system

Abstract

システムを提供する。【解決手段】生体情報収集装置が内蔵されたカプセルを用いて内部データを取得する手段と、前記内部データを通信するための外部装置手段と、前記外部装置が受信した内部データを評価する人工知能手段と、前記評価結果に基づいて異常を検出し、警告を出力する手段と、前記評価結果を基に生成された健康状況報告を提供する手段と、前記警告が異常検出時に介護担当者に対して自動的に送信される手段と、前記健康状況報告に基づき、個別に調整された健康管理指示を利用者に提供する手段と、を含むシステム。

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, 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, due to busy daily life and geographical constraints, there are many situations where it is difficult to receive regular health checkups and medical examinations. Therefore, there is a problem that it is difficult to detect diseases and health abnormalities early and start prompt treatment. In addition, the opportunity to receive appropriate advice and health guidance according to individual health conditions is also limited.

Means for Solving the Problems

[0005] This invention solves this problem by collecting biological data in real time using a capsule containing a biosensor introduced into the body and transmitting it to an external device. The received data is analyzed using artificial intelligence, and if an abnormality is detected, healthcare professionals are immediately notified. Furthermore, a health report is generated based on the analysis results, and personalized health management advice is provided to the user, helping them understand and improve their health status.

[0006] A "biosensor" is a device used to detect and measure the physiological state within the body.

[0007] A "capsule" is a small, enclosed body that can be introduced into the body and may contain electronic components or sensors.

[0008] "Internal body data" refers to numerical information about a person's physical condition, such as heart rate, body temperature, blood components, and digestive function.

[0009] "External devices" refer to devices or terminals used to receive and process data transmitted from the capsule.

[0010] "Artificial intelligence" refers to human intelligent activity that is mimicked by computers, and it has functions such as data analysis and anomaly detection.

[0011] "Analysis" is the process of processing data to obtain structured information, which is used to identify anomalies and patterns.

[0012] "Abnormal" refers to physiological values ​​or conditions that deviate from normal health.

[0013] "Notification" refers to a message or signal used to communicate a specific event or information to a user or other system.

[0014] A "health report" is a document or digital information created based on the analysis of biometric data, providing a detailed description of the user's health status.

[0015] "Personalized health management advice" refers to specific improvement measures and guidance provided based on the health status and lifestyle of individual users.

Brief Description of Drawings

[0016] [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 a data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of a data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of a data processing system in Example 2 when an emotion engine is combined. [Figure 14]It is a sequence diagram showing the processing flow of a data processing system in Application Example 2 when a sentiment engine is combined.

Embodiments for Carrying out the Invention

[0017] 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.

[0018] First, the terms used in the following description will be explained.

[0019] In the following embodiments, a numbered 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), etc.

[0020] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0021] In the following embodiments, a numbered 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, etc.

[0022] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0023] 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."

[0024] [First Embodiment]

[0025] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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".

[0037] This invention is a system that incorporates multiple biosensors within a microcapsule ingested by the user, and transmits biometric data acquired from within the body to an external device using communication technology. This makes it possible to monitor the user's health status in real time and provide appropriate responses based on the analysis results.

[0038] The main system consists of microcapsules, external devices (smartphones and wearable devices), a server, and an analysis system including artificial intelligence.

[0039] Capsule Function

[0040] Users take microcapsules before going to sleep. The capsules have the function of continuously acquiring biometric data such as heart rate, body temperature, and blood components within the body. This data is transmitted to an external device using wireless communication.

[0041] Role of external devices

[0042] The device has the function of receiving data from the capsule and transmitting that data to a server via the internet. Through a pre-installed application, the device provides an interface for visualizing the user's health information and receiving real-time notifications.

[0043] Data analysis using servers and artificial intelligence

[0044] The server immediately analyzes the received biometric data using AI. The analysis system compares it with past user data and identifies any data that deviates from normal values ​​as abnormal. If an abnormality is detected, an automatic notification is sent to the medical institution or the attending physician.

[0045] Based on the analyzed data, the server generates a detailed health report. This report includes personalized health management advice for the user and is sent to the user's device.

[0046] Specific example

[0047] For example, if a user has a chronic heart condition and needs to monitor their daily heart rate, the data collected by the microcapsules is analyzed regularly. If a higher-than-normal heart rate is detected one night, the server identifies it as an anomaly and immediately sends a notification to the user and their doctor. Based on this information, the user can receive appropriate medical attention early on. This system contributes to maintaining the user's health by supporting daily health management and simplifying access to medical care.

[0048] The following describes the processing flow.

[0049] Step 1:

[0050] The user takes a microcapsule before going to sleep. The capsule prepares to collect biometric data such as heart rate, body temperature, digestive system status, and blood components in real time within the body.

[0051] Step 2:

[0052] The device receives biometric data transmitted wirelessly from the capsule. During reception, it checks the battery level and communication status to confirm that the data has been received correctly.

[0053] Step 3:

[0054] The device temporarily stores the received biometric data and transmits it to a server via the internet. The data is encrypted during transmission to protect privacy.

[0055] Step 4:

[0056] The server begins processing the received biometric data for analysis. It performs data format conversion and initial filtering of outliers, preparing the data for analysis.

[0057] Step 5:

[0058] The artificial intelligence installed on the server analyzes the data. It compares it with past data to detect changes in patterns and anomalies. If an anomaly is found, it evaluates the type of anomaly and its urgency.

[0059] Step 6:

[0060] The server generates an alert when an anomaly is detected and sends a notification to the designated physician or healthcare facility. This includes a summary of the analysis results and recommended next steps.

[0061] Step 7:

[0062] The server generates a daily health report. The report includes an overview of your daily health status, any abnormalities, and advice for improving your health.

[0063] Step 8:

[0064] The server sends the generated health report to the terminal. The user receives this report and can get feedback on their daily health status and areas for improvement.

[0065] Step 9:

[0066] If a user deems it necessary, they will be able to book online medical appointments and have remote consultations with their doctor via their device.

[0067] (Example 1)

[0068] 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."

[0069] In modern medicine, there is a need for rapid and accurate monitoring of health conditions, but there is a lack of technology to continuously acquire biometric data in daily life and detect abnormalities in real time. Furthermore, when an abnormality is detected, it is necessary to quickly notify medical professionals and provide individually tailored health management guidance, but the means to efficiently achieve this have been limited.

[0070] 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.

[0071] In this invention, the server includes means for acquiring internal bodily information using a small device with a built-in biosensor, means for transmitting the internal bodily information to an external device, and means for a machine learning model that analyzes the internal bodily information received by the external device. This enables real-time monitoring of the user's health status and, if an abnormality is detected, prompt notification to medical professionals and provision of individually tailored health management guidance.

[0072] A "biosensor" is a device used to measure the internal state of the body, and has the function of acquiring information such as heart rate, body temperature, and blood components.

[0073] A "miniature device" is a device designed to be small enough to penetrate the human body, containing biosensors, and used to collect biological data.

[0074] "Internal bodily information" refers to data on physiological indicators such as heart rate and body temperature, and is fundamental information for evaluating an individual's health status.

[0075] An "external device" is a device that receives information transmitted from a small device and functions as a platform for analyzing that information.

[0076] A "machine learning model" is a system composed of algorithms that learn patterns using large amounts of data and perform predictions and analyses on new data.

[0077] A "health report" is a document that summarizes the health status and any abnormalities based on the results of biometric data obtained through analysis, and provides guidance based on those results.

[0078] "Communication" refers to the process of sending and receiving information, and is particularly relevant when an anomaly is detected and the information is transmitted to medical professionals.

[0079] "Medical professionals" refer to occupational workers who possess specialized medical knowledge and skills, including doctors and nurses.

[0080] "Adapted health management guidance" refers to specific advice for maintaining or improving health that is customized to an individual's health condition based on the analysis results.

[0081] This invention provides a system for monitoring health status in real time. The user first takes a small device containing a biosensor. This device continuously acquires biometric information and wirelessly transmits it to an external device. The data acquired as internal bodily information includes important physiological indicators such as heart rate, body temperature, and blood components.

[0082] The external device uses common hardware such as smartphones and wearable devices. The terminal has the function of transmitting biometric information received from this small device to a server via the internet. The server uses a machine learning model built with a programming language such as Python to analyze the received data. If this analysis detects values ​​outside the normal range, the server immediately identifies the anomaly and automatically sends a communication.

[0083] The generated health report provides users with tailored health management guidance. This guidance includes advice on specific health problems and recommended daily management methods. Users can view the health report through an application on their device and take early medical action if necessary.

[0084] As a concrete example, consider a scenario where a user utilizes this system to aim for early detection of heart disease. The small device acquires heart rate data at night, and if an abnormality is detected, a notification is sent to the attending physician via the server. Based on this information, the user can take prompt and appropriate medical action.

[0085] An example of a prompt when using a generative AI model would be: "How can we design a system that uses an advanced anomaly detection algorithm to identify abnormal values ​​based on heart rate data acquired by a small device taken by the user, and notifies the user in real time?"

[0086] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0087] Step 1:

[0088] The user ingests a small device, which acquires biometric information within the body. Inputs include heart rate, body temperature, and blood components, which are measured by sensors. The output is digital data of this biometric information. Specifically, the device's sensors acquire these values ​​in real time and temporarily store them in internal memory.

[0089] Step 2:

[0090] The terminal wirelessly receives biometric information from a small device. The input to this process is the digitized biometric data transmitted by the small device. The output is this data stored within the terminal. Specifically, the terminal establishes communication with the small device via Bluetooth or NFC and downloads the data.

[0091] Step 3:

[0092] The device transmits the received biometric information to the server. The input is the biometric data stored on the device. The output is the biometric data that has been successfully transferred to the server. Specifically, the device securely transmits the data to the server using the HTTPS protocol via an internet connection.

[0093] Step 4:

[0094] The server analyzes the received biometric data. The input is the biometric information sent to the server. The output is the analysis result, including whether or not there are abnormalities and an assessment of health status. The server processes the data using machine learning models and compares this data with historical records. The specific operation for detecting abnormalities involves using algorithms to find deviations from the normal range.

[0095] Step 5:

[0096] The server sends a notification and generates a health report when an anomaly is detected. The input is analyzed biometric data. The output is a notification message and the generated health report. Specifically, the server sends email and application push notifications to users and healthcare professionals. The report also includes individually tailored health management advice.

[0097] Step 6:

[0098] The user checks their health report on their device and takes medical action as needed. The input is the health report sent from the server to the device. The output is the medical action the user requires. Specifically, the user views the report using a dedicated application on their device and contacts a medical institution when they receive a notification.

[0099] (Application Example 1)

[0100] 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."

[0101] There is a need for a system that can monitor the health status of the elderly and patients requiring care in real time and quickly detect abnormalities. However, existing systems have shortcomings in data collection and analysis, making early detection of abnormalities and appropriate responses difficult.

[0102] 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.

[0103] In this invention, the server includes means for acquiring internal data using a capsule containing a biometric information collection device, means for an external device for communicating the internal data, and means for artificial intelligence for evaluating the internal data received by the external device. This enables real-time monitoring of changes in the user's physical condition and allows for early intervention.

[0104] A "biometric information collection device" is a device placed inside the body to acquire data about the user's health status.

[0105] A "capsule" is a small container that can be taken into the body by the user and contains a biometric information collection device.

[0106] "Internal data" refers to data such as heart rate, body temperature, and other health-related information obtained directly from the user's body.

[0107] "External device means" refers to a device for receiving and communicating internal data acquired from the capsule, and includes smartphones and wearable devices.

[0108] "Artificial intelligence means" refers to algorithms and technologies for analyzing and evaluating received data, and is a system used for detecting anomalies and providing instructions for health management.

[0109] A "warning" is a notification or alert issued when an abnormality is detected, and is sent to the user or caregiver.

[0110] A "health status report" is a detailed health status report generated based on analyzed data, and it contains information useful for the user's health management.

[0111] A "caregiver" is someone responsible for providing care to a user, and typically refers to a caregiver or nurse.

[0112] A "user" is an individual whose health status is monitored by this system, and this mainly includes elderly people and patients who require health management.

[0113] This invention is realized by a capsule containing a biometric information collection device that is ingested by the user. The capsule acquires internal data such as heart rate and body temperature while inside the user's body. The acquired data is transmitted to an external device, such as a smartphone or wearable device, using Wi-Fi or Bluetooth.

[0114] The terminal transmits the received internal data to the server via the internet. The server analyzes the data using artificial intelligence and evaluates the user's health status. This analysis compares the data with past data to determine whether or not there are any abnormalities. If an abnormality is detected, the server automatically sends a warning to the caregiver. The server also generates a detailed health status report based on the evaluation results and sends it to the terminal.

[0115] This health status report is designed to make it easier for users and caregivers to understand the situation and includes personalized health management instructions. A specific example of its use is in a care facility where elderly individuals are using the system. This system can monitor changes in health in real time, even at night, and immediately notifies care staff of any abnormalities, enabling early medical intervention.

[0116] An example of a prompt message would be, "Please describe the concept of an application that analyzes health monitoring data of elderly people in real time and immediately notifies if an abnormality is detected."

