system

Abstract

We provide the system. [Solution] Information recording means for collecting and managing personal data of elderly users, A dialogue generation means that generates dialogues based on input from elderly users using natural language processing technology, A health monitoring system that monitors the health information of elderly users and generates warnings when abnormalities occur, A means of communication to send notifications and warnings to elderly users, A time management system that tracks the behavior of elderly users and can issue health checks and reminders, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method 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 chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern society, the elderly often suffer from loneliness and may also have insufficient health management. Such a situation not only reduces the quality of life of the elderly but also increases the burden on family members to watch over them. Solving this problem is very important for increasing the sense of security of the elderly and reducing the mental burden on family members. Therefore, it is required to prevent the isolation of the elderly and provide an efficient health management and watch-over function.

Means for Solving the Problems

[0005] This invention provides a digital companion system for the elderly that utilizes personal data to offer personalized conversations, enabling seniors to enjoy conversations on topics familiar to them. Furthermore, it uses natural language processing technology to facilitate conversations with seniors and provides a means for managing their health information. It also detects abnormalities based on monitored health information and automatically notifies family members and medical institutions as needed. This system can alleviate feelings of loneliness among seniors while streamlining health management, thereby reducing the burden of monitoring on families.

[0006] A "database system" is an information management system for collecting and storing personal data of elderly people.

[0007] "Natural language processing technology" is a technology that enables computers to understand human language and perform dialogue and information processing.

[0008] A "dialogue engine" is a collection of programs and algorithms necessary to generate conversations with users and provide real-time responses.

[0009] A "health management system" is a system that continuously monitors and analyzes the health status of elderly people, and generates warnings and alerts as needed.

[0010] A "communication system" is a system that has the function of sending and receiving data and information between a user and external devices such as a server.

[0011] A "means for generating conversation topics" is a program that selects and provides topics appropriate for an elderly person's age group based on their profile information.

[0012] A "means of notifying in the event of an abnormal situation" refers to a system that has the function of automatically sending information to emergency contacts when an abnormality is detected. [Brief explanation of the drawing]

[0013] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This 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] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This 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] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This 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] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

[0014] An example of an embodiment of the system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0015] First, the terms used in the following description will be explained.

[0016] 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.

[0017] 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.

[0018] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0019] 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).

[0020] 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."

[0021] [First Embodiment]

[0022] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0023] 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.

[0024] 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).

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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.

[0029] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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".

[0034] This invention relates to a digital companion system for improving the quality of life for the elderly. The system consists of a server, a terminal, and a user, and provides individually personalized conversational and health management services.

[0035] 1. Details of the database method

[0036] The server has a database that securely stores and manages personal data provided by users. This database includes data on age, health information, and preferences, and the data can be updated at any time.

[0037] 2. Application of Natural Language Processing Techniques

[0038] The server uses natural language processing technology to analyze the voice or text input by the user. This generates conversations about nostalgic topics and daily events that are of interest to the elderly, and provides them to the device.

[0039] Specific example: If a user types, "I want to talk about movies I used to watch a lot," the server retrieves information on popular movies from its database that match the user's age group. The dialogue engine then generates anecdotes and trivia about those movies and sends them to the terminal.

[0040] 3. Explanation of health management methods

[0041] The device collects the user's daily health information and sends it to the server. The server uses this information to analyze the user's health status and provides health guidance and alerts as needed. Furthermore, it has a system that automatically notifies registered contacts in case of an emergency.

[0042] Specific example: If a user enters "I feel like my blood pressure has been high lately," the device sends this information to the server, which then generates appropriate advice based on that information and returns it to the device for display to the user.

[0043] 4. Functions of communication means

[0044] The communication method enables efficient data sharing between the terminal and the server. This communication is bidirectional and designed to ensure that user input and server notifications are received without delay.

[0045] As described above, this system provides an environment where elderly people can live their daily lives with peace of mind and without isolation. By combining a unique conversational experience with health management support, it can improve the quality of life for users while reducing the burden of monitoring.

[0046] The following describes the processing flow.

[0047] Step 1:

[0048] Users enter profile and health information through their devices. The devices then transmit this data to the server in real time.

[0049] Step 2:

[0050] The server stores the received user data in a database and creates individual profiles. This enables the provision of personalized services.

[0051] Step 3:

[0052] The user instructs the device to start a conversation. The device sends this request to the server and requests a topic for the conversation.

[0053] Step 4:

[0054] The server selects relevant topics based on the user's age and preferences. The dialogue engine then generates a conversation script using the selected topics.

[0055] Step 5:

[0056] The server sends the generated conversation script to the terminal. The terminal then presents this to the user as audio or text.

[0057] Step 6:

[0058] Users input or periodically update their health information daily through their device. The device sends this information to a server, which updates the health database.

[0059] Step 7:

[0060] The server analyzes the updated health data and creates notifications to provide users with warnings and health advice as needed.

[0061] Step 8:

[0062] The device receives notifications from the server and issues an alarm to the user at the appropriate time, either visually or audibly.

[0063] Step 9:

[0064] If a user becomes aware of an abnormal health condition, they enter the emergency situation into the device. The device immediately sends this information to the server.

[0065] Step 10:

[0066] Based on the abnormal information, the server automatically sends notifications to registered emergency contacts (family members or medical institutions) and takes measures to ensure the user's safety.

[0067] (Example 1)

[0068] 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."

[0069] There is a need for digital companions to prevent social isolation and deterioration of health among the elderly, and to enable them to live their daily lives with peace of mind. However, conventional technology makes it difficult to provide personalized support that meets the individual needs of each elderly person.

[0070] 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.

[0071] In this invention, the server includes information storage means for collecting and managing user attribute information, dialogue generation means for generating dialogues based on user input using natural language processing, and health monitoring means for monitoring the user's health status and generating warnings when abnormalities occur. This enables elderly people to receive individually personalized dialogues and health management support, leading to a higher quality of life and a more secure lifestyle.

[0072] "Information storage means" refers to a function for safely and efficiently collecting and managing user attribute information.

[0073] A "dialogue generation means" is a mechanism that uses natural language processing to automatically generate appropriate dialogue based on user input.

[0074] A "health monitoring system" is a technology that continuously observes the user's health status and quickly generates a warning when an abnormality occurs.

[0075] "Information transmission means" refers to communication technologies used to effectively send notifications and warnings to users.

[0076] A "content delivery method" is a system that uses information generation algorithms to provide users with personalized information.

[0077] The "dialogue topic generation method" is a function that automatically generates themes related to specific eras, tailored to the user's generation.

[0078] An "automatic notification system" is a function that automatically sends notifications to pre-registered emergency contacts when an abnormal situation occurs.

[0079] In implementing this invention, the system mainly consists of three components: a server, a terminal, and a user. The role of each component is described in detail below.

[0080] The server is primarily configured as an information storage system, aggregating and securely managing user attribute information. This utilizes general-purpose database software, on which personalized information is continuously updated. Furthermore, the server implements a dialogue generation system, leveraging natural language processing technology to analyze user input and generate appropriate dialogue. This process employs advanced analytical algorithms using generative AI models. In addition, the server monitors user health information, acting as a health monitoring tool and generating warnings if abnormalities are detected. This enables real-time monitoring of health status.

[0081] The terminal functions as a means of information transmission, effectively conveying notifications and warnings sent from the server to the user. The terminal also displays personalized content received from the server through a content delivery system. Users can input attribute information and record daily health information via the terminal. For example, if a user measures their blood pressure or body temperature and inputs that data into the terminal, the server can use it to analyze their health status and generate health advice as needed.

[0082] For example, if a user enters "I want to know about old movies," the server will retrieve data on movies popular during that era from its database based on the user's attribute information. The server can then use a generative AI model to generate trivia and interesting topics about the movies and provide them to the user through the terminal. An example of a prompt in this case would be, "If an elderly person says they want to talk about old movies, please generate information and trivia about those movies."

[0083] By using a system configured in this way, it can serve as a digital companion, enabling elderly people to live safely and securely without becoming isolated.

[0084] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0085] Step 1:

[0086] Users input attribute and health information through a terminal. The terminal then sends the entered data to the server. Specifically, the user physically uses the terminal's interface to input the necessary information. The input data on the server includes age and current health status, and this becomes the output stored in the server's database.

[0087] Step 2:

[0088] The server securely records the received attribute information in the database using an information storage mechanism. Data processing involves normalizing the information and storing it in the database in a consistent format. The output obtained during this process is a record of the updated attribute information.

[0089] Step 3:

[0090] The user enters a dialogue request via a terminal. The terminal sends this input to the server. For example, the user might request, "Please tell me about classic movies." The server's input includes this request text.

[0091] Step 4:

[0092] The server uses natural language processing technology to analyze user requests. A generative AI model is used to generate appropriate dialogue topics. The prompt used is: "If an elderly person says they want to talk about old movies, generate information and trivia about those movies." The output is specific answers and information for the user.

[0093] Step 5:

[0094] The generated content is sent from the server to the terminal. The terminal then provides the received information to the user, either through display or audio. As a concrete example, anecdotes about a movie are displayed on the terminal's screen. The server's output constitutes the provision of information to the user.

[0095] Step 6:

[0096] The device continuously collects the user's health information and sends it to the server. The server uses this information to perform health monitoring and generates warnings if any abnormalities are detected. Health information inputs include, for example, daily body temperature and blood pressure data, while outputs include health status assessments and warning notifications.

[0097] This system allows users to receive personalized conversations and health management services tailored to their individual needs.

[0098] (Application Example 1)

[0099] 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."

[0100] To ensure that elderly people do not become isolated and can live their daily lives with peace of mind, they need daily health management and emotional support through appropriate dialogue. However, conventional systems have difficulty responding flexibly to the individual circumstances of elderly people, and there is a lack of means to understand and manage specific changes in their health status and daily life activities. In particular, there is a need for reminder functions to maintain a healthy lifestyle and rapid response in emergencies.

[0101] 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.

[0102] In this invention, the server includes information recording means for collecting and managing personal data of elderly users, dialogue generation means for generating dialogues based on input from elderly users using natural language processing technology, and health monitoring means for monitoring the health information of elderly users and generating warnings in the event of abnormalities. This enables elderly people to check their daily health status and receive continuous support in their daily lives. Furthermore, by using a time management function tailored to individual users, it is possible to support the maintenance of healthy lifestyle habits and respond quickly to emergencies.

[0103] "Information recording means" refers to a device or method for securely collecting, managing, and storing information concerning an individual's age and health.

[0104] A "dialogue generation means" is a mechanism that uses natural language processing technology to generate human-to-human dialogue based on input speech or text.

[0105] A "health monitoring device" is a device or system that has the function of checking the health status of individual elderly people in real time and issuing a warning if an abnormality is detected.

[0106] A "means of communication" refers to a communication system that transmits necessary notifications and warnings to users without delay.

[0107] "Time management tools" refer to functions and devices that track the actions of elderly people and manage their daily activities by providing health checks and reminders.

[0108] A "generation method" is a mechanism for automatically generating conversation topics related to a specific era, tailored to the user's age group.

[0109] An "automatic notification system" is a device or technology that automatically sends notifications to pre-registered contacts when an abnormal situation occurs.

[0110] The system implementing this invention is a digital companion system that combines functions to support both personal health information and dialogue in order to improve the quality of life for the elderly. The server is operated by incorporating information recording means, dialogue generation means, health monitoring means, communication means, time management means, generation means, and automatic notification means.

[0111] The server first uses information recording means to securely collect and store personal data of elderly individuals. This includes data on age and health. The collected information is efficiently managed using a database management system (e.g., Firebase or AWS® DynamoDB).

[0112] Dialogue generation utilizes natural language processing (NLP) technology, with the server employing NLP libraries (e.g., spaCy and NLTK) to analyze user voice or text input. This process generates conversation topics and appropriate health advice tailored to the user's age group, which are then communicated to the user along with reminders.

[0113] Health monitoring is achieved by collecting daily health data from sensors built into the device (e.g., pedometer, blood pressure measurement function). The server analyzes this information and sends a warning to the user via a contact method if an abnormality is detected in real time. In addition, in the event of an abnormality, an automatic notification system is used to immediately notify pre-registered emergency contacts.

[0114] For example, if an elderly person enters "I'm not feeling well today," the server immediately analyzes their health data, identifies potential contributing patterns, and displays suggestions for improvement on their device. Furthermore, for regular medication times, the system uses time management tools to automatically send reminders, helping elderly people avoid forgetting to take their medication.

[0115] By incorporating generative AI models, the accuracy of dialogue and health management is improved. An example of a prompt is, "Design a dialogue function for a smartphone app that provides real-time information necessary for seniors to live safely and healthily." This enables a personalized dialogue experience for each user, improving their quality of life.

[0116] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0117] Step 1:

[0118] Users input their health status and requests into the device via voice or text. This input is converted into text data using the device's built-in speech recognition software. The resulting text data is then sent to the server.

