system

Abstract

We provide the system. [Solution] A means for receiving and analyzing a saliva or blood sample, A method for calculating disease risk using analyzed DNA data, A means of saving the calculation results to the user's profile, A means of providing analysis results and preventive measures in response to user requests, A method for identifying ancestral roots based on the user's DNA data, A system that includes means of identifying other users with similar roots and providing them with local information.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern medical systems, early disease detection and prevention are important for extending healthy life expectancy and suppressing the soaring medical costs associated with an aging society. However, with current health diagnosis methods, it is difficult to identify the risks of a wide variety of diseases and future onset risks, and useful data obtained from an individual's genetic information has not been fully utilized. Thus, there is a need for a system that can efficiently analyze an individual's genetic information and provide diverse health information.

Means for Solving the Problems

[0005] The present invention solves the above problems by providing a system that includes means for receiving and analyzing saliva or blood samples, means for calculating disease risk using the analyzed DNA data, means for storing the calculation results in the user's profile, means for providing the analysis results and preventive measures upon request from the user, means for identifying the user's ancestral roots based on the user's DNA data, and means for identifying other users with similar roots and providing regional information. This system makes it possible to predict the risk of a wide range of diseases and the risk of future onset, as well as identify ancestral roots, and provides users with comprehensive health information.

[0006] A "saliva or blood sample" refers to a portion of saliva or blood provided by the user, which will be used for DNA analysis.

[0007] "Analysis" is the process of extracting DNA sequences from provided saliva or blood samples to identify information such as disease risk and ancestral roots.

[0008] "DNA data" refers to data containing the user's genetic information obtained through analysis.

[0009] "Disease risk" is the probability of developing a specific disease in the future, calculated based on analyzed DNA data.

[0010] A "profile" is a database entry containing analytical data and risk information related to an individual user.

[0011] A "request" is an operation or request that a user makes to obtain information from a system.

[0012] "Preventive measures" refer to specific advice and action guidelines provided to users to prevent the onset of disease, based on the calculated disease risk.

[0013] "Ancestral roots" refers to information about the genetic origins of a user, identified based on their DNA data, specifically which region or ethnic group they are from.

[0014] "Other users with similar roots" refers to other users within the system who share characteristics with the user's DNA data.

[0015] "Local information" refers to geographical information and statistical data provided to users in relation to their specific ancestral roots. [Brief explanation of the drawing]

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

Modes for Carrying Out the Invention

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

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

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

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

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

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

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0024] [First Embodiment]

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

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

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

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

[0029] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

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

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

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

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

[0037] This system analyzes saliva or blood samples provided by users to identify disease risks and ancestral roots. The following describes the system's program processing in natural language, along with specific examples.

[0038] *Detailed steps will be omitted at this stage, as there will be questions about the processing steps later.

[0039] System Overview

[0040] This system consists of users, terminals, and a server. Users access the server through their terminals to request sample kits, check results, and obtain preventative measures. The server is responsible for receiving samples, analyzing them, storing data, and providing results.

[0041] Program processing

[0042] Request and send out sample kits

[0043] 1. The user accesses the server's website using their device and applies for a sample kit.

[0044] 2. The server receives the application information and arranges for the sample kit to be sent to the user.

[0045] 3. The user receives a sample kit and collects a saliva or blood sample.

[0046] 4. The user sends the collected samples to the designated laboratory.

[0047] Sample reception and analysis

[0048] 5. The lab receives the sample and begins DNA analysis.

[0049] 6. The analyzed DNA data is sent to the server and linked to the user profile.

[0050] Analysis of disease risk and provision of results

[0051] 7. The server analyzes the received DNA data and calculates the user's disease risk.

[0052] 8. The server stores disease risk in the user profile and provides the results upon user request.

[0053] 9. Based on the analysis results, the server also provides suggestions for preventative measures and lifestyle improvements.

[0054] Analysis of ancestral roots and provision of results

[0055] 10. The server analyzes the user's DNA data to identify their ancestral roots.

[0056] 11. The server matches the data with other users to identify users with similar backgrounds and regional information.

[0057] 12. The user requests information about their ancestral roots through their device, and the server provides that information.

[0058] Specific example

[0059] Request and send out sample kits

[0060] Person A, wanting to learn about their health risks, accesses the system's website using their device. Person A fills in the required information on the sample kit application form and clicks the submit button. The server receives the application information, and a few days later, the sample kit arrives at Person A's address.

[0061] Sample reception and analysis

[0062] Person A collects a saliva sample according to the instructions in the kit and sends it to the lab. The lab receives the sample and performs DNA analysis. The analysis results are sent to the server and added to Person A's profile.

[0063] Analysis of disease risk and provision of results

[0064] The server calculates disease risk based on person A's DNA data and saves this information to person A's profile. When person A logs in from their device and views the results report, the server displays the analysis results and preventive measures.

[0065] Analysis of ancestral roots and provision of results

[0066] The server analyzes A's DNA data to identify their ancestral roots. In addition, it compares the data of other users with similar roots to extract common regional information. When A requests information about their ancestral roots, the server displays that information on their device.

[0067] In this way, the system can provide users with comprehensive information about their health risks and ancestral roots, and offer advice on preventative measures and lifestyle improvements.

[0068] The following describes the processing flow.

[0069] Step 1:

[0070] The user accesses the server's website through their device and opens the sample kit application page.

[0071] Step 2:

[0072] The user enters the required information, such as their name, address, and contact details, into the application form and clicks the "Submit" button.

[0073] Step 3:

[0074] The server receives the application data and saves it to the database. The process then automatically proceeds to arrange for the shipment of the sample kit.

[0075] Step 4:

[0076] The server sends a confirmation email to the user notifying them that the sample kit has been shipped.

[0077] Step 5:

[0078] The user receives a sample kit and collects a saliva or blood sample according to the instructions in the kit.

[0079] Step 6:

[0080] The user uses the enclosed return envelope to send the collected sample to the designated laboratory.

[0081] Step 7:

[0082] The lab verifies the contents of the received samples, scans the barcodes, and registers them in the database.

[0083] Step 8:

[0084] The lab begins DNA analysis by extracting DNA from a saliva or blood sample.

[0085] Step 9:

[0086] The extracted DNA is analyzed using a sequencing device to obtain the user's genetic information. Analysis data is then generated.

[0087] Step 10:

[0088] The lab sends the analysis data to the server, which is then linked to the user's profile.

[0089] Step 11:

[0090] The server analyzes the received DNA data and calculates the user's risk of various diseases.

[0091] Step 12:

[0092] The server saves the calculation results to the user profile and notifies the user that the results are ready.

[0093] Step 13:

[0094] The user logs into the server using their device and requests to view the results report.

[0095] Step 14:

[0096] The server generates a report containing analysis results and preventative measures in response to the user's request and displays it on the terminal.

[0097] Step 15:

[0098] The server will, if necessary, predict diseases with a high incidence rate in the future and suggest additional preventive measures.

[0099] Step 16:

[0100] The server identifies the user's ancestral roots based on their DNA data and adds relevant information to the database.

[0101] Step 17:

[0102] The server matches this data with other users' ancestry to identify people with similar roots and extracts regional information.

[0103] Step 18:

[0104] Users request information about their ancestors and roots through their devices, and the server compiles and provides the information to the users.

[0105] Step 19:

[0106] Users can view information about their ancestral roots and related regions on their devices, and learn about regions and cultures that interest them.

[0107] Through this series of steps, the system can provide comprehensive information on the user's health risks and ancestral roots, and suggest individualized preventative measures.

[0108] (Example 1)

[0109] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0110] Currently, while systems exist on the market for analyzing individual disease risks and ancestral roots, they often lack sufficient preventative measures or lifestyle improvement suggestions for users, and the management of sample kits is uncertain. Furthermore, data protection and encryption measures may be inadequate. A major challenge is the lack of efficient and secure means to deliver analysis results and related information.

[0111] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0112] In this invention, the server includes means for receiving and analyzing saliva or blood samples, means for calculating disease risk using the analyzed DNA data, means for storing the calculation results in the user's profile, means for providing analysis results and preventive measures upon request from the user, means for identifying the user's ancestral roots based on the user's DNA data, means for identifying other users with similar roots and providing regional information, means for generating preventive measures and lifestyle improvement suggestions using a generative AI model, means for arranging the delivery of sample kits, means for tracking the delivery status of samples, and means for data protection and encryption. As a result, users can not only obtain comprehensive disease risk information and ancestral roots information, but also receive suggestions for effective preventive measures, and furthermore, reliability in sample management and data protection is improved.

[0113] A "saliva sample" is a liquid biological sample collected from the user's oral cavity.

[0114] A "blood sample" is a biological sample that uses blood collected from the user's body.

[0115] "Analysis" is the process of examining DNA information extracted from a biological sample and clarifying its contents.

[0116] "DNA data" refers to digital data containing deoxyribonucleic acid information obtained from saliva or blood samples.

[0117] "Disease risk" is a quantitative assessment of the likelihood of a specific disease occurring.

[0118] A "user profile" is a digital database that aggregates information about an individual user.

[0119] "Preventive measures" are specific action guidelines aimed at reducing the risk of a particular disease.

[0120] "Ancestral roots" refers to geographical and genetic information about the user's distant ancestors.

[0121] A "generative AI model" is an algorithm that uses artificial intelligence to generate useful information and suggestions from data.

[0122] A "sample kit" is a set that includes equipment and containers for collecting biological samples.

[0123] "Shipping arrangements" refers to the series of procedures for delivering sample kits to users.

[0124] "Tracking delivery status" is the process of checking the status of a sample kit to the user or lab.

[0125] "Data protection" refers to measures taken to protect users' personal information and analytical data from unauthorized access.

[0126] "Encryption" is a technique that transforms data into a format that cannot be deciphered in order to protect it.

[0127] System Overview

[0128] This system analyzes saliva or blood samples provided by users to identify disease risks and ancestral roots. The system consists of users, terminals, and a server. Users access the server via their terminals to request sample kits, check results, and obtain preventative measures. The server is responsible for receiving samples, analyzing them, storing data, and providing results.

[0129] Explain the program's processing in natural language.

[0130] Request and send out sample kits

[0131] 1. The user accesses the application form on the website using their device and enters the required information. This utilizes a web form using HTML and JavaScript (registered trademark).

[0132] 2. The server receives the information sent by the user and stores it in a database (e.g., MySQL®).

[0133] 3. The server will arrange for the sample kit to be sent, using the APIs of external shipping companies (e.g., DHL or FedEx) to request shipment.

[0134] 4. The user receives the sample kit at home a few days later.

[0135] Sample reception and analysis

[0136] 1. The user collects a saliva or blood sample following the instructions on the sample kit.

[0137] 2. The user sends the collected samples to the lab.

[0138] 3. The lab receives the sample and performs DNA analysis (e.g., using PCR equipment or next-generation sequencers). The analysis results are converted into digital data.

[0139] 4. The lab sends the analysis results to the server using the SSL / TLS encryption protocol.

[0140] 5. The server links the received analysis results to the user profile and saves them in the database.

[0141] Analysis of disease risk and provision of results

[0142] 1. The server calculates disease risk based on the analysis results. Specifically, it executes data analysis scripts using Python's pandas or scikit-learn.

[0143] 2. The server saves the calculation results to the user profile.

[0144] 3. The user logs into the website via their device and checks the results on their My Page.

[0145] 4. The server uses an AI model (e.g., GPT-3® from OpenAI®) to display preventative measures and lifestyle improvement suggestions based on the analysis results.

[0146] Examples of prompt statements:

[0147] "According to Ms. A's DNA data, she is at risk of heart disease. Please advise her to take preventative measures such as proper diet, exercise, and regular medical checkups."

[0148] Analysis of ancestral roots and provision of results

[0149] 1. The server analyzes the user's ancestral roots using their DNA data. It uses a genome database and matching algorithms.

[0150] 2. The server matches the data with other users' data to identify common ancestors and regional information.

[0151] 3. The user requests information about their ancestral roots using their device.

[0152] 4. The server receives the request and displays the analysis results on the user's device. This includes geographical root maps and shared genetic characteristics.

[0153] As described above, this system provides comprehensive information about users' health risks and ancestral roots, offers advice on preventative measures and lifestyle improvements, and implements reliable data management and encryption.

[0154] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0155] Step 1:

[0156] The user accesses the application form on the website using their device, enters the required personal information (name, address, contact information, etc.), and presses the "Submit" button. The entered data is then sent from the device to the server.

[0157] Input: Personal information entered by the user.

[0158] Output: Transmitted personal data.

[0159] Step 2:

[0160] The server receives the information sent by the user and saves it to a database (e.g., MySQL). After saving is complete, the server proceeds with arranging the shipment of the sample kit.

[0161] Input: Personal information data submitted.

[0162] Output: Personal information stored in the database.

[0163] Step 3:

[0164] The server uses the shipping company's API (e.g., DHL or FedEx) to request the shipment of sample kits. It receives information such as shipping costs and estimated delivery dates from the shipping company and arranges for the delivery of the sample kits.

[0165] Input: Personal information stored in the database.

[0166] Output: Shipping arrangement information from the delivery company.

[0167] Step 4:

[0168] The user receives a sample kit at home a few days later. The sample kit includes instructions and a container for collecting a saliva or blood sample.

[0169] Input: Sample kit.

[0170] Output: User receives sample kit.

[0171] Step 5:

[0172] The user collects a saliva or blood sample according to the instructions on the sample kit. For saliva, the specified amount is placed in a dedicated container, and for blood, it is collected in a specific tube.

[0173] Input: Sample kit.

[0174] Output: Collected saliva or blood sample.

[0175] Step 6:

[0176] The user places the collected sample in the enclosed return envelope and sends it to the lab's address. The lab receives the sample and confirms receipt.

[0177] Input: A collected saliva or blood sample.

[0178] Output: Sample sent to the lab.

[0179] Step 7:

[0180] The lab begins DNA analysis on the received samples. PCR equipment and next-generation sequencers are used to obtain the DNA sequence information of the samples.

[0181] Input: Sample sent to the lab.

[0182] Output: Analyzed DNA data.

[0183] Step 8:

[0184] The lab sends the analyzed DNA data to the server in digital format. SSL / TLS encryption protocol is used for communication.

[0185] Input: Analyzed DNA data.

[0186] Output: DNA data sent to the server.

[0187] Step 9:

[0188] The server links the received DNA data to the user profile and saves it to the database. The user is then notified when the saving process is complete.

[0189] Input: DNA data sent to the server.

[0190] Output: DNA data linked to the user profile.

[0191] Step 10:

[0192] The server calculates disease risk based on the analysis results. It executes data analysis scripts using Python's pandas and scikit-learn and applies a risk assessment model.

[0193] Input: DNA data linked to the user profile.

[0194] Output: Calculated disease risk data.

[0195] Step 11:

[0196] The server saves the calculation results to the user's profile, making them accessible to the user. The saved results are displayed on the user's My Page on the website.

[0197] Input: Calculated disease risk data.

[0198] Output: Risk data stored in the user profile.

[0199] Step 12:

[0200] Users log in to the website via their device and view their results on their personal page. Along with the analysis results, preventative measures and lifestyle improvement suggestions are displayed using a generated AI model.

[0201] Input: User login information.

[0202] Output: A My Page displaying analysis results and preventative measures.

[0203] Step 13:

[0204] The server uses generated AI models (e.g., OpenAI's GPT-3) to create customized preventative measures and lifestyle improvement suggestions based on the analysis results.

[0205] Input: Analysis results.

[0206] Output: Generated precautions.

[0207] Examples of prompt statements:

[0208] "According to Ms. A's DNA data, she is at risk of heart disease. Please advise her to take preventative measures such as proper diet, exercise, and regular medical checkups."

[0209] Step 14:

[0210] The server analyzes the user's ancestral roots using their DNA data. It uses a genome database and matching algorithms to identify geographical and genetic information about their ancestors.

[0211] Input: DNA data linked to the user profile.

[0212] Output: Identified ancestral roots information.

[0213] Step 15:

[0214] The server matches DNA data with other users to identify common ancestors and regional information. Statistical analysis is performed to extract user information with high similarity.

[0215] Input: Identified ancestral root information.

[0216] Output: Similar users and location information.

[0217] Step 16:

[0218] The user uses their device to request information about their ancestral roots. The request is sent to the server.

[0219] Input: User request information.

[0220] Output: The request sent to the server.

[0221] Step 17:

[0222] The server receives the request and displays the analysis results on the user's device. This includes geographical root maps and shared genetic characteristics.

[0223] Input: The request sent to the server.

[0224] Output: Analysis results displayed on the user's terminal.

[0225] (Application Example 1)

[0226] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0227] In modern society, personalized health management tailored to each individual's health condition and genetic risks is in demand. However, current systems make it difficult to provide specific health guidance based on disease risk and genetic background. Furthermore, there is a lack of means to propose and efficiently deliver optimal meal plans for each individual. As a result, many people are unable to manage their health properly and face lifestyle-related diseases and other health risks.

[0228] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0229] This invention includes a server that provides means for receiving and analyzing saliva or blood samples, means for calculating disease risk using the analyzed DNA data, means for storing the calculation results in the user's profile, means for providing analysis results and preventive measures upon user request, means for identifying ancestral roots based on the user's DNA data, means for identifying other users with similar roots and providing regional information, means for proposing a meal plan based on the analyzed DNA data, means for ordering and managing the delivery of meals based on the proposed meal plan, and means for tracking the delivery status in real time. This enables health management based on the individual user's genetic risk and provides appropriate meal plans tailored to that risk. This reduces individual health risks and enables more effective health management.

[0230] A "saliva or blood sample" is a type of biological fluid collected from the user and used for the extraction and analysis of DNA containing genetic information.

[0231] "Means of analysis" refer to devices, systems, and software that perform a series of processes to extract DNA from a sample and to reveal its structure and properties.

[0232] "DNA data" refers to DNA sequence information containing a user's genetic information, and is used to identify disease risks and ancestral roots.

[0233] "Disease risk" is an indicator that shows the likelihood of a user developing a specific disease in the future, based on their specific genetic information.

[0234] A "user profile" is a dataset containing personal information, analysis results, and health risk information about a user.

[0235] "Preventive measures" refer to specific actions and advice for maintaining health and preventing disease, proposed based on the analysis results.

[0236] "Ancestral roots" refers to historical and geographical origin information identified based on the user's genetic information.

[0237] "Other users with similar roots" refers to other users who have been identified as having the same ancestors or geographical background.

[0238] "Regional information" refers to data about the geographical distribution of users who are related by ancestry or genetics.

[0239] A "meal plan" is a plan for optimal nutritional intake suggested based on the user's genetic information and health risks.

[0240] "Means of managing delivery" refers to the system and procedures that oversee the process of cooking and delivering meals selected by the user based on the proposed meal plan.

[0241] "A means of tracking delivery status in real time" refers to a system that monitors the delivery progress of meals ordered by users in real time and provides information on it.

[0242] System Overview

[0243] The system implemented based on this invention involves a user providing a saliva or blood sample, and then analyzing the DNA data obtained from that sample to suggest and deliver personalized healthy meals based on the individual's disease risk and genetic background. This system operates in conjunction with a server, terminals, and delivery service.

[0244] Sample submission and analysis

[0245] The user first accesses the server's website or application using a terminal and requests a saliva or blood sample kit. The server receives the request and ships the sample kit to the user. The user receives the kit, collects a saliva or blood sample, and then sends the sample to a designated laboratory.

[0246] In the lab, samples are received, and specialized analytical equipment analyzes the DNA. The analyzed DNA data is sent to a server using a secure communication method and linked to the user profile.

[0247] Analysis of disease risk and proposals for healthy eating

[0248] The server calculates the user's disease risk based on the received DNA data and stores the results in the user's profile. Furthermore, it suggests appropriate preventive measures based on the analysis results. The server then uses a generative AI model to generate an optimal diet plan based on the user's genetic information and health risks.

[0249] For example, if the server predicts a high risk of diabetes based on the genetic information of "User ID: 12345," it will suggest a diet plan that reduces sugar intake. This result will be displayed on the user's device.

[0250] Food ordering and delivery management

[0251] The user uses a terminal to select a meal from the suggested meal plan and sends the order to the server. The server orders the selected meal from the appropriate delivery service and proceeds with the delivery arrangements. This includes the ability to send specific order information using the delivery service's API and track the progress in real time.

[0252] Track delivery status

[0253] Users can monitor the delivery status of their ordered meals in real time through their device. The server receives delivery information from the delivery service and provides it to the user. This process allows users to track the progress until their meal arrives.

[0254] Example of a prompt

[0255] For example, the prompt for a user to submit a sample is as follows:

[0256] "User data: User ID: 12345, Sample data: Saliva sample"

[0257] Furthermore, the prompt text for a user to request a meal plan is as follows:

[0258] "User data: User ID: 12345"

[0259] In this way, the system provides each user with a scientifically-based health plan and supports health management in a way that can be implemented in daily life.

[0260] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0261] Step 1:

[0262] A user accesses the server's website or application using their device and requests a sample kit. The input consists of the user's personal information and sample kit request information. The server receives this data and outputs instructions for shipping the kit. Specifically, the user enters the required information into a form, and that data is sent to the server.

[0263] Step 2:

[0264] The server ships the sample kit to the user based on the application information. The input is the user's address information received in step 1, and this address information is forwarded to the delivery service, which then outputs instructions to ship the kit. Specifically, the server works in conjunction with the delivery system to send the kit to the user.

[0265] Step 3:

[0266] The user receives a kit, follows the instructions to collect a saliva or blood sample, and sends it to the designated lab. The input is the sample obtained from the user, and the output is the lab receiving that sample. Specifically, the user mails the sample to the lab.

[0267] Step 4:

[0268] The lab receives the sample and begins DNA analysis. The input is a saliva or blood sample sent by the user, and the output is the DNA data resulting from the analysis. Specifically, the lab processes the sample, extracts DNA, and analyzes the gene sequence.

[0269] Step 5:

[0270] The analyzed DNA data is transmitted to the server using a secure communication method. The input is DNA data sent from the lab, and the output is the storage of that DNA data on the server. Specifically, the data is encrypted and transferred through a secure channel.

[0271] Step 6:

[0272] The server calculates the user's disease risk based on DNA data. The input is analyzed DNA data, and the output is a health risk score resulting from the calculation. Specifically, the process involves matching gene sequences with known disease-related markers.

