System

Abstract

A system is provided.SOLUTION: A system includes biological information measurement means for measuring biological information of a user, data storage means for storing the measured biological information, data transmission means for transmitting the stored biological information to a server, and notification means for receiving an analysis result from the server and notifying the user of the analysis result.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional health support devices are primarily wristwatch-type and are limited to collecting data from specific body parts. Furthermore, users must open an app to check their health data, and Bluetooth connection problems frequently occur. This makes it difficult for users to regularly check their data or detect abnormalities early. The present invention aims to solve these problems and provide a means for more efficient and real-time monitoring of a user's health status and for prompt action to be taken when an abnormality occurs. [Means for solving the problem]

[0005] The present invention provides a system including the following means: a biometric information measuring means for measuring a user's biometric information, a data storage means for storing the measured biometric information, a data transmission means for transmitting the stored biometric information to a server, and a notification means for receiving analysis results from the server and notifying the user. This system allows the user to monitor their health in real time on a daily basis and respond quickly if an abnormality is detected. Specifically, the biometric information measuring means uses sensors for measuring pulse and body temperature, and the notification means alerts the user by voice or push notification if an abnormal value is detected. This allows the user to easily monitor their own health condition and discover and address problems early.

[0006] The term "biological information measuring means" refers to a device or part of a device for measuring a user's biological information, such as pulse rate or body temperature.

[0007] "Data storage means" refers to a device or part of a device for temporarily or long-term storage of measured biological information.

[0008] The "data transmission means" is a device or part of a device that has the function of transmitting stored biometric information to a server.

[0009] The "notification means" is a device or part of a device for notifying the user of information based on the analysis results from the server or the detection of anomalies.

[0010] "Pulse" is a value measured by the vibrations that occur when blood passes through blood vessels due to heartbeats.

[0011] "Body temperature" is the measured temperature of the user's body.

[0012] "Server" refers to a computer system for managing the analysis, storage, and notification of biometric information.

[0013] The "user" is a person who wears the device of the present invention and provides biometric information while living their daily life.

[0014] A "sensor" is a device that detects a physical quantity and converts it into an electrical signal, and in this case includes a pulse measurement sensor and a body temperature measurement sensor.

[0015] "Voice notification" is a function that allows the system to convey information to the user through voice.

[0016] "Push notifications" are a feature that allows a system to send information to a user's device in real time. [Brief explanation of the drawings]

[0017] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0018] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0019] First, the terms used in the following description will be explained.

[0020] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0021] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0022] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0023] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0024] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0025] [First embodiment]

[0026] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0027] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0028] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0029] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0030] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0031] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0032] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0033] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0035] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0036] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0037] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0038] This invention relates to a device and system for supporting daily health management of users. Specifically, we provide a system that measures the user's biological information such as pulse and body temperature in real time, transmits the data to a server for analysis and storage, and notifies the user as necessary.

[0039] The system includes the following major components:

[0040] 1. Terminal (device): A device that has the ability to measure biometric information and store and transmit the data. Specifically, it can be a wristwatch, necklace, or earring-type device with built-in sensors that measure pulse and body temperature.

[0041] 2. Server: A computer system that receives, analyzes, and stores biometric data sent from the device. It analyzes the data using AI algorithms and notifies the user of countermeasures if an abnormality is detected.

[0042] 3. Notification system: A system with voice and push notification functions to provide information feedback to users.

[0043] System Overview

[0044] Device behavior

[0045] The device has built-in sensors that periodically measure the user's pulse and body temperature, and uses these sensors to collect the user's biological information in real time. The collected data is temporarily stored in the internal memory.

[0046] Examples:

[0047] When the user wears the necklace, the device measures the pulse and body temperature every 10 minutes, stores the data in its internal memory, and transmits the data to a server at appropriate intervals.

[0048] Server Operation

[0049] The server receives the data sent from the device, stores it in a database, and then uses AI algorithms to analyze the data in real time to detect abnormalities and assess health status.

[0050] Examples:

[0051] The server receives 24-hour biometric data and analyzes it with an AI algorithm. If the server detects that the user's heart rate is abnormally high during a specific time period, it generates a notification to report the abnormality.

[0052] How the notification system works

[0053] The notification system receives notification information sent from the server and provides real-time feedback to the user via voice or push notifications. If an abnormality is detected, the system alerts the user and suggests specific countermeasures.

[0054] Examples:

[0055] The server detects an abnormal heart rate and sends that information to the device, which then sends a voice notification to the user saying, "Your heart rate is abnormally high. Please take a break and take a deep breath."

[0056] Program processing

[0057] The programs in this system are designed to fulfill the roles of terminal, server, and notification system. Each process is explained below in natural language.

[0058] Terminal Programs

[0059] The device periodically collects the user's biometric information and stores it in its internal memory. After collecting a certain amount of data, it transmits it to a server using a secure communication protocol.

[0060] Server Program

[0061] The server analyzes the data received from the device, evaluates abnormal values ​​and health status, and then generates notification messages as needed and sends them to the notification system.

[0062] Notification System Program

[0063] The notification system sends real-time notifications to users based on the notification information received from the server, providing appropriate warnings and countermeasures.

[0064] The above is an embodiment of the present invention. By using this system, users can easily monitor their own health condition on a daily basis and can respond quickly if an abnormality is detected.

[0065] The processing flow will be explained below.

[0066] Step 1:

[0067] The device initializes the sensors and prepares them to measure the user's pulse and temperature. This sensor initialization occurs when the device is turned on.

[0068] Step 2:

[0069] The device periodically (e.g., every 10 minutes) measures the user's pulse and body temperature. After the measurement, the data obtained from the sensors is temporarily stored in the internal memory.

[0070] Step 3:

[0071] When the data stored in the device's internal memory reaches a certain amount (e.g., 30 points), the device prepares to send the data. When preparing to send the data, the data is encrypted.

[0072] Step 4:

[0073] The device sends encrypted data to the server using a secure communication protocol (e.g., HTTPS).

[0074] Step 5:

[0075] The server stores the data received from the device in a database, then extracts a sample of the data and performs an initial analysis using an AI algorithm.

[0076] Step 6:

[0077] The server then uses AI algorithms to analyze the data in detail, detecting anomalies and assessing health status, identifying abnormal heart rate and body temperature fluctuations.

[0078] Step 7:

[0079] If the server detects an anomaly based on the analysis results, it generates a warning message that includes details of the anomaly and appropriate countermeasures.

[0080] Step 8:

[0081] The server sends the generated warning message to the terminal, using real-time communication.

[0082] Step 9:

[0083] The device notifies the user of the warning message received from the server. The notification method is audio notification or push notification. For example, a message such as "Your heart rate is abnormally high. Please take a break and relax" may be sent.

[0084] Step 10:

[0085] The user checks the notification and takes necessary action, such as taking a deep breath, taking a break, or seeking medical attention.

[0086] Step 11:

[0087] After the user responds, the device measures again and sends the collected data to the server to continuously monitor the user's health condition.

[0088] Step 12:

[0089] The server periodically analyzes the collected data over the long term to evaluate the user's health trends, and generates regular health advice based on the evaluation results.

[0090] Step 13:

[0091] The server sends the generated health advice to the device, and the device notifies the user of the advice. For example, the device may notify the user of the advice, saying, "We recommend walking 20 minutes every day."

[0092] Step 14:

[0093] The user receives the advice, decides whether to incorporate it into their daily life, and takes the necessary action.

[0094] Example 1

[0095] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0096] In modern society, personal health management has become an important issue. However, many current systems are insufficient for continuously monitoring a user's health status, and in particular, they lack the means to prompt and appropriate action when an abnormality occurs. Therefore, there is a need for a system that can measure a user's biological information in real time, detect abnormalities, and provide immediate countermeasures.

[0097] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0098] In this invention, the server includes a biological information measuring means for measuring a user's biological information, a data storage means for temporarily storing the measured biological information, a data transmission means for transmitting a certain amount of data to the server after accumulating the data, an analysis means for analyzing the data received by the server using an AI algorithm, a message generation means for detecting an abnormality based on the analysis result and generating a notification message, and a notification means for notifying the user of the generated notification message. This enables real-time monitoring of biological information and rapid detection and response to abnormalities.

[0099] The term "biological information measuring means" refers to a device or sensor for measuring biological information such as the user's pulse rate and body temperature.

[0100] "Data storage means" refers to a memory or storage device for temporarily storing measured biological information.

[0101] "Data transmission means" refers to the communication protocol or device used to transmit the stored biometric information to the server.

[0102] "Analysis means" refers to the function or process of analyzing biometric information received by the server using an AI algorithm.

[0103] "Message generation means" refers to a device or process that detects an abnormality based on the analysis results and generates a message to notify the user.

[0104] The "notification means" refers to a means for notifying the user of the generated notification message, such as a voice notification or a push notification.

[0105] The term "biological information measuring means" refers to a device or sensor for measuring biological information such as the user's pulse rate and body temperature.

[0106] "Data storage means" refers to a memory or storage device for temporarily storing measured biological information.

[0107] "Data transmission means" refers to the communication protocol or device used to transmit the stored biometric information to the server.

[0108] "Analysis means" refers to the function or process of analyzing biometric information received by the server using an AI algorithm.

[0109] "Message generation means" refers to a device or process that detects an abnormality based on the analysis results and generates a message to notify the user.

[0110] The "notification means" refers to a means for notifying the user of the generated notification message, such as a voice notification or a push notification.

[0111] MODE FOR CARRYING OUT THE INVENTION

[0112] This invention relates to a device and system for supporting daily health management of users. Specifically, we provide a system that measures a user's biological information, such as pulse and body temperature, in real time, transmits the data to a server for analysis and storage, and notifies the user as needed. A specific embodiment of this system is described below.

[0113] Hardware Configuration

[0114] The present invention includes the following major components:

[0115] 1. Terminal (device): A device that has the ability to measure biometric information and store and transmit the data. Specifically, it can be a wristwatch, necklace, or earring-type device with built-in sensors that measure pulse and body temperature.

[0116] 2. Server: A computer system that receives, analyzes, and stores biometric data sent from the device. It analyzes the data using AI algorithms and notifies the user of countermeasures if an abnormality is detected.

[0117] 3. Notification system: A system with voice and push notification functions to provide information feedback to users.

[0118] Software Configuration

[0119] The device is equipped with dedicated software for measuring biometric information in real time, while the server is equipped with AI algorithms for receiving, storing, and analyzing the data, and also includes a program for generating notification messages required for the notification system.

[0120] Specific software used includes:

[0121] Database system: MySQL, PostgreSQL, etc.

[0122] AI algorithms: TensorFlow, PyTorch, etc.

[0123] Device behavior

[0124] The device has a built-in sensor that periodically measures the user's biometric information (specifically, pulse and body temperature). This sensor is used to collect the user's biometric information in real time and temporarily store it in the internal memory. Once a certain amount of data has been accumulated, the data is sent to the server using a secure communication protocol (e.g., Bluetooth Low Energy or Wi-Fi).

[0125] Examples:

[0126] When the user wears the necklace, it measures their pulse and body temperature every 10 minutes, stores the data in its internal memory, and once a certain amount of data is reached, it transmits the data to a server using Bluetooth Low Energy.

[0127] Server Operation

[0128] The server receives the data sent from the device and stores it in a database. It then uses AI algorithms to analyze the data in real time, detect abnormalities, and assess health status. If necessary, it generates notification messages based on the analysis results and sends them to the notification system.

[0129] Examples:

[0130] The server receives 24-hour biometric data and analyzes it using an AI algorithm powered by TensorFlow. If the server detects that the user's heart rate is abnormally high during a specific time period, it generates a notification message stating, "An abnormal heart rate has been detected."

[0131] How the notification system works

[0132] The notification system receives notification information sent from the server and provides real-time feedback to the user via voice and push notifications. If an abnormality is detected, the system alerts the user and suggests specific countermeasures.

[0133] Examples:

[0134] The user's smartphone will receive a push notification that displays the message "Your heart rate is abnormally high. Please take a rest," or an audio notification will be played over the device's speaker.

[0135] Examples of prompt statements

[0136] Here are some example prompts to input to a generative AI model:

[0137] Please explain in detail how you will analyze the data from the health management device and how you will notify the user if an abnormality is detected.

[0138] The above is an embodiment of the present invention. By using this system, users can easily monitor their own health condition on a daily basis and can respond quickly when an abnormality is detected.

[0139] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0140] Step 1:

[0141] The device measures the user's biometric information.

[0142] Specifically, the device's built-in pulse sensor and body temperature sensor measure data every 10 minutes to obtain pulse rate and body temperature.

[0143] Input: User's biometric information (pulse, body temperature)

[0144] Output: Measured biological information data (e.g. pulse rate 75 beats / min, body temperature 36.5°C)

[0145] Step 2:

[0146] The device stores the measured biometric information in its internal memory.

[0147] The data storage means is used to temporarily store the biometric information.

[0148] Input: Measured biological information data

[0149] Output: Biometric data stored in internal memory

[0150] Step 3:

[0151] After the terminal accumulates a certain amount of data, it transmits the data to the server using a secure communication protocol.

[0152] Specifically, once the data in the internal memory reaches 100 data points, it is sent to a server using Bluetooth Low Energy or Wi-Fi.

[0153] Input: Biometric data stored in the internal memory

[0154] Output: Biometric data sent to the server

[0155] Step 4:

[0156] The server receives the data sent from the terminal and stores it in a database.

[0157] Specifically, after the server receives the data, it stores the data in a database such as MySQL or PostgreSQL.

[0158] Input: Biometric data sent from the device

[0159] Output: Biometric data stored in a database

[0160] Step 5:

[0161] The server analyzes the received data using AI algorithms.

[0162] Specifically, it uses TensorFlow and PyTorch to analyze data, detect outliers, and assess health status.

[0163] Input: Biometric data stored in a database

[0164] Output: Analysis results (e.g., detection of periods when heart rate is abnormally high)

[0165] Step 6:

[0166] If the server detects an abnormality based on the analysis results, it generates a notification message.

[0167] Specifically, when an abnormality is detected, a message is generated saying, "Your heart rate is abnormally high. Please take a rest."

[0168] Input: Analysis results

[0169] Output: Notification message

[0170] Step 7:

[0171] The notification system receives the notification information sent from the server and notifies the user.

[0172] Specifically, users will be notified via push notifications to their smartphones or voice notifications from the device's speaker.

[0173] Input: Notification message

[0174] Output: User notification (e.g., push notification, "Your heart rate is abnormally high. Please take a rest.")

[0175] The above are the processing steps of the program for this system and the specific operation of each step. This system is capable of monitoring the user's health condition in real time and quickly detecting and notifying abnormalities.

[0176] (Application example 1)

[0177] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0178] Conventional health management systems lacked the means to effectively monitor individuals' biometric information in real time and quickly detect and notify abnormalities. Furthermore, when an abnormality occurred, there was no means of properly notifying all relevant parties. This created the problem of being unable to quickly respond to the deterioration of staff health, particularly in brick-and-mortar stores.

[0179] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0180] In this invention, the server includes a data storage means for storing measured biometric information, a data transmission means for transmitting the stored biometric information to the server, a notification means for receiving analysis results from the server and notifying the user, and a means for the notification means to notify the administrator and the relevant user of abnormal values. This makes it possible to monitor biometric information such as pulse and body temperature of users, including staff, in real time, and to quickly notify the administrator and the relevant user if an abnormality is detected.

[0181] "User's biological information" is data that indicates a person's health condition, such as pulse rate and body temperature.

[0182] The "biological information measuring means" is a device with built-in sensors for measuring the user's pulse and body temperature.

[0183] "Data storage means" refers to internal memory or storage for temporarily storing measured biological information.

[0184] "Data transmission means" refers to a communication module or protocol for transmitting stored biometric information to a server.

[0185] The "notification means" is a function for receiving the analysis results from the server and notifying the user and administrator by voice or push notification as necessary.

[0186] The "server" is a computer system that receives, stores, and analyzes biometric information sent from the device and generates a notification if an abnormality is detected.

[0187] "Administrator" refers to the person responsible for monitoring and managing biometric information.

[0188] "Abnormal values" refer to pulse or temperature measurements that are outside the normal range.

[0189] The present invention is a system for supporting a user's daily health management. The system includes the following main components:

[0190] 1. Device: This device has built-in sensors to measure pulse and body temperature. The device periodically measures the user's biometric information and temporarily stores the data in its internal memory. This device is available in various forms, such as a wristwatch, necklace, or earring.

[0191] 2. Server: Receives biometric data sent from the device and stores it in a database. The server uses AI algorithms to analyze the data in real time and generates a notification message if an abnormal value is detected.

[0192] 3. Notification System: The notification system receives notification information sent from the server and provides feedback to users and administrators through voice notifications and push notifications.

[0193] Program processing

[0194] Terminal Programs

[0195] The device periodically collects biometric information and stores it in its internal memory. After collecting a certain amount of data, it transmits the data to a server using a secure communication protocol via a wireless communication module such as Wi-Fi or Bluetooth. This process is performed using Python and the requests library.

[0196] Server Program

[0197] The server uses a web framework such as Flask to analyze the data received from the device. The server analyzes the data stored in the database in real time and uses AI algorithms to evaluate abnormal values ​​and health status. Any abnormal values ​​detected by this algorithm are notified to the administrator and the relevant user.

[0198] Notification System Program

[0199] The notification system notifies users in real time based on the notification information received from the server. Notifications are provided as voice notifications or push notifications to smartphones, allowing users to take prompt action when an abnormality occurs.

[0200] Specific examples

[0201] Scenario: A staff member working in a store wears a necklace-type device. This device measures the staff member's pulse and body temperature every 10 minutes and sends the data to a server. The server analyzes the received data in real time and notifies the manager and the relevant staff member if an abnormality is detected.

[0202] Example prompts to input to a generative AI model:

[0203] I am designing a system to monitor the health of store staff 24 / 7. Staff will wear a necklace-type device that measures their pulse and body temperature every 10 minutes and sends the data to a server. The server will perform real-time analysis and notify managers and staff if any abnormalities are detected. The terminals will collect data using Python, and the server will analyze the data using Flask. Can you give me a code example for this system?

[0204] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0205] Step 1:

[0206] The device measures the user's biometric information. Specifically, the device's built-in pulse sensor and body temperature sensor measure the user's pulse and body temperature. The input is the biometric information measured by the sensor, and the output is pulse and body temperature data.

[0207] Step 2:

[0208] The device stores the measured biometric information. The measured pulse and body temperature data is temporarily stored in the device's internal memory. The input is the measured biometric data, and the output is data stored in the internal memory.

[0209] Step 3:

[0210] The device periodically transmits biometric data to the server. The device transmits the stored data to the server using Wi-Fi or Bluetooth. The input is the data stored in the internal memory, and the output is the biometric data transmitted to the server.

[0211] Step 4:

[0212] The server receives the biometric data sent from the device. The server stores the data in a database and prepares it for analysis. The input is the biometric data sent from the device, and the output is data stored in the database.

[0213] Step 5:

[0214] The server analyzes the received biometric data. The server uses an AI algorithm to analyze and detect abnormal values. The input is the biometric data stored in the database, and the output is the analysis results.

[0215] Step 6:

[0216] If the server detects an abnormal value, it generates a notification message. If the server detects an abnormal value, it generates a notification message and sends it to the notification system. The input is the analysis result, and the output is the notification message.

[0217] Step 7:

[0218] The notification system receives notification messages and notifies users and administrators. The notification system provides real-time feedback through voice or push notifications. The input is the notification message sent from the server, and the output is the notification to users and administrators.

[0219] Adding specific actions

[0220] Step 1:

[0221] The device activates the pulse and temperature sensors and performs measurements for a few seconds. During the measurement, the sensors collect pulse and temperature data from the skin surface.

[0222] Step 2:

[0223] After each measurement, the device stores the pulse and temperature data in a specific area of ​​its internal memory.

[0224] Step 3:

[0225] Every 10 minutes, the device collects the stored data in packets and sends them to a server via Wi-Fi or Bluetooth using a secure protocol.

[0226] Step 4:

[0227] The server receives data packets sent from the terminals and stores the data by creating entries in a database.

[0228] Step 5:

[0229] An AI algorithm on the server scans new entries in the database, analyzing pulse and temperature data, and if it detects any abnormalities, it stores that information in specific variables.

