System

Abstract

A system is provided.SOLUTION: A system including means for storing health information and symptom data received from a user, means for using an AI algorithm for analyzing the health information and the symptom data, means for generating an individual treatment plan based on an analysis result of the AI algorithm, means for selecting an optimal treatment center based on the individual treatment plan, means for displaying the individual treatment plan and optimal treatment center information on a user terminal, means for managing reservation information of the treatment center, means for receiving and managing treatment progress and feedback information, and means for improving the treatment plan based on the feedback information.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] There are a wide variety of treatment methods for lower back pain, making it difficult for patients to find the most appropriate treatment and treatment facility. Furthermore, the current medical system makes it difficult to provide treatment plans optimized for each patient's symptoms, resulting in poor treatment effectiveness. Furthermore, there are few ways to manage and check the progress and effectiveness of treatment in real time. As a result, patients do not know which treatments are effective, and they risk missing out on opportunities to receive appropriate treatment. [Means for solving the problem]

[0005] This invention solves the above problems by the following means: It provides a means for storing health information and symptom data received from a user. It then provides a means for using an AI algorithm to analyze the health information and symptom data, and includes a means for generating an individualized treatment plan based on the analysis results. It also provides a means for selecting an optimal treatment center based on the individualized treatment plan, and includes a means for displaying the individualized treatment plan and information about the optimal treatment center on a user terminal. This system also provides a means for managing treatment center reservation information and for receiving and managing treatment progress and feedback information. It also provides a means for improving the treatment plan based on the feedback information, enabling users to continuously receive optimal treatment.

[0006] "User information" refers to basic data about the user, including age, gender, medical history, and the like.

[0007] "Symptom data" is detailed information about the health problems the user is currently experiencing, including the location of pain, the severity of pain, and the duration of pain.

[0008] "Health information" is data relating to the user's health condition, including past illnesses, current health condition, past medical history, and the like.

[0009] "Analysis" refers to the process of analyzing input data using AI algorithms to derive specific conclusions or results.

[0010] An "AI algorithm" is a computational method that uses artificial intelligence technology to analyze large amounts of data, recognize patterns, and generate optimal treatment plans.

[0011] A "treatment plan" is a plan that proposes the most appropriate treatment method based on the user's symptoms, and includes specific treatment methods and recommended treatment centers.

[0012] A "treatment center" is a facility that provides medical services, including hospitals, clinics, osteopathic clinics, etc.

[0013] "Feedback information" refers to information relating to the results and satisfaction of treatment provided by users or treatment centers, and is used to evaluate the effectiveness of treatment.

[0014] An "interface" refers to a screen or operating means that allows a user to interact with a system, and includes an application display screen and operation menu. [Brief explanation of the drawings]

[0015] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11]FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0016] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0017] First, the terms used in the following description will be explained.

[0018] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0019] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0020] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0021] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0023] [First embodiment]

[0024] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0025] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0026] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0027] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0028] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0031] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0033] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0034] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0035] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0036] The present invention provides a system for providing information on lower back pain treatment, creating an optimal treatment plan, and managing the progress of treatment. Hereinafter, an embodiment of this system will be described in detail.

[0037] Entering user information

[0038] Subject: User

[0039] Example: A user accesses an application on a smartphone or PC and enters general health information such as age, gender, and medical history, as well as detailed symptom data such as pain location, pain intensity, and duration. This is done through the app's intuitive interface.

[0040] Receiving and analyzing patient information

[0041] Subject: Server

[0042] Example: The server receives health information and symptom data sent by the user and stores it in a database. It then launches an AI algorithm to analyze the received data. The AI ​​analyzes the user's input data to identify the cause of back pain and the best treatment.

[0043] Treatment plan generation

[0044] Subject: Server

[0045] Example: The server generates an individualized treatment plan based on the analysis results. This treatment plan includes specific treatment methods such as physical therapy, acupuncture, and drug therapy. It also recommends the most suitable treatment center from among nearby treatment centers.

[0046] View Treatment Plan

[0047] Subject: Terminal

[0048] Example: The user's device receives the generated treatment plan and recommended clinic information from the server. This information is displayed on the application's user interface so that the user can check it. For example, the user's screen might display the following message: "Physical therapy and acupuncture are recommended. The nearest recommended clinic is Clinic A."

[0049] Selecting and booking a treatment center

[0050] Subject: User

[0051] Example: A user selects one from a list of clinics and makes an appointment online. Once the appointment is completed, the information is sent to the server and stored in a database.

[0052] Monitoring treatment progress

[0053] Subject: Server

[0054] Example: The server receives progress information from the clinic and adds it to the database for each user. Treatment progress information may include, for example, information such as "First physical therapy session completed, next scheduled treatment date."

[0055] Receiving Feedback

[0056] Subject: User

[0057] Example: After treatment, the user provides feedback through the application. For example, they input specific effects such as "pain was reduced after treatment" and send it to the server. The feedback information is used to improve the next treatment plan.

[0058] Data collection and treatment plan refinement

[0059] Subject: Server

[0060] Example: The server aggregates progress information from clinics and feedback from users, and uses an AI algorithm to compile the data. Based on this data, the effectiveness of the treatment plan is evaluated and the model is updated to improve future treatment plans.

[0061] Confirmation of treatment effectiveness

[0062] Subject: User

[0063] Example: Users can access the application's "My Page" to check their own treatment history and upcoming treatment schedules. By understanding progress in real time, the effectiveness of treatment can be visualized.

[0064] Through the above process, the back pain treatment navigation system provides users with the optimal treatment plan and supports them in maximizing the effectiveness of treatment. By linking the user, server, and device, it becomes possible to provide precise treatment tailored to each individual patient.

[0065] The processing flow will be explained below.

[0066] Step 1: Enter your user information

[0067] Subject: User

[0068] Specific behavior:

[0069] The user opens the application on their smartphone or PC.

[0070] Follow the application interface to enter health information such as age, gender, and medical history.

[0071] Enter details of your symptoms (e.g., location of pain, duration of pain, current pain level, etc.).

[0072] Check the information you entered and click the "Submit" button to send the information to the server.

[0073] Step 2: Receiving and storing patient information

[0074] Subject: Server

[0075] Specific behavior:

[0076] Receive health information and symptom data submitted by a user.

[0077] The received data is saved in the database.

[0078] Checks are performed to ensure data completeness and consistency.

[0079] Step 3: Analyze the data

[0080] Subject: Server

[0081] Specific behavior:

[0082] The stored data is analyzed using AI algorithms.

[0083] Recognize patterns in symptoms and identify the source of problems.

[0084] Analysis will be performed based on criteria for selecting the optimal treatment.

[0085] Step 4: Generate a treatment plan

[0086] Subject: Server

[0087] Specific behavior:

[0088] Based on the analysis results, an individual treatment plan is generated.

[0089] The treatment plan will include recommended treatments (e.g., physical therapy, acupuncture, medication).

[0090] The system uses the user's current location information to select a suitable nearby clinic.

[0091] The generated treatment plan and clinic information are stored in a database.

[0092] Step 5: View your treatment plan

[0093] Subject: Terminal

[0094] Specific behavior:

[0095] The user's terminal obtains the treatment plan and clinic information from the server.

[0096] The application interface displays treatment plans and recommended clinics.

[0097] It provides users with detailed information about their treatment plan and a list of recommended treatment centers.

[0098] Step 6: Select a clinic and book an appointment

[0099] Subject: User

[0100] Specific behavior:

[0101] The user selects one of the displayed clinics.

[0102] Check the details and available appointment times for the clinic you selected.

[0103] Select your desired date and time and confirm your reservation.

[0104] The reservation information is sent to the server and stored in a database.

[0105] Step 7: Monitor your treatment progress

[0106] Subject: Server

[0107] Specific behavior:

[0108] Receive treatment progress updates from the clinic.

[0109] The progress status includes the details of the treatment that was actually performed and the next treatment appointment information.

[0110] The received progress information is added to the patient database.

[0111] Continually update and manage your medical history.

[0112] Step 8: Receiving feedback

[0113] Subject: User

[0114] Specific behavior:

[0115] The user accesses the application to enter feedback after treatment.

[0116] Please fill in the feedback form to describe the effectiveness and satisfaction of the treatment.

[0117] The feedback is checked and sent to the server.

[0118] Step 9: Analyze feedback and refine treatment plan

[0119] Subject: Server

[0120] Specific behavior:

[0121] The received feedback information is stored in a database.

[0122] The feedback data is analyzed using an AI algorithm to evaluate the effectiveness of the treatment.

[0123] The treatment plan will be improved based on the analysis results.

[0124] The improved treatment plan is reflected in the next plan generation.

[0125] Step 10: Check the effectiveness of the treatment

[0126] Subject: User

[0127] Specific behavior:

[0128] The user accesses the application's "My Page."

[0129] Review your treatment history, progress, and upcoming treatment schedule.

[0130] Check the effectiveness of treatment in real time and prepare for the next treatment.

[0131] Through this series of processes, the lower back pain treatment navigation system can provide the user with an optimal treatment plan, manage the progress of treatment, and confirm its effectiveness.

[0132] Example 1

[0133] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0134] In the treatment of lower back pain, existing systems have difficulty providing optimal treatment plans based on individual patients' symptoms and progress. Furthermore, management of treatment progress and collection and analysis of feedback are often done manually, preventing efficient improvements to treatment plans. This makes it difficult to quickly and effectively provide treatment methods appropriate for each patient.

[0135] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0136] In this invention, the server includes: [means for storing health information and symptom data received from a user;] [means for using a generative AI model to analyze the health information and symptom data; and] [means for generating an individual treatment plan based on the analysis results of the generative AI model.] This makes it possible [to automatically generate and refine an optimal treatment plan based on the patient's individual symptoms and progress, and provide effective treatment for lower back pain].

[0137] "Health information" refers to data that indicates the patient's overall health condition, such as the patient's age, sex, medical history, etc.

[0138] "Symptom data" refers to data that indicates specific symptoms such as the location of pain felt by the patient, the degree of pain, and the duration of pain.

[0139] A "generative AI model" is an algorithm that uses artificial intelligence to analyze received health information and symptom data and generate an optimal treatment plan.

[0140] A "treatment plan" is a plan that includes specific treatment methods such as physical therapy, acupuncture, and drug therapy that the generative AI model proposes based on the analysis results.

[0141] The "optimal medical facility" is a medical facility such as a clinic or hospital that the generative AI model recommends based on the analysis results.

[0142] A "user terminal" is a device used by a user, such as a smartphone or PC.

[0143] "Reservation information" is information regarding reservations for treatment at a medical facility selected by the user.

[0144] "Treatment progress status" is information indicating the progress status of treatment currently in progress.

[0145] "Feedback information" is data indicating opinions and impressions provided by the user regarding the effectiveness of treatment and the state of improvement.

[0146] "Updating the generative AI model" refers to the operation of retraining the generative AI model to improve the next treatment plan based on the received treatment progress and feedback information.

[0147] This invention is a system for providing information on lower back pain treatment, creating optimal treatment plans, and managing treatment progress. This system allows users to input their own health information and symptom data, which is then analyzed by a server, which then generates an optimal treatment plan and displays it on the user's device. It also maximizes the effectiveness of treatment by allowing users to select and book treatment centers, manage treatment progress, and collect feedback.

[0148] Hardware and software used

[0149] Server: A computing environment equipped with a high-performance processor and large memory capacity

[0150] Database: A relational database such as MySQL or PostgreSQL

[0151] Generative AI models: Machine learning frameworks such as Python and TensorFlow

[0152] User devices: smartphones, PCs

[0153] Application: Web or mobile application

[0154] Specific system operations and procedures

[0155] Users access the application using a smartphone or PC. They enter their health information, such as their age, gender, medical history, location and severity of pain, and duration, into the application's input form. This information is sent to the server by pressing the send button.

[0156] The server receives the health information and symptom data sent by the user and stores it in a database. The stored data is analyzed by an AI algorithm using Python and TensorFlow. The AI ​​algorithm identifies the cause of back pain and the optimal treatment based on the user's input data.

[0157] Based on the analysis results, the server generates an individualized treatment plan, which includes specific treatment methods such as physical therapy, acupuncture, and drug therapy, and also recommends appropriate nearby medical facilities. The generated treatment plan is sent from the server to the user's device and displayed on the application interface.

[0158] The user selects one from the list of clinics displayed and makes a reservation online. The reservation information is sent to the server and stored in a database.

[0159] The server receives progress information from the clinic and adds it to the database for each user. Treatment progress information can be checked in real time on the "My Page" page within the application.

[0160] After treatment, users provide feedback on the effectiveness of the treatment through the application. This feedback is sent to the server, which uses it to refine the next treatment plan. The server then retrains and updates the generative AI model based on the collected treatment progress and feedback information.

[0161] Specific examples

[0162] The user enters the information "I have a sharp pain in the right side of my lower back that has lasted for more than a week" into the input form and presses the submit button. The server stores this information in a database and analyzes it using an AI algorithm. The AI ​​identifies the condition as "lower back pain caused by long hours of desk work," recommends physical therapy and acupuncture, and finds that the nearest clinic B is the most suitable. This information is displayed on the user's device, and the user selects clinic B and makes an online reservation.

[0163] Prompt Sentence Examples

[0164] "Enter information about your back pain symptoms and generate an optimal treatment plan."

[0165] "The received data is analyzed and the optimal back pain treatment plan is proposed to the user."

[0166] Through the above process, the system provides users with the optimal treatment plan and supports them in maximizing the effectiveness of treatment. By linking users, servers, and devices, it becomes possible to provide precise treatment tailored to each individual patient.

[0167] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0168] Step 1:

[0169] Users access the application using a smartphone or PC, enter their health information such as age, gender, medical history, location and severity of pain, and duration into the application's input form, and then press the submit button.

[0170] Input: User health information and symptom data

[0171] Output: Health information and symptom data sent to the server

[0172] Step 2:

[0173] The server receives the health information and symptom data submitted by the user and stores it in a database.

[0174] Input: User-submitted health and symptom data

[0175] Output: Health information and symptom data stored in a database

[0176] Specific operation: The server stores the received data in a "patient database."

[0177] Step 3:

[0178] The server accesses health information and symptom data stored in the database and runs a generative AI model using Python and TensorFlow to analyze it. The generative AI model uses the user's data to identify the cause of their back pain and the optimal treatment.

[0179] Input: Health information and symptom data stored in a database

[0180] Output: Analysis of causes of lower back pain and optimal treatment

[0181] Specific operation: The generative AI model is activated and analysis is performed. For example, it determines that "this patient's back pain is caused by long hours of desk work."

[0182] Step 4:

[0183] Based on the analysis results, the server generates a personalized treatment plan, which includes specific treatment methods such as physical therapy, acupuncture, and medication, and also recommends suitable nearby medical facilities.

[0184] Input: Analysis results

[0185] Output: Individualized treatment plan and recommended medical facility information

[0186] Specific operation: The server creates a treatment plan such as "recommending physical therapy and acupuncture treatment, with the nearest medical facility B being the best."

[0187] Step 5:

[0188] The user's device retrieves the generated treatment plan and recommended medical facility information from the server and displays it on the application interface. The user interface is designed to be easy to read, allowing users to easily check the information.

[0189] Input: Treatment plan and recommended medical facility information sent from the server

[0190] Output: Treatment plan and recommended medical facility information displayed in the application

[0191] Specific operation: The device screen displays the message, "Physical therapy and acupuncture are recommended. The nearest medical facility is Facility B."

[0192] Step 6:

[0193] The user selects one from the list of medical facilities displayed and makes an appointment online. Once the appointment is completed, the information is sent to the server and stored in a database.

[0194] Input: Information about the medical facility and appointment date and time selected by the user

[0195] Output: Reservation information sent to the server and stored in the database

[0196] Specific action: The user "selects medical facility B and confirms the appointment at 2:00 PM on December 1st."

[0197] Step 7:

[0198] The server receives progress information from the medical facility and adds it to the database for each user. Treatment progress information includes specific details such as the next scheduled treatment date.

[0199] Input: Progress information from medical facilities

[0200] Output: Progress information added to the database

[0201] Specific operation: The server records the information "The first physical therapy session has ended, and the next session will be on December 8th" in the database.

[0202] Step 8:

[0203] After treatment, users provide feedback through the application, including specific details about the effectiveness of the treatment and the progress of the treatment. The feedback information is sent to the server and used to improve the next treatment plan.

[0204] Input: User feedback information on the effectiveness of the treatment

[0205] Output: Feedback information sent to the server

[0206] Specific action: The user enters feedback such as "My pain has significantly decreased after treatment" and presses the submit button.

[0207] Step 9:

[0208] The server aggregates progress information from clinics and feedback from users, and uses AI algorithms to refine the next treatment plan. Based on the aggregated results, the generative AI model is updated to optimize the effectiveness of treatment.

[0209] Input: Treatment progress information and feedback information

[0210] Output: Improved generative AI model and next treatment plan

[0211] Specific operation: The server retrains the generative AI model based on the conclusion that "combining physical therapy and acupuncture is effective."

[0212] Step 10:

[0213] Users can access the application's "My Page" to check their own treatment history and upcoming treatment schedules. The treatment history includes detailed progress information, allowing users to intuitively check the effectiveness of their treatment.

[0214] Input: User's treatment history and next treatment schedule information

[0215] Output: Treatment history and treatment schedule information displayed on the personal page within the application

[0216] Specific operation: The user checks the information on his / her personal page that "the first physical therapy session has ended and the next session is scheduled for December 8th."

[0217] (Application example 1)

[0218] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0219] In conventional lower back pain treatment, it has been difficult to quickly present an optimal treatment plan tailored to individual symptoms and the user's specific conditions, and to monitor the progress of the plan in real time. Furthermore, there has been a lack of systems in place to efficiently manage treatment clinic appointments and provide feedback. The present invention aims to solve these problems and maximize the effectiveness of lower back pain treatment.

[0220] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0221] In this invention, the server includes means for storing health information and symptom data received from a user, means for using an AI algorithm to analyze the health information and symptom data, means for generating an individualized treatment plan based on the analysis results of the AI ​​algorithm, means for selecting an optimal treatment clinic based on the individualized treatment plan, means for displaying the individualized treatment plan and information on the optimal treatment clinic on a user terminal, means for managing reservation information for the treatment clinic, means for receiving and managing treatment progress and feedback information, means for improving the treatment plan based on the feedback information, means for providing an interface for making reservations and managing progress for osteopathic clinics using a user terminal, and means for users to input and check data using a smartphone. This enables the provision of an optimal treatment plan for each user, real-time confirmation of treatment progress, efficient reservation management, and effective improvement of the treatment plan based on feedback.

[0222] A "user terminal" is a digital device used by each user to input information and review treatment plans.

[0223] "Health information" refers to data relating to the user's general health, such as age, gender, medical history, etc.

[0224] "Symptom data" is information about specific symptoms experienced by the user, such as the location of pain, the degree of pain, and the duration of pain.

[0225] "AI algorithm" is an artificial intelligence technology that analyzes collected health information and symptom data to generate optimal treatment plans.

[0226] A "personalized treatment plan" is a detailed plan of treatment that is generated based on a user's specific health information and symptom data.

[0227] The "optimal treatment center" is a medical facility that can provide the most appropriate treatment based on the user's treatment plan.

[0228] The "display means" is an interface for visually presenting treatment plans and clinic information on a user terminal.

[0229] The "means for managing reservation information" is a function that manages the reservation status of the treatment center selected by the user and makes changes or cancellations as necessary.

[0230] "Treatment progress status" is information indicating the stage of treatment.

[0231] "Feedback information" refers to opinions and evaluations regarding the effectiveness and satisfaction of a treatment provided by a user after the treatment.

[0232] "Treatment plan refinement" is the process of updating an existing treatment plan to make it more effective based on collected feedback information.

[0233] The "interface" refers to the screens and menus that users operate, and is the part that provides functions such as treatment reservations and progress checks.

[0234] A system for effectively implementing this invention is preferably constructed using a user terminal, a server, and an AI algorithm. Specific embodiments are described below.

[0235] First, the user accesses the application from a smartphone or other device. The user inputs health information such as age, gender, and medical history, as well as symptom data such as the location, severity, and duration of pain. This data is collected via an intuitive user interface and sent to the server.

[0236] The server stores the received health information and symptom data in a database. It then uses AI algorithms to analyze this information and generate an optimal treatment plan for each individual user. This treatment plan may include recommendations for physical therapy, acupuncture, medication, and more. The AI ​​algorithms can be, for example, Python's TensorFlow or SciKit-Learn.

[0237] The server selects the most suitable clinic in the user's area based on the generated treatment plan. The treatment plan is then sent to the user's device along with information about the selected clinic. The user can then review this information and make a reservation at the recommended clinic through the application interface.

[0238] Once treatment begins at the clinic, the user's treatment progress is sent to the server in real time. The user can check their treatment progress from their smartphone. When the user provides feedback after treatment, that information is also sent to the server and stored in the database.

[0239] The server analyzes this feedback information and uses it to improve future treatment plans. By updating the AI ​​algorithm, it is possible to provide increasingly effective treatment plans.

[0240] For example, the following prompt sentence is used as the user's input:

[0241] "30-year-old male with unremarkable health history. Presenting with severe pain in the lower back for two weeks."

[0242] "My back pain has significantly decreased after treatment."

[0243] "The physical therapy at the clinic I booked was effective."

[0244] This allows users to easily and quickly input their health information and select the optimal treatment plan and clinic, and the treatment plan is continuously improved based on feedback, maximizing the effectiveness of treatment.

[0245] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0246] Step 1:

[0247] Users access the application from their smartphones and input their health information and symptom data. The input data includes age, gender, medical history, pain location, pain severity, and duration. This data is collected via an intuitive user interface and sent to the server. The input data is sent from the user's device to the server as initial data.

[0248] Step 2:

[0249] The server stores the health information and symptom data received from the user in a database. During this storage process, the received data is formatted to fit the database format. Specifically, the data is processed so that each item is stored appropriately in the database table. From the health information and symptom data received as input, user information in database format is output.

[0250] Step 3:

[0251] The server passes the stored health information and symptom data to an AI algorithm for analysis. The AI ​​algorithm used is implemented using Python's TensorFlow and SciKit-Learn, and analyzes the user's data to generate an optimal treatment plan. This analysis process uses pattern recognition and predictive models to identify treatment methods based on the input data. The treatment plan generated based on the analyzed data is output.

[0252] Step 4:

[0253] The server selects the most suitable clinic in the user's area based on the generated individual treatment plan. In this selection process, it searches a database of clinics for geographically nearby clinics and determines the most suitable clinic based on each clinic's specialty and evaluation information. The output is a list of the selected optimal clinics.

[0254] Step 5:

[0255] The server sends the individual treatment plan and information on the most suitable treatment center to the user's device. The details of the treatment plan and information on the recommended treatment center are displayed on the user's smartphone. The user can check this information on the screen. The displayed treatment plan and treatment center information are output.

[0256] Step 6:

[0257] After checking the displayed clinic information, the user uses the application interface to make a reservation at the clinic of their choice. The reservation information is sent to the server via the user interface, and the server stores this information in a database and notifies the clinic. The reservation information is entered, and a notification of reservation completion is output.