[0273] Step 7:

[0274] The server saves the disease risk assessment results to the user's profile. The input is the health risk score, and the output is that it is added to the user's profile database. Specifically, the process involves writing data through database operations.

[0275] Step 8:

[0276] The server provides appropriate preventative measures to the user based on the analysis results. The input is a health risk score, and the output is related preventative measures. Specifically, it uses a health advice generation AI model to create preventative measures and notifies the user.

[0277] Step 9:

[0278] The server generates an optimal meal plan for the user based on DNA data. The input is analyzed DNA data, and the output is a personalized meal plan. Specifically, it uses a generative AI model that generates a nutrition plan that takes genetic information and health risks into consideration.

[0279] Step 10:

[0280] The user selects a meal from a suggested meal plan using their device and sends the order to the server. The input is the meal plan selected by the user, and the output is the order information. Specifically, the user selects a menu item from the application, and the order information is transferred to the server.

[0281] Step 11:

[0282] The server instructs the delivery service with the order information and manages the delivery. The input is the user's order information, and the output is the delivery instruction to the delivery service. As a specific operation, it uses an API to cooperate with the delivery system and send the delivery instruction.

[0283] Step 12:

[0284] The user monitors in real time the delivery status of the meal ordered by himself / herself through the terminal. The input is the delivery progress information from the delivery service, and the output is the delivery status provided to the user. As a specific operation, it receives the status information from the delivery service and notifies the user.

[0285] Furthermore, an emotion engine for estimating the user's emotion may be combined. That is, the specific processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform specific processing using the user's emotion.

[0286] This system not only analyzes the saliva or blood sample provided by the user to identify the disease risk and ancestral roots, but also combines an emotion engine for recognizing the user's emotion to adjust the method of providing the analysis result and provide appropriate advice and preventive measures. The processing of the program of this system will be described in natural language below. Specific examples will also be described together.

[0287] System Overview

[0288] This system is composed of a user, a terminal, a server, a laboratory, and an emotion engine. The user accesses the server through the terminal to apply for a sample kit, check the results, and obtain preventive measures. The server is responsible for receiving samples, analyzing them, storing data, providing results, and recognizing the user's emotion by the emotion engine.

[0289] Program processing

[0290] Request and send out sample kits

[0291] 1. The user accesses the server's website using their device and applies for a sample kit.

[0292] 2. The server receives the application information and arranges for the sample kit to be sent to the user.

[0293] 3. The user receives a sample kit and collects a saliva or blood sample.

[0294] 4. The user sends the collected samples to the designated laboratory.

[0295] Sample reception and analysis

[0296] 5. The lab receives the sample and begins DNA analysis.

[0297] 6. The analyzed DNA data is sent to the server and linked to the user profile.

[0298] Analysis of disease risk and provision of results

[0299] 7. The server analyzes the received DNA data and calculates the user's disease risk.

[0300] 8. The server saves the disease risk to the user profile and notifies the user when the results are ready.

[0301] 9. The emotion engine recognizes the user's emotions based on data obtained from the user's device (e.g., feedback, behavioral history, facial expressions, etc.).

[0302] 10. When the server provides analysis results, it adjusts the presentation method of the results based on the user's emotional state recognized by the emotion engine.

[0303] 11. Based on the analysis results, the server provides appropriate preventive measures and suggestions for improving life. In addition, the emotion engine monitors the user's emotional state and provides information at an appropriate timing as needed.

[0304] Analysis of Ancestral Roots and Provision of Results

[0305] 12. The server analyzes the user's DNA data to identify the ancestral roots.

[0306] 13. The server compares with the data of other users to identify users with similar roots and regional information.

[0307] 14. The user requests information about the ancestral roots through the terminal, and the server provides the information.

[0308] Specific Example

[0309] Application and Sending of Sample Kit

[0310] User B wants to know his own health risks and uses the terminal to access the system's website. User B enters the necessary information in the application form for the sample kit and clicks the send button. The server receives the application information, and the sample kit arrives at User B's address after a few days.

[0311] Receiving and Analyzing Samples

[0312] User B collects a saliva sample according to the instructions in the kit and sends it to the laboratory. The laboratory receives the sample and conducts DNA analysis. The analysis results are sent to the server and added to User B's profile.

[0313] Analysis of Disease Risks and Provision of Results

[0314] The server calculates disease risk based on B's DNA data and stores this information in B's profile. When B logs in from their device and views the results report, the server displays the analysis results and preventative measures. During this process, an emotion engine recognizes B's emotional state and presents the analysis results at the appropriate time and in the appropriate manner. For example, if B is feeling anxious, the server provides preventative measures along with calm and detailed explanations, taking steps to reassure them.

[0315] Analysis of ancestral roots and provision of results

[0316] The server analyzes B's DNA data to identify their ancestral roots. In addition, it compares the data of other users with similar roots to extract common regional information. When B requests information about their ancestral roots, the server displays that information on their device.

[0317] Through this series of steps, the system can comprehensively provide information on the user's health risks and ancestral roots, and appropriately suggest individualized preventative measures while taking the user's emotional state into consideration.

[0318] The following describes the processing flow.

[0319] Step 1:

[0320] The user accesses the server's website through their device and opens the sample kit application page.

[0321] Step 2:

[0322] The user enters the required information, such as their name, address, and contact details, into the application form and clicks the "Submit" button.

[0323] Step 3:

[0324] The server receives the application data and saves it to the database. The process then automatically proceeds to arrange for the shipment of the sample kit.

[0325] Step 4:

[0326] The server sends a confirmation email to the user notifying them that the sample kit has been shipped.

[0327] Step 5:

[0328] The user receives a sample kit and collects a saliva or blood sample according to the instructions in the kit.

[0329] Step 6:

[0330] The user uses the enclosed return envelope to send the collected sample to the designated laboratory.

[0331] Step 7:

[0332] The lab verifies the contents of the received samples, scans the barcodes, and registers them in the database.

[0333] Step 8:

[0334] The lab begins DNA analysis by extracting DNA from a saliva or blood sample.

[0335] Step 9:

[0336] The extracted DNA is analyzed using a sequencing device to obtain the user's genetic information. Analysis data is then generated.

[0337] Step 10:

[0338] The lab sends the analysis data to the server, which is then linked to the user's profile.

[0339] Step 11:

[0340] The server analyzes the received DNA data and calculates the user's risk of various diseases.

[0341] Step 12:

[0342] The server saves the calculation results to the user profile and notifies the user that the results are ready.

[0343] Step 13:

[0344] The emotion engine recognizes the user's emotions based on data obtained from the user's device (e.g., feedback, behavioral history, facial expressions, etc.).

[0345] Step 14:

[0346] The user logs into the server using their device and requests to view the results report.

[0347] Step 15:

[0348] The server generates a report containing analysis results and preventative measures in response to the user's request.

[0349] Step 16:

[0350] The server adjusts how it presents analysis results based on the user's emotional state recognized by the emotion engine. For example, if the user is feeling anxious, it provides a calm and detailed explanation.

[0351] Step 17:

[0352] Based on the analysis results, the server provides appropriate preventative measures and lifestyle improvement suggestions. Additionally, an emotion engine monitors the user's emotional state and provides timely information as needed.

[0353] Step 18:

[0354] The server identifies the user's ancestral roots based on their DNA data and adds relevant information to the database.

[0355] Step 19:

[0356] The server matches this data with other users' ancestry to identify people with similar roots and extracts regional information.

[0357] Step 20:

[0358] Users request information about their ancestors and roots through their devices, and the server compiles and provides the information to the users.

[0359] Step 21:

[0360] Users can view information about their ancestral roots and related regions on their devices, and learn about regions and cultures that interest them.

[0361] Through this series of steps, the system can comprehensively provide users with information on their health risks and ancestral roots, and appropriately suggest individual preventative measures. Furthermore, the emotion engine can understand the user's emotional state, enabling the provision of optimal information.

[0362] (Example 2)

[0363] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0364] Traditional DNA analysis systems were limited to calculating disease risk and identifying ancestral roots, and did not provide information that took into account the user's emotions. As a result, users who received analysis results were more likely to experience anxiety and stress. Furthermore, detailed preventative measures and lifestyle improvement suggestions were rarely provided in a timely manner.

[0365] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving and analyzing a saliva or blood sample, means for calculating disease risk using the analyzed data, means for storing the calculation results in the user's profile, means for providing analysis results and preventive measures in response to a user request, means for recognizing the user's emotions and adjusting the method of providing analysis results, means for identifying ancestral roots based on the user's data, and means for identifying other users with similar roots and providing regional information. This makes it possible to provide analysis results that give users a greater sense of security and to propose preventive measures and lifestyle improvement plans at the appropriate time.

[0366] A "saliva or blood sample" is a biological sample provided by the user that includes saliva or blood.

[0367] "Analysis" refers to the process of processing data obtained from a sample and extracting meaningful information. Specifically, this includes DNA sequencing and gene analysis.

[0368] "Disease risk calculation" is the process of numerically predicting the risk of developing a specific disease based on analyzed DNA data.

[0369] A "user profile" is an information database that centrally manages all user-related data within the system.

[0370] "Preventive measures" are specific actions or policies provided based on analysis results to reduce the risk of a particular disease.

[0371] "Emotion recognition" is the process of analyzing and identifying a user's emotional state at a given time based on their behavior, facial expressions, and feedback data.

[0372] "Adjusting the method of providing analysis results" refers to a technique that changes the display format and notification method of analysis results according to the user's emotional state.

[0373] "Identifying ancestral roots" is the process of analyzing DNA data to reveal the user's genetic origins and the place of origin of their ancestors.

[0374] "Regional information" refers to information about a specific region obtained by cross-referencing it with data from other users who have a similar genetic origin to the user.

[0375] A "system" is a complex collection of hardware and software that integrates all of the above means and functions to provide consistent services to the user.

[0376] This invention is a system that not only analyzes a user's health risks and ancestral roots, but also provides information tailored to the user's emotions. This system consists of a user, a terminal, a server, a lab, and an emotion recognition engine.

[0377] The user accesses the system via a terminal and requests a sample kit. The server receives the request information and arranges for the sample kit. The user then collects the sample and sends it to the lab. The lab analyzes the received sample and sends the analysis results to the server. Based on the analysis data, the server calculates disease risk and ancestral roots and notifies the user of the results. The following hardware and software are used to ensure this entire process runs smoothly.

[0378] Specifically, we employ the following steps and technologies.

[0379] Hardware and software to be used

[0380] 1. DNA sequencer (e.g., Illumina, Thermo Fisher)

[0381] The lab uses it to analyze samples.

[0382] 2. Genetic analysis tools (e.g., Plink, BEAGLE)

[0383] The server uses DNA data to analyze and calculate disease risk.

[0384] 3. Emotion recognition engine (e.g., Amazon Rekognition, Microsoft® Azure®'s Emotion API)

[0385] The server uses this to recognize the user's emotions and adjust how the analysis results are presented.

[0386] Explanation of program processing in natural language

[0387] Request a sample kit

[0388] The user accesses the system's website using their device and reaches the sample kit application page. The entered application information is sent to the server, which uses the shipping carrier's API to arrange for the kit to be shipped.

[0389] Sample collection and mailing

[0390] A few days later, the user receives a sample kit. The user collects a saliva or blood sample according to the instructions and sends it to the lab using the provided return envelope. The lab receives the sample and analyzes it using a DNA sequencer.

[0391] Calculation and analysis of disease risk

[0392] The analysis data is encrypted and sent to the server. The server uses genetic analysis tools such as Plink and BEAGLE to calculate disease risk. The calculation results are saved in the user's profile, and the user is notified when the results are ready.

[0393] Adjusting emotion recognition and result delivery

[0394] When a user reviews their results, the emotion recognition engine analyzes their emotional state. If anxiety or stress is detected, the server adjusts the content and timing of its display and provides detailed explanations. It also simultaneously offers suggestions for preventative measures and lifestyle improvements.

[0395] Identifying ancestral roots and providing regional information

[0396] The server uses genealogical analysis software such as Genealogist to identify the user's ancestral roots. It then matches this information with user data of similar origins and provides regional information.

[0397] Specific example

[0398] Person B, wanting to learn about their health risks, uses their device to access the system's website. They fill in the required information on the application form and click the submit button. The server receives the application information, and a sample kit arrives at Person B's address a few days later.

[0399] Person B collects a saliva sample according to the instructions in the kit and sends it to the lab. The lab receives the sample and performs DNA analysis. The analysis results are sent to the server and added to Person B's profile.

[0400] The server calculates disease risk based on B's DNA data and saves this information in a profile. When B logs in from their device and views the results report, the server displays the analysis results and preventative measures. An emotion engine recognizes B's emotional state and presents the analysis results at the appropriate time and in the appropriate manner.

[0401] For example, if person B is feeling anxious, the system will provide calm and detailed explanations along with preventative measures to help them feel at ease. The server will analyze person B's DNA data to identify their ancestral roots. In addition, it will cross-reference data with other users who have similar roots to extract common regional information. When person B requests information about their ancestral roots, the server will display that information on their device.

[0402] Example of a prompt

[0403] "How can I calculate disease risk based on DNA data and save it to a user profile?"

[0404] "How can I use an emotion engine to recognize a user's emotions and change how the analysis results are presented?"

[0405] "Please tell me how to design a system that identifies ancestral roots and provides that information to users."

[0406] Through the process described above, the present invention is a system that comprehensively provides information on the user's health risks and ancestral roots, and provides optimal information while taking into account their emotional state.

[0407] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0408] Step 1:

[0409] The user accesses the system's website using their device and reaches the sample kit application page. The user enters the required information, such as their name, address, and contact information, into the form and clicks the application button. This sends the entered application data to the server.

[0410] Input: Application information such as name, address, and contact information.

[0411] Output: Application data stored on the server.

[0412] Step 2:

[0413] The server receives the application information and begins the process of sending the sample kit. The server uses the shipping company's API to arrange for the sample kit to be shipped to the specified address. Once the shipping arrangements are complete, the server sends a confirmation email to the user.

[0414] Input: User application information.

[0415] Output: Arrangement for delivery with the shipping company and confirmation email to the user.

[0416] Step 3:

[0417] A few days later, the user receives a sample kit. The user collects a saliva or blood sample according to the instructions in the kit.

[0418] Input: Sample kit.

[0419] Output: Collected saliva or blood sample.

[0420] Step 4:

[0421] The user places the collected sample in the return envelope included in the sample kit and sends it to the designated lab.

[0422] Input: A collected saliva or blood sample.

[0423] Output: Sample placed in a return envelope.

[0424] Step 5:

[0425] The lab receives the sample sent by the user and sends an acknowledgment of receipt to the system. The lab then analyzes the sample using a DNA sequencer (e.g., a general-purpose DNA sequencer).

[0426] Input: Collected sample.

[0427] Output: Analyzed DNA data.

[0428] Step 6:

[0429] The server receives the analyzed DNA data sent from the lab and stores it, linking it to the corresponding user profile. Data integrity checks are also performed during this process.

[0430] Input: Analyzed DNA data.

[0431] Output: DNA data linked to the user profile.

[0432] Step 7:

[0433] The server uses genetic analysis tools such as Plink and BEAGLE to calculate the user's disease risk based on the received DNA data. The calculated risk information is stored in the user profile.

[0434] Input: Stored DNA data.

[0435] Output: Calculated disease risk information.

[0436] Step 8:

[0437] The server notifies the user when the calculated disease risk results are ready. This notification may be sent via email or in-app message.

[0438] Input: Calculated disease risk information.

[0439] Output: Notification to the user.

[0440] Step 9:

[0441] The emotion recognition engine uses data acquired from the user's device (such as feedback, behavioral history, and facial expressions) to analyze the user's emotions. For example, anxiety may be recognized based on feedback data.

[0442] Input: Feedback, behavioral history, and facial expression data.

[0443] Output: Analyzed emotional state.

[0444] Step 10:

[0445] The server adjusts how the analysis results are presented based on the results from the emotion recognition engine. For example, if the user is anxious, it provides a calm explanation, while if they are relaxed, it adds a detailed technical explanation.

[0446] Input: Analyzed emotional state and disease risk information.

[0447] Output: Adjusted result display.

[0448] Step 11:

[0449] Based on the analysis results, the server generates and provides to the user appropriate preventative measures and lifestyle improvement suggestions. The emotion recognition engine continues to monitor the user's emotions and provides information in a timely manner.

[0450] Input: Disease risk information and analyzed emotional state.

[0451] Output: Proposed preventative measures and lifestyle improvements.

[0452] Step 12:

[0453] The server uses genealogical analysis software such as Genealogist to analyze the user's DNA data and identify their ancestral roots.

[0454] Input: User's DNA data.

[0455] Output: Identified ancestral roots information.

[0456] Step 13:

[0457] The server matches DNA data with that of other users to identify users with similar roots and their geographical information.

[0458] Input: Identified ancestral roots information.

[0459] Output: Matched regional information.

[0460] Step 14:

[0461] When a user requests information about their ancestral roots through their device, the server provides that information in real time.

[0462] Input: User request.

[0463] Output: Provided ancestral roots information and regional information.

[0464] (Application Example 2)

[0465] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0466] Traditional health risk and ancestral roots analysis systems often fail to provide users with appropriate feedback tailored to their emotional state, leading to anxiety and doubt about the results. Furthermore, when viewing analysis results in real-time at physical stores, the lack of information based on the user's emotional state can result in decreased user satisfaction.

[0467] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0468] In this invention, the server includes means for receiving and analyzing a saliva or blood sample, means for calculating disease risk using the analyzed DNA data, means for storing the calculation results in the user's profile, means for providing analysis results and preventive measures upon request from the user, means for identifying the user's ancestral roots based on the user's DNA data, means for identifying other users with similar roots and providing regional information, means for recognizing the user's emotions, means for adjusting the method of presenting analysis results based on the recognized emotional state, and means for recognizing the user's emotional state in real time at the store and providing appropriate advice. This enables appropriate feedback and advice based on the user's emotional state.

[0469] A "saliva or blood sample" is a biological sample provided by the user and is used as material for DNA analysis.

[0470] "Means of analysis" refers to a device or software that extracts DNA from a saliva or blood sample and reads that DNA information.

[0471] A "means for calculating disease risk" refers to an algorithm or program that quantifies the risk of developing a specific disease based on analyzed DNA data.

[0472] "Means of saving to the user's profile" refers to a system that records calculation results in a database and manages them in conjunction with the user's identification information.

[0473] "Means of providing analysis results and preventive measures" refers to a method of displaying or notifying users of calculated disease risks and corresponding preventive measures in response to their requests.

[0474] "Methods for identifying ancestral roots" refers to algorithms that analyze a user's DNA data to identify their genetic background.

[0475] "Means for identifying other users with similar roots and providing regional information" refers to a system that matches users against a database of other users to identify genetically similar users or those sharing common regions.

[0476] "Means of recognizing user emotions" refers to technologies that identify a user's emotional state by analyzing their facial expressions, behavior, and feedback.

[0477] "Means for adjusting the presentation method of analysis results based on recognized emotional states" refers to a system for presenting analysis results in different formats and timings depending on the user's emotions.

[0478] "A means of providing appropriate advice in real time" refers to a method of analyzing the emotional state of users in physical stores in real time and immediately providing corresponding feedback and recommendations.

[0479] The following describes an embodiment for carrying out this invention. This system mainly consists of a server, terminals, users, a lab, and an emotion engine.

[0480] Equipment and hardware configuration

[0481] The server possesses high-performance data analysis and storage capabilities, and manages analysis algorithms and user profile data. The server also incorporates an emotion engine that recognizes user emotions and adjusts feedback accordingly.

[0482] A terminal is a device that users operate, and can take various forms such as smartphones, PCs, and tablets. In addition, smart glasses and head-mounted displays are sometimes adopted for use in physical stores.

[0483] The lab is a specialized facility that receives saliva or blood samples provided by users and performs DNA analysis.

[0484] Software Configuration

[0485] The software used includes TENSORFLOW® as the emotion recognition engine, and a specialized API for DNA analysis. Additionally, a dedicated SDK (Software Development Kit) is incorporated to process data from smart glasses and head-mounted displays.

[0486] Data processing and calculations

[0487] The server first analyzes the sample provided by the user in a lab to obtain DNA data. Based on this DNA data, the server analyzes disease risk and ancestral roots. The generated data is stored in the user profile. When the user requests these results, the server provides the analysis results along with appropriate preventive measures.

[0488] Furthermore, the emotion recognition engine recognizes the user's emotions based on real-time data obtained from the device or smart glasses (e.g., facial expressions, behavioral history) and adjusts how the analysis results are presented. For example, if the user is feeling anxious, it provides reassuring feedback.

[0489] Specific example

[0490] For example, consider a scenario where a user visits a physical store and interacts with a store employee wearing smart glasses. When the user requests health risk information, the server presents disease risks based on DNA analysis data. If the emotion engine detects the user's anxiety, the server provides a message such as, "Don't worry. The risks are minimal, and please take the following precautions to manage your health."

[0491] Example of a prompt

[0492] The following prompt statements are used as input to the generative AI model.

[0493] "If a user is feeling anxious when health risks are displayed, what kind of calming feedback should be provided?"

[0494] This format makes it possible to provide feedback that takes into account the user's real-time emotional state, even in physical stores. This improves user satisfaction and deepens their understanding and acceptance of the results.

[0495] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0496] Step 1:

[0497] The user accesses the server's website using their device and applies for a sample kit. The user enters details such as their user information and shipping address, and the server records the application information as output.

[0498] Step 2:

[0499] The server receives the application information and arranges for the sample kit to be sent to the user. It uses the user's application information as input and generates an order for the shipping procedure as output.

[0500] Step 3:

[0501] The user receives a sample kit, collects a saliva or blood sample, and sends the sample to the designated lab according to the instructions. The input requires the kit instructions and the user's actions, and the output is the sample sent to the lab.

[0502] Step 4:

[0503] The lab receives the sample and performs DNA analysis. The analysis results are sent to a server. A saliva or blood sample is used as input, and the analyzed DNA data is sent to the server as output.

[0504] Step 5:

[0505] The server processes DNA data received from the lab and adds disease risk and ancestral roots information to the user's profile. DNA analysis data is used as input, and the updated user profile is saved as output.

[0506] Step 6:

[0507] When a user requests analysis results and preventive measures through their device, the server retrieves the results from stored profile information. The user's request information is used as input, and disease risk and preventive measures are generated as output.

