).

[0591] 5. A way to input user feedback

[0592] The user then enters their thoughts after viewing the displayed artwork in text format, for example, "Looking at this art made me feel a little relaxed."

[0593] 6. A means of analyzing inputted impression data and providing mental care information

[0594] The retransmitted impression data is analyzed by the server, and optimal mental care information is generated. This information is then sent to the user and displayed on their device.

[0595] 7. A means of delivering artwork and mental health information generated based on emotional data

[0596] The generated digital art and mental care information are distributed individually to multiple users.

[0597] Hardware and software used

[0598] Server: A server with high-performance computing power is used. This server is responsible for analyzing data and generating artwork.

[0599] Natural Language Processing (NLP) engine: For example, the Transformers library from Hugging Face is used.

[0600] Generative AI models: These are built using machine learning frameworks such as TensorFlow and PyTorch.

[0601] Smartphones: Used for users to input emotional data and display generated digital art and mental health information.

[0602] Data processing and calculation

[0603] 1. Emotion data analysis: The server uses a natural language processing engine to analyze the input text data and extract emotion categories and intensities.

[0604] 2. Artwork generation: Select colors and shapes based on the analysis results and generate appropriate digital art using a generative AI model.

[0605] 3. Analysis of impression data: The re-entered impression data is analyzed to understand the user's latest emotional state and provide appropriate mental care information.

[0606] Specific examples

[0607] If a user types, "I've been under a lot of pressure at work lately," this text data is sent from the device to the server. The NLP engine analyzes the emotional category of "stress" and extracts the corresponding intensity. The server selects red and sharp shapes and generates digital art using a generative AI model. The generated artwork is displayed on the smartphone for the user to visually confirm. If the user types, "Looking at this art helped me relax a bit," the impression data is sent again to the server, and appropriate mental care information is generated and displayed.

[0608] Prompt Sentence Examples

[0609] "The user has mentioned feeling stressed at work recently. Generate colorful, vivid digital art to visualize this emotion and provide appropriate mental health information."

[0610] In this way, users can receive help in effectively managing their emotions and relaxing through their smartphones.

[0611] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0612] Step 1:

[0613] The user inputs emotion data

[0614] The user uses a smartphone to input the emotions and stress factors they are feeling at that time in text format. For example, they might enter a sentence such as "I've been feeling a lot of pressure at work lately" into the smartphone's input form. This data is temporarily stored as text data on the device.

[0615] Input: Emotion text data entered by the user

[0616] Output: Emotion text data temporarily stored on the smartphone

[0617] Step 2:

[0618] Send emotion data to the server

[0619] The device sends the input emotion text data to a server via the Internet using a network protocol such as an HTTP POST request.

[0620] Input: Emotion text data sent from the device

[0621] Output: Emotion text data received by the server

[0622] Step 3:

[0623] The server analyzes the emotional data

[0624] The server passes the received emotion text data to a natural language processing (NLP) engine for analysis, specifically using Hugging Face's Transformers library to extract emotion categories (e.g., stress) and their intensity.

[0625] Input: Emotion text data received by the server

[0626] Output: Parsed emotion categories and their intensities

[0627] Step 4:

[0628] Generate artwork

[0629] The server generates digital art using a generative AI model (e.g., TensorFlow or PyTorch) based on the emotion category and its intensity obtained by the NLP engine, with color and shape determined by the emotion category.

[0630] Input: Parsed emotion category and its intensity

[0631] Output: Generated digital art data

[0632] Step 5:

[0633] Send the generated artwork to your device

[0634] The server then transmits the generated digital art data to the user's device via the Internet, again using the HTTP protocol.

[0635] Input: Generated digital art data

[0636] Output: Digital art data received on the device

[0637] Step 6:

[0638] View user-generated artwork

[0639] The user then views the digital art received on the device on a visual display device (smartphone display), thereby confirming the visualization of their own emotions.

[0640] Input: Digital art data displayed on the device

[0641] Output: Visual confirmation for the user

[0642] Step 7:

[0643] The user enters their feedback

[0644] After viewing the generated artwork, the user again enters their impressions in text format. For example, they might enter a comment like, "Looking at this art made me feel a little relaxed." This data is also temporarily stored on the device.

[0645] Input: User-entered text data

[0646] Output: Impression text data temporarily saved on the smartphone

[0647] Step 8:

[0648] Send the feedback data to the server

[0649] The terminal again transmits the input impression text data to the server via the Internet.

[0650] Input: Text data of impressions sent from the device

[0651] Output: Text data of the impressions received by the server

[0652] Step 9:

[0653] The server analyzes the opinion data

[0654] The server then passes the received impression text data back to the natural language processing (NLP) engine for analysis to grasp the user's latest emotional state.

[0655] Input: Text data of impressions received by the server

[0656] Output: Latest analyzed emotional state

[0657] Step 10:

[0658] Generates mental health information and provides it to users

[0659] The server generates appropriate mental care information based on the analyzed latest emotional state. This information is generated using a mental care database prepared in advance. The generated information is sent to the terminal via the Internet. The terminal receives this information and displays it to the user.

[0660] Input: Analyzed latest emotional state and mental care database

[0661] Output: Generated mental health information and its display

[0662] This allows users to effectively manage their emotions and receive appropriate mental health information.

[0663] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0664] The following describes in detail the embodiments of the present invention. The present invention is a system that recognizes and analyzes a user's emotions, generates artwork based on the analysis, and provides mental care information. In particular, the system is configured to incorporate an emotion engine for recognizing a user's emotions in real time.

[0665] The system includes the following main components:

[0666] Emotion input method

[0667] Emotion analysis means

[0668] Emotion Engine

[0669] Artwork Generation Method

[0670] Artwork display method

[0671] Comment input method

[0672] Impression analysis means

[0673] Means of providing mental health information

[0674] System flow

[0675] 1. User emotion input

[0676] The user inputs their feelings and stressors into the device in text format, for example, "I feel a lot of pressure at work."

[0677] 2. Sending Emotional Data

[0678] The device sends the input text data to the server, and the emotion engine uses this data to recognize emotions.

[0679] 3. Emotion Recognition by Emotion Engine

[0680] The server's emotion engine analyzes the transmitted text, voice, and even the user's facial expression data to recognize the emotion category (e.g., stress, pressure) and its intensity (numerical score) in real time. For example, if the user enters "tired," it will recognize the emotion as "fatigue." It also obtains complementary emotion data from the user's voice and facial expressions.

[0681] 4. Emotion analysis

[0682] The emotion data recognized by the emotion engine is further analyzed in detail by the server to identify the user's current emotional state.

[0683] 5. Artwork generation

[0684] The server then activates an artwork generation algorithm based on the emotion analysis results. For example, if the intensity of "stress" is high, it will select stimulating colors like red and yellow and sharp shapes to generate digital art.

[0685] 6. Artwork display

[0686] The server sends image data of the generated artwork to the device, which then displays the received artwork to the user, allowing the user to visually view the artwork that expresses their own emotions.

[0687] 7. User feedback

[0688] The user then inputs their impressions and positive emotions into the device after viewing the artwork. For example, they might input, "Looking at this art made me feel a little relaxed."

[0689] 8. Sending and analyzing feedback data

[0690] The device sends the user's impression data to the server, which then analyzes the received impression data to identify changes in the user's emotional state and trends in positive emotions. For example, it analyzes the keyword "relaxation."

[0691] 9. Providing mental health care information

[0692] Based on the analysis results, the server generates useful mental care information for the user (advice on relaxation methods and stress management). The generated mental care information is sent to the user's device and displayed to the user. Based on this, the user can practice further relaxation and stress management.

[0693] Specific examples

[0694] For example, if a user types "I've been feeling a lot of pressure at work lately," this text data is sent from the device to the server. The emotion engine then recognizes emotions such as "pressure" and "stress" in real time and evaluates their intensity. Furthermore, the user's facial expressions and voice data are also used for analysis.

[0695] The server generates digital art using colors such as red and yellow and sharp shapes based on the obtained emotional data, and sends this artwork to the user's device. The user looks at the displayed artwork and inputs their impression, such as "Looking at this art made me feel a little relaxed."

[0696] Finally, the server analyzes this data again to generate mental care information that will help users relax and send it to their device. In this way, users can easily express their feelings and obtain appropriate mental care information to maintain their mental health, even without specialized knowledge or skills.

[0697] The processing flow will be explained below.

[0698] Step 1:

[0699] The user enters their feelings and the causes of stress into the device in text format. For example, they might enter "I'm under a lot of pressure at work."

[0700] Step 2:

[0701] The terminal sends the entered text data to the server, using a communication protocol to ensure the data is sent reliably.

[0702] Step 3:

[0703] The server passes the received text data to the emotion engine and begins analysis. The emotion engine uses natural language processing technology to analyze the input text and recognize emotion categories (e.g., "stress") and their intensity (numerical score).

[0704] Step 4:

[0705] The emotion engine simultaneously analyzes the user's facial expression and voice data and recognizes emotions from these data, improving the accuracy of emotion category and intensity recognition.

[0706] Step 5:

[0707] The server uses the emotion data obtained from the emotion engine to activate an artwork generation algorithm. Based on the analysis results, it selects appropriate colors and shapes to generate digital art. For example, if the intensity of "stress" is high, it selects stimulating colors like red and yellow and sharp shapes.

[0708] Step 6:

[0709] The server saves the generated artwork in image format and sends the data to the terminal, using a communication protocol to ensure that the image data is transferred accurately.

[0710] Step 7:

[0711] The device displays the received artwork to the user, allowing the user to visually confirm the artwork that expresses their emotions.

[0712] Step 8:

[0713] After viewing the artwork, the user again inputs their impressions and positive emotions into the device, for example, "Looking at this art made me feel a little relaxed."

[0714] Step 9:

[0715] The terminal transmits the user's impression data to the server using a communication protocol to ensure that the impression data is transmitted accurately.

[0716] Step 10:

[0717] The server then passes the received impression data back to the emotion engine, which analyzes changes in the emotional state and trends in positive emotions. For example, it checks whether the keyword "relaxed" is included.

[0718] Step 11:

[0719] Based on the analysis results, the server generates useful mental care information for the user, such as advice on relaxation techniques and stress management.

[0720] Step 12:

[0721] The server transmits the generated mental care information to the terminal, using a communication protocol to ensure reliable data transfer.

[0722] Step 13:

[0723] The device then displays the received mental care information to the user, who can then use the information to further relax and manage stress.

[0724] Example 2

[0725] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0726] In modern society, many people suffer from stress and emotional burdens, and managing and caring for these stressors is becoming increasingly important. However, there are few systems that can accurately recognize these emotions in real time and provide appropriate mental care information based on that information. Therefore, there is a need for a system that allows users to easily input their own emotional state, have it analyzed, and provide appropriate coping strategies. Furthermore, expressing emotions through visual means and receiving feedback based on those emotions is expected to lead to more effective mental care.

[0727] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0728] In this invention, the server includes a means for transmitting user emotion data to the server, a means for analyzing the emotion data received by the server using a natural language processing algorithm, and a means for generating artwork based on the analyzed emotion data. This allows the emotion data input by the user to be analyzed, and artwork generated based on the analysis results to be quickly provided to the user. As a result, the user can visually understand their own emotions and receive individually customized mental care information.

[0729] "User" refers to a person who uses this system to input emotion data and impression data.

[0730] "Terminal" refers to the electronic device used by the User to input emotional and / or impression data and to receive and display artwork and mental health information.

[0731] The term "server" refers to a remote computer system that analyzes the received emotional and impression data and generates artwork and mental care information.

[0732] "Emotion data" refers to data entered by a user in text format about their emotions and the causes of stress.

[0733] A "natural language processing algorithm" refers to a computational method for analyzing emotional data and recognizing the emotional categories and intensity contained within it.

[0734] "Emotion category" refers to the type of emotion (e.g., "stress" or "pressure") classified as a result of analyzing emotion data.

[0735] "Intensity" refers to a numerical representation of the strength of an emotion for a particular emotion category.

[0736] "Artwork" refers to visual content (images) generated based on analyzed emotional data.

[0737] "Opinion data" refers to data entered by a user in text format as their impressions or feedback on the displayed artwork.

[0738] "Mental care information" refers to information such as advice on relaxation methods and stress management that is generated based on the analyzed impression data and provided to the user.

[0739] The system of the present invention recognizes and analyzes the user's emotions in real time, and generates artwork based on the results to provide mental care information. This system is implemented mainly using the following hardware and software.

[0740] Hardware and software used

[0741] Device: Used by users to input and send emotional and sentiment data, and to receive and display artwork and mental health information. Examples include smartphones, tablets, and PCs.

[0742] Server: A computer system that receives and analyzes emotional and impression data, and generates and transmits artwork and mental care information.

[0743] Natural language processing algorithms: Software techniques used to analyze user sentiment data, for example, NLP libraries implemented in Python.

[0744] Generative AI model: An algorithm that uses machine learning techniques to generate artwork based on sentiment analysis results.

[0745] Example of a system

[0746] For example, if a user types "I've been under a lot of pressure at work lately," this text data is sent from the device to the server. The server then uses an emotion engine to recognize emotions such as "pressure" and "stress" in real time and evaluate their intensity. Furthermore, the user's facial expressions and voice data are also used for analysis.

