System

Abstract

A system is provided.SOLUTION: A system comprising: means for monitoring the health status of an elderly person in real-time; means for detecting abnormal health conditions; means for automatically providing information about appropriate medical institutions and departments based on detected abnormalities; means for issuing notifications to family and care manager; means for automatically generating and providing application flows for necessary procedures and ancillary systems; and means for monitoring progress and sending reminders for uncompleted procedures.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] When an elderly person suddenly falls ill, their family or caregiver may not be able to take appropriate action quickly. Furthermore, the necessary procedures and applications for assistance after hospitalization or admission to a facility can be burdensome and complicated for family and caregivers. Therefore, there is a need for a system that supports prompt and appropriate responses in emergencies and a mechanism that provides comprehensive support for a series of procedures related to aftercare. [Means for solving the problem]

[0005] This invention provides a system that monitors the health status of elderly people in real time, and if an abnormality is detected, automatically provides information about appropriate medical institutions and departments to visit, and notifies family members and care managers. Specifically, a wearable device is used to acquire data on the elderly person's heart rate, blood pressure, amount of exercise, etc., and transmits it to a server. The server analyzes this data and generates appropriate instructions when an abnormal health condition is detected. In addition, after hospitalization or admission to a facility, the system automatically generates and provides users with a flow chart for necessary procedures and assistance program applications. Furthermore, the system is equipped with a function to monitor progress and send reminders for incomplete procedures, reducing the burden on elderly people and their families and enabling prompt and appropriate responses.

[0006] "Means for monitoring health status in real time" refers to a system that uses wearable devices and sensors to collect vital data such as elderly people's heart rate, blood pressure, and amount of exercise in real time.

[0007] The "means for detecting abnormal health conditions" is a mechanism that analyzes collected vital data and detects abnormal values ​​that exceed a pre-set threshold.

[0008] "Means for automatically providing information about appropriate medical institutions and departments to visit" refers to a system that automatically analyzes information about the necessary departments to visit and the nearest medical institutions based on detected abnormalities and provides it to the user.

[0009] "Means for issuing notifications to family members or care managers" refers to a system that sends notifications in real time to registered emergency contacts (family members or care managers) when an abnormality is detected.

[0010] "Means for automatically generating and providing necessary procedures and application flows for subsidy programs" refers to a system that automatically organizes information regarding necessary procedures and applications for subsidy programs after hospitalization or admission to a facility, and provides users with the procedures.

[0011] "Means for monitoring progress and sending reminders for incomplete procedures" refers to a mechanism for constantly checking the progress of procedures and sending reminders to the user for incomplete procedures.

[0012] A "wearable device" is a device that can be worn on the body and has the function of collecting vital data such as heart rate, blood pressure, and amount of exercise.

[0013] A "server" is a computer system that receives data via a network and performs processes such as analysis, storage, and notification.

[0014] "Data analysis" is the process of analyzing collected vital data to detect abnormal values.

[0015] An "alert" is a notification that alerts the user or emergency contacts when an abnormality is detected.

[0016] A "procedure flow" is a series of steps that indicate the order and content of procedures required after hospitalization or admission to a facility.

[0017] A "template" is a model of a document required for a specific procedure, and is provided in a format that allows the user to easily input and print.

[0018] "Reminders" is a function that notifies users of incomplete procedures or required actions. [Brief explanation of the drawings]

[0019] [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

[0020] 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.

[0021] First, the terms used in the following description will be explained.

[0022] 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).

[0023] 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.

[0024] 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.

[0025] 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.

[0026] 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."

[0027] [First embodiment]

[0028] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0029] 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.

[0030] 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).

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0036] 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.

[0037] 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.

[0038] 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.

[0039] 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."

[0040] To implement this invention, it is necessary to prepare a wearable device for monitoring the health status of the elderly, a server for analyzing the data, and a terminal that links with the user and emergency contacts. Below, the overall processing flow of the system is explained in natural language.

[0041] 1. Real-time health monitoring

[0042] Device: A wearable device collects vital data such as heart rate, blood pressure, and exercise volume of elderly people in real time. The device is worn on the user's body and measures the data periodically.

[0043] Server: Receives vital data sent from the device and stores it in a database, allowing the health of the elderly to be constantly monitored.

[0044] 2. Data analysis and anomaly detection

[0045] Server: Analyzes the received vital signs and compares them with historical data and baseline values. Algorithms are applied to detect abnormal values ​​(e.g., sudden increases in heart rate or abnormal blood pressure fluctuations).

[0046] Server: Generates an alert if an anomaly is detected. This alert is issued if an immediate response is required.

[0047] 3. Notification and Instructions

[0048] Server: When an alert is generated, a notification is sent to registered emergency contacts (family members or care managers), along with information about the relevant medical institution and department.

[0049] Device: The device of the emergency contact (e.g., a smartphone) receives the notification and instructs the elderly person's family member via voice or text on the appropriate action to take. Specifically, the message "Please contact the nearest internal medicine clinic" is displayed.

[0050] 4. Aftercare support

[0051] Server: When an elderly person is hospitalized or admitted to a facility, information on related procedures is collected and the necessary procedures and application flows for subsidy programs are automatically generated.

[0052] Device: Based on this flow, messages are displayed to guide the family member in need of assistance through the procedure. Templates of the necessary documents are also provided, allowing the family member to efficiently complete the necessary procedures.

[0053] 5. Progress monitoring and reminders

[0054] Terminal: As the user goes through each procedure, the progress is reported to the server. The user inputs the progress of the procedure from a smartphone or tablet.

[0055] Server: Records the progress in a database and generates reminders for incomplete procedures and sends them to the user's device, for example, a message saying "This procedure is not yet complete."

[0056] Specific examples

[0057] Scenario 1: Elderly person A records a heart rate of 150 bpm and blood pressure of 180 / 100

[0058] Device: The smartwatch collects this data and sends it to the server.

[0059] Server: Detects an abnormal value and notifies family member B, who is the emergency contact, that "A's heart rate has suddenly increased. Please contact the nearest internal medicine clinic."

[0060] Device: A notification appears on Mr. B's smartphone, and he rushes to the internal medicine department with Mr. A.

[0061] Scenario 2: Person A is hospitalized and family member B completes the necessary procedures

[0062] Server: Receives information about hospitalization and generates the necessary procedures and application flow for subsidy programs.

[0063] Device: Display the procedure flow on Mr. B's smartphone, stating "Please follow the admission procedures in this order," along with a template of the necessary documents.

[0064] Server: Monitors the progress of the transaction and sends reminders for any outstanding transactions.

[0065] The above is a specific method for carrying out the present invention. This system allows elderly people and their families to receive prompt and appropriate medical treatment and aftercare.

[0066] The processing flow will be explained below.

[0067] Step 1: Collecting health data

[0068] Device: A wearable device collects vital data such as heart rate, blood pressure, and exercise volume in real time. The device is attached to the elderly person's body and measures the data periodically.

[0069] Step 2: Sending data

[0070] Terminal: Collected vital data is sent to the server. The data is encrypted and transmitted securely over the network.

[0071] Step 3: Receiving and storing data

[0072] Server: Receives the data sent from the device and stores it in a database, which also includes the elderly person's past health data.

[0073] Step 4: Analyze the data

[0074] Server: Analyzes the stored data, comparing it with historical data and baseline values ​​and applying algorithms to detect abnormal values ​​(e.g., sudden increases in heart rate or abnormal blood pressure fluctuations).

[0075] Step 5: Detect anomalies

[0076] Server: Generates an alert if an anomaly is detected that exceeds a certain threshold, for example, if the heart rate increases by more than 50% of normal.

[0077] Step 6: Generate notifications

[0078] Server: Based on the generated alert, the server issues a notification to registered emergency contacts (family members or care managers), and also provides information on appropriate medical institutions and departments to visit.

[0079] Step 7: Receiving and Viewing Notifications

[0080] Device: The emergency contact's device (e.g., smartphone) receives the notification. The device displays specific instructions to the family member via voice or text, such as "Please contact the nearest internal medicine doctor."

[0081] Step 8: Family response

[0082] User: Family members receive notifications and follow instructions to take the elderly to medical facilities. They act quickly based on specific instructions.

[0083] Step 9: Obtain admission information

[0084] Server: When an elderly person is hospitalized, the server receives information about the hospitalization from the medical institution and stores it in a database.

[0085] Step 10: Generate procedural flow

[0086] Server: Automatically generates procedures for hospitalization and application procedures for subsidy programs, including the required documents and procedure sequence.

[0087] Step 11: Notification of procedure flow

[0088] Server: Sends the generated procedure flow to the family member's device. The device displays instructions such as "Please follow the procedure at the hospital in this order."

[0089] Step 12: Provide documentation

[0090] Server: Sends templates of the necessary documents to the device so that family members can use them to complete the procedures.

[0091] Step 13: Record the progress of the procedure

[0092] Device: As the family member goes through each procedure, they report their progress to the server. For example, they can use their smartphone to press a button to complete the procedure.

[0093] Step 14: Monitoring progress

[0094] Server: Records progress in a database and generates reminders for incomplete procedures.

[0095] Step 15: Send a reminder

[0096] Server: Sends a reminder to the family member's device about the incomplete procedure. The device displays the message "This procedure is not yet completed."

[0097] Example 1

[0098] 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."

[0099] There is a need for a system that can constantly monitor the health status of elderly people, detect abnormalities, and provide appropriate medical care promptly. However, existing systems are unable to collect and analyze data in real time, making it difficult to quickly notify patients when an abnormality occurs or take appropriate action. In addition, there is no automated system for providing information about hospitalization and procedures, monitoring progress, or sending reminders. For these reasons, there is a need to provide a system that can efficiently and effectively manage the health of elderly people.

[0100] 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.

[0101] In this invention, the server includes: a means for monitoring health status in real time; a means for detecting abnormal health status; a means for automatically providing information on appropriate medical institutions and departments based on the detected abnormalities; a means for issuing notifications to emergency contacts; a means for automatically generating and providing necessary procedures and application flows for subsidy programs; a means for monitoring progress and sending reminders for incomplete procedures; a means for analyzing data stored on the server and using an algorithm to detect abnormal values; a means for using a secure protocol for data communication between the server and a terminal; and a means for sending voice or text notifications to emergency contacts. This allows for real-time monitoring of the health status of elderly people and enables prompt and appropriate response in the event of an abnormality. Furthermore, the provision of information on hospitalization and procedures, progress monitoring, and sending reminders are automated, reducing the burden on elderly people and their families.

[0102] "Real-time health monitoring" refers to the use of wearable devices to continuously collect personal physical data (e.g., heart rate, blood pressure, and exercise volume) and to analyze and manage that data in real time.

[0103] "Detecting abnormal health conditions" refers to identifying abnormal values ​​(e.g., sudden increases in heart rate or abnormal fluctuations in blood pressure) based on collected data and comparing them with baseline values ​​or past data.

[0104] "Automatically providing information about appropriate medical institutions and departments" means that when an abnormality is detected, information about the medical institution and department that is most suitable for the abnormality is automatically provided to the user.

[0105] "Issuing a notification to an emergency contact" means that if an abnormality is detected, a notification will be sent promptly to a pre-registered emergency contact (e.g., family member or care manager).

[0106] "Automatic generation of application flows for procedures and subsidy systems" means that the system automatically generates and provides application flows for procedures and subsidy systems that are necessary when elderly people are hospitalized or admitted to a facility.

[0107] "Progress monitoring" means tracking and managing the progress of each step of a user's procedure in real time.

[0108] "Sending reminders" means sending notifications or alerts to users when there are incomplete procedures or important steps.

[0109] An "algorithm for analyzing data and detecting outliers" is a program or mathematical method for identifying outliers based on collected data.

[0110] A "secure protocol for data communication between a server and a terminal" is a communication method (e.g., HTTPS, TLS) for securely transmitting data between a server and a terminal.

[0111] "Send voice and text notifications" refers to sending important messages to users in the form of voice alerts and text messages.

[0112] A "wearable device" is a small electronic device that can be worn on the body and collects physical data such as heart rate, blood pressure, and exercise volume.

[0113] A "server" is a computer on a network that stores and analyzes data, detects anomalies, and sends notifications.

[0114] A "terminal" is a device (e.g., a smartphone or tablet) that receives data from a server or wearable device and gives instructions to the user.

[0115] "Entering progress status" means that the user reports the progress of the procedure to the system using a smartphone or tablet.

[0116] "Procedure flow suggestions" means that the system automatically provides the order and methods of procedures that elderly people and their families should follow.

[0117] "Providing templates for required documents" means providing the user with formats for documents required to carry out the procedure.

[0118] MODE FOR CARRYING OUT THE INVENTION

[0119] To implement this invention, it is necessary to build a system that monitors the health status of elderly people in real time, detects abnormalities, and provides instructions on appropriate measures. Specifically, the following hardware and software are required:

[0120] System configuration

[0121] 1. Wearable devices

[0122] Device:

[0123] Wearable devices (e.g., health trackers, smartwatches) collect real-time vital data such as heart rate, blood pressure, and physical activity of elderly people. These devices can be worn on the body and transmit the data to a connected smartphone via Bluetooth or Wi-Fi.

[0124] 2. Smartphone (or tablet)

[0125] Device:

[0126] The smartphone receives data from the wearable device and sends it to a cloud server using a secure communication protocol (e.g., HTTPS).

[0127] 3. Cloud Server

[0128] server:

[0129] A cloud server (e.g., Amazon Web Services, Google (registered trademark) Cloud) receives the vital data sent from the smartphone and stores it in a dedicated database (e.g., Amazon RDS, Firebase RealTime Database).

[0130] Data analysis and anomaly detection

[0131] server:

[0132] The received data is analyzed using an anomaly detection algorithm (e.g., machine learning model) created in Python or R. Anomalies are detected by comparing them with past data and reference values ​​(e.g., heart rate 60-100 bpm, blood pressure below 120 / 80).

[0133] Sending alerts and notifications

[0134] server:

[0135] If abnormal data is detected (e.g. heart rate 150 bpm, blood pressure 180 / 100), an alert is generated and a notification is sent to emergency contacts using Twilio or Firebase Notifications.

[0136] Device:

[0137] The smartphone of the emergency contact (e.g., family member or care manager) receives a notification and instructs the elderly person's family member on appropriate actions via voice notification or text message.

[0138] Automatic generation and support of procedures

[0139] server:

[0140] When an elderly person is hospitalized or admitted to a facility, information about the hospitalization is received and a Python script is used to automatically generate the necessary procedures and application flow for subsidy programs.

[0141] Device:

[0142] The system sends a notification to the emergency contact's smartphone explaining the procedure and provides templates for the necessary documents. For example, it includes specific instructions such as "Please follow this order when completing the admission procedures."

[0143] Progress monitoring and reminders

[0144] User:

[0145] As the emergency contact (family member) goes through the procedure, they enter the progress into the server via their smartphone.

[0146] server:

[0147] The entered progress is recorded in a database, and reminders are generated and sent to the user's device for any incomplete procedures, such as a "This procedure is not yet complete" reminder.

[0148] Specific examples

[0149] Scenario 1: Elderly person A records a heart rate of 150 bpm and blood pressure of 180 / 100

[0150] Device: The smartwatch collects this data and sends it to a cloud server via the smartphone.

[0151] Server: Detects an abnormal value and uses the Twilio API to notify the family member who is the emergency contact, saying, "Mr. A's heart rate has suddenly increased. Please contact the nearest internal medicine clinic."

[0152] Device: A notification appears on the family member's smartphone, and they rush to the internal medicine department with Mr. A.

[0153] Scenario 2: Person A is hospitalized and family member B completes the necessary procedures

[0154] Server: Receives information about hospitalization and generates procedures and application flows for subsidy programs.

[0155] Device: The family member's smartphone will be shown a procedure flow stating, "Please follow the admission procedures in this order," along with a template of the necessary documents.

[0156] Server: Monitors the progress of the transaction and sends reminders for any outstanding transactions.

[0157] Prompt Sentence Examples

[0158] "Write Python code to analyze heart rate and blood pressure data and detect outliers."

[0159] "How do I use the Twilio API to send an SMS in case of an error?"

[0160] This system allows elderly people and their families to receive prompt and appropriate medical response and aftercare.

[0161] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0162] Step 1:

[0163] Data collection

[0164] Device: A wearable device (e.g., a smartwatch) collects vital data such as heart rate, blood pressure, and activity level in real time. The device collects data every few seconds and transmits it to a connected smartphone via Bluetooth or Wi-Fi.

[0165] Input: Real-time vital data from biosensors.

[0166] Output: Collected vital data is sent to a smartphone.

[0167] Step 2:

[0168] Data transmission

[0169] Terminal: The smartphone receives data from the wearable device and sends it to the cloud server using a secure communication protocol (e.g., HTTPS).

[0170] Input: Vital data collected by the device.

[0171] Output: Vital data sent to cloud server via secure communication.

[0172] Step 3:

[0173] Data reception and storage

[0174] Server: A cloud server (e.g., AWS (registered trademark) EC2) receives the vital data sent from the smartphone and stores it in a dedicated database (e.g., Amazon RDS).

[0175] Input: Vital data sent over secure communication.

[0176] Output: Vital data stored in a database.

[0177] Step 4:

[0178] Data analysis

[0179] Server: The received data is analyzed using an anomaly detection algorithm (e.g., machine learning model) created in Python or R. The data is compared with past vital signs and reference values ​​(e.g., heart rate 60-100 bpm, blood pressure below 120 / 80) to detect abnormal values.

[0180] Input: Saved vital data and baseline values, historical data.

[0181] Output: Information about detected outliers.

[0182] Step 5:

[0183] Alert Generation

[0184] Server: If abnormal data is detected (e.g., heart rate 150 bpm, blood pressure 180 / 100), a Python script generates an alert that explains what caused the abnormality and recommends corrective actions.

[0185] Input: Outlier information as an analysis result.

[0186] Output: Alert information.

[0187] Step 6:

[0188] Send notifications

[0189] Server: Based on the generated alert, a notification is sent to emergency contacts using Twilio or Firebase Notifications. The notification includes specific instructions such as "Your heart rate has increased dramatically. Please contact the nearest medical facility."

[0190] Input: The generated alert information.

[0191] Output: Notification message sent to emergency contacts.

[0192] Step 7:

[0193] Receive notifications

[0194] Device: The smartphone of the emergency contact (e.g., family member) receives the notification and instructs the elderly family member on appropriate actions via voice notification or text.

[0195] Input: The notification message sent by the server.

[0196] Output: Notification content displayed on the emergency contact's device.

[0197] Step 8:

[0198] Procedural flow generation

[0199] Server: When an elderly person is hospitalized or admitted to a facility, a Python script is used to automatically generate the necessary procedures and application flow for subsidy programs.

[0200] Input: Information about hospitalization and institutionalization.

[0201] Output: Generated procedure flow and subsidy application guide.

[0202] Step 9:

[0203] Procedure flow notification

[0204] Server: The generated procedure flow is sent to the smartphone of the emergency contact. The notification includes specific instructions such as "Please follow the admission procedure in this order."

[0205] Input: The generated procedure flow.

[0206] Output: The procedure flow sent to the emergency contact's device.

[0207] Step 10:

[0208] Entering the progress of procedures

[0209] User: As the emergency contact (family member) goes through each procedure, they enter the progress information into the server using their smartphone or tablet.

[0210] Input: Procedural progress.

[0211] Output: Progress data reported to the server.

[0212] Step 11:

[0213] Progress monitoring

[0214] Server: Records the entered progress in a database and monitors the progress of the procedure.

[0215] Input: User-reported progress data.

[0216] Output: Progress and monitoring results recorded in a database.

[0217] Step 12:

[0218] Generate and send reminders

[0219] Server: Generates reminders for incomplete procedures and sends them to the user's device. For example, it sends a reminder notification saying "This procedure has not yet been completed."

[0220] Input: Progress data and open procedure information.

[0221] Output: The reminder notification sent to the user's device.

[0222] (Application example 1)

[0223] 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."

[0224] Real-time monitoring of the health status of elderly people and early detection of abnormalities are important challenges for families and care managers. Rapid and accurate responses are also required when abnormalities are detected. Furthermore, there is a need to streamline procedures for post-health abnormality procedures and applications for subsidies, and to appropriately manage progress. However, conventional systems have had difficulty fully meeting these requirements.

[0225] 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.

[0226] In this invention, the server includes a means for collecting and analyzing vital data from the wearable device using a smartphone and smart glasses, detecting abnormalities and sending notifications, a means for acquiring data such as the elderly person's heart rate, blood pressure, and amount of exercise using the wearable device and sending it to the server via the smartphone and smart glasses, and a means for providing templates for required documents based on a proposed procedure flow and sending incomplete reminders, thereby enabling early detection of abnormalities and rapid response, efficient procedure support, and appropriate progress management.

[0227] Here are the definitions:

[0228] "Health status of the elderly" refers to vital data such as the elderly's heart rate, blood pressure, and amount of exercise.

[0229] "Means of real-time monitoring" refers to a system that uses wearable devices to continuously collect vital data and send it to a server, allowing the data to be checked immediately.

[0230] "Means for detecting abnormal health conditions" refers to algorithms that analyze collected vital data and compare it with baseline values ​​to detect abnormal values.

[0231] "Means for automatically providing information about appropriate medical institutions and departments" refers to a system that provides data about the nearest appropriate medical institutions and departments based on detected abnormalities.

[0232] "Means of issuing notifications to family members or care managers" refers to a notification mechanism that sends an alert to emergency contacts when an abnormality is detected.

[0233] "Means for automatically generating and providing application flows for procedures and subsidy programs" refers to the function of automatically generating and providing information regarding procedures and applications for subsidy programs that are necessary when an elderly person is hospitalized, for example.

[0234] "Means for monitoring progress and sending reminders for incomplete procedures" refers to a system that monitors the progress of procedures and sends reminder notifications for incomplete procedures.

[0235] "Smartphones and smart glasses" refer to portable devices that receive, analyze, and notify data from wearable devices.

[0236] A "wearable device" refers to a device that is worn on the body and continuously collects vital data.

[0237] "Means for collecting and analyzing data, detecting abnormalities, and notifying" refers to a system that collects vital data from wearable devices, analyzes it on a server to detect abnormalities, and sends notifications to emergency contacts.

[0238] In order to implement the present invention, the following hardware and software are used.

[0239] Hardware:

[0240] 1. Wearable devices: Devices that collect vital data such as heart rate, blood pressure, and physical activity of elderly people. These devices include, for example, smart watches and fitness trackers.

[0241] 2. Smartphones and smart glasses: These devices are used to receive data collected from wearable devices and send it to the server. Smartphones are used to run applications and display notifications. Smart glasses are also used to display data and receive notifications.

[0242] 3. Server: A server that receives and analyzes data from wearable devices.

[0243] software:

[0244] 1. Data collection and transmission program: A program for collecting data from wearable devices and transmitting it to a server through smartphones and smart glasses.

[0245] 2. Data analysis program: A program that analyzes vital data on the server and detects abnormalities. For example, it can be implemented using Python or R.

[0246] 3. Notification program: This program sends an alert to emergency contacts when an abnormality is detected. This program uses RESTful APIs or Firebase Cloud Messaging (FCM) to send notifications.

[0247] 4. Procedure flow provision and reminder program: This program automatically generates information regarding procedures after a health abnormality and applications for subsidies, and reminds users of incomplete procedures.

[0248] Process flow:

[0249] 1. Data collection: The wearable device periodically measures the elderly person's heart rate, blood pressure, and physical activity, and transmits the data to a smartphone and smart glasses.

[0250] 2. Data transmission: The smartphone and smart glasses transmit the received vital data to the server via Bluetooth.

[0251] 3. Data analysis: The server analyzes the received vital data and compares it with baseline values ​​to detect abnormalities. Machine learning algorithms and rule-based analysis methods are used for the analysis.

[0252] 4. Anomaly detection and notification: If an anomaly is detected, the server will send an alert to emergency contacts, notifying them of the abnormal data and recommending a course of action (e.g., "Contact your local internal medicine doctor").

[0253] 5. Providing procedure flow and reminders: When an elderly person is hospitalized, the server automatically generates a procedure flow and a template of the necessary documents and sends them to the smartphone or smart glasses. It also monitors the progress and sends reminder notifications if the procedure is incomplete.

[0254] Examples:

[0255] Scenario 1:

[0256] When an elderly person's heart rate reaches 150 bpm and blood pressure reaches 180 / 100, the server detects the abnormality and sends an alert to the smartphone and smart glasses saying, "Your heart rate has suddenly increased. Please contact your internal medicine doctor."

