system

Abstract

Provide a system. A terminal means for a user to input information about the health condition of a child; a server means for receiving and analyzing data transmitted from the terminal means; means for presenting an appropriate initial response method to a user based on the data analyzed by the server means; means for transmitting the analyzed data to a medical professional; The system includes a means for responding to requests for additional information from a medical professional.

Description

[Technical Field]

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

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

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] There is a need to resolve the situation where young children are unable to accurately explain their illness, making it difficult for parents and caregivers to make appropriate decisions. Furthermore, there is the problem of increasing the burden on medical institutions because it is difficult for parents to provide prompt and accurate initial treatment for their sick children. Furthermore, there is also the problem of medical professionals lacking sufficient information when making diagnoses, which increases the possibility of delayed or incorrect diagnosis. [Means for solving the problem]

[0005] The present invention solves the above problem by providing a system including a terminal means for a user to input information regarding the health condition of a child, a server means for receiving and analyzing data transmitted from the terminal means, a means for presenting an appropriate initial response method to the user based on the data analyzed by the server means, a means for transmitting the analyzed data to a medical professional, and a means for responding to requests for additional information from the medical professional.

[0006] Specifically, detailed information about a child's health condition is entered using a terminal device, and the data is analyzed by a server device, which assesses the severity of the condition and suggests initial response methods. Furthermore, analysis results are sent to medical professionals, supporting rapid and accurate diagnosis and treatment. Furthermore, if there is feedback from medical professionals and a request for additional information, the user can easily respond. This reduces the burden on medical institutions, eases anxiety for parents and caregivers, and enables more appropriate and prompt responses.

[0007] A "user" is an individual who utilizes the system to input information about their child's health status and receive the results.

[0008] "Terminal means" refers to a device, specifically a smartphone or tablet, through which a user inputs information about their child's health condition.

[0009] The "server means" is a computer system that receives and analyzes data sent from users.

[0010] "Data" refers to information about a child's health, including specific information such as temperature, type of symptoms, and when symptoms began.

[0011] "Analysis" refers to the process by which the server means evaluates the classification and severity of symptoms based on the data received from the user.

[0012] "Initial response method" refers to first aid or countermeasures for the child's symptoms that the server means presents to the user based on the analysis results.

[0013] "Medical Professional" refers to the person who receives the analyzed data and provides further information requests and feedback to provide the necessary diagnosis and treatment.

[0014] "Interface" refers to the operating screens and input methods used by the user to respond to feedback and requests for additional information from healthcare professionals.

[0015] "Feedback" refers to the process by which medical professionals review the analysis results and request additional information if necessary. [Brief explanation of the drawings]

[0016] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10]1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0017] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

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

[0019] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

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

[0021] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0022] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0024] [First embodiment]

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

[0026] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0027] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0029] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

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

[0031] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0033] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0036] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0037] System Overview

[0038] This invention relates to a system in which a user inputs information about their child's health condition using a terminal means, the data is analyzed by a server means, an appropriate initial response method is provided, and the data is then sent to a medical professional.

[0039] Program processing

[0040] User Action:

[0041] The user uses a terminal (such as a smartphone or tablet) to input information about their child's health condition. The questionnaire includes the following information: "Current body temperature," "Type of symptoms (fever, cough, vomiting, etc.)," ​​"Time of symptom onset," and "Other related symptoms (rash, difficulty breathing, etc.)."

[0042] Terminal behavior:

[0043] The device receives the information entered by the user and sends the data to the server, where it is encrypted to protect privacy and security.

[0044] Server behavior:

[0045] The server receives the data sent from the terminal and then performs the following analysis:

[0046] 1. Data Validation:

[0047] The server verifies the accuracy and completeness of the received data.

[0048] 2. Symptom classification and severity assessment:

[0049] The server analyzes the data using special algorithms to classify the child's symptoms and assess their severity - for example, a temperature of 39 degrees or higher is considered severe.

[0050] 3. Generate initial response methods:

[0051] Based on the analysis results, the server generates initial action instructions for the user, such as "use a cooling sheet and stay hydrated" and "contact a medical institution immediately."

[0052] 4. Data transmission to medical professionals:

[0053] The server then sends detailed data, including the analysis results, to medical professionals, who can then use this data to make more accurate diagnoses and treatments.

[0054] 5. Responding to requests for additional information:

[0055] If the medical professional determines that further information is needed, they will request it from the user via the server, and a follow-up question such as "Do you have a rash?" will be displayed on the device.

[0056] Examples:

[0057] Scenario: A child has a high fever of 39 degrees.

[0058] The user (parent) opens the terminal and enters the fever information:

[0059] Enter "Temperature: 39 degrees," "Coughing," and "Symptoms started last night."

[0060] The terminal sends the entered data to the server:

[0061] After transmission, the server immediately validates the received data.

[0062] The server evaluates the symptom classification and severity based on the received data:

[0063] "His body temperature is over 39 degrees, so his condition is considered serious."

[0064] The server provides the user with an initial response:

[0065] The device displays the following advice: "Use cooling pads and stay hydrated. Contact a medical institution immediately."

[0066] The server sends the analysis results to the medical professional:

[0067] A medical professional makes a diagnosis based on the received data.

[0068] If your healthcare professional needs additional information:

[0069] For example, an additional question such as "Do you have a rash?" is displayed on the terminal via the server, and the user answers it.

[0070] The system enables parents and caregivers to respond quickly and accurately to their child's health conditions and allows medical professionals to make efficient diagnoses.

[0071] The processing flow will be explained below.

[0072] Step 1:

[0073] The user enters information about their child's health condition using a terminal (e.g., a smartphone or tablet). The questionnaire includes questions such as "current body temperature," "type of symptoms (fever, cough, vomiting, etc.)," ​​"when symptoms began," and "other related symptoms (rash, difficulty breathing, etc.)."

[0074] Step 2:

[0075] The user presses the submit button to submit the information entered in the inquiry form.

[0076] Step 3:

[0077] The terminal receives the transmitted information, encrypts the data, and transmits it to the server means.

[0078] Step 4:

[0079] The server receives the data sent from the device and validates it for accuracy and completeness.

[0080] Step 5:

[0081] The server begins analyzing the incoming data. It uses an algorithm to analyze the data and classify symptoms and assess their severity. For example, a temperature of 39 degrees or higher is considered severe.

[0082] Step 6:

[0083] Based on the analysis results, the server generates initial action instructions for the user, such as "use a cooling sheet and stay hydrated" or "contact a medical institution immediately."

[0084] Step 7:

[0085] The server transmits the generated initial response method to the terminal means.

[0086] Step 8:

[0087] The terminal displays the initial response advice received from the server to the user, who then takes appropriate initial response according to the advice provided.

[0088] Step 9:

[0089] The server sends the analysis results as detailed data to medical professionals, enabling them to make quick and accurate diagnoses and take appropriate action based on the data.

[0090] Step 10:

[0091] If the medical professional determines that more information is needed, the additional information is requested from the user through the server.

[0092] Step 11:

[0093] The server sends a request for additional information from the medical professional to the terminal means.

[0094] Step 12:

[0095] The terminal displays a request for additional information to the user, who answers the additional questions and resubmits the answers through the terminal.

[0096] Step 13:

[0097] The server analyzes the re-received additional data and transmits it again to the medical professional.

[0098] Step 14:

[0099] The medical professional will determine the final diagnosis and treatment and notify the user via the server, who will then follow the final instructions.

[0100] This process allows users to quickly and accurately address their child's health condition and allows medical professionals to efficiently diagnose the condition.

[0101] Example 1

[0102] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0103] In today's world, it is extremely important to quickly and accurately assess a child's health condition and provide appropriate initial treatment. However, because most parents and caregivers have limited medical knowledge, it is difficult to determine whether a child's symptoms are serious. They also have limited means of quickly learning the appropriate treatment. Furthermore, access to medical facilities can be difficult, and communication with medical professionals can be difficult. To solve these problems, a system is needed that can quickly analyze data on a child's health condition, provide appropriate initial treatment, and send data to medical professionals for feedback.

[0104] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0105] In this invention, the server includes means for receiving data sent from the user, encrypting it, and analyzing it, means for classifying symptoms and assessing their severity based on the analyzed data, and means for generating an appropriate initial response method based on the analysis results. This allows the user to quickly and accurately understand their child's health condition and take appropriate initial responses. Furthermore, by including means for sending the analyzed data to a medical professional and means for responding to requests for additional information from the medical professional, communication with the medical professional is facilitated, enabling more accurate diagnoses and responses.

[0106] "Terminal means" refers to a device used by a user to input information, specifically a smartphone or tablet.

[0107] The term "server means" refers to a computer system that receives data sent from the terminal means and performs analysis and other processing of the data.

[0108] "Encryption" refers to the technology of using a specific algorithm to protect the contents of data in order to transmit it securely.

[0109] "Validation" refers to the process of checking whether received data is accurate and complete, and verifying that there are no anomalies.

[0110] "Symptom classification" refers to the process of analyzing data about a child's health and categorizing it based on specific symptoms.

[0111] "Severity assessment" refers to the process of determining the severity of a symptom and assessing its severity.

[0112] "Initial response methods" refers to specific response procedures and advice that users should take immediately regarding their child's health condition.

[0113] "Medical professionals" refers to people in professions such as doctors and nurses who have specialized knowledge and skills related to medical care.

[0114] "Information Request" refers to the act of asking a User for additional data or information required by a medical professional.

[0115] "Interface" refers to the screen and input method that a user uses to interact with a system, and specifically refers to the user interface of an application.

[0116] This invention is a system in which a user inputs information about the child's health condition using a terminal means, and a server means analyzes the data, provides an appropriate initial response method, and then transmits the data to a medical professional.

[0117] User Actions

[0118] Users use a device such as a smartphone or tablet to launch the application and enter information about their child's health. The questionnaire includes items such as "current body temperature," "type of symptoms (fever, cough, vomiting, etc.)," ​​"when symptoms began," and "other related symptoms (rash, difficulty breathing, etc.)." By entering this information, users can record their child's health in detail.

[0119] Device behavior

[0120] The device receives the information entered by the user and sends the data to the server, where it is encrypted using the AES-256 algorithm and transmitted using a secure communication protocol (e.g., HTTPS), ensuring the privacy and security of the data.

[0121] Server Operation

[0122] The server receives the data sent from the terminal and then performs the following analysis:

[0123] 1. Data Validation

[0124] The server checks the accuracy and completeness of the received data, checking the data format (e.g., whether the body temperature is within the range of 35-42°C) and whether required fields have been filled in, and returns an error to the terminal if there are any errors.

[0125] 2. Symptom classification and severity assessment

[0126] The server uses an analytical algorithm to analyze the data and classify the child's symptoms and assess their severity. For example, a temperature of 39 degrees or higher is considered severe. The algorithm is based on a machine learning model and uses patterns learned from past data to make the classification.

[0127] 3. Generate initial response methods

[0128] The server generates appropriate initial response instructions based on the analysis results. For example, if the patient has a temperature of 39°C, a cough, and symptoms began last night, the server generates the following advice: "Use a cooling pad, stay hydrated, and contact a medical institution immediately."

[0129] Sending data to medical professionals and responding to requests for additional information

[0130] The server sends the data, including the analysis results, to the medical professional. The medical professional accesses the EHR system using a secure communication protocol and makes a diagnosis based on the received data. If the medical professional determines that additional information is required, an additional question, such as "Do you have a rash?", is displayed on the device via the server. By answering this question, the user can provide the medical professional with the necessary additional information.

[0131] Specific examples

[0132] Scenario: A child has a high fever of 39 degrees.

[0133] 1. User:

[0134] The parent opens the device and enters the following information into the application's question form: "Temperature: 39 degrees," "Having a cough," and "Symptoms started last night."

[0135] 2. Terminal:

[0136] The terminal encrypts the entered data and sends it to the server using a secure communication protocol (HTTPS).

[0137] 3. Server:

[0138] The server validates the incoming data to ensure it is in the correct format and range, then uses an analytical algorithm to assess the symptom classification and severity, resulting in a "high fever" diagnosis.

[0139] 4. Server:

[0140] The server generates an initial response method such as "Use a cooling sheet and stay hydrated. Contact a medical institution immediately," and displays it on the terminal.

[0141] 5. Server:

[0142] The server sends the analysis results to medical professionals, who then make a diagnosis based on the received data via the EHR system.

[0143] 6. Request for additional information:

[0144] The medical professional sends a follow-up question, "Do you have a rash?", which is displayed on the device and the user answers.

[0145] The system allows users to respond quickly and accurately to their child's health conditions and allows medical professionals to make efficient diagnoses.

[0146] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0147] Step 1:

[0148] Data Entry

[0149] User action: The user launches an application using a smartphone or tablet.

[0150] Input: The user inputs information about their health condition (e.g., "Temperature: 39°C," "I have a cough," "Symptoms started last night").

[0151] What it does: The user provides information about their child's health by filling out a form in the application.

[0152] Step 2:

[0153] Data Receipt and Encryption

[0154] Terminal operation: The terminal receives the information entered by the user.

[0155] Input: Health information data entered by the user.

[0156] Data processing: The terminal encrypts the data with the AES-256 algorithm and sends it to the server using a secure communication protocol (HTTPS).

[0157] Output: The encrypted health information data is sent to the server.

[0158] Specific operation: The device encrypts data and communicates securely.

[0159] Step 3:

[0160] Data Validation

[0161] Server operation: The server receives the data sent from the terminal.

[0162] Input: Encrypted health information data.

[0163] Data calculation: The server decrypts the data and checks the data format (e.g., whether the body temperature is within the range of 35-42 degrees) and whether all required fields have been filled in.

[0164] Output: Successfully validated health information data.

[0165] Specific operation: Checks the data format and required fields, and returns an error to the terminal if there are any errors.

[0166] Step 4:

[0167] Symptom classification and severity rating

[0168] Server Operation: The server executes the data analysis algorithms.

[0169] Input: Health information data that has passed validation.

[0170] Data calculation: The server uses machine learning models to analyze health information. If the body temperature is 39 degrees, it will be classified as a high fever and the severity will be assessed as "high."

[0171] Output: Categorized symptom data and assessment results.

[0172] What it does: It uses machine learning algorithms to analyze health information, classify it into appropriate categories, and assess its severity.

[0173] Step 5:

[0174] Generate initial response methods

[0175] Server operation: The server generates an initial response method based on the analysis results.

[0176] Input: Categorized symptom data and assessment results.

[0177] Data calculation: The server generates appropriate initial response measures based on predefined response measures. For example, if the patient has a temperature of 39 degrees, a cough, and symptoms began last night, the server generates advice such as, "Use a cooling pad, stay hydrated, and contact a medical institution immediately."

[0178] Output: Advice on how to respond first.

[0179] Specific action: Generate a response method based on the conditions and provide it to the user.

[0180] Step 6:

[0181] Sending data to medical professionals

[0182] Server operation: The server sends detailed data including the analysis results to a medical professional.

[0183] Input: Initial response advice and analyzed health information data.

[0184] Data processing: The server re-encrypts the data and sends it using a secure communication protocol to a system accessed by medical professionals.

[0185] Output: Detailed data received by the medical professional.

[0186] What happens: Sends data to an EHR system and makes it available to healthcare professionals.

[0187] Step 7:

[0188] Responding to requests for additional information

[0189] User Action: If necessary, the medical professional can request additional information.

[0190] Input: Request for additional information from medical professional.

[0191] Data computation: The server sends a request for additional information to the terminal, and the user answers it to gather more data (e.g., "Do you have a rash?").

[0192] Output: Additional information from the user.

[0193] Specific operation: The server sends a request for additional information to the terminal and collects the response.

[0194] In this way, each step works in coordination, enabling a quick and accurate assessment of a child's health condition and early response.

[0195] (Application example 1)

[0196] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0197] In modern society, it is extremely important for parents and caregivers to respond promptly and appropriately to their children's health conditions. However, when sudden symptoms occur, accurate initial response is required, which is difficult for general users without specialized knowledge. Furthermore, rapid collaboration with medical professionals is also required, which requires a system that can appropriately collect, analyze, and share information. Data security and privacy protection are also important issues.

[0198] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0199] In this invention, the server includes a terminal means for receiving and analyzing information on the child's health condition entered by the user, a means for encrypting and receiving data transmitted from the terminal means and analyzing it, a means for presenting an appropriate initial response method to the user based on the data analyzed by the server means, a means for transmitting the analyzed data to a specialist, a means for responding to requests for additional information from the specialist, a display means for presenting an initial response method to the user based on the analysis results, and a means for validating the data. This enables parents and caregivers to respond to the child's health condition quickly and accurately and facilitates smooth cooperation with specialists.

[0200] The "terminal means" is a device that allows a user to input information about the health condition of a child.

[0201] "Data" refers to information entered by the user about the child's health, including temperature, symptoms, and the timing of symptoms.

[0202] The "server means" is a device for receiving and analyzing data sent from the terminal means.

[0203] "Initial response method" refers to guidelines for specific steps and actions that users should take based on the analyzed data.

[0204] "Expert" refers to someone with specialized medical knowledge, including doctors and nurses.

[0205] "Request for additional information" refers to the expert requesting further required information from the user.

[0206] The "display means" is a device or function for visually presenting the analysis results and initial response methods to the user.

[0207] "Data validation" is the process of verifying the accuracy and completeness of received data.

[0208] An "algorithm" is a computational method by which the server means analyzes the data and assesses the severity of the symptoms.

[0209] This invention builds a system that monitors children's health conditions and provides users with appropriate initial response methods. The system is mainly composed of a terminal means used by the user, a server means for analyzing data, and a means for supporting collaboration with experts.

[0210] Hardware and software used

[0211] 1. Terminal means:

[0212] Hardware: Smartphones, tablets

[0213] Software: User interface using React Native

[0214] 2. Server means:

[0215] Hardware: Standard server machine

[0216] Software: Python (Flask framework), MySQL database, data encryption with OpenSSL

[0217] Program processing

[0218] User Action:

[0219] Users use a smartphone or tablet application to enter data about their child's health, including the following:

[0220] Body temperature: 39 degrees

[0221] Cough: Yes

[0222] Symptom onset: Last night

[0223] Other associated symptoms: None

[0224] Terminal behavior:

[0225] The device encrypts the entered information (AES-256) and sends it to the server using a device-specific method (e.g., sendSecureData). This method ensures data integrity and privacy.

[0226] Server behavior:

[0227] The server receives the data sent from the terminal and then performs the following processes.

[0228] 1. Data Validation:

[0229] The server verifies the received data for accuracy and completeness, checking for blanks and filtering out inappropriate data.

[0230] 2. Data Analysis:

[0231] The server uses special algorithms (e.g., malignancy determination algorithms) to analyze the child's symptoms and severity.

[0232] 3. Generate initial response methods:

[0233] Based on the analysis results, the system generates initial action instructions to be presented to the user, such as "Use a cooling sheet, stay hydrated, and contact a medical institution immediately."

[0234] 4. Sending data to the expert:

[0235] If necessary, detailed data including analysis results can be sent to medical professionals, who can use this data to make more accurate diagnoses and treatments.

[0236] 5. Request for additional information:

[0237] If the medical professional needs more information, they will ask the user a follow-up question via the server, e.g., "Do you have a rash?"

[0238] Specific examples

[0239] Example of a prompt for the user to enter:

[0240] Child's current status:

[0241] Body temperature: 39°C

[0242] Cough: Yes

[0243] Symptoms started last night

[0244] Other associated symptoms: None

[0245] Send: true

[0246] The system allows parents and caregivers to respond quickly to sudden illnesses and medical professionals to provide appropriate support. The system also ensures data security and privacy, making it safe to use in everyday life.

[0247] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0248] Step 1:

[0249] Users use a smartphone or tablet to enter information about their child's health into the application form. Information entered includes body temperature, whether or not the child has a cough, when symptoms began, and other related symptoms. Examples of input data include "body temperature: 39°C," "cough present," "when symptoms began: last night," and "no other related symptoms."

[0250] Step 2:

[0251] The terminal encrypts the entered information. Specifically, it encrypts the data using the AES-256 encryption method. The encrypted data is then sent to the server using the terminal's sendSecureData method. This method ensures data integrity and privacy.

[0252] Step 3:

[0253] The server receives the encrypted data sent from the device. It first decrypts the received data and then validates it. Data validation checks whether there are any blank fields or inappropriate data. For example, it checks whether "body temperature" is a numeric value and whether "cough" is "yes" or "no."

[0254] Step 4:

[0255] The server inputs the validated data into a data analysis algorithm, which primarily classifies symptoms and assesses their severity. If the temperature is 39°C or higher, the algorithm evaluates the symptoms as severe and determines that escalation is necessary. Based on the results, the initial response method to be taken is generated.

[0256] Step 5:

[0257] Based on the analysis results, the server provides the user with initial response instructions. The displayed initial response instructions include specific instructions for action. For example, advice such as "Use a cooling sheet, stay hydrated, and contact a medical institution immediately" is displayed on the smartphone.