[0117] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0118] Step 1:

[0119] The user takes a capsule. Inside the body, the capsule uses a biometric data collection device to acquire internal data such as heart rate and body temperature. The input is the body's internal biometric information, and the output is the acquired biometric data. This data is temporarily stored inside the capsule.

[0120] Step 2:

[0121] The terminal wirelessly receives internal data from the capsule. The input is biometric data from the capsule, and the output is data stored in the terminal. The terminal prepares to transmit this data to a server via the internet.

[0122] Step 3:

[0123] The server receives internal data transmitted from the terminal. The input is health data from the terminal, and the output is biometric information as received data. The server stores this data in a database for analysis.

[0124] Step 4:

[0125] The server uses artificial intelligence to compare and analyze received data against past records. The input consists of biometric information and historical database data, while the output is anomaly detection information as a result of the analysis. In this step, a generative AI model is used to identify anomaly patterns.

[0126] Step 5:

[0127] If the server detects an anomaly, it automatically notifies the caregiver. The input is the anomaly information from the analysis results, and the output is a notification message as a warning. Notifications are sent via email or push notifications from a dedicated application.

[0128] Step 6:

[0129] The server generates a health status report based on the analysis results and sends it to the terminal. The input is the analysis results, and the output is a health status report for the user. The report includes individually tailored health management instructions.

[0130] Step 7:

[0131] The terminal receives health status reports, which are then reviewed by the user and caregivers. The input is the health status report from the server, and the output is the health information received by the user. The terminal visualizes this information and provides it to the user.

[0132] The above steps enable real-time monitoring of the user's health status, allowing for early detection of anomalies and rapid response.

[0133] 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.

[0134] This invention integrates an emotion engine into a system that acquires various in vivo data using microcapsules ingested by the user, thereby enabling deeper analysis and management of health conditions. The system consists of microcapsules, an external device, artificial intelligence on a server, and an emotion engine.

[0135] Capsule Function

[0136] Users take a microcapsule equipped with a biosensor before going to sleep. This capsule has the function of acquiring biometric data such as heart rate, body temperature, digestive system status, and blood components in real time and transmitting it to an external device.

[0137] Role of external devices

[0138] The device wirelessly receives data from the microcapsules. The received data is transmitted to the server in an encrypted form. Furthermore, the device displays notifications to the user and provides feedback on the user's health status.

[0139] Data analysis using servers and artificial intelligence

[0140] The server analyzes the received data using AI. This analysis not only detects abnormalities in physiological data but also includes recognizing the user's emotional state through an emotion engine. The emotion engine analyzes heart rate variability and other biosignals to infer the user's emotional state. This makes it possible to assess the user's mental health as well.

[0141] Use of analysis results

[0142] Based on the analysis results, the server generates a detailed health report. This report includes not only the user's overall health status but also their emotional state, providing personalized health management advice. Furthermore, if an abnormality is detected, the system immediately sends a notification to the attending physician or healthcare provider.

[0143] Specific example

[0144] For example, when a user is experiencing high levels of stress, data is collected from the capsule along with fluctuations in heart rate and body temperature. This data is analyzed by an emotion engine, which determines that the user is experiencing a high level of stress. The server then adds specific advice for stress reduction to the report, providing information that can be used for daily health management. In this way, the system contributes not only to physical health management but also to maintaining mental health.

[0145] The following describes the processing flow.

[0146] Step 1:

[0147] Users take a microcapsule containing a biosensor before going to sleep. This capsule detects heart rate, body temperature, digestive system status, blood components, and other parameters in real time.

[0148] Step 2:

[0149] The device receives biometric data transmitted wirelessly from the capsule. This data includes subtle fluctuations in heart rate and temperature changes, as well as other data necessary for emotion recognition.

[0150] Step 3:

[0151] The device transmits the received biometric data to a server via the internet. The data is encrypted during transmission, ensuring secure transfer.

[0152] Step 4:

[0153] The server analyzes the received data using AI and an emotion engine. The AI ​​detects anomalies in the data, and the emotion engine infers the user's emotional state based on heart rate variability patterns and other biometric data.

[0154] Step 5:

[0155] If the server detects an anomaly based on the analysis results, it will immediately send a notification to the attending physician or medical professional. This notification will also include information about the user's emotional state, allowing the physician to take into account the user's mental condition when responding.

[0156] Step 6:

[0157] The server generates a detailed health report. This report includes analysis of physical health status as well as emotional state, providing information to help users manage their daily health.

[0158] Step 7:

[0159] The server sends the generated health report to the user's device. The user can then receive this report to understand their own health status and identify areas that need improvement.

[0160] Step 8:

[0161] Users can use their devices as needed to book online consultations and medical advice appointments. This is particularly useful for receiving mental health support when emotional disturbances are recognized.

[0162] (Example 2)

[0163] 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 will be referred to as the "terminal."

[0164] In health management, not only physical data but also mental health status is important. However, conventional systems were limited to monitoring only physiological data, making it difficult to grasp the user's emotional state in real time and provide appropriate advice. As a result, comprehensive health management was not adequately provided.

[0165] 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.

[0166] In this invention, the server includes means for using a capsule containing a biosensor for acquiring biometric information, means for transmitting the biometric information to an external device, artificial intelligence means for analyzing the biometric information received by the external device, and emotion estimation means for inferring emotional states. This enables a comprehensive evaluation of physical and emotional health status and the provision of personalized health management advice.

[0167] A "biosensor" is a device used to measure the physiological state of an organism, and has the function of collecting data such as heart rate and body temperature.

[0168] A "capsule" is a small container that has the ability to acquire information from inside the body using built-in sensors and transmit it to the outside.

[0169] An "external device" is a terminal device that receives data transmitted from the capsule and transfers it to the server.

[0170] "Artificial intelligence means" refers to algorithms and technologies used to analyze received data and detect anomalies or infer emotional states.

[0171] "Emotion estimation methods" refer to technologies and algorithms for analyzing biosignals to infer an individual's emotional state.

[0172] "Notification" refers to a means of communication that is sent to users or healthcare professionals when an abnormality is detected.

[0173] A "health report" is a document that provides an overview of a user's health status, generated based on acquired and analyzed biometric data.

[0174] "Personalized health management advice" refers to specific instructions and suggestions for improving one's lifestyle and health, provided based on an individual's health data and emotional state.

[0175] This invention is a system that comprehensively monitors a user's physical and emotional health using a capsule containing a biosensor. The user takes the capsule before going to sleep, and the capsule acquires physiological data such as heart rate and body temperature in real time. The data acquired by the capsule is transmitted to an external device using wireless communication technologies such as Bluetooth or Wi-Fi.

[0176] The terminal securely transfers biometric data received from the capsule to a server. Data transfer uses AES encryption and is conducted via the HTTPS protocol to ensure data confidentiality. The terminal also plays a role in providing health-related feedback to the user.

[0177] The server uses a generative AI model to analyze the received biometric data. This analysis utilizes machine learning algorithms implemented using Python and related libraries. The server not only detects anomalies in physiological data but also evaluates the user's emotional state using emotion estimation tools. As a result, the server generates a detailed health report and notifies the user, while also automatically contacting healthcare professionals in case of abnormalities.

[0178] As a concrete example, consider a case where a user's heart rate increases due to daytime stress. In this case, the capsule records the fluctuations in heart rate and transmits the data to a server via the terminal. The server analyzes the stress level using emotion estimation methods and provides the user with a health report via the terminal, which includes appropriate stress management measures. This report includes personalized advice for reducing the user's stress.

[0179] An example of a prompt for a generative AI model is: "Generate a sample report showing data analysis results for when a user experiences stress in the evening. This report should include details such as heart rate and body temperature, as well as an assessment of the stress level by an emotion engine."

[0180] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0181] Step 1:

[0182] The user ingests a capsule containing a biosensor. The sensor acquires physiological data such as heart rate and body temperature. The user's internal state is provided as input, and biometric data acquired in real time is obtained as output. The sensor acquires this data and prepares for wireless communication.

[0183] Step 2:

[0184] The terminal wirelessly receives biometric data transmitted from the capsule. The input is the biometric data from the capsule, and the output is the encrypted received data. Specifically, the terminal receives the data via Bluetooth or Wi-Fi connection and prepares to securely transfer it to the server using AES encryption.

[0185] Step 3:

[0186] The terminal sends data to the server. The input is encrypted biometric data, and the output is data transfer to the server. The terminal uses the HTTPS protocol to establish a secure communication channel and send data to the server.

[0187] Step 4:

[0188] The server analyzes the received biometric data. The input is encrypted biometric data, and the output is the result of the analyzed health and emotional state. The server uses a generative AI model to analyze the data and perform calculations to detect health abnormalities and emotional fluctuations. The analysis is carried out using programming languages ​​such as Python and machine learning algorithms.

[0189] Step 5:

[0190] The server generates a health report based on the analysis results. The input is the result of the analyzed data, and the output is a detailed report on the user's health and emotional state. The report is generated in a user-friendly format and includes additional instructions or alerts if any anomalies are detected.

[0191] Step 6:

[0192] The server sends generated reports and anomaly notifications to the user via the terminal. Input is the generated health report, and output is explicit health information and possible action suggestions to the user. Furthermore, the system also sends notifications to healthcare professionals as needed. The terminal displays information on the user's screen, providing actionable insights for health management.

[0193] (Application Example 2)

[0194] 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".

[0195] There is a need to continuously and promptly monitor the health status of the elderly and those requiring physical care, and to provide comprehensive support for their physical and mental health management. However, conventional methods have the challenge of not being able to consider not only physical condition but also emotional state, and to provide specific health advice tailored to individual circumstances.

[0196] 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.

[0197] In this invention, the server includes means for acquiring internal bodily data using microcapsules containing biometric information sensors, artificial intelligence means for analyzing the internal bodily data received by an external terminal, and means for performing a detailed evaluation of the health status report, including not only the physical state but also the emotional state. This makes it possible to realize more comprehensive and personalized health management.

[0198] A "biometric information sensor" is a device embedded in a microcapsule to acquire data from inside the body.

[0199] A "microcapsule" is a small capsule containing a bio-information sensor that collects information within the user's body.

[0200] "Internal bodily data" refers to various physiological data obtained from within the body, such as heart rate, body temperature, digestive system status, and blood components.

[0201] An "external terminal" is a communication device that receives internal body data from microcapsules and then transmits it to a server.

[0202] "Artificial intelligence tools" refer to software systems used to perform advanced data analysis and evaluate physical and emotional states.

[0203] A "health status report" is a detailed assessment report generated based on analyzed physiological and emotional data of the body.

[0204] "Emotional state" refers to the emotional state or tendency of the user, inferred from fluctuations in biometric information.

[0205] This invention is a system that uses microcapsules containing biometric sensors to acquire and analyze internal bodily data of elderly individuals and others requiring health management. Users take the microcapsules before going to bed, and the capsules collect physiological data such as heart rate, body temperature, and digestive system status within the body.

[0206] The collected data is transmitted to an external device using Bluetooth. This external device could be a smartphone or tablet. The device encrypts the received data and transfers it to a dedicated server via the internet.

[0207] The server analyzes the received data using artificial intelligence (AI). This AI utilizes a generative AI model and is capable of not only detecting physiological abnormalities but also evaluating the user's emotional state through an emotion engine. The emotional state is inferred from changes in heart rate variability and body temperature, and the analysis results are generated as a detailed health status report. This report includes not only potential physical abnormalities but also stress levels and emotional trends.

[0208] Health status reports are provided to users along with individually personalized health management advice. This advice can include specific guidelines to help with daily life. For example, if a user has a persistently elevated heart rate, they might receive advice such as, "Increase your stretching time today to stabilize your heart rate." This information is shared not only with the user but also with healthcare professionals as needed.

[0209] For example, if the server determines that a user may be experiencing a lot of stress based on their body temperature fluctuations, it can include a suggestion in the health report such as, "To improve your sleep, please reduce your caffeine intake." An example of a prompt would be, "Based on today's data, create a detailed report on user B's health and emotional state and add personalized advice," which could be given to the generating AI model.

[0210] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0211] Step 1:

[0212] The user takes a microcapsule containing a biometric sensor before going to sleep. This capsule collects physiological data such as heart rate, body temperature, and digestive system status within the body. The input is the capsule taken by the user, and the output is the biometric data acquired within the body. The capsule prepares to transmit the collected data to an external terminal.

[0213] Step 2:

[0214] An external terminal receives biometric data transmitted from the microcapsule via Bluetooth. The input acquired by the terminal is the biometric data sent from the capsule, and the output is data that has been encrypted and is ready to be sent to the server. This data is encrypted for security purposes.

[0215] Step 3:

[0216] The terminal transfers encrypted data to the server via the internet. The input here is the data received and encrypted by the terminal, and the output is the secure data that reaches the server. The terminal confirms the completion of the data transfer.

[0217] Step 4:

[0218] The server analyzes the received biometric data using a generating AI model. Here, an emotion engine is driven based on changes in heart rate and body temperature, with the received data as input and the analysis results as output. The specific actions performed by the server include data classification, anomaly detection, and emotion prediction generation.

