System

Abstract

An object of a system according to an embodiment is to easily record and analyze a state of a tongue and display a health trend.SOLUTION: A system according to an embodiment includes a tongue condition recorder, a tongue color or shape analyzer, and a health trend display. The tongue state recording unit acquires a photograph of the tongue. The tongue color or shape analyzer analyzes the photograph of the tongue acquired by the tongue condition recorder. The health trend display unit displays a health trend on the basis of the result analyzed by the tongue color or shape analysis unit.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional technology has made it difficult to easily record and analyze the condition of the tongue and understand health trends.

[0005] The system according to the embodiment aims to easily record and analyze the condition of the tongue and display health trends. [Means for solving the problem]

[0006] The system according to the embodiment includes a tongue condition recording unit, a tongue color or shape analysis unit, and a health trend display unit. The tongue condition recording unit acquires a photograph of the tongue. The tongue color or shape analysis unit analyzes the photograph of the tongue acquired by the tongue condition recording unit. The health trend display unit displays the health trend based on the results of the analysis by the tongue color or shape analysis unit. [Effects of the Invention]

[0007] The system according to the embodiment can easily record and analyze the condition of the tongue and display health trends. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. DETAILED DESCRIPTION OF THE INVENTION

[0009] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0010] First, the terms used in the following description will be explained.

[0011] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, the processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (Tensor Processing Unit).

[0012] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0013] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0014] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), and Bluetooth (registered trademark).

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0016] [First embodiment] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0017] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0019] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0020] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (for example, a pen or a finger) to receive user input by the touch of the pointer. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 (see FIG. 2) acquires the data indicating the user input.

[0021] Output device 40 includes a display 40A and a speaker 40B, and presents data to a user by outputting the data in a form of expression that the user can perceive (e.g., audio and / or text). Display 40A displays visible information such as text and images in accordance with instructions from processor 46. Speaker 40B outputs audio in accordance with instructions from processor 46. Camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0023] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0024] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0025] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0026] In the smart device 14, the specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart device 14 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0027] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device (e.g., a generation server) may have the data generation model 58. In this case, the data processing device 12 obtains a processing result (prediction result, etc.) using the data generation model 58 by communicating with the server device having the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device owned by a user (e.g., a mobile phone, a robot, a home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example 1) The health management system according to an embodiment of the present invention records and analyzes the condition of the tongue and displays health trends based on traditional Chinese medicine, allowing the user to easily understand their health condition and support early detection and prevention.

[0029] A health management system according to an embodiment includes a tongue condition recording unit, a tongue color and shape analysis unit, and a health trend display unit. The tongue condition recording unit acquires a photograph of the tongue. For example, the photograph of the tongue is taken using a smartphone or a dedicated device. The tongue condition recording unit can also save the photograph of the tongue as digital data. For example, the photograph of the tongue can be stored in cloud storage for later analysis. The tongue color and shape analysis unit analyzes the photograph of the tongue acquired by the tongue condition recording unit. For example, AI can evaluate the color, shape, and surface condition of the tongue. The tongue color and shape analysis unit can also analyze various conditions in detail, such as whether the tongue is red or has a lot of white coating. For example, AI can detect changes in tongue color and evaluate the health condition. The health trend display unit displays the health trend based on the analysis results of the tongue color and shape analysis unit. For example, based on the theory of traditional Chinese medicine, if there is a possibility of fever in the body, it can advise the user to eat cold foods and drinks. The health trend display unit can also provide specific health management advice based on the analysis results. For example, if stress builds up, the system suggests increasing the amount of time spent relaxing. This allows the health management system according to the embodiment to easily grasp the user's health condition and support early detection and early prevention. For example, by periodically taking pictures of the tongue and having AI analyze them, it is possible to track changes in health condition. This allows abnormalities to be detected early and appropriate preventive measures to be taken.

