system

Abstract

We provide the system. [Solution] A means of automatically generating treatment policies and care plans by analyzing patient information using generative artificial intelligence, A method for converting visit records into digital data using handwriting recognition technology and centrally managing the information, A means of automatically generating answers to questions outside of one's area of ​​expertise based on analyzed information, We protect information in secure data centers and implement measures to ensure the strict management of highly confidential information. A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of the chatbot's 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] In home care, it may be difficult to share information when medical and care experts manage medical records independently. Also, due to differences in expertise, there are problems such as information misunderstanding and care plan inconsistencies. These issues are obstacles to providing accurate and prompt care for patients.

Means for Solving the Problems

[0005] This invention solves these problems by providing a management system that utilizes generative artificial intelligence and handwriting recognition technology. By analyzing patient information using generative artificial intelligence and automatically generating treatment policies and care plans, it enables centralized information management and accelerates collaboration among specialists. Furthermore, by digitizing visit records using handwriting recognition technology and summarizing relevant information for distribution to specialists, it streamlines the flow of information. It also features a chat function that generates automatic responses based on the analyzed information, even for questions outside of the specialist's area of ​​expertise, thereby realizing comprehensive information sharing. This improves the quality of home care services and enables efficient work execution.

[0006] "Generative artificial intelligence" is an intelligent system that analyzes vast amounts of data and generates or improves information according to specific tasks.

[0007] "Handwriting recognition technology" is a technology that scans handwritten characters and symbols and converts them into digital data in a format that can be interpreted by a computer.

[0008] A "care plan" is a plan that outlines specific treatment and care policies, formulated based on the patient's health condition and care needs.

[0009] "Centralized information management" is a system that facilitates access to and use of information by consolidating multiple pieces of information in one place and managing them in an organized manner.

[0010] "Automatic response generation" is the process of automatically generating appropriate answers to received questions or inputs based on relevant information.

[0011] "Security measures" refer to a set of technologies and procedures for protecting digital data and systems from unauthorized access, leakage, tampering, and other threats. [Brief explanation of the drawing]

[0012] [Figure 1]This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

[0013] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0014] First, the terms used in the following description will be explained.

[0015] In the following embodiments, a tagged processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0016] In the following embodiments, a tagged RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0017] In the following embodiments, a tagged storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0018] In the following embodiments, a tagged communication I / F (Interface) is an interface including a communication processor and an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applicable to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark), and the like.

[0019] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0020] [First Embodiment]

[0021] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0022] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0023] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0024] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0025] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0026] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0027] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0028] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0029] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0030] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0031] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0032] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0033] The system of this invention is designed to improve the efficiency and accuracy of information sharing in home care. The specific operation of each component is described below.

[0034] First, healthcare and care professionals, acting as users, input basic patient information through a terminal. This information includes important data about the patient, such as name, age, address, medical history, and allergy information. The terminal then transmits this data to the server in a secure format.

[0035] Next, the device uses handwriting recognition technology to convert the handwritten records left by the user after their visit into digital data. This conversion process digitizes the visit records, which are then centrally managed on a server. The digitized information is analyzed by a generative AI, and a summary is automatically created.

[0036] The server aggregates all information and uses a generative AI to automatically generate treatment plans and care plans for each patient. The generated care plans are notified to relevant specialists for review and modified as needed. The generative AI's analysis is based on the patient's past medical history, current health status, and the latest medical knowledge.

[0037] The system also includes a support chat function that generates automated responses based on information for questions outside of the user's area of ​​expertise. When a user enters a question in the chat, the server analyzes the question, and the AI ​​generator prepares an appropriate answer. This process provides immediate feedback and supports the smooth execution of tasks.

[0038] For example, after a nurse visits a new patient, they take handwritten notes, which are then scanned and digitized by a terminal. This data is immediately sent to a server, where it is summarized and distributed to other relevant professionals. Furthermore, AI generates an initial care plan based on the patient's symptoms, which is then reviewed and adjusted as needed. In the case of non-specialist questions, such as when a caregiver asks about the side effects of a particular medication via chat, the server provides reference information to support safe care.

[0039] In this way, the system of the present invention enables the rapid and accurate sharing of information, improving operational efficiency and the quality of care in home care settings.

[0040] The following describes the processing flow.

[0041] Step 1:

[0042] The user enters the patient's basic information on the terminal. This includes name, age, address, medical history, and allergy information. Once the input is complete, the terminal organizes this information according to a format, encrypts it, and sends it to the server.

[0043] Step 2:

[0044] The server stores the received patient information in a database. The stored data is further analyzed, and patient history is updated as needed. Information is properly managed to ensure access by all relevant specialists.

[0045] Step 3:

[0046] The user creates a handwritten care record after the visit. This record is scanned using a terminal. The terminal uses handwriting recognition technology to digitize the scanned data and convert it into text format.

[0047] Step 4:

[0048] The server receives digitized visit records and automatically generates summaries. The generated summaries are stored in a database and quickly distributed to the relevant experts.

[0049] Step 5:

[0050] Based on the information aggregated in the database, the server uses AI to automatically generate treatment plans and care plans for each patient. The generated plans are then notified to the relevant specialist for review.

[0051] Step 6:

[0052] The user enters a question outside their area of ​​expertise using the chat function. The terminal forwards the entered question to the server.

[0053] Step 7:

[0054] The server analyzes the received question and generates an automated response using a generative AI. This response is generated instantly based on relevant data.

[0055] Step 8:

[0056] The terminal displays the response received from the server to the user. The user can then use this response as a reference to proceed with their work.

[0057] Step 9:

[0058] The server implements security measures for all data to prevent unauthorized access and leakage of information. Data is not used for learning models, and any secondary use is monitored and managed to ensure it is done under control.

[0059] (Example 1)

[0060] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0061] In home care and visiting medical settings, inefficiencies and inaccuracies in information sharing are problematic. In particular, human errors in digitizing handwritten records and insufficient prompt responses to specialized questions are factors that reduce the quality of care. Furthermore, the difficulty in dynamically updating care plans based on the patient's latest condition hinders efficient support. This increases the risk of overwork for caregivers and medical professionals, as well as inappropriate care for patients.

[0062] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0063] In this invention, the server includes means for analyzing user information and automatically generating care plans and support plans using generative artificial intelligence, means for converting visit records into electronic data using handwriting recognition technology and centrally managing the information, and means for automatically generating responses to inquiries outside of one's area of ​​expertise based on the analyzed information. This enables the rapid and accurate sharing of information, making it possible to improve the operational efficiency and quality of care in home care settings.

[0064] "Generative artificial intelligence" refers to algorithms and technologies that automatically generate care plans and support plans by analyzing user information.

[0065] "Handwriting recognition technology" is a technology that converts handwritten information into electronic data, and is used when digitizing visitor records and other similar documents.

[0066] "Electronic data" refers to information acquired from physical media through technologies such as handwriting recognition, and then stored and processed electronically.

[0067] "Centralized management" refers to a method of managing data collected from multiple sources in one place to improve access control and information integrity.

[0068] An "inquiry" refers to questions or requests for information from users or stakeholders, and should be addressed promptly even if it falls outside one's area of ​​expertise.

[0069] The embodiments for carrying out the present invention are shown below.

[0070] This system is designed to enable efficient management and sharing of information in home care. The following describes each component of the system and its operation.

[0071] The terminal is a device used by users to input basic patient information, and can be a tablet or laptop. These terminals provide users with an intuitive input interface and have the ability to verify the accuracy of the data in real time. The data is encrypted via the SSL / TLS protocol and securely transmitted to the server.

[0072] The server receives data and centrally manages it in a secure data storage facility. The server is equipped with a generative AI that automatically generates support plans based on the patient's past medical history, current health status, and the latest medical knowledge. This enables medical and care professionals to provide care that is up-to-date. The generative AI utilizes commonly used AI frameworks and models.

[0073] The terminal also scans handwritten records filled out after the visit and converts them into electronic data using handwriting recognition technology. This technology, for example, uses Tesseract. The converted data is sent to a server, where it is automatically summarized by a generating AI.

[0074] Users can ask questions outside their area of ​​expertise through the support chat function. Questions entered in this chat are analyzed by the server, and responses are provided immediately by a generating AI. This improves operational efficiency.

[0075] For example, when a nurse visits a new patient, they scan their notes, and the information is sent to a server for processing. As a result, necessary information is quickly provided to relevant professionals. Furthermore, the server provides appropriate information in response to inquiries about side effects of specific medications, ensuring safety in the field. However, the generated information is to be reviewed by each user to aid in their final decision-making.

[0076] An example of a prompt message would be: "Patient A, a 70-year-old male, has a history of diabetes and hypertension. During the visit, he complained of a cough and a slight fever. Based on the examination results, please generate an appropriate care plan and precautions." This allows the generating AI to provide a professional and realistic care plan.

[0077] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0078] Step 1:

[0079] The user enters the patient's basic information into the terminal. The terminal provides an interface for entering data such as name, age, address, medical history, and allergy information through an on-screen form. The entered information is formally verified on the spot and sent to the server in an encrypted format using the SSL / TLS protocol. As a result, patient information is stored securely.

[0080] Step 2:

[0081] The terminal scans the records that the user has written after their visit. As input, handwritten paper records are digitized using a camera or scanner and imported into the terminal as image data. The terminal applies handwriting recognition technology and uses OCR technology such as Tesseract to convert the image data into text data. This process transforms the user's visit records into a format that can be stored electronically.

[0082] Step 3:

[0083] The server receives text data sent from terminals and stores it centrally in a database. OCR-processed text data is used as input. The server passes this data to a generating AI, which automatically creates a summary for each patient. The AI ​​model then sends the generated summaries to relevant professionals, ensuring the data is shared appropriately.

[0084] Step 4:

[0085] The server uses generative AI to automatically generate individual patient care plans. Input data includes the patient's past medical history and current health status. The generative AI analyzes this data and outputs treatment policies and care plans that reflect the latest medical knowledge. This output is communicated to relevant professionals, who provide feedback and make adjustments as needed.

[0086] Step 5:

[0087] Users enter questions outside their area of ​​expertise using the support chat function. The server analyzes the entered inquiry and prepares an appropriate response using AI generation. The output is an immediate response returned to the user, allowing them to quickly obtain the necessary information. This function enables users to quickly resolve questions that arise in their daily work.

[0088] (Application Example 1)

[0089] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0090] In home care and medical settings, the rapid and accurate management and sharing of patient information is extremely important. However, traditional methods have presented challenges such as delays in digitizing handwritten records and information sharing, which prolong the development and implementation of care plans. Furthermore, there are limited means of checking necessary information in real time during visits, increasing the burden on caregivers. There is a need to solve these problems and improve the efficiency and quality of home care.

[0091] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0092] In this invention, the server includes means for analyzing person information and automatically generating treatment policies and care plans using generative artificial intelligence; means for converting visit records into digital data using document shape recognition technology and integrating and managing the information; and means for using a visual device to allow those involved to quickly refer to the information, receive the analysis results from the artificial intelligence, and display them visually. This makes it possible for caregivers to grasp the patient's condition in real time during visits and to quickly create and implement appropriate care plans.

[0093] "Generative artificial intelligence" is a type of artificial intelligence that analyzes collected personal information and automatically generates treatment plans and care plans.

[0094] "Document shape recognition technology" is a technology that converts handwritten visit records into digital data and manages the information in a centralized manner.

[0095] An "information storage device" is a device used to securely store digitized information and ensure its confidentiality and integrity.

[0096] A "visual device" is a device that allows caregivers to access information in real time and displays the results of AI-generated analysis visually.

[0097] The system that implements this application is designed to streamline information management and care plan generation in home care and medical settings. This system primarily operates through the coordinated efforts of the following three elements:

[0098] First, the user, a care professional, wears a visual device to check patient information. This device, such as smart glasses, allows those involved to instantly receive necessary information on-site. The information displayed on the visual device is retrieved from a vast database managed by a server.

[0099] Next, the terminal digitizes observations and handwritten records made during the visit in real time. This process uses document shape recognition technology to instantly integrate paper notes as data. The terminal sends this data to a server, where the information is centrally managed.

[0100] The server uses generative artificial intelligence to analyze the aggregated data. Based on the patient's current health status and past medical history, the AI ​​automatically generates treatment plans and care plans. It also dynamically updates the care plan as needed and reflects the results on the visual display.

[0101] As a concrete example, a caregiver observes changes in a patient's heart rate and blood pressure during a visit. This data is immediately digitized and analyzed on a server. Based on the analysis, if the server determines that urgent care is needed, it displays an alert to the caregiver via a visual device.