[0747] The server generates digital art using colors such as red and yellow and sharp shapes based on the obtained emotional data, and sends this artwork to the user's device. The user looks at the displayed artwork and inputs their impression, such as "Looking at this art made me feel a little relaxed."

[0748] Finally, the server analyzes this feedback data, generates mental care information that will help users relax, and sends it to the user's device. Based on the displayed advice, users can practice further relaxation and stress management.

[0749] Prompt Sentence Examples

[0750] "Describe a system that recognizes and analyzes a user's emotions, generates artwork based on the user's emotional state, and displays the results to the user."

[0751] The system of the present invention allows users to easily express their feelings and obtain appropriate mental care information to maintain their mental health, even without specialized knowledge or skills.

[0752] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0753] Step 1:

[0754] The user inputs emotion data into the terminal. Specifically, the user inputs emotion or stress factors such as "I've been under a lot of pressure at work lately" into a text input field on the terminal.

[0755] Input: User's text data

[0756] Output: Text information entered into the terminal

[0757] Step 2:

[0758] The device sends the input emotion data to the server. When the user taps the "Send" button, the device generates an HTTP request and sends the text data to the server.

[0759] Input: Text information entered into the device

[0760] Output: Text data sent to the server

[0761] Step 3:

[0762] The server analyzes the received text data using a natural language processing algorithm. The server uses an NLP library to analyze the text and calculates an emotion category (e.g., "stress" or "pressure") and its intensity score.

[0763] Input: Text data sent

[0764] Output: Emotion category and its intensity score

[0765] Step 4:

[0766] The server performs a detailed analysis of the acquired emotional data. It compares it with past emotional data and analyzes changes and patterns in the user's emotions. For example, it evaluates whether the intensity of pressure has increased over the past few days.

[0767] Input: Emotion categories and their intensity scores

[0768] Output: Detailed analysis results

[0769] Step 5:

[0770] The server then uses a generative AI model to generate artwork based on the analysis results. Based on the emotion category and its intensity, the generative AI model selects colors and shapes to generate digital art. For example, if the intensity of stress is high, stimulating colors like red and yellow will be used, and sharp shapes will be created.

[0771] Input: Detailed analysis results

[0772] Output: Image data of the generated artwork

[0773] Step 6:

[0774] The server sends the image data of the generated artwork to the terminal, and information including the image data is sent as an HTTP response.

[0775] Input: Image data of the generated artwork

[0776] Output: Image data sent to the device

[0777] Step 7:

[0778] The terminal displays the received artwork to the user. Specifically, the artwork is displayed full-screen on the terminal screen, allowing the user to enjoy it visually.

[0779] Input: Image data

[0780] Output: Artwork displayed on screen

[0781] Step 8:

[0782] The user inputs their thoughts after viewing the artwork into the device, for example, by typing "This art made me feel a little relaxed" into the text input field.

[0783] Input: User testimonial text

[0784] Output: Impression data entered into the terminal

[0785] Step 9:

[0786] The device sends the impression data to the server. When you enter your impression and tap the "Send" button, an HTTP request is generated and sent to the server.

[0787] Input: Impression data entered into the terminal

[0788] Output: Feedback data sent to the server

[0789] Step 10:

[0790] The server analyzes the sentiment data using a natural language processing algorithm to extract positive emotions and keywords, and evaluates changes in the user's emotional state.

[0791] Input: Impression data

[0792] Output: Changes in emotional state and evaluation results

[0793] Step 11:

[0794] The server generates mental care information based on the analysis results. Based on changes in emotional state and the evaluation results, it generates advice on relaxation methods and stress management, and creates mental care information to provide to the user.

[0795] Input: Emotional state changes and evaluation results

[0796] Output: Generated mental health information

[0797] Step 12:

[0798] The server sends the generated mental care information to the terminal, and data including the mental care information is sent as an HTTP response.

[0799] Input: Generated mental health information

[0800] Output: Mental health information sent to the device

[0801] Step 13:

[0802] The mental care information received by the device is displayed to the user. The mental care information is displayed on the device screen in the form of a dedicated widget or notification.

[0803] Input: Mental care information

[0804] Output: Mental health information displayed on the screen

[0805] (Application example 2)

[0806] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0807] In modern society, stress and pressure affect many people. However, there are limited systems that can identify an individual's emotional state in real time and provide appropriate mental health care information based on that information. Even if emotion recognition systems exist, there is a lack of a way to input emotions without requiring the user's effort or to provide visual feedback of emotions.

[0808] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for inputting a user's emotions in voice or text format, means for analyzing the input emotional data, means for generating artwork based on the analyzed emotional data, means installed in the smart device for displaying the generated artwork to the user, means for inputting the user's impressions, and means for analyzing the input impression data and providing mental care information. This allows the user to easily input their emotional state via the smart device and receive appropriate mental care information in real time based on the analysis results.

[0809] "A means for inputting emotions in voice or text format" refers to a device or software that has the function of allowing a user to input emotions as voice or text data.

[0810] "Means for analyzing emotional data" refers to devices or software that have the function of analyzing input emotional data using algorithms or AI models and identifying the type and intensity of emotions.

[0811] "Means for generating artwork" refers to devices or software that have the function of creating digital art using specific colors and shapes based on analyzed emotional data.

[0812] "Means installed on a smart device" means a device or software installed on smart glasses or other wearable devices that has the ability to display generated artwork or mental health information to the user.

[0813] The "means for inputting user's impressions" refers to a device or software that has a function that allows the user to re-input impressions or genetic emotions after viewing the generated artwork.

[0814] "Means for analyzing input impression data and providing mental care information" refers to a device or software that has the function of analyzing the user's impression data and generating and providing useful mental care information to the user based on the results.

[0815] The "means for converting voice input into text format" refers to a device or software that has the function of automatically converting a user's voice data into text data.

[0816] A "cloud-based AI model" is an algorithm or software that accesses a cloud server via the internet and uses artificial intelligence technology to perform data analysis and emotion recognition.

[0817] A "means for generating prompt sentences" is a device or software that has the function of enabling an AI model to generate appropriate prompt sentences or responses based on input data from a user.

[0818] The present invention will be described in detail below with reference to an embodiment thereof. This system allows a user to input their emotions in the form of voice or text, analyzes the data in real time, generates artwork, and provides mental health information to the user.

[0819] Hardware and software used

[0820] The system includes the following hardware and software:

[0821] Smart devices (smart glasses, smartphones, etc.)

[0822] Voice Recognition Software

[0823] Text Analysis Software

[0824] Cloud Server

[0825] AI model (generative AI model)

[0826] Digital Art Generation Software

[0827] Display

[0828] System flow

[0829] 1. Emotion Input

[0830] Users can input their emotions using the voice input function of their smart device, for example, by speaking, "I've been feeling pressure at work lately," or by typing in text, "I've been feeling stressed lately."

[0831] 2. Speech-to-text conversion

[0832] When voice input is performed, the voice recognition software in the device converts the voice data into text data, which is then sent to a cloud server.

[0833] 3. Emotion analysis

[0834] The cloud server analyzes the received text data and uses a generative AI model to identify the type of emotion (e.g., stress, pressure) and its intensity. The analyzed emotion data is then sent back to the smart device.

[0835] 4. Artwork generation

[0836] The smart device generates digital art based on the emotion analysis results. For example, if the stress level is high, artwork using red and yellow colors and sharp shapes will be generated. This artwork visually represents the user's emotions.

[0837] 5. Artwork display

[0838] The generated digital art is displayed on the smart device's display, allowing the user to visually appreciate the artwork.

[0839] 6. Input your thoughts

[0840] The user then re-enters their thoughts and positive emotions after viewing the displayed artwork. For example, they might enter text such as, "Looking at this art made me feel a little relaxed."

[0841] 7. Analysis of impressions and provision of mental health information

[0842] The cloud server then analyzes the sentiment data again to identify changes in the user's emotional state and trends in positive emotions. This information is then used to generate useful mental health information for the user, which is then sent to the user's smart device. For example, advice such as "Take a deep breath. It's important to take time to relax" is provided.

[0843] Specific examples

[0844] For example, if a user types, "I've been feeling pressure at work lately," the speech is converted into text, and the cloud server identifies emotions such as "pressure" and "stress" and evaluates their intensity. Based on this data, the smart device generates digital art with red and yellow colors and sharp shapes and displays it to the user. The user then types their impression, such as "Looking at this art made me feel a little more relaxed," and the cloud server analyzes the data and provides mental care information such as "Take a deep breath."

[0845] Example prompt sentence:

[0846] "I've been feeling a lot of pressure at work lately. I'd like to relax a bit."

[0847] In this way, this system allows users to effectively express their emotions and provides appropriate mental care information based on those emotions.

[0848] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0849] Step 1:

[0850] A user inputs their emotions in the form of voice or text using a smart device. For example, they can say or type, "I've been feeling pressure at work lately." This is input data, which is collected as voice data or text data.

[0851] Step 2:

[0852] The device's voice recognition software converts voice data into text data. If the input is voice, the voice recognition software analyzes the voice and outputs it as text data. In this case, the input is voice data and the output is text data.

[0853] Step 3:

[0854] The device sends the converted text data to the cloud server using a data communication protocol. The input is text data, and the output is data sent to the server.

[0855] Step 4:

[0856] The cloud server performs emotion analysis on the received text data using a generative AI model. The generative AI model analyzes the text and identifies the type of emotion (e.g., stress, pressure) and its intensity. The input is text data, and the output is emotion data (type and intensity of emotion).

[0857] Step 5:

[0858] The server sends the analyzed emotion data to the smart device using a data communication protocol. The input is emotion data, and the output is data sent to the device.

[0859] Step 6:

[0860] The device generates digital art based on the emotion analysis results. Digital art generation software analyzes the emotion data and generates artwork with appropriate colors and shapes. The input is emotion data, and the output is digital art data.

[0861] Step 7:

[0862] The terminal displays the generated digital art on a display, allowing the user to visually appreciate the artwork. The input is digital art data, and the output is a display of the artwork.

[0863] Step 8:

[0864] The user then inputs his or her impressions after viewing the displayed artwork. For example, the user may input text such as "Looking at this artwork helped me to relax a little." This is the input of new impression data.

[0865] Step 9:

[0866] The device sends user feedback data to the cloud server. The input is the feedback data, and the output is the data sent to the server.

[0867] Step 10:

[0868] The cloud server analyzes the input impression data and analyzes changes in emotional state and trends in positive emotions. The generative AI model analyzes the impression data and generates mental care information. The input is impression data, and the output is mental care information.

[0869] Step 11:

[0870] The server sends the generated mental care information to the smart device and displays it to the user. For example, advice such as "Take a deep breath. It's important to take time to relax" is displayed. The input is the mental care information, and the output is the display to the user.

[0871] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0872] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0873] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0874] [Third embodiment]

[0875] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0876] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0877] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0878] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0879] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0880] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0881] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0882] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0883] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0884] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0885] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0886] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0887] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The following describes in detail the embodiments of the present invention.

[0888] This system generates artwork based on the user's emotional data to support mental care. The system mainly includes the following components: emotion input means, emotion analysis means, artwork generation means, artwork display means, impression input means, impression analysis means, and mental care information provision means.

[0889] System flow

[0890] 1. User emotion input

[0891] Users can input negative emotions and stress factors they are feeling at that time in text format into the device, for example, "I'm feeling stressed because of work pressure."

[0892] 2. Sending Emotional Data

[0893] The device sends the entered text data to the server, which receives the data and prepares it for analysis.

[0894] 3. Emotion analysis

[0895] The server passes the text data to a natural language processing (NLP) engine for analysis. The analysis extracts the main emotional categories and their intensity from the data. For example, if the data contains keywords such as "pressure" or "stress," an emotional score is calculated for each.

[0896] 4. Artwork generation

[0897] The server generates artwork based on the analysis results. It selects appropriate colors and shapes based on the emotion category and intensity, generating digital art. For example, if the user is feeling stressed, it selects bright red or yellow colors and sharp shapes to visualize the user's emotions.

[0898] 5. Artwork display

[0899] The generated artwork is sent from the server to the device, which displays it to the user, allowing the user to visually confirm their own emotions and record their reactions.

[0900] 6. User feedback

[0901] The user then inputs their impressions and positive feelings into the terminal after viewing the displayed artwork. For example, they might write something like, "Looking at this artwork helped me relax a little."

[0902] 7. Analysis of impressions and provision of mental health information

[0903] The device sends the user's impression data to the server. The server then analyzes the impression data again to understand the user's emotional state. The server then generates appropriate mental care information to help improve the user's emotions and sends it to the device. The device displays this information to the user to support further mental care.

[0904] Specific examples

[0905] For example, if a working user types, "I've been under a lot of pressure at work lately," this text data is sent from the device to the server, which uses an NLP engine to analyze the emotion keywords "pressure" and "stress" and calculates the corresponding emotion score.

[0906] The server then generates artwork based on the emotion score, choosing shades of red and yellow, sharp shapes, and applying design patterns, which are then sent to the user's device for viewing.