[0258] Step 7:

[0259] Once treatment begins, treatment progress information is sent from the treatment clinic to the server. This progress information includes the treatment status and the next scheduled treatment date. The server adds and updates this information in real time to the user's database. The entered treatment progress information is output as updated database information.

[0260] Step 8:

[0261] After treatment, users provide feedback through the application. The feedback information includes the user's opinions on the effectiveness of treatment and satisfaction. The feedback information is sent to the server, stored in a database, and used to improve future treatment plans. The input feedback information is output as data for improving treatment plans.

[0262] Step 9:

[0263] The server analyzes the received treatment progress information and user feedback information, and improves future treatment plans based on the AI ​​algorithm model. This ensures effective treatment for each user. An improved treatment plan is output based on the analyzed feedback information.

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

[0265] This invention is a system that provides information on lower back pain treatment, creates an optimal treatment plan, and manages the progress of treatment, and also combines it with an emotion engine that recognizes the user's emotions. Below, we will explain in detail the embodiments of this system.

[0266] Entering user information

[0267] Subject: User

[0268] Example: A user accesses the application from a smartphone or PC and enters general health information such as their age, gender, and medical history. They also enter detailed symptom data such as the location of pain, its severity, and duration. At this time, the emotion engine recognizes emotions from the user's facial expressions and tone of voice and transfers them to the system.

[0269] Receiving and storing patient information

[0270] Subject: Server

[0271] Example: The server receives health and symptom data submitted by the user, as well as the user's emotion information received from the emotion engine, and stores them in a database. It performs checks to ensure the data is complete and consistent.

[0272] Data analysis

[0273] Subject: Server

[0274] Example: The server analyzes the stored data using an AI algorithm. The AI ​​algorithm identifies the cause of the problem based on the user's health information and symptom data. Furthermore, it adds emotional information from the emotion engine to the analysis results and selects the optimal treatment based on the user's stress level and emotional state.

[0275] Treatment plan generation

[0276] Subject: Server

[0277] Example: The server generates an individualized treatment plan based on the analysis results. This treatment plan includes specific treatment methods such as physical therapy, acupuncture, and drug therapy. It can also incorporate a plan to provide psychological support by taking into account the user's emotional information. It can also select the most suitable treatment center from among nearby treatment centers.

[0278] View Treatment Plan

[0279] Subject: Terminal

[0280] Example: The user's device receives the generated treatment plan and recommended clinic information from the server. This information is displayed on the application's user interface for the user to review. For example, the user's screen might display, "Physical therapy and acupuncture are recommended. The nearest recommended clinic is Clinic A. Taking your emotional state into consideration, we've also added a relaxation session."

[0281] Selecting and booking a treatment center

[0282] Subject: User

[0283] Example: A user selects one from a list of clinics and makes an appointment online. Once the appointment is completed, the information is sent to the server and stored in a database.

[0284] Monitoring treatment progress

[0285] Subject: Server

[0286] Example: The server receives progress information from the clinic and adds it to the database for each user. The treatment progress information includes the details of the actual treatment and the next treatment appointment information. The treatment history is continuously updated and managed.

[0287] Receiving Feedback

[0288] Subject: User

[0289] Example: A user accesses an application to enter feedback after treatment. The user writes about the effectiveness of the treatment and their satisfaction in the feedback form. The emotion engine also obtains the user's emotion information at this point, and sends it to the server along with the feedback information.

[0290] Analyze feedback and refine treatment plans

[0291] Subject: Server

[0292] Example: The server stores the feedback and emotional information received from the emotion engine in a database. The feedback data is analyzed using an AI algorithm to evaluate the effectiveness of treatment. The treatment plan is improved based on the analysis results. The improved treatment plan is reflected in the next plan generation.

[0293] Confirmation of treatment effectiveness

[0294] Subject: User

[0295] Example: Users can access the application's "My Page" to check their own treatment history and upcoming treatment schedules. By understanding progress in real time, the effectiveness of treatment can be visualized.

[0296] Through this series of processes, the low back pain treatment navigation system can provide the user with an optimal treatment plan, manage the progress of treatment, and confirm its effectiveness. Furthermore, by combining it with an emotion engine, it becomes possible to provide more comprehensive treatment support that takes into account the user's emotional state.

[0297] The processing flow will be explained below.

[0298] Step 1: Enter your user information

[0299] Subject: User

[0300] Specific behavior:

[0301] The user opens the application on their smartphone or PC.

[0302] Follow the application interface to enter health information such as age, gender, and medical history.

[0303] Enter details of your symptoms (e.g., location of pain, duration of pain, current pain level, etc.).

[0304] The emotion engine analyzes the user's facial expressions and tone of voice in real time and records emotional information.

[0305] Check the input and emotion information, then click the "Submit" button to send the information to the server.

[0306] Step 2: Receiving and storing patient information

[0307] Subject: Server

[0308] Specific behavior:

[0309] Health information and symptom data submitted by the user and emotion information from the emotion engine are received.

[0310] The received data is saved in the database.

[0311] Checks are performed to ensure data completeness and consistency.

[0312] Step 3: Analyze the data

[0313] Subject: Server

[0314] Specific behavior:

[0315] The stored data is analyzed using AI algorithms.

[0316] Use health and symptom data to identify the cause of the problem.

[0317] Emotional information from the emotion engine is added to the analysis results, and a treatment method is selected taking into account the user's stress level and emotional state.

[0318] Step 4: Generate a treatment plan

[0319] Subject: Server

[0320] Specific behavior:

[0321] Based on the analysis results, an individual treatment plan is generated.

[0322] The treatment plan will include recommended treatments (e.g., physical therapy, acupuncture, medication).

[0323] Taking into account the user's emotional information, a plan is incorporated that also includes psychological support.

[0324] Select the most suitable treatment center from nearby treatment centers.

[0325] The generated treatment plan and clinic information are stored in a database.

[0326] Step 5: View your treatment plan

[0327] Subject: Terminal

[0328] Specific behavior:

[0329] The user's terminal obtains the treatment plan and clinic information from the server.

[0330] The application interface displays treatment plans and recommended clinics.

[0331] It provides users with detailed information about their treatment plan and a list of recommended treatment centers.

[0332] Step 6: Select a clinic and book an appointment

[0333] Subject: User

[0334] Specific behavior:

[0335] The user selects one from the displayed list of clinics.

[0336] Check the details and available appointment times for the clinic you selected.

[0337] Select the date and time you want and confirm your reservation.

[0338] The reservation information is sent to the server and stored in a database.

[0339] Step 7: Monitor your treatment progress

[0340] Subject: Server

[0341] Specific behavior:

[0342] Receive progress updates from the clinic.

[0343] The progress status includes the actual treatment performed and the next treatment appointment information.

[0344] The received progress information is added to the patient database.

[0345] Continually update and manage your medical history.

[0346] Step 8: Receiving feedback

[0347] Subject: User

[0348] Specific behavior:

[0349] The user accesses the application to enter feedback after treatment.

[0350] Please fill in the feedback form to describe the effectiveness and satisfaction of the treatment.

[0351] The emotion engine also analyzes the user's facial expressions and voice and records emotional information when sending feedback.

[0352] The feedback content and emotion information are checked and sent to the server.

[0353] Step 9: Analyze feedback and refine treatment plan

[0354] Subject: Server

[0355] Specific behavior:

[0356] The received feedback information and emotion information are stored in a database.

[0357] Feedback data and emotional information are analyzed using AI algorithms to evaluate the effectiveness of treatment.

[0358] The treatment plan will be improved based on the analysis results.

[0359] The improved treatment plan is reflected in the next plan generation.

[0360] Step 10: Check the effectiveness of the treatment

[0361] Subject: User

[0362] Specific behavior:

[0363] The user accesses the application's "My Page."

[0364] Review your treatment history, progress, and upcoming treatment schedule.

[0365] Check the effectiveness of treatment in real time and prepare for the next treatment.

[0366] This processing flow enables the low back pain treatment navigation system to provide users with an optimal treatment plan, manage the progress of treatment, and confirm its effectiveness. Furthermore, by combining it with an emotion engine, comprehensive treatment support that takes into account the user's emotional state can be realized.

[0367] Example 2

[0368] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0369] A current challenge in treating lower back pain is the difficulty of providing an optimal treatment plan by evaluating each patient's symptoms and emotional state in detail. In particular, emotional information is not reflected in the treatment plan, making it difficult to grasp the patient's mental stress and achieving comprehensive treatment results. Furthermore, treatment progress and feedback information are not managed in real time, making efficient treatment follow-up difficult.

[0370] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0371] In this invention, the server includes: [means for storing health information, symptom data, and emotional information received from a user;] [means for using an AI algorithm to analyze the health information, symptom data, and emotional information;] [means for generating an individual treatment plan based on the analysis results of the AI ​​algorithm;] [means for selecting an optimal medical institution based on the individual treatment plan;] [means for displaying the individual treatment plan and information on the optimal medical institution on a user terminal;] [means for managing reservation information for the medical institution;] [means for receiving and managing treatment progress and feedback information; and [means for improving the treatment plan based on the feedback information]. This makes it possible to analyze each patient's health information and emotional state in detail, provide an optimal treatment plan, and manage progress information and feedback in real time.

[0372] "Health information" is data relating to the user's overall health, such as the user's age, gender, medical history, and current health condition.

[0373] "Symptom data" refers to information about specific symptoms reported by the user, such as the location of pain, the degree of pain, and the duration of pain.

[0374] "Emotion information" is data on the emotional state of the user based on facial expressions and tone of voice obtained by the emotion engine.

[0375] An "AI algorithm" is a computational method that uses artificial intelligence technologies such as machine learning and deep learning to analyze data and derive results.

[0376] A "treatment plan" is a proposal for an individual treatment method created based on the analysis results, and includes specific treatment methods such as physical therapy, acupuncture, and drug therapy.

[0377] "Medical institution" refers to a facility such as a hospital, clinic, or doctor's office that provides treatment to users.

[0378] A "user terminal" is a device used by a user, such as a smartphone or a personal computer.

[0379] "Reservation information" is data related to a reservation for treatment at a medical institution selected by the user.

[0380] "Progress information" is information indicating the stage to which treatment has progressed, and includes specific treatment details and information on the next treatment appointment.

[0381] "Feedback information" is information provided by the user after treatment regarding the effectiveness and satisfaction of the treatment.

[0382] MODE FOR CARRYING OUT THE INVENTION

[0383] System Overview

[0384] This invention is a system that provides information on lower back pain treatment, creates optimal treatment plans, and manages treatment progress. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it provides comprehensive treatment support that takes into account the user's emotional state. The system consists of a server, a user terminal, and an emotion engine, and the server, acting as a central processing unit, performs data analysis using an AI algorithm.

[0385] System configuration

[0386] Server: Stores and analyzes data, generates treatment plans, and manages progress information. Specific software includes machine learning models and data analysis tools for implementing AI algorithms.

[0387] User terminal: A device such as a smartphone or PC that is used by users to input information and check treatment plans.

[0388] Emotion engine: Has the function of analyzing the user's facial expressions and tone of voice to obtain emotional information.

[0389] Processing flow

[0390] Entering user information

[0391] Users access the application from their smartphone or PC and enter specific health information such as their age, gender, medical history, location and degree of pain, and duration. The emotion engine analyzes the user's facial expressions and tone of voice to obtain emotional information.

[0392] Sending user information

[0393] The device sends the entered health information, symptom data, and emotional information to a server, securely using the SSL / TLS protocol.

[0394] Receiving and storing patient information

[0395] The server receives the health, symptom, and emotion information sent by the device and stores it in a database, checking the data for completeness and consistency and backing it up for redundancy if necessary.

[0396] Data analysis

[0397] The server analyzes the stored data with AI algorithms, using machine learning models and deep learning to identify the cause of the problem based on the user's health information and symptom data, and evaluates stress levels and emotional state by taking emotional information into account.

[0398] Treatment plan generation

[0399] Based on the analysis results, the server generates a treatment plan tailored to each individual user. This plan includes treatment methods such as physical therapy, acupuncture, and medication. It also provides mental support based on emotional information. It also selects and recommends the most appropriate medical institution.

[0400] View Treatment Plan

[0401] The user device receives the treatment plan and information on recommended medical institutions from the server and displays it on the application's user interface. For example, it may display information such as, "Physical therapy and acupuncture treatment are recommended. The nearest recommended medical institution is Medical Institution A. Taking into account the user's emotional state, a relaxation session has also been added."

[0402] Selecting and booking a treatment center

[0403] The user selects one from the list of clinics displayed and makes a reservation online. The reservation information is sent to the server and stored in a database.

[0404] Monitoring treatment progress

[0405] The server receives treatment progress information sent from the treatment center and adds it to the database for each user. The progress information is updated in real time and next treatment appointment information is also managed.

[0406] Receiving Feedback

[0407] After treatment, the user enters feedback via the application, including information about the effectiveness of the treatment and their satisfaction. The emotion engine also acquires emotion information at this point and sends it to the server.

[0408] Analyze feedback and refine treatment plans

[0409] The server uses an AI algorithm to analyze the feedback and emotional information, evaluate the effectiveness of the treatment, and improve the treatment plan based on the analysis results, which will be reflected in the next treatment.

[0410] Confirmation of treatment effectiveness

[0411] Users can access the application's "My Page" to check their treatment history and next treatment schedule, which allows them to understand the progress of their treatment in real time and visualize the effects of their treatment.

[0412] Examples of prompt statements

[0413] Here is an example prompt:

[0414] You are using the lower back pain treatment navigation system. First, enter your health information, such as your age, gender, medical history, location and severity of your pain, and duration. Next, check the treatment plan and list of recommended clinics provided by the system, select your preferred clinic, and make an appointment. After treatment, you enter your feedback into the system, and the emotion engine evaluates your emotional state. This will further improve the treatment plan.

[0415] Through this series of processes, the system can provide the user with an optimal treatment plan, manage progress, and check effectiveness.In addition, by utilizing the emotion engine, it can also provide comprehensive treatment support that takes emotional states into account.

[0416] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0417] Step 1:

[0418] Input: Health information such as age, gender, medical history, location of pain, degree, duration, and user's emotional information

[0419] How it works: Users access the application from their smartphone or PC and enter health information such as age, gender, medical history, location of pain, degree, duration, etc. At the same time, the emotion engine analyzes the user's facial expressions and tone of voice to obtain emotional information.

[0420] Output: Obtained health information, symptom data and emotional information

[0421] Step 2:

[0422] Input: Acquired health information, symptom data and emotional information

[0423] How it works: The device sends the entered health information, symptom data, and emotional information to the server. Data transmission is secure using the SSL / TLS protocol.

[0424] Output: Health information, symptom data and emotional information sent to the server

[0425] Step 3:

[0426] Input: Health information, symptom data and emotional information sent to the server

[0427] Operation: The server receives the information sent from the device and stores it in the system's database, checking the data for completeness and consistency and backing it up if necessary.

[0428] Output: Health information, symptom data and emotional information stored in a database

[0429] Step 4:

[0430] Input: Health information, symptom data and emotional information stored in a database

[0431] How it works: The server analyzes the stored data with AI algorithms, which use machine learning models and deep learning to identify the cause of health issues based on the user's health information and symptom data, and evaluate stress levels and emotional states based on emotional information.

[0432] Output: Causes of health problems, stress levels, and emotional states as analysis results

[0433] Step 5:

[0434] Input: Causes of health problems as analysis results, stress levels, and emotional states

[0435] How it works: Based on the analysis results, the server generates an individualized treatment plan, which includes physical therapy, acupuncture, medication, and emotional support. It also uses AI algorithms to select and recommend the most appropriate medical institution.

[0436] Output: Generated personalized treatment plan and recommended medical institution information

[0437] Step 6:

[0438] Input: Generated individual treatment plan and recommended medical institution information

[0439] Operation: The user's device displays the treatment plan and recommended medical institution information received from the server on the application's user interface. For example, the following information may be displayed: "Physical therapy and acupuncture treatment are recommended. The nearest recommended medical institution is Medical Institution A. Taking into account the user's emotional state, a relaxation session has also been added."

[0440] Output: Treatment plan and recommended medical institution information displayed on the device

[0441] Step 7:

[0442] Input: Treatment plan and recommended medical institution information displayed on the device

[0443] How it works: The user selects one of the clinics from the list and makes an appointment online. The appointment information is sent from the device to the server and stored in a database.

[0444] Output: Reservation information sent and stored on the server

[0445] Step 8:

[0446] Input: Reservation information sent and stored on the server

[0447] Operation: The server adds treatment progress information received from the clinic to the database for each user. The progress information includes the details of the treatment performed and the next appointment information.

[0448] Output: Progress information added to the database per user

[0449] Step 9:

[0450] Input: Treatment progress information

[0451] How it works: After treatment, the user enters feedback through the application. At the same time, the emotion engine also acquires the user's emotion information and sends it to the server. The feedback includes information about the effectiveness of the treatment and the level of satisfaction.

[0452] Output: Feedback and emotion information sent to the server

[0453] Step 10:

[0454] Input: Feedback and emotion information sent to the server

[0455] How it works: The server analyzes feedback and emotional information using AI algorithms to evaluate the effectiveness of treatment. Based on the analysis results, it improves the existing treatment plan and reflects it in the next treatment.

[0456] Output: Improved treatment plan

[0457] Step 11:

[0458] Input: Improved treatment plans and treatment progress information

[0459] How it works: Users can access the application's "My Page" to check their treatment history and upcoming treatment schedules, allowing them to understand the progress of their treatment in real time and visually confirm the effectiveness of their treatment.

[0460] Output: User's treatment history and next treatment schedule information

[0461] (Application example 2)

[0462] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0463] In modern factories, workers are prone to developing back pain due to long periods of standing and carrying heavy objects, making worker health management important. However, there is a lack of a system that can monitor the health and emotional state of individual workers in real time and provide optimal treatment plans. This can lead to reduced worker productivity and a decrease in safety in the work environment.

[0464] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0465] In this invention, the server includes: [means for storing health information and symptom data received from a user;] [means for using an AI algorithm to analyze the health information and symptom data;] [means for generating an individualized treatment plan based on the analysis results of the AI ​​algorithm;] [means for selecting an optimal treatment clinic based on the individualized treatment plan;] [means for displaying the individualized treatment plan and information on the optimal treatment clinic on a user terminal;] [means for managing reservation information for the treatment clinic;] [means for receiving and managing treatment progress and feedback information;] [means for improving the treatment plan based on the feedback information;] [means for analyzing the user's emotional state using an emotion recognition engine and reflecting it in the treatment plan;] [means installed on a robot terminal used in the work environment and managing worker health information; and [means for checking and responding to worker progress and treatment history in real time.] This makes it possible to monitor workers' health conditions in real time and provide optimal treatment plans, thereby improving worker productivity and safety.

[0466] "Health information received from users" refers to general health data such as age, gender, medical history, etc. provided by individual users.

[0467] "Symptom data" is detailed data such as the location, severity, and duration of pain provided by the user based on their specific health condition.

[0468] "AI Algorithms" are artificial intelligence technologies for analyzing received and stored health information and symptom data.

[0469] An "individualized treatment plan" is a set of treatment processes and methods optimized for each individual user, generated based on the results of analysis by an AI algorithm.

[0470] The "best treatment center" is the medical facility or specialist best suited to treatment, selected based on the individual treatment plan.

[0471] A "user terminal" is an electronic device such as a personal computer or smartphone that displays individual treatment plans and information on the most suitable treatment center.

[0472] "Managing reservation information" means making reservations online with the treatment center of the user's choice, and recording and monitoring the reservation information.

[0473] "Treatment progress status" is data including the details of the treatment that was actually performed and information about the next treatment appointment.

[0474] "Feedback information" is information provided by the user after treatment regarding the effectiveness and satisfaction of the treatment.

[0475] An "emotion recognition engine" is a technology that detects emotions from a user's facial expressions and tone of voice and uses that information for analysis.

[0476] A "robot terminal" is an automated device used in work environments such as factories to manage workers' health information.

[0477] "Real-time monitoring" means being able to instantly access and monitor treatment progress and history.

[0478] This invention provides a system that collects a user's health information and symptom data, analyzes it using an AI algorithm, and proposes and manages an optimal treatment plan. Specific embodiments for implementing this system are described below.

[0479] Entering user information

[0480] Subject: User

[0481] Users access the application from their smartphone or computer and enter their health information and symptom data, such as their age, gender, medical history, location and degree of pain, and duration. At this time, the emotion recognition engine recognizes emotions from the user's facial expressions and tone of voice and transmits them to the system.

[0482] Receiving and storing patient information

[0483] Subject: Server

[0484] The server receives the health information and symptom data submitted by the user, as well as the emotion information received from the emotion recognition engine, and stores them securely in a database.

[0485] Data analysis

[0486] Subject: Server

[0487] The server analyzes the stored data using an AI algorithm. The AI ​​algorithm uses frameworks such as TensorFlow and PyTorch to analyze the user's health condition and symptoms. Furthermore, it adds emotional information received from an emotion recognition engine to the analysis results and selects the optimal treatment based on the user's stress level and emotional state.

[0488] Treatment plan generation

[0489] Subject: Server

[0490] Based on the analysis results, the server generates an individualized treatment plan, which includes specific treatment methods such as physical therapy, acupuncture, and medication. It also considers the user's emotional information and suggests treatment plans that include stress management and psychological support.

[0491] View Treatment Plan

[0492] Subject: User

[0493] The user's device retrieves the generated treatment plan and recommended clinic information from the server and displays them on the application interface. For example, it might say, "Physical therapy and acupuncture are recommended. The nearest recommended clinic is Clinic A. Taking your emotional state into consideration, we've also added a relaxation program."

[0494] Selecting and booking a treatment center

[0495] Subject: User

[0496] The user selects one from the list of clinics displayed and makes a reservation online. The reservation information is sent to the server and stored in a database.

[0497] Monitoring treatment progress

[0498] Subject: Server

[0499] The server receives progress information from the clinic and adds it to the database for each user, continuously updating and managing the progress, including treatment details and next appointment information.

[0500] Receiving Feedback

[0501] Subject: User

[0502] After treatment, users enter feedback into the application, including the effectiveness and satisfaction of the treatment. The emotion recognition engine recognizes the user's emotions from their facial expressions and tone of voice, and sends this along with the feedback data to the server.

[0503] Analyze feedback and refine treatment plans

[0504] Subject: Server

[0505] The server analyzes the received feedback and emotional information to evaluate the effectiveness of the treatment, and improves the treatment plan based on the analysis results, which are then reflected in the next treatment plan.

[0506] Confirmation of treatment effectiveness

[0507] Subject: User

[0508] Users can access the application's "My Page" to check their own treatment history and upcoming treatment schedules, grasp progress in real time, and visualize the effects of treatment.

[0509] Hardware and Software Used

[0510] The system uses smartphones, computers, and robotic devices, and uses MySQL as the database, Microsoft Azure Emotion API as the emotion recognition engine, and frameworks such as TensorFlow and PyTorch for AI data analysis.

[0511] Examples of concrete examples and prompts

[0512] For example, if the system recognizes an emotion such as "tired" from a worker's facial expression, it will input the following prompt sentence into the generative AI model:

[0513] Prompt Sentence Examples

[0514] "Consider how fatigued the worker is and include relaxing stretching techniques in your next treatment plan."