[0230] Step 6:

[0231] If an abnormal value is detected, the server generates a notification message for the administrator and the affected user and sends the message to the notification system.

[0232] Step 7:

[0233] The notification system analyzes the received notification messages and sends voice and push notifications to the relevant users and administrators, including specific anomalies and recommended actions.

[0234] The above is a specific processing procedure of the embodiment of the invention.

[0235] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0236] The present invention relates to a device and system for supporting daily health management of users. Specifically, the present invention provides a system that combines technology for recognizing a user's biological information, such as pulse rate and body temperature, and the user's emotions. The system includes the following main components:

[0237] 1. Terminal (device): A device that has the ability to measure biometric information and store and transmit that data. Specifically, it could be a wristwatch, necklace, or earring-type device with built-in sensors that measure pulse and body temperature, and an emotion engine that analyzes voice and facial expressions to recognize emotions.

[0238] 2. Server: A computer system that receives, analyzes, and stores data sent from the device. The server uses AI algorithms to analyze the data and notifies the user of countermeasures if an anomaly is detected. It also recommends specific actions based on the user's emotions.

[0239] 3. Notification system: A system with voice and push notification functions to provide information feedback to users.

[0240] 4. Emotion Engine: A machine learning model that analyzes the user's voice and facial expression data to recognize the user's emotions.

[0241] System Program Processing

[0242] The program in this system is designed to fulfill the roles of terminal, server, notification system, and emotion engine. Each process is explained below.

[0243] Terminal handling

[0244] The device periodically measures the user's pulse and body temperature and stores the data in its internal memory. It also uses a sound sensor and camera to collect the user's voice and facial expression data, and uses an emotion engine to recognize emotions. The recognized emotion data is stored along with biometric information, and once a certain amount of data has been collected, it is sent to a server using a secure communication protocol.

[0245] Examples:

[0246] When the user wears the necklace-type device, it measures their pulse and body temperature every 10 minutes and stores the data in its internal memory. Additionally, when the user speaks, the audio sensor collects their voice, and the camera simultaneously captures facial expression data. If the emotion engine detects "stress," it stores this information along with their biometric information and sends it to the server as appropriate.

[0247] Server Processing

[0248] The server analyzes the data received from the device and evaluates abnormal values ​​and health status. It also analyzes the emotion data recognized by the emotion engine and evaluates the correlation between the user's physiological changes and emotions. Furthermore, if an abnormality is detected or a specific emotion is recognized, it generates a warning message and sends it to the notification system.

[0249] Examples:

[0250] The server receives 24-hour biometric and emotional data and analyzes it using an AI algorithm. As a result, it discovers that the user's heart rate is abnormally high during a specific time period, and that the emotion of "stress" is frequently recognized at that time. The server generates a message saying, "Stress tends to increase during this time period. We recommend taking deep breaths," and sends it to the device.

[0251] Notification System Processing

[0252] The notification system notifies users in real time based on notification information sent from the server. If an abnormality is detected, the system alerts the user and suggests specific countermeasures. It also prompts the user to take appropriate action based on emotional data.

[0253] Examples:

[0254] The server generates a message saying "Your stress is rising. Please take a deep breath" and sends it to the device. The device then notifies the user with a voice message saying "Your stress is rising. Please take a deep breath and relax."

[0255] Emotion engine processing

[0256] The emotion engine analyzes the user's voice and facial expression data to recognize specific emotions. For example, it can detect emotions such as "happiness," "sadness," and "anger" from voice characteristics and facial changes. The recognized emotions are stored along with biometric data and sent to the server.

[0257] Examples:

[0258] The user wears the necklace-type device, and the emotion engine analyzes voice and facial expression data during conversation to recognize "happiness." This information, along with pulse and body temperature data, is stored and sent to the server at the appropriate time.

[0259] The above is an embodiment of the present invention. By using this system, users can monitor their own health condition and emotional changes in real time and take appropriate measures when necessary.

[0260] The processing flow will be explained below.

[0261] Step 1:

[0262] The device initializes the sensors and prepares them to measure the user's pulse and temperature. This sensor initialization occurs when the device is turned on.

[0263] Step 2:

[0264] The device periodically (e.g., every 10 minutes) measures the user's pulse and body temperature. After the measurement, the data obtained from the sensors is temporarily stored in the internal memory.

[0265] Step 3:

[0266] The device uses a sound sensor and a camera to collect the user's voice and facial expression data, which is then processed by an emotion engine to recognize the user's emotions in real time.

[0267] Step 4:

[0268] The device stores the recognized emotion data along with biometric data in its internal memory, recording, for example, the user's stress level or happiness level.

[0269] Step 5:

[0270] When the data stored in the device's internal memory reaches a certain amount (e.g., 30 points), the device prepares to send the data. When preparing to send the data, the data is encrypted.

[0271] Step 6:

[0272] The device sends encrypted data to the server using a secure communication protocol (e.g., HTTPS).

[0273] Step 7:

[0274] The server stores the data received from the device in a database, then extracts a sample of the data and performs an initial analysis using an AI algorithm.

[0275] Step 8:

[0276] The server uses AI algorithms to analyze the data in detail, detect abnormalities, and assess the user's health. During this process, it identifies abnormal heart rate and body temperature fluctuations. It also analyzes emotional data to recognize changes in emotions.

[0277] Step 9:

[0278] If the server detects an anomaly based on the analysis results, it generates a warning message that includes details of the anomaly and appropriate countermeasures. It also generates a message that suggests specific actions based on the user's emotions.

[0279] Step 10:

[0280] The server sends the generated warning message to the terminal, using real-time communication.

[0281] Step 11:

[0282] The device notifies the user of the warning message received from the server. Notification methods include voice notification and push notification. For example, a message such as "Your heart rate is abnormally high. Please take a break and relax" or "Stress tends to increase at this time of day. We recommend taking deep breaths" may be sent.

[0283] Step 12:

[0284] The user checks the notification and takes necessary action, such as taking a deep breath, taking a break, or seeking medical attention.

[0285] Step 13:

[0286] The device then measures biometric and emotional data again, repeating this process and sending the data to the server each time, continuously monitoring the user's health.

[0287] Step 14:

[0288] The server analyzes the data over a long period of time to identify trends in the user's health and generates regular health advice based on the analysis results.

[0289] Step 15:

[0290] The server sends the generated health advice to the device, and the device notifies the user of the advice. For example, the device may notify the user of the advice, saying, "We recommend walking 20 minutes every day."

[0291] Step 16:

[0292] The user receives the advice, decides whether to incorporate it into their daily life, and takes the necessary action.

[0293] Example 2

[0294] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0295] In modern society, many people suffer from stress and health problems, but there are limited systems that can monitor these conditions in real time and suggest timely solutions. Conventional health management devices primarily focus on measuring biometric information and lack the ability to simultaneously recognize and provide feedback on the user's emotional state. This often prevents users from effectively managing their health, delaying early detection and countermeasures. To address these issues, the present invention provides a system that monitors and analyzes a user's biometric information and emotional state in real time and provides appropriate feedback.

[0296] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0297] In this invention, the server includes a measuring means for measuring the user's biometric information, a storage means for storing the measured biometric information, a data transmission means for transmitting the stored biometric information to the server, a notification means for receiving analysis results from the server and notifying the user, an emotion recognition means for analyzing the user's voice data and facial expression data and recognizing emotions, a means for storing the recognized emotion data together with the biometric information and transmitting it to the server, a means for the server to analyze the received data and notify the user of how to deal with any abnormalities detected, and a notification system means for notifying the user in real time based on notification messages from the server. This enables the user to monitor their own health and emotional state in real time and take prompt action if an abnormality is detected.

[0298] "Biometric information" is data that indicates the physical condition of the user, such as pulse, body temperature, and blood pressure.

[0299] "Measurement means" refers to sensors and devices used to acquire biometric information from a user.

[0300] "Storage means" refers to a storage device for storing measured biological information.

[0301] "Data transmission means" refers to a communication function for transferring stored biometric information to a server.

[0302] The "server" is a central processing system that analyzes and stores data sent from the measurement means and storage means, and provides feedback to the user as needed.

[0303] "Notification means" refers to a means for notifying the user of analysis results and feedback from the server, and includes, for example, voice notification and push notification.

[0304] "Voice data" is digital information that is a recording of the user's voice.

[0305] "Facial expression data" is image data of the user's facial expression captured by a camera.

[0306] "Emotion recognition means" refers to a function that analyzes voice data and facial expression data to identify the user's emotions.

[0307] "Abnormal" refers to a significant deviation from normal biometric or emotional states, which may indicate health risks or mental health problems.

[0308] "Countermeasures" refers to specific actions or advice that a user should take when an abnormality is detected.

[0309] "Real-time notification" is a function that instantly provides information to users based on data analyzed by the server.

[0310] The present invention relates to a device and system for supporting daily health management of users. Specifically, the system combines technology for recognizing a user's biological information, such as pulse and body temperature, and the user's emotions. The system includes the following main components:

[0311] 1. Data collection by device

[0312] The device periodically measures the user's pulse and body temperature and stores the data in its internal memory. It also uses a sound sensor and camera to collect the user's voice and facial expression data, and uses an emotion engine to recognize emotions. The recognized emotion data is stored along with biometric information, and once a certain amount of data has been collected, it is sent to a server using a secure communication protocol (e.g., HTTPS).

[0313] Specifically, when a user wears the necklace-type device, it measures their pulse and body temperature every 10 minutes and stores the data in its internal memory. When the user speaks, the audio sensor collects voice data, and the camera captures facial expression data in real time. If the emotion engine recognizes "stress," it stores that information along with biometric information and sends it to a server as appropriate.

[0314] 2. Data reception and analysis by the server

[0315] The server receives the biometric and emotional data sent from the device and analyzes it using an AI algorithm (e.g., TensorFlow model), detecting outliers and evaluating the correlation between emotions and biometric data.

[0316] For example, if the server receives 24-hour biometric and emotional data and analyzes it using an AI algorithm, and finds that the user's heart rate is abnormally high during a particular time period and that they frequently express feelings of "stress," this abnormal data will be detected.

[0317] 3. Server-generated action recommendations

[0318] The server generates notification messages for users based on the analysis results. If an abnormal value is detected or a specific emotion is recognized, a warning message is created and sent to the notification system.

[0319] For example, the server generates a message saying, "Stress tends to increase at this time of day. We recommend taking deep breaths," and sends it to a notification system.

[0320] 4. Notification via the notification system

[0321] The notification system notifies users in real time based on messages sent from the server, suggests specific countermeasures, and encourages necessary actions.

[0322] For example, if the notification system receives the message "Your stress levels are rising. Please take a deep breath," the device will relay that message to the user via voice notification, instructing them, "This is a time when stress levels are rising. Please take a deep breath and relax."

[0323] 5. User Response

[0324] Based on the notifications from the notification system, the user can take appropriate actions, such as taking deep breaths, to improve their mood or health.

[0325] When the user receives the notification message, he or she should follow the advice and take several deep breaths to relax mentally.

[0326] 6. Feedback rating by the server

[0327] The server continuously monitors user responses, analyzes newly acquired data, evaluates the effectiveness of the feedback, and adjusts notification messages and recommended actions as needed.

[0328] For example, if the server reanalyzes the user's biometric data and the heart rate returns to the normal range after taking a deep breath, it will evaluate the action as effective and recommend continuing to use it in the future.Similarly, if no effect is observed, new measures will be considered.

[0329] Prompt Sentence Examples

[0330] Below are some example prompts to be input to the generative AI model:

[0331] "A user is wearing a necklace-like device. The device measures their pulse and temperature every 10 minutes and collects audio and facial expression data. The system identifies that the user is experiencing stress. Explain how this information can be sent to a server and an appropriate notification can be provided to the user."

[0332] The above is an embodiment of the present invention. By using this system, users can monitor their own health condition and emotional changes in real time and take appropriate measures when necessary.

[0333] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0334] Step 1: Measurement

[0335] The device measures the user's biometric information. Specifically, it uses sensors to measure pulse and body temperature every 10 minutes, and uses an audio sensor and camera to collect the user's voice data and facial expression data in real time.

[0336] Input: User's pulse, body temperature, voice, facial expression

[0337] Data processing / calculation: pulse and temperature sensor readings, voice and facial expression capture

[0338] Output: Measured biometric information, acquired voice data, facial expression data

[0339] Step 2: Save

[0340] The device stores the measured biometric information and collected emotional data in its internal memory.

[0341] Input: Measured biometric information, collected voice data, facial expression data

[0342] Data processing / calculation: Data storage processing

[0343] Output: Data stored in the internal memory

[0344] Step 3: Send

[0345] Once a certain amount of data has been collected, the terminal transmits this data to a server using a secure communication protocol (e.g., HTTPS).

[0346] Input: Data stored in the internal memory

[0347] Data processing / calculation: Packetizing data, sending data using HTTPS

[0348] Output: Biometric and emotional data sent to the server

[0349] Step 4: Data reception and analysis

[0350] The server receives biometric and emotional data from the device and analyzes it using AI algorithms to detect abnormalities and evaluate the correlation between emotions and biometric data.

[0351] Input: Biometric data and emotional data sent from the device

[0352] Data processing / calculation: Data analysis using AI algorithms, outlier detection, and emotional data analysis

[0353] Output: Analysis results, anomaly detection results

[0354] Step 5: Generate action recommendations

[0355] The server generates a notification message for the user based on the analysis results. If an abnormal value is detected or a specific emotion is recognized, a warning message is created and sent to the notification system.

[0356] Input: Analysis results, anomaly detection results

[0357] Data processing / calculation: Notification message generation

[0358] Output: Message sent to the notification system

[0359] Step 6: Notification

[0360] The notification system notifies users in real time based on messages sent from the server, suggests specific countermeasures, and encourages necessary actions.

[0361] Input: The message sent from the server

[0362] Data processing / calculation: Message analysis, generation of voice or push notifications

[0363] Output: User notification

[0364] Step 7: User Action

[0365] Based on the notification from the notification system, the user takes appropriate action, for example, taking deep breaths to try to improve their mood or health.

[0366] Input: Notification message from the notification system

[0367] Data processing / calculation: Actions based on notifications

[0368] Output: User behavior, improved health status

[0369] Step 8: Feedback evaluation

[0370] The server continuously monitors user responses, analyzes newly acquired data, evaluates the effectiveness of the feedback, and adjusts notification messages and recommended actions as needed.

[0371] Input: New biometric data and emotional data from the user

[0372] Data processing / calculation: Data analysis, evaluation of feedback effects

[0373] Output: Evaluation results, tailored notification messages and recommended actions

[0374] The above is the specific processing flow of this system. We have explained in detail how the input data is processed and analyzed at each step, and how it is provided as specific output.

[0375] (Application example 2)

[0376] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0377] Conventional health management systems lack the means to monitor users' health status in real time while they are in the vehicle and to respond quickly if an abnormality occurs. Furthermore, in emergencies, appropriate responses may be delayed, making it difficult to ensure user safety. This creates a need for a means to effectively manage user health risks, especially in autonomous vehicles.

[0378] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting health information and emotional information of the user using sensors installed in the vehicle, means for analyzing the collected health information and emotional information in real time and immediately transmitting the information to the server if an abnormality is detected, means for automatically stopping the vehicle in a safe place if an abnormality is detected, and means for automatically contacting an emergency contact. This makes it possible to respond quickly to the user's health condition or an emergency situation.

[0379] The "biological information measuring means" is a device for measuring biological information such as the pulse rate and body temperature of the user.

[0380] The "data storage means" is a storage device for recording measured biometric information and emotional information.

[0381] The "data transmission means" is a communication device for transmitting the stored biometric information and emotional information to the server.

[0382] The "notification means" is a device for notifying the user of the analysis results from the server.

[0383] A "sensor" is a device placed in a vehicle that measures the user's health and emotional information.

[0384] "Means for real-time analysis" refers to a system for instantly analyzing collected biometric and emotional information.

[0385] The "means for transmitting information to a server when an abnormality is detected" is a device that has the function of quickly transmitting information about an abnormal value to a server when that value is detected.

[0386] "Means for stopping a vehicle in a safe location" refers to a system that moves an autonomous vehicle to a safe location and stops it in an emergency.

[0387] The "means for automatically contacting emergency contacts" is a device that automatically contacts a pre-set emergency contact when an abnormality is detected.

[0388] The present invention relates to a health management system that monitors the health status and emotions of a user in a vehicle in real time and provides a prompt response if an abnormality is detected. This system is composed of a biological information measurement means, a data storage means, a data transmission means, a notification means, and a safety management means for the vehicle.

[0389] System hardware and software configuration

[0390] The system hardware includes the following major components:

[0391] Biometric measurement means: Sensors placed inside the vehicle (e.g., heart rate sensors built into seat belts, interior temperature sensors) measure the user's pulse and body temperature in real time.

[0392] Data storage means: A memory device for temporarily storing measured biometric and emotional information.

[0393] Data transmission means: A communication module for transmitting the measured data to the server via a secure communication protocol (e.g., HTTPS).

[0394] Notification means: A system that receives notification information sent from the server and notifies the user via the vehicle's infotainment system or the user's smartphone.

[0395] In-vehicle safety management measures: an autonomous driving system that automatically stops the vehicle in a safe location if an abnormality is detected, and a communication system that automatically contacts designated contacts in the event of an emergency.

[0396] The system software configuration includes the following components:

[0397] Real-time data collection module: Collects data from the biological information measurement means in real time and stores it in the data storage means.

[0398] Data analysis module: Runs on the server and uses AI algorithms to analyze the transmitted biometric and emotional information. If an abnormality is detected, it generates a warning notification and countermeasures.

[0399] Notification management module: Sends notification information from the server to the terminal and notifies the user of appropriate measures.

[0400] Emergency response module: Links with the vehicle's safety management measures, automatically stops the vehicle in the event of an abnormality, and makes emergency contact if necessary.

[0401] Example of operation

[0402] When a user gets into an autonomous vehicle, the biometric information measurement means periodically measures the user's pulse and body temperature. This data is stored in the data storage means in real time and transmitted to the server via the data transmission means. The server uses an AI algorithm to analyze the data, and if an abnormality is detected, the notification management module sends a voice or push notification to the user. Furthermore, if a serious abnormality is detected, the safety management means within the vehicle is automatically activated, stopping the vehicle in a safe location and making an emergency call.

[0403] Prompt Sentence Examples

[0404] Below are some examples of specific prompt sentences for this system.

[0405] markdown

[0406] Use case: Vehicle Health Monitoring System

[0407] Requirements:

[0408] 1. Monitor real-time heart rate, body temperature, and user emotions using in-car sensors.

[0409] 2. Analyze collected data and send to centralized server for further processing.

[0410] 3. Alert the user with voice messages or display notifications on the Infotainment system if any abnormalities are detected.

[0411] ----

[0412] User Scenario:

[0413] A user is on a long drive. The system monitors the user's vital signs every 10 minutes. At 3 PM, the user's heart rate suddenly spikes and the emotion engine detects stress. The system alerts the user through the car's infotainment system, advising them to take a break and relax. If the user does not respond or if the signs of stress persist, the system automatically contacts emergency services.

[0414] The system of the present invention effectively manages the safety and health of users by monitoring their health status in real time and taking appropriate measures quickly and automatically if an abnormality is detected.

[0415] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0416] Step 1:

[0417] Sensors installed in the vehicle measure the user's biometric information (pulse, body temperature) and emotional information in real time. Heart rate and body temperature data, as well as voice and sidelong glance data to identify emotions, are required as input. The measured data is obtained as output.

[0418] Step 2:

[0419] The device temporarily stores the measured data in a data storage means. The input requires biometric and emotional information data provided by the sensors. The stored data is obtained as the output.

[0420] Step 3:

[0421] The device sends the stored data to the server using a secure communication protocol (e.g. HTTPS). The stored data is required as input. The data sent to the server is obtained as output.

[0422] Step 4:

[0423] The server analyzes the received data using AI algorithms to detect abnormal values ​​and dangerous health conditions. The input requires the transmitted biometric and emotional data. The output is the analysis results.

[0424] Step 5:

[0425] If the server detects an anomaly based on the analysis results, it generates a warning message for the user. The analysis result data is required as input, and the generated warning message is obtained as output.

