system

Abstract

We provide the system. [Solution] A means for acquiring user eye-tracking data, An evaluation means for analyzing the aforementioned gaze data and evaluating the user's posture and usage time, Based on the above evaluation, an output means for providing alerts to the user, An environmental monitoring system that photographs the user's environment and monitors their posture, The aforementioned environmental monitoring means analyzes the information obtained and proposes healthy activities, and the activity proposal means proposes healthy activities. A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern society, due to the spread of information receiving terminals, the cases where users use terminals for a long time are increasing. Such long-term use is likely to cause deterioration of posture, eye fatigue, and associated health damage. However, since the current system lacks an effective approach to prevent these health damages, self-management by the user is required. Therefore, there is a need for technical means that can monitor the user's posture and usage status in real time during terminal use and promote effective improvement.

Means for Solving the Problems

[0005] This invention solves the above-mentioned problems by acquiring user gaze data in real time using sensor means, and by having an analysis device, which is an evaluation means, analyze the user's posture and usage time based on that data. Based on the analysis results, appropriate alerts are provided to the user by a display means, automatically prompting improvement of unbalanced posture and prolonged use. This makes it possible for the user to prevent health problems. The image acquisition device used in this system acts as a sensor means for gaze data, and the artificial intelligence model is used as an evaluation means for gaze data analysis.

[0006] A "sensor" is a device used to acquire data such as the user's gaze and posture in real time.

[0007] "Evaluation means" refers to devices or programs that have the function of analyzing acquired data and evaluating the user's attitude and usage.

[0008] A "display means" is a device or program that has the function of providing alerts or messages to the user based on the results obtained by the evaluation means.

[0009] "Eye-gaze data" refers to information that includes the user's eye movements, direction of gaze, and duration of fixed gaze.

[0010] An "image acquisition device" is a machine that uses equipment such as a camera to acquire user gaze data.

[0011] An "artificial intelligence model" is a program built using machine learning or deep learning algorithms to analyze data.

[0012] An "alert" is a notification or warning message designed to draw attention to a user's needs and encourage them to improve their behavior. [Brief explanation of the drawing]

[0013] [Figure 1]This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

[0014] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0015] First, the terms used in the following description will be explained.

[0016] In the following embodiments, the labeled 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.

[0017] In the following embodiments, the labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0018] In the following embodiments, the labeled 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, etc.

[0019] In the following embodiments, the labeled communication I / F (Interface) is an interface including a communication processor and an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark), etc.

[0020] 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."

[0021] [First Embodiment]

[0022] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0023] 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.

[0024] 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).

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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.

[0029] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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".

[0034] This invention is a system for supporting healthy device use by users. The system aims to monitor the user's posture and usage time while using the device and provide appropriate alerts. It mainly includes the following components:

[0035] First, the device has a built-in front-facing camera that serves as a sensor for acquiring eye-tracking data. The front-facing camera captures the user's facial movements in real time and measures the angle of their gaze and the distance from the screen. This data forms the basis for evaluating whether the user is using the smartphone appropriately.

[0036] Next, the device is equipped with an evaluation means for analyzing the collected data. In one embodiment, an artificial intelligence model is used for this evaluation means. The AI ​​compares the user's gaze data with pre-set criteria (e.g., the appropriate angle of gaze and the upper limit of usage time) to detect whether the user is in an inappropriate posture or using the device for an extended period.

[0037] The analysis results are directly passed to the display device. The display device then issues an alert to the user based on the evaluation results. The alert is displayed on the device screen as a visual notification. For example, messages such as "Take a 5-minute break" or "Improve your posture" are presented in a way that allows the user to notice the alert.

[0038] As a concrete example, consider a scenario where a user is watching a video on their device. The device's front camera continuously monitors the user's gaze, and AI evaluates the data. If the user's gaze deviates from a certain angle for two minutes, the display will notify them with a message such as, "Please straighten your posture." By providing interactive, real-time feedback in this way, users can prevent unhealthy device use and maintain their health.

[0039] The following describes the processing flow.

[0040] Step 1:

[0041] The device activates its front camera and captures the user's face and eye position in real time. Through image processing, it measures the angle of gaze and the distance to the screen, collecting gaze data.

[0042] Step 2:

[0043] The device transmits the eye-tracking data it collects to an evaluation system. The evaluation system includes an artificial intelligence model that compares the angle of gaze and the distance to the screen with reference values ​​to evaluate the user's posture and usage in real time.

[0044] Step 3:

[0045] Based on the analysis results from the evaluation method, the terminal makes a decision. If the user's posture is inappropriate or if the terminal is used continuously for a certain period of time, it generates the necessary alerts.

[0046] Step 4:

[0047] The device notifies the user of the generated alert message via a display device. The user is presented with a visual warning on the device screen, such as "Please correct your posture" or "We recommend taking a 5-minute break."

[0048] Step 5:

[0049] The system improves behavior based on alerts received by the user. The user checks the displayed message and adjusts their posture or temporarily stops using the device.

[0050] Step 6:

[0051] The device accumulates user responses and alert history, and stores this information in a database. Later, the device can use this history to provide feedback to the user.

[0052] (Example 1)

[0053] 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."

[0054] In modern times, it is common for individuals to use electronic devices for extended periods, but improper posture and excessive use can have adverse effects on health. Conventional systems face the challenge of effectively monitoring this and providing real-time feedback.

[0055] 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.

[0056] In this invention, the server includes a sensing device for acquiring the user's gaze direction and distance information, an analysis device for analyzing the gaze direction and distance information and evaluating the user's posture and usage duration, and a display device for providing visual notifications to the user based on the evaluation. This promotes healthy terminal use by the user and enables real-time feedback.

[0057] A "sensing device" is a device used to acquire information about the user's line of sight and distance.

[0058] An "analysis device" is a device that analyzes acquired gaze direction and distance information to evaluate the user's posture and duration of use.

[0059] A "display device" is a device that provides visual notifications to the user based on the analysis results.

[0060] "Communication means" refers to the means of implementing a communication process to provide real-time feedback.

[0061] "Eyewitness direction and distance information" refers to information about the direction in which the user's gaze is directed and the physical distance between the user and the device.

[0062] "Real-time feedback" refers to the immediate evaluation of the user's status and the prompt provision of appropriate notifications.

[0063] This invention is a system for monitoring a user's posture and usage duration when using electronic devices, and for supporting healthy device use. The system is configured as follows:

[0064] First, the device has a built-in video capture device (e.g., front camera) as a sensing device to acquire information about the user's gaze direction and distance. This sensing device tracks the position of the user's eyes based on facial recognition technology and measures the angle of their gaze and the distance from the device in real time.

[0065] Next, the device processes this gaze information using an internally installed analysis device. This analysis device implements a generated algorithm (e.g., an artificial intelligence model) and compares the user's gaze information with pre-set criteria (e.g., gaze angle, usage time limit). This determines whether the user's posture is inappropriate or whether the device has been used for an extended period.

[0066] The analysis results are fed back to the user through a display device. Specifically, based on the evaluation results, visual notifications such as "Please correct your posture" or "Please take a 5-minute break" are displayed on the device screen. These notifications are immediate and help users prevent unhealthy device use.

[0067] As a concrete example, consider a case where a user is watching a movie on their device. If their gaze remains outside the proper range for two minutes, the device immediately displays a notification saying, "Please correct your posture." This feedback makes it easier for the user to maintain good health.

[0068] An example of a prompt is: "Generate an alert message to notify the user if they use the device for an extended period and their gaze deviates from the correct angle." This prompt is input into the AI ​​model and provides instructions that serve as a basis for evaluating the user's condition.

[0069] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0070] Step 1:

[0071] The terminal uses a built-in video capture device as a sensing device to acquire information on the direction and distance of the user's gaze. Specifically, it recognizes the user's face and tracks the position of their eyes to measure the angle of their gaze and the distance to the terminal. The input for this step is video data, and the output is information on the angle of gaze and distance.

[0072] Step 2:

[0073] The terminal inputs the acquired gaze direction and distance information into an analysis device. This analysis device processes the data using a generated AI model. The AI ​​model compares the gaze information to pre-set criteria and evaluates the user's posture and usage time. The input for this step is gaze direction and distance information, and the output is the evaluation results of posture and usage duration. Specifically, the AI ​​model determines whether the user's gaze angle is within an appropriate range and whether the usage time exceeds a set limit.

[0074] Step 3:

[0075] The device provides feedback to the user through a display device, specifically by displaying visual notifications on the device's screen. These notifications may include messages such as "Please straighten your posture" or "Please take a 5-minute break." The input for this step is the evaluation result, and the output is the visual notification to the user. Specifically, the notification message is intended to pop up on the screen so that the user will notice it.

[0076] Step 4:

[0077] The user receives notifications from the device and modifies their actions based on them. The input is the notification message, and the output is the user's actions, such as improving posture or starting a rest. Specifically, the user is expected to follow the instructions from the device, readjust their posture, and take short breaks as needed.

[0078] (Application Example 1)

[0079] 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."

[0080] In modern society, prolonged use of electronic devices raises concerns about poor posture and health effects on users. This invention aims to support healthy device use by monitoring the user's posture in real time and providing appropriate feedback.

[0081] 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.

[0082] In this invention, the server includes sensor means for acquiring user gaze data, evaluation means for analyzing the gaze data and evaluating the user's posture and usage time, and output means for providing alerts to the user based on the evaluation. This makes it possible to suggest appropriate posture improvements and rest times to the user.

[0083] A "user" is a person who uses this system and is the target of support in maintaining healthy posture and lifestyle habits.

[0084] "Eye-gaze data" refers to information about the position and movement of a user's gaze, and is acquired from sensors such as the front camera.

[0085] "Sensing means" is a general term for devices and technologies that acquire eye-tracking data and environmental information.

[0086] "Evaluation means" refers to functions or devices used to analyze user posture and device usage based on acquired data.

[0087] "Output means" refers to interfaces such as screen displays or audio output used to notify the user of the evaluation results.

[0088] An "environmental monitoring device" is a device that photographs and records the user's surrounding environment and activities, and acquires information to support healthy posture and activities.

[0089] An "activity suggestion tool" is a function or device that evaluates the user's activity level and suggests appropriate actions for maintaining health.

[0090] A "machine learning model" is an artificial intelligence technology that learns from large amounts of data and analyzes eye-tracking and posture data.

[0091] Modes for carrying out the invention

[0092] In this embodiment, a system is constructed to support users in using the terminal in a healthy manner. The system includes sensor means for acquiring user gaze data, evaluation means for analyzing and evaluating gaze data, output means for providing alerts to the user based on the evaluation results, environmental monitoring means for monitoring the environment, and activity suggestion means for suggesting activities.

[0093] Program Processing Description

[0094] The server uses a Python program to acquire gaze data from the camera installed in the terminal. It processes the acquired video using the OpenCV library to extract user gaze and posture information. Machine learning models such as TENSORFLOW® are used to analyze this data and determine whether the posture is healthy or if the device is being used for extended periods.

[0095] The analysis results are communicated to the user as visual or audio alerts via the device's display or speaker. These alerts may include messages such as "Improve your posture" or "Take a 30-minute break."

[0096] For example, if a user tends to sit for long periods while watching television, this system uses environmental monitoring to detect the user's sitting position and suggests posture improvements or breaks. The generative AI model evaluates the user's condition in real time and provides feedback to help maintain healthier lifestyle habits.

[0097] Example of a prompt:

[0098] "Generate a message suggesting healthy activities to users who have been sitting for more than 30 minutes."

