System

Abstract

A system is provided.SOLUTION: A system comprising: means for collecting health information of a subject from a sensor; means for analyzing the collected health information and detecting an abnormality; means for notifying a medical facility if an abnormality is detected; means for generating a dietary plan based on the health information; means for suggesting the generated dietary plan; means for generating and distributing content based on the subject's hobbies and interests; and means for monitoring location information and notifying when the subject is out.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] As our society ages, the number of elderly people requiring nursing care is increasing. However, current nursing care services face many problems, placing a heavy burden on caregivers and resulting in a lack of support for elderly people to live a high quality of life. Specific issues include inadequate health management, inability to provide appropriate meals, and feelings of loneliness and lack of daily enjoyment among the elderly. There is a need to resolve these issues and improve the quality of life for the elderly. [Means for solving the problem]

[0005] To solve the above problems, the present invention provides the following means. First, a means for collecting a subject's health information from sensors is installed, and the subject's health condition is monitored in real time. Next, a means for analyzing the collected health information and promptly notifying a medical facility if an abnormality is detected is incorporated. Furthermore, a means for generating and proposing an individualized meal plan based on the health information is added. Also, a means for ordering food from a delivery service based on the generated meal plan is provided, providing appropriate meals to the elderly. In addition, a means for generating and distributing content tailored to the subject's hobbies and interests is provided, providing daily enjoyment. Finally, a means for monitoring the subject's location when going out and providing timely notifications to ensure safety is implemented, thereby building a comprehensive nursing care support system. This reduces the burden on caregivers and enables the elderly to live a higher quality of life.

[0006] "Subject's health information" refers to data regarding the subject's physical condition, such as vital signs such as blood pressure, heart rate, body temperature, and respiratory rate, as well as other physiological indicators.

[0007] A "sensor" is a device for detecting and collecting health information of a subject, and includes wearable devices and embedded systems.

[0008] "Analysis" is the act of processing and evaluating collected data, a process that uses algorithms to identify significant patterns or anomalies in the data.

[0009] "Notifying a medical facility" means that if an abnormality is detected, the subject's health information will be promptly transmitted to a medical institution or nursing facility.

[0010] A "meal plan" is a meal plan suggested based on the subject's health status, taking into account calories, nutritional content, types of food, etc.

[0011] "Content" refers to information or media provided based on the subject's hobbies and interests, and is provided in the form of video, music, text, etc.

[0012] "Location Information" means data about a subject's current location, obtained using GPS or other location measurement technologies.

[0013] "Target people" refers to users of this system, primarily elderly people and people who require care.

[0014] "Monitoring" is the process of continuously collecting and managing a subject's health and location information and detecting abnormalities as necessary.

[0015] "Delivery service" means a service that delivers meals and other items to a target person, and includes affiliated external businesses.

[0016] An "alert" is a notification that provides important information or a reminder to a subject or caregiver, and may be provided in audio, text, or visual format. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

[0025] [First embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0038] The present invention relates to a system that utilizes AI to provide health management, dietary support, and daily life support for the elderly. This system realizes comprehensive nursing support through collaboration between a server, a terminal, and a user. Specific embodiments of the present invention are described below.

[0039] Health management support

[0040] server

[0041] The server periodically collects the latest health data (blood pressure, heart rate, body temperature, etc.) from the subject's sensors. The sensors are wearable devices worn by the subject.

[0042] The collected data is processed by an analytical algorithm on the server. For example, if blood pressure exceeds the normal range, it is determined to be abnormal.

[0043] If an abnormality is detected, the server will promptly notify the medical facility via email or automated communication via API.

[0044] Terminal

[0045] The device receives the health status analysis results sent from the server and notifies the subject and caregiver. For example, the device screen displays a message saying, "Your blood pressure is high. Please contact a medical facility."

[0046] It also has a function to send out an alert so that you don't forget to take your medicine, notifying you with sound and vibration when it's time to take your medicine.

[0047] User

[0048] The user receives notifications from the device and contacts the medical facility as needed, for example, by checking the alert from the device and taking the prescribed medication promptly.

[0049] Meal support

[0050] server

[0051] The server generates a customized meal plan based on the individual's health information and preferences, suggesting low-carb options for someone with diabetes, for example.

[0052] Orders are placed with partner delivery services based on the meal plan.

[0053] Terminal

[0054] The device receives the meal plan information sent from the server and notifies the user of the next meal and the scheduled delivery time. For example, it displays, "Dinner will be delivered at 7 p.m. The menu is grilled salmon."

[0055] User

[0056] Users can view the proposed meal plan and receive meals from the delivery service through the device, and can also provide feedback on the meals.

[0057] Daily life support

[0058] server

[0059] The server generates customized content based on the subject's hobbies and interests, including music playlists, articles, videos, and more.

[0060] The content is delivered to the terminal at the appropriate time.

[0061] Terminal

[0062] The content sent from the server is received and provided to the subject, for example, by playing a music playlist to help the subject relax.

[0063] In addition, when the target person goes out, their location information is monitored and notifications are sent to ensure their safety.

[0064] User

[0065] Users can select and enjoy their favorite content through their device, and when they go out, they can receive location information from the device, allowing them to move around with peace of mind.

[0066] This system will improve the health management, dietary support, and quality of daily life of the recipient, while also reducing the burden on caregivers and realizing more efficient and safe care.

[0067] The processing flow will be explained below.

[0068] Health management support

[0069] Step 1:

[0070] server

[0071] Health data such as blood pressure, heart rate, and body temperature are collected from sensors worn by the subjects, and the data is periodically sent to a server via an API.

[0072] Step 2:

[0073] server

[0074] The collected health data is analyzed and compared with the standard values ​​within the healthy range to check for abnormalities. For example, blood pressure of 160 / 100 mmHg or higher is determined to be high blood pressure.

[0075] Step 3:

[0076] server

[0077] If an abnormality is detected, the system automatically notifies the medical facility via email or API, and includes details of the abnormality and the subject's latest health data.

[0078] Step 4:

[0079] Terminal

[0080] Receives analysis results sent from the server. For example, if blood pressure is high, displays a message saying "Your blood pressure is high. Please contact a medical facility."

[0081] Step 5:

[0082] Terminal

[0083] It sends out alerts to prevent you from forgetting to take your medicine. For example, it notifies you every night at 9pm that it's time to take your medicine.

[0084] Meal support

[0085] Step 1:

[0086] server

[0087] Generate a meal plan based on the subject's health information (e.g., diabetes) and preferences, for example, selecting low-carb menus.

[0088] Step 2:

[0089] server

[0090] It proposes meal plans and places meal orders with partner delivery services, including menu details and delivery times.

[0091] Step 3:

[0092] Terminal

[0093] It receives information from the server and notifies the user of the next meal and the estimated delivery time. It displays, "Dinner will arrive at 7 p.m. The menu is grilled salmon."

[0094] Daily life support

[0095] Step 1:

[0096] server

[0097] It takes the user's hobbies and interests from a database and generates customized content, for example, creating a playlist of the latest classical music for a user who likes classical music.

[0098] Step 2:

[0099] server

[0100] The generated content is delivered to the device at the appropriate time, for example, sending a music playlist to relax in the morning.

[0101] Step 3:

[0102] Terminal

[0103] Receive and play content sent from a server, for example, playing a music playlist through a speaker.

[0104] Step 4:

[0105] Terminal

[0106] When the subject goes out, the location information is monitored by GPS. The location information is periodically checked and notified to the subject and caregiver.

[0107] User Interaction

[0108] Step 1:

[0109] User

[0110] Receive notifications from your device to check your health status and diet, and take necessary actions, such as taking medicine based on the notification.

[0111] Step 2:

[0112] User

[0113] Enjoy suggested meal plans and content, and provide feedback through your device.

[0114] This will complete a process in which the entire system works together to provide multifaceted support for the lives of the elderly.

[0115] Example 1

[0116] 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."

[0117] In today's aging society, there is an increasing need for systems that provide comprehensive health management, dietary support, and daily life support for the elderly. However, conventional systems often provide these support services separately, making it difficult to achieve integrated and efficient care. Furthermore, it is difficult to quickly and accurately respond to various issues, such as detecting abnormal health conditions, notifying users when medication should be taken, and meal planning. Another issue is the lack of personalized content tailored to the preferences and interests of each user.

[0118] 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.

[0119] In this invention, the server includes means for collecting the subject's biometric information from a measurement device, means for analyzing the collected biometric information and detecting abnormalities, means for notifying a medical institution when an abnormality is detected, means for generating a meal plan based on the biometric information, means for proposing the generated meal plan, means for generating and distributing content based on the subject's preferences and interests, means for monitoring location information and notifying the subject when the subject leaves the home, means for displaying the analysis results and notifying the subject and caregiver, and means for issuing alerts to encourage medication. This enables integrated health management, dietary support, and daily life support for the subject, enabling prompt and accurate responses. It also enables the provision of content tailored to the subject's individual needs.

[0120] "Target population" refers to users who receive support from this system, and primarily includes elderly people and those who require nursing care.

[0121] "Biometric information" refers to health data such as blood pressure, heart rate, and body temperature, which are measured and collected using measuring devices.

[0122] "Measuring devices" refer to wearable devices and sensors, which are equipment used to regularly record and collect biometric information from subjects.

[0123] "Server" refers to a central system for analyzing collected biometric information and detecting and notifying abnormalities, and includes cloud servers and data centers.

[0124] "Medical Institution" means a hospital, clinic, or medical facility to which you may be notified about any abnormal health condition.

[0125] A "meal plan" refers to a customized meal menu based on the subject's health condition and preferences, taking nutritional balance into consideration.

[0126] "Content" refers to information and entertainment generated based on a target's preferences and interests, including music playlists, articles, videos, etc.

[0127] "Location information" refers to the subject's current location and is collected via GPS data.

[0128] "Analysis results" refers to the results of data analysis conducted based on collected biometric information, including evaluation of health status and detection of abnormalities.

[0129] An "alert" refers to a notification sent from a device to alert users or encourage them to take action when they take medication or when an abnormality is detected.

[0130] "Notification" refers to a means of communicating abnormalities or important information to the subject, caregiver, or medical institution, and includes email, message, voice, etc.

[0131] This invention is a system that utilizes AI to provide comprehensive health management, dietary support, and daily life support for the elderly. This system operates in cooperation with a server, terminals, and users, and functions as follows:

[0132] Health management support

[0133] server

[0134] First, the server periodically collects biometric information such as blood pressure, heart rate, and body temperature from a wearable device (e.g., commonly known as a "measuring device") worn by the subject. The data is transferred via Bluetooth or Wi-Fi and stored on the server. The collected data is then processed and analyzed using machine learning algorithms and analysis algorithms written in Python or other languages. If an abnormal value is detected through this analysis, it is determined to be abnormal based on a set threshold. If an abnormality is detected, the server automatically sends a notification to the medical institution via the SMTP protocol or REST API.

[0135] As a specific example, the server collects heart rate data from the wearable device every five minutes, and if it detects an abnormal value, it sends an email to the medical institution stating, "Warning: The subject's heart rate has exceeded the normal range."

[0136] Terminal

[0137] The device (e.g., smartphone or tablet) receives the analysis results sent from the server and notifies the user. Using a dedicated health management app, a message will be displayed on the screen saying, "Your blood pressure is high. Please contact a medical institution." In addition, to prevent users from forgetting to take their medication, an alert will be sent via voice assistant or vibration when it is time to take the medication.

[0138] For example, the device will notify you with a voice notification at 8:00 a.m. saying, "It's time to take your medicine."

[0139] User

[0140] The user checks the notification from the device and contacts a medical institution if necessary. The user also receives an alert and takes action to ensure that they do not forget to take the prescribed medication.

[0141] Meal support

[0142] server

[0143] The server generates a customized meal plan based on the user's health status and preferences, using machine learning algorithms and nutritional databases to suggest appropriate menu items, and then issues an order to a partner delivery service.

[0144] For example, a server might suggest low-carb options for diabetics and send an order saying, "Please deliver low-carb grilled salmon for dinner tonight at 6 p.m."

[0145] Terminal

[0146] The device receives the meal plan and estimated delivery time sent from the server and notifies the user, displaying on the screen, "The next meal is scheduled to arrive at 7 p.m. and the menu is grilled salmon."

[0147] User

[0148] Users can check their meal plans and receive meals from the delivery service through their devices, and can also send feedback about their meals to the server through their devices.

[0149] Daily life support

[0150] server

[0151] The server generates customized content (e.g., music playlists, articles, videos, etc.) based on the user's preferences and interests, and delivers the generated content to the device at the appropriate time.

[0152] As a specific example, the server generates a music playlist for relaxation and transmits it to the terminal as a "playlist for afternoon relaxation time."

[0153] Terminal

[0154] The device receives the content sent from the server and provides it to the target user. It plays the playlist through a music player app or similar, allowing the target user to enjoy it. It also uses GPS to monitor the target user's location when they go out and sends notifications to ensure their safety.

[0155] User

[0156] Users can enjoy the content provided through the terminal, and when they go out, they can move around with peace of mind by receiving location information notifications from the terminal.

[0157] Examples of prompt statements

[0158] Health data collection settings: "Collect and analyze my heart rate data today."

[0159] Meal plan suggestions: "Please suggest low-carb meals for diabetics."

[0160] Content generation for daily living support: "Generate a relaxing music playlist for seniors."

[0161] This system will not only comprehensively improve the health management, dietary support, and quality of daily life of the elderly, but will also reduce the burden on their caregivers and provide more efficient and safer support.

[0162] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0163] Health management support

[0164] server

[0165] Step 1:

[0166] The server collects biometric information from the measurement device. The input is data from the wearable device (e.g., heart rate, blood pressure, body temperature). The data is sent to the server via Bluetooth or Wi-Fi. The output is biometric information stored in the server's database. Specifically, the server polls the data from the device every five minutes.

[0167] Step 2:

[0168] The server analyzes the collected biometric information. The input is the biometric information collected in the previous step. A machine learning algorithm written in Python is used for the analysis, and data that exceeds the normal range is judged to be abnormal. The output is the analysis results and the detection of abnormalities. Specifically, the data is input into the algorithm and compared with a threshold for detecting abnormal values.

[0169] Step 3:

[0170] The server notifies the medical institution if an abnormality is detected. The input is the analysis result from the previous step. The notification is sent via email or API request. The output is a warning message sent to the medical institution. Specifically, the server sends a warning email using the SMTP protocol.

[0171] Terminal

[0172] Step 4:

[0173] The terminal receives the analysis results sent from the server and notifies the user. The input is the analysis results from the server. A warning message is displayed on the screen through a dedicated application. The output is the warning message displayed on the screen. For example, it might say, "Your blood pressure is high, please contact a medical institution."

[0174] Step 5:

[0175] The device sends an alert to remind the user to take their medicine. The input is the scheduled time to take the medicine. The notification is sent via a voice assistant or vibration. The output is an alert notification to the user. Specifically, at 8:00 AM, the device notifies the user by voice, saying, "It's time to take your medicine."

[0176] User

[0177] Step 6:

[0178] The user checks the notification from the device and takes the necessary action. The input is a warning message or alert from the device. The output is the action of actually contacting a medical institution or taking medication. The specific action is the user checking the message and taking the prescribed medication.

[0179] Meal support

[0180] server

[0181] Step 1:

[0182] The server generates a meal plan based on the subject's health status and preferences. The input is pre-stored health and preference information. The meal plan is created using machine learning algorithms and a nutrition database. The output is a customized meal plan. Specifically, it generates a low-carb menu for diabetics.

[0183] Step 2:

[0184] The server issues an order to a partner delivery service based on the meal plan. The input is the generated meal plan. The order is sent using API communication. The output is the order sent to the delivery service. A specific operation is to send an order such as "Please deliver grilled salmon for tonight's dinner at 6 p.m."

[0185] Terminal

[0186] Step 3:

[0187] The terminal receives the meal plan and estimated delivery time sent from the server and notifies the user. The input is the meal plan information from the server. The next meal contents and estimated delivery time are displayed on the screen. The output is a notification to the user. For example, it might display "The next meal is scheduled to arrive at 7pm and the menu is grilled salmon."

[0188] User

[0189] Step 4:

[0190] The user checks the meal plan through the terminal and receives the meal from the delivery service. The input is a notification from the terminal. The user checks the actual menu and receives the meal. The output is the action of receiving the meal. The specific actions are the user checking the notification and receiving the meal from the delivery person.

[0191] Daily life support

[0192] server

[0193] Step 1:

[0194] The server generates customized content based on the subject's preferences and interests. The input is the subject's preference information. The generative AI model is used to generate the personalized content. The output is the generated content. A specific operation is to generate a relaxation music playlist.

[0195] Step 2:

[0196] The server delivers content to the terminal at the appropriate time. The input is the generated content. It is sent to the terminal according to the content delivery schedule. The output is the delivered content. A specific operation is to send a "playlist for afternoon relaxation time" to the terminal.

[0197] Terminal

[0198] Step 3:

[0199] The device receives content sent from the server and provides it to the target person. The input is content data from the server. The content is played using a music player app or similar. The output is the content provided to the target person. As a specific example, a music playlist can be played to support relaxation time.

[0200] Step 4:

[0201] The device monitors the location information when the target person goes out and sends a notification to ensure safety. The input is GPS data. The device tracks the target person's location in real time and sends a notification if the target person goes out of range. The output is a notification to ensure safety. Specifically, if the target person goes far away from home, the device sends a notification saying "Please check your current location."

[0202] User

[0203] Step 5:

[0204] Users enjoy content provided through their devices and receive location notifications when they are out and about. The inputs are notifications and content from the device. The outputs are the behavior of enjoying the content and ensuring safety based on location information. Specific actions include the user playing a music playlist, checking notifications, and moving safely.

[0205] Through the above processing steps, this system can comprehensively improve the health management, dietary support, and quality of daily life of elderly people, and reduce the burden on caregivers.

[0206] (Application example 1)

[0207] 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."

[0208] To provide health management, dietary support, and daily living support for the elderly in a unified manner, it is necessary to use multiple different systems and devices, which poses the problem of complex data integration and operation between each system. There is also the risk that the elderly themselves and their caregivers may forget certain procedures or not receive information at the appropriate time. For this reason, there is a need for a system that can efficiently and safely improve the quality of health management, meal plan proposals and implementation, and daily life for the elderly.

[0209] 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.

[0210] In this invention, the server includes means for collecting health information of the subject from a sensor, means for analyzing the collected health information and detecting abnormalities, means for notifying a medical facility when an abnormality is detected, means for generating a meal plan based on the health information, means for proposing the generated meal plan, means for automatically ordering food from a delivery service based on the proposed meal plan, means for generating and distributing content based on the subject's hobbies and interests, and means for monitoring location information and notifying when the subject goes out. This makes it possible to comprehensively and efficiently improve the health management, meal support, and quality of daily life of the elderly.

[0211] A "sensor" is a device used to collect biometric information about a subject, such as blood pressure, heart rate, and body temperature.

[0212] "Analysis" refers to the process of processing and evaluating collected data to determine whether or not there are any abnormalities.

[0213] "Notification" is the act of automatically sending alerts and information to medical facilities and caregivers when an abnormality is detected.

[0214] "Meal Plan" means a customized meal plan based on a Subject's health status and personal preferences, designed to maintain or improve health.

[0215] "Means for automatically placing orders with delivery services" is a function that automatically places orders with affiliated food delivery services based on the generated meal plan.

[0216] "Content" means information and entertainment content provided according to the hobbies and interests of the target user, including music, articles, videos, etc.

[0217] "Location information" refers to geographic location data collected through a subject's device and is used to monitor the subject's movements when out and about.

[0218] "Feedback" refers to opinions and impressions provided by users, and is information collected to improve the quality of service provided by the system.

[0219] This invention is a system that provides health management, dietary support, and daily living support for the elderly, and is linked by a server, terminals, and users. This system collects health information of the target person from sensors and converts it into customized suggestions to realize comprehensive nursing support.

[0220] Server Roles

[0221] 1. Health data collection and analysis

[0222] The server periodically collects health data (blood pressure, heart rate, body temperature, etc.) from sensors worn by the subject. This data is sent to a smartphone via Bluetooth, and then from the smartphone to the server via a REST API. The server analyzes the data using Python and TensorFlow to evaluate the subject's health. If an abnormality is detected, the server automatically notifies medical facilities.

[0223] 2. Meal plan generation and automatic ordering

[0224] Based on the collected health data and the individual's preferences, the server generates an appropriate meal plan, which is then automatically ordered from a partner food delivery service via an API.

[0225] 3. Content generation and distribution

[0226] The server generates customized content based on the user's hobbies and interests, including music playlists, articles, videos, and more, and delivers it to the device at the appropriate time.

[0227] Device Role

[0228] 1. Data Receipt and Notification

[0229] The device receives the health analysis results and meal plans sent from the server and notifies the patient and their caregiver, as well as the contents of the meal and the scheduled delivery time.

[0230] 2. Gathering feedback

[0231] The device collects feedback from the user and sends it to the server, which uses it to improve the service for the next time.

[0232] 3. Location monitoring

[0233] When the target person goes out, the device monitors their location and sends notifications to ensure their safety.

[0234] User Roles

[0235] The user receives information provided through the device and contacts medical facilities as needed, for example, checks alerts from the device and takes prescribed medication promptly, checks suggested meal plans, and receives meals from delivery services.

[0236] Specific examples

[0237] The participants' daily blood pressure and heart rate measurements are sent to a server via their smartphone. The server analyzes the data and notifies medical facilities as needed. Based on their health status, a customized meal plan is generated and automatically ordered from a food delivery service. For example, if the patient has high blood pressure, a low-salt diet is suggested, and grilled salmon is delivered to their home for dinner.

[0238] Example of input prompt for generative AI model

[0239] Health Data:

[0240] Blood pressure: 125 / 80

[0241] Heart rate: 70

[0242] Temperature: 36.5

[0243] Preferences: Low carb

[0244] Suggested meal plan:

[0245] Breakfast: Oatmeal and berries

[0246] Lunch: Grilled chicken salad

[0247] Dinner: Grilled salmon and vegetables

[0248] In this way, the system of the present invention can comprehensively improve the health management, dietary support, and quality of daily life of the elderly.

[0249] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0250] Step 1:

[0251] The server collects health data (blood pressure, heart rate, body temperature, etc.) from the subject's sensors (such as a smartwatch). The sensors send the data to a smartphone via Bluetooth, and the smartphone app sends it to the server through a REST API. The input is the health data from the sensors, and the output is the raw data stored on the server.

[0252] Step 2:

[0253] The server analyzes the collected health data. The analysis is performed using Python and TensorFlow to detect outliers. The input is the collected raw data, and the output is the analysis result (normal / abnormal determination). If an abnormality is detected, the server automatically sends a warning notification to the medical facility.

[0254] Step 3:

[0255] The server generates an appropriate meal plan based on the collected health data and the subject's preferences. The generated meal plan is stored in the server's database. The input is the analyzed health data and the subject's preference information, and the output is a customized meal plan.

[0256] Step 4:

[0257] The server automatically places meal orders with partner delivery services based on the generated meal plan. Orders are placed via the partner delivery service's API. The input is the generated meal plan, and the output is the placed order information.

[0258] Step 5:

[0259] The device receives the analysis results and meal plan details sent from the server and notifies the subject and caregiver. Notifications are made by voice, vibration, or screen display. The input is the notification information sent from the server, and the output is the notification displayed on the subject's device.

[0260] Step 6:

[0261] The user receives notification of the provided meal plan through the terminal, receives the delivered meal, and sends feedback about the meal to the server through the terminal. The input is the user's feedback based on the provided meal, and the output is the feedback data sent to the server.

[0262] Step 7:

[0263] The server generates customized content (music playlists, articles, videos, etc.) based on the user's hobbies and interests and delivers it to the device. The input is data about the user's interests, and the output is the generated content.