[0508] Step 7:

[0509] The emotion recognition engine acquires real-time user emotion data from the device or smart glasses in a physical store. Facial expressions and behavioral data are used as input, and the user's emotional state is recognized as output.

[0510] Step 8:

[0511] The server adjusts the presentation method of the analysis results based on the emotion recognition results. Emotion recognition data is used as input, and the adjusted presentation method and feedback are generated as output.

[0512] Step 9:

[0513] Using smart glasses in physical stores, store staff interact with users in real time, providing tailored analysis results and preventative measures. Feedback data from a server is used as input, and appropriate advice is provided to the user as output.

[0514] This process enables personalized healthcare and advice that takes into account the user's emotional state.

[0515] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0516] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0517] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0518] [Second Embodiment]

[0519] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0520] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0521] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0522] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0523] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0524] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0525] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0526] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0527] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0528] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0529] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0530] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0531] This system analyzes saliva or blood samples provided by users to identify disease risks and ancestral roots. The following describes the system's program processing in natural language, along with specific examples.

[0532] *Detailed steps will be omitted at this stage, as there will be questions about the processing steps later.

[0533] System Overview

[0534] This system consists of users, terminals, and a server. Users access the server through their terminals to request sample kits, check results, and obtain preventative measures. The server is responsible for receiving samples, analyzing them, storing data, and providing results.

[0535] Program processing

[0536] Request and send out sample kits

[0537] 1. The user accesses the server's website using their device and applies for a sample kit.

[0538] 2. The server receives the application information and arranges for the sample kit to be sent to the user.

[0539] 3. The user receives a sample kit and collects a saliva or blood sample.

[0540] 4. The user sends the collected samples to the designated laboratory.

[0541] Sample reception and analysis

[0542] 5. The lab receives the sample and begins DNA analysis.

[0543] 6. The analyzed DNA data is sent to the server and linked to the user profile.

[0544] Analysis of disease risk and provision of results

[0545] 7. The server analyzes the received DNA data and calculates the user's disease risk.

[0546] 8. The server stores disease risk in the user profile and provides the results upon user request.

[0547] 9. Based on the analysis results, the server also provides suggestions for preventative measures and lifestyle improvements.

[0548] Analysis of ancestral roots and provision of results

[0549] 10. The server analyzes the user's DNA data to identify their ancestral roots.

[0550] 11. The server matches the data with other users to identify users with similar backgrounds and regional information.

[0551] 12. The user requests information about their ancestral roots through their device, and the server provides that information.

[0552] Specific example

[0553] Request and send out sample kits

[0554] Person A, wanting to learn about their health risks, accesses the system's website using their device. Person A fills in the required information on the sample kit application form and clicks the submit button. The server receives the application information, and a few days later, the sample kit arrives at Person A's address.

[0555] Sample reception and analysis

[0556] Person A collects a saliva sample according to the instructions in the kit and sends it to the lab. The lab receives the sample and performs DNA analysis. The analysis results are sent to the server and added to Person A's profile.

[0557] Analysis of disease risk and provision of results

[0558] The server calculates disease risk based on person A's DNA data and saves this information to person A's profile. When person A logs in from their device and views the results report, the server displays the analysis results and preventive measures.

[0559] Analysis of ancestral roots and provision of results

[0560] The server analyzes A's DNA data to identify their ancestral roots. In addition, it compares the data of other users with similar roots to extract common regional information. When A requests information about their ancestral roots, the server displays that information on their device.

[0561] In this way, the system can provide users with comprehensive information about their health risks and ancestral roots, and offer advice on preventative measures and lifestyle improvements.

[0562] The following describes the processing flow.

[0563] Step 1:

[0564] The user accesses the server's website through their device and opens the sample kit application page.

[0565] Step 2:

[0566] The user enters the required information, such as their name, address, and contact details, into the application form and clicks the "Submit" button.

[0567] Step 3:

[0568] The server receives the application data and saves it to the database. The process then automatically proceeds to arrange for the shipment of the sample kit.

[0569] Step 4:

[0570] The server sends a confirmation email to the user notifying them that the sample kit has been shipped.

[0571] Step 5:

[0572] The user receives a sample kit and collects a saliva or blood sample according to the instructions in the kit.

[0573] Step 6:

[0574] The user uses the enclosed return envelope to send the collected sample to the designated laboratory.

[0575] Step 7:

[0576] The lab verifies the contents of the received samples, scans the barcodes, and registers them in the database.

[0577] Step 8:

[0578] The lab begins DNA analysis by extracting DNA from a saliva or blood sample.

[0579] Step 9:

[0580] The extracted DNA is analyzed using a sequencing device to obtain the user's genetic information. Analysis data is then generated.

[0581] Step 10:

[0582] The lab sends the analysis data to the server, which is then linked to the user's profile.

[0583] Step 11:

[0584] The server analyzes the received DNA data and calculates the user's risk of various diseases.

[0585] Step 12:

[0586] The server saves the calculation results to the user profile and notifies the user that the results are ready.

[0587] Step 13:

[0588] The user logs into the server using their device and requests to view the results report.

[0589] Step 14:

[0590] The server generates a report containing analysis results and preventative measures in response to the user's request and displays it on the terminal.

[0591] Step 15:

[0592] The server will, if necessary, predict diseases with a high incidence rate in the future and suggest additional preventive measures.

[0593] Step 16:

[0594] The server identifies the user's ancestral roots based on their DNA data and adds relevant information to the database.

[0595] Step 17:

[0596] The server matches this data with other users' ancestry to identify people with similar roots and extracts regional information.

[0597] Step 18:

[0598] Users request information about their ancestors and roots through their devices, and the server compiles and provides the information to the users.

[0599] Step 19:

[0600] Users can view information about their ancestral roots and related regions on their devices, and learn about regions and cultures that interest them.

[0601] Through this series of steps, the system can provide comprehensive information on the user's health risks and ancestral roots, and suggest individualized preventative measures.

[0602] (Example 1)

[0603] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0604] Currently, while systems exist on the market for analyzing individual disease risks and ancestral roots, they often lack sufficient preventative measures or lifestyle improvement suggestions for users, and the management of sample kits is uncertain. Furthermore, data protection and encryption measures may be inadequate. A major challenge is the lack of efficient and secure means to deliver analysis results and related information.

[0605] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0606] In this invention, the server includes means for receiving and analyzing saliva or blood samples, means for calculating disease risk using the analyzed DNA data, means for storing the calculation results in the user's profile, means for providing analysis results and preventive measures upon request from the user, means for identifying the user's ancestral roots based on the user's DNA data, means for identifying other users with similar roots and providing regional information, means for generating preventive measures and lifestyle improvement suggestions using a generative AI model, means for arranging the delivery of sample kits, means for tracking the delivery status of samples, and means for data protection and encryption. As a result, users can not only obtain comprehensive disease risk information and ancestral roots information, but also receive suggestions for effective preventive measures, and furthermore, reliability in sample management and data protection is improved.

[0607] A "saliva sample" is a liquid biological sample collected from the user's oral cavity.

[0608] A "blood sample" is a biological sample that uses blood collected from the user's body.

[0609] "Analysis" is the process of examining DNA information extracted from a biological sample and clarifying its contents.

[0610] "DNA data" refers to digital data containing deoxyribonucleic acid information obtained from saliva or blood samples.

[0611] "Disease risk" is a quantitative assessment of the likelihood of a specific disease occurring.

[0612] A "user profile" is a digital database that aggregates information about an individual user.

[0613] "Preventive measures" are specific action guidelines aimed at reducing the risk of a particular disease.

[0614] "Ancestral roots" refers to geographical and genetic information about the user's distant ancestors.

[0615] A "generative AI model" is an algorithm that uses artificial intelligence to generate useful information and suggestions from data.

[0616] A "sample kit" is a set that includes equipment and containers for collecting biological samples.

[0617] "Shipping arrangements" refers to the series of procedures for delivering sample kits to users.

[0618] "Tracking delivery status" is the process of checking the status of a sample kit to the user or lab.

[0619] "Data protection" refers to measures taken to protect users' personal information and analytical data from unauthorized access.

[0620] "Encryption" is a technique that transforms data into a format that cannot be deciphered in order to protect it.

[0621] System Overview

[0622] This system analyzes saliva or blood samples provided by users to identify disease risks and ancestral roots. The system consists of users, terminals, and a server. Users access the server via their terminals to request sample kits, check results, and obtain preventative measures. The server is responsible for receiving samples, analyzing them, storing data, and providing results.

[0623] Explain the program's processing in natural language.

[0624] Request and send out sample kits

[0625] 1. The user accesses the application form on the website using their device and enters the required information. This utilizes a web form using HTML and JavaScript.

[0626] 2. The server receives the information sent by the user and stores it in a database (e.g., MySQL).

[0627] 3. The server will arrange for the sample kit to be sent, using the APIs of external shipping companies (e.g., DHL or FedEx) to request shipment.

[0628] 4. The user receives the sample kit at home a few days later.

[0629] Sample reception and analysis

[0630] 1. The user collects a saliva or blood sample following the instructions on the sample kit.

[0631] 2. The user sends the collected samples to the lab.

[0632] 3. The lab receives the sample and performs DNA analysis (e.g., using PCR equipment or next-generation sequencers). The analysis results are converted into digital data.

[0633] 4. The lab sends the analysis results to the server using the SSL / TLS encryption protocol.

[0634] 5. The server links the received analysis results to the user profile and saves them in the database.

[0635] Analysis of disease risk and provision of results

[0636] 1. The server calculates disease risk based on the analysis results. Specifically, it executes data analysis scripts using Python's pandas or scikit-learn.

[0637] 2. The server saves the calculation results to the user profile.

[0638] 3. The user logs into the website via their device and checks the results on their My Page.

[0639] 4. The server uses an generated AI model (e.g., OpenAI's GPT-3) to display preventative measures and lifestyle improvement suggestions based on the analysis results.

[0640] Examples of prompt statements:

[0641] "According to Ms. A's DNA data, she is at risk of heart disease. Please advise her to take preventative measures such as proper diet, exercise, and regular medical checkups."

[0642] Analysis of ancestral roots and provision of results

[0643] 1. The server analyzes the user's ancestral roots using their DNA data. It uses a genome database and matching algorithms.

[0644] 2. The server matches the data with other users' data to identify common ancestors and regional information.

[0645] 3. The user requests information about their ancestral roots using their device.

[0646] 4. The server receives the request and displays the analysis results on the user's device. This includes geographical root maps and shared genetic characteristics.

[0647] As described above, this system provides comprehensive information about users' health risks and ancestral roots, offers advice on preventative measures and lifestyle improvements, and implements reliable data management and encryption.

[0648] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0649] Step 1:

[0650] The user accesses the application form on the website using their device, enters the required personal information (name, address, contact information, etc.), and presses the "Submit" button. The entered data is then sent from the device to the server.

[0651] Input: Personal information entered by the user.

[0652] Output: Transmitted personal data.

[0653] Step 2:

[0654] The server receives the information sent by the user and saves it to a database (e.g., MySQL). After saving is complete, the server proceeds with arranging the shipment of the sample kit.

[0655] Input: Personal information data submitted.

[0656] Output: Personal information stored in the database.

[0657] Step 3:

[0658] The server uses the shipping company's API (e.g., DHL or FedEx) to request the shipment of sample kits. It receives information such as shipping costs and estimated delivery dates from the shipping company and arranges for the delivery of the sample kits.

[0659] Input: Personal information stored in the database.

[0660] Output: Shipping arrangement information from the delivery company.

[0661] Step 4:

[0662] The user receives a sample kit at home a few days later. The sample kit includes instructions and a container for collecting a saliva or blood sample.

[0663] Input: Sample kit.

[0664] Output: User receives sample kit.

[0665] Step 5:

[0666] The user collects a saliva or blood sample according to the instructions on the sample kit. For saliva, the specified amount is placed in a dedicated container, and for blood, it is collected in a specific tube.

[0667] Input: Sample kit.

[0668] Output: Collected saliva or blood sample.

[0669] Step 6:

[0670] The user places the collected sample in the enclosed return envelope and sends it to the lab's address. The lab receives the sample and confirms receipt.

[0671] Input: A collected saliva or blood sample.

[0672] Output: Sample sent to the lab.

[0673] Step 7:

[0674] The lab begins DNA analysis on the received samples. PCR equipment and next-generation sequencers are used to obtain the DNA sequence information of the samples.

[0675] Input: Sample sent to the lab.

[0676] Output: Analyzed DNA data.

[0677] Step 8:

[0678] The lab sends the analyzed DNA data to the server in digital format. SSL / TLS encryption protocol is used for communication.

[0679] Input: Analyzed DNA data.

[0680] Output: DNA data sent to the server.

[0681] Step 9:

[0682] The server links the received DNA data to the user profile and saves it to the database. The user is then notified when the saving process is complete.

[0683] Input: DNA data sent to the server.

[0684] Output: DNA data linked to the user profile.

[0685] Step 10:

[0686] The server calculates disease risk based on the analysis results. It executes data analysis scripts using Python's pandas and scikit-learn and applies a risk assessment model.

[0687] Input: DNA data linked to the user profile.

[0688] Output: Calculated disease risk data.

[0689] Step 11:

[0690] The server saves the calculation results to the user's profile, making them accessible to the user. The saved results are displayed on the user's My Page on the website.

[0691] Input: Calculated disease risk data.

[0692] Output: Risk data stored in the user profile.

[0693] Step 12:

[0694] Users log in to the website via their device and view their results on their personal page. Along with the analysis results, preventative measures and lifestyle improvement suggestions are displayed using a generated AI model.

[0695] Input: User login information.

[0696] Output: A My Page displaying analysis results and preventative measures.

[0697] Step 13:

[0698] The server uses generated AI models (e.g., OpenAI's GPT-3) to create customized preventative measures and lifestyle improvement suggestions based on the analysis results.

[0699] Input: Analysis results.

[0700] Output: Generated precautions.

[0701] Examples of prompt statements:

[0702] "According to Ms. A's DNA data, she is at risk of heart disease. Please advise her to take preventative measures such as proper diet, exercise, and regular medical checkups."

[0703] Step 14:

[0704] The server analyzes the user's ancestral roots using their DNA data. It uses a genome database and matching algorithms to identify geographical and genetic information about their ancestors.

[0705] Input: DNA data linked to the user profile.

[0706] Output: Identified ancestral roots information.

[0707] Step 15:

[0708] The server matches DNA data with other users to identify common ancestors and regional information. Statistical analysis is performed to extract user information with high similarity.

[0709] Input: Identified ancestral root information.

[0710] Output: Similar users and location information.

[0711] Step 16:

[0712] The user uses their device to request information about their ancestral roots. The request is sent to the server.

[0713] Input: User request information.

[0714] Output: The request sent to the server.

[0715] Step 17:

[0716] The server receives the request and displays the analysis results on the user's device. This includes geographical root maps and shared genetic characteristics.

[0717] Input: The request sent to the server.

[0718] Output: Analysis results displayed on the user's terminal.

[0719] (Application Example 1)

[0720] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0721] In modern society, personalized health management tailored to each individual's health condition and genetic risks is in demand. However, current systems make it difficult to provide specific health guidance based on disease risk and genetic background. Furthermore, there is a lack of means to propose and efficiently deliver optimal meal plans for each individual. As a result, many people are unable to manage their health properly and face lifestyle-related diseases and other health risks.

[0722] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0723] This invention includes a server that provides means for receiving and analyzing saliva or blood samples, means for calculating disease risk using the analyzed DNA data, means for storing the calculation results in the user's profile, means for providing analysis results and preventive measures upon user request, means for identifying ancestral roots based on the user's DNA data, means for identifying other users with similar roots and providing regional information, means for proposing a meal plan based on the analyzed DNA data, means for ordering and managing the delivery of meals based on the proposed meal plan, and means for tracking the delivery status in real time. This enables health management based on the individual user's genetic risk and provides appropriate meal plans tailored to that risk. This reduces individual health risks and enables more effective health management.

[0724] A "saliva or blood sample" is a type of biological fluid collected from the user and used for the extraction and analysis of DNA containing genetic information.

[0725] "Means of analysis" refer to devices, systems, and software that perform a series of processes to extract DNA from a sample and to reveal its structure and properties.

[0726] "DNA data" refers to DNA sequence information containing a user's genetic information, and is used to identify disease risks and ancestral roots.

[0727] "Disease risk" is an indicator that shows the likelihood of a user developing a specific disease in the future, based on their specific genetic information.

[0728] A "user profile" is a dataset containing personal information, analysis results, and health risk information about a user.

[0729] "Preventive measures" refer to specific actions and advice for maintaining health and preventing disease, proposed based on the analysis results.

[0730] "Ancestral roots" refers to historical and geographical origin information identified based on the user's genetic information.

[0731] "Other users with similar roots" refers to other users who have been identified as having the same ancestors or geographical background.

[0732] "Regional information" refers to data about the geographical distribution of users who are related by ancestry or genetics.

[0733] A "meal plan" is a plan for optimal nutritional intake suggested based on the user's genetic information and health risks.

[0734] "Means of managing delivery" refers to the system and procedures that oversee the process of cooking and delivering meals selected by the user based on the proposed meal plan.

[0735] "A means of tracking delivery status in real time" refers to a system that monitors the delivery progress of meals ordered by users in real time and provides information on it.

[0736] System Overview

[0737] The system implemented based on this invention involves a user providing a saliva or blood sample, and then analyzing the DNA data obtained from that sample to suggest and deliver personalized healthy meals based on the individual's disease risk and genetic background. This system operates in conjunction with a server, terminals, and delivery service.

[0738] Sample submission and analysis

[0739] The user first accesses the server's website or application using a terminal and requests a saliva or blood sample kit. The server receives the request and ships the sample kit to the user. The user receives the kit, collects a saliva or blood sample, and then sends the sample to a designated laboratory.

[0740] In the lab, samples are received, and specialized analytical equipment analyzes the DNA. The analyzed DNA data is sent to a server using a secure communication method and linked to the user profile.

[0741] Analysis of disease risk and proposals for healthy eating

[0742] The server calculates the user's disease risk based on the received DNA data and stores the results in the user's profile. Furthermore, it suggests appropriate preventive measures based on the analysis results. The server then uses a generative AI model to generate an optimal diet plan based on the user's genetic information and health risks.

[0743] For example, if the server predicts a high risk of diabetes based on the genetic information of "User ID: 12345," it will suggest a diet plan that reduces sugar intake. This result will be displayed on the user's device.

[0744] Food ordering and delivery management

[0745] The user uses a terminal to select a meal from the suggested meal plan and sends the order to the server. The server orders the selected meal from the appropriate delivery service and proceeds with the delivery arrangements. This includes the ability to send specific order information using the delivery service's API and track the progress in real time.

[0746] Track delivery status

[0747] Users can monitor the delivery status of their ordered meals in real time through their device. The server receives delivery information from the delivery service and provides it to the user. This process allows users to track the progress until their meal arrives.

[0748] Example of a prompt

[0749] For example, the prompt for a user to submit a sample is as follows:

[0750] "User data: User ID: 12345, Sample data: Saliva sample"

[0751] Furthermore, the prompt text for a user to request a meal plan is as follows:

[0752] "User data: User ID: 12345"

[0753] In this way, the system provides each user with a scientifically-based health plan and supports health management in a way that can be implemented in daily life.

[0754] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0755] Step 1:

[0756] A user accesses the server's website or application using their device and requests a sample kit. The input consists of the user's personal information and sample kit request information. The server receives this data and outputs instructions for shipping the kit. Specifically, the user enters the required information into a form, and that data is sent to the server.

[0757] Step 2:

[0758] The server ships the sample kit to the user based on the application information. The input is the user's address information received in step 1, and this address information is forwarded to the delivery service, which then outputs instructions to ship the kit. Specifically, the server works in conjunction with the delivery system to send the kit to the user.

[0759] Step 3:

[0760] The user receives a kit, follows the instructions to collect a saliva or blood sample, and sends it to the designated lab. The input is the sample obtained from the user, and the output is the lab receiving that sample. Specifically, the user mails the sample to the lab.

[0761] Step 4:

[0762] The lab receives the sample and begins DNA analysis. The input is a saliva or blood sample sent by the user, and the output is the DNA data resulting from the analysis. Specifically, the lab processes the sample, extracts DNA, and analyzes the gene sequence.

[0763] Step 5:

[0764] The analyzed DNA data is transmitted to the server using a secure communication method. The input is DNA data sent from the lab, and the output is the storage of that DNA data on the server. Specifically, the data is encrypted and transferred through a secure channel.

[0765] Step 6:

[0766] The server calculates the user's disease risk based on DNA data. The input is analyzed DNA data, and the output is a health risk score resulting from the calculation. Specifically, the process involves matching gene sequences with known disease-related markers.

[0767] Step 7:

[0768] The server saves the disease risk assessment results to the user's profile. The input is the health risk score, and the output is that it is added to the user's profile database. Specifically, the process involves writing data through database operations.

[0769] Step 8:

[0770] The server provides appropriate preventative measures to the user based on the analysis results. The input is a health risk score, and the output is related preventative measures. Specifically, it uses a health advice generation AI model to create preventative measures and notifies the user.

[0771] Step 9:

[0772] The server generates an optimal meal plan for the user based on DNA data. The input is analyzed DNA data, and the output is a personalized meal plan. Specifically, it uses a generative AI model that generates a nutrition plan that takes genetic information and health risks into consideration.

[0773] Step 10:

[0774] The user selects a meal from a suggested meal plan using their device and sends the order to the server. The input is the meal plan selected by the user, and the output is the order information. Specifically, the user selects a menu item from the application, and the order information is transferred to the server.

[0775] Step 11:

[0776] The server instructs the delivery service with order information and manages the delivery. The input is the user's order information, and the output is a delivery instruction to the delivery service. Specifically, it uses an API to connect with the delivery system and send delivery instructions.

[0777] Step 12:

[0778] Users can monitor the delivery status of their ordered meals in real time via their device. Input is delivery progress information from the delivery service, and output is the delivery status provided to the user. Specifically, the system receives status information from the delivery service and notifies the user.

[0779] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0780] This system analyzes saliva or blood samples provided by the user to identify disease risks and ancestral roots. Furthermore, by combining this with an emotion engine that recognizes the user's emotions, it tailors the presentation of the analysis results to provide appropriate advice and preventative measures. The following describes the system's program processing in natural language, along with specific examples.