[0119] Step 2:

[0120] The server analyzes the received text data using natural language processing libraries (e.g., spaCy or NLTK). Through this analysis, it understands the user's intent and interests and generates the necessary dialogue content. Generative AI models may also be used to improve the understanding of the input data. At this stage, the generated dialogue topics and health information are selected.

[0121] Step 3:

[0122] The server retrieves past health data related to the user from a personal database. It uses database systems such as Firebase or AWS DynamoDB to search and extract the corresponding data. This prepares the server to suggest appropriate health advice and lifestyle improvements to the user.

[0123] Step 4:

[0124] Based on the analysis results, the server generates user-specific conversations and health notifications. The generated content includes age-appropriate topics and health advice, which are then converted into audio and notification formats.

[0125] Step 5:

[0126] The server sends generated conversations and health advice to the device via a communication method. The device presents this to the user as text or voice notifications. Text-to-speech functionality may be used for voice notifications.

[0127] Step 6:

[0128] Users receive information provided through their devices and use it to help with their daily activities and health management. For example, by setting and utilizing reminders based on time management methods, such as taking medication or going for a walk, they can lead a healthier life.

[0129] Step 7:

[0130] If an anomaly is detected, the server will use an automated notification system to send information to emergency contacts. If an emergency response is necessary, prompt action will be taken to ensure the safety of the elderly.

[0131] 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.

[0132] This invention relates to a digital companion system for the elderly that incorporates an emotion engine to recognize user emotions and provide dialogue and services tailored to individual needs. The system consists of a server, a terminal, and a user, and aims to enrich the user's life and improve their health management.

[0133] 1. Implementation of the emotion engine

[0134] The server uses an emotion engine to analyze the user's emotional state from their voice and text. This analysis includes elements such as voice tone, text content, and facial recognition (if applicable). The device accepts voice or camera input as needed to provide this information to the server.

[0135] 2. Adjusting dialogue based on emotions

[0136] Based on the results of sentiment analysis, the server generates conversations that match the user's intentions and mental state. If it determines that the user is experiencing stress, it adjusts the conversation content and provides relaxing topics and encouraging words.

[0137] Specific example: If a user inputs "I haven't been sleeping well lately" in a depressed tone, the server, through its emotion engine, recognizes that the user is experiencing stress related to insomnia and suggests breathing exercises and music to help them relax.

[0138] 3. Customization of content delivery

[0139] The device receives instructions from the server and provides appropriate content according to the user's emotional state. This includes relaxation music, meditation guides, or video clips on stress reduction.

[0140] Specific example: When a user types "I want a change of pace," the device plays hit songs from the user's preferred era or videos related to their hobbies, based on suggestions from the server.

[0141] This system will reduce the mental burden caused by loneliness in the daily lives of the elderly, enabling them to lead richer and healthier lives. By using an emotion engine, flexible services tailored to the individual needs of each user will be provided, contributing to an improved quality of life.

[0142] The following describes the processing flow.

[0143] Step 1:

[0144] The user initiates a daily conversation through the device by inputting voice or text. The device receives this input.

[0145] Step 2:

[0146] The device sends the acquired voice or text data to the server for sentiment analysis. This includes the user's voice tone and the words they use.

[0147] Step 3:

[0148] The server uses an emotion engine to analyze the user's emotional state from their input. For example, if the tone of voice is subdued, the server will determine that the user is sad.

[0149] Step 4:

[0150] Based on the emotional analysis, the server generates a conversation script tailored to the user's mental state. If it determines that the user is stressed, it selects a relaxing topic.

[0151] Step 5:

[0152] The server sends the generated conversation script to the terminal. The terminal presents the received script to the user in either audio or text format.

[0153] Step 6:

[0154] The system continues the conversation or asks further questions based on the user's input from their device. The user's responses are then sent back to the server via the device.

[0155] Step 7:

[0156] The server continuously analyzes user responses and re-evaluates the emotional state as needed. It then dynamically adjusts and resends the conversation content.

[0157] Step 8:

[0158] If the user's emotions are unstable, the server will decide to provide relaxation content or stress-reducing advice. It may also suggest music or meditation guides.

[0159] Step 9:

[0160] The device plays appropriate content for the user according to instructions from the server. The user can then experience mental relaxation through this content.

[0161] (Example 2)

[0162] 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 as the "terminal".

[0163] Elderly users are prone to feelings of loneliness and stress in their daily lives, which can negatively impact their physical and mental health. However, conventional systems have struggled to adequately recognize users' emotional states and provide services and content tailored to their individual needs. Furthermore, there is a lack of systems that can continuously monitor the health status of elderly users and respond quickly in the event of an abnormality.

[0164] 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.

[0165] In this invention, the server includes emotion analysis means that analyzes voice tone and text content to recognize the user's emotions, content provision means that provides optimal content based on the emotional state of the elderly user, and health monitoring means that monitors the health status of the elderly user and generates a warning in case of abnormality. As a result, the elderly user can enjoy appropriate dialogue and content based on their emotions, and can receive prompt and appropriate responses if there is a change in their health status.

[0166] "Information management means" refers to methods or devices for securely collecting and managing personal information of elderly users.

[0167] "Dialogue generation means" refers to a method or apparatus for generating dialogue based on input from elderly users using natural language processing technology.

[0168] "Emotional analysis means" refers to a method or device for recognizing a user's emotions by analyzing their voice tone or text content.

[0169] "Content delivery means" refers to a method or device for selecting and providing optimal content based on the emotional state of elderly users.

[0170] "Health monitoring means" refers to a method or device for continuously monitoring the health status of elderly users and generating warnings in the event of abnormalities.

[0171] "Communication means" refers to methods or devices for conveying notifications or warnings to elderly users.

[0172] This invention is a digital companion system for the elderly that incorporates an emotion engine to recognize the user's emotions and provide dialogue and services tailored to their individual needs. The system consists of a server, a terminal, and a user, and aims to improve the quality of life for the elderly.

[0173] The server features an emotion engine that utilizes a generative AI model to analyze voice tone and text content to recognize the user's emotions. This involves using voice data analysis and natural language processing technologies to extract voice tone and estimate emotions. The terminal uses hardware such as a microphone and camera to obtain voice and video input from the user and transmit this to the server.

[0174] When a user speaks to the system or gives instructions, the terminal receives that information and sends it to the server in real time. For example, if a user inputs "I'm a little tired," the server recognizes that emotion and provides music or meditation guidance to help them relax.

[0175] Examples of specific prompts include, "I want to create a system that identifies emotions from user speech and suggests relaxing content," and "Please write a program that analyzes emotional states from voice tone and text and adjusts the dialogue accordingly."

[0176] The terminal receives the results of emotion analysis from the server and presents appropriate dialogue and content to the elderly. This allows users to receive services tailored to their individual needs, contributing to reducing feelings of loneliness and maintaining their physical and mental health.

[0177] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0178] Step 1:

[0179] The device receives voice input and camera footage from the user. Input data includes the user's spoken words and facial expressions. The device converts these inputs into digital signals and formats them for transmission to the server. Natural user interaction is crucial in this step.

[0180] Step 2:

[0181] The server analyzes the audio and video data received from the terminal. Using an emotion engine, the server analyzes the voice tone and text content to estimate the user's emotional state. Specific operations include feature extraction from audio data, voice tone analysis, and facial expression recognition from video data. The output generates data related to the user's emotional state.

[0182] Step 3:

[0183] The server uses a generative AI model to generate conversational content tailored to the user, based on the results of the emotion analysis. The input used is the result of the emotion analysis. Based on this analysis, the server creates conversational content that promotes relaxation and a sense of security. For example, if the user is feeling stressed, it will generate advice and topics to help them relax.

[0184] Step 4:

[0185] The server selects the most appropriate content based on the user's emotional state and sends it to the device. Input includes data on the user's preferences, along with the generated dialogue. The server selects content that meets the user's needs, such as relaxation music or meditation guides. The selected content data is sent to the device as output.

[0186] Step 5:

[0187] The device provides the user with content received from the server. The device can play music or provide meditation guides. As output, the user can view or listen to relaxing content. Specifically, audio and video are output through speakers or a display.

[0188] This series of processes allows the system to provide individually customized dialogue and content while taking into account the emotional state of the elderly person.

[0189] (Application Example 2)

[0190] 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".

[0191] Loneliness and stress experienced by older adults in their daily lives are problems that negatively impact their quality of life and health. Furthermore, as older adults experience increased physical changes and health risks, regular health monitoring and emergency response are essential. In addition, a lack of skills to appropriately recognize emotional changes and provide corresponding support is also a challenge.

[0192] 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.

[0193] In this invention, the server includes information storage means for collecting and managing personal data of elderly users, conversation generation means for generating dialogue using natural language processing technology, health observation means for monitoring the health information of elderly users, information communication means for transmitting information to elderly users, recognition means for recognizing emotions, and emotion adaptation means for adjusting dialogue based on emotions. This enables accurate understanding of the emotional state of elderly people, the provision of appropriate dialogue, and the maintenance of health and emergency response.

[0194] "Information storage means" refers to technologies and devices for efficiently collecting and managing personal data of elderly users.

[0195] "Conversation generation means" refers to a technology that uses natural language processing to automatically generate dialogues based on input from elderly users.

[0196] "Health monitoring means" refers to methods and devices for regularly monitoring the health information of elderly users and evaluating their health status.

[0197] "Information and communication means" refers to communication technologies and devices used to transmit information such as notifications and warnings to elderly users.

[0198] "Recognition means" refers to technology for analyzing and recognizing the emotions of elderly users through their voice, facial expressions, and text input.

[0199] "Emotional adaptation means" refers to technology that appropriately adjusts the content of a conversation based on recognized emotions, thereby providing a service tailored to the user.

[0200] This invention is a digital companion system designed to enrich the lives of elderly users and support their health management. The system includes means for information storage, conversation generation, health observation, information communication, recognition, and emotional adaptation.

[0201] First, the device collects voice and text data from elderly users. Voice data is captured by a microphone, and text data is converted using speech recognition technology. This data is sent to a server and managed as personal data of elderly users by an information storage system.

[0202] Next, using natural language processing technology, the server generates a dialogue based on the acquired data through a conversation generation mechanism. A conversation topic appropriate to the age group of the elderly user is selected, and an appropriate response is formed. Specifically, the voice data is processed using the Google® Cloud Speech-to-Text API, and the dialogue is generated using a natural language processing library.

[0203] In addition, the server uses health monitoring devices to monitor health-related information sent from terminals, and if an abnormality is detected, it sends a notification to elderly users or emergency contacts via information and communication devices.

[0204] Furthermore, the server uses recognition mechanisms to analyze emotions based on audio and facial expression data acquired from cameras and microphones. Technologies such as OpenCV are utilized to implement the ability to read emotions from facial expressions. Based on the analyzed emotions, emotion adaptation mechanisms adjust the dialogue content to provide appropriate conversations and content.

[0205] As a concrete example, in the morning, the device asks, "Shall we check today's schedule?" and the user replies, "I'm not feeling very well today." The server recognizes the user's tired facial expression and tone of voice, sensing stress and fatigue. Based on this, the server suggests to the user, "Let's take a short break. Shall I suggest some relaxing music or stretching?"

[0206] An example of a prompt for a generative AI model is the text: "When the user says they are tired with a melancholic expression, please come up with a conversation to cheer them up. The user is a woman in her 70s who likes music."

[0207] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0208] Step 1:

[0209] The device collects audio and video data from the user using a microphone and camera. This data is input as the user's speech and facial expressions. Audio data is processed using signal processing technology to remove noise and output as a clean audio file. Video data is processed using image processing technology to extract specific frames and output as an image containing the user's facial expression information.

[0210] Step 2:

[0211] The device applies speech recognition technology to convert the collected audio data into text. The Google Cloud Speech-to-Text API receives the audio data as input and outputs the corresponding text data. This text data is used in the next step as the user's spoken content.

[0212] Step 3:

[0213] The server processes the received text data and facial image data through recognition tools to analyze the user's emotions. Text data is analyzed using natural language processing techniques, and facial image data is processed using a face recognition algorithm based on OpenCV. This data is output as information about the emotional state and passed to the emotion adaptation tool.

[0214] Step 4:

[0215] The server receives the analyzed emotional state as input and uses a conversation generation tool to form an appropriate dialogue. Using a natural language processing library, it generates a dialogue flow based on the emotional state and outputs the result as text data. This output includes suggestions to promote relaxation and conversational content to encourage the user.

[0216] Step 5:

[0217] The device converts the outputted dialogue text into speech using speech synthesis technology. The generated speech is played through the speaker and delivered to the user. This allows the user to receive the response as speech, thus completing the dialogue.