[0102] An example of a prompt message is: "Review this patient's past treatment history and generate and display a care plan based on their current health status. Also, check for allergies and issue a warning if there are any risks." This prompt message allows the server to perform the appropriate actions and provide the user with the necessary information.

[0103] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0104] Step 1:

[0105] The server prepares the data necessary to display the latest patient information on the user's visual device. Inputs include basic patient information and medical history retrieved from a database. The server organizes this information and performs data processing to extract important details. Output is a data feed for display on the visual device.

[0106] Step 2:

[0107] The user's visual device receives and visualizes a data feed sent from the server in real time. The input is the data feed generated in step 1. The visual device receives this and performs data calculations to visually display the information on the display. The output is an information screen viewable by the user.

[0108] Step 3:

[0109] The user inputs the patient's biometric information observed into the terminal. This input includes biometric data manually acquired by the user, such as heart rate and blood pressure. The terminal receives this data and performs data processing, converting it into a digital format. The output is digital data ready for transmission to the server.

[0110] Step 4:

[0111] The device captures handwritten notes using a camera or scanner and converts them into digital data using document shape recognition technology. The input is a handwritten visitor's note. The device uses image processing and character recognition algorithms to perform data calculations, converting this data into text format. The output is digitized text data.

[0112] Step 5:

[0113] The server uses an AI model to analyze digital data, including biometric information and handwritten notes received from the user. The input consists of all digital data transmitted from the terminal. The server uses artificial intelligence to analyze this data and perform calculations to automatically generate treatment plans and care plans. The output is a care plan that is sent back to the visual device.

[0114] Step 6:

[0115] The server sends alerts and suggestions to the user's visual device based on the analysis results of the generated AI model. The inputs are the care plan and analysis results generated in step 5. The server performs a risk assessment and, if necessary, processes the data to create additional data, including emergency alerts. The outputs include alerts and recommended actions sent to the visual device.

[0116] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0117] The system according to the present invention not only improves the efficiency of information management in home care but also enables responses that take into account the user's emotions. This system supports medical and care professionals in providing the best possible care to patients.

[0118] First, medical and care professionals, acting as users, input basic patient information into a terminal. This information is transmitted to a server via the terminal and securely managed in an encrypted form. The server stores the information in a database and uses AI to automatically generate treatment policies and care plans for each patient.

[0119] Users record information on paper during visits, but the terminal uses handwriting recognition technology to scan the contents and convert them into digital data. The server receives this digitized information, summarizes its contents, distributes it to relevant specialists, and manages it centrally.

[0120] Furthermore, the emotion engine, a key feature of this invention, analyzes user input and voice data to identify the user's emotional state. For example, if the user is experiencing stress, the system flexibly modifies the generated care plan proposal to provide support that is sensitive to the user's feelings. This emotion analysis information is fed back to the server and used to generate future care plans.

[0121] As a concrete example, consider a scenario where a nurse visits a patient and takes handwritten notes. After the visit, a device scans the notes and converts them into a digital format. This information is immediately sent to a server and shared with all relevant professionals along with a summary. Simultaneously, if the patient's anxiety or concerns that the nurse felt during the visit are detected by an emotion engine via speech recognition, the system adjusts the care plan based on that feedback to ensure appropriate responses are taken.

[0122] Thus, the present invention not only improves the quality of care but also realizes a system that provides more comprehensive support by being attentive to the user's emotions.

[0123] The following describes the processing flow.

[0124] Step 1:

[0125] The user enters the patient's basic information on the terminal. This information includes the patient's name, age, medical history, allergies, etc. Once the input is complete, the terminal securely transmits this information to the server.

[0126] Step 2:

[0127] The server stores the received patient information in a database. This data is encrypted and stored for use in subsequent processing. Additionally, some of the information is made accessible to specialists as needed.

[0128] Step 3:

[0129] The terminal scans the handwritten records left by the user after their visit. The scanned image data is converted into digital text using handwriting recognition technology. This conversion makes the information electronically processable.

[0130] Step 4:

[0131] The server receives digitized visit records and automatically summarizes their contents. The summarized information is quickly distributed to relevant medical professionals, streamlining information sharing.

[0132] Step 5:

[0133] The server uses AI to analyze all patient data and automatically generates treatment plans and care plans. These plans are individually optimized based on the patient's historical data and the latest medical data.

[0134] Step 6:

[0135] Users input real-time feedback and questions in a chat format via their devices. This input is sent to the server.

[0136] Step 7:

[0137] The emotion engine analyzes user input and voice data to identify their emotional state. The server then adjusts its response based on this analysis, and in some cases, fine-tunes the care plan as well.

[0138] Step 8:

[0139] The terminal displays the adjusted information, care plan, and response content received from the server to the user. This allows the user to provide more appropriate care to the patient.

[0140] Step 9:

[0141] The server manages all data with security measures in place. This prevents information leaks and unauthorized access, while ensuring the strict management of highly confidential information.

[0142] (Example 2)

[0143] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0144] In home care, managing patient information is complex, and efficient information processing is required to enable medical and care professionals to respond effectively. Furthermore, the provision of flexible care plans tailored to each user's individual emotions and condition is also necessary. To address these challenges, a system is needed that allows for centralized information management and efficient individualized responses.

[0145] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0146] In this invention, the server includes means for analyzing service user information and automatically generating treatment plans and support plans using an automated information processing device, means for converting visit records into electronic data using handwriting recognition technology and integrating and managing the information, and means for analyzing voice data to determine the emotional state of the service user and flexibly adjusting the support plan based on that. This enables efficient and secure management of information and the provision of care plans that are sensitive to the user's feelings.

[0147] An "automatic information processing device" is a device that processes user information and automatically generates various plans.

[0148] "Service user information" refers to data including users' personal information and health status related to medical care and nursing care.

[0149] A "treatment plan" is a plan that outlines the specific treatments and support to be provided to an individual who requires medical and nursing care.

[0150] A "support plan" is a plan that outlines the overall support policy to ensure that service users receive appropriate care.

[0151] "Handwriting code recognition technology" is a technology that converts handwritten records into electronic data, and generally uses OCR technology.

[0152] "Electronic data" refers to digital data that has been converted into a format that can be processed by a computer.

[0153] "Integrated information management" means efficiently managing data from different sources within a single system.

[0154] "Audio data" refers to data that records audio information, including user speech and recordings, in digital format.

[0155] "Emotional state" refers to a psychological condition that reflects an individual's feelings and mental state.

[0156] A "care plan" is a specific support plan designed to ensure the health and well-being of the user.

[0157] This invention consists of a system for information management in home care and for empathizing with the user's emotions. The entire system functions through complex operations by a server, terminals, and users.

[0158] First, the user, a medical or care professional, enters the patient's basic information into a terminal. This terminal is primarily a tablet or personal computer, but other portable information devices can also be used if necessary. The entered information is verified on the terminal, encrypted, and then sent to the server.

[0159] The server stores the received information in a database. A commonly used SQL-based management system can be used for database management. Next, the server uses a generative AI model to automatically generate patient-specific treatment and support plans based on the collected information. Various data analysis platforms can be selected as the AI ​​model, and through this process, an initial plan tailored to each patient's needs is created.

[0160] During a visit, the user takes handwritten notes on paper, which are then converted into electronic data using optical character recognition (OCR) technology. The converted data is immediately sent to a server, which analyzes the data and manages the information in an integrated manner. During this process, voice data is also analyzed to determine the emotional state of the user or patient.

[0161] Furthermore, the analyzed information is notified to experts, and the care plan is dynamically updated. If emotional abnormalities are detected during the analysis, the server uses a prompt message to instruct the AI ​​model to "adjust the care plan," thereby improving the plan. An example of a prompt message is, "Propose a stable care plan based on the patient's latest data."

[0162] This enables the system to manage information efficiently and securely, and to provide appropriate support tailored to the emotional state of users and patients.

[0163] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0164] Step 1:

[0165] The user enters the patient's basic information (name, age, medical history, allergy information, etc.) into the terminal. The terminal validates the format of the input data to ensure it is in the correct format. After the input data is validated, the terminal encrypts it. Next, this encrypted data is sent to the server. The output is the transmitted encrypted data.

[0166] Step 2:

[0167] The server decodes the received encrypted patient information and securely stores it in the database. After saving is complete, the server starts the generating AI model and generates prompt messages to input into the AI ​​model. The input is the patient information from earlier, and the output is the generated treatment plan and support plan. In particular, the AI ​​model receives the prompt, "Generate the optimal care plan based on the patient information."

[0168] Step 3:

[0169] Users record the patient's condition and care details on paper during visits. After the visit, the terminal uses optical character recognition (OCR) technology to scan this paper record and convert it into electronic data. Input is a handwritten visit record, and output is electronic data in text format. This digital data is immediately transmitted to the server.

[0170] Step 4:

[0171] The server analyzes the received electronic data and extracts key information using an automated summarization algorithm. The summarized information is then notified to the relevant medical professionals. The input is scanned electronic data, and the output is the summarized information and notification content.

[0172] Step 5:

[0173] The terminal analyzes voice data to determine the emotional state of the user or patient. Once the voice data is analyzed and the emotional state is identified, the results are sent to the server. The server uses this emotional information to dynamically adjust the generated care plan as needed. The input is voice data, and the output is an adapted plan with the information fed back into it.

[0174] Through these steps, the system provides advanced information processing and emotional support tailored to the needs of both the user and the patient.

[0175] (Application Example 2)

[0176] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0177] In today's world, where efficient information management and flexible, emotion-based responses are essential, ensuring efficiency and safety in various tasks is a particularly important challenge. Traditionally, the digitization of handwritten records and the automation of plan adjustments through emotion analysis have been insufficient, making it difficult to manage worker stress and optimize work plans.

[0178] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0179] In this invention, the server includes means for analyzing individual information and automatically generating policies and plans using generative artificial intelligence, means for converting records into digital data and integrating and managing the information using character recognition technology, and means for determining the user's emotional state and dynamically adjusting the plan using emotion analysis technology. This enables automatic adjustment of the work plan according to the emotional state.

[0180] "Generative artificial intelligence" is a technology used to analyze individual information and automatically generate policies and plans.

[0181] "Character recognition technology" is a technology that converts handwritten or printed records into digital data and integrates and manages that information.

[0182] "Emotional analysis technology" is a technology that assesses the user's emotional state and dynamically adjusts plans based on that assessment.

[0183] A "secure storage device" is a device that provides data protection measures for protecting and managing confidential information.

[0184] "Automatic plan adjustment" is a process that flexibly modifies work plans according to emotional states to optimize work efficiency.

[0185] In the system that implements this application, the server uses generative artificial intelligence to analyze individual information and automatically generate policies and plans. When a user leaves handwritten records using a device such as smart glasses, the device uses character recognition technology to convert the records into digital data. This data is sent to the server and centrally managed. The server also uses emotion analysis technology to determine the user's emotional state and dynamically adjust the work plan. This enables automatic adjustment of the work plan according to the worker's stress level. A specific use case would be a factory worker using smart glasses to record their work, and their emotional state would be determined through voice input. An example of a prompt for the generative AI model would be, "Please propose an algorithm that digitizes factory maintenance records and adjusts the work plan according to the worker's emotional state."

[0186] Smart glasses function as the platform, digitizing data using OCR technologies such as Tesseract, and performing emotion analysis using Google® Cloud Speech-to-Text and AWS® Comprehend. This system enables centralized data management and dynamic, emotion-based responses, providing a safe and efficient work environment.

[0187] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0188] Step 1:

[0189] The user inputs information into smart glasses. They record it by hand, and the glasses' camera scans the information. The input is handwritten text, and the output is scanned image data. This image data is digitized in subsequent processing.

[0190] Step 2:

[0191] The device processes image data using optical character recognition (OCR) technology and converts it into text data. It receives scanned image data as input and generates text data as output. This conversion process utilizes optical character recognition technology to digitize handwritten information.

[0192] Step 3:

[0193] The server passes the received text data to the generating artificial intelligence, which performs individual data analysis and automatic plan generation. The input is text data, and the output is analyzed data and a generated plan. As part of the data processing, the AI ​​model performs analysis and constructs policies and plans.

[0194] Step 4:

[0195] The user inputs information via voice. Voice data is acquired through the microphone of smart glasses. Voice information is the input, and voice data is obtained as the output. This data is used for sentiment analysis.

[0196] Step 5:

[0197] The server converts audio data into text using speech recognition technology and performs sentiment analysis. It uses tools such as AWS Comprehend to determine the emotional state. The input is the transcribed audio data, and the output is the sentiment analysis result. As a data calculation, it analyzes the user's emotions and identifies their specific state.