[0907] After viewing the artwork, the user inputs their impression, such as, "Looking at this artwork helped me relax a little." This impression data is sent back to the server, where it is analyzed and specific mental care information that will help them relax is generated and provided to the user.

[0908] In this way, users can easily express their feelings without any specialized knowledge or skills, and by obtaining appropriate mental care information, they can reduce stress and negative emotions.

[0909] The processing flow will be explained below.

[0910] Step 1:

[0911] The user enters their feelings and the causes of stress into the device in text format. For example, they might enter "I'm under a lot of pressure at work."

[0912] Step 2:

[0913] The terminal sends the entered text data to the server, using a communication protocol to ensure that the user's input is transmitted to the server accurately.

[0914] Step 3:

[0915] The server passes the received text data to a natural language processing (NLP) engine to begin analysis. The NLP engine extracts emotion categories (e.g., stress, pressure) and their intensity (numerical scores) from the text data.

[0916] Step 4:

[0917] The server then activates an artwork generation algorithm based on the emotion category and intensity obtained from the NLP engine. For example, if stress is detected as high, it will select stimulating colors like red and yellow and sharp shapes.

[0918] Step 5:

[0919] The server generates digital art using appropriate colors and shapes based on the emotion category and intensity, and the generated artwork is saved in image format.

[0920] Step 6:

[0921] The server transmits the generated artwork image data to the terminal and packages the data in a format that can be accessed by the user.

[0922] Step 7:

[0923] The device displays the received artwork to the user, who can then visually see the artwork that expresses their emotions.

[0924] Step 8:

[0925] The user then inputs their impressions and positive emotions after viewing the artwork into the device, for example, "Looking at this art made me feel a little relaxed."

[0926] Step 9:

[0927] The terminal transmits the user's impression data to the server using a communication protocol to ensure that the impression data is transmitted accurately.

[0928] Step 10:

[0929] The server analyzes the received data to identify changes in emotional state and trends in positive emotions, such as positive keywords like relaxation and a sense of security.

[0930] Step 11:

[0931] Based on the analysis results, the server generates useful mental care information for users (such as relaxation methods and stress management advice). The generated mental care information is stored in text format and link format.

[0932] Step 12:

[0933] The server transmits the generated mental care information to the terminal, packaging the data in a format that is easy for the user to access.

[0934] Step 13:

[0935] The device displays the received mental care information to the user, who can then practice further relaxation and stress management based on the mental care information.

[0936] Example 1

[0937] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0938] In modern society, the increase in stress and negative emotions caused by daily life and work has become a problem. This has led to a growing need for mental health care, but the difficulty of self-awareness and emotional expression makes effective care difficult. In particular, there are few systems that allow users to visually check their own emotions and obtain appropriate mental health care information. Safe handling of emotional and impression data is also an important issue.

[0939] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0940] In this invention, the server includes means for inputting a user's emotions in text format, means for securely transmitting the input emotion data to the server, means for analyzing the transmitted emotion data using natural language processing technology, means for generating artwork using a generative AI model based on the analyzed emotion data, means for displaying the generated artwork to the user, means for inputting the user's impressions, and means for re-analyzing the input emotion data and providing mental care information, thereby enabling the user to visually confirm their own emotions and obtain appropriate mental care information.

[0941] A "user" is someone who uses the system to input their own emotions and receive artwork and mental care information.

[0942] The "means for inputting emotions in text format" is an interface that allows a user to input their own emotions and stress factors as text information.

[0943] "Means for securely transmitting input emotion data to a server" refers to a function that transmits the emotion text data input by the user to a server using a secure communication method (e.g., HTTPS).

[0944] "Means for analyzing using natural language processing technology" refers to technology (e.g., a natural language processing engine) used to analyze the text data received by the server and extract the main emotional categories and intensity of the emotions.

[0945] "Means for generating artwork using a generative AI model" refers to an artificial intelligence model (e.g., image generation AI) for automatically generating digital art based on the results of sentiment analysis.

[0946] The "means for displaying the generated artwork to the user" is a function for displaying the artwork sent from the server on the user terminal.

[0947] The "means for inputting user's impressions" is an interface that allows the user to re-input their impressions and feelings about the displayed artwork.

[0948] The "means for re-analyzing input impression data and providing mental care information" is a function that analyzes the impression data input by the user again, grasps the user's emotional state, and then generates and provides appropriate mental care information.

[0949] An "emotion category" is a category for classifying the user's emotions (e.g., pressure, stress).

[0950] "Emotion Intensity" is a score that quantifies the strength of the emotion the user is feeling.

[0951] A "secure connection" is an encrypted communication method used to securely send and receive data between a device and a server.

[0952] The present invention provides a system for supporting mental health care by generating artwork based on a user's emotional data. The system mainly includes the following components: an emotion input means, an emotion analysis means, an artwork generation means, an artwork display means, an impression input means, an impression analysis means, and a mental health care information provision means.

[0953] System Configuration

[0954] The hardware required to implement the system includes the devices used by users (e.g., smartphones, PCs) and the server that processes and manages the data. The software uses a natural language processing engine (e.g., Google NLP API) and a generative AI model (e.g., DALL-E).

[0955] Processing flow

[0956] First, the user enters the negative emotions or stressors they are currently experiencing into the device in text format. For example, they might enter, "I'm feeling stressed because of work pressure."

[0957] The device then sends the entered text data to the server using a secure connection (e.g., HTTPS), and notifies the user whether the transmission was successful.

[0958] The server cleans the received text data and passes it to a natural language processing engine for analysis, which extracts major emotional categories (e.g., pressure, stress) and emotional intensities (scores) from the data.

[0959] The server then uses a generative AI model to generate artwork based on the emotion analysis—for example, choosing vibrant colors like red and yellow and sharp shapes when stress levels are high—and the artwork is generated digitally.

[0960] The generated artwork is sent from the server to the device, which then displays it to the user. After viewing the artwork, the user can input their impressions and positive emotions into the device. For example, they can input a comment like, "Looking at this art made me feel a little more relaxed."

[0961] The user's impression data is sent back to the server, which analyzes it again. This analysis allows the server to understand the user's emotional state and generate appropriate mental care information. The generated mental care information is then sent to the user's device and displayed to the user.

[0962] Specific examples

[0963] A working user types, "I've been under a lot of pressure at work lately." This text data is sent from the device to a server, which uses a natural language processing engine to analyze the emotion keywords "pressure" and "stress" and calculates an emotion score.

[0964] The server then uses a generative AI model to generate artwork with sharp shapes in red and yellow tones based on the emotion scores, and the artwork is sent to the user's device for viewing.

[0965] The user inputs their impression, such as, "Looking at this art helped me relax a little." This impression data is sent back to the server, where it is analyzed and specific advice on how to relax is generated and provided to the user's device.

[0966] Prompt Sentence Examples

[0967] "I'm feeling the pressure. Visualize how it feels."

[0968] "Look at this art and tell us how it makes you feel so we can provide you with helpful care information for next time."

[0969] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0970] Step 1:

[0971] The user inputs their emotions in text format. For example, they input a sentence such as "I feel stressed because of work pressure" into the device interface. Input: User's emotion text data. Output: Emotion text data saved on the device.

[0972] Step 2:

[0973] The device sends the entered text data to the server using a secure connection. HTTPS is used to protect the data when it is sent. Input: Emotion text data stored on the device. Output: Emotion text data sent to the server.

[0974] Step 3:

[0975] The server stores the received text data and performs data cleaning. Preprocessing is performed to remove unnecessary spaces and special characters. Input: Emotion text data sent to the server. Output: Cleaned emotion text data stored on the server.

[0976] Step 4:

[0977] The server passes the cleaned text data to a natural language processing engine for sentiment analysis. The analysis extracts the main sentiment categories and their numerical values ​​of sentiment intensity. Input: Cleaned sentiment text data. Output: Sentiment categories and sentiment intensity as analysis results.

[0978] Step 5:

[0979] The server uses a generative AI model based on the results of emotion analysis to generate artwork. For example, if the emotion intensity is high, it will use red and yellow colors and generate artwork with sharp shapes. Input: Emotion category and emotion intensity. Output: Generated digital artwork.

[0980] Step 6:

[0981] The server sends the generated artwork to the device. The device displays the received artwork to the user in a dedicated viewer. Input: Generated digital artwork. Output: Artwork displayed on the device.

[0982] Step 7:

[0983] The user inputs their impressions after viewing the artwork in text format into the device. For example, they might input "Looking at this art made me feel a little relaxed." Input: User's impression text data. Output: Impression text data saved on the device.

[0984] Step 8:

[0985] The device sends the user's feedback data to the server using a secure connection. Input: Feedback text data stored on the device. Output: Feedback text data sent to the server.

[0986] Step 9:

[0987] The server passes the received sentiment data to the natural language processing engine for further analysis. Emotion categories and emotional intensities are extracted to understand the user's current emotional state. Input: sentiment text data sent to the server. Output: Emotional state as the analysis result.

[0988] Step 10:

[0989] The server generates appropriate mental care information based on the analysis results and sends it to the device. The device displays the received mental care information to the user. Input: Emotional state as the analysis result. Output: Mental care information displayed on the device.

[0990] (Application example 1)

[0991] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0992] There is a need for a method to effectively alleviate users' stress and negative emotions and support their mental health. However, current mental health services lack a mechanism for providing instant and personalized care based on a user's emotional analysis. They also lack a method for visually expressing emotions and thereby improving the user's psychological state. Furthermore, there is a need for an efficient means for providing such care to multiple users individually.

[0993] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0994] In this invention, the server includes a means for inputting a user's emotions, a means for analyzing the input emotion data, and a means for generating artwork based on the analyzed emotion data. This allows users to visually check their own emotions in real time and instantly obtain optimal mental care information based on the results. Furthermore, by including a means for distributing the artwork and mental care information generated based on the emotion data, it becomes possible to provide care efficiently and individually to multiple users.

[0995] The "means for inputting user's emotions" is an interface that allows the user to input their own emotions and situations into the system in text format.

[0996] The "means for analyzing input emotional data" is a mechanism for analyzing the emotional data input by the user using natural language processing and machine learning techniques, and extracting emotional categories and their intensities.

[0997] The "means for generating artwork based on analyzed emotional data" refers to an algorithm or program that selects appropriate colors and shapes based on emotional analysis and generates digital art.

[0998] The "means for displaying the generated artwork to the user" refers to a display device or software that displays the generated digital art on the user's terminal, allowing the user to visually confirm it.

[0999] The "means for inputting user impressions" is an interface that allows the user to re-input impressions and feelings that they had after viewing the displayed artwork.

[1000] The "means for analyzing inputted impression data and providing mental care information" is a system that analyzes the user's impression data to re-understand the emotional state, and generates and provides appropriate mental care information.

[1001] "Means for distributing artwork and mental care information generated based on emotional data" refers to a network or communication means for distributing the generated digital art and mental care information to users and providing care individually to multiple users.

[1002] "Natural language processing technology" is a technology for mechanically analyzing text data and extracting structured information.

[1003] An "emotion category" is a type of emotion classified based on analyzed emotion data.

[1004] "Emotion intensity" is an index that indicates the strength or degree of an emotion in the analyzed emotion category.

[1005] The present invention provides details of a system for supporting mental care by generating artwork based on a user's emotional data. An embodiment of the system will be described below.

[1006] Overall system configuration

[1007] The system mainly consists of the following components:

[1008] 1. A way to input user emotions

[1009] Users use a device such as a smartphone to input their feelings into the system in text format, such as "I've been feeling a lot of pressure at work lately."

[1010] 2. A method for analyzing input emotion data

[1011] Emotional text data sent from the device is passed to a server, where it is analyzed for emotional category and intensity using natural language processing (NLP) technology.

[1012] 3. A method for generating artwork based on analyzed emotion data

[1013] Based on the analysis of emotional data, appropriate colors and shapes are selected and digital art is generated using a generative AI model.

[1014] 4. A means of displaying the generated artwork to the user

[1015] The generated digital art is sent from the server to the terminal and displayed on the user's visual display device (smartphone display).

[1016] 5. A way to input user feedback

[1017] The user then enters their thoughts after viewing the displayed artwork in text format, for example, "Looking at this art made me feel a little relaxed."

[1018] 6. A means of analyzing inputted impression data and providing mental care information

[1019] The retransmitted impression data is analyzed by the server, and optimal mental care information is generated. This information is then sent to the user and displayed on their device.

[1020] 7. A means of delivering artwork and mental health information generated based on emotional data

[1021] The generated digital art and mental care information are distributed individually to multiple users.

[1022] Hardware and software used

[1023] Server: A server with high-performance computing power is used. This server is responsible for analyzing data and generating artwork.

[1024] Natural Language Processing (NLP) engine: For example, the Transformers library from Hugging Face is used.

[1025] Generative AI models: These are built using machine learning frameworks such as TensorFlow and PyTorch.

[1026] Smartphones: Used for users to input emotional data and display generated digital art and mental health information.

[1027] Data processing and calculation

[1028] 1. Emotion data analysis: The server uses a natural language processing engine to analyze the input text data and extract emotion categories and intensities.

[1029] 2. Artwork generation: Select colors and shapes based on the analysis results and generate appropriate digital art using a generative AI model.

