system

Abstract

We provide the system. [Solution] A means of wirelessly receiving biometric data measured inside the body, A data analysis means for analyzing received biological data and detecting abnormalities, A means of notifying a medical institution or person in charge if an abnormality is detected, A means of displaying the analysis results on the user's terminal, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern society, busy businesspersons and elderly people with difficulty in moving have difficulty in regularly visiting medical institutions for health management. Therefore, there is a need for a technology that can easily monitor the health status of the body and detect health risks at an early stage, but there is a problem that it is difficult to achieve with conventional methods.

Means for Solving the Problems

[0005] To solve this problem, the present invention provides a system equipped with means for wirelessly receiving and analyzing biological data measured in the body in real time. Furthermore, if an abnormality is detected, the system immediately notifies a medical institution or person in charge, and presents the analysis results on the user's terminal, enabling predictive analysis by comparing with past data. This allows for efficient health management in daily life without the need for regular visits to medical institutions.

[0006] "Biometric data" refers to information that indicates the physical or chemical state of the body, and includes heart rate, body temperature, blood components, etc.

[0007] "Wireless" refers to a method of sending and receiving data using wireless communication technology that does not require wires or cables.

[0008] "Analysis means" refers to processes or devices used to analyze received data and detect specific patterns or anomalies.

[0009] "Abnormal" refers to symptoms or values ​​that deviate from the normal range of health conditions or data, indicating that attention or countermeasures are necessary.

[0010] A "medical institution" is a facility that has the equipment and specialists necessary for diagnosis, treatment, and prevention.

[0011] "User's device" refers to an electronic device owned by an individual user and used to display or operate information, such as a smartphone or tablet.

[0012] A "notification means" is a method or device for informing a target person of specific information or a change in status.

[0013] "Predictive analytics" is an analytical method that uses existing data to predict future states or events. [Brief explanation of the drawing]

[0014] [Figure 1]It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

MODE FOR CARRYING OUT THE INVENTION

[0015] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, the labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0018] In the following embodiments, the labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0019] In the following embodiments, the labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0020] In the following embodiments, the labeled communication I / F (Interface) is an interface including a communication processor and 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), or Bluetooth (registered trademark), and the like.

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0022] [First Embodiment]

[0023] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0024] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0025] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0027] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0030] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0033] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0034] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0035] This invention relates to a healthcare system that uses microcapsules taken by the user before going to bed. This system monitors biometric data in real time and promptly notifies the user if any abnormalities are detected.

[0036] This system begins by collecting biometric data from within the body using sensors inside a capsule. The capsule is designed to measure information such as heart rate, body temperature, and blood components.

[0037] When a user swallows a capsule, data is continuously collected within their body. This data is transmitted wirelessly to a server.

[0038] The server stores the received biometric data in a secure database. This data is then analyzed by an AI agent. The AI ​​agent can retrieve and analyze the data at any time to attempt to detect anomalies.

[0039] If an anomaly is detected, the server will immediately begin taking action. Specifically, it will notify the medical institution or relevant personnel of the nature of the anomaly. The server will also send notifications to the user's smartphone or wearable device so that the user can immediately check the anomaly.

[0040] Subsequently, the AI ​​agent performs predictive analysis based on the user's past data and provides specific health advice. Finally, the device presents the user with a generated health report. This report includes a real-time overview of their health status, a comparison with past data, and suggestions for improving their lifestyle.

[0041] This allows users to efficiently manage their health while continuing their daily lives.

[0042] The following describes the processing flow.

[0043] Step 1:

[0044] Users take microcapsules into their bodies before going to bed. Since these capsules measure internal bodily data, it is important to take them at the appropriate time.

[0045] Step 2:

[0046] The sensors inside the capsule begin collecting biometric data within the body. Important data such as heart rate, body temperature, and blood components are continuously recorded and updated at regular intervals.

[0047] Step 3:

[0048] The data collected by the capsule is transmitted to a server via wireless communication. The data is encrypted to ensure privacy and security.

[0049] Step 4:

[0050] The server stores the received data and saves it in a database. At the same time, it provides this data to the AI ​​agent to prepare it for analysis.

[0051] Step 5:

[0052] The AI ​​agent analyzes biometric data provided by the server. It attempts to identify patterns and anomalies within the data using anomaly detection algorithms.

[0053] Step 6:

[0054] If an anomaly is detected, the server will immediately notify the medical institution or relevant personnel of the details. This notification will be sent via email or a dedicated communication application.

[0055] Step 7:

[0056] At the same time, the server sends an anomaly notification to the user's device. The notification is sent in real time, allowing the user to check it on their smartphone or wearable device.

[0057] Step 8:

[0058] The AI ​​agent further analyzes health trends using historical data to predict the user's health risks. This analysis is then generated as a detailed health report.

[0059] Step 9:

[0060] The device displays a health report sent from the server to the user. The report includes suggestions for lifestyle improvements and points to be aware of.

[0061] Step 10:

[0062] Users can review the report, understand their own health status, and use the feedback to improve their daily lives.

[0063] (Example 1)

[0064] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0065] In recent years, with the increasing demand for personal health management, there is a growing need for systems that can monitor biological information in the body in real time and quickly detect and notify of abnormalities. However, existing systems have shortcomings in terms of the accuracy of anomaly detection, the speed of notification, and the efficiency of predictive analysis using historical data, thus requiring more advanced technology.

[0066] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0067] In this invention, the server includes means for receiving biological information measured within the body via wireless communication, an analysis device for analyzing the received biological information and detecting abnormalities, and means for performing abnormality detection using a generated knowledge processing model. This enables real-time, highly accurate abnormality detection, rapid notification, and the provision of health advice through predictive analysis.

[0068] "Biometric information measured within the body" refers to data on health status obtained using sensors inside the body, such as heart rate, body temperature, and blood components.

[0069] "Means of receiving via wireless communication" refers to a function for transmitting collected biometric information to a server via wireless technology.

[0070] An "analysis device" is a computer system used to process received biological information and detect abnormalities.

[0071] "Means of performing anomaly detection using a generated knowledge processing model" refers to a method of analyzing data using a generative AI model to find anomalous patterns.

[0072] An "analysis device for detecting abnormalities" is a device that analyzes biological information and identifies changes that are different from the normal state.

[0073] "Means for displaying analysis results on the user's information terminal" refers to a method of presenting the results after analysis on the information terminal so that the user can confirm them.

[0074] "A means of performing predictive analytics and generating health advice" refers to a function that compares past data with the current situation and uses machine learning to create suggestions regarding future health.

[0075] "Means for sending health status reports to user information terminals" refers to methods for transferring generated health reports to information terminals owned by the user.

[0076] This invention is a healthcare system that uses microcapsules taken by the user before going to bed to monitor biological information in the body in real time. The microcapsules contain sensors that measure heart rate, body temperature, blood components, etc., and transmit this data to a server via wireless communication.

[0077] The server processes the received biometric information using a dedicated analysis device. The analysis utilizes a generative AI model based on Python and TENSORFLOW®, enabling high-precision detection of data anomalies. For example, the server constantly sends the following prompt to the generative AI model to perform anomaly detection: "Please analyze the user's heart rate data for any anomalies."

[0078] If an abnormality is detected, the server will promptly provide information to the medical institution or relevant personnel. Specifically, it will send detailed information, including analysis results, via email or SMS. The server will also send notifications to the user's smartphone or wearable device so that the user can immediately check for the abnormality. These notifications may include messages such as, "Your body temperature is outside the normal range. Please check the details."

[0079] Furthermore, the server's AI agent performs predictive analysis and provides users with specific health advice. It compares past and current data to derive suggestions for improving health. The results of this analysis are sent to the user's information terminal as a health status report. An example of specific advice is generated, such as, "Based on recent data analysis, we recommend light exercise every day to reduce stress."

[0080] The terminal ultimately presents the user with a health status report generated based on this information, thereby enabling improved health management in daily life. In this way, the present invention provides an advanced system that meets the need for personal health management in modern society.

[0081] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0082] Step 1:

[0083] The user swallows a microcapsule.

[0084] Input: The action of taking a capsule.

[0085] Output: Measurement of biological information by sensors within the body begins.

[0086] Specifically, sensors inside the capsule continuously collect biometric information such as heart rate, body temperature, and blood components.

[0087] Step 2:

[0088] The server receives biometric information wirelessly.

[0089] Input: Biometric information transmitted from the sensor.

[0090] Output: The received biometric information is stored on the server.

[0091] Biometric information is sent to a server via secure wireless communication, and the server records this information in a database protected by the latest security protocols.

[0092] Step 3:

[0093] Data analysis is performed using a generated AI model on the server.

[0094] Input: Biometric information stored in the database.

[0095] Output: Analysis results regarding the presence or absence of abnormalities.

[0096] Using Python and TensorFlow, the generated AI model executes the prompt message "Analyze the heart rate data for any abnormalities" and searches for outliers.

[0097] Step 4:

[0098] The server will send a notification when it detects an anomaly.

[0099] Input: Anomaly information detected by AI analysis.

[0100] Output: Notifications to medical institutions and users.

[0101] The server sends notifications containing details of the anomaly to medical institutions via email or SMS, and also sends push notifications to users' smartphones and wearable devices.

[0102] Step 5:

[0103] The server performs predictive analysis and generates health advice.

[0104] Input: Past biometric data and current analysis results.

[0105] Output: Health advice for the user.

[0106] Based on the data, the AI ​​model performs an analysis with the prompt message, "Create health advice based on the results of predictive analysis," and generates suggestions.

[0107] Step 6:

[0108] The device presents the user with a health report.

[0109] Input: Generated health status report.

[0110] Output: A health report in a format that can be viewed by the user.

[0111] The device will display reports, allowing users to check their health status in real time and use the information to improve their lifestyle.

[0112] (Application Example 1)

[0113] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0114] In modern society, there is a need to understand health conditions in real time and respond immediately when abnormalities occur. However, conventional methods rely on external devices for monitoring biometric data, making real-time response difficult. Furthermore, health conditions may deteriorate without the user noticing. Therefore, there is a need for a system that can continuously monitor the user's health condition and respond quickly to abnormalities.

[0115] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0116] In this invention, the server includes a device for wirelessly receiving biological data measured in the body, a data analysis device for analyzing the received biological data and detecting abnormalities, a device for notifying a medical facility or responsible person when an abnormality is detected, a device for presenting the analysis results to the user's information processing terminal, and a device for the information processing terminal to provide health information to the user in real time. This enables continuous monitoring of the user's health status, rapid detection of abnormalities, and appropriate responses.

[0117] "Biometric data measured inside the body" refers to physiological information acquired in real time by measuring devices placed inside the user's body.

[0118] A "wireless receiving device" is a device that uses wireless communication technology to remotely receive biometric data.

[0119] A "data analysis device" is a device that uses received biometric data to analyze the user's health status and determine whether there are any abnormalities.

[0120] A "device that notifies when an abnormality is detected" is a device that, based on the results of biometric data analysis, notifies relevant organizations and users when it is determined that there is a health abnormality.

[0121] A "user's information processing terminal" refers to a device, such as a smartphone or tablet, that a user uses to receive and verify information.

[0122] A "device that presents analysis results" is a device that displays the results of the analysis of biometric data to the user.

[0123] A "device that provides health information in real time" is a device that provides information immediately so that users can quickly understand their current health status.

[0124] The system that realizes this invention consists of multiple hardware and software components. The server wirelessly acquires data from microcapsules placed inside the body in order to receive biometric data. The microcapsules are equipped with sensors that measure the user's physiological information, such as heart rate, body temperature, and blood components.

[0125] The server can analyze the received biometric data using a data analysis device to detect anomalies. This analysis device compares past biometric data with data received in real time and executes an algorithm to identify anomalies. This algorithm incorporates a generative AI model, enabling advanced analysis.

[0126] If an anomaly is detected, the server notifies the medical facility and responsible party of the details of the anomaly. Appropriate communication protocols are used for this process. Furthermore, the analysis results are immediately transmitted to the user's information processing terminal, allowing the user to monitor their health status in real time.

[0127] On the user's information processing terminal, the analysis results are presented visually or audibly. The information processing terminal can take the form of a smartphone or tablet, allowing users to access health information in their daily lives. For example, if there are no abnormalities, the user is notified accordingly; if abnormalities are found, specific health advice is provided by the AI ​​model. Prompt messages can include instructions such as, "Your body temperature is high, so please drink plenty of fluids."

[0128] This invention allows users to continuously monitor their health status and take immediate action when an abnormality is detected, thereby streamlining health management in daily life.

[0129] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0130] Step 1:

[0131] The server wirelessly receives biometric data transmitted from the microcapsules. Specifically, it uses a wireless module to capture the signal and stores this signal as data in the server's memory. The input is the wireless signal from the microcapsule, and the output is the biometric data stored on the server side.

[0132] Step 2:

[0133] The server analyzes the received biometric data using an analysis device. Here, the current data is evaluated by comparing it with previously stored data. The input is the biometric information data acquired in step 1, and the output is the analysis result, i.e., whether or not there is an abnormality. Specifically, data analysis is performed by a generative AI model incorporating an AI agent.