[0781] System Overview

[0782] This system consists of a user, a terminal, a server, a lab, and an emotion engine. Users access the server via their terminal to request sample kits, check results, and obtain preventative measures. The server is responsible for receiving and analyzing samples, storing data, providing results, and recognizing the user's emotions using the emotion engine.

[0783] Program processing

[0784] Request and send out sample kits

[0785] 1. The user accesses the server's website using their device and applies for a sample kit.

[0786] 2. The server receives the application information and arranges for the sample kit to be sent to the user.

[0787] 3. The user receives a sample kit and collects a saliva or blood sample.

[0788] 4. The user sends the collected samples to the designated laboratory.

[0789] Sample reception and analysis

[0790] 5. The lab receives the sample and begins DNA analysis.

[0791] 6. The analyzed DNA data is sent to the server and linked to the user profile.

[0792] Analysis of disease risk and provision of results

[0793] 7. The server analyzes the received DNA data and calculates the user's disease risk.

[0794] 8. The server saves the disease risk to the user profile and notifies the user when the results are ready.

[0795] 9. The emotion engine recognizes the user's emotions based on data obtained from the user's device (e.g., feedback, behavioral history, facial expressions, etc.).

[0796] 10. When the server provides analysis results, it adjusts the presentation method of the results based on the user's emotional state recognized by the emotion engine.

[0797] 11. Based on the analysis results, the server provides appropriate preventative measures and suggestions for lifestyle improvements. Additionally, the emotion engine monitors the user's emotional state and provides timely information as needed.

[0798] Analysis of ancestral roots and provision of results

[0799] 12. The server analyzes the user's DNA data to identify their ancestral roots.

[0800] 13. The server matches the data with other users to identify users with similar backgrounds and regional information.

[0801] 14. The user requests information about their ancestral roots through their device, and the server provides that information.

[0802] Specific example

[0803] Request and send out sample kits

[0804] Person B, wanting to learn about their health risks, uses their device to access the system's website. Person B fills in the required information on the sample kit application form and clicks the submit button. The server receives the application information, and a few days later, the sample kit arrives at Person B's address.

[0805] Sample reception and analysis

[0806] Person B collects a saliva sample according to the instructions in the kit and sends it to the lab. The lab receives the sample and performs DNA analysis. The analysis results are sent to the server and added to Person B's profile.

[0807] Analysis of disease risk and provision of results

[0808] The server calculates disease risk based on B's DNA data and stores this information in B's profile. When B logs in from their device and views the results report, the server displays the analysis results and preventative measures. During this process, an emotion engine recognizes B's emotional state and presents the analysis results at the appropriate time and in the appropriate manner. For example, if B is feeling anxious, the server provides preventative measures along with calm and detailed explanations, taking steps to reassure them.

[0809] Analysis of ancestral roots and provision of results

[0810] The server analyzes B's DNA data to identify their ancestral roots. In addition, it compares the data of other users with similar roots to extract common regional information. When B requests information about their ancestral roots, the server displays that information on their device.

[0811] Through this series of steps, the system can comprehensively provide information on the user's health risks and ancestral roots, and appropriately suggest individualized preventative measures while taking the user's emotional state into consideration.

[0812] The following describes the processing flow.

[0813] Step 1:

[0814] The user accesses the server's website through their device and opens the sample kit application page.

[0815] Step 2:

[0816] The user enters the required information, such as their name, address, and contact details, into the application form and clicks the "Submit" button.

[0817] Step 3:

[0818] The server receives the application data and saves it to the database. The process then automatically proceeds to arrange for the shipment of the sample kit.

[0819] Step 4:

[0820] The server sends a confirmation email to the user notifying them that the sample kit has been shipped.

[0821] Step 5:

[0822] The user receives a sample kit and collects a saliva or blood sample according to the instructions in the kit.

[0823] Step 6:

[0824] The user uses the enclosed return envelope to send the collected sample to the designated laboratory.

[0825] Step 7:

[0826] The lab verifies the contents of the received samples, scans the barcodes, and registers them in the database.

[0827] Step 8:

[0828] The lab begins DNA analysis by extracting DNA from a saliva or blood sample.

[0829] Step 9:

[0830] The extracted DNA is analyzed using a sequencing device to obtain the user's genetic information. Analysis data is then generated.

[0831] Step 10:

[0832] The lab sends the analysis data to the server, which is then linked to the user's profile.

[0833] Step 11:

[0834] The server analyzes the received DNA data and calculates the user's risk of various diseases.

[0835] Step 12:

[0836] The server saves the calculation results to the user profile and notifies the user that the results are ready.

[0837] Step 13:

[0838] The emotion engine recognizes the user's emotions based on data obtained from the user's device (e.g., feedback, behavioral history, facial expressions, etc.).

[0839] Step 14:

[0840] The user logs into the server using their device and requests to view the results report.

[0841] Step 15:

[0842] The server generates a report containing analysis results and preventative measures in response to the user's request.

[0843] Step 16:

[0844] The server adjusts how it presents analysis results based on the user's emotional state recognized by the emotion engine. For example, if the user is feeling anxious, it provides a calm and detailed explanation.

[0845] Step 17:

[0846] Based on the analysis results, the server provides appropriate preventative measures and lifestyle improvement suggestions. Additionally, an emotion engine monitors the user's emotional state and provides timely information as needed.

[0847] Step 18:

[0848] The server identifies the user's ancestral roots based on their DNA data and adds relevant information to the database.

[0849] Step 19:

[0850] The server matches this data with other users' ancestry to identify people with similar roots and extracts regional information.

[0851] Step 20:

[0852] Users request information about their ancestors and roots through their devices, and the server compiles and provides the information to the users.

[0853] Step 21:

[0854] Users can view information about their ancestral roots and related regions on their devices, and learn about regions and cultures that interest them.

[0855] Through this series of steps, the system can comprehensively provide users with information on their health risks and ancestral roots, and appropriately suggest individual preventative measures. Furthermore, the emotion engine can understand the user's emotional state, enabling the provision of optimal information.

[0856] (Example 2)

[0857] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0858] Traditional DNA analysis systems were limited to calculating disease risk and identifying ancestral roots, and did not provide information that took into account the user's emotions. As a result, users who received analysis results were more likely to experience anxiety and stress. Furthermore, detailed preventative measures and lifestyle improvement suggestions were rarely provided in a timely manner.

[0859] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving and analyzing a saliva or blood sample, means for calculating disease risk using the analyzed data, means for storing the calculation results in the user's profile, means for providing analysis results and preventive measures in response to a user request, means for recognizing the user's emotions and adjusting the method of providing analysis results, means for identifying ancestral roots based on the user's data, and means for identifying other users with similar roots and providing regional information. This makes it possible to provide analysis results that give users a greater sense of security and to propose preventive measures and lifestyle improvement plans at the appropriate time.

[0860] A "saliva or blood sample" is a biological sample provided by the user that includes saliva or blood.

[0861] "Analysis" refers to the process of processing data obtained from a sample and extracting meaningful information. Specifically, this includes DNA sequencing and gene analysis.

[0862] "Disease risk calculation" is the process of numerically predicting the risk of developing a specific disease based on analyzed DNA data.

[0863] A "user profile" is an information database that centrally manages all user-related data within the system.

[0864] "Preventive measures" are specific actions or policies provided based on analysis results to reduce the risk of a particular disease.

[0865] "Emotion recognition" is the process of analyzing and identifying a user's emotional state at a given time based on their behavior, facial expressions, and feedback data.

[0866] "Adjusting the method of providing analysis results" refers to a technique that changes the display format and notification method of analysis results according to the user's emotional state.

[0867] "Identifying ancestral roots" is the process of analyzing DNA data to reveal the user's genetic origins and the place of origin of their ancestors.

[0868] "Regional information" refers to information about a specific region obtained by cross-referencing it with data from other users who have a similar genetic origin to the user.

[0869] A "system" is a complex collection of hardware and software that integrates all of the above means and functions to provide consistent services to the user.

[0870] This invention is a system that not only analyzes a user's health risks and ancestral roots, but also provides information tailored to the user's emotions. This system consists of a user, a terminal, a server, a lab, and an emotion recognition engine.

[0871] The user accesses the system via a terminal and requests a sample kit. The server receives the request information and arranges for the sample kit. The user then collects the sample and sends it to the lab. The lab analyzes the received sample and sends the analysis results to the server. Based on the analysis data, the server calculates disease risk and ancestral roots and notifies the user of the results. The following hardware and software are used to ensure this entire process runs smoothly.

[0872] Specifically, we employ the following steps and technologies.

[0873] Hardware and software to be used

[0874] 1. DNA sequencer (e.g., Illumina, Thermo Fisher)

[0875] The lab uses it to analyze samples.

[0876] 2. Genetic analysis tools (e.g., Plink, BEAGLE)

[0877] The server uses DNA data to analyze and calculate disease risk.

[0878] 3. Emotion recognition engine (e.g., Amazon Rekognition, Microsoft Azure's Emotion API)

[0879] The server uses this to recognize the user's emotions and adjust how the analysis results are presented.

[0880] Explanation of program processing in natural language

[0881] Request a sample kit

[0882] The user accesses the system's website using their device and reaches the sample kit application page. The entered application information is sent to the server, which uses the shipping carrier's API to arrange for the kit to be shipped.

[0883] Sample collection and mailing

[0884] A few days later, the user receives a sample kit. The user collects a saliva or blood sample according to the instructions and sends it to the lab using the provided return envelope. The lab receives the sample and analyzes it using a DNA sequencer.

[0885] Calculation and analysis of disease risk

[0886] The analysis data is encrypted and sent to the server. The server uses genetic analysis tools such as Plink and BEAGLE to calculate disease risk. The calculation results are saved in the user's profile, and the user is notified when the results are ready.

[0887] Adjusting emotion recognition and result delivery

[0888] When a user reviews their results, the emotion recognition engine analyzes their emotional state. If anxiety or stress is detected, the server adjusts the content and timing of its display and provides detailed explanations. It also simultaneously offers suggestions for preventative measures and lifestyle improvements.

[0889] Identifying ancestral roots and providing regional information

[0890] The server uses genealogical analysis software such as Genealogist to identify the user's ancestral roots. It then matches this information with user data of similar origins and provides regional information.

[0891] Specific example

[0892] Person B, wanting to learn about their health risks, uses their device to access the system's website. They fill in the required information on the application form and click the submit button. The server receives the application information, and a sample kit arrives at Person B's address a few days later.

[0893] Person B collects a saliva sample according to the instructions in the kit and sends it to the lab. The lab receives the sample and performs DNA analysis. The analysis results are sent to the server and added to Person B's profile.

[0894] The server calculates disease risk based on B's DNA data and saves this information in a profile. When B logs in from their device and views the results report, the server displays the analysis results and preventative measures. An emotion engine recognizes B's emotional state and presents the analysis results at the appropriate time and in the appropriate manner.

[0895] For example, if person B is feeling anxious, the system will provide calm and detailed explanations along with preventative measures to help them feel at ease. The server will analyze person B's DNA data to identify their ancestral roots. In addition, it will cross-reference data with other users who have similar roots to extract common regional information. When person B requests information about their ancestral roots, the server will display that information on their device.

[0896] Example of a prompt

[0897] "How can I calculate disease risk based on DNA data and save it to a user profile?"

[0898] "How can I use an emotion engine to recognize a user's emotions and change how the analysis results are presented?"

[0899] "Please tell me how to design a system that identifies ancestral roots and provides that information to users."

[0900] Through the process described above, the present invention is a system that comprehensively provides information on the user's health risks and ancestral roots, and provides optimal information while taking into account their emotional state.

[0901] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0902] Step 1:

[0903] The user accesses the system's website using their device and reaches the sample kit application page. The user enters the required information, such as their name, address, and contact information, into the form and clicks the application button. This sends the entered application data to the server.

[0904] Input: Application information such as name, address, and contact information.

[0905] Output: Application data stored on the server.

[0906] Step 2:

[0907] The server receives the application information and begins the process of sending the sample kit. The server uses the shipping company's API to arrange for the sample kit to be shipped to the specified address. Once the shipping arrangements are complete, the server sends a confirmation email to the user.

[0908] Input: User application information.

[0909] Output: Arrangement for delivery with the shipping company and confirmation email to the user.

[0910] Step 3:

[0911] A few days later, the user receives a sample kit. The user collects a saliva or blood sample according to the instructions in the kit.

[0912] Input: Sample kit.

[0913] Output: Collected saliva or blood sample.

[0914] Step 4:

[0915] The user places the collected sample in the return envelope included in the sample kit and sends it to the designated lab.

[0916] Input: A collected saliva or blood sample.

[0917] Output: Sample placed in a return envelope.

[0918] Step 5:

[0919] The lab receives the sample sent by the user and sends an acknowledgment of receipt to the system. The lab then analyzes the sample using a DNA sequencer (e.g., a general-purpose DNA sequencer).

[0920] Input: Collected sample.

[0921] Output: Analyzed DNA data.

[0922] Step 6:

[0923] The server receives the analyzed DNA data sent from the lab and stores it, linking it to the corresponding user profile. Data integrity checks are also performed during this process.

[0924] Input: Analyzed DNA data.

[0925] Output: DNA data linked to the user profile.

[0926] Step 7:

[0927] The server uses genetic analysis tools such as Plink and BEAGLE to calculate the user's disease risk based on the received DNA data. The calculated risk information is stored in the user profile.

[0928] Input: Stored DNA data.

[0929] Output: Calculated disease risk information.

[0930] Step 8:

[0931] The server notifies the user when the calculated disease risk results are ready. This notification may be sent via email or in-app message.

[0932] Input: Calculated disease risk information.

[0933] Output: Notification to the user.

[0934] Step 9:

[0935] The emotion recognition engine uses data acquired from the user's device (such as feedback, behavioral history, and facial expressions) to analyze the user's emotions. For example, anxiety may be recognized based on feedback data.

[0936] Input: Feedback, behavioral history, and facial expression data.

[0937] Output: Analyzed emotional state.

[0938] Step 10:

[0939] The server adjusts how the analysis results are presented based on the results from the emotion recognition engine. For example, if the user is anxious, it provides a calm explanation, while if they are relaxed, it adds a detailed technical explanation.

[0940] Input: Analyzed emotional state and disease risk information.

[0941] Output: Adjusted result display.

[0942] Step 11:

[0943] Based on the analysis results, the server generates and provides to the user appropriate preventative measures and lifestyle improvement suggestions. The emotion recognition engine continues to monitor the user's emotions and provides information in a timely manner.

[0944] Input: Disease risk information and analyzed emotional state.

[0945] Output: Proposed preventative measures and lifestyle improvements.

[0946] Step 12:

[0947] The server uses genealogical analysis software such as Genealogist to analyze the user's DNA data and identify their ancestral roots.

[0948] Input: User's DNA data.

[0949] Output: Identified ancestral roots information.

[0950] Step 13:

[0951] The server matches DNA data with that of other users to identify users with similar roots and their geographical information.

[0952] Input: Identified ancestral roots information.

[0953] Output: Matched regional information.

[0954] Step 14:

[0955] When a user requests information about their ancestral roots through their device, the server provides that information in real time.

[0956] Input: User request.

[0957] Output: Provided ancestral roots information and regional information.

[0958] (Application Example 2)

[0959] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0960] Traditional health risk and ancestral roots analysis systems often fail to provide users with appropriate feedback tailored to their emotional state, leading to anxiety and doubt about the results. Furthermore, when viewing analysis results in real-time at physical stores, the lack of information based on the user's emotional state can result in decreased user satisfaction.

[0961] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0962] In this invention, the server includes means for receiving and analyzing a saliva or blood sample, means for calculating disease risk using the analyzed DNA data, means for storing the calculation results in the user's profile, means for providing analysis results and preventive measures upon request from the user, means for identifying the user's ancestral roots based on the user's DNA data, means for identifying other users with similar roots and providing regional information, means for recognizing the user's emotions, means for adjusting the method of presenting analysis results based on the recognized emotional state, and means for recognizing the user's emotional state in real time at the store and providing appropriate advice. This enables appropriate feedback and advice based on the user's emotional state.

[0963] A "saliva or blood sample" is a biological sample provided by the user and is used as material for DNA analysis.

[0964] "Means of analysis" refers to a device or software that extracts DNA from a saliva or blood sample and reads that DNA information.

[0965] A "means for calculating disease risk" refers to an algorithm or program that quantifies the risk of developing a specific disease based on analyzed DNA data.

[0966] "Means of saving to the user's profile" refers to a system that records calculation results in a database and manages them in conjunction with the user's identification information.

[0967] "Means of providing analysis results and preventive measures" refers to a method of displaying or notifying users of calculated disease risks and corresponding preventive measures in response to their requests.

[0968] "Methods for identifying ancestral roots" refers to algorithms that analyze a user's DNA data to identify their genetic background.

[0969] "Means for identifying other users with similar roots and providing regional information" refers to a system that matches users against a database of other users to identify genetically similar users or those sharing common regions.

[0970] "Means of recognizing user emotions" refers to technologies that identify a user's emotional state by analyzing their facial expressions, behavior, and feedback.

[0971] "Means for adjusting the presentation method of analysis results based on recognized emotional states" refers to a system for presenting analysis results in different formats and timings depending on the user's emotions.

[0972] "A means of providing appropriate advice in real time" refers to a method of analyzing the emotional state of users in physical stores in real time and immediately providing corresponding feedback and recommendations.

[0973] The following describes an embodiment for carrying out this invention. This system mainly consists of a server, terminals, users, a lab, and an emotion engine.

[0974] Equipment and hardware configuration

[0975] The server possesses high-performance data analysis and storage capabilities, and manages analysis algorithms and user profile data. The server also incorporates an emotion engine that recognizes user emotions and adjusts feedback accordingly.

[0976] A terminal is a device that users operate, and can take various forms such as smartphones, PCs, and tablets. In addition, smart glasses and head-mounted displays are sometimes adopted for use in physical stores.

[0977] The lab is a specialized facility that receives saliva or blood samples provided by users and performs DNA analysis.

[0978] Software Configuration

[0979] The software used includes TensorFlow for emotion recognition and a specialized API for DNA analysis. Additionally, a dedicated SDK (Software Development Kit) is incorporated to process data from smart glasses and head-mounted displays.

[0980] Data processing and calculations

[0981] The server first analyzes the sample provided by the user in a lab to obtain DNA data. Based on this DNA data, the server analyzes disease risk and ancestral roots. The generated data is stored in the user profile. When the user requests these results, the server provides the analysis results along with appropriate preventive measures.

[0982] Furthermore, the emotion recognition engine recognizes the user's emotions based on real-time data obtained from the device or smart glasses (e.g., facial expressions, behavioral history) and adjusts how the analysis results are presented. For example, if the user is feeling anxious, it provides reassuring feedback.

[0983] Specific example

[0984] For example, consider a scenario where a user visits a physical store and interacts with a store employee wearing smart glasses. When the user requests health risk information, the server presents disease risks based on DNA analysis data. If the emotion engine detects the user's anxiety, the server provides a message such as, "Don't worry. The risks are minimal, and please take the following precautions to manage your health."

[0985] Example of a prompt

[0986] The following prompt statements are used as input to the generative AI model.

[0987] "If a user is feeling anxious when health risks are displayed, what kind of calming feedback should be provided?"

[0988] This format makes it possible to provide feedback that takes into account the user's real-time emotional state, even in physical stores. This improves user satisfaction and deepens their understanding and acceptance of the results.

[0989] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0990] Step 1:

[0991] The user accesses the server's website using their device and applies for a sample kit. The user enters details such as their user information and shipping address, and the server records the application information as output.

[0992] Step 2:

[0993] The server receives the application information and arranges for the sample kit to be sent to the user. It uses the user's application information as input and generates an order for the shipping procedure as output.

[0994] Step 3:

[0995] The user receives a sample kit, collects a saliva or blood sample, and sends the sample to the designated lab according to the instructions. The input requires the kit instructions and the user's actions, and the output is the sample sent to the lab.

[0996] Step 4:

[0997] The lab receives the sample and performs DNA analysis. The analysis results are sent to a server. A saliva or blood sample is used as input, and the analyzed DNA data is sent to the server as output.

[0998] Step 5:

[0999] The server processes DNA data received from the lab and adds disease risk and ancestral roots information to the user's profile. DNA analysis data is used as input, and the updated user profile is saved as output.

[1000] Step 6:

[1001] When a user requests analysis results and preventive measures through their device, the server retrieves the results from stored profile information. The user's request information is used as input, and disease risk and preventive measures are generated as output.

[1002] Step 7:

[1003] The emotion recognition engine acquires real-time user emotion data from the device or smart glasses in a physical store. Facial expressions and behavioral data are used as input, and the user's emotional state is recognized as output.

[1004] Step 8:

[1005] The server adjusts the presentation method of the analysis results based on the emotion recognition results. Emotion recognition data is used as input, and the adjusted presentation method and feedback are generated as output.

[1006] Step 9:

[1007] Using smart glasses in physical stores, store staff interact with users in real time, providing tailored analysis results and preventative measures. Feedback data from a server is used as input, and appropriate advice is provided to the user as output.

[1008] This process enables personalized healthcare and advice that takes into account the user's emotional state.

[1009] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1010] The data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One 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">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1011] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[1012] [Third Embodiment]

[1013] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[1014] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1015] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1016] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[1017] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1018] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1019] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1020] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1021] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1022] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1023] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1024] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[1025] This system analyzes saliva or blood samples provided by users to identify disease risks and ancestral roots. The following describes the system's program processing in natural language, along with specific examples.

[1026] *Detailed steps will be omitted at this stage, as there will be questions about the processing steps later.

[1027] System Overview

[1028] This system consists of users, terminals, and a server. Users access the server through their terminals to request sample kits, check results, and obtain preventative measures. The server is responsible for receiving samples, analyzing them, storing data, and providing results.

[1029] Program processing

[1030] Request and send out sample kits

[1031] 1. The user accesses the server's website using their device and applies for a sample kit.

[1032] 2. The server receives the application information and arranges for the sample kit to be sent to the user.

[1033] 3. The user receives a sample kit and collects a saliva or blood sample.

[1034] 4. The user sends the collected samples to the designated laboratory.

[1035] Sample reception and analysis

[1036] 5. The lab receives the sample and begins DNA analysis.

[1037] 6. The analyzed DNA data is sent to the server and linked to the user profile.

[1038] Analysis of disease risk and provision of results

[1039] 7. The server analyzes the received DNA data and calculates the user's disease risk.

[1040] 8. The server stores disease risk in the user profile and provides the results upon user request.