[0219] Step 5:

[0220] The server generates a health status report based on the analysis results. The input is the analysis results obtained in step 4, and the output is a detailed health status report. This report includes information on emotional state and physical abnormalities, as well as personalized health management advice. The server organizes this information and prepares for the next step.

[0221] Step 6:

[0222] Users receive health status reports via an external device. The input is a health status report sent from the server, and the output is specific health management advice displayed to the user. Users can use this information to improve their lifestyle and implement stress reduction measures.

[0223] 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.

[0224] 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.

[0225] 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.

[0226] [Second Embodiment]

[0227] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0228] 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.

[0229] 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).

[0230] 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.

[0231] 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.

[0232] 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).

[0233] 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.

[0234] 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.

[0235] 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.

[0236] 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.

[0237] 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.

[0238] 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".

[0239] This invention is a system that incorporates multiple biosensors within a microcapsule ingested by the user, and transmits biometric data acquired from within the body to an external device using communication technology. This makes it possible to monitor the user's health status in real time and provide appropriate responses based on the analysis results.

[0240] The main system consists of microcapsules, external devices (smartphones and wearable devices), a server, and an analysis system including artificial intelligence.

[0241] Capsule Function

[0242] Users take microcapsules before going to sleep. The capsules have the function of continuously acquiring biometric data such as heart rate, body temperature, and blood components within the body. This data is transmitted to an external device using wireless communication.

[0243] Role of external devices

[0244] The device has the function of receiving data from the capsule and transmitting that data to a server via the internet. Through a pre-installed application, the device provides an interface for visualizing the user's health information and receiving real-time notifications.

[0245] Data analysis using servers and artificial intelligence

[0246] The server immediately analyzes the received biometric data using AI. The analysis system compares it with past user data and identifies any data that deviates from normal values ​​as abnormal. If an abnormality is detected, an automatic notification is sent to the medical institution or the attending physician.

[0247] Based on the analyzed data, the server generates a detailed health report. This report includes personalized health management advice for the user and is sent to the user's device.

[0248] Specific example

[0249] For example, if a user has a chronic heart condition and needs to monitor their daily heart rate, the data collected by the microcapsules is analyzed regularly. If a higher-than-normal heart rate is detected one night, the server identifies it as an anomaly and immediately sends a notification to the user and their doctor. Based on this information, the user can receive appropriate medical attention early on. This system contributes to maintaining the user's health by supporting daily health management and simplifying access to medical care.

[0250] The following describes the processing flow.

[0251] Step 1:

[0252] The user takes a microcapsule before going to sleep. The capsule prepares to collect biometric data such as heart rate, body temperature, digestive system status, and blood components in real time within the body.

[0253] Step 2:

[0254] The device receives biometric data transmitted wirelessly from the capsule. During reception, it checks the battery level and communication status to confirm that the data has been received correctly.

[0255] Step 3:

[0256] The device temporarily stores the received biometric data and transmits it to a server via the internet. The data is encrypted during transmission to protect privacy.

[0257] Step 4:

[0258] The server begins processing the received biometric data for analysis. It performs data format conversion and initial filtering of outliers, preparing the data for analysis.

[0259] Step 5:

[0260] The artificial intelligence installed on the server analyzes the data. It compares it with past data to detect changes in patterns and anomalies. If an anomaly is found, it evaluates the type of anomaly and its urgency.

[0261] Step 6:

[0262] The server generates an alert when an anomaly is detected and sends a notification to the designated physician or healthcare facility. This includes a summary of the analysis results and recommended next steps.

[0263] Step 7:

[0264] The server generates a daily health report. The report includes an overview of your daily health status, any abnormalities, and advice for improving your health.

[0265] Step 8:

[0266] The server sends the generated health report to the terminal. The user receives this report and can get feedback on their daily health status and areas for improvement.

[0267] Step 9:

[0268] If a user deems it necessary, they will be able to book online medical appointments and have remote consultations with their doctor via their device.

[0269] (Example 1)

[0270] 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."

[0271] In modern medicine, there is a need for rapid and accurate monitoring of health conditions, but there is a lack of technology to continuously acquire biometric data in daily life and detect abnormalities in real time. Furthermore, when an abnormality is detected, it is necessary to quickly notify medical professionals and provide individually tailored health management guidance, but the means to efficiently achieve this have been limited.

[0272] 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.

[0273] In this invention, the server includes means for acquiring internal bodily information using a small device with a built-in biosensor, means for transmitting the internal bodily information to an external device, and means for a machine learning model that analyzes the internal bodily information received by the external device. This enables real-time monitoring of the user's health status and, if an abnormality is detected, prompt notification to medical professionals and provision of individually tailored health management guidance.

[0274] A "biosensor" is a device used to measure the internal state of the body, and has the function of acquiring information such as heart rate, body temperature, and blood components.

[0275] A "miniature device" is a device designed to be small enough to penetrate the human body, containing biosensors, and used to collect biological data.

[0276] "Internal bodily information" refers to data on physiological indicators such as heart rate and body temperature, and is fundamental information for evaluating an individual's health status.

[0277] An "external device" is a device that receives information transmitted from a small device and functions as a platform for analyzing that information.

[0278] A "machine learning model" is a system composed of algorithms that learn patterns using large amounts of data and perform predictions and analyses on new data.

[0279] A "health report" is a document that summarizes the health status and any abnormalities based on the results of biometric data obtained through analysis, and provides guidance based on those results.

[0280] "Communication" refers to the process of sending and receiving information, and is particularly relevant when an anomaly is detected and the information is transmitted to medical professionals.

[0281] "Medical professionals" refer to occupational workers who possess specialized medical knowledge and skills, including doctors and nurses.

[0282] The "adapted health management guidance" refers to specific advice for maintaining and improving health customized according to an individual's health condition based on the analysis results.

[0283] This invention provides a system for real-time monitoring of health status. First, the user takes a small device equipped with a biosensor. This small device continuously acquires biological information and wirelessly transmits the information to an external device. At that time, the data acquired as internal body information are important physiological indexes such as heart rate, body temperature, and blood components.

[0284] The external device uses common hardware such as a smartphone or a wearable device. The terminal has a function of transmitting the biological information received from this small device to a server via the Internet. The server uses a machine learning model constructed in a programming language such as Python to analyze the received data. Through this analysis, when a value outside the normal range is detected, the server immediately identifies the abnormality and automatically makes a communication call.

[0285] The generated health report provides adapted health management guidance to the user. This guidance includes advice on specific health problems and recommended daily management methods. The user can view the health report through an application on the terminal and take early medical measures as needed.

[0286] As a specific example, consider the case where a user aims to detect heart disease at an early stage by using this system. The small device acquires the heart rate at night, and if an abnormality is detected, a notification is sent by the server to the doctor in charge. Based on this information, the user can quickly take appropriate medical measures.

[0287] An example of a prompt when using a generative AI model would be: "How can we design a system that uses an advanced anomaly detection algorithm to identify abnormal values ​​based on heart rate data acquired by a small device taken by the user, and notifies the user in real time?"

[0288] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0289] Step 1:

[0290] The user ingests a small device, which acquires biometric information within the body. Inputs include heart rate, body temperature, and blood components, which are measured by sensors. The output is digital data of this biometric information. Specifically, the device's sensors acquire these values ​​in real time and temporarily store them in internal memory.

[0291] Step 2:

[0292] The terminal wirelessly receives biometric information from a small device. The input to this process is the digitized biometric data transmitted by the small device. The output is this data stored within the terminal. Specifically, the terminal establishes communication with the small device via Bluetooth or NFC and downloads the data.

[0293] Step 3:

[0294] The device transmits the received biometric information to the server. The input is the biometric data stored on the device. The output is the biometric data that has been successfully transferred to the server. Specifically, the device securely transmits the data to the server using the HTTPS protocol via an internet connection.

[0295] Step 4:

[0296] The server analyzes the received biometric data. The input is the biometric information sent to the server. The output is the analysis result, including whether or not there are abnormalities and an assessment of health status. The server processes the data using machine learning models and compares this data with historical records. The specific operation for detecting abnormalities involves using algorithms to find deviations from the normal range.

[0297] Step 5:

[0298] The server sends a notification and generates a health report when an anomaly is detected. The input is analyzed biometric data. The output is a notification message and the generated health report. Specifically, the server sends email and application push notifications to users and healthcare professionals. The report also includes individually tailored health management advice.

[0299] Step 6:

[0300] The user checks their health report on their device and takes medical action as needed. The input is the health report sent from the server to the device. The output is the medical action the user requires. Specifically, the user views the report using a dedicated application on their device and contacts a medical institution when they receive a notification.

[0301] (Application Example 1)

[0302] 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."

[0303] There is a need for a system that can monitor the health status of the elderly and patients requiring care in real time and quickly detect abnormalities. However, existing systems have shortcomings in data collection and analysis, making early detection of abnormalities and appropriate responses difficult.

[0304] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0305] In this invention, the server includes means for acquiring internal data using a capsule in which a biological information collection device is incorporated, external device means for communicating the internal data, and artificial intelligence means for evaluating the internal data received by the external device. Thereby, the change in the user's physical condition can be grasped in real time, and early measures can be taken.

[0306] The "biological information collection device" is a device that is disposed inside the body and acquires data related to the user's health condition.

[0307] The "capsule" is a small container that can be taken into the body by the user and incorporates a biological information collection device.

[0308] The "internal data" is data such as the heart rate, body temperature, and other health-related information directly acquired from the user's body.

[0309] The "external device means" is a device for receiving and communicating the internal data acquired from the capsule, and a smartphone or a wearable device corresponds to it.

[0310] The "artificial intelligence means" refers to an algorithm or technology for analyzing and evaluating the received data, and is a system used for detecting abnormalities and giving instructions for health management.

[0311] A "warning" is a notification or alert issued when an abnormality is detected, and is output to the user or a caregiver.

[0312] A "health status report" is a detailed health status report generated based on the analyzed data and includes information useful for the user's health management.

[0313] A "caregiver" is someone responsible for providing care to a user, and typically refers to a caregiver or nurse.

[0314] A "user" is an individual whose health status is monitored by this system, and this mainly includes elderly people and patients who require health management.

[0315] This invention is realized by a capsule containing a biometric information collection device that is ingested by the user. The capsule acquires internal data such as heart rate and body temperature while inside the user's body. The acquired data is transmitted to an external device, such as a smartphone or wearable device, using Wi-Fi or Bluetooth.

[0316] The terminal transmits the received internal data to the server via the internet. The server analyzes the data using artificial intelligence and evaluates the user's health status. This analysis compares the data with past data to determine whether or not there are any abnormalities. If an abnormality is detected, the server automatically sends a warning to the caregiver. The server also generates a detailed health status report based on the evaluation results and sends it to the terminal.

[0317] This health status report is designed to make it easier for users and caregivers to understand the situation and includes personalized health management instructions. A specific example of its use is in a care facility where elderly individuals are using the system. This system can monitor changes in health in real time, even at night, and immediately notifies care staff of any abnormalities, enabling early medical intervention.

[0318] An example of a prompt message would be, "Please describe the concept of an application that analyzes health monitoring data of elderly people in real time and immediately notifies if an abnormality is detected."

[0319] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0320] Step 1:

[0321] The user takes a capsule. Inside the body, the capsule uses a biometric data collection device to acquire internal data such as heart rate and body temperature. The input is the body's internal biometric information, and the output is the acquired biometric data. This data is temporarily stored inside the capsule.

[0322] Step 2:

[0323] The terminal wirelessly receives internal data from the capsule. The input is biometric data from the capsule, and the output is data stored in the terminal. The terminal prepares to transmit this data to a server via the internet.

[0324] Step 3:

[0325] The server receives internal data transmitted from the terminal. The input is health data from the terminal, and the output is biometric information as received data. The server stores this data in a database for analysis.

[0326] Step 4:

[0327] The server uses artificial intelligence to compare and analyze received data against past records. The input consists of biometric information and historical database data, while the output is anomaly detection information as a result of the analysis. In this step, a generative AI model is used to identify anomaly patterns.

[0328] Step 5:

[0329] If the server detects an anomaly, it automatically notifies the caregiver. The input is the anomaly information from the analysis results, and the output is a notification message as a warning. Notifications are sent via email or push notifications from a dedicated application.

[0330] Step 6:

[0331] The server generates a health status report based on the analysis results and sends it to the terminal. The input is the analysis results, and the output is a health status report for the user. The report includes individually tailored health management instructions.

[0332] Step 7:

[0333] The terminal receives health status reports, which are then reviewed by the user and caregivers. The input is the health status report from the server, and the output is the health information received by the user. The terminal visualizes this information and provides it to the user.

[0334] The above steps enable real-time monitoring of the user's health status, allowing for early detection of anomalies and rapid response.

[0335] 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.

[0336] This invention integrates an emotion engine into a system that acquires various in vivo data using microcapsules ingested by the user, thereby enabling deeper analysis and management of health conditions. The system consists of microcapsules, an external device, artificial intelligence on a server, and an emotion engine.