[0134] Step 3:

[0135] If the server detects an anomaly, it activates the notification system. This includes notifying medical facilities, personnel, and users' information processing terminals of the details of the anomaly. The input is the anomaly information detected in step 2, and the output is the notified anomaly information. Specifically, the server uses push notifications and email to quickly disseminate information to relevant parties.

[0136] Step 4:

[0137] The user's information processing terminal receives analysis results and anomaly notifications transmitted from the server. The input is the information notified in step 3, and the output is the confirmed information received by the user visually or audibly. Specifically, the terminal displays the notification content on its screen and provides the user with anomaly information and health advice through voice guidance.

[0138] Step 5:

[0139] The user checks their health status based on the received information and takes action as needed. The input is the analysis results and health advice received in step 4, and the output is the specific actions the user will take. These specific actions might include drinking water or consulting a doctor to maintain their health.

[0140] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0141] This invention combines an emotional engine with a healthcare system that uses microcapsules ingested by the user before bedtime. This system recognizes not only biometric data but also the user's emotional state, providing a comprehensive analysis of their health status and personalized health advice.

[0142] This system first collects biometric data from within the body using sensors inside a capsule. The data measured includes heart rate, body temperature, and other physiological parameters. Once the user ingests the capsule, continuous data collection within the body begins.

[0143] The collected data is transmitted wirelessly to a server. The server receives and stores the encrypted data, and then passes it on to the AI ​​agent and emotion engine.

[0144] The AI ​​agent analyzes biometric data and attempts to detect anomalies. Predictive analytics are also performed during this analysis to assess the user's health risks. Meanwhile, the emotion engine infers the user's emotional state based on the collected data. For example, it can estimate stress levels and happiness levels from heart rate fluctuations and body temperature changes. These estimation results are incorporated into the health report.

[0145] If an anomaly is detected, or if a specific emotional state persists, the server will promptly notify a healthcare provider or relevant personnel. Simultaneously, the server will send a notification to the user's device, allowing the user to immediately access the information.

[0146] The health report is an overall health assessment that includes emotional state and is provided to the user via the device. This report includes lifestyle improvement advice based on the user's emotional state, as well as information on the correlation between emotions and health status.

[0147] For example, if a user's heart rate is abnormally high and the emotional engine recognizes a high-stress state, the server immediately notifies the attending physician. Furthermore, relaxation techniques for stress management are recommended on the user's smartphone. This system enables comprehensive health support from both an emotional and physical perspective.

[0148] The following describes the processing flow.

[0149] Step 1:

[0150] Users ingest microcapsules before going to sleep. These capsules contain sensors that measure biometric data such as heart rate and body temperature.

[0151] Step 2:

[0152] Sensors inside the capsule begin to continuously collect biometric data within the body. The data is updated regularly, and health status is monitored in real time.

[0153] Step 3:

[0154] The collected biometric data is transmitted to a server via wireless communication. This communication is encrypted to ensure data security.

[0155] Step 4:

[0156] The server records the received data in a database and prepares it for analysis. At the same time, it sends the data to the AI ​​agent and emotion engine.

[0157] Step 5:

[0158] The AI ​​agent analyzes biometric data and attempts to identify anomalies. It compares this data with past data and uses predictive analytics to assess future health risks.

[0159] Step 6:

[0160] The emotion engine analyzes fluctuations in heart rate and body temperature from biometric data to estimate the user's emotional state. For example, a high heart rate may indicate a state of stress.

[0161] Step 7:

[0162] If a user's health risk is determined to be high, or if a specific emotional state is recognized, the server will notify a healthcare provider or relevant personnel. This notification is made electronically, enabling a rapid response.

[0163] Step 8:

[0164] Simultaneously, the server sends a notification to the user's terminal, providing real-time alerts. Users can check the notification on their smartphone or wearable device.

[0165] Step 9:

[0166] Based on the analysis results from the AI ​​agent and emotion engine, a detailed health report is generated. This report includes an overall assessment of health status, an estimated emotional state, and personalized health advice.

[0167] Step 10:

[0168] The device displays a generated health report to the user. The report details suggestions and points to note for improving lifestyle habits based on the user's emotional state. The user can use this information to adjust their lifestyle.

[0169] (Example 2)

[0170] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0171] Traditional healthcare systems assessed health status by analyzing only the user's biometric information, making it difficult to provide comprehensive health support that considered the user's emotional state and stress levels. Furthermore, the inability to detect anomalies in real time or track emotional states could lead to delays in situations requiring rapid response.

[0172] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0173] In this invention, the server includes means for wirelessly receiving biometric information, information analysis means for analyzing the received biometric information and detecting anomalies, and emotion estimation means for inferring the user's emotional state based on the analyzed biometric information. This makes it possible to comprehensively evaluate the user's biometric information and emotional state, detect anomalies in real time, and provide necessary notifications and advice.

[0174] "Biometric information measured within the body" refers to health-related physiological indicators, such as heart rate and body temperature, that are continuously acquired by sensors placed inside the user's body.

[0175] "Means of receiving wirelessly" refers to communication technologies that transmit biometric information to external devices using Bluetooth, Wi-Fi, etc.

[0176] "Information analysis means" refers to algorithms and programs used to analyze received biological information and perform abnormal value detection and predictive analysis.

[0177] "Emotion estimation methods" refer to technologies and processes that estimate a user's emotional state and stress level based on the results of biometric data analysis.

[0178] A "notification method" refers to a system that informs medical institutions or relevant personnel of the situation when an abnormality or a specific emotional state is detected.

[0179] "User's device" refers to an information terminal such as a smartphone or tablet owned by the user, and is a device used to display health status reports and notifications.

[0180] A "health status report" is a report that summarizes the analysis results, including the user's biometric information and emotional state, and is a document that provides health advice to the user.

[0181] This invention is a unique healthcare system that uses microcapsules ingested by the user before going to sleep. By ingesting the microcapsules, the user's body continuously collects biological information through sensors. The capsules contain small sensors and communication modules that collect data such as heart rate and body temperature. This data is transmitted wirelessly from the capsule to a server. Wireless communication technologies used in this system include Bluetooth and Wi-Fi.

[0182] The server encrypts the received biometric information and stores it in a database. Next, it processes this data using information analysis tools, and an AI model performs anomaly detection and predictive analysis. The AI ​​model compares historical data with real-time data to assess the user's health risk.

[0183] Simultaneously, the emotion estimation system predicts the user's emotional state based on heart rate fluctuations and changes in body temperature. This process utilizes an emotion engine to predict stress levels and happiness levels. This allows for a comprehensive assessment of the user's health status.

[0184] If an abnormality or a specific emotional state is detected, the server immediately notifies the attending physician or medical institution. This notification is often sent via email or a dedicated application. The server also sends a health status report to the user's device, providing the user with analysis results and advice for lifestyle improvements.

[0185] As a concrete example, consider a scenario where a user ingests a microcapsule and the system detects a high-stress state. In this case, the server quickly notifies the attending physician, and the user's terminal recommends relaxation techniques such as "take five minutes of deep breathing." An example of a prompt message might be, "Use the data collected by the microcapsule to evaluate the user's emotional state and generate specific advice for stress management." This invention allows users to receive comprehensive support from both emotional and physical perspectives.

[0186] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0187] Step 1:

[0188] When a user ingests a microcapsule, sensors placed inside the body collect biometric information such as heart rate and body temperature in real time. The input is the user's biometric information, and the output is a backend system for wireless data transmission. Specifically, the microcapsule's sensors detect the biometric information and prepare the data for transmission by packetizing it via a built-in wireless communication module.

[0189] Step 2:

[0190] The transmitted biometric information reaches the server, where it is encrypted and received. The input is encrypted biometric information transmitted from the microcapsule, and the output is a secure database for temporary storage. The server then decrypts the received data and performs the specific actions of storing it in the database for appropriate storage.

[0191] Step 3:

[0192] Biometric information stored on the server is passed to an information analysis system, where an AI model performs anomaly detection and predictive analysis. The input is the biometric information stored on the server, and the output is the analysis results, such as the identification of anomalies. Specifically, the AI ​​model analyzes the biometric information and detects anomalies in real time while comparing it with past data.

[0193] Step 4:

[0194] Based on the analysis results, the server uses emotion estimation tools to predict the emotional state. The input is the analyzed biometric information, and the output is the user's emotional state and stress level. The emotion engine uses fluctuations in heart rate and changes in body temperature to estimate emotions and perform specific actions to identify the user's emotional state.

[0195] Step 5:

[0196] If the server detects an abnormality or a specific emotional state, it immediately notifies healthcare providers and relevant personnel, and also sends a notification to the user's terminal. The input is the result of analysis and estimation, and the output is the notification content. The server uses communication means to perform specific actions to inform healthcare professionals and users of the situation.

[0197] Step 6:

[0198] Ultimately, the server generates a health status report and sends it to the user's device. The inputs are the analysis results and emotional state, and the output is the health status report. The server performs a comprehensive health assessment, generates a report, and delivers it to the user's device.

[0199] (Application Example 2)

[0200] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0201] For elderly individuals and those with specific health concerns, there is a need for a system that can comprehensively understand fluctuations in physiological parameters within the body and emotional states, and immediately assess their health status. However, conventional healthcare systems have challenges in assessing health, including emotional states, and thus hindering rapid care responses.

[0202] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0203] In this invention, the server includes means for wirelessly receiving physiological parameters measured within the body, information analysis means for analyzing the received physiological parameters and detecting abnormal values, and means for estimating the user's emotional state and incorporating that information into the health status assessment. This enables a comprehensive health assessment that also takes emotional state into consideration.

[0204] "Physiological parameters" are numerical data related to the body, such as heart rate and body temperature, that are measured within the body.

[0205] "Means of receiving wirelessly" refers to a system for remotely acquiring data using wireless communication technologies such as Bluetooth or Wi-Fi.

[0206] "Information analysis means" refers to processes and equipment used to detect and analyze numerical anomalies based on acquired data.

[0207] An "abnormal value" is a physiological parameter value that falls outside the normal range and may indicate a health problem.

[0208] "Means for reporting to a medical institution or responsible organization" refers to communication methods for quickly informing medical personnel or management organizations when abnormal values ​​are detected.

[0209] "Means for displaying analysis results on information devices" refers to screen display functions that visually show analysis results on devices such as smartphones and computers.

[0210] "Emotional state" refers to an individual's emotional state, such as stress or happiness, estimated from fluctuations in acquired physiological parameters.

[0211] "Health assessment" is a process of diagnosing and analyzing an individual's overall health based on information about physiological parameters and emotional state.

[0212] This system provides users with wearable or ingestible sensors that continuously measure physiological parameters within the body. The measured data is transmitted to a server using wireless communication technologies such as Bluetooth or Wi-Fi. The server performs real-time analysis of the data using programming languages ​​such as Python. Machine learning libraries such as TensorFlow and PyTorch are used as information analysis tools to efficiently detect anomalies in the obtained data in order to detect abnormal values ​​of physiological parameters.

[0213] The server also utilizes AI agents and an emotion engine to estimate emotional states. This emotional state estimation employs sophisticated algorithms based on heart rate and body temperature fluctuations to understand the emotional state of each individual user. This enables a comprehensive health assessment of the user.

[0214] The analysis results and estimated emotional state are transmitted in real time to the user's device, specifically a smartphone or tablet. This device is designed to visually present information, making it easy for the user to understand their own health status. In particular, if an abnormality is detected, the system immediately notifies medical institutions or relevant organizations.

[0215] As a concrete example, consider a scenario where an abnormal heart rate is detected in an elderly person while they are sleeping, and the emotional engine recognizes a high-stress state. The server can immediately issue a warning and send a notification to the caregiver recommending relaxation techniques.

[0216] An example of a prompt message is, "Write code to analyze the user's heart rate and body temperature and estimate their stress level." This enables advanced health support utilizing generative AI models.

[0217] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0218] Step 1:

[0219] The sensor measures physiological parameters such as heart rate and body temperature inside the user's body. The input is biometric data acquired in real time. This data is temporarily stored within the sensor.

[0220] Step 2:

[0221] The sensor wirelessly transmits physiological parameters to the server via Bluetooth or Wi-Fi. The server receives this data as input and stores it in a database. The output is temporary data storage on the server.

[0222] Step 3:

[0223] The server initiates data analysis using a Python program. Input consists of historical data and newly received biometric data. An AI agent and machine learning algorithms (e.g., TensorFlow) are used to detect anomalies in the data. The output is the analysis result regarding the presence or absence of anomalies.

[0224] Step 4:

[0225] The server simultaneously uses an emotion engine to estimate the user's emotional state. The input consists of data on heart rate and body temperature fluctuations. Through data processing, it generates and outputs emotional indicators such as stress levels and feelings of well-being.

[0226] Step 5:

[0227] The server wirelessly transmits the analysis results and estimated emotional state to the user's terminal. The input is the enriched data obtained through the analysis process. The terminal receives this data and outputs it by visually displaying it on the screen.