[0426] Step 6:

[0427] The server sends the generated alert message to the user's terminal, the vehicle's infotainment system, or the user's smartphone via a notification means. The alert message is required as input, and the message notified to the user is obtained as output.

[0428] Step 7:

[0429] If a serious abnormality is detected, the vehicle's autonomous driving system will be activated and stop the vehicle in a safe place. Information on the abnormality detection is required as input, and the stopped vehicle is obtained as output.

[0430] Step 8:

[0431] Furthermore, in the event of an emergency, the server automatically contacts the emergency contacts that have been set up. Emergency contact information and anomaly detection information are required as input. The output indicates that the emergency contact has been completed.

[0432] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0433] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0434] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0435] [Second embodiment]

[0436] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0437] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0438] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0439] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0440] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0441] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0442] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0443] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0444] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0445] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0446] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0447] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0448] This invention relates to a device and system for supporting daily health management of users. Specifically, we provide a system that measures the user's biological information such as pulse and body temperature in real time, transmits the data to a server for analysis and storage, and notifies the user as necessary.

[0449] The system includes the following major components:

[0450] 1. Terminal (device): A device that has the ability to measure biometric information and store and transmit the data. Specifically, it can be a wristwatch, necklace, or earring-type device with built-in sensors that measure pulse and body temperature.

[0451] 2. Server: A computer system that receives, analyzes, and stores biometric data sent from the device. It analyzes the data using AI algorithms and notifies the user of countermeasures if an abnormality is detected.

[0452] 3. Notification system: A system with voice and push notification functions to provide information feedback to users.

[0453] System Overview

[0454] Device behavior

[0455] The device has built-in sensors that periodically measure the user's pulse and body temperature, and uses these sensors to collect the user's biological information in real time. The collected data is temporarily stored in the internal memory.

[0456] Examples:

[0457] When the user wears the necklace, the device measures the pulse and body temperature every 10 minutes, stores the data in its internal memory, and transmits the data to a server at appropriate intervals.

[0458] Server Operation

[0459] The server receives the data sent from the device, stores it in a database, and then uses AI algorithms to analyze the data in real time to detect abnormalities and assess health status.

[0460] Examples:

[0461] The server receives 24-hour biometric data and analyzes it with an AI algorithm. If the server detects that the user's heart rate is abnormally high during a specific time period, it generates a notification to report the abnormality.

[0462] How the notification system works

[0463] The notification system receives notification information sent from the server and provides real-time feedback to the user via voice or push notifications. If an abnormality is detected, the system alerts the user and suggests specific countermeasures.

[0464] Examples:

[0465] The server detects an abnormal heart rate and sends that information to the device, which then sends a voice notification to the user saying, "Your heart rate is abnormally high. Please take a break and take a deep breath."

[0466] Program processing

[0467] The programs in this system are designed to fulfill the roles of terminal, server, and notification system. Each process is explained below in natural language.

[0468] Terminal Programs

[0469] The device periodically collects the user's biometric information and stores it in its internal memory. After collecting a certain amount of data, it transmits it to a server using a secure communication protocol.

[0470] Server Program

[0471] The server analyzes the data received from the device, evaluates abnormal values ​​and health status, and then generates notification messages as needed and sends them to the notification system.

[0472] Notification System Program

[0473] The notification system sends real-time notifications to users based on the notification information received from the server, providing appropriate warnings and countermeasures.

[0474] The above is an embodiment of the present invention. By using this system, users can easily monitor their own health condition on a daily basis and can respond quickly if an abnormality is detected.

[0475] The processing flow will be explained below.

[0476] Step 1:

[0477] The device initializes the sensors and prepares them to measure the user's pulse and temperature. This sensor initialization occurs when the device is turned on.

[0478] Step 2:

[0479] The device periodically (e.g., every 10 minutes) measures the user's pulse and body temperature. After the measurement, the data obtained from the sensors is temporarily stored in the internal memory.

[0480] Step 3:

[0481] When the data stored in the device's internal memory reaches a certain amount (e.g., 30 points), the device prepares to send the data. When preparing to send the data, the data is encrypted.

[0482] Step 4:

[0483] The device sends encrypted data to the server using a secure communication protocol (e.g., HTTPS).

[0484] Step 5:

[0485] The server stores the data received from the device in a database, then extracts a sample of the data and performs an initial analysis using an AI algorithm.

[0486] Step 6:

[0487] The server then uses AI algorithms to analyze the data in detail, detect abnormalities, and assess the patient's health, identifying abnormal heart rate and body temperature fluctuations.

[0488] Step 7:

[0489] If the server detects an anomaly based on the analysis results, it generates a warning message that includes details of the anomaly and appropriate countermeasures.

[0490] Step 8:

[0491] The server sends the generated warning message to the terminal, using real-time communication.

[0492] Step 9:

[0493] The device notifies the user of the warning message received from the server. The notification method is audio notification or push notification. For example, a message such as "Your heart rate is abnormally high. Please take a break and relax" may be sent.

[0494] Step 10:

[0495] The user checks the notification and takes necessary action, such as taking a deep breath, taking a break, or seeking medical attention.

[0496] Step 11:

[0497] After the user responds, the device measures again and sends the collected data to the server to continuously monitor the user's health condition.

[0498] Step 12:

[0499] The server periodically analyzes the collected data over the long term to evaluate the user's health trends, and generates regular health advice based on the evaluation results.

[0500] Step 13:

[0501] The server sends the generated health advice to the device, and the device notifies the user of the advice. For example, the device may notify the user of the advice, saying, "We recommend walking 20 minutes every day."

[0502] Step 14:

[0503] The user receives the advice, decides whether to incorporate it into their daily life, and takes the necessary action.

[0504] Example 1

[0505] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0506] In modern society, personal health management has become an important issue. However, many current systems are insufficient for continuously monitoring a user's health status, and in particular, they lack the means to prompt and appropriate action when an abnormality occurs. Therefore, there is a need for a system that can measure a user's biological information in real time, detect abnormalities, and provide immediate countermeasures.

[0507] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0508] In this invention, the server includes a biological information measuring means for measuring a user's biological information, a data storage means for temporarily storing the measured biological information, a data transmission means for transmitting a certain amount of data to the server after accumulating the data, an analysis means for analyzing the data received by the server using an AI algorithm, a message generation means for detecting an abnormality based on the analysis result and generating a notification message, and a notification means for notifying the user of the generated notification message. This enables real-time monitoring of biological information and rapid detection and response to abnormalities.

[0509] The term "biological information measuring means" refers to a device or sensor for measuring biological information such as the user's pulse rate and body temperature.

[0510] "Data storage means" refers to a memory or storage device for temporarily storing measured biological information.

[0511] "Data transmission means" refers to the communication protocol or device used to transmit the stored biometric information to the server.

[0512] "Analysis means" refers to the function or process of analyzing biometric information received by the server using an AI algorithm.

[0513] "Message generation means" refers to a device or process that detects an abnormality based on the analysis results and generates a message to notify the user.

[0514] The "notification means" refers to a means for notifying the user of the generated notification message, such as a voice notification or a push notification.

[0515] The term "biological information measuring means" refers to a device or sensor for measuring biological information such as the user's pulse rate and body temperature.

[0516] "Data storage means" refers to a memory or storage device for temporarily storing measured biological information.

[0517] "Data transmission means" refers to the communication protocol or device used to transmit the stored biometric information to the server.

[0518] "Analysis means" refers to the function or process of analyzing biometric information received by the server using an AI algorithm.

[0519] "Message generation means" refers to a device or process that detects an abnormality based on the analysis results and generates a message to notify the user.

[0520] The "notification means" refers to a means for notifying the user of the generated notification message, such as a voice notification or a push notification.

[0521] MODE FOR CARRYING OUT THE INVENTION

[0522] This invention relates to a device and system for supporting daily health management of users. Specifically, we provide a system that measures a user's biological information, such as pulse and body temperature, in real time, transmits the data to a server for analysis and storage, and notifies the user as needed. A specific embodiment of this system is described below.

[0523] Hardware Configuration

[0524] The present invention includes the following major components:

[0525] 1. Terminal (device): A device that has the ability to measure biometric information and store and transmit the data. Specifically, it can be a wristwatch, necklace, or earring-type device with built-in sensors that measure pulse and body temperature.

[0526] 2. Server: A computer system that receives, analyzes, and stores biometric data sent from the device. It analyzes the data using AI algorithms and notifies the user of countermeasures if an abnormality is detected.

[0527] 3. Notification system: A system with voice and push notification functions to provide information feedback to users.

[0528] Software Configuration

[0529] The device is equipped with dedicated software for measuring biometric information in real time, while the server is equipped with AI algorithms for receiving, storing, and analyzing the data, and also includes a program for generating notification messages required for the notification system.

[0530] Specific software used includes:

[0531] Database system: MySQL, PostgreSQL, etc.

[0532] AI algorithms: TensorFlow, PyTorch, etc.

[0533] Device behavior

[0534] The device has a built-in sensor that periodically measures the user's biometric information (specifically, pulse and body temperature). This sensor is used to collect the user's biometric information in real time and temporarily store it in the internal memory. Once a certain amount of data has been accumulated, the data is sent to the server using a secure communication protocol (e.g., Bluetooth Low Energy or Wi-Fi).

[0535] Examples:

[0536] When the user wears the necklace, it measures their pulse and body temperature every 10 minutes, stores the data in its internal memory, and once a certain amount of data is reached, it transmits the data to a server using Bluetooth Low Energy.

[0537] Server Operation

[0538] The server receives the data sent from the device and stores it in a database. It then uses AI algorithms to analyze the data in real time, detect abnormalities, and assess health status. If necessary, it generates notification messages based on the analysis results and sends them to the notification system.

[0539] Examples:

[0540] The server receives 24-hour biometric data and analyzes it using an AI algorithm powered by TensorFlow. If the server detects that the user's heart rate is abnormally high during a specific time period, it generates a notification message stating, "An abnormal heart rate has been detected."

[0541] How the notification system works

[0542] The notification system receives notification information sent from the server and provides real-time feedback to the user via voice and push notifications. If an abnormality is detected, the system alerts the user and suggests specific countermeasures.

[0543] Examples:

[0544] The user's smartphone will receive a push notification that displays the message "Your heart rate is abnormally high. Please take a rest," or an audio notification will be played over the device's speaker.

[0545] Examples of prompt statements

[0546] Here are some example prompts to input to a generative AI model:

[0547] Please explain in detail how you will analyze the data from the health management device and how you will notify the user if an abnormality is detected.

[0548] The above is an embodiment of the present invention. By using this system, users can easily monitor their own health condition on a daily basis and can respond quickly when an abnormality is detected.

[0549] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0550] Step 1:

[0551] The device measures the user's biometric information.

[0552] Specifically, the device's built-in pulse sensor and body temperature sensor measure data every 10 minutes to obtain pulse rate and body temperature.

[0553] Input: User's biometric information (pulse, body temperature)

[0554] Output: Measured biological information data (e.g. pulse rate 75 beats / min, body temperature 36.5°C)

[0555] Step 2:

[0556] The device stores the measured biometric information in its internal memory.

[0557] The data storage means is used to temporarily store the biometric information.

[0558] Input: Measured biological information data

[0559] Output: Biometric data stored in internal memory

[0560] Step 3:

[0561] After the terminal accumulates a certain amount of data, it transmits the data to the server using a secure communication protocol.

[0562] Specifically, once the data in the internal memory reaches 100 data points, it is sent to a server using Bluetooth Low Energy or Wi-Fi.

[0563] Input: Biometric data stored in the internal memory

[0564] Output: Biometric data sent to the server

[0565] Step 4:

[0566] The server receives the data sent from the terminal and stores it in a database.

[0567] Specifically, after the server receives the data, it stores the data in a database such as MySQL or PostgreSQL.

[0568] Input: Biometric data sent from the device

[0569] Output: Biometric data stored in a database

[0570] Step 5:

[0571] The server analyzes the received data using AI algorithms.

[0572] Specifically, it uses TensorFlow and PyTorch to analyze data, detect outliers, and assess health status.

[0573] Input: Biometric data stored in a database

[0574] Output: Analysis results (e.g., detection of periods when heart rate is abnormally high)

[0575] Step 6:

[0576] If the server detects an abnormality based on the analysis results, it generates a notification message.

[0577] Specifically, when an abnormality is detected, a message is generated saying, "Your heart rate is abnormally high. Please take a rest."

[0578] Input: Analysis results

[0579] Output: Notification message

[0580] Step 7:

[0581] The notification system receives the notification information sent from the server and notifies the user.

[0582] Specifically, users will be notified via push notifications to their smartphones or voice notifications from the device's speaker.

[0583] Input: Notification message

[0584] Output: User notification (e.g., push notification, "Your heart rate is abnormally high. Please take a rest.")

[0585] The above are the processing steps of the program for this system and the specific operation of each step. This system is capable of monitoring the user's health condition in real time and quickly detecting and notifying abnormalities.

[0586] (Application example 1)

[0587] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0588] Conventional health management systems lacked the means to effectively monitor individuals' biometric information in real time and quickly detect and notify abnormalities. Furthermore, when an abnormality occurred, there was no means of properly notifying all relevant parties. This created the problem of being unable to quickly respond to the deterioration of staff health, particularly in brick-and-mortar stores.

[0589] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0590] In this invention, the server includes a data storage means for storing measured biometric information, a data transmission means for transmitting the stored biometric information to the server, a notification means for receiving analysis results from the server and notifying the user, and a means for the notification means to notify the administrator and the relevant user of abnormal values. This makes it possible to monitor biometric information such as pulse and body temperature of users, including staff, in real time, and to quickly notify the administrator and the relevant user if an abnormality is detected.

[0591] "User's biological information" is data that indicates a person's health condition, such as pulse rate and body temperature.

[0592] The "biological information measuring means" is a device with built-in sensors for measuring the user's pulse and body temperature.

[0593] "Data storage means" refers to internal memory or storage for temporarily storing measured biological information.

[0594] "Data transmission means" refers to a communication module or protocol for transmitting stored biometric information to a server.

[0595] The "notification means" is a function for receiving the analysis results from the server and notifying the user and administrator by voice or push notification as necessary.

[0596] The "server" is a computer system that receives, stores, and analyzes biometric information sent from the device and generates a notification if an abnormality is detected.

[0597] "Administrator" refers to the person responsible for monitoring and managing biometric information.

[0598] "Abnormal values" refer to pulse or temperature measurements that are outside the normal range.

[0599] The present invention is a system for supporting a user's daily health management. The system includes the following main components:

[0600] 1. Device: This device has built-in sensors to measure pulse and body temperature. The device periodically measures the user's biometric information and temporarily stores the data in its internal memory. This device is available in various forms, such as a wristwatch, necklace, or earring.

[0601] 2. Server: Receives biometric data sent from the device and stores it in a database. The server uses AI algorithms to analyze the data in real time and generates a notification message if an abnormal value is detected.

[0602] 3. Notification System: The notification system receives notification information sent from the server and provides feedback to users and administrators through voice notifications and push notifications.

[0603] Program processing

[0604] Terminal Programs

[0605] The device periodically collects biometric information and stores it in its internal memory. After collecting a certain amount of data, it transmits the data to a server using a secure communication protocol via a wireless communication module such as Wi-Fi or Bluetooth. This process is performed using Python and the requests library.

[0606] Server Program

[0607] The server uses a web framework such as Flask to analyze the data received from the device. The server analyzes the data stored in the database in real time and uses AI algorithms to evaluate abnormal values ​​and health status. Any abnormal values ​​detected by this algorithm are notified to the administrator and the relevant user.

[0608] Notification System Program

[0609] The notification system notifies users in real time based on the notification information received from the server. Notifications are provided as voice notifications or push notifications to smartphones, allowing users to take prompt action when an abnormality occurs.

[0610] Specific examples

[0611] Scenario: A staff member working in a store wears a necklace-type device. This device measures the staff member's pulse and body temperature every 10 minutes and sends the data to a server. The server analyzes the received data in real time and notifies the manager and the relevant staff member if an abnormality is detected.

[0612] Example prompts to input to a generative AI model:

[0613] I am designing a system to monitor the health of store staff 24 / 7. Staff will wear a necklace-type device that measures their pulse and body temperature every 10 minutes and sends the data to a server. The server will perform real-time analysis and notify managers and staff if any abnormalities are detected. The terminals will use Python to collect data, and the server will use Flask to analyze the data. Can you give me a code example for this system?

[0614] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0615] Step 1:

[0616] The device measures the user's biometric information. Specifically, the device's built-in pulse sensor and body temperature sensor measure the user's pulse and body temperature. The input is the biometric information measured by the sensor, and the output is pulse and body temperature data.

[0617] Step 2:

[0618] The device stores the measured biometric information. The measured pulse and body temperature data is temporarily stored in the device's internal memory. The input is the measured biometric data, and the output is data stored in the internal memory.

[0619] Step 3:

[0620] The device periodically transmits biometric data to the server. The device transmits the stored data to the server using Wi-Fi or Bluetooth. The input is the data stored in the internal memory, and the output is the biometric data transmitted to the server.

[0621] Step 4:

[0622] The server receives the biometric data sent from the device. The server stores the data in a database and prepares it for analysis. The input is the biometric data sent from the device, and the output is data stored in the database.

[0623] Step 5:

[0624] The server analyzes the received biometric data. The server uses an AI algorithm to analyze and detect abnormal values. The input is the biometric data stored in the database, and the output is the analysis results.

[0625] Step 6:

[0626] If the server detects an abnormal value, it generates a notification message. If the server detects an abnormal value, it generates a notification message and sends it to the notification system. The input is the analysis result, and the output is the notification message.

[0627] Step 7:

[0628] The notification system receives notification messages and notifies users and administrators. The notification system provides real-time feedback through voice or push notifications. The input is the notification message sent from the server, and the output is the notification to users and administrators.

[0629] Adding specific actions

[0630] Step 1:

[0631] The device activates the pulse and temperature sensors and performs measurements for a few seconds. During the measurement, the sensors collect pulse and temperature data from the skin surface.

[0632] Step 2:

[0633] After each measurement, the device stores the pulse and temperature data in a specific area of ​​its internal memory.

[0634] Step 3:

[0635] Every 10 minutes, the device collects the stored data in packets and sends them to a server via Wi-Fi or Bluetooth using a secure protocol.

[0636] Step 4:

[0637] The server receives data packets sent from the terminals and stores the data by creating entries in a database.

[0638] Step 5:

[0639] An AI algorithm on the server scans new entries in the database, analyzing pulse and temperature data, and if it detects any abnormalities, it stores that information in specific variables.

[0640] Step 6:

[0641] If an abnormal value is detected, the server generates a notification message for the administrator and the affected user and sends the message to the notification system.

[0642] Step 7:

[0643] The notification system analyzes the received notification messages and sends voice and push notifications to the relevant users and administrators, including specific anomalies and recommended actions.

[0644] The above is a specific processing procedure of the embodiment of the invention.

[0645] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0646] The present invention relates to a device and system for supporting daily health management of users. Specifically, the present invention provides a system that combines technology for recognizing a user's biological information, such as pulse rate and body temperature, and the user's emotions. The system includes the following main components:

[0647] 1. Terminal (device): A device that has the ability to measure biometric information and store and transmit that data. Specifically, it could be a wristwatch, necklace, or earring-type device with built-in sensors that measure pulse and body temperature, and an emotion engine that analyzes voice and facial expressions to recognize emotions.

[0648] 2. Server: A computer system that receives, analyzes, and stores data sent from the device. The server uses AI algorithms to analyze the data and notifies the user of countermeasures if an anomaly is detected. It also recommends specific actions based on the user's emotions.

[0649] 3. Notification system: A system with voice and push notification functions to provide information feedback to users.

[0650] 4. Emotion Engine: A machine learning model that analyzes the user's voice and facial expression data to recognize the user's emotions.

[0651] System Program Processing

[0652] The program in this system is designed to fulfill the roles of terminal, server, notification system, and emotion engine. Each process is explained below.

[0653] Terminal handling

[0654] The device periodically measures the user's pulse and body temperature and stores the data in its internal memory. It also uses a sound sensor and camera to collect the user's voice and facial expression data, and uses an emotion engine to recognize emotions. The recognized emotion data is stored along with biometric information, and once a certain amount of data has been collected, it is sent to a server using a secure communication protocol.