[0337] Capsule Function

[0338] Users take a microcapsule equipped with a biosensor before going to sleep. This capsule has the function of acquiring biometric data such as heart rate, body temperature, digestive system status, and blood components in real time and transmitting it to an external device.

[0339] Role of external devices

[0340] The device wirelessly receives data from the microcapsules. The received data is transmitted to the server in an encrypted form. Furthermore, the device displays notifications to the user and provides feedback on the user's health status.

[0341] Data analysis using servers and artificial intelligence

[0342] The server analyzes the received data using AI. This analysis not only detects abnormalities in physiological data but also includes recognizing the user's emotional state through an emotion engine. The emotion engine analyzes heart rate variability and other biosignals to infer the user's emotional state. This makes it possible to assess the user's mental health as well.

[0343] Use of analysis results

[0344] Based on the analysis results, the server generates a detailed health report. This report includes not only the user's overall health status but also their emotional state, providing personalized health management advice. Furthermore, if an abnormality is detected, the system immediately sends a notification to the attending physician or healthcare provider.

[0345] Specific example

[0346] For example, when a user is experiencing high levels of stress, data is collected from the capsule along with fluctuations in heart rate and body temperature. This data is analyzed by an emotion engine, which determines that the user is experiencing a high level of stress. The server then adds specific advice for stress reduction to the report, providing information that can be used for daily health management. In this way, the system contributes not only to physical health management but also to maintaining mental health.

[0347] The following describes the processing flow.

[0348] Step 1:

[0349] Users take a microcapsule containing a biosensor before going to sleep. This capsule detects heart rate, body temperature, digestive system status, blood components, and other parameters in real time.

[0350] Step 2:

[0351] The device receives biometric data transmitted wirelessly from the capsule. This data includes subtle fluctuations in heart rate and temperature changes, as well as other data necessary for emotion recognition.

[0352] Step 3:

[0353] The device transmits the received biometric data to a server via the internet. The data is encrypted during transmission, ensuring secure transfer.

[0354] Step 4:

[0355] The server analyzes the received data using AI and an emotion engine. The AI ​​detects anomalies in the data, and the emotion engine infers the user's emotional state based on heart rate variability patterns and other biometric data.

[0356] Step 5:

[0357] If the server detects an anomaly based on the analysis results, it will immediately send a notification to the attending physician or medical professional. This notification will also include information about the user's emotional state, allowing the physician to take into account the user's mental condition when responding.

[0358] Step 6:

[0359] The server generates a detailed health report. This report includes analysis of physical health status as well as emotional state, providing information to help users manage their daily health.

[0360] Step 7:

[0361] The server sends the generated health report to the user's device. The user can then receive this report to understand their own health status and identify areas that need improvement.

[0362] Step 8:

[0363] Users can use their devices as needed to book online consultations and medical advice appointments. This is particularly useful for receiving mental health support when emotional disturbances are recognized.

[0364] (Example 2)

[0365] 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".

[0366] In health management, not only physical data but also mental health status is important. However, conventional systems were limited to monitoring only physiological data, making it difficult to grasp the user's emotional state in real time and provide appropriate advice. As a result, comprehensive health management was not adequately provided.

[0367] 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.

[0368] In this invention, the server includes means for using a capsule containing a biosensor for acquiring biometric information, means for transmitting the biometric information to an external device, artificial intelligence means for analyzing the biometric information received by the external device, and emotion estimation means for inferring emotional states. This enables a comprehensive evaluation of physical and emotional health status and the provision of personalized health management advice.

[0369] A "biosensor" is a device used to measure the physiological state of an organism, and has the function of collecting data such as heart rate and body temperature.

[0370] A "capsule" is a small container that has the ability to acquire information from inside the body using built-in sensors and transmit it to the outside.

[0371] An "external device" is a terminal device that receives data transmitted from the capsule and transfers it to the server.

[0372] "Artificial intelligence means" refers to algorithms and technologies used to analyze received data and detect anomalies or infer emotional states.

[0373] "Emotion estimation methods" refer to technologies and algorithms for analyzing biosignals to infer an individual's emotional state.

[0374] "Notification" refers to a means of communication that is sent to users or healthcare professionals when an abnormality is detected.

[0375] A "health report" is a document that provides an overview of a user's health status, generated based on acquired and analyzed biometric data.

[0376] "Personalized health management advice" refers to specific instructions and suggestions for improving one's lifestyle and health, provided based on an individual's health data and emotional state.

[0377] This invention is a system that comprehensively monitors a user's physical and emotional health using a capsule containing a biosensor. The user takes the capsule before going to sleep, and the capsule acquires physiological data such as heart rate and body temperature in real time. The data acquired by the capsule is transmitted to an external device using wireless communication technologies such as Bluetooth or Wi-Fi.

[0378] The terminal securely transfers biometric data received from the capsule to a server. Data transfer uses AES encryption and is conducted via the HTTPS protocol to ensure data confidentiality. The terminal also plays a role in providing health-related feedback to the user.

[0379] The server uses a generative AI model to analyze the received biometric data. This analysis utilizes machine learning algorithms implemented using Python and related libraries. The server not only detects anomalies in physiological data but also evaluates the user's emotional state using emotion estimation tools. As a result, the server generates a detailed health report and notifies the user, while also automatically contacting healthcare professionals in case of abnormalities.

[0380] As a concrete example, consider a case where a user's heart rate increases due to daytime stress. In this case, the capsule records the fluctuations in heart rate and transmits the data to a server via the terminal. The server analyzes the stress level using emotion estimation methods and provides the user with a health report via the terminal, which includes appropriate stress management measures. This report includes personalized advice for reducing the user's stress.

[0381] An example of a prompt for a generative AI model is: "Generate a sample report showing data analysis results for when a user experiences stress in the evening. This report should include details such as heart rate and body temperature, as well as an assessment of the stress level by an emotion engine."

[0382] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0383] Step 1:

[0384] The user ingests a capsule containing a biosensor. The sensor acquires physiological data such as heart rate and body temperature. The user's internal state is provided as input, and biometric data acquired in real time is obtained as output. The sensor acquires this data and prepares for wireless communication.

[0385] Step 2:

[0386] The terminal wirelessly receives biometric data transmitted from the capsule. The input is the biometric data from the capsule, and the output is the encrypted received data. Specifically, the terminal receives the data via Bluetooth or Wi-Fi connection and prepares to securely transfer it to the server using AES encryption.

[0387] Step 3:

[0388] The terminal sends data to the server. The input is encrypted biometric data, and the output is data transfer to the server. The terminal uses the HTTPS protocol to establish a secure communication channel and send data to the server.

[0389] Step 4:

[0390] The server analyzes the received biometric data. The input is encrypted biometric data, and the output is the result of the analyzed health and emotional state. The server uses a generative AI model to analyze the data and perform calculations to detect health abnormalities and emotional fluctuations. The analysis is carried out using programming languages ​​such as Python and machine learning algorithms.

[0391] Step 5:

[0392] The server generates a health report based on the analysis results. The input is the result of the analyzed data, and the output is a detailed report on the user's health and emotional state. The report is generated in a user-friendly format and includes additional instructions or alerts if any anomalies are detected.

[0393] Step 6:

[0394] The server sends generated reports and anomaly notifications to the user via the terminal. Input is the generated health report, and output is explicit health information and possible action suggestions to the user. Furthermore, the system also sends notifications to healthcare professionals as needed. The terminal displays information on the user's screen, providing actionable insights for health management.

[0395] (Application Example 2)

[0396] 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".

[0397] There is a need to continuously and promptly monitor the health status of the elderly and those requiring physical care, and to provide comprehensive support for their physical and mental health management. However, conventional methods have the challenge of not being able to consider not only physical condition but also emotional state, and to provide specific health advice tailored to individual circumstances.

[0398] 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.

[0399] In this invention, the server includes means for acquiring internal bodily data using microcapsules containing biometric information sensors, artificial intelligence means for analyzing the internal bodily data received by an external terminal, and means for performing a detailed evaluation of the health status report, including not only the physical state but also the emotional state. This makes it possible to realize more comprehensive and personalized health management.

[0400] A "biometric information sensor" is a device embedded in a microcapsule to acquire data from inside the body.

[0401] A "microcapsule" is a small capsule containing a bio-information sensor that collects information within the user's body.

[0402] "Internal bodily data" refers to various physiological data obtained from within the body, such as heart rate, body temperature, digestive system status, and blood components.

[0403] An "external terminal" is a communication device that receives internal body data from microcapsules and then transmits it to a server.

[0404] "Artificial intelligence tools" refer to software systems used to perform advanced data analysis and evaluate physical and emotional states.

[0405] A "health status report" is a detailed assessment report generated based on analyzed physiological and emotional data of the body.

[0406] "Emotional state" refers to the emotional state or tendency of the user, inferred from fluctuations in biometric information.

[0407] This invention is a system that uses microcapsules containing biometric sensors to acquire and analyze internal bodily data of elderly individuals and others requiring health management. Users take the microcapsules before going to bed, and the capsules collect physiological data such as heart rate, body temperature, and digestive system status within the body.

[0408] The collected data is transmitted to an external device using Bluetooth. This external device could be a smartphone or tablet. The device encrypts the received data and transfers it to a dedicated server via the internet.

[0409] The server analyzes the received data using artificial intelligence (AI). This AI utilizes a generative AI model and is capable of not only detecting physiological abnormalities but also evaluating the user's emotional state through an emotion engine. The emotional state is inferred from changes in heart rate variability and body temperature, and the analysis results are generated as a detailed health status report. This report includes not only potential physical abnormalities but also stress levels and emotional trends.

[0410] Health status reports are provided to users along with individually personalized health management advice. This advice can include specific guidelines to help with daily life. For example, if a user has a persistently elevated heart rate, they might receive advice such as, "Increase your stretching time today to stabilize your heart rate." This information is shared not only with the user but also with healthcare professionals as needed.

[0411] For example, if the server determines that a user may be experiencing a lot of stress based on their body temperature fluctuations, it can include a suggestion in the health report such as, "To improve your sleep, please reduce your caffeine intake." An example of a prompt would be, "Based on today's data, create a detailed report on user B's health and emotional state and add personalized advice," which could be given to the generating AI model.

[0412] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0413] Step 1:

[0414] The user takes a microcapsule containing a biometric sensor before going to sleep. This capsule collects physiological data such as heart rate, body temperature, and digestive system status within the body. The input is the capsule taken by the user, and the output is the biometric data acquired within the body. The capsule prepares to transmit the collected data to an external terminal.

[0415] Step 2:

[0416] An external terminal receives biometric data transmitted from the microcapsule via Bluetooth. The input acquired by the terminal is the biometric data sent from the capsule, and the output is data that has been encrypted and is ready to be sent to the server. This data is encrypted for security purposes.

[0417] Step 3:

[0418] The terminal transfers encrypted data to the server via the internet. The input here is the data received and encrypted by the terminal, and the output is the secure data that reaches the server. The terminal confirms the completion of the data transfer.

[0419] Step 4:

[0420] The server analyzes the received biometric data using a generating AI model. Here, an emotion engine is driven based on changes in heart rate and body temperature, with the received data as input and the analysis results as output. The specific actions performed by the server include data classification, anomaly detection, and emotion prediction generation.

[0421] Step 5:

[0422] The server generates a health status report based on the analysis results. The input is the analysis results obtained in step 4, and the output is a detailed health status report. This report includes information on emotional state and physical abnormalities, as well as personalized health management advice. The server organizes this information and prepares for the next step.

[0423] Step 6:

[0424] Users receive health status reports via an external device. The input is a health status report sent from the server, and the output is specific health management advice displayed to the user. Users can use this information to improve their lifestyle and implement stress reduction measures.

[0425] 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.

[0426] 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.

[0427] 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.

[0428] [Third Embodiment]

[0429] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0430] 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.

[0431] 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).

[0432] 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.

[0433] 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.

[0434] 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).

[0435] 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.

[0436] 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.

[0437] 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.

[0438] 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.

[0439] 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.

[0440] 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".

[0441] This invention is a system that incorporates multiple biosensors within a microcapsule ingested by the user, and transmits biometric data acquired from within the body to an external device using communication technology. This makes it possible to monitor the user's health status in real time and provide appropriate responses based on the analysis results.

[0442] The main system consists of microcapsules, external devices (smartphones and wearable devices), a server, and an analysis system including artificial intelligence.

[0443] Capsule Function

[0444] Users take microcapsules before going to sleep. The capsules have the function of continuously acquiring biometric data such as heart rate, body temperature, and blood components within the body. This data is transmitted to an external device using wireless communication.

[0445] Role of external devices

[0446] The device has the function of receiving data from the capsule and transmitting that data to a server via the internet. Through a pre-installed application, the device provides an interface for visualizing the user's health information and receiving real-time notifications.

[0447] Data analysis using servers and artificial intelligence

[0448] The server immediately analyzes the received biometric data using AI. The analysis system compares it with past user data and identifies any data that deviates from normal values ​​as abnormal. If an abnormality is detected, an automatic notification is sent to the medical institution or the attending physician.

