system

Abstract

We provide the system. [Solution] Information processing means for receiving information about activities and daily life obtained from users, An analytical means for analyzing information related to the aforementioned activities and lifestyle and evaluating the user's condition, Based on the aforementioned evaluation, a guideline generation means for providing users with appropriate exercise and dietary guidelines, A means of communication for conveying the aforementioned guidelines to users, An adjustment means for adaptively adjusting the guidelines based on responses to the guidelines obtained from users, A means of analyzing health data across the entire city and providing health promotion guidelines to individual users based on the results, 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 persona chatbot control method 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 a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Due to the diversification of modern people's lifestyles, they are in a situation where it is difficult to manage stress, suffer from sleep deprivation, lack of exercise, and maintain a balanced diet. There is a demand for a system that provides individually optimized health guidelines so that users can achieve a healthy lifestyle.

Means for Solving the Problems

[0005] This invention collects information on various forms of activities and lifestyles from users, analyzes it, and evaluates the users' health status. Based on the evaluation, it generates and presents personalized advice, including exercise and dietary guidelines, to support the users in maintaining their health. It also includes means for providing relaxation methods and sleep improvement measures based on stress and sleep patterns, and for adaptively adjusting the guidelines based on related feedback.

[0006] "Information processing means" refers to the technical elements used to collect and appropriately handle data from users regarding their daily activities and lifestyles.

[0007] "Analysis means" refers to a technical element that has the function of analyzing and evaluating the user's health status based on the collected information.

[0008] "Guideline generation means" refers to the technical elements for creating exercise and dietary guidelines optimized for the user based on the analysis results.

[0009] "Communication means" refers to the technical elements used to transmit generated guidelines and information to users.

[0010] "Adjustment mechanisms" refer to technical elements that adaptively modify the guidelines provided based on user feedback, thereby offering more accurate advice.

[0011] "Stress" is an element that represents the psychological or physiological state of a user and is a factor that affects their quality of life.

[0012] "Sleep patterns" refer to data that shows characteristics related to a user's sleep duration, quality, and rhythm.

[0013] "Relaxation methods" refer to specific techniques and approaches used to reduce stress and calm the mind and body of users.

[0014] "Sleep improvement measures" refer to specific suggestions and strategies for improving the quality and habits of users' sleep. [Brief explanation of the drawing]

[0015] [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.

Embodiments for Carrying Out the Invention

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

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

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

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

[0020] In the following embodiments, a numbered 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.

[0021] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0022] 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."

[0023] [First Embodiment]

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

[0025] 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.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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.

[0030] 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.

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

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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".

[0036] This invention is a system that continuously monitors the user's health status and provides appropriate guidelines for health promotion. This system functions through cooperation between the user, terminal, and server, as shown below.

[0037] First, users record their daily activities and meals on the device. This information can be provided in the form of text, photos, audio, or video data. Users can record their daily meals, exercise habits, and even sleep patterns in this system.

[0038] Next, the terminal formats the received information appropriately and prepares it for transmission to the server. To ensure security, the information is encrypted before being sent to the server.

[0039] Subsequently, the server stores the received data in a database and analyzes it using an AI algorithm. This data analysis allows for a detailed evaluation of the user's health status and behavioral patterns, enabling the identification of anomalies and areas for improvement.

[0040] Based on the analysis results, the server generates personalized exercise plans and dietary guidelines for each user. It also considers the user's stress levels and sleep patterns to provide lifestyle advice, including relaxation methods and sleep improvement strategies.

[0041] The device then notifies the user of advice information sent from the server. The user can receive the notification and provide feedback. For example, they can report the results of their exercise or input their thoughts on dietary improvements into the device.

[0042] Ultimately, the server analyzes user feedback and adaptively adjusts the advice it provides. This allows for more accurate and repeated advice, enabling users to maintain their health in the long term.

[0043] For example, if a user is experiencing sleep deprivation, the server can analyze their pre-sleep behavior patterns from collected data and provide calming stretches or relaxation techniques before bedtime. If the user provides feedback accordingly, the server can offer further personalized suggestions. In this way, the present invention is a system that continuously supports the user's health through a series of information processing steps.

[0044] The following describes the processing flow.

[0045] Step 1:

[0046] Users record their daily activities and diet on their devices. They provide information in various formats, such as text, images, and audio, accumulating daily health data.

[0047] Step 2:

[0048] The terminal collects information entered by the user and standardizes the data format. It encrypts the data and prepares it for transmission to the server, ensuring the security of the communication.

[0049] Step 3:

[0050] The server receives data sent from the terminal and stores it in a database. The stored data is managed on an individual basis and used for future analysis and evaluation.

[0051] Step 4:

[0052] The server analyzes the stored data using AI algorithms. It compares this data with the user's past data to assess their current health status and comprehensively analyzes their lifestyle patterns and health trends.

[0053] Step 5:

[0054] Based on the analysis results, the server generates personalized exercise plans and dietary guidelines for the user. Furthermore, it creates specific advice for stress management and sleep improvement.

[0055] Step 6:

[0056] The server sends the generated health guidelines to the terminal.

[0057] Step 7:

[0058] The terminal notifies the user of advice information received from the server. It displays the information on the interface so the user can review it, and allows for reminder settings as needed.

[0059] Step 8:

[0060] Users take action based on the advice provided and record the results and their impressions as feedback on their device. This feedback is used for further analysis.

[0061] Step 9:

[0062] The server receives and analyzes user feedback data. This allows for adjustments to be made to improve the accuracy of health guidelines and incorporate the findings into future recommendations.

[0063] By repeatedly performing the steps described above, users can manage their health in a sustainable manner, and the entire system can flexibly respond to the user's needs.

[0064] (Example 1)

[0065] 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."

[0066] In modern times, many people face health problems due to stress and irregular lifestyles in their daily lives. However, solving these problems requires appropriate and personalized guidance tailored to individual circumstances. Traditional methods merely aggregate user data without fully utilizing data-driven insights, and a particular problem is the lack of continuous support for long-term health maintenance.

[0067] 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.

[0068] In this invention, the server includes data processing means that receive activity and lifestyle information obtained from users and handle the data in multiple information formats; analysis means that analyze the activity and lifestyle information and evaluate the user's health status and behavioral patterns in detail using a generated AI model; and guideline generation means that generate personalized exercise and dietary guidelines for the user based on the evaluation. This enables the timely provision of highly personalized health advice and guidelines for each user, making long-term health improvement and maintenance possible.

[0069] "Data processing means" refers to a device or function for appropriately receiving information in various formats obtained from users and performing encryption or format conversion.

[0070] "Analysis means" refers to a device or function that uses an AI model generated based on received information to evaluate in detail the user's health status and behavioral patterns.

[0071] A "guideline generation means" refers to a device or function that generates exercise plans and dietary guidelines tailored to each individual user based on the analysis results.

[0072] "Communication means" refers to a device or function for transmitting guidelines to users and collecting feedback from users.

[0073] "Adjustment means" refers to a device or function that analyzes user feedback to refine suggestions for future use and improve the accuracy of the advice provided.

[0074] This invention is a system that continuously monitors the user's health status and provides personalized health guidance. The system mainly consists of three elements: a terminal, a server, and the user.

[0075] Users input information about their daily activities and lifestyle into the device. Input methods are diverse and can be provided in various formats, including text, images, audio, and video. For example, a user can record their morning run using the device.

[0076] The device receives this information, formats the data appropriately, encrypts it, and prepares it for transmission to the server. This protects the user's privacy. The hardware used includes smartphones and tablets, and the corresponding software is a dedicated health management application.

[0077] The server receives information transmitted from the terminal and analyzes the data using a generative AI model. Specifically, it evaluates behavioral patterns and health status from accumulated user activity data, identifying issues such as lack of exercise or nutritional imbalances. Based on the analysis results, it generates personalized exercise programs and dietary guidelines for the user. For example, based on sleep data, the server can provide specific advice to promote higher quality sleep.

[0078] The generated advice and guidelines are then communicated to the user via the device. The user implements the guidance and provides feedback on the results and their impressions. This allows the system to incorporate user feedback and improve the accuracy of the next set of guidelines it provides.

[0079] In this process, by providing the generating AI model with specific instructions, such as "Based on the user's past meal data, suggest a meal plan that takes nutritional balance into consideration for next week," personalized health guidance can be achieved.

[0080] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0081] Step 1:

[0082] Users input information about their daily activities and lifestyle using devices such as smartphones and tablets. This information includes text, images, audio, and video, and may include recordings of steps taken, meals eaten, and sleep duration in a dedicated application. When inputting information, users use input interfaces compatible with each format, and the day's activities are saved on the device.

[0083] Step 2:

[0084] The terminal receives information from the user and converts it into a unified format. This includes formatting text data and compressing image and audio data. The data is then AES encrypted and prepared for secure transfer to the server. The output is encrypted data, which is then sent to the server.

[0085] Step 3:

[0086] The server receives encrypted data sent from the terminal and decrypts it. The decrypted information is stored in a dedicated cloud database. Subsequently, data analysis begins using a generative AI model, which analyzes health status and behavioral patterns in detail. Based on the input data, the user's exercise level and nutritional balance are evaluated, and a health assessment is conducted and saved as output.

[0087] Step 4:

[0088] The server creates personalized exercise plans and dietary guidelines based on the analysis results. These generated guidelines might include suggestions for users who are sedentary, such as recommending three walks per week or dietary improvements. The generating AI model automatically generates optimized advice for future health maintenance, taking past data into consideration. The output is personalized guideline information tailored to each user.

[0089] Step 5:

[0090] The device receives personalized guidelines sent from the server and notifies the user. Notifications are delivered via push notifications, in-app notifications, etc., allowing the user to review the provided guidelines. A feedback input interface is also provided to facilitate user responses. The output consists of specific health guidelines for the user to take action.

[0091] Step 6:

[0092] Users follow the instructions received from their device and input the results and their impressions as feedback into the device. For example, they input the results after completing a walking plan suggested by the server, providing information to be used for future advice. Feedback is entered through the data input screen of a dedicated app.

[0093] Step 7:

[0094] The server receives feedback from the user and analyzes its content again using the generative AI model. This analysis evaluates the user's improvement and the effectiveness of the guidelines, and the feedback is incorporated into future suggestions. As a result, the server can improve the accuracy of personalized guidelines and develop future health support that is more tailored to the user.

[0095] (Application Example 1)

[0096] 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."

[0097] In modern society, health management is crucial for improving an individual's quality of life. However, conventional health management systems are limited to analyzing individual data and fail to utilize data from the entire community or society as a whole, making it difficult to provide more accurate and personalized health promotion guidelines.

[0098] 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.

[0099] In this invention, the server includes information processing means for receiving information on activities and lifestyles obtained from users; analysis means for analyzing the information on activities and lifestyles and evaluating the user's condition; and means for analyzing health data for the entire city and providing health promotion guidelines to individual users based on the results. This enables more appropriate and detailed health management based not only on individual circumstances but also on health data for the entire city.

[0100] "Information processing means" refers to fundamental technologies for receiving information about users' activities and lifestyles, converting it into data format, and performing analysis.

[0101] "Analysis means" refers to technologies that evaluate the user's condition based on received information and understand their health status and behavioral tendencies.

[0102] A "guideline generation method" is a technology that provides users with appropriate exercise and dietary guidelines based on analysis results.

[0103] "Communication means" refers to the technology used to transmit generated guidelines to users and to ensure that this communication is reliable.

[0104] "Adjustment methods" refer to technologies that adaptively adjust guidelines based on feedback obtained from users, thereby providing more personalized health promotion guidelines.

[0105] "Health data" refers to data that indicates the overall health status of a city, and is used to generate health guidelines for individual users.

[0106] The system that realizes this invention consists of a terminal including a smartphone, a server that analyzes data, and a user that utilizes an application. The system's program collects information on the user's activities and lifestyle, analyzes it, and generates individualized health promotion guidelines.

[0107] The device receives information such as activity data, meal data, and sleep patterns entered by the user. This information is recorded in the form of text data, image data, audio data, and video data. Upon receiving this information, the device encrypts it and sends it to the server.

[0108] The server analyzes the received information using advanced AI algorithms. Machine learning libraries such as TENSORFLOW® and PyTorch are used for the analysis. This analysis allows for the assessment of the user's health status and a detailed understanding of their behavioral patterns. Furthermore, it generates more precise guidelines by comparing this data with city-wide health data.

[0109] The guidelines generated from the analysis results are sent to the device and notified to the user. The user can then use these guidelines to improve their daily life. Furthermore, the feedback function allows the user to input their own thoughts and results again into the device.

[0110] Ultimately, the server adaptively adjusts the guidelines using user feedback and incorporates it into future guideline generation. This allows users to continuously promote their health.

[0111] For example, if a user feels they are not getting enough exercise, the server compares the user's past exercise data with the city's average data and suggests an appropriate exercise plan. An example of a prompt to the generating AI could be: "Compare the user's exercise data with the city's average data and provide reasonable exercise advice."

[0112] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0113] Step 1:

[0114] Users input information about their daily activities and meals into a smartphone or other device. This input can be in text, image, audio, or video format. The entered information is temporarily stored on the device.

[0115] Step 2:

[0116] The terminal encrypts stored user data and transmits it to the server via a secure communication protocol. The input here is user activity data, and the output is encrypted data. The terminal uses encryption algorithms such as AES.

[0117] Step 3:

[0118] The server decrypts the received encrypted data and stores it in the database. The input here is encrypted data, and the output is analyzable raw data. The server maintains data security using SSL / TLS.

[0119] Step 4:

[0120] The server analyzes the data using AI libraries such as TensorFlow and PyTorch. The input is decoded user data, and the output is the health status assessment result. In this step, the server analyzes historical data and city-wide health data together.

[0121] Step 5:

[0122] The server generates personalized health promotion guidelines for users based on the analysis results. The input is the health status assessment, and the output is specific guidance for the user. A generation AI model streamlines this process.

[0123] Step 6:

[0124] The server sends the generated guidelines to the terminal and communicates them to the user via a notification function. The input is the generated guidelines, and the output is the notification on the user's terminal. The terminal uses a push notification service.