[1041] 9. Based on the analysis results, the server also provides suggestions for preventative measures and lifestyle improvements.

[1042] Analysis of ancestral roots and provision of results

[1043] 10. The server analyzes the user's DNA data to identify their ancestral roots.

[1044] 11. The server matches the data with other users to identify users with similar backgrounds and regional information.

[1045] 12. The user requests information about their ancestral roots through their device, and the server provides that information.

[1046] Specific example

[1047] Request and send out sample kits

[1048] Person A, wanting to learn about their health risks, accesses the system's website using their device. Person A fills in the required information on the sample kit application form and clicks the submit button. The server receives the application information, and a few days later, the sample kit arrives at Person A's address.

[1049] Sample reception and analysis

[1050] Person A collects a saliva sample according to the instructions in the kit and sends it to the lab. The lab receives the sample and performs DNA analysis. The analysis results are sent to the server and added to Person A's profile.

[1051] Analysis of disease risk and provision of results

[1052] The server calculates disease risk based on person A's DNA data and saves this information to person A's profile. When person A logs in from their device and views the results report, the server displays the analysis results and preventive measures.

[1053] Analysis of ancestral roots and provision of results

[1054] The server analyzes A's DNA data to identify their ancestral roots. In addition, it compares the data of other users with similar roots to extract common regional information. When A requests information about their ancestral roots, the server displays that information on their device.

[1055] In this way, the system can provide users with comprehensive information about their health risks and ancestral roots, and offer advice on preventative measures and lifestyle improvements.

[1056] The following describes the processing flow.

[1057] Step 1:

[1058] The user accesses the server's website through their device and opens the sample kit application page.

[1059] Step 2:

[1060] The user enters the required information, such as their name, address, and contact details, into the application form and clicks the "Submit" button.

[1061] Step 3:

[1062] The server receives the application data and saves it to the database. The process then automatically proceeds to arrange for the shipment of the sample kit.

[1063] Step 4:

[1064] The server sends a confirmation email to the user notifying them that the sample kit has been shipped.

[1065] Step 5:

[1066] The user receives a sample kit and collects a saliva or blood sample according to the instructions in the kit.

[1067] Step 6:

[1068] The user uses the enclosed return envelope to send the collected sample to the designated laboratory.

[1069] Step 7:

[1070] The lab verifies the contents of the received samples, scans the barcodes, and registers them in the database.

[1071] Step 8:

[1072] The lab begins DNA analysis by extracting DNA from a saliva or blood sample.

[1073] Step 9:

[1074] The extracted DNA is analyzed using a sequencing device to obtain the user's genetic information. Analysis data is then generated.

[1075] Step 10:

[1076] The lab sends the analysis data to the server, which is then linked to the user's profile.

[1077] Step 11:

[1078] The server analyzes the received DNA data and calculates the user's risk of various diseases.

[1079] Step 12:

[1080] The server saves the calculation results to the user profile and notifies the user that the results are ready.

[1081] Step 13:

[1082] The user logs into the server using their device and requests to view the results report.

[1083] Step 14:

[1084] The server generates a report containing analysis results and preventative measures in response to the user's request and displays it on the terminal.

[1085] Step 15:

[1086] The server will, if necessary, predict diseases with a high incidence rate in the future and suggest additional preventive measures.

[1087] Step 16:

[1088] The server identifies the user's ancestral roots based on their DNA data and adds relevant information to the database.

[1089] Step 17:

[1090] The server matches this data with other users' ancestry to identify people with similar roots and extracts regional information.

[1091] Step 18:

[1092] Users request information about their ancestors and roots through their devices, and the server compiles and provides the information to the users.

[1093] Step 19:

[1094] Users can view information about their ancestral roots and related regions on their devices, and learn about regions and cultures that interest them.

[1095] Through this series of steps, the system can provide comprehensive information on the user's health risks and ancestral roots, and suggest individualized preventative measures.

[1096] (Example 1)

[1097] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1098] Currently, while systems exist on the market for analyzing individual disease risks and ancestral roots, they often lack sufficient preventative measures or lifestyle improvement suggestions for users, and the management of sample kits is uncertain. Furthermore, data protection and encryption measures may be inadequate. A major challenge is the lack of efficient and secure means to deliver analysis results and related information.

[1099] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1100] In this invention, the server includes means for receiving and analyzing saliva or blood samples, means for calculating disease risk using the analyzed DNA data, means for storing the calculation results in the user's profile, means for providing analysis results and preventive measures upon request from the user, means for identifying the user's ancestral roots based on the user's DNA data, means for identifying other users with similar roots and providing regional information, means for generating preventive measures and lifestyle improvement suggestions using a generative AI model, means for arranging the delivery of sample kits, means for tracking the delivery status of samples, and means for data protection and encryption. As a result, users can not only obtain comprehensive disease risk information and ancestral roots information, but also receive suggestions for effective preventive measures, and furthermore, reliability in sample management and data protection is improved.

[1101] A "saliva sample" is a liquid biological sample collected from the user's oral cavity.

[1102] A "blood sample" is a biological sample that uses blood collected from the user's body.

[1103] "Analysis" is the process of examining DNA information extracted from a biological sample and clarifying its contents.

[1104] "DNA data" refers to digital data containing deoxyribonucleic acid information obtained from saliva or blood samples.

[1105] "Disease risk" is a quantitative assessment of the likelihood of a specific disease occurring.

[1106] A "user profile" is a digital database that aggregates information about an individual user.

[1107] "Preventive measures" are specific action guidelines aimed at reducing the risk of a particular disease.

[1108] "Ancestral roots" refers to geographical and genetic information about the user's distant ancestors.

[1109] A "generative AI model" is an algorithm that uses artificial intelligence to generate useful information and suggestions from data.

[1110] A "sample kit" is a set that includes equipment and containers for collecting biological samples.

[1111] "Shipping arrangements" refers to the series of procedures for delivering sample kits to users.

[1112] "Tracking delivery status" is the process of checking the status of a sample kit to the user or lab.

[1113] "Data protection" refers to measures taken to protect users' personal information and analytical data from unauthorized access.

[1114] "Encryption" is a technique that transforms data into a format that cannot be deciphered in order to protect it.

[1115] System Overview

[1116] This system analyzes saliva or blood samples provided by users to identify disease risks and ancestral roots. The system consists of users, terminals, and a server. Users access the server via their terminals to request sample kits, check results, and obtain preventative measures. The server is responsible for receiving samples, analyzing them, storing data, and providing results.

[1117] Explain the program's processing in natural language.

[1118] Request and send out sample kits

[1119] 1. The user accesses the application form on the website using their device and enters the required information. This utilizes a web form using HTML and JavaScript.

[1120] 2. The server receives the information sent by the user and stores it in a database (e.g., MySQL).

[1121] 3. The server will arrange for the sample kit to be sent, using the APIs of external shipping companies (e.g., DHL or FedEx) to request shipment.

[1122] 4. The user receives the sample kit at home a few days later.

[1123] Sample reception and analysis

[1124] 1. The user collects a saliva or blood sample following the instructions on the sample kit.

[1125] 2. The user sends the collected samples to the lab.

[1126] 3. The lab receives the sample and performs DNA analysis (e.g., using PCR equipment or next-generation sequencers). The analysis results are converted into digital data.

[1127] 4. The lab sends the analysis results to the server using the SSL / TLS encryption protocol.

[1128] 5. The server links the received analysis results to the user profile and saves them in the database.

[1129] Analysis of disease risk and provision of results

[1130] 1. The server calculates disease risk based on the analysis results. Specifically, it executes data analysis scripts using Python's pandas or scikit-learn.

[1131] 2. The server saves the calculation results to the user profile.

[1132] 3. The user logs into the website via their device and checks the results on their My Page.

[1133] 4. The server uses an generated AI model (e.g., OpenAI's GPT-3) to display preventative measures and lifestyle improvement suggestions based on the analysis results.

[1134] Examples of prompt statements:

[1135] "According to Ms. A's DNA data, she is at risk of heart disease. Please advise her to take preventative measures such as proper diet, exercise, and regular medical checkups."

[1136] Analysis of ancestral roots and provision of results

[1137] 1. The server analyzes the user's ancestral roots using their DNA data. It uses a genome database and matching algorithms.

[1138] 2. The server matches the data with other users' data to identify common ancestors and regional information.

[1139] 3. The user requests information about their ancestral roots using their device.

[1140] 4. The server receives the request and displays the analysis results on the user's device. This includes geographical root maps and shared genetic characteristics.

[1141] As described above, this system provides comprehensive information about users' health risks and ancestral roots, offers advice on preventative measures and lifestyle improvements, and implements reliable data management and encryption.

[1142] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1143] Step 1:

[1144] The user accesses the application form on the website using their device, enters the required personal information (name, address, contact information, etc.), and presses the "Submit" button. The entered data is then sent from the device to the server.

[1145] Input: Personal information entered by the user.

[1146] Output: Transmitted personal data.

[1147] Step 2:

[1148] The server receives the information sent by the user and saves it to a database (e.g., MySQL). After saving is complete, the server proceeds with arranging the shipment of the sample kit.

[1149] Input: Personal information data submitted.

[1150] Output: Personal information stored in the database.

[1151] Step 3:

[1152] The server uses the shipping company's API (e.g., DHL or FedEx) to request the shipment of sample kits. It receives information such as shipping costs and estimated delivery dates from the shipping company and arranges for the delivery of the sample kits.

[1153] Input: Personal information stored in the database.

[1154] Output: Shipping arrangement information from the delivery company.

[1155] Step 4:

[1156] The user receives a sample kit at home a few days later. The sample kit includes instructions and a container for collecting a saliva or blood sample.

[1157] Input: Sample kit.

[1158] Output: User receives sample kit.

[1159] Step 5:

[1160] The user collects a saliva or blood sample according to the instructions on the sample kit. For saliva, the specified amount is placed in a dedicated container, and for blood, it is collected in a specific tube.

[1161] Input: Sample kit.

[1162] Output: Collected saliva or blood sample.

[1163] Step 6:

[1164] The user places the collected sample in the enclosed return envelope and sends it to the lab's address. The lab receives the sample and confirms receipt.

[1165] Input: A collected saliva or blood sample.

[1166] Output: Sample sent to the lab.

[1167] Step 7:

[1168] The lab begins DNA analysis on the received samples. PCR equipment and next-generation sequencers are used to obtain the DNA sequence information of the samples.

[1169] Input: Sample sent to the lab.

[1170] Output: Analyzed DNA data.

[1171] Step 8:

[1172] The lab sends the analyzed DNA data to the server in digital format. SSL / TLS encryption protocol is used for communication.

[1173] Input: Analyzed DNA data.

[1174] Output: DNA data sent to the server.

[1175] Step 9:

[1176] The server links the received DNA data to the user profile and saves it to the database. The user is then notified when the saving process is complete.

[1177] Input: DNA data sent to the server.

[1178] Output: DNA data linked to the user profile.

[1179] Step 10:

[1180] The server calculates disease risk based on the analysis results. It executes data analysis scripts using Python's pandas and scikit-learn and applies a risk assessment model.

[1181] Input: DNA data linked to the user profile.

[1182] Output: Calculated disease risk data.

[1183] Step 11:

[1184] The server saves the calculation results to the user's profile, making them accessible to the user. The saved results are displayed on the user's My Page on the website.

[1185] Input: Calculated disease risk data.

[1186] Output: Risk data stored in the user profile.

[1187] Step 12:

[1188] Users log in to the website via their device and view their results on their personal page. Along with the analysis results, preventative measures and lifestyle improvement suggestions are displayed using a generated AI model.

[1189] Input: User login information.

[1190] Output: A My Page displaying analysis results and preventative measures.

[1191] Step 13:

[1192] The server uses generated AI models (e.g., OpenAI's GPT-3) to create customized preventative measures and lifestyle improvement suggestions based on the analysis results.

[1193] Input: Analysis results.

[1194] Output: Generated precautions.

[1195] Examples of prompt statements:

[1196] "According to Ms. A's DNA data, she is at risk of heart disease. Please advise her to take preventative measures such as proper diet, exercise, and regular medical checkups."

[1197] Step 14:

[1198] The server analyzes the user's ancestral roots using their DNA data. It uses a genome database and matching algorithms to identify geographical and genetic information about their ancestors.

[1199] Input: DNA data linked to the user profile.

[1200] Output: Identified ancestral roots information.

[1201] Step 15:

[1202] The server matches DNA data with other users to identify common ancestors and regional information. Statistical analysis is performed to extract user information with high similarity.

[1203] Input: Identified ancestral root information.

[1204] Output: Similar users and location information.

[1205] Step 16:

[1206] The user uses their device to request information about their ancestral roots. The request is sent to the server.

[1207] Input: User request information.

[1208] Output: The request sent to the server.

[1209] Step 17:

[1210] The server receives the request and displays the analysis results on the user's device. This includes geographical root maps and shared genetic characteristics.

[1211] Input: The request sent to the server.

[1212] Output: Analysis results displayed on the user's terminal.

[1213] (Application Example 1)

[1214] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1215] In modern society, personalized health management tailored to each individual's health condition and genetic risks is in demand. However, current systems make it difficult to provide specific health guidance based on disease risk and genetic background. Furthermore, there is a lack of means to propose and efficiently deliver optimal meal plans for each individual. As a result, many people are unable to manage their health properly and face lifestyle-related diseases and other health risks.

[1216] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1217] This invention includes a server that provides means for receiving and analyzing saliva or blood samples, means for calculating disease risk using the analyzed DNA data, means for storing the calculation results in the user's profile, means for providing analysis results and preventive measures upon user request, means for identifying ancestral roots based on the user's DNA data, means for identifying other users with similar roots and providing regional information, means for proposing a meal plan based on the analyzed DNA data, means for ordering and managing the delivery of meals based on the proposed meal plan, and means for tracking the delivery status in real time. This enables health management based on the individual user's genetic risk and provides appropriate meal plans tailored to that risk. This reduces individual health risks and enables more effective health management.

[1218] A "saliva or blood sample" is a type of biological fluid collected from the user and used for the extraction and analysis of DNA containing genetic information.

[1219] "Means of analysis" refer to devices, systems, and software that perform a series of processes to extract DNA from a sample and to reveal its structure and properties.

[1220] "DNA data" refers to DNA sequence information containing a user's genetic information, and is used to identify disease risks and ancestral roots.

[1221] "Disease risk" is an indicator that shows the likelihood of a user developing a specific disease in the future, based on their specific genetic information.

[1222] A "user profile" is a dataset containing personal information, analysis results, and health risk information about a user.

[1223] "Preventive measures" refer to specific actions and advice for maintaining health and preventing disease, proposed based on the analysis results.

[1224] "Ancestral roots" refers to historical and geographical origin information identified based on the user's genetic information.

[1225] "Other users with similar roots" refers to other users who have been identified as having the same ancestors or geographical background.

[1226] "Regional information" refers to data about the geographical distribution of users who are related by ancestry or genetics.

[1227] A "meal plan" is a plan for optimal nutritional intake suggested based on the user's genetic information and health risks.

[1228] "Means of managing delivery" refers to the system and procedures that oversee the process of cooking and delivering meals selected by the user based on the proposed meal plan.

[1229] "A means of tracking delivery status in real time" refers to a system that monitors the delivery progress of meals ordered by users in real time and provides information on it.

[1230] System Overview

[1231] The system implemented based on this invention involves a user providing a saliva or blood sample, and then analyzing the DNA data obtained from that sample to suggest and deliver personalized healthy meals based on the individual's disease risk and genetic background. This system operates in conjunction with a server, terminals, and delivery service.

[1232] Sample submission and analysis

[1233] The user first accesses the server's website or application using a terminal and requests a saliva or blood sample kit. The server receives the request and ships the sample kit to the user. The user receives the kit, collects a saliva or blood sample, and then sends the sample to a designated laboratory.

[1234] In the lab, samples are received, and specialized analytical equipment analyzes the DNA. The analyzed DNA data is sent to a server using a secure communication method and linked to the user profile.

[1235] Analysis of disease risk and proposals for healthy eating

[1236] The server calculates the user's disease risk based on the received DNA data and stores the results in the user's profile. Furthermore, it suggests appropriate preventive measures based on the analysis results. The server then uses a generative AI model to generate an optimal diet plan based on the user's genetic information and health risks.

[1237] For example, if the server predicts a high risk of diabetes based on the genetic information of "User ID: 12345," it will suggest a diet plan that reduces sugar intake. This result will be displayed on the user's device.

[1238] Food ordering and delivery management

[1239] The user uses a terminal to select a meal from the suggested meal plan and sends the order to the server. The server orders the selected meal from the appropriate delivery service and proceeds with the delivery arrangements. This includes the ability to send specific order information using the delivery service's API and track the progress in real time.

[1240] Track delivery status

[1241] Users can monitor the delivery status of their ordered meals in real time through their device. The server receives delivery information from the delivery service and provides it to the user. This process allows users to track the progress until their meal arrives.

[1242] Example of a prompt

[1243] For example, the prompt for a user to submit a sample is as follows:

[1244] "User data: User ID: 12345, Sample data: Saliva sample"

[1245] Furthermore, the prompt text for a user to request a meal plan is as follows:

[1246] "User data: User ID: 12345"

[1247] In this way, the system provides each user with a scientifically-based health plan and supports health management in a way that can be implemented in daily life.

[1248] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1249] Step 1:

[1250] A user accesses the server's website or application using their device and requests a sample kit. The input consists of the user's personal information and sample kit request information. The server receives this data and outputs instructions for shipping the kit. Specifically, the user enters the required information into a form, and that data is sent to the server.

[1251] Step 2:

[1252] The server ships the sample kit to the user based on the application information. The input is the user's address information received in step 1, and this address information is forwarded to the delivery service, which then outputs instructions to ship the kit. Specifically, the server works in conjunction with the delivery system to send the kit to the user.

[1253] Step 3:

[1254] The user receives a kit, follows the instructions to collect a saliva or blood sample, and sends it to the designated lab. The input is the sample obtained from the user, and the output is the lab receiving that sample. Specifically, the user mails the sample to the lab.

[1255] Step 4:

[1256] The lab receives the sample and begins DNA analysis. The input is a saliva or blood sample sent by the user, and the output is the DNA data resulting from the analysis. Specifically, the lab processes the sample, extracts DNA, and analyzes the gene sequence.

[1257] Step 5:

[1258] The analyzed DNA data is transmitted to the server using a secure communication method. The input is DNA data sent from the lab, and the output is the storage of that DNA data on the server. Specifically, the data is encrypted and transferred through a secure channel.

[1259] Step 6:

[1260] The server calculates the user's disease risk based on DNA data. The input is analyzed DNA data, and the output is a health risk score resulting from the calculation. Specifically, the process involves matching gene sequences with known disease-related markers.

[1261] Step 7:

[1262] The server saves the disease risk assessment results to the user's profile. The input is the health risk score, and the output is that it is added to the user's profile database. Specifically, the process involves writing data through database operations.

[1263] Step 8:

[1264] The server provides appropriate preventative measures to the user based on the analysis results. The input is a health risk score, and the output is related preventative measures. Specifically, it uses a health advice generation AI model to create preventative measures and notifies the user.

[1265] Step 9:

[1266] The server generates an optimal meal plan for the user based on DNA data. The input is analyzed DNA data, and the output is a personalized meal plan. Specifically, it uses a generative AI model that generates a nutrition plan that takes genetic information and health risks into consideration.

[1267] Step 10:

[1268] The user selects a meal from a suggested meal plan using their device and sends the order to the server. The input is the meal plan selected by the user, and the output is the order information. Specifically, the user selects a menu item from the application, and the order information is transferred to the server.

[1269] Step 11:

[1270] The server instructs the delivery service with order information and manages the delivery. The input is the user's order information, and the output is a delivery instruction to the delivery service. Specifically, it uses an API to connect with the delivery system and send delivery instructions.

[1271] Step 12:

[1272] Users can monitor the delivery status of their ordered meals in real time via their device. Input is delivery progress information from the delivery service, and output is the delivery status provided to the user. Specifically, the system receives status information from the delivery service and notifies the user.

[1273] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1274] This system analyzes saliva or blood samples provided by the user to identify disease risks and ancestral roots. Furthermore, by combining this with an emotion engine that recognizes the user's emotions, it tailors the presentation of the analysis results to provide appropriate advice and preventative measures. The following describes the system's program processing in natural language, along with specific examples.

[1275] System Overview

[1276] This system consists of a user, a terminal, a server, a lab, and an emotion engine. Users access the server via their terminal to request sample kits, check results, and obtain preventative measures. The server is responsible for receiving and analyzing samples, storing data, providing results, and recognizing the user's emotions using the emotion engine.

[1277] Program processing

[1278] Request and send out sample kits

[1279] 1. The user accesses the server's website using their device and applies for a sample kit.

[1280] 2. The server receives the application information and arranges for the sample kit to be sent to the user.

[1281] 3. The user receives a sample kit and collects a saliva or blood sample.

[1282] 4. The user sends the collected samples to the designated laboratory.

[1283] Sample reception and analysis

[1284] 5. The lab receives the sample and begins DNA analysis.

[1285] 6. The analyzed DNA data is sent to the server and linked to the user profile.

[1286] Analysis of disease risk and provision of results

[1287] 7. The server analyzes the received DNA data and calculates the user's disease risk.

[1288] 8. The server saves the disease risk to the user profile and notifies the user when the results are ready.

[1289] 9. The emotion engine recognizes the user's emotions based on data obtained from the user's device (e.g., feedback, behavioral history, facial expressions, etc.).

[1290] 10. When the server provides analysis results, it adjusts the presentation method of the results based on the user's emotional state recognized by the emotion engine.

[1291] 11. Based on the analysis results, the server provides appropriate preventative measures and suggestions for lifestyle improvements. Additionally, the emotion engine monitors the user's emotional state and provides timely information as needed.

[1292] Analysis of ancestral roots and provision of results

[1293] 12. The server analyzes the user's DNA data to identify their ancestral roots.

[1294] 13. The server matches the data with other users to identify users with similar backgrounds and regional information.

[1295] 14. The user requests information about their ancestral roots through their device, and the server provides that information.

[1296] Specific example

[1297] Request and send out sample kits

[1298] Person B, wanting to learn about their health risks, uses their device to access the system's website. Person B fills in the required information on the sample kit application form and clicks the submit button. The server receives the application information, and a few days later, the sample kit arrives at Person B's address.