[0030] The tongue condition recording unit can incorporate an algorithm that automatically corrects for light reflections or shadows when taking a photograph of the tongue. The tongue condition recording unit, for example, incorporates an algorithm that automatically corrects for light reflections and shadows when taking a photograph of the tongue. For example, by adjusting the intensity and angle of light when taking a photograph to prevent shadows, the color and shape of the tongue can be accurately recorded. The tongue condition recording unit can also use image processing technology to correct for light reflections and shadows in the photograph. For example, an image processing algorithm can be used to adjust the brightness and contrast of the photograph to accurately record the tongue condition. This allows for correcting for light reflections and shadows, thereby obtaining more accurate data.

[0031] The tongue condition recording unit simultaneously records the oral temperature or humidity when taking a photograph of the tongue, and these data can be used for analysis. For example, the tongue condition recording unit is equipped with a sensor that measures oral temperature when taking a photograph of the tongue, and simultaneously records temperature data. For example, a temperature sensor can be incorporated into the camera, and the temperature can be automatically measured when taking a photograph. The tongue condition recording unit can also measure the humidity inside the mouth using a humidity sensor and record the data. For example, a humidity sensor can be incorporated into the camera, and the humidity can be automatically measured when taking a photograph. Furthermore, the tongue condition recording unit can store the temperature data and humidity data in cloud storage to utilize them for analysis. For example, the temperature data and humidity data can be stored in the cloud and used for later analysis. In this way, recording the oral temperature and humidity enables more detailed analysis of the health condition.

[0032] The tongue condition recording unit can not only take photos of the tongue, but also the entire mouth, simultaneously recording and analyzing the condition of the teeth and gums. For example, the tongue condition recording unit can incorporate a system that simultaneously takes photos of the entire mouth when taking photos of the tongue. For example, a wide-angle lens can be used to capture images of the entire mouth and record the condition of the teeth and gums. The tongue condition recording unit can also incorporate algorithms to analyze the condition of the teeth and gums and analyze the data. For example, it can analyze the color and shape of the teeth and gums to evaluate the health condition. Furthermore, the tongue condition recording unit can also save photos of the entire mouth in cloud storage for later analysis. For example, photos of the entire mouth can be saved in the cloud for later analysis. This allows for a more comprehensive health assessment by recording and analyzing the condition of the entire mouth.

[0033] The tongue state recording unit can provide audio guidance and instructions on the correct way to take a picture of the tongue when the user takes a picture of the tongue. For example, a system can be developed that provides audio guidance when the user takes a picture of the tongue. For example, an app can provide audio instructions such as "Stick out your tongue firmly" or "Keep the camera level." The tongue state recording unit can also customize the content of the audio guidance and provide instructions tailored to the user. For example, it can provide appropriate instructions depending on the user's age and gender. Furthermore, the tongue state recording unit can save the content of the audio guidance in cloud storage for later analysis. For example, the content of the audio guidance can be saved in cloud storage for later analysis. This allows the audio guidance to guide the user in taking a picture of the tongue in the correct way.

[0034] The tongue color and shape analysis unit can incorporate an algorithm that analyzes not only the color or shape of the tongue, but also the texture of the tongue surface or the state of the fine blood vessels. For example, the tongue color and shape analysis unit can develop an algorithm for analyzing the texture of the tongue surface to evaluate the health state of the tongue. For example, the unevenness and smoothness of the tongue surface can be analyzed to determine the health state. The tongue color and shape analysis unit can also incorporate an algorithm for analyzing the state of the fine blood vessels to analyze data. For example, the state of the blood vessels on the tongue can be analyzed to evaluate the health state. Furthermore, the tongue color and shape analysis unit can save the analysis results in cloud storage for later analysis. For example, the texture of the tongue surface and the state of the fine blood vessels can be saved in the cloud for later analysis. This allows for a more detailed health state evaluation by analyzing the texture of the tongue surface and the state of the fine blood vessels.