[0228] Step 6:

[0229] When an anomaly is detected, the server immediately sends a notification to the healthcare institution or responsible organization. The input is the anomaly detection result. A notification message is generated via the communication protocol and output to the necessary location.

[0230] Step 7:

[0231] Based on data received by the user's device, the system suggests appropriate health advice and relaxation techniques. Input consists of analysis results and emotion estimation results. The output is displayed in a user-friendly format via the device's GUI.

[0232] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0233] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0234] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0235] [Second Embodiment]

[0236] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0237] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0238] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0239] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0240] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0241] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0242] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0243] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0244] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0245] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0246] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0247] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0248] This invention relates to a healthcare system that uses microcapsules taken by the user before going to bed. This system monitors biometric data in real time and promptly notifies the user if any abnormalities are detected.

[0249] This system begins by collecting biometric data from within the body using sensors inside a capsule. The capsule is designed to measure information such as heart rate, body temperature, and blood components.

[0250] When a user swallows a capsule, data is continuously collected within their body. This data is transmitted wirelessly to a server.

[0251] The server stores the received biometric data in a secure database. This data is then analyzed by an AI agent. The AI ​​agent can retrieve and analyze the data at any time to attempt to detect anomalies.

[0252] If an anomaly is detected, the server will immediately begin taking action. Specifically, it will notify the medical institution or relevant personnel of the nature of the anomaly. The server will also send notifications to the user's smartphone or wearable device so that the user can immediately check the anomaly.

[0253] Subsequently, the AI ​​agent performs predictive analysis based on the user's past data and provides specific health advice. Finally, the device presents the user with a generated health report. This report includes a real-time overview of their health status, a comparison with past data, and suggestions for improving their lifestyle.

[0254] This allows users to efficiently manage their health while continuing their daily lives.

[0255] The following describes the processing flow.

[0256] Step 1:

[0257] Users take microcapsules into their bodies before going to bed. Since these capsules measure internal bodily data, it is important to take them at the appropriate time.

[0258] Step 2:

[0259] The sensors inside the capsule begin collecting biometric data within the body. Important data such as heart rate, body temperature, and blood components are continuously recorded and updated at regular intervals.

[0260] Step 3:

[0261] The data collected by the capsule is transmitted to a server via wireless communication. The data is encrypted to ensure privacy and security.

[0262] Step 4:

[0263] The server stores the received data and saves it in a database. At the same time, it provides this data to the AI ​​agent to prepare it for analysis.

[0264] Step 5:

[0265] The AI ​​agent analyzes biometric data provided by the server. It attempts to identify patterns and anomalies within the data using anomaly detection algorithms.

[0266] Step 6:

[0267] If an anomaly is detected, the server will immediately notify the medical institution or relevant personnel of the details. This notification will be sent via email or a dedicated communication application.

[0268] Step 7:

[0269] At the same time, the server sends an anomaly notification to the user's device. The notification is sent in real time, allowing the user to check it on their smartphone or wearable device.

[0270] Step 8:

[0271] The AI ​​agent further analyzes health trends using historical data to predict the user's health risks. This analysis is then generated as a detailed health report.

[0272] Step 9:

[0273] The device displays a health report sent from the server to the user. The report includes suggestions for lifestyle improvements and points to be aware of.

[0274] Step 10:

[0275] Users can review the report, understand their own health status, and use the feedback to improve their daily lives.

[0276] (Example 1)

[0277] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0278] In recent years, with the increasing demand for personal health management, there is a growing need for systems that can monitor biological information in the body in real time and quickly detect and notify of abnormalities. However, existing systems have shortcomings in terms of the accuracy of anomaly detection, the speed of notification, and the efficiency of predictive analysis using historical data, thus requiring more advanced technology.

[0279] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0280] In this invention, the server includes means for receiving biological information measured within the body via wireless communication, an analysis device for analyzing the received biological information and detecting abnormalities, and means for performing abnormality detection using a generated knowledge processing model. This enables real-time, highly accurate abnormality detection, rapid notification, and the provision of health advice through predictive analysis.

[0281] "Biometric information measured within the body" refers to data on health status obtained using sensors inside the body, such as heart rate, body temperature, and blood components.

[0282] "Means of receiving via wireless communication" refers to a function for transmitting collected biometric information to a server via wireless technology.

[0283] The "analysis device" is a computer system used to process the received biological information and detect abnormalities.

[0284] The "means for executing anomaly detection using the generated knowledge processing model" is a method for analyzing data using a generation AI model to find abnormal patterns.

[0285] The "analysis device for detecting abnormalities" is a device for analyzing biological information and identifying changes different from normal.

[0286] The "means for displaying the analysis result on the user's information terminal" is a method for presenting the analyzed result to the information terminal so that the user can confirm it.

[0287] The "means for performing predictive analysis and generating health advice" is a function for comparing past data with the current situation and using machine learning to generate proposals regarding future health.

[0288] The "means for transmitting the health status report to the user information terminal" is a method for transferring the generated health report to the information terminal owned by the user.

[0289] This invention is a healthcare system that uses microcapsules drunk by the user before going to bed to monitor the biological information in the body in real time. The microcapsules are built-in with sensors for measuring heart rate, body temperature, blood components, etc., and these data are transmitted to the server via wireless communication.

[0290] The server processes the received biological information using a dedicated analysis device. A generation AI model using Python and TensorFlow is used for the analysis to detect data abnormalities with high accuracy. For example, the server always executes anomaly detection by sending the following prompt sentence to the generation AI model: "Please analyze whether there is any abnormality in the user's heart rate data."

[0291] If an abnormality is detected, the server will promptly provide information to the medical institution or relevant personnel. Specifically, it will send detailed information, including analysis results, via email or SMS. The server will also send notifications to the user's smartphone or wearable device so that the user can immediately check for the abnormality. These notifications may include messages such as, "Your body temperature is outside the normal range. Please check the details."

[0292] Furthermore, the server's AI agent performs predictive analysis and provides users with specific health advice. It compares past and current data to derive suggestions for improving health. The results of this analysis are sent to the user's information terminal as a health status report. An example of specific advice is generated, such as, "Based on recent data analysis, we recommend light exercise every day to reduce stress."

[0293] The terminal ultimately presents the user with a health status report generated based on this information, thereby enabling improved health management in daily life. In this way, the present invention provides an advanced system that meets the need for personal health management in modern society.

[0294] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0295] Step 1:

[0296] The user swallows a microcapsule.

[0297] Input: The action of taking a capsule.

[0298] Output: Measurement of biological information by sensors within the body begins.

[0299] Specifically, sensors inside the capsule continuously collect biometric information such as heart rate, body temperature, and blood components.

[0300] Step 2:

[0301] The server receives biometric information wirelessly.

[0302] Input: Biometric information sent from the sensor.

[0303] Output: The received biometric information is stored in the server.

[0304] The biometric information is sent to the server via secure wireless communication, and the server records this information in a database protected by the latest security protocol.

[0305] Step 3:

[0306] Perform data analysis using the generative AI model in the server.

[0307] Input: Biometric information stored in the database.

[0308] Output: Analysis results regarding the presence or absence of anomalies.

[0309] Using Python and TensorFlow, the generative AI model executes the prompt sentence "Please analyze whether there are any anomalies in the heart rate data" to find outliers.

[0310] Step 4:

[0311] The server sends a notification when an anomaly is detected.

[0312] Input: Anomaly information detected by AI analysis.

[0313] Output: Notification to medical institutions and users.

[0314] The server sends a notification containing the details of the anomaly to medical institutions via email or SMS, and also sends push notifications to the user's smartphone or wearable device.

[0315] Step 5:

[0316] The server performs predictive analysis and generates health advice.

[0317] Input: Past biometric data and current analysis results.

[0318] Output: Health advice for the user.

[0319] Based on the data, the AI ​​model performs an analysis with the prompt message, "Create health advice based on the results of predictive analysis," and generates suggestions.

[0320] Step 6:

[0321] The device presents the user with a health report.

[0322] Input: Generated health status report.

[0323] Output: A health report in a format that can be viewed by the user.

[0324] The device will display reports, allowing users to check their health status in real time and use the information to improve their lifestyle.

[0325] (Application Example 1)

[0326] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0327] In modern society, there is a need to understand health conditions in real time and respond immediately when abnormalities occur. However, conventional methods rely on external devices for monitoring biometric data, making real-time response difficult. Furthermore, health conditions may deteriorate without the user noticing. Therefore, there is a need for a system that can continuously monitor the user's health condition and respond quickly to abnormalities.

[0328] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0329] In this invention, the server includes a device for wirelessly receiving biological data measured in the body, a data analysis device for analyzing the received biological data and detecting abnormalities, a device for notifying a medical facility or responsible person when an abnormality is detected, a device for presenting the analysis results to the user's information processing terminal, and a device for the information processing terminal to provide health information to the user in real time. This enables continuous monitoring of the user's health status, rapid detection of abnormalities, and appropriate responses.

[0330] "Biometric data measured inside the body" refers to physiological information acquired in real time by measuring devices placed inside the user's body.

[0331] A "wireless receiving device" is a device that uses wireless communication technology to remotely receive biometric data.

[0332] A "data analysis device" is a device that uses received biometric data to analyze the user's health status and determine whether there are any abnormalities.

[0333] A "device that notifies when an abnormality is detected" is a device that, based on the results of biometric data analysis, notifies relevant organizations and users when it is determined that there is a health abnormality.

[0334] A "user's information processing terminal" refers to a device, such as a smartphone or tablet, that a user uses to receive and verify information.

[0335] A "device that presents analysis results" is a device that displays the results of the analysis of biometric data to the user.

[0336] A "device that provides health information in real time" is a device that provides information immediately so that users can quickly understand their current health status.

[0337] The system that realizes this invention consists of multiple hardware and software components. The server wirelessly acquires data from microcapsules placed inside the body in order to receive biometric data. The microcapsules are equipped with sensors that measure the user's physiological information, such as heart rate, body temperature, and blood components.

[0338] The server can analyze the received biometric data using a data analysis device to detect anomalies. This analysis device compares past biometric data with data received in real time and executes an algorithm to identify anomalies. This algorithm incorporates a generative AI model, enabling advanced analysis.

[0339] If an anomaly is detected, the server notifies the medical facility and responsible party of the details of the anomaly. Appropriate communication protocols are used for this process. Furthermore, the analysis results are immediately transmitted to the user's information processing terminal, allowing the user to monitor their health status in real time.

[0340] On the user's information processing terminal, the analysis results are presented visually or audibly. The information processing terminal can take the form of a smartphone or tablet, allowing users to access health information in their daily lives. For example, if there are no abnormalities, the user is notified accordingly; if abnormalities are found, specific health advice is provided by the AI ​​model. Prompt messages can include instructions such as, "Your body temperature is high, so please drink plenty of fluids."

[0341] This invention allows users to continuously monitor their health status and take immediate action when an abnormality is detected, thereby streamlining health management in daily life.

[0342] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0343] Step 1:

[0344] The server wirelessly receives biometric data transmitted from the microcapsules. Specifically, it uses a wireless module to capture the signal and stores this signal as data in the server's memory. The input is the wireless signal from the microcapsule, and the output is the biometric data stored on the server side.

[0345] Step 2:

[0346] The server analyzes the received biometric data using an analysis device. Here, the current data is evaluated by comparing it with previously stored data. The input is the biometric information data acquired in step 1, and the output is the analysis result, i.e., whether or not there is an abnormality. Specifically, data analysis is performed by a generative AI model incorporating an AI agent.

[0347] Step 3:

[0348] If the server detects an anomaly, it activates the notification system. This includes notifying medical facilities, personnel, and users' information processing terminals of the details of the anomaly. The input is the anomaly information detected in step 2, and the output is the notified anomaly information. Specifically, the server uses push notifications and email to quickly disseminate information to relevant parties.

[0349] Step 4:

[0350] The user's information processing terminal receives analysis results and anomaly notifications transmitted from the server. The input is the information notified in step 3, and the output is the confirmed information received by the user visually or audibly. Specifically, the terminal displays the notification content on its screen and provides the user with anomaly information and health advice through voice guidance.

[0351] Step 5:

[0352] The user checks their health status based on the received information and takes action as needed. The input is the analysis results and health advice received in step 4, and the output is the specific actions the user will take. These specific actions might include drinking water or consulting a doctor to maintain their health.

[0353] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0354] This invention combines an emotional engine with a healthcare system that uses microcapsules ingested by the user before bedtime. This system recognizes not only biometric data but also the user's emotional state, providing a comprehensive analysis of their health status and personalized health advice.

[0355] This system first collects biometric data from within the body using sensors inside a capsule. The data measured includes heart rate, body temperature, and other physiological parameters. Once the user ingests the capsule, continuous data collection within the body begins.

[0356] The collected data is transmitted wirelessly to a server. The server receives and stores the encrypted data, and then passes it on to the AI ​​agent and emotion engine.

[0357] The AI ​​agent analyzes biometric data and attempts to detect anomalies. Predictive analytics are also performed during this analysis to assess the user's health risks. Meanwhile, the emotion engine infers the user's emotional state based on the collected data. For example, it can estimate stress levels and happiness levels from heart rate fluctuations and body temperature changes. These estimation results are incorporated into the health report.

