system

Abstract

Provide a system. 【Solution means】 Means for acquiring emotional information input by the user, Means for analyzing the emotional information and generating a response based on the analysis result, Means for providing the analysis result to the user, Means for acquiring biological information, Means for analyzing the biological information and generating a proposal according to the user's state, Means for providing the proposal to the user, Means for providing means for anonymous and safe communication between users, Means for proposing daily life support and relaxation methods based on the user's health status, A system including the above.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance as a response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern society, mental health problems are worsening, and many people are seeking support that can be quickly and individually addressed. However, with conventional methods, it is difficult to provide real-time responses based on the emotional state and biometric data of users, and there is also a lack of a safe environment for communicating with others while maintaining privacy. It is required to improve such a situation.

Means for Solving the Problems

[0005] This invention provides means for acquiring user emotional data, analyzing it using natural language processing technology, and providing feedback. It also includes means for acquiring user biometric data and generating and providing suggestions tailored to the user's state. Furthermore, by providing means for anonymous and secure communication among users, it provides a system that realizes comprehensive support for the mental health problems faced by individual users.

[0006] A "user" refers to an individual who uses this system and is the entity that provides emotional data and biometric data.

[0007] "Emotional data" refers to text information entered by the user, which includes descriptions of their mental state and emotions.

[0008] "Natural language processing" is a technology that enables computers to understand human language, and it is a method of analyzing text data to extract specific information.

[0009] "Feedback" refers to advice and recommendations for users that are generated based on the results of analyzing emotional data.

[0010] "Biometric data" refers to information that indicates a user's physical condition, and includes measurable data such as heart rate and skin potential response.

[0011] A "suggestion" is advice or recommendations that indicate actions the user should take or things they should consider, based on the analyzed biometric data.

[0012] "Anonymity" refers to a state in which a user's personal information is protected from identification, enabling information exchange while maintaining privacy.

[0013] "Interaction" refers to communication and information exchange among users, and is an activity that contributes to mutual emotional support. [Brief explanation of the drawing]

[0014] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Embodiments for Carrying Out the Invention

[0015] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0018] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0019] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs, various parameters, and the like. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0020] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0022] [First Embodiment]

[0023] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0024] As shown in Figure 1, the 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.

[0025] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0027] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and 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.

[0028] 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 perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0030] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 according to the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0033] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0034] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0035] This invention is a system designed to support the mental health of users. The system acquires emotional data entered by the user through a terminal, and a server analyzes this data to provide feedback to the user. Furthermore, it can analyze biometric data acquired from the user themselves and provide appropriate suggestions based on their psychological state.

[0036] First, the user inputs their emotional state in text format into the device. This emotional data is then sent from the device to the server. The server uses natural language processing technology to analyze the emotional data. This analysis reveals the user's emotional patterns and mood tendencies, and feedback is generated based on the analysis results. For example, if the emotional data entered is "I'm very tired today," the server generates the feedback "I recommend you take some time to relax" and sends it to the device for the user to receive.

[0037] Next, utilizing the sensor functions built into the device, the device collects biometric data in real time. This data includes heart rate and skin potential responses, and is used as an indicator of the user's physical stress and relaxation level. The collected biometric data is sent back to the server and analyzed to understand the user's current state. Through this analysis, the server makes suggestions, such as recommending rest, as needed and notifies the user. In this way, by combining monitoring of physical data and analysis of emotional data, the system provides support tailored to the user's mental and physical state.

[0038] Furthermore, users can participate anonymously in online communities within the system. The server anonymizes posts and immediately checks for inappropriate content. This allows users to interact with others and receive support regarding their issues. The server can also recommend helpful community groups and threads based on the user's interests and emotional state.

[0039] The present invention aims to effectively and safely address the individual mental health issues of users, and provides a specific system configuration for doing so.

[0040] The following describes the processing flow.

[0041] Step 1:

[0042] The user inputs their emotional state as text into the device. Emotional data is entered in the form of "I'm tired today."

[0043] Step 2:

[0044] The terminal retrieves the input emotion data and prepares to send that data to the server.

[0045] Step 3:

[0046] The server receives emotion data sent from the terminal and runs an AI model for analysis. The AI ​​model uses natural language processing techniques to analyze the text and identify the user's emotional state.

[0047] Step 4:

[0048] The server generates appropriate feedback based on the results of the emotion analysis. For example, if fatigue is detected, feedback such as "We recommend you take a rest" will be generated.

[0049] Step 5:

[0050] The server sends the generated feedback to the terminal and notifies the user.

[0051] Step 6:

[0052] The device's sensors continuously collect biometric data such as heart rate and skin potential responses.

[0053] Step 7:

[0054] The device transmits the collected biometric data to the server.

[0055] Step 8:

[0056] The server analyzes biometric data to assess the user's stress level and relaxation level.

[0057] Step 9:

[0058] The server will suggest rest and relaxation as needed. For example, if your stress level is high, it might suggest, "We recommend taking a short break."

[0059] Step 10:

[0060] The server manages online communities that users can join and supports anonymous interaction. It also filters out inappropriate content.

[0061] Step 11:

[0062] The server recommends relevant community chats and groups based on the user's past interactions and interests.

[0063] (Example 1)

[0064] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0065] In modern society, there is a need to comprehensively support the mental and physical health of users. However, existing systems struggle to effectively analyze both emotional and biometric information and provide appropriate responses and recommendations based on that analysis. Furthermore, ensuring safe and anonymous communication among users is not adequately achieved. Solving these problems is the objective of this invention.

[0066] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0067] In this invention, the server includes means for acquiring emotional information input by the user, means for analyzing the emotional information and biometric information to generate indicators, and means for generating and providing responses based on the analysis results. This enables comprehensive support tailored to the mental and physical state of the user, as well as safe interaction among users.

[0068] A "user" is a person who uses the system to input emotional and biometric information and receive support.

[0069] "Emotional information" refers to text data that users input to express their own emotional state.

[0070] "Biometric information" refers to data that objectively indicates the user's physical condition, such as heart rate and electrocutaneous response.

[0071] A "server" is a device that analyzes acquired emotional and biometric information and generates appropriate responses and recommendations for the user.

[0072] "Natural language processing technology" refers to techniques for analyzing text data and understanding its meaning and emotions.

[0073] "Response" refers to feedback to the user generated based on the analysis results of emotional and biometric information.

[0074] A "recommendation" refers to specific action plans or advice provided to users based on the analysis results.

[0075] "Interaction" refers to a form of communication where users can communicate with each other anonymously and safely.

[0076] The embodiment of this invention is configured as a system for supporting the mental and physical health of users. This system is primarily intended for inputting and analyzing emotional information, collecting and analyzing biometric information, and supporting interaction among users.

[0077] The user first inputs their emotional state as text data and sends it to a device. This device can be a smartphone or a personal computer. The input emotional information is sent to a server where it is analyzed. The server utilizes natural language processing technology, employing Python's NLTK and spaCy libraries to analyze the text data. Based on this analysis, the server understands the user's emotional tendencies and generates an appropriate response. For example, in response to input such as "I'm very tired today," the server might generate a response like, "I recommend you take some time to relax."

[0078] Sensors embedded in the device collect biometric information in real time. Specific data includes heart rate and electrocutaneous response. The collected biometric information is sent to a server where it is analyzed using Python's Pandas and NumPy libraries. The server uses this data to understand the user's current physical condition and, if necessary, generates recommendations to encourage rest.

[0079] The server also provides an environment where users can interact anonymously and securely within the system. User posts are instantly checked for inappropriate content using natural language processing. Furthermore, the server considers users' emotional states and interests to recommend appropriate communities and topics.

[0080] An example of a prompt in this invention is a question such as, "When my heart rate is elevated, what kind of relaxation advice should I receive?" This allows the system to provide specific support tailored to the user's individual condition through a generated AI model.

[0081] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0082] Step 1:

[0083] The user enters their emotional state into the device in text format. This input might be a sentence like, "I'm very tired today." This text is recognized as emotional information.

[0084] Step 2:

[0085] The terminal sends emotion information entered by the user to the server. This input data is securely transferred to the server using HTTPS as the communication protocol. The output is the transfer of text data to the server.

[0086] Step 3:

[0087] The server analyzes the received sentiment information using natural language processing techniques. This analysis process utilizes Python's NLTK and spaCy libraries; text data is tokenized, and sentiment scores are calculated. The analysis results output the sentiment tendency of the text.

[0088] Step 4:

[0089] The server generates an appropriate response based on the analysis results. For example, it might generate feedback such as, "We recommend you take some time to relax." This output is a terminal message intended for the user.

[0090] Step 5:

[0091] The terminal displays feedback sent from the server to the user. This allows the user to receive specific advice on how to take appropriate action. The output is a display of feedback information to the user.

[0092] Step 6:

[0093] Sensors embedded in the device collect biometric data in real time. This data includes heart rate and electrocutaneous responses. The output is the transfer of this biometric data from the device to a server.

[0094] Step 7:

[0095] The server analyzes the received biometric data. The analysis uses Python libraries such as Pandas and NumPy to extract trends and outliers from the data. This analysis then outputs the user's physical stress level.

[0096] Step 8:

[0097] Based on the analysis of biometric data, the server generates recommendations to encourage users to rest as needed. The output consists of specific action plans tailored to the user's condition.

[0098] Step 9:

[0099] Users participate anonymously in online communities within the system. Here, they exchange information with other users in text format. Input consists of user posts, which form the basis of the interaction.

[0100] Step 10:

[0101] The server monitors posts within the community and uses natural language processing to check for inappropriate content. The output consists of filtered posts to ensure safe communication.

[0102] Step 11:

[0103] The server recommends useful threads and groups based on the user's interests and emotional state. This allows the user to receive information and support that is relevant to them. The output is recommendation information for the user.

[0104] (Application Example 1)

[0105] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0106] In modern society, there is a need for effective systems to support the mental and physical health of the elderly. In particular, for the elderly to live their daily lives with peace of mind, it is crucial to understand their emotional state and biometric information in real time and provide appropriate feedback. However, conventional systems fail to adequately address the characteristics and needs of the elderly, making it difficult to provide effective support.

[0107] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0108] In this invention, the server includes means for analyzing emotional information input by the user and generating a response based on the analysis results, means for analyzing biometric information and generating suggestions tailored to the user's condition, and means for suggesting daily life support and relaxation methods based on the user's health condition. This comprehensively supports the mental and physical health of the elderly, enabling them to live their daily lives with peace of mind.

[0109] "User-inputted emotional information" refers to data that users use to record and input their own emotional state.

[0110] "Responses based on analysis results" refer to feedback provided to the user after analyzing emotional information obtained from the user.

[0111] "Means of providing information to users" refers to methods for informing users of the analyzed information and suggestions, and enabling them to view or utilize it.

[0112] "Means for acquiring biometric information" refers to methods for acquiring data that indicates the user's physical condition, such as heart rate and skin potential response.

[0113] "Suggestions tailored to the user's condition" refers to advice and recommendations for actions that help the user achieve a better state of being, based on the results of the user's biometric and emotional information.

[0114] "Means of anonymous and secure communication between users" refers to methods that allow users to exchange information and communicate with each other with peace of mind while protecting each other's privacy.

[0115] "Means of proposing support for daily life and relaxation methods" refers to methods that propose ways to contribute to stress reduction and relaxation in order to make the user's daily life more comfortable.

[0116] The system that realizes this invention includes three main components: a user, a terminal, and a server.

[0117] Users first input their emotional information using a device. This device is a portable electronic device such as a smartphone or tablet, and it can transmit this information to a server. The device provides a simple interface to assist with emotional information input. Furthermore, the device incorporates sensors that allow it to acquire biometric information such as heart rate and skin potential responses.

[0118] The server uses natural language processing techniques to analyze emotional information sent by the user. The program utilizes programming languages ​​such as Python and their libraries for this purpose. The responses generated from the emotional information analysis are provided to the user via the terminal as feedback. In addition, the server also analyzes biometric information and, based on the results, suggests appropriate daily life support and relaxation methods to the user.

[0119] For example, if a user enters "I'm very tired today," the server analyzes this emotional information and provides advice to encourage relaxation. The server also evaluates the user's stress level based on collected heart rate data and generates feedback such as "take a break."

[0120] Furthermore, the system utilizes generative AI models to provide an anonymous and secure online community in which users can participate. In this online community, users can interact with other users and share their experiences while protecting their privacy.

[0121] An example of a prompt message is: "Propose a mental health support app for seniors. This app will analyze emotional input and biometric data to provide feedback tailored to the user's health status. Please also describe specific use cases and recommended interface designs and features."

