System

Abstract

A system is provided.SOLUTION: A means for a user to request a kit for collecting a sample by the user, a means for the user to collect the sample and send it, a means for analyzing the sample by an AI model after receiving the sample to generate a primary determination result, a means for notifying the user of the primary determination result, and a means for providing an instruction regarding a next step.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional cancer testing systems require users to go to a hospital to undergo testing, which is time-consuming and laborious. Furthermore, to eliminate the need for users to go to a hospital, there is a demand for systems that allow users to collect samples at home and send them for analysis. However, such systems have issues with sample quality control, analytical accuracy, safety, and other factors. The present invention aims to provide a system that solves these issues, enables simple and reliable analysis of samples, and allows users to receive an initial diagnosis early. [Means for solving the problem]

[0005] The present invention provides a system that includes a means for a user to request a kit for self-collection of a specimen, a means for the user to collect the specimen and send it, a testing device for analyzing the specimen after receiving it, a means for analyzing the analysis results using an AI model and generating a preliminary determination result, a means for notifying the user of the preliminary determination result, and a means for providing instructions regarding next steps. The system also includes a means for storing the specimen analysis results in a database and comparing them with subsequent test results, enabling accurate health monitoring. Furthermore, the use of an AI model improves the accuracy of specimen analysis and provides rapid preliminary determination results.

[0006] "User" refers to the individual who requests a test kit and collects and sends in a specimen.

[0007] "Kit" refers to a package that contains tools and instructions for a user to collect a specimen.

[0008] "Request" refers to the application process a user performs to have a test kit sent to them.

[0009] "Specimen" means a blood, urine, or saliva sample taken by a User to assess their health status.

[0010] "Sending" refers to the act of the user mailing the collected sample to the designated laboratory.

[0011] "Means" refers to a technical device or method for achieving a specific function or operation.

[0012] "Laboratory Equipment" means equipment used to analyze specimens received at a laboratory.

[0013] "Analysis" means any scientific or technical examination of a specimen to determine whether it may be cancerous.

[0014] "AI model" refers to artificial intelligence software that learns and analyzes sample data.

[0015] "Primary assessment result" refers to the test result initially generated by the AI ​​model.

[0016] "Notification" refers to the act of informing the user of the results of the initial assessment and information regarding next steps.

[0017] "Instructions" refers to content that guides the user on what to do next.

[0018] "Database" refers to a collection of information that stores analysis results and can be retrieved and used as needed. [Brief explanation of the drawings]

[0019] [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

[0020] 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.

[0021] First, the terms used in the following description will be explained.

[0022] 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).

[0023] 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.

[0024] 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.

[0025] 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.

[0026] 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."

[0027] [First embodiment]

[0028] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0029] 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.

[0030] 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).

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0036] 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.

[0037] 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.

[0038] 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.

[0039] 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."

[0040] The present invention relates to a system that allows users to collect samples themselves and provides rapid and highly accurate primary determination results through AI analysis. Specific embodiments of the present invention are described below.

[0041] Test kit request

[0042] User:

[0043] Users log in to a dedicated web or mobile application and request a test kit from the menu, answering questions about their name, address, contact information, and health status.

[0044] Device:

[0045] The terminal verifies the information entered by the user to ensure there are no omissions or errors. Once verification is complete, the user presses the send request button to send the input details to the server.

[0046] server:

[0047] The server receives the request data from the user and stores it in a database. At the same time, it prepares the test kit and begins the process of sending it to the user's address. Once the process is complete, it generates a tracking number to track the delivery status and returns that information to the terminal.

[0048] Sample collection and shipping

[0049] User:

[0050] Users receive the test kit at home and follow the instructions in the kit to collect a sample. For example, for a blood test, users use a special lancet to collect blood from their fingertip. The collected sample is then placed in the enclosed return envelope and sent to the designated lab.

[0051] Device:

[0052] The device provides an interface for users to record information about the collected specimen (collection date, type, etc.), and the app also guides users through the process of properly packaging the specimen and mailing it to the lab.

[0053] Sample analysis and initial determination

[0054] server:

[0055] When the laboratory receives the sample, it notifies the server, which updates the database and notifies the user that the sample has been received, and then sends the information to the analyzer to begin analyzing the sample.

[0056] Analysis equipment:

[0057] The analysis device analyzes the received sample and generates the results, which are then sent back to the server.

[0058] server:

[0059] The server inputs the received analysis data into the AI ​​model, which then analyzes the images of the specimens. The AI ​​model aggregates the results of multiple specimen tests and evaluates the presence or absence of cancer-related markers.

[0060] AI model:

[0061] The AI ​​model generates a preliminary judgment result based on the sample analysis results, which is then sent back to the server.

[0062] Notification of initial assessment results and next steps

[0063] server:

[0064] The server receives the initial assessment results sent by the AI ​​model and notifies the user of the results, as well as providing instructions on the next steps the user should take (e.g., recommending further testing).

[0065] Device:

[0066] The device will notify the user of the initial assessment results and instructions on next steps via in-app push notification or email, where the user can review the details.

[0067] User:

[0068] The user takes the necessary action based on the notified initial assessment result and the next step. For example, if a detailed examination is required, the user makes an appointment.

[0069] This allows users to easily collect samples from the comfort of their own home and receive a rapid and accurate primary diagnosis of cancer.The present invention provides a system that improves the quality control and analytical accuracy of samples and effectively monitors the health status of users.

[0070] The processing flow will be explained below.

[0071] Step 1:

[0072] User:

[0073] Users launch the HELPO app and log in to their account. They then select "Apply for a Test Kit" from the menu and follow the instructions to enter the required information (name, address, contact information, and health status questions).

[0074] Step 2:

[0075] Device:

[0076] The terminal validates the information entered by the user, checking for missing or incorrect data, and when the send request button is pressed, sends the contents to the server. If the transmission is successful, a confirmation message is displayed to the user.

[0077] Step 3:

[0078] server:

[0079] The server receives the request data from the user and stores it in a database. It then prepares the test kit and arranges for it to be sent to the user's address. Once the delivery arrangements are complete, it generates a tracking number to track the delivery status and sends it to the terminal.

[0080] Step 4:

[0081] Device:

[0082] The terminal will display information to the user, including a tracking number, and notify them of the expected arrival date of the test kit.

[0083] Step 5:

[0084] User:

[0085] Users receive a test kit and follow the instructions in the kit to collect a sample (either blood, urine, or saliva), then place the sample in a designated return envelope and mail it to the lab.

[0086] Step 6:

[0087] Device:

[0088] The device provides an interface for users to record information about the collected specimen (collection date and time, specimen type, etc.), and the app also guides users through the process of sending the specimen to a laboratory.

[0089] Step 7:

[0090] server:

[0091] The server receives a notification of sample receipt from the laboratory, confirms that the laboratory has received the sample, updates the database with that information, and notifies the terminal.

[0092] Step 8:

[0093] Device:

[0094] The device will notify the user via push notification or email that the sample has arrived at the lab.

[0095] Step 9:

[0096] server:

[0097] The server sends the sample information to the analysis device and starts the analysis. The received analysis results are input into the AI ​​model and the analysis is carried out.

[0098] Step 10:

[0099] AI model:

[0100] The AI ​​model analyzes the images of the specimens, assessing the presence or absence of cancer-related markers and abnormalities, and generates analysis results that are sent back to the server.

[0101] Step 11:

[0102] server:

[0103] The server receives the analysis results from the AI ​​model, generates a preliminary judgment based on the results, and creates instructions for the next steps and sends them to the device.

[0104] Step 12:

[0105] Device:

[0106] The device will notify the user of the initial results and instructions for next steps. The user will receive detailed results via in-app notifications or email.

[0107] Step 13:

[0108] User:

[0109] The user checks the notified primary assessment result and follows the instructions for the next step, making an appointment for a detailed examination if necessary.

[0110] The above are the specific processing steps and their details of the system. This process allows users to receive a simple and highly accurate primary cancer diagnosis from the comfort of their own home.

[0111] Example 1

[0112] 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."

[0113] In the prior art, when a user collects a sample themselves and has it analyzed at a specialized institution, it is difficult to obtain a rapid and accurate determination result. Furthermore, there are challenges in controlling the quality of the sample and improving the accuracy of the analysis results. Furthermore, specific instructions regarding the next steps the user should take are not provided, which may delay appropriate action. The present invention aims to solve these problems and provide a system that allows a user to easily collect a sample from home and obtain a rapid and accurate initial determination result.

[0114] 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.

[0115] In this invention, the server includes means for a user to request a kit for collecting a specimen themselves, means for a terminal to verify information entered by the user and send it to the server, means for the server to store the received information in a database and ship a test kit, a testing device for analyzing the specimen after receiving it, means for generating analysis results and sending the data to the server, means for the server to input the analysis data into an AI model and generate a primary determination result, means for notifying the user of the primary determination result, and means for providing instructions regarding the next step. This enables the user to obtain a primary determination result quickly and accurately.

[0116] "User" refers to an individual who uses the system to collect specimens and receive analytical results.

[0117] A "specimen" refers to a biological substance such as blood, urine, or saliva that is collected by the user and subjected to testing.

[0118] "Kit" refers to a set containing tools that a user can use to collect a specimen themselves.

[0119] "Terminal" refers to an information processing device used by a user, such as a computer, smartphone, or tablet.

[0120] "Server" refers to the central processing unit that receives requests from users, processes and stores data, and returns results to users.

[0121] A "database" refers to a system that allows a server to efficiently store, manage, and search information.

[0122] "Testing device" refers to a device that analyzes received specimens and generates result data.

[0123] "AI model" refers to software that includes algorithms for using artificial intelligence to analyze data and generate initial assessment results.

[0124] "Primary assessment result" refers to the initial analysis result generated by the AI ​​model and refers to the evaluation information provided to the user.

[0125] "Instructions" refers to guidance or recommendations regarding the next action a user should take after receiving the initial assessment results.

[0126] This invention relates to a system that allows users to collect samples themselves and provides rapid and highly accurate initial results through analysis by an AI model. This system consists of multiple components, including users, terminals, and servers.

[0127] Test kit request

[0128] User:

[0129] Users log in to a dedicated web or mobile application and request a test kit from the menu, answering questions about their name, address, contact information, and health status.

[0130] Device:

[0131] The terminal validates the information entered by the user to ensure there are no missing or incorrect information. For example, it uses form validation to check that address fields are not blank and that phone numbers are entered in the correct format. Once the validation is complete, the user presses the send button to send the input information to the server.

[0132] server:

[0133] The server receives the request data from the user and stores that information in a database. For example, MySQL (registered trademark) or PostgreSQL is used for the database. The server also initiates the procedure for shipping the test kit and requests the shipping company to ship the kit. At this time, the server generates a tracking number to track the delivery status and returns that information to the terminal.

[0134] Sample collection and shipping

[0135] User:

[0136] Users receive the test kit at home and collect the sample according to the instructions included in the kit. For example, for a blood test, a special lancet is used to collect blood from the fingertip. The collected sample is placed in the enclosed return envelope and sent to the designated lab. The user then records the date and time of collection and the type of sample in the application.

[0137] Device:

[0138] The terminal records the collection information entered by the user and stores it in a database. The terminal also displays a screen that guides the user through the process of safely packaging the specimen and sending it to the lab.

[0139] Sample analysis and initial determination

[0140] server:

[0141] When the laboratory receives the specimen, it notifies the server, which updates the database and notifies the user that the specimen has been received, and then the server sends the information to the analyzer to begin analyzing the specimen.

[0142] Analysis equipment:

[0143] The analysis device analyzes the received sample and generates result data, for example, using a spectrophotometer or flow cytometer, and the analysis result data is sent back to the server.

[0144] server:

[0145] The server inputs the received analysis data into a generative AI model. The generative AI model is built using, for example, Tensorflow (registered trademark) or PyTorch. The AI ​​model generates a primary judgment result based on the sample analysis results and returns the result to the server.

[0146] Notification of initial assessment results and next steps

[0147] server:

[0148] The server receives the initial assessment results sent by the AI ​​model and notifies the user of the results, along with instructions on what next steps to take (e.g., recommending further testing).

[0149] Device:

[0150] The device will notify the user with the initial assessment results and instructions on next steps via an in-app push notification or email, and the user can open the app for more details.

[0151] User:

[0152] The user takes the necessary action based on the notified primary assessment result and the next step. For example, if a detailed examination is required, the user makes an appointment.

[0153] Prompt Sentence Examples

[0154] "Please generate a preliminary AI result based on the analysis results of the sample I provide. Please write a sentence in natural language that explains the entire process from requesting a test kit to receiving the results."

[0155] This allows users to easily collect samples from the comfort of their own home and receive a rapid and highly accurate initial diagnosis. This system improves the quality control and analysis accuracy of samples, enabling effective monitoring of users' health conditions.

[0156] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0157] Step 1:

[0158] User:

[0159] Log in to the dedicated web application or mobile application. The information required for login is your user ID and password. Once you have successfully logged in, your user dashboard will be displayed.

[0160] input:

[0161] User ID and password

[0162] output:

[0163] Login success message, dashboard display

[0164] Specific behavior:

[0165] A user opens the app, enters their user ID and password on the login screen, and clicks the "Login" button. The system verifies the authentication information, and if it is correct, the dashboard is displayed.

[0166] Step 2:

[0167] User:

[0168] Request a test kit: Users select the "Request a test kit" option from the menu and answer questions about their name, address, contact information, and health status.

[0169] input:

[0170] Name, address, contact information, and health status

[0171] output:

[0172] Request confirmation message and input details display screen

[0173] Specific behavior:

[0174] The user enters the required information on the "Request a Test Kit" screen and clicks the "Submit" button. A confirmation message for the entered information is displayed on the screen.

[0175] Step 3:

[0176] Device:

[0177] Validate user-entered information and format submitted data.

[0178] input:

[0179] User-provided name, address, contact information, and health status answers

[0180] output:

[0181] Verified data, data sent to server

[0182] Specific behavior:

[0183] The device checks the contents of the input fields, formats them as needed (e.g., checks if the address field is empty, verifies that the contact information is in the correct format), and prepares the data to be sent to the server.

[0184] Step 4:

[0185] server:

[0186] It receives the request data, stores the information in a database, and processes the shipping of the test kit.

[0187] input:

[0188] Request data sent from the device

[0189] output:

[0190] Request information and tracking number stored in the database

[0191] Specific behavior:

[0192] The server receives the request data and saves it in a database. Then, it requests the shipping company to ship the test kit via API. It receives a tracking number from the shipping company and returns it to the user.

[0193] Step 5:

[0194] User:

[0195] After receiving the test kit, collect the sample according to the instructions, place the collected sample in the return envelope, and send it to the designated laboratory.

[0196] input:

[0197] Test kit instructions, user samples

[0198] output:

[0199] Collected specimen and message of completion of sending

[0200] Specific behavior:

[0201] The user follows the instructions to collect a sample (e.g., using a lancet to collect blood from a fingertip), seals it in a return envelope, and then goes to the post office to mail it off to the lab.

[0202] Step 6:

[0203] server:

[0204] When the lab receives the sample, it receives a notification and updates the database with the information, which is then sent to the analyzer.

[0205] input:

[0206] Acknowledgment from the lab

[0207] output:

[0208] Database update information, data sent to analysis equipment

[0209] Specific behavior:

[0210] When the laboratory receives the sample, it notifies the server, which updates the database with the receipt information and sends an analysis request to the analyzer.

[0211] Step 7:

[0212] Analysis equipment:

[0213] The received samples are analyzed, and analysis result data is generated and sent to the server.

[0214] input:

[0215] Sample information sent to the analyzer

[0216] output:

[0217] Analysis result data

[0218] Specific behavior:

[0219] The analytical device analyzes the sample, generates the result data, and sends it to the server. For example, a spectrophotometer or flow cytometer is used.

[0220] Step 8:

[0221] server:

[0222] The received analysis data is input into the AI ​​model to generate a primary judgment result, which is then notified to the user.

[0223] input:

[0224] Analysis result data

[0225] output:

[0226] Primary judgment results, user notification data

[0227] Specific behavior:

[0228] The server sends the analysis results data to the AI ​​model, which generates a first-order judgment. The generation AI model uses pre-trained TensorFlow or PyTorch, and notifies the user of the result.

[0229] Step 9:

[0230] Device:

[0231] The user is notified of the initial assessment results and instructions regarding next steps.

[0232] input:

[0233] Initial assessment results and instructions on next steps

[0234] output:

[0235] Notification Message

[0236] Specific behavior:

[0237] The device will notify the user of the initial assessment results and next steps via in-app push notification or email.

[0238] Step 10:

[0239] User:

[0240] Respond according to the notified initial assessment result and next steps, for example, make an appointment for a detailed examination.

[0241] input:

[0242] Initial assessment results and instructions on next steps

[0243] output:

[0244] Detailed examination reservation information, etc.

[0245] Specific behavior:

[0246] The user confirms the notification and takes the necessary next steps (e.g., schedules an appointment for a detailed examination if necessary).

[0247] (Application example 1)

[0248] 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."

[0249] Conventional home sample collection and analysis systems lack sufficient support for users in the accurate sample collection process, resulting in issues with sample collection accuracy and adherence to procedures. Furthermore, methods for quickly and accurately notifying users of sample analysis results are limited, and clear guidance on how to proceed to the next step is lacking. To address these issues, a system is needed that allows users to intuitively and reliably collect samples and instantly receive analysis results.

[0250] 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.

[0251] In this invention, the server includes means for a user to request a kit for collecting a specimen by themselves, means for the user to collect and send the specimen, a testing device for analyzing the specimen after receiving the specimen, means for analyzing the analysis result using an AI model and generating a primary determination result, means for notifying the user of the primary determination result, means for providing instructions regarding the next step, means for the user to receive visual and audio guidance by wearing a head-mounted display device, and means for checking the user's specimen collection procedure in real time, thereby enabling the user to reliably collect a specimen and obtain a rapid and highly accurate analysis result.

[0252] "User" means an individual or organization that uses the system to collect specimens and receive analysis and notification of results.

[0253] A "kit for collecting specimens" is a set that includes tools and instructions that allow users to collect specimens safely and accurately themselves.

[0254] A "method of requesting a kit" is how a user places an order for a test kit through a web or mobile application.

[0255] "Means for sending specimens" refers to a method that provides procedures and tools for users to send collected specimens to a designated analysis laboratory.

[0256] A "test device" is a physical or chemical device that analyzes a received specimen and generates a result.

[0257] "AI Model" means the artificial intelligence algorithms and models used to generate a preliminary determination result based on the analysis of a received specimen.

[0258] The "means for generating a primary judgment result" is a method for using an AI model to summarize the analysis results of a sample as a primary evaluation.

[0259] The "means for notifying the user of the primary determination results" refers to a communication means or notification system for immediately notifying the user of the analysis results.

[0260] The "means for providing instructions regarding the next step" is a method for guiding the user on the next action or necessary response to be taken based on the results of the primary determination.

[0261] A "head-mounted display device" is a device that displays visual and audio information when worn by a user.

[0262] "Means for receiving visual and audio guidance" refers to a method in which the user is provided with visual and audio guidance via a head-mounted display to guide them through the sample collection procedure and delivery method.

[0263] "Means for verifying a user's sample collection procedures in real time" refers to a method for using a head-mounted display to monitor a user's procedures in real time and verify accuracy and compliance.

[0264] The present invention relates to a system that includes a series of processes in which a user collects a sample themselves and receives visual and audio guidance using a head-mounted display device. The system comprises the following steps:

[0265] First, a user wears a head-mounted display device with a dedicated application installed and requests a test kit. The user logs in to the application and follows the on-screen instructions to answer questions about their personal information and health status. This information is displayed visually through the head-mounted display, and a voice assistant guides the input. The server receives this information, processes the request, and delivers the test kit to the user's address.

[0266] Next, the user collects a sample at home using the provided test kit. The head-mounted display device provides step-by-step instructions visually and audibly. For example, for a blood test, the user is guided on how to use the lancet and properly collect the sample, with real-time confirmation of the procedure. Once the sample is collected, it is placed in the provided return envelope and sent to the designated analysis lab.

[0267] When the sample arrives at the lab, the information is sent to the server, which updates the information and notifies the user via a push notification on the head-mounted display that the sample has been received. The testing device then analyzes the sample and generates the results, which are then sent back to the server.

[0268] The server inputs the received analysis results into the generative AI model to generate a preliminary assessment result, which is then communicated to the user via a head-mounted display, where the user can check the results in real time and receive visual and audio instructions regarding next steps (e.g., recommending further testing).

[0269] (Hardware and Software Use)

[0270] A common device such as Oculus Quest 2 is used as the head-mounted display device. The VoiceAssistant library is used for the voice assistant, and the requests library is used for communication processing. The hmd_display library is used for display management. This allows users to intuitively follow prompts and smoothly carry out the process from sample collection to checking analysis results.

[0271] (Example)

[0272] When the user wears the head-mounted display device and gives a voice command such as "Hello, please tell me the procedure for sample collection," visual and voice guidance begins. Similarly, the system operates appropriately when the user gives voice commands following prompts such as "I would like to check the current test results" to send the sample and receive notification of the analysis results.

[0273] This allows users to collect samples easily and safely from the comfort of their own home and receive prompt and highly accurate initial results.

[0274] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0275] Step 1:

[0276] The user launches the application and requests a test kit.

[0277] Specific behavior:

[0278] The user wears a head-mounted display device and logs in to the application. Next, they follow the on-screen instructions to answer questions about their personal information and health status. This information is then sent to the server as input data.

[0279] Input: User information (name, address, health status, etc.)

[0280] Output: A request for a test kit is sent to the server.

[0281] Step 2:

[0282] The server receives and processes requests for test kits.

[0283] Specific behavior:

[0284] The server validates the received request data and stores it in a database. After checking for any missing or incorrect information, it initiates the shipping process for the test kit and obtains a tracking number from the delivery company. The tracking number is then returned to the user.

[0285] Input: Request data

[0286] Output: Tracking number is sent to the user

[0287] Step 3:

[0288] The user receives the test kit and collects the specimen.

[0289] Specific behavior:

[0290] The user opens the test kit and follows the visual and audio guidance on the head-mounted display device to collect a sample, such as using a lancet to draw blood from a fingertip. The user is then checked in real time during the process.

[0291] Input: Test kit, visual and audio guidance

[0292] Output: Collected specimen

[0293] Step 4:

[0294] The user sends the collected specimen.

[0295] Specific behavior:

[0296] The collected sample is placed in the enclosed return envelope and sent to the designated analysis lab, and the head-mounted display device provides visual and audio guidance on proper packaging and mailing instructions.

[0297] Input: Collected specimen, return envelope

[0298] Output: Specimen sent to the lab

[0299] Step 5:

[0300] The server confirms receipt of the specimen.

[0301] Specific behavior:

[0302] When the sample arrives at the lab, the information is sent to the server, which updates the information and sends a push notification to the user to let them know the sample has been received.

[0303] Input: Specimen receipt notice

[0304] Output: Acknowledgement to user

[0305] Step 6:

[0306] The testing device analyzes the sample and generates a result.

[0307] Specific behavior:

[0308] The testing device analyzes the sample received from the server and generates the result data, which is then sent back to the server.