[0449] Based on the analyzed data, the server generates a detailed health report. This report includes personalized health management advice for the user and is sent to the user's device.

[0450] Specific example

[0451] For example, if a user has a chronic heart condition and needs to monitor their daily heart rate, the data collected by the microcapsules is analyzed regularly. If a higher-than-normal heart rate is detected one night, the server identifies it as an anomaly and immediately sends a notification to the user and their doctor. Based on this information, the user can receive appropriate medical attention early on. This system contributes to maintaining the user's health by supporting daily health management and simplifying access to medical care.

[0452] The following describes the processing flow.

[0453] Step 1:

[0454] The user takes a microcapsule before going to sleep. The capsule prepares to collect biometric data such as heart rate, body temperature, digestive system status, and blood components in real time within the body.

[0455] Step 2:

[0456] The device receives biometric data transmitted wirelessly from the capsule. During reception, it checks the battery level and communication status to confirm that the data has been received correctly.

[0457] Step 3:

[0458] The device temporarily stores the received biometric data and transmits it to a server via the internet. The data is encrypted during transmission to protect privacy.

[0459] Step 4:

[0460] The server begins processing the received biometric data for analysis. It performs data format conversion and initial filtering of outliers, preparing the data for analysis.

[0461] Step 5:

[0462] The artificial intelligence installed on the server analyzes the data. It compares it with past data to detect changes in patterns and anomalies. If an anomaly is found, it evaluates the type of anomaly and its urgency.

[0463] Step 6:

[0464] The server generates an alert when an anomaly is detected and sends a notification to the designated physician or healthcare facility. This includes a summary of the analysis results and recommended next steps.

[0465] Step 7:

[0466] The server generates a daily health report. The report includes an overview of your daily health status, any abnormalities, and advice for improving your health.

[0467] Step 8:

[0468] The server sends the generated health report to the terminal. The user receives this report and can get feedback on their daily health status and areas for improvement.

[0469] Step 9:

[0470] If a user deems it necessary, they will be able to book online medical appointments and have remote consultations with their doctor via their device.

[0471] (Example 1)

[0472] 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."

[0473] In modern medicine, there is a need for rapid and accurate monitoring of health conditions, but there is a lack of technology to continuously acquire biometric data in daily life and detect abnormalities in real time. Furthermore, when an abnormality is detected, it is necessary to quickly notify medical professionals and provide individually tailored health management guidance, but the means to efficiently achieve this have been limited.

[0474] 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.

[0475] In this invention, the server includes means for acquiring internal bodily information using a small device with a built-in biosensor, means for transmitting the internal bodily information to an external device, and means for a machine learning model that analyzes the internal bodily information received by the external device. This enables real-time monitoring of the user's health status and, if an abnormality is detected, prompt notification to medical professionals and provision of individually tailored health management guidance.

[0476] A "biosensor" is a device used to measure the internal state of the body, and has the function of acquiring information such as heart rate, body temperature, and blood components.

[0477] A "miniature device" is a device designed to be small enough to penetrate the human body, containing biosensors, and used to collect biological data.

[0478] "Internal bodily information" refers to data on physiological indicators such as heart rate and body temperature, and is fundamental information for evaluating an individual's health status.

[0479] An "external device" is a device that receives information transmitted from a small device and functions as a platform for analyzing that information.

[0480] A "machine learning model" is a system composed of algorithms that learn patterns using large amounts of data and perform predictions and analyses on new data.

[0481] A "health report" is a document that summarizes the health status and any abnormalities based on the results of biometric data obtained through analysis, and provides guidance based on those results.

[0482] "Communication" refers to the process of sending and receiving information, and is particularly relevant when an anomaly is detected and the information is transmitted to medical professionals.

[0483] "Medical professionals" refer to occupational workers who possess specialized medical knowledge and skills, including doctors and nurses.

[0484] "Adapted health management guidance" refers to specific advice for maintaining or improving health that is customized to an individual's health condition based on the analysis results.

[0485] This invention provides a system for monitoring health status in real time. The user first takes a small device containing a biosensor. This device continuously acquires biometric information and wirelessly transmits it to an external device. The data acquired as internal bodily information includes important physiological indicators such as heart rate, body temperature, and blood components.

[0486] The external device uses common hardware such as smartphones and wearable devices. The terminal has the function of transmitting biometric information received from this small device to a server via the internet. The server uses a machine learning model built with a programming language such as Python to analyze the received data. If this analysis detects values ​​outside the normal range, the server immediately identifies the anomaly and automatically sends a communication.

[0487] The generated health report provides users with tailored health management guidance. This guidance includes advice on specific health problems and recommended daily management methods. Users can view the health report through an application on their device and take early medical action if necessary.

[0488] As a concrete example, consider a scenario where a user utilizes this system to aim for early detection of heart disease. The small device acquires heart rate data at night, and if an abnormality is detected, a notification is sent to the attending physician via the server. Based on this information, the user can take prompt and appropriate medical action.

[0489] An example of a prompt when using a generative AI model would be: "How can we design a system that uses an advanced anomaly detection algorithm to identify abnormal values ​​based on heart rate data acquired by a small device taken by the user, and notifies the user in real time?"

[0490] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0491] Step 1:

[0492] The user ingests a small device, which acquires biometric information within the body. Inputs include heart rate, body temperature, and blood components, which are measured by sensors. The output is digital data of this biometric information. Specifically, the device's sensors acquire these values ​​in real time and temporarily store them in internal memory.

[0493] Step 2:

[0494] The terminal wirelessly receives biometric information from a small device. The input to this process is the digitized biometric data transmitted by the small device. The output is this data stored within the terminal. Specifically, the terminal establishes communication with the small device via Bluetooth or NFC and downloads the data.

[0495] Step 3:

[0496] The device transmits the received biometric information to the server. The input is the biometric data stored on the device. The output is the biometric data that has been successfully transferred to the server. Specifically, the device securely transmits the data to the server using the HTTPS protocol via an internet connection.

[0497] Step 4:

[0498] The server analyzes the received biometric data. The input is the biometric information sent to the server. The output is the analysis result, including whether or not there are abnormalities and an assessment of health status. The server processes the data using machine learning models and compares this data with historical records. The specific operation for detecting abnormalities involves using algorithms to find deviations from the normal range.

[0499] Step 5:

[0500] The server sends a notification and generates a health report when an anomaly is detected. The input is analyzed biometric data. The output is a notification message and the generated health report. Specifically, the server sends email and application push notifications to users and healthcare professionals. The report also includes individually tailored health management advice.

[0501] Step 6:

[0502] The user checks their health report on their device and takes medical action as needed. The input is the health report sent from the server to the device. The output is the medical action the user requires. Specifically, the user views the report using a dedicated application on their device and contacts a medical institution when they receive a notification.

[0503] (Application Example 1)

[0504] 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."

[0505] There is a need for a system that can monitor the health status of the elderly and patients requiring care in real time and quickly detect abnormalities. However, existing systems have shortcomings in data collection and analysis, making early detection of abnormalities and appropriate responses difficult.

[0506] 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.

[0507] In this invention, the server includes means for acquiring internal data using a capsule containing a biometric information collection device, means for an external device for communicating the internal data, and means for artificial intelligence for evaluating the internal data received by the external device. This enables real-time monitoring of changes in the user's physical condition and allows for early intervention.

[0508] A "biometric information collection device" is a device placed inside the body to acquire data about the user's health status.

[0509] A "capsule" is a small container that can be taken into the body by the user and contains a biometric information collection device.

[0510] "Internal data" refers to data such as heart rate, body temperature, and other health-related information obtained directly from the user's body.

[0511] "External device means" refers to a device for receiving and communicating internal data acquired from the capsule, and includes smartphones and wearable devices.

[0512] "Artificial intelligence means" refers to algorithms and technologies for analyzing and evaluating received data, and is a system used for detecting anomalies and providing instructions for health management.

[0513] A "warning" is a notification or alert issued when an abnormality is detected, and is sent to the user or caregiver.

[0514] A "health status report" is a detailed health status report generated based on analyzed data, and it contains information useful for the user's health management.

[0515] A "caregiver" is someone responsible for providing care to a user, and typically refers to a caregiver or nurse.

[0516] A "user" is an individual whose health status is monitored by this system, and this mainly includes elderly people and patients who require health management.

[0517] This invention is realized by a capsule containing a biometric information collection device that is ingested by the user. The capsule acquires internal data such as heart rate and body temperature while inside the user's body. The acquired data is transmitted to an external device, such as a smartphone or wearable device, using Wi-Fi or Bluetooth.

[0518] The terminal transmits the received internal data to the server via the internet. The server analyzes the data using artificial intelligence and evaluates the user's health status. This analysis compares the data with past data to determine whether or not there are any abnormalities. If an abnormality is detected, the server automatically sends a warning to the caregiver. The server also generates a detailed health status report based on the evaluation results and sends it to the terminal.

[0519] This health status report is designed to make it easier for users and caregivers to understand the situation and includes personalized health management instructions. A specific example of its use is in a care facility where elderly individuals are using the system. This system can monitor changes in health in real time, even at night, and immediately notifies care staff of any abnormalities, enabling early medical intervention.

[0520] An example of a prompt message would be, "Please describe the concept of an application that analyzes health monitoring data of elderly people in real time and immediately notifies if an abnormality is detected."

[0521] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0522] Step 1:

[0523] The user takes a capsule. Inside the body, the capsule uses a biometric data collection device to acquire internal data such as heart rate and body temperature. The input is the body's internal biometric information, and the output is the acquired biometric data. This data is temporarily stored inside the capsule.

[0524] Step 2:

[0525] The terminal wirelessly receives internal data from the capsule. The input is biometric data from the capsule, and the output is data stored in the terminal. The terminal prepares to transmit this data to a server via the internet.

[0526] Step 3:

[0527] The server receives internal data transmitted from the terminal. The input is health data from the terminal, and the output is biometric information as received data. The server stores this data in a database for analysis.

[0528] Step 4:

[0529] The server uses artificial intelligence to compare and analyze received data against past records. The input consists of biometric information and historical database data, while the output is anomaly detection information as a result of the analysis. In this step, a generative AI model is used to identify anomaly patterns.

[0530] Step 5:

[0531] If the server detects an anomaly, it automatically notifies the caregiver. The input is the anomaly information from the analysis results, and the output is a notification message as a warning. Notifications are sent via email or push notifications from a dedicated application.

[0532] Step 6:

[0533] The server generates a health status report based on the analysis results and sends it to the terminal. The input is the analysis results, and the output is a health status report for the user. The report includes individually tailored health management instructions.

[0534] Step 7:

[0535] The terminal receives health status reports, which are then reviewed by the user and caregivers. The input is the health status report from the server, and the output is the health information received by the user. The terminal visualizes this information and provides it to the user.

[0536] The above steps enable real-time monitoring of the user's health status, allowing for early detection of anomalies and rapid response.

[0537] 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.

[0538] This invention integrates an emotion engine into a system that acquires various in vivo data using microcapsules ingested by the user, thereby enabling deeper analysis and management of health conditions. The system consists of microcapsules, an external device, artificial intelligence on a server, and an emotion engine.

[0539] Capsule Function

[0540] Users take a microcapsule equipped with a biosensor before going to sleep. This capsule has the function of acquiring biometric data such as heart rate, body temperature, digestive system status, and blood components in real time and transmitting it to an external device.

[0541] Role of external devices

[0542] The device wirelessly receives data from the microcapsules. The received data is transmitted to the server in an encrypted form. Furthermore, the device displays notifications to the user and provides feedback on the user's health status.

[0543] Data analysis using servers and artificial intelligence

[0544] The server analyzes the received data using AI. This analysis not only detects abnormalities in physiological data but also includes recognizing the user's emotional state through an emotion engine. The emotion engine analyzes heart rate variability and other biosignals to infer the user's emotional state. This makes it possible to assess the user's mental health as well.

[0545] Use of analysis results

[0546] Based on the analysis results, the server generates a detailed health report. This report includes not only the user's overall health status but also their emotional state, providing personalized health management advice. Furthermore, if an abnormality is detected, the system immediately sends a notification to the attending physician or healthcare provider.

[0547] Specific example

[0548] For example, when a user is experiencing high levels of stress, data is collected from the capsule along with fluctuations in heart rate and body temperature. This data is analyzed by an emotion engine, which determines that the user is experiencing a high level of stress. The server then adds specific advice for stress reduction to the report, providing information that can be used for daily health management. In this way, the system contributes not only to physical health management but also to maintaining mental health.

[0549] The following describes the processing flow.

[0550] Step 1:

[0551] Users take a microcapsule containing a biosensor before going to sleep. This capsule detects heart rate, body temperature, digestive system status, blood components, and other parameters in real time.

[0552] Step 2:

[0553] The device receives biometric data transmitted wirelessly from the capsule. This data includes subtle fluctuations in heart rate and temperature changes, as well as other data necessary for emotion recognition.

[0554] Step 3:

[0555] The device transmits the received biometric data to a server via the internet. The data is encrypted during transmission, ensuring secure transfer.