[0122] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0123] Step 1:

[0124] Users input their emotional information using a device. This input is in text format, and the device receives this information as data and sends it to the server.

[0125] Step 2:

[0126] The server analyzes the received emotional information using natural language processing techniques. The input is the user's emotional information, and the output is the analysis result based on emotional patterns. Through this analysis process, the server determines the user's emotional state.

[0127] Step 3:

[0128] The server generates a response based on the analysis results. In this step, it determines appropriate feedback from the sentiment analysis results and sends it directly to the terminal as output. For example, it might generate a suggestion such as "Take some time to relax."

[0129] Step 4:

[0130] Sensors on the device acquire biometric information. This includes heart rate and skin potential responses, and this data is collected in real time. The device compiles the biometric information and sends it back to the server.

[0131] Step 5:

[0132] The server performs data analysis based on biometric information. In this step, the input is biometric information, and the output is an evaluation result indicating the user's physical condition. Based on this, the server generates recommended actions for the user.

[0133] Step 6:

[0134] The device sends notifications to the user's device that provide suggestions based on their current state, such as "Take adequate rest." The device then displays these notifications to the user and provides an interface for them to take action on the specific suggestions.

[0135] Step 7:

[0136] The server utilizes a generative AI model to recommend online communities that the user can join. The input includes the user's interests and emotional state, and the output is a list of appropriate community groups. The server sends this list to the user's device, providing a safe and secure environment for interaction.

[0137] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0138] This invention is a system designed to support users' mental health management. By incorporating an emotion engine, it can more accurately recognize the user's emotions and provide feedback and suggestions. This system utilizes emotional data and biometric data to provide personalized advice to the user.

[0139] First, the user inputs their emotions as text into the device. This emotion data is sent from the device to the server. The server then utilizes an emotion engine and natural language processing techniques to analyze the text data. The emotion engine identifies emotions from the input text, detects specific emotional states, and then generates feedback corresponding to the identified emotions.

[0140] For example, if a user enters "I'm busy and tired from work," the emotion engine identifies this as a "stressed state." Based on the identified emotional state, the server generates feedback such as "We recommend you make time to relax" and provides it to the user through the device.

[0141] Next, sensors installed in the device collect biometric data such as the user's heart rate and skin potential response. Using this biometric data, the server analyzes the user's physical state and, in conjunction with the emotion engine, enables further suggestions tailored to the user's condition. For example, if a sudden increase in heart rate is detected, it can provide specific countermeasures such as, "We recommend you try taking some deep breaths."

[0142] Furthermore, users can interact anonymously within the online communities on this system. The servers manage these interactions to ensure their security and utilize an emotion engine to naturally recommend topics and groups that users might be interested in or should join.

[0143] Thus, this invention places an emotion engine at its core and embodies comprehensive support for users' mental health by performing multifaceted analysis that combines emotional data and biometric data. This results in a system that provides practical and effective responses tailored to the individual needs of users.

[0144] The following describes the processing flow.

[0145] Step 1:

[0146] The user enters text into the device that expresses their emotional state. The emotional data is entered in a format such as, for example, "I was very irritated today."

[0147] Step 2:

[0148] The terminal prepares to send the entered emotion data to the server. The data is formatted appropriately during this process.

[0149] Step 3:

[0150] The server passes the received emotion data to the emotion engine, which then begins analysis. The emotion engine uses natural language processing technology to identify the user's specific emotions from the text.

[0151] Step 4:

[0152] The server generates feedback based on the emotions identified by the emotion engine. For example, if "irritation" is detected, it will create feedback that includes advice on stress management.

[0153] Step 5:

[0154] The server sends the generated feedback to the terminal. The information is processed quickly so that users can see the feedback in a timely manner.

[0155] Step 6:

[0156] Sensors built into the device continuously collect biometric data such as heart rate and skin potential response. The acquired biometric data is then transmitted directly to the server.

[0157] Step 7:

[0158] The server analyzes the collected biometric data to assess the user's physical and emotional state. Based on this assessment, it integrates physical responses and emotional data to generate further action suggestions.

[0159] Step 8:

[0160] The server creates and sends suggestions to the user's device based on their real-time state. For example, if the user is experiencing high stress levels, a suggestion such as "We recommend taking some time to take deep breaths" might be sent.

[0161] Step 9:

[0162] Users can access online communities within the system and interact with other users anonymously. The server securely manages these interactions and checks for inappropriate content.

[0163] Step 10:

[0164] The server recommends community groups that users should join and topics they might be interested in, based on their past sentiment data and interaction history.

[0165] (Example 2)

[0166] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0167] While the importance of mental health management is recognized in modern society, systems that efficiently provide individually tailored suggestions to users are not yet widespread. In particular, there is a lack of technology that integrates emotional and biometric information to provide accurate feedback tailored to the user's condition. Furthermore, there is insufficient provision of safe and anonymous spaces for users to interact with each other. Solving these challenges requires a more accurate and comprehensive approach.

[0168] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0169] In this invention, the server includes means for acquiring emotional information input by the user, means for analyzing the emotional information and generating a response based on the analysis results, and means for acquiring biometric information. This enables the provision of personalized feedback based on the user's emotions and biometric state.

[0170] A "user" refers to an individual who operates the system, inputs emotional information, and provides biometric data.

[0171] "Emotional information" refers to data that users input as text to express their own emotions and state of mind.

[0172] "Biometric information" refers to data that indicates the user's physical condition, such as heart rate and skin potential response.

[0173] A "generative AI model" refers to an artificial intelligence model used to analyze emotional information using natural language processing technology.

[0174] A "prompt sentence" refers to an input sentence used to instruct a generative AI model to analyze emotional information.

[0175] The embodiment of this invention is based on the construction of a system that provides personalized feedback by integrally utilizing the user's emotional information and biometric information and using a generative AI model.

[0176] First, the user inputs emotional information into a device in text format. This device has the functionality to retrieve emotional information via a specific application and send it to a server. Specific software examples include mobile applications and web applications.

[0177] The server analyzes emotional information using a generative AI model. It utilizes natural language processing techniques to identify underlying emotions from the input text. The emotion engine generates appropriate feedback while referencing a database. A sample prompt might be, "Analyze the user's emotions and generate a response based on that state."

[0178] Next, sensors installed in the device collect biometric information such as the user's heart rate and skin potential response. Specific hardware, such as heart rate sensors and skin potential response sensors, are used. This biometric information is transmitted to a server and analyzed in conjunction with emotional information.

[0179] For example, if a user inputs "I'm so relieved that my recent project is finished," the emotion engine will analyze this as a feeling of "relief." Based on this emotion, the server will provide feedback such as "Now is the time to get some good rest." Furthermore, if a decrease in heart rate is detected, it's possible to add positive feedback such as "You are in a relaxed state."

[0180] This system makes it possible to provide comprehensive and detailed suggestions for supporting users' mental health in a multifaceted way.

[0181] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0182] Step 1:

[0183] Users input their emotions in text format into the device. Specifically, users open an application on their smartphone or computer, enter text describing their emotions or state into the input field, and press the "Send" button. This input data is treated as emotional information. The device immediately processes the emotional information obtained from the input, converts it into a format suitable for the next processing, and prepares to send it to the server.

[0184] Step 2:

[0185] The device sends the sentiment information entered by the user to the server. For security and reliability, HTTPS is used as the communication protocol. This transmission process encrypts the sentiment information and delivers it to the server over the network. The device performs this process in the background, and displays a message to the user confirming successful transmission.

[0186] Step 3:

[0187] The server inputs the received emotional information into a generative AI model and performs emotion analysis using natural language processing technology. Specifically, the server tokenizes the input text data and forms the prompt "Analyze the user's emotions and generate a response based on that state." This prompt is input into the generative AI model, which outputs the analyzed emotions and the feedback based on them. The output data is prepared as feedback information in a format suitable for the user.

[0188] Step 4:

[0189] The server sends the generated feedback to the terminal for the user to receive. The feedback is formatted as JSON data and sent to the terminal over the network. After sending, the server logs the transmission status and incorporates a program to retry sending if necessary.

[0190] Step 5:

[0191] The device analyzes the feedback received from the server and displays it on the user's screen. The device receives data in JSON format and displays the feedback message in a UI component. It is possible to present the feedback in a way that is easy for the user to understand and to include buttons or links to encourage more specific actions.

[0192] Step 6:

[0193] The device collects the user's biometric information using its built-in sensors. It activates heart rate sensors and skin potential response sensors to periodically acquire data. The collected biometric information is processed at regular time intervals and formatted in preparation for the next analysis.

[0194] Step 7:

[0195] The server analyzes biometric information transmitted from the terminal and integrates it with emotional information to generate optimal feedback for the user. Based on the obtained biometric information, such as heart rate and skin potential responses, the emotional engine interprets the user's physical and psychological state and outputs new feedback. This data is updated as suggestions that take the user's physical condition into account.

[0196] (Application Example 2)

[0197] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0198] To comprehensively support users' mental health, it is necessary not only to generate appropriate feedback and suggestions based on analysis results using emotional and biometric data, but also to provide an environment where users can interact with each other safely and recommend opportunities for interaction and activities that are individually suited to them. Existing systems cannot comprehensively provide these functions, resulting in insufficient support for users.

[0199] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0200] In this invention, the server includes means for acquiring emotional data entered by the user, means for analyzing the emotional data and generating feedback based on the analysis results, means for acquiring biometric data and generating suggestions tailored to the user's state, and means for recommending online interaction opportunities suitable for the user. This makes it possible to provide a comprehensive, safe, and individually optimized communication environment to support the user's mental health.

[0201] "User-input emotional data" refers to data that users use to communicate their emotional state to the system in the form of text or other formats.

[0202] "Means for analyzing emotional data and generating feedback based on the analysis results" refers to a function or device that receives emotional data and processes that data to generate feedback information tailored to the user.

[0203] "Means for acquiring biometric data and generating suggestions tailored to the user's condition" refers to a function or device that acquires biometric signals such as heart rate and skin potential responses, and uses them to create optimal advice and action plans for the user.

[0204] "Means of providing a means for users to interact anonymously and securely" refers to functions or devices that create an environment in which users can interact safely with other users without disclosing their personal information.

[0205] "Means of recommending suitable online interaction opportunities to users" refers to a function or device that selects and presents suitable online communities and interaction events based on the user's interests and preferences.

[0206] The system realizing this invention uses the user's smartphone or wearable device as a terminal. The terminal acquires emotional data entered by the user and transmits it to a server. The server uses an emotion engine to analyze this emotional data through natural language processing technology and generates feedback based on the analysis results. For example, IBM Watson® NLP may be used for the analysis. The terminal is also equipped with a heart rate sensor and a skin potential response sensor, which are used to acquire this biometric data.

[0207] The server analyzes the acquired biometric data and generates suggestions tailored to the user's state. For example, if a sudden increase in heart rate is detected, the server will use that information to suggest "deep breathing" to the user. Furthermore, in online communities, the server provides anonymous and secure interaction between users and recommends online interaction opportunities that are suitable for the user.

[0208] For example, if a user operating the device inputs a feeling such as "I've been feeling tired lately," the server will generate feedback such as "I suggest a short walk to refresh yourself." The analysis results and suggestions are displayed on the device's screen and provided to the user in an intuitively understandable format.

[0209] Examples of prompts generated by the AI ​​model include "Please tell me how to improve my mood when I'm feeling down" or "Please suggest ways to relax when my heart rate is high." By inputting such questions, the system can generate appropriate feedback. This invention is a system that supports the user's mental and physical health from multiple perspectives.

[0210] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0211] Step 1:

[0212] The user enters their emotional state in text format into the terminal. The emotional data entered by the user is sent to the server via the terminal.

[0213] Step 2:

[0214] The server analyzes received sentiment data using natural language processing techniques. It uses a sentiment engine to process input data, identify the user's emotions, and build the foundation for generating feedback. The input is user sentiment text data, and the output is foundational data for emotion identification and feedback.

[0215] Step 3:

[0216] The server generates appropriate feedback based on the analysis results. The generated feedback is presented to the user. For example, if a stress state is identified, feedback suggesting "relaxation recommendations" will be generated. The input is the analysis results from step 2, and the output is the feedback to the user.

[0217] Step 4:

[0218] The biosensors installed in the device acquire biometric data such as the user's heart rate and skin potential response. The acquired biometric data is transmitted to the server in real time.

[0219] Step 5:

[0220] The server analyzes biometric data and evaluates the user's physical condition. It works in conjunction with an emotion engine to generate suggestions based on the user's biometric data. For example, if the heart rate is high, it might generate specific advice such as "try taking deep breaths." The input is the acquired biometric data, and the output is suggestions based on the user's physical condition.