[0258] Step 6:

[0259] The server then sends the analysis results to a medical professional, if necessary. The data sent includes the information entered by the user and the server's analysis results, allowing the professional to perform a more detailed diagnosis.

[0260] Step 7:

[0261] If the specialist needs more information, the server sends the user a follow-up question, such as "Do you have a rash?", which is displayed on the smartphone. The user answers the question and the data is sent back to the server.

[0262] Step 8:

[0263] The server then re-analyzes the additional information and updates the necessary response procedures, ensuring that the user receives appropriate guidance on an ongoing basis. This process provides real-time collaboration between the user and the expert.

[0264] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0265] System Overview

[0266] This invention relates to a system in which a user inputs information about their child's health condition, transmits the information to a server via a terminal, and the server analyzes the received data and provides an appropriate initial response method. The analyzed data is then transmitted to a medical professional, who provides any necessary additional information. The system also incorporates an emotion engine that recognizes the user's emotions and reflects them in the analysis results and response methods.

[0267] Program processing

[0268] User Action:

[0269] The user uses a terminal (e.g., a smartphone or tablet) to input information about their child's health condition. The questionnaire includes questions such as "current body temperature," "type of symptoms (fever, cough, vomiting, etc.)," ​​"when symptoms began," and "other related symptoms (rash, difficulty breathing, etc.)." In addition, an emotion engine runs to collect the user's emotional state while they are entering information.

[0270] Terminal behavior:

[0271] The terminal collects information and emotion data input by the user, encrypts it, and transmits it to the server. The emotion engine analyzes the user's emotion from their voice, input speed, facial expression, etc., and transmits this data to the server as additional information.

[0272] Server behavior:

[0273] The server receives the data sent from the terminal and then performs the following analysis:

[0274] 1. Data Validation:

[0275] The server verifies the accuracy and completeness of the received data.

[0276] 2. Symptom classification and severity assessment:

[0277] The server analyzes the data using special algorithms to classify the child's symptoms and assess their severity - for example, a temperature of 39 degrees or higher is considered severe.

[0278] 3. Emotional Data Analysis:

[0279] The server analyzes the emotion data sent from the emotion engine to understand the user's emotional state. For example, if it determines that the user is very anxious, it will adjust the content and expression of the advice appropriately.

[0280] 4. Generate initial response methods:

[0281] Based on the analysis results and emotional data, the server generates initial action instructions for the user, such as "use a cooling sheet and stay hydrated" or "contact a medical institution immediately."

[0282] 5. Data transmission to medical professionals:

[0283] The server then sends detailed data, including the analysis results, to medical professionals, who can then use this data to make more accurate diagnoses and treatments.

[0284] 6. Responding to Requests for Additional Information:

[0285] If the medical professional determines that further information is needed, they will request it from the user via the server, and a follow-up question such as "Do you have a rash?" will be displayed on the device.

[0286] Examples:

[0287] Scenario: A child has a high fever of 39 degrees.

[0288] The user (parent) opens the terminal and enters the fever information:

[0289] The user types in "Temperature: 39 degrees," "Having a cough," and "Symptoms started last night." The emotion engine also collects feelings of anxiety and impatience from the parent's tone of voice and typing speed while they are typing.

[0290] The device sends the input data and emotion data to the server:

[0291] After transmission, the server immediately validates the received data and emotion data.

[0292] The server evaluates the symptom classification and severity based on the received data and emotion data:

[0293] The assessment is that the child's temperature is over 39 degrees, making the condition critical, and takes into account the parents' emotional state of high anxiety.

[0294] The server provides the user with an initial response:

[0295] The advice displayed is, "Use cooling pads and stay hydrated. Remain calm and contact a medical institution immediately."

[0296] The server sends the analysis results to the medical professional:

[0297] Medical professionals will make a diagnosis based on the data received, take into account parental concerns, and provide professional advice.

[0298] If your healthcare professional needs additional information:

[0299] For example, an additional question such as "Do you have a rash?" is displayed on the terminal via the server, and the user answers it.

[0300] The system allows parents and caregivers to respond quickly and accurately to their child's health condition, and medical professionals to make efficient diagnoses. The addition of emotional data-based responses also reduces the psychological burden on users, enabling smoother medical responses.

[0301] The processing flow will be explained below.

[0302] Step 1:

[0303] The user inputs information about their child's health condition using a terminal (e.g., a smartphone or tablet). The questionnaire includes information such as "current body temperature," "type of symptoms (fever, cough, vomiting, etc.)," ​​"when symptoms began," and "other related symptoms (rash, difficulty breathing, etc.)." As the user inputs information, the emotion engine analyzes the user's emotional state based on their tone of voice, typing speed, facial expression, etc.

[0304] Step 2:

[0305] The user clicks the submit button to submit the input.

[0306] Step 3:

[0307] The terminal encrypts the information and emotion data input by the user and transmits them to the server means.

[0308] Step 4:

[0309] The server receives the data sent from the terminal and validates the received data to check its accuracy and completeness.

[0310] Step 5:

[0311] The server begins analyzing the incoming data. It uses an algorithm to analyze the data from the user, classify the child's symptoms, and assess their severity. For example, a temperature of 39 degrees or higher is considered severe.

[0312] Step 6:

[0313] The emotion engine analyzes the transmitted emotion data and understands the user's emotional state, such as assessing anxiety, impatience, or restlessness.

[0314] Step 7:

[0315] The server then uses the analysis results and emotional data to provide the user with appropriate initial response advice, such as "Use a cooling sheet and stay hydrated. Remain calm and immediately contact a medical institution."

[0316] Step 8:

[0317] The server transmits the generated initial response method to the terminal means.

[0318] Step 9:

[0319] The terminal displays the initial response advice received from the server to the user, who then takes appropriate initial response according to the advice provided.

[0320] Step 10:

[0321] The server sends the analysis results to medical professionals, allowing them to make quick and accurate diagnoses and take appropriate action based on the data.

[0322] Step 11:

[0323] If the medical professional determines that more information is needed, a request for additional information is sent to the user through the server means.

[0324] Step 12:

[0325] The server sends a request for additional information from the medical professional to the terminal means.

[0326] Step 13:

[0327] The terminal displays a request for additional information to the user, who answers the additional questions and resubmits through the terminal.

[0328] Step 14:

[0329] The server analyzes the additional data received from the user and transmits it back to the medical professional.

[0330] Step 15:

[0331] The medical professional will determine the final diagnosis and treatment and notify the user via the server, who will then follow the final instructions.

[0332] This series of processes allows users to deal with their child's health condition quickly and accurately, and medical professionals can make efficient diagnoses. In addition, the emotional engine reduces the user's psychological burden and enables smoother medical treatment.

[0333] Example 2

[0334] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0335] Conventional health monitoring systems primarily involve inputting and analyzing information about a child's health condition. However, they lack consideration for the user's emotional state, making it difficult to completely alleviate the user's psychological burden. Furthermore, it is difficult to generate a fast and accurate initial response method or to communicate efficiently with medical professionals. Therefore, there is a need for a system that can respond quickly and appropriately while taking the user's emotional state into account.

[0336] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0337] In this invention, the server includes means for analyzing data sent from the user, means for generating an initial response method based on the analyzed data, and means for analyzing emotion data collected by the emotion engine and adjusting the initial response method, thereby enabling prompt and appropriate health management that takes the user's emotional state into consideration.

[0338] "Terminal means" refers to an electronic device such as a smartphone or tablet, which allows a user to input information about the child's health condition.

[0339] The term "server means" refers to a computer system that receives and analyzes data sent from the terminal means.

[0340] The "means for presenting an appropriate initial response method to the user" refers to a method for presenting an appropriate response method to the user based on the data analyzed by the server means.

[0341] "Means for sending to a medical professional" refers to a method by which the server means sends the analyzed data to a medical professional.

[0342] "Means for responding to requests for additional information" refers to methods for asking questions or gathering information from the user in response to requests for additional information from medical professionals.

[0343] An "emotion engine" refers to a tool that has the function of collecting and analyzing a user's emotional state from their voice, input speed, facial expressions, etc.

[0344] "Means for transmitting emotion data to server means" refers to a method for transmitting emotion data collected by the emotion engine to server means.

[0345] The "means for adjusting the initial response method based on the emotion data" refers to a method in which the server means analyzes the emotion data and appropriately adjusts the initial response method based on the results of the analysis.

[0346] This invention relates to a system in which a user inputs information about their child's health condition, transmits the information to a server via a terminal, and the server analyzes the received data and provides an appropriate initial response method. The analyzed data is then transmitted to a medical professional, who provides any necessary additional information. The system also incorporates an emotion engine that recognizes the user's emotions and reflects them in the analysis results and response methods.

[0347] User Action:

[0348] The user uses a terminal (e.g., a smartphone or tablet) to input information about their child's health condition. The questionnaire includes questions such as "current body temperature," "type of symptoms (fever, cough, vomiting, etc.)," ​​"time of symptom onset," and "other related symptoms (rash, difficulty breathing, etc.)." In addition, an emotion engine runs to collect the user's emotional state while they are entering information.

[0349] Terminal behavior:

[0350] The device temporarily stores the health information and emotional data entered by the user. It then encrypts this data and sends it to the server using a secure communication channel (e.g., HTTPS). The emotion engine analyzes the user's emotions based on their voice, typing speed, facial expressions, etc., and sends this data to the server as additional information.

[0351] Server behavior:

[0352] The server receives the data sent from the terminal and then performs the following series of analyses:

[0353] 1. Data Validation:

[0354] The server checks the received data for accuracy and completeness, especially for missing mandatory fields and anomalous data.

[0355] 2. Symptom classification and severity assessment:

[0356] The server uses a special algorithm to analyze the data, classify the child's symptoms, and assess their severity: for example, a temperature of 39 degrees or higher is considered severe.

[0357] 3. Emotional Data Analysis:

[0358] The server analyzes the emotion data sent from the emotion engine to understand the user's emotional state. For example, if it determines that the user is very anxious, it will adjust the content and expression of the advice appropriately.

[0359] 4. Generate initial response methods:

[0360] Based on the analysis results and emotional data, the server generates initial action instructions for the user, such as "use a cooling sheet and stay hydrated" or "contact a medical institution immediately."

[0361] 5. Data transmission to medical professionals:

[0362] The server then sends detailed data, including the analysis results, to medical professionals, who can then use this data to make more accurate diagnoses and treatments.

[0363] 6. Responding to Requests for Additional Information:

[0364] If the medical professional needs more information, the server forwards the request to the user, who will then be prompted with a follow-up question, such as "Do you have a rash?", which the user can answer and then send the data back to the server.

[0365] Examples:

[0366] Scenario: A child has a high fever of 39 degrees.

[0367] User Action:

[0368] The user (parent) opens the app on their smartphone and enters information into the question form, such as "Temperature: 39 degrees," "I have a cough," and "Symptoms started last night." As the parent types, the emotion engine analyzes the parent's tone of voice and typing speed in real time. If the parent says something like, "What should I do now?", the voice is judged to be highly anxious.

[0369] Terminal behavior:

[0370] The device temporarily stores the input data and emotion data, and transmits them to the server via encrypted communication.

[0371] Server behavior:

[0372] After receiving the data, the server validates it, classifies the symptoms, and assesses their severity. It assesses the temperature as "39°C or higher, a serious condition," taking into account the user's high level of anxiety. As an initial response, it generates and displays the following advice: "Use a cooling sheet and stay hydrated. Remain calm and contact a medical institution immediately." The analysis results are sent to a medical professional, who makes a diagnosis based on the received data. If necessary, additional questions such as "Do you have a rash?" are displayed in the device application, and additional information is collected when the user answers them.

[0373] This system allows parents and caregivers to respond quickly and accurately to their child's health condition, and medical professionals to make efficient diagnoses. In addition, the addition of emotional data-based responses reduces the psychological burden on users and enables smoother medical responses.

[0374] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0375] Step 1:

[0376] The user uses the terminal means to input information about the child's health condition.

[0377] Input: The questionnaire includes information such as current body temperature, type of symptoms (fever, cough, vomiting, etc.), when symptoms began, and other related symptoms (rash, difficulty breathing, etc.). The user's voice, typing speed, and facial expressions are also collected.

[0378] Specific actions: The user opens the smartphone application and enters specific numerical values ​​and symptom information into the form, such as "body temperature: 39 degrees" or "persistent cough."

[0379] Step 2:

[0380] The device collects and temporarily stores the entered health and emotional data.

[0381] Input: Health information entered by the user and voice, typing speed, and facial expression data collected by the emotion engine.

[0382] Data processing: Encrypt the collected data.

[0383] Output: Encrypted health information and emotion data.

[0384] Specific operation: The device encrypts the collected information and prepares it to be sent to the server.

[0385] Step 3:

[0386] The terminal transmits data to the server over a secure communication channel.

[0387] Input: Encrypted health information and emotion data.

[0388] Output: The encrypted data sent to the server.

[0389] What happens: The device sends data using a secure communications protocol such as HTTPS.

[0390] Step 4:

[0391] The server receives and decrypts the encrypted data.

[0392] Input: Encrypted data sent from the terminal.

[0393] Data processing: Decryption of encrypted data.

[0394] Output: Decoded health information and emotion data.

[0395] Specific operation: The server decrypts the received data and obtains the original health information and emotion data.

[0396] Step 5:

[0397] The server validates the received data.

[0398] Input: Decoded health information and emotion data.

[0399] Data calculation: Check for missing required fields and abnormal values.

[0400] Output: The validated data.

[0401] Specific behavior: The server checks the accuracy and completeness of the data and generates a warning message if there are any abnormal values.

[0402] Step 6:

[0403] The server categorizes symptoms and assesses their severity.

[0404] Input: Validated health information.

[0405] Data computation: Classification and severity assessment using ML-based algorithms.

[0406] Output: Symptom classification and severity rating.

[0407] Specific operation: For example, the server evaluates the patient's body temperature as "39 ​​degrees or higher, a serious condition," and decides on the next course of action.

[0408] Step 7:

[0409] The server analyzes the emotion data.

[0410] Input: Validated emotion data.

[0411] Data Computation: Emotional state is assessed using the emotion engine's analytical algorithms.

[0412] Output: Emotional state assessment results.

[0413] Specific behavior: If the user is determined to be in a highly anxious state, appropriate countermeasures are adjusted based on the analysis results.

[0414] Step 8:

[0415] The server generates an initial response method.

[0416] Input: Symptom classification results, severity rating, emotional state rating results.

[0417] Data calculation: Generate appropriate response methods based on this data.

[0418] Output: Initial response method.

[0419] Specific actions: The server generates specific advice such as "Use cooling pads, stay hydrated, stay calm and contact a medical professional."

[0420] Step 9:

[0421] The server sends the generated initial response instructions to the user.

[0422] Input: Initial response method.

[0423] Output: Initial response instructions sent to the user.

[0424] Specific operation: The server sends the advice to the terminal, which displays it to the user.

[0425] Step 10:

[0426] The server sends the analysis results to a medical professional.

[0427] Input: Analysis results.

[0428] Output: Analysis results sent to medical professionals.

[0429] What it does: The server encrypts the analysis results and sends them to the medical professional's system using a secure communication channel.

[0430] Step 11:

[0431] A server responds to requests for additional information from medical professionals.

[0432] Input: Request for additional information.

[0433] Output: The result of collecting additional information.

[0434] What it does: The medical professional enters a follow-up question, such as "Do you have a rash?", which the server forwards to the user's device. The user provides additional information and sends it back to the server.

[0435] (Application example 2)

[0436] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0437] There is a need for a system that can quickly and accurately monitor a child's health condition, reduce the psychological burden on parents and caregivers, and immediately provide appropriate medical treatment from experts. However, existing systems do not adequately consider the user's emotional state, do not adequately assess the severity of the condition, and do not provide an easy-to-use interface for the user. This makes it difficult to provide prompt medical treatment.

[0438] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting and analyzing the user's emotional state, means for adjusting an initial response method based on the emotional data, and robot means for collecting the child's health condition data and emotional data and transmitting them to the server. This enables a quick and accurate initial response adapted to the user's emotions and improves the accuracy of expert diagnoses.

[0439] The "terminal means" is a device that allows a user to input information about the health condition of a child.

[0440] The "server means" is a device that receives data sent from the terminal means and performs various analyses.

[0441] The "expert means" is a means for transmitting the analyzed data to an expert and providing feedback from the expert to the user.

[0442] The "additional information request means" is a means for responding to requests for additional information from experts.

[0443] The "emotion collection means" is a device that collects the user's voice, input speed, facial expression, etc., and analyzes their emotional state.

[0444] The "emotion response means" is a means for adjusting the initial response method based on the emotion data.

[0445] The "robot means" is a device that collects the child's health and emotional data and transmits it to the server.

[0446] The system of this invention includes terminal means for a user to input information about the child's health condition, server means for receiving and analyzing data sent from the terminal means, means for presenting an appropriate initial response method to the user based on the analyzed data, means for sending the analysis results to an expert, means for responding to requests for additional information from the expert, means for collecting and analyzing the user's emotional state, means for adjusting the initial response method based on the emotional data, and robot means for collecting the child's health condition data and emotional data and sending it to the server.

[0447] The hardware used is a terminal such as a smartphone or tablet, as well as a home security robot, while the software used is the EmotionRecognizer library (for emotion collection), the HealthDataCollector library (for health status data collection), the ActionSuggester library (for suggesting initial response methods), the Python programming language, and the HTTP request library (for data communication).

[0448] The process begins with the user entering information about their child's health using a terminal. The entered information includes body temperature, the type of symptoms (fever, cough, vomiting, etc.), the time of symptom onset, and other related symptoms (rash, difficulty breathing, etc.). In addition, the emotion collection means collects emotion data from the user's voice, input speed, facial expressions, etc.

[0449] The health condition data and emotion data sent from the terminal means are received by the server means. The server means validates the received data and then executes an algorithm to classify symptoms and assess their severity. It also analyzes the emotion data to understand the user's emotional state. Based on this, it adjusts the initial response method provided to the user and generates appropriate advice.

[0450] The advice includes specific instructions such as "use a cooling sheet and stay hydrated" and "contact a medical institution immediately." The results are presented to the user and simultaneously sent to the specialist. The specialist can make a highly accurate diagnosis and take appropriate action based on the received data. If the specialist requires additional information, additional questions for the user are displayed on the terminal means. The user inputs the additional information and sends it to the server means.

[0451] As a concrete example, if a child has a high fever of 39 degrees, the parent would use the terminal to input information such as "Temperature: 39 degrees," "Coughing," and "Symptoms started last night." At this time, feelings of anxiety and impatience are also collected from the parent's tone of voice and input speed. The data sent from the terminal means is analyzed by the server means, and specific advice such as "Use a cooling sheet and stay hydrated. Remain calm and contact a medical institution immediately" is returned. Furthermore, if the specialist asks additional questions such as "Do you have a rash?", these are also displayed to the user, and the answer is sent to the server.

[0452] An example of a prompt is, "A parent has entered their child's health status. The child's temperature is 39 degrees and they have been coughing since last night. The parent's voice is very unstable and they are typing quickly. Please provide an appropriate initial response based on the analysis results."

[0453] In this way, the present invention enables quick and smooth information flow between users and specialists, and provides emotionally sensitive responses, thereby realizing more accurate medical responses.

[0454] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0455] Step 1:

[0456] The user uses the device to input information about the child's health condition. The input data includes body temperature, type of symptoms, time of onset, and other related symptoms. This information is collected through the device's input interface. In addition, the device also collects the user's emotional data, which is obtained through voice tone, input speed, and facial expression analysis.

[0457] Step 2:

[0458] The device encrypts the health condition data and emotional data entered by the user and sends them to the server. The data sent includes the user's input information (e.g., body temperature, symptoms) and the collected emotional data.

[0459] Step 3:

[0460] The server validates the received data. Validation is a process to check the accuracy and completeness of the data, checking for missing data or abnormal values. Input: Health status data and emotion data sent from the device. Output: Validated data.

[0461] Step 4:

[0462] The server runs an algorithm to assess the severity of symptoms based on the validated data. For example, a body temperature of 39°C or higher is considered severe. Input: Validated data. Output: Symptom classification and severity assessment results.

[0463] Step 5:

[0464] The server analyzes the emotional data and understands the user's emotional state. The analysis is based on collected voice tone, input speed, and facial expression data. Input: Emotional data. Output: Analyzed emotional state.

[0465] Step 6:

[0466] The server generates an initial response method to provide to the user based on the symptom severity assessment result and emotional state. This includes specific actions such as "use a cooling sheet and stay hydrated" and "contact a medical institution immediately." Input: Severity assessment result and emotional state. Output: Initial response method.

[0467] Step 7:

[0468] The server sends the generated initial response method to the terminal and presents it to the user. The user responds accordingly. Input: Initial response method. Output: Initial response method displayed on the terminal.