[0556] Step 4:

[0557] The server analyzes the received data using AI and an emotion engine. The AI ​​detects anomalies in the data, and the emotion engine infers the user's emotional state based on heart rate variability patterns and other biometric data.

[0558] Step 5:

[0559] If the server detects an anomaly based on the analysis results, it will immediately send a notification to the attending physician or medical professional. This notification will also include information about the user's emotional state, allowing the physician to take into account the user's mental condition when responding.

[0560] Step 6:

[0561] The server generates a detailed health report. This report includes analysis of physical health status as well as emotional state, providing information to help users manage their daily health.

[0562] Step 7:

[0563] The server sends the generated health report to the user's device. The user can then receive this report to understand their own health status and identify areas that need improvement.

[0564] Step 8:

[0565] Users can use their devices as needed to book online consultations and medical advice appointments. This is particularly useful for receiving mental health support when emotional disturbances are recognized.

[0566] (Example 2)

[0567] 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."

[0568] In health management, not only physical data but also mental health status is important. However, conventional systems were limited to monitoring only physiological data, making it difficult to grasp the user's emotional state in real time and provide appropriate advice. As a result, comprehensive health management was not adequately provided.

[0569] 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.

[0570] In this invention, the server includes means for using a capsule containing a biosensor for acquiring biometric information, means for transmitting the biometric information to an external device, artificial intelligence means for analyzing the biometric information received by the external device, and emotion estimation means for inferring emotional states. This enables a comprehensive evaluation of physical and emotional health status and the provision of personalized health management advice.

[0571] A "biosensor" is a device used to measure the physiological state of an organism, and has the function of collecting data such as heart rate and body temperature.

[0572] A "capsule" is a small container that has the ability to acquire information from inside the body using built-in sensors and transmit it to the outside.

[0573] An "external device" is a terminal device that receives data transmitted from the capsule and transfers it to the server.

[0574] "Artificial intelligence means" refers to algorithms and technologies used to analyze received data and detect anomalies or infer emotional states.

[0575] "Emotion estimation methods" refer to technologies and algorithms for analyzing biosignals to infer an individual's emotional state.

[0576] "Notification" refers to a means of communication that is sent to users or healthcare professionals when an abnormality is detected.

[0577] A "health report" is a document that provides an overview of a user's health status, generated based on acquired and analyzed biometric data.

[0578] "Personalized health management advice" refers to specific instructions and suggestions for improving one's lifestyle and health, provided based on an individual's health data and emotional state.

[0579] This invention is a system that comprehensively monitors a user's physical and emotional health using a capsule containing a biosensor. The user takes the capsule before going to sleep, and the capsule acquires physiological data such as heart rate and body temperature in real time. The data acquired by the capsule is transmitted to an external device using wireless communication technologies such as Bluetooth or Wi-Fi.

[0580] The terminal securely transfers biometric data received from the capsule to a server. Data transfer uses AES encryption and is conducted via the HTTPS protocol to ensure data confidentiality. The terminal also plays a role in providing health-related feedback to the user.

[0581] The server uses a generative AI model to analyze the received biometric data. This analysis utilizes machine learning algorithms implemented using Python and related libraries. The server not only detects anomalies in physiological data but also evaluates the user's emotional state using emotion estimation tools. As a result, the server generates a detailed health report and notifies the user, while also automatically contacting healthcare professionals in case of abnormalities.

[0582] As a concrete example, consider a case where a user's heart rate increases due to daytime stress. In this case, the capsule records the fluctuations in heart rate and transmits the data to a server via the terminal. The server analyzes the stress level using emotion estimation methods and provides the user with a health report via the terminal, which includes appropriate stress management measures. This report includes personalized advice for reducing the user's stress.

[0583] An example of a prompt for a generative AI model is: "Generate a sample report showing data analysis results for when a user experiences stress in the evening. This report should include details such as heart rate and body temperature, as well as an assessment of the stress level by an emotion engine."

[0584] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0585] Step 1:

[0586] The user ingests a capsule containing a biosensor. The sensor acquires physiological data such as heart rate and body temperature. The user's internal state is provided as input, and biometric data acquired in real time is obtained as output. The sensor acquires this data and prepares for wireless communication.

[0587] Step 2:

[0588] The terminal wirelessly receives biometric data transmitted from the capsule. The input is the biometric data from the capsule, and the output is the encrypted received data. Specifically, the terminal receives the data via Bluetooth or Wi-Fi connection and prepares to securely transfer it to the server using AES encryption.

[0589] Step 3:

[0590] The terminal sends data to the server. The input is encrypted biometric data, and the output is data transfer to the server. The terminal uses the HTTPS protocol to establish a secure communication channel and send data to the server.

[0591] Step 4:

[0592] The server analyzes the received biometric data. The input is encrypted biometric data, and the output is the result of the analyzed health and emotional state. The server uses a generative AI model to analyze the data and perform calculations to detect health abnormalities and emotional fluctuations. The analysis is carried out using programming languages ​​such as Python and machine learning algorithms.

[0593] Step 5:

[0594] The server generates a health report based on the analysis results. The input is the result of the analyzed data, and the output is a detailed report on the user's health and emotional state. The report is generated in a user-friendly format and includes additional instructions or alerts if any anomalies are detected.

[0595] Step 6:

[0596] The server sends generated reports and anomaly notifications to the user via the terminal. Input is the generated health report, and output is explicit health information and possible action suggestions to the user. Furthermore, the system also sends notifications to healthcare professionals as needed. The terminal displays information on the user's screen, providing actionable insights for health management.

[0597] (Application Example 2)

[0598] 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."

[0599] There is a need to continuously and promptly monitor the health status of the elderly and those requiring physical care, and to provide comprehensive support for their physical and mental health management. However, conventional methods have the challenge of not being able to consider not only physical condition but also emotional state, and to provide specific health advice tailored to individual circumstances.

[0600] 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.

[0601] In this invention, the server includes means for acquiring internal bodily data using microcapsules containing biometric information sensors, artificial intelligence means for analyzing the internal bodily data received by an external terminal, and means for performing a detailed evaluation of the health status report, including not only the physical state but also the emotional state. This makes it possible to realize more comprehensive and personalized health management.

[0602] A "biometric information sensor" is a device embedded in a microcapsule to acquire data from inside the body.

[0603] A "microcapsule" is a small capsule containing a bio-information sensor that collects information within the user's body.

[0604] "Internal bodily data" refers to various physiological data obtained from within the body, such as heart rate, body temperature, digestive system status, and blood components.

[0605] An "external terminal" is a communication device that receives internal body data from microcapsules and then transmits it to a server.

[0606] "Artificial intelligence tools" refer to software systems used to perform advanced data analysis and evaluate physical and emotional states.

[0607] A "health status report" is a detailed assessment report generated based on analyzed physiological and emotional data of the body.

[0608] "Emotional state" refers to the emotional state or tendency of the user, inferred from fluctuations in biometric information.

[0609] This invention is a system that uses microcapsules containing biometric sensors to acquire and analyze internal bodily data of elderly individuals and others requiring health management. Users take the microcapsules before going to bed, and the capsules collect physiological data such as heart rate, body temperature, and digestive system status within the body.

[0610] The collected data is transmitted to an external device using Bluetooth. This external device could be a smartphone or tablet. The device encrypts the received data and transfers it to a dedicated server via the internet.

[0611] The server analyzes the received data using artificial intelligence (AI). This AI utilizes a generative AI model and is capable of not only detecting physiological abnormalities but also evaluating the user's emotional state through an emotion engine. The emotional state is inferred from changes in heart rate variability and body temperature, and the analysis results are generated as a detailed health status report. This report includes not only potential physical abnormalities but also stress levels and emotional trends.

[0612] Health status reports are provided to users along with individually personalized health management advice. This advice can include specific guidelines to help with daily life. For example, if a user has a persistently elevated heart rate, they might receive advice such as, "Increase your stretching time today to stabilize your heart rate." This information is shared not only with the user but also with healthcare professionals as needed.

[0613] For example, if the server determines that a user may be experiencing a lot of stress based on their body temperature fluctuations, it can include a suggestion in the health report such as, "To improve your sleep, please reduce your caffeine intake." An example of a prompt would be, "Based on today's data, create a detailed report on user B's health and emotional state and add personalized advice," which could be given to the generating AI model.

[0614] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0615] Step 1:

[0616] The user takes a microcapsule containing a biometric sensor before going to sleep. This capsule collects physiological data such as heart rate, body temperature, and digestive system status within the body. The input is the capsule taken by the user, and the output is the biometric data acquired within the body. The capsule prepares to transmit the collected data to an external terminal.

[0617] Step 2:

[0618] An external terminal receives biometric data transmitted from the microcapsule via Bluetooth. The input acquired by the terminal is the biometric data sent from the capsule, and the output is data that has been encrypted and is ready to be sent to the server. This data is encrypted for security purposes.

[0619] Step 3:

[0620] The terminal transfers encrypted data to the server via the internet. The input here is the data received and encrypted by the terminal, and the output is the secure data that reaches the server. The terminal confirms the completion of the data transfer.

[0621] Step 4:

[0622] The server analyzes the received biometric data using a generating AI model. Here, an emotion engine is driven based on changes in heart rate and body temperature, with the received data as input and the analysis results as output. The specific actions performed by the server include data classification, anomaly detection, and emotion prediction generation.

[0623] Step 5:

[0624] The server generates a health status report based on the analysis results. The input is the analysis results obtained in step 4, and the output is a detailed health status report. This report includes information on emotional state and physical abnormalities, as well as personalized health management advice. The server organizes this information and prepares for the next step.

[0625] Step 6:

[0626] Users receive health status reports via an external device. The input is a health status report sent from the server, and the output is specific health management advice displayed to the user. Users can use this information to improve their lifestyle and implement stress reduction measures.

[0627] 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.

[0628] 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.

[0629] 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.

[0630] [Fourth Embodiment]

[0631] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0632] 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.

[0633] 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).

[0634] 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.

[0635] 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.

[0636] 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).

[0637] 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.

[0638] 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.

[0639] 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.

[0640] 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.

[0641] 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.

[0642] 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.

[0643] 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".

[0644] This invention is a system that incorporates multiple biosensors within a microcapsule ingested by the user, and transmits biometric data acquired from within the body to an external device using communication technology. This makes it possible to monitor the user's health status in real time and provide appropriate responses based on the analysis results.

[0645] The main system consists of microcapsules, external devices (smartphones and wearable devices), a server, and an analysis system including artificial intelligence.

[0646] Capsule Function

[0647] Users take microcapsules before going to sleep. The capsules have the function of continuously acquiring biometric data such as heart rate, body temperature, and blood components within the body. This data is transmitted to an external device using wireless communication.

[0648] Role of external devices

[0649] The device has the function of receiving data from the capsule and transmitting that data to a server via the internet. Through a pre-installed application, the device provides an interface for visualizing the user's health information and receiving real-time notifications.

[0650] Data analysis using servers and artificial intelligence

[0651] The server immediately analyzes the received biometric data using AI. The analysis system compares it with past user data and identifies any data that deviates from normal values ​​as abnormal. If an abnormality is detected, an automatic notification is sent to the medical institution or the attending physician.

[0652] Based on the analyzed data, the server generates a detailed health report. This report includes personalized health management advice for the user and is sent to the user's device.

[0653] Specific example

[0654] For example, if a user has a chronic heart condition and needs to monitor their daily heart rate, the data collected by the microcapsules is analyzed regularly. If a higher-than-normal heart rate is detected one night, the server identifies it as an anomaly and immediately sends a notification to the user and their doctor. Based on this information, the user can receive appropriate medical attention early on. This system contributes to maintaining the user's health by supporting daily health management and simplifying access to medical care.

[0655] The following describes the processing flow.

[0656] Step 1:

[0657] The user takes a microcapsule before going to sleep. The capsule prepares to collect biometric data such as heart rate, body temperature, digestive system status, and blood components in real time within the body.

[0658] Step 2:

[0659] The device receives biometric data transmitted wirelessly from the capsule. During reception, it checks the battery level and communication status to confirm that the data has been received correctly.

[0660] Step 3:

[0661] The device temporarily stores the received biometric data and transmits it to a server via the internet. The data is encrypted during transmission to protect privacy.

[0662] Step 4:

[0663] The server begins processing the received biometric data for analysis. It performs data format conversion and initial filtering of outliers, preparing the data for analysis.

[0664] Step 5:

[0665] The artificial intelligence installed on the server analyzes the data. It compares it with past data to detect changes in patterns and anomalies. If an anomaly is found, it evaluates the type of anomaly and its urgency.

[0666] Step 6:

[0667] The server generates an alert when an anomaly is detected and sends a notification to the designated physician or healthcare facility. This includes a summary of the analysis results and recommended next steps.

[0668] Step 7:

[0669] The server generates a daily health report. The report includes an overview of your daily health status, any abnormalities, and advice for improving your health.

[0670] Step 8:

[0671] The server sends the generated health report to the terminal. The user receives this report and can get feedback on their daily health status and areas for improvement.

[0672] Step 9:

[0673] If a user deems it necessary, they will be able to book online medical appointments and have remote consultations with their doctor via their device.