[0264] Step 8:

[0265] The device monitors the location information when the subject goes out and sends appropriate notifications to ensure safety. The input is the subject's location data, and the output is a safety notification when the subject goes out.

[0266] In this way, this system can coordinate multiple processing steps to provide health management, dietary support, and daily living support for the elderly.

[0267] 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.

[0268] This invention relates to a system that utilizes AI and an emotion engine to provide health management, dietary support, and daily life support for the elderly. As explained below, this system realizes functions that comprehensively improve the quality of life for the elderly by linking the server, terminals, and users and combining the emotion engine.

[0269] Health management support

[0270] server

[0271] The server periodically collects the latest health data from the subject's sensors, including blood pressure, heart rate, and body temperature.

[0272] The collected data is processed by an analysis algorithm on the server, which compares it with normal ranges to detect abnormalities.

[0273] If an abnormality is detected, the server notifies the medical facility via email or API.

[0274] Terminal

[0275] The analysis results sent from the server are received and notified to the subject and caregiver. For example, a message such as "Your blood pressure is high. Please contact a medical facility." is displayed.

[0276] It also sends out alerts to prevent you from forgetting to take your medicine. For example, it will notify you at 9pm every night that it's time to take your medicine.

[0277] User

[0278] Users receive notifications from their devices, contact medical facilities as needed, and manage health risks by taking prescribed medications at the appropriate times.

[0279] Meal support

[0280] server

[0281] The server generates a customized meal plan based on the subject's health information and dietary preferences, suggesting low-carb options for a diabetic, for example.

[0282] Based on this meal plan, meal orders are placed with affiliated delivery services.

[0283] Terminal

[0284] The system receives meal plan information sent from the server and notifies the user of the next meal and estimated delivery time. For example, it displays, "Dinner will arrive at 7 p.m. The menu is grilled salmon."

[0285] User

[0286] Users can check the meal plan provided and receive meals from the delivery service through the device, and can also provide feedback on the taste and quality of the meal through the device.

[0287] Daily life support

[0288] server

[0289] The server generates customized content based on the subject's hobbies and interests, including music playlists, videos, articles, and more.

[0290] The content is delivered to the device at the appropriate time, for example, a classical music playlist when the person is relaxing in the morning.

[0291] Terminal

[0292] Receives content sent from the server and provides it to the target user, for example, playing a music playlist through a speaker.

[0293] When the target person goes out, the location information is monitored and a timely notification is sent to ensure safety. For example, a notification such as "Your current location is in a park" is sent periodically.

[0294] Utilizing the Emotion Engine

[0295] server

[0296] The emotion engine recognizes emotions from the target person's facial expressions, tone of voice, etc. and adapts behavior accordingly.

[0297] Based on the recognized emotions, more personalized content can be generated and delivered, for example, if the target person is feeling stressed, it can suggest relaxing music or soothing videos.

[0298] The results of health analysis will also be adjusted based on your emotional state. For example, if you are under high stress, your health data will be analyzed more carefully than usual.

[0299] Terminal

[0300] The device receives feedback from the emotion engine and provides real-time support according to the user's emotional state. For example, if the device detects that the user is stressed, it will play soothing content.

[0301] User

[0302] Users can receive services adapted to their emotional state through their devices. By accepting suggestions and notifications based on their emotional state, they can live their daily lives more comfortably.

[0303] This system will enable comprehensive care support for the elderly, including health management, dietary support, improving the quality of daily life, and even addressing their emotional state.

[0304] The processing flow will be explained below.

[0305] Health management support

[0306] Step 1:

[0307] server

[0308] The server periodically collects health data such as blood pressure, heart rate, and body temperature from the subject's sensors, which are typically wearable devices.

[0309] Step 2:

[0310] server

[0311] The collected health data is processed using an analytical algorithm. For example, if blood pressure exceeds 160 / 100 mmHg, it is deemed abnormal.

[0312] Step 3:

[0313] server

[0314] If an abnormality is detected, the server automatically notifies the medical facility, including details of the abnormality and the latest health data.

[0315] Step 4:

[0316] Terminal

[0317] The analysis results sent from the server are received and notified to the subject and caregiver. For example, a message such as "Your blood pressure is high. Please contact a medical facility" is displayed on the screen.

[0318] Step 5:

[0319] Terminal

[0320] To prevent forgetting to take medicine, the device will send out periodic alerts. At 9 p.m. every night, it will notify you by voice or vibration that it's time to take your medicine.

[0321] Meal support

[0322] Step 1:

[0323] server

[0324] It generates a customized meal plan based on the individual's health information and dietary preferences, suggesting low-carb options for someone with diabetes, for example.

[0325] Step 2:

[0326] server

[0327] Based on the meal plan, you will place a meal order with a partner delivery service, which will include meal details and delivery times.

[0328] Step 3:

[0329] Terminal

[0330] It receives meal plan and delivery information sent from the server and notifies the user of the next meal and estimated delivery time. It displays, "Dinner will arrive at 7 p.m. The menu is grilled salmon."

[0331] Daily life support

[0332] Step 1:

[0333] server

[0334] The server generates customized content based on the user's hobbies and interests, such as music playlists or TV show listings.

[0335] Step 2:

[0336] server

[0337] The generated content is delivered to the device at the appropriate time, for example, a classical music playlist is sent in the morning when the target person is relaxing.

[0338] Step 3:

[0339] Terminal

[0340] Receives content sent from the server and provides it to the target user, for example, playing a music playlist through a speaker.

[0341] Step 4:

[0342] Terminal

[0343] When the target person goes out, GPS technology is used to monitor their location and periodically notify them of their current location, with a message such as "Your current location is in a park" displayed on the screen.

[0344] Utilizing the Emotion Engine

[0345] Step 1:

[0346] server

[0347] The emotion engine is used to recognize emotions by analyzing the subject's facial expressions and tone of voice. For example, it analyzes data acquired through a camera and microphone to identify emotions such as stress or joy.

[0348] Step 2:

[0349] server

[0350] Based on the emotions recognized, the system generates more personalized content, for example, suggesting relaxing music or meditation videos if the subject is feeling stressed.

[0351] Step 3:

[0352] Terminal

[0353] The device receives emotion-based content sent from the server and provides it to the subject in real time. For example, if stress is detected, the device will play soothing music.

[0354] User Interaction

[0355] Step 1:

[0356] User

[0357] The user checks the notification from the device and takes action based on the provided information. For example, if the user receives a notification to take medicine, the user takes the medicine promptly.

[0358] Step 2:

[0359] User

[0360] Receive meals based on a suggested meal plan and enjoy content, such as a new music playlist, to enhance your relaxation time.

[0361] Step 3:

[0362] User

[0363] Accept suggestions and notifications based on emotion monitoring to make your daily life more comfortable. For example, if you are feeling stressed, you can watch a meditation video to relax.

[0364] Through these processing steps, a comprehensive care system is realized that includes health management, meal support, daily living assistance, and emotional care for the elderly.

[0365] Example 2

[0366] 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."

[0367] A system that provides integrated health management, dietary support, and daily life support for the elderly is needed. In particular, there is a need for systems that can detect abnormalities in health data and notify medical facilities, generate and deliver meal plans based on health information, provide content based on hobbies and interests in daily life, and ensure safety when out and about. Comprehensive support that takes into account the emotional state of the recipient and promotes relaxation and stress reduction is also needed.

[0368] 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.

[0369] In this invention, the server includes means for collecting health information of the subject from a sensor, means for analyzing the collected health information and detecting abnormalities, means for notifying a medical facility when an abnormality is detected, means for generating a meal plan based on the health information, means for proposing the generated meal plan, means for generating and distributing content based on the subject's hobbies and interests, means for monitoring location information and notifying when the subject goes out, and means for recognizing the subject's emotional state and adapting behavior based thereon. This enables health management, meal support, improvement of quality of daily life for the elderly, and comprehensive care support that responds to emotional states.

[0370] A "sensor" is a device used to collect a subject's health information (blood pressure, heart rate, body temperature, etc.) in real time.

[0371] "Analysis" refers to data processing procedures for detecting abnormal values ​​based on collected health information.

[0372] "Notification" is a means of transmitting information to medical facilities and the like when an abnormality is detected.

[0373] A "meal plan" refers to a meal menu customized for health management based on a subject's health information and dietary preferences.

[0374] "Content" refers to information and entertainment generated based on the subject's hobbies and interests.

[0375] "Location information" is data that indicates the subject's current geographic location.

[0376] "Emotional state" is the result of recognizing the subject's current psychological state from facial expressions, tone of voice, etc.

[0377] "Delivery service" refers to a service that delivers food based on a meal plan to the target person.

[0378] An "alert" is a notification sent to prevent you from forgetting to take your medicine.

[0379] The present invention relates to a system that provides integrated health management, dietary support, and daily life support for the elderly. This system improves the quality of life for the elderly in a comprehensive manner by linking a server, terminals, and users and by utilizing an emotion engine. A specific embodiment of the system is shown below.

[0380] Health management support

[0381] server

[0382] The server collects health data such as the subject's blood pressure, heart rate, and body temperature from sensors in wearable devices and other devices. This data is collected using cloud services such as AWS IoT and Google Cloud IoT Core. The collected data is processed using analysis algorithms written in Python or R. Data analysis evaluates whether the subject's health data is within the normal range and detects abnormal values. For example, if blood pressure is higher than normal, it is determined to be abnormal.

[0383] If an abnormality is detected, the server uses the Twilio API to send a notification to the medical facility. The notification includes basic information about the subject and the type of abnormality. For example, a notification such as "Subject A's blood pressure is 180 / 120. Emergency treatment is required" may be sent.

[0384] Terminal

[0385] The device receives the analysis results sent from the server. This is done using Firebase or REST API. The received information is notified to the subject and caregiver. Specifically, it displays a message saying, "Your blood pressure is high. Please contact a medical facility." Additionally, to prevent forgetting to take medication, an alert is displayed every night at 9 p.m. saying, "It's time to take your medication."

[0386] User

[0387] The user receives notifications from the device and contacts a medical facility as needed. For example, if an abnormality in blood pressure is detected, the user can call a medical facility. Also, based on the alerts on the device, the user can take prescribed medication at the specified time.

[0388] Meal support

[0389] server

[0390] The server generates a customized meal plan using a cloud-based database (e.g., Firebase Firestore) based on the subject's health information and dietary preferences. For example, it creates a low-carb menu for a diabetic patient. Based on this meal plan, the server issues an order to a partner delivery service (e.g., Uber Eats API). The server provides the subject's information (address, meal contents) to the delivery service.

[0391] Terminal

[0392] The device receives the meal plan information sent from the server. Firebase and REST APIs are also used for this. The device then notifies the target user of the next meal plan and the estimated delivery time. For example, it might display, "Dinner will arrive at 7 p.m. The menu is grilled salmon."

[0393] User

[0394] The user checks the provided meal plan on the device and receives the meal from the delivery service. Specifically, they receive a grilled salmon meal at 7 p.m. They also send feedback about the taste and quality of the meal to the server via the device. For example, they can enter, "The grilled salmon was delicious, but I wish it was a little less salty."

[0395] Daily life support

[0396] server

[0397] The server uses the Spotify API or Netflix API to generate content based on the user's hobbies and interests. For example, it creates a playlist of relaxing classical music or an interesting video. The generated content is delivered to the user's device at the time they want. For example, a classical music playlist is sent to relax in the morning.

[0398] Terminal

[0399] The device receives the content sent from the server and provides it to the target person. For example, it plays a generated music playlist from a speaker. The device also monitors the target person's location using its GPS function and sends notifications to ensure their safety. Specifically, the device periodically notifies the target person that "Your current location is in a park."

[0400] User

[0401] Users can check notifications from their devices to ensure their safety. They can listen to classical music during relaxation time, or check location notifications to confirm that they are in a park or other location.

[0402] Utilizing the Emotion Engine

[0403] server

[0404] The server uses an emotion engine such as Microsoft Azure Cognitive Services to recognize emotions from the subject's facial expressions and tone of voice. Specifically, it determines whether the subject is stressed or relaxed. Based on the recognized emotions, it generates more personalized content, for example, suggesting music or videos to relax the subject if they are stressed. It also adjusts the analysis results of health information based on the subject's emotional state. For example, when the subject is in a high stress state, it analyzes health data more carefully.

[0405] Terminal

[0406] The device receives feedback from the emotion engine and provides support that adapts to the user's emotional state in real time. For example, if the device detects stress, it will play soothing music or videos.

[0407] User

[0408] Users can receive services adapted to their emotional state through their devices. For example, listening to soothing music when feeling stressed can help users lead a more comfortable daily life.

[0409] This system can provide comprehensive care support for the elderly, including health management, dietary support, improving the quality of daily life, and even addressing their emotional state.

[0410] Prompt Sentence Examples

[0411] You want to develop a system to provide health management, meal support, and daily life support for the elderly. Collect and analyze health data, customize meal plans, order them from delivery services, and deliver customized content at the right time. Consider how to incorporate an emotion engine into this system to provide more personalized support.

[0412] Based on this example and prompt, it is believed that it will be easier to understand the system's functionality and how it is implemented.

[0413] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0414] Health management support

[0415] server

[0416] Step 1:

[0417] The server collects health data from the sensors.

[0418] Input: Data such as blood pressure, heart rate, and temperature obtained from wearable devices.

[0419] Output: Store the collected health data in a cloud database.

[0420] Specific operation: Uses AWS IoT or Google Cloud IoT Core to acquire data in real time and store it in a database.

[0421] Step 2:

[0422] The server analyzes the collected health data.

[0423] Input: Health data stored in a cloud database.

[0424] Output: Analyzed data results (e.g. outlier detection).

[0425] What it does: It uses analytics algorithms written in Python or R to compare data with health standards and detect abnormalities. For example, a blood pressure of 180 / 120 is considered abnormal.

[0426] Step 3:

[0427] The server notifies the medical facility if an abnormality is detected.

[0428] Input: Parsed data results.

[0429] Output: Notification sent to healthcare facility.

[0430] Specific behavior: Uses the Twilio API to send notifications to medical facilities via email and SMS. Example: "Subject A's blood pressure is 180 / 120. Emergency treatment is required."

[0431] Terminal

[0432] Step 1:

[0433] The terminal receives the analysis result from the server.

[0434] Input: Analysis results sent from the server.

[0435] Output: Analysis results displayed on the terminal.

[0436] Specific operation: Retrieves data via Firebase or REST API and displays it on the device screen.

[0437] Step 2:

[0438] The terminal notifies the analysis result.

[0439] Input: Received analysis results.

[0440] Output: Notification to subject and caregiver.

[0441] Specific behavior: Display "Your blood pressure is high. Please contact a medical facility." Also, display an alert every night at 9 PM saying "It's time to take your medication."

[0442] User

[0443] Step 1:

[0444] The user receives the notification and responds.

[0445] Input: Notifications from your device.

[0446] Output: Contact medical facility and take medication.

[0447] Specific actions: See the notification on the device, call a medical facility, see the notification at 9 PM, and take the prescribed medication.

[0448] Meal support

[0449] server

[0450] Step 1:

[0451] The server generates a meal plan based on the health information and dietary preferences.

[0452] Input: A database containing health information and dietary preferences.

[0453] Output: A customized meal plan.

[0454] What it does: It uses Firebase Firestore to retrieve information from a database and then uses an algorithm to generate a meal plan, for example, a low-carb menu for a diabetic.

[0455] Step 2:

[0456] The server issues orders to a delivery service based on the meal plan.

[0457] Input: The generated meal plan.

[0458] Output: Order information sent to the delivery service.

[0459] Specific operation: Use the Uber Eats API to provide the meal details and the target address to the delivery service. For example, specify "grilled salmon."

[0460] Terminal

[0461] Step 1:

[0462] The terminal receives the meal plan information from the server.

[0463] Input: Meal plan information sent from the server.

[0464] Output: Meal plan information displayed on the device.

[0465] Specific behavior: Receives data via Firebase or REST API and displays the next meal contents and estimated delivery time. Example: Notifies "Dinner will arrive at 7pm. The menu is grilled salmon."

[0466] User

[0467] Step 1:

[0468] The user confirms and receives the meal plan.

[0469] Input: Meal plan information provided on device.

[0470] Output: Meals from a delivery service.

[0471] Specific action: Pick up a grilled salmon meal from a delivery service at 7pm.

[0472] Step 2:

[0473] The user provides feedback.

[0474] Input: Feedback on the taste and quality of the food provided.

[0475] Output: Feedback information sent to the server.

[0476] Specific action: Enter "The grilled salmon was delicious, but I wish it was a little less salty" into the device.

[0477] Daily life support

[0478] server

[0479] Step 1:

[0480] The server generates content based on hobbies and interests.

[0481] Input: A database storing the subject's hobbies and interests.

[0482] Output: The generated content.

[0483] What it does: Uses Spotify API and Netflix API to generate music playlists and videos tailored to the target audience. For example, create a classical music playlist.

[0484] Step 2:

[0485] The server distributes the generated content.

[0486] Input: Generated content.

[0487] Output: Content information delivered to the device.

[0488] What it does: Send a morning relaxation classical music playlist via Firebase Cloud Messaging or the REST API.

[0489] Terminal

[0490] Step 1:

[0491] The terminal receives the content transmitted from the server.

[0492] Input: Content information sent from the server.

[0493] Output: The content that is displayed or played on a device.

[0494] Specific operation: Play the received music playlist from the speaker.

[0495] Step 2:

[0496] The terminal monitors and notifies the location information.

[0497] Input: Location information obtained by GPS.

[0498] Output: Location-based notifications.

[0499] Specific operation: Notify "Your current location is a park" at regular intervals.

[0500] User

[0501] Step 1:

[0502] The user uses the distributed content.

[0503] Input: Content displayed or played on the device.

[0504] Output: Satisfaction and relaxation from the content used.

[0505] Specific action: Listen to classical music during relaxation time.

[0506] Step 2:

[0507] The user checks the location information notification.

[0508] Input: Location notification from device.

[0509] Output: Your current safety status.

[0510] Specific operation: Check the notification on the device to confirm that you are in the park correctly.

[0511] Utilizing the Emotion Engine

[0512] server

[0513] Step 1:

[0514] The server analyzes the emotion data using an emotion engine.

[0515] Input: Data based on the subject's facial expressions and tone of voice.

[0516] Output: Parsed emotional state.

[0517] How it works: Using Microsoft Azure Cognitive Services, it analyzes whether a subject is stressed or relaxed.

[0518] Step 2:

[0519] The server generates personalized content based on the emotional state.

[0520] Input: Parsed emotional state.

[0521] Output: Personalized content.

[0522] Specific operation: When you are feeling stressed, generate and transmit music or images to help you relax.

[0523] Step 3:

[0524] The server analyzes the health data to reflect the emotional state.

[0525] Input: Parsed emotional state and collected health data.

[0526] Output: Analysis results of health data taking into account emotional state.

[0527] Specific behavior: When the emotional state is stressful, analyze health data more carefully.

[0528] Terminal

[0529] Step 1:

[0530] The device receives feedback from the emotion engine.

[0531] Input: Parsed emotional state.

[0532] Output: Service depending on emotional state.

[0533] Specific operation: Play music and video in real time according to the emotional state.

[0534] User

[0535] Step 1:

[0536] The user receives a service adapted to his emotional state.

[0537] Input: Emotion-based service provided by the device.

[0538] Output: Relaxation and satisfaction depending on emotional state.

[0539] Specific action: Listen to soothing music when you feel stressed and make your daily life more comfortable.

[0540] (Application example 2)

[0541] 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."

[0542] In the daily lives of elderly people, there is a need to efficiently manage their health, provide dietary support, and recognize their emotions to improve their quality of life. However, these functions are currently provided individually, and there is no integrated support system, which places a heavy burden on elderly people and their caregivers. Furthermore, the lack of support in response to emotional changes makes it difficult to reduce stress and anxiety.

[0543] 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.

[0544] In this invention, the server includes means for collecting health information of the subject from a sensor, means for analyzing the collected health information and detecting abnormalities, means for notifying a medical facility when an abnormality is detected, means for generating a meal plan based on the health information, means for proposing the generated meal plan, means for generating and distributing content based on the subject's hobbies and interests, means for monitoring location information and notifying when the subject goes out, and means for recognizing emotions and adapting behavior based on emotions. This enables health management, meal support, and emotion recognition to be performed in an integrated manner, thereby comprehensively improving the quality of daily life of elderly people.

[0545] "Health information" is data that indicates the subject's physical condition, and specifically includes blood pressure, heart rate, body temperature, and the like.

[0546] A "sensor" is a device for collecting health information about a subject, and includes wearable devices and vital sign monitors.

[0547] "Analysis" refers to algorithmic methods used to process data and detect anomalies based on collected health information.

[0548] "Abnormal" refers to a state in which the subject's health information deviates from the normal range, indicating a condition requiring early intervention.

[0549] "Medical facility" refers to a place that provides medical services, such as a hospital or clinic.

[0550] A "meal plan" refers to a meal menu customized based on the subject's health information, and includes content that takes into consideration nutritional balance and health status.

[0551] "Recommendation" refers to the act of informing the subject or their caregiver of the generated meal plan.

[0552] "Hobbies and interests" refers to activities that the subject enjoys on a daily basis and areas of interest.

[0553] "Content" includes information materials such as videos, music, articles, etc. that are provided based on the subject's hobbies and interests.

[0554] "Distribution" refers to the act of delivering the generated content to the target audience, which may be via the Internet or a local network.

[0555] "Location information" is data that indicates a subject's current physical location and is obtained using technologies such as GPS.

[0556] "Notification" refers to the act of informing a subject or their caregiver of necessary information, and may take the form of an alert or message.

[0557] "Emotion recognition" refers to the technology of determining a subject's emotions from their facial expressions, tone of voice, etc.

[0558] "Behavioral adaptation" refers to the act of responding to provide services and content that meet the needs of the target person based on emotion recognition.

[0559] This invention relates to a comprehensive system that provides health management, dietary support, and daily life support for the elderly. This system aims to improve the quality of life of the target individuals by linking the server, terminals, and users, and by combining an emotion engine.

[0560] Health management support

[0561] server

[0562] The server periodically collects health information from the subject's sensors. This health information includes blood pressure, heart rate, and body temperature. The collected data is processed by an analysis algorithm on the server and compared with the normal range to detect abnormalities. If an abnormality is detected, the server notifies medical facilities. Notification methods include email and API.

[0563] Terminal

[0564] The device receives the analysis results sent from the server and notifies the subject and caregiver. For example, it displays a message saying, "Your blood pressure is high. Please contact a medical facility." To prevent patients from forgetting to take their medication, the device also sends an alert every night at 9 p.m. saying, "It's time to take your medication."

[0565] User

[0566] Users receive notifications from their devices, contact medical facilities as needed, and manage health risks by taking prescribed medications at the appropriate times.

[0567] Meal support

[0568] server

[0569] The server generates a customized meal plan based on the user's health information and dietary preferences. For example, it suggests low-carb options for diabetics. Based on this meal plan, it issues a meal order to a partner delivery service.

[0570] Terminal

[0571] The device receives the meal plan information sent from the server and notifies the user of the next meal and the estimated delivery time. For example, it displays, "Dinner will arrive at 7 p.m. The menu is grilled salmon."

[0572] User

[0573] Users can check the meal plan provided and receive meals from the delivery service through the device, and can also provide feedback on the taste and quality of the meal through the device.

[0574] Daily life support

[0575] server

[0576] The server generates customized content based on the user's hobbies and interests, including music playlists, videos, and articles. The content is delivered to the device at the appropriate time. For example, a classical music playlist could be sent when the user is relaxing in the morning.