[0469] Step 8:

[0470] The server sends the analysis results and detailed data about the user's emotional state to the expert. Input: Analysis results and emotional state. Output: Data transmission to the expert.

[0471] Step 9:

[0472] If the expert needs more information, he sends a follow-up question to the user through the server, for example a specific question such as "Do you have a rash?" Input: Follow-up question from the expert Output: Follow-up question displayed on the terminal.

[0473] Step 10:

[0474] The user inputs additional information through the terminal, which is then sent to the server. The server then performs the necessary analysis again and sends the results to the expert. Input: Additional information from the user. Output: Reanalysis results.

[0475] This allows for smooth information flow between users and specialists, enabling prompt and appropriate medical responses.

[0476] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0477] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0478] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0479] [Second embodiment]

[0480] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0481] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0482] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0483] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0484] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0485] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0486] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0487] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0488] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0489] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0490] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0491] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0492] System Overview

[0493] This invention relates to a system in which a user inputs information about their child's health condition using a terminal means, the data is analyzed by a server means, an appropriate initial response method is provided, and the data is then sent to a medical professional.

[0494] Program processing

[0495] User Action:

[0496] The user uses a terminal (such as a smartphone or tablet) to input information about their child's health condition. The questionnaire includes the following information: "Current body temperature," "Type of symptoms (fever, cough, vomiting, etc.)," ​​"Time of symptom onset," and "Other related symptoms (rash, difficulty breathing, etc.)."

[0497] Terminal behavior:

[0498] The device receives the information entered by the user and sends the data to the server, where it is encrypted to protect privacy and security.

[0499] Server behavior:

[0500] The server receives the data sent from the terminal and then performs the following analysis:

[0501] 1. Data Validation:

[0502] The server verifies the accuracy and completeness of the received data.

[0503] 2. Symptom classification and severity assessment:

[0504] The server analyzes the data using special algorithms to classify the child's symptoms and assess their severity - for example, a temperature of 39 degrees or higher is considered severe.

[0505] 3. Generate initial response methods:

[0506] Based on the analysis results, the server generates initial action instructions for the user, such as "use a cooling sheet and stay hydrated" and "contact a medical institution immediately."

[0507] 4. Data transmission to medical professionals:

[0508] The server then sends detailed data, including the analysis results, to medical professionals, who can then use this data to make more accurate diagnoses and treatments.

[0509] 5. Responding to requests for additional information:

[0510] If the medical professional determines that further information is needed, they will request it from the user via the server, and a follow-up question such as "Do you have a rash?" will be displayed on the device.

[0511] Examples:

[0512] Scenario: A child has a high fever of 39 degrees.

[0513] The user (parent) opens the terminal and enters the fever information:

[0514] Enter "Temperature: 39 degrees," "Coughing," and "Symptoms started last night."

[0515] The terminal sends the entered data to the server:

[0516] After transmission, the server immediately validates the received data.

[0517] The server evaluates the symptom classification and severity based on the received data:

[0518] "His body temperature is over 39 degrees, so his condition is considered serious."

[0519] The server provides the user with an initial response:

[0520] The device displays the following advice: "Use cooling pads and stay hydrated. Contact a medical institution immediately."

[0521] The server sends the analysis results to the medical professional:

[0522] A medical professional makes a diagnosis based on the received data.

[0523] If your healthcare professional needs additional information:

[0524] For example, an additional question such as "Do you have a rash?" is displayed on the terminal via the server, and the user answers it.

[0525] The system enables parents and caregivers to respond quickly and accurately to their child's health conditions and allows medical professionals to make efficient diagnoses.

[0526] The processing flow will be explained below.

[0527] Step 1:

[0528] The user enters information about their child's health condition using a terminal (e.g., a smartphone or tablet). The questionnaire includes questions such as "current body temperature," "type of symptoms (fever, cough, vomiting, etc.)," ​​"when symptoms began," and "other related symptoms (rash, difficulty breathing, etc.)."

[0529] Step 2:

[0530] The user presses the submit button to submit the information entered in the inquiry form.

[0531] Step 3:

[0532] The terminal receives the transmitted information, encrypts the data, and transmits it to the server means.

[0533] Step 4:

[0534] The server receives the data sent from the device and validates it for accuracy and completeness.

[0535] Step 5:

[0536] The server begins analyzing the incoming data. It uses an algorithm to analyze the data and classify symptoms and assess their severity. For example, a temperature of 39 degrees or higher is considered severe.

[0537] Step 6:

[0538] Based on the analysis results, the server generates initial action instructions for the user, such as "use a cooling sheet and stay hydrated" or "contact a medical institution immediately."

[0539] Step 7:

[0540] The server transmits the generated initial response method to the terminal means.

[0541] Step 8:

[0542] The terminal displays the initial response advice received from the server to the user, who then takes appropriate initial response according to the advice provided.

[0543] Step 9:

[0544] The server sends the analysis results as detailed data to medical professionals, enabling them to make quick and accurate diagnoses and take appropriate action based on the data.

[0545] Step 10:

[0546] If the medical professional determines that more information is needed, the additional information is requested from the user through the server.

[0547] Step 11:

[0548] The server sends a request for additional information from the medical professional to the terminal means.

[0549] Step 12:

[0550] The terminal displays a request for additional information to the user, who answers the additional questions and resubmits the answers through the terminal.

[0551] Step 13:

[0552] The server analyzes the re-received additional data and transmits it again to the medical professional.

[0553] Step 14:

[0554] The medical professional will determine the final diagnosis and treatment and notify the user via the server, who will then follow the final instructions.

[0555] This process allows users to quickly and accurately address their child's health condition and allows medical professionals to efficiently diagnose the condition.

[0556] Example 1

[0557] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0558] In today's world, it is extremely important to quickly and accurately assess a child's health condition and provide appropriate initial treatment. However, because most parents and caregivers have limited medical knowledge, it is difficult to determine whether a child's symptoms are serious. They also have limited means of quickly learning the appropriate treatment. Furthermore, access to medical facilities can be difficult, and communication with medical professionals can be difficult. To solve these problems, a system is needed that can quickly analyze data on a child's health condition, provide appropriate initial treatment, and send data to medical professionals for feedback.

[0559] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0560] In this invention, the server includes means for receiving data sent from the user, encrypting it, and analyzing it, means for classifying symptoms and assessing their severity based on the analyzed data, and means for generating an appropriate initial response method based on the analysis results. This allows the user to quickly and accurately understand their child's health condition and take appropriate initial responses. Furthermore, by including means for sending the analyzed data to a medical professional and means for responding to requests for additional information from the medical professional, communication with the medical professional is facilitated, enabling more accurate diagnoses and responses.

[0561] "Terminal means" refers to a device used by a user to input information, specifically a smartphone or tablet.

[0562] The term "server means" refers to a computer system that receives data sent from the terminal means and performs analysis and other processing of the data.

[0563] "Encryption" refers to the technology of using a specific algorithm to protect the contents of data in order to transmit it securely.

[0564] "Validation" refers to the process of checking whether received data is accurate and complete, and verifying that there are no anomalies.

[0565] "Symptom classification" refers to the process of analyzing data about a child's health and categorizing it based on specific symptoms.

[0566] "Severity assessment" refers to the process of determining the severity of a symptom and assessing its severity.

[0567] "Initial response methods" refers to specific response procedures and advice that users should take immediately regarding their child's health condition.

[0568] "Medical professionals" refers to people in professions such as doctors and nurses who have specialized knowledge and skills related to medical care.

[0569] "Information Request" refers to the act of asking a User for additional data or information required by a medical professional.

[0570] "Interface" refers to the screen and input method that a user uses to interact with a system, and specifically refers to the user interface of an application.

[0571] This invention is a system in which a user inputs information about the child's health condition using a terminal means, and a server means analyzes the data, provides an appropriate initial response method, and then transmits the data to a medical professional.

[0572] User Actions

[0573] Users use a device such as a smartphone or tablet to launch the application and enter information about their child's health. The questionnaire includes items such as "current body temperature," "type of symptoms (fever, cough, vomiting, etc.)," ​​"when symptoms began," and "other related symptoms (rash, difficulty breathing, etc.)." By entering this information, users can record their child's health in detail.

[0574] Device behavior

[0575] The device receives the information entered by the user and sends the data to the server, where it is encrypted using the AES-256 algorithm and transmitted using a secure communication protocol (e.g., HTTPS), ensuring the privacy and security of the data.

[0576] Server Operation

[0577] The server receives the data sent from the terminal and then performs the following analysis:

[0578] 1. Data Validation

[0579] The server checks the accuracy and completeness of the received data, checking the data format (e.g., whether the body temperature is within the range of 35-42°C) and whether required fields have been filled in, and returns an error to the terminal if there are any errors.

[0580] 2. Symptom classification and severity assessment

[0581] The server uses an analytical algorithm to analyze the data and classify the child's symptoms and assess their severity. For example, a temperature of 39 degrees or higher is considered severe. The algorithm is based on a machine learning model and uses patterns learned from past data to make the classification.

[0582] 3. Generate initial response methods

[0583] The server generates appropriate initial response instructions based on the analysis results. For example, if the patient has a temperature of 39°C, a cough, and symptoms began last night, the server generates the following advice: "Use a cooling pad, stay hydrated, and contact a medical institution immediately."

[0584] Sending data to medical professionals and responding to requests for additional information

[0585] The server sends the data, including the analysis results, to the medical professional. The medical professional accesses the EHR system using a secure communication protocol and makes a diagnosis based on the received data. If the medical professional determines that additional information is required, an additional question, such as "Do you have a rash?", is displayed on the device via the server. By answering this question, the user can provide the medical professional with the necessary additional information.

[0586] Specific examples

[0587] Scenario: A child has a high fever of 39 degrees.

[0588] 1. User:

[0589] The parent opens the device and enters the following information into the application's question form: "Temperature: 39 degrees," "Having a cough," and "Symptoms started last night."

[0590] 2. Terminal:

[0591] The terminal encrypts the entered data and sends it to the server using a secure communication protocol (HTTPS).

[0592] 3. Server:

[0593] The server validates the incoming data to ensure it is in the correct format and range, then uses an analytical algorithm to assess the symptom classification and severity, resulting in a "high fever" diagnosis.

[0594] 4. Server:

[0595] The server generates an initial response method such as "Use a cooling sheet and stay hydrated. Contact a medical institution immediately," and displays it on the terminal.

[0596] 5. Server:

[0597] The server sends the analysis results to medical professionals, who then make a diagnosis based on the received data via the EHR system.

[0598] 6. Request for additional information:

[0599] The medical professional sends a follow-up question, "Do you have a rash?", which is displayed on the device and the user answers.

[0600] The system allows users to respond quickly and accurately to their child's health conditions and allows medical professionals to make efficient diagnoses.

[0601] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0602] Step 1:

[0603] Data Entry

[0604] User action: The user launches an application using a smartphone or tablet.

[0605] Input: The user inputs information about their health condition (e.g., "Temperature: 39°C," "I have a cough," "Symptoms started last night").

[0606] What it does: The user provides information about their child's health by filling out a form in the application.

[0607] Step 2:

[0608] Data Receipt and Encryption

[0609] Terminal operation: The terminal receives the information entered by the user.

[0610] Input: Health information data entered by the user.

[0611] Data processing: The terminal encrypts the data with the AES-256 algorithm and sends it to the server using a secure communication protocol (HTTPS).

[0612] Output: The encrypted health information data is sent to the server.

[0613] Specific operation: The device encrypts data and communicates securely.

[0614] Step 3:

[0615] Data Validation

[0616] Server operation: The server receives the data sent from the terminal.

[0617] Input: Encrypted health information data.

[0618] Data calculation: The server decrypts the data and checks the data format (e.g., whether the body temperature is within the range of 35-42 degrees) and whether all required fields have been filled in.

[0619] Output: Successfully validated health information data.

[0620] Specific operation: Checks the data format and required fields, and returns an error to the terminal if there are any errors.

[0621] Step 4:

[0622] Symptom classification and severity rating

[0623] Server Operation: The server executes the data analysis algorithms.

[0624] Input: Health information data that has passed validation.

[0625] Data calculation: The server uses machine learning models to analyze health information. If the body temperature is 39 degrees, it will be classified as a high fever and the severity will be assessed as "high."

[0626] Output: Categorized symptom data and assessment results.

[0627] What it does: It uses machine learning algorithms to analyze health information, classify it into appropriate categories, and assess its severity.

[0628] Step 5:

[0629] Generate initial response methods

[0630] Server operation: The server generates an initial response method based on the analysis results.

[0631] Input: Categorized symptom data and assessment results.

[0632] Data calculation: The server generates appropriate initial response measures based on predefined response measures. For example, if the patient has a temperature of 39 degrees, a cough, and symptoms began last night, the server generates advice such as, "Use a cooling pad, stay hydrated, and contact a medical institution immediately."

[0633] Output: Advice on how to respond first.

[0634] Specific action: Generate a response method based on the conditions and provide it to the user.

[0635] Step 6:

[0636] Sending data to medical professionals

[0637] Server operation: The server sends detailed data including the analysis results to a medical professional.

[0638] Input: Initial response advice and analyzed health information data.

[0639] Data processing: The server re-encrypts the data and sends it using a secure communication protocol to a system accessed by medical professionals.

[0640] Output: Detailed data received by the medical professional.

[0641] What happens: Sends data to an EHR system and makes it available to healthcare professionals.

[0642] Step 7:

[0643] Responding to requests for additional information

[0644] User Action: If necessary, the medical professional can request additional information.

[0645] Input: Request for additional information from medical professional.

[0646] Data computation: The server sends a request for additional information to the terminal, and the user answers it to gather more data (e.g., "Do you have a rash?").

[0647] Output: Additional information from the user.

[0648] Specific operation: The server sends a request for additional information to the terminal and collects the response.

[0649] In this way, each step works in coordination, enabling a quick and accurate assessment of a child's health condition and early response.

[0650] (Application example 1)

[0651] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0652] In modern society, it is extremely important for parents and caregivers to respond promptly and appropriately to their children's health conditions. However, when sudden symptoms occur, accurate initial response is required, which is difficult for general users without specialized knowledge. Furthermore, rapid collaboration with medical professionals is also required, which requires a system that can appropriately collect, analyze, and share information. Data security and privacy protection are also important issues.

[0653] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0654] In this invention, the server includes a terminal means for receiving and analyzing information on the child's health condition entered by the user, a means for encrypting and receiving data transmitted from the terminal means and analyzing it, a means for presenting an appropriate initial response method to the user based on the data analyzed by the server means, a means for transmitting the analyzed data to a specialist, a means for responding to requests for additional information from the specialist, a display means for presenting an initial response method to the user based on the analysis results, and a means for validating the data. This enables parents and caregivers to respond to the child's health condition quickly and accurately and facilitates smooth cooperation with specialists.

[0655] The "terminal means" is a device that allows a user to input information about the health condition of a child.

[0656] "Data" refers to information entered by the user about the child's health, including temperature, symptoms, and the timing of symptoms.

[0657] The "server means" is a device for receiving and analyzing data sent from the terminal means.

[0658] "Initial response method" refers to guidelines for specific steps and actions that users should take based on the analyzed data.

[0659] "Expert" refers to someone with specialized medical knowledge, including doctors and nurses.

[0660] "Request for additional information" refers to the expert requesting further required information from the user.

[0661] The "display means" is a device or function for visually presenting the analysis results and initial response methods to the user.

[0662] "Data validation" is the process of verifying the accuracy and completeness of received data.

[0663] An "algorithm" is a computational method by which the server means analyzes the data and assesses the severity of the symptoms.

[0664] This invention builds a system that monitors children's health conditions and provides users with appropriate initial response methods. The system is mainly composed of a terminal means used by the user, a server means for analyzing data, and a means for supporting collaboration with experts.

[0665] Hardware and software used

[0666] 1. Terminal means:

[0667] Hardware: Smartphones, tablets

[0668] Software: User interface using React Native

[0669] 2. Server means:

[0670] Hardware: Standard server machine

[0671] Software: Python (Flask framework), MySQL database, data encryption with OpenSSL

[0672] Program processing

[0673] User Action:

[0674] Users use a smartphone or tablet application to enter data about their child's health, including the following:

[0675] Body temperature: 39 degrees

[0676] Cough: Yes

[0677] Symptom onset: Last night

[0678] Other associated symptoms: None

[0679] Terminal behavior:

[0680] The device encrypts the entered information (AES-256) and sends it to the server using a device-specific method (e.g., sendSecureData). This method ensures data integrity and privacy.

[0681] Server behavior:

[0682] The server receives the data sent from the terminal and then performs the following processes.

[0683] 1. Data Validation:

[0684] The server verifies the received data for accuracy and completeness, checking for blanks and filtering out inappropriate data.

[0685] 2. Data Analysis:

[0686] The server uses special algorithms (e.g., malignancy determination algorithms) to analyze the child's symptoms and severity.

[0687] 3. Generate initial response methods:

[0688] Based on the analysis results, the system generates initial action instructions to be presented to the user, such as "Use a cooling sheet, stay hydrated, and contact a medical institution immediately."

[0689] 4. Sending data to the expert:

[0690] If necessary, detailed data including analysis results can be sent to medical professionals, who can use this data to make more accurate diagnoses and treatments.

[0691] 5. Request for additional information:

[0692] If the medical professional needs more information, they will ask the user a follow-up question via the server, e.g., "Do you have a rash?"

[0693] Specific examples

[0694] Example of a prompt for the user to enter:

[0695] Child's current status:

[0696] Body temperature: 39°C

[0697] Cough: Yes

[0698] Symptoms started last night

[0699] Other associated symptoms: None

[0700] Send: true

[0701] The system allows parents and caregivers to respond quickly to sudden illnesses and medical professionals to provide appropriate support. The system also ensures data security and privacy, making it safe to use in everyday life.

[0702] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0703] Step 1:

[0704] Users use a smartphone or tablet to enter information about their child's health into the application form. Information entered includes body temperature, whether or not the child has a cough, when symptoms began, and other related symptoms. Examples of input data include "body temperature: 39°C," "cough present," "when symptoms began: last night," and "no other related symptoms."

[0705] Step 2:

[0706] The terminal encrypts the entered information. Specifically, it encrypts the data using the AES-256 encryption method. The encrypted data is then sent to the server using the terminal's sendSecureData method. This method ensures data integrity and privacy.

[0707] Step 3:

[0708] The server receives the encrypted data sent from the device. It first decrypts the received data and then validates it. Data validation checks whether there are any blank fields or inappropriate data. For example, it checks whether "body temperature" is a numeric value and whether "cough" is "yes" or "no."

[0709] Step 4:

[0710] The server inputs the validated data into a data analysis algorithm, which primarily classifies symptoms and assesses their severity. If the temperature is 39°C or higher, the algorithm evaluates the symptoms as severe and determines that escalation is necessary. Based on the results, the initial response method to be taken is generated.

[0711] Step 5:

[0712] Based on the analysis results, the server provides the user with initial response instructions. The displayed initial response instructions include specific instructions for action. For example, advice such as "Use a cooling sheet, stay hydrated, and contact a medical institution immediately" is displayed on the smartphone.

[0713] Step 6:

[0714] The server then sends the analysis results to a medical professional, if necessary. The data sent includes the information entered by the user and the server's analysis results, allowing the professional to perform a more detailed diagnosis.

[0715] Step 7:

[0716] If the specialist needs more information, the server sends the user a follow-up question, such as "Do you have a rash?", which is displayed on the smartphone. The user answers the question and the data is sent back to the server.

[0717] Step 8:

[0718] The server then re-analyzes the additional information and updates the necessary response procedures, ensuring that the user receives appropriate guidance on an ongoing basis. This process provides real-time collaboration between the user and the expert.

[0719] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0720] System Overview

[0721] This invention relates to a system in which a user inputs information about their child's health condition, transmits the information to a server via a terminal, and the server analyzes the received data and provides an appropriate initial response method. The analyzed data is then transmitted to a medical professional, who provides any necessary additional information. The system also incorporates an emotion engine that recognizes the user's emotions and reflects them in the analysis results and response methods.

[0722] Program processing

[0723] User Action:

[0724] The user uses a terminal (e.g., a smartphone or tablet) to input information about their child's health condition. The questionnaire includes questions such as "current body temperature," "type of symptoms (fever, cough, vomiting, etc.)," ​​"when symptoms began," and "other related symptoms (rash, difficulty breathing, etc.)." In addition, an emotion engine runs to collect the user's emotional state while they are entering information.

[0725] Terminal behavior:

[0726] The terminal collects information and emotion data input by the user, encrypts it, and transmits it to the server. The emotion engine analyzes the user's emotion from their voice, input speed, facial expression, etc., and transmits this data to the server as additional information.

[0727] Server behavior:

[0728] The server receives the data sent from the terminal and then performs the following analysis:

[0729] 1. Data Validation:

[0730] The server verifies the accuracy and completeness of the received data.