[0198] Step 6:

[0199] The server dynamically adjusts the work plan based on the sentiment analysis results and provides feedback to the user. The input is the result of the sentiment analysis, and the output is the generated adjusted work plan, which is then notified to the user. Through this process, the optimal plan is provided according to the user's emotional state.

[0200] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0201] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0202] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0203] [Second Embodiment]

[0204] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0205] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0206] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0207] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0208] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0209] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0210] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0211] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0212] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0213] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0214] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0215] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0216] The system of this invention is designed to improve the efficiency and accuracy of information sharing in home care. The specific operation of each component is described below.

[0217] First, healthcare and care professionals, acting as users, input basic patient information through a terminal. This information includes important data about the patient, such as name, age, address, medical history, and allergy information. The terminal then transmits this data to the server in a secure format.

[0218] Next, the device uses handwriting recognition technology to convert the handwritten records left by the user after their visit into digital data. This conversion process digitizes the visit records, which are then centrally managed on a server. The digitized information is analyzed by a generative AI, and a summary is automatically created.

[0219] The server aggregates all information and uses a generative AI to automatically generate treatment plans and care plans for each patient. The generated care plans are notified to relevant specialists for review and modified as needed. The generative AI's analysis is based on the patient's past medical history, current health status, and the latest medical knowledge.

[0220] The system also includes a support chat function that generates automated responses based on information for questions outside of the user's area of ​​expertise. When a user enters a question in the chat, the server analyzes the question, and the AI ​​generator prepares an appropriate answer. This process provides immediate feedback and supports the smooth execution of tasks.

[0221] For example, after a nurse visits a new patient, they take handwritten notes, which are then scanned and digitized by a terminal. This data is immediately sent to a server, where it is summarized and distributed to other relevant professionals. Furthermore, AI generates an initial care plan based on the patient's symptoms, which is then reviewed and adjusted as needed. In the case of non-specialist questions, such as when a caregiver asks about the side effects of a particular medication via chat, the server provides reference information to support safe care.

[0222] In this way, the system of the present invention enables the rapid and accurate sharing of information, improving operational efficiency and the quality of care in home care settings.

[0223] The following describes the processing flow.

[0224] Step 1:

[0225] The user enters the patient's basic information on the terminal. This includes name, age, address, medical history, and allergy information. Once the input is complete, the terminal organizes this information according to a format, encrypts it, and sends it to the server.

[0226] Step 2:

[0227] The server stores the received patient information in a database. The stored data is further analyzed, and patient history is updated as needed. Information is properly managed to ensure access by all relevant specialists.

[0228] Step 3:

[0229] The user creates a handwritten care record after the visit. This record is scanned using a terminal. The terminal uses handwriting recognition technology to digitize the scanned data and convert it into text format.

[0230] Step 4:

[0231] The server receives digitized visit records and automatically generates summaries. The generated summaries are stored in a database and quickly distributed to the relevant experts.

[0232] Step 5:

[0233] Based on the information aggregated in the database, the server uses AI to automatically generate treatment plans and care plans for each patient. The generated plans are then notified to the relevant specialist for review.

[0234] Step 6:

[0235] The user enters a question outside their area of ​​expertise using the chat function. The terminal forwards the entered question to the server.

[0236] Step 7:

[0237] The server analyzes the received question and generates an automated response using a generative AI. This response is generated instantly based on relevant data.

[0238] Step 8:

[0239] The terminal displays the response received from the server to the user. The user can then use this response as a reference to proceed with their work.

[0240] Step 9:

[0241] The server implements security measures for all data to prevent unauthorized access and leakage of information. Data is not used for learning models, and any secondary use is monitored and managed to ensure it is done under control.

[0242] (Example 1)

[0243] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0244] In home care and visiting medical settings, inefficiencies and inaccuracies in information sharing are problematic. In particular, human errors in digitizing handwritten records and insufficient prompt responses to specialized questions are factors that reduce the quality of care. Furthermore, the difficulty in dynamically updating care plans based on the patient's latest condition hinders efficient support. This increases the risk of overwork for caregivers and medical professionals, as well as inappropriate care for patients.

[0245] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0246] In this invention, the server includes means for analyzing user information and automatically generating care plans and support plans using generative artificial intelligence, means for converting visit records into electronic data using handwriting recognition technology and centrally managing the information, and means for automatically generating responses to inquiries outside of one's area of ​​expertise based on the analyzed information. This enables the rapid and accurate sharing of information, making it possible to improve the operational efficiency and quality of care in home care settings.

[0247] "Generative artificial intelligence" refers to algorithms and technologies that automatically generate care plans and support plans by analyzing user information.

[0248] "Handwriting recognition technology" is a technology that converts handwritten information into electronic data, and is used when digitizing visitor records and other similar documents.

[0249] "Electronic data" refers to information acquired from physical media through technologies such as handwriting recognition, and then stored and processed electronically.

[0250] "Centralized management" refers to a method of managing data collected from multiple sources in one place to improve access control and information integrity.

[0251] An "inquiry" refers to questions or requests for information from users or stakeholders, and should be addressed promptly even if it falls outside one's area of ​​expertise.

[0252] The embodiments for carrying out the present invention are shown below.

[0253] This system is designed to enable efficient management and sharing of information in home care. The following describes each component of the system and its operation.

[0254] The terminal is a device used by users to input basic patient information, and can be a tablet or laptop. These terminals provide users with an intuitive input interface and have the ability to verify the accuracy of the data in real time. The data is encrypted via the SSL / TLS protocol and securely transmitted to the server.

[0255] The server receives data and centrally manages it in a secure data storage facility. The server is equipped with a generative AI that automatically generates support plans based on the patient's past medical history, current health status, and the latest medical knowledge. This enables medical and care professionals to provide care that is up-to-date. The generative AI utilizes commonly used AI frameworks and models.

[0256] The terminal also scans handwritten records filled out after the visit and converts them into electronic data using handwriting recognition technology. This technology, for example, uses Tesseract. The converted data is sent to a server, where it is automatically summarized by a generating AI.

[0257] Users can ask questions outside their area of ​​expertise through the support chat function. Questions entered in this chat are analyzed by the server, and responses are provided immediately by a generating AI. This improves operational efficiency.

[0258] For example, when a nurse visits a new patient, they scan their notes, and the information is sent to a server for processing. As a result, necessary information is quickly provided to relevant professionals. Furthermore, the server provides appropriate information in response to inquiries about side effects of specific medications, ensuring safety in the field. However, the generated information is to be reviewed by each user to aid in their final decision-making.

[0259] An example of a prompt message would be: "Patient A, a 70-year-old male, has a history of diabetes and hypertension. During the visit, he complained of a cough and a slight fever. Based on the examination results, please generate an appropriate care plan and precautions." This allows the generating AI to provide a professional and realistic care plan.

[0260] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0261] Step 1:

[0262] The user enters the patient's basic information into the terminal. The terminal provides an interface for entering data such as name, age, address, medical history, and allergy information through an on-screen form. The entered information is formally verified on the spot and sent to the server in an encrypted format using the SSL / TLS protocol. As a result, patient information is stored securely.

[0263] Step 2:

[0264] The terminal scans the records that the user has written after their visit. As input, handwritten paper records are digitized using a camera or scanner and imported into the terminal as image data. The terminal applies handwriting recognition technology and uses OCR technology such as Tesseract to convert the image data into text data. This process transforms the user's visit records into a format that can be stored electronically.

[0265] Step 3:

[0266] The server receives text data sent from terminals and stores it centrally in a database. OCR-processed text data is used as input. The server passes this data to a generating AI, which automatically creates a summary for each patient. The AI ​​model then sends the generated summaries to relevant professionals, ensuring the data is shared appropriately.

[0267] Step 4:

[0268] The server uses generative AI to automatically generate individual patient care plans. Input data includes the patient's past medical history and current health status. The generative AI analyzes this data and outputs treatment policies and care plans that reflect the latest medical knowledge. This output is communicated to relevant professionals, who provide feedback and make adjustments as needed.

[0269] Step 5:

[0270] Users enter questions outside their area of ​​expertise using the support chat function. The server analyzes the entered inquiry and prepares an appropriate response using AI generation. The output is an immediate response returned to the user, allowing them to quickly obtain the necessary information. This function enables users to quickly resolve questions that arise in their daily work.

[0271] (Application Example 1)

[0272] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0273] In home care and medical settings, the rapid and accurate management and sharing of patient information is extremely important. However, traditional methods have presented challenges such as delays in digitizing handwritten records and information sharing, which prolong the development and implementation of care plans. Furthermore, there are limited means of checking necessary information in real time during visits, increasing the burden on caregivers. There is a need to solve these problems and improve the efficiency and quality of home care.

[0274] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0275] In this invention, the server includes means for analyzing person information and automatically generating treatment policies and care plans using generative artificial intelligence; means for converting visit records into digital data using document shape recognition technology and integrating and managing the information; and means for using a visual device to allow those involved to quickly refer to the information, receive the analysis results from the artificial intelligence, and display them visually. This makes it possible for caregivers to grasp the patient's condition in real time during visits and to quickly create and implement appropriate care plans.

[0276] "Generative artificial intelligence" is a type of artificial intelligence that analyzes collected personal information and automatically generates treatment plans and care plans.

[0277] "Document shape recognition technology" is a technology that converts handwritten visit records into digital data and manages the information in a centralized manner.

[0278] An "information storage device" is a device used to securely store digitized information and ensure its confidentiality and integrity.

[0279] A "visual device" is a device that allows caregivers to access information in real time and displays the results of AI-generated analysis visually.

[0280] The system that implements this application is designed to streamline information management and care plan generation in home care and medical settings. This system primarily operates through the coordinated efforts of the following three elements:

[0281] First, the user, a care professional, wears a visual device to check patient information. This device, such as smart glasses, allows those involved to instantly receive necessary information on-site. The information displayed on the visual device is retrieved from a vast database managed by a server.

[0282] Next, the terminal digitizes the observations and handwritten records made during the visit in real time. In this process, document shape recognition technology is used to immediately integrate the paper-based memo as data. The terminal sends this data to the server, where the information is centrally managed.

[0283] The server analyzes the aggregated data using generative artificial intelligence. Based on the patient's current health status and past medical history, the artificial intelligence automatically generates a treatment plan and care plan. It also dynamically updates the care plan as needed and reflects the results on the visual device.

[0284] As a specific example, the caregiver observes changes in the patient's heart rate and blood pressure at the visit location. This data is immediately digitized and analyzed by the server. If the server determines based on the analysis that urgent care is needed, it displays an alert to the caregiver through the visual device.

[0285] An example of a prompt sentence is "Please check the patient's past treatment history, generate and display a care plan based on the current health status. Also, check for allergies and issue a warning if there is a risk." With this prompt sentence, the server can perform appropriate processing and provide the necessary information to the user.

[0286] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0287] Step 1:

[0288] The server prepares the data necessary to display the latest patient information on the user's visual device. The inputs include the patient's basic information and medical history obtained from the database. The server organizes this information and performs data processing to extract important information. As output, it generates a data feed for display on the visual device.

[0289] Step 2:

[0290] The user's visual device receives and visualizes a data feed sent from the server in real time. The input is the data feed generated in step 1. The visual device receives this and performs data calculations to visually display the information on the display. The output is an information screen viewable by the user.

[0291] Step 3:

[0292] The user inputs the patient's biometric information observed into the terminal. This input includes biometric data manually acquired by the user, such as heart rate and blood pressure. The terminal receives this data and performs data processing, converting it into a digital format. The output is digital data ready for transmission to the server.

[0293] Step 4:

[0294] The device captures handwritten notes using a camera or scanner and converts them into digital data using document shape recognition technology. The input is a handwritten visitor's note. The device uses image processing and character recognition algorithms to perform data calculations, converting this data into text format. The output is digitized text data.

[0295] Step 5:

[0296] The server uses an AI model to analyze digital data, including biometric information and handwritten notes received from the user. The input consists of all digital data transmitted from the terminal. The server uses artificial intelligence to analyze this data and perform calculations to automatically generate treatment plans and care plans. The output is a care plan that is sent back to the visual device.

[0297] Step 6:

[0298] The server sends alerts and suggestions to the user's visual device based on the analysis results of the generated AI model. The inputs are the care plan and analysis results generated in step 5. The server performs a risk assessment and, if necessary, processes the data to create additional data, including emergency alerts. The outputs include alerts and recommended actions sent to the visual device.