[0577] Terminal

[0578] The device receives the content sent from the server and provides it to the target person. For example, a music playlist can be played from a speaker. When the target person goes out, the device monitors the target person's location and sends timely notifications to ensure their safety. For example, the device periodically sends a notification saying, "Your current location is in a park."

[0579] Utilizing the Emotion Engine

[0580] server

[0581] The server uses an emotion engine to recognize emotions from the subject's facial expressions, tone of voice, and other factors. Based on the recognized emotions, the server generates and delivers more personalized content. For example, if the subject is feeling stressed, it will suggest relaxing music or soothing videos. The results of health information analysis are also adjusted according to the subject's emotional state. For example, when the subject is under high stress, the server will analyze health data more carefully than usual.

[0582] Terminal

[0583] The device receives feedback from the emotion engine and provides real-time support according to the subject's emotional state. For example, if the device detects stress in the subject, it will play soothing content.

[0584] User

[0585] Users can receive services adapted to their emotional state through their devices. By accepting suggestions and notifications based on their emotional state, they can live their daily lives more comfortably.

[0586] Hardware and software used

[0587] The system utilizes hardware such as smartphones, head-mounted displays, and smart glasses, as well as software such as Python programs, RESTful APIs, and emotion recognition algorithms.

[0588] Specific examples

[0589] For example, if a user sends their health data to a server, the server can detect that they have high blood pressure and suggest a low-salt diet plan. If the app's emotion recognition function determines that the user is feeling stressed, it can suggest relaxing music and videos.

[0590] Prompt Sentence Examples

[0591] "Enter your latest health data: blood pressure, heart rate, temperature"

[0592] "Please tell us your current emotional state: happy, sad, stressed, neutral"

[0593] "What is your suggested meal plan based on my current health condition?"

[0594] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0595] Step 1: Collecting health data

[0596] Input: Sensors collect the subject's health information (blood pressure, heart rate, temperature).

[0597] Server behavior:

[0598] The server receives health data sent from sensors, specifically from wearable devices and vital sign monitors, and stores the data.

[0599] Output: The collected health data is stored on the server.

[0600] Step 2: Analyzing health data

[0601] Input: Collected health data

[0602] Server behavior:

[0603] The subject's health data is analyzed using an analysis algorithm (for example, using a Python library) on the server. The analysis detects abnormalities by comparing the health information with the normal range.

[0604] Output: The analysis results (normal or abnormal) are generated and saved.

[0605] Step 3: Notification of abnormalities

[0606] Input: If the analysis result is abnormal

[0607] Server behavior:

[0608] If an abnormality is detected, the server notifies the medical facility by email or using a RESTful API.

[0609] Output: A notification to the healthcare facility is sent.

[0610] Step 4: Generate a meal plan

[0611] Input: Health data and analysis results

[0612] Server behavior:

[0613] The server generates a customized meal plan based on the subject's health information and dietary preferences. The meal plan is created using a nutrition calculation algorithm.

[0614] Output: The generated meal plan is saved.

[0615] Step 5: Meal plan suggestions

[0616] Input: Generated meal plan

[0617] Server behavior:

[0618] The server transmits the generated meal plan to the terminal.

[0619] Device operation: The device notifies the recipient and their caregiver of the received meal plan. For example, it displays, "Dinner will arrive at 7 p.m. The menu is grilled salmon."

[0620] Output: The subject and / or caregiver will be notified of the meal plan information.

[0621] Step 6: Order from a delivery service

[0622] Enter: Check Meal Plan

[0623] Terminal behavior:

[0624] After the user confirms the meal plan, the device issues an order to the partner delivery service, specifically by sending the order information using the delivery service's API.

[0625] Output: A food order is placed with the delivery service.

[0626] Step 7: Recognize emotions

[0627] Input: Subject's facial expressions and tone of voice

[0628] Terminal behavior:

[0629] The device's camera and microphone are used to recognize the subject's emotions, and an emotion engine (AI model) is used to analyze the collected data.

[0630] Output: The recognized emotion is saved on the device.

[0631] Step 8: Adapting behavior based on emotions

[0632] Input: Recognized emotion

[0633] Server behavior:

[0634] Based on the emotions detected, the server generates and sends personalized content to the device, such as relaxing music or soothing videos.

[0635] Terminal behavior:

[0636] The device then provides the received content to the subject, for example, playing relaxing music if the subject is feeling stressed.

[0637] Output: Personalized content is provided to the subject, improving their emotional state.

[0638] 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.

[0639] 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.

[0640] 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.

[0641] [Second embodiment]

[0642] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0643] 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.

[0644] 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).

[0645] 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.

[0646] 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.

[0647] 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).

[0648] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0649] 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.

[0650] 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.

[0651] 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.

[0652] 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.

[0653] 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."

[0654] The present invention relates to a system that utilizes AI to provide health management, dietary support, and daily life support for the elderly. This system realizes comprehensive nursing support through collaboration between a server, a terminal, and a user. Specific embodiments of the present invention are described below.

[0655] Health management support

[0656] server

[0657] The server periodically collects the latest health data (blood pressure, heart rate, body temperature, etc.) from the subject's sensors. The sensors are wearable devices worn by the subject.

[0658] The collected data is processed by an analytical algorithm on the server. For example, if blood pressure exceeds the normal range, it is determined to be abnormal.

[0659] If an abnormality is detected, the server will promptly notify the medical facility via email or automated communication via API.

[0660] Terminal

[0661] The device receives the health status analysis results sent from the server and notifies the subject and caregiver. For example, the device screen displays a message saying, "Your blood pressure is high. Please contact a medical facility."

[0662] It also has a function to send out an alert so that you don't forget to take your medicine, notifying you with sound and vibration when it's time to take your medicine.

[0663] User

[0664] The user receives notifications from the device and contacts the medical facility as needed, for example, by checking the alert from the device and taking the prescribed medication promptly.

[0665] Meal support

[0666] server

[0667] The server generates a customized meal plan based on the individual's health information and preferences, suggesting low-carb options for someone with diabetes, for example.

[0668] Orders are placed with partner delivery services based on the meal plan.

[0669] Terminal

[0670] The device receives the meal plan information sent from the server and notifies the user of the next meal and the scheduled delivery time. For example, it displays, "Dinner will be delivered at 7 p.m. The menu is grilled salmon."

[0671] User

[0672] Users can view the proposed meal plan and receive meals from the delivery service through the device, and can also provide feedback on the meals.

[0673] Daily life support

[0674] server

[0675] The server generates customized content based on the subject's hobbies and interests, including music playlists, articles, videos, and more.

[0676] The content is delivered to the terminal at the appropriate time.

[0677] Terminal

[0678] The content sent from the server is received and provided to the subject, for example, by playing a music playlist to help the subject relax.

[0679] In addition, when the target person goes out, their location information is monitored and notifications are sent to ensure their safety.

[0680] User

[0681] Users can select and enjoy their favorite content through their device, and when they go out, they can receive location information from the device, allowing them to move around with peace of mind.

[0682] This system will improve the health management, dietary support, and quality of daily life of the recipient, while also reducing the burden on caregivers and realizing more efficient and safe care.

[0683] The processing flow will be explained below.

[0684] Health management support

[0685] Step 1:

[0686] server

[0687] Health data such as blood pressure, heart rate, and body temperature are collected from sensors worn by the subjects, and the data is periodically sent to a server via an API.

[0688] Step 2:

[0689] server

[0690] The collected health data is analyzed and compared with the standard values ​​within the healthy range to check for abnormalities. For example, blood pressure of 160 / 100 mmHg or higher is determined to be high blood pressure.

[0691] Step 3:

[0692] server

[0693] If an abnormality is detected, the system automatically notifies the medical facility via email or API, and includes details of the abnormality and the subject's latest health data.

[0694] Step 4:

[0695] Terminal

[0696] Receives analysis results sent from the server. For example, if blood pressure is high, displays a message saying "Your blood pressure is high. Please contact a medical facility."

[0697] Step 5:

[0698] Terminal

[0699] It sends out alerts to prevent you from forgetting to take your medicine. For example, it notifies you every night at 9pm that it's time to take your medicine.

[0700] Meal support

[0701] Step 1:

[0702] server

[0703] Generate a meal plan based on the subject's health information (e.g., diabetes) and preferences, for example, selecting low-carb menus.

[0704] Step 2:

[0705] server

[0706] It proposes meal plans and places meal orders with partner delivery services, including menu details and delivery times.

[0707] Step 3:

[0708] Terminal

[0709] It receives information from the server and notifies the user of the next meal and the estimated delivery time. It displays, "Dinner will arrive at 7 p.m. The menu is grilled salmon."

[0710] Daily life support

[0711] Step 1:

[0712] server

[0713] It takes the user's hobbies and interests from a database and generates customized content, for example, creating a playlist of the latest classical music for a user who likes classical music.

[0714] Step 2:

[0715] server

[0716] The generated content is delivered to the device at the appropriate time, for example, sending a music playlist to relax in the morning.

[0717] Step 3:

[0718] Terminal

[0719] Receive and play content sent from a server, for example, playing a music playlist through a speaker.

[0720] Step 4:

[0721] Terminal

[0722] When the subject goes out, the location information is monitored by GPS. The location information is periodically checked and notified to the subject and caregiver.

[0723] User Interaction

[0724] Step 1:

[0725] User

[0726] Receive notifications from your device to check your health status and diet, and take necessary actions, such as taking medicine based on the notification.

[0727] Step 2:

[0728] User

[0729] Enjoy suggested meal plans and content, and provide feedback through your device.

[0730] This will complete a process in which the entire system works together to provide multifaceted support for the lives of the elderly.

[0731] Example 1

[0732] 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."

[0733] In today's aging society, there is an increasing need for systems that provide comprehensive health management, dietary support, and daily life support for the elderly. However, conventional systems often provide these support services separately, making it difficult to achieve integrated and efficient care. Furthermore, it is difficult to quickly and accurately respond to various issues, such as detecting abnormal health conditions, notifying users when medication should be taken, and meal planning. Another issue is the lack of personalized content tailored to the preferences and interests of each user.

[0734] 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.

[0735] In this invention, the server includes means for collecting the subject's biometric information from a measurement device, means for analyzing the collected biometric information and detecting abnormalities, means for notifying a medical institution when an abnormality is detected, means for generating a meal plan based on the biometric information, means for proposing the generated meal plan, means for generating and distributing content based on the subject's preferences and interests, means for monitoring location information and notifying the subject when the subject leaves the home, means for displaying the analysis results and notifying the subject and caregiver, and means for issuing alerts to encourage medication. This enables integrated health management, dietary support, and daily life support for the subject, enabling prompt and accurate responses. It also enables the provision of content tailored to the subject's individual needs.

[0736] "Target population" refers to users who receive support from this system, and primarily includes elderly people and those who require nursing care.

[0737] "Biometric information" refers to health data such as blood pressure, heart rate, and body temperature, which are measured and collected using measuring devices.

[0738] "Measuring devices" refer to wearable devices and sensors, which are equipment used to regularly record and collect biometric information from subjects.

[0739] "Server" refers to a central system for analyzing collected biometric information and detecting and notifying abnormalities, and includes cloud servers and data centers.

[0740] "Medical Institution" means a hospital, clinic, or medical facility to which you may be notified about any abnormal health condition.

[0741] A "meal plan" refers to a customized meal menu based on the subject's health condition and preferences, taking nutritional balance into consideration.

[0742] "Content" refers to information and entertainment generated based on a target's preferences and interests, including music playlists, articles, videos, etc.

[0743] "Location information" refers to the subject's current location and is collected via GPS data.

[0744] "Analysis results" refers to the results of data analysis conducted based on collected biometric information, including evaluation of health status and detection of abnormalities.

[0745] An "alert" refers to a notification sent from a device to alert users or encourage them to take action when they take medication or when an abnormality is detected.

[0746] "Notification" refers to a means of communicating abnormalities or important information to the subject, caregiver, or medical institution, and includes email, message, voice, etc.

[0747] This invention is a system that utilizes AI to provide comprehensive health management, dietary support, and daily life support for the elderly. This system operates in cooperation with a server, terminals, and users, and functions as follows:

[0748] Health management support

[0749] server

[0750] First, the server periodically collects biometric information such as blood pressure, heart rate, and body temperature from a wearable device (e.g., commonly known as a "measuring device") worn by the subject. The data is transferred via Bluetooth or Wi-Fi and stored on the server. The collected data is then processed and analyzed using machine learning algorithms and analysis algorithms written in Python or other languages. If an abnormal value is detected through this analysis, it is determined to be abnormal based on a set threshold. If an abnormality is detected, the server automatically sends a notification to the medical institution via the SMTP protocol or REST API.

[0751] As a specific example, the server collects heart rate data from the wearable device every five minutes, and if it detects an abnormal value, it sends an email to the medical institution stating, "Warning: The subject's heart rate has exceeded the normal range."

[0752] Terminal

[0753] The device (e.g., smartphone or tablet) receives the analysis results sent from the server and notifies the user. Using a dedicated health management app, a message will be displayed on the screen saying, "Your blood pressure is high. Please contact a medical institution." In addition, to prevent users from forgetting to take their medication, an alert will be sent via voice assistant or vibration when it is time to take the medication.

[0754] For example, the device will notify you with a voice notification at 8:00 a.m. saying, "It's time to take your medicine."

[0755] User

[0756] The user checks the notification from the device and contacts a medical institution if necessary. The user also receives an alert and takes action to ensure that they do not forget to take the prescribed medication.

[0757] Meal support

[0758] server

[0759] The server generates a customized meal plan based on the user's health status and preferences, using machine learning algorithms and nutritional databases to suggest appropriate menu items, and then issues an order to a partner delivery service.

[0760] For example, a server might suggest low-carb options for diabetics and send an order saying, "Please deliver low-carb grilled salmon for dinner tonight at 6 p.m."

[0761] Terminal

[0762] The device receives the meal plan and estimated delivery time sent from the server and notifies the user, displaying on the screen, "The next meal is scheduled to arrive at 7 p.m. and the menu is grilled salmon."

[0763] User

[0764] Users can check their meal plans and receive meals from the delivery service through their devices, and can also send feedback about their meals to the server through their devices.

[0765] Daily life support

[0766] server

[0767] The server generates customized content (e.g., music playlists, articles, videos, etc.) based on the user's preferences and interests, and delivers the generated content to the device at the appropriate time.

[0768] As a specific example, the server generates a music playlist for relaxation and transmits it to the terminal as a "playlist for afternoon relaxation time."

[0769] Terminal

[0770] The device receives the content sent from the server and provides it to the target user. It plays the playlist through a music player app or similar, allowing the target user to enjoy it. It also uses GPS to monitor the target user's location when they go out and sends notifications to ensure their safety.

[0771] User

[0772] Users can enjoy the content provided through the terminal, and when they go out, they can move around with peace of mind by receiving location information notifications from the terminal.

[0773] Examples of prompt statements

[0774] Health data collection settings: "Collect and analyze my heart rate data today."

[0775] Meal plan suggestions: "Please suggest low-carb meals for diabetics."

[0776] Content generation for daily living support: "Generate a relaxing music playlist for seniors."

[0777] This system will not only comprehensively improve the health management, dietary support, and quality of daily life of the elderly, but will also reduce the burden on their caregivers and provide more efficient and safer support.

[0778] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0779] Health management support

[0780] server

[0781] Step 1:

[0782] The server collects biometric information from the measurement device. The input is data from the wearable device (e.g., heart rate, blood pressure, body temperature). The data is sent to the server via Bluetooth or Wi-Fi. The output is biometric information stored in the server's database. Specifically, the server polls the data from the device every five minutes.

[0783] Step 2:

[0784] The server analyzes the collected biometric information. The input is the biometric information collected in the previous step. A machine learning algorithm written in Python is used for the analysis, and data that exceeds the normal range is judged to be abnormal. The output is the analysis results and the detection of abnormalities. Specifically, the data is input into the algorithm and compared with a threshold for detecting abnormal values.

[0785] Step 3:

[0786] The server notifies the medical institution if an abnormality is detected. The input is the analysis result from the previous step. The notification is sent via email or API request. The output is a warning message sent to the medical institution. Specifically, the server sends a warning email using the SMTP protocol.

[0787] Terminal

[0788] Step 4:

[0789] The terminal receives the analysis results sent from the server and notifies the user. The input is the analysis results from the server. A warning message is displayed on the screen through a dedicated application. The output is the warning message displayed on the screen. For example, it might say, "Your blood pressure is high, please contact a medical institution."

[0790] Step 5:

[0791] The device sends an alert to remind the user to take their medicine. The input is the scheduled time to take the medicine. The notification is sent via a voice assistant or vibration. The output is an alert notification to the user. Specifically, at 8:00 AM, the device notifies the user by voice, saying, "It's time to take your medicine."

[0792] User

[0793] Step 6:

[0794] The user checks the notification from the device and takes the necessary action. The input is a warning message or alert from the device. The output is the action of actually contacting a medical institution or taking medication. The specific action is the user checking the message and taking the prescribed medication.

[0795] Meal support

[0796] server

[0797] Step 1:

[0798] The server generates a meal plan based on the subject's health status and preferences. The input is pre-stored health and preference information. The meal plan is created using machine learning algorithms and a nutrition database. The output is a customized meal plan. Specifically, it generates a low-carb menu for diabetics.

[0799] Step 2:

[0800] The server issues an order to a partner delivery service based on the meal plan. The input is the generated meal plan. The order is sent using API communication. The output is the order sent to the delivery service. A specific operation is to send an order such as "Please deliver grilled salmon for tonight's dinner at 6 p.m."

[0801] Terminal

[0802] Step 3:

[0803] The terminal receives the meal plan and estimated delivery time sent from the server and notifies the user. The input is the meal plan information from the server. The next meal contents and estimated delivery time are displayed on the screen. The output is a notification to the user. For example, it might display "The next meal is scheduled to arrive at 7pm and the menu is grilled salmon."

[0804] User

[0805] Step 4:

[0806] The user checks the meal plan through the terminal and receives the meal from the delivery service. The input is a notification from the terminal. The user checks the actual menu and receives the meal. The output is the action of receiving the meal. The specific actions are the user checking the notification and receiving the meal from the delivery person.

[0807] Daily life support

[0808] server

[0809] Step 1:

[0810] The server generates customized content based on the subject's preferences and interests. The input is the subject's preference information. The generative AI model is used to generate the personalized content. The output is the generated content. A specific operation is to generate a relaxation music playlist.

[0811] Step 2:

[0812] The server delivers content to the terminal at the appropriate time. The input is the generated content. It is sent to the terminal according to the content delivery schedule. The output is the delivered content. A specific operation is to send a "playlist for afternoon relaxation time" to the terminal.

[0813] Terminal

[0814] Step 3:

[0815] The device receives content sent from the server and provides it to the target person. The input is content data from the server. The content is played using a music player app or similar. The output is the content provided to the target person. As a specific example, a music playlist can be played to support relaxation time.

[0816] Step 4:

[0817] The device monitors the location information when the target person goes out and sends a notification to ensure safety. The input is GPS data. The device tracks the target person's location in real time and sends a notification if the target person goes out of range. The output is a notification to ensure safety. Specifically, if the target person goes far away from home, the device sends a notification saying "Please check your current location."

[0818] User

[0819] Step 5:

[0820] Users enjoy content provided through their devices and receive location notifications when they are out and about. The inputs are notifications and content from the device. The outputs are the behavior of enjoying the content and ensuring safety based on location information. Specific actions include the user playing a music playlist, checking notifications, and moving safely.

[0821] Through the above processing steps, this system can comprehensively improve the health management, dietary support, and quality of daily life of elderly people, and reduce the burden on caregivers.

[0822] (Application example 1)

[0823] 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."

[0824] To provide health management, dietary support, and daily living support for the elderly in a unified manner, it is necessary to use multiple different systems and devices, which poses the problem of complex data integration and operation between each system. There is also the risk that the elderly themselves and their caregivers may forget certain procedures or not receive information at the appropriate time. For this reason, there is a need for a system that can efficiently and safely improve the quality of health management, meal plan proposals and implementation, and daily life for the elderly.

[0825] 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.

[0826] In this invention, the server includes means for collecting health information of the subject from a sensor, means for analyzing the collected health information and detecting abnormalities, means for notifying a medical facility when an abnormality is detected, means for generating a meal plan based on the health information, means for proposing the generated meal plan, means for automatically ordering food from a delivery service based on the proposed meal plan, means for generating and distributing content based on the subject's hobbies and interests, and means for monitoring location information and notifying when the subject goes out. This makes it possible to comprehensively and efficiently improve the health management, meal support, and quality of daily life of the elderly.

[0827] A "sensor" is a device used to collect biometric information about a subject, such as blood pressure, heart rate, and body temperature.

[0828] "Analysis" refers to the process of processing and evaluating collected data to determine whether or not there are any abnormalities.

[0829] "Notification" is the act of automatically sending alerts and information to medical facilities and caregivers when an abnormality is detected.

[0830] "Meal Plan" means a customized meal plan based on a Subject's health status and personal preferences, designed to maintain or improve health.

[0831] "Means for automatically placing orders with delivery services" is a function that automatically places orders with affiliated food delivery services based on the generated meal plan.

[0832] "Content" means information and entertainment content provided according to the hobbies and interests of the target user, including music, articles, videos, etc.

[0833] "Location information" refers to geographic location data collected through a subject's device and is used to monitor the subject's movements when out and about.

[0834] "Feedback" refers to opinions and impressions provided by users, and is information collected to improve the quality of service provided by the system.

[0835] This invention is a system that provides health management, dietary support, and daily living support for the elderly, and is linked by a server, terminals, and users. This system collects health information of the target person from sensors and converts it into customized suggestions to realize comprehensive nursing support.

[0836] Server Roles

[0837] 1. Health data collection and analysis

[0838] The server periodically collects health data (blood pressure, heart rate, body temperature, etc.) from sensors worn by the subject. This data is sent to a smartphone via Bluetooth, and then from the smartphone to the server via a REST API. The server analyzes the data using Python and TensorFlow to evaluate the subject's health. If an abnormality is detected, the server automatically notifies medical facilities.

[0839] 2. Meal plan generation and automatic ordering

[0840] Based on the collected health data and the individual's preferences, the server generates an appropriate meal plan, which is then automatically ordered from a partner food delivery service via an API.

[0841] 3. Content generation and distribution

[0842] The server generates customized content based on the user's hobbies and interests, including music playlists, articles, videos, and more, and delivers it to the device at the appropriate time.

[0843] Device Role

[0844] 1. Data Receipt and Notification

[0845] The device receives the health analysis results and meal plans sent from the server and notifies the patient and their caregiver, as well as the contents of the meal and the scheduled delivery time.

[0846] 2. Gathering feedback

[0847] The device collects feedback from the user and sends it to the server, which uses it to improve the service for the next time.

[0848] 3. Location monitoring

[0849] When the target person goes out, the device monitors their location and sends notifications to ensure their safety.

[0850] User Roles

[0851] The user receives information provided through the device and contacts medical facilities as needed, for example, checks alerts from the device and takes prescribed medication promptly, checks suggested meal plans, and receives meals from delivery services.

[0852] Specific examples

[0853] The participants' daily blood pressure and heart rate measurements are sent to a server via their smartphone. The server analyzes the data and notifies medical facilities as needed. Based on their health status, a customized meal plan is generated and automatically ordered from a food delivery service. For example, if the patient has high blood pressure, a low-salt diet is suggested, and grilled salmon is delivered to their home for dinner.

[0854] Example of input prompt for generative AI model

[0855] Health Data:

[0856] Blood pressure: 125 / 80

[0857] Heart rate: 70

[0858] Temperature: 36.5

[0859] Preferences: Low carb

[0860] Suggested meal plan:

[0861] Breakfast: Oatmeal and berries

[0862] Lunch: Grilled chicken salad

[0863] Dinner: Grilled salmon and vegetables

[0864] In this way, the system of the present invention can comprehensively improve the health management, dietary support, and quality of daily life of the elderly.