[0731] 2. Symptom classification and severity assessment:

[0732] The server analyzes the data using special algorithms to classify the child's symptoms and assess their severity - for example, a temperature of 39 degrees or higher is considered severe.

[0733] 3. Emotional Data Analysis:

[0734] The server analyzes the emotion data sent from the emotion engine to understand the user's emotional state. For example, if it determines that the user is very anxious, it will adjust the content and expression of the advice appropriately.

[0735] 4. Generate initial response methods:

[0736] Based on the analysis results and emotional data, the server generates initial action instructions for the user, such as "use a cooling sheet and stay hydrated" or "contact a medical institution immediately."

[0737] 5. Data transmission to medical professionals:

[0738] The server then sends detailed data, including the analysis results, to medical professionals, who can then use this data to make more accurate diagnoses and treatments.

[0739] 6. Responding to Requests for Additional Information:

[0740] If the medical professional determines that further information is needed, they will request it from the user via the server, and a follow-up question such as "Do you have a rash?" will be displayed on the device.

[0741] Examples:

[0742] Scenario: A child has a high fever of 39 degrees.

[0743] The user (parent) opens the terminal and enters the fever information:

[0744] The user types in "Temperature: 39 degrees," "Having a cough," and "Symptoms started last night." The emotion engine also collects feelings of anxiety and impatience from the parent's tone of voice and typing speed while they are typing.

[0745] The device sends the input data and emotion data to the server:

[0746] After transmission, the server immediately validates the received data and emotion data.

[0747] The server evaluates the symptom classification and severity based on the received data and emotion data:

[0748] The assessment is that the child's temperature is over 39 degrees, making the condition critical, and takes into account the parents' emotional state of high anxiety.

[0749] The server provides the user with an initial response:

[0750] The advice displayed is, "Use cooling pads and stay hydrated. Remain calm and contact a medical institution immediately."

[0751] The server sends the analysis results to the medical professional:

[0752] Medical professionals will make a diagnosis based on the data received, take into account parental concerns, and provide professional advice.

[0753] If your healthcare professional needs additional information:

[0754] For example, an additional question such as "Do you have a rash?" is displayed on the terminal via the server, and the user answers it.

[0755] The system allows parents and caregivers to respond quickly and accurately to their child's health condition, and medical professionals to make efficient diagnoses. The addition of emotional data-based responses also reduces the psychological burden on users, enabling smoother medical responses.

[0756] The processing flow will be explained below.

[0757] Step 1:

[0758] The user inputs information about their child's health condition using a terminal (e.g., a smartphone or tablet). The questionnaire includes information such as "current body temperature," "type of symptoms (fever, cough, vomiting, etc.)," ​​"when symptoms began," and "other related symptoms (rash, difficulty breathing, etc.)." As the user inputs information, the emotion engine analyzes the user's emotional state based on their tone of voice, typing speed, facial expression, etc.

[0759] Step 2:

[0760] The user clicks the submit button to submit the input.

[0761] Step 3:

[0762] The terminal encrypts the information and emotion data input by the user and transmits them to the server means.

[0763] Step 4:

[0764] The server receives the data sent from the terminal and validates the received data to check its accuracy and completeness.

[0765] Step 5:

[0766] The server begins analyzing the incoming data. It uses an algorithm to analyze the data from the user, classify the child's symptoms, and assess their severity. For example, a temperature of 39 degrees or higher is considered severe.

[0767] Step 6:

[0768] The emotion engine analyzes the transmitted emotion data and understands the user's emotional state, such as assessing anxiety, impatience, or restlessness.

[0769] Step 7:

[0770] The server then uses the analysis results and emotional data to provide the user with appropriate initial response advice, such as "Use a cooling sheet and stay hydrated. Remain calm and immediately contact a medical institution."

[0771] Step 8:

[0772] The server transmits the generated initial response method to the terminal means.

[0773] Step 9:

[0774] The terminal displays the initial response advice received from the server to the user, who then takes appropriate initial response according to the advice provided.

[0775] Step 10:

[0776] The server sends the analysis results to medical professionals, allowing them to make quick and accurate diagnoses and take appropriate action based on the data.

[0777] Step 11:

[0778] If the medical professional determines that more information is needed, a request for additional information is sent to the user through the server means.

[0779] Step 12:

[0780] The server sends a request for additional information from the medical professional to the terminal means.

[0781] Step 13:

[0782] The terminal displays a request for additional information to the user, who answers the additional questions and resubmits through the terminal.

[0783] Step 14:

[0784] The server analyzes the additional data received from the user and transmits it back to the medical professional.

[0785] Step 15:

[0786] The medical professional will determine the final diagnosis and treatment and notify the user via the server, who will then follow the final instructions.

[0787] This series of processes allows users to deal with their child's health condition quickly and accurately, and medical professionals can make efficient diagnoses. In addition, the emotional engine reduces the user's psychological burden and enables smoother medical treatment.

[0788] Example 2

[0789] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0790] Conventional health monitoring systems primarily involve inputting and analyzing information about a child's health condition. However, they lack consideration for the user's emotional state, making it difficult to completely alleviate the user's psychological burden. Furthermore, it is difficult to generate a fast and accurate initial response method or to communicate efficiently with medical professionals. Therefore, there is a need for a system that can respond quickly and appropriately while taking the user's emotional state into account.

[0791] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0792] In this invention, the server includes means for analyzing data sent from the user, means for generating an initial response method based on the analyzed data, and means for analyzing emotion data collected by the emotion engine and adjusting the initial response method, thereby enabling prompt and appropriate health management that takes the user's emotional state into consideration.

[0793] "Terminal means" refers to an electronic device such as a smartphone or tablet, which allows a user to input information about the child's health condition.

[0794] The term "server means" refers to a computer system that receives and analyzes data sent from the terminal means.

[0795] The "means for presenting an appropriate initial response method to the user" refers to a method for presenting an appropriate response method to the user based on the data analyzed by the server means.

[0796] "Means for sending to a medical professional" refers to a method by which the server means sends the analyzed data to a medical professional.

[0797] "Means for responding to requests for additional information" refers to methods for asking questions or gathering information from the user in response to requests for additional information from medical professionals.

[0798] An "emotion engine" refers to a tool that has the function of collecting and analyzing a user's emotional state from their voice, input speed, facial expressions, etc.

[0799] "Means for transmitting emotion data to server means" refers to a method for transmitting emotion data collected by the emotion engine to server means.

[0800] The "means for adjusting the initial response method based on the emotion data" refers to a method in which the server means analyzes the emotion data and appropriately adjusts the initial response method based on the results of the analysis.

[0801] This invention relates to a system in which a user inputs information about their child's health condition, transmits the information to a server via a terminal, and the server analyzes the received data and provides an appropriate initial response method. The analyzed data is then transmitted to a medical professional, who provides any necessary additional information. The system also incorporates an emotion engine that recognizes the user's emotions and reflects them in the analysis results and response methods.

[0802] User Action:

[0803] The user uses a terminal (e.g., a smartphone or tablet) to input information about their child's health condition. The questionnaire includes questions such as "current body temperature," "type of symptoms (fever, cough, vomiting, etc.)," ​​"time of symptom onset," and "other related symptoms (rash, difficulty breathing, etc.)." In addition, an emotion engine runs to collect the user's emotional state while they are entering information.

[0804] Terminal behavior:

[0805] The device temporarily stores the health information and emotional data entered by the user. It then encrypts this data and sends it to the server using a secure communication channel (e.g., HTTPS). The emotion engine analyzes the user's emotions based on their voice, typing speed, facial expressions, etc., and sends this data to the server as additional information.

[0806] Server behavior:

[0807] The server receives the data sent from the terminal and then performs the following series of analyses:

[0808] 1. Data Validation:

[0809] The server checks the received data for accuracy and completeness, especially for missing mandatory fields and anomalous data.

[0810] 2. Symptom classification and severity assessment:

[0811] The server uses a special algorithm to analyze the data, classify the child's symptoms, and assess their severity: for example, a temperature of 39 degrees or higher is considered severe.

[0812] 3. Emotional Data Analysis:

[0813] The server analyzes the emotion data sent from the emotion engine to understand the user's emotional state. For example, if it determines that the user is very anxious, it will adjust the content and expression of the advice appropriately.

[0814] 4. Generate initial response methods:

[0815] Based on the analysis results and emotional data, the server generates initial action instructions for the user, such as "use a cooling sheet and stay hydrated" or "contact a medical institution immediately."

[0816] 5. Data transmission to medical professionals:

[0817] The server then sends detailed data, including the analysis results, to medical professionals, who can then use this data to make more accurate diagnoses and treatments.

[0818] 6. Responding to Requests for Additional Information:

[0819] If the medical professional needs more information, the server forwards the request to the user, who will then be prompted with a follow-up question, such as "Do you have a rash?", which the user can answer and then send the data back to the server.

[0820] Examples:

[0821] Scenario: A child has a high fever of 39 degrees.

[0822] User Action:

[0823] The user (parent) opens the app on their smartphone and enters information into the question form, such as "Temperature: 39 degrees," "I have a cough," and "Symptoms started last night." As the parent types, the emotion engine analyzes the parent's tone of voice and typing speed in real time. If the parent says something like, "What should I do now?", the voice is judged to be highly anxious.

[0824] Terminal behavior:

[0825] The device temporarily stores the input data and emotion data, and transmits them to the server via encrypted communication.

[0826] Server behavior:

[0827] After receiving the data, the server validates it, classifies the symptoms, and assesses their severity. It assesses the temperature as "39°C or higher, a serious condition," taking into account the user's high level of anxiety. As an initial response, it generates and displays the following advice: "Use a cooling sheet and stay hydrated. Remain calm and contact a medical institution immediately." The analysis results are sent to a medical professional, who makes a diagnosis based on the received data. If necessary, additional questions such as "Do you have a rash?" are displayed in the device application, and additional information is collected when the user answers them.

[0828] This system allows parents and caregivers to respond quickly and accurately to their child's health condition, and medical professionals to make efficient diagnoses. In addition, the addition of emotional data-based responses reduces the psychological burden on users and enables smoother medical responses.

[0829] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0830] Step 1:

[0831] The user uses the terminal means to input information about the child's health condition.

[0832] Input: The questionnaire includes information such as current body temperature, type of symptoms (fever, cough, vomiting, etc.), when symptoms began, and other related symptoms (rash, difficulty breathing, etc.). The user's voice, typing speed, and facial expressions are also collected.

[0833] Specific actions: The user opens the smartphone application and enters specific numerical values ​​and symptom information into the form, such as "body temperature: 39 degrees" or "persistent cough."

[0834] Step 2:

[0835] The device collects and temporarily stores the entered health and emotional data.

[0836] Input: Health information entered by the user and voice, typing speed, and facial expression data collected by the emotion engine.

[0837] Data processing: Encrypt the collected data.

[0838] Output: Encrypted health information and emotion data.

[0839] Specific operation: The device encrypts the collected information and prepares it to be sent to the server.

[0840] Step 3:

[0841] The terminal transmits data to the server over a secure communication channel.

[0842] Input: Encrypted health information and emotion data.

[0843] Output: The encrypted data sent to the server.

[0844] What happens: The device sends data using a secure communications protocol such as HTTPS.

[0845] Step 4:

[0846] The server receives and decrypts the encrypted data.

[0847] Input: Encrypted data sent from the terminal.

[0848] Data processing: Decryption of encrypted data.

[0849] Output: Decoded health information and emotion data.

[0850] Specific operation: The server decrypts the received data and obtains the original health information and emotion data.

[0851] Step 5:

[0852] The server validates the received data.

[0853] Input: Decoded health information and emotion data.

[0854] Data calculation: Check for missing required fields and abnormal values.

[0855] Output: The validated data.

[0856] Specific behavior: The server checks the accuracy and completeness of the data and generates a warning message if there are any abnormal values.

[0857] Step 6:

[0858] The server categorizes symptoms and assesses their severity.

[0859] Input: Validated health information.

[0860] Data computation: Classification and severity assessment using ML-based algorithms.

[0861] Output: Symptom classification and severity rating.

[0862] Specific operation: For example, the server evaluates the patient's body temperature as "39 ​​degrees or higher, a serious condition," and decides on the next course of action.

[0863] Step 7:

[0864] The server analyzes the emotion data.

[0865] Input: Validated emotion data.

[0866] Data Computation: Emotional state is assessed using the emotion engine's analytical algorithms.

[0867] Output: Emotional state assessment results.

[0868] Specific behavior: If the user is determined to be in a highly anxious state, appropriate countermeasures are adjusted based on the analysis results.

[0869] Step 8:

[0870] The server generates an initial response method.

[0871] Input: Symptom classification results, severity rating, emotional state rating results.

[0872] Data calculation: Generate appropriate response methods based on this data.

[0873] Output: Initial response method.

[0874] Specific actions: The server generates specific advice such as "Use cooling pads, stay hydrated, stay calm and contact a medical professional."

[0875] Step 9:

[0876] The server sends the generated initial response instructions to the user.

[0877] Input: Initial response method.

[0878] Output: Initial response instructions sent to the user.

[0879] Specific operation: The server sends the advice to the terminal, which displays it to the user.

[0880] Step 10:

[0881] The server sends the analysis results to a medical professional.

[0882] Input: Analysis results.

[0883] Output: Analysis results sent to medical professionals.

[0884] What it does: The server encrypts the analysis results and sends them to the medical professional's system using a secure communication channel.

[0885] Step 11:

[0886] A server responds to requests for additional information from medical professionals.

[0887] Input: Request for additional information.

[0888] Output: The result of collecting additional information.

[0889] What it does: The medical professional enters a follow-up question, such as "Do you have a rash?", which the server forwards to the user's device. The user provides additional information and sends it back to the server.

[0890] (Application example 2)

[0891] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0892] There is a need for a system that can quickly and accurately monitor a child's health condition, reduce the psychological burden on parents and caregivers, and immediately provide appropriate medical treatment from experts. However, existing systems do not adequately consider the user's emotional state, do not adequately assess the severity of the condition, and do not provide an easy-to-use interface for the user. This makes it difficult to provide prompt medical treatment.

[0893] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting and analyzing the user's emotional state, means for adjusting an initial response method based on the emotional data, and robot means for collecting the child's health condition data and emotional data and transmitting them to the server. This enables a quick and accurate initial response adapted to the user's emotions and improves the accuracy of expert diagnoses.

[0894] The "terminal means" is a device that allows a user to input information about the health condition of a child.

[0895] The "server means" is a device that receives data sent from the terminal means and performs various analyses.

[0896] The "expert means" is a means for transmitting the analyzed data to an expert and providing feedback from the expert to the user.

[0897] The "additional information request means" is a means for responding to requests for additional information from experts.

[0898] The "emotion collection means" is a device that collects the user's voice, input speed, facial expression, etc., and analyzes their emotional state.

[0899] The "emotion response means" is a means for adjusting the initial response method based on the emotion data.

[0900] The "robot means" is a device that collects the child's health and emotional data and transmits it to the server.

[0901] The system of this invention includes terminal means for a user to input information about the child's health condition, server means for receiving and analyzing data sent from the terminal means, means for presenting an appropriate initial response method to the user based on the analyzed data, means for sending the analysis results to an expert, means for responding to requests for additional information from the expert, means for collecting and analyzing the user's emotional state, means for adjusting the initial response method based on the emotional data, and robot means for collecting the child's health condition data and emotional data and sending it to the server.

[0902] The hardware used is a terminal such as a smartphone or tablet, as well as a home security robot, while the software used is the EmotionRecognizer library (for emotion collection), the HealthDataCollector library (for health status data collection), the ActionSuggester library (for suggesting initial response methods), the Python programming language, and the HTTP request library (for data communication).

[0903] The process begins with the user entering information about their child's health using a terminal. The entered information includes body temperature, the type of symptoms (fever, cough, vomiting, etc.), the time of symptom onset, and other related symptoms (rash, difficulty breathing, etc.). In addition, the emotion collection means collects emotion data from the user's voice, input speed, facial expressions, etc.

[0904] The health condition data and emotion data sent from the terminal means are received by the server means. The server means validates the received data and then executes an algorithm to classify symptoms and assess their severity. It also analyzes the emotion data to understand the user's emotional state. Based on this, it adjusts the initial response method provided to the user and generates appropriate advice.

[0905] The advice includes specific instructions such as "use a cooling sheet and stay hydrated" and "contact a medical institution immediately." The results are presented to the user and simultaneously sent to the specialist. The specialist can make a highly accurate diagnosis and take appropriate action based on the received data. If the specialist requires additional information, additional questions for the user are displayed on the terminal means. The user inputs the additional information and sends it to the server means.

[0906] As a concrete example, if a child has a high fever of 39 degrees, the parent would use the terminal to input information such as "Temperature: 39 degrees," "Coughing," and "Symptoms started last night." At this time, feelings of anxiety and impatience are also collected from the parent's tone of voice and input speed. The data sent from the terminal means is analyzed by the server means, and specific advice such as "Use a cooling sheet and stay hydrated. Remain calm and contact a medical institution immediately" is returned. Furthermore, if the specialist asks additional questions such as "Do you have a rash?", these are also displayed to the user, and the answer is sent to the server.

[0907] An example of a prompt is, "A parent has entered their child's health status. The child's temperature is 39 degrees and they have been coughing since last night. The parent's voice is very unstable and they are typing quickly. Please provide an appropriate initial response based on the analysis results."

[0908] In this way, the present invention enables quick and smooth information flow between users and specialists, and provides emotionally sensitive responses, thereby realizing more accurate medical responses.

[0909] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0910] Step 1:

[0911] The user uses the device to input information about the child's health condition. The input data includes body temperature, type of symptoms, time of onset, and other related symptoms. This information is collected through the device's input interface. In addition, the device also collects the user's emotional data, which is obtained through voice tone, input speed, and facial expression analysis.

[0912] Step 2:

[0913] The device encrypts the health condition data and emotional data entered by the user and sends them to the server. The data sent includes the user's input information (e.g., body temperature, symptoms) and the collected emotional data.

[0914] Step 3:

[0915] The server validates the received data. Validation is a process to check the accuracy and completeness of the data, checking for missing data or abnormal values. Input: Health status data and emotion data sent from the device. Output: Validated data.

[0916] Step 4:

[0917] The server runs an algorithm to assess the severity of symptoms based on the validated data. For example, a body temperature of 39°C or higher is considered severe. Input: Validated data. Output: Symptom classification and severity assessment results.

[0918] Step 5:

[0919] The server analyzes the emotional data and understands the user's emotional state. The analysis is based on collected voice tone, input speed, and facial expression data. Input: Emotional data. Output: Analyzed emotional state.

[0920] Step 6:

[0921] The server generates an initial response method to provide to the user based on the symptom severity assessment result and emotional state. This includes specific actions such as "use a cooling sheet and stay hydrated" and "contact a medical institution immediately." Input: Severity assessment result and emotional state. Output: Initial response method.

[0922] Step 7:

[0923] The server sends the generated initial response method to the terminal and presents it to the user. The user responds accordingly. Input: Initial response method. Output: Initial response method displayed on the terminal.

[0924] Step 8:

[0925] The server sends the analysis results and detailed data about the user's emotional state to the expert. Input: Analysis results and emotional state. Output: Data transmission to the expert.

[0926] Step 9:

[0927] If the expert needs more information, he sends a follow-up question to the user through the server, for example a specific question such as "Do you have a rash?" Input: Follow-up question from the expert Output: Follow-up question displayed on the terminal.

[0928] Step 10:

[0929] The user inputs additional information through the terminal, which is then sent to the server. The server then performs the necessary analysis again and sends the results to the expert. Input: Additional information from the user. Output: Reanalysis results.

[0930] This allows for smooth information flow between users and specialists, enabling prompt and appropriate medical responses.

[0931] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0932] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0933] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0934] [Third embodiment]

[0935] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0936] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0937] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0938] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0939] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0940] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0941] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0942] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0943] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0944] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0945] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0946] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0947] System Overview

[0948] This invention relates to a system in which a user inputs information about their child's health condition using a terminal means, the data is analyzed by a server means, an appropriate initial response method is provided, and the data is then sent to a medical professional.

[0949] Program processing

[0950] User Action:

[0951] The user uses a terminal (such as a smartphone or tablet) to input information about their child's health condition. The questionnaire includes the following information: "Current body temperature," "Type of symptoms (fever, cough, vomiting, etc.)," ​​"Time of symptom onset," and "Other related symptoms (rash, difficulty breathing, etc.)."

[0952] Terminal behavior:

[0953] The device receives the information entered by the user and sends the data to the server, where it is encrypted to protect privacy and security.

[0954] Server behavior:

[0955] The server receives the data sent from the terminal and then performs the following analysis:

[0956] 1. Data Validation:

[0957] The server verifies the accuracy and completeness of the received data.

[0958] 2. Symptom classification and severity assessment:

[0959] The server analyzes the data using special algorithms to classify the child's symptoms and assess their severity - for example, a temperature of 39 degrees or higher is considered severe.