[0299] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0300] The system according to the present invention not only improves the efficiency of information management in home care but also enables responses that take into account the user's emotions. This system supports medical and care professionals in providing the best possible care to patients.

[0301] First, medical and care professionals, acting as users, input basic patient information into a terminal. This information is transmitted to a server via the terminal and securely managed in an encrypted form. The server stores the information in a database and uses AI to automatically generate treatment policies and care plans for each patient.

[0302] Users record information on paper during visits, but the terminal uses handwriting recognition technology to scan the contents and convert them into digital data. The server receives this digitized information, summarizes its contents, distributes it to relevant specialists, and manages it centrally.

[0303] Furthermore, the emotion engine, a key feature of this invention, analyzes user input and voice data to identify the user's emotional state. For example, if the user is experiencing stress, the system flexibly modifies the generated care plan proposal to provide support that is sensitive to the user's feelings. This emotion analysis information is fed back to the server and used to generate future care plans.

[0304] As a specific example, consider the scenario where a nurse visits a patient and leaves a handwritten record. After the visit, the terminal scans the record and converts it into a digital format. This information is immediately sent to the server and shared with all relevant experts along with a summary. At the same time, if the patient's uneasiness and concerns felt by the nurse during the visit are detected by the emotion engine through speech recognition, the system adjusts the care plan based on that feedback to ensure appropriate responses are made.

[0305] Thus, the present invention not only improves the quality of care but also realizes a system that provides more comprehensive support by empathizing with the user's emotions.

[0306] The following describes the processing flow.

[0307] Step 1:

[0308] The user enters the patient's basic information on the terminal. This information includes the patient's name, age, past medical history, allergies, etc. When the input is complete, the terminal securely sends this information to the server.

[0309] Step 2:

[0310] The server stores the received patient information in the database. This data is encrypted for storage as it will be used in later processing. Also, make part of the information accessible to experts as needed.

[0311] Step 3:

[0312] The terminal scans the handwritten record left by the user after the visit. The scanned image data is converted into digital text by handwriting recognition technology. This conversion makes the information electronically processable.

[0313] Step 4:

[0314] The server receives digitized visit records and automatically summarizes their contents. The summarized information is quickly distributed to relevant medical professionals, streamlining information sharing.

[0315] Step 5:

[0316] The server uses AI to analyze all patient data and automatically generates treatment plans and care plans. These plans are individually optimized based on the patient's historical data and the latest medical data.

[0317] Step 6:

[0318] Users input real-time feedback and questions in a chat format via their devices. This input is sent to the server.

[0319] Step 7:

[0320] The emotion engine analyzes user input and voice data to identify their emotional state. The server then adjusts its response based on this analysis, and in some cases, fine-tunes the care plan as well.

[0321] Step 8:

[0322] The terminal displays the adjusted information, care plan, and response content received from the server to the user. This allows the user to provide more appropriate care to the patient.

[0323] Step 9:

[0324] The server manages all data with security measures in place. This prevents information leaks and unauthorized access, while ensuring the strict management of highly confidential information.

[0325] (Example 2)

[0326] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0327] In home care, managing patient information is complex, and efficient information processing is required to enable medical and care professionals to respond effectively. Furthermore, the provision of flexible care plans tailored to each user's individual emotions and condition is also necessary. To address these challenges, a system is needed that allows for centralized information management and efficient individualized responses.

[0328] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0329] In this invention, the server includes means for analyzing service user information and automatically generating treatment plans and support plans using an automated information processing device, means for converting visit records into electronic data using handwriting recognition technology and integrating and managing the information, and means for analyzing voice data to determine the emotional state of the service user and flexibly adjusting the support plan based on that. This enables efficient and secure management of information and the provision of care plans that are sensitive to the user's feelings.

[0330] An "automatic information processing device" is a device that processes user information and automatically generates various plans.

[0331] "Service user information" refers to data including users' personal information and health status related to medical care and nursing care.

[0332] A "treatment plan" is a plan that outlines the specific treatments and support to be provided to an individual who requires medical and nursing care.

[0333] A "support plan" is a plan that outlines the overall support policy to ensure that service users receive appropriate care.

[0334] "Handwriting code recognition technology" is a technology that converts handwritten records into electronic data, and generally uses OCR technology.

[0335] "Electronic data" refers to digital data that has been converted into a format that can be processed by a computer.

[0336] "Integrated information management" means efficiently managing data from different sources within a single system.

[0337] "Audio data" refers to data that records audio information, including user speech and recordings, in digital format.

[0338] "Emotional state" refers to a psychological condition that reflects an individual's feelings and mental state.

[0339] A "care plan" is a specific support plan designed to ensure the health and well-being of the user.

[0340] This invention consists of a system for information management in home care and for empathizing with the user's emotions. The entire system functions through complex operations by a server, terminals, and users.

[0341] First, the user, a medical or care professional, enters the patient's basic information into a terminal. This terminal is primarily a tablet or personal computer, but other portable information devices can also be used if necessary. The entered information is verified on the terminal, encrypted, and then sent to the server.

[0342] The server stores the received information in a database. A commonly used SQL-based management system can be used for database management. Next, the server uses a generative AI model to automatically generate patient-specific treatment and support plans based on the collected information. Various data analysis platforms can be selected as the AI ​​model, and through this process, an initial plan tailored to each patient's needs is created.

[0343] During a visit, the user takes handwritten notes on paper, which are then converted into electronic data using optical character recognition (OCR) technology. The converted data is immediately sent to a server, which analyzes the data and manages the information in an integrated manner. During this process, voice data is also analyzed to determine the emotional state of the user or patient.

[0344] Furthermore, the analyzed information is notified to experts, and the care plan is dynamically updated. If emotional abnormalities are detected during the analysis, the server uses a prompt message to instruct the AI ​​model to "adjust the care plan," thereby improving the plan. An example of a prompt message is, "Propose a stable care plan based on the patient's latest data."

[0345] This enables the system to manage information efficiently and securely, and to provide appropriate support tailored to the emotional state of users and patients.

[0346] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0347] Step 1:

[0348] The user enters the patient's basic information (name, age, medical history, allergy information, etc.) into the terminal. The terminal validates the format of the input data to ensure it is in the correct format. After the input data is validated, the terminal encrypts it. Next, this encrypted data is sent to the server. The output is the transmitted encrypted data.

[0349] Step 2:

[0350] The server decodes the received encrypted patient information and securely stores it in the database. After saving is complete, the server starts the generating AI model and generates prompt messages to input into the AI ​​model. The input is the patient information from earlier, and the output is the generated treatment plan and support plan. In particular, the AI ​​model receives the prompt, "Generate the optimal care plan based on the patient information."

[0351] Step 3:

[0352] Users record the patient's condition and care details on paper during visits. After the visit, the terminal uses optical character recognition (OCR) technology to scan this paper record and convert it into electronic data. Input is a handwritten visit record, and output is electronic data in text format. This digital data is immediately transmitted to the server.

[0353] Step 4:

[0354] The server analyzes the received electronic data and extracts key information using an automated summarization algorithm. The summarized information is then notified to the relevant medical professionals. The input is scanned electronic data, and the output is the summarized information and notification content.

[0355] Step 5:

[0356] The terminal analyzes voice data to determine the emotional state of the user or patient. Once the voice data is analyzed and the emotional state is identified, the results are sent to the server. The server uses this emotional information to dynamically adjust the generated care plan as needed. The input is voice data, and the output is an adapted plan with the information fed back into it.

[0357] Through these steps, the system provides advanced information processing and emotional support tailored to the needs of both the user and the patient.

[0358] (Application Example 2)

[0359] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0360] In today's world, where efficient information management and flexible, emotion-based responses are essential, ensuring efficiency and safety in various tasks is a particularly important challenge. Traditionally, the digitization of handwritten records and the automation of plan adjustments through emotion analysis have been insufficient, making it difficult to manage worker stress and optimize work plans.

[0361] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0362] In this invention, the server includes means for analyzing individual information and automatically generating policies and plans using generative artificial intelligence, means for converting records into digital data and integrating and managing the information using character recognition technology, and means for determining the user's emotional state and dynamically adjusting the plan using emotion analysis technology. This enables automatic adjustment of the work plan according to the emotional state.

[0363] "Generative artificial intelligence" is a technology used to analyze individual information and automatically generate policies and plans.

[0364] "Character recognition technology" is a technology that converts handwritten or printed records into digital data and integrates and manages that information.

[0365] "Emotional analysis technology" is a technology that assesses the user's emotional state and dynamically adjusts plans based on that assessment.

[0366] A "secure storage device" is a device that provides data protection measures for protecting and managing confidential information.

[0367] "Automatic plan adjustment" is a process that flexibly modifies work plans according to emotional states to optimize work efficiency.

[0368] In the system that implements this application, the server uses generative artificial intelligence to analyze individual information and automatically generate policies and plans. When a user leaves handwritten records using a device such as smart glasses, the device uses character recognition technology to convert the records into digital data. This data is sent to the server and centrally managed. The server also uses emotion analysis technology to determine the user's emotional state and dynamically adjust the work plan. This enables automatic adjustment of the work plan according to the worker's stress level. A specific use case would be a factory worker using smart glasses to record their work, and their emotional state would be determined through voice input. An example of a prompt for the generative AI model would be, "Please propose an algorithm that digitizes factory maintenance records and adjusts the work plan according to the worker's emotional state."

[0369] Smart glasses serve as the platform, digitizing data using OCR technologies such as Tesseract, and performing emotion analysis using Google Cloud Speech-to-Text and AWS Comprehend. This system enables centralized data management and dynamic, emotion-based responses, providing a safe and efficient work environment.

[0370] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0371] Step 1:

[0372] The user inputs information into smart glasses. They record it by hand, and the glasses' camera scans the information. The input is handwritten text, and the output is scanned image data. This image data is digitized in subsequent processing.

[0373] Step 2:

[0374] The device processes image data using optical character recognition (OCR) technology and converts it into text data. It receives scanned image data as input and generates text data as output. This conversion process utilizes optical character recognition technology to digitize handwritten information.

[0375] Step 3:

[0376] The server passes the received text data to the generating artificial intelligence, which performs individual data analysis and automatic plan generation. The input is text data, and the output is analyzed data and a generated plan. As part of the data processing, the AI ​​model performs analysis and constructs policies and plans.

[0377] Step 4:

[0378] The user inputs information via voice. Voice data is acquired through the microphone of smart glasses. Voice information is the input, and voice data is obtained as the output. This data is used for sentiment analysis.

[0379] Step 5:

[0380] The server converts audio data into text using speech recognition technology and performs sentiment analysis. It uses tools such as AWS Comprehend to determine the emotional state. The input is the transcribed audio data, and the output is the sentiment analysis result. As a data calculation, it analyzes the user's emotions and identifies their specific state.

[0381] Step 6:

[0382] The server dynamically adjusts the work plan based on the sentiment analysis results and provides feedback to the user. The input is the result of the sentiment analysis, and the output is the generated adjusted work plan, which is then notified to the user. Through this process, the optimal plan is provided according to the user's emotional state.

[0383] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0384] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0385] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0386] [Third Embodiment]

[0387] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0388] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0389] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0390] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0391] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0392] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0393] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0394] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0395] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0396] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0397] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0398] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0399] The system of this invention is designed to improve the efficiency and accuracy of information sharing in home care. The specific operation of each component is described below.

[0400] First, healthcare and care professionals, acting as users, input basic patient information through a terminal. This information includes important data about the patient, such as name, age, address, medical history, and allergy information. The terminal then transmits this data to the server in a secure format.

[0401] Next, the device uses handwriting recognition technology to convert the handwritten records left by the user after their visit into digital data. This conversion process digitizes the visit records, which are then centrally managed on a server. The digitized information is analyzed by a generative AI, and a summary is automatically created.

[0402] The server aggregates all information and uses a generative AI to automatically generate treatment plans and care plans for each patient. The generated care plans are notified to relevant specialists for review and modified as needed. The generative AI's analysis is based on the patient's past medical history, current health status, and the latest medical knowledge.

[0403] The system also includes a support chat function that generates automated responses based on information for questions outside of the user's area of ​​expertise. When a user enters a question in the chat, the server analyzes the question, and the AI ​​generator prepares an appropriate answer. This process provides immediate feedback and supports the smooth execution of tasks.

[0404] For example, after a nurse visits a new patient, they take handwritten notes, which are then scanned and digitized by a terminal. This data is immediately sent to a server, where it is summarized and distributed to other relevant professionals. Furthermore, AI generates an initial care plan based on the patient's symptoms, which is then reviewed and adjusted as needed. In the case of non-specialist questions, such as when a caregiver asks about the side effects of a particular medication via chat, the server provides reference information to support safe care.