[0218] Step 6:

[0219] Additionally, the server monitors the user's health status using health monitoring devices and sends necessary notifications via information and communication devices if an abnormality is detected. Sensor data is collected as input, and if it exceeds pre-set health status parameters, an alarm is generated and output as a notification.

[0220] 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.

[0221] 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.

[0222] 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.

[0223] [Second Embodiment]

[0224] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0225] 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.

[0226] 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).

[0227] 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.

[0228] 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.

[0229] 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).

[0230] 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.

[0231] 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.

[0232] 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.

[0233] 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.

[0234] 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.

[0235] 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".

[0236] This invention relates to a digital companion system for improving the quality of life for the elderly. The system consists of a server, a terminal, and a user, and provides individually personalized conversational and health management services.

[0237] 1. Details of the database method

[0238] The server has a database that securely stores and manages personal data provided by users. This database includes data on age, health information, and preferences, and the data can be updated at any time.

[0239] 2. Application of Natural Language Processing Techniques

[0240] The server uses natural language processing technology to analyze the voice or text input by the user. This generates conversations about nostalgic topics and daily events that are of interest to the elderly, and provides them to the device.

[0241] Specific example: If a user types, "I want to talk about movies I used to watch a lot," the server retrieves information on popular movies from its database that match the user's age group. The dialogue engine then generates anecdotes and trivia about those movies and sends them to the terminal.

[0242] 3. Explanation of health management methods

[0243] The device collects the user's daily health information and sends it to the server. The server uses this information to analyze the user's health status and provides health guidance and alerts as needed. Furthermore, it has a system that automatically notifies registered contacts in case of an emergency.

[0244] Specific example: If a user enters "I feel like my blood pressure has been high lately," the device sends this information to the server, which then generates appropriate advice based on that information and returns it to the device for display to the user.

[0245] 4. Functions of communication means

[0246] The communication method enables efficient data sharing between the terminal and the server. This communication is bidirectional and designed to ensure that user input and server notifications are received without delay.

[0247] As described above, this system provides an environment where elderly people can live their daily lives with peace of mind and without isolation. By combining a unique conversational experience with health management support, it can improve the quality of life for users while reducing the burden of monitoring.

[0248] The following describes the processing flow.

[0249] Step 1:

[0250] Users enter profile and health information through their devices. The devices then transmit this data to the server in real time.

[0251] Step 2:

[0252] The server stores the received user data in a database and creates individual profiles. This enables the provision of personalized services.

[0253] Step 3:

[0254] The user instructs the device to start a conversation. The device sends this request to the server and requests a topic for the conversation.

[0255] Step 4:

[0256] The server selects relevant topics based on the user's age and preferences. The dialogue engine then generates a conversation script using the selected topics.

[0257] Step 5:

[0258] The server sends the generated conversation script to the terminal. The terminal then presents this to the user as audio or text.

[0259] Step 6:

[0260] Users input or periodically update their health information daily through their device. The device sends this information to a server, which updates the health database.

[0261] Step 7:

[0262] The server analyzes the updated health data and creates notifications to provide users with warnings and health advice as needed.

[0263] Step 8:

[0264] The device receives notifications from the server and issues an alarm to the user at the appropriate time, either visually or audibly.

[0265] Step 9:

[0266] If a user becomes aware of an abnormal health condition, they enter the emergency situation into the device. The device immediately sends this information to the server.

[0267] Step 10:

[0268] Based on the abnormal information, the server automatically sends notifications to registered emergency contacts (family members or medical institutions) and takes measures to ensure the user's safety.

[0269] (Example 1)

[0270] 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."

[0271] There is a need for digital companions to prevent social isolation and deterioration of health among the elderly, and to enable them to live their daily lives with peace of mind. However, conventional technology makes it difficult to provide personalized support that meets the individual needs of each elderly person.

[0272] 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.

[0273] In this invention, the server includes information storage means for collecting and managing user attribute information, dialogue generation means for generating dialogues based on user input using natural language processing, and health monitoring means for monitoring the user's health status and generating warnings when abnormalities occur. This enables elderly people to receive individually personalized dialogues and health management support, leading to a higher quality of life and a more secure lifestyle.

[0274] "Information storage means" refers to a function for safely and efficiently collecting and managing user attribute information.

[0275] A "dialogue generation means" is a mechanism that uses natural language processing to automatically generate appropriate dialogue based on user input.

[0276] A "health monitoring system" is a technology that continuously observes the user's health status and quickly generates a warning when an abnormality occurs.

[0277] "Information transmission means" refers to communication technologies used to effectively send notifications and warnings to users.

[0278] A "content delivery method" is a system that uses information generation algorithms to provide users with personalized information.

[0279] The "dialogue topic generation method" is a function that automatically generates themes related to specific eras, tailored to the user's generation.

[0280] An "automatic notification system" is a function that automatically sends notifications to pre-registered emergency contacts when an abnormal situation occurs.

[0281] In implementing this invention, the system mainly consists of three components: a server, a terminal, and a user. The role of each component is described in detail below.

[0282] The server is centered around information storage means, aggregates users' attribute information, and manages it securely. General database software is used for this, and personalized information is sequentially updated thereon. Furthermore, an interaction generation means is implemented in the server, which utilizes natural language processing technology to analyze users' inputs and generate appropriate interactions. Advanced analysis algorithms using a generation AI model are used in this process. In addition, the server monitors users' health information, acts as a health monitoring means, and generates warnings when abnormalities are detected. This enables real-time understanding of the health status.

[0283] The terminal functions as an information transmission means and is responsible for effectively conveying notifications and warnings sent from the server to the user. Also, the terminal displays personalized content received from the server to the user through the content providing means. The user can input attribute information and record daily health information via the terminal. For example, when the user measures blood pressure and body temperature and inputs the data into the terminal, the server utilizes it to analyze the health status and generate health advice as needed.

[0284] As a specific example, when the user inputs "I want to know about old movies", the server retrieves data on movies popular in that era from the database based on the user's attribute information. It is possible for the server to use the generation AI model to generate movie trivia and interesting topics and provide them to the user through the terminal. An example of the prompt sentence in this case is "When an elderly person says they want to talk about old movies, generate information and trivia about those movies."

[0285] By using the system configured in this way, it serves as a digital companion for the elderly to live safely without feeling isolated.

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

[0287] Step 1:

[0288] Users input attribute and health information through a terminal. The terminal then sends the entered data to the server. Specifically, the user physically uses the terminal's interface to input the necessary information. The input data on the server includes age and current health status, and this becomes the output stored in the server's database.

[0289] Step 2:

[0290] The server securely records the received attribute information in the database using an information storage mechanism. Data processing involves normalizing the information and storing it in the database in a consistent format. The output obtained during this process is a record of the updated attribute information.

[0291] Step 3:

[0292] The user enters a dialogue request via a terminal. The terminal sends this input to the server. For example, the user might request, "Please tell me about classic movies." The server's input includes this request text.

[0293] Step 4:

[0294] The server uses natural language processing technology to analyze user requests. A generative AI model is used to generate appropriate dialogue topics. The prompt used is: "If an elderly person says they want to talk about old movies, generate information and trivia about those movies." The output is specific answers and information for the user.

[0295] Step 5:

[0296] The generated content is sent from the server to the terminal. The terminal then provides the received information to the user, either through display or audio. As a concrete example, anecdotes about a movie are displayed on the terminal's screen. The server's output constitutes the provision of information to the user.

[0297] Step 6:

[0298] The device continuously collects the user's health information and sends it to the server. The server uses this information to perform health monitoring and generates warnings if any abnormalities are detected. Health information inputs include, for example, daily body temperature and blood pressure data, while outputs include health status assessments and warning notifications.

[0299] This system allows users to receive personalized conversations and health management services tailored to their individual needs.

[0300] (Application Example 1)

[0301] 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."

[0302] To ensure that elderly people do not become isolated and can live their daily lives with peace of mind, they need daily health management and emotional support through appropriate dialogue. However, conventional systems have difficulty responding flexibly to the individual circumstances of elderly people, and there is a lack of means to understand and manage specific changes in their health status and daily life activities. In particular, there is a need for reminder functions to maintain a healthy lifestyle and rapid response in emergencies.

[0303] 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.

[0304] In this invention, the server includes an information recording means for collecting and managing the personal data of elderly users, a dialogue generation means for generating a dialogue based on the input of elderly users using natural language processing technology, and a health monitoring means for monitoring the health information of elderly users and generating a warning when an abnormality occurs. As a result, it becomes possible for the elderly to receive continuous support in their daily lives while checking their daily health status. In addition, by using a time management function tailored to individual users, it is possible to support the maintenance of a healthy lifestyle and respond promptly to emergencies.

[0305] The "information recording means" is a device or method for safely collecting, managing, and storing information related to an individual's age and health.

[0306] The "dialogue generation means" is a mechanism for generating a dialogue with humans based on the input voice or text using natural language processing technology.

[0307] The "health monitoring means" is a device or system having a function of checking the health status of individual elderly people in real time and issuing a warning when an abnormality is found.

[0308] The "communication means" is a communication system for transmitting necessary notifications and warnings to users without delay.

[0309] The "time management means" is a function or device for managing daily activities by tracking the actions of elderly people and issuing health checks and reminders.

[0310] The "generation means" is a mechanism for automatically creating topics for conversations related to a specific era according to the age group of users.

[0311] The "automatic notification means" is a device or technology for automatically sending a notification to a pre-registered contact when an abnormal situation occurs.

[0312] The system implementing this invention is a digital companion system that combines functions to support both personal health information and dialogue in order to improve the quality of life for the elderly. The server is operated by incorporating information recording means, dialogue generation means, health monitoring means, communication means, time management means, generation means, and automatic notification means.

[0313] The server first uses information recording means to securely collect and store personal data of elderly individuals. This includes data on age and health. The collected information is efficiently managed using a database management system (e.g., Firebase or AWS DynamoDB).

[0314] Dialogue generation utilizes natural language processing (NLP) technology, with the server employing NLP libraries (e.g., spaCy and NLTK) to analyze user voice or text input. This process generates conversation topics and appropriate health advice tailored to the user's age group, which are then communicated to the user along with reminders.

[0315] Health monitoring is achieved by collecting daily health data from sensors built into the device (e.g., pedometer, blood pressure measurement function). The server analyzes this information and sends a warning to the user via a contact method if an abnormality is detected in real time. In addition, in the event of an abnormality, an automatic notification system is used to immediately notify pre-registered emergency contacts.

[0316] For example, if an elderly person enters "I'm not feeling well today," the server immediately analyzes their health data, identifies potential contributing patterns, and displays suggestions for improvement on their device. Furthermore, for regular medication times, the system uses time management tools to automatically send reminders, helping elderly people avoid forgetting to take their medication.

[0317] By incorporating generative AI models, the accuracy of dialogue and health management is improved. An example of a prompt is, "Design a dialogue function for a smartphone app that provides real-time information necessary for seniors to live safely and healthily." This enables a personalized dialogue experience for each user, improving their quality of life.

[0318] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0319] Step 1:

[0320] Users input their health status and requests into the device via voice or text. This input is converted into text data using the device's built-in speech recognition software. The resulting text data is then sent to the server.

[0321] Step 2:

[0322] The server analyzes the received text data using natural language processing libraries (e.g., spaCy or NLTK). Through this analysis, it understands the user's intent and interests and generates the necessary dialogue content. Generative AI models may also be used to improve the understanding of the input data. At this stage, the generated dialogue topics and health information are selected.

[0323] Step 3:

[0324] The server retrieves past health data related to the user from a personal database. It uses database systems such as Firebase or AWS DynamoDB to search and extract the corresponding data. This prepares the server to suggest appropriate health advice and lifestyle improvements to the user.

[0325] Step 4:

[0326] Based on the analysis results, the server generates user-specific conversations and health notifications. The generated content includes age-appropriate topics and health advice, which are then converted into audio and notification formats.

[0327] Step 5:

[0328] The server sends generated conversations and health advice to the device via a communication method. The device presents this to the user as text or voice notifications. Text-to-speech functionality may be used for voice notifications.

[0329] Step 6:

[0330] Users receive information provided through their devices and use it to help with their daily activities and health management. For example, by setting and utilizing reminders based on time management methods, such as taking medication or going for a walk, they can lead a healthier life.

[0331] Step 7:

[0332] If an anomaly is detected, the server will use an automated notification system to send information to emergency contacts. If an emergency response is necessary, prompt action will be taken to ensure the safety of the elderly.

[0333] 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.

[0334] This invention relates to a digital companion system for the elderly that incorporates an emotion engine to recognize user emotions and provide dialogue and services tailored to individual needs. The system consists of a server, a terminal, and a user, and aims to enrich the user's life and improve their health management.

[0335] 1. Implementation of the emotion engine

[0336] The server uses an emotion engine to analyze the user's emotional state from their voice and text. This analysis includes elements such as voice tone, text content, and facial recognition (if applicable). The device accepts voice or camera input as needed to provide this information to the server.