[0960] 3. Generate initial response methods:

[0961] Based on the analysis results, the server generates initial action instructions for the user, such as "use a cooling sheet and stay hydrated" and "contact a medical institution immediately."

[0962] 4. Data transmission to medical professionals:

[0963] The server then sends detailed data, including the analysis results, to medical professionals, who can then use this data to make more accurate diagnoses and treatments.

[0964] 5. Responding to requests for additional information:

[0965] If the medical professional determines that further information is needed, they will request it from the user via the server, and a follow-up question such as "Do you have a rash?" will be displayed on the device.

[0966] Examples:

[0967] Scenario: A child has a high fever of 39 degrees.

[0968] The user (parent) opens the terminal and enters the fever information:

[0969] Enter "Temperature: 39 degrees," "Coughing," and "Symptoms started last night."

[0970] The terminal sends the entered data to the server:

[0971] After transmission, the server immediately validates the received data.

[0972] The server evaluates the symptom classification and severity based on the received data:

[0973] "His body temperature is over 39 degrees, so his condition is considered serious."

[0974] The server provides the user with an initial response:

[0975] The device displays the following advice: "Use cooling pads and stay hydrated. Contact a medical institution immediately."

[0976] The server sends the analysis results to the medical professional:

[0977] A medical professional makes a diagnosis based on the received data.

[0978] If your healthcare professional needs additional information:

[0979] For example, an additional question such as "Do you have a rash?" is displayed on the terminal via the server, and the user answers it.

[0980] The system enables parents and caregivers to respond quickly and accurately to their child's health conditions and allows medical professionals to make efficient diagnoses.

[0981] The processing flow will be explained below.

[0982] Step 1:

[0983] The user enters information about their child's health condition using a terminal (e.g., a smartphone or tablet). The questionnaire includes questions such as "current body temperature," "type of symptoms (fever, cough, vomiting, etc.)," ​​"when symptoms began," and "other related symptoms (rash, difficulty breathing, etc.)."

[0984] Step 2:

[0985] The user presses the submit button to submit the information entered in the inquiry form.

[0986] Step 3:

[0987] The terminal receives the transmitted information, encrypts the data, and transmits it to the server means.

[0988] Step 4:

[0989] The server receives the data sent from the device and validates it for accuracy and completeness.

[0990] Step 5:

[0991] The server begins analyzing the incoming data. It uses an algorithm to analyze the data and classify symptoms and assess their severity. For example, a temperature of 39 degrees or higher is considered severe.

[0992] Step 6:

[0993] Based on the analysis results, the server generates initial action instructions for the user, such as "use a cooling sheet and stay hydrated" or "contact a medical institution immediately."

[0994] Step 7:

[0995] The server transmits the generated initial response method to the terminal means.

[0996] Step 8:

[0997] The terminal displays the initial response advice received from the server to the user, who then takes appropriate initial response according to the advice provided.

[0998] Step 9:

[0999] The server sends the analysis results as detailed data to medical professionals, enabling them to make quick and accurate diagnoses and take appropriate action based on the data.

[1000] Step 10:

[1001] If the medical professional determines that more information is needed, the additional information is requested from the user through the server.

[1002] Step 11:

[1003] The server sends a request for additional information from the medical professional to the terminal means.

[1004] Step 12:

[1005] The terminal displays a request for additional information to the user, who answers the additional questions and resubmits the answers through the terminal.

[1006] Step 13:

[1007] The server analyzes the re-received additional data and transmits it again to the medical professional.

[1008] Step 14:

[1009] The medical professional will determine the final diagnosis and treatment and notify the user via the server, who will then follow the final instructions.

[1010] This process allows users to quickly and accurately address their child's health condition and allows medical professionals to efficiently diagnose the condition.

[1011] Example 1

[1012] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1013] In today's world, it is extremely important to quickly and accurately assess a child's health condition and provide appropriate initial treatment. However, because most parents and caregivers have limited medical knowledge, it is difficult to determine whether a child's symptoms are serious. They also have limited means of quickly learning the appropriate treatment. Furthermore, access to medical facilities can be difficult, and communication with medical professionals can be difficult. To solve these problems, a system is needed that can quickly analyze data on a child's health condition, provide appropriate initial treatment, and send data to medical professionals for feedback.

[1014] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1015] In this invention, the server includes means for receiving data sent from the user, encrypting it, and analyzing it, means for classifying symptoms and assessing their severity based on the analyzed data, and means for generating an appropriate initial response method based on the analysis results. This allows the user to quickly and accurately understand their child's health condition and take appropriate initial responses. Furthermore, by including means for sending the analyzed data to a medical professional and means for responding to requests for additional information from the medical professional, communication with the medical professional is facilitated, enabling more accurate diagnoses and responses.

[1016] "Terminal means" refers to a device used by a user to input information, specifically a smartphone or tablet.

[1017] The term "server means" refers to a computer system that receives data sent from the terminal means and performs analysis and other processing of the data.

[1018] "Encryption" refers to the technology of using a specific algorithm to protect the contents of data in order to transmit it securely.

[1019] "Validation" refers to the process of checking whether received data is accurate and complete, and verifying that there are no anomalies.

[1020] "Symptom classification" refers to the process of analyzing data about a child's health and categorizing it based on specific symptoms.

[1021] "Severity assessment" refers to the process of determining the severity of a symptom and assessing its severity.

[1022] "Initial response methods" refers to specific response procedures and advice that users should take immediately regarding their child's health condition.

[1023] "Medical professionals" refers to people in professions such as doctors and nurses who have specialized knowledge and skills related to medical care.

[1024] "Information Request" refers to the act of asking a User for additional data or information required by a medical professional.

[1025] "Interface" refers to the screen and input method that a user uses to interact with a system, and specifically refers to the user interface of an application.

[1026] This invention is a system in which a user inputs information about the child's health condition using a terminal means, and a server means analyzes the data, provides an appropriate initial response method, and then transmits the data to a medical professional.

[1027] User Actions

[1028] Users use a device such as a smartphone or tablet to launch the application and enter information about their child's health. The questionnaire includes items such as "current body temperature," "type of symptoms (fever, cough, vomiting, etc.)," ​​"when symptoms began," and "other related symptoms (rash, difficulty breathing, etc.)." By entering this information, users can record their child's health in detail.

[1029] Device behavior

[1030] The device receives the information entered by the user and sends the data to the server, where it is encrypted using the AES-256 algorithm and transmitted using a secure communication protocol (e.g., HTTPS), ensuring the privacy and security of the data.

[1031] Server Operation

[1032] The server receives the data sent from the terminal and then performs the following analysis:

[1033] 1. Data Validation

[1034] The server checks the accuracy and completeness of the received data, checking the data format (e.g., whether the body temperature is within the range of 35-42°C) and whether required fields have been filled in, and returns an error to the terminal if there are any errors.

[1035] 2. Symptom classification and severity assessment

[1036] The server uses an analytical algorithm to analyze the data and classify the child's symptoms and assess their severity. For example, a temperature of 39 degrees or higher is considered severe. The algorithm is based on a machine learning model and uses patterns learned from past data to make the classification.

[1037] 3. Generate initial response methods

[1038] The server generates appropriate initial response instructions based on the analysis results. For example, if the patient has a temperature of 39°C, a cough, and symptoms began last night, the server generates the following advice: "Use a cooling pad, stay hydrated, and contact a medical institution immediately."

[1039] Sending data to medical professionals and responding to requests for additional information

[1040] The server sends the data, including the analysis results, to the medical professional. The medical professional accesses the EHR system using a secure communication protocol and makes a diagnosis based on the received data. If the medical professional determines that additional information is required, an additional question, such as "Do you have a rash?", is displayed on the device via the server. By answering this question, the user can provide the medical professional with the necessary additional information.

[1041] Specific examples

[1042] Scenario: A child has a high fever of 39 degrees.

[1043] 1. User:

[1044] The parent opens the device and enters the following information into the application's question form: "Temperature: 39 degrees," "Having a cough," and "Symptoms started last night."

[1045] 2. Terminal:

[1046] The terminal encrypts the entered data and sends it to the server using a secure communication protocol (HTTPS).

[1047] 3. Server:

[1048] The server validates the incoming data to ensure it is in the correct format and range, then uses an analytical algorithm to assess the symptom classification and severity, resulting in a "high fever" diagnosis.

[1049] 4. Server:

[1050] The server generates an initial response method such as "Use a cooling sheet and stay hydrated. Contact a medical institution immediately," and displays it on the terminal.

[1051] 5. Server:

[1052] The server sends the analysis results to medical professionals, who then make a diagnosis based on the received data via the EHR system.

[1053] 6. Request for additional information:

[1054] The medical professional sends a follow-up question, "Do you have a rash?", which is displayed on the device and the user answers.

[1055] The system allows users to respond quickly and accurately to their child's health conditions and allows medical professionals to make efficient diagnoses.

[1056] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1057] Step 1:

[1058] Data Entry

[1059] User action: The user launches an application using a smartphone or tablet.

[1060] Input: The user inputs information about their health condition (e.g., "Temperature: 39°C," "I have a cough," "Symptoms started last night").

[1061] What it does: The user provides information about their child's health by filling out a form in the application.

[1062] Step 2:

[1063] Data Receipt and Encryption

[1064] Terminal operation: The terminal receives the information entered by the user.

[1065] Input: Health information data entered by the user.

[1066] Data processing: The terminal encrypts the data with the AES-256 algorithm and sends it to the server using a secure communication protocol (HTTPS).

[1067] Output: The encrypted health information data is sent to the server.

[1068] Specific operation: The device encrypts data and communicates securely.

[1069] Step 3:

[1070] Data Validation

[1071] Server operation: The server receives the data sent from the terminal.

[1072] Input: Encrypted health information data.

[1073] Data calculation: The server decrypts the data and checks the data format (e.g., whether the body temperature is within the range of 35-42 degrees) and whether all required fields have been filled in.

[1074] Output: Successfully validated health information data.

[1075] Specific operation: Checks the data format and required fields, and returns an error to the terminal if there are any errors.

[1076] Step 4:

[1077] Symptom classification and severity rating

[1078] Server Operation: The server executes the data analysis algorithms.

[1079] Input: Health information data that has passed validation.

[1080] Data calculation: The server uses machine learning models to analyze health information. If the body temperature is 39 degrees, it will be classified as a high fever and the severity will be assessed as "high."

[1081] Output: Categorized symptom data and assessment results.

[1082] What it does: It uses machine learning algorithms to analyze health information, classify it into appropriate categories, and assess its severity.

[1083] Step 5:

[1084] Generate initial response methods

[1085] Server operation: The server generates an initial response method based on the analysis results.

[1086] Input: Categorized symptom data and assessment results.

[1087] Data calculation: The server generates appropriate initial response measures based on predefined response measures. For example, if the patient has a temperature of 39 degrees, a cough, and symptoms began last night, the server generates advice such as, "Use a cooling pad, stay hydrated, and contact a medical institution immediately."

[1088] Output: Advice on how to respond first.

[1089] Specific action: Generate a response method based on the conditions and provide it to the user.

[1090] Step 6:

[1091] Sending data to medical professionals

[1092] Server operation: The server sends detailed data including the analysis results to a medical professional.

[1093] Input: Initial response advice and analyzed health information data.

[1094] Data processing: The server re-encrypts the data and sends it using a secure communication protocol to a system accessed by medical professionals.

[1095] Output: Detailed data received by the medical professional.

[1096] What happens: Sends data to an EHR system and makes it available to healthcare professionals.

[1097] Step 7:

[1098] Responding to requests for additional information

[1099] User Action: If necessary, the medical professional can request additional information.

[1100] Input: Request for additional information from medical professional.

[1101] Data computation: The server sends a request for additional information to the terminal, and the user answers it to gather more data (e.g., "Do you have a rash?").

[1102] Output: Additional information from the user.

[1103] Specific operation: The server sends a request for additional information to the terminal and collects the response.

[1104] In this way, each step works in coordination, enabling a quick and accurate assessment of a child's health condition and early response.

[1105] (Application example 1)

[1106] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1107] In modern society, it is extremely important for parents and caregivers to respond promptly and appropriately to their children's health conditions. However, when sudden symptoms occur, accurate initial response is required, which is difficult for general users without specialized knowledge. Furthermore, rapid collaboration with medical professionals is also required, which requires a system that can appropriately collect, analyze, and share information. Data security and privacy protection are also important issues.

[1108] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1109] In this invention, the server includes a terminal means for receiving and analyzing information on the child's health condition entered by the user, a means for encrypting and receiving data transmitted from the terminal means and analyzing it, a means for presenting an appropriate initial response method to the user based on the data analyzed by the server means, a means for transmitting the analyzed data to a specialist, a means for responding to requests for additional information from the specialist, a display means for presenting an initial response method to the user based on the analysis results, and a means for validating the data. This enables parents and caregivers to respond to the child's health condition quickly and accurately and facilitates smooth cooperation with specialists.

[1110] The "terminal means" is a device that allows a user to input information about the health condition of a child.

[1111] "Data" refers to information entered by the user about the child's health, including temperature, symptoms, and the timing of symptoms.

[1112] The "server means" is a device for receiving and analyzing data sent from the terminal means.

[1113] "Initial response method" refers to guidelines for specific steps and actions that users should take based on the analyzed data.

[1114] "Expert" refers to someone with specialized medical knowledge, including doctors and nurses.

[1115] "Request for additional information" refers to the expert requesting further required information from the user.

[1116] The "display means" is a device or function for visually presenting the analysis results and initial response methods to the user.

[1117] "Data validation" is the process of verifying the accuracy and completeness of received data.

[1118] An "algorithm" is a computational method by which the server means analyzes the data and assesses the severity of the symptoms.

[1119] This invention builds a system that monitors children's health conditions and provides users with appropriate initial response methods. The system is mainly composed of a terminal means used by the user, a server means for analyzing data, and a means for supporting collaboration with experts.

[1120] Hardware and software used

[1121] 1. Terminal means:

[1122] Hardware: Smartphones, tablets

[1123] Software: User interface using React Native

[1124] 2. Server means:

[1125] Hardware: Standard server machine

[1126] Software: Python (Flask framework), MySQL database, data encryption with OpenSSL

[1127] Program processing

[1128] User Action:

[1129] Users use a smartphone or tablet application to enter data about their child's health, including the following:

[1130] Body temperature: 39 degrees

[1131] Cough: Yes

[1132] Symptom onset: Last night

[1133] Other associated symptoms: None

[1134] Terminal behavior:

[1135] The device encrypts the entered information (AES-256) and sends it to the server using a device-specific method (e.g., sendSecureData). This method ensures data integrity and privacy.

[1136] Server behavior:

[1137] The server receives the data sent from the terminal and then performs the following processes.

[1138] 1. Data Validation:

[1139] The server verifies the received data for accuracy and completeness, checking for blanks and filtering out inappropriate data.

[1140] 2. Data Analysis:

[1141] The server uses special algorithms (e.g., malignancy determination algorithms) to analyze the child's symptoms and severity.

[1142] 3. Generate initial response methods:

[1143] Based on the analysis results, the system generates initial action instructions to be presented to the user, such as "Use a cooling sheet, stay hydrated, and contact a medical institution immediately."

[1144] 4. Sending data to the expert:

[1145] If necessary, detailed data including analysis results can be sent to medical professionals, who can use this data to make more accurate diagnoses and treatments.

[1146] 5. Request for additional information:

[1147] If the medical professional needs more information, they will ask the user a follow-up question via the server, e.g., "Do you have a rash?"

[1148] Specific examples

[1149] Example of a prompt for the user to enter:

[1150] Child's current status:

[1151] Body temperature: 39°C

[1152] Cough: Yes

[1153] Symptoms started last night

[1154] Other associated symptoms: None

[1155] Send: true

[1156] The system allows parents and caregivers to respond quickly to sudden illnesses and medical professionals to provide appropriate support. The system also ensures data security and privacy, making it safe to use in everyday life.

[1157] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1158] Step 1:

[1159] Users use a smartphone or tablet to enter information about their child's health into the application form. Information entered includes body temperature, whether or not the child has a cough, when symptoms began, and other related symptoms. Examples of input data include "body temperature: 39°C," "cough present," "when symptoms began: last night," and "no other related symptoms."

[1160] Step 2:

[1161] The terminal encrypts the entered information. Specifically, it encrypts the data using the AES-256 encryption method. The encrypted data is then sent to the server using the terminal's sendSecureData method. This method ensures data integrity and privacy.

[1162] Step 3:

[1163] The server receives the encrypted data sent from the device. It first decrypts the received data and then validates it. Data validation checks whether there are any blank fields or inappropriate data. For example, it checks whether "body temperature" is a numeric value and whether "cough" is "yes" or "no."

[1164] Step 4:

[1165] The server inputs the validated data into a data analysis algorithm, which primarily classifies symptoms and assesses their severity. If the temperature is 39°C or higher, the algorithm evaluates the symptoms as severe and determines that escalation is necessary. Based on the results, the initial response method to be taken is generated.

[1166] Step 5:

[1167] Based on the analysis results, the server provides the user with initial response instructions. The displayed initial response instructions include specific instructions for action. For example, advice such as "Use a cooling sheet, stay hydrated, and contact a medical institution immediately" is displayed on the smartphone.

[1168] Step 6:

[1169] The server then sends the analysis results to a medical professional, if necessary. The data sent includes the information entered by the user and the server's analysis results, allowing the professional to perform a more detailed diagnosis.

[1170] Step 7:

[1171] If the specialist needs more information, the server sends the user a follow-up question, such as "Do you have a rash?", which is displayed on the smartphone. The user answers the question and the data is sent back to the server.

[1172] Step 8:

[1173] The server then re-analyzes the additional information and updates the necessary response procedures, ensuring that the user receives appropriate guidance on an ongoing basis. This process provides real-time collaboration between the user and the expert.

[1174] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1175] System Overview

[1176] This invention relates to a system in which a user inputs information about their child's health condition, transmits the information to a server via a terminal, and the server analyzes the received data and provides an appropriate initial response method. The analyzed data is then transmitted to a medical professional, who provides any necessary additional information. The system also incorporates an emotion engine that recognizes the user's emotions and reflects them in the analysis results and response methods.

[1177] Program processing

[1178] User Action:

[1179] The user uses a terminal (e.g., a smartphone or tablet) to input information about their child's health condition. The questionnaire includes questions such as "current body temperature," "type of symptoms (fever, cough, vomiting, etc.)," ​​"when symptoms began," and "other related symptoms (rash, difficulty breathing, etc.)." In addition, an emotion engine runs to collect the user's emotional state while they are entering information.

[1180] Terminal behavior:

[1181] The terminal collects information and emotion data input by the user, encrypts it, and transmits it to the server. The emotion engine analyzes the user's emotion from their voice, input speed, facial expression, etc., and transmits this data to the server as additional information.

[1182] Server behavior:

[1183] The server receives the data sent from the terminal and then performs the following analysis:

[1184] 1. Data Validation:

[1185] The server verifies the accuracy and completeness of the received data.

[1186] 2. Symptom classification and severity assessment:

[1187] The server analyzes the data using special algorithms to classify the child's symptoms and assess their severity - for example, a temperature of 39 degrees or higher is considered severe.

[1188] 3. Emotional Data Analysis:

[1189] The server analyzes the emotion data sent from the emotion engine to understand the user's emotional state. For example, if it determines that the user is very anxious, it will adjust the content and expression of the advice appropriately.

[1190] 4. Generate initial response methods:

[1191] Based on the analysis results and emotional data, the server generates initial action instructions for the user, such as "use a cooling sheet and stay hydrated" or "contact a medical institution immediately."

[1192] 5. Data transmission to medical professionals:

[1193] The server then sends detailed data, including the analysis results, to medical professionals, who can then use this data to make more accurate diagnoses and treatments.

[1194] 6. Responding to Requests for Additional Information:

[1195] If the medical professional determines that further information is needed, they will request it from the user via the server, and a follow-up question such as "Do you have a rash?" will be displayed on the device.

[1196] Examples:

[1197] Scenario: A child has a high fever of 39 degrees.

[1198] The user (parent) opens the terminal and enters the fever information:

[1199] The user types in "Temperature: 39 degrees," "Having a cough," and "Symptoms started last night." The emotion engine also collects feelings of anxiety and impatience from the parent's tone of voice and typing speed while they are typing.

[1200] The device sends the input data and emotion data to the server:

[1201] After transmission, the server immediately validates the received data and emotion data.

[1202] The server evaluates the symptom classification and severity based on the received data and emotion data:

[1203] The assessment is that the child's temperature is over 39 degrees, making the condition critical, and takes into account the parents' emotional state of high anxiety.

[1204] The server provides the user with an initial response:

[1205] The advice displayed is, "Use cooling pads and stay hydrated. Remain calm and contact a medical institution immediately."

[1206] The server sends the analysis results to the medical professional:

[1207] Medical professionals will make a diagnosis based on the data received, take into account parental concerns, and provide professional advice.