[0515] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0516] Step 1:

[0517] Entering user information

[0518] Subject: User

[0519] Users access the application from their smartphone or computer and enter their health information and symptom data, such as age, gender, medical history, location and degree of pain, and duration. The emotion recognition engine recognizes emotions from the user's facial expressions and tone of voice, and sends that data to the system to complete the input.

[0520] Input: User's health information, symptom data, and emotional data

[0521] Output: The information entered is sent to the system

[0522] Step 2:

[0523] Receiving and storing patient information

[0524] Subject: Server

[0525] The server receives the health and symptom data sent by the user and the emotion information received from the emotion recognition engine, and stores this data in a database using MySQL, which checks the consistency and completeness of the data.

[0526] Input: User's health information, symptom data, emotional data

[0527] Output: Saved data

[0528] Step 3:

[0529] Data analysis

[0530] Subject: Server

[0531] The server analyzes the stored data using AI algorithms. Using TensorFlow and PyTorch, it analyzes health information and symptom data to identify the cause of the problem. It also incorporates emotional information from an emotion recognition engine into the analysis and outputs the optimal treatment plan based on the user's emotional state.

[0532] Input: Health information, symptom data, emotion data

[0533] Output: Analysis results (candidate treatments)

[0534] Step 4:

[0535] Treatment plan generation

[0536] Subject: Server

[0537] The server generates an individualized treatment plan based on the analysis results, which includes specific treatment methods such as physical therapy, acupuncture, and medication, as well as stress management and psychological support, taking into account the user's emotional information.

[0538] Input: Analysis results, emotion information

[0539] Output: Individual treatment plan

[0540] Step 5:

[0541] View Treatment Plan

[0542] Subject: User

[0543] The user's device receives the generated treatment plan and recommended clinic information from the server and displays it on the application interface. The user can then review this information and select the appropriate treatment.

[0544] Input: Treatment plan, recommended clinic information

[0545] Output: Information displayed in the user interface

[0546] Step 6:

[0547] Selecting and booking a treatment center

[0548] Subject: User

[0549] The user selects the most suitable clinic from the displayed list and makes a reservation online. The reservation information is sent to the server and stored in a database.

[0550] Input: List of clinics, user selection

[0551] Output: Saved reservation information

[0552] Step 7:

[0553] Monitoring treatment progress

[0554] Subject: Server

[0555] The server receives progress information from the clinic and adds it to the database for each user, continuously updating and managing the progress status including treatment details and next appointment information.

[0556] Input: Progress information

[0557] Output: Updated user data

[0558] Step 8:

[0559] Receiving Feedback

[0560] Subject: User

[0561] After treatment, the user enters feedback into the application, and the emotion recognition engine extracts emotional information from the user's facial expressions and tone of voice, and all feedback data is sent to the server.

[0562] Input: User feedback, emotional data

[0563] Output: Saved feedback information

[0564] Step 9:

[0565] Analyze feedback and refine treatment plans

[0566] Subject: Server

[0567] The server analyzes the received feedback and emotional information to evaluate the effectiveness of the treatment, and improves the treatment plan based on the analysis results, which are reflected in the next plan generation.

[0568] Input: Feedback information, emotion data

[0569] Output: Improved treatment plan

[0570] Step 10:

[0571] Confirmation of treatment effectiveness

[0572] Subject: User

[0573] Users can access the application's "My Page" to check their own treatment history and upcoming treatment schedules, grasp progress in real time, and visualize the effects of treatment.

[0574] Input: User data

[0575] Output: Real-time display of treatment history and progress

[0576] Examples of concrete examples and prompts

[0577] For example, if the system recognizes an emotion such as "tired" from a worker's facial expression, it will input the following prompt sentence into the generative AI model:

[0578] Prompt Sentence Examples

[0579] "Consider how fatigued the worker is and include relaxing stretching techniques in your next treatment plan."

[0580] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0581] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0582] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0583] [Second embodiment]

[0584] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0585] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0586] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0587] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0588] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0589] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0590] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0591] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0592] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0593] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0594] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0595] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0596] The present invention provides a system for providing information on lower back pain treatment, creating an optimal treatment plan, and managing the progress of treatment. Hereinafter, an embodiment of this system will be described in detail.

[0597] Entering user information

[0598] Subject: User

[0599] Example: A user accesses an application on a smartphone or PC and enters general health information such as age, gender, and medical history, as well as detailed symptom data such as pain location, pain intensity, and duration. This is done through the app's intuitive interface.

[0600] Receiving and analyzing patient information

[0601] Subject: Server

[0602] Example: The server receives health information and symptom data sent by the user and stores it in a database. It then launches an AI algorithm to analyze the received data. The AI ​​analyzes the user's input data to identify the cause of back pain and the best treatment.

[0603] Treatment plan generation

[0604] Subject: Server

[0605] Example: The server generates an individualized treatment plan based on the analysis results. This treatment plan includes specific treatment methods such as physical therapy, acupuncture, and drug therapy. It also recommends the most suitable treatment center from among nearby treatment centers.

[0606] View Treatment Plan

[0607] Subject: Terminal

[0608] Example: The user's device receives the generated treatment plan and recommended clinic information from the server. This information is displayed on the application's user interface so that the user can check it. For example, the user's screen might display the following message: "Physical therapy and acupuncture are recommended. The nearest recommended clinic is Clinic A."

[0609] Selecting and booking a treatment center

[0610] Subject: User

[0611] Example: A user selects one from a list of clinics and makes an appointment online. Once the appointment is completed, the information is sent to the server and stored in a database.

[0612] Monitoring treatment progress

[0613] Subject: Server

[0614] Example: The server receives progress information from the clinic and adds it to the database for each user. Treatment progress information may include, for example, information such as "First physical therapy session completed, next scheduled treatment date."

[0615] Receiving Feedback

[0616] Subject: User

[0617] Example: After treatment, the user provides feedback through the application. For example, they input specific effects such as "pain was reduced after treatment" and send it to the server. The feedback information is used to improve the next treatment plan.

[0618] Data collection and treatment plan refinement

[0619] Subject: Server

[0620] Example: The server aggregates progress information from clinics and feedback from users, and uses an AI algorithm to compile the data. Based on this data, the effectiveness of the treatment plan is evaluated and the model is updated to improve future treatment plans.

[0621] Confirmation of treatment effectiveness

[0622] Subject: User

[0623] Example: Users can access the application's "My Page" to check their own treatment history and upcoming treatment schedules. By understanding progress in real time, the effectiveness of treatment can be visualized.

[0624] Through the above process, the back pain treatment navigation system provides users with the optimal treatment plan and supports them in maximizing the effectiveness of treatment. By linking the user, server, and device, it becomes possible to provide precise treatment tailored to each individual patient.

[0625] The processing flow will be explained below.

[0626] Step 1: Enter your user information

[0627] Subject: User

[0628] Specific behavior:

[0629] The user opens the application on their smartphone or PC.

[0630] Follow the application interface to enter health information such as age, gender, and medical history.

[0631] Enter details of your symptoms (e.g., location of pain, duration of pain, current pain level, etc.).

[0632] Check the information you entered and click the "Submit" button to send the information to the server.

[0633] Step 2: Receiving and storing patient information

[0634] Subject: Server

[0635] Specific behavior:

[0636] Receive health information and symptom data submitted by a user.

[0637] The received data is saved in the database.

[0638] Checks are performed to ensure data completeness and consistency.

[0639] Step 3: Analyze the data

[0640] Subject: Server

[0641] Specific behavior:

[0642] The stored data is analyzed using AI algorithms.

[0643] Recognize patterns in symptoms and identify the source of problems.

[0644] Analysis will be performed based on criteria for selecting the optimal treatment.

[0645] Step 4: Generate a treatment plan

[0646] Subject: Server

[0647] Specific behavior:

[0648] Based on the analysis results, an individual treatment plan is generated.

[0649] The treatment plan will include recommended treatments (e.g., physical therapy, acupuncture, medication).

[0650] The system uses the user's current location information to select a suitable nearby clinic.

[0651] The generated treatment plan and clinic information are stored in a database.

[0652] Step 5: View your treatment plan

[0653] Subject: Terminal

[0654] Specific behavior:

[0655] The user's terminal obtains the treatment plan and clinic information from the server.

[0656] The application interface displays treatment plans and recommended clinics.

[0657] It provides users with detailed information about their treatment plan and a list of recommended treatment centers.

[0658] Step 6: Select a clinic and book an appointment

[0659] Subject: User

[0660] Specific behavior:

[0661] The user selects one of the displayed clinics.

[0662] Check the details and available appointment times for the clinic you selected.

[0663] Select your desired date and time and confirm your reservation.

[0664] The reservation information is sent to the server and stored in a database.

[0665] Step 7: Monitor your treatment progress

[0666] Subject: Server

[0667] Specific behavior:

[0668] Receive treatment progress updates from the clinic.

[0669] The progress status includes the details of the treatment that was actually performed and the next treatment appointment information.

[0670] The received progress information is added to the patient database.

[0671] Continually update and manage your medical history.

[0672] Step 8: Receiving feedback

[0673] Subject: User

[0674] Specific behavior:

[0675] The user accesses the application to enter feedback after treatment.

[0676] Please fill in the feedback form to describe the effectiveness and satisfaction of the treatment.

[0677] The feedback is checked and sent to the server.

[0678] Step 9: Analyze feedback and refine treatment plan

[0679] Subject: Server

[0680] Specific behavior:

[0681] The received feedback information is stored in a database.

[0682] The feedback data is analyzed using an AI algorithm to evaluate the effectiveness of the treatment.

[0683] The treatment plan will be improved based on the analysis results.

[0684] The improved treatment plan is reflected in the next plan generation.

[0685] Step 10: Check the effectiveness of the treatment

[0686] Subject: User

[0687] Specific behavior:

[0688] The user accesses the application's "My Page."

[0689] Review your treatment history, progress, and upcoming treatment schedule.

[0690] Check the effectiveness of treatment in real time and prepare for the next treatment.

[0691] Through this series of processes, the lower back pain treatment navigation system can provide the user with an optimal treatment plan, manage the progress of treatment, and confirm its effectiveness.

[0692] Example 1

[0693] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0694] In the treatment of lower back pain, existing systems have difficulty providing optimal treatment plans based on individual patients' symptoms and progress. Furthermore, management of treatment progress and collection and analysis of feedback are often done manually, preventing efficient improvements to treatment plans. This makes it difficult to quickly and effectively provide treatment methods appropriate for each patient.

[0695] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0696] In this invention, the server includes: [means for storing health information and symptom data received from a user;] [means for using a generative AI model to analyze the health information and symptom data; and] [means for generating an individual treatment plan based on the analysis results of the generative AI model.] This makes it possible [to automatically generate and refine an optimal treatment plan based on the patient's individual symptoms and progress, and provide effective treatment for lower back pain].

[0697] "Health information" refers to data that indicates the patient's overall health condition, such as the patient's age, sex, medical history, etc.

[0698] "Symptom data" refers to data that indicates specific symptoms such as the location of pain felt by the patient, the degree of pain, and the duration of pain.

[0699] A "generative AI model" is an algorithm that uses artificial intelligence to analyze received health information and symptom data and generate an optimal treatment plan.

[0700] A "treatment plan" is a plan that includes specific treatment methods such as physical therapy, acupuncture, and drug therapy that the generative AI model proposes based on the analysis results.

[0701] The "optimal medical facility" is a medical facility such as a clinic or hospital that the generative AI model recommends based on the analysis results.

[0702] A "user terminal" is a device used by a user, such as a smartphone or PC.

[0703] "Reservation information" is information regarding reservations for treatment at a medical facility selected by the user.

[0704] "Treatment progress status" is information indicating the progress status of treatment currently in progress.

[0705] "Feedback information" is data indicating opinions and impressions provided by the user regarding the effectiveness of treatment and the state of improvement.

[0706] "Updating the generative AI model" refers to the operation of retraining the generative AI model to improve the next treatment plan based on the received treatment progress and feedback information.

[0707] This invention is a system for providing information on lower back pain treatment, creating optimal treatment plans, and managing treatment progress. This system allows users to input their own health information and symptom data, which is then analyzed by a server, which then generates an optimal treatment plan and displays it on the user's device. It also maximizes the effectiveness of treatment by allowing users to select and book treatment centers, manage treatment progress, and collect feedback.

[0708] Hardware and software used

[0709] Server: A computing environment equipped with a high-performance processor and large memory capacity

[0710] Database: A relational database such as MySQL or PostgreSQL

[0711] Generative AI models: Machine learning frameworks such as Python and TensorFlow

[0712] User devices: smartphones, PCs

[0713] Application: Web or mobile application

[0714] Specific system operations and procedures

[0715] Users access the application using a smartphone or PC. They enter their health information, such as their age, gender, medical history, location and severity of pain, and duration, into the application's input form. This information is sent to the server by pressing the send button.

[0716] The server receives the health information and symptom data sent by the user and stores it in a database. The stored data is analyzed by an AI algorithm using Python and TensorFlow. The AI ​​algorithm identifies the cause of back pain and the optimal treatment based on the user's input data.

[0717] Based on the analysis results, the server generates an individualized treatment plan, which includes specific treatment methods such as physical therapy, acupuncture, and drug therapy, and also recommends appropriate nearby medical facilities. The generated treatment plan is sent from the server to the user's device and displayed on the application interface.

[0718] The user selects one from the list of clinics displayed and makes a reservation online. The reservation information is sent to the server and stored in a database.

[0719] The server receives progress information from the clinic and adds it to the database for each user. Treatment progress information can be checked in real time on the "My Page" page within the application.

[0720] After treatment, users provide feedback on the effectiveness of the treatment through the application. This feedback is sent to the server, which uses it to refine the next treatment plan. The server then retrains and updates the generative AI model based on the collected treatment progress and feedback information.

[0721] Specific examples

[0722] The user enters the information "I have a sharp pain in the right side of my lower back that has lasted for more than a week" into the input form and presses the submit button. The server stores this information in a database and analyzes it using an AI algorithm. The AI ​​identifies the condition as "lower back pain caused by long hours of desk work," recommends physical therapy and acupuncture, and finds that the nearest clinic B is the most suitable. This information is displayed on the user's device, and the user selects clinic B and makes an online reservation.

[0723] Prompt Sentence Examples

[0724] "Enter information about your back pain symptoms and generate an optimal treatment plan."

[0725] "The received data is analyzed and the optimal back pain treatment plan is proposed to the user."

[0726] Through the above process, the system provides users with the optimal treatment plan and supports them in maximizing the effectiveness of treatment. By linking users, servers, and devices, it becomes possible to provide precise treatment tailored to each individual patient.

[0727] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0728] Step 1:

[0729] Users access the application using a smartphone or PC, enter their health information such as age, gender, medical history, location and severity of pain, and duration into the application's input form, and then press the submit button.

[0730] Input: User health information and symptom data

[0731] Output: Health information and symptom data sent to the server

[0732] Step 2:

[0733] The server receives the health information and symptom data submitted by the user and stores it in a database.

[0734] Input: User-submitted health and symptom data

[0735] Output: Health information and symptom data stored in a database

[0736] Specific operation: The server stores the received data in a "patient database."

[0737] Step 3:

[0738] The server accesses health information and symptom data stored in the database and runs a generative AI model using Python and TensorFlow to analyze it. The generative AI model uses the user's data to identify the cause of their back pain and the optimal treatment.

[0739] Input: Health information and symptom data stored in a database

[0740] Output: Analysis of causes of lower back pain and optimal treatment

[0741] Specific operation: The generative AI model is activated and analysis is performed. For example, it determines that "this patient's back pain is caused by long hours of desk work."

[0742] Step 4:

[0743] Based on the analysis results, the server generates a personalized treatment plan, which includes specific treatment methods such as physical therapy, acupuncture, and medication, and also recommends suitable nearby medical facilities.

[0744] Input: Analysis results

[0745] Output: Individualized treatment plan and recommended medical facility information

[0746] Specific operation: The server creates a treatment plan such as "recommending physical therapy and acupuncture treatment, with the nearest medical facility B being the best."

[0747] Step 5:

[0748] The user's device retrieves the generated treatment plan and recommended medical facility information from the server and displays it on the application interface. The user interface is designed to be easy to read, allowing users to easily check the information.

[0749] Input: Treatment plan and recommended medical facility information sent from the server

[0750] Output: Treatment plan and recommended medical facility information displayed in the application

[0751] Specific operation: The device screen displays the message, "Physical therapy and acupuncture are recommended. The nearest medical facility is Facility B."

[0752] Step 6:

[0753] The user selects one from the list of medical facilities displayed and makes an appointment online. Once the appointment is completed, the information is sent to the server and stored in a database.

[0754] Input: Information about the medical facility and appointment date and time selected by the user

[0755] Output: Reservation information sent to the server and stored in the database

[0756] Specific action: The user "selects medical facility B and confirms the appointment at 2:00 PM on December 1st."

[0757] Step 7:

[0758] The server receives progress information from the medical facility and adds it to the database for each user. Treatment progress information includes specific details such as the next scheduled treatment date.

[0759] Input: Progress information from medical facilities

[0760] Output: Progress information added to the database

[0761] Specific operation: The server records the information "The first physical therapy session has ended, and the next session will be on December 8th" in the database.

[0762] Step 8:

[0763] After treatment, users provide feedback through the application, including specific details about the effectiveness of the treatment and the progress of the treatment. The feedback information is sent to the server and used to improve the next treatment plan.

[0764] Input: User feedback information on the effectiveness of the treatment

[0765] Output: Feedback information sent to the server

[0766] Specific action: The user enters feedback such as "My pain has significantly decreased after treatment" and presses the submit button.

[0767] Step 9:

[0768] The server aggregates progress information from clinics and feedback from users, and uses AI algorithms to refine the next treatment plan. Based on the aggregated results, the generative AI model is updated to optimize the effectiveness of treatment.

[0769] Input: Treatment progress information and feedback information

[0770] Output: Improved generative AI model and next treatment plan

[0771] Specific operation: The server retrains the generative AI model based on the conclusion that "combining physical therapy and acupuncture is effective."

[0772] Step 10:

[0773] Users can access the application's "My Page" to check their own treatment history and upcoming treatment schedules. The treatment history includes detailed progress information, allowing users to intuitively check the effectiveness of their treatment.

[0774] Input: User's treatment history and next treatment schedule information

[0775] Output: Treatment history and treatment schedule information displayed on the personal page within the application

[0776] Specific operation: The user checks the information on his / her personal page that "the first physical therapy session has ended and the next session is scheduled for December 8th."

[0777] (Application example 1)

[0778] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0779] In conventional lower back pain treatment, it has been difficult to quickly present an optimal treatment plan tailored to individual symptoms and the user's specific conditions, and to monitor the progress of the plan in real time. Furthermore, there has been a lack of systems in place to efficiently manage treatment clinic appointments and provide feedback. The present invention aims to solve these problems and maximize the effectiveness of lower back pain treatment.

[0780] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0781] In this invention, the server includes means for storing health information and symptom data received from a user, means for using an AI algorithm to analyze the health information and symptom data, means for generating an individualized treatment plan based on the analysis results of the AI ​​algorithm, means for selecting an optimal treatment clinic based on the individualized treatment plan, means for displaying the individualized treatment plan and information on the optimal treatment clinic on a user terminal, means for managing reservation information for the treatment clinic, means for receiving and managing treatment progress and feedback information, means for improving the treatment plan based on the feedback information, means for providing an interface for making reservations and managing progress for osteopathic clinics using a user terminal, and means for users to input and check data using a smartphone. This enables the provision of an optimal treatment plan for each user, real-time confirmation of treatment progress, efficient reservation management, and effective improvement of the treatment plan based on feedback.

[0782] A "user terminal" is a digital device used by each user to input information and review treatment plans.

[0783] "Health information" refers to data relating to the user's general health, such as age, gender, medical history, etc.

[0784] "Symptom data" is information about specific symptoms experienced by the user, such as the location of pain, the degree of pain, and the duration of pain.

[0785] "AI algorithm" is an artificial intelligence technology that analyzes collected health information and symptom data to generate optimal treatment plans.

[0786] A "personalized treatment plan" is a detailed plan of treatment that is generated based on a user's specific health information and symptom data.

[0787] The "optimal treatment center" is a medical facility that can provide the most appropriate treatment based on the user's treatment plan.

[0788] The "display means" is an interface for visually presenting treatment plans and clinic information on a user terminal.

[0789] The "means for managing reservation information" is a function that manages the reservation status of the treatment center selected by the user and makes changes or cancellations as necessary.

[0790] "Treatment progress status" is information indicating the stage of treatment.

[0791] "Feedback information" refers to opinions and evaluations regarding the effectiveness and satisfaction of a treatment provided by a user after the treatment.

[0792] "Treatment plan refinement" is the process of updating an existing treatment plan to make it more effective based on collected feedback information.

[0793] The "interface" refers to the screens and menus that users operate, and is the part that provides functions such as treatment reservations and progress checks.

[0794] A system for effectively implementing this invention is preferably constructed using a user terminal, a server, and an AI algorithm. Specific embodiments are described below.

[0795] First, the user accesses the application from a smartphone or other device. The user inputs health information such as age, gender, and medical history, as well as symptom data such as the location, severity, and duration of pain. This data is collected via an intuitive user interface and sent to the server.

[0796] The server stores the received health information and symptom data in a database. It then uses AI algorithms to analyze this information and generate an optimal treatment plan for each individual user. This treatment plan may include recommendations for physical therapy, acupuncture, medication, and more. The AI ​​algorithms can be, for example, Python's TensorFlow or SciKit-Learn.

[0797] The server selects the most suitable clinic in the user's area based on the generated treatment plan. The treatment plan is then sent to the user's device along with information about the selected clinic. The user can then review this information and make a reservation at the recommended clinic through the application interface.

[0798] Once treatment begins at the clinic, the user's treatment progress is sent to the server in real time. The user can check their treatment progress from their smartphone. When the user provides feedback after treatment, that information is also sent to the server and stored in the database.

[0799] The server analyzes this feedback information and uses it to improve future treatment plans. By updating the AI ​​algorithm, it is possible to provide increasingly effective treatment plans.

[0800] For example, the following prompt sentence is used as the user's input:

[0801] "30-year-old male with unremarkable health history. Presenting with severe pain in the lower back for two weeks."

[0802] "My back pain has significantly decreased after treatment."

[0803] "The physical therapy at the clinic I booked was effective."

[0804] This allows users to easily and quickly input their health information and select the optimal treatment plan and clinic, and the treatment plan is continuously improved based on feedback, maximizing the effectiveness of treatment.

[0805] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0806] Step 1:

[0807] Users access the application from their smartphones and input their health information and symptom data. The input data includes age, gender, medical history, pain location, pain severity, and duration. This data is collected via an intuitive user interface and sent to the server. The input data is sent from the user's device to the server as initial data.

[0808] Step 2:

[0809] The server stores the health information and symptom data received from the user in a database. During this storage process, the received data is formatted to fit the database format. Specifically, the data is processed so that each item is stored appropriately in the database table. From the health information and symptom data received as input, user information in database format is output.