[0655] Examples:

[0656] When the user wears the necklace-type device, it measures their pulse and body temperature every 10 minutes and stores the data in its internal memory. Additionally, when the user speaks, the audio sensor collects their voice, and the camera simultaneously captures facial expression data. If the emotion engine detects "stress," it stores this information along with their biometric information and sends it to the server as appropriate.

[0657] Server Processing

[0658] The server analyzes the data received from the device and evaluates abnormal values ​​and health status. It also analyzes the emotion data recognized by the emotion engine and evaluates the correlation between the user's physiological changes and emotions. Furthermore, if an abnormality is detected or a specific emotion is recognized, it generates a warning message and sends it to the notification system.

[0659] Examples:

[0660] The server receives 24-hour biometric and emotional data and analyzes it using an AI algorithm. As a result, it discovers that the user's heart rate is abnormally high during a specific time period, and that the emotion of "stress" is frequently recognized at that time. The server generates a message saying, "Stress tends to increase during this time period. We recommend taking deep breaths," and sends it to the device.

[0661] Notification System Processing

[0662] The notification system notifies users in real time based on notification information sent from the server. If an abnormality is detected, the system alerts the user and suggests specific countermeasures. It also prompts the user to take appropriate action based on emotional data.

[0663] Examples:

[0664] The server generates a message saying "Your stress is rising. Please take a deep breath" and sends it to the device. The device then notifies the user with a voice message saying "Your stress is rising. Please take a deep breath and relax."

[0665] Emotion engine processing

[0666] The emotion engine analyzes the user's voice and facial expression data to recognize specific emotions. For example, it can detect emotions such as "happiness," "sadness," and "anger" from voice characteristics and facial changes. The recognized emotions are stored along with biometric data and sent to the server.

[0667] Examples:

[0668] The user wears the necklace-type device, and the emotion engine analyzes voice and facial expression data during conversation to recognize "happiness." This information, along with pulse and body temperature data, is stored and sent to the server at the appropriate time.

[0669] The above is an embodiment of the present invention. By using this system, users can monitor their own health condition and emotional changes in real time and take appropriate measures when necessary.

[0670] The processing flow will be explained below.

[0671] Step 1:

[0672] The device initializes the sensors and prepares them to measure the user's pulse and temperature. This sensor initialization occurs when the device is turned on.

[0673] Step 2:

[0674] The device periodically (e.g., every 10 minutes) measures the user's pulse and body temperature. After the measurement, the data obtained from the sensors is temporarily stored in the internal memory.

[0675] Step 3:

[0676] The device uses a sound sensor and a camera to collect the user's voice and facial expression data, which is then processed by an emotion engine to recognize the user's emotions in real time.

[0677] Step 4:

[0678] The device stores the recognized emotion data along with biometric data in its internal memory, recording, for example, the user's stress level or happiness level.

[0679] Step 5:

[0680] When the data stored in the device's internal memory reaches a certain amount (e.g., 30 points), the device prepares to send the data. When preparing to send the data, the data is encrypted.

[0681] Step 6:

[0682] The device sends encrypted data to the server using a secure communication protocol (e.g., HTTPS).

[0683] Step 7:

[0684] The server stores the data received from the device in a database, then extracts a sample of the data and performs an initial analysis using an AI algorithm.

[0685] Step 8:

[0686] The server uses AI algorithms to analyze the data in detail, detect abnormalities, and assess the user's health. During this process, it identifies abnormal heart rate and body temperature fluctuations. It also analyzes emotional data to recognize changes in emotions.

[0687] Step 9:

[0688] If the server detects an anomaly based on the analysis results, it generates a warning message that includes details of the anomaly and appropriate countermeasures. It also generates a message that suggests specific actions based on the user's emotions.

[0689] Step 10:

[0690] The server sends the generated warning message to the terminal, using real-time communication.

[0691] Step 11:

[0692] The device notifies the user of the warning message received from the server. Notification methods include voice notification and push notification. For example, a message such as "Your heart rate is abnormally high. Please take a break and relax" or "Stress tends to increase at this time of day. We recommend taking deep breaths" may be sent.

[0693] Step 12:

[0694] The user checks the notification and takes necessary action, such as taking a deep breath, taking a break, or seeking medical attention.

[0695] Step 13:

[0696] The device then measures biometric and emotional data again, repeating this process and sending the data to the server each time, continuously monitoring the user's health.

[0697] Step 14:

[0698] The server analyzes the data over a long period of time to identify trends in the user's health and generates regular health advice based on the analysis results.

[0699] Step 15:

[0700] The server sends the generated health advice to the device, and the device notifies the user of the advice. For example, the device may notify the user of the advice, saying, "We recommend walking 20 minutes every day."

[0701] Step 16:

[0702] The user receives the advice, decides whether to incorporate it into their daily life, and takes the necessary action.

[0703] Example 2

[0704] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0705] In modern society, many people suffer from stress and health problems, but there are limited systems that can monitor these conditions in real time and suggest timely solutions. Conventional health management devices primarily focus on measuring biometric information and lack the ability to simultaneously recognize and provide feedback on the user's emotional state. This often prevents users from effectively managing their health, delaying early detection and countermeasures. To address these issues, the present invention provides a system that monitors and analyzes a user's biometric information and emotional state in real time and provides appropriate feedback.

[0706] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0707] In this invention, the server includes a measuring means for measuring the user's biometric information, a storage means for storing the measured biometric information, a data transmission means for transmitting the stored biometric information to the server, a notification means for receiving analysis results from the server and notifying the user, an emotion recognition means for analyzing the user's voice data and facial expression data and recognizing emotions, a means for storing the recognized emotion data together with the biometric information and transmitting it to the server, a means for the server to analyze the received data and notify the user of how to deal with any abnormalities detected, and a notification system means for notifying the user in real time based on notification messages from the server. This enables the user to monitor their own health and emotional state in real time and take prompt action if an abnormality is detected.

[0708] "Biometric information" is data that indicates the physical condition of the user, such as pulse, body temperature, and blood pressure.

[0709] "Measurement means" refers to sensors and devices used to acquire biometric information from a user.

[0710] "Storage means" refers to a storage device for storing measured biological information.

[0711] "Data transmission means" refers to a communication function for transferring stored biometric information to a server.

[0712] The "server" is a central processing system that analyzes and stores data sent from the measurement means and storage means, and provides feedback to the user as needed.

[0713] "Notification means" refers to a means for notifying the user of analysis results and feedback from the server, and includes, for example, voice notification and push notification.

[0714] "Voice data" is digital information that is a recording of the user's voice.

[0715] "Facial expression data" is image data of the user's facial expression captured by a camera.

[0716] "Emotion recognition means" refers to a function that analyzes voice data and facial expression data to identify the user's emotions.

[0717] "Abnormal" refers to a significant deviation from normal biometric or emotional states, which may indicate health risks or mental health problems.

[0718] "Countermeasures" refers to specific actions or advice that a user should take when an abnormality is detected.

[0719] "Real-time notification" is a function that instantly provides information to users based on data analyzed by the server.

[0720] The present invention relates to a device and system for supporting daily health management of users. Specifically, the system combines technology for recognizing a user's biological information, such as pulse and body temperature, and the user's emotions. The system includes the following main components:

[0721] 1. Data collection by device

[0722] The device periodically measures the user's pulse and body temperature and stores the data in its internal memory. It also uses a sound sensor and camera to collect the user's voice and facial expression data, and uses an emotion engine to recognize emotions. The recognized emotion data is stored along with biometric information, and once a certain amount of data has been collected, it is sent to a server using a secure communication protocol (e.g., HTTPS).

[0723] Specifically, when a user wears the necklace-type device, it measures their pulse and body temperature every 10 minutes and stores the data in its internal memory. When the user speaks, the audio sensor collects voice data, and the camera captures facial expression data in real time. If the emotion engine recognizes "stress," it stores that information along with biometric information and sends it to a server as appropriate.

[0724] 2. Data reception and analysis by the server

[0725] The server receives the biometric and emotional data sent from the device and analyzes it using an AI algorithm (e.g., TensorFlow model), detecting outliers and evaluating the correlation between emotions and biometric data.

[0726] For example, if the server receives 24-hour biometric and emotional data and analyzes it using an AI algorithm, and finds that the user's heart rate is abnormally high during a particular time period and that they frequently express feelings of "stress," this abnormal data will be detected.

[0727] 3. Server-generated action recommendations

[0728] The server generates notification messages for users based on the analysis results. If an abnormal value is detected or a specific emotion is recognized, a warning message is created and sent to the notification system.

[0729] For example, the server generates a message saying, "Stress tends to increase at this time of day. We recommend taking deep breaths," and sends it to a notification system.

[0730] 4. Notification via the notification system

[0731] The notification system notifies users in real time based on messages sent from the server, suggests specific countermeasures, and encourages necessary actions.

[0732] For example, if the notification system receives the message "Your stress levels are rising. Please take a deep breath," the device will relay that message to the user via voice notification, instructing them, "This is a time when stress levels are rising. Please take a deep breath and relax."

[0733] 5. User Response

[0734] Based on the notifications from the notification system, the user can take appropriate actions, such as taking deep breaths, to improve their mood or health.

[0735] When the user receives the notification message, he or she should follow the advice and take several deep breaths to relax mentally.

[0736] 6. Feedback rating by the server

[0737] The server continuously monitors user responses, analyzes newly acquired data, evaluates the effectiveness of the feedback, and adjusts notification messages and recommended actions as needed.

[0738] For example, if the server reanalyzes the user's biometric data and the heart rate returns to the normal range after taking a deep breath, it will evaluate the action as effective and recommend continuing to use it in the future.Similarly, if no effect is observed, new measures will be considered.

[0739] Prompt Sentence Examples

[0740] Below are some example prompts to be input to the generative AI model:

[0741] "A user is wearing a necklace-like device. The device measures their pulse and temperature every 10 minutes and collects audio and facial expression data. The system identifies that the user is experiencing stress. Explain how this information can be sent to a server and an appropriate notification can be provided to the user."

[0742] The above is an embodiment of the present invention. By using this system, users can monitor their own health condition and emotional changes in real time and take appropriate measures when necessary.

[0743] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0744] Step 1: Measurement

[0745] The device measures the user's biometric information. Specifically, it uses sensors to measure pulse and body temperature every 10 minutes, and uses an audio sensor and camera to collect the user's voice data and facial expression data in real time.

[0746] Input: User's pulse, body temperature, voice, facial expression

[0747] Data processing / calculation: pulse and temperature sensor readings, voice and facial expression capture

[0748] Output: Measured biometric information, acquired voice data, facial expression data

[0749] Step 2: Save

[0750] The device stores the measured biometric information and collected emotional data in its internal memory.

[0751] Input: Measured biometric information, collected voice data, facial expression data

[0752] Data processing / calculation: Data storage processing

[0753] Output: Data stored in the internal memory

[0754] Step 3: Send

[0755] Once a certain amount of data has been collected, the terminal transmits this data to a server using a secure communication protocol (e.g., HTTPS).

[0756] Input: Data stored in the internal memory

[0757] Data processing / calculation: Packetizing data, sending data using HTTPS

[0758] Output: Biometric and emotional data sent to the server

[0759] Step 4: Data reception and analysis

[0760] The server receives biometric and emotional data from the device and analyzes it using AI algorithms to detect abnormalities and evaluate the correlation between emotions and biometric data.

[0761] Input: Biometric data and emotional data sent from the device

[0762] Data processing / calculation: Data analysis using AI algorithms, outlier detection, and emotional data analysis

[0763] Output: Analysis results, anomaly detection results

[0764] Step 5: Generate action recommendations

[0765] The server generates a notification message for the user based on the analysis results. If an abnormal value is detected or a specific emotion is recognized, a warning message is created and sent to the notification system.

[0766] Input: Analysis results, anomaly detection results

[0767] Data processing / calculation: Notification message generation

[0768] Output: Message sent to the notification system

[0769] Step 6: Notification

[0770] The notification system notifies users in real time based on messages sent from the server, suggests specific countermeasures, and encourages necessary actions.

[0771] Input: The message sent from the server

[0772] Data processing / calculation: Message analysis, generation of voice or push notifications

[0773] Output: User notification

[0774] Step 7: User Action

[0775] Based on the notification from the notification system, the user takes appropriate action, for example, taking deep breaths to try to improve their mood or health.

[0776] Input: Notification message from the notification system

[0777] Data processing / calculation: Actions based on notifications

[0778] Output: User behavior, improved health status

[0779] Step 8: Feedback evaluation

[0780] The server continuously monitors user responses, analyzes newly acquired data, evaluates the effectiveness of the feedback, and adjusts notification messages and recommended actions as needed.

[0781] Input: New biometric data and emotional data from the user

[0782] Data processing / calculation: Data analysis, evaluation of feedback effects

[0783] Output: Evaluation results, tailored notification messages and recommended actions

[0784] The above is the specific processing flow of this system. We have explained in detail how the input data is processed and analyzed at each step, and how it is provided as specific output.

[0785] (Application example 2)

[0786] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0787] Conventional health management systems lack the means to monitor users' health status in real time while they are in the vehicle and to respond quickly if an abnormality occurs. Furthermore, in emergencies, appropriate responses may be delayed, making it difficult to ensure user safety. This creates a need for a means to effectively manage user health risks, especially in autonomous vehicles.

[0788] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting health information and emotional information of the user using sensors installed in the vehicle, means for analyzing the collected health information and emotional information in real time and immediately transmitting the information to the server if an abnormality is detected, means for automatically stopping the vehicle in a safe place if an abnormality is detected, and means for automatically contacting an emergency contact. This makes it possible to respond quickly to the user's health condition or an emergency situation.

[0789] The "biological information measuring means" is a device for measuring biological information such as the pulse rate and body temperature of the user.

[0790] The "data storage means" is a storage device for recording measured biometric information and emotional information.

[0791] The "data transmission means" is a communication device for transmitting the stored biometric information and emotional information to the server.

[0792] The "notification means" is a device for notifying the user of the analysis results from the server.

[0793] A "sensor" is a device placed in a vehicle that measures the user's health and emotional information.

[0794] "Means for real-time analysis" refers to a system for instantly analyzing collected biometric and emotional information.

[0795] The "means for transmitting information to a server when an abnormality is detected" is a device that has the function of quickly transmitting information about an abnormal value to a server when that value is detected.

[0796] "Means for stopping a vehicle in a safe location" refers to a system that moves an autonomous vehicle to a safe location and stops it in an emergency.

[0797] The "means for automatically contacting emergency contacts" is a device that automatically contacts a pre-set emergency contact when an abnormality is detected.

[0798] The present invention relates to a health management system that monitors the health status and emotions of a user in a vehicle in real time and provides a prompt response if an abnormality is detected. This system is composed of a biological information measurement means, a data storage means, a data transmission means, a notification means, and a safety management means for the vehicle.

[0799] System hardware and software configuration

[0800] The system hardware includes the following major components:

[0801] Biometric measurement means: Sensors placed inside the vehicle (e.g., heart rate sensors built into seat belts, interior temperature sensors) measure the user's pulse and body temperature in real time.

[0802] Data storage means: A memory device for temporarily storing measured biometric and emotional information.

[0803] Data transmission means: A communication module for transmitting the measured data to the server via a secure communication protocol (e.g., HTTPS).

[0804] Notification means: A system that receives notification information sent from the server and notifies the user via the vehicle's infotainment system or the user's smartphone.

[0805] In-vehicle safety management measures: an autonomous driving system that automatically stops the vehicle in a safe location if an abnormality is detected, and a communication system that automatically contacts designated contacts in the event of an emergency.

[0806] The system software configuration includes the following components:

[0807] Real-time data collection module: Collects data from the biological information measurement means in real time and stores it in the data storage means.

[0808] Data analysis module: Runs on the server and uses AI algorithms to analyze the transmitted biometric and emotional information. If an abnormality is detected, it generates a warning notification and countermeasures.

[0809] Notification management module: Sends notification information from the server to the terminal and notifies the user of appropriate measures.

[0810] Emergency response module: Links with the vehicle's safety management measures, automatically stops the vehicle in the event of an abnormality, and makes emergency contact if necessary.

[0811] Example of operation

[0812] When a user gets into an autonomous vehicle, the biometric information measurement means periodically measures the user's pulse and body temperature. This data is stored in the data storage means in real time and transmitted to the server via the data transmission means. The server uses an AI algorithm to analyze the data, and if an abnormality is detected, the notification management module sends a voice or push notification to the user. Furthermore, if a serious abnormality is detected, the safety management means within the vehicle is automatically activated, stopping the vehicle in a safe location and making an emergency call.

[0813] Prompt Sentence Examples

[0814] Below are some examples of specific prompt sentences for this system.

[0815] markdown

[0816] Use case: Vehicle Health Monitoring System

[0817] Requirements:

[0818] 1. Monitor real-time heart rate, body temperature, and user emotions using in-car sensors.

[0819] 2. Analyze collected data and send to centralized server for further processing.

[0820] 3. Alert the user with voice messages or display notifications on the Infotainment system if any abnormalities are detected.

[0821] ----

[0822] User Scenario:

[0823] A user is on a long drive. The system monitors the user's vital signs every 10 minutes. At 3 PM, the user's heart rate suddenly spikes and the emotion engine detects stress. The system alerts the user through the car's infotainment system, advising them to take a break and relax. If the user does not respond or if the signs of stress persist, the system automatically contacts emergency services.

[0824] The system of the present invention effectively manages the safety and health of users by monitoring their health status in real time and taking appropriate measures quickly and automatically if an abnormality is detected.

[0825] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0826] Step 1:

[0827] Sensors installed in the vehicle measure the user's biometric information (pulse, body temperature) and emotional information in real time. Heart rate and body temperature data, as well as voice and sidelong glance data to identify emotions, are required as input. The measured data is obtained as output.

[0828] Step 2:

[0829] The device temporarily stores the measured data in a data storage means. The input requires biometric and emotional information data provided by the sensors. The stored data is obtained as the output.

[0830] Step 3:

[0831] The device sends the stored data to the server using a secure communication protocol (e.g. HTTPS). The stored data is required as input. The data sent to the server is obtained as output.

[0832] Step 4:

[0833] The server analyzes the received data using AI algorithms to detect abnormal values ​​and dangerous health conditions. The input requires the transmitted biometric and emotional data. The output is the analysis results.

[0834] Step 5:

[0835] If the server detects an anomaly based on the analysis results, it generates a warning message for the user. The analysis result data is required as input, and the generated warning message is obtained as output.

[0836] Step 6:

[0837] The server sends the generated alert message to the user's terminal, the vehicle's infotainment system, or the user's smartphone via a notification means. The alert message is required as input, and the message notified to the user is obtained as output.

[0838] Step 7:

[0839] If a serious abnormality is detected, the vehicle's autonomous driving system will be activated and stop the vehicle in a safe place. Information on the abnormality detection is required as input, and the stopped vehicle is obtained as output.

[0840] Step 8:

[0841] Furthermore, in the event of an emergency, the server automatically contacts the emergency contacts that have been set up. Emergency contact information and anomaly detection information are required as input. The output indicates that the emergency contact has been completed.

[0842] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0843] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0844] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0845] [Third embodiment]

[0846] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0847] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0848] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0849] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0850] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0851] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0852] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0853] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0854] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0855] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0856] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0857] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0858] This invention relates to a device and system for supporting daily health management of users. Specifically, we provide a system that measures the user's biological information such as pulse and body temperature in real time, transmits the data to a server for analysis and storage, and notifies the user as necessary.

[0859] The system includes the following major components:

[0860] 1. Terminal (device): A device that has the ability to measure biometric information and store and transmit the data. Specifically, it can be a wristwatch, necklace, or earring-type device with built-in sensors that measure pulse and body temperature.

[0861] 2. Server: A computer system that receives, analyzes, and stores biometric data sent from the device. It analyzes the data using AI algorithms and notifies the user of countermeasures if an abnormality is detected.

[0862] 3. Notification system: A system with voice and push notification functions to provide information feedback to users.

[0863] System Overview

[0864] Device behavior

[0865] The device has built-in sensors that periodically measure the user's pulse and body temperature, and uses these sensors to collect the user's biological information in real time. The collected data is temporarily stored in the internal memory.

