System

Abstract

A system is provided.SOLUTION: A system comprising: means for obtaining physiological information from a user; means for converting the obtained physiological information into digital form for transmission; means for receiving and storing the transmitted physiological information; means for analyzing the stored physiological information to generate a primary diagnosis; and means for notifying a physician of the primary diagnosis.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] The purpose of this invention is to solve the problem of declining medical services due to a shortage of doctors in rural areas. In particular, it aims to provide a system that reduces the burden on medical institutions and detects abnormalities early by supporting daily health management for the elderly and single-person households. Another objective is to create an environment in which doctors can quickly and accurately grasp the patient's condition and prioritize necessary medical treatment. [Means for solving the problem]

[0005] The present invention provides the following means:

[0006] means for acquiring physiological information from a user;

[0007] means for converting the acquired physiological information into a digital format and transmitting the digital information;

[0008] means for receiving and storing the transmitted physiological information;

[0009] means for analyzing the accumulated physiological information and generating a primary diagnosis result;

[0010] The system includes a means for notifying a physician of the results of the primary examination.

[0011] The means for acquiring physiological information from the user includes a smart watch, a blood pressure monitor, or a thermometer, and the means for generating the primary examination results uses an analysis algorithm to detect abnormal values ​​in blood pressure and heart rate, and can promptly notify a doctor when an abnormality is detected. This system can strengthen health management for the elderly and single-person households, and effectively solve the problem of a shortage of doctors in rural areas.

[0012] "User" refers to an individual who uses the system, and in particular, refers to a person who provides physiological information.

[0013] "Physiological information" refers to data that indicates the user's physical condition, and specifically refers to vital data such as heart rate, blood pressure, and body temperature.

[0014] "Means for acquiring" refers to the devices and methods used to collect physiological information from the user.

[0015] "Means for converting to digital form and transmitting" means the functions and technologies for electronically processing physiological information and transmitting it over a network.

[0016] "Means for receiving and storing" refers to the technology or method for receiving transmitted digital physiological information and storing it in a database, etc.

[0017] "Means for analyzing" refers to an algorithm or processing system for analyzing the received physiological information and identifying abnormal values ​​or patterns.

[0018] "Means for generating primary diagnostic results" means functions and technologies for generating diagnostic results based on the results of analyzing physiological information.

[0019] "Means of notification" refers to communication means or notification systems for informing doctors of the generated primary examination results.

[0020] A "smartwatch" is a wristwatch-type wearable device that is a digital device with the ability to measure physiological information such as heart rate and body temperature.

[0021] A "sphygmomanometer" is a medical device used to measure a user's blood pressure.

[0022] A "thermometer" is a medical device used to measure a user's body temperature.

[0023] "Analysis algorithm" refers to a computational method or program for processing and analyzing physiological information.

[0024] An "abnormal value" is a value that exceeds a predetermined normal range and is an indicator of the possibility of an abnormality in health status.

[0025] "Physician" refers to a person who is a medical professional and qualified to diagnose and treat patients. [Brief explanation of the drawings]

[0026] [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

[0027] 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.

[0028] First, the terms used in the following description will be explained.

[0029] 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).

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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."

[0034] [First embodiment]

[0035] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0036] 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.

[0037] 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).

[0038] 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.

[0039] 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.

[0040] 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.

[0041] 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.

[0042] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0043] 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.

[0044] 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.

[0045] 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.

[0046] 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."

[0047] As an embodiment of the present invention, the following system is provided.

[0048] System Overview

[0049] The system of the present invention manages the health of elderly people and single-person households, obtaining physiological information (e.g., heart rate, blood pressure, body temperature, etc.) from users and providing this information to medical institutions to support home medical care.

[0050] Device behavior

[0051] The devices consist of a smartwatch worn by the user, a blood pressure monitor, a thermometer, etc. These devices periodically collect the user's daily physiological information. The collected data is converted into digital format and sent to a server via the Internet. For example, a smartwatch collects and transmits data such as the user's heart rate, blood pressure, and body temperature at 9:00 a.m. every day.

[0052] Server Operation

[0053] The server receives the physiological information sent from the device and stores it in a database. This database stores information for long-term monitoring of the user's health. The received data is analyzed, and if abnormal values ​​are detected, a primary diagnosis result is generated.

[0054] If the analysis detects an abnormal value, such as blood pressure exceeding 140, the server generates a primary diagnosis result such as "Warning: Abnormal vital signs have been detected." If the value is normal, the server generates a diagnosis result such as "All vital signs are normal."

[0055] Notify your doctor

[0056] The server notifies the doctor of the generated primary examination results and physiological information. This notification is sent via a notification system dedicated to doctors and includes the patient ID, physiological information, and details of the primary examination results. This notification allows doctors to quickly identify patients who require attention and prioritize their examinations.

[0057] Specific examples

[0058] Consider a case where user A is wearing a smartwatch. The smartwatch measures A's heart rate (80 bpm), blood pressure (150 / 95 mmHg), and body temperature (36.8°C) at 9:00 a.m. This data is automatically sent to the server.

[0059] The server stores and analyzes the received data. In this case, the blood pressure is abnormal (150 / 95 mmHg), so it generates a primary examination result stating "Warning: Abnormal vital signs detected." It then notifies the doctor of this result and the physiological information. The doctor receives this notification, checks Mr. A's condition, and takes the necessary measures promptly.

[0060] Results and Effects

[0061] This system allows doctors to monitor patients' health conditions in real time, enabling prompt medical examinations. It also allows users to easily manage their health at home, reducing the burden on medical institutions. This effectively solves the issues of doctor shortages and declining medical functions in rural areas.

[0062] The processing flow will be explained below.

[0063] Step 1:

[0064] The device collects physiological information from the user. Devices such as smartwatches worn by the user, blood pressure monitors, and thermometers used by the user periodically measure data such as heart rate, blood pressure, and body temperature.

[0065] Step 2:

[0066] The device converts the collected physiological information into a digital format. Software installed in devices such as smartwatches and blood pressure monitors converts the measurement data into a digital format, such as JSON.

[0067] Step 3:

[0068] The device then sends the converted digital data to a server over the Internet, specifically by using an HTTP POST request to send the data to a pre-configured server URL.

[0069] Step 4:

[0070] The server receives the digital data sent from the device. An API endpoint is set up on the server side, and this endpoint receives a POST request from the device.

[0071] Step 5:

[0072] The server stores the received digital data in a database. Specifically, it uses a database management system (DBMS) to store new measurement data for each user.

[0073] Step 6:

[0074] The server analyzes the accumulated data and detects abnormalities. Based on the analysis algorithm, it evaluates whether there are any abnormal values, such as blood pressure exceeding 140 or heart rate exceeding 100.

[0075] Step 7:

[0076] The server generates a primary diagnosis result based on the analysis results. If an abnormal value is detected, a warning message is generated, and if the value is normal, a diagnosis result stating "All vital signs are normal" is generated.

[0077] Step 8:

[0078] The server notifies the doctor of the initial examination results and physiological information by issuing an API request to a notification system dedicated to doctors and sending a notification including the patient ID, analysis results, physiological information, etc.

[0079] Step 9:

[0080] Doctors receive notifications from the server and check for abnormalities in patients, enabling them to respond quickly and prioritize patients who need medical attention.

[0081] Example 1

[0082] 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."

[0083] Health management for the elderly and single-person households requires a system that allows users to accurately and quickly grasp their own health status while at home and respond quickly when abnormalities occur. However, conventional systems often collect and analyze physiological information manually, making it difficult to respond quickly. In addition, there is a problem that doctors have difficulty understanding patients' conditions in real time due to insufficient collaboration with medical institutions.

[0084] 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.

[0085] In this invention, the server includes means for acquiring physiological information from a user, means for converting the acquired physiological information into digital format and transmitting it, means for receiving the transmitted physiological information and storing it in a database, means for analyzing the stored physiological information and automatically detecting abnormal values, means for generating a primary examination result based on the analysis result, and means for notifying a doctor of the primary examination result and the physiological information. This allows the physiological information collected by a user at home to be automatically analyzed, and if an abnormality is detected, the doctor will be promptly notified. This allows the doctor to grasp the patient's health condition in real time and to diagnose and respond promptly.

[0086] "User" refers to an individual who uses the service and is the subject of physiological information collection.

[0087] "Physiological information" refers to data that indicates the user's health condition, such as heart rate, blood pressure, and body temperature.

[0088] "Digital format" refers to a format in which physiological information is stored and transmitted electronically.

[0089] "Transmitting means" refers to the technical means for transferring the acquired physiological information in digital form to the server.

[0090] "Server" refers to a computer system that receives, stores, analyzes, and notifies data.

[0091] "Database" refers to a system for storing received physiological information as structured data.

[0092] "Means for analyzing" refers to the technical means for analyzing the accumulated physiological information and detecting abnormal values.

[0093] "Primary examination results" refers to initial diagnostic information regarding the user's health condition obtained through analysis.

[0094] "Means of notification" refers to the technical means for communicating the results of the primary examination and physiological information to the physician.

[0095] An "abnormal value" refers to a value of physiological information that deviates from a set normal range.

[0096] A "smartwatch" refers to a wearable device that periodically collects and transmits physiological information about the user.

[0097] A "sphygmomanometer" refers to a device that measures a user's blood pressure and acquires the data.

[0098] A "thermometer" refers to a device that measures a user's body temperature and acquires that data.

[0099] MODE FOR CARRYING OUT THE INVENTION

[0100] Overall system overview

[0101] The system of this invention supports home medical care by acquiring physiological information from elderly people and single-person households, appropriately analyzing it, and providing it to medical institutions. The system consists of a terminal worn by the user, a server that receives and analyzes the data, and a means for notifying doctors.

[0102] Device behavior

[0103] The terminals used include devices such as smartwatches, blood pressure monitors, and thermometers. These terminals automatically measure the user's physiological information (heart rate, blood pressure, body temperature, etc.) at regular intervals. The measured data is converted into digital format in real time and sent to a server via the Internet. For example, a smartwatch obtains and sends the following information every day at 9:00 AM:

[0104] Heart rate: 80 bpm

[0105] Blood pressure: 150 / 95 mmHg

[0106] Body temperature: 36.8℃

[0107] Server Operation

[0108] The server receives the physiological information sent from the device and stores it in a database. The database accumulates the user's health status over time, including past measurement data. This accumulated data is automatically analyzed using data analysis libraries such as Python and Pandas. During the analysis process, abnormal values ​​are detected based on a set algorithm.

[0109] Specifically, the received data is screened, and when abnormal values ​​are detected, such as blood pressure exceeding 140 / 90 mmHg, it is determined to be abnormal. Based on this determination, a primary medical examination result is generated. The following medical examination results are generated:

[0110] "Warning: Abnormal vital signs detected."

[0111] "All vital signs are normal."

[0112] Notify your doctor

[0113] The generated primary examination results and the user's physiological information are communicated to the doctor via a dedicated notification system. The notification includes the following information:

[0114] patient ID

[0115] Heart rate

[0116] blood pressure

[0117] body temperature

[0118] Examination results

[0119] For example, the following notification will be given:

[0120] Patient ID: UserA

[0121] Heart rate: 80 bpm

[0122] Blood pressure: 150 / 95 mmHg

[0123] Body temperature: 36.8℃

[0124] Examination results: Warning: Abnormal vital signs detected

[0125] Deployment Examples and Real-World Usage Scenarios

[0126] Consider the case where user A is wearing a smartwatch. The smartwatch measures A's heart rate (80 bpm), blood pressure (150 / 95 mmHg), and body temperature (36.8°C) at 9:00 a.m. and automatically sends this data to the server. The server accumulates and analyzes the data. In this case, because the blood pressure is abnormal (150 / 95 mmHg), the server generates a primary examination result stating "Warning: Abnormal vital signs detected" and notifies the doctor along with A's physiological information. The doctor receives this notification, checks A's condition, and takes any necessary measures promptly.

[0127] Prompt Sentence Examples

[0128] "Please explain the health care system for the elderly. Please be specific about which devices collect what data, how that data is analyzed on the server, and how the doctor is notified. Also, please give specific examples of users."

[0129] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0130] Step 1: The user wears a device such as a smartwatch, blood pressure monitor, or thermometer to collect physiological information. The input is physiological data such as the user's heart rate, blood pressure, and body temperature. The output is this data converted into digital form. For example, the smartwatch measures the user's heart rate as 80 bpm, blood pressure as 150 / 95 mmHg, and body temperature as 36.8°C.

[0131] Step 2: The device converts the acquired physiological information into a digital format and sends it to a server via the Internet. The input is the digitized physiological data. The output is the data sent to the server via the Internet. For example, a smartwatch sends the measured values ​​to the server as packet data.

[0132] Step 3: The server receives the physiological information sent from the device and stores it in a database. The input is the physiological data sent from the device. The output is the physiological data stored in the database. For example, the server saves the data received in an SQL database.

[0133] Step 4: The server analyzes the accumulated data. The input is the physiological data stored in the database. The output is the analysis results. This analysis uses Python and the Pandas library to detect outliers. For example, the server analyzes the accumulated blood pressure data and extracts outliers where the blood pressure exceeds 140 / 90 mmHg.

[0134] Step 5: The server generates a primary medical examination result based on the analysis result. The input is the analysis result. The output is the primary medical examination result. For example, if the blood pressure is abnormal (150 / 95 mmHg), the server generates a medical examination result saying "Warning: Abnormal vital signs detected."

[0135] Step 6: The server notifies the doctor of the generated primary examination results and the user's physiological information. The input is the primary examination results and physiological data. The output is the notification sent to the doctor. For example, a notification such as "Patient ID: UserA, Heart rate: 80 bpm, Blood pressure: 150 / 95 mmHg, Body temperature: 36.8℃, Examination results: Warning: Abnormal vital signs detected" is sent to the doctor.

[0136] (Application example 1)

[0137] 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."

[0138] The purpose of this invention is to improve the quality of home medical care for the elderly and single-person households, while also reducing the burden on doctors. In particular, it is important to provide a rapid response to sudden changes in health conditions and to implement comprehensive safety measures in cooperation with security services.

[0139] 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.

[0140] In this invention, the server includes a means for acquiring physiological information from a user, a means for converting the acquired physiological information into a digital format and transmitting it, a means for receiving and storing the transmitted physiological information, a means for analyzing the stored physiological information and generating a primary examination result, and a means for notifying a doctor and a security service of the primary examination result. This makes it possible to grasp changes in the health status of elderly people and single-person households in real time and take prompt and appropriate measures if necessary. Furthermore, by linking with a security service, it is possible to ensure the overall safety of elderly people and single-person households.

[0141] "Means for acquiring physiological information from a user" refers to means for collecting physiological data such as heart rate, blood pressure, and body temperature through a device worn or used by the user.

[0142] The "means for converting the acquired physiological information into a digital format and transmitting it" refers to a means for converting the collected physiological data into digital data and transmitting it to a server.

[0143] The "means for receiving and storing the transmitted physiological information" refers to a means for receiving the transmitted digital data on the server side and storing it in a database or the like.

[0144] The "means for analyzing the accumulated physiological information and generating initial examination results" refers to a means for detecting abnormal values ​​in the data using an algorithm that analyzes the stored physiological data and generates initial examination results.

[0145] The "means for notifying the doctor and security service of the primary examination results" refers to a means for notifying the doctor and, if necessary, the security service of the generated primary examination results.

[0146] This invention is a system that monitors the health of elderly people and single-person households in real time and notifies doctors and security services if abnormal values ​​are detected. The system consists of devices worn by users, such as smart watches, blood pressure monitors, and thermometers, and a server that receives and analyzes data sent from these devices.

[0147] Hardware and Software Details

[0148] Hardware

[0149] User devices: Devices worn by users, such as smartwatches (e.g., Apple Watch and Fitbit), blood pressure monitors, and thermometers. These devices collect users' daily physiological information (e.g., heart rate, blood pressure, body temperature, etc.).

[0150] Server: The server is responsible for storing and analyzing the received data. It includes a high-performance database server and network equipment for sending notifications to doctors and security services based on the analysis results.

[0151] software

[0152] Data collection and transmission software: Software installed in the smartwatch or thermometer converts physiological information into a digital format and periodically transmits it to a server.

[0153] Data storage software: Software on the server side for storing received data in a database.

[0154] Data analysis software: Using an analysis algorithm (e.g., an analysis program written in Python or R), abnormal values ​​in physiological information are detected and primary examination results are generated.

[0155] Notification software: Software for automatically notifying doctors and security services of the generated primary examination results and physiological information.

[0156] System operation example

[0157] For example, if user A is wearing a smartwatch, the smartwatch will measure A's heart rate, blood pressure, body temperature, etc. every morning at 9:00 a.m. The measured data is automatically converted into digital format and sent to a server via the Internet. Upon receiving this data, the server stores it in a database and begins analysis. If the analysis detects an abnormal value, such as a blood pressure of 150 / 95 mmHg, a primary examination result will be generated stating, "Warning: Abnormal vital signs detected." This result is automatically sent to a notification system and security service dedicated to doctors. The doctors and security services will receive this notification and be able to respond promptly to the user's health condition.

[0158] Prompt Sentence Examples

[0159] "Design a system to monitor the health status of elderly people and notify doctors and security services if any abnormalities are detected. The device measures heart rate, blood pressure, and temperature, converts them into digital format, and transmits them. The server receives, stores, and analyzes these data. If any abnormal values ​​are detected based on the analysis results, it generates a primary examination result and notifies doctors and security services."

[0160] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0161] Step 1:

[0162] Devices worn by users, such as smartwatches, blood pressure monitors, and thermometers, periodically collect physiological information such as the user's heart rate, blood pressure, and body temperature. Specifically, the smartwatch automatically measures the heart rate, blood pressure, and body temperature every morning at 9:00. The input is physiological data obtained from each device, and the output is physiological data converted into digital format.

[0163] Step 2:

[0164] The device converts the collected physiological data into digital format and sends it to a server via the Internet. Specifically, the data measured by the smartwatch is converted into digital format by the internal software and sent to the server via Wi-Fi or 4G / 5G communication. The input is physiological data acquired in analog format, and the output is digital data sent to the server.

[0165] Step 3:

[0166] The server receives the digital physiological data sent from the terminal and stores it in a database. Specifically, a program that stores the received data in the database runs, and the data storage is completed. The input is the transmitted digital data, and the output is the physiological data stored in the database.

[0167] Step 4:

[0168] The server launches an analysis algorithm to analyze the accumulated physiological data. The analysis algorithm is used to detect abnormal values ​​in the data and generate a primary examination result. Specifically, the analysis algorithm, written in a programming language such as Python, scans the data and detects abnormal values. The input is the physiological data stored in the database, and the output is the primary examination result.

[0169] Step 5:

[0170] The server notifies the doctor and security service of the generated primary examination results. Specifically, it sends a notification to a doctor-specific notification system and security service API based on the generated primary examination results. The input is the primary examination results, and the output is the notification sent to the doctor and security service.

[0171] 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.

[0172] As an embodiment of the present invention, the following system is provided.

[0173] System Overview

[0174] The system of the present invention manages the health of elderly people and single-person households, and supports home medical care by acquiring physiological information (e.g., heart rate, blood pressure, body temperature, etc.) from the user and providing it to medical institutions. This system also incorporates an emotion engine that recognizes the user's emotional state, allowing it to grasp the user's overall health condition.