[0125] Step 7:

[0126] Based on the guidelines received, users improve their lifestyles and input feedback on what they did and the results they experienced into their device. This feedback is then sent back to the server. In this step, the input is the results of the actions taken, and the output is feedback data.

[0127] Step 8:

[0128] The server analyzes user feedback and uses a generative AI model to incorporate that feedback into future guideline creation. The input is user feedback, and the output is a revised draft of future guidelines. This allows for progressively more accurate advice.

[0129] 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.

[0130] This invention is a system that evaluates a user's health status from multiple perspectives and provides individually optimized health guidelines. In particular, by incorporating an emotion engine, it realizes support that also takes into account the user's emotional state. This system functions in cooperation with the user, terminal, and server.

[0131] First, users record various daily activities, meals, and emotions on the device. This information can be entered in various formats, including text, photos, audio, and video. In addition, voice and facial expression data are analyzed by an emotion engine to collect the user's emotions in real time.

[0132] Next, the terminal centralizes this information and standardizes the data format. The data is encrypted for secure transmission to the server. At this stage, data related to emotions, in particular, is treated as an important element in subsequent analysis.

[0133] The server organizes the data received from the terminal and stores it in a database. Next, an AI algorithm analyzes this data to comprehensively evaluate the user's health and emotional state. By using an emotion engine, the user's psychological state is also examined, and this information can be reflected in the health guidelines provided.

[0134] Subsequently, the server generates an exercise plan and dietary guidelines optimized for the user based on the analysis results, and also creates comprehensive advice that includes mental health support guidelines tailored to the user's emotional state. This advice serves as a concrete guideline for the user to improve their current situation.

[0135] The device notifies the user of advice received from the server. The user then takes action based on this advice and provides feedback to the device regarding the results and their impressions, accumulating feedback data. Based on this feedback, the advice is continuously improved.

[0136] For example, if a user is experiencing emotional stress, the emotion engine detects this state, and the server provides advice, including methods for stress reduction. For instance, it can suggest relaxation techniques such as deep breathing, meditation, or listening to music. Based on user feedback, the server adjusts its next suggestions to be more personalized.

[0137] Thus, the present invention aims to provide an integrated healthcare system that simultaneously supports physical and mental health, thereby improving the quality of life for users.

[0138] The following describes the processing flow.

[0139] Step 1:

[0140] Users input their daily habits, diet, and emotions at the time into the device. In particular, emotional data is recorded through voice input and facial expression capture, and detailed information is collected.

[0141] Step 2:

[0142] The terminal receives diverse data from users and standardizes it according to each data format. The obtained information is integrated and appropriately formatted in preparation for analysis.

[0143] Step 3:

[0144] The device encrypts standardized data and sends it to the server using a secure communication protocol. This process is crucial to ensure data security and privacy.

[0145] Step 4:

[0146] The server receives data sent from the terminal, organizes it in the database, and stores it. Integrated management is performed with historical information, including past data.

[0147] Step 5:

[0148] The server analyzes the accumulated data using AI algorithms and an emotion engine. It comprehensively evaluates the user's health status, behavioral patterns, and emotional state to identify problems and pinpoint areas for improvement.

[0149] Step 6:

[0150] Based on the analysis results, the server generates specific exercise and dietary guidelines for the user. The analysis results from the emotion engine are also incorporated, including advice aimed at stress reduction and emotional care.

[0151] Step 7:

[0152] The server sends the generated health guidelines and emotional care advice to the terminal, enabling rapid information delivery to the user.

[0153] Step 8:

[0154] The terminal notifies the user of guidance information received from the server. This information is appropriately communicated to the user through a visual or auditory interface.

[0155] Step 9:

[0156] Users act based on the guidance and advice they receive, and record the process and results as feedback on their device.

[0157] Step 10:

[0158] The server receives and analyzes feedback sent from the terminal. This allows for continuous improvement of the guidance provided and adaptive adjustments to make future suggestions more personalized.

[0159] Through this series of processing steps, the system provides support for both the user's physical and emotional well-being, and optimizes itself to meet individual needs.

[0160] (Example 2)

[0161] 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 will be referred to as the "terminal."

[0162] In modern society, comprehensively managing an individual's health and psychological state and providing optimized health guidelines is a challenging task. In particular, methods for integrating and analyzing biometric and emotional data to provide personalized advice have not yet been sufficiently realized. This invention aims to provide a system that delivers health and psychological support tailored to each individual.

[0163] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes data collection means for organizing and receiving biometric information and psychological data in a unified format, analysis means for evaluating the user's health and psychological state through analysis, and guideline generation means for generating personalized exercise, diet, and mental health guidelines based on the analysis results. This enables comprehensive support in both health and psychological aspects that meet the individual needs of the user.

[0164]

[0165] A "data collection method" is a system that receives information about biological activity and psychological state from users in various formats and processes it within the system.

[0166] "Data transfer means" includes technologies and protocols for securely encrypting collected information and transmitting it to a server.

[0167] "Analysis means" refers to methods that use data analysis techniques to evaluate received biometric and emotional data in order to understand the user's health and psychological state.

[0168] A "guideline generation means" is a device that has the function of generating specific guidelines and advice for exercise, diet, and mental health that are suitable for the user, based on the analysis results.

[0169] "Communication methods" refer to transmission technologies used to notify users of generated guidelines and advice and to receive feedback.

[0170] "Adjustment mechanisms" refer to systems that dynamically adapt and improve individual health and psychological support advice based on feedback from users.

[0171] An "emotion engine" is a technology that analyzes voice and facial expression data to evaluate the user's emotional state in real time.

[0172] This invention is an information processing system for comprehensively evaluating a user's health and psychological state and providing personalized guidelines. To achieve this, the system mainly consists of a user terminal, a server for data processing, and an engine for analysis. One embodiment of this invention is shown below.

[0173] Hardware and software selection

[0174] The devices are mobile information terminals such as smartphones and tablets, equipped with interfaces for inputting data in various formats (text, images, audio, and video). This allows users to record their daily activities, meals, and emotions.

[0175] The servers are deployed on a cloud platform and possess advanced data processing capabilities. Data is encrypted using AES (Advanced Encryption Standard) and transmitted securely via the HTTPS protocol.

[0176] The analysis engine incorporates machine learning models and includes an emotion engine for performing emotion analysis using voice and facial expression data. These technologies make it possible to evaluate the user's psychological state and reflect this in the generation of guidelines.

[0177] System operating procedures and functions

[0178] Users input their daily experiences through a dedicated application, including details about their diet, exercise, and emotions.

[0179] The device centralizes the collected data, encrypts it, and then securely transmits it to the server.

[0180] The server uses AI algorithms to analyze information stored in the database, evaluate the user's health and emotional state, and generate personalized health guidelines.

[0181] The terminal notifies the user of guidance information from the server and encourages appropriate action. Furthermore, the server continuously improves its advice based on the feedback received.

[0182] Specific example

[0183] For example, if a user is experiencing emotional stress, the emotion engine detects this state, and the server suggests stress reduction methods. Examples of suggested methods include deep breathing, meditation, and listening to music. After the user acts on these suggestions and provides feedback, the system further personalizes the advice.

[0184] Example of a prompt

[0185] The prompt used is "Suggest effective stress reduction methods when the user is experiencing emotional stress." This prompts the server to utilize a generative AI model to generate appropriate advice.

[0186] As described above, the present invention makes it possible to provide users with personalized health and psychological support and improve their quality of life.

[0187] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0188] Step 1:

[0189] Users input their daily activities and emotional states into the device. The input data includes information on meals, exercise records, and emotions, and is provided in text, image, audio, and video formats. This information serves as foundational data for comprehensively understanding the user's daily life.

[0190] Step 2:

[0191] The terminal receives user input data and converts it into a unified format (e.g., JSON format). This unification of data formats allows for efficient handling of data in subsequent processing. Specifically, this includes pre-processing steps such as compressing image data and converting audio data to text.

[0192] Step 3:

[0193] The terminal encrypts the unified data and sends it to the server. Here, AES encryption technology is used, and secure data transfer is performed via the HTTPS protocol. The input is the encryption key, and the output is the encrypted data file.

[0194] Step 4:

[0195] The server decodes the data received from the terminal and stores it in the database. The decoded data is inserted into the corresponding field in the database. The server checks the integrity of the data and logs the information as needed.

[0196] Step 5:

[0197] The server applies AI algorithms to analyze biometric and emotional information in the database. Here, an emotion engine is used to analyze the user's voice and facial expressions to evaluate their psychological state. The input is raw data, and the output is the analysis results and a health assessment score.

[0198] Step 6:

[0199] The server generates personalized exercise, diet, and mental health guidelines based on the analysis results. Using a generation AI model, it creates individual health guidelines according to the prompt text. The output is a set of advice for the user.

[0200] Step 7:

[0201] The device receives guidance information from the server and notifies the user. The notification is sent using the smartphone's push notification function and is presented as specific advice to encourage the user to take action.

[0202] Step 8:

[0203] Users take action based on notifications from their devices and provide feedback on the results and their impressions to the device. This feedback data is used for future analysis and guideline development. The input is the result of the user's actions, and the output is new data that will lead to improvements in future advice.

[0204] Step 9:

[0205] The server analyzes user feedback data and adaptively updates its guidelines based on newly acquired insights. This ensures that personalized advice is continuously provided, promoting ongoing improvements tailored to user needs.

[0206] (Application Example 2)

[0207] 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".

[0208] In recent years, with the advancement of an aging society, the importance of individualized health support and mental health support has increased. However, conventional technologies have faced the challenge of not being able to comprehensively evaluate physical and mental health status and provide optimized guidelines based on that evaluation. There is also the problem of a lack of systems that can provide personalized health guidelines for the elderly. Therefore, the present invention aims to provide a health support system that takes into account not only the user's physical condition but also their emotional state, and to efficiently generate individualized guidelines.

[0209] 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.

[0210] In this invention, the server includes information processing means for receiving information about activities and lifestyles obtained from users; analysis means for analyzing the information about activities and lifestyles and evaluating the user's condition; guideline generation means for providing appropriate exercise and dietary guidelines to the user based on the evaluation; and means for generating mental health support guidelines based on the emotional state obtained from the evaluation. This makes it possible to comprehensively support the physical and mental health of users and provide personalized health support.

[0211] An "information processing device" is a device that centralizes various forms of input information related to activities and daily life received from users and converts the format as needed.

[0212] An "analysis device" is a device that analyzes and evaluates the user's physical health and emotional state based on the received information.

[0213] A "guideline generation device" is a device that automatically generates appropriate exercise, diet, and mental health guidelines for users based on analysis results.

[0214] A "communication device" is a device used to transmit generated guidelines to users and to notify and share information.

[0215] A "modification mechanism" is a device that receives feedback from users and makes adjustments to continuously optimize the guidelines it provides.

[0216] An "emotion engine" is a device or program that analyzes a user's voice and facial expression data to evaluate their emotional state.

[0217] To implement this invention, it is necessary to build a system in which users, terminals, and servers work together. This system evaluates the user's health and emotional state and provides optimal guidance.

[0218] Users record their daily activities, meals, and emotions using their smartphones. Information can be entered in text, photos, audio, and video formats. Emotions, in particular, are analyzed in real-time by an emotion engine using voice and facial recognition. This emotion engine is software designed to analyze emotional states.

[0219] The device centralizes the received data, encrypts it, and transmits it to a cloud server. In particular, emotional data is treated as a crucial element in subsequent analysis. The device is equipped with communication capabilities and plays a role in notifying the user of the generated guidelines in a timely manner.

[0220] The server uses AI algorithms to comprehensively assess health and emotional states by analyzing incoming data. Here, the server utilizes a generated AI model upon request. Specifically, it proposes mental health support measures based on the assessed emotional state. For example, if the emotion engine detects a stressed state, it generates guidelines including relaxation methods.

[0221] The cloud server accumulates the feedback data it receives and continuously adjusts its guidance generation system to make future advice more personalized. This contributes to the user's long-term health improvement.

[0222] For example, if a user records in voice that they are "feeling a little down," the emotion engine will analyze that emotion and suggest relaxation methods using meditation or music. An example of a prompt would be, "If the user says 'worried,' generate personalized advice suggesting relaxation methods (deep breathing, simple exercises, etc.) to alleviate that emotion."

[0223] It is expected that the implementation of such a system will simultaneously support users' physical and emotional well-being, thereby improving their quality of life.

[0224] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0225] Step 1:

[0226] Users input information about their daily activities, meals, and emotions into their smartphones in various formats such as text, photos, audio, and video. This information is analyzed in real time by an emotion engine via voice or facial recognition. The input here is data in various formats, and the output is the analyzed emotional state.

[0227] Step 2:

[0228] The terminal centralizes this input data and standardizes its format. This data is securely transmitted to the cloud server using industry-standard encryption technology. Specifically, image data is converted to JPEG format and audio to WAV format. The output is encrypted data in a transmittable format.

[0229] Step 3:

[0230] The server analyzes the received data. Using AI algorithms, it assesses the user's health and emotional state. Input is standardized data, and output includes exercise plans and dietary guidelines based on health status, and mental health support measures based on emotional state. A generative AI model is used to refer to the user's past data and create specific advice.

[0231] Step 4:

[0232] The server generates optimized guidelines based on the evaluated data and sends them to the terminal. Specifically, it suggests personalized exercise plans and relaxation methods. The output here consists of individual health guidelines and mental health support measures.

[0233] Step 5:

[0234] The device notifies the user of guidelines received from the server. These notifications are delivered via pop-up messages or in-app notifications. The output is advice information displayed in a user-recognizable format.

[0235] Step 6:

[0236] The user takes action based on the advice provided and then provides feedback on the results and their impressions back to the device. The input is the user's feedback or additional information, and the output is adjusted health guidelines.

[0237] Step 7:

[0238] The server adjusts its guidelines based on user feedback. It evaluates the effectiveness of previous advice and incorporates it into future guidelines. Specifically, it stores feedback data in a database and uses an AI algorithm to generate the next set of guidelines. This enables more personalized suggestions.