[0337] 2. Adjusting dialogue based on emotions

[0338] Based on the results of sentiment analysis, the server generates conversations that match the user's intentions and mental state. If it determines that the user is experiencing stress, it adjusts the conversation content and provides relaxing topics and encouraging words.

[0339] Specific example: If a user inputs "I haven't been sleeping well lately" in a depressed tone, the server, through its emotion engine, recognizes that the user is experiencing stress related to insomnia and suggests breathing exercises and music to help them relax.

[0340] 3. Customization of content delivery

[0341] The device receives instructions from the server and provides appropriate content according to the user's emotional state. This includes relaxation music, meditation guides, or video clips on stress reduction.

[0342] Specific example: When a user types "I want a change of pace," the device plays hit songs from the user's preferred era or videos related to their hobbies, based on suggestions from the server.

[0343] This system will reduce the mental burden caused by loneliness in the daily lives of the elderly, enabling them to lead richer and healthier lives. By using an emotion engine, flexible services tailored to the individual needs of each user will be provided, contributing to an improved quality of life.

[0344] The following describes the processing flow.

[0345] Step 1:

[0346] The user initiates a daily conversation through the device by inputting voice or text. The device receives this input.

[0347] Step 2:

[0348] The device sends the acquired voice or text data to the server for sentiment analysis. This includes the user's voice tone and the words they use.

[0349] Step 3:

[0350] The server uses an emotion engine to analyze the user's emotional state from their input. For example, if the tone of voice is subdued, the server will determine that the user is sad.

[0351] Step 4:

[0352] Based on the emotional analysis, the server generates a conversation script tailored to the user's mental state. If it determines that the user is stressed, it selects a relaxing topic.

[0353] Step 5:

[0354] The server sends the generated conversation script to the terminal. The terminal presents the received script to the user in either audio or text format.

[0355] Step 6:

[0356] The system continues the conversation or asks further questions based on the user's input from their device. The user's responses are then sent back to the server via the device.

[0357] Step 7:

[0358] The server continuously analyzes user responses and re-evaluates the emotional state as needed. It then dynamically adjusts and resends the conversation content.

[0359] Step 8:

[0360] If the user's emotions are unstable, the server will decide to provide relaxation content or stress-reducing advice. It may also suggest music or meditation guides.

[0361] Step 9:

[0362] The device plays appropriate content for the user according to instructions from the server. The user can then experience mental relaxation through this content.

[0363] (Example 2)

[0364] 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".

[0365] Elderly users are prone to feelings of loneliness and stress in their daily lives, which can negatively impact their physical and mental health. However, conventional systems have struggled to adequately recognize users' emotional states and provide services and content tailored to their individual needs. Furthermore, there is a lack of systems that can continuously monitor the health status of elderly users and respond quickly in the event of an abnormality.

[0366] 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.

[0367] In this invention, the server includes emotion analysis means that analyzes voice tone and text content to recognize the user's emotions, content provision means that provides optimal content based on the emotional state of the elderly user, and health monitoring means that monitors the health status of the elderly user and generates a warning in case of abnormality. As a result, the elderly user can enjoy appropriate dialogue and content based on their emotions, and can receive prompt and appropriate responses if there is a change in their health status.

[0368] "Information management means" refers to methods or devices for securely collecting and managing personal information of elderly users.

[0369] "Dialogue generation means" refers to a method or apparatus for generating dialogue based on input from elderly users using natural language processing technology.

[0370] "Emotional analysis means" refers to a method or device for recognizing a user's emotions by analyzing their voice tone or text content.

[0371] "Content delivery means" refers to a method or device for selecting and providing optimal content based on the emotional state of elderly users.

[0372] "Health monitoring means" refers to a method or device for continuously monitoring the health status of elderly users and generating warnings in the event of abnormalities.

[0373] "Communication means" refers to methods or devices for conveying notifications or warnings to elderly users.

[0374] This invention is a digital companion system for the elderly that incorporates an emotion engine to recognize the user's emotions and provide dialogue and services tailored to their individual needs. The system consists of a server, a terminal, and a user, and aims to improve the quality of life for the elderly.

[0375] The server features an emotion engine that utilizes a generative AI model to analyze voice tone and text content to recognize the user's emotions. This involves using voice data analysis and natural language processing technologies to extract voice tone and estimate emotions. The terminal uses hardware such as a microphone and camera to obtain voice and video input from the user and transmit this to the server.

[0376] When a user speaks to the system or gives instructions, the terminal receives that information and sends it to the server in real time. For example, if a user inputs "I'm a little tired," the server recognizes that emotion and provides music or meditation guidance to help them relax.

[0377] Examples of specific prompts include, "I want to create a system that identifies emotions from user speech and suggests relaxing content," and "Please write a program that analyzes emotional states from voice tone and text and adjusts the dialogue accordingly."

[0378] The terminal receives the results of emotion analysis from the server and presents appropriate dialogue and content to the elderly. This allows users to receive services tailored to their individual needs, contributing to reducing feelings of loneliness and maintaining their physical and mental health.

[0379] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0380] Step 1:

[0381] The device receives voice input and camera footage from the user. Input data includes the user's spoken words and facial expressions. The device converts these inputs into digital signals and formats them for transmission to the server. Natural user interaction is crucial in this step.

[0382] Step 2:

[0383] The server analyzes the audio and video data received from the terminal. Using an emotion engine, the server analyzes the voice tone and text content to estimate the user's emotional state. Specific operations include feature extraction from audio data, voice tone analysis, and facial expression recognition from video data. The output generates data related to the user's emotional state.

[0384] Step 3:

[0385] The server uses a generative AI model to generate conversational content tailored to the user, based on the results of the emotion analysis. The input used is the result of the emotion analysis. Based on this analysis, the server creates conversational content that promotes relaxation and a sense of security. For example, if the user is feeling stressed, it will generate advice and topics to help them relax.

[0386] Step 4:

[0387] The server selects the most appropriate content based on the user's emotional state and sends it to the device. Input includes data on the user's preferences, along with the generated dialogue. The server selects content that meets the user's needs, such as relaxation music or meditation guides. The selected content data is sent to the device as output.

[0388] Step 5:

[0389] The device provides the user with content received from the server. The device can play music or provide meditation guides. As output, the user can view or listen to relaxing content. Specifically, audio and video are output through speakers or a display.

[0390] This series of processes allows the system to provide individually customized dialogue and content while taking into account the emotional state of the elderly person.

[0391] (Application Example 2)

[0392] 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 as the "terminal".

[0393] Loneliness and stress experienced by older adults in their daily lives are problems that negatively impact their quality of life and health. Furthermore, as older adults experience increased physical changes and health risks, regular health monitoring and emergency response are essential. In addition, a lack of skills to appropriately recognize emotional changes and provide corresponding support is also a challenge.

[0394] 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.

[0395] In this invention, the server includes information storage means for collecting and managing personal data of elderly users, conversation generation means for generating dialogue using natural language processing technology, health observation means for monitoring the health information of elderly users, information communication means for transmitting information to elderly users, recognition means for recognizing emotions, and emotion adaptation means for adjusting dialogue based on emotions. This enables accurate understanding of the emotional state of elderly people, the provision of appropriate dialogue, and the maintenance of health and emergency response.

[0396] "Information storage means" refers to technologies and devices for efficiently collecting and managing personal data of elderly users.

[0397] "Conversation generation means" refers to a technology that uses natural language processing to automatically generate dialogues based on input from elderly users.

[0398] "Health monitoring means" refers to methods and devices for regularly monitoring the health information of elderly users and evaluating their health status.

[0399] "Information and communication means" refers to communication technologies and devices used to transmit information such as notifications and warnings to elderly users.

[0400] "Recognition means" refers to technology for analyzing and recognizing the emotions of elderly users through their voice, facial expressions, and text input.

[0401] "Emotional adaptation means" refers to technology that appropriately adjusts the content of a conversation based on recognized emotions, thereby providing a service tailored to the user.

[0402] This invention is a digital companion system designed to enrich the lives of elderly users and support their health management. The system includes means for information storage, conversation generation, health observation, information communication, recognition, and emotional adaptation.

[0403] First, the device collects voice and text data from elderly users. Voice data is captured by a microphone, and text data is converted using speech recognition technology. This data is sent to a server and managed as personal data of elderly users by an information storage system.

[0404] Next, using natural language processing technology, the server generates a dialogue based on the acquired data through a conversation generation mechanism. Conversation topics appropriate to the age group of the elderly users are selected, and appropriate responses are formed. Specifically, the audio data is processed using the Google Cloud Speech-to-Text API, and the dialogue is generated using a natural language processing library.

[0405] In addition, the server uses health monitoring devices to monitor health-related information sent from terminals, and if an abnormality is detected, it sends a notification to elderly users or emergency contacts via information and communication devices.

[0406] Furthermore, the server uses recognition mechanisms to analyze emotions based on audio and facial expression data acquired from cameras and microphones. Technologies such as OpenCV are utilized to implement the ability to read emotions from facial expressions. Based on the analyzed emotions, emotion adaptation mechanisms adjust the dialogue content to provide appropriate conversations and content.

[0407] As a concrete example, in the morning, the device asks, "Shall we check today's schedule?" and the user replies, "I'm not feeling very well today." The server recognizes the user's tired facial expression and tone of voice, sensing stress and fatigue. Based on this, the server suggests to the user, "Let's take a short break. Shall I suggest some relaxing music or stretching?"

[0408] An example of a prompt for a generative AI model is the text: "When the user says they are tired with a melancholic expression, please come up with a conversation to cheer them up. The user is a woman in her 70s who likes music."

[0409] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0410] Step 1:

[0411] The device collects audio and video data from the user using a microphone and camera. This data is input as the user's speech and facial expressions. Audio data is processed using signal processing technology to remove noise and output as a clean audio file. Video data is processed using image processing technology to extract specific frames and output as an image containing the user's facial expression information.

[0412] Step 2:

[0413] The device applies speech recognition technology to convert the collected audio data into text. The Google Cloud Speech-to-Text API receives the audio data as input and outputs the corresponding text data. This text data is used in the next step as the user's spoken content.

[0414] Step 3:

[0415] The server processes the received text data and facial image data through recognition tools to analyze the user's emotions. Text data is analyzed using natural language processing techniques, and facial image data is processed using a face recognition algorithm based on OpenCV. This data is output as information about the emotional state and passed to the emotion adaptation tool.

[0416] Step 4:

[0417] The server receives the analyzed emotional state as input and uses a conversation generation tool to form an appropriate dialogue. Using a natural language processing library, it generates a dialogue flow based on the emotional state and outputs the result as text data. This output includes suggestions to promote relaxation and conversational content to encourage the user.

[0418] Step 5:

[0419] The device converts the outputted dialogue text into speech using speech synthesis technology. The generated speech is played through the speaker and delivered to the user. This allows the user to receive the response as speech, thus completing the dialogue.

[0420] Step 6:

[0421] Additionally, the server monitors the user's health status using health monitoring devices and sends necessary notifications via information and communication devices if an abnormality is detected. Sensor data is collected as input, and if it exceeds pre-set health status parameters, an alarm is generated and output as a notification.

[0422] 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.

[0423] 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.

[0424] 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.

[0425] [Third Embodiment]

[0426] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0427] 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.

[0428] 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).

[0429] 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.

[0430] 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.

[0431] 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).

[0432] 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.

[0433] 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.

[0434] 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.

[0435] 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.

[0436] 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.

[0437] 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".

[0438] This invention relates to a digital companion system for improving the quality of life for the elderly. The system consists of a server, a terminal, and a user, and provides individually personalized conversational and health management services.

[0439] 1. Details of the database method

[0440] The server has a database that securely stores and manages personal data provided by users. This database includes data on age, health information, and preferences, and the data can be updated at any time.

[0441] 2. Application of Natural Language Processing Techniques

[0442] The server uses natural language processing technology to analyze the voice or text input by the user. This generates conversations about nostalgic topics and daily events that are of interest to the elderly, and provides them to the device.

[0443] Specific example: If a user types, "I want to talk about movies I used to watch a lot," the server retrieves information on popular movies from its database that match the user's age group. The dialogue engine then generates anecdotes and trivia about those movies and sends them to the terminal.

[0444] 3. Explanation of health management methods

[0445] The device collects the user's daily health information and sends it to the server. The server uses this information to analyze the user's health status and provides health guidance and alerts as needed. Furthermore, it has a system that automatically notifies registered contacts in case of an emergency.

[0446] Specific example: If a user enters "I feel like my blood pressure has been high lately," the device sends this information to the server, which then generates appropriate advice based on that information and returns it to the device for display to the user.

[0447] 4. Functions of communication means

[0448] The communication method enables efficient data sharing between the terminal and the server. This communication is bidirectional and designed to ensure that user input and server notifications are received without delay.

