system

Abstract

We provide the system. [Solution] A glasses-type display means incorporating a camera for recording the user's movements, Information processing means that analyzes recorded video data to generate information that points out the user's actions, A display control means for multiplexing the generated information on the glasses-type display, 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 a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance as a 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 the conventional practice method, it is difficult to operate while holding a device, so it is difficult to practice efficiently in activities that require the free use of both hands, such as playing a musical instrument, sports, and machine operation. As a result, there is a problem that it is impossible to receive guidance and feedback tailored to individual users in real time, and it is difficult to improve the quality of practice.

Means for Solving the Problems

[0005] This invention provides a glasses-type display with a built-in camera for recording the user's movements, and an information processing system for analyzing the recorded video data and generating information that points out the user's actions. Furthermore, by displaying the generated information on the glasses-type display, the user can receive real-time feedback while keeping both hands free, thereby improving the efficiency of practice.

[0006] A "recording device" is a device that includes cameras and sensors for recording the user's actions.

[0007] A "glasses-type display" is a glasses-shaped device that incorporates a display for directly presenting visual information to the user's field of vision.

[0008] "Information processing means" refers to a processing device that analyzes recorded video data and generates feedback and suggestions regarding the user's actions.

[0009] "Display control means" refers to a device or system that performs control to appropriately display the generated information on a glasses-type display.

[0010] "User" refers to the person who wears and operates the system.

[0011] "Operation history" refers to a collection of user operation data recorded in the past, and is basic data that information processing devices refer to. [Brief explanation of the drawing]

[0012] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4]It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It 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] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. <好 [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Modes for Carrying Out the Invention

[0013] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described according to the accompanying drawings.

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

[0015] 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.

[0016] 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.

[0017] 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.

[0018] 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.

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

[0020] [First Embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0033] This invention provides a system that enables users to receive efficient and effective feedback during practice and training. This system overcomes the limitations of conventional training methods by recording and analyzing the user's movements and providing real-time, individually optimized instruction.

[0034] The device (equipped with glasses-type displays) captures the user's movements with high precision while they play musical instruments or participate in sports. The recording device incorporates multiple sensors, such as those measuring acceleration and angles, to capture detailed movements. Furthermore, this data is processed rapidly, minimizing delays before it is transmitted to the server.

[0035] The server receives data sent from the terminal and uses an AI algorithm to analyze the behavioral data in detail. During the analysis, the user's past behavioral history and skill level are also considered to determine the most effective teaching method. This generates specific and appropriate advice tailored to the user's current performance.

[0036] Users can modify their actions based on feedback displayed across multiple devices. For example, a user playing the piano might see specific instructions such as, "You should slow down the tempo in this section." This allows users to repeatedly adjust their actions under real-time guidance. Feedback is provided not only through visual guidelines but also through voice assistance, enabling users to practice in the most effective way using multiple senses.

[0037] As a concrete example, consider a scenario where a user is practicing their tennis swing. The device accurately records the user's hand movements and body posture, and the server analyzes this data to generate specific advice such as "finish your swing higher." This advice is communicated to the user in real time, and the user can incorporate and use this feedback. This allows the user to improve their skills at a faster pace than with traditional methods.

[0038] Thus, the present invention allows users to practice actions more efficiently and improve their skills in a short period of time.

[0039] The following describes the processing flow.

[0040] Step 1:

[0041] The device activates its built-in camera and sensors to record the user's movements in real time. This starts capturing video of the movements and various data points (acceleration, angle, etc.).

[0042] Step 2:

[0043] The terminal compresses the captured data using a dedicated algorithm and prepares it for transmission to the server. The data is divided into small units in a batch format, taking communication speed into consideration.

[0044] Step 3:

[0045] The server receives data sent from the terminal, verifies its integrity, and then passes it to the AI ​​processor. The processor applies an optimized algorithm to analyze the received data.

[0046] Step 4:

[0047] The server generates feedback on the user's actions based on the analyzed data. In doing so, it considers past behavioral history and set goals to create optimized advice.

[0048] Step 5:

[0049] The server packets the generated feedback and verifies the network configuration for low-latency transmission to the terminal. Then, it executes the transmission.

[0050] Step 6:

[0051] The terminal decodes the feedback received from the server and prepares it for display in the user's field of view. This involves managing display layers and adjusting the interface.

[0052] Step 7:

[0053] Users review feedback displayed on the device's glasses-type display and fine-tune their actions based on it. This feedback is provided in various forms, including text, graphical hints, and audio guidance, which users use to modify their behavior.

[0054] (Example 1)

[0055] 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."

[0056] Current practice and training methods have the challenge of not being able to quickly provide feedback that fully takes into account the individual skill level and past performance history of the user. As a result, users may experience slow performance improvement or continue with inefficient practice.

[0057] 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.

[0058] In this invention, the server includes a recording means for recording the user's actions, a data processing means for analyzing the recorded action data and generating instruction optimized for the user, and a display control means for transmitting the generated instruction information to a portable display device and presenting it to the user. This allows the user to receive specific and effective feedback on their actions in real time.

[0059] "Recording means" refers to a device that records the user's actions with high precision, and includes cameras and sensors, playing a role in acquiring motion data.

[0060] "Data processing means" refers to computer systems or software algorithms that analyze recorded motion data and generate instructional information optimized for the user.

[0061] "Display control means" refers to a mechanism or process for transmitting generated instructional information to a portable display device and presenting it to the user visually or audibly.

[0062] A "portable display device" is a device that is easy for the user to carry, and includes devices such as glasses-type displays that are used to display real-time feedback.

[0063] A "sensor" is a device that detects the acceleration and angle of movement, and its role is to collect data necessary for a detailed analysis of the user's movements.

[0064] This invention is a system designed to efficiently and effectively improve user performance. The system consists of the interaction of three parties: a terminal equipped with a glasses-type display, a server, and the user.

[0065] The device is designed to record the user's movements while they are playing a musical instrument or participating in sports. It has a built-in camera, accelerometer, and gyroscope, allowing it to acquire detailed data on their movements. For example, during tennis practice, the speed and angle of the swing are recorded in real time.

[0066] The server receives and analyzes the operation data transmitted from the terminal. Using a data processing method based on a generative AI model, it quickly analyzes the user's operation data and generates instructional information based on the analysis results. Because the analysis takes into account past operation history and the user's skill level, it can provide more individually optimized instruction. The generated information is processed by the server as concrete and actionable advice for the user.

[0067] The user receives feedback sent from the server via their device. This feedback is displayed visually within the user's field of view, and audio guidance is also provided. This feedback helps the user correct their actions in real time. For example, the user can learn specific directions for correcting their actions, such as "finish your swing higher."

[0068] As a concrete example, consider a scenario where a user plays the piano. The device records the user's hand and finger movements, and the server analyzes this data to generate advice such as, "You should slow down the tempo in this section." Based on this feedback, the user can improve their playing.

[0069] An example of a prompt to input into the generating AI model is: "Generate effective feedback based on user behavior data. Optimize the instruction content considering past behavior history."

[0070] This system provides users with an environment where they can receive immediate feedback and efficiently improve their own performance.

[0071] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0072] Step 1:

[0073] The device records the user's movements. It uses video and acceleration / angle data acquired by cameras and sensors as input. This data reflects the user's movements in detail and includes multidimensional motion information. Specifically, it records the movements of the hands and racket, as well as body posture, with high precision during a tennis swing. The output consists of recorded video data and measurement data from the sensors.

[0074] Step 2:

[0075] The terminal transmits the recorded data to the server. The input is the motion data generated in step 1. The data is transmitted to the server via wireless communication. Real-time functionality is maintained through rapid transmission. The output is the user's motion data received by the server.

[0076] Step 3:

[0077] The server analyzes the received motion data. The input data is motion data sent from the terminal. The server uses a generative AI model to analyze the data in detail. In this process, it also considers the user's past motion history and skill level, and performs calculations to generate optimal instruction information. Specifically, the data is processed by analyzing the average speed and angle changes of the motion. The output is instruction information tailored to the user.

[0078] Step 4:

[0079] The server generates feedback based on the analysis results. The input is the analysis results from step 3, which are used to construct effective guidance advice. The generating AI model determines the feedback content that is best suited to the user's skill level. The output is specific and individually optimized guidance information.

[0080] Step 5:

[0081] The terminal displays instructional information received from the server to the user. The input is instructional information sent from the server. The terminal presents information to the user through sight and sound, prompting corrections to their movements. Specifically, the glasses-type display visually shows instructional content such as "finish your swing higher." The output is feedback in a form that the user can see.

[0082] Step 6:

[0083] The user modifies their actions based on the feedback provided. The input is the feedback received from the device. Based on this, the user adjusts their practice and actions to improve their skills. The output is the movement reflecting the modified actions and starting points. Specific actions include executing instructed points and re-evaluating the actions.

[0084] (Application Example 1)

[0085] 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."

[0086] Robot motion training in factories is crucial for improving on-site efficiency. However, conventional robot motion optimization methods lack the ability to provide real-time feedback and refine movements, resulting in limited productivity. This invention aims to significantly improve factory efficiency by measuring and analyzing movements in real time and providing immediate, optimal motion guidance.

[0087] 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.

[0088] In this invention, the server includes a glasses-type display means with a built-in camera for recording the user's movements, an information processing means for analyzing the recorded video data and generating information that points out the user's actions, a display control means for multiplexing the generated information on the glasses-type display, and a feedback means for monitoring the movements in real time and providing efficient movement guidance based on the analysis results. This makes it possible for the robot to immediately correct its movements and achieve optimal performance.

[0089] "User" refers to the entity that uses the system to perform training or tasks.

[0090] "Recording device" is a general term for a device that includes sensors and cameras for recording the actions of a user.

[0091] "Eyeglass-type display means" refers to a head-mounted display or smart glasses that allows the wearer to view visual information in real time.

[0092] "Video data" refers to video information about the user's actions recorded by a recording device.

[0093] "Information processing means" refers to a computer program that analyzes recorded video data and generates necessary feedback and guidance.

[0094] "Display control means" refers to a control program for appropriately displaying the generated instructional information on the glasses-type display.

[0095] A "sensor" refers to a physical device used to measure the speed, direction, and force of a user's movements.

[0096] "Feedback methods" refer to systems that provide users with guidance and corrective information based on analysis results in real time.

[0097] "Analysis results" refer to the output after data analysis obtained by information processing means, and include evaluations and guidance regarding the user's actions.

[0098] "Operation history" refers to a collection of data that shows records and trends of the user's actions in the past.

[0099] In order to implement this invention, multiple hardware and software components must work together. The system primarily consists of interactions between servers, terminals, and users.

[0100] The device features a glasses-type display for recording the user's movements with high precision. This display incorporates a camera, accelerometer, gyroscope, and other sensors to acquire user movement data in real time. For example, it can record the movements of a robotic arm or the movements of fingers during factory work.

[0101] The server receives motion data sent from the terminal and analyzes the data using a generated AI model. This analysis uses libraries such as Python's TENSORFLOW® and PyTorch to calculate the speed, direction, and force of the motion, and generates detailed feedback that also takes into account the user's past motion history. This feedback provides important information for achieving efficient operation. For example, it may provide specific advice such as "reducing the torque by 20% would be optimal."

[0102] Users can instantly correct their actions based on feedback displayed on the glasses-type display. This shortens the learning curve and allows for rapid improvement of necessary skills. Feedback is provided not only visually but also audibly, enabling multi-sensory training.

[0103] As a concrete example, when using a robotic arm in the automobile assembly process, feedback is provided to ensure that parts are tightened efficiently without applying excessive force. An example of a prompt message generated by the AI ​​model is: "The robotic arm has detected excessive torque during screw tightening. Please generate optimal feedback to adjust the force."

[0104] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0105] Step 1:

[0106] The device records the user's actions in real time.

[0107] Input: User's movements during operation.

[0108] Data processing / calculation: Cameras and sensors are used to acquire video footage of the action and data related to that action (velocity, direction, etc.).

[0109] Output: Acquired operation data.

[0110] Specific operation: The sensor measures the speed and direction of movement and records it as video.

[0111] Step 2:

[0112] The terminal sends the recorded operation data to the server.

[0113] Input: Acquired behavioral data.

[0114] Data processing / calculation: Packet data and send it to the server using a communication protocol.

[0115] Output: Data packets received by the server.

[0116] Specific operation: Use Bluetooth or Wi-Fi to reliably transmit operation data to the server.

[0117] Step 3:

[0118] The server receives operational data and analyzes it using a generated AI model.