[0257] Scenario 2:

[0258] When an elderly person is hospitalized and their family members are completing the necessary procedures, the server generates a procedure flow and a template of the necessary documents, and displays it on the family members' smartphones and smart glasses, telling them to "proceed with the procedures in this order." It also reminds them of any incomplete procedures.

[0259] Example of a generative AI model prompt:

[0260] Example prompt:

[0261] We built a system to monitor the health of elderly people. The system collects and analyzes data from wearable devices in real time and sends notifications to emergency contacts if an abnormality is detected. We used Python and RESTful APIs to implement the processes for data transmission, anomaly detection, and notification generation.

[0262] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0263] Step 1:

[0264] Data collection

[0265] Input: A wearable device (e.g., a smartwatch) collects vital data such as an elderly person's heart rate, blood pressure, and activity level.

[0266] How it works: Measures vital signs at regular intervals and syncs the data with your smartphone and smart glasses.

[0267] Output: The measured vital data is sent to a smartphone and smart glasses.

[0268] Step 2:

[0269] Data transmission

[0270] Input: Vital data received from a wearable device.

[0271] How it works: The smartphone and smart glasses transmit the vital data they receive via Bluetooth to a server.

[0272] Output: Vital data arrives at the server.

[0273] Step 3:

[0274] Data analysis

[0275] Input: Vital data sent to the server.

[0276] How it works: The server uses programs such as Python to analyze vital data. The data is compared with known normal values ​​and calculations are performed to detect abnormalities.

[0277] Output: If an anomaly is detected, the type of anomaly and the anomaly detection result are generated. If no anomaly is detected, the analysis result is stored.

[0278] Step 4:

[0279] Anomaly detection and notification

[0280] Input: Anomaly detection results generated by data analysis.

[0281] How it works: The server generates and sends alerts to emergency contacts based on the anomaly detection results. Alerts are sent using RESTful APIs and Firebase Cloud Messaging (FCM).

[0282] Output: An alert is sent to emergency contacts and a notification is displayed on the smartphone and smart glasses.

[0283] Step 5:

[0284] Procedural flow provided

[0285] Input: Elderly person's admission information and related procedure information.

[0286] Operation: The server automatically generates the steps required for a target procedure such as hospitalization and prepares templates for the necessary documents.

[0287] Output: The procedure flow and templates of required documents are sent to the smartphone and smart glasses.

[0288] Step 6:

[0289] Reminder generation

[0290] Input: Procedural progress data entered by the user.

[0291] Behavior: The server monitors the progress of procedures and generates reminders for incomplete procedures. Reminders are generated based on progress data.

[0292] Output: Reminders for outstanding procedures are sent to the user's smartphone and smart glasses.

[0293] (Example prompt):

[0294] "We built a system to monitor the health of elderly people. The system collects and analyzes data from wearable devices in real time, and sends notifications to emergency contacts if an abnormality is detected. We used Python and RESTful APIs to implement the processes for data transmission, anomaly detection, and notification generation."

[0295] 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.

[0296] This system monitors the health status of elderly people in real time, and when abnormalities are detected, it provides information on appropriate medical institutions and departments and issues notifications to family members and care managers. It also automatically generates procedures for post-hospitalization and facility admission, as well as application flows for subsidy programs, and monitors progress to send reminders for incomplete procedures. Furthermore, by combining it with an emotion engine that recognizes user emotions, it can automatically adjust the content of notifications and the presentation method of the procedure flow.

[0297] System configuration

[0298] 1. Health monitoring

[0299] Device: A wearable device collects vital data such as heart rate, blood pressure, and exercise volume of elderly people in real time. It is worn on the user's body and measures the data periodically.

[0300] Server: Receives vital data sent from the device and stores it in a database. This data is analyzed and generates an alert if an abnormality is detected.

[0301] 2. Anomaly detection and notification

[0302] Server: Analyzes the received data and compares it with the reference values. If an abnormal value is detected, a notification is sent to the registered emergency contacts. The notification also includes information on the appropriate medical institution and department to visit.

[0303] Device: The emergency contact's device will receive a notification and display voice and text instructions, allowing for a quick response.

[0304] 3. Assistance with admission procedures

[0305] Server: When an elderly person is hospitalized, the necessary procedures and application flow for subsidy programs are automatically generated. This information is sent to the family's device, and the procedure order and templates for the necessary documents are provided.

[0306] Device: The procedure flow is displayed on the family member's device, helping the user to complete the procedure easily.

[0307] 4. Progress monitoring and reminders

[0308] The device reports its progress to the server as it processes the transaction, which records the progress in a database and sends reminders about any outstanding transactions.

[0309] Server: Monitors the progress of procedures and sends reminders to family members' devices about incomplete procedures, helping them remember to complete them.

[0310] Combining Emotion Engines

[0311] 5. Emotion recognition

[0312] Device: Using sensors such as cameras and microphones, the device recognizes the user's emotions in real time, analyzing facial expressions and tone of voice to detect emotional states.

[0313] Server: Receives emotional data analyzed by the emotion engine and adjusts the notification content and procedure flow presentation method based on this data. For example, if the user is feeling stressed, the notification will be more friendly and the procedure flow will be more concise.

[0314] 6. Emotion-Based Regulation

[0315] Server: Based on the user's emotional state detected by the emotion engine, the server dynamically adjusts the content of notifications and the way procedural flow is presented, making it easier for users to understand and reducing stress.

[0316] Device: Display tailored notifications and procedural flows on the user's device, for example adding encouraging messages if the user is feeling anxious.

[0317] Specific examples

[0318] Health monitoring and anomaly detection

[0319] Scenario: Elderly person A's heart rate is 150 bpm and blood pressure is 180 / 100.

[0320] Device: The smartwatch collects this data and sends it to the server.

[0321] Server: Detects an abnormality and notifies emergency contacts, saying, "Mr. A's heart rate has suddenly increased. Please contact the nearest internal medicine clinic."

[0322] Device: A notification appears on the emergency contact's smartphone, and family member B takes person A to the internal medicine clinic.

[0323] Assistance with admission procedures

[0324] Scenario: Person A is hospitalized and family member B completes the necessary procedures.

[0325] Server: Collects information about hospitalization and automatically generates procedural flow.

[0326] Device: Mr. B's smartphone displays instructions such as "Please complete the admission procedures in this order," and also provides templates for the necessary documents.

[0327] Emotional Engine Adjustment

[0328] Scenario: When B is going through the procedure, the camera detects an anxious expression on B's face.

[0329] Device: The camera analyzes Mr. B's facial expression and sends his stress level to the emotion engine.

[0330] Server: Receives emotion data, simplifies the process, and adds encouraging messages.

[0331] Device: The adjusted procedure flow is displayed on Mr. B's smartphone, making it easier to proceed with the procedure.

[0332] The above is a specific method for implementing the present invention. This system enables elderly people and their families to receive prompt and appropriate medical treatment and aftercare, and furthermore, the emotional engine provides support to reduce stress and anxiety in users.

[0333] The processing flow will be explained below.

[0334] This system monitors the health status of elderly people in real time, and when abnormalities are detected, it provides information on appropriate medical institutions and departments and issues notifications to family members and care managers. It also automatically generates procedures for post-hospitalization and facility admission, as well as application flows for subsidy programs, and monitors progress to send reminders for incomplete procedures. Furthermore, by combining it with an emotion engine that recognizes user emotions, it can automatically adjust the content of notifications and the presentation method of the procedure flow.

[0335] System processing steps

[0336] 1. Real-time health monitoring

[0337] Step 1:

[0338] Device: Wearable devices (e.g., smartwatches) collect vital data such as heart rate, blood pressure, and exercise volume in real time. The device is worn on the user's body and measures data every second.

[0339] Step 2:

[0340] Terminal: Sends collected vital data to the server. The data is encrypted and sent over the network using a secure protocol.

[0341] Step 3:

[0342] Server: Receives data sent from the device and stores it in a real-time database. The stored data is immediately available for analysis.

[0343] 2. Data analysis and anomaly detection

[0344] Step 4:

[0345] Server: Analyzes the received vital data. It compares it with past data and preset reference values ​​and uses algorithms to detect abnormalities. For example, if the heart rate rises by more than 50% of normal.

[0346] Step 5:

[0347] Server: Generates an alert when an anomaly is detected. The alert includes details of the anomaly (e.g., a sudden increase in heart rate).

[0348] 3. Issuing and Receiving Emergency Notifications

[0349] Step 6:

[0350] Server: Based on the generated alert, the server issues a notification to registered emergency contacts (family members or care managers), including information on the appropriate medical institution and department.

[0351] Step 7:

[0352] Device: The emergency contact's device (e.g., smartphone) receives the notification, which may include a voice notification or a text message with specific instructions, such as "Contact your nearest internal medicine doctor."

[0353] 4. Incorporating and adjusting the emotional engine

[0354] Step 8:

[0355] Device: Uses a camera and microphone to collect the user's facial expressions and tone of voice in real time. Example: Analyzing emotional state from facial expressions.

[0356] Step 9:

[0357] Server: The emotion engine analyzes the collected data and determines the user's emotional state (e.g., anxiety, stress, relief).

[0358] Step 10:

[0359] Server: Based on the analysis results of the emotion engine, the server automatically adjusts the notification content and the way the procedure flow is presented. If the user is anxious, the server makes the notification content more user-friendly and simplifies the procedure flow.

[0360] Step 11:

[0361] Device: Display tailored notifications and procedural flows on the user's device. For example, display encouraging messages or simple instructions to a user who is feeling anxious.

[0362] 5. Assist with admission procedures and monitor progress

[0363] Step 12:

[0364] Server: When an elderly person is hospitalized, the server receives information about the hospitalization from the medical institution and stores it in a database.

[0365] Step 13:

[0366] Server: Automatically generates the procedures required to support hospital admission procedures and application flows for subsidy programs, including the required documents and procedure sequence.

[0367] Step 14:

[0368] Device: The procedure flow and templates for required documents are displayed on the family member's device (e.g., smartphone). For example, instructions such as "Please complete the admission procedures in this order" are displayed.

[0369] Step 15:

[0370] Device: As family members go through the process, they report their progress to the server. Progress is recorded manually or automatically.

[0371] Step 16:

[0372] Server: Monitors progress in real time and generates reminders for incomplete procedures.

[0373] Step 17:

[0374] Devices: Reminders are sent to family members' devices about incomplete transactions, such as the message "This transaction is not yet complete."

[0375] Specific examples

[0376] Scenario 1: Health monitoring and anomaly detection

[0377] If elderly person A's heart rate is recorded as 150 bpm and blood pressure as 180 / 100, the following steps are executed:

[0378] Device: The smartwatch collects this data and sends it to the server.

[0379] Server: Detects an abnormality and notifies emergency contacts, saying, "Mr. A's heart rate has suddenly increased. Please contact the nearest internal medicine clinic."

[0380] Device: A notification appears on the emergency contact's smartphone, and family member B takes person A to the internal medicine clinic.

[0381] Scenario 2: Assistance with admission procedures

[0382] When Person A is admitted to the hospital and Family Member B makes the necessary arrangements, the following steps are taken:

[0383] Server: Collects information about hospitalization and sends an automatically generated procedure flow to the family's device.

[0384] Device: Mr. B's smartphone displays instructions such as "Please complete the admission procedures in this order," and also provides templates for the necessary documents.

[0385] Scenario 3: Emotion Engine Regulation

[0386] If the camera detects an anxious expression on Mr. B's face as he goes through the process, the next step is executed.

[0387] Device: The camera analyzes Mr. B's facial expression and sends his stress level to the emotion engine.

[0388] Server: Receives emotion data, simplifies the process, and adds encouraging messages.

[0389] Device: The adjusted procedure flow is displayed on Mr. B's smartphone, making it easier to proceed with the procedure.

[0390] The above is a specific method for implementing the present invention. This system enables elderly people and their families to receive prompt and appropriate medical treatment and aftercare, and furthermore, the emotional engine provides support to reduce stress and anxiety in users.

[0391] Example 2

[0392] 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."

[0393] The challenge is to monitor the health status of elderly people in real time and provide prompt and appropriate medical treatment when abnormalities occur. It is also necessary to reduce incomplete procedures by managing the progress of procedures and sending necessary reminders. Furthermore, it is required to reduce stress and anxiety by adjusting notification content and procedure flow according to the user's emotional state.

[0394] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for monitoring the health condition of the elderly person in real time, means for detecting abnormal health conditions, means for automatically providing information on appropriate medical institutions and departments to visit based on the detected abnormalities, means for issuing notifications to family members and care managers, means for automatically generating and providing necessary procedures and application flows for subsidy programs, means for monitoring progress and sending reminders for incomplete procedures, and means for adjusting the notification content and the presentation method of the procedure flow using an emotion engine that recognizes the user's emotions. This makes it possible to monitor the health condition of the elderly person in real time, detect abnormalities, provide appropriate medical information, manage the progress of procedures, and adjust the notification content according to the user's emotions.

[0395] The term "elderly" generally refers to people aged 65 and over.

[0396] "Health status" refers to physiological and physical data such as heart rate, blood pressure, and activity level.

[0397] "Real-time" refers to processing and response occurring immediately with little or no delay.

[0398] "Abnormal" refers to health indicators such as heart rate, blood pressure, or activity level that are outside the normal range.

[0399] "Medical institution" refers to a facility that provides medical services, such as a hospital, clinic, or medical office.

[0400] "Medical department" refers to a medical department that handles a specific medical field, such as internal medicine, surgery, or psychosomatic medicine.

[0401] "Notification" refers to an alert or communication of information issued when an abnormality is detected, etc.

[0402] "Family" refers to the elderly person's close relatives, kin, or trusted acquaintances.

[0403] A "care manager" is a professional who creates care plans for elderly people and supports their progress.

[0404] "Procedure flow" refers to the series of procedures or steps required to achieve a specific purpose.

[0405] "Subsidy system" refers to public support programs for health management, medical care, nursing care, etc. available to the elderly.

[0406] "Reminder" refers to a notification or message that informs a user about an incomplete procedure.

[0407] An "emotion engine" refers to a system that analyzes a user's emotional state and adjusts the way information is presented accordingly.

[0408] This system monitors the health status of elderly people in real time, and when abnormalities are detected, it provides information on appropriate medical institutions and departments and issues notifications to family members and care managers. It also automatically generates procedures for post-hospitalization and facility admission, as well as application flows for subsidy programs, and monitors progress to send reminders for incomplete procedures. Furthermore, by combining it with an emotion engine that recognizes user emotions, it can automatically adjust the content of notifications and the presentation method of the procedure flow.

[0409] System configuration

[0410] 1. Health monitoring

[0411] Devices: Wearable devices collect vital data such as heart rate, blood pressure, and physical activity of elderly people in real time. These devices usually use APIs to collect data and send it to a server at regular intervals. For example, a smartwatch can be used as a device to collect and send this data.

[0412] Server: Receives vital data sent from the device and stores it in a database. This data is analyzed and an alert is generated if an abnormality is detected. Machine learning models are used to analyze the data.

[0413] 2. Anomaly detection and notification

[0414] Server: Compares the received vital data with the reference values, and if an abnormal value is detected, issues a notification to the registered emergency contacts. The notification also includes information on the appropriate medical institution and department to visit, enabling a prompt response.

[0415] Device: The emergency contact's device receives the notification and displays voice and text instructions. For example, a smartphone can handle this function.

[0416] 3. Assistance with admission procedures

[0417] Server: When an elderly person is hospitalized, the necessary procedures and application flow for subsidy programs are automatically generated. This information is sent to the family's device, and the order of procedures and templates for required documents are provided.

[0418] Device: The procedure flow is displayed on the family member's device, helping the user to easily proceed with the procedure.

[0419] 4. Progress monitoring and reminders

[0420] Terminal: Reports progress to the server as the procedure proceeds.

[0421] Server: Progress is recorded in a database and reminders are generated for any outstanding procedures. These reminders are sent to family members' devices, helping them remember to complete the procedures.

[0422] Combining Emotion Engines

[0423] 5. Emotion recognition

[0424] Device: Using sensors such as cameras and microphones, the device recognizes the user's emotions in real time. For example, it analyzes facial expressions and tone of voice to detect emotional states.

[0425] Server: Receives emotional data analyzed by the emotion engine and adjusts the notification content and procedure flow presentation method based on this data. For example, if the user is feeling stressed, the notification will be more friendly and the procedure flow will be more concise.

[0426] 6. Emotion-Based Regulation

[0427] Server: Based on the user's emotional state detected by the emotion engine, the server dynamically adjusts the notification content and the way the procedure flow is presented, making it easier for the user to understand and reducing stress.

[0428] Device: Tailored notifications and flow of procedures are displayed on the user's device, for example, adding encouraging messages if the user is feeling anxious.

[0429] Specific examples

[0430] Health monitoring and anomaly detection

[0431] Scenario: An elderly person has a heart rate of 150 bpm and a blood pressure of 180 / 100.

[0432] Device: The smartwatch collects this data and sends it to the server.

[0433] Server: Detects an abnormality and notifies the emergency contact, saying, "Mr. A's heart rate has suddenly increased. Please contact the nearest internal medicine clinic."

[0434] Device: A notification appears on the emergency contact's smartphone, allowing the family member to take the elderly person to the internal medicine clinic.

[0435] Assistance with admission procedures

[0436] Scenario: An elderly person is hospitalized and a family member handles the procedures.

[0437] Server: Collects information about hospitalization and automatically generates procedural flow.

[0438] Device: Instructions such as "Please complete the admission procedures in this order" are displayed on the family member's smartphone, and templates for the necessary documents are also provided.

[0439] Emotional Engine Adjustment

[0440] Scenario: The camera detects anxious facial expressions as a family member goes through a procedure.

[0441] Device: The camera analyzes facial expressions and sends the stress level to the emotion engine.

[0442] Server: Receives emotion data, simplifies the procedure flow, and adds encouraging messages.

[0443] Device: The adjusted procedure flow is displayed on the family member's smartphone, making it easier to proceed with the procedure.

[0444] The above is a specific embodiment of the present invention. This system enables elderly people and their families to receive prompt and appropriate medical treatment and aftercare, and also reduces stress and anxiety with the support of the emotion engine.

[0445] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0446] Step 1: Collect data

[0447] Device: Wearable devices collect vital data such as heart rate, blood pressure, and physical activity of elderly people in real time. For example, a smart watch measures and records this data instantly. The input is the biometric data collected by the sensor, and the output is a set of obtained vital data.

[0448] Step 2: Sending data

[0449] Terminal: The collected data is encrypted using a secure protocol (e.g., HTTPS) and sent to the server. When sending, the API's sendVitalData() function is called. The input is the collected vital data, and the output is the data received on the server side.

[0450] Step 3: Receiving and storing data

[0451] Server: Receives vital data sent from the device and saves it in the database. The receiveData() function is used for receiving, and the saveToDatabase() function is used for saving. The input is the vital data sent from the device, and the output is the data saved in the database.

[0452] Step 4: Analyze the data

[0453] Server: Analyzes the stored vital data and detects abnormal values ​​using a machine learning model (generative AI model). The analyzeData() function is used for the analysis. The input is the stored vital data, and the output is the anomaly detection information as the analysis result.

[0454] Step 5: Detect anomalies and generate notifications

[0455] Server: If an anomaly is detected, a notification is generated containing information about the appropriate medical institution and department. The generateAlert() function is used to generate the notification. The input is the anomaly detection information, and the output is the notification message.

[0456] Step 6: Sending notifications

[0457] Server: Sends the generated notification to the registered emergency contacts. The sendNotification() function is used to send notifications. The input is the notification message, and the output is the notification sent to the emergency contacts.

[0458] Step 7: View notifications

[0459] Terminal: The emergency contact's terminal receives the notification and displays instructions by voice or text. The showNotification() function is used for display. The input is the received notification message, and the output is the displayed notification information.

[0460] Step 8: Automatic generation of procedural flow

[0461] Server: When an elderly person is hospitalized, the necessary procedures and application flow for subsidy programs are automatically generated. The generateProcedureFlow() function is used for generation. The input is hospitalization information, and the output is the automatically generated procedure flow.

[0462] Step 9: Present the procedure flow

[0463] Terminal: The procedure flow is displayed on the family member's terminal, helping the user to easily proceed with the procedure. The displayProcedureInstructions() function is used for display. The input is the automatically generated procedure flow, and the output is the displayed procedure flow.

[0464] Step 10: Report progress

[0465] Terminal: When a procedure is performed, the progress is reported to the server. The reportProgress() function is used for reporting. The input is the procedure information in progress, and the output is the progress data sent to the server.

[0466] Step 11: Track progress and generate reminders

[0467] Server: Records progress in a database and generates reminders for incomplete procedures. Recording is done using the recordProgress() function, and reminders are generated using the generateReminder() function. The input is the progress data, and the output is the recorded progress and the generated reminders.

[0468] Step 12: Send a reminder

[0469] Server: Sends reminders to family members' devices about incomplete procedures. The sendReminder() function is used for sending. The input is the reminder message, and the output is the reminder sent to the user's device.

[0470] Step 13: Recognize emotions

[0471] Device: Recognizes the user's emotions in real time using sensors such as a camera and microphone. The captureEmotionData() function is used for recognition, and the analyzeEmotion() function is used for analysis. The input is facial expression and tone of voice data, and the output is the analyzed emotional state.

[0472] Step 14: Sending Emotion Data

[0473] Terminal: The collected emotion data is sent to the server. The sendEmotionData() function is used for sending. The input is the analyzed emotional state, and the output is the emotion data sent to the server.

[0474] Step 15: Emotional Adjustment

[0475] Server: Dynamically adjusts the notification content and procedure flow presentation method based on the user's emotional state detected by the emotion engine. The adjustProcedureFlowBasedOnEmotion() function is used for adjustment. The input is emotional data, and the output is the adjusted notification content and procedure flow.

[0476] Step 16: Present tailored notifications and procedural flows

[0477] Terminal: The adjusted notification or procedure flow is displayed on the user's terminal. The displayAdjustedProcedureFlow() function is used for display. The input is the adjusted notification content or procedure flow, and the output is the displayed adjusted procedure flow.

[0478] Through these steps, the system can monitor the health status of elderly people in real time, provide appropriate medical treatment if an abnormality is detected, assist with the progress of procedures, and adapt the system's behavior according to the user's emotions.

[0479] (Application example 2)

[0480] 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."

[0481] Real-time health management for the elderly is important for prompt medical response. However, many elderly people have difficulty traveling to medical institutions and completing the appropriate procedures on their own. It is also difficult to constantly monitor the health status of elderly people remotely, and it is often impossible to respond quickly even if an abnormality occurs. Furthermore, there is concern that when elderly people and their families are under stress or anxiety, they may not understand or respond properly to procedures and information provision.

[0482] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for monitoring the elderly person's health condition in real time, means for detecting abnormal health conditions, means for automatically providing information on appropriate medical institutions and departments based on the detected abnormalities, means for issuing notifications to family members and care managers, means for automatically generating and providing necessary procedures and subsidy application flows, means for monitoring progress and sending reminders for incomplete procedures, means for linking with the autonomous vehicle's system and automatically guiding the user to the nearest hospital if an abnormality is detected, and means for analyzing the user's emotional state and adjusting the notification content and procedure flow. This allows the elderly person's health condition to be constantly monitored, and when an abnormality is detected, it is possible to quickly support transportation to a medical institution and necessary procedures. Furthermore, adjusting the method of providing notifications and procedures based on the emotional state reduces stress and anxiety for the elderly person and their family, and more appropriate and prompt responses are expected.

[0483] "Means for monitoring health status in real time" refers to devices or methods that continuously acquire the elderly person's physical vital signs and immediately transmit them to the system.

[0484] "Means for detecting abnormal health conditions" refers to devices or methods that analyze acquired vital data and compare it with reference values ​​to detect abnormalities.

[0485] The "means for automatically providing information about appropriate medical institutions and departments" refers to a device or method that automatically presents information about the appropriate medical institutions and departments based on the detected abnormality.

[0486] "Means for issuing notifications to family members or care managers" refers to a device or method that sends an alert to pre-registered contacts when an abnormality is detected.

[0487] "Means for automatically generating and providing necessary procedures and application flows for subsidy systems" refers to devices and methods that automatically organize and provide information on the procedures and subsidy systems required when elderly people receive medical care.