[0810] Step 3:

[0811] The server passes the stored health information and symptom data to an AI algorithm for analysis. The AI ​​algorithm used is implemented using Python's TensorFlow and SciKit-Learn, and analyzes the user's data to generate an optimal treatment plan. This analysis process uses pattern recognition and predictive models to identify treatment methods based on the input data. The treatment plan generated based on the analyzed data is output.

[0812] Step 4:

[0813] The server selects the most suitable clinic in the user's area based on the generated individual treatment plan. In this selection process, it searches a database of clinics for geographically nearby clinics and determines the most suitable clinic based on each clinic's specialty and evaluation information. The output is a list of the selected optimal clinics.

[0814] Step 5:

[0815] The server sends the individual treatment plan and information on the most suitable treatment center to the user's device. The details of the treatment plan and information on the recommended treatment center are displayed on the user's smartphone. The user can check this information on the screen. The displayed treatment plan and treatment center information are output.

[0816] Step 6:

[0817] After checking the displayed clinic information, the user uses the application interface to make a reservation at the clinic of their choice. The reservation information is sent to the server via the user interface, and the server stores this information in a database and notifies the clinic. The reservation information is entered, and a notification of reservation completion is output.

[0818] Step 7:

[0819] Once treatment begins, treatment progress information is sent from the treatment clinic to the server. This progress information includes the treatment status and the next scheduled treatment date. The server adds and updates this information in real time to the user's database. The entered treatment progress information is output as updated database information.

[0820] Step 8:

[0821] After treatment, users provide feedback through the application. The feedback information includes the user's opinions on the effectiveness of treatment and satisfaction. The feedback information is sent to the server, stored in a database, and used to improve future treatment plans. The input feedback information is output as data for improving treatment plans.

[0822] Step 9:

[0823] The server analyzes the received treatment progress information and user feedback information, and improves future treatment plans based on the AI ​​algorithm model. This ensures effective treatment for each user. An improved treatment plan is output based on the analyzed feedback information.

[0824] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0825] This invention is a system that provides information on lower back pain treatment, creates an optimal treatment plan, and manages the progress of treatment, and also combines it with an emotion engine that recognizes the user's emotions. Below, we will explain in detail the embodiments of this system.

[0826] Entering user information

[0827] Subject: User

[0828] Example: A user accesses the application from a smartphone or PC and enters general health information such as their age, gender, and medical history. They also enter detailed symptom data such as the location of pain, its severity, and duration. At this time, the emotion engine recognizes emotions from the user's facial expressions and tone of voice and transfers them to the system.

[0829] Receiving and storing patient information

[0830] Subject: Server

[0831] Example: The server receives health and symptom data submitted by the user, as well as the user's emotion information received from the emotion engine, and stores them in a database. It performs checks to ensure the data is complete and consistent.

[0832] Data analysis

[0833] Subject: Server

[0834] Example: The server analyzes the stored data using an AI algorithm. The AI ​​algorithm identifies the cause of the problem based on the user's health information and symptom data. Furthermore, it adds emotional information from the emotion engine to the analysis results and selects the optimal treatment based on the user's stress level and emotional state.

[0835] Treatment plan generation

[0836] Subject: Server

[0837] Example: The server generates an individualized treatment plan based on the analysis results. This treatment plan includes specific treatment methods such as physical therapy, acupuncture, and drug therapy. It can also incorporate a plan to provide psychological support by taking into account the user's emotional information. It can also select the most suitable treatment center from among nearby treatment centers.

[0838] View Treatment Plan

[0839] Subject: Terminal

[0840] Example: The user's device receives the generated treatment plan and recommended clinic information from the server. This information is displayed on the application's user interface for the user to review. For example, the user's screen might display, "Physical therapy and acupuncture are recommended. The nearest recommended clinic is Clinic A. Taking your emotional state into consideration, we've also added a relaxation session."

[0841] Selecting and booking a treatment center

[0842] Subject: User

[0843] Example: A user selects one from a list of clinics and makes an appointment online. Once the appointment is completed, the information is sent to the server and stored in a database.

[0844] Monitoring treatment progress

[0845] Subject: Server

[0846] Example: The server receives progress information from the clinic and adds it to the database for each user. The treatment progress information includes the details of the actual treatment and the next treatment appointment information. The treatment history is continuously updated and managed.

[0847] Receiving Feedback

[0848] Subject: User

[0849] Example: A user accesses an application to enter feedback after treatment. The user writes about the effectiveness of the treatment and their satisfaction in the feedback form. The emotion engine also obtains the user's emotion information at this point, and sends it to the server along with the feedback information.

[0850] Analyze feedback and refine treatment plans

[0851] Subject: Server

[0852] Example: The server stores the feedback and emotional information received from the emotion engine in a database. The feedback data is analyzed using an AI algorithm to evaluate the effectiveness of treatment. The treatment plan is improved based on the analysis results. The improved treatment plan is reflected in the next plan generation.

[0853] Confirmation of treatment effectiveness

[0854] Subject: User

[0855] Example: Users can access the application's "My Page" to check their own treatment history and upcoming treatment schedules. By understanding progress in real time, the effectiveness of treatment can be visualized.

[0856] Through this series of processes, the low back pain treatment navigation system can provide the user with an optimal treatment plan, manage the progress of treatment, and confirm its effectiveness. Furthermore, by combining it with an emotion engine, it becomes possible to provide more comprehensive treatment support that takes into account the user's emotional state.

[0857] The processing flow will be explained below.

[0858] Step 1: Enter your user information

[0859] Subject: User

[0860] Specific behavior:

[0861] The user opens the application on their smartphone or PC.

[0862] Follow the application interface to enter health information such as age, gender, and medical history.

[0863] Enter details of your symptoms (e.g., location of pain, duration of pain, current pain level, etc.).

[0864] The emotion engine analyzes the user's facial expressions and tone of voice in real time and records emotional information.

[0865] Check the input and emotion information, then click the "Submit" button to send the information to the server.

[0866] Step 2: Receiving and storing patient information

[0867] Subject: Server

[0868] Specific behavior:

[0869] Health information and symptom data submitted by the user and emotion information from the emotion engine are received.

[0870] The received data is saved in the database.

[0871] Checks are performed to ensure data completeness and consistency.

[0872] Step 3: Analyze the data

[0873] Subject: Server

[0874] Specific behavior:

[0875] The stored data is analyzed using AI algorithms.

[0876] Use health and symptom data to identify the cause of the problem.

[0877] Emotional information from the emotion engine is added to the analysis results, and a treatment method is selected taking into account the user's stress level and emotional state.

[0878] Step 4: Generate a treatment plan

[0879] Subject: Server

[0880] Specific behavior:

[0881] Based on the analysis results, an individual treatment plan is generated.

[0882] The treatment plan will include recommended treatments (e.g., physical therapy, acupuncture, medication).

[0883] Taking into account the user's emotional information, a plan is incorporated that also includes psychological support.

[0884] Select the most suitable treatment center from nearby treatment centers.

[0885] The generated treatment plan and clinic information are stored in a database.

[0886] Step 5: View your treatment plan

[0887] Subject: Terminal

[0888] Specific behavior:

[0889] The user's terminal obtains the treatment plan and clinic information from the server.

[0890] The application interface displays treatment plans and recommended clinics.

[0891] It provides users with detailed information about their treatment plan and a list of recommended treatment centers.

[0892] Step 6: Select a clinic and book an appointment

[0893] Subject: User

[0894] Specific behavior:

[0895] The user selects one from the displayed list of clinics.

[0896] Check the details and available appointment times for the clinic you selected.

[0897] Select the date and time you want and confirm your reservation.

[0898] The reservation information is sent to the server and stored in a database.

[0899] Step 7: Monitor your treatment progress

[0900] Subject: Server

[0901] Specific behavior:

[0902] Receive progress updates from the clinic.

[0903] The progress status includes the actual treatment performed and the next treatment appointment information.

[0904] The received progress information is added to the patient database.

[0905] Continually update and manage your medical history.

[0906] Step 8: Receiving feedback

[0907] Subject: User

[0908] Specific behavior:

[0909] The user accesses the application to enter feedback after treatment.

[0910] Please fill in the feedback form to describe the effectiveness and satisfaction of the treatment.

[0911] The emotion engine also analyzes the user's facial expressions and voice and records emotional information when sending feedback.

[0912] The feedback content and emotion information are checked and sent to the server.

[0913] Step 9: Analyze feedback and refine treatment plan

[0914] Subject: Server

[0915] Specific behavior:

[0916] The received feedback information and emotion information are stored in a database.

[0917] Feedback data and emotional information are analyzed using AI algorithms to evaluate the effectiveness of treatment.

[0918] The treatment plan will be improved based on the analysis results.

[0919] The improved treatment plan is reflected in the next plan generation.

[0920] Step 10: Check the effectiveness of the treatment

[0921] Subject: User

[0922] Specific behavior:

[0923] The user accesses the application's "My Page."

[0924] Review your treatment history, progress, and upcoming treatment schedule.

[0925] Check the effectiveness of treatment in real time and prepare for the next treatment.

[0926] This processing flow enables the low back pain treatment navigation system to provide users with an optimal treatment plan, manage the progress of treatment, and confirm its effectiveness. Furthermore, by combining it with an emotion engine, comprehensive treatment support that takes into account the user's emotional state can be realized.

[0927] Example 2

[0928] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0929] A current challenge in treating lower back pain is the difficulty of providing an optimal treatment plan by evaluating each patient's symptoms and emotional state in detail. In particular, emotional information is not reflected in the treatment plan, making it difficult to grasp the patient's mental stress and achieving comprehensive treatment results. Furthermore, treatment progress and feedback information are not managed in real time, making efficient treatment follow-up difficult.

[0930] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0931] In this invention, the server includes: [means for storing health information, symptom data, and emotional information received from a user;] [means for using an AI algorithm to analyze the health information, symptom data, and emotional information;] [means for generating an individual treatment plan based on the analysis results of the AI ​​algorithm;] [means for selecting an optimal medical institution based on the individual treatment plan;] [means for displaying the individual treatment plan and information on the optimal medical institution on a user terminal;] [means for managing reservation information for the medical institution;] [means for receiving and managing treatment progress and feedback information; and [means for improving the treatment plan based on the feedback information]. This makes it possible to analyze each patient's health information and emotional state in detail, provide an optimal treatment plan, and manage progress information and feedback in real time.

[0932] "Health information" is data relating to the user's overall health, such as the user's age, gender, medical history, and current health condition.

[0933] "Symptom data" refers to information about specific symptoms reported by the user, such as the location of pain, the degree of pain, and the duration of pain.

[0934] "Emotion information" is data on the emotional state of the user based on facial expressions and tone of voice obtained by the emotion engine.

[0935] An "AI algorithm" is a computational method that uses artificial intelligence technologies such as machine learning and deep learning to analyze data and derive results.

[0936] A "treatment plan" is a proposal for an individual treatment method created based on the analysis results, and includes specific treatment methods such as physical therapy, acupuncture, and drug therapy.

[0937] "Medical institution" refers to a facility such as a hospital, clinic, or doctor's office that provides treatment to users.

[0938] A "user terminal" is a device used by a user, such as a smartphone or a personal computer.

[0939] "Reservation information" is data related to a reservation for treatment at a medical institution selected by the user.

[0940] "Progress information" is information indicating the stage to which treatment has progressed, and includes specific treatment details and information on the next treatment appointment.

[0941] "Feedback information" is information provided by the user after treatment regarding the effectiveness and satisfaction of the treatment.

[0942] MODE FOR CARRYING OUT THE INVENTION

[0943] System Overview

[0944] This invention is a system that provides information on lower back pain treatment, creates optimal treatment plans, and manages treatment progress. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it provides comprehensive treatment support that takes into account the user's emotional state. The system consists of a server, a user terminal, and an emotion engine, and the server, acting as a central processing unit, performs data analysis using an AI algorithm.

[0945] System configuration

[0946] Server: Stores and analyzes data, generates treatment plans, and manages progress information. Specific software includes machine learning models and data analysis tools for implementing AI algorithms.

[0947] User terminal: A device such as a smartphone or PC that is used by users to input information and check treatment plans.

[0948] Emotion engine: Has the function of analyzing the user's facial expressions and tone of voice to obtain emotional information.

[0949] Processing flow

[0950] Entering user information

[0951] Users access the application from their smartphone or PC and enter specific health information such as their age, gender, medical history, location and degree of pain, and duration. The emotion engine analyzes the user's facial expressions and tone of voice to obtain emotional information.

[0952] Sending user information

[0953] The device sends the entered health information, symptom data, and emotional information to a server, securely using the SSL / TLS protocol.

[0954] Receiving and storing patient information

[0955] The server receives the health, symptom, and emotion information sent by the device and stores it in a database, checking the data for completeness and consistency and backing it up for redundancy if necessary.

[0956] Data analysis

[0957] The server analyzes the stored data with AI algorithms, using machine learning models and deep learning to identify the cause of the problem based on the user's health information and symptom data, and evaluates stress levels and emotional state by taking emotional information into account.

[0958] Treatment plan generation

[0959] Based on the analysis results, the server generates a treatment plan tailored to each individual user. This plan includes treatment methods such as physical therapy, acupuncture, and medication. It also provides mental support based on emotional information. It also selects and recommends the most appropriate medical institution.

[0960] View Treatment Plan

[0961] The user device receives the treatment plan and information on recommended medical institutions from the server and displays it on the application's user interface. For example, it may display information such as, "Physical therapy and acupuncture treatment are recommended. The nearest recommended medical institution is Medical Institution A. Taking into account the user's emotional state, a relaxation session has also been added."

[0962] Selecting and booking a treatment center

[0963] The user selects one from the list of clinics displayed and makes a reservation online. The reservation information is sent to the server and stored in a database.

[0964] Monitoring treatment progress

[0965] The server receives treatment progress information sent from the treatment center and adds it to the database for each user. The progress information is updated in real time and next treatment appointment information is also managed.

[0966] Receiving Feedback

[0967] After treatment, the user enters feedback via the application, including information about the effectiveness of the treatment and their satisfaction. The emotion engine also acquires emotion information at this point and sends it to the server.

[0968] Analyze feedback and refine treatment plans

[0969] The server uses an AI algorithm to analyze the feedback and emotional information, evaluate the effectiveness of the treatment, and improve the treatment plan based on the analysis results, which will be reflected in the next treatment.

[0970] Confirmation of treatment effectiveness

[0971] Users can access the application's "My Page" to check their treatment history and next treatment schedule, which allows them to understand the progress of their treatment in real time and visualize the effects of their treatment.

[0972] Examples of prompt statements

[0973] Here is an example prompt:

[0974] You are using the lower back pain treatment navigation system. First, enter your health information, such as your age, gender, medical history, location and severity of your pain, and duration. Next, check the treatment plan and list of recommended clinics provided by the system, select your preferred clinic, and make an appointment. After treatment, you enter your feedback into the system, and the emotion engine evaluates your emotional state. This will further improve the treatment plan.

[0975] Through this series of processes, the system can provide the user with an optimal treatment plan, manage progress, and check effectiveness.In addition, by utilizing the emotion engine, it can also provide comprehensive treatment support that takes emotional states into account.

[0976] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0977] Step 1:

[0978] Input: Health information such as age, gender, medical history, location of pain, degree, duration, and user's emotional information

[0979] How it works: Users access the application from their smartphone or PC and enter health information such as age, gender, medical history, location of pain, degree, duration, etc. At the same time, the emotion engine analyzes the user's facial expressions and tone of voice to obtain emotional information.

[0980] Output: Obtained health information, symptom data and emotional information

[0981] Step 2:

[0982] Input: Acquired health information, symptom data and emotional information

[0983] How it works: The device sends the entered health information, symptom data, and emotional information to the server. Data transmission is secure using the SSL / TLS protocol.

[0984] Output: Health information, symptom data and emotional information sent to the server

[0985] Step 3:

[0986] Input: Health information, symptom data and emotional information sent to the server

[0987] Operation: The server receives the information sent from the device and stores it in the system's database, checking the data for completeness and consistency and backing it up if necessary.

[0988] Output: Health information, symptom data and emotional information stored in a database

[0989] Step 4:

[0990] Input: Health information, symptom data and emotional information stored in a database

[0991] How it works: The server analyzes the stored data with AI algorithms, which use machine learning models and deep learning to identify the cause of health issues based on the user's health information and symptom data, and evaluate stress levels and emotional states based on emotional information.

[0992] Output: Causes of health problems, stress levels, and emotional states as analysis results

[0993] Step 5:

[0994] Input: Causes of health problems as analysis results, stress levels, and emotional states

[0995] How it works: Based on the analysis results, the server generates an individualized treatment plan, which includes physical therapy, acupuncture, medication, and emotional support. It also uses AI algorithms to select and recommend the most appropriate medical institution.

[0996] Output: Generated personalized treatment plan and recommended medical institution information

[0997] Step 6:

[0998] Input: Generated individual treatment plan and recommended medical institution information

[0999] Operation: The user's device displays the treatment plan and recommended medical institution information received from the server on the application's user interface. For example, the following information may be displayed: "Physical therapy and acupuncture treatment are recommended. The nearest recommended medical institution is Medical Institution A. Taking into account the user's emotional state, a relaxation session has also been added."

[1000] Output: Treatment plan and recommended medical institution information displayed on the device

[1001] Step 7:

[1002] Input: Treatment plan and recommended medical institution information displayed on the device

[1003] How it works: The user selects one of the clinics from the list and makes an appointment online. The appointment information is sent from the device to the server and stored in a database.

[1004] Output: Reservation information sent and stored on the server

[1005] Step 8:

[1006] Input: Reservation information sent and stored on the server

[1007] Operation: The server adds treatment progress information received from the clinic to the database for each user. The progress information includes the details of the treatment performed and the next appointment information.

[1008] Output: Progress information added to the database per user

[1009] Step 9:

[1010] Input: Treatment progress information

[1011] How it works: After treatment, the user enters feedback through the application. At the same time, the emotion engine also acquires the user's emotion information and sends it to the server. The feedback includes information about the effectiveness of the treatment and the level of satisfaction.

[1012] Output: Feedback and emotion information sent to the server

[1013] Step 10:

[1014] Input: Feedback and emotion information sent to the server

[1015] How it works: The server analyzes feedback and emotional information using AI algorithms to evaluate the effectiveness of treatment. Based on the analysis results, it improves the existing treatment plan and reflects it in the next treatment.

[1016] Output: Improved treatment plan

[1017] Step 11:

[1018] Input: Improved treatment plans and treatment progress information

[1019] How it works: Users can access the application's "My Page" to check their treatment history and upcoming treatment schedules, allowing them to understand the progress of their treatment in real time and visually confirm the effectiveness of their treatment.

[1020] Output: User's treatment history and next treatment schedule information

[1021] (Application example 2)

[1022] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1023] In modern factories, workers are prone to developing back pain due to long periods of standing and carrying heavy objects, making worker health management important. However, there is a lack of a system that can monitor the health and emotional state of individual workers in real time and provide optimal treatment plans. This can lead to reduced worker productivity and a decrease in safety in the work environment.

[1024] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1025] In this invention, the server includes: [means for storing health information and symptom data received from a user;] [means for using an AI algorithm to analyze the health information and symptom data;] [means for generating an individualized treatment plan based on the analysis results of the AI ​​algorithm;] [means for selecting an optimal treatment clinic based on the individualized treatment plan;] [means for displaying the individualized treatment plan and information on the optimal treatment clinic on a user terminal;] [means for managing reservation information for the treatment clinic;] [means for receiving and managing treatment progress and feedback information;] [means for improving the treatment plan based on the feedback information;] [means for analyzing the user's emotional state using an emotion recognition engine and reflecting it in the treatment plan;] [means installed on a robot terminal used in the work environment and managing worker health information; and [means for checking and responding to worker progress and treatment history in real time.] This makes it possible to monitor workers' health conditions in real time and provide optimal treatment plans, thereby improving worker productivity and safety.

[1026] "Health information received from users" refers to general health data such as age, gender, medical history, etc. provided by individual users.

[1027] "Symptom data" is detailed data such as the location, severity, and duration of pain provided by the user based on their specific health condition.

[1028] "AI Algorithms" are artificial intelligence technologies for analyzing received and stored health information and symptom data.

[1029] An "individualized treatment plan" is a set of treatment processes and methods optimized for each individual user, generated based on the results of analysis by an AI algorithm.

[1030] The "best treatment center" is the medical facility or specialist best suited to treatment, selected based on the individual treatment plan.

[1031] A "user terminal" is an electronic device such as a personal computer or smartphone that displays individual treatment plans and information on the most suitable treatment center.

[1032] "Managing reservation information" means making reservations online with the treatment center of the user's choice, and recording and monitoring the reservation information.

[1033] "Treatment progress status" is data including the details of the treatment that was actually performed and information about the next treatment appointment.

[1034] "Feedback information" is information provided by the user after treatment regarding the effectiveness and satisfaction of the treatment.

[1035] An "emotion recognition engine" is a technology that detects emotions from a user's facial expressions and tone of voice and uses that information for analysis.

[1036] A "robot terminal" is an automated device used in work environments such as factories to manage workers' health information.

[1037] "Real-time monitoring" means being able to instantly access and monitor treatment progress and history.

[1038] This invention provides a system that collects a user's health information and symptom data, analyzes it using an AI algorithm, and proposes and manages an optimal treatment plan. Specific embodiments for implementing this system are described below.

[1039] Entering user information

[1040] Subject: User

[1041] Users access the application from their smartphone or computer and enter their health information and symptom data, such as their age, gender, medical history, location and degree of pain, and duration. At this time, the emotion recognition engine recognizes emotions from the user's facial expressions and tone of voice and transmits them to the system.

[1042] Receiving and storing patient information

[1043] Subject: Server

[1044] The server receives the health information and symptom data submitted by the user, as well as the emotion information received from the emotion recognition engine, and stores them securely in a database.

[1045] Data analysis

[1046] Subject: Server

[1047] The server analyzes the stored data using an AI algorithm. The AI ​​algorithm uses frameworks such as TensorFlow and PyTorch to analyze the user's health condition and symptoms. Furthermore, it adds emotional information received from an emotion recognition engine to the analysis results and selects the optimal treatment based on the user's stress level and emotional state.

[1048] Treatment plan generation

[1049] Subject: Server

[1050] Based on the analysis results, the server generates an individualized treatment plan, which includes specific treatment methods such as physical therapy, acupuncture, and medication. It also considers the user's emotional information and suggests treatment plans that include stress management and psychological support.

[1051] View Treatment Plan

[1052] Subject: User

[1053] The user's device retrieves the generated treatment plan and recommended clinic information from the server and displays them on the application interface. For example, it might say, "Physical therapy and acupuncture are recommended. The nearest recommended clinic is Clinic A. Taking your emotional state into consideration, we've also added a relaxation program."

[1054] Selecting and booking a treatment center

[1055] Subject: User

[1056] The user selects one from the list of clinics displayed and makes a reservation online. The reservation information is sent to the server and stored in a database.

[1057] Monitoring treatment progress

[1058] Subject: Server

[1059] The server receives progress information from the clinic and adds it to the database for each user, continuously updating and managing the progress, including treatment details and next appointment information.