[0119] Input: The transmitted operation data packet.

[0120] Data processing / calculation: Using machine learning models, analyze velocity, direction, and force, and compare with historical data to generate optimal motion guidance.

[0121] Output: Feedback information for the user.

[0122] Specific actions: Using TensorFlow and PyTorch libraries, analyze data and create effective guidance based on the user's behavior history.

[0123] Step 4:

[0124] The server sends feedback generated based on the analysis results to the terminal.

[0125] Input: Instructional feedback generated by the server.

[0126] Data processing / calculation: Convert feedback into a format that can be visualized or audibly expressed, and send it to the terminal via a communication protocol.

[0127] Output: User-viewable feedback data.

[0128] Specific operation: Using streaming technology, feedback is displayed on the user's glasses-type display.

[0129] Step 5:

[0130] Users modify the behavior based on the feedback they receive.

[0131] Input: Feedback displayed on glasses-type display.

[0132] Data processing / calculation: Optimize and correct operations based on feedback.

[0133] Output: Improved performance.

[0134] Specific operation: Users can adjust the operation based on their feedback to achieve efficient work.

[0135] 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.

[0136] This invention combines a system that uses glasses-type displays to record the user's actions in real time, analyzes the data, and provides feedback, with an emotion engine. In this system, guidance and advice can be provided while considering not only the user's actions but also their emotions at that time.

[0137] The device uses cameras and sensors to capture the user's movements and record their movements and gestures with high precision. It also acquires information on speed and direction from the sensors, transmitting detailed movement data to the server. The emotion engine analyzes the user's emotions based on facial expressions captured by the camera, voice tone obtained from the voice sensor, and data from the heart rate monitor. The server aggregates and analyzes this data to recognize the user's emotional state.

[0138] On the server, information processing is performed by fusing behavioral data and emotional data. In particular, the results of the emotion engine's analysis are used to adjust the content of the feedback and how it is presented. For example, if the user is surprised, a calm, steady guide is provided, and if they are anxious, clearer hints are provided to alleviate the user's psychological state.

[0139] Users can receive visual or auditory feedback from their device and adjust their actions based on that feedback. For example, if a user practicing the piano becomes frustrated due to a mistake, the system, through emotion engine analysis, can understand this and provide empathetic advice such as, "Take a deep breath and try again slowly." In this way, appropriate approaches tailored to the user's emotional state can improve their overall practice experience.

[0140] This invention allows users to receive instruction that takes into account not only their physical movements but also their psychological state, enabling them to achieve more fulfilling training results. This system operates in various environments and contributes to improving the user's performance.

[0141] The following describes the processing flow.

[0142] Step 1:

[0143] The device activates its built-in camera and sensors as soon as the user begins activity, capturing the user's movements and facial expressions in real time. This allows for the simultaneous collection of movement and facial expression data.

[0144] Step 2:

[0145] The device transmits captured video data, including speed and direction data related to its movement, to the server. Simultaneously, the emotion engine analyzes facial expression data, voice tone, and heart rate to understand the user's emotional state.

[0146] Step 3:

[0147] The server analyzes the behavioral data sent from the terminal. AI processing is used for the analysis to extract current behavioral patterns, error frequency, accuracy, and other information.

[0148] Step 4:

[0149] The server evaluates the user's psychological state based on emotional data obtained from the emotion engine. Based on this evaluation, it further individualizes future feedback and plans support in a way that is psychologically optimal for the user.

[0150] Step 5:

[0151] The server integrates the results of behavioral analysis and emotion assessment to generate feedback for the user. For example, if it determines that relaxation is needed, it adjusts the wording to a gentler one, such as, "Calm down, try this next."

[0152] Step 6:

[0153] Feedback data is sent from the server to the terminal. The terminal receives this feedback and displays it in the user's field of view through the glasses-type display.

[0154] Step 7:

[0155] Users review the feedback provided and adjust their next actions and practice methods accordingly. By matching visual guidance with emotionally responsive feedback, users can practice efficiently and with less stress.

[0156] (Example 2)

[0157] 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".

[0158] Conventional motion recording and analysis systems focused solely on the user's physical movements, failing to provide feedback that took into account the user's emotional state. This made it difficult to provide appropriate guidance tailored to the user's psychological state, particularly in improving performance when experiencing stress or frustration. Furthermore, providing optimal feedback that considered the user's motion and emotional history remained a challenge.

[0159] 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.

[0160] In this invention, the server includes information processing means for analyzing recorded video and audio data and generating information that points out the user's behavior and emotional state; integrated analysis means for integrating action data and emotional data and generating feedback; and generation engine means for dynamically generating feedback according to the user's emotional state. This makes it possible to provide appropriate feedback according to the user's psychological state and improve the user's performance.

[0161] A "visual presentation device" is a device that records the user's actions and visually presents that information to the user.

[0162] "Information processing means" refers to a device or system that analyzes recorded video and audio data and generates information to identify the user's behavior and emotional state.

[0163] "Presentation control means" refers to a device or system that controls the presentation of generated information visually and aurally.

[0164] An "integrated analysis means" is a device or system that integrates motion data and emotional data and performs analysis to generate feedback based on the user's state.

[0165] "Generation engine means" refers to a device or program for dynamically generating feedback that corresponds to the user's emotional state.

[0166] A "detection device" is a device used to detect the speed and direction of a user's movements.

[0167] The present invention is a system implemented using a visual presentation device, information processing means, presentation control means, integrated analysis means, and generation engine means. A spectacle-type display is used as the visual presentation device, and the user's movements are recorded by a camera and sensors. This device also incorporates a detection device for detecting the speed and direction of the movements.

[0168] The terminal transmits the acquired video and audio data to the server. The server uses information processing tools to analyze this data and determine the user's behavior and emotional state. An emotion engine is used to analyze the emotional state, based on facial expression data, voice tone, and heart rate information. An integrated analysis tool fuses the motion data and emotional data to generate more precise feedback.

[0169] The generation engine dynamically generates feedback according to the user's psychological state, and this feedback is presented to the user visually or audibly by the presentation control means.

[0170] For example, if a user practicing the piano becomes frustrated with a section where they frequently make mistakes, the device sends this information to a server, which then generates feedback such as, "Take a deep breath and try again slowly." This feedback is presented to the user through a glasses-type display and audio output. In this way, the user can alleviate stress during practice and practice more efficiently.

[0171] The generative AI model plays a crucial role in generating user feedback. An example of a prompt is, "What advice would you offer if the user becomes frustrated during practice?" Based on this prompt, the AI ​​model generates optimal feedback to improve the user's experience.

[0172] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0173] Step 1:

[0174] The device activates a camera and sensors built into the glasses-type display to record the user's movements in real time. It acquires data on the user's movements, posture, and gestures as input. The output is high-precision digital data showing the user's movement patterns. This data is used for the next analysis step.

[0175] Step 2:

[0176] The device captures the user's facial expressions with a camera and acquires their voice tone using a voice sensor. It also uses a heart rate monitor to collect the user's biometric information. The inputs are the user's facial expressions, voice, and heart rate, and the output is emotional data that forms the basis for emotion judgment.

[0177] Step 3:

[0178] The terminal sends the behavioral and emotional data acquired in steps 1 and 2 to the server. The input is behavioral and emotional data, and the output is the secure transmission of data to the server. The data is transmitted using a secure communication protocol.

[0179] Step 4:

[0180] The server analyzes the received operational data using information processing tools. The input is operational data, and the output is an evaluation result indicating the accuracy and effectiveness of the user's actions. Advanced algorithms are used for this analysis.

[0181] Step 5:

[0182] The server analyzes emotional data using an emotion engine. The input is emotional data, and the output is an evaluation result indicating the user's emotional state (e.g., calm, surprised, irritated). An emotion recognition algorithm is used.

[0183] Step 6:

[0184] The server integrates behavioral data and emotional data using an integrated analysis mechanism. The input consists of evaluation results for behavioral data and emotional data, while the output is information indicating the overall user state. Appropriate feedback is generated based on this information.

[0185] Step 7:

[0186] The server dynamically generates feedback tailored to the user's psychological state using a generation engine. The input is integrated user state information, and the output is specific feedback in a format easily understood by the user. The feedback is generated using a generation AI model and prompt statements.

[0187] Step 8:

[0188] The terminal provides the user with feedback received from the server. Input is the feedback sent from the server, and output is a visual or auditory presentation to the user. The user can use this feedback to improve their behavior.

[0189] (Application Example 2)

[0190] 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".

[0191] The present invention aims to provide a system that can provide efficient and comfortable support by simultaneously analyzing the user's actions and emotions and providing feedback that takes into account the user's psychological state. In particular, in situations such as work and learning, it is necessary to maintain the user's concentration and motivation and reduce unnecessary stress.

[0192] 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.

[0193] In this invention, the server includes a display device means incorporating a camera and an emotion analysis device for recording the user's actions and emotions; a data processing means for analyzing the recorded video data and emotion data to identify the user's actions and generate emotion-based guidance information; and a display control means for multiplexing the generated guidance information on the display device. This enables appropriate feedback in accordance with the user's actions and emotions.

[0194] "User" refers to a person who uses the system in this invention to record and analyze their actions and emotions.

[0195] "Movement" is a concept that includes information about the physical movements performed by the user, as well as their speed and direction.

[0196] "Emotions" refer to the user's psychological state and are mental responses detected through facial expressions, voice, and other biometric information.

[0197] A "recording device" is a device that includes a camera and related sensors equipped to record the user's actions.

[0198] An "emotion analysis device" is a device used to analyze the emotional state of a user, and has the function of detecting emotions based on data such as voice, facial expressions, and heart rate.

[0199] "Display device means" refers to equipment for visually presenting information to the user, and includes glasses-type displays and monitors.

[0200] "Data processing means" refers to a computer or its components used to integrate and analyze behavioral data and emotional data acquired from the user.

[0201] "Display control means" refers to means that have the function of controlling the display of generated information to the user in an appropriate manner.

[0202] "Guidance information" refers to specific feedback generated by data processing tools, based on the user's actions and emotions, to advise or improve their behavior.

[0203] The system for implementing this invention mainly consists of an exhibition device incorporating a motion recording device and an emotion analysis device, and a data processing system connected thereto.

[0204] The server receives data from display devices such as smart glasses to acquire information about actions and emotions. Hardware used includes smart glasses equipped with imaging devices and sensors. Software includes a motion analysis engine, an emotion analysis engine, and a feedback generation module. The server analyzes this data and generates appropriate guidance information based on the user's behavior and emotional state. For example, if a worker feels fatigued, it can generate specific feedback such as, "It would be effective to do some light stretching between tasks."

[0205] The terminal presents instructional information generated based on the analysis results to the user visually or audibly. In this process, display control technology is required to ensure the information is placed appropriately.

[0206] Based on the feedback provided, users can take appropriate actions that correspond to their own movements and emotions. This makes it possible to improve work efficiency and learning effectiveness. The designed system provides support for both the psychological and physiological needs of people in factory and educational settings.

[0207] An example of a prompt to use with this generative AI model is: "Design a system that analyzes user behavior and emotions in real time and generates situation-appropriate feedback."

[0208] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0209] Step 1:

[0210] The device collects data on the user's movements and emotions through the camera and sensors built into the smart glasses. Inputs include video data from the camera, information on speed and direction from the sensors, and emotion data from the emotion analysis device. This data is transmitted to a server.

[0211] Step 2:

[0212] The server analyzes the received video data using a motion analysis engine to identify the user's motion patterns. The input consists of the video data and sensor data acquired in step 1. The output consists of speed, direction, and identified motion patterns related to the motion. During this process, specific characteristics of each motion are detected, quantified, and stored.

[0213] Step 3:

[0214] The server analyzes emotional data using an emotion analysis engine. Inputs include facial expression data, voice data, and biometric information such as heart rate. Outputs identify the user's emotional state as numerical values ​​or categories. Here, the user's stress and fatigue levels are quantified.

[0215] Step 4:

[0216] The server integrates the analyzed behavioral and emotional data and generates guidance information through data processing. The input consists of behavioral patterns and emotional states obtained in steps 2 and 3. The output is a feedback message best suited to the user's psychological and physiological state. Historical data is also used to generate specific advice and reminders.

[0217] Step 5:

[0218] The user receives feedback generated through the device, either visually or audibly. The input is the guidance information generated in step 4. The output is a specific action plan to support the user's behavior and improve their psychological state. Here, it is important that the feedback provided is clear and timely.

[0219] 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.

[0220] 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.

[0221] 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.

[0222] [Second Embodiment]

[0223] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0224] 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.