[0865] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0866] Step 1:

[0867] The server collects health data (blood pressure, heart rate, body temperature, etc.) from the subject's sensors (such as a smartwatch). The sensors send the data to a smartphone via Bluetooth, and the smartphone app sends it to the server through a REST API. The input is the health data from the sensors, and the output is the raw data stored on the server.

[0868] Step 2:

[0869] The server analyzes the collected health data. The analysis is performed using Python and TensorFlow to detect outliers. The input is the collected raw data, and the output is the analysis result (normal / abnormal determination). If an abnormality is detected, the server automatically sends a warning notification to the medical facility.

[0870] Step 3:

[0871] The server generates an appropriate meal plan based on the collected health data and the subject's preferences. The generated meal plan is stored in the server's database. The input is the analyzed health data and the subject's preference information, and the output is a customized meal plan.

[0872] Step 4:

[0873] The server automatically places meal orders with partner delivery services based on the generated meal plan. Orders are placed via the partner delivery service's API. The input is the generated meal plan, and the output is the placed order information.

[0874] Step 5:

[0875] The device receives the analysis results and meal plan details sent from the server and notifies the subject and caregiver. Notifications are made by voice, vibration, or screen display. The input is the notification information sent from the server, and the output is the notification displayed on the subject's device.

[0876] Step 6:

[0877] The user receives notification of the provided meal plan through the terminal, receives the delivered meal, and sends feedback about the meal to the server through the terminal. The input is the user's feedback based on the provided meal, and the output is the feedback data sent to the server.

[0878] Step 7:

[0879] The server generates customized content (music playlists, articles, videos, etc.) based on the user's hobbies and interests and delivers it to the device. The input is data about the user's interests, and the output is the generated content.

[0880] Step 8:

[0881] The device monitors the location information when the subject goes out and sends appropriate notifications to ensure safety. The input is the subject's location data, and the output is a safety notification when the subject goes out.

[0882] In this way, this system can coordinate multiple processing steps to provide health management, dietary support, and daily living support for the elderly.

[0883] 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.

[0884] This invention relates to a system that utilizes AI and an emotion engine to provide health management, dietary support, and daily life support for the elderly. As explained below, this system realizes functions that comprehensively improve the quality of life for the elderly by linking the server, terminals, and users and combining the emotion engine.

[0885] Health management support

[0886] server

[0887] The server periodically collects the latest health data from the subject's sensors, including blood pressure, heart rate, and body temperature.

[0888] The collected data is processed by an analysis algorithm on the server, which compares it with normal ranges to detect abnormalities.

[0889] If an abnormality is detected, the server notifies the medical facility via email or API.

[0890] Terminal

[0891] The analysis results sent from the server are received and notified to the subject and caregiver. For example, a message such as "Your blood pressure is high. Please contact a medical facility." is displayed.

[0892] It also sends out alerts to prevent you from forgetting to take your medicine. For example, it will notify you at 9pm every night that it's time to take your medicine.

[0893] User

[0894] Users receive notifications from their devices, contact medical facilities as needed, and manage health risks by taking prescribed medications at the appropriate times.

[0895] Meal support

[0896] server

[0897] The server generates a customized meal plan based on the subject's health information and dietary preferences, suggesting low-carb options for a diabetic, for example.

[0898] Based on this meal plan, meal orders are placed with affiliated delivery services.

[0899] Terminal

[0900] The system receives meal plan information sent from the server and notifies the user of the next meal and estimated delivery time. For example, it displays, "Dinner will arrive at 7 p.m. The menu is grilled salmon."

[0901] User

[0902] Users can check the meal plan provided and receive meals from the delivery service through the device, and can also provide feedback on the taste and quality of the meal through the device.

[0903] Daily life support

[0904] server

[0905] The server generates customized content based on the subject's hobbies and interests, including music playlists, videos, articles, and more.

[0906] The content is delivered to the device at the appropriate time, for example, a classical music playlist when the person is relaxing in the morning.

[0907] Terminal

[0908] Receives content sent from the server and provides it to the target user, for example, playing a music playlist through a speaker.

[0909] When the target person goes out, the location information is monitored and a timely notification is sent to ensure safety. For example, a notification such as "Your current location is in a park" is sent periodically.

[0910] Utilizing the Emotion Engine

[0911] server

[0912] The emotion engine recognizes emotions from the target person's facial expressions, tone of voice, etc. and adapts behavior accordingly.

[0913] Based on the recognized emotions, more personalized content can be generated and delivered, for example, if the target person is feeling stressed, it can suggest relaxing music or soothing videos.

[0914] The results of health analysis will also be adjusted based on your emotional state. For example, if you are under high stress, your health data will be analyzed more carefully than usual.

[0915] Terminal

[0916] The device receives feedback from the emotion engine and provides real-time support according to the user's emotional state. For example, if the device detects that the user is stressed, it will play soothing content.

[0917] User

[0918] Users can receive services adapted to their emotional state through their devices. By accepting suggestions and notifications based on their emotional state, they can live their daily lives more comfortably.

[0919] This system will enable comprehensive care support for the elderly, including health management, dietary support, improving the quality of daily life, and even addressing their emotional state.

[0920] The processing flow will be explained below.

[0921] Health management support

[0922] Step 1:

[0923] server

[0924] The server periodically collects health data such as blood pressure, heart rate, and body temperature from the subject's sensors, which are typically wearable devices.

[0925] Step 2:

[0926] server

[0927] The collected health data is processed using an analytical algorithm. For example, if blood pressure exceeds 160 / 100 mmHg, it is deemed abnormal.

[0928] Step 3:

[0929] server

[0930] If an abnormality is detected, the server automatically notifies the medical facility, including details of the abnormality and the latest health data.

[0931] Step 4:

[0932] Terminal

[0933] The analysis results sent from the server are received and notified to the subject and caregiver. For example, a message such as "Your blood pressure is high. Please contact a medical facility" is displayed on the screen.

[0934] Step 5:

[0935] Terminal

[0936] To prevent forgetting to take medicine, the device will send out periodic alerts. At 9 p.m. every night, it will notify you by voice or vibration that it's time to take your medicine.

[0937] Meal support

[0938] Step 1:

[0939] server

[0940] It generates a customized meal plan based on the individual's health information and dietary preferences, suggesting low-carb options for someone with diabetes, for example.

[0941] Step 2:

[0942] server

[0943] Based on the meal plan, you will place a meal order with a partner delivery service, which will include meal details and delivery times.

[0944] Step 3:

[0945] Terminal

[0946] It receives meal plan and delivery information sent from the server and notifies the user of the next meal and estimated delivery time. It displays, "Dinner will arrive at 7 p.m. The menu is grilled salmon."

[0947] Daily life support

[0948] Step 1:

[0949] server

[0950] The server generates customized content based on the user's hobbies and interests, such as music playlists or TV show listings.

[0951] Step 2:

[0952] server

[0953] The generated content is delivered to the device at the appropriate time, for example, a classical music playlist is sent in the morning when the target person is relaxing.

[0954] Step 3:

[0955] Terminal

[0956] Receives content sent from the server and provides it to the target user, for example, playing a music playlist through a speaker.

[0957] Step 4:

[0958] Terminal

[0959] When the target person goes out, GPS technology is used to monitor their location and periodically notify them of their current location, with a message such as "Your current location is in a park" displayed on the screen.

[0960] Utilizing the Emotion Engine

[0961] Step 1:

[0962] server

[0963] The emotion engine is used to recognize emotions by analyzing the subject's facial expressions and tone of voice. For example, it analyzes data acquired through a camera and microphone to identify emotions such as stress or joy.

[0964] Step 2:

[0965] server

[0966] Based on the emotions recognized, the system generates more personalized content, for example, suggesting relaxing music or meditation videos if the subject is feeling stressed.

[0967] Step 3:

[0968] Terminal

[0969] The device receives emotion-based content sent from the server and provides it to the subject in real time. For example, if stress is detected, the device will play soothing music.

[0970] User Interaction

[0971] Step 1:

[0972] User

[0973] The user checks the notification from the device and takes action based on the provided information. For example, if the user receives a notification to take medicine, the user takes the medicine promptly.

[0974] Step 2:

[0975] User

[0976] Receive meals based on a suggested meal plan and enjoy content, such as a new music playlist, to enhance your relaxation time.

[0977] Step 3:

[0978] User

[0979] Accept suggestions and notifications based on emotion monitoring to make your daily life more comfortable. For example, if you are feeling stressed, you can watch a meditation video to relax.

[0980] Through these processing steps, a comprehensive care system is realized that includes health management, meal support, daily living assistance, and emotional care for the elderly.

[0981] Example 2

[0982] 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."

[0983] A system that provides integrated health management, dietary support, and daily life support for the elderly is needed. In particular, there is a need for systems that can detect abnormalities in health data and notify medical facilities, generate and deliver meal plans based on health information, provide content based on hobbies and interests in daily life, and ensure safety when out and about. Comprehensive support that takes into account the emotional state of the recipient and promotes relaxation and stress reduction is also needed.

[0984] 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.

[0985] In this invention, the server includes means for collecting health information of the subject from a sensor, means for analyzing the collected health information and detecting abnormalities, means for notifying a medical facility when an abnormality is detected, means for generating a meal plan based on the health information, means for proposing the generated meal plan, means for generating and distributing content based on the subject's hobbies and interests, means for monitoring location information and notifying when the subject goes out, and means for recognizing the subject's emotional state and adapting behavior based thereon. This enables health management, meal support, improvement of quality of daily life for the elderly, and comprehensive care support that responds to emotional states.

[0986] A "sensor" is a device used to collect a subject's health information (blood pressure, heart rate, body temperature, etc.) in real time.

[0987] "Analysis" refers to data processing procedures for detecting abnormal values ​​based on collected health information.

[0988] "Notification" is a means of transmitting information to medical facilities and the like when an abnormality is detected.

[0989] A "meal plan" refers to a meal menu customized for health management based on a subject's health information and dietary preferences.

[0990] "Content" refers to information and entertainment generated based on the subject's hobbies and interests.

[0991] "Location information" is data that indicates the subject's current geographic location.

[0992] "Emotional state" is the result of recognizing the subject's current psychological state from facial expressions, tone of voice, etc.

[0993] "Delivery service" refers to a service that delivers food based on a meal plan to the target person.

[0994] An "alert" is a notification sent to prevent you from forgetting to take your medicine.

[0995] The present invention relates to a system that provides integrated health management, dietary support, and daily life support for the elderly. This system improves the quality of life for the elderly in a comprehensive manner by linking a server, terminals, and users and by utilizing an emotion engine. A specific embodiment of the system is shown below.

[0996] Health management support

[0997] server

[0998] The server collects health data such as the subject's blood pressure, heart rate, and body temperature from sensors in wearable devices and other devices. This data is collected using cloud services such as AWS IoT and Google Cloud IoT Core. The collected data is processed using analysis algorithms written in Python or R. Data analysis evaluates whether the subject's health data is within the normal range and detects abnormal values. For example, if blood pressure is higher than normal, it is determined to be abnormal.

[0999] If an abnormality is detected, the server uses the Twilio API to send a notification to the medical facility. The notification includes basic information about the subject and the type of abnormality. For example, a notification such as "Subject A's blood pressure is 180 / 120. Emergency treatment is required" may be sent.

[1000] Terminal

[1001] The device receives the analysis results sent from the server. This is done using Firebase or REST API. The received information is notified to the subject and caregiver. Specifically, it displays a message saying, "Your blood pressure is high. Please contact a medical facility." Additionally, to prevent forgetting to take medication, an alert is displayed every night at 9 p.m. saying, "It's time to take your medication."

[1002] User

[1003] The user receives notifications from the device and contacts a medical facility as needed. For example, if an abnormality in blood pressure is detected, the user can call a medical facility. Also, based on the alerts on the device, the user can take prescribed medication at the specified time.

[1004] Meal support

[1005] server

[1006] The server generates a customized meal plan using a cloud-based database (e.g., Firebase Firestore) based on the subject's health information and dietary preferences. For example, it creates a low-carb menu for a diabetic patient. Based on this meal plan, the server issues an order to a partner delivery service (e.g., Uber Eats API). The server provides the subject's information (address, meal contents) to the delivery service.

[1007] Terminal

[1008] The device receives the meal plan information sent from the server. Firebase and REST APIs are also used for this. The device then notifies the target user of the next meal plan and the estimated delivery time. For example, it might display, "Dinner will arrive at 7 p.m. The menu is grilled salmon."

[1009] User

[1010] The user checks the provided meal plan on the device and receives the meal from the delivery service. Specifically, they receive a grilled salmon meal at 7 p.m. They also send feedback about the taste and quality of the meal to the server via the device. For example, they can enter, "The grilled salmon was delicious, but I wish it was a little less salty."

[1011] Daily life support

[1012] server

[1013] The server uses the Spotify API or Netflix API to generate content based on the user's hobbies and interests. For example, it creates a playlist of relaxing classical music or an interesting video. The generated content is delivered to the user's device at the time they want. For example, a classical music playlist is sent to relax in the morning.

[1014] Terminal

[1015] The device receives the content sent from the server and provides it to the target person. For example, it plays a generated music playlist from a speaker. The device also monitors the target person's location using its GPS function and sends notifications to ensure their safety. Specifically, the device periodically notifies the target person that "Your current location is in a park."

[1016] User

[1017] Users can check notifications from their devices to ensure their safety. They can listen to classical music during relaxation time, or check location notifications to confirm that they are in a park or other location.

[1018] Utilizing the Emotion Engine

[1019] server

[1020] The server uses an emotion engine such as Microsoft Azure Cognitive Services to recognize emotions from the subject's facial expressions and tone of voice. Specifically, it determines whether the subject is stressed or relaxed. Based on the recognized emotions, it generates more personalized content, for example, suggesting music or videos to relax the subject if they are stressed. It also adjusts the analysis results of health information based on the subject's emotional state. For example, when the subject is in a high stress state, it analyzes health data more carefully.

[1021] Terminal

[1022] The device receives feedback from the emotion engine and provides support that adapts to the user's emotional state in real time. For example, if the device detects stress, it will play soothing music or videos.

[1023] User

[1024] Users can receive services adapted to their emotional state through their devices. For example, listening to soothing music when feeling stressed can help users lead a more comfortable daily life.

[1025] This system can provide comprehensive care support for the elderly, including health management, dietary support, improving the quality of daily life, and even addressing their emotional state.

[1026] Prompt Sentence Examples

[1027] You want to develop a system to provide health management, meal support, and daily life support for the elderly. Collect and analyze health data, customize meal plans, order them from delivery services, and deliver customized content at the right time. Consider how to incorporate an emotion engine into this system to provide more personalized support.

[1028] Based on this example and prompt, it is believed that it will be easier to understand the system's functionality and how it is implemented.

[1029] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1030] Health management support

[1031] server

[1032] Step 1:

[1033] The server collects health data from the sensors.

[1034] Input: Data such as blood pressure, heart rate, and temperature obtained from wearable devices.

[1035] Output: Store the collected health data in a cloud database.

[1036] Specific operation: Uses AWS IoT or Google Cloud IoT Core to acquire data in real time and store it in a database.

[1037] Step 2:

[1038] The server analyzes the collected health data.

[1039] Input: Health data stored in a cloud database.

[1040] Output: Analyzed data results (e.g. outlier detection).

[1041] What it does: It uses analytics algorithms written in Python or R to compare data with health standards and detect abnormalities. For example, a blood pressure of 180 / 120 is considered abnormal.

[1042] Step 3:

[1043] The server notifies the medical facility if an abnormality is detected.

[1044] Input: Parsed data results.

[1045] Output: Notification sent to healthcare facility.

[1046] Specific behavior: Uses the Twilio API to send notifications to medical facilities via email and SMS. Example: "Subject A's blood pressure is 180 / 120. Emergency treatment is required."

[1047] Terminal

[1048] Step 1:

[1049] The terminal receives the analysis result from the server.

[1050] Input: Analysis results sent from the server.

[1051] Output: Analysis results displayed on the terminal.

[1052] Specific operation: Retrieves data via Firebase or REST API and displays it on the device screen.

[1053] Step 2:

[1054] The terminal notifies the analysis result.

[1055] Input: Received analysis results.

[1056] Output: Notification to subject and caregiver.

[1057] Specific behavior: Display "Your blood pressure is high. Please contact a medical facility." Also, display an alert every night at 9 PM saying "It's time to take your medication."

[1058] User

[1059] Step 1:

[1060] The user receives the notification and responds.

[1061] Input: Notifications from your device.

[1062] Output: Contact medical facility and take medication.

[1063] Specific actions: See the notification on the device, call a medical facility, see the notification at 9 PM, and take the prescribed medication.

[1064] Meal support

[1065] server

[1066] Step 1:

[1067] The server generates a meal plan based on the health information and dietary preferences.

[1068] Input: A database containing health information and dietary preferences.

[1069] Output: A customized meal plan.

[1070] What it does: It uses Firebase Firestore to retrieve information from a database and then uses an algorithm to generate a meal plan, for example, a low-carb menu for a diabetic.

[1071] Step 2:

[1072] The server issues orders to a delivery service based on the meal plan.

[1073] Input: The generated meal plan.

[1074] Output: Order information sent to the delivery service.

[1075] Specific operation: Use the Uber Eats API to provide the meal details and the target address to the delivery service. For example, specify "grilled salmon."

[1076] Terminal

[1077] Step 1:

[1078] The terminal receives the meal plan information from the server.

[1079] Input: Meal plan information sent from the server.

[1080] Output: Meal plan information displayed on the device.

[1081] Specific behavior: Receives data via Firebase or REST API and displays the next meal contents and estimated delivery time. Example: Notifies "Dinner will arrive at 7pm. The menu is grilled salmon."

[1082] User

[1083] Step 1:

[1084] The user confirms and receives the meal plan.

[1085] Input: Meal plan information provided on device.

[1086] Output: Meals from a delivery service.

[1087] Specific action: Pick up a grilled salmon meal from a delivery service at 7pm.

[1088] Step 2:

[1089] The user provides feedback.

[1090] Input: Feedback on the taste and quality of the food provided.

[1091] Output: Feedback information sent to the server.

[1092] Specific action: Enter "The grilled salmon was delicious, but I wish it was a little less salty" into the device.

[1093] Daily life support

[1094] server

[1095] Step 1:

[1096] The server generates content based on hobbies and interests.

[1097] Input: A database storing the subject's hobbies and interests.

[1098] Output: The generated content.

[1099] What it does: Uses Spotify API and Netflix API to generate music playlists and videos tailored to the target audience. For example, create a classical music playlist.

[1100] Step 2:

[1101] The server distributes the generated content.

[1102] Input: Generated content.

[1103] Output: Content information delivered to the device.

[1104] What it does: Send a morning relaxation classical music playlist via Firebase Cloud Messaging or the REST API.

[1105] Terminal

[1106] Step 1:

[1107] The terminal receives the content transmitted from the server.

[1108] Input: Content information sent from the server.

[1109] Output: The content that is displayed or played on a device.

[1110] Specific operation: Play the received music playlist from the speaker.

[1111] Step 2:

[1112] The terminal monitors and notifies the location information.

[1113] Input: Location information obtained by GPS.

[1114] Output: Location-based notifications.

[1115] Specific operation: Notify "Your current location is a park" at regular intervals.

[1116] User

[1117] Step 1:

[1118] The user uses the distributed content.

[1119] Input: Content displayed or played on the device.

[1120] Output: Satisfaction and relaxation from the content used.

[1121] Specific action: Listen to classical music during relaxation time.

[1122] Step 2:

[1123] The user checks the location information notification.

[1124] Input: Location notification from device.

[1125] Output: Your current safety status.

[1126] Specific operation: Check the notification on the device to confirm that you are in the park correctly.

[1127] Utilizing the Emotion Engine

[1128] server

[1129] Step 1:

[1130] The server analyzes the emotion data using an emotion engine.

[1131] Input: Data based on the subject's facial expressions and tone of voice.

[1132] Output: Parsed emotional state.

[1133] How it works: Using Microsoft Azure Cognitive Services, it analyzes whether a subject is stressed or relaxed.

[1134] Step 2:

[1135] The server generates personalized content based on the emotional state.

[1136] Input: Parsed emotional state.

[1137] Output: Personalized content.

[1138] Specific operation: When you are feeling stressed, generate and transmit music or images to help you relax.

[1139] Step 3:

[1140] The server analyzes the health data to reflect the emotional state.

[1141] Input: Parsed emotional state and collected health data.

[1142] Output: Analysis results of health data taking into account emotional state.

[1143] Specific behavior: When the emotional state is stressful, analyze health data more carefully.

[1144] Terminal

[1145] Step 1:

[1146] The device receives feedback from the emotion engine.

[1147] Input: Parsed emotional state.

[1148] Output: Service depending on emotional state.

[1149] Specific operation: Play music and video in real time according to the emotional state.

[1150] User

[1151] Step 1:

[1152] The user receives a service adapted to his emotional state.

[1153] Input: Emotion-based service provided by the device.

[1154] Output: Relaxation and satisfaction depending on emotional state.

[1155] Specific action: Listen to soothing music when you feel stressed and make your daily life more comfortable.

[1156] (Application example 2)

[1157] 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."

[1158] In the daily lives of elderly people, there is a need to efficiently manage their health, provide dietary support, and recognize their emotions to improve their quality of life. However, these functions are currently provided individually, and there is no integrated support system, which places a heavy burden on elderly people and their caregivers. Furthermore, the lack of support in response to emotional changes makes it difficult to reduce stress and anxiety.

[1159] 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.

[1160] In this invention, the server includes means for collecting health information of the subject from a sensor, means for analyzing the collected health information and detecting abnormalities, means for notifying a medical facility when an abnormality is detected, means for generating a meal plan based on the health information, means for proposing the generated meal plan, means for generating and distributing content based on the subject's hobbies and interests, means for monitoring location information and notifying when the subject goes out, and means for recognizing emotions and adapting behavior based on emotions. This enables health management, meal support, and emotion recognition to be performed in an integrated manner, thereby comprehensively improving the quality of daily life of elderly people.

[1161] "Health information" is data that indicates the subject's physical condition, and specifically includes blood pressure, heart rate, body temperature, and the like.

[1162] A "sensor" is a device for collecting health information about a subject, and includes wearable devices and vital sign monitors.

[1163] "Analysis" refers to algorithmic methods used to process data and detect anomalies based on collected health information.

[1164] "Abnormal" refers to a state in which the subject's health information deviates from the normal range, indicating a condition requiring early intervention.

[1165] "Medical facility" refers to a place that provides medical services, such as a hospital or clinic.

[1166] A "meal plan" refers to a meal menu customized based on the subject's health information, and includes content that takes into consideration nutritional balance and health status.

[1167] "Recommendation" refers to the act of informing the subject or their caregiver of the generated meal plan.

[1168] "Hobbies and interests" refers to activities that the subject enjoys on a daily basis and areas of interest.

[1169] "Content" includes information materials such as videos, music, articles, etc. that are provided based on the subject's hobbies and interests.

[1170] "Distribution" refers to the act of delivering the generated content to the target audience, which may be via the Internet or a local network.

[1171] "Location information" is data that indicates a subject's current physical location and is obtained using technologies such as GPS.

[1172] "Notification" refers to the act of informing a subject or their caregiver of necessary information, and may take the form of an alert or message.

[1173] "Emotion recognition" refers to the technology of determining a subject's emotions from their facial expressions, tone of voice, etc.

[1174] "Behavioral adaptation" refers to the act of responding to provide services and content that meet the needs of the target person based on emotion recognition.

