system

Abstract

To provide a system that enables patients to quickly and efficiently obtain the optimal treatment plan for themselves and easily find an appropriate treatment facility. [Solution] A system including an input means for inputting patient symptom information, a receiving means for receiving the patient symptom information input from the input means, an analysis means for analyzing the patient symptom information received by the receiving means, a generation means for generating an individual treatment plan based on the analysis results obtained by the analysis means, a notification means for notifying the patient of the treatment plan generated by the generation means, a selection means for selecting an appropriate treatment facility based on the treatment plan notified by the notification means, a reservation means for making a reservation at the treatment facility selected by the selection means, and an update means for receiving treatment progress information from the patient and updating the treatment plan.

Description

[Technical Field]

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

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

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

[0004] Conventional back pain treatments require a great deal of time and effort for patients to obtain an appropriate treatment plan tailored to their symptoms. Other issues include difficulty in finding an appropriate treatment facility and in monitoring and adjusting treatment progress in real time. Furthermore, there is a lack of mechanisms for evaluating the effectiveness of treatment and continuously optimizing individual treatment plans. As a result, there is a high possibility that improvement in patients' symptoms will be delayed, resulting in issues such as insufficient treatment effectiveness. [Means for solving the problem]

[0005] The present invention provides a system including an input means for inputting a patient's symptom information, a receiving means for receiving the input patient's symptom information, an analysis means for analyzing the received patient's symptom information, a generation means for generating an individualized treatment plan based on the analysis results, a notification means for notifying the patient of the generated treatment plan, a selection means for selecting an appropriate treatment facility based on the notified treatment plan, a reservation means for making a reservation at the selected treatment facility, and an update means for receiving treatment progress information from the patient and updating the treatment plan. This allows the patient to quickly and efficiently obtain an optimal treatment plan and easily find an appropriate treatment facility. Furthermore, it is possible to grasp the progress of treatment in real time and continuously optimize the treatment plan, thereby promoting improvement of the patient's symptoms.

[0006] "Patient information input means" refers to a device or interface that allows a patient to input information about their symptoms, medical history, and lifestyle habits.

[0007] The "receiving means" is a device or system for receiving the patient information sent from the input means and processing the information.

[0008] The "analysis means" refers to an algorithm or program for analyzing the patient information obtained by the receiving means and evaluating the cause and severity of symptoms.

[0009] The "generation means" refers to an algorithm or program for generating an individual treatment plan based on the results of the analysis means.

[0010] The "notification means" is a communication device or interface for notifying the patient of the generated treatment plan.

[0011] A "selection means" is a method or device for selecting an appropriate treatment facility based on the notified treatment plan.

[0012] The "reservation means" refers to a method or system for making a reservation at the treatment facility selected by the selection means.

[0013] The "update means" is an algorithm or program for receiving treatment progress information from the patient and updating the treatment plan as necessary. [Brief explanation of the drawings]

[0014] [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

[0015] 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.

[0016] First, the terms used in the following description will be explained.

[0017] 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).

[0018] 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.

[0019] 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.

[0020] 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.

[0021] 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."

[0022] [First embodiment]

[0023] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0024] 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.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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.

[0030] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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."

[0035] This invention is a system that provides personalized treatment plans specifically tailored to patients with lower back pain. The system aims to provide optimal treatment by automating everything from inputting patient information to managing treatment progress.

[0036] System Overview

[0037] The system is configured using the following means:

[0038] 1. Means for inputting patient information: A dedicated app or web form for patients to enter information about their symptoms, medical history, and lifestyle habits.

[0039] 2. Receiving means: A server for receiving and storing the entered information.

[0040] 3. Analysis method: The received information is analyzed using an AI algorithm to evaluate symptoms and identify causes.

[0041] 4. Generation method: Generate an individual treatment plan based on the analysis results.

[0042] 5. Notification Methods: Methods for informing the patient of the generated treatment plan.

[0043] 6. Selection tools: Tools to select the appropriate treatment facility for pain relief.

[0044] 7. Booking Method: A method for automatically scheduling appointments with selected treatment facilities.

[0045] 8. Updates: Receives patient progress information and the AI ​​updates the treatment plan as needed.

[0046] Natural language programming

[0047] 1. Enter patient information

[0048] User: Accesses a dedicated app or web form and enters information such as their symptoms, medical history, and lifestyle habits.

[0049] Terminal: Formats the entered information and sends it to the server using a secure communication protocol.

[0050] 2. Receiving patient information

[0051] Server: Stores the received patient information in a database.

[0052] 3. Analysis of patient information

[0053] Server: Analyzes stored patient information using AI algorithms. This analysis is done using natural language processing (NLP) and machine learning. For example, if someone says, "I have a pain in my lower back and it's hard to get up in the morning," the algorithm evaluates the possibility of muscle tension or a herniated disc.

[0054] 4. Generation of treatment plan

[0055] Server: Based on the analysis results, it generates an individualized treatment plan, which may include physical therapy, medication, stretching, etc.

[0056] 5. Notification of Treatment Plan

[0057] Server: Sends the generated treatment plan to the user's device.

[0058] Terminal: Displays the received treatment plan to the user.

[0059] User: Review the proposed treatment plan and approve or provide feedback.

[0060] 6. Selecting and booking a treatment facility

[0061] User: Based on the proposed treatment plan, select the appropriate treatment facility from the list provided by the system.

[0062] Server: Provides the list using the selection means and receives the user's selection.

[0063] Terminal: Sends an appointment request to the selected treatment facility.

[0064] 7. Treatment progress management and feedback

[0065] User: Once actual treatment begins, the user will periodically enter progress information and pain level into the system.

[0066] Device: Sends progress information to the server in real time.

[0067] Server: Analyzes progress information and makes necessary adjustments to the treatment plan.

[0068] 8. Treatment evaluation and optimization

[0069] User: Upon completion of treatment, complete a full treatment evaluation.

[0070] Device: Sends rating information to the server.

[0071] Server: Analyzes the evaluation information and uses it to optimize future treatment plans.

[0072] Specific examples

[0073] For example, a patient with back pain might use the system in the following steps:

[0074] 1. Enter patient information

[0075] User: "I have pain on the left side of my lower back, especially when I wake up in the morning."

[0076] Terminal: "Symptom information has been sent."

[0077] 2. Analyzing patient information and generating treatment plans

[0078] Server: "This case may be due to muscle tension."

[0079] Server: "I've generated a treatment plan that focuses on physical therapy."

[0080] 3. Confirm your treatment plan and make a reservation

[0081] User: "I reviewed the treatment plan and selected X Clinic."

[0082] Terminal: "Clinic information sent."

[0083] Server: "Your reservation is complete."

[0084] 4. Progress management and optimization

[0085] User: "I feel less pain today."

[0086] Terminal: "Progress information sent."

[0087] Server: "New instructions added."

[0088] In this way, the system allows patients to receive the treatment that is most suitable for them quickly and efficiently, and achieves improvement in their symptoms.

[0089] The processing flow will be explained below.

[0090] Step 1:

[0091] User: Accesses a dedicated app or web form and enters detailed information about their symptoms, medical history, lifestyle habits, etc. For example, they enter information such as, "I have pain in the left side of my lower back, especially when I wake up in the morning."

[0092] Step 2:

[0093] Terminal: Formats the entered patient information and sends it to the server using a secure communication protocol (e.g., HTTPS).

[0094] Step 3:

[0095] Server: Stores the received patient information in a database and performs data integrity checks, for example, checking that all required fields have been filled in.

[0096] Step 4:

[0097] Server: Analyzes patient information stored in a database using an AI algorithm. Specifically, it uses natural language processing (NLP) technology to extract details of symptoms from input text and compares them with a case database to make a diagnosis.

[0098] Step 5:

[0099] Server: Generates an individualized treatment plan based on the analysis results. For example, if muscle tension is determined to be the cause, a treatment plan including physical therapy, stretching, and pain medication will be created.

[0100] Step 6:

[0101] Server: Sends the generated treatment plan to the patient's device, along with a detailed description of each item included in the plan.

[0102] Step 7:

[0103] Terminal: Displays the received treatment plan to the user, providing an interface for the user to review the contents and enter feedback.

[0104] Step 8:

[0105] User: Review the proposed treatment plan and approve or enter questions or feedback.

[0106] Step 9:

[0107] Device: Sends user approval and feedback to the server.

[0108] Step 10:

[0109] Server: Receives user feedback and modifies the treatment plan as needed, which may require reanalysis.

[0110] Step 11:

[0111] User: Based on the proposed treatment plan, the user selects the appropriate treatment facility from a list provided by the system. For example, if physical therapy is required, the user selects a specialized facility.

[0112] Step 12:

[0113] Terminal: Sends information about the selected treatment facility to the server.

[0114] Step 13:

[0115] Server: Receives the treatment facility selection information, sends a reservation request to the facility, and once the reservation is confirmed, provides the final reservation information to the user.

[0116] Step 14:

[0117] User: Once the actual treatment begins, the user periodically enters progress information and pain level into the system. For example, "Today's pain level is 3 / 10."

[0118] Step 15:

[0119] Device: Sends progress information to the server in real time.

[0120] Step 16:

[0121] Server: Analyzes progress information and evaluates the effectiveness of the treatment plan. Readjusts the treatment plan if necessary and sends new instructions to the user.

[0122] Step 17:

[0123] User: Upon completion of treatment, complete an overall treatment evaluation, for example, entering a final rating such as "The treatment was very effective."

[0124] Step 18:

[0125] Device: Sends rating information to the server.

[0126] Step 19:

[0127] Server: The received evaluation information is stored in a database, and statistical analysis is performed using AI algorithms to optimize future treatment plans.

[0128] In this way, the system allows patients to receive the treatment that is most suitable for them quickly and efficiently, and achieves improvement in their symptoms.

[0129] Example 1

[0130] 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."

[0131] It is difficult to effectively collect and analyze patient symptom information, including lower back pain, and provide optimal treatment plans. Continuously updating treatment plans based on treatment progress is also time-consuming, requiring patients to accurately input symptom information and properly manage their progress. Furthermore, automating the selection and reservation of appropriate treatment facilities is necessary to reduce the burden on patients. To address these challenges, a system is needed that integrates functions such as efficient collection and analysis of patient information, generation and notification of optimal treatment plans, selection and reservation of treatment facilities, and management of treatment progress.

[0132] 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.

[0133] In this invention, the server includes an update unit for receiving treatment progress information from a patient and updating the treatment plan, a storage unit for storing the received patient symptom information in a database, an AI analysis unit for analyzing the patient symptom information stored in the storage unit using natural language processing and machine learning, and a notification system for generating and notifying a treatment plan based on the analysis results obtained by the AI ​​analysis unit. This makes it possible to efficiently collect and analyze patient symptom information, generate and notify an optimal treatment plan, and continuously update the treatment plan according to the progress of treatment. Furthermore, patients can select and make reservations at appropriate treatment facilities through the system, thereby reducing their burden.

[0134] "Patient symptom information" refers to all information entered by the patient themselves, such as symptoms, medical history, and lifestyle habits.

[0135] "Input means" refers to a device or software such as a dedicated application or web form that allows a patient to input their symptom information.

[0136] "Receiving means" refers to a system or process for receiving and storing patient symptom information sent from the input means.

[0137] The "storage means" refers to a method or device for appropriately storing the patient symptom information received by the receiving means in a database.

[0138] "Analysis means" means a system having processing capabilities for analyzing received and stored patient symptom information, and includes methods using natural language processing and machine learning, among others.

[0139] "AI analysis means" refers to means for analyzing a patient's symptom information using natural language processing and machine learning algorithms to evaluate the symptoms and identify their causes.

[0140] "Generator" refers to an algorithm or system for generating an individualized treatment plan based on the analyzed data.

[0141] "Notification means" refers to a method for informing a patient of the treatment plan created by the generation means, and includes email, SMS, in-app notification, etc.

[0142] "Selection method" refers to the system or process for selecting an appropriate treatment facility based on the notified treatment plan.

[0143] "Appointment Facility" refers to a method or system for automatically scheduling appointments with selected treatment facilities.

[0144] "Updater" refers to a system for receiving treatment progress information from a patient and modifying or adjusting the treatment plan accordingly.

[0145] A "notification system" refers to a series of processes and devices that generate a treatment plan based on the analysis results obtained by AI analysis means and notify the patient of this plan.

[0146] This invention is a system that provides personalized treatment plans specifically tailored to patients with lower back pain. The system aims to provide optimal treatment by automating everything from inputting patient information to managing treatment progress.

[0147] Hardware and software used

[0148] This system is configured using the following hardware and software.

[0149] Hardware used

[0150] Server: A server that provides high-performance data processing and storage (e.g., a virtual server for cloud services)

[0151] Devices: PCs, tablets, smartphones, etc. for user interfaces

[0152] Software used

[0153] Database: Relational database such as MySQL (registered trademark) or PostgreSQL

[0154] Natural Language Processing (NLP) libraries: spaCy and NLTK

[0155] Machine learning frameworks: TENSORFLOW (registered trademark) and PyTorch

[0156] Communication protocol: HTTPS

[0157] System configuration and functions

[0158] Entering patient information

[0159] User: The user accesses a dedicated application or web form and enters information about their symptoms, medical history, lifestyle habits, etc. For example, they enter information such as, "I have pain in the left side of my lower back, especially when I wake up in the morning."

[0160] Terminal: The entered information is formatted into JSON format and sent to the server using a secure communication protocol (HTTPS).

[0161] Receiving and storing patient information

[0162] Server: Validates the received patient symptom information and stores it securely in a database (e.g., MySQL database).

[0163] Patient information analysis

[0164] Server: Analyzes stored patient information using AI algorithms. This analysis uses natural language processing (spaCy) and machine learning (TensorFlow). For example, if a patient says, "My lower back hurts and it's hard for me to get up in the morning," the system evaluates the possibility of muscle tension or a herniated disc.

[0165] Treatment plan generation

[0166] Server: Generates a personalized treatment plan based on the analysis results, including recommendations for physical therapy, medication, and stretching.

[0167] Treatment plan notification

[0168] Server: Sends the generated treatment plan to the user's device via email, SMS, in-app notifications, etc.

[0169] Terminal: Displays the received treatment plan to the user.

[0170] Selecting and booking a treatment facility

[0171] User: Follows the proposed treatment plan and selects the appropriate treatment facility from the list provided by the system.

[0172] Server: Provides a list of treatment facilities, receives the user's selection, and confirms the appointment.

[0173] Treatment progress management and feedback

[0174] User: Once actual treatment begins, the user will periodically enter progress information and pain level into the system.

[0175] Device: This progress information is sent to the server in real time.

[0176] Server: Analyzes progress information and updates treatment plans as needed.

[0177] Treatment evaluation and optimization

[0178] User: Upon completion of treatment, complete a full treatment evaluation.

[0179] Device: Sends rating information to the server.

[0180] Server: Analyzes the received evaluation information and uses it to optimize future treatment plans.

[0181] Prompt Sentence Examples

[0182] "Please tell me more about your back pain symptoms."

[0183] Please enter some information about your lifestyle.

[0184] "Review the treatment plan and provide feedback."

[0185] In this way, patients can receive the treatment that is best suited to them quickly and efficiently, resulting in an improvement in their symptoms.

[0186] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0187] Step 1:

[0188] Entering patient information

[0189] User: Accesses a dedicated application or web form and enters information about their symptoms, medical history, lifestyle habits, etc. For example, they enter information such as "I have lower back pain" or "I have severe pain when I wake up in the morning."

[0190] Input: Patient symptom information, medical history, and lifestyle data.

[0191] Output: Formatted symptom information in JSON format.

[0192] Terminal: Converts the input information into JSON format and sends it to the server using a secure communication protocol (e.g. HTTPS).

[0193] Step 2:

[0194] Receiving and storing patient information

[0195] Server: Validates incoming patient symptom information and stores it securely in a database. For example, validates patient information and then executes an INSERT query into a MySQL database.

[0196] Input: Formatted symptom information (JSON format) sent from the device.

[0197] Output: Patient information stored in a database.

[0198] Specific operation: The server detects the receiving trigger, performs data validation, and if the data is correct, executes an INSERT query to save it to the database.

[0199] Step 3:

[0200] Patient information analysis

[0201] Server: Analyzes stored patient information using AI algorithms. Classifies symptoms using natural language processing and identifies causes using machine learning. For example, analyzes symptoms using an NLP model (e.g., spaCy) and diagnoses using a machine learning model (e.g., TensorFlow).

[0202] Input: Patient information stored in the database.

[0203] Output: Parsed symptom information and diagnosis results.

[0204] How it works: The server retrieves patient information from the database, runs it through an NLP model to classify symptoms, then invokes a machine learning model to generate a diagnosis.

[0205] Step 4:

[0206] Treatment plan generation

[0207] Server: Based on the analysis results, it generates an individualized treatment plan, which may include physical therapy, medication, stretching, etc.

[0208] Input: Parsed symptom information and diagnosis results.

[0209] Output: Individualized treatment plan.

[0210] Specific operation: Based on the analysis results, the optimal plan is generated by combining treatment options. A template engine is used to generate the plan in a format that is easy for users to view.

[0211] Step 5:

[0212] Treatment plan notification

[0213] Server: Sends the generated treatment plan to the user's device via email, SMS, in-app notifications, etc.

[0214] Input: Individualized treatment plan.

[0215] Output: Notification to the user.

[0216] Terminal: Displays the received treatment plan to the user.

[0217] Specific operation: The server calls the notification system and sends the treatment plan in the appropriate format. The device receives the notification and displays it to the user as a pop-up message or similar.

[0218] Step 6:

[0219] Selecting and booking a treatment facility

[0220] User: Follows the proposed treatment plan and selects the appropriate treatment facility from the list provided by the system.

[0221] Input: Proposed treatment plan and list of treatment facilities.

[0222] Output: Selected treatment facilities.

[0223] Server: Provides a list of treatment facilities, receives the user's selection, and confirms the appointment, e.g., by calling a booking API to confirm the appointment.

[0224] What happens: The server sends a POST request to the reservation endpoint and receives confirmation of the reservation.

[0225] Step 7:

[0226] Treatment progress management and feedback

[0227] User: Once the actual treatment begins, the user periodically enters progress information and pain level into the system, for example, providing feedback such as "Today the pain has decreased."

[0228] Input: Treatment progress information, pain level.

[0229] Output: Progress information sent to the system.

[0230] Device: Sends progress information to the server in real time.

[0231] Specific operation: The device detects user input and periodically sends progress information to the server.

[0232] Step 8:

[0233] Treatment evaluation and optimization

[0234] User: Upon completion of treatment, complete an overall treatment evaluation, such as "My pain is almost gone after treatment."

[0235] Input: Treatment evaluation information.

[0236] Output: The rating information sent to the server.

[0237] Device: Sends rating information to the server.

[0238] Server: Analyzes the received evaluation information and uses it to optimize future treatment plans.

[0239] How it works: The server analyzes the evaluation information in real time and stores it in a feedback database. This data is then used to optimize the next treatment plan.

[0240] (Application example 1)

[0241] 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."

[0242] Health management is extremely important for security staff, as they are subjected to high physical and mental strain during their work. However, there is a lack of a system to provide appropriate treatment plans tailored to individual health conditions, making effective health management difficult. This can result in a decline in security staff performance and have a negative impact on the overall security level.

[0243] 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.

[0244] In this invention, the server includes an input means for inputting symptom information of a patient, a receiving means for receiving the symptom information of the patient input from the input means, an analysis means for analyzing the symptom information of the patient received by the receiving means, a generation means for generating an individual treatment plan based on the analysis results obtained by the analysis means, a notification means for notifying the patient of the treatment plan generated by the generation means, a selection means for selecting an appropriate treatment facility based on the treatment plan notified by the notification means, a reservation means for making a reservation at the treatment facility selected by the selection means, an update means for receiving treatment progress information from the patient and updating the treatment plan, a means for inputting and analyzing health information of security staff and generating individual health management plans, and a means for monitoring the health status of the security staff and managing and optimizing their progress in real time, thereby individually optimizing the health status of the security staff, improving performance and ensuring safety.

[0245] "Patient information" refers to information necessary for treatment, such as the patient's symptoms, medical history, and lifestyle habits.

[0246] "Input means" refers to a device or interface that allows a patient or a medical professional to input symptom information into the system.

[0247] The "receiving means" is a function or device for receiving information input through the input means.

[0248] The "analysis means" refers to a device or algorithm that analyzes the information obtained by the receiving means and evaluates symptoms and identifies causes based on the content of the information.

[0249] The "generation means" refers to a function or process that creates an individual treatment plan based on the analysis results obtained by the analysis means.

[0250] The "notification means" is a method or device for informing the patient of the treatment plan created by the generation means.

[0251] "Selection means" is a function of the system for selecting an appropriate treatment facility based on a treatment plan.

[0252] "Reservation means" refers to a function or mechanism for making a reservation at a treatment facility selected by the selection means.

[0253] "Update means" is a function for receiving information on the patient's treatment progress and updating and adjusting the treatment plan based on that information.

[0254] "Security staff health information" refers to data indicating the health status of security staff, including symptoms, medical history, exercise habits, etc.

[0255] "Monitoring means" is a function for monitoring the health status of security staff in real time and managing progress.

[0256] A "health management plan" is a specific instruction or plan for maintaining or improving the health of security personnel that is tailored to each individual based on analytical methods.

[0257] This invention is a system that inputs and analyzes the health information of patients and security staff, and provides individualized treatment or health management plans. This system is designed to utilize hardware and software to enable patients and security staff to receive care efficiently.

[0258] About program processing

[0259] The program of this system has the function of performing the following main processes. First, it uses the input means to collect symptom information and health information of patients and security staff. Next, it uses the receiving means to send this information to the server and store it. The server then analyzes the received information using the analysis means and generates an individual treatment plan or health management plan based on the results.

[0260] The generated plan is communicated to the user through a notification means. The user can review the plan and select an appropriate treatment facility. The selection means automatically makes a reservation at the facility selected by the user. In addition, the system also includes an update means for receiving progress information from the user in real time and updating the treatment plan as necessary.

[0261] Hardware and Software Use

[0262] Server: AWS (registered trademark) or Google (registered trademark) Cloud is used to store data, analyze data, and generate plans.

[0263] AI models: Using natural language processing (NLP) and machine learning (e.g., TensorFlow and PyTorch).

[0264] Devices: Smartphones, smart glasses, head-mounted displays, etc.

[0265] Data processing and calculation

[0266] 1. Input method:

[0267] Symptom information and health information are entered using a device (such as a smartphone). For example, a patient enters their lower back pain symptoms.

[0268] 2. Receiving means:

[0269] The server receives the information sent from the device and stores it in a database via a secure communication protocol (e.g., HTTPS).

[0270] 3. Analysis method:

[0271] The server analyzes the stored information and uses NLP and machine learning to evaluate symptoms. For example, if someone says, "My lower back hurts and it's hard to get up in the morning," it will evaluate the possibility of muscle tension or a herniated disc.

[0272] 4. Generation means:

[0273] Based on the analysis results, a personalized treatment or health management plan is generated, which may include, for example, physical therapy, medication, and stretching.

[0274] 5. Means of notification:

[0275] The generated plan is notified to the user's terminal so that the user can check it.

[0276] 6. Selection method:

[0277] Based on the proposed treatment plan, the user selects an appropriate treatment facility from a list provided by the system.

[0278] 7. Reservation Method:

[0279] Automatically send appointment requests to selected treatment facilities.

[0280] 8. Update method:

[0281] Progress information from the user is sent to the server in real time, and the AI ​​updates the treatment plan as needed.

[0282] Examples of concrete examples and prompts

[0283] Specific examples

[0284] User input: "My lower back hurts from standing for long periods of time every day, especially the right side."

[0285] AI analysis result: "It's likely due to muscle tension on the right side."

[0286] Treatment plan: "Physical therapy three times a week and simple stretching exercises."

[0287] Prompt Sentence Examples

[0288] User input: "I have pain on the left side of my lower back, especially when I wake up in the morning."