[0225] 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).

[0226] 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.

[0227] 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.

[0228] 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).

[0229] 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.

[0230] 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.

[0231] 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.

[0232] 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.

[0233] 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.

[0234] 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".

[0235] This invention provides a system that enables users to receive efficient and effective feedback during practice and training. This system overcomes the limitations of conventional training methods by recording and analyzing the user's movements and providing real-time, individually optimized instruction.

[0236] The device (equipped with glasses-type displays) captures the user's movements with high precision while they play musical instruments or participate in sports. The recording device incorporates multiple sensors, such as those measuring acceleration and angles, to capture detailed movements. Furthermore, this data is processed rapidly, minimizing delays before it is transmitted to the server.

[0237] The server receives data sent from the terminal and uses an AI algorithm to analyze the behavioral data in detail. During the analysis, the user's past behavioral history and skill level are also considered to determine the most effective teaching method. This generates specific and appropriate advice tailored to the user's current performance.

[0238] Users can modify their actions based on feedback displayed across multiple devices. For example, a user playing the piano might see specific instructions such as, "You should slow down the tempo in this section." This allows users to repeatedly adjust their actions under real-time guidance. Feedback is provided not only through visual guidelines but also through voice assistance, enabling users to practice in the most effective way using multiple senses.

[0239] As a concrete example, consider a scenario where a user is practicing their tennis swing. The device accurately records the user's hand movements and body posture, and the server analyzes this data to generate specific advice such as "finish your swing higher." This advice is communicated to the user in real time, and the user can incorporate and use this feedback. This allows the user to improve their skills at a faster pace than with traditional methods.

[0240] Thus, the present invention allows users to practice actions more efficiently and improve their skills in a short period of time.

[0241] The following describes the processing flow.

[0242] Step 1:

[0243] The device activates its built-in camera and sensors to record the user's movements in real time. This starts capturing video of the movements and various data points (acceleration, angle, etc.).

[0244] Step 2:

[0245] The terminal compresses the captured data using a dedicated algorithm and prepares it for transmission to the server. The data is divided into small units in a batch format, taking communication speed into consideration.

[0246] Step 3:

[0247] The server receives data sent from the terminal, verifies its integrity, and then passes it to the AI ​​processor. The processor applies an optimized algorithm to analyze the received data.

[0248] Step 4:

[0249] The server generates feedback on the user's actions based on the analyzed data. In doing so, it considers past behavioral history and set goals to create optimized advice.

[0250] Step 5:

[0251] The server packets the generated feedback and verifies the network configuration for low-latency transmission to the terminal. Then, it executes the transmission.

[0252] Step 6:

[0253] The terminal decodes the feedback received from the server and prepares it for display in the user's field of view. This involves managing display layers and adjusting the interface.

[0254] Step 7:

[0255] Users review feedback displayed on the device's glasses-type display and fine-tune their actions based on it. This feedback is provided in various forms, including text, graphical hints, and audio guidance, which users use to modify their behavior.

[0256] (Example 1)

[0257] 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."

[0258] Current practice and training methods have the challenge of not being able to quickly provide feedback that fully takes into account the individual skill level and past performance history of the user. As a result, users may experience slow performance improvement or continue with inefficient practice.

[0259] 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.

[0260] In this invention, the server includes a recording means for recording the user's actions, a data processing means for analyzing the recorded action data and generating instruction optimized for the user, and a display control means for transmitting the generated instruction information to a portable display device and presenting it to the user. This allows the user to receive specific and effective feedback on their actions in real time.

[0261] "Recording means" refers to a device that records the user's actions with high precision, and includes cameras and sensors, playing a role in acquiring motion data.

[0262] "Data processing means" refers to computer systems or software algorithms that analyze recorded motion data and generate instructional information optimized for the user.

[0263] "Display control means" refers to a mechanism or process for transmitting generated instructional information to a portable display device and presenting it to the user visually or audibly.

[0264] A "portable display device" is a device that is easy for the user to carry, and includes devices such as glasses-type displays that are used to display real-time feedback.

[0265] A "sensor" is a device that detects the acceleration and angle of movement, and its role is to collect data necessary for a detailed analysis of the user's movements.

[0266] This invention is a system designed to efficiently and effectively improve user performance. The system consists of the interaction of three parties: a terminal equipped with a glasses-type display, a server, and the user.

[0267] The device is designed to record the user's movements while they are playing a musical instrument or participating in sports. It has a built-in camera, accelerometer, and gyroscope, allowing it to acquire detailed data on their movements. For example, during tennis practice, the speed and angle of the swing are recorded in real time.

[0268] The server receives and analyzes the operation data transmitted from the terminal. Using a data processing method based on a generative AI model, it quickly analyzes the user's operation data and generates instructional information based on the analysis results. Because the analysis takes into account past operation history and the user's skill level, it can provide more individually optimized instruction. The generated information is processed by the server as concrete and actionable advice for the user.

[0269] The user receives feedback sent from the server via their device. This feedback is displayed visually within the user's field of view, and audio guidance is also provided. This feedback helps the user correct their actions in real time. For example, the user can learn specific directions for correcting their actions, such as "finish your swing higher."

[0270] As a concrete example, consider a scenario where a user plays the piano. The device records the user's hand and finger movements, and the server analyzes this data to generate advice such as, "You should slow down the tempo in this section." Based on this feedback, the user can improve their playing.

[0271] An example of a prompt to input into the generating AI model is: "Generate effective feedback based on user behavior data. Optimize the instruction content considering past behavior history."

[0272] This system provides users with an environment where they can receive immediate feedback and efficiently improve their own performance.

[0273] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0274] Step 1:

[0275] The device records the user's movements. It uses video and acceleration / angle data acquired by cameras and sensors as input. This data reflects the user's movements in detail and includes multidimensional motion information. Specifically, it records the movements of the hands and racket, as well as body posture, with high precision during a tennis swing. The output consists of recorded video data and measurement data from the sensors.

[0276] Step 2:

[0277] The terminal transmits the recorded data to the server. The input is the motion data generated in step 1. The data is transmitted to the server via wireless communication. Real-time functionality is maintained through rapid transmission. The output is the user's motion data received by the server.

[0278] Step 3:

[0279] The server analyzes the received operation data. The input data is the operation data transmitted from the terminal. The server analyzes the data in detail using a generative AI model. In this process, the user's past operation history and skill level are also considered, and calculations are performed to generate optimal guidance information. As specific data processing, the average speed of the operation and changes in angles are analyzed. The output is guidance information suitable for the user.

[0280] Step 4:

[0281] The server generates feedback based on the analysis results. The input is the analysis result of Step 3, and based on this, effective guidance advice is constructed. The generative AI model determines the feedback content most suitable for the user's technical level. The output is specific and individually optimized guidance information. [[ID=I0]]

[0282] Step 5: <I

[0283] The terminal presents the guidance information received from the server to the user. The input is the guidance information sent from the server. The terminal presents the information to the user through vision and hearing, and prompts the user to correct the operation. As a specific operation, guidance content such as "Raise the end position of the swing higher" is visually displayed on the glasses-type display. The output is feedback in a form that the user can visually recognize.

[0284] Step 6:

[0285] The user corrects their own operation based on the presented feedback. The input is the feedback received from the terminal. Based on this, the user adjusts their practice and operations to improve their skills. The output is the movement reflecting the corrected operation and starting matters. As specific operations, it includes executing the indicated points and re-evaluating the operation. ]

[0286] (Application Example 1)

[0287] 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."

[0288] Robot motion training in factories is crucial for improving on-site efficiency. However, conventional robot motion optimization methods lack the ability to provide real-time feedback and refine movements, resulting in limited productivity. This invention aims to significantly improve factory efficiency by measuring and analyzing movements in real time and providing immediate, optimal motion guidance.

[0289] 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.

[0290] In this invention, the server includes a glasses-type display means with a built-in camera for recording the user's movements, an information processing means for analyzing the recorded video data and generating information that points out the user's actions, a display control means for multiplexing the generated information on the glasses-type display, and a feedback means for monitoring the movements in real time and providing efficient movement guidance based on the analysis results. This makes it possible for the robot to immediately correct its movements and achieve optimal performance.

[0291] "User" refers to the entity that uses the system to perform training or tasks.

[0292] "Recording device" is a general term for a device that includes sensors and cameras for recording the actions of a user.

[0293] "Eyeglass-type display means" refers to a head-mounted display or smart glasses that allows the wearer to view visual information in real time.

[0294] "Video data" refers to video information about the user's actions recorded by a recording device.

[0295] "Information processing means" refers to a computer program that analyzes recorded video data and generates necessary feedback and guidance.

[0296] "Display control means" refers to a control program for appropriately displaying the generated instructional information on the glasses-type display.

[0297] A "sensor" refers to a physical device used to measure the speed, direction, and force of a user's movements.

[0298] "Feedback methods" refer to systems that provide users with guidance and corrective information based on analysis results in real time.

[0299] "Analysis results" refer to the output after data analysis obtained by information processing means, and include evaluations and guidance regarding the user's actions.

[0300] "Operation history" refers to a collection of data that shows records and trends of the user's actions in the past.

[0301] In order to implement this invention, multiple hardware and software components must work together. The system primarily consists of interactions between servers, terminals, and users.

[0302] The device features a glasses-type display for recording the user's movements with high precision. This display incorporates a camera, accelerometer, gyroscope, and other sensors to acquire user movement data in real time. For example, it can record the movements of a robotic arm or the movements of fingers during factory work.

[0303] The server receives the operation data transmitted from the terminal and analyzes the data using a generative AI model. For this analysis, libraries such as Python's TensorFlow and PyTorch are used to calculate the speed, direction, force, etc. of the operation, and generate detailed feedback taking into account the user's past operation history. This feedback becomes important information for achieving efficient operations. For example, specific advice such as "Reducing torque by 20% is optimal" may be given.

[0304] Based on the feedback displayed on the glasses-type display, the user can immediately correct their operation. This shortens the learning curve and enables rapid improvement of the required skills. The feedback is provided not only as visual information but also by voice, enabling multi-sensory training.

[0305] As a specific example, when using a robotic arm in an automobile assembly process, feedback is provided to enable efficient tightening of parts without applying excessive force. An example of a prompt sentence by the generative AI model is something like "The robotic arm detected excessive torque during the screw tightening operation. Please generate the optimal feedback for adjusting the force."

[0306] The flow of a specific process in Application Example 1 will be described using FIG. 12.

[0307] Step 1:

[0308] The terminal records the user's operation in real time.

[0309] Input: Movements of the user during operation.

[0310] Data processing / Calculation: Obtain video of the operation and data related to the operation (speed, direction, etc.) using a camera and sensors. <00,00978>

[0311] Output: The obtained operation data.

[0312] Specific operation: The sensor measures the speed and direction of movement and records it as video.

[0313] Step 2:

[0314] The terminal sends the recorded operation data to the server.

[0315] Input: Acquired behavioral data.

[0316] Data processing / calculation: Packet data and send it to the server using a communication protocol.

[0317] Output: Data packets received by the server.

[0318] Specific operation: Use Bluetooth or Wi-Fi to reliably transmit operation data to the server.

[0319] Step 3:

[0320] The server receives operational data and analyzes it using a generated AI model.

[0321] Input: The transmitted operation data packet.

[0322] Data processing / calculation: Using machine learning models, analyze velocity, direction, and force, and compare with historical data to generate optimal motion guidance.

[0323] Output: Feedback information for the user.

[0324] Specific actions: Using TensorFlow and PyTorch libraries, analyze data and create effective guidance based on the user's behavior history.

[0325] Step 4:

[0326] The server sends feedback generated based on the analysis results to the terminal.

[0327] Input: Instructional feedback generated by the server.

[0328] Data processing / calculation: Convert feedback into a format that can be visualized or audibly expressed, and send it to the terminal via a communication protocol.

[0329] Output: User-viewable feedback data.

[0330] Specific operation: Using streaming technology, feedback is displayed on the user's glasses-type display.

[0331] Step 5:

[0332] Users modify the behavior based on the feedback they receive.

[0333] Input: Feedback displayed on glasses-type display.

[0334] Data processing / calculation: Optimize and correct operations based on feedback.

[0335] Output: Improved performance.

[0336] Specific operation: Users can adjust the operation based on their feedback to achieve efficient work.

[0337] 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.

[0338] This invention combines a system that uses glasses-type displays to record the user's actions in real time, analyzes the data, and provides feedback, with an emotion engine. In this system, guidance and advice can be provided while considering not only the user's actions but also their emotions at that time.