[1030] 3. Analysis of impression data: The re-entered impression data is analyzed to understand the user's latest emotional state and provide appropriate mental care information.

[1031] Specific examples

[1032] If a user types, "I've been under a lot of pressure at work lately," this text data is sent from the device to the server. The NLP engine analyzes the emotional category of "stress" and extracts the corresponding intensity. The server selects red and sharp shapes and generates digital art using a generative AI model. The generated artwork is displayed on the smartphone for the user to visually confirm. If the user types, "Looking at this art helped me relax a bit," the impression data is sent again to the server, and appropriate mental care information is generated and displayed.

[1033] Prompt Sentence Examples

[1034] "The user has mentioned feeling stressed at work recently. Generate colorful, vivid digital art to visualize this emotion and provide appropriate mental health information."

[1035] In this way, users can receive help in effectively managing their emotions and relaxing through their smartphones.

[1036] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1037] Step 1:

[1038] The user inputs emotion data

[1039] The user uses a smartphone to input the emotions and stress factors they are feeling at that time in text format. For example, they might enter a sentence such as "I've been feeling a lot of pressure at work lately" into the smartphone's input form. This data is temporarily stored as text data on the device.

[1040] Input: Emotion text data entered by the user

[1041] Output: Emotion text data temporarily stored on the smartphone

[1042] Step 2:

[1043] Send emotion data to the server

[1044] The device sends the input emotion text data to a server via the Internet using a network protocol such as an HTTP POST request.

[1045] Input: Emotion text data sent from the device

[1046] Output: Emotion text data received by the server

[1047] Step 3:

[1048] The server analyzes the emotional data

[1049] The server passes the received emotion text data to a natural language processing (NLP) engine for analysis, specifically using Hugging Face's Transformers library to extract emotion categories (e.g., stress) and their intensity.

[1050] Input: Emotion text data received by the server

[1051] Output: Parsed emotion categories and their intensities

[1052] Step 4:

[1053] Generate artwork

[1054] The server generates digital art using a generative AI model (e.g., TensorFlow or PyTorch) based on the emotion category and its intensity obtained by the NLP engine, with color and shape determined by the emotion category.

[1055] Input: Parsed emotion category and its intensity

[1056] Output: Generated digital art data

[1057] Step 5:

[1058] Send the generated artwork to your device

[1059] The server then transmits the generated digital art data to the user's device via the Internet, again using the HTTP protocol.

[1060] Input: Generated digital art data

[1061] Output: Digital art data received on the device

[1062] Step 6:

[1063] View user-generated artwork

[1064] The user then views the digital art received on the device on a visual display device (smartphone display), thereby confirming the visualization of their own emotions.

[1065] Input: Digital art data displayed on the device

[1066] Output: Visual confirmation for the user

[1067] Step 7:

[1068] The user enters their feedback

[1069] After viewing the generated artwork, the user again enters their impressions in text format. For example, they might enter a comment like, "Looking at this art made me feel a little relaxed." This data is also temporarily stored on the device.

[1070] Input: User-entered text data

[1071] Output: Impression text data temporarily saved on the smartphone

[1072] Step 8:

[1073] Send the feedback data to the server

[1074] The terminal again transmits the input impression text data to the server via the Internet.

[1075] Input: Text data of impressions sent from the device

[1076] Output: Text data of the impressions received by the server

[1077] Step 9:

[1078] The server analyzes the opinion data

[1079] The server then passes the received impression text data back to the natural language processing (NLP) engine for analysis to grasp the user's latest emotional state.

[1080] Input: Text data of impressions received by the server

[1081] Output: Latest analyzed emotional state

[1082] Step 10:

[1083] Generates mental health information and provides it to users

[1084] The server generates appropriate mental care information based on the analyzed latest emotional state. This information is generated using a mental care database prepared in advance. The generated information is sent to the terminal via the Internet. The terminal receives this information and displays it to the user.

[1085] Input: Analyzed latest emotional state and mental care database

[1086] Output: Generated mental health information and its display

[1087] This allows users to effectively manage their emotions and receive appropriate mental health information.

[1088] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1089] The following describes in detail the embodiments of the present invention. The present invention is a system that recognizes and analyzes a user's emotions, generates artwork based on the analysis, and provides mental care information. In particular, the system is configured to incorporate an emotion engine for recognizing a user's emotions in real time.

[1090] The system includes the following main components:

[1091] Emotion input method

[1092] Emotion analysis means

[1093] Emotion Engine

[1094] Artwork Generation Method

[1095] Artwork display method

[1096] Comment input method

[1097] Impression analysis means

[1098] Means of providing mental health information

[1099] System flow

[1100] 1. User emotion input

[1101] The user inputs their feelings and stressors into the device in text format, for example, "I feel a lot of pressure at work."

[1102] 2. Sending Emotional Data

[1103] The device sends the input text data to the server, and the emotion engine uses this data to recognize emotions.

[1104] 3. Emotion Recognition by Emotion Engine

[1105] The server's emotion engine analyzes the transmitted text, voice, and even the user's facial expression data to recognize the emotion category (e.g., stress, pressure) and its intensity (numerical score) in real time. For example, if the user enters "tired," it will recognize the emotion as "fatigue." It also obtains complementary emotion data from the user's voice and facial expressions.

[1106] 4. Emotion analysis

[1107] The emotion data recognized by the emotion engine is further analyzed in detail by the server to identify the user's current emotional state.

[1108] 5. Artwork generation

[1109] The server then activates an artwork generation algorithm based on the emotion analysis results. For example, if the intensity of "stress" is high, it will select stimulating colors like red and yellow and sharp shapes to generate digital art.

[1110] 6. Artwork display

[1111] The server sends image data of the generated artwork to the device, which then displays the received artwork to the user, allowing the user to visually view the artwork that expresses their own emotions.

[1112] 7. User feedback

[1113] The user then inputs their impressions and positive emotions into the device after viewing the artwork. For example, they might input, "Looking at this art made me feel a little relaxed."

[1114] 8. Sending and analyzing feedback data

[1115] The device sends the user's impression data to the server, which then analyzes the received impression data to identify changes in the user's emotional state and trends in positive emotions. For example, it analyzes the keyword "relaxation."

[1116] 9. Providing mental health care information

[1117] Based on the analysis results, the server generates useful mental care information for the user (advice on relaxation methods and stress management). The generated mental care information is sent to the user's device and displayed to the user. Based on this, the user can practice further relaxation and stress management.

[1118] Specific examples

[1119] For example, if a user types "I've been feeling a lot of pressure at work lately," this text data is sent from the device to the server. The emotion engine then recognizes emotions such as "pressure" and "stress" in real time and evaluates their intensity. Furthermore, the user's facial expressions and voice data are also used for analysis.

[1120] The server generates digital art using colors such as red and yellow and sharp shapes based on the obtained emotional data, and sends this artwork to the user's device. The user looks at the displayed artwork and inputs their impression, such as "Looking at this art made me feel a little relaxed."

[1121] Finally, the server analyzes this data again to generate mental care information that will help users relax and send it to their device. In this way, users can easily express their feelings and obtain appropriate mental care information to maintain their mental health, even without specialized knowledge or skills.

[1122] The processing flow will be explained below.

[1123] Step 1:

[1124] The user enters their feelings and the causes of stress into the device in text format. For example, they might enter "I'm under a lot of pressure at work."

[1125] Step 2:

[1126] The terminal sends the entered text data to the server, using a communication protocol to ensure the data is sent reliably.

[1127] Step 3:

[1128] The server passes the received text data to the emotion engine and begins analysis. The emotion engine uses natural language processing technology to analyze the input text and recognize emotion categories (e.g., "stress") and their intensity (numerical score).

[1129] Step 4:

[1130] The emotion engine simultaneously analyzes the user's facial expression and voice data and recognizes emotions from these data, improving the accuracy of emotion category and intensity recognition.

[1131] Step 5:

[1132] The server uses the emotion data obtained from the emotion engine to activate an artwork generation algorithm. Based on the analysis results, it selects appropriate colors and shapes to generate digital art. For example, if the intensity of "stress" is high, it selects stimulating colors like red and yellow and sharp shapes.

[1133] Step 6:

[1134] The server saves the generated artwork in image format and sends the data to the terminal, using a communication protocol to ensure that the image data is transferred accurately.

[1135] Step 7:

[1136] The device displays the received artwork to the user, allowing the user to visually confirm the artwork that expresses their emotions.

[1137] Step 8:

[1138] After viewing the artwork, the user again inputs their impressions and positive emotions into the device, for example, "Looking at this art made me feel a little relaxed."

[1139] Step 9:

[1140] The terminal transmits the user's impression data to the server using a communication protocol to ensure that the impression data is transmitted accurately.

[1141] Step 10:

[1142] The server then passes the received impression data back to the emotion engine, which analyzes changes in the emotional state and trends in positive emotions. For example, it checks whether the keyword "relaxed" is included.

[1143] Step 11:

[1144] Based on the analysis results, the server generates useful mental care information for the user, such as advice on relaxation techniques and stress management.

[1145] Step 12:

[1146] The server transmits the generated mental care information to the terminal, using a communication protocol to ensure reliable data transfer.

[1147] Step 13:

[1148] The device then displays the received mental care information to the user, who can then use the information to further relax and manage stress.

[1149] Example 2

[1150] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1151] In modern society, many people suffer from stress and emotional burdens, and managing and caring for these stressors is becoming increasingly important. However, there are few systems that can accurately recognize these emotions in real time and provide appropriate mental care information based on that information. Therefore, there is a need for a system that allows users to easily input their own emotional state, have it analyzed, and provide appropriate coping strategies. Furthermore, expressing emotions through visual means and receiving feedback based on those emotions is expected to lead to more effective mental care.

[1152] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1153] In this invention, the server includes a means for transmitting user emotion data to the server, a means for analyzing the emotion data received by the server using a natural language processing algorithm, and a means for generating artwork based on the analyzed emotion data. This allows the emotion data input by the user to be analyzed, and artwork generated based on the analysis results to be quickly provided to the user. As a result, the user can visually understand their own emotions and receive individually customized mental care information.

[1154] "User" refers to a person who uses this system to input emotion data and impression data.

[1155] "Terminal" refers to the electronic device used by the User to input emotional and / or impression data and to receive and display artwork and mental health information.

[1156] The term "server" refers to a remote computer system that analyzes the received emotional and impression data and generates artwork and mental care information.

[1157] "Emotion data" refers to data entered by a user in text format about their emotions and the causes of stress.

[1158] A "natural language processing algorithm" refers to a computational method for analyzing emotional data and recognizing the emotional categories and intensity contained within it.

[1159] "Emotion category" refers to the type of emotion (e.g., "stress" or "pressure") classified as a result of analyzing emotion data.

[1160] "Intensity" refers to a numerical representation of the strength of an emotion for a particular emotion category.

[1161] "Artwork" refers to visual content (images) generated based on analyzed emotional data.

[1162] "Opinion data" refers to data entered by a user in text format as their impressions or feedback on the displayed artwork.

[1163] "Mental care information" refers to information such as advice on relaxation methods and stress management that is generated based on the analyzed impression data and provided to the user.

[1164] The system of the present invention recognizes and analyzes the user's emotions in real time, and generates artwork based on the results to provide mental care information. This system is implemented mainly using the following hardware and software.

[1165] Hardware and software used

[1166] Device: Used by users to input and send emotional and sentiment data, and to receive and display artwork and mental health information. Examples include smartphones, tablets, and PCs.

[1167] Server: A computer system that receives and analyzes emotional and impression data, and generates and transmits artwork and mental care information.

[1168] Natural language processing algorithms: Software techniques used to analyze user sentiment data, for example, NLP libraries implemented in Python.

[1169] Generative AI model: An algorithm that uses machine learning techniques to generate artwork based on sentiment analysis results.

[1170] Example of a system

[1171] For example, if a user types "I've been under a lot of pressure at work lately," this text data is sent from the device to the server. The server then uses an emotion engine to recognize emotions such as "pressure" and "stress" in real time and evaluate their intensity. Furthermore, the user's facial expressions and voice data are also used for analysis.

[1172] The server generates digital art using colors such as red and yellow and sharp shapes based on the obtained emotional data, and sends this artwork to the user's device. The user looks at the displayed artwork and inputs their impression, such as "Looking at this art made me feel a little relaxed."

[1173] Finally, the server analyzes this feedback data, generates mental care information that will help users relax, and sends it to the user's device. Based on the displayed advice, users can practice further relaxation and stress management.

[1174] Prompt Sentence Examples

[1175] "Describe a system that recognizes and analyzes a user's emotions, generates artwork based on the user's emotional state, and displays the results to the user."

[1176] The system of the present invention allows users to easily express their feelings and obtain appropriate mental care information to maintain their mental health, even without specialized knowledge or skills.

[1177] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1178] Step 1:

[1179] The user inputs emotion data into the terminal. Specifically, the user inputs emotion or stress factors such as "I've been under a lot of pressure at work lately" into a text input field on the terminal.

[1180] Input: User's text data

[1181] Output: Text information entered into the terminal

[1182] Step 2:

[1183] The device sends the input emotion data to the server. When the user taps the "Send" button, the device generates an HTTP request and sends the text data to the server.