[0866] Examples:

[0867] When the user wears the necklace, the device measures the pulse and body temperature every 10 minutes, stores the data in its internal memory, and transmits the data to a server at appropriate intervals.

[0868] Server Operation

[0869] The server receives the data sent from the device, stores it in a database, and then uses AI algorithms to analyze the data in real time to detect abnormalities and assess health status.

[0870] Examples:

[0871] The server receives 24-hour biometric data and analyzes it with an AI algorithm. If the server detects that the user's heart rate is abnormally high during a specific time period, it generates a notification to report the abnormality.

[0872] How the notification system works

[0873] The notification system receives notification information sent from the server and provides real-time feedback to the user via voice or push notifications. If an abnormality is detected, the system alerts the user and suggests specific countermeasures.

[0874] Examples:

[0875] The server detects an abnormal heart rate and sends that information to the device, which then sends a voice notification to the user saying, "Your heart rate is abnormally high. Please take a break and take a deep breath."

[0876] Program processing

[0877] The programs in this system are designed to fulfill the roles of terminal, server, and notification system. Each process is explained below in natural language.

[0878] Terminal Programs

[0879] The device periodically collects the user's biometric information and stores it in its internal memory. After collecting a certain amount of data, it transmits it to a server using a secure communication protocol.

[0880] Server Program

[0881] The server analyzes the data received from the device, evaluates abnormal values ​​and health status, and then generates notification messages as needed and sends them to the notification system.

[0882] Notification System Program

[0883] The notification system sends real-time notifications to users based on the notification information received from the server, providing appropriate warnings and countermeasures.

[0884] The above is an embodiment of the present invention. By using this system, users can easily monitor their own health condition on a daily basis and can respond quickly if an abnormality is detected.

[0885] The processing flow will be explained below.

[0886] Step 1:

[0887] The device initializes the sensors and prepares them to measure the user's pulse and temperature. This sensor initialization occurs when the device is turned on.

[0888] Step 2:

[0889] The device periodically (e.g., every 10 minutes) measures the user's pulse and body temperature. After the measurement, the data obtained from the sensors is temporarily stored in the internal memory.

[0890] Step 3:

[0891] When the data stored in the device's internal memory reaches a certain amount (e.g., 30 points), the device prepares to send the data. When preparing to send the data, the data is encrypted.

[0892] Step 4:

[0893] The device sends encrypted data to the server using a secure communication protocol (e.g., HTTPS).

[0894] Step 5:

[0895] The server stores the data received from the device in a database, then extracts a sample of the data and performs an initial analysis using an AI algorithm.

[0896] Step 6:

[0897] The server then uses AI algorithms to analyze the data in detail, detect abnormalities, and assess the patient's health, identifying abnormal heart rate and body temperature fluctuations.

[0898] Step 7:

[0899] If the server detects an anomaly based on the analysis results, it generates a warning message that includes details of the anomaly and appropriate countermeasures.

[0900] Step 8:

[0901] The server sends the generated warning message to the terminal, using real-time communication.

[0902] Step 9:

[0903] The device notifies the user of the warning message received from the server. The notification method is audio notification or push notification. For example, a message such as "Your heart rate is abnormally high. Please take a break and relax" may be sent.

[0904] Step 10:

[0905] The user checks the notification and takes necessary action, such as taking a deep breath, taking a break, or seeking medical attention.

[0906] Step 11:

[0907] After the user responds, the device measures again and sends the collected data to the server to continuously monitor the user's health condition.

[0908] Step 12:

[0909] The server periodically analyzes the collected data over the long term to evaluate the user's health trends, and generates regular health advice based on the evaluation results.

[0910] Step 13:

[0911] The server sends the generated health advice to the device, and the device notifies the user of the advice. For example, the device may notify the user of the advice, saying, "We recommend walking 20 minutes every day."

[0912] Step 14:

[0913] The user receives the advice, decides whether to incorporate it into their daily life, and takes the necessary action.

[0914] Example 1

[0915] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0916] In modern society, personal health management has become an important issue. However, many current systems are insufficient for continuously monitoring a user's health status, and in particular, they lack the means to prompt and appropriate action when an abnormality occurs. Therefore, there is a need for a system that can measure a user's biological information in real time, detect abnormalities, and provide immediate countermeasures.

[0917] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0918] In this invention, the server includes a biological information measuring means for measuring a user's biological information, a data storage means for temporarily storing the measured biological information, a data transmission means for transmitting a certain amount of data to the server after accumulating the data, an analysis means for analyzing the data received by the server using an AI algorithm, a message generation means for detecting an abnormality based on the analysis result and generating a notification message, and a notification means for notifying the user of the generated notification message. This enables real-time monitoring of biological information and rapid detection and response to abnormalities.

[0919] The term "biological information measuring means" refers to a device or sensor for measuring biological information such as the user's pulse rate and body temperature.

[0920] "Data storage means" refers to a memory or storage device for temporarily storing measured biological information.

[0921] "Data transmission means" refers to the communication protocol or device used to transmit the stored biometric information to the server.

[0922] "Analysis means" refers to the function or process of analyzing biometric information received by the server using an AI algorithm.

[0923] "Message generation means" refers to a device or process that detects an abnormality based on the analysis results and generates a message to notify the user.

[0924] The "notification means" refers to a means for notifying the user of the generated notification message, such as a voice notification or a push notification.

[0925] The term "biological information measuring means" refers to a device or sensor for measuring biological information such as the user's pulse rate and body temperature.

[0926] "Data storage means" refers to a memory or storage device for temporarily storing measured biological information.

[0927] "Data transmission means" refers to the communication protocol or device used to transmit the stored biometric information to the server.

[0928] "Analysis means" refers to the function or process of analyzing biometric information received by the server using an AI algorithm.

[0929] "Message generation means" refers to a device or process that detects an abnormality based on the analysis results and generates a message to notify the user.

[0930] The "notification means" refers to a means for notifying the user of the generated notification message, such as a voice notification or a push notification.

[0931] MODE FOR CARRYING OUT THE INVENTION

[0932] This invention relates to a device and system for supporting daily health management of users. Specifically, we provide a system that measures a user's biological information, such as pulse and body temperature, in real time, transmits the data to a server for analysis and storage, and notifies the user as needed. A specific embodiment of this system is described below.

[0933] Hardware Configuration

[0934] The present invention includes the following major components:

[0935] 1. Terminal (device): A device that has the ability to measure biometric information and store and transmit the data. Specifically, it can be a wristwatch, necklace, or earring-type device with built-in sensors that measure pulse and body temperature.

[0936] 2. Server: A computer system that receives, analyzes, and stores biometric data sent from the device. It analyzes the data using AI algorithms and notifies the user of countermeasures if an abnormality is detected.

[0937] 3. Notification system: A system with voice and push notification functions to provide information feedback to users.

[0938] Software Configuration

[0939] The device is equipped with dedicated software for measuring biometric information in real time, while the server is equipped with AI algorithms for receiving, storing, and analyzing the data, and also includes a program for generating notification messages required for the notification system.

[0940] Specific software used includes:

[0941] Database system: MySQL, PostgreSQL, etc.

[0942] AI algorithms: TensorFlow, PyTorch, etc.

[0943] Device behavior

[0944] The device has a built-in sensor that periodically measures the user's biometric information (specifically, pulse and body temperature). This sensor is used to collect the user's biometric information in real time and temporarily store it in the internal memory. Once a certain amount of data has been accumulated, the data is sent to the server using a secure communication protocol (e.g., Bluetooth Low Energy or Wi-Fi).

[0945] Examples:

[0946] When the user wears the necklace, it measures their pulse and body temperature every 10 minutes, stores the data in its internal memory, and once a certain amount of data is reached, it transmits the data to a server using Bluetooth Low Energy.

[0947] Server Operation

[0948] The server receives the data sent from the device and stores it in a database. It then uses AI algorithms to analyze the data in real time, detect abnormalities, and assess health status. If necessary, it generates notification messages based on the analysis results and sends them to the notification system.

[0949] Examples:

[0950] The server receives 24-hour biometric data and analyzes it using an AI algorithm powered by TensorFlow. If the server detects that the user's heart rate is abnormally high during a specific time period, it generates a notification message stating, "An abnormal heart rate has been detected."

[0951] How the notification system works

[0952] The notification system receives notification information sent from the server and provides real-time feedback to the user via voice and push notifications. If an abnormality is detected, the system alerts the user and suggests specific countermeasures.

[0953] Examples:

[0954] The user's smartphone will receive a push notification that displays the message "Your heart rate is abnormally high. Please take a rest," or an audio notification will be played over the device's speaker.

[0955] Examples of prompt statements

[0956] Here are some example prompts to input to a generative AI model:

[0957] Please explain in detail how you will analyze the data from the health management device and how you will notify the user if an abnormality is detected.

[0958] The above is an embodiment of the present invention. By using this system, users can easily monitor their own health condition on a daily basis and can respond quickly when an abnormality is detected.

[0959] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0960] Step 1:

[0961] The device measures the user's biometric information.

[0962] Specifically, the device's built-in pulse sensor and body temperature sensor measure data every 10 minutes to obtain pulse rate and body temperature.

[0963] Input: User's biometric information (pulse, body temperature)

[0964] Output: Measured biological information data (e.g. pulse rate 75 beats / min, body temperature 36.5°C)

[0965] Step 2:

[0966] The device stores the measured biometric information in its internal memory.

[0967] The data storage means is used to temporarily store the biometric information.

[0968] Input: Measured biological information data

[0969] Output: Biometric data stored in internal memory

[0970] Step 3:

[0971] After the terminal accumulates a certain amount of data, it transmits the data to the server using a secure communication protocol.

[0972] Specifically, once the data in the internal memory reaches 100 data points, it is sent to a server using Bluetooth Low Energy or Wi-Fi.

[0973] Input: Biometric data stored in the internal memory

[0974] Output: Biometric data sent to the server

[0975] Step 4:

[0976] The server receives the data sent from the terminal and stores it in a database.

[0977] Specifically, after the server receives the data, it stores the data in a database such as MySQL or PostgreSQL.

[0978] Input: Biometric data sent from the device

[0979] Output: Biometric data stored in a database

[0980] Step 5:

[0981] The server analyzes the received data using AI algorithms.

[0982] Specifically, it uses TensorFlow and PyTorch to analyze data, detect outliers, and assess health status.

[0983] Input: Biometric data stored in a database

[0984] Output: Analysis results (e.g., detection of periods when heart rate is abnormally high)

[0985] Step 6:

[0986] If the server detects an abnormality based on the analysis results, it generates a notification message.

[0987] Specifically, when an abnormality is detected, a message is generated saying, "Your heart rate is abnormally high. Please take a rest."

[0988] Input: Analysis results

[0989] Output: Notification message

[0990] Step 7:

[0991] The notification system receives the notification information sent from the server and notifies the user.

[0992] Specifically, users will be notified via push notifications to their smartphones or voice notifications from the device's speaker.

[0993] Input: Notification message

[0994] Output: User notification (e.g., push notification, "Your heart rate is abnormally high. Please take a rest.")

[0995] The above are the processing steps of the program for this system and the specific operation of each step. This system is capable of monitoring the user's health condition in real time and quickly detecting and notifying abnormalities.

[0996] (Application example 1)

[0997] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0998] Conventional health management systems lacked the means to effectively monitor individuals' biometric information in real time and quickly detect and notify abnormalities. Furthermore, when an abnormality occurred, there was no means of properly notifying all relevant parties. This created the problem of being unable to quickly respond to the deterioration of staff health, particularly in brick-and-mortar stores.

[0999] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1000] In this invention, the server includes a data storage means for storing measured biometric information, a data transmission means for transmitting the stored biometric information to the server, a notification means for receiving analysis results from the server and notifying the user, and a means for the notification means to notify the administrator and the relevant user of abnormal values. This makes it possible to monitor biometric information such as pulse and body temperature of users, including staff, in real time, and to quickly notify the administrator and the relevant user if an abnormality is detected.

[1001] "User's biological information" is data that indicates a person's health condition, such as pulse rate and body temperature.

[1002] The "biological information measuring means" is a device with built-in sensors for measuring the user's pulse and body temperature.

[1003] "Data storage means" refers to internal memory or storage for temporarily storing measured biological information.

[1004] "Data transmission means" refers to a communication module or protocol for transmitting stored biometric information to a server.

[1005] The "notification means" is a function for receiving the analysis results from the server and notifying the user and administrator by voice or push notification as necessary.

[1006] The "server" is a computer system that receives, stores, and analyzes biometric information sent from the device and generates a notification if an abnormality is detected.

[1007] "Administrator" refers to the person responsible for monitoring and managing biometric information.

[1008] "Abnormal values" refer to pulse or temperature measurements that are outside the normal range.

[1009] The present invention is a system for supporting a user's daily health management. The system includes the following main components:

[1010] 1. Device: This device has built-in sensors to measure pulse and body temperature. The device periodically measures the user's biometric information and temporarily stores the data in its internal memory. This device is available in various forms, such as a wristwatch, necklace, or earring.

[1011] 2. Server: Receives biometric data sent from the device and stores it in a database. The server uses AI algorithms to analyze the data in real time and generates a notification message if an abnormal value is detected.

[1012] 3. Notification System: The notification system receives notification information sent from the server and provides feedback to users and administrators through voice notifications and push notifications.

[1013] Program processing

[1014] Terminal Programs

[1015] The device periodically collects biometric information and stores it in its internal memory. After collecting a certain amount of data, it transmits the data to a server using a secure communication protocol via a wireless communication module such as Wi-Fi or Bluetooth. This process is performed using Python and the requests library.

[1016] Server Program

[1017] The server uses a web framework such as Flask to analyze the data received from the device. The server analyzes the data stored in the database in real time and uses AI algorithms to evaluate abnormal values ​​and health status. Any abnormal values ​​detected by this algorithm are notified to the administrator and the relevant user.

[1018] Notification System Program

[1019] The notification system notifies users in real time based on the notification information received from the server. Notifications are provided as voice notifications or push notifications to smartphones, allowing users to take prompt action when an abnormality occurs.

[1020] Specific examples

[1021] Scenario: A staff member working in a store wears a necklace-type device. This device measures the staff member's pulse and body temperature every 10 minutes and sends the data to a server. The server analyzes the received data in real time and notifies the manager and the relevant staff member if an abnormality is detected.

[1022] Example prompts to input to a generative AI model:

[1023] I am designing a system to monitor the health of store staff 24 / 7. Staff will wear a necklace-type device that measures their pulse and body temperature every 10 minutes and sends the data to a server. The server will perform real-time analysis and notify managers and staff if any abnormalities are detected. The terminals will use Python to collect data, and the server will use Flask to analyze the data. Can you give me a code example for this system?

[1024] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1025] Step 1:

[1026] The device measures the user's biometric information. Specifically, the device's built-in pulse sensor and body temperature sensor measure the user's pulse and body temperature. The input is the biometric information measured by the sensor, and the output is pulse and body temperature data.

[1027] Step 2:

[1028] The device stores the measured biometric information. The measured pulse and body temperature data is temporarily stored in the device's internal memory. The input is the measured biometric data, and the output is data stored in the internal memory.

[1029] Step 3:

[1030] The device periodically transmits biometric data to the server. The device transmits the stored data to the server using Wi-Fi or Bluetooth. The input is the data stored in the internal memory, and the output is the biometric data transmitted to the server.

[1031] Step 4:

[1032] The server receives the biometric data sent from the device. The server stores the data in a database and prepares it for analysis. The input is the biometric data sent from the device, and the output is data stored in the database.

[1033] Step 5:

[1034] The server analyzes the received biometric data. The server uses an AI algorithm to analyze and detect abnormal values. The input is the biometric data stored in the database, and the output is the analysis results.

[1035] Step 6:

[1036] If the server detects an abnormal value, it generates a notification message. If the server detects an abnormal value, it generates a notification message and sends it to the notification system. The input is the analysis result, and the output is the notification message.

[1037] Step 7:

[1038] The notification system receives notification messages and notifies users and administrators. The notification system provides real-time feedback through voice or push notifications. The input is the notification message sent from the server, and the output is the notification to users and administrators.

[1039] Adding specific actions

[1040] Step 1:

[1041] The device activates the pulse and temperature sensors and performs measurements for a few seconds. During the measurement, the sensors collect pulse and temperature data from the skin surface.

[1042] Step 2:

[1043] After each measurement, the device stores the pulse and temperature data in a specific area of ​​its internal memory.

[1044] Step 3:

[1045] Every 10 minutes, the device collects the stored data in packets and sends them to a server via Wi-Fi or Bluetooth using a secure protocol.

[1046] Step 4:

[1047] The server receives data packets sent from the terminals and stores the data by creating entries in a database.

[1048] Step 5:

[1049] An AI algorithm on the server scans new entries in the database, analyzing pulse and temperature data, and if it detects any abnormalities, it stores that information in specific variables.

[1050] Step 6:

[1051] If an abnormal value is detected, the server generates a notification message for the administrator and the affected user and sends the message to the notification system.

[1052] Step 7:

[1053] The notification system analyzes the received notification messages and sends voice and push notifications to the relevant users and administrators, including specific anomalies and recommended actions.

[1054] The above is a specific processing procedure of the embodiment of the invention.

[1055] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1056] The present invention relates to a device and system for supporting daily health management of users. Specifically, the present invention provides a system that combines technology for recognizing a user's biological information, such as pulse rate and body temperature, and the user's emotions. The system includes the following main components:

[1057] 1. Terminal (device): A device that has the ability to measure biometric information and store and transmit that data. Specifically, it could be a wristwatch, necklace, or earring-type device with built-in sensors that measure pulse and body temperature, and an emotion engine that analyzes voice and facial expressions to recognize emotions.

[1058] 2. Server: A computer system that receives, analyzes, and stores data sent from the device. The server uses AI algorithms to analyze the data and notifies the user of countermeasures if an anomaly is detected. It also recommends specific actions based on the user's emotions.

[1059] 3. Notification system: A system with voice and push notification functions to provide information feedback to users.

[1060] 4. Emotion Engine: A machine learning model that analyzes the user's voice and facial expression data to recognize the user's emotions.

[1061] System Program Processing

[1062] The program in this system is designed to fulfill the roles of terminal, server, notification system, and emotion engine. Each process is explained below.

[1063] Terminal handling

[1064] The device periodically measures the user's pulse and body temperature and stores the data in its internal memory. It also uses a sound sensor and camera to collect the user's voice and facial expression data, and uses an emotion engine to recognize emotions. The recognized emotion data is stored along with biometric information, and once a certain amount of data has been collected, it is sent to a server using a secure communication protocol.

[1065] Examples:

[1066] When the user wears the necklace-type device, it measures their pulse and body temperature every 10 minutes and stores the data in its internal memory. Additionally, when the user speaks, the audio sensor collects their voice, and the camera simultaneously captures facial expression data. If the emotion engine detects "stress," it stores this information along with their biometric information and sends it to the server as appropriate.

[1067] Server Processing

[1068] The server analyzes the data received from the device and evaluates abnormal values ​​and health status. It also analyzes the emotion data recognized by the emotion engine and evaluates the correlation between the user's physiological changes and emotions. Furthermore, if an abnormality is detected or a specific emotion is recognized, it generates a warning message and sends it to the notification system.

[1069] Examples:

[1070] The server receives 24-hour biometric and emotional data and analyzes it using an AI algorithm. As a result, it discovers that the user's heart rate is abnormally high during a specific time period, and that the emotion of "stress" is frequently recognized at that time. The server generates a message saying, "Stress tends to increase during this time period. We recommend taking deep breaths," and sends it to the device.

[1071] Notification System Processing

[1072] The notification system notifies users in real time based on notification information sent from the server. If an abnormality is detected, the system alerts the user and suggests specific countermeasures. It also prompts the user to take appropriate action based on emotional data.

[1073] Examples:

[1074] The server generates a message saying "Your stress is rising. Please take a deep breath" and sends it to the device. The device then notifies the user with a voice message saying "Your stress is rising. Please take a deep breath and relax."

[1075] Emotion engine processing

[1076] The emotion engine analyzes the user's voice and facial expression data to recognize specific emotions. For example, it can detect emotions such as "happiness," "sadness," and "anger" from voice characteristics and facial changes. The recognized emotions are stored along with biometric data and sent to the server.