[0035] The tongue color and shape analysis unit can be equipped with a function for comparing the tongue condition with past data and tracking long-term changes. For example, the tongue color and shape analysis unit can be equipped with a function for comparing the tongue condition with past data, developing a system for tracking long-term changes. For example, it can compare past photos with current photos and visualize changes. The tongue color and shape analysis unit can also store past data in cloud storage for later analysis. For example, past tongue photos and health data can be stored in the cloud for later analysis. Furthermore, the tongue color and shape analysis unit can also incorporate an algorithm for tracking long-term changes and analyze the data. For example, a temporal change analysis method can be used to evaluate changes in tongue condition. This makes it possible to track long-term changes in health by comparing with past data.

[0036] The tongue color and shape analysis unit can integrate other health data when analyzing the condition of the tongue to perform a comprehensive health assessment. For example, the tongue color and shape analysis unit can integrate blood pressure data when analyzing the condition of the tongue to develop a system for performing a comprehensive health assessment. For example, it can analyze blood pressure fluctuations and changes in tongue color and shape. The tongue color and shape analysis unit can also integrate heart rate data to perform a comprehensive health assessment. For example, it can analyze heart rate fluctuations and changes in tongue condition. Furthermore, the tongue color and shape analysis unit can store other health data in cloud storage for later analysis. For example, blood pressure data and heart rate data can be stored in the cloud for later analysis. This allows for integration with other health data to perform a more comprehensive health assessment.

[0037] When analyzing the condition of the tongue, the tongue color and shape analysis unit can compare photos taken under different light sources and implement an algorithm to eliminate the effects of light. For example, the tongue color and shape analysis unit can compare photos of the tongue taken under different light sources and develop an algorithm to eliminate the effects of light. For example, it can analyze photos taken under natural and artificial light and correct for color differences. The tongue color and shape analysis unit can also implement image processing technology to eliminate the effects of light and analyze the data. For example, it can use an image processing algorithm to adjust the brightness and contrast of the photos to accurately record the condition of the tongue. Furthermore, the tongue color and shape analysis unit can save the analysis results in cloud storage for later analysis. For example, data with the effects of light eliminated can be saved in the cloud for later analysis. This allows for more accurate analysis by comparing photos taken under different light sources and eliminating the effects of light.

[0038] The health trend display unit can provide comprehensive health advice that incorporates modern medical knowledge in addition to displaying health trends based on traditional Chinese medicine theory. For example, a system can be developed in which the health trend display unit provides advice that incorporates modern medical knowledge in addition to displaying health trends based on traditional Chinese medicine theory. For example, health advice can be provided from a modern medical perspective based on the condition of the tongue. The health trend display unit can also provide specific health management advice based on the latest research results and diagnostic criteria in modern medicine. For example, it can suggest lifestyle improvement ideas based on the latest medical research. Furthermore, the health trend display unit can store advice that integrates traditional Chinese medicine and modern medical knowledge in cloud storage for later analysis. For example, advice that integrates traditional Chinese medicine and modern medical knowledge can be stored in the cloud for later analysis. This allows for more comprehensive health advice to be provided by integrating traditional Chinese medicine and modern medical knowledge.

[0039] The health trend display unit can provide more personalized advice by taking into account the user's lifestyle habits or dietary content when displaying the health trend. For example, a system can be developed in which the health trend display unit provides personalized advice by taking into account the user's lifestyle habit data when displaying the health trend. For example, advice can be provided based on exercise habits and sleep patterns. The health trend display unit can also provide personalized advice by taking into account the user's dietary content. For example, advice can be provided based on nutritional balance and meal frequency. Furthermore, the health trend display unit can store data on lifestyle habits and dietary content in cloud storage for later use in analysis. For example, data on lifestyle habits and dietary content can be stored in the cloud for later use in analysis. This allows for more personalized health advice to be provided by taking into account the lifestyle habits and dietary content.