[1184] Input: Text information entered into the device

[1185] Output: Text data sent to the server

[1186] Step 3:

[1187] The server analyzes the received text data using a natural language processing algorithm. The server uses an NLP library to analyze the text and calculates an emotion category (e.g., "stress" or "pressure") and its intensity score.

[1188] Input: Text data sent

[1189] Output: Emotion category and its intensity score

[1190] Step 4:

[1191] The server performs a detailed analysis of the acquired emotional data. It compares it with past emotional data and analyzes changes and patterns in the user's emotions. For example, it evaluates whether the intensity of pressure has increased over the past few days.

[1192] Input: Emotion categories and their intensity scores

[1193] Output: Detailed analysis results

[1194] Step 5:

[1195] The server then uses a generative AI model to generate artwork based on the analysis results. Based on the emotion category and its intensity, the generative AI model selects colors and shapes to generate digital art. For example, if the intensity of stress is high, stimulating colors like red and yellow will be used, and sharp shapes will be created.

[1196] Input: Detailed analysis results

[1197] Output: Image data of the generated artwork

[1198] Step 6:

[1199] The server sends the image data of the generated artwork to the terminal, and information including the image data is sent as an HTTP response.

[1200] Input: Image data of the generated artwork

[1201] Output: Image data sent to the device

[1202] Step 7:

[1203] The terminal displays the received artwork to the user. Specifically, the artwork is displayed full-screen on the terminal screen, allowing the user to enjoy it visually.

[1204] Input: Image data

[1205] Output: Artwork displayed on screen

[1206] Step 8:

[1207] The user inputs their thoughts after viewing the artwork into the device, for example, by typing "This art made me feel a little relaxed" into the text input field.

[1208] Input: User testimonial text

[1209] Output: Impression data entered into the terminal

[1210] Step 9:

[1211] The device sends the impression data to the server. When you enter your impression and tap the "Send" button, an HTTP request is generated and sent to the server.

[1212] Input: Impression data entered into the terminal

[1213] Output: Feedback data sent to the server

[1214] Step 10:

[1215] The server analyzes the sentiment data using a natural language processing algorithm to extract positive emotions and keywords, and evaluates changes in the user's emotional state.

[1216] Input: Impression data

[1217] Output: Changes in emotional state and evaluation results

[1218] Step 11:

[1219] The server generates mental care information based on the analysis results. Based on changes in emotional state and the evaluation results, it generates advice on relaxation methods and stress management, and creates mental care information to provide to the user.

[1220] Input: Emotional state changes and evaluation results

[1221] Output: Generated mental health information

[1222] Step 12:

[1223] The server sends the generated mental care information to the terminal, and data including the mental care information is sent as an HTTP response.

[1224] Input: Generated mental health information

[1225] Output: Mental health information sent to the device

[1226] Step 13:

[1227] The mental care information received by the device is displayed to the user. The mental care information is displayed on the device screen in the form of a dedicated widget or notification.

[1228] Input: Mental care information

[1229] Output: Mental health information displayed on the screen

[1230] (Application example 2)

[1231] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1232] In modern society, stress and pressure affect many people. However, there are limited systems that can identify an individual's emotional state in real time and provide appropriate mental health care information based on that information. Even if emotion recognition systems exist, there is a lack of a way to input emotions without requiring the user's effort or to provide visual feedback of emotions.

[1233] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for inputting a user's emotions in voice or text format, means for analyzing the input emotional data, means for generating artwork based on the analyzed emotional data, means installed in the smart device for displaying the generated artwork to the user, means for inputting the user's impressions, and means for analyzing the input impression data and providing mental care information. This allows the user to easily input their emotional state via the smart device and receive appropriate mental care information in real time based on the analysis results.

[1234] "A means for inputting emotions in voice or text format" refers to a device or software that has the function of allowing a user to input emotions as voice or text data.

[1235] "Means for analyzing emotional data" refers to devices or software that have the function of analyzing input emotional data using algorithms or AI models and identifying the type and intensity of emotions.

[1236] "Means for generating artwork" refers to devices or software that have the function of creating digital art using specific colors and shapes based on analyzed emotional data.

[1237] "Means installed on a smart device" means a device or software installed on smart glasses or other wearable devices that has the ability to display generated artwork or mental health information to the user.

[1238] The "means for inputting user's impressions" refers to a device or software that has a function that allows the user to re-input impressions or genetic emotions after viewing the generated artwork.

[1239] "Means for analyzing input impression data and providing mental care information" refers to a device or software that has the function of analyzing the user's impression data and generating and providing useful mental care information to the user based on the results.

[1240] The "means for converting voice input into text format" refers to a device or software that has the function of automatically converting a user's voice data into text data.

[1241] A "cloud-based AI model" is an algorithm or software that accesses a cloud server via the internet and uses artificial intelligence technology to perform data analysis and emotion recognition.

[1242] A "means for generating prompt sentences" is a device or software that has the function of enabling an AI model to generate appropriate prompt sentences or responses based on input data from a user.

[1243] The present invention will be described in detail below with reference to an embodiment thereof. This system allows a user to input their emotions in the form of voice or text, analyzes the data in real time, generates artwork, and provides mental health information to the user.

[1244] Hardware and software used

[1245] The system includes the following hardware and software:

[1246] Smart devices (smart glasses, smartphones, etc.)

[1247] Voice Recognition Software

[1248] Text Analysis Software

[1249] Cloud Server

[1250] AI model (generative AI model)

[1251] Digital Art Generation Software

[1252] Display

[1253] System flow

[1254] 1. Emotion Input

[1255] Users can input their emotions using the voice input function of their smart device, for example, by speaking, "I've been feeling pressure at work lately," or by typing in text, "I've been feeling stressed lately."

[1256] 2. Speech-to-text conversion

[1257] When voice input is performed, the voice recognition software in the device converts the voice data into text data, which is then sent to a cloud server.

[1258] 3. Emotion analysis

[1259] The cloud server analyzes the received text data and uses a generative AI model to identify the type of emotion (e.g., stress, pressure) and its intensity. The analyzed emotion data is then sent back to the smart device.

[1260] 4. Artwork generation

[1261] The smart device generates digital art based on the emotion analysis results. For example, if the stress level is high, artwork using red and yellow colors and sharp shapes will be generated. This artwork visually represents the user's emotions.

[1262] 5. Artwork display

[1263] The generated digital art is displayed on the smart device's display, allowing the user to visually appreciate the artwork.

[1264] 6. Input your thoughts

[1265] The user then re-enters their thoughts and positive emotions after viewing the displayed artwork. For example, they might enter text such as, "Looking at this art made me feel a little relaxed."

[1266] 7. Analysis of impressions and provision of mental health information

[1267] The cloud server then analyzes the sentiment data again to identify changes in the user's emotional state and trends in positive emotions. This information is then used to generate useful mental health information for the user, which is then sent to the user's smart device. For example, advice such as "Take a deep breath. It's important to take time to relax" is provided.

[1268] Specific examples

[1269] For example, if a user types, "I've been feeling pressure at work lately," the speech is converted into text, and the cloud server identifies emotions such as "pressure" and "stress" and evaluates their intensity. Based on this data, the smart device generates digital art with red and yellow colors and sharp shapes and displays it to the user. The user then types their impression, such as "Looking at this art made me feel a little more relaxed," and the cloud server analyzes the data and provides mental care information such as "Take a deep breath."

[1270] Example prompt sentence:

[1271] "I've been feeling a lot of pressure at work lately. I'd like to relax a bit."

[1272] In this way, this system allows users to effectively express their emotions and provides appropriate mental care information based on those emotions.

[1273] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1274] Step 1:

[1275] A user inputs their emotions in the form of voice or text using a smart device. For example, they can say or type, "I've been feeling pressure at work lately." This is input data, which is collected as voice data or text data.

[1276] Step 2:

[1277] The device's voice recognition software converts voice data into text data. If the input is voice, the voice recognition software analyzes the voice and outputs it as text data. In this case, the input is voice data and the output is text data.

[1278] Step 3:

[1279] The device sends the converted text data to the cloud server using a data communication protocol. The input is text data, and the output is data sent to the server.

[1280] Step 4:

[1281] The cloud server performs emotion analysis on the received text data using a generative AI model. The generative AI model analyzes the text and identifies the type of emotion (e.g., stress, pressure) and its intensity. The input is text data, and the output is emotion data (type and intensity of emotion).

[1282] Step 5:

[1283] The server sends the analyzed emotion data to the smart device using a data communication protocol. The input is emotion data, and the output is data sent to the device.

[1284] Step 6:

[1285] The device generates digital art based on the emotion analysis results. Digital art generation software analyzes the emotion data and generates artwork with appropriate colors and shapes. The input is emotion data, and the output is digital art data.

[1286] Step 7:

[1287] The terminal displays the generated digital art on a display, allowing the user to visually appreciate the artwork. The input is digital art data, and the output is a display of the artwork.

[1288] Step 8:

[1289] The user then inputs his or her impressions after viewing the displayed artwork. For example, the user may input text such as "Looking at this artwork helped me to relax a little." This is the input of new impression data.

[1290] Step 9:

[1291] The device sends user feedback data to the cloud server. The input is the feedback data, and the output is the data sent to the server.

[1292] Step 10:

[1293] The cloud server analyzes the input impression data and analyzes changes in emotional state and trends in positive emotions. The generative AI model analyzes the impression data and generates mental care information. The input is impression data, and the output is mental care information.

[1294] Step 11:

[1295] The server sends the generated mental care information to the smart device and displays it to the user. For example, advice such as "Take a deep breath. It's important to take time to relax" is displayed. The input is the mental care information, and the output is the display to the user.

[1296] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1297] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1298] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1299] [Fourth embodiment]

[1300] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1301] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1302] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1303] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1304] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1305] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1306] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1307] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1308] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1309] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1310] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1311] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1312] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1313] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The following describes in detail the embodiments of the present invention.

[1314] This system generates artwork based on the user's emotional data to support mental care. The system mainly includes the following components: emotion input means, emotion analysis means, artwork generation means, artwork display means, impression input means, impression analysis means, and mental care information provision means.

[1315] System flow

[1316] 1. User emotion input

[1317] Users can input negative emotions and stress factors they are feeling at that time in text format into the device, for example, "I'm feeling stressed because of work pressure."

[1318] 2. Sending Emotional Data

[1319] The device sends the entered text data to the server, which receives the data and prepares it for analysis.

[1320] 3. Emotion analysis

[1321] The server passes the text data to a natural language processing (NLP) engine for analysis. The analysis extracts the main emotional categories and their intensity from the data. For example, if the data contains keywords such as "pressure" or "stress," an emotional score is calculated for each.

[1322] 4. Artwork generation

[1323] The server generates artwork based on the analysis results. It selects appropriate colors and shapes based on the emotion category and intensity, generating digital art. For example, if the user is feeling stressed, it selects bright red or yellow colors and sharp shapes to visualize the user's emotions.

[1324] 5. Artwork display

[1325] The generated artwork is sent from the server to the device, which displays it to the user, allowing the user to visually confirm their own emotions and record their reactions.

[1326] 6. User feedback

[1327] The user then inputs their impressions and positive feelings into the terminal after viewing the displayed artwork. For example, they might write something like, "Looking at this artwork helped me relax a little."

[1328] 7. Analysis of impressions and provision of mental health information

[1329] The device sends the user's impression data to the server. The server then analyzes the impression data again to understand the user's emotional state. The server then generates appropriate mental care information to help improve the user's emotions and sends it to the device. The device displays this information to the user to support further mental care.

[1330] Specific examples

[1331] For example, if a working user types, "I've been under a lot of pressure at work lately," this text data is sent from the device to the server, which uses an NLP engine to analyze the emotion keywords "pressure" and "stress" and calculates the corresponding emotion score.

[1332] The server then generates artwork based on the emotion score, choosing shades of red and yellow, sharp shapes, and applying design patterns, which are then sent to the user's device for viewing.

[1333] After viewing the artwork, the user inputs their impression, such as, "Looking at this artwork helped me relax a little." This impression data is sent back to the server, where it is analyzed and specific mental care information that will help them relax is generated and provided to the user.

[1334] In this way, users can easily express their feelings without any specialized knowledge or skills, and by obtaining appropriate mental care information, they can reduce stress and negative emotions.

[1335] The processing flow will be explained below.

[1336] Step 1:

[1337] The user enters their feelings and the causes of stress into the device in text format. For example, they might enter "I'm under a lot of pressure at work."

[1338] Step 2:

[1339] The terminal sends the entered text data to the server, using a communication protocol to ensure that the user's input is transmitted to the server accurately.

[1340] Step 3:

[1341] The server passes the received text data to a natural language processing (NLP) engine to begin analysis. The NLP engine extracts emotion categories (e.g., stress, pressure) and their intensity (numerical scores) from the text data.

[1342] Step 4:

[1343] The server then activates an artwork generation algorithm based on the emotion category and intensity obtained from the NLP engine. For example, if stress is detected as high, it will select stimulating colors like red and yellow and sharp shapes.

[1344] Step 5:

[1345] The server generates digital art using appropriate colors and shapes based on the emotion category and intensity, and the generated artwork is saved in image format.