[0358] If an anomaly is detected, or if a specific emotional state persists, the server will promptly notify a healthcare provider or relevant personnel. Simultaneously, the server will send a notification to the user's device, allowing the user to immediately access the information.

[0359] The health report is an overall health assessment that includes emotional state and is provided to the user via the device. This report includes lifestyle improvement advice based on the user's emotional state, as well as information on the correlation between emotions and health status.

[0360] For example, if a user's heart rate is abnormally high and the emotional engine recognizes a high-stress state, the server immediately notifies the attending physician. Furthermore, relaxation techniques for stress management are recommended on the user's smartphone. This system enables comprehensive health support from both an emotional and physical perspective.

[0361] The following describes the processing flow.

[0362] Step 1:

[0363] Users ingest microcapsules before going to sleep. These capsules contain sensors that measure biometric data such as heart rate and body temperature.

[0364] Step 2:

[0365] Sensors inside the capsule begin to continuously collect biometric data within the body. The data is updated regularly, and health status is monitored in real time.

[0366] Step 3:

[0367] The collected biometric data is transmitted to a server via wireless communication. This communication is encrypted to ensure data security.

[0368] Step 4:

[0369] The server records the received data in a database and prepares it for analysis. At the same time, it sends the data to the AI ​​agent and emotion engine.

[0370] Step 5:

[0371] The AI ​​agent analyzes biometric data and attempts to identify anomalies. It compares this data with past data and uses predictive analytics to assess future health risks.

[0372] Step 6:

[0373] The emotion engine analyzes fluctuations in heart rate and body temperature from biometric data to estimate the user's emotional state. For example, a high heart rate may indicate a state of stress.

[0374] Step 7:

[0375] If a user's health risk is determined to be high, or if a specific emotional state is recognized, the server will notify a healthcare provider or relevant personnel. This notification is made electronically, enabling a rapid response.

[0376] Step 8:

[0377] Simultaneously, the server sends a notification to the user's terminal, providing real-time alerts. Users can check the notification on their smartphone or wearable device.

[0378] Step 9:

[0379] Based on the analysis results from the AI ​​agent and emotion engine, a detailed health report is generated. This report includes an overall assessment of health status, an estimated emotional state, and personalized health advice.

[0380] Step 10:

[0381] The device displays a generated health report to the user. The report details suggestions and points to note for improving lifestyle habits based on the user's emotional state. The user can use this information to adjust their lifestyle.

[0382] (Example 2)

[0383] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0384] Traditional healthcare systems assessed health status by analyzing only the user's biometric information, making it difficult to provide comprehensive health support that considered the user's emotional state and stress levels. Furthermore, the inability to detect anomalies in real time or track emotional states could lead to delays in situations requiring rapid response.

[0385] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0386] In this invention, the server includes means for wirelessly receiving biometric information, information analysis means for analyzing the received biometric information and detecting anomalies, and emotion estimation means for inferring the user's emotional state based on the analyzed biometric information. This makes it possible to comprehensively evaluate the user's biometric information and emotional state, detect anomalies in real time, and provide necessary notifications and advice.

[0387] "Biometric information measured within the body" refers to health-related physiological indicators, such as heart rate and body temperature, that are continuously acquired by sensors placed inside the user's body.

[0388] "Means of receiving wirelessly" refers to communication technologies that transmit biometric information to external devices using Bluetooth, Wi-Fi, etc.

[0389] "Information analysis means" refers to algorithms and programs used to analyze received biological information and perform abnormal value detection and predictive analysis.

[0390] "Emotion estimation methods" refer to technologies and processes that estimate a user's emotional state and stress level based on the results of biometric data analysis.

[0391] A "notification method" refers to a system that informs medical institutions or relevant personnel of the situation when an abnormality or a specific emotional state is detected.

[0392] "User's device" refers to an information terminal such as a smartphone or tablet owned by the user, and is a device used to display health status reports and notifications.

[0393] A "health status report" is a report that summarizes the analysis results, including the user's biometric information and emotional state, and is a document that provides health advice to the user.

[0394] This invention is a unique healthcare system that uses microcapsules ingested by the user before going to sleep. By ingesting the microcapsules, the user's body continuously collects biological information through sensors. The capsules contain small sensors and communication modules that collect data such as heart rate and body temperature. This data is transmitted wirelessly from the capsule to a server. Wireless communication technologies used in this system include Bluetooth and Wi-Fi.

[0395] The server encrypts the received biometric information and stores it in a database. Next, it processes this data using information analysis tools, and an AI model performs anomaly detection and predictive analysis. The AI ​​model compares historical data with real-time data to assess the user's health risk.

[0396] Simultaneously, the emotion estimation system predicts the user's emotional state based on heart rate fluctuations and changes in body temperature. This process utilizes an emotion engine to predict stress levels and happiness levels. This allows for a comprehensive assessment of the user's health status.

[0397] If an abnormality or a specific emotional state is detected, the server immediately notifies the attending physician or medical institution. This notification is often sent via email or a dedicated application. The server also sends a health status report to the user's device, providing the user with analysis results and advice for lifestyle improvements.

[0398] As a concrete example, consider a scenario where a user ingests a microcapsule and the system detects a high-stress state. In this case, the server quickly notifies the attending physician, and the user's terminal recommends relaxation techniques such as "take five minutes of deep breathing." An example of a prompt message might be, "Use the data collected by the microcapsule to evaluate the user's emotional state and generate specific advice for stress management." This invention allows users to receive comprehensive support from both emotional and physical perspectives.

[0399] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0400] Step 1:

[0401] When a user ingests a microcapsule, sensors placed inside the body collect biometric information such as heart rate and body temperature in real time. The input is the user's biometric information, and the output is a backend system for wireless data transmission. Specifically, the microcapsule's sensors detect the biometric information and prepare the data for transmission by packetizing it via a built-in wireless communication module.

[0402] Step 2:

[0403] The transmitted biometric information reaches the server, where it is encrypted and received. The input is encrypted biometric information transmitted from the microcapsule, and the output is a secure database for temporary storage. The server then decrypts the received data and performs the specific actions of storing it in the database for appropriate storage.

[0404] Step 3:

[0405] Biometric information stored on the server is passed to an information analysis system, where an AI model performs anomaly detection and predictive analysis. The input is the biometric information stored on the server, and the output is the analysis results, such as the identification of anomalies. Specifically, the AI ​​model analyzes the biometric information and detects anomalies in real time while comparing it with past data.

[0406] Step 4:

[0407] Based on the analysis results, the server uses emotion estimation tools to predict the emotional state. The input is the analyzed biometric information, and the output is the user's emotional state and stress level. The emotion engine uses fluctuations in heart rate and changes in body temperature to estimate emotions and perform specific actions to identify the user's emotional state.

[0408] Step 5:

[0409] If the server detects an abnormality or a specific emotional state, it immediately notifies healthcare providers and relevant personnel, and also sends a notification to the user's terminal. The input is the result of analysis and estimation, and the output is the notification content. The server uses communication means to perform specific actions to inform healthcare professionals and users of the situation.

[0410] Step 6:

[0411] Ultimately, the server generates a health status report and sends it to the user's device. The inputs are the analysis results and emotional state, and the output is the health status report. The server performs a comprehensive health assessment, generates a report, and delivers it to the user's device.

[0412] (Application Example 2)

[0413] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart glasses 214 as the "terminal".

[0414] For elderly individuals and those with specific health concerns, there is a need for a system that can comprehensively understand fluctuations in physiological parameters within the body and emotional states, and immediately assess their health status. However, conventional healthcare systems have challenges in assessing health, including emotional states, and thus hindering rapid care responses.

[0415] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0416] In this invention, the server includes means for wirelessly receiving physiological parameters measured within the body, information analysis means for analyzing the received physiological parameters and detecting abnormal values, and means for estimating the user's emotional state and incorporating that information into the health status assessment. This enables a comprehensive health assessment that also takes emotional state into consideration.

[0417] "Physiological parameters" are numerical data related to the body, such as heart rate and body temperature, that are measured within the body.

[0418] "Means of receiving wirelessly" refers to a system for remotely acquiring data using wireless communication technologies such as Bluetooth or Wi-Fi.

[0419] "Information analysis means" refers to processes and equipment used to detect and analyze numerical anomalies based on acquired data.

[0420] An "abnormal value" is a physiological parameter value that falls outside the normal range and may indicate a health problem.

[0421] "Means for reporting to a medical institution or responsible organization" refers to communication methods for quickly informing medical personnel or management organizations when abnormal values ​​are detected.

[0422] "Means for displaying analysis results on information devices" refers to screen display functions that visually show analysis results on devices such as smartphones and computers.

[0423] "Emotional state" refers to an individual's emotional state, such as stress or happiness, estimated from fluctuations in acquired physiological parameters.

[0424] "Health assessment" is a process of diagnosing and analyzing an individual's overall health based on information about physiological parameters and emotional state.

[0425] This system provides users with wearable or ingestible sensors that continuously measure physiological parameters within the body. The measured data is transmitted to a server using wireless communication technologies such as Bluetooth or Wi-Fi. The server performs real-time analysis of the data using programming languages ​​such as Python. Machine learning libraries such as TensorFlow and PyTorch are used as information analysis tools to efficiently detect anomalies in the obtained data in order to detect abnormal values ​​of physiological parameters.

[0426] The server also utilizes AI agents and an emotion engine to estimate emotional states. This emotional state estimation employs sophisticated algorithms based on heart rate and body temperature fluctuations to understand the emotional state of each individual user. This enables a comprehensive health assessment of the user.

[0427] The analysis results and estimated emotional state are transmitted in real time to the user's device, specifically a smartphone or tablet. This device is designed to visually present information, making it easy for the user to understand their own health status. In particular, if an abnormality is detected, the system immediately notifies medical institutions or relevant organizations.

[0428] As a concrete example, consider a scenario where an abnormal heart rate is detected in an elderly person while they are sleeping, and the emotional engine recognizes a high-stress state. The server can immediately issue a warning and send a notification to the caregiver recommending relaxation techniques.

[0429] An example of a prompt message is, "Write code to analyze the user's heart rate and body temperature and estimate their stress level." This enables advanced health support utilizing generative AI models.

[0430] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0431] Step 1:

[0432] The sensor measures physiological parameters such as heart rate and body temperature inside the user's body. The input is biometric data acquired in real time. This data is temporarily stored within the sensor.

[0433] Step 2:

[0434] The sensor wirelessly transmits physiological parameters to the server via Bluetooth or Wi-Fi. The server receives this data as input and stores it in a database. The output is temporary data storage on the server.

[0435] Step 3:

[0436] The server initiates data analysis using a Python program. Input consists of historical data and newly received biometric data. An AI agent and machine learning algorithms (e.g., TensorFlow) are used to detect anomalies in the data. The output is the analysis result regarding the presence or absence of anomalies.

[0437] Step 4:

[0438] The server simultaneously uses an emotion engine to estimate the user's emotional state. The input consists of data on heart rate and body temperature fluctuations. Through data processing, it generates and outputs emotional indicators such as stress levels and feelings of well-being.

[0439] Step 5:

[0440] The server wirelessly transmits the analysis results and estimated emotional state to the user's terminal. The input is the enriched data obtained through the analysis process. The terminal receives this data and outputs it by visually displaying it on the screen.

[0441] Step 6:

[0442] When an anomaly is detected, the server immediately sends a notification to the healthcare institution or responsible organization. The input is the anomaly detection result. A notification message is generated via the communication protocol and output to the necessary location.

[0443] Step 7:

[0444] Based on data received by the user's device, the system suggests appropriate health advice and relaxation techniques. Input consists of analysis results and emotion estimation results. The output is displayed in a user-friendly format via the device's GUI.

[0445] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0446] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0447] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0448] [Third Embodiment]

[0449] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0450] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0451] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0452] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0453] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0454] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0455] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0456] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0457] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0458] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0459] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0460] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0461] This invention relates to a healthcare system that uses microcapsules taken by the user before going to bed. This system monitors biometric data in real time and promptly notifies the user if any abnormalities are detected.

[0462] This system begins by collecting biometric data from within the body using sensors inside a capsule. The capsule is designed to measure information such as heart rate, body temperature, and blood components.

[0463] When a user swallows a capsule, data is continuously collected within their body. This data is transmitted wirelessly to a server.

[0464] The server stores the received biometric data in a secure database. This data is then analyzed by an AI agent. The AI ​​agent can retrieve and analyze the data at any time to attempt to detect anomalies.

[0465] If an anomaly is detected, the server will immediately begin taking action. Specifically, it will notify the medical institution or relevant personnel of the nature of the anomaly. The server will also send notifications to the user's smartphone or wearable device so that the user can immediately check the anomaly.

[0466] Subsequently, the AI ​​agent performs predictive analysis based on the user's past data and provides specific health advice. Finally, the device presents the user with a generated health report. This report includes a real-time overview of their health status, a comparison with past data, and suggestions for improving their lifestyle.