[0175] Device behavior

[0176] The devices consist of a smartwatch worn by the user, a blood pressure monitor, a thermometer, etc. These devices periodically collect the user's daily physiological information. The collected data is converted into digital format and sent to a server via the Internet. For example, a smartwatch collects and transmits data such as the user's heart rate, blood pressure, and body temperature at 9:00 a.m. every day.

[0177] Emotion Engine Operation

[0178] The emotion engine analyzes the user's physiological information to estimate their emotional state. Specifically, it analyzes heart rate, body temperature fluctuations, blood pressure trends, etc. to estimate whether the user is stressed, relaxed, or in some other emotional state. This emotional state data is also sent to the server and used to notify the doctor.

[0179] Server Operation

[0180] The server receives the physiological and emotional state data sent from the device and stores it in a database, which stores information for long-term health monitoring of the user. The received data is analyzed, and if abnormal values ​​are detected, a preliminary diagnosis result is generated.

[0181] If the analysis detects an abnormal value, such as blood pressure exceeding 140, the server generates a primary diagnosis result stating "Warning: Abnormal vital signs have been detected." If the result is normal, the server generates a diagnosis result stating "All vital signs are normal." The analysis also includes the results of the emotion engine, such as information such as "The user is in a state of stress."

[0182] Notify your doctor

[0183] The server notifies the doctor of the generated primary examination results, physiological information, and emotional state data. This notification is sent via a notification system dedicated to doctors and includes the patient ID, physiological information, details of the primary examination results, and emotional state data. This notification allows doctors to quickly identify patients who require attention and prioritize their examinations.

[0184] Specific examples

[0185] Consider a case where user A is wearing a smartwatch. The smartwatch measures A's heart rate (80 bpm), blood pressure (150 / 95 mmHg), and body temperature (36.8°C) at 9:00 a.m. This data is automatically sent to the server.

[0186] The server accumulates and analyzes the received data. In this case, because the blood pressure is abnormal (150 / 95 mmHg), it generates a primary examination result stating, "Warning: Abnormal vital signs detected." The emotion engine also recognizes that Person A is in a stressful state and generates data stating, "User is in a stressful state." This result and the physiological information are then notified to the doctor. The doctor receives this notification, checks Person A's condition, and takes the necessary measures promptly.

[0187] Results and Effects

[0188] This system allows doctors to monitor patients' health and emotional status in real time, enabling prompt medical examinations. It also allows users to easily manage their health at home, reducing the burden on medical institutions. This effectively addresses the issues of a shortage of doctors and declining medical capabilities in rural areas.

[0189] The processing flow will be explained below.

[0190] Step 1:

[0191] The device collects physiological information from the user. Devices such as smartwatches worn by the user, blood pressure monitors, and thermometers used by the user periodically measure data such as heart rate, blood pressure, and body temperature.

[0192] Step 2:

[0193] The device converts the collected physiological information into a digital format. Software installed in devices such as smartwatches and blood pressure monitors converts the measurement data into a digital format, such as JSON.

[0194] Step 3:

[0195] The device then sends the converted digital data to a server over the Internet, specifically by using an HTTP POST request to send the data to a pre-configured server URL.

[0196] Step 4:

[0197] The server receives the digital data sent from the device. An API endpoint is set up on the server side, and this endpoint receives a POST request from the device.

[0198] Step 5:

[0199] The server stores the received digital data in a database. Specifically, it uses a database management system (DBMS) to store new measurement data for each user.

[0200] Step 6:

[0201] The server analyzes the accumulated data and detects abnormalities. Based on the analysis algorithm, it evaluates whether there are any abnormal values, such as blood pressure exceeding 140 or heart rate exceeding 100.

[0202] Step 7:

[0203] The server generates a primary diagnosis result based on the analysis results. If an abnormal value is detected, a warning message is generated, and if the value is normal, a diagnosis result stating "All vital signs are normal" is generated.

[0204] Step 8:

[0205] The emotion engine analyzes the received physiological information and estimates the user's emotional state. For example, it can recognize whether the user is stressed or relaxed based on heart rate fluctuations and blood pressure patterns.

[0206] Step 9:

[0207] The server generates emotional state data based on the results of the emotion engine. Specifically, if the server determines that the user is in a stressful state, it generates data such as "Warning: User is in a stressful state."

[0208] Step 10:

[0209] The server notifies the doctor of the primary examination results, physiological information, and emotional state data via a dedicated notification system for the doctor, and includes the patient ID, physiological information, details of the primary examination results, and emotional state data.

[0210] Step 11:

[0211] Doctors receive notifications from the server and check for abnormal patients and their emotional states, allowing them to respond to patients who need prompt and prioritized medical attention.

[0212] Example 2

[0213] 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."

[0214] In modern society, health management for the elderly and single-person households has become a serious issue. These people often find it difficult to visit a medical institution, leading to neglect of daily health management. Medical institutions are also required to efficiently manage a large number of patients with limited resources. Therefore, there is a need for a system that can remotely monitor users' health and emotional states in real time and provide prompt, necessary responses.

[0215] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0216] In this invention, the server includes means for acquiring physiological information from a user, means for converting the acquired physiological information into a digital format and transmitting it, means for receiving and storing the transmitted physiological information, means for analyzing the stored physiological information and generating a primary examination result, means for inferring an emotional state based on the user's physiological information, means for receiving and analyzing the emotional state data, and means for notifying a doctor of the primary examination result and the emotional state data. This allows users to easily manage their health at home and doctors to monitor the health and emotional states of patients in real time, thereby realizing prompt examination and treatment.

[0217] A "user" is a person who utilizes the system to provide physiological information.

[0218] "Physiological information" is data that indicates the user's health condition, such as heart rate, blood pressure, and body temperature.

[0219] "Means of acquisition" refers to methods of obtaining physiological information using a smartwatch, blood pressure monitor, thermometer, etc.

[0220] "Digital format" means that the collected physiological information is in a format that can be processed as electronic data.

[0221] The "means for transmitting" is a method for transmitting the physiological information converted into digital form to the server.

[0222] The "means for receiving and storing" refers to the method by which the server receives the transmitted physiological information and stores it in a database.

[0223] The "means for analyzing and generating initial diagnostic results" refers to a method for analyzing physiological information and generating initial diagnostic information based on the results.

[0224] The "means for inferring emotional state" is a method for inferring the user's emotional state by analyzing fluctuations in heart rate and body temperature.

[0225] "Emotional state data" is information about the user's emotions obtained through analysis.

[0226] "Means of notification" refers to the method by which the primary examination results and emotional state data are communicated to the physician.

[0227] A "doctor" is a professional who makes a diagnosis and responds based on the notified data.

[0228] MODE FOR CARRYING OUT THE INVENTION

[0229] This invention is a system for managing the health of elderly people and single-person households, and supports home medical care by acquiring physiological information from users and providing it to medical institutions. This system acquires physiological information (e.g., heart rate, blood pressure, body temperature, etc.) from users and includes a function to infer their emotional state based on that data.

[0230] System configuration

[0231] This system consists of a terminal that acquires physiological information from a wearable device worn by the user, a means for converting the acquired data into digital format and transmitting it, a server that stores and analyzes the received data to generate the results of the initial examination, an emotion analysis engine that estimates the emotional state, and a means for notifying the doctor of the results.

[0232] Device behavior

[0233] The terminals are smartwatches worn by users, blood pressure monitors, thermometers, etc. These devices periodically collect daily physiological information from users. Specifically, smartwatches and fitness trackers are used as wearable devices. These devices measure data such as the user's heart rate, blood pressure, and body temperature, and convert it into digital format. For example, if a user wears a smartwatch at 9:00 a.m., the smartwatch will measure the user's heart rate (80 bpm), blood pressure (150 / 95 mmHg), and body temperature (36.8°C) and send the data to a server.

[0234] How the sentiment analysis engine works

[0235] The emotion engine is built using Python and machine learning frameworks such as TENSORFLOW®. This engine analyzes fluctuations in the user's heart rate, body temperature, and blood pressure to estimate the user's emotional state. For example, a sudden increase in heart rate is estimated to indicate the user's stress state. This emotional state data is also sent to the server.

[0236] Server Operation

[0237] The server is built using AWS (registered trademark) (Amazon Web Services) and receives physiological information and emotional state data sent from the device and stores it in a database. The database uses Amazon RDS. The server analyzes the received data and generates a primary examination result if an abnormal value is detected. Processing is performed using Python and data analysis libraries such as numpy and pandas. For example, if the user's blood pressure is abnormal at 150 / 95 mmHg, the primary examination result will be "Warning: Abnormal vital signs detected." Based on the results of the emotion engine, the server will also add information that "the user is in a state of stress."

[0238] Notify your doctor

[0239] The server notifies doctors of the generated initial examination results, physiological information, and emotional state data. This notification is done through a dedicated app such as PatientMonitoringApp or a web portal, and also includes an alert function. The notification includes the patient ID, physiological information, details of the initial examination results, and emotional state data. This allows doctors to quickly identify patients who require attention and prioritize their examinations.

[0240] Specific examples

[0241] A user puts on a smartwatch at 9am and collects the following data:

[0242] Heart rate: 80 bpm

[0243] Blood pressure: 150 / 95mmHg

[0244] Body temperature: 36.8℃

[0245] This data is automatically sent to the server, and if an abnormal heart rate or blood pressure is detected through analysis, a primary diagnosis result such as "Warning: Abnormal vital signs detected" and emotional state data such as "User is in a state of stress" are generated. These results are then notified to a doctor, who can then take prompt action.

[0246] Prompt Sentence Examples

[0247] By inputting the following prompt sentence into the generative AI model, abnormal values ​​can be detected and a primary examination result can be generated.

[0248] "Detect abnormal values ​​based on the following data and generate a primary examination result: Heart rate: 80 bpm, Blood pressure: 150 / 95 mmHg, Body temperature: 36.8°C, Emotional state: Stress"

[0249] As described above, the present invention provides a system that can monitor and manage the health condition of a user in real time from a remote location while reducing the burden on medical institutions.

[0250] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0251] Step 1:

[0252] Physiological information (heart rate, blood pressure, body temperature) is collected using wearable devices (smartwatches, blood pressure monitors, thermometers, etc.) worn by the user.

[0253] Specifically, when a user wears a smartwatch at 9:00 a.m., the smartwatch measures the user's heart rate (80 bpm), blood pressure (150 / 95 mmHg), and body temperature (36.8°C). The input is the user's physiological information, and the output is the collected physiological information data.

[0254] Step 2:

[0255] The terminal converts the collected physiological information into a digital format and transmits it to a server over the Internet.

[0256] Specifically, a smartwatch transmits the measured physiological information using Wi-Fi or a mobile network. The data is converted into a digital format and encrypted before being transmitted. The input is the collected physiological information data, and the output is the transmitted digital data.

[0257] Step 3:

[0258] The server receives the physiological information transmitted from the terminal and stores it in a database.

[0259] Specifically, AWS functions are used to receive data and store it in a database using Amazon RDS. The received data is first checked for consistency and then stored. The input is the transmitted digital data, and the output is the stored database entry.

[0260] Step 4:

[0261] An emotion engine analyzes physiological information and estimates the user's emotional state.

[0262] Specifically, an emotion analysis algorithm using Python and TensorFlow is executed to analyze the data. For example, if the heart rate fluctuates significantly, it is estimated as a "stressed state." The input is the accumulated physiological information data, and the output is the estimated emotional state data.

[0263] Step 5:

[0264] The server analyzes the stored physiological information and emotional state data and generates a primary diagnosis result.

[0265] Specifically, the system checks for abnormal values ​​in the data using data analysis libraries such as Python's numpy and pandas. For example, a blood pressure of 150 / 95 mmHg is judged to be an abnormal value and generates a medical examination result stating "Warning: Abnormal vital signs detected." The input is the accumulated physiological information data and emotional state data, and the output is the primary medical examination result.

[0266] Step 6:

[0267] The server notifies the physician of the generated primary examination results and emotional state data.

[0268] Specifically, the results are sent to the doctor's smartphone or web portal through a dedicated notification system such as PatientMonitoringApp. This notification includes the patient ID, physiological information, primary examination results, and emotional state data. The input is the primary examination results and emotional state data, and the output is the notification to the doctor.

[0269] Step 7:

[0270] The doctor will receive a notification, check the patient's condition, and respond promptly.

[0271] Specifically, the data displayed on a dedicated app or web portal is used to provide the necessary medical examinations and treatment. The input is the notified data, and the output is the appropriate medical response.

[0272] The specific operations for each step and the inputs and outputs for each step have been described above.

[0273] (Application example 2)

[0274] 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."

[0275] In modern society, health management for the elderly and single-person households is an important issue. In particular, sudden changes in physical condition or emotional states such as stress can pose serious health risks if not addressed promptly. Rapid response from medical institutions is also required, which requires real-time monitoring of physiological information and emotional states. However, conventional systems lack sufficient means to effectively acquire and analyze this data and promptly notify appropriate institutions when abnormalities are detected. Therefore, the present invention provides a system to solve these problems.

[0276] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0277] In this invention,

[0278] The server includes means for obtaining physiological information and emotional state from the user;

[0279] means for converting the acquired physiological information and emotional state into digital form and transmitting the digital information;

[0280] means for receiving and storing the transmitted physiological information and emotional state;

[0281] means for analyzing the accumulated physiological information and emotional state to generate a primary diagnosis result;

[0282] a means for notifying a doctor of the results of the initial examination;

[0283] a means of notifying emergency contacts if an abnormality is detected;

[0284] Includes.

[0285] This allows for real-time monitoring of the user's health and emotional state, and if an abnormality is detected, it will immediately notify a doctor or emergency contact, enabling a rapid response and improving the user's safety and peace of mind.

[0286] "Means for acquiring physiological information and emotional state from a user" refers to devices such as smart watches, blood pressure monitors, thermometers, and smartphones that are used to measure a user's physical condition and emotions.

[0287] "Means for converting physiological information and emotional state into digital form and transmitting it" refers to a technology for converting acquired physiological data and emotional data into digital data and transmitting it to a server using a communication means such as the Internet.

[0288] The "receiving and storing means" is a server unit including a main memory and a database that receives the digital data sent from the user's device and stores it in the long term.

[0289] The "means for analyzing and generating primary examination results" refers to a system that uses programs and algorithms to analyze accumulated data, detects abnormal values ​​and emotional states, and automatically generates primary examination results based on the results.

[0290] "Physician notification means" means a communication means for promptly notifying healthcare professionals of the results of the primary consultation and analyzed data, including email, SMS, or a dedicated application notification system.

[0291] "Means for notifying emergency contacts when an abnormality is detected" refers to a communication means for quickly sending an alert to pre-set emergency contacts (such as family members or nurses) when an abnormality is detected in the user's health condition.

[0292] The embodiments for carrying out the present invention will be described in detail below.

[0293] 1. Program Overview

[0294] The system of the present invention collects physiological information and emotional states from elderly and single-person users in real time, and provides the function of notifying emergency contacts if an abnormality is detected. The main hardware used includes smartwatches, blood pressure monitors, thermometers, and smartphones.

[0295] 2. Hardware and Software

[0296] The following hardware and software are used to operate the system:

[0297] Smartwatch: Collects heart rate, blood pressure, and temperature data.

[0298] Sphygmomanometer: Collects blood pressure data.

[0299] Thermometer: Collects temperature data.

[0300] Smartphone: Collects data, transmits data, displays analytics, and sends notifications.

[0301] Server: Responsible for data accumulation, analysis, generation of primary consultation results, and notification.

[0302] 3. Software Operation

[0303] Data collection and transmission

[0304] Smartwatches and other measuring devices (blood pressure monitors, thermometers) worn by users periodically collect daily physiological information and emotional states of users. This information is converted into digital format and transmitted to smartphones via communication methods such as Bluetooth and Wi-Fi. The smartphones then transmit this data to a server via the Internet.

[0305] Analyzing data and generating consultation results

[0306] The server stores the data and uses an analysis algorithm to detect abnormal values. Heart rate, blood pressure, and temperature data are used for analysis, and if an abnormal value is detected, a primary examination result is generated. For example, if the heart rate exceeds 100 bpm or blood pressure exceeds 140 / 90, it is marked as abnormal.

[0307] Emotional state analysis

[0308] The emotion engine analyzes the user's heart rate, body temperature fluctuations, blood pressure trends, etc. to estimate the user's emotional state. For example, if a sudden increase in heart rate or body temperature fluctuations is observed, it is assumed that this indicates stress or anxiety. This emotional state is also sent to the server and used to evaluate the user's overall health.

[0309] emergency notification

[0310] If an abnormality is detected, the server sends a notification to pre-defined emergency contacts (e.g., family members, doctors, nurses). The notification includes details of the abnormal value and an estimated emotional state. For example, if the heart rate spikes and the emotional state is estimated to be "stressed," this information will be sent to the emergency contacts.

[0311] Examples of concrete examples and prompts

[0312] For example, consider a user wearing a smartwatch. The smartwatch measures heart rate (e.g., 100 bpm), blood pressure (e.g., 150 / 95 mmHg), and body temperature (e.g., 37.5°C). This data is converted into digital format and sent to a server via the smartphone. The server analyzes the data, and if an abnormality is detected, it sends a notification saying, "Warning: Abnormal vital signs detected." Also, if the emotion engine estimates that the user is in a state of stress, this will also be included in the notification.

[0313] Here are some examples of prompts for an AI model:

[0314] Write a Python program that will send an email notification if the user's heart rate is abnormally high. The program will generate heart rate, blood pressure, and temperature data, and send a notification to a specified email address if it detects abnormal values. It should also include an emotion engine that estimates the user's emotional state (stressed, relaxed, etc.).

[0315] Thus, the present invention is a system that enables real-time monitoring of health and emotional states and rapid notification of abnormalities based thereon.

[0316] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0317] Step 1: Data collection

[0318] Input: User's heart rate, blood pressure, and temperature data

[0319] How it works: The smartwatch worn by the user, and the blood pressure monitor and thermometer used by the user, periodically collect data on the user's heart rate, blood pressure, and temperature. The smartwatch collects this data every day at 9:00 AM, for example.

[0320] Output: Collected physiological information

[0321] Step 2: Send data

[0322] Input: Physiological information collected from devices such as smartwatches

[0323] How it works: The device (such as a smartwatch) converts the collected physiological information into a digital format and transmits it to a smartphone using Bluetooth or Wi-Fi.

[0324] Output: Digital physiological information

[0325] Step 3: Transferring data to the server

[0326] Input: Digital physiological information received by a smartphone

[0327] How it works: The smartphone transmits physiological information to a server over the internet.

[0328] Output: Physiological information arriving at the server

[0329] Step 4: Data accumulation

[0330] Input: Physiological information arriving at the server

[0331] Operation: The server stores the received data in a database and manages it for each user.

[0332] Output: Physiological information stored in a database

[0333] Step 5: Data analysis

[0334] Input: Physiological information stored in a database

[0335] How it works: The server uses an analytical algorithm to analyze the accumulated data and detect abnormal values ​​such as heart rate, blood pressure, and body temperature. For example, blood pressure above 140 / 90 is considered abnormal.

[0336] Output: Analysis results and anomaly detection results

[0337] Step 6: Estimating emotional state

[0338] Input: Analyzed physiological information

[0339] How it works: The emotion engine uses analyzed heart rate, body temperature, and blood pressure fluctuation data to infer a user's emotional state, for example determining whether a sudden increase in heart rate indicates stress.