[0099] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0100] Step 1:

[0101] The server acquires gaze data from the camera installed in the terminal. The camera captures the user's face and posture and transmits the video data to the server in real time. The input is video data, and the output is raw gaze information.

[0102] Step 2:

[0103] The server preprocesses the acquired video data using the OpenCV library to detect the user's facial movements and gaze position. By performing face detection and feature point extraction to obtain gaze data, it understands how the user is using the device. The input is raw gaze video data, and the output is gaze position information and gaze angle information.

[0104] Step 3:

[0105] The server analyzes gaze data using machine learning models such as TensorFlow. Based on gaze position, angle, and usage time, it determines whether the user's posture is healthy or if they are using the device for an extended period. The input is gaze position information and gaze angle information, and the output is evaluation results and analysis data.

[0106] Step 4:

[0107] The device outputs alerts to the user based on the evaluation results obtained. If the evaluation results exceed the standard, it displays messages such as "Please correct your posture" or "Take a 30-minute break" as visual or audio alerts. The input is the evaluation result, and the output is the alert message.

[0108] Step 5:

[0109] The server utilizes environmental monitoring tools to continuously monitor the user's surroundings and activity status. It acquires environmental information and uses it as foundational data to analyze the user's activity patterns and provide health-conscious suggestions. The input is environmental information, and the output is user activity status data.

[0110] Step 6:

[0111] The server uses an activity suggestion mechanism to propose healthy activities to the user based on predetermined criteria. The suggestions are automatically generated using a generative AI model, selecting the most suitable action for the user's current state. The input is the user's activity status data, and the output is the suggested activity message.

[0112] 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.

[0113] This invention proposes a system that recognizes a user's eye-tracking data and emotional state, and provides appropriate feedback based on this data. This system takes into account not only the user's posture and usage time when using the device, but also their emotional state, enabling more personalized support.

[0114] This system includes the following main components:

[0115] First, the device is equipped with an in-camera, which serves as a sensor to acquire user gaze data. The in-camera has the function of detecting the user's face and measuring the direction and distance of their gaze.

[0116] Next, the evaluation method includes an artificial intelligence model that performs analysis based on gaze data as well as emotional data output by an emotion engine. The emotion engine has the function of analyzing facial expression data acquired from the front camera and estimating the user's emotional state (e.g., fatigue, stress). This ensures that not only the user's physical state but also their mental state is reflected in the evaluation.

[0117] Based on the analysis results, the device's display system provides the user with alerts and support messages. The display system takes the user's emotional state into consideration and displays customized messages tailored to the user's condition, such as "Take a short break and refresh yourself" or "Try some deep breathing to relax."

[0118] As a concrete example, consider a situation where a user is working on a device for an extended period of time. The front camera captures eye-tracking and facial expression data, and the evaluation system analyzes this data to determine that the user is in a hunched-over posture and is experiencing stress based on their facial expression. Based on these results, the device sends an alert to the user, such as, "Take a 5-minute break and try to relax."

[0119] In summary, the present invention provides an innovative system that supports users in maintaining both physical and mental health.

[0120] The following describes the processing flow.

[0121] Step 1:

[0122] The device activates its front camera and captures the user's face in real time. Using a face detection algorithm, it measures the direction of gaze and the distance to the screen, and acquires facial expression data.

[0123] Step 2:

[0124] The device collects eye-tracking and facial expression data and transmits it to an evaluation system. The evaluation system includes an artificial intelligence model and an emotion engine, which begin analysis after receiving the data.

[0125] Step 3:

[0126] The AI ​​model used for evaluation analyzes eye-tracking data to assess the user's posture and usage time. The emotion engine analyzes facial expression data to estimate the user's emotional state.

[0127] Step 4:

[0128] Based on the analysis results, the device comprehensively assesses the user's physical and emotional state. For example, if the posture is inappropriate and the emotional engine indicates a stressed state, it will determine that a warning is necessary.

[0129] Step 5:

[0130] The device generates customized alerts based on its own judgment. It prepares messages adapted to the user's emotional and physical state through display means.

[0131] Step 6:

[0132] The device displays alerts to the user. For example, it might display, "Your neck is strained from prolonged use. Please stretch," prompting the user to take specific actions to improve their behavior.

[0133] Step 7:

[0134] Users check alerts and adjust their actions based on the messages presented. Their responses can help raise awareness of maintaining good health.

[0135] Step 8:

[0136] The device records user responses and alert history, saving it to a database. This data will be used for future feedback and system improvements.

[0137] (Example 2)

[0138] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0139] Conventional technologies have made it difficult to comprehensively evaluate and individually address the physical burden and mental stress experienced by users while using devices. As a result, users often neglected to consider their health and experienced physical and mental strain due to inappropriate postures and prolonged use. Therefore, the present invention aims to support users in maintaining their health by more precisely evaluating their physical and mental state based on their gaze and facial expression data and providing appropriate feedback.

[0140] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0141] In this invention, the server includes measurement means for acquiring user eye-gaze data and facial expression data; analysis means for analyzing the eye-gaze data and facial expression data and evaluating the user's posture, usage time, and emotional state; and notification means for providing the user with customized alerts and support messages based on the evaluation. This makes it possible to monitor the user's health status in real time while they are using the device and to quickly provide appropriate alerts and support.

[0142] "Measurement means" refers to a function consisting of a device or sensor for acquiring user gaze data and facial expression data.

[0143] The "analysis means" refers to a function that uses acquired gaze data and facial expression data to evaluate the user's posture, usage time, and emotional state.

[0144] "Notification means" refers to a device or function that provides users with customized alerts or support messages based on evaluation results from analysis means.

[0145] An "optical image acquisition device" is an optical device, including in-cameras and webcams, used to acquire gaze data and facial expression data.

[0146] A "generative AI model" is a model that utilizes artificial intelligence technology to estimate a user's state by analyzing large amounts of data and learning specific patterns.

[0147] The system according to the present invention is a mechanism that collects and analyzes the user's gaze data and facial expression data to provide appropriate feedback to the user.

[0148] First, the device is equipped with an in-camera, which acts as an optical device to acquire the user's gaze data and facial expression data. The in-camera captures the user's eye movements and facial features in real time. This data is temporarily processed on the device and then transmitted to a server via the internet.

[0149] The server uses received eye-tracking and facial expression data to analyze the user's state using a generative AI model. The analysis results include the user's posture, an evaluation of device usage time, and emotional state derived from facial expressions. This generative AI model is trained on a wealth of case studies, enabling highly accurate predictions.

[0150] Once the analysis is complete, the server generates feedback based on the analysis results and sends it to the device. Based on this feedback, the device notifies the user with customized alerts and support messages. For example, if the user has been in the same position for a long time, it might display a message such as, "Take a short break, stand up and stretch."

[0151] For example, if it is suspected that a user is fatigued from continuous computer work, the prompts for the generative AI model might include phrases like, "Which data should be prioritized in order to predict that the user is fatigued?" or "Please tell me an effective way to provide feedback to reduce user stress."

[0152] In this way, users are supported in maintaining their physical and mental health while using the device. The system of the present invention can firmly support the user's comfort and health in everyday device use.

[0153] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0154] Step 1:

[0155] The device uses its front camera to acquire user gaze and facial expression data in real time. Input is the user's face and eye movements, while output is numerical data regarding gaze direction, eye opening / closing status, and facial expression. This data is used as fundamental information to understand the user's current state.

[0156] Step 2:

[0157] The terminal temporarily stores the acquired gaze and facial expression data and transmits it to the server via the internet. The input is the data captured within the terminal, and the output is the data transfer to the server. This process aggregates the data on the server in a format that can be analyzed.

[0158] Step 3:

[0159] The server utilizes a generative AI model to analyze the received gaze and facial expression data. The input is gaze and facial expression data, and the output is a quantitative evaluation of the user's posture, usage time, and emotional state. Specifically, the AI ​​model estimates the user's state from gaze focus patterns and changes in facial expression.

[0160] Step 4:

[0161] The server generates feedback messages for the user based on the analysis results. The input is the user's evaluation result, and the output is a customized message to promote the user's health. For example, if shoulder stiffness due to prolonged work is predicted, a message such as "Take a break and move your shoulders" will be generated.

[0162] Step 5:

[0163] The device receives feedback sent from the server and notifies the user. The input is the feedback message from the server, and the output is the information displayed on the screen. This process allows the user to receive specific advice about their health status.

[0164] (Application Example 2)

[0165] 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".

[0166] In modern society, users often experience physical and mental strain due to long hours of work and daily stress. Given the lack of available support systems in these situations, there is a need for means to adequately support users' health. Furthermore, providing appropriate feedback tailored to users' emotional states is a challenge in order to improve their quality of life.

[0167] 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.

[0168] In this invention, the server includes sensor means for acquiring user gaze data, evaluation means for analyzing the gaze data and evaluating the user's posture and usage time, and emotion analysis means for estimating the user's emotional state and generating a message corresponding to that state. This makes it possible to provide customized feedback that takes into account the user's physical and mental health.

[0169] A "user" refers to an individual who uses the system, and their eye-tracking data and emotional state are the subjects of evaluation.

[0170] "Eye-gaze data" refers to data that includes information about the user's eye movements and points of fixation, and is acquired by sensor devices.

[0171] A "sensor means" is a device for acquiring user gaze data, and it primarily functions using an image acquisition device.

[0172] An "image acquisition device" refers to a device used to obtain user gaze data, such as a camera.

[0173] "Evaluation means" refers to a device or method that analyzes acquired eye-tracking data to evaluate the user's posture and usage time.

[0174] An "artificial intelligence model" refers to a set of programs or algorithms used to analyze eye-tracking data and other information, enabling advanced analysis.

[0175] "Emotional state" refers to information that indicates the user's mental state, representing the user's emotions estimated from facial expression data.

[0176] "Emotional analysis means" refers to a device or method for estimating a user's emotional state and generating an appropriate message based on that information.

[0177] "Information provision means" refers to means of conveying messages generated based on analyzed data to the user, and includes audio and screen displays.

[0178] The system for implementing this invention is configured to provide users with feedback to support their physical and mental health using a household robot. The system is equipped with a camera as a sensor for acquiring gaze data, thereby capturing the user's gaze and facial expressions. Specific hardware examples include consumer robots equipped with cameras.

[0179] Data acquired by the sensor is analyzed by an evaluation system inside the robot. This evaluation system is programmed using Python and utilizes image processing libraries such as OpenCV and emotion analysis libraries (e.g., fer) to estimate the user's emotional state. This allows the robot to analyze the user's gaze data and facial expression data to understand the user's posture, fatigue level, and stress level.

[0180] Based on the user's emotional state, a generative AI model is used to provide appropriate feedback to the user. Specific means of providing this information include messages displayed on the screen and voice guidance. These methods generate and deliver messages that suggest measures to help the user relax.

[0181] For example, if a robot detects a user's face and recognizes fatigue after prolonged work, the robot will provide a message via voice or display saying, "I suggest a tea break. Why not refresh yourself?" In a generative AI model, a prompt such as the following might be used: "Use facial expression data that may indicate the user is tired to generate a message suggesting actions to relax."

[0182] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0183] Step 1:

[0184] The device uses a camera as a sensor to capture the user's face and acquire gaze and facial expression data. This input data is saved in image file format.

[0185] Step 2:

[0186] The device preprocesses the acquired image data using the OpenCV library to extract facial feature points. This process removes noise and identifies facial regions, outputting data in a format suitable for analysis.

[0187] Step 3:

[0188] The device inputs pre-processed data into a sentiment analysis library (e.g., fer) to estimate the emotional state. This data calculation outputs an estimated value of the emotion the user is expressing (e.g., joy, anger, sadness, fatigue).