[0309] Input: Sample

[0310] Output: Analysis result data

[0311] Step 7:

[0312] The server inputs the analysis results into the AI ​​model and generates a primary judgment result.

[0313] Specific behavior:

[0314] The server inputs the received analysis result data into the generative AI model to generate a primary judgment result, which is then sent back to the server.

[0315] Input: Analysis result data

[0316] Output: Primary judgment result

[0317] Step 8:

[0318] The server notifies the user of the results of the initial judgment.

[0319] Specific behavior:

[0320] The server notifies the user of the generated primary judgment result via the head-mounted display device. The user receives a push notification and can check the details.

[0321] Input: Primary judgment result

[0322] Output: User notification

[0323] Step 9:

[0324] The server provides instructions to the user regarding next steps.

[0325] Specific behavior:

[0326] Based on the results of the initial assessment, the server generates instructions regarding the next steps the user should take (e.g., recommending a detailed examination) and provides them to the user via the head-mounted display device.

[0327] Input: Primary judgment result

[0328] Output: Instructions for next steps

[0329] 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.

[0330] The present invention combines a system in which users collect samples themselves and provide rapid and highly accurate initial results through AI analysis with an emotion engine that recognizes the user's emotions. The present invention aims to improve the quality of the testing experience by enabling appropriate responses and follow-ups based on the user's emotional state. Specific embodiments of the present invention are described below.

[0331] Test kit request

[0332] User:

[0333] Users log in to a dedicated web or mobile application, request a test kit from the menu, and enter the required information (name, address, contact information, and questions about their health status).

[0334] Device:

[0335] The terminal validates the information entered by the user to ensure there are no missing or incorrect information. If the request is correct, it sends the input to the server. If the transmission is successful, a confirmation message is displayed to the user.

[0336] server:

[0337] The server receives the request data from the user and stores it in a database. It prepares the test kit and arranges for it to be sent to the user's address. It generates a tracking number and notifies the terminal.

[0338] Sample collection and shipping

[0339] User:

[0340] The user receives the test kit and collects the sample according to the instructions in the kit (e.g., for blood samples, use a special lancet), places the sample in the designated return envelope, and sends it to the lab.

[0341] Device:

[0342] The device provides an interface for users to record information about the collected specimen (collection date and time, specimen type, etc.), and supports the specimen sending procedure within the app.

[0343] Sample analysis and initial determination

[0344] server:

[0345] The server receives a notification of sample receipt from the laboratory, updates the database with the receipt information, notifies the user that the sample has arrived, and then sends the sample information to the analyzer to begin analysis.

[0346] Analysis equipment:

[0347] The analyzer analyzes the received sample and generates the results, which are then sent to the server.

[0348] server:

[0349] The server inputs the received analysis data into the AI ​​model, which then analyzes the image of the sample. The AI ​​model then generates a primary judgment result based on the sample test results.

[0350] AI model:

[0351] The AI ​​model generates analysis results and sends them back to the server.

[0352] Emotion engine response and notification

[0353] server:

[0354] The server receives the analysis results from the AI ​​model and generates a primary judgment result. Next, it uses an emotion engine to recognize the user's emotional state. The emotion engine analyzes behavioral data (facial expressions, operation timing, voice, etc.) when the user uses the app to determine the user's emotional state. Based on this emotional information, the content and method of notification messages are adjusted.

[0355] Device:

[0356] The device notifies the user of the initial assessment results and instructions for the next step. Based on the analysis results of the emotion engine, the device notifies the user in a gentle manner so as not to cause stress to the user. If necessary, the device also provides follow-up notifications and emotionally sensitive health advice.

[0357] Specific examples

[0358] 1. Execute the request:

[0359] A user requests a test kit and the information is sent to the server, which dispatches the kit and notifies the user.

[0360] 2. Sample collection and shipping:

[0361] The user receives the test kit, collects a blood sample, and sends it to the laboratory, which receives the sample and sends it to the analyzer.

[0362] 3. Analysis and Notification:

[0363] The AI ​​model analyzes the sample and generates a preliminary assessment. Based on this assessment, the emotion engine analyzes the user's emotional state and creates an appropriate notification message. The device then notifies the user of this message and the next steps.

[0364] 4. Follow-up:

[0365] If necessary, provide users with additional follow-up notifications and empathetic health advice.

[0366] This allows users to conveniently collect samples from the comfort of their own home and receive a quick and accurate initial result. Furthermore, the combination of an emotion engine enables appropriate responses based on the user's emotional state, improving the overall quality of the testing experience.

[0367] The processing flow will be explained below.

[0368] Step 1:

[0369] User:

[0370] Users launch the HELPO app and log in to their account. They then select "Apply for a Test Kit" from the menu and follow the instructions to enter the required information (name, address, contact information, and health status questions).

[0371] Step 2:

[0372] Device:

[0373] The terminal verifies the information entered by the user to check for omissions or errors. When the send request button is pressed, the input details are sent to the server. If the transmission is successful, a confirmation message is displayed to the user.

[0374] Step 3:

[0375] server:

[0376] The server receives the request data from the user and stores it in a database. It then prepares the test kit and sends it to the user's address. Once the delivery arrangements are complete, it generates a tracking number to track the delivery status and notifies the terminal.

[0377] Step 4:

[0378] Device:

[0379] The terminal will display information to the user, including a tracking number, and notify them of the expected arrival date of the test kit.

[0380] Step 5:

[0381] User:

[0382] Users receive a test kit and collect a sample (either blood, urine, or saliva) according to the instructions enclosed with the kit. The collected sample is placed in a designated return envelope and mailed to the lab.

[0383] Step 6:

[0384] Device:

[0385] The device provides an interface for users to record information about the collected specimen (collection date and time, specimen type, etc.), and the app also guides users through the process of sending the specimen to a laboratory.

[0386] Step 7:

[0387] server:

[0388] The server receives a notification of sample receipt from the laboratory, confirms that the laboratory has received the sample, updates the database with that information, and notifies the terminal.

[0389] Step 8:

[0390] Device:

[0391] The device will notify the user via push notification or email that the sample has arrived at the lab.

[0392] Step 9:

[0393] server:

[0394] The server sends the sample information to the analysis device and starts the analysis. After receiving the sample analysis results, it inputs them into the AI ​​model and performs additional analysis.

[0395] Step 10:

[0396] AI model:

[0397] The AI ​​model analyzes the images of the specimens, assessing the presence or absence of cancer-related markers and abnormalities, and generates analysis results that are sent back to the server.

[0398] Step 11:

[0399] server:

[0400] The server generates a preliminary judgment result using the analysis results received from the AI ​​model, and simultaneously uses an emotion engine to recognize the user's emotions and adjust notification messages based on the user's emotional state.

[0401] Step 12:

[0402] Emotion Engine:

[0403] The emotion engine determines emotions based on behavioral data (facial expressions, operation timing, voice, etc.) when the user uses the app, and provides this information to the server to optimize the content of notification messages.

[0404] Step 13:

[0405] server:

[0406] Based on the information from the emotion engine, the server creates a primary judgment result and instructions for the next step using expressions to reduce the user's stress, and sends them to the terminal.

[0407] Step 14:

[0408] Device:

[0409] The device notifies the user of the results of the initial assessment and instructions on next steps, with the content of the notification optimized according to the user's emotional state.

[0410] Step 15:

[0411] User:

[0412] The user checks the notified initial assessment results and next steps and takes the necessary action. For example, if a detailed examination is recommended, the user can make an appointment. The device also provides support during this process.

[0413] Step 16:

[0414] server:

[0415] If necessary, the system will send users additional follow-up notifications and provide health advice, allowing them to continually manage their health.

[0416] Example 2

[0417] 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."

[0418] In conventional sample analysis systems, the process of users collecting samples and sending them to a laboratory is time-consuming, and it often takes a long time for results to be notified. Furthermore, because feedback and responses do not take into account the user's emotional state, users may feel stressed or anxious when receiving their test results. The present invention aims to solve these problems and provide fast and accurate sample analysis and responses that take into account the user's emotional state.

[0419] 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.

[0420] In this invention, the server includes means for a user to request a kit for collecting a sample themselves, means for the user to collect the sample and send it, a testing device for analyzing the sample after receiving it, means for analyzing the analysis results using an AI model and generating a primary determination result, means for using an emotion engine that recognizes the user's emotional state and adjusts the content and method of a notification message, and means for notifying the user of the primary determination result and instructions regarding the next step. This allows the user to receive a primary determination of their sample quickly and accurately from the comfort of their own home, and the emotion engine provides an appropriate response, thereby reducing stress and anxiety when receiving the test results.

[0421] "User" refers to the entity that uses this system to collect specimens and receive analysis results.

[0422] "Specimen" refers to the biological material (e.g., blood, saliva, etc.) to be analyzed.

[0423] "Means for requesting a kit" refers to the functionality that allows a user to order a specimen collection kit using a dedicated application.

[0424] "Means of sending" refers to the mechanism by which the user sends the collected specimen to the laboratory (e.g., return envelope, sending confirmation function).

[0425] "Laboratory equipment" refers to the equipment and software used to analyze samples sent to a laboratory and generate results.

[0426] "AI model" refers to an artificial intelligence algorithm that analyzes samples and generates initial judgment results based on data obtained from an analytical device.

[0427] "Emotion engine" refers to a function that analyzes user behavior data (e.g., facial expressions, operation timing, voice, etc.) and determines the user's emotional state.

[0428] "Means for analyzing a sample" refers to the entire process of receiving a sample and performing analysis using a testing device.

[0429] "Means for generating a preliminary judgment result" refers to the process of outputting a preliminary test result based on data analyzed by an AI model.

[0430] "Means for adjusting the content and method of notification messages" refers to a mechanism for optimizing the expression of notification messages and notification methods according to the user's emotional state determined by the emotion engine.

[0431] "Means for providing instructions regarding next steps" refers to a function that informs the user of future actions to be taken or the need for additional testing based on the initial assessment results.

[0432] The present invention combines a system in which users collect samples themselves and provide rapid and highly accurate initial results through AI analysis, with an emotion engine that recognizes the user's emotions. Specific embodiments of this system are described below.

[0433] Test kit request

[0434] User

[0435] Users log in to the dedicated web or mobile application, click the "Request a Test Kit" button from the menu, and enter the required information (name, address, contact information, and questions about their health status).

[0436] Terminal

[0437] The device verifies the information entered by the user in real time. For example, it checks to make sure the address field is not empty, the phone number is not invalid, etc. If there are no missing or incorrect information, it sends the input details to the server as an HTTP POST request. If the transmission is successful, it displays a confirmation message to the user saying "Request accepted."

[0438] server

[0439] The server receives the request data from the user and saves it in a database. It inserts it into the database using an SQL query, and if successful, prepares the test kit. It then initiates the shipping process for the test kit and generates a tracking number. It then includes this tracking number in the HTTP response to notify the user's device.

[0440] Sample collection and shipping

[0441] User

[0442] The user receives the test kit and collects the sample according to the manual included with the kit. For example, for blood samples, a special lancet is used to collect a small amount of blood from the fingertip. The collected sample is then placed in a special container. Next, the user places the collected sample in the return envelope provided and sends it to the lab. After sending it, the user presses the "Sample sent" button in the app.

[0443] Terminal

[0444] The terminal provides an interface for recording the user's sending procedures. For example, when the send button is pressed, the collection date and time and type of specimen are recorded in the database. If the sending confirmation is successful, a notification "Specimen sending has been completed" is displayed to the user.

[0445] Sample analysis and initial determination

[0446] server

[0447] The server receives a notification of sample receipt from the lab. This notification is typically sent to the server via an HTTP POST request. The server records the receipt information in a database and notifies the user that the sample has arrived. The server then sends the sample information received from the lab to the analyzer, which then begins analysis.

[0448] analysis device

[0449] The analyzer analyzes the received sample and generates the results. For example, in the case of a blood sample, it uses equipment to detect specific markers in the blood. The resulting data is sent to the server in CSV or JSON format.

[0450] server

[0451] After receiving the analysis results, the server inputs the data into the AI ​​model, for example, by sending the analysis results to the AI ​​model as an HTTP POST request.

[0452] AI model

[0453] The AI ​​model generates a preliminary assessment result based on the analysis results. For example, an image recognition model is used to detect abnormal cells in the blood. Once the preliminary assessment result is generated, it is sent back to the server.

[0454] server

[0455] The server receives the initial judgment results from the AI ​​model, stores them in a database, and prepares to notify the user.

[0456] Emotion engine response and notification

[0457] server

[0458] The server calls the emotion engine and collects data to determine the user's emotional state. For example, facial expression data and operation timing when the user uses the app are acquired from cameras and sensors and input into the emotion engine. The emotion engine analyzes this data and determines the user's emotional state (e.g., tension, relief, stress, etc.).

[0459] Terminal

[0460] The device notifies the user of the initial results and instructions for the next step. For example, it may say, "The test results show an abnormality. Please consult your doctor for details." The wording of the notification is adjusted based on the analysis results of the emotion engine to avoid stressing the user. If necessary, the device may provide follow-up notifications or emotionally sensitive health advice.

[0461] Specific examples

[0462] 1. Executing the request

[0463] The user logs in to the application and requests a test kit. The terminal sends the request to the server, which then dispatches the kit and sends a tracking number to the terminal. The terminal then displays a confirmation message.

[0464] 2. Sample collection and shipping

[0465] The user collects a blood sample using the test kit and sends it to the lab in a return envelope. The terminal records the sending procedure and displays a notification of completion.

[0466] 3. Analysis and Notification

[0467] The server receives a receipt from the lab and sends the sample information to the analyzer. The analyzer sends the results to the server, which inputs them into the AI ​​model. The AI ​​model generates a preliminary judgment result and sends it back to the server. The server uses an emotion engine to determine the user's emotional state and creates an appropriate notification. The device displays the notification.

[0468] 4. Follow-up

[0469] If necessary, the server will send the user additional follow-up notifications and health advice, which the device will display and prompt the user to take appropriate action.

[0470] Prompt Sentence Examples

[0471] Here are some example prompts to input to a generative AI model:

[0472] The server dispatches the test kit requested by the user. A tracking number is assigned to the test kit and notified to the user. The user then receives the test kit, collects a blood sample according to the specified procedure, and sends it to the lab. The lab receives the sample, analyzes it, and sends the results to the server. The server uses an AI model to generate a preliminary assessment result and an emotion engine to analyze the user's emotional state and create an appropriate notification message.

[0473] This system allows users to easily collect samples from the comfort of their own home and receive a rapid, highly accurate initial result. Furthermore, the combination of an emotion engine enables appropriate responses based on the user's emotional state, improving the overall quality of the testing experience.

[0474] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0475] Step 1:

[0476] User:

[0477] Users log in to a dedicated web or mobile application, click the "Request a Test Kit" button from the menu, and then enter the required information, such as name, address, contact information, and health questions. This data serves as input for the next processing step.

[0478] Step 2:

[0479] Device:

[0480] The terminal verifies the information entered by the user in real time. For example, it checks to see if the address field is empty or if an invalid phone number has been entered. This ensures the accuracy of the data. The verified data is sent as input to the next process. If there are no omissions or errors, it is sent to the server as an HTTP POST request. If the transmission is successful, a confirmation message "Request accepted" is displayed to the user. This message becomes the output.

[0481] Step 3:

[0482] server:

[0483] The server receives the request data from the user. To save the input data in a database, it generates an SQL query and inserts it into the database. If the database insertion is successful, it begins preparing the test kit. Next, it carries out shipping procedures and generates a tracking number. It includes the generated tracking number in an HTTP response and sends it to the user's device. This tracking number becomes the output.

[0484] Step 4:

[0485] User:

[0486] The user receives the test kit and collects the sample according to the manual included in the kit. Specifically, for blood samples, a special lancet is used to collect a small amount of blood from the fingertip. The collected sample is then placed in a special container. This sample becomes the input for the next step.

[0487] Step 5:

[0488] User:

[0489] The user places the collected sample in the return envelope provided and sends it to the lab. The lab's address is pre-printed on the return envelope, so no additional information is required. The sent sample will be used as input for the next step. After sending the sample, press the "Sample sent" button in the app.

[0490] Step 6:

[0491] Device:

[0492] The terminal provides an interface for recording the user's sending procedure. This interface receives data such as the collection date and time and the type of specimen as input and records it in a database. If the sending confirmation is successful, a notification stating "Specimen sending completed" is displayed to the user as output.

[0493] Step 7:

[0494] server:

[0495] The server receives a sample receipt notification from the laboratory. The notification from the laboratory is sent to the server via an HTTP POST request. This receipt information is recorded in a database and the user is notified that the sample has arrived. To send the received sample information to the analyzer, an HTTP request is generated to send data to the analyzer. The output of this process is the sample information sent to the analyzer.

[0496] Step 8:

[0497] Analysis equipment:

[0498] The analyzer analyzes the received sample and generates the results. For example, in the case of a blood sample, it uses equipment to detect specific markers. The analysis results are sent to the server in CSV or JSON format. These analysis results are the output.

[0499] Step 9:

[0500] server:

[0501] The server receives the analysis results and inputs the data into the AI ​​model. It sends the analysis results to the AI ​​model as an HTTP POST request. The input for the AI ​​model includes this analysis data.

[0502] Step 10:

[0503] AI model:

[0504] The AI ​​model generates a primary judgment result based on the analysis results. For example, an image recognition model is used to detect abnormal cells in the blood. Once the primary judgment result is generated, it is sent back to the server. This primary judgment result becomes the output.

[0505] Step 11:

[0506] server:

[0507] The server receives the initial judgment results from the AI ​​model and stores them in a database. Next, it calls the emotion engine and collects data to determine the user's emotional state. For example, it uses a camera or sensor to acquire facial expression data and operation timing, and inputs this data into the emotion engine. The emotional state data generated by this analysis is the output.

[0508] Step 12:

[0509] server:

[0510] The server adjusts the content and format of the notification message based on the analysis results of the emotion engine. For example, it creates a notification using gentler language so that the user does not feel stressed. The adjusted notification message is sent to the device. The adjusted notification message becomes the output.

[0511] Step 13:

[0512] Device:

[0513] The device notifies the user of the initial assessment results and instructions for the next step. Based on the analysis results of the emotion engine, the device displays notifications tailored to prevent the user from feeling stressed. If necessary, it provides follow-up notifications and emotionally sensitive health advice. This notification is the output.

[0514] (Application example 2)

[0515] 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."

[0516] Conventional sample analysis systems are unable to respond to the user's emotional state between the time the user collects the sample and the time they receive the analysis results, resulting in an unsatisfactory user experience. Food delivery services, in particular, require services that take the user's emotional state into consideration, but lack mechanisms for addressing this. Therefore, it is necessary to improve the quality of service by analyzing the user's emotional state and providing appropriate responses and follow-up.

[0517] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0518] In this invention, the server includes: means for a user to request a device for collecting a sample themselves; means for the user to collect and send the sample; an analysis device for analyzing the sample after receiving the sample; means for analyzing the analysis result using a generative AI model and generating a primary determination result; means for notifying the user of the primary determination result; means including an emotion engine for analyzing the user's emotional state and providing responses and instructions according to the emotion; and means for providing instructions regarding the next step. This enables the provision of services according to the user's emotional state, improving the user experience.

[0519] A "user" is an individual who utilizes the system to collect specimens and receive analytical results.

[0520] A "specimen" is a biological sample that a user collects and sends for analysis.

[0521] "Equipment" refers to the tools and equipment required by the user to collect a specimen.

[0522] "Requesting means" is the ability for a user to request an instrument for collecting a specimen.

[0523] "Means for sending" is a function that allows the user to send the collected specimen to a specified location.

[0524] An "analytical device" is a device for analyzing a sample and generating a result.

[0525] A "generative AI model" is an artificial intelligence model that generates a primary judgment result based on the analysis results.

[0526] The "primary judgment result" is the first analytical evaluation derived by the generative AI model.

[0527] The "notification means" is a function for notifying the user of the primary judgment result.

[0528] An "emotion engine" is a system that analyzes the user's emotional state and responds or gives instructions based on that data.

[0529] The "instructions regarding the next step" are instructions indicating the specific action to be taken next based on the results of the primary determination and the user's emotional state.

[0530] A "food delivery service" is a service that delivers food to a location specified by the user.

[0531] This invention combines a system in which users collect samples at home and provide rapid and highly accurate initial results through analysis by a generative AI model with an emotion engine that recognizes the user's emotional state. This system aims to improve the quality of the service experience by enabling appropriate responses and follow-ups according to the user's emotional state.

[0532] User

[0533] User Registration and Ordering

[0534] Users log in to a dedicated food delivery app and search for their favorite meal. The app uses the built-in camera and microphone to capture the user's facial recognition and voice data, which is then analyzed by an emotion engine to understand the user's emotional state.

[0535] server

[0536] Executing the request

[0537] The server receives the user's request for the specimen collection equipment, verifies the accuracy of the request, and then ships the specimen collection equipment to the user's address, generates a tracking number, and notifies the terminal.

[0538] Sample analysis

[0539] After receiving the sample from the lab, the server updates the sample information in the database and notifies the user that the sample has arrived. The server then sends the sample information to the analyzer to begin analysis. The analysis results are then input into the AI ​​model to generate a preliminary judgment result.

[0540] Emotional state analysis

[0541] The emotion engine on the server analyzes the user's emotional state based on facial recognition and voice data when using the app. This emotional information is then analyzed using a language processing model to create an appropriate message.

[0542] Terminal

[0543] Order Support and Notifications

[0544] The device receives the analysis results and notifies the user. Based on the analysis results from the emotion engine, the device provides a notification message and instructions on the next step in a gentle manner that reflects the user's emotional state. The device provides real-time delivery tracking information and a message that is sensitive to the user's emotions.

[0545] Adding specific examples

[0546] For example, when a user places an order using the app, if the emotion is recognized as "sad," the app will suggest hot soup or comfort food. Along with the suggested menu, a message such as "You're feeling a little blue today. Warm your body and soul with hot soup or comfort food!" will be displayed.

[0547] Prompt Sentence Examples

[0548] A concrete example of a prompt input to a generative AI model might be the following text:

[0549] What foods should you suggest for users when they are feeling very busy and stressed?

[0550] Such a system allows services to be provided according to the user's emotional state, improving the user experience.

[0551] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0552] Step 1:

[0553] User Registration and Sample Collection Equipment Request

[0554] The user logs into the dedicated app and inputs the necessary information (name, address, contact details, health status) to request sample collection equipment. The server receives the input data and verifies the information. If there are no omissions or errors, the request details are saved in the database and the sample collection equipment is shipped. A tracking number is generated and sent to the device.

[0555] Input: User registration information and request data

[0556] Output: Stores accurate request data and generates tracking numbers

[0557] Specific operations: Validation and storage process, generation of tracking number, notification

[0558] Step 2:

[0559] Sample collection and shipping

[0560] The user collects a specimen (e.g., a blood sample) using the specimen collection device they received. They then place the collected specimen in a designated return envelope and send it to the laboratory. The terminal records information such as the specimen collection date and time and type, and sends it to the server.