[0221] Step 6:

[0222] The server manages anonymous and secure user interaction within online communities. It recommends suitable online interaction opportunities to users and encourages participation in communities that match their interests. Input is the user's interests and activity history, and output is information on recommended interaction opportunities.

[0223] In this way, the system provides multifaceted support based on the user's emotions and biological state.

[0224] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0225] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0226] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0227] [Second Embodiment]

[0228] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0229] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0230] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0231] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0232] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0233] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0234] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0235] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0236] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0237] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0238] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0239] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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".

[0240] This invention is a system designed to support the mental health of users. The system acquires emotional data entered by the user through a terminal, and a server analyzes this data to provide feedback to the user. Furthermore, it can analyze biometric data acquired from the user themselves and provide appropriate suggestions based on their psychological state.

[0241] First, the user inputs their emotional state in text format into the device. This emotional data is then sent from the device to the server. The server uses natural language processing technology to analyze the emotional data. This analysis reveals the user's emotional patterns and mood tendencies, and feedback is generated based on the analysis results. For example, if the emotional data entered is "I'm very tired today," the server generates the feedback "I recommend you take some time to relax" and sends it to the device for the user to receive.

[0242] Next, utilizing the sensor functions built into the device, the device collects biometric data in real time. This data includes heart rate and skin potential responses, and is used as an indicator of the user's physical stress and relaxation level. The collected biometric data is sent back to the server and analyzed to understand the user's current state. Through this analysis, the server makes suggestions, such as recommending rest, as needed and notifies the user. In this way, by combining monitoring of physical data and analysis of emotional data, the system provides support tailored to the user's mental and physical state.

[0243] Furthermore, users can participate anonymously in online communities within the system. The server anonymizes posts and immediately checks for inappropriate content. This allows users to interact with others and receive support regarding their issues. The server can also recommend helpful community groups and threads based on the user's interests and emotional state.

[0244] The present invention aims to effectively and safely address the individual mental health issues of users, and provides a specific system configuration for doing so.

[0245] The following describes the processing flow.

[0246] Step 1:

[0247] The user inputs their emotional state as text into the device. Emotional data is entered in the form of "I'm tired today."

[0248] Step 2:

[0249] The terminal retrieves the input emotion data and prepares to send that data to the server.

[0250] Step 3:

[0251] The server receives emotion data sent from the terminal and runs an AI model for analysis. The AI ​​model uses natural language processing techniques to analyze the text and identify the user's emotional state.

[0252] Step 4:

[0253] The server generates appropriate feedback based on the results of the emotion analysis. For example, if fatigue is detected, feedback such as "We recommend you take a rest" will be generated.

[0254] Step 5:

[0255] The server sends the generated feedback to the terminal and notifies the user.

[0256] Step 6:

[0257] The device's sensors continuously collect biometric data such as heart rate and skin potential responses.

[0258] Step 7:

[0259] The device transmits the collected biometric data to the server.

[0260] Step 8:

[0261] The server analyzes biometric data to assess the user's stress level and relaxation level.

[0262] Step 9:

[0263] The server will suggest rest and relaxation as needed. For example, if your stress level is high, it might suggest, "We recommend taking a short break."

[0264] Step 10:

[0265] The server manages online communities that users can join and supports anonymous interaction. It also filters out inappropriate content.

[0266] Step 11:

[0267] The server recommends relevant community chats and groups based on the user's past interactions and interests.

[0268] (Example 1)

[0269] Next, we will describe Example 1. 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."

[0270] In modern society, there is a need to comprehensively support the mental and physical health of users. However, existing systems struggle to effectively analyze both emotional and biometric information and provide appropriate responses and recommendations based on that analysis. Furthermore, ensuring safe and anonymous communication among users is not adequately achieved. Solving these problems is the objective of this invention.

[0271] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0272] In this invention, the server includes means for acquiring emotional information input by the user, means for analyzing the emotional information and biometric information to generate indicators, and means for generating and providing responses based on the analysis results. This enables comprehensive support tailored to the mental and physical state of the user, as well as safe interaction among users.

[0273] A "user" is a person who uses the system to input emotional and biometric information and receive support.

[0274] "Emotional information" refers to text data that users input to express their own emotional state.

[0275] "Biometric information" refers to data that objectively indicates the user's physical condition, such as heart rate and electrocutaneous response.

[0276] A "server" is a device that analyzes acquired emotional and biometric information and generates appropriate responses and recommendations for the user.

[0277] "Natural language processing technology" refers to techniques for analyzing text data and understanding its meaning and emotions.

[0278] "Response" refers to feedback to the user generated based on the analysis results of emotional and biometric information.

[0279] A "recommendation" refers to specific action plans or advice provided to users based on the analysis results.

[0280] "Interaction" refers to a form of communication where users can communicate with each other anonymously and safely.

[0281] The embodiment of this invention is configured as a system for supporting the mental and physical health of users. This system is primarily intended for inputting and analyzing emotional information, collecting and analyzing biometric information, and supporting interaction among users.

[0282] The user first inputs their emotional state as text data and sends it to the terminal. Smartphones, personal computers, etc. are used as the terminal. The input emotional information is sent to the server, where analysis is performed. The server utilizes natural language processing technology and uses Python's NLTK and spaCy libraries to analyze the text data. Based on this analysis, the server understands the user's emotional tendency and generates an appropriate response. For example, for an input like "I'm very tired today", a response like "It is recommended to set aside some time to relax" is generated.

[0283] The sensors incorporated in the terminal collect biometric information in real time. Specific data includes heart rate, electrodermal response, etc. The collected biometric information is sent to the server and analyzed using Python's Pandas and NumPy. The server uses this data to grasp the user's current physical state and generates advice to encourage rest if necessary.

[0284] The server also provides an environment where users can communicate anonymously and securely within the system. Posts between users are immediately checked for inappropriate content using natural language processing. Furthermore, the server recommends appropriate communities and topics considering the users' emotional states and interests.

[0285] As an example of the prompt sentence in this invention, a query like "When my heart rate is rising, please tell me how I should give relaxation advice" can be considered. Thereby, it is possible for the system to provide specific support tailored to the individual state of the user through the generative AI model.

[0286] The flow of the specific process in Example 1 will be described using FIG. 11.

[0287] Step 1:

[0288] The user enters their emotional state into the device in text format. This input might be a sentence like, "I'm very tired today." This text is recognized as emotional information.

[0289] Step 2:

[0290] The terminal sends emotion information entered by the user to the server. This input data is securely transferred to the server using HTTPS as the communication protocol. The output is the transfer of text data to the server.

[0291] Step 3:

[0292] The server analyzes the received sentiment information using natural language processing techniques. This analysis process utilizes Python's NLTK and spaCy libraries; text data is tokenized, and sentiment scores are calculated. The analysis results output the sentiment tendency of the text.

[0293] Step 4:

[0294] The server generates an appropriate response based on the analysis results. For example, it might generate feedback such as, "We recommend you take some time to relax." This output is a terminal message intended for the user.

[0295] Step 5:

[0296] The terminal displays feedback sent from the server to the user. This allows the user to receive specific advice on how to take appropriate action. The output is a display of feedback information to the user.

[0297] Step 6:

[0298] Sensors embedded in the device collect biometric data in real time. This data includes heart rate and electrocutaneous responses. The output is the transfer of this biometric data from the device to a server.

[0299] Step 7:

[0300] The server analyzes the received biological data. In the analysis, Python's Pandas and NumPy libraries are used to extract trends and outliers from the data. Through this analysis, the user's physical stress state is output.

[0301] Step 8:

[0302] Based on the analysis results of the biological data, the server generates advice to prompt the user to rest if necessary. What is output is a specific action plan according to the user's state.

[0303] Step 9:

[0304] The user participates anonymously in the online community within the system. Here, information is exchanged with other users in text form. The input is the user's post, which becomes the basic information for communication.

[0305] <​​​​​​​​​​​​​​​​​​​​Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0311] In modern society, there is a need for effective systems to support the mental and physical health of the elderly. In particular, for the elderly to live their daily lives with peace of mind, it is crucial to understand their emotional state and biometric information in real time and provide appropriate feedback. However, conventional systems fail to adequately address the characteristics and needs of the elderly, making it difficult to provide effective support.

[0312] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0313] In this invention, the server includes means for analyzing emotional information input by the user and generating a response based on the analysis results, means for analyzing biometric information and generating suggestions tailored to the user's condition, and means for suggesting daily life support and relaxation methods based on the user's health condition. This comprehensively supports the mental and physical health of the elderly, enabling them to live their daily lives with peace of mind.

[0314] "User-inputted emotional information" refers to data that users use to record and input their own emotional state.

[0315] "Responses based on analysis results" refer to feedback provided to the user after analyzing emotional information obtained from the user.

[0316] "Means of providing information to users" refers to methods for informing users of the analyzed information and suggestions, and enabling them to view or utilize it.

[0317] "Means for acquiring biometric information" refers to methods for acquiring data that indicates the user's physical condition, such as heart rate and skin potential response.

[0318] "Suggestions tailored to the user's condition" refers to advice and recommendations for actions that help the user achieve a better state of being, based on the results of the user's biometric and emotional information.

[0319] "Means of anonymous and secure communication between users" refers to methods that allow users to exchange information and communicate with each other with peace of mind while protecting each other's privacy.

[0320] "Means of proposing support for daily life and relaxation methods" refers to methods that propose ways to contribute to stress reduction and relaxation in order to make the user's daily life more comfortable.

[0321] The system that realizes this invention includes three main components: a user, a terminal, and a server.

[0322] Users first input their emotional information using a device. This device is a portable electronic device such as a smartphone or tablet, and it can transmit this information to a server. The device provides a simple interface to assist with emotional information input. Furthermore, the device incorporates sensors that allow it to acquire biometric information such as heart rate and skin potential responses.

[0323] The server uses natural language processing techniques to analyze emotional information sent by the user. The program utilizes programming languages ​​such as Python and their libraries for this purpose. The responses generated from the emotional information analysis are provided to the user via the terminal as feedback. In addition, the server also analyzes biometric information and, based on the results, suggests appropriate daily life support and relaxation methods to the user.

[0324] For example, if a user enters "I'm very tired today," the server analyzes this emotional information and provides advice to encourage relaxation. The server also evaluates the user's stress level based on collected heart rate data and generates feedback such as "take a break."

[0325] Furthermore, the system utilizes generative AI models to provide an anonymous and secure online community in which users can participate. In this online community, users can interact with other users and share their experiences while protecting their privacy.

[0326] An example of a prompt message is: "Propose a mental health support app for seniors. This app will analyze emotional input and biometric data to provide feedback tailored to the user's health status. Please also describe specific use cases and recommended interface designs and features."

[0327] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0328] Step 1:

[0329] Users input their emotional information using a device. This input is in text format, and the device receives this information as data and sends it to the server.

[0330] Step 2:

[0331] The server analyzes the received emotional information using natural language processing techniques. The input is the user's emotional information, and the output is the analysis result based on emotional patterns. Through this analysis process, the server determines the user's emotional state.

[0332] Step 3:

[0333] The server generates a response based on the analysis results. In this step, it determines appropriate feedback from the sentiment analysis results and sends it directly to the terminal as output. For example, it might generate a suggestion such as "Take some time to relax."

[0334] Step 4:

[0335] Sensors on the device acquire biometric information. This includes heart rate and skin potential responses, and this data is collected in real time. The device compiles the biometric information and sends it back to the server.

[0336] Step 5:

[0337] The server performs data analysis based on biometric information. In this step, the input is biometric information, and the output is an evaluation result indicating the user's physical condition. Based on this, the server generates recommended actions for the user.

[0338] Step 6:

[0339] The device sends notifications to the user's device that provide suggestions based on their current state, such as "Take adequate rest." The device then displays these notifications to the user and provides an interface for them to take action on the specific suggestions.

[0340] Step 7:

[0341] The server utilizes a generative AI model to recommend online communities that the user can join. The input includes the user's interests and emotional state, and the output is a list of appropriate community groups. The server sends this list to the user's device, providing a safe and secure environment for interaction.

[0342] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0343] This invention is a system designed to support users' mental health management. By incorporating an emotion engine, it can more accurately recognize the user's emotions and provide feedback and suggestions. This system utilizes emotional data and biometric data to provide personalized advice to the user.

[0344] First, the user inputs their emotions as text into the device. This emotion data is sent from the device to the server. The server then utilizes an emotion engine and natural language processing techniques to analyze the text data. The emotion engine identifies emotions from the input text, detects specific emotional states, and then generates feedback corresponding to the identified emotions.

[0345] For example, if a user enters "I'm busy and tired from work," the emotion engine identifies this as a "stressed state." Based on the identified emotional state, the server generates feedback such as "We recommend you make time to relax" and provides it to the user through the device.