[1208] If your healthcare professional needs additional information:

[1209] For example, an additional question such as "Do you have a rash?" is displayed on the terminal via the server, and the user answers it.

[1210] The system allows parents and caregivers to respond quickly and accurately to their child's health condition, and medical professionals to make efficient diagnoses. The addition of emotional data-based responses also reduces the psychological burden on users, enabling smoother medical responses.

[1211] The processing flow will be explained below.

[1212] Step 1:

[1213] The user inputs information about their child's health condition using a terminal (e.g., a smartphone or tablet). The questionnaire includes information such as "current body temperature," "type of symptoms (fever, cough, vomiting, etc.)," ​​"when symptoms began," and "other related symptoms (rash, difficulty breathing, etc.)." As the user inputs information, the emotion engine analyzes the user's emotional state based on their tone of voice, typing speed, facial expression, etc.

[1214] Step 2:

[1215] The user clicks the submit button to submit the input.

[1216] Step 3:

[1217] The terminal encrypts the information and emotion data input by the user and transmits them to the server means.

[1218] Step 4:

[1219] The server receives the data sent from the terminal and validates the received data to check its accuracy and completeness.

[1220] Step 5:

[1221] The server begins analyzing the incoming data. It uses an algorithm to analyze the data from the user, classify the child's symptoms, and assess their severity. For example, a temperature of 39 degrees or higher is considered severe.

[1222] Step 6:

[1223] The emotion engine analyzes the transmitted emotion data and understands the user's emotional state, such as assessing anxiety, impatience, or restlessness.

[1224] Step 7:

[1225] The server then uses the analysis results and emotional data to provide the user with appropriate initial response advice, such as "Use a cooling sheet and stay hydrated. Remain calm and immediately contact a medical institution."

[1226] Step 8:

[1227] The server transmits the generated initial response method to the terminal means.

[1228] Step 9:

[1229] The terminal displays the initial response advice received from the server to the user, who then takes appropriate initial response according to the advice provided.

[1230] Step 10:

[1231] The server sends the analysis results to medical professionals, allowing them to make quick and accurate diagnoses and take appropriate action based on the data.

[1232] Step 11:

[1233] If the medical professional determines that more information is needed, a request for additional information is sent to the user through the server means.

[1234] Step 12:

[1235] The server sends a request for additional information from the medical professional to the terminal means.

[1236] Step 13:

[1237] The terminal displays a request for additional information to the user, who answers the additional questions and resubmits through the terminal.

[1238] Step 14:

[1239] The server analyzes the additional data received from the user and transmits it back to the medical professional.

[1240] Step 15:

[1241] The medical professional will determine the final diagnosis and treatment and notify the user via the server, who will then follow the final instructions.

[1242] This series of processes allows users to deal with their child's health condition quickly and accurately, and medical professionals can make efficient diagnoses. In addition, the emotional engine reduces the user's psychological burden and enables smoother medical treatment.

[1243] Example 2

[1244] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1245] Conventional health monitoring systems primarily involve inputting and analyzing information about a child's health condition. However, they lack consideration for the user's emotional state, making it difficult to completely alleviate the user's psychological burden. Furthermore, it is difficult to generate a fast and accurate initial response method or to communicate efficiently with medical professionals. Therefore, there is a need for a system that can respond quickly and appropriately while taking the user's emotional state into account.

[1246] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1247] In this invention, the server includes means for analyzing data sent from the user, means for generating an initial response method based on the analyzed data, and means for analyzing emotion data collected by the emotion engine and adjusting the initial response method, thereby enabling prompt and appropriate health management that takes the user's emotional state into consideration.

[1248] "Terminal means" refers to an electronic device such as a smartphone or tablet, which allows a user to input information about the child's health condition.

[1249] The term "server means" refers to a computer system that receives and analyzes data sent from the terminal means.

[1250] The "means for presenting an appropriate initial response method to the user" refers to a method for presenting an appropriate response method to the user based on the data analyzed by the server means.

[1251] "Means for sending to a medical professional" refers to a method by which the server means sends the analyzed data to a medical professional.

[1252] "Means for responding to requests for additional information" refers to methods for asking questions or gathering information from the user in response to requests for additional information from medical professionals.

[1253] An "emotion engine" refers to a tool that has the function of collecting and analyzing a user's emotional state from their voice, input speed, facial expressions, etc.

[1254] "Means for transmitting emotion data to server means" refers to a method for transmitting emotion data collected by the emotion engine to server means.

[1255] The "means for adjusting the initial response method based on the emotion data" refers to a method in which the server means analyzes the emotion data and appropriately adjusts the initial response method based on the results of the analysis.

[1256] This invention relates to a system in which a user inputs information about their child's health condition, transmits the information to a server via a terminal, and the server analyzes the received data and provides an appropriate initial response method. The analyzed data is then transmitted to a medical professional, who provides any necessary additional information. The system also incorporates an emotion engine that recognizes the user's emotions and reflects them in the analysis results and response methods.

[1257] User Action:

[1258] The user uses a terminal (e.g., a smartphone or tablet) to input information about their child's health condition. The questionnaire includes questions such as "current body temperature," "type of symptoms (fever, cough, vomiting, etc.)," ​​"time of symptom onset," and "other related symptoms (rash, difficulty breathing, etc.)." In addition, an emotion engine runs to collect the user's emotional state while they are entering information.

[1259] Terminal behavior:

[1260] The device temporarily stores the health information and emotional data entered by the user. It then encrypts this data and sends it to the server using a secure communication channel (e.g., HTTPS). The emotion engine analyzes the user's emotions based on their voice, typing speed, facial expressions, etc., and sends this data to the server as additional information.

[1261] Server behavior:

[1262] The server receives the data sent from the terminal and then performs the following series of analyses:

[1263] 1. Data Validation:

[1264] The server checks the received data for accuracy and completeness, especially for missing mandatory fields and anomalous data.

[1265] 2. Symptom classification and severity assessment:

[1266] The server uses a special algorithm to analyze the data, classify the child's symptoms, and assess their severity: for example, a temperature of 39 degrees or higher is considered severe.

[1267] 3. Emotional Data Analysis:

[1268] The server analyzes the emotion data sent from the emotion engine to understand the user's emotional state. For example, if it determines that the user is very anxious, it will adjust the content and expression of the advice appropriately.

[1269] 4. Generate initial response methods:

[1270] Based on the analysis results and emotional data, the server generates initial action instructions for the user, such as "use a cooling sheet and stay hydrated" or "contact a medical institution immediately."

[1271] 5. Data transmission to medical professionals:

[1272] The server then sends detailed data, including the analysis results, to medical professionals, who can then use this data to make more accurate diagnoses and treatments.

[1273] 6. Responding to Requests for Additional Information:

[1274] If the medical professional needs more information, the server forwards the request to the user, who will then be prompted with a follow-up question, such as "Do you have a rash?", which the user can answer and then send the data back to the server.

[1275] Examples:

[1276] Scenario: A child has a high fever of 39 degrees.

[1277] User Action:

[1278] The user (parent) opens the app on their smartphone and enters information into the question form, such as "Temperature: 39 degrees," "I have a cough," and "Symptoms started last night." As the parent types, the emotion engine analyzes the parent's tone of voice and typing speed in real time. If the parent says something like, "What should I do now?", the voice is judged to be highly anxious.

[1279] Terminal behavior:

[1280] The device temporarily stores the input data and emotion data, and transmits them to the server via encrypted communication.

[1281] Server behavior:

[1282] After receiving the data, the server validates it, classifies the symptoms, and assesses their severity. It assesses the temperature as "39°C or higher, a serious condition," taking into account the user's high level of anxiety. As an initial response, it generates and displays the following advice: "Use a cooling sheet and stay hydrated. Remain calm and contact a medical institution immediately." The analysis results are sent to a medical professional, who makes a diagnosis based on the received data. If necessary, additional questions such as "Do you have a rash?" are displayed in the device application, and additional information is collected when the user answers them.

[1283] This system allows parents and caregivers to respond quickly and accurately to their child's health condition, and medical professionals to make efficient diagnoses. In addition, the addition of emotional data-based responses reduces the psychological burden on users and enables smoother medical responses.

[1284] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1285] Step 1:

[1286] The user uses the terminal means to input information about the child's health condition.

[1287] Input: The questionnaire includes information such as current body temperature, type of symptoms (fever, cough, vomiting, etc.), when symptoms began, and other related symptoms (rash, difficulty breathing, etc.). The user's voice, typing speed, and facial expressions are also collected.

[1288] Specific actions: The user opens the smartphone application and enters specific numerical values ​​and symptom information into the form, such as "body temperature: 39 degrees" or "persistent cough."

[1289] Step 2:

[1290] The device collects and temporarily stores the entered health and emotional data.

[1291] Input: Health information entered by the user and voice, typing speed, and facial expression data collected by the emotion engine.

[1292] Data processing: Encrypt the collected data.

[1293] Output: Encrypted health information and emotion data.

[1294] Specific operation: The device encrypts the collected information and prepares it to be sent to the server.

[1295] Step 3:

[1296] The terminal transmits data to the server over a secure communication channel.

[1297] Input: Encrypted health information and emotion data.

[1298] Output: The encrypted data sent to the server.

[1299] What happens: The device sends data using a secure communications protocol such as HTTPS.

[1300] Step 4:

[1301] The server receives and decrypts the encrypted data.

[1302] Input: Encrypted data sent from the terminal.

[1303] Data processing: Decryption of encrypted data.

[1304] Output: Decoded health information and emotion data.

[1305] Specific operation: The server decrypts the received data and obtains the original health information and emotion data.

[1306] Step 5:

[1307] The server validates the received data.

[1308] Input: Decoded health information and emotion data.

[1309] Data calculation: Check for missing required fields and abnormal values.

[1310] Output: The validated data.

[1311] Specific behavior: The server checks the accuracy and completeness of the data and generates a warning message if there are any abnormal values.

[1312] Step 6:

[1313] The server categorizes symptoms and assesses their severity.

[1314] Input: Validated health information.

[1315] Data computation: Classification and severity assessment using ML-based algorithms.

[1316] Output: Symptom classification and severity rating.

[1317] Specific operation: For example, the server evaluates the patient's body temperature as "39 ​​degrees or higher, a serious condition," and decides on the next course of action.

[1318] Step 7:

[1319] The server analyzes the emotion data.

[1320] Input: Validated emotion data.

[1321] Data Computation: Emotional state is assessed using the emotion engine's analytical algorithms.

[1322] Output: Emotional state assessment results.

[1323] Specific behavior: If the user is determined to be in a highly anxious state, appropriate countermeasures are adjusted based on the analysis results.

[1324] Step 8:

[1325] The server generates an initial response method.

[1326] Input: Symptom classification results, severity rating, emotional state rating results.

[1327] Data calculation: Generate appropriate response methods based on this data.

[1328] Output: Initial response method.

[1329] Specific actions: The server generates specific advice such as "Use cooling pads, stay hydrated, stay calm and contact a medical professional."

[1330] Step 9:

[1331] The server sends the generated initial response instructions to the user.

[1332] Input: Initial response method.

[1333] Output: Initial response instructions sent to the user.

[1334] Specific operation: The server sends the advice to the terminal, which displays it to the user.

[1335] Step 10:

[1336] The server sends the analysis results to a medical professional.

[1337] Input: Analysis results.

[1338] Output: Analysis results sent to medical professionals.

[1339] What it does: The server encrypts the analysis results and sends them to the medical professional's system using a secure communication channel.

[1340] Step 11:

[1341] A server responds to requests for additional information from medical professionals.

[1342] Input: Request for additional information.

[1343] Output: The result of collecting additional information.

[1344] What it does: The medical professional enters a follow-up question, such as "Do you have a rash?", which the server forwards to the user's device. The user provides additional information and sends it back to the server.

[1345] (Application example 2)

[1346] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1347] There is a need for a system that can quickly and accurately monitor a child's health condition, reduce the psychological burden on parents and caregivers, and immediately provide appropriate medical treatment from experts. However, existing systems do not adequately consider the user's emotional state, do not adequately assess the severity of the condition, and do not provide an easy-to-use interface for the user. This makes it difficult to provide prompt medical treatment.

[1348] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting and analyzing the user's emotional state, means for adjusting an initial response method based on the emotional data, and robot means for collecting the child's health condition data and emotional data and transmitting them to the server. This enables a quick and accurate initial response adapted to the user's emotions and improves the accuracy of expert diagnoses.

[1349] The "terminal means" is a device that allows a user to input information about the health condition of a child.

[1350] The "server means" is a device that receives data sent from the terminal means and performs various analyses.

[1351] The "expert means" is a means for transmitting the analyzed data to an expert and providing feedback from the expert to the user.

[1352] The "additional information request means" is a means for responding to requests for additional information from experts.

[1353] The "emotion collection means" is a device that collects the user's voice, input speed, facial expression, etc., and analyzes their emotional state.

[1354] The "emotion response means" is a means for adjusting the initial response method based on the emotion data.

[1355] The "robot means" is a device that collects the child's health and emotional data and transmits it to the server.

[1356] The system of this invention includes terminal means for a user to input information about the child's health condition, server means for receiving and analyzing data sent from the terminal means, means for presenting an appropriate initial response method to the user based on the analyzed data, means for sending the analysis results to an expert, means for responding to requests for additional information from the expert, means for collecting and analyzing the user's emotional state, means for adjusting the initial response method based on the emotional data, and robot means for collecting the child's health condition data and emotional data and sending it to the server.

[1357] The hardware used is a terminal such as a smartphone or tablet, as well as a home security robot, while the software used is the EmotionRecognizer library (for emotion collection), the HealthDataCollector library (for health status data collection), the ActionSuggester library (for suggesting initial response methods), the Python programming language, and the HTTP request library (for data communication).

[1358] The process begins with the user entering information about their child's health using a terminal. The entered information includes body temperature, the type of symptoms (fever, cough, vomiting, etc.), the time of symptom onset, and other related symptoms (rash, difficulty breathing, etc.). In addition, the emotion collection means collects emotion data from the user's voice, input speed, facial expressions, etc.

[1359] The health condition data and emotion data sent from the terminal means are received by the server means. The server means validates the received data and then executes an algorithm to classify symptoms and assess their severity. It also analyzes the emotion data to understand the user's emotional state. Based on this, it adjusts the initial response method provided to the user and generates appropriate advice.

[1360] The advice includes specific instructions such as "use a cooling sheet and stay hydrated" and "contact a medical institution immediately." The results are presented to the user and simultaneously sent to the specialist. The specialist can make a highly accurate diagnosis and take appropriate action based on the received data. If the specialist requires additional information, additional questions for the user are displayed on the terminal means. The user inputs the additional information and sends it to the server means.

[1361] As a concrete example, if a child has a high fever of 39 degrees, the parent would use the terminal to input information such as "Temperature: 39 degrees," "Coughing," and "Symptoms started last night." At this time, feelings of anxiety and impatience are also collected from the parent's tone of voice and input speed. The data sent from the terminal means is analyzed by the server means, and specific advice such as "Use a cooling sheet and stay hydrated. Remain calm and contact a medical institution immediately" is returned. Furthermore, if the specialist asks additional questions such as "Do you have a rash?", these are also displayed to the user, and the answer is sent to the server.

[1362] An example of a prompt is, "A parent has entered their child's health status. The child's temperature is 39 degrees and they have been coughing since last night. The parent's voice is very unstable and they are typing quickly. Please provide an appropriate initial response based on the analysis results."

[1363] In this way, the present invention enables quick and smooth information flow between users and specialists, and provides emotionally sensitive responses, thereby realizing more accurate medical responses.

[1364] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1365] Step 1:

[1366] The user uses the device to input information about the child's health condition. The input data includes body temperature, type of symptoms, time of onset, and other related symptoms. This information is collected through the device's input interface. In addition, the device also collects the user's emotional data, which is obtained through voice tone, input speed, and facial expression analysis.

[1367] Step 2:

[1368] The device encrypts the health condition data and emotional data entered by the user and sends them to the server. The data sent includes the user's input information (e.g., body temperature, symptoms) and the collected emotional data.

[1369] Step 3:

[1370] The server validates the received data. Validation is a process to check the accuracy and completeness of the data, checking for missing data or abnormal values. Input: Health status data and emotion data sent from the device. Output: Validated data.

[1371] Step 4:

[1372] The server runs an algorithm to assess the severity of symptoms based on the validated data. For example, a body temperature of 39°C or higher is considered severe. Input: Validated data. Output: Symptom classification and severity assessment results.

[1373] Step 5:

[1374] The server analyzes the emotional data and understands the user's emotional state. The analysis is based on collected voice tone, input speed, and facial expression data. Input: Emotional data. Output: Analyzed emotional state.

[1375] Step 6:

[1376] The server generates an initial response method to provide to the user based on the symptom severity assessment result and emotional state. This includes specific actions such as "use a cooling sheet and stay hydrated" and "contact a medical institution immediately." Input: Severity assessment result and emotional state. Output: Initial response method.

[1377] Step 7:

[1378] The server sends the generated initial response method to the terminal and presents it to the user. The user responds accordingly. Input: Initial response method. Output: Initial response method displayed on the terminal.

[1379] Step 8:

[1380] The server sends the analysis results and detailed data about the user's emotional state to the expert. Input: Analysis results and emotional state. Output: Data transmission to the expert.

[1381] Step 9:

[1382] If the expert needs more information, he sends a follow-up question to the user through the server, for example a specific question such as "Do you have a rash?" Input: Follow-up question from the expert Output: Follow-up question displayed on the terminal.

[1383] Step 10:

[1384] The user inputs additional information through the terminal, which is then sent to the server. The server then performs the necessary analysis again and sends the results to the expert. Input: Additional information from the user. Output: Reanalysis results.

[1385] This allows for smooth information flow between users and specialists, enabling prompt and appropriate medical responses.

[1386] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1387] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1388] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1389] [Fourth embodiment]

[1390] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1391] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1392] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1393] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1394] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1395] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1396] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1397] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1398] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1399] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1400] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1401] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1402] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1403] System Overview

[1404] This invention relates to a system in which a user inputs information about their child's health condition using a terminal means, the data is analyzed by a server means, an appropriate initial response method is provided, and the data is then sent to a medical professional.

[1405] Program processing

[1406] User Action:

[1407] The user uses a terminal (such as a smartphone or tablet) to input information about their child's health condition. The questionnaire includes the following information: "Current body temperature," "Type of symptoms (fever, cough, vomiting, etc.)," ​​"Time of symptom onset," and "Other related symptoms (rash, difficulty breathing, etc.)."

[1408] Terminal behavior:

[1409] The device receives the information entered by the user and sends the data to the server, where it is encrypted to protect privacy and security.

[1410] Server behavior:

[1411] The server receives the data sent from the terminal and then performs the following analysis:

[1412] 1. Data Validation:

[1413] The server verifies the accuracy and completeness of the received data.

[1414] 2. Symptom classification and severity assessment:

[1415] The server analyzes the data using special algorithms to classify the child's symptoms and assess their severity - for example, a temperature of 39 degrees or higher is considered severe.

[1416] 3. Generate initial response methods:

[1417] Based on the analysis results, the server generates initial action instructions for the user, such as "use a cooling sheet and stay hydrated" and "contact a medical institution immediately."

[1418] 4. Data transmission to medical professionals:

[1419] The server then sends detailed data, including the analysis results, to medical professionals, who can then use this data to make more accurate diagnoses and treatments.

[1420] 5. Responding to requests for additional information:

[1421] If the medical professional determines that further information is needed, they will request it from the user via the server, and a follow-up question such as "Do you have a rash?" will be displayed on the device.

[1422] Examples:

[1423] Scenario: A child has a high fever of 39 degrees.

[1424] The user (parent) opens the terminal and enters the fever information:

[1425] Enter "Temperature: 39 degrees," "Coughing," and "Symptoms started last night."

[1426] The terminal sends the entered data to the server:

[1427] After transmission, the server immediately validates the received data.

[1428] The server evaluates the symptom classification and severity based on the received data:

[1429] "His body temperature is over 39 degrees, so his condition is considered serious."

[1430] The server provides the user with an initial response:

[1431] The device displays the following advice: "Use cooling pads and stay hydrated. Contact a medical institution immediately."

[1432] The server sends the analysis results to the medical professional:

[1433] A medical professional makes a diagnosis based on the received data.

[1434] If your healthcare professional needs additional information:

[1435] For example, an additional question such as "Do you have a rash?" is displayed on the terminal via the server, and the user answers it.

[1436] The system enables parents and caregivers to respond quickly and accurately to their child's health conditions and allows medical professionals to make efficient diagnoses.

[1437] The processing flow will be explained below.

[1438] Step 1:

[1439] The user enters information about their child's health condition using a terminal (e.g., a smartphone or tablet). The questionnaire includes questions such as "current body temperature," "type of symptoms (fever, cough, vomiting, etc.)," ​​"when symptoms began," and "other related symptoms (rash, difficulty breathing, etc.)."