[0239] 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.

[0240] 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.

[0241] 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.

[0242] [Second Embodiment]

[0243] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0244] 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.

[0245] 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).

[0246] 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.

[0247] 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.

[0248] 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).

[0249] 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.

[0250] 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.

[0251] 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.

[0252] 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.

[0253] 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.

[0254] 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".

[0255] This invention is a system that continuously monitors the user's health status and provides appropriate guidelines for health promotion. This system functions through cooperation between the user, terminal, and server, as shown below.

[0256] First, users record their daily activities and meals on the device. This information can be provided in the form of text, photos, audio, or video data. Users can record their daily meals, exercise habits, and even sleep patterns in this system.

[0257] Next, the terminal formats the received information appropriately and prepares it for transmission to the server. To ensure security, the information is encrypted before being sent to the server.

[0258] Subsequently, the server stores the received data in a database and analyzes it using an AI algorithm. This data analysis allows for a detailed evaluation of the user's health status and behavioral patterns, enabling the identification of anomalies and areas for improvement.

[0259] Based on the analysis results, the server generates personalized exercise plans and dietary guidelines for each user. It also considers the user's stress levels and sleep patterns to provide lifestyle advice, including relaxation methods and sleep improvement strategies.

[0260] The device then notifies the user of advice information sent from the server. The user can receive the notification and provide feedback. For example, they can report the results of their exercise or input their thoughts on dietary improvements into the device.

[0261] Ultimately, the server analyzes user feedback and adaptively adjusts the advice it provides. This allows for more accurate and repeated advice, enabling users to maintain their health in the long term.

[0262] For example, if a user is experiencing sleep deprivation, the server can analyze their pre-sleep behavior patterns from collected data and provide calming stretches or relaxation techniques before bedtime. If the user provides feedback accordingly, the server can offer further personalized suggestions. In this way, the present invention is a system that continuously supports the user's health through a series of information processing steps.

[0263] The following describes the processing flow.

[0264] Step 1:

[0265] Users record their daily activities and diet on their devices. They provide information in various formats, such as text, images, and audio, accumulating daily health data.

[0266] Step 2:

[0267] The terminal collects information entered by the user and standardizes the data format. It encrypts the data and prepares it for transmission to the server, ensuring the security of the communication.

[0268] Step 3:

[0269] The server receives data sent from the terminal and stores it in a database. The stored data is managed on an individual basis and used for future analysis and evaluation.

[0270] Step 4:

[0271] The server analyzes the stored data using AI algorithms. It compares this data with the user's past data to assess their current health status and comprehensively analyzes their lifestyle patterns and health trends.

[0272] Step 5:

[0273] Based on the analysis results, the server generates personalized exercise plans and dietary guidelines for the user. Furthermore, it creates specific advice for stress management and sleep improvement.

[0274] Step 6:

[0275] The server sends the generated health guidelines to the terminal.

[0276] Step 7:

[0277] The terminal notifies the user of advice information received from the server. It displays the information on the interface so the user can review it, and allows for reminder settings as needed.

[0278] Step 8:

[0279] The user takes actions based on the provided advice and records the results and feelings as feedback on the terminal. This feedback is used for the next analysis.

[0280] Step 9:

[0281] The server receives and analyzes the feedback data from the user. Based on this, adjustments are made to improve the accuracy of the health guidelines and reflect them in the next proposal.

[0282] By repeatedly executing the above steps, the user can perform continuous health management, and the entire system can flexibly respond to the needs of the users.

[0283] (Example 1)

[0284] Next, Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0285] In modern times, many people have health problems due to stress and irregular lifestyles in their daily lives. However, to solve these problems, appropriate and personalized guidance according to individual situations is necessary. In the conventional methods, it only aggregates the users' data and cannot fully utilize the insights based on the data. In particular, there is a lack of continuous support for long-term health maintenance, which has been a problem.

[0286] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0287] In this invention, the server includes data processing means that receive activity and lifestyle information obtained from users and handle the data in multiple information formats; analysis means that analyze the activity and lifestyle information and evaluate the user's health status and behavioral patterns in detail using a generated AI model; and guideline generation means that generate personalized exercise and dietary guidelines for the user based on the evaluation. This enables the timely provision of highly personalized health advice and guidelines for each user, making long-term health improvement and maintenance possible.

[0288] "Data processing means" refers to a device or function for appropriately receiving information in various formats obtained from users and performing encryption or format conversion.

[0289] "Analysis means" refers to a device or function that uses an AI model generated based on received information to evaluate in detail the user's health status and behavioral patterns.

[0290] A "guideline generation means" refers to a device or function that generates exercise plans and dietary guidelines tailored to each individual user based on the analysis results.

[0291] "Communication means" refers to a device or function for transmitting guidelines to users and collecting feedback from users.

[0292] "Adjustment means" refers to a device or function that analyzes user feedback to refine suggestions for future use and improve the accuracy of the advice provided.

[0293] This invention is a system that continuously monitors the user's health status and provides personalized health guidance. The system mainly consists of three elements: a terminal, a server, and the user.

[0294] Users input information about their daily activities and lifestyle into the device. Input methods are diverse and can be provided in various formats, including text, images, audio, and video. For example, a user can record their morning run using the device.

[0295] The device receives this information, formats the data appropriately, encrypts it, and prepares it for transmission to the server. This protects the user's privacy. The hardware used includes smartphones and tablets, and the corresponding software is a dedicated health management application.

[0296] The server receives information transmitted from the terminal and analyzes the data using a generative AI model. Specifically, it evaluates behavioral patterns and health status from accumulated user activity data, identifying issues such as lack of exercise or nutritional imbalances. Based on the analysis results, it generates personalized exercise programs and dietary guidelines for the user. For example, based on sleep data, the server can provide specific advice to promote higher quality sleep.

[0297] The generated advice and guidelines are then communicated to the user via the device. The user implements the guidance and provides feedback on the results and their impressions. This allows the system to incorporate user feedback and improve the accuracy of the next set of guidelines it provides.

[0298] In this process, by providing the generating AI model with specific instructions, such as "Based on the user's past meal data, suggest a meal plan that takes nutritional balance into consideration for next week," personalized health guidance can be achieved.

[0299] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0300] Step 1:

[0301] Users input information related to their daily activities and life using devices such as smartphones and tablets. This information includes text, images, audio, videos, etc. For example, the number of steps, meal content, and sleep duration may be recorded in dedicated applications. When inputting, an input interface corresponding to each format is used to save the activity content of the day on the device.

[0302] Step 2:

[0303] The device receives the information received from the user and converts the information into a unified format. This includes formatting text data, compressing image and audio data, etc. After that, the data is encrypted using AES and is ready to be transferred to the server while ensuring security. As output, encrypted data is generated and sent to the server.

[0304] Step 3:

[0305] The server receives the encrypted data sent from the device and decrypts the data. The decrypted information is saved in a dedicated cloud database. After that, data analysis begins using a generated AI model to analyze the health status and behavior patterns in detail. Based on the input data, the user's exercise volume and nutritional balance are evaluated, and a health assessment is carried out and saved as output.

[0306] Step 4:

[0307] The server creates individualized exercise plans and dietary guidelines based on the analysis results. The generated guidelines include, for example, a proposal to walk three times a week for users with insufficient exercise and improvement plans for diet. The generated AI model automatically generates optimized advice for maintaining future health while considering past data. As output, customized guideline information for each user is completed.

[0308] Step 5:

[0309] The device receives personalized guidelines sent from the server and notifies the user. Notifications are delivered via push notifications, in-app notifications, etc., allowing the user to review the provided guidelines. A feedback input interface is also provided to facilitate user responses. The output consists of specific health guidelines for the user to take action.

[0310] Step 6:

[0311] Users follow the instructions received from their device and input the results and their impressions as feedback into the device. For example, they input the results after completing a walking plan suggested by the server, providing information to be used for future advice. Feedback is entered through the data input screen of a dedicated app.

[0312] Step 7:

[0313] The server receives feedback from the user and analyzes its content again using the generative AI model. This analysis evaluates the user's improvement and the effectiveness of the guidelines, and the feedback is incorporated into future suggestions. As a result, the server can improve the accuracy of personalized guidelines and develop future health support that is more tailored to the user.

[0314] (Application Example 1)

[0315] 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."

[0316] In modern society, health management is crucial for improving an individual's quality of life. However, conventional health management systems are limited to analyzing individual data and fail to utilize data from the entire community or society as a whole, making it difficult to provide more accurate and personalized health promotion guidelines.

[0317] 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.

[0318] In this invention, the server includes information processing means for receiving information on activities and lifestyles obtained from users; analysis means for analyzing the information on activities and lifestyles and evaluating the user's condition; and means for analyzing health data for the entire city and providing health promotion guidelines to individual users based on the results. This enables more appropriate and detailed health management based not only on individual circumstances but also on health data for the entire city.

[0319] "Information processing means" refers to fundamental technologies for receiving information about users' activities and lifestyles, converting it into data format, and performing analysis.

[0320] "Analysis means" refers to technologies that evaluate the user's condition based on received information and understand their health status and behavioral tendencies.

[0321] A "guideline generation method" is a technology that provides users with appropriate exercise and dietary guidelines based on analysis results.

[0322] "Communication means" refers to the technology used to transmit generated guidelines to users and to ensure that this communication is reliable.

[0323] "Adjustment methods" refer to technologies that adaptively adjust guidelines based on feedback obtained from users, thereby providing more personalized health promotion guidelines.

[0324] "Health data" refers to data that indicates the overall health status of a city, and is used to generate health guidelines for individual users.

[0325] The system that realizes this invention consists of a terminal including a smartphone, a server that analyzes data, and a user that utilizes an application. The system's program collects information on the user's activities and lifestyle, analyzes it, and generates individualized health promotion guidelines.

[0326] The device receives information such as activity data, meal data, and sleep patterns entered by the user. This information is recorded in the form of text data, image data, audio data, and video data. Upon receiving this information, the device encrypts it and sends it to the server.

[0327] The server uses advanced AI algorithms to analyze the received information. Machine learning libraries such as TensorFlow and PyTorch are used for this analysis. This analysis allows for the assessment of the user's health status and a detailed understanding of their behavioral patterns. Furthermore, it generates more precise guidelines by comparing this data with city-wide health data.

[0328] The guidelines generated from the analysis results are sent to the device and notified to the user. The user can then use these guidelines to improve their daily life. Furthermore, the feedback function allows the user to input their own thoughts and results again into the device.

[0329] Ultimately, the server adaptively adjusts the guidelines using user feedback and incorporates it into future guideline generation. This allows users to continuously promote their health.

[0330] For example, if a user feels they are not getting enough exercise, the server compares the user's past exercise data with the city's average data and suggests an appropriate exercise plan. An example of a prompt to the generating AI could be: "Compare the user's exercise data with the city's average data and provide reasonable exercise advice."

[0331] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0332] Step 1:

[0333] Users input information about their daily activities and meals into a smartphone or other device. This input can be in text, image, audio, or video format. The entered information is temporarily stored on the device.

[0334] Step 2:

[0335] The terminal encrypts stored user data and transmits it to the server via a secure communication protocol. The input here is user activity data, and the output is encrypted data. The terminal uses encryption algorithms such as AES.

[0336] Step 3:

[0337] The server decrypts the received encrypted data and stores it in the database. The input here is encrypted data, and the output is analyzable raw data. The server maintains data security using SSL / TLS.

[0338] Step 4:

[0339] The server analyzes the data using AI libraries such as TensorFlow and PyTorch. The input is decoded user data, and the output is the health status assessment result. In this step, the server analyzes historical data and city-wide health data together.

[0340] Step 5:

[0341] The server generates personalized health promotion guidelines for users based on the analysis results. The input is the health status assessment, and the output is specific guidance for the user. A generation AI model streamlines this process.

[0342] Step 6:

[0343] The server sends the generated guidelines to the terminal and communicates them to the user via a notification function. The input is the generated guidelines, and the output is the notification on the user's terminal. The terminal uses a push notification service.

[0344] Step 7:

[0345] Based on the guidelines received, users improve their lifestyles and input feedback on what they did and the results they experienced into their device. This feedback is then sent back to the server. In this step, the input is the results of the actions taken, and the output is feedback data.

[0346] Step 8:

[0347] The server analyzes user feedback and uses a generative AI model to incorporate that feedback into future guideline creation. The input is user feedback, and the output is a revised draft of future guidelines. This allows for progressively more accurate advice.

[0348] 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.

[0349] This invention is a system that evaluates a user's health status from multiple perspectives and provides individually optimized health guidelines. In particular, by incorporating an emotion engine, it realizes support that also takes into account the user's emotional state. This system functions in cooperation with the user, terminal, and server.

[0350] First, users record various daily activities, meals, and emotions on the device. This information can be entered in various formats, including text, photos, audio, and video. In addition, voice and facial expression data are analyzed by an emotion engine to collect the user's emotions in real time.

[0351] Next, the terminal centralizes this information and standardizes the data format. The data is encrypted for secure transmission to the server. At this stage, data related to emotions, in particular, is treated as an important element in subsequent analysis.

[0352] The server organizes the data received from the terminal and stores it in a database. Next, an AI algorithm analyzes this data to comprehensively evaluate the user's health and emotional state. By using an emotion engine, the user's psychological state is also examined, and this information can be reflected in the health guidelines provided.

[0353] Subsequently, the server generates an exercise plan and dietary guidelines optimized for the user based on the analysis results, and also creates comprehensive advice that includes mental health support guidelines tailored to the user's emotional state. This advice serves as a concrete guideline for the user to improve their current situation.

[0354] The device notifies the user of advice received from the server. The user then takes action based on this advice and provides feedback to the device regarding the results and their impressions, accumulating feedback data. Based on this feedback, the advice is continuously improved.

[0355] For example, if a user is experiencing emotional stress, the emotion engine detects this state, and the server provides advice, including methods for stress reduction. For instance, it can suggest relaxation techniques such as deep breathing, meditation, or listening to music. Based on user feedback, the server adjusts its next suggestions to be more personalized.