[0467] This allows users to efficiently manage their health while continuing their daily lives.

[0468] The following describes the processing flow.

[0469] Step 1:

[0470] Users take microcapsules into their bodies before going to bed. Since these capsules measure internal bodily data, it is important to take them at the appropriate time.

[0471] Step 2:

[0472] The sensors inside the capsule begin collecting biometric data within the body. Important data such as heart rate, body temperature, and blood components are continuously recorded and updated at regular intervals.

[0473] Step 3:

[0474] The data collected by the capsule is transmitted to a server via wireless communication. The data is encrypted to ensure privacy and security.

[0475] Step 4:

[0476] The server stores the received data and saves it in a database. At the same time, it provides this data to the AI ​​agent to prepare it for analysis.

[0477] Step 5:

[0478] The AI ​​agent analyzes biometric data provided by the server. It attempts to identify patterns and anomalies within the data using anomaly detection algorithms.

[0479] Step 6:

[0480] If an anomaly is detected, the server will immediately notify the medical institution or relevant personnel of the details. This notification will be sent via email or a dedicated communication application.

[0481] Step 7:

[0482] At the same time, the server sends an anomaly notification to the user's device. The notification is sent in real time, allowing the user to check it on their smartphone or wearable device.

[0483] Step 8:

[0484] The AI ​​agent further analyzes health trends using historical data to predict the user's health risks. This analysis is then generated as a detailed health report.

[0485] Step 9:

[0486] The device displays a health report sent from the server to the user. The report includes suggestions for lifestyle improvements and points to be aware of.

[0487] Step 10:

[0488] Users can review the report, understand their own health status, and use the feedback to improve their daily lives.

[0489] (Example 1)

[0490] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0491] In recent years, with the increasing demand for personal health management, there is a growing need for systems that can monitor biological information in the body in real time and quickly detect and notify of abnormalities. However, existing systems have shortcomings in terms of the accuracy of anomaly detection, the speed of notification, and the efficiency of predictive analysis using historical data, thus requiring more advanced technology.

[0492] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0493] In this invention, the server includes means for receiving biological information measured within the body via wireless communication, an analysis device for analyzing the received biological information and detecting abnormalities, and means for performing abnormality detection using a generated knowledge processing model. This enables real-time, highly accurate abnormality detection, rapid notification, and the provision of health advice through predictive analysis.

[0494] "Biometric information measured within the body" refers to data on health status obtained using sensors inside the body, such as heart rate, body temperature, and blood components.

[0495] "Means of receiving via wireless communication" refers to a function for transmitting collected biometric information to a server via wireless technology.

[0496] An "analysis device" is a computer system used to process received biological information and detect abnormalities.

[0497] "Means of performing anomaly detection using a generated knowledge processing model" refers to a method of analyzing data using a generative AI model to find anomalous patterns.

[0498] An "analysis device for detecting abnormalities" is a device that analyzes biological information and identifies changes that are different from the normal state.

[0499] "Means for displaying analysis results on the user's information terminal" refers to a method of presenting the results after analysis on the information terminal so that the user can confirm them.

[0500] "A means of performing predictive analytics and generating health advice" refers to a function that compares past data with the current situation and uses machine learning to create suggestions regarding future health.

[0501] "Means for sending health status reports to user information terminals" refers to methods for transferring generated health reports to information terminals owned by the user.

[0502] This invention is a healthcare system that uses microcapsules taken by the user before going to bed to monitor biological information in the body in real time. The microcapsules contain sensors that measure heart rate, body temperature, blood components, etc., and transmit this data to a server via wireless communication.

[0503] The server processes the received biometric information using a dedicated analysis device. A generative AI model using Python and TensorFlow is employed for analysis, enabling high-precision detection of data anomalies. For example, the server constantly sends the following prompt to the generative AI model to perform anomaly detection: "Please analyze the user's heart rate data for any anomalies."

[0504] If an abnormality is detected, the server will promptly provide information to the medical institution or relevant personnel. Specifically, it will send detailed information, including analysis results, via email or SMS. The server will also send notifications to the user's smartphone or wearable device so that the user can immediately check for the abnormality. These notifications may include messages such as, "Your body temperature is outside the normal range. Please check the details."

[0505] Furthermore, the server's AI agent performs predictive analysis and provides users with specific health advice. It compares past and current data to derive suggestions for improving health. The results of this analysis are sent to the user's information terminal as a health status report. An example of specific advice is generated, such as, "Based on recent data analysis, we recommend light exercise every day to reduce stress."

[0506] The terminal ultimately presents the user with a health status report generated based on this information, thereby enabling improved health management in daily life. In this way, the present invention provides an advanced system that meets the need for personal health management in modern society.

[0507] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0508] Step 1:

[0509] The user swallows a microcapsule.

[0510] Input: The action of taking a capsule.

[0511] Output: Measurement of biological information by sensors within the body begins.

[0512] Specifically, sensors inside the capsule continuously collect biometric information such as heart rate, body temperature, and blood components.

[0513] Step 2:

[0514] The server receives biometric information wirelessly.

[0515] Input: Biometric information transmitted from the sensor.

[0516] Output: The received biometric information is stored on the server.

[0517] Biometric information is sent to a server via secure wireless communication, and the server records this information in a database protected by the latest security protocols.

[0518] Step 3:

[0519] Data analysis is performed using a generated AI model on the server.

[0520] Input: Biometric information stored in the database.

[0521] Output: Analysis results regarding the presence or absence of abnormalities.

[0522] Using Python and TensorFlow, the generated AI model executes the prompt message "Analyze the heart rate data for any abnormalities" and searches for outliers.

[0523] Step 4:

[0524] The server will send a notification when it detects an anomaly.

[0525] Input: Anomaly information detected by AI analysis.

[0526] Output: Notifications to medical institutions and users.

[0527] The server sends notifications containing details of the anomaly to medical institutions via email or SMS, and also sends push notifications to users' smartphones and wearable devices.

[0528] Step 5:

[0529] The server performs predictive analysis and generates health advice.

[0530] Input: Past biometric data and current analysis results.

[0531] Output: Health advice for the user.

[0532] Based on the data, the AI ​​model performs an analysis with the prompt message, "Create health advice based on the results of predictive analysis," and generates suggestions.

[0533] Step 6:

[0534] The device presents the user with a health report.

[0535] Input: Generated health status report.

[0536] Output: A health report in a format that can be viewed by the user.

[0537] The device will display reports, allowing users to check their health status in real time and use the information to improve their lifestyle.

[0538] (Application Example 1)

[0539] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0540] In modern society, there is a need to understand health conditions in real time and respond immediately when abnormalities occur. However, conventional methods rely on external devices for monitoring biometric data, making real-time response difficult. Furthermore, health conditions may deteriorate without the user noticing. Therefore, there is a need for a system that can continuously monitor the user's health condition and respond quickly to abnormalities.

[0541] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0542] In this invention, the server includes a device for wirelessly receiving biological data measured in the body, a data analysis device for analyzing the received biological data and detecting abnormalities, a device for notifying a medical facility or responsible person when an abnormality is detected, a device for presenting the analysis results to the user's information processing terminal, and a device for the information processing terminal to provide health information to the user in real time. This enables continuous monitoring of the user's health status, rapid detection of abnormalities, and appropriate responses.

[0543] "Biometric data measured inside the body" refers to physiological information acquired in real time by measuring devices placed inside the user's body.

[0544] A "wireless receiving device" is a device that uses wireless communication technology to remotely receive biometric data.

[0545] A "data analysis device" is a device that uses received biometric data to analyze the user's health status and determine whether there are any abnormalities.

[0546] A "device that notifies when an abnormality is detected" is a device that, based on the results of biometric data analysis, notifies relevant organizations and users when it is determined that there is a health abnormality.

[0547] A "user's information processing terminal" refers to a device, such as a smartphone or tablet, that a user uses to receive and verify information.

[0548] A "device that presents analysis results" is a device that displays the results of the analysis of biometric data to the user.

[0549] A "device that provides health information in real time" is a device that provides information immediately so that users can quickly understand their current health status.

[0550] The system that realizes this invention consists of multiple hardware and software components. The server wirelessly acquires data from microcapsules placed inside the body in order to receive biometric data. The microcapsules are equipped with sensors that measure the user's physiological information, such as heart rate, body temperature, and blood components.

[0551] The server can analyze the received biometric data using a data analysis device to detect anomalies. This analysis device compares past biometric data with data received in real time and executes an algorithm to identify anomalies. This algorithm incorporates a generative AI model, enabling advanced analysis.

[0552] If an anomaly is detected, the server notifies the medical facility and responsible party of the details of the anomaly. Appropriate communication protocols are used for this process. Furthermore, the analysis results are immediately transmitted to the user's information processing terminal, allowing the user to monitor their health status in real time.

[0553] On the user's information processing terminal, the analysis results are presented visually or audibly. The information processing terminal can take the form of a smartphone or tablet, allowing users to access health information in their daily lives. For example, if there are no abnormalities, the user is notified accordingly; if abnormalities are found, specific health advice is provided by the AI ​​model. Prompt messages can include instructions such as, "Your body temperature is high, so please drink plenty of fluids."

[0554] This invention allows users to continuously monitor their health status and take immediate action when an abnormality is detected, thereby streamlining health management in daily life.

[0555] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0556] Step 1:

[0557] The server wirelessly receives biometric data transmitted from the microcapsules. Specifically, it uses a wireless module to capture the signal and stores this signal as data in the server's memory. The input is the wireless signal from the microcapsule, and the output is the biometric data stored on the server side.

[0558] Step 2:

[0559] The server analyzes the received biometric data using an analysis device. Here, the current data is evaluated by comparing it with previously stored data. The input is the biometric information data acquired in step 1, and the output is the analysis result, i.e., whether or not there is an abnormality. Specifically, data analysis is performed by a generative AI model incorporating an AI agent.

[0560] Step 3:

[0561] If the server detects an anomaly, it activates the notification system. This includes notifying medical facilities, personnel, and users' information processing terminals of the details of the anomaly. The input is the anomaly information detected in step 2, and the output is the notified anomaly information. Specifically, the server uses push notifications and email to quickly disseminate information to relevant parties.

[0562] Step 4:

[0563] The user's information processing terminal receives analysis results and anomaly notifications transmitted from the server. The input is the information notified in step 3, and the output is the confirmed information received by the user visually or audibly. Specifically, the terminal displays the notification content on its screen and provides the user with anomaly information and health advice through voice guidance.

[0564] Step 5:

[0565] The user checks their health status based on the received information and takes action as needed. The input is the analysis results and health advice received in step 4, and the output is the specific actions the user will take. These specific actions might include drinking water or consulting a doctor to maintain their health.

[0566] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0567] This invention combines an emotional engine with a healthcare system that uses microcapsules ingested by the user before bedtime. This system recognizes not only biometric data but also the user's emotional state, providing a comprehensive analysis of their health status and personalized health advice.

[0568] This system first collects biometric data from within the body using sensors inside a capsule. The data measured includes heart rate, body temperature, and other physiological parameters. Once the user ingests the capsule, continuous data collection within the body begins.

[0569] The collected data is transmitted wirelessly to a server. The server receives and stores the encrypted data, and then passes it on to the AI ​​agent and emotion engine.

[0570] The AI ​​agent analyzes biometric data and attempts to detect anomalies. Predictive analytics are also performed during this analysis to assess the user's health risks. Meanwhile, the emotion engine infers the user's emotional state based on the collected data. For example, it can estimate stress levels and happiness levels from heart rate fluctuations and body temperature changes. These estimation results are incorporated into the health report.

[0571] If an anomaly is detected, or if a specific emotional state persists, the server will promptly notify a healthcare provider or relevant personnel. Simultaneously, the server will send a notification to the user's device, allowing the user to immediately access the information.

[0572] The health report is an overall health assessment that includes emotional state and is provided to the user via the device. This report includes lifestyle improvement advice based on the user's emotional state, as well as information on the correlation between emotions and health status.

[0573] For example, if a user's heart rate is abnormally high and the emotional engine recognizes a high-stress state, the server immediately notifies the attending physician. Furthermore, relaxation techniques for stress management are recommended on the user's smartphone. This system enables comprehensive health support from both an emotional and physical perspective.

[0574] The following describes the processing flow.

[0575] Step 1:

[0576] Users ingest microcapsules before going to sleep. These capsules contain sensors that measure biometric data such as heart rate and body temperature.

[0577] Step 2:

[0578] Sensors inside the capsule begin to continuously collect biometric data within the body. The data is updated regularly, and health status is monitored in real time.

[0579] Step 3:

[0580] The collected biometric data is transmitted to a server via wireless communication. This communication is encrypted to ensure data security.

[0581] Step 4:

[0582] The server records the received data in a database and prepares it for analysis. At the same time, it sends the data to the AI ​​agent and emotion engine.

[0583] Step 5:

[0584] The AI ​​agent analyzes biometric data and attempts to identify anomalies. It compares this data with past data and uses predictive analytics to assess future health risks.