[1077] Examples:

[1078] The user wears the necklace-type device, and the emotion engine analyzes voice and facial expression data during conversation to recognize "happiness." This information, along with pulse and body temperature data, is stored and sent to the server at the appropriate time.

[1079] The above is an embodiment of the present invention. By using this system, users can monitor their own health condition and emotional changes in real time and take appropriate measures when necessary.

[1080] The processing flow will be explained below.

[1081] Step 1:

[1082] The device initializes the sensors and prepares them to measure the user's pulse and temperature. This sensor initialization occurs when the device is turned on.

[1083] Step 2:

[1084] The device periodically (e.g., every 10 minutes) measures the user's pulse and body temperature. After the measurement, the data obtained from the sensors is temporarily stored in the internal memory.

[1085] Step 3:

[1086] The device uses a sound sensor and a camera to collect the user's voice and facial expression data, which is then processed by an emotion engine to recognize the user's emotions in real time.

[1087] Step 4:

[1088] The device stores the recognized emotion data along with biometric data in its internal memory, recording, for example, the user's stress level or happiness level.

[1089] Step 5:

[1090] When the data stored in the device's internal memory reaches a certain amount (e.g., 30 points), the device prepares to send the data. When preparing to send the data, the data is encrypted.

[1091] Step 6:

[1092] The device sends encrypted data to the server using a secure communication protocol (e.g., HTTPS).

[1093] Step 7:

[1094] The server stores the data received from the device in a database, then extracts a sample of the data and performs an initial analysis using an AI algorithm.

[1095] Step 8:

[1096] The server uses AI algorithms to analyze the data in detail, detect abnormalities, and assess the user's health. During this process, it identifies abnormal heart rate and body temperature fluctuations. It also analyzes emotional data to recognize changes in emotions.

[1097] Step 9:

[1098] If the server detects an anomaly based on the analysis results, it generates a warning message that includes details of the anomaly and appropriate countermeasures. It also generates a message that suggests specific actions based on the user's emotions.

[1099] Step 10:

[1100] The server sends the generated warning message to the terminal, using real-time communication.

[1101] Step 11:

[1102] The device notifies the user of the warning message received from the server. Notification methods include voice notification and push notification. For example, a message such as "Your heart rate is abnormally high. Please take a break and relax" or "Stress tends to increase at this time of day. We recommend taking deep breaths" may be sent.

[1103] Step 12:

[1104] The user checks the notification and takes necessary action, such as taking a deep breath, taking a break, or seeking medical attention.

[1105] Step 13:

[1106] The device then measures biometric and emotional data again, repeating this process and sending the data to the server each time, continuously monitoring the user's health.

[1107] Step 14:

[1108] The server analyzes the data over a long period of time to identify trends in the user's health and generates regular health advice based on the analysis results.

[1109] Step 15:

[1110] The server sends the generated health advice to the device, and the device notifies the user of the advice. For example, the device may notify the user of the advice, saying, "We recommend walking 20 minutes every day."

[1111] Step 16:

[1112] The user receives the advice, decides whether to incorporate it into their daily life, and takes the necessary action.

[1113] Example 2

[1114] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1115] In modern society, many people suffer from stress and health problems, but there are limited systems that can monitor these conditions in real time and suggest timely solutions. Conventional health management devices primarily focus on measuring biometric information and lack the ability to simultaneously recognize and provide feedback on the user's emotional state. This often prevents users from effectively managing their health, delaying early detection and countermeasures. To address these issues, the present invention provides a system that monitors and analyzes a user's biometric information and emotional state in real time and provides appropriate feedback.

[1116] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1117] In this invention, the server includes a measuring means for measuring the user's biometric information, a storage means for storing the measured biometric information, a data transmission means for transmitting the stored biometric information to the server, a notification means for receiving analysis results from the server and notifying the user, an emotion recognition means for analyzing the user's voice data and facial expression data and recognizing emotions, a means for storing the recognized emotion data together with the biometric information and transmitting it to the server, a means for the server to analyze the received data and notify the user of how to deal with any abnormalities detected, and a notification system means for notifying the user in real time based on notification messages from the server. This enables the user to monitor their own health and emotional state in real time and take prompt action if an abnormality is detected.

[1118] "Biometric information" is data that indicates the physical condition of the user, such as pulse, body temperature, and blood pressure.

[1119] "Measurement means" refers to sensors and devices used to acquire biometric information from a user.

[1120] "Storage means" refers to a storage device for storing measured biological information.

[1121] "Data transmission means" refers to a communication function for transferring stored biometric information to a server.

[1122] The "server" is a central processing system that analyzes and stores data sent from the measurement means and storage means, and provides feedback to the user as needed.

[1123] "Notification means" refers to a means for notifying the user of analysis results and feedback from the server, and includes, for example, voice notification and push notification.

[1124] "Voice data" is digital information that is a recording of the user's voice.

[1125] "Facial expression data" is image data of the user's facial expression captured by a camera.

[1126] "Emotion recognition means" refers to a function that analyzes voice data and facial expression data to identify the user's emotions.

[1127] "Abnormal" refers to a significant deviation from normal biometric or emotional states, which may indicate health risks or mental health problems.

[1128] "Countermeasures" refers to specific actions or advice that a user should take when an abnormality is detected.

[1129] "Real-time notification" is a function that instantly provides information to users based on data analyzed by the server.

[1130] The present invention relates to a device and system for supporting daily health management of users. Specifically, the present invention provides a system that combines technology for recognizing a user's biological information, such as pulse rate and body temperature, and the user's emotions. The system includes the following main components:

[1131] 1. Data collection by device

[1132] The device periodically measures the user's pulse and body temperature and stores the data in its internal memory. It also uses a sound sensor and camera to collect the user's voice and facial expression data, and uses an emotion engine to recognize emotions. The recognized emotion data is stored along with biometric information, and once a certain amount of data has been collected, it is sent to a server using a secure communication protocol (e.g., HTTPS).

[1133] Specifically, when a user wears the necklace-type device, it measures their pulse and body temperature every 10 minutes and stores the data in its internal memory. When the user speaks, the audio sensor collects voice data, and the camera captures facial expression data in real time. If the emotion engine recognizes "stress," it stores that information along with biometric information and sends it to a server as appropriate.

[1134] 2. Data reception and analysis by the server

[1135] The server receives the biometric and emotional data sent from the device and analyzes it using an AI algorithm (e.g., TensorFlow model), detecting outliers and evaluating the correlation between emotions and biometric data.

[1136] For example, if the server receives 24-hour biometric and emotional data and analyzes it using an AI algorithm, and finds that the user's heart rate is abnormally high during a particular time period and that the user frequently expresses feelings of "stress," this abnormal data will be detected.

[1137] 3. Server-generated action recommendations

[1138] The server generates a notification message for the user based on the analysis results. If an abnormal value is detected or a specific emotion is recognized, a warning message is created and sent to the notification system.

[1139] For example, the server generates a message saying, "Stress tends to increase at this time of day. We recommend taking deep breaths," and sends it to a notification system.

[1140] 4. Notification via the notification system

[1141] The notification system notifies users in real time based on messages sent from the server, suggests specific countermeasures, and encourages necessary actions.

[1142] For example, if the notification system receives the message "Your stress levels are rising. Please take a deep breath," the device will relay that message to the user via voice notification, instructing them, "This is a time when stress levels are rising. Please take a deep breath and relax."

[1143] 5. User Response

[1144] Based on the notifications from the notification system, the user can take appropriate actions, such as taking deep breaths, to improve their mood or health.

[1145] When the user receives the notification message, he or she should follow the advice and take several deep breaths to relax mentally.

[1146] 6. Feedback rating by server

[1147] The server continuously monitors user responses, analyzes newly acquired data, evaluates the effectiveness of the feedback, and adjusts notification messages and recommended actions as needed.

[1148] For example, if the server reanalyzes the user's biometric data and the heart rate returns to the normal range after taking a deep breath, it will evaluate the action as effective and recommend continuing to use it in the future.Similarly, if no effect is observed, new measures will be considered.

[1149] Prompt Sentence Examples

[1150] Below are some example prompts to be input to the generative AI model:

[1151] "A user is wearing a necklace-like device. The device measures their pulse and temperature every 10 minutes and collects audio and facial expression data. The system identifies that the user is experiencing stress. Explain how this information can be sent to a server and an appropriate notification can be provided to the user."

[1152] The above is an embodiment of the present invention. By using this system, users can monitor their own health condition and emotional changes in real time and take appropriate measures when necessary.

[1153] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1154] Step 1: Measurement

[1155] The device measures the user's biometric information. Specifically, it uses sensors to measure pulse and body temperature every 10 minutes, and uses an audio sensor and camera to collect the user's voice data and facial expression data in real time.

[1156] Input: User's pulse, body temperature, voice, facial expression

[1157] Data processing / calculation: pulse and temperature sensor readings, voice and facial expression capture

[1158] Output: Measured biometric information, acquired voice data, facial expression data

[1159] Step 2: Save

[1160] The device stores the measured biometric information and collected emotional data in its internal memory.

[1161] Input: Measured biometric information, collected voice data, facial expression data

[1162] Data processing / calculation: Data storage processing

[1163] Output: Data stored in the internal memory

[1164] Step 3: Send

[1165] Once a certain amount of data has been collected, the terminal transmits this data to a server using a secure communication protocol (e.g., HTTPS).

[1166] Input: Data stored in the internal memory

[1167] Data processing / calculation: Packetizing data, sending data using HTTPS

[1168] Output: Biometric and emotional data sent to the server

[1169] Step 4: Data reception and analysis

[1170] The server receives biometric and emotional data from the device and analyzes it using AI algorithms to detect abnormalities and evaluate the correlation between emotions and biometric data.

[1171] Input: Biometric data and emotional data sent from the device

[1172] Data processing / calculation: Data analysis using AI algorithms, outlier detection, and emotional data analysis

[1173] Output: Analysis results, anomaly detection results

[1174] Step 5: Generate action recommendations

[1175] The server generates notification messages for users based on the analysis results. If an abnormal value is detected or a specific emotion is recognized, a warning message is created and sent to the notification system.

[1176] Input: Analysis results, anomaly detection results

[1177] Data processing / calculation: Notification message generation

[1178] Output: Message sent to the notification system

[1179] Step 6: Notification

[1180] The notification system notifies users in real time based on messages sent from the server, suggests specific countermeasures, and encourages necessary actions.

[1181] Input: The message sent from the server

[1182] Data processing / calculation: Message analysis, generation of voice or push notifications

[1183] Output: User notification

[1184] Step 7: User Action

[1185] Based on the notification from the notification system, the user takes appropriate action, for example, taking deep breaths to try to improve their mood or health.

[1186] Input: Notification message from the notification system

[1187] Data processing / calculation: Actions based on notifications

[1188] Output: User behavior, improved health status

[1189] Step 8: Feedback evaluation

[1190] The server continuously monitors user responses, analyzes newly acquired data, evaluates the effectiveness of the feedback, and adjusts notification messages and recommended actions as needed.

[1191] Input: New biometric data and emotional data from the user

[1192] Data processing / calculation: Data analysis, evaluation of feedback effects

[1193] Output: Evaluation results, tailored notification messages and recommended actions

[1194] The above is the specific processing flow of this system. We have explained in detail how the input data is processed and analyzed at each step, and how it is provided as specific output.

[1195] (Application example 2)

[1196] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1197] Conventional health management systems lack the means to monitor users' health status in real time while they are in the vehicle and to respond quickly if an abnormality occurs. Furthermore, in emergencies, appropriate responses may be delayed, making it difficult to ensure user safety. This creates a need for a means to effectively manage user health risks, especially in autonomous vehicles.

[1198] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting health information and emotional information of the user using sensors installed in the vehicle, means for analyzing the collected health information and emotional information in real time and immediately transmitting the information to the server if an abnormality is detected, means for automatically stopping the vehicle in a safe place if an abnormality is detected, and means for automatically contacting an emergency contact. This makes it possible to respond quickly to the user's health condition or an emergency situation.

[1199] The "biological information measuring means" is a device for measuring biological information such as the pulse rate and body temperature of the user.

[1200] The "data storage means" is a storage device for recording measured biometric information and emotional information.

[1201] The "data transmission means" is a communication device for transmitting the stored biometric information and emotional information to the server.

[1202] The "notification means" is a device for notifying the user of the analysis results from the server.

[1203] A "sensor" is a device placed in a vehicle that measures the user's health and emotional information.

[1204] "Means for real-time analysis" refers to a system for instantly analyzing collected biometric and emotional information.

[1205] The "means for transmitting information to a server when an abnormality is detected" is a device that has the function of quickly transmitting information about an abnormal value to a server when that value is detected.

[1206] "Means for stopping a vehicle in a safe location" refers to a system that moves an autonomous vehicle to a safe location and stops it in an emergency.

[1207] The "means for automatically contacting emergency contacts" is a device that automatically contacts a pre-set emergency contact when an abnormality is detected.

[1208] The present invention relates to a health management system that monitors the health status and emotions of a user in a vehicle in real time and provides a prompt response if an abnormality is detected. This system is composed of a biological information measuring means, a data storage means, a data transmission means, a notification means, and a safety management means for the vehicle.

[1209] System hardware and software configuration

[1210] The system hardware includes the following major components:

[1211] Biometric measurement means: Sensors placed inside the vehicle (e.g., heart rate sensors built into seat belts, interior temperature sensors) measure the user's pulse and body temperature in real time.

[1212] Data storage means: A memory device for temporarily storing measured biometric and emotional information.

[1213] Data transmission means: A communication module for transmitting the measured data to the server via a secure communication protocol (e.g., HTTPS).

[1214] Notification means: A system that receives notification information sent from the server and notifies the user via the vehicle's infotainment system or the user's smartphone.

[1215] In-vehicle safety management measures: an autonomous driving system that automatically stops the vehicle in a safe location if an abnormality is detected, and a communication system that automatically contacts designated contacts in the event of an emergency.

[1216] The system software configuration includes the following components:

[1217] Real-time data collection module: Collects data from the biological information measurement means in real time and stores it in the data storage means.

[1218] Data analysis module: Runs on the server and uses AI algorithms to analyze the transmitted biometric and emotional information. If an abnormality is detected, it generates a warning notification and countermeasures.

[1219] Notification management module: Sends notification information from the server to the terminal and notifies the user of appropriate measures.

[1220] Emergency response module: Links with the vehicle's safety management measures, automatically stops the vehicle in the event of an abnormality, and makes emergency contact if necessary.

[1221] Example of operation

[1222] When a user gets into an autonomous vehicle, the biometric information measurement means periodically measures the user's pulse and body temperature. This data is stored in the data storage means in real time and transmitted to the server via the data transmission means. The server uses an AI algorithm to analyze the data, and if an abnormality is detected, the notification management module sends a voice or push notification to the user. Furthermore, if a serious abnormality is detected, the safety management means within the vehicle is automatically activated, stopping the vehicle in a safe location and making an emergency call.

[1223] Prompt Sentence Examples

[1224] Below are some examples of specific prompt sentences for this system.

[1225] markdown

[1226] Use case: Vehicle Health Monitoring System

[1227] Requirements:

[1228] 1. Monitor real-time heart rate, body temperature, and user emotions using in-car sensors.

[1229] 2. Analyze collected data and send to centralized server for further processing.

[1230] 3. Alert the user with voice messages or display notifications on the Infotainment system if any abnormalities are detected.

[1231] ----

[1232] User Scenario:

[1233] A user is on a long drive. The system monitors the user's vital signs every 10 minutes. At 3 PM, the user's heart rate suddenly spikes and the emotion engine detects stress. The system alerts the user through the car's infotainment system, advising them to take a break and relax. If the user does not respond or if the signs of stress persist, the system automatically contacts emergency services.

[1234] The system of the present invention effectively manages the safety and health of users by monitoring their health status in real time and taking appropriate measures quickly and automatically if an abnormality is detected.

[1235] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1236] Step 1:

[1237] Sensors installed in the vehicle measure the user's biometric information (pulse, body temperature) and emotional information in real time. Heart rate and body temperature data, as well as voice and sidelong glance data to identify emotions, are required as input. The measured data is obtained as output.

[1238] Step 2:

[1239] The device temporarily stores the measured data in a data storage means. The input requires biometric and emotional information data provided by the sensors. The stored data is obtained as the output.

[1240] Step 3:

[1241] The device sends the stored data to the server using a secure communication protocol (e.g. HTTPS). The stored data is required as input. The data sent to the server is obtained as output.

[1242] Step 4:

[1243] The server analyzes the received data using AI algorithms to detect abnormal values ​​and dangerous health conditions. The input requires the transmitted biometric and emotional data. The output is the analysis results.

[1244] Step 5:

[1245] If the server detects an anomaly based on the analysis results, it generates a warning message for the user. The analysis result data is required as input, and the generated warning message is obtained as output.

[1246] Step 6:

[1247] The server sends the generated alert message to the user's terminal, the vehicle's infotainment system, or the user's smartphone via a notification means. The alert message is required as input, and the message notified to the user is obtained as output.

[1248] Step 7:

[1249] If a serious abnormality is detected, the vehicle's autonomous driving system will be activated and stop the vehicle in a safe place. Information on the abnormality detection is required as input, and the stopped vehicle is obtained as output.

[1250] Step 8:

[1251] Furthermore, in the event of an emergency, the server automatically contacts the configured emergency contacts. Emergency contact information and anomaly detection information are required as input. The output indicates that the emergency contact has been completed.

[1252] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1253] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1254] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1255] [Fourth embodiment]

[1256] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1257] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1258] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1259] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1260] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1261] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1262] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1263] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1264] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1265] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1266] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1267] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1268] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1269] This invention relates to a device and system for supporting daily health management of users. Specifically, we provide a system that measures the user's biological information such as pulse and body temperature in real time, transmits the data to a server for analysis and storage, and notifies the user as necessary.

[1270] The system includes the following major components:

[1271] 1. Terminal (device): A device that has the ability to measure biometric information and store and transmit the data. Specifically, it can be a wristwatch, necklace, or earring-type device with built-in sensors that measure pulse and body temperature.

[1272] 2. Server: A computer system that receives, analyzes, and stores biometric data sent from the device. It analyzes the data using AI algorithms and notifies the user of countermeasures if an abnormality is detected.

[1273] 3. Notification system: A system with voice and push notification functions to provide information feedback to users.

[1274] System Overview

[1275] Device behavior

[1276] The device has built-in sensors that periodically measure the user's pulse and body temperature, and uses these sensors to collect the user's biological information in real time. The collected data is temporarily stored in the internal memory.

[1277] Examples:

[1278] When the user wears the necklace, the device measures the pulse and body temperature every 10 minutes, stores the data in its internal memory, and transmits the data to a server at appropriate intervals.

[1279] Server Operation

[1280] The server receives the data sent from the device, stores it in a database, and then uses AI algorithms to analyze the data in real time to detect abnormalities and assess health status.

[1281] Examples:

[1282] The server receives 24-hour biometric data and analyzes it with an AI algorithm. If the server detects that the user's heart rate is abnormally high during a specific time period, it generates a notification to report the abnormality.

[1283] How the notification system works

[1284] The notification system receives notification information sent from the server and provides real-time feedback to the user via voice or push notifications. If an abnormality is detected, the system alerts the user and suggests specific countermeasures.

[1285] Examples:

[1286] The server detects an abnormal heart rate and sends that information to the device, which then sends a voice notification to the user saying, "Your heart rate is abnormally high. Please take a break and take a deep breath."

[1287] Program processing

[1288] The programs in this system are designed to fulfill the roles of terminal, server, and notification system. Each process is explained below in natural language.

[1289] Terminal Programs

[1290] The device periodically collects the user's biometric information and stores it in its internal memory. After collecting a certain amount of data, it transmits it to a server using a secure communication protocol.

[1291] Server Program

[1292] The server analyzes the data received from the device, evaluates abnormal values ​​and health status, and then generates notification messages as needed and sends them to the notification system.

[1293] Notification System Program

[1294] The notification system sends real-time notifications to users based on the notification information received from the server, providing appropriate warnings and countermeasures.

[1295] The above is an embodiment of the present invention. By using this system, users can easily monitor their own health condition on a daily basis and can respond quickly if an abnormality is detected.

[1296] The processing flow will be explained below.

[1297] Step 1:

[1298] The device initializes the sensors and prepares them to measure the user's pulse and temperature. This sensor initialization occurs when the device is turned on.