[0340] Output: Estimated emotional state

[0341] Step 7: Generate primary consultation results

[0342] Input: Analysis results, anomaly detection results, estimated emotional state

[0343] Operation: The server generates a primary diagnosis result based on these results, such as a message like "Warning: Abnormal vital signs detected" or "User is in a stressed state."

[0344] Output: First examination results

[0345] Step 8: Notify your doctor

[0346] Input: Primary examination results (anomaly detection results and estimated emotional state)

[0347] Operation: The server notifies the doctor of the generated primary consultation results through a notification system dedicated to the doctor.

[0348] Output: Initial consultation result notification sent to the doctor

[0349] Step 9: Emergency Notification

[0350] Input: Initial medical examination results, abnormality detection results, estimated emotional state

[0351] How it works: If an anomaly is detected, the server sends a warning notification to pre-defined emergency contacts (such as family members or nurses), including details of the anomaly and the patient's emotional state.

[0352] Output: Alert notification sent to emergency contacts

[0353] 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.

[0354] 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.

[0355] 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.

[0356] [Second embodiment]

[0357] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0358] 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.

[0359] 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).

[0360] 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.

[0361] 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.

[0362] 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).

[0363] 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. 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.

[0364] 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.

[0365] 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.

[0366] 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.

[0367] 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.

[0368] 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."

[0369] As an embodiment of the present invention, the following system is provided.

[0370] System Overview

[0371] The system of the present invention manages the health of elderly people and single-person households, obtaining physiological information (e.g., heart rate, blood pressure, body temperature, etc.) from users and providing this information to medical institutions to support home medical care.

[0372] Device behavior

[0373] The devices consist of a smartwatch worn by the user, a blood pressure monitor, a thermometer, etc. These devices periodically collect the user's daily physiological information. The collected data is converted into digital format and sent to a server via the Internet. For example, a smartwatch collects and transmits data such as the user's heart rate, blood pressure, and body temperature at 9:00 a.m. every day.

[0374] Server Operation

[0375] The server receives the physiological information sent from the device and stores it in a database. This database stores information for long-term monitoring of the user's health. The received data is analyzed, and if abnormal values ​​are detected, a primary diagnosis result is generated.

[0376] If the analysis detects an abnormal value, such as blood pressure exceeding 140, the server generates a primary diagnosis result such as "Warning: Abnormal vital signs have been detected." If the value is normal, the server generates a diagnosis result such as "All vital signs are normal."

[0377] Notify your doctor

[0378] The server notifies the doctor of the generated primary examination results and physiological information. This notification is sent via a notification system dedicated to doctors and includes the patient ID, physiological information, and details of the primary examination results. This notification allows doctors to quickly identify patients who require attention and prioritize their examinations.

[0379] Specific examples

[0380] Consider a case where user A is wearing a smartwatch. The smartwatch measures A's heart rate (80 bpm), blood pressure (150 / 95 mmHg), and body temperature (36.8°C) at 9:00 a.m. This data is automatically sent to the server.

[0381] The server stores and analyzes the received data. In this case, the blood pressure is abnormal (150 / 95 mmHg), so it generates a primary examination result stating "Warning: Abnormal vital signs detected." It then notifies the doctor of this result and the physiological information. The doctor receives this notification, checks Mr. A's condition, and takes the necessary measures promptly.

[0382] Results and Effects

[0383] This system allows doctors to monitor patients' health conditions in real time, enabling prompt medical examinations. It also allows users to easily manage their health at home, reducing the burden on medical institutions. This effectively solves the issues of doctor shortages and declining medical functions in rural areas.

[0384] The processing flow will be explained below.

[0385] Step 1:

[0386] The device collects physiological information from the user. Devices such as smartwatches worn by the user, blood pressure monitors, and thermometers used by the user periodically measure data such as heart rate, blood pressure, and body temperature.

[0387] Step 2:

[0388] The device converts the collected physiological information into a digital format. Software installed in devices such as smartwatches and blood pressure monitors converts the measurement data into a digital format, such as JSON.

[0389] Step 3:

[0390] The device then sends the converted digital data to a server over the Internet, specifically by using an HTTP POST request to send the data to a pre-configured server URL.

[0391] Step 4:

[0392] The server receives the digital data sent from the device. An API endpoint is set up on the server side, and this endpoint receives a POST request from the device.

[0393] Step 5:

[0394] The server stores the received digital data in a database. Specifically, it uses a database management system (DBMS) to store new measurement data for each user.

[0395] Step 6:

[0396] The server analyzes the accumulated data and detects abnormalities. Based on the analysis algorithm, it evaluates whether there are any abnormal values, such as blood pressure exceeding 140 or heart rate exceeding 100.

[0397] Step 7:

[0398] The server generates a primary diagnosis result based on the analysis results. If an abnormal value is detected, a warning message is generated, and if the value is normal, a diagnosis result stating "All vital signs are normal" is generated.

[0399] Step 8:

[0400] The server notifies the doctor of the initial examination results and physiological information by issuing an API request to a notification system dedicated to doctors and sending a notification including the patient ID, analysis results, physiological information, etc.

[0401] Step 9:

[0402] Doctors receive notifications from the server and check for abnormalities in patients, enabling them to respond quickly and prioritize patients who need medical attention.

[0403] Example 1

[0404] 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."

[0405] Health management for the elderly and single-person households requires a system that allows users to accurately and quickly grasp their own health status while at home and respond quickly when abnormalities occur. However, conventional systems often collect and analyze physiological information manually, making it difficult to respond quickly. In addition, there is a problem that doctors have difficulty understanding patients' conditions in real time due to insufficient collaboration with medical institutions.

[0406] 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.

[0407] In this invention, the server includes means for acquiring physiological information from a user, means for converting the acquired physiological information into digital format and transmitting it, means for receiving the transmitted physiological information and storing it in a database, means for analyzing the stored physiological information and automatically detecting abnormal values, means for generating a primary examination result based on the analysis result, and means for notifying a doctor of the primary examination result and the physiological information. This allows the physiological information collected by a user at home to be automatically analyzed, and if an abnormality is detected, the doctor will be promptly notified. This allows the doctor to grasp the patient's health condition in real time and to diagnose and respond promptly.

[0408] "User" refers to an individual who uses the service and is the subject of physiological information collection.

[0409] "Physiological information" refers to data that indicates the user's health condition, such as heart rate, blood pressure, and body temperature.

[0410] "Digital format" refers to a format in which physiological information is stored and transmitted electronically.

[0411] "Transmitting means" refers to the technical means for transferring the acquired physiological information in digital form to the server.

[0412] "Server" refers to a computer system that receives, stores, analyzes, and notifies data.

[0413] "Database" refers to a system for storing received physiological information as structured data.

[0414] "Means for analyzing" refers to the technical means for analyzing the accumulated physiological information and detecting abnormal values.

[0415] "Primary examination results" refers to initial diagnostic information regarding the user's health condition obtained through analysis.

[0416] "Means of notification" refers to the technical means for communicating the results of the primary examination and physiological information to the physician.

[0417] An "abnormal value" refers to a value of physiological information that deviates from a set normal range.

[0418] A "smartwatch" refers to a wearable device that periodically collects and transmits physiological information about the user.

[0419] A "sphygmomanometer" refers to a device that measures a user's blood pressure and acquires the data.

[0420] A "thermometer" refers to a device that measures a user's body temperature and acquires that data.

[0421] MODE FOR CARRYING OUT THE INVENTION

[0422] Overall system overview

[0423] The system of this invention supports home medical care by acquiring physiological information from elderly people and single-person households, appropriately analyzing it, and providing it to medical institutions. The system consists of a terminal worn by the user, a server that receives and analyzes the data, and a means for notifying doctors.

[0424] Device behavior

[0425] The terminals used include devices such as smartwatches, blood pressure monitors, and thermometers. These terminals automatically measure the user's physiological information (heart rate, blood pressure, body temperature, etc.) at regular intervals. The measured data is converted into digital format in real time and sent to a server via the Internet. For example, a smartwatch obtains and sends the following information every day at 9:00 AM:

[0426] Heart rate: 80 bpm

[0427] Blood pressure: 150 / 95 mmHg

[0428] Body temperature: 36.8℃

[0429] Server Operation

[0430] The server receives the physiological information sent from the device and stores it in a database. The database accumulates the user's health status over time, including past measurement data. This accumulated data is automatically analyzed using data analysis libraries such as Python and Pandas. During the analysis process, abnormal values ​​are detected based on a set algorithm.

[0431] Specifically, the received data is screened, and when abnormal values ​​are detected, such as blood pressure exceeding 140 / 90 mmHg, it is determined to be abnormal. Based on this determination, a primary medical examination result is generated. The following medical examination results are generated:

[0432] "Warning: Abnormal vital signs detected."

[0433] "All vital signs are normal."

[0434] Notify your doctor

[0435] The generated primary examination results and the user's physiological information are communicated to the doctor via a dedicated notification system. The notification includes the following information:

[0436] patient ID

[0437] Heart rate

[0438] blood pressure

[0439] body temperature

[0440] Examination results

[0441] For example, the following notification will be given:

[0442] Patient ID: UserA

[0443] Heart rate: 80 bpm

[0444] Blood pressure: 150 / 95 mmHg

[0445] Body temperature: 36.8℃

[0446] Examination results: Warning: Abnormal vital signs detected

[0447] Deployment Examples and Real-World Usage Scenarios

[0448] Consider the case where user A is wearing a smartwatch. The smartwatch measures A's heart rate (80 bpm), blood pressure (150 / 95 mmHg), and body temperature (36.8°C) at 9:00 a.m. and automatically sends this data to the server. The server accumulates and analyzes the data. In this case, because the blood pressure is abnormal (150 / 95 mmHg), the server generates a primary examination result stating "Warning: Abnormal vital signs detected" and notifies the doctor along with A's physiological information. The doctor receives this notification, checks A's condition, and takes any necessary measures promptly.

[0449] Prompt Sentence Examples

[0450] "Please explain the health care system for the elderly. Please be specific about which devices collect what data, how that data is analyzed on the server, and how the doctor is notified. Also, please give specific examples of users."

[0451] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0452] Step 1: The user wears a device such as a smartwatch, blood pressure monitor, or thermometer to collect physiological information. The input is physiological data such as the user's heart rate, blood pressure, and body temperature. The output is this data converted into digital form. For example, the smartwatch measures the user's heart rate as 80 bpm, blood pressure as 150 / 95 mmHg, and body temperature as 36.8°C.

[0453] Step 2: The device converts the acquired physiological information into a digital format and sends it to a server via the Internet. The input is the digitized physiological data. The output is the data sent to the server via the Internet. For example, a smartwatch sends the measured values ​​to the server as packet data.

[0454] Step 3: The server receives the physiological information sent from the device and stores it in a database. The input is the physiological data sent from the device. The output is the physiological data stored in the database. For example, the server saves the data received in an SQL database.

[0455] Step 4: The server analyzes the accumulated data. The input is the physiological data stored in the database. The output is the analysis results. This analysis uses Python and the Pandas library to detect outliers. For example, the server analyzes the accumulated blood pressure data and extracts outliers where the blood pressure exceeds 140 / 90 mmHg.

[0456] Step 5: The server generates a primary medical examination result based on the analysis result. The input is the analysis result. The output is the primary medical examination result. For example, if the blood pressure is abnormal (150 / 95 mmHg), the server generates a medical examination result saying "Warning: Abnormal vital signs detected."

[0457] Step 6: The server notifies the doctor of the generated primary examination results and the user's physiological information. The input is the primary examination results and physiological data. The output is the notification sent to the doctor. For example, a notification such as "Patient ID: UserA, Heart rate: 80 bpm, Blood pressure: 150 / 95 mmHg, Body temperature: 36.8℃, Examination results: Warning: Abnormal vital signs detected" is sent to the doctor.

[0458] (Application example 1)

[0459] 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."

[0460] The purpose of this invention is to improve the quality of home medical care for the elderly and single-person households, while also reducing the burden on doctors. In particular, it is important to provide a rapid response to sudden changes in health conditions and to implement comprehensive safety measures in cooperation with security services.

[0461] 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.

[0462] In this invention, the server includes a means for acquiring physiological information from a user, a means for converting the acquired physiological information into a digital format and transmitting it, a means for receiving and storing the transmitted physiological information, a means for analyzing the stored physiological information and generating a primary examination result, and a means for notifying a doctor and a security service of the primary examination result. This makes it possible to grasp changes in the health status of elderly people and single-person households in real time and take prompt and appropriate measures if necessary. Furthermore, by linking with a security service, it is possible to ensure the overall safety of elderly people and single-person households.

[0463] "Means for acquiring physiological information from a user" refers to means for collecting physiological data such as heart rate, blood pressure, and body temperature through a device worn or used by the user.

[0464] The "means for converting the acquired physiological information into a digital format and transmitting it" refers to a means for converting the collected physiological data into digital data and transmitting it to a server.

[0465] The "means for receiving and storing the transmitted physiological information" refers to a means for receiving the transmitted digital data on the server side and storing it in a database or the like.

[0466] The "means for analyzing the accumulated physiological information and generating initial examination results" refers to a means for detecting abnormal values ​​in the data using an algorithm that analyzes the stored physiological data and generates initial examination results.

[0467] The "means for notifying the doctor and security service of the primary examination results" refers to a means for notifying the doctor and, if necessary, the security service of the generated primary examination results.

[0468] This invention is a system that monitors the health of elderly people and single-person households in real time and notifies doctors and security services if abnormal values ​​are detected. The system consists of devices worn by users, such as smart watches, blood pressure monitors, and thermometers, and a server that receives and analyzes data sent from these devices.

[0469] Hardware and Software Details

[0470] Hardware

[0471] User devices: Devices worn by users, such as smartwatches (e.g., Apple Watch and Fitbit), blood pressure monitors, and thermometers. These devices collect users' daily physiological information (e.g., heart rate, blood pressure, body temperature, etc.).

[0472] Server: The server is responsible for storing and analyzing the received data. It includes a high-performance database server and network equipment for sending notifications to doctors and security services based on the analysis results.

[0473] software

[0474] Data collection and transmission software: Software installed in the smartwatch or thermometer converts physiological information into a digital format and periodically transmits it to a server.

[0475] Data storage software: Software on the server side for storing received data in a database.

[0476] Data analysis software: Using an analysis algorithm (e.g., an analysis program written in Python or R), abnormal values ​​in physiological information are detected and primary examination results are generated.

[0477] Notification software: Software for automatically notifying doctors and security services of the generated primary examination results and physiological information.

[0478] System operation example

[0479] For example, if user A is wearing a smartwatch, the smartwatch will measure A's heart rate, blood pressure, body temperature, etc. every morning at 9:00 a.m. The measured data is automatically converted into digital format and sent to a server via the Internet. Upon receiving this data, the server stores it in a database and begins analysis. If the analysis detects an abnormal value, such as a blood pressure of 150 / 95 mmHg, a primary examination result will be generated stating, "Warning: Abnormal vital signs detected." This result is automatically sent to a notification system and security service dedicated to doctors. The doctors and security services will receive this notification and be able to respond promptly to the user's health condition.

[0480] Prompt Sentence Examples

[0481] "Design a system to monitor the health status of elderly people and notify doctors and security services if any abnormalities are detected. The device measures heart rate, blood pressure, and temperature, converts them into digital format, and transmits them. The server receives, stores, and analyzes these data. If any abnormal values ​​are detected based on the analysis results, it generates a primary examination result and notifies doctors and security services."

[0482] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0483] Step 1:

[0484] Devices worn by users, such as smartwatches, blood pressure monitors, and thermometers, periodically collect physiological information such as the user's heart rate, blood pressure, and body temperature. Specifically, the smartwatch automatically measures the heart rate, blood pressure, and body temperature every morning at 9:00. The input is physiological data obtained from each device, and the output is physiological data converted into digital format.

[0485] Step 2:

[0486] The device converts the collected physiological data into digital format and sends it to a server via the Internet. Specifically, the data measured by the smartwatch is converted into digital format by the internal software and sent to the server via Wi-Fi or 4G / 5G communication. The input is physiological data acquired in analog format, and the output is digital data sent to the server.

[0487] Step 3:

[0488] The server receives the digital physiological data sent from the terminal and stores it in a database. Specifically, a program that stores the received data in the database runs, and the data storage is completed. The input is the transmitted digital data, and the output is the physiological data stored in the database.

[0489] Step 4:

[0490] The server launches an analysis algorithm to analyze the accumulated physiological data. The analysis algorithm is used to detect abnormal values ​​in the data and generate a primary examination result. Specifically, the analysis algorithm, written in a programming language such as Python, scans the data and detects abnormal values. The input is the physiological data stored in the database, and the output is the primary examination result.

[0491] Step 5:

[0492] The server notifies the doctor and security service of the generated primary examination results. Specifically, it sends a notification to a doctor-specific notification system and security service API based on the generated primary examination results. The input is the primary examination results, and the output is the notification sent to the doctor and security service.

[0493] 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.

[0494] As an embodiment of the present invention, the following system is provided.

[0495] System Overview

[0496] The system of the present invention manages the health of elderly people and single-person households, and supports home medical care by acquiring physiological information (e.g., heart rate, blood pressure, body temperature, etc.) from the user and providing it to medical institutions. This system also incorporates an emotion engine that recognizes the user's emotional state, allowing it to grasp the user's overall health condition.

[0497] Device behavior

[0498] The devices consist of a smartwatch worn by the user, a blood pressure monitor, a thermometer, etc. These devices periodically collect the user's daily physiological information. The collected data is converted into digital format and sent to a server via the Internet. For example, a smartwatch collects and transmits data such as the user's heart rate, blood pressure, and body temperature at 9:00 a.m. every day.

[0499] Emotion Engine Operation

[0500] The emotion engine analyzes the user's physiological information to estimate their emotional state. Specifically, it analyzes heart rate, body temperature fluctuations, blood pressure trends, etc. to estimate whether the user is stressed, relaxed, or in some other emotional state. This emotional state data is also sent to the server and used to notify the doctor.

[0501] Server Operation

[0502] The server receives the physiological and emotional state data sent from the device and stores it in a database, which stores information for long-term health monitoring of the user. The received data is analyzed, and if abnormal values ​​are detected, a preliminary diagnosis result is generated.

[0503] If the analysis detects an abnormal value, such as blood pressure exceeding 140, the server generates a primary diagnosis result stating "Warning: Abnormal vital signs have been detected." If the result is normal, the server generates a diagnosis result stating "All vital signs are normal." The analysis also includes the results of the emotion engine, such as information such as "The user is in a state of stress."

[0504] Notify your doctor

[0505] The server notifies the doctor of the generated primary examination results, physiological information, and emotional state data. This notification is sent via a notification system dedicated to doctors and includes the patient ID, physiological information, details of the primary examination results, and emotional state data. This notification allows doctors to quickly identify patients who require attention and prioritize their examinations.

[0506] Specific examples

[0507] Consider a case where user A is wearing a smartwatch. The smartwatch measures A's heart rate (80 bpm), blood pressure (150 / 95 mmHg), and body temperature (36.8°C) at 9:00 a.m. This data is automatically sent to the server.

[0508] The server accumulates and analyzes the received data. In this case, because the blood pressure is abnormal (150 / 95 mmHg), it generates a primary examination result stating, "Warning: Abnormal vital signs detected." The emotion engine also recognizes that Person A is in a stressful state and generates data stating, "User is in a stressful state." This result and the physiological information are then notified to the doctor. The doctor receives this notification, checks Person A's condition, and takes the necessary measures promptly.