[0356] Thus, the present invention aims to provide an integrated healthcare system that simultaneously supports physical and mental health, thereby improving the quality of life for users.

[0357] The following describes the processing flow.

[0358] Step 1:

[0359] Users input their daily habits, diet, and emotions at the time into the device. In particular, emotional data is recorded through voice input and facial expression capture, and detailed information is collected.

[0360] Step 2:

[0361] The terminal receives diverse data from users and standardizes it according to each data format. The obtained information is integrated and appropriately formatted in preparation for analysis.

[0362] Step 3:

[0363] The device encrypts standardized data and sends it to the server using a secure communication protocol. This process is crucial to ensure data security and privacy.

[0364] Step 4:

[0365] The server receives data sent from the terminal, organizes it in the database, and stores it. Integrated management is performed with historical information, including past data.

[0366] Step 5:

[0367] The server analyzes the accumulated data using AI algorithms and an emotion engine. It comprehensively evaluates the user's health status, behavioral patterns, and emotional state to identify problems and pinpoint areas for improvement.

[0368] Step 6:

[0369] Based on the analysis results, the server generates specific exercise and dietary guidelines for the user. The analysis results from the emotion engine are also incorporated, including advice aimed at stress reduction and emotional care.

[0370] Step 7:

[0371] The server sends the generated health guidelines and emotional care advice to the terminal, enabling rapid information delivery to the user.

[0372] Step 8:

[0373] The terminal notifies the user of guidance information received from the server. This information is appropriately communicated to the user through a visual or auditory interface.

[0374] Step 9:

[0375] Users act based on the guidance and advice they receive, and record the process and results as feedback on their device.

[0376] Step 10:

[0377] The server receives and analyzes feedback sent from the terminal. This allows for continuous improvement of the guidance provided and adaptive adjustments to make future suggestions more personalized.

[0378] Through this series of processing steps, the system provides support for both the user's physical and emotional well-being, and optimizes itself to meet individual needs.

[0379] (Example 2)

[0380] 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".

[0381] In modern society, comprehensively managing an individual's health and psychological state and providing optimized health guidelines is a challenging task. In particular, methods for integrating and analyzing biometric and emotional data to provide personalized advice have not yet been sufficiently realized. This invention aims to provide a system that delivers health and psychological support tailored to each individual.

[0382] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes data collection means for organizing and receiving biometric information and psychological data in a unified format, analysis means for evaluating the user's health and psychological state through analysis, and guideline generation means for generating personalized exercise, diet, and mental health guidelines based on the analysis results. This enables comprehensive support in both health and psychological aspects that meet the individual needs of the user.

[0383]

[0384] A "data collection method" is a system that receives information about biological activity and psychological state from users in various formats and processes it within the system.

[0385] "Data transfer means" includes technologies and protocols for securely encrypting collected information and transmitting it to a server.

[0386] "Analysis means" refers to methods that use data analysis techniques to evaluate received biometric and emotional data in order to understand the user's health and psychological state.

[0387] A "guideline generation means" is a device that has the function of generating specific guidelines and advice for exercise, diet, and mental health that are suitable for the user, based on the analysis results.

[0388] "Communication methods" refer to transmission technologies used to notify users of generated guidelines and advice and to receive feedback.

[0389] "Adjustment mechanisms" refer to systems that dynamically adapt and improve individual health and psychological support advice based on feedback from users.

[0390] An "emotion engine" is a technology that analyzes voice and facial expression data to evaluate the user's emotional state in real time.

[0391] This invention is an information processing system for comprehensively evaluating a user's health and psychological state and providing personalized guidelines. To achieve this, the system mainly consists of a user terminal, a server for data processing, and an engine for analysis. One embodiment of this invention is shown below.

[0392] Hardware and software selection

[0393] The devices are mobile information terminals such as smartphones and tablets, equipped with interfaces for inputting data in various formats (text, images, audio, and video). This allows users to record their daily activities, meals, and emotions.

[0394] The servers are deployed on a cloud platform and possess advanced data processing capabilities. Data is encrypted using AES (Advanced Encryption Standard) and transmitted securely via the HTTPS protocol.

[0395] The analysis engine incorporates machine learning models and includes an emotion engine for performing emotion analysis using voice and facial expression data. These technologies make it possible to evaluate the user's psychological state and reflect this in the generation of guidelines.

[0396] System operating procedures and functions

[0397] Users input their daily experiences through a dedicated application, including details about their diet, exercise, and emotions.

[0398] The device centralizes the collected data, encrypts it, and then securely transmits it to the server.

[0399] The server uses AI algorithms to analyze information stored in the database, evaluate the user's health and emotional state, and generate personalized health guidelines.

[0400] The terminal notifies the user of guidance information from the server and encourages appropriate action. Furthermore, the server continuously improves its advice based on the feedback received.

[0401] Specific example

[0402] For example, if a user is experiencing emotional stress, the emotion engine detects this state, and the server suggests stress reduction methods. Examples of suggested methods include deep breathing, meditation, and listening to music. After the user acts on these suggestions and provides feedback, the system further personalizes the advice.

[0403] Example of a prompt

[0404] The prompt used is "Suggest effective stress reduction methods when the user is experiencing emotional stress." This prompts the server to utilize a generative AI model to generate appropriate advice.

[0405] As described above, the present invention makes it possible to provide users with personalized health and psychological support and improve their quality of life.

[0406] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0407] Step 1:

[0408] Users input their daily activities and emotional states into the device. The input data includes information on meals, exercise records, and emotions, and is provided in text, image, audio, and video formats. This information serves as foundational data for comprehensively understanding the user's daily life.

[0409] Step 2:

[0410] The terminal receives user input data and converts it into a unified format (e.g., JSON format). This unification of data formats allows for efficient handling of data in subsequent processing. Specifically, this includes pre-processing steps such as compressing image data and converting audio data to text.

[0411] Step 3:

[0412] The terminal encrypts the unified data and sends it to the server. Here, AES encryption technology is used, and secure data transfer is performed via the HTTPS protocol. The input is the encryption key, and the output is the encrypted data file.

[0413] Step 4:

[0414] The server decodes the data received from the terminal and stores it in the database. The decoded data is inserted into the corresponding field in the database. The server checks the integrity of the data and logs the information as needed.

[0415] Step 5:

[0416] The server applies AI algorithms to analyze biometric and emotional information in the database. Here, an emotion engine is used to analyze the user's voice and facial expressions to evaluate their psychological state. The input is raw data, and the output is the analysis results and a health assessment score.

[0417] Step 6:

[0418] The server generates personalized exercise, diet, and mental health guidelines based on the analysis results. Using a generation AI model, it creates individual health guidelines according to the prompt text. The output is a set of advice for the user.

[0419] Step 7:

[0420] The device receives guidance information from the server and notifies the user. The notification is sent using the smartphone's push notification function and is presented as specific advice to encourage the user to take action.

[0421] Step 8:

[0422] Users take action based on notifications from their devices and provide feedback on the results and their impressions to the device. This feedback data is used for future analysis and guideline development. The input is the result of the user's actions, and the output is new data that will lead to improvements in future advice.

[0423] Step 9:

[0424] The server analyzes user feedback data and adaptively updates its guidelines based on newly acquired insights. This ensures that personalized advice is continuously provided, promoting ongoing improvements tailored to user needs.

[0425] (Application Example 2)

[0426] 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."

[0427] In recent years, with the advancement of an aging society, the importance of individualized health support and mental health support has increased. However, conventional technologies have faced the challenge of not being able to comprehensively evaluate physical and mental health status and provide optimized guidelines based on that evaluation. There is also the problem of a lack of systems that can provide personalized health guidelines for the elderly. Therefore, the present invention aims to provide a health support system that takes into account not only the user's physical condition but also their emotional state, and to efficiently generate individualized guidelines.

[0428] 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.

[0429] In this invention, the server includes information processing means for receiving information about activities and lifestyles obtained from users; analysis means for analyzing the information about activities and lifestyles and evaluating the user's condition; guideline generation means for providing appropriate exercise and dietary guidelines to the user based on the evaluation; and means for generating mental health support guidelines based on the emotional state obtained from the evaluation. This makes it possible to comprehensively support the physical and mental health of users and provide personalized health support.

[0430] An "information processing device" is a device that centralizes various forms of input information related to activities and daily life received from users and converts the format as needed.

[0431] An "analysis device" is a device that analyzes and evaluates the user's physical health and emotional state based on the received information.

[0432] A "guideline generation device" is a device that automatically generates appropriate exercise, diet, and mental health guidelines for users based on analysis results.

[0433] A "communication device" is a device used to transmit generated guidelines to users and to notify and share information.

[0434] A "modification mechanism" is a device that receives feedback from users and makes adjustments to continuously optimize the guidelines it provides.

[0435] An "emotion engine" is a device or program that analyzes a user's voice and facial expression data to evaluate their emotional state.

[0436] To implement this invention, it is necessary to build a system in which users, terminals, and servers work together. This system evaluates the user's health and emotional state and provides optimal guidance.

[0437] Users record their daily activities, meals, and emotions using their smartphones. Information can be entered in text, photos, audio, and video formats. Emotions, in particular, are analyzed in real-time by an emotion engine using voice and facial recognition. This emotion engine is software designed to analyze emotional states.

[0438] The device centralizes the received data, encrypts it, and transmits it to a cloud server. In particular, emotional data is treated as a crucial element in subsequent analysis. The device is equipped with communication capabilities and plays a role in notifying the user of the generated guidelines in a timely manner.

[0439] The server uses AI algorithms to comprehensively assess health and emotional states by analyzing incoming data. Here, the server utilizes a generated AI model upon request. Specifically, it proposes mental health support measures based on the assessed emotional state. For example, if the emotion engine detects a stressed state, it generates guidelines including relaxation methods.

[0440] The cloud server accumulates the feedback data it receives and continuously adjusts its guidance generation system to make future advice more personalized. This contributes to the user's long-term health improvement.

[0441] For example, if a user records in voice that they are "feeling a little down," the emotion engine will analyze that emotion and suggest relaxation methods using meditation or music. An example of a prompt would be, "If the user says 'worried,' generate personalized advice suggesting relaxation methods (deep breathing, simple exercises, etc.) to alleviate that emotion."

[0442] It is expected that the implementation of such a system will simultaneously support users' physical and emotional well-being, thereby improving their quality of life.

[0443] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0444] Step 1:

[0445] Users input information about their daily activities, meals, and emotions into their smartphones in various formats such as text, photos, audio, and video. This information is analyzed in real time by an emotion engine via voice or facial recognition. The input here is data in various formats, and the output is the analyzed emotional state.

[0446] Step 2:

[0447] The terminal centralizes this input data and standardizes its format. This data is securely transmitted to the cloud server using industry-standard encryption technology. Specifically, image data is converted to JPEG format and audio to WAV format. The output is encrypted data in a transmittable format.

[0448] Step 3:

[0449] The server analyzes the received data. Using AI algorithms, it assesses the user's health and emotional state. Input is standardized data, and output includes exercise plans and dietary guidelines based on health status, and mental health support measures based on emotional state. A generative AI model is used to refer to the user's past data and create specific advice.

[0450] Step 4:

[0451] The server generates optimized guidelines based on the evaluated data and sends them to the terminal. Specifically, it suggests personalized exercise plans and relaxation methods. The output here consists of individual health guidelines and mental health support measures.

[0452] Step 5:

[0453] The device notifies the user of guidelines received from the server. These notifications are delivered via pop-up messages or in-app notifications. The output is advice information displayed in a user-recognizable format.

[0454] Step 6:

[0455] The user takes action based on the advice provided and then provides feedback on the results and their impressions back to the device. The input is the user's feedback or additional information, and the output is adjusted health guidelines.

[0456] Step 7:

[0457] The server adjusts its guidelines based on user feedback. It evaluates the effectiveness of previous advice and incorporates it into future guidelines. Specifically, it stores feedback data in a database and uses an AI algorithm to generate the next set of guidelines. This enables more personalized suggestions.

[0458] 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.

[0459] 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.

[0460] 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.

[0461] [Third Embodiment]

[0462] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0463] 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.

[0464] 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).

[0465] 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.

[0466] 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.

[0467] 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).

[0468] 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.

[0469] 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.

[0470] 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.

[0471] 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.

[0472] 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.

[0473] 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".

[0474] This invention is a system that continuously monitors the user's health status and provides appropriate guidelines for health promotion. This system functions through cooperation between the user, terminal, and server, as shown below.

[0475] First, users record their daily activities and meals on the device. This information can be provided in the form of text, photos, audio, or video data. Users can record their daily meals, exercise habits, and even sleep patterns in this system.

[0476] Next, the terminal formats the received information appropriately and prepares it for transmission to the server. To ensure security, the information is encrypted before being sent to the server.

[0477] Subsequently, the server stores the received data in a database and analyzes it using an AI algorithm. This data analysis allows for a detailed evaluation of the user's health status and behavioral patterns, enabling the identification of anomalies and areas for improvement.

[0478] Based on the analysis results, the server generates personalized exercise plans and dietary guidelines for each user. It also considers the user's stress levels and sleep patterns to provide lifestyle advice, including relaxation methods and sleep improvement strategies.

[0479] The device then notifies the user of advice information sent from the server. The user can receive the notification and provide feedback. For example, they can report the results of their exercise or input their thoughts on dietary improvements into the device.

[0480] Ultimately, the server analyzes user feedback and adaptively adjusts the advice it provides. This allows for more accurate and repeated advice, enabling users to maintain their health in the long term.

[0481] For example, if a user is experiencing sleep deprivation, the server can analyze their pre-sleep behavior patterns from collected data and provide calming stretches or relaxation techniques before bedtime. If the user provides feedback accordingly, the server can offer further personalized suggestions. In this way, the present invention is a system that continuously supports the user's health through a series of information processing steps.

[0482] The following describes the processing flow.

[0483] Step 1:

[0484] Users record their daily activities and diet on their devices. They provide information in various formats, such as text, images, and audio, accumulating daily health data.