[1299] Sample reception and analysis

[1300] Person B collects a saliva sample according to the instructions in the kit and sends it to the lab. The lab receives the sample and performs DNA analysis. The analysis results are sent to the server and added to Person B's profile.

[1301] Analysis of disease risk and provision of results

[1302] The server calculates disease risk based on B's DNA data and stores this information in B's profile. When B logs in from their device and views the results report, the server displays the analysis results and preventative measures. During this process, an emotion engine recognizes B's emotional state and presents the analysis results at the appropriate time and in the appropriate manner. For example, if B is feeling anxious, the server provides preventative measures along with calm and detailed explanations, taking steps to reassure them.

[1303] Analysis of ancestral roots and provision of results

[1304] The server analyzes B's DNA data to identify their ancestral roots. In addition, it compares the data of other users with similar roots to extract common regional information. When B requests information about their ancestral roots, the server displays that information on their device.

[1305] Through this series of steps, the system can comprehensively provide information on the user's health risks and ancestral roots, and appropriately suggest individualized preventative measures while taking the user's emotional state into consideration.

[1306] The following describes the processing flow.

[1307] Step 1:

[1308] The user accesses the server's website through their device and opens the sample kit application page.

[1309] Step 2:

[1310] The user enters the required information, such as their name, address, and contact details, into the application form and clicks the "Submit" button.

[1311] Step 3:

[1312] The server receives the application data and saves it to the database. The process then automatically proceeds to arrange for the shipment of the sample kit.

[1313] Step 4:

[1314] The server sends a confirmation email to the user notifying them that the sample kit has been shipped.

[1315] Step 5:

[1316] The user receives a sample kit and collects a saliva or blood sample according to the instructions in the kit.

[1317] Step 6:

[1318] The user uses the enclosed return envelope to send the collected sample to the designated laboratory.

[1319] Step 7:

[1320] The lab verifies the contents of the received samples, scans the barcodes, and registers them in the database.

[1321] Step 8:

[1322] The lab begins DNA analysis by extracting DNA from a saliva or blood sample.

[1323] Step 9:

[1324] The extracted DNA is analyzed using a sequencing device to obtain the user's genetic information. Analysis data is then generated.

[1325] Step 10:

[1326] The lab sends the analysis data to the server, which is then linked to the user's profile.

[1327] Step 11:

[1328] The server analyzes the received DNA data and calculates the user's risk of various diseases.

[1329] Step 12:

[1330] The server saves the calculation results to the user profile and notifies the user that the results are ready.

[1331] Step 13:

[1332] The emotion engine recognizes the user's emotions based on data obtained from the user's device (e.g., feedback, behavioral history, facial expressions, etc.).

[1333] Step 14:

[1334] The user logs into the server using their device and requests to view the results report.

[1335] Step 15:

[1336] The server generates a report containing analysis results and preventative measures in response to the user's request.

[1337] Step 16:

[1338] The server adjusts how it presents analysis results based on the user's emotional state recognized by the emotion engine. For example, if the user is feeling anxious, it provides a calm and detailed explanation.

[1339] Step 17:

[1340] Based on the analysis results, the server provides appropriate preventative measures and lifestyle improvement suggestions. Additionally, an emotion engine monitors the user's emotional state and provides timely information as needed.

[1341] Step 18:

[1342] The server identifies the user's ancestral roots based on their DNA data and adds relevant information to the database.

[1343] Step 19:

[1344] The server matches this data with other users' ancestry to identify people with similar roots and extracts regional information.

[1345] Step 20:

[1346] Users request information about their ancestors and roots through their devices, and the server compiles and provides the information to the users.

[1347] Step 21:

[1348] Users can view information about their ancestral roots and related regions on their devices, and learn about regions and cultures that interest them.

[1349] Through this series of steps, the system can comprehensively provide users with information on their health risks and ancestral roots, and appropriately suggest individual preventative measures. Furthermore, the emotion engine can understand the user's emotional state, enabling the provision of optimal information.

[1350] (Example 2)

[1351] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1352] Traditional DNA analysis systems were limited to calculating disease risk and identifying ancestral roots, and did not provide information that took into account the user's emotions. As a result, users who received analysis results were more likely to experience anxiety and stress. Furthermore, detailed preventative measures and lifestyle improvement suggestions were rarely provided in a timely manner.

[1353] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving and analyzing a saliva or blood sample, means for calculating disease risk using the analyzed data, means for storing the calculation results in the user's profile, means for providing analysis results and preventive measures in response to a user request, means for recognizing the user's emotions and adjusting the method of providing analysis results, means for identifying ancestral roots based on the user's data, and means for identifying other users with similar roots and providing regional information. This makes it possible to provide analysis results that give users a greater sense of security and to propose preventive measures and lifestyle improvement plans at the appropriate time.

[1354] A "saliva or blood sample" is a biological sample provided by the user that includes saliva or blood.

[1355] "Analysis" refers to the process of processing data obtained from a sample and extracting meaningful information. Specifically, this includes DNA sequencing and gene analysis.

[1356] "Disease risk calculation" is the process of numerically predicting the risk of developing a specific disease based on analyzed DNA data.

[1357] A "user profile" is an information database that centrally manages all user-related data within the system.

[1358] "Preventive measures" are specific actions or policies provided based on analysis results to reduce the risk of a particular disease.

[1359] "Emotion recognition" is the process of analyzing and identifying a user's emotional state at a given time based on their behavior, facial expressions, and feedback data.

[1360] "Adjusting the method of providing analysis results" refers to a technique that changes the display format and notification method of analysis results according to the user's emotional state.

[1361] "Identifying ancestral roots" is the process of analyzing DNA data to reveal the user's genetic origins and the place of origin of their ancestors.

[1362] "Regional information" refers to information about a specific region obtained by cross-referencing it with data from other users who have a similar genetic origin to the user.

[1363] A "system" is a complex collection of hardware and software that integrates all of the above means and functions to provide consistent services to the user.

[1364] This invention is a system that not only analyzes a user's health risks and ancestral roots, but also provides information tailored to the user's emotions. This system consists of a user, a terminal, a server, a lab, and an emotion recognition engine.

[1365] The user accesses the system via a terminal and requests a sample kit. The server receives the request information and arranges for the sample kit. The user then collects the sample and sends it to the lab. The lab analyzes the received sample and sends the analysis results to the server. Based on the analysis data, the server calculates disease risk and ancestral roots and notifies the user of the results. The following hardware and software are used to ensure this entire process runs smoothly.

[1366] Specifically, we employ the following steps and technologies.

[1367] Hardware and software to be used

[1368] 1. DNA sequencer (e.g., Illumina, Thermo Fisher)

[1369] The lab uses it to analyze samples.

[1370] 2. Genetic analysis tools (e.g., Plink, BEAGLE)

[1371] The server uses DNA data to analyze and calculate disease risk.

[1372] 3. Emotion recognition engine (e.g., Amazon Rekognition, Microsoft Azure's Emotion API)

[1373] The server uses this to recognize the user's emotions and adjust how the analysis results are presented.

[1374] Explanation of program processing in natural language

[1375] Request a sample kit

[1376] The user accesses the system's website using their device and reaches the sample kit application page. The entered application information is sent to the server, which uses the shipping carrier's API to arrange for the kit to be shipped.

[1377] Sample collection and mailing

[1378] A few days later, the user receives a sample kit. The user collects a saliva or blood sample according to the instructions and sends it to the lab using the provided return envelope. The lab receives the sample and analyzes it using a DNA sequencer.

[1379] Calculation and analysis of disease risk

[1380] The analysis data is encrypted and sent to the server. The server uses genetic analysis tools such as Plink and BEAGLE to calculate disease risk. The calculation results are saved in the user's profile, and the user is notified when the results are ready.

[1381] Adjusting emotion recognition and result delivery

[1382] When a user reviews their results, the emotion recognition engine analyzes their emotional state. If anxiety or stress is detected, the server adjusts the content and timing of its display and provides detailed explanations. It also simultaneously offers suggestions for preventative measures and lifestyle improvements.

[1383] Identifying ancestral roots and providing regional information

[1384] The server uses genealogical analysis software such as Genealogist to identify the user's ancestral roots. It then matches this information with user data of similar origins and provides regional information.

[1385] Specific example

[1386] Person B, wanting to learn about their health risks, uses their device to access the system's website. They fill in the required information on the application form and click the submit button. The server receives the application information, and a sample kit arrives at Person B's address a few days later.

[1387] Person B collects a saliva sample according to the instructions in the kit and sends it to the lab. The lab receives the sample and performs DNA analysis. The analysis results are sent to the server and added to Person B's profile.

[1388] The server calculates disease risk based on B's DNA data and saves this information in a profile. When B logs in from their device and views the results report, the server displays the analysis results and preventative measures. An emotion engine recognizes B's emotional state and presents the analysis results at the appropriate time and in the appropriate manner.

[1389] For example, if person B is feeling anxious, the system will provide calm and detailed explanations along with preventative measures to help them feel at ease. The server will analyze person B's DNA data to identify their ancestral roots. In addition, it will cross-reference data with other users who have similar roots to extract common regional information. When person B requests information about their ancestral roots, the server will display that information on their device.

[1390] Example of a prompt

[1391] "How can I calculate disease risk based on DNA data and save it to a user profile?"

[1392] "How can I use an emotion engine to recognize a user's emotions and change how the analysis results are presented?"

[1393] "Please tell me how to design a system that identifies ancestral roots and provides that information to users."

[1394] Through the process described above, the present invention is a system that comprehensively provides information on the user's health risks and ancestral roots, and provides optimal information while taking into account their emotional state.

[1395] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1396] Step 1:

[1397] The user accesses the system's website using their device and reaches the sample kit application page. The user enters the required information, such as their name, address, and contact information, into the form and clicks the application button. This sends the entered application data to the server.

[1398] Input: Application information such as name, address, and contact information.

[1399] Output: Application data stored on the server.

[1400] Step 2:

[1401] The server receives the application information and begins the process of sending the sample kit. The server uses the shipping company's API to arrange for the sample kit to be shipped to the specified address. Once the shipping arrangements are complete, the server sends a confirmation email to the user.

[1402] Input: User application information.

[1403] Output: Arrangement for delivery with the shipping company and confirmation email to the user.

[1404] Step 3:

[1405] A few days later, the user receives a sample kit. The user collects a saliva or blood sample according to the instructions in the kit.

[1406] Input: Sample kit.

[1407] Output: Collected saliva or blood sample.

[1408] Step 4:

[1409] The user places the collected sample in the return envelope included in the sample kit and sends it to the designated lab.

[1410] Input: A collected saliva or blood sample.

[1411] Output: Sample placed in a return envelope.

[1412] Step 5:

[1413] The lab receives the sample sent by the user and sends an acknowledgment of receipt to the system. The lab then analyzes the sample using a DNA sequencer (e.g., a general-purpose DNA sequencer).

[1414] Input: Collected sample.

[1415] Output: Analyzed DNA data.

[1416] Step 6:

[1417] The server receives the analyzed DNA data sent from the lab and stores it, linking it to the corresponding user profile. Data integrity checks are also performed during this process.

[1418] Input: Analyzed DNA data.

[1419] Output: DNA data linked to the user profile.

[1420] Step 7:

[1421] The server uses genetic analysis tools such as Plink and BEAGLE to calculate the user's disease risk based on the received DNA data. The calculated risk information is stored in the user profile.

[1422] Input: Stored DNA data.

[1423] Output: Calculated disease risk information.

[1424] Step 8:

[1425] The server notifies the user when the calculated disease risk results are ready. This notification may be sent via email or in-app message.

[1426] Input: Calculated disease risk information.

[1427] Output: Notification to the user.

[1428] Step 9:

[1429] The emotion recognition engine uses data acquired from the user's device (such as feedback, behavioral history, and facial expressions) to analyze the user's emotions. For example, anxiety may be recognized based on feedback data.

[1430] Input: Feedback, behavioral history, and facial expression data.

[1431] Output: Analyzed emotional state.

[1432] Step 10:

[1433] The server adjusts how the analysis results are presented based on the results from the emotion recognition engine. For example, if the user is anxious, it provides a calm explanation, while if they are relaxed, it adds a detailed technical explanation.

[1434] Input: Analyzed emotional state and disease risk information.

[1435] Output: Adjusted result display.

[1436] Step 11:

[1437] Based on the analysis results, the server generates and provides to the user appropriate preventative measures and lifestyle improvement suggestions. The emotion recognition engine continues to monitor the user's emotions and provides information in a timely manner.

[1438] Input: Disease risk information and analyzed emotional state.

[1439] Output: Proposed preventative measures and lifestyle improvements.

[1440] Step 12:

[1441] The server uses genealogical analysis software such as Genealogist to analyze the user's DNA data and identify their ancestral roots.

[1442] Input: User's DNA data.

[1443] Output: Identified ancestral roots information.

[1444] Step 13:

[1445] The server matches DNA data with that of other users to identify users with similar roots and their geographical information.

[1446] Input: Identified ancestral roots information.

[1447] Output: Matched regional information.

[1448] Step 14:

[1449] When a user requests information about their ancestral roots through their device, the server provides that information in real time.

[1450] Input: User request.

[1451] Output: Provided ancestral roots information and regional information.

[1452] (Application Example 2)

[1453] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1454] Traditional health risk and ancestral roots analysis systems often fail to provide users with appropriate feedback tailored to their emotional state, leading to anxiety and doubt about the results. Furthermore, when viewing analysis results in real-time at physical stores, the lack of information based on the user's emotional state can result in decreased user satisfaction.

[1455] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1456] In this invention, the server includes means for receiving and analyzing a saliva or blood sample, means for calculating disease risk using the analyzed DNA data, means for storing the calculation results in the user's profile, means for providing analysis results and preventive measures upon request from the user, means for identifying the user's ancestral roots based on the user's DNA data, means for identifying other users with similar roots and providing regional information, means for recognizing the user's emotions, means for adjusting the method of presenting analysis results based on the recognized emotional state, and means for recognizing the user's emotional state in real time at the store and providing appropriate advice. This enables appropriate feedback and advice based on the user's emotional state.

[1457] A "saliva or blood sample" is a biological sample provided by the user and is used as material for DNA analysis.

[1458] "Means of analysis" refers to a device or software that extracts DNA from a saliva or blood sample and reads that DNA information.

[1459] A "means for calculating disease risk" refers to an algorithm or program that quantifies the risk of developing a specific disease based on analyzed DNA data.

[1460] "Means of saving to the user's profile" refers to a system that records calculation results in a database and manages them in conjunction with the user's identification information.

[1461] "Means of providing analysis results and preventive measures" refers to a method of displaying or notifying users of calculated disease risks and corresponding preventive measures in response to their requests.

[1462] "Methods for identifying ancestral roots" refers to algorithms that analyze a user's DNA data to identify their genetic background.

[1463] "Means for identifying other users with similar roots and providing regional information" refers to a system that matches users against a database of other users to identify genetically similar users or those sharing common regions.

[1464] "Means of recognizing user emotions" refers to technologies that identify a user's emotional state by analyzing their facial expressions, behavior, and feedback.

[1465] "Means for adjusting the presentation method of analysis results based on recognized emotional states" refers to a system for presenting analysis results in different formats and timings depending on the user's emotions.

[1466] "A means of providing appropriate advice in real time" refers to a method of analyzing the emotional state of users in physical stores in real time and immediately providing corresponding feedback and recommendations.

[1467] The following describes an embodiment for carrying out this invention. This system mainly consists of a server, terminals, users, a lab, and an emotion engine.

[1468] Equipment and hardware configuration

[1469] The server possesses high-performance data analysis and storage capabilities, and manages analysis algorithms and user profile data. The server also incorporates an emotion engine that recognizes user emotions and adjusts feedback accordingly.

[1470] A terminal is a device that users operate, and can take various forms such as smartphones, PCs, and tablets. In addition, smart glasses and head-mounted displays are sometimes adopted for use in physical stores.

[1471] The lab is a specialized facility that receives saliva or blood samples provided by users and performs DNA analysis.

[1472] Software Configuration

[1473] The software used includes TensorFlow for emotion recognition and a specialized API for DNA analysis. Additionally, a dedicated SDK (Software Development Kit) is incorporated to process data from smart glasses and head-mounted displays.

[1474] Data processing and calculations

[1475] The server first analyzes the sample provided by the user in a lab to obtain DNA data. Based on this DNA data, the server analyzes disease risk and ancestral roots. The generated data is stored in the user profile. When the user requests these results, the server provides the analysis results along with appropriate preventive measures.

[1476] Furthermore, the emotion recognition engine recognizes the user's emotions based on real-time data obtained from the device or smart glasses (e.g., facial expressions, behavioral history) and adjusts how the analysis results are presented. For example, if the user is feeling anxious, it provides reassuring feedback.

[1477] Specific example

[1478] For example, consider a scenario where a user visits a physical store and interacts with a store employee wearing smart glasses. When the user requests health risk information, the server presents disease risks based on DNA analysis data. If the emotion engine detects the user's anxiety, the server provides a message such as, "Don't worry. The risks are minimal, and please take the following precautions to manage your health."

[1479] Example of a prompt

[1480] The following prompt statements are used as input to the generative AI model.

[1481] "If a user is feeling anxious when health risks are displayed, what kind of calming feedback should be provided?"

[1482] This format makes it possible to provide feedback that takes into account the user's real-time emotional state, even in physical stores. This improves user satisfaction and deepens their understanding and acceptance of the results.

[1483] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1484] Step 1:

[1485] The user accesses the server's website using their device and applies for a sample kit. The user enters details such as their user information and shipping address, and the server records the application information as output.

[1486] Step 2:

[1487] The server receives the application information and arranges for the sample kit to be sent to the user. It uses the user's application information as input and generates an order for the shipping procedure as output.

[1488] Step 3:

[1489] The user receives a sample kit, collects a saliva or blood sample, and sends the sample to the designated lab according to the instructions. The input requires the kit instructions and the user's actions, and the output is the sample sent to the lab.

[1490] Step 4:

[1491] The lab receives the sample and performs DNA analysis. The analysis results are sent to a server. A saliva or blood sample is used as input, and the analyzed DNA data is sent to the server as output.

[1492] Step 5:

[1493] The server processes DNA data received from the lab and adds disease risk and ancestral roots information to the user's profile. DNA analysis data is used as input, and the updated user profile is saved as output.

[1494] Step 6:

[1495] When a user requests analysis results and preventive measures through their device, the server retrieves the results from stored profile information. The user's request information is used as input, and disease risk and preventive measures are generated as output.

[1496] Step 7:

[1497] The emotion recognition engine acquires real-time user emotion data from the device or smart glasses in a physical store. Facial expressions and behavioral data are used as input, and the user's emotional state is recognized as output.

[1498] Step 8:

[1499] The server adjusts the presentation method of the analysis results based on the emotion recognition results. Emotion recognition data is used as input, and the adjusted presentation method and feedback are generated as output.

[1500] Step 9:

[1501] Using smart glasses in physical stores, store staff interact with users in real time, providing tailored analysis results and preventative measures. Feedback data from a server is used as input, and appropriate advice is provided to the user as output.

[1502] This process enables personalized healthcare and advice that takes into account the user's emotional state.

[1503] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1504] The data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One 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">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1505] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[1506] [Fourth Embodiment]

[1507] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1508] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1509] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1510] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[1511] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1512] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1513] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1514] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[1515] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1516] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1517] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1518] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1519] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1520] This system analyzes saliva or blood samples provided by users to identify disease risks and ancestral roots. The following describes the system's program processing in natural language, along with specific examples.

[1521] *Detailed steps will be omitted at this stage, as there will be questions about the processing steps later.

[1522] System Overview

[1523] This system consists of users, terminals, and a server. Users access the server through their terminals to request sample kits, check results, and obtain preventative measures. The server is responsible for receiving samples, analyzing them, storing data, and providing results.

[1524] Program processing

[1525] Request and send out sample kits

[1526] 1. The user accesses the server's website using their device and applies for a sample kit.

[1527] 2. The server receives the application information and arranges for the sample kit to be sent to the user.

[1528] 3. The user receives a sample kit and collects a saliva or blood sample.

[1529] 4. The user sends the collected samples to the designated laboratory.

[1530] Sample reception and analysis

[1531] 5. The lab receives the sample and begins DNA analysis.

[1532] 6. The analyzed DNA data is sent to the server and linked to the user profile.

[1533] Analysis of disease risk and provision of results

[1534] 7. The server analyzes the received DNA data and calculates the user's disease risk.

[1535] 8. The server stores disease risk in the user profile and provides the results upon user request.

[1536] 9. Based on the analysis results, the server also provides suggestions for preventative measures and lifestyle improvements.

[1537] Analysis of ancestral roots and provision of results

[1538] 10. The server analyzes the user's DNA data to identify their ancestral roots.

[1539] 11. The server matches the data with other users to identify users with similar backgrounds and regional information.

[1540] 12. The user requests information about their ancestral roots through their device, and the server provides that information.

[1541] Specific example

[1542] Request and send out sample kits

[1543] Person A, wanting to learn about their health risks, accesses the system's website using their device. Person A fills in the required information on the sample kit application form and clicks the submit button. The server receives the application information, and a few days later, the sample kit arrives at Person A's address.

[1544] Sample reception and analysis

[1545] Person A collects a saliva sample according to the instructions in the kit and sends it to the lab. The lab receives the sample and performs DNA analysis. The analysis results are sent to the server and added to Person A's profile.

[1546] Analysis of disease risk and provision of results

[1547] The server calculates disease risk based on person A's DNA data and saves this information to person A's profile. When person A logs in from their device and views the results report, the server displays the analysis results and preventive measures.

[1548] Analysis of ancestral roots and provision of results

[1549] The server analyzes A's DNA data to identify their ancestral roots. In addition, it compares the data of other users with similar roots to extract common regional information. When A requests information about their ancestral roots, the server displays that information on their device.

[1550] In this way, the system can provide users with comprehensive information about their health risks and ancestral roots, and offer advice on preventative measures and lifestyle improvements.

[1551] The following describes the processing flow.

[1552] Step 1:

[1553] The user accesses the server's website through their device and opens the sample kit application page.

[1554] Step 2:

[1555] The user enters the required information, such as their name, address, and contact details, into the application form and clicks the "Submit" button.

[1556] Step 3:

[1557] The server receives the application data and saves it to the database. The process then automatically proceeds to arrange for the shipment of the sample kit.

[1558] Step 4:

[1559] The server sends a confirmation email to the user notifying them that the sample kit has been shipped.