[1175] This invention relates to a comprehensive system that provides health management, dietary support, and daily life support for the elderly. This system aims to improve the quality of life of the target individuals by linking the server, terminals, and users, and by combining an emotion engine.

[1176] Health management support

[1177] server

[1178] The server periodically collects health information from the subject's sensors. This health information includes blood pressure, heart rate, and body temperature. The collected data is processed by an analysis algorithm on the server and compared with the normal range to detect abnormalities. If an abnormality is detected, the server notifies medical facilities. Notification methods include email and API.

[1179] Terminal

[1180] The device receives the analysis results sent from the server and notifies the subject and caregiver. For example, it displays a message saying, "Your blood pressure is high. Please contact a medical facility." To prevent patients from forgetting to take their medication, the device also sends an alert every night at 9 p.m. saying, "It's time to take your medication."

[1181] User

[1182] Users receive notifications from their devices, contact medical facilities as needed, and manage health risks by taking prescribed medications at the appropriate times.

[1183] Meal support

[1184] server

[1185] The server generates a customized meal plan based on the user's health information and dietary preferences. For example, it suggests low-carb options for diabetics. Based on this meal plan, it issues a meal order to a partner delivery service.

[1186] Terminal

[1187] The device receives the meal plan information sent from the server and notifies the user of the next meal and the estimated delivery time. For example, it displays, "Dinner will arrive at 7 p.m. The menu is grilled salmon."

[1188] User

[1189] Users can check the meal plan provided and receive meals from the delivery service through the device, and can also provide feedback on the taste and quality of the meal through the device.

[1190] Daily life support

[1191] server

[1192] The server generates customized content based on the user's hobbies and interests, including music playlists, videos, and articles. The content is delivered to the device at the appropriate time. For example, a classical music playlist could be sent when the user is relaxing in the morning.

[1193] Terminal

[1194] The device receives the content sent from the server and provides it to the target person. For example, a music playlist can be played from a speaker. When the target person goes out, the device monitors the target person's location and sends timely notifications to ensure their safety. For example, the device periodically sends a notification saying, "Your current location is in a park."

[1195] Utilizing the Emotion Engine

[1196] server

[1197] The server uses an emotion engine to recognize emotions from the subject's facial expressions, tone of voice, and other factors. Based on the recognized emotions, the server generates and delivers more personalized content. For example, if the subject is feeling stressed, it will suggest relaxing music or soothing videos. The results of health information analysis are also adjusted according to the subject's emotional state. For example, when the subject is under high stress, the server will analyze health data more carefully than usual.

[1198] Terminal

[1199] The device receives feedback from the emotion engine and provides real-time support according to the subject's emotional state. For example, if the device detects stress in the subject, it will play soothing content.

[1200] User

[1201] Users can receive services adapted to their emotional state through their devices. By accepting suggestions and notifications based on their emotional state, they can live their daily lives more comfortably.

[1202] Hardware and software used

[1203] The system utilizes hardware such as smartphones, head-mounted displays, and smart glasses, as well as software such as Python programs, RESTful APIs, and emotion recognition algorithms.

[1204] Specific examples

[1205] For example, if a user sends their health data to a server, the server can detect that they have high blood pressure and suggest a low-salt diet plan. If the app's emotion recognition function determines that the user is feeling stressed, it can suggest relaxing music and videos.

[1206] Prompt Sentence Examples

[1207] "Enter your latest health data: blood pressure, heart rate, temperature"

[1208] "Please tell us your current emotional state: happy, sad, stressed, neutral"

[1209] "What is your suggested meal plan based on my current health condition?"

[1210] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1211] Step 1: Collecting health data

[1212] Input: Sensors collect the subject's health information (blood pressure, heart rate, temperature).

[1213] Server behavior:

[1214] The server receives health data sent from sensors, specifically from wearable devices and vital sign monitors, and stores the data.

[1215] Output: The collected health data is stored on the server.

[1216] Step 2: Analyzing health data

[1217] Input: Collected health data

[1218] Server behavior:

[1219] The subject's health data is analyzed using an analysis algorithm (for example, using a Python library) on the server. The analysis detects abnormalities by comparing the health information with the normal range.

[1220] Output: The analysis results (normal or abnormal) are generated and saved.

[1221] Step 3: Notification of abnormalities

[1222] Input: If the analysis result is abnormal

[1223] Server behavior:

[1224] If an abnormality is detected, the server notifies the medical facility by email or using a RESTful API.

[1225] Output: A notification to the healthcare facility is sent.

[1226] Step 4: Generate a meal plan

[1227] Input: Health data and analysis results

[1228] Server behavior:

[1229] The server generates a customized meal plan based on the subject's health information and dietary preferences. The meal plan is created using a nutrition calculation algorithm.

[1230] Output: The generated meal plan is saved.

[1231] Step 5: Meal plan suggestions

[1232] Input: Generated meal plan

[1233] Server behavior:

[1234] The server transmits the generated meal plan to the terminal.

[1235] Device operation: The device notifies the recipient and their caregiver of the received meal plan. For example, it displays, "Dinner will arrive at 7 p.m. The menu is grilled salmon."

[1236] Output: The subject and / or caregiver will be notified of the meal plan information.

[1237] Step 6: Order from a delivery service

[1238] Enter: Check Meal Plan

[1239] Terminal behavior:

[1240] After the user confirms the meal plan, the device issues an order to the partner delivery service, specifically by sending the order information using the delivery service's API.

[1241] Output: A food order is placed with the delivery service.

[1242] Step 7: Recognize emotions

[1243] Input: Subject's facial expressions and tone of voice

[1244] Terminal behavior:

[1245] The device's camera and microphone are used to recognize the subject's emotions, and an emotion engine (AI model) is used to analyze the collected data.

[1246] Output: The recognized emotion is saved on the device.

[1247] Step 8: Adapting behavior based on emotions

[1248] Input: Recognized emotion

[1249] Server behavior:

[1250] Based on the emotions detected, the server generates and sends personalized content to the device, such as relaxing music or soothing videos.

[1251] Terminal behavior:

[1252] The device then provides the received content to the subject, for example, playing relaxing music if the subject is feeling stressed.

[1253] Output: Personalized content is provided to the subject, improving their emotional state.

[1254] 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.

[1255] 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.

[1256] 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.

[1257] [Third embodiment]

[1258] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1259] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1260] 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).

[1261] 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.

[1262] 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.

[1263] 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).

[1264] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1265] 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.

[1266] 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.

[1267] 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.

[1268] 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.

[1269] 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."

[1270] The present invention relates to a system that utilizes AI to provide health management, dietary support, and daily life support for the elderly. This system realizes comprehensive nursing support through collaboration between a server, a terminal, and a user. Specific embodiments of the present invention are described below.

[1271] Health management support

[1272] server

[1273] The server periodically collects the latest health data (blood pressure, heart rate, body temperature, etc.) from the subject's sensors. The sensors are wearable devices worn by the subject.

[1274] The collected data is processed by an analytical algorithm on the server. For example, if blood pressure exceeds the normal range, it is determined to be abnormal.

[1275] If an abnormality is detected, the server will promptly notify the medical facility via email or automated communication via API.

[1276] Terminal

[1277] The device receives the health status analysis results sent from the server and notifies the subject and caregiver. For example, the device screen displays a message saying, "Your blood pressure is high. Please contact a medical facility."

[1278] It also has a function to send out an alert so that you don't forget to take your medicine, notifying you with sound and vibration when it's time to take your medicine.

[1279] User

[1280] The user receives notifications from the device and contacts the medical facility as needed, for example, by checking the alert from the device and taking the prescribed medication promptly.

[1281] Meal support

[1282] server

[1283] The server generates a customized meal plan based on the individual's health information and preferences, suggesting low-carb options for someone with diabetes, for example.

[1284] Orders are placed with partner delivery services based on the meal plan.

[1285] Terminal

[1286] The device receives the meal plan information sent from the server and notifies the user of the next meal and the scheduled delivery time. For example, it displays, "Dinner will be delivered at 7 p.m. The menu is grilled salmon."

[1287] User

[1288] Users can view the proposed meal plan and receive meals from the delivery service through the device, and can also provide feedback on the meals.

[1289] Daily life support

[1290] server

[1291] The server generates customized content based on the subject's hobbies and interests, including music playlists, articles, videos, and more.

[1292] The content is delivered to the terminal at the appropriate time.

[1293] Terminal

[1294] The content sent from the server is received and provided to the subject, for example, by playing a music playlist to help the subject relax.

[1295] In addition, when the target person goes out, their location information is monitored and notifications are sent to ensure their safety.

[1296] User

[1297] Users can select and enjoy their favorite content through their device, and when they go out, they can receive location information from the device, allowing them to move around with peace of mind.

[1298] This system will improve the health management, dietary support, and quality of daily life of the recipient, while also reducing the burden on caregivers and realizing more efficient and safe care.

[1299] The processing flow will be explained below.

[1300] Health management support

[1301] Step 1:

[1302] server

[1303] Health data such as blood pressure, heart rate, and body temperature are collected from sensors worn by the subjects, and the data is periodically sent to a server via an API.

[1304] Step 2:

[1305] server

[1306] The collected health data is analyzed and compared with the standard values ​​within the healthy range to check for abnormalities. For example, blood pressure of 160 / 100 mmHg or higher is determined to be high blood pressure.

[1307] Step 3:

[1308] server

[1309] If an abnormality is detected, the system automatically notifies the medical facility via email or API, and includes details of the abnormality and the subject's latest health data.

[1310] Step 4:

[1311] Terminal

[1312] Receives analysis results sent from the server. For example, if blood pressure is high, displays a message saying "Your blood pressure is high. Please contact a medical facility."

[1313] Step 5:

[1314] Terminal

[1315] It sends out alerts to prevent you from forgetting to take your medicine. For example, it notifies you every night at 9pm that it's time to take your medicine.

[1316] Meal support

[1317] Step 1:

[1318] server

[1319] Generate a meal plan based on the subject's health information (e.g., diabetes) and preferences, for example, selecting low-carb menus.

[1320] Step 2:

[1321] server

[1322] It proposes meal plans and places meal orders with partner delivery services, including menu details and delivery times.

[1323] Step 3:

[1324] Terminal

[1325] It receives information from the server and notifies the user of the next meal and the estimated delivery time. It displays, "Dinner will arrive at 7 p.m. The menu is grilled salmon."

[1326] Daily life support

[1327] Step 1:

[1328] server

[1329] It takes the user's hobbies and interests from a database and generates customized content, for example, creating a playlist of the latest classical music for a user who likes classical music.

[1330] Step 2:

[1331] server

[1332] The generated content is delivered to the device at the appropriate time, for example, sending a music playlist to relax in the morning.

[1333] Step 3:

[1334] Terminal

[1335] Receive and play content sent from a server, for example, playing a music playlist through a speaker.

[1336] Step 4:

[1337] Terminal

[1338] When the subject goes out, the location information is monitored by GPS. The location information is periodically checked and notified to the subject and caregiver.

[1339] User Interaction

[1340] Step 1:

[1341] User

[1342] Receive notifications from your device to check your health status and diet, and take necessary actions, such as taking medicine based on the notification.

[1343] Step 2:

[1344] User

[1345] Enjoy suggested meal plans and content, and provide feedback through your device.

[1346] This will complete a process in which the entire system works together to provide multifaceted support for the lives of the elderly.

[1347] Example 1

[1348] 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."

[1349] In today's aging society, there is an increasing need for systems that provide comprehensive health management, dietary support, and daily life support for the elderly. However, conventional systems often provide these support services separately, making it difficult to achieve integrated and efficient care. Furthermore, it is difficult to quickly and accurately respond to various issues, such as detecting abnormal health conditions, notifying users when medication should be taken, and meal planning. Another issue is the lack of personalized content tailored to the preferences and interests of each user.

[1350] 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.

[1351] In this invention, the server includes means for collecting the subject's biometric information from a measurement device, means for analyzing the collected biometric information and detecting abnormalities, means for notifying a medical institution when an abnormality is detected, means for generating a meal plan based on the biometric information, means for proposing the generated meal plan, means for generating and distributing content based on the subject's preferences and interests, means for monitoring location information and notifying the subject when the subject leaves the home, means for displaying the analysis results and notifying the subject and caregiver, and means for issuing alerts to encourage medication. This enables integrated health management, dietary support, and daily life support for the subject, enabling prompt and accurate responses. It also enables the provision of content tailored to the subject's individual needs.

[1352] "Target population" refers to users who receive support from this system, and primarily includes elderly people and those who require nursing care.

[1353] "Biometric information" refers to health data such as blood pressure, heart rate, and body temperature, which are measured and collected using measuring devices.

[1354] "Measuring devices" refer to wearable devices and sensors, which are equipment used to regularly record and collect biometric information from subjects.

[1355] "Server" refers to a central system for analyzing collected biometric information and detecting and notifying abnormalities, and includes cloud servers and data centers.

[1356] "Medical Institution" means a hospital, clinic, or medical facility to which you may be notified about any abnormal health condition.

[1357] A "meal plan" refers to a customized meal menu based on the subject's health condition and preferences, taking nutritional balance into consideration.

[1358] "Content" refers to information and entertainment generated based on a target's preferences and interests, including music playlists, articles, videos, etc.

[1359] "Location information" refers to the subject's current location and is collected via GPS data.

[1360] "Analysis results" refers to the results of data analysis conducted based on collected biometric information, including evaluation of health status and detection of abnormalities.

[1361] An "alert" refers to a notification sent from a device to alert users or encourage them to take action when they take medication or when an abnormality is detected.

[1362] "Notification" refers to a means of communicating abnormalities or important information to the subject, caregiver, or medical institution, and includes email, message, voice, etc.

[1363] This invention is a system that utilizes AI to provide comprehensive health management, dietary support, and daily life support for the elderly. This system operates in cooperation with a server, terminals, and users, and functions as follows:

[1364] Health management support

[1365] server

[1366] First, the server periodically collects biometric information such as blood pressure, heart rate, and body temperature from a wearable device (e.g., commonly known as a "measuring device") worn by the subject. The data is transferred via Bluetooth or Wi-Fi and stored on the server. The collected data is then processed and analyzed using machine learning algorithms and analysis algorithms written in Python or other languages. If an abnormal value is detected through this analysis, it is determined to be abnormal based on a set threshold. If an abnormality is detected, the server automatically sends a notification to the medical institution via the SMTP protocol or REST API.

[1367] As a specific example, the server collects heart rate data from the wearable device every five minutes, and if it detects an abnormal value, it sends an email to the medical institution stating, "Warning: The subject's heart rate has exceeded the normal range."

[1368] Terminal

[1369] The device (e.g., smartphone or tablet) receives the analysis results sent from the server and notifies the user. Using a dedicated health management app, a message will be displayed on the screen saying, "Your blood pressure is high. Please contact a medical institution." In addition, to prevent users from forgetting to take their medication, an alert will be sent via voice assistant or vibration when it is time to take the medication.

[1370] For example, the device will notify you with a voice notification at 8:00 a.m. saying, "It's time to take your medicine."

[1371] User

[1372] The user checks the notification from the device and contacts a medical institution if necessary. The user also receives an alert and takes action to ensure that they do not forget to take the prescribed medication.

[1373] Meal support

[1374] server

[1375] The server generates a customized meal plan based on the user's health status and preferences, using machine learning algorithms and nutritional databases to suggest appropriate menu items, and then issues an order to a partner delivery service.

[1376] For example, a server might suggest low-carb options for diabetics and send an order saying, "Please deliver low-carb grilled salmon for dinner tonight at 6 p.m."

[1377] Terminal

[1378] The device receives the meal plan and estimated delivery time sent from the server and notifies the user, displaying on the screen, "The next meal is scheduled to arrive at 7 p.m. and the menu is grilled salmon."

[1379] User

[1380] Users can check their meal plans and receive meals from the delivery service through their devices, and can also send feedback about their meals to the server through their devices.

[1381] Daily life support

[1382] server

[1383] The server generates customized content (e.g., music playlists, articles, videos, etc.) based on the user's preferences and interests, and delivers the generated content to the device at the appropriate time.

[1384] As a specific example, the server generates a music playlist for relaxation and transmits it to the terminal as a "playlist for afternoon relaxation time."

[1385] Terminal

[1386] The device receives the content sent from the server and provides it to the target user. It plays the playlist through a music player app or similar, allowing the target user to enjoy it. It also uses GPS to monitor the target user's location when they go out and sends notifications to ensure their safety.

[1387] User

[1388] Users can enjoy the content provided through the terminal, and when they go out, they can move around with peace of mind by receiving location information notifications from the terminal.

[1389] Examples of prompt statements

[1390] Health data collection settings: "Collect and analyze my heart rate data today."

[1391] Meal plan suggestions: "Please suggest low-carb meals for diabetics."

[1392] Content generation for daily living support: "Generate a relaxing music playlist for seniors."

[1393] This system will not only comprehensively improve the health management, dietary support, and quality of daily life of the elderly, but will also reduce the burden on their caregivers and provide more efficient and safer support.

[1394] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1395] Health management support

[1396] server

[1397] Step 1:

[1398] The server collects biometric information from the measurement device. The input is data from the wearable device (e.g., heart rate, blood pressure, body temperature). The data is sent to the server via Bluetooth or Wi-Fi. The output is biometric information stored in the server's database. Specifically, the server polls the data from the device every five minutes.

[1399] Step 2:

[1400] The server analyzes the collected biometric information. The input is the biometric information collected in the previous step. A machine learning algorithm written in Python is used for the analysis, and data that exceeds the normal range is judged to be abnormal. The output is the analysis results and the detection of abnormalities. Specifically, the data is input into the algorithm and compared with a threshold for detecting abnormal values.

[1401] Step 3:

[1402] The server notifies the medical institution if an abnormality is detected. The input is the analysis result from the previous step. The notification is sent via email or API request. The output is a warning message sent to the medical institution. Specifically, the server sends a warning email using the SMTP protocol.

[1403] Terminal

[1404] Step 4:

[1405] The terminal receives the analysis results sent from the server and notifies the user. The input is the analysis results from the server. A warning message is displayed on the screen through a dedicated application. The output is the warning message displayed on the screen. For example, it might say, "Your blood pressure is high, please contact a medical institution."

[1406] Step 5:

[1407] The device sends an alert to remind the user to take their medicine. The input is the scheduled time to take the medicine. The notification is sent via a voice assistant or vibration. The output is an alert notification to the user. Specifically, at 8:00 AM, the device notifies the user by voice, saying, "It's time to take your medicine."

[1408] User

[1409] Step 6:

[1410] The user checks the notification from the device and takes the necessary action. The input is a warning message or alert from the device. The output is the action of actually contacting a medical institution or taking medication. The specific action is the user checking the message and taking the prescribed medication.

[1411] Meal support

[1412] server

[1413] Step 1:

[1414] The server generates a meal plan based on the subject's health status and preferences. The input is pre-stored health and preference information. The meal plan is created using machine learning algorithms and a nutrition database. The output is a customized meal plan. Specifically, it generates a low-carb menu for diabetics.

[1415] Step 2:

[1416] The server issues an order to a partner delivery service based on the meal plan. The input is the generated meal plan. The order is sent using API communication. The output is the order sent to the delivery service. A specific operation is to send an order such as "Please deliver grilled salmon for tonight's dinner at 6 p.m."

[1417] Terminal

[1418] Step 3:

[1419] The terminal receives the meal plan and estimated delivery time sent from the server and notifies the user. The input is the meal plan information from the server. The next meal contents and estimated delivery time are displayed on the screen. The output is a notification to the user. For example, it might display "The next meal is scheduled to arrive at 7pm and the menu is grilled salmon."

[1420] User

[1421] Step 4:

[1422] The user checks the meal plan through the terminal and receives the meal from the delivery service. The input is a notification from the terminal. The user checks the actual menu and receives the meal. The output is the action of receiving the meal. The specific actions are the user checking the notification and receiving the meal from the delivery person.

[1423] Daily life support

[1424] server

[1425] Step 1:

[1426] The server generates customized content based on the subject's preferences and interests. The input is the subject's preference information. The generative AI model is used to generate the personalized content. The output is the generated content. A specific operation is to generate a relaxation music playlist.

[1427] Step 2:

[1428] The server delivers content to the terminal at the appropriate time. The input is the generated content. It is sent to the terminal according to the content delivery schedule. The output is the delivered content. A specific operation is to send a "playlist for afternoon relaxation time" to the terminal.

[1429] Terminal

[1430] Step 3:

[1431] The device receives content sent from the server and provides it to the target person. The input is content data from the server. The content is played using a music player app or similar. The output is the content provided to the target person. As a specific example, a music playlist can be played to support relaxation time.

[1432] Step 4:

[1433] The device monitors the location information when the target person goes out and sends a notification to ensure safety. The input is GPS data. The device tracks the target person's location in real time and sends a notification if the target person goes out of range. The output is a notification to ensure safety. Specifically, if the target person goes far away from home, the device sends a notification saying "Please check your current location."

[1434] User

[1435] Step 5:

[1436] Users enjoy content provided through their devices and receive location notifications when they are out and about. The inputs are notifications and content from the device. The outputs are the behavior of enjoying the content and ensuring safety based on location information. Specific actions include the user playing a music playlist, checking notifications, and moving safely.

[1437] Through the above processing steps, this system can comprehensively improve the health management, dietary support, and quality of daily life of elderly people, and reduce the burden on caregivers.

[1438] (Application example 1)

[1439] 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."

[1440] To provide health management, dietary support, and daily living support for the elderly in a unified manner, it is necessary to use multiple different systems and devices, which poses the problem of complex data integration and operation between each system. There is also the risk that the elderly themselves and their caregivers may forget certain procedures or not receive information at the appropriate time. For this reason, there is a need for a system that can efficiently and safely improve the quality of health management, meal plan proposals and implementation, and daily life for the elderly.

[1441] 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.

[1442] In this invention, the server includes means for collecting health information of the subject from a sensor, means for analyzing the collected health information and detecting abnormalities, means for notifying a medical facility when an abnormality is detected, means for generating a meal plan based on the health information, means for proposing the generated meal plan, means for automatically ordering food from a delivery service based on the proposed meal plan, means for generating and distributing content based on the subject's hobbies and interests, and means for monitoring location information and notifying when the subject goes out. This makes it possible to comprehensively and efficiently improve the health management, meal support, and quality of daily life of the elderly.

[1443] A "sensor" is a device used to collect biometric information about a subject, such as blood pressure, heart rate, and body temperature.

[1444] "Analysis" refers to the process of processing and evaluating collected data to determine whether or not there are any abnormalities.

[1445] "Notification" is the act of automatically sending alerts and information to medical facilities and caregivers when an abnormality is detected.

[1446] "Meal Plan" means a customized meal plan based on a Subject's health status and personal preferences, designed to maintain or improve health.

[1447] "Means for automatically placing orders with delivery services" is a function that automatically places orders with affiliated food delivery services based on the generated meal plan.

[1448] "Content" means information and entertainment content provided according to the hobbies and interests of the target user, including music, articles, videos, etc.

[1449] "Location information" refers to geographic location data collected through a subject's device and is used to monitor the subject's movements when out and about.

[1450] "Feedback" refers to opinions and impressions provided by users, and is information collected to improve the quality of service provided by the system.

[1451] This invention is a system that provides health management, dietary support, and daily living support for the elderly, and is linked by a server, terminals, and users. This system collects health information of the target person from sensors and converts it into customized suggestions to realize comprehensive nursing support.

[1452] Server Roles

[1453] 1. Health data collection and analysis

[1454] The server periodically collects health data (blood pressure, heart rate, body temperature, etc.) from sensors worn by the subject. This data is sent to a smartphone via Bluetooth, and then from the smartphone to the server via a REST API. The server analyzes the data using Python and TensorFlow to evaluate the subject's health. If an abnormality is detected, the server automatically notifies medical facilities.