[0040] The health trend display unit can provide more accurate advice by taking into account the user's past medical diagnoses or treatment history when displaying the health trend. For example, a system can be developed in which the health trend display unit takes into account the user's past medical diagnosis data when displaying the health trend and provides more accurate advice. For example, the health trend display unit displays the health trend based on past diagnosis results. The health trend display unit can also provide specific health management advice by taking into account the user's past treatment history. For example, the health trend display unit can make suggestions for improving lifestyle habits based on the details of past treatment. Furthermore, the health trend display unit can store data on past medical diagnoses and treatment history in cloud storage for later analysis. For example, the health trend display unit can store data on past medical diagnoses and treatment history in the cloud for later analysis. In this way, more accurate health advice can be provided by taking into account the user's past medical diagnoses and treatment history.

[0041] The health trend display unit can provide a display of the health trend in a visually easy-to-understand graph or chart, allowing the user to intuitively understand. For example, a system is developed in which the health trend display unit provides a display of the health trend in a visually easy-to-understand graph or chart. For example, changes in the condition of the tongue are displayed in a line graph. The health trend display unit can also display the health condition evaluation results in a pie chart or heat map. For example, the health score is displayed in a pie chart and the risk assessment is displayed in a heat map. Furthermore, the health trend display unit can save the data of the visually easy-to-understand graph or chart in cloud storage for later use in analysis. For example, the data of the graph or chart is saved in the cloud for later use in analysis. In this way, by providing the data in a visually easy-to-understand graph or chart, the user can intuitively understand their health condition.

[0042] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0043] The health management system can also add a function to evaluate tongue movement and flexibility when recording the user's tongue condition. For example, the speed and range of tongue movement can be measured to evaluate tongue muscle strength and flexibility. Tongue movement data can also be saved in cloud storage for later analysis. This allows for a more detailed understanding of health conditions by evaluating tongue movement and flexibility.

[0044] The health management system can also measure the temperature of the user's tongue when recording the condition of the tongue and use the data for analysis. For example, a sensor that measures tongue temperature can be incorporated into the camera, automatically measuring the temperature when photographing. In addition, tongue temperature data can be saved in cloud storage and used for later analysis. This allows for more detailed analysis of health conditions by recording tongue temperature.

[0045] The health management system can also measure the humidity on the surface of the user's tongue when recording the condition of the tongue and use the data for analysis. For example, a humidity sensor can be built into the camera to automatically measure humidity when taking a photo. The humidity data on the surface of the tongue can also be saved in cloud storage and used for later analysis. This allows for more detailed analysis of health conditions by recording the humidity on the surface of the tongue.

[0046] The health management system can also add a function to analyze the surface texture of the user's tongue when recording the condition of the tongue. For example, the system can analyze the unevenness and smoothness of the tongue surface to evaluate the health condition. In addition, tongue surface texture data can be saved in cloud storage and used for later analysis. This allows for a more detailed evaluation of the health condition by analyzing the tongue surface texture.

[0047] The health management system can also add a function to analyze the state of the fine blood vessels in the user's tongue when recording the state of the tongue. For example, the state of the blood vessels in the tongue can be analyzed to evaluate the health state. In addition, data on the fine blood vessels in the tongue can be saved in cloud storage and used for later analysis. This allows for a more detailed evaluation of the health state by analyzing the state of the fine blood vessels in the tongue.

[0048] The processing flow of the first embodiment will be briefly explained below.

[0049] Step 1: The tongue state recording unit acquires a photograph of the tongue. For example, the tongue photograph can be taken using a smartphone or a dedicated device. The tongue state recording unit can also save the photograph of the tongue as digital data. For example, the tongue photograph can be saved in cloud storage for later analysis. Step 2: The tongue color or shape analysis unit analyzes the photograph of the tongue captured by the tongue condition recording unit. For example, AI evaluates the color, shape, and surface condition of the tongue. The tongue color and shape analysis unit can also perform detailed analysis of various conditions, such as whether the tongue is red or has a lot of white coating. For example, AI can detect changes in tongue color and evaluate the health condition. Step 3: The health trend display unit displays health trends based on the results of the analysis by the tongue color or shape analysis unit. For example, based on the theory of traditional Chinese medicine, if there is a possibility that the body is overheated, it will advise the user to eat cool foods and drinks. The health trend display unit can also provide specific health management advice based on the analysis results. For example, if stress is building up, it will suggest that the user spend more time relaxing.