[1060] Receiving Feedback

[1061] Subject: User

[1062] After treatment, users enter feedback into the application, including the effectiveness and satisfaction of the treatment. The emotion recognition engine recognizes the user's emotions from their facial expressions and tone of voice, and sends this along with the feedback data to the server.

[1063] Analyze feedback and refine treatment plans

[1064] Subject: Server

[1065] The server analyzes the received feedback and emotional information to evaluate the effectiveness of the treatment, and improves the treatment plan based on the analysis results, which are then reflected in the next treatment plan.

[1066] Confirmation of treatment effectiveness

[1067] Subject: User

[1068] Users can access the application's "My Page" to check their own treatment history and upcoming treatment schedules, grasp progress in real time, and visualize the effects of treatment.

[1069] Hardware and Software Used

[1070] The system uses smartphones, computers, and robotic devices, and uses MySQL as the database, Microsoft Azure Emotion API as the emotion recognition engine, and frameworks such as TensorFlow and PyTorch for AI data analysis.

[1071] Examples of concrete examples and prompts

[1072] For example, if the system recognizes an emotion such as "tired" from a worker's facial expression, it will input the following prompt sentence into the generative AI model:

[1073] Prompt Sentence Examples

[1074] "Consider how fatigued the worker is and include relaxing stretching techniques in your next treatment plan."

[1075] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1076] Step 1:

[1077] Entering user information

[1078] Subject: User

[1079] Users access the application from their smartphone or computer and enter their health information and symptom data, such as age, gender, medical history, location and degree of pain, and duration. The emotion recognition engine recognizes emotions from the user's facial expressions and tone of voice, and sends that data to the system to complete the input.

[1080] Input: User's health information, symptom data, and emotional data

[1081] Output: The information entered is sent to the system

[1082] Step 2:

[1083] Receiving and storing patient information

[1084] Subject: Server

[1085] The server receives the health and symptom data sent by the user and the emotion information received from the emotion recognition engine, and stores this data in a database using MySQL, which checks the consistency and completeness of the data.

[1086] Input: User's health information, symptom data, emotional data

[1087] Output: Saved data

[1088] Step 3:

[1089] Data analysis

[1090] Subject: Server

[1091] The server analyzes the stored data using AI algorithms. Using TensorFlow and PyTorch, it analyzes health information and symptom data to identify the cause of the problem. It also incorporates emotional information from an emotion recognition engine into the analysis and outputs the optimal treatment plan based on the user's emotional state.

[1092] Input: Health information, symptom data, emotion data

[1093] Output: Analysis results (candidate treatments)

[1094] Step 4:

[1095] Treatment plan generation

[1096] Subject: Server

[1097] The server generates an individualized treatment plan based on the analysis results, which includes specific treatment methods such as physical therapy, acupuncture, and medication, as well as stress management and psychological support, taking into account the user's emotional information.

[1098] Input: Analysis results, emotion information

[1099] Output: Individual treatment plan

[1100] Step 5:

[1101] View Treatment Plan

[1102] Subject: User

[1103] The user's device receives the generated treatment plan and recommended clinic information from the server and displays it on the application interface. The user can then review this information and select the appropriate treatment.

[1104] Input: Treatment plan, recommended clinic information

[1105] Output: Information displayed in the user interface

[1106] Step 6:

[1107] Selecting and booking a treatment center

[1108] Subject: User

[1109] The user selects the most suitable clinic from the displayed list and makes a reservation online. The reservation information is sent to the server and stored in a database.

[1110] Input: List of clinics, user selection

[1111] Output: Saved reservation information

[1112] Step 7:

[1113] Monitoring treatment progress

[1114] Subject: Server

[1115] The server receives progress information from the clinic and adds it to the database for each user, continuously updating and managing the progress status including treatment details and next appointment information.

[1116] Input: Progress information

[1117] Output: Updated user data

[1118] Step 8:

[1119] Receiving Feedback

[1120] Subject: User

[1121] After treatment, the user enters feedback into the application, and the emotion recognition engine extracts emotional information from the user's facial expressions and tone of voice, and all feedback data is sent to the server.

[1122] Input: User feedback, emotional data

[1123] Output: Saved feedback information

[1124] Step 9:

[1125] Analyze feedback and refine treatment plans

[1126] Subject: Server

[1127] The server analyzes the received feedback and emotional information to evaluate the effectiveness of the treatment, and improves the treatment plan based on the analysis results, which are reflected in the next plan generation.

[1128] Input: Feedback information, emotion data

[1129] Output: Improved treatment plan

[1130] Step 10:

[1131] Confirmation of treatment effectiveness

[1132] Subject: User

[1133] Users can access the application's "My Page" to check their own treatment history and upcoming treatment schedules, grasp progress in real time, and visualize the effects of treatment.

[1134] Input: User data

[1135] Output: Real-time display of treatment history and progress

[1136] Examples of concrete examples and prompts

[1137] For example, if the system recognizes an emotion such as "tired" from a worker's facial expression, it will input the following prompt sentence into the generative AI model:

[1138] Prompt Sentence Examples

[1139] "Consider how fatigued the worker is and include relaxing stretching techniques in your next treatment plan."

[1140] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1141] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1142] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1143] [Third embodiment]

[1144] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1145] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1146] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1147] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1148] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1149] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1150] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1151] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1152] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1153] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1154] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1155] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1156] The present invention provides a system for providing information on lower back pain treatment, creating an optimal treatment plan, and managing the progress of treatment. Hereinafter, an embodiment of this system will be described in detail.

[1157] Entering user information

[1158] Subject: User

[1159] Example: A user accesses an application on a smartphone or PC and enters general health information such as age, gender, and medical history, as well as detailed symptom data such as pain location, pain intensity, and duration. This is done through the app's intuitive interface.

[1160] Receiving and analyzing patient information

[1161] Subject: Server

[1162] Example: The server receives health information and symptom data sent by the user and stores it in a database. It then launches an AI algorithm to analyze the received data. The AI ​​analyzes the user's input data to identify the cause of back pain and the best treatment.

[1163] Treatment plan generation

[1164] Subject: Server

[1165] Example: The server generates an individualized treatment plan based on the analysis results. This treatment plan includes specific treatment methods such as physical therapy, acupuncture, and drug therapy. It also recommends the most suitable treatment center from among nearby treatment centers.

[1166] View Treatment Plan

[1167] Subject: Terminal

[1168] Example: The user's device receives the generated treatment plan and recommended clinic information from the server. This information is displayed on the application's user interface so that the user can check it. For example, the user's screen might display the following message: "Physical therapy and acupuncture are recommended. The nearest recommended clinic is Clinic A."

[1169] Selecting and booking a treatment center

[1170] Subject: User

[1171] Example: A user selects one from a list of clinics and makes an appointment online. Once the appointment is completed, the information is sent to the server and stored in a database.

[1172] Monitoring treatment progress

[1173] Subject: Server

[1174] Example: The server receives progress information from the clinic and adds it to the database for each user. Treatment progress information may include, for example, information such as "First physical therapy session completed, next scheduled treatment date."

[1175] Receiving Feedback

[1176] Subject: User

[1177] Example: After treatment, the user provides feedback through the application. For example, they input specific effects such as "pain was reduced after treatment" and send it to the server. The feedback information is used to improve the next treatment plan.

[1178] Data collection and treatment plan refinement

[1179] Subject: Server

[1180] Example: The server aggregates progress information from clinics and feedback from users, and uses an AI algorithm to compile the data. Based on this data, the effectiveness of the treatment plan is evaluated and the model is updated to improve future treatment plans.

[1181] Confirmation of treatment effectiveness

[1182] Subject: User

[1183] Example: Users can access the application's "My Page" to check their own treatment history and upcoming treatment schedules. By understanding progress in real time, the effectiveness of treatment can be visualized.

[1184] Through the above process, the back pain treatment navigation system provides users with the optimal treatment plan and supports them in maximizing the effectiveness of treatment. By linking the user, server, and device, it becomes possible to provide precise treatment tailored to each individual patient.

[1185] The processing flow will be explained below.

[1186] Step 1: Enter your user information

[1187] Subject: User

[1188] Specific behavior:

[1189] The user opens the application on their smartphone or PC.

[1190] Follow the application interface to enter health information such as age, gender, and medical history.

[1191] Enter details of your symptoms (e.g., location of pain, duration of pain, current pain level, etc.).

[1192] Check the information you entered and click the "Submit" button to send the information to the server.

[1193] Step 2: Receiving and storing patient information

[1194] Subject: Server

[1195] Specific behavior:

[1196] Receive health information and symptom data submitted by a user.

[1197] The received data is saved in the database.

[1198] Checks are performed to ensure data completeness and consistency.

[1199] Step 3: Analyze the data

[1200] Subject: Server

[1201] Specific behavior:

[1202] The stored data is analyzed using AI algorithms.

[1203] Recognize patterns in symptoms and identify the source of problems.

[1204] Analysis will be performed based on criteria for selecting the optimal treatment.

[1205] Step 4: Generate a treatment plan

[1206] Subject: Server

[1207] Specific behavior:

[1208] Based on the analysis results, an individual treatment plan is generated.

[1209] The treatment plan will include recommended treatments (e.g., physical therapy, acupuncture, medication).

[1210] The system uses the user's current location information to select a suitable nearby clinic.

[1211] The generated treatment plan and clinic information are stored in a database.

[1212] Step 5: View your treatment plan

[1213] Subject: Terminal

[1214] Specific behavior:

[1215] The user's terminal obtains the treatment plan and clinic information from the server.

[1216] The application interface displays treatment plans and recommended clinics.

[1217] It provides users with detailed information about their treatment plan and a list of recommended treatment centers.

[1218] Step 6: Select a clinic and book an appointment

[1219] Subject: User

[1220] Specific behavior:

[1221] The user selects one of the displayed clinics.

[1222] Check the details and available appointment times for the clinic you selected.

[1223] Select your desired date and time and confirm your reservation.

[1224] The reservation information is sent to the server and stored in a database.

[1225] Step 7: Monitor your treatment progress

[1226] Subject: Server

[1227] Specific behavior:

[1228] Receive treatment progress updates from the clinic.

[1229] The progress status includes the details of the treatment that was actually performed and the next treatment appointment information.

[1230] The received progress information is added to the patient database.

[1231] Continually update and manage your medical history.

[1232] Step 8: Receiving feedback

[1233] Subject: User

[1234] Specific behavior:

[1235] The user accesses the application to enter feedback after treatment.

[1236] Please fill in the feedback form to describe the effectiveness and satisfaction of the treatment.

[1237] The feedback is checked and sent to the server.

[1238] Step 9: Analyze feedback and refine treatment plan

[1239] Subject: Server

[1240] Specific behavior:

[1241] The received feedback information is stored in a database.

[1242] The feedback data is analyzed using an AI algorithm to evaluate the effectiveness of the treatment.

[1243] The treatment plan will be improved based on the analysis results.

[1244] The improved treatment plan is reflected in the next plan generation.

[1245] Step 10: Check the effectiveness of the treatment

[1246] Subject: User

[1247] Specific behavior:

[1248] The user accesses the application's "My Page."

[1249] Review your treatment history, progress, and upcoming treatment schedule.

[1250] Check the effectiveness of treatment in real time and prepare for the next treatment.

[1251] Through this series of processes, the lower back pain treatment navigation system can provide the user with an optimal treatment plan, manage the progress of treatment, and confirm its effectiveness.

[1252] Example 1

[1253] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1254] In the treatment of lower back pain, existing systems have difficulty providing optimal treatment plans based on individual patients' symptoms and progress. Furthermore, management of treatment progress and collection and analysis of feedback are often done manually, preventing efficient improvements to treatment plans. This makes it difficult to quickly and effectively provide treatment methods appropriate for each patient.

[1255] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1256] In this invention, the server includes: [means for storing health information and symptom data received from a user;] [means for using a generative AI model to analyze the health information and symptom data; and] [means for generating an individual treatment plan based on the analysis results of the generative AI model.] This makes it possible [to automatically generate and refine an optimal treatment plan based on the patient's individual symptoms and progress, and provide effective treatment for lower back pain].

[1257] "Health information" refers to data that indicates the patient's overall health condition, such as the patient's age, sex, medical history, etc.

[1258] "Symptom data" refers to data that indicates specific symptoms such as the location of pain felt by the patient, the degree of pain, and the duration of pain.

[1259] A "generative AI model" is an algorithm that uses artificial intelligence to analyze received health information and symptom data and generate an optimal treatment plan.

[1260] A "treatment plan" is a plan that includes specific treatment methods such as physical therapy, acupuncture, and drug therapy that the generative AI model proposes based on the analysis results.

[1261] The "optimal medical facility" is a medical facility such as a clinic or hospital that the generative AI model recommends based on the analysis results.

[1262] A "user terminal" is a device used by a user, such as a smartphone or PC.

[1263] "Reservation information" is information regarding reservations for treatment at a medical facility selected by the user.

[1264] "Treatment progress status" is information indicating the progress status of treatment currently in progress.

[1265] "Feedback information" is data indicating opinions and impressions provided by the user regarding the effectiveness of treatment and the state of improvement.

[1266] "Updating the generative AI model" refers to the operation of retraining the generative AI model to improve the next treatment plan based on the received treatment progress and feedback information.

[1267] This invention is a system for providing information on lower back pain treatment, creating optimal treatment plans, and managing treatment progress. This system allows users to input their own health information and symptom data, which is then analyzed by a server, which then generates an optimal treatment plan and displays it on the user's device. It also maximizes the effectiveness of treatment by allowing users to select and book treatment centers, manage treatment progress, and collect feedback.

[1268] Hardware and software used

[1269] Server: A computing environment equipped with a high-performance processor and large memory capacity

[1270] Database: A relational database such as MySQL or PostgreSQL

[1271] Generative AI models: Machine learning frameworks such as Python and TensorFlow

[1272] User devices: smartphones, PCs

[1273] Application: Web or mobile application

[1274] Specific system operations and procedures

[1275] Users access the application using a smartphone or PC. They enter their health information, such as their age, gender, medical history, location and severity of pain, and duration, into the application's input form. This information is sent to the server by pressing the send button.

[1276] The server receives the health information and symptom data sent by the user and stores it in a database. The stored data is analyzed by an AI algorithm using Python and TensorFlow. The AI ​​algorithm identifies the cause of back pain and the optimal treatment based on the user's input data.

[1277] Based on the analysis results, the server generates an individualized treatment plan, which includes specific treatment methods such as physical therapy, acupuncture, and drug therapy, and also recommends appropriate nearby medical facilities. The generated treatment plan is sent from the server to the user's device and displayed on the application interface.

[1278] The user selects one from the list of clinics displayed and makes a reservation online. The reservation information is sent to the server and stored in a database.

[1279] The server receives progress information from the clinic and adds it to the database for each user. Treatment progress information can be checked in real time on the "My Page" page within the application.

[1280] After treatment, users provide feedback on the effectiveness of the treatment through the application. This feedback is sent to the server, which uses it to refine the next treatment plan. The server then retrains and updates the generative AI model based on the collected treatment progress and feedback information.

[1281] Specific examples

[1282] The user enters the information "I have a sharp pain in the right side of my lower back that has lasted for more than a week" into the input form and presses the submit button. The server stores this information in a database and analyzes it using an AI algorithm. The AI ​​identifies the condition as "lower back pain caused by long hours of desk work," recommends physical therapy and acupuncture, and finds that the nearest clinic B is the most suitable. This information is displayed on the user's device, and the user selects clinic B and makes an online reservation.

[1283] Prompt Sentence Examples

[1284] "Enter information about your back pain symptoms and generate an optimal treatment plan."

[1285] "The received data is analyzed and the optimal back pain treatment plan is proposed to the user."

[1286] Through the above process, the system provides users with the optimal treatment plan and supports them in maximizing the effectiveness of treatment. By linking users, servers, and devices, it becomes possible to provide precise treatment tailored to each individual patient.

[1287] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1288] Step 1:

[1289] Users access the application using a smartphone or PC, enter their health information such as age, gender, medical history, location and severity of pain, and duration into the application's input form, and then press the submit button.

[1290] Input: User health information and symptom data

[1291] Output: Health information and symptom data sent to the server

[1292] Step 2:

[1293] The server receives the health information and symptom data submitted by the user and stores it in a database.

[1294] Input: User-submitted health and symptom data

[1295] Output: Health information and symptom data stored in a database

[1296] Specific operation: The server stores the received data in a "patient database."

[1297] Step 3:

[1298] The server accesses health information and symptom data stored in the database and runs a generative AI model using Python and TensorFlow to analyze it. The generative AI model uses the user's data to identify the cause of their back pain and the optimal treatment.

[1299] Input: Health information and symptom data stored in a database

[1300] Output: Analysis of causes of lower back pain and optimal treatment

[1301] Specific operation: The generative AI model is activated and analysis is performed. For example, it determines that "this patient's back pain is caused by long hours of desk work."

[1302] Step 4:

[1303] Based on the analysis results, the server generates a personalized treatment plan, which includes specific treatment methods such as physical therapy, acupuncture, and medication, and also recommends suitable nearby medical facilities.

[1304] Input: Analysis results

[1305] Output: Individualized treatment plan and recommended medical facility information

[1306] Specific operation: The server creates a treatment plan such as "recommending physical therapy and acupuncture treatment, with the nearest medical facility B being the best."

[1307] Step 5:

[1308] The user's device retrieves the generated treatment plan and recommended medical facility information from the server and displays it on the application interface. The user interface is designed to be easy to read, allowing users to easily check the information.

[1309] Input: Treatment plan and recommended medical facility information sent from the server

[1310] Output: Treatment plan and recommended medical facility information displayed in the application

[1311] Specific operation: The device screen displays the message, "Physical therapy and acupuncture are recommended. The nearest medical facility is Facility B."

[1312] Step 6:

[1313] The user selects one from the list of medical facilities displayed and makes an appointment online. Once the appointment is completed, the information is sent to the server and stored in a database.

[1314] Input: Information about the medical facility and appointment date and time selected by the user

[1315] Output: Reservation information sent to the server and stored in the database

[1316] Specific action: The user "selects medical facility B and confirms the appointment at 2:00 PM on December 1st."

[1317] Step 7:

[1318] The server receives progress information from the medical facility and adds it to the database for each user. Treatment progress information includes specific details such as the next scheduled treatment date.

[1319] Input: Progress information from medical facilities

[1320] Output: Progress information added to the database

[1321] Specific operation: The server records the information "The first physical therapy session has ended, and the next session will be on December 8th" in the database.

[1322] Step 8:

[1323] After treatment, users provide feedback through the application, including specific details about the effectiveness of the treatment and the progress of the treatment. The feedback information is sent to the server and used to improve the next treatment plan.

[1324] Input: User feedback information on the effectiveness of the treatment

[1325] Output: Feedback information sent to the server

[1326] Specific action: The user enters feedback such as "My pain has significantly decreased after treatment" and presses the submit button.

[1327] Step 9:

[1328] The server aggregates progress information from clinics and feedback from users, and uses AI algorithms to refine the next treatment plan. Based on the aggregated results, the generative AI model is updated to optimize the effectiveness of treatment.

[1329] Input: Treatment progress information and feedback information

[1330] Output: Improved generative AI model and next treatment plan

[1331] Specific operation: The server retrains the generative AI model based on the conclusion that "combining physical therapy and acupuncture is effective."

[1332] Step 10:

[1333] Users can access the application's "My Page" to check their own treatment history and upcoming treatment schedules. The treatment history includes detailed progress information, allowing users to intuitively check the effectiveness of their treatment.

[1334] Input: User's treatment history and next treatment schedule information

[1335] Output: Treatment history and treatment schedule information displayed on the personal page within the application

[1336] Specific operation: The user checks the information on his / her personal page that "the first physical therapy session has ended and the next session is scheduled for December 8th."

[1337] (Application example 1)

[1338] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1339] In conventional lower back pain treatment, it has been difficult to quickly present an optimal treatment plan tailored to individual symptoms and the user's specific conditions, and to monitor the progress of the plan in real time. Furthermore, there has been a lack of systems in place to efficiently manage treatment clinic appointments and provide feedback. The present invention aims to solve these problems and maximize the effectiveness of lower back pain treatment.

[1340] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1341] In this invention, the server includes means for storing health information and symptom data received from a user, means for using an AI algorithm to analyze the health information and symptom data, means for generating an individualized treatment plan based on the analysis results of the AI ​​algorithm, means for selecting an optimal treatment clinic based on the individualized treatment plan, means for displaying the individualized treatment plan and information on the optimal treatment clinic on a user terminal, means for managing reservation information for the treatment clinic, means for receiving and managing treatment progress and feedback information, means for improving the treatment plan based on the feedback information, means for providing an interface for making reservations and managing progress for osteopathic clinics using a user terminal, and means for users to input and check data using a smartphone. This enables the provision of an optimal treatment plan for each user, real-time confirmation of treatment progress, efficient reservation management, and effective improvement of the treatment plan based on feedback.

[1342] A "user terminal" is a digital device used by each user to input information and review treatment plans.

[1343] "Health information" refers to data relating to the user's general health, such as age, gender, medical history, etc.

[1344] "Symptom data" is information about specific symptoms experienced by the user, such as the location of pain, the degree of pain, and the duration of pain.

[1345] "AI algorithm" is an artificial intelligence technology that analyzes collected health information and symptom data to generate optimal treatment plans.

[1346] A "personalized treatment plan" is a detailed plan of treatment that is generated based on a user's specific health information and symptom data.

[1347] The "optimal treatment center" is a medical facility that can provide the most appropriate treatment based on the user's treatment plan.

[1348] The "display means" is an interface for visually presenting treatment plans and clinic information on a user terminal.

[1349] The "means for managing reservation information" is a function that manages the reservation status of the treatment center selected by the user and makes changes or cancellations as necessary.

[1350] "Treatment progress status" is information indicating the stage of treatment.

[1351] "Feedback information" refers to opinions and evaluations regarding the effectiveness and satisfaction of a treatment provided by a user after the treatment.

[1352] "Treatment plan refinement" is the process of updating an existing treatment plan to make it more effective based on collected feedback information.

[1353] The "interface" refers to the screens and menus that users operate, and is the part that provides functions such as treatment reservations and progress checks.

[1354] A system for effectively implementing this invention is preferably constructed using a user terminal, a server, and an AI algorithm. Specific embodiments are described below.

[1355] First, the user accesses the application from a smartphone or other device. The user inputs health information such as age, gender, and medical history, as well as symptom data such as the location, severity, and duration of pain. This data is collected via an intuitive user interface and sent to the server.

[1356] The server stores the received health information and symptom data in a database. It then uses AI algorithms to analyze this information and generate an optimal treatment plan for each individual user. This treatment plan may include recommendations for physical therapy, acupuncture, medication, and more. The AI ​​algorithms can be, for example, Python's TensorFlow or SciKit-Learn.

[1357] The server selects the most suitable clinic in the user's area based on the generated treatment plan. The treatment plan is then sent to the user's device along with information about the selected clinic. The user can then review this information and make a reservation at the recommended clinic through the application interface.

[1358] Once treatment begins at the clinic, the user's treatment progress is sent to the server in real time. The user can check their treatment progress from their smartphone. When the user provides feedback after treatment, that information is also sent to the server and stored in the database.