[0561] Input: Sample collection information (date, time, type)

[0562] Output: Send sample information to the server

[0563] Specific actions: Collecting samples, recording and transmitting information

[0564] Step 3:

[0565] Receipt of samples and initiation of analysis

[0566] The server receives a notification of sample receipt from the laboratory, updates the database, and then sends the sample information to the analyzer to start analysis.

[0567] Input: Specimen receipt notice from lab

[0568] Output: Instructions to update the database and start analysis

[0569] Specific operations: Database update, sending instruction to start analysis

[0570] Step 4:

[0571] Analysis and generation of initial judgment results

[0572] The analysis device analyzes the received sample and generates result data. The result data is sent to the server and input into the generative AI model. The AI ​​model analyzes the image of the sample and generates a primary judgment result. The server receives this result and stores it in a database.

[0573] Input: Sample analysis result data

[0574] Output: Generate and save the first judgment result

[0575] Specific operations: Running the analysis device, generating and sending data, analyzing it using an AI model, and saving the results

[0576] Step 5:

[0577] Sentiment analysis and follow-up with emotion engine

[0578] The device acquires the user's facial recognition and voice data and analyzes it with an emotion engine. The emotion engine determines the user's emotional state and sends it to the server. The server uses this information to create a notification message in a gentle manner according to the initial assessment result, and also provides instructions on the next step.

[0579] Input: User's facial recognition and voice data

[0580] Output: Sentiment analysis results and a soft-spoken message

[0581] Specific operations: facial recognition and voice data acquisition, emotion analysis, message generation

[0582] Step 6:

[0583] Delivery tracking and notifications

[0584] The server tracks the delivery status and sends real-time notifications to the device, including messages to reduce the stress felt by the user based on the analysis results of the emotion engine.

[0585] Input: Delivery status data

[0586] Output: Real-time delivery status notification

[0587] Specific behavior: Tracking delivery status, generating and sending notification messages

[0588] Step 7:

[0589] Delivery completion and feedback

[0590] The user receives the food and rates it within the app. The device analyzes the user's rating and emotional state and sends the results to the server, which uses the information to improve the service in the future.

[0591] Input: User ratings and emotional state data

[0592] Output: Data for service improvement

[0593] Specific actions: getting and sending feedback, analyzing and storing data

[0594] 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.

[0595] 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.

[0596] 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.

[0597] [Second embodiment]

[0598] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0599] 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.

[0600] 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).

[0601] 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.

[0602] 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.

[0603] 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).

[0604] 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.

[0605] 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.

[0606] 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.

[0607] 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.

[0608] 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.

[0609] 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."

[0610] The present invention relates to a system that allows users to collect samples themselves and provides rapid and highly accurate primary determination results through AI analysis. Specific embodiments of the present invention are described below.

[0611] Test kit request

[0612] User:

[0613] Users log in to a dedicated web or mobile application and request a test kit from the menu, answering questions about their name, address, contact information, and health status.

[0614] Device:

[0615] The terminal verifies the information entered by the user to ensure there are no omissions or errors. Once verification is complete, the user presses the send request button to send the input details to the server.

[0616] server:

[0617] The server receives the request data from the user and stores it in a database. At the same time, it prepares the test kit and begins the process of sending it to the user's address. Once the process is complete, it generates a tracking number to track the delivery status and returns that information to the terminal.

[0618] Sample collection and shipping

[0619] User:

[0620] Users receive the test kit at home and follow the instructions in the kit to collect a sample. For example, for a blood test, users use a special lancet to collect blood from their fingertip. The collected sample is then placed in the enclosed return envelope and sent to the designated lab.

[0621] Device:

[0622] The device provides an interface for users to record information about the collected specimen (collection date, type, etc.), and the app also guides users through the process of properly packaging the specimen and mailing it to the lab.

[0623] Sample analysis and initial determination

[0624] server:

[0625] When the laboratory receives the sample, it notifies the server, which updates the database and notifies the user that the sample has been received, and then sends the information to the analyzer to begin analyzing the sample.

[0626] Analysis equipment:

[0627] The analysis device analyzes the received sample and generates the results, which are then sent back to the server.

[0628] server:

[0629] The server inputs the received analysis data into the AI ​​model, which then analyzes the images of the specimens. The AI ​​model aggregates the results of multiple specimen tests and evaluates the presence or absence of cancer-related markers.

[0630] AI model:

[0631] The AI ​​model generates a preliminary judgment result based on the sample analysis results, which is then sent back to the server.

[0632] Notification of initial assessment results and next steps

[0633] server:

[0634] The server receives the initial assessment results sent by the AI ​​model and notifies the user of the results, as well as providing instructions on the next steps the user should take (e.g., recommending further testing).

[0635] Device:

[0636] The device will notify the user of the initial assessment results and instructions on next steps via in-app push notification or email, where the user can review the details.

[0637] User:

[0638] The user takes the necessary action based on the notified initial assessment result and the next step. For example, if a detailed examination is required, the user makes an appointment.

[0639] This allows users to easily collect samples from the comfort of their own home and receive a rapid and accurate primary diagnosis of cancer.The present invention provides a system that improves the quality control and analytical accuracy of samples and effectively monitors the health status of users.

[0640] The processing flow will be explained below.

[0641] Step 1:

[0642] User:

[0643] Users launch the HELPO app and log in to their account. They then select "Apply for a Test Kit" from the menu and follow the instructions to enter the required information (name, address, contact information, and health status questions).

[0644] Step 2:

[0645] Device:

[0646] The terminal validates the information entered by the user, checking for missing or incorrect data, and when the send request button is pressed, sends the contents to the server. If the transmission is successful, a confirmation message is displayed to the user.

[0647] Step 3:

[0648] server:

[0649] The server receives the request data from the user and stores it in a database. It then prepares the test kit and arranges for it to be sent to the user's address. Once the delivery arrangements are complete, it generates a tracking number to track the delivery status and sends it to the terminal.

[0650] Step 4:

[0651] Device:

[0652] The terminal will display information to the user, including a tracking number, and notify them of the expected arrival date of the test kit.

[0653] Step 5:

[0654] User:

[0655] Users receive a test kit and follow the instructions in the kit to collect a sample (either blood, urine, or saliva), then place the sample in a designated return envelope and mail it to the lab.

[0656] Step 6:

[0657] Device:

[0658] The device provides an interface for users to record information about the collected specimen (collection date and time, specimen type, etc.), and the app also guides users through the process of sending the specimen to a laboratory.

[0659] Step 7:

[0660] server:

[0661] The server receives a notification of sample receipt from the laboratory, confirms that the laboratory has received the sample, updates the database with that information, and notifies the terminal.

[0662] Step 8:

[0663] Device:

[0664] The device will notify the user via push notification or email that the sample has arrived at the lab.

[0665] Step 9:

[0666] server:

[0667] The server sends the sample information to the analysis device and starts the analysis. The received analysis results are input into the AI ​​model and the analysis is carried out.

[0668] Step 10:

[0669] AI model:

[0670] The AI ​​model analyzes the images of the specimens, assessing the presence or absence of cancer-related markers and abnormalities, and generates analysis results that are sent back to the server.

[0671] Step 11:

[0672] server:

[0673] The server receives the analysis results from the AI ​​model, generates a preliminary judgment based on the results, and creates instructions for the next steps and sends them to the device.

[0674] Step 12:

[0675] Device:

[0676] The device will notify the user of the initial results and instructions for next steps. The user will receive detailed results via in-app notifications or email.

[0677] Step 13:

[0678] User:

[0679] The user checks the notified primary assessment result and follows the instructions for the next step, making an appointment for a detailed examination if necessary.

[0680] The above are the specific processing steps and their details of the system. This process allows users to receive a simple and highly accurate primary cancer diagnosis from the comfort of their own home.

[0681] Example 1

[0682] 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."

[0683] In the prior art, when a user collects a sample themselves and has it analyzed at a specialized institution, it is difficult to obtain a rapid and accurate determination result. Furthermore, there are challenges in controlling the quality of the sample and improving the accuracy of the analysis results. Furthermore, specific instructions regarding the next steps the user should take are not provided, which may delay appropriate action. The present invention aims to solve these problems and provide a system that allows a user to easily collect a sample from home and obtain a rapid and accurate initial determination result.

[0684] 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.

[0685] In this invention, the server includes means for a user to request a kit for collecting a specimen themselves, means for a terminal to verify information entered by the user and send it to the server, means for the server to store the received information in a database and ship a test kit, a testing device for analyzing the specimen after receiving it, means for generating analysis results and sending the data to the server, means for the server to input the analysis data into an AI model and generate a primary determination result, means for notifying the user of the primary determination result, and means for providing instructions regarding the next step. This enables the user to obtain a primary determination result quickly and accurately.

[0686] "User" refers to an individual who uses the system to collect specimens and receive analytical results.

[0687] A "specimen" refers to a biological substance such as blood, urine, or saliva that is collected by the user and subjected to testing.

[0688] "Kit" refers to a set containing tools that a user can use to collect a specimen themselves.

[0689] "Terminal" refers to an information processing device used by a user, such as a computer, smartphone, or tablet.

[0690] "Server" refers to the central processing unit that receives requests from users, processes and stores data, and returns results to users.

[0691] A "database" refers to a system that allows a server to efficiently store, manage, and search information.

[0692] "Testing device" refers to a device that analyzes received specimens and generates result data.

[0693] "AI model" refers to software that includes algorithms for using artificial intelligence to analyze data and generate initial assessment results.

[0694] "Primary assessment result" refers to the initial analysis result generated by the AI ​​model and refers to the evaluation information provided to the user.

[0695] "Instructions" refers to guidance or recommendations regarding the next action a user should take after receiving the initial assessment results.

[0696] This invention relates to a system that allows users to collect samples themselves and provides rapid and highly accurate initial results through analysis by an AI model. This system consists of multiple components, including users, terminals, and servers.

[0697] Test kit request

[0698] User:

[0699] Users log in to a dedicated web or mobile application and request a test kit from the menu, answering questions about their name, address, contact information, and health status.

[0700] Device:

[0701] The terminal validates the information entered by the user to ensure there are no missing or incorrect information. For example, it uses form validation to check that address fields are not blank and that phone numbers are entered in the correct format. Once the validation is complete, the user presses the send button to send the input information to the server.

[0702] server:

[0703] The server receives the request data from the user and stores that information in a database. For example, MySQL or PostgreSQL is used for the database. The server also initiates the procedure for shipping the test kit and requests the shipping company to ship the kit. At this time, the server generates a tracking number to track the delivery status and returns that information to the terminal.

[0704] Sample collection and shipping

[0705] User:

[0706] Users receive the test kit at home and collect the sample according to the instructions included in the kit. For example, for a blood test, a special lancet is used to collect blood from the fingertip. The collected sample is placed in the enclosed return envelope and sent to the designated lab. The user then records the date and time of collection and the type of sample in the application.

[0707] Device:

[0708] The terminal records the collection information entered by the user and stores it in a database. The terminal also displays a screen that guides the user through the process of safely packaging the specimen and sending it to the lab.

[0709] Sample analysis and initial determination

[0710] server:

[0711] When the laboratory receives the specimen, it notifies the server, which updates the database and notifies the user that the specimen has been received, and then the server sends the information to the analyzer to begin analyzing the specimen.

[0712] Analysis equipment:

[0713] The analysis device analyzes the received sample and generates result data, for example, using a spectrophotometer or flow cytometer, and the analysis result data is sent back to the server.

[0714] server:

[0715] The server inputs the received analysis data into a generative AI model, which is built using TensorFlow or PyTorch, for example. The AI ​​model generates a primary judgment result based on the sample analysis results and returns the result to the server.

[0716] Notification of initial assessment results and next steps

[0717] server:

[0718] The server receives the initial assessment results sent by the AI ​​model and notifies the user of the results, along with instructions on what next steps to take (e.g., recommending further testing).

[0719] Device:

[0720] The device will notify the user with the initial assessment results and instructions on next steps via an in-app push notification or email, and the user can open the app for more details.

[0721] User:

[0722] The user takes the necessary action based on the notified primary assessment result and the next step. For example, if a detailed examination is required, the user makes an appointment.

[0723] Prompt Sentence Examples

[0724] "Please generate a preliminary AI result based on the analysis results of the sample I provide. Please write a sentence in natural language that explains the entire process from requesting a test kit to receiving the results."

[0725] This allows users to easily collect samples from the comfort of their own home and receive a rapid and highly accurate initial diagnosis. This system improves the quality control and analysis accuracy of samples, enabling effective monitoring of users' health conditions.

[0726] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0727] Step 1:

[0728] User:

[0729] Log in to the dedicated web application or mobile application. The information required for logging in is your user ID and password. Once you have successfully logged in, your user dashboard will be displayed.

[0730] input:

[0731] User ID and password

[0732] output:

[0733] Login success message, dashboard display

[0734] Specific behavior:

[0735] A user opens the app, enters their user ID and password on the login screen, and clicks the "Login" button. The system verifies the authentication information, and if it is correct, the dashboard is displayed.

[0736] Step 2:

[0737] User:

[0738] Request a test kit: Users select the "Request a test kit" option from the menu and answer questions about their name, address, contact information, and health status.

[0739] input:

[0740] Name, address, contact information, and health status

[0741] output:

[0742] Request confirmation message and input details display screen

[0743] Specific behavior:

[0744] The user enters the required information on the "Request a Test Kit" screen and clicks the "Submit" button. A confirmation message for the entered information is displayed on the screen.

[0745] Step 3:

[0746] Device:

[0747] Validate user-entered information and format submitted data.

[0748] input:

[0749] User-provided name, address, contact information, and health status answers

[0750] output:

[0751] Verified data, data sent to server

[0752] Specific behavior:

[0753] The device checks the contents of the input fields, formats them as needed (e.g., checks if the address field is empty, verifies that the contact information is in the correct format), and prepares the data to be sent to the server.

[0754] Step 4:

[0755] server:

[0756] It receives the request data, stores the information in a database, and processes the shipping of the test kit.

[0757] input:

[0758] Request data sent from the device

[0759] output:

[0760] Request information and tracking number stored in the database

[0761] Specific behavior:

[0762] The server receives the request data and saves it in a database. Then, it requests the shipping company to ship the test kit via API. It receives a tracking number from the shipping company and returns it to the user.

[0763] Step 5:

[0764] User:

[0765] After receiving the test kit, collect the sample according to the instructions, place the collected sample in the return envelope, and send it to the designated laboratory.

[0766] input:

[0767] Test kit instructions, user samples

[0768] output:

[0769] Collected specimen and message of completion of sending

[0770] Specific behavior:

[0771] The user follows the instructions to collect a sample (e.g., using a lancet to collect blood from a fingertip), seals it in a return envelope, and then goes to the post office to mail it off to the lab.

[0772] Step 6:

[0773] server:

[0774] When the lab receives the sample, it receives a notification and updates the database with the information, which is then sent to the analyzer.

[0775] input:

[0776] Acknowledgment from the lab

[0777] output:

[0778] Database update information, data sent to analysis equipment

[0779] Specific behavior:

[0780] When the laboratory receives the sample, it notifies the server, which updates the database with the receipt information and sends an analysis request to the analyzer.

[0781] Step 7:

[0782] Analysis equipment:

[0783] The received samples are analyzed, and analysis result data is generated and sent to the server.

[0784] input:

[0785] Sample information sent to the analyzer

[0786] output:

[0787] Analysis result data

[0788] Specific behavior:

[0789] The analytical device analyzes the sample, generates the result data, and sends it to the server. For example, a spectrophotometer or flow cytometer is used.

[0790] Step 8:

[0791] server:

[0792] The received analysis data is input into the AI ​​model to generate a primary judgment result, which is then notified to the user.

[0793] input:

[0794] Analysis result data

[0795] output:

[0796] Primary judgment results, user notification data

[0797] Specific behavior:

[0798] The server sends the analysis results data to the AI ​​model, which generates a first-order judgment. The generation AI model uses pre-trained TensorFlow or PyTorch, and notifies the user of the result.

[0799] Step 9:

[0800] Device:

[0801] The user is notified of the initial assessment results and instructions regarding next steps.

[0802] input:

[0803] Initial assessment results and instructions on next steps

[0804] output:

[0805] Notification Message

[0806] Specific behavior:

[0807] The device will notify the user of the initial assessment results and next steps via in-app push notification or email.

[0808] Step 10:

[0809] User:

[0810] Respond according to the notified initial assessment result and next steps, for example, make an appointment for a detailed examination.

[0811] input:

[0812] Initial assessment results and instructions on next steps

[0813] output:

[0814] Detailed examination reservation information, etc.

[0815] Specific behavior:

[0816] The user confirms the notification and takes the necessary next steps (e.g., schedules an appointment for a detailed examination if necessary).

[0817] (Application example 1)

[0818] 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."

[0819] Conventional home sample collection and analysis systems lack sufficient support for users in the accurate sample collection process, resulting in issues with sample collection accuracy and adherence to procedures. Furthermore, methods for quickly and accurately notifying users of sample analysis results are limited, and clear guidance on how to proceed to the next step is lacking. To address these issues, a system is needed that allows users to intuitively and reliably collect samples and instantly receive analysis results.

[0820] 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.

[0821] In this invention, the server includes means for a user to request a kit for collecting a specimen by themselves, means for the user to collect and send the specimen, a testing device for analyzing the specimen after receiving the specimen, means for analyzing the analysis result using an AI model and generating a primary determination result, means for notifying the user of the primary determination result, means for providing instructions regarding the next step, means for the user to receive visual and audio guidance by wearing a head-mounted display device, and means for checking the user's specimen collection procedure in real time, thereby enabling the user to reliably collect a specimen and obtain a rapid and highly accurate analysis result.

[0822] "User" means an individual or organization that uses the system to collect specimens and receive analysis and notification of results.

[0823] A "kit for collecting specimens" is a set that includes tools and instructions that allow users to collect specimens safely and accurately themselves.

[0824] A "method of requesting a kit" is how a user places an order for a test kit through a web or mobile application.

[0825] "Means for sending specimens" refers to a method that provides procedures and tools for users to send collected specimens to a designated analysis laboratory.

[0826] A "test device" is a physical or chemical device that analyzes a received specimen and generates a result.

[0827] "AI Model" means the artificial intelligence algorithms and models used to generate a preliminary determination result based on the analysis of a received specimen.

[0828] The "means for generating a primary judgment result" is a method for using an AI model to summarize the analysis results of a sample as a primary evaluation.

[0829] The "means for notifying the user of the primary determination results" refers to a communication means or notification system for immediately notifying the user of the analysis results.

[0830] The "means for providing instructions regarding the next step" is a method for guiding the user on the next action or necessary response to be taken based on the results of the primary determination.

[0831] A "head-mounted display device" is a device that displays visual and audio information when worn by a user.

[0832] "Means for receiving visual and audio guidance" refers to a method in which the user is provided with visual and audio guidance via a head-mounted display to guide them through the sample collection procedure and delivery method.

[0833] "Means for verifying a user's sample collection procedures in real time" refers to a method for using a head-mounted display to monitor a user's procedures in real time and verify accuracy and compliance.

[0834] The present invention relates to a system that includes a series of processes in which a user collects a sample themselves and receives visual and audio guidance using a head-mounted display device. The system comprises the following steps:

[0835] First, a user wears a head-mounted display device with a dedicated application installed and requests a test kit. The user logs in to the application and follows the on-screen instructions to answer questions about their personal information and health status. This information is displayed visually through the head-mounted display, and a voice assistant guides the input. The server receives this information, processes the request, and delivers the test kit to the user's address.

[0836] Next, the user collects a sample at home using the provided test kit. The head-mounted display device provides step-by-step instructions visually and audibly. For example, for a blood test, the user is guided on how to use the lancet and properly collect the sample, with real-time confirmation of the procedure. Once the sample is collected, it is placed in the provided return envelope and sent to the designated analysis lab.

[0837] When the sample arrives at the lab, the information is sent to the server, which updates the information and notifies the user via a push notification on the head-mounted display that the sample has been received. The testing device then analyzes the sample and generates the results, which are then sent back to the server.

[0838] The server inputs the received analysis results into the generative AI model to generate a preliminary assessment result, which is then communicated to the user via a head-mounted display, where the user can check the results in real time and receive visual and audio instructions regarding next steps (e.g., recommending further testing).

[0839] (Hardware and Software Use)

[0840] A common device such as Oculus Quest 2 is used as the head-mounted display device. The VoiceAssistant library is used for the voice assistant, and the requests library is used for communication processing. The hmd_display library is used for display management. This allows users to intuitively follow prompts and smoothly carry out the process from sample collection to checking analysis results.

[0841] (Example)

[0842] When the user wears the head-mounted display device and gives a voice command such as "Hello, please tell me the procedure for sample collection," visual and voice guidance begins. Similarly, the system operates appropriately when the user gives voice commands following prompts such as "I would like to check the current test results" to send the sample and receive notification of the analysis results.

[0843] This allows users to collect samples easily and safely from the comfort of their own home and receive prompt and highly accurate initial results.

[0844] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0845] Step 1:

[0846] The user launches the application and requests a test kit.

[0847] Specific behavior:

[0848] The user wears a head-mounted display device and logs in to the application. Next, they follow the on-screen instructions to answer questions about their personal information and health status. This information is then sent to the server as input data.

[0849] Input: User information (name, address, health status, etc.)

[0850] Output: A request for a test kit is sent to the server.

[0851] Step 2:

[0852] The server receives and processes requests for test kits.

[0853] Specific behavior:

[0854] The server validates the received request data and stores it in a database. After checking for any missing or incorrect information, it initiates the shipping process for the test kit and obtains a tracking number from the delivery company. The tracking number is then returned to the user.

[0855] Input: Request data

[0856] Output: Tracking number is sent to the user

[0857] Step 3:

[0858] The user receives the test kit and collects the specimen.

[0859] Specific behavior:

[0860] The user opens the test kit and follows the visual and audio guidance on the head-mounted display device to collect a sample, such as using a lancet to draw blood from a fingertip. The user is then checked in real time during the process.

[0861] Input: Test kit, visual and audio guidance

[0862] Output: Collected specimen

[0863] Step 4:

[0864] The user sends the collected specimen.

[0865] Specific behavior:

[0866] The collected sample is placed in the enclosed return envelope and sent to the designated analysis lab, and the head-mounted display device provides visual and audio guidance on proper packaging and mailing instructions.

[0867] Input: Collected specimen, return envelope

[0868] Output: Specimen sent to the lab

[0869] Step 5:

[0870] The server confirms receipt of the specimen.

[0871] Specific behavior:

[0872] When the sample arrives at the lab, the information is sent to the server, which updates the information and sends a push notification to the user to let them know the sample has been received.

[0873] Input: Specimen receipt notice

[0874] Output: Acknowledgement to user

[0875] Step 6:

[0876] The testing device analyzes the sample and generates a result.

[0877] Specific behavior:

[0878] The testing device analyzes the sample received from the server and generates the result data, which is then sent back to the server.

[0879] Input: Sample

[0880] Output: Analysis result data

[0881] Step 7:

[0882] The server inputs the analysis results into the AI ​​model and generates a primary judgment result.

[0883] Specific behavior:

[0884] The server inputs the received analysis result data into the generative AI model to generate a primary judgment result, which is then sent back to the server.

[0885] Input: Analysis result data

[0886] Output: Primary judgment result

[0887] Step 8:

[0888] The server notifies the user of the results of the initial judgment.