[0509] Results and Effects

[0510] This system allows doctors to monitor patients' health and emotional status in real time, enabling prompt medical examinations. It also allows users to easily manage their health at home, reducing the burden on medical institutions. This effectively addresses the issues of a shortage of doctors and declining medical capabilities in rural areas.

[0511] The processing flow will be explained below.

[0512] Step 1:

[0513] The device collects physiological information from the user. Devices such as smartwatches worn by the user, blood pressure monitors, and thermometers used by the user periodically measure data such as heart rate, blood pressure, and body temperature.

[0514] Step 2:

[0515] The device converts the collected physiological information into a digital format. Software installed in devices such as smartwatches and blood pressure monitors converts the measurement data into a digital format, such as JSON.

[0516] Step 3:

[0517] The device then sends the converted digital data to a server over the Internet, specifically by using an HTTP POST request to send the data to a pre-configured server URL.

[0518] Step 4:

[0519] The server receives the digital data sent from the device. An API endpoint is set up on the server side, and this endpoint receives a POST request from the device.

[0520] Step 5:

[0521] The server stores the received digital data in a database. Specifically, it uses a database management system (DBMS) to store new measurement data for each user.

[0522] Step 6:

[0523] The server analyzes the accumulated data and detects abnormalities. Based on the analysis algorithm, it evaluates whether there are any abnormal values, such as blood pressure exceeding 140 or heart rate exceeding 100.

[0524] Step 7:

[0525] The server generates a primary diagnosis result based on the analysis results. If an abnormal value is detected, a warning message is generated, and if the value is normal, a diagnosis result stating "All vital signs are normal" is generated.

[0526] Step 8:

[0527] The emotion engine analyzes the received physiological information and estimates the user's emotional state. For example, it can recognize whether the user is stressed or relaxed based on heart rate fluctuations and blood pressure patterns.

[0528] Step 9:

[0529] The server generates emotional state data based on the results of the emotion engine. Specifically, if the server determines that the user is in a stressful state, it generates data such as "Warning: User is in a stressful state."

[0530] Step 10:

[0531] The server notifies the doctor of the primary examination results, physiological information, and emotional state data via a dedicated notification system for the doctor, and includes the patient ID, physiological information, details of the primary examination results, and emotional state data.

[0532] Step 11:

[0533] Doctors receive notifications from the server and check for abnormal patients and their emotional states, allowing them to respond to patients who need prompt and prioritized medical attention.

[0534] Example 2

[0535] 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."

[0536] In modern society, health management for the elderly and single-person households has become a serious issue. These people often find it difficult to visit a medical institution, leading to neglect of daily health management. Medical institutions are also required to efficiently manage a large number of patients with limited resources. Therefore, there is a need for a system that can remotely monitor users' health and emotional states in real time and provide prompt, necessary responses.

[0537] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0538] In this invention, the server includes means for acquiring physiological information from a user, means for converting the acquired physiological information into a digital format and transmitting it, means for receiving and storing the transmitted physiological information, means for analyzing the stored physiological information and generating a primary examination result, means for inferring an emotional state based on the user's physiological information, means for receiving and analyzing the emotional state data, and means for notifying a doctor of the primary examination result and the emotional state data. This allows users to easily manage their health at home and doctors to monitor the health and emotional states of patients in real time, thereby realizing prompt examination and treatment.

[0539] A "user" is a person who utilizes the system to provide physiological information.

[0540] "Physiological information" is data that indicates the user's health condition, such as heart rate, blood pressure, and body temperature.

[0541] "Means of acquisition" refers to methods of obtaining physiological information using a smartwatch, blood pressure monitor, thermometer, etc.

[0542] "Digital format" means that the collected physiological information is in a format that can be processed as electronic data.

[0543] The "means for transmitting" is a method for transmitting the physiological information converted into digital form to the server.

[0544] The "means for receiving and storing" refers to the method by which the server receives the transmitted physiological information and stores it in a database.

[0545] The "means for analyzing and generating initial diagnostic results" refers to a method for analyzing physiological information and generating initial diagnostic information based on the results.

[0546] The "means for inferring emotional state" is a method for inferring the user's emotional state by analyzing fluctuations in heart rate and body temperature.

[0547] "Emotional state data" is information about the user's emotions obtained through analysis.

[0548] "Means of notification" refers to the method by which the primary examination results and emotional state data are communicated to the physician.

[0549] A "doctor" is a professional who makes a diagnosis and responds based on the notified data.

[0550] MODE FOR CARRYING OUT THE INVENTION

[0551] This invention is a system for managing the health of elderly people and single-person households, and supports home medical care by acquiring physiological information from users and providing it to medical institutions. This system acquires physiological information (e.g., heart rate, blood pressure, body temperature, etc.) from users and includes a function to infer their emotional state based on that data.

[0552] System configuration

[0553] This system consists of a terminal that acquires physiological information from a wearable device worn by the user, a means for converting the acquired data into digital format and transmitting it, a server that stores and analyzes the received data to generate the results of the initial examination, an emotion analysis engine that estimates the emotional state, and a means for notifying the doctor of the results.

[0554] Device behavior

[0555] The terminals are smartwatches worn by users, blood pressure monitors, thermometers, etc. These devices periodically collect daily physiological information from users. Specifically, smartwatches and fitness trackers are used as wearable devices. These devices measure data such as the user's heart rate, blood pressure, and body temperature, and convert it into digital format. For example, if a user wears a smartwatch at 9:00 a.m., the smartwatch will measure the user's heart rate (80 bpm), blood pressure (150 / 95 mmHg), and body temperature (36.8°C) and send the data to a server.

[0556] How the sentiment analysis engine works

[0557] The emotion engine is built using Python and machine learning frameworks such as TensorFlow. The engine analyzes fluctuations in the user's heart rate, body temperature, and blood pressure to estimate the user's emotional state. For example, a sudden increase in heart rate is assumed to indicate the user's stress level. This emotional state data is also sent to the server.

[0558] Server Operation

[0559] The server was built using AWS (Amazon Web Services) and receives physiological information and emotional state data sent from the device and stores it in a database. The database uses Amazon RDS. The server analyzes the received data and generates a primary examination result if an abnormal value is detected. Processing is carried out using Python and data analysis libraries such as numpy and pandas. For example, if the user's blood pressure is abnormal at 150 / 95 mmHg, the primary examination result will be "Warning: Abnormal vital signs detected." In addition, based on the results of the emotion engine, the server adds information that "the user is in a state of stress."

[0560] Notify your doctor

[0561] The server notifies doctors of the generated initial examination results, physiological information, and emotional state data. This notification is done through a dedicated app such as PatientMonitoringApp or a web portal, and also includes an alert function. The notification includes the patient ID, physiological information, details of the initial examination results, and emotional state data. This allows doctors to quickly identify patients who require attention and prioritize their examinations.

[0562] Specific examples

[0563] A user puts on a smartwatch at 9am and collects the following data:

[0564] Heart rate: 80 bpm

[0565] Blood pressure: 150 / 95mmHg

[0566] Body temperature: 36.8℃

[0567] This data is automatically sent to the server, and if an abnormal heart rate or blood pressure is detected through analysis, a primary diagnosis result such as "Warning: Abnormal vital signs detected" and emotional state data such as "User is in a state of stress" are generated. These results are then notified to a doctor, who can then take prompt action.

[0568] Prompt Sentence Examples

[0569] By inputting the following prompt sentence into the generative AI model, abnormal values ​​can be detected and a primary examination result can be generated.

[0570] "Detect abnormal values ​​based on the following data and generate a primary examination result: Heart rate: 80 bpm, Blood pressure: 150 / 95 mmHg, Body temperature: 36.8°C, Emotional state: Stress"

[0571] As described above, the present invention provides a system that can monitor and manage the health condition of a user in real time from a remote location while reducing the burden on medical institutions.

[0572] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0573] Step 1:

[0574] Physiological information (heart rate, blood pressure, body temperature) is collected using wearable devices (smartwatches, blood pressure monitors, thermometers, etc.) worn by the user.

[0575] Specifically, when a user wears a smartwatch at 9:00 a.m., the smartwatch measures the user's heart rate (80 bpm), blood pressure (150 / 95 mmHg), and body temperature (36.8°C). The input is the user's physiological information, and the output is the collected physiological information data.

[0576] Step 2:

[0577] The terminal converts the collected physiological information into a digital format and transmits it to a server over the Internet.

[0578] Specifically, a smartwatch transmits the measured physiological information using Wi-Fi or a mobile network. The data is converted into a digital format and encrypted before being transmitted. The input is the collected physiological information data, and the output is the transmitted digital data.

[0579] Step 3:

[0580] The server receives the physiological information transmitted from the terminal and stores it in a database.

[0581] Specifically, AWS functions are used to receive data and store it in a database using Amazon RDS. The received data is first checked for consistency and then stored. The input is the transmitted digital data, and the output is the stored database entry.

[0582] Step 4:

[0583] An emotion engine analyzes physiological information and estimates the user's emotional state.

[0584] Specifically, an emotion analysis algorithm using Python and TensorFlow is executed to analyze the data. For example, if the heart rate fluctuates significantly, it is estimated as a "stressed state." The input is the accumulated physiological information data, and the output is the estimated emotional state data.

[0585] Step 5:

[0586] The server analyzes the stored physiological information and emotional state data and generates a primary diagnosis result.

[0587] Specifically, the system checks for abnormal values ​​in the data using data analysis libraries such as Python's numpy and pandas. For example, a blood pressure of 150 / 95 mmHg is judged to be an abnormal value and generates a medical examination result stating "Warning: Abnormal vital signs detected." The input is the accumulated physiological information data and emotional state data, and the output is the primary medical examination result.

[0588] Step 6:

[0589] The server notifies the physician of the generated primary examination results and emotional state data.

[0590] Specifically, the results are sent to the doctor's smartphone or web portal through a dedicated notification system such as PatientMonitoringApp. This notification includes the patient ID, physiological information, primary examination results, and emotional state data. The input is the primary examination results and emotional state data, and the output is the notification to the doctor.

[0591] Step 7:

[0592] The doctor will receive a notification, check the patient's condition, and respond promptly.

[0593] Specifically, the data displayed on a dedicated app or web portal is used to provide the necessary medical examinations and treatment. The input is the notified data, and the output is the appropriate medical response.

[0594] The specific operations for each step and the inputs and outputs for each step have been described above.

[0595] (Application example 2)

[0596] 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."

[0597] In modern society, health management for the elderly and single-person households is an important issue. In particular, sudden changes in physical condition or emotional states such as stress can pose serious health risks if not addressed promptly. Rapid response from medical institutions is also required, which requires real-time monitoring of physiological information and emotional states. However, conventional systems lack sufficient means to effectively acquire and analyze this data and promptly notify appropriate institutions when abnormalities are detected. Therefore, the present invention provides a system to solve these problems.

[0598] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0599] In this invention,

[0600] The server includes means for obtaining physiological information and emotional state from the user;

[0601] means for converting the acquired physiological information and emotional state into digital form and transmitting the digital information;

[0602] means for receiving and storing the transmitted physiological information and emotional state;

[0603] means for analyzing the accumulated physiological information and emotional state to generate a primary diagnosis result;

[0604] a means for notifying a doctor of the results of the initial examination;

[0605] a means of notifying emergency contacts if an abnormality is detected;

[0606] Includes.

[0607] This allows for real-time monitoring of the user's health and emotional state, and if an abnormality is detected, it will immediately notify a doctor or emergency contact, enabling a rapid response and improving the user's safety and peace of mind.

[0608] "Means for acquiring physiological information and emotional state from a user" refers to devices such as smart watches, blood pressure monitors, thermometers, and smartphones that are used to measure a user's physical condition and emotions.

[0609] "Means for converting physiological information and emotional state into digital form and transmitting it" refers to a technology for converting acquired physiological data and emotional data into digital data and transmitting it to a server using a communication means such as the Internet.

[0610] The "receiving and storing means" is a server unit including a main memory and a database that receives the digital data sent from the user's device and stores it in the long term.

[0611] The "means for analyzing and generating primary examination results" refers to a system that uses programs and algorithms to analyze accumulated data, detects abnormal values ​​and emotional states, and automatically generates primary examination results based on the results.

[0612] "Physician notification means" means a communication means for promptly notifying healthcare professionals of the results of the primary consultation and analyzed data, including email, SMS, or a dedicated application notification system.

[0613] "Means for notifying emergency contacts when an abnormality is detected" refers to a communication means for quickly sending an alert to pre-set emergency contacts (such as family members or nurses) when an abnormality is detected in the user's health condition.

[0614] The embodiments for carrying out the present invention will be described in detail below.

[0615] 1. Program Overview

[0616] The system of the present invention collects physiological information and emotional states from elderly and single-person users in real time, and provides the function of notifying emergency contacts if an abnormality is detected. The main hardware used includes smartwatches, blood pressure monitors, thermometers, and smartphones.

[0617] 2. Hardware and Software

[0618] The following hardware and software are used to operate the system:

[0619] Smartwatch: Collects heart rate, blood pressure, and temperature data.

[0620] Sphygmomanometer: Collects blood pressure data.

[0621] Thermometer: Collects temperature data.

[0622] Smartphone: Collects data, transmits data, displays analytics, and sends notifications.

[0623] Server: Responsible for data accumulation, analysis, generation of primary consultation results, and notification.

[0624] 3. Software Operation

[0625] Data collection and transmission

[0626] Smartwatches and other measuring devices (blood pressure monitors, thermometers) worn by users periodically collect daily physiological information and emotional states of users. This information is converted into digital format and transmitted to smartphones via communication methods such as Bluetooth and Wi-Fi. The smartphones then transmit this data to a server via the Internet.

[0627] Analyzing data and generating consultation results

[0628] The server stores the data and uses an analysis algorithm to detect abnormal values. Heart rate, blood pressure, and temperature data are used for analysis, and if an abnormal value is detected, a primary examination result is generated. For example, if the heart rate exceeds 100 bpm or blood pressure exceeds 140 / 90, it is marked as abnormal.

[0629] Emotional state analysis

[0630] The emotion engine analyzes the user's heart rate, body temperature fluctuations, blood pressure trends, etc. to estimate the user's emotional state. For example, if a sudden increase in heart rate or body temperature fluctuations is observed, it is assumed that this indicates stress or anxiety. This emotional state is also sent to the server and used to evaluate the user's overall health.

[0631] emergency notification

[0632] If an abnormality is detected, the server sends a notification to pre-defined emergency contacts (e.g., family members, doctors, nurses). The notification includes details of the abnormal value and an estimated emotional state. For example, if the heart rate spikes and the emotional state is estimated to be "stressed," this information will be sent to the emergency contacts.

[0633] Examples of concrete examples and prompts

[0634] For example, consider a user wearing a smartwatch. The smartwatch measures heart rate (e.g., 100 bpm), blood pressure (e.g., 150 / 95 mmHg), and body temperature (e.g., 37.5°C). This data is converted into digital format and sent to a server via the smartphone. The server analyzes the data, and if an abnormality is detected, it sends a notification saying, "Warning: Abnormal vital signs detected." Also, if the emotion engine estimates that the user is in a state of stress, this will also be included in the notification.

[0635] Here are some examples of prompts for an AI model:

[0636] Write a Python program that will send an email notification if the user's heart rate is abnormally high. The program will generate heart rate, blood pressure, and temperature data, and send a notification to a specified email address if it detects abnormal values. It should also include an emotion engine that estimates the user's emotional state (stressed, relaxed, etc.).

[0637] Thus, the present invention is a system that enables real-time monitoring of health and emotional states and rapid notification of abnormalities based thereon.

[0638] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0639] Step 1: Data collection

[0640] Input: User's heart rate, blood pressure, and temperature data

[0641] How it works: The smartwatch worn by the user, and the blood pressure monitor and thermometer used by the user, periodically collect data on the user's heart rate, blood pressure, and temperature. The smartwatch collects this data every day at 9:00 AM, for example.

[0642] Output: Collected physiological information

[0643] Step 2: Send data

[0644] Input: Physiological information collected from devices such as smartwatches

[0645] How it works: The device (such as a smartwatch) converts the collected physiological information into a digital format and transmits it to a smartphone using Bluetooth or Wi-Fi.

[0646] Output: Digital physiological information

[0647] Step 3: Transferring data to the server

[0648] Input: Digital physiological information received by a smartphone

[0649] How it works: The smartphone transmits physiological information to a server over the internet.

[0650] Output: Physiological information arriving at the server

[0651] Step 4: Data accumulation

[0652] Input: Physiological information arriving at the server

[0653] Operation: The server stores the received data in a database and manages it for each user.

[0654] Output: Physiological information stored in a database

[0655] Step 5: Data analysis

[0656] Input: Physiological information stored in a database

[0657] How it works: The server uses an analytical algorithm to analyze the accumulated data and detect abnormal values ​​such as heart rate, blood pressure, and body temperature. For example, blood pressure above 140 / 90 is considered abnormal.

[0658] Output: Analysis results and anomaly detection results

[0659] Step 6: Estimating emotional state

[0660] Input: Analyzed physiological information

[0661] How it works: The emotion engine uses analyzed heart rate, body temperature, and blood pressure fluctuation data to infer a user's emotional state, for example determining whether a sudden increase in heart rate indicates stress.

[0662] Output: Estimated emotional state

[0663] Step 7: Generate primary consultation results

[0664] Input: Analysis results, anomaly detection results, estimated emotional state

[0665] Operation: The server generates a primary diagnosis result based on these results, such as a message like "Warning: Abnormal vital signs detected" or "User is in a stressed state."

[0666] Output: First examination results

[0667] Step 8: Notify your doctor

[0668] Input: Primary examination results (anomaly detection results and estimated emotional state)

[0669] Operation: The server notifies the doctor of the generated primary consultation results through a notification system dedicated to the doctor.

[0670] Output: Initial consultation result notification sent to the doctor

[0671] Step 9: Emergency Notification

[0672] Input: Initial medical examination results, abnormality detection results, estimated emotional state

[0673] How it works: If an anomaly is detected, the server sends a warning notification to pre-defined emergency contacts (such as family members or nurses), including details of the anomaly and the patient's emotional state.

[0674] Output: Alert notification sent to emergency contacts

[0675] 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.

[0676] 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.

[0677] 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.

[0678] [Third embodiment]

[0679] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0680] 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.

[0681] 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).

[0682] 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.

[0683] 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.

[0684] 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).

[0685] 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. 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.

[0686] 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.

[0687] 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.

[0688] 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.

[0689] 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.

[0690] 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."

[0691] As an embodiment of the present invention, the following system is provided.

[0692] System Overview

[0693] The system of the present invention manages the health of elderly people and single-person households, obtaining physiological information (e.g., heart rate, blood pressure, body temperature, etc.) from users and providing this information to medical institutions to support home medical care.

[0694] Device behavior

[0695] The devices consist of a smartwatch worn by the user, a blood pressure monitor, a thermometer, etc. These devices periodically collect the user's daily physiological information. The collected data is converted into digital format and sent to a server via the Internet. For example, a smartwatch collects and transmits data such as the user's heart rate, blood pressure, and body temperature at 9:00 a.m. every day.