[0346] Next, sensors installed in the device collect biometric data such as the user's heart rate and skin potential response. Using this biometric data, the server analyzes the user's physical state and, in conjunction with the emotion engine, enables further suggestions tailored to the user's condition. For example, if a sudden increase in heart rate is detected, it can provide specific countermeasures such as, "We recommend you try taking some deep breaths."

[0347] Furthermore, users can interact anonymously within the online communities on this system. The servers manage these interactions to ensure their security and utilize an emotion engine to naturally recommend topics and groups that users might be interested in or should join.

[0348] Thus, this invention places an emotion engine at its core and embodies comprehensive support for users' mental health by performing multifaceted analysis that combines emotional data and biometric data. This results in a system that provides practical and effective responses tailored to the individual needs of users.

[0349] The following describes the processing flow.

[0350] Step 1:

[0351] The user enters text into the device that expresses their emotional state. The emotional data is entered in a format such as, for example, "I was very irritated today."

[0352] Step 2:

[0353] The terminal prepares to send the entered emotion data to the server. The data is formatted appropriately during this process.

[0354] Step 3:

[0355] The server passes the received emotion data to the emotion engine, which then begins analysis. The emotion engine uses natural language processing technology to identify the user's specific emotions from the text.

[0356] Step 4:

[0357] The server generates feedback based on the emotions identified by the emotion engine. For example, if "irritation" is detected, it will create feedback that includes advice on stress management.

[0358] Step 5:

[0359] The server sends the generated feedback to the terminal. The information is processed quickly so that users can see the feedback in a timely manner.

[0360] Step 6:

[0361] Sensors built into the device continuously collect biometric data such as heart rate and skin potential response. The acquired biometric data is then transmitted directly to the server.

[0362] Step 7:

[0363] The server analyzes the collected biometric data to assess the user's physical and emotional state. Based on this assessment, it integrates physical responses and emotional data to generate further action suggestions.

[0364] Step 8:

[0365] The server creates and sends suggestions to the user's device based on their real-time state. For example, if the user is experiencing high stress levels, a suggestion such as "We recommend taking some time to take deep breaths" might be sent.

[0366] Step 9:

[0367] Users can access online communities within the system and interact with other users anonymously. The server securely manages these interactions and checks for inappropriate content.

[0368] Step 10:

[0369] The server recommends community groups that users should join and topics they might be interested in, based on their past sentiment data and interaction history.

[0370] (Example 2)

[0371] Next, we will describe Example 2. 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".

[0372] While the importance of mental health management is recognized in modern society, systems that efficiently provide individually tailored suggestions to users are not yet widespread. In particular, there is a lack of technology that integrates emotional and biometric information to provide accurate feedback tailored to the user's condition. Furthermore, there is insufficient provision of safe and anonymous spaces for users to interact with each other. Solving these challenges requires a more accurate and comprehensive approach.

[0373] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0374] In this invention, the server includes means for acquiring emotional information input by the user, means for analyzing the emotional information and generating a response based on the analysis results, and means for acquiring biometric information. This enables the provision of personalized feedback based on the user's emotions and biometric state.

[0375] A "user" refers to an individual who operates the system, inputs emotional information, and provides biometric data.

[0376] "Emotional information" refers to data that users input as text to express their own emotions and state of mind.

[0377] "Biometric information" refers to data that indicates the user's physical condition, such as heart rate and skin potential response.

[0378] A "generative AI model" refers to an artificial intelligence model used to analyze emotional information using natural language processing technology.

[0379] A "prompt sentence" refers to an input sentence used to instruct a generative AI model to analyze emotional information.

[0380] The embodiment of this invention is based on the construction of a system that provides personalized feedback by integrally utilizing the user's emotional information and biometric information and using a generative AI model.

[0381] First, the user inputs emotional information into a device in text format. This device has the functionality to retrieve emotional information via a specific application and send it to a server. Specific software examples include mobile applications and web applications.

[0382] The server analyzes emotional information using a generative AI model. It utilizes natural language processing techniques to identify underlying emotions from the input text. The emotion engine generates appropriate feedback while referencing a database. A sample prompt might be, "Analyze the user's emotions and generate a response based on that state."

[0383] Next, sensors installed in the device collect biometric information such as the user's heart rate and skin potential response. Specific hardware, such as heart rate sensors and skin potential response sensors, are used. This biometric information is transmitted to a server and analyzed in conjunction with emotional information.

[0384] For example, if a user inputs "I'm so relieved that my recent project is finished," the emotion engine will analyze this as a feeling of "relief." Based on this emotion, the server will provide feedback such as "Now is the time to get some good rest." Furthermore, if a decrease in heart rate is detected, it's possible to add positive feedback such as "You are in a relaxed state."

[0385] This system makes it possible to provide comprehensive and detailed suggestions for supporting users' mental health in a multifaceted way.

[0386] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0387] Step 1:

[0388] Users input their emotions in text format into the device. Specifically, users open an application on their smartphone or computer, enter text describing their emotions or state into the input field, and press the "Send" button. This input data is treated as emotional information. The device immediately processes the emotional information obtained from the input, converts it into a format suitable for the next processing, and prepares to send it to the server.

[0389] Step 2:

[0390] The device sends the sentiment information entered by the user to the server. For security and reliability, HTTPS is used as the communication protocol. This transmission process encrypts the sentiment information and delivers it to the server over the network. The device performs this process in the background, and displays a message to the user confirming successful transmission.

[0391] Step 3:

[0392] The server inputs the received emotional information into a generative AI model and performs emotion analysis using natural language processing technology. Specifically, the server tokenizes the input text data and forms the prompt "Analyze the user's emotions and generate a response based on that state." This prompt is input into the generative AI model, which outputs the analyzed emotions and the feedback based on them. The output data is prepared as feedback information in a format suitable for the user.

[0393] Step 4:

[0394] The server sends the generated feedback to the terminal for the user to receive. The feedback is formatted as JSON data and sent to the terminal over the network. After sending, the server logs the transmission status and incorporates a program to retry sending if necessary.

[0395] Step 5:

[0396] The device analyzes the feedback received from the server and displays it on the user's screen. The device receives data in JSON format and displays the feedback message in a UI component. It is possible to present the feedback in a way that is easy for the user to understand and to include buttons or links to encourage more specific actions.

[0397] Step 6:

[0398] The device collects the user's biometric information using its built-in sensors. It activates heart rate sensors and skin potential response sensors to periodically acquire data. The collected biometric information is processed at regular time intervals and formatted in preparation for the next analysis.

[0399] Step 7:

[0400] The server analyzes biometric information transmitted from the terminal and integrates it with emotional information to generate optimal feedback for the user. Based on the obtained biometric information, such as heart rate and skin potential responses, the emotional engine interprets the user's physical and psychological state and outputs new feedback. This data is updated as suggestions that take the user's physical condition into account.

[0401] (Application Example 2)

[0402] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0403] To comprehensively support users' mental health, it is necessary not only to generate appropriate feedback and suggestions based on analysis results using emotional and biometric data, but also to provide an environment where users can interact with each other safely and recommend opportunities for interaction and activities that are individually suited to them. Existing systems cannot comprehensively provide these functions, resulting in insufficient support for users.

[0404] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0405] In this invention, the server includes means for acquiring emotional data entered by the user, means for analyzing the emotional data and generating feedback based on the analysis results, means for acquiring biometric data and generating suggestions tailored to the user's state, and means for recommending online interaction opportunities suitable for the user. This makes it possible to provide a comprehensive, safe, and individually optimized communication environment to support the user's mental health.

[0406] "User-input emotional data" refers to data that users use to communicate their emotional state to the system in the form of text or other formats.

[0407] "Means for analyzing emotional data and generating feedback based on the analysis results" refers to a function or device that receives emotional data and processes that data to generate feedback information tailored to the user.

[0408] "Means for acquiring biometric data and generating suggestions tailored to the user's condition" refers to a function or device that acquires biometric signals such as heart rate and skin potential responses, and uses them to create optimal advice and action plans for the user.

[0409] "Means of providing a means for users to interact anonymously and securely" refers to functions or devices that create an environment in which users can interact safely with other users without disclosing their personal information.

[0410] "Means of recommending suitable online interaction opportunities to users" refers to a function or device that selects and presents suitable online communities and interaction events based on the user's interests and preferences.

[0411] The system that realizes this invention uses the user's smartphone or wearable device as a terminal. The terminal acquires emotional data entered by the user and transmits it to a server. The server uses an emotion engine to analyze this emotional data through natural language processing technology and generates feedback based on the analysis results. IBM Watson NLP, for example, may be used for the analysis. The terminal is also equipped with a heart rate sensor and a skin potential response sensor, which are used to acquire this biometric data.

[0412] The server analyzes the acquired biometric data and generates suggestions tailored to the user's state. For example, if a sudden increase in heart rate is detected, the server will use that information to suggest "deep breathing" to the user. Furthermore, in online communities, the server provides anonymous and secure interaction between users and recommends online interaction opportunities that are suitable for the user.

[0413] For example, if a user operating the device inputs a feeling such as "I've been feeling tired lately," the server will generate feedback such as "I suggest a short walk to refresh yourself." The analysis results and suggestions are displayed on the device's screen and provided to the user in an intuitively understandable format.

[0414] Examples of prompts generated by the AI ​​model include "Please tell me how to improve my mood when I'm feeling down" or "Please suggest ways to relax when my heart rate is high." By inputting such questions, the system can generate appropriate feedback. This invention is a system that supports the user's mental and physical health from multiple perspectives.

[0415] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0416] Step 1:

[0417] The user enters their emotional state in text format into the terminal. The emotional data entered by the user is sent to the server via the terminal.

[0418] Step 2:

[0419] The server analyzes received sentiment data using natural language processing techniques. It uses a sentiment engine to process input data, identify the user's emotions, and build the foundation for generating feedback. The input is user sentiment text data, and the output is foundational data for emotion identification and feedback.

[0420] Step 3:

[0421] The server generates appropriate feedback based on the analysis results. The generated feedback is presented to the user. For example, if a stress state is identified, feedback suggesting "relaxation recommendations" will be generated. The input is the analysis results from step 2, and the output is the feedback to the user.

[0422] Step 4:

[0423] The biosensors installed in the device acquire biometric data such as the user's heart rate and skin potential response. The acquired biometric data is transmitted to the server in real time.

[0424] Step 5:

[0425] The server analyzes biometric data and evaluates the user's physical condition. It works in conjunction with an emotion engine to generate suggestions based on the user's biometric data. For example, if the heart rate is high, it might generate specific advice such as "try taking deep breaths." The input is the acquired biometric data, and the output is suggestions based on the user's physical condition.

[0426] Step 6:

[0427] The server manages anonymous and secure user interaction within online communities. It recommends suitable online interaction opportunities to users and encourages participation in communities that match their interests. Input is the user's interests and activity history, and output is information on recommended interaction opportunities.

[0428] In this way, the system provides multifaceted support based on the user's emotions and biological state.

[0429] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0430] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0431] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0432] [Third Embodiment]

[0433] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0434] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0435] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0436] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0437] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0438] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0439] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0440] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0441] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0442] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0443] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0444] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0445] This invention is a system designed to support the mental health of users. The system acquires emotional data entered by the user through a terminal, and a server analyzes this data to provide feedback to the user. Furthermore, it can analyze biometric data acquired from the user themselves and provide appropriate suggestions based on their psychological state.

[0446] First, the user inputs their emotional state in text format into the device. This emotional data is then sent from the device to the server. The server uses natural language processing technology to analyze the emotional data. This analysis reveals the user's emotional patterns and mood tendencies, and feedback is generated based on the analysis results. For example, if the emotional data entered is "I'm very tired today," the server generates the feedback "I recommend you take some time to relax" and sends it to the device for the user to receive.

[0447] Next, utilizing the sensor functions built into the device, the device collects biometric data in real time. This data includes heart rate and skin potential responses, and is used as an indicator of the user's physical stress and relaxation level. The collected biometric data is sent back to the server and analyzed to understand the user's current state. Through this analysis, the server makes suggestions, such as recommending rest, as needed and notifies the user. In this way, by combining monitoring of physical data and analysis of emotional data, the system provides support tailored to the user's mental and physical state.

[0448] Furthermore, users can participate anonymously in online communities within the system. The server anonymizes posts and immediately checks for inappropriate content. This allows users to interact with others and receive support regarding their issues. The server can also recommend helpful community groups and threads based on the user's interests and emotional state.

[0449] The present invention aims to effectively and safely address the individual mental health issues of users, and provides a specific system configuration for doing so.

[0450] The following describes the processing flow.