[0889] Specific behavior:

[0890] The server notifies the user of the generated primary judgment result via the head-mounted display device. The user receives a push notification and can check the details.

[0891] Input: Primary judgment result

[0892] Output: User notification

[0893] Step 9:

[0894] The server provides instructions to the user regarding next steps.

[0895] Specific behavior:

[0896] Based on the results of the initial assessment, the server generates instructions regarding the next steps the user should take (e.g., recommending a detailed examination) and provides them to the user via the head-mounted display device.

[0897] Input: Primary judgment result

[0898] Output: Instructions for next steps

[0899] 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.

[0900] The present invention combines a system in which users collect samples themselves and provide rapid and highly accurate initial results through AI analysis with an emotion engine that recognizes the user's emotions. The present invention aims to improve the quality of the testing experience by enabling appropriate responses and follow-ups based on the user's emotional state. Specific embodiments of the present invention are described below.

[0901] Test kit request

[0902] User:

[0903] Users log in to a dedicated web or mobile application, request a test kit from the menu, and enter the required information (name, address, contact information, and questions about their health status).

[0904] Device:

[0905] The terminal validates the information entered by the user to ensure there are no missing or incorrect information. If the request is correct, it sends the input to the server. If the transmission is successful, a confirmation message is displayed to the user.

[0906] server:

[0907] The server receives the request data from the user and stores it in a database. It prepares the test kit and arranges for it to be sent to the user's address. It generates a tracking number and notifies the terminal.

[0908] Sample collection and shipping

[0909] User:

[0910] The user receives the test kit and collects the sample according to the instructions in the kit (e.g., for blood samples, use a special lancet), places the sample in the designated return envelope, and sends it to the lab.

[0911] Device:

[0912] The device provides an interface for users to record information about the collected specimen (collection date and time, specimen type, etc.), and supports the specimen sending procedure within the app.

[0913] Sample analysis and initial determination

[0914] server:

[0915] The server receives a notification of sample receipt from the laboratory, updates the database with the receipt information, notifies the user that the sample has arrived, and then sends the sample information to the analyzer to begin analysis.

[0916] Analysis equipment:

[0917] The analyzer analyzes the received sample and generates the results, which are then sent to the server.

[0918] server:

[0919] The server inputs the received analysis data into the AI ​​model, which then analyzes the image of the sample. The AI ​​model then generates a primary judgment result based on the sample test results.

[0920] AI model:

[0921] The AI ​​model generates analysis results and sends them back to the server.

[0922] Emotion engine response and notification

[0923] server:

[0924] The server receives the analysis results from the AI ​​model and generates a primary judgment result. Next, it uses an emotion engine to recognize the user's emotional state. The emotion engine analyzes behavioral data (facial expressions, operation timing, voice, etc.) when the user uses the app to determine the user's emotional state. Based on this emotional information, the content and method of notification messages are adjusted.

[0925] Device:

[0926] The device notifies the user of the initial assessment results and instructions for the next step. Based on the analysis results of the emotion engine, the device notifies the user in a gentle manner so as not to cause stress to the user. If necessary, the device also provides follow-up notifications and emotionally sensitive health advice.

[0927] Specific examples

[0928] 1. Execute the request:

[0929] A user requests a test kit and the information is sent to the server, which dispatches the kit and notifies the user.

[0930] 2. Sample collection and shipping:

[0931] The user receives the test kit, collects a blood sample, and sends it to the laboratory, which receives the sample and sends it to the analyzer.

[0932] 3. Analysis and Notification:

[0933] The AI ​​model analyzes the sample and generates a preliminary assessment. Based on this assessment, the emotion engine analyzes the user's emotional state and creates an appropriate notification message. The device then notifies the user of this message and the next steps.

[0934] 4. Follow-up:

[0935] If necessary, provide users with additional follow-up notifications and empathetic health advice.

[0936] This allows users to conveniently collect samples from the comfort of their own home and receive a quick and accurate initial result. Furthermore, the combination of an emotion engine enables appropriate responses based on the user's emotional state, improving the overall quality of the testing experience.

[0937] The processing flow will be explained below.

[0938] Step 1:

[0939] User:

[0940] Users launch the HELPO app and log in to their account. They then select "Apply for a Test Kit" from the menu and follow the instructions to enter the required information (name, address, contact information, and health status questions).

[0941] Step 2:

[0942] Device:

[0943] The terminal verifies the information entered by the user to check for omissions or errors. When the send request button is pressed, the input details are sent to the server. If the transmission is successful, a confirmation message is displayed to the user.

[0944] Step 3:

[0945] server:

[0946] The server receives the request data from the user and stores it in a database. It then prepares the test kit and sends it to the user's address. Once the delivery arrangements are complete, it generates a tracking number to track the delivery status and notifies the terminal.

[0947] Step 4:

[0948] Device:

[0949] The terminal will display information to the user, including a tracking number, and notify them of the expected arrival date of the test kit.

[0950] Step 5:

[0951] User:

[0952] Users receive a test kit and collect a sample (either blood, urine, or saliva) according to the instructions enclosed with the kit. The collected sample is placed in a designated return envelope and mailed to the lab.

[0953] Step 6:

[0954] Device:

[0955] The device provides an interface for users to record information about the collected specimen (collection date and time, specimen type, etc.), and the app also guides users through the process of sending the specimen to a laboratory.

[0956] Step 7:

[0957] server:

[0958] The server receives a notification of sample receipt from the laboratory, confirms that the laboratory has received the sample, updates the database with that information, and notifies the terminal.

[0959] Step 8:

[0960] Device:

[0961] The device will notify the user via push notification or email that the sample has arrived at the lab.

[0962] Step 9:

[0963] server:

[0964] The server sends the sample information to the analysis device and starts the analysis. After receiving the sample analysis results, it inputs them into the AI ​​model and performs additional analysis.

[0965] Step 10:

[0966] AI model:

[0967] The AI ​​model analyzes the images of the specimens, assessing the presence or absence of cancer-related markers and abnormalities, and generates analysis results that are sent back to the server.

[0968] Step 11:

[0969] server:

[0970] The server generates a preliminary judgment result using the analysis results received from the AI ​​model, and simultaneously uses an emotion engine to recognize the user's emotions and adjust notification messages based on the user's emotional state.

[0971] Step 12:

[0972] Emotion Engine:

[0973] The emotion engine determines emotions based on behavioral data (facial expressions, operation timing, voice, etc.) when the user uses the app, and provides this information to the server to optimize the content of notification messages.

[0974] Step 13:

[0975] server:

[0976] Based on the information from the emotion engine, the server creates a primary judgment result and instructions for the next step using expressions to reduce the user's stress, and sends them to the terminal.

[0977] Step 14:

[0978] Device:

[0979] The device notifies the user of the results of the initial assessment and instructions on next steps, with the content of the notification optimized according to the user's emotional state.

[0980] Step 15:

[0981] User:

[0982] The user checks the notified initial assessment results and next steps and takes the necessary action. For example, if a detailed examination is recommended, the user can make an appointment. The device also provides support during this process.

[0983] Step 16:

[0984] server:

[0985] If necessary, the system will send users additional follow-up notifications and provide health advice, allowing them to continually manage their health.

[0986] Example 2

[0987] 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."

[0988] In conventional sample analysis systems, the process of users collecting samples and sending them to a laboratory is time-consuming, and it often takes a long time for results to be notified. Furthermore, because feedback and responses do not take into account the user's emotional state, users may feel stressed or anxious when receiving their test results. The present invention aims to solve these problems and provide fast and accurate sample analysis and responses that take into account the user's emotional state.

[0989] 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.

[0990] In this invention, the server includes means for a user to request a kit for collecting a sample themselves, means for the user to collect the sample and send it, a testing device for analyzing the sample after receiving it, means for analyzing the analysis results using an AI model and generating a primary determination result, means for using an emotion engine that recognizes the user's emotional state and adjusts the content and method of a notification message, and means for notifying the user of the primary determination result and instructions regarding the next step. This allows the user to receive a primary determination of their sample quickly and accurately from the comfort of their own home, and the emotion engine provides an appropriate response, thereby reducing stress and anxiety when receiving the test results.

[0991] "User" refers to the entity that uses this system to collect specimens and receive analysis results.

[0992] "Specimen" refers to the biological material (e.g., blood, saliva, etc.) to be analyzed.

[0993] "Means for requesting a kit" refers to the functionality that allows a user to order a specimen collection kit using a dedicated application.

[0994] "Means of sending" refers to the mechanism by which the user sends the collected specimen to the laboratory (e.g., return envelope, sending confirmation function).

[0995] "Laboratory equipment" refers to the equipment and software used to analyze samples sent to a laboratory and generate results.

[0996] "AI model" refers to an artificial intelligence algorithm that analyzes samples and generates initial judgment results based on data obtained from an analytical device.

[0997] "Emotion engine" refers to a function that analyzes user behavior data (e.g., facial expressions, operation timing, voice, etc.) and determines the user's emotional state.

[0998] "Means for analyzing a sample" refers to the entire process of receiving a sample and performing analysis using a testing device.

[0999] "Means for generating a preliminary judgment result" refers to the process of outputting a preliminary test result based on data analyzed by an AI model.

[1000] "Means for adjusting the content and method of notification messages" refers to a mechanism for optimizing the expression of notification messages and notification methods according to the user's emotional state determined by the emotion engine.

[1001] "Means for providing instructions regarding next steps" refers to a function that informs the user of future actions to be taken or the need for additional testing based on the initial assessment results.

[1002] The present invention combines a system in which users collect samples themselves and provide rapid and highly accurate initial results through AI analysis, with an emotion engine that recognizes the user's emotions. Specific embodiments of this system are described below.

[1003] Test kit request

[1004] User

[1005] Users log in to the dedicated web or mobile application, click the "Request a Test Kit" button from the menu, and enter the required information (name, address, contact information, and questions about their health status).

[1006] Terminal

[1007] The device verifies the information entered by the user in real time. For example, it checks to make sure the address field is not empty, the phone number is not invalid, etc. If there are no missing or incorrect information, it sends the input details to the server as an HTTP POST request. If the transmission is successful, it displays a confirmation message to the user saying "Request accepted."

[1008] server

[1009] The server receives the request data from the user and saves it in a database. It inserts it into the database using an SQL query, and if successful, prepares the test kit. It then initiates the shipping process for the test kit and generates a tracking number. It then includes this tracking number in the HTTP response to notify the user's device.

[1010] Sample collection and shipping

[1011] User

[1012] The user receives the test kit and collects the sample according to the manual included with the kit. For example, for blood samples, a special lancet is used to collect a small amount of blood from the fingertip. The collected sample is then placed in a special container. Next, the user places the collected sample in the return envelope provided and sends it to the lab. After sending it, the user presses the "Sample sent" button in the app.

[1013] Terminal

[1014] The terminal provides an interface for recording the user's sending procedures. For example, when the send button is pressed, the collection date and time and type of specimen are recorded in the database. If the sending confirmation is successful, a notification "Specimen sending has been completed" is displayed to the user.

[1015] Sample analysis and initial determination

[1016] server

[1017] The server receives a notification of sample receipt from the lab. This notification is typically sent to the server via an HTTP POST request. The server records the receipt information in a database and notifies the user that the sample has arrived. The server then sends the sample information received from the lab to the analyzer, which then begins analysis.

[1018] analysis device

[1019] The analyzer analyzes the received sample and generates the results. For example, in the case of a blood sample, it uses equipment to detect specific markers in the blood. The resulting data is sent to the server in CSV or JSON format.

[1020] server

[1021] After receiving the analysis results, the server inputs the data into the AI ​​model, for example, by sending the analysis results to the AI ​​model as an HTTP POST request.

[1022] AI model

[1023] The AI ​​model generates a preliminary assessment result based on the analysis results. For example, an image recognition model is used to detect abnormal cells in the blood. Once the preliminary assessment result is generated, it is sent back to the server.

[1024] server

[1025] The server receives the initial judgment results from the AI ​​model, stores them in a database, and prepares to notify the user.

[1026] Emotion engine response and notification

[1027] server

[1028] The server calls the emotion engine and collects data to determine the user's emotional state. For example, facial expression data and operation timing when the user uses the app are acquired from cameras and sensors and input into the emotion engine. The emotion engine analyzes this data and determines the user's emotional state (e.g., tension, relief, stress, etc.).

[1029] Terminal

[1030] The device notifies the user of the initial results and instructions for the next step. For example, it may say, "The test results show an abnormality. Please consult your doctor for details." The wording of the notification is adjusted based on the analysis results of the emotion engine to avoid stressing the user. If necessary, the device may provide follow-up notifications or emotionally sensitive health advice.

[1031] Specific examples

[1032] 1. Executing the request

[1033] The user logs in to the application and requests a test kit. The terminal sends the request to the server, which then dispatches the kit and sends a tracking number to the terminal. The terminal then displays a confirmation message.

[1034] 2. Sample collection and shipping

[1035] The user collects a blood sample using the test kit and sends it to the lab in a return envelope. The terminal records the sending procedure and displays a notification of completion.

[1036] 3. Analysis and Notification

[1037] The server receives a receipt from the lab and sends the sample information to the analyzer. The analyzer sends the results to the server, which inputs them into the AI ​​model. The AI ​​model generates a preliminary judgment result and sends it back to the server. The server uses an emotion engine to determine the user's emotional state and creates an appropriate notification. The device displays the notification.

[1038] 4. Follow-up

[1039] If necessary, the server will send the user additional follow-up notifications and health advice, which the device will display and prompt the user to take appropriate action.

[1040] Prompt Sentence Examples

[1041] Here are some example prompts to input to a generative AI model:

[1042] The server dispatches the test kit requested by the user. A tracking number is assigned to the test kit and notified to the user. The user then receives the test kit, collects a blood sample according to the specified procedure, and sends it to the lab. The lab receives the sample, analyzes it, and sends the results to the server. The server uses an AI model to generate a preliminary assessment result and an emotion engine to analyze the user's emotional state and create an appropriate notification message.

[1043] This system allows users to easily collect samples from the comfort of their own home and receive a rapid, highly accurate initial result. Furthermore, the combination of an emotion engine enables appropriate responses based on the user's emotional state, improving the overall quality of the testing experience.

[1044] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1045] Step 1:

[1046] User:

[1047] Users log in to a dedicated web or mobile application, click the "Request a Test Kit" button from the menu, and then enter the required information, such as name, address, contact information, and health questions. This data serves as input for the next processing step.

[1048] Step 2:

[1049] Device:

[1050] The terminal verifies the information entered by the user in real time. For example, it checks to see if the address field is empty or if an invalid phone number has been entered. This ensures the accuracy of the data. The verified data is sent as input to the next process. If there are no omissions or errors, it is sent to the server as an HTTP POST request. If the transmission is successful, a confirmation message "Request accepted" is displayed to the user. This message becomes the output.

[1051] Step 3:

[1052] server:

[1053] The server receives the request data from the user. To save the input data in a database, it generates an SQL query and inserts it into the database. If the database insertion is successful, it begins preparing the test kit. Next, it carries out shipping procedures and generates a tracking number. It includes the generated tracking number in an HTTP response and sends it to the user's device. This tracking number becomes the output.

[1054] Step 4:

[1055] User:

[1056] The user receives the test kit and collects the sample according to the manual included in the kit. Specifically, for blood samples, a special lancet is used to collect a small amount of blood from the fingertip. The collected sample is then placed in a special container. This sample becomes the input for the next step.

[1057] Step 5:

[1058] User:

[1059] The user places the collected sample in the return envelope provided and sends it to the lab. The lab's address is pre-printed on the return envelope, so no additional information is required. The sent sample will be used as input for the next step. After sending the sample, press the "Sample sent" button in the app.

[1060] Step 6:

[1061] Device:

[1062] The terminal provides an interface for recording the user's sending procedure. This interface receives data such as the collection date and time and the type of specimen as input and records it in a database. If the sending confirmation is successful, a notification stating "Specimen sending completed" is displayed to the user as output.

[1063] Step 7:

[1064] server:

[1065] The server receives a sample receipt notification from the laboratory. The notification from the laboratory is sent to the server via an HTTP POST request. This receipt information is recorded in a database and the user is notified that the sample has arrived. To send the received sample information to the analyzer, an HTTP request is generated to send data to the analyzer. The output of this process is the sample information sent to the analyzer.

[1066] Step 8:

[1067] Analysis equipment:

[1068] The analyzer analyzes the received sample and generates the results. For example, in the case of a blood sample, it uses equipment to detect specific markers. The analysis results are sent to the server in CSV or JSON format. These analysis results are the output.

[1069] Step 9:

[1070] server:

[1071] The server receives the analysis results and inputs the data into the AI ​​model. It sends the analysis results to the AI ​​model as an HTTP POST request. The input for the AI ​​model includes this analysis data.

[1072] Step 10:

[1073] AI model:

[1074] The AI ​​model generates a primary judgment result based on the analysis results. For example, an image recognition model is used to detect abnormal cells in the blood. Once the primary judgment result is generated, it is sent back to the server. This primary judgment result becomes the output.

[1075] Step 11:

[1076] server:

[1077] The server receives the initial judgment results from the AI ​​model and stores them in a database. Next, it calls the emotion engine and collects data to determine the user's emotional state. For example, it uses a camera or sensor to acquire facial expression data and operation timing, and inputs this data into the emotion engine. The emotional state data generated by this analysis is the output.

[1078] Step 12:

[1079] server:

[1080] The server adjusts the content and format of the notification message based on the analysis results of the emotion engine. For example, it creates a notification using gentler language so that the user does not feel stressed. The adjusted notification message is sent to the device. The adjusted notification message becomes the output.

[1081] Step 13:

[1082] Device:

[1083] The device notifies the user of the initial assessment results and instructions for the next step. Based on the analysis results of the emotion engine, the device displays notifications tailored to prevent the user from feeling stressed. If necessary, it provides follow-up notifications and emotionally sensitive health advice. This notification is the output.

[1084] (Application example 2)

[1085] 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."

[1086] Conventional sample analysis systems are unable to respond to the user's emotional state between the time the user collects the sample and the time they receive the analysis results, resulting in an unsatisfactory user experience. Food delivery services, in particular, require services that take the user's emotional state into consideration, but lack mechanisms for addressing this. Therefore, it is necessary to improve the quality of service by analyzing the user's emotional state and providing appropriate responses and follow-up.

[1087] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1088] In this invention, the server includes: means for a user to request a device for collecting a sample themselves; means for the user to collect and send the sample; an analysis device for analyzing the sample after receiving the sample; means for analyzing the analysis result using a generative AI model and generating a primary determination result; means for notifying the user of the primary determination result; means including an emotion engine for analyzing the user's emotional state and providing responses and instructions according to the emotion; and means for providing instructions regarding the next step. This enables the provision of services according to the user's emotional state, improving the user experience.

[1089] A "user" is an individual who utilizes the system to collect specimens and receive analytical results.

[1090] A "specimen" is a biological sample that a user collects and sends for analysis.

[1091] "Equipment" refers to the tools and equipment required by the user to collect a specimen.

[1092] "Requesting means" is the ability for a user to request an instrument for collecting a specimen.

[1093] "Means for sending" is a function that allows the user to send the collected specimen to a specified location.

[1094] An "analytical device" is a device for analyzing a sample and generating a result.

[1095] A "generative AI model" is an artificial intelligence model that generates a primary judgment result based on the analysis results.

[1096] The "primary judgment result" is the first analytical evaluation derived by the generative AI model.

[1097] The "notification means" is a function for notifying the user of the primary judgment result.

[1098] An "emotion engine" is a system that analyzes the user's emotional state and responds or gives instructions based on that data.

[1099] The "instructions regarding the next step" are instructions indicating the specific action to be taken next based on the results of the primary determination and the user's emotional state.

[1100] A "food delivery service" is a service that delivers food to a location specified by the user.

[1101] This invention combines a system in which users collect samples at home and provide rapid and highly accurate initial results through analysis by a generative AI model with an emotion engine that recognizes the user's emotional state. This system aims to improve the quality of the service experience by enabling appropriate responses and follow-ups according to the user's emotional state.

[1102] User

[1103] User Registration and Ordering

[1104] Users log in to a dedicated food delivery app and search for their favorite meal. The app uses the built-in camera and microphone to capture the user's facial recognition and voice data, which is then analyzed by an emotion engine to understand the user's emotional state.

[1105] server

[1106] Executing the request

[1107] The server receives the user's request for the specimen collection equipment, verifies the accuracy of the information, and then ships the specimen collection equipment to the user's address, generates a tracking number, and notifies the terminal.

[1108] Sample analysis

[1109] After receiving the sample from the lab, the server updates the sample information in the database and notifies the user that the sample has arrived. The server then sends the sample information to the analyzer to begin analysis. The analysis results are then input into the AI ​​model, which generates a preliminary judgment result.

[1110] Emotional state analysis

[1111] The emotion engine on the server analyzes the user's emotional state based on facial recognition and voice data when using the app. This emotional information is then analyzed using a language processing model to create an appropriate message.

[1112] Terminal

[1113] Order Support and Notifications

[1114] The device receives the analysis results and notifies the user. Based on the analysis results from the emotion engine, the device provides a notification message and instructions on the next step in a gentle manner that reflects the user's emotional state. The device provides real-time delivery tracking information and a message that is sensitive to the user's emotions.

[1115] Adding specific examples

[1116] For example, when a user places an order using the app, if the emotion is recognized as "sad," the app will suggest hot soup or comfort food. Along with the suggested menu, a message such as "You're feeling a little blue today. Warm your body and soul with hot soup or comfort food!" will be displayed.

[1117] Prompt Sentence Examples

[1118] A concrete example of a prompt input to a generative AI model might be the following text:

[1119] What foods should you suggest for users when they are feeling very busy and stressed?

[1120] Such a system allows services to be provided according to the user's emotional state, improving the user experience.

[1121] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1122] Step 1:

[1123] User Registration and Sample Collection Equipment Request

[1124] The user logs into the dedicated app and inputs the necessary information (name, address, contact details, health status) to request a specimen collection device. The server receives the input data and verifies the information. If there are no omissions or errors, the request details are saved in the database and the specimen collection device is shipped. A tracking number is generated and sent to the device.

[1125] Input: User registration information and request data

[1126] Output: Stores accurate request data and generates tracking numbers

[1127] Specific operations: Validation and storage process, generation of tracking number, notification

[1128] Step 2:

[1129] Sample collection and shipping

[1130] The user collects a specimen (e.g., a blood sample) using the specimen collection device they received. They then place the collected specimen in a designated return envelope and send it to the laboratory. The terminal records information such as the specimen collection date and time and type, and sends it to the server.

[1131] Input: Sample collection information (date, time, type)

[1132] Output: Send sample information to the server

[1133] Specific actions: Collecting samples, recording and transmitting information

[1134] Step 3:

[1135] Receipt of samples and initiation of analysis

[1136] The server receives a notification of sample receipt from the laboratory, updates the database, and then sends the sample information to the analyzer to start analysis.