[0674] (Example 1)

[0675] 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".

[0676] In modern medicine, there is a need for rapid and accurate monitoring of health conditions, but there is a lack of technology to continuously acquire biometric data in daily life and detect abnormalities in real time. Furthermore, when an abnormality is detected, it is necessary to quickly notify medical professionals and provide individually tailored health management guidance, but the means to efficiently achieve this have been limited.

[0677] 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.

[0678] In this invention, the server includes means for acquiring internal bodily information using a small device with a built-in biosensor, means for transmitting the internal bodily information to an external device, and means for a machine learning model that analyzes the internal bodily information received by the external device. This enables real-time monitoring of the user's health status and, if an abnormality is detected, prompt notification to medical professionals and provision of individually tailored health management guidance.

[0679] A "biosensor" is a device used to measure the internal state of the body, and has the function of acquiring information such as heart rate, body temperature, and blood components.

[0680] A "miniature device" is a device designed to be small enough to penetrate the human body, containing biosensors, and used to collect biological data.

[0681] "Internal bodily information" refers to data on physiological indicators such as heart rate and body temperature, and is fundamental information for evaluating an individual's health status.

[0682] An "external device" is a device that receives information transmitted from a small device and functions as a platform for analyzing that information.

[0683] A "machine learning model" is a system composed of algorithms that learn patterns using large amounts of data and perform predictions and analyses on new data.

[0684] A "health report" is a document that summarizes the health status and any abnormalities based on the results of biometric data obtained through analysis, and provides guidance based on those results.

[0685] "Communication" refers to the process of sending and receiving information, and is particularly relevant when an anomaly is detected and the information is transmitted to medical professionals.

[0686] "Medical professionals" refer to occupational workers who possess specialized medical knowledge and skills, including doctors and nurses.

[0687] "Adapted health management guidance" refers to specific advice for maintaining or improving health that is customized to an individual's health condition based on the analysis results.

[0688] This invention provides a system for monitoring health status in real time. The user first takes a small device containing a biosensor. This device continuously acquires biometric information and wirelessly transmits it to an external device. The data acquired as internal bodily information includes important physiological indicators such as heart rate, body temperature, and blood components.

[0689] The external device uses common hardware such as smartphones and wearable devices. The terminal has the function of transmitting biometric information received from this small device to a server via the internet. The server uses a machine learning model built with a programming language such as Python to analyze the received data. If this analysis detects values ​​outside the normal range, the server immediately identifies the anomaly and automatically sends a communication.

[0690] The generated health report provides users with tailored health management guidance. This guidance includes advice on specific health problems and recommended daily management methods. Users can view the health report through an application on their device and take early medical action if necessary.

[0691] As a concrete example, consider a scenario where a user utilizes this system to aim for early detection of heart disease. The small device acquires heart rate data at night, and if an abnormality is detected, a notification is sent to the attending physician via the server. Based on this information, the user can take prompt and appropriate medical action.

[0692] An example of a prompt when using a generative AI model would be: "How can we design a system that uses an advanced anomaly detection algorithm to identify abnormal values ​​based on heart rate data acquired by a small device taken by the user, and notifies the user in real time?"

[0693] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0694] Step 1:

[0695] The user ingests a small device, which acquires biometric information within the body. Inputs include heart rate, body temperature, and blood components, which are measured by sensors. The output is digital data of this biometric information. Specifically, the device's sensors acquire these values ​​in real time and temporarily store them in internal memory.

[0696] Step 2:

[0697] The terminal wirelessly receives biometric information from a small device. The input to this process is the digitized biometric data transmitted by the small device. The output is this data stored within the terminal. Specifically, the terminal establishes communication with the small device via Bluetooth or NFC and downloads the data.

[0698] Step 3:

[0699] The device transmits the received biometric information to the server. The input is the biometric data stored on the device. The output is the biometric data that has been successfully transferred to the server. Specifically, the device securely transmits the data to the server using the HTTPS protocol via an internet connection.

[0700] Step 4:

[0701] The server analyzes the received biometric data. The input is the biometric information sent to the server. The output is the analysis result, including whether or not there are abnormalities and an assessment of health status. The server processes the data using machine learning models and compares this data with historical records. The specific operation for detecting abnormalities involves using algorithms to find deviations from the normal range.

[0702] Step 5:

[0703] The server sends a notification and generates a health report when an anomaly is detected. The input is analyzed biometric data. The output is a notification message and the generated health report. Specifically, the server sends email and application push notifications to users and healthcare professionals. The report also includes individually tailored health management advice.

[0704] Step 6:

[0705] The user checks their health report on their device and takes medical action as needed. The input is the health report sent from the server to the device. The output is the medical action the user requires. Specifically, the user views the report using a dedicated application on their device and contacts a medical institution when they receive a notification.

[0706] (Application Example 1)

[0707] 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".

[0708] There is a need for a system that can monitor the health status of the elderly and patients requiring care in real time and quickly detect abnormalities. However, existing systems have shortcomings in data collection and analysis, making early detection of abnormalities and appropriate responses difficult.

[0709] 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.

[0710] In this invention, the server includes means for acquiring internal data using a capsule containing a biometric information collection device, means for an external device for communicating the internal data, and means for artificial intelligence for evaluating the internal data received by the external device. This enables real-time monitoring of changes in the user's physical condition and allows for early intervention.

[0711] A "biometric information collection device" is a device placed inside the body to acquire data about the user's health status.

[0712] A "capsule" is a small container that can be taken into the body by the user and contains a biometric information collection device.

[0713] "Internal data" refers to data such as heart rate, body temperature, and other health-related information obtained directly from the user's body.

[0714] "External device means" refers to a device for receiving and communicating internal data acquired from the capsule, and includes smartphones and wearable devices.

[0715] "Artificial intelligence means" refers to algorithms and technologies for analyzing and evaluating received data, and is a system used for detecting anomalies and providing instructions for health management.

[0716] A "warning" is a notification or alert issued when an abnormality is detected, and is sent to the user or caregiver.

[0717] A "health status report" is a detailed health status report generated based on analyzed data, and it contains information useful for the user's health management.

[0718] A "caregiver" is someone responsible for providing care to a user, and typically refers to a caregiver or nurse.

[0719] A "user" is an individual whose health status is monitored by this system, and this mainly includes elderly people and patients who require health management.

[0720] This invention is realized by a capsule containing a biometric information collection device that is ingested by the user. The capsule acquires internal data such as heart rate and body temperature while inside the user's body. The acquired data is transmitted to an external device, such as a smartphone or wearable device, using Wi-Fi or Bluetooth.

[0721] The terminal transmits the received internal data to the server via the internet. The server analyzes the data using artificial intelligence and evaluates the user's health status. This analysis compares the data with past data to determine whether or not there are any abnormalities. If an abnormality is detected, the server automatically sends a warning to the caregiver. The server also generates a detailed health status report based on the evaluation results and sends it to the terminal.

[0722] This health status report is designed to make it easier for users and caregivers to understand the situation and includes personalized health management instructions. A specific example of its use is in a care facility where elderly individuals are using the system. This system can monitor changes in health in real time, even at night, and immediately notifies care staff of any abnormalities, enabling early medical intervention.

[0723] An example of a prompt message would be, "Please describe the concept of an application that analyzes health monitoring data of elderly people in real time and immediately notifies if an abnormality is detected."

[0724] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0725] Step 1:

[0726] The user takes a capsule. Inside the body, the capsule uses a biometric data collection device to acquire internal data such as heart rate and body temperature. The input is the body's internal biometric information, and the output is the acquired biometric data. This data is temporarily stored inside the capsule.

[0727] Step 2:

[0728] The terminal wirelessly receives internal data from the capsule. The input is biometric data from the capsule, and the output is data stored in the terminal. The terminal prepares to transmit this data to a server via the internet.

[0729] Step 3:

[0730] The server receives internal data transmitted from the terminal. The input is health data from the terminal, and the output is biometric information as received data. The server stores this data in a database for analysis.

[0731] Step 4:

[0732] The server uses artificial intelligence to compare and analyze received data against past records. The input consists of biometric information and historical database data, while the output is anomaly detection information as a result of the analysis. In this step, a generative AI model is used to identify anomaly patterns.

[0733] Step 5:

[0734] If the server detects an anomaly, it automatically notifies the caregiver. The input is the anomaly information from the analysis results, and the output is a notification message as a warning. Notifications are sent via email or push notifications from a dedicated application.

[0735] Step 6:

[0736] The server generates a health status report based on the analysis results and sends it to the terminal. The input is the analysis results, and the output is a health status report for the user. The report includes individually tailored health management instructions.

[0737] Step 7:

[0738] The terminal receives health status reports, which are then reviewed by the user and caregivers. The input is the health status report from the server, and the output is the health information received by the user. The terminal visualizes this information and provides it to the user.

[0739] The above steps enable real-time monitoring of the user's health status, allowing for early detection of anomalies and rapid response.

[0740] 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.

[0741] This invention integrates an emotion engine into a system that acquires various in vivo data using microcapsules ingested by the user, thereby enabling deeper analysis and management of health conditions. The system consists of microcapsules, an external device, artificial intelligence on a server, and an emotion engine.

[0742] Capsule Function

[0743] Users take a microcapsule equipped with a biosensor before going to sleep. This capsule has the function of acquiring biometric data such as heart rate, body temperature, digestive system status, and blood components in real time and transmitting it to an external device.

[0744] Role of external devices

[0745] The device wirelessly receives data from the microcapsules. The received data is transmitted to the server in an encrypted form. Furthermore, the device displays notifications to the user and provides feedback on the user's health status.

[0746] Data analysis using servers and artificial intelligence

[0747] The server analyzes the received data using AI. This analysis not only detects abnormalities in physiological data but also includes recognizing the user's emotional state through an emotion engine. The emotion engine analyzes heart rate variability and other biosignals to infer the user's emotional state. This makes it possible to assess the user's mental health as well.

[0748] Use of analysis results

[0749] Based on the analysis results, the server generates a detailed health report. This report includes not only the user's overall health status but also their emotional state, providing personalized health management advice. Furthermore, if an abnormality is detected, the system immediately sends a notification to the attending physician or healthcare provider.

[0750] Specific example

[0751] For example, when a user is experiencing high levels of stress, data is collected from the capsule along with fluctuations in heart rate and body temperature. This data is analyzed by an emotion engine, which determines that the user is experiencing a high level of stress. The server then adds specific advice for stress reduction to the report, providing information that can be used for daily health management. In this way, the system contributes not only to physical health management but also to maintaining mental health.

[0752] The following describes the processing flow.

[0753] Step 1:

[0754] Users take a microcapsule containing a biosensor before going to sleep. This capsule detects heart rate, body temperature, digestive system status, blood components, and other parameters in real time.

[0755] Step 2:

[0756] The device receives biometric data transmitted wirelessly from the capsule. This data includes subtle fluctuations in heart rate and temperature changes, as well as other data necessary for emotion recognition.

[0757] Step 3:

[0758] The device transmits the received biometric data to a server via the internet. The data is encrypted during transmission, ensuring secure transfer.

[0759] Step 4:

[0760] The server analyzes the received data using AI and an emotion engine. The AI ​​detects anomalies in the data, and the emotion engine infers the user's emotional state based on heart rate variability patterns and other biometric data.

[0761] Step 5:

[0762] If the server detects an anomaly based on the analysis results, it will immediately send a notification to the attending physician or medical professional. This notification will also include information about the user's emotional state, allowing the physician to take into account the user's mental condition when responding.

[0763] Step 6:

[0764] The server generates a detailed health report. This report includes analysis of physical health status as well as emotional state, providing information to help users manage their daily health.

[0765] Step 7:

[0766] The server sends the generated health report to the user's device. The user can then receive this report to understand their own health status and identify areas that need improvement.

[0767] Step 8:

[0768] Users can use their devices as needed to book online consultations and medical advice appointments. This is particularly useful for receiving mental health support when emotional disturbances are recognized.

[0769] (Example 2)

[0770] 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".

[0771] In health management, not only physical data but also mental health status is important. However, conventional systems were limited to monitoring only physiological data, making it difficult to grasp the user's emotional state in real time and provide appropriate advice. As a result, comprehensive health management was not adequately provided.

[0772] 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.

[0773] In this invention, the server includes means for using a capsule containing a biosensor for acquiring biometric information, means for transmitting the biometric information to an external device, artificial intelligence means for analyzing the biometric information received by the external device, and emotion estimation means for inferring emotional states. This enables a comprehensive evaluation of physical and emotional health status and the provision of personalized health management advice.

[0774] A "biosensor" is a device used to measure the physiological state of an organism, and has the function of collecting data such as heart rate and body temperature.

[0775] A "capsule" is a small container that has the ability to acquire information from inside the body using built-in sensors and transmit it to the outside.

[0776] An "external device" is a terminal device that receives data transmitted from the capsule and transfers it to the server.

[0777] "Artificial intelligence means" refers to algorithms and technologies used to analyze received data and detect anomalies or infer emotional states.

[0778] "Emotion estimation methods" refer to technologies and algorithms for analyzing biosignals to infer an individual's emotional state.