[0696] Server Operation

[0697] The server receives the physiological information sent from the device and stores it in a database. This database stores information for long-term monitoring of the user's health. The received data is analyzed, and if abnormal values ​​are detected, a primary diagnosis result is generated.

[0698] If the analysis detects an abnormal value, such as blood pressure exceeding 140, the server generates a primary diagnosis result such as "Warning: Abnormal vital signs have been detected." If the value is normal, the server generates a diagnosis result such as "All vital signs are normal."

[0699] Notify your doctor

[0700] The server notifies the doctor of the generated primary examination results and physiological information. This notification is sent via a notification system dedicated to doctors and includes the patient ID, physiological information, and details of the primary examination results. This notification allows doctors to quickly identify patients who require attention and prioritize their examinations.

[0701] Specific examples

[0702] Consider a case where user A is wearing a smartwatch. The smartwatch measures A's heart rate (80 bpm), blood pressure (150 / 95 mmHg), and body temperature (36.8°C) at 9:00 a.m. This data is automatically sent to the server.

[0703] The server stores and analyzes the received data. In this case, the blood pressure is abnormal (150 / 95 mmHg), so it generates a primary examination result stating "Warning: Abnormal vital signs detected." It then notifies the doctor of this result and the physiological information. The doctor receives this notification, checks Mr. A's condition, and takes the necessary measures promptly.

[0704] Results and Effects

[0705] This system allows doctors to monitor patients' health conditions in real time, enabling prompt medical examinations. It also allows users to easily manage their health at home, reducing the burden on medical institutions. This effectively solves the issues of doctor shortages and declining medical functions in rural areas.

[0706] The processing flow will be explained below.

[0707] Step 1:

[0708] The device collects physiological information from the user. Devices such as smartwatches worn by the user, blood pressure monitors, and thermometers used by the user periodically measure data such as heart rate, blood pressure, and body temperature.

[0709] Step 2:

[0710] The device converts the collected physiological information into a digital format. Software installed in devices such as smartwatches and blood pressure monitors converts the measurement data into a digital format, such as JSON.

[0711] Step 3:

[0712] The device then sends the converted digital data to a server over the Internet, specifically by using an HTTP POST request to send the data to a pre-configured server URL.

[0713] Step 4:

[0714] The server receives the digital data sent from the device. An API endpoint is set up on the server side, and this endpoint receives a POST request from the device.

[0715] Step 5:

[0716] The server stores the received digital data in a database. Specifically, it uses a database management system (DBMS) to store new measurement data for each user.

[0717] Step 6:

[0718] The server analyzes the accumulated data and detects abnormalities. Based on the analysis algorithm, it evaluates whether there are any abnormal values, such as blood pressure exceeding 140 or heart rate exceeding 100.

[0719] Step 7:

[0720] The server generates a primary diagnosis result based on the analysis results. If an abnormal value is detected, a warning message is generated, and if the value is normal, a diagnosis result stating "All vital signs are normal" is generated.

[0721] Step 8:

[0722] The server notifies the doctor of the initial examination results and physiological information by issuing an API request to a notification system dedicated to doctors and sending a notification including the patient ID, analysis results, physiological information, etc.

[0723] Step 9:

[0724] Doctors receive notifications from the server and check for abnormalities in patients, enabling them to respond quickly and prioritize patients who need medical attention.

[0725] Example 1

[0726] 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."

[0727] Health management for the elderly and single-person households requires a system that allows users to accurately and quickly grasp their own health status while at home and respond quickly when abnormalities occur. However, conventional systems often collect and analyze physiological information manually, making it difficult to respond quickly. In addition, there is a problem that doctors have difficulty understanding patients' conditions in real time due to insufficient collaboration with medical institutions.

[0728] 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.

[0729] In this invention, the server includes means for acquiring physiological information from a user, means for converting the acquired physiological information into digital format and transmitting it, means for receiving the transmitted physiological information and storing it in a database, means for analyzing the stored physiological information and automatically detecting abnormal values, means for generating a primary examination result based on the analysis result, and means for notifying a doctor of the primary examination result and the physiological information. This allows the physiological information collected by a user at home to be automatically analyzed, and if an abnormality is detected, the doctor will be promptly notified. This allows the doctor to grasp the patient's health condition in real time and to diagnose and respond promptly.

[0730] "User" refers to an individual who uses the service and is the subject of physiological information collection.

[0731] "Physiological information" refers to data that indicates the user's health condition, such as heart rate, blood pressure, and body temperature.

[0732] "Digital format" refers to a format in which physiological information is stored and transmitted electronically.

[0733] "Transmitting means" refers to the technical means for transferring the acquired physiological information in digital form to the server.

[0734] "Server" refers to a computer system that receives, stores, analyzes, and notifies data.

[0735] "Database" refers to a system for storing received physiological information as structured data.

[0736] "Means for analyzing" refers to the technical means for analyzing the accumulated physiological information and detecting abnormal values.

[0737] "Primary examination results" refers to initial diagnostic information regarding the user's health condition obtained through analysis.

[0738] "Means of notification" refers to the technical means for communicating the results of the primary examination and physiological information to the physician.

[0739] An "abnormal value" refers to a value of physiological information that deviates from a set normal range.

[0740] A "smartwatch" refers to a wearable device that periodically collects and transmits physiological information about the user.

[0741] A "sphygmomanometer" refers to a device that measures a user's blood pressure and acquires the data.

[0742] A "thermometer" refers to a device that measures a user's body temperature and acquires that data.

[0743] MODE FOR CARRYING OUT THE INVENTION

[0744] Overall system overview

[0745] The system of this invention supports home medical care by acquiring physiological information from elderly people and single-person households, appropriately analyzing it, and providing it to medical institutions. The system consists of a terminal worn by the user, a server that receives and analyzes the data, and a means for notifying doctors.

[0746] Device behavior

[0747] The terminals used include devices such as smartwatches, blood pressure monitors, and thermometers. These terminals automatically measure the user's physiological information (heart rate, blood pressure, body temperature, etc.) at regular intervals. The measured data is converted into digital format in real time and sent to a server via the Internet. For example, a smartwatch obtains and sends the following information every day at 9:00 AM:

[0748] Heart rate: 80 bpm

[0749] Blood pressure: 150 / 95 mmHg

[0750] Body temperature: 36.8℃

[0751] Server Operation

[0752] The server receives the physiological information sent from the device and stores it in a database. The database accumulates the user's health status over time, including past measurement data. This accumulated data is automatically analyzed using data analysis libraries such as Python and Pandas. During the analysis process, abnormal values ​​are detected based on a set algorithm.

[0753] Specifically, the received data is screened, and when abnormal values ​​are detected, such as blood pressure exceeding 140 / 90 mmHg, it is determined to be abnormal. Based on this determination, a primary medical examination result is generated. The following medical examination results are generated:

[0754] "Warning: Abnormal vital signs detected."

[0755] "All vital signs are normal."

[0756] Notify your doctor

[0757] The generated primary examination results and the user's physiological information are communicated to the doctor via a dedicated notification system. The notification includes the following information:

[0758] patient ID

[0759] Heart rate

[0760] blood pressure

[0761] body temperature

[0762] Examination results

[0763] For example, the following notification will be given:

[0764] Patient ID: UserA

[0765] Heart rate: 80 bpm

[0766] Blood pressure: 150 / 95 mmHg

[0767] Body temperature: 36.8℃

[0768] Examination results: Warning: Abnormal vital signs detected

[0769] Deployment Examples and Real-World Usage Scenarios

[0770] Consider the case where user A is wearing a smartwatch. The smartwatch measures A's heart rate (80 bpm), blood pressure (150 / 95 mmHg), and body temperature (36.8°C) at 9:00 a.m. and automatically sends this data to the server. The server accumulates and analyzes the data. In this case, because the blood pressure is abnormal (150 / 95 mmHg), the server generates a primary examination result stating "Warning: Abnormal vital signs detected" and notifies the doctor along with A's physiological information. The doctor receives this notification, checks A's condition, and takes any necessary measures promptly.

[0771] Prompt Sentence Examples

[0772] "Please explain the health care system for the elderly. Please be specific about which devices collect what data, how that data is analyzed on the server, and how the doctor is notified. Also, please give specific examples of users."

[0773] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0774] Step 1: The user wears a device such as a smartwatch, blood pressure monitor, or thermometer to collect physiological information. The input is physiological data such as the user's heart rate, blood pressure, and body temperature. The output is this data converted into digital form. For example, the smartwatch measures the user's heart rate as 80 bpm, blood pressure as 150 / 95 mmHg, and body temperature as 36.8°C.

[0775] Step 2: The device converts the acquired physiological information into a digital format and sends it to a server via the Internet. The input is the digitized physiological data. The output is the data sent to the server via the Internet. For example, a smartwatch sends the measured values ​​to the server as packet data.

[0776] Step 3: The server receives the physiological information sent from the device and stores it in a database. The input is the physiological data sent from the device. The output is the physiological data stored in the database. For example, the server saves the data received in an SQL database.

[0777] Step 4: The server analyzes the accumulated data. The input is the physiological data stored in the database. The output is the analysis results. This analysis uses Python and the Pandas library to detect outliers. For example, the server analyzes the accumulated blood pressure data and extracts outliers where the blood pressure exceeds 140 / 90 mmHg.

[0778] Step 5: The server generates a primary medical examination result based on the analysis result. The input is the analysis result. The output is the primary medical examination result. For example, if the blood pressure is abnormal (150 / 95 mmHg), the server generates a medical examination result saying "Warning: Abnormal vital signs detected."

[0779] Step 6: The server notifies the doctor of the generated primary examination results and the user's physiological information. The input is the primary examination results and physiological data. The output is the notification sent to the doctor. For example, a notification such as "Patient ID: UserA, Heart rate: 80 bpm, Blood pressure: 150 / 95 mmHg, Body temperature: 36.8℃, Examination results: Warning: Abnormal vital signs detected" is sent to the doctor.

[0780] (Application example 1)

[0781] 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."

[0782] The purpose of this invention is to improve the quality of home medical care for the elderly and single-person households, while also reducing the burden on doctors. In particular, it is important to provide a rapid response to sudden changes in health conditions and to implement comprehensive safety measures in cooperation with security services.

[0783] 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.

[0784] In this invention, the server includes a means for acquiring physiological information from a user, a means for converting the acquired physiological information into a digital format and transmitting it, a means for receiving and storing the transmitted physiological information, a means for analyzing the stored physiological information and generating a primary examination result, and a means for notifying a doctor and a security service of the primary examination result. This makes it possible to grasp changes in the health status of elderly people and single-person households in real time and take prompt and appropriate measures if necessary. Furthermore, by linking with a security service, it is possible to ensure the overall safety of elderly people and single-person households.

[0785] "Means for acquiring physiological information from a user" refers to means for collecting physiological data such as heart rate, blood pressure, and body temperature through a device worn or used by the user.

[0786] The "means for converting the acquired physiological information into a digital format and transmitting it" refers to a means for converting the collected physiological data into digital data and transmitting it to a server.

[0787] The "means for receiving and storing the transmitted physiological information" refers to a means for receiving the transmitted digital data on the server side and storing it in a database or the like.

[0788] The "means for analyzing the accumulated physiological information and generating initial examination results" refers to a means for detecting abnormal values ​​in the data using an algorithm that analyzes the stored physiological data and generates initial examination results.

[0789] The "means for notifying the doctor and security service of the primary examination results" refers to a means for notifying the doctor and, if necessary, the security service of the generated primary examination results.

[0790] This invention is a system that monitors the health of elderly people and single-person households in real time and notifies doctors and security services if abnormal values ​​are detected. The system consists of devices worn by users, such as smart watches, blood pressure monitors, and thermometers, and a server that receives and analyzes data sent from these devices.

[0791] Hardware and Software Details

[0792] Hardware

[0793] User devices: Devices worn by users, such as smartwatches (e.g., Apple Watch and Fitbit), blood pressure monitors, and thermometers. These devices collect users' daily physiological information (e.g., heart rate, blood pressure, body temperature, etc.).

[0794] Server: The server is responsible for storing and analyzing the received data. It includes a high-performance database server and network equipment for sending notifications to doctors and security services based on the analysis results.

[0795] software

[0796] Data collection and transmission software: Software installed in the smartwatch or thermometer converts physiological information into a digital format and periodically transmits it to a server.

[0797] Data storage software: Software on the server side for storing received data in a database.

[0798] Data analysis software: Using an analysis algorithm (e.g., an analysis program written in Python or R), abnormal values ​​in physiological information are detected and primary examination results are generated.

[0799] Notification software: Software for automatically notifying doctors and security services of the generated primary examination results and physiological information.

[0800] System operation example

[0801] For example, if user A is wearing a smartwatch, the smartwatch will measure A's heart rate, blood pressure, body temperature, etc. every morning at 9:00 a.m. The measured data is automatically converted into digital format and sent to a server via the Internet. Upon receiving this data, the server stores it in a database and begins analysis. If the analysis detects an abnormal value, such as a blood pressure of 150 / 95 mmHg, a primary examination result will be generated stating, "Warning: Abnormal vital signs detected." This result is automatically sent to a notification system and security service dedicated to doctors. The doctors and security services will receive this notification and be able to respond promptly to the user's health condition.

[0802] Prompt Sentence Examples

[0803] "Design a system to monitor the health status of elderly people and notify doctors and security services if any abnormalities are detected. The device measures heart rate, blood pressure, and temperature, converts them into digital format, and transmits them. The server receives, stores, and analyzes these data. If any abnormal values ​​are detected based on the analysis results, it generates a primary examination result and notifies doctors and security services."

[0804] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0805] Step 1:

[0806] Devices worn by users, such as smartwatches, blood pressure monitors, and thermometers, periodically collect physiological information such as the user's heart rate, blood pressure, and body temperature. Specifically, the smartwatch automatically measures the heart rate, blood pressure, and body temperature every morning at 9:00. The input is physiological data obtained from each device, and the output is physiological data converted into digital format.

[0807] Step 2:

[0808] The device converts the collected physiological data into digital format and sends it to a server via the Internet. Specifically, the data measured by the smartwatch is converted into digital format by the internal software and sent to the server via Wi-Fi or 4G / 5G communication. The input is physiological data acquired in analog format, and the output is digital data sent to the server.

[0809] Step 3:

[0810] The server receives the digital physiological data sent from the terminal and stores it in a database. Specifically, a program that stores the received data in the database runs, and the data storage is completed. The input is the transmitted digital data, and the output is the physiological data stored in the database.

[0811] Step 4:

[0812] The server launches an analysis algorithm to analyze the accumulated physiological data. The analysis algorithm is used to detect abnormal values ​​in the data and generate a primary examination result. Specifically, the analysis algorithm, written in a programming language such as Python, scans the data and detects abnormal values. The input is the physiological data stored in the database, and the output is the primary examination result.

[0813] Step 5:

[0814] The server notifies the doctor and security service of the generated primary examination results. Specifically, it sends a notification to a doctor-specific notification system and security service API based on the generated primary examination results. The input is the primary examination results, and the output is the notification sent to the doctor and security service.

[0815] 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.

[0816] As an embodiment of the present invention, the following system is provided.

[0817] System Overview

[0818] The system of the present invention manages the health of elderly people and single-person households, and supports home medical care by acquiring physiological information (e.g., heart rate, blood pressure, body temperature, etc.) from the user and providing it to medical institutions. This system also incorporates an emotion engine that recognizes the user's emotional state, allowing it to grasp the user's overall health condition.

[0819] Device behavior

[0820] The devices consist of a smartwatch worn by the user, a blood pressure monitor, a thermometer, etc. These devices periodically collect the user's daily physiological information. The collected data is converted into digital format and sent to a server via the Internet. For example, a smartwatch collects and transmits data such as the user's heart rate, blood pressure, and body temperature at 9:00 a.m. every day.

[0821] Emotion Engine Operation

[0822] The emotion engine analyzes the user's physiological information to estimate their emotional state. Specifically, it analyzes heart rate, body temperature fluctuations, blood pressure trends, etc. to estimate whether the user is stressed, relaxed, or in some other emotional state. This emotional state data is also sent to the server and used to notify the doctor.

[0823] Server Operation

[0824] The server receives the physiological and emotional state data sent from the device and stores it in a database, which stores information for long-term health monitoring of the user. The received data is analyzed, and if abnormal values ​​are detected, a preliminary diagnosis result is generated.

[0825] If the analysis detects an abnormal value, such as blood pressure exceeding 140, the server generates a primary diagnosis result stating "Warning: Abnormal vital signs have been detected." If the result is normal, the server generates a diagnosis result stating "All vital signs are normal." The analysis also includes the results of the emotion engine, such as information such as "The user is in a state of stress."

[0826] Notify your doctor

[0827] The server notifies the doctor of the generated primary examination results, physiological information, and emotional state data. This notification is sent via a notification system dedicated to doctors and includes the patient ID, physiological information, details of the primary examination results, and emotional state data. This notification allows doctors to quickly identify patients who require attention and prioritize their examinations.

[0828] Specific examples

[0829] Consider a case where user A is wearing a smartwatch. The smartwatch measures A's heart rate (80 bpm), blood pressure (150 / 95 mmHg), and body temperature (36.8°C) at 9:00 a.m. This data is automatically sent to the server.

[0830] The server accumulates and analyzes the received data. In this case, because the blood pressure is abnormal (150 / 95 mmHg), it generates a primary examination result stating, "Warning: Abnormal vital signs detected." The emotion engine also recognizes that Person A is in a stressful state and generates data stating, "User is in a stressful state." This result and the physiological information are then notified to the doctor. The doctor receives this notification, checks Person A's condition, and takes the necessary measures promptly.

[0831] Results and Effects

[0832] This system allows doctors to monitor patients' health and emotional status in real time, enabling prompt medical examinations. It also allows users to easily manage their health at home, reducing the burden on medical institutions. This effectively addresses the issues of a shortage of doctors and declining medical capabilities in rural areas.

[0833] The processing flow will be explained below.

[0834] Step 1:

[0835] The device collects physiological information from the user. Devices such as smartwatches worn by the user, blood pressure monitors, and thermometers used by the user periodically measure data such as heart rate, blood pressure, and body temperature.

[0836] Step 2:

[0837] The device converts the collected physiological information into a digital format. Software installed in devices such as smartwatches and blood pressure monitors converts the measurement data into a digital format, such as JSON.

[0838] Step 3:

[0839] The device then sends the converted digital data to a server over the Internet, specifically by using an HTTP POST request to send the data to a pre-configured server URL.

[0840] Step 4:

[0841] The server receives the digital data sent from the device. An API endpoint is set up on the server side, and this endpoint receives a POST request from the device.

[0842] Step 5:

[0843] The server stores the received digital data in a database. Specifically, it uses a database management system (DBMS) to store new measurement data for each user.

[0844] Step 6:

[0845] The server analyzes the accumulated data and detects abnormalities. Based on the analysis algorithm, it evaluates whether there are any abnormal values, such as blood pressure exceeding 140 or heart rate exceeding 100.

[0846] Step 7:

[0847] The server generates a primary diagnosis result based on the analysis results. If an abnormal value is detected, a warning message is generated, and if the value is normal, a diagnosis result stating "All vital signs are normal" is generated.

[0848] Step 8:

[0849] The emotion engine analyzes the received physiological information and estimates the user's emotional state. For example, it can recognize whether the user is stressed or relaxed based on heart rate fluctuations and blood pressure patterns.