[0339] The device uses cameras and sensors to capture the user's movements and record their movements and gestures with high precision. It also acquires information on speed and direction from the sensors, transmitting detailed movement data to the server. The emotion engine analyzes the user's emotions based on facial expressions captured by the camera, voice tone obtained from the voice sensor, and data from the heart rate monitor. The server aggregates and analyzes this data to recognize the user's emotional state.

[0340] On the server, information processing is performed by fusing behavioral data and emotional data. In particular, the results of the emotion engine's analysis are used to adjust the content of the feedback and how it is presented. For example, if the user is surprised, a calm, steady guide is provided, and if they are anxious, clearer hints are provided to alleviate the user's psychological state.

[0341] Users can receive visual or auditory feedback from their device and adjust their actions based on that feedback. For example, if a user practicing the piano becomes frustrated due to a mistake, the system, through emotion engine analysis, can understand this and provide empathetic advice such as, "Take a deep breath and try again slowly." In this way, appropriate approaches tailored to the user's emotional state can improve their overall practice experience.

[0342] This invention allows users to receive instruction that takes into account not only their physical movements but also their psychological state, enabling them to achieve more fulfilling training results. This system operates in various environments and contributes to improving the user's performance.

[0343] The following describes the processing flow.

[0344] Step 1:

[0345] The device activates its built-in camera and sensors as soon as the user begins activity, capturing the user's movements and facial expressions in real time. This allows for the simultaneous collection of movement and facial expression data.

[0346] Step 2:

[0347] The device transmits captured video data, including speed and direction data related to its movement, to the server. Simultaneously, the emotion engine analyzes facial expression data, voice tone, and heart rate to understand the user's emotional state.

[0348] Step 3:

[0349] The server analyzes the behavioral data sent from the terminal. AI processing is used for the analysis to extract current behavioral patterns, error frequency, accuracy, and other information.

[0350] Step 4:

[0351] The server evaluates the user's psychological state based on emotional data obtained from the emotion engine. Based on this evaluation, it further individualizes future feedback and plans support in a way that is psychologically optimal for the user.

[0352] Step 5:

[0353] The server integrates the results of behavioral analysis and emotion assessment to generate feedback for the user. For example, if it determines that relaxation is needed, it adjusts the wording to a gentler one, such as, "Calm down, try this next."

[0354] Step 6:

[0355] Feedback data is sent from the server to the terminal. The terminal receives this feedback and displays it in the user's field of view through the glasses-type display.

[0356] Step 7:

[0357] Users review the feedback provided and adjust their next actions and practice methods accordingly. By matching visual guidance with emotionally responsive feedback, users can practice efficiently and with less stress.

[0358] (Example 2)

[0359] 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".

[0360] Conventional motion recording and analysis systems focused solely on the user's physical movements, failing to provide feedback that took into account the user's emotional state. This made it difficult to provide appropriate guidance tailored to the user's psychological state, particularly in improving performance when experiencing stress or frustration. Furthermore, providing optimal feedback that considered the user's motion and emotional history remained a challenge.

[0361] 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.

[0362] In this invention, the server includes information processing means for analyzing recorded video and audio data and generating information that points out the user's behavior and emotional state; integrated analysis means for integrating action data and emotional data and generating feedback; and generation engine means for dynamically generating feedback according to the user's emotional state. This makes it possible to provide appropriate feedback according to the user's psychological state and improve the user's performance.

[0363] A "visual presentation device" is a device that records the user's actions and visually presents that information to the user.

[0364] "Information processing means" refers to a device or system that analyzes recorded video and audio data and generates information to identify the user's behavior and emotional state.

[0365] "Presentation control means" refers to a device or system that controls the presentation of generated information visually and aurally.

[0366] An "integrated analysis means" is a device or system that integrates motion data and emotional data and performs analysis to generate feedback based on the user's state.

[0367] "Generation engine means" refers to a device or program for dynamically generating feedback that corresponds to the user's emotional state.

[0368] A "detection device" is a device used to detect the speed and direction of a user's movements.

[0369] The present invention is a system implemented using a visual presentation device, information processing means, presentation control means, integrated analysis means, and generation engine means. A spectacle-type display is used as the visual presentation device, and the user's movements are recorded by a camera and sensors. This device also incorporates a detection device for detecting the speed and direction of the movements.

[0370] The terminal transmits the acquired video and audio data to the server. The server uses information processing tools to analyze this data and determine the user's behavior and emotional state. An emotion engine is used to analyze the emotional state, based on facial expression data, voice tone, and heart rate information. An integrated analysis tool fuses the motion data and emotional data to generate more precise feedback.

[0371] The generation engine dynamically generates feedback according to the user's psychological state, and this feedback is presented to the user visually or audibly by the presentation control means.

[0372] For example, if a user practicing the piano becomes frustrated with a section where they frequently make mistakes, the device sends this information to a server, which then generates feedback such as, "Take a deep breath and try again slowly." This feedback is presented to the user through a glasses-type display and audio output. In this way, the user can alleviate stress during practice and practice more efficiently.

[0373] The generative AI model plays a crucial role in generating user feedback. An example of a prompt is, "What advice would you offer if the user becomes frustrated during practice?" Based on this prompt, the AI ​​model generates optimal feedback to improve the user's experience.

[0374] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0375] Step 1:

[0376] The device activates a camera and sensors built into the glasses-type display to record the user's movements in real time. It acquires data on the user's movements, posture, and gestures as input. The output is high-precision digital data showing the user's movement patterns. This data is used for the next analysis step.

[0377] Step 2:

[0378] The device captures the user's facial expressions with a camera and acquires their voice tone using a voice sensor. It also uses a heart rate monitor to collect the user's biometric information. The inputs are the user's facial expressions, voice, and heart rate, and the output is emotional data that forms the basis for emotion judgment.

[0379] Step 3:

[0380] The terminal sends the behavioral and emotional data acquired in steps 1 and 2 to the server. The input is behavioral and emotional data, and the output is the secure transmission of data to the server. The data is transmitted using a secure communication protocol.

[0381] Step 4:

[0382] The server analyzes the received operational data using information processing tools. The input is operational data, and the output is an evaluation result indicating the accuracy and effectiveness of the user's actions. Advanced algorithms are used for this analysis.

[0383] Step 5:

[0384] The server analyzes emotional data using an emotion engine. The input is emotional data, and the output is an evaluation result indicating the user's emotional state (e.g., calm, surprised, irritated). An emotion recognition algorithm is used.

[0385] Step 6:

[0386] The server integrates behavioral data and emotional data using an integrated analysis mechanism. The input consists of evaluation results for behavioral data and emotional data, while the output is information indicating the overall user state. Appropriate feedback is generated based on this information.

[0387] Step 7:

[0388] The server dynamically generates feedback tailored to the user's psychological state using a generation engine. The input is integrated user state information, and the output is specific feedback in a format easily understood by the user. The feedback is generated using a generation AI model and prompt statements.

[0389] Step 8:

[0390] The terminal provides the user with feedback received from the server. Input is the feedback sent from the server, and output is a visual or auditory presentation to the user. The user can use this feedback to improve their behavior.

[0391] (Application Example 2)

[0392] 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."

[0393] The present invention aims to provide a system that can provide efficient and comfortable support by simultaneously analyzing the user's actions and emotions and providing feedback that takes into account the user's psychological state. In particular, in situations such as work and learning, it is necessary to maintain the user's concentration and motivation and reduce unnecessary stress.

[0394] 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.

[0395] In this invention, the server includes a display device means incorporating a camera and an emotion analysis device for recording the user's actions and emotions; a data processing means for analyzing the recorded video data and emotion data to identify the user's actions and generate emotion-based guidance information; and a display control means for multiplexing the generated guidance information on the display device. This enables appropriate feedback in accordance with the user's actions and emotions.

[0396] "User" refers to a person who uses the system in this invention to record and analyze their actions and emotions.

[0397] "Movement" is a concept that includes information about the physical movements performed by the user, as well as their speed and direction.

[0398] "Emotions" refer to the user's psychological state and are mental responses detected through facial expressions, voice, and other biometric information.

[0399] A "recording device" is a device that includes a camera and related sensors equipped to record the user's actions.

[0400] An "emotion analysis device" is a device used to analyze the emotional state of a user, and has the function of detecting emotions based on data such as voice, facial expressions, and heart rate.

[0401] "Display device means" refers to equipment for visually presenting information to the user, and includes glasses-type displays and monitors.

[0402] "Data processing means" refers to a computer or its components used to integrate and analyze behavioral data and emotional data acquired from the user.

[0403] "Display control means" refers to means that have the function of controlling the display of generated information to the user in an appropriate manner.

[0404] "Guidance information" refers to specific feedback generated by data processing tools, based on the user's actions and emotions, to advise or improve their behavior.

[0405] The system for implementing this invention mainly consists of an exhibition device incorporating a motion recording device and an emotion analysis device, and a data processing system connected thereto.

[0406] The server receives data from display devices such as smart glasses to acquire information about actions and emotions. Hardware used includes smart glasses equipped with imaging devices and sensors. Software includes a motion analysis engine, an emotion analysis engine, and a feedback generation module. The server analyzes this data and generates appropriate guidance information based on the user's behavior and emotional state. For example, if a worker feels fatigued, it can generate specific feedback such as, "It would be effective to do some light stretching between tasks."

[0407] The terminal presents instructional information generated based on the analysis results to the user visually or audibly. In this process, display control technology is required to ensure the information is placed appropriately.

[0408] Based on the feedback provided, users can take appropriate actions that correspond to their own movements and emotions. This makes it possible to improve work efficiency and learning effectiveness. The designed system provides support for both the psychological and physiological needs of people in factory and educational settings.

[0409] An example of a prompt to use with this generative AI model is: "Design a system that analyzes user behavior and emotions in real time and generates situation-appropriate feedback."

[0410] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0411] Step 1:

[0412] The device collects data on the user's movements and emotions through the camera and sensors built into the smart glasses. Inputs include video data from the camera, information on speed and direction from the sensors, and emotion data from the emotion analysis device. This data is transmitted to a server.

[0413] Step 2:

[0414] The server analyzes the received video data using a motion analysis engine to identify the user's motion patterns. The input consists of the video data and sensor data acquired in step 1. The output consists of speed, direction, and identified motion patterns related to the motion. During this process, specific characteristics of each motion are detected, quantified, and stored.

[0415] Step 3:

[0416] The server analyzes emotional data using an emotion analysis engine. Inputs include facial expression data, voice data, and biometric information such as heart rate. Outputs identify the user's emotional state as numerical values ​​or categories. Here, the user's stress and fatigue levels are quantified.

[0417] Step 4:

[0418] The server integrates the analyzed behavioral and emotional data and generates guidance information through data processing. The input consists of behavioral patterns and emotional states obtained in steps 2 and 3. The output is a feedback message best suited to the user's psychological and physiological state. Historical data is also used to generate specific advice and reminders.

[0419] Step 5:

[0420] The user receives feedback generated through the device, either visually or audibly. The input is the guidance information generated in step 4. The output is a specific action plan to support the user's behavior and improve their psychological state. Here, it is important that the feedback provided is clear and timely.

[0421] 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.

[0422] 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.

[0423] 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.

[0424] [Third Embodiment]

[0425] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0426] 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.

[0427] 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).

[0428] 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.

[0429] 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.

[0430] 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).

[0431] 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.

[0432] 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.

[0433] 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.

[0434] 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.

[0435] 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.

[0436] 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".

[0437] This invention provides a system that enables users to receive efficient and effective feedback during practice and training. This system overcomes the limitations of conventional training methods by recording and analyzing the user's movements and providing real-time, individually optimized instruction.

[0438] The device (equipped with glasses-type displays) captures the user's movements with high precision while they play musical instruments or participate in sports. The recording device incorporates multiple sensors, such as those measuring acceleration and angles, to capture detailed movements. Furthermore, this data is processed rapidly, minimizing delays before it is transmitted to the server.

[0439] The server receives data sent from the terminal and uses an AI algorithm to analyze the behavioral data in detail. During the analysis, the user's past behavioral history and skill level are also considered to determine the most effective teaching method. This generates specific and appropriate advice tailored to the user's current performance.

[0440] Users can modify their actions based on feedback displayed across multiple devices. For example, a user playing the piano might see specific instructions such as, "You should slow down the tempo in this section." This allows users to repeatedly adjust their actions under real-time guidance. Feedback is provided not only through visual guidelines but also through voice assistance, enabling users to practice in the most effective way using multiple senses.