[0488] A "means for monitoring progress and sending reminders for outstanding procedures" is a device or method that tracks the progress of procedures and sends reminders for outstanding procedures.

[0489] "Means of working in conjunction with the system of an autonomous vehicle to automatically guide the vehicle to the nearest hospital when an abnormality is detected" refers to a device or method that automatically instructs an autonomous vehicle to head to the nearest hospital when an abnormality is detected in real time.

[0490] "Means for analyzing the user's emotional state and adjusting notification content and procedure flow" refers to a device or method that analyzes the user's facial expressions and voice to recognize emotions, and appropriately changes the notification content and procedure presentation method based on that.

[0491] This invention is a system for monitoring the health status of elderly people in real time and responding quickly when an abnormality is detected. Specific embodiments of this system will be described below.

[0492] System configuration

[0493] 1. Health monitoring

[0494] Wearable devices:

[0495] Various wearable devices (e.g., smartwatches) are used as terminals. These devices collect vital data such as the elderly's heart rate, blood pressure, and amount of exercise in real time and send this data to a server. For example, a smartwatch measures the user's heart rate and blood pressure every minute and sends the data to a cloud server.

[0496] 2. Anomaly detection and notification

[0497] server:

[0498] The server analyzes the received data and compares it with reference values ​​to detect any abnormalities. If an abnormality is detected, a notification is issued to the registered emergency contacts (family members or care managers). This notification also includes information on the appropriate medical institution and department to visit. For example, if the server detects an abnormal heart rate, it sends a notification stating "heart rate has risen sharply" and including the contact information of the nearest doctor.

[0499] 3. Collaboration with autonomous vehicles

[0500] Autonomous vehicles:

[0501] This system works in conjunction with the autonomous vehicle's system to automatically guide the elderly person to the nearest hospital if an abnormality is detected. For example, if an elderly person's heart rate shows an abnormal value, the autonomous vehicle will automatically set a route to the nearest hospital and begin moving.

[0502] 4. Assistance with admission procedures

[0503] server:

[0504] The server automatically generates and provides the necessary procedures and application flows for subsidy programs. This allows families to receive the information they need in real time after arriving at the hospital. For example, the "hospitalization procedure flow" provides a list of required documents and templates.

[0505] 5. Progress monitoring and reminders

[0506] Device:

[0507] As the procedure progresses, the progress is reported to the server, which records the progress in a database and sends reminders to the family members' devices about any incomplete procedures, helping them remember to complete them.

[0508] 6. Emotion recognition

[0509] Device:

[0510] The smartphones used by the elderly and their families are equipped with cameras and microphones that can be used to recognize the user's emotions in real time. For example, when a family member goes through a procedure, the camera analyzes their facial expressions to detect emotions such as anxiety or impatience.

[0511] 7. Emotion-Based Adjustment

[0512] server:

[0513] The emotion engine dynamically adjusts notification content and procedure flow based on emotional data analyzed. For example, if it recognizes that the user is feeling stressed, notification content will be displayed in more user-friendly language. The procedure flow will also be simplified and adjusted to require fewer steps.

[0514] Specific examples

[0515] Health monitoring and anomaly detection

[0516] For example, if an elderly person's heart rate exceeds a set threshold (usually less than 100 bpm), the server will detect this as an abnormality and send a notification to emergency contacts, including the message, "Your heart rate is rising rapidly. Please contact a medical institution."

[0517] Collaboration with autonomous vehicles

[0518] When an abnormality is detected, the autonomous vehicle immediately sets a route to the nearest medical facility and quickly transports the elderly person to the hospital. At this time, the necessary information for procedures and the application flow for subsidy programs are automatically generated and displayed on the smartphone.

[0519] Emotional Engine Adjustment

[0520] If the camera detects an anxious expression on a family member's face as they go through the admission procedures, the server will make the notification more friendly and display an encouraging message such as, "Don't worry, the procedure is going smoothly."

[0521] Prompt Sentence Examples

[0522] "If an elderly person's heart rate spikes or blood pressure rises while riding in an autonomous vehicle, please design a system that automatically guides the vehicle to the nearest hospital and sends an emergency alert to registered family members and medical institutions. Also, please include a function that displays the hospital admission procedure flow after the vehicle arrives, analyzes the elderly person's facial expressions with a camera to determine their stress level, and adjusts the content of the notification accordingly."

[0523] As a result, this invention can provide safe and appropriate medical support by monitoring the health status of elderly people in real time and responding quickly when abnormalities are detected.In addition, the introduction of an emotion engine reduces stress and anxiety for elderly people and their families, enabling smoother procedures.

[0524] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0525] Step 1:

[0526] Real-time acquisition of health data for the elderly

[0527] A wearable device collects real-time data on the elderly person's heart rate, blood pressure, and physical activity. This data is measured through sensors on the wearable device. The measured data is sent to a server via the device. The input data is vital signs such as heart rate and blood pressure, and the output is sensor data sent to the server.

[0528] Step 2:

[0529] Health data analysis and anomaly detection

[0530] The server receives data sent from the wearable device and analyzes it using an anomaly detection algorithm. Specifically, if the heart rate exceeds 150 bpm or the blood pressure exceeds 180 / 100, it is deemed to be abnormal. The input data is the vital signs data sent from the wearable device, and the output is the analysis result, such as "normal" or "abnormal."

[0531] Step 3:

[0532] Notification when an abnormality is detected

[0533] If the server detects an abnormality, it sends an emergency alert to registered family members and care managers. The notification also includes information on the appropriate medical institution and department to visit. The input is the abnormality detection result, and the output is a notification message sent to emergency contacts. Notifications are sent via email or SMS.

[0534] Step 4:

[0535] Autonomous vehicle routing

[0536] When the server detects an abnormality, it sends a command to the autonomous vehicle to set a route to the nearest hospital. The input is the abnormality detection and hospital information, and the output is route information sent to the autonomous vehicle. The vehicle's navigation system automatically sets the optimal route and begins moving.

[0537] Step 5:

[0538] Providing information on admission procedures

[0539] The server automatically generates the necessary procedures and application flow for subsidy programs, and sends them to the family's device. The input is a notification of arrival at the hospital, and the output is the procedure flow and a list or template of required documents. The family can then view this and proceed with the procedures.

[0540] Step 6:

[0541] Progress monitoring and reminders

[0542] As family members go through procedures, the device reports their progress to the server. The server records the progress in a database and sends reminders to family members' devices if there are any procedures that need to be completed. The input is the progress data of the procedures, and the output is reminder notifications.

[0543] Step 7:

[0544] Emotion recognition and notification content adjustment

[0545] The device uses a camera and microphone to recognize the emotional state of family members in real time. The server receives the emotional data analyzed using an emotion recognition engine. For example, if a family member shows an anxious expression, the notification content is made more friendly and an encouraging message is added if necessary. The input is the emotional data sent from the device, and the output is the adjusted notification content.

[0546] Through these steps, this system can monitor the health status of elderly people in real time and automatically take appropriate action when an abnormality is detected. It also reduces stress for family members and care managers and enables prompt and appropriate medical support.

[0547] 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.

[0548] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0549] 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.

[0550] [Second embodiment]

[0551] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0552] 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.

[0553] 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).

[0554] 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.

[0555] 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.

[0556] 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).

[0557] 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.

[0558] 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.

[0559] 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.

[0560] 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.

[0561] 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.

[0562] 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."

[0563] To implement this invention, it is necessary to prepare a wearable device for monitoring the health status of the elderly, a server for analyzing the data, and a terminal that links with the user and emergency contacts. Below, the overall processing flow of the system is explained in natural language.

[0564] 1. Real-time health monitoring

[0565] Device: A wearable device collects vital data such as heart rate, blood pressure, and exercise volume of elderly people in real time. The device is worn on the user's body and measures the data periodically.

[0566] Server: Receives vital data sent from the device and stores it in a database, allowing the health of the elderly to be constantly monitored.

[0567] 2. Data analysis and anomaly detection

[0568] Server: Analyzes the received vital signs and compares them with historical data and baseline values. Algorithms are applied to detect abnormal values ​​(e.g., sudden increases in heart rate or abnormal blood pressure fluctuations).

[0569] Server: Generates an alert if an anomaly is detected. This alert is issued if an immediate response is required.

[0570] 3. Notification and Instructions

[0571] Server: When an alert is generated, a notification is sent to registered emergency contacts (family members or care managers), along with information about the relevant medical institution and department.

[0572] Device: The device of the emergency contact (e.g., a smartphone) receives the notification and instructs the elderly person's family member via voice or text on the appropriate action to take. Specifically, the message "Please contact the nearest internal medicine clinic" is displayed.

[0573] 4. Aftercare support

[0574] Server: When an elderly person is hospitalized or admitted to a facility, information on related procedures is collected and the necessary procedures and application flows for subsidy programs are automatically generated.

[0575] Device: Based on this flow, messages are displayed to guide the family member in need of assistance through the procedure. Templates of the necessary documents are also provided, allowing the family member to efficiently complete the necessary procedures.

[0576] 5. Progress monitoring and reminders

[0577] Terminal: As the user goes through each procedure, the progress is reported to the server. The user inputs the progress of the procedure from a smartphone or tablet.

[0578] Server: Records the progress in a database and generates reminders for incomplete procedures and sends them to the user's device, for example, a message saying "This procedure is not yet complete."

[0579] Specific examples

[0580] Scenario 1: Elderly person A records a heart rate of 150 bpm and blood pressure of 180 / 100

[0581] Device: The smartwatch collects this data and sends it to the server.

[0582] Server: Detects an abnormal value and notifies family member B, who is the emergency contact, that "A's heart rate has suddenly increased. Please contact the nearest internal medicine clinic."

[0583] Device: A notification appears on Mr. B's smartphone, and he rushes to the internal medicine department with Mr. A.

[0584] Scenario 2: Person A is hospitalized and family member B completes the necessary procedures

[0585] Server: Receives information about hospitalization and generates the necessary procedures and application flow for subsidy programs.

[0586] Device: Display the procedure flow on Mr. B's smartphone, stating "Please follow the admission procedures in this order," along with a template of the necessary documents.

[0587] Server: Monitors the progress of the transaction and sends reminders for any outstanding transactions.

[0588] The above is a specific method for carrying out the present invention. This system allows elderly people and their families to receive prompt and appropriate medical treatment and aftercare.

[0589] The processing flow will be explained below.

[0590] Step 1: Collecting health data

[0591] Device: A wearable device collects vital data such as heart rate, blood pressure, and exercise volume in real time. The device is attached to the elderly person's body and measures the data periodically.

[0592] Step 2: Sending data

[0593] Terminal: Collected vital data is sent to the server. The data is encrypted and transmitted securely over the network.

[0594] Step 3: Receiving and storing data

[0595] Server: Receives the data sent from the device and stores it in a database, which also includes the elderly person's past health data.

[0596] Step 4: Analyze the data

[0597] Server: Analyzes the stored data, comparing it with historical data and baseline values ​​and applying algorithms to detect abnormal values ​​(e.g., sudden increases in heart rate or abnormal blood pressure fluctuations).

[0598] Step 5: Detect anomalies

[0599] Server: Generates an alert if an anomaly is detected that exceeds a certain threshold, for example, if the heart rate increases by more than 50% of normal.

[0600] Step 6: Generate notifications

[0601] Server: Based on the generated alert, the server issues a notification to registered emergency contacts (family members or care managers), and also provides information on appropriate medical institutions and departments to visit.

[0602] Step 7: Receiving and Viewing Notifications

[0603] Device: The emergency contact's device (e.g., smartphone) receives the notification. The device displays specific instructions to the family member via voice or text, such as "Please contact the nearest internal medicine doctor."

[0604] Step 8: Family response

[0605] User: Family members receive notifications and follow instructions to take the elderly to medical facilities. They act quickly based on specific instructions.

[0606] Step 9: Obtain admission information

[0607] Server: When an elderly person is hospitalized, the server receives information about the hospitalization from the medical institution and stores it in a database.

[0608] Step 10: Generate procedural flow

[0609] Server: Automatically generates procedures for hospitalization and application procedures for subsidy programs, including the required documents and procedure sequence.

[0610] Step 11: Notification of procedure flow

[0611] Server: Sends the generated procedure flow to the family member's device. The device displays instructions such as "Please follow the procedure at the hospital in this order."

[0612] Step 12: Provide documentation

[0613] Server: Sends templates of the necessary documents to the device so that family members can use them to complete the procedures.

[0614] Step 13: Record the progress of the procedure

[0615] Device: As the family member goes through each procedure, they report their progress to the server. For example, they can use their smartphone to press a button to complete the procedure.

[0616] Step 14: Monitoring progress

[0617] Server: Records progress in a database and generates reminders for incomplete procedures.

[0618] Step 15: Send a reminder

[0619] Server: Sends a reminder to the family member's device about the incomplete procedure. The device displays the message "This procedure is not yet completed."

[0620] Example 1

[0621] 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."

[0622] There is a need for a system that can constantly monitor the health status of elderly people, detect abnormalities, and provide appropriate medical care promptly. However, existing systems are unable to collect and analyze data in real time, making it difficult to quickly notify patients when an abnormality occurs or take appropriate action. In addition, there is no automated system for providing information about hospitalization and procedures, monitoring progress, or sending reminders. For these reasons, there is a need to provide a system that can efficiently and effectively manage the health of elderly people.

[0623] 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.

[0624] In this invention, the server includes: a means for monitoring health status in real time; a means for detecting abnormal health status; a means for automatically providing information on appropriate medical institutions and departments based on the detected abnormalities; a means for issuing notifications to emergency contacts; a means for automatically generating and providing necessary procedures and application flows for subsidy programs; a means for monitoring progress and sending reminders for incomplete procedures; a means for analyzing data stored on the server and using an algorithm to detect abnormal values; a means for using a secure protocol for data communication between the server and a terminal; and a means for sending voice or text notifications to emergency contacts. This allows for real-time monitoring of the health status of elderly people and enables prompt and appropriate response in the event of an abnormality. Furthermore, the provision of information on hospitalization and procedures, progress monitoring, and sending reminders are automated, reducing the burden on elderly people and their families.

[0625] "Real-time health monitoring" refers to the use of wearable devices to continuously collect personal physical data (e.g., heart rate, blood pressure, and exercise volume) and to analyze and manage that data in real time.

[0626] "Detecting abnormal health conditions" refers to identifying abnormal values ​​(e.g., sudden increases in heart rate or abnormal fluctuations in blood pressure) based on collected data and comparing them with baseline values ​​or past data.

[0627] "Automatically providing information about appropriate medical institutions and departments" means that when an abnormality is detected, information about the medical institution and department that is most suitable for the abnormality is automatically provided to the user.

[0628] "Issuing a notification to an emergency contact" means that if an abnormality is detected, a notification will be sent promptly to a pre-registered emergency contact (e.g., family member or care manager).

[0629] "Automatic generation of application flows for procedures and subsidy systems" means that the system automatically generates and provides application flows for procedures and subsidy systems that are necessary when elderly people are hospitalized or admitted to a facility.

[0630] "Progress monitoring" means tracking and managing the progress of each step of a user's procedure in real time.

[0631] "Sending reminders" means sending notifications or alerts to users when there are incomplete procedures or important steps.

[0632] An "algorithm for analyzing data and detecting outliers" is a program or mathematical method for identifying outliers based on collected data.

[0633] A "secure protocol for data communication between a server and a terminal" is a communication method (e.g., HTTPS, TLS) for securely transmitting data between a server and a terminal.

[0634] "Send voice and text notifications" refers to sending important messages to users in the form of voice alerts and text messages.

[0635] A "wearable device" is a small electronic device that can be worn on the body and collects physical data such as heart rate, blood pressure, and exercise volume.

[0636] A "server" is a computer on a network that stores and analyzes data, detects anomalies, and sends notifications.

[0637] A "terminal" is a device (e.g., a smartphone or tablet) that receives data from a server or wearable device and gives instructions to the user.

[0638] "Entering progress status" means that the user reports the progress of the procedure to the system using a smartphone or tablet.

[0639] "Procedure flow suggestions" means that the system automatically provides the order and methods of procedures that elderly people and their families should follow.

[0640] "Providing templates for required documents" means providing the user with formats for documents required to carry out the procedure.

[0641] MODE FOR CARRYING OUT THE INVENTION

[0642] To implement this invention, it is necessary to build a system that monitors the health status of elderly people in real time, detects abnormalities, and provides instructions on appropriate measures. Specifically, the following hardware and software are required:

[0643] System configuration

[0644] 1. Wearable devices

[0645] Device:

[0646] Wearable devices (e.g., health trackers, smartwatches) collect real-time vital data such as heart rate, blood pressure, and physical activity of elderly people. These devices can be worn on the body and transmit the data to a connected smartphone via Bluetooth or Wi-Fi.

[0647] 2. Smartphone (or tablet)

[0648] Device:

[0649] The smartphone receives data from the wearable device and sends it to a cloud server using a secure communication protocol (e.g., HTTPS).

[0650] 3. Cloud Server

[0651] server:

[0652] A cloud server (e.g., Amazon Web Services, Google Cloud) receives the vital data sent from the smartphone and stores it in a dedicated database (e.g., Amazon RDS, Firebase RealTime Database).

[0653] Data analysis and anomaly detection

[0654] server:

[0655] The received data is analyzed using an anomaly detection algorithm (e.g., machine learning model) created in Python or R. Anomalies are detected by comparing them with past data and reference values ​​(e.g., heart rate 60-100 bpm, blood pressure below 120 / 80).

[0656] Sending alerts and notifications

[0657] server:

[0658] If abnormal data is detected (e.g. heart rate 150 bpm, blood pressure 180 / 100), an alert is generated and a notification is sent to emergency contacts using Twilio or Firebase Notifications.

[0659] Device:

[0660] The smartphone of the emergency contact (e.g., family member or care manager) receives a notification and instructs the elderly person's family member on appropriate actions via voice notification or text message.

[0661] Automatic generation and support of procedures

[0662] server:

[0663] When an elderly person is hospitalized or admitted to a facility, information about the hospitalization is received and a Python script is used to automatically generate the necessary procedures and application flow for subsidy programs.

[0664] Device:

[0665] The system sends a notification to the emergency contact's smartphone explaining the procedure and provides templates for the necessary documents. For example, it includes specific instructions such as "Please follow this order when completing the admission procedures."

[0666] Progress monitoring and reminders

[0667] User:

[0668] As the emergency contact (family member) goes through the procedure, they enter the progress into the server via their smartphone.

[0669] server:

[0670] The entered progress is recorded in a database, and reminders are generated and sent to the user's device for any incomplete procedures, such as a "This procedure is not yet complete" reminder.

[0671] Specific examples

[0672] Scenario 1: Elderly person A records a heart rate of 150 bpm and blood pressure of 180 / 100

[0673] Device: The smartwatch collects this data and sends it to a cloud server via the smartphone.

[0674] Server: Detects an abnormal value and uses the Twilio API to notify the family member who is the emergency contact, saying, "Mr. A's heart rate has suddenly increased. Please contact the nearest internal medicine clinic."

[0675] Device: A notification appears on the family member's smartphone, and they rush to the internal medicine department with Mr. A.

[0676] Scenario 2: Person A is hospitalized and family member B completes the necessary procedures

[0677] Server: Receives information about hospitalization and generates procedures and application flows for subsidy programs.

[0678] Device: The family member's smartphone will be shown a procedure flow stating, "Please follow the admission procedures in this order," along with a template of the necessary documents.

[0679] Server: Monitors the progress of the transaction and sends reminders for any outstanding transactions.

[0680] Prompt Sentence Examples

[0681] "Write Python code to analyze heart rate and blood pressure data and detect outliers."

[0682] "How do I use the Twilio API to send an SMS in case of an error?"

[0683] This system allows elderly people and their families to receive prompt and appropriate medical response and aftercare.

[0684] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0685] Step 1:

[0686] Data collection

[0687] Device: A wearable device (e.g., a smartwatch) collects vital data such as heart rate, blood pressure, and activity level in real time. The device collects data every few seconds and transmits it to a connected smartphone via Bluetooth or Wi-Fi.

[0688] Input: Real-time vital data from biosensors.

[0689] Output: Collected vital data is sent to a smartphone.

[0690] Step 2:

[0691] Data transmission

[0692] Terminal: The smartphone receives data from the wearable device and sends it to the cloud server using a secure communication protocol (e.g., HTTPS).

[0693] Input: Vital data collected by the device.

[0694] Output: Vital data sent to cloud server via secure communication.

[0695] Step 3:

[0696] Data reception and storage

[0697] Server: A cloud server (e.g., AWS EC2) receives the vital data sent from the smartphone and stores it in a dedicated database (e.g., Amazon RDS).

[0698] Input: Vital data sent over secure communication.

[0699] Output: Vital data stored in a database.

[0700] Step 4:

[0701] Data analysis

[0702] Server: The received data is analyzed using an anomaly detection algorithm (e.g., machine learning model) created in Python or R. The data is compared with past vital signs and reference values ​​(e.g., heart rate 60-100 bpm, blood pressure below 120 / 80) to detect abnormal values.

[0703] Input: Saved vital data and baseline values, historical data.

[0704] Output: Information about detected outliers.

[0705] Step 5:

[0706] Alert Generation

[0707] Server: If abnormal data is detected (e.g., heart rate 150 bpm, blood pressure 180 / 100), a Python script generates an alert that explains what caused the abnormality and recommends corrective actions.

[0708] Input: Outlier information as an analysis result.

[0709] Output: Alert information.

[0710] Step 6:

[0711] Send notifications

[0712] Server: Based on the generated alert, a notification is sent to emergency contacts using Twilio or Firebase Notifications. The notification includes specific instructions such as "Your heart rate has increased dramatically. Please contact the nearest medical facility."

[0713] Input: The generated alert information.

[0714] Output: Notification message sent to emergency contacts.

[0715] Step 7:

[0716] Receive notifications

[0717] Device: The smartphone of the emergency contact (e.g., family member) receives the notification and instructs the elderly family member on appropriate actions via voice notification or text.

[0718] Input: The notification message sent by the server.

[0719] Output: Notification content displayed on the emergency contact's device.

[0720] Step 8:

[0721] Procedural flow generation

[0722] Server: When an elderly person is hospitalized or admitted to a facility, a Python script is used to automatically generate the necessary procedures and application flow for subsidy programs.

[0723] Input: Information about hospitalization and institutionalization.

[0724] Output: Generated procedure flow and subsidy application guide.

[0725] Step 9:

[0726] Procedure flow notification

[0727] Server: The generated procedure flow is sent to the smartphone of the emergency contact. The notification includes specific instructions such as "Please follow the admission procedure in this order."

[0728] Input: The generated procedure flow.

[0729] Output: The procedure flow sent to the emergency contact's device.

[0730] Step 10:

[0731] Entering the progress of procedures

[0732] User: As the emergency contact (family member) goes through each procedure, they enter the progress information into the server using their smartphone or tablet.

[0733] Input: Procedural progress.

[0734] Output: Progress data reported to the server.

[0735] Step 11:

[0736] Progress monitoring

[0737] Server: Records the entered progress in a database and monitors the progress of the procedure.

[0738] Input: User-reported progress data.

[0739] Output: Progress and monitoring results recorded in a database.

[0740] Step 12:

[0741] Generate and send reminders

[0742] Server: Generates reminders for incomplete procedures and sends them to the user's device. For example, it sends a reminder notification saying "This procedure has not yet been completed."

[0743] Input: Progress data and open procedure information.

[0744] Output: The reminder notification sent to the user's device.

[0745] (Application example 1)

[0746] 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."

[0747] Real-time monitoring of the health status of elderly people and early detection of abnormalities are important challenges for families and care managers. Rapid and accurate responses are also required when abnormalities are detected. Furthermore, there is a need to streamline procedures for post-health abnormality procedures and applications for subsidies, and to appropriately manage progress. However, conventional systems have had difficulty fully meeting these requirements.

[0748] 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.

[0749] In this invention, the server includes a means for collecting and analyzing vital data from the wearable device using a smartphone and smart glasses, detecting abnormalities and sending notifications, a means for acquiring data such as the elderly person's heart rate, blood pressure, and amount of exercise using the wearable device and sending it to the server via the smartphone and smart glasses, and a means for providing templates for required documents based on a proposed procedure flow and sending incomplete reminders, thereby enabling early detection of abnormalities and rapid response, efficient procedure support, and appropriate progress management.