[1137] Input: Specimen receipt notice from lab

[1138] Output: Instructions to update the database and start analysis

[1139] Specific operations: Database update, sending instruction to start analysis

[1140] Step 4:

[1141] Analysis and generation of initial judgment results

[1142] The analysis device analyzes the received sample and generates result data. The result data is sent to the server and input into the generative AI model. The AI ​​model analyzes the image of the sample and generates a primary judgment result. The server receives this result and stores it in a database.

[1143] Input: Sample analysis result data

[1144] Output: Generate and save the first judgment result

[1145] Specific operations: Running the analysis device, generating and sending data, analyzing it using an AI model, and saving the results

[1146] Step 5:

[1147] Sentiment analysis and follow-up with emotion engine

[1148] The device acquires the user's facial recognition and voice data and analyzes it with an emotion engine. The emotion engine determines the user's emotional state and sends it to the server. The server uses this information to create a notification message in a gentle manner according to the initial assessment result, and also provides instructions on the next step.

[1149] Input: User's facial recognition and voice data

[1150] Output: Sentiment analysis results and a soft-spoken message

[1151] Specific operations: Facial recognition and voice data acquisition, emotion analysis, message generation

[1152] Step 6:

[1153] Delivery tracking and notifications

[1154] The server tracks the delivery status and sends real-time notifications to the device, including messages to reduce the stress felt by the user based on the analysis results of the emotion engine.

[1155] Input: Delivery status data

[1156] Output: Real-time delivery status notification

[1157] Specific behavior: Tracking delivery status, generating and sending notification messages

[1158] Step 7:

[1159] Delivery completion and feedback

[1160] The user receives the food and rates it within the app. The device analyzes the user's rating and emotional state and sends the results to the server, which uses the information to improve the service in the future.

[1161] Input: User ratings and emotional state data

[1162] Output: Data for service improvement

[1163] Specific actions: getting and sending feedback, analyzing and storing data

[1164] 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.

[1165] 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.

[1166] 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.

[1167] [Third embodiment]

[1168] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1169] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1170] 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).

[1171] 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.

[1172] 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.

[1173] 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).

[1174] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1175] 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.

[1176] 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.

[1177] 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.

[1178] 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.

[1179] 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."

[1180] The present invention relates to a system that allows users to collect samples themselves and provides rapid and highly accurate primary determination results through AI analysis. Specific embodiments of the present invention are described below.

[1181] Test kit request

[1182] User:

[1183] Users log in to a dedicated web or mobile application and request a test kit from the menu, answering questions about their name, address, contact information, and health status.

[1184] Device:

[1185] The terminal verifies the information entered by the user to ensure there are no omissions or errors. Once verification is complete, the user presses the send request button to send the input details to the server.

[1186] server:

[1187] The server receives the request data from the user and stores it in a database. At the same time, it prepares the test kit and begins the process of sending it to the user's address. Once the process is complete, it generates a tracking number to track the delivery status and returns that information to the terminal.

[1188] Sample collection and shipping

[1189] User:

[1190] Users receive the test kit at home and follow the instructions in the kit to collect a sample. For example, for a blood test, users use a special lancet to collect blood from their fingertip. The collected sample is then placed in the enclosed return envelope and sent to the designated lab.

[1191] Device:

[1192] The device provides an interface for users to record information about the collected specimen (collection date, type, etc.), and the app also guides users through the process of properly packaging the specimen and mailing it to the lab.

[1193] Sample analysis and initial determination

[1194] server:

[1195] When the laboratory receives the sample, it notifies the server, which updates the database and notifies the user that the sample has been received, and then sends the information to the analyzer to begin analyzing the sample.

[1196] Analysis equipment:

[1197] The analysis device analyzes the received sample and generates the results, which are then sent back to the server.

[1198] server:

[1199] The server inputs the received analysis data into the AI ​​model, which then analyzes the images of the specimens. The AI ​​model aggregates the results of multiple specimen tests and evaluates the presence or absence of cancer-related markers.

[1200] AI model:

[1201] The AI ​​model generates a preliminary judgment result based on the sample analysis results, which is then sent back to the server.

[1202] Notification of initial assessment results and next steps

[1203] server:

[1204] The server receives the initial assessment results sent by the AI ​​model and notifies the user of the results, as well as providing instructions on the next steps the user should take (e.g., recommending further testing).

[1205] Device:

[1206] The device will notify the user of the initial assessment results and instructions on next steps via in-app push notification or email, where the user can review the details.

[1207] User:

[1208] The user takes the necessary action based on the notified initial assessment result and the next step. For example, if a detailed examination is required, the user makes an appointment.

[1209] This allows users to easily collect samples from the comfort of their own home and receive a rapid and accurate primary diagnosis of cancer.The present invention provides a system that improves the quality control and analytical accuracy of samples and effectively monitors the health status of users.

[1210] The processing flow will be explained below.

[1211] Step 1:

[1212] User:

[1213] Users launch the HELPO app and log in to their account. They then select "Apply for a Test Kit" from the menu and follow the instructions to enter the required information (name, address, contact information, and health status questions).

[1214] Step 2:

[1215] Device:

[1216] The terminal validates the information entered by the user, checking for missing or incorrect data, and when the send request button is pressed, sends the contents to the server. If the transmission is successful, a confirmation message is displayed to the user.

[1217] Step 3:

[1218] server:

[1219] The server receives the request data from the user and stores it in a database. It then prepares the test kit and arranges for it to be sent to the user's address. Once the delivery arrangements are complete, it generates a tracking number to track the delivery status and sends it to the terminal.

[1220] Step 4:

[1221] Device:

[1222] The terminal will display information to the user, including a tracking number, and notify them of the expected arrival date of the test kit.

[1223] Step 5:

[1224] User:

[1225] Users receive a test kit and follow the instructions in the kit to collect a sample (either blood, urine, or saliva), then place the sample in a designated return envelope and mail it to the lab.

[1226] Step 6:

[1227] Device:

[1228] The device provides an interface for users to record information about the collected specimen (collection date and time, specimen type, etc.), and the app also guides users through the process of sending the specimen to a laboratory.

[1229] Step 7:

[1230] server:

[1231] The server receives a notification of sample receipt from the laboratory, confirms that the laboratory has received the sample, updates the database with that information, and notifies the terminal.

[1232] Step 8:

[1233] Device:

[1234] The device will notify the user via push notification or email that the sample has arrived at the lab.

[1235] Step 9:

[1236] server:

[1237] The server sends the sample information to the analysis device and starts the analysis. The received analysis results are input into the AI ​​model and the analysis is carried out.

[1238] Step 10:

[1239] AI model:

[1240] The AI ​​model analyzes the images of the specimens, assessing the presence or absence of cancer-related markers and abnormalities, and generates analysis results that are sent back to the server.

[1241] Step 11:

[1242] server:

[1243] The server receives the analysis results from the AI ​​model, generates a preliminary judgment based on the results, and creates instructions for the next steps and sends them to the device.

[1244] Step 12:

[1245] Device:

[1246] The device will notify the user of the initial results and instructions for next steps. The user will receive detailed results via in-app notifications or email.

[1247] Step 13:

[1248] User:

[1249] The user checks the notified primary assessment result and follows the instructions for the next step, making an appointment for a detailed examination if necessary.

[1250] The above are the specific processing steps and their details of the system. This process allows users to receive a simple and highly accurate primary cancer diagnosis from the comfort of their own home.

[1251] Example 1

[1252] 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."

[1253] In the prior art, when a user collects a sample themselves and has it analyzed at a specialized institution, it is difficult to obtain a rapid and accurate determination result. Furthermore, there are challenges in controlling the quality of the sample and improving the accuracy of the analysis results. Furthermore, specific instructions regarding the next steps the user should take are not provided, which may delay appropriate action. The present invention aims to solve these problems and provide a system that allows a user to easily collect a sample from home and obtain a rapid and accurate initial determination result.

[1254] 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.

[1255] In this invention, the server includes means for a user to request a kit for collecting a specimen themselves, means for a terminal to verify information entered by the user and send it to the server, means for the server to store the received information in a database and ship a test kit, a testing device for analyzing the specimen after receiving it, means for generating analysis results and sending the data to the server, means for the server to input the analysis data into an AI model and generate a primary determination result, means for notifying the user of the primary determination result, and means for providing instructions regarding the next step. This enables the user to obtain a primary determination result quickly and accurately.

[1256] "User" refers to an individual who uses the system to collect specimens and receive analytical results.

[1257] A "specimen" refers to a biological substance such as blood, urine, or saliva that is collected by the user and subjected to testing.

[1258] "Kit" refers to a set containing tools that a user can use to collect a specimen themselves.

[1259] "Terminal" refers to an information processing device used by a user, such as a computer, smartphone, or tablet.

[1260] "Server" refers to the central processing unit that receives requests from users, processes and stores data, and returns results to users.

[1261] A "database" refers to a system that allows a server to efficiently store, manage, and search information.

[1262] "Testing device" refers to a device that analyzes received specimens and generates result data.

[1263] "AI model" refers to software that includes algorithms for using artificial intelligence to analyze data and generate initial assessment results.

[1264] "Primary assessment result" refers to the initial analysis result generated by the AI ​​model and refers to the evaluation information provided to the user.

[1265] "Instructions" refers to guidance or recommendations regarding the next action a user should take after receiving the initial assessment results.

[1266] This invention relates to a system that allows users to collect samples themselves and provides rapid and highly accurate initial results through analysis by an AI model. This system consists of multiple components, including users, terminals, and servers.

[1267] Test kit request

[1268] User:

[1269] Users log in to a dedicated web or mobile application and request a test kit from the menu, answering questions about their name, address, contact information, and health status.

[1270] Device:

[1271] The terminal validates the information entered by the user to ensure there are no missing or incorrect information. For example, it uses form validation to check that address fields are not blank and that phone numbers are entered in the correct format. Once the validation is complete, the user presses the send button to send the input information to the server.

[1272] server:

[1273] The server receives the request data from the user and stores that information in a database. For example, MySQL or PostgreSQL is used for the database. The server also initiates the procedure for shipping the test kit and requests the shipping company to ship the kit. At this time, the server generates a tracking number to track the delivery status and returns that information to the terminal.

[1274] Sample collection and shipping

[1275] User:

[1276] Users receive the test kit at home and collect the sample according to the instructions included in the kit. For example, for a blood test, a special lancet is used to collect blood from the fingertip. The collected sample is placed in the enclosed return envelope and sent to the designated lab. The user then records the date and time of collection and the type of sample in the application.

[1277] Device:

[1278] The terminal records the collection information entered by the user and stores it in a database. The terminal also displays a screen that guides the user through the process of safely packaging the specimen and sending it to the lab.

[1279] Sample analysis and initial determination

[1280] server:

[1281] When the laboratory receives the specimen, it notifies the server, which updates the database and notifies the user that the specimen has been received, and then the server sends the information to the analyzer to begin analyzing the specimen.

[1282] Analysis equipment:

[1283] The analysis device analyzes the received sample and generates result data, for example, using a spectrophotometer or flow cytometer, and the analysis result data is sent back to the server.

[1284] server:

[1285] The server inputs the received analysis data into a generative AI model, which is built using TensorFlow or PyTorch, for example. The AI ​​model generates a primary judgment result based on the sample analysis results and returns the result to the server.

[1286] Notification of initial assessment results and next steps

[1287] server:

[1288] The server receives the initial assessment results sent by the AI ​​model and notifies the user of the results, along with instructions on what next steps to take (e.g., recommending further testing).

[1289] Device:

[1290] The device will notify the user with the initial assessment results and instructions on next steps via an in-app push notification or email, and the user can open the app for more details.

[1291] User:

[1292] The user takes the necessary action based on the notified primary assessment result and the next step. For example, if a detailed examination is required, the user makes an appointment.

[1293] Prompt Sentence Examples

[1294] "Please generate a preliminary AI result based on the analysis results of the sample I provide. Please write a sentence in natural language that explains the entire process from requesting a test kit to receiving the results."

[1295] This allows users to easily collect samples from the comfort of their own home and receive a rapid and highly accurate initial diagnosis. This system improves the quality control and analysis accuracy of samples, enabling effective monitoring of users' health conditions.

[1296] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1297] Step 1:

[1298] User:

[1299] Log in to the dedicated web application or mobile application. The information required for login is your user ID and password. Once you have successfully logged in, your user dashboard will be displayed.

[1300] input:

[1301] User ID and password

[1302] output:

[1303] Login success message, dashboard display

[1304] Specific behavior:

[1305] A user opens the app, enters their user ID and password on the login screen, and clicks the "Login" button. The system verifies the authentication information, and if it is correct, the dashboard is displayed.

[1306] Step 2:

[1307] User:

[1308] Request a test kit: Users select the "Request a test kit" option from the menu and answer questions about their name, address, contact information, and health status.

[1309] input:

[1310] Name, address, contact information, and health status

[1311] output:

[1312] Request confirmation message and input details display screen

[1313] Specific behavior:

[1314] The user enters the required information on the "Request a Test Kit" screen and clicks the "Submit" button. A confirmation message for the entered information is displayed on the screen.

[1315] Step 3:

[1316] Device:

[1317] Validate user-entered information and format submitted data.

[1318] input:

[1319] User-provided name, address, contact information, and health status answers

[1320] output:

[1321] Verified data, data sent to server

[1322] Specific behavior:

[1323] The device checks the contents of the input fields, formats them as needed (e.g., checks if the address field is empty, verifies that the contact information is in the correct format), and prepares the data to be sent to the server.

[1324] Step 4:

[1325] server:

[1326] It receives the request data, stores the information in a database, and processes the shipping of the test kit.

[1327] input:

[1328] Request data sent from the device

[1329] output:

[1330] Request information and tracking number stored in the database

[1331] Specific behavior:

[1332] The server receives the request data and saves it in a database. Then, it requests the shipping company to ship the test kit via API. It receives a tracking number from the shipping company and returns it to the user.

[1333] Step 5:

[1334] User:

[1335] After receiving the test kit, collect the sample according to the instructions, place the collected sample in the return envelope, and send it to the designated laboratory.

[1336] input:

[1337] Test kit instructions, user samples

[1338] output:

[1339] Collected specimen and message of completion of sending

[1340] Specific behavior:

[1341] The user follows the instructions to collect a sample (e.g., using a lancet to collect blood from a fingertip), seals it in a return envelope, and then goes to the post office to mail it off to the lab.

[1342] Step 6:

[1343] server:

[1344] When the lab receives the sample, it receives a notification and updates the database with the information, which is then sent to the analyzer.

[1345] input:

[1346] Acknowledgment from the lab

[1347] output:

[1348] Database update information, data sent to analysis equipment

[1349] Specific behavior:

[1350] When the laboratory receives the sample, it notifies the server, which updates the database with the receipt information and sends an analysis request to the analyzer.

[1351] Step 7:

[1352] Analysis equipment:

[1353] The received samples are analyzed, and analysis result data is generated and sent to the server.

[1354] input:

[1355] Sample information sent to the analyzer

[1356] output:

[1357] Analysis result data

[1358] Specific behavior:

[1359] The analytical device analyzes the sample, generates the result data, and sends it to the server. For example, a spectrophotometer or flow cytometer is used.

[1360] Step 8:

[1361] server:

[1362] The received analysis data is input into the AI ​​model to generate a primary judgment result, which is then notified to the user.

[1363] input:

[1364] Analysis result data

[1365] output:

[1366] Primary judgment results, user notification data

[1367] Specific behavior:

[1368] The server sends the analysis results data to the AI ​​model, which generates a first-order judgment. The generation AI model uses pre-trained TensorFlow or PyTorch, and notifies the user of the result.

[1369] Step 9:

[1370] Device:

[1371] The user is notified of the initial assessment results and instructions regarding next steps.

[1372] input:

[1373] Initial assessment results and instructions on next steps

[1374] output:

[1375] Notification Message

[1376] Specific behavior:

[1377] The device will notify the user of the initial assessment results and next steps via in-app push notification or email.

[1378] Step 10:

[1379] User:

[1380] Respond according to the notified initial assessment result and next steps, for example, make an appointment for a detailed examination.

[1381] input:

[1382] Initial assessment results and instructions on next steps

[1383] output:

[1384] Detailed examination reservation information, etc.

[1385] Specific behavior:

[1386] The user confirms the notification and takes the necessary next steps (e.g., schedules an appointment for a detailed examination if necessary).

[1387] (Application example 1)

[1388] 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."

[1389] Conventional home sample collection and analysis systems lack sufficient support for users in the accurate sample collection process, resulting in issues with sample collection accuracy and adherence to procedures. Furthermore, methods for quickly and accurately notifying users of sample analysis results are limited, and clear guidance on how to proceed to the next step is lacking. To address these issues, a system is needed that allows users to intuitively and reliably collect samples and instantly receive analysis results.

[1390] 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.

[1391] In this invention, the server includes means for a user to request a kit for collecting a specimen by themselves, means for the user to collect and send the specimen, a testing device for analyzing the specimen after receiving the specimen, means for analyzing the analysis result using an AI model and generating a primary determination result, means for notifying the user of the primary determination result, means for providing instructions regarding the next step, means for the user to receive visual and audio guidance by wearing a head-mounted display device, and means for checking the user's specimen collection procedure in real time, thereby enabling the user to reliably collect a specimen and obtain a rapid and highly accurate analysis result.

[1392] "User" means an individual or organization that uses the system to collect specimens and receive analysis and notification of results.

[1393] A "kit for collecting specimens" is a set that includes tools and instructions that allow users to collect specimens safely and accurately themselves.

[1394] A "method of requesting a kit" is how a user places an order for a test kit through a web or mobile application.

[1395] "Means for sending specimens" refers to a method that provides procedures and tools for users to send collected specimens to a designated analysis laboratory.

[1396] A "test device" is a physical or chemical device that analyzes a received specimen and generates a result.

[1397] "AI Model" means the artificial intelligence algorithms and models used to generate a preliminary determination result based on the analysis of a received specimen.

[1398] The "means for generating a primary judgment result" is a method for using an AI model to summarize the analysis results of a sample as a primary evaluation.

[1399] The "means for notifying the user of the primary determination results" refers to a communication means or notification system for immediately notifying the user of the analysis results.

[1400] The "means for providing instructions regarding the next step" is a method for guiding the user on the next action or necessary response to be taken based on the results of the primary determination.

[1401] A "head-mounted display device" is a device that displays visual and audio information when worn by a user.

[1402] "Means for receiving visual and audio guidance" refers to a method in which the user is provided with visual and audio guidance via a head-mounted display to guide them through the sample collection procedure and delivery method.

[1403] "Means for verifying a user's sample collection procedures in real time" refers to a method for using a head-mounted display to monitor a user's procedures in real time and verify accuracy and compliance.

[1404] The present invention relates to a system that includes a series of processes in which a user collects a sample themselves and receives visual and audio guidance using a head-mounted display device. The system comprises the following steps:

[1405] First, a user wears a head-mounted display device with a dedicated application installed and requests a test kit. The user logs in to the application and follows the on-screen instructions to answer questions about their personal information and health status. This information is displayed visually through the head-mounted display, and a voice assistant guides the input. The server receives this information, processes the request, and delivers the test kit to the user's address.

[1406] Next, the user collects a sample at home using the provided test kit. The head-mounted display device provides step-by-step instructions visually and audibly. For example, for a blood test, the user is guided on how to use the lancet and properly collect the sample, with real-time confirmation of the procedure. Once the sample is collected, it is placed in the provided return envelope and sent to the designated analysis lab.

[1407] When the sample arrives at the lab, the information is sent to the server, which updates the information and notifies the user via a push notification on the head-mounted display that the sample has been received. The testing device then analyzes the sample and generates the results, which are then sent back to the server.

[1408] The server inputs the received analysis results into the generative AI model to generate a preliminary assessment result, which is then communicated to the user via a head-mounted display, where the user can check the results in real time and receive visual and audio instructions regarding next steps (e.g., recommending further testing).

[1409] (Hardware and Software Use)

[1410] A common device such as Oculus Quest 2 is used as the head-mounted display device. The VoiceAssistant library is used for the voice assistant, and the requests library is used for communication processing. The hmd_display library is used for display management. This allows users to intuitively follow prompts and smoothly carry out the process from sample collection to checking analysis results.

[1411] (Example)

[1412] When the user wears the head-mounted display device and gives a voice command such as "Hello, please tell me the procedure for sample collection," visual and voice guidance begins. Similarly, the system operates appropriately when the user gives voice commands following prompts such as "I would like to check the current test results" to send the sample and receive notification of the analysis results.

[1413] This allows users to collect samples easily and safely from the comfort of their own home and receive prompt and highly accurate initial results.

[1414] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1415] Step 1:

[1416] The user launches the application and requests a test kit.

[1417] Specific behavior:

[1418] The user wears a head-mounted display device and logs in to the application. Next, they follow the on-screen instructions to answer questions about their personal information and health status. This information is then sent to the server as input data.

[1419] Input: User information (name, address, health status, etc.)

[1420] Output: A request for a test kit is sent to the server.

[1421] Step 2:

[1422] The server receives and processes requests for test kits.

[1423] Specific behavior:

[1424] The server validates the received request data and stores it in a database. After checking for any missing or incorrect information, it initiates the shipping process for the test kit and obtains a tracking number from the delivery company. The tracking number is then returned to the user.

[1425] Input: Request data

[1426] Output: Tracking number is sent to the user

[1427] Step 3:

[1428] The user receives the test kit and collects the specimen.

[1429] Specific behavior:

[1430] The user opens the test kit and follows the visual and audio guidance on the head-mounted display device to collect a sample, such as using a lancet to draw blood from a fingertip. The user is then checked in real time during the process.

[1431] Input: Test kit, visual and audio guidance

[1432] Output: Collected specimen

[1433] Step 4:

[1434] The user sends the collected specimen.

[1435] Specific behavior:

[1436] The collected sample is placed in the enclosed return envelope and sent to the designated analysis lab, and the head-mounted display device provides visual and audio guidance on proper packaging and mailing instructions.

[1437] Input: Collected specimen, return envelope

[1438] Output: Specimen sent to the lab

[1439] Step 5:

[1440] The server confirms receipt of the specimen.

[1441] Specific behavior:

[1442] When the sample arrives at the lab, the information is sent to the server, which updates the information and sends a push notification to the user to let them know the sample has been received.

[1443] Input: Specimen receipt notice

[1444] Output: Acknowledgement to user

[1445] Step 6:

[1446] The testing device analyzes the sample and generates a result.

[1447] Specific behavior:

[1448] The testing device analyzes the sample received from the server and generates the result data, which is then sent back to the server.

[1449] Input: Sample

[1450] Output: Analysis result data

[1451] Step 7:

[1452] The server inputs the analysis results into the AI ​​model and generates a primary judgment result.

[1453] Specific behavior:

[1454] The server inputs the received analysis result data into the generative AI model to generate a primary judgment result, which is then sent back to the server.

[1455] Input: Analysis result data

[1456] Output: Primary judgment result

[1457] Step 8:

[1458] The server notifies the user of the results of the initial judgment.

[1459] Specific behavior:

[1460] The server notifies the user of the generated primary judgment result via the head-mounted display device. The user receives a push notification and can check the details.

[1461] Input: Primary judgment result

[1462] Output: User notification

[1463] Step 9:

[1464] The server provides instructions to the user regarding next steps.