[0850] Step 9:

[0851] The server generates emotional state data based on the results of the emotion engine. Specifically, if the server determines that the user is in a stressful state, it generates data such as "Warning: User is in a stressful state."

[0852] Step 10:

[0853] The server notifies the doctor of the primary examination results, physiological information, and emotional state data via a dedicated notification system for the doctor, and includes the patient ID, physiological information, details of the primary examination results, and emotional state data.

[0854] Step 11:

[0855] Doctors receive notifications from the server and check for abnormal patients and their emotional states, allowing them to respond to patients who need prompt and prioritized medical attention.

[0856] Example 2

[0857] 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."

[0858] In modern society, health management for the elderly and single-person households has become a serious issue. These people often find it difficult to visit a medical institution, leading to neglect of daily health management. Medical institutions are also required to efficiently manage a large number of patients with limited resources. Therefore, there is a need for a system that can remotely monitor users' health and emotional states in real time and provide prompt, necessary responses.

[0859] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0860] In this invention, the server includes means for acquiring physiological information from a user, means for converting the acquired physiological information into a digital format and transmitting it, means for receiving and storing the transmitted physiological information, means for analyzing the stored physiological information and generating a primary examination result, means for inferring an emotional state based on the user's physiological information, means for receiving and analyzing the emotional state data, and means for notifying a doctor of the primary examination result and the emotional state data. This allows users to easily manage their health at home and doctors to monitor the health and emotional states of patients in real time, thereby realizing prompt examination and treatment.

[0861] A "user" is a person who utilizes the system to provide physiological information.

[0862] "Physiological information" is data that indicates the user's health condition, such as heart rate, blood pressure, and body temperature.

[0863] "Means of acquisition" refers to methods of obtaining physiological information using a smartwatch, blood pressure monitor, thermometer, etc.

[0864] "Digital format" means that the collected physiological information is in a format that can be processed as electronic data.

[0865] The "means for transmitting" is a method for transmitting the physiological information converted into digital form to the server.

[0866] The "means for receiving and storing" refers to the method by which the server receives the transmitted physiological information and stores it in a database.

[0867] The "means for analyzing and generating initial diagnostic results" refers to a method for analyzing physiological information and generating initial diagnostic information based on the results.

[0868] The "means for inferring emotional state" is a method for inferring the user's emotional state by analyzing fluctuations in heart rate and body temperature.

[0869] "Emotional state data" is information about the user's emotions obtained through analysis.

[0870] "Means of notification" refers to the method by which the primary examination results and emotional state data are communicated to the physician.

[0871] A "doctor" is a professional who makes a diagnosis and responds based on the notified data.

[0872] MODE FOR CARRYING OUT THE INVENTION

[0873] This invention is a system for managing the health of elderly people and single-person households, and supports home medical care by acquiring physiological information from users and providing it to medical institutions. This system acquires physiological information (e.g., heart rate, blood pressure, body temperature, etc.) from users and includes a function to infer their emotional state based on that data.

[0874] System configuration

[0875] This system consists of a terminal that acquires physiological information from a wearable device worn by the user, a means for converting the acquired data into digital format and transmitting it, a server that stores and analyzes the received data to generate the results of the initial examination, an emotion analysis engine that estimates the emotional state, and a means for notifying the doctor of the results.

[0876] Device behavior

[0877] The terminals are smartwatches worn by users, blood pressure monitors, thermometers, etc. These devices periodically collect daily physiological information from users. Specifically, smartwatches and fitness trackers are used as wearable devices. These devices measure data such as the user's heart rate, blood pressure, and body temperature, and convert it into digital format. For example, if a user wears a smartwatch at 9:00 a.m., the smartwatch will measure the user's heart rate (80 bpm), blood pressure (150 / 95 mmHg), and body temperature (36.8°C) and send the data to a server.

[0878] How the sentiment analysis engine works

[0879] The emotion engine is built using Python and machine learning frameworks such as TensorFlow. The engine analyzes fluctuations in the user's heart rate, body temperature, and blood pressure to estimate the user's emotional state. For example, a sudden increase in heart rate is assumed to indicate the user's stress level. This emotional state data is also sent to the server.

[0880] Server Operation

[0881] The server was built using AWS (Amazon Web Services) and receives physiological information and emotional state data sent from the device and stores it in a database. The database uses Amazon RDS. The server analyzes the received data and generates a primary examination result if an abnormal value is detected. Processing is carried out using Python and data analysis libraries such as numpy and pandas. For example, if the user's blood pressure is abnormal at 150 / 95 mmHg, the primary examination result will be "Warning: Abnormal vital signs detected." In addition, based on the results of the emotion engine, the server adds information that "the user is in a state of stress."

[0882] Notify your doctor

[0883] The server notifies doctors of the generated initial examination results, physiological information, and emotional state data. This notification is done through a dedicated app such as PatientMonitoringApp or a web portal, and also includes an alert function. The notification includes the patient ID, physiological information, details of the initial examination results, and emotional state data. This allows doctors to quickly identify patients who require attention and prioritize their examinations.

[0884] Specific examples

[0885] A user puts on a smartwatch at 9am and collects the following data:

[0886] Heart rate: 80 bpm

[0887] Blood pressure: 150 / 95mmHg

[0888] Body temperature: 36.8℃

[0889] This data is automatically sent to the server, and if an abnormal heart rate or blood pressure is detected through analysis, a primary diagnosis result such as "Warning: Abnormal vital signs detected" and emotional state data such as "User is in a state of stress" are generated. These results are then notified to a doctor, who can then take prompt action.

[0890] Prompt Sentence Examples

[0891] By inputting the following prompt sentence into the generative AI model, abnormal values ​​can be detected and a primary examination result can be generated.

[0892] "Detect abnormal values ​​based on the following data and generate a primary examination result: Heart rate: 80 bpm, Blood pressure: 150 / 95 mmHg, Body temperature: 36.8°C, Emotional state: Stress"

[0893] As described above, the present invention provides a system that can monitor and manage the health condition of a user in real time from a remote location while reducing the burden on medical institutions.

[0894] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0895] Step 1:

[0896] Physiological information (heart rate, blood pressure, body temperature) is collected using wearable devices (smartwatches, blood pressure monitors, thermometers, etc.) worn by the user.

[0897] Specifically, when a user wears a smartwatch at 9:00 a.m., the smartwatch measures the user's heart rate (80 bpm), blood pressure (150 / 95 mmHg), and body temperature (36.8°C). The input is the user's physiological information, and the output is the collected physiological information data.

[0898] Step 2:

[0899] The terminal converts the collected physiological information into a digital format and transmits it to a server over the Internet.

[0900] Specifically, a smartwatch transmits the measured physiological information using Wi-Fi or a mobile network. The data is converted into a digital format and encrypted before being transmitted. The input is the collected physiological information data, and the output is the transmitted digital data.

[0901] Step 3:

[0902] The server receives the physiological information transmitted from the terminal and stores it in a database.

[0903] Specifically, AWS functions are used to receive data and store it in a database using Amazon RDS. The received data is first checked for consistency and then stored. The input is the transmitted digital data, and the output is the stored database entry.

[0904] Step 4:

[0905] An emotion engine analyzes physiological information and estimates the user's emotional state.

[0906] Specifically, an emotion analysis algorithm using Python and TensorFlow is executed to analyze the data. For example, if the heart rate fluctuates significantly, it is estimated as a "stressed state." The input is the accumulated physiological information data, and the output is the estimated emotional state data.

[0907] Step 5:

[0908] The server analyzes the stored physiological information and emotional state data and generates a primary diagnosis result.

[0909] Specifically, the system checks for abnormal values ​​in the data using data analysis libraries such as Python's numpy and pandas. For example, a blood pressure of 150 / 95 mmHg is judged to be an abnormal value and generates a medical examination result stating "Warning: Abnormal vital signs detected." The input is the accumulated physiological information data and emotional state data, and the output is the primary medical examination result.

[0910] Step 6:

[0911] The server notifies the physician of the generated primary examination results and emotional state data.

[0912] Specifically, the results are sent to the doctor's smartphone or web portal through a dedicated notification system such as PatientMonitoringApp. This notification includes the patient ID, physiological information, primary examination results, and emotional state data. The input is the primary examination results and emotional state data, and the output is the notification to the doctor.

[0913] Step 7:

[0914] The doctor will receive a notification, check the patient's condition, and respond promptly.

[0915] Specifically, the data displayed on a dedicated app or web portal is used to provide the necessary medical examinations and treatment. The input is the notified data, and the output is the appropriate medical response.

[0916] The specific operations for each step and the inputs and outputs for each step have been described above.

[0917] (Application example 2)

[0918] 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."

[0919] In modern society, health management for the elderly and single-person households is an important issue. In particular, sudden changes in physical condition or emotional states such as stress can pose serious health risks if not addressed promptly. Rapid response from medical institutions is also required, which requires real-time monitoring of physiological information and emotional states. However, conventional systems lack sufficient means to effectively acquire and analyze this data and promptly notify appropriate institutions when abnormalities are detected. Therefore, the present invention provides a system to solve these problems.

[0920] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0921] In this invention,

[0922] The server includes means for obtaining physiological information and emotional state from the user;

[0923] means for converting the acquired physiological information and emotional state into digital form and transmitting the digital information;

[0924] means for receiving and storing the transmitted physiological information and emotional state;

[0925] means for analyzing the accumulated physiological information and emotional state to generate a primary diagnosis result;

[0926] a means for notifying a doctor of the results of the initial examination;

[0927] a means of notifying emergency contacts if an abnormality is detected;

[0928] Includes.

[0929] This allows for real-time monitoring of the user's health and emotional state, and if an abnormality is detected, it will immediately notify a doctor or emergency contact, enabling a rapid response and improving the user's safety and peace of mind.

[0930] "Means for acquiring physiological information and emotional state from a user" refers to devices such as smart watches, blood pressure monitors, thermometers, and smartphones that are used to measure a user's physical condition and emotions.

[0931] "Means for converting physiological information and emotional state into digital form and transmitting it" refers to a technology for converting acquired physiological data and emotional data into digital data and transmitting it to a server using a communication means such as the Internet.

[0932] The "receiving and storing means" is a server unit including a main memory and a database that receives the digital data sent from the user's device and stores it in the long term.

[0933] The "means for analyzing and generating primary examination results" refers to a system that uses programs and algorithms to analyze accumulated data, detects abnormal values ​​and emotional states, and automatically generates primary examination results based on the results.

[0934] "Physician notification means" means a communication means for promptly notifying healthcare professionals of the results of the primary consultation and analyzed data, including email, SMS, or a dedicated application notification system.

[0935] "Means for notifying emergency contacts when an abnormality is detected" refers to a communication means for quickly sending an alert to pre-set emergency contacts (such as family members or nurses) when an abnormality is detected in the user's health condition.

[0936] The embodiments for carrying out the present invention will be described in detail below.

[0937] 1. Program Overview

[0938] The system of the present invention collects physiological information and emotional states from elderly and single-person users in real time, and provides the function of notifying emergency contacts if an abnormality is detected. The main hardware used includes smartwatches, blood pressure monitors, thermometers, and smartphones.

[0939] 2. Hardware and Software

[0940] The following hardware and software are used to operate the system:

[0941] Smartwatch: Collects heart rate, blood pressure, and temperature data.

[0942] Sphygmomanometer: Collects blood pressure data.

[0943] Thermometer: Collects temperature data.

[0944] Smartphone: Collects data, transmits data, displays analytics, and sends notifications.

[0945] Server: Responsible for data accumulation, analysis, generation of primary consultation results, and notification.

[0946] 3. Software Operation

[0947] Data collection and transmission

[0948] Smartwatches and other measuring devices (blood pressure monitors, thermometers) worn by users periodically collect daily physiological information and emotional states of users. This information is converted into digital format and transmitted to smartphones via communication methods such as Bluetooth and Wi-Fi. The smartphones then transmit this data to a server via the Internet.

[0949] Analyzing data and generating consultation results

[0950] The server stores the data and uses an analysis algorithm to detect abnormal values. Heart rate, blood pressure, and temperature data are used for analysis, and if an abnormal value is detected, a primary examination result is generated. For example, if the heart rate exceeds 100 bpm or blood pressure exceeds 140 / 90, it is marked as abnormal.

[0951] Emotional state analysis

[0952] The emotion engine analyzes the user's heart rate, body temperature fluctuations, blood pressure trends, etc. to estimate the user's emotional state. For example, if a sudden increase in heart rate or body temperature fluctuations is observed, it is assumed that this indicates stress or anxiety. This emotional state is also sent to the server and used to evaluate the user's overall health.

[0953] emergency notification

[0954] If an abnormality is detected, the server sends a notification to pre-defined emergency contacts (e.g., family members, doctors, nurses). The notification includes details of the abnormal value and an estimated emotional state. For example, if the heart rate spikes and the emotional state is estimated to be "stressed," this information will be sent to the emergency contacts.

[0955] Examples of concrete examples and prompts

[0956] For example, consider a user wearing a smartwatch. The smartwatch measures heart rate (e.g., 100 bpm), blood pressure (e.g., 150 / 95 mmHg), and body temperature (e.g., 37.5°C). This data is converted into digital format and sent to a server via the smartphone. The server analyzes the data, and if an abnormality is detected, it sends a notification saying, "Warning: Abnormal vital signs detected." Also, if the emotion engine estimates that the user is in a state of stress, this will also be included in the notification.

[0957] Here are some examples of prompts for an AI model:

[0958] Write a Python program that will send an email notification if the user's heart rate is abnormally high. The program will generate heart rate, blood pressure, and temperature data, and send a notification to a specified email address if it detects abnormal values. It should also include an emotion engine that estimates the user's emotional state (stressed, relaxed, etc.).

[0959] Thus, the present invention is a system that enables real-time monitoring of health and emotional states and rapid notification of abnormalities based thereon.

[0960] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0961] Step 1: Data collection

[0962] Input: User's heart rate, blood pressure, and temperature data

[0963] How it works: The smartwatch worn by the user, and the blood pressure monitor and thermometer used by the user, periodically collect data on the user's heart rate, blood pressure, and temperature. The smartwatch collects this data every day at 9:00 AM, for example.

[0964] Output: Collected physiological information

[0965] Step 2: Send data

[0966] Input: Physiological information collected from devices such as smartwatches

[0967] How it works: The device (such as a smartwatch) converts the collected physiological information into a digital format and transmits it to a smartphone using Bluetooth or Wi-Fi.

[0968] Output: Digital physiological information

[0969] Step 3: Transferring data to the server

[0970] Input: Digital physiological information received by a smartphone

[0971] How it works: The smartphone transmits physiological information to a server over the internet.

[0972] Output: Physiological information arriving at the server

[0973] Step 4: Data accumulation

[0974] Input: Physiological information arriving at the server

[0975] Operation: The server stores the received data in a database and manages it for each user.

[0976] Output: Physiological information stored in a database

[0977] Step 5: Data analysis

[0978] Input: Physiological information stored in a database

[0979] How it works: The server uses an analytical algorithm to analyze the accumulated data and detect abnormal values ​​such as heart rate, blood pressure, and body temperature. For example, blood pressure above 140 / 90 is considered abnormal.

[0980] Output: Analysis results and anomaly detection results

[0981] Step 6: Estimating emotional state

[0982] Input: Analyzed physiological information

[0983] How it works: The emotion engine uses analyzed heart rate, body temperature, and blood pressure fluctuation data to infer a user's emotional state, for example determining whether a sudden increase in heart rate indicates stress.

[0984] Output: Estimated emotional state

[0985] Step 7: Generate primary consultation results

[0986] Input: Analysis results, anomaly detection results, estimated emotional state

[0987] Operation: The server generates a primary diagnosis result based on these results, such as a message like "Warning: Abnormal vital signs detected" or "User is in a stressed state."

[0988] Output: First examination results

[0989] Step 8: Notify your doctor

[0990] Input: Primary examination results (anomaly detection results and estimated emotional state)

[0991] Operation: The server notifies the doctor of the generated primary consultation results through a notification system dedicated to the doctor.

[0992] Output: Initial consultation result notification sent to the doctor

[0993] Step 9: Emergency Notification

[0994] Input: Initial medical examination results, abnormality detection results, estimated emotional state

[0995] How it works: If an anomaly is detected, the server sends a warning notification to pre-defined emergency contacts (such as family members or nurses), including details of the anomaly and the patient's emotional state.

[0996] Output: Alert notification sent to emergency contacts

[0997] 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.

[0998] 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.

[0999] 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.

[1000] [Fourth embodiment]

[1001] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1002] 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.

[1003] 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).

[1004] 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.

[1005] 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.

[1006] 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).

[1007] 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. 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.

[1008] 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.

[1009] 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.

[1010] 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.

[1011] 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.

[1012] 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.

[1013] 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."

[1014] As an embodiment of the present invention, the following system is provided.

[1015] System Overview

[1016] The system of the present invention manages the health of elderly people and single-person households, obtaining physiological information (e.g., heart rate, blood pressure, body temperature, etc.) from users and providing this information to medical institutions to support home medical care.

[1017] Device behavior

[1018] The devices consist of a smartwatch worn by the user, a blood pressure monitor, a thermometer, etc. These devices periodically collect the user's daily physiological information. The collected data is converted into digital format and sent to a server via the Internet. For example, a smartwatch collects and transmits data such as the user's heart rate, blood pressure, and body temperature at 9:00 a.m. every day.

[1019] Server Operation

[1020] The server receives the physiological information sent from the device and stores it in a database. This database stores information for long-term monitoring of the user's health. The received data is analyzed, and if abnormal values ​​are detected, a primary diagnosis result is generated.

[1021] If the analysis detects an abnormal value, such as blood pressure exceeding 140, the server generates a primary diagnosis result such as "Warning: Abnormal vital signs have been detected." If the value is normal, the server generates a diagnosis result such as "All vital signs are normal."

[1022] Notify your doctor

[1023] The server notifies the doctor of the generated primary examination results and physiological information. This notification is sent via a notification system dedicated to doctors and includes the patient ID, physiological information, and details of the primary examination results. This notification allows doctors to quickly identify patients who require attention and prioritize their examinations.

[1024] Specific examples

[1025] Consider a case where user A is wearing a smartwatch. The smartwatch measures A's heart rate (80 bpm), blood pressure (150 / 95 mmHg), and body temperature (36.8°C) at 9:00 a.m. This data is automatically sent to the server.

[1026] The server stores and analyzes the received data. In this case, the blood pressure is abnormal (150 / 95 mmHg), so it generates a primary examination result stating "Warning: Abnormal vital signs detected." It then notifies the doctor of this result and the physiological information. The doctor receives this notification, checks Mr. A's condition, and takes the necessary measures promptly.

[1027] Results and Effects

[1028] This system allows doctors to monitor patients' health conditions in real time, enabling prompt medical examinations. It also allows users to easily manage their health at home, reducing the burden on medical institutions. This effectively solves the issues of doctor shortages and declining medical functions in rural areas.

[1029] The processing flow will be explained below.

[1030] Step 1:

[1031] The device collects physiological information from the user. Devices such as smartwatches worn by the user, blood pressure monitors, and thermometers used by the user periodically measure data such as heart rate, blood pressure, and body temperature.

[1032] Step 2:

[1033] The device converts the collected physiological information into a digital format. Software installed in devices such as smartwatches and blood pressure monitors converts the measurement data into a digital format, such as JSON.