[0779] "Notification" refers to a means of communication that is sent to users or healthcare professionals when an abnormality is detected.

[0780] A "health report" is a document that provides an overview of a user's health status, generated based on acquired and analyzed biometric data.

[0781] "Personalized health management advice" refers to specific instructions and suggestions for improving one's lifestyle and health, provided based on an individual's health data and emotional state.

[0782] This invention is a system that comprehensively monitors a user's physical and emotional health using a capsule containing a biosensor. The user takes the capsule before going to sleep, and the capsule acquires physiological data such as heart rate and body temperature in real time. The data acquired by the capsule is transmitted to an external device using wireless communication technologies such as Bluetooth or Wi-Fi.

[0783] The terminal securely transfers biometric data received from the capsule to a server. Data transfer uses AES encryption and is conducted via the HTTPS protocol to ensure data confidentiality. The terminal also plays a role in providing health-related feedback to the user.

[0784] The server uses a generative AI model to analyze the received biometric data. This analysis utilizes machine learning algorithms implemented using Python and related libraries. The server not only detects anomalies in physiological data but also evaluates the user's emotional state using emotion estimation tools. As a result, the server generates a detailed health report and notifies the user, while also automatically contacting healthcare professionals in case of abnormalities.

[0785] As a concrete example, consider a case where a user's heart rate increases due to daytime stress. In this case, the capsule records the fluctuations in heart rate and transmits the data to a server via the terminal. The server analyzes the stress level using emotion estimation methods and provides the user with a health report via the terminal, which includes appropriate stress management measures. This report includes personalized advice for reducing the user's stress.

[0786] An example of a prompt for a generative AI model is: "Generate a sample report showing data analysis results for when a user experiences stress in the evening. This report should include details such as heart rate and body temperature, as well as an assessment of the stress level by an emotion engine."

[0787] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0788] Step 1:

[0789] The user ingests a capsule containing a biosensor. The sensor acquires physiological data such as heart rate and body temperature. The user's internal state is provided as input, and biometric data acquired in real time is obtained as output. The sensor acquires this data and prepares for wireless communication.

[0790] Step 2:

[0791] The terminal wirelessly receives biometric data transmitted from the capsule. The input is the biometric data from the capsule, and the output is the encrypted received data. Specifically, the terminal receives the data via Bluetooth or Wi-Fi connection and prepares to securely transfer it to the server using AES encryption.

[0792] Step 3:

[0793] The terminal sends data to the server. The input is encrypted biometric data, and the output is data transfer to the server. The terminal uses the HTTPS protocol to establish a secure communication channel and send data to the server.

[0794] Step 4:

[0795] The server analyzes the received biometric data. The input is encrypted biometric data, and the output is the result of the analyzed health and emotional state. The server uses a generative AI model to analyze the data and perform calculations to detect health abnormalities and emotional fluctuations. The analysis is carried out using programming languages ​​such as Python and machine learning algorithms.

[0796] Step 5:

[0797] The server generates a health report based on the analysis results. The input is the result of the analyzed data, and the output is a detailed report on the user's health and emotional state. The report is generated in a user-friendly format and includes additional instructions or alerts if any anomalies are detected.

[0798] Step 6:

[0799] The server sends generated reports and anomaly notifications to the user via the terminal. Input is the generated health report, and output is explicit health information and possible action suggestions to the user. Furthermore, the system also sends notifications to healthcare professionals as needed. The terminal displays information on the user's screen, providing actionable insights for health management.

[0800] (Application Example 2)

[0801] 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".

[0802] There is a need to continuously and promptly monitor the health status of the elderly and those requiring physical care, and to provide comprehensive support for their physical and mental health management. However, conventional methods have the challenge of not being able to consider not only physical condition but also emotional state, and to provide specific health advice tailored to individual circumstances.

[0803] 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.

[0804] In this invention, the server includes means for acquiring internal bodily data using microcapsules containing biometric information sensors, artificial intelligence means for analyzing the internal bodily data received by an external terminal, and means for performing a detailed evaluation of the health status report, including not only the physical state but also the emotional state. This makes it possible to realize more comprehensive and personalized health management.

[0805] A "biometric information sensor" is a device embedded in a microcapsule to acquire data from inside the body.

[0806] A "microcapsule" is a small capsule containing a bio-information sensor that collects information within the user's body.

[0807] "Internal bodily data" refers to various physiological data obtained from within the body, such as heart rate, body temperature, digestive system status, and blood components.

[0808] An "external terminal" is a communication device that receives internal body data from microcapsules and then transmits it to a server.

[0809] "Artificial intelligence tools" refer to software systems used to perform advanced data analysis and evaluate physical and emotional states.

[0810] A "health status report" is a detailed assessment report generated based on analyzed physiological and emotional data of the body.

[0811] "Emotional state" refers to the emotional state or tendency of the user, inferred from fluctuations in biometric information.

[0812] This invention is a system that uses microcapsules containing biometric sensors to acquire and analyze internal bodily data of elderly individuals and others requiring health management. Users take the microcapsules before going to bed, and the capsules collect physiological data such as heart rate, body temperature, and digestive system status within the body.

[0813] The collected data is transmitted to an external device using Bluetooth. This external device could be a smartphone or tablet. The device encrypts the received data and transfers it to a dedicated server via the internet.

[0814] The server analyzes the received data using artificial intelligence (AI). This AI utilizes a generative AI model and is capable of not only detecting physiological abnormalities but also evaluating the user's emotional state through an emotion engine. The emotional state is inferred from changes in heart rate variability and body temperature, and the analysis results are generated as a detailed health status report. This report includes not only potential physical abnormalities but also stress levels and emotional trends.

[0815] Health status reports are provided to users along with individually personalized health management advice. This advice can include specific guidelines to help with daily life. For example, if a user has a persistently elevated heart rate, they might receive advice such as, "Increase your stretching time today to stabilize your heart rate." This information is shared not only with the user but also with healthcare professionals as needed.

[0816] For example, if the server determines that a user may be experiencing a lot of stress based on their body temperature fluctuations, it can include a suggestion in the health report such as, "To improve your sleep, please reduce your caffeine intake." An example of a prompt would be, "Based on today's data, create a detailed report on user B's health and emotional state and add personalized advice," which could be given to the generating AI model.

[0817] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0818] Step 1:

[0819] The user takes a microcapsule containing a biometric sensor before going to sleep. This capsule collects physiological data such as heart rate, body temperature, and digestive system status within the body. The input is the capsule taken by the user, and the output is the biometric data acquired within the body. The capsule prepares to transmit the collected data to an external terminal.

[0820] Step 2:

[0821] An external terminal receives biometric data transmitted from the microcapsule via Bluetooth. The input acquired by the terminal is the biometric data sent from the capsule, and the output is data that has been encrypted and is ready to be sent to the server. This data is encrypted for security purposes.

[0822] Step 3:

[0823] The terminal transfers encrypted data to the server via the internet. The input here is the data received and encrypted by the terminal, and the output is the secure data that reaches the server. The terminal confirms the completion of the data transfer.

[0824] Step 4:

[0825] The server analyzes the received biometric data using a generating AI model. Here, an emotion engine is driven based on changes in heart rate and body temperature, with the received data as input and the analysis results as output. The specific actions performed by the server include data classification, anomaly detection, and emotion prediction generation.

[0826] Step 5:

[0827] The server generates a health status report based on the analysis results. The input is the analysis results obtained in step 4, and the output is a detailed health status report. This report includes information on emotional state and physical abnormalities, as well as personalized health management advice. The server organizes this information and prepares for the next step.

[0828] Step 6:

[0829] Users receive health status reports via an external device. The input is a health status report sent from the server, and the output is specific health management advice displayed to the user. Users can use this information to improve their lifestyle and implement stress reduction measures.

[0830] 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.

[0831] 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.

[0832] 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.

[0833] 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.

[0834] 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.

[0835] 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.

[0836] 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.

[0837] 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.

[0838] 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."

[0839] 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.

[0840] 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.

[0841] 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.

[0842] 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.

[0843] 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.

[0844] 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.

[0845] 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.

[0846] 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.

[0847] 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.

[0848] 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.

[0849] 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.

[0850] 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.

[0851] The following is further disclosed regarding the embodiments described above.

[0852] (Claim 1)

[0853] A means of acquiring in-body data using a capsule containing a biosensor,

[0854] Means for transmitting the aforementioned internal body data to an external device,

[0855] An artificial intelligence means for analyzing internal body data received by the external device,

[0856] A means for detecting an anomaly based on the analysis results and sending a notification,

[0857] A means for providing a health report generated based on the aforementioned analysis results,

[0858] A system that includes this.

[0859] (Claim 2)

[0860] The system according to claim 1, further comprising means for automatically transmitting the notification to a medical professional when an abnormality is detected.

[0861] (Claim 3)

[0862] The system according to claim 1, further comprising means for providing individually personalized health management advice to the user based on the aforementioned health report.

[0863] "Example 1"

[0864] (Claim 1)

[0865] A means of acquiring internal bodily information using a small device with a built-in biosensor,

[0866] Means for transmitting the aforementioned internal bodily information to an external device,

[0867] The aforementioned external device includes a machine learning model for analyzing internal bodily information received,

[0868] A means for detecting an anomaly based on the analysis results and transmitting a communication,

[0869] A means for providing a health report generated based on the aforementioned analysis results,

[0870] Means including a terminal device for displaying the aforementioned report to the user,

[0871] A system that includes this.

[0872] (Claim 2)

[0873] The system according to claim 1, wherein the communication is a means for automatically transmitting the communication to a medical professional when an anomaly is detected.

[0874] (Claim 3)

[0875] The system according to claim 1, comprising means for providing individually tailored health management guidance to the user based on the aforementioned health report.

[0876] "Application Example 1"

[0877] (Claim 1)

[0878] A means of acquiring internal data using a capsule containing a biological information collection device,

[0879] External device means for communicating the aforementioned internal data,

[0880] Artificial intelligence means for evaluating internal data received by the external device,

[0881] A means for detecting an anomaly based on the evaluation results and outputting a warning,

[0882] A means for providing a health status report generated based on the aforementioned evaluation results,

[0883] The means by which the aforementioned warning is automatically sent to the caregiver when an abnormality is detected,

[0884] A means of providing users with individually tailored health management instructions based on the aforementioned health status report,

[0885] A system that includes this.

[0886] (Claim 2)

[0887] The system according to claim 1, which has means for enabling the administrator of a nursing care facility to check physical monitoring data at any time.

[0888] (Claim 3)

[0889] The system according to claim 1, which includes means for understanding changes in a user's physical condition in real time and enabling early intervention.

[0890] "Example 2 of combining an emotion engine"

[0891] (Claim 1)

[0892] A method using a capsule containing a biosensor for acquiring biological information,

[0893] Means for transmitting the aforementioned biological information to an external device,

[0894] Artificial intelligence means for analyzing biological information received by the external device,

[0895] In addition to physiological data, there are emotion estimation methods for inferring emotional states,

[0896] A means for detecting anomalies based on the aforementioned analysis results and sending notifications to medical professionals and institutions,

[0897] A means for providing a health report and an emotional state report generated based on the aforementioned analysis results,

[0898] A system that includes this.

[0899] (Claim 2)

[0900] The system according to claim 1, further comprising means for automatically transmitting the notification to a medical professional when an abnormality is detected.

[0901] (Claim 3)

[0902] The system according to claim 1, further comprising means for providing individually personalized health management advice to the user based on the aforementioned health report and emotional state report.

[0903] "Application example 2 when combining with an emotional engine"

[0904] (Claim 1)

[0905] A means of acquiring internal body data using microcapsules containing biometric sensors,

[0906] Means for transmitting the aforementioned internal bodily data to an external terminal,

[0907] An artificial intelligence means for analyzing internal bodily data received by the external terminal,

[0908] A means for identifying an anomaly based on the aforementioned analysis results and transmitting a report,

[0909] A means for providing a health status report generated based on the aforementioned analysis results,

[0910] The aforementioned health status report is a means of conducting a detailed evaluation that includes not only physical condition but also emotional condition,

[0911] A system that includes this.

[0912] (Claim 2)

[0913] The system according to claim 1, further comprising means for automatically transmitting the aforementioned report to medical professionals when an anomaly is identified.

[0914] (Claim 3)

[0915] The system according to claim 1, further comprising means for providing users with individually personalized health management guidance based on the aforementioned health status report. [Explanation of Symbols]

[0916] 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 acquiring internal data using a capsule containing a biological information collection device, External device means for communicating the aforementioned internal data, Artificial intelligence means for evaluating internal data received by the external device, A means for detecting an anomaly based on the evaluation results and outputting a warning, A means for providing a health status report generated based on the aforementioned evaluation results, The means by which the aforementioned warning is automatically sent to the caregiver when an abnormality is detected, A means of providing users with individually tailored health management instructions based on the aforementioned health status report, A system that includes this.

2. The system according to claim 1, which has means for enabling the administrator of a nursing care facility to check physical monitoring data at any time.

3. The system according to claim 1, which includes means for understanding changes in a user's physical condition in real time and enabling early intervention.

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