[1346] Step 6:

[1347] The server transmits the generated artwork image data to the terminal and packages the data in a format that can be accessed by the user.

[1348] Step 7:

[1349] The device displays the received artwork to the user, who can then visually see the artwork that expresses their emotions.

[1350] Step 8:

[1351] The user then inputs their impressions and positive emotions after viewing the artwork into the device, for example, "Looking at this art made me feel a little relaxed."

[1352] Step 9:

[1353] The terminal transmits the user's impression data to the server using a communication protocol to ensure that the impression data is transmitted accurately.

[1354] Step 10:

[1355] The server analyzes the received data to identify changes in emotional state and trends in positive emotions, such as positive keywords like relaxation and a sense of security.

[1356] Step 11:

[1357] Based on the analysis results, the server generates useful mental care information for users (such as relaxation methods and stress management advice). The generated mental care information is stored in text format and link format.

[1358] Step 12:

[1359] The server transmits the generated mental care information to the terminal, packaging the data in a format that is easy for the user to access.

[1360] Step 13:

[1361] The device displays the received mental care information to the user, who can then practice further relaxation and stress management based on the mental care information.

[1362] Example 1

[1363] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1364] In modern society, the increase in stress and negative emotions caused by daily life and work has become a problem. This has led to a growing need for mental health care, but the difficulty of self-awareness and emotional expression makes effective care difficult. In particular, there are few systems that allow users to visually check their own emotions and obtain appropriate mental health care information. Safe handling of emotional and impression data is also an important issue.

[1365] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1366] In this invention, the server includes means for inputting a user's emotions in text format, means for securely transmitting the input emotion data to the server, means for analyzing the transmitted emotion data using natural language processing technology, means for generating artwork using a generative AI model based on the analyzed emotion data, means for displaying the generated artwork to the user, means for inputting the user's impressions, and means for re-analyzing the input emotion data and providing mental care information, thereby enabling the user to visually confirm their own emotions and obtain appropriate mental care information.

[1367] A "user" is someone who uses the system to input their own emotions and receive artwork and mental care information.

[1368] The "means for inputting emotions in text format" is an interface that allows a user to input their own emotions and stress factors as text information.

[1369] "Means for securely transmitting input emotion data to a server" refers to a function that transmits the emotion text data input by the user to a server using a secure communication method (e.g., HTTPS).

[1370] "Means for analyzing using natural language processing technology" refers to technology (e.g., a natural language processing engine) used to analyze the text data received by the server and extract the main emotional categories and intensity of the emotions.

[1371] "Means for generating artwork using a generative AI model" refers to an artificial intelligence model (e.g., image generation AI) for automatically generating digital art based on the results of sentiment analysis.

[1372] The "means for displaying the generated artwork to the user" is a function for displaying the artwork sent from the server on the user terminal.

[1373] The "means for inputting user's impressions" is an interface that allows the user to re-input their impressions and feelings about the displayed artwork.

[1374] The "means for re-analyzing input impression data and providing mental care information" is a function that analyzes the impression data input by the user again, grasps the user's emotional state, and then generates and provides appropriate mental care information.

[1375] An "emotion category" is a category for classifying the user's emotions (e.g., pressure, stress).

[1376] "Emotion Intensity" is a score that quantifies the strength of the emotion the user is feeling.

[1377] A "secure connection" is an encrypted communication method used to securely send and receive data between a device and a server.

[1378] The present invention provides a system for supporting mental health care by generating artwork based on a user's emotional data. The system mainly includes the following components: an emotion input means, an emotion analysis means, an artwork generation means, an artwork display means, an impression input means, an impression analysis means, and a mental health care information provision means.

[1379] System Configuration

[1380] The hardware required to implement the system includes the devices used by users (e.g., smartphones, PCs) and the server that processes and manages the data. The software uses a natural language processing engine (e.g., Google NLP API) and a generative AI model (e.g., DALL-E).

[1381] Processing flow

[1382] First, the user enters the negative emotions or stressors they are currently experiencing into the device in text format. For example, they might enter, "I'm feeling stressed because of work pressure."

[1383] The device then sends the entered text data to the server using a secure connection (e.g., HTTPS), and notifies the user whether the transmission was successful.

[1384] The server cleans the received text data and passes it to a natural language processing engine for analysis, which extracts major emotional categories (e.g., pressure, stress) and emotional intensities (scores) from the data.

[1385] The server then uses a generative AI model to generate artwork based on the emotion analysis—for example, choosing vibrant colors like red and yellow and sharp shapes when stress levels are high—and the artwork is generated digitally.

[1386] The generated artwork is sent from the server to the device, which then displays it to the user. After viewing the artwork, the user can input their impressions and positive emotions into the device. For example, they can input a comment like, "Looking at this art made me feel a little more relaxed."

[1387] The user's impression data is sent back to the server, which analyzes it again. This analysis allows the server to understand the user's emotional state and generate appropriate mental care information. The generated mental care information is then sent to the user's device and displayed to the user.

[1388] Specific examples

[1389] A working user types, "I've been under a lot of pressure at work lately." This text data is sent from the device to a server, which uses a natural language processing engine to analyze the emotion keywords "pressure" and "stress" and calculates an emotion score.

[1390] The server then uses a generative AI model to generate artwork with sharp shapes in red and yellow tones based on the emotion scores, and the artwork is sent to the user's device for viewing.

[1391] The user inputs their impression, such as, "Looking at this art helped me relax a little." This impression data is sent back to the server, where it is analyzed and specific advice on how to relax is generated and provided to the user's device.

[1392] Prompt Sentence Examples

[1393] "I'm feeling the pressure. Visualize how it feels."

[1394] "Look at this art and tell us how it makes you feel so we can provide you with helpful care information for next time."

[1395] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1396] Step 1:

[1397] The user inputs their emotions in text format. For example, they input a sentence such as "I feel stressed because of work pressure" into the device interface. Input: User's emotion text data. Output: Emotion text data saved on the device.

[1398] Step 2:

[1399] The device sends the entered text data to the server using a secure connection. HTTPS is used to protect the data when it is sent. Input: Emotion text data stored on the device. Output: Emotion text data sent to the server.

[1400] Step 3:

[1401] The server stores the received text data and performs data cleaning. Preprocessing is performed to remove unnecessary spaces and special characters. Input: Emotion text data sent to the server. Output: Cleaned emotion text data stored on the server.

[1402] Step 4:

[1403] The server passes the cleaned text data to a natural language processing engine for sentiment analysis. The analysis extracts the main sentiment categories and their numerical values ​​of sentiment intensity. Input: Cleaned sentiment text data. Output: Sentiment categories and sentiment intensity as analysis results.

[1404] Step 5:

[1405] The server uses a generative AI model based on the results of emotion analysis to generate artwork. For example, if the emotion intensity is high, it will use red and yellow colors and generate artwork with sharp shapes. Input: Emotion category and emotion intensity. Output: Generated digital artwork.

[1406] Step 6:

[1407] The server sends the generated artwork to the device. The device displays the received artwork to the user in a dedicated viewer. Input: Generated digital artwork. Output: Artwork displayed on the device.

[1408] Step 7:

[1409] The user inputs their impressions after viewing the artwork in text format into the device. For example, they might input "Looking at this art made me feel a little relaxed." Input: User's impression text data. Output: Impression text data saved on the device.

[1410] Step 8:

[1411] The device sends the user's feedback data to the server using a secure connection. Input: Feedback text data stored on the device. Output: Feedback text data sent to the server.

[1412] Step 9:

[1413] The server passes the received sentiment data to the natural language processing engine for further analysis. Emotion categories and emotional intensities are extracted to understand the user's current emotional state. Input: sentiment text data sent to the server. Output: Emotional state as the analysis result.

[1414] Step 10:

[1415] The server generates appropriate mental care information based on the analysis results and sends it to the device. The device displays the received mental care information to the user. Input: Emotional state as the analysis result. Output: Mental care information displayed on the device.

[1416] (Application example 1)

[1417] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1418] There is a need for a method to effectively alleviate users' stress and negative emotions and support their mental health. However, current mental health services lack a mechanism for providing instant and personalized care based on a user's emotional analysis. They also lack a method for visually expressing emotions and thereby improving the user's psychological state. Furthermore, there is a need for an efficient means for providing such care to multiple users individually.

[1419] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1420] In this invention, the server includes a means for inputting a user's emotions, a means for analyzing the input emotion data, and a means for generating artwork based on the analyzed emotion data. This allows users to visually check their own emotions in real time and instantly obtain optimal mental care information based on the results. Furthermore, by including a means for distributing the artwork and mental care information generated based on the emotion data, it becomes possible to provide care efficiently and individually to multiple users.

[1421] The "means for inputting user's emotions" is an interface that allows the user to input their own emotions and situations into the system in text format.

[1422] The "means for analyzing input emotional data" is a mechanism for analyzing the emotional data input by the user using natural language processing and machine learning techniques, and extracting emotional categories and their intensities.

[1423] The "means for generating artwork based on analyzed emotional data" refers to an algorithm or program that selects appropriate colors and shapes based on emotional analysis and generates digital art.

[1424] The "means for displaying the generated artwork to the user" refers to a display device or software that displays the generated digital art on the user's terminal, allowing the user to visually confirm it.

[1425] The "means for inputting user impressions" is an interface that allows the user to re-input impressions and feelings that they had after viewing the displayed artwork.

[1426] The "means for analyzing inputted impression data and providing mental care information" is a system that analyzes the user's impression data to re-understand the emotional state, and generates and provides appropriate mental care information.

[1427] "Means for distributing artwork and mental care information generated based on emotional data" refers to a network or communication means for distributing the generated digital art and mental care information to users and providing care individually to multiple users.

[1428] "Natural language processing technology" is a technology for mechanically analyzing text data and extracting structured information.

[1429] An "emotion category" is a type of emotion classified based on analyzed emotion data.

[1430] "Emotion intensity" is an index that indicates the strength or degree of an emotion in the analyzed emotion category.

[1431] The present invention provides details of a system for supporting mental care by generating artwork based on a user's emotional data. An embodiment of the system will be described below.

[1432] Overall system configuration

[1433] The system mainly consists of the following components:

[1434] 1. A way to input user emotions

[1435] Users use a device such as a smartphone to input their feelings into the system in text format, such as "I've been feeling a lot of pressure at work lately."

[1436] 2. A method for analyzing input emotion data

[1437] Emotional text data sent from the device is passed to a server, where it is analyzed for emotional category and intensity using natural language processing (NLP) technology.

[1438] 3. A method for generating artwork based on analyzed emotion data

[1439] Based on the analysis of emotional data, appropriate colors and shapes are selected and digital art is generated using a generative AI model.

[1440] 4. A means of displaying the generated artwork to the user

[1441] The generated digital art is sent from the server to the terminal and displayed on the user's visual display device (smartphone display).

[1442] 5. A way to input user feedback

[1443] The user then enters their thoughts after viewing the displayed artwork in text format, for example, "Looking at this art made me feel a little relaxed."

[1444] 6. A means of analyzing inputted impression data and providing mental care information

[1445] The retransmitted impression data is analyzed by the server, and optimal mental care information is generated. This information is then sent to the user and displayed on their device.

[1446] 7. A means of delivering artwork and mental health information generated based on emotional data

[1447] The generated digital art and mental care information are distributed individually to multiple users.

[1448] Hardware and software used

[1449] Server: A server with high-performance computing power is used. This server is responsible for analyzing data and generating artwork.

[1450] Natural Language Processing (NLP) engine: For example, the Transformers library from Hugging Face is used.

[1451] Generative AI models: These are built using machine learning frameworks such as TensorFlow and PyTorch.

[1452] Smartphones: Used for users to input emotional data and display generated digital art and mental health information.

[1453] Data processing and calculation

[1454] 1. Emotion data analysis: The server uses a natural language processing engine to analyze the input text data and extract emotion categories and intensities.

[1455] 2. Artwork generation: Select colors and shapes based on the analysis results and generate appropriate digital art using a generative AI model.

[1456] 3. Analysis of impression data: The re-entered impression data is analyzed to understand the user's latest emotional state and provide appropriate mental care information.

[1457] Specific examples

[1458] If a user types, "I've been under a lot of pressure at work lately," this text data is sent from the device to the server. The NLP engine analyzes the emotional category of "stress" and extracts the corresponding intensity. The server selects red and sharp shapes and generates digital art using a generative AI model. The generated artwork is displayed on the smartphone for the user to visually confirm. If the user types, "Looking at this art helped me relax a bit," the impression data is sent again to the server, and appropriate mental care information is generated and displayed.

[1459] Prompt Sentence Examples

[1460] "The user has mentioned feeling stressed at work recently. Generate colorful, vivid digital art to visualize this emotion and provide appropriate mental health information."

[1461] In this way, users can receive help in effectively managing their emotions and relaxing through their smartphones.

[1462] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1463] Step 1:

[1464] The user inputs emotion data

[1465] The user uses a smartphone to input the emotions and stress factors they are feeling at that time in text format. For example, they might enter a sentence such as "I've been feeling a lot of pressure at work lately" into the smartphone's input form. This data is temporarily stored as text data on the device.