[0451] Step 1:

[0452] The user inputs their emotional state as text into the device. Emotional data is entered in the form of "I'm tired today."

[0453] Step 2:

[0454] The terminal retrieves the input emotion data and prepares to send that data to the server.

[0455] Step 3:

[0456] The server receives emotion data sent from the terminal and runs an AI model for analysis. The AI ​​model uses natural language processing techniques to analyze the text and identify the user's emotional state.

[0457] Step 4:

[0458] The server generates appropriate feedback based on the results of the emotion analysis. For example, if fatigue is detected, feedback such as "We recommend you take a rest" will be generated.

[0459] Step 5:

[0460] The server sends the generated feedback to the terminal and notifies the user.

[0461] Step 6:

[0462] The device's sensors continuously collect biometric data such as heart rate and skin potential responses.

[0463] Step 7:

[0464] The device transmits the collected biometric data to the server.

[0465] Step 8:

[0466] The server analyzes biometric data to assess the user's stress level and relaxation level.

[0467] Step 9:

[0468] The server will suggest rest and relaxation as needed. For example, if your stress level is high, it might suggest, "We recommend taking a short break."

[0469] Step 10:

[0470] The server manages online communities that users can join and supports anonymous interaction. It also filters out inappropriate content.

[0471] Step 11:

[0472] The server recommends relevant community chats and groups based on the user's past interactions and interests.

[0473] (Example 1)

[0474] Next, we will describe Example 1. 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."

[0475] In modern society, there is a need to comprehensively support the mental and physical health of users. However, existing systems struggle to effectively analyze both emotional and biometric information and provide appropriate responses and recommendations based on that analysis. Furthermore, ensuring safe and anonymous communication among users is not adequately achieved. Solving these problems is the objective of this invention.

[0476] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0477] In this invention, the server includes means for acquiring emotional information input by the user, means for analyzing the emotional information and biometric information to generate indicators, and means for generating and providing responses based on the analysis results. This enables comprehensive support tailored to the mental and physical state of the user, as well as safe interaction among users.

[0478] A "user" is a person who uses the system to input emotional and biometric information and receive support.

[0479] "Emotional information" refers to text data that users input to express their own emotional state.

[0480] "Biometric information" refers to data that objectively indicates the user's physical condition, such as heart rate and electrocutaneous response.

[0481] A "server" is a device that analyzes acquired emotional and biometric information and generates appropriate responses and recommendations for the user.

[0482] "Natural language processing technology" refers to techniques for analyzing text data and understanding its meaning and emotions.

[0483] "Response" refers to feedback to the user generated based on the analysis results of emotional and biometric information.

[0484] A "recommendation" refers to specific action plans or advice provided to users based on the analysis results.

[0485] "Interaction" refers to a form of communication where users can communicate with each other anonymously and safely.

[0486] The embodiment of this invention is configured as a system for supporting the mental and physical health of users. This system is primarily intended for inputting and analyzing emotional information, collecting and analyzing biometric information, and supporting interaction among users.

[0487] The user first inputs their emotional state as text data and sends it to a device. This device can be a smartphone or a personal computer. The input emotional information is sent to a server where it is analyzed. The server utilizes natural language processing technology, employing Python's NLTK and spaCy libraries to analyze the text data. Based on this analysis, the server understands the user's emotional tendencies and generates an appropriate response. For example, in response to input such as "I'm very tired today," the server might generate a response like, "I recommend you take some time to relax."

[0488] Sensors embedded in the device collect biometric information in real time. Specific data includes heart rate and electrocutaneous response. The collected biometric information is sent to a server where it is analyzed using Python's Pandas and NumPy libraries. The server uses this data to understand the user's current physical condition and, if necessary, generates recommendations to encourage rest.

[0489] The server also provides an environment where users can interact anonymously and securely within the system. User posts are instantly checked for inappropriate content using natural language processing. Furthermore, the server considers users' emotional states and interests to recommend appropriate communities and topics.

[0490] An example of a prompt in this invention is a question such as, "When my heart rate is elevated, what kind of relaxation advice should I receive?" This allows the system to provide specific support tailored to the user's individual condition through a generated AI model.

[0491] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0492] Step 1:

[0493] The user enters their emotional state into the device in text format. This input might be a sentence like, "I'm very tired today." This text is recognized as emotional information.

[0494] Step 2:

[0495] The terminal sends emotion information entered by the user to the server. This input data is securely transferred to the server using HTTPS as the communication protocol. The output is the transfer of text data to the server.

[0496] Step 3:

[0497] The server analyzes the received sentiment information using natural language processing techniques. This analysis process utilizes Python's NLTK and spaCy libraries; text data is tokenized, and sentiment scores are calculated. The analysis results output the sentiment tendency of the text.

[0498] Step 4:

[0499] The server generates an appropriate response based on the analysis results. For example, it might generate feedback such as, "We recommend you take some time to relax." This output is a terminal message intended for the user.

[0500] Step 5:

[0501] The terminal displays feedback sent from the server to the user. This allows the user to receive specific advice on how to take appropriate action. The output is a display of feedback information to the user.

[0502] Step 6:

[0503] Sensors embedded in the device collect biometric data in real time. This data includes heart rate and electrocutaneous responses. The output is the transfer of this biometric data from the device to a server.

[0504] Step 7:

[0505] The server analyzes the received biometric data. The analysis uses Python libraries such as Pandas and NumPy to extract trends and outliers from the data. This analysis then outputs the user's physical stress level.

[0506] Step 8:

[0507] Based on the analysis of biometric data, the server generates recommendations to encourage users to rest as needed. The output consists of specific action plans tailored to the user's condition.

[0508] Step 9:

[0509] Users participate anonymously in online communities within the system. Here, they exchange information with other users in text format. Input consists of user posts, which form the basis of the interaction.

[0510] Step 10:

[0511] The server monitors posts within the community and uses natural language processing to check for inappropriate content. The output consists of filtered posts to ensure safe communication.

[0512] Step 11:

[0513] The server recommends useful threads and groups based on the user's interests and emotional state. This allows the user to receive information and support that is relevant to them. The output is recommendation information for the user.

[0514] (Application Example 1)

[0515] Next, we will explain Application Example 1. In the following explanation, 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."

[0516] In modern society, there is a need for effective systems to support the mental and physical health of the elderly. In particular, for the elderly to live their daily lives with peace of mind, it is crucial to understand their emotional state and biometric information in real time and provide appropriate feedback. However, conventional systems fail to adequately address the characteristics and needs of the elderly, making it difficult to provide effective support.

[0517] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0518] In this invention, the server includes means for analyzing emotional information input by the user and generating a response based on the analysis results, means for analyzing biometric information and generating suggestions tailored to the user's condition, and means for suggesting daily life support and relaxation methods based on the user's health condition. This comprehensively supports the mental and physical health of the elderly, enabling them to live their daily lives with peace of mind.

[0519] "User-inputted emotional information" refers to data that users use to record and input their own emotional state.

[0520] "Responses based on analysis results" refer to feedback provided to the user after analyzing emotional information obtained from the user.

[0521] "Means of providing information to users" refers to methods for informing users of the analyzed information and suggestions, and enabling them to view or utilize it.

[0522] "Means for acquiring biometric information" refers to methods for acquiring data that indicates the user's physical condition, such as heart rate and skin potential response.

[0523] "Suggestions tailored to the user's condition" refers to advice and recommendations for actions that help the user achieve a better state of being, based on the results of the user's biometric and emotional information.

[0524] "Means of anonymous and secure communication between users" refers to methods that allow users to exchange information and communicate with each other with peace of mind while protecting each other's privacy.

[0525] "Means of proposing support for daily life and relaxation methods" refers to methods that propose ways to contribute to stress reduction and relaxation in order to make the user's daily life more comfortable.

[0526] The system that realizes this invention includes three main components: a user, a terminal, and a server.

[0527] Users first input their emotional information using a device. This device is a portable electronic device such as a smartphone or tablet, and it can transmit this information to a server. The device provides a simple interface to assist with emotional information input. Furthermore, the device incorporates sensors that allow it to acquire biometric information such as heart rate and skin potential responses.

[0528] The server uses natural language processing techniques to analyze emotional information sent by the user. The program utilizes programming languages ​​such as Python and their libraries for this purpose. The responses generated from the emotional information analysis are provided to the user via the terminal as feedback. In addition, the server also analyzes biometric information and, based on the results, suggests appropriate daily life support and relaxation methods to the user.

[0529] For example, if a user enters "I'm very tired today," the server analyzes this emotional information and provides advice to encourage relaxation. The server also evaluates the user's stress level based on collected heart rate data and generates feedback such as "take a break."

[0530] Furthermore, the system utilizes generative AI models to provide an anonymous and secure online community in which users can participate. In this online community, users can interact with other users and share their experiences while protecting their privacy.

[0531] An example of a prompt message is: "Propose a mental health support app for seniors. This app will analyze emotional input and biometric data to provide feedback tailored to the user's health status. Please also describe specific use cases and recommended interface designs and features."

[0532] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0533] Step 1:

[0534] Users input their emotional information using a device. This input is in text format, and the device receives this information as data and sends it to the server.

[0535] Step 2:

[0536] The server analyzes the received emotional information using natural language processing techniques. The input is the user's emotional information, and the output is the analysis result based on emotional patterns. Through this analysis process, the server determines the user's emotional state.

[0537] Step 3:

[0538] The server generates a response based on the analysis results. In this step, it determines appropriate feedback from the sentiment analysis results and sends it directly to the terminal as output. For example, it might generate a suggestion such as "Take some time to relax."

[0539] Step 4:

[0540] Sensors on the device acquire biometric information. This includes heart rate and skin potential responses, and this data is collected in real time. The device compiles the biometric information and sends it back to the server.

[0541] Step 5:

[0542] The server performs data analysis based on biometric information. In this step, the input is biometric information, and the output is an evaluation result indicating the user's physical condition. Based on this, the server generates recommended actions for the user.

[0543] Step 6:

[0544] The device sends notifications to the user's device that provide suggestions based on their current state, such as "Take adequate rest." The device then displays these notifications to the user and provides an interface for them to take action on the specific suggestions.

[0545] Step 7:

[0546] The server utilizes a generative AI model to recommend online communities that the user can join. The input includes the user's interests and emotional state, and the output is a list of appropriate community groups. The server sends this list to the user's device, providing a safe and secure environment for interaction.

[0547] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0548] This invention is a system designed to support users' mental health management. By incorporating an emotion engine, it can more accurately recognize the user's emotions and provide feedback and suggestions. This system utilizes emotional data and biometric data to provide personalized advice to the user.

[0549] First, the user inputs their emotions as text into the device. This emotion data is sent from the device to the server. The server then utilizes an emotion engine and natural language processing techniques to analyze the text data. The emotion engine identifies emotions from the input text, detects specific emotional states, and then generates feedback corresponding to the identified emotions.

[0550] For example, if a user enters "I'm busy and tired from work," the emotion engine identifies this as a "stressed state." Based on the identified emotional state, the server generates feedback such as "We recommend you make time to relax" and provides it to the user through the device.

[0551] Next, sensors installed in the device collect biometric data such as the user's heart rate and skin potential response. Using this biometric data, the server analyzes the user's physical state and, in conjunction with the emotion engine, enables further suggestions tailored to the user's condition. For example, if a sudden increase in heart rate is detected, it can provide specific countermeasures such as, "We recommend you try taking some deep breaths."

[0552] Furthermore, users can interact anonymously within the online communities on this system. The servers manage these interactions to ensure their security and utilize an emotion engine to naturally recommend topics and groups that users might be interested in or should join.

[0553] Thus, this invention places an emotion engine at its core and embodies comprehensive support for users' mental health by performing multifaceted analysis that combines emotional data and biometric data. This results in a system that provides practical and effective responses tailored to the individual needs of users.

[0554] The following describes the processing flow.

[0555] Step 1:

[0556] The user enters text into the device that expresses their emotional state. The emotional data is entered in a format such as, for example, "I was very irritated today."

[0557] Step 2:

[0558] The terminal prepares to send the entered emotion data to the server. The data is formatted appropriately during this process.

[0559] Step 3:

[0560] The server passes the received emotion data to the emotion engine, which then begins analysis. The emotion engine uses natural language processing technology to identify the user's specific emotions from the text.

[0561] Step 4:

[0562] The server generates feedback based on the emotions identified by the emotion engine. For example, if "irritation" is detected, it will create feedback that includes advice on stress management.

[0563] Step 5:

[0564] The server sends the generated feedback to the terminal. The information is processed quickly so that users can see the feedback in a timely manner.