[0050] (Example 2) The health management system according to an embodiment of the present invention records and analyzes the condition of the tongue and displays health trends based on traditional Chinese medicine, allowing the user to easily understand their health condition and support early detection and prevention.

[0051] A health management system according to an embodiment includes a tongue condition recording unit, a tongue color and shape analysis unit, and a health trend display unit. The tongue condition recording unit acquires a photograph of the tongue. For example, the photograph of the tongue is taken using a smartphone or a dedicated device. The tongue condition recording unit can also save the photograph of the tongue as digital data. For example, the photograph of the tongue can be stored in cloud storage for later analysis. The tongue color and shape analysis unit analyzes the photograph of the tongue acquired by the tongue condition recording unit. For example, AI can evaluate the color, shape, and surface condition of the tongue. The tongue color and shape analysis unit can also analyze various conditions in detail, such as whether the tongue is red or has a lot of white coating. For example, AI can detect changes in tongue color and evaluate the health condition. The health trend display unit displays the health trend based on the analysis results of the tongue color and shape analysis unit. For example, based on the theory of traditional Chinese medicine, if there is a possibility of fever in the body, it can advise the user to eat cold foods and drinks. The health trend display unit can also provide specific health management advice based on the analysis results. For example, if stress builds up, the system suggests increasing the amount of time spent relaxing. This allows the health management system according to the embodiment to easily grasp the user's health condition and support early detection and early prevention. For example, by periodically taking pictures of the tongue and having AI analyze them, it is possible to track changes in health condition. This allows abnormalities to be detected early and appropriate preventive measures to be taken.

[0052] The tongue condition recording unit can incorporate an algorithm that automatically corrects for light reflections or shadows when taking a photograph of the tongue. The tongue condition recording unit, for example, incorporates an algorithm that automatically corrects for light reflections and shadows when taking a photograph of the tongue. For example, by adjusting the intensity and angle of light when taking a photograph to prevent shadows, the color and shape of the tongue can be accurately recorded. The tongue condition recording unit can also use image processing technology to correct for light reflections and shadows in the photograph. For example, an image processing algorithm can be used to adjust the brightness and contrast of the photograph to accurately record the tongue condition. This allows for correcting for light reflections and shadows, thereby obtaining more accurate data.

[0053] The tongue condition recording unit simultaneously records the oral temperature or humidity when taking a photograph of the tongue, and these data can be used for analysis. For example, the tongue condition recording unit is equipped with a sensor that measures oral temperature when taking a photograph of the tongue, and simultaneously records temperature data. For example, a temperature sensor can be incorporated into the camera, and the temperature can be automatically measured when taking a photograph. The tongue condition recording unit can also measure the humidity inside the mouth using a humidity sensor and record the data. For example, a humidity sensor can be incorporated into the camera, and the humidity can be automatically measured when taking a photograph. Furthermore, the tongue condition recording unit can store the temperature data and humidity data in cloud storage to utilize them for analysis. For example, the temperature data and humidity data can be stored in the cloud and used for later analysis. In this way, recording the oral temperature and humidity enables more detailed analysis of the health condition.

[0054] The tongue state recording unit can use an emotion estimation function to record the user's emotional state at the time of photographing and analyze the relationship between the emotion and the tongue state. For example, when taking a photo of the tongue, the tongue state recording unit estimates the user's emotional state using facial expression recognition technology and records the data. For example, a camera analyzes the user's facial expression and calculates an emotion score. The tongue state recording unit can also use voice analysis technology to analyze the tone and speed of the user's voice and estimate the emotional state. For example, voice recognition software analyzes the user's voice and calculates an emotion score. Furthermore, the tongue state recording unit can collect biometric data (heart rate and electrodermal activity) using a sensor and analyze the emotion using an emotion estimation algorithm. For example, an emotion score is calculated based on heart rate fluctuations. This allows for a more detailed understanding of the user's health condition by analyzing the relationship between the emotional state and the tongue state.