[1466] Input: Emotion text data entered by the user

[1467] Output: Emotion text data temporarily stored on the smartphone

[1468] Step 2:

[1469] Send emotion data to the server

[1470] The device sends the input emotion text data to a server via the Internet using a network protocol such as an HTTP POST request.

[1471] Input: Emotion text data sent from the device

[1472] Output: Emotion text data received by the server

[1473] Step 3:

[1474] The server analyzes the emotional data

[1475] The server passes the received emotion text data to a natural language processing (NLP) engine for analysis, specifically using Hugging Face's Transformers library to extract emotion categories (e.g., stress) and their intensity.

[1476] Input: Emotion text data received by the server

[1477] Output: Parsed emotion categories and their intensities

[1478] Step 4:

[1479] Generate artwork

[1480] The server generates digital art using a generative AI model (e.g., TensorFlow or PyTorch) based on the emotion category and its intensity obtained by the NLP engine, with color and shape determined by the emotion category.

[1481] Input: Parsed emotion category and its intensity

[1482] Output: Generated digital art data

[1483] Step 5:

[1484] Send the generated artwork to your device

[1485] The server then transmits the generated digital art data to the user's device via the Internet, again using the HTTP protocol.

[1486] Input: Generated digital art data

[1487] Output: Digital art data received on the device

[1488] Step 6:

[1489] View user-generated artwork

[1490] The user then views the digital art received on the device on a visual display device (smartphone display), thereby confirming the visualization of their own emotions.

[1491] Input: Digital art data displayed on the device

[1492] Output: Visual confirmation for the user

[1493] Step 7:

[1494] The user enters their feedback

[1495] After viewing the generated artwork, the user again enters their impressions in text format. For example, they might enter a comment like, "Looking at this art made me feel a little relaxed." This data is also temporarily stored on the device.

[1496] Input: User-entered text data

[1497] Output: Impression text data temporarily saved on the smartphone

[1498] Step 8:

[1499] Send the feedback data to the server

[1500] The terminal again transmits the input impression text data to the server via the Internet.

[1501] Input: Text data of impressions sent from the device

[1502] Output: Text data of the impressions received by the server

[1503] Step 9:

[1504] The server analyzes the opinion data

[1505] The server then passes the received impression text data back to the natural language processing (NLP) engine for analysis to grasp the user's latest emotional state.

[1506] Input: Text data of impressions received by the server

[1507] Output: Latest analyzed emotional state

[1508] Step 10:

[1509] Generates mental health information and provides it to users

[1510] The server generates appropriate mental care information based on the analyzed latest emotional state. This information is generated using a mental care database prepared in advance. The generated information is sent to the terminal via the Internet. The terminal receives this information and displays it to the user.

[1511] Input: Analyzed latest emotional state and mental care database

[1512] Output: Generated mental health information and its display

[1513] This allows users to effectively manage their emotions and receive appropriate mental health information.

[1514] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1515] The following describes in detail the embodiments of the present invention. The present invention is a system that recognizes and analyzes a user's emotions, generates artwork based on the analysis, and provides mental care information. In particular, the system is configured to incorporate an emotion engine for recognizing a user's emotions in real time.

[1516] The system includes the following main components:

[1517] Emotion input method

[1518] Emotion analysis means

[1519] Emotion Engine

[1520] Artwork Generation Method

[1521] Artwork display method

[1522] Comment input method

[1523] Impression analysis means

[1524] Means of providing mental health information

[1525] System flow

[1526] 1. User emotion input

[1527] The user inputs their feelings and stressors into the device in text format, for example, "I feel a lot of pressure at work."

[1528] 2. Sending Emotional Data

[1529] The device sends the input text data to the server, and the emotion engine uses this data to recognize emotions.

[1530] 3. Emotion Recognition by Emotion Engine

[1531] The server's emotion engine analyzes the transmitted text, voice, and even the user's facial expression data to recognize the emotion category (e.g., stress, pressure) and its intensity (numerical score) in real time. For example, if the user enters "tired," it will recognize the emotion as "fatigue." It also obtains complementary emotion data from the user's voice and facial expressions.

[1532] 4. Emotion analysis

[1533] The emotion data recognized by the emotion engine is further analyzed in detail by the server to identify the user's current emotional state.

[1534] 5. Artwork generation

[1535] The server then activates an artwork generation algorithm based on the emotion analysis results. For example, if the intensity of "stress" is high, it will select stimulating colors like red and yellow and sharp shapes to generate digital art.

[1536] 6. Artwork display

[1537] The server sends image data of the generated artwork to the device, which then displays the received artwork to the user, allowing the user to visually view the artwork that expresses their own emotions.

[1538] 7. User feedback

[1539] The user then inputs their impressions and positive emotions into the device after viewing the artwork. For example, they might input, "Looking at this art made me feel a little relaxed."

[1540] 8. Sending and analyzing feedback data

[1541] The device sends the user's impression data to the server, which then analyzes the received impression data to identify changes in the user's emotional state and trends in positive emotions. For example, it analyzes the keyword "relaxation."

[1542] 9. Providing mental health care information

[1543] Based on the analysis results, the server generates useful mental care information for the user (advice on relaxation methods and stress management). The generated mental care information is sent to the user's device and displayed to the user. Based on this, the user can practice further relaxation and stress management.

[1544] Specific examples

[1545] For example, if a user types "I've been feeling a lot of pressure at work lately," this text data is sent from the device to the server. The emotion engine then recognizes emotions such as "pressure" and "stress" in real time and evaluates their intensity. Furthermore, the user's facial expressions and voice data are also used for analysis.

[1546] The server generates digital art using colors such as red and yellow and sharp shapes based on the obtained emotional data, and sends this artwork to the user's device. The user looks at the displayed artwork and inputs their impression, such as "Looking at this art made me feel a little relaxed."

[1547] Finally, the server analyzes this data again to generate mental care information that will help users relax and send it to their device. In this way, users can easily express their feelings and obtain appropriate mental care information to maintain their mental health, even without specialized knowledge or skills.

[1548] The processing flow will be explained below.

[1549] Step 1:

[1550] The user enters their feelings and the causes of stress into the device in text format. For example, they might enter "I'm under a lot of pressure at work."

[1551] Step 2:

[1552] The terminal sends the entered text data to the server, using a communication protocol to ensure the data is sent reliably.

[1553] Step 3:

[1554] The server passes the received text data to the emotion engine and begins analysis. The emotion engine uses natural language processing technology to analyze the input text and recognize emotion categories (e.g., "stress") and their intensity (numerical score).

[1555] Step 4:

[1556] The emotion engine simultaneously analyzes the user's facial expression and voice data and recognizes emotions from these data, improving the accuracy of emotion category and intensity recognition.

[1557] Step 5:

[1558] The server uses the emotion data obtained from the emotion engine to activate an artwork generation algorithm. Based on the analysis results, it selects appropriate colors and shapes to generate digital art. For example, if the intensity of "stress" is high, it selects stimulating colors like red and yellow and sharp shapes.

[1559] Step 6:

[1560] The server saves the generated artwork in image format and sends the data to the terminal, using a communication protocol to ensure that the image data is transferred accurately.

[1561] Step 7:

[1562] The device displays the received artwork to the user, allowing the user to visually confirm the artwork that expresses their emotions.

[1563] Step 8:

[1564] After viewing the artwork, the user again inputs their impressions and positive emotions into the device, for example, "Looking at this art made me feel a little relaxed."

[1565] Step 9:

[1566] The terminal transmits the user's impression data to the server using a communication protocol to ensure that the impression data is transmitted accurately.

[1567] Step 10:

[1568] The server then passes the received impression data back to the emotion engine, which analyzes changes in the emotional state and trends in positive emotions. For example, it checks whether the keyword "relaxed" is included.

[1569] Step 11:

[1570] Based on the analysis results, the server generates useful mental care information for the user, such as advice on relaxation techniques and stress management.

[1571] Step 12:

[1572] The server transmits the generated mental care information to the terminal, using a communication protocol to ensure reliable data transfer.

[1573] Step 13:

[1574] The device then displays the received mental care information to the user, who can then use the information to further relax and manage stress.

[1575] Example 2

[1576] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1577] In modern society, many people suffer from stress and emotional burdens, and managing and caring for these stressors is becoming increasingly important. However, there are few systems that can accurately recognize these emotions in real time and provide appropriate mental care information based on that information. Therefore, there is a need for a system that allows users to easily input their own emotional state, have it analyzed, and provide appropriate coping strategies. Furthermore, expressing emotions through visual means and receiving feedback based on those emotions is expected to lead to more effective mental care.

[1578] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1579] In this invention, the server includes a means for transmitting user emotion data to the server, a means for analyzing the emotion data received by the server using a natural language processing algorithm, and a means for generating artwork based on the analyzed emotion data. This allows the emotion data input by the user to be analyzed, and artwork generated based on the analysis results to be quickly provided to the user. As a result, the user can visually understand their own emotions and receive individually customized mental care information.

[1580] "User" refers to a person who uses this system to input emotion data and impression data.

[1581] "Terminal" refers to the electronic device used by the User to input emotional and / or impression data and to receive and display artwork and mental health information.

[1582] The term "server" refers to a remote computer system that analyzes the received emotional and impression data and generates artwork and mental care information.

[1583] "Emotion data" refers to data entered by a user in text format about their emotions and the causes of stress.

[1584] A "natural language processing algorithm" refers to a computational method for analyzing emotional data and recognizing the emotional categories and intensity contained within it.

[1585] "Emotion category" refers to the type of emotion (e.g., "stress" or "pressure") classified as a result of analyzing emotion data.

[1586] "Intensity" refers to a numerical representation of the strength of an emotion for a particular emotion category.

[1587] "Artwork" refers to visual content (images) generated based on analyzed emotional data.

[1588] "Opinion data" refers to data entered by a user in text format as their impressions or feedback on the displayed artwork.

[1589] "Mental care information" refers to information such as advice on relaxation methods and stress management that is generated based on the analyzed impression data and provided to the user.

[1590] The system of the present invention recognizes and analyzes the user's emotions in real time, and generates artwork based on the results to provide mental care information. This system is implemented mainly using the following hardware and software.

[1591] Hardware and software used

[1592] Device: Used by users to input and send emotional and sentiment data, and to receive and display artwork and mental health information. Examples include smartphones, tablets, and PCs.

[1593] Server: A computer system that receives and analyzes emotional and impression data, and generates and transmits artwork and mental care information.

[1594] Natural language processing algorithms: Software techniques used to analyze user sentiment data, for example, NLP libraries implemented in Python.

[1595] Generative AI model: An algorithm that uses machine learning techniques to generate artwork based on sentiment analysis results.

[1596] Example of a system

[1597] For example, if a user types "I've been under a lot of pressure at work lately," this text data is sent from the device to the server. The server then uses an emotion engine to recognize emotions such as "pressure" and "stress" in real time and evaluate their intensity. Furthermore, the user's facial expressions and voice data are also used for analysis.

[1598] The server generates digital art using colors such as red and yellow and sharp shapes based on the obtained emotional data, and sends this artwork to the user's device. The user looks at the displayed artwork and inputs their impression, such as "Looking at this art made me feel a little relaxed."

[1599] Finally, the server analyzes this feedback data, generates mental care information that will help users relax, and sends it to the user's device. Based on the displayed advice, users can practice further relaxation and stress management.

[1600] Prompt Sentence Examples

[1601] "Describe a system that recognizes and analyzes a user's emotions, generates artwork based on the user's emotional state, and displays the results to the user."

[1602] The system of the present invention allows users to easily express their feelings and obtain appropriate mental care information to maintain their mental health, even without specialized knowledge or skills.

[1603] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1604] Step 1:

[1605] The user inputs emotion data into the terminal. Specifically, the user inputs emotion or stress factors such as "I've been under a lot of pressure at work lately" into a text input field on the terminal.

[1606] Input: User's text data

[1607] Output: Text information entered into the terminal

[1608] Step 2:

[1609] The device sends the input emotion data to the server. When the user taps the "Send" button, the device generates an HTTP request and sends the text data to the server.

[1610] Input: Text information entered into the device

[1611] Output: Text data sent to the server

[1612] Step 3:

[1613] The server analyzes the received text data using a natural language processing algorithm. The server uses an NLP library to analyze the text and calculates an emotion category (e.g., "stress" or "pressure") and its intensity score.

[1614] Input: Text data sent

[1615] Output: Emotion category and its intensity score

[1616] Step 4:

[1617] The server performs a detailed analysis of the acquired emotional data. It compares it with past emotional data and analyzes changes and patterns in the user's emotions. For example, it evaluates whether the intensity of pressure has increased over the past few days.

[1618] Input: Emotion categories and their intensity scores

[1619] Output: Detailed analysis results

[1620] Step 5:

[1621] The server then uses a generative AI model to generate artwork based on the analysis results. Based on the emotion category and its intensity, the generative AI model selects colors and shapes to generate digital art. For example, if the intensity of stress is high, stimulating colors like red and yellow will be used, and sharp shapes will be created.

[1622] Input: Detailed analysis results

[1623] Output: Image data of the generated artwork

[1624] Step 6:

[1625] The server sends the image data of the generated artwork to the terminal, and information including the image data is sent as an HTTP response.