[0565] Step 6:

[0566] Sensors built into the device continuously collect biometric data such as heart rate and skin potential response. The acquired biometric data is then transmitted directly to the server.

[0567] Step 7:

[0568] The server analyzes the collected biometric data to assess the user's physical and emotional state. Based on this assessment, it integrates physical responses and emotional data to generate further action suggestions.

[0569] Step 8:

[0570] The server creates and sends suggestions to the user's device based on their real-time state. For example, if the user is experiencing high stress levels, a suggestion such as "We recommend taking some time to take deep breaths" might be sent.

[0571] Step 9:

[0572] Users can access online communities within the system and interact with other users anonymously. The server securely manages these interactions and checks for inappropriate content.

[0573] Step 10:

[0574] The server recommends community groups that users should join and topics they might be interested in, based on their past sentiment data and interaction history.

[0575] (Example 2)

[0576] Next, we will describe Example 2. 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."

[0577] While the importance of mental health management is recognized in modern society, systems that efficiently provide individually tailored suggestions to users are not yet widespread. In particular, there is a lack of technology that integrates emotional and biometric information to provide accurate feedback tailored to the user's condition. Furthermore, there is insufficient provision of safe and anonymous spaces for users to interact with each other. Solving these challenges requires a more accurate and comprehensive approach.

[0578] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0579] In this invention, the server includes means for acquiring emotional information input by the user, means for analyzing the emotional information and generating a response based on the analysis results, and means for acquiring biometric information. This enables the provision of personalized feedback based on the user's emotions and biometric state.

[0580] A "user" refers to an individual who operates the system, inputs emotional information, and provides biometric data.

[0581] "Emotional information" refers to data that users input as text to express their own emotions and state of mind.

[0582] "Biometric information" refers to data that indicates the user's physical condition, such as heart rate and skin potential response.

[0583] A "generative AI model" refers to an artificial intelligence model used to analyze emotional information using natural language processing technology.

[0584] A "prompt sentence" refers to an input sentence used to instruct a generative AI model to analyze emotional information.

[0585] The embodiment of this invention is based on the construction of a system that provides personalized feedback by integrally utilizing the user's emotional information and biometric information and using a generative AI model.

[0586] First, the user inputs emotional information into a device in text format. This device has the functionality to retrieve emotional information via a specific application and send it to a server. Specific software examples include mobile applications and web applications.

[0587] The server analyzes emotional information using a generative AI model. It utilizes natural language processing techniques to identify underlying emotions from the input text. The emotion engine generates appropriate feedback while referencing a database. A sample prompt might be, "Analyze the user's emotions and generate a response based on that state."

[0588] Next, sensors installed in the device collect biometric information such as the user's heart rate and skin potential response. Specific hardware, such as heart rate sensors and skin potential response sensors, are used. This biometric information is transmitted to a server and analyzed in conjunction with emotional information.

[0589] For example, if a user inputs "I'm so relieved that my recent project is finished," the emotion engine will analyze this as a feeling of "relief." Based on this emotion, the server will provide feedback such as "Now is the time to get some good rest." Furthermore, if a decrease in heart rate is detected, it's possible to add positive feedback such as "You are in a relaxed state."

[0590] This system makes it possible to provide comprehensive and detailed suggestions for supporting users' mental health in a multifaceted way.

[0591] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0592] Step 1:

[0593] Users input their emotions in text format into the device. Specifically, users open an application on their smartphone or computer, enter text describing their emotions or state into the input field, and press the "Send" button. This input data is treated as emotional information. The device immediately processes the emotional information obtained from the input, converts it into a format suitable for the next processing, and prepares to send it to the server.

[0594] Step 2:

[0595] The device sends the sentiment information entered by the user to the server. For security and reliability, HTTPS is used as the communication protocol. This transmission process encrypts the sentiment information and delivers it to the server over the network. The device performs this process in the background, and displays a message to the user confirming successful transmission.

[0596] Step 3:

[0597] The server inputs the received emotional information into a generative AI model and performs emotion analysis using natural language processing technology. Specifically, the server tokenizes the input text data and forms the prompt "Analyze the user's emotions and generate a response based on that state." This prompt is input into the generative AI model, which outputs the analyzed emotions and the feedback based on them. The output data is prepared as feedback information in a format suitable for the user.

[0598] Step 4:

[0599] The server sends the generated feedback to the terminal for the user to receive. The feedback is formatted as JSON data and sent to the terminal over the network. After sending, the server logs the transmission status and incorporates a program to retry sending if necessary.

[0600] Step 5:

[0601] The device analyzes the feedback received from the server and displays it on the user's screen. The device receives data in JSON format and displays the feedback message in a UI component. It is possible to present the feedback in a way that is easy for the user to understand and to include buttons or links to encourage more specific actions.

[0602] Step 6:

[0603] The device collects the user's biometric information using its built-in sensors. It activates heart rate sensors and skin potential response sensors to periodically acquire data. The collected biometric information is processed at regular time intervals and formatted in preparation for the next analysis.

[0604] Step 7:

[0605] The server analyzes biometric information transmitted from the terminal and integrates it with emotional information to generate optimal feedback for the user. Based on the obtained biometric information, such as heart rate and skin potential responses, the emotional engine interprets the user's physical and psychological state and outputs new feedback. This data is updated as suggestions that take the user's physical condition into account.

[0606] (Application Example 2)

[0607] Next, we will explain application example 2. In the following explanation, 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."

[0608] To comprehensively support users' mental health, it is necessary not only to generate appropriate feedback and suggestions based on analysis results using emotional and biometric data, but also to provide an environment where users can interact with each other safely and recommend opportunities for interaction and activities that are individually suited to them. Existing systems cannot comprehensively provide these functions, resulting in insufficient support for users.

[0609] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0610] In this invention, the server includes means for acquiring emotional data entered by the user, means for analyzing the emotional data and generating feedback based on the analysis results, means for acquiring biometric data and generating suggestions tailored to the user's state, and means for recommending online interaction opportunities suitable for the user. This makes it possible to provide a comprehensive, safe, and individually optimized communication environment to support the user's mental health.

[0611] "User-input emotional data" refers to data that users use to communicate their emotional state to the system in the form of text or other formats.

[0612] "Means for analyzing emotional data and generating feedback based on the analysis results" refers to a function or device that receives emotional data and processes that data to generate feedback information tailored to the user.

[0613] "Means for acquiring biometric data and generating suggestions tailored to the user's condition" refers to a function or device that acquires biometric signals such as heart rate and skin potential responses, and uses them to create optimal advice and action plans for the user.

[0614] "Means of providing a means for users to interact anonymously and securely" refers to functions or devices that create an environment in which users can interact safely with other users without disclosing their personal information.

[0615] "Means of recommending suitable online interaction opportunities to users" refers to a function or device that selects and presents suitable online communities and interaction events based on the user's interests and preferences.

[0616] The system that realizes this invention uses the user's smartphone or wearable device as a terminal. The terminal acquires emotional data entered by the user and transmits it to a server. The server uses an emotion engine to analyze this emotional data through natural language processing technology and generates feedback based on the analysis results. IBM Watson NLP, for example, may be used for the analysis. The terminal is also equipped with a heart rate sensor and a skin potential response sensor, which are used to acquire this biometric data.

[0617] The server analyzes the acquired biometric data and generates suggestions tailored to the user's state. For example, if a sudden increase in heart rate is detected, the server will use that information to suggest "deep breathing" to the user. Furthermore, in online communities, the server provides anonymous and secure interaction between users and recommends online interaction opportunities that are suitable for the user.

[0618] For example, if a user operating the device inputs a feeling such as "I've been feeling tired lately," the server will generate feedback such as "I suggest a short walk to refresh yourself." The analysis results and suggestions are displayed on the device's screen and provided to the user in an intuitively understandable format.

[0619] Examples of prompts generated by the AI ​​model include "Please tell me how to improve my mood when I'm feeling down" or "Please suggest ways to relax when my heart rate is high." By inputting such questions, the system can generate appropriate feedback. This invention is a system that supports the user's mental and physical health from multiple perspectives.

[0620] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0621] Step 1:

[0622] The user enters their emotional state in text format into the terminal. The emotional data entered by the user is sent to the server via the terminal.

[0623] Step 2:

[0624] The server analyzes received sentiment data using natural language processing techniques. It uses a sentiment engine to process input data, identify the user's emotions, and build the foundation for generating feedback. The input is user sentiment text data, and the output is foundational data for emotion identification and feedback.

[0625] Step 3:

[0626] The server generates appropriate feedback based on the analysis results. The generated feedback is presented to the user. For example, if a stress state is identified, feedback suggesting "relaxation recommendations" will be generated. The input is the analysis results from step 2, and the output is the feedback to the user.

[0627] Step 4:

[0628] The biosensors installed in the device acquire biometric data such as the user's heart rate and skin potential response. The acquired biometric data is transmitted to the server in real time.

[0629] Step 5:

[0630] The server analyzes biometric data and evaluates the user's physical condition. It works in conjunction with an emotion engine to generate suggestions based on the user's biometric data. For example, if the heart rate is high, it might generate specific advice such as "try taking deep breaths." The input is the acquired biometric data, and the output is suggestions based on the user's physical condition.

[0631] Step 6:

[0632] The server manages anonymous and secure user interaction within online communities. It recommends suitable online interaction opportunities to users and encourages participation in communities that match their interests. Input is the user's interests and activity history, and output is information on recommended interaction opportunities.

[0633] In this way, the system provides multifaceted support based on the user's emotions and biological state.

[0634] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0635] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0636] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0637] [Fourth Embodiment]

[0638] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0639] As shown in Figure 7, the 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.

[0640] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0641] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0642] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0643] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0644] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0645] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0646] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0647] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0648] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0649] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0650] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0651] This invention is a system designed to support the mental health of users. The system acquires emotional data entered by the user through a terminal, and a server analyzes this data to provide feedback to the user. Furthermore, it can analyze biometric data acquired from the user themselves and provide appropriate suggestions based on their psychological state.

[0652] First, the user inputs their emotional state in text format into the device. This emotional data is then sent from the device to the server. The server uses natural language processing technology to analyze the emotional data. This analysis reveals the user's emotional patterns and mood tendencies, and feedback is generated based on the analysis results. For example, if the emotional data entered is "I'm very tired today," the server generates the feedback "I recommend you take some time to relax" and sends it to the device for the user to receive.

[0653] Next, utilizing the sensor functions built into the device, the device collects biometric data in real time. This data includes heart rate and skin potential responses, and is used as an indicator of the user's physical stress and relaxation level. The collected biometric data is sent back to the server and analyzed to understand the user's current state. Through this analysis, the server makes suggestions, such as recommending rest, as needed and notifies the user. In this way, by combining monitoring of physical data and analysis of emotional data, the system provides support tailored to the user's mental and physical state.

[0654] Furthermore, users can participate anonymously in online communities within the system. The server anonymizes posts and immediately checks for inappropriate content. This allows users to interact with others and receive support regarding their issues. The server can also recommend helpful community groups and threads based on the user's interests and emotional state.

[0655] The present invention aims to effectively and safely address the individual mental health issues of users, and provides a specific system configuration for doing so.

[0656] The following describes the processing flow.

[0657] Step 1:

[0658] The user inputs their emotional state as text into the device. Emotional data is entered in the form of "I'm tired today."

[0659] Step 2:

[0660] The terminal retrieves the input emotion data and prepares to send that data to the server.

[0661] Step 3:

[0662] The server receives emotion data sent from the terminal and runs an AI model for analysis. The AI ​​model uses natural language processing techniques to analyze the text and identify the user's emotional state.

[0663] Step 4:

[0664] The server generates appropriate feedback based on the results of the emotion analysis. For example, if fatigue is detected, feedback such as "We recommend you take a rest" will be generated.

[0665] Step 5:

[0666] The server sends the generated feedback to the terminal and notifies the user.

[0667] Step 6:

[0668] The device's sensors continuously collect biometric data such as heart rate and skin potential responses.

[0669] Step 7:

[0670] The device transmits the collected biometric data to the server.

[0671] Step 8:

[0672] The server analyzes biometric data to assess the user's stress level and relaxation level.

[0673] Step 9:

[0674] The server will suggest rest and relaxation as needed. For example, if your stress level is high, it might suggest, "We recommend taking a short break."

[0675] Step 10:

[0676] The server manages online communities that users can join and supports anonymous interaction. It also filters out inappropriate content.

[0677] Step 11:

[0678] The server recommends relevant community chats and groups based on the user's past interactions and interests.

[0679] (Example 1)

[0680] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0681] In modern society, there is a need to comprehensively support the mental and physical health of users. However, existing systems struggle to effectively analyze both emotional and biometric information and provide appropriate responses and recommendations based on that analysis. Furthermore, ensuring safe and anonymous communication among users is not adequately achieved. Solving these problems is the objective of this invention.