[0405] In this way, the system of the present invention enables the rapid and accurate sharing of information, improving operational efficiency and the quality of care in home care settings.

[0406] The following describes the processing flow.

[0407] Step 1:

[0408] The user enters the patient's basic information on the terminal. This includes name, age, address, medical history, and allergy information. Once the input is complete, the terminal organizes this information according to a format, encrypts it, and sends it to the server.

[0409] Step 2:

[0410] The server stores the received patient information in a database. The stored data is further analyzed, and patient history is updated as needed. Information is properly managed to ensure access by all relevant specialists.

[0411] Step 3:

[0412] The user creates a handwritten care record after the visit. This record is scanned using a terminal. The terminal uses handwriting recognition technology to digitize the scanned data and convert it into text format.

[0413] Step 4:

[0414] The server receives digitized visit records and automatically generates summaries. The generated summaries are stored in a database and quickly distributed to the relevant experts.

[0415] Step 5:

[0416] Based on the information aggregated in the database, the server uses AI to automatically generate treatment plans and care plans for each patient. The generated plans are then notified to the relevant specialist for review.

[0417] Step 6:

[0418] The user enters a question outside their area of ​​expertise using the chat function. The terminal forwards the entered question to the server.

[0419] Step 7:

[0420] The server analyzes the received question and generates an automated response using a generative AI. This response is generated instantly based on relevant data.

[0421] Step 8:

[0422] The terminal displays the response received from the server to the user. The user can then use this response as a reference to proceed with their work.

[0423] Step 9:

[0424] The server implements security measures for all data to prevent unauthorized access and leakage of information. Data is not used for learning models, and any secondary use is monitored and managed to ensure it is done under control.

[0425] (Example 1)

[0426] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0427] In home care and visiting medical settings, inefficiencies and inaccuracies in information sharing are problematic. In particular, human errors in digitizing handwritten records and insufficient prompt responses to specialized questions are factors that reduce the quality of care. Furthermore, the difficulty in dynamically updating care plans based on the patient's latest condition hinders efficient support. This increases the risk of overwork for caregivers and medical professionals, as well as inappropriate care for patients.

[0428] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0429] In this invention, the server includes means for analyzing user information and automatically generating care plans and support plans using generative artificial intelligence, means for converting visit records into electronic data using handwriting recognition technology and centrally managing the information, and means for automatically generating responses to inquiries outside of one's area of ​​expertise based on the analyzed information. This enables the rapid and accurate sharing of information, making it possible to improve the operational efficiency and quality of care in home care settings.

[0430] "Generative artificial intelligence" refers to algorithms and technologies that automatically generate care plans and support plans by analyzing user information.

[0431] "Handwriting recognition technology" is a technology that converts handwritten information into electronic data, and is used when digitizing visitor records and other similar documents.

[0432] "Electronic data" refers to information acquired from physical media through technologies such as handwriting recognition, and then stored and processed electronically.

[0433] "Centralized management" refers to a method of managing data collected from multiple sources in one place to improve access control and information integrity.

[0434] An "inquiry" refers to questions or requests for information from users or stakeholders, and should be addressed promptly even if it falls outside one's area of ​​expertise.

[0435] The embodiments for carrying out the present invention are shown below.

[0436] This system is designed to enable efficient management and sharing of information in home care. The following describes each component of the system and its operation.

[0437] The terminal is a device used by users to input basic patient information, and can be a tablet or laptop. These terminals provide users with an intuitive input interface and have the ability to verify the accuracy of the data in real time. The data is encrypted via the SSL / TLS protocol and securely transmitted to the server.

[0438] The server receives data and centrally manages it in a secure data storage facility. The server is equipped with a generative AI that automatically generates support plans based on the patient's past medical history, current health status, and the latest medical knowledge. This enables medical and care professionals to provide care that is up-to-date. The generative AI utilizes commonly used AI frameworks and models.

[0439] The terminal also scans handwritten records filled out after the visit and converts them into electronic data using handwriting recognition technology. This technology, for example, uses Tesseract. The converted data is sent to a server, where it is automatically summarized by a generating AI.

[0440] Users can ask questions outside their area of ​​expertise through the support chat function. Questions entered in this chat are analyzed by the server, and responses are provided immediately by a generating AI. This improves operational efficiency.

[0441] For example, when a nurse visits a new patient, they scan their notes, and the information is sent to a server for processing. As a result, necessary information is quickly provided to relevant professionals. Furthermore, the server provides appropriate information in response to inquiries about side effects of specific medications, ensuring safety in the field. However, the generated information is to be reviewed by each user to aid in their final decision-making.

[0442] An example of a prompt message would be: "Patient A, a 70-year-old male, has a history of diabetes and hypertension. During the visit, he complained of a cough and a slight fever. Based on the examination results, please generate an appropriate care plan and precautions." This allows the generating AI to provide a professional and realistic care plan.

[0443] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0444] Step 1:

[0445] The user enters the patient's basic information into the terminal. The terminal provides an interface for entering data such as name, age, address, medical history, and allergy information through an on-screen form. The entered information is formally verified on the spot and sent to the server in an encrypted format using the SSL / TLS protocol. As a result, patient information is stored securely.

[0446] Step 2:

[0447] The terminal scans the records that the user has written after their visit. As input, handwritten paper records are digitized using a camera or scanner and imported into the terminal as image data. The terminal applies handwriting recognition technology and uses OCR technology such as Tesseract to convert the image data into text data. This process transforms the user's visit records into a format that can be stored electronically.

[0448] Step 3:

[0449] The server receives text data sent from terminals and stores it centrally in a database. OCR-processed text data is used as input. The server passes this data to a generating AI, which automatically creates a summary for each patient. The AI ​​model then sends the generated summaries to relevant professionals, ensuring the data is shared appropriately.

[0450] Step 4:

[0451] The server uses generative AI to automatically generate individual patient care plans. Input data includes the patient's past medical history and current health status. The generative AI analyzes this data and outputs treatment policies and care plans that reflect the latest medical knowledge. This output is communicated to relevant professionals, who provide feedback and make adjustments as needed.

[0452] Step 5:

[0453] Users enter questions outside their area of ​​expertise using the support chat function. The server analyzes the entered inquiry and prepares an appropriate response using AI generation. The output is an immediate response returned to the user, allowing them to quickly obtain the necessary information. This function enables users to quickly resolve questions that arise in their daily work.

[0454] (Application Example 1)

[0455] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0456] In home care and medical settings, the rapid and accurate management and sharing of patient information is extremely important. However, traditional methods have presented challenges such as delays in digitizing handwritten records and information sharing, which prolong the development and implementation of care plans. Furthermore, there are limited means of checking necessary information in real time during visits, increasing the burden on caregivers. There is a need to solve these problems and improve the efficiency and quality of home care.

[0457] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0458] In this invention, the server includes means for analyzing person information and automatically generating treatment policies and care plans using generative artificial intelligence; means for converting visit records into digital data using document shape recognition technology and integrating and managing the information; and means for using a visual device to allow those involved to quickly refer to the information, receive the analysis results from the artificial intelligence, and display them visually. This makes it possible for caregivers to grasp the patient's condition in real time during visits and to quickly create and implement appropriate care plans.

[0459] "Generative artificial intelligence" is a type of artificial intelligence that analyzes collected personal information and automatically generates treatment plans and care plans.

[0460] "Document shape recognition technology" is a technology that converts handwritten visit records into digital data and manages the information in a centralized manner.

[0461] An "information storage device" is a device used to securely store digitized information and ensure its confidentiality and integrity.

[0462] A "visual device" is a device that allows caregivers to access information in real time and displays the results of AI-generated analysis visually.

[0463] The system that implements this application is designed to streamline information management and care plan generation in home care and medical settings. This system primarily operates through the coordinated efforts of the following three elements:

[0464] First, the user, a care professional, wears a visual device to check patient information. This device, such as smart glasses, allows those involved to instantly receive necessary information on-site. The information displayed on the visual device is retrieved from a vast database managed by a server.

[0465] Next, the terminal digitizes observations and handwritten records made during the visit in real time. This process uses document shape recognition technology to instantly integrate paper notes as data. The terminal sends this data to a server, where the information is centrally managed.

[0466] The server uses generative artificial intelligence to analyze the aggregated data. Based on the patient's current health status and past medical history, the AI ​​automatically generates treatment plans and care plans. It also dynamically updates the care plan as needed and reflects the results on the visual display.

[0467] As a concrete example, a caregiver observes changes in a patient's heart rate and blood pressure during a visit. This data is immediately digitized and analyzed on a server. Based on the analysis, if the server determines that urgent care is needed, it displays an alert to the caregiver via a visual device.

[0468] An example of a prompt message is: "Review this patient's past treatment history and generate and display a care plan based on their current health status. Also, check for allergies and issue a warning if there are any risks." This prompt message allows the server to perform the appropriate actions and provide the user with the necessary information.

[0469] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0470] Step 1:

[0471] The server prepares the data necessary to display the latest patient information on the user's visual device. Inputs include basic patient information and medical history retrieved from a database. The server organizes this information and performs data processing to extract important details. Output is a data feed for display on the visual device.

[0472] Step 2:

[0473] The user's visual device receives and visualizes a data feed sent from the server in real time. The input is the data feed generated in step 1. The visual device receives this and performs data calculations to visually display the information on the display. The output is an information screen viewable by the user.

[0474] Step 3:

[0475] The user inputs the patient's biometric information observed into the terminal. This input includes biometric data manually acquired by the user, such as heart rate and blood pressure. The terminal receives this data and performs data processing, converting it into a digital format. The output is digital data ready for transmission to the server.

[0476] Step 4:

[0477] The device captures handwritten notes using a camera or scanner and converts them into digital data using document shape recognition technology. The input is a handwritten visitor's note. The device uses image processing and character recognition algorithms to perform data calculations, converting this data into text format. The output is digitized text data.

[0478] Step 5:

[0479] The server uses an AI model to analyze digital data, including biometric information and handwritten notes received from the user. The input consists of all digital data transmitted from the terminal. The server uses artificial intelligence to analyze this data and perform calculations to automatically generate treatment plans and care plans. The output is a care plan that is sent back to the visual device.

[0480] Step 6:

[0481] The server sends alerts and suggestions to the user's visual device based on the analysis results of the generated AI model. The inputs are the care plan and analysis results generated in step 5. The server performs a risk assessment and, if necessary, processes the data to create additional data, including emergency alerts. The outputs include alerts and recommended actions sent to the visual device.

[0482] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0483] The system according to the present invention not only improves the efficiency of information management in home care but also enables responses that take into account the user's emotions. This system supports medical and care professionals in providing the best possible care to patients.

[0484] First, medical and care professionals, acting as users, input basic patient information into a terminal. This information is transmitted to a server via the terminal and securely managed in an encrypted form. The server stores the information in a database and uses AI to automatically generate treatment policies and care plans for each patient.

[0485] Users record information on paper during visits, but the terminal uses handwriting recognition technology to scan the contents and convert them into digital data. The server receives this digitized information, summarizes its contents, distributes it to relevant specialists, and manages it centrally.

[0486] Furthermore, the emotion engine, a key feature of this invention, analyzes user input and voice data to identify the user's emotional state. For example, if the user is experiencing stress, the system flexibly modifies the generated care plan proposal to provide support that is sensitive to the user's feelings. This emotion analysis information is fed back to the server and used to generate future care plans.

[0487] As a concrete example, consider a scenario where a nurse visits a patient and takes handwritten notes. After the visit, a device scans the notes and converts them into a digital format. This information is immediately sent to a server and shared with all relevant professionals along with a summary. Simultaneously, if the patient's anxiety or concerns that the nurse felt during the visit are detected by an emotion engine via speech recognition, the system adjusts the care plan based on that feedback to ensure appropriate responses are taken.

[0488] Thus, the present invention not only improves the quality of care but also realizes a system that provides more comprehensive support by being attentive to the user's emotions.

[0489] The following describes the processing flow.

[0490] Step 1:

[0491] The user enters the patient's basic information on the terminal. This information includes the patient's name, age, medical history, allergies, etc. Once the input is complete, the terminal securely transmits this information to the server.

[0492] Step 2:

[0493] The server stores the received patient information in a database. This data is encrypted and stored for use in subsequent processing. Additionally, some of the information is made accessible to specialists as needed.