[0289] The system responds: "This case may be due to muscle tension. We've generated a treatment plan focused on physical therapy."

[0290] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0291] Step 1:

[0292] Users use a smartphone or dedicated device to input symptom information or health information. The input information is sent to the system. Specifically, a patient might input, "I have pain in the left side of my lower back, especially when I wake up in the morning."

[0293] Input: Symptom information and health information

[0294] Output: Sending input information

[0295] Step 2:

[0296] The device formats the entered information and sends it to the server using a secure communication protocol (e.g., HTTPS). During this step, encryption is used to prevent data tampering or leakage.

[0297] Input: Formatted input information

[0298] Output: Sending encrypted data

[0299] Step 3:

[0300] The server receives the transmitted information using the receiving means and stores it in a database. Upon receiving the information, it checks the integrity of the data and performs error checks as necessary.

[0301] Input: Encrypted data

[0302] Output: Information stored in the database

[0303] Step 4:

[0304] The server then uses analytics to analyze the stored information. It uses natural language processing (NLP) and machine learning algorithms to assess symptoms and identify causes. For example, if someone says, "My lower back hurts and it's hard for me to get up in the morning," it can assess whether they have muscle tension or a herniated disc.

[0305] Input: Stored patient information

[0306] Output: Analysis results

[0307] Step 5:

[0308] The server generates an individualized treatment plan based on the analysis results using the generation means. The generated treatment plan includes physical therapy, drug therapy, stretching, etc. For example, a plan including "physical therapy three times a week and simple stretching exercises" is generated based on the analysis results.

[0309] Input: Analysis results

[0310] Output: Individual treatment plan

[0311] Step 6:

[0312] The server uses the notification means to send the generated treatment plan to the user's terminal, and the user receives the notification and checks the treatment plan.

[0313] Input: Individual Treatment Plan

[0314] Output: User notification

[0315] Step 7:

[0316] The user checks the notified treatment plan and selects an appropriate treatment facility from the list provided by the system. The information of the selected facility is sent to the system.

[0317] Input: Confirm treatment plan, select treatment facility

[0318] Output: Send selected treatment facility information

[0319] Step 8:

[0320] The server automatically sends an appointment request to the treatment facility selected by the user using the selection means, and a confirmation message is sent to the user once the appointment is completed.

[0321] Input: Selected Treatment Facility Information

[0322] Output: Reservation confirmation message

[0323] Step 9:

[0324] Users periodically enter progress information into the system, such as "Today my pain is reduced."

[0325] Input: Progress information

[0326] Output: Sending input information

[0327] Step 10:

[0328] The device formats the progress information and sends it to the server over a secure communication protocol.

[0329] Input: Formatted progress information

[0330] Output: Sending encrypted data

[0331] Step 11:

[0332] The server receives progress information and uses AI to update the treatment plan, recommending new instructions or changes based on the analysis results.

[0333] Input: Progress information

[0334] Output: Updated treatment plan

[0335] Step 12:

[0336] The server then notifies the user's device of the updated treatment plan again, continuing optimal treatment according to the patient's progress.

[0337] Input: Updated treatment plan

[0338] Output: User notification

[0339] 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.

[0340] This invention is a system that provides personalized treatment plans specifically tailored to patients with lower back pain, and includes a function that recognizes the patient's emotions and reflects them in the treatment plan. The system aims to provide optimal treatment by automating everything from inputting patient information to managing the progress of treatment.

[0341] System Overview

[0342] The system is configured using the following means:

[0343] 1. A means of patient information entry: A dedicated app or web form for patients to enter their symptoms, medical history, lifestyle information, and even emotional state.

[0344] 2. Receiving means: A server for receiving and storing the entered information.

[0345] 3. Analysis method: The received information is analyzed using AI algorithms and an emotion engine to evaluate symptoms and identify causes.

[0346] 4. Generation method: Generate an individual treatment plan based on the analysis results.

[0347] 5. Notification Methods: Methods for informing the patient of the generated treatment plan.

[0348] 6. Selection tools: Tools to select the appropriate treatment facility for pain relief.

[0349] 7. Booking Method: A method for automatically scheduling appointments with selected treatment facilities.

[0350] 8. Updates: Receives patient progress information and the AI ​​updates the treatment plan as needed.

[0351] 9. Emotion Engine: Analyzes the patient's written and spoken information, assesses their emotional state, and provides information to the analysis and generation means.

[0352] Natural language programming

[0353] 1. Enter patient information

[0354] User: Accesses a dedicated app or web form and enters information about their symptoms, medical history, lifestyle habits, and emotional state. For example, they might enter, "I have pain in the left side of my lower back, especially when I wake up in the morning. Lately, the pain has been making me feel stressed."

[0355] 2. Receiving patient information

[0356] Terminal: Formats the entered patient and emotion information and sends it to the server using a secure communication protocol (e.g., HTTPS).

[0357] 3. Patient Information Storage

[0358] Server: Stores the received patient and emotion information in a database and performs data integrity checks, for example, checking whether all required fields have been filled in.

[0359] 4. Analysis of patient information and emotional information

[0360] Server: Analyzes patient information and emotional information stored in a database using AI algorithms and an emotion engine. Using natural language processing (NLP) technology, details of symptoms and emotions are extracted from input text and compared with a case database to make a diagnosis. For example, the emotion engine analyzes the information that "pain causes stress" and determines that stress relief should also be included in treatment.

[0361] 5. Treatment plan generation

[0362] Server: Based on the analysis results, it generates an individualized treatment plan. For example, if muscle tension is determined to be the cause, it will create a treatment plan that includes physical therapy, stretching, prescription painkillers, and relaxation techniques to reduce stress.

[0363] 6. Notification of Treatment Plan

[0364] Server: Sends the generated treatment plan to the patient's device, along with a detailed explanation of each item in the plan and customized feedback based on emotions.

[0365] 7. Confirmation of treatment plan

[0366] Terminal: Displays the received treatment plan to the user, providing an interface for the user to review the contents and enter feedback.

[0367] User: Review the proposed treatment plan and approve or enter questions or feedback.

[0368] 8. Selecting and booking a treatment facility

[0369] User: Based on the proposed treatment plan, the user selects the appropriate treatment facility from a list provided by the system. For example, if physical therapy is required, the user selects a specialized facility.

[0370] Terminal: Sends information about the selected treatment facility to the server.

[0371] Server: Receives the treatment facility selection information, sends a reservation request to the facility, and once the reservation is confirmed, provides the final reservation information to the user.

[0372] 9. Treatment progress management and feedback

[0373] User: Once the actual treatment begins, the user periodically enters progress information, pain level, and emotional state into the system. For example, "Today my pain has decreased, but I still feel stressed."

[0374] Device: Sends progress and emotion information to the server in real time.

[0375] Server: Analyzes progress and emotional information to evaluate the effectiveness of the treatment plan, readjusts the treatment plan if necessary, and sends new instructions to the user based on their emotional state.

[0376] 10. Treatment evaluation and optimization

[0377] User: Upon completion of treatment, complete an overall treatment evaluation. For example, enter a final rating such as, "The treatment was very effective, but I would like to see more stress reduction techniques added."

[0378] Device: Sends rating information to the server.

[0379] Server: The received evaluation and emotional information is stored in a database, and statistical analysis is performed using an AI algorithm to optimize future treatment plans.

[0380] In this way, patients can receive the treatment that is best suited to them quickly and efficiently, and the system provides emotional support as well as symptom improvement.

[0381] The processing flow will be explained below.

[0382] Step 1:

[0383] User: Accesses a dedicated app or web form and enters detailed information such as their symptoms, medical history, lifestyle habits, emotional state, etc. An example entry is, "I have pain on the left side of my lower back, especially when I wake up in the morning. Lately, the pain has been making me feel stressed."

[0384] Step 2:

[0385] Terminal: Formats the entered patient and emotion information and sends it to the server using a secure communication protocol (e.g., HTTPS).

[0386] Step 3:

[0387] Server: Saves the received patient information and emotion information in the database. When saving, checks whether all required fields have been entered.

[0388] Step 4:

[0389] Server: Analyzes patient information and emotional information stored in a database using AI algorithms and an emotion engine. Using natural language processing (NLP) technology, details of symptoms and emotions are extracted from input text and compared with a case database to make a diagnosis. For example, the emotion engine analyzes the information that "pain causes stress" and determines that stress management should also be included in the treatment plan.

[0390] Step 5:

[0391] Server: Based on the analysis results, it generates an individualized treatment plan. Specifically, if muscle tension is determined to be the cause, it creates a treatment plan that includes physical therapy, stretching, prescription painkillers, and relaxation techniques for stress management.

[0392] Step 6:

[0393] Server: Sends the generated treatment plan to the patient's device, including detailed explanations of each item and customized feedback based on emotions.

[0394] Step 7:

[0395] Terminal: Displays the received treatment plan to the user, using an interface that allows the user to review the contents and provide feedback.

[0396] Step 8:

[0397] User: Review the proposed treatment plan and approve it if it is acceptable, as well as provide any questions or feedback.

[0398] Step 9:

[0399] Terminal: Sends user approvals and feedback to the server in a secure format.

[0400] Step 10:

[0401] Server: Receives user feedback and modifies the treatment plan as needed, which may require reanalysis.

[0402] Step 11:

[0403] User: Based on the proposed treatment plan, the user selects the appropriate treatment facility from a list provided by the system. For example, if physical therapy is required, the user selects a specialized facility.

[0404] Step 12:

[0405] Terminal: Sends information about the selected treatment facility to the server.

[0406] Step 13:

[0407] Server: Receives the treatment facility selection information, sends a reservation request to the facility, and returns the reservation confirmation to the user.

[0408] Step 14:

[0409] User: Once the actual treatment begins, the user periodically enters progress information, pain level, and emotional state into the system. For example, "Today my pain has decreased, but I still feel stressed."

[0410] Step 15:

[0411] Device: Sends progress and emotion information to the server in real time.

[0412] Step 16:

[0413] Server: Analyzes progress and emotional information to evaluate the effectiveness of the treatment plan, readjusts the treatment plan if necessary, and sends new instructions to the user based on their emotional state.

[0414] Step 17:

[0415] User: Upon completion of treatment, complete an overall treatment evaluation. For example, enter a final rating such as, "The treatment was very effective, but I would like to receive more advice on stress management."

[0416] Step 18:

[0417] Terminal: Sends evaluation information and emotion information to the server.

[0418] Step 19:

[0419] Server: The received evaluation and emotional information is stored in a database and statistically analyzed using an AI algorithm, which is used to optimize future treatment plans.

[0420] In this way, patients can receive the treatment that is best suited to them quickly and efficiently, and the system provides emotional support as well as symptom improvement.

[0421] Example 2

[0422] 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."

[0423] Conventional lower back pain treatment systems generate treatment plans based solely on the patient's symptom information, making it difficult to provide optimal treatment plans that take into account the emotional state and lifestyle habits of each individual patient. In particular, when emotional states affect pain and stress, treatment plans that ignore this factor are unable to achieve sufficient results. Furthermore, the lack of a function to update treatment plans while reflecting treatment progress information in real time makes it difficult to maximize the effectiveness of treatment.

[0424] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes an input means for a user to input information on the patient's symptoms, medical history, lifestyle, and emotional state, a receiving means for receiving the input symptom information and emotional information of the patient, an analyzing means for analyzing the received symptom information and emotional information of the patient, a generating means for generating an individualized treatment plan based on the analysis results, a notifying means for notifying the patient of the generated treatment plan, a selecting means for selecting an appropriate treatment facility based on the notified treatment plan, a booking means for making a booking at the selected treatment facility, and an updating means for receiving treatment progress information and emotional information from the patient and updating the treatment plan. This makes it possible to provide an individualized treatment plan that takes into account the patient's emotional state and lifestyle, and to provide a treatment plan that is optimized in real time according to the progress of treatment.

[0425] A "user" is a person who uses a dedicated app or web form to enter information about their symptoms, medical history, lifestyle habits, and emotional state.

[0426] An "input means" is an application or web form used by a user to input information about a patient's symptoms, medical history, lifestyle habits, and emotional state.

[0427] The "receiving means" is a component for receiving symptom information and emotion information of a patient transmitted from the input means.

[0428] The "analysis means" is a component that uses an AI algorithm and a natural language processing engine to analyze the received symptom information and emotional information of the patient, and evaluate the symptoms and identify the cause.

[0429] The "generation means" is a component for generating an individual treatment plan based on the analysis results.

[0430] The "notification means" is a component for notifying the patient of the treatment plan generated by the generation means.

[0431] The "selection means" is a component for selecting an appropriate treatment facility based on the notified treatment plan.

[0432] The "reservation means" is a component for making a reservation at a selected treatment facility.

[0433] The "updater" is a component for receiving treatment progress and emotional information from the patient and updating the treatment plan.

[0434] "Patient symptom information" is information entered by the patient about their symptoms, specifically the location of the pain, the degree of pain, the circumstances under which the pain occurs, and the like.

[0435] "Emotional information" is information about the patient's emotional state, specifically a detailed description of stress and physical and mental state.

[0436] An "AI algorithm" is an algorithm that uses artificial intelligence technology to analyze data and generate diagnoses and treatment plans.

[0437] A "natural language processing engine" is a technology that analyzes the meaning and emotions of sentences entered by patients and extracts details.

[0438] This invention is a system that provides personalized treatment plans specifically tailored to patients with lower back pain, and includes a function that recognizes the patient's emotions and reflects them in the treatment plan. The system aims to provide optimal treatment by automating everything from inputting patient information to managing the progress of treatment.

[0439] System configuration

[0440] This system is configured using the following hardware and software.

[0441] 1. Input method:

[0442] Users use a dedicated app or web form to enter information about their symptoms, medical history, lifestyle habits, and emotional state. For example, they might enter, "I have pain in the left side of my lower back, especially when I wake up in the morning. Lately, the pain has been making me feel stressed."

[0443] 2. Receiving means:

[0444] The terminal formats and transmits the entered patient and emotion information to the server using a secure communication protocol (e.g., HTTPS).

[0445] 3. Preservation means:

[0446] The server stores the received patient information and emotion information in a database and checks the integrity of the data, for example, whether all required fields have been filled in.

[0447] 4. Analysis method:

[0448] The server analyzes the information stored in the database using AI algorithms (e.g., TensorFlow or PyTorch) and natural language processing engines (e.g., IBM Watson® NLU). Using natural language processing technology, the server extracts details of symptoms and emotions from the text entered by the patient and compares them with a case database to make a diagnosis. For example, based on the information that "pain causes stress," the server determines that stress relief should also be included in treatment.

[0449] 5. Generation means:

[0450] The server generates a personalized treatment plan based on the analysis results. For example, if muscle tension is determined to be the cause, the plan will include physical therapy, stretching, prescription painkillers, and relaxation techniques to reduce stress.

[0451] 6. Means of notification:

[0452] The server sends the generated treatment plan to the patient's device, for example, by using a REST API to send the treatment plan information in JSON format and also provides a feedback function.

[0453] 7. MEANS OF SELECTION AND RESERVATION:

[0454] The user selects a treatment facility from a list provided by the system based on the proposed treatment plan and makes an appointment at that facility, for example, by selecting a physical therapy facility from a list and transmitting the selection information to the server.

[0455] The server receives the selected treatment facility information, sends a reservation request to the facility, and returns the final reservation information to the terminal once the reservation is confirmed.

[0456] 8. Update method:

[0457] The user periodically enters information about their treatment progress, pain level, and emotional state into the system, for example, "Today my pain has decreased, but I still feel stressed."

[0458] The terminal transmits the input progress information and emotion information to the server in real time.

[0459] The server analyzes the received progress and emotion information to evaluate the effectiveness of the treatment plan, readjusting the treatment plan if necessary, and sending new instructions to the user.

[0460] Specific examples

[0461] We will explain in detail a scene where a user inputs information using a dedicated app and a treatment plan is generated and notified.

[0462] The user opens the dedicated app and enters, "I have severe pain in my lower back, especially when I wake up in the morning. This pain has been causing me a lot of stress lately."

[0463] The terminal formats the entered information and sends it to the server using HTTPS.

[0464] The server stores the input data in a database and checks the integrity of the information.

[0465] The server uses NLP and an emotion engine to analyze the stored information and recognize that stress is part of the cause of the pain.

[0466] The server generates a personalized treatment plan and suggests a treatment plan to the user that includes relaxation techniques and stretches.

[0467] The server transmits the generated treatment plan to the user's terminal.

[0468] The user reviews and approves the proposed treatment plan.

[0469] The user selects a physical therapy facility based on the proposed treatment plan and schedules an appointment with that facility.

[0470] Users enter their treatment progress into the app and report changes in stress levels and pain.

[0471] The server analyzes the entered information and sends suggested treatment plan modifications to the user.

[0472] Prompt Sentence Examples

[0473] "Generate a personalized treatment plan based on the information below.

[0474] Symptoms: Lower back pain, especially when waking up in the morning.

[0475] Emotional state: Feeling stressed.

[0476] Lifestyle: Sitting for long periods at work.”

[0477] In this way, the system can provide a personalized treatment plan that takes into account the patient's symptoms and emotional state, and provides an optimized treatment plan in real time as the treatment progresses.

[0478] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0479] Step 1:

[0480] Users access a dedicated app or web form and enter information about their symptoms, medical history, lifestyle habits, and emotional state. Examples of input data include, "I have pain in the left side of my lower back, especially when I wake up in the morning. Lately, the pain has been making me feel stressed." This allows detailed patient information to be collected.

[0481] Step 2:

[0482] The terminal converts the input patient information and emotion information into an appropriate format (e.g., JSON format) and sends it to the server using a secure communication protocol such as HTTPS. Specifically, the terminal integrates the patient information and emotion information and communicates them as a series of JSON data. This prepares the server to receive the patient information.

[0483] Step 3:

[0484] The server stores the received patient and emotion information in a database. As it stores the information, it verifies data integrity, checks for required fields, and ensures the data format is correct. For example, it runs validation scripts to ensure all required fields are filled in. This ensures accurate information.

[0485] Step 4:

[0486] The server uses AI algorithms and natural language processing engines (e.g., TensorFlow, IBM Watson NLU) to analyze the stored patient information and emotional information. Input: Patient information and emotional information stored in a database. Processing: Natural language processing technology is used to analyze the input data and extract details of symptoms and emotions. Output: The analysis results in an evaluation of specific symptoms and emotional states. Specifically, detailed evaluations of pain location, intensity, stress levels, etc. are provided.

[0487] Step 5:

[0488] The server generates an individualized treatment plan based on the analysis results. Input: Analysis results. Processing: Based on the analysis results, the optimal treatment plan for each patient is generated. An AI algorithm is used to create a treatment plan that includes physical therapy, stretching, drug therapy, stress relief techniques, etc. Output: The generated individualized treatment plan. For example, if muscle tension is determined to be the cause, suggestions such as physical therapy, stretching, prescription painkillers, and relaxation techniques may be suggested.

[0489] Step 6:

[0490] The server sends the generated treatment plan to the patient's device. Input: Generated treatment plan. Processing: Package the treatment plan, its details, and customized feedback based on emotions in JSON format. Output: Packaged treatment plan information is sent to the patient's device. This allows the user to check their treatment plan.

[0491] Step 7:

[0492] The terminal displays the received treatment plan to the user. Input: Treatment plan information sent from the server. Processing: Provides an interface that displays the received information to the user in an appropriate format. Output: The user can check the details of the treatment plan and approve or enter feedback. For example, when the user checks the treatment plan on the screen and clicks the "Approve" button, the information is sent to the server.

[0493] Step 8:

[0494] Based on the proposed treatment plan, the user selects an appropriate treatment facility from a list provided by the system. For example, if physical therapy is required, the user selects a specialized facility. Input: A list of treatment facilities provided as candidates. Processing: The user selects the most suitable treatment facility and determines its information. Output: Information on the selected treatment facility.

[0495] Step 9:

[0496] The terminal sends information about the selected treatment facility to the server. Input: Information about the selected treatment facility. Processing: The selection information is sent to the server in JSON format. Output: The server receives the information and prepares to proceed to the next step. This allows the selection information about the selected treatment facility to reach the server.

[0497] Step 10:

[0498] The server receives the treatment facility selection information and sends a reservation request to that facility. Once the reservation is confirmed, the final reservation information is fed back to the patient's terminal. Input: Information of the selected treatment facility. Processing: Sends a reservation request to the facility and waits for confirmation. Output: Once the reservation is confirmed, the details are notified to the user. This allows the user to receive the confirmed reservation information.

[0499] Step 11:

[0500] Even after the actual treatment has begun, the user periodically inputs progress information, pain level, and emotional state into the system. For example, the user might input, "Today the pain has decreased, but I still feel stressed." Input: Treatment progress information, pain level, emotional state, etc. Processing: Information is periodically updated and sent to the system. Output: Progress information is sent to the server.

[0501] Step 12:

[0502] The terminal sends progress information and emotional information to the server in real time. Input: Progress information and emotional information entered by the user. Processing: This information is formatted and sent in real time. Output: The server receives this information. This allows the server to grasp the patient's latest condition.

[0503] Step 13:

[0504] The server analyzes the progress information and emotional information to evaluate the effectiveness of the treatment plan. It readjusts the treatment plan as needed and sends new instructions to the user. Input: Progress information and emotional information. Processing: Using an AI algorithm, it analyzes the progress information and emotional information and evaluates the effectiveness of the treatment plan. Output: A new treatment plan and instructions with any necessary readjustments are generated and sent to the user. This optimizes the treatment plan.

[0505] In this way, the system provides an individualized treatment plan that takes into account the patient's symptoms and emotional state, and optimizes treatment as it progresses in real time, resulting in effective treatment.

[0506] (Application example 2)

[0507] 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."

[0508] Factory workers' physical fatigue and pain during work can reduce their work efficiency and have a negative impact on their health in the long term. Furthermore, employees' emotional state also has a significant impact on their work efficiency and health. A system is needed that provides optimal treatment plans for each employee and takes their emotions into account in real time.

[0509] 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.

[0510] In this invention, the server includes an input means for inputting symptom information and emotional information of the patient, a receiving means for receiving the symptom information and emotional information of the patient, an analyzing means for analyzing the symptom information and emotional information of the patient, a generating means for generating an optimal treatment plan based on the emotional information of the patient, a notifying means for notifying the patient of the treatment plan, an updating means for receiving treatment progress information and emotional information of the patient and updating the treatment plan, and a notifying means for notifying the smart device of the updated treatment plan. This enables factory employees to manage their own symptoms and emotions in real time and receive individually optimized treatment plans.

[0511] "Patient symptom information" is data about physical pain or discomfort experienced by an employee.

[0512] "Emotional information" is data about an employee's emotional state and mental stress level.

[0513] "Input means" refers to a digital device or interface through which employees can input their symptom and emotional information.

[0514] The "receiving means" refers to a communication technology or device for collecting the symptom information and emotion information of the patient transmitted from the input means.

[0515] "Analysis means" refers to an AI algorithm or software platform for processing and analyzing received patient symptom and emotional information.

[0516] The "generation means" refers to an algorithm or system for generating an individual treatment plan based on the analysis results obtained by the analysis means.

[0517] The "notification means" is a means for notifying employees of the generated treatment plan, and is a system for transmitting information via smart devices.

[0518] A "selection tool" is a system or interface that allows an employee to select an appropriate treatment facility or treatment option based on the notified treatment plan.

[0519] A "reservation means" is a system that automatically makes a reservation at a selected treatment facility or treatment option based on the selection means.

[0520] "Updater" means a system for receiving treatment progress and sentiment information from employees and adjusting and updating treatment plans in real time.

[0521] "Smart devices" are digital devices such as smartphones, smart glasses, and head-mounted displays used to manage and display treatment plans and notifications.

[0522] This invention is a system designed to allow factory workers to manage their own health status in real time, collecting and analyzing symptom and emotional information and presenting optimal treatment plans.

[0523] 1. System Configuration

[0524] The system consists of the following main components:

[0525] 1. An input means for inputting the patient's symptom information and emotional information.