[1455] 2. Meal plan generation and automatic ordering

[1456] Based on the collected health data and the individual's preferences, the server generates an appropriate meal plan, which is then automatically ordered from a partner food delivery service via an API.

[1457] 3. Content generation and distribution

[1458] The server generates customized content based on the user's hobbies and interests, including music playlists, articles, videos, and more, and delivers it to the device at the appropriate time.

[1459] Device Role

[1460] 1. Data Receipt and Notification

[1461] The device receives the health analysis results and meal plans sent from the server and notifies the patient and their caregiver, as well as the contents of the meal and the scheduled delivery time.

[1462] 2. Gathering feedback

[1463] The device collects feedback from the user and sends it to the server, which uses it to improve the service for the next time.

[1464] 3. Location monitoring

[1465] When the target person goes out, the device monitors their location and sends notifications to ensure their safety.

[1466] User Roles

[1467] The user receives information provided through the device and contacts medical facilities as needed, for example, checks alerts from the device and takes prescribed medication promptly, checks suggested meal plans, and receives meals from delivery services.

[1468] Specific examples

[1469] The participants' daily blood pressure and heart rate measurements are sent to a server via their smartphone. The server analyzes the data and notifies medical facilities as needed. Based on their health status, a customized meal plan is generated and automatically ordered from a food delivery service. For example, if the patient has high blood pressure, a low-salt diet is suggested, and grilled salmon is delivered to their home for dinner.

[1470] Example of input prompt for generative AI model

[1471] Health Data:

[1472] Blood pressure: 125 / 80

[1473] Heart rate: 70

[1474] Temperature: 36.5

[1475] Preferences: Low carb

[1476] Suggested meal plan:

[1477] Breakfast: Oatmeal and berries

[1478] Lunch: Grilled chicken salad

[1479] Dinner: Grilled salmon and vegetables

[1480] In this way, the system of the present invention can comprehensively improve the health management, dietary support, and quality of daily life of the elderly.

[1481] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1482] Step 1:

[1483] The server collects health data (blood pressure, heart rate, body temperature, etc.) from the subject's sensors (such as a smartwatch). The sensors send the data to a smartphone via Bluetooth, and the smartphone app sends it to the server through a REST API. The input is the health data from the sensors, and the output is the raw data stored on the server.

[1484] Step 2:

[1485] The server analyzes the collected health data. The analysis is performed using Python and TensorFlow to detect outliers. The input is the collected raw data, and the output is the analysis result (normal / abnormal determination). If an abnormality is detected, the server automatically sends a warning notification to the medical facility.

[1486] Step 3:

[1487] The server generates an appropriate meal plan based on the collected health data and the subject's preferences. The generated meal plan is stored in the server's database. The input is the analyzed health data and the subject's preference information, and the output is a customized meal plan.

[1488] Step 4:

[1489] The server automatically places meal orders with partner delivery services based on the generated meal plan. Orders are placed via the partner delivery service's API. The input is the generated meal plan, and the output is the placed order information.

[1490] Step 5:

[1491] The device receives the analysis results and meal plan details sent from the server and notifies the subject and caregiver. Notifications are made by voice, vibration, or screen display. The input is the notification information sent from the server, and the output is the notification displayed on the subject's device.

[1492] Step 6:

[1493] The user receives notification of the provided meal plan through the terminal, receives the delivered meal, and sends feedback about the meal to the server through the terminal. The input is the user's feedback based on the provided meal, and the output is the feedback data sent to the server.

[1494] Step 7:

[1495] The server generates customized content (music playlists, articles, videos, etc.) based on the user's hobbies and interests and delivers it to the device. The input is data about the user's interests, and the output is the generated content.

[1496] Step 8:

[1497] The device monitors the location information when the subject goes out and sends appropriate notifications to ensure safety. The input is the subject's location data, and the output is a safety notification when the subject goes out.

[1498] In this way, this system can coordinate multiple processing steps to provide health management, dietary support, and daily living support for the elderly.

[1499] 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.

[1500] This invention relates to a system that utilizes AI and an emotion engine to provide health management, dietary support, and daily life support for the elderly. As explained below, this system realizes functions that comprehensively improve the quality of life for the elderly by linking the server, terminals, and users and combining the emotion engine.

[1501] Health management support

[1502] server

[1503] The server periodically collects the latest health data from the subject's sensors, including blood pressure, heart rate, and body temperature.

[1504] The collected data is processed by an analysis algorithm on the server, which compares it with normal ranges to detect abnormalities.

[1505] If an abnormality is detected, the server notifies the medical facility via email or API.

[1506] Terminal

[1507] The analysis results sent from the server are received and notified to the subject and caregiver. For example, a message such as "Your blood pressure is high. Please contact a medical facility." is displayed.

[1508] It also sends out alerts to prevent you from forgetting to take your medicine. For example, it will notify you at 9pm every night that it's time to take your medicine.

[1509] User

[1510] Users receive notifications from their devices, contact medical facilities as needed, and manage health risks by taking prescribed medications at the appropriate times.

[1511] Meal support

[1512] server

[1513] The server generates a customized meal plan based on the subject's health information and dietary preferences, suggesting low-carb options for a diabetic, for example.

[1514] Based on this meal plan, meal orders are placed with affiliated delivery services.

[1515] Terminal

[1516] The system receives meal plan information sent from the server and notifies the user of the next meal and estimated delivery time. For example, it displays, "Dinner will arrive at 7 p.m. The menu is grilled salmon."

[1517] User

[1518] Users can check the meal plan provided and receive meals from the delivery service through the device, and can also provide feedback on the taste and quality of the meal through the device.

[1519] Daily life support

[1520] server

[1521] The server generates customized content based on the subject's hobbies and interests, including music playlists, videos, articles, and more.

[1522] The content is delivered to the device at the appropriate time, for example, a classical music playlist when the person is relaxing in the morning.

[1523] Terminal

[1524] Receives content sent from the server and provides it to the target user, for example, playing a music playlist through a speaker.

[1525] When the target person goes out, the location information is monitored and a timely notification is sent to ensure safety. For example, a notification such as "Your current location is in a park" is sent periodically.

[1526] Utilizing the Emotion Engine

[1527] server

[1528] The emotion engine recognizes emotions from the target person's facial expressions, tone of voice, etc. and adapts behavior accordingly.

[1529] Based on the recognized emotions, more personalized content can be generated and delivered, for example, if the target person is feeling stressed, it can suggest relaxing music or soothing videos.

[1530] The results of health analysis will also be adjusted based on your emotional state. For example, if you are under high stress, your health data will be analyzed more carefully than usual.

[1531] Terminal

[1532] The device receives feedback from the emotion engine and provides real-time support according to the user's emotional state. For example, if the device detects that the user is stressed, it will play soothing content.

[1533] User

[1534] Users can receive services adapted to their emotional state through their devices. By accepting suggestions and notifications based on their emotional state, they can live their daily lives more comfortably.

[1535] This system will enable comprehensive care support for the elderly, including health management, dietary support, improving the quality of daily life, and even addressing their emotional state.

[1536] The processing flow will be explained below.

[1537] Health management support

[1538] Step 1:

[1539] server

[1540] The server periodically collects health data such as blood pressure, heart rate, and body temperature from the subject's sensors, which are typically wearable devices.

[1541] Step 2:

[1542] server

[1543] The collected health data is processed using an analytical algorithm. For example, if blood pressure exceeds 160 / 100 mmHg, it is deemed abnormal.

[1544] Step 3:

[1545] server

[1546] If an abnormality is detected, the server automatically notifies the medical facility, including details of the abnormality and the latest health data.

[1547] Step 4:

[1548] Terminal

[1549] The analysis results sent from the server are received and notified to the subject and caregiver. For example, a message such as "Your blood pressure is high. Please contact a medical facility" is displayed on the screen.

[1550] Step 5:

[1551] Terminal

[1552] To prevent forgetting to take medicine, the device will send out periodic alerts. At 9 p.m. every night, it will notify you by voice or vibration that it's time to take your medicine.

[1553] Meal support

[1554] Step 1:

[1555] server

[1556] It generates a customized meal plan based on the individual's health information and dietary preferences, suggesting low-carb options for someone with diabetes, for example.

[1557] Step 2:

[1558] server

[1559] Based on the meal plan, you will place a meal order with a partner delivery service, which will include meal details and delivery times.

[1560] Step 3:

[1561] Terminal

[1562] It receives meal plan and delivery information sent from the server and notifies the user of the next meal and estimated delivery time. It displays, "Dinner will arrive at 7 p.m. The menu is grilled salmon."

[1563] Daily life support

[1564] Step 1:

[1565] server

[1566] The server generates customized content based on the user's hobbies and interests, such as music playlists or TV show listings.

[1567] Step 2:

[1568] server

[1569] The generated content is delivered to the device at the appropriate time, for example, a classical music playlist is sent in the morning when the target person is relaxing.

[1570] Step 3:

[1571] Terminal

[1572] Receives content sent from the server and provides it to the target user, for example, playing a music playlist through a speaker.

[1573] Step 4:

[1574] Terminal

[1575] When the target person goes out, GPS technology is used to monitor their location and periodically notify them of their current location, with a message such as "Your current location is in a park" displayed on the screen.

[1576] Utilizing the Emotion Engine

[1577] Step 1:

[1578] server

[1579] The emotion engine is used to recognize emotions by analyzing the subject's facial expressions and tone of voice. For example, it analyzes data acquired through a camera and microphone to identify emotions such as stress or joy.

[1580] Step 2:

[1581] server

[1582] Based on the emotions recognized, the system generates more personalized content, for example, suggesting relaxing music or meditation videos if the subject is feeling stressed.

[1583] Step 3:

[1584] Terminal

[1585] The device receives emotion-based content sent from the server and provides it to the subject in real time. For example, if stress is detected, the device will play soothing music.

[1586] User Interaction

[1587] Step 1:

[1588] User

[1589] The user checks the notification from the device and takes action based on the provided information. For example, if the user receives a notification to take medicine, the user takes the medicine promptly.

[1590] Step 2:

[1591] User

[1592] Receive meals based on a suggested meal plan and enjoy content, such as a new music playlist, to enhance your relaxation time.

[1593] Step 3:

[1594] User

[1595] Accept suggestions and notifications based on emotion monitoring to make your daily life more comfortable. For example, if you are feeling stressed, you can watch a meditation video to relax.

[1596] Through these processing steps, a comprehensive care system is realized that includes health management, meal support, daily living assistance, and emotional care for the elderly.

[1597] Example 2

[1598] 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."

[1599] A system that provides integrated health management, dietary support, and daily life support for the elderly is needed. In particular, there is a need for systems that can detect abnormalities in health data and notify medical facilities, generate and deliver meal plans based on health information, provide content based on hobbies and interests in daily life, and ensure safety when out and about. Comprehensive support that takes into account the emotional state of the recipient and promotes relaxation and stress reduction is also needed.

[1600] 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.

[1601] In this invention, the server includes means for collecting health information of the subject from a sensor, means for analyzing the collected health information and detecting abnormalities, means for notifying a medical facility when an abnormality is detected, means for generating a meal plan based on the health information, means for proposing the generated meal plan, means for generating and distributing content based on the subject's hobbies and interests, means for monitoring location information and notifying when the subject goes out, and means for recognizing the subject's emotional state and adapting behavior based thereon. This enables health management, meal support, improvement of quality of daily life for the elderly, and comprehensive care support that responds to emotional states.

[1602] A "sensor" is a device used to collect a subject's health information (blood pressure, heart rate, body temperature, etc.) in real time.

[1603] "Analysis" refers to data processing procedures for detecting abnormal values ​​based on collected health information.

[1604] "Notification" is a means of transmitting information to medical facilities and the like when an abnormality is detected.

[1605] A "meal plan" refers to a meal menu customized for health management based on a subject's health information and dietary preferences.

[1606] "Content" refers to information and entertainment generated based on the subject's hobbies and interests.

[1607] "Location information" is data that indicates the subject's current geographic location.

[1608] "Emotional state" is the result of recognizing the subject's current psychological state from facial expressions, tone of voice, etc.

[1609] "Delivery service" refers to a service that delivers food based on a meal plan to the target person.

[1610] An "alert" is a notification sent to prevent you from forgetting to take your medicine.

[1611] The present invention relates to a system that provides integrated health management, dietary support, and daily life support for the elderly. This system improves the quality of life for the elderly in a comprehensive manner by linking a server, terminals, and users and by utilizing an emotion engine. A specific embodiment of the system is shown below.

[1612] Health management support

[1613] server

[1614] The server collects health data such as the subject's blood pressure, heart rate, and body temperature from sensors in wearable devices and other devices. This data is collected using cloud services such as AWS IoT and Google Cloud IoT Core. The collected data is processed using analysis algorithms written in Python or R. Data analysis evaluates whether the subject's health data is within the normal range and detects abnormal values. For example, if blood pressure is higher than normal, it is determined to be abnormal.

[1615] If an abnormality is detected, the server uses the Twilio API to send a notification to the medical facility. The notification includes basic information about the subject and the type of abnormality. For example, a notification such as "Subject A's blood pressure is 180 / 120. Emergency treatment is required" may be sent.

[1616] Terminal

[1617] The device receives the analysis results sent from the server. This is done using Firebase or REST API. The received information is notified to the subject and caregiver. Specifically, it displays a message saying, "Your blood pressure is high. Please contact a medical facility." Additionally, to prevent forgetting to take medication, an alert is displayed every night at 9 p.m. saying, "It's time to take your medication."

[1618] User

[1619] The user receives notifications from the device and contacts a medical facility as needed. For example, if an abnormality in blood pressure is detected, the user can call a medical facility. Also, based on the alerts on the device, the user can take prescribed medication at the specified time.

[1620] Meal support

[1621] server

[1622] The server generates a customized meal plan using a cloud-based database (e.g., Firebase Firestore) based on the subject's health information and dietary preferences. For example, it creates a low-carb menu for a diabetic patient. Based on this meal plan, the server issues an order to a partner delivery service (e.g., Uber Eats API). The server provides the subject's information (address, meal contents) to the delivery service.

[1623] Terminal

[1624] The device receives the meal plan information sent from the server. Firebase and REST APIs are also used for this. The device then notifies the target user of the next meal plan and the estimated delivery time. For example, it might display, "Dinner will arrive at 7 p.m. The menu is grilled salmon."

[1625] User

[1626] The user checks the provided meal plan on the device and receives the meal from the delivery service. Specifically, they receive a grilled salmon meal at 7 p.m. They also send feedback about the taste and quality of the meal to the server via the device. For example, they can enter, "The grilled salmon was delicious, but I wish it was a little less salty."

[1627] Daily life support

[1628] server

[1629] The server uses the Spotify API or Netflix API to generate content based on the user's hobbies and interests. For example, it creates a playlist of relaxing classical music or an interesting video. The generated content is delivered to the user's device at the time they want. For example, a classical music playlist is sent to relax in the morning.

[1630] Terminal

[1631] The device receives the content sent from the server and provides it to the target person. For example, it plays a generated music playlist from a speaker. The device also monitors the target person's location using its GPS function and sends notifications to ensure their safety. Specifically, the device periodically notifies the target person that "Your current location is in a park."

[1632] User

[1633] Users can check notifications from their devices to ensure their safety. They can listen to classical music during relaxation time, or check location notifications to confirm that they are in a park or other location.

[1634] Utilizing the Emotion Engine

[1635] server

[1636] The server uses an emotion engine such as Microsoft Azure Cognitive Services to recognize emotions from the subject's facial expressions and tone of voice. Specifically, it determines whether the subject is stressed or relaxed. Based on the recognized emotions, it generates more personalized content, for example, suggesting music or videos to relax the subject if they are stressed. It also adjusts the analysis results of health information based on the subject's emotional state. For example, when the subject is in a high stress state, it analyzes health data more carefully.

[1637] Terminal

[1638] The device receives feedback from the emotion engine and provides support that adapts to the user's emotional state in real time. For example, if the device detects stress, it will play soothing music or videos.

[1639] User

[1640] Users can receive services adapted to their emotional state through their devices. For example, listening to soothing music when feeling stressed can help users lead a more comfortable daily life.

[1641] This system can provide comprehensive care support for the elderly, including health management, dietary support, improving the quality of daily life, and even addressing their emotional state.

[1642] Prompt Sentence Examples

[1643] You want to develop a system to provide health management, meal support, and daily life support for the elderly. Collect and analyze health data, customize meal plans, order them from delivery services, and deliver customized content at the right time. Consider how to incorporate an emotion engine into this system to provide more personalized support.

[1644] Based on this example and prompt, it is believed that it will be easier to understand the system's functionality and how it is implemented.

[1645] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1646] Health management support

[1647] server

[1648] Step 1:

[1649] The server collects health data from the sensors.

[1650] Input: Data such as blood pressure, heart rate, and temperature obtained from wearable devices.

[1651] Output: Store the collected health data in a cloud database.

[1652] Specific operation: Uses AWS IoT or Google Cloud IoT Core to acquire data in real time and store it in a database.

[1653] Step 2:

[1654] The server analyzes the collected health data.

[1655] Input: Health data stored in a cloud database.

[1656] Output: Analyzed data results (e.g. outlier detection).

[1657] What it does: It uses analytics algorithms written in Python or R to compare data with health standards and detect abnormalities. For example, a blood pressure of 180 / 120 is considered abnormal.

[1658] Step 3:

[1659] The server notifies the medical facility if an abnormality is detected.

[1660] Input: Parsed data results.

[1661] Output: Notification sent to healthcare facility.

[1662] Specific behavior: Uses the Twilio API to send notifications to medical facilities via email and SMS. Example: "Subject A's blood pressure is 180 / 120. Emergency treatment is required."

[1663] Terminal

[1664] Step 1:

[1665] The terminal receives the analysis result from the server.

[1666] Input: Analysis results sent from the server.

[1667] Output: Analysis results displayed on the terminal.

[1668] Specific operation: Retrieves data via Firebase or REST API and displays it on the device screen.

[1669] Step 2:

[1670] The terminal notifies the analysis result.

[1671] Input: Received analysis results.

[1672] Output: Notification to subject and caregiver.

[1673] Specific behavior: Display "Your blood pressure is high. Please contact a medical facility." Also, display an alert every night at 9 PM saying "It's time to take your medication."

[1674] User

[1675] Step 1:

[1676] The user receives the notification and responds.

[1677] Input: Notifications from your device.

[1678] Output: Contact medical facility and take medication.

[1679] Specific actions: See the notification on the device, call a medical facility, see the notification at 9 PM, and take the prescribed medication.

[1680] Meal support

[1681] server

[1682] Step 1:

[1683] The server generates a meal plan based on the health information and dietary preferences.

[1684] Input: A database containing health information and dietary preferences.

[1685] Output: A customized meal plan.

[1686] What it does: It uses Firebase Firestore to retrieve information from a database and then uses an algorithm to generate a meal plan, for example, a low-carb menu for a diabetic.

[1687] Step 2:

[1688] The server issues orders to a delivery service based on the meal plan.

[1689] Input: The generated meal plan.

[1690] Output: Order information sent to the delivery service.

[1691] Specific operation: Use the Uber Eats API to provide the meal details and the target address to the delivery service. For example, specify "grilled salmon."

[1692] Terminal

[1693] Step 1:

[1694] The terminal receives the meal plan information from the server.

[1695] Input: Meal plan information sent from the server.

[1696] Output: Meal plan information displayed on the device.

[1697] Specific behavior: Receives data via Firebase or REST API and displays the next meal contents and estimated delivery time. Example: Notifies "Dinner will arrive at 7pm. The menu is grilled salmon."

[1698] User

[1699] Step 1:

[1700] The user confirms and receives the meal plan.

[1701] Input: Meal plan information provided on device.

[1702] Output: Meals from a delivery service.

[1703] Specific action: Pick up a grilled salmon meal from a delivery service at 7pm.

[1704] Step 2:

[1705] The user provides feedback.

[1706] Input: Feedback on the taste and quality of the food provided.

[1707] Output: Feedback information sent to the server.

[1708] Specific action: Enter "The grilled salmon was delicious, but I wish it was a little less salty" into the device.

[1709] Daily life support

[1710] server

[1711] Step 1:

[1712] The server generates content based on hobbies and interests.

[1713] Input: A database storing the subject's hobbies and interests.

[1714] Output: The generated content.

[1715] What it does: Uses Spotify API and Netflix API to generate music playlists and videos tailored to the target audience. For example, create a classical music playlist.

[1716] Step 2:

[1717] The server distributes the generated content.

[1718] Input: Generated content.

[1719] Output: Content information delivered to the device.

[1720] What it does: Send a morning relaxation classical music playlist via Firebase Cloud Messaging or the REST API.

[1721] Terminal

[1722] Step 1:

[1723] The terminal receives the content transmitted from the server.

[1724] Input: Content information sent from the server.

[1725] Output: The content that is displayed or played on a device.

[1726] Specific operation: Play the received music playlist from the speaker.

[1727] Step 2:

[1728] The terminal monitors and notifies the location information.

[1729] Input: Location information obtained by GPS.

[1730] Output: Location-based notifications.

[1731] Specific operation: Notify "Your current location is a park" at regular intervals.

[1732] User

[1733] Step 1:

[1734] The user uses the distributed content.

[1735] Input: Content displayed or played on the device.

[1736] Output: Satisfaction and relaxation from the content used.

[1737] Specific action: Listen to classical music during relaxation time.

[1738] Step 2:

[1739] The user checks the location information notification.

[1740] Input: Location notification from device.

[1741] Output: Your current safety status.

[1742] Specific operation: Check the notification on the device to confirm that you are in the park correctly.

[1743] Utilizing the Emotion Engine

[1744] server

[1745] Step 1:

[1746] The server analyzes the emotion data using an emotion engine.

[1747] Input: Data based on the subject's facial expressions and tone of voice.

[1748] Output: Parsed emotional state.

[1749] How it works: Using Microsoft Azure Cognitive Services, it analyzes whether a subject is stressed or relaxed.

[1750] Step 2:

[1751] The server generates personalized content based on the emotional state.

[1752] Input: Parsed emotional state.

[1753] Output: Personalized content.

[1754] Specific operation: When you are feeling stressed, generate and transmit music or images to help you relax.

[1755] Step 3:

[1756] The server analyzes the health data to reflect the emotional state.

[1757] Input: Parsed emotional state and collected health data.

[1758] Output: Analysis results of health data taking into account emotional state.

[1759] Specific behavior: When the emotional state is stressful, analyze health data more carefully.

[1760] Terminal

[1761] Step 1:

[1762] The device receives feedback from the emotion engine.

[1763] Input: Parsed emotional state.

[1764] Output: Service depending on emotional state.

[1765] Specific operation: Play music and video in real time according to the emotional state.

[1766] User

[1767] Step 1:

[1768] The user receives a service adapted to his emotional state.

[1769] Input: Emotion-based service provided by the device.

[1770] Output: Relaxation and satisfaction depending on emotional state.

[1771] Specific action: Listen to soothing music when you feel stressed and make your daily life more comfortable.

[1772] (Application example 2)

[1773] 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."

[1774] In the daily lives of elderly people, there is a need to efficiently manage their health, provide dietary support, and recognize their emotions to improve their quality of life. However, these functions are currently provided individually, and there is no integrated support system, which places a heavy burden on elderly people and their caregivers. Furthermore, the lack of support in response to emotional changes makes it difficult to reduce stress and anxiety.

[1775] 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.

[1776] In this invention, the server includes means for collecting health information of the subject from a sensor, means for analyzing the collected health information and detecting abnormalities, means for notifying a medical facility when an abnormality is detected, means for generating a meal plan based on the health information, means for proposing the generated meal plan, means for generating and distributing content based on the subject's hobbies and interests, means for monitoring location information and notifying when the subject goes out, and means for recognizing emotions and adapting behavior based on emotions. This enables health management, meal support, and emotion recognition to be performed in an integrated manner, thereby comprehensively improving the quality of daily life of elderly people.