[1626] Input: Image data of the generated artwork

[1627] Output: Image data sent to the device

[1628] Step 7:

[1629] The terminal displays the received artwork to the user. Specifically, the artwork is displayed full-screen on the terminal screen, allowing the user to enjoy it visually.

[1630] Input: Image data

[1631] Output: Artwork displayed on screen

[1632] Step 8:

[1633] The user inputs their thoughts after viewing the artwork into the device, for example, by typing "This art made me feel a little relaxed" into the text input field.

[1634] Input: User testimonial text

[1635] Output: Impression data entered into the terminal

[1636] Step 9:

[1637] The device sends the impression data to the server. When you enter your impression and tap the "Send" button, an HTTP request is generated and sent to the server.

[1638] Input: Impression data entered into the terminal

[1639] Output: Feedback data sent to the server

[1640] Step 10:

[1641] The server analyzes the sentiment data using a natural language processing algorithm to extract positive emotions and keywords, and evaluates changes in the user's emotional state.

[1642] Input: Impression data

[1643] Output: Changes in emotional state and evaluation results

[1644] Step 11:

[1645] The server generates mental care information based on the analysis results. Based on changes in emotional state and the evaluation results, it generates advice on relaxation methods and stress management, and creates mental care information to provide to the user.

[1646] Input: Emotional state changes and evaluation results

[1647] Output: Generated mental health information

[1648] Step 12:

[1649] The server sends the generated mental care information to the terminal, and data including the mental care information is sent as an HTTP response.

[1650] Input: Generated mental health information

[1651] Output: Mental health information sent to the device

[1652] Step 13:

[1653] The mental care information received by the device is displayed to the user. The mental care information is displayed on the device screen in the form of a dedicated widget or notification.

[1654] Input: Mental care information

[1655] Output: Mental health information displayed on the screen

[1656] (Application example 2)

[1657] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1658] In modern society, stress and pressure affect many people. However, there are limited systems that can identify an individual's emotional state in real time and provide appropriate mental health care information based on that information. Even if emotion recognition systems exist, there is a lack of a way to input emotions without requiring the user's effort or to provide visual feedback of emotions.

[1659] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for inputting a user's emotions in voice or text format, means for analyzing the input emotional data, means for generating artwork based on the analyzed emotional data, means installed in the smart device for displaying the generated artwork to the user, means for inputting the user's impressions, and means for analyzing the input impression data and providing mental care information. This allows the user to easily input their emotional state via the smart device and receive appropriate mental care information in real time based on the analysis results.

[1660] "A means for inputting emotions in voice or text format" refers to a device or software that has the function of allowing a user to input emotions as voice or text data.

[1661] "Means for analyzing emotional data" refers to devices or software that have the function of analyzing input emotional data using algorithms or AI models and identifying the type and intensity of emotions.

[1662] "Means for generating artwork" refers to devices or software that have the function of creating digital art using specific colors and shapes based on analyzed emotional data.

[1663] "Means installed on a smart device" means a device or software installed on smart glasses or other wearable devices that has the ability to display generated artwork or mental health information to the user.

[1664] The "means for inputting user's impressions" refers to a device or software that has a function that allows the user to re-input impressions or genetic emotions after viewing the generated artwork.

[1665] "Means for analyzing input impression data and providing mental care information" refers to a device or software that has the function of analyzing the user's impression data and generating and providing useful mental care information to the user based on the results.

[1666] The "means for converting voice input into text format" refers to a device or software that has the function of automatically converting a user's voice data into text data.

[1667] A "cloud-based AI model" is an algorithm or software that accesses a cloud server via the internet and uses artificial intelligence technology to perform data analysis and emotion recognition.

[1668] A "means for generating prompt sentences" is a device or software that has the function of enabling an AI model to generate appropriate prompt sentences or responses based on input data from a user.

[1669] The present invention will be described in detail below with reference to an embodiment thereof. This system allows a user to input their emotions in the form of voice or text, analyzes the data in real time, generates artwork, and provides mental health information to the user.

[1670] Hardware and software used

[1671] The system includes the following hardware and software:

[1672] Smart devices (smart glasses, smartphones, etc.)

[1673] Voice Recognition Software

[1674] Text Analysis Software

[1675] Cloud Server

[1676] AI model (generative AI model)

[1677] Digital Art Generation Software

[1678] Display

[1679] System flow

[1680] 1. Emotion Input

[1681] Users can input their emotions using the voice input function of their smart device, for example, by speaking, "I've been feeling pressure at work lately," or by typing in text, "I've been feeling stressed lately."

[1682] 2. Speech-to-text conversion

[1683] When voice input is performed, the voice recognition software in the device converts the voice data into text data, which is then sent to a cloud server.

[1684] 3. Emotion analysis

[1685] The cloud server analyzes the received text data and uses a generative AI model to identify the type of emotion (e.g., stress, pressure) and its intensity. The analyzed emotion data is then sent back to the smart device.

[1686] 4. Artwork generation

[1687] The smart device generates digital art based on the emotion analysis results. For example, if the stress level is high, artwork using red and yellow colors and sharp shapes will be generated. This artwork visually represents the user's emotions.

[1688] 5. Artwork display

[1689] The generated digital art is displayed on the smart device's display, allowing the user to visually appreciate the artwork.

[1690] 6. Input your thoughts

[1691] The user then re-enters their thoughts and positive emotions after viewing the displayed artwork. For example, they might enter text such as, "Looking at this art made me feel a little relaxed."

[1692] 7. Analysis of impressions and provision of mental health information

[1693] The cloud server then analyzes the sentiment data again to identify changes in the user's emotional state and trends in positive emotions. This information is then used to generate useful mental health information for the user, which is then sent to the user's smart device. For example, advice such as "Take a deep breath. It's important to take time to relax" is provided.

[1694] Specific examples

[1695] For example, if a user types, "I've been feeling pressure at work lately," the speech is converted into text, and the cloud server identifies emotions such as "pressure" and "stress" and evaluates their intensity. Based on this data, the smart device generates digital art with red and yellow colors and sharp shapes and displays it to the user. The user then types their impression, such as "Looking at this art made me feel a little more relaxed," and the cloud server analyzes the data and provides mental care information such as "Take a deep breath."

[1696] Example prompt sentence:

[1697] "I've been feeling a lot of pressure at work lately. I'd like to relax a bit."

[1698] In this way, this system allows users to effectively express their emotions and provides appropriate mental care information based on those emotions.

[1699] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1700] Step 1:

[1701] A user inputs their emotions in the form of voice or text using a smart device. For example, they can say or type, "I've been feeling pressure at work lately." This is input data, which is collected as voice data or text data.

[1702] Step 2:

[1703] The device's voice recognition software converts voice data into text data. If the input is voice, the voice recognition software analyzes the voice and outputs it as text data. In this case, the input is voice data and the output is text data.

[1704] Step 3:

[1705] The device sends the converted text data to the cloud server using a data communication protocol. The input is text data, and the output is data sent to the server.

[1706] Step 4:

[1707] The cloud server performs emotion analysis on the received text data using a generative AI model. The generative AI model analyzes the text and identifies the type of emotion (e.g., stress, pressure) and its intensity. The input is text data, and the output is emotion data (type and intensity of emotion).

[1708] Step 5:

[1709] The server sends the analyzed emotion data to the smart device using a data communication protocol. The input is emotion data, and the output is data sent to the device.

[1710] Step 6:

[1711] The device generates digital art based on the emotion analysis results. Digital art generation software analyzes the emotion data and generates artwork with appropriate colors and shapes. The input is emotion data, and the output is digital art data.

[1712] Step 7:

[1713] The terminal displays the generated digital art on a display, allowing the user to visually appreciate the artwork. The input is digital art data, and the output is a display of the artwork.

[1714] Step 8:

[1715] The user then inputs his or her impressions after viewing the displayed artwork. For example, the user may input text such as "Looking at this artwork helped me to relax a little." This is the input of new impression data.

[1716] Step 9:

[1717] The device sends user feedback data to the cloud server. The input is the feedback data, and the output is the data sent to the server.

[1718] Step 10:

[1719] The cloud server analyzes the input impression data and analyzes changes in emotional state and trends in positive emotions. The generative AI model analyzes the impression data and generates mental care information. The input is impression data, and the output is mental care information.

[1720] Step 11:

[1721] The server sends the generated mental care information to the smart device and displays it to the user. For example, advice such as "Take a deep breath. It's important to take time to relax" is displayed. The input is the mental care information, and the output is the display to the user.

[1722] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1723] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1724] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1725] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1726] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1727] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1728] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1729] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1730] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1731] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1732] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1733] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1734] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1735] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1736] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1737] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1738] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1739] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1740] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1741] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1742] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1743] The following is further disclosed regarding the above embodiment.

[1744] (Claim 1)

[1745] a means for inputting a user's emotion;

[1746] A means for analyzing input emotion data;

[1747] means for generating artwork based on the analyzed emotion data;

[1748] means for displaying the generated artwork to a user;

[1749] A means for inputting user feedback;

[1750] A means for analyzing the inputted impression data and providing mental care information;

[1751] A system including:

[1752] (Claim 2)

[1753] 10. The system of claim 1, further comprising means for analyzing the user's emotion data with natural language processing techniques.

[1754] (Claim 3)

[1755] 10. The system of claim 1, further comprising means for selecting colors and shapes when generating artwork based on emotional categories and their intensities.

[1756] "Example 1"

[1757] (Claim 1)

[1758] a means for inputting a user's emotion in text form;

[1759] a means for securely transmitting the input emotion data to a server;

[1760] A means for analyzing the transmitted emotion data using natural language processing technology;

[1761] a means for generating artwork using a generative AI model based on the analyzed emotion data; and

[1762] means for displaying the generated artwork to a user;

[1763] A means for inputting user feedback;

[1764] A means for reanalyzing the inputted impression data and providing mental care information;

[1765] A system including:

[1766] (Claim 2)

[1767] 10. The system of claim 1, further comprising means for selecting a color and a shape of the artwork based on the emotional category and its intensity.

[1768] (Claim 3)

[1769] 10. The system of claim 1, further comprising means for transmitting and receiving input emotion data and sentiment data over a secure connection.

[1770] "Application Example 1"

[1771] (Claim 1)

[1772] a means for inputting a user's emotion;

[1773] A means for analyzing input emotion data;

[1774] means for generating artwork based on the analyzed emotion data;

[1775] means for displaying the generated artwork to a user;

[1776] A means for inputting user feedback;

[1777] A means for analyzing the inputted impression data and providing mental care information;

[1778] Further comprising means for delivering artwork and mental care information generated based on the emotion data;

[1779] A system including:

[1780] (Claim 2)

[1781] 10. The system of claim 1, further comprising means for analyzing the user's emotion data with natural language processing techniques.

[1782] (Claim 3)

[1783] 10. The system of claim 1, further comprising means for selecting colors and shapes when generating artwork based on emotional categories and their intensities.

[1784] "Example 2: Combining Emotion Engines"

[1785] (Claim 1)

[1786] a means for inputting a user's emotion;

[1787] means for transmitting the input emotion data to a server;

[1788] A means for analyzing the emotion data received by the server using a natural language processing algorithm;

[1789] means for generating artwork based on the analyzed emotion data;

[1790] means for transmitting the generated artwork to a user terminal;

[1791] means for displaying the generated artwork on the user's terminal;

[1792] a means for the user to input their thoughts on the artwork;

[1793] means for transmitting the inputted impression data to a server;

[1794] A means for the server to analyze the impression data and generate mental care information;

[1795] means for transmitting the generated mental care information to a terminal of the user and displaying the information;

[1796] A system including:

[1797] (Claim 2)

[1798] 10. The system according to claim 1, further comprising means for analyzing the user's emotion data using natural language processing techniques and recognizing emotion categories and their intensities based on the results.

[1799] (Claim 3)

[1800] The system according to claim 1, further comprising means for selecting a color and a shape based on the emotional category and its intensity when generating the artwork, and transmitting image data of the generated artwork to the user's terminal.

[1801] "Application example 2 when combining emotion engines"

[1802] (Claim 1)

[1803] a means for inputting a user's emotion in voice or text form;

[1804] A means for analyzing input emotion data;

[1805] means for generating artwork based on the analyzed emotion data;

[1806] means installed on the smart device for displaying the generated artwork to the user;

[1807] A means for inputting user feedback;

[1808] A means for analyzing the inputted impression data and providing mental care information;

[1809] A system including:

[1810] (Claim 2)

[1811] 10. The system of claim 1, further comprising means for converting a user's voice input into text form.

[1812] (Claim 3)

[1813] 10. The system of claim 1, further comprising means for analyzing the emotion data using a cloud-based AI model to generate prompt sentences. [Explanation of symbols]

[1814] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means for inputting a user's emotion; A means for analyzing input emotion data; means for generating artwork based on the analyzed emotion data; means for displaying the generated artwork to a user; A means for inputting user feedback; A means for analyzing the inputted impression data and providing mental care information; A system including:

2. The system of claim 1 , further comprising means for analyzing the user's emotion data using natural language processing techniques.

3. 10. The system of claim 1, further comprising means for selecting colors and shapes based on emotional categories and their intensities when generating artwork.

Images