[0585] Step 6:

[0586] The emotion engine analyzes fluctuations in heart rate and body temperature from biometric data to estimate the user's emotional state. For example, a high heart rate may indicate a state of stress.

[0587] Step 7:

[0588] If a user's health risk is determined to be high, or if a specific emotional state is recognized, the server will notify a healthcare provider or relevant personnel. This notification is made electronically, enabling a rapid response.

[0589] Step 8:

[0590] Simultaneously, the server sends a notification to the user's terminal, providing real-time alerts. Users can check the notification on their smartphone or wearable device.

[0591] Step 9:

[0592] Based on the analysis results from the AI ​​agent and emotion engine, a detailed health report is generated. This report includes an overall assessment of health status, an estimated emotional state, and personalized health advice.

[0593] Step 10:

[0594] The device displays a generated health report to the user. The report details suggestions and points to note for improving lifestyle habits based on the user's emotional state. The user can use this information to adjust their lifestyle.

[0595] (Example 2)

[0596] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0597] Traditional healthcare systems assessed health status by analyzing only the user's biometric information, making it difficult to provide comprehensive health support that considered the user's emotional state and stress levels. Furthermore, the inability to detect anomalies in real time or track emotional states could lead to delays in situations requiring rapid response.

[0598] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0599] In this invention, the server includes means for wirelessly receiving biometric information, information analysis means for analyzing the received biometric information and detecting anomalies, and emotion estimation means for inferring the user's emotional state based on the analyzed biometric information. This makes it possible to comprehensively evaluate the user's biometric information and emotional state, detect anomalies in real time, and provide necessary notifications and advice.

[0600] "Biometric information measured within the body" refers to health-related physiological indicators, such as heart rate and body temperature, that are continuously acquired by sensors placed inside the user's body.

[0601] "Means of receiving wirelessly" refers to communication technologies that transmit biometric information to external devices using Bluetooth, Wi-Fi, etc.

[0602] "Information analysis means" refers to algorithms and programs used to analyze received biological information and perform abnormal value detection and predictive analysis.

[0603] "Emotion estimation methods" refer to technologies and processes that estimate a user's emotional state and stress level based on the results of biometric data analysis.

[0604] A "notification method" refers to a system that informs medical institutions or relevant personnel of the situation when an abnormality or a specific emotional state is detected.

[0605] "User's device" refers to an information terminal such as a smartphone or tablet owned by the user, and is a device used to display health status reports and notifications.

[0606] A "health status report" is a report that summarizes the analysis results, including the user's biometric information and emotional state, and is a document that provides health advice to the user.

[0607] This invention is a unique healthcare system that uses microcapsules ingested by the user before going to sleep. By ingesting the microcapsules, the user's body continuously collects biological information through sensors. The capsules contain small sensors and communication modules that collect data such as heart rate and body temperature. This data is transmitted wirelessly from the capsule to a server. Wireless communication technologies used in this system include Bluetooth and Wi-Fi.

[0608] The server encrypts the received biometric information and stores it in a database. Next, it processes this data using information analysis tools, and an AI model performs anomaly detection and predictive analysis. The AI ​​model compares historical data with real-time data to assess the user's health risk.

[0609] Simultaneously, the emotion estimation system predicts the user's emotional state based on heart rate fluctuations and changes in body temperature. This process utilizes an emotion engine to predict stress levels and happiness levels. This allows for a comprehensive assessment of the user's health status.

[0610] If an abnormality or a specific emotional state is detected, the server immediately notifies the attending physician or medical institution. This notification is often sent via email or a dedicated application. The server also sends a health status report to the user's device, providing the user with analysis results and advice for lifestyle improvements.

[0611] As a concrete example, consider a scenario where a user ingests a microcapsule and the system detects a high-stress state. In this case, the server quickly notifies the attending physician, and the user's terminal recommends relaxation techniques such as "take five minutes of deep breathing." An example of a prompt message might be, "Use the data collected by the microcapsule to evaluate the user's emotional state and generate specific advice for stress management." This invention allows users to receive comprehensive support from both emotional and physical perspectives.

[0612] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0613] Step 1:

[0614] When a user ingests a microcapsule, sensors placed inside the body collect biometric information such as heart rate and body temperature in real time. The input is the user's biometric information, and the output is a backend system for wireless data transmission. Specifically, the microcapsule's sensors detect the biometric information and prepare the data for transmission by packetizing it via a built-in wireless communication module.

[0615] Step 2:

[0616] The transmitted biometric information reaches the server, where it is encrypted and received. The input is encrypted biometric information transmitted from the microcapsule, and the output is a secure database for temporary storage. The server then decrypts the received data and performs the specific actions of storing it in the database for appropriate storage.

[0617] Step 3:

[0618] Biometric information stored on the server is passed to an information analysis system, where an AI model performs anomaly detection and predictive analysis. The input is the biometric information stored on the server, and the output is the analysis results, such as the identification of anomalies. Specifically, the AI ​​model analyzes the biometric information and detects anomalies in real time while comparing it with past data.

[0619] Step 4:

[0620] Based on the analysis results, the server uses emotion estimation tools to predict the emotional state. The input is the analyzed biometric information, and the output is the user's emotional state and stress level. The emotion engine uses fluctuations in heart rate and changes in body temperature to estimate emotions and perform specific actions to identify the user's emotional state.

[0621] Step 5:

[0622] If the server detects an abnormality or a specific emotional state, it immediately notifies healthcare providers and relevant personnel, and also sends a notification to the user's terminal. The input is the result of analysis and estimation, and the output is the notification content. The server uses communication means to perform specific actions to inform healthcare professionals and users of the situation.

[0623] Step 6:

[0624] Ultimately, the server generates a health status report and sends it to the user's device. The inputs are the analysis results and emotional state, and the output is the health status report. The server performs a comprehensive health assessment, generates a report, and delivers it to the user's device.

[0625] (Application Example 2)

[0626] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0627] For elderly individuals and those with specific health concerns, there is a need for a system that can comprehensively understand fluctuations in physiological parameters within the body and emotional states, and immediately assess their health status. However, conventional healthcare systems have challenges in assessing health, including emotional states, and thus hindering rapid care responses.

[0628] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0629] In this invention, the server includes means for wirelessly receiving physiological parameters measured within the body, information analysis means for analyzing the received physiological parameters and detecting abnormal values, and means for estimating the user's emotional state and incorporating that information into the health status assessment. This enables a comprehensive health assessment that also takes emotional state into consideration.

[0630] "Physiological parameters" are numerical data related to the body, such as heart rate and body temperature, that are measured within the body.

[0631] "Means of receiving wirelessly" refers to a system for remotely acquiring data using wireless communication technologies such as Bluetooth or Wi-Fi.

[0632] "Information analysis means" refers to processes and equipment used to detect and analyze numerical anomalies based on acquired data.

[0633] An "abnormal value" is a physiological parameter value that falls outside the normal range and may indicate a health problem.

[0634] "Means for reporting to a medical institution or responsible organization" refers to communication methods for quickly informing medical personnel or management organizations when abnormal values ​​are detected.

[0635] "Means for displaying analysis results on information devices" refers to screen display functions that visually show analysis results on devices such as smartphones and computers.

[0636] "Emotional state" refers to an individual's emotional state, such as stress or happiness, estimated from fluctuations in acquired physiological parameters.

[0637] "Health assessment" is a process of diagnosing and analyzing an individual's overall health based on information about physiological parameters and emotional state.

[0638] This system provides users with wearable or ingestible sensors that continuously measure physiological parameters within the body. The measured data is transmitted to a server using wireless communication technologies such as Bluetooth or Wi-Fi. The server performs real-time analysis of the data using programming languages ​​such as Python. Machine learning libraries such as TensorFlow and PyTorch are used as information analysis tools to efficiently detect anomalies in the obtained data in order to detect abnormal values ​​of physiological parameters.

[0639] The server also utilizes AI agents and an emotion engine to estimate emotional states. This emotional state estimation employs sophisticated algorithms based on heart rate and body temperature fluctuations to understand the emotional state of each individual user. This enables a comprehensive health assessment of the user.

[0640] The analysis results and estimated emotional state are transmitted in real time to the user's device, specifically a smartphone or tablet. This device is designed to visually present information, making it easy for the user to understand their own health status. In particular, if an abnormality is detected, the system immediately notifies medical institutions or relevant organizations.

[0641] As a concrete example, consider a scenario where an abnormal heart rate is detected in an elderly person while they are sleeping, and the emotional engine recognizes a high-stress state. The server can immediately issue a warning and send a notification to the caregiver recommending relaxation techniques.

[0642] An example of a prompt message is, "Write code to analyze the user's heart rate and body temperature and estimate their stress level." This enables advanced health support utilizing generative AI models.

[0643] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0644] Step 1:

[0645] The sensor measures physiological parameters such as heart rate and body temperature inside the user's body. The input is biometric data acquired in real time. This data is temporarily stored within the sensor.

[0646] Step 2:

[0647] The sensor wirelessly transmits physiological parameters to the server via Bluetooth or Wi-Fi. The server receives this data as input and stores it in a database. The output is temporary data storage on the server.

[0648] Step 3:

[0649] The server initiates data analysis using a Python program. Input consists of historical data and newly received biometric data. An AI agent and machine learning algorithms (e.g., TensorFlow) are used to detect anomalies in the data. The output is the analysis result regarding the presence or absence of anomalies.

[0650] Step 4:

[0651] The server simultaneously uses an emotion engine to estimate the user's emotional state. The input consists of data on heart rate and body temperature fluctuations. Through data processing, it generates and outputs emotional indicators such as stress levels and feelings of well-being.

[0652] Step 5:

[0653] The server wirelessly transmits the analysis results and estimated emotional state to the user's terminal. The input is the enriched data obtained through the analysis process. The terminal receives this data and outputs it by visually displaying it on the screen.

[0654] Step 6:

[0655] When an anomaly is detected, the server immediately sends a notification to the healthcare institution or responsible organization. The input is the anomaly detection result. A notification message is generated via the communication protocol and output to the necessary location.

[0656] Step 7:

[0657] Based on data received by the user's device, the system suggests appropriate health advice and relaxation techniques. Input consists of analysis results and emotion estimation results. The output is displayed in a user-friendly format via the device's GUI.

[0658] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0659] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0660] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0661] [Fourth Embodiment]

[0662] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0663] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0664] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0665] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0666] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0667] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0668] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0669] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0670] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0671] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0672] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0673] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0674] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0675] This invention relates to a healthcare system that uses microcapsules taken by the user before going to bed. This system monitors biometric data in real time and promptly notifies the user if any abnormalities are detected.

[0676] This system begins by collecting biometric data from within the body using sensors inside a capsule. The capsule is designed to measure information such as heart rate, body temperature, and blood components.

[0677] When a user swallows a capsule, data is continuously collected within their body. This data is transmitted wirelessly to a server.

[0678] The server stores the received biometric data in a secure database. This data is then analyzed by an AI agent. The AI ​​agent can retrieve and analyze the data at any time to attempt to detect anomalies.

[0679] If an anomaly is detected, the server will immediately begin taking action. Specifically, it will notify the medical institution or relevant personnel of the nature of the anomaly. The server will also send notifications to the user's smartphone or wearable device so that the user can immediately check the anomaly.

[0680] Subsequently, the AI ​​agent performs predictive analysis based on the user's past data and provides specific health advice. Finally, the device presents the user with a generated health report. This report includes a real-time overview of their health status, a comparison with past data, and suggestions for improving their lifestyle.

[0681] This allows users to efficiently manage their health while continuing their daily lives.

[0682] The following describes the processing flow.

[0683] Step 1:

[0684] Users take microcapsules into their bodies before going to bed. Since these capsules measure internal bodily data, it is important to take them at the appropriate time.

[0685] Step 2:

[0686] The sensors inside the capsule begin collecting biometric data within the body. Important data such as heart rate, body temperature, and blood components are continuously recorded and updated at regular intervals.

[0687] Step 3:

[0688] The data collected by the capsule is transmitted to a server via wireless communication. The data is encrypted to ensure privacy and security.

[0689] Step 4:

[0690] The server stores the received data and saves it in a database. At the same time, it provides this data to the AI ​​agent to prepare it for analysis.

[0691] Step 5:

[0692] The AI ​​agent analyzes biometric data provided by the server. It attempts to identify patterns and anomalies within the data using anomaly detection algorithms.

[0693] Step 6:

[0694] If an anomaly is detected, the server will immediately notify the medical institution or relevant personnel of the details. This notification will be sent via email or a dedicated communication application.

[0695] Step 7:

[0696] At the same time, the server sends an anomaly notification to the user's device. The notification is sent in real time, allowing the user to check it on their smartphone or wearable device.

[0697] Step 8:

[0698] The AI ​​agent further analyzes health trends using historical data to predict the user's health risks. This analysis is then generated as a detailed health report.

[0699] Step 9:

[0700] The device displays a health report sent from the server to the user. The report includes suggestions for lifestyle improvements and points to be aware of.

[0701] Step 10:

[0702] Users can review the report, understand their own health status, and use the feedback to improve their daily lives.