[0449] As described above, this system provides an environment where elderly people can live their daily lives with peace of mind and without isolation. By combining a unique conversational experience with health management support, it can improve the quality of life for users while reducing the burden of monitoring.

[0450] The following describes the processing flow.

[0451] Step 1:

[0452] Users enter profile and health information through their devices. The devices then transmit this data to the server in real time.

[0453] Step 2:

[0454] The server stores the received user data in a database and creates individual profiles. This enables the provision of personalized services.

[0455] Step 3:

[0456] The user instructs the device to start a conversation. The device sends this request to the server and requests a topic for the conversation.

[0457] Step 4:

[0458] The server selects relevant topics based on the user's age and preferences. The dialogue engine then generates a conversation script using the selected topics.

[0459] Step 5:

[0460] The server sends the generated conversation script to the terminal. The terminal then presents this to the user as audio or text.

[0461] Step 6:

[0462] Users input or periodically update their health information daily through their device. The device sends this information to a server, which updates the health database.

[0463] Step 7:

[0464] The server analyzes the updated health data and creates notifications to provide users with warnings and health advice as needed.

[0465] Step 8:

[0466] The device receives notifications from the server and issues an alarm to the user at the appropriate time, either visually or audibly.

[0467] Step 9:

[0468] If a user becomes aware of an abnormal health condition, they enter the emergency situation into the device. The device immediately sends this information to the server.

[0469] Step 10:

[0470] Based on the abnormal information, the server automatically sends notifications to registered emergency contacts (family members or medical institutions) and takes measures to ensure the user's safety.

[0471] (Example 1)

[0472] 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."

[0473] There is a need for digital companions to prevent social isolation and deterioration of health among the elderly, and to enable them to live their daily lives with peace of mind. However, conventional technology makes it difficult to provide personalized support that meets the individual needs of each elderly person.

[0474] 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.

[0475] In this invention, the server includes information storage means for collecting and managing user attribute information, dialogue generation means for generating dialogues based on user input using natural language processing, and health monitoring means for monitoring the user's health status and generating warnings when abnormalities occur. This enables elderly people to receive individually personalized dialogues and health management support, leading to a higher quality of life and a more secure lifestyle.

[0476] "Information storage means" refers to a function for safely and efficiently collecting and managing user attribute information.

[0477] A "dialogue generation means" is a mechanism that uses natural language processing to automatically generate appropriate dialogue based on user input.

[0478] A "health monitoring system" is a technology that continuously observes the user's health status and quickly generates a warning when an abnormality occurs.

[0479] "Information transmission means" refers to communication technologies used to effectively send notifications and warnings to users.

[0480] A "content delivery method" is a system that uses information generation algorithms to provide users with personalized information.

[0481] The "dialogue topic generation method" is a function that automatically generates themes related to specific eras, tailored to the user's generation.

[0482] An "automatic notification system" is a function that automatically sends notifications to pre-registered emergency contacts when an abnormal situation occurs.

[0483] In implementing this invention, the system mainly consists of three components: a server, a terminal, and a user. The role of each component is described in detail below.

[0484] The server is primarily configured as an information storage system, aggregating and securely managing user attribute information. This utilizes general-purpose database software, on which personalized information is continuously updated. Furthermore, the server implements a dialogue generation system, leveraging natural language processing technology to analyze user input and generate appropriate dialogue. This process employs advanced analytical algorithms using generative AI models. In addition, the server monitors user health information, acting as a health monitoring tool and generating warnings if abnormalities are detected. This enables real-time monitoring of health status.

[0485] The terminal functions as a means of information transmission, effectively conveying notifications and warnings sent from the server to the user. The terminal also displays personalized content received from the server through a content delivery system. Users can input attribute information and record daily health information via the terminal. For example, if a user measures their blood pressure or body temperature and inputs that data into the terminal, the server can use it to analyze their health status and generate health advice as needed.

[0486] For example, if a user enters "I want to know about old movies," the server will retrieve data on movies popular during that era from its database based on the user's attribute information. The server can then use a generative AI model to generate trivia and interesting topics about the movies and provide them to the user through the terminal. An example of a prompt in this case would be, "If an elderly person says they want to talk about old movies, please generate information and trivia about those movies."

[0487] By using a system configured in this way, it can serve as a digital companion, enabling elderly people to live safely and securely without becoming isolated.

[0488] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0489] Step 1:

[0490] Users input attribute and health information through a terminal. The terminal then sends the entered data to the server. Specifically, the user physically uses the terminal's interface to input the necessary information. The input data on the server includes age and current health status, and this becomes the output stored in the server's database.

[0491] Step 2:

[0492] The server securely records the received attribute information in the database using an information storage mechanism. Data processing involves normalizing the information and storing it in the database in a consistent format. The output obtained during this process is a record of the updated attribute information.

[0493] Step 3:

[0494] The user enters a dialogue request via a terminal. The terminal sends this input to the server. For example, the user might request, "Please tell me about classic movies." The server's input includes this request text.

[0495] Step 4:

[0496] The server uses natural language processing technology to analyze user requests. A generative AI model is used to generate appropriate dialogue topics. The prompt used is: "If an elderly person says they want to talk about old movies, generate information and trivia about those movies." The output is specific answers and information for the user.

[0497] Step 5:

[0498] The generated content is sent from the server to the terminal. The terminal then provides the received information to the user, either through display or audio. As a concrete example, anecdotes about a movie are displayed on the terminal's screen. The server's output constitutes the provision of information to the user.

[0499] Step 6:

[0500] The device continuously collects the user's health information and sends it to the server. The server uses this information to perform health monitoring and generates warnings if any abnormalities are detected. Health information inputs include, for example, daily body temperature and blood pressure data, while outputs include health status assessments and warning notifications.

[0501] This system allows users to receive personalized conversations and health management services tailored to their individual needs.

[0502] (Application Example 1)

[0503] 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."

[0504] To ensure that elderly people do not become isolated and can live their daily lives with peace of mind, they need daily health management and emotional support through appropriate dialogue. However, conventional systems have difficulty responding flexibly to the individual circumstances of elderly people, and there is a lack of means to understand and manage specific changes in their health status and daily life activities. In particular, there is a need for reminder functions to maintain a healthy lifestyle and rapid response in emergencies.

[0505] 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.

[0506] In this invention, the server includes information recording means for collecting and managing personal data of elderly users, dialogue generation means for generating dialogues based on input from elderly users using natural language processing technology, and health monitoring means for monitoring the health information of elderly users and generating warnings in the event of abnormalities. This enables elderly people to check their daily health status and receive continuous support in their daily lives. Furthermore, by using a time management function tailored to individual users, it is possible to support the maintenance of healthy lifestyle habits and respond quickly to emergencies.

[0507] "Information recording means" refers to a device or method for securely collecting, managing, and storing information concerning an individual's age and health.

[0508] A "dialogue generation means" is a mechanism that uses natural language processing technology to generate human-to-human dialogue based on input speech or text.

[0509] A "health monitoring device" is a device or system that has the function of checking the health status of individual elderly people in real time and issuing a warning if an abnormality is detected.

[0510] A "means of communication" refers to a communication system that transmits necessary notifications and warnings to users without delay.

[0511] "Time management tools" refer to functions and devices that track the actions of elderly people and manage their daily activities by providing health checks and reminders.

[0512] A "generation method" is a mechanism for automatically generating conversation topics related to a specific era, tailored to the user's age group.

[0513] An "automatic notification system" is a device or technology that automatically sends notifications to pre-registered contacts when an abnormal situation occurs.

[0514] The system implementing this invention is a digital companion system that combines functions to support both personal health information and dialogue in order to improve the quality of life for the elderly. The server is operated by incorporating information recording means, dialogue generation means, health monitoring means, communication means, time management means, generation means, and automatic notification means.

[0515] The server first uses information recording means to securely collect and store personal data of elderly individuals. This includes data on age and health. The collected information is efficiently managed using a database management system (e.g., Firebase or AWS DynamoDB).

[0516] Dialogue generation utilizes natural language processing (NLP) technology, with the server employing NLP libraries (e.g., spaCy and NLTK) to analyze user voice or text input. This process generates conversation topics and appropriate health advice tailored to the user's age group, which are then communicated to the user along with reminders.

[0517] Health monitoring is achieved by collecting daily health data from sensors built into the device (e.g., pedometer, blood pressure measurement function). The server analyzes this information and sends a warning to the user via a contact method if an abnormality is detected in real time. In addition, in the event of an abnormality, an automatic notification system is used to immediately notify pre-registered emergency contacts.

[0518] For example, if an elderly person enters "I'm not feeling well today," the server immediately analyzes their health data, identifies potential contributing patterns, and displays suggestions for improvement on their device. Furthermore, for regular medication times, the system uses time management tools to automatically send reminders, helping elderly people avoid forgetting to take their medication.

[0519] By incorporating generative AI models, the accuracy of dialogue and health management is improved. An example of a prompt is, "Design a dialogue function for a smartphone app that provides real-time information necessary for seniors to live safely and healthily." This enables a personalized dialogue experience for each user, improving their quality of life.

[0520] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0521] Step 1:

[0522] Users input their health status and requests into the device via voice or text. This input is converted into text data using the device's built-in speech recognition software. The resulting text data is then sent to the server.

[0523] Step 2:

[0524] The server analyzes the received text data using natural language processing libraries (e.g., spaCy or NLTK). Through this analysis, it understands the user's intent and interests and generates the necessary dialogue content. Generative AI models may also be used to improve the understanding of the input data. At this stage, the generated dialogue topics and health information are selected.

[0525] Step 3:

[0526] The server retrieves past health data related to the user from a personal database. It uses database systems such as Firebase or AWS DynamoDB to search and extract the corresponding data. This prepares the server to suggest appropriate health advice and lifestyle improvements to the user.

[0527] Step 4:

[0528] Based on the analysis results, the server generates user-specific conversations and health notifications. The generated content includes age-appropriate topics and health advice, which are then converted into audio and notification formats.

[0529] Step 5:

[0530] The server sends generated conversations and health advice to the device via a communication method. The device presents this to the user as text or voice notifications. Text-to-speech functionality may be used for voice notifications.

[0531] Step 6:

[0532] Users receive information provided through their devices and use it to help with their daily activities and health management. For example, by setting and utilizing reminders based on time management methods, such as taking medication or going for a walk, they can lead a healthier life.

[0533] Step 7:

[0534] If an anomaly is detected, the server will use an automated notification system to send information to emergency contacts. If an emergency response is necessary, prompt action will be taken to ensure the safety of the elderly.

[0535] 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.

[0536] This invention relates to a digital companion system for the elderly that incorporates an emotion engine to recognize user emotions and provide dialogue and services tailored to individual needs. The system consists of a server, a terminal, and a user, and aims to enrich the user's life and improve their health management.

[0537] 1. Implementation of the emotion engine

[0538] The server uses an emotion engine to analyze the user's emotional state from their voice and text. This analysis includes elements such as voice tone, text content, and facial recognition (if applicable). The device accepts voice or camera input as needed to provide this information to the server.

[0539] 2. Adjusting dialogue based on emotions

[0540] Based on the results of sentiment analysis, the server generates conversations that match the user's intentions and mental state. If it determines that the user is experiencing stress, it adjusts the conversation content and provides relaxing topics and encouraging words.

[0541] Specific example: If a user inputs "I haven't been sleeping well lately" in a depressed tone, the server, through its emotion engine, recognizes that the user is experiencing stress related to insomnia and suggests breathing exercises and music to help them relax.

[0542] 3. Customization of content delivery

[0543] The device receives instructions from the server and provides appropriate content according to the user's emotional state. This includes relaxation music, meditation guides, or video clips on stress reduction.

[0544] Specific example: When a user types "I want a change of pace," the device plays hit songs from the user's preferred era or videos related to their hobbies, based on suggestions from the server.

[0545] This system will reduce the mental burden caused by loneliness in the daily lives of the elderly, enabling them to lead richer and healthier lives. By using an emotion engine, flexible services tailored to the individual needs of each user will be provided, contributing to an improved quality of life.

[0546] The following describes the processing flow.

[0547] Step 1:

[0548] The user initiates a daily conversation through the device by inputting voice or text. The device receives this input.

[0549] Step 2:

[0550] The device sends the acquired voice or text data to the server for sentiment analysis. This includes the user's voice tone and the words they use.

[0551] Step 3:

[0552] The server uses an emotion engine to analyze the user's emotional state from their input. For example, if the tone of voice is subdued, the server will determine that the user is sad.

[0553] Step 4:

[0554] Based on the emotional analysis, the server generates a conversation script tailored to the user's mental state. If it determines that the user is stressed, it selects a relaxing topic.

[0555] Step 5:

[0556] The server sends the generated conversation script to the terminal. The terminal presents the received script to the user in either audio or text format.

[0557] Step 6:

[0558] The system continues the conversation or asks further questions based on the user's input from their device. The user's responses are then sent back to the server via the device.