[1359] The server analyzes this feedback information and uses it to improve future treatment plans. By updating the AI ​​algorithm, it is possible to provide increasingly effective treatment plans.

[1360] For example, the following prompt sentence is used as the user's input:

[1361] "30-year-old male with unremarkable health history. Presenting with severe pain in the lower back for two weeks."

[1362] "My back pain has significantly decreased after treatment."

[1363] "The physical therapy at the clinic I booked was effective."

[1364] This allows users to easily and quickly input their health information and select the optimal treatment plan and clinic, and the treatment plan is continuously improved based on feedback, maximizing the effectiveness of treatment.

[1365] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1366] Step 1:

[1367] Users access the application from their smartphones and input their health information and symptom data. The input data includes age, gender, medical history, pain location, pain severity, and duration. This data is collected via an intuitive user interface and sent to the server. The input data is sent from the user's device to the server as initial data.

[1368] Step 2:

[1369] The server stores the health information and symptom data received from the user in a database. During this storage process, the received data is formatted to fit the database format. Specifically, the data is processed so that each item is stored appropriately in the database table. From the health information and symptom data received as input, user information in database format is output.

[1370] Step 3:

[1371] The server passes the stored health information and symptom data to an AI algorithm for analysis. The AI ​​algorithm used is implemented using Python's TensorFlow and SciKit-Learn, and analyzes the user's data to generate an optimal treatment plan. This analysis process uses pattern recognition and predictive models to identify treatment methods based on the input data. The treatment plan generated based on the analyzed data is output.

[1372] Step 4:

[1373] The server selects the most suitable clinic in the user's area based on the generated individual treatment plan. In this selection process, it searches a database of clinics for geographically nearby clinics and determines the most suitable clinic based on each clinic's specialty and evaluation information. The output is a list of the selected optimal clinics.

[1374] Step 5:

[1375] The server sends the individual treatment plan and information on the most suitable treatment center to the user's device. The details of the treatment plan and information on the recommended treatment center are displayed on the user's smartphone. The user can check this information on the screen. The displayed treatment plan and treatment center information are output.

[1376] Step 6:

[1377] After checking the displayed clinic information, the user uses the application interface to make a reservation at the clinic of their choice. The reservation information is sent to the server via the user interface, and the server stores this information in a database and notifies the clinic. The reservation information is entered, and a notification of reservation completion is output.

[1378] Step 7:

[1379] Once treatment begins, treatment progress information is sent from the treatment clinic to the server. This progress information includes the treatment status and the next scheduled treatment date. The server adds and updates this information in real time to the user's database. The entered treatment progress information is output as updated database information.

[1380] Step 8:

[1381] After treatment, users provide feedback through the application. The feedback information includes the user's opinions on the effectiveness of treatment and satisfaction. The feedback information is sent to the server, stored in a database, and used to improve future treatment plans. The input feedback information is output as data for improving treatment plans.

[1382] Step 9:

[1383] The server analyzes the received treatment progress information and user feedback information, and improves future treatment plans based on the AI ​​algorithm model. This ensures effective treatment for each user. An improved treatment plan is output based on the analyzed feedback information.

[1384] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1385] This invention is a system that provides information on lower back pain treatment, creates an optimal treatment plan, and manages the progress of treatment, and also combines it with an emotion engine that recognizes the user's emotions. Below, we will explain in detail the embodiments of this system.

[1386] Entering user information

[1387] Subject: User

[1388] Example: A user accesses the application from a smartphone or PC and enters general health information such as their age, gender, and medical history. They also enter detailed symptom data such as the location of pain, its severity, and duration. At this time, the emotion engine recognizes emotions from the user's facial expressions and tone of voice and transfers them to the system.

[1389] Receiving and storing patient information

[1390] Subject: Server

[1391] Example: The server receives health and symptom data submitted by the user, as well as the user's emotion information received from the emotion engine, and stores them in a database. It performs checks to ensure the data is complete and consistent.

[1392] Data analysis

[1393] Subject: Server

[1394] Example: The server analyzes the stored data using an AI algorithm. The AI ​​algorithm identifies the cause of the problem based on the user's health information and symptom data. Furthermore, it adds emotional information from the emotion engine to the analysis results and selects the optimal treatment based on the user's stress level and emotional state.

[1395] Treatment plan generation

[1396] Subject: Server

[1397] Example: The server generates an individualized treatment plan based on the analysis results. This treatment plan includes specific treatment methods such as physical therapy, acupuncture, and drug therapy. It can also incorporate a plan to provide psychological support by taking into account the user's emotional information. It can also select the most suitable treatment center from among nearby treatment centers.

[1398] View Treatment Plan

[1399] Subject: Terminal

[1400] Example: The user's device receives the generated treatment plan and recommended clinic information from the server. This information is displayed on the application's user interface for the user to review. For example, the user's screen might display, "Physical therapy and acupuncture are recommended. The nearest recommended clinic is Clinic A. Taking your emotional state into consideration, we've also added a relaxation session."

[1401] Selecting and booking a treatment center

[1402] Subject: User

[1403] Example: A user selects one from a list of clinics and makes an appointment online. Once the appointment is completed, the information is sent to the server and stored in a database.

[1404] Monitoring treatment progress

[1405] Subject: Server

[1406] Example: The server receives progress information from the clinic and adds it to the database for each user. The treatment progress information includes the details of the actual treatment and the next treatment appointment information. The treatment history is continuously updated and managed.

[1407] Receiving Feedback

[1408] Subject: User

[1409] Example: A user accesses an application to enter feedback after treatment. The user writes about the effectiveness of the treatment and their satisfaction in the feedback form. The emotion engine also obtains the user's emotion information at this point, and sends it to the server along with the feedback information.

[1410] Analyze feedback and refine treatment plans

[1411] Subject: Server

[1412] Example: The server stores the feedback and emotional information received from the emotion engine in a database. The feedback data is analyzed using an AI algorithm to evaluate the effectiveness of treatment. The treatment plan is improved based on the analysis results. The improved treatment plan is reflected in the next plan generation.

[1413] Confirmation of treatment effectiveness

[1414] Subject: User

[1415] Example: Users can access the application's "My Page" to check their own treatment history and upcoming treatment schedules. By understanding progress in real time, the effectiveness of treatment can be visualized.

[1416] Through this series of processes, the low back pain treatment navigation system can provide the user with an optimal treatment plan, manage the progress of treatment, and confirm its effectiveness. Furthermore, by combining it with an emotion engine, it becomes possible to provide more comprehensive treatment support that takes into account the user's emotional state.

[1417] The processing flow will be explained below.

[1418] Step 1: Enter your user information

[1419] Subject: User

[1420] Specific behavior:

[1421] The user opens the application on their smartphone or PC.

[1422] Follow the application interface to enter health information such as age, gender, and medical history.

[1423] Enter details of your symptoms (e.g., location of pain, duration of pain, current pain level, etc.).

[1424] The emotion engine analyzes the user's facial expressions and tone of voice in real time and records emotional information.

[1425] Check the input and emotion information, then click the "Submit" button to send the information to the server.

[1426] Step 2: Receiving and storing patient information

[1427] Subject: Server

[1428] Specific behavior:

[1429] Health information and symptom data submitted by the user and emotion information from the emotion engine are received.

[1430] The received data is saved in the database.

[1431] Checks are performed to ensure data completeness and consistency.

[1432] Step 3: Analyze the data

[1433] Subject: Server

[1434] Specific behavior:

[1435] The stored data is analyzed using AI algorithms.

[1436] Use health and symptom data to identify the cause of the problem.

[1437] Emotional information from the emotion engine is added to the analysis results, and a treatment method is selected taking into account the user's stress level and emotional state.

[1438] Step 4: Generate a treatment plan

[1439] Subject: Server

[1440] Specific behavior:

[1441] Based on the analysis results, an individual treatment plan is generated.

[1442] The treatment plan will include recommended treatments (e.g., physical therapy, acupuncture, medication).

[1443] Taking into account the user's emotional information, a plan is incorporated that also includes psychological support.

[1444] Select the most suitable treatment center from nearby treatment centers.

[1445] The generated treatment plan and clinic information are stored in a database.

[1446] Step 5: View your treatment plan

[1447] Subject: Terminal

[1448] Specific behavior:

[1449] The user's terminal obtains the treatment plan and clinic information from the server.

[1450] The application interface displays treatment plans and recommended clinics.

[1451] It provides users with detailed information about their treatment plan and a list of recommended treatment centers.

[1452] Step 6: Select a clinic and book an appointment

[1453] Subject: User

[1454] Specific behavior:

[1455] The user selects one from the displayed list of clinics.

[1456] Check the details and available appointment times for the clinic you selected.

[1457] Select the date and time you want and confirm your reservation.

[1458] The reservation information is sent to the server and stored in a database.

[1459] Step 7: Monitor your treatment progress

[1460] Subject: Server

[1461] Specific behavior:

[1462] Receive progress updates from the clinic.

[1463] The progress status includes the actual treatment performed and the next treatment appointment information.

[1464] The received progress information is added to the patient database.

[1465] Continually update and manage your medical history.

[1466] Step 8: Receiving feedback

[1467] Subject: User

[1468] Specific behavior:

[1469] The user accesses the application to enter feedback after treatment.

[1470] Please fill in the feedback form to describe the effectiveness and satisfaction of the treatment.

[1471] The emotion engine also analyzes the user's facial expressions and voice and records emotional information when sending feedback.

[1472] The feedback content and emotion information are checked and sent to the server.

[1473] Step 9: Analyze feedback and refine treatment plan

[1474] Subject: Server

[1475] Specific behavior:

[1476] The received feedback information and emotion information are stored in a database.

[1477] Feedback data and emotional information are analyzed using AI algorithms to evaluate the effectiveness of treatment.

[1478] The treatment plan will be improved based on the analysis results.

[1479] The improved treatment plan is reflected in the next plan generation.

[1480] Step 10: Check the effectiveness of the treatment

[1481] Subject: User

[1482] Specific behavior:

[1483] The user accesses the application's "My Page."

[1484] Review your treatment history, progress, and upcoming treatment schedule.

[1485] Check the effectiveness of treatment in real time and prepare for the next treatment.

[1486] This processing flow enables the low back pain treatment navigation system to provide users with an optimal treatment plan, manage the progress of treatment, and confirm its effectiveness. Furthermore, by combining it with an emotion engine, comprehensive treatment support that takes into account the user's emotional state can be realized.

[1487] Example 2

[1488] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1489] A current challenge in treating lower back pain is the difficulty of providing an optimal treatment plan by evaluating each patient's symptoms and emotional state in detail. In particular, emotional information is not reflected in the treatment plan, making it difficult to grasp the patient's mental stress and achieving comprehensive treatment results. Furthermore, treatment progress and feedback information are not managed in real time, making efficient treatment follow-up difficult.

[1490] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1491] In this invention, the server includes: [means for storing health information, symptom data, and emotional information received from a user;] [means for using an AI algorithm to analyze the health information, symptom data, and emotional information;] [means for generating an individual treatment plan based on the analysis results of the AI ​​algorithm;] [means for selecting an optimal medical institution based on the individual treatment plan;] [means for displaying the individual treatment plan and information on the optimal medical institution on a user terminal;] [means for managing reservation information for the medical institution;] [means for receiving and managing treatment progress and feedback information; and [means for improving the treatment plan based on the feedback information]. This makes it possible to analyze each patient's health information and emotional state in detail, provide an optimal treatment plan, and manage progress information and feedback in real time.

[1492] "Health information" is data relating to the user's overall health, such as the user's age, gender, medical history, and current health condition.

[1493] "Symptom data" refers to information about specific symptoms reported by the user, such as the location of pain, the degree of pain, and the duration of pain.

[1494] "Emotion information" is data on the emotional state of the user based on facial expressions and tone of voice obtained by the emotion engine.

[1495] An "AI algorithm" is a computational method that uses artificial intelligence technologies such as machine learning and deep learning to analyze data and derive results.

[1496] A "treatment plan" is a proposal for an individual treatment method created based on the analysis results, and includes specific treatment methods such as physical therapy, acupuncture, and drug therapy.

[1497] "Medical institution" refers to a facility such as a hospital, clinic, or doctor's office that provides treatment to users.

[1498] A "user terminal" is a device used by a user, such as a smartphone or a personal computer.

[1499] "Reservation information" is data related to a reservation for treatment at a medical institution selected by the user.

[1500] "Progress information" is information indicating the stage to which treatment has progressed, and includes specific treatment details and information on the next treatment appointment.

[1501] "Feedback information" is information provided by the user after treatment regarding the effectiveness and satisfaction of the treatment.

[1502] MODE FOR CARRYING OUT THE INVENTION

[1503] System Overview

[1504] This invention is a system that provides information on lower back pain treatment, creates optimal treatment plans, and manages treatment progress. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it provides comprehensive treatment support that takes into account the user's emotional state. The system consists of a server, a user terminal, and an emotion engine, and the server, acting as a central processing unit, performs data analysis using an AI algorithm.

[1505] System configuration

[1506] Server: Stores and analyzes data, generates treatment plans, and manages progress information. Specific software includes machine learning models and data analysis tools for implementing AI algorithms.

[1507] User terminal: A device such as a smartphone or PC that is used by users to input information and check treatment plans.

[1508] Emotion engine: Has the function of analyzing the user's facial expressions and tone of voice to obtain emotional information.

[1509] Processing flow

[1510] Entering user information

[1511] Users access the application from their smartphone or PC and enter specific health information such as their age, gender, medical history, location and degree of pain, and duration. The emotion engine analyzes the user's facial expressions and tone of voice to obtain emotional information.

[1512] Sending user information

[1513] The device sends the entered health information, symptom data, and emotional information to a server, securely using the SSL / TLS protocol.

[1514] Receiving and storing patient information

[1515] The server receives the health, symptom, and emotion information sent by the device and stores it in a database, checking the data for completeness and consistency and backing it up for redundancy if necessary.

[1516] Data analysis

[1517] The server analyzes the stored data with AI algorithms, using machine learning models and deep learning to identify the cause of the problem based on the user's health information and symptom data, and evaluates stress levels and emotional state by taking emotional information into account.

[1518] Treatment plan generation

[1519] Based on the analysis results, the server generates a treatment plan tailored to each individual user. This plan includes treatment methods such as physical therapy, acupuncture, and medication. It also provides mental support based on emotional information. It also selects and recommends the most appropriate medical institution.

[1520] View Treatment Plan

[1521] The user device receives the treatment plan and information on recommended medical institutions from the server and displays it on the application's user interface. For example, it may display information such as, "Physical therapy and acupuncture treatment are recommended. The nearest recommended medical institution is Medical Institution A. Taking into account the user's emotional state, a relaxation session has also been added."

[1522] Selecting and booking a treatment center

[1523] The user selects one from the list of clinics displayed and makes a reservation online. The reservation information is sent to the server and stored in a database.

[1524] Monitoring treatment progress

[1525] The server receives treatment progress information sent from the treatment center and adds it to the database for each user. The progress information is updated in real time and next treatment appointment information is also managed.

[1526] Receiving Feedback

[1527] After treatment, the user enters feedback via the application, including information about the effectiveness of the treatment and their satisfaction. The emotion engine also acquires emotion information at this point and sends it to the server.

[1528] Analyze feedback and refine treatment plans

[1529] The server uses an AI algorithm to analyze the feedback and emotional information, evaluate the effectiveness of the treatment, and improve the treatment plan based on the analysis results, which will be reflected in the next treatment.

[1530] Confirmation of treatment effectiveness

[1531] Users can access the application's "My Page" to check their treatment history and next treatment schedule, which allows them to understand the progress of their treatment in real time and visualize the effects of their treatment.

[1532] Examples of prompt statements

[1533] Here is an example prompt:

[1534] You are using the lower back pain treatment navigation system. First, enter your health information, such as your age, gender, medical history, location and severity of your pain, and duration. Next, check the treatment plan and list of recommended clinics provided by the system, select your preferred clinic, and make an appointment. After treatment, you enter your feedback into the system, and the emotion engine evaluates your emotional state. This will further improve the treatment plan.

[1535] Through this series of processes, the system can provide the user with an optimal treatment plan, manage progress, and check effectiveness.In addition, by utilizing the emotion engine, it can also provide comprehensive treatment support that takes emotional states into account.

[1536] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1537] Step 1:

[1538] Input: Health information such as age, gender, medical history, location of pain, degree, duration, and user's emotional information

[1539] How it works: Users access the application from their smartphone or PC and enter health information such as age, gender, medical history, location of pain, degree, duration, etc. At the same time, the emotion engine analyzes the user's facial expressions and tone of voice to obtain emotional information.

[1540] Output: Obtained health information, symptom data and emotional information

[1541] Step 2:

[1542] Input: Acquired health information, symptom data and emotional information

[1543] How it works: The device sends the entered health information, symptom data, and emotional information to the server. Data transmission is secure using the SSL / TLS protocol.

[1544] Output: Health information, symptom data and emotional information sent to the server

[1545] Step 3:

[1546] Input: Health information, symptom data and emotional information sent to the server

[1547] Operation: The server receives the information sent from the device and stores it in the system's database, checking the data for completeness and consistency and backing it up if necessary.

[1548] Output: Health information, symptom data and emotional information stored in a database

[1549] Step 4:

[1550] Input: Health information, symptom data and emotional information stored in a database

[1551] How it works: The server analyzes the stored data with AI algorithms, which use machine learning models and deep learning to identify the cause of health issues based on the user's health information and symptom data, and evaluate stress levels and emotional states based on emotional information.

[1552] Output: Causes of health problems, stress levels, and emotional states as analysis results

[1553] Step 5:

[1554] Input: Causes of health problems as analysis results, stress levels, and emotional states

[1555] How it works: Based on the analysis results, the server generates an individualized treatment plan, which includes physical therapy, acupuncture, medication, and emotional support. It also uses AI algorithms to select and recommend the most appropriate medical institution.

[1556] Output: Generated personalized treatment plan and recommended medical institution information

[1557] Step 6:

[1558] Input: Generated individual treatment plan and recommended medical institution information

[1559] Operation: The user's device displays the treatment plan and recommended medical institution information received from the server on the application's user interface. For example, the following information may be displayed: "Physical therapy and acupuncture treatment are recommended. The nearest recommended medical institution is Medical Institution A. Taking into account the user's emotional state, a relaxation session has also been added."

[1560] Output: Treatment plan and recommended medical institution information displayed on the device

[1561] Step 7:

[1562] Input: Treatment plan and recommended medical institution information displayed on the device

[1563] How it works: The user selects one of the clinics from the list and makes an appointment online. The appointment information is sent from the device to the server and stored in a database.

[1564] Output: Reservation information sent and stored on the server

[1565] Step 8:

[1566] Input: Reservation information sent and stored on the server

[1567] Operation: The server adds treatment progress information received from the clinic to the database for each user. The progress information includes the details of the treatment performed and the next appointment information.

[1568] Output: Progress information added to the database per user

[1569] Step 9:

[1570] Input: Treatment progress information

[1571] How it works: After treatment, the user enters feedback through the application. At the same time, the emotion engine also acquires the user's emotion information and sends it to the server. The feedback includes information about the effectiveness of the treatment and the level of satisfaction.

[1572] Output: Feedback and emotion information sent to the server

[1573] Step 10:

[1574] Input: Feedback and emotion information sent to the server

[1575] How it works: The server analyzes feedback and emotional information using AI algorithms to evaluate the effectiveness of treatment. Based on the analysis results, it improves the existing treatment plan and reflects it in the next treatment.

[1576] Output: Improved treatment plan

[1577] Step 11:

[1578] Input: Improved treatment plans and treatment progress information

[1579] How it works: Users can access the application's "My Page" to check their treatment history and upcoming treatment schedules, allowing them to understand the progress of their treatment in real time and visually confirm the effectiveness of their treatment.

[1580] Output: User's treatment history and next treatment schedule information

[1581] (Application example 2)

[1582] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1583] In modern factories, workers are prone to developing back pain due to long periods of standing and carrying heavy objects, making worker health management important. However, there is a lack of a system that can monitor the health and emotional state of individual workers in real time and provide optimal treatment plans. This can lead to reduced worker productivity and a decrease in safety in the work environment.

[1584] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1585] In this invention, the server includes: [means for storing health information and symptom data received from a user;] [means for using an AI algorithm to analyze the health information and symptom data;] [means for generating an individualized treatment plan based on the analysis results of the AI ​​algorithm;] [means for selecting an optimal treatment clinic based on the individualized treatment plan;] [means for displaying the individualized treatment plan and information on the optimal treatment clinic on a user terminal;] [means for managing reservation information for the treatment clinic;] [means for receiving and managing treatment progress and feedback information;] [means for improving the treatment plan based on the feedback information;] [means for analyzing the user's emotional state using an emotion recognition engine and reflecting it in the treatment plan;] [means installed on a robot terminal used in the work environment and managing worker health information; and [means for checking and responding to worker progress and treatment history in real time.] This makes it possible to monitor workers' health conditions in real time and provide optimal treatment plans, thereby improving worker productivity and safety.

[1586] "Health information received from users" refers to general health data such as age, gender, medical history, etc. provided by individual users.

[1587] "Symptom data" is detailed data such as the location, severity, and duration of pain provided by the user based on their specific health condition.

[1588] "AI Algorithms" are artificial intelligence technologies for analyzing received and stored health information and symptom data.

[1589] An "individualized treatment plan" is a set of treatment processes and methods optimized for each individual user, generated based on the results of analysis by an AI algorithm.

[1590] The "best treatment center" is the medical facility or specialist best suited to treatment, selected based on the individual treatment plan.

[1591] A "user terminal" is an electronic device such as a personal computer or smartphone that displays individual treatment plans and information on the most suitable treatment center.

[1592] "Managing reservation information" means making reservations online with the treatment center of the user's choice, and recording and monitoring the reservation information.

[1593] "Treatment progress status" is data including the details of the treatment that was actually performed and information about the next treatment appointment.

[1594] "Feedback information" is information provided by the user after treatment regarding the effectiveness and satisfaction of the treatment.

[1595] An "emotion recognition engine" is a technology that detects emotions from a user's facial expressions and tone of voice and uses that information for analysis.

[1596] A "robot terminal" is an automated device used in work environments such as factories to manage workers' health information.

[1597] "Real-time monitoring" means being able to instantly access and monitor treatment progress and history.

[1598] This invention provides a system that collects a user's health information and symptom data, analyzes it using an AI algorithm, and proposes and manages an optimal treatment plan. Specific embodiments for implementing this system are described below.

[1599] Entering user information

[1600] Subject: User

[1601] Users access the application from their smartphone or computer and enter their health information and symptom data, such as their age, gender, medical history, location and degree of pain, and duration. At this time, the emotion recognition engine recognizes emotions from the user's facial expressions and tone of voice and transmits them to the system.

[1602] Receiving and storing patient information

[1603] Subject: Server

[1604] The server receives the health information and symptom data submitted by the user, as well as the emotion information received from the emotion recognition engine, and stores them securely in a database.

[1605] Data analysis

[1606] Subject: Server

[1607] The server analyzes the stored data using an AI algorithm. The AI ​​algorithm uses frameworks such as TensorFlow and PyTorch to analyze the user's health condition and symptoms. Furthermore, it adds emotional information received from an emotion recognition engine to the analysis results and selects the optimal treatment based on the user's stress level and emotional state.