[1465] Specific behavior:

[1466] Based on the results of the initial assessment, the server generates instructions regarding the next steps the user should take (e.g., recommending a detailed examination) and provides them to the user via the head-mounted display device.

[1467] Input: Primary judgment result

[1468] Output: Instructions for next steps

[1469] 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.

[1470] The present invention combines a system in which users collect samples themselves and provide rapid and highly accurate initial results through AI analysis with an emotion engine that recognizes the user's emotions. The present invention aims to improve the quality of the testing experience by enabling appropriate responses and follow-ups based on the user's emotional state. Specific embodiments of the present invention are described below.

[1471] Test kit request

[1472] User:

[1473] Users log in to a dedicated web or mobile application, request a test kit from the menu, and enter the required information (name, address, contact information, and questions about their health status).

[1474] Device:

[1475] The terminal validates the information entered by the user to ensure there are no missing or incorrect information. If the request is correct, it sends the input to the server. If the transmission is successful, a confirmation message is displayed to the user.

[1476] server:

[1477] The server receives the request data from the user and stores it in a database. It prepares the test kit and arranges for it to be sent to the user's address. It generates a tracking number and notifies the terminal.

[1478] Sample collection and shipping

[1479] User:

[1480] The user receives the test kit and collects the sample according to the instructions in the kit (e.g., for blood samples, use a special lancet), places the sample in the designated return envelope, and sends it to the lab.

[1481] Device:

[1482] The device provides an interface for users to record information about the collected specimen (collection date and time, specimen type, etc.), and supports the specimen sending procedure within the app.

[1483] Sample analysis and initial determination

[1484] server:

[1485] The server receives a notification of sample receipt from the laboratory, updates the database with the receipt information, notifies the user that the sample has arrived, and then sends the sample information to the analyzer to begin analysis.

[1486] Analysis equipment:

[1487] The analyzer analyzes the received sample and generates the results, which are then sent to the server.

[1488] server:

[1489] The server inputs the received analysis data into the AI ​​model, which then analyzes the image of the sample. The AI ​​model then generates a primary judgment result based on the sample test results.

[1490] AI model:

[1491] The AI ​​model generates analysis results and sends them back to the server.

[1492] Emotion engine response and notification

[1493] server:

[1494] The server receives the analysis results from the AI ​​model and generates a primary judgment result. Next, it uses an emotion engine to recognize the user's emotional state. The emotion engine analyzes behavioral data (facial expressions, operation timing, voice, etc.) when the user uses the app to determine the user's emotional state. Based on this emotional information, the content and method of notification messages are adjusted.

[1495] Device:

[1496] The device notifies the user of the initial assessment results and instructions for the next step. Based on the analysis results of the emotion engine, the device notifies the user in a gentle manner so as not to cause stress to the user. If necessary, the device also provides follow-up notifications and emotionally sensitive health advice.

[1497] Specific examples

[1498] 1. Execute the request:

[1499] A user requests a test kit and the information is sent to the server, which dispatches the kit and notifies the user.

[1500] 2. Sample collection and shipping:

[1501] The user receives the test kit, collects a blood sample, and sends it to the laboratory, which receives the sample and sends it to the analyzer.

[1502] 3. Analysis and Notification:

[1503] The AI ​​model analyzes the sample and generates a preliminary assessment. Based on this assessment, the emotion engine analyzes the user's emotional state and creates an appropriate notification message. The device then notifies the user of this message and the next steps.

[1504] 4. Follow-up:

[1505] If necessary, provide users with additional follow-up notifications and empathetic health advice.

[1506] This allows users to conveniently collect samples from the comfort of their own home and receive a quick and accurate initial result. Furthermore, the combination of an emotion engine enables appropriate responses based on the user's emotional state, improving the overall quality of the testing experience.

[1507] The processing flow will be explained below.

[1508] Step 1:

[1509] User:

[1510] Users launch the HELPO app and log in to their account. They then select "Apply for a Test Kit" from the menu and follow the instructions to enter the required information (name, address, contact information, and health status questions).

[1511] Step 2:

[1512] Device:

[1513] The terminal verifies the information entered by the user to check for omissions or errors. When the send request button is pressed, the input details are sent to the server. If the transmission is successful, a confirmation message is displayed to the user.

[1514] Step 3:

[1515] server:

[1516] The server receives the request data from the user and stores it in a database. It then prepares the test kit and sends it to the user's address. Once the delivery arrangements are complete, it generates a tracking number to track the delivery status and notifies the terminal.

[1517] Step 4:

[1518] Device:

[1519] The terminal will display information to the user, including a tracking number, and notify them of the expected arrival date of the test kit.

[1520] Step 5:

[1521] User:

[1522] Users receive a test kit and collect a sample (either blood, urine, or saliva) according to the instructions enclosed with the kit. The collected sample is placed in a designated return envelope and mailed to the lab.

[1523] Step 6:

[1524] Device:

[1525] The device provides an interface for users to record information about the collected specimen (collection date and time, specimen type, etc.), and the app also guides users through the process of sending the specimen to a laboratory.

[1526] Step 7:

[1527] server:

[1528] The server receives a notification of sample receipt from the laboratory, confirms that the laboratory has received the sample, updates the database with that information, and notifies the terminal.

[1529] Step 8:

[1530] Device:

[1531] The device will notify the user via push notification or email that the sample has arrived at the lab.

[1532] Step 9:

[1533] server:

[1534] The server sends the sample information to the analysis device and starts the analysis. After receiving the sample analysis results, it inputs them into the AI ​​model and performs additional analysis.

[1535] Step 10:

[1536] AI model:

[1537] The AI ​​model analyzes the images of the specimens, assessing the presence or absence of cancer-related markers and abnormalities, and generates analysis results that are sent back to the server.

[1538] Step 11:

[1539] server:

[1540] The server generates a preliminary judgment result using the analysis results received from the AI ​​model, and simultaneously uses an emotion engine to recognize the user's emotions and adjust notification messages based on the user's emotional state.

[1541] Step 12:

[1542] Emotion Engine:

[1543] The emotion engine determines emotions based on behavioral data (facial expressions, operation timing, voice, etc.) when the user uses the app, and provides this information to the server to optimize the content of notification messages.

[1544] Step 13:

[1545] server:

[1546] Based on the information from the emotion engine, the server creates a primary judgment result and instructions for the next step using expressions to reduce the user's stress, and sends them to the terminal.

[1547] Step 14:

[1548] Device:

[1549] The device notifies the user of the results of the initial assessment and instructions on next steps, with the content of the notification optimized according to the user's emotional state.

[1550] Step 15:

[1551] User:

[1552] The user checks the notified initial assessment results and next steps and takes the necessary action. For example, if a detailed examination is recommended, the user can make an appointment. The device also provides support during this process.

[1553] Step 16:

[1554] server:

[1555] If necessary, the system will send users additional follow-up notifications and provide health advice, allowing them to continually manage their health.

[1556] Example 2

[1557] 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."

[1558] In conventional sample analysis systems, the process of users collecting samples and sending them to a laboratory is time-consuming, and it often takes a long time for results to be notified. Furthermore, because feedback and responses do not take into account the user's emotional state, users may feel stressed or anxious when receiving their test results. The present invention aims to solve these problems and provide fast and accurate sample analysis and responses that take into account the user's emotional state.

[1559] 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.

[1560] In this invention, the server includes means for a user to request a kit for collecting a sample themselves, means for the user to collect the sample and send it, a testing device for analyzing the sample after receiving it, means for analyzing the analysis results using an AI model and generating a primary determination result, means for using an emotion engine that recognizes the user's emotional state and adjusts the content and method of a notification message, and means for notifying the user of the primary determination result and instructions regarding the next step. This allows the user to receive a primary determination of their sample quickly and accurately from the comfort of their own home, and the emotion engine provides an appropriate response, thereby reducing stress and anxiety when receiving the test results.

[1561] "User" refers to the entity that uses this system to collect specimens and receive analysis results.

[1562] "Specimen" refers to the biological material (e.g., blood, saliva, etc.) to be analyzed.

[1563] "Means for requesting a kit" refers to the functionality that allows a user to order a specimen collection kit using a dedicated application.

[1564] "Means of sending" refers to the mechanism by which the user sends the collected specimen to the laboratory (e.g., return envelope, sending confirmation function).

[1565] "Laboratory equipment" refers to the equipment and software used to analyze samples sent to a laboratory and generate results.

[1566] "AI model" refers to an artificial intelligence algorithm that analyzes samples and generates initial judgment results based on data obtained from an analytical device.

[1567] "Emotion engine" refers to a function that analyzes user behavior data (e.g., facial expressions, operation timing, voice, etc.) and determines the user's emotional state.

[1568] "Means for analyzing a sample" refers to the entire process of receiving a sample and performing analysis using a testing device.

[1569] "Means for generating a preliminary judgment result" refers to the process of outputting a preliminary test result based on data analyzed by an AI model.

[1570] "Means for adjusting the content and method of notification messages" refers to a mechanism for optimizing the expression of notification messages and notification methods according to the user's emotional state determined by the emotion engine.

[1571] "Means for providing instructions regarding next steps" refers to a function that informs the user of future actions to be taken or the need for additional testing based on the initial assessment results.

[1572] The present invention combines a system in which users collect samples themselves and provide rapid and highly accurate initial results through AI analysis, with an emotion engine that recognizes the user's emotions. Specific embodiments of this system are described below.

[1573] Test kit request

[1574] User

[1575] Users log in to the dedicated web or mobile application, click the "Request a Test Kit" button from the menu, and enter the required information (name, address, contact information, and questions about their health status).

[1576] Terminal

[1577] The device verifies the information entered by the user in real time. For example, it checks to make sure the address field is not empty, the phone number is not invalid, etc. If there are no missing or incorrect information, it sends the input details to the server as an HTTP POST request. If the transmission is successful, it displays a confirmation message to the user saying "Request accepted."

[1578] server

[1579] The server receives the request data from the user and saves it in a database. It inserts it into the database using an SQL query, and if successful, prepares the test kit. It then initiates the shipping process for the test kit and generates a tracking number. It then includes this tracking number in the HTTP response to notify the user's device.

[1580] Sample collection and shipping

[1581] User

[1582] The user receives the test kit and collects the sample according to the manual included with the kit. For example, for blood samples, a special lancet is used to collect a small amount of blood from the fingertip. The collected sample is then placed in a special container. Next, the user places the collected sample in the return envelope provided and sends it to the lab. After sending it, the user presses the "Sample sent" button in the app.

[1583] Terminal

[1584] The terminal provides an interface for recording the user's sending procedures. For example, when the send button is pressed, the collection date and time and type of specimen are recorded in the database. If the sending confirmation is successful, a notification "Specimen sending has been completed" is displayed to the user.

[1585] Sample analysis and initial determination

[1586] server

[1587] The server receives a notification of sample receipt from the lab. This notification is typically sent to the server via an HTTP POST request. The server records the receipt information in a database and notifies the user that the sample has arrived. The server then sends the sample information received from the lab to the analyzer, which then begins analysis.

[1588] analysis device

[1589] The analyzer analyzes the received sample and generates the results. For example, in the case of a blood sample, it uses equipment to detect specific markers in the blood. The resulting data is sent to the server in CSV or JSON format.

[1590] server

[1591] After receiving the analysis results, the server inputs the data into the AI ​​model, for example, by sending the analysis results to the AI ​​model as an HTTP POST request.

[1592] AI model

[1593] The AI ​​model generates a preliminary assessment result based on the analysis results. For example, an image recognition model is used to detect abnormal cells in the blood. Once the preliminary assessment result is generated, it is sent back to the server.

[1594] server

[1595] The server receives the initial judgment results from the AI ​​model, stores them in a database, and prepares to notify the user.

[1596] Emotion engine response and notification

[1597] server

[1598] The server calls the emotion engine and collects data to determine the user's emotional state. For example, facial expression data and operation timing when the user uses the app are acquired from cameras and sensors and input into the emotion engine. The emotion engine analyzes this data and determines the user's emotional state (e.g., tension, relief, stress, etc.).

[1599] Terminal

[1600] The device notifies the user of the initial results and instructions for the next step. For example, it may say, "The test results show an abnormality. Please consult your doctor for details." The wording of the notification is adjusted based on the analysis results of the emotion engine to avoid stressing the user. If necessary, the device may provide follow-up notifications or emotionally sensitive health advice.

[1601] Specific examples

[1602] 1. Executing the request

[1603] The user logs in to the application and requests a test kit. The terminal sends the request to the server, which then dispatches the kit and sends a tracking number to the terminal. The terminal then displays a confirmation message.

[1604] 2. Sample collection and shipping

[1605] The user collects a blood sample using the test kit and sends it to the lab in a return envelope. The terminal records the sending procedure and displays a notification of completion.

[1606] 3. Analysis and Notification

[1607] The server receives a receipt from the lab and sends the sample information to the analyzer. The analyzer sends the results to the server, which inputs them into the AI ​​model. The AI ​​model generates a preliminary judgment result and sends it back to the server. The server uses an emotion engine to determine the user's emotional state and creates an appropriate notification. The device displays the notification.

[1608] 4. Follow-up

[1609] If necessary, the server will send the user additional follow-up notifications and health advice, which the device will display and prompt the user to take appropriate action.

[1610] Prompt Sentence Examples

[1611] Here are some example prompts to input to a generative AI model:

[1612] The server dispatches the test kit requested by the user. A tracking number is assigned to the test kit and notified to the user. The user then receives the test kit, collects a blood sample according to the specified procedure, and sends it to the lab. The lab receives the sample, analyzes it, and sends the results to the server. The server uses an AI model to generate a preliminary assessment result and an emotion engine to analyze the user's emotional state and create an appropriate notification message.

[1613] This system allows users to easily collect samples from the comfort of their own home and receive a rapid, highly accurate initial result. Furthermore, the combination of an emotion engine enables appropriate responses based on the user's emotional state, improving the overall quality of the testing experience.

[1614] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1615] Step 1:

[1616] User:

[1617] Users log in to a dedicated web or mobile application, click the "Request a Test Kit" button from the menu, and then enter the required information, such as name, address, contact information, and health questions. This data serves as input for the next processing step.

[1618] Step 2:

[1619] Device:

[1620] The terminal verifies the information entered by the user in real time. For example, it checks to see if the address field is empty or if an invalid phone number has been entered. This ensures the accuracy of the data. The verified data is sent as input to the next process. If there are no omissions or errors, it is sent to the server as an HTTP POST request. If the transmission is successful, a confirmation message "Request accepted" is displayed to the user. This message becomes the output.

[1621] Step 3:

[1622] server:

[1623] The server receives the request data from the user. To save the input data in a database, it generates an SQL query and inserts it into the database. If the database insertion is successful, it begins preparing the test kit. Next, it carries out shipping procedures and generates a tracking number. It includes the generated tracking number in an HTTP response and sends it to the user's device. This tracking number becomes the output.

[1624] Step 4:

[1625] User:

[1626] The user receives the test kit and collects the sample according to the manual included in the kit. Specifically, for blood samples, a special lancet is used to collect a small amount of blood from the fingertip. The collected sample is then placed in a special container. This sample becomes the input for the next step.

[1627] Step 5:

[1628] User:

[1629] The user places the collected sample in the return envelope provided and sends it to the lab. The lab's address is pre-printed on the return envelope, so no additional information is required. The sent sample will be used as input for the next step. After sending the sample, press the "Sample sent" button in the app.

[1630] Step 6:

[1631] Device:

[1632] The terminal provides an interface for recording the user's sending procedure. This interface receives data such as the collection date and time and the type of specimen as input and records it in a database. If the sending confirmation is successful, a notification stating "Specimen sending completed" is displayed to the user as output.

[1633] Step 7:

[1634] server:

[1635] The server receives a sample receipt notification from the laboratory. The notification from the laboratory is sent to the server via an HTTP POST request. This receipt information is recorded in a database and the user is notified that the sample has arrived. To send the received sample information to the analyzer, an HTTP request is generated to send data to the analyzer. The output of this process is the sample information sent to the analyzer.

[1636] Step 8:

[1637] Analysis equipment:

[1638] The analyzer analyzes the received sample and generates the results. For example, in the case of a blood sample, it uses equipment to detect specific markers. The analysis results are sent to the server in CSV or JSON format. These analysis results are the output.

[1639] Step 9:

[1640] server:

[1641] The server receives the analysis results and inputs the data into the AI ​​model. It sends the analysis results to the AI ​​model as an HTTP POST request. The input for the AI ​​model includes this analysis data.

[1642] Step 10:

[1643] AI model:

[1644] The AI ​​model generates a primary judgment result based on the analysis results. For example, an image recognition model is used to detect abnormal cells in the blood. Once the primary judgment result is generated, it is sent back to the server. This primary judgment result becomes the output.

[1645] Step 11:

[1646] server:

[1647] The server receives the initial judgment results from the AI ​​model and stores them in a database. Next, it calls the emotion engine and collects data to determine the user's emotional state. For example, it uses a camera or sensor to acquire facial expression data and operation timing, and inputs this data into the emotion engine. The emotional state data generated by this analysis is the output.

[1648] Step 12:

[1649] server:

[1650] The server adjusts the content and format of the notification message based on the analysis results of the emotion engine. For example, it creates a notification using gentler language so that the user does not feel stressed. The adjusted notification message is sent to the device. The adjusted notification message becomes the output.

[1651] Step 13:

[1652] Device:

[1653] The device notifies the user of the initial assessment results and instructions for the next step. Based on the analysis results of the emotion engine, the device displays notifications tailored to prevent the user from feeling stressed. If necessary, it provides follow-up notifications and emotionally sensitive health advice. This notification is the output.

[1654] (Application example 2)

[1655] 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."

[1656] Conventional sample analysis systems are unable to respond to the user's emotional state between the time the user collects the sample and the time they receive the analysis results, resulting in an unsatisfactory user experience. Food delivery services, in particular, require services that take the user's emotional state into consideration, but lack mechanisms for addressing this. Therefore, it is necessary to improve the quality of service by analyzing the user's emotional state and providing appropriate responses and follow-up.

[1657] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1658] In this invention, the server includes: means for a user to request a device for collecting a sample themselves; means for the user to collect and send the sample; an analysis device for analyzing the sample after receiving the sample; means for analyzing the analysis result using a generative AI model and generating a primary determination result; means for notifying the user of the primary determination result; means including an emotion engine for analyzing the user's emotional state and providing responses and instructions according to the emotion; and means for providing instructions regarding the next step. This enables the provision of services according to the user's emotional state, improving the user experience.

[1659] A "user" is an individual who utilizes the system to collect specimens and receive analytical results.

[1660] A "specimen" is a biological sample that a user collects and sends for analysis.

[1661] "Equipment" refers to the tools and equipment required by the user to collect a specimen.

[1662] "Requesting means" is the ability for a user to request an instrument for collecting a specimen.

[1663] "Means for sending" is a function that allows the user to send the collected specimen to a specified location.

[1664] An "analytical device" is a device for analyzing a sample and generating a result.

[1665] A "generative AI model" is an artificial intelligence model that generates a primary judgment result based on the analysis results.

[1666] The "primary judgment result" is the first analytical evaluation derived by the generative AI model.

[1667] The "notification means" is a function for notifying the user of the primary judgment result.

[1668] An "emotion engine" is a system that analyzes the user's emotional state and responds or gives instructions based on that data.

[1669] The "instructions regarding the next step" are instructions indicating the specific action to be taken next based on the results of the primary determination and the user's emotional state.

[1670] A "food delivery service" is a service that delivers food to a location specified by the user.

[1671] This invention combines a system in which users collect samples at home and provide rapid and highly accurate initial results through analysis by a generative AI model with an emotion engine that recognizes the user's emotional state. This system aims to improve the quality of the service experience by enabling appropriate responses and follow-ups according to the user's emotional state.

[1672] User

[1673] User Registration and Ordering

[1674] Users log in to a dedicated food delivery app and search for their favorite meal. The app uses the built-in camera and microphone to capture the user's facial recognition and voice data, which is then analyzed by an emotion engine to understand the user's emotional state.

[1675] server

[1676] Executing the request

[1677] The server receives the user's request for the specimen collection equipment, verifies the accuracy of the information, and then ships the specimen collection equipment to the user's address, generates a tracking number, and notifies the terminal.

[1678] Sample analysis

[1679] After receiving the sample from the lab, the server updates the sample information in the database and notifies the user that the sample has arrived. The server then sends the sample information to the analyzer to begin analysis. The analysis results are then input into the AI ​​model, which generates a preliminary judgment result.

[1680] Emotional state analysis

[1681] The emotion engine on the server analyzes the user's emotional state based on facial recognition and voice data when using the app. This emotional information is then analyzed using a language processing model to create an appropriate message.

[1682] Terminal

[1683] Order Support and Notifications

[1684] The device receives the analysis results and notifies the user. Based on the analysis results from the emotion engine, the device provides a notification message and instructions on the next step in a gentle manner that reflects the user's emotional state. The device provides real-time delivery tracking information and a message that is sensitive to the user's emotions.

[1685] Adding specific examples

[1686] For example, when a user places an order using the app, if the emotion is recognized as "sad," the app will suggest hot soup or comfort food. Along with the suggested menu, a message such as "You're feeling a little blue today. Warm your body and soul with hot soup or comfort food!" will be displayed.

[1687] Prompt Sentence Examples

[1688] A concrete example of a prompt input to a generative AI model might be the following text:

[1689] What foods should you suggest for users when they are feeling very busy and stressed?

[1690] Such a system allows services to be provided according to the user's emotional state, improving the user experience.

[1691] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1692] Step 1:

[1693] User Registration and Sample Collection Equipment Request

[1694] The user logs into the dedicated app and inputs the necessary information (name, address, contact details, health status) to request a specimen collection device. The server receives the input data and verifies the information. If there are no omissions or errors, the request details are saved in the database and the specimen collection device is shipped. A tracking number is generated and sent to the device.

[1695] Input: User registration information and request data

[1696] Output: Stores accurate request data and generates tracking numbers

[1697] Specific operations: Validation and storage process, generation of tracking number, notification

[1698] Step 2:

[1699] Sample collection and shipping

[1700] The user collects a specimen (e.g., a blood sample) using the specimen collection device they received. They then place the collected specimen in a designated return envelope and send it to the laboratory. The terminal records information such as the specimen collection date and time and type, and sends it to the server.

[1701] Input: Sample collection information (date, time, type)

[1702] Output: Send sample information to the server

[1703] Specific actions: Collecting samples, recording and transmitting information

[1704] Step 3:

[1705] Receipt of samples and initiation of analysis

[1706] The server receives a notification of sample receipt from the laboratory, updates the database, and then sends the sample information to the analyzer to start analysis.

[1707] Input: Specimen receipt notice from lab

[1708] Output: Instructions to update the database and start analysis

[1709] Specific operations: Database update, sending instruction to start analysis

[1710] Step 4:

[1711] Analysis and generation of initial judgment results

[1712] The analysis device analyzes the received sample and generates result data. The result data is sent to the server and input into the generative AI model. The AI ​​model analyzes the image of the sample and generates a primary judgment result. The server receives this result and stores it in a database.