[0485] Step 2:

[0486] The terminal collects information entered by the user and standardizes the data format. It encrypts the data and prepares it for transmission to the server, ensuring the security of the communication.

[0487] Step 3:

[0488] The server receives data sent from the terminal and stores it in a database. The stored data is managed on an individual basis and used for future analysis and evaluation.

[0489] Step 4:

[0490] The server analyzes the stored data using AI algorithms. It compares this data with the user's past data to assess their current health status and comprehensively analyzes their lifestyle patterns and health trends.

[0491] Step 5:

[0492] Based on the analysis results, the server generates personalized exercise plans and dietary guidelines for the user. Furthermore, it creates specific advice for stress management and sleep improvement.

[0493] Step 6:

[0494] The server sends the generated health guidelines to the terminal.

[0495] Step 7:

[0496] The terminal notifies the user of advice information received from the server. It displays the information on the interface so the user can review it, and allows for reminder settings as needed.

[0497] Step 8:

[0498] Users take action based on the advice provided and record the results and their impressions as feedback on their device. This feedback is used for further analysis.

[0499] Step 9:

[0500] The server receives and analyzes user feedback data. This allows for adjustments to be made to improve the accuracy of health guidelines and incorporate the findings into future recommendations.

[0501] By repeatedly performing the steps described above, users can manage their health in a sustainable manner, and the entire system can flexibly respond to the user's needs.

[0502] (Example 1)

[0503] 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."

[0504] In modern times, many people face health problems due to stress and irregular lifestyles in their daily lives. However, solving these problems requires appropriate and personalized guidance tailored to individual circumstances. Traditional methods merely aggregate user data without fully utilizing data-driven insights, and a particular problem is the lack of continuous support for long-term health maintenance.

[0505] 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.

[0506] In this invention, the server includes data processing means that receive activity and lifestyle information obtained from users and handle the data in multiple information formats; analysis means that analyze the activity and lifestyle information and evaluate the user's health status and behavioral patterns in detail using a generated AI model; and guideline generation means that generate personalized exercise and dietary guidelines for the user based on the evaluation. This enables the timely provision of highly personalized health advice and guidelines for each user, making long-term health improvement and maintenance possible.

[0507] "Data processing means" refers to a device or function for appropriately receiving information in various formats obtained from users and performing encryption or format conversion.

[0508] "Analysis means" refers to a device or function that uses an AI model generated based on received information to evaluate in detail the user's health status and behavioral patterns.

[0509] A "guideline generation means" refers to a device or function that generates exercise plans and dietary guidelines tailored to each individual user based on the analysis results.

[0510] "Communication means" refers to a device or function for transmitting guidelines to users and collecting feedback from users.

[0511] "Adjustment means" refers to a device or function that analyzes user feedback to refine suggestions for future use and improve the accuracy of the advice provided.

[0512] This invention is a system that continuously monitors the user's health status and provides personalized health guidance. The system mainly consists of three elements: a terminal, a server, and the user.

[0513] Users input information about their daily activities and lifestyle into the device. Input methods are diverse and can be provided in various formats, including text, images, audio, and video. For example, a user can record their morning run using the device.

[0514] The device receives this information, formats the data appropriately, encrypts it, and prepares it for transmission to the server. This protects the user's privacy. The hardware used includes smartphones and tablets, and the corresponding software is a dedicated health management application.

[0515] The server receives information transmitted from the terminal and analyzes the data using a generative AI model. Specifically, it evaluates behavioral patterns and health status from accumulated user activity data, identifying issues such as lack of exercise or nutritional imbalances. Based on the analysis results, it generates personalized exercise programs and dietary guidelines for the user. For example, based on sleep data, the server can provide specific advice to promote higher quality sleep.

[0516] The generated advice and guidelines are then communicated to the user via the device. The user implements the guidance and provides feedback on the results and their impressions. This allows the system to incorporate user feedback and improve the accuracy of the next set of guidelines it provides.

[0517] In this process, by providing the generating AI model with specific instructions, such as "Based on the user's past meal data, suggest a meal plan that takes nutritional balance into consideration for next week," personalized health guidance can be achieved.

[0518] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0519] Step 1:

[0520] Users input information about their daily activities and lifestyle using devices such as smartphones and tablets. This information includes text, images, audio, and video, and may include recordings of steps taken, meals eaten, and sleep duration in a dedicated application. When inputting information, users use input interfaces compatible with each format, and the day's activities are saved on the device.

[0521] Step 2:

[0522] The terminal receives information from the user and converts it into a unified format. This includes formatting text data and compressing image and audio data. The data is then AES encrypted and prepared for secure transfer to the server. The output is encrypted data, which is then sent to the server.

[0523] Step 3:

[0524] The server receives encrypted data sent from the terminal and decrypts it. The decrypted information is stored in a dedicated cloud database. Subsequently, data analysis begins using a generative AI model, which analyzes health status and behavioral patterns in detail. Based on the input data, the user's exercise level and nutritional balance are evaluated, and a health assessment is conducted and saved as output.

[0525] Step 4:

[0526] The server creates personalized exercise plans and dietary guidelines based on the analysis results. These generated guidelines might include suggestions for users who are sedentary, such as recommending three walks per week or dietary improvements. The generating AI model automatically generates optimized advice for future health maintenance, taking past data into consideration. The output is personalized guideline information tailored to each user.

[0527] Step 5:

[0528] The device receives personalized guidelines sent from the server and notifies the user. Notifications are delivered via push notifications, in-app notifications, etc., allowing the user to review the provided guidelines. A feedback input interface is also provided to facilitate user responses. The output consists of specific health guidelines for the user to take action.

[0529] Step 6:

[0530] Users follow the instructions received from their device and input the results and their impressions as feedback into the device. For example, they input the results after completing a walking plan suggested by the server, providing information to be used for future advice. Feedback is entered through the data input screen of a dedicated app.

[0531] Step 7:

[0532] The server receives feedback from the user and analyzes its content again using the generative AI model. This analysis evaluates the user's improvement and the effectiveness of the guidelines, and the feedback is incorporated into future suggestions. As a result, the server can improve the accuracy of personalized guidelines and develop future health support that is more tailored to the user.

[0533] (Application Example 1)

[0534] 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."

[0535] In modern society, health management is crucial for improving an individual's quality of life. However, conventional health management systems are limited to analyzing individual data and fail to utilize data from the entire community or society as a whole, making it difficult to provide more accurate and personalized health promotion guidelines.

[0536] 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.

[0537] In this invention, the server includes information processing means for receiving information on activities and lifestyles obtained from users; analysis means for analyzing the information on activities and lifestyles and evaluating the user's condition; and means for analyzing health data for the entire city and providing health promotion guidelines to individual users based on the results. This enables more appropriate and detailed health management based not only on individual circumstances but also on health data for the entire city.

[0538] "Information processing means" refers to fundamental technologies for receiving information about users' activities and lifestyles, converting it into data format, and performing analysis.

[0539] "Analysis means" refers to technologies that evaluate the user's condition based on received information and understand their health status and behavioral tendencies.

[0540] A "guideline generation method" is a technology that provides users with appropriate exercise and dietary guidelines based on analysis results.

[0541] "Communication means" refers to the technology used to transmit generated guidelines to users and to ensure that this communication is reliable.

[0542] "Adjustment methods" refer to technologies that adaptively adjust guidelines based on feedback obtained from users, thereby providing more personalized health promotion guidelines.

[0543] "Health data" refers to data that indicates the overall health status of a city, and is used to generate health guidelines for individual users.

[0544] The system that realizes this invention consists of a terminal including a smartphone, a server that analyzes data, and a user that utilizes an application. The system's program collects information on the user's activities and lifestyle, analyzes it, and generates individualized health promotion guidelines.

[0545] The device receives information such as activity data, meal data, and sleep patterns entered by the user. This information is recorded in the form of text data, image data, audio data, and video data. Upon receiving this information, the device encrypts it and sends it to the server.

[0546] The server uses advanced AI algorithms to analyze the received information. Machine learning libraries such as TensorFlow and PyTorch are used for this analysis. This analysis allows for the assessment of the user's health status and a detailed understanding of their behavioral patterns. Furthermore, it generates more precise guidelines by comparing this data with city-wide health data.

[0547] The guidelines generated from the analysis results are sent to the device and notified to the user. The user can then use these guidelines to improve their daily life. Furthermore, the feedback function allows the user to input their own thoughts and results again into the device.

[0548] Ultimately, the server adaptively adjusts the guidelines using user feedback and incorporates it into future guideline generation. This allows users to continuously promote their health.

[0549] For example, if a user feels they are not getting enough exercise, the server compares the user's past exercise data with the city's average data and suggests an appropriate exercise plan. An example of a prompt to the generating AI could be: "Compare the user's exercise data with the city's average data and provide reasonable exercise advice."

[0550] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0551] Step 1:

[0552] Users input information about their daily activities and meals into a smartphone or other device. This input can be in text, image, audio, or video format. The entered information is temporarily stored on the device.

[0553] Step 2:

[0554] The terminal encrypts stored user data and transmits it to the server via a secure communication protocol. The input here is user activity data, and the output is encrypted data. The terminal uses encryption algorithms such as AES.

[0555] Step 3:

[0556] The server decrypts the received encrypted data and stores it in the database. The input here is encrypted data, and the output is analyzable raw data. The server maintains data security using SSL / TLS.

[0557] Step 4:

[0558] The server analyzes the data using AI libraries such as TensorFlow and PyTorch. The input is decoded user data, and the output is the health status assessment result. In this step, the server analyzes historical data and city-wide health data together.

[0559] Step 5:

[0560] The server generates personalized health promotion guidelines for users based on the analysis results. The input is the health status assessment, and the output is specific guidance for the user. A generation AI model streamlines this process.

[0561] Step 6:

[0562] The server sends the generated guidelines to the terminal and communicates them to the user via a notification function. The input is the generated guidelines, and the output is the notification on the user's terminal. The terminal uses a push notification service.

[0563] Step 7:

[0564] Based on the guidelines received, users improve their lifestyles and input feedback on what they did and the results they experienced into their device. This feedback is then sent back to the server. In this step, the input is the results of the actions taken, and the output is feedback data.

[0565] Step 8:

[0566] The server analyzes user feedback and uses a generative AI model to incorporate that feedback into future guideline creation. The input is user feedback, and the output is a revised draft of future guidelines. This allows for progressively more accurate advice.

[0567] 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.

[0568] This invention is a system that evaluates a user's health status from multiple perspectives and provides individually optimized health guidelines. In particular, by incorporating an emotion engine, it realizes support that also takes into account the user's emotional state. This system functions in cooperation with the user, terminal, and server.

[0569] First, users record various daily activities, meals, and emotions on the device. This information can be entered in various formats, including text, photos, audio, and video. In addition, voice and facial expression data are analyzed by an emotion engine to collect the user's emotions in real time.

[0570] Next, the terminal centralizes this information and standardizes the data format. The data is encrypted for secure transmission to the server. At this stage, data related to emotions, in particular, is treated as an important element in subsequent analysis.

[0571] The server organizes the data received from the terminal and stores it in a database. Next, an AI algorithm analyzes this data to comprehensively evaluate the user's health and emotional state. By using an emotion engine, the user's psychological state is also examined, and this information can be reflected in the health guidelines provided.

[0572] Subsequently, the server generates an exercise plan and dietary guidelines optimized for the user based on the analysis results, and also creates comprehensive advice that includes mental health support guidelines tailored to the user's emotional state. This advice serves as a concrete guideline for the user to improve their current situation.

[0573] The device notifies the user of advice received from the server. The user then takes action based on this advice and provides feedback to the device regarding the results and their impressions, accumulating feedback data. Based on this feedback, the advice is continuously improved.

[0574] For example, if a user is experiencing emotional stress, the emotion engine detects this state, and the server provides advice, including methods for stress reduction. For instance, it can suggest relaxation techniques such as deep breathing, meditation, or listening to music. Based on user feedback, the server adjusts its next suggestions to be more personalized.

[0575] Thus, the present invention aims to provide an integrated healthcare system that simultaneously supports physical and mental health, thereby improving the quality of life for users.

[0576] The following describes the processing flow.

[0577] Step 1:

[0578] Users input their daily habits, diet, and emotions at the time into the device. In particular, emotional data is recorded through voice input and facial expression capture, and detailed information is collected.

[0579] Step 2:

[0580] The terminal receives diverse data from users and standardizes it according to each data format. The obtained information is integrated and appropriately formatted in preparation for analysis.

[0581] Step 3:

[0582] The device encrypts standardized data and sends it to the server using a secure communication protocol. This process is crucial to ensure data security and privacy.

[0583] Step 4:

[0584] The server receives data sent from the terminal, organizes it in the database, and stores it. Integrated management is performed with historical information, including past data.

[0585] Step 5:

[0586] The server analyzes the accumulated data using AI algorithms and an emotion engine. It comprehensively evaluates the user's health status, behavioral patterns, and emotional state to identify problems and pinpoint areas for improvement.

[0587] Step 6:

[0588] Based on the analysis results, the server generates specific exercise and dietary guidelines for the user. The analysis results from the emotion engine are also incorporated, including advice aimed at stress reduction and emotional care.

[0589] Step 7:

[0590] The server sends the generated health guidelines and emotional care advice to the terminal, enabling rapid information delivery to the user.

[0591] Step 8:

[0592] The terminal notifies the user of guidance information received from the server. This information is appropriately communicated to the user through a visual or auditory interface.

[0593] Step 9:

[0594] Users act based on the guidance and advice they receive, and record the process and results as feedback on their device.

[0595] Step 10:

[0596] The server receives and analyzes feedback sent from the terminal. This allows for continuous improvement of the guidance provided and adaptive adjustments to make future suggestions more personalized.

[0597] Through this series of processing steps, the system provides support for both the user's physical and emotional well-being, and optimizes itself to meet individual needs.

[0598] (Example 2)

[0599] 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."