[0441] As a concrete example, consider a scenario where a user is practicing their tennis swing. The device accurately records the user's hand movements and body posture, and the server analyzes this data to generate specific advice such as "finish your swing higher." This advice is communicated to the user in real time, and the user can incorporate and use this feedback. This allows the user to improve their skills at a faster pace than with traditional methods.

[0442] Thus, the present invention allows users to practice actions more efficiently and improve their skills in a short period of time.

[0443] The following describes the processing flow.

[0444] Step 1:

[0445] The device activates its built-in camera and sensors to record the user's movements in real time. This starts capturing video of the movements and various data points (acceleration, angle, etc.).

[0446] Step 2:

[0447] The terminal compresses the captured data using a dedicated algorithm and prepares it for transmission to the server. The data is divided into small units in a batch format, taking communication speed into consideration.

[0448] Step 3:

[0449] The server receives data sent from the terminal, verifies its integrity, and then passes it to the AI ​​processor. The processor applies an optimized algorithm to analyze the received data.

[0450] Step 4:

[0451] The server generates feedback on the user's actions based on the analyzed data. In doing so, it considers past behavioral history and set goals to create optimized advice.

[0452] Step 5:

[0453] The server packets the generated feedback and verifies the network configuration for low-latency transmission to the terminal. Then, it executes the transmission.

[0454] Step 6:

[0455] The terminal decodes the feedback received from the server and prepares it for display in the user's field of view. This involves managing display layers and adjusting the interface.

[0456] Step 7:

[0457] Users review feedback displayed on the device's glasses-type display and fine-tune their actions based on it. This feedback is provided in various forms, including text, graphical hints, and audio guidance, which users use to modify their behavior.

[0458] (Example 1)

[0459] 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."

[0460] Current practice and training methods have the challenge of not being able to quickly provide feedback that fully takes into account the individual skill level and past performance history of the user. As a result, users may experience slow performance improvement or continue with inefficient practice.

[0461] 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.

[0462] In this invention, the server includes a recording means for recording the user's actions, a data processing means for analyzing the recorded action data and generating instruction optimized for the user, and a display control means for transmitting the generated instruction information to a portable display device and presenting it to the user. This allows the user to receive specific and effective feedback on their actions in real time.

[0463] "Recording means" refers to a device that records the user's actions with high precision, and includes cameras and sensors, playing a role in acquiring motion data.

[0464] "Data processing means" refers to computer systems or software algorithms that analyze recorded motion data and generate instructional information optimized for the user.

[0465] "Display control means" refers to a mechanism or process for transmitting generated instructional information to a portable display device and presenting it to the user visually or audibly.

[0466] A "portable display device" is a device that is easy for the user to carry, and includes devices such as glasses-type displays that are used to display real-time feedback.

[0467] A "sensor" is a device that detects the acceleration and angle of movement, and its role is to collect data necessary for a detailed analysis of the user's movements.

[0468] This invention is a system designed to efficiently and effectively improve user performance. The system consists of the interaction of three parties: a terminal equipped with a glasses-type display, a server, and the user.

[0469] The device is designed to record the user's movements while they are playing a musical instrument or participating in sports. It has a built-in camera, accelerometer, and gyroscope, allowing it to acquire detailed data on their movements. For example, during tennis practice, the speed and angle of the swing are recorded in real time.

[0470] The server receives and analyzes the operation data transmitted from the terminal. Using a data processing method based on a generative AI model, it quickly analyzes the user's operation data and generates instructional information based on the analysis results. Because the analysis takes into account past operation history and the user's skill level, it can provide more individually optimized instruction. The generated information is processed by the server as concrete and actionable advice for the user.

[0471] The user receives feedback sent from the server via their device. This feedback is displayed visually within the user's field of view, and audio guidance is also provided. This feedback helps the user correct their actions in real time. For example, the user can learn specific directions for correcting their actions, such as "finish your swing higher."

[0472] As a concrete example, consider a scenario where a user plays the piano. The device records the user's hand and finger movements, and the server analyzes this data to generate advice such as, "You should slow down the tempo in this section." Based on this feedback, the user can improve their playing.

[0473] An example of a prompt to input into the generating AI model is: "Generate effective feedback based on user behavior data. Optimize the instruction content considering past behavior history."

[0474] This system provides users with an environment where they can receive immediate feedback and efficiently improve their own performance.

[0475] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0476] Step 1:

[0477] The device records the user's movements. It uses video and acceleration / angle data acquired by cameras and sensors as input. This data reflects the user's movements in detail and includes multidimensional motion information. Specifically, it records the movements of the hands and racket, as well as body posture, with high precision during a tennis swing. The output consists of recorded video data and measurement data from the sensors.

[0478] Step 2:

[0479] The terminal transmits the recorded data to the server. The input is the motion data generated in step 1. The data is transmitted to the server via wireless communication. Real-time functionality is maintained through rapid transmission. The output is the user's motion data received by the server.

[0480] Step 3:

[0481] The server analyzes the received motion data. The input data is motion data sent from the terminal. The server uses a generative AI model to analyze the data in detail. In this process, it also considers the user's past motion history and skill level, and performs calculations to generate optimal instruction information. Specifically, the data is processed by analyzing the average speed and angle changes of the motion. The output is instruction information tailored to the user.

[0482] Step 4:

[0483] The server generates feedback based on the analysis results. The input is the analysis results from step 3, which are used to construct effective guidance advice. The generating AI model determines the feedback content that is best suited to the user's skill level. The output is specific and individually optimized guidance information.

[0484] Step 5:

[0485] The terminal displays instructional information received from the server to the user. The input is instructional information sent from the server. The terminal presents information to the user through sight and sound, prompting corrections to their movements. Specifically, the glasses-type display visually shows instructional content such as "finish your swing higher." The output is feedback in a form that the user can see.

[0486] Step 6:

[0487] The user modifies their actions based on the feedback provided. The input is the feedback received from the device. Based on this, the user adjusts their practice and actions to improve their skills. The output is the movement reflecting the modified actions and starting points. Specific actions include executing instructed points and re-evaluating the actions.

[0488] (Application Example 1)

[0489] 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."

[0490] Robot motion training in factories is crucial for improving on-site efficiency. However, conventional robot motion optimization methods lack the ability to provide real-time feedback and refine movements, resulting in limited productivity. This invention aims to significantly improve factory efficiency by measuring and analyzing movements in real time and providing immediate, optimal motion guidance.

[0491] 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.

[0492] In this invention, the server includes a glasses-type display means with a built-in camera for recording the user's movements, an information processing means for analyzing the recorded video data and generating information that points out the user's actions, a display control means for multiplexing the generated information on the glasses-type display, and a feedback means for monitoring the movements in real time and providing efficient movement guidance based on the analysis results. This makes it possible for the robot to immediately correct its movements and achieve optimal performance.

[0493] "User" refers to the entity that uses the system to perform training or tasks.

[0494] "Recording device" is a general term for a device that includes sensors and cameras for recording the actions of a user.

[0495] "Eyeglass-type display means" refers to a head-mounted display or smart glasses that allows the wearer to view visual information in real time.

[0496] "Video data" refers to video information about the user's actions recorded by a recording device.

[0497] "Information processing means" refers to a computer program that analyzes recorded video data and generates necessary feedback and guidance.

[0498] "Display control means" refers to a control program for appropriately displaying the generated instructional information on the glasses-type display.

[0499] A "sensor" refers to a physical device used to measure the speed, direction, and force of a user's movements.

[0500] "Feedback methods" refer to systems that provide users with guidance and corrective information based on analysis results in real time.

[0501] "Analysis results" refer to the output after data analysis obtained by information processing means, and include evaluations and guidance regarding the user's actions.

[0502] "Operation history" refers to a collection of data that shows records and trends of the user's actions in the past.

[0503] In order to implement this invention, multiple hardware and software components must work together. The system primarily consists of interactions between servers, terminals, and users.

[0504] The device features a glasses-type display for recording the user's movements with high precision. This display incorporates a camera, accelerometer, gyroscope, and other sensors to acquire user movement data in real time. For example, it can record the movements of a robotic arm or the movements of fingers during factory work.

[0505] The server receives motion data sent from the terminal and analyzes the data using a generated AI model. This analysis uses libraries such as Python's TensorFlow and PyTorch to calculate the speed, direction, and force of the motion, and generates detailed feedback that also takes into account the user's past motion history. This feedback provides important information for achieving efficient operation. For example, it may provide specific advice such as, "Reducing the torque by 20% would be optimal."

[0506] Users can instantly correct their actions based on feedback displayed on the glasses-type display. This shortens the learning curve and allows for rapid improvement of necessary skills. Feedback is provided not only visually but also audibly, enabling multi-sensory training.

[0507] As a concrete example, when using a robotic arm in the automobile assembly process, feedback is provided to ensure that parts are tightened efficiently without applying excessive force. An example of a prompt message generated by the AI ​​model is: "The robotic arm has detected excessive torque during screw tightening. Please generate optimal feedback to adjust the force."

[0508] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0509] Step 1:

[0510] The device records the user's actions in real time.

[0511] Input: User's movements during operation.

[0512] Data processing / calculation: Cameras and sensors are used to acquire video footage of the action and data related to that action (velocity, direction, etc.).

[0513] Output: Acquired operation data.

[0514] Specific operation: The sensor measures the speed and direction of movement and records it as video.

[0515] Step 2:

[0516] The terminal sends the recorded operation data to the server.

[0517] Input: Acquired behavioral data.

[0518] Data processing / calculation: Packet data and send it to the server using a communication protocol.

[0519] Output: Data packets received by the server.

[0520] Specific operation: Use Bluetooth or Wi-Fi to reliably transmit operation data to the server.

[0521] Step 3:

[0522] The server receives operational data and analyzes it using a generated AI model.

[0523] Input: The transmitted operation data packet.

[0524] Data processing / calculation: Using machine learning models, analyze velocity, direction, and force, and compare with historical data to generate optimal motion guidance.

[0525] Output: Feedback information for the user.

[0526] Specific actions: Using TensorFlow and PyTorch libraries, analyze data and create effective guidance based on the user's behavior history.

[0527] Step 4:

[0528] The server sends feedback generated based on the analysis results to the terminal.

[0529] Input: Instructional feedback generated by the server.

[0530] Data processing / calculation: Convert feedback into a format that can be visualized or audibly expressed, and send it to the terminal via a communication protocol.

[0531] Output: User-viewable feedback data.

[0532] Specific operation: Using streaming technology, feedback is displayed on the user's glasses-type display.

[0533] Step 5:

[0534] Users modify the behavior based on the feedback they receive.

[0535] Input: Feedback displayed on glasses-type display.

[0536] Data processing / calculation: Optimize and correct operations based on feedback.

[0537] Output: Improved performance.

[0538] Specific operation: Users can adjust the operation based on their feedback to achieve efficient work.

[0539] 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.

[0540] This invention combines a system that uses glasses-type displays to record the user's actions in real time, analyzes the data, and provides feedback, with an emotion engine. In this system, guidance and advice can be provided while considering not only the user's actions but also their emotions at that time.

[0541] The device uses cameras and sensors to capture the user's movements and record their movements and gestures with high precision. It also acquires information on speed and direction from the sensors, transmitting detailed movement data to the server. The emotion engine analyzes the user's emotions based on facial expressions captured by the camera, voice tone obtained from the voice sensor, and data from the heart rate monitor. The server aggregates and analyzes this data to recognize the user's emotional state.

[0542] On the server, information processing is performed by fusing behavioral data and emotional data. In particular, the results of the emotion engine's analysis are used to adjust the content of the feedback and how it is presented. For example, if the user is surprised, a calm, steady guide is provided, and if they are anxious, clearer hints are provided to alleviate the user's psychological state.

[0543] Users can receive visual or auditory feedback from their device and adjust their actions based on that feedback. For example, if a user practicing the piano becomes frustrated due to a mistake, the system, through emotion engine analysis, can understand this and provide empathetic advice such as, "Take a deep breath and try again slowly." In this way, appropriate approaches tailored to the user's emotional state can improve their overall practice experience.

[0544] This invention allows users to receive instruction that takes into account not only their physical movements but also their psychological state, enabling them to achieve more fulfilling training results. This system operates in various environments and contributes to improving the user's performance.

[0545] The following describes the processing flow.

[0546] Step 1:

[0547] The device activates its built-in camera and sensors as soon as the user begins activity, capturing the user's movements and facial expressions in real time. This allows for the simultaneous collection of movement and facial expression data.