[0055] The tongue condition recording unit can not only take photos of the tongue, but also the entire mouth, simultaneously recording and analyzing the condition of the teeth and gums. For example, the tongue condition recording unit can incorporate a system that simultaneously takes photos of the entire mouth when taking photos of the tongue. For example, a wide-angle lens can be used to capture images of the entire mouth and record the condition of the teeth and gums. The tongue condition recording unit can also incorporate algorithms to analyze the condition of the teeth and gums and analyze the data. For example, it can analyze the color and shape of the teeth and gums to evaluate the health condition. Furthermore, the tongue condition recording unit can also save photos of the entire mouth in cloud storage for later analysis. For example, photos of the entire mouth can be saved in the cloud for later analysis. This allows for a more comprehensive health assessment by recording and analyzing the condition of the entire mouth.

[0056] The tongue state recording unit can provide audio guidance and instructions on the correct way to take a picture of the tongue when the user takes a picture of the tongue. For example, a system can be developed that provides audio guidance when the user takes a picture of the tongue. For example, an app can provide audio instructions such as "Stick out your tongue firmly" or "Keep the camera level." The tongue state recording unit can also customize the content of the audio guidance and provide instructions tailored to the user. For example, it can provide appropriate instructions depending on the user's age and gender. Furthermore, the tongue state recording unit can save the content of the audio guidance in cloud storage for later analysis. For example, the content of the audio guidance can be saved in cloud storage for later analysis. This allows the audio guidance to guide the user in taking a picture of the tongue in the correct way.

[0057] The tongue state recording unit can use the emotion estimation function to provide music or video with a relaxing effect so that the user can take a photo in a relaxed state. For example, a system is developed in which the tongue state recording unit provides music with a relaxing effect when the user takes a photo of their tongue. For example, an app plays relaxing music so that the user can take a photo in a calm state. The tongue state recording unit can also provide video with a relaxing effect. For example, it can play natural scenery or tranquil video so that the user can take a photo in a relaxed state. Furthermore, the tongue state recording unit can save the content of the relaxing music or video in cloud storage for later analysis. For example, the content of the relaxing music or video can be saved in the cloud for later analysis. This allows the user to take a photo of their tongue in a relaxed state thanks to the relaxing music or video.

[0058] The tongue color and shape analysis unit can incorporate an algorithm that analyzes not only the color or shape of the tongue, but also the texture of the tongue surface or the state of the fine blood vessels. For example, the tongue color and shape analysis unit can develop an algorithm for analyzing the texture of the tongue surface to evaluate the health state of the tongue. For example, the unevenness and smoothness of the tongue surface can be analyzed to determine the health state. The tongue color and shape analysis unit can also incorporate an algorithm for analyzing the state of the fine blood vessels to analyze data. For example, the state of the blood vessels on the tongue can be analyzed to evaluate the health state. Furthermore, the tongue color and shape analysis unit can save the analysis results in cloud storage for later analysis. For example, the texture of the tongue surface and the state of the fine blood vessels can be saved in the cloud for later analysis. This allows for a more detailed health state evaluation by analyzing the texture of the tongue surface and the state of the fine blood vessels.

[0059] The tongue color and shape analysis unit can be equipped with a function for comparing the tongue condition with past data and tracking long-term changes. For example, the tongue color and shape analysis unit can be equipped with a function for comparing the tongue condition with past data, developing a system for tracking long-term changes. For example, it can compare past photos with current photos and visualize changes. The tongue color and shape analysis unit can also store past data in cloud storage for later analysis. For example, past tongue photos and health data can be stored in the cloud for later analysis. Furthermore, the tongue color and shape analysis unit can also incorporate an algorithm for tracking long-term changes and analyze the data. For example, a temporal change analysis method can be used to evaluate changes in tongue condition. This makes it possible to track long-term changes in health by comparing with past data.