[0750] Here are the definitions:

[0751] "Health status of the elderly" refers to vital data such as the elderly's heart rate, blood pressure, and amount of exercise.

[0752] "Means of real-time monitoring" refers to a system that uses wearable devices to continuously collect vital data and send it to a server, allowing the data to be checked immediately.

[0753] "Means for detecting abnormal health conditions" refers to algorithms that analyze collected vital data and compare it with baseline values ​​to detect abnormal values.

[0754] "Means for automatically providing information about appropriate medical institutions and departments" refers to a system that provides data about the nearest appropriate medical institutions and departments based on detected abnormalities.

[0755] "Means of issuing notifications to family members or care managers" refers to a notification mechanism that sends an alert to emergency contacts when an abnormality is detected.

[0756] "Means for automatically generating and providing application flows for procedures and subsidy programs" refers to the function of automatically generating and providing information regarding procedures and applications for subsidy programs that are necessary when an elderly person is hospitalized, for example.

[0757] "Means for monitoring progress and sending reminders for incomplete procedures" refers to a system that monitors the progress of procedures and sends reminder notifications for incomplete procedures.

[0758] "Smartphones and smart glasses" refer to portable devices that receive, analyze, and notify data from wearable devices.

[0759] A "wearable device" refers to a device that is worn on the body and continuously collects vital data.

[0760] "Means for collecting and analyzing data, detecting abnormalities, and notifying" refers to a system that collects vital data from wearable devices, analyzes it on a server to detect abnormalities, and sends notifications to emergency contacts.

[0761] In order to implement the present invention, the following hardware and software are used.

[0762] Hardware:

[0763] 1. Wearable devices: Devices that collect vital data such as heart rate, blood pressure, and physical activity of elderly people. These devices include, for example, smart watches and fitness trackers.

[0764] 2. Smartphones and smart glasses: These devices are used to receive data collected from wearable devices and send it to the server. Smartphones are used to run applications and display notifications. Smart glasses are also used to display data and receive notifications.

[0765] 3. Server: A server that receives and analyzes data from wearable devices.

[0766] software:

[0767] 1. Data collection and transmission program: A program for collecting data from wearable devices and transmitting it to a server through smartphones and smart glasses.

[0768] 2. Data analysis program: A program that analyzes vital data on the server and detects abnormalities. For example, it can be implemented using Python or R.

[0769] 3. Notification program: This program sends an alert to emergency contacts when an abnormality is detected. This program uses RESTful APIs or Firebase Cloud Messaging (FCM) to send notifications.

[0770] 4. Procedure flow provision and reminder program: This program automatically generates information regarding procedures after a health abnormality and applications for subsidies, and reminds users of incomplete procedures.

[0771] Process flow:

[0772] 1. Data collection: The wearable device periodically measures the elderly person's heart rate, blood pressure, and physical activity, and transmits the data to a smartphone and smart glasses.

[0773] 2. Data transmission: The smartphone and smart glasses transmit the received vital data to the server via Bluetooth.

[0774] 3. Data analysis: The server analyzes the received vital data and compares it with baseline values ​​to detect abnormalities. Machine learning algorithms and rule-based analysis methods are used for the analysis.

[0775] 4. Anomaly detection and notification: If an anomaly is detected, the server will send an alert to emergency contacts, notifying them of the abnormal data and recommending a course of action (e.g., "Contact your local internal medicine doctor").

[0776] 5. Providing procedure flow and reminders: When an elderly person is hospitalized, the server automatically generates a procedure flow and a template of the necessary documents and sends them to the smartphone or smart glasses. It also monitors the progress and sends reminder notifications if the procedure is incomplete.

[0777] Examples:

[0778] Scenario 1:

[0779] When an elderly person's heart rate reaches 150 bpm and blood pressure reaches 180 / 100, the server detects the abnormality and sends an alert to the smartphone and smart glasses saying, "Your heart rate has suddenly increased. Please contact your internal medicine doctor."

[0780] Scenario 2:

[0781] When an elderly person is hospitalized and their family members are completing the necessary procedures, the server generates a procedure flow and a template of the necessary documents, and displays it on the family members' smartphones and smart glasses, telling them to "proceed with the procedures in this order." It also reminds them of any incomplete procedures.

[0782] Example of a generative AI model prompt:

[0783] Example prompt:

[0784] We built a system to monitor the health of elderly people. The system collects and analyzes data from wearable devices in real time and sends notifications to emergency contacts if an abnormality is detected. We used Python and RESTful APIs to implement the processes for data transmission, anomaly detection, and notification generation.

[0785] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0786] Step 1:

[0787] Data collection

[0788] Input: A wearable device (e.g., a smartwatch) collects vital data such as an elderly person's heart rate, blood pressure, and activity level.

[0789] How it works: Measures vital signs at regular intervals and syncs the data with your smartphone and smart glasses.

[0790] Output: The measured vital data is sent to a smartphone and smart glasses.

[0791] Step 2:

[0792] Data transmission

[0793] Input: Vital data received from a wearable device.

[0794] How it works: The smartphone and smart glasses transmit the vital data they receive via Bluetooth to a server.

[0795] Output: Vital data arrives at the server.

[0796] Step 3:

[0797] Data analysis

[0798] Input: Vital data sent to the server.

[0799] How it works: The server uses programs such as Python to analyze vital data. The data is compared with known normal values ​​and calculations are performed to detect abnormalities.

[0800] Output: If an anomaly is detected, the type of anomaly and the anomaly detection result are generated. If no anomaly is detected, the analysis result is stored.

[0801] Step 4:

[0802] Anomaly detection and notification

[0803] Input: Anomaly detection results generated by data analysis.

[0804] How it works: The server generates and sends alerts to emergency contacts based on the anomaly detection results. Alerts are sent using RESTful APIs and Firebase Cloud Messaging (FCM).

[0805] Output: An alert is sent to emergency contacts and a notification is displayed on the smartphone and smart glasses.

[0806] Step 5:

[0807] Procedural flow provided

[0808] Input: Elderly person's admission information and related procedure information.

[0809] Operation: The server automatically generates the steps required for a target procedure such as hospitalization and prepares templates for the necessary documents.

[0810] Output: The procedure flow and templates of required documents are sent to the smartphone and smart glasses.

[0811] Step 6:

[0812] Reminder generation

[0813] Input: Procedural progress data entered by the user.

[0814] Behavior: The server monitors the progress of procedures and generates reminders for incomplete procedures. Reminders are generated based on progress data.

[0815] Output: Reminders for outstanding procedures are sent to the user's smartphone and smart glasses.

[0816] (Example prompt):

[0817] "We built a system to monitor the health of elderly people. The system collects and analyzes data from wearable devices in real time, and sends notifications to emergency contacts if an abnormality is detected. We used Python and RESTful APIs to implement the processes for data transmission, anomaly detection, and notification generation."

[0818] 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.

[0819] This system monitors the health status of elderly people in real time, and when abnormalities are detected, it provides information on appropriate medical institutions and departments and issues notifications to family members and care managers. It also automatically generates procedures for post-hospitalization and facility admission, as well as application flows for subsidy programs, and monitors progress to send reminders for incomplete procedures. Furthermore, by combining it with an emotion engine that recognizes user emotions, it can automatically adjust the content of notifications and the presentation method of the procedure flow.

[0820] System configuration

[0821] 1. Health monitoring

[0822] Device: A wearable device collects vital data such as heart rate, blood pressure, and exercise volume of elderly people in real time. It is worn on the user's body and measures the data periodically.

[0823] Server: Receives vital data sent from the device and stores it in a database. This data is analyzed and generates an alert if an abnormality is detected.

[0824] 2. Anomaly detection and notification

[0825] Server: Analyzes the received data and compares it with the reference values. If an abnormal value is detected, a notification is sent to the registered emergency contacts. The notification also includes information on the appropriate medical institution and department to visit.

[0826] Device: The emergency contact's device will receive a notification and display voice and text instructions, allowing for a quick response.

[0827] 3. Assistance with admission procedures

[0828] Server: When an elderly person is hospitalized, the necessary procedures and application flow for subsidy programs are automatically generated. This information is sent to the family's device, and the procedure order and templates for the necessary documents are provided.

[0829] Device: The procedure flow is displayed on the family member's device, helping the user to complete the procedure easily.

[0830] 4. Progress monitoring and reminders

[0831] The device reports its progress to the server as it processes the transaction, which records the progress in a database and sends reminders about any outstanding transactions.

[0832] Server: Monitors the progress of procedures and sends reminders to family members' devices about incomplete procedures, helping them remember to complete them.

[0833] Combining Emotion Engines

[0834] 5. Emotion recognition

[0835] Device: Using sensors such as cameras and microphones, the device recognizes the user's emotions in real time, analyzing facial expressions and tone of voice to detect emotional states.

[0836] Server: Receives emotional data analyzed by the emotion engine and adjusts the notification content and procedure flow presentation method based on this data. For example, if the user is feeling stressed, the notification will be more friendly and the procedure flow will be more concise.

[0837] 6. Emotion-Based Regulation

[0838] Server: Based on the user's emotional state detected by the emotion engine, the server dynamically adjusts the content of notifications and the way procedural flow is presented, making it easier for users to understand and reducing stress.

[0839] Device: Display tailored notifications and procedural flows on the user's device, for example adding encouraging messages if the user is feeling anxious.

[0840] Specific examples

[0841] Health monitoring and anomaly detection

[0842] Scenario: Elderly person A's heart rate is 150 bpm and blood pressure is 180 / 100.

[0843] Device: The smartwatch collects this data and sends it to the server.

[0844] Server: Detects an abnormality and notifies emergency contacts, saying, "Mr. A's heart rate has suddenly increased. Please contact the nearest internal medicine clinic."

[0845] Device: A notification appears on the emergency contact's smartphone, and family member B takes person A to the internal medicine clinic.

[0846] Assistance with admission procedures

[0847] Scenario: Person A is hospitalized and family member B completes the necessary procedures.

[0848] Server: Collects information about hospitalization and automatically generates procedural flow.

[0849] Device: Mr. B's smartphone displays instructions such as "Please complete the admission procedures in this order," and also provides templates for the necessary documents.

[0850] Emotional Engine Adjustment

[0851] Scenario: When B is going through the procedure, the camera detects an anxious expression on B's face.

[0852] Device: The camera analyzes Mr. B's facial expression and sends his stress level to the emotion engine.

[0853] Server: Receives emotion data, simplifies the process, and adds encouraging messages.

[0854] Device: The adjusted procedure flow is displayed on Mr. B's smartphone, making it easier to proceed with the procedure.

[0855] The above is a specific method for implementing the present invention. This system enables elderly people and their families to receive prompt and appropriate medical treatment and aftercare, and furthermore, the emotional engine provides support to reduce stress and anxiety in users.

[0856] The processing flow will be explained below.

[0857] This system monitors the health status of elderly people in real time, and when abnormalities are detected, it provides information on appropriate medical institutions and departments and issues notifications to family members and care managers. It also automatically generates procedures for post-hospitalization and facility admission, as well as application flows for subsidy programs, and monitors progress to send reminders for incomplete procedures. Furthermore, by combining it with an emotion engine that recognizes user emotions, it can automatically adjust the content of notifications and the presentation method of the procedure flow.

[0858] System processing steps

[0859] 1. Real-time health monitoring

[0860] Step 1:

[0861] Device: Wearable devices (e.g., smartwatches) collect vital data such as heart rate, blood pressure, and exercise volume in real time. The device is worn on the user's body and measures data every second.

[0862] Step 2:

[0863] Terminal: Sends collected vital data to the server. The data is encrypted and sent over the network using a secure protocol.

[0864] Step 3:

[0865] Server: Receives data sent from the device and stores it in a real-time database. The stored data is immediately available for analysis.

[0866] 2. Data analysis and anomaly detection

[0867] Step 4:

[0868] Server: Analyzes the received vital data. It compares it with past data and preset reference values ​​and uses algorithms to detect abnormalities. For example, if the heart rate rises by more than 50% of normal.

[0869] Step 5:

[0870] Server: Generates an alert when an anomaly is detected. The alert includes details of the anomaly (e.g., a sudden increase in heart rate).

[0871] 3. Issuing and Receiving Emergency Notifications

[0872] Step 6:

[0873] Server: Based on the generated alert, the server issues a notification to registered emergency contacts (family members or care managers), including information on the appropriate medical institution and department.

[0874] Step 7:

[0875] Device: The emergency contact's device (e.g., smartphone) receives the notification, which may include a voice notification or a text message with specific instructions, such as "Contact your nearest internal medicine doctor."

[0876] 4. Incorporating and adjusting the emotional engine

[0877] Step 8:

[0878] Device: Uses a camera and microphone to collect the user's facial expressions and tone of voice in real time. Example: Analyzing emotional state from facial expressions.

[0879] Step 9:

[0880] Server: The emotion engine analyzes the collected data and determines the user's emotional state (e.g., anxiety, stress, relief).

[0881] Step 10:

[0882] Server: Based on the analysis results of the emotion engine, the server automatically adjusts the notification content and the way the procedure flow is presented. If the user is anxious, the server makes the notification content more user-friendly and simplifies the procedure flow.

[0883] Step 11:

[0884] Device: Display tailored notifications and procedural flows on the user's device. For example, display encouraging messages or simple instructions to a user who is feeling anxious.

[0885] 5. Assist with admission procedures and monitor progress

[0886] Step 12:

[0887] Server: When an elderly person is hospitalized, the server receives information about the hospitalization from the medical institution and stores it in a database.

[0888] Step 13:

[0889] Server: Automatically generates the procedures required to support hospital admission procedures and application flows for subsidy programs, including the required documents and procedure sequence.

[0890] Step 14:

[0891] Device: The procedure flow and templates for required documents are displayed on the family member's device (e.g., smartphone). For example, instructions such as "Please complete the admission procedures in this order" are displayed.

[0892] Step 15:

[0893] Device: As family members go through the process, they report their progress to the server. Progress is recorded manually or automatically.

[0894] Step 16:

[0895] Server: Monitors progress in real time and generates reminders for incomplete procedures.

[0896] Step 17:

[0897] Devices: Reminders are sent to family members' devices about incomplete transactions, such as the message "This transaction is not yet complete."

[0898] Specific examples

[0899] Scenario 1: Health monitoring and anomaly detection

[0900] If elderly person A's heart rate is recorded as 150 bpm and blood pressure as 180 / 100, the following steps are executed:

[0901] Device: The smartwatch collects this data and sends it to the server.

[0902] Server: Detects an abnormality and notifies emergency contacts, saying, "Mr. A's heart rate has suddenly increased. Please contact the nearest internal medicine clinic."

[0903] Device: A notification appears on the emergency contact's smartphone, and family member B takes person A to the internal medicine clinic.

[0904] Scenario 2: Assistance with admission procedures

[0905] When Person A is admitted to the hospital and Family Member B makes the necessary arrangements, the following steps are taken:

[0906] Server: Collects information about hospitalization and sends an automatically generated procedure flow to the family's device.

[0907] Device: Mr. B's smartphone displays instructions such as "Please complete the admission procedures in this order," and also provides templates for the necessary documents.

[0908] Scenario 3: Emotion Engine Regulation

[0909] If the camera detects an anxious expression on Mr. B's face as he goes through the process, the next step is executed.

[0910] Device: The camera analyzes Mr. B's facial expression and sends his stress level to the emotion engine.

[0911] Server: Receives emotion data, simplifies the process, and adds encouraging messages.

[0912] Device: The adjusted procedure flow is displayed on Mr. B's smartphone, making it easier to proceed with the procedure.

[0913] The above is a specific method for implementing the present invention. This system enables elderly people and their families to receive prompt and appropriate medical treatment and aftercare, and furthermore, the emotional engine provides support to reduce stress and anxiety in users.

[0914] Example 2

[0915] 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."

[0916] The challenge is to monitor the health status of elderly people in real time and provide prompt and appropriate medical treatment when abnormalities occur. It is also necessary to reduce incomplete procedures by managing the progress of procedures and sending necessary reminders. Furthermore, it is required to reduce stress and anxiety by adjusting notification content and procedure flow according to the user's emotional state.

[0917] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for monitoring the health condition of the elderly person in real time, means for detecting abnormal health conditions, means for automatically providing information on appropriate medical institutions and departments to visit based on the detected abnormalities, means for issuing notifications to family members and care managers, means for automatically generating and providing necessary procedures and application flows for subsidy programs, means for monitoring progress and sending reminders for incomplete procedures, and means for adjusting the notification content and the presentation method of the procedure flow using an emotion engine that recognizes the user's emotions. This makes it possible to monitor the health condition of the elderly person in real time, detect abnormalities, provide appropriate medical information, manage the progress of procedures, and adjust the notification content according to the user's emotions.

[0918] The term "elderly" generally refers to people aged 65 and over.

[0919] "Health status" refers to physiological and physical data such as heart rate, blood pressure, and activity level.

[0920] "Real-time" refers to processing and response occurring immediately with little or no delay.

[0921] "Abnormal" refers to health indicators such as heart rate, blood pressure, or activity level that are outside the normal range.

[0922] "Medical institution" refers to a facility that provides medical services, such as a hospital, clinic, or medical office.

[0923] "Medical department" refers to a medical department that handles a specific medical field, such as internal medicine, surgery, or psychosomatic medicine.

[0924] "Notification" refers to an alert or communication of information issued when an abnormality is detected, etc.

[0925] "Family" refers to the elderly person's close relatives, kin, or trusted acquaintances.

[0926] A "care manager" is a professional who creates care plans for elderly people and supports their progress.

[0927] "Procedure flow" refers to the series of procedures or steps required to achieve a specific purpose.

[0928] "Subsidy system" refers to public support programs for health management, medical care, nursing care, etc. available to the elderly.

[0929] "Reminder" refers to a notification or message that informs a user about an incomplete procedure.

[0930] An "emotion engine" refers to a system that analyzes a user's emotional state and adjusts the way information is presented accordingly.

[0931] This system monitors the health status of elderly people in real time, and when abnormalities are detected, it provides information on appropriate medical institutions and departments and issues notifications to family members and care managers. It also automatically generates procedures for post-hospitalization and facility admission, as well as application flows for subsidy programs, and monitors progress to send reminders for incomplete procedures. Furthermore, by combining it with an emotion engine that recognizes user emotions, it can automatically adjust the content of notifications and the presentation method of the procedure flow.

[0932] System configuration

[0933] 1. Health monitoring

[0934] Devices: Wearable devices collect vital data such as heart rate, blood pressure, and physical activity of elderly people in real time. These devices usually use APIs to collect data and send it to a server at regular intervals. For example, a smartwatch can be used as a device to collect and send this data.

[0935] Server: Receives vital data sent from the device and stores it in a database. This data is analyzed and an alert is generated if an abnormality is detected. Machine learning models are used to analyze the data.

[0936] 2. Anomaly detection and notification

[0937] Server: Compares the received vital data with the reference values, and if an abnormal value is detected, issues a notification to the registered emergency contacts. The notification also includes information on the appropriate medical institution and department to visit, enabling a prompt response.

[0938] Device: The emergency contact's device receives the notification and displays voice and text instructions. For example, a smartphone can handle this function.

[0939] 3. Assistance with admission procedures

[0940] Server: When an elderly person is hospitalized, the necessary procedures and application flow for subsidy programs are automatically generated. This information is sent to the family's device, and the order of procedures and templates for required documents are provided.

[0941] Device: The procedure flow is displayed on the family member's device, helping the user to easily proceed with the procedure.

[0942] 4. Progress monitoring and reminders

[0943] Terminal: Reports progress to the server as the procedure proceeds.

[0944] Server: Progress is recorded in a database and reminders are generated for any outstanding procedures. These reminders are sent to family members' devices, helping them remember to complete the procedures.

[0945] Combining Emotion Engines

[0946] 5. Emotion recognition

[0947] Device: Using sensors such as cameras and microphones, the device recognizes the user's emotions in real time. For example, it analyzes facial expressions and tone of voice to detect emotional states.

[0948] Server: Receives emotional data analyzed by the emotion engine and adjusts the notification content and procedure flow presentation method based on this data. For example, if the user is feeling stressed, the notification will be more friendly and the procedure flow will be more concise.

[0949] 6. Emotion-Based Regulation

[0950] Server: Based on the user's emotional state detected by the emotion engine, the server dynamically adjusts the notification content and the way the procedure flow is presented, making it easier for the user to understand and reducing stress.

[0951] Device: Tailored notifications and flow of procedures are displayed on the user's device, for example, adding encouraging messages if the user is feeling anxious.

[0952] Specific examples

[0953] Health monitoring and anomaly detection

[0954] Scenario: An elderly person has a heart rate of 150 bpm and a blood pressure of 180 / 100.

[0955] Device: The smartwatch collects this data and sends it to the server.

[0956] Server: Detects an abnormality and notifies the emergency contact, saying, "Mr. A's heart rate has suddenly increased. Please contact the nearest internal medicine clinic."

[0957] Device: A notification appears on the emergency contact's smartphone, allowing the family member to take the elderly person to the internal medicine clinic.

[0958] Assistance with admission procedures

[0959] Scenario: An elderly person is hospitalized and a family member handles the procedures.

[0960] Server: Collects information about hospitalization and automatically generates procedural flow.

[0961] Device: Instructions such as "Please complete the admission procedures in this order" are displayed on the family member's smartphone, and templates for the necessary documents are also provided.

[0962] Emotional Engine Adjustment

[0963] Scenario: The camera detects anxious facial expressions as a family member goes through a procedure.

[0964] Device: The camera analyzes facial expressions and sends the stress level to the emotion engine.

[0965] Server: Receives emotion data, simplifies the procedure flow, and adds encouraging messages.

[0966] Device: The adjusted procedure flow is displayed on the family member's smartphone, making it easier to proceed with the procedure.

[0967] The above is a specific embodiment of the present invention. This system enables elderly people and their families to receive prompt and appropriate medical treatment and aftercare, and also reduces stress and anxiety with the support of the emotion engine.

[0968] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0969] Step 1: Collect data

[0970] Device: Wearable devices collect vital data such as heart rate, blood pressure, and physical activity of elderly people in real time. For example, a smart watch measures and records this data instantly. The input is the biometric data collected by the sensor, and the output is a set of obtained vital data.

[0971] Step 2: Sending data

[0972] Terminal: The collected data is encrypted using a secure protocol (e.g., HTTPS) and sent to the server. When sending, the API's sendVitalData() function is called. The input is the collected vital data, and the output is the data received on the server side.

[0973] Step 3: Receiving and storing data

[0974] Server: Receives vital data sent from the device and saves it in the database. The receiveData() function is used for receiving, and the saveToDatabase() function is used for saving. The input is the vital data sent from the device, and the output is the data saved in the database.

[0975] Step 4: Analyze the data

[0976] Server: Analyzes the stored vital data and detects abnormal values ​​using a machine learning model (generative AI model). The analyzeData() function is used for the analysis. The input is the stored vital data, and the output is the anomaly detection information as the analysis result.

[0977] Step 5: Detect anomalies and generate notifications

[0978] Server: If an anomaly is detected, a notification is generated containing information about the appropriate medical institution and department. The generateAlert() function is used to generate the notification. The input is the anomaly detection information, and the output is the notification message.

[0979] Step 6: Sending notifications

[0980] Server: Sends the generated notification to the registered emergency contacts. The sendNotification() function is used to send notifications. The input is the notification message, and the output is the notification sent to the emergency contacts.

[0981] Step 7: View notifications

[0982] Terminal: The emergency contact's terminal receives the notification and displays instructions by voice or text. The showNotification() function is used for display. The input is the received notification message, and the output is the displayed notification information.

[0983] Step 8: Automatic generation of procedural flow

[0984] Server: When an elderly person is hospitalized, the necessary procedures and application flow for subsidy programs are automatically generated. The generateProcedureFlow() function is used for generation. The input is hospitalization information, and the output is the automatically generated procedure flow.

[0985] Step 9: Present the procedure flow

[0986] Terminal: The procedure flow is displayed on the family member's terminal, helping the user to easily proceed with the procedure. The displayProcedureInstructions() function is used for display. The input is the automatically generated procedure flow, and the output is the displayed procedure flow.

[0987] Step 10: Report progress

[0988] Terminal: When a procedure is performed, the progress is reported to the server. The reportProgress() function is used for reporting. The input is the procedure information in progress, and the output is the progress data sent to the server.