[1777] "Health information" is data that indicates the subject's physical condition, and specifically includes blood pressure, heart rate, body temperature, and the like.

[1778] A "sensor" is a device for collecting health information about a subject, and includes wearable devices and vital sign monitors.

[1779] "Analysis" refers to algorithmic methods used to process data and detect anomalies based on collected health information.

[1780] "Abnormal" refers to a state in which the subject's health information deviates from the normal range, indicating a condition requiring early intervention.

[1781] "Medical facility" refers to a place that provides medical services, such as a hospital or clinic.

[1782] A "meal plan" refers to a meal menu customized based on the subject's health information, and includes content that takes into consideration nutritional balance and health status.

[1783] "Recommendation" refers to the act of informing the subject or their caregiver of the generated meal plan.

[1784] "Hobbies and interests" refers to activities that the subject enjoys on a daily basis and areas of interest.

[1785] "Content" includes information materials such as videos, music, articles, etc. that are provided based on the subject's hobbies and interests.

[1786] "Distribution" refers to the act of delivering the generated content to the target audience, which may be via the Internet or a local network.

[1787] "Location information" is data that indicates a subject's current physical location and is obtained using technologies such as GPS.

[1788] "Notification" refers to the act of informing a subject or their caregiver of necessary information, and may take the form of an alert or message.

[1789] "Emotion recognition" refers to the technology of determining a subject's emotions from their facial expressions, tone of voice, etc.

[1790] "Behavioral adaptation" refers to the act of responding to provide services and content that meet the needs of the target person based on emotion recognition.

[1791] This invention relates to a comprehensive system that provides health management, dietary support, and daily life support for the elderly. This system aims to improve the quality of life of the target individuals by linking the server, terminals, and users, and by combining an emotion engine.

[1792] Health management support

[1793] server

[1794] The server periodically collects health information from the subject's sensors. This health information includes blood pressure, heart rate, and body temperature. The collected data is processed by an analysis algorithm on the server and compared with the normal range to detect abnormalities. If an abnormality is detected, the server notifies medical facilities. Notification methods include email and API.

[1795] Terminal

[1796] The device receives the analysis results sent from the server and notifies the subject and caregiver. For example, it displays a message saying, "Your blood pressure is high. Please contact a medical facility." To prevent patients from forgetting to take their medication, the device also sends an alert every night at 9 p.m. saying, "It's time to take your medication."

[1797] User

[1798] Users receive notifications from their devices, contact medical facilities as needed, and manage health risks by taking prescribed medications at the appropriate times.

[1799] Meal support

[1800] server

[1801] The server generates a customized meal plan based on the user's health information and dietary preferences. For example, it suggests low-carb options for diabetics. Based on this meal plan, it issues a meal order to a partner delivery service.

[1802] Terminal

[1803] The device receives the meal plan information sent from the server and notifies the user of the next meal and the estimated delivery time. For example, it displays, "Dinner will arrive at 7 p.m. The menu is grilled salmon."

[1804] User

[1805] Users can check the meal plan provided and receive meals from the delivery service through the device, and can also provide feedback on the taste and quality of the meal through the device.

[1806] Daily life support

[1807] server

[1808] The server generates customized content based on the user's hobbies and interests, including music playlists, videos, and articles. The content is delivered to the device at the appropriate time. For example, a classical music playlist could be sent when the user is relaxing in the morning.

[1809] Terminal

[1810] The device receives the content sent from the server and provides it to the target person. For example, a music playlist can be played from a speaker. When the target person goes out, the device monitors the target person's location and sends timely notifications to ensure their safety. For example, the device periodically sends a notification saying, "Your current location is in a park."

[1811] Utilizing the Emotion Engine

[1812] server

[1813] The server uses an emotion engine to recognize emotions from the subject's facial expressions, tone of voice, and other factors. Based on the recognized emotions, the server generates and delivers more personalized content. For example, if the subject is feeling stressed, it will suggest relaxing music or soothing videos. The results of health information analysis are also adjusted according to the subject's emotional state. For example, when the subject is under high stress, the server will analyze health data more carefully than usual.

[1814] Terminal

[1815] The device receives feedback from the emotion engine and provides real-time support according to the subject's emotional state. For example, if the device detects stress in the subject, it will play soothing content.

[1816] User

[1817] Users can receive services adapted to their emotional state through their devices. By accepting suggestions and notifications based on their emotional state, they can live their daily lives more comfortably.

[1818] Hardware and software used

[1819] The system utilizes hardware such as smartphones, head-mounted displays, and smart glasses, as well as software such as Python programs, RESTful APIs, and emotion recognition algorithms.

[1820] Specific examples

[1821] For example, if a user sends their health data to a server, the server can detect that they have high blood pressure and suggest a low-salt diet plan. If the app's emotion recognition function determines that the user is feeling stressed, it can suggest relaxing music and videos.

[1822] Prompt Sentence Examples

[1823] "Enter your latest health data: blood pressure, heart rate, temperature"

[1824] "Please tell us your current emotional state: happy, sad, stressed, neutral"

[1825] "What is your suggested meal plan based on my current health condition?"

[1826] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1827] Step 1: Collecting health data

[1828] Input: Sensors collect the subject's health information (blood pressure, heart rate, temperature).

[1829] Server behavior:

[1830] The server receives health data sent from sensors, specifically from wearable devices and vital sign monitors, and stores the data.

[1831] Output: The collected health data is stored on the server.

[1832] Step 2: Analyzing health data

[1833] Input: Collected health data

[1834] Server behavior:

[1835] The subject's health data is analyzed using an analysis algorithm (for example, using a Python library) on the server. The analysis detects abnormalities by comparing the health information with the normal range.

[1836] Output: The analysis results (normal or abnormal) are generated and saved.

[1837] Step 3: Notification of abnormalities

[1838] Input: If the analysis result is abnormal

[1839] Server behavior:

[1840] If an abnormality is detected, the server notifies the medical facility by email or using a RESTful API.

[1841] Output: A notification to the healthcare facility is sent.

[1842] Step 4: Generate a meal plan

[1843] Input: Health data and analysis results

[1844] Server behavior:

[1845] The server generates a customized meal plan based on the subject's health information and dietary preferences. The meal plan is created using a nutrition calculation algorithm.

[1846] Output: The generated meal plan is saved.

[1847] Step 5: Meal plan suggestions

[1848] Input: Generated meal plan

[1849] Server behavior:

[1850] The server transmits the generated meal plan to the terminal.

[1851] Device operation: The device notifies the recipient and their caregiver of the received meal plan. For example, it displays, "Dinner will arrive at 7 p.m. The menu is grilled salmon."

[1852] Output: The subject and / or caregiver will be notified of the meal plan information.

[1853] Step 6: Order from a delivery service

[1854] Enter: Check Meal Plan

[1855] Terminal behavior:

[1856] After the user confirms the meal plan, the device issues an order to the partner delivery service, specifically by sending the order information using the delivery service's API.

[1857] Output: A food order is placed with the delivery service.

[1858] Step 7: Recognize emotions

[1859] Input: Subject's facial expressions and tone of voice

[1860] Terminal behavior:

[1861] The device's camera and microphone are used to recognize the subject's emotions, and an emotion engine (AI model) is used to analyze the collected data.

[1862] Output: The recognized emotion is saved on the device.

[1863] Step 8: Adapting behavior based on emotions

[1864] Input: Recognized emotion

[1865] Server behavior:

[1866] Based on the emotions detected, the server generates and sends personalized content to the device, such as relaxing music or soothing videos.

[1867] Terminal behavior:

[1868] The device then provides the received content to the subject, for example, playing relaxing music if the subject is feeling stressed.

[1869] Output: Personalized content is provided to the subject, improving their emotional state.

[1870] 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.

[1871] 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.

[1872] 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.

[1873] [Fourth embodiment]

[1874] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1875] 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.

[1876] 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).

[1877] 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.

[1878] 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.

[1879] 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).

[1880] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1881] 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.

[1882] 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.

[1883] 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.

[1884] 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.

[1885] 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.

[1886] 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."

[1887] The present invention relates to a system that utilizes AI to provide health management, dietary support, and daily life support for the elderly. This system realizes comprehensive nursing support through collaboration between a server, a terminal, and a user. Specific embodiments of the present invention are described below.

[1888] Health management support

[1889] server

[1890] The server periodically collects the latest health data (blood pressure, heart rate, body temperature, etc.) from the subject's sensors. The sensors are wearable devices worn by the subject.

[1891] The collected data is processed by an analytical algorithm on the server. For example, if blood pressure exceeds the normal range, it is determined to be abnormal.

[1892] If an abnormality is detected, the server will promptly notify the medical facility via email or automated communication via API.

[1893] Terminal

[1894] The device receives the health status analysis results sent from the server and notifies the subject and caregiver. For example, the device screen displays a message saying, "Your blood pressure is high. Please contact a medical facility."

[1895] It also has a function to send out an alert so that you don't forget to take your medicine, notifying you with sound and vibration when it's time to take your medicine.

[1896] User

[1897] The user receives notifications from the device and contacts the medical facility as needed, for example, by checking the alert from the device and taking the prescribed medication promptly.

[1898] Meal support

[1899] server

[1900] The server generates a customized meal plan based on the individual's health information and preferences, suggesting low-carb options for someone with diabetes, for example.

[1901] Orders are placed with partner delivery services based on the meal plan.

[1902] Terminal

[1903] The device receives the meal plan information sent from the server and notifies the user of the next meal and the scheduled delivery time. For example, it displays, "Dinner will be delivered at 7 p.m. The menu is grilled salmon."

[1904] User

[1905] Users can view the proposed meal plan and receive meals from the delivery service through the device, and can also provide feedback on the meals.

[1906] Daily life support

[1907] server

[1908] The server generates customized content based on the subject's hobbies and interests, including music playlists, articles, videos, and more.

[1909] The content is delivered to the terminal at the appropriate time.

[1910] Terminal

[1911] The content sent from the server is received and provided to the subject, for example, by playing a music playlist to help the subject relax.

[1912] In addition, when the target person goes out, their location information is monitored and notifications are sent to ensure their safety.

[1913] User

[1914] Users can select and enjoy their favorite content through their device, and when they go out, they can receive location information from the device, allowing them to move around with peace of mind.

[1915] This system will improve the health management, dietary support, and quality of daily life of the recipient, while also reducing the burden on caregivers and realizing more efficient and safe care.

[1916] The processing flow will be explained below.

[1917] Health management support

[1918] Step 1:

[1919] server

[1920] Health data such as blood pressure, heart rate, and body temperature are collected from sensors worn by the subjects, and the data is periodically sent to a server via an API.

[1921] Step 2:

[1922] server

[1923] The collected health data is analyzed and compared with the standard values ​​within the healthy range to check for abnormalities. For example, blood pressure of 160 / 100 mmHg or higher is determined to be high blood pressure.

[1924] Step 3:

[1925] server

[1926] If an abnormality is detected, the system automatically notifies the medical facility via email or API, and includes details of the abnormality and the subject's latest health data.

[1927] Step 4:

[1928] Terminal

[1929] Receives analysis results sent from the server. For example, if blood pressure is high, displays a message saying "Your blood pressure is high. Please contact a medical facility."

[1930] Step 5:

[1931] Terminal

[1932] It sends out alerts to prevent you from forgetting to take your medicine. For example, it notifies you every night at 9pm that it's time to take your medicine.

[1933] Meal support

[1934] Step 1:

[1935] server

[1936] Generate a meal plan based on the subject's health information (e.g., diabetes) and preferences, for example, selecting low-carb menus.

[1937] Step 2:

[1938] server

[1939] It proposes meal plans and places meal orders with partner delivery services, including menu details and delivery times.

[1940] Step 3:

[1941] Terminal

[1942] It receives information from the server and notifies the user of the next meal and the estimated delivery time. It displays, "Dinner will arrive at 7 p.m. The menu is grilled salmon."

[1943] Daily life support

[1944] Step 1:

[1945] server

[1946] It takes the user's hobbies and interests from a database and generates customized content, for example, creating a playlist of the latest classical music for a user who likes classical music.

[1947] Step 2:

[1948] server

[1949] The generated content is delivered to the device at the appropriate time, for example, sending a music playlist to relax in the morning.

[1950] Step 3:

[1951] Terminal

[1952] Receive and play content sent from a server, for example, playing a music playlist through a speaker.

[1953] Step 4:

[1954] Terminal

[1955] When the subject goes out, the location information is monitored by GPS. The location information is periodically checked and notified to the subject and caregiver.

[1956] User Interaction

[1957] Step 1:

[1958] User

[1959] Receive notifications from your device to check your health status and diet, and take necessary actions, such as taking medicine based on the notification.

[1960] Step 2:

[1961] User

[1962] Enjoy suggested meal plans and content, and provide feedback through your device.

[1963] This will complete a process in which the entire system works together to provide multifaceted support for the lives of the elderly.

[1964] Example 1

[1965] 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."

[1966] In today's aging society, there is an increasing need for systems that provide comprehensive health management, dietary support, and daily life support for the elderly. However, conventional systems often provide these support services separately, making it difficult to achieve integrated and efficient care. Furthermore, it is difficult to quickly and accurately respond to various issues, such as detecting abnormal health conditions, notifying users when medication should be taken, and meal planning. Another issue is the lack of personalized content tailored to the preferences and interests of each user.

[1967] 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.

[1968] In this invention, the server includes means for collecting the subject's biometric information from a measurement device, means for analyzing the collected biometric information and detecting abnormalities, means for notifying a medical institution when an abnormality is detected, means for generating a meal plan based on the biometric information, means for proposing the generated meal plan, means for generating and distributing content based on the subject's preferences and interests, means for monitoring location information and notifying the subject when the subject leaves the home, means for displaying the analysis results and notifying the subject and caregiver, and means for issuing alerts to encourage medication. This enables integrated health management, dietary support, and daily life support for the subject, enabling prompt and accurate responses. It also enables the provision of content tailored to the subject's individual needs.

[1969] "Target population" refers to users who receive support from this system, and primarily includes elderly people and those who require nursing care.

[1970] "Biometric information" refers to health data such as blood pressure, heart rate, and body temperature, which are measured and collected using measuring devices.

[1971] "Measuring devices" refer to wearable devices and sensors, which are equipment used to regularly record and collect biometric information from subjects.

[1972] "Server" refers to a central system for analyzing collected biometric information and detecting and notifying abnormalities, and includes cloud servers and data centers.

[1973] "Medical Institution" means a hospital, clinic, or medical facility to which you may be notified about any abnormal health condition.

[1974] A "meal plan" refers to a customized meal menu based on the subject's health condition and preferences, taking nutritional balance into consideration.

[1975] "Content" refers to information and entertainment generated based on a target's preferences and interests, including music playlists, articles, videos, etc.

[1976] "Location information" refers to the subject's current location and is collected via GPS data.

[1977] "Analysis results" refers to the results of data analysis conducted based on collected biometric information, including evaluation of health status and detection of abnormalities.

[1978] An "alert" refers to a notification sent from a device to alert users or encourage them to take action when they take medication or when an abnormality is detected.

[1979] "Notification" refers to a means of communicating abnormalities or important information to the subject, caregiver, or medical institution, and includes email, message, voice, etc.

[1980] This invention is a system that utilizes AI to provide comprehensive health management, dietary support, and daily life support for the elderly. This system operates in cooperation with a server, terminals, and users, and functions as follows:

[1981] Health management support

[1982] server

[1983] First, the server periodically collects biometric information such as blood pressure, heart rate, and body temperature from a wearable device (e.g., commonly known as a "measuring device") worn by the subject. The data is transferred via Bluetooth or Wi-Fi and stored on the server. The collected data is then processed and analyzed using machine learning algorithms and analysis algorithms written in Python or other languages. If an abnormal value is detected through this analysis, it is determined to be abnormal based on a set threshold. If an abnormality is detected, the server automatically sends a notification to the medical institution via the SMTP protocol or REST API.

[1984] As a specific example, the server collects heart rate data from the wearable device every five minutes, and if it detects an abnormal value, it sends an email to the medical institution stating, "Warning: The subject's heart rate has exceeded the normal range."

[1985] Terminal

[1986] The device (e.g., smartphone or tablet) receives the analysis results sent from the server and notifies the user. Using a dedicated health management app, a message will be displayed on the screen saying, "Your blood pressure is high. Please contact a medical institution." In addition, to prevent users from forgetting to take their medication, an alert will be sent via voice assistant or vibration when it is time to take the medication.

[1987] For example, the device will notify you with a voice notification at 8:00 a.m. saying, "It's time to take your medicine."

[1988] User

[1989] The user checks the notification from the device and contacts a medical institution if necessary. The user also receives an alert and takes action to ensure that they do not forget to take the prescribed medication.

[1990] Meal support

[1991] server

[1992] The server generates a customized meal plan based on the user's health status and preferences, using machine learning algorithms and nutritional databases to suggest appropriate menu items, and then issues an order to a partner delivery service.

[1993] For example, a server might suggest low-carb options for diabetics and send an order saying, "Please deliver low-carb grilled salmon for dinner tonight at 6 p.m."

[1994] Terminal

[1995] The device receives the meal plan and estimated delivery time sent from the server and notifies the user, displaying on the screen, "The next meal is scheduled to arrive at 7 p.m. and the menu is grilled salmon."

[1996] User

[1997] Users can check their meal plans and receive meals from the delivery service through their devices, and can also send feedback about their meals to the server through their devices.

[1998] Daily life support

[1999] server

[2000] The server generates customized content (e.g., music playlists, articles, videos, etc.) based on the user's preferences and interests, and delivers the generated content to the device at the appropriate time.

[2001] As a specific example, the server generates a music playlist for relaxation and transmits it to the terminal as a "playlist for afternoon relaxation time."

[2002] Terminal

[2003] The device receives the content sent from the server and provides it to the target user. It plays the playlist through a music player app or similar, allowing the target user to enjoy it. It also uses GPS to monitor the target user's location when they go out and sends notifications to ensure their safety.

[2004] User

[2005] Users can enjoy the content provided through the terminal, and when they go out, they can move around with peace of mind by receiving location information notifications from the terminal.

[2006] Examples of prompt statements

[2007] Health data collection settings: "Collect and analyze my heart rate data today."

[2008] Meal plan suggestions: "Please suggest low-carb meals for diabetics."

[2009] Content generation for daily living support: "Generate a relaxing music playlist for seniors."

[2010] This system will not only comprehensively improve the health management, dietary support, and quality of daily life of the elderly, but will also reduce the burden on their caregivers and provide more efficient and safer support.

[2011] The flow of the identification process in the first embodiment will be described with reference to FIG.

[2012] Health management support

[2013] server

[2014] Step 1:

[2015] The server collects biometric information from the measurement device. The input is data from the wearable device (e.g., heart rate, blood pressure, body temperature). The data is sent to the server via Bluetooth or Wi-Fi. The output is biometric information stored in the server's database. Specifically, the server polls the data from the device every five minutes.

[2016] Step 2:

[2017] The server analyzes the collected biometric information. The input is the biometric information collected in the previous step. A machine learning algorithm written in Python is used for the analysis, and data that exceeds the normal range is judged to be abnormal. The output is the analysis results and the detection of abnormalities. Specifically, the data is input into the algorithm and compared with a threshold for detecting abnormal values.

[2018] Step 3:

[2019] The server notifies the medical institution if an abnormality is detected. The input is the analysis result from the previous step. The notification is sent via email or API request. The output is a warning message sent to the medical institution. Specifically, the server sends a warning email using the SMTP protocol.

[2020] Terminal

[2021] Step 4:

[2022] The terminal receives the analysis results sent from the server and notifies the user. The input is the analysis results from the server. A warning message is displayed on the screen through a dedicated application. The output is the warning message displayed on the screen. For example, it might say, "Your blood pressure is high, please contact a medical institution."

[2023] Step 5:

[2024] The device sends an alert to remind the user to take their medicine. The input is the scheduled time to take the medicine. The notification is sent via a voice assistant or vibration. The output is an alert notification to the user. Specifically, at 8:00 AM, the device notifies the user by voice, saying, "It's time to take your medicine."

[2025] User

[2026] Step 6:

[2027] The user checks the notification from the device and takes the necessary action. The input is a warning message or alert from the device. The output is the action of actually contacting a medical institution or taking medication. The specific action is the user checking the message and taking the prescribed medication.

[2028] Meal support

[2029] server

[2030] Step 1:

[2031] The server generates a meal plan based on the subject's health status and preferences. The input is pre-stored health and preference information. The meal plan is created using machine learning algorithms and a nutrition database. The output is a customized meal plan. Specifically, it generates a low-carb menu for diabetics.

[2032] Step 2:

[2033] The server issues an order to a partner delivery service based on the meal plan. The input is the generated meal plan. The order is sent using API communication. The output is the order sent to the delivery service. A specific operation is to send an order such as "Please deliver grilled salmon for tonight's dinner at 6 p.m."

[2034] Terminal

[2035] Step 3:

[2036] The terminal receives the meal plan and estimated delivery time sent from the server and notifies the user. The input is the meal plan information from the server. The next meal contents and estimated delivery time are displayed on the screen. The output is a notification to the user. For example, it might display "The next meal is scheduled to arrive at 7pm and the menu is grilled salmon."

[2037] User

[2038] Step 4:

[2039] The user checks the meal plan through the terminal and receives the meal from the delivery service. The input is a notification from the terminal. The user checks the actual menu and receives the meal. The output is the action of receiving the meal. The specific actions are the user checking the notification and receiving the meal from the delivery person.

[2040] Daily life support

[2041] server

[2042] Step 1:

[2043] The server generates customized content based on the subject's preferences and interests. The input is the subject's preference information. The generative AI model is used to generate the personalized content. The output is the generated content. A specific operation is to generate a relaxation music playlist.

[2044] Step 2:

[2045] The server delivers content to the terminal at the appropriate time. The input is the generated content. It is sent to the terminal according to the content delivery schedule. The output is the delivered content. A specific operation is to send a "playlist for afternoon relaxation time" to the terminal.

[2046] Terminal

[2047] Step 3:

[2048] The device receives content sent from the server and provides it to the target person. The input is content data from the server. The content is played using a music player app or similar. The output is the content provided to the target person. As a specific example, a music playlist can be played to support relaxation time.

[2049] Step 4:

[2050] The device monitors the location information when the target person goes out and sends a notification to ensure safety. The input is GPS data. The device tracks the target person's location in real time and sends a notification if the target person goes out of range. The output is a notification to ensure safety. Specifically, if the target person goes far away from home, the device sends a notification saying "Please check your current location."

[2051] User

[2052] Step 5:

[2053] Users enjoy content provided through their devices and receive location notifications when they are out and about. The inputs are notifications and content from the device. The outputs are the behavior of enjoying the content and ensuring safety based on location information. Specific actions include the user playing a music playlist, checking notifications, and moving safely.

[2054] Through the above processing steps, this system can comprehensively improve the health management, dietary support, and quality of daily life of elderly people, and reduce the burden on caregivers.

[2055] (Application example 1)

[2056] 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."

[2057] To provide health management, dietary support, and daily living support for the elderly in a unified manner, it is necessary to use multiple different systems and devices, which poses the problem of complex data integration and operation between each system. There is also the risk that the elderly themselves and their caregivers may forget certain procedures or not receive information at the appropriate time. For this reason, there is a need for a system that can efficiently and safely improve the quality of health management, meal plan proposals and implementation, and daily life for the elderly.

[2058] 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.