[0548] Step 2:

[0549] The device transmits captured video data, including speed and direction data related to its movement, to the server. Simultaneously, the emotion engine analyzes facial expression data, voice tone, and heart rate to understand the user's emotional state.

[0550] Step 3:

[0551] The server analyzes the behavioral data sent from the terminal. AI processing is used for the analysis to extract current behavioral patterns, error frequency, accuracy, and other information.

[0552] Step 4:

[0553] The server evaluates the user's psychological state based on emotional data obtained from the emotion engine. Based on this evaluation, it further individualizes future feedback and plans support in a way that is psychologically optimal for the user.

[0554] Step 5:

[0555] The server integrates the results of behavioral analysis and emotion assessment to generate feedback for the user. For example, if it determines that relaxation is needed, it adjusts the wording to a gentler one, such as, "Calm down, try this next."

[0556] Step 6:

[0557] Feedback data is sent from the server to the terminal. The terminal receives this feedback and displays it in the user's field of view through the glasses-type display.

[0558] Step 7:

[0559] Users review the feedback provided and adjust their next actions and practice methods accordingly. By matching visual guidance with emotionally responsive feedback, users can practice efficiently and with less stress.

[0560] (Example 2)

[0561] 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."

[0562] Conventional motion recording and analysis systems focused solely on the user's physical movements, failing to provide feedback that took into account the user's emotional state. This made it difficult to provide appropriate guidance tailored to the user's psychological state, particularly in improving performance when experiencing stress or frustration. Furthermore, providing optimal feedback that considered the user's motion and emotional history remained a challenge.

[0563] 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.

[0564] In this invention, the server includes information processing means for analyzing recorded video and audio data and generating information that points out the user's behavior and emotional state; integrated analysis means for integrating action data and emotional data and generating feedback; and generation engine means for dynamically generating feedback according to the user's emotional state. This makes it possible to provide appropriate feedback according to the user's psychological state and improve the user's performance.

[0565] A "visual presentation device" is a device that records the user's actions and visually presents that information to the user.

[0566] "Information processing means" refers to a device or system that analyzes recorded video and audio data and generates information to identify the user's behavior and emotional state.

[0567] "Presentation control means" refers to a device or system that controls the presentation of generated information visually and aurally.

[0568] An "integrated analysis means" is a device or system that integrates motion data and emotional data and performs analysis to generate feedback based on the user's state.

[0569] "Generation engine means" refers to a device or program for dynamically generating feedback that corresponds to the user's emotional state.

[0570] A "detection device" is a device used to detect the speed and direction of a user's movements.

[0571] The present invention is a system implemented using a visual presentation device, information processing means, presentation control means, integrated analysis means, and generation engine means. A spectacle-type display is used as the visual presentation device, and the user's movements are recorded by a camera and sensors. This device also incorporates a detection device for detecting the speed and direction of the movements.

[0572] The terminal transmits the acquired video and audio data to the server. The server uses information processing tools to analyze this data and determine the user's behavior and emotional state. An emotion engine is used to analyze the emotional state, based on facial expression data, voice tone, and heart rate information. An integrated analysis tool fuses the motion data and emotional data to generate more precise feedback.

[0573] The generation engine dynamically generates feedback according to the user's psychological state, and this feedback is presented to the user visually or audibly by the presentation control means.

[0574] For example, if a user practicing the piano becomes frustrated with a section where they frequently make mistakes, the device sends this information to a server, which then generates feedback such as, "Take a deep breath and try again slowly." This feedback is presented to the user through a glasses-type display and audio output. In this way, the user can alleviate stress during practice and practice more efficiently.

[0575] The generative AI model plays a crucial role in generating user feedback. An example of a prompt is, "What advice would you offer if the user becomes frustrated during practice?" Based on this prompt, the AI ​​model generates optimal feedback to improve the user's experience.

[0576] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0577] Step 1:

[0578] The device activates a camera and sensors built into the glasses-type display to record the user's movements in real time. It acquires data on the user's movements, posture, and gestures as input. The output is high-precision digital data showing the user's movement patterns. This data is used for the next analysis step.

[0579] Step 2:

[0580] The device captures the user's facial expressions with a camera and acquires their voice tone using a voice sensor. It also uses a heart rate monitor to collect the user's biometric information. The inputs are the user's facial expressions, voice, and heart rate, and the output is emotional data that forms the basis for emotion judgment.

[0581] Step 3:

[0582] The terminal sends the behavioral and emotional data acquired in steps 1 and 2 to the server. The input is behavioral and emotional data, and the output is the secure transmission of data to the server. The data is transmitted using a secure communication protocol.

[0583] Step 4:

[0584] The server analyzes the received operational data using information processing tools. The input is operational data, and the output is an evaluation result indicating the accuracy and effectiveness of the user's actions. Advanced algorithms are used for this analysis.

[0585] Step 5:

[0586] The server analyzes emotional data using an emotion engine. The input is emotional data, and the output is an evaluation result indicating the user's emotional state (e.g., calm, surprised, irritated). An emotion recognition algorithm is used.

[0587] Step 6:

[0588] The server integrates behavioral data and emotional data using an integrated analysis mechanism. The input consists of evaluation results for behavioral data and emotional data, while the output is information indicating the overall user state. Appropriate feedback is generated based on this information.

[0589] Step 7:

[0590] The server dynamically generates feedback tailored to the user's psychological state using a generation engine. The input is integrated user state information, and the output is specific feedback in a format easily understood by the user. The feedback is generated using a generation AI model and prompt statements.

[0591] Step 8:

[0592] The terminal provides the user with feedback received from the server. Input is the feedback sent from the server, and output is a visual or auditory presentation to the user. The user can use this feedback to improve their behavior.

[0593] (Application Example 2)

[0594] 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."

[0595] The present invention aims to provide a system that can provide efficient and comfortable support by simultaneously analyzing the user's actions and emotions and providing feedback that takes into account the user's psychological state. In particular, in situations such as work and learning, it is necessary to maintain the user's concentration and motivation and reduce unnecessary stress.

[0596] 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.

[0597] In this invention, the server includes a display device means incorporating a camera and an emotion analysis device for recording the user's actions and emotions; a data processing means for analyzing the recorded video data and emotion data to identify the user's actions and generate emotion-based guidance information; and a display control means for multiplexing the generated guidance information on the display device. This enables appropriate feedback in accordance with the user's actions and emotions.

[0598] "User" refers to a person who uses the system in this invention to record and analyze their actions and emotions.

[0599] "Movement" is a concept that includes information about the physical movements performed by the user, as well as their speed and direction.

[0600] "Emotions" refer to the user's psychological state and are mental responses detected through facial expressions, voice, and other biometric information.

[0601] A "recording device" is a device that includes a camera and related sensors equipped to record the user's actions.

[0602] An "emotion analysis device" is a device used to analyze the emotional state of a user, and has the function of detecting emotions based on data such as voice, facial expressions, and heart rate.

[0603] "Display device means" refers to equipment for visually presenting information to the user, and includes glasses-type displays and monitors.

[0604] "Data processing means" refers to a computer or its components used to integrate and analyze behavioral data and emotional data acquired from the user.

[0605] "Display control means" refers to means that have the function of controlling the display of generated information to the user in an appropriate manner.

[0606] "Guidance information" refers to specific feedback generated by data processing tools, based on the user's actions and emotions, to advise or improve their behavior.

[0607] The system for implementing this invention mainly consists of an exhibition device incorporating a motion recording device and an emotion analysis device, and a data processing system connected thereto.

[0608] The server receives data from display devices such as smart glasses to acquire information about actions and emotions. Hardware used includes smart glasses equipped with imaging devices and sensors. Software includes a motion analysis engine, an emotion analysis engine, and a feedback generation module. The server analyzes this data and generates appropriate guidance information based on the user's behavior and emotional state. For example, if a worker feels fatigued, it can generate specific feedback such as, "It would be effective to do some light stretching between tasks."

[0609] The terminal presents instructional information generated based on the analysis results to the user visually or audibly. In this process, display control technology is required to ensure the information is placed appropriately.

[0610] Based on the feedback provided, users can take appropriate actions that correspond to their own movements and emotions. This makes it possible to improve work efficiency and learning effectiveness. The designed system provides support for both the psychological and physiological needs of people in factory and educational settings.

[0611] An example of a prompt to use with this generative AI model is: "Design a system that analyzes user behavior and emotions in real time and generates situation-appropriate feedback."

[0612] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0613] Step 1:

[0614] The device collects data on the user's movements and emotions through the camera and sensors built into the smart glasses. Inputs include video data from the camera, information on speed and direction from the sensors, and emotion data from the emotion analysis device. This data is transmitted to a server.

[0615] Step 2:

[0616] The server analyzes the received video data using a motion analysis engine to identify the user's motion patterns. The input consists of the video data and sensor data acquired in step 1. The output consists of speed, direction, and identified motion patterns related to the motion. During this process, specific characteristics of each motion are detected, quantified, and stored.

[0617] Step 3:

[0618] The server analyzes emotional data using an emotion analysis engine. Inputs include facial expression data, voice data, and biometric information such as heart rate. Outputs identify the user's emotional state as numerical values ​​or categories. Here, the user's stress and fatigue levels are quantified.

[0619] Step 4:

[0620] The server integrates the analyzed behavioral and emotional data and generates guidance information through data processing. The input consists of behavioral patterns and emotional states obtained in steps 2 and 3. The output is a feedback message best suited to the user's psychological and physiological state. Historical data is also used to generate specific advice and reminders.

[0621] Step 5:

[0622] The user receives feedback generated through the device, either visually or audibly. The input is the guidance information generated in step 4. The output is a specific action plan to support the user's behavior and improve their psychological state. Here, it is important that the feedback provided is clear and timely.

[0623] 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.

[0624] 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.

[0625] 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.

[0626] [Fourth Embodiment]

[0627] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0628] 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.

[0629] 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).

[0630] 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.

[0631] 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.

[0632] 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).

[0633] 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.

[0634] 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.

[0635] 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.

[0636] 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.

[0637] 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.

[0638] 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.

[0639] 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".

[0640] This invention provides a system that enables users to receive efficient and effective feedback during practice and training. This system overcomes the limitations of conventional training methods by recording and analyzing the user's movements and providing real-time, individually optimized instruction.

[0641] The device (equipped with glasses-type displays) captures the user's movements with high precision while they play musical instruments or participate in sports. The recording device incorporates multiple sensors, such as those measuring acceleration and angles, to capture detailed movements. Furthermore, this data is processed rapidly, minimizing delays before it is transmitted to the server.

[0642] The server receives data sent from the terminal and uses an AI algorithm to analyze the behavioral data in detail. During the analysis, the user's past behavioral history and skill level are also considered to determine the most effective teaching method. This generates specific and appropriate advice tailored to the user's current performance.

[0643] Users can modify their actions based on feedback displayed across multiple devices. For example, a user playing the piano might see specific instructions such as, "You should slow down the tempo in this section." This allows users to repeatedly adjust their actions under real-time guidance. Feedback is provided not only through visual guidelines but also through voice assistance, enabling users to practice in the most effective way using multiple senses.

[0644] As a concrete example, consider a scenario where a user is practicing their tennis swing. The device accurately records the user's hand movements and body posture, and the server analyzes this data to generate specific advice such as "finish your swing higher." This advice is communicated to the user in real time, and the user can incorporate and use this feedback. This allows the user to improve their skills at a faster pace than with traditional methods.

[0645] Thus, the present invention allows users to practice actions more efficiently and improve their skills in a short period of time.

[0646] The following describes the processing flow.

[0647] Step 1:

[0648] The device activates its built-in camera and sensors to record the user's movements in real time. This starts capturing video of the movements and various data points (acceleration, angle, etc.).

[0649] Step 2:

[0650] The terminal compresses the captured data using a dedicated algorithm and prepares it for transmission to the server. The data is divided into small units in a batch format, taking communication speed into consideration.

[0651] Step 3:

[0652] The server receives data sent from the terminal, verifies its integrity, and then passes it to the AI ​​processor. The processor applies an optimized algorithm to analyze the received data.

[0653] Step 4:

[0654] The server generates feedback on the user's actions based on the analyzed data. In doing so, it considers past behavioral history and set goals to create optimized advice.

[0655] Step 5:

[0656] The server packets the generated feedback and verifies the network configuration for low-latency transmission to the terminal. Then, it executes the transmission.

[0657] Step 6:

[0658] The terminal decodes the feedback received from the server and prepares it for display in the user's field of view. This involves managing display layers and adjusting the interface.