[1713] Input: Sample analysis result data

[1714] Output: Generate and save the first judgment result

[1715] Specific operations: Running the analysis device, generating and sending data, analyzing it using an AI model, and saving the results

[1716] Step 5:

[1717] Sentiment analysis and follow-up with emotion engine

[1718] The device acquires the user's facial recognition and voice data and analyzes it with an emotion engine. The emotion engine determines the user's emotional state and sends it to the server. The server uses this information to create a notification message in a gentle manner according to the initial assessment result, and also provides instructions on the next step.

[1719] Input: User's facial recognition and voice data

[1720] Output: Sentiment analysis results and a soft-spoken message

[1721] Specific operations: Facial recognition and voice data acquisition, emotion analysis, message generation

[1722] Step 6:

[1723] Delivery tracking and notifications

[1724] The server tracks the delivery status and sends real-time notifications to the device, including messages to reduce the stress felt by the user based on the analysis results of the emotion engine.

[1725] Input: Delivery status data

[1726] Output: Real-time delivery status notification

[1727] Specific behavior: Tracking delivery status, generating and sending notification messages

[1728] Step 7:

[1729] Delivery completion and feedback

[1730] The user receives the food and rates it within the app. The device analyzes the user's rating and emotional state and sends the results to the server, which uses the information to improve the service in the future.

[1731] Input: User ratings and emotional state data

[1732] Output: Data for service improvement

[1733] Specific actions: getting and sending feedback, analyzing and storing data

[1734] 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.

[1735] 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.

[1736] 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.

[1737] [Fourth embodiment]

[1738] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1739] 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.

[1740] 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).

[1741] 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.

[1742] 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.

[1743] 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).

[1744] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1745] 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.

[1746] 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.

[1747] 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.

[1748] 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.

[1749] 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.

[1750] 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."

[1751] The present invention relates to a system that allows users to collect samples themselves and provides rapid and highly accurate primary determination results through AI analysis. Specific embodiments of the present invention are described below.

[1752] Test kit request

[1753] User:

[1754] Users log in to a dedicated web or mobile application and request a test kit from the menu, answering questions about their name, address, contact information, and health status.

[1755] Device:

[1756] The terminal verifies the information entered by the user to ensure there are no omissions or errors. Once verification is complete, the user presses the send request button to send the input details to the server.

[1757] server:

[1758] The server receives the request data from the user and stores it in a database. At the same time, it prepares the test kit and begins the process of sending it to the user's address. Once the process is complete, it generates a tracking number to track the delivery status and returns that information to the terminal.

[1759] Sample collection and shipping

[1760] User:

[1761] Users receive the test kit at home and follow the instructions in the kit to collect a sample. For example, for a blood test, users use a special lancet to collect blood from their fingertip. The collected sample is then placed in the enclosed return envelope and sent to the designated lab.

[1762] Device:

[1763] The device provides an interface for users to record information about the collected specimen (collection date, type, etc.), and the app also guides users through the process of properly packaging the specimen and mailing it to the lab.

[1764] Sample analysis and initial determination

[1765] server:

[1766] When the laboratory receives the sample, it notifies the server, which updates the database and notifies the user that the sample has been received, and then sends the information to the analyzer to begin analyzing the sample.

[1767] Analysis equipment:

[1768] The analysis device analyzes the received sample and generates the results, which are then sent back to the server.

[1769] server:

[1770] The server inputs the received analysis data into the AI ​​model, which then analyzes the images of the specimens. The AI ​​model aggregates the results of multiple specimen tests and evaluates the presence or absence of cancer-related markers.

[1771] AI model:

[1772] The AI ​​model generates a preliminary judgment result based on the sample analysis results, which is then sent back to the server.

[1773] Notification of initial assessment results and next steps

[1774] server:

[1775] The server receives the initial assessment results sent by the AI ​​model and notifies the user of the results, as well as providing instructions on the next steps the user should take (e.g., recommending further testing).

[1776] Device:

[1777] The device will notify the user of the initial assessment results and instructions on next steps via in-app push notification or email, where the user can review the details.

[1778] User:

[1779] The user takes the necessary action based on the notified initial assessment result and the next step. For example, if a detailed examination is required, the user makes an appointment.

[1780] This allows users to easily collect samples from the comfort of their own home and receive a rapid and accurate primary diagnosis of cancer.The present invention provides a system that improves the quality control and analytical accuracy of samples and effectively monitors the health status of users.

[1781] The processing flow will be explained below.

[1782] Step 1:

[1783] User:

[1784] Users launch the HELPO app and log in to their account. They then select "Apply for a Test Kit" from the menu and follow the instructions to enter the required information (name, address, contact information, and health status questions).

[1785] Step 2:

[1786] Device:

[1787] The terminal validates the information entered by the user, checking for missing or incorrect data, and when the send request button is pressed, sends the contents to the server. If the transmission is successful, a confirmation message is displayed to the user.

[1788] Step 3:

[1789] server:

[1790] The server receives the request data from the user and stores it in a database. It then prepares the test kit and arranges for it to be sent to the user's address. Once the delivery arrangements are complete, it generates a tracking number to track the delivery status and sends it to the terminal.

[1791] Step 4:

[1792] Device:

[1793] The terminal will display information to the user, including a tracking number, and notify them of the expected arrival date of the test kit.

[1794] Step 5:

[1795] User:

[1796] Users receive a test kit and follow the instructions in the kit to collect a sample (either blood, urine, or saliva), then place the sample in a designated return envelope and mail it to the lab.

[1797] Step 6:

[1798] Device:

[1799] The device provides an interface for users to record information about the collected specimen (collection date and time, specimen type, etc.), and the app also guides users through the process of sending the specimen to a laboratory.

[1800] Step 7:

[1801] server:

[1802] The server receives a notification of sample receipt from the laboratory, confirms that the laboratory has received the sample, updates the database with that information, and notifies the terminal.

[1803] Step 8:

[1804] Device:

[1805] The device will notify the user via push notification or email that the sample has arrived at the lab.

[1806] Step 9:

[1807] server:

[1808] The server sends the sample information to the analysis device and starts the analysis. The received analysis results are input into the AI ​​model and the analysis is carried out.

[1809] Step 10:

[1810] AI model:

[1811] The AI ​​model analyzes the images of the specimens, assessing the presence or absence of cancer-related markers and abnormalities, and generates analysis results that are sent back to the server.

[1812] Step 11:

[1813] server:

[1814] The server receives the analysis results from the AI ​​model, generates a preliminary judgment based on the results, and creates instructions for the next steps and sends them to the device.

[1815] Step 12:

[1816] Device:

[1817] The device will notify the user of the initial results and instructions for next steps. The user will receive detailed results via in-app notifications or email.

[1818] Step 13:

[1819] User:

[1820] The user checks the notified primary assessment result and follows the instructions for the next step, making an appointment for a detailed examination if necessary.

[1821] The above are the specific processing steps and their details of the system. This process allows users to receive a simple and highly accurate primary cancer diagnosis from the comfort of their own home.

[1822] Example 1

[1823] 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."

[1824] In the prior art, when a user collects a sample themselves and has it analyzed at a specialized institution, it is difficult to obtain a rapid and accurate determination result. Furthermore, there are challenges in controlling the quality of the sample and improving the accuracy of the analysis results. Furthermore, specific instructions regarding the next steps the user should take are not provided, which may delay appropriate action. The present invention aims to solve these problems and provide a system that allows a user to easily collect a sample from home and obtain a rapid and accurate initial determination result.

[1825] 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.

[1826] In this invention, the server includes means for a user to request a kit for collecting a specimen themselves, means for a terminal to verify information entered by the user and send it to the server, means for the server to store the received information in a database and ship a test kit, a testing device for analyzing the specimen after receiving it, means for generating analysis results and sending the data to the server, means for the server to input the analysis data into an AI model and generate a primary determination result, means for notifying the user of the primary determination result, and means for providing instructions regarding the next step. This enables the user to obtain a primary determination result quickly and accurately.

[1827] "User" refers to an individual who uses the system to collect specimens and receive analytical results.

[1828] A "specimen" refers to a biological substance such as blood, urine, or saliva that is collected by the user and subjected to testing.

[1829] "Kit" refers to a set containing tools that a user can use to collect a specimen themselves.

[1830] "Terminal" refers to an information processing device used by a user, such as a computer, smartphone, or tablet.

[1831] "Server" refers to the central processing unit that receives requests from users, processes and stores data, and returns results to users.

[1832] A "database" refers to a system that allows a server to efficiently store, manage, and search information.

[1833] "Testing device" refers to a device that analyzes received specimens and generates result data.

[1834] "AI model" refers to software that includes algorithms for using artificial intelligence to analyze data and generate initial assessment results.

[1835] "Primary assessment result" refers to the initial analysis result generated by the AI ​​model and refers to the evaluation information provided to the user.

[1836] "Instructions" refers to guidance or recommendations regarding the next action a user should take after receiving the initial assessment results.

[1837] This invention relates to a system that allows users to collect samples themselves and provides rapid and highly accurate initial results through analysis by an AI model. This system consists of multiple components, including users, terminals, and servers.

[1838] Test kit request

[1839] User:

[1840] Users log in to a dedicated web or mobile application and request a test kit from the menu, answering questions about their name, address, contact information, and health status.

[1841] Device:

[1842] The terminal validates the information entered by the user to ensure there are no missing or incorrect information. For example, it uses form validation to check that address fields are not blank and that phone numbers are entered in the correct format. Once the validation is complete, the user presses the send button to send the input information to the server.

[1843] server:

[1844] The server receives the request data from the user and stores that information in a database. For example, MySQL or PostgreSQL is used for the database. The server also initiates the procedure for shipping the test kit and requests the shipping company to ship the kit. At this time, the server generates a tracking number to track the delivery status and returns that information to the terminal.

[1845] Sample collection and shipping

[1846] User:

[1847] Users receive the test kit at home and collect the sample according to the instructions included in the kit. For example, for a blood test, a special lancet is used to collect blood from the fingertip. The collected sample is placed in the enclosed return envelope and sent to the designated lab. The user then records the date and time of collection and the type of sample in the application.

[1848] Device:

[1849] The terminal records the collection information entered by the user and stores it in a database. The terminal also displays a screen that guides the user through the process of safely packaging the specimen and sending it to the lab.

[1850] Sample analysis and initial determination

[1851] server:

[1852] When the laboratory receives the specimen, it notifies the server, which updates the database and notifies the user that the specimen has been received, and then the server sends the information to the analyzer to begin analyzing the specimen.

[1853] Analysis equipment:

[1854] The analysis device analyzes the received sample and generates result data, for example, using a spectrophotometer or flow cytometer, and the analysis result data is sent back to the server.

[1855] server:

[1856] The server inputs the received analysis data into a generative AI model, which is built using TensorFlow or PyTorch, for example. The AI ​​model generates a primary judgment result based on the sample analysis results and returns the result to the server.

[1857] Notification of initial assessment results and next steps

[1858] server:

[1859] The server receives the initial assessment results sent by the AI ​​model and notifies the user of the results, along with instructions on what next steps to take (e.g., recommending further testing).

[1860] Device:

[1861] The device will notify the user with the initial assessment results and instructions on next steps via an in-app push notification or email, and the user can open the app for more details.

[1862] User:

[1863] The user takes the necessary action based on the notified primary assessment result and the next step. For example, if a detailed examination is required, the user makes an appointment.

[1864] Prompt Sentence Examples

[1865] "Please generate a preliminary AI result based on the analysis results of the sample I provide. Please write a sentence in natural language that explains the entire process from requesting a test kit to receiving the results."

[1866] This allows users to easily collect samples from the comfort of their own home and receive a rapid and highly accurate initial diagnosis. This system improves the quality control and analysis accuracy of samples, enabling effective monitoring of users' health conditions.

[1867] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1868] Step 1:

[1869] User:

[1870] Log in to the dedicated web application or mobile application. The information required for login is your user ID and password. Once you have successfully logged in, your user dashboard will be displayed.

[1871] input:

[1872] User ID and password

[1873] output:

[1874] Login success message, dashboard display

[1875] Specific behavior:

[1876] A user opens the app, enters their user ID and password on the login screen, and clicks the "Login" button. The system verifies the authentication information, and if it is correct, the dashboard is displayed.

[1877] Step 2:

[1878] User:

[1879] Request a test kit: Users select the "Request a test kit" option from the menu and answer questions about their name, address, contact information, and health status.

[1880] input:

[1881] Name, address, contact information, and health status

[1882] output:

[1883] Request confirmation message and input details display screen

[1884] Specific behavior:

[1885] The user enters the required information on the "Request a Test Kit" screen and clicks the "Submit" button. A confirmation message for the entered information is displayed on the screen.

[1886] Step 3:

[1887] Device:

[1888] Validate user-entered information and format submitted data.

[1889] input:

[1890] User-provided name, address, contact information, and health status answers

[1891] output:

[1892] Verified data, data sent to server

[1893] Specific behavior:

[1894] The device checks the contents of the input fields, formats them as needed (e.g., checks if the address field is empty, verifies that the contact information is in the correct format), and prepares the data to be sent to the server.

[1895] Step 4:

[1896] server:

[1897] It receives the request data, stores the information in a database, and processes the shipping of the test kit.

[1898] input:

[1899] Request data sent from the device

[1900] output:

[1901] Request information and tracking number stored in the database

[1902] Specific behavior:

[1903] The server receives the request data and saves it in a database. Then, it requests the shipping company to ship the test kit via API. It receives a tracking number from the shipping company and returns it to the user.

[1904] Step 5:

[1905] User:

[1906] After receiving the test kit, collect the sample according to the instructions, place the collected sample in the return envelope, and send it to the designated laboratory.

[1907] input:

[1908] Test kit instructions, user samples

[1909] output:

[1910] Collected specimen and message of completion of sending

[1911] Specific behavior:

[1912] The user follows the instructions to collect a sample (e.g., using a lancet to collect blood from a fingertip), seals it in a return envelope, and then goes to the post office to mail it off to the lab.

[1913] Step 6:

[1914] server:

[1915] When the lab receives the sample, it receives a notification and updates the database with the information, which is then sent to the analyzer.

[1916] input:

[1917] Acknowledgment from the lab

[1918] output:

[1919] Database update information, data sent to analysis equipment

[1920] Specific behavior:

[1921] When the laboratory receives the sample, it notifies the server, which updates the database with the receipt information and sends an analysis request to the analyzer.

[1922] Step 7:

[1923] Analysis equipment:

[1924] The received samples are analyzed, and analysis result data is generated and sent to the server.

[1925] input:

[1926] Sample information sent to the analyzer

[1927] output:

[1928] Analysis result data

[1929] Specific behavior:

[1930] The analytical device analyzes the sample, generates the result data, and sends it to the server. For example, a spectrophotometer or flow cytometer is used.

[1931] Step 8:

[1932] server:

[1933] The received analysis data is input into the AI ​​model to generate a primary judgment result, which is then notified to the user.

[1934] input:

[1935] Analysis result data

[1936] output:

[1937] Primary judgment results, user notification data

[1938] Specific behavior:

[1939] The server sends the analysis results data to the AI ​​model, which generates a first-order judgment. The generation AI model uses pre-trained TensorFlow or PyTorch, and notifies the user of the result.

[1940] Step 9:

[1941] Device:

[1942] The user is notified of the initial assessment results and instructions regarding next steps.

[1943] input:

[1944] Initial assessment results and instructions on next steps

[1945] output:

[1946] Notification Message

[1947] Specific behavior:

[1948] The device will notify the user of the initial assessment results and next steps via in-app push notification or email.

[1949] Step 10:

[1950] User:

[1951] Respond according to the notified initial assessment result and next steps, for example, make an appointment for a detailed examination.

[1952] input:

[1953] Initial assessment results and instructions on next steps

[1954] output:

[1955] Detailed examination reservation information, etc.

[1956] Specific behavior:

[1957] The user confirms the notification and takes the necessary next steps (e.g., schedules an appointment for a detailed examination if necessary).

[1958] (Application example 1)

[1959] 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."

[1960] Conventional home sample collection and analysis systems lack sufficient support for users in the accurate sample collection process, resulting in issues with sample collection accuracy and adherence to procedures. Furthermore, methods for quickly and accurately notifying users of sample analysis results are limited, and clear guidance on how to proceed to the next step is lacking. To address these issues, a system is needed that allows users to intuitively and reliably collect samples and instantly receive analysis results.

[1961] 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.

[1962] In this invention, the server includes means for a user to request a kit for collecting a specimen by themselves, means for the user to collect and send the specimen, a testing device for analyzing the specimen after receiving the specimen, means for analyzing the analysis result using an AI model and generating a primary determination result, means for notifying the user of the primary determination result, means for providing instructions regarding the next step, means for the user to receive visual and audio guidance by wearing a head-mounted display device, and means for checking the user's specimen collection procedure in real time, thereby enabling the user to reliably collect a specimen and obtain a rapid and highly accurate analysis result.

[1963] "User" means an individual or organization that uses the system to collect specimens and receive analysis and notification of results.

[1964] A "kit for collecting specimens" is a set that includes tools and instructions that allow users to collect specimens safely and accurately themselves.

[1965] A "method of requesting a kit" is how a user places an order for a test kit through a web or mobile application.

[1966] "Means for sending specimens" refers to a method that provides procedures and tools for users to send collected specimens to a designated analysis laboratory.

[1967] A "test device" is a physical or chemical device that analyzes a received specimen and generates a result.

[1968] "AI Model" means the artificial intelligence algorithms and models used to generate a preliminary determination result based on the analysis of a received specimen.

[1969] The "means for generating a primary judgment result" is a method for using an AI model to summarize the analysis results of a sample as a primary evaluation.

[1970] The "means for notifying the user of the primary determination results" refers to a communication means or notification system for immediately notifying the user of the analysis results.

[1971] The "means for providing instructions regarding the next step" is a method for guiding the user on the next action or necessary response to be taken based on the results of the primary determination.

[1972] A "head-mounted display device" is a device that displays visual and audio information when worn by a user.

[1973] "Means for receiving visual and audio guidance" refers to a method in which the user is provided with visual and audio guidance via a head-mounted display to guide them through the sample collection procedure and delivery method.

[1974] "Means for verifying a user's sample collection procedures in real time" refers to a method for using a head-mounted display to monitor a user's procedures in real time and verify accuracy and compliance.

[1975] The present invention relates to a system that includes a series of processes in which a user collects a sample themselves and receives visual and audio guidance using a head-mounted display device. The system comprises the following steps:

[1976] First, a user wears a head-mounted display device with a dedicated application installed and requests a test kit. The user logs in to the application and follows the on-screen instructions to answer questions about their personal information and health status. This information is displayed visually through the head-mounted display, and a voice assistant guides the input. The server receives this information, processes the request, and delivers the test kit to the user's address.

[1977] Next, the user collects a sample at home using the provided test kit. The head-mounted display device provides step-by-step instructions visually and audibly. For example, for a blood test, the user is guided on how to use the lancet and properly collect the sample, with real-time confirmation of the procedure. Once the sample is collected, it is placed in the provided return envelope and sent to the designated analysis lab.

[1978] When the sample arrives at the lab, the information is sent to the server, which updates the information and notifies the user via a push notification on the head-mounted display that the sample has been received. The testing device then analyzes the sample and generates the results, which are then sent back to the server.

[1979] The server inputs the received analysis results into the generative AI model to generate a preliminary assessment result, which is then communicated to the user via a head-mounted display, where the user can check the results in real time and receive visual and audio instructions regarding next steps (e.g., recommending further testing).

[1980] (Hardware and Software Use)

[1981] A common device such as Oculus Quest 2 is used as the head-mounted display device. The VoiceAssistant library is used for the voice assistant, and the requests library is used for communication processing. The hmd_display library is used for display management. This allows users to intuitively follow prompts and smoothly carry out the process from sample collection to checking analysis results.

[1982] (Example)

[1983] When the user wears the head-mounted display device and gives a voice command such as "Hello, please tell me the procedure for sample collection," visual and voice guidance begins. Similarly, the system operates appropriately when the user gives voice commands following prompts such as "I would like to check the current test results" to send the sample and receive notification of the analysis results.

[1984] This allows users to collect samples easily and safely from the comfort of their own home and receive prompt and highly accurate initial results.

[1985] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1986] Step 1:

[1987] The user launches the application and requests a test kit.

[1988] Specific behavior:

[1989] The user wears a head-mounted display device and logs in to the application. Next, they follow the on-screen instructions to answer questions about their personal information and health status. This information is then sent to the server as input data.

[1990] Input: User information (name, address, health status, etc.)

[1991] Output: A request for a test kit is sent to the server.

[1992] Step 2:

[1993] The server receives and processes requests for test kits.

[1994] Specific behavior:

[1995] The server validates the received request data and stores it in a database. After checking for any missing or incorrect information, it initiates the shipping process for the test kit and obtains a tracking number from the delivery company. The tracking number is then returned to the user.

[1996] Input: Request data

[1997] Output: Tracking number is sent to the user

[1998] Step 3:

[1999] The user receives the test kit and collects the specimen.

[2000] Specific behavior:

[2001] The user opens the test kit and follows the visual and audio guidance on the head-mounted display device to collect a sample, such as using a lancet to draw blood from a fingertip. The user is then checked in real time during the process.

[2002] Input: Test kit, visual and audio guidance

[2003] Output: Collected specimen

[2004] Step 4:

[2005] The user sends the collected specimen.

[2006] Specific behavior:

[2007] The collected sample is placed in the enclosed return envelope and sent to the designated analysis lab, and the head-mounted display device provides visual and audio guidance on proper packaging and mailing instructions.

[2008] Input: Collected specimen, return envelope

[2009] Output: Specimen sent to the lab

[2010] Step 5:

[2011] The server confirms receipt of the specimen.

[2012] Specific behavior:

[2013] When the sample arrives at the lab, the information is sent to the server, which updates the information and sends a push notification to the user to let them know the sample has been received.

[2014] Input: Specimen receipt notice

[2015] Output: Acknowledgement to user

[2016] Step 6:

[2017] The testing device analyzes the sample and generates a result.

[2018] Specific behavior:

[2019] The testing device analyzes the sample received from the server and generates the result data, which is then sent back to the server.

[2020] Input: Sample

[2021] Output: Analysis result data

[2022] Step 7:

[2023] The server inputs the analysis results into the AI ​​model and generates a primary judgment result.

[2024] Specific behavior:

[2025] The server inputs the received analysis result data into the generative AI model to generate a primary judgment result, which is then sent back to the server.

[2026] Input: Analysis result data

[2027] Output: Primary judgment result

[2028] Step 8:

[2029] The server notifies the user of the results of the initial judgment.

[2030] Specific behavior:

[2031] The server notifies the user of the generated primary judgment result via the head-mounted display device. The user receives a push notification and can check the details.

[2032] Input: Primary judgment result

[2033] Output: User notification

[2034] Step 9:

[2035] The server provides instructions to the user regarding next steps.

[2036] Specific behavior:

[2037] Based on the results of the initial assessment, the server generates instructions regarding the next steps the user should take (e.g., recommending a detailed examination) and provides them to the user via the head-mounted display device.

[2038] Input: Primary judgment result

[2039] Output: Instructions for next steps

[2040] 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.

[2041] The present invention combines a system in which users collect samples themselves and provide rapid and highly accurate initial results through AI analysis with an emotion engine that recognizes the user's emotions. The present invention aims to improve the quality of the testing experience by enabling appropriate responses and follow-ups based on the user's emotional state. Specific embodiments of the present invention are described below.