[1034] Step 3:

[1035] The device then sends the converted digital data to a server over the Internet, specifically by using an HTTP POST request to send the data to a pre-configured server URL.

[1036] Step 4:

[1037] The server receives the digital data sent from the device. An API endpoint is set up on the server side, and this endpoint receives a POST request from the device.

[1038] Step 5:

[1039] The server stores the received digital data in a database. Specifically, it uses a database management system (DBMS) to store new measurement data for each user.

[1040] Step 6:

[1041] The server analyzes the accumulated data and detects abnormalities. Based on the analysis algorithm, it evaluates whether there are any abnormal values, such as blood pressure exceeding 140 or heart rate exceeding 100.

[1042] Step 7:

[1043] The server generates a primary diagnosis result based on the analysis results. If an abnormal value is detected, a warning message is generated, and if the value is normal, a diagnosis result stating "All vital signs are normal" is generated.

[1044] Step 8:

[1045] The server notifies the doctor of the initial examination results and physiological information by issuing an API request to a notification system dedicated to doctors and sending a notification including the patient ID, analysis results, physiological information, etc.

[1046] Step 9:

[1047] Doctors receive notifications from the server and check for abnormalities in patients, enabling them to respond quickly and prioritize patients who need medical attention.

[1048] Example 1

[1049] 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."

[1050] Health management for the elderly and single-person households requires a system that allows users to accurately and quickly grasp their own health status while at home and respond quickly when abnormalities occur. However, conventional systems often collect and analyze physiological information manually, making it difficult to respond quickly. In addition, there is a problem that doctors have difficulty understanding patients' conditions in real time due to insufficient collaboration with medical institutions.

[1051] 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.

[1052] In this invention, the server includes means for acquiring physiological information from a user, means for converting the acquired physiological information into digital format and transmitting it, means for receiving the transmitted physiological information and storing it in a database, means for analyzing the stored physiological information and automatically detecting abnormal values, means for generating a primary examination result based on the analysis result, and means for notifying a doctor of the primary examination result and the physiological information. This allows the physiological information collected by a user at home to be automatically analyzed, and if an abnormality is detected, the doctor will be promptly notified. This allows the doctor to grasp the patient's health condition in real time and to diagnose and respond promptly.

[1053] "User" refers to an individual who uses the service and is the subject of physiological information collection.

[1054] "Physiological information" refers to data that indicates the user's health condition, such as heart rate, blood pressure, and body temperature.

[1055] "Digital format" refers to a format in which physiological information is stored and transmitted electronically.

[1056] "Transmitting means" refers to the technical means for transferring the acquired physiological information in digital form to the server.

[1057] "Server" refers to a computer system that receives, stores, analyzes, and notifies data.

[1058] "Database" refers to a system for storing received physiological information as structured data.

[1059] "Means for analyzing" refers to the technical means for analyzing the accumulated physiological information and detecting abnormal values.

[1060] "Primary examination results" refers to initial diagnostic information regarding the user's health condition obtained through analysis.

[1061] "Means of notification" refers to the technical means for communicating the results of the primary examination and physiological information to the physician.

[1062] An "abnormal value" refers to a value of physiological information that deviates from a set normal range.

[1063] A "smartwatch" refers to a wearable device that periodically collects and transmits physiological information about the user.

[1064] A "sphygmomanometer" refers to a device that measures a user's blood pressure and acquires the data.

[1065] A "thermometer" refers to a device that measures a user's body temperature and acquires that data.

[1066] MODE FOR CARRYING OUT THE INVENTION

[1067] Overall system overview

[1068] The system of this invention supports home medical care by acquiring physiological information from elderly people and single-person households, appropriately analyzing it, and providing it to medical institutions. The system consists of a terminal worn by the user, a server that receives and analyzes the data, and a means for notifying doctors.

[1069] Device behavior

[1070] The terminals used include devices such as smartwatches, blood pressure monitors, and thermometers. These terminals automatically measure the user's physiological information (heart rate, blood pressure, body temperature, etc.) at regular intervals. The measured data is converted into digital format in real time and sent to a server via the Internet. For example, a smartwatch obtains and sends the following information every day at 9:00 AM:

[1071] Heart rate: 80 bpm

[1072] Blood pressure: 150 / 95 mmHg

[1073] Body temperature: 36.8℃

[1074] Server Operation

[1075] The server receives the physiological information sent from the device and stores it in a database. The database accumulates the user's health status over time, including past measurement data. This accumulated data is automatically analyzed using data analysis libraries such as Python and Pandas. During the analysis process, abnormal values ​​are detected based on a set algorithm.

[1076] Specifically, the received data is screened, and when abnormal values ​​are detected, such as blood pressure exceeding 140 / 90 mmHg, it is determined to be abnormal. Based on this determination, a primary medical examination result is generated. The following medical examination results are generated:

[1077] "Warning: Abnormal vital signs detected."

[1078] "All vital signs are normal."

[1079] Notify your doctor

[1080] The generated primary examination results and the user's physiological information are communicated to the doctor via a dedicated notification system. The notification includes the following information:

[1081] patient ID

[1082] Heart rate

[1083] blood pressure

[1084] body temperature

[1085] Examination results

[1086] For example, the following notification will be given:

[1087] Patient ID: UserA

[1088] Heart rate: 80 bpm

[1089] Blood pressure: 150 / 95 mmHg

[1090] Body temperature: 36.8℃

[1091] Examination results: Warning: Abnormal vital signs detected

[1092] Deployment Examples and Real-World Usage Scenarios

[1093] Consider the case where user A is wearing a smartwatch. The smartwatch measures A's heart rate (80 bpm), blood pressure (150 / 95 mmHg), and body temperature (36.8°C) at 9:00 a.m. and automatically sends this data to the server. The server accumulates and analyzes the data. In this case, because the blood pressure is abnormal (150 / 95 mmHg), the server generates a primary examination result stating "Warning: Abnormal vital signs detected" and notifies the doctor along with A's physiological information. The doctor receives this notification, checks A's condition, and takes any necessary measures promptly.

[1094] Prompt Sentence Examples

[1095] "Please explain the health care system for the elderly. Please be specific about which devices collect what data, how that data is analyzed on the server, and how the doctor is notified. Also, please give specific examples of users."

[1096] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1097] Step 1: The user wears a device such as a smartwatch, blood pressure monitor, or thermometer to collect physiological information. The input is physiological data such as the user's heart rate, blood pressure, and body temperature. The output is this data converted into digital form. For example, the smartwatch measures the user's heart rate as 80 bpm, blood pressure as 150 / 95 mmHg, and body temperature as 36.8°C.

[1098] Step 2: The device converts the acquired physiological information into a digital format and sends it to a server via the Internet. The input is the digitized physiological data. The output is the data sent to the server via the Internet. For example, a smartwatch sends the measured values ​​to the server as packet data.

[1099] Step 3: The server receives the physiological information sent from the device and stores it in a database. The input is the physiological data sent from the device. The output is the physiological data stored in the database. For example, the server saves the data received in an SQL database.

[1100] Step 4: The server analyzes the accumulated data. The input is the physiological data stored in the database. The output is the analysis results. This analysis uses Python and the Pandas library to detect outliers. For example, the server analyzes the accumulated blood pressure data and extracts outliers where the blood pressure exceeds 140 / 90 mmHg.

[1101] Step 5: The server generates a primary medical examination result based on the analysis result. The input is the analysis result. The output is the primary medical examination result. For example, if the blood pressure is abnormal (150 / 95 mmHg), the server generates a medical examination result saying "Warning: Abnormal vital signs detected."

[1102] Step 6: The server notifies the doctor of the generated primary examination results and the user's physiological information. The input is the primary examination results and physiological data. The output is the notification sent to the doctor. For example, a notification such as "Patient ID: UserA, Heart rate: 80 bpm, Blood pressure: 150 / 95 mmHg, Body temperature: 36.8℃, Examination results: Warning: Abnormal vital signs detected" is sent to the doctor.

[1103] (Application example 1)

[1104] 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."

[1105] The purpose of this invention is to improve the quality of home medical care for the elderly and single-person households, while also reducing the burden on doctors. In particular, it is important to provide a rapid response to sudden changes in health conditions and to implement comprehensive safety measures in cooperation with security services.

[1106] 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.

[1107] In this invention, the server includes a means for acquiring physiological information from a user, a means for converting the acquired physiological information into a digital format and transmitting it, a means for receiving and storing the transmitted physiological information, a means for analyzing the stored physiological information and generating a primary examination result, and a means for notifying a doctor and a security service of the primary examination result. This makes it possible to grasp changes in the health status of elderly people and single-person households in real time and take prompt and appropriate measures if necessary. Furthermore, by linking with a security service, it is possible to ensure the overall safety of elderly people and single-person households.

[1108] "Means for acquiring physiological information from a user" refers to means for collecting physiological data such as heart rate, blood pressure, and body temperature through a device worn or used by the user.

[1109] The "means for converting the acquired physiological information into a digital format and transmitting it" refers to a means for converting the collected physiological data into digital data and transmitting it to a server.

[1110] The "means for receiving and storing the transmitted physiological information" refers to a means for receiving the transmitted digital data on the server side and storing it in a database or the like.

[1111] The "means for analyzing the accumulated physiological information and generating initial examination results" refers to a means for detecting abnormal values ​​in the data using an algorithm that analyzes the stored physiological data and generates initial examination results.

[1112] The "means for notifying the doctor and security service of the primary examination results" refers to a means for notifying the doctor and, if necessary, the security service of the generated primary examination results.

[1113] This invention is a system that monitors the health of elderly people and single-person households in real time and notifies doctors and security services if abnormal values ​​are detected. The system consists of devices worn by users, such as smart watches, blood pressure monitors, and thermometers, and a server that receives and analyzes data sent from these devices.

[1114] Hardware and Software Details

[1115] Hardware

[1116] User devices: Devices worn by users, such as smartwatches (e.g., Apple Watch and Fitbit), blood pressure monitors, and thermometers. These devices collect users' daily physiological information (e.g., heart rate, blood pressure, body temperature, etc.).

[1117] Server: The server is responsible for storing and analyzing the received data. It includes a high-performance database server and network equipment for sending notifications to doctors and security services based on the analysis results.

[1118] software

[1119] Data collection and transmission software: Software installed in the smartwatch or thermometer converts physiological information into a digital format and periodically transmits it to a server.

[1120] Data storage software: Software on the server side for storing received data in a database.

[1121] Data analysis software: Using an analysis algorithm (e.g., an analysis program written in Python or R), abnormal values ​​in physiological information are detected and primary examination results are generated.

[1122] Notification software: Software for automatically notifying doctors and security services of the generated primary examination results and physiological information.

[1123] System operation example

[1124] For example, if user A is wearing a smartwatch, the smartwatch will measure A's heart rate, blood pressure, body temperature, etc. every morning at 9:00 a.m. The measured data is automatically converted into digital format and sent to a server via the Internet. Upon receiving this data, the server stores it in a database and begins analysis. If the analysis detects an abnormal value, such as a blood pressure of 150 / 95 mmHg, a primary examination result will be generated stating, "Warning: Abnormal vital signs detected." This result is automatically sent to a notification system and security service dedicated to doctors. The doctors and security services will receive this notification and be able to respond promptly to the user's health condition.

[1125] Prompt Sentence Examples

[1126] "Design a system to monitor the health status of elderly people and notify doctors and security services if any abnormalities are detected. The device measures heart rate, blood pressure, and temperature, converts them into digital format, and transmits them. The server receives, stores, and analyzes these data. If any abnormal values ​​are detected based on the analysis results, it generates a primary examination result and notifies doctors and security services."

[1127] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1128] Step 1:

[1129] Devices worn by users, such as smartwatches, blood pressure monitors, and thermometers, periodically collect physiological information such as the user's heart rate, blood pressure, and body temperature. Specifically, the smartwatch automatically measures the heart rate, blood pressure, and body temperature every morning at 9:00. The input is physiological data obtained from each device, and the output is physiological data converted into digital format.

[1130] Step 2:

[1131] The device converts the collected physiological data into digital format and sends it to a server via the Internet. Specifically, the data measured by the smartwatch is converted into digital format by the internal software and sent to the server via Wi-Fi or 4G / 5G communication. The input is physiological data acquired in analog format, and the output is digital data sent to the server.

[1132] Step 3:

[1133] The server receives the digital physiological data sent from the terminal and stores it in a database. Specifically, a program that stores the received data in the database runs, and the data storage is completed. The input is the transmitted digital data, and the output is the physiological data stored in the database.

[1134] Step 4:

[1135] The server launches an analysis algorithm to analyze the accumulated physiological data. The analysis algorithm is used to detect abnormal values ​​in the data and generate a primary examination result. Specifically, the analysis algorithm, written in a programming language such as Python, scans the data and detects abnormal values. The input is the physiological data stored in the database, and the output is the primary examination result.

[1136] Step 5:

[1137] The server notifies the doctor and security service of the generated primary examination results. Specifically, it sends a notification to a doctor-specific notification system and security service API based on the generated primary examination results. The input is the primary examination results, and the output is the notification sent to the doctor and security service.

[1138] 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.

[1139] As an embodiment of the present invention, the following system is provided.

[1140] System Overview

[1141] The system of the present invention manages the health of elderly people and single-person households, and supports home medical care by acquiring physiological information (e.g., heart rate, blood pressure, body temperature, etc.) from the user and providing it to medical institutions. This system also incorporates an emotion engine that recognizes the user's emotional state, allowing it to grasp the user's overall health condition.

[1142] Device behavior

[1143] The devices consist of a smartwatch worn by the user, a blood pressure monitor, a thermometer, etc. These devices periodically collect the user's daily physiological information. The collected data is converted into digital format and sent to a server via the Internet. For example, a smartwatch collects and transmits data such as the user's heart rate, blood pressure, and body temperature at 9:00 a.m. every day.

[1144] Emotion Engine Operation

[1145] The emotion engine analyzes the user's physiological information to estimate their emotional state. Specifically, it analyzes heart rate, body temperature fluctuations, blood pressure trends, etc. to estimate whether the user is stressed, relaxed, or in some other emotional state. This emotional state data is also sent to the server and used to notify the doctor.

[1146] Server Operation

[1147] The server receives the physiological and emotional state data sent from the device and stores it in a database, which stores information for long-term health monitoring of the user. The received data is analyzed, and if abnormal values ​​are detected, a preliminary diagnosis result is generated.

[1148] If the analysis detects an abnormal value, such as blood pressure exceeding 140, the server generates a primary diagnosis result stating "Warning: Abnormal vital signs have been detected." If the result is normal, the server generates a diagnosis result stating "All vital signs are normal." The analysis also includes the results of the emotion engine, such as information such as "The user is in a state of stress."

[1149] Notify your doctor

[1150] The server notifies the doctor of the generated primary examination results, physiological information, and emotional state data. This notification is sent via a notification system dedicated to doctors and includes the patient ID, physiological information, details of the primary examination results, and emotional state data. This notification allows doctors to quickly identify patients who require attention and prioritize their examinations.

[1151] Specific examples

[1152] Consider a case where user A is wearing a smartwatch. The smartwatch measures A's heart rate (80 bpm), blood pressure (150 / 95 mmHg), and body temperature (36.8°C) at 9:00 a.m. This data is automatically sent to the server.

[1153] The server accumulates and analyzes the received data. In this case, because the blood pressure is abnormal (150 / 95 mmHg), it generates a primary examination result stating, "Warning: Abnormal vital signs detected." The emotion engine also recognizes that Person A is in a stressful state and generates data stating, "User is in a stressful state." This result and the physiological information are then notified to the doctor. The doctor receives this notification, checks Person A's condition, and takes the necessary measures promptly.

[1154] Results and Effects

[1155] This system allows doctors to monitor patients' health and emotional status in real time, enabling prompt medical examinations. It also allows users to easily manage their health at home, reducing the burden on medical institutions. This effectively addresses the issues of a shortage of doctors and declining medical capabilities in rural areas.

[1156] The processing flow will be explained below.

[1157] Step 1:

[1158] The device collects physiological information from the user. Devices such as smartwatches worn by the user, blood pressure monitors, and thermometers used by the user periodically measure data such as heart rate, blood pressure, and body temperature.

[1159] Step 2:

[1160] The device converts the collected physiological information into a digital format. Software installed in devices such as smartwatches and blood pressure monitors converts the measurement data into a digital format, such as JSON.

[1161] Step 3:

[1162] The device then sends the converted digital data to a server over the Internet, specifically by using an HTTP POST request to send the data to a pre-configured server URL.

[1163] Step 4:

[1164] The server receives the digital data sent from the device. An API endpoint is set up on the server side, and this endpoint receives a POST request from the device.

[1165] Step 5:

[1166] The server stores the received digital data in a database. Specifically, it uses a database management system (DBMS) to store new measurement data for each user.

[1167] Step 6:

[1168] The server analyzes the accumulated data and detects abnormalities. Based on the analysis algorithm, it evaluates whether there are any abnormal values, such as blood pressure exceeding 140 or heart rate exceeding 100.

[1169] Step 7:

[1170] The server generates a primary diagnosis result based on the analysis results. If an abnormal value is detected, a warning message is generated, and if the value is normal, a diagnosis result stating "All vital signs are normal" is generated.

[1171] Step 8:

[1172] The emotion engine analyzes the received physiological information and estimates the user's emotional state. For example, it can recognize whether the user is stressed or relaxed based on heart rate fluctuations and blood pressure patterns.

[1173] Step 9:

[1174] The server generates emotional state data based on the results of the emotion engine. Specifically, if the server determines that the user is in a stressful state, it generates data such as "Warning: User is in a stressful state."

[1175] Step 10:

[1176] The server notifies the doctor of the primary examination results, physiological information, and emotional state data via a dedicated notification system for the doctor, and includes the patient ID, physiological information, details of the primary examination results, and emotional state data.

[1177] Step 11:

[1178] Doctors receive notifications from the server and check for abnormal patients and their emotional states, allowing them to respond to patients who need prompt and prioritized medical attention.

[1179] Example 2

[1180] 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."

[1181] In modern society, health management for the elderly and single-person households has become a serious issue. These people often find it difficult to visit a medical institution, leading to neglect of daily health management. Medical institutions are also required to efficiently manage a large number of patients with limited resources. Therefore, there is a need for a system that can remotely monitor users' health and emotional states in real time and provide prompt, necessary responses.

[1182] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1183] In this invention, the server includes means for acquiring physiological information from a user, means for converting the acquired physiological information into a digital format and transmitting it, means for receiving and storing the transmitted physiological information, means for analyzing the stored physiological information and generating a primary examination result, means for inferring an emotional state based on the user's physiological information, means for receiving and analyzing the emotional state data, and means for notifying a doctor of the primary examination result and the emotional state data. This allows users to easily manage their health at home and doctors to monitor the health and emotional states of patients in real time, thereby realizing prompt examination and treatment.

[1184] A "user" is a person who utilizes the system to provide physiological information.

[1185] "Physiological information" is data that indicates the user's health condition, such as heart rate, blood pressure, and body temperature.

[1186] "Means of acquisition" refers to methods of obtaining physiological information using a smartwatch, blood pressure monitor, thermometer, etc.

[1187] "Digital format" means that the collected physiological information is in a format that can be processed as electronic data.

[1188] The "means for transmitting" is a method for transmitting the physiological information converted into digital form to the server.

[1189] The "means for receiving and storing" refers to the method by which the server receives the transmitted physiological information and stores it in a database.