[0659] Step 7:

[0660] Users review feedback displayed on the device's glasses-type display and fine-tune their actions based on it. This feedback is provided in various forms, including text, graphical hints, and audio guidance, which users use to modify their behavior.

[0661] (Example 1)

[0662] 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".

[0663] Current practice and training methods have the challenge of not being able to quickly provide feedback that fully takes into account the individual skill level and past performance history of the user. As a result, users may experience slow performance improvement or continue with inefficient practice.

[0664] 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.

[0665] In this invention, the server includes a recording means for recording the user's actions, a data processing means for analyzing the recorded action data and generating instruction optimized for the user, and a display control means for transmitting the generated instruction information to a portable display device and presenting it to the user. This allows the user to receive specific and effective feedback on their actions in real time.

[0666] "Recording means" refers to a device that records the user's actions with high precision, and includes cameras and sensors, playing a role in acquiring motion data.

[0667] "Data processing means" refers to computer systems or software algorithms that analyze recorded motion data and generate instructional information optimized for the user.

[0668] "Display control means" refers to a mechanism or process for transmitting generated instructional information to a portable display device and presenting it to the user visually or audibly.

[0669] A "portable display device" is a device that is easy for the user to carry, and includes devices such as glasses-type displays that are used to display real-time feedback.

[0670] A "sensor" is a device that detects the acceleration and angle of movement, and its role is to collect data necessary for a detailed analysis of the user's movements.

[0671] This invention is a system designed to efficiently and effectively improve user performance. The system consists of the interaction of three parties: a terminal equipped with a glasses-type display, a server, and the user.

[0672] The device is designed to record the user's movements while they are playing a musical instrument or participating in sports. It has a built-in camera, accelerometer, and gyroscope, allowing it to acquire detailed data on their movements. For example, during tennis practice, the speed and angle of the swing are recorded in real time.

[0673] The server receives and analyzes the operation data transmitted from the terminal. Using a data processing method based on a generative AI model, it quickly analyzes the user's operation data and generates instructional information based on the analysis results. Because the analysis takes into account past operation history and the user's skill level, it can provide more individually optimized instruction. The generated information is processed by the server as concrete and actionable advice for the user.

[0674] The user receives feedback sent from the server via their device. This feedback is displayed visually within the user's field of view, and audio guidance is also provided. This feedback helps the user correct their actions in real time. For example, the user can learn specific directions for correcting their actions, such as "finish your swing higher."

[0675] As a concrete example, consider a scenario where a user plays the piano. The device records the user's hand and finger movements, and the server analyzes this data to generate advice such as, "You should slow down the tempo in this section." Based on this feedback, the user can improve their playing.

[0676] An example of a prompt to input into the generating AI model is: "Generate effective feedback based on user behavior data. Optimize the instruction content considering past behavior history."

[0677] This system provides users with an environment where they can receive immediate feedback and efficiently improve their own performance.

[0678] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0679] Step 1:

[0680] The device records the user's movements. It uses video and acceleration / angle data acquired by cameras and sensors as input. This data reflects the user's movements in detail and includes multidimensional motion information. Specifically, it records the movements of the hands and racket, as well as body posture, with high precision during a tennis swing. The output consists of recorded video data and measurement data from the sensors.

[0681] Step 2:

[0682] The terminal transmits the recorded data to the server. The input is the motion data generated in step 1. The data is transmitted to the server via wireless communication. Real-time functionality is maintained through rapid transmission. The output is the user's motion data received by the server.

[0683] Step 3:

[0684] The server analyzes the received motion data. The input data is motion data sent from the terminal. The server uses a generative AI model to analyze the data in detail. In this process, it also considers the user's past motion history and skill level, and performs calculations to generate optimal instruction information. Specifically, the data is processed by analyzing the average speed and angle changes of the motion. The output is instruction information tailored to the user.

[0685] Step 4:

[0686] The server generates feedback based on the analysis results. The input is the analysis results from step 3, which are used to construct effective guidance advice. The generating AI model determines the feedback content that is best suited to the user's skill level. The output is specific and individually optimized guidance information.

[0687] Step 5:

[0688] The terminal displays instructional information received from the server to the user. The input is instructional information sent from the server. The terminal presents information to the user through sight and sound, prompting corrections to their movements. Specifically, the glasses-type display visually shows instructional content such as "finish your swing higher." The output is feedback in a form that the user can see.

[0689] Step 6:

[0690] The user modifies their actions based on the feedback provided. The input is the feedback received from the device. Based on this, the user adjusts their practice and actions to improve their skills. The output is the movement reflecting the modified actions and starting points. Specific actions include executing instructed points and re-evaluating the actions.

[0691] (Application Example 1)

[0692] 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".

[0693] Robot motion training in factories is crucial for improving on-site efficiency. However, conventional robot motion optimization methods lack the ability to provide real-time feedback and refine movements, resulting in limited productivity. This invention aims to significantly improve factory efficiency by measuring and analyzing movements in real time and providing immediate, optimal motion guidance.

[0694] 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.

[0695] In this invention, the server includes a glasses-type display means with a built-in camera for recording the user's movements, an information processing means for analyzing the recorded video data and generating information that points out the user's actions, a display control means for multiplexing the generated information on the glasses-type display, and a feedback means for monitoring the movements in real time and providing efficient movement guidance based on the analysis results. This makes it possible for the robot to immediately correct its movements and achieve optimal performance.

[0696] "User" refers to the entity that uses the system to perform training or tasks.

[0697] "Recording device" is a general term for a device that includes sensors and cameras for recording the actions of a user.

[0698] "Eyeglass-type display means" refers to a head-mounted display or smart glasses that allows the wearer to view visual information in real time.

[0699] "Video data" refers to video information about the user's actions recorded by a recording device.

[0700] "Information processing means" refers to a computer program that analyzes recorded video data and generates necessary feedback and guidance.

[0701] "Display control means" refers to a control program for appropriately displaying the generated instructional information on the glasses-type display.

[0702] A "sensor" refers to a physical device used to measure the speed, direction, and force of a user's movements.

[0703] "Feedback methods" refer to systems that provide users with guidance and corrective information based on analysis results in real time.

[0704] "Analysis results" refer to the output after data analysis obtained by information processing means, and include evaluations and guidance regarding the user's actions.

[0705] "Operation history" refers to a collection of data that shows records and trends of the user's actions in the past.

[0706] In order to implement this invention, multiple hardware and software components must work together. The system primarily consists of interactions between servers, terminals, and users.

[0707] The device features a glasses-type display for recording the user's movements with high precision. This display incorporates a camera, accelerometer, gyroscope, and other sensors to acquire user movement data in real time. For example, it can record the movements of a robotic arm or the movements of fingers during factory work.

[0708] The server receives motion data sent from the terminal and analyzes the data using a generated AI model. This analysis uses libraries such as Python's TensorFlow and PyTorch to calculate the speed, direction, and force of the motion, and generates detailed feedback that also takes into account the user's past motion history. This feedback provides important information for achieving efficient operation. For example, it may provide specific advice such as, "Reducing the torque by 20% would be optimal."

[0709] Users can instantly correct their actions based on feedback displayed on the glasses-type display. This shortens the learning curve and allows for rapid improvement of necessary skills. Feedback is provided not only visually but also audibly, enabling multi-sensory training.

[0710] As a concrete example, when using a robotic arm in the automobile assembly process, feedback is provided to ensure that parts are tightened efficiently without applying excessive force. An example of a prompt message generated by the AI ​​model is: "The robotic arm has detected excessive torque during screw tightening. Please generate optimal feedback to adjust the force."

[0711] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0712] Step 1:

[0713] The device records the user's actions in real time.

[0714] Input: User's movements during operation.

[0715] Data processing / calculation: Cameras and sensors are used to acquire video footage of the action and data related to that action (velocity, direction, etc.).

[0716] Output: Acquired operation data.

[0717] Specific operation: The sensor measures the speed and direction of movement and records it as video.

[0718] Step 2:

[0719] The terminal sends the recorded operation data to the server.

[0720] Input: Acquired behavioral data.

[0721] Data processing / calculation: Packet data and send it to the server using a communication protocol.

[0722] Output: Data packets received by the server.

[0723] Specific operation: Use Bluetooth or Wi-Fi to reliably transmit operation data to the server.

[0724] Step 3:

[0725] The server receives operational data and analyzes it using a generated AI model.

[0726] Input: The transmitted operation data packet.

[0727] Data processing / calculation: Using machine learning models, analyze velocity, direction, and force, and compare with historical data to generate optimal motion guidance.

[0728] Output: Feedback information for the user.

[0729] Specific actions: Using TensorFlow and PyTorch libraries, analyze data and create effective guidance based on the user's behavior history.

[0730] Step 4:

[0731] The server sends feedback generated based on the analysis results to the terminal.

[0732] Input: Instructional feedback generated by the server.

[0733] Data processing / calculation: Convert feedback into a format that can be visualized or audibly expressed, and send it to the terminal via a communication protocol.

[0734] Output: User-viewable feedback data.

[0735] Specific operation: Using streaming technology, feedback is displayed on the user's glasses-type display.

[0736] Step 5:

[0737] Users modify the behavior based on the feedback they receive.

[0738] Input: Feedback displayed on glasses-type display.

[0739] Data processing / calculation: Optimize and correct operations based on feedback.

[0740] Output: Improved performance.

[0741] Specific operation: Users can adjust the operation based on their feedback to achieve efficient work.

[0742] 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.

[0743] This invention combines a system that uses glasses-type displays to record the user's actions in real time, analyzes the data, and provides feedback, with an emotion engine. In this system, guidance and advice can be provided while considering not only the user's actions but also their emotions at that time.

[0744] The device uses cameras and sensors to capture the user's movements and record their movements and gestures with high precision. It also acquires information on speed and direction from the sensors, transmitting detailed movement data to the server. The emotion engine analyzes the user's emotions based on facial expressions captured by the camera, voice tone obtained from the voice sensor, and data from the heart rate monitor. The server aggregates and analyzes this data to recognize the user's emotional state.

[0745] On the server, information processing is performed by fusing behavioral data and emotional data. In particular, the results of the emotion engine's analysis are used to adjust the content of the feedback and how it is presented. For example, if the user is surprised, a calm, steady guide is provided, and if they are anxious, clearer hints are provided to alleviate the user's psychological state.

[0746] Users can receive visual or auditory feedback from their device and adjust their actions based on that feedback. For example, if a user practicing the piano becomes frustrated due to a mistake, the system, through emotion engine analysis, can understand this and provide empathetic advice such as, "Take a deep breath and try again slowly." In this way, appropriate approaches tailored to the user's emotional state can improve their overall practice experience.

[0747] This invention allows users to receive instruction that takes into account not only their physical movements but also their psychological state, enabling them to achieve more fulfilling training results. This system operates in various environments and contributes to improving the user's performance.

[0748] The following describes the processing flow.

[0749] Step 1:

[0750] The device activates its built-in camera and sensors as soon as the user begins activity, capturing the user's movements and facial expressions in real time. This allows for the simultaneous collection of movement and facial expression data.

[0751] Step 2:

[0752] The device transmits captured video data, including speed and direction data related to its movement, to the server. Simultaneously, the emotion engine analyzes facial expression data, voice tone, and heart rate to understand the user's emotional state.

[0753] Step 3:

[0754] The server analyzes the behavioral data sent from the terminal. AI processing is used for the analysis to extract current behavioral patterns, error frequency, accuracy, and other information.

[0755] Step 4:

[0756] The server evaluates the user's psychological state based on emotional data obtained from the emotion engine. Based on this evaluation, it further individualizes future feedback and plans support in a way that is psychologically optimal for the user.

[0757] Step 5:

[0758] The server integrates the results of behavioral analysis and emotion assessment to generate feedback for the user. For example, if it determines that relaxation is needed, it adjusts the wording to a gentler one, such as, "Calm down, try this next."

[0759] Step 6:

[0760] Feedback data is sent from the server to the terminal. The terminal receives this feedback and displays it in the user's field of view through the glasses-type display.

[0761] Step 7:

[0762] Users review the feedback provided and adjust their next actions and practice methods accordingly. By matching visual guidance with emotionally responsive feedback, users can practice efficiently and with less stress.

[0763] (Example 2)

[0764] 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".

[0765] Conventional motion recording and analysis systems focused solely on the user's physical movements, failing to provide feedback that took into account the user's emotional state. This made it difficult to provide appropriate guidance tailored to the user's psychological state, particularly in improving performance when experiencing stress or frustration. Furthermore, providing optimal feedback that considered the user's motion and emotional history remained a challenge.

[0766] 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.