[0600] In modern society, comprehensively managing an individual's health and psychological state and providing optimized health guidelines is a challenging task. In particular, methods for integrating and analyzing biometric and emotional data to provide personalized advice have not yet been sufficiently realized. This invention aims to provide a system that delivers health and psychological support tailored to each individual.

[0601] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes data collection means for organizing and receiving biometric information and psychological data in a unified format, analysis means for evaluating the user's health and psychological state through analysis, and guideline generation means for generating personalized exercise, diet, and mental health guidelines based on the analysis results. This enables comprehensive support in both health and psychological aspects that meet the individual needs of the user.

[0602]

[0603] A "data collection method" is a system that receives information about biological activity and psychological state from users in various formats and processes it within the system.

[0604] "Data transfer means" includes technologies and protocols for securely encrypting collected information and transmitting it to a server.

[0605] "Analysis means" refers to methods that use data analysis techniques to evaluate received biometric and emotional data in order to understand the user's health and psychological state.

[0606] A "guideline generation means" is a device that has the function of generating specific guidelines and advice for exercise, diet, and mental health that are suitable for the user, based on the analysis results.

[0607] "Communication methods" refer to transmission technologies used to notify users of generated guidelines and advice and to receive feedback.

[0608] "Adjustment mechanisms" refer to systems that dynamically adapt and improve individual health and psychological support advice based on feedback from users.

[0609] An "emotion engine" is a technology that analyzes voice and facial expression data to evaluate the user's emotional state in real time.

[0610] This invention is an information processing system for comprehensively evaluating a user's health and psychological state and providing personalized guidelines. To achieve this, the system mainly consists of a user terminal, a server for data processing, and an engine for analysis. One embodiment of this invention is shown below.

[0611] Hardware and software selection

[0612] The devices are mobile information terminals such as smartphones and tablets, equipped with interfaces for inputting data in various formats (text, images, audio, and video). This allows users to record their daily activities, meals, and emotions.

[0613] The servers are deployed on a cloud platform and possess advanced data processing capabilities. Data is encrypted using AES (Advanced Encryption Standard) and transmitted securely via the HTTPS protocol.

[0614] The analysis engine incorporates machine learning models and includes an emotion engine for performing emotion analysis using voice and facial expression data. These technologies make it possible to evaluate the user's psychological state and reflect this in the generation of guidelines.

[0615] System operating procedures and functions

[0616] Users input their daily experiences through a dedicated application, including details about their diet, exercise, and emotions.

[0617] The device centralizes the collected data, encrypts it, and then securely transmits it to the server.

[0618] The server uses AI algorithms to analyze information stored in the database, evaluate the user's health and emotional state, and generate personalized health guidelines.

[0619] The terminal notifies the user of guidance information from the server and encourages appropriate action. Furthermore, the server continuously improves its advice based on the feedback received.

[0620] Specific example

[0621] For example, if a user is experiencing emotional stress, the emotion engine detects this state, and the server suggests stress reduction methods. Examples of suggested methods include deep breathing, meditation, and listening to music. After the user acts on these suggestions and provides feedback, the system further personalizes the advice.

[0622] Example of a prompt

[0623] The prompt used is "Suggest effective stress reduction methods when the user is experiencing emotional stress." This prompts the server to utilize a generative AI model to generate appropriate advice.

[0624] As described above, the present invention makes it possible to provide users with personalized health and psychological support and improve their quality of life.

[0625] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0626] Step 1:

[0627] Users input their daily activities and emotional states into the device. The input data includes information on meals, exercise records, and emotions, and is provided in text, image, audio, and video formats. This information serves as foundational data for comprehensively understanding the user's daily life.

[0628] Step 2:

[0629] The terminal receives user input data and converts it into a unified format (e.g., JSON format). This unification of data formats allows for efficient handling of data in subsequent processing. Specifically, this includes pre-processing steps such as compressing image data and converting audio data to text.

[0630] Step 3:

[0631] The terminal encrypts the unified data and sends it to the server. Here, AES encryption technology is used, and secure data transfer is performed via the HTTPS protocol. The input is the encryption key, and the output is the encrypted data file.

[0632] Step 4:

[0633] The server decodes the data received from the terminal and stores it in the database. The decoded data is inserted into the corresponding field in the database. The server checks the integrity of the data and logs the information as needed.

[0634] Step 5:

[0635] The server applies AI algorithms to analyze biometric and emotional information in the database. Here, an emotion engine is used to analyze the user's voice and facial expressions to evaluate their psychological state. The input is raw data, and the output is the analysis results and a health assessment score.

[0636] Step 6:

[0637] The server generates personalized exercise, diet, and mental health guidelines based on the analysis results. Using a generation AI model, it creates individual health guidelines according to the prompt text. The output is a set of advice for the user.

[0638] Step 7:

[0639] The device receives guidance information from the server and notifies the user. The notification is sent using the smartphone's push notification function and is presented as specific advice to encourage the user to take action.

[0640] Step 8:

[0641] Users take action based on notifications from their devices and provide feedback on the results and their impressions to the device. This feedback data is used for future analysis and guideline development. The input is the result of the user's actions, and the output is new data that will lead to improvements in future advice.

[0642] Step 9:

[0643] The server analyzes user feedback data and adaptively updates its guidelines based on newly acquired insights. This ensures that personalized advice is continuously provided, promoting ongoing improvements tailored to user needs.

[0644] (Application Example 2)

[0645] 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."

[0646] In recent years, with the advancement of an aging society, the importance of individualized health support and mental health support has increased. However, conventional technologies have faced the challenge of not being able to comprehensively evaluate physical and mental health status and provide optimized guidelines based on that evaluation. There is also the problem of a lack of systems that can provide personalized health guidelines for the elderly. Therefore, the present invention aims to provide a health support system that takes into account not only the user's physical condition but also their emotional state, and to efficiently generate individualized guidelines.

[0647] 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.

[0648] In this invention, the server includes information processing means for receiving information about activities and lifestyles obtained from users; analysis means for analyzing the information about activities and lifestyles and evaluating the user's condition; guideline generation means for providing appropriate exercise and dietary guidelines to the user based on the evaluation; and means for generating mental health support guidelines based on the emotional state obtained from the evaluation. This makes it possible to comprehensively support the physical and mental health of users and provide personalized health support.

[0649] An "information processing device" is a device that centralizes various forms of input information related to activities and daily life received from users and converts the format as needed.

[0650] An "analysis device" is a device that analyzes and evaluates the user's physical health and emotional state based on the received information.

[0651] A "guideline generation device" is a device that automatically generates appropriate exercise, diet, and mental health guidelines for users based on analysis results.

[0652] A "communication device" is a device used to transmit generated guidelines to users and to notify and share information.

[0653] A "modification mechanism" is a device that receives feedback from users and makes adjustments to continuously optimize the guidelines it provides.

[0654] An "emotion engine" is a device or program that analyzes a user's voice and facial expression data to evaluate their emotional state.

[0655] To implement this invention, it is necessary to build a system in which users, terminals, and servers work together. This system evaluates the user's health and emotional state and provides optimal guidance.

[0656] Users record their daily activities, meals, and emotions using their smartphones. Information can be entered in text, photos, audio, and video formats. Emotions, in particular, are analyzed in real-time by an emotion engine using voice and facial recognition. This emotion engine is software designed to analyze emotional states.

[0657] The device centralizes the received data, encrypts it, and transmits it to a cloud server. In particular, emotional data is treated as a crucial element in subsequent analysis. The device is equipped with communication capabilities and plays a role in notifying the user of the generated guidelines in a timely manner.

[0658] The server uses AI algorithms to comprehensively assess health and emotional states by analyzing incoming data. Here, the server utilizes a generated AI model upon request. Specifically, it proposes mental health support measures based on the assessed emotional state. For example, if the emotion engine detects a stressed state, it generates guidelines including relaxation methods.

[0659] The cloud server accumulates the feedback data it receives and continuously adjusts its guidance generation system to make future advice more personalized. This contributes to the user's long-term health improvement.

[0660] For example, if a user records in voice that they are "feeling a little down," the emotion engine will analyze that emotion and suggest relaxation methods using meditation or music. An example of a prompt would be, "If the user says 'worried,' generate personalized advice suggesting relaxation methods (deep breathing, simple exercises, etc.) to alleviate that emotion."

[0661] It is expected that the implementation of such a system will simultaneously support users' physical and emotional well-being, thereby improving their quality of life.

[0662] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0663] Step 1:

[0664] Users input information about their daily activities, meals, and emotions into their smartphones in various formats such as text, photos, audio, and video. This information is analyzed in real time by an emotion engine via voice or facial recognition. The input here is data in various formats, and the output is the analyzed emotional state.

[0665] Step 2:

[0666] The terminal centralizes this input data and standardizes its format. This data is securely transmitted to the cloud server using industry-standard encryption technology. Specifically, image data is converted to JPEG format and audio to WAV format. The output is encrypted data in a transmittable format.

[0667] Step 3:

[0668] The server analyzes the received data. Using AI algorithms, it assesses the user's health and emotional state. Input is standardized data, and output includes exercise plans and dietary guidelines based on health status, and mental health support measures based on emotional state. A generative AI model is used to refer to the user's past data and create specific advice.

[0669] Step 4:

[0670] The server generates optimized guidelines based on the evaluated data and sends them to the terminal. Specifically, it suggests personalized exercise plans and relaxation methods. The output here consists of individual health guidelines and mental health support measures.

[0671] Step 5:

[0672] The device notifies the user of guidelines received from the server. These notifications are delivered via pop-up messages or in-app notifications. The output is advice information displayed in a user-recognizable format.

[0673] Step 6:

[0674] The user takes action based on the advice provided and then provides feedback on the results and their impressions back to the device. The input is the user's feedback or additional information, and the output is adjusted health guidelines.

[0675] Step 7:

[0676] The server adjusts its guidelines based on user feedback. It evaluates the effectiveness of previous advice and incorporates it into future guidelines. Specifically, it stores feedback data in a database and uses an AI algorithm to generate the next set of guidelines. This enables more personalized suggestions.

[0677] 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.

[0678] 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.

[0679] 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.

[0680] [Fourth Embodiment]

[0681] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0682] 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.

[0683] 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).

[0684] 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.

[0685] 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.

[0686] 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).

[0687] 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.

[0688] 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.

[0689] 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.

[0690] 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.

[0691] 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.

[0692] 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.

[0693] 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".

[0694] This invention is a system that continuously monitors the user's health status and provides appropriate guidelines for health promotion. This system functions through cooperation between the user, terminal, and server, as shown below.

[0695] First, users record their daily activities and meals on the device. This information can be provided in the form of text, photos, audio, or video data. Users can record their daily meals, exercise habits, and even sleep patterns in this system.

[0696] Next, the terminal formats the received information appropriately and prepares it for transmission to the server. To ensure security, the information is encrypted before being sent to the server.

[0697] Subsequently, the server stores the received data in a database and analyzes it using an AI algorithm. This data analysis allows for a detailed evaluation of the user's health status and behavioral patterns, enabling the identification of anomalies and areas for improvement.

[0698] Based on the analysis results, the server generates personalized exercise plans and dietary guidelines for each user. It also considers the user's stress levels and sleep patterns to provide lifestyle advice, including relaxation methods and sleep improvement strategies.

[0699] The device then notifies the user of advice information sent from the server. The user can receive the notification and provide feedback. For example, they can report the results of their exercise or input their thoughts on dietary improvements into the device.

[0700] Ultimately, the server analyzes user feedback and adaptively adjusts the advice it provides. This allows for more accurate and repeated advice, enabling users to maintain their health in the long term.

[0701] For example, if a user is experiencing sleep deprivation, the server can analyze their pre-sleep behavior patterns from collected data and provide calming stretches or relaxation techniques before bedtime. If the user provides feedback accordingly, the server can offer further personalized suggestions. In this way, the present invention is a system that continuously supports the user's health through a series of information processing steps.

[0702] The following describes the processing flow.

[0703] Step 1:

[0704] Users record their daily activities and diet on their devices. They provide information in various formats, such as text, images, and audio, accumulating daily health data.

[0705] Step 2:

[0706] The terminal collects information entered by the user and standardizes the data format. It encrypts the data and prepares it for transmission to the server, ensuring the security of the communication.

[0707] Step 3:

[0708] The server receives data sent from the terminal and stores it in a database. The stored data is managed on an individual basis and used for future analysis and evaluation.

[0709] Step 4:

[0710] The server analyzes the stored data using AI algorithms. It compares this data with the user's past data to assess their current health status and comprehensively analyzes their lifestyle patterns and health trends.

[0711] Step 5:

[0712] Based on the analysis results, the server generates personalized exercise plans and dietary guidelines for the user. Furthermore, it creates specific advice for stress management and sleep improvement.

[0713] Step 6:

[0714] The server sends the generated health guidelines to the terminal.

[0715] Step 7:

[0716] The terminal notifies the user of advice information received from the server. It displays the information on the interface so the user can review it, and allows for reminder settings as needed.

[0717] Step 8:

[0718] Users take action based on the advice provided and record the results and their impressions as feedback on their device. This feedback is used for further analysis.

[0719] Step 9:

[0720] The server receives and analyzes user feedback data. This allows for adjustments to be made to improve the accuracy of health guidelines and incorporate the findings into future recommendations.

[0721] By repeatedly performing the steps described above, users can manage their health in a sustainable manner, and the entire system can flexibly respond to the user's needs.

[0722] (Example 1)

[0723] 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".

[0724] In modern times, many people face health problems due to stress and irregular lifestyles in their daily lives. However, solving these problems requires appropriate and personalized guidance tailored to individual circumstances. Traditional methods merely aggregate user data without fully utilizing data-driven insights, and a particular problem is the lack of continuous support for long-term health maintenance.

[0725] 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.

[0726] In this invention, the server includes data processing means that receive activity and lifestyle information obtained from users and handle the data in multiple information formats; analysis means that analyze the activity and lifestyle information and evaluate the user's health status and behavioral patterns in detail using a generated AI model; and guideline generation means that generate personalized exercise and dietary guidelines for the user based on the evaluation. This enables the timely provision of highly personalized health advice and guidelines for each user, making long-term health improvement and maintenance possible.