[0526] 2. A receiving means for receiving the input information.

[0527] 3. Analytical tools for analyzing patient and emotional information.

[0528] 4. A generating means for generating a treatment plan based on the analysis results.

[0529] 5. Notification means to communicate the generated treatment plan.

[0530] 6. A selection tool to select an appropriate treatment facility based on the notified treatment plan.

[0531] 7. Booking facilities to make appointments at selected treatment facilities.

[0532] 8. A means of updating to receive treatment progress and emotional information and update the treatment plan.

[0533] 9. Notification methods to notify smart devices of updated treatment plans.

[0534] 2. Data entry and receipt

[0535] Users use smart devices (e.g., smartphones, smart glasses, head-mounted displays) to input their symptoms and emotional information. For example, they enter detailed information such as, "I have pain in the left side of my lower back. It hurts especially when I wake up in the morning. Lately, the pain has been making me feel stressed." This information is sent to the server using a secure communication protocol (e.g., HTTPS).

[0536] 3. Data Analysis and Generation

[0537] The server analyzes the received information using AI algorithms and an emotion engine. For example, it uses NLP techniques to extract symptom details and emotional state from the input text. After identifying symptoms and assessing emotional state, it generates a personalized treatment plan. This plan may include, for example, physical therapy, stress relief exercises, and pain medication prescriptions.

[0538] 4. Notification and Choice of Treatment Plan

[0539] The generated treatment plan is sent to the user's smart device via a notification means. The user receives the notification and can select an appropriate treatment facility based on the displayed plan. This selection information is then sent back to the server, and a reservation at the treatment facility is automatically made.

[0540] 5. Track and update your progress

[0541] Users periodically enter information about their treatment progress and emotions into the system, such as, "Today, my pain has decreased, but I still feel stressed." This information is sent in real time to a server, which analyzes it to evaluate the effectiveness of the treatment plan and update it as necessary.

[0542] 6. Hardware and Software Used

[0543] The system uses AI algorithms and emotion engines (including NLP technology) on smart devices (smartphones, smart glasses, head-mounted displays) and servers, and uses HTTPS as the communication protocol to ensure data security and privacy.

[0544] Examples of prompt sentences

[0545] An example of what might actually be entered is as follows:

[0546] "I have pain on the left side of my lower back, especially when I wake up in the morning. Lately the pain has been making me feel stressed."

[0547] The prompts are analyzed by the server and an optimal treatment plan is generated, enabling factory workers to manage their symptoms and emotions in real time and receive appropriate treatment early.

[0548] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0549] Program processing steps

[0550] Step 1:

[0551] Entering patient information

[0552] Users input their own symptom information and emotional information using a smart device (smartphone, smart glasses, head-mounted display).

[0553] Input: Symptom information (e.g., "I have pain in the left side of my lower back, especially when I wake up in the morning."), Emotion information (e.g., "The pain has been making me feel stressed lately.")

[0554] Data processing: Formatted as text data.

[0555] Output: The input information is stored on the device as text data.

[0556] Step 2:

[0557] Sending patient information

[0558] The terminal transmits the input information to the server via a secure communication protocol (HTTPS).

[0559] Input: Symptom and emotion information entered by the user

[0560] Data Computing: Data is encrypted using the HTTPS protocol

[0561] Output: Encrypted data sent to the server

[0562] Step 3:

[0563] Receiving and storing patient information

[0564] The server receives the data sent from the terminal and stores it in a database.

[0565] Input: Encrypted data

[0566] Data processing: Decrypting data and storing it in a database

[0567] Output: Decrypted data stored in database

[0568] Step 4:

[0569] Data analysis

[0570] The server analyzes the received data using AI algorithms and an emotion engine.

[0571] Input: Symptom information and emotion information stored in the database

[0572] Data Computing: Analyzing symptoms and emotions using natural language processing (NLP) algorithms

[0573] Output: Analysis results (symptom assessment and emotional state)

[0574] Step 5:

[0575] Treatment plan generation

[0576] The server generates an individualized treatment plan based on the analysis results.

[0577] Input: Analysis results

[0578] Data computation: Using algorithms to generate optimal treatment plans

[0579] Output: Individualized treatment plan

[0580] Step 6:

[0581] Treatment plan notification

[0582] The server transmits the generated treatment plan to the terminal and notifies the user.

[0583] Input: Individualized Treatment Plan

[0584] Data Calculation: Format treatment plans based on user settings

[0585] Output: Sent to the terminal as a notification message

[0586] Step 7:

[0587] Choosing a Treatment Facility

[0588] The user selects an appropriate treatment facility based on the notified treatment plan.

[0589] Input: Details of the notified treatment plan

[0590] Data processing: Select from a list of treatment facilities

[0591] Output: Information about the selected treatment facility is registered on the terminal.

[0592] Step 8:

[0593] Treatment facility booking

[0594] The terminal makes an appointment with the selected treatment facility.

[0595] Input: Selected treatment facility information

[0596] Data calculation: Generate reservation information and send it to the facility

[0597] Output: Appointment information is sent to treatment facility and confirmed

[0598] Step 9:

[0599] Entering treatment progress

[0600] Users periodically enter treatment progress and emotional information into the system.

[0601] Input: Treatment progress information (e.g., "Today I feel less pain, but I still feel stressed.")

[0602] Data processing: Format as text data

[0603] Output: The input data is stored on the device.

[0604] Step 10:

[0605] Treatment plan updates

[0606] The server analyzes the entered progress and emotion information and updates the treatment plan.

[0607] Input: Treatment progress information and emotional information

[0608] Data Computation: Using AI Algorithms to Optimize Treatment Plans

[0609] Output: An updated treatment plan is generated.

[0610] Step 11:

[0611] Notification of updated treatment plans

[0612] The server sends the updated treatment plan to the terminal and notifies the user.

[0613] Input: Updated treatment plan

[0614] Data calculation: Format update plan based on user settings

[0615] Output: Sent to the terminal as a notification message

[0616] 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.

[0617] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0618] 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.

[0619] [Second embodiment]

[0620] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0621] 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.

[0622] 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).

[0623] 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.

[0624] 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.

[0625] 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).

[0626] 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.

[0627] 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.

[0628] 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.

[0629] 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.

[0630] In the smart glasses 214, 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.

[0631] 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."

[0632] This invention is a system that provides personalized treatment plans specifically tailored to patients with lower back pain. The system aims to provide optimal treatment by automating everything from inputting patient information to managing treatment progress.

[0633] System Overview

[0634] The system is configured using the following means:

[0635] 1. Means for inputting patient information: A dedicated app or web form for patients to enter information about their symptoms, medical history, and lifestyle habits.

[0636] 2. Receiving means: A server for receiving and storing the entered information.

[0637] 3. Analysis method: The received information is analyzed using an AI algorithm to evaluate symptoms and identify causes.

[0638] 4. Generation method: Generate an individual treatment plan based on the analysis results.

[0639] 5. Notification Methods: Methods for informing the patient of the generated treatment plan.

[0640] 6. Selection tools: Tools to select the appropriate treatment facility for pain relief.

[0641] 7. Booking Method: A method for automatically scheduling appointments with selected treatment facilities.

[0642] 8. Updates: Receives patient progress information and the AI ​​updates the treatment plan as needed.

[0643] Natural language programming

[0644] 1. Enter patient information

[0645] User: Accesses a dedicated app or web form and enters information such as their symptoms, medical history, and lifestyle habits.

[0646] Terminal: Formats the entered information and sends it to the server using a secure communication protocol.

[0647] 2. Receiving patient information

[0648] Server: Stores the received patient information in a database.

[0649] 3. Analysis of patient information

[0650] Server: Analyzes stored patient information using AI algorithms. This analysis is done using natural language processing (NLP) and machine learning. For example, if someone says, "I have a pain in my lower back and it's hard to get up in the morning," the algorithm evaluates the possibility of muscle tension or a herniated disc.

[0651] 4. Generation of treatment plan

[0652] Server: Based on the analysis results, it generates an individualized treatment plan, which may include physical therapy, medication, stretching, etc.

[0653] 5. Notification of Treatment Plan

[0654] Server: Sends the generated treatment plan to the user's device.

[0655] Terminal: Displays the received treatment plan to the user.

[0656] User: Review the proposed treatment plan and approve or provide feedback.

[0657] 6. Selecting and booking a treatment facility

[0658] User: Based on the proposed treatment plan, select the appropriate treatment facility from the list provided by the system.

[0659] Server: Provides the list using the selection means and receives the user's selection.

[0660] Terminal: Sends an appointment request to the selected treatment facility.

[0661] 7. Treatment progress management and feedback

[0662] User: Once actual treatment begins, the user will periodically enter progress information and pain level into the system.

[0663] Device: Sends progress information to the server in real time.

[0664] Server: Analyzes progress information and makes necessary adjustments to the treatment plan.

[0665] 8. Treatment evaluation and optimization

[0666] User: Upon completion of treatment, complete a full treatment evaluation.

[0667] Device: Sends rating information to the server.

[0668] Server: Analyzes the evaluation information and uses it to optimize future treatment plans.

[0669] Specific examples

[0670] For example, a patient with back pain might use the system in the following steps:

[0671] 1. Enter patient information

[0672] User: "I have pain on the left side of my lower back, especially when I wake up in the morning."

[0673] Terminal: "Symptom information has been sent."

[0674] 2. Analyzing patient information and generating treatment plans

[0675] Server: "This case may be due to muscle tension."

[0676] Server: "I've generated a treatment plan that focuses on physical therapy."

[0677] 3. Confirm your treatment plan and make a reservation

[0678] User: "I reviewed the treatment plan and selected X Clinic."

[0679] Terminal: "Clinic information sent."

[0680] Server: "Your reservation is complete."

[0681] 4. Progress management and optimization

[0682] User: "I feel less pain today."

[0683] Terminal: "Progress information sent."

[0684] Server: "New instructions added."

[0685] In this way, the system allows patients to receive the treatment that is most suitable for them quickly and efficiently, and achieves improvement in their symptoms.

[0686] The processing flow will be explained below.

[0687] Step 1:

[0688] User: Accesses a dedicated app or web form and enters detailed information about their symptoms, medical history, lifestyle habits, etc. For example, they enter information such as, "I have pain in the left side of my lower back, especially when I wake up in the morning."

[0689] Step 2:

[0690] Terminal: Formats the entered patient information and sends it to the server using a secure communication protocol (e.g., HTTPS).

[0691] Step 3:

[0692] Server: Stores the received patient information in a database and performs data integrity checks, for example, checking that all required fields have been filled in.

[0693] Step 4:

[0694] Server: Analyzes patient information stored in a database using an AI algorithm. Specifically, it uses natural language processing (NLP) technology to extract details of symptoms from input text and compares them with a case database to make a diagnosis.

[0695] Step 5:

[0696] Server: Generates an individualized treatment plan based on the analysis results. For example, if muscle tension is determined to be the cause, a treatment plan including physical therapy, stretching, and pain medication will be created.

[0697] Step 6:

[0698] Server: Sends the generated treatment plan to the patient's device, along with a detailed description of each item included in the plan.

[0699] Step 7:

[0700] Terminal: Displays the received treatment plan to the user, providing an interface for the user to review the contents and enter feedback.

[0701] Step 8:

[0702] User: Review the proposed treatment plan and approve or enter questions or feedback.

[0703] Step 9:

[0704] Device: Sends user approval and feedback to the server.

[0705] Step 10:

[0706] Server: Receives user feedback and modifies the treatment plan as needed, which may require reanalysis.

[0707] Step 11:

[0708] User: Based on the proposed treatment plan, the user selects the appropriate treatment facility from a list provided by the system. For example, if physical therapy is required, the user selects a specialized facility.

[0709] Step 12:

[0710] Terminal: Sends information about the selected treatment facility to the server.

[0711] Step 13:

[0712] Server: Receives the treatment facility selection information, sends a reservation request to the facility, and once the reservation is confirmed, provides the final reservation information to the user.

[0713] Step 14:

[0714] User: Once the actual treatment begins, the user periodically enters progress information and pain level into the system. For example, "Today's pain level is 3 / 10."

[0715] Step 15:

[0716] Device: Sends progress information to the server in real time.

[0717] Step 16:

[0718] Server: Analyzes progress information and evaluates the effectiveness of the treatment plan. Readjusts the treatment plan if necessary and sends new instructions to the user.

[0719] Step 17:

[0720] User: Upon completion of treatment, complete an overall treatment evaluation, for example, entering a final rating such as "The treatment was very effective."

[0721] Step 18:

[0722] Device: Sends rating information to the server.

[0723] Step 19:

[0724] Server: The received evaluation information is stored in a database, and statistical analysis is performed using AI algorithms to optimize future treatment plans.

[0725] In this way, the system allows patients to receive the treatment that is most suitable for them quickly and efficiently, and achieves improvement in their symptoms.

[0726] Example 1

[0727] 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."

[0728] It is difficult to effectively collect and analyze patient symptom information, including lower back pain, and provide optimal treatment plans. Continuously updating treatment plans based on treatment progress is also time-consuming, requiring patients to accurately input symptom information and properly manage their progress. Furthermore, automating the selection and reservation of appropriate treatment facilities is necessary to reduce the burden on patients. To address these challenges, a system is needed that integrates functions such as efficient collection and analysis of patient information, generation and notification of optimal treatment plans, selection and reservation of treatment facilities, and management of treatment progress.

[0729] 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.

[0730] In this invention, the server includes an update unit for receiving treatment progress information from a patient and updating the treatment plan, a storage unit for storing the received patient symptom information in a database, an AI analysis unit for analyzing the patient symptom information stored in the storage unit using natural language processing and machine learning, and a notification system for generating and notifying a treatment plan based on the analysis results obtained by the AI ​​analysis unit. This makes it possible to efficiently collect and analyze patient symptom information, generate and notify an optimal treatment plan, and continuously update the treatment plan according to the progress of treatment. Furthermore, patients can select and make reservations at appropriate treatment facilities through the system, thereby reducing their burden.

[0731] "Patient symptom information" refers to all information entered by the patient themselves, such as symptoms, medical history, and lifestyle habits.

[0732] "Input means" refers to a device or software such as a dedicated application or web form that allows a patient to input their symptom information.

[0733] "Receiving means" refers to a system or process for receiving and storing patient symptom information sent from the input means.

[0734] The "storage means" refers to a method or device for appropriately storing the patient symptom information received by the receiving means in a database.

[0735] "Analysis means" means a system having processing capabilities for analyzing received and stored patient symptom information, and includes methods using natural language processing and machine learning, among others.

[0736] "AI analysis means" refers to means for analyzing a patient's symptom information using natural language processing and machine learning algorithms to evaluate the symptoms and identify their causes.

[0737] "Generator" refers to an algorithm or system for generating an individualized treatment plan based on the analyzed data.

[0738] "Notification means" refers to a method for informing a patient of the treatment plan created by the generation means, and includes email, SMS, in-app notification, etc.

[0739] "Selection method" refers to the system or process for selecting an appropriate treatment facility based on the notified treatment plan.

[0740] "Appointment Facility" refers to a method or system for automatically scheduling appointments with selected treatment facilities.

[0741] "Updater" refers to a system for receiving treatment progress information from a patient and modifying or adjusting the treatment plan accordingly.

[0742] A "notification system" refers to a series of processes and devices that generate a treatment plan based on the analysis results obtained by AI analysis means and notify the patient of this plan.

[0743] This invention is a system that provides personalized treatment plans specifically tailored to patients with lower back pain. The system aims to provide optimal treatment by automating everything from inputting patient information to managing treatment progress.

[0744] Hardware and software used

[0745] This system is configured using the following hardware and software.

[0746] Hardware used

[0747] Server: A server that provides high-performance data processing and storage (e.g., a virtual server for cloud services)

[0748] Devices: PCs, tablets, smartphones, etc. for user interfaces

[0749] Software used

[0750] Database: A relational database such as MySQL or PostgreSQL

[0751] Natural Language Processing (NLP) libraries: spaCy and NLTK

[0752] Machine learning frameworks: TensorFlow and PyTorch

[0753] Communication protocol: HTTPS

[0754] System configuration and functions

[0755] Entering patient information

[0756] User: The user accesses a dedicated application or web form and enters information about their symptoms, medical history, lifestyle habits, etc. For example, they enter information such as, "I have pain in the left side of my lower back, especially when I wake up in the morning."

[0757] Terminal: The entered information is formatted into JSON format and sent to the server using a secure communication protocol (HTTPS).

[0758] Receiving and storing patient information

[0759] Server: Validates the received patient symptom information and stores it securely in a database (e.g., MySQL database).

[0760] Patient information analysis

[0761] Server: Analyzes stored patient information using AI algorithms. This analysis uses natural language processing (spaCy) and machine learning (TensorFlow). For example, if a patient says, "My lower back hurts and it's hard for me to get up in the morning," the system evaluates the possibility of muscle tension or a herniated disc.

[0762] Treatment plan generation

[0763] Server: Generates a personalized treatment plan based on the analysis results, including recommendations for physical therapy, medication, and stretching.

[0764] Treatment plan notification

[0765] Server: Sends the generated treatment plan to the user's device via email, SMS, in-app notifications, etc.

[0766] Terminal: Displays the received treatment plan to the user.

[0767] Selecting and booking a treatment facility

[0768] User: Follows the proposed treatment plan and selects the appropriate treatment facility from the list provided by the system.

[0769] Server: Provides a list of treatment facilities, receives the user's selection, and confirms the appointment.

[0770] Treatment progress management and feedback

[0771] User: Once actual treatment begins, the user will periodically enter progress information and pain level into the system.

[0772] Device: This progress information is sent to the server in real time.

[0773] Server: Analyzes progress information and updates treatment plans as needed.

[0774] Treatment evaluation and optimization

[0775] User: Upon completion of treatment, complete a full treatment evaluation.

[0776] Device: Sends rating information to the server.

[0777] Server: Analyzes the received evaluation information and uses it to optimize future treatment plans.

[0778] Prompt Sentence Examples

[0779] "Please tell me more about your back pain symptoms."

[0780] Please enter some information about your lifestyle.

[0781] "Review the treatment plan and provide feedback."

[0782] In this way, patients can receive the treatment that is best suited to them quickly and efficiently, resulting in an improvement in their symptoms.

[0783] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0784] Step 1:

[0785] Entering patient information

[0786] User: Accesses a dedicated application or web form and enters information about their symptoms, medical history, lifestyle habits, etc. For example, they enter information such as "I have lower back pain" or "I have severe pain when I wake up in the morning."

[0787] Input: Patient symptom information, medical history, and lifestyle data.

[0788] Output: Formatted symptom information in JSON format.

[0789] Terminal: Converts the input information into JSON format and sends it to the server using a secure communication protocol (e.g. HTTPS).

[0790] Step 2:

[0791] Receiving and storing patient information

[0792] Server: Validates incoming patient symptom information and stores it securely in a database. For example, validates patient information and then executes an INSERT query into a MySQL database.

[0793] Input: Formatted symptom information (JSON format) sent from the device.

[0794] Output: Patient information stored in a database.

[0795] Specific operation: The server detects the receiving trigger, performs data validation, and if the data is correct, executes an INSERT query to save it to the database.

[0796] Step 3:

[0797] Patient information analysis

[0798] Server: Analyzes stored patient information using AI algorithms. Classifies symptoms using natural language processing and identifies causes using machine learning. For example, analyzes symptoms using an NLP model (e.g., spaCy) and diagnoses using a machine learning model (e.g., TensorFlow).

[0799] Input: Patient information stored in the database.

[0800] Output: Parsed symptom information and diagnosis results.

[0801] How it works: The server retrieves patient information from the database, runs it through an NLP model to classify symptoms, then invokes a machine learning model to generate a diagnosis.

[0802] Step 4:

[0803] Treatment plan generation

[0804] Server: Based on the analysis results, it generates an individualized treatment plan, which may include physical therapy, medication, stretching, etc.

[0805] Input: Parsed symptom information and diagnosis results.

[0806] Output: Individualized treatment plan.

[0807] Specific operation: Based on the analysis results, the optimal plan is generated by combining treatment options. A template engine is used to generate the plan in a format that is easy for users to view.

[0808] Step 5:

[0809] Treatment plan notification

[0810] Server: Sends the generated treatment plan to the user's device via email, SMS, in-app notifications, etc.

[0811] Input: Individualized treatment plan.

[0812] Output: Notification to the user.

[0813] Terminal: Displays the received treatment plan to the user.

[0814] Specific operation: The server calls the notification system and sends the treatment plan in the appropriate format. The device receives the notification and displays it to the user as a pop-up message or similar.

[0815] Step 6:

[0816] Selecting and booking a treatment facility

[0817] User: Follows the proposed treatment plan and selects the appropriate treatment facility from the list provided by the system.

[0818] Input: Proposed treatment plan and list of treatment facilities.

[0819] Output: Selected treatment facilities.

[0820] Server: Provides a list of treatment facilities, receives the user's selection, and confirms the appointment, e.g., by calling a booking API to confirm the appointment.

[0821] What happens: The server sends a POST request to the reservation endpoint and receives confirmation of the reservation.

[0822] Step 7:

[0823] Treatment progress management and feedback

[0824] User: Once the actual treatment begins, the user periodically enters progress information and pain level into the system, for example, providing feedback such as "Today the pain has decreased."

[0825] Input: Treatment progress information, pain level.

[0826] Output: Progress information sent to the system.

[0827] Device: Sends progress information to the server in real time.

[0828] Specific operation: The device detects user input and periodically sends progress information to the server.

[0829] Step 8:

[0830] Treatment evaluation and optimization

[0831] User: Upon completion of treatment, complete an overall treatment evaluation, such as "My pain is almost gone after treatment."

[0832] Input: Treatment evaluation information.

[0833] Output: The rating information sent to the server.

[0834] Device: Sends rating information to the server.

[0835] Server: Analyzes the received evaluation information and uses it to optimize future treatment plans.

[0836] How it works: The server analyzes the evaluation information in real time and stores it in a feedback database. This data is then used to optimize the next treatment plan.

[0837] (Application example 1)

[0838] 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."

[0839] Health management is extremely important for security staff, as they are subjected to high physical and mental strain during their work. However, there is a lack of a system to provide appropriate treatment plans tailored to individual health conditions, making effective health management difficult. This can result in a decline in security staff performance and have a negative impact on the overall security level.

[0840] 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.

[0841] In this invention, the server includes an input means for inputting symptom information of a patient, a receiving means for receiving the symptom information of the patient input from the input means, an analysis means for analyzing the symptom information of the patient received by the receiving means, a generation means for generating an individual treatment plan based on the analysis results obtained by the analysis means, a notification means for notifying the patient of the treatment plan generated by the generation means, a selection means for selecting an appropriate treatment facility based on the treatment plan notified by the notification means, a reservation means for making a reservation at the treatment facility selected by the selection means, an update means for receiving treatment progress information from the patient and updating the treatment plan, a means for inputting and analyzing health information of security staff and generating individual health management plans, and a means for monitoring the health status of the security staff and managing and optimizing their progress in real time, thereby individually optimizing the health status of the security staff, improving performance and ensuring safety.

[0842] "Patient information" refers to information necessary for treatment, such as the patient's symptoms, medical history, and lifestyle habits.

[0843] "Input means" refers to a device or interface that allows a patient or a medical professional to input symptom information into the system.

[0844] The "receiving means" is a function or device for receiving information input through the input means.

[0845] The "analysis means" refers to a device or algorithm that analyzes the information obtained by the receiving means and evaluates symptoms and identifies causes based on the content of the information.

[0846] The "generation means" refers to a function or process that creates an individual treatment plan based on the analysis results obtained by the analysis means.

[0847] The "notification means" is a method or device for informing the patient of the treatment plan created by the generation means.

[0848] "Selection means" is a function of the system for selecting an appropriate treatment facility based on a treatment plan.

[0849] "Reservation means" refers to a function or mechanism for making a reservation at a treatment facility selected by the selection means.

[0850] "Update means" is a function for receiving information on the patient's treatment progress and updating and adjusting the treatment plan based on that information.