[0494] Step 3:

[0495] The terminal scans the handwritten records left by the user after their visit. The scanned image data is converted into digital text using handwriting recognition technology. This conversion makes the information electronically processable.

[0496] Step 4:

[0497] The server receives digitized visit records and automatically summarizes their contents. The summarized information is quickly distributed to relevant medical professionals, streamlining information sharing.

[0498] Step 5:

[0499] The server uses AI to analyze all patient data and automatically generates treatment plans and care plans. These plans are individually optimized based on the patient's historical data and the latest medical data.

[0500] Step 6:

[0501] Users input real-time feedback and questions in a chat format via their devices. This input is sent to the server.

[0502] Step 7:

[0503] The emotion engine analyzes user input and voice data to identify their emotional state. The server then adjusts its response based on this analysis, and in some cases, fine-tunes the care plan as well.

[0504] Step 8:

[0505] The terminal displays the adjusted information, care plan, and response content received from the server to the user. This allows the user to provide more appropriate care to the patient.

[0506] Step 9:

[0507] The server manages all data with security measures in place. This prevents information leaks and unauthorized access, while ensuring the strict management of highly confidential information.

[0508] (Example 2)

[0509] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0510] In home care, managing patient information is complex, and efficient information processing is required to enable medical and care professionals to respond effectively. Furthermore, the provision of flexible care plans tailored to each user's individual emotions and condition is also necessary. To address these challenges, a system is needed that allows for centralized information management and efficient individualized responses.

[0511] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0512] In this invention, the server includes means for analyzing service user information and automatically generating treatment plans and support plans using an automated information processing device, means for converting visit records into electronic data using handwriting recognition technology and integrating and managing the information, and means for analyzing voice data to determine the emotional state of the service user and flexibly adjusting the support plan based on that. This enables efficient and secure management of information and the provision of care plans that are sensitive to the user's feelings.

[0513] An "automatic information processing device" is a device that processes user information and automatically generates various plans.

[0514] "Service user information" refers to data including users' personal information and health status related to medical care and nursing care.

[0515] A "treatment plan" is a plan that outlines the specific treatments and support to be provided to an individual who requires medical and nursing care.

[0516] A "support plan" is a plan that outlines the overall support policy to ensure that service users receive appropriate care.

[0517] "Handwriting code recognition technology" is a technology that converts handwritten records into electronic data, and generally uses OCR technology.

[0518] "Electronic data" refers to digital data that has been converted into a format that can be processed by a computer.

[0519] "Integrated information management" means efficiently managing data from different sources within a single system.

[0520] "Audio data" refers to data that records audio information, including user speech and recordings, in digital format.

[0521] "Emotional state" refers to a psychological condition that reflects an individual's feelings and mental state.

[0522] A "care plan" is a specific support plan designed to ensure the health and well-being of the user.

[0523] This invention consists of a system for information management in home care and for empathizing with the user's emotions. The entire system functions through complex operations by a server, terminals, and users.

[0524] First, the user, a medical or care professional, enters the patient's basic information into a terminal. This terminal is primarily a tablet or personal computer, but other portable information devices can also be used if necessary. The entered information is verified on the terminal, encrypted, and then sent to the server.

[0525] The server stores the received information in a database. A commonly used SQL-based management system can be used for database management. Next, the server uses a generative AI model to automatically generate patient-specific treatment and support plans based on the collected information. Various data analysis platforms can be selected as the AI ​​model, and through this process, an initial plan tailored to each patient's needs is created.

[0526] During a visit, the user takes handwritten notes on paper, which are then converted into electronic data using optical character recognition (OCR) technology. The converted data is immediately sent to a server, which analyzes the data and manages the information in an integrated manner. During this process, voice data is also analyzed to determine the emotional state of the user or patient.

[0527] Furthermore, the analyzed information is notified to experts, and the care plan is dynamically updated. If emotional abnormalities are detected during the analysis, the server uses a prompt message to instruct the AI ​​model to "adjust the care plan," thereby improving the plan. An example of a prompt message is, "Propose a stable care plan based on the patient's latest data."

[0528] This enables the system to manage information efficiently and securely, and to provide appropriate support tailored to the emotional state of users and patients.

[0529] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0530] Step 1:

[0531] The user enters the patient's basic information (name, age, medical history, allergy information, etc.) into the terminal. The terminal validates the format of the input data to ensure it is in the correct format. After the input data is validated, the terminal encrypts it. Next, this encrypted data is sent to the server. The output is the transmitted encrypted data.

[0532] Step 2:

[0533] The server decodes the received encrypted patient information and securely stores it in the database. After saving is complete, the server starts the generating AI model and generates prompt messages to input into the AI ​​model. The input is the patient information from earlier, and the output is the generated treatment plan and support plan. In particular, the AI ​​model receives the prompt, "Generate the optimal care plan based on the patient information."

[0534] Step 3:

[0535] Users record the patient's condition and care details on paper during visits. After the visit, the terminal uses optical character recognition (OCR) technology to scan this paper record and convert it into electronic data. Input is a handwritten visit record, and output is electronic data in text format. This digital data is immediately transmitted to the server.

[0536] Step 4:

[0537] The server analyzes the received electronic data and extracts key information using an automated summarization algorithm. The summarized information is then notified to the relevant medical professionals. The input is scanned electronic data, and the output is the summarized information and notification content.

[0538] Step 5:

[0539] The terminal analyzes voice data to determine the emotional state of the user or patient. Once the voice data is analyzed and the emotional state is identified, the results are sent to the server. The server uses this emotional information to dynamically adjust the generated care plan as needed. The input is voice data, and the output is an adapted plan with the information fed back into it.

[0540] Through these steps, the system provides advanced information processing and emotional support tailored to the needs of both the user and the patient.

[0541] (Application Example 2)

[0542] Next, we will explain Application Example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0543] In today's world, where efficient information management and flexible, emotion-based responses are essential, ensuring efficiency and safety in various tasks is a particularly important challenge. Traditionally, the digitization of handwritten records and the automation of plan adjustments through emotion analysis have been insufficient, making it difficult to manage worker stress and optimize work plans.

[0544] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0545] In this invention, the server includes means for analyzing individual information and automatically generating policies and plans using generative artificial intelligence, means for converting records into digital data and integrating and managing the information using character recognition technology, and means for determining the user's emotional state and dynamically adjusting the plan using emotion analysis technology. This enables automatic adjustment of the work plan according to the emotional state.

[0546] "Generative artificial intelligence" is a technology used to analyze individual information and automatically generate policies and plans.

[0547] "Character recognition technology" is a technology that converts handwritten or printed records into digital data and integrates and manages that information.

[0548] "Emotional analysis technology" is a technology that assesses the user's emotional state and dynamically adjusts plans based on that assessment.

[0549] A "secure storage device" is a device that provides data protection measures for protecting and managing confidential information.

[0550] "Automatic plan adjustment" is a process that flexibly modifies work plans according to emotional states to optimize work efficiency.

[0551] In the system that implements this application, the server uses generative artificial intelligence to analyze individual information and automatically generate policies and plans. When a user leaves handwritten records using a device such as smart glasses, the device uses character recognition technology to convert the records into digital data. This data is sent to the server and centrally managed. The server also uses emotion analysis technology to determine the user's emotional state and dynamically adjust the work plan. This enables automatic adjustment of the work plan according to the worker's stress level. A specific use case would be a factory worker using smart glasses to record their work, and their emotional state would be determined through voice input. An example of a prompt for the generative AI model would be, "Please propose an algorithm that digitizes factory maintenance records and adjusts the work plan according to the worker's emotional state."

[0552] Smart glasses serve as the platform, digitizing data using OCR technologies such as Tesseract, and performing emotion analysis using Google Cloud Speech-to-Text and AWS Comprehend. This system enables centralized data management and dynamic, emotion-based responses, providing a safe and efficient work environment.

[0553] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0554] Step 1:

[0555] The user inputs information into smart glasses. They record it by hand, and the glasses' camera scans the information. The input is handwritten text, and the output is scanned image data. This image data is digitized in subsequent processing.

[0556] Step 2:

[0557] The device processes image data using optical character recognition (OCR) technology and converts it into text data. It receives scanned image data as input and generates text data as output. This conversion process utilizes optical character recognition technology to digitize handwritten information.

[0558] Step 3:

[0559] The server passes the received text data to the generating artificial intelligence, which performs individual data analysis and automatic plan generation. The input is text data, and the output is analyzed data and a generated plan. As part of the data processing, the AI ​​model performs analysis and constructs policies and plans.

[0560] Step 4:

[0561] The user inputs information via voice. Voice data is acquired through the microphone of smart glasses. Voice information is the input, and voice data is obtained as the output. This data is used for sentiment analysis.

[0562] Step 5:

[0563] The server converts audio data into text using speech recognition technology and performs sentiment analysis. It uses tools such as AWS Comprehend to determine the emotional state. The input is the transcribed audio data, and the output is the sentiment analysis result. As a data calculation, it analyzes the user's emotions and identifies their specific state.

[0564] Step 6:

[0565] The server dynamically adjusts the work plan based on the sentiment analysis results and provides feedback to the user. The input is the result of the sentiment analysis, and the output is the generated adjusted work plan, which is then notified to the user. Through this process, the optimal plan is provided according to the user's emotional state.

[0566] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0567] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0568] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0569] [Fourth Embodiment]

[0570] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0571] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0572] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0573] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0574] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0575] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0576] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0577] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0578] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0579] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0580] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0581] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0582] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0583] The system of this invention is designed to improve the efficiency and accuracy of information sharing in home care. The specific operation of each component is described below.

[0584] First, healthcare and care professionals, acting as users, input basic patient information through a terminal. This information includes important data about the patient, such as name, age, address, medical history, and allergy information. The terminal then transmits this data to the server in a secure format.

[0585] Next, the device uses handwriting recognition technology to convert the handwritten records left by the user after their visit into digital data. This conversion process digitizes the visit records, which are then centrally managed on a server. The digitized information is analyzed by a generative AI, and a summary is automatically created.

[0586] The server aggregates all information and uses a generative AI to automatically generate treatment plans and care plans for each patient. The generated care plans are notified to relevant specialists for review and modified as needed. The generative AI's analysis is based on the patient's past medical history, current health status, and the latest medical knowledge.

[0587] The system also includes a support chat function that generates automated responses based on information for questions outside of the user's area of ​​expertise. When a user enters a question in the chat, the server analyzes the question, and the AI ​​generator prepares an appropriate answer. This process provides immediate feedback and supports the smooth execution of tasks.

[0588] For example, after a nurse visits a new patient, they take handwritten notes, which are then scanned and digitized by a terminal. This data is immediately sent to a server, where it is summarized and distributed to other relevant professionals. Furthermore, AI generates an initial care plan based on the patient's symptoms, which is then reviewed and adjusted as needed. In the case of non-specialist questions, such as when a caregiver asks about the side effects of a particular medication via chat, the server provides reference information to support safe care.

[0589] In this way, the system of the present invention enables the rapid and accurate sharing of information, improving operational efficiency and the quality of care in home care settings.

[0590] The following describes the processing flow.

[0591] Step 1:

[0592] The user enters the patient's basic information on the terminal. This includes name, age, address, medical history, and allergy information. Once the input is complete, the terminal organizes this information according to a format, encrypts it, and sends it to the server.

[0593] Step 2:

[0594] The server stores the received patient information in a database. The stored data is further analyzed, and patient history is updated as needed. Information is properly managed to ensure access by all relevant specialists.

[0595] Step 3:

[0596] The user creates a handwritten care record after the visit. This record is scanned using a terminal. The terminal uses handwriting recognition technology to digitize the scanned data and convert it into text format.

[0597] Step 4:

[0598] The server receives digitized visit records and automatically generates summaries. The generated summaries are stored in a database and quickly distributed to the relevant experts.

[0599] Step 5:

[0600] Based on the information aggregated in the database, the server uses AI to automatically generate treatment plans and care plans for each patient. The generated plans are then notified to the relevant specialist for review.

[0601] Step 6:

[0602] The user enters a question outside their area of ​​expertise using the chat function. The terminal forwards the entered question to the server.

[0603] Step 7:

[0604] The server analyzes the received question and generates an automated response using a generative AI. This response is generated instantly based on relevant data.

[0605] Step 8:

[0606] The terminal displays the response received from the server to the user. The user can then use this response as a reference to proceed with their work.

[0607] Step 9:

[0608] The server implements security measures for all data to prevent unauthorized access and leakage of information. Data is not used for learning models, and any secondary use is monitored and managed to ensure it is done under control.