[0767] In this invention, the server includes information processing means for analyzing recorded video and audio data and generating information that points out the user's behavior and emotional state; integrated analysis means for integrating action data and emotional data and generating feedback; and generation engine means for dynamically generating feedback according to the user's emotional state. This makes it possible to provide appropriate feedback according to the user's psychological state and improve the user's performance.

[0768] A "visual presentation device" is a device that records the user's actions and visually presents that information to the user.

[0769] "Information processing means" refers to a device or system that analyzes recorded video and audio data and generates information to identify the user's behavior and emotional state.

[0770] "Presentation control means" refers to a device or system that controls the presentation of generated information visually and aurally.

[0771] An "integrated analysis means" is a device or system that integrates motion data and emotional data and performs analysis to generate feedback based on the user's state.

[0772] "Generation engine means" refers to a device or program for dynamically generating feedback that corresponds to the user's emotional state.

[0773] A "detection device" is a device used to detect the speed and direction of a user's movements.

[0774] The present invention is a system implemented using a visual presentation device, information processing means, presentation control means, integrated analysis means, and generation engine means. A spectacle-type display is used as the visual presentation device, and the user's movements are recorded by a camera and sensors. This device also incorporates a detection device for detecting the speed and direction of the movements.

[0775] The terminal transmits the acquired video and audio data to the server. The server uses information processing tools to analyze this data and determine the user's behavior and emotional state. An emotion engine is used to analyze the emotional state, based on facial expression data, voice tone, and heart rate information. An integrated analysis tool fuses the motion data and emotional data to generate more precise feedback.

[0776] The generation engine dynamically generates feedback according to the user's psychological state, and this feedback is presented to the user visually or audibly by the presentation control means.

[0777] For example, if a user practicing the piano becomes frustrated with a section where they frequently make mistakes, the device sends this information to a server, which then generates feedback such as, "Take a deep breath and try again slowly." This feedback is presented to the user through a glasses-type display and audio output. In this way, the user can alleviate stress during practice and practice more efficiently.

[0778] The generative AI model plays a crucial role in generating user feedback. An example of a prompt is, "What advice would you offer if the user becomes frustrated during practice?" Based on this prompt, the AI ​​model generates optimal feedback to improve the user's experience.

[0779] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0780] Step 1:

[0781] The device activates a camera and sensors built into the glasses-type display to record the user's movements in real time. It acquires data on the user's movements, posture, and gestures as input. The output is high-precision digital data showing the user's movement patterns. This data is used for the next analysis step.

[0782] Step 2:

[0783] The device captures the user's facial expressions with a camera and acquires their voice tone using a voice sensor. It also uses a heart rate monitor to collect the user's biometric information. The inputs are the user's facial expressions, voice, and heart rate, and the output is emotional data that forms the basis for emotion judgment.

[0784] Step 3:

[0785] The terminal sends the behavioral and emotional data acquired in steps 1 and 2 to the server. The input is behavioral and emotional data, and the output is the secure transmission of data to the server. The data is transmitted using a secure communication protocol.

[0786] Step 4:

[0787] The server analyzes the received operational data using information processing tools. The input is operational data, and the output is an evaluation result indicating the accuracy and effectiveness of the user's actions. Advanced algorithms are used for this analysis.

[0788] Step 5:

[0789] The server analyzes emotional data using an emotion engine. The input is emotional data, and the output is an evaluation result indicating the user's emotional state (e.g., calm, surprised, irritated). An emotion recognition algorithm is used.

[0790] Step 6:

[0791] The server integrates behavioral data and emotional data using an integrated analysis mechanism. The input consists of evaluation results for behavioral data and emotional data, while the output is information indicating the overall user state. Appropriate feedback is generated based on this information.

[0792] Step 7:

[0793] The server dynamically generates feedback tailored to the user's psychological state using a generation engine. The input is integrated user state information, and the output is specific feedback in a format easily understood by the user. The feedback is generated using a generation AI model and prompt statements.

[0794] Step 8:

[0795] The terminal provides the user with feedback received from the server. Input is the feedback sent from the server, and output is a visual or auditory presentation to the user. The user can use this feedback to improve their behavior.

[0796] (Application Example 2)

[0797] 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".

[0798] The present invention aims to provide a system that can provide efficient and comfortable support by simultaneously analyzing the user's actions and emotions and providing feedback that takes into account the user's psychological state. In particular, in situations such as work and learning, it is necessary to maintain the user's concentration and motivation and reduce unnecessary stress.

[0799] 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.

[0800] In this invention, the server includes a display device means incorporating a camera and an emotion analysis device for recording the user's actions and emotions; a data processing means for analyzing the recorded video data and emotion data to identify the user's actions and generate emotion-based guidance information; and a display control means for multiplexing the generated guidance information on the display device. This enables appropriate feedback in accordance with the user's actions and emotions.

[0801] "User" refers to a person who uses the system in this invention to record and analyze their actions and emotions.

[0802] "Movement" is a concept that includes information about the physical movements performed by the user, as well as their speed and direction.

[0803] "Emotions" refer to the user's psychological state and are mental responses detected through facial expressions, voice, and other biometric information.

[0804] A "recording device" is a device that includes a camera and related sensors equipped to record the user's actions.

[0805] An "emotion analysis device" is a device used to analyze the emotional state of a user, and has the function of detecting emotions based on data such as voice, facial expressions, and heart rate.

[0806] "Display device means" refers to equipment for visually presenting information to the user, and includes glasses-type displays and monitors.

[0807] "Data processing means" refers to a computer or its components used to integrate and analyze behavioral data and emotional data acquired from the user.

[0808] "Display control means" refers to means that have the function of controlling the display of generated information to the user in an appropriate manner.

[0809] "Guidance information" refers to specific feedback generated by data processing tools, based on the user's actions and emotions, to advise or improve their behavior.

[0810] The system for implementing this invention mainly consists of an exhibition device incorporating a motion recording device and an emotion analysis device, and a data processing system connected thereto.

[0811] The server receives data from display devices such as smart glasses to acquire information about actions and emotions. Hardware used includes smart glasses equipped with imaging devices and sensors. Software includes a motion analysis engine, an emotion analysis engine, and a feedback generation module. The server analyzes this data and generates appropriate guidance information based on the user's behavior and emotional state. For example, if a worker feels fatigued, it can generate specific feedback such as, "It would be effective to do some light stretching between tasks."

[0812] The terminal presents instructional information generated based on the analysis results to the user visually or audibly. In this process, display control technology is required to ensure the information is placed appropriately.

[0813] Based on the feedback provided, users can take appropriate actions that correspond to their own movements and emotions. This makes it possible to improve work efficiency and learning effectiveness. The designed system provides support for both the psychological and physiological needs of people in factory and educational settings.

[0814] An example of a prompt to use with this generative AI model is: "Design a system that analyzes user behavior and emotions in real time and generates situation-appropriate feedback."

[0815] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0816] Step 1:

[0817] The device collects data on the user's movements and emotions through the camera and sensors built into the smart glasses. Inputs include video data from the camera, information on speed and direction from the sensors, and emotion data from the emotion analysis device. This data is transmitted to a server.

[0818] Step 2:

[0819] The server analyzes the received video data using a motion analysis engine to identify the user's motion patterns. The input consists of the video data and sensor data acquired in step 1. The output consists of speed, direction, and identified motion patterns related to the motion. During this process, specific characteristics of each motion are detected, quantified, and stored.

[0820] Step 3:

[0821] The server analyzes emotional data using an emotion analysis engine. Inputs include facial expression data, voice data, and biometric information such as heart rate. Outputs identify the user's emotional state as numerical values ​​or categories. Here, the user's stress and fatigue levels are quantified.

[0822] Step 4:

[0823] The server integrates the analyzed behavioral and emotional data and generates guidance information through data processing. The input consists of behavioral patterns and emotional states obtained in steps 2 and 3. The output is a feedback message best suited to the user's psychological and physiological state. Historical data is also used to generate specific advice and reminders.

[0824] Step 5:

[0825] The user receives feedback generated through the device, either visually or audibly. The input is the guidance information generated in step 4. The output is a specific action plan to support the user's behavior and improve their psychological state. Here, it is important that the feedback provided is clear and timely.

[0826] 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.

[0827] 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.

[0828] 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.

[0829] 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.

[0830] 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.

[0831] 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.

[0832] 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.

[0833] 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.

[0834] 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."

[0835] 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.

[0836] 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.

[0837] 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.

[0838] 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.

[0839] 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.

[0840] 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.

[0841] 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.

[0842] 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.

[0843] 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.

[0844] 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.

[0845] 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.

[0846] 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.

[0847] The following is further disclosed regarding the embodiments described above.

[0848] (Claim 1)

[0849] A glasses-type display means incorporating a camera for recording the user's movements,

[0850] Information processing means that analyzes recorded video data to generate information that points out the user's actions,

[0851] A display control means for multiplexing the generated information on the glasses-type display,

[0852] A system that includes this.

[0853] (Claim 2)

[0854] The system according to claim 1, characterized in that the imaging device includes a sensor that detects the speed and direction of the user's movements.

[0855] (Claim 3)

[0856] The system according to claim 1, characterized in that the information processing means optimizes the information taking into account the user's past operation history.

[0857] "Example 1"

[0858] (Claim 1)

[0859] A means of recording the user's actions,

[0860] A data processing means that analyzes recorded motion data to generate instruction optimized for the user,

[0861] A display control means that transmits the generated instructional information to a portable display device and presents it to the user,

[0862] A system that includes this.

[0863] (Claim 2)

[0864] The system according to claim 1, characterized in that the shooting means includes a sensor that detects the acceleration and angle of the user's movements.

[0865] (Claim 3)

[0866] The system according to claim 1, characterized in that the data processing means optimizes the information taking into account the user's past operation history and skill level.

[0867] "Application Example 1"

[0868] (Claim 1)

[0869] A glasses-type display means incorporating a camera for recording the user's movements,

[0870] Information processing means that analyzes recorded video data to generate information that points out the user's actions,

[0871] A display control means for multiplexing the generated information on the glasses-type display,

[0872] A feedback mechanism for monitoring movements in real time and providing efficient movement guidance based on analysis results,

[0873] A system that includes this.

[0874] (Claim 2)

[0875] The system according to claim 1, characterized in that the imaging device includes a sensor that detects the speed and direction of the user's movements, measures the force required for the movement, and generates an optimized behavior pattern.

[0876] (Claim 3)

[0877] The system according to claim 1, characterized in that the information processing means optimizes the information considering the user's past action history and generates feedback that enables real-time behavioral correction.

[0878] "Example 2 of combining an emotion engine"

[0879] (Claim 1)

[0880] A visual presentation device means incorporating a camera for recording the user's movements,

[0881] Information processing means that analyzes recorded video and audio data and generates information that points out the user's behavior and emotional state,

[0882] Presentation control means for visually and audibly displaying the generated information on the visual presentation device,

[0883] An integrated analysis means for integrating motion data and emotion data to generate feedback,

[0884] A generation engine means that dynamically generates feedback according to the user's emotional state,

[0885] A system that includes this.

[0886] (Claim 2)

[0887] The system according to claim 1, characterized in that the imaging device includes a detection device for detecting the speed and direction of the user's movements.

[0888] (Claim 3)

[0889] The system according to claim 1, characterized in that the information processing means optimizes the information taking into account the user's past behavioral history and emotional data.

[0890] "Application example 2 when combining with an emotional engine"

[0891] (Claim 1)

[0892] A display device incorporating a camera and emotion analysis device for recording the user's actions and emotions,

[0893] A data processing means that analyzes recorded video data and emotional data to identify the user's behavior and generate emotionally-based guidance information,

[0894] A display control means for multiplexing the generated instruction information on the display device,

[0895] A system that includes this.

[0896] (Claim 2)

[0897] The system according to claim 1, characterized in that the imaging device and emotion analysis device include a sensing device that detects the speed and direction of the user's movements and the user's psychological state.

[0898] (Claim 3)

[0899] The system according to claim 1, characterized in that the data processing means optimizes the information taking into account the user's past behavioral history and emotional history. [Explanation of Symbols]

[0900] 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 glasses-type display means incorporating a camera for recording the user's movements, Information processing means that analyzes recorded video data to generate information that points out the user's actions, A display control means for multiplexing the generated information on the glasses-type display, A system that includes this.

2. The system according to claim 1, characterized in that the imaging device includes a sensor that detects the speed and direction of the user's movements.

3. The system according to claim 1, characterized in that the information processing means optimizes the information taking into account the user's past operation history.

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