[0851] "Security staff health information" refers to data indicating the health status of security staff, including symptoms, medical history, exercise habits, etc.

[0852] "Monitoring means" is a function for monitoring the health status of security staff in real time and managing progress.

[0853] A "health management plan" is a specific instruction or plan for maintaining or improving the health of security personnel that is tailored to each individual based on analytical methods.

[0854] This invention is a system that inputs and analyzes the health information of patients and security staff, and provides individualized treatment or health management plans. This system is designed to utilize hardware and software to enable patients and security staff to receive care efficiently.

[0855] About program processing

[0856] The program of this system has the function of performing the following main processes. First, it uses the input means to collect symptom information and health information of patients and security staff. Next, it uses the receiving means to send this information to the server and store it. The server then analyzes the received information using the analysis means and generates an individual treatment plan or health management plan based on the results.

[0857] The generated plan is communicated to the user through a notification means. The user can review the plan and select an appropriate treatment facility. The selection means automatically makes a reservation at the facility selected by the user. In addition, the system also includes an update means for receiving progress information from the user in real time and updating the treatment plan as necessary.

[0858] Hardware and Software Use

[0859] Server: Uses AWS or Google Cloud to store data, analyze data, and generate plans.

[0860] AI models: Using natural language processing (NLP) and machine learning (e.g., TensorFlow and PyTorch).

[0861] Devices: Smartphones, smart glasses, head-mounted displays, etc.

[0862] Data processing and calculation

[0863] 1. Input method:

[0864] Symptom information and health information are entered using a device (such as a smartphone). For example, a patient enters their lower back pain symptoms.

[0865] 2. Receiving means:

[0866] The server receives the information sent from the device and stores it in a database via a secure communication protocol (e.g., HTTPS).

[0867] 3. Analysis method:

[0868] The server analyzes the stored information and uses NLP and machine learning to evaluate symptoms. For example, if someone says, "My lower back hurts and it's hard to get up in the morning," it will evaluate the possibility of muscle tension or a herniated disc.

[0869] 4. Generation means:

[0870] Based on the analysis results, a personalized treatment or health management plan is generated, which may include, for example, physical therapy, medication, and stretching.

[0871] 5. Means of notification:

[0872] The generated plan is notified to the user's terminal so that the user can check it.

[0873] 6. Selection method:

[0874] Based on the proposed treatment plan, the user selects an appropriate treatment facility from a list provided by the system.

[0875] 7. Reservation Method:

[0876] Automatically send appointment requests to selected treatment facilities.

[0877] 8. Update method:

[0878] Progress information from the user is sent to the server in real time, and the AI ​​updates the treatment plan as needed.

[0879] Examples of concrete examples and prompts

[0880] Specific examples

[0881] User input: "My lower back hurts from standing for long periods of time every day, especially the right side."

[0882] AI analysis result: "It's likely due to muscle tension on the right side."

[0883] Treatment plan: "Physical therapy three times a week and simple stretching exercises."

[0884] Prompt Sentence Examples

[0885] User input: "I have pain on the left side of my lower back, especially when I wake up in the morning."

[0886] The system responds: "This case may be due to muscle tension. We've generated a treatment plan focused on physical therapy."

[0887] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0888] Step 1:

[0889] Users use a smartphone or dedicated device to input symptom information or health information. The input information is sent to the system. Specifically, a patient might input, "I have pain in the left side of my lower back, especially when I wake up in the morning."

[0890] Input: Symptom information and health information

[0891] Output: Sending input information

[0892] Step 2:

[0893] The device formats the entered information and sends it to the server using a secure communication protocol (e.g., HTTPS). During this step, encryption is used to prevent data tampering or leakage.

[0894] Input: Formatted input information

[0895] Output: Sending encrypted data

[0896] Step 3:

[0897] The server receives the transmitted information using the receiving means and stores it in a database. Upon receiving the information, it checks the integrity of the data and performs error checks as necessary.

[0898] Input: Encrypted data

[0899] Output: Information stored in the database

[0900] Step 4:

[0901] The server then uses analytics to analyze the stored information. It uses natural language processing (NLP) and machine learning algorithms to assess symptoms and identify causes. For example, if someone says, "My lower back hurts and it's hard for me to get up in the morning," it can assess whether they have muscle tension or a herniated disc.

[0902] Input: Stored patient information

[0903] Output: Analysis results

[0904] Step 5:

[0905] The server generates an individualized treatment plan based on the analysis results using the generation means. The generated treatment plan includes physical therapy, drug therapy, stretching, etc. For example, a plan including "physical therapy three times a week and simple stretching exercises" is generated based on the analysis results.

[0906] Input: Analysis results

[0907] Output: Individual treatment plan

[0908] Step 6:

[0909] The server uses the notification means to send the generated treatment plan to the user's terminal, and the user receives the notification and checks the treatment plan.

[0910] Input: Individual Treatment Plan

[0911] Output: User notification

[0912] Step 7:

[0913] The user checks the notified treatment plan and selects an appropriate treatment facility from the list provided by the system. The information of the selected facility is sent to the system.

[0914] Input: Confirm treatment plan, select treatment facility

[0915] Output: Send selected treatment facility information

[0916] Step 8:

[0917] The server automatically sends an appointment request to the treatment facility selected by the user using the selection means, and a confirmation message is sent to the user once the appointment is completed.

[0918] Input: Selected Treatment Facility Information

[0919] Output: Reservation confirmation message

[0920] Step 9:

[0921] Users periodically enter progress information into the system, such as "Today my pain is reduced."

[0922] Input: Progress information

[0923] Output: Sending input information

[0924] Step 10:

[0925] The device formats the progress information and sends it to the server over a secure communication protocol.

[0926] Input: Formatted progress information

[0927] Output: Sending encrypted data

[0928] Step 11:

[0929] The server receives progress information and uses AI to update the treatment plan, recommending new instructions or changes based on the analysis results.

[0930] Input: Progress information

[0931] Output: Updated treatment plan

[0932] Step 12:

[0933] The server then notifies the user's device of the updated treatment plan again, continuing optimal treatment according to the patient's progress.

[0934] Input: Updated treatment plan

[0935] Output: User notification

[0936] 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.

[0937] This invention is a system that provides personalized treatment plans specifically tailored to patients with lower back pain, and includes a function that recognizes the patient's emotions and reflects them in the treatment plan. The system aims to provide optimal treatment by automating everything from inputting patient information to managing the progress of treatment.

[0938] System Overview

[0939] The system is configured using the following means:

[0940] 1. A means of patient information entry: A dedicated app or web form for patients to enter their symptoms, medical history, lifestyle information, and even emotional state.

[0941] 2. Receiving means: A server for receiving and storing the entered information.

[0942] 3. Analysis method: The received information is analyzed using AI algorithms and an emotion engine to evaluate symptoms and identify causes.

[0943] 4. Generation method: Generate an individual treatment plan based on the analysis results.

[0944] 5. Notification Methods: Methods for informing the patient of the generated treatment plan.

[0945] 6. Selection tools: Tools to select the appropriate treatment facility for pain relief.

[0946] 7. Booking Method: A method for automatically scheduling appointments with selected treatment facilities.

[0947] 8. Updates: Receives patient progress information and the AI ​​updates the treatment plan as needed.

[0948] 9. Emotion Engine: Analyzes the patient's written and spoken information, assesses their emotional state, and provides information to the analysis and generation means.

[0949] Natural language programming

[0950] 1. Enter patient information

[0951] User: Accesses a dedicated app or web form and enters information about their symptoms, medical history, lifestyle habits, and emotional state. For example, they might enter, "I have pain in the left side of my lower back, especially when I wake up in the morning. Lately, the pain has been making me feel stressed."

[0952] 2. Receiving patient information

[0953] Terminal: Formats the entered patient and emotion information and sends it to the server using a secure communication protocol (e.g., HTTPS).

[0954] 3. Patient Information Storage

[0955] Server: Stores the received patient and emotion information in a database and performs data integrity checks, for example, checking whether all required fields have been filled in.

[0956] 4. Analysis of patient information and emotional information

[0957] Server: Analyzes patient information and emotional information stored in a database using AI algorithms and an emotion engine. Using natural language processing (NLP) technology, details of symptoms and emotions are extracted from input text and compared with a case database to make a diagnosis. For example, the emotion engine analyzes the information that "pain causes stress" and determines that stress relief should also be included in treatment.

[0958] 5. Treatment plan generation

[0959] Server: Based on the analysis results, it generates an individualized treatment plan. For example, if muscle tension is determined to be the cause, it will create a treatment plan that includes physical therapy, stretching, prescription painkillers, and relaxation techniques to reduce stress.

[0960] 6. Notification of Treatment Plan

[0961] Server: Sends the generated treatment plan to the patient's device, along with a detailed explanation of each item in the plan and customized feedback based on emotions.

[0962] 7. Confirmation of treatment plan

[0963] Terminal: Displays the received treatment plan to the user, providing an interface for the user to review the contents and enter feedback.

[0964] User: Review the proposed treatment plan and approve or enter questions or feedback.

[0965] 8. Selecting and booking a treatment facility

[0966] User: Based on the proposed treatment plan, the user selects the appropriate treatment facility from a list provided by the system. For example, if physical therapy is required, the user selects a specialized facility.

[0967] Terminal: Sends information about the selected treatment facility to the server.

[0968] Server: Receives the treatment facility selection information, sends a reservation request to the facility, and once the reservation is confirmed, provides the final reservation information to the user.

[0969] 9. Treatment progress management and feedback

[0970] User: Once the actual treatment begins, the user periodically enters progress information, pain level, and emotional state into the system. For example, "Today my pain has decreased, but I still feel stressed."

[0971] Device: Sends progress and emotion information to the server in real time.

[0972] Server: Analyzes progress and emotional information to evaluate the effectiveness of the treatment plan, readjusts the treatment plan if necessary, and sends new instructions to the user based on their emotional state.

[0973] 10. Treatment evaluation and optimization

[0974] User: Upon completion of treatment, complete an overall treatment evaluation. For example, enter a final rating such as, "The treatment was very effective, but I would like to see more stress reduction techniques added."

[0975] Device: Sends rating information to the server.

[0976] Server: The received evaluation and emotional information is stored in a database, and statistical analysis is performed using an AI algorithm to optimize future treatment plans.

[0977] In this way, patients can receive the treatment that is best suited to them quickly and efficiently, and the system provides emotional support as well as symptom improvement.

[0978] The processing flow will be explained below.

[0979] Step 1:

[0980] User: Accesses a dedicated app or web form and enters detailed information such as their symptoms, medical history, lifestyle habits, emotional state, etc. An example entry is, "I have pain on the left side of my lower back, especially when I wake up in the morning. Lately, the pain has been making me feel stressed."

[0981] Step 2:

[0982] Terminal: Formats the entered patient and emotion information and sends it to the server using a secure communication protocol (e.g., HTTPS).

[0983] Step 3:

[0984] Server: Saves the received patient information and emotion information in the database. When saving, checks whether all required fields have been entered.

[0985] Step 4:

[0986] Server: Analyzes patient information and emotional information stored in a database using AI algorithms and an emotion engine. Using natural language processing (NLP) technology, details of symptoms and emotions are extracted from input text and compared with a case database to make a diagnosis. For example, the emotion engine analyzes the information that "pain causes stress" and determines that stress management should also be included in the treatment plan.

[0987] Step 5:

[0988] Server: Based on the analysis results, it generates an individualized treatment plan. Specifically, if muscle tension is determined to be the cause, it creates a treatment plan that includes physical therapy, stretching, prescription painkillers, and relaxation techniques for stress management.

[0989] Step 6:

[0990] Server: Sends the generated treatment plan to the patient's device, including detailed explanations of each item and customized feedback based on emotions.

[0991] Step 7:

[0992] Terminal: Displays the received treatment plan to the user, using an interface that allows the user to review the contents and provide feedback.

[0993] Step 8:

[0994] User: Review the proposed treatment plan and approve it if it is acceptable, as well as provide any questions or feedback.

[0995] Step 9:

[0996] Terminal: Sends user approvals and feedback to the server in a secure format.

[0997] Step 10:

[0998] Server: Receives user feedback and modifies the treatment plan as needed, which may require reanalysis.

[0999] Step 11:

[1000] User: Based on the proposed treatment plan, the user selects the appropriate treatment facility from a list provided by the system. For example, if physical therapy is required, the user selects a specialized facility.

[1001] Step 12:

[1002] Terminal: Sends information about the selected treatment facility to the server.

[1003] Step 13:

[1004] Server: Receives the treatment facility selection information, sends a reservation request to the facility, and returns the reservation confirmation to the user.

[1005] Step 14:

[1006] User: Once the actual treatment begins, the user periodically enters progress information, pain level, and emotional state into the system. For example, "Today my pain has decreased, but I still feel stressed."

[1007] Step 15:

[1008] Device: Sends progress and emotion information to the server in real time.

[1009] Step 16:

[1010] Server: Analyzes progress and emotional information to evaluate the effectiveness of the treatment plan, readjusts the treatment plan if necessary, and sends new instructions to the user based on their emotional state.

[1011] Step 17:

[1012] User: Upon completion of treatment, complete an overall treatment evaluation. For example, enter a final rating such as, "The treatment was very effective, but I would like to receive more advice on stress management."

[1013] Step 18:

[1014] Terminal: Sends evaluation information and emotion information to the server.

[1015] Step 19:

[1016] Server: The received evaluation and emotional information is stored in a database and statistically analyzed using an AI algorithm, which is used to optimize future treatment plans.

[1017] In this way, patients can receive the treatment that is best suited to them quickly and efficiently, and the system provides emotional support as well as symptom improvement.

[1018] Example 2

[1019] 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."

[1020] Conventional lower back pain treatment systems generate treatment plans based solely on the patient's symptom information, making it difficult to provide optimal treatment plans that take into account the emotional state and lifestyle habits of each individual patient. In particular, when emotional states affect pain and stress, treatment plans that ignore this factor are unable to achieve sufficient results. Furthermore, the lack of a function to update treatment plans while reflecting treatment progress information in real time makes it difficult to maximize the effectiveness of treatment.

[1021] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes an input means for a user to input information on the patient's symptoms, medical history, lifestyle, and emotional state, a receiving means for receiving the input symptom information and emotional information of the patient, an analyzing means for analyzing the received symptom information and emotional information of the patient, a generating means for generating an individualized treatment plan based on the analysis results, a notifying means for notifying the patient of the generated treatment plan, a selecting means for selecting an appropriate treatment facility based on the notified treatment plan, a booking means for making a booking at the selected treatment facility, and an updating means for receiving treatment progress information and emotional information from the patient and updating the treatment plan. This makes it possible to provide an individualized treatment plan that takes into account the patient's emotional state and lifestyle, and to provide a treatment plan that is optimized in real time according to the progress of treatment.

[1022] A "user" is a person who uses a dedicated app or web form to enter information about their symptoms, medical history, lifestyle habits, and emotional state.

[1023] An "input means" is an application or web form used by a user to input information about a patient's symptoms, medical history, lifestyle habits, and emotional state.

[1024] The "receiving means" is a component for receiving symptom information and emotion information of a patient transmitted from the input means.

[1025] The "analysis means" is a component that uses an AI algorithm and a natural language processing engine to analyze the received symptom information and emotional information of the patient, and evaluate the symptoms and identify the cause.

[1026] The "generation means" is a component for generating an individual treatment plan based on the analysis results.

[1027] The "notification means" is a component for notifying the patient of the treatment plan generated by the generation means.

[1028] The "selection means" is a component for selecting an appropriate treatment facility based on the notified treatment plan.

[1029] The "reservation means" is a component for making a reservation at a selected treatment facility.

[1030] The "updater" is a component for receiving treatment progress and emotional information from the patient and updating the treatment plan.

[1031] "Patient symptom information" is information entered by the patient about their symptoms, specifically the location of the pain, the degree of pain, the circumstances under which the pain occurs, and the like.

[1032] "Emotional information" is information about the patient's emotional state, specifically a detailed description of stress and physical and mental state.

[1033] An "AI algorithm" is an algorithm that uses artificial intelligence technology to analyze data and generate diagnoses and treatment plans.

[1034] A "natural language processing engine" is a technology that analyzes the meaning and emotions of sentences entered by patients and extracts details.

[1035] This invention is a system that provides personalized treatment plans specifically tailored to patients with lower back pain, and includes a function that recognizes the patient's emotions and reflects them in the treatment plan. The system aims to provide optimal treatment by automating everything from inputting patient information to managing the progress of treatment.

[1036] System configuration

[1037] This system is configured using the following hardware and software.

[1038] 1. Input method:

[1039] Users use a dedicated app or web form to enter information about their symptoms, medical history, lifestyle habits, and emotional state. For example, they might enter, "I have pain in the left side of my lower back, especially when I wake up in the morning. Lately, the pain has been making me feel stressed."

[1040] 2. Receiving means:

[1041] The terminal formats and transmits the entered patient and emotion information to the server using a secure communication protocol (e.g., HTTPS).

[1042] 3. Preservation means:

[1043] The server stores the received patient information and emotion information in a database and checks the integrity of the data, for example, whether all required fields have been filled in.

[1044] 4. Analysis method:

[1045] The server analyzes the information stored in the database using AI algorithms (for example, TensorFlow or PyTorch) and natural language processing engines (for example, IBM Watson NLU). Using natural language processing technology, it extracts details of symptoms and emotions from the text entered by the patient and compares them with a case database to make a diagnosis. For example, based on the information that "pain causes stress," it determines that stress relief should also be included in treatment.

[1046] 5. Generation means:

[1047] The server generates a personalized treatment plan based on the analysis results. For example, if muscle tension is determined to be the cause, the plan will include physical therapy, stretching, prescription painkillers, and relaxation techniques to reduce stress.

[1048] 6. Means of notification:

[1049] The server sends the generated treatment plan to the patient's device, for example, by using a REST API to send the treatment plan information in JSON format and also provides a feedback function.

[1050] 7. MEANS OF SELECTION AND RESERVATION:

[1051] The user selects a treatment facility from a list provided by the system based on the proposed treatment plan and makes an appointment at that facility, for example, by selecting a physical therapy facility from a list and transmitting the selection information to the server.

[1052] The server receives the selected treatment facility information, sends a reservation request to the facility, and returns the final reservation information to the terminal once the reservation is confirmed.

[1053] 8. Update method:

[1054] The user periodically enters information about their treatment progress, pain level, and emotional state into the system, for example, "Today my pain has decreased, but I still feel stressed."

[1055] The terminal transmits the input progress information and emotion information to the server in real time.

[1056] The server analyzes the received progress and emotion information to evaluate the effectiveness of the treatment plan, readjusting the treatment plan if necessary, and sending new instructions to the user.

[1057] Specific examples

[1058] We will explain in detail a scene where a user inputs information using a dedicated app and a treatment plan is generated and notified.

[1059] The user opens the dedicated app and enters, "I have severe pain in my lower back, especially when I wake up in the morning. This pain has been causing me a lot of stress lately."

[1060] The terminal formats the entered information and sends it to the server using HTTPS.

[1061] The server stores the input data in a database and checks the integrity of the information.

[1062] The server uses NLP and an emotion engine to analyze the stored information and recognize that stress is part of the cause of the pain.

[1063] The server generates a personalized treatment plan and suggests a treatment plan to the user that includes relaxation techniques and stretches.

[1064] The server transmits the generated treatment plan to the user's terminal.

[1065] The user reviews and approves the proposed treatment plan.

[1066] The user selects a physical therapy facility based on the proposed treatment plan and schedules an appointment with that facility.

[1067] Users enter their treatment progress into the app and report changes in stress levels and pain.

[1068] The server analyzes the entered information and sends suggested treatment plan modifications to the user.

[1069] Prompt Sentence Examples

[1070] "Generate a personalized treatment plan based on the information below.

[1071] Symptoms: Lower back pain, especially when waking up in the morning.

[1072] Emotional state: Feeling stressed.

[1073] Lifestyle: Sitting for long periods at work.”

[1074] In this way, the system can provide a personalized treatment plan that takes into account the patient's symptoms and emotional state, and provides an optimized treatment plan in real time as the treatment progresses.

[1075] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1076] Step 1:

[1077] Users access a dedicated app or web form and enter information about their symptoms, medical history, lifestyle habits, and emotional state. Examples of input data include, "I have pain in the left side of my lower back, especially when I wake up in the morning. Lately, the pain has been making me feel stressed." This allows detailed patient information to be collected.

[1078] Step 2:

[1079] The terminal converts the input patient information and emotion information into an appropriate format (e.g., JSON format) and sends it to the server using a secure communication protocol such as HTTPS. Specifically, the terminal integrates the patient information and emotion information and communicates them as a series of JSON data. This prepares the server to receive the patient information.

[1080] Step 3:

[1081] The server stores the received patient and emotion information in a database. As it stores the information, it verifies data integrity, checks for required fields, and ensures the data format is correct. For example, it runs validation scripts to ensure all required fields are filled in. This ensures accurate information.

[1082] Step 4:

[1083] The server uses AI algorithms and natural language processing engines (e.g., TensorFlow, IBM Watson NLU) to analyze the stored patient information and emotional information. Input: Patient information and emotional information stored in a database. Processing: Natural language processing technology is used to analyze the input data and extract details of symptoms and emotions. Output: The analysis results in an evaluation of specific symptoms and emotional states. Specifically, detailed evaluations of pain location, intensity, stress levels, etc. are provided.

[1084] Step 5:

[1085] The server generates an individualized treatment plan based on the analysis results. Input: Analysis results. Processing: Based on the analysis results, the optimal treatment plan for each patient is generated. An AI algorithm is used to create a treatment plan that includes physical therapy, stretching, drug therapy, stress relief techniques, etc. Output: The generated individualized treatment plan. For example, if muscle tension is determined to be the cause, suggestions such as physical therapy, stretching, prescription painkillers, and relaxation techniques may be suggested.

[1086] Step 6:

[1087] The server sends the generated treatment plan to the patient's device. Input: Generated treatment plan. Processing: Package the treatment plan, its details, and customized feedback based on emotions in JSON format. Output: Packaged treatment plan information is sent to the patient's device. This allows the user to check their treatment plan.

[1088] Step 7:

[1089] The terminal displays the received treatment plan to the user. Input: Treatment plan information sent from the server. Processing: Provides an interface that displays the received information to the user in an appropriate format. Output: The user can check the details of the treatment plan and approve or enter feedback. For example, when the user checks the treatment plan on the screen and clicks the "Approve" button, the information is sent to the server.

[1090] Step 8:

[1091] Based on the proposed treatment plan, the user selects an appropriate treatment facility from a list provided by the system. For example, if physical therapy is required, the user selects a specialized facility. Input: A list of treatment facilities provided as candidates. Processing: The user selects the most suitable treatment facility and determines its information. Output: Information on the selected treatment facility.

[1092] Step 9:

[1093] The terminal sends information about the selected treatment facility to the server. Input: Information about the selected treatment facility. Processing: The selection information is sent to the server in JSON format. Output: The server receives the information and prepares to proceed to the next step. This allows the selection information about the selected treatment facility to reach the server.

[1094] Step 10:

[1095] The server receives the treatment facility selection information and sends a reservation request to that facility. Once the reservation is confirmed, the final reservation information is fed back to the patient's terminal. Input: Information of the selected treatment facility. Processing: Sends a reservation request to the facility and waits for confirmation. Output: Once the reservation is confirmed, the details are notified to the user. This allows the user to receive the confirmed reservation information.

[1096] Step 11:

[1097] Even after the actual treatment has begun, the user periodically inputs progress information, pain level, and emotional state into the system. For example, the user might input, "Today the pain has decreased, but I still feel stressed." Input: Treatment progress information, pain level, emotional state, etc. Processing: Information is periodically updated and sent to the system. Output: Progress information is sent to the server.

[1098] Step 12:

[1099] The terminal sends progress information and emotional information to the server in real time. Input: Progress information and emotional information entered by the user. Processing: This information is formatted and sent in real time. Output: The server receives this information. This allows the server to grasp the patient's latest condition.