[0189] Step 4:

[0190] The device uses a generative AI model to generate feedback messages based on emotional states. As input, it forms prompt sentences based on estimated emotional data. This generation process outputs messages that suggest specific actions for the user.

[0191] Step 5:

[0192] The device delivers generated messages to the user through its display or speaker. This action provides specific feedback and suggestions tailored to the user's state.

[0193] 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.

[0194] 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.

[0195] 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.

[0196] [Second Embodiment]

[0197] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0198] 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.

[0199] 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).

[0200] 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.

[0201] 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.

[0202] 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).

[0203] 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.

[0204] 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.

[0205] 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.

[0206] 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.

[0207] 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.

[0208] 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".

[0209] This invention is a system for supporting healthy device use by users. The system aims to monitor the user's posture and usage time while using the device and provide appropriate alerts. It mainly includes the following components:

[0210] First, the device has a built-in front-facing camera that serves as a sensor for acquiring eye-tracking data. The front-facing camera captures the user's facial movements in real time and measures the angle of their gaze and the distance from the screen. This data forms the basis for evaluating whether the user is using the smartphone appropriately.

[0211] Next, the device is equipped with an evaluation means for analyzing the collected data. In one embodiment, an artificial intelligence model is used for this evaluation means. The AI ​​compares the user's gaze data with pre-set criteria (e.g., the appropriate angle of gaze and the upper limit of usage time) to detect whether the user is in an inappropriate posture or using the device for an extended period.

[0212] The analysis results are directly passed to the display device. The display device then issues an alert to the user based on the evaluation results. The alert is displayed on the device screen as a visual notification. For example, messages such as "Take a 5-minute break" or "Improve your posture" are presented in a way that allows the user to notice the alert.

[0213] As a concrete example, consider a scenario where a user is watching a video on their device. The device's front camera continuously monitors the user's gaze, and AI evaluates the data. If the user's gaze deviates from a certain angle for two minutes, the display will notify them with a message such as, "Please straighten your posture." By providing interactive, real-time feedback in this way, users can prevent unhealthy device use and maintain their health.

[0214] The following describes the processing flow.

[0215] Step 1:

[0216] The device activates its front camera and captures the user's face and eye position in real time. Through image processing, it measures the angle of gaze and the distance to the screen, collecting gaze data.

[0217] Step 2:

[0218] The device transmits the eye-tracking data it collects to an evaluation system. The evaluation system includes an artificial intelligence model that compares the angle of gaze and the distance to the screen with reference values ​​to evaluate the user's posture and usage in real time.

[0219] Step 3:

[0220] Based on the analysis results from the evaluation method, the terminal makes a decision. If the user's posture is inappropriate or if the terminal is used continuously for a certain period of time, it generates the necessary alerts.

[0221] Step 4:

[0222] The device notifies the user of the generated alert message via a display device. The user is presented with a visual warning on the device screen, such as "Please correct your posture" or "We recommend taking a 5-minute break."

[0223] Step 5:

[0224] The system improves behavior based on alerts received by the user. The user checks the displayed message and adjusts their posture or temporarily stops using the device.

[0225] Step 6:

[0226] The device accumulates user responses and alert history, and stores this information in a database. Later, the device can use this history to provide feedback to the user.

[0227] (Example 1)

[0228] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0229] In modern times, it is common for individuals to use electronic devices for extended periods, but improper posture and excessive use can have adverse effects on health. Conventional systems face the challenge of effectively monitoring this and providing real-time feedback.

[0230] 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.

[0231] In this invention, the server includes a sensing device for acquiring the user's gaze direction and distance information, an analysis device for analyzing the gaze direction and distance information and evaluating the user's posture and usage duration, and a display device for providing visual notifications to the user based on the evaluation. This promotes healthy terminal use by the user and enables real-time feedback.

[0232] A "sensing device" is a device used to acquire information about the user's line of sight and distance.

[0233] An "analysis device" is a device that analyzes acquired gaze direction and distance information to evaluate the user's posture and duration of use.

[0234] A "display device" is a device that provides visual notifications to the user based on the analysis results.

[0235] "Communication means" refers to the means of implementing a communication process to provide real-time feedback.

[0236] "Eyewitness direction and distance information" refers to information about the direction in which the user's gaze is directed and the physical distance between the user and the device.

[0237] "Real-time feedback" refers to the immediate evaluation of the user's status and the prompt provision of appropriate notifications.

[0238] This invention is a system for monitoring a user's posture and usage duration when using electronic devices, and for supporting healthy device use. The system is configured as follows:

[0239] First, the device has a built-in video capture device (e.g., front camera) as a sensing device to acquire information about the user's gaze direction and distance. This sensing device tracks the position of the user's eyes based on facial recognition technology and measures the angle of their gaze and the distance from the device in real time.

[0240] Next, the device processes this gaze information using an internally installed analysis device. This analysis device implements a generated algorithm (e.g., an artificial intelligence model) and compares the user's gaze information with pre-set criteria (e.g., gaze angle, usage time limit). This determines whether the user's posture is inappropriate or whether the device has been used for an extended period.

[0241] The analysis results are fed back to the user through a display device. Specifically, based on the evaluation results, visual notifications such as "Please correct your posture" or "Please take a 5-minute break" are displayed on the device screen. These notifications are immediate and help users prevent unhealthy device use.

[0242] As a concrete example, consider a case where a user is watching a movie on their device. If their gaze remains outside the proper range for two minutes, the device immediately displays a notification saying, "Please correct your posture." This feedback makes it easier for the user to maintain good health.

[0243] An example of a prompt is: "Generate an alert message to notify the user if they use the device for an extended period and their gaze deviates from the correct angle." This prompt is input into the AI ​​model and provides instructions that serve as a basis for evaluating the user's condition.

[0244] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0245] Step 1:

[0246] The terminal uses a built-in video capture device as a sensing device to acquire information on the direction and distance of the user's gaze. Specifically, it recognizes the user's face and tracks the position of their eyes to measure the angle of their gaze and the distance to the terminal. The input for this step is video data, and the output is information on the angle of gaze and distance.

[0247] Step 2:

[0248] The terminal inputs the acquired gaze direction and distance information into an analysis device. This analysis device processes the data using a generated AI model. The AI ​​model compares the gaze information to pre-set criteria and evaluates the user's posture and usage time. The input for this step is gaze direction and distance information, and the output is the evaluation results of posture and usage duration. Specifically, the AI ​​model determines whether the user's gaze angle is within an appropriate range and whether the usage time exceeds a set limit.

[0249] Step 3:

[0250] The device provides feedback to the user through a display device, specifically by displaying visual notifications on the device's screen. These notifications may include messages such as "Please straighten your posture" or "Please take a 5-minute break." The input for this step is the evaluation result, and the output is the visual notification to the user. Specifically, the notification message is intended to pop up on the screen so that the user will notice it.

[0251] Step 4:

[0252] The user receives notifications from the device and modifies their actions based on them. The input is the notification message, and the output is the user's actions, such as improving posture or starting a rest. Specifically, the user is expected to follow the instructions from the device, readjust their posture, and take short breaks as needed.

[0253] (Application Example 1)

[0254] 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."

[0255] In modern society, prolonged use of electronic devices raises concerns about poor posture and health effects on users. This invention aims to support healthy device use by monitoring the user's posture in real time and providing appropriate feedback.

[0256] 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.

[0257] In this invention, the server includes sensor means for acquiring user gaze data, evaluation means for analyzing the gaze data and evaluating the user's posture and usage time, and output means for providing alerts to the user based on the evaluation. This makes it possible to suggest appropriate posture improvements and rest times to the user.

[0258] A "user" is a person who uses this system and is the target of support in maintaining healthy posture and lifestyle habits.

[0259] "Eye-gaze data" refers to information about the position and movement of a user's gaze, and is acquired from sensors such as the front camera.

[0260] "Sensing means" is a general term for devices and technologies that acquire eye-tracking data and environmental information.

[0261] "Evaluation means" refers to functions or devices used to analyze user posture and device usage based on acquired data.

[0262] "Output means" refers to interfaces such as screen displays or audio output used to notify the user of the evaluation results.

[0263] An "environmental monitoring device" is a device that photographs and records the user's surrounding environment and activities, and acquires information to support healthy posture and activities.

[0264] An "activity suggestion tool" is a function or device that evaluates the user's activity level and suggests appropriate actions for maintaining health.

[0265] A "machine learning model" is an artificial intelligence technology that learns from large amounts of data and analyzes eye-tracking and posture data.

[0266] Modes for carrying out the invention

[0267] In this embodiment, a system is constructed to support users in using the terminal in a healthy manner. The system includes sensor means for acquiring user gaze data, evaluation means for analyzing and evaluating gaze data, output means for providing alerts to the user based on the evaluation results, environmental monitoring means for monitoring the environment, and activity suggestion means for suggesting activities.

[0268] Program Processing Description

[0269] The server uses a Python program to acquire gaze data from the camera installed on the device. It processes the acquired video using the OpenCV library to extract user gaze and posture information. Machine learning models such as TensorFlow are used to analyze this data and determine whether the user is maintaining a healthy posture or if the device is being used for extended periods.

[0270] The analysis results are communicated to the user as visual or audio alerts via the device's display or speaker. These alerts may include messages such as "Improve your posture" or "Take a 30-minute break."

[0271] For example, if a user tends to sit for long periods while watching television, this system uses environmental monitoring to detect the user's sitting position and suggests posture improvements or breaks. The generative AI model evaluates the user's condition in real time and provides feedback to help maintain healthier lifestyle habits.

[0272] Example of a prompt:

[0273] "Generate a message suggesting healthy activities to users who have been sitting for more than 30 minutes."

[0274] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0275] Step 1:

[0276] The server acquires gaze data from the camera installed in the terminal. The camera captures the user's face and posture and transmits the video data to the server in real time. The input is video data, and the output is raw gaze information.

[0277] Step 2:

[0278] The server preprocesses the acquired video data using the OpenCV library to detect the user's facial movements and gaze position. By performing face detection and feature point extraction to obtain gaze data, it understands how the user is using the device. The input is raw gaze video data, and the output is gaze position information and gaze angle information.

[0279] Step 3:

[0280] The server analyzes gaze data using machine learning models such as TensorFlow. Based on gaze position, angle, and usage time, it determines whether the user's posture is healthy or if they are using the device for an extended period. The input is gaze position information and gaze angle information, and the output is evaluation results and analysis data.

[0281] Step 4:

[0282] Based on the obtained evaluation results, the terminal outputs an alert to the user. When the evaluation result exceeds the standard, as a visual alert or an audio alert, messages such as "Please correct your posture" or "Let's take a 30-minute break" are displayed. The input is the evaluation result, and the output is the alert message.

[0283] Step 5:

[0284] The server utilizes environmental monitoring means to continuously monitor the user's surrounding environment and activity status. It acquires environmental information and analyzes the user's activity patterns to serve as basic data for making healthy suggestions. The input is the environmental information, and the output is the user's activity status data.

[0285] Step 6:

[0286] The server uses activity suggestion means to propose healthy activities to the user based on pre-determined criteria. The proposed content utilizes a generation AI model to automatically generate the most suitable actions for the user's current state. The input is the user's activity status data, and the output is the proposed activity message.

[0287] Furthermore, an emotion engine for estimating the user's emotion may be combined. That is, the specific processing unit 290 may estimate the user's emotion using the emotion recognition model 59 and perform specific processing using the user's emotion.