[0727] "Data processing means" refers to a device or function for appropriately receiving information in various formats obtained from users and performing encryption or format conversion.

[0728] "Analysis means" refers to a device or function that uses an AI model generated based on received information to evaluate in detail the user's health status and behavioral patterns.

[0729] A "guideline generation means" refers to a device or function that generates exercise plans and dietary guidelines tailored to each individual user based on the analysis results.

[0730] "Communication means" refers to a device or function for transmitting guidelines to users and collecting feedback from users.

[0731] "Adjustment means" refers to a device or function that analyzes user feedback to refine suggestions for future use and improve the accuracy of the advice provided.

[0732] This invention is a system that continuously monitors the user's health status and provides personalized health guidance. The system mainly consists of three elements: a terminal, a server, and the user.

[0733] Users input information about their daily activities and lifestyle into the device. Input methods are diverse and can be provided in various formats, including text, images, audio, and video. For example, a user can record their morning run using the device.

[0734] The device receives this information, formats the data appropriately, encrypts it, and prepares it for transmission to the server. This protects the user's privacy. The hardware used includes smartphones and tablets, and the corresponding software is a dedicated health management application.

[0735] The server receives information transmitted from the terminal and analyzes the data using a generative AI model. Specifically, it evaluates behavioral patterns and health status from accumulated user activity data, identifying issues such as lack of exercise or nutritional imbalances. Based on the analysis results, it generates personalized exercise programs and dietary guidelines for the user. For example, based on sleep data, the server can provide specific advice to promote higher quality sleep.

[0736] The generated advice and guidelines are then communicated to the user via the device. The user implements the guidance and provides feedback on the results and their impressions. This allows the system to incorporate user feedback and improve the accuracy of the next set of guidelines it provides.

[0737] In this process, by providing the generating AI model with specific instructions, such as "Based on the user's past meal data, suggest a meal plan that takes nutritional balance into consideration for next week," personalized health guidance can be achieved.

[0738] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0739] Step 1:

[0740] Users input information about their daily activities and lifestyle using devices such as smartphones and tablets. This information includes text, images, audio, and video, and may include recordings of steps taken, meals eaten, and sleep duration in a dedicated application. When inputting information, users use input interfaces compatible with each format, and the day's activities are saved on the device.

[0741] Step 2:

[0742] The terminal receives information from the user and converts it into a unified format. This includes formatting text data and compressing image and audio data. The data is then AES encrypted and prepared for secure transfer to the server. The output is encrypted data, which is then sent to the server.

[0743] Step 3:

[0744] The server receives encrypted data sent from the terminal and decrypts it. The decrypted information is stored in a dedicated cloud database. Subsequently, data analysis begins using a generative AI model, which analyzes health status and behavioral patterns in detail. Based on the input data, the user's exercise level and nutritional balance are evaluated, and a health assessment is conducted and saved as output.

[0745] Step 4:

[0746] The server creates personalized exercise plans and dietary guidelines based on the analysis results. These generated guidelines might include suggestions for users who are sedentary, such as recommending three walks per week or dietary improvements. The generating AI model automatically generates optimized advice for future health maintenance, taking past data into consideration. The output is personalized guideline information tailored to each user.

[0747] Step 5:

[0748] The device receives personalized guidelines sent from the server and notifies the user. Notifications are delivered via push notifications, in-app notifications, etc., allowing the user to review the provided guidelines. A feedback input interface is also provided to facilitate user responses. The output consists of specific health guidelines for the user to take action.

[0749] Step 6:

[0750] Users follow the instructions received from their device and input the results and their impressions as feedback into the device. For example, they input the results after completing a walking plan suggested by the server, providing information to be used for future advice. Feedback is entered through the data input screen of a dedicated app.

[0751] Step 7:

[0752] The server receives feedback from the user and analyzes its content again using the generative AI model. This analysis evaluates the user's improvement and the effectiveness of the guidelines, and the feedback is incorporated into future suggestions. As a result, the server can improve the accuracy of personalized guidelines and develop future health support that is more tailored to the user.

[0753] (Application Example 1)

[0754] 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".

[0755] In modern society, health management is crucial for improving an individual's quality of life. However, conventional health management systems are limited to analyzing individual data and fail to utilize data from the entire community or society as a whole, making it difficult to provide more accurate and personalized health promotion guidelines.

[0756] 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.

[0757] In this invention, the server includes information processing means for receiving information on activities and lifestyles obtained from users; analysis means for analyzing the information on activities and lifestyles and evaluating the user's condition; and means for analyzing health data for the entire city and providing health promotion guidelines to individual users based on the results. This enables more appropriate and detailed health management based not only on individual circumstances but also on health data for the entire city.

[0758] "Information processing means" refers to fundamental technologies for receiving information about users' activities and lifestyles, converting it into data format, and performing analysis.

[0759] "Analysis means" refers to technologies that evaluate the user's condition based on received information and understand their health status and behavioral tendencies.

[0760] A "guideline generation method" is a technology that provides users with appropriate exercise and dietary guidelines based on analysis results.

[0761] "Communication means" refers to the technology used to transmit generated guidelines to users and to ensure that this communication is reliable.

[0762] "Adjustment methods" refer to technologies that adaptively adjust guidelines based on feedback obtained from users, thereby providing more personalized health promotion guidelines.

[0763] "Health data" refers to data that indicates the overall health status of a city, and is used to generate health guidelines for individual users.

[0764] The system that realizes this invention consists of a terminal including a smartphone, a server that analyzes data, and a user that utilizes an application. The system's program collects information on the user's activities and lifestyle, analyzes it, and generates individualized health promotion guidelines.

[0765] The device receives information such as activity data, meal data, and sleep patterns entered by the user. This information is recorded in the form of text data, image data, audio data, and video data. Upon receiving this information, the device encrypts it and sends it to the server.

[0766] The server uses advanced AI algorithms to analyze the received information. Machine learning libraries such as TensorFlow and PyTorch are used for this analysis. This analysis allows for the assessment of the user's health status and a detailed understanding of their behavioral patterns. Furthermore, it generates more precise guidelines by comparing this data with city-wide health data.

[0767] The guidelines generated from the analysis results are sent to the device and notified to the user. The user can then use these guidelines to improve their daily life. Furthermore, the feedback function allows the user to input their own thoughts and results again into the device.

[0768] Ultimately, the server adaptively adjusts the guidelines using user feedback and incorporates it into future guideline generation. This allows users to continuously promote their health.

[0769] For example, if a user feels they are not getting enough exercise, the server compares the user's past exercise data with the city's average data and suggests an appropriate exercise plan. An example of a prompt to the generating AI could be: "Compare the user's exercise data with the city's average data and provide reasonable exercise advice."

[0770] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0771] Step 1:

[0772] Users input information about their daily activities and meals into a smartphone or other device. This input can be in text, image, audio, or video format. The entered information is temporarily stored on the device.

[0773] Step 2:

[0774] The terminal encrypts stored user data and transmits it to the server via a secure communication protocol. The input here is user activity data, and the output is encrypted data. The terminal uses encryption algorithms such as AES.

[0775] Step 3:

[0776] The server decrypts the received encrypted data and stores it in the database. The input here is encrypted data, and the output is analyzable raw data. The server maintains data security using SSL / TLS.

[0777] Step 4:

[0778] The server analyzes the data using AI libraries such as TensorFlow and PyTorch. The input is decoded user data, and the output is the health status assessment result. In this step, the server analyzes historical data and city-wide health data together.

[0779] Step 5:

[0780] The server generates personalized health promotion guidelines for users based on the analysis results. The input is the health status assessment, and the output is specific guidance for the user. A generation AI model streamlines this process.

[0781] Step 6:

[0782] The server sends the generated guidelines to the terminal and communicates them to the user via a notification function. The input is the generated guidelines, and the output is the notification on the user's terminal. The terminal uses a push notification service.

[0783] Step 7:

[0784] Based on the guidelines received, users improve their lifestyles and input feedback on what they did and the results they experienced into their device. This feedback is then sent back to the server. In this step, the input is the results of the actions taken, and the output is feedback data.

[0785] Step 8:

[0786] The server analyzes user feedback and uses a generative AI model to incorporate that feedback into future guideline creation. The input is user feedback, and the output is a revised draft of future guidelines. This allows for progressively more accurate advice.

[0787] 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.

[0788] This invention is a system that evaluates a user's health status from multiple perspectives and provides individually optimized health guidelines. In particular, by incorporating an emotion engine, it realizes support that also takes into account the user's emotional state. This system functions in cooperation with the user, terminal, and server.

[0789] First, users record various daily activities, meals, and emotions on the device. This information can be entered in various formats, including text, photos, audio, and video. In addition, voice and facial expression data are analyzed by an emotion engine to collect the user's emotions in real time.

[0790] Next, the terminal centralizes this information and standardizes the data format. The data is encrypted for secure transmission to the server. At this stage, data related to emotions, in particular, is treated as an important element in subsequent analysis.

[0791] The server organizes the data received from the terminal and stores it in a database. Next, an AI algorithm analyzes this data to comprehensively evaluate the user's health and emotional state. By using an emotion engine, the user's psychological state is also examined, and this information can be reflected in the health guidelines provided.

[0792] Subsequently, the server generates an exercise plan and dietary guidelines optimized for the user based on the analysis results, and also creates comprehensive advice that includes mental health support guidelines tailored to the user's emotional state. This advice serves as a concrete guideline for the user to improve their current situation.

[0793] The device notifies the user of advice received from the server. The user then takes action based on this advice and provides feedback to the device regarding the results and their impressions, accumulating feedback data. Based on this feedback, the advice is continuously improved.

[0794] For example, if a user is experiencing emotional stress, the emotion engine detects this state, and the server provides advice, including methods for stress reduction. For instance, it can suggest relaxation techniques such as deep breathing, meditation, or listening to music. Based on user feedback, the server adjusts its next suggestions to be more personalized.

[0795] Thus, the present invention aims to provide an integrated healthcare system that simultaneously supports physical and mental health, thereby improving the quality of life for users.

[0796] The following describes the processing flow.

[0797] Step 1:

[0798] Users input their daily habits, diet, and emotions at the time into the device. In particular, emotional data is recorded through voice input and facial expression capture, and detailed information is collected.

[0799] Step 2:

[0800] The terminal receives diverse data from users and standardizes it according to each data format. The obtained information is integrated and appropriately formatted in preparation for analysis.

[0801] Step 3:

[0802] The device encrypts standardized data and sends it to the server using a secure communication protocol. This process is crucial to ensure data security and privacy.

[0803] Step 4:

[0804] The server receives data sent from the terminal, organizes it in the database, and stores it. Integrated management is performed with historical information, including past data.

[0805] Step 5:

[0806] The server analyzes the accumulated data using AI algorithms and an emotion engine. It comprehensively evaluates the user's health status, behavioral patterns, and emotional state to identify problems and pinpoint areas for improvement.

[0807] Step 6:

[0808] Based on the analysis results, the server generates specific exercise and dietary guidelines for the user. The analysis results from the emotion engine are also incorporated, including advice aimed at stress reduction and emotional care.

[0809] Step 7:

[0810] The server sends the generated health guidelines and emotional care advice to the terminal, enabling rapid information delivery to the user.

[0811] Step 8:

[0812] The terminal notifies the user of guidance information received from the server. This information is appropriately communicated to the user through a visual or auditory interface.

[0813] Step 9:

[0814] Users act based on the guidance and advice they receive, and record the process and results as feedback on their device.

[0815] Step 10:

[0816] The server receives and analyzes feedback sent from the terminal. This allows for continuous improvement of the guidance provided and adaptive adjustments to make future suggestions more personalized.

[0817] Through this series of processing steps, the system provides support for both the user's physical and emotional well-being, and optimizes itself to meet individual needs.

[0818] (Example 2)

[0819] 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".

[0820] In modern society, comprehensively managing an individual's health and psychological state and providing optimized health guidelines is a challenging task. In particular, methods for integrating and analyzing biometric and emotional data to provide personalized advice have not yet been sufficiently realized. This invention aims to provide a system that delivers health and psychological support tailored to each individual.

[0821] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes data collection means for organizing and receiving biometric information and psychological data in a unified format, analysis means for evaluating the user's health and psychological state through analysis, and guideline generation means for generating personalized exercise, diet, and mental health guidelines based on the analysis results. This enables comprehensive support in both health and psychological aspects that meet the individual needs of the user.

[0822]

[0823] A "data collection method" is a system that receives information about biological activity and psychological state from users in various formats and processes it within the system.

[0824] "Data transfer means" includes technologies and protocols for securely encrypting collected information and transmitting it to a server.

[0825] "Analysis means" refers to methods that use data analysis techniques to evaluate received biometric and emotional data in order to understand the user's health and psychological state.

[0826] A "guideline generation means" is a device that has the function of generating specific guidelines and advice for exercise, diet, and mental health that are suitable for the user, based on the analysis results.

[0827] "Communication methods" refer to transmission technologies used to notify users of generated guidelines and advice and to receive feedback.

[0828] "Adjustment mechanisms" refer to systems that dynamically adapt and improve individual health and psychological support advice based on feedback from users.

[0829] An "emotion engine" is a technology that analyzes voice and facial expression data to evaluate the user's emotional state in real time.

[0830] This invention is an information processing system for comprehensively evaluating a user's health and psychological state and providing personalized guidelines. To achieve this, the system mainly consists of a user terminal, a server for data processing, and an engine for analysis. One embodiment of this invention is shown below.

[0831] Hardware and software selection

[0832] The devices are mobile information terminals such as smartphones and tablets, equipped with interfaces for inputting data in various formats (text, images, audio, and video). This allows users to record their daily activities, meals, and emotions.

[0833] The servers are deployed on a cloud platform and possess advanced data processing capabilities. Data is encrypted using AES (Advanced Encryption Standard) and transmitted securely via the HTTPS protocol.

[0834] The analysis engine incorporates machine learning models and includes an emotion engine for performing emotion analysis using voice and facial expression data. These technologies make it possible to evaluate the user's psychological state and reflect this in the generation of guidelines.