[0989] Step 11: Track progress and generate reminders

[0990] Server: Records progress in a database and generates reminders for incomplete procedures. Recording is done using the recordProgress() function, and reminders are generated using the generateReminder() function. The input is the progress data, and the output is the recorded progress and the generated reminders.

[0991] Step 12: Send a reminder

[0992] Server: Sends reminders to family members' devices about incomplete procedures. The sendReminder() function is used for sending. The input is the reminder message, and the output is the reminder sent to the user's device.

[0993] Step 13: Recognize emotions

[0994] Device: Recognizes the user's emotions in real time using sensors such as a camera and microphone. The captureEmotionData() function is used for recognition, and the analyzeEmotion() function is used for analysis. The input is facial expression and tone of voice data, and the output is the analyzed emotional state.

[0995] Step 14: Sending Emotion Data

[0996] Terminal: The collected emotion data is sent to the server. The sendEmotionData() function is used for sending. The input is the analyzed emotional state, and the output is the emotion data sent to the server.

[0997] Step 15: Emotional Adjustment

[0998] Server: Dynamically adjusts the notification content and procedure flow presentation method based on the user's emotional state detected by the emotion engine. The adjustProcedureFlowBasedOnEmotion() function is used for adjustment. The input is emotional data, and the output is the adjusted notification content and procedure flow.

[0999] Step 16: Present tailored notifications and procedural flows

[1000] Terminal: The adjusted notification or procedure flow is displayed on the user's terminal. The displayAdjustedProcedureFlow() function is used for display. The input is the adjusted notification content or procedure flow, and the output is the displayed adjusted procedure flow.

[1001] Through these steps, the system can monitor the health status of elderly people in real time, provide appropriate medical treatment if an abnormality is detected, assist with the progress of procedures, and adapt the system's behavior according to the user's emotions.

[1002] (Application example 2)

[1003] 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."

[1004] Real-time health management for the elderly is important for prompt medical response. However, many elderly people have difficulty traveling to medical institutions and completing the appropriate procedures on their own. It is also difficult to constantly monitor the health status of elderly people remotely, and it is often impossible to respond quickly even if an abnormality occurs. Furthermore, there is concern that when elderly people and their families are under stress or anxiety, they may not understand or respond properly to procedures and information provision.

[1005] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for monitoring the elderly person's health condition in real time, means for detecting abnormal health conditions, means for automatically providing information on appropriate medical institutions and departments based on the detected abnormalities, means for issuing notifications to family members and care managers, means for automatically generating and providing necessary procedures and subsidy application flows, means for monitoring progress and sending reminders for incomplete procedures, means for linking with the autonomous vehicle's system and automatically guiding the user to the nearest hospital if an abnormality is detected, and means for analyzing the user's emotional state and adjusting the notification content and procedure flow. This allows the elderly person's health condition to be constantly monitored, and when an abnormality is detected, it is possible to quickly support transportation to a medical institution and necessary procedures. Furthermore, adjusting the method of providing notifications and procedures based on the emotional state reduces stress and anxiety for the elderly person and their family, and more appropriate and prompt responses are expected.

[1006] "Means for monitoring health status in real time" refers to devices or methods that continuously acquire the elderly person's physical vital signs and immediately transmit them to the system.

[1007] "Means for detecting abnormal health conditions" refers to devices or methods that analyze acquired vital data and compare it with reference values ​​to detect abnormalities.

[1008] The "means for automatically providing information about appropriate medical institutions and departments" refers to a device or method that automatically presents information about the appropriate medical institutions and departments based on the detected abnormality.

[1009] "Means for issuing notifications to family members or care managers" refers to a device or method that sends an alert to pre-registered contacts when an abnormality is detected.

[1010] "Means for automatically generating and providing necessary procedures and application flows for subsidy systems" refers to devices and methods that automatically organize and provide information on the procedures and subsidy systems required when elderly people receive medical care.

[1011] A "means for monitoring progress and sending reminders for outstanding procedures" is a device or method that tracks the progress of procedures and sends reminders for outstanding procedures.

[1012] "Means of working in conjunction with the system of an autonomous vehicle to automatically guide the vehicle to the nearest hospital when an abnormality is detected" refers to a device or method that automatically instructs an autonomous vehicle to head to the nearest hospital when an abnormality is detected in real time.

[1013] "Means for analyzing the user's emotional state and adjusting notification content and procedure flow" refers to a device or method that analyzes the user's facial expressions and voice to recognize emotions, and appropriately changes the notification content and procedure presentation method based on that.

[1014] This invention is a system for monitoring the health status of elderly people in real time and responding quickly when an abnormality is detected. Specific embodiments of this system will be described below.

[1015] System configuration

[1016] 1. Health monitoring

[1017] Wearable devices:

[1018] Various wearable devices (e.g., smartwatches) are used as terminals. These devices collect vital data such as the elderly's heart rate, blood pressure, and amount of exercise in real time and send this data to a server. For example, a smartwatch measures the user's heart rate and blood pressure every minute and sends the data to a cloud server.

[1019] 2. Anomaly detection and notification

[1020] server:

[1021] The server analyzes the received data and compares it with reference values ​​to detect any abnormalities. If an abnormality is detected, a notification is issued to the registered emergency contacts (family members or care managers). This notification also includes information on the appropriate medical institution and department to visit. For example, if the server detects an abnormal heart rate, it sends a notification stating "heart rate has risen sharply" and including the contact information of the nearest doctor.

[1022] 3. Collaboration with autonomous vehicles

[1023] Autonomous vehicles:

[1024] This system works in conjunction with the autonomous vehicle's system to automatically guide the elderly person to the nearest hospital if an abnormality is detected. For example, if an elderly person's heart rate shows an abnormal value, the autonomous vehicle will automatically set a route to the nearest hospital and begin moving.

[1025] 4. Assistance with admission procedures

[1026] server:

[1027] The server automatically generates and provides the necessary procedures and application flows for subsidy programs. This allows families to receive the information they need in real time after arriving at the hospital. For example, the "hospitalization procedure flow" provides a list of required documents and templates.

[1028] 5. Progress monitoring and reminders

[1029] Device:

[1030] As the procedure progresses, the progress is reported to the server, which records the progress in a database and sends reminders to the family members' devices about any incomplete procedures, helping them remember to complete them.

[1031] 6. Emotion recognition

[1032] Device:

[1033] The smartphones used by the elderly and their families are equipped with cameras and microphones that can be used to recognize the user's emotions in real time. For example, when a family member goes through a procedure, the camera analyzes their facial expressions to detect emotions such as anxiety or impatience.

[1034] 7. Emotion-Based Adjustment

[1035] server:

[1036] The emotion engine dynamically adjusts notification content and procedure flow based on emotional data analyzed. For example, if it recognizes that the user is feeling stressed, notification content will be displayed in more user-friendly language. The procedure flow will also be simplified and adjusted to require fewer steps.

[1037] Specific examples

[1038] Health monitoring and anomaly detection

[1039] For example, if an elderly person's heart rate exceeds a set threshold (usually less than 100 bpm), the server will detect this as an abnormality and send a notification to emergency contacts, including the message, "Your heart rate is rising rapidly. Please contact a medical institution."

[1040] Collaboration with autonomous vehicles

[1041] When an abnormality is detected, the autonomous vehicle immediately sets a route to the nearest medical facility and quickly transports the elderly person to the hospital. At this time, the necessary information for procedures and the application flow for subsidy programs are automatically generated and displayed on the smartphone.

[1042] Emotional Engine Adjustment

[1043] If the camera detects an anxious expression on a family member's face as they go through the admission procedures, the server will make the notification more friendly and display an encouraging message such as, "Don't worry, the procedure is going smoothly."

[1044] Prompt Sentence Examples

[1045] "If an elderly person's heart rate spikes or blood pressure rises while riding in an autonomous vehicle, please design a system that automatically guides the vehicle to the nearest hospital and sends an emergency alert to registered family members and medical institutions. Also, please include a function that displays the hospital admission procedure flow after the vehicle arrives, analyzes the elderly person's facial expressions with a camera to determine their stress level, and adjusts the content of the notification accordingly."

[1046] As a result, this invention can provide safe and appropriate medical support by monitoring the health status of elderly people in real time and responding quickly when abnormalities are detected.In addition, the introduction of an emotion engine reduces stress and anxiety for elderly people and their families, enabling smoother procedures.

[1047] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1048] Step 1:

[1049] Real-time acquisition of health data for the elderly

[1050] A wearable device collects real-time data on the elderly person's heart rate, blood pressure, and physical activity. This data is measured through sensors on the wearable device. The measured data is sent to a server via the device. The input data is vital signs such as heart rate and blood pressure, and the output is sensor data sent to the server.

[1051] Step 2:

[1052] Health data analysis and anomaly detection

[1053] The server receives data sent from the wearable device and analyzes it using an anomaly detection algorithm. Specifically, if the heart rate exceeds 150 bpm or the blood pressure exceeds 180 / 100, it is deemed to be abnormal. The input data is the vital signs data sent from the wearable device, and the output is the analysis result, such as "normal" or "abnormal."

[1054] Step 3:

[1055] Notification when an abnormality is detected

[1056] If the server detects an abnormality, it sends an emergency alert to registered family members and care managers. The notification also includes information on the appropriate medical institution and department to visit. The input is the abnormality detection result, and the output is a notification message sent to emergency contacts. Notifications are sent via email or SMS.

[1057] Step 4:

[1058] Autonomous vehicle routing

[1059] When the server detects an abnormality, it sends a command to the autonomous vehicle to set a route to the nearest hospital. The input is the abnormality detection and hospital information, and the output is route information sent to the autonomous vehicle. The vehicle's navigation system automatically sets the optimal route and begins moving.

[1060] Step 5:

[1061] Providing information on admission procedures

[1062] The server automatically generates the necessary procedures and application flow for subsidy programs, and sends them to the family's device. The input is a notification of arrival at the hospital, and the output is the procedure flow and a list or template of required documents. The family can then view this and proceed with the procedures.

[1063] Step 6:

[1064] Progress monitoring and reminders

[1065] As family members go through procedures, the device reports their progress to the server. The server records the progress in a database and sends reminders to family members' devices if there are any procedures that need to be completed. The input is the progress data of the procedures, and the output is reminder notifications.

[1066] Step 7:

[1067] Emotion recognition and notification content adjustment

[1068] The device uses a camera and microphone to recognize the emotional state of family members in real time. The server receives the emotional data analyzed using an emotion recognition engine. For example, if a family member shows an anxious expression, the notification content is made more friendly and an encouraging message is added if necessary. The input is the emotional data sent from the device, and the output is the adjusted notification content.

[1069] Through these steps, this system can monitor the health status of elderly people in real time and automatically take appropriate action when an abnormality is detected. It also reduces stress for family members and care managers and enables prompt and appropriate medical support.

[1070] 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.

[1071] 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.

[1072] 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.

[1073] [Third embodiment]

[1074] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1075] 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.

[1076] 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).

[1077] 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.

[1078] 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.

[1079] 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).

[1080] 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.

[1081] 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.

[1082] 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.

[1083] 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.

[1084] 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.

[1085] 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."

[1086] To implement this invention, it is necessary to prepare a wearable device for monitoring the health status of the elderly, a server for analyzing the data, and a terminal that links with the user and emergency contacts. Below, the overall processing flow of the system is explained in natural language.

[1087] 1. Real-time health monitoring

[1088] Device: A wearable device collects vital data such as heart rate, blood pressure, and exercise volume of elderly people in real time. The device is worn on the user's body and measures the data periodically.

[1089] Server: Receives vital data sent from the device and stores it in a database, allowing the health of the elderly to be constantly monitored.

[1090] 2. Data analysis and anomaly detection

[1091] Server: Analyzes the received vital signs and compares them with historical data and baseline values. Algorithms are applied to detect abnormal values ​​(e.g., sudden increases in heart rate or abnormal blood pressure fluctuations).

[1092] Server: Generates an alert if an anomaly is detected. This alert is issued if an immediate response is required.

[1093] 3. Notification and Instructions

[1094] Server: When an alert is generated, a notification is sent to registered emergency contacts (family members or care managers), along with information about the relevant medical institution and department.

[1095] Device: The device of the emergency contact (e.g., a smartphone) receives the notification and instructs the elderly person's family member via voice or text on the appropriate action to take. Specifically, the message "Please contact the nearest internal medicine clinic" is displayed.

[1096] 4. Aftercare support

[1097] Server: When an elderly person is hospitalized or admitted to a facility, information on related procedures is collected and the necessary procedures and application flows for subsidy programs are automatically generated.

[1098] Device: Based on this flow, messages are displayed to guide the family member in need of assistance through the procedure. Templates of the necessary documents are also provided, allowing the family member to efficiently complete the necessary procedures.

[1099] 5. Progress monitoring and reminders

[1100] Terminal: As the user goes through each procedure, the progress is reported to the server. The user inputs the progress of the procedure from a smartphone or tablet.

[1101] Server: Records the progress in a database and generates reminders for incomplete procedures and sends them to the user's device, for example, a message saying "This procedure is not yet complete."

[1102] Specific examples

[1103] Scenario 1: Elderly person A records a heart rate of 150 bpm and blood pressure of 180 / 100

[1104] Device: The smartwatch collects this data and sends it to the server.

[1105] Server: Detects an abnormal value and notifies family member B, who is the emergency contact, that "A's heart rate has suddenly increased. Please contact the nearest internal medicine clinic."

[1106] Device: A notification appears on Mr. B's smartphone, and he rushes to the internal medicine department with Mr. A.

[1107] Scenario 2: Person A is hospitalized and family member B completes the necessary procedures

[1108] Server: Receives information about hospitalization and generates the necessary procedures and application flow for subsidy programs.

[1109] Device: Display the procedure flow on Mr. B's smartphone, stating "Please follow the admission procedures in this order," along with a template of the necessary documents.

[1110] Server: Monitors the progress of the transaction and sends reminders for any outstanding transactions.

[1111] The above is a specific method for carrying out the present invention. This system allows elderly people and their families to receive prompt and appropriate medical treatment and aftercare.

[1112] The processing flow will be explained below.

[1113] Step 1: Collecting health data

[1114] Device: A wearable device collects vital data such as heart rate, blood pressure, and exercise volume in real time. The device is attached to the elderly person's body and measures the data periodically.

[1115] Step 2: Sending data

[1116] Terminal: Collected vital data is sent to the server. The data is encrypted and transmitted securely over the network.

[1117] Step 3: Receiving and storing data

[1118] Server: Receives the data sent from the device and stores it in a database, which also includes the elderly person's past health data.

[1119] Step 4: Analyze the data

[1120] Server: Analyzes the stored data, comparing it with historical data and baseline values ​​and applying algorithms to detect abnormal values ​​(e.g., sudden increases in heart rate or abnormal blood pressure fluctuations).

[1121] Step 5: Detect anomalies

[1122] Server: Generates an alert if an anomaly is detected that exceeds a certain threshold, for example, if the heart rate increases by more than 50% of normal.

[1123] Step 6: Generate notifications

[1124] Server: Based on the generated alert, the server issues a notification to registered emergency contacts (family members or care managers), and also provides information on appropriate medical institutions and departments to visit.

[1125] Step 7: Receiving and Viewing Notifications

[1126] Device: The emergency contact's device (e.g., smartphone) receives the notification. The device displays specific instructions to the family member via voice or text, such as "Please contact the nearest internal medicine doctor."

[1127] Step 8: Family response

[1128] User: Family members receive notifications and follow instructions to take the elderly to medical facilities. They act quickly based on specific instructions.

[1129] Step 9: Obtain admission information

[1130] Server: When an elderly person is hospitalized, the server receives information about the hospitalization from the medical institution and stores it in a database.

[1131] Step 10: Generate procedural flow

[1132] Server: Automatically generates procedures for hospitalization and application procedures for subsidy programs, including the required documents and procedure sequence.

[1133] Step 11: Notification of procedure flow

[1134] Server: Sends the generated procedure flow to the family member's device. The device displays instructions such as "Please follow the procedure at the hospital in this order."

[1135] Step 12: Provide documentation

[1136] Server: Sends templates of the necessary documents to the device so that family members can use them to complete the procedures.

[1137] Step 13: Record the progress of the procedure

[1138] Device: As the family member goes through each procedure, they report their progress to the server. For example, they can use their smartphone to press a button to complete the procedure.

[1139] Step 14: Monitoring progress

[1140] Server: Records progress in a database and generates reminders for incomplete procedures.

[1141] Step 15: Send a reminder

[1142] Server: Sends a reminder to the family member's device about the incomplete procedure. The device displays the message "This procedure is not yet completed."

[1143] Example 1

[1144] 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."

[1145] There is a need for a system that can constantly monitor the health status of elderly people, detect abnormalities, and provide appropriate medical care promptly. However, existing systems are unable to collect and analyze data in real time, making it difficult to quickly notify patients when an abnormality occurs or take appropriate action. In addition, there is no automated system for providing information about hospitalization and procedures, monitoring progress, or sending reminders. For these reasons, there is a need to provide a system that can efficiently and effectively manage the health of elderly people.

[1146] 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.

[1147] In this invention, the server includes: a means for monitoring health status in real time; a means for detecting abnormal health status; a means for automatically providing information on appropriate medical institutions and departments based on the detected abnormalities; a means for issuing notifications to emergency contacts; a means for automatically generating and providing necessary procedures and application flows for subsidy programs; a means for monitoring progress and sending reminders for incomplete procedures; a means for analyzing data stored on the server and using an algorithm to detect abnormal values; a means for using a secure protocol for data communication between the server and a terminal; and a means for sending voice or text notifications to emergency contacts. This allows for real-time monitoring of the health status of elderly people and enables prompt and appropriate response in the event of an abnormality. Furthermore, the provision of information on hospitalization and procedures, progress monitoring, and sending reminders are automated, reducing the burden on elderly people and their families.

[1148] "Real-time health monitoring" refers to the use of wearable devices to continuously collect personal physical data (e.g., heart rate, blood pressure, and exercise volume) and to analyze and manage that data in real time.

[1149] "Detecting abnormal health conditions" refers to identifying abnormal values ​​(e.g., sudden increases in heart rate or abnormal fluctuations in blood pressure) based on collected data and comparing them with baseline values ​​or past data.

[1150] "Automatically providing information about appropriate medical institutions and departments" means that when an abnormality is detected, information about the medical institution and department that is most suitable for the abnormality is automatically provided to the user.

[1151] "Issuing a notification to an emergency contact" means that if an abnormality is detected, a notification will be sent promptly to a pre-registered emergency contact (e.g., family member or care manager).

[1152] "Automatic generation of application flows for procedures and subsidy systems" means that the system automatically generates and provides application flows for procedures and subsidy systems that are necessary when elderly people are hospitalized or admitted to a facility.

[1153] "Progress monitoring" means tracking and managing the progress of each step of a user's procedure in real time.

[1154] "Sending reminders" means sending notifications or alerts to users when there are incomplete procedures or important steps.

[1155] An "algorithm for analyzing data and detecting outliers" is a program or mathematical method for identifying outliers based on collected data.

[1156] A "secure protocol for data communication between a server and a terminal" is a communication method (e.g., HTTPS, TLS) for securely transmitting data between a server and a terminal.

[1157] "Send voice and text notifications" refers to sending important messages to users in the form of voice alerts and text messages.

[1158] A "wearable device" is a small electronic device that can be worn on the body and collects physical data such as heart rate, blood pressure, and exercise volume.

[1159] A "server" is a computer on a network that stores and analyzes data, detects anomalies, and sends notifications.

[1160] A "terminal" is a device (e.g., a smartphone or tablet) that receives data from a server or wearable device and gives instructions to the user.

[1161] "Entering progress status" means that the user reports the progress of the procedure to the system using a smartphone or tablet.

[1162] "Procedure flow suggestions" means that the system automatically provides the order and methods of procedures that elderly people and their families should follow.

[1163] "Providing templates for required documents" means providing the user with formats for documents required to carry out the procedure.

[1164] MODE FOR CARRYING OUT THE INVENTION

[1165] To implement this invention, it is necessary to build a system that monitors the health status of elderly people in real time, detects abnormalities, and provides instructions on appropriate measures. Specifically, the following hardware and software are required:

[1166] System configuration

[1167] 1. Wearable devices

[1168] Device:

[1169] Wearable devices (e.g., health trackers, smartwatches) collect real-time vital data such as heart rate, blood pressure, and physical activity of elderly people. These devices can be worn on the body and transmit the data to a connected smartphone via Bluetooth or Wi-Fi.

[1170] 2. Smartphone (or tablet)

[1171] Device:

[1172] The smartphone receives data from the wearable device and sends it to a cloud server using a secure communication protocol (e.g., HTTPS).

[1173] 3. Cloud Server

[1174] server:

[1175] A cloud server (e.g., Amazon Web Services, Google Cloud) receives the vital data sent from the smartphone and stores it in a dedicated database (e.g., Amazon RDS, Firebase RealTime Database).

[1176] Data analysis and anomaly detection

[1177] server:

[1178] The received data is analyzed using an anomaly detection algorithm (e.g., machine learning model) created in Python or R. Anomalies are detected by comparing them with past data and reference values ​​(e.g., heart rate 60-100 bpm, blood pressure below 120 / 80).

[1179] Sending alerts and notifications

[1180] server:

[1181] If abnormal data is detected (e.g. heart rate 150 bpm, blood pressure 180 / 100), an alert is generated and a notification is sent to emergency contacts using Twilio or Firebase Notifications.

[1182] Device:

[1183] The smartphone of the emergency contact (e.g., family member or care manager) receives a notification and instructs the elderly person's family member on appropriate actions via voice notification or text message.

[1184] Automatic generation and support of procedures

[1185] server:

[1186] When an elderly person is hospitalized or admitted to a facility, information about the hospitalization is received and a Python script is used to automatically generate the necessary procedures and application flow for subsidy programs.

[1187] Device:

[1188] The system sends a notification to the emergency contact's smartphone explaining the procedure and provides templates for the necessary documents. For example, it includes specific instructions such as "Please follow this order when completing the admission procedures."

[1189] Progress monitoring and reminders

[1190] User:

[1191] As the emergency contact (family member) goes through the procedure, they enter the progress into the server via their smartphone.

[1192] server:

[1193] The entered progress is recorded in a database, and reminders are generated and sent to the user's device for any incomplete procedures, such as a "This procedure is not yet complete" reminder.

[1194] Specific examples

[1195] Scenario 1: Elderly person A records a heart rate of 150 bpm and blood pressure of 180 / 100

[1196] Device: The smartwatch collects this data and sends it to a cloud server via the smartphone.

[1197] Server: Detects an abnormal value and uses the Twilio API to notify the family member who is the emergency contact, saying, "Mr. A's heart rate has suddenly increased. Please contact the nearest internal medicine clinic."

[1198] Device: A notification appears on the family member's smartphone, and they rush to the internal medicine department with Mr. A.

[1199] Scenario 2: Person A is hospitalized and family member B completes the necessary procedures

[1200] Server: Receives information about hospitalization and generates procedures and application flows for subsidy programs.

[1201] Device: The family member's smartphone will be shown a procedure flow stating, "Please follow the admission procedures in this order," along with a template of the necessary documents.

[1202] Server: Monitors the progress of the transaction and sends reminders for any outstanding transactions.

[1203] Prompt Sentence Examples

[1204] "Write Python code to analyze heart rate and blood pressure data and detect outliers."

[1205] "How do I use the Twilio API to send an SMS in case of an error?"

[1206] This system allows elderly people and their families to receive prompt and appropriate medical response and aftercare.

[1207] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1208] Step 1:

[1209] Data collection

[1210] Device: A wearable device (e.g., a smartwatch) collects vital data such as heart rate, blood pressure, and activity level in real time. The device collects data every few seconds and transmits it to a connected smartphone via Bluetooth or Wi-Fi.

[1211] Input: Real-time vital data from biosensors.

[1212] Output: Collected vital data is sent to a smartphone.

[1213] Step 2:

[1214] Data transmission

[1215] Terminal: The smartphone receives data from the wearable device and sends it to the cloud server using a secure communication protocol (e.g., HTTPS).

[1216] Input: Vital data collected by the device.

[1217] Output: Vital data sent to cloud server via secure communication.

[1218] Step 3:

[1219] Data reception and storage

[1220] Server: A cloud server (e.g., AWS EC2) receives the vital data sent from the smartphone and stores it in a dedicated database (e.g., Amazon RDS).

[1221] Input: Vital data sent over secure communication.

[1222] Output: Vital data stored in a database.