[0288] The present invention proposes a system that recognizes the user's gaze data and emotional state and provides appropriate feedback based on them. With this system, in addition to the user's posture and usage time when using the terminal, the emotional state is also considered, enabling more personalized support.

[0289] This system includes the following main components.

[0290] First, the device is equipped with an in-camera, which serves as a sensor to acquire user gaze data. The in-camera has the function of detecting the user's face and measuring the direction and distance of their gaze.

[0291] Next, the evaluation method includes an artificial intelligence model that performs analysis based on gaze data as well as emotional data output by an emotion engine. The emotion engine has the function of analyzing facial expression data acquired from the front camera and estimating the user's emotional state (e.g., fatigue, stress). This ensures that not only the user's physical state but also their mental state is reflected in the evaluation.

[0292] Based on the analysis results, the device's display system provides the user with alerts and support messages. The display system takes the user's emotional state into consideration and displays customized messages tailored to the user's condition, such as "Take a short break and refresh yourself" or "Try some deep breathing to relax."

[0293] As a concrete example, consider a situation where a user is working on a device for an extended period of time. The front camera captures eye-tracking and facial expression data, and the evaluation system analyzes this data to determine that the user is in a hunched-over posture and is experiencing stress based on their facial expression. Based on these results, the device sends an alert to the user, such as, "Take a 5-minute break and try to relax."

[0294] In summary, the present invention provides an innovative system that supports users in maintaining both physical and mental health.

[0295] The following describes the processing flow.

[0296] Step 1:

[0297] The device activates its front camera and captures the user's face in real time. Using a face detection algorithm, it measures the direction of gaze and the distance to the screen, and acquires facial expression data.

[0298] Step 2:

[0299] Collect eye line data and facial expression data on the terminal and send them to the evaluation means. The evaluation means includes an artificial intelligence model and an emotion engine, and starts analysis after receiving the data.

[0300] Step 3:

[0301] The artificial intelligence model of the evaluation means analyzes the eye line data and evaluates the user's posture and usage time. The emotion engine analyzes the facial expression data and estimates the user's emotional state.

[0302] Step 4:

[0303] Based on the analysis results, the terminal comprehensively judges the user's physical and emotional states. For example, if the posture is inappropriate and the emotion engine indicates a stressed state, it is determined that it is necessary to prompt attention.

[0304] Step 5:

[0305] The terminal generates a customized alert based on the judgment. Prepare a message adapted to the user's emotional state and physical state by the display means.

[0306] Step 6:

[0307] The terminal displays an alert to the user. For example, display "长时间的使用により首に負担がかかっています。ストレッチをしましょう" (Long-term use is putting a strain on your neck. Let's do some stretching) and prompt the user to improve specific actions.

[0308] Step 7:

[0309] The user checks the alert and adjusts their actions based on the presented message. The user's reaction can enhance awareness of maintaining health.

[0310] Step 8:

[0311] The device records user responses and alert history, saving it to a database. This data will be used for future feedback and system improvements.

[0312] (Example 2)

[0313] 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".

[0314] Conventional technologies have made it difficult to comprehensively evaluate and individually address the physical burden and mental stress experienced by users while using devices. As a result, users often neglected to consider their health and experienced physical and mental strain due to inappropriate postures and prolonged use. Therefore, the present invention aims to support users in maintaining their health by more precisely evaluating their physical and mental state based on their gaze and facial expression data and providing appropriate feedback.

[0315] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0316] In this invention, the server includes measurement means for acquiring user eye-gaze data and facial expression data; analysis means for analyzing the eye-gaze data and facial expression data and evaluating the user's posture, usage time, and emotional state; and notification means for providing the user with customized alerts and support messages based on the evaluation. This makes it possible to monitor the user's health status in real time while they are using the device and to quickly provide appropriate alerts and support.

[0317] "Measurement means" refers to a function consisting of a device or sensor for acquiring user gaze data and facial expression data.

[0318] The "analysis means" refers to a function that uses acquired gaze data and facial expression data to evaluate the user's posture, usage time, and emotional state.

[0319] "Notification means" refers to a device or function that provides users with customized alerts or support messages based on evaluation results from analysis means.

[0320] An "optical image acquisition device" is an optical device, including in-cameras and webcams, used to acquire gaze data and facial expression data.

[0321] A "generative AI model" is a model that utilizes artificial intelligence technology to estimate a user's state by analyzing large amounts of data and learning specific patterns.

[0322] The system according to the present invention is a mechanism that collects and analyzes the user's gaze data and facial expression data to provide appropriate feedback to the user.

[0323] First, the device is equipped with an in-camera, which acts as an optical device to acquire the user's gaze data and facial expression data. The in-camera captures the user's eye movements and facial features in real time. This data is temporarily processed on the device and then transmitted to a server via the internet.

[0324] The server uses received eye-tracking and facial expression data to analyze the user's state using a generative AI model. The analysis results include the user's posture, an evaluation of device usage time, and emotional state derived from facial expressions. This generative AI model is trained on a wealth of case studies, enabling highly accurate predictions.

[0325] Once the analysis is complete, the server generates feedback based on the analysis results and sends it to the device. Based on this feedback, the device notifies the user with customized alerts and support messages. For example, if the user has been in the same position for a long time, it might display a message such as, "Take a short break, stand up and stretch."

[0326] For example, if it is suspected that a user is fatigued from continuous computer work, the prompts for the generative AI model might include phrases like, "Which data should be prioritized in order to predict that the user is fatigued?" or "Please tell me an effective way to provide feedback to reduce user stress."

[0327] In this way, users are supported in maintaining their physical and mental health while using the device. The system of the present invention can firmly support the user's comfort and health in everyday device use.

[0328] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0329] Step 1:

[0330] The device uses its front camera to acquire user gaze and facial expression data in real time. Input is the user's face and eye movements, while output is numerical data regarding gaze direction, eye opening / closing status, and facial expression. This data is used as fundamental information to understand the user's current state.

[0331] Step 2:

[0332] The terminal temporarily stores the acquired gaze and facial expression data and transmits it to the server via the internet. The input is the data captured within the terminal, and the output is the data transfer to the server. This process aggregates the data on the server in a format that can be analyzed.

[0333] Step 3:

[0334] The server utilizes a generative AI model to analyze the received gaze and facial expression data. The input is gaze and facial expression data, and the output is a quantitative evaluation of the user's posture, usage time, and emotional state. Specifically, the AI ​​model estimates the user's state from gaze focus patterns and changes in facial expression.

[0335] Step 4:

[0336] The server generates feedback messages for the user based on the analysis results. The input is the user's evaluation result, and the output is a customized message to promote the user's health. For example, if shoulder stiffness due to prolonged work is predicted, a message such as "Take a break and move your shoulders" will be generated.

[0337] Step 5:

[0338] The device receives feedback sent from the server and notifies the user. The input is the feedback message from the server, and the output is the information displayed on the screen. This process allows the user to receive specific advice about their health status.

[0339] (Application Example 2)

[0340] 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."

[0341] In modern society, users often experience physical and mental strain due to long hours of work and daily stress. Given the lack of available support systems in these situations, there is a need for means to adequately support users' health. Furthermore, providing appropriate feedback tailored to users' emotional states is a challenge in order to improve their quality of life.

[0342] 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.

[0343] In this invention, the server includes sensor means for acquiring user gaze data, evaluation means for analyzing the gaze data and evaluating the user's posture and usage time, and emotion analysis means for estimating the user's emotional state and generating a message corresponding to that state. This makes it possible to provide customized feedback that takes into account the user's physical and mental health.

[0344] A "user" refers to an individual who uses the system, and their eye-tracking data and emotional state are the subjects of evaluation.

[0345] "Eye-gaze data" refers to data that includes information about the user's eye movements and points of fixation, and is acquired by sensor devices.

[0346] A "sensor means" is a device for acquiring user gaze data, and it primarily functions using an image acquisition device.

[0347] An "image acquisition device" refers to a device used to obtain user gaze data, such as a camera.

[0348] "Evaluation means" refers to a device or method that analyzes acquired eye-tracking data to evaluate the user's posture and usage time.

[0349] An "artificial intelligence model" refers to a set of programs or algorithms used to analyze eye-tracking data and other information, enabling advanced analysis.

[0350] "Emotional state" refers to information that indicates the user's mental state, representing the user's emotions estimated from facial expression data.

[0351] "Emotional analysis means" refers to a device or method for estimating a user's emotional state and generating an appropriate message based on that information.

[0352] "Information provision means" refers to means of conveying messages generated based on analyzed data to the user, and includes audio and screen displays.

[0353] The system for implementing this invention is configured to provide users with feedback to support their physical and mental health using a household robot. The system is equipped with a camera as a sensor for acquiring gaze data, thereby capturing the user's gaze and facial expressions. Specific hardware examples include consumer robots equipped with cameras.

[0354] Data acquired by the sensor is analyzed by an evaluation system inside the robot. This evaluation system is programmed using Python and utilizes image processing libraries such as OpenCV and emotion analysis libraries (e.g., fer) to estimate the user's emotional state. This allows the robot to analyze the user's gaze data and facial expression data to understand the user's posture, fatigue level, and stress level.

[0355] Based on the user's emotional state, a generative AI model is used to provide appropriate feedback to the user. Specific means of providing this information include messages displayed on the screen and voice guidance. These methods generate and deliver messages that suggest measures to help the user relax.

[0356] For example, if a robot detects a user's face and recognizes fatigue after prolonged work, the robot will provide a message via voice or display saying, "I suggest a tea break. Why not refresh yourself?" In a generative AI model, a prompt such as the following might be used: "Use facial expression data that may indicate the user is tired to generate a message suggesting actions to relax."

[0357] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0358] Step 1:

[0359] The device uses a camera as a sensor to capture the user's face and acquire gaze and facial expression data. This input data is saved in image file format.

[0360] Step 2:

[0361] The device preprocesses the acquired image data using the OpenCV library to extract facial feature points. This process removes noise and identifies facial regions, outputting data in a format suitable for analysis.

[0362] Step 3:

[0363] The device inputs pre-processed data into a sentiment analysis library (e.g., fer) to estimate the emotional state. This data calculation outputs an estimated value of the emotion the user is expressing (e.g., joy, anger, sadness, fatigue).

[0364] Step 4:

[0365] The device uses a generative AI model to generate feedback messages based on emotional states. As input, it forms prompt sentences based on estimated emotional data. This generation process outputs messages that suggest specific actions for the user.

[0366] Step 5:

[0367] The device delivers generated messages to the user through its display or speaker. This action provides specific feedback and suggestions tailored to the user's state.

[0368] 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.

[0369] 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.

[0370] 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.

[0371] [Third Embodiment]

[0372] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0373] 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.

[0374] 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).

[0375] 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.

[0376] 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.

[0377] 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).

[0378] 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.

[0379] 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.

[0380] 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.

[0381] 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.

[0382] 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.

[0383] 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".

[0384] This invention is a system for supporting healthy device use by users. The system aims to monitor the user's posture and usage time while using the device and provide appropriate alerts. It mainly includes the following components:

[0385] First, the device has a built-in front-facing camera that serves as a sensor for acquiring eye-tracking data. The front-facing camera captures the user's facial movements in real time and measures the angle of their gaze and the distance from the screen. This data forms the basis for evaluating whether the user is using the smartphone appropriately.

[0386] Next, the device is equipped with an evaluation means for analyzing the collected data. In one embodiment, an artificial intelligence model is used for this evaluation means. The AI ​​compares the user's gaze data with pre-set criteria (e.g., the appropriate angle of gaze and the upper limit of usage time) to detect whether the user is in an inappropriate posture or using the device for an extended period.