[0559] Step 7:

[0560] The server continuously analyzes user responses and re-evaluates the emotional state as needed. It then dynamically adjusts and resends the conversation content.

[0561] Step 8:

[0562] If the user's emotions are unstable, the server will decide to provide relaxation content or stress-reducing advice. It may also suggest music or meditation guides.

[0563] Step 9:

[0564] The device plays appropriate content for the user according to instructions from the server. The user can then experience mental relaxation through this content.

[0565] (Example 2)

[0566] 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."

[0567] Elderly users are prone to feelings of loneliness and stress in their daily lives, which can negatively impact their physical and mental health. However, conventional systems have struggled to adequately recognize users' emotional states and provide services and content tailored to their individual needs. Furthermore, there is a lack of systems that can continuously monitor the health status of elderly users and respond quickly in the event of an abnormality.

[0568] 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.

[0569] In this invention, the server includes emotion analysis means that analyzes voice tone and text content to recognize the user's emotions, content provision means that provides optimal content based on the emotional state of the elderly user, and health monitoring means that monitors the health status of the elderly user and generates a warning in case of abnormality. As a result, the elderly user can enjoy appropriate dialogue and content based on their emotions, and can receive prompt and appropriate responses if there is a change in their health status.

[0570] "Information management means" refers to methods or devices for securely collecting and managing personal information of elderly users.

[0571] "Dialogue generation means" refers to a method or apparatus for generating dialogue based on input from elderly users using natural language processing technology.

[0572] "Emotional analysis means" refers to a method or device for recognizing a user's emotions by analyzing their voice tone or text content.

[0573] "Content delivery means" refers to a method or device for selecting and providing optimal content based on the emotional state of elderly users.

[0574] "Health monitoring means" refers to a method or device for continuously monitoring the health status of elderly users and generating warnings in the event of abnormalities.

[0575] "Communication means" refers to methods or devices for conveying notifications or warnings to elderly users.

[0576] This invention is a digital companion system for the elderly that incorporates an emotion engine to recognize the user's emotions and provide dialogue and services tailored to their individual needs. The system consists of a server, a terminal, and a user, and aims to improve the quality of life for the elderly.

[0577] The server features an emotion engine that utilizes a generative AI model to analyze voice tone and text content to recognize the user's emotions. This involves using voice data analysis and natural language processing technologies to extract voice tone and estimate emotions. The terminal uses hardware such as a microphone and camera to obtain voice and video input from the user and transmit this to the server.

[0578] When a user speaks to the system or gives instructions, the terminal receives that information and sends it to the server in real time. For example, if a user inputs "I'm a little tired," the server recognizes that emotion and provides music or meditation guidance to help them relax.

[0579] Examples of specific prompts include, "I want to create a system that identifies emotions from user speech and suggests relaxing content," and "Please write a program that analyzes emotional states from voice tone and text and adjusts the dialogue accordingly."

[0580] The terminal receives the results of emotion analysis from the server and presents appropriate dialogue and content to the elderly. This allows users to receive services tailored to their individual needs, contributing to reducing feelings of loneliness and maintaining their physical and mental health.

[0581] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0582] Step 1:

[0583] The device receives voice input and camera footage from the user. Input data includes the user's spoken words and facial expressions. The device converts these inputs into digital signals and formats them for transmission to the server. Natural user interaction is crucial in this step.

[0584] Step 2:

[0585] The server analyzes the audio and video data received from the terminal. Using an emotion engine, the server analyzes the voice tone and text content to estimate the user's emotional state. Specific operations include feature extraction from audio data, voice tone analysis, and facial expression recognition from video data. The output generates data related to the user's emotional state.

[0586] Step 3:

[0587] The server uses a generative AI model to generate conversational content tailored to the user, based on the results of the emotion analysis. The input used is the result of the emotion analysis. Based on this analysis, the server creates conversational content that promotes relaxation and a sense of security. For example, if the user is feeling stressed, it will generate advice and topics to help them relax.

[0588] Step 4:

[0589] The server selects the most appropriate content based on the user's emotional state and sends it to the device. Input includes data on the user's preferences, along with the generated dialogue. The server selects content that meets the user's needs, such as relaxation music or meditation guides. The selected content data is sent to the device as output.

[0590] Step 5:

[0591] The device provides the user with content received from the server. The device can play music or provide meditation guides. As output, the user can view or listen to relaxing content. Specifically, audio and video are output through speakers or a display.

[0592] This series of processes allows the system to provide individually customized dialogue and content while taking into account the emotional state of the elderly person.

[0593] (Application Example 2)

[0594] 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."

[0595] Loneliness and stress experienced by older adults in their daily lives are problems that negatively impact their quality of life and health. Furthermore, as older adults experience increased physical changes and health risks, regular health monitoring and emergency response are essential. In addition, a lack of skills to appropriately recognize emotional changes and provide corresponding support is also a challenge.

[0596] 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.

[0597] In this invention, the server includes information storage means for collecting and managing personal data of elderly users, conversation generation means for generating dialogue using natural language processing technology, health observation means for monitoring the health information of elderly users, information communication means for transmitting information to elderly users, recognition means for recognizing emotions, and emotion adaptation means for adjusting dialogue based on emotions. This enables accurate understanding of the emotional state of elderly people, the provision of appropriate dialogue, and the maintenance of health and emergency response.

[0598] "Information storage means" refers to technologies and devices for efficiently collecting and managing personal data of elderly users.

[0599] "Conversation generation means" refers to a technology that uses natural language processing to automatically generate dialogues based on input from elderly users.

[0600] "Health monitoring means" refers to methods and devices for regularly monitoring the health information of elderly users and evaluating their health status.

[0601] "Information and communication means" refers to communication technologies and devices used to transmit information such as notifications and warnings to elderly users.

[0602] "Recognition means" refers to technology for analyzing and recognizing the emotions of elderly users through their voice, facial expressions, and text input.

[0603] "Emotional adaptation means" refers to technology that appropriately adjusts the content of a conversation based on recognized emotions, thereby providing a service tailored to the user.

[0604] This invention is a digital companion system designed to enrich the lives of elderly users and support their health management. The system includes means for information storage, conversation generation, health observation, information communication, recognition, and emotional adaptation.

[0605] First, the device collects voice and text data from elderly users. Voice data is captured by a microphone, and text data is converted using speech recognition technology. This data is sent to a server and managed as personal data of elderly users by an information storage system.

[0606] Next, using natural language processing technology, the server generates a dialogue based on the acquired data through a conversation generation mechanism. Conversation topics appropriate to the age group of the elderly users are selected, and appropriate responses are formed. Specifically, the audio data is processed using the Google Cloud Speech-to-Text API, and the dialogue is generated using a natural language processing library.

[0607] In addition, the server uses health monitoring devices to monitor health-related information sent from terminals, and if an abnormality is detected, it sends a notification to elderly users or emergency contacts via information and communication devices.

[0608] Furthermore, the server uses recognition mechanisms to analyze emotions based on audio and facial expression data acquired from cameras and microphones. Technologies such as OpenCV are utilized to implement the ability to read emotions from facial expressions. Based on the analyzed emotions, emotion adaptation mechanisms adjust the dialogue content to provide appropriate conversations and content.

[0609] As a concrete example, in the morning, the device asks, "Shall we check today's schedule?" and the user replies, "I'm not feeling very well today." The server recognizes the user's tired facial expression and tone of voice, sensing stress and fatigue. Based on this, the server suggests to the user, "Let's take a short break. Shall I suggest some relaxing music or stretching?"

[0610] An example of a prompt for a generative AI model is the text: "When the user says they are tired with a melancholic expression, please come up with a conversation to cheer them up. The user is a woman in her 70s who likes music."

[0611] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0612] Step 1:

[0613] The device collects audio and video data from the user using a microphone and camera. This data is input as the user's speech and facial expressions. Audio data is processed using signal processing technology to remove noise and output as a clean audio file. Video data is processed using image processing technology to extract specific frames and output as an image containing the user's facial expression information.

[0614] Step 2:

[0615] The device applies speech recognition technology to convert the collected audio data into text. The Google Cloud Speech-to-Text API receives the audio data as input and outputs the corresponding text data. This text data is used in the next step as the user's spoken content.

[0616] Step 3:

[0617] The server processes the received text data and facial image data through recognition tools to analyze the user's emotions. Text data is analyzed using natural language processing techniques, and facial image data is processed using a face recognition algorithm based on OpenCV. This data is output as information about the emotional state and passed to the emotion adaptation tool.

[0618] Step 4:

[0619] The server receives the analyzed emotional state as input and uses a conversation generation tool to form an appropriate dialogue. Using a natural language processing library, it generates a dialogue flow based on the emotional state and outputs the result as text data. This output includes suggestions to promote relaxation and conversational content to encourage the user.

[0620] Step 5:

[0621] The device converts the outputted dialogue text into speech using speech synthesis technology. The generated speech is played through the speaker and delivered to the user. This allows the user to receive the response as speech, thus completing the dialogue.

[0622] Step 6:

[0623] Additionally, the server monitors the user's health status using health monitoring devices and sends necessary notifications via information and communication devices if an abnormality is detected. Sensor data is collected as input, and if it exceeds pre-set health status parameters, an alarm is generated and output as a notification.

[0624] 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.

[0625] 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.

[0626] 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.

[0627] [Fourth Embodiment]

[0628] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0629] 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.

[0630] 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).

[0631] 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.

[0632] 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.

[0633] 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).

[0634] 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.

[0635] 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.

[0636] 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.

[0637] 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.

[0638] 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.

[0639] 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.

[0640] 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".

[0641] This invention relates to a digital companion system for improving the quality of life for the elderly. The system consists of a server, a terminal, and a user, and provides individually personalized conversational and health management services.

[0642] 1. Details of the database method

[0643] The server has a database that securely stores and manages personal data provided by users. This database includes data on age, health information, and preferences, and the data can be updated at any time.

[0644] 2. Application of Natural Language Processing Techniques

[0645] The server uses natural language processing technology to analyze the voice or text input by the user. This generates conversations about nostalgic topics and daily events that are of interest to the elderly, and provides them to the device.

[0646] Specific example: If a user types, "I want to talk about movies I used to watch a lot," the server retrieves information on popular movies from its database that match the user's age group. The dialogue engine then generates anecdotes and trivia about those movies and sends them to the terminal.

[0647] 3. Explanation of health management methods

[0648] The device collects the user's daily health information and sends it to the server. The server uses this information to analyze the user's health status and provides health guidance and alerts as needed. Furthermore, it has a system that automatically notifies registered contacts in case of an emergency.

[0649] Specific example: If a user enters "I feel like my blood pressure has been high lately," the device sends this information to the server, which then generates appropriate advice based on that information and returns it to the device for display to the user.

[0650] 4. Functions of communication means

[0651] The communication method enables efficient data sharing between the terminal and the server. This communication is bidirectional and designed to ensure that user input and server notifications are received without delay.

[0652] As described above, this system provides an environment where elderly people can live their daily lives with peace of mind and without isolation. By combining a unique conversational experience with health management support, it can improve the quality of life for users while reducing the burden of monitoring.

[0653] The following describes the processing flow.

[0654] Step 1:

[0655] Users enter profile and health information through their devices. The devices then transmit this data to the server in real time.

[0656] Step 2:

[0657] The server stores the received user data in a database and creates individual profiles. This enables the provision of personalized services.

[0658] Step 3:

[0659] The user instructs the device to start a conversation. The device sends this request to the server and requests a topic for the conversation.

[0660] Step 4:

[0661] The server selects relevant topics based on the user's age and preferences. The dialogue engine then generates a conversation script using the selected topics.

[0662] Step 5:

[0663] The server sends the generated conversation script to the terminal. The terminal then presents this to the user as audio or text.

[0664] Step 6:

[0665] Users input or periodically update their health information daily through their device. The device sends this information to a server, which updates the health database.

[0666] Step 7:

[0667] The server analyzes the updated health data and creates notifications to provide users with warnings and health advice as needed.

[0668] Step 8:

[0669] The device receives notifications from the server and issues an alarm to the user at the appropriate time, either visually or audibly.

[0670] Step 9:

[0671] If a user becomes aware of an abnormal health condition, they enter the emergency situation into the device. The device immediately sends this information to the server.

[0672] Step 10:

[0673] Based on the abnormal information, the server automatically sends notifications to registered emergency contacts (family members or medical institutions) and takes measures to ensure the user's safety.

[0674] (Example 1)

[0675] 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".

[0676] There is a need for digital companions to prevent social isolation and deterioration of health among the elderly, and to enable them to live their daily lives with peace of mind. However, conventional technology makes it difficult to provide personalized support that meets the individual needs of each elderly person.

[0677] 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.