[1560] Step 5:

[1561] The user receives a sample kit and collects a saliva or blood sample according to the instructions in the kit.

[1562] Step 6:

[1563] The user uses the enclosed return envelope to send the collected sample to the designated laboratory.

[1564] Step 7:

[1565] The lab verifies the contents of the received samples, scans the barcodes, and registers them in the database.

[1566] Step 8:

[1567] The lab begins DNA analysis by extracting DNA from a saliva or blood sample.

[1568] Step 9:

[1569] The extracted DNA is analyzed using a sequencing device to obtain the user's genetic information. Analysis data is then generated.

[1570] Step 10:

[1571] The lab sends the analysis data to the server, which is then linked to the user's profile.

[1572] Step 11:

[1573] The server analyzes the received DNA data and calculates the user's risk of various diseases.

[1574] Step 12:

[1575] The server saves the calculation results to the user profile and notifies the user that the results are ready.

[1576] Step 13:

[1577] The user logs into the server using their device and requests to view the results report.

[1578] Step 14:

[1579] The server generates a report containing analysis results and preventative measures in response to the user's request and displays it on the terminal.

[1580] Step 15:

[1581] The server will, if necessary, predict diseases with a high incidence rate in the future and suggest additional preventive measures.

[1582] Step 16:

[1583] The server identifies the user's ancestral roots based on their DNA data and adds relevant information to the database.

[1584] Step 17:

[1585] The server matches this data with other users' ancestry to identify people with similar roots and extracts regional information.

[1586] Step 18:

[1587] Users request information about their ancestors and roots through their devices, and the server compiles and provides the information to the users.

[1588] Step 19:

[1589] Users can view information about their ancestral roots and related regions on their devices, and learn about regions and cultures that interest them.

[1590] Through this series of steps, the system can provide comprehensive information on the user's health risks and ancestral roots, and suggest individualized preventative measures.

[1591] (Example 1)

[1592] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1593] Currently, while systems exist on the market for analyzing individual disease risks and ancestral roots, they often lack sufficient preventative measures or lifestyle improvement suggestions for users, and the management of sample kits is uncertain. Furthermore, data protection and encryption measures may be inadequate. A major challenge is the lack of efficient and secure means to deliver analysis results and related information.

[1594] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1595] In this invention, the server includes means for receiving and analyzing saliva or blood samples, means for calculating disease risk using the analyzed DNA data, means for storing the calculation results in the user's profile, means for providing analysis results and preventive measures upon request from the user, means for identifying the user's ancestral roots based on the user's DNA data, means for identifying other users with similar roots and providing regional information, means for generating preventive measures and lifestyle improvement suggestions using a generative AI model, means for arranging the delivery of sample kits, means for tracking the delivery status of samples, and means for data protection and encryption. As a result, users can not only obtain comprehensive disease risk information and ancestral roots information, but also receive suggestions for effective preventive measures, and furthermore, reliability in sample management and data protection is improved.

[1596] A "saliva sample" is a liquid biological sample collected from the user's oral cavity.

[1597] A "blood sample" is a biological sample that uses blood collected from the user's body.

[1598] "Analysis" is the process of examining DNA information extracted from a biological sample and clarifying its contents.

[1599] "DNA data" refers to digital data containing deoxyribonucleic acid information obtained from saliva or blood samples.

[1600] "Disease risk" is a quantitative assessment of the likelihood of a specific disease occurring.

[1601] A "user profile" is a digital database that aggregates information about an individual user.

[1602] "Preventive measures" are specific action guidelines aimed at reducing the risk of a particular disease.

[1603] "Ancestral roots" refers to geographical and genetic information about the user's distant ancestors.

[1604] A "generative AI model" is an algorithm that uses artificial intelligence to generate useful information and suggestions from data.

[1605] A "sample kit" is a set that includes equipment and containers for collecting biological samples.

[1606] "Shipping arrangements" refers to the series of procedures for delivering sample kits to users.

[1607] "Tracking delivery status" is the process of checking the status of a sample kit to the user or lab.

[1608] "Data protection" refers to measures taken to protect users' personal information and analytical data from unauthorized access.

[1609] "Encryption" is a technique that transforms data into a format that cannot be deciphered in order to protect it.

[1610] System Overview

[1611] This system analyzes saliva or blood samples provided by users to identify disease risks and ancestral roots. The system consists of users, terminals, and a server. Users access the server via their terminals to request sample kits, check results, and obtain preventative measures. The server is responsible for receiving samples, analyzing them, storing data, and providing results.

[1612] Explain the program's processing in natural language.

[1613] Request and send out sample kits

[1614] 1. The user accesses the application form on the website using their device and enters the required information. This utilizes a web form using HTML and JavaScript.

[1615] 2. The server receives the information sent by the user and stores it in a database (e.g., MySQL).

[1616] 3. The server will arrange for the sample kit to be sent, using the APIs of external shipping companies (e.g., DHL or FedEx) to request shipment.

[1617] 4. The user receives the sample kit at home a few days later.

[1618] Sample reception and analysis

[1619] 1. The user collects a saliva or blood sample following the instructions on the sample kit.

[1620] 2. The user sends the collected samples to the lab.

[1621] 3. The lab receives the sample and performs DNA analysis (e.g., using PCR equipment or next-generation sequencers). The analysis results are converted into digital data.

[1622] 4. The lab sends the analysis results to the server using the SSL / TLS encryption protocol.

[1623] 5. The server links the received analysis results to the user profile and saves them in the database.

[1624] Analysis of disease risk and provision of results

[1625] 1. The server calculates disease risk based on the analysis results. Specifically, it executes data analysis scripts using Python's pandas or scikit-learn.

[1626] 2. The server saves the calculation results to the user profile.

[1627] 3. The user logs into the website via their device and checks the results on their My Page.

[1628] 4. The server uses an generated AI model (e.g., OpenAI's GPT-3) to display preventative measures and lifestyle improvement suggestions based on the analysis results.

[1629] Examples of prompt statements:

[1630] "According to Ms. A's DNA data, she is at risk of heart disease. Please advise her to take preventative measures such as proper diet, exercise, and regular medical checkups."

[1631] Analysis of ancestral roots and provision of results

[1632] 1. The server analyzes the user's ancestral roots using their DNA data. It uses a genome database and matching algorithms.

[1633] 2. The server matches the data with other users' data to identify common ancestors and regional information.

[1634] 3. The user requests information about their ancestral roots using their device.

[1635] 4. The server receives the request and displays the analysis results on the user's device. This includes geographical root maps and shared genetic characteristics.

[1636] As described above, this system provides comprehensive information about users' health risks and ancestral roots, offers advice on preventative measures and lifestyle improvements, and implements reliable data management and encryption.

[1637] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1638] Step 1:

[1639] The user accesses the application form on the website using their device, enters the required personal information (name, address, contact information, etc.), and presses the "Submit" button. The entered data is then sent from the device to the server.

[1640] Input: Personal information entered by the user.

[1641] Output: Transmitted personal data.

[1642] Step 2:

[1643] The server receives the information sent by the user and saves it to a database (e.g., MySQL). After saving is complete, the server proceeds with arranging the shipment of the sample kit.

[1644] Input: Personal information data submitted.

[1645] Output: Personal information stored in the database.

[1646] Step 3:

[1647] The server uses the shipping company's API (e.g., DHL or FedEx) to request the shipment of sample kits. It receives information such as shipping costs and estimated delivery dates from the shipping company and arranges for the delivery of the sample kits.

[1648] Input: Personal information stored in the database.

[1649] Output: Shipping arrangement information from the delivery company.

[1650] Step 4:

[1651] The user receives a sample kit at home a few days later. The sample kit includes instructions and a container for collecting a saliva or blood sample.

[1652] Input: Sample kit.

[1653] Output: User receives sample kit.

[1654] Step 5:

[1655] The user collects a saliva or blood sample according to the instructions on the sample kit. For saliva, the specified amount is placed in a dedicated container, and for blood, it is collected in a specific tube.

[1656] Input: Sample kit.

[1657] Output: Collected saliva or blood sample.

[1658] Step 6:

[1659] The user places the collected sample in the enclosed return envelope and sends it to the lab's address. The lab receives the sample and confirms receipt.

[1660] Input: A collected saliva or blood sample.

[1661] Output: Sample sent to the lab.

[1662] Step 7:

[1663] The lab begins DNA analysis on the received samples. PCR equipment and next-generation sequencers are used to obtain the DNA sequence information of the samples.

[1664] Input: Sample sent to the lab.

[1665] Output: Analyzed DNA data.

[1666] Step 8:

[1667] The lab sends the analyzed DNA data to the server in digital format. SSL / TLS encryption protocol is used for communication.

[1668] Input: Analyzed DNA data.

[1669] Output: DNA data sent to the server.

[1670] Step 9:

[1671] The server links the received DNA data to the user profile and saves it to the database. The user is then notified when the saving process is complete.

[1672] Input: DNA data sent to the server.

[1673] Output: DNA data linked to the user profile.

[1674] Step 10:

[1675] The server calculates disease risk based on the analysis results. It executes data analysis scripts using Python's pandas and scikit-learn and applies a risk assessment model.

[1676] Input: DNA data linked to the user profile.

[1677] Output: Calculated disease risk data.

[1678] Step 11:

[1679] The server saves the calculation results to the user's profile, making them accessible to the user. The saved results are displayed on the user's My Page on the website.

[1680] Input: Calculated disease risk data.

[1681] Output: Risk data stored in the user profile.

[1682] Step 12:

[1683] Users log in to the website via their device and view their results on their personal page. Along with the analysis results, preventative measures and lifestyle improvement suggestions are displayed using a generated AI model.

[1684] Input: User login information.

[1685] Output: A My Page displaying analysis results and preventative measures.

[1686] Step 13:

[1687] The server uses generated AI models (e.g., OpenAI's GPT-3) to create customized preventative measures and lifestyle improvement suggestions based on the analysis results.

[1688] Input: Analysis results.

[1689] Output: Generated precautions.

[1690] Examples of prompt statements:

[1691] "According to Ms. A's DNA data, she is at risk of heart disease. Please advise her to take preventative measures such as proper diet, exercise, and regular medical checkups."

[1692] Step 14:

[1693] The server analyzes the user's ancestral roots using their DNA data. It uses a genome database and matching algorithms to identify geographical and genetic information about their ancestors.

[1694] Input: DNA data linked to the user profile.

[1695] Output: Identified ancestral roots information.

[1696] Step 15:

[1697] The server matches DNA data with other users to identify common ancestors and regional information. Statistical analysis is performed to extract user information with high similarity.

[1698] Input: Identified ancestral root information.

[1699] Output: Similar users and location information.

[1700] Step 16:

[1701] The user uses their device to request information about their ancestral roots. The request is sent to the server.

[1702] Input: User request information.

[1703] Output: The request sent to the server.

[1704] Step 17:

[1705] The server receives the request and displays the analysis results on the user's device. This includes geographical root maps and shared genetic characteristics.

[1706] Input: The request sent to the server.

[1707] Output: Analysis results displayed on the user's terminal.

[1708] (Application Example 1)

[1709] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1710] In modern society, personalized health management tailored to each individual's health condition and genetic risks is in demand. However, current systems make it difficult to provide specific health guidance based on disease risk and genetic background. Furthermore, there is a lack of means to propose and efficiently deliver optimal meal plans for each individual. As a result, many people are unable to manage their health properly and face lifestyle-related diseases and other health risks.

[1711] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1712] This invention includes a server that provides means for receiving and analyzing saliva or blood samples, means for calculating disease risk using the analyzed DNA data, means for storing the calculation results in the user's profile, means for providing analysis results and preventive measures upon user request, means for identifying ancestral roots based on the user's DNA data, means for identifying other users with similar roots and providing regional information, means for proposing a meal plan based on the analyzed DNA data, means for ordering and managing the delivery of meals based on the proposed meal plan, and means for tracking the delivery status in real time. This enables health management based on the individual user's genetic risk and provides appropriate meal plans tailored to that risk. This reduces individual health risks and enables more effective health management.

[1713] A "saliva or blood sample" is a type of biological fluid collected from the user and used for the extraction and analysis of DNA containing genetic information.

[1714] "Means of analysis" refer to devices, systems, and software that perform a series of processes to extract DNA from a sample and to reveal its structure and properties.

[1715] "DNA data" refers to DNA sequence information containing a user's genetic information, and is used to identify disease risks and ancestral roots.

[1716] "Disease risk" is an indicator that shows the likelihood of a user developing a specific disease in the future, based on their specific genetic information.

[1717] A "user profile" is a dataset containing personal information, analysis results, and health risk information about a user.

[1718] "Preventive measures" refer to specific actions and advice for maintaining health and preventing disease, proposed based on the analysis results.

[1719] "Ancestral roots" refers to historical and geographical origin information identified based on the user's genetic information.

[1720] "Other users with similar roots" refers to other users who have been identified as having the same ancestors or geographical background.

[1721] "Regional information" refers to data about the geographical distribution of users who are related by ancestry or genetics.

[1722] A "meal plan" is a plan for optimal nutritional intake suggested based on the user's genetic information and health risks.

[1723] "Means of managing delivery" refers to the system and procedures that oversee the process of cooking and delivering meals selected by the user based on the proposed meal plan.

[1724] "A means of tracking delivery status in real time" refers to a system that monitors the delivery progress of meals ordered by users in real time and provides information on it.

[1725] System Overview

[1726] The system implemented based on this invention involves a user providing a saliva or blood sample, and then analyzing the DNA data obtained from that sample to suggest and deliver personalized healthy meals based on the individual's disease risk and genetic background. This system operates in conjunction with a server, terminals, and delivery service.

[1727] Sample submission and analysis

[1728] The user first accesses the server's website or application using a terminal and requests a saliva or blood sample kit. The server receives the request and ships the sample kit to the user. The user receives the kit, collects a saliva or blood sample, and then sends the sample to a designated laboratory.

[1729] In the lab, samples are received, and specialized analytical equipment analyzes the DNA. The analyzed DNA data is sent to a server using a secure communication method and linked to the user profile.

[1730] Analysis of disease risk and proposals for healthy eating

[1731] The server calculates the user's disease risk based on the received DNA data and stores the results in the user's profile. Furthermore, it suggests appropriate preventive measures based on the analysis results. The server then uses a generative AI model to generate an optimal diet plan based on the user's genetic information and health risks.

[1732] For example, if the server predicts a high risk of diabetes based on the genetic information of "User ID: 12345," it will suggest a diet plan that reduces sugar intake. This result will be displayed on the user's device.

[1733] Food ordering and delivery management

[1734] The user uses a terminal to select a meal from the suggested meal plan and sends the order to the server. The server orders the selected meal from the appropriate delivery service and proceeds with the delivery arrangements. This includes the ability to send specific order information using the delivery service's API and track the progress in real time.

[1735] Track delivery status

[1736] Users can monitor the delivery status of their ordered meals in real time through their device. The server receives delivery information from the delivery service and provides it to the user. This process allows users to track the progress until their meal arrives.

[1737] Example of a prompt

[1738] For example, the prompt for a user to submit a sample is as follows:

[1739] "User data: User ID: 12345, Sample data: Saliva sample"

[1740] Furthermore, the prompt text for a user to request a meal plan is as follows:

[1741] "User data: User ID: 12345"

[1742] In this way, the system provides each user with a scientifically-based health plan and supports health management in a way that can be implemented in daily life.

[1743] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1744] Step 1:

[1745] A user accesses the server's website or application using their device and requests a sample kit. The input consists of the user's personal information and sample kit request information. The server receives this data and outputs instructions for shipping the kit. Specifically, the user enters the required information into a form, and that data is sent to the server.

[1746] Step 2:

[1747] The server ships the sample kit to the user based on the application information. The input is the user's address information received in step 1, and this address information is forwarded to the delivery service, which then outputs instructions to ship the kit. Specifically, the server works in conjunction with the delivery system to send the kit to the user.

[1748] Step 3:

[1749] The user receives a kit, follows the instructions to collect a saliva or blood sample, and sends it to the designated lab. The input is the sample obtained from the user, and the output is the lab receiving that sample. Specifically, the user mails the sample to the lab.

[1750] Step 4:

[1751] The lab receives the sample and begins DNA analysis. The input is a saliva or blood sample sent by the user, and the output is the DNA data resulting from the analysis. Specifically, the lab processes the sample, extracts DNA, and analyzes the gene sequence.

[1752] Step 5:

[1753] The analyzed DNA data is transmitted to the server using a secure communication method. The input is DNA data sent from the lab, and the output is the storage of that DNA data on the server. Specifically, the data is encrypted and transferred through a secure channel.

[1754] Step 6:

[1755] The server calculates the user's disease risk based on DNA data. The input is analyzed DNA data, and the output is a health risk score resulting from the calculation. Specifically, the process involves matching gene sequences with known disease-related markers.

[1756] Step 7:

[1757] The server saves the disease risk assessment results to the user's profile. The input is the health risk score, and the output is that it is added to the user's profile database. Specifically, the process involves writing data through database operations.

[1758] Step 8:

[1759] The server provides appropriate preventative measures to the user based on the analysis results. The input is a health risk score, and the output is related preventative measures. Specifically, it uses a health advice generation AI model to create preventative measures and notifies the user.

[1760] Step 9:

[1761] The server generates an optimal meal plan for the user based on DNA data. The input is analyzed DNA data, and the output is a personalized meal plan. Specifically, it uses a generative AI model that generates a nutrition plan that takes genetic information and health risks into consideration.

[1762] Step 10:

[1763] The user selects a meal from a suggested meal plan using their device and sends the order to the server. The input is the meal plan selected by the user, and the output is the order information. Specifically, the user selects a menu item from the application, and the order information is transferred to the server.

[1764] Step 11:

[1765] The server instructs the delivery service with order information and manages the delivery. The input is the user's order information, and the output is a delivery instruction to the delivery service. Specifically, it uses an API to connect with the delivery system and send delivery instructions.

[1766] Step 12:

[1767] Users can monitor the delivery status of their ordered meals in real time via their device. Input is delivery progress information from the delivery service, and output is the delivery status provided to the user. Specifically, the system receives status information from the delivery service and notifies the user.

[1768] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1769] This system analyzes saliva or blood samples provided by the user to identify disease risks and ancestral roots. Furthermore, by combining this with an emotion engine that recognizes the user's emotions, it tailors the presentation of the analysis results to provide appropriate advice and preventative measures. The following describes the system's program processing in natural language, along with specific examples.

[1770] System Overview

[1771] This system consists of a user, a terminal, a server, a lab, and an emotion engine. Users access the server via their terminal to request sample kits, check results, and obtain preventative measures. The server is responsible for receiving and analyzing samples, storing data, providing results, and recognizing the user's emotions using the emotion engine.

[1772] Program processing

[1773] Request and send out sample kits

[1774] 1. The user accesses the server's website using their device and applies for a sample kit.

[1775] 2. The server receives the application information and arranges for the sample kit to be sent to the user.

[1776] 3. The user receives a sample kit and collects a saliva or blood sample.

[1777] 4. The user sends the collected samples to the designated laboratory.

[1778] Sample reception and analysis

[1779] 5. The lab receives the sample and begins DNA analysis.

[1780] 6. The analyzed DNA data is sent to the server and linked to the user profile.

[1781] Analysis of disease risk and provision of results

[1782] 7. The server analyzes the received DNA data and calculates the user's disease risk.

[1783] 8. The server saves the disease risk to the user profile and notifies the user when the results are ready.

[1784] 9. The emotion engine recognizes the user's emotions based on data obtained from the user's device (e.g., feedback, behavioral history, facial expressions, etc.).

[1785] 10. When the server provides analysis results, it adjusts the presentation method of the results based on the user's emotional state recognized by the emotion engine.

[1786] 11. Based on the analysis results, the server provides appropriate preventative measures and suggestions for lifestyle improvements. Additionally, the emotion engine monitors the user's emotional state and provides timely information as needed.

[1787] Analysis of ancestral roots and provision of results

[1788] 12. The server analyzes the user's DNA data to identify their ancestral roots.

[1789] 13. The server matches the data with other users to identify users with similar backgrounds and regional information.

[1790] 14. The user requests information about their ancestral roots through their device, and the server provides that information.

[1791] Specific example

[1792] Request and send out sample kits

[1793] Person B, wanting to learn about their health risks, uses their device to access the system's website. Person B fills in the required information on the sample kit application form and clicks the submit button. The server receives the application information, and a few days later, the sample kit arrives at Person B's address.

[1794] Sample reception and analysis

[1795] Person B collects a saliva sample according to the instructions in the kit and sends it to the lab. The lab receives the sample and performs DNA analysis. The analysis results are sent to the server and added to Person B's profile.

[1796] Analysis of disease risk and provision of results

[1797] The server calculates disease risk based on B's DNA data and stores this information in B's profile. When B logs in from their device and views the results report, the server displays the analysis results and preventative measures. During this process, an emotion engine recognizes B's emotional state and presents the analysis results at the appropriate time and in the appropriate manner. For example, if B is feeling anxious, the server provides preventative measures along with calm and detailed explanations, taking steps to reassure them.

[1798] Analysis of ancestral roots and provision of results

[1799] The server analyzes B's DNA data to identify their ancestral roots. In addition, it compares the data of other users with similar roots to extract common regional information. When B requests information about their ancestral roots, the server displays that information on their device.

[1800] Through this series of steps, the system can comprehensively provide information on the user's health risks and ancestral roots, and appropriately suggest individualized preventative measures while taking the user's emotional state into consideration.

[1801] The following describes the processing flow.

[1802] Step 1:

[1803] The user accesses the server's website through their device and opens the sample kit application page.

[1804] Step 2:

[1805] The user enters the required information, such as their name, address, and contact details, into the application form and clicks the "Submit" button.

[1806] Step 3:

[1807] The server receives the application data and saves it to the database. The process then automatically proceeds to arrange for the shipment of the sample kit.

[1808] Step 4:

[1809] The server sends a confirmation email to the user notifying them that the sample kit has been shipped.

[1810] Step 5:

[1811] The user receives a sample kit and collects a saliva or blood sample according to the instructions in the kit.

[1812] Step 6:

[1813] The user uses the enclosed return envelope to send the collected sample to the designated laboratory.

[1814] Step 7:

[1815] The lab verifies the contents of the received samples, scans the barcodes, and registers them in the database.

[1816] Step 8:

[1817] The lab begins DNA analysis by extracting DNA from a saliva or blood sample.