[0387] The analysis results are directly passed to the display device. The display device then issues an alert to the user based on the evaluation results. The alert is displayed on the device screen as a visual notification. For example, messages such as "Take a 5-minute break" or "Improve your posture" are presented in a way that allows the user to notice the alert.

[0388] As a concrete example, consider a scenario where a user is watching a video on their device. The device's front camera continuously monitors the user's gaze, and AI evaluates the data. If the user's gaze deviates from a certain angle for two minutes, the display will notify them with a message such as, "Please straighten your posture." By providing interactive, real-time feedback in this way, users can prevent unhealthy device use and maintain their health.

[0389] The following describes the processing flow.

[0390] Step 1:

[0391] The device activates its front camera and captures the user's face and eye position in real time. Through image processing, it measures the angle of gaze and the distance to the screen, collecting gaze data.

[0392] Step 2:

[0393] The device transmits the eye-tracking data it collects to an evaluation system. The evaluation system includes an artificial intelligence model that compares the angle of gaze and the distance to the screen with reference values ​​to evaluate the user's posture and usage in real time.

[0394] Step 3:

[0395] Based on the analysis results from the evaluation method, the terminal makes a decision. If the user's posture is inappropriate or if the terminal is used continuously for a certain period of time, it generates the necessary alerts.

[0396] Step 4:

[0397] The device notifies the user of the generated alert message via a display device. The user is presented with a visual warning on the device screen, such as "Please correct your posture" or "We recommend taking a 5-minute break."

[0398] Step 5:

[0399] The system improves behavior based on alerts received by the user. The user checks the displayed message and adjusts their posture or temporarily stops using the device.

[0400] Step 6:

[0401] The device accumulates user responses and alert history, and stores this information in a database. Later, the device can use this history to provide feedback to the user.

[0402] (Example 1)

[0403] 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."

[0404] In modern times, it is common for individuals to use electronic devices for extended periods, but improper posture and excessive use can have adverse effects on health. Conventional systems face the challenge of effectively monitoring this and providing real-time feedback.

[0405] 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.

[0406] In this invention, the server includes a sensing device for acquiring the user's gaze direction and distance information, an analysis device for analyzing the gaze direction and distance information and evaluating the user's posture and usage duration, and a display device for providing visual notifications to the user based on the evaluation. This promotes healthy terminal use by the user and enables real-time feedback.

[0407] A "sensing device" is a device used to acquire information about the user's line of sight and distance.

[0408] An "analysis device" is a device that analyzes acquired gaze direction and distance information to evaluate the user's posture and duration of use.

[0409] A "display device" is a device that provides visual notifications to the user based on the analysis results.

[0410] "Communication means" refers to the means of implementing a communication process to provide real-time feedback.

[0411] "Eyewitness direction and distance information" refers to information about the direction in which the user's gaze is directed and the physical distance between the user and the device.

[0412] "Real-time feedback" refers to the immediate evaluation of the user's status and the prompt provision of appropriate notifications.

[0413] This invention is a system for monitoring a user's posture and usage duration when using electronic devices, and for supporting healthy device use. The system is configured as follows:

[0414] First, the device has a built-in video capture device (e.g., front camera) as a sensing device to acquire information about the user's gaze direction and distance. This sensing device tracks the position of the user's eyes based on facial recognition technology and measures the angle of their gaze and the distance from the device in real time.

[0415] Next, the device processes this gaze information using an internally installed analysis device. This analysis device implements a generated algorithm (e.g., an artificial intelligence model) and compares the user's gaze information with pre-set criteria (e.g., gaze angle, usage time limit). This determines whether the user's posture is inappropriate or whether the device has been used for an extended period.

[0416] The analysis results are fed back to the user through a display device. Specifically, based on the evaluation results, visual notifications such as "Please correct your posture" or "Please take a 5-minute break" are displayed on the device screen. These notifications are immediate and help users prevent unhealthy device use.

[0417] As a concrete example, consider a case where a user is watching a movie on their device. If their gaze remains outside the proper range for two minutes, the device immediately displays a notification saying, "Please correct your posture." This feedback makes it easier for the user to maintain good health.

[0418] An example of a prompt is: "Generate an alert message to notify the user if they use the device for an extended period and their gaze deviates from the correct angle." This prompt is input into the AI ​​model and provides instructions that serve as a basis for evaluating the user's condition.

[0419] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0420] Step 1:

[0421] The terminal uses a built-in video capture device as a sensing device to acquire information on the direction and distance of the user's gaze. Specifically, it recognizes the user's face and tracks the position of their eyes to measure the angle of their gaze and the distance to the terminal. The input for this step is video data, and the output is information on the angle of gaze and distance.

[0422] Step 2:

[0423] The terminal inputs the acquired gaze direction and distance information into an analysis device. This analysis device processes the data using a generated AI model. The AI ​​model compares the gaze information to pre-set criteria and evaluates the user's posture and usage time. The input for this step is gaze direction and distance information, and the output is the evaluation results of posture and usage duration. Specifically, the AI ​​model determines whether the user's gaze angle is within an appropriate range and whether the usage time exceeds a set limit.

[0424] Step 3:

[0425] The device provides feedback to the user through a display device, specifically by displaying visual notifications on the device's screen. These notifications may include messages such as "Please straighten your posture" or "Please take a 5-minute break." The input for this step is the evaluation result, and the output is the visual notification to the user. Specifically, the notification message is intended to pop up on the screen so that the user will notice it.

[0426] Step 4:

[0427] The user receives notifications from the device and modifies their actions based on them. The input is the notification message, and the output is the user's actions, such as improving posture or starting a rest. Specifically, the user is expected to follow the instructions from the device, readjust their posture, and take short breaks as needed.

[0428] (Application Example 1)

[0429] 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."

[0430] In modern society, prolonged use of electronic devices raises concerns about poor posture and health effects on users. This invention aims to support healthy device use by monitoring the user's posture in real time and providing appropriate feedback.

[0431] 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.

[0432] In this invention, the server includes sensor means for acquiring user gaze data, evaluation means for analyzing the gaze data and evaluating the user's posture and usage time, and output means for providing alerts to the user based on the evaluation. This makes it possible to suggest appropriate posture improvements and rest times to the user.

[0433] A "user" is a person who uses this system and is the target of support in maintaining healthy posture and lifestyle habits.

[0434] "Eye-gaze data" refers to information about the position and movement of a user's gaze, and is acquired from sensors such as the front camera.

[0435] "Sensing means" is a general term for devices and technologies that acquire eye-tracking data and environmental information.

[0436] "Evaluation means" refers to functions or devices used to analyze user posture and device usage based on acquired data.

[0437] "Output means" refers to interfaces such as screen displays or audio output used to notify the user of the evaluation results.

[0438] An "environmental monitoring device" is a device that photographs and records the user's surrounding environment and activities, and acquires information to support healthy posture and activities.

[0439] An "activity suggestion tool" is a function or device that evaluates the user's activity level and suggests appropriate actions for maintaining health.

[0440] A "machine learning model" is an artificial intelligence technology that learns from large amounts of data and analyzes eye-tracking and posture data.

[0441] Modes for carrying out the invention

[0442] In this embodiment, a system is constructed to support users in using the terminal in a healthy manner. The system includes sensor means for acquiring user gaze data, evaluation means for analyzing and evaluating gaze data, output means for providing alerts to the user based on the evaluation results, environmental monitoring means for monitoring the environment, and activity suggestion means for suggesting activities.

[0443] Program Processing Description

[0444] The server uses a Python program to acquire gaze data from the camera installed on the device. It processes the acquired video using the OpenCV library to extract user gaze and posture information. Machine learning models such as TensorFlow are used to analyze this data and determine whether the user is maintaining a healthy posture or if the device is being used for extended periods.

[0445] The analysis results are communicated to the user as visual or audio alerts via the device's display or speaker. These alerts may include messages such as "Improve your posture" or "Take a 30-minute break."

[0446] For example, if a user tends to sit for long periods while watching television, this system uses environmental monitoring to detect the user's sitting position and suggests posture improvements or breaks. The generative AI model evaluates the user's condition in real time and provides feedback to help maintain healthier lifestyle habits.

[0447] Example of a prompt:

[0448] "Generate a message suggesting healthy activities to users who have been sitting for more than 30 minutes."

[0449] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0450] Step 1:

[0451] The server acquires gaze data from the camera installed in the terminal. The camera captures the user's face and posture and transmits the video data to the server in real time. The input is video data, and the output is raw gaze information.

[0452] Step 2:

[0453] The server preprocesses the acquired video data using the OpenCV library to detect the user's facial movements and gaze position. By performing face detection and feature point extraction to obtain gaze data, it understands how the user is using the device. The input is raw gaze video data, and the output is gaze position information and gaze angle information.

[0454] Step 3:

[0455] The server analyzes gaze data using machine learning models such as TensorFlow. Based on gaze position, angle, and usage time, it determines whether the user's posture is healthy or if they are using the device for an extended period. The input is gaze position information and gaze angle information, and the output is evaluation results and analysis data.

[0456] Step 4:

[0457] The device outputs alerts to the user based on the evaluation results obtained. If the evaluation results exceed the standard, it displays messages such as "Please correct your posture" or "Take a 30-minute break" as visual or audio alerts. The input is the evaluation result, and the output is the alert message.

[0458] Step 5:

[0459] The server utilizes environmental monitoring tools to continuously monitor the user's surroundings and activity status. It acquires environmental information and uses it as foundational data to analyze the user's activity patterns and provide health-conscious suggestions. The input is environmental information, and the output is user activity status data.

[0460] Step 6:

[0461] The server uses an activity suggestion mechanism to propose healthy activities to the user based on predetermined criteria. The suggestions are automatically generated using a generative AI model, selecting the most suitable action for the user's current state. The input is the user's activity status data, and the output is the suggested activity message.

[0462] 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.

[0463] This invention proposes a system that recognizes a user's eye-tracking data and emotional state, and provides appropriate feedback based on this data. This system takes into account not only the user's posture and usage time when using the device, but also their emotional state, enabling more personalized support.

[0464] This system includes the following main components:

[0465] First, the device is equipped with an in-camera, which serves as a sensor to acquire user gaze data. The in-camera has the function of detecting the user's face and measuring the direction and distance of their gaze.

[0466] Next, the evaluation method includes an artificial intelligence model that performs analysis based on gaze data as well as emotional data output by an emotion engine. The emotion engine has the function of analyzing facial expression data acquired from the front camera and estimating the user's emotional state (e.g., fatigue, stress). This ensures that not only the user's physical state but also their mental state is reflected in the evaluation.

[0467] Based on the analysis results, the device's display system provides the user with alerts and support messages. The display system takes the user's emotional state into consideration and displays customized messages tailored to the user's condition, such as "Take a short break and refresh yourself" or "Try some deep breathing to relax."

[0468] As a concrete example, consider a situation where a user is working on a device for an extended period of time. The front camera captures eye-tracking and facial expression data, and the evaluation system analyzes this data to determine that the user is in a hunched-over posture and is experiencing stress based on their facial expression. Based on these results, the device sends an alert to the user, such as, "Take a 5-minute break and try to relax."

[0469] In summary, the present invention provides an innovative system that supports users in maintaining both physical and mental health.

[0470] The following describes the processing flow.

[0471] Step 1:

[0472] The device activates its front camera and captures the user's face in real time. Using a face detection algorithm, it measures the direction of gaze and the distance to the screen, and acquires facial expression data.