[1223] Step 4:

[1224] Data analysis

[1225] Server: The received data is analyzed using an anomaly detection algorithm (e.g., machine learning model) created in Python or R. The data is compared with past vital signs and reference values ​​(e.g., heart rate 60-100 bpm, blood pressure below 120 / 80) to detect abnormal values.

[1226] Input: Saved vital data and baseline values, historical data.

[1227] Output: Information about detected outliers.

[1228] Step 5:

[1229] Alert Generation

[1230] Server: If abnormal data is detected (e.g., heart rate 150 bpm, blood pressure 180 / 100), a Python script generates an alert that explains what caused the abnormality and recommends corrective actions.

[1231] Input: Outlier information as an analysis result.

[1232] Output: Alert information.

[1233] Step 6:

[1234] Send notifications

[1235] Server: Based on the generated alert, a notification is sent to emergency contacts using Twilio or Firebase Notifications. The notification includes specific instructions such as "Your heart rate has increased dramatically. Please contact the nearest medical facility."

[1236] Input: The generated alert information.

[1237] Output: Notification message sent to emergency contacts.

[1238] Step 7:

[1239] Receive notifications

[1240] Device: The smartphone of the emergency contact (e.g., family member) receives the notification and instructs the elderly family member on appropriate actions via voice notification or text.

[1241] Input: The notification message sent by the server.

[1242] Output: Notification content displayed on the emergency contact's device.

[1243] Step 8:

[1244] Procedural flow generation

[1245] Server: When an elderly person is hospitalized or admitted to a facility, a Python script is used to automatically generate the necessary procedures and application flow for subsidy programs.

[1246] Input: Information about hospitalization and institutionalization.

[1247] Output: Generated procedure flow and subsidy application guide.

[1248] Step 9:

[1249] Procedure flow notification

[1250] Server: The generated procedure flow is sent to the smartphone of the emergency contact. The notification includes specific instructions such as "Please follow the admission procedure in this order."

[1251] Input: The generated procedure flow.

[1252] Output: The procedure flow sent to the emergency contact's device.

[1253] Step 10:

[1254] Entering the progress of procedures

[1255] User: As the emergency contact (family member) goes through each procedure, they enter the progress information into the server using their smartphone or tablet.

[1256] Input: Procedural progress.

[1257] Output: Progress data reported to the server.

[1258] Step 11:

[1259] Progress monitoring

[1260] Server: Records the entered progress in a database and monitors the progress of the procedure.

[1261] Input: User-reported progress data.

[1262] Output: Progress and monitoring results recorded in a database.

[1263] Step 12:

[1264] Generate and send reminders

[1265] Server: Generates reminders for incomplete procedures and sends them to the user's device. For example, it sends a reminder notification saying "This procedure has not yet been completed."

[1266] Input: Progress data and open procedure information.

[1267] Output: The reminder notification sent to the user's device.

[1268] (Application example 1)

[1269] 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."

[1270] Real-time monitoring of the health status of elderly people and early detection of abnormalities are important challenges for families and care managers. Rapid and accurate responses are also required when abnormalities are detected. Furthermore, there is a need to streamline procedures for post-health abnormality procedures and applications for subsidies, and to appropriately manage progress. However, conventional systems have had difficulty fully meeting these requirements.

[1271] 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.

[1272] In this invention, the server includes a means for collecting and analyzing vital data from the wearable device using a smartphone and smart glasses, detecting abnormalities and sending notifications, a means for acquiring data such as the elderly person's heart rate, blood pressure, and amount of exercise using the wearable device and sending it to the server via the smartphone and smart glasses, and a means for providing templates for required documents based on a proposed procedure flow and sending incomplete reminders, thereby enabling early detection of abnormalities and rapid response, efficient procedure support, and appropriate progress management.

[1273] Here are the definitions:

[1274] "Health status of the elderly" refers to vital data such as the elderly's heart rate, blood pressure, and amount of exercise.

[1275] "Means of real-time monitoring" refers to a system that uses wearable devices to continuously collect vital data and send it to a server, allowing the data to be checked immediately.

[1276] "Means for detecting abnormal health conditions" refers to algorithms that analyze collected vital data and compare it with baseline values ​​to detect abnormal values.

[1277] "Means for automatically providing information about appropriate medical institutions and departments" refers to a system that provides data about the nearest appropriate medical institutions and departments based on detected abnormalities.

[1278] "Means of issuing notifications to family members or care managers" refers to a notification mechanism that sends an alert to emergency contacts when an abnormality is detected.

[1279] "Means for automatically generating and providing application flows for procedures and subsidy programs" refers to the function of automatically generating and providing information regarding procedures and applications for subsidy programs that are necessary when an elderly person is hospitalized, for example.

[1280] "Means for monitoring progress and sending reminders for incomplete procedures" refers to a system that monitors the progress of procedures and sends reminder notifications for incomplete procedures.

[1281] "Smartphones and smart glasses" refer to portable devices that receive, analyze, and notify data from wearable devices.

[1282] A "wearable device" refers to a device that is worn on the body and continuously collects vital data.

[1283] "Means for collecting and analyzing data, detecting abnormalities, and notifying" refers to a system that collects vital data from wearable devices, analyzes it on a server to detect abnormalities, and sends notifications to emergency contacts.

[1284] In order to implement the present invention, the following hardware and software are used.

[1285] Hardware:

[1286] 1. Wearable devices: Devices that collect vital data such as heart rate, blood pressure, and physical activity of elderly people. These devices include, for example, smart watches and fitness trackers.

[1287] 2. Smartphones and smart glasses: These devices are used to receive data collected from wearable devices and send it to the server. Smartphones are used to run applications and display notifications. Smart glasses are also used to display data and receive notifications.

[1288] 3. Server: A server that receives and analyzes data from wearable devices.

[1289] software:

[1290] 1. Data collection and transmission program: A program for collecting data from wearable devices and transmitting it to a server through smartphones and smart glasses.

[1291] 2. Data analysis program: A program that analyzes vital data on the server and detects abnormalities. For example, it can be implemented using Python or R.

[1292] 3. Notification program: This program sends an alert to emergency contacts when an abnormality is detected. This program uses RESTful APIs or Firebase Cloud Messaging (FCM) to send notifications.

[1293] 4. Procedure flow provision and reminder program: This program automatically generates information regarding procedures after a health abnormality and applications for subsidies, and reminds users of incomplete procedures.

[1294] Process flow:

[1295] 1. Data collection: The wearable device periodically measures the elderly person's heart rate, blood pressure, and physical activity, and transmits the data to a smartphone and smart glasses.

[1296] 2. Data transmission: The smartphone and smart glasses transmit the received vital data to the server via Bluetooth.

[1297] 3. Data analysis: The server analyzes the received vital data and compares it with baseline values ​​to detect abnormalities. Machine learning algorithms and rule-based analysis methods are used for the analysis.

[1298] 4. Anomaly detection and notification: If an anomaly is detected, the server will send an alert to emergency contacts, notifying them of the abnormal data and recommending a course of action (e.g., "Contact your local internal medicine doctor").

[1299] 5. Providing procedure flow and reminders: When an elderly person is hospitalized, the server automatically generates a procedure flow and a template of the necessary documents and sends them to the smartphone or smart glasses. It also monitors the progress and sends reminder notifications if the procedure is incomplete.

[1300] Examples:

[1301] Scenario 1:

[1302] When an elderly person's heart rate reaches 150 bpm and blood pressure reaches 180 / 100, the server detects the abnormality and sends an alert to the smartphone and smart glasses saying, "Your heart rate has suddenly increased. Please contact your internal medicine doctor."

[1303] Scenario 2:

[1304] When an elderly person is hospitalized and their family members are completing the necessary procedures, the server generates a procedure flow and a template of the necessary documents, and displays it on the family members' smartphones and smart glasses, telling them to "proceed with the procedures in this order." It also reminds them of any incomplete procedures.

[1305] Example of a generative AI model prompt:

[1306] Example prompt:

[1307] We built a system to monitor the health of elderly people. The system collects and analyzes data from wearable devices in real time and sends notifications to emergency contacts if an abnormality is detected. We used Python and RESTful APIs to implement the processes for data transmission, anomaly detection, and notification generation.

[1308] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1309] Step 1:

[1310] Data collection

[1311] Input: A wearable device (e.g., a smartwatch) collects vital data such as an elderly person's heart rate, blood pressure, and activity level.

[1312] How it works: Measures vital signs at regular intervals and syncs the data with your smartphone and smart glasses.

[1313] Output: The measured vital data is sent to a smartphone and smart glasses.

[1314] Step 2:

[1315] Data transmission

[1316] Input: Vital data received from a wearable device.

[1317] How it works: The smartphone and smart glasses transmit the vital data they receive via Bluetooth to a server.

[1318] Output: Vital data arrives at the server.

[1319] Step 3:

[1320] Data analysis

[1321] Input: Vital data sent to the server.

[1322] How it works: The server uses programs such as Python to analyze vital data. The data is compared with known normal values ​​and calculations are performed to detect abnormalities.

[1323] Output: If an anomaly is detected, the type of anomaly and the anomaly detection result are generated. If no anomaly is detected, the analysis result is stored.

[1324] Step 4:

[1325] Anomaly detection and notification

[1326] Input: Anomaly detection results generated by data analysis.

[1327] How it works: The server generates and sends alerts to emergency contacts based on the anomaly detection results. Alerts are sent using RESTful APIs and Firebase Cloud Messaging (FCM).

[1328] Output: An alert is sent to emergency contacts and a notification is displayed on the smartphone and smart glasses.

[1329] Step 5:

[1330] Procedural flow provided

[1331] Input: Elderly person's admission information and related procedure information.

[1332] Operation: The server automatically generates the steps required for a target procedure such as hospitalization and prepares templates for the necessary documents.

[1333] Output: The procedure flow and templates of required documents are sent to the smartphone and smart glasses.

[1334] Step 6:

[1335] Reminder generation

[1336] Input: Procedural progress data entered by the user.

[1337] Behavior: The server monitors the progress of procedures and generates reminders for incomplete procedures. Reminders are generated based on progress data.

[1338] Output: Reminders for outstanding procedures are sent to the user's smartphone and smart glasses.

[1339] (Example prompt):

[1340] "We built a system to monitor the health of elderly people. The system collects and analyzes data from wearable devices in real time, and sends notifications to emergency contacts if an abnormality is detected. We used Python and RESTful APIs to implement the processes for data transmission, anomaly detection, and notification generation."

[1341] 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.

[1342] This system monitors the health status of elderly people in real time, and when abnormalities are detected, it provides information on appropriate medical institutions and departments and issues notifications to family members and care managers. It also automatically generates procedures for post-hospitalization and facility admission, as well as application flows for subsidy programs, and monitors progress to send reminders for incomplete procedures. Furthermore, by combining it with an emotion engine that recognizes user emotions, it can automatically adjust the content of notifications and the presentation method of the procedure flow.

[1343] System configuration

[1344] 1. Health monitoring

[1345] Device: A wearable device collects vital data such as heart rate, blood pressure, and exercise volume of elderly people in real time. It is worn on the user's body and measures the data periodically.

[1346] Server: Receives vital data sent from the device and stores it in a database. This data is analyzed and generates an alert if an abnormality is detected.

[1347] 2. Anomaly detection and notification

[1348] Server: Analyzes the received data and compares it with the reference values. If an abnormal value is detected, a notification is sent to the registered emergency contacts. The notification also includes information on the appropriate medical institution and department to visit.

[1349] Device: The emergency contact's device will receive a notification and display voice and text instructions, allowing for a quick response.

[1350] 3. Assistance with admission procedures

[1351] Server: When an elderly person is hospitalized, the necessary procedures and application flow for subsidy programs are automatically generated. This information is sent to the family's device, and the procedure order and templates for the necessary documents are provided.

[1352] Device: The procedure flow is displayed on the family member's device, helping the user to complete the procedure easily.

[1353] 4. Progress monitoring and reminders

[1354] The device reports its progress to the server as it processes the transaction, which records the progress in a database and sends reminders about any outstanding transactions.

[1355] Server: Monitors the progress of procedures and sends reminders to family members' devices about incomplete procedures, helping them remember to complete them.

[1356] Combining Emotion Engines

[1357] 5. Emotion recognition

[1358] Device: Using sensors such as cameras and microphones, the device recognizes the user's emotions in real time, analyzing facial expressions and tone of voice to detect emotional states.

[1359] Server: Receives emotional data analyzed by the emotion engine and adjusts the notification content and procedure flow presentation method based on this data. For example, if the user is feeling stressed, the notification will be more friendly and the procedure flow will be more concise.

[1360] 6. Emotion-Based Regulation

[1361] Server: Based on the user's emotional state detected by the emotion engine, the server dynamically adjusts the content of notifications and the way procedural flow is presented, making it easier for users to understand and reducing stress.

[1362] Device: Display tailored notifications and procedural flows on the user's device, for example adding encouraging messages if the user is feeling anxious.

[1363] Specific examples

[1364] Health monitoring and anomaly detection

[1365] Scenario: Elderly person A's heart rate is 150 bpm and blood pressure is 180 / 100.

[1366] Device: The smartwatch collects this data and sends it to the server.

[1367] Server: Detects an abnormality and notifies emergency contacts, saying, "Mr. A's heart rate has suddenly increased. Please contact the nearest internal medicine clinic."

[1368] Device: A notification appears on the emergency contact's smartphone, and family member B takes person A to the internal medicine clinic.

[1369] Assistance with admission procedures

[1370] Scenario: Person A is hospitalized and family member B completes the necessary procedures.

[1371] Server: Collects information about hospitalization and automatically generates procedural flow.

[1372] Device: Mr. B's smartphone displays instructions such as "Please complete the admission procedures in this order," and also provides templates for the necessary documents.

[1373] Emotional Engine Adjustment

[1374] Scenario: When B is going through the procedure, the camera detects an anxious expression on B's face.

[1375] Device: The camera analyzes Mr. B's facial expression and sends his stress level to the emotion engine.

[1376] Server: Receives emotion data, simplifies the process, and adds encouraging messages.

[1377] Device: The adjusted procedure flow is displayed on Mr. B's smartphone, making it easier to proceed with the procedure.

[1378] The above is a specific method for implementing the present invention. This system enables elderly people and their families to receive prompt and appropriate medical treatment and aftercare, and furthermore, the emotional engine provides support to reduce stress and anxiety in users.

[1379] The processing flow will be explained below.

[1380] This system monitors the health status of elderly people in real time, and when abnormalities are detected, it provides information on appropriate medical institutions and departments and issues notifications to family members and care managers. It also automatically generates procedures for post-hospitalization and facility admission, as well as application flows for subsidy programs, and monitors progress to send reminders for incomplete procedures. Furthermore, by combining it with an emotion engine that recognizes user emotions, it can automatically adjust the content of notifications and the presentation method of the procedure flow.

[1381] System processing steps

[1382] 1. Real-time health monitoring

[1383] Step 1:

[1384] Device: Wearable devices (e.g., smartwatches) collect vital data such as heart rate, blood pressure, and exercise volume in real time. The device is worn on the user's body and measures data every second.

[1385] Step 2:

[1386] Terminal: Sends collected vital data to the server. The data is encrypted and sent over the network using a secure protocol.

[1387] Step 3:

[1388] Server: Receives data sent from the device and stores it in a real-time database. The stored data is immediately available for analysis.

[1389] 2. Data analysis and anomaly detection

[1390] Step 4:

[1391] Server: Analyzes the received vital data. It compares it with past data and preset reference values ​​and uses algorithms to detect abnormalities. For example, if the heart rate rises by more than 50% of normal.

[1392] Step 5:

[1393] Server: Generates an alert when an anomaly is detected. The alert includes details of the anomaly (e.g., a sudden increase in heart rate).

[1394] 3. Issuing and Receiving Emergency Notifications

[1395] Step 6:

[1396] Server: Based on the generated alert, the server issues a notification to registered emergency contacts (family members or care managers), including information on the appropriate medical institution and department.

[1397] Step 7:

[1398] Device: The emergency contact's device (e.g., smartphone) receives the notification, which may include a voice notification or a text message with specific instructions, such as "Contact your nearest internal medicine doctor."

[1399] 4. Incorporating and adjusting the emotional engine

[1400] Step 8:

[1401] Device: Uses a camera and microphone to collect the user's facial expressions and tone of voice in real time. Example: Analyzing emotional state from facial expressions.

[1402] Step 9:

[1403] Server: The emotion engine analyzes the collected data and determines the user's emotional state (e.g., anxiety, stress, relief).

[1404] Step 10:

[1405] Server: Based on the analysis results of the emotion engine, the server automatically adjusts the notification content and the way the procedure flow is presented. If the user is anxious, the server makes the notification content more user-friendly and simplifies the procedure flow.

[1406] Step 11:

[1407] Device: Display tailored notifications and procedural flows on the user's device. For example, display encouraging messages or simple instructions to a user who is feeling anxious.

[1408] 5. Assist with admission procedures and monitor progress

[1409] Step 12:

[1410] Server: When an elderly person is hospitalized, the server receives information about the hospitalization from the medical institution and stores it in a database.

[1411] Step 13:

[1412] Server: Automatically generates the procedures required to support hospital admission procedures and application flows for subsidy programs, including the required documents and procedure sequence.

[1413] Step 14:

[1414] Device: The procedure flow and templates for required documents are displayed on the family member's device (e.g., smartphone). For example, instructions such as "Please complete the admission procedures in this order" are displayed.

[1415] Step 15:

[1416] Device: As family members go through the process, they report their progress to the server. Progress is recorded manually or automatically.

[1417] Step 16:

[1418] Server: Monitors progress in real time and generates reminders for incomplete procedures.

[1419] Step 17:

[1420] Devices: Reminders are sent to family members' devices about incomplete transactions, such as the message "This transaction is not yet complete."

[1421] Specific examples

[1422] Scenario 1: Health monitoring and anomaly detection

[1423] If elderly person A's heart rate is recorded as 150 bpm and blood pressure as 180 / 100, the following steps are executed:

[1424] Device: The smartwatch collects this data and sends it to the server.

[1425] Server: Detects an abnormality and notifies emergency contacts, saying, "Mr. A's heart rate has suddenly increased. Please contact the nearest internal medicine clinic."

[1426] Device: A notification appears on the emergency contact's smartphone, and family member B takes person A to the internal medicine clinic.

[1427] Scenario 2: Assistance with admission procedures

[1428] When Person A is admitted to the hospital and Family Member B makes the necessary arrangements, the following steps are taken:

[1429] Server: Collects information about hospitalization and sends an automatically generated procedure flow to the family's device.

[1430] Device: Mr. B's smartphone displays instructions such as "Please complete the admission procedures in this order," and also provides templates for the necessary documents.

[1431] Scenario 3: Emotion Engine Regulation

[1432] If the camera detects an anxious expression on Mr. B's face as he goes through the process, the next step is executed.

[1433] Device: The camera analyzes Mr. B's facial expression and sends his stress level to the emotion engine.

[1434] Server: Receives emotion data, simplifies the process, and adds encouraging messages.

[1435] Device: The adjusted procedure flow is displayed on Mr. B's smartphone, making it easier to proceed with the procedure.

[1436] The above is a specific method for implementing the present invention. This system enables elderly people and their families to receive prompt and appropriate medical treatment and aftercare, and furthermore, the emotional engine provides support to reduce stress and anxiety in users.

[1437] Example 2

[1438] 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."

[1439] The challenge is to monitor the health status of elderly people in real time and provide prompt and appropriate medical treatment when abnormalities occur. It is also necessary to reduce incomplete procedures by managing the progress of procedures and sending necessary reminders. Furthermore, it is required to reduce stress and anxiety by adjusting notification content and procedure flow according to the user's emotional state.

[1440] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for monitoring the health condition of the elderly person in real time, means for detecting abnormal health conditions, means for automatically providing information on appropriate medical institutions and departments to visit based on the detected abnormalities, means for issuing notifications to family members and care managers, means for automatically generating and providing necessary procedures and application flows for subsidy programs, means for monitoring progress and sending reminders for incomplete procedures, and means for adjusting the notification content and the presentation method of the procedure flow using an emotion engine that recognizes the user's emotions. This makes it possible to monitor the health condition of the elderly person in real time, detect abnormalities, provide appropriate medical information, manage the progress of procedures, and adjust the notification content according to the user's emotions.

[1441] The term "elderly" generally refers to people aged 65 and over.

[1442] "Health status" refers to physiological and physical data such as heart rate, blood pressure, and activity level.

[1443] "Real-time" refers to processing and response occurring immediately with little or no delay.

[1444] "Abnormal" refers to health indicators such as heart rate, blood pressure, or activity level that are outside the normal range.

[1445] "Medical institution" refers to a facility that provides medical services, such as a hospital, clinic, or medical office.

[1446] "Medical department" refers to a medical department that handles a specific medical field, such as internal medicine, surgery, or psychosomatic medicine.

[1447] "Notification" refers to an alert or communication of information issued when an abnormality is detected, etc.

[1448] "Family" refers to the elderly person's close relatives, kin, or trusted acquaintances.

[1449] A "care manager" is a professional who creates care plans for elderly people and supports their progress.

[1450] "Procedure flow" refers to the series of procedures or steps required to achieve a specific purpose.

[1451] "Subsidy system" refers to public support programs for health management, medical care, nursing care, etc. available to the elderly.

[1452] "Reminder" refers to a notification or message that informs a user about an incomplete procedure.

[1453] An "emotion engine" refers to a system that analyzes a user's emotional state and adjusts the way information is presented accordingly.

[1454] This system monitors the health status of elderly people in real time, and when abnormalities are detected, it provides information on appropriate medical institutions and departments and issues notifications to family members and care managers. It also automatically generates procedures for post-hospitalization and facility admission, as well as application flows for subsidy programs, and monitors progress to send reminders for incomplete procedures. Furthermore, by combining it with an emotion engine that recognizes user emotions, it can automatically adjust the content of notifications and the presentation method of the procedure flow.

[1455] System configuration

[1456] 1. Health monitoring

[1457] Devices: Wearable devices collect vital data such as heart rate, blood pressure, and physical activity of elderly people in real time. These devices usually use APIs to collect data and send it to a server at regular intervals. For example, a smartwatch can be used as a device to collect and send this data.

[1458] Server: Receives vital data sent from the device and stores it in a database. This data is analyzed and an alert is generated if an abnormality is detected. Machine learning models are used to analyze the data.

[1459] 2. Anomaly detection and notification

[1460] Server: Compares the received vital data with the reference values, and if an abnormal value is detected, issues a notification to the registered emergency contacts. The notification also includes information on the appropriate medical institution and department to visit, enabling a prompt response.

[1461] Device: The emergency contact's device receives the notification and displays voice and text instructions. For example, a smartphone can handle this function.

[1462] 3. Assistance with admission procedures

[1463] Server: When an elderly person is hospitalized, the necessary procedures and application flow for subsidy programs are automatically generated. This information is sent to the family's device, and the order of procedures and templates for required documents are provided.

[1464] Device: The procedure flow is displayed on the family member's device, helping the user to easily proceed with the procedure.

[1465] 4. Progress monitoring and reminders

[1466] Terminal: Reports progress to the server as the procedure proceeds.

[1467] Server: Progress is recorded in a database and reminders are generated for any outstanding procedures. These reminders are sent to family members' devices, helping them remember to complete the procedures.

[1468] Combining Emotion Engines

[1469] 5. Emotion recognition

[1470] Device: Using sensors such as cameras and microphones, the device recognizes the user's emotions in real time. For example, it analyzes facial expressions and tone of voice to detect emotional states.

[1471] Server: Receives emotional data analyzed by the emotion engine and adjusts the notification content and procedure flow presentation method based on this data. For example, if the user is feeling stressed, the notification will be more friendly and the procedure flow will be more concise.

[1472] 6. Emotion-Based Regulation

[1473] Server: Based on the user's emotional state detected by the emotion engine, the server dynamically adjusts the notification content and the way the procedure flow is presented, making it easier for the user to understand and reducing stress.

[1474] Device: Tailored notifications and flow of procedures are displayed on the user's device, for example, adding encouraging messages if the user is feeling anxious.

[1475] Specific examples

[1476] Health monitoring and anomaly detection

[1477] Scenario: An elderly person has a heart rate of 150 bpm and a blood pressure of 180 / 100.

[1478] Device: The smartwatch collects this data and sends it to the server.

[1479] Server: Detects an abnormality and notifies the emergency contact, saying, "Mr. A's heart rate has suddenly increased. Please contact the nearest internal medicine clinic."