[1100] Step 13:

[1101] The server analyzes the progress information and emotional information to evaluate the effectiveness of the treatment plan. It readjusts the treatment plan as needed and sends new instructions to the user. Input: Progress information and emotional information. Processing: Using an AI algorithm, it analyzes the progress information and emotional information and evaluates the effectiveness of the treatment plan. Output: A new treatment plan and instructions with any necessary readjustments are generated and sent to the user. This optimizes the treatment plan.

[1102] In this way, the system provides an individualized treatment plan that takes into account the patient's symptoms and emotional state, and optimizes treatment as it progresses in real time, resulting in effective treatment.

[1103] (Application example 2)

[1104] 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."

[1105] Factory workers' physical fatigue and pain during work can reduce their work efficiency and have a negative impact on their health in the long term. Furthermore, employees' emotional state also has a significant impact on their work efficiency and health. A system is needed that provides optimal treatment plans for each employee and takes their emotions into account in real time.

[1106] 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.

[1107] In this invention, the server includes an input means for inputting symptom information and emotional information of the patient, a receiving means for receiving the symptom information and emotional information of the patient, an analyzing means for analyzing the symptom information and emotional information of the patient, a generating means for generating an optimal treatment plan based on the emotional information of the patient, a notifying means for notifying the patient of the treatment plan, an updating means for receiving treatment progress information and emotional information of the patient and updating the treatment plan, and a notifying means for notifying the smart device of the updated treatment plan. This enables factory employees to manage their own symptoms and emotions in real time and receive individually optimized treatment plans.

[1108] "Patient symptom information" is data about physical pain or discomfort experienced by an employee.

[1109] "Emotional information" is data about an employee's emotional state and mental stress level.

[1110] "Input means" refers to a digital device or interface through which employees can input their symptom and emotional information.

[1111] The "receiving means" refers to a communication technology or device for collecting the symptom information and emotion information of the patient transmitted from the input means.

[1112] "Analysis means" refers to an AI algorithm or software platform for processing and analyzing received patient symptom and emotional information.

[1113] The "generation means" refers to an algorithm or system for generating an individual treatment plan based on the analysis results obtained by the analysis means.

[1114] The "notification means" is a means for notifying employees of the generated treatment plan, and is a system for transmitting information via smart devices.

[1115] A "selection tool" is a system or interface that allows an employee to select an appropriate treatment facility or treatment option based on the notified treatment plan.

[1116] A "reservation means" is a system that automatically makes a reservation at a selected treatment facility or treatment option based on the selection means.

[1117] "Updater" means a system for receiving treatment progress and sentiment information from employees and adjusting and updating treatment plans in real time.

[1118] "Smart devices" are digital devices such as smartphones, smart glasses, and head-mounted displays used to manage and display treatment plans and notifications.

[1119] This invention is a system designed to allow factory workers to manage their own health status in real time, collecting and analyzing symptom and emotional information and presenting optimal treatment plans.

[1120] 1. System Configuration

[1121] The system consists of the following main components:

[1122] 1. An input means for inputting the patient's symptom information and emotional information.

[1123] 2. A receiving means for receiving the input information.

[1124] 3. Analytical tools for analyzing patient and emotional information.

[1125] 4. A generating means for generating a treatment plan based on the analysis results.

[1126] 5. Notification means to communicate the generated treatment plan.

[1127] 6. A selection tool to select an appropriate treatment facility based on the notified treatment plan.

[1128] 7. Booking facilities to make appointments at selected treatment facilities.

[1129] 8. A means of updating to receive treatment progress and emotional information and update the treatment plan.

[1130] 9. Notification methods to notify smart devices of updated treatment plans.

[1131] 2. Data entry and receipt

[1132] Users use smart devices (e.g., smartphones, smart glasses, head-mounted displays) to input their symptoms and emotional information. For example, they enter detailed information such as, "I have pain in the left side of my lower back. It hurts especially when I wake up in the morning. Lately, the pain has been making me feel stressed." This information is sent to the server using a secure communication protocol (e.g., HTTPS).

[1133] 3. Data Analysis and Generation

[1134] The server analyzes the received information using AI algorithms and an emotion engine. For example, it uses NLP techniques to extract symptom details and emotional state from the input text. After identifying symptoms and assessing emotional state, it generates a personalized treatment plan. This plan may include, for example, physical therapy, stress relief exercises, and pain medication prescriptions.

[1135] 4. Notification and Choice of Treatment Plan

[1136] The generated treatment plan is sent to the user's smart device via a notification means. The user receives the notification and can select an appropriate treatment facility based on the displayed plan. This selection information is then sent back to the server, and a reservation at the treatment facility is automatically made.

[1137] 5. Track and update your progress

[1138] Users periodically enter information about their treatment progress and emotions into the system, such as, "Today, my pain has decreased, but I still feel stressed." This information is sent in real time to a server, which analyzes it to evaluate the effectiveness of the treatment plan and update it as necessary.

[1139] 6. Hardware and Software Used

[1140] The system uses AI algorithms and emotion engines (including NLP technology) on smart devices (smartphones, smart glasses, head-mounted displays) and servers, and uses HTTPS as the communication protocol to ensure data security and privacy.

[1141] Examples of prompt sentences

[1142] An example of what might actually be entered is as follows:

[1143] "I have pain on the left side of my lower back, especially when I wake up in the morning. Lately the pain has been making me feel stressed."

[1144] The prompts are analyzed by the server and an optimal treatment plan is generated, enabling factory workers to manage their symptoms and emotions in real time and receive appropriate treatment early.

[1145] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1146] Program processing steps

[1147] Step 1:

[1148] Entering patient information

[1149] Users input their own symptom information and emotional information using a smart device (smartphone, smart glasses, head-mounted display).

[1150] Input: Symptom information (e.g., "I have pain in the left side of my lower back, especially when I wake up in the morning."), Emotion information (e.g., "The pain has been making me feel stressed lately.")

[1151] Data processing: Formatted as text data.

[1152] Output: The input information is stored on the device as text data.

[1153] Step 2:

[1154] Sending patient information

[1155] The terminal transmits the input information to the server via a secure communication protocol (HTTPS).

[1156] Input: Symptom and emotion information entered by the user

[1157] Data Computing: Data is encrypted using the HTTPS protocol

[1158] Output: Encrypted data sent to the server

[1159] Step 3:

[1160] Receiving and storing patient information

[1161] The server receives the data sent from the terminal and stores it in a database.

[1162] Input: Encrypted data

[1163] Data processing: Decrypting data and storing it in a database

[1164] Output: Decrypted data stored in database

[1165] Step 4:

[1166] Data analysis

[1167] The server analyzes the received data using AI algorithms and an emotion engine.

[1168] Input: Symptom information and emotion information stored in the database

[1169] Data Computing: Analyzing symptoms and emotions using natural language processing (NLP) algorithms

[1170] Output: Analysis results (symptom assessment and emotional state)

[1171] Step 5:

[1172] Treatment plan generation

[1173] The server generates an individualized treatment plan based on the analysis results.

[1174] Input: Analysis results

[1175] Data computation: Using algorithms to generate optimal treatment plans

[1176] Output: Individualized treatment plan

[1177] Step 6:

[1178] Treatment plan notification

[1179] The server transmits the generated treatment plan to the terminal and notifies the user.

[1180] Input: Individualized Treatment Plan

[1181] Data Calculation: Format treatment plans based on user settings

[1182] Output: Sent to the terminal as a notification message

[1183] Step 7:

[1184] Choosing a Treatment Facility

[1185] The user selects an appropriate treatment facility based on the notified treatment plan.

[1186] Input: Details of the notified treatment plan

[1187] Data processing: Select from a list of treatment facilities

[1188] Output: Information about the selected treatment facility is registered on the terminal.

[1189] Step 8:

[1190] Treatment facility booking

[1191] The terminal makes an appointment with the selected treatment facility.

[1192] Input: Selected treatment facility information

[1193] Data calculation: Generate reservation information and send it to the facility

[1194] Output: Appointment information is sent to treatment facility and confirmed

[1195] Step 9:

[1196] Entering treatment progress

[1197] Users periodically enter treatment progress and emotional information into the system.

[1198] Input: Treatment progress information (e.g., "Today I feel less pain, but I still feel stressed.")

[1199] Data processing: Format as text data

[1200] Output: The input data is stored on the device.

[1201] Step 10:

[1202] Treatment plan updates

[1203] The server analyzes the entered progress and emotion information and updates the treatment plan.

[1204] Input: Treatment progress information and emotional information

[1205] Data Computation: Using AI Algorithms to Optimize Treatment Plans

[1206] Output: An updated treatment plan is generated.

[1207] Step 11:

[1208] Notification of updated treatment plans

[1209] The server sends the updated treatment plan to the terminal and notifies the user.

[1210] Input: Updated treatment plan

[1211] Data calculation: Format update plan based on user settings

[1212] Output: Sent to the terminal as a notification message

[1213] 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.

[1214] 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.

[1215] 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.

[1216] [Third embodiment]

[1217] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1218] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1219] 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).

[1220] 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.

[1221] 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.

[1222] 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).

[1223] 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.

[1224] 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.

[1225] 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.

[1226] 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.

[1227] 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.

[1228] 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."

[1229] This invention is a system that provides personalized treatment plans specifically tailored to patients with lower back pain. The system aims to provide optimal treatment by automating everything from inputting patient information to managing treatment progress.

[1230] System Overview

[1231] The system is configured using the following means:

[1232] 1. Means for inputting patient information: A dedicated app or web form for patients to enter information about their symptoms, medical history, and lifestyle habits.

[1233] 2. Receiving means: A server for receiving and storing the entered information.

[1234] 3. Analysis method: The received information is analyzed using an AI algorithm to evaluate symptoms and identify causes.

[1235] 4. Generation method: Generate an individual treatment plan based on the analysis results.

[1236] 5. Notification Methods: Methods for informing the patient of the generated treatment plan.

[1237] 6. Selection tools: Tools to select the appropriate treatment facility for pain relief.

[1238] 7. Booking Method: A method for automatically scheduling appointments with selected treatment facilities.

[1239] 8. Updates: Receives patient progress information and the AI ​​updates the treatment plan as needed.

[1240] Natural language programming

[1241] 1. Enter patient information

[1242] User: Accesses a dedicated app or web form and enters information such as their symptoms, medical history, and lifestyle habits.

[1243] Terminal: Formats the entered information and sends it to the server using a secure communication protocol.

[1244] 2. Receiving patient information

[1245] Server: Stores the received patient information in a database.

[1246] 3. Analysis of patient information

[1247] Server: Analyzes stored patient information using AI algorithms. This analysis is done using natural language processing (NLP) and machine learning. For example, if someone says, "I have a pain in my lower back and it's hard to get up in the morning," the algorithm evaluates the possibility of muscle tension or a herniated disc.

[1248] 4. Generation of treatment plan

[1249] Server: Based on the analysis results, it generates an individualized treatment plan, which may include physical therapy, medication, stretching, etc.

[1250] 5. Notification of Treatment Plan

[1251] Server: Sends the generated treatment plan to the user's device.

[1252] Terminal: Displays the received treatment plan to the user.

[1253] User: Review the proposed treatment plan and approve or provide feedback.

[1254] 6. Selecting and booking a treatment facility

[1255] User: Based on the proposed treatment plan, select the appropriate treatment facility from the list provided by the system.

[1256] Server: Provides the list using the selection means and receives the user's selection.

[1257] Terminal: Sends an appointment request to the selected treatment facility.

[1258] 7. Treatment progress management and feedback

[1259] User: Once actual treatment begins, the user will periodically enter progress information and pain level into the system.

[1260] Device: Sends progress information to the server in real time.

[1261] Server: Analyzes progress information and makes necessary adjustments to the treatment plan.

[1262] 8. Treatment evaluation and optimization

[1263] User: Upon completion of treatment, complete a full treatment evaluation.

[1264] Device: Sends rating information to the server.

[1265] Server: Analyzes the evaluation information and uses it to optimize future treatment plans.

[1266] Specific examples

[1267] For example, a patient with back pain might use the system in the following steps:

[1268] 1. Enter patient information

[1269] User: "I have pain on the left side of my lower back, especially when I wake up in the morning."

[1270] Terminal: "Symptom information has been sent."

[1271] 2. Analyzing patient information and generating treatment plans

[1272] Server: "This case may be due to muscle tension."

[1273] Server: "I've generated a treatment plan that focuses on physical therapy."

[1274] 3. Confirm your treatment plan and make a reservation

[1275] User: "I reviewed the treatment plan and selected X Clinic."

[1276] Terminal: "Clinic information sent."

[1277] Server: "Your reservation is complete."

[1278] 4. Progress management and optimization

[1279] User: "I feel less pain today."

[1280] Terminal: "Progress information sent."

[1281] Server: "New instructions added."

[1282] In this way, the system allows patients to receive the treatment that is most suitable for them quickly and efficiently, and achieves improvement in their symptoms.

[1283] The processing flow will be explained below.

[1284] Step 1:

[1285] User: Accesses a dedicated app or web form and enters detailed information about their symptoms, medical history, lifestyle habits, etc. For example, they enter information such as, "I have pain in the left side of my lower back, especially when I wake up in the morning."

[1286] Step 2:

[1287] Terminal: Formats the entered patient information and sends it to the server using a secure communication protocol (e.g., HTTPS).

[1288] Step 3:

[1289] Server: Stores the received patient information in a database and performs data integrity checks, for example, checking that all required fields have been filled in.

[1290] Step 4:

[1291] Server: Analyzes patient information stored in a database using an AI algorithm. Specifically, it uses natural language processing (NLP) technology to extract details of symptoms from input text and compares them with a case database to make a diagnosis.

[1292] Step 5:

[1293] Server: Generates an individualized treatment plan based on the analysis results. For example, if muscle tension is determined to be the cause, a treatment plan including physical therapy, stretching, and pain medication will be created.

[1294] Step 6:

[1295] Server: Sends the generated treatment plan to the patient's device, along with a detailed description of each item included in the plan.

[1296] Step 7:

[1297] Terminal: Displays the received treatment plan to the user, providing an interface for the user to review the contents and enter feedback.

[1298] Step 8:

[1299] User: Review the proposed treatment plan and approve or enter questions or feedback.

[1300] Step 9:

[1301] Device: Sends user approval and feedback to the server.

[1302] Step 10:

[1303] Server: Receives user feedback and modifies the treatment plan as needed, which may require reanalysis.

[1304] Step 11:

[1305] User: Based on the proposed treatment plan, the user selects the appropriate treatment facility from a list provided by the system. For example, if physical therapy is required, the user selects a specialized facility.

[1306] Step 12:

[1307] Terminal: Sends information about the selected treatment facility to the server.

[1308] Step 13:

[1309] Server: Receives the treatment facility selection information, sends a reservation request to the facility, and once the reservation is confirmed, provides the final reservation information to the user.

[1310] Step 14:

[1311] User: Once the actual treatment begins, the user periodically enters progress information and pain level into the system. For example, "Today's pain level is 3 / 10."

[1312] Step 15:

[1313] Device: Sends progress information to the server in real time.

[1314] Step 16:

[1315] Server: Analyzes progress information and evaluates the effectiveness of the treatment plan. Readjusts the treatment plan if necessary and sends new instructions to the user.

[1316] Step 17:

[1317] User: Upon completion of treatment, complete an overall treatment evaluation, for example, entering a final rating such as "The treatment was very effective."

[1318] Step 18:

[1319] Device: Sends rating information to the server.

[1320] Step 19:

[1321] Server: The received evaluation information is stored in a database, and statistical analysis is performed using AI algorithms to optimize future treatment plans.

[1322] In this way, the system allows patients to receive the treatment that is most suitable for them quickly and efficiently, and achieves improvement in their symptoms.

[1323] Example 1

[1324] 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."

[1325] It is difficult to effectively collect and analyze patient symptom information, including lower back pain, and provide optimal treatment plans. Continuously updating treatment plans based on treatment progress is also time-consuming, requiring patients to accurately input symptom information and properly manage their progress. Furthermore, automating the selection and reservation of appropriate treatment facilities is necessary to reduce the burden on patients. To address these challenges, a system is needed that integrates functions such as efficient collection and analysis of patient information, generation and notification of optimal treatment plans, selection and reservation of treatment facilities, and management of treatment progress.

[1326] 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.

[1327] In this invention, the server includes an update unit for receiving treatment progress information from a patient and updating the treatment plan, a storage unit for storing the received patient symptom information in a database, an AI analysis unit for analyzing the patient symptom information stored in the storage unit using natural language processing and machine learning, and a notification system for generating and notifying a treatment plan based on the analysis results obtained by the AI ​​analysis unit. This makes it possible to efficiently collect and analyze patient symptom information, generate and notify an optimal treatment plan, and continuously update the treatment plan according to the progress of treatment. Furthermore, patients can select and make reservations at appropriate treatment facilities through the system, thereby reducing their burden.

[1328] "Patient symptom information" refers to all information entered by the patient themselves, such as symptoms, medical history, and lifestyle habits.

[1329] "Input means" refers to a device or software such as a dedicated application or web form that allows a patient to input their symptom information.

[1330] "Receiving means" refers to a system or process for receiving and storing patient symptom information sent from the input means.

[1331] The "storage means" refers to a method or device for appropriately storing the patient symptom information received by the receiving means in a database.

[1332] "Analysis means" means a system having processing capabilities for analyzing received and stored patient symptom information, and includes methods using natural language processing and machine learning, among others.

[1333] "AI analysis means" refers to means for analyzing a patient's symptom information using natural language processing and machine learning algorithms to evaluate the symptoms and identify their causes.

[1334] "Generator" refers to an algorithm or system for generating an individualized treatment plan based on the analyzed data.

[1335] "Notification means" refers to a method for informing a patient of the treatment plan created by the generation means, and includes email, SMS, in-app notification, etc.

[1336] "Selection method" refers to the system or process for selecting an appropriate treatment facility based on the notified treatment plan.

[1337] "Appointment Facility" refers to a method or system for automatically scheduling appointments with selected treatment facilities.

[1338] "Updater" refers to a system for receiving treatment progress information from a patient and modifying or adjusting the treatment plan accordingly.

[1339] A "notification system" refers to a series of processes and devices that generate a treatment plan based on the analysis results obtained by AI analysis means and notify the patient of this plan.

[1340] This invention is a system that provides personalized treatment plans specifically tailored to patients with lower back pain. The system aims to provide optimal treatment by automating everything from inputting patient information to managing treatment progress.

[1341] Hardware and software used

[1342] This system is configured using the following hardware and software.

[1343] Hardware used

[1344] Server: A server that provides high-performance data processing and storage (e.g., a virtual server for cloud services)

[1345] Devices: PCs, tablets, smartphones, etc. for user interfaces

[1346] Software used

[1347] Database: A relational database such as MySQL or PostgreSQL

[1348] Natural Language Processing (NLP) libraries: spaCy and NLTK

[1349] Machine learning frameworks: TensorFlow and PyTorch

[1350] Communication protocol: HTTPS

[1351] System configuration and functions

[1352] Entering patient information

[1353] User: The user accesses a dedicated application or web form and enters information about their symptoms, medical history, lifestyle habits, etc. For example, they enter information such as, "I have pain in the left side of my lower back, especially when I wake up in the morning."

[1354] Terminal: The entered information is formatted into JSON format and sent to the server using a secure communication protocol (HTTPS).

[1355] Receiving and storing patient information

[1356] Server: Validates the received patient symptom information and stores it securely in a database (e.g., MySQL database).

[1357] Patient information analysis

[1358] Server: Analyzes stored patient information using AI algorithms. This analysis uses natural language processing (spaCy) and machine learning (TensorFlow). For example, if a patient says, "My lower back hurts and it's hard for me to get up in the morning," the system evaluates the possibility of muscle tension or a herniated disc.

[1359] Treatment plan generation

[1360] Server: Generates a personalized treatment plan based on the analysis results, including recommendations for physical therapy, medication, and stretching.

[1361] Treatment plan notification

[1362] Server: Sends the generated treatment plan to the user's device via email, SMS, in-app notifications, etc.

[1363] Terminal: Displays the received treatment plan to the user.

[1364] Selecting and booking a treatment facility

[1365] User: Follows the proposed treatment plan and selects the appropriate treatment facility from the list provided by the system.

[1366] Server: Provides a list of treatment facilities, receives the user's selection, and confirms the appointment.

[1367] Treatment progress management and feedback

[1368] User: Once actual treatment begins, the user will periodically enter progress information and pain level into the system.

[1369] Device: This progress information is sent to the server in real time.

[1370] Server: Analyzes progress information and updates treatment plans as needed.

[1371] Treatment evaluation and optimization

[1372] User: Upon completion of treatment, complete a full treatment evaluation.

[1373] Device: Sends rating information to the server.

[1374] Server: Analyzes the received evaluation information and uses it to optimize future treatment plans.

[1375] Prompt Sentence Examples

[1376] "Please tell me more about your back pain symptoms."

[1377] Please enter some information about your lifestyle.

[1378] "Review the treatment plan and provide feedback."

[1379] In this way, patients can receive the treatment that is best suited to them quickly and efficiently, resulting in an improvement in their symptoms.

[1380] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1381] Step 1:

[1382] Entering patient information

[1383] User: Accesses a dedicated application or web form and enters information about their symptoms, medical history, lifestyle habits, etc. For example, they enter information such as "I have lower back pain" or "I have severe pain when I wake up in the morning."

[1384] Input: Patient symptom information, medical history, and lifestyle data.

[1385] Output: Formatted symptom information in JSON format.

[1386] Terminal: Converts the input information into JSON format and sends it to the server using a secure communication protocol (e.g. HTTPS).

[1387] Step 2:

[1388] Receiving and storing patient information

[1389] Server: Validates incoming patient symptom information and stores it securely in a database. For example, validates patient information and then executes an INSERT query into a MySQL database.

[1390] Input: Formatted symptom information (JSON format) sent from the device.

[1391] Output: Patient information stored in a database.

[1392] Specific operation: The server detects the receiving trigger, performs data validation, and if the data is correct, executes an INSERT query to save it to the database.

[1393] Step 3:

[1394] Patient information analysis

[1395] Server: Analyzes stored patient information using AI algorithms. Classifies symptoms using natural language processing and identifies causes using machine learning. For example, analyzes symptoms using an NLP model (e.g., spaCy) and diagnoses using a machine learning model (e.g., TensorFlow).

[1396] Input: Patient information stored in the database.

[1397] Output: Parsed symptom information and diagnosis results.

[1398] How it works: The server retrieves patient information from the database, runs it through an NLP model to classify symptoms, then invokes a machine learning model to generate a diagnosis.

[1399] Step 4:

[1400] Treatment plan generation

[1401] Server: Based on the analysis results, it generates an individualized treatment plan, which may include physical therapy, medication, stretching, etc.

[1402] Input: Parsed symptom information and diagnosis results.

[1403] Output: Individualized treatment plan.

[1404] Specific operation: Based on the analysis results, the optimal plan is generated by combining treatment options. A template engine is used to generate the plan in a format that is easy for users to view.

[1405] Step 5:

[1406] Treatment plan notification

[1407] Server: Sends the generated treatment plan to the user's device via email, SMS, in-app notifications, etc.

[1408] Input: Individualized treatment plan.

[1409] Output: Notification to the user.

[1410] Terminal: Displays the received treatment plan to the user.

[1411] Specific operation: The server calls the notification system and sends the treatment plan in the appropriate format. The device receives the notification and displays it to the user as a pop-up message or similar.

[1412] Step 6:

[1413] Selecting and booking a treatment facility

[1414] User: Follows the proposed treatment plan and selects the appropriate treatment facility from the list provided by the system.

[1415] Input: Proposed treatment plan and list of treatment facilities.

[1416] Output: Selected treatment facilities.

[1417] Server: Provides a list of treatment facilities, receives the user's selection, and confirms the appointment, e.g., by calling a booking API to confirm the appointment.