[0473] Step 2:

[0474] The device collects eye-tracking and facial expression data and transmits it to an evaluation system. The evaluation system includes an artificial intelligence model and an emotion engine, which begin analysis after receiving the data.

[0475] Step 3:

[0476] The AI ​​model used for evaluation analyzes eye-tracking data to assess the user's posture and usage time. The emotion engine analyzes facial expression data to estimate the user's emotional state.

[0477] Step 4:

[0478] Based on the analysis results, the device comprehensively assesses the user's physical and emotional state. For example, if the posture is inappropriate and the emotional engine indicates a stressed state, it will determine that a warning is necessary.

[0479] Step 5:

[0480] The device generates customized alerts based on its own judgment. It prepares messages adapted to the user's emotional and physical state through display means.

[0481] Step 6:

[0482] The device displays alerts to the user. For example, it might display, "Your neck is strained from prolonged use. Please stretch," prompting the user to take specific actions to improve their behavior.

[0483] Step 7:

[0484] Users check alerts and adjust their actions based on the messages presented. Their responses can help raise awareness of maintaining good health.

[0485] Step 8:

[0486] The device records user responses and alert history, saving it to a database. This data will be used for future feedback and system improvements.

[0487] (Example 2)

[0488] 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."

[0489] Conventional technologies have made it difficult to comprehensively evaluate and individually address the physical burden and mental stress experienced by users while using devices. As a result, users often neglected to consider their health and experienced physical and mental strain due to inappropriate postures and prolonged use. Therefore, the present invention aims to support users in maintaining their health by more precisely evaluating their physical and mental state based on their gaze and facial expression data and providing appropriate feedback.

[0490] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0491] In this invention, the server includes measurement means for acquiring user eye-gaze data and facial expression data; analysis means for analyzing the eye-gaze data and facial expression data and evaluating the user's posture, usage time, and emotional state; and notification means for providing the user with customized alerts and support messages based on the evaluation. This makes it possible to monitor the user's health status in real time while they are using the device and to quickly provide appropriate alerts and support.

[0492] "Measurement means" refers to a function consisting of a device or sensor for acquiring user gaze data and facial expression data.

[0493] The "analysis means" refers to a function that uses acquired gaze data and facial expression data to evaluate the user's posture, usage time, and emotional state.

[0494] "Notification means" refers to a device or function that provides users with customized alerts or support messages based on evaluation results from analysis means.

[0495] An "optical image acquisition device" is an optical device, including in-cameras and webcams, used to acquire gaze data and facial expression data.

[0496] A "generative AI model" is a model that utilizes artificial intelligence technology to estimate a user's state by analyzing large amounts of data and learning specific patterns.

[0497] The system according to the present invention is a mechanism that collects and analyzes the user's gaze data and facial expression data to provide appropriate feedback to the user.

[0498] First, the device is equipped with an in-camera, which acts as an optical device to acquire the user's gaze data and facial expression data. The in-camera captures the user's eye movements and facial features in real time. This data is temporarily processed on the device and then transmitted to a server via the internet.

[0499] The server uses received eye-tracking and facial expression data to analyze the user's state using a generative AI model. The analysis results include the user's posture, an evaluation of device usage time, and emotional state derived from facial expressions. This generative AI model is trained on a wealth of case studies, enabling highly accurate predictions.

[0500] Once the analysis is complete, the server generates feedback based on the analysis results and sends it to the device. Based on this feedback, the device notifies the user with customized alerts and support messages. For example, if the user has been in the same position for a long time, it might display a message such as, "Take a short break, stand up and stretch."

[0501] For example, if it is suspected that a user is fatigued from continuous computer work, the prompts for the generative AI model might include phrases like, "Which data should be prioritized in order to predict that the user is fatigued?" or "Please tell me an effective way to provide feedback to reduce user stress."

[0502] In this way, users are supported in maintaining their physical and mental health while using the device. The system of the present invention can firmly support the user's comfort and health in everyday device use.

[0503] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0504] Step 1:

[0505] The device uses its front camera to acquire user gaze and facial expression data in real time. Input is the user's face and eye movements, while output is numerical data regarding gaze direction, eye opening / closing status, and facial expression. This data is used as fundamental information to understand the user's current state.

[0506] Step 2:

[0507] The terminal temporarily stores the acquired gaze and facial expression data and transmits it to the server via the internet. The input is the data captured within the terminal, and the output is the data transfer to the server. This process aggregates the data on the server in a format that can be analyzed.

[0508] Step 3:

[0509] The server utilizes a generative AI model to analyze the received gaze and facial expression data. The input is gaze and facial expression data, and the output is a quantitative evaluation of the user's posture, usage time, and emotional state. Specifically, the AI ​​model estimates the user's state from gaze focus patterns and changes in facial expression.

[0510] Step 4:

[0511] The server generates feedback messages for the user based on the analysis results. The input is the user's evaluation result, and the output is a customized message to promote the user's health. For example, if shoulder stiffness due to prolonged work is predicted, a message such as "Take a break and move your shoulders" will be generated.

[0512] Step 5:

[0513] The device receives feedback sent from the server and notifies the user. The input is the feedback message from the server, and the output is the information displayed on the screen. This process allows the user to receive specific advice about their health status.

[0514] (Application Example 2)

[0515] 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."

[0516] In modern society, users often experience physical and mental strain due to long hours of work and daily stress. Given the lack of available support systems in these situations, there is a need for means to adequately support users' health. Furthermore, providing appropriate feedback tailored to users' emotional states is a challenge in order to improve their quality of life.

[0517] 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.

[0518] In this invention, the server includes sensor means for acquiring user gaze data, evaluation means for analyzing the gaze data and evaluating the user's posture and usage time, and emotion analysis means for estimating the user's emotional state and generating a message corresponding to that state. This makes it possible to provide customized feedback that takes into account the user's physical and mental health.

[0519] A "user" refers to an individual who uses the system, and their eye-tracking data and emotional state are the subjects of evaluation.

[0520] "Eye-gaze data" refers to data that includes information about the user's eye movements and points of fixation, and is acquired by sensor devices.

[0521] A "sensor means" is a device for acquiring user gaze data, and it primarily functions using an image acquisition device.

[0522] An "image acquisition device" refers to a device used to obtain user gaze data, such as a camera.

[0523] "Evaluation means" refers to a device or method that analyzes acquired eye-tracking data to evaluate the user's posture and usage time.

[0524] An "artificial intelligence model" refers to a set of programs or algorithms used to analyze eye-tracking data and other information, enabling advanced analysis.

[0525] "Emotional state" refers to information that indicates the user's mental state, representing the user's emotions estimated from facial expression data.

[0526] "Emotional analysis means" refers to a device or method for estimating a user's emotional state and generating an appropriate message based on that information.

[0527] "Information provision means" refers to means of conveying messages generated based on analyzed data to the user, and includes audio and screen displays.

[0528] The system for implementing this invention is configured to provide users with feedback to support their physical and mental health using a household robot. The system is equipped with a camera as a sensor for acquiring gaze data, thereby capturing the user's gaze and facial expressions. Specific hardware examples include consumer robots equipped with cameras.

[0529] Data acquired by the sensor is analyzed by an evaluation system inside the robot. This evaluation system is programmed using Python and utilizes image processing libraries such as OpenCV and emotion analysis libraries (e.g., fer) to estimate the user's emotional state. This allows the robot to analyze the user's gaze data and facial expression data to understand the user's posture, fatigue level, and stress level.

[0530] Based on the user's emotional state, a generative AI model is used to provide appropriate feedback to the user. Specific means of providing this information include messages displayed on the screen and voice guidance. These methods generate and deliver messages that suggest measures to help the user relax.

[0531] For example, if a robot detects a user's face and recognizes fatigue after prolonged work, the robot will provide a message via voice or display saying, "I suggest a tea break. Why not refresh yourself?" In a generative AI model, a prompt such as the following might be used: "Use facial expression data that may indicate the user is tired to generate a message suggesting actions to relax."

[0532] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0533] Step 1:

[0534] The device uses a camera as a sensor to capture the user's face and acquire gaze and facial expression data. This input data is saved in image file format.

[0535] Step 2:

[0536] The device preprocesses the acquired image data using the OpenCV library to extract facial feature points. This process removes noise and identifies facial regions, outputting data in a format suitable for analysis.

[0537] Step 3:

[0538] The device inputs pre-processed data into a sentiment analysis library (e.g., fer) to estimate the emotional state. This data calculation outputs an estimated value of the emotion the user is expressing (e.g., joy, anger, sadness, fatigue).

[0539] Step 4:

[0540] The device uses a generative AI model to generate feedback messages based on emotional states. As input, it forms prompt sentences based on estimated emotional data. This generation process outputs messages that suggest specific actions for the user.

[0541] Step 5:

[0542] The device delivers generated messages to the user through its display or speaker. This action provides specific feedback and suggestions tailored to the user's state.

[0543] 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.

[0544] 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.

[0545] 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.

[0546] [Fourth Embodiment]

[0547] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0548] 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.

[0549] 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).

[0550] 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.

[0551] 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.

[0552] 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).

[0553] 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.

[0554] 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.

[0555] 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.

[0556] 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.

[0557] 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.

[0558] 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.

[0559] 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".

[0560] This invention is a system for supporting healthy device use by users. The system aims to monitor the user's posture and usage time while using the device and provide appropriate alerts. It mainly includes the following components:

[0561] First, the device has a built-in front-facing camera that serves as a sensor for acquiring eye-tracking data. The front-facing camera captures the user's facial movements in real time and measures the angle of their gaze and the distance from the screen. This data forms the basis for evaluating whether the user is using the smartphone appropriately.

[0562] Next, the device is equipped with an evaluation means for analyzing the collected data. In one embodiment, an artificial intelligence model is used for this evaluation means. The AI ​​compares the user's gaze data with pre-set criteria (e.g., the appropriate angle of gaze and the upper limit of usage time) to detect whether the user is in an inappropriate posture or using the device for an extended period.

[0563] The analysis results are directly passed to the display device. The display device then issues an alert to the user based on the evaluation results. The alert is displayed on the device screen as a visual notification. For example, messages such as "Take a 5-minute break" or "Improve your posture" are presented in a way that allows the user to notice the alert.

[0564] As a concrete example, consider a scenario where a user is watching a video on their device. The device's front camera continuously monitors the user's gaze, and AI evaluates the data. If the user's gaze deviates from a certain angle for two minutes, the display will notify them with a message such as, "Please straighten your posture." By providing interactive, real-time feedback in this way, users can prevent unhealthy device use and maintain their health.

[0565] The following describes the processing flow.

[0566] Step 1:

[0567] The device activates its front camera and captures the user's face and eye position in real time. Through image processing, it measures the angle of gaze and the distance to the screen, collecting gaze data.

[0568] Step 2:

[0569] The device transmits the eye-tracking data it collects to an evaluation system. The evaluation system includes an artificial intelligence model that compares the angle of gaze and the distance to the screen with reference values ​​to evaluate the user's posture and usage in real time.

[0570] Step 3:

[0571] Based on the analysis results from the evaluation method, the terminal makes a decision. If the user's posture is inappropriate or if the terminal is used continuously for a certain period of time, it generates the necessary alerts.

[0572] Step 4:

[0573] The device notifies the user of the generated alert message via a display device. The user is presented with a visual warning on the device screen, such as "Please correct your posture" or "We recommend taking a 5-minute break."

[0574] Step 5:

[0575] The system improves behavior based on alerts received by the user. The user checks the displayed message and adjusts their posture or temporarily stops using the device.

[0576] Step 6:

[0577] The device accumulates user responses and alert history, and stores this information in a database. Later, the device can use this history to provide feedback to the user.