[0703] (Example 1)

[0704] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0705] In recent years, with the increasing demand for personal health management, there is a growing need for systems that can monitor biological information in the body in real time and quickly detect and notify of abnormalities. However, existing systems have shortcomings in terms of the accuracy of anomaly detection, the speed of notification, and the efficiency of predictive analysis using historical data, thus requiring more advanced technology.

[0706] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0707] In this invention, the server includes means for receiving biological information measured within the body via wireless communication, an analysis device for analyzing the received biological information and detecting abnormalities, and means for performing abnormality detection using a generated knowledge processing model. This enables real-time, highly accurate abnormality detection, rapid notification, and the provision of health advice through predictive analysis.

[0708] "Biometric information measured within the body" refers to data on health status obtained using sensors inside the body, such as heart rate, body temperature, and blood components.

[0709] "Means of receiving via wireless communication" refers to a function for transmitting collected biometric information to a server via wireless technology.

[0710] An "analysis device" is a computer system used to process received biological information and detect abnormalities.

[0711] "Means of performing anomaly detection using a generated knowledge processing model" refers to a method of analyzing data using a generative AI model to find anomalous patterns.

[0712] An "analysis device for detecting abnormalities" is a device that analyzes biological information and identifies changes that are different from the normal state.

[0713] "Means for displaying analysis results on the user's information terminal" refers to a method of presenting the results after analysis on the information terminal so that the user can confirm them.

[0714] "A means of performing predictive analytics and generating health advice" refers to a function that compares past data with the current situation and uses machine learning to create suggestions regarding future health.

[0715] "Means for sending health status reports to user information terminals" refers to methods for transferring generated health reports to information terminals owned by the user.

[0716] This invention is a healthcare system that uses microcapsules taken by the user before going to bed to monitor biological information in the body in real time. The microcapsules contain sensors that measure heart rate, body temperature, blood components, etc., and transmit this data to a server via wireless communication.

[0717] The server processes the received biometric information using a dedicated analysis device. A generative AI model using Python and TensorFlow is employed for analysis, enabling high-precision detection of data anomalies. For example, the server constantly sends the following prompt to the generative AI model to perform anomaly detection: "Please analyze the user's heart rate data for any anomalies."

[0718] If an abnormality is detected, the server will promptly provide information to the medical institution or relevant personnel. Specifically, it will send detailed information, including analysis results, via email or SMS. The server will also send notifications to the user's smartphone or wearable device so that the user can immediately check for the abnormality. These notifications may include messages such as, "Your body temperature is outside the normal range. Please check the details."

[0719] Furthermore, the server's AI agent performs predictive analysis and provides users with specific health advice. It compares past and current data to derive suggestions for improving health. The results of this analysis are sent to the user's information terminal as a health status report. An example of specific advice is generated, such as, "Based on recent data analysis, we recommend light exercise every day to reduce stress."

[0720] The terminal ultimately presents the user with a health status report generated based on this information, thereby enabling improved health management in daily life. In this way, the present invention provides an advanced system that meets the need for personal health management in modern society.

[0721] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0722] Step 1:

[0723] The user swallows a microcapsule.

[0724] Input: The action of taking a capsule.

[0725] Output: Measurement of biological information by sensors within the body begins.

[0726] Specifically, sensors inside the capsule continuously collect biometric information such as heart rate, body temperature, and blood components.

[0727] Step 2:

[0728] The server receives biometric information wirelessly.

[0729] Input: Biometric information transmitted from the sensor.

[0730] Output: The received biometric information is stored on the server.

[0731] Biometric information is sent to a server via secure wireless communication, and the server records this information in a database protected by the latest security protocols.

[0732] Step 3:

[0733] Data analysis is performed using a generated AI model on the server.

[0734] Input: Biometric information stored in the database.

[0735] Output: Analysis results regarding the presence or absence of abnormalities.

[0736] Using Python and TensorFlow, the generated AI model executes the prompt message "Analyze the heart rate data for any abnormalities" and searches for outliers.

[0737] Step 4:

[0738] The server will send a notification when it detects an anomaly.

[0739] Input: Anomaly information detected by AI analysis.

[0740] Output: Notifications to medical institutions and users.

[0741] The server sends notifications containing details of the anomaly to medical institutions via email or SMS, and also sends push notifications to users' smartphones and wearable devices.

[0742] Step 5:

[0743] The server performs predictive analysis and generates health advice.

[0744] Input: Past biometric data and current analysis results.

[0745] Output: Health advice for the user.

[0746] Based on the data, the AI ​​model performs an analysis with the prompt message, "Create health advice based on the results of predictive analysis," and generates suggestions.

[0747] Step 6:

[0748] The device presents the user with a health report.

[0749] Input: Generated health status report.

[0750] Output: A health report in a format that can be viewed by the user.

[0751] The device will display reports, allowing users to check their health status in real time and use the information to improve their lifestyle.

[0752] (Application Example 1)

[0753] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0754] In modern society, there is a need to understand health conditions in real time and respond immediately when abnormalities occur. However, conventional methods rely on external devices for monitoring biometric data, making real-time response difficult. Furthermore, health conditions may deteriorate without the user noticing. Therefore, there is a need for a system that can continuously monitor the user's health condition and respond quickly to abnormalities.

[0755] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0756] In this invention, the server includes a device for wirelessly receiving biological data measured in the body, a data analysis device for analyzing the received biological data and detecting abnormalities, a device for notifying a medical facility or responsible person when an abnormality is detected, a device for presenting the analysis results to the user's information processing terminal, and a device for the information processing terminal to provide health information to the user in real time. This enables continuous monitoring of the user's health status, rapid detection of abnormalities, and appropriate responses.

[0757] "Biometric data measured inside the body" refers to physiological information acquired in real time by measuring devices placed inside the user's body.

[0758] A "wireless receiving device" is a device that uses wireless communication technology to remotely receive biometric data.

[0759] A "data analysis device" is a device that uses received biometric data to analyze the user's health status and determine whether there are any abnormalities.

[0760] A "device that notifies when an abnormality is detected" is a device that, based on the results of biometric data analysis, notifies relevant organizations and users when it is determined that there is a health abnormality.

[0761] A "user's information processing terminal" refers to a device, such as a smartphone or tablet, that a user uses to receive and verify information.

[0762] A "device that presents analysis results" is a device that displays the results of the analysis of biometric data to the user.

[0763] A "device that provides health information in real time" is a device that provides information immediately so that users can quickly understand their current health status.

[0764] The system that realizes this invention consists of multiple hardware and software components. The server wirelessly acquires data from microcapsules placed inside the body in order to receive biometric data. The microcapsules are equipped with sensors that measure the user's physiological information, such as heart rate, body temperature, and blood components.

[0765] The server can analyze the received biometric data using a data analysis device to detect anomalies. This analysis device compares past biometric data with data received in real time and executes an algorithm to identify anomalies. This algorithm incorporates a generative AI model, enabling advanced analysis.

[0766] If an anomaly is detected, the server notifies the medical facility and responsible party of the details of the anomaly. Appropriate communication protocols are used for this process. Furthermore, the analysis results are immediately transmitted to the user's information processing terminal, allowing the user to monitor their health status in real time.

[0767] On the user's information processing terminal, the analysis results are presented visually or audibly. The information processing terminal can take the form of a smartphone or tablet, allowing users to access health information in their daily lives. For example, if there are no abnormalities, the user is notified accordingly; if abnormalities are found, specific health advice is provided by the AI ​​model. Prompt messages can include instructions such as, "Your body temperature is high, so please drink plenty of fluids."

[0768] This invention allows users to continuously monitor their health status and take immediate action when an abnormality is detected, thereby streamlining health management in daily life.

[0769] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0770] Step 1:

[0771] The server wirelessly receives biometric data transmitted from the microcapsules. Specifically, it uses a wireless module to capture the signal and stores this signal as data in the server's memory. The input is the wireless signal from the microcapsule, and the output is the biometric data stored on the server side.

[0772] Step 2:

[0773] The server analyzes the received biometric data using an analysis device. Here, the current data is evaluated by comparing it with previously stored data. The input is the biometric information data acquired in step 1, and the output is the analysis result, i.e., whether or not there is an abnormality. Specifically, data analysis is performed by a generative AI model incorporating an AI agent.

[0774] Step 3:

[0775] If the server detects an anomaly, it activates the notification system. This includes notifying medical facilities, personnel, and users' information processing terminals of the details of the anomaly. The input is the anomaly information detected in step 2, and the output is the notified anomaly information. Specifically, the server uses push notifications and email to quickly disseminate information to relevant parties.

[0776] Step 4:

[0777] The user's information processing terminal receives analysis results and anomaly notifications transmitted from the server. The input is the information notified in step 3, and the output is the confirmed information received by the user visually or audibly. Specifically, the terminal displays the notification content on its screen and provides the user with anomaly information and health advice through voice guidance.

[0778] Step 5:

[0779] The user checks their health status based on the received information and takes action as needed. The input is the analysis results and health advice received in step 4, and the output is the specific actions the user will take. These specific actions might include drinking water or consulting a doctor to maintain their health.

[0780] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0781] This invention combines an emotional engine with a healthcare system that uses microcapsules ingested by the user before bedtime. This system recognizes not only biometric data but also the user's emotional state, providing a comprehensive analysis of their health status and personalized health advice.

[0782] This system first collects biometric data from within the body using sensors inside a capsule. The data measured includes heart rate, body temperature, and other physiological parameters. Once the user ingests the capsule, continuous data collection within the body begins.

[0783] The collected data is transmitted wirelessly to a server. The server receives and stores the encrypted data, and then passes it on to the AI ​​agent and emotion engine.

[0784] The AI ​​agent analyzes biometric data and attempts to detect anomalies. Predictive analytics are also performed during this analysis to assess the user's health risks. Meanwhile, the emotion engine infers the user's emotional state based on the collected data. For example, it can estimate stress levels and happiness levels from heart rate fluctuations and body temperature changes. These estimation results are incorporated into the health report.

[0785] If an anomaly is detected, or if a specific emotional state persists, the server will promptly notify a healthcare provider or relevant personnel. Simultaneously, the server will send a notification to the user's device, allowing the user to immediately access the information.

[0786] The health report is an overall health assessment that includes emotional state and is provided to the user via the device. This report includes lifestyle improvement advice based on the user's emotional state, as well as information on the correlation between emotions and health status.

[0787] For example, if a user's heart rate is abnormally high and the emotional engine recognizes a high-stress state, the server immediately notifies the attending physician. Furthermore, relaxation techniques for stress management are recommended on the user's smartphone. This system enables comprehensive health support from both an emotional and physical perspective.

[0788] The following describes the processing flow.

[0789] Step 1:

[0790] Users ingest microcapsules before going to sleep. These capsules contain sensors that measure biometric data such as heart rate and body temperature.

[0791] Step 2:

[0792] Sensors inside the capsule begin to continuously collect biometric data within the body. The data is updated regularly, and health status is monitored in real time.

[0793] Step 3:

[0794] The collected biometric data is transmitted to a server via wireless communication. This communication is encrypted to ensure data security.

[0795] Step 4:

[0796] The server records the received data in a database and prepares it for analysis. At the same time, it sends the data to the AI ​​agent and emotion engine.

[0797] Step 5:

[0798] The AI ​​agent analyzes biometric data and attempts to identify anomalies. It compares this data with past data and uses predictive analytics to assess future health risks.

[0799] Step 6:

[0800] The emotion engine analyzes fluctuations in heart rate and body temperature from biometric data to estimate the user's emotional state. For example, a high heart rate may indicate a state of stress.

[0801] Step 7:

[0802] If a user's health risk is determined to be high, or if a specific emotional state is recognized, the server will notify a healthcare provider or relevant personnel. This notification is made electronically, enabling a rapid response.

[0803] Step 8:

[0804] Simultaneously, the server sends a notification to the user's terminal, providing real-time alerts. Users can check the notification on their smartphone or wearable device.

[0805] Step 9:

[0806] Based on the analysis results from the AI ​​agent and emotion engine, a detailed health report is generated. This report includes an overall assessment of health status, an estimated emotional state, and personalized health advice.

[0807] Step 10:

[0808] The device displays a generated health report to the user. The report details suggestions and points to note for improving lifestyle habits based on the user's emotional state. The user can use this information to adjust their lifestyle.

[0809] (Example 2)

[0810] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0811] Traditional healthcare systems assessed health status by analyzing only the user's biometric information, making it difficult to provide comprehensive health support that considered the user's emotional state and stress levels. Furthermore, the inability to detect anomalies in real time or track emotional states could lead to delays in situations requiring rapid response.

[0812] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0813] In this invention, the server includes means for wirelessly receiving biometric information, information analysis means for analyzing the received biometric information and detecting anomalies, and emotion estimation means for inferring the user's emotional state based on the analyzed biometric information. This makes it possible to comprehensively evaluate the user's biometric information and emotional state, detect anomalies in real time, and provide necessary notifications and advice.

[0814] "Biometric information measured within the body" refers to health-related physiological indicators, such as heart rate and body temperature, that are continuously acquired by sensors placed inside the user's body.