[2042] Test kit request

[2043] User:

[2044] Users log in to a dedicated web or mobile application, request a test kit from the menu, and enter the required information (name, address, contact information, and questions about their health status).

[2045] Device:

[2046] The terminal validates the information entered by the user to ensure there are no missing or incorrect information. If the request is correct, it sends the input to the server. If the transmission is successful, a confirmation message is displayed to the user.

[2047] server:

[2048] The server receives the request data from the user and stores it in a database. It prepares the test kit and arranges for it to be sent to the user's address. It generates a tracking number and notifies the terminal.

[2049] Sample collection and shipping

[2050] User:

[2051] The user receives the test kit and collects the sample according to the instructions in the kit (e.g., for blood samples, use a special lancet), places the sample in the designated return envelope, and sends it to the lab.

[2052] Device:

[2053] The device provides an interface for users to record information about the collected specimen (collection date and time, specimen type, etc.), and supports the specimen sending procedure within the app.

[2054] Sample analysis and initial determination

[2055] server:

[2056] The server receives a notification of sample receipt from the laboratory, updates the database with the receipt information, notifies the user that the sample has arrived, and then sends the sample information to the analyzer to begin analysis.

[2057] Analysis equipment:

[2058] The analyzer analyzes the received sample and generates the results, which are then sent to the server.

[2059] server:

[2060] The server inputs the received analysis data into the AI ​​model, which then analyzes the image of the sample. The AI ​​model then generates a primary judgment result based on the sample test results.

[2061] AI model:

[2062] The AI ​​model generates analysis results and sends them back to the server.

[2063] Emotion engine response and notification

[2064] server:

[2065] The server receives the analysis results from the AI ​​model and generates a primary judgment result. Next, it uses an emotion engine to recognize the user's emotional state. The emotion engine analyzes behavioral data (facial expressions, operation timing, voice, etc.) when the user uses the app to determine the user's emotional state. Based on this emotional information, the content and method of notification messages are adjusted.

[2066] Device:

[2067] The device notifies the user of the initial assessment results and instructions for the next step. Based on the analysis results of the emotion engine, the device notifies the user in a gentle manner so as not to cause stress to the user. If necessary, the device also provides follow-up notifications and emotionally sensitive health advice.

[2068] Specific examples

[2069] 1. Execute the request:

[2070] A user requests a test kit and the information is sent to the server, which dispatches the kit and notifies the user.

[2071] 2. Sample collection and shipping:

[2072] The user receives the test kit, collects a blood sample, and sends it to the laboratory, which receives the sample and sends it to the analyzer.

[2073] 3. Analysis and Notification:

[2074] The AI ​​model analyzes the sample and generates a preliminary assessment. Based on this assessment, the emotion engine analyzes the user's emotional state and creates an appropriate notification message. The device then notifies the user of this message and the next steps.

[2075] 4. Follow-up:

[2076] If necessary, provide users with additional follow-up notifications and empathetic health advice.

[2077] This allows users to conveniently collect samples from the comfort of their own home and receive a quick and accurate initial result. Furthermore, the combination of an emotion engine enables appropriate responses based on the user's emotional state, improving the overall quality of the testing experience.

[2078] The processing flow will be explained below.

[2079] Step 1:

[2080] User:

[2081] Users launch the HELPO app and log in to their account. They then select "Apply for a Test Kit" from the menu and follow the instructions to enter the required information (name, address, contact information, and health status questions).

[2082] Step 2:

[2083] Device:

[2084] The terminal verifies the information entered by the user to check for omissions or errors. When the send request button is pressed, the input details are sent to the server. If the transmission is successful, a confirmation message is displayed to the user.

[2085] Step 3:

[2086] server:

[2087] The server receives the request data from the user and stores it in a database. It then prepares the test kit and sends it to the user's address. Once the delivery arrangements are complete, it generates a tracking number to track the delivery status and notifies the terminal.

[2088] Step 4:

[2089] Device:

[2090] The terminal will display information to the user, including a tracking number, and notify them of the expected arrival date of the test kit.

[2091] Step 5:

[2092] User:

[2093] Users receive a test kit and collect a sample (either blood, urine, or saliva) according to the instructions enclosed with the kit. The collected sample is placed in a designated return envelope and mailed to the lab.

[2094] Step 6:

[2095] Device:

[2096] The device provides an interface for users to record information about the collected specimen (collection date and time, specimen type, etc.), and the app also guides users through the process of sending the specimen to a laboratory.

[2097] Step 7:

[2098] server:

[2099] The server receives a notification of sample receipt from the laboratory, confirms that the laboratory has received the sample, updates the database with that information, and notifies the terminal.

[2100] Step 8:

[2101] Device:

[2102] The device will notify the user via push notification or email that the sample has arrived at the lab.

[2103] Step 9:

[2104] server:

[2105] The server sends the sample information to the analysis device and starts the analysis. After receiving the sample analysis results, it inputs them into the AI ​​model and performs additional analysis.

[2106] Step 10:

[2107] AI model:

[2108] The AI ​​model analyzes the images of the specimens, assessing the presence or absence of cancer-related markers and abnormalities, and generates analysis results that are sent back to the server.

[2109] Step 11:

[2110] server:

[2111] The server generates a preliminary judgment result using the analysis results received from the AI ​​model, and simultaneously uses an emotion engine to recognize the user's emotions and adjust notification messages based on the user's emotional state.

[2112] Step 12:

[2113] Emotion Engine:

[2114] The emotion engine determines emotions based on behavioral data (facial expressions, operation timing, voice, etc.) when the user uses the app, and provides this information to the server to optimize the content of notification messages.

[2115] Step 13:

[2116] server:

[2117] Based on the information from the emotion engine, the server creates a primary judgment result and instructions for the next step using expressions to reduce the user's stress, and sends them to the terminal.

[2118] Step 14:

[2119] Device:

[2120] The device notifies the user of the results of the initial assessment and instructions on next steps, with the content of the notification optimized according to the user's emotional state.

[2121] Step 15:

[2122] User:

[2123] The user checks the notified initial assessment results and next steps and takes the necessary action. For example, if a detailed examination is recommended, the user can make an appointment. The device also provides support during this process.

[2124] Step 16:

[2125] server:

[2126] If necessary, the system will send users additional follow-up notifications and provide health advice, allowing them to continually manage their health.

[2127] Example 2

[2128] 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."

[2129] In conventional sample analysis systems, the process of users collecting samples and sending them to a laboratory is time-consuming, and it often takes a long time for results to be notified. Furthermore, because feedback and responses do not take into account the user's emotional state, users may feel stressed or anxious when receiving test results. The present invention aims to solve these problems and provide fast and accurate sample analysis and responses that take into account the user's emotional state.

[2130] 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.

[2131] In this invention, the server includes means for a user to request a kit for collecting a sample themselves, means for the user to collect the sample and send it, a testing device for analyzing the sample after receiving it, means for analyzing the analysis results using an AI model and generating a primary determination result, means for using an emotion engine that recognizes the user's emotional state and adjusts the content and method of a notification message, and means for notifying the user of the primary determination result and instructions regarding the next step. This allows the user to receive a primary determination of their sample quickly and accurately from the comfort of their own home, and the emotion engine provides an appropriate response, thereby reducing stress and anxiety when receiving the test results.

[2132] "User" refers to the entity that uses this system to collect specimens and receive analysis results.

[2133] "Specimen" refers to the biological material to be analyzed (e.g., blood, saliva, etc.).

[2134] "Means for requesting a kit" refers to the functionality that allows a user to order a specimen collection kit using a dedicated application.

[2135] "Means of sending" refers to the mechanism by which the user sends the collected specimen to the laboratory (e.g., return envelope, sending confirmation function).

[2136] "Laboratory equipment" refers to the equipment and software used to analyze samples sent to a laboratory and generate results.

[2137] "AI model" refers to an artificial intelligence algorithm that analyzes samples based on data obtained from an analytical device and generates a primary judgment result.

[2138] "Emotion engine" refers to a function that analyzes user behavior data (e.g., facial expressions, operation timing, voice, etc.) and determines the user's emotional state.

[2139] "Means for analyzing a sample" refers to the entire process of receiving a sample and performing analysis using a testing device.

[2140] "Means for generating a preliminary judgment result" refers to the process of outputting a preliminary test result based on data analyzed by an AI model.

[2141] "Means for adjusting the content and method of notification messages" refers to a mechanism for optimizing the expression of notification messages and notification methods according to the user's emotional state determined by the emotion engine.

[2142] "Means for providing instructions regarding next steps" refers to a function that informs the user of future actions to be taken or the need for additional testing based on the initial assessment results.

[2143] The present invention combines a system in which users collect samples themselves and provide rapid and highly accurate initial results through AI analysis, with an emotion engine that recognizes the user's emotions. Specific embodiments of this system are described below.

[2144] Test kit request

[2145] User

[2146] Users log in to the dedicated web or mobile application, click the "Request a Test Kit" button from the menu, and enter the required information (name, address, contact information, and questions about their health status).

[2147] Terminal

[2148] The device verifies the information entered by the user in real time. For example, it checks to make sure the address field is not empty, the phone number is not invalid, etc. If there are no missing or incorrect information, it sends the input details to the server as an HTTP POST request. If the transmission is successful, it displays a confirmation message to the user saying "Request accepted."

[2149] server

[2150] The server receives the request data from the user and saves it in a database. It inserts it into the database using an SQL query, and if successful, prepares the test kit. It then initiates the shipping process for the test kit and generates a tracking number. It then includes this tracking number in the HTTP response to notify the user's device.

[2151] Sample collection and shipping

[2152] User

[2153] The user receives the test kit and collects the sample according to the manual included with the kit. For example, for blood samples, a special lancet is used to collect a small amount of blood from the fingertip. The collected sample is then placed in a special container. Next, the user places the collected sample in the return envelope provided and sends it to the lab. After sending it, the user presses the "Sample sent" button in the app.

[2154] Terminal

[2155] The terminal provides an interface for recording the user's sending procedures. For example, when the send button is pressed, the collection date and time and type of specimen are recorded in the database. If the sending confirmation is successful, a notification "Specimen sending has been completed" is displayed to the user.

[2156] Sample analysis and initial determination

[2157] server

[2158] The server receives a notification of sample receipt from the lab. This notification is typically sent to the server via an HTTP POST request. The server records the receipt information in a database and notifies the user that the sample has arrived. The server then sends the sample information received from the lab to the analyzer, which then begins analysis.

[2159] analysis device

[2160] The analyzer analyzes the received sample and generates the results. For example, in the case of a blood sample, it uses equipment to detect specific markers in the blood. The result data is sent to the server in CSV or JSON format.

[2161] server

[2162] After receiving the analysis results, the server inputs the data into the AI ​​model, for example, by sending the analysis results to the AI ​​model as an HTTP POST request.

[2163] AI model

[2164] The AI ​​model generates a preliminary assessment result based on the analysis results. For example, an image recognition model is used to detect abnormal cells in the blood. Once the preliminary assessment result is generated, it is sent back to the server.

[2165] server

[2166] The server receives the initial judgment results from the AI ​​model, stores them in a database, and prepares to notify the user.

[2167] Emotion engine response and notification

[2168] server

[2169] The server calls the emotion engine and collects data to determine the user's emotional state. For example, facial expression data and operation timing when the user uses the app are acquired from cameras and sensors and input into the emotion engine. The emotion engine analyzes this data and determines the user's emotional state (e.g., tension, relief, stress, etc.).

[2170] Terminal

[2171] The device notifies the user of the initial results and instructions for the next step. For example, it may say, "The test results show an abnormality. Please consult your doctor for details." The wording of the notification is adjusted based on the analysis results of the emotion engine to avoid stressing the user. If necessary, the device may provide follow-up notifications or emotionally sensitive health advice.

[2172] Specific examples

[2173] 1. Executing the request

[2174] The user logs in to the application and requests a test kit. The terminal sends the request to the server, which then dispatches the kit and sends a tracking number to the terminal. The terminal then displays a confirmation message.

[2175] 2. Sample collection and shipping

[2176] The user collects a blood sample using the test kit and sends it to the lab in a return envelope. The terminal records the sending procedure and displays a notification of completion.

[2177] 3. Analysis and Notification

[2178] The server receives a receipt from the lab and sends the sample information to the analyzer. The analyzer sends the results to the server, which inputs them into the AI ​​model. The AI ​​model generates a preliminary judgment result and sends it back to the server. The server uses an emotion engine to determine the user's emotional state and creates an appropriate notification. The device displays the notification.

[2179] 4. Follow-up

[2180] If necessary, the server will send the user additional follow-up notifications and health advice, which the device will display and prompt the user to take appropriate action.

[2181] Prompt Sentence Examples

[2182] Here are some example prompts to input to a generative AI model:

[2183] The server dispatches the test kit requested by the user. A tracking number is assigned to the test kit and notified to the user. The user then receives the test kit, collects a blood sample according to the specified procedure, and sends it to the lab. The lab receives the sample, analyzes it, and sends the results to the server. The server uses an AI model to generate a preliminary assessment result and an emotion engine to analyze the user's emotional state and create an appropriate notification message.

[2184] This system allows users to easily collect samples from the comfort of their own home and receive a rapid, highly accurate initial result. Furthermore, the combination of an emotion engine enables appropriate responses based on the user's emotional state, improving the overall quality of the testing experience.

[2185] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2186] Step 1:

[2187] User:

[2188] Users log in to a dedicated web or mobile application, click the "Request a Test Kit" button from the menu, and then enter the required information, such as name, address, contact information, and health questions. This data serves as input for the next processing step.

[2189] Step 2:

[2190] Device:

[2191] The terminal verifies the information entered by the user in real time. For example, it checks to see if the address field is empty or if an invalid phone number has been entered. This ensures the accuracy of the data. The verified data is sent as input to the next process. If there are no omissions or errors, it is sent to the server as an HTTP POST request. If the transmission is successful, a confirmation message "Request accepted" is displayed to the user. This message becomes the output.

[2192] Step 3:

[2193] server:

[2194] The server receives the request data from the user. To save the input data in a database, it generates an SQL query and inserts it into the database. If the database insertion is successful, it begins preparing the test kit. Next, it carries out shipping procedures and generates a tracking number. It includes the generated tracking number in an HTTP response and sends it to the user's device. This tracking number becomes the output.

[2195] Step 4:

[2196] User:

[2197] The user receives the test kit and collects the sample according to the manual included in the kit. Specifically, for blood samples, a special lancet is used to collect a small amount of blood from the fingertip. The collected sample is then placed in a special container. This sample becomes the input for the next step.

[2198] Step 5:

[2199] User:

[2200] The user places the collected sample in the return envelope provided and sends it to the lab. The lab's address is pre-printed on the return envelope, so no additional information is required. The sent sample will be used as input for the next step. After sending the sample, press the "Sample sent" button in the app.

[2201] Step 6:

[2202] Device:

[2203] The terminal provides an interface for recording the user's sending procedure. This interface receives data such as the collection date and time and the type of specimen as input and records it in a database. If the sending confirmation is successful, a notification stating "Specimen sending completed" is displayed to the user as output.

[2204] Step 7:

[2205] server:

[2206] The server receives a sample receipt notification from the laboratory. The notification from the laboratory is sent to the server via an HTTP POST request. This receipt information is recorded in a database and the user is notified that the sample has arrived. To send the received sample information to the analyzer, an HTTP request is generated to send data to the analyzer. The output of this process is the sample information sent to the analyzer.

[2207] Step 8:

[2208] Analysis equipment:

[2209] The analyzer analyzes the received sample and generates the results. For example, in the case of a blood sample, it uses equipment to detect specific markers. The analysis results are sent to the server in CSV or JSON format. These analysis results are the output.

[2210] Step 9:

[2211] server:

[2212] The server receives the analysis results and inputs the data into the AI ​​model. It sends the analysis results to the AI ​​model as an HTTP POST request. The input for the AI ​​model includes this analysis data.

[2213] Step 10:

[2214] AI model:

[2215] The AI ​​model generates a primary judgment result based on the analysis results. For example, an image recognition model is used to detect abnormal cells in the blood. Once the primary judgment result is generated, it is sent back to the server. This primary judgment result becomes the output.

[2216] Step 11:

[2217] server:

[2218] The server receives the initial judgment results from the AI ​​model and stores them in a database. Next, it calls the emotion engine and collects data to determine the user's emotional state. For example, it uses a camera or sensor to acquire facial expression data and operation timing, and inputs this data into the emotion engine. The emotional state data generated by this analysis is the output.

[2219] Step 12:

[2220] server:

[2221] The server adjusts the content and format of the notification message based on the analysis results of the emotion engine. For example, it creates a notification using gentler language so that the user does not feel stressed. The adjusted notification message is sent to the device. The adjusted notification message becomes the output.

[2222] Step 13:

[2223] Device:

[2224] The device notifies the user of the initial assessment results and instructions for the next step. Based on the analysis results of the emotion engine, the device displays notifications tailored to prevent the user from feeling stressed. If necessary, it provides follow-up notifications and emotionally sensitive health advice. This notification is the output.

[2225] (Application example 2)

[2226] 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."

[2227] Conventional sample analysis systems have been unable to respond to the user's emotional state between the time the user collects the sample and the time they receive the analysis results, resulting in an unsatisfactory user experience. Food delivery services, in particular, require services that take the user's emotional state into consideration, but lack mechanisms for addressing this. Therefore, it is necessary to improve the quality of service by analyzing the user's emotional state and providing appropriate responses and follow-up.

[2228] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[2229] In this invention, the server includes: means for a user to request a device for collecting a sample themselves; means for the user to collect and send the sample; an analysis device for analyzing the sample after receiving the sample; means for analyzing the analysis result using a generative AI model and generating a primary determination result; means for notifying the user of the primary determination result; means including an emotion engine for analyzing the user's emotional state and providing responses and instructions according to the emotion; and means for providing instructions regarding the next step. This enables the provision of services according to the user's emotional state, improving the user experience.

[2230] A "user" is an individual who utilizes the system to collect specimens and receive analytical results.

[2231] A "specimen" is a biological sample that a user collects and sends for analysis.

[2232] "Equipment" refers to the tools and equipment required by the user to collect a specimen.

[2233] "Requesting means" is the ability for a user to request an instrument for collecting a specimen.

[2234] "Means for sending" is a function that allows the user to send the collected specimen to a specified location.

[2235] An "analytical device" is a device for analyzing a sample and generating a result.

[2236] A "generative AI model" is an artificial intelligence model that generates a primary judgment result based on the analysis results.

[2237] The "primary judgment result" is the first analytical evaluation derived by the generative AI model.

[2238] The "notification means" is a function for notifying the user of the primary judgment result.

[2239] An "emotion engine" is a system that analyzes the user's emotional state and responds or gives instructions based on that data.

[2240] The "instructions regarding the next step" are instructions indicating the specific action to be taken next based on the results of the primary determination and the user's emotional state.

[2241] A "food delivery service" is a service that delivers food to a location specified by the user.

[2242] This invention combines a system in which users collect samples at home and provide rapid and highly accurate initial results through analysis by a generative AI model with an emotion engine that recognizes the user's emotional state. This system aims to improve the quality of the service experience by enabling appropriate responses and follow-ups according to the user's emotional state.

[2243] User

[2244] User Registration and Ordering

[2245] Users log in to a dedicated food delivery app and search for their favorite meal. The app uses the built-in camera and microphone to capture the user's facial recognition and voice data, which is then analyzed by an emotion engine to understand the user's emotional state.

[2246] server

[2247] Executing the request

[2248] The server receives the user's request for the specimen collection equipment, verifies the accuracy of the information, and then ships the specimen collection equipment to the user's address, generates a tracking number, and notifies the terminal.

[2249] Sample analysis

[2250] After receiving the sample from the lab, the server updates the sample information in the database and notifies the user that the sample has arrived. The server then sends the sample information to the analyzer to begin analysis. The analysis results are then input into the AI ​​model, which generates a preliminary judgment result.

[2251] Emotional state analysis

[2252] The emotion engine on the server analyzes the user's emotional state based on facial recognition and voice data when using the app. This emotional information is then analyzed using a language processing model to create an appropriate message.

[2253] Terminal

[2254] Order Support and Notifications

[2255] The device receives the analysis results and notifies the user. Based on the analysis results from the emotion engine, the device provides a notification message and instructions on the next step in a gentle manner that reflects the user's emotional state. The device provides real-time delivery tracking information and a message that is sensitive to the user's emotions.

[2256] Adding specific examples

[2257] For example, when a user places an order using the app, if the emotion is recognized as "sad," the app will suggest hot soup or comfort food. Along with the suggested menu, a message such as "You're feeling a little blue today. Warm your body and soul with hot soup or comfort food!" will be displayed.

[2258] Prompt Sentence Examples

[2259] A concrete example of a prompt input to a generative AI model might be the following text:

[2260] What foods should you suggest for users when they are feeling very busy and stressed?

[2261] Such a system allows services to be provided according to the user's emotional state, improving the user experience.

[2262] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2263] Step 1:

[2264] User Registration and Sample Collection Equipment Request

[2265] The user logs into the dedicated app and inputs the necessary information (name, address, contact details, health status) to request sample collection equipment. The server receives the input data and verifies the information. If there are no omissions or errors, the request details are saved in the database and the sample collection equipment is shipped. A tracking number is generated and sent to the device.

[2266] Input: User registration information and request data

[2267] Output: Stores accurate request data and generates tracking numbers

[2268] Specific operations: Validation and storage process, generation of tracking number, notification

[2269] Step 2:

[2270] Sample collection and shipping

[2271] The user collects a specimen (e.g., a blood sample) using the specimen collection device they received. They then place the collected specimen in a designated return envelope and send it to the laboratory. The terminal records information such as the specimen collection date and time and type, and sends it to the server.

[2272] Input: Sample collection information (date, time, type)

[2273] Output: Send sample information to the server

[2274] Specific actions: Collecting samples, recording and transmitting information

[2275] Step 3:

[2276] Receipt of samples and initiation of analysis

[2277] The server receives a notification of sample receipt from the laboratory, updates the database, and then sends the sample information to the analyzer to start analysis.

[2278] Input: Specimen receipt notice from lab

[2279] Output: Instructions to update the database and start analysis

[2280] Specific operations: Database update, sending instruction to start analysis

[2281] Step 4:

[2282] Analysis and generation of initial judgment results

[2283] The analysis device analyzes the received sample and generates result data. The result data is sent to the server and input into the generative AI model. The AI ​​model analyzes the image of the sample and generates a primary judgment result. The server receives this result and stores it in a da...

Claims

1. a means for users to request a kit for self-collection of a specimen; A means for the user to collect and send a specimen; a testing device for analyzing the sample after receiving the sample; A means for analyzing the analysis result using an AI model and generating a primary judgment result; means for notifying a user of the result of the primary determination; a means for providing instructions regarding next steps; A system including:

2. 2. The system according to claim 1, further comprising means for storing the analysis results of the specimen in a database and for comparing them with the test results from the next time onwards.

3. 10. The system of claim 1, further comprising means for using an AI model to analyze the sample and generate a preliminary determination result.

Images