[0578] (Example 1)

[0579] 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".

[0580] In modern times, it is common for individuals to use electronic devices for extended periods, but improper posture and excessive use can have adverse effects on health. Conventional systems face the challenge of effectively monitoring this and providing real-time feedback.

[0581] 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.

[0582] In this invention, the server includes a sensing device for acquiring the user's gaze direction and distance information, an analysis device for analyzing the gaze direction and distance information and evaluating the user's posture and usage duration, and a display device for providing visual notifications to the user based on the evaluation. This promotes healthy terminal use by the user and enables real-time feedback.

[0583] A "sensing device" is a device used to acquire information about the user's line of sight and distance.

[0584] An "analysis device" is a device that analyzes acquired gaze direction and distance information to evaluate the user's posture and duration of use.

[0585] A "display device" is a device that provides visual notifications to the user based on the analysis results.

[0586] "Communication means" refers to the means of implementing a communication process to provide real-time feedback.

[0587] "Eyewitness direction and distance information" refers to information about the direction in which the user's gaze is directed and the physical distance between the user and the device.

[0588] "Real-time feedback" refers to the immediate evaluation of the user's status and the prompt provision of appropriate notifications.

[0589] This invention is a system for monitoring a user's posture and usage duration when using electronic devices, and for supporting healthy device use. The system is configured as follows:

[0590] First, the device has a built-in video capture device (e.g., front camera) as a sensing device to acquire information about the user's gaze direction and distance. This sensing device tracks the position of the user's eyes based on facial recognition technology and measures the angle of their gaze and the distance from the device in real time.

[0591] Next, the device processes this gaze information using an internally installed analysis device. This analysis device implements a generated algorithm (e.g., an artificial intelligence model) and compares the user's gaze information with pre-set criteria (e.g., gaze angle, usage time limit). This determines whether the user's posture is inappropriate or whether the device has been used for an extended period.

[0592] The analysis results are fed back to the user through a display device. Specifically, based on the evaluation results, visual notifications such as "Please correct your posture" or "Please take a 5-minute break" are displayed on the device screen. These notifications are immediate and help users prevent unhealthy device use.

[0593] As a concrete example, consider a case where a user is watching a movie on their device. If their gaze remains outside the proper range for two minutes, the device immediately displays a notification saying, "Please correct your posture." This feedback makes it easier for the user to maintain good health.

[0594] An example of a prompt is: "Generate an alert message to notify the user if they use the device for an extended period and their gaze deviates from the correct angle." This prompt is input into the AI ​​model and provides instructions that serve as a basis for evaluating the user's condition.

[0595] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0596] Step 1:

[0597] The terminal uses a built-in video capture device as a sensing device to acquire information on the direction and distance of the user's gaze. Specifically, it recognizes the user's face and tracks the position of their eyes to measure the angle of their gaze and the distance to the terminal. The input for this step is video data, and the output is information on the angle of gaze and distance.

[0598] Step 2:

[0599] The terminal inputs the acquired gaze direction and distance information into an analysis device. This analysis device processes the data using a generated AI model. The AI ​​model compares the gaze information to pre-set criteria and evaluates the user's posture and usage time. The input for this step is gaze direction and distance information, and the output is the evaluation results of posture and usage duration. Specifically, the AI ​​model determines whether the user's gaze angle is within an appropriate range and whether the usage time exceeds a set limit.

[0600] Step 3:

[0601] The device provides feedback to the user through a display device, specifically by displaying visual notifications on the device's screen. These notifications may include messages such as "Please straighten your posture" or "Please take a 5-minute break." The input for this step is the evaluation result, and the output is the visual notification to the user. Specifically, the notification message is intended to pop up on the screen so that the user will notice it.

[0602] Step 4:

[0603] The user receives notifications from the device and modifies their actions based on them. The input is the notification message, and the output is the user's actions, such as improving posture or starting a rest. Specifically, the user is expected to follow the instructions from the device, readjust their posture, and take short breaks as needed.

[0604] (Application Example 1)

[0605] 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".

[0606] In modern society, prolonged use of electronic devices raises concerns about poor posture and health effects on users. This invention aims to support healthy device use by monitoring the user's posture in real time and providing appropriate feedback.

[0607] 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.

[0608] In this invention, the server includes sensor means for acquiring user gaze data, evaluation means for analyzing the gaze data and evaluating the user's posture and usage time, and output means for providing alerts to the user based on the evaluation. This makes it possible to suggest appropriate posture improvements and rest times to the user.

[0609] A "user" is a person who uses this system and is the target of support in maintaining healthy posture and lifestyle habits.

[0610] "Eye-gaze data" refers to information about the position and movement of a user's gaze, and is acquired from sensors such as the front camera.

[0611] "Sensing means" is a general term for devices and technologies that acquire eye-tracking data and environmental information.

[0612] "Evaluation means" refers to functions or devices used to analyze user posture and device usage based on acquired data.

[0613] "Output means" refers to interfaces such as screen displays or audio output used to notify the user of the evaluation results.

[0614] An "environmental monitoring device" is a device that photographs and records the user's surrounding environment and activities, and acquires information to support healthy posture and activities.

[0615] An "activity suggestion tool" is a function or device that evaluates the user's activity level and suggests appropriate actions for maintaining health.

[0616] A "machine learning model" is an artificial intelligence technology that learns from large amounts of data and analyzes eye-tracking and posture data.

[0617] Modes for carrying out the invention

[0618] In this embodiment, a system is constructed to support users in using the terminal in a healthy manner. The system includes sensor means for acquiring user gaze data, evaluation means for analyzing and evaluating gaze data, output means for providing alerts to the user based on the evaluation results, environmental monitoring means for monitoring the environment, and activity suggestion means for suggesting activities.

[0619] Program Processing Description

[0620] The server uses a Python program to acquire gaze data from the camera installed on the device. It processes the acquired video using the OpenCV library to extract user gaze and posture information. Machine learning models such as TensorFlow are used to analyze this data and determine whether the user is maintaining a healthy posture or if the device is being used for extended periods.

[0621] The analysis results are communicated to the user as visual or audio alerts via the device's display or speaker. These alerts may include messages such as "Improve your posture" or "Take a 30-minute break."

[0622] For example, if a user tends to sit for long periods while watching television, this system uses environmental monitoring to detect the user's sitting position and suggests posture improvements or breaks. The generative AI model evaluates the user's condition in real time and provides feedback to help maintain healthier lifestyle habits.

[0623] Example of a prompt:

[0624] "Generate a message suggesting healthy activities to users who have been sitting for more than 30 minutes."

[0625] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0626] Step 1:

[0627] The server acquires gaze data from the camera installed in the terminal. The camera captures the user's face and posture and transmits the video data to the server in real time. The input is video data, and the output is raw gaze information.

[0628] Step 2:

[0629] The server preprocesses the acquired video data using the OpenCV library to detect the user's facial movements and gaze position. By performing face detection and feature point extraction to obtain gaze data, it understands how the user is using the device. The input is raw gaze video data, and the output is gaze position information and gaze angle information.

[0630] Step 3:

[0631] The server analyzes gaze data using machine learning models such as TensorFlow. Based on gaze position, angle, and usage time, it determines whether the user's posture is healthy or if they are using the device for an extended period. The input is gaze position information and gaze angle information, and the output is evaluation results and analysis data.

[0632] Step 4:

[0633] The device outputs alerts to the user based on the evaluation results obtained. If the evaluation results exceed the standard, it displays messages such as "Please correct your posture" or "Take a 30-minute break" as visual or audio alerts. The input is the evaluation result, and the output is the alert message.

[0634] Step 5:

[0635] The server utilizes environmental monitoring tools to continuously monitor the user's surroundings and activity status. It acquires environmental information and uses it as foundational data to analyze the user's activity patterns and provide health-conscious suggestions. The input is environmental information, and the output is user activity status data.

[0636] Step 6:

[0637] The server uses an activity suggestion mechanism to propose healthy activities to the user based on predetermined criteria. The suggestions are automatically generated using a generative AI model, selecting the most suitable action for the user's current state. The input is the user's activity status data, and the output is the suggested activity message.

[0638] 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.

[0639] This invention proposes a system that recognizes a user's eye-tracking data and emotional state, and provides appropriate feedback based on this data. This system takes into account not only the user's posture and usage time when using the device, but also their emotional state, enabling more personalized support.

[0640] This system includes the following main components:

[0641] First, the device is equipped with an in-camera, which serves as a sensor to acquire user gaze data. The in-camera has the function of detecting the user's face and measuring the direction and distance of their gaze.

[0642] Next, the evaluation method includes an artificial intelligence model that performs analysis based on gaze data as well as emotional data output by an emotion engine. The emotion engine has the function of analyzing facial expression data acquired from the front camera and estimating the user's emotional state (e.g., fatigue, stress). This ensures that not only the user's physical state but also their mental state is reflected in the evaluation.

[0643] Based on the analysis results, the device's display system provides the user with alerts and support messages. The display system takes the user's emotional state into consideration and displays customized messages tailored to the user's condition, such as "Take a short break and refresh yourself" or "Try some deep breathing to relax."

[0644] As a concrete example, consider a situation where a user is working on a device for an extended period of time. The front camera captures eye-tracking and facial expression data, and the evaluation system analyzes this data to determine that the user is in a hunched-over posture and is experiencing stress based on their facial expression. Based on these results, the device sends an alert to the user, such as, "Take a 5-minute break and try to relax."

[0645] In summary, the present invention provides an innovative system that supports users in maintaining both physical and mental health.

[0646] The following describes the processing flow.

[0647] Step 1:

[0648] The device activates its front camera and captures the user's face in real time. Using a face detection algorithm, it measures the direction of gaze and the distance to the screen, and acquires facial expression data.

[0649] Step 2:

[0650] The device collects eye-tracking and facial expression data and transmits it to an evaluation system. The evaluation system includes an artificial intelligence model and an emotion engine, which begin analysis after receiving the data.

[0651] Step 3:

[0652] The AI ​​model used for evaluation analyzes eye-tracking data to assess the user's posture and usage time. The emotion engine analyzes facial expression data to estimate the user's emotional state.

[0653] Step 4:

[0654] Based on the analysis results, the device comprehensively assesses the user's physical and emotional state. For example, if the posture is inappropriate and the emotional engine indicates a stressed state, it will determine that a warning is necessary.

[0655] Step 5:

[0656] The device generates customized alerts based on its own judgment. It prepares messages adapted to the user's emotional and physical state through display means.

[0657] Step 6:

[0658] The device displays alerts to the user. For example, it might display, "Your neck is strained from prolonged use. Please stretch," prompting the user to take specific actions to improve their behavior.

[0659] Step 7:

[0660] Users check alerts and adjust their actions based on the messages presented. Their responses can help raise awareness of maintaining good health.

[0661] Step 8:

[0662] The device records user responses and alert history, saving it to a database. This data will be used for future feedback and system improvements.

[0663] (Example 2)

[0664] 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".

[0665] Conventional technologies have made it difficult to comprehensively evaluate and individually address the physical burden and mental stress experienced by users while using devices. As a result, users often neglected to consider their health and experienced physical and mental strain due to inappropriate postures and prolonged use. Therefore, the present invention aims to support users in maintaining their health by more precisely evaluating their physical and mental state based on their gaze and facial expression data and providing appropriate feedback.

[0666] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0667] In this invention, the server includes measurement means for acquiring user eye-gaze data and facial expression data; analysis means for analyzing the eye-gaze data and facial expression data and evaluating the user's posture, usage time, and emotional state; and notification means for providing the user with customized alerts and support messages based on the evaluation. This makes it possible to monitor the user's health status in real time while they are using the device and to quickly provide appropriate alerts and support.