[0609] (Example 1)

[0610] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0611] In home care and visiting medical settings, inefficiencies and inaccuracies in information sharing are problematic. In particular, human errors in digitizing handwritten records and insufficient prompt responses to specialized questions are factors that reduce the quality of care. Furthermore, the difficulty in dynamically updating care plans based on the patient's latest condition hinders efficient support. This increases the risk of overwork for caregivers and medical professionals, as well as inappropriate care for patients.

[0612] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0613] In this invention, the server includes means for analyzing user information and automatically generating care plans and support plans using generative artificial intelligence, means for converting visit records into electronic data using handwriting recognition technology and centrally managing the information, and means for automatically generating responses to inquiries outside of one's area of ​​expertise based on the analyzed information. This enables the rapid and accurate sharing of information, making it possible to improve the operational efficiency and quality of care in home care settings.

[0614] "Generative artificial intelligence" refers to algorithms and technologies that automatically generate care plans and support plans by analyzing user information.

[0615] "Handwriting recognition technology" is a technology that converts handwritten information into electronic data, and is used when digitizing visitor records and other similar documents.

[0616] "Electronic data" refers to information acquired from physical media through technologies such as handwriting recognition, and then stored and processed electronically.

[0617] "Centralized management" refers to a method of managing data collected from multiple sources in one place to improve access control and information integrity.

[0618] An "inquiry" refers to questions or requests for information from users or stakeholders, and should be addressed promptly even if it falls outside one's area of ​​expertise.

[0619] The embodiments for carrying out the present invention are shown below.

[0620] This system is designed to enable efficient management and sharing of information in home care. The following describes each component of the system and its operation.

[0621] The terminal is a device used by users to input basic patient information, and can be a tablet or laptop. These terminals provide users with an intuitive input interface and have the ability to verify the accuracy of the data in real time. The data is encrypted via the SSL / TLS protocol and securely transmitted to the server.

[0622] The server receives data and centrally manages it in a secure data storage facility. The server is equipped with a generative AI that automatically generates support plans based on the patient's past medical history, current health status, and the latest medical knowledge. This enables medical and care professionals to provide care that is up-to-date. The generative AI utilizes commonly used AI frameworks and models.

[0623] The terminal also scans handwritten records filled out after the visit and converts them into electronic data using handwriting recognition technology. This technology, for example, uses Tesseract. The converted data is sent to a server, where it is automatically summarized by a generating AI.

[0624] Users can ask questions outside their area of ​​expertise through the support chat function. Questions entered in this chat are analyzed by the server, and responses are provided immediately by a generating AI. This improves operational efficiency.

[0625] For example, when a nurse visits a new patient, they scan their notes, and the information is sent to a server for processing. As a result, necessary information is quickly provided to relevant professionals. Furthermore, the server provides appropriate information in response to inquiries about side effects of specific medications, ensuring safety in the field. However, the generated information is to be reviewed by each user to aid in their final decision-making.

[0626] An example of a prompt message would be: "Patient A, a 70-year-old male, has a history of diabetes and hypertension. During the visit, he complained of a cough and a slight fever. Based on the examination results, please generate an appropriate care plan and precautions." This allows the generating AI to provide a professional and realistic care plan.

[0627] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0628] Step 1:

[0629] The user enters the patient's basic information into the terminal. The terminal provides an interface for entering data such as name, age, address, medical history, and allergy information through an on-screen form. The entered information is formally verified on the spot and sent to the server in an encrypted format using the SSL / TLS protocol. As a result, patient information is stored securely.

[0630] Step 2:

[0631] The terminal scans the records that the user has written after their visit. As input, handwritten paper records are digitized using a camera or scanner and imported into the terminal as image data. The terminal applies handwriting recognition technology and uses OCR technology such as Tesseract to convert the image data into text data. This process transforms the user's visit records into a format that can be stored electronically.

[0632] Step 3:

[0633] The server receives text data sent from terminals and stores it centrally in a database. OCR-processed text data is used as input. The server passes this data to a generating AI, which automatically creates a summary for each patient. The AI ​​model then sends the generated summaries to relevant professionals, ensuring the data is shared appropriately.

[0634] Step 4:

[0635] The server uses generative AI to automatically generate individual patient care plans. Input data includes the patient's past medical history and current health status. The generative AI analyzes this data and outputs treatment policies and care plans that reflect the latest medical knowledge. This output is communicated to relevant professionals, who provide feedback and make adjustments as needed.

[0636] Step 5:

[0637] Users enter questions outside their area of ​​expertise using the support chat function. The server analyzes the entered inquiry and prepares an appropriate response using AI generation. The output is an immediate response returned to the user, allowing them to quickly obtain the necessary information. This function enables users to quickly resolve questions that arise in their daily work.

[0638] (Application Example 1)

[0639] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0640] In home care and medical settings, the rapid and accurate management and sharing of patient information is extremely important. However, traditional methods have presented challenges such as delays in digitizing handwritten records and information sharing, which prolong the development and implementation of care plans. Furthermore, there are limited means of checking necessary information in real time during visits, increasing the burden on caregivers. There is a need to solve these problems and improve the efficiency and quality of home care.

[0641] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0642] In this invention, the server includes means for analyzing person information and automatically generating treatment policies and care plans using generative artificial intelligence; means for converting visit records into digital data using document shape recognition technology and integrating and managing the information; and means for using a visual device to allow those involved to quickly refer to the information, receive the analysis results from the artificial intelligence, and display them visually. This makes it possible for caregivers to grasp the patient's condition in real time during visits and to quickly create and implement appropriate care plans.

[0643] "Generative artificial intelligence" is a type of artificial intelligence that analyzes collected personal information and automatically generates treatment plans and care plans.

[0644] "Document shape recognition technology" is a technology that converts handwritten visit records into digital data and manages the information in a centralized manner.

[0645] An "information storage device" is a device used to securely store digitized information and ensure its confidentiality and integrity.

[0646] A "visual device" is a device that allows caregivers to access information in real time and displays the results of AI-generated analysis visually.

[0647] The system that implements this application is designed to streamline information management and care plan generation in home care and medical settings. This system primarily operates through the coordinated efforts of the following three elements:

[0648] First, the user, a care professional, wears a visual device to check patient information. This device, such as smart glasses, allows those involved to instantly receive necessary information on-site. The information displayed on the visual device is retrieved from a vast database managed by a server.

[0649] Next, the terminal digitizes observations and handwritten records made during the visit in real time. This process uses document shape recognition technology to instantly integrate paper notes as data. The terminal sends this data to a server, where the information is centrally managed.

[0650] The server uses generative artificial intelligence to analyze the aggregated data. Based on the patient's current health status and past medical history, the AI ​​automatically generates treatment plans and care plans. It also dynamically updates the care plan as needed and reflects the results on the visual display.

[0651] As a concrete example, a caregiver observes changes in a patient's heart rate and blood pressure during a visit. This data is immediately digitized and analyzed on a server. Based on the analysis, if the server determines that urgent care is needed, it displays an alert to the caregiver via a visual device.

[0652] An example of a prompt message is: "Review this patient's past treatment history and generate and display a care plan based on their current health status. Also, check for allergies and issue a warning if there are any risks." This prompt message allows the server to perform the appropriate actions and provide the user with the necessary information.

[0653] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0654] Step 1:

[0655] The server prepares the data necessary to display the latest patient information on the user's visual device. Inputs include basic patient information and medical history retrieved from a database. The server organizes this information and performs data processing to extract important details. Output is a data feed for display on the visual device.

[0656] Step 2:

[0657] The user's visual device receives and visualizes a data feed sent from the server in real time. The input is the data feed generated in step 1. The visual device receives this and performs data calculations to visually display the information on the display. The output is an information screen viewable by the user.

[0658] Step 3:

[0659] The user inputs the patient's biometric information observed into the terminal. This input includes biometric data manually acquired by the user, such as heart rate and blood pressure. The terminal receives this data and performs data processing, converting it into a digital format. The output is digital data ready for transmission to the server.

[0660] Step 4:

[0661] The device captures handwritten notes using a camera or scanner and converts them into digital data using document shape recognition technology. The input is a handwritten visitor's note. The device uses image processing and character recognition algorithms to perform data calculations, converting this data into text format. The output is digitized text data.

[0662] Step 5:

[0663] The server uses an AI model to analyze digital data, including biometric information and handwritten notes received from the user. The input consists of all digital data transmitted from the terminal. The server uses artificial intelligence to analyze this data and perform calculations to automatically generate treatment plans and care plans. The output is a care plan that is sent back to the visual device.

[0664] Step 6:

[0665] The server sends alerts and suggestions to the user's visual device based on the analysis results of the generated AI model. The inputs are the care plan and analysis results generated in step 5. The server performs a risk assessment and, if necessary, processes the data to create additional data, including emergency alerts. The outputs include alerts and recommended actions sent to the visual device.

[0666] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0667] The system according to the present invention not only improves the efficiency of information management in home care but also enables responses that take into account the user's emotions. This system supports medical and care professionals in providing the best possible care to patients.

[0668] First, medical and care professionals, acting as users, input basic patient information into a terminal. This information is transmitted to a server via the terminal and securely managed in an encrypted form. The server stores the information in a database and uses AI to automatically generate treatment policies and care plans for each patient.

[0669] Users record information on paper during visits, but the terminal uses handwriting recognition technology to scan the contents and convert them into digital data. The server receives this digitized information, summarizes its contents, distributes it to relevant specialists, and manages it centrally.

[0670] Furthermore, the emotion engine, a key feature of this invention, analyzes user input and voice data to identify the user's emotional state. For example, if the user is experiencing stress, the system flexibly modifies the generated care plan proposal to provide support that is sensitive to the user's feelings. This emotion analysis information is fed back to the server and used to generate future care plans.

[0671] As a concrete example, consider a scenario where a nurse visits a patient and takes handwritten notes. After the visit, a device scans the notes and converts them into a digital format. This information is immediately sent to a server and shared with all relevant professionals along with a summary. Simultaneously, if the patient's anxiety or concerns that the nurse felt during the visit are detected by an emotion engine via speech recognition, the system adjusts the care plan based on that feedback to ensure appropriate responses are taken.

[0672] Thus, the present invention not only improves the quality of care but also realizes a system that provides more comprehensive support by being attentive to the user's emotions.

[0673] The following describes the processing flow.

[0674] Step 1:

[0675] The user enters the patient's basic information on the terminal. This information includes the patient's name, age, medical history, allergies, etc. Once the input is complete, the terminal securely transmits this information to the server.

[0676] Step 2:

[0677] The server stores the received patient information in a database. This data is encrypted and stored for use in subsequent processing. Additionally, some of the information is made accessible to specialists as needed.

[0678] Step 3:

[0679] The terminal scans the handwritten records left by the user after their visit. The scanned image data is converted into digital text using handwriting recognition technology. This conversion makes the information electronically processable.

[0680] Step 4:

[0681] The server receives digitized visit records and automatically summarizes their contents. The summarized information is quickly distributed to relevant medical professionals, streamlining information sharing.

[0682] Step 5:

[0683] The server uses AI to analyze all patient data and automatically generates treatment plans and care plans. These plans are individually optimized based on the patient's historical data and the latest medical data.

[0684] Step 6:

[0685] Users input real-time feedback and questions in a chat format via their devices. This input is sent to the server.

[0686] Step 7:

[0687] The emotion engine analyzes user input and voice data to identify their emotional state. The server then adjusts its response based on this analysis, and in some cases, fine-tunes the care plan as well.

[0688] Step 8:

[0689] The terminal displays the adjusted information, care plan, and response content received from the server to the user. This allows the user to provide more appropriate care to the patient.

[0690] Step 9:

[0691] The server manages all data with security measures in place. This prevents information leaks and unauthorized access, while ensuring the strict management of highly confidential information.

[0692] (Example 2)

[0693] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0694] In home care, managing patient information is complex, and efficient information processing is required to enable medical and care professionals to respond effectively. Furthermore, the provision of flexible care plans tailored to each user's individual emotions and condition is also necessary. To address these challenges, a system is needed that allows for centralized information management and efficient individualized responses.

[0695] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0696] In this invention, the server includes means for analyzing service user information and automatically generating treatment plans and support plans using an automated information processing device, means for converting visit records into electronic data using handwriting recognition technology and integrating and managing the information, and means for analyzing voice data to determine the emotional state of the service user and flexibly adjusting the support plan based on that. This enables efficient and secure management of information and the provision of care plans that are sensitive to the user's feelings.

[0697] An "automatic information processing device" is a device that processes user information and automatically generates various plans.