[1299] Step 2:

[1300] The device periodically (e.g., every 10 minutes) measures the user's pulse and body temperature. After the measurement, the data obtained from the sensors is temporarily stored in the internal memory.

[1301] Step 3:

[1302] When the data stored in the device's internal memory reaches a certain amount (e.g., 30 points), the device prepares to send the data. When preparing to send the data, the data is encrypted.

[1303] Step 4:

[1304] The device sends encrypted data to the server using a secure communication protocol (e.g., HTTPS).

[1305] Step 5:

[1306] The server stores the data received from the device in a database, then extracts a sample of the data and performs an initial analysis using an AI algorithm.

[1307] Step 6:

[1308] The server then uses AI algorithms to analyze the data in detail, detect abnormalities, and assess the patient's health, identifying abnormal heart rate and body temperature fluctuations.

[1309] Step 7:

[1310] If the server detects an anomaly based on the analysis results, it generates a warning message that includes details of the anomaly and appropriate countermeasures.

[1311] Step 8:

[1312] The server sends the generated warning message to the terminal, using real-time communication.

[1313] Step 9:

[1314] The device notifies the user of the warning message received from the server. The notification method is audio notification or push notification. For example, a message such as "Your heart rate is abnormally high. Please take a break and relax" may be sent.

[1315] Step 10:

[1316] The user checks the notification and takes necessary action, such as taking a deep breath, taking a break, or seeking medical attention.

[1317] Step 11:

[1318] After the user responds, the device measures again and sends the collected data to the server to continuously monitor the user's health condition.

[1319] Step 12:

[1320] The server periodically analyzes the collected data over the long term to evaluate the user's health trends, and generates regular health advice based on the evaluation results.

[1321] Step 13:

[1322] The server sends the generated health advice to the device, and the device notifies the user of the advice. For example, the device may notify the user of the advice, saying, "We recommend walking 20 minutes every day."

[1323] Step 14:

[1324] The user receives the advice, decides whether to incorporate it into their daily life, and takes the necessary action.

[1325] Example 1

[1326] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1327] In modern society, personal health management has become an important issue. However, many current systems are insufficient for continuously monitoring a user's health status, and in particular, they lack the means to prompt and appropriate action when an abnormality occurs. Therefore, there is a need for a system that can measure a user's biological information in real time, detect abnormalities, and provide immediate countermeasures.

[1328] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1329] In this invention, the server includes a biological information measuring means for measuring a user's biological information, a data storage means for temporarily storing the measured biological information, a data transmission means for transmitting a certain amount of data to the server after accumulating the data, an analysis means for analyzing the data received by the server using an AI algorithm, a message generation means for detecting an abnormality based on the analysis result and generating a notification message, and a notification means for notifying the user of the generated notification message. This enables real-time monitoring of biological information and rapid detection and response to abnormalities.

[1330] The term "biological information measuring means" refers to a device or sensor for measuring biological information such as the user's pulse rate and body temperature.

[1331] "Data storage means" refers to a memory or storage device for temporarily storing measured biological information.

[1332] "Data transmission means" refers to the communication protocol or device used to transmit the stored biometric information to the server.

[1333] "Analysis means" refers to the function or process of analyzing biometric information received by the server using an AI algorithm.

[1334] "Message generation means" refers to a device or process that detects an abnormality based on the analysis results and generates a message to notify the user.

[1335] The "notification means" refers to a means for notifying the user of the generated notification message, such as a voice notification or a push notification.

[1336] The term "biological information measuring means" refers to a device or sensor for measuring biological information such as the user's pulse rate and body temperature.

[1337] "Data storage means" refers to a memory or storage device for temporarily storing measured biological information.

[1338] "Data transmission means" refers to the communication protocol or device used to transmit the stored biometric information to the server.

[1339] "Analysis means" refers to the function or process of analyzing biometric information received by the server using an AI algorithm.

[1340] "Message generation means" refers to a device or process that detects an abnormality based on the analysis results and generates a message to notify the user.

[1341] The "notification means" refers to a means for notifying the user of the generated notification message, such as a voice notification or a push notification.

[1342] MODE FOR CARRYING OUT THE INVENTION

[1343] This invention relates to a device and system for supporting daily health management of users. Specifically, we provide a system that measures a user's biological information, such as pulse and body temperature, in real time, transmits the data to a server for analysis and storage, and notifies the user as needed. A specific embodiment of this system is described below.

[1344] Hardware Configuration

[1345] The present invention includes the following major components:

[1346] 1. Terminal (device): A device that has the ability to measure biometric information and store and transmit the data. Specifically, it can be a wristwatch, necklace, or earring-type device with built-in sensors that measure pulse and body temperature.

[1347] 2. Server: A computer system that receives, analyzes, and stores biometric data sent from the device. It analyzes the data using AI algorithms and notifies the user of countermeasures if an abnormality is detected.

[1348] 3. Notification system: A system with voice and push notification functions to provide information feedback to users.

[1349] Software Configuration

[1350] The device is equipped with dedicated software for measuring biometric information in real time, while the server is equipped with AI algorithms for receiving, storing, and analyzing the data, and also includes a program for generating notification messages required for the notification system.

[1351] Specific software used includes:

[1352] Database system: MySQL, PostgreSQL, etc.

[1353] AI algorithms: TensorFlow, PyTorch, etc.

[1354] Device behavior

[1355] The device has a built-in sensor that periodically measures the user's biometric information (specifically, pulse and body temperature). This sensor is used to collect the user's biometric information in real time and temporarily store it in the internal memory. Once a certain amount of data has been accumulated, the data is sent to the server using a secure communication protocol (e.g., Bluetooth Low Energy or Wi-Fi).

[1356] Examples:

[1357] When the user wears the necklace, it measures their pulse and body temperature every 10 minutes, stores the data in its internal memory, and once a certain amount of data is reached, it transmits the data to a server using Bluetooth Low Energy.

[1358] Server Operation

[1359] The server receives the data sent from the device and stores it in a database. It then uses AI algorithms to analyze the data in real time, detect abnormalities, and assess health status. If necessary, it generates notification messages based on the analysis results and sends them to the notification system.

[1360] Examples:

[1361] The server receives 24-hour biometric data and analyzes it using an AI algorithm powered by TensorFlow. If the server detects that the user's heart rate is abnormally high during a specific time period, it generates a notification message stating, "An abnormal heart rate has been detected."

[1362] How the notification system works

[1363] The notification system receives notification information sent from the server and provides real-time feedback to the user via voice and push notifications. If an abnormality is detected, the system alerts the user and suggests specific countermeasures.

[1364] Examples:

[1365] The user's smartphone will receive a push notification that displays the message "Your heart rate is abnormally high. Please take a rest," or an audio notification will be played over the device's speaker.

[1366] Examples of prompt statements

[1367] Here are some example prompts to input to a generative AI model:

[1368] Please explain in detail how you will analyze the data from the health management device and how you will notify the user if an abnormality is detected.

[1369] The above is an embodiment of the present invention. By using this system, users can easily monitor their own health condition on a daily basis and can respond quickly when an abnormality is detected.

[1370] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1371] Step 1:

[1372] The device measures the user's biometric information.

[1373] Specifically, the device's built-in pulse sensor and body temperature sensor measure data every 10 minutes to obtain pulse rate and body temperature.

[1374] Input: User's biometric information (pulse, body temperature)

[1375] Output: Measured biological information data (e.g. pulse rate 75 beats / min, body temperature 36.5°C)

[1376] Step 2:

[1377] The device stores the measured biometric information in its internal memory.

[1378] The data storage means is used to temporarily store the biometric information.

[1379] Input: Measured biological information data

[1380] Output: Biometric data stored in internal memory

[1381] Step 3:

[1382] After the terminal accumulates a certain amount of data, it transmits the data to the server using a secure communication protocol.

[1383] Specifically, once the data in the internal memory reaches 100 data points, it is sent to a server using Bluetooth Low Energy or Wi-Fi.

[1384] Input: Biometric data stored in the internal memory

[1385] Output: Biometric data sent to the server

[1386] Step 4:

[1387] The server receives the data sent from the terminal and stores it in a database.

[1388] Specifically, after the server receives the data, it stores the data in a database such as MySQL or PostgreSQL.

[1389] Input: Biometric data sent from the device

[1390] Output: Biometric data stored in a database

[1391] Step 5:

[1392] The server analyzes the received data using AI algorithms.

[1393] Specifically, it uses TensorFlow and PyTorch to analyze data, detect outliers, and assess health status.

[1394] Input: Biometric data stored in a database

[1395] Output: Analysis results (e.g., detection of periods when heart rate is abnormally high)

[1396] Step 6:

[1397] If the server detects an abnormality based on the analysis results, it generates a notification message.

[1398] Specifically, when an abnormality is detected, a message is generated saying, "Your heart rate is abnormally high. Please take a rest."

[1399] Input: Analysis results

[1400] Output: Notification message

[1401] Step 7:

[1402] The notification system receives the notification information sent from the server and notifies the user.

[1403] Specifically, users will be notified via push notifications to their smartphones or voice notifications from the device's speaker.

[1404] Input: Notification message

[1405] Output: User notification (e.g., push notification, "Your heart rate is abnormally high. Please take a rest.")

[1406] The above are the processing steps of the program for this system and the specific operation of each step. This system is capable of monitoring the user's health condition in real time and quickly detecting and notifying abnormalities.

[1407] (Application example 1)

[1408] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1409] Conventional health management systems lacked the means to effectively monitor individuals' biometric information in real time and quickly detect and notify abnormalities. Furthermore, when an abnormality occurred, there was no means of properly notifying all relevant parties. This created the problem of being unable to quickly respond to the deterioration of staff health, particularly in brick-and-mortar stores.

[1410] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1411] In this invention, the server includes a data storage means for storing measured biometric information, a data transmission means for transmitting the stored biometric information to the server, a notification means for receiving analysis results from the server and notifying the user, and a means for the notification means to notify the administrator and the relevant user of abnormal values. This makes it possible to monitor biometric information such as pulse and body temperature of users, including staff, in real time, and to quickly notify the administrator and the relevant user if an abnormality is detected.

[1412] "User's biological information" is data that indicates a person's health condition, such as pulse rate and body temperature.

[1413] The "biological information measuring means" is a device with built-in sensors for measuring the user's pulse and body temperature.

[1414] "Data storage means" refers to internal memory or storage for temporarily storing measured biological information.

[1415] "Data transmission means" refers to a communication module or protocol for transmitting stored biometric information to a server.

[1416] The "notification means" is a function for receiving the analysis results from the server and notifying the user and administrator by voice or push notification as necessary.

[1417] The "server" is a computer system that receives, stores, and analyzes biometric information sent from the device and generates a notification if an abnormality is detected.

[1418] "Administrator" refers to the person responsible for monitoring and managing biometric information.

[1419] "Abnormal values" refer to pulse or temperature measurements that are outside the normal range.

[1420] The present invention is a system for supporting a user's daily health management. The system includes the following main components:

[1421] 1. Device: This device has built-in sensors to measure pulse and body temperature. The device periodically measures the user's biometric information and temporarily stores the data in its internal memory. This device is available in various forms, such as a wristwatch, necklace, or earring.

[1422] 2. Server: Receives biometric data sent from the device and stores it in a database. The server uses AI algorithms to analyze the data in real time and generates a notification message if an abnormal value is detected.

[1423] 3. Notification System: The notification system receives notification information sent from the server and provides feedback to users and administrators through voice notifications and push notifications.

[1424] Program processing

[1425] Terminal Programs

[1426] The device periodically collects biometric information and stores it in its internal memory. After collecting a certain amount of data, it transmits the data to a server using a secure communication protocol via a wireless communication module such as Wi-Fi or Bluetooth. This process is performed using Python and the requests library.

[1427] Server Program

[1428] The server uses a web framework such as Flask to analyze the data received from the device. The server analyzes the data stored in the database in real time and uses AI algorithms to evaluate abnormal values ​​and health status. Any abnormal values ​​detected by this algorithm are notified to the administrator and the relevant user.

[1429] Notification System Program

[1430] The notification system notifies users in real time based on the notification information received from the server. Notifications are provided as voice notifications or push notifications to smartphones, allowing users to take prompt action when an abnormality occurs.

[1431] Specific examples

[1432] Scenario: A staff member working in a store wears a necklace-type device. This device measures the staff member's pulse and body temperature every 10 minutes and sends the data to a server. The server analyzes the received data in real time and notifies the manager and the relevant staff member if an abnormality is detected.

[1433] Example prompts to input to a generative AI model:

[1434] I am designing a system to monitor the health of store staff 24 / 7. Staff will wear a necklace-type device that measures their pulse and body temperature every 10 minutes and sends the data to a server. The server will perform real-time analysis and notify managers and staff if any abnormalities are detected. The terminals will use Python to collect data, and the server will use Flask to analyze the data. Can you give me a code example for this system?

[1435] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1436] Step 1:

[1437] The device measures the user's biometric information. Specifically, the device's built-in pulse sensor and body temperature sensor measure the user's pulse and body temperature. The input is the biometric information measured by the sensor, and the output is pulse and body temperature data.

[1438] Step 2:

[1439] The device stores the measured biometric information. The measured pulse and body temperature data is temporarily stored in the device's internal memory. The input is the measured biometric data, and the output is data stored in the internal memory.

[1440] Step 3:

[1441] The device periodically transmits biometric data to the server. The device transmits the stored data to the server using Wi-Fi or Bluetooth. The input is the data stored in the internal memory, and the output is the biometric data transmitted to the server.

[1442] Step 4:

[1443] The server receives the biometric data sent from the device. The server stores the data in a database and prepares it for analysis. The input is the biometric data sent from the device, and the output is data stored in the database.

[1444] Step 5:

[1445] The server analyzes the received biometric data. The server uses an AI algorithm to analyze and detect abnormal values. The input is the biometric data stored in the database, and the output is the analysis results.

[1446] Step 6:

[1447] If the server detects an abnormal value, it generates a notification message. If the server detects an abnormal value, it generates a notification message and sends it to the notification system. The input is the analysis result, and the output is the notification message.

[1448] Step 7:

[1449] The notification system receives notification messages and notifies users and administrators. The notification system provides real-time feedback through voice or push notifications. The input is the notification message sent from the server, and the output is the notification to users and administrators.

[1450] Adding specific actions

[1451] Step 1:

[1452] The device activates the pulse and temperature sensors and performs measurements for a few seconds. During the measurement, the sensors collect pulse and temperature data from the skin surface.

[1453] Step 2:

[1454] After each measurement, the device stores the pulse and temperature data in a specific area of ​​its internal memory.

[1455] Step 3:

[1456] Every 10 minutes, the device collects the stored data in packets and sends them to a server via Wi-Fi or Bluetooth using a secure protocol.

[1457] Step 4:

[1458] The server receives data packets sent from the terminals and stores the data by creating entries in a database.

[1459] Step 5:

[1460] An AI algorithm on the server scans new entries in the database, analyzing pulse and temperature data, and if it detects any abnormalities, it stores that information in specific variables.

[1461] Step 6:

[1462] If an abnormal value is detected, the server generates a notification message for the administrator and the affected user and sends the message to the notification system.

[1463] Step 7:

[1464] The notification system analyzes the received notification messages and sends voice and push notifications to the relevant users and administrators, including specific anomalies and recommended actions.

[1465] The above is a specific processing procedure of the embodiment of the invention.

[1466] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1467] The present invention relates to a device and system for supporting daily health management of users. Specifically, the present invention provides a system that combines technology for recognizing a user's biological information, such as pulse rate and body temperature, and the user's emotions. The system includes the following main components:

[1468] 1. Terminal (device): A device that has the ability to measure biometric information and store and transmit that data. Specifically, it could be a wristwatch, necklace, or earring-type device with built-in sensors that measure pulse and body temperature, and an emotion engine that analyzes voice and facial expressions to recognize emotions.

[1469] 2. Server: A computer system that receives, analyzes, and stores data sent from the device. The server uses AI algorithms to analyze the data and notifies the user of countermeasures if an anomaly is detected. It also recommends specific actions based on the user's emotions.

[1470] 3. Notification system: A system with voice and push notification functions to provide information feedback to users.

[1471] 4. Emotion Engine: A machine learning model that analyzes the user's voice and facial expression data to recognize the user's emotions.

[1472] System Program Processing

[1473] The program in this system is designed to fulfill the roles of terminal, server, notification system, and emotion engine. Each process is explained below.

[1474] Terminal handling

[1475] The device periodically measures the user's pulse and body temperature and stores the data in its internal memory. It also uses a sound sensor and camera to collect the user's voice and facial expression data, and uses an emotion engine to recognize emotions. The recognized emotion data is stored along with biometric information, and once a certain amount of data has been collected, it is sent to a server using a secure communication protocol.

[1476] Examples:

[1477] When the user wears the necklace-type device, it measures their pulse and body temperature every 10 minutes and stores the data in its internal memory. Additionally, when the user speaks, the audio sensor collects their voice, and the camera simultaneously captures facial expression data. If the emotion engine detects "stress," it stores this information along with their biometric information and sends it to the server as appropriate.

[1478] Server Processing

[1479] The server analyzes the data received from the device and evaluates abnormal values ​​and health status. It also analyzes the emotion data recognized by the emotion engine and evaluates the correlation between the user's physiological changes and emotions. Furthermore, if an abnormality is detected or a specific emotion is recognized, it generates a warning message and sends it to the notification system.

[1480] Examples:

[1481] The server receives 24-hour biometric and emotional data and analyzes it using an AI algorithm. As a result, it discovers that the user's heart rate is abnormally high during a specific time period, and that the emotion of "stress" is frequently recognized at that time. The server generates a message saying, "Stress tends to increase during this time period. We recommend taking deep breaths," and sends it to the device.

[1482] Notification System Processing

[1483] The notification system notifies users in real time based on notification information sent from the server. If an abnormality is detected, the system alerts the user and suggests specific countermeasures. It also prompts the user to take appropriate action based on emotional data.

[1484] Examples:

[1485] The server generates a message saying "Your stress is rising. Please take a deep breath" and sends it to the device. The device then notifies the user with a voice message saying "Your stress is rising. Please take a deep breath and relax."

[1486] Emotion engine processing

[1487] The emotion engine analyzes the user's voice and facial expression data to recognize specific emotions. For example, it can detect emotions such as "happiness," "sadness," and "anger" from voice characteristics and facial changes. The recognized emotions are stored along with biometric data and sent to the server.

[1488] Examples:

[1489] The user wears the necklace-type device, and the emotion engine analyzes voice and facial expression data during conversation to recognize "happiness." This information, along with pulse and body temperature data, is stored and sent to the server at the appropriate time.

[1490] The above is an embodiment of the present invention. By using this system, users can monitor their own health condition and emotional changes in real time and take appropriate measures when necessary.

[1491] The processing flow will be explained below.

[1492] Step 1:

[1493] The device initializes the sensors and prepares them to measure the user's pulse and temperature. This sensor initialization occurs when the device is turned on.

[1494] Step 2:

[1495] The device periodically (e.g., every 10 minutes) measures the user's pulse and body temperature. After the measurement, the data obtained from the sensors is temporarily stored in the internal memory.

[1496] Step 3:

[1497] The device uses a sound sensor and a camera to collect the user's voice and facial expression data, which is then processed by an emotion engine to recognize the user's emotions in real time.

[1498] Step 4:

[1499] The device stores the recognized emotion data along with biometric data in its internal memory, recording, for example, the user's stress level or happiness level.

[1500] Step 5:

[1501] When the data stored in the device's internal memory reaches a certain amount (e.g., 30 points), the device prepares to send the data. When preparing to send the data, the data is encrypted.

[1502] Step 6:

[1503] The device sends encrypted data to the server using a secure communication protocol (e.g., HTTPS).

[1504] Step 7:

[1505] The server stores the data received from the device in a database, then extracts a sample of the data and performs an initial analysis using an AI algorithm.

[1506] Step 8:

[1507] The server uses AI algorithms to analyze the data in detail, detect abnormalities, and assess the user's health. During this process, it identifies abnormal heart rate and body temperature fluctuations. It also analyzes emotional data to recognize changes in emotions.

[1508] Step 9:

[1509] If the server detects an anomaly based on the analysis results, it generates a warning message that includes details of the anomaly and appropriate countermeasures. It also generates a message that suggests specific actions based on the user's emotions.