[0668] "Measurement means" refers to a function consisting of a device or sensor for acquiring user gaze data and facial expression data.

[0669] The "analysis means" refers to a function that uses acquired gaze data and facial expression data to evaluate the user's posture, usage time, and emotional state.

[0670] "Notification means" refers to a device or function that provides users with customized alerts or support messages based on evaluation results from analysis means.

[0671] An "optical image acquisition device" is an optical device, including in-cameras and webcams, used to acquire gaze data and facial expression data.

[0672] A "generative AI model" is a model that utilizes artificial intelligence technology to estimate a user's state by analyzing large amounts of data and learning specific patterns.

[0673] The system according to the present invention is a mechanism that collects and analyzes the user's gaze data and facial expression data to provide appropriate feedback to the user.

[0674] First, the device is equipped with an in-camera, which acts as an optical device to acquire the user's gaze data and facial expression data. The in-camera captures the user's eye movements and facial features in real time. This data is temporarily processed on the device and then transmitted to a server via the internet.

[0675] The server uses received eye-tracking and facial expression data to analyze the user's state using a generative AI model. The analysis results include the user's posture, an evaluation of device usage time, and emotional state derived from facial expressions. This generative AI model is trained on a wealth of case studies, enabling highly accurate predictions.

[0676] Once the analysis is complete, the server generates feedback based on the analysis results and sends it to the device. Based on this feedback, the device notifies the user with customized alerts and support messages. For example, if the user has been in the same position for a long time, it might display a message such as, "Take a short break, stand up and stretch."

[0677] For example, if it is suspected that a user is fatigued from continuous computer work, the prompts for the generative AI model might include phrases like, "Which data should be prioritized in order to predict that the user is fatigued?" or "Please tell me an effective way to provide feedback to reduce user stress."

[0678] In this way, users are supported in maintaining their physical and mental health while using the device. The system of the present invention can firmly support the user's comfort and health in everyday device use.

[0679] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0680] Step 1:

[0681] The device uses its front camera to acquire user gaze and facial expression data in real time. Input is the user's face and eye movements, while output is numerical data regarding gaze direction, eye opening / closing status, and facial expression. This data is used as fundamental information to understand the user's current state.

[0682] Step 2:

[0683] The terminal temporarily stores the acquired gaze and facial expression data and transmits it to the server via the internet. The input is the data captured within the terminal, and the output is the data transfer to the server. This process aggregates the data on the server in a format that can be analyzed.

[0684] Step 3:

[0685] The server utilizes a generative AI model to analyze the received gaze and facial expression data. The input is gaze and facial expression data, and the output is a quantitative evaluation of the user's posture, usage time, and emotional state. Specifically, the AI ​​model estimates the user's state from gaze focus patterns and changes in facial expression.

[0686] Step 4:

[0687] The server generates feedback messages for the user based on the analysis results. The input is the user's evaluation result, and the output is a customized message to promote the user's health. For example, if shoulder stiffness due to prolonged work is predicted, a message such as "Take a break and move your shoulders" will be generated.

[0688] Step 5:

[0689] The device receives feedback sent from the server and notifies the user. The input is the feedback message from the server, and the output is the information displayed on the screen. This process allows the user to receive specific advice about their health status.

[0690] (Application Example 2)

[0691] 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".

[0692] In modern society, users often experience physical and mental strain due to long hours of work and daily stress. Given the lack of available support systems in these situations, there is a need for means to adequately support users' health. Furthermore, providing appropriate feedback tailored to users' emotional states is a challenge in order to improve their quality of life.

[0693] 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.

[0694] In this invention, the server includes sensor means for acquiring user gaze data, evaluation means for analyzing the gaze data and evaluating the user's posture and usage time, and emotion analysis means for estimating the user's emotional state and generating a message corresponding to that state. This makes it possible to provide customized feedback that takes into account the user's physical and mental health.

[0695] A "user" refers to an individual who uses the system, and their eye-tracking data and emotional state are the subjects of evaluation.

[0696] "Eye-gaze data" refers to data that includes information about the user's eye movements and points of fixation, and is acquired by sensor devices.

[0697] A "sensor means" is a device for acquiring user gaze data, and it primarily functions using an image acquisition device.

[0698] An "image acquisition device" refers to a device used to obtain user gaze data, such as a camera.

[0699] "Evaluation means" refers to a device or method that analyzes acquired eye-tracking data to evaluate the user's posture and usage time.

[0700] An "artificial intelligence model" refers to a set of programs or algorithms used to analyze eye-tracking data and other information, enabling advanced analysis.

[0701] "Emotional state" refers to information that indicates the user's mental state, representing the user's emotions estimated from facial expression data.

[0702] "Emotional analysis means" refers to a device or method for estimating a user's emotional state and generating an appropriate message based on that information.

[0703] "Information provision means" refers to means of conveying messages generated based on analyzed data to the user, and includes audio and screen displays.

[0704] The system for implementing this invention is configured to provide users with feedback to support their physical and mental health using a household robot. The system is equipped with a camera as a sensor for acquiring gaze data, thereby capturing the user's gaze and facial expressions. Specific hardware examples include consumer robots equipped with cameras.

[0705] Data acquired by the sensor is analyzed by an evaluation system inside the robot. This evaluation system is programmed using Python and utilizes image processing libraries such as OpenCV and emotion analysis libraries (e.g., fer) to estimate the user's emotional state. This allows the robot to analyze the user's gaze data and facial expression data to understand the user's posture, fatigue level, and stress level.

[0706] Based on the user's emotional state, a generative AI model is used to provide appropriate feedback to the user. Specific means of providing this information include messages displayed on the screen and voice guidance. These methods generate and deliver messages that suggest measures to help the user relax.

[0707] For example, if a robot detects a user's face and recognizes fatigue after prolonged work, the robot will provide a message via voice or display saying, "I suggest a tea break. Why not refresh yourself?" In a generative AI model, a prompt such as the following might be used: "Use facial expression data that may indicate the user is tired to generate a message suggesting actions to relax."

[0708] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0709] Step 1:

[0710] The device uses a camera as a sensor to capture the user's face and acquire gaze and facial expression data. This input data is saved in image file format.

[0711] Step 2:

[0712] The device preprocesses the acquired image data using the OpenCV library to extract facial feature points. This process removes noise and identifies facial regions, outputting data in a format suitable for analysis.

[0713] Step 3:

[0714] The device inputs pre-processed data into a sentiment analysis library (e.g., fer) to estimate the emotional state. This data calculation outputs an estimated value of the emotion the user is expressing (e.g., joy, anger, sadness, fatigue).

[0715] Step 4:

[0716] The device uses a generative AI model to generate feedback messages based on emotional states. As input, it forms prompt sentences based on estimated emotional data. This generation process outputs messages that suggest specific actions for the user.

[0717] Step 5:

[0718] The device delivers generated messages to the user through its display or speaker. This action provides specific feedback and suggestions tailored to the user's state.

[0719] 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.

[0720] 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.

[0721] 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.

[0722] 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.

[0723] 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.

[0724] 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.

[0725] 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.

[0726] 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.

[0727] 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."

[0728] 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.

[0729] 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.

[0730] 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.

[0731] 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.

[0732] 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.

[0733] 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.

[0734] 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.

[0735] 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.

[0736] 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.

[0737] 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.

[0738] 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.

[0739] 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.

[0740] The following is further disclosed regarding the embodiments described above.

[0741] (Claim 1)

[0742] A means for acquiring user eye-tracking data,

[0743] An evaluation means for analyzing the aforementioned gaze data and evaluating the user's posture and usage time,

[0744] Based on the above evaluation, a display means for providing alerts to the user,

[0745] A system that includes this.

[0746] (Claim 2)

[0747] The system according to claim 1, wherein the sensor means acquires gaze data using an image acquisition device.

[0748] (Claim 3)

[0749] The system according to claim 1, wherein the evaluation means analyzes the user's gaze data using an artificial intelligence model.

[0750] "Example 1"

[0751] (Claim 1)

[0752] A sensing device for acquiring user's line of sight direction and distance information,

[0753] An analysis device that analyzes the aforementioned gaze direction and distance information and evaluates the user's posture and usage duration,

[0754] Based on the above evaluation, a display device that provides visual notifications to the user,

[0755] Communication means for providing real-time feedback,

[0756] A system that includes this.

[0757] (Claim 2)

[0758] The system according to claim 1, wherein the sensing device acquires line-of-sight direction and distance information using a video recording device.

[0759] (Claim 3)

[0760] The system according to claim 1, wherein the analysis device analyzes the user's line of sight direction and distance information using the generated algorithm.

[0761] "Application Example 1"

[0762] (Claim 1)

[0763] A means for acquiring user eye-tracking data,

[0764] An evaluation means for analyzing the aforementioned gaze data and evaluating the user's posture and usage time,

[0765] Based on the above evaluation, an output means for providing alerts to the user,

[0766] An environmental monitoring system that photographs the user's environment and monitors their posture,

[0767] The aforementioned environmental monitoring means analyzes the information obtained and proposes healthy activities, and the activity proposal means proposes healthy activities.

[0768] A system that includes this.

[0769] (Claim 2)

[0770] The system according to claim 1, wherein the sensor means acquires gaze data using an imaging device.

[0771] (Claim 3)

[0772] The system according to claim 1, wherein the evaluation means analyzes the user's gaze data using a machine learning model.

[0773] "Example 2 of combining an emotion engine"

[0774] (Claim 1)

[0775] Measurement means for acquiring user gaze data and facial expression data,

[0776] An analysis means for analyzing the aforementioned gaze data and facial expression data to evaluate the user's posture, usage time, and emotional state,

[0777] Based on the aforementioned evaluation, a notification means is provided to deliver customized alerts and support messages to the user.

[0778] A system that includes this.

[0779] (Claim 2)

[0780] The system according to claim 1, wherein the measurement means acquires gaze data and facial expression data using an optical image acquisition device.

[0781] (Claim 3)

[0782] The system according to claim 1, wherein the analysis means analyzes the user's gaze data and facial expression data using a generated AI model.

[0783] "Application example 2 when combining with an emotional engine"

[0784] (Claim 1)

[0785] A means for acquiring user eye-tracking data,

[0786] An evaluation means for analyzing the aforementioned gaze data and evaluating the user's posture and usage time,

[0787] Based on the above evaluation, a display means for providing alerts to the user,

[0788] A sentiment analysis means that estimates the user's emotional state and generates a message corresponding to that state,

[0789] A means of providing information to convey the aforementioned message to the user,

[0790] A system that includes this.

[0791] (Claim 2)

[0792] The system according to claim 1, wherein the sensor means acquires gaze data using an image acquisition device.

[0793] (Claim 3)

[0794] The system according to claim 1, wherein the evaluation means analyzes the user's gaze data using an artificial intelligence model. [Explanation of Symbols]

[0795] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for acquiring user eye-tracking data, An evaluation means for analyzing the aforementioned gaze data and evaluating the user's posture and usage time, Based on the above evaluation, an output means for providing alerts to the user, An environmental monitoring system that photographs the user's environment and monitors their posture, The aforementioned environmental monitoring means analyzes the information obtained and proposes healthy activities, and the activity proposal means proposes healthy activities. A system that includes this.

2. The system according to claim 1, wherein the sensor means acquires gaze data using an imaging device.

3. The system according to claim 1, wherein the evaluation means analyzes the user's gaze data using a machine learning model.

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