[1440] Step 2:

[1441] The user presses the submit button to submit the information entered in the inquiry form.

[1442] Step 3:

[1443] The terminal receives the transmitted information, encrypts the data, and transmits it to the server means.

[1444] Step 4:

[1445] The server receives the data sent from the device and validates it for accuracy and completeness.

[1446] Step 5:

[1447] The server begins analyzing the incoming data. It uses an algorithm to analyze the data and classify symptoms and assess their severity. For example, a temperature of 39 degrees or higher is considered severe.

[1448] Step 6:

[1449] Based on the analysis results, the server generates initial action instructions for the user, such as "use a cooling sheet and stay hydrated" or "contact a medical institution immediately."

[1450] Step 7:

[1451] The server transmits the generated initial response method to the terminal means.

[1452] Step 8:

[1453] The terminal displays the initial response advice received from the server to the user, who then takes appropriate initial response according to the advice provided.

[1454] Step 9:

[1455] The server sends the analysis results as detailed data to medical professionals, enabling them to make quick and accurate diagnoses and take appropriate action based on the data.

[1456] Step 10:

[1457] If the medical professional determines that more information is needed, the additional information is requested from the user through the server.

[1458] Step 11:

[1459] The server sends a request for additional information from the medical professional to the terminal means.

[1460] Step 12:

[1461] The terminal displays a request for additional information to the user, who answers the additional questions and resubmits the answers through the terminal.

[1462] Step 13:

[1463] The server analyzes the re-received additional data and transmits it again to the medical professional.

[1464] Step 14:

[1465] The medical professional will determine the final diagnosis and treatment and notify the user via the server, who will then follow the final instructions.

[1466] This process allows users to quickly and accurately address their child's health condition and allows medical professionals to efficiently diagnose the condition.

[1467] Example 1

[1468] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1469] In today's world, it is extremely important to quickly and accurately assess a child's health condition and provide appropriate initial treatment. However, because most parents and caregivers have limited medical knowledge, it is difficult to determine whether a child's symptoms are serious. They also have limited means of quickly learning the appropriate treatment. Furthermore, access to medical facilities can be difficult, and communication with medical professionals can be difficult. To solve these problems, a system is needed that can quickly analyze data on a child's health condition, provide appropriate initial treatment, and send data to medical professionals for feedback.

[1470] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1471] In this invention, the server includes means for receiving data sent from the user, encrypting it, and analyzing it, means for classifying symptoms and assessing their severity based on the analyzed data, and means for generating an appropriate initial response method based on the analysis results. This allows the user to quickly and accurately understand their child's health condition and take appropriate initial responses. Furthermore, by including means for sending the analyzed data to a medical professional and means for responding to requests for additional information from the medical professional, communication with the medical professional is facilitated, enabling more accurate diagnoses and responses.

[1472] "Terminal means" refers to a device used by a user to input information, specifically a smartphone or tablet.

[1473] The term "server means" refers to a computer system that receives data sent from the terminal means and performs analysis and other processing of the data.

[1474] "Encryption" refers to the technology of using a specific algorithm to protect the contents of data in order to transmit it securely.

[1475] "Validation" refers to the process of checking whether received data is accurate and complete, and verifying that there are no anomalies.

[1476] "Symptom classification" refers to the process of analyzing data about a child's health and categorizing it based on specific symptoms.

[1477] "Severity assessment" refers to the process of determining the severity of a symptom and assessing its severity.

[1478] "Initial response methods" refers to specific response procedures and advice that users should take immediately regarding their child's health condition.

[1479] "Medical professionals" refers to people in professions such as doctors and nurses who have specialized knowledge and skills related to medical care.

[1480] "Information Request" refers to the act of asking a User for additional data or information required by a medical professional.

[1481] "Interface" refers to the screen and input method that a user uses to interact with a system, and specifically refers to the user interface of an application.

[1482] This invention is a system in which a user inputs information about the child's health condition using a terminal means, and a server means analyzes the data, provides an appropriate initial response method, and then transmits the data to a medical professional.

[1483] User Actions

[1484] Users use a device such as a smartphone or tablet to launch the application and enter information about their child's health. The questionnaire includes items such as "current body temperature," "type of symptoms (fever, cough, vomiting, etc.)," ​​"when symptoms began," and "other related symptoms (rash, difficulty breathing, etc.)." By entering this information, users can record their child's health in detail.

[1485] Device behavior

[1486] The device receives the information entered by the user and sends the data to the server, where it is encrypted using the AES-256 algorithm and transmitted using a secure communication protocol (e.g., HTTPS), ensuring the privacy and security of the data.

[1487] Server Operation

[1488] The server receives the data sent from the terminal and then performs the following analysis:

[1489] 1. Data Validation

[1490] The server checks the accuracy and completeness of the received data, checking the data format (e.g., whether the body temperature is within the range of 35-42°C) and whether required fields have been filled in, and returns an error to the terminal if there are any errors.

[1491] 2. Symptom classification and severity assessment

[1492] The server uses an analytical algorithm to analyze the data and classify the child's symptoms and assess their severity. For example, a temperature of 39 degrees or higher is considered severe. The algorithm is based on a machine learning model and uses patterns learned from past data to make the classification.

[1493] 3. Generate initial response methods

[1494] The server generates appropriate initial response instructions based on the analysis results. For example, if the patient has a temperature of 39°C, a cough, and symptoms began last night, the server generates the following advice: "Use a cooling pad, stay hydrated, and contact a medical institution immediately."

[1495] Sending data to medical professionals and responding to requests for additional information

[1496] The server sends the data, including the analysis results, to the medical professional. The medical professional accesses the EHR system using a secure communication protocol and makes a diagnosis based on the received data. If the medical professional determines that additional information is required, an additional question, such as "Do you have a rash?", is displayed on the device via the server. By answering this question, the user can provide the medical professional with the necessary additional information.

[1497] Specific examples

[1498] Scenario: A child has a high fever of 39 degrees.

[1499] 1. User:

[1500] The parent opens the device and enters the following information into the application's question form: "Temperature: 39 degrees," "Having a cough," and "Symptoms started last night."

[1501] 2. Terminal:

[1502] The terminal encrypts the entered data and sends it to the server using a secure communication protocol (HTTPS).

[1503] 3. Server:

[1504] The server validates the incoming data to ensure it is in the correct format and range, then uses an analytical algorithm to assess the symptom classification and severity, resulting in a "high fever" diagnosis.

[1505] 4. Server:

[1506] The server generates an initial response method such as "Use a cooling sheet and stay hydrated. Contact a medical institution immediately," and displays it on the terminal.

[1507] 5. Server:

[1508] The server sends the analysis results to medical professionals, who then make a diagnosis based on the received data via the EHR system.

[1509] 6. Request for additional information:

[1510] The medical professional sends a follow-up question, "Do you have a rash?", which is displayed on the device and the user answers.

[1511] The system allows users to respond quickly and accurately to their child's health conditions and allows medical professionals to make efficient diagnoses.

[1512] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1513] Step 1:

[1514] Data Entry

[1515] User action: The user launches an application using a smartphone or tablet.

[1516] Input: The user inputs information about their health condition (e.g., "Temperature: 39°C," "I have a cough," "Symptoms started last night").

[1517] What it does: The user provides information about their child's health by filling out a form in the application.

[1518] Step 2:

[1519] Data Receipt and Encryption

[1520] Terminal operation: The terminal receives the information entered by the user.

[1521] Input: Health information data entered by the user.

[1522] Data processing: The terminal encrypts the data with the AES-256 algorithm and sends it to the server using a secure communication protocol (HTTPS).

[1523] Output: The encrypted health information data is sent to the server.

[1524] Specific operation: The device encrypts data and communicates securely.

[1525] Step 3:

[1526] Data Validation

[1527] Server operation: The server receives the data sent from the terminal.

[1528] Input: Encrypted health information data.

[1529] Data calculation: The server decrypts the data and checks the data format (e.g., whether the body temperature is within the range of 35-42 degrees) and whether all required fields have been filled in.

[1530] Output: Successfully validated health information data.

[1531] Specific operation: Checks the data format and required fields, and returns an error to the terminal if there are any errors.

[1532] Step 4:

[1533] Symptom classification and severity rating

[1534] Server Operation: The server executes the data analysis algorithms.

[1535] Input: Health information data that has passed validation.

[1536] Data calculation: The server uses machine learning models to analyze health information. If the body temperature is 39 degrees, it will be classified as a high fever and the severity will be assessed as "high."

[1537] Output: Categorized symptom data and assessment results.

[1538] What it does: It uses machine learning algorithms to analyze health information, classify it into appropriate categories, and assess its severity.

[1539] Step 5:

[1540] Generate initial response methods

[1541] Server operation: The server generates an initial response method based on the analysis results.

[1542] Input: Categorized symptom data and assessment results.

[1543] Data calculation: The server generates appropriate initial response measures based on predefined response measures. For example, if the patient has a temperature of 39 degrees, a cough, and symptoms began last night, the server generates advice such as, "Use a cooling pad, stay hydrated, and contact a medical institution immediately."

[1544] Output: Advice on how to respond first.

[1545] Specific action: Generate a response method based on the conditions and provide it to the user.

[1546] Step 6:

[1547] Sending data to medical professionals

[1548] Server operation: The server sends detailed data including the analysis results to a medical professional.

[1549] Input: Initial response advice and analyzed health information data.

[1550] Data processing: The server re-encrypts the data and sends it using a secure communication protocol to a system accessed by medical professionals.

[1551] Output: Detailed data received by the medical professional.

[1552] What happens: Sends data to an EHR system and makes it available to healthcare professionals.

[1553] Step 7:

[1554] Responding to requests for additional information

[1555] User Action: If necessary, the medical professional can request additional information.

[1556] Input: Request for additional information from medical professional.

[1557] Data computation: The server sends a request for additional information to the terminal, and the user answers it to gather more data (e.g., "Do you have a rash?").

[1558] Output: Additional information from the user.

[1559] Specific operation: The server sends a request for additional information to the terminal and collects the response.

[1560] In this way, each step works in coordination, enabling a quick and accurate assessment of a child's health condition and early response.

[1561] (Application example 1)

[1562] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1563] In modern society, it is extremely important for parents and caregivers to respond promptly and appropriately to their children's health conditions. However, when sudden symptoms occur, accurate initial response is required, which is difficult for general users without specialized knowledge. Furthermore, rapid collaboration with medical professionals is also required, which requires a system that can appropriately collect, analyze, and share information. Data security and privacy protection are also important issues.

[1564] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1565] In this invention, the server includes a terminal means for receiving and analyzing information on the child's health condition entered by the user, a means for encrypting and receiving data transmitted from the terminal means and analyzing it, a means for presenting an appropriate initial response method to the user based on the data analyzed by the server means, a means for transmitting the analyzed data to a specialist, a means for responding to requests for additional information from the specialist, a display means for presenting an initial response method to the user based on the analysis results, and a means for validating the data. This enables parents and caregivers to respond to the child's health condition quickly and accurately and facilitates smooth cooperation with specialists.

[1566] The "terminal means" is a device that allows a user to input information about the health condition of a child.

[1567] "Data" refers to information entered by the user about the child's health, including temperature, symptoms, and the timing of symptoms.

[1568] The "server means" is a device for receiving and analyzing data sent from the terminal means.

[1569] "Initial response method" refers to guidelines for specific steps and actions that users should take based on the analyzed data.

[1570] "Expert" refers to someone with specialized medical knowledge, including doctors and nurses.

[1571] "Request for additional information" refers to the expert requesting further required information from the user.

[1572] The "display means" is a device or function for visually presenting the analysis results and initial response methods to the user.

[1573] "Data validation" is the process of verifying the accuracy and completeness of received data.

[1574] An "algorithm" is a computational method by which the server means analyzes the data and assesses the severity of the symptoms.

[1575] This invention builds a system that monitors children's health conditions and provides users with appropriate initial response methods. The system is mainly composed of a terminal means used by the user, a server means for analyzing data, and a means for supporting collaboration with experts.

[1576] Hardware and software used

[1577] 1. Terminal means:

[1578] Hardware: Smartphones, tablets

[1579] Software: User interface using React Native

[1580] 2. Server means:

[1581] Hardware: Standard server machine

[1582] Software: Python (Flask framework), MySQL database, data encryption with OpenSSL

[1583] Program processing

[1584] User Action:

[1585] Users use a smartphone or tablet application to enter data about their child's health, including the following:

[1586] Body temperature: 39 degrees

[1587] Cough: Yes

[1588] Symptom onset: Last night

[1589] Other associated symptoms: None

[1590] Terminal behavior:

[1591] The device encrypts the entered information (AES-256) and sends it to the server using a device-specific method (e.g., sendSecureData). This method ensures data integrity and privacy.

[1592] Server behavior:

[1593] The server receives the data sent from the terminal and then performs the following processes.

[1594] 1. Data Validation:

[1595] The server verifies the received data for accuracy and completeness, checking for blanks and filtering out inappropriate data.

[1596] 2. Data Analysis:

[1597] The server uses special algorithms (e.g., malignancy determination algorithms) to analyze the child's symptoms and severity.

[1598] 3. Generate initial response methods:

[1599] Based on the analysis results, the system generates initial action instructions to be presented to the user, such as "Use a cooling sheet, stay hydrated, and contact a medical institution immediately."

[1600] 4. Sending data to the expert:

[1601] If necessary, detailed data including analysis results can be sent to medical professionals, who can use this data to make more accurate diagnoses and treatments.

[1602] 5. Request for additional information:

[1603] If the medical professional needs more information, they will ask the user a follow-up question via the server, e.g., "Do you have a rash?"

[1604] Specific examples

[1605] Example of a prompt for the user to enter:

[1606] Child's current status:

[1607] Body temperature: 39°C

[1608] Cough: Yes

[1609] Symptoms started last night

[1610] Other associated symptoms: None

[1611] Send: true

[1612] The system allows parents and caregivers to respond quickly to sudden illnesses and medical professionals to provide appropriate support. The system also ensures data security and privacy, making it safe to use in everyday life.

[1613] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1614] Step 1:

[1615] Users use a smartphone or tablet to enter information about their child's health into the application form. Information entered includes body temperature, whether or not the child has a cough, when symptoms began, and other related symptoms. Examples of input data include "body temperature: 39°C," "cough present," "when symptoms began: last night," and "no other related symptoms."

[1616] Step 2:

[1617] The terminal encrypts the entered information. Specifically, it encrypts the data using the AES-256 encryption method. The encrypted data is then sent to the server using the terminal's sendSecureData method. This method ensures data integrity and privacy.

[1618] Step 3:

[1619] The server receives the encrypted data sent from the device. It first decrypts the received data and then validates it. Data validation checks whether there are any blank fields or inappropriate data. For example, it checks whether "body temperature" is a numeric value and whether "cough" is "yes" or "no."

[1620] Step 4:

[1621] The server inputs the validated data into a data analysis algorithm, which primarily classifies symptoms and assesses their severity. If the temperature is 39°C or higher, the algorithm evaluates the symptoms as severe and determines that escalation is necessary. Based on the results, the initial response method to be taken is generated.

[1622] Step 5:

[1623] Based on the analysis results, the server provides the user with initial response instructions. The displayed initial response instructions include specific instructions for action. For example, advice such as "Use a cooling sheet, stay hydrated, and contact a medical institution immediately" is displayed on the smartphone.

[1624] Step 6:

[1625] The server then sends the analysis results to a medical professional, if necessary. The data sent includes the information entered by the user and the server's analysis results, allowing the professional to perform a more detailed diagnosis.

[1626] Step 7:

[1627] If the specialist needs more information, the server sends the user a follow-up question, such as "Do you have a rash?", which is displayed on the smartphone. The user answers the question and the data is sent back to the server.

[1628] Step 8:

[1629] The server then re-analyzes the additional information and updates the necessary response procedures, ensuring that the user receives appropriate guidance on an ongoing basis. This process provides real-time collaboration between the user and the expert.

[1630] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1631] System Overview

[1632] This invention relates to a system in which a user inputs information about their child's health condition, transmits the information to a server via a terminal, and the server analyzes the received data and provides an appropriate initial response method. The analyzed data is then transmitted to a medical professional, who provides any necessary additional information. The system also incorporates an emotion engine that recognizes the user's emotions and reflects them in the analysis results and response methods.

[1633] Program processing

[1634] User Action:

[1635] The user uses a terminal (e.g., a smartphone or tablet) to input information about their child's health condition. The questionnaire includes questions such as "current body temperature," "type of symptoms (fever, cough, vomiting, etc.)," ​​"when symptoms began," and "other related symptoms (rash, difficulty breathing, etc.)." In addition, an emotion engine runs to collect the user's emotional state while they are entering information.

[1636] Terminal behavior:

[1637] The terminal collects information and emotion data input by the user, encrypts it, and transmits it to the server. The emotion engine analyzes the user's emotion from their voice, input speed, facial expression, etc., and transmits this data to the server as additional information.

[1638] Server behavior:

[1639] The server receives the data sent from the terminal and then performs the following analysis:

[1640] 1. Data Validation:

[1641] The server verifies the accuracy and completeness of the received data.

[1642] 2. Symptom classification and severity assessment:

[1643] The server analyzes the data using special algorithms to classify the child's symptoms and assess their severity - for example, a temperature of 39 degrees or higher is considered severe.

[1644] 3. Emotional Data Analysis:

[1645] The server analyzes the emotion data sent from the emotion engine to understand the user's emotional state. For example, if it determines that the user is very anxious, it will adjust the content and expression of the advice appropriately.

[1646] 4. Generate initial response methods:

[1647] Based on the analysis results and emotional data, the server generates initial action instructions for the user, such as "use a cooling sheet and stay hydrated" or "contact a medical institution immediately."

[1648] 5. Data transmission to medical professionals:

[1649] The server then sends detailed data, including the analysis results, to medical professionals, who can then use this data to make more accurate diagnoses and treatments.

[1650] 6. Responding to Requests for Additional Information:

[1651] If the medical professional determines that further information is needed, they will request it from the user via the server, and a follow-up question such as "Do you have a rash?" will be displayed on the device.

[1652] Examples:

[1653] Scenario: A child has a high fever of 39 degrees.

[1654] The user (parent) opens the terminal and enters the fever information:

[1655] The user types in "Temperature: 39 degrees," "Having a cough," and "Symptoms started last night." The emotion engine also collects feelings of anxiety and impatience from the parent's tone of voice and typing speed while they are typing.

[1656] The device sends the input data and emotion data to the server:

[1657] After transmission, the server immediately validates the received data and emotion data.

[1658] The server evaluates the symptom classification and severity based on the received data and emotion data:

[1659] The assessment is that the child's temperature is over 39 degrees, making the condition critical, and takes into account the parents' emotional state of high anxiety.

[1660] The server provides the user with an initial response:

[1661] The advice displayed is, "Use cooling pads and stay hydrated. Remain calm and contact a medical institution immediately."

[1662] The server sends the analysis results to the medical professional:

[1663] Medical professionals will make a diagnosis based on the data received, take into account parental concerns, and provide professional advice.

[1664] If your healthcare professional needs additional information:

[1665] For example, an additional question such as "Do you have a rash?" is displayed on the terminal via the server, and the user answers it.

[1666] The system allows parents and caregivers to respond quickly and accurately to their child's health condition, and medical professionals to make efficient diagnoses. The addition of emotional data-based responses also reduces the psychological burden on users, enabling smoother medical responses.

[1667] The processing flow will be explained below.

[1668] Step 1:

[1669] The user inputs information about their child's health condition using a terminal (e.g., a smartphone or tablet). The questionnaire includes information such as "current body temperature," "type of symptoms (fever, cough, vomiting, etc.)," ​​"when symptoms began," and "other related symptoms (rash, difficulty breathing, etc.)." As the user inputs information, the emotion engine analyzes the user's emotional state based on their tone of voice, typing speed, facial expression, etc.

[1670] Step 2:

[1671] The user clicks the submit button to submit the input.

[1672] Step 3:

[1673] The terminal encrypts the information and emotion data input by the user and transmits them to the server means.

[1674] Step 4:

[1675] The server receives the data sent from the terminal and validates the received data to check its accuracy and completeness.

[1676] Step 5:

[1677] The server begins analyzing the incoming data. It uses an algorithm to analyze the data from the user, classify the child's symptoms, and assess their severity. For example, a temperature of 39 degrees or higher is considered severe.

[1678] Step 6:

[1679] The emotion engine analyzes the transmitted emotion data and understands the user's emotional state, such as assessing anxiety, impatience, or restlessness.

[1680] Step 7:

[1681] The server then uses the analysis results and emotional data to provide the user with appropriate initial response advice, such as "Use a cooling sheet and stay hydrated. Remain calm and immediately contact a medical institution."

[1682] Step 8:

[1683] The server transmits the generated initial response method to the terminal means.

[1684] Step 9:

[1685] The terminal displays the initial response advice received from the server to the user, who then takes appropriate initial response according to the advice provided.