[0698] "Service user information" refers to data including users' personal information and health status related to medical care and nursing care.

[0699] A "treatment plan" is a plan that outlines the specific treatments and support to be provided to an individual who requires medical and nursing care.

[0700] A "support plan" is a plan that outlines the overall support policy to ensure that service users receive appropriate care.

[0701] "Handwriting code recognition technology" is a technology that converts handwritten records into electronic data, and generally uses OCR technology.

[0702] "Electronic data" refers to digital data that has been converted into a format that can be processed by a computer.

[0703] "Integrated information management" means efficiently managing data from different sources within a single system.

[0704] "Audio data" refers to data that records audio information, including user speech and recordings, in digital format.

[0705] "Emotional state" refers to a psychological condition that reflects an individual's feelings and mental state.

[0706] A "care plan" is a specific support plan designed to ensure the health and well-being of the user.

[0707] This invention consists of a system for information management in home care and for empathizing with the user's emotions. The entire system functions through complex operations by a server, terminals, and users.

[0708] First, the user, a medical or care professional, enters the patient's basic information into a terminal. This terminal is primarily a tablet or personal computer, but other portable information devices can also be used if necessary. The entered information is verified on the terminal, encrypted, and then sent to the server.

[0709] The server stores the received information in a database. A commonly used SQL-based management system can be used for database management. Next, the server uses a generative AI model to automatically generate patient-specific treatment and support plans based on the collected information. Various data analysis platforms can be selected as the AI ​​model, and through this process, an initial plan tailored to each patient's needs is created.

[0710] During a visit, the user takes handwritten notes on paper, which are then converted into electronic data using optical character recognition (OCR) technology. The converted data is immediately sent to a server, which analyzes the data and manages the information in an integrated manner. During this process, voice data is also analyzed to determine the emotional state of the user or patient.

[0711] Furthermore, the analyzed information is notified to experts, and the care plan is dynamically updated. If emotional abnormalities are detected during the analysis, the server uses a prompt message to instruct the AI ​​model to "adjust the care plan," thereby improving the plan. An example of a prompt message is, "Propose a stable care plan based on the patient's latest data."

[0712] This enables the system to manage information efficiently and securely, and to provide appropriate support tailored to the emotional state of users and patients.

[0713] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0714] Step 1:

[0715] The user enters the patient's basic information (name, age, medical history, allergy information, etc.) into the terminal. The terminal validates the format of the input data to ensure it is in the correct format. After the input data is validated, the terminal encrypts it. Next, this encrypted data is sent to the server. The output is the transmitted encrypted data.

[0716] Step 2:

[0717] The server decodes the received encrypted patient information and securely stores it in the database. After saving is complete, the server starts the generating AI model and generates prompt messages to input into the AI ​​model. The input is the patient information from earlier, and the output is the generated treatment plan and support plan. In particular, the AI ​​model receives the prompt, "Generate the optimal care plan based on the patient information."

[0718] Step 3:

[0719] Users record the patient's condition and care details on paper during visits. After the visit, the terminal uses optical character recognition (OCR) technology to scan this paper record and convert it into electronic data. Input is a handwritten visit record, and output is electronic data in text format. This digital data is immediately transmitted to the server.

[0720] Step 4:

[0721] The server analyzes the received electronic data and extracts key information using an automated summarization algorithm. The summarized information is then notified to the relevant medical professionals. The input is scanned electronic data, and the output is the summarized information and notification content.

[0722] Step 5:

[0723] The terminal analyzes voice data to determine the emotional state of the user or patient. Once the voice data is analyzed and the emotional state is identified, the results are sent to the server. The server uses this emotional information to dynamically adjust the generated care plan as needed. The input is voice data, and the output is an adapted plan with the information fed back into it.

[0724] Through these steps, the system provides advanced information processing and emotional support tailored to the needs of both the user and the patient.

[0725] (Application Example 2)

[0726] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0727] In today's world, where efficient information management and flexible, emotion-based responses are essential, ensuring efficiency and safety in various tasks is a particularly important challenge. Traditionally, the digitization of handwritten records and the automation of plan adjustments through emotion analysis have been insufficient, making it difficult to manage worker stress and optimize work plans.

[0728] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0729] In this invention, the server includes means for analyzing individual information and automatically generating policies and plans using generative artificial intelligence, means for converting records into digital data and integrating and managing the information using character recognition technology, and means for determining the user's emotional state and dynamically adjusting the plan using emotion analysis technology. This enables automatic adjustment of the work plan according to the emotional state.

[0730] "Generative artificial intelligence" is a technology used to analyze individual information and automatically generate policies and plans.

[0731] "Character recognition technology" is a technology that converts handwritten or printed records into digital data and integrates and manages that information.

[0732] "Emotional analysis technology" is a technology that assesses the user's emotional state and dynamically adjusts plans based on that assessment.

[0733] A "secure storage device" is a device that provides data protection measures for protecting and managing confidential information.

[0734] "Automatic plan adjustment" is a process that flexibly modifies work plans according to emotional states to optimize work efficiency.

[0735] In the system that implements this application, the server uses generative artificial intelligence to analyze individual information and automatically generate policies and plans. When a user leaves handwritten records using a device such as smart glasses, the device uses character recognition technology to convert the records into digital data. This data is sent to the server and centrally managed. The server also uses emotion analysis technology to determine the user's emotional state and dynamically adjust the work plan. This enables automatic adjustment of the work plan according to the worker's stress level. A specific use case would be a factory worker using smart glasses to record their work, and their emotional state would be determined through voice input. An example of a prompt for the generative AI model would be, "Please propose an algorithm that digitizes factory maintenance records and adjusts the work plan according to the worker's emotional state."

[0736] Smart glasses serve as the platform, digitizing data using OCR technologies such as Tesseract, and performing emotion analysis using Google Cloud Speech-to-Text and AWS Comprehend. This system enables centralized data management and dynamic, emotion-based responses, providing a safe and efficient work environment.

[0737] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0738] Step 1:

[0739] The user inputs information into smart glasses. They record it by hand, and the glasses' camera scans the information. The input is handwritten text, and the output is scanned image data. This image data is digitized in subsequent processing.

[0740] Step 2:

[0741] The device processes image data using optical character recognition (OCR) technology and converts it into text data. It receives scanned image data as input and generates text data as output. This conversion process utilizes optical character recognition technology to digitize handwritten information.

[0742] Step 3:

[0743] The server passes the received text data to the generating artificial intelligence, which performs individual data analysis and automatic plan generation. The input is text data, and the output is analyzed data and a generated plan. As part of the data processing, the AI ​​model performs analysis and constructs policies and plans.

[0744] Step 4:

[0745] The user inputs information via voice. Voice data is acquired through the microphone of smart glasses. Voice information is the input, and voice data is obtained as the output. This data is used for sentiment analysis.

[0746] Step 5:

[0747] The server converts audio data into text using speech recognition technology and performs sentiment analysis. It uses tools such as AWS Comprehend to determine the emotional state. The input is the transcribed audio data, and the output is the sentiment analysis result. As a data calculation, it analyzes the user's emotions and identifies their specific state.

[0748] Step 6:

[0749] The server dynamically adjusts the work plan based on the sentiment analysis results and provides feedback to the user. The input is the result of the sentiment analysis, and the output is the generated adjusted work plan, which is then notified to the user. Through this process, the optimal plan is provided according to the user's emotional state.

[0750] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0751] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0752] 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 this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0753] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0754] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0755] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0756] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0757] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0758] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0759] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0760] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0761] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0762] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0763] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0764] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0765] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0766] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0767] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0768] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0769] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0770] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0771] The following is further disclosed regarding the embodiments described above.

[0772] (Claim 1)

[0773] A means of automatically generating treatment policies and care plans by analyzing patient information using generative artificial intelligence,

[0774] A method for converting visit records into digital data using handwriting recognition technology and centrally managing the information,

[0775] A means of automatically generating answers to questions outside of one's area of ​​expertise based on analyzed information,

[0776] We protect information in secure data centers and implement measures to ensure the strict management of highly confidential information.

[0777] A system that includes this.

[0778] (Claim 2)

[0779] The system according to claim 1, wherein the generating artificial intelligence dynamically updates the care plan based on the patient's basic information and aggregated medical data.

[0780] (Claim 3)

[0781] The system according to claim 1, wherein the handwriting recognition technology automatically summarizes the contents of the visit record and notifies the relevant medical professional.

[0782] "Example 1"

[0783] (Claim 1)

[0784] A means of automatically generating care plans and support plans by analyzing user information using generative artificial intelligence,

[0785] A means of converting visit records into electronic data using handwriting recognition technology and centrally managing the information,

[0786] A means of automatically generating a response based on analyzed information to inquiries outside of one's area of ​​expertise,

[0787] Measures to protect information in secure data storage facilities and to thoroughly manage confidential information,

[0788] A system that includes this.

[0789] (Claim 2)

[0790] The system according to claim 1, wherein the generating artificial intelligence dynamically updates the support plan based on the user's basic information and aggregated medical data.

[0791] (Claim 3)

[0792] The system according to claim 1, wherein the handwriting recognition technology automatically summarizes the contents of a visit record and notifies the relevant medical professionals.

[0793] "Application Example 1"

[0794] (Claim 1)

[0795] A means of automatically generating treatment policies and care plans by analyzing personal information using generative artificial intelligence,

[0796] A means of converting visit records into digital data using document shape recognition technology and integrating and managing the information,

[0797] A means of automatically generating answers to questions outside of one's area of ​​expertise based on analyzed information,

[0798] A means of protecting information with secure information storage devices and thoroughly managing confidential information,

[0799] A means of using visual devices to allow those involved to quickly access information, receive and visually display the results of analysis by artificial intelligence,

[0800] ...

[0801] A system that includes this.

[0802] (Claim 2)

[0803] The system according to claim 1, wherein the generating artificial intelligence dynamically updates a care plan based on a person's basic information and aggregated medical data, and displays it through a visual device.

[0804] (Claim 3)

[0805] The system according to claim 1, wherein the document shape recognition technology automatically summarizes the contents of a visit record, notifies relevant medical professionals, and displays it on a visual device.

[0806] "Example 2 of combining an emotion engine"

[0807] (Claim 1)

[0808] A means for analyzing service user information and automatically generating treatment plans and support plans using an automated information processing device,

[0809] A means of converting visit records into electronic data using handwriting recognition technology and integrating and managing the information,

[0810] A means for automatically generating notification content based on analyzed information for specialized fields that require relevant notifications,

[0811] Protecting information in a secure data storage facility and ensuring thorough management of confidential information,

[0812] A means of analyzing voice data to determine the emotional state of service users and flexibly adjusting support plans based on that,

[0813] A system that includes this.

[0814] (Claim 2)

[0815] The system according to claim 1, wherein the automated information processing device dynamically updates the support plan based on the basic information of the service user and aggregated medical-related data.

[0816] (Claim 3)

[0817] The system according to claim 1, wherein the handwriting recognition technology automatically summarizes the contents of a visit record and notifies relevant medical professionals.

[0818] "Application example 2 when combining with an emotional engine"

[0819] (Claim 1)

[0820] A means for analyzing individual information and automatically generating policies and plans using generative artificial intelligence,

[0821] A means of converting records into digital data using character recognition technology and integrating and managing information,

[0822] A means of automatically generating a response based on analyzed information to inquiries outside of one's area of ​​expertise,

[0823] A means of protecting information with secure storage devices and thoroughly managing confidential information,

[0824] A means of determining the user's emotional state using emotion analysis technology and dynamically adjusting the plan,

[0825] A means to flexibly change work plans according to emotional state and optimize work efficiency,

[0826] A system that includes this.

[0827] (Claim 2)

[0828] The system according to claim 1, wherein the generating artificial intelligence dynamically updates the plan based on basic information and aggregated data.

[0829] (Claim 3)

[0830] The system according to claim 1, wherein the character recognition technology automatically summarizes the contents of a record and notifies the relevant experts. [Explanation of symbols]

[0831] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of automatically generating treatment policies and care plans by analyzing patient information using generative artificial intelligence, A method for converting visit records into digital data using handwriting recognition technology and centrally managing the information, A means of automatically generating answers to questions outside of one's area of ​​expertise based on analyzed information, We protect information in secure data centers and implement measures to ensure the strict management of highly confidential information. A system that includes this.

2. The system according to claim 1, wherein the generating artificial intelligence dynamically updates the care plan based on the patient's basic information and aggregated medical data.

3. The system according to claim 1, wherein the handwriting recognition technology automatically summarizes the contents of the visit record and notifies the relevant medical professionals.

Images