[1418] What happens: The server sends a POST request to the reservation endpoint and receives confirmation of the reservation.

[1419] Step 7:

[1420] Treatment progress management and feedback

[1421] User: Once the actual treatment begins, the user periodically enters progress information and pain level into the system, for example, providing feedback such as "Today the pain has decreased."

[1422] Input: Treatment progress information, pain level.

[1423] Output: Progress information sent to the system.

[1424] Device: Sends progress information to the server in real time.

[1425] Specific operation: The device detects user input and periodically sends progress information to the server.

[1426] Step 8:

[1427] Treatment evaluation and optimization

[1428] User: Upon completion of treatment, complete an overall treatment evaluation, such as "My pain is almost gone after treatment."

[1429] Input: Treatment evaluation information.

[1430] Output: The rating information sent to the server.

[1431] Device: Sends rating information to the server.

[1432] Server: Analyzes the received evaluation information and uses it to optimize future treatment plans.

[1433] How it works: The server analyzes the evaluation information in real time and stores it in a feedback database. This data is then used to optimize the next treatment plan.

[1434] (Application example 1)

[1435] 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."

[1436] Health management is extremely important for security staff, as they are subjected to high physical and mental strain during their work. However, there is a lack of a system to provide appropriate treatment plans tailored to individual health conditions, making effective health management difficult. This can result in a decline in security staff performance and have a negative impact on the overall security level.

[1437] 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.

[1438] In this invention, the server includes an input means for inputting symptom information of a patient, a receiving means for receiving the symptom information of the patient input from the input means, an analysis means for analyzing the symptom information of the patient received by the receiving means, a generation means for generating an individual treatment plan based on the analysis results obtained by the analysis means, a notification means for notifying the patient of the treatment plan generated by the generation means, a selection means for selecting an appropriate treatment facility based on the treatment plan notified by the notification means, a reservation means for making a reservation at the treatment facility selected by the selection means, an update means for receiving treatment progress information from the patient and updating the treatment plan, a means for inputting and analyzing health information of security staff and generating individual health management plans, and a means for monitoring the health status of the security staff and managing and optimizing their progress in real time, thereby individually optimizing the health status of the security staff, improving performance and ensuring safety.

[1439] "Patient information" refers to information necessary for treatment, such as the patient's symptoms, medical history, and lifestyle habits.

[1440] "Input means" refers to a device or interface that allows a patient or a medical professional to input symptom information into the system.

[1441] The "receiving means" is a function or device for receiving information input through the input means.

[1442] The "analysis means" refers to a device or algorithm that analyzes the information obtained by the receiving means and evaluates symptoms and identifies causes based on the content of the information.

[1443] The "generation means" refers to a function or process that creates an individual treatment plan based on the analysis results obtained by the analysis means.

[1444] The "notification means" is a method or device for informing the patient of the treatment plan created by the generation means.

[1445] "Selection means" is a function of the system for selecting an appropriate treatment facility based on a treatment plan.

[1446] "Reservation means" refers to a function or mechanism for making a reservation at a treatment facility selected by the selection means.

[1447] "Update means" is a function for receiving information on the patient's treatment progress and updating and adjusting the treatment plan based on that information.

[1448] "Security staff health information" refers to data indicating the health status of security staff, including symptoms, medical history, exercise habits, etc.

[1449] "Monitoring means" is a function for monitoring the health status of security staff in real time and managing progress.

[1450] A "health management plan" is a specific instruction or plan for maintaining or improving the health of security personnel that is tailored to each individual based on analytical methods.

[1451] This invention is a system that inputs and analyzes the health information of patients and security staff, and provides individualized treatment or health management plans. This system is designed to utilize hardware and software to enable patients and security staff to receive care efficiently.

[1452] About program processing

[1453] The program of this system has the function of performing the following main processes. First, it uses the input means to collect symptom information and health information of patients and security staff. Next, it uses the receiving means to send this information to the server and store it. The server then analyzes the received information using the analysis means and generates an individual treatment plan or health management plan based on the results.

[1454] The generated plan is communicated to the user through a notification means. The user can review the plan and select an appropriate treatment facility. The selection means automatically makes a reservation at the facility selected by the user. In addition, the system also includes an update means for receiving progress information from the user in real time and updating the treatment plan as necessary.

[1455] Hardware and Software Use

[1456] Server: Uses AWS or Google Cloud to store data, analyze data, and generate plans.

[1457] AI models: Using natural language processing (NLP) and machine learning (e.g., TensorFlow and PyTorch).

[1458] Devices: Smartphones, smart glasses, head-mounted displays, etc.

[1459] Data processing and calculation

[1460] 1. Input method:

[1461] Symptom information and health information are entered using a device (such as a smartphone). For example, a patient enters their lower back pain symptoms.

[1462] 2. Receiving means:

[1463] The server receives the information sent from the device and stores it in a database via a secure communication protocol (e.g., HTTPS).

[1464] 3. Analysis method:

[1465] The server analyzes the stored information and uses NLP and machine learning to evaluate symptoms. For example, if someone says, "My lower back hurts and it's hard to get up in the morning," it will evaluate the possibility of muscle tension or a herniated disc.

[1466] 4. Generation means:

[1467] Based on the analysis results, a personalized treatment or health management plan is generated, which may include, for example, physical therapy, medication, and stretching.

[1468] 5. Means of notification:

[1469] The generated plan is notified to the user's terminal so that the user can check it.

[1470] 6. Selection method:

[1471] Based on the proposed treatment plan, the user selects an appropriate treatment facility from a list provided by the system.

[1472] 7. Reservation Method:

[1473] Automatically send appointment requests to selected treatment facilities.

[1474] 8. Update method:

[1475] Progress information from the user is sent to the server in real time, and the AI ​​updates the treatment plan as needed.

[1476] Examples of concrete examples and prompts

[1477] Specific examples

[1478] User input: "My lower back hurts from standing for long periods of time every day, especially the right side."

[1479] AI analysis result: "It's likely due to muscle tension on the right side."

[1480] Treatment plan: "Physical therapy three times a week and simple stretching exercises."

[1481] Prompt Sentence Examples

[1482] User input: "I have pain on the left side of my lower back, especially when I wake up in the morning."

[1483] The system responds: "This case may be due to muscle tension. We've generated a treatment plan focused on physical therapy."

[1484] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1485] Step 1:

[1486] Users use a smartphone or dedicated device to input symptom information or health information. The input information is sent to the system. Specifically, a patient might input, "I have pain in the left side of my lower back, especially when I wake up in the morning."

[1487] Input: Symptom information and health information

[1488] Output: Sending input information

[1489] Step 2:

[1490] The device formats the entered information and sends it to the server using a secure communication protocol (e.g., HTTPS). During this step, encryption is used to prevent data tampering or leakage.

[1491] Input: Formatted input information

[1492] Output: Sending encrypted data

[1493] Step 3:

[1494] The server receives the transmitted information using the receiving means and stores it in a database. Upon receiving the information, it checks the integrity of the data and performs error checks as necessary.

[1495] Input: Encrypted data

[1496] Output: Information stored in the database

[1497] Step 4:

[1498] The server then uses analytics to analyze the stored information. It uses natural language processing (NLP) and machine learning algorithms to assess symptoms and identify causes. For example, if someone says, "My lower back hurts and it's hard for me to get up in the morning," it can assess whether they have muscle tension or a herniated disc.

[1499] Input: Stored patient information

[1500] Output: Analysis results

[1501] Step 5:

[1502] The server generates an individualized treatment plan based on the analysis results using the generation means. The generated treatment plan includes physical therapy, drug therapy, stretching, etc. For example, a plan including "physical therapy three times a week and simple stretching exercises" is generated based on the analysis results.

[1503] Input: Analysis results

[1504] Output: Individual treatment plan

[1505] Step 6:

[1506] The server uses the notification means to send the generated treatment plan to the user's terminal, and the user receives the notification and checks the treatment plan.

[1507] Input: Individual Treatment Plan

[1508] Output: User notification

[1509] Step 7:

[1510] The user checks the notified treatment plan and selects an appropriate treatment facility from the list provided by the system. The information of the selected facility is sent to the system.

[1511] Input: Confirm treatment plan, select treatment facility

[1512] Output: Send selected treatment facility information

[1513] Step 8:

[1514] The server automatically sends an appointment request to the treatment facility selected by the user using the selection means, and a confirmation message is sent to the user once the appointment is completed.

[1515] Input: Selected Treatment Facility Information

[1516] Output: Reservation confirmation message

[1517] Step 9:

[1518] Users periodically enter progress information into the system, such as "Today my pain is reduced."

[1519] Input: Progress information

[1520] Output: Sending input information

[1521] Step 10:

[1522] The device formats the progress information and sends it to the server over a secure communication protocol.

[1523] Input: Formatted progress information

[1524] Output: Sending encrypted data

[1525] Step 11:

[1526] The server receives progress information and uses AI to update the treatment plan, recommending new instructions or changes based on the analysis results.

[1527] Input: Progress information

[1528] Output: Updated treatment plan

[1529] Step 12:

[1530] The server then notifies the user's device of the updated treatment plan again, continuing optimal treatment according to the patient's progress.

[1531] Input: Updated treatment plan

[1532] Output: User notification

[1533] 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.

[1534] This invention is a system that provides personalized treatment plans specifically tailored to patients with lower back pain, and includes a function that recognizes the patient's emotions and reflects them in the treatment plan. The system aims to provide optimal treatment by automating everything from inputting patient information to managing the progress of treatment.

[1535] System Overview

[1536] The system is configured using the following means:

[1537] 1. A means of patient information entry: A dedicated app or web form for patients to enter their symptoms, medical history, lifestyle information, and even emotional state.

[1538] 2. Receiving means: A server for receiving and storing the entered information.

[1539] 3. Analysis method: The received information is analyzed using AI algorithms and an emotion engine to evaluate symptoms and identify causes.

[1540] 4. Generation method: Generate an individual treatment plan based on the analysis results.

[1541] 5. Notification Methods: Methods for informing the patient of the generated treatment plan.

[1542] 6. Selection tools: Tools to select the appropriate treatment facility for pain relief.

[1543] 7. Booking Method: A method for automatically scheduling appointments with selected treatment facilities.

[1544] 8. Updates: Receives patient progress information and the AI ​​updates the treatment plan as needed.

[1545] 9. Emotion Engine: Analyzes the patient's written and spoken information, assesses their emotional state, and provides information to the analysis and generation means.

[1546] Natural language programming

[1547] 1. Enter patient information

[1548] User: Accesses a dedicated app or web form and enters information about their symptoms, medical history, lifestyle habits, and emotional state. For example, they might enter, "I have pain in the left side of my lower back, especially when I wake up in the morning. Lately, the pain has been making me feel stressed."

[1549] 2. Receiving patient information

[1550] Terminal: Formats the entered patient and emotion information and sends it to the server using a secure communication protocol (e.g., HTTPS).

[1551] 3. Patient Information Storage

[1552] Server: Stores the received patient and emotion information in a database and performs data integrity checks, for example, checking whether all required fields have been filled in.

[1553] 4. Analysis of patient information and emotional information

[1554] Server: Analyzes patient information and emotional information stored in a database using AI algorithms and an emotion engine. Using natural language processing (NLP) technology, details of symptoms and emotions are extracted from input text and compared with a case database to make a diagnosis. For example, the emotion engine analyzes the information that "pain causes stress" and determines that stress relief should also be included in treatment.

[1555] 5. Treatment plan generation

[1556] Server: Based on the analysis results, it generates an individualized treatment plan. For example, if muscle tension is determined to be the cause, it will create a treatment plan that includes physical therapy, stretching, prescription painkillers, and relaxation techniques to reduce stress.

[1557] 6. Notification of Treatment Plan

[1558] Server: Sends the generated treatment plan to the patient's device, along with a detailed explanation of each item in the plan and customized feedback based on emotions.

[1559] 7. Confirmation of treatment plan

[1560] Terminal: Displays the received treatment plan to the user, providing an interface for the user to review the contents and enter feedback.

[1561] User: Review the proposed treatment plan and approve or enter questions or feedback.

[1562] 8. Selecting and booking a treatment facility

[1563] User: Based on the proposed treatment plan, the user selects the appropriate treatment facility from a list provided by the system. For example, if physical therapy is required, the user selects a specialized facility.

[1564] Terminal: Sends information about the selected treatment facility to the server.

[1565] Server: Receives the treatment facility selection information, sends a reservation request to the facility, and once the reservation is confirmed, provides the final reservation information to the user.

[1566] 9. Treatment progress management and feedback

[1567] User: Once the actual treatment begins, the user periodically enters progress information, pain level, and emotional state into the system. For example, "Today my pain has decreased, but I still feel stressed."

[1568] Device: Sends progress and emotion information to the server in real time.

[1569] Server: Analyzes progress and emotional information to evaluate the effectiveness of the treatment plan, readjusts the treatment plan if necessary, and sends new instructions to the user based on their emotional state.

[1570] 10. Treatment evaluation and optimization

[1571] User: Upon completion of treatment, complete an overall treatment evaluation. For example, enter a final rating such as, "The treatment was very effective, but I would like to see more stress reduction techniques added."

[1572] Device: Sends rating information to the server.

[1573] Server: The received evaluation and emotional information is stored in a database, and statistical analysis is performed using an AI algorithm to optimize future treatment plans.

[1574] In this way, patients can receive the treatment that is best suited to them quickly and efficiently, and the system provides emotional support as well as symptom improvement.

[1575] The processing flow will be explained below.

[1576] Step 1:

[1577] User: Accesses a dedicated app or web form and enters detailed information such as their symptoms, medical history, lifestyle habits, emotional state, etc. An example entry is, "I have pain on the left side of my lower back, especially when I wake up in the morning. Lately, the pain has been making me feel stressed."

[1578] Step 2:

[1579] Terminal: Formats the entered patient and emotion information and sends it to the server using a secure communication protocol (e.g., HTTPS).

[1580] Step 3:

[1581] Server: Saves the received patient information and emotion information in the database. When saving, checks whether all required fields have been entered.

[1582] Step 4:

[1583] Server: Analyzes patient information and emotional information stored in a database using AI algorithms and an emotion engine. Using natural language processing (NLP) technology, details of symptoms and emotions are extracted from input text and compared with a case database to make a diagnosis. For example, the emotion engine analyzes the information that "pain causes stress" and determines that stress management should also be included in the treatment plan.

[1584] Step 5:

[1585] Server: Based on the analysis results, it generates an individualized treatment plan. Specifically, if muscle tension is determined to be the cause, it creates a treatment plan that includes physical therapy, stretching, prescription painkillers, and relaxation techniques for stress management.

[1586] Step 6:

[1587] Server: Sends the generated treatment plan to the patient's device, including detailed explanations of each item and customized feedback based on emotions.

[1588] Step 7:

[1589] Terminal: Displays the received treatment plan to the user, using an interface that allows the user to review the contents and provide feedback.

[1590] Step 8:

[1591] User: Review the proposed treatment plan and approve it if it is acceptable, as well as provide any questions or feedback.

[1592] Step 9:

[1593] Terminal: Sends user approvals and feedback to the server in a secure format.

[1594] Step 10:

[1595] Server: Receives user feedback and modifies the treatment plan as needed, which may require reanalysis.

[1596] Step 11:

[1597] User: Based on the proposed treatment plan, the user selects the appropriate treatment facility from a list provided by the system. For example, if physical therapy is required, the user selects a specialized facility.

[1598] Step 12:

[1599] Terminal: Sends information about the selected treatment facility to the server.

[1600] Step 13:

[1601] Server: Receives the treatment facility selection information, sends a reservation request to the facility, and returns the reservation confirmation to the user.

[1602] Step 14:

[1603] User: Once the actual treatment begins, the user periodically enters progress information, pain level, and emotional state into the system. For example, "Today my pain has decreased, but I still feel stressed."

[1604] Step 15:

[1605] Device: Sends progress and emotion information to the server in real time.

[1606] Step 16:

[1607] Server: Analyzes progress and emotional information to evaluate the effectiveness of the treatment plan, readjusts the treatment plan if necessary, and sends new instructions to the user based on their emotional state.

[1608] Step 17:

[1609] User: Upon completion of treatment, complete an overall treatment evaluation. For example, enter a final rating such as, "The treatment was very effective, but I would like to receive more advice on stress management."

[1610] Step 18:

[1611] Terminal: Sends evaluation information and emotion information to the server.

[1612] Step 19:

[1613] Server: The received evaluation and emotional information is stored in a database and statistically analyzed using an AI algorithm, which is used to optimize future treatment plans.

[1614] In this way, patients can receive the treatment that is best suited to them quickly and efficiently, and the system provides emotional support as well as symptom improvement.

[1615] Example 2

[1616] 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."

[1617] Conventional lower back pain treatment systems generate treatment plans based solely on the patient's symptom information, making it difficult to provide optimal treatment plans that take into account the emotional state and lifestyle habits of each individual patient. In particular, when emotional states affect pain and stress, treatment plans that ignore this factor are unable to achieve sufficient results. Furthermore, the lack of a function to update treatment plans while reflecting treatment progress information in real time makes it difficult to maximize the effectiveness of treatment.

[1618] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes an input means for a user to input information on the patient's symptoms, medical history, lifestyle, and emotional state, a receiving means for receiving the input symptom information and emotional information of the patient, an analyzing means for analyzing the received symptom information and emotional information of the patient, a generating means for generating an individualized treatment plan based on the analysis results, a notifying means for notifying the patient of the generated treatment plan, a selecting means for selecting an appropriate treatment facility based on the notified treatment plan, a booking means for making a booking at the selected treatment facility, and an updating means for receiving treatment progress information and emotional information from the patient and updating the treatment plan. This makes it possible to provide an individualized treatment plan that takes into account the patient's emotional state and lifestyle, and to provide a treatment plan that is optimized in real time according to the progress of treatment.

[1619] A "user" is a person who uses a dedicated app or web form to enter information about their symptoms, medical history, lifestyle habits, and emotional state.

[1620] An "input means" is an application or web form used by a user to input information about a patient's symptoms, medical history, lifestyle habits, and emotional state.

[1621] The "receiving means" is a component for receiving symptom information and emotion information of a patient transmitted from the input means.

[1622] The "analysis means" is a component that uses an AI algorithm and a natural language processing engine to analyze the received symptom information and emotional information of the patient, and evaluate the symptoms and identify the cause.

[1623] The "generation means" is a component for generating an individual treatment plan based on the analysis results.

[1624] The "notification means" is a component for notifying the patient of the treatment plan generated by the generation means.

[1625] The "selection means" is a component for selecting an appropriate treatment facility based on the notified treatment plan.

[1626] The "reservation means" is a component for making a reservation at a selected treatment facility.

[1627] The "updater" is a component for receiving treatment progress and emotional information from the patient and updating the treatment plan.

[1628] "Patient symptom information" is information entered by the patient about their symptoms, specifically the location of the pain, the degree of pain, the circumstances under which the pain occurs, and the like.

[1629] "Emotional information" is information about the patient's emotional state, specifically a detailed description of stress and physical and mental state.

[1630] An "AI algorithm" is an algorithm that uses artificial intelligence technology to analyze data and generate diagnoses and treatment plans.

[1631] A "natural language processing engine" is a technology that analyzes the meaning and emotions of sentences entered by patients and extracts details.

[1632] This invention is a system that provides personalized treatment plans specifically tailored to patients with lower back pain, and includes a function that recognizes the patient's emotions and reflects them in the treatment plan. The system aims to provide optimal treatment by automating everything from inputting patient information to managing the progress of treatment.

[1633] System configuration

[1634] This system is configured using the following hardware and software.

[1635] 1. Input method:

[1636] Users use a dedicated app or web form to enter information about their symptoms, medical history, lifestyle habits, and emotional state. For example, they might enter, "I have pain in the left side of my lower back, especially when I wake up in the morning. Lately, the pain has been making me feel stressed."

[1637] 2. Receiving means:

[1638] The terminal formats and transmits the entered patient and emotion information to the server using a secure communication protocol (e.g., HTTPS).

[1639] 3. Preservation means:

[1640] The server stores the received patient information and emotion information in a database and checks the integrity of the data, for example, whether all required fields have been filled in.

[1641] 4. Analysis method:

[1642] The server analyzes the information stored in the database using AI algorithms (for example, TensorFlow or PyTorch) and natural language processing engines (for example, IBM Watson NLU). Using natural language processing technology, it extracts details of symptoms and emotions from the text entered by the patient and compares them with a case database to make a diagnosis. For example, based on the information that "pain causes stress," it determines that stress relief should also be included in treatment.

[1643] 5. Generation means:

[1644] The server generates a personalized treatment plan based on the analysis results. For example, if muscle tension is determined to be the cause, the plan will include physical therapy, stretching, prescription painkillers, and relaxation techniques to reduce stress.

[1645] 6. Means of notification:

[1646] The server sends the generated treatment plan to the patient's device, for example, by using a REST API to send the treatment plan information in JSON format and also provides a feedback function.

[1647] 7. MEANS OF SELECTION AND RESERVATION:

[1648] The user selects a treatment facility from a list provided by the system based on the proposed treatment plan and makes an appointment at that facility, for example, by selecting a physical therapy facility from a list and transmitting the selection information to the server.

[1649] The server receives the selected treatment facility information, sends a reservation request to the facility, and returns the final reservation information to the terminal once the reservation is confirmed.

[1650] 8. Update method:

[1651] The user periodically enters information about their treatment progress, pain level, and emotional state into the system, for example, "Today my pain has decreased, but I still feel stressed."

[1652] The terminal transmits the input progress information and emotion information to the server in real time.

[1653] The server analyzes the received progress and emotion information to evaluate the effectiveness of the treatment plan, readjusting the treatment plan if necessary, and sending new instructions to the user.

[1654] Specific examples

[1655] We will explain in detail a scene where a user inputs information using a dedicated app and a treatment plan is generated and notified.

[1656] The user opens the dedicated app and enters, "I have severe pain in my lower back, especially when I wake up in the morning. This pain has been causing me a lot of stress lately."

[1657] The terminal formats the entered information and sends it to the server using HTTPS.

[1658] The server stores the input data in a database and checks the integrity of the information.

[1659] The server uses NLP and an emotion engine to analyze the stored information and recognize that stress is part of the cause of the pain.

[1660] The server generates a personalized treatment plan and suggests a treatment plan to the user that includes relaxation techniques and stretches.

[1661] The server transmits the generated treatment plan to the user's terminal.

[1662] The user reviews and approves the proposed treatment plan.

[1663] The user selects a physical therapy facility based on the proposed treatment plan and schedules an appointment with that facility.

[1664] Users enter their treatment progress into the app and report changes in stress levels and pain.

[1665] The server analyzes the entered information and sends suggested treatment plan modifications to the user.

[1666] Prompt Sentence Examples

[1667] "Generate a personalized treatment plan based on the information below.

[1668] Symptoms: Lower back pain, especially when waking up in the morning.

[1669] Emotional state: Feeling stressed.

[1670] Lifestyle: Sitting for long periods at work.”

[1671] In this way, the system can provide a personalized treatment plan that takes into account the patient's symptoms and emotional state, and provides an optimized treatment plan in real time as the treatment progresses.

[1672] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1673] Step 1:

[1674] Users access a dedicated app or web form and enter information about their symptoms, medical history, lifestyle habits, and emotional state. Examples of input data include, "I have pain in the left side of my lower back, especially when I wake up in the morning. Lately, the pain has been making me feel stressed." This allows detailed patient information to be collected.

[1675] Step 2:

[1676] The terminal converts the input patient information and emotion information into an appropriate format (e.g., JSON format) and sends it to the server using a secure communication protocol such as HTTPS. Specifically, the terminal integrates the patient information and emotion information and communicates them as a series of JSON data. This prepares the server to receive the patient information.

[1677] Step 3:

[1678] The server stores the received patient and emotion information in a database. As it stores the information, it verifies data integrity, checks for required fields, and ensures the data format is correct. For example, it runs validation scripts to ensure all required fields are filled in. This ensures accurate information.