[1686] Step 10:

[1687] The server sends the analysis results to medical professionals, allowing them to make quick and accurate diagnoses and take appropriate action based on the data.

[1688] Step 11:

[1689] If the medical professional determines that more information is needed, a request for additional information is sent to the user through the server means.

[1690] Step 12:

[1691] The server sends a request for additional information from the medical professional to the terminal means.

[1692] Step 13:

[1693] The terminal displays a request for additional information to the user, who answers the additional questions and resubmits through the terminal.

[1694] Step 14:

[1695] The server analyzes the additional data received from the user and transmits it back to the medical professional.

[1696] Step 15:

[1697] The medical professional will determine the final diagnosis and treatment and notify the user via the server, who will then follow the final instructions.

[1698] This series of processes allows users to deal with their child's health condition quickly and accurately, and medical professionals can make efficient diagnoses. In addition, the emotional engine reduces the user's psychological burden and enables smoother medical treatment.

[1699] Example 2

[1700] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1701] Conventional health monitoring systems primarily involve inputting and analyzing information about a child's health condition. However, they lack consideration for the user's emotional state, making it difficult to completely alleviate the user's psychological burden. Furthermore, it is difficult to generate a fast and accurate initial response method or to communicate efficiently with medical professionals. Therefore, there is a need for a system that can respond quickly and appropriately while taking the user's emotional state into account.

[1702] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1703] In this invention, the server includes means for analyzing data sent from the user, means for generating an initial response method based on the analyzed data, and means for analyzing emotion data collected by the emotion engine and adjusting the initial response method, thereby enabling prompt and appropriate health management that takes the user's emotional state into consideration.

[1704] "Terminal means" refers to an electronic device such as a smartphone or tablet, which allows a user to input information about the child's health condition.

[1705] The term "server means" refers to a computer system that receives and analyzes data sent from the terminal means.

[1706] The "means for presenting an appropriate initial response method to the user" refers to a method for presenting an appropriate response method to the user based on the data analyzed by the server means.

[1707] "Means for sending to a medical professional" refers to a method by which the server means sends the analyzed data to a medical professional.

[1708] "Means for responding to requests for additional information" refers to methods for asking questions or gathering information from the user in response to requests for additional information from medical professionals.

[1709] An "emotion engine" refers to a tool that has the function of collecting and analyzing a user's emotional state from their voice, input speed, facial expressions, etc.

[1710] "Means for transmitting emotion data to server means" refers to a method for transmitting emotion data collected by the emotion engine to server means.

[1711] The "means for adjusting the initial response method based on the emotion data" refers to a method in which the server means analyzes the emotion data and appropriately adjusts the initial response method based on the results of the analysis.

[1712] This invention relates to a system in which a user inputs information about their child's health condition, transmits the information to a server via a terminal, and the server analyzes the received data and provides an appropriate initial response method. The analyzed data is then transmitted to a medical professional, who provides any necessary additional information. The system also incorporates an emotion engine that recognizes the user's emotions and reflects them in the analysis results and response methods.

[1713] User Action:

[1714] The user uses a terminal (e.g., a smartphone or tablet) to input information about their child's health condition. The questionnaire includes questions such as "current body temperature," "type of symptoms (fever, cough, vomiting, etc.)," ​​"time of symptom onset," and "other related symptoms (rash, difficulty breathing, etc.)." In addition, an emotion engine runs to collect the user's emotional state while they are entering information.

[1715] Terminal behavior:

[1716] The device temporarily stores the health information and emotional data entered by the user. It then encrypts this data and sends it to the server using a secure communication channel (e.g., HTTPS). The emotion engine analyzes the user's emotions based on their voice, typing speed, facial expressions, etc., and sends this data to the server as additional information.

[1717] Server behavior:

[1718] The server receives the data sent from the terminal and then performs the following series of analyses:

[1719] 1. Data Validation:

[1720] The server checks the received data for accuracy and completeness, especially for missing mandatory fields and anomalous data.

[1721] 2. Symptom classification and severity assessment:

[1722] The server uses a special algorithm to analyze the data, classify the child's symptoms, and assess their severity: for example, a temperature of 39 degrees or higher is considered severe.

[1723] 3. Emotional Data Analysis:

[1724] The server analyzes the emotion data sent from the emotion engine to understand the user's emotional state. For example, if it determines that the user is very anxious, it will adjust the content and expression of the advice appropriately.

[1725] 4. Generate initial response methods:

[1726] Based on the analysis results and emotional data, the server generates initial action instructions for the user, such as "use a cooling sheet and stay hydrated" or "contact a medical institution immediately."

[1727] 5. Data transmission to medical professionals:

[1728] The server then sends detailed data, including the analysis results, to medical professionals, who can then use this data to make more accurate diagnoses and treatments.

[1729] 6. Responding to Requests for Additional Information:

[1730] If the medical professional needs more information, the server forwards the request to the user, who will then be prompted with a follow-up question, such as "Do you have a rash?", which the user can answer and then send the data back to the server.

[1731] Examples:

[1732] Scenario: A child has a high fever of 39 degrees.

[1733] User Action:

[1734] The user (parent) opens the app on their smartphone and enters information into the question form, such as "Temperature: 39 degrees," "I have a cough," and "Symptoms started last night." As the parent types, the emotion engine analyzes the parent's tone of voice and typing speed in real time. If the parent says something like, "What should I do now?", the voice is judged to be highly anxious.

[1735] Terminal behavior:

[1736] The device temporarily stores the input data and emotion data, and transmits them to the server via encrypted communication.

[1737] Server behavior:

[1738] After receiving the data, the server validates it, classifies the symptoms, and assesses their severity. It assesses the temperature as "39°C or higher, a serious condition," taking into account the user's high level of anxiety. As an initial response, it generates and displays the following advice: "Use a cooling sheet and stay hydrated. Remain calm and contact a medical institution immediately." The analysis results are sent to a medical professional, who makes a diagnosis based on the received data. If necessary, additional questions such as "Do you have a rash?" are displayed in the device application, and additional information is collected when the user answers them.

[1739] This system allows parents and caregivers to respond quickly and accurately to their child's health condition, and medical professionals to make efficient diagnoses. In addition, the addition of emotional data-based responses reduces the psychological burden on users and enables smoother medical responses.

[1740] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1741] Step 1:

[1742] The user uses the terminal means to input information about the child's health condition.

[1743] Input: The questionnaire includes information such as current body temperature, type of symptoms (fever, cough, vomiting, etc.), when symptoms began, and other related symptoms (rash, difficulty breathing, etc.). The user's voice, typing speed, and facial expressions are also collected.

[1744] Specific actions: The user opens the smartphone application and enters specific numerical values ​​and symptom information into the form, such as "body temperature: 39 degrees" or "persistent cough."

[1745] Step 2:

[1746] The device collects and temporarily stores the entered health and emotional data.

[1747] Input: Health information entered by the user and voice, typing speed, and facial expression data collected by the emotion engine.

[1748] Data processing: Encrypt the collected data.

[1749] Output: Encrypted health information and emotion data.

[1750] Specific operation: The device encrypts the collected information and prepares it to be sent to the server.

[1751] Step 3:

[1752] The terminal transmits data to the server over a secure communication channel.

[1753] Input: Encrypted health information and emotion data.

[1754] Output: The encrypted data sent to the server.

[1755] What happens: The device sends data using a secure communications protocol such as HTTPS.

[1756] Step 4:

[1757] The server receives and decrypts the encrypted data.

[1758] Input: Encrypted data sent from the terminal.

[1759] Data processing: Decryption of encrypted data.

[1760] Output: Decoded health information and emotion data.

[1761] Specific operation: The server decrypts the received data and obtains the original health information and emotion data.

[1762] Step 5:

[1763] The server validates the received data.

[1764] Input: Decoded health information and emotion data.

[1765] Data calculation: Check for missing required fields and abnormal values.

[1766] Output: The validated data.

[1767] Specific behavior: The server checks the accuracy and completeness of the data and generates a warning message if there are any abnormal values.

[1768] Step 6:

[1769] The server categorizes symptoms and assesses their severity.

[1770] Input: Validated health information.

[1771] Data computation: Classification and severity assessment using ML-based algorithms.

[1772] Output: Symptom classification and severity rating.

[1773] Specific operation: For example, the server evaluates the patient's body temperature as "39 ​​degrees or higher, a serious condition," and decides on the next course of action.

[1774] Step 7:

[1775] The server analyzes the emotion data.

[1776] Input: Validated emotion data.

[1777] Data Computation: Emotional state is assessed using the emotion engine's analytical algorithms.

[1778] Output: Emotional state assessment results.

[1779] Specific behavior: If the user is determined to be in a highly anxious state, appropriate countermeasures are adjusted based on the analysis results.

[1780] Step 8:

[1781] The server generates an initial response method.

[1782] Input: Symptom classification results, severity rating, emotional state rating results.

[1783] Data calculation: Generate appropriate response methods based on this data.

[1784] Output: Initial response method.

[1785] Specific actions: The server generates specific advice such as "Use cooling pads, stay hydrated, stay calm and contact a medical professional."

[1786] Step 9:

[1787] The server sends the generated initial response instructions to the user.

[1788] Input: Initial response method.

[1789] Output: Initial response instructions sent to the user.

[1790] Specific operation: The server sends the advice to the terminal, which displays it to the user.

[1791] Step 10:

[1792] The server sends the analysis results to a medical professional.

[1793] Input: Analysis results.

[1794] Output: Analysis results sent to medical professionals.

[1795] What it does: The server encrypts the analysis results and sends them to the medical professional's system using a secure communication channel.

[1796] Step 11:

[1797] A server responds to requests for additional information from medical professionals.

[1798] Input: Request for additional information.

[1799] Output: The result of collecting additional information.

[1800] What it does: The medical professional enters a follow-up question, such as "Do you have a rash?", which the server forwards to the user's device. The user provides additional information and sends it back to the server.

[1801] (Application example 2)

[1802] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1803] There is a need for a system that can quickly and accurately monitor a child's health condition, reduce the psychological burden on parents and caregivers, and immediately provide appropriate medical treatment from experts. However, existing systems do not adequately consider the user's emotional state, do not adequately assess the severity of the condition, and do not provide an easy-to-use interface for the user. This makes it difficult to provide prompt medical treatment.

[1804] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting and analyzing the user's emotional state, means for adjusting an initial response method based on the emotional data, and robot means for collecting the child's health condition data and emotional data and transmitting them to the server. This enables a quick and accurate initial response adapted to the user's emotions and improves the accuracy of expert diagnoses.

[1805] The "terminal means" is a device that allows a user to input information about the health condition of a child.

[1806] The "server means" is a device that receives data sent from the terminal means and performs various analyses.

[1807] The "expert means" is a means for transmitting the analyzed data to an expert and providing feedback from the expert to the user.

[1808] The "additional information request means" is a means for responding to requests for additional information from experts.

[1809] The "emotion collection means" is a device that collects the user's voice, input speed, facial expression, etc., and analyzes their emotional state.

[1810] The "emotion response means" is a means for adjusting the initial response method based on the emotion data.

[1811] The "robot means" is a device that collects the child's health and emotional data and transmits it to the server.

[1812] The system of this invention includes terminal means for a user to input information about the child's health condition, server means for receiving and analyzing data sent from the terminal means, means for presenting an appropriate initial response method to the user based on the analyzed data, means for sending the analysis results to an expert, means for responding to requests for additional information from the expert, means for collecting and analyzing the user's emotional state, means for adjusting the initial response method based on the emotional data, and robot means for collecting the child's health condition data and emotional data and sending it to the server.

[1813] The hardware used is a terminal such as a smartphone or tablet, as well as a home security robot, while the software used is the EmotionRecognizer library (for emotion collection), the HealthDataCollector library (for health status data collection), the ActionSuggester library (for suggesting initial response methods), the Python programming language, and the HTTP request library (for data communication).

[1814] The process begins with the user entering information about their child's health using a terminal. The entered information includes body temperature, the type of symptoms (fever, cough, vomiting, etc.), the time of symptom onset, and other related symptoms (rash, difficulty breathing, etc.). In addition, the emotion collection means collects emotion data from the user's voice, input speed, facial expressions, etc.

[1815] The health condition data and emotion data sent from the terminal means are received by the server means. The server means validates the received data and then executes an algorithm to classify symptoms and assess their severity. It also analyzes the emotion data to understand the user's emotional state. Based on this, it adjusts the initial response method provided to the user and generates appropriate advice.

[1816] The advice includes specific instructions such as "use a cooling sheet and stay hydrated" and "contact a medical institution immediately." The results are presented to the user and simultaneously sent to the specialist. The specialist can make a highly accurate diagnosis and take appropriate action based on the received data. If the specialist requires additional information, additional questions for the user are displayed on the terminal means. The user inputs the additional information and sends it to the server means.

[1817] As a concrete example, if a child has a high fever of 39 degrees, the parent would use the terminal to input information such as "Temperature: 39 degrees," "Coughing," and "Symptoms started last night." At this time, feelings of anxiety and impatience are also collected from the parent's tone of voice and input speed. The data sent from the terminal means is analyzed by the server means, and specific advice such as "Use a cooling sheet and stay hydrated. Remain calm and contact a medical institution immediately" is returned. Furthermore, if the specialist asks additional questions such as "Do you have a rash?", these are also displayed to the user, and the answer is sent to the server.

[1818] An example of a prompt is, "A parent has entered their child's health status. The child's temperature is 39 degrees and they have been coughing since last night. The parent's voice is very unstable and they are typing quickly. Please provide an appropriate initial response based on the analysis results."

[1819] In this way, the present invention enables quick and smooth information flow between users and specialists, and provides emotionally sensitive responses, thereby realizing more accurate medical responses.

[1820] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1821] Step 1:

[1822] The user uses the device to input information about the child's health condition. The input data includes body temperature, type of symptoms, time of onset, and other related symptoms. This information is collected through the device's input interface. In addition, the device also collects the user's emotional data, which is obtained through voice tone, input speed, and facial expression analysis.

[1823] Step 2:

[1824] The device encrypts the health condition data and emotional data entered by the user and sends them to the server. The data sent includes the user's input information (e.g., body temperature, symptoms) and the collected emotional data.

[1825] Step 3:

[1826] The server validates the received data. Validation is a process to check the accuracy and completeness of the data, checking for missing data or abnormal values. Input: Health status data and emotion data sent from the device. Output: Validated data.

[1827] Step 4:

[1828] The server runs an algorithm to assess the severity of symptoms based on the validated data. For example, a body temperature of 39°C or higher is considered severe. Input: Validated data. Output: Symptom classification and severity assessment results.

[1829] Step 5:

[1830] The server analyzes the emotional data and understands the user's emotional state. The analysis is based on collected voice tone, input speed, and facial expression data. Input: Emotional data. Output: Analyzed emotional state.

[1831] Step 6:

[1832] The server generates an initial response method to provide to the user based on the symptom severity assessment result and emotional state. This includes specific actions such as "use a cooling sheet and stay hydrated" and "contact a medical institution immediately." Input: Severity assessment result and emotional state. Output: Initial response method.

[1833] Step 7:

[1834] The server sends the generated initial response method to the terminal and presents it to the user. The user responds accordingly. Input: Initial response method. Output: Initial response method displayed on the terminal.

[1835] Step 8:

[1836] The server sends the analysis results and detailed data about the user's emotional state to the expert. Input: Analysis results and emotional state. Output: Data transmission to the expert.

[1837] Step 9:

[1838] If the expert needs more information, he sends a follow-up question to the user through the server, for example a specific question such as "Do you have a rash?" Input: Follow-up question from the expert Output: Follow-up question displayed on the terminal.

[1839] Step 10:

[1840] The user inputs additional information through the terminal, which is then sent to the server. The server then performs the necessary analysis again and sends the results to the expert. Input: Additional information from the user. Output: Reanalysis results.

[1841] This allows for smooth information flow between users and specialists, enabling prompt and appropriate medical responses.

[1842] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1843] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1844] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1845] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1846] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1847] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1848] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1849] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1850] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1851] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1852] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1853] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1854] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1855] 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.

[1856] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1857] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1858] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1859] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1860] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1861] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1862] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1863] The following is further disclosed regarding the above embodiment.

[1864] (Claim 1)

[1865] a terminal means for a user to input information about the child's health condition;

[1866] a server means for receiving and analyzing data transmitted from the terminal means;

[1867] means for presenting an appropriate initial response method to a user based on the data analyzed by the server means;

[1868] means for transmitting the analyzed data to a medical professional;

[1869] The system includes a means for responding to requests for additional information from a medical professional.

[1870] (Claim 2)

[1871] 10. The system of claim 1, wherein the server means executes an algorithm to assess the severity of symptoms based on data received from the user.

[1872] (Claim 3)

[1873] 10. The system of claim 1, wherein the user means provides an interface that displays feedback from a medical professional and allows the user to enter additional information.

[1874] "Example 1"

[1875] (Claim 1)

[1876] a terminal means for a user to input information about the child's health condition;

[1877] a server means for receiving the data transmitted from the terminal means, encrypting the data, and analyzing the data;

[1878] means for classifying symptoms and assessing severity based on the data analyzed by the server means;

[1879] means for presenting an appropriate initial response method to a user based on the analysis result;

[1880] means for transmitting the analyzed data to a medical professional;

[1881] The system includes a means for responding to requests for additional information from a medical professional.

[1882] (Claim 2)

[1883] 10. The system of claim 1, wherein the server means executes an algorithm to validate data received from a user and assess severity based on symptom classification.

[1884] (Claim 3)

[1885] 10. The system of claim 1, wherein the user means provides an interface that displays feedback from a medical professional and allows the user to enter additional information.

[1886] "Application Example 1"

[1887] (Claim 1)

[1888] a terminal means for a user to input information about the child's health condition;

[1889] a server means for receiving and analyzing data transmitted from the terminal means;

[1890] means for presenting an appropriate initial response method to a user based on the data analyzed by the server means;

[1891] means for transmitting the analyzed data to an expert;

[1892] a means for responding to requests for additional information from experts; and

[1893] a display means for providing an initial response method to a user based on the analysis result;

[1894] means for validating said data;

[1895] A system including:

[1896] (Claim 2)

[1897] 10. The system of claim 1, wherein the server means executes an algorithm to assess the severity of symptoms based on data received from the user.

[1898] (Claim 3)

[1899] 10. The system of claim 1, wherein the user means provides an interface that displays feedback from the expert and allows the user to enter additional information.

[1900] "Example 2: Combining Emotion Engines"

[1901] (Claim 1)

[1902] a terminal means for a user to input information about the child's health condition;

[1903] a server means for receiving and analyzing data transmitted from the terminal means;

[1904] means for presenting an appropriate initial response method to a user based on the data analyzed by the server means;

[1905] means for transmitting the analyzed data to a medical professional;

[1906] a means to respond to requests for additional information from health care professionals;

[1907] An emotion engine that analyzes the user's voice, input speed, facial expressions, etc. to collect emotional states;

[1908] means for transmitting emotion data collected by said emotion engine to a server means;

[1909] a means for adjusting an initial response method based on the emotion data;

[1910] A system including:

[1911] (Claim 2)

[1912] 2. The system according to claim 1, wherein the server means executes an algorithm for assessing the severity of symptoms based on the data received from the user, and analyzes the emotion data.

[1913] (Claim 3)

[1914] 10. The system of claim 1, wherein the user means displays feedback from a medical professional, provides an interface through which the user can input additional information, and tailors advice to the user's psychological state based on emotional data.

[1915] "Application example 2 when combining emotion engines"

[1916] (Claim 1)

[1917] a terminal means for a user to input information about the child's health condition;

[1918] a server means for receiving and analyzing data transmitted from the terminal means;

[1919] means for presenting an appropriate initial response method to a user based on the data analyzed by the server means;

[1920] means for transmitting the analyzed data to an expert;

[1921] a means for responding to requests for additional information from experts; and

[1922] A means for collecting and analyzing the user's emotional state;

[1923] a means for adjusting an initial response method based on the emotion data;

[1924] a robotic means for collecting and transmitting health and emotional data of the child to a server;

[1925] A system including:

[1926] (Claim 2)

[1927] 10. The system of claim 1, wherein the server means executes an algorithm to assess the severity of symptoms based on data received from the user.

[1928] (Claim 3)

[1929] 10. The system of claim 1, wherein the user means provides an interface that displays feedback from the expert and allows the user to enter additional information. [Explanation of symbols]

[1930] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a terminal means for a user to input information about the child's health condition; a server means for receiving and analyzing data transmitted from the terminal means; means for presenting an appropriate initial response method to a user based on the data analyzed by the server means; means for transmitting the analyzed data to a medical professional; The system includes a means for responding to requests for additional information from a medical professional.

2. 10. The system of claim 1, wherein said server means executes an algorithm to assess the severity of symptoms based on data received from the user.

3. 10. The system of claim 1, wherein said user means provides an interface for displaying feedback from a medical professional and for allowing a user to enter additional information.

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