[0682] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0683] In this invention, the server includes means for acquiring emotional information input by the user, means for analyzing the emotional information and biometric information to generate indicators, and means for generating and providing responses based on the analysis results. This enables comprehensive support tailored to the mental and physical state of the user, as well as safe interaction among users.

[0684] A "user" is a person who uses the system to input emotional and biometric information and receive support.

[0685] "Emotional information" refers to text data that users input to express their own emotional state.

[0686] "Biometric information" refers to data that objectively indicates the user's physical condition, such as heart rate and electrocutaneous response.

[0687] A "server" is a device that analyzes acquired emotional and biometric information and generates appropriate responses and recommendations for the user.

[0688] "Natural language processing technology" refers to techniques for analyzing text data and understanding its meaning and emotions.

[0689] "Response" refers to feedback to the user generated based on the analysis results of emotional and biometric information.

[0690] A "recommendation" refers to specific action plans or advice provided to users based on the analysis results.

[0691] "Interaction" refers to a form of communication where users can communicate with each other anonymously and safely.

[0692] The embodiment of this invention is configured as a system for supporting the mental and physical health of users. This system is primarily intended for inputting and analyzing emotional information, collecting and analyzing biometric information, and supporting interaction among users.

[0693] The user first inputs their emotional state as text data and sends it to a device. This device can be a smartphone or a personal computer. The input emotional information is sent to a server where it is analyzed. The server utilizes natural language processing technology, employing Python's NLTK and spaCy libraries to analyze the text data. Based on this analysis, the server understands the user's emotional tendencies and generates an appropriate response. For example, in response to input such as "I'm very tired today," the server might generate a response like, "I recommend you take some time to relax."

[0694] Sensors embedded in the device collect biometric information in real time. Specific data includes heart rate and electrocutaneous response. The collected biometric information is sent to a server where it is analyzed using Python's Pandas and NumPy libraries. The server uses this data to understand the user's current physical condition and, if necessary, generates recommendations to encourage rest.

[0695] The server also provides an environment where users can interact anonymously and securely within the system. User posts are instantly checked for inappropriate content using natural language processing. Furthermore, the server considers users' emotional states and interests to recommend appropriate communities and topics.

[0696] An example of a prompt in this invention is a question such as, "When my heart rate is elevated, what kind of relaxation advice should I receive?" This allows the system to provide specific support tailored to the user's individual condition through a generated AI model.

[0697] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0698] Step 1:

[0699] The user enters their emotional state into the device in text format. This input might be a sentence like, "I'm very tired today." This text is recognized as emotional information.

[0700] Step 2:

[0701] The terminal sends emotion information entered by the user to the server. This input data is securely transferred to the server using HTTPS as the communication protocol. The output is the transfer of text data to the server.

[0702] Step 3:

[0703] The server analyzes the received sentiment information using natural language processing techniques. This analysis process utilizes Python's NLTK and spaCy libraries; text data is tokenized, and sentiment scores are calculated. The analysis results output the sentiment tendency of the text.

[0704] Step 4:

[0705] The server generates an appropriate response based on the analysis results. For example, it might generate feedback such as, "We recommend you take some time to relax." This output is a terminal message intended for the user.

[0706] Step 5:

[0707] The terminal displays feedback sent from the server to the user. This allows the user to receive specific advice on how to take appropriate action. The output is a display of feedback information to the user.

[0708] Step 6:

[0709] Sensors embedded in the device collect biometric data in real time. This data includes heart rate and electrocutaneous responses. The output is the transfer of this biometric data from the device to a server.

[0710] Step 7:

[0711] The server analyzes the received biometric data. The analysis uses Python libraries such as Pandas and NumPy to extract trends and outliers from the data. This analysis then outputs the user's physical stress level.

[0712] Step 8:

[0713] Based on the analysis of biometric data, the server generates recommendations to encourage users to rest as needed. The output consists of specific action plans tailored to the user's condition.

[0714] Step 9:

[0715] Users participate anonymously in online communities within the system. Here, they exchange information with other users in text format. Input consists of user posts, which form the basis of the interaction.

[0716] Step 10:

[0717] The server monitors posts within the community and uses natural language processing to check for inappropriate content. The output consists of filtered posts to ensure safe communication.

[0718] Step 11:

[0719] The server recommends useful threads and groups based on the user's interests and emotional state. This allows the user to receive information and support that is relevant to them. The output is recommendation information for the user.

[0720] (Application Example 1)

[0721] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0722] In modern society, there is a need for effective systems to support the mental and physical health of the elderly. In particular, for the elderly to live their daily lives with peace of mind, it is crucial to understand their emotional state and biometric information in real time and provide appropriate feedback. However, conventional systems fail to adequately address the characteristics and needs of the elderly, making it difficult to provide effective support.

[0723] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0724] In this invention, the server includes means for analyzing emotional information input by the user and generating a response based on the analysis results, means for analyzing biometric information and generating suggestions tailored to the user's condition, and means for suggesting daily life support and relaxation methods based on the user's health condition. This comprehensively supports the mental and physical health of the elderly, enabling them to live their daily lives with peace of mind.

[0725] "User-inputted emotional information" refers to data that users use to record and input their own emotional state.

[0726] "Responses based on analysis results" refer to feedback provided to the user after analyzing emotional information obtained from the user.

[0727] "Means of providing information to users" refers to methods for informing users of the analyzed information and suggestions, and enabling them to view or utilize it.

[0728] "Means for acquiring biometric information" refers to methods for acquiring data that indicates the user's physical condition, such as heart rate and skin potential response.

[0729] "Suggestions tailored to the user's condition" refers to advice and recommendations for actions that help the user achieve a better state of being, based on the results of the user's biometric and emotional information.

[0730] "Means of anonymous and secure communication between users" refers to methods that allow users to exchange information and communicate with each other with peace of mind while protecting each other's privacy.

[0731] "Means of proposing support for daily life and relaxation methods" refers to methods that propose ways to contribute to stress reduction and relaxation in order to make the user's daily life more comfortable.

[0732] The system that realizes this invention includes three main components: a user, a terminal, and a server.

[0733] Users first input their emotional information using a device. This device is a portable electronic device such as a smartphone or tablet, and it can transmit this information to a server. The device provides a simple interface to assist with emotional information input. Furthermore, the device incorporates sensors that allow it to acquire biometric information such as heart rate and skin potential responses.

[0734] The server uses natural language processing techniques to analyze emotional information sent by the user. The program utilizes programming languages ​​such as Python and their libraries for this purpose. The responses generated from the emotional information analysis are provided to the user via the terminal as feedback. In addition, the server also analyzes biometric information and, based on the results, suggests appropriate daily life support and relaxation methods to the user.

[0735] For example, if a user enters "I'm very tired today," the server analyzes this emotional information and provides advice to encourage relaxation. The server also evaluates the user's stress level based on collected heart rate data and generates feedback such as "take a break."

[0736] Furthermore, the system utilizes generative AI models to provide an anonymous and secure online community in which users can participate. In this online community, users can interact with other users and share their experiences while protecting their privacy.

[0737] An example of a prompt message is: "Propose a mental health support app for seniors. This app will analyze emotional input and biometric data to provide feedback tailored to the user's health status. Please also describe specific use cases and recommended interface designs and features."

[0738] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0739] Step 1:

[0740] Users input their emotional information using a device. This input is in text format, and the device receives this information as data and sends it to the server.

[0741] Step 2:

[0742] The server analyzes the received emotional information using natural language processing techniques. The input is the user's emotional information, and the output is the analysis result based on emotional patterns. Through this analysis process, the server determines the user's emotional state.

[0743] Step 3:

[0744] The server generates a response based on the analysis results. In this step, it determines appropriate feedback from the sentiment analysis results and sends it directly to the terminal as output. For example, it might generate a suggestion such as "Take some time to relax."

[0745] Step 4:

[0746] Sensors on the device acquire biometric information. This includes heart rate and skin potential responses, and this data is collected in real time. The device compiles the biometric information and sends it back to the server.

[0747] Step 5:

[0748] The server performs data analysis based on biometric information. In this step, the input is biometric information, and the output is an evaluation result indicating the user's physical condition. Based on this, the server generates recommended actions for the user.

[0749] Step 6:

[0750] The device sends notifications to the user's device that provide suggestions based on their current state, such as "Take adequate rest." The device then displays these notifications to the user and provides an interface for them to take action on the specific suggestions.

[0751] Step 7:

[0752] The server utilizes a generative AI model to recommend online communities that the user can join. The input includes the user's interests and emotional state, and the output is a list of appropriate community groups. The server sends this list to the user's device, providing a safe and secure environment for interaction.

[0753] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0754] This invention is a system designed to support users' mental health management. By incorporating an emotion engine, it can more accurately recognize the user's emotions and provide feedback and suggestions. This system utilizes emotional data and biometric data to provide personalized advice to the user.

[0755] First, the user inputs their emotions as text into the device. This emotion data is sent from the device to the server. The server then utilizes an emotion engine and natural language processing techniques to analyze the text data. The emotion engine identifies emotions from the input text, detects specific emotional states, and then generates feedback corresponding to the identified emotions.

[0756] For example, if a user enters "I'm busy and tired from work," the emotion engine identifies this as a "stressed state." Based on the identified emotional state, the server generates feedback such as "We recommend you make time to relax" and provides it to the user through the device.

[0757] Next, sensors installed in the device collect biometric data such as the user's heart rate and skin potential response. Using this biometric data, the server analyzes the user's physical state and, in conjunction with the emotion engine, enables further suggestions tailored to the user's condition. For example, if a sudden increase in heart rate is detected, it can provide specific countermeasures such as, "We recommend you try taking some deep breaths."

[0758] Furthermore, users can interact anonymously within the online communities on this system. The servers manage these interactions to ensure their security and utilize an emotion engine to naturally recommend topics and groups that users might be interested in or should join.

[0759] Thus, this invention places an emotion engine at its core and embodies comprehensive support for users' mental health by performing multifaceted analysis that combines emotional data and biometric data. This results in a system that provides practical and effective responses tailored to the individual needs of users.

[0760] The following describes the processing flow.

[0761] Step 1:

[0762] The user enters text into the device that expresses their emotional state. The emotional data is entered in a format such as, for example, "I was very irritated today."

[0763] Step 2:

[0764] The terminal prepares to send the entered emotion data to the server. The data is formatted appropriately during this process.

[0765] Step 3:

[0766] The server passes the received emotion data to the emotion engine, which then begins analysis. The emotion engine uses natural language processing technology to identify the user's specific emotions from the text.

[0767] Step 4:

[0768] The server generates feedback based on the emotions identified by the emotion engine. For example, if "irritation" is detected, it will create feedback that includes advice on stress management.

[0769] Step 5:

[0770] The server sends the generated feedback to the terminal. The information is processed quickly so that users can see the feedback in a timely manner.

[0771] Step 6:

[0772] Sensors built into the device continuously collect biometric data such as heart rate and skin potential response. The acquired biometric data is then transmitted directly to the server.

[0773] Step 7:

[0774] The server analyzes the collected biometric data to assess the user's physical and emotional state. Based on this assessment, it integrates physical responses and emotional data to generate further action suggestions.

[0775] Step 8:

[0776] The server creates and sends suggestions to the user's device based on their real-time state. For example, if the user is experiencing high stress levels, a suggestion such as "We recommend taking some time to take deep breaths" might be sent.

[0777] Step 9:

[0778] Users can access online communities within the system and interact with other users anonymously. The server securely manages these interactions and checks for inappropriate content.

[0779] Step 10:

[0780] The server recommends community groups that users should join and topics they might be interested in, based on their past sentiment data and interaction history.

[0781] (Example 2)

[0782] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0783] While the importance of mental health management is recognized in modern society, systems that efficiently provide individually tailored suggestions to users are not yet widespread. In particular, there is a lack of technology that integrates emotional and biometric information to provide accurate feedback tailored to the user's condition. Furthermore, there is insufficient provision of safe and anonymous spaces for users to interact with each other. Solving these challenges requires a more accurate and comprehensive approach.

[0784] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0785] In this invention, the server includes means for acquiring emotional information input by the user, means for analyzing the emotional information and generating a response based on the analysis results, and means for acquiring biometric information. This enables the provision of personalized feedback based on the user's emotions and biometric state.

[0786] A "user" refers to an individual who operates the system, inputs emotional information, and provides biometric data.

[0787] "Emotional information" refers to data that users input as text to express their own emotions and state of mind.

[0788] "Biometric information" refers to data that indicates the user's physical condition, such as heart rate and skin potential response.