[1480] Device: A notification appears on the emergency contact's smartphone, allowing the family member to take the elderly person to the internal medicine clinic.

[1481] Assistance with admission procedures

[1482] Scenario: An elderly person is hospitalized and a family member handles the procedures.

[1483] Server: Collects information about hospitalization and automatically generates procedural flow.

[1484] Device: Instructions such as "Please complete the admission procedures in this order" are displayed on the family member's smartphone, and templates for the necessary documents are also provided.

[1485] Emotional Engine Adjustment

[1486] Scenario: The camera detects anxious facial expressions as a family member goes through a procedure.

[1487] Device: The camera analyzes facial expressions and sends the stress level to the emotion engine.

[1488] Server: Receives emotion data, simplifies the procedure flow, and adds encouraging messages.

[1489] Device: The adjusted procedure flow is displayed on the family member's smartphone, making it easier to proceed with the procedure.

[1490] The above is a specific embodiment of the present invention. This system enables elderly people and their families to receive prompt and appropriate medical treatment and aftercare, and also reduces stress and anxiety with the support of the emotion engine.

[1491] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1492] Step 1: Collect data

[1493] Device: Wearable devices collect vital data such as heart rate, blood pressure, and physical activity of elderly people in real time. For example, a smart watch measures and records this data instantly. The input is the biometric data collected by the sensor, and the output is a set of obtained vital data.

[1494] Step 2: Sending data

[1495] Terminal: The collected data is encrypted using a secure protocol (e.g., HTTPS) and sent to the server. When sending, the API's sendVitalData() function is called. The input is the collected vital data, and the output is the data received on the server side.

[1496] Step 3: Receiving and storing data

[1497] Server: Receives vital data sent from the device and saves it in the database. The receiveData() function is used for receiving, and the saveToDatabase() function is used for saving. The input is the vital data sent from the device, and the output is the data saved in the database.

[1498] Step 4: Analyze the data

[1499] Server: Analyzes the stored vital data and detects abnormal values ​​using a machine learning model (generative AI model). The analyzeData() function is used for the analysis. The input is the stored vital data, and the output is the anomaly detection information as the analysis result.

[1500] Step 5: Detect anomalies and generate notifications

[1501] Server: If an anomaly is detected, a notification is generated containing information about the appropriate medical institution and department. The generateAlert() function is used to generate the notification. The input is the anomaly detection information, and the output is the notification message.

[1502] Step 6: Sending notifications

[1503] Server: Sends the generated notification to the registered emergency contacts. The sendNotification() function is used to send notifications. The input is the notification message, and the output is the notification sent to the emergency contacts.

[1504] Step 7: View notifications

[1505] Terminal: The emergency contact's terminal receives the notification and displays instructions by voice or text. The showNotification() function is used for display. The input is the received notification message, and the output is the displayed notification information.

[1506] Step 8: Automatic generation of procedural flow

[1507] Server: When an elderly person is hospitalized, the necessary procedures and application flow for subsidy programs are automatically generated. The generateProcedureFlow() function is used for generation. The input is hospitalization information, and the output is the automatically generated procedure flow.

[1508] Step 9: Present the procedure flow

[1509] Terminal: The procedure flow is displayed on the family member's terminal, helping the user to easily proceed with the procedure. The displayProcedureInstructions() function is used for display. The input is the automatically generated procedure flow, and the output is the displayed procedure flow.

[1510] Step 10: Report progress

[1511] Terminal: When a procedure is performed, the progress is reported to the server. The reportProgress() function is used for reporting. The input is the procedure information in progress, and the output is the progress data sent to the server.

[1512] Step 11: Track progress and generate reminders

[1513] Server: Records progress in a database and generates reminders for incomplete procedures. Recording is done using the recordProgress() function, and reminders are generated using the generateReminder() function. The input is the progress data, and the output is the recorded progress and the generated reminders.

[1514] Step 12: Send a reminder

[1515] Server: Sends reminders to family members' devices about incomplete procedures. The sendReminder() function is used for sending. The input is the reminder message, and the output is the reminder sent to the user's device.

[1516] Step 13: Recognize emotions

[1517] Device: Recognizes the user's emotions in real time using sensors such as a camera and microphone. The captureEmotionData() function is used for recognition, and the analyzeEmotion() function is used for analysis. The input is facial expression and tone of voice data, and the output is the analyzed emotional state.

[1518] Step 14: Sending Emotion Data

[1519] Terminal: The collected emotion data is sent to the server. The sendEmotionData() function is used for sending. The input is the analyzed emotional state, and the output is the emotion data sent to the server.

[1520] Step 15: Emotional Adjustment

[1521] Server: Dynamically adjusts the notification content and procedure flow presentation method based on the user's emotional state detected by the emotion engine. The adjustProcedureFlowBasedOnEmotion() function is used for adjustment. The input is emotional data, and the output is the adjusted notification content and procedure flow.

[1522] Step 16: Present tailored notifications and procedural flows

[1523] Terminal: The adjusted notification or procedure flow is displayed on the user's terminal. The displayAdjustedProcedureFlow() function is used for display. The input is the adjusted notification content or procedure flow, and the output is the displayed adjusted procedure flow.

[1524] Through these steps, the system can monitor the health status of elderly people in real time, provide appropriate medical treatment if an abnormality is detected, assist with the progress of procedures, and adapt the system's behavior according to the user's emotions.

[1525] (Application example 2)

[1526] 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."

[1527] Real-time health management for the elderly is important for prompt medical response. However, many elderly people have difficulty traveling to medical institutions and completing the appropriate procedures on their own. It is also difficult to constantly monitor the health status of elderly people remotely, and it is often impossible to respond quickly even if an abnormality occurs. Furthermore, there is concern that when elderly people and their families are under stress or anxiety, they may not understand or respond properly to procedures and information provision.

[1528] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for monitoring the elderly person's health condition in real time, means for detecting abnormal health conditions, means for automatically providing information on appropriate medical institutions and departments based on the detected abnormalities, means for issuing notifications to family members and care managers, means for automatically generating and providing necessary procedures and subsidy application flows, means for monitoring progress and sending reminders for incomplete procedures, means for linking with the autonomous vehicle's system and automatically guiding the user to the nearest hospital if an abnormality is detected, and means for analyzing the user's emotional state and adjusting the notification content and procedure flow. This allows the elderly person's health condition to be constantly monitored, and when an abnormality is detected, it is possible to quickly support transportation to a medical institution and necessary procedures. Furthermore, adjusting the method of providing notifications and procedures based on the emotional state reduces stress and anxiety for the elderly person and their family, and more appropriate and prompt responses are expected.

[1529] "Means for monitoring health status in real time" refers to devices or methods that continuously acquire the elderly person's physical vital signs and immediately transmit them to the system.

[1530] "Means for detecting abnormal health conditions" refers to devices or methods that analyze acquired vital data and compare it with reference values ​​to detect abnormalities.

[1531] The "means for automatically providing information about appropriate medical institutions and departments" refers to a device or method that automatically presents information about the appropriate medical institutions and departments based on the detected abnormality.

[1532] "Means for issuing notifications to family members or care managers" refers to a device or method that sends an alert to pre-registered contacts when an abnormality is detected.

[1533] "Means for automatically generating and providing necessary procedures and application flows for subsidy systems" refers to devices and methods that automatically organize and provide information on the procedures and subsidy systems required when elderly people receive medical care.

[1534] A "means for monitoring progress and sending reminders for outstanding procedures" is a device or method that tracks the progress of procedures and sends reminders for outstanding procedures.

[1535] "Means of working in conjunction with the system of an autonomous vehicle to automatically guide the vehicle to the nearest hospital when an abnormality is detected" refers to a device or method that automatically instructs an autonomous vehicle to head to the nearest hospital when an abnormality is detected in real time.

[1536] "Means for analyzing the user's emotional state and adjusting notification content and procedure flow" refers to a device or method that analyzes the user's facial expressions and voice to recognize emotions, and appropriately changes the notification content and procedure presentation method based on that.

[1537] This invention is a system for monitoring the health status of elderly people in real time and responding quickly when an abnormality is detected. Specific embodiments of this system will be described below.

[1538] System configuration

[1539] 1. Health monitoring

[1540] Wearable devices:

[1541] Various wearable devices (e.g., smartwatches) are used as terminals. These devices collect vital data such as the elderly's heart rate, blood pressure, and amount of exercise in real time and send this data to a server. For example, a smartwatch measures the user's heart rate and blood pressure every minute and sends the data to a cloud server.

[1542] 2. Anomaly detection and notification

[1543] server:

[1544] The server analyzes the received data and compares it with reference values ​​to detect any abnormalities. If an abnormality is detected, a notification is issued to the registered emergency contacts (family members or care managers). This notification also includes information on the appropriate medical institution and department to visit. For example, if the server detects an abnormal heart rate, it sends a notification stating "heart rate has risen sharply" and including the contact information of the nearest doctor.

[1545] 3. Collaboration with autonomous vehicles

[1546] Autonomous vehicles:

[1547] This system works in conjunction with the autonomous vehicle's system to automatically guide the elderly person to the nearest hospital if an abnormality is detected. For example, if an elderly person's heart rate shows an abnormal value, the autonomous vehicle will automatically set a route to the nearest hospital and begin moving.

[1548] 4. Assistance with admission procedures

[1549] server:

[1550] The server automatically generates and provides the necessary procedures and application flows for subsidy programs. This allows families to receive the information they need in real time after arriving at the hospital. For example, the "hospitalization procedure flow" provides a list of required documents and templates.

[1551] 5. Progress monitoring and reminders

[1552] Device:

[1553] As the procedure progresses, the progress is reported to the server, which records the progress in a database and sends reminders to the family members' devices about any incomplete procedures, helping them remember to complete them.

[1554] 6. Emotion recognition

[1555] Device:

[1556] The smartphones used by the elderly and their families are equipped with cameras and microphones that can be used to recognize the user's emotions in real time. For example, when a family member goes through a procedure, the camera analyzes their facial expressions to detect emotions such as anxiety or impatience.

[1557] 7. Emotion-Based Adjustment

[1558] server:

[1559] The emotion engine dynamically adjusts notification content and procedure flow based on emotional data analyzed. For example, if it recognizes that the user is feeling stressed, notification content will be displayed in more user-friendly language. The procedure flow will also be simplified and adjusted to require fewer steps.

[1560] Specific examples

[1561] Health monitoring and anomaly detection

[1562] For example, if an elderly person's heart rate exceeds a set threshold (usually less than 100 bpm), the server will detect this as an abnormality and send a notification to emergency contacts, including the message, "Your heart rate is rising rapidly. Please contact a medical institution."

[1563] Collaboration with autonomous vehicles

[1564] When an abnormality is detected, the autonomous vehicle immediately sets a route to the nearest medical facility and quickly transports the elderly person to the hospital. At this time, the necessary information for procedures and the application flow for subsidy programs are automatically generated and displayed on the smartphone.

[1565] Emotional Engine Adjustment

[1566] If the camera detects an anxious expression on a family member's face as they go through the admission procedures, the server will make the notification more friendly and display an encouraging message such as, "Don't worry, the procedure is going smoothly."

[1567] Prompt Sentence Examples

[1568] "If an elderly person's heart rate spikes or blood pressure rises while riding in an autonomous vehicle, please design a system that automatically guides the vehicle to the nearest hospital and sends an emergency alert to registered family members and medical institutions. Also, please include a function that displays the hospital admission procedure flow after the vehicle arrives, analyzes the elderly person's facial expressions with a camera to determine their stress level, and adjusts the content of the notification accordingly."

[1569] As a result, this invention can provide safe and appropriate medical support by monitoring the health status of elderly people in real time and responding quickly when abnormalities are detected.In addition, the introduction of an emotion engine reduces stress and anxiety for elderly people and their families, enabling smoother procedures.

[1570] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1571] Step 1:

[1572] Real-time acquisition of health data for the elderly

[1573] A wearable device collects real-time data on the elderly person's heart rate, blood pressure, and physical activity. This data is measured through sensors on the wearable device. The measured data is sent to a server via the device. The input data is vital signs such as heart rate and blood pressure, and the output is sensor data sent to the server.

[1574] Step 2:

[1575] Health data analysis and anomaly detection

[1576] The server receives data sent from the wearable device and analyzes it using an anomaly detection algorithm. Specifically, if the heart rate exceeds 150 bpm or the blood pressure exceeds 180 / 100, it is deemed to be abnormal. The input data is the vital signs data sent from the wearable device, and the output is the analysis result, such as "normal" or "abnormal."

[1577] Step 3:

[1578] Notification when an abnormality is detected

[1579] If the server detects an abnormality, it sends an emergency alert to registered family members and care managers. The notification also includes information on the appropriate medical institution and department to visit. The input is the abnormality detection result, and the output is a notification message sent to emergency contacts. Notifications are sent via email or SMS.

[1580] Step 4:

[1581] Autonomous vehicle routing

[1582] When the server detects an abnormality, it sends a command to the autonomous vehicle to set a route to the nearest hospital. The input is the abnormality detection and hospital information, and the output is route information sent to the autonomous vehicle. The vehicle's navigation system automatically sets the optimal route and begins moving.

[1583] Step 5:

[1584] Providing information on admission procedures

[1585] The server automatically generates the necessary procedures and application flow for subsidy programs, and sends them to the family's device. The input is a notification of arrival at the hospital, and the output is the procedure flow and a list or template of required documents. The family can then view this and proceed with the procedures.

[1586] Step 6:

[1587] Progress monitoring and reminders

[1588] As family members go through procedures, the device reports their progress to the server. The server records the progress in a database and sends reminders to family members' devices if there are any procedures that need to be completed. The input is the progress data of the procedures, and the output is reminder notifications.

[1589] Step 7:

[1590] Emotion recognition and notification content adjustment

[1591] The device uses a camera and microphone to recognize the emotional state of family members in real time. The server receives the emotional data analyzed using an emotion recognition engine. For example, if a family member shows an anxious expression, the notification content is made more friendly and an encouraging message is added if necessary. The input is the emotional data sent from the device, and the output is the adjusted notification content.

[1592] Through these steps, this system can monitor the health status of elderly people in real time and automatically take appropriate action when an abnormality is detected. It also reduces stress for family members and care managers and enables prompt and appropriate medical support.

[1593] 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.

[1594] 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.

[1595] 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.

[1596] [Fourth embodiment]

[1597] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1598] 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.

[1599] 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).

[1600] 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.

[1601] 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.

[1602] 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).

[1603] 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.

[1604] 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.

[1605] 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.

[1606] 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.

[1607] 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.

[1608] 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.

[1609] 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."

[1610] To implement this invention, it is necessary to prepare a wearable device for monitoring the health status of the elderly, a server for analyzing the data, and a terminal that links with the user and emergency contacts. Below, the overall processing flow of the system is explained in natural language.

[1611] 1. Real-time health monitoring

[1612] Device: A wearable device collects vital data such as heart rate, blood pressure, and exercise volume of elderly people in real time. The device is worn on the user's body and measures the data periodically.

[1613] Server: Receives vital data sent from the device and stores it in a database, allowing the health of the elderly to be constantly monitored.

[1614] 2. Data analysis and anomaly detection

[1615] Server: Analyzes the received vital signs and compares them with historical data and baseline values. Algorithms are applied to detect abnormal values ​​(e.g., sudden increases in heart rate or abnormal blood pressure fluctuations).

[1616] Server: Generates an alert if an anomaly is detected. This alert is issued if an immediate response is required.

[1617] 3. Notification and Instructions

[1618] Server: When an alert is generated, a notification is sent to registered emergency contacts (family members or care managers), along with information about the relevant medical institution and department.

[1619] Device: The device of the emergency contact (e.g., a smartphone) receives the notification and instructs the elderly person's family member via voice or text on the appropriate action to take. Specifically, the message "Please contact the nearest internal medicine clinic" is displayed.

[1620] 4. Aftercare support

[1621] Server: When an elderly person is hospitalized or admitted to a facility, information on related procedures is collected and the necessary procedures and application flows for subsidy programs are automatically generated.

[1622] Device: Based on this flow, messages are displayed to guide the family member in need of assistance through the procedure. Templates of the necessary documents are also provided, allowing the family member to efficiently complete the necessary procedures.

[1623] 5. Progress monitoring and reminders

[1624] Terminal: As the user goes through each procedure, the progress is reported to the server. The user inputs the progress of the procedure from a smartphone or tablet.

[1625] Server: Records the progress in a database and generates reminders for incomplete procedures and sends them to the user's device, for example, a message saying "This procedure is not yet complete."

[1626] Specific examples

[1627] Scenario 1: Elderly person A records a heart rate of 150 bpm and blood pressure of 180 / 100

[1628] Device: The smartwatch collects this data and sends it to the server.

[1629] Server: Detects an abnormal value and notifies family member B, who is the emergency contact, that "A's heart rate has suddenly increased. Please contact the nearest internal medicine clinic."

[1630] Device: A notification appears on Mr. B's smartphone, and he rushes to the internal medicine department with Mr. A.

[1631] Scenario 2: Person A is hospitalized and family member B completes the necessary procedures

[1632] Server: Receives information about hospitalization and generates the necessary procedures and application flow for subsidy programs.

[1633] Device: Display the procedure flow on Mr. B's smartphone, stating "Please follow the admission procedures in this order," along with a template of the necessary documents.

[1634] Server: Monitors the progress of the transaction and sends reminders for any outstanding transactions.

[1635] The above is a specific method for carrying out the present invention. This system allows elderly people and their families to receive prompt and appropriate medical treatment and aftercare.

[1636] The processing flow will be explained below.

[1637] Step 1: Collecting health data

[1638] Device: A wearable device collects vital data such as heart rate, blood pressure, and exercise volume in real time. The device is attached to the elderly person's body and measures the data periodically.

[1639] Step 2: Sending data

[1640] Terminal: Collected vital data is sent to the server. The data is encrypted and transmitted securely over the network.

[1641] Step 3: Receiving and storing data

[1642] Server: Receives the data sent from the device and stores it in a database, which also includes the elderly person's past health data.

[1643] Step 4: Analyze the data

[1644] Server: Analyzes the stored data, comparing it with historical data and baseline values ​​and applying algorithms to detect abnormal values ​​(e.g., sudden increases in heart rate or abnormal blood pressure fluctuations).

[1645] Step 5: Detect anomalies

[1646] Server: Generates an alert if an anomaly is detected that exceeds a certain threshold, for example, if the heart rate increases by more than 50% of normal.

[1647] Step 6: Generate notifications

[1648] Server: Based on the generated alert, the server issues a notification to registered emergency contacts (family members or care managers), and also provides information on appropriate medical institutions and departments to visit.

[1649] Step 7: Receiving and Viewing Notifications

[1650] Device: The emergency contact's device (e.g., smartphone) receives the notification. The device displays specific instructions to the family member via voice or text, such as "Please contact the nearest internal medicine doctor."

[1651] Step 8: Family response

[1652] User: Family members receive notifications and follow instructions to take the elderly to medical facilities. They act quickly based on specific instructions.

[1653] Step 9: Obtain admission information

[1654] Server: When an elderly person is hospitalized, the server receives information about the hospitalization from the medical institution and stores it in a database.

[1655] Step 10: Generate procedural flow

[1656] Server: Automatically generates procedures for hospitalization and application procedures for subsidy programs, including the required documents and procedure sequence.

[1657] Step 11: Notification of procedure flow

[1658] Server: Sends the generated procedure flow to the family member's device. The device displays instructions such as "Please follow the procedure at the hospital in this order."

[1659] Step 12: Provide documentation

[1660] Server: Sends templates of the necessary documents to the device so that family members can use them to complete the procedures.

[1661] Step 13: Record the progress of the procedure

[1662] Device: As the family member goes through each procedure, they report their progress to the server. For example, they can use their smartphone to press a button to complete the procedure.

[1663] Step 14: Monitoring progress

[1664] Server: Records progress in a database and generates reminders for incomplete procedures.

[1665] Step 15: Send a reminder

[1666] Server: Sends a reminder to the family member's device about the incomplete procedure. The device displays the message "This procedure is not yet completed."

[1667] Example 1

[1668] 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."

[1669] There is a need for a system that can constantly monitor the health status of elderly people, detect abnormalities, and provide appropriate medical care promptly. However, existing systems are unable to collect and analyze data in real time, making it difficult to quickly notify patients when an abnormality occurs or take appropriate action. In addition, there is no automated system for providing information about hospitalization and procedures, monitoring progress, or sending reminders. For these reasons, there is a need to provide a system that can efficiently and effectively manage the health of elderly people.

[1670] 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.

[1671] In this invention, the server includes: a means for monitoring health status in real time; a means for detecting abnormal health status; a means for automatically providing information on appropriate medical institutions and departments based on the detected abnormalities; a means for issuing notifications to emergency contacts; a means for automatically generating and providing necessary procedures and application flows for subsidy programs; a means for monitoring progress and sending reminders for incomplete procedures; a means for analyzing data stored on the server and using an algorithm to detect abnormal values; a means for using a secure protocol for data communication between the server and a terminal; and a means for sending voice or text notifications to emergency contacts. This allows for real-time monitoring of the health status of elderly people and enables prompt and appropriate response in the event of an abnormality. Furthermore, the provision of information on hospitalization and procedures, progress monitoring, and sending reminders are automated, reducing the burden on elderly people and their families.

[1672] "Real-time health monitoring" refers to the use of wearable devices to continuously collect personal physical data (e.g., heart rate, blood pressure, and exercise volume) and to analyze and manage that data in real time.

[1673] "Detecting abnormal health conditions" refers to identifying abnormal values ​​(e.g., sudden increases in heart rate or abnormal fluctuations in blood pressure) based on collected data and comparing them with baseline values ​​or past data.

[1674] "Automatically providing information about appropriate medical institutions and departments" means that when an abnormality is detected, information about the medical institution and department that is most suitable for the abnormality is automatically provided to the user.

[1675] "Issuing a notification to an emergency contact" means that if an abnormality is detected, a notification will be sent promptly to a pre-registered emergency contact (e.g., family member or care manager).

[1676] "Automatic generation of application flows for procedures and subsidy systems" means that the system automatically generates and provides application flows for procedures and subsidy systems that are necessary when elderly people are hospitalized or admitted to a facility.

[1677] "Progress monitoring" means tracking and managing the progress of each step of a user's procedure in real time.

[1678] "Sending reminders" means sending notifications or alerts to users when there are incomplete procedures or important steps.

[1679] An "algorithm for analyzing data and detecting outliers" is a program or mathematical method for identifying outliers based on collected data.

[1680] A "secure protocol for data communication between a server and a terminal" is a communication method (e.g., HTTPS, TLS) for securely transmitting data between a server and a terminal.

[1681] "Send voice and text notifications" refers to sending important messages to users in the form of voice alerts and text messages.

[1682] A "wearable device" is a small electronic device that can be worn on the body and collects physical data such as heart rate, blood pressure, and exercise volume.

[1683] A "server" is a computer on a network that stores and analyzes data, detects anomalies, and sends notifications.

[1684] A "terminal" is a device (e.g., a smartphone or tablet) that receives data from a server or wearable device and gives instructions to the user.

[1685] "Entering progress status" means that the user reports the progress of the procedure to the system using a smartphone or tablet.

[1686] "Procedure flow suggestions" means that the system automatically provides the order and methods of procedures that elderly people and their families should follow.

[1687] "Providing templates for required documents" means providing the user with formats for documents required to carry out the procedure.

[1688] MODE FOR CARRYING OUT THE INVENTION

[1689] To implement this invention, it is necessary to build a system that monitors the health status of elderly people in real time, detects abnormalities, and provides instructions on appropriate measures. Specifically, the following hardware and software are required:

[1690] System configuration

[1691] 1. Wearable devices

[1692] Device:

[1693] Wearable devices (e.g., health trackers, smartwatches) collect real-time vital data such as heart rate, blood pressure, and physical activity of elderly people. These devices can be worn on the body and transmit the data to a connected smartphone via Bluetooth or Wi-Fi.

[1694] 2. Smartphone (or tablet)

[1695] Device:

[1696] The smartphone receives data from the wearable device and sends it to a cloud server using a secure communication protocol (e.g., HTTPS).

[1697] 3. Cloud Server

[1698] server:

[1699] A cloud server (e.g., Amazon Web Services, Google Cloud) receives the vital data sent from the smartphone and stores it in a dedicated database (e.g., Amazon RDS, Firebase RealTime Database).