[1510] Step 10:

[1511] The server sends the generated warning message to the terminal, using real-time communication.

[1512] Step 11:

[1513] The device notifies the user of the warning message received from the server. Notification methods include voice notification and push notification. For example, a message such as "Your heart rate is abnormally high. Please take a break and relax" or "Stress tends to increase at this time of day. We recommend taking deep breaths" may be sent.

[1514] Step 12:

[1515] The user checks the notification and takes necessary action, such as taking a deep breath, taking a break, or seeking medical attention.

[1516] Step 13:

[1517] The device then measures biometric and emotional data again, repeating this process and sending the data to the server each time, continuously monitoring the user's health.

[1518] Step 14:

[1519] The server analyzes the data over a long period of time to identify trends in the user's health and generates regular health advice based on the analysis results.

[1520] Step 15:

[1521] The server sends the generated health advice to the device, and the device notifies the user of the advice. For example, the device may notify the user of the advice, saying, "We recommend walking 20 minutes every day."

[1522] Step 16:

[1523] The user receives the advice, decides whether to incorporate it into their daily life, and takes the necessary action.

[1524] Example 2

[1525] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1526] In modern society, many people suffer from stress and health problems, but there are limited systems that can monitor these conditions in real time and suggest timely solutions. Conventional health management devices primarily focus on measuring biometric information and lack the ability to simultaneously recognize and provide feedback on the user's emotional state. This often prevents users from effectively managing their health, delaying early detection and countermeasures. To address these issues, the present invention provides a system that monitors and analyzes a user's biometric information and emotional state in real time and provides appropriate feedback.

[1527] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1528] In this invention, the server includes a measuring means for measuring the user's biometric information, a storage means for storing the measured biometric information, a data transmission means for transmitting the stored biometric information to the server, a notification means for receiving analysis results from the server and notifying the user, an emotion recognition means for analyzing the user's voice data and facial expression data and recognizing emotions, a means for storing the recognized emotion data together with the biometric information and transmitting it to the server, a means for the server to analyze the received data and notify the user of how to deal with any abnormalities detected, and a notification system means for notifying the user in real time based on notification messages from the server. This enables the user to monitor their own health and emotional state in real time and take prompt action if an abnormality is detected.

[1529] "Biometric information" is data that indicates the physical condition of the user, such as pulse, body temperature, and blood pressure.

[1530] "Measurement means" refers to sensors and devices used to acquire biometric information from a user.

[1531] "Storage means" refers to a storage device for storing measured biological information.

[1532] "Data transmission means" refers to a communication function for transferring stored biometric information to a server.

[1533] The "server" is a central processing system that analyzes and stores data sent from the measurement means and storage means, and provides feedback to the user as needed.

[1534] "Notification means" refers to a means for notifying the user of analysis results and feedback from the server, and includes, for example, voice notification and push notification.

[1535] "Voice data" is digital information that is a recording of the user's voice.

[1536] "Facial expression data" is image data of the user's facial expression captured by a camera.

[1537] "Emotion recognition means" refers to a function that analyzes voice data and facial expression data to identify the user's emotions.

[1538] "Abnormal" refers to a significant deviation from normal biometric or emotional states, which may indicate health risks or mental health problems.

[1539] "Countermeasures" refers to specific actions or advice that a user should take when an abnormality is detected.

[1540] "Real-time notification" is a function that instantly provides information to users based on data analyzed by the server.

[1541] The present invention relates to a device and system for supporting daily health management of users. Specifically, the present invention provides a system that combines technology for recognizing a user's biological information, such as pulse rate and body temperature, and the user's emotions. The system includes the following main components:

[1542] 1. Data collection by device

[1543] The device periodically measures the user's pulse and body temperature and stores the data in its internal memory. It also uses a sound sensor and camera to collect the user's voice and facial expression data, and uses an emotion engine to recognize emotions. The recognized emotion data is stored along with biometric information, and once a certain amount of data has been collected, it is sent to a server using a secure communication protocol (e.g., HTTPS).

[1544] Specifically, when a user wears the necklace-type device, it measures their pulse and body temperature every 10 minutes and stores the data in its internal memory. When the user speaks, the audio sensor collects voice data, and the camera captures facial expression data in real time. If the emotion engine recognizes "stress," it stores that information along with biometric information and sends it to a server as appropriate.

[1545] 2. Data reception and analysis by the server

[1546] The server receives the biometric and emotional data sent from the device and analyzes it using an AI algorithm (e.g., TensorFlow model), detecting outliers and evaluating the correlation between emotions and biometric data.

[1547] For example, if the server receives 24-hour biometric and emotional data and analyzes it using an AI algorithm, and finds that the user's heart rate is abnormally high during a particular time period and that the user frequently expresses feelings of "stress," this abnormal data will be detected.

[1548] 3. Server-generated action recommendations

[1549] The server generates a notification message for the user based on the analysis results. If an abnormal value is detected or a specific emotion is recognized, a warning message is created and sent to the notification system.

[1550] For example, the server generates a message saying, "Stress tends to increase at this time of day. We recommend taking deep breaths," and sends it to a notification system.

[1551] 4. Notification via the notification system

[1552] The notification system notifies users in real time based on messages sent from the server, suggests specific countermeasures, and encourages necessary actions.

[1553] For example, if the notification system receives the message "Your stress levels are rising. Please take a deep breath," the device will relay that message to the user via voice notification, instructing them, "This is a time when stress levels are rising. Please take a deep breath and relax."

[1554] 5. User Response

[1555] Based on the notifications from the notification system, the user can take appropriate actions, such as taking deep breaths, to improve their mood or health.

[1556] When the user receives the notification message, he or she should follow the advice and take several deep breaths to relax mentally.

[1557] 6. Feedback rating by server

[1558] The server continuously monitors user responses, analyzes newly acquired data, evaluates the effectiveness of the feedback, and adjusts notification messages and recommended actions as needed.

[1559] For example, if the server reanalyzes the user's biometric data and the heart rate returns to the normal range after taking a deep breath, it will evaluate the action as effective and recommend continuing to use it in the future.Similarly, if no effect is observed, new measures will be considered.

[1560] Prompt Sentence Examples

[1561] Below are some example prompts to be input to the generative AI model:

[1562] "A user is wearing a necklace-like device. The device measures their pulse and temperature every 10 minutes and collects audio and facial expression data. The system identifies that the user is experiencing stress. Explain how this information can be sent to a server and an appropriate notification can be provided to the user."

[1563] The above is an embodiment of the present invention. By using this system, users can monitor their own health condition and emotional changes in real time and take appropriate measures when necessary.

[1564] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1565] Step 1: Measurement

[1566] The device measures the user's biometric information. Specifically, it uses sensors to measure pulse and body temperature every 10 minutes, and uses an audio sensor and camera to collect the user's voice data and facial expression data in real time.

[1567] Input: User's pulse, body temperature, voice, facial expression

[1568] Data processing / calculation: pulse and temperature sensor readings, voice and facial expression capture

[1569] Output: Measured biometric information, acquired voice data, facial expression data

[1570] Step 2: Save

[1571] The device stores the measured biometric information and collected emotional data in its internal memory.

[1572] Input: Measured biometric information, collected voice data, facial expression data

[1573] Data processing / calculation: Data storage processing

[1574] Output: Data stored in the internal memory

[1575] Step 3: Send

[1576] Once a certain amount of data has been collected, the terminal transmits this data to a server using a secure communication protocol (e.g., HTTPS).

[1577] Input: Data stored in the internal memory

[1578] Data processing / calculation: Packetizing data, sending data using HTTPS

[1579] Output: Biometric and emotional data sent to the server

[1580] Step 4: Data reception and analysis

[1581] The server receives biometric and emotional data from the device and analyzes it using AI algorithms to detect abnormalities and evaluate the correlation between emotions and biometric data.

[1582] Input: Biometric data and emotional data sent from the device

[1583] Data processing / calculation: Data analysis using AI algorithms, outlier detection, and emotional data analysis

[1584] Output: Analysis results, anomaly detection results

[1585] Step 5: Generate action recommendations

[1586] The server generates notification messages for users based on the analysis results. If an abnormal value is detected or a specific emotion is recognized, a warning message is created and sent to the notification system.

[1587] Input: Analysis results, anomaly detection results

[1588] Data processing / calculation: Notification message generation

[1589] Output: Message sent to the notification system

[1590] Step 6: Notification

[1591] The notification system notifies users in real time based on messages sent from the server, suggests specific countermeasures, and encourages necessary actions.

[1592] Input: The message sent from the server

[1593] Data processing / calculation: Message analysis, generation of voice or push notifications

[1594] Output: User notification

[1595] Step 7: User Action

[1596] Based on the notification from the notification system, the user takes appropriate action, for example, taking deep breaths to try to improve their mood or health.

[1597] Input: Notification message from the notification system

[1598] Data processing / calculation: Actions based on notifications

[1599] Output: User behavior, improved health status

[1600] Step 8: Feedback evaluation

[1601] The server continuously monitors user responses, analyzes newly acquired data, evaluates the effectiveness of the feedback, and adjusts notification messages and recommended actions as needed.

[1602] Input: New biometric data and emotional data from the user

[1603] Data processing / calculation: Data analysis, evaluation of feedback effects

[1604] Output: Evaluation results, tailored notification messages and recommended actions

[1605] The above is the specific processing flow of this system. We have explained in detail how the input data is processed and analyzed at each step, and how it is provided as specific output.

[1606] (Application example 2)

[1607] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1608] Conventional health management systems lack the means to monitor users' health status in real time while they are in the vehicle and to respond quickly if an abnormality occurs. Furthermore, in emergencies, appropriate responses may be delayed, making it difficult to ensure user safety. This creates a need for a means to effectively manage user health risks, especially in autonomous vehicles.

[1609] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting health information and emotional information of the user using sensors installed in the vehicle, means for analyzing the collected health information and emotional information in real time and immediately transmitting the information to the server if an abnormality is detected, means for automatically stopping the vehicle in a safe place if an abnormality is detected, and means for automatically contacting an emergency contact. This makes it possible to respond quickly to the user's health condition or an emergency situation.

[1610] The "biological information measuring means" is a device for measuring biological information such as the pulse rate and body temperature of the user.

[1611] The "data storage means" is a storage device for recording measured biometric information and emotional information.

[1612] The "data transmission means" is a communication device for transmitting the stored biometric information and emotional information to the server.

[1613] The "notification means" is a device for notifying the user of the analysis results from the server.

[1614] A "sensor" is a device placed in a vehicle that measures the user's health and emotional information.

[1615] "Means for real-time analysis" refers to a system for instantly analyzing collected biometric and emotional information.

[1616] The "means for transmitting information to a server when an abnormality is detected" is a device that has the function of quickly transmitting information about an abnormal value to a server when that value is detected.

[1617] "Means for stopping a vehicle in a safe location" refers to a system that moves an autonomous vehicle to a safe location and stops it in an emergency.

[1618] The "means for automatically contacting emergency contacts" is a device that automatically contacts a pre-set emergency contact when an abnormality is detected.

[1619] The present invention relates to a health management system that monitors the health status and emotions of a user in a vehicle in real time and provides a prompt response if an abnormality is detected. This system is composed of a biological information measuring means, a data storage means, a data transmission means, a notification means, and a safety management means for the vehicle.

[1620] System hardware and software configuration

[1621] The system hardware includes the following major components:

[1622] Biometric measurement means: Sensors placed inside the vehicle (e.g., heart rate sensors built into seat belts, interior temperature sensors) measure the user's pulse and body temperature in real time.

[1623] Data storage means: A memory device for temporarily storing measured biometric and emotional information.

[1624] Data transmission means: A communication module for transmitting the measured data to the server via a secure communication protocol (e.g., HTTPS).

[1625] Notification means: A system that receives notification information sent from the server and notifies the user via the vehicle's infotainment system or the user's smartphone.

[1626] In-vehicle safety management measures: an autonomous driving system that automatically stops the vehicle in a safe location if an abnormality is detected, and a communication system that automatically contacts designated contacts in the event of an emergency.

[1627] The system software configuration includes the following components:

[1628] Real-time data collection module: Collects data from the biological information measurement means in real time and stores it in the data storage means.

[1629] Data analysis module: Runs on the server and uses AI algorithms to analyze the transmitted biometric and emotional information. If an abnormality is detected, it generates a warning notification and countermeasures.

[1630] Notification management module: Sends notification information from the server to the terminal and notifies the user of appropriate measures.

[1631] Emergency response module: Links with the vehicle's safety management measures, automatically stops the vehicle in the event of an abnormality, and makes emergency contact if necessary.

[1632] Example of operation

[1633] When a user gets into an autonomous vehicle, the biometric information measurement means periodically measures the user's pulse and body temperature. This data is stored in the data storage means in real time and transmitted to the server via the data transmission means. The server uses an AI algorithm to analyze the data, and if an abnormality is detected, the notification management module sends a voice or push notification to the user. Furthermore, if a serious abnormality is detected, the safety management means within the vehicle is automatically activated, stopping the vehicle in a safe location and making an emergency call.

[1634] Prompt Sentence Examples

[1635] Below are some examples of specific prompt sentences for this system.

[1636] markdown

[1637] Use case: Vehicle Health Monitoring System

[1638] Requirements:

[1639] 1. Monitor real-time heart rate, body temperature, and user emotions using in-car sensors.

[1640] 2. Analyze collected data and send to centralized server for further processing.

[1641] 3. Alert the user with voice messages or display notifications on the Infotainment system if any abnormalities are detected.

[1642] ----

[1643] User Scenario:

[1644] A user is on a long drive. The system monitors the user's vital signs every 10 minutes. At 3 PM, the user's heart rate suddenly spikes and the emotion engine detects stress. The system alerts the user through the car's infotainment system, advising them to take a break and relax. If the user does not respond or if the signs of stress persist, the system automatically contacts emergency services.

[1645] The system of the present invention effectively manages the safety and health of users by monitoring their health status in real time and taking appropriate measures quickly and automatically if an abnormality is detected.

[1646] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1647] Step 1:

[1648] Sensors installed in the vehicle measure the user's biometric information (pulse, body temperature) and emotional information in real time. Heart rate and body temperature data, as well as voice and sidelong glance data to identify emotions, are required as input. The measured data is obtained as output.

[1649] Step 2:

[1650] The device temporarily stores the measured data in a data storage means. The input requires biometric and emotional information data provided by the sensors. The stored data is obtained as the output.

[1651] Step 3:

[1652] The device sends the stored data to the server using a secure communication protocol (e.g. HTTPS). The stored data is required as input. The data sent to the server is obtained as output.

[1653] Step 4:

[1654] The server analyzes the received data using AI algorithms to detect abnormal values ​​and dangerous health conditions. The input requires the transmitted biometric and emotional data. The output is the analysis results.

[1655] Step 5:

[1656] If the server detects an anomaly based on the analysis results, it generates a warning message for the user. The analysis result data is required as input, and the generated warning message is obtained as output.

[1657] Step 6:

[1658] The server sends the generated alert message to the user's terminal, the vehicle's infotainment system, or the user's smartphone via a notification means. The alert message is required as input, and the message notified to the user is obtained as output.

[1659] Step 7:

[1660] If a serious abnormality is detected, the vehicle's autonomous driving system will be activated and stop the vehicle in a safe place. Information on the abnormality detection is required as input, and the stopped vehicle is obtained as output.

[1661] Step 8:

[1662] Furthermore, in the event of an emergency, the server automatically contacts the configured emergency contacts. Emergency contact information and anomaly detection information are required as input. The output indicates that the emergency contact has been completed.

[1663] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1664] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1665] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1666] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1667] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1668] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1669] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1670] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1671] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1672] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1673] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1674] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1675] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1676] 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.

[1677] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1678] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1679] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1680] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1681] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1682] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1683] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1684] The following is further disclosed regarding the above embodiment.

[1685] (Claim 1)

[1686] a biological information measuring means for measuring biological information of a user;

[1687] a data storage means for storing the measured biological information;

[1688] a data transmission means for transmitting the stored biometric information to a server;

[1689] a notification means for receiving the analysis result from the server and notifying the user;

[1690] A system including:

[1691] (Claim 2)

[1692] 10. The system of claim 1,

[1693] The biological information measuring means is a system including sensors that measure pulse and body temperature.

[1694] (Claim 3)

[1695] 10. The system of claim 1,

[1696] The notification means is a system including a means for notifying the user by voice or push notification when an abnormal value is detected.

[1697] "Example 1"

[1698] (Claim 1)

[1699] a biological information measuring means for measuring biological information of a user;

[1700] a data storage means for temporarily storing the measured biological information;

[1701] data transmission means for transmitting a certain amount of data to a server after the data has been accumulated;

[1702] An analysis means for analyzing the data received by the server using an AI algorithm;

[1703] a message generating means for detecting an abnormality based on the analysis result and generating a notification message;

[1704] a notification means for notifying a user of the generated notification message;

[1705] A system including:

[1706] (Claim 2)

[1707] 10. The system of claim 1, including sensors for measuring pulse and temperature.

[1708] (Claim 3)

[1709] 10. The system of claim 1, further comprising means for notifying the user by voice or push notification when an abnormal value is detected.

[1710] "Application Example 1"

[1711] (Claim 1)

[1712] a biological information measuring means for measuring biological information of a user;

[1713] a data storage means for storing the measured biological information;

[1714] a data transmission means for transmitting the stored biometric information to a server;

[1715] a notification means for receiving the analysis result from the server and notifying the user;

[1716] The notification means is a means for notifying the administrator and the relevant user of abnormal values;

[1717] A system including:

[1718] (Claim 2)

[1719] The biological information measuring means includes a sensor for measuring pulse and body temperature.

[1720] 10. The system of claim 1.

[1721] (Claim 3)

[1722] The notification means includes means for notifying the user by voice or push notification when an abnormal value is detected.

[1723] 10. The system of claim 1.

[1724] "Example 2: Combining Emotion Engines"

[1725] (Claim 1)

[1726] a measuring means for measuring biometric information of a user;

[1727] a storage means for storing the measured biological information;

[1728] a data transmission means for transmitting the stored biometric information to a server;

[1729] a notification means for receiving the analysis result from the server and notifying the user;

[1730] emotion recognition means for analyzing voice data and facial expression data of a user and recognizing emotions;

[1731] a means for storing the recognized emotion data together with the biometric information and transmitting the data to a server;

[1732] The server analyzes the received data and, if an abnormality is detected, notifies the user of how to deal with the problem.

[1733] The notification system provides a means to notify users in real time based on notification messages from the server,

[1734] A system including:

[1735] (Claim 2)

[1736] 2. The system of claim 1, wherein the measuring means includes sensors for measuring pulse and body temperature.

[1737] (Claim 3)

[1738] 2. The system according to claim 1, wherein the notification means includes means for notifying the user by voice or push notification when an abnormal value is detected.

[1739] "Application example 2 when combining emotion engines"

[1740] (Claim 1)

[1741] a biological information measuring means for measuring biological information of a user;

[1742] a data storage means for storing the measured biological information;

[1743] a data transmission means for transmitting the stored biometric information to a server;

[1744] a notification means for receiving the analysis result from the server and notifying the user;

[1745] means for collecting health and emotional information of a user using sensors located within the vehicle;

[1746] A means to analyze the collected health and emotional information in real time and immediately send it to a server if an abnormality is detected.

[1747] If an abnormality is detected, a means for automatically stopping the vehicle in a safe place;

[1748] A means of automatically contacting emergency contacts,

[1749] A system including:

[1750] (Claim 2)

[1751] 2. The system according to claim 1, wherein the biological information measuring means includes sensors for measuring pulse and body temperature.

[1752] (Claim 3)

[1753] 2. The system according to claim 1, wherein the notification means notifies the user by voice or push notification when an abnormal value is detected. [Explanation of symbols]

[1754] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a biological information measuring means for measuring biological information of a user; a data storage means for storing the measured biological information; a data transmission means for transmitting the stored biometric information to a server; a notification means for receiving the analysis result from the server and notifying the user; A system including:

2. 10. The system of claim 1, The biological information measuring means is a system including sensors that measure pulse and body temperature.

3. 10. The system of claim 1, The notification means is a system including a means for notifying the user by voice or push notification when an abnormal value is detected.

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