[1679] Step 4:

[1680] The server uses AI algorithms and natural language processing engines (e.g., TensorFlow, IBM Watson NLU) to analyze the stored patient information and emotional information. Input: Patient information and emotional information stored in a database. Processing: Natural language processing technology is used to analyze the input data and extract details of symptoms and emotions. Output: The analysis results in an evaluation of specific symptoms and emotional states. Specifically, detailed evaluations of pain location, intensity, stress levels, etc. are provided.

[1681] Step 5:

[1682] The server generates an individualized treatment plan based on the analysis results. Input: Analysis results. Processing: Based on the analysis results, the optimal treatment plan for each patient is generated. An AI algorithm is used to create a treatment plan that includes physical therapy, stretching, drug therapy, stress relief techniques, etc. Output: The generated individualized treatment plan. For example, if muscle tension is determined to be the cause, suggestions such as physical therapy, stretching, prescription painkillers, and relaxation techniques may be suggested.

[1683] Step 6:

[1684] The server sends the generated treatment plan to the patient's device. Input: Generated treatment plan. Processing: Package the treatment plan, its details, and customized feedback based on emotions in JSON format. Output: Packaged treatment plan information is sent to the patient's device. This allows the user to check their treatment plan.

[1685] Step 7:

[1686] The terminal displays the received treatment plan to the user. Input: Treatment plan information sent from the server. Processing: Provides an interface that displays the received information to the user in an appropriate format. Output: The user can check the details of the treatment plan and approve or enter feedback. For example, when the user checks the treatment plan on the screen and clicks the "Approve" button, the information is sent to the server.

[1687] Step 8:

[1688] Based on the proposed treatment plan, the user selects an appropriate treatment facility from a list provided by the system. For example, if physical therapy is required, the user selects a specialized facility. Input: A list of treatment facilities provided as candidates. Processing: The user selects the most suitable treatment facility and determines its information. Output: Information on the selected treatment facility.

[1689] Step 9:

[1690] The terminal sends information about the selected treatment facility to the server. Input: Information about the selected treatment facility. Processing: The selection information is sent to the server in JSON format. Output: The server receives the information and prepares to proceed to the next step. This allows the selection information about the selected treatment facility to reach the server.

[1691] Step 10:

[1692] The server receives the treatment facility selection information and sends a reservation request to that facility. Once the reservation is confirmed, the final reservation information is fed back to the patient's terminal. Input: Information of the selected treatment facility. Processing: Sends a reservation request to the facility and waits for confirmation. Output: Once the reservation is confirmed, the details are notified to the user. This allows the user to receive the confirmed reservation information.

[1693] Step 11:

[1694] Even after the actual treatment has begun, the user periodically inputs progress information, pain level, and emotional state into the system. For example, the user might input, "Today the pain has decreased, but I still feel stressed." Input: Treatment progress information, pain level, emotional state, etc. Processing: Information is periodically updated and sent to the system. Output: Progress information is sent to the server.

[1695] Step 12:

[1696] The terminal sends progress information and emotional information to the server in real time. Input: Progress information and emotional information entered by the user. Processing: This information is formatted and sent in real time. Output: The server receives this information. This allows the server to grasp the patient's latest condition.

[1697] Step 13:

[1698] The server analyzes the progress information and emotional information to evaluate the effectiveness of the treatment plan. It readjusts the treatment plan as needed and sends new instructions to the user. Input: Progress information and emotional information. Processing: Using an AI algorithm, it analyzes the progress information and emotional information and evaluates the effectiveness of the treatment plan. Output: A new treatment plan and instructions with any necessary readjustments are generated and sent to the user. This optimizes the treatment plan.

[1699] In this way, the system provides an individualized treatment plan that takes into account the patient's symptoms and emotional state, and optimizes treatment as it progresses in real time, resulting in effective treatment.

[1700] (Application example 2)

[1701] 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."

[1702] Factory workers' physical fatigue and pain during work can reduce their work efficiency and have a negative impact on their health in the long term. Furthermore, employees' emotional state also has a significant impact on their work efficiency and health. A system is needed that provides optimal treatment plans for each employee and takes their emotions into account in real time.

[1703] 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.

[1704] In this invention, the server includes an input means for inputting symptom information and emotional information of the patient, a receiving means for receiving the symptom information and emotional information of the patient, an analyzing means for analyzing the symptom information and emotional information of the patient, a generating means for generating an optimal treatment plan based on the emotional information of the patient, a notifying means for notifying the patient of the treatment plan, an updating means for receiving treatment progress information and emotional information of the patient and updating the treatment plan, and a notifying means for notifying the smart device of the updated treatment plan. This enables factory employees to manage their own symptoms and emotions in real time and receive individually optimized treatment plans.

[1705] "Patient symptom information" is data about physical pain or discomfort experienced by an employee.

[1706] "Emotional information" is data about an employee's emotional state and mental stress level.

[1707] "Input means" refers to a digital device or interface through which employees can input their symptom and emotional information.

[1708] The "receiving means" refers to a communication technology or device for collecting the symptom information and emotion information of the patient transmitted from the input means.

[1709] "Analysis means" refers to an AI algorithm or software platform for processing and analyzing received patient symptom and emotional information.

[1710] The "generation means" refers to an algorithm or system for generating an individual treatment plan based on the analysis results obtained by the analysis means.

[1711] The "notification means" is a means for notifying employees of the generated treatment plan, and is a system for transmitting information via smart devices.

[1712] A "selection tool" is a system or interface that allows an employee to select an appropriate treatment facility or treatment option based on the notified treatment plan.

[1713] A "reservation means" is a system that automatically makes a reservation at a selected treatment facility or treatment option based on the selection means.

[1714] "Updater" means a system for receiving treatment progress and sentiment information from employees and adjusting and updating treatment plans in real time.

[1715] "Smart devices" are digital devices such as smartphones, smart glasses, and head-mounted displays used to manage and display treatment plans and notifications.

[1716] This invention is a system designed to allow factory workers to manage their own health status in real time, collecting and analyzing symptom and emotional information and presenting optimal treatment plans.

[1717] 1. System Configuration

[1718] The system consists of the following main components:

[1719] 1. An input means for inputting the patient's symptom information and emotional information.

[1720] 2. A receiving means for receiving the input information.

[1721] 3. Analytical tools for analyzing patient and emotional information.

[1722] 4. A generating means for generating a treatment plan based on the analysis results.

[1723] 5. Notification means to communicate the generated treatment plan.

[1724] 6. A selection tool to select an appropriate treatment facility based on the notified treatment plan.

[1725] 7. Booking facilities to make appointments at selected treatment facilities.

[1726] 8. A means of updating to receive treatment progress and emotional information and update the treatment plan.

[1727] 9. Notification methods to notify smart devices of updated treatment plans.

[1728] 2. Data entry and receipt

[1729] Users use smart devices (e.g., smartphones, smart glasses, head-mounted displays) to input their symptoms and emotional information. For example, they enter detailed information such as, "I have pain in the left side of my lower back. It hurts especially when I wake up in the morning. Lately, the pain has been making me feel stressed." This information is sent to the server using a secure communication protocol (e.g., HTTPS).

[1730] 3. Data Analysis and Generation

[1731] The server analyzes the received information using AI algorithms and an emotion engine. For example, it uses NLP techniques to extract symptom details and emotional state from the input text. After identifying symptoms and assessing emotional state, it generates a personalized treatment plan. This plan may include, for example, physical therapy, stress relief exercises, and pain medication prescriptions.

[1732] 4. Notification and Choice of Treatment Plan

[1733] The generated treatment plan is sent to the user's smart device via a notification means. The user receives the notification and can select an appropriate treatment facility based on the displayed plan. This selection information is then sent back to the server, and a reservation at the treatment facility is automatically made.

[1734] 5. Track and update your progress

[1735] Users periodically enter information about their treatment progress and emotions into the system, such as, "Today, my pain has decreased, but I still feel stressed." This information is sent in real time to a server, which analyzes it to evaluate the effectiveness of the treatment plan and update it as necessary.

[1736] 6. Hardware and Software Used

[1737] The system uses AI algorithms and emotion engines (including NLP technology) on smart devices (smartphones, smart glasses, head-mounted displays) and servers, and uses HTTPS as the communication protocol to ensure data security and privacy.

[1738] Examples of prompt sentences

[1739] An example of what might actually be entered is as follows:

[1740] "I have pain on the left side of my lower back, especially when I wake up in the morning. Lately the pain has been making me feel stressed."

[1741] The prompts are analyzed by the server and an optimal treatment plan is generated, enabling factory workers to manage their symptoms and emotions in real time and receive appropriate treatment early.

[1742] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1743] Program processing steps

[1744] Step 1:

[1745] Entering patient information

[1746] Users input their own symptom information and emotional information using a smart device (smartphone, smart glasses, head-mounted display).

[1747] Input: Symptom information (e.g., "I have pain in the left side of my lower back, especially when I wake up in the morning."), Emotion information (e.g., "The pain has been making me feel stressed lately.")

[1748] Data processing: Formatted as text data.

[1749] Output: The input information is stored on the device as text data.

[1750] Step 2:

[1751] Sending patient information

[1752] The terminal transmits the input information to the server via a secure communication protocol (HTTPS).

[1753] Input: Symptom and emotion information entered by the user

[1754] Data Computing: Data is encrypted using the HTTPS protocol

[1755] Output: Encrypted data sent to the server

[1756] Step 3:

[1757] Receiving and storing patient information

[1758] The server receives the data sent from the terminal and stores it in a database.

[1759] Input: Encrypted data

[1760] Data processing: Decrypting data and storing it in a database

[1761] Output: Decrypted data stored in database

[1762] Step 4:

[1763] Data analysis

[1764] The server analyzes the received data using AI algorithms and an emotion engine.

[1765] Input: Symptom information and emotion information stored in the database

[1766] Data Computing: Analyzing symptoms and emotions using natural language processing (NLP) algorithms

[1767] Output: Analysis results (symptom assessment and emotional state)

[1768] Step 5:

[1769] Treatment plan generation

[1770] The server generates an individualized treatment plan based on the analysis results.

[1771] Input: Analysis results

[1772] Data computation: Using algorithms to generate optimal treatment plans

[1773] Output: Individualized treatment plan

[1774] Step 6:

[1775] Treatment plan notification

[1776] The server transmits the generated treatment plan to the terminal and notifies the user.

[1777] Input: Individualized Treatment Plan

[1778] Data Calculation: Format treatment plans based on user settings

[1779] Output: Sent to the terminal as a notification message

[1780] Step 7:

[1781] Choosing a Treatment Facility

[1782] The user selects an appropriate treatment facility based on the notified treatment plan.

[1783] Input: Details of the notified treatment plan

[1784] Data processing: Select from a list of treatment facilities

[1785] Output: Information about the selected treatment facility is registered on the terminal.

[1786] Step 8:

[1787] Treatment facility booking

[1788] The terminal makes an appointment with the selected treatment facility.

[1789] Input: Selected treatment facility information

[1790] Data calculation: Generate reservation information and send it to the facility

[1791] Output: Appointment information is sent to treatment facility and confirmed

[1792] Step 9:

[1793] Entering treatment progress

[1794] Users periodically enter treatment progress and emotional information into the system.

[1795] Input: Treatment progress information (e.g., "Today I feel less pain, but I still feel stressed.")

[1796] Data processing: Format as text data

[1797] Output: The input data is stored on the device.

[1798] Step 10:

[1799] Treatment plan updates

[1800] The server analyzes the entered progress and emotion information and updates the treatment plan.

[1801] Input: Treatment progress information and emotional information

[1802] Data Computation: Using AI Algorithms to Optimize Treatment Plans

[1803] Output: An updated treatment plan is generated.

[1804] Step 11:

[1805] Notification of updated treatment plans

[1806] The server sends the updated treatment plan to the terminal and notifies the user.

[1807] Input: Updated treatment plan

[1808] Data calculation: Format update plan based on user settings

[1809] Output: Sent to the terminal as a notification message

[1810] 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.

[1811] 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.

[1812] 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.

[1813] [Fourth embodiment]

[1814] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1815] 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.

[1816] 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).

[1817] 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.

[1818] 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.

[1819] 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).

[1820] 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.

[1821] 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.

[1822] 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.

[1823] 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.

[1824] 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.

[1825] 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.

[1826] 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."

[1827] This invention is a system that provides personalized treatment plans specifically tailored to patients with lower back pain. The system aims to provide optimal treatment by automating everything from inputting patient information to managing treatment progress.

[1828] System Overview

[1829] The system is configured using the following means:

[1830] 1. Means for inputting patient information: A dedicated app or web form for patients to enter information about their symptoms, medical history, and lifestyle habits.

[1831] 2. Receiving means: A server for receiving and storing the entered information.

[1832] 3. Analysis method: The received information is analyzed using an AI algorithm to evaluate symptoms and identify causes.

[1833] 4. Generation method: Generate an individual treatment plan based on the analysis results.

[1834] 5. Notification Methods: Methods for informing the patient of the generated treatment plan.

[1835] 6. Selection tools: Tools to select the appropriate treatment facility for pain relief.

[1836] 7. Booking Method: A method for automatically scheduling appointments with selected treatment facilities.

[1837] 8. Updates: Receives patient progress information and the AI ​​updates the treatment plan as needed.

[1838] Natural language programming

[1839] 1. Enter patient information

[1840] User: Accesses a dedicated app or web form and enters information such as their symptoms, medical history, and lifestyle habits.

[1841] Terminal: Formats the entered information and sends it to the server using a secure communication protocol.

[1842] 2. Receiving patient information

[1843] Server: Stores the received patient information in a database.

[1844] 3. Analysis of patient information

[1845] Server: Analyzes stored patient information using AI algorithms. This analysis is done using natural language processing (NLP) and machine learning. For example, if someone says, "I have a pain in my lower back and it's hard to get up in the morning," the algorithm evaluates the possibility of muscle tension or a herniated disc.

[1846] 4. Generation of treatment plan

[1847] Server: Based on the analysis results, it generates an individualized treatment plan, which may include physical therapy, medication, stretching, etc.

[1848] 5. Notification of Treatment Plan

[1849] Server: Sends the generated treatment plan to the user's device.

[1850] Terminal: Displays the received treatment plan to the user.

[1851] User: Review the proposed treatment plan and approve or provide feedback.

[1852] 6. Selecting and booking a treatment facility

[1853] User: Based on the proposed treatment plan, select the appropriate treatment facility from the list provided by the system.

[1854] Server: Provides the list using the selection means and receives the user's selection.

[1855] Terminal: Sends an appointment request to the selected treatment facility.

[1856] 7. Treatment progress management and feedback

[1857] User: Once actual treatment begins, the user will periodically enter progress information and pain level into the system.

[1858] Device: Sends progress information to the server in real time.

[1859] Server: Analyzes progress information and makes necessary adjustments to the treatment plan.

[1860] 8. Treatment evaluation and optimization

[1861] User: Upon completion of treatment, complete a full treatment evaluation.

[1862] Device: Sends rating information to the server.

[1863] Server: Analyzes the evaluation information and uses it to optimize future treatment plans.

[1864] Specific examples

[1865] For example, a patient with back pain might use the system in the following steps:

[1866] 1. Enter patient information

[1867] User: "I have pain on the left side of my lower back, especially when I wake up in the morning."

[1868] Terminal: "Symptom information has been sent."

[1869] 2. Analyzing patient information and generating treatment plans

[1870] Server: "This case may be due to muscle tension."

[1871] Server: "I've generated a treatment plan that focuses on physical therapy."

[1872] 3. Confirm your treatment plan and make a reservation

[1873] User: "I reviewed the treatment plan and selected X Clinic."

[1874] Terminal: "Clinic information sent."

[1875] Server: "Your reservation is complete."

[1876] 4. Progress management and optimization

[1877] User: "I feel less pain today."

[1878] Terminal: "Progress information sent."

[1879] Server: "New instructions added."

[1880] In this way, the system allows patients to receive the treatment that is most suitable for them quickly and efficiently, and achieves improvement in their symptoms.

[1881] The processing flow will be explained below.

[1882] Step 1:

[1883] User: Accesses a dedicated app or web form and enters detailed information about their symptoms, medical history, lifestyle habits, etc. For example, they enter information such as, "I have pain in the left side of my lower back, especially when I wake up in the morning."

[1884] Step 2:

[1885] Terminal: Formats the entered patient information and sends it to the server using a secure communication protocol (e.g., HTTPS).

[1886] Step 3:

[1887] Server: Stores the received patient information in a database and performs data integrity checks, for example, checking that all required fields have been filled in.

[1888] Step 4:

[1889] Server: Analyzes patient information stored in a database using an AI algorithm. Specifically, it uses natural language processing (NLP) technology to extract details of symptoms from input text and compares them with a case database to make a diagnosis.

[1890] Step 5:

[1891] Server: Generates an individualized treatment plan based on the analysis results. For example, if muscle tension is determined to be the cause, a treatment plan including physical therapy, stretching, and pain medication will be created.

[1892] Step 6:

[1893] Server: Sends the generated treatment plan to the patient's device, along with a detailed description of each item included in the plan.

[1894] Step 7:

[1895] Terminal: Displays the received treatment plan to the user, providing an interface for the user to review the contents and enter feedback.

[1896] Step 8:

[1897] User: Review the proposed treatment plan and approve or enter questions or feedback.

[1898] Step 9:

[1899] Device: Sends user approval and feedback to the server.

[1900] Step 10:

[1901] Server: Receives user feedback and modifies the treatment plan as needed, which may require reanalysis.

[1902] Step 11:

[1903] User: Based on the proposed treatment plan, the user selects the appropriate treatment facility from a list provided by the system. For example, if physical therapy is required, the user selects a specialized facility.

[1904] Step 12:

[1905] Terminal: Sends information about the selected treatment facility to the server.

[1906] Step 13:

[1907] Server: Receives the treatment facility selection information, sends a reservation request to the facility, and once the reservation is confirmed, provides the final reservation information to the user.

[1908] Step 14:

[1909] User: Once the actual treatment begins, the user periodically enters progress information and pain level into the system. For example, "Today's pain level is 3 / 10."

[1910] Step 15:

[1911] Device: Sends progress information to the server in real time.

[1912] Step 16:

[1913] Server: Analyzes progress information and evaluates the effectiveness of the treatment plan. Readjusts the treatment plan if necessary and sends new instructions to the user.

[1914] Step 17:

[1915] User: Upon completion of treatment, complete an overall treatment evaluation, for example, entering a final rating such as "The treatment was very effective."

[1916] Step 18:

[1917] Device: Sends rating information to the server.

[1918] Step 19:

[1919] Server: The received evaluation information is stored in a database, and statistical analysis is performed using AI algorithms to optimize future treatment plans.

[1920] In this way, the system allows patients to receive the treatment that is most suitable for them quickly and efficiently, and achieves improvement in their symptoms.

[1921] Example 1

[1922] 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."

[1923] It is difficult to effectively collect and analyze patient symptom information, including lower back pain, and provide optimal treatment plans. Continuously updating treatment plans based on treatment progress is also time-consuming, requiring patients to accurately input symptom information and properly manage their progress. Furthermore, automating the selection and reservation of appropriate treatment facilities is necessary to reduce the burden on patients. To address these challenges, a system is needed that integrates functions such as efficient collection and analysis of patient information, generation and notification of optimal treatment plans, selection and reservation of treatment facilities, and management of treatment progress.

[1924] 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.

[1925] In this invention, the server includes an update unit for receiving treatment progress information from a patient and updating the treatment plan, a storage unit for storing the received patient symptom information in a database, an AI analysis unit for analyzing the patient symptom information stored in the storage unit using natural language processing and machine learning, and a notification system for generating and notifying a treatment plan based on the analysis results obtained by the AI ​​analysis unit. This makes it possible to efficiently collect and analyze patient symptom information, generate and notify an optimal treatment plan, and continuously update the treatment plan according to the progress of treatment. Furthermore, patients can select and make reservations at appropriate treatment facilities through the system, thereby reducing their burden.

[1926] "Patient symptom information" refers to all information entered by the patient themselves, such as symptoms, medical history, and lifestyle habits.

[1927] "Input means" refers to a device or software such as a dedicated application or web form that allows a patient to input their symptom information.

[1928] "Receiving means" refers to a system or process for receiving and storing patient symptom information sent from the input means.

[1929] The "storage means" refers to a method or device for appropriately storing the patient symptom information received by the receiving means in a database.

[1930] "Analysis means" means a system having processing capabilities for analyzing received and stored patient symptom information, and includes methods using natural language processing and machine learning, among others.

[1931] "AI analysis means" refers to means for analyzing a patient's symptom information using natural language processing and machine learning algorithms to evaluate the symptoms and identify their causes.

[1932] "Generator" refers to an algorithm or system for generating an individualized treatment plan based on the analyzed data.

[1933] "Notification means" refers to a method for informing a patient of the treatment plan created by the generation means, and includes email, SMS, in-app notification, etc.

[1934] "Selection method" refers to the system or process for selecting an appropriate treatment facility based on the notified treatment plan.

[1935] "Appointment Facility" refers to a method or system for automatically scheduling appointments with selected treatment facilities.

[1936] "Updater" refers to a system for receiving treatment progress information from a patient and modifying or adjusting the treatment plan accordingly.

[1937] A "notification system" refers to a series of processes and devices that generate a treatment plan based on the analysis results obtained by AI analysis means and notify the patient of this plan.

[1938] This invention is a system that provides personalized treatment plans specifically tailored to patients with lower back pain. The system aims to provide optimal treatment by automating everything from inputting patient information to managing treatment progress.

[1939] Hardware and software used

[1940] This system is configured using the following hardware and software.

[1941] Hardware used

[1942] Server: A server that provides high-performance data processing and storage (e.g., a virtual server for cloud services)

[1943] Devices: PCs, tablets, smartphones, etc. for user interfaces

[1944] Software used

[1945] Database: A relational database such as MySQL or PostgreSQL

[1946] Natural Language Processing (NLP) libraries: spaCy and NLTK

[1947] Machine learning frameworks: TensorFlow and PyTorch

[1948] Communication protocol: HTTPS

[1949] System configuration and functions

[1950] Entering patient information

[1951] User: The user accesses a dedicated application or web form and enters information about their symptoms, medical history, lifestyle habits, etc. For example, they enter information such as, "I have pain in the left side of my lower back, especially when I wake up in the morning."

[1952] Terminal: The entered information is formatted into JSON format and sent to the server using a secure communication protocol (HTTPS).

[1953] Receiving and storing patient information

[1954] Server: Validates the received patient symptom information and stores it securely in a database (e.g., MySQL database).

[1955] Patient information analysis

[1956] Server: Analyzes stored patient information using AI algorithms. This analysis uses natural language processing (spaCy) and machine learning (TensorFlow). For example, if a patient says, "My lower back hurts and it's hard for me to get up in the morning," the system evaluates the possibility of muscle tension or a herniated disc.

[1957] Treatment plan generation

[1958] Server: Generates a personalized treatment plan based on the analysis results, including recommendations for physical therapy, medication, and stretching.

[1959] Treatment plan notification

[1960] Server: Sends the generated treatment plan to the user's device via email, SMS, in-app notifications, etc.

[1961] Terminal: Displays the received treatment plan to the user.

[1962] Selecting and booking a treatment facility

[1963] User: Follows the proposed treatment plan and selects the appropriate treatment facility from the list provided by the system.

[1964] Server: Provides a list of treatment facilities, receives the user's selection, and confirms the appointment.

[1965] Treatment progress management and feedback

[1966] User: Once actual treatment begins, the user will periodically enter progress information and pain level into the system.

[1967] Device: This progress information is sent to the server in real time.

[1968] Server: Analyzes progress information and updates treatment plans as needed.

[1969] Treatment evaluation and optimization

[1970] User: Upon completion of treatment, complete a full treatment evaluation.

[1971] Device: Sends rating information to the server.

[1972] Server: Analyzes the received evaluation information and uses it to optimize future treatment plans.

[1973] Prompt Sentence Examples

[1974] "Please tell me more about your back pain symptoms."