[0678] In this invention, the server includes information storage means for collecting and managing user attribute information, dialogue generation means for generating dialogues based on user input using natural language processing, and health monitoring means for monitoring the user's health status and generating warnings when abnormalities occur. This enables elderly people to receive individually personalized dialogues and health management support, leading to a higher quality of life and a more secure lifestyle.

[0679] "Information storage means" refers to a function for safely and efficiently collecting and managing user attribute information.

[0680] A "dialogue generation means" is a mechanism that uses natural language processing to automatically generate appropriate dialogue based on user input.

[0681] A "health monitoring system" is a technology that continuously observes the user's health status and quickly generates a warning when an abnormality occurs.

[0682] "Information transmission means" refers to communication technologies used to effectively send notifications and warnings to users.

[0683] A "content delivery method" is a system that uses information generation algorithms to provide users with personalized information.

[0684] The "dialogue topic generation method" is a function that automatically generates themes related to specific eras, tailored to the user's generation.

[0685] An "automatic notification system" is a function that automatically sends notifications to pre-registered emergency contacts when an abnormal situation occurs.

[0686] In implementing this invention, the system mainly consists of three components: a server, a terminal, and a user. The role of each component is described in detail below.

[0687] The server is primarily configured as an information storage system, aggregating and securely managing user attribute information. This utilizes general-purpose database software, on which personalized information is continuously updated. Furthermore, the server implements a dialogue generation system, leveraging natural language processing technology to analyze user input and generate appropriate dialogue. This process employs advanced analytical algorithms using generative AI models. In addition, the server monitors user health information, acting as a health monitoring tool and generating warnings if abnormalities are detected. This enables real-time monitoring of health status.

[0688] The terminal functions as a means of information transmission, effectively conveying notifications and warnings sent from the server to the user. The terminal also displays personalized content received from the server through a content delivery system. Users can input attribute information and record daily health information via the terminal. For example, if a user measures their blood pressure or body temperature and inputs that data into the terminal, the server can use it to analyze their health status and generate health advice as needed.

[0689] For example, if a user enters "I want to know about old movies," the server will retrieve data on movies popular during that era from its database based on the user's attribute information. The server can then use a generative AI model to generate trivia and interesting topics about the movies and provide them to the user through the terminal. An example of a prompt in this case would be, "If an elderly person says they want to talk about old movies, please generate information and trivia about those movies."

[0690] By using a system configured in this way, it can serve as a digital companion, enabling elderly people to live safely and securely without becoming isolated.

[0691] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0692] Step 1:

[0693] Users input attribute and health information through a terminal. The terminal then sends the entered data to the server. Specifically, the user physically uses the terminal's interface to input the necessary information. The input data on the server includes age and current health status, and this becomes the output stored in the server's database.

[0694] Step 2:

[0695] The server securely records the received attribute information in the database using an information storage mechanism. Data processing involves normalizing the information and storing it in the database in a consistent format. The output obtained during this process is a record of the updated attribute information.

[0696] Step 3:

[0697] The user enters a dialogue request via a terminal. The terminal sends this input to the server. For example, the user might request, "Please tell me about classic movies." The server's input includes this request text.

[0698] Step 4:

[0699] The server uses natural language processing technology to analyze user requests. A generative AI model is used to generate appropriate dialogue topics. The prompt used is: "If an elderly person says they want to talk about old movies, generate information and trivia about those movies." The output is specific answers and information for the user.

[0700] Step 5:

[0701] The generated content is sent from the server to the terminal. The terminal then provides the received information to the user, either through display or audio. As a concrete example, anecdotes about a movie are displayed on the terminal's screen. The server's output constitutes the provision of information to the user.

[0702] Step 6:

[0703] The device continuously collects the user's health information and sends it to the server. The server uses this information to perform health monitoring and generates warnings if any abnormalities are detected. Health information inputs include, for example, daily body temperature and blood pressure data, while outputs include health status assessments and warning notifications.

[0704] This system allows users to receive personalized conversations and health management services tailored to their individual needs.

[0705] (Application Example 1)

[0706] 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".

[0707] To ensure that elderly people do not become isolated and can live their daily lives with peace of mind, they need daily health management and emotional support through appropriate dialogue. However, conventional systems have difficulty responding flexibly to the individual circumstances of elderly people, and there is a lack of means to understand and manage specific changes in their health status and daily life activities. In particular, there is a need for reminder functions to maintain a healthy lifestyle and rapid response in emergencies.

[0708] 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.

[0709] In this invention, the server includes information recording means for collecting and managing personal data of elderly users, dialogue generation means for generating dialogues based on input from elderly users using natural language processing technology, and health monitoring means for monitoring the health information of elderly users and generating warnings in the event of abnormalities. This enables elderly people to check their daily health status and receive continuous support in their daily lives. Furthermore, by using a time management function tailored to individual users, it is possible to support the maintenance of healthy lifestyle habits and respond quickly to emergencies.

[0710] "Information recording means" refers to a device or method for securely collecting, managing, and storing information concerning an individual's age and health.

[0711] A "dialogue generation means" is a mechanism that uses natural language processing technology to generate human-to-human dialogue based on input speech or text.

[0712] A "health monitoring device" is a device or system that has the function of checking the health status of individual elderly people in real time and issuing a warning if an abnormality is detected.

[0713] A "means of communication" refers to a communication system that transmits necessary notifications and warnings to users without delay.

[0714] "Time management tools" refer to functions and devices that track the actions of elderly people and manage their daily activities by providing health checks and reminders.

[0715] A "generation method" is a mechanism for automatically generating conversation topics related to a specific era, tailored to the user's age group.

[0716] An "automatic notification system" is a device or technology that automatically sends notifications to pre-registered contacts when an abnormal situation occurs.

[0717] The system implementing this invention is a digital companion system that combines functions to support both personal health information and dialogue in order to improve the quality of life for the elderly. The server is operated by incorporating information recording means, dialogue generation means, health monitoring means, communication means, time management means, generation means, and automatic notification means.

[0718] The server first uses information recording means to securely collect and store personal data of elderly individuals. This includes data on age and health. The collected information is efficiently managed using a database management system (e.g., Firebase or AWS DynamoDB).

[0719] Dialogue generation utilizes natural language processing (NLP) technology, with the server employing NLP libraries (e.g., spaCy and NLTK) to analyze user voice or text input. This process generates conversation topics and appropriate health advice tailored to the user's age group, which are then communicated to the user along with reminders.

[0720] Health monitoring is achieved by collecting daily health data from sensors built into the device (e.g., pedometer, blood pressure measurement function). The server analyzes this information and sends a warning to the user via a contact method if an abnormality is detected in real time. In addition, in the event of an abnormality, an automatic notification system is used to immediately notify pre-registered emergency contacts.

[0721] For example, if an elderly person enters "I'm not feeling well today," the server immediately analyzes their health data, identifies potential contributing patterns, and displays suggestions for improvement on their device. Furthermore, for regular medication times, the system uses time management tools to automatically send reminders, helping elderly people avoid forgetting to take their medication.

[0722] By incorporating generative AI models, the accuracy of dialogue and health management is improved. An example of a prompt is, "Design a dialogue function for a smartphone app that provides real-time information necessary for seniors to live safely and healthily." This enables a personalized dialogue experience for each user, improving their quality of life.

[0723] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0724] Step 1:

[0725] Users input their health status and requests into the device via voice or text. This input is converted into text data using the device's built-in speech recognition software. The resulting text data is then sent to the server.

[0726] Step 2:

[0727] The server analyzes the received text data using natural language processing libraries (e.g., spaCy or NLTK). Through this analysis, it understands the user's intent and interests and generates the necessary dialogue content. Generative AI models may also be used to improve the understanding of the input data. At this stage, the generated dialogue topics and health information are selected.

[0728] Step 3:

[0729] The server retrieves past health data related to the user from a personal database. It uses database systems such as Firebase or AWS DynamoDB to search and extract the corresponding data. This prepares the server to suggest appropriate health advice and lifestyle improvements to the user.

[0730] Step 4:

[0731] Based on the analysis results, the server generates user-specific conversations and health notifications. The generated content includes age-appropriate topics and health advice, which are then converted into audio and notification formats.

[0732] Step 5:

[0733] The server sends generated conversations and health advice to the device via a communication method. The device presents this to the user as text or voice notifications. Text-to-speech functionality may be used for voice notifications.

[0734] Step 6:

[0735] Users receive information provided through their devices and use it to help with their daily activities and health management. For example, by setting and utilizing reminders based on time management methods, such as taking medication or going for a walk, they can lead a healthier life.

[0736] Step 7:

[0737] If an anomaly is detected, the server will use an automated notification system to send information to emergency contacts. If an emergency response is necessary, prompt action will be taken to ensure the safety of the elderly.

[0738] 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.

[0739] This invention relates to a digital companion system for the elderly that incorporates an emotion engine to recognize user emotions and provide dialogue and services tailored to individual needs. The system consists of a server, a terminal, and a user, and aims to enrich the user's life and improve their health management.

[0740] 1. Implementation of the emotion engine

[0741] The server uses an emotion engine to analyze the user's emotional state from their voice and text. This analysis includes elements such as voice tone, text content, and facial recognition (if applicable). The device accepts voice or camera input as needed to provide this information to the server.

[0742] 2. Adjusting dialogue based on emotions

[0743] Based on the results of sentiment analysis, the server generates conversations that match the user's intentions and mental state. If it determines that the user is experiencing stress, it adjusts the conversation content and provides relaxing topics and encouraging words.

[0744] Specific example: If a user inputs "I haven't been sleeping well lately" in a depressed tone, the server, through its emotion engine, recognizes that the user is experiencing stress related to insomnia and suggests breathing exercises and music to help them relax.

[0745] 3. Customization of content delivery

[0746] The device receives instructions from the server and provides appropriate content according to the user's emotional state. This includes relaxation music, meditation guides, or video clips on stress reduction.

[0747] Specific example: When a user types "I want a change of pace," the device plays hit songs from the user's preferred era or videos related to their hobbies, based on suggestions from the server.

[0748] This system will reduce the mental burden caused by loneliness in the daily lives of the elderly, enabling them to lead richer and healthier lives. By using an emotion engine, flexible services tailored to the individual needs of each user will be provided, contributing to an improved quality of life.

[0749] The following describes the processing flow.

[0750] Step 1:

[0751] The user initiates a daily conversation through the device by inputting voice or text. The device receives this input.

[0752] Step 2:

[0753] The device sends the acquired voice or text data to the server for sentiment analysis. This includes the user's voice tone and the words they use.

[0754] Step 3:

[0755] The server uses an emotion engine to analyze the user's emotional state from their input. For example, if the tone of voice is subdued, the server will determine that the user is sad.

[0756] Step 4:

[0757] Based on the emotional analysis, the server generates a conversation script tailored to the user's mental state. If it determines that the user is stressed, it selects a relaxing topic.

[0758] Step 5:

[0759] The server sends the generated conversation script to the terminal. The terminal presents the received script to the user in either audio or text format.

[0760] Step 6:

[0761] The system continues the conversation or asks further questions based on the user's input from their device. The user's responses are then sent back to the server via the device.

[0762] Step 7:

[0763] The server continuously analyzes user responses and re-evaluates the emotional state as needed. It then dynamically adjusts and resends the conversation content.

[0764] Step 8:

[0765] If the user's emotions are unstable, the server will decide to provide relaxation content or stress-reducing advice. It may also suggest music or meditation guides.

[0766] Step 9:

[0767] The device plays appropriate content for the user according to instructions from the server. The user can then experience mental relaxation through this content.

[0768] (Example 2)

[0769] 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".

[0770] Elderly users are prone to feelings of loneliness and stress in their daily lives, which can negatively impact their physical and mental health. However, conventional systems have struggled to adequately recognize users' emotional states and provide services and content tailored to their individual needs. Furthermore, there is a lack of systems that can continuously monitor the health status of elderly users and respond quickly in the event of an abnormality.

[0771] 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.

[0772] In this invention, the server includes emotion analysis means that analyzes voice tone and text content to recognize the user's emotions, content provision means that provides optimal content based on the emotional state of the elderly user, and health monitoring means that monitors the health status of the elderly user and generates a warning in case of abnormality. As a result, the elderly user can enjoy appropriate dialogue and content based on their emotions, and can receive prompt and appropriate responses if there is a change in their health status.

[0773] "Information management means" refers to methods or devices for securely collecting and managing personal information of elderly users.

[0774] "Dialogue generation means" refers to a method or apparatus for generating dialogue based on input from elderly users using natural language processing technology.

[0775] "Emotional analysis means" refers to a method or device for recognizing a user's emotions by analyzing their voice tone or text content.

[0776] "Content delivery means" refers to a method or device for selecting and providing optimal content based on the emotional state of elderly users.

[0777] "Health monitoring means" refers to a method or device for continuously monitoring the health status of elderly users and generating warnings in the event of abnormalities.