[1818] Step 9:

[1819] The extracted DNA is analyzed using a sequencing device to obtain the user's genetic information. Analysis data is then generated.

[1820] Step 10:

[1821] The lab sends the analysis data to the server, which is then linked to the user's profile.

[1822] Step 11:

[1823] The server analyzes the received DNA data and calculates the user's risk of various diseases.

[1824] Step 12:

[1825] The server saves the calculation results to the user profile and notifies the user that the results are ready.

[1826] Step 13:

[1827] The emotion engine recognizes the user's emotions based on data obtained from the user's device (e.g., feedback, behavioral history, facial expressions, etc.).

[1828] Step 14:

[1829] The user logs into the server using their device and requests to view the results report.

[1830] Step 15:

[1831] The server generates a report containing analysis results and preventative measures in response to the user's request.

[1832] Step 16:

[1833] The server adjusts how it presents analysis results based on the user's emotional state recognized by the emotion engine. For example, if the user is feeling anxious, it provides a calm and detailed explanation.

[1834] Step 17:

[1835] Based on the analysis results, the server provides appropriate preventative measures and lifestyle improvement suggestions. Additionally, an emotion engine monitors the user's emotional state and provides timely information as needed.

[1836] Step 18:

[1837] The server identifies the user's ancestral roots based on their DNA data and adds relevant information to the database.

[1838] Step 19:

[1839] The server matches this data with other users' ancestry to identify people with similar roots and extracts regional information.

[1840] Step 20:

[1841] Users request information about their ancestors and roots through their devices, and the server compiles and provides the information to the users.

[1842] Step 21:

[1843] Users can view information about their ancestral roots and related regions on their devices, and learn about regions and cultures that interest them.

[1844] Through this series of steps, the system can comprehensively provide users with information on their health risks and ancestral roots, and appropriately suggest individual preventative measures. Furthermore, the emotion engine can understand the user's emotional state, enabling the provision of optimal information.

[1845] (Example 2)

[1846] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1847] Traditional DNA analysis systems were limited to calculating disease risk and identifying ancestral roots, and did not provide information that took into account the user's emotions. As a result, users who received analysis results were more likely to experience anxiety and stress. Furthermore, detailed preventative measures and lifestyle improvement suggestions were rarely provided in a timely manner.

[1848] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving and analyzing a saliva or blood sample, means for calculating disease risk using the analyzed data, means for storing the calculation results in the user's profile, means for providing analysis results and preventive measures in response to a user request, means for recognizing the user's emotions and adjusting the method of providing analysis results, means for identifying ancestral roots based on the user's data, and means for identifying other users with similar roots and providing regional information. This makes it possible to provide analysis results that give users a greater sense of security and to propose preventive measures and lifestyle improvement plans at the appropriate time.

[1849] A "saliva or blood sample" is a biological sample provided by the user that includes saliva or blood.

[1850] "Analysis" refers to the process of processing data obtained from a sample and extracting meaningful information. Specifically, this includes DNA sequencing and gene analysis.

[1851] "Disease risk calculation" is the process of numerically predicting the risk of developing a specific disease based on analyzed DNA data.

[1852] A "user profile" is an information database that centrally manages all user-related data within the system.

[1853] "Preventive measures" are specific actions or policies provided based on analysis results to reduce the risk of a particular disease.

[1854] "Emotion recognition" is the process of analyzing and identifying a user's emotional state at a given time based on their behavior, facial expressions, and feedback data.

[1855] "Adjusting the method of providing analysis results" refers to a technique that changes the display format and notification method of analysis results according to the user's emotional state.

[1856] "Identifying ancestral roots" is the process of analyzing DNA data to reveal the user's genetic origins and the place of origin of their ancestors.

[1857] "Regional information" refers to information about a specific region obtained by cross-referencing it with data from other users who have a similar genetic origin to the user.

[1858] A "system" is a complex collection of hardware and software that integrates all of the above means and functions to provide consistent services to the user.

[1859] This invention is a system that not only analyzes a user's health risks and ancestral roots, but also provides information tailored to the user's emotions. This system consists of a user, a terminal, a server, a lab, and an emotion recognition engine.

[1860] The user accesses the system via a terminal and requests a sample kit. The server receives the request information and arranges for the sample kit. The user then collects the sample and sends it to the lab. The lab analyzes the received sample and sends the analysis results to the server. Based on the analysis data, the server calculates disease risk and ancestral roots and notifies the user of the results. The following hardware and software are used to ensure this entire process runs smoothly.

[1861] Specifically, we employ the following steps and technologies.

[1862] Hardware and software to be used

[1863] 1. DNA sequencer (e.g., Illumina, Thermo Fisher)

[1864] The lab uses it to analyze samples.

[1865] 2. Genetic analysis tools (e.g., Plink, BEAGLE)

[1866] The server uses DNA data to analyze and calculate disease risk.

[1867] 3. Emotion recognition engine (e.g., Amazon Rekognition, Microsoft Azure's Emotion API)

[1868] The server uses this to recognize the user's emotions and adjust how the analysis results are presented.

[1869] Explanation of program processing in natural language

[1870] Request a sample kit

[1871] The user accesses the system's website using their device and reaches the sample kit application page. The entered application information is sent to the server, which uses the shipping carrier's API to arrange for the kit to be shipped.

[1872] Sample collection and mailing

[1873] A few days later, the user receives a sample kit. The user collects a saliva or blood sample according to the instructions and sends it to the lab using the provided return envelope. The lab receives the sample and analyzes it using a DNA sequencer.

[1874] Calculation and analysis of disease risk

[1875] The analysis data is encrypted and sent to the server. The server uses genetic analysis tools such as Plink and BEAGLE to calculate disease risk. The calculation results are saved in the user's profile, and the user is notified when the results are ready.

[1876] Adjusting emotion recognition and result delivery

[1877] When a user reviews their results, the emotion recognition engine analyzes their emotional state. If anxiety or stress is detected, the server adjusts the content and timing of its display and provides detailed explanations. It also simultaneously offers suggestions for preventative measures and lifestyle improvements.

[1878] Identifying ancestral roots and providing regional information

[1879] The server uses genealogical analysis software such as Genealogist to identify the user's ancestral roots. It then matches this information with user data of similar origins and provides regional information.

[1880] Specific example

[1881] Person B, wanting to learn about their health risks, uses their device to access the system's website. They fill in the required information on the application form and click the submit button. The server receives the application information, and a sample kit arrives at Person B's address a few days later.

[1882] Person B collects a saliva sample according to the instructions in the kit and sends it to the lab. The lab receives the sample and performs DNA analysis. The analysis results are sent to the server and added to Person B's profile.

[1883] The server calculates disease risk based on B's DNA data and saves this information in a profile. When B logs in from their device and views the results report, the server displays the analysis results and preventative measures. An emotion engine recognizes B's emotional state and presents the analysis results at the appropriate time and in the appropriate manner.

[1884] For example, if person B is feeling anxious, the system will provide calm and detailed explanations along with preventative measures to help them feel at ease. The server will analyze person B's DNA data to identify their ancestral roots. In addition, it will cross-reference data with other users who have similar roots to extract common regional information. When person B requests information about their ancestral roots, the server will display that information on their device.

[1885] Example of a prompt

[1886] "How can I calculate disease risk based on DNA data and save it to a user profile?"

[1887] "How can I use an emotion engine to recognize a user's emotions and change how the analysis results are presented?"

[1888] "Please tell me how to design a system that identifies ancestral roots and provides that information to users."

[1889] Through the process described above, the present invention is a system that comprehensively provides information on the user's health risks and ancestral roots, and provides optimal information while taking into account their emotional state.

[1890] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1891] Step 1:

[1892] The user accesses the system's website using their device and reaches the sample kit application page. The user enters the required information, such as their name, address, and contact information, into the form and clicks the application button. This sends the entered application data to the server.

[1893] Input: Application information such as name, address, and contact information.

[1894] Output: Application data stored on the server.

[1895] Step 2:

[1896] The server receives the application information and begins the process of sending the sample kit. The server uses the shipping company's API to arrange for the sample kit to be shipped to the specified address. Once the shipping arrangements are complete, the server sends a confirmation email to the user.

[1897] Input: User application information.

[1898] Output: Arrangement for delivery with the shipping company and confirmation email to the user.

[1899] Step 3:

[1900] A few days later, the user receives a sample kit. The user collects a saliva or blood sample according to the instructions in the kit.

[1901] Input: Sample kit.

[1902] Output: Collected saliva or blood sample.

[1903] Step 4:

[1904] The user places the collected sample in the return envelope included in the sample kit and sends it to the designated lab.

[1905] Input: A collected saliva or blood sample.

[1906] Output: Sample placed in a return envelope.

[1907] Step 5:

[1908] The lab receives the sample sent by the user and sends an acknowledgment of receipt to the system. The lab then analyzes the sample using a DNA sequencer (e.g., a general-purpose DNA sequencer).

[1909] Input: Collected sample.

[1910] Output: Analyzed DNA data.

[1911] Step 6:

[1912] The server receives the analyzed DNA data sent from the lab and stores it, linking it to the corresponding user profile. Data integrity checks are also performed during this process.

[1913] Input: Analyzed DNA data.

[1914] Output: DNA data linked to the user profile.

[1915] Step 7:

[1916] The server uses genetic analysis tools such as Plink and BEAGLE to calculate the user's disease risk based on the received DNA data. The calculated risk information is stored in the user profile.

[1917] Input: Stored DNA data.

[1918] Output: Calculated disease risk information.

[1919] Step 8:

[1920] The server notifies the user when the calculated disease risk results are ready. This notification may be sent via email or in-app message.

[1921] Input: Calculated disease risk information.

[1922] Output: Notification to the user.

[1923] Step 9:

[1924] The emotion recognition engine uses data acquired from the user's device (such as feedback, behavioral history, and facial expressions) to analyze the user's emotions. For example, anxiety may be recognized based on feedback data.

[1925] Input: Feedback, behavioral history, and facial expression data.

[1926] Output: Analyzed emotional state.

[1927] Step 10:

[1928] The server adjusts how the analysis results are presented based on the results from the emotion recognition engine. For example, if the user is anxious, it provides a calm explanation, while if they are relaxed, it adds a detailed technical explanation.

[1929] Input: Analyzed emotional state and disease risk information.

[1930] Output: Adjusted result display.

[1931] Step 11:

[1932] Based on the analysis results, the server generates and provides to the user appropriate preventative measures and lifestyle improvement suggestions. The emotion recognition engine continues to monitor the user's emotions and provides information in a timely manner.

[1933] Input: Disease risk information and analyzed emotional state.

[1934] Output: Proposed preventative measures and lifestyle improvements.

[1935] Step 12:

[1936] The server uses genealogical analysis software such as Genealogist to analyze the user's DNA data and identify their ancestral roots.

[1937] Input: User's DNA data.

[1938] Output: Identified ancestral roots information.

[1939] Step 13:

[1940] The server matches DNA data with that of other users to identify users with similar roots and their geographical information.

[1941] Input: Identified ancestral roots information.

[1942] Output: Matched regional information.

[1943] Step 14:

[1944] When a user requests information about their ancestral roots through their device, the server provides that information in real time.

[1945] Input: User request.

[1946] Output: Provided ancestral roots information and regional information.

[1947] (Application Example 2)

[1948] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1949] Traditional health risk and ancestral roots analysis systems often fail to provide users with appropriate feedback tailored to their emotional state, leading to anxiety and doubt about the results. Furthermore, when viewing analysis results in real-time at physical stores, the lack of information based on the user's emotional state can result in decreased user satisfaction.

[1950] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1951] In this invention, the server includes means for receiving and analyzing a saliva or blood sample, means for calculating disease risk using the analyzed DNA data, means for storing the calculation results in the user's profile, means for providing analysis results and preventive measures upon request from the user, means for identifying the user's ancestral roots based on the user's DNA data, means for identifying other users with similar roots and providing regional information, means for recognizing the user's emotions, means for adjusting the method of presenting analysis results based on the recognized emotional state, and means for recognizing the user's emotional state in real time at the store and providing appropriate advice. This enables appropriate feedback and advice based on the user's emotional state.

[1952] A "saliva or blood sample" is a biological sample provided by the user and is used as material for DNA analysis.

[1953] "Means of analysis" refers to a device or software that extracts DNA from a saliva or blood sample and reads that DNA information.

[1954] A "means for calculating disease risk" refers to an algorithm or program that quantifies the risk of developing a specific disease based on analyzed DNA data.

[1955] "Means of saving to the user's profile" refers to a system that records calculation results in a database and manages them in conjunction with the user's identification information.

[1956] "Means of providing analysis results and preventive measures" refers to a method of displaying or notifying users of calculated disease risks and corresponding preventive measures in response to their requests.

[1957] "Methods for identifying ancestral roots" refers to algorithms that analyze a user's DNA data to identify their genetic background.

[1958] "Means for identifying other users with similar roots and providing regional information" refers to a system that matches users against a database of other users to identify genetically similar users or those sharing common regions.

[1959] "Means of recognizing user emotions" refers to technologies that identify a user's emotional state by analyzing their facial expressions, behavior, and feedback.

[1960] "Means for adjusting the presentation method of analysis results based on recognized emotional states" refers to a system for presenting analysis results in different formats and timings depending on the user's emotions.

[1961] "A means of providing appropriate advice in real time" refers to a method of analyzing the emotional state of users in physical stores in real time and immediately providing corresponding feedback and recommendations.

[1962] The following describes an embodiment for carrying out this invention. This system mainly consists of a server, terminals, users, a lab, and an emotion engine.

[1963] Equipment and hardware configuration

[1964] The server possesses high-performance data analysis and storage capabilities, and manages analysis algorithms and user profile data. The server also incorporates an emotion engine that recognizes user emotions and adjusts feedback accordingly.

[1965] A terminal is a device that users operate, and can take various forms such as smartphones, PCs, and tablets. In addition, smart glasses and head-mounted displays are sometimes adopted for use in physical stores.

[1966] The lab is a specialized facility that receives saliva or blood samples provided by users and performs DNA analysis.

[1967] Software Configuration

[1968] The software used includes TensorFlow for emotion recognition and a specialized API for DNA analysis. Additionally, a dedicated SDK (Software Development Kit) is incorporated to process data from smart glasses and head-mounted displays.

[1969] Data processing and calculations

[1970] The server first analyzes the sample provided by the user in a lab to obtain DNA data. Based on this DNA data, the server analyzes disease risk and ancestral roots. The generated data is stored in the user profile. When the user requests these results, the server provides the analysis results along with appropriate preventive measures.

[1971] Furthermore, the emotion recognition engine recognizes the user's emotions based on real-time data obtained from the device or smart glasses (e.g., facial expressions, behavioral history) and adjusts how the analysis results are presented. For example, if the user is feeling anxious, it provides reassuring feedback.

[1972] Specific example

[1973] For example, consider a scenario where a user visits a physical store and interacts with a store employee wearing smart glasses. When the user requests health risk information, the server presents disease risks based on DNA analysis data. If the emotion engine detects the user's anxiety, the server provides a message such as, "Don't worry. The risks are minimal, and please take the following precautions to manage your health."

[1974] Example of a prompt

[1975] The following prompt statements are used as input to the generative AI model.

[1976] "If a user is feeling anxious when health risks are displayed, what kind of calming feedback should be provided?"

[1977] This format makes it possible to provide feedback that takes into account the user's real-time emotional state, even in physical stores. This improves user satisfaction and deepens their understanding and acceptance of the results.

[1978] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1979] Step 1:

[1980] The user accesses the server's website using their device and applies for a sample kit. The user enters details such as their user information and shipping address, and the server records the application information as output.

[1981] Step 2:

[1982] The server receives the application information and arranges for the sample kit to be sent to the user. It uses the user's application information as input and generates an order for the shipping procedure as output.

[1983] Step 3:

[1984] The user receives a sample kit, collects a saliva or blood sample, and sends the sample to the designated lab according to the instructions. The input requires the kit instructions and the user's actions, and the output is the sample sent to the lab.

[1985] Step 4:

[1986] The lab receives the sample and performs DNA analysis. The analysis results are sent to a server. A saliva or blood sample is used as input, and the analyzed DNA data is sent to the server as output.

[1987] Step 5:

[1988] The server processes DNA data received from the lab and adds disease risk and ancestral roots information to the user's profile. DNA analysis data is used as input, and the updated user profile is saved as output.

[1989] Step 6:

[1990] When a user requests analysis results and preventive measures through their device, the server retrieves the results from stored profile information. The user's request information is used as input, and disease risk and preventive measures are generated as output.

[1991] Step 7:

[1992] The emotion recognition engine acquires real-time user emotion data from the device or smart glasses in a physical store. Facial expressions and behavioral data are used as input, and the user's emotional state is recognized as output.

[1993] Step 8:

[1994] The server adjusts the presentation method of the analysis results based on the emotion recognition results. Emotion recognition data is used as input, and the adjusted presentation method and feedback are generated as output.

[1995] Step 9:

[1996] Using smart glasses in physical stores, store staff interact with users in real time, providing tailored analysis results and preventative measures. Feedback data from a server is used as input, and appropriate advice is provided to the user as output.

[1997] This process enables personalized healthcare and advice that takes into account the user's emotional state.

[1998] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1999] The data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One 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">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2000] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[2001] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2002] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[2003] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[2004] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[2005] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[2006] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[2007] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[2008] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[2009] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[2010] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[2011] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[2012] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[2013] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[2014] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[2015] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[2016] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[2017] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[2018] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[2019] The following is further disclosed regarding the embodiments described above.

[2020] (Claim 1)

[2021] A means for receiving and analyzing a saliva or blood sample,

[2022] A method for calculating disease risk using analyzed DNA data,

[2023] A means of saving the calculation results to the user's profile,

[2024] A means of providing analysis results and preventive measures in response to user requests,

[2025] A method for identifying ancestral roots based on the user's DNA data,

[2026] A system that includes means of identifying other users with similar roots and providing them with local information.

[2027] (Claim 2)

[2028] The system according to claim 1, further comprising means for predicting the risk of developing a specific disease based on analyzed DNA data.

[2029] (Claim 3)

[2030] The system according to claim 1, further comprising means for predicting diseases with a high incidence rate in the future based on the user's DNA analysis data.

[2031] "Example 1"

[2032] (Claim 1)

[2033] A means for receiving and analyzing a saliva or blood sample,

[2034] A method for calculating disease risk using analyzed DNA data,

[2035] A means of saving the calculation results to the user's profile,

[2036] A means of providing analysis results and preventive measures in response to user requests,

[2037] A method for identifying ancestral roots based on the user's DNA data,

[2038] A means of identifying other users with similar roots and providing local information,

[2039] A means of generating preventative measures and lifestyle improvement suggestions using a generative AI model,

[2040] The means of arranging for the delivery of the sample kit,

[2041] A means of tracking the delivery status of samples,

[2042] Means for data protection and encryption,

[2043] A system that includes this.

[2044] (Claim 2)

[2045] The system according to claim 1, further comprising means for predicting the risk of developing a specific disease based on analyzed DNA data.

[2046] (Claim 3)

[2047] The system according to claim 1, further comprising means for predicting diseases with a high incidence rate in the future based on the user's DNA analysis data.

[2048] "Application Example 1"

[2049] (Claim 1)

[2050] A means for receiving and analyzing a saliva or blood sample,

[2051] A method for calculating disease risk using analyzed DNA data,

[2052] A means of saving the calculation results to the user's profile,

[2053] A means of providing analysis results and preventive measures in response to user requests,

[2054] A method for identifying ancestral roots based on the user's DNA data,

[2055] A means of identifying other users with similar roots and providing local information,

[2056] A method for proposing a meal plan based on analyzed DNA data,

[2057] A means of ordering and managing the delivery of meals based on the proposed meal plan,

[2058] A system that includes a means to track the delivery status in real time.

[2059] (Claim 2)

[2060] The system according to claim 1, further comprising means for predicting the risk of developing a specific disease based on analyzed DNA data.

[2061] (Claim 3)

[2062] The system according to claim 1, further comprising means for predicting diseases with a high incidence rate in the future based on the user's DNA analysis data.

[2063] "Example 2 of combining an emotion engine"

[2064] (Claim 1)

[2065] A means for receiving and analyzing a saliva or blood sample,

[2066] A means of calculating disease risk using analyzed data,

[2067] A means of saving the calculation results to the user's profile,

[2068] A means of providing analysis results and preventive measures in response to user requests,

[2069] A means of recognizing user emotions and adjusting the method of providing analysis results,

[2070] A means of identifying ancestral roots based on user data,

[2071] A system that includes means of identifying other users with similar roots and providing them with local information.

[2072] (Claim 2)

[2073] The system according to claim 1, further comprising means for predicting the risk of developing a specific disease based on analyzed data.

[2074] (Claim 3)

[2075] The system according to claim 1, further comprising means for predicting diseases with a high incidence rate in the future based on user analysis data.

[2076] "Application example 2 when combining with an emotional engine"

[2077] (Claim 1)

[2078] A means for receiving and analyzing a saliva or blood sample,

[2079] A method for calculating disease risk using analyzed DNA data,

[2080] A means of saving the calculation results to the user's profile,

[2081] A means of providing analysis results and preventive measures in response to user requests,

[2082] A method for identifying ancestral roots based on the user's DNA data,

[2083] A means of identifying other users with similar roots and providing local information,

[2084] Means of recognizing user emotions,

[2085] A means for adjusting the method of presenting analysis results based on the recognized emotional state,

[2086] A system that includes means for recognizing the emotional state of users in real time at a store and providing appropriate advice.

[2087] (Claim 2)

[2088] The system according to claim 1, further comprising means for predicting the risk of developing a specific disease based on analyzed DNA data.

[2089] (Claim 3)

[2090] The system according to claim 1, further comprising means for predicting diseases with a high incidence rate in the future based on the user's DNA analysis data. [Explanation of symbols]

[2091] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for receiving and analyzing a saliva or blood sample, A method for calculating disease risk using analyzed DNA data, A means of saving the calculation results to the user's profile, A means of providing analysis results and preventive measures in response to user requests, A method for identifying ancestral roots based on the user's DNA data, A system that includes means of identifying other users with similar roots and providing them with local information.

2. The system according to claim 1, further comprising means for predicting the risk of developing a specific disease based on analyzed DNA data.

3. The system according to claim 1, further comprising means for predicting diseases with a high incidence rate in the future based on the user's DNA analysis data.

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