[0835] System operating procedures and functions

[0836] Users input their daily experiences through a dedicated application, including details about their diet, exercise, and emotions.

[0837] The device centralizes the collected data, encrypts it, and then securely transmits it to the server.

[0838] The server uses AI algorithms to analyze information stored in the database, evaluate the user's health and emotional state, and generate personalized health guidelines.

[0839] The terminal notifies the user of guidance information from the server and encourages appropriate action. Furthermore, the server continuously improves its advice based on the feedback received.

[0840] Specific example

[0841] For example, if a user is experiencing emotional stress, the emotion engine detects this state, and the server suggests stress reduction methods. Examples of suggested methods include deep breathing, meditation, and listening to music. After the user acts on these suggestions and provides feedback, the system further personalizes the advice.

[0842] Example of a prompt

[0843] The prompt used is "Suggest effective stress reduction methods when the user is experiencing emotional stress." This prompts the server to utilize a generative AI model to generate appropriate advice.

[0844] As described above, the present invention makes it possible to provide users with personalized health and psychological support and improve their quality of life.

[0845] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0846] Step 1:

[0847] Users input their daily activities and emotional states into the device. The input data includes information on meals, exercise records, and emotions, and is provided in text, image, audio, and video formats. This information serves as foundational data for comprehensively understanding the user's daily life.

[0848] Step 2:

[0849] The terminal receives user input data and converts it into a unified format (e.g., JSON format). This unification of data formats allows for efficient handling of data in subsequent processing. Specifically, this includes pre-processing steps such as compressing image data and converting audio data to text.

[0850] Step 3:

[0851] The terminal encrypts the unified data and sends it to the server. Here, AES encryption technology is used, and secure data transfer is performed via the HTTPS protocol. The input is the encryption key, and the output is the encrypted data file.

[0852] Step 4:

[0853] The server decodes the data received from the terminal and stores it in the database. The decoded data is inserted into the corresponding field in the database. The server checks the integrity of the data and logs the information as needed.

[0854] Step 5:

[0855] The server applies AI algorithms to analyze biometric and emotional information in the database. Here, an emotion engine is used to analyze the user's voice and facial expressions to evaluate their psychological state. The input is raw data, and the output is the analysis results and a health assessment score.

[0856] Step 6:

[0857] The server generates personalized exercise, diet, and mental health guidelines based on the analysis results. Using a generation AI model, it creates individual health guidelines according to the prompt text. The output is a set of advice for the user.

[0858] Step 7:

[0859] The device receives guidance information from the server and notifies the user. The notification is sent using the smartphone's push notification function and is presented as specific advice to encourage the user to take action.

[0860] Step 8:

[0861] Users take action based on notifications from their devices and provide feedback on the results and their impressions to the device. This feedback data is used for future analysis and guideline development. The input is the result of the user's actions, and the output is new data that will lead to improvements in future advice.

[0862] Step 9:

[0863] The server analyzes user feedback data and adaptively updates its guidelines based on newly acquired insights. This ensures that personalized advice is continuously provided, promoting ongoing improvements tailored to user needs.

[0864] (Application Example 2)

[0865] 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".

[0866] In recent years, with the advancement of an aging society, the importance of individualized health support and mental health support has increased. However, conventional technologies have faced the challenge of not being able to comprehensively evaluate physical and mental health status and provide optimized guidelines based on that evaluation. There is also the problem of a lack of systems that can provide personalized health guidelines for the elderly. Therefore, the present invention aims to provide a health support system that takes into account not only the user's physical condition but also their emotional state, and to efficiently generate individualized guidelines.

[0867] 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.

[0868] In this invention, the server includes information processing means for receiving information about activities and lifestyles obtained from users; analysis means for analyzing the information about activities and lifestyles and evaluating the user's condition; guideline generation means for providing appropriate exercise and dietary guidelines to the user based on the evaluation; and means for generating mental health support guidelines based on the emotional state obtained from the evaluation. This makes it possible to comprehensively support the physical and mental health of users and provide personalized health support.

[0869] An "information processing device" is a device that centralizes various forms of input information related to activities and daily life received from users and converts the format as needed.

[0870] An "analysis device" is a device that analyzes and evaluates the user's physical health and emotional state based on the received information.

[0871] A "guideline generation device" is a device that automatically generates appropriate exercise, diet, and mental health guidelines for users based on analysis results.

[0872] A "communication device" is a device used to transmit generated guidelines to users and to notify and share information.

[0873] A "modification mechanism" is a device that receives feedback from users and makes adjustments to continuously optimize the guidelines it provides.

[0874] An "emotion engine" is a device or program that analyzes a user's voice and facial expression data to evaluate their emotional state.

[0875] To implement this invention, it is necessary to build a system in which users, terminals, and servers work together. This system evaluates the user's health and emotional state and provides optimal guidance.

[0876] Users record their daily activities, meals, and emotions using their smartphones. Information can be entered in text, photos, audio, and video formats. Emotions, in particular, are analyzed in real-time by an emotion engine using voice and facial recognition. This emotion engine is software designed to analyze emotional states.

[0877] The device centralizes the received data, encrypts it, and transmits it to a cloud server. In particular, emotional data is treated as a crucial element in subsequent analysis. The device is equipped with communication capabilities and plays a role in notifying the user of the generated guidelines in a timely manner.

[0878] The server uses AI algorithms to comprehensively assess health and emotional states by analyzing incoming data. Here, the server utilizes a generated AI model upon request. Specifically, it proposes mental health support measures based on the assessed emotional state. For example, if the emotion engine detects a stressed state, it generates guidelines including relaxation methods.

[0879] The cloud server accumulates the feedback data it receives and continuously adjusts its guidance generation system to make future advice more personalized. This contributes to the user's long-term health improvement.

[0880] For example, if a user records in voice that they are "feeling a little down," the emotion engine will analyze that emotion and suggest relaxation methods using meditation or music. An example of a prompt would be, "If the user says 'worried,' generate personalized advice suggesting relaxation methods (deep breathing, simple exercises, etc.) to alleviate that emotion."

[0881] It is expected that the implementation of such a system will simultaneously support users' physical and emotional well-being, thereby improving their quality of life.

[0882] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0883] Step 1:

[0884] Users input information about their daily activities, meals, and emotions into their smartphones in various formats such as text, photos, audio, and video. This information is analyzed in real time by an emotion engine via voice or facial recognition. The input here is data in various formats, and the output is the analyzed emotional state.

[0885] Step 2:

[0886] The terminal centralizes this input data and standardizes its format. This data is securely transmitted to the cloud server using industry-standard encryption technology. Specifically, image data is converted to JPEG format and audio to WAV format. The output is encrypted data in a transmittable format.

[0887] Step 3:

[0888] The server analyzes the received data. Using AI algorithms, it assesses the user's health and emotional state. Input is standardized data, and output includes exercise plans and dietary guidelines based on health status, and mental health support measures based on emotional state. A generative AI model is used to refer to the user's past data and create specific advice.

[0889] Step 4:

[0890] The server generates optimized guidelines based on the evaluated data and sends them to the terminal. Specifically, it suggests personalized exercise plans and relaxation methods. The output here consists of individual health guidelines and mental health support measures.

[0891] Step 5:

[0892] The device notifies the user of guidelines received from the server. These notifications are delivered via pop-up messages or in-app notifications. The output is advice information displayed in a user-recognizable format.

[0893] Step 6:

[0894] The user takes action based on the advice provided and then provides feedback on the results and their impressions back to the device. The input is the user's feedback or additional information, and the output is adjusted health guidelines.

[0895] Step 7:

[0896] The server adjusts its guidelines based on user feedback. It evaluates the effectiveness of previous advice and incorporates it into future guidelines. Specifically, it stores feedback data in a database and uses an AI algorithm to generate the next set of guidelines. This enables more personalized suggestions.

[0897] 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.

[0898] 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.

[0899] 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.

[0900] 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.

[0901] 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.

[0902] 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.

[0903] 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.

[0904] 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.

[0905] 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."

[0906] 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.

[0907] 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.

[0908] 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.

[0909] 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.

[0910] 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.

[0911] 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.

[0912] 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.

[0913] 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.

[0914] 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.

[0915] 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.

[0916] 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.

[0917] 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 to be incorporated by reference.

[0918] The following is further disclosed regarding the embodiments described above.

[0919] (Claim 1)

[0920] Information processing means for receiving information about activities and daily life obtained from users,

[0921] An analytical means for analyzing information related to the aforementioned activities and lifestyle and evaluating the user's condition,

[0922] Based on the aforementioned evaluation, a guideline generation means for providing users with appropriate exercise and dietary guidelines,

[0923] A means of communication for conveying the aforementioned guidelines to users,

[0924] An adjustment means for adaptively adjusting the guidelines based on responses to the guidelines obtained from users,

[0925] A system that includes this.

[0926] (Claim 2)

[0927] The system according to claim 1, wherein the analysis means comprises means for evaluating the user's stress and sleep patterns and generating appropriate relaxation methods and sleep improvement measures.

[0928] (Claim 3)

[0929] The system according to claim 1, wherein the information processing means comprises means for receiving information in text format, image format, audio format and video format.

[0930] "Example 1"

[0931] (Claim 1)

[0932] A data processing means that receives information about activities and daily life from users and handles the data in multiple information formats,

[0933] An analytical means for analyzing information on the aforementioned activities and lifestyle, and for using a generative AI model to evaluate the user's health status and behavioral patterns in detail,

[0934] Based on the aforementioned evaluation, a guideline generation means generates personalized exercise and dietary guidelines for the user,

[0935] A means of communication for conveying the aforementioned guidelines to users and collecting user feedback,

[0936] Based on feedback obtained from users, the aforementioned guidelines are adaptively adjusted to improve the accuracy of future proposals, and adjustment means are provided.

[0937] A system that includes this.

[0938] (Claim 2)

[0939] The system according to claim 1, wherein the analysis means comprises means for evaluating the user's stress and sleep patterns and generating relaxation methods and sleep improvement measures using a generated AI model.

[0940] (Claim 3)

[0941] The system according to claim 1, wherein the data processing means comprises means for receiving information in various formats, including text, image, audio, and video.

[0942] "Application Example 1"

[0943] (Claim 1)

[0944] Information processing means for receiving information about activities and daily life obtained from users,

[0945] An analytical means for analyzing information related to the aforementioned activities and lifestyle and evaluating the user's condition,

[0946] Based on the aforementioned evaluation, a guideline generation means for providing users with appropriate exercise and dietary guidelines,

[0947] A means of communication for conveying the aforementioned guidelines to users,

[0948] An adjustment means for adaptively adjusting the guidelines based on responses to the guidelines obtained from users,

[0949] A means of analyzing health data across the entire city and providing health promotion guidelines to individual users based on the results,

[0950] A system that includes this.

[0951] (Claim 2)

[0952] The system according to claim 1, wherein the analysis means comprises means for evaluating the user's stress and sleep patterns and generating appropriate relaxation methods and sleep improvement measures.

[0953] (Claim 3)

[0954] The system according to claim 1, wherein the information processing means comprises means for receiving information in text format, image format, audio format and video format.

[0955] "Example 2 of combining an emotion engine"

[0956] (Claim 1)

[0957] A data collection method for receiving information on biological activity and psychological state obtained from users,

[0958] A data transfer means for organizing the aforementioned information into a unified format, encrypting it, and transmitting it,

[0959] An analytical means for analyzing biometric information and emotional data to evaluate the user's health and psychological state,

[0960] A guideline generation means for generating personalized exercise, diet, and mental health guidelines based on the analysis results,

[0961] A means of communication for notifying users of the generated guidelines,

[0962] A means of adaptively adjusting the guidelines based on feedback obtained from users,

[0963] A system that includes this.

[0964] (Claim 2)

[0965] The system according to claim 1, wherein the analysis means comprises means for examining the user's psychological state using an emotion engine and providing appropriate stress reduction methods and measures to improve mental health.

[0966] (Claim 3)

[0967] The system according to claim 1, wherein the data collection means has the function of receiving information in text, image, audio, and video formats.

[0968] "Application example 2 when combining with an emotional engine"

[0969] (Claim 1)

[0970] Information processing means for receiving information about activities and daily life obtained from users,

[0971] An analytical means for analyzing information related to the aforementioned activities and lifestyle and evaluating the user's condition,

[0972] Based on the aforementioned evaluation, a guideline generation means for providing users with appropriate exercise and dietary guidelines,

[0973] A means of generating mental health support guidelines based on the emotional state obtained through evaluation,

[0974] A means of communication for conveying the aforementioned guidelines to users,

[0975] An adjustment means for adaptively adjusting the guidelines based on responses to the guidelines obtained from users,

[0976] A system that includes this.

[0977] (Claim 2)

[0978] The system according to claim 1, wherein the analysis means comprises means for evaluating the user's stress and sleep patterns and generating appropriate relaxation methods and sleep improvement measures, and further presents specific relaxation methods for alleviating emotions based on the evaluated emotional state.

[0979] (Claim 3)

[0980] The system according to claim 1, wherein the information processing means includes means for receiving information in text format, image format, audio and video format, and analyzing the emotional state in real time using an emotion engine. [Explanation of symbols]

[0981] 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. Information processing means for receiving information about activities and daily life obtained from users, An analytical means for analyzing information related to the aforementioned activities and lifestyle and evaluating the user's condition, Based on the aforementioned evaluation, a guideline generation means for providing users with appropriate exercise and dietary guidelines, A means of communication for conveying the aforementioned guidelines to users, An adjustment means for adaptively adjusting the guidelines based on responses to the guidelines obtained from users, A means of analyzing health data across the entire city and providing health promotion guidelines to individual users based on the results, A system that includes this.

2. The system according to claim 1, wherein the analysis means comprises means for evaluating the user's stress and sleep patterns and generating appropriate relaxation methods and sleep improvement measures.

3. The system according to claim 1, wherein the information processing means comprises means for receiving information in text format, image format, audio format and video format.

Images