[0815] "Means of receiving wirelessly" refers to communication technologies that transmit biometric information to external devices using Bluetooth, Wi-Fi, etc.

[0816] "Information analysis means" refers to algorithms and programs used to analyze received biological information and perform abnormal value detection and predictive analysis.

[0817] "Emotion estimation methods" refer to technologies and processes that estimate a user's emotional state and stress level based on the results of biometric data analysis.

[0818] A "notification method" refers to a system that informs medical institutions or relevant personnel of the situation when an abnormality or a specific emotional state is detected.

[0819] "User's device" refers to an information terminal such as a smartphone or tablet owned by the user, and is a device used to display health status reports and notifications.

[0820] A "health status report" is a report that summarizes the analysis results, including the user's biometric information and emotional state, and is a document that provides health advice to the user.

[0821] This invention is a unique healthcare system that uses microcapsules ingested by the user before going to sleep. By ingesting the microcapsules, the user's body continuously collects biological information through sensors. The capsules contain small sensors and communication modules that collect data such as heart rate and body temperature. This data is transmitted wirelessly from the capsule to a server. Wireless communication technologies used in this system include Bluetooth and Wi-Fi.

[0822] The server encrypts the received biometric information and stores it in a database. Next, it processes this data using information analysis tools, and an AI model performs anomaly detection and predictive analysis. The AI ​​model compares historical data with real-time data to assess the user's health risk.

[0823] Simultaneously, the emotion estimation system predicts the user's emotional state based on heart rate fluctuations and changes in body temperature. This process utilizes an emotion engine to predict stress levels and happiness levels. This allows for a comprehensive assessment of the user's health status.

[0824] If an abnormality or a specific emotional state is detected, the server immediately notifies the attending physician or medical institution. This notification is often sent via email or a dedicated application. The server also sends a health status report to the user's device, providing the user with analysis results and advice for lifestyle improvements.

[0825] As a concrete example, consider a scenario where a user ingests a microcapsule and the system detects a high-stress state. In this case, the server quickly notifies the attending physician, and the user's terminal recommends relaxation techniques such as "take five minutes of deep breathing." An example of a prompt message might be, "Use the data collected by the microcapsule to evaluate the user's emotional state and generate specific advice for stress management." This invention allows users to receive comprehensive support from both emotional and physical perspectives.

[0826] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0827] Step 1:

[0828] When a user ingests a microcapsule, sensors placed inside the body collect biometric information such as heart rate and body temperature in real time. The input is the user's biometric information, and the output is a backend system for wireless data transmission. Specifically, the microcapsule's sensors detect the biometric information and prepare the data for transmission by packetizing it via a built-in wireless communication module.

[0829] Step 2:

[0830] The transmitted biometric information reaches the server, where it is encrypted and received. The input is encrypted biometric information transmitted from the microcapsule, and the output is a secure database for temporary storage. The server then decrypts the received data and performs the specific actions of storing it in the database for appropriate storage.

[0831] Step 3:

[0832] Biometric information stored on the server is passed to an information analysis system, where an AI model performs anomaly detection and predictive analysis. The input is the biometric information stored on the server, and the output is the analysis results, such as the identification of anomalies. Specifically, the AI ​​model analyzes the biometric information and detects anomalies in real time while comparing it with past data.

[0833] Step 4:

[0834] Based on the analysis results, the server uses emotion estimation tools to predict the emotional state. The input is the analyzed biometric information, and the output is the user's emotional state and stress level. The emotion engine uses fluctuations in heart rate and changes in body temperature to estimate emotions and perform specific actions to identify the user's emotional state.

[0835] Step 5:

[0836] If the server detects an abnormality or a specific emotional state, it immediately notifies healthcare providers and relevant personnel, and also sends a notification to the user's terminal. The input is the result of analysis and estimation, and the output is the notification content. The server uses communication means to perform specific actions to inform healthcare professionals and users of the situation.

[0837] Step 6:

[0838] Ultimately, the server generates a health status report and sends it to the user's device. The inputs are the analysis results and emotional state, and the output is the health status report. The server performs a comprehensive health assessment, generates a report, and delivers it to the user's device.

[0839] (Application Example 2)

[0840] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0841] For elderly individuals and those with specific health concerns, there is a need for a system that can comprehensively understand fluctuations in physiological parameters within the body and emotional states, and immediately assess their health status. However, conventional healthcare systems have challenges in assessing health, including emotional states, and thus hindering rapid care responses.

[0842] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0843] In this invention, the server includes means for wirelessly receiving physiological parameters measured within the body, information analysis means for analyzing the received physiological parameters and detecting abnormal values, and means for estimating the user's emotional state and incorporating that information into the health status assessment. This enables a comprehensive health assessment that also takes emotional state into consideration.

[0844] "Physiological parameters" are numerical data related to the body, such as heart rate and body temperature, that are measured within the body.

[0845] "Means of receiving wirelessly" refers to a system for remotely acquiring data using wireless communication technologies such as Bluetooth or Wi-Fi.

[0846] "Information analysis means" refers to processes and equipment used to detect and analyze numerical anomalies based on acquired data.

[0847] An "abnormal value" is a physiological parameter value that falls outside the normal range and may indicate a health problem.

[0848] "Means for reporting to a medical institution or responsible organization" refers to communication methods for quickly informing medical personnel or management organizations when abnormal values ​​are detected.

[0849] "Means for displaying analysis results on information devices" refers to screen display functions that visually show analysis results on devices such as smartphones and computers.

[0850] "Emotional state" refers to an individual's emotional state, such as stress or happiness, estimated from fluctuations in acquired physiological parameters.

[0851] "Health assessment" is a process of diagnosing and analyzing an individual's overall health based on information about physiological parameters and emotional state.

[0852] This system provides users with wearable or ingestible sensors that continuously measure physiological parameters within the body. The measured data is transmitted to a server using wireless communication technologies such as Bluetooth or Wi-Fi. The server performs real-time analysis of the data using programming languages ​​such as Python. Machine learning libraries such as TensorFlow and PyTorch are used as information analysis tools to efficiently detect anomalies in the obtained data in order to detect abnormal values ​​of physiological parameters.

[0853] The server also utilizes AI agents and an emotion engine to estimate emotional states. This emotional state estimation employs sophisticated algorithms based on heart rate and body temperature fluctuations to understand the emotional state of each individual user. This enables a comprehensive health assessment of the user.

[0854] The analysis results and estimated emotional state are transmitted in real time to the user's device, specifically a smartphone or tablet. This device is designed to visually present information, making it easy for the user to understand their own health status. In particular, if an abnormality is detected, the system immediately notifies medical institutions or relevant organizations.

[0855] As a concrete example, consider a scenario where an abnormal heart rate is detected in an elderly person while they are sleeping, and the emotional engine recognizes a high-stress state. The server can immediately issue a warning and send a notification to the caregiver recommending relaxation techniques.

[0856] An example of a prompt message is, "Write code to analyze the user's heart rate and body temperature and estimate their stress level." This enables advanced health support utilizing generative AI models.

[0857] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0858] Step 1:

[0859] The sensor measures physiological parameters such as heart rate and body temperature inside the user's body. The input is biometric data acquired in real time. This data is temporarily stored within the sensor.

[0860] Step 2:

[0861] The sensor wirelessly transmits physiological parameters to the server via Bluetooth or Wi-Fi. The server receives this data as input and stores it in a database. The output is temporary data storage on the server.

[0862] Step 3:

[0863] The server initiates data analysis using a Python program. Input consists of historical data and newly received biometric data. An AI agent and machine learning algorithms (e.g., TensorFlow) are used to detect anomalies in the data. The output is the analysis result regarding the presence or absence of anomalies.

[0864] Step 4:

[0865] The server simultaneously uses an emotion engine to estimate the user's emotional state. The input consists of data on heart rate and body temperature fluctuations. Through data processing, it generates and outputs emotional indicators such as stress levels and feelings of well-being.

[0866] Step 5:

[0867] The server wirelessly transmits the analysis results and estimated emotional state to the user's terminal. The input is the enriched data obtained through the analysis process. The terminal receives this data and outputs it by visually displaying it on the screen.

[0868] Step 6:

[0869] When an anomaly is detected, the server immediately sends a notification to the healthcare institution or responsible organization. The input is the anomaly detection result. A notification message is generated via the communication protocol and output to the necessary location.

[0870] Step 7:

[0871] Based on data received by the user's device, the system suggests appropriate health advice and relaxation techniques. Input consists of analysis results and emotion estimation results. The output is displayed in a user-friendly format via the device's GUI.

[0872] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0873] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0874] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0875] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0876] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0877] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0878] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0879] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0880] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0881] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0882] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0883] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0884] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0885] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0886] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0887] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0888] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0889] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0890] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0891] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0892] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0893] The following is further disclosed regarding the embodiments described above.

[0894] (Claim 1)

[0895] A means of wirelessly receiving biometric data measured inside the body,

[0896] A data analysis means for analyzing received biological data and detecting abnormalities,

[0897] A means of notifying a medical institution or person in charge if an abnormality is detected,

[0898] A means of displaying the analysis results on the user's terminal,

[0899] A system that includes this.

[0900] (Claim 2)

[0901] The system according to claim 1, wherein the analysis means has the function of comparing past biological data with biological data measured in real time and performing predictive analysis.

[0902] (Claim 3)

[0903] The system according to claim 1, further comprising means for transmitting a health status report generated based on received biometric data to a user terminal.

[0904] "Example 1"

[0905] (Claim 1)

[0906] A means of receiving biological information measured inside the body via wireless communication,

[0907] An analysis device for analyzing received biological information and detecting abnormalities,

[0908] A means of providing information to a medical institution or person in charge when an abnormality is detected,

[0909] A means of displaying the analysis results on the user's information terminal,

[0910] A method for generating health advice by comparing past biometric data with biometric data acquired in real time, performing predictive analysis, and

[0911] A means for transmitting the generated health status report to the user information terminal,

[0912] A system that includes this.

[0913] (Claim 2)

[0914] The system according to claim 1, wherein the analysis device has a function to perform anomaly detection using the generated knowledge processing model.

[0915] (Claim 3)

[0916] The system according to claim 1, comprising means for performing computer processing using prompt statements for anomaly detection.

[0917] "Application Example 1"

[0918] (Claim 1)

[0919] A device that wirelessly receives biological data measured inside the body,

[0920] A data analysis device for analyzing received biological data and detecting abnormalities,

[0921] A device that notifies the medical facility or person in charge if an abnormality is detected,

[0922] A device that displays the analysis results on the user's information processing terminal,

[0923] A device in which an information processing terminal provides health information to the user in real time,

[0924] A system that includes this.

[0925] (Claim 2)

[0926] The system according to claim 1, wherein the analysis device has the ability to compare past biological data with biological data measured in real time and perform predictive analysis.

[0927] (Claim 3)

[0928] The system according to claim 1, comprising a device that transmits a health status report generated based on received biometric data to a user information processing terminal.

[0929] "Example 2 of combining an emotion engine"

[0930] (Claim 1)

[0931] A means of wirelessly receiving biological information measured inside the body,

[0932] Information analysis means for analyzing received biological information and detecting abnormalities,

[0933] An emotion estimation method that infers the user's emotional state based on analyzed biometric information,

[0934] A means of notifying a medical institution or person in charge if an abnormal or specific emotional state is detected,

[0935] A means of presenting analysis results and emotional states to the user's device,

[0936] A system that includes this.

[0937] (Claim 2)

[0938] The system according to claim 1, wherein the analysis means has a function to compare past biological information with biological information measured in real time and perform predictive analysis.

[0939] (Claim 3)

[0940] The system according to claim 1, comprising means for transmitting a health status report generated based on received biometric information to a user device, wherein the report includes an emotional state.

[0941] "Application example 2 when combining with an emotional engine"

[0942] (Claim 1)

[0943] A means of wirelessly receiving physiological parameters measured within the body,

[0944] Information analysis means for analyzing received physiological parameters and detecting abnormal values,

[0945] A means of reporting abnormal values ​​to a medical institution or the relevant organization,

[0946] A means for displaying the analysis results on the user's information device,

[0947] A means of estimating the emotional state of users and incorporating that information into health status assessments,

[0948] A system that includes this.

[0949] (Claim 2)

[0950] The system according to claim 1, wherein the analysis means has a function to compare accumulated past biological data with physiological parameters acquired in real time and perform predictive analysis.

[0951] (Claim 3)

[0952] The system according to claim 1, further comprising means for transmitting an overall health assessment report, generated based on received biometric data and estimated emotional state, to an information device. [Explanation of symbols]

[0953] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of wirelessly receiving biometric data measured inside the body, A data analysis means for analyzing received biological data and detecting abnormalities, A means of notifying a medical institution or person in charge if an abnormality is detected, A means of displaying the analysis results on the user's terminal, A system that includes this.

2. The system according to claim 1, wherein the analysis means has a function to compare past biological data with biological data measured in real time and perform predictive analysis.

3. The system according to claim 1, further comprising means for transmitting a health status report generated based on received biometric data to a user terminal.

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