[1975] Please enter some information about your lifestyle.

[1976] "Review the treatment plan and provide feedback."

[1977] In this way, patients can receive the treatment that is best suited to them quickly and efficiently, resulting in an improvement in their symptoms.

[1978] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1979] Step 1:

[1980] Entering patient information

[1981] User: Accesses a dedicated application or web form and enters information about their symptoms, medical history, lifestyle habits, etc. For example, they enter information such as "I have lower back pain" or "I have severe pain when I wake up in the morning."

[1982] Input: Patient symptom information, medical history, and lifestyle data.

[1983] Output: Formatted symptom information in JSON format.

[1984] Terminal: Converts the input information into JSON format and sends it to the server using a secure communication protocol (e.g. HTTPS).

[1985] Step 2:

[1986] Receiving and storing patient information

[1987] Server: Validates incoming patient symptom information and stores it securely in a database. For example, validates patient information and then executes an INSERT query into a MySQL database.

[1988] Input: Formatted symptom information (JSON format) sent from the device.

[1989] Output: Patient information stored in a database.

[1990] Specific operation: The server detects the receiving trigger, performs data validation, and if the data is correct, executes an INSERT query to save it to the database.

[1991] Step 3:

[1992] Patient information analysis

[1993] Server: Analyzes stored patient information using AI algorithms. Classifies symptoms using natural language processing and identifies causes using machine learning. For example, analyzes symptoms using an NLP model (e.g., spaCy) and diagnoses using a machine learning model (e.g., TensorFlow).

[1994] Input: Patient information stored in the database.

[1995] Output: Parsed symptom information and diagnosis results.

[1996] How it works: The server retrieves patient information from the database, runs it through an NLP model to classify symptoms, then invokes a machine learning model to generate a diagnosis.

[1997] Step 4:

[1998] Treatment plan generation

[1999] Server: Based on the analysis results, it generates an individualized treatment plan, which may include physical therapy, medication, stretching, etc.

[2000] Input: Parsed symptom information and diagnosis results.

[2001] Output: Individualized treatment plan.

[2002] Specific operation: Based on the analysis results, the optimal plan is generated by combining treatment options. A template engine is used to generate the plan in a format that is easy for users to view.

[2003] Step 5:

[2004] Treatment plan notification

[2005] Server: Sends the generated treatment plan to the user's device via email, SMS, in-app notifications, etc.

[2006] Input: Individualized treatment plan.

[2007] Output: Notification to the user.

[2008] Terminal: Displays the received treatment plan to the user.

[2009] Specific operation: The server calls the notification system and sends the treatment plan in the appropriate format. The device receives the notification and displays it to the user as a pop-up message or similar.

[2010] Step 6:

[2011] Selecting and booking a treatment facility

[2012] User: Follows the proposed treatment plan and selects the appropriate treatment facility from the list provided by the system.

[2013] Input: Proposed treatment plan and list of treatment facilities.

[2014] Output: Selected treatment facilities.

[2015] Server: Provides a list of treatment facilities, receives the user's selection, and confirms the appointment, e.g., by calling a booking API to confirm the appointment.

[2016] What happens: The server sends a POST request to the reservation endpoint and receives confirmation of the reservation.

[2017] Step 7:

[2018] Treatment progress management and feedback

[2019] User: Once the actual treatment begins, the user periodically enters progress information and pain level into the system, for example, providing feedback such as "Today the pain has decreased."

[2020] Input: Treatment progress information, pain level.

[2021] Output: Progress information sent to the system.

[2022] Device: Sends progress information to the server in real time.

[2023] Specific operation: The device detects user input and periodically sends progress information to the server.

[2024] Step 8:

[2025] Treatment evaluation and optimization

[2026] User: Upon completion of treatment, complete an overall treatment evaluation, such as "My pain is almost gone after treatment."

[2027] Input: Treatment evaluation information.

[2028] Output: The rating information sent to the server.

[2029] Device: Sends rating information to the server.

[2030] Server: Analyzes the received evaluation information and uses it to optimize future treatment plans.

[2031] How it works: The server analyzes the evaluation information in real time and stores it in a feedback database. This data is then used to optimize the next treatment plan.

[2032] (Application example 1)

[2033] 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."

[2034] Health management is extremely important for security staff, as they are subjected to high physical and mental strain during their work. However, there is a lack of a system to provide appropriate treatment plans tailored to individual health conditions, making effective health management difficult. This can result in a decline in security staff performance and have a negative impact on the overall security level.

[2035] 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.

[2036] In this invention, the server includes an input means for inputting symptom information of a patient, a receiving means for receiving the symptom information of the patient input from the input means, an analysis means for analyzing the symptom information of the patient received by the receiving means, a generation means for generating an individual treatment plan based on the analysis results obtained by the analysis means, a notification means for notifying the patient of the treatment plan generated by the generation means, a selection means for selecting an appropriate treatment facility based on the treatment plan notified by the notification means, a reservation means for making a reservation at the treatment facility selected by the selection means, an update means for receiving treatment progress information from the patient and updating the treatment plan, a means for inputting and analyzing health information of security staff and generating individual health management plans, and a means for monitoring the health status of the security staff and managing and optimizing their progress in real time, thereby individually optimizing the health status of the security staff, improving performance and ensuring safety.

[2037] "Patient information" refers to information necessary for treatment, such as the patient's symptoms, medical history, and lifestyle habits.

[2038] "Input means" refers to a device or interface that allows a patient or a medical professional to input symptom information into the system.

[2039] The "receiving means" is a function or device for receiving information input through the input means.

[2040] The "analysis means" refers to a device or algorithm that analyzes the information obtained by the receiving means and evaluates symptoms and identifies causes based on the content of the information.

[2041] The "generation means" refers to a function or process that creates an individual treatment plan based on the analysis results obtained by the analysis means.

[2042] The "notification means" is a method or device for informing the patient of the treatment plan created by the generation means.

[2043] "Selection means" is a function of the system for selecting an appropriate treatment facility based on a treatment plan.

[2044] "Reservation means" refers to a function or mechanism for making a reservation at a treatment facility selected by the selection means.

[2045] "Update means" is a function for receiving information on the patient's treatment progress and updating and adjusting the treatment plan based on that information.

[2046] "Security staff health information" refers to data indicating the health status of security staff, including symptoms, medical history, exercise habits, etc.

[2047] "Monitoring means" is a function for monitoring the health status of security staff in real time and managing progress.

[2048] A "health management plan" is a specific instruction or plan for maintaining or improving the health of security personnel that is tailored to each individual based on analytical methods.

[2049] This invention is a system that inputs and analyzes the health information of patients and security staff, and provides individualized treatment or health management plans. This system is designed to utilize hardware and software to enable patients and security staff to receive care efficiently.

[2050] About program processing

[2051] The program of this system has the function of performing the following main processes. First, it uses the input means to collect symptom information and health information of patients and security staff. Next, it uses the receiving means to send this information to the server and store it. The server then analyzes the received information using the analysis means and generates an individual treatment plan or health management plan based on the results.

[2052] The generated plan is communicated to the user through a notification means. The user can review the plan and select an appropriate treatment facility. The selection means automatically makes a reservation at the facility selected by the user. In addition, the system also includes an update means for receiving progress information from the user in real time and updating the treatment plan as necessary.

[2053] Hardware and Software Use

[2054] Server: Uses AWS or Google Cloud to store data, analyze data, and generate plans.

[2055] AI models: Using natural language processing (NLP) and machine learning (e.g., TensorFlow and PyTorch).

[2056] Devices: Smartphones, smart glasses, head-mounted displays, etc.

[2057] Data processing and calculation

[2058] 1. Input method:

[2059] Symptom information and health information are entered using a device (such as a smartphone). For example, a patient enters their lower back pain symptoms.

[2060] 2. Receiving means:

[2061] The server receives the information sent from the device and stores it in a database via a secure communication protocol (e.g., HTTPS).

[2062] 3. Analysis method:

[2063] The server analyzes the stored information and uses NLP and machine learning to evaluate symptoms. For example, if someone says, "My lower back hurts and it's hard to get up in the morning," it will evaluate the possibility of muscle tension or a herniated disc.

[2064] 4. Generation means:

[2065] Based on the analysis results, a personalized treatment or health management plan is generated, which may include, for example, physical therapy, medication, and stretching.

[2066] 5. Means of notification:

[2067] The generated plan is notified to the user's terminal so that the user can check it.

[2068] 6. Selection method:

[2069] Based on the proposed treatment plan, the user selects an appropriate treatment facility from a list provided by the system.

[2070] 7. Reservation Method:

[2071] Automatically send appointment requests to selected treatment facilities.

[2072] 8. Update method:

[2073] Progress information from the user is sent to the server in real time, and the AI ​​updates the treatment plan as needed.

[2074] Examples of concrete examples and prompts

[2075] Specific examples

[2076] User input: "My lower back hurts from standing for long periods of time every day, especially the right side."

[2077] AI analysis result: "It's likely due to muscle tension on the right side."

[2078] Treatment plan: "Physical therapy three times a week and simple stretching exercises."

[2079] Prompt Sentence Examples

[2080] User input: "I have pain on the left side of my lower back, especially when I wake up in the morning."

[2081] The system responds: "This case may be due to muscle tension. We've generated a treatment plan focused on physical therapy."

[2082] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2083] Step 1:

[2084] Users use a smartphone or dedicated device to input symptom information or health information. The input information is sent to the system. Specifically, a patient might input, "I have pain in the left side of my lower back, especially when I wake up in the morning."

[2085] Input: Symptom information and health information

[2086] Output: Sending input information

[2087] Step 2:

[2088] The device formats the entered information and sends it to the server using a secure communication protocol (e.g., HTTPS). During this step, encryption is used to prevent data tampering or leakage.

[2089] Input: Formatted input information

[2090] Output: Sending encrypted data

[2091] Step 3:

[2092] The server receives the transmitted information using the receiving means and stores it in a database. Upon receiving the information, it checks the integrity of the data and performs error checks as necessary.

[2093] Input: Encrypted data

[2094] Output: Information stored in the database

[2095] Step 4:

[2096] The server then uses analytics to analyze the stored information. It uses natural language processing (NLP) and machine learning algorithms to assess symptoms and identify causes. For example, if someone says, "My lower back hurts and it's hard for me to get up in the morning," it can assess whether they have muscle tension or a herniated disc.

[2097] Input: Stored patient information

[2098] Output: Analysis results

[2099] Step 5:

[2100] The server generates an individualized treatment plan based on the analysis results using the generation means. The generated treatment plan includes physical therapy, drug therapy, stretching, etc. For example, a plan including "physical therapy three times a week and simple stretching exercises" is generated based on the analysis results.

[2101] Input: Analysis results

[2102] Output: Individual treatment plan

[2103] Step 6:

[2104] The server uses the notification means to send the generated treatment plan to the user's terminal, and the user receives the notification and checks the treatment plan.

[2105] Input: Individual Treatment Plan

[2106] Output: User notification

[2107] Step 7:

[2108] The user checks the notified treatment plan and selects an appropriate treatment facility from the list provided by the system. The information of the selected facility is sent to the system.

[2109] Input: Confirm treatment plan, select treatment facility

[2110] Output: Send selected treatment facility information

[2111] Step 8:

[2112] The server automatically sends an appointment request to the treatment facility selected by the user using the selection means, and a confirmation message is sent to the user once the appointment is completed.

[2113] Input: Selected Treatment Facility Information

[2114] Output: Reservation confirmation message

[2115] Step 9:

[2116] Users periodically enter progress information into the system, such as "Today my pain is reduced."

[2117] Input: Progress information

[2118] Output: Sending input information

[2119] Step 10:

[2120] The device formats the progress information and sends it to the server over a secure communication protocol.

[2121] Input: Formatted progress information

[2122] Output: Sending encrypted data

[2123] Step 11:

[2124] The server receives progress information and uses AI to update the treatment plan, recommending new instructions or changes based on the analysis results.

[2125] Input: Progress information

[2126] Output: Updated treatment plan

[2127] Step 12:

[2128] The server then notifies the user's device of the updated treatment plan again, continuing optimal treatment according to the patient's progress.

[2129] Input: Updated treatment plan

[2130] Output: User notification

[2131] 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.

[2132] This invention is a system that provides personalized treatment plans specifically tailored to patients with lower back pain, and includes a function that recognizes the patient's emotions and reflects them in the treatment plan. The system aims to provide optimal treatment by automating everything from inputting patient information to managing the progress of treatment.

[2133] System Overview

[2134] The system is configured using the following means:

[2135] 1. A means of patient information entry: A dedicated app or web form for patients to enter their symptoms, medical history, lifestyle information, and even emotional state.

[2136] 2. Receiving means: A server for receiving and storing the entered information.

[2137] 3. Analysis method: The received information is analyzed using AI algorithms and an emotion engine to evaluate symptoms and identify causes.

[2138] 4. Generation method: Generate an individual treatment plan based on the analysis results.

[2139] 5. Notification Methods: Methods for informing the patient of the generated treatment plan.

[2140] 6. Selection tools: Tools to select the appropriate treatment facility for pain relief.

[2141] 7. Booking Method: A method for automatically scheduling appointments with selected treatment facilities.

[2142] 8. Updates: Receives patient progress information and the AI ​​updates the treatment plan as needed.

[2143] 9. Emotion Engine: Analyzes the patient's written and spoken information, assesses their emotional state, and provides information to the analysis and generation means.

[2144] Natural language programming

[2145] 1. Enter patient information

[2146] User: Accesses a dedicated app or web form and enters information about their symptoms, medical history, lifestyle habits, and emotional state. For example, they might enter, "I have pain in the left side of my lower back, especially when I wake up in the morning. Lately, the pain has been making me feel stressed."

[2147] 2. Receiving patient information

[2148] Terminal: Formats the entered patient and emotion information and sends it to the server using a secure communication protocol (e.g., HTTPS).

[2149] 3. Patient Information Storage

[2150] Server: Stores the received patient and emotion information in a database and performs data integrity checks, for example, checking whether all required fields have been filled in.

[2151] 4. Analysis of patient information and emotional information

[2152] Server: Analyzes patient information and emotional information stored in a database using AI algorithms and an emotion engine. Using natural language processing (NLP) technology, details of symptoms and emotions are extracted from input text and compared with a case database to make a diagnosis. For example, the emotion engine analyzes the information that "pain causes stress" and determines that stress relief should also be included in treatment.

[2153] 5. Treatment plan generation

[2154] Server: Based on the analysis results, it generates an individualized treatment plan. For example, if muscle tension is determined to be the cause, it will create a treatment plan that includes physical therapy, stretching, prescription painkillers, and relaxation techniques to reduce stress.

[2155] 6. Notification of Treatment Plan

[2156] Server: Sends the generated treatment plan to the patient's device, along with a detailed explanation of each item in the plan and customized feedback based on emotions.

[2157] 7. Confirmation of treatment plan

[2158] Terminal: Displays the received treatment plan to the user, providing an interface for the user to review the contents and enter feedback.

[2159] User: Review the proposed treatment plan and approve or enter questions or feedback.

[2160] 8. Selecting and booking a treatment facility

[2161] User: Based on the proposed treatment plan, the user selects the appropriate treatment facility from a list provided by the system. For example, if physical therapy is required, the user selects a specialized facility.

[2162] Terminal: Sends information about the selected treatment facility to the server.

[2163] Server: Receives the treatment facility selection information, sends a reservation request to the facility, and once the reservation is confirmed, provides the final reservation information to the user.

[2164] 9. Treatment progress management and feedback

[2165] User: Once the actual treatment begins, the user periodically enters progress information, pain level, and emotional state into the system. For example, "Today my pain has decreased, but I still feel stressed."

[2166] Device: Sends progress and emotion information to the server in real time.

[2167] Server: Analyzes progress and emotional information to evaluate the effectiveness of the treatment plan, readjusts the treatment plan if necessary, and sends new instructions to the user based on their emotional state.

[2168] 10. Treatment evaluation and optimization

[2169] User: Upon completion of treatment, complete an overall treatment evaluation. For example, enter a final rating such as, "The treatment was very effective, but I would like to see more stress reduction techniques added."

[2170] Device: Sends rating information to the server.

[2171] Server: The received evaluation and emotional information is stored in a database, and statistical analysis is performed using an AI algorithm to optimize future treatment plans.

[2172] In this way, patients can receive the treatment that is best suited to them quickly and efficiently, and the system provides emotional support as well as symptom improvement.

[2173] The processing flow will be explained below.

[2174] Step 1:

[2175] User: Accesses a dedicated app or web form and enters detailed information such as their symptoms, medical history, lifestyle habits, emotional state, etc. An example entry is, "I have pain on the left side of my lower back, especially when I wake up in the morning. Lately, the pain has been making me feel stressed."

[2176] Step 2:

[2177] Terminal: Formats the entered patient and emotion information and sends it to the server using a secure communication protocol (e.g., HTTPS).

[2178] Step 3:

[2179] Server: Saves the received patient information and emotion information in the database. When saving, checks whether all required fields have been entered.

[2180] Step 4:

[2181] Server: Analyzes patient information and emotional information stored in a database using AI algorithms and an emotion engine. Using natural language processing (NLP) technology, details of symptoms and emotions are extracted from input text and compared with a case database to make a diagnosis. For example, the emotion engine analyzes the information that "pain causes stress" and determines that stress management should also be included in the treatment plan.

[2182] Step 5:

[2183] Server: Based on the analysis results, it generates an individualized treatment plan. Specifically, if muscle tension is determined to be the cause, it creates a treatment plan that includes physical therapy, stretching, prescription painkillers, and relaxation techniques for stress management.

[2184] Step 6:

[2185] Server: Sends the generated treatment plan to the patient's device, including detailed explanations of each item and customized feedback based on emotions.

[2186] Step 7:

[2187] Terminal: Displays the received treatment plan to the user, using an interface that allows the user to review the contents and provide feedback.

[2188] Step 8:

[2189] User: Review the proposed treatment plan and approve it if it is acceptable, as well as provide any questions or feedback.

[2190] Step 9:

[2191] Terminal: Sends user approvals and feedback to the server in a secure format.

[2192] Step 10:

[2193] Server: Receives user feedback and modifies the treatment plan as needed, which may require reanalysis.

[2194] Step 11:

[2195] User: Based on the proposed treatment plan, the user selects the appropriate treatment facility from a list provided by the system. For example, if physical therapy is required, the user selects a specialized facility.

[2196] Step 12:

[2197] Terminal: Sends information about the selected treatment facility to the server.

[2198] Step 13:

[2199] Server: Receives the treatment facility selection information, sends a reservation request to the facility, and returns the reservation confirmation to the user.

[2200] Step 14:

[2201] User: Once the actual treatment begins, the user periodically enters progress information, pain level, and emotional state into the system. For example, "Today my pain has decreased, but I still feel stressed."

[2202] Step 15:

[2203] Device: Sends progress and emotion information to the server in real time.

[2204] Step 16:

[2205] Server: Analyzes progress and emotional information to evaluate the effectiveness of the treatment plan, readjusts the treatment plan if necessary, and sends new instructions to the user based on their emotional state.

[2206] Step 17:

[2207] User: Upon completion of treatment, complete an overall treatment evaluation. For example, enter a final rating such as, "The treatment was very effective, but I would like to receive more advice on stress management."

[2208] Step 18:

[2209] Terminal: Sends evaluation information and emotion information to the server.

[2210] Step 19:

[2211] Server: The received evaluation and emotional information is stored in a database and statistically analyzed using an AI algorithm, which is used to optimize future treatment plans.

[2212] In this way, patients can receive the treatment that is best suited to them quickly and efficiently, and the system provides emotional support as well as symptom improvement.

[2213] Example 2

[2214] 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."

[2215] Conventional lower back pain treatment systems generate treatment plans based solely on the patient's symptom information, making it difficult to provide optimal treatment plans that take into account the emotional state and lifestyle habits of each individual patient. In particular, when emotional states affect pain and stress, treatment plans that ignore this factor are unable to achieve sufficient results. Furthermore, the lack of a function to update treatment plans while reflecting treatment progress information in real time makes it difficult to maximize the effectiveness of treatment.

[2216] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes an input means for a user to input information on the patient's symptoms, medical history, lifestyle, and emotional state, a receiving means for receiving the input symptom information and emotional information of the patient, an analyzing means for analyzing the received symptom information and emotional information of the patient, a generating means for generating an individualized treatment plan based on the analysis results, a notifying means for notifying the patient of the generated treatment plan, a selecting means for selecting an appropriate treatment facility based on the notified treatment plan, a booking means for making a booking at the selected treatment facility, and an updating means for receiving treatment progress information and emotional information from the patient and updating the treatment plan. This makes it possible to provide an individualized treatment plan that takes into account the patient's emotional state and lifestyle, and to provide a treatment plan that is optimized in real time according to the progress of treatment.

[2217] A "user" is a person who uses a dedicated app or web form to enter information about their symptoms, medical history, lifestyle habits, and emotional state.

[2218] An "input means" is an application or web form used by a user to input information about a patient's symptoms, medical history, lifestyle habits, and emotional state.

[2219] The "receiving means" is a component for receiving symptom information and emotion information of a patient transmitted from the input means.

[2220] The "analysis means" is a component that uses an AI algorithm and a natural language processing engine to analyze the received symptom information and emotional information of the patient, and evaluate the symptoms and identify the cause.

[2221] The "generation means" is a component for generating an individual treatment plan based on the analysis results.

[2222] The "notification means" is a component for notifying the patient of the treatment plan generated by the generation means.

[2223] The "selection means" is a component for selecting an appropriate treatment facility based on the notified treatment plan.

[2224] The "reservation means" is a component for making a reservation at a selected treatment facility.

[2225] The "updater" is a component for receiving treatment progress and emotional information from the patient and updating the treatment plan.

[2226] "Patient symptom information" is information entered by the patient about their symptoms, specifically the location of the pain, the degree of pain, the circumstances under which the pain occurs, and the like.

[2227] "Emotional information" is information about the patient's emotional state, specifically a detailed description of stress and physical and mental state.

[2228] An "AI algorithm" is an algorithm that uses artificial intelligence technology to analyze data and generate diagnoses and treatment plans.

[2229] A "natural language processing engine" is a technology that analyzes the meaning and emotions of sentences entered by patients and extracts details.

[2230] This invention is a system that provides personalized treatment plans specifically tailored to patients with lower back pain, and includes a function that recognizes the patient's emotions and reflects them in the treatment plan. The system aims to provide optimal treatment by automating everything from inputting patient information to managing the progress of treatment.

[2231] System configuration

[2232] This system is configured using the following hardware and software.

[2233] 1. Input method:

[2234] Users use a dedicated app or web form to enter information about their symptoms, medical history, lifestyle habits, and emotional state. For example, they might enter, "I have pain in the left side of my lower back, especially when I wake up in the morning. Lately, the pain has been making me feel stressed."

[2235] 2. Receiving means:

[2236] The terminal formats and transmits the entered patient and emotion information to the server using a secure communication protocol (e.g., HTTPS).

[2237] 3. Preservation means:

[2238] The server stores the received patient information and emotion information in a database and checks the integrity of the data, for example, whether all required fields have been filled in.

[2239] 4. Analysis method:

[2240] The server analyzes the information stored in th...

Claims

1. an input means for inputting symptom information of a patient; receiving means for receiving symptom information of the patient inputted from the input means; an analysis means for analyzing the symptom information of the patient received by the receiving means; a generating means for generating an individual treatment plan based on the analysis results obtained by the analyzing means; a notification means for notifying a patient of the treatment plan generated by the generation means; a selection means for selecting an appropriate treatment facility based on the treatment plan notified by the notification means; a reservation means for making a reservation at the treatment facility selected by the selection means; and an update means for receiving treatment progress information from the patient and updating the treatment plan.

2. 2. The system according to claim 1, wherein the input means for inputting the symptom information of the patient is a means for inputting information about the patient's symptoms, medical history, and lifestyle habits.

3. The system of claim 1, wherein the treatment plan update means receives information on the patient's treatment progress and adjusts the treatment plan using AI.

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