[1700] Data analysis and anomaly detection

[1701] server:

[1702] The received data is analyzed using an anomaly detection algorithm (e.g., machine learning model) created in Python or R. Anomalies are detected by comparing them with past data and reference values ​​(e.g., heart rate 60-100 bpm, blood pressure below 120 / 80).

[1703] Sending alerts and notifications

[1704] server:

[1705] If abnormal data is detected (e.g. heart rate 150 bpm, blood pressure 180 / 100), an alert is generated and a notification is sent to emergency contacts using Twilio or Firebase Notifications.

[1706] Device:

[1707] The smartphone of the emergency contact (e.g., family member or care manager) receives a notification and instructs the elderly person's family member on appropriate actions via voice notification or text message.

[1708] Automatic generation and support of procedures

[1709] server:

[1710] When an elderly person is hospitalized or admitted to a facility, information about the hospitalization is received and a Python script is used to automatically generate the necessary procedures and application flow for subsidy programs.

[1711] Device:

[1712] The system sends a notification to the emergency contact's smartphone explaining the procedure and provides templates for the necessary documents. For example, it includes specific instructions such as "Please follow this order when completing the admission procedures."

[1713] Progress monitoring and reminders

[1714] User:

[1715] As the emergency contact (family member) goes through the procedure, they enter the progress into the server via their smartphone.

[1716] server:

[1717] The entered progress is recorded in a database, and reminders are generated and sent to the user's device for any incomplete procedures, such as a "This procedure is not yet complete" reminder.

[1718] Specific examples

[1719] Scenario 1: Elderly person A records a heart rate of 150 bpm and blood pressure of 180 / 100

[1720] Device: The smartwatch collects this data and sends it to a cloud server via the smartphone.

[1721] Server: Detects an abnormal value and uses the Twilio API to notify the family member who is the emergency contact, saying, "Mr. A's heart rate has suddenly increased. Please contact the nearest internal medicine clinic."

[1722] Device: A notification appears on the family member's smartphone, and they rush to the internal medicine department with Mr. A.

[1723] Scenario 2: Person A is hospitalized and family member B completes the necessary procedures

[1724] Server: Receives information about hospitalization and generates procedures and application flows for subsidy programs.

[1725] Device: The family member's smartphone will be shown a procedure flow stating, "Please follow the admission procedures in this order," along with a template of the necessary documents.

[1726] Server: Monitors the progress of the transaction and sends reminders for any outstanding transactions.

[1727] Prompt Sentence Examples

[1728] "Write Python code to analyze heart rate and blood pressure data and detect outliers."

[1729] "How do I use the Twilio API to send an SMS in case of an error?"

[1730] This system allows elderly people and their families to receive prompt and appropriate medical response and aftercare.

[1731] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1732] Step 1:

[1733] Data collection

[1734] Device: A wearable device (e.g., a smartwatch) collects vital data such as heart rate, blood pressure, and activity level in real time. The device collects data every few seconds and transmits it to a connected smartphone via Bluetooth or Wi-Fi.

[1735] Input: Real-time vital data from biosensors.

[1736] Output: Collected vital data is sent to a smartphone.

[1737] Step 2:

[1738] Data transmission

[1739] Terminal: The smartphone receives data from the wearable device and sends it to the cloud server using a secure communication protocol (e.g., HTTPS).

[1740] Input: Vital data collected by the device.

[1741] Output: Vital data sent to cloud server via secure communication.

[1742] Step 3:

[1743] Data reception and storage

[1744] Server: A cloud server (e.g., AWS EC2) receives the vital data sent from the smartphone and stores it in a dedicated database (e.g., Amazon RDS).

[1745] Input: Vital data sent over secure communication.

[1746] Output: Vital data stored in a database.

[1747] Step 4:

[1748] Data analysis

[1749] Server: The received data is analyzed using an anomaly detection algorithm (e.g., machine learning model) created in Python or R. The data is compared with past vital signs and reference values ​​(e.g., heart rate 60-100 bpm, blood pressure below 120 / 80) to detect abnormal values.

[1750] Input: Saved vital data and baseline values, historical data.

[1751] Output: Information about detected outliers.

[1752] Step 5:

[1753] Alert Generation

[1754] Server: If abnormal data is detected (e.g., heart rate 150 bpm, blood pressure 180 / 100), a Python script generates an alert that explains what caused the abnormality and recommends corrective actions.

[1755] Input: Outlier information as an analysis result.

[1756] Output: Alert information.

[1757] Step 6:

[1758] Send notifications

[1759] Server: Based on the generated alert, a notification is sent to emergency contacts using Twilio or Firebase Notifications. The notification includes specific instructions such as "Your heart rate has increased dramatically. Please contact the nearest medical facility."

[1760] Input: The generated alert information.

[1761] Output: Notification message sent to emergency contacts.

[1762] Step 7:

[1763] Receive notifications

[1764] Device: The smartphone of the emergency contact (e.g., family member) receives the notification and instructs the elderly family member on appropriate actions via voice notification or text.

[1765] Input: The notification message sent by the server.

[1766] Output: Notification content displayed on the emergency contact's device.

[1767] Step 8:

[1768] Procedural flow generation

[1769] Server: When an elderly person is hospitalized or admitted to a facility, a Python script is used to automatically generate the necessary procedures and application flow for subsidy programs.

[1770] Input: Information about hospitalization and institutionalization.

[1771] Output: Generated procedure flow and subsidy application guide.

[1772] Step 9:

[1773] Procedure flow notification

[1774] Server: The generated procedure flow is sent to the smartphone of the emergency contact. The notification includes specific instructions such as "Please follow the admission procedure in this order."

[1775] Input: The generated procedure flow.

[1776] Output: The procedure flow sent to the emergency contact's device.

[1777] Step 10:

[1778] Entering the progress of procedures

[1779] User: As the emergency contact (family member) goes through each procedure, they enter the progress information into the server using their smartphone or tablet.

[1780] Input: Procedural progress.

[1781] Output: Progress data reported to the server.

[1782] Step 11:

[1783] Progress monitoring

[1784] Server: Records the entered progress in a database and monitors the progress of the procedure.

[1785] Input: User-reported progress data.

[1786] Output: Progress and monitoring results recorded in a database.

[1787] Step 12:

[1788] Generate and send reminders

[1789] Server: Generates reminders for incomplete procedures and sends them to the user's device. For example, it sends a reminder notification saying "This procedure has not yet been completed."

[1790] Input: Progress data and open procedure information.

[1791] Output: The reminder notification sent to the user's device.

[1792] (Application example 1)

[1793] 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."

[1794] Real-time monitoring of the health status of elderly people and early detection of abnormalities are important challenges for families and care managers. Rapid and accurate responses are also required when abnormalities are detected. Furthermore, there is a need to streamline procedures for post-health abnormality procedures and applications for subsidies, and to appropriately manage progress. However, conventional systems have had difficulty fully meeting these requirements.

[1795] 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.

[1796] In this invention, the server includes a means for collecting and analyzing vital data from the wearable device using a smartphone and smart glasses, detecting abnormalities and sending notifications, a means for acquiring data such as the elderly person's heart rate, blood pressure, and amount of exercise using the wearable device and sending it to the server via the smartphone and smart glasses, and a means for providing templates for required documents based on a proposed procedure flow and sending incomplete reminders, thereby enabling early detection of abnormalities and rapid response, efficient procedure support, and appropriate progress management.

[1797] Here are the definitions:

[1798] "Health status of the elderly" refers to vital data such as the elderly's heart rate, blood pressure, and amount of exercise.

[1799] "Means of real-time monitoring" refers to a system that uses wearable devices to continuously collect vital data and send it to a server, allowing the data to be checked immediately.

[1800] "Means for detecting abnormal health conditions" refers to algorithms that analyze collected vital data and compare it with baseline values ​​to detect abnormal values.

[1801] "Means for automatically providing information about appropriate medical institutions and departments" refers to a system that provides data about the nearest appropriate medical institutions and departments based on detected abnormalities.

[1802] "Means of issuing notifications to family members or care managers" refers to a notification mechanism that sends an alert to emergency contacts when an abnormality is detected.

[1803] "Means for automatically generating and providing application flows for procedures and subsidy programs" refers to the function of automatically generating and providing information regarding procedures and applications for subsidy programs that are necessary when an elderly person is hospitalized, for example.

[1804] "Means for monitoring progress and sending reminders for incomplete procedures" refers to a system that monitors the progress of procedures and sends reminder notifications for incomplete procedures.

[1805] "Smartphones and smart glasses" refer to portable devices that receive, analyze, and notify data from wearable devices.

[1806] A "wearable device" refers to a device that is worn on the body and continuously collects vital data.

[1807] "Means for collecting and analyzing data, detecting abnormalities, and notifying" refers to a system that collects vital data from wearable devices, analyzes it on a server to detect abnormalities, and sends notifications to emergency contacts.

[1808] In order to implement the present invention, the following hardware and software are used.

[1809] Hardware:

[1810] 1. Wearable devices: Devices that collect vital data such as heart rate, blood pressure, and physical activity of elderly people. These devices include, for example, smart watches and fitness trackers.

[1811] 2. Smartphones and smart glasses: These devices are used to receive data collected from wearable devices and send it to the server. Smartphones are used to run applications and display notifications. Smart glasses are also used to display data and receive notifications.

[1812] 3. Server: A server that receives and analyzes data from wearable devices.

[1813] software:

[1814] 1. Data collection and transmission program: A program for collecting data from wearable devices and transmitting it to a server through smartphones and smart glasses.

[1815] 2. Data analysis program: A program that analyzes vital data on the server and detects abnormalities. For example, it can be implemented using Python or R.

[1816] 3. Notification program: This program sends an alert to emergency contacts when an abnormality is detected. This program uses RESTful APIs or Firebase Cloud Messaging (FCM) to send notifications.

[1817] 4. Procedure flow provision and reminder program: This program automatically generates information regarding procedures after a health abnormality and applications for subsidies, and reminds users of incomplete procedures.

[1818] Process flow:

[1819] 1. Data collection: The wearable device periodically measures the elderly person's heart rate, blood pressure, and physical activity, and transmits the data to a smartphone and smart glasses.

[1820] 2. Data transmission: The smartphone and smart glasses transmit the received vital data to the server via Bluetooth.

[1821] 3. Data analysis: The server analyzes the received vital data and compares it with baseline values ​​to detect abnormalities. Machine learning algorithms and rule-based analysis methods are used for the analysis.

[1822] 4. Anomaly detection and notification: If an anomaly is detected, the server will send an alert to emergency contacts, notifying them of the abnormal data and recommending a course of action (e.g., "Contact your local internal medicine doctor").

[1823] 5. Providing procedure flow and reminders: When an elderly person is hospitalized, the server automatically generates a procedure flow and a template of the necessary documents and sends them to the smartphone or smart glasses. It also monitors the progress and sends reminder notifications if the procedure is incomplete.

[1824] Examples:

[1825] Scenario 1:

[1826] When an elderly person's heart rate reaches 150 bpm and blood pressure reaches 180 / 100, the server detects the abnormality and sends an alert to the smartphone and smart glasses saying, "Your heart rate has suddenly increased. Please contact your internal medicine doctor."

[1827] Scenario 2:

[1828] When an elderly person is hospitalized and their family members are completing the necessary procedures, the server generates a procedure flow and a template of the necessary documents, and displays it on the family members' smartphones and smart glasses, telling them to "proceed with the procedures in this order." It also reminds them of any incomplete procedures.

[1829] Example of a generative AI model prompt:

[1830] Example prompt:

[1831] We built a system to monitor the health of elderly people. The system collects and analyzes data from wearable devices in real time and sends notifications to emergency contacts if an abnormality is detected. We used Python and RESTful APIs to implement the processes for data transmission, anomaly detection, and notification generation.

[1832] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1833] Step 1:

[1834] Data collection

[1835] Input: A wearable device (e.g., a smartwatch) collects vital data such as an elderly person's heart rate, blood pressure, and activity level.

[1836] How it works: Measures vital signs at regular intervals and syncs the data with your smartphone and smart glasses.

[1837] Output: The measured vital data is sent to a smartphone and smart glasses.

[1838] Step 2:

[1839] Data transmission

[1840] Input: Vital data received from a wearable device.

[1841] How it works: The smartphone and smart glasses transmit the vital data they receive via Bluetooth to a server.

[1842] Output: Vital data arrives at the server.

[1843] Step 3:

[1844] Data analysis

[1845] Input: Vital data sent to the server.

[1846] How it works: The server uses programs such as Python to analyze vital data. The data is compared with known normal values ​​and calculations are performed to detect abnormalities.

[1847] Output: If an anomaly is detected, the type of anomaly and the anomaly detection result are generated. If no anomaly is detected, the analysis result is stored.

[1848] Step 4:

[1849] Anomaly detection and notification

[1850] Input: Anomaly detection results generated by data analysis.

[1851] How it works: The server generates and sends alerts to emergency contacts based on the anomaly detection results. Alerts are sent using RESTful APIs and Firebase Cloud Messaging (FCM).

[1852] Output: An alert is sent to emergency contacts and a notification is displayed on the smartphone and smart glasses.

[1853] Step 5:

[1854] Procedural flow provided

[1855] Input: Elderly person's admission information and related procedure information.

[1856] Operation: The server automatically generates the steps required for a target procedure such as hospitalization and prepares templates for the necessary documents.

[1857] Output: The procedure flow and templates of required documents are sent to the smartphone and smart glasses.

[1858] Step 6:

[1859] Reminder generation

[1860] Input: Procedural progress data entered by the user.

[1861] Behavior: The server monitors the progress of procedures and generates reminders for incomplete procedures. Reminders are generated based on progress data.

[1862] Output: Reminders for outstanding procedures are sent to the user's smartphone and smart glasses.

[1863] (Example prompt):

[1864] "We built a system to monitor the health of elderly people. The system collects and analyzes data from wearable devices in real time, and sends notifications to emergency contacts if an abnormality is detected. We used Python and RESTful APIs to implement the processes for data transmission, anomaly detection, and notification generation."

[1865] 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.

[1866] This system monitors the health status of elderly people in real time, and when abnormalities are detected, it provides information on appropriate medical institutions and departments and issues notifications to family members and care managers. It also automatically generates procedures for post-hospitalization and facility admission, as well as application flows for subsidy programs, and monitors progress to send reminders for incomplete procedures. Furthermore, by combining it with an emotion engine that recognizes user emotions, it can automatically adjust the content of notifications and the presentation method of the procedure flow.

[1867] System configuration

[1868] 1. Health monitoring

[1869] Device: A wearable device collects vital data such as heart rate, blood pressure, and exercise volume of elderly people in real time. It is worn on the user's body and measures the data periodically.

[1870] Server: Receives vital data sent from the device and stores it in a database. This data is analyzed and generates an alert if an abnormality is detected.

[1871] 2. Anomaly detection and notification

[1872] Server: Analyzes the received data and compares it with the reference values. If an abnormal value is detected, a notification is sent to the registered emergency contacts. The notification also includes information on the appropriate medical institution and department to visit.

[1873] Device: The emergency contact's device will receive a notification and display voice and text instructions, allowing for a quick response.

[1874] 3. Assistance with admission procedures

[1875] Server: When an elderly person is hospitalized, the necessary procedures and application flow for subsidy programs are automatically generated. This information is sent to the family's device, and the procedure order and templates for the necessary documents are provided.

[1876] Device: The procedure flow is displayed on the family member's device, helping the user to complete the procedure easily.

[1877] 4. Progress monitoring and reminders

[1878] The device reports its progress to the server as it processes the transaction, which records the progress in a database and sends reminders about any outstanding transactions.

[1879] Server: Monitors the progress of procedures and sends reminders to family members' devices about incomplete procedures, helping them remember to complete them.

[1880] Combining Emotion Engines

[1881] 5. Emotion recognition

[1882] Device: Using sensors such as cameras and microphones, the device recognizes the user's emotions in real time, analyzing facial expressions and tone of voice to detect emotional states.

[1883] Server: Receives emotional data analyzed by the emotion engine and adjusts the notification content and procedure flow presentation method based on this data. For example, if the user is feeling stressed, the notification will be more friendly and the procedure flow will be more concise.

[1884] 6. Emotion-Based Regulation

[1885] Server: Based on the user's emotional state detected by the emotion engine, the server dynamically adjusts the content of notifications and the way procedural flow is presented, making it easier for users to understand and reducing stress.

[1886] Device: Display tailored notifications and procedural flows on the user's device, for example adding encouraging messages if the user is feeling anxious.

[1887] Specific examples

[1888] Health monitoring and anomaly detection

[1889] Scenario: Elderly person A's heart rate is 150 bpm and blood pressure is 180 / 100.

[1890] Device: The smartwatch collects this data and sends it to the server.

[1891] Server: Detects an abnormality and notifies emergency contacts, saying, "Mr. A's heart rate has suddenly increased. Please contact the nearest internal medicine clinic."

[1892] Device: A notification appears on the emergency contact's smartphone, and family member B takes person A to the internal medicine clinic.

[1893] Assistance with admission procedures

[1894] Scenario: Person A is hospitalized and family member B completes the necessary procedures.

[1895] Server: Collects information about hospitalization and automatically generates procedural flow.

[1896] Device: Mr. B's smartphone displays instructions such as "Please complete the admission procedures in this order," and also provides templates for the necessary documents.

[1897] Emotional Engine Adjustment

[1898] Scenario: When B is going through the procedure, the camera detects an anxious expression on B's face.

[1899] Device: The camera analyzes Mr. B's facial expression and sends his stress level to the emotion engine.

[1900] Server: Receives emotion data, simplifies the process, and adds encouraging messages.

[1901] Device: The adjusted procedure flow is displayed on Mr. B's smartphone, making it easier to proceed with the procedure.

[1902] The above is a specific method for implementing the present invention. This system enables elderly people and their families to receive prompt and appropriate medical treatment and aftercare, and furthermore, the emotional engine provides support to reduce stress and anxiety in users.

[1903] The processing flow will be explained below.

[1904] This system monitors the health status of elderly people in real time, and when abnormalities are detected, it provides information on appropriate medical institutions and departments and issues notifications to family members and care managers. It also automatically generates procedures for post-hospitalization and facility admission, as well as application flows for subsidy programs, and monitors progress to send reminders for incomplete procedures. Furthermore, by combining it with an emotion engine that recognizes user emotions, it can automatically adjust the content of notifications and the presentation method of the procedure flow.

[1905] System processing steps

[1906] 1. Real-time health monitoring

[1907] Step 1:

[1908] Device: Wearable devices (e.g., smartwatches) collect vital data such as heart rate, blood pressure, and exercise volume in real time. The device is worn on the user's body and measures data every second.

[1909] Step 2:

[1910] Terminal: Sends collected vital data to the server. The data is encrypted and sent over the network using a secure protocol.

[1911] Step 3:

[1912] Server: Receives data sent from the device and stores it in a real-time database. The stored data is immediately available for analysis.

[1913] 2. Data analysis and anomaly detection

[1914] Step 4:

[1915] Server: Analyzes the received vital data. It compares it with past data and preset reference values ​​and uses algorithms to detect abnormalities. For example, if the heart rate rises by more than 50% of normal.

[1916] Step 5:

[1917] Server: Generates an alert when an anomaly is detected. The alert includes details of the anomaly (e.g., a sudden increase in heart rate).

[1918] 3. Issuing and Receiving Emergency Notifications

[1919] Step 6:

[1920] Server: Based on the generated alert, the server issues a notification to registered emergency contacts (family members or care managers), including information on the appropriate medical institution and department.

[1921] Step 7:

[1922] Device: The emergency contact's device (e.g., smartphone) receives the notification, which may include a voice notification or a text message with specific instructions, such as "Contact your nearest internal medicine doctor."

[1923] 4. Incorporating and adjusting the emotional engine

[1924] Step 8:

[1925] Device: Uses a camera and microphone to collect the user's facial expressions and tone of voice in real time. Example: Analyzing emotional state from facial expressions.

[1926] Step 9:

[1927] Server: The emotion engine analyzes the collected data and determines the user's emotional state (e.g., anxiety, stress, relief).

[1928] Step 10:

[1929] Server: Based on the analysis results of the emotion engine, the server automatically adjusts the notification content and the way the procedure flow is presented. If the user is anxious, the server makes the notification content more user-friendly and simplifies the procedure flow.

[1930] Step 11:

[1931] Device: Display tailored notifications and procedural flows on the user's device. For example, display encouraging messages or simple instructions to a user who is feeling anxious.

[1932] 5. Assist with admission procedures and monitor progress

[1933] Step 12:

[1934] Server: When an elderly person is hospitalized, the server receives information about the hospitalization from the medical institution and stores it in a database.

[1935] Step 13:

[1936] Server: Automatically generates the procedures required to support hospital admission procedures and application flows for subsidy programs, including the required documents and procedure sequence.

[1937] Step 14:

[1938] Device: The procedure flow and templates for required documents are displayed on the family member's device (e.g., smartphone). For example, instructions such as "Please complete the admission procedures in this order" are displayed.

[1939] Step 15:

[1940] Device: As family members go through the process, they report their progress to the server. Progress is recorded manually or automatically.

[1941] Step 16:

[1942] Server: Monitors progress in real time and generates reminders for incomplete procedures.

[1943] Step 17:

[1944] Devices: Reminders are sent to family members' devices about incomplete transactions, such as the message "This transaction is not yet complete."

[1945] Specific examples

[1946] Scenario 1: Health monitoring and anomaly detection

[1947] If elderly person A's heart rate is recorded as 150 bpm and blood pressure as 180 / 100, the following steps are executed:

[1948] Device: The smartwatch collects this data and sends it to the server.

[1949] Server: Detects an abnormality and notifies emergency contacts, saying, "Mr. A's heart rate has suddenly increased. Please contact the nearest internal medicine clinic."

[1950] Device: A notification appears on the emergency contact's smartphone, and family member B takes person A to the internal medicine clinic.

[1951] Scenario 2: Assistance with admission procedures

[1952] When Person A is admitted to the hospital and Family Member B makes the necessary arrangements, the following steps are taken:

[1953] Server: Collects information about hospitalization and sends an automatically generated procedure flow to the family's device.

[1954] Device: Mr. B's smartphone displays instructions such as "Please complete the admission procedures in this order," and also provides templates for the necessary documents.

[1955] Scenario 3: Emotion Engine Regulation

[1956] If the camera detects an anxious expression on Mr. B's face as he goes through the process, the next step is executed.

[1957] Device: The camera analyzes Mr. B's facial expression and sends his stress level to the emotion engine.

[1958] Server: Receives emotion data, simplifies the process, and adds encouraging messages.

[1959] Device: The adjusted procedure flow is displayed on Mr. B's smartphone, making it easier to proceed with the procedure.

[1960] The above is a specific method for implementing the present invention. This system enables elderly people and their families to receive prompt and appropriate medical treatment and aftercare, and furthermore, the emotional engine provides support to reduce stress and anxiety in users.

[1961] Example 2

[1962] 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."

[1963] The challenge is to monitor the health status of elderly people in real time and provide prompt and appropriate medical treatment when abnormalities occur. It is also necessary to reduce incomplete procedures by managing the progress of procedures and sending necessary reminders. Furthermore, it is required to reduce stress and anxiety by adjusting notification content and procedure flow according to the user's emotional state.

[1964] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for monitoring the health condition of the elderly person in real time, means for detecting abnormal health conditions, means for automatically providing information on appropriate medical institutions and departments to visit based on the detected abnormalities, means for issuing notifications to family members and care managers, means for automatically generating and providing necessary procedures and application flows for subsidy programs, means for monitoring progress and sending reminders for incomplete procedures, and means for adjusting the notification content and the presentation method of the procedure flow using an emotion engine that recognizes the user's emotions. This makes it possible to monitor the health condition of the elderl...

Claims

1. a means of monitoring the health status of elderly people in real time; a means for detecting abnormal health conditions; A means for automatically providing information about appropriate medical institutions and departments based on detected abnormalities; A means of issuing notices to family members and care managers; A means to automatically generate and provide the necessary procedures and application flows for subsidy programs, A means to monitor progress and send reminders about outstanding procedures; A system including:

2. The system according to claim 1, further comprising means for acquiring data such as the elderly person's heart rate, blood pressure, and amount of exercise using a wearable device and transmitting the data to a server.

3. The system of claim 1 further comprising means for providing templates of required documents based on the proposed procedure flow.

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