[0778] "Communication means" refers to methods or devices for conveying notifications or warnings to elderly users.

[0779] This invention is a digital companion system for the elderly that incorporates an emotion engine to recognize the user's emotions and provide dialogue and services tailored to their individual needs. The system consists of a server, a terminal, and a user, and aims to improve the quality of life for the elderly.

[0780] The server features an emotion engine that utilizes a generative AI model to analyze voice tone and text content to recognize the user's emotions. This involves using voice data analysis and natural language processing technologies to extract voice tone and estimate emotions. The terminal uses hardware such as a microphone and camera to obtain voice and video input from the user and transmit this to the server.

[0781] When a user speaks to the system or gives instructions, the terminal receives that information and sends it to the server in real time. For example, if a user inputs "I'm a little tired," the server recognizes that emotion and provides music or meditation guidance to help them relax.

[0782] Examples of specific prompts include, "I want to create a system that identifies emotions from user speech and suggests relaxing content," and "Please write a program that analyzes emotional states from voice tone and text and adjusts the dialogue accordingly."

[0783] The terminal receives the results of emotion analysis from the server and presents appropriate dialogue and content to the elderly. This allows users to receive services tailored to their individual needs, contributing to reducing feelings of loneliness and maintaining their physical and mental health.

[0784] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0785] Step 1:

[0786] The device receives voice input and camera footage from the user. Input data includes the user's spoken words and facial expressions. The device converts these inputs into digital signals and formats them for transmission to the server. Natural user interaction is crucial in this step.

[0787] Step 2:

[0788] The server analyzes the audio and video data received from the terminal. Using an emotion engine, the server analyzes the voice tone and text content to estimate the user's emotional state. Specific operations include feature extraction from audio data, voice tone analysis, and facial expression recognition from video data. The output generates data related to the user's emotional state.

[0789] Step 3:

[0790] The server uses a generative AI model to generate conversational content tailored to the user, based on the results of the emotion analysis. The input used is the result of the emotion analysis. Based on this analysis, the server creates conversational content that promotes relaxation and a sense of security. For example, if the user is feeling stressed, it will generate advice and topics to help them relax.

[0791] Step 4:

[0792] The server selects the most appropriate content based on the user's emotional state and sends it to the device. Input includes data on the user's preferences, along with the generated dialogue. The server selects content that meets the user's needs, such as relaxation music or meditation guides. The selected content data is sent to the device as output.

[0793] Step 5:

[0794] The device provides the user with content received from the server. The device can play music or provide meditation guides. As output, the user can view or listen to relaxing content. Specifically, audio and video are output through speakers or a display.

[0795] This series of processes allows the system to provide individually customized dialogue and content while taking into account the emotional state of the elderly person.

[0796] (Application Example 2)

[0797] 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".

[0798] Loneliness and stress experienced by older adults in their daily lives are problems that negatively impact their quality of life and health. Furthermore, as older adults experience increased physical changes and health risks, regular health monitoring and emergency response are essential. In addition, a lack of skills to appropriately recognize emotional changes and provide corresponding support is also a challenge.

[0799] 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.

[0800] In this invention, the server includes information storage means for collecting and managing personal data of elderly users, conversation generation means for generating dialogue using natural language processing technology, health observation means for monitoring the health information of elderly users, information communication means for transmitting information to elderly users, recognition means for recognizing emotions, and emotion adaptation means for adjusting dialogue based on emotions. This enables accurate understanding of the emotional state of elderly people, the provision of appropriate dialogue, and the maintenance of health and emergency response.

[0801] "Information storage means" refers to technologies and devices for efficiently collecting and managing personal data of elderly users.

[0802] "Conversation generation means" refers to a technology that uses natural language processing to automatically generate dialogues based on input from elderly users.

[0803] "Health monitoring means" refers to methods and devices for regularly monitoring the health information of elderly users and evaluating their health status.

[0804] "Information and communication means" refers to communication technologies and devices used to transmit information such as notifications and warnings to elderly users.

[0805] "Recognition means" refers to technology for analyzing and recognizing the emotions of elderly users through their voice, facial expressions, and text input.

[0806] "Emotional adaptation means" refers to technology that appropriately adjusts the content of a conversation based on recognized emotions, thereby providing a service tailored to the user.

[0807] This invention is a digital companion system designed to enrich the lives of elderly users and support their health management. The system includes means for information storage, conversation generation, health observation, information communication, recognition, and emotional adaptation.

[0808] First, the device collects voice and text data from elderly users. Voice data is captured by a microphone, and text data is converted using speech recognition technology. This data is sent to a server and managed as personal data of elderly users by an information storage system.

[0809] Next, using natural language processing technology, the server generates a dialogue based on the acquired data through a conversation generation mechanism. Conversation topics appropriate to the age group of the elderly users are selected, and appropriate responses are formed. Specifically, the audio data is processed using the Google Cloud Speech-to-Text API, and the dialogue is generated using a natural language processing library.

[0810] In addition, the server uses health monitoring devices to monitor health-related information sent from terminals, and if an abnormality is detected, it sends a notification to elderly users or emergency contacts via information and communication devices.

[0811] Furthermore, the server uses recognition mechanisms to analyze emotions based on audio and facial expression data acquired from cameras and microphones. Technologies such as OpenCV are utilized to implement the ability to read emotions from facial expressions. Based on the analyzed emotions, emotion adaptation mechanisms adjust the dialogue content to provide appropriate conversations and content.

[0812] As a concrete example, in the morning, the device asks, "Shall we check today's schedule?" and the user replies, "I'm not feeling very well today." The server recognizes the user's tired facial expression and tone of voice, sensing stress and fatigue. Based on this, the server suggests to the user, "Let's take a short break. Shall I suggest some relaxing music or stretching?"

[0813] An example of a prompt for a generative AI model is the text: "When the user says they are tired with a melancholic expression, please come up with a conversation to cheer them up. The user is a woman in her 70s who likes music."

[0814] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0815] Step 1:

[0816] The device collects audio and video data from the user using a microphone and camera. This data is input as the user's speech and facial expressions. Audio data is processed using signal processing technology to remove noise and output as a clean audio file. Video data is processed using image processing technology to extract specific frames and output as an image containing the user's facial expression information.

[0817] Step 2:

[0818] The device applies speech recognition technology to convert the collected audio data into text. The Google Cloud Speech-to-Text API receives the audio data as input and outputs the corresponding text data. This text data is used in the next step as the user's spoken content.

[0819] Step 3:

[0820] The server processes the received text data and facial image data through recognition tools to analyze the user's emotions. Text data is analyzed using natural language processing techniques, and facial image data is processed using a face recognition algorithm based on OpenCV. This data is output as information about the emotional state and passed to the emotion adaptation tool.

[0821] Step 4:

[0822] The server receives the analyzed emotional state as input and uses a conversation generation tool to form an appropriate dialogue. Using a natural language processing library, it generates a dialogue flow based on the emotional state and outputs the result as text data. This output includes suggestions to promote relaxation and conversational content to encourage the user.

[0823] Step 5:

[0824] The device converts the outputted dialogue text into speech using speech synthesis technology. The generated speech is played through the speaker and delivered to the user. This allows the user to receive the response as speech, thus completing the dialogue.

[0825] Step 6:

[0826] Additionally, the server monitors the user's health status using health monitoring devices and sends necessary notifications via information and communication devices if an abnormality is detected. Sensor data is collected as input, and if it exceeds pre-set health status parameters, an alarm is generated and output as a notification.

[0827] 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.

[0828] 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.

[0829] 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.

[0830] 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.

[0831] 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. In the upper and lower directions of the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. Also, the upper side of the concentric circles is where "pleasant" emotions are located, and the lower side is where "unpleasant" emotions are located. In this way, 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.

[0832] 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.

[0833] 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.

[0834] 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.

[0835] 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."

[0836] 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.

[0837] 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.

[0838] 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.

[0839] 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.

[0840] 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.

[0841] 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.

[0842] 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.

[0843] 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.

[0844] 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.

[0845] 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.

[0846] 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.

[0847] 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.

[0848] The following is further disclosed regarding the embodiments described above.

[0849] (Claim 1)

[0850] A database means for collecting and managing personal data of elderly users,

[0851] A dialogue engine that generates dialogues based on input from elderly users using natural language processing technology,

[0852] A health management system that monitors the health information of elderly users and generates warnings when abnormalities occur,

[0853] A means of communication to send notifications and warnings to elderly users,

[0854] A system that includes this.

[0855] (Claim 2)

[0856] The system according to claim 1, further comprising means for generating conversation topics related to a specific era corresponding to the age group of elderly users.

[0857] (Claim 3)

[0858] The system according to claim 1, further comprising means for automatically sending a notification to a pre-registered emergency contact in the event of an abnormal situation involving an elderly user.

[0859] "Example 1"

[0860] (Claim 1)

[0861] Information storage means for collecting and managing user attribute information,

[0862] A dialogue generation means that generates a dialogue based on user input using natural language processing,

[0863] A health monitoring system that monitors the user's health status and generates a warning when an abnormality occurs,

[0864] A means of transmitting information to send notifications and warnings to users,

[0865] A content delivery method that generates personalized content using an information generation algorithm,

[0866] A system that includes this.

[0867] (Claim 2)

[0868] The system according to claim 1, further comprising a dialogue topic generation means for generating conversation topics related to a specific era corresponding to the user's generation.

[0869] (Claim 3)

[0870] The system according to claim 1, further comprising an automatic notification means for automatically sending a notification to a pre-registered emergency contact when an abnormal situation occurs with a user.

[0871] "Application Example 1"

[0872] (Claim 1)

[0873] Information recording means for collecting and managing personal data of elderly users,

[0874] A dialogue generation means that generates dialogues based on input from elderly users using natural language processing technology,

[0875] A health monitoring system that monitors the health information of elderly users and generates warnings when abnormalities occur,

[0876] A means of communication to send notifications and warnings to elderly users,

[0877] A time management system that tracks the behavior of elderly users and can issue health checks and reminders,

[0878] A system that includes this.

[0879] (Claim 2)

[0880] The system according to claim 1, further comprising a generation means for generating conversation topics related to a specific era that corresponds to the age group of elderly users.

[0881] (Claim 3)

[0882] The system according to claim 1, further comprising an automatic notification means for automatically sending a notification to a pre-registered emergency contact in the event of an emergency involving an elderly user.

[0883] "Example 2 of combining an emotion engine"

[0884] (Claim 1)

[0885] Information management means for collecting and managing personal information of elderly users,

[0886] A dialogue generation means that generates dialogues based on input from elderly users using natural language processing technology,

[0887] An emotion analysis method that analyzes voice tone and text content to recognize the user's emotions,

[0888] A content delivery method that provides optimal content based on the emotional state of elderly users,

[0889] A health monitoring system that monitors the health status of elderly users and generates warnings when abnormalities occur,

[0890] Communication methods for conveying notifications and warnings to elderly users,

[0891] A system that includes this.

[0892] (Claim 2)

[0893] The system according to claim 1, further comprising means for generating conversation topics related to a specific era corresponding to the age group of elderly users.

[0894] (Claim 3)

[0895] The system according to claim 1, further comprising means for automatically sending a notification to a pre-registered emergency contact in the event of an abnormal situation involving an elderly user.

[0896] "Application example 2 when combining with an emotional engine"

[0897] (Claim 1)

[0898] Information storage means for collecting and managing personal data of elderly users,

[0899] A conversation generation means that generates dialogue based on input from elderly users using natural language processing technology,

[0900] A health monitoring system that monitors the health information of elderly users and generates warnings when abnormalities occur,

[0901] Information and communication means for sending notifications and warnings to elderly users,

[0902] A recognition method that analyzes the voice, facial expressions, and text of elderly users to recognize their emotions,

[0903] An emotion-adapting mechanism that adjusts the content of the dialogue based on the user's emotions,

[0904] A system that includes this.

[0905] (Claim 2)

[0906] The system according to claim 1, further comprising a content generation means for generating conversation topics related to a specific era that corresponds to the age group of elderly users.

[0907] (Claim 3)

[0908] The system according to claim 1, further comprising an automatic notification means for automatically sending a notification to a pre-registered emergency contact in the event of an emergency involving an elderly user. [Explanation of Symbols]

[0909] 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. Information recording means for collecting and managing personal data of elderly users, A dialogue generation means that generates dialogues based on input from elderly users using natural language processing technology, A health monitoring system that monitors the health information of elderly users and generates warnings when abnormalities occur, A means of communication to send notifications and warnings to elderly users, A time management system that tracks the behavior of elderly users and can issue health checks and reminders, A system that includes this.

2. The system according to claim 1, further comprising a generation means for generating conversation topics related to a specific era that corresponds to the age group of elderly users.

3. The system according to claim 1, further comprising an automatic notification means for automatically sending a notification to a pre-registered emergency contact in the event of an abnormal situation involving an elderly user.

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