[1608] Treatment plan generation

[1609] Subject: Server

[1610] Based on the analysis results, the server generates an individualized treatment plan, which includes specific treatment methods such as physical therapy, acupuncture, and medication. It also considers the user's emotional information and suggests treatment plans that include stress management and psychological support.

[1611] View Treatment Plan

[1612] Subject: User

[1613] The user's device retrieves the generated treatment plan and recommended clinic information from the server and displays them on the application interface. For example, it might say, "Physical therapy and acupuncture are recommended. The nearest recommended clinic is Clinic A. Taking your emotional state into consideration, we've also added a relaxation program."

[1614] Selecting and booking a treatment center

[1615] Subject: User

[1616] The user selects one from the list of clinics displayed and makes a reservation online. The reservation information is sent to the server and stored in a database.

[1617] Monitoring treatment progress

[1618] Subject: Server

[1619] The server receives progress information from the clinic and adds it to the database for each user, continuously updating and managing the progress, including treatment details and next appointment information.

[1620] Receiving Feedback

[1621] Subject: User

[1622] After treatment, users enter feedback into the application, including the effectiveness and satisfaction of the treatment. The emotion recognition engine recognizes the user's emotions from their facial expressions and tone of voice, and sends this along with the feedback data to the server.

[1623] Analyze feedback and refine treatment plans

[1624] Subject: Server

[1625] The server analyzes the received feedback and emotional information to evaluate the effectiveness of the treatment, and improves the treatment plan based on the analysis results, which are then reflected in the next treatment plan.

[1626] Confirmation of treatment effectiveness

[1627] Subject: User

[1628] Users can access the application's "My Page" to check their own treatment history and upcoming treatment schedules, grasp progress in real time, and visualize the effects of treatment.

[1629] Hardware and Software Used

[1630] The system uses smartphones, computers, and robotic devices, and uses MySQL as the database, Microsoft Azure Emotion API as the emotion recognition engine, and frameworks such as TensorFlow and PyTorch for AI data analysis.

[1631] Examples of concrete examples and prompts

[1632] For example, if the system recognizes an emotion such as "tired" from a worker's facial expression, it will input the following prompt sentence into the generative AI model:

[1633] Prompt Sentence Examples

[1634] "Consider how fatigued the worker is and include relaxing stretching techniques in your next treatment plan."

[1635] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1636] Step 1:

[1637] Entering user information

[1638] Subject: User

[1639] Users access the application from their smartphone or computer and enter their health information and symptom data, such as age, gender, medical history, location and degree of pain, and duration. The emotion recognition engine recognizes emotions from the user's facial expressions and tone of voice, and sends that data to the system to complete the input.

[1640] Input: User's health information, symptom data, and emotional data

[1641] Output: The information entered is sent to the system

[1642] Step 2:

[1643] Receiving and storing patient information

[1644] Subject: Server

[1645] The server receives the health and symptom data sent by the user and the emotion information received from the emotion recognition engine, and stores this data in a database using MySQL, which checks the consistency and completeness of the data.

[1646] Input: User's health information, symptom data, emotional data

[1647] Output: Saved data

[1648] Step 3:

[1649] Data analysis

[1650] Subject: Server

[1651] The server analyzes the stored data using AI algorithms. Using TensorFlow and PyTorch, it analyzes health information and symptom data to identify the cause of the problem. It also incorporates emotional information from an emotion recognition engine into the analysis and outputs the optimal treatment plan based on the user's emotional state.

[1652] Input: Health information, symptom data, emotion data

[1653] Output: Analysis results (candidate treatments)

[1654] Step 4:

[1655] Treatment plan generation

[1656] Subject: Server

[1657] The server generates an individualized treatment plan based on the analysis results, which includes specific treatment methods such as physical therapy, acupuncture, and medication, as well as stress management and psychological support, taking into account the user's emotional information.

[1658] Input: Analysis results, emotion information

[1659] Output: Individual treatment plan

[1660] Step 5:

[1661] View Treatment Plan

[1662] Subject: User

[1663] The user's device receives the generated treatment plan and recommended clinic information from the server and displays it on the application interface. The user can then review this information and select the appropriate treatment.

[1664] Input: Treatment plan, recommended clinic information

[1665] Output: Information displayed in the user interface

[1666] Step 6:

[1667] Selecting and booking a treatment center

[1668] Subject: User

[1669] The user selects the most suitable clinic from the displayed list and makes a reservation online. The reservation information is sent to the server and stored in a database.

[1670] Input: List of clinics, user selection

[1671] Output: Saved reservation information

[1672] Step 7:

[1673] Monitoring treatment progress

[1674] Subject: Server

[1675] The server receives progress information from the clinic and adds it to the database for each user, continuously updating and managing the progress status including treatment details and next appointment information.

[1676] Input: Progress information

[1677] Output: Updated user data

[1678] Step 8:

[1679] Receiving Feedback

[1680] Subject: User

[1681] After treatment, the user enters feedback into the application, and the emotion recognition engine extracts emotional information from the user's facial expressions and tone of voice, and all feedback data is sent to the server.

[1682] Input: User feedback, emotional data

[1683] Output: Saved feedback information

[1684] Step 9:

[1685] Analyze feedback and refine treatment plans

[1686] Subject: Server

[1687] The server analyzes the received feedback and emotional information to evaluate the effectiveness of the treatment, and improves the treatment plan based on the analysis results, which are reflected in the next plan generation.

[1688] Input: Feedback information, emotion data

[1689] Output: Improved treatment plan

[1690] Step 10:

[1691] Confirmation of treatment effectiveness

[1692] Subject: User

[1693] Users can access the application's "My Page" to check their own treatment history and upcoming treatment schedules, grasp progress in real time, and visualize the effects of treatment.

[1694] Input: User data

[1695] Output: Real-time display of treatment history and progress

[1696] Examples of concrete examples and prompts

[1697] For example, if the system recognizes an emotion such as "tired" from a worker's facial expression, it will input the following prompt sentence into the generative AI model:

[1698] Prompt Sentence Examples

[1699] "Consider how fatigued the worker is and include relaxing stretching techniques in your next treatment plan."

[1700] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1701] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1702] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1703] [Fourth embodiment]

[1704] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1705] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1706] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1707] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1708] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1709] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1710] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1711] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1712] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1713] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1714] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1715] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1716] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1717] The present invention provides a system for providing information on lower back pain treatment, creating an optimal treatment plan, and managing the progress of treatment. Hereinafter, an embodiment of this system will be described in detail.

[1718] Entering user information

[1719] Subject: User

[1720] Example: A user accesses an application on a smartphone or PC and enters general health information such as age, gender, and medical history, as well as detailed symptom data such as pain location, pain intensity, and duration. This is done through the app's intuitive interface.

[1721] Receiving and analyzing patient information

[1722] Subject: Server

[1723] Example: The server receives health information and symptom data sent by the user and stores it in a database. It then launches an AI algorithm to analyze the received data. The AI ​​analyzes the user's input data to identify the cause of back pain and the best treatment.

[1724] Treatment plan generation

[1725] Subject: Server

[1726] Example: The server generates an individualized treatment plan based on the analysis results. This treatment plan includes specific treatment methods such as physical therapy, acupuncture, and drug therapy. It also recommends the most suitable treatment center from among nearby treatment centers.

[1727] View Treatment Plan

[1728] Subject: Terminal

[1729] Example: The user's device receives the generated treatment plan and recommended clinic information from the server. This information is displayed on the application's user interface so that the user can check it. For example, the user's screen might display the following message: "Physical therapy and acupuncture are recommended. The nearest recommended clinic is Clinic A."

[1730] Selecting and booking a treatment center

[1731] Subject: User

[1732] Example: A user selects one from a list of clinics and makes an appointment online. Once the appointment is completed, the information is sent to the server and stored in a database.

[1733] Monitoring treatment progress

[1734] Subject: Server

[1735] Example: The server receives progress information from the clinic and adds it to the database for each user. Treatment progress information may include, for example, information such as "First physical therapy session completed, next scheduled treatment date."

[1736] Receiving Feedback

[1737] Subject: User

[1738] Example: After treatment, the user provides feedback through the application. For example, they input specific effects such as "pain was reduced after treatment" and send it to the server. The feedback information is used to improve the next treatment plan.

[1739] Data collection and treatment plan refinement

[1740] Subject: Server

[1741] Example: The server aggregates progress information from clinics and feedback from users, and uses an AI algorithm to compile the data. Based on this data, the effectiveness of the treatment plan is evaluated and the model is updated to improve future treatment plans.

[1742] Confirmation of treatment effectiveness

[1743] Subject: User

[1744] Example: Users can access the application's "My Page" to check their own treatment history and upcoming treatment schedules. By understanding progress in real time, the effectiveness of treatment can be visualized.

[1745] Through the above process, the back pain treatment navigation system provides users with the optimal treatment plan and supports them in maximizing the effectiveness of treatment. By linking the user, server, and device, it becomes possible to provide precise treatment tailored to each individual patient.

[1746] The processing flow will be explained below.

[1747] Step 1: Enter your user information

[1748] Subject: User

[1749] Specific behavior:

[1750] The user opens the application on their smartphone or PC.

[1751] Follow the application interface to enter health information such as age, gender, and medical history.

[1752] Enter details of your symptoms (e.g., location of pain, duration of pain, current pain level, etc.).

[1753] Check the information you entered and click the "Submit" button to send the information to the server.

[1754] Step 2: Receiving and storing patient information

[1755] Subject: Server

[1756] Specific behavior:

[1757] Receive health information and symptom data submitted by a user.

[1758] The received data is saved in the database.

[1759] Checks are performed to ensure data completeness and consistency.

[1760] Step 3: Analyze the data

[1761] Subject: Server

[1762] Specific behavior:

[1763] The stored data is analyzed using AI algorithms.

[1764] Recognize patterns in symptoms and identify the source of problems.

[1765] Analysis will be performed based on criteria for selecting the optimal treatment.

[1766] Step 4: Generate a treatment plan

[1767] Subject: Server

[1768] Specific behavior:

[1769] Based on the analysis results, an individual treatment plan is generated.

[1770] The treatment plan will include recommended treatments (e.g., physical therapy, acupuncture, medication).

[1771] The system uses the user's current location information to select a suitable nearby clinic.

[1772] The generated treatment plan and clinic information are stored in a database.

[1773] Step 5: View your treatment plan

[1774] Subject: Terminal

[1775] Specific behavior:

[1776] The user's terminal obtains the treatment plan and clinic information from the server.

[1777] The application interface displays treatment plans and recommended clinics.

[1778] It provides users with detailed information about their treatment plan and a list of recommended treatment centers.

[1779] Step 6: Select a clinic and book an appointment

[1780] Subject: User

[1781] Specific behavior:

[1782] The user selects one of the displayed clinics.

[1783] Check the details and available appointment times for the clinic you selected.

[1784] Select your desired date and time and confirm your reservation.

[1785] The reservation information is sent to the server and stored in a database.

[1786] Step 7: Monitor your treatment progress

[1787] Subject: Server

[1788] Specific behavior:

[1789] Receive treatment progress updates from the clinic.

[1790] The progress status includes the details of the treatment that was actually performed and the next treatment appointment information.

[1791] The received progress information is added to the patient database.

[1792] Continually update and manage your medical history.

[1793] Step 8: Receiving feedback

[1794] Subject: User

[1795] Specific behavior:

[1796] The user accesses the application to enter feedback after treatment.

[1797] Please fill in the feedback form to describe the effectiveness and satisfaction of the treatment.

[1798] The feedback is checked and sent to the server.

[1799] Step 9: Analyze feedback and refine treatment plan

[1800] Subject: Server

[1801] Specific behavior:

[1802] The received feedback information is stored in a database.

[1803] The feedback data is analyzed using an AI algorithm to evaluate the effectiveness of the treatment.

[1804] The treatment plan will be improved based on the analysis results.

[1805] The improved treatment plan is reflected in the next plan generation.

[1806] Step 10: Check the effectiveness of the treatment

[1807] Subject: User

[1808] Specific behavior:

[1809] The user accesses the application's "My Page."

[1810] Review your treatment history, progress, and upcoming treatment schedule.

[1811] Check the effectiveness of treatment in real time and prepare for the next treatment.

[1812] Through this series of processes, the lower back pain treatment navigation system can provide the user with an optimal treatment plan, manage the progress of treatment, and confirm its effectiveness.

[1813] Example 1

[1814] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1815] In the treatment of lower back pain, existing systems have difficulty providing optimal treatment plans based on individual patients' symptoms and progress. Furthermore, management of treatment progress and collection and analysis of feedback are often done manually, preventing efficient improvements to treatment plans. This makes it difficult to quickly and effectively provide treatment methods appropriate for each patient.

[1816] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1817] In this invention, the server includes: [means for storing health information and symptom data received from a user;] [means for using a generative AI model to analyze the health information and symptom data; and] [means for generating an individual treatment plan based on the analysis results of the generative AI model.] This makes it possible [to automatically generate and refine an optimal treatment plan based on the patient's individual symptoms and progress, and provide effective treatment for lower back pain].

[1818] "Health information" refers to data that indicates the patient's overall health condition, such as the patient's age, sex, medical history, etc.

[1819] "Symptom data" refers to data that indicates specific symptoms such as the location of pain felt by the patient, the degree of pain, and the duration of pain.

[1820] A "generative AI model" is an algorithm that uses artificial intelligence to analyze received health information and symptom data and generate an optimal treatment plan.

[1821] A "treatment plan" is a plan that includes specific treatment methods such as physical therapy, acupuncture, and drug therapy that the generative AI model proposes based on the analysis results.

[1822] The "optimal medical facility" is a medical facility such as a clinic or hospital that the generative AI model recommends based on the analysis results.

[1823] A "user terminal" is a device used by a user, such as a smartphone or PC.

[1824] "Reservation information" is information regarding reservations for treatment at a medical facility selected by the user.

[1825] "Treatment progress status" is information indicating the progress status of treatment currently in progress.

[1826] "Feedback information" is data indicating opinions and impressions provided by the user regarding the effectiveness of treatment and the state of improvement.

[1827] "Updating the generative AI model" refers to the operation of retraining the generative AI model to improve the next treatment plan based on the received treatment progress and feedback information.

[1828] This invention is a system for providing information on lower back pain treatment, creating optimal treatment plans, and managing treatment progress. This system allows users to input their own health information and symptom data, which is then analyzed by a server, which then generates an optimal treatment plan and displays it on the user's device. It also maximizes the effectiveness of treatment by allowing users to select and book treatment centers, manage treatment progress, and collect feedback.

[1829] Hardware and software used

[1830] Server: A computing environment equipped with a high-performance processor and large memory capacity

[1831] Database: A relational database such as MySQL or PostgreSQL

[1832] Generative AI models: Machine learning frameworks such as Python and TensorFlow

[1833] User devices: smartphones, PCs

[1834] Application: Web or mobile application

[1835] Specific system operations and procedures

[1836] Users access the application using a smartphone or PC. They enter their health information, such as their age, gender, medical history, location and severity of pain, and duration, into the application's input form. This information is sent to the server by pressing the send button.

[1837] The server receives the health information and symptom data sent by the user and stores it in a database. The stored data is analyzed by an AI algorithm using Python and TensorFlow. The AI ​​algorithm identifies the cause of back pain and the optimal treatment based on the user's input data.

[1838] Based on the analysis results, the server generates an individualized treatment plan, which includes specific treatment methods such as physical therapy, acupuncture, and drug therapy, and also recommends appropriate nearby medical facilities. The generated treatment plan is sent from the server to the user's device and displayed on the application interface.

[1839] The user selects one from the list of clinics displayed and makes a reservation online. The reservation information is sent to the server and stored in a database.

[1840] The server receives progress information from the clinic and adds it to the database for each user. Treatment progress information can be checked in real time on the "My Page" page within the application.

[1841] After treatment, users provide feedback on the effectiveness of the treatment through the application. This feedback is sent to the server, which uses it to refine the next treatment plan. The server then retrains and updates the generative AI model based on the collected treatment progress and feedback information.

[1842] Specific examples

[1843] The user enters the information "I have a sharp pain in the right side of my lower back that has lasted for more than a week" into the input form and presses the submit button. The server stores this information in a database and analyzes it using an AI algorithm. The AI ​​identifies the condition as "lower back pain caused by long hours of desk work," recommends physical therapy and acupuncture, and finds that the nearest clinic B is the most suitable. This information is displayed on the user's device, and the user selects clinic B and makes an online reservation.

[1844] Prompt Sentence Examples

[1845] "Enter information about your back pain symptoms and generate an optimal treatment plan."

[1846] "The received data is analyzed and the optimal back pain treatment plan is proposed to the user."

[1847] Through the above process, the system provides users with the optimal treatment plan and supports them in maximizing the effectiveness of treatment. By linking users, servers, and devices, it becomes possible to provide precise treatment tailored to each individual patient.

[1848] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1849] Step 1:

[1850] Users access the application using a smartphone or PC, enter their health information such as age, gender, medical history, location and severity of pain, and duration into the application's input form, and then press the submit button.

[1851] Input: User health information and symptom data

[1852] Output: Health information and symptom data sent to the server

[1853] Step 2:

[1854] The server receives the health information and symptom data submitted by the user and stores it in a database.

[1855] Input: User-submitted health and symptom data

[1856] Output: Health information and symptom data stored in a database

[1857] Specific operation: The server stores the received data in a "patient database."

[1858] Step 3:

[1859] The server accesses health information and symptom data stored in the database and runs a generative AI model using Python and TensorFlow to analyze it. The generative AI model uses the user's data to identify the cause of their back pain and the optimal treatment.

[1860] Input: Health information and symptom data stored in a database

[1861] Output: Analysis of causes of lower back pain and optimal treatment

[1862] Specific operation: The generative AI model is activated and analysis is performed. For example, it determines that "this patient's back pain is caused by long hours of desk work."

[1863] Step 4:

[1864] Based on the analysis results, the server generates a personalized treatment plan, which includes specific treatment methods such as physical therapy, acupuncture, and medication, and also recommends suitable nearby medical facilities.

[1865] Input: Analysis results

[1866] Output: Individualized treatment plan and recommended medical facility information

[1867] Specific operation: The server creates a treatment plan such as "recommending physical therapy and acupuncture treatment, with the nearest medical facility B being the best."

[1868] Step 5:

[1869] The user's device retrieves the generated treatment plan and recommended medical facility information from the server and displays it on the application interface. The user interface is designed to be easy to read, allowing users to easily check the information.

[1870] Input: Treatment plan and recommended medical facility information sent from the server

[1871] Output: Treatment plan and recommended medical facility information displayed in the application

[1872] Specific operation: The device screen displays the message, "Physical therapy and acupuncture are recommended. The nearest medical facility is Facility B."

[1873] Step 6:

[1874] The user selects one from the list of medical facilities displayed and makes an appointment online. Once the appointment is completed, the information is sent to the server and stored in a database.

[1875] Input: Information about the medical facility and appointment date and time selected by the user

[1876] Output: Reservation information sent to the server and stored in the database

[1877] Specific action: The user "selects medical facility B and confirms the appointment at 2:00 PM on December 1st."

[1878] Step 7:

[1879] The server receives progress information from the medical facility and adds it to the database for each user. Treatment progress information includes specific details such as the next scheduled treatment date.

[1880] Input: Progress information from medical facilities

[1881] Output: Progress information added to the database

[1882] Specific operation: The server records the information "The first physical therapy session has ended, and the next session will be on December 8th" in the database.

[1883] Step 8:

[1884] After treatment, users provide feedback through the application, including specific details about the effectiveness of the treatment and the progress of the treatment. The feedback information is sent to the server and used to improve the next treatment plan.

[1885] Input: User feedback information on the effectiveness of the treatment

[1886] Output: Feedback information sent to the server

[1887] Specific action: The user enters feedback such as "My pain has significantly decreased after treatment" and presses the submit button.

[1888] Step 9:

[1889] The server aggregates progress information from clinics and feedback from users, and uses AI algorithms to refine the next treatment plan. Based on the aggregated results, the generative AI model is updated to optimize the effectiveness of treatment.

[1890] Input: Treatment progress information and feedback information

[1891] Output: Improved generative AI model and next treatment plan

[1892] Specific operation: The server retrains the generative AI model based on the conclusion that "combining physical therapy and acupuncture is effective."

[1893] Step 10:

[1894] Users can access the application's "My Page" to check their own treatment history and upcoming treatment schedules. The treatment history includes detailed progress information, allowing users to intuitively check the effectiveness of their treatment.

[1895] Input: User's treatment history and next treatment schedule information

[1896] Output: Treatment history and treatment schedule information displayed on the personal page within the application

[1897] Specific operation: The user checks the information on his / her personal page that "the first physical therapy session has ended and the next session is scheduled for December 8th."

[1898] (Application example 1)

[1899] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1900] In conventional lower back pain treatment, it has been difficult to quickly present an optimal treatment plan tailored to individual symptoms and the user's specific conditions, and to monitor the progress of the plan in real time. Furthermore, there has been a lack of systems in place to efficiently manage treatment clinic appointments and provide feedback. The present invention aims to solve these problems and maximize the effectiveness of lower back pain treatment.

[1901] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1902] In this invention, the server includes means for storing health information and symptom data received from a user, means for using an AI algorithm to analyze the health information and symptom data, means for generating an individualized treatment plan based on the analysis results of the AI ​​algorithm, means for selecting an optimal treatment clinic based on the individualized treatment plan, means for displaying the individualized treatment plan and information on the optimal treatment clinic on a user terminal, means for managing reservation information for the treatment clinic, means for receiving and managing treatment progress and feedback information, means for improving the treatment plan based on the feedback information, means for providing an interface for making reservations and managing progress for osteopathic clinics using a user terminal, and means for users to input and check data using a smartphone. This enables the provision of an optimal treatment plan for each user, real-time confirmation of treatment progress, efficient reservation management, and effective improvement of the treatment plan based on feedback.

[1903] A "user terminal" is a digital device used by each user to input information and review treatment plans.

[1904] "Health information" refers to data relating to the user's general health, such as age, gender, medical history, etc.

[1905] "Symptom data" is information about specific symptoms experienced by the user, such as the location of pain, the degree of pain, and the duration of pain.

[1906] "AI algorithm" is an artificial intelligence technology that analyzes collected health information and symptom data to generate optimal treatment plans.

[1907] A "personalized treatment plan" is a detailed plan of treatment that is generated based on a user's specific health information and symptom data.

[1908] The "optimal treatment center" is a medical facility that can provide the most appropriate treatment based on the user's treatment plan.

[1909] The "display means" is an interface for visually presenting treatment plans and clinic information on a user terminal.

[1910] The "means for managing reservation information" is a function that manages the reservation status of the treatment center selected by the user and makes changes or cancellations as necessary.

[1911] "Treatment progress status" is information indicating the stage of treatment.

[1912] "Feedback information" refers to opinions and evaluations regarding the effectiveness and satisfaction of a treatment provided by a user after the treatment.

[1913] "Treatment plan refinement" is the process of updating an existing treatment plan to make it more effective based on collected feedback information.