[1190] The "means for analyzing and generating initial diagnostic results" refers to a method for analyzing physiological information and generating initial diagnostic information based on the results.

[1191] The "means for inferring emotional state" is a method for inferring the user's emotional state by analyzing fluctuations in heart rate and body temperature.

[1192] "Emotional state data" is information about the user's emotions obtained through analysis.

[1193] "Means of notification" refers to the method by which the primary examination results and emotional state data are communicated to the physician.

[1194] A "doctor" is a professional who makes a diagnosis and responds based on the notified data.

[1195] MODE FOR CARRYING OUT THE INVENTION

[1196] This invention is a system for managing the health of elderly people and single-person households, and supports home medical care by acquiring physiological information from users and providing it to medical institutions. This system acquires physiological information (e.g., heart rate, blood pressure, body temperature, etc.) from users and includes a function to infer their emotional state based on that data.

[1197] System configuration

[1198] This system consists of a terminal that acquires physiological information from a wearable device worn by the user, a means for converting the acquired data into digital format and transmitting it, a server that stores and analyzes the received data to generate the results of the initial examination, an emotion analysis engine that estimates the emotional state, and a means for notifying the doctor of the results.

[1199] Device behavior

[1200] The terminals are smartwatches worn by users, blood pressure monitors, thermometers, etc. These devices periodically collect daily physiological information from users. Specifically, smartwatches and fitness trackers are used as wearable devices. These devices measure data such as the user's heart rate, blood pressure, and body temperature, and convert it into digital format. For example, if a user wears a smartwatch at 9:00 a.m., the smartwatch will measure the user's heart rate (80 bpm), blood pressure (150 / 95 mmHg), and body temperature (36.8°C) and send the data to a server.

[1201] How the sentiment analysis engine works

[1202] The emotion engine is built using Python and machine learning frameworks such as TensorFlow. The engine analyzes fluctuations in the user's heart rate, body temperature, and blood pressure to estimate the user's emotional state. For example, a sudden increase in heart rate is assumed to indicate the user's stress level. This emotional state data is also sent to the server.

[1203] Server Operation

[1204] The server was built using AWS (Amazon Web Services) and receives physiological information and emotional state data sent from the device and stores it in a database. The database uses Amazon RDS. The server analyzes the received data and generates a primary examination result if an abnormal value is detected. Processing is carried out using Python and data analysis libraries such as numpy and pandas. For example, if the user's blood pressure is abnormal at 150 / 95 mmHg, the primary examination result will be "Warning: Abnormal vital signs detected." In addition, based on the results of the emotion engine, the server adds information that "the user is in a state of stress."

[1205] Notify your doctor

[1206] The server notifies doctors of the generated initial examination results, physiological information, and emotional state data. This notification is done through a dedicated app such as PatientMonitoringApp or a web portal, and also includes an alert function. The notification includes the patient ID, physiological information, details of the initial examination results, and emotional state data. This allows doctors to quickly identify patients who require attention and prioritize their examinations.

[1207] Specific examples

[1208] A user puts on a smartwatch at 9am and collects the following data:

[1209] Heart rate: 80 bpm

[1210] Blood pressure: 150 / 95mmHg

[1211] Body temperature: 36.8℃

[1212] This data is automatically sent to the server, and if an abnormal heart rate or blood pressure is detected through analysis, a primary diagnosis result such as "Warning: Abnormal vital signs detected" and emotional state data such as "User is in a state of stress" are generated. These results are then notified to a doctor, who can then take prompt action.

[1213] Prompt Sentence Examples

[1214] By inputting the following prompt sentence into the generative AI model, abnormal values ​​can be detected and a primary examination result can be generated.

[1215] "Detect abnormal values ​​based on the following data and generate a primary examination result: Heart rate: 80 bpm, Blood pressure: 150 / 95 mmHg, Body temperature: 36.8°C, Emotional state: Stress"

[1216] As described above, the present invention provides a system that can monitor and manage the health condition of a user in real time from a remote location while reducing the burden on medical institutions.

[1217] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1218] Step 1:

[1219] Physiological information (heart rate, blood pressure, body temperature) is collected using wearable devices (smartwatches, blood pressure monitors, thermometers, etc.) worn by the user.

[1220] Specifically, when a user wears a smartwatch at 9:00 a.m., the smartwatch measures the user's heart rate (80 bpm), blood pressure (150 / 95 mmHg), and body temperature (36.8°C). The input is the user's physiological information, and the output is the collected physiological information data.

[1221] Step 2:

[1222] The terminal converts the collected physiological information into a digital format and transmits it to a server over the Internet.

[1223] Specifically, a smartwatch transmits the measured physiological information using Wi-Fi or a mobile network. The data is converted into a digital format and encrypted before being transmitted. The input is the collected physiological information data, and the output is the transmitted digital data.

[1224] Step 3:

[1225] The server receives the physiological information transmitted from the terminal and stores it in a database.

[1226] Specifically, AWS functions are used to receive data and store it in a database using Amazon RDS. The received data is first checked for consistency and then stored. The input is the transmitted digital data, and the output is the stored database entry.

[1227] Step 4:

[1228] An emotion engine analyzes physiological information and estimates the user's emotional state.

[1229] Specifically, an emotion analysis algorithm using Python and TensorFlow is executed to analyze the data. For example, if the heart rate fluctuates significantly, it is estimated as a "stressed state." The input is the accumulated physiological information data, and the output is the estimated emotional state data.

[1230] Step 5:

[1231] The server analyzes the stored physiological information and emotional state data and generates a primary diagnosis result.

[1232] Specifically, the system checks for abnormal values ​​in the data using data analysis libraries such as Python's numpy and pandas. For example, a blood pressure of 150 / 95 mmHg is judged to be an abnormal value and generates a medical examination result stating "Warning: Abnormal vital signs detected." The input is the accumulated physiological information data and emotional state data, and the output is the primary medical examination result.

[1233] Step 6:

[1234] The server notifies the physician of the generated primary examination results and emotional state data.

[1235] Specifically, the results are sent to the doctor's smartphone or web portal through a dedicated notification system such as PatientMonitoringApp. This notification includes the patient ID, physiological information, primary examination results, and emotional state data. The input is the primary examination results and emotional state data, and the output is the notification to the doctor.

[1236] Step 7:

[1237] The doctor will receive a notification, check the patient's condition, and respond promptly.

[1238] Specifically, the data displayed on a dedicated app or web portal is used to provide the necessary medical examinations and treatment. The input is the notified data, and the output is the appropriate medical response.

[1239] The specific operations for each step and the inputs and outputs for each step have been described above.

[1240] (Application example 2)

[1241] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1242] In modern society, health management for the elderly and single-person households is an important issue. In particular, sudden changes in physical condition or emotional states such as stress can pose serious health risks if not addressed promptly. Rapid response from medical institutions is also required, which requires real-time monitoring of physiological information and emotional states. However, conventional systems lack sufficient means to effectively acquire and analyze this data and promptly notify appropriate institutions when abnormalities are detected. Therefore, the present invention provides a system to solve these problems.

[1243] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1244] In this invention,

[1245] The server includes means for obtaining physiological information and emotional state from the user;

[1246] means for converting the acquired physiological information and emotional state into digital form and transmitting the digital information;

[1247] means for receiving and storing the transmitted physiological information and emotional state;

[1248] means for analyzing the accumulated physiological information and emotional state to generate a primary diagnosis result;

[1249] a means for notifying a doctor of the results of the initial examination;

[1250] a means of notifying emergency contacts if an abnormality is detected;

[1251] Includes.

[1252] This allows for real-time monitoring of the user's health and emotional state, and if an abnormality is detected, it will immediately notify a doctor or emergency contact, enabling a rapid response and improving the user's safety and peace of mind.

[1253] "Means for acquiring physiological information and emotional state from a user" refers to devices such as smart watches, blood pressure monitors, thermometers, and smartphones that are used to measure a user's physical condition and emotions.

[1254] "Means for converting physiological information and emotional state into digital form and transmitting it" refers to a technology for converting acquired physiological data and emotional data into digital data and transmitting it to a server using a communication means such as the Internet.

[1255] The "receiving and storing means" is a server unit including a main memory and a database that receives the digital data sent from the user's device and stores it in the long term.

[1256] The "means for analyzing and generating primary examination results" refers to a system that uses programs and algorithms to analyze accumulated data, detects abnormal values ​​and emotional states, and automatically generates primary examination results based on the results.

[1257] "Physician notification means" means a communication means for promptly notifying healthcare professionals of the results of the primary consultation and analyzed data, including email, SMS, or a dedicated application notification system.

[1258] "Means for notifying emergency contacts when an abnormality is detected" refers to a communication means for quickly sending an alert to pre-set emergency contacts (such as family members or nurses) when an abnormality is detected in the user's health condition.

[1259] The embodiments for carrying out the present invention will be described in detail below.

[1260] 1. Program Overview

[1261] The system of the present invention collects physiological information and emotional states from elderly and single-person users in real time, and provides the function of notifying emergency contacts if an abnormality is detected. The main hardware used includes smartwatches, blood pressure monitors, thermometers, and smartphones.

[1262] 2. Hardware and Software

[1263] The following hardware and software are used to operate the system:

[1264] Smartwatch: Collects heart rate, blood pressure, and temperature data.

[1265] Sphygmomanometer: Collects blood pressure data.

[1266] Thermometer: Collects temperature data.

[1267] Smartphone: Collects data, transmits data, displays analytics, and sends notifications.

[1268] Server: Responsible for data accumulation, analysis, generation of primary consultation results, and notification.

[1269] 3. Software Operation

[1270] Data collection and transmission

[1271] Smartwatches and other measuring devices (blood pressure monitors, thermometers) worn by users periodically collect daily physiological information and emotional states of users. This information is converted into digital format and transmitted to smartphones via communication methods such as Bluetooth and Wi-Fi. The smartphones then transmit this data to a server via the Internet.

[1272] Analyzing data and generating consultation results

[1273] The server stores the data and uses an analysis algorithm to detect abnormal values. Heart rate, blood pressure, and temperature data are used for analysis, and if an abnormal value is detected, a primary examination result is generated. For example, if the heart rate exceeds 100 bpm or blood pressure exceeds 140 / 90, it is marked as abnormal.

[1274] Emotional state analysis

[1275] The emotion engine analyzes the user's heart rate, body temperature fluctuations, blood pressure trends, etc. to estimate the user's emotional state. For example, if a sudden increase in heart rate or body temperature fluctuations is observed, it is assumed that this indicates stress or anxiety. This emotional state is also sent to the server and used to evaluate the user's overall health.

[1276] emergency notification

[1277] If an abnormality is detected, the server sends a notification to pre-defined emergency contacts (e.g., family members, doctors, nurses). The notification includes details of the abnormal value and an estimated emotional state. For example, if the heart rate spikes and the emotional state is estimated to be "stressed," this information will be sent to the emergency contacts.

[1278] Examples of concrete examples and prompts

[1279] For example, consider a user wearing a smartwatch. The smartwatch measures heart rate (e.g., 100 bpm), blood pressure (e.g., 150 / 95 mmHg), and body temperature (e.g., 37.5°C). This data is converted into digital format and sent to a server via the smartphone. The server analyzes the data, and if an abnormality is detected, it sends a notification saying, "Warning: Abnormal vital signs detected." Also, if the emotion engine estimates that the user is in a state of stress, this will also be included in the notification.

[1280] Here are some examples of prompts for an AI model:

[1281] Write a Python program that will send an email notification if the user's heart rate is abnormally high. The program will generate heart rate, blood pressure, and temperature data, and send a notification to a specified email address if it detects abnormal values. It should also include an emotion engine that estimates the user's emotional state (stressed, relaxed, etc.).

[1282] Thus, the present invention is a system that enables real-time monitoring of health and emotional states and rapid notification of abnormalities based thereon.

[1283] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1284] Step 1: Data collection

[1285] Input: User's heart rate, blood pressure, and temperature data

[1286] How it works: The smartwatch worn by the user, and the blood pressure monitor and thermometer used by the user, periodically collect data on the user's heart rate, blood pressure, and temperature. The smartwatch collects this data every day at 9:00 AM, for example.

[1287] Output: Collected physiological information

[1288] Step 2: Send data

[1289] Input: Physiological information collected from devices such as smartwatches

[1290] How it works: The device (such as a smartwatch) converts the collected physiological information into a digital format and transmits it to a smartphone using Bluetooth or Wi-Fi.

[1291] Output: Digital physiological information

[1292] Step 3: Transferring data to the server

[1293] Input: Digital physiological information received by a smartphone

[1294] How it works: The smartphone transmits physiological information to a server over the internet.

[1295] Output: Physiological information arriving at the server

[1296] Step 4: Data accumulation

[1297] Input: Physiological information arriving at the server

[1298] Operation: The server stores the received data in a database and manages it for each user.

[1299] Output: Physiological information stored in a database

[1300] Step 5: Data analysis

[1301] Input: Physiological information stored in a database

[1302] How it works: The server uses an analytical algorithm to analyze the accumulated data and detect abnormal values ​​such as heart rate, blood pressure, and body temperature. For example, blood pressure above 140 / 90 is considered abnormal.

[1303] Output: Analysis results and anomaly detection results

[1304] Step 6: Estimating emotional state

[1305] Input: Analyzed physiological information

[1306] How it works: The emotion engine uses analyzed heart rate, body temperature, and blood pressure fluctuation data to infer a user's emotional state, for example determining whether a sudden increase in heart rate indicates stress.

[1307] Output: Estimated emotional state

[1308] Step 7: Generate primary consultation results

[1309] Input: Analysis results, anomaly detection results, estimated emotional state

[1310] Operation: The server generates a primary diagnosis result based on these results, such as a message like "Warning: Abnormal vital signs detected" or "User is in a stressed state."

[1311] Output: First examination results

[1312] Step 8: Notify your doctor

[1313] Input: Primary examination results (anomaly detection results and estimated emotional state)

[1314] Operation: The server notifies the doctor of the generated primary consultation results through a notification system dedicated to the doctor.

[1315] Output: Initial consultation result notification sent to the doctor

[1316] Step 9: Emergency Notification

[1317] Input: Initial medical examination results, abnormality detection results, estimated emotional state

[1318] How it works: If an anomaly is detected, the server sends a warning notification to pre-defined emergency contacts (such as family members or nurses), including details of the anomaly and the patient's emotional state.

[1319] Output: Alert notification sent to emergency contacts

[1320] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1321] 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.

[1322] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1323] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1324] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1325] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1326] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1327] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1328] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1329] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1330] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1331] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1332] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1333] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1334] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1335] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1336] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1337] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1338] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1339] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1340] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1341] The following is further disclosed regarding the above embodiment.

[1342] (Claim 1)

[1343] means for acquiring physiological information from a user;

[1344] means for converting the acquired physiological information into a digital format and transmitting the digital information;

[1345] means for receiving and storing the transmitted physiological information;

[1346] means for analyzing the accumulated physiological information and generating a primary diagnosis result;

[1347] a means for notifying a doctor of the results of the initial examination;

[1348] A system including:

[1349] (Claim 2)

[1350] 10. The system of claim 1, wherein the means for acquiring physiological information from the user includes a smart watch, a blood pressure monitor, or a thermometer.

[1351] (Claim 3)

[1352] 10. The system of claim 1, wherein the means for generating the primary diagnosis results uses analytical algorithms to detect abnormal values ​​of blood pressure and heart rate.

[1353] "Example 1"

[1354] (Claim 1)

[1355] means for acquiring physiological information from a user;

[1356] means for converting the acquired physiological information into a digital format and transmitting the digital information;

[1357] means for receiving the transmitted physiological information and storing it in a database;

[1358] means for analyzing the accumulated physiological information and automatically detecting abnormal values;

[1359] A means for generating a primary diagnosis result based on the analysis result;

[1360] means for notifying a doctor of the primary examination results and physiological information;

[1361] A system including:

[1362] (Claim 2)

[1363] 10. The system of claim 1, further comprising means for acquiring physiological information from a user, the means including a smartwatch, a blood pressure monitor, or a thermometer.

[1364] (Claim 3)

[1365] 10. The system of claim 1, further comprising means for detecting abnormal values ​​of blood pressure and heart rate using analytical algorithms.

[1366] "Application Example 1"

[1367] (Claim 1)

[1368] means for acquiring physiological information from a user;

[1369] means for converting the acquired physiological information into a digital format and transmitting the digital information;

[1370] means for receiving and storing the transmitted physiological information;

[1371] means for analyzing the accumulated physiological information and generating a primary diagnosis result;

[1372] means for notifying a doctor and security services of the results of said initial examination;

[1373] A system including:

[1374] (Claim 2)

[1375] 10. The system of claim 1, wherein the means for acquiring physiological information from the user includes a smartwatch, a blood pressure monitor, or a thermometer.

[1376] (Claim 3)

[1377] 10. The system of claim 1, wherein the means for generating the primary diagnosis results uses analytical algorithms to detect abnormal values ​​in blood pressure and heart rate.

[1378] "Example 2: Combining Emotion Engines"

[1379] (Claim 1)

[1380] means for acquiring physiological information from a user;

[1381] means for converting the acquired physiological information into a digital format and transmitting the digital information;

[1382] means for receiving and storing the transmitted physiological information;

[1383] means for analyzing the accumulated physiological information and generating a primary diagnosis result;

[1384] means for inferring an emotional state of a user based on physiological information;

[1385] means for receiving and analyzing said emotional state data;

[1386] means for notifying a physician of the primary examination results and emotional state data;

[1387] A system including:

[1388] (Claim 2)

[1389] The system of claim 1 , wherein the means for acquiring physiological information from the user includes a wearable device, a blood pressure monitor, or a thermometer.

[1390] (Claim 3)

[1391] 2. The system according to claim 1, wherein the means for generating the primary diagnosis results uses an analysis algorithm to detect abnormal values ​​in the physiological information.

[1392] "Application example 2 when combining emotion engines"

[1393] (Claim 1)

[1394] means for acquiring physiological information and emotional state from a user;

[1395] means for converting the acquired physiological information and emotional state into digital form and transmitting the digital information;

[1396] means for receiving and storing the transmitted physiological information and emotional state;

[1397] means for analyzing the accumulated physiological information and emotional state to generate a primary diagnosis result;

[1398] a means for notifying a doctor of the results of the initial examination;

[1399] a means of notifying emergency contacts if an abnormality is detected;

[1400] A system including:

[1401] (Claim 2)

[1402] 10. The system of claim 1, comprising means for acquiring physiological information and emotional state from a user, the means including a smartwatch, a blood pressure monitor, a thermometer, or a smartphone.

[1403] (Claim 3)

[1404] 10. The system of claim 1, further comprising means for detecting abnormal values ​​of physiological information and emotional state using analytical algorithms and notifying emergency contacts. [Explanation of symbols]

[1405] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for acquiring physiological information from a user; means for converting the acquired physiological information into a digital format and transmitting the digital information; means for receiving and storing the transmitted physiological information; means for analyzing the accumulated physiological information and generating a primary diagnosis result; a means for notifying a doctor of the results of the initial examination; A system including:

2. The system according to claim 1 , wherein the means for acquiring physiological information from the user includes a smart watch, a blood pressure monitor, or a thermometer.

3. 2. The system of claim 1, wherein the means for generating the primary diagnosis results uses analytical algorithms to detect abnormal values ​​of blood pressure and heart rate.

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