[0789] A "generative AI model" refers to an artificial intelligence model used to analyze emotional information using natural language processing technology.

[0790] A "prompt sentence" refers to an input sentence used to instruct a generative AI model to analyze emotional information.

[0791] The embodiment of this invention is based on the construction of a system that provides personalized feedback by integrally utilizing the user's emotional information and biometric information and using a generative AI model.

[0792] First, the user inputs emotional information into a device in text format. This device has the functionality to retrieve emotional information via a specific application and send it to a server. Specific software examples include mobile applications and web applications.

[0793] The server analyzes emotional information using a generative AI model. It utilizes natural language processing techniques to identify underlying emotions from the input text. The emotion engine generates appropriate feedback while referencing a database. A sample prompt might be, "Analyze the user's emotions and generate a response based on that state."

[0794] Next, sensors installed in the device collect biometric information such as the user's heart rate and skin potential response. Specific hardware, such as heart rate sensors and skin potential response sensors, are used. This biometric information is transmitted to a server and analyzed in conjunction with emotional information.

[0795] For example, if a user inputs "I'm so relieved that my recent project is finished," the emotion engine will analyze this as a feeling of "relief." Based on this emotion, the server will provide feedback such as "Now is the time to get some good rest." Furthermore, if a decrease in heart rate is detected, it's possible to add positive feedback such as "You are in a relaxed state."

[0796] This system makes it possible to provide comprehensive and detailed suggestions for supporting users' mental health in a multifaceted way.

[0797] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0798] Step 1:

[0799] Users input their emotions in text format into the device. Specifically, users open an application on their smartphone or computer, enter text describing their emotions or state into the input field, and press the "Send" button. This input data is treated as emotional information. The device immediately processes the emotional information obtained from the input, converts it into a format suitable for the next processing, and prepares to send it to the server.

[0800] Step 2:

[0801] The device sends the sentiment information entered by the user to the server. For security and reliability, HTTPS is used as the communication protocol. This transmission process encrypts the sentiment information and delivers it to the server over the network. The device performs this process in the background, and displays a message to the user confirming successful transmission.

[0802] Step 3:

[0803] The server inputs the received emotional information into a generative AI model and performs emotion analysis using natural language processing technology. Specifically, the server tokenizes the input text data and forms the prompt "Analyze the user's emotions and generate a response based on that state." This prompt is input into the generative AI model, which outputs the analyzed emotions and the feedback based on them. The output data is prepared as feedback information in a format suitable for the user.

[0804] Step 4:

[0805] The server sends the generated feedback to the terminal for the user to receive. The feedback is formatted as JSON data and sent to the terminal over the network. After sending, the server logs the transmission status and incorporates a program to retry sending if necessary.

[0806] Step 5:

[0807] The device analyzes the feedback received from the server and displays it on the user's screen. The device receives data in JSON format and displays the feedback message in a UI component. It is possible to present the feedback in a way that is easy for the user to understand and to include buttons or links to encourage more specific actions.

[0808] Step 6:

[0809] The device collects the user's biometric information using its built-in sensors. It activates heart rate sensors and skin potential response sensors to periodically acquire data. The collected biometric information is processed at regular time intervals and formatted in preparation for the next analysis.

[0810] Step 7:

[0811] The server analyzes biometric information transmitted from the terminal and integrates it with emotional information to generate optimal feedback for the user. Based on the obtained biometric information, such as heart rate and skin potential responses, the emotional engine interprets the user's physical and psychological state and outputs new feedback. This data is updated as suggestions that take the user's physical condition into account.

[0812] (Application Example 2)

[0813] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0814] To comprehensively support users' mental health, it is necessary not only to generate appropriate feedback and suggestions based on analysis results using emotional and biometric data, but also to provide an environment where users can interact with each other safely and recommend opportunities for interaction and activities that are individually suited to them. Existing systems cannot comprehensively provide these functions, resulting in insufficient support for users.

[0815] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0816] In this invention, the server includes means for acquiring emotional data entered by the user, means for analyzing the emotional data and generating feedback based on the analysis results, means for acquiring biometric data and generating suggestions tailored to the user's state, and means for recommending online interaction opportunities suitable for the user. This makes it possible to provide a comprehensive, safe, and individually optimized communication environment to support the user's mental health.

[0817] "User-input emotional data" refers to data that users use to communicate their emotional state to the system in the form of text or other formats.

[0818] "Means for analyzing emotional data and generating feedback based on the analysis results" refers to a function or device that receives emotional data and processes that data to generate feedback information tailored to the user.

[0819] "Means for acquiring biometric data and generating suggestions tailored to the user's condition" refers to a function or device that acquires biometric signals such as heart rate and skin potential responses, and uses them to create optimal advice and action plans for the user.

[0820] "Means of providing a means for users to interact anonymously and securely" refers to functions or devices that create an environment in which users can interact safely with other users without disclosing their personal information.

[0821] "Means of recommending suitable online interaction opportunities to users" refers to a function or device that selects and presents suitable online communities and interaction events based on the user's interests and preferences.

[0822] The system that realizes this invention uses the user's smartphone or wearable device as a terminal. The terminal acquires emotional data entered by the user and transmits it to a server. The server uses an emotion engine to analyze this emotional data through natural language processing technology and generates feedback based on the analysis results. IBM Watson NLP, for example, may be used for the analysis. The terminal is also equipped with a heart rate sensor and a skin potential response sensor, which are used to acquire this biometric data.

[0823] The server analyzes the acquired biometric data and generates suggestions tailored to the user's state. For example, if a sudden increase in heart rate is detected, the server will use that information to suggest "deep breathing" to the user. Furthermore, in online communities, the server provides anonymous and secure interaction between users and recommends online interaction opportunities that are suitable for the user.

[0824] For example, if a user operating the device inputs a feeling such as "I've been feeling tired lately," the server will generate feedback such as "I suggest a short walk to refresh yourself." The analysis results and suggestions are displayed on the device's screen and provided to the user in an intuitively understandable format.

[0825] Examples of prompts generated by the AI ​​model include "Please tell me how to improve my mood when I'm feeling down" or "Please suggest ways to relax when my heart rate is high." By inputting such questions, the system can generate appropriate feedback. This invention is a system that supports the user's mental and physical health from multiple perspectives.

[0826] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0827] Step 1:

[0828] The user enters their emotional state in text format into the terminal. The emotional data entered by the user is sent to the server via the terminal.

[0829] Step 2:

[0830] The server analyzes received sentiment data using natural language processing techniques. It uses a sentiment engine to process input data, identify the user's emotions, and build the foundation for generating feedback. The input is user sentiment text data, and the output is foundational data for emotion identification and feedback.

[0831] Step 3:

[0832] The server generates appropriate feedback based on the analysis results. The generated feedback is presented to the user. For example, if a stress state is identified, feedback suggesting "relaxation recommendations" will be generated. The input is the analysis results from step 2, and the output is the feedback to the user.

[0833] Step 4:

[0834] The biosensors installed in the device acquire biometric data such as the user's heart rate and skin potential response. The acquired biometric data is transmitted to the server in real time.

[0835] Step 5:

[0836] The server analyzes biometric data and evaluates the user's physical condition. It works in conjunction with an emotion engine to generate suggestions based on the user's biometric data. For example, if the heart rate is high, it might generate specific advice such as "try taking deep breaths." The input is the acquired biometric data, and the output is suggestions based on the user's physical condition.

[0837] Step 6:

[0838] The server manages anonymous and secure user interaction within online communities. It recommends suitable online interaction opportunities to users and encourages participation in communities that match their interests. Input is the user's interests and activity history, and output is information on recommended interaction opportunities.

[0839] In this way, the system provides multifaceted support based on the user's emotions and biological state.

[0840] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0841] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0842] 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 this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0843] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0844] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0845] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0846] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0847] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0848] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0849] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0850] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0851] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0852] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0853] 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.

[0854] Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0855] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0856] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0857] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0858] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0859] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0860] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0861] The following is further disclosed regarding the embodiments described above.

[0862] (Claim 1)

[0863] A means of obtaining emotional data entered by the user,

[0864] A means for analyzing emotional data and generating feedback based on the analysis results,

[0865] Means of providing analysis results to users,

[0866] Means of acquiring biometric data,

[0867] A means of analyzing biometric data and generating suggestions tailored to the user's condition,

[0868] Means of providing proposals to users,

[0869] A means of providing a way for users to interact anonymously and securely,

[0870] A system that includes this.

[0871] (Claim 2)

[0872] The system according to claim 1, which uses natural language processing technology for analyzing emotional data.

[0873] (Claim 3)

[0874] The system according to claim 1, wherein the biometric data includes at least one of heart rate and skin potential response.

[0875] "Example 1"

[0876] (Claim 1)

[0877] A means of obtaining emotional information entered by the user,

[0878] A means for analyzing emotional information and generating a response based on the analysis results,

[0879] Means for providing analysis results to users,

[0880] Means for acquiring biometric information,

[0881] A means for analyzing biometric information and generating recommendations tailored to the user's condition,

[0882] Means of providing recommendations to users,

[0883] A means of providing a way for users to communicate anonymously and securely with each other,

[0884] A means for generating an index corresponding to the user's state using emotional information and biometric information,

[0885] A system that includes this.

[0886] (Claim 2)

[0887] The system according to claim 1, which uses natural language processing technology for analyzing emotional information.

[0888] (Claim 3)

[0889] The system according to claim 1, wherein the biological information includes at least one of heart rate and electrocutaneous response.

[0890] "Application Example 1"

[0891] (Claim 1)

[0892] A means of obtaining emotional information entered by the user,

[0893] A means for analyzing emotional information and generating a response based on the analysis results,

[0894] Means for providing analysis results to users,

[0895] Means for acquiring biometric information,

[0896] A means for analyzing biometric information and generating suggestions tailored to the user's condition,

[0897] Means of providing proposals to users,

[0898] A means of providing a way for users to communicate anonymously and securely with each other,

[0899] A means of suggesting daily life support and relaxation methods based on the user's health condition,

[0900] A system that includes this.

[0901] (Claim 2)

[0902] The system according to claim 1, which uses natural language processing technology for analyzing emotional information.

[0903] (Claim 3)

[0904] The system according to claim 1, wherein the biological information includes at least one of heart rate and skin potential response.

[0905] "Example 2 of combining an emotion engine"

[0906] (Claim 1)

[0907] A mechanism and means for acquiring emotional information entered by users.

[0908] A mechanism and means for analyzing emotional information and generating responses based on the analysis results.

[0909] The mechanism and means for providing analysis results to users,

[0910] Mechanisms and methods for acquiring biometric information,

[0911] A system and means for analyzing biometric information and generating suggestions tailored to the user's condition.

[0912] The mechanism and means for providing proposals to users,

[0913] A system and means to provide a mechanism for anonymous and secure communication among users.

[0914] A mechanism and means for generating prompt sentences for sentiment analysis using a generative AI model.

[0915] A mechanism and means for integrating and analyzing emotional and biological information to generate complex feedback.

[0916] A system that includes this.

[0917] (Claim 2)

[0918] The system according to claim 1, which uses natural language processing technology for analyzing emotional information.

[0919] (Claim 3)

[0920] The system according to claim 1, wherein the biological information includes at least one of heart rate and skin potential response.

[0921] "Application example 2 when combining with an emotional engine"

[0922] (Claim 1)

[0923] A means of obtaining emotional data entered by the user,

[0924] A means for analyzing emotional data and generating feedback based on the analysis results,

[0925] Means of providing analysis results to users,

[0926] Means of acquiring biometric data,

[0927] A means of analyzing biometric data and generating suggestions tailored to the user's condition,

[0928] Means of providing proposals to users,

[0929] A means of providing a way for users to interact anonymously and securely,

[0930] A means of recommending suitable online interaction opportunities to users,

[0931] ...

[0932] A system that includes this.

[0933] (Claim 2)

[0934] The system according to claim 1, which uses natural language processing technology for analyzing emotional data.

[0935] (Claim 3)

[0936] The system according to claim 1, wherein the biometric data includes at least one of heart rate and skin potential response. [Explanation of Symbols]

[0937] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of obtaining emotional information entered by the user, A means for analyzing emotional information and generating a response based on the analysis results, Means for providing analysis results to users, Means for acquiring biometric information, A means for analyzing biometric information and generating suggestions tailored to the user's condition, Means of providing proposals to users, A means of providing a way for users to communicate anonymously and securely with each other, A means of suggesting daily life support and relaxation methods based on the user's health condition, A system that includes this.

2. The system according to claim 1, which uses natural language processing technology for analyzing emotional information.

3. The system according to claim 1, wherein the biological information includes at least one of heart rate and skin potential response.

Images