[1914] The "interface" refers to the screens and menus that users operate, and is the part that provides functions such as treatment reservations and progress checks.

[1915] A system for effectively implementing this invention is preferably constructed using a user terminal, a server, and an AI algorithm. Specific embodiments are described below.

[1916] First, the user accesses the application from a smartphone or other device. The user inputs health information such as age, gender, and medical history, as well as symptom data such as the location, severity, and duration of pain. This data is collected via an intuitive user interface and sent to the server.

[1917] The server stores the received health information and symptom data in a database. It then uses AI algorithms to analyze this information and generate an optimal treatment plan for each individual user. This treatment plan may include recommendations for physical therapy, acupuncture, medication, and more. The AI ​​algorithms can be, for example, Python's TensorFlow or SciKit-Learn.

[1918] The server selects the most suitable clinic in the user's area based on the generated treatment plan. The treatment plan is then sent to the user's device along with information about the selected clinic. The user can then review this information and make a reservation at the recommended clinic through the application interface.

[1919] Once treatment begins at the clinic, the user's treatment progress is sent to the server in real time. The user can check their treatment progress from their smartphone. When the user provides feedback after treatment, that information is also sent to the server and stored in the database.

[1920] The server analyzes this feedback information and uses it to improve future treatment plans. By updating the AI ​​algorithm, it is possible to provide increasingly effective treatment plans.

[1921] For example, the following prompt sentence is used as the user's input:

[1922] "30-year-old male with unremarkable health history. Presenting with severe pain in the lower back for two weeks."

[1923] "My back pain has significantly decreased after treatment."

[1924] "The physical therapy at the clinic I booked was effective."

[1925] This allows users to easily and quickly input their health information and select the optimal treatment plan and clinic, and the treatment plan is continuously improved based on feedback, maximizing the effectiveness of treatment.

[1926] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1927] Step 1:

[1928] Users access the application from their smartphones and input their health information and symptom data. The input data includes age, gender, medical history, pain location, pain severity, and duration. This data is collected via an intuitive user interface and sent to the server. The input data is sent from the user's device to the server as initial data.

[1929] Step 2:

[1930] The server stores the health information and symptom data received from the user in a database. During this storage process, the received data is formatted to fit the database format. Specifically, the data is processed so that each item is stored appropriately in the database table. From the health information and symptom data received as input, user information in database format is output.

[1931] Step 3:

[1932] The server passes the stored health information and symptom data to an AI algorithm for analysis. The AI ​​algorithm used is implemented using Python's TensorFlow and SciKit-Learn, and analyzes the user's data to generate an optimal treatment plan. This analysis process uses pattern recognition and predictive models to identify treatment methods based on the input data. The treatment plan generated based on the analyzed data is output.

[1933] Step 4:

[1934] The server selects the most suitable clinic in the user's area based on the generated individual treatment plan. In this selection process, it searches a database of clinics for geographically nearby clinics and determines the most suitable clinic based on each clinic's specialty and evaluation information. The output is a list of the selected optimal clinics.

[1935] Step 5:

[1936] The server sends the individual treatment plan and information on the most suitable treatment center to the user's device. The details of the treatment plan and information on the recommended treatment center are displayed on the user's smartphone. The user can check this information on the screen. The displayed treatment plan and treatment center information are output.

[1937] Step 6:

[1938] After checking the displayed clinic information, the user uses the application interface to make a reservation at the clinic of their choice. The reservation information is sent to the server via the user interface, and the server stores this information in a database and notifies the clinic. The reservation information is entered, and a notification of reservation completion is output.

[1939] Step 7:

[1940] Once treatment begins, treatment progress information is sent from the treatment clinic to the server. This progress information includes the treatment status and the next scheduled treatment date. The server adds and updates this information in real time to the user's database. The entered treatment progress information is output as updated database information.

[1941] Step 8:

[1942] After treatment, users provide feedback through the application. The feedback information includes the user's opinions on the effectiveness of treatment and satisfaction. The feedback information is sent to the server, stored in a database, and used to improve future treatment plans. The input feedback information is output as data for improving treatment plans.

[1943] Step 9:

[1944] The server analyzes the received treatment progress information and user feedback information, and improves future treatment plans based on the AI ​​algorithm model. This ensures effective treatment for each user. An improved treatment plan is output based on the analyzed feedback information.

[1945] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1946] This invention is a system that provides information on lower back pain treatment, creates an optimal treatment plan, and manages the progress of treatment, and also combines it with an emotion engine that recognizes the user's emotions. Below, we will explain in detail the embodiments of this system.

[1947] Entering user information

[1948] Subject: User

[1949] Example: A user accesses the application from a smartphone or PC and enters general health information such as their age, gender, and medical history. They also enter detailed symptom data such as the location of pain, its severity, and duration. At this time, the emotion engine recognizes emotions from the user's facial expressions and tone of voice and transfers them to the system.

[1950] Receiving and storing patient information

[1951] Subject: Server

[1952] Example: The server receives health and symptom data submitted by the user, as well as the user's emotion information received from the emotion engine, and stores them in a database. It performs checks to ensure the data is complete and consistent.

[1953] Data analysis

[1954] Subject: Server

[1955] Example: The server analyzes the stored data using an AI algorithm. The AI ​​algorithm identifies the cause of the problem based on the user's health information and symptom data. Furthermore, it adds emotional information from the emotion engine to the analysis results and selects the optimal treatment based on the user's stress level and emotional state.

[1956] Treatment plan generation

[1957] Subject: Server

[1958] Example: The server generates an individualized treatment plan based on the analysis results. This treatment plan includes specific treatment methods such as physical therapy, acupuncture, and drug therapy. It can also incorporate a plan to provide psychological support by taking into account the user's emotional information. It can also select the most suitable treatment center from among nearby treatment centers.

[1959] View Treatment Plan

[1960] Subject: Terminal

[1961] Example: The user's device receives the generated treatment plan and recommended clinic information from the server. This information is displayed on the application's user interface for the user to review. For example, the user's screen might display, "Physical therapy and acupuncture are recommended. The nearest recommended clinic is Clinic A. Taking your emotional state into consideration, we've also added a relaxation session."

[1962] Selecting and booking a treatment center

[1963] Subject: User

[1964] Example: A user selects one from a list of clinics and makes an appointment online. Once the appointment is completed, the information is sent to the server and stored in a database.

[1965] Monitoring treatment progress

[1966] Subject: Server

[1967] Example: The server receives progress information from the clinic and adds it to the database for each user. The treatment progress information includes the details of the actual treatment and the next treatment appointment information. The treatment history is continuously updated and managed.

[1968] Receiving Feedback

[1969] Subject: User

[1970] Example: A user accesses an application to enter feedback after treatment. The user writes about the effectiveness of the treatment and their satisfaction in the feedback form. The emotion engine also obtains the user's emotion information at this point, and sends it to the server along with the feedback information.

[1971] Analyze feedback and refine treatment plans

[1972] Subject: Server

[1973] Example: The server stores the feedback and emotional information received from the emotion engine in a database. The feedback data is analyzed using an AI algorithm to evaluate the effectiveness of treatment. The treatment plan is improved based on the analysis results. The improved treatment plan is reflected in the next plan generation.

[1974] Confirmation of treatment effectiveness

[1975] Subject: User

[1976] Example: Users can access the application's "My Page" to check their own treatment history and upcoming treatment schedules. By understanding progress in real time, the effectiveness of treatment can be visualized.

[1977] Through this series of processes, the low back pain treatment navigation system can provide the user with an optimal treatment plan, manage the progress of treatment, and confirm its effectiveness. Furthermore, by combining it with an emotion engine, it becomes possible to provide more comprehensive treatment support that takes into account the user's emotional state.

[1978] The processing flow will be explained below.

[1979] Step 1: Enter your user information

[1980] Subject: User

[1981] Specific behavior:

[1982] The user opens the application on their smartphone or PC.

[1983] Follow the application interface to enter health information such as age, gender, and medical history.

[1984] Enter details of your symptoms (e.g., location of pain, duration of pain, current pain level, etc.).

[1985] The emotion engine analyzes the user's facial expressions and tone of voice in real time and records emotional information.

[1986] Check the input and emotion information, then click the "Submit" button to send the information to the server.

[1987] Step 2: Receiving and storing patient information

[1988] Subject: Server

[1989] Specific behavior:

[1990] Health information and symptom data submitted by the user and emotion information from the emotion engine are received.

[1991] The received data is saved in the database.

[1992] Checks are performed to ensure data completeness and consistency.

[1993] Step 3: Analyze the data

[1994] Subject: Server

[1995] Specific behavior:

[1996] The stored data is analyzed using AI algorithms.

[1997] Use health and symptom data to identify the cause of the problem.

[1998] Emotional information from the emotion engine is added to the analysis results, and a treatment method is selected taking into account the user's stress level and emotional state.

[1999] Step 4: Generate a treatment plan

[2000] Subject: Server

[2001] Specific behavior:

[2002] Based on the analysis results, an individual treatment plan is generated.

[2003] The treatment plan will include recommended treatments (e.g., physical therapy, acupuncture, medication).

[2004] Taking into account the user's emotional information, a plan is incorporated that also includes psychological support.

[2005] Select the most suitable treatment center from nearby treatment centers.

[2006] The generated treatment plan and clinic information are stored in a database.

[2007] Step 5: View your treatment plan

[2008] Subject: Terminal

[2009] Specific behavior:

[2010] The user's terminal obtains the treatment plan and clinic information from the server.

[2011] The application interface displays treatment plans and recommended clinics.

[2012] It provides users with detailed information about their treatment plan and a list of recommended treatment centers.

[2013] Step 6: Select a clinic and book an appointment

[2014] Subject: User

[2015] Specific behavior:

[2016] The user selects one from the displayed list of clinics.

[2017] Check the details and available appointment times for the clinic you selected.

[2018] Select the date and time you want and confirm your reservation.

[2019] The reservation information is sent to the server and stored in a database.

[2020] Step 7: Monitor your treatment progress

[2021] Subject: Server

[2022] Specific behavior:

[2023] Receive progress updates from the clinic.

[2024] The progress status includes the actual treatment performed and the next treatment appointment information.

[2025] The received progress information is added to the patient database.

[2026] Continually update and manage your medical history.

[2027] Step 8: Receiving feedback

[2028] Subject: User

[2029] Specific behavior:

[2030] The user accesses the application to enter feedback after treatment.

[2031] Please fill in the feedback form to describe the effectiveness and satisfaction of the treatment.

[2032] The emotion engine also analyzes the user's facial expressions and voice and records emotional information when sending feedback.

[2033] The feedback content and emotion information are checked and sent to the server.

[2034] Step 9: Analyze feedback and refine treatment plan

[2035] Subject: Server

[2036] Specific behavior:

[2037] The received feedback information and emotion information are stored in a database.

[2038] Feedback data and emotional information are analyzed using AI algorithms to evaluate the effectiveness of treatment.

[2039] The treatment plan will be improved based on the analysis results.

[2040] The improved treatment plan is reflected in the next plan generation.

[2041] Step 10: Check the effectiveness of the treatment

[2042] Subject: User

[2043] Specific behavior:

[2044] The user accesses the application's "My Page."

[2045] Review your treatment history, progress, and upcoming treatment schedule.

[2046] Check the effectiveness of treatment in real time and prepare for the next treatment.

[2047] This processing flow enables the low back pain treatment navigation system to provide users with an optimal treatment plan, manage the progress of treatment, and confirm its effectiveness. Furthermore, by combining it with an emotion engine, comprehensive treatment support that takes into account the user's emotional state can be realized.

[2048] Example 2

[2049] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2050] A current challenge in treating lower back pain is the difficulty of providing an optimal treatment plan by evaluating each patient's symptoms and emotional state in detail. In particular, emotional information is not reflected in the treatment plan, making it difficult to grasp the patient's mental stress and achieving comprehensive treatment results. Furthermore, treatment progress and feedback information are not managed in real time, making efficient treatment follow-up difficult.

[2051] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[2052] In this invention, the server includes: [means for storing health information, symptom data, and emotional information received from a user;] [means for using an AI algorithm to analyze the health information, symptom data, and emotional information;] [means for generating an individual treatment plan based on the analysis results of the AI ​​algorithm;] [means for selecting an optimal medical institution based on the individual treatment plan;] [means for displaying the individual treatment plan and information on the optimal medical institution on a user terminal;] [means for managing reservation information for the medical institution;] [means for receiving and managing treatment progress and feedback information; and [means for improving the treatment plan based on the feedback information]. This makes it possible to analyze each patient's health information and emotional state in detail, provide an optimal treatment plan, and manage progress information and feedback in real time.

[2053] "Health information" is data relating to the user's overall health, such as the user's age, gender, medical history, and current health condition.

[2054] "Symptom data" refers to information about specific symptoms reported by the user, such as the location of pain, the degree of pain, and the duration of pain.

[2055] "Emotion information" is data on the emotional state of the user based on facial expressions and tone of voice obtained by the emotion engine.

[2056] An "AI algorithm" is a computational method that uses artificial intelligence technologies such as machine learning and deep learning to analyze data and derive results.

[2057] A "treatment plan" is a proposal for an individual treatment method created based on the analysis results, and includes specific treatment methods such as physical therapy, acupuncture, and drug therapy.

[2058] "Medical institution" refers to a facility such as a hospital, clinic, or doctor's office that provides treatment to users.

[2059] A "user terminal" is a device used by a user, such as a smartphone or a personal computer.

[2060] "Reservation information" is data related to a reservation for treatment at a medical institution selected by the user.

[2061] "Progress information" is information indicating the stage to which treatment has progressed, and includes specific treatment details and information on the next treatment appointment.

[2062] "Feedback information" is information provided by the user after treatment regarding the effectiveness and satisfaction of the treatment.

[2063] MODE FOR CARRYING OUT THE INVENTION

[2064] System Overview

[2065] This invention is a system that provides information on lower back pain treatment, creates optimal treatment plans, and manages treatment progress. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it provides comprehensive treatment support that takes into account the user's emotional state. The system consists of a server, a user terminal, and an emotion engine, and the server, acting as a central processing unit, performs data analysis using an AI algorithm.

[2066] System configuration

[2067] Server: Stores and analyzes data, generates treatment plans, and manages progress information. Specific software includes machine learning models and data analysis tools for implementing AI algorithms.

[2068] User terminal: A device such as a smartphone or PC that is used by users to input information and check treatment plans.

[2069] Emotion engine: Has the function of analyzing the user's facial expressions and tone of voice to obtain emotional information.

[2070] Processing flow

[2071] Entering user information

[2072] Users access the application from their smartphone or PC and enter specific health information such as their age, gender, medical history, location and degree of pain, and duration. The emotion engine analyzes the user's facial expressions and tone of voice to obtain emotional information.

[2073] Sending user information

[2074] The device sends the entered health information, symptom data, and emotional information to a server, securely using the SSL / TLS protocol.

[2075] Receiving and storing patient information

[2076] The server receives the health, symptom, and emotion information sent by the device and stores it in a database, checking the data for completeness and consistency and backing it up for redundancy if necessary.

[2077] Data analysis

[2078] The server analyzes the stored data with AI algorithms, using machine learning models and deep learning to identify the cause of the problem based on the user's health information and symptom data, and evaluates stress levels and emotional state by taking emotional information into account.

[2079] Treatment plan generation

[2080] Based on the analysis results, the server generates a treatment plan tailored to each individual user. This plan includes treatment methods such as physical therapy, acupuncture, and medication. It also provides mental support based on emotional information. It also selects and recommends the most appropriate medical institution.

[2081] View Treatment Plan

[2082] The user device receives the treatment plan and information on recommended medical institutions from the server and displays it on the application's user interface. For example, it may display information such as, "Physical therapy and acupuncture treatment are recommended. The nearest recommended medical institution is Medical Institution A. Taking into account the user's emotional state, a relaxation session has also been added."

[2083] Selecting and booking a treatment center

[2084] The user selects one from the list of clinics displayed and makes a reservation online. The reservation information is sent to the server and stored in a database.

[2085] Monitoring treatment progress

[2086] The server receives treatment progress information sent from the treatment center and adds it to the database for each user. The progress information is updated in real time and next treatment appointment information is also managed.

[2087] Receiving Feedback

[2088] After treatment, the user enters feedback via the application, including information about the effectiveness of the treatment and their satisfaction. The emotion engine also acquires emotion information at this point and sends it to the server.

[2089] Analyze feedback and refine treatment plans

[2090] The server uses an AI algorithm to analyze the feedback and emotional information, evaluate the effectiveness of the treatment, and improve the treatment plan based on the analysis results, which will be reflected in the next treatment.

[2091] Confirmation of treatment effectiveness

[2092] Users can access the application's "My Page" to check their treatment history and next treatment schedule, which allows them to understand the progress of their treatment in real time and visualize the effects of their treatment.

[2093] Examples of prompt statements

[2094] Here is an example prompt:

[2095] You are using the lower back pain treatment navigation system. First, enter your health information, such as your age, gender, medical history, location and severity of your pain, and duration. Next, check the treatment plan and list of recommended clinics provided by the system, select your preferred clinic, and make an appointment. After treatment, you enter your feedback into the system, and the emotion engine evaluates your emotional state. This will further improve the treatment plan.

[2096] Through this series of processes, the system can provide the user with an optimal treatment plan, manage progress, and check effectiveness.In addition, by utilizing the emotion engine, it can also provide comprehensive treatment support that takes emotional states into account.

[2097] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2098] Step 1:

[2099] Input: Health information such as age, gender, medical history, location of pain, degree, duration, and user's emotional information

[2100] How it works: Users access the application from their smartphone or PC and enter health information such as age, gender, medical history, location of pain, degree, duration, etc. At the same time, the emotion engine analyzes the user's facial expressions and tone of voice to obtain emotional information.

[2101] Output: Obtained health information, symptom data and emotional information

[2102] Step 2:

[2103] Input: Acquired health information, symptom data and emotional information

[2104] How it works: The device sends the entered health information, symptom data, and emotional information to the server. Data transmission is secure using the SSL / TLS protocol.

[2105] Output: Health information, symptom data and emotional information sent to the server

[2106] Step 3:

[2107] Input: Health information, symptom data and emotional information sent to the server

[2108] Operation: The server receives the information sent from the device and stores it in the system's database, checking the data for completeness and consistency and backing it up if necessary.

[2109] Output: Health information, symptom data and emotional information stored in a database

[2110] Step 4:

[2111] Input: Health information, symptom data and emotional information stored in a database

[2112] How it works: The server analyzes the stored data with AI algorithms, which use machine learning models and deep learning to identify the cause of health issues based on the user's health information and symptom data, and evaluate stress levels and emotional states based on emotional information.

[2113] Output: Causes of health problems, stress levels, and emotional states as analysis results

[2114] Step 5:

[2115] Input: Causes of health problems as analysis results, stress levels, and emotional states

[2116] How it works: Based on the analysis results, the server generates an individualized treatment plan, which includes physical therapy, acupuncture, medication, and emotional support. It also uses AI algorithms to select and recommend the most appropriate medical institution.

[2117] Output: Generated personalized treatment plan and recommended medical institution information

[2118] Step 6:

[2119] Input: Generated individual treatment plan and recommended medical institution information

[2120] Operation: The user's device displays the treatment plan and recommended medical institution information received from the server on the application's user interface. For example, the following information may be displayed: "Physical therapy and acupuncture treatment are recommended. The nearest recommended medical institution is Medical Institution A. Taking into account the user's emotional state, a relaxation session has also been added."

[2121] Output: Treatment plan and recommended medical institution information displayed on the device

[2122] Step 7:

[2123] Input: Treatment plan and recommended medical institution information displayed on the device

[2124] How it works: The user selects one of the clinics from the list and makes an appointment online. The appointment information is sent from the device to the server and stored in a database.

[2125] Output: Reservation information sent and stored on the server

[2126] Step 8:

[2127] Input: Reservation information sent and stored on the server

[2128] Operation: The server adds treatment progress information received from the clinic to the database for each user. The progress information includes the details of the treatment performed and the next appointment information.

[2129] Output: Progress information added to the database per user

[2130] Step 9:

[2131] Input: Treatment progress information

[2132] How it works: After treatment, the user enters feedback through the application. At the same time, the emotion engine also acquires the user's emotion information and sends it to the server. The feedback includes information about the effectiveness of the treatment and the level of satisfaction.

[2133] Output: Feedback and emotion information sent to the server

[2134] Step 10:

[2135] Input: Feedback and emotion information sent to the server

[2136] How it works: The server analyzes feedback and emotional information using AI algorithms to evaluate the effectiveness of treatment. Based on the analysis results, it improves the existing treatment plan and reflects it in the next treatment.

[2137] Output: Improved treatment plan

[2138] Step 11:

[2139] Input: Improved treatment plans and treatment progress information

[2140] How it works: Users can access the application's "My Page" to check their treatment history and upcoming treatment schedules, allowing them to understand the progress of their treatment in real time and visually confirm the effectiveness of their treatment.

[2141] Output: User's treatment history and next treatment schedule information

[2142] (Application example 2)

[2143] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2144] In modern factories, workers are prone to developing back pain due to long periods of standing and carrying heavy objects, making worker health management important. However, there is a lack of a system that can monitor the health and emotional state of individual workers in real time and provide optimal treatment plans. This can lead to reduced worker productivity and a decrease in safety in the work environment.

[2145] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[2146] In this invention, the server includes: [means for storing health information and symptom data received from a user;] [means for using an AI algorithm to analyze the health information and symptom data;] [means for generating an individualized treatment plan based on the analysis results of the AI ​​algorithm;] [means for selecting an optimal treatment clinic based on the individualized treatment plan;] [means for displaying the individualized treatment plan and information on the optimal treatment clinic on a user terminal;] [means for managing reservation information for the treatment clinic;] [means for receiving and managing treatment progress and feedback information;] [means for improving the treatment plan based on the feedback information;] [means for analyzing the user's emotional state using an emotion recognition engine and reflecting it in the treatment plan;] [means installed on a robot terminal used in the work environment and managing worker health information; and [means for checking and responding to worker progress and treatment history in real time.] This makes it possible to monitor workers' health conditions in real time and provide optimal treatment plans, thereby improving worker productivity and safety.

[2147] "Health information received from users" refers to general health data such as age, gender, medical history, etc. provided by individual users.

[2148] "Symptom data" is detailed data such as the location, severity, and duration of pain provided by the user based on their specific health condition.

[2149] "AI Algorithms" are artificial intelligence technologies for analyzing received and st...

Claims

1. means for storing health information and symptom data received from a user; a means for using an AI algorithm to analyze the health information and symptom data; A means for generating an individual treatment plan based on the analysis results of the AI ​​algorithm; A means for selecting an optimal treatment center based on the individual treatment plan; a means for displaying the individual treatment plan and information on the most suitable treatment center on a user terminal; a means for managing reservation information of the treatment center; A means of receiving and managing treatment progress and feedback information; A system comprising means for improving the treatment plan based on said feedback information.

2. The system of claim 1 , wherein the generation of the treatment plan includes one or more of physical therapy, acupuncture, and drug therapy.

3. The system of claim 1 , which provides an interface for viewing the treatment progress and feedback information in real time.

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