[2059] In this invention, the server includes means for collecting health information of the subject from a sensor, means for analyzing the collected health information and detecting abnormalities, means for notifying a medical facility when an abnormality is detected, means for generating a meal plan based on the health information, means for proposing the generated meal plan, means for automatically ordering food from a delivery service based on the proposed meal plan, means for generating and distributing content based on the subject's hobbies and interests, and means for monitoring location information and notifying when the subject goes out. This makes it possible to comprehensively and efficiently improve the health management, meal support, and quality of daily life of the elderly.

[2060] A "sensor" is a device used to collect biometric information about a subject, such as blood pressure, heart rate, and body temperature.

[2061] "Analysis" refers to the process of processing and evaluating collected data to determine whether or not there are any abnormalities.

[2062] "Notification" is the act of automatically sending alerts and information to medical facilities and caregivers when an abnormality is detected.

[2063] "Meal Plan" means a customized meal plan based on a Subject's health status and personal preferences, designed to maintain or improve health.

[2064] "Means for automatically placing orders with delivery services" is a function that automatically places orders with affiliated food delivery services based on the generated meal plan.

[2065] "Content" means information and entertainment content provided according to the hobbies and interests of the target user, including music, articles, videos, etc.

[2066] "Location information" refers to geographic location data collected through a subject's device and is used to monitor the subject's movements when out and about.

[2067] "Feedback" refers to opinions and impressions provided by users, and is information collected to improve the quality of service provided by the system.

[2068] This invention is a system that provides health management, dietary support, and daily living support for the elderly, and is linked by a server, terminals, and users. This system collects health information of the target person from sensors and converts it into customized suggestions to realize comprehensive nursing support.

[2069] Server Roles

[2070] 1. Health data collection and analysis

[2071] The server periodically collects health data (blood pressure, heart rate, body temperature, etc.) from sensors worn by the subject. This data is sent to a smartphone via Bluetooth, and then from the smartphone to the server via a REST API. The server analyzes the data using Python and TensorFlow to evaluate the subject's health. If an abnormality is detected, the server automatically notifies medical facilities.

[2072] 2. Meal plan generation and automatic ordering

[2073] Based on the collected health data and the individual's preferences, the server generates an appropriate meal plan, which is then automatically ordered from a partner food delivery service via an API.

[2074] 3. Content generation and distribution

[2075] The server generates customized content based on the user's hobbies and interests, including music playlists, articles, videos, and more, and delivers it to the device at the appropriate time.

[2076] Device Role

[2077] 1. Data Receipt and Notification

[2078] The device receives the health analysis results and meal plans sent from the server and notifies the patient and their caregiver, as well as the contents of the meal and the scheduled delivery time.

[2079] 2. Gathering feedback

[2080] The device collects feedback from the user and sends it to the server, which uses it to improve the service for the next time.

[2081] 3. Location monitoring

[2082] When the target person goes out, the device monitors their location and sends notifications to ensure their safety.

[2083] User Roles

[2084] The user receives information provided through the device and contacts medical facilities as needed, for example, checks alerts from the device and takes prescribed medication promptly, checks suggested meal plans, and receives meals from delivery services.

[2085] Specific examples

[2086] The participants' daily blood pressure and heart rate measurements are sent to a server via their smartphone. The server analyzes the data and notifies medical facilities as needed. Based on their health status, a customized meal plan is generated and automatically ordered from a food delivery service. For example, if the patient has high blood pressure, a low-salt diet is suggested, and grilled salmon is delivered to their home for dinner.

[2087] Example of input prompt for generative AI model

[2088] Health Data:

[2089] Blood pressure: 125 / 80

[2090] Heart rate: 70

[2091] Temperature: 36.5

[2092] Preferences: Low carb

[2093] Suggested meal plan:

[2094] Breakfast: Oatmeal and berries

[2095] Lunch: Grilled chicken salad

[2096] Dinner: Grilled salmon and vegetables

[2097] In this way, the system of the present invention can comprehensively improve the health management, dietary support, and quality of daily life of the elderly.

[2098] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2099] Step 1:

[2100] The server collects health data (blood pressure, heart rate, body temperature, etc.) from the subject's sensors (such as a smartwatch). The sensors send the data to a smartphone via Bluetooth, and the smartphone app sends it to the server through a REST API. The input is the health data from the sensors, and the output is the raw data stored on the server.

[2101] Step 2:

[2102] The server analyzes the collected health data. The analysis is performed using Python and TensorFlow to detect outliers. The input is the collected raw data, and the output is the analysis result (normal / abnormal determination). If an abnormality is detected, the server automatically sends a warning notification to the medical facility.

[2103] Step 3:

[2104] The server generates an appropriate meal plan based on the collected health data and the subject's preferences. The generated meal plan is stored in the server's database. The input is the analyzed health data and the subject's preference information, and the output is a customized meal plan.

[2105] Step 4:

[2106] The server automatically places meal orders with partner delivery services based on the generated meal plan. Orders are placed via the partner delivery service's API. The input is the generated meal plan, and the output is the placed order information.

[2107] Step 5:

[2108] The device receives the analysis results and meal plan details sent from the server and notifies the subject and caregiver. Notifications are made by voice, vibration, or screen display. The input is the notification information sent from the server, and the output is the notification displayed on the subject's device.

[2109] Step 6:

[2110] The user receives notification of the provided meal plan through the terminal, receives the delivered meal, and sends feedback about the meal to the server through the terminal. The input is the user's feedback based on the provided meal, and the output is the feedback data sent to the server.

[2111] Step 7:

[2112] The server generates customized content (music playlists, articles, videos, etc.) based on the user's hobbies and interests and delivers it to the device. The input is data about the user's interests, and the output is the generated content.

[2113] Step 8:

[2114] The device monitors the location information when the subject goes out and sends appropriate notifications to ensure safety. The input is the subject's location data, and the output is a safety notification when the subject goes out.

[2115] In this way, this system can coordinate multiple processing steps to provide health management, dietary support, and daily living support for the elderly.

[2116] 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.

[2117] This invention relates to a system that utilizes AI and an emotion engine to provide health management, dietary support, and daily life support for the elderly. As explained below, this system realizes functions that comprehensively improve the quality of life for the elderly by linking the server, terminals, and users and combining the emotion engine.

[2118] Health management support

[2119] server

[2120] The server periodically collects the latest health data from the subject's sensors, including blood pressure, heart rate, and body temperature.

[2121] The collected data is processed by an analysis algorithm on the server, which compares it with normal ranges to detect abnormalities.

[2122] If an abnormality is detected, the server notifies the medical facility via email or API.

[2123] Terminal

[2124] The analysis results sent from the server are received and notified to the subject and caregiver. For example, a message such as "Your blood pressure is high. Please contact a medical facility." is displayed.

[2125] It also sends out alerts to prevent you from forgetting to take your medicine. For example, it will notify you at 9pm every night that it's time to take your medicine.

[2126] User

[2127] Users receive notifications from their devices, contact medical facilities as needed, and manage health risks by taking prescribed medications at the appropriate times.

[2128] Meal support

[2129] server

[2130] The server generates a customized meal plan based on the subject's health information and dietary preferences, suggesting low-carb options for a diabetic, for example.

[2131] Based on this meal plan, meal orders are placed with affiliated delivery services.

[2132] Terminal

[2133] The system receives meal plan information sent from the server and notifies the user of the next meal and estimated delivery time. For example, it displays, "Dinner will arrive at 7 p.m. The menu is grilled salmon."

[2134] User

[2135] Users can check the meal plan provided and receive meals from the delivery service through the device, and can also provide feedback on the taste and quality of the meal through the device.

[2136] Daily life support

[2137] server

[2138] The server generates customized content based on the subject's hobbies and interests, including music playlists, videos, articles, and more.

[2139] The content is delivered to the device at the appropriate time, for example, a classical music playlist when the person is relaxing in the morning.

[2140] Terminal

[2141] Receives content sent from the server and provides it to the target user, for example, playing a music playlist through a speaker.

[2142] When the target person goes out, the location information is monitored and a timely notification is sent to ensure safety. For example, a notification such as "Your current location is in a park" is sent periodically.

[2143] Utilizing the Emotion Engine

[2144] server

[2145] The emotion engine recognizes emotions from the target person's facial expressions, tone of voice, etc. and adapts behavior accordingly.

[2146] Based on the recognized emotions, more personalized content can be generated and delivered, for example, if the target person is feeling stressed, it can suggest relaxing music or soothing videos.

[2147] The results of health analysis will also be adjusted based on your emotional state. For example, if you are under high stress, your health data will be analyzed more carefully than usual.

[2148] Terminal

[2149] The device receives feedback from the emotion engine and provides real-time support according to the user's emotional state. For example, if the device detects that the user is stressed, it will play soothing content.

[2150] User

[2151] Users can receive services adapted to their emotional state through their devices. By accepting suggestions and notifications based on their emotional state, they can live their daily lives more comfortably.

[2152] This system will enable comprehensive care support for the elderly, including health management, dietary support, improving the quality of daily life, and even addressing their emotional state.

[2153] The processing flow will be explained below.

[2154] Health management support

[2155] Step 1:

[2156] server

[2157] The server periodically collects health data such as blood pressure, heart rate, and body temperature from the subject's sensors, which are typically wearable devices.

[2158] Step 2:

[2159] server

[2160] The collected health data is processed using an analytical algorithm. For example, if blood pressure exceeds 160 / 100 mmHg, it is deemed abnormal.

[2161] Step 3:

[2162] server

[2163] If an abnormality is detected, the server automatically notifies the medical facility, including details of the abnormality and the latest health data.

[2164] Step 4:

[2165] Terminal

[2166] The analysis results sent from the server are received and notified to the subject and caregiver. For example, a message such as "Your blood pressure is high. Please contact a medical facility" is displayed on the screen.

[2167] Step 5:

[2168] Terminal

[2169] To prevent forgetting to take medicine, the device will send out periodic alerts. At 9 p.m. every night, it will notify you by voice or vibration that it's time to take your medicine.

[2170] Meal support

[2171] Step 1:

[2172] server

[2173] It generates a customized meal plan based on the individual's health information and dietary preferences, suggesting low-carb options for someone with diabetes, for example.

[2174] Step 2:

[2175] server

[2176] Based on the meal plan, you will place a meal order with a partner delivery service, which will include meal details and delivery times.

[2177] Step 3:

[2178] Terminal

[2179] It receives meal plan and delivery information sent from the server and notifies the user of the next meal and estimated delivery time. It displays, "Dinner will arrive at 7 p.m. The menu is grilled salmon."

[2180] Daily life support

[2181] Step 1:

[2182] server

[2183] The server generates customized content based on the user's hobbies and interests, such as music playlists or TV show listings.

[2184] Step 2:

[2185] server

[2186] The generated content is delivered to the device at the appropriate time, for example, a classical music playlist is sent in the morning when the target person is relaxing.

[2187] Step 3:

[2188] Terminal

[2189] Receives content sent from the server and provides it to the target user, for example, playing a music playlist through a speaker.

[2190] Step 4:

[2191] Terminal

[2192] When the target person goes out, GPS technology is used to monitor their location and periodically notify them of their current location, with a message such as "Your current location is in a park" displayed on the screen.

[2193] Utilizing the Emotion Engine

[2194] Step 1:

[2195] server

[2196] The emotion engine is used to recognize emotions by analyzing the subject's facial expressions and tone of voice. For example, it analyzes data acquired through a camera and microphone to identify emotions such as stress or joy.

[2197] Step 2:

[2198] server

[2199] Based on the emotions recognized, the system generates more personalized content, for example, suggesting relaxing music or meditation videos if the subject is feeling stressed.

[2200] Step 3:

[2201] Terminal

[2202] The device receives emotion-based content sent from the server and provides it to the subject in real time. For example, if stress is detected, the device will play soothing music.

[2203] User Interaction

[2204] Step 1:

[2205] User

[2206] The user checks the notification from the device and takes action based on the provided information. For example, if the user receives a notification to take medicine, the user takes the medicine promptly.

[2207] Step 2:

[2208] User

[2209] Receive meals based on a suggested meal plan and enjoy content, such as a new music playlist, to enhance your relaxation time.

[2210] Step 3:

[2211] User

[2212] Accept suggestions and notifications based on emotion monitoring to make your daily life more comfortable. For example, if you are feeling stressed, you can watch a meditation video to relax.

[2213] Through these processing steps, a comprehensive care system is realized that includes health management, meal support, daily living assistance, and emotional care for the elderly.

[2214] Example 2

[2215] 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."

[2216] A system that provides integrated health management, dietary support, and daily life support for the elderly is needed. In particular, there is a need for systems that can detect abnormalities in health data and notify medical facilities, generate and deliver meal plans based on health information, provide content based on hobbies and interests in daily life, and ensure safety when out and about. Comprehensive support that takes into account the emotional state of the recipient and promotes relaxation and stress reduction is also needed.

[2217] 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.

[2218] In this invention, the server includes means for collecting health information of the subject from a sensor, means for analyzing the collected health information and detecting abnormalities, means for notifying a medical facility when an abnormality is detected, means for generating a meal plan based on the health information, means for proposing the generated meal plan, means for generating and distributing content based on the subject's hobbies and interests, means for monitoring location information and notifying when the subject goes out, and means for recognizing the subject's emotional state and adapting behavior based thereon. This enables health management, meal support, improvement of quality of daily life for the elderly, and comprehensive care support that responds to emotional states.

[2219] A "sensor" is a device used to collect a subject's health information (blood pressure, heart rate, body temperature, etc.) in real time.

[2220] "Analysis" refers to data processing procedures for detecting abnormal values ​​based on collected health information.

[2221] "Notification" is a means of transmitting information to medical facilities and the like when an abnormality is detected.

[2222] A "meal plan" refers to a meal menu customized for health management based on a subject's health information and dietary preferences.

[2223] "Content" refers to information and entertainment generated based on the subject's hobbies and interests.

[2224] "Location information" is data that indicates the subject's current geographic location.

[2225] "Emotional state" is the result of recognizing the subject's current psychological state from facial expressions, tone of voice, etc.

[2226] "Delivery service" refers to a service that delivers food based on a meal plan to the target person.

[2227] An "alert" is a notification sent to prevent you from forgetting to take your medicine.

[2228] The present invention relates to a system that provides integrated health management, dietary support, and daily life support for the elderly. This system improves the quality of life for the elderly in a comprehensive manner by linking a server, terminals, and users and by utilizing an emotion engine. A specific embodiment of the system is shown below.

[2229] Health management support

[2230] server

[2231] The server collects health data such as the subject's blood pressure, heart rate, and body temperature from sensors in wearable devices and other devices. This data is collected using cloud services such as AWS IoT and Google Cloud IoT Core. The collected data is processed using analysis algorithms written in Python or R. Data analysis evaluates whether the subject's health data is within the normal range and detects abnormal values. For example, if blood pressure is higher than normal, it is determined to be abnormal.

[2232] If an abnormality is detected, the server uses the Twilio API to send a notification to the medical facility. The notification includes basic information about the subject and the type of abnormality. For example, a notification such as "Subject A's blood pressure is 180 / 120. Emergency treatment is required" may be sent.

[2233] Terminal

[2234] The device receives the analysis results sent from the server. This is done using Firebase or REST API. The received information is notified to the subject and caregiver. Specifically, it displays a message saying, "Your blood pressure is high. Please contact a medical facility." Additionally, to prevent forgetting to take medication, an alert is displayed every night at 9 p.m. saying, "It's time to take your medication."

[2235] User

[2236] The user receives notifications from the device and contacts a medical facility as needed. For example, if an abnormality in blood pressure is detected, the user can call a medical facility. Also, based on the alerts on the device, the user can take prescribed medication at the specified time.

[2237] Meal support

[2238] server

[2239] The server generates a customized meal plan using a cloud-based database (e.g., Firebase Firestore) based on the subject's health information and dietary preferences. For example, it creates a low-carb menu for a diabetic patient. Based on this meal plan, the server issues an order to a partner delivery service (e.g., Uber Eats API). The server provides the subject's information (address, meal contents) to the delivery service.

[2240] Terminal

[2241] The device receives the meal plan information sent from the server. Firebase and REST APIs are also used for this. The device then notifies the target user of the next meal plan and the estimated delivery time. For example, it might display, "Dinner will arrive at 7 p.m. The menu is grilled salmon."

[2242] User

[2243] The user checks the provided meal plan on the device and receives the meal from the delivery service. Specifically, they receive a grilled salmon meal at 7 p.m. They also send feedback about the taste and quality of the meal to the server via the device. For example, they can enter, "The grilled salmon was delicious, but I wish it was a little less salty."

[2244] Daily life support

[2245] server

[2246] The server uses the Spotify API or Netflix API to generate content based on the user's hobbies and interests. For example, it creates a playlist of relaxing classical music or an interesting video. The generated content is delivered to the user's device at the time they want. For example, a classical music playlist is sent to relax in the morning.

[2247] Terminal

[2248] The device receives the content sent from the server and provides it to the target person. For example, it plays a generated music playlist from a speaker. The device also monitors the target person's location using its GPS function and sends notifications to ensure their safety. Specifically, the device periodically notifies the target person that "Your current location is in a park."

[2249] User

[2250] Users can check notifications from their devices to ensure their safety. They can listen to classical music during relaxation time, or check location notifications to confirm that they are in a park or other location.

[2251] Utilizing the Emotion Engine

[2252] server

[2253] The server uses an emotion engine such as Microsoft Azure Cognitive Services to recognize emotions from the subject's facial expressions and tone of voice. Specifically, it determines whether the subject is stressed or relaxed. Based on the recognized emotions, it generates more personalized content, for example, suggesting music or videos to relax the subject if they are stressed. It also adjusts the analysis results of health information based on the subject's emotional state. For example, when the subject is in a high stress state, it analyzes health data more carefully.

[2254] Terminal

[2255] The device receives feedback from the emotion engine and provides support that adapts to the user's emotional state in real time. For example, if the device detects stress, it will play soothing music or videos.

[2256] User

[2257] Users can receive services adapted to their emotional state through their devices. For example, listening to soothing music when feeling stressed can help users lead a more comfortable daily life.

[2258] This system can provide comprehensive care support for the elderly, including health management, dietary support, improving the quality of daily life, and even addressing their emotional state.

[2259] Prompt Sentence Examples

[2260] You want to develop a system to provide health management, meal support, and daily life support for the elderly. Collect and analyze health data, customize meal plans, order them from delivery services, and deliver customized content at the right time. Consider how to incorporate an emotion engine into this system to provide more personalized support.

[2261] Based on this example and prompt, it is believed that it will be easier to understand the system's functionality and how it is implemented.

[2262] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2263] Health management support

[2264] server

[2265] Step 1:

[2266] The server collects health data from the sensors.

[2267] Input: Data such as blood pressure, heart rate, and temperature obtained from wearable devices.

[2268] Output: Store the collected health data in a cloud database.

[2269] Specific operation: Uses AWS IoT or Google Cloud IoT Core to acquire data in real time and store it in a database.

[2270] Step 2:

[2271] The server analyzes the collected health data.

[2272] Input: Health data stored in a cloud database.

[2273] Output: Analyzed data results (e.g. outlier detection).

[2274] What it does: It uses analytics algorithms written in Python or R to compare data with health standards and detect abnormalities. For example, a blood pressure of 180 / 120 is considered abnormal.

[2275] Step 3:

[2276] The server notifies the medical facility if an abnormality is detected.

[2277] Input: Parsed data results.

[2278] Output: Notification sent to healthcare facility.

[2279] Specific behavior: Uses the Twilio API to send notifications to medical facilities via email and SMS. Example: "Subject A's blood pressure is 180 / 120. Emergency treatment is required."

[2280] Terminal

[2281] Step 1:

[2282] The terminal receives the analysis result from the server.

[2283] Input: Analysis results sent from the server.

[2284] Output: Analysis results displayed on the terminal.

[2285] Specific operation: Retrieves data via Firebase or REST API and displays it on the device screen.

[2286] Step 2:

[2287] The terminal notifies the analysis result.

[2288] Input: Received analysis results.

[2289] Output: Notification to subject and caregiver.

[2290] Specific behavior: Display "Your blood pressure is high. Please contact a medical facility." Also, display an alert every night at 9 PM saying "It's time to take your medication."

[2291] User

[2292] Step 1:

[2293] The user receives the notification and responds.

[2294] Input: Notifications from your device.

[2295] Output: Contact medical facility and take medication.

[2296] Specific actions: See the notification on the device, call a medical facility, see the notification at 9 PM, and take the prescribed medication.

[2297] Meal support

[2298] server

[2299] Step 1:

[2300] The server generates a meal plan based on the health information and dietary preferences.

[2301] Input: A database containing health information and dietary preferences.

[2302] Output: A customized meal plan.

[2303] What it does: It uses Firebase Firestore to retrieve information from a database and then uses an algorithm to generate a meal plan, for example, a low-carb menu for a diabetic.

[2304] Step 2:

[2305] The server issues orders to a delivery service based on the meal plan.

[2306] Input: The generated meal plan.

[2307] Output: Order information sent to the delivery service.

[2308] Specific operation: Use the Uber Eats API to provide the meal details and the target address to the delivery service. For example, specify "grilled salmon."

[2309] Terminal

[2310] Step 1:

[2311] The terminal receives the meal plan information from the server.

[2312] Input: Meal plan information sent from the server.

[2313] Output: Meal plan information displayed on the device.

[2314] Specific behavior: Receives data via Firebase or REST API and displays the next meal contents and estimated delivery time. Example: Notifies "Dinner will arrive at 7pm. The menu is grilled salmon."

[2315] User

[2316] Step 1:

[2317] The user confirms and receives the meal plan.

[2318] Input: Meal plan information provided on device.

[2319] Output: Meals from a delivery service.

[2320] Specific action: Pick up a grilled salmon meal from a delivery service at 7pm.

[2321] Step 2:

[2322] The user provides feedback.

[2323] Input: Feedback on the taste and quality of the food provided.

[2324] Output: Feedback information sent to the server.

[2325] Specific action: Enter "The grilled salmon was delicious, but I wish it was a little less salty" into the device.

[2326] Daily life support

[2327] server

[2328] Step 1:

[2329] The server generates content based on hobbies and interests.

[2330] Input: A database storing the subject's hobbies and interests.

[2331] Output: The generated content.

[2332] What it does: Uses Spotify API and Netflix API to generate music playlists and videos tailored to the target audience. For example, create a classical music playlist.

[2333] Step 2:

[2334] The server distributes the generated content.

[2335] Input: Generated content.

[2336] Output: Content information delivered to the device.

[2337] What it does: Send a morning relaxation classical music playlist via Firebase Cloud Messaging or the REST API.

[2338] Terminal

[2339] Step 1:

[2340] The terminal receives the content transmitted from the server.

[2341] Input: Content information sent from the server.

[2342] Output: The content that is displayed or played on a device.

[2343] Specific operation: Play the received music playlist from the speaker.

[2344] Step 2:

[2345] The terminal monitors and notifies the location information.

[2346] Input: Location information obtained by GPS.

[2347] Output: Location-based notifications.

[2348] Specific operation: Notify "Your current location is a park" at regular intervals.

[2349] User

[2350] Step 1:

[2351] The user uses the distributed content.

[2352] Input: Content displayed or played on the device.

[2353] Output: Satisfaction and relaxation from the content used.

[2354] Specific action: Listen to classical music during relaxation time. ...

Claims

1. a means for collecting health information of the subject from a sensor; A means for analyzing the collected health information and detecting abnormalities; a means for notifying a medical facility if an abnormality is detected; means for generating a meal plan based on the health information; a means for suggesting the generated meal plan; A means of generating and distributing content based on the hobbies and interests of the target audience; A means for monitoring location information and notifying the subject when he or she leaves the home; A system including:

2. The system of claim 1 further comprising means for issuing an alert to prevent forgetting to take medicine.

3. 10. The system of claim 1, further comprising means for ordering food from a delivery service based on the meal plan.

Images