[0060] The tongue color and shape analysis unit can use the emotion estimation function to analyze the effect of a user's emotional state on the color or shape of the tongue, thereby clarifying the relationship between emotion and health condition. For example, the tongue color and shape analysis unit can develop a system that uses the emotion estimation function to analyze the effect of a user's emotional state on the color and shape of the tongue. For example, the tongue color and shape analysis unit can analyze data by introducing an algorithm for analyzing the relationship between the emotional state and the tongue state. For example, the tongue color and shape analysis unit can evaluate the effect of changes in the emotional state on the color and shape of the tongue. Furthermore, the tongue color and shape analysis unit can save the analysis results in cloud storage for later analysis. For example, data showing the relationship between the emotional state and the tongue state can be saved in the cloud for later analysis. This makes it possible to understand the health condition in more detail by analyzing the relationship between the emotional state and the tongue state.

[0061] The tongue color and shape analysis unit can integrate other health data when analyzing the condition of the tongue to perform a comprehensive health assessment. For example, the tongue color and shape analysis unit can integrate blood pressure data when analyzing the condition of the tongue to develop a system for performing a comprehensive health assessment. For example, it can analyze blood pressure fluctuations and changes in tongue color and shape. The tongue color and shape analysis unit can also integrate heart rate data to perform a comprehensive health assessment. For example, it can analyze heart rate fluctuations and changes in tongue condition. Furthermore, the tongue color and shape analysis unit can store other health data in cloud storage for later analysis. For example, blood pressure data and heart rate data can be stored in the cloud for later analysis. This allows for integration with other health data to perform a more comprehensive health assessment.

[0062] When analyzing the condition of the tongue, the tongue color and shape analysis unit can compare photos taken under different light sources and implement an algorithm to eliminate the effects of light. For example, the tongue color and shape analysis unit can compare photos of the tongue taken under different light sources and develop an algorithm to eliminate the effects of light. For example, it can analyze photos taken under natural and artificial light and correct for color differences. The tongue color and shape analysis unit can also implement image processing technology to eliminate the effects of light and analyze the data. For example, it can use an image processing algorithm to adjust the brightness and contrast of the photos to accurately record the condition of the tongue. Furthermore, the tongue color and shape analysis unit can save the analysis results in cloud storage for later analysis. For example, data with the effects of light eliminated can be saved in the cloud for later analysis. This allows for more accurate analysis by comparing photos taken under different light sources and eliminating the effects of light.

[0063] The tongue color and shape analysis unit can use the emotion estimation function to suggest the optimal timing to take a tongue photo so that the user can take a tongue photo in the most relaxed state. For example, a system is developed in which the tongue color and shape analysis unit uses the emotion estimation function to suggest the optimal timing to take a tongue photo so that the user can take a tongue photo in a relaxed state. For example, it may recommend a time of day when the emotion score is high. The tongue color and shape analysis unit can also monitor the emotional state in real time and suggest the optimal timing to take a tongue photo. For example, it may recommend taking a tongue photo when the emotion score meets a certain standard. Furthermore, the tongue color and shape analysis unit can save the optimal timing to take a tongue photo in cloud storage for later analysis. For example, data indicating the optimal timing to take a tongue photo can be saved in the cloud for later analysis. This allows the optimal timing to be suggested so that the user can take a tongue photo in a relaxed state.

[0064] The health trend display unit can provide comprehensive health advice that incorporates modern medical knowledge in addition to displaying health trends based on traditional Chinese medicine theory. For example, a system can be developed in which the health trend display unit provides advice that incorporates modern medical knowledge in addition to displaying health trends based on traditional Chinese medicine theory. For example, health advice can be provided from a modern medical perspective based on the condition of the tongue. The health trend display unit can also provide specific health management advice based on the latest research results and diagnostic criteria in modern medicine. For example, it can suggest lifestyle improvement ideas based on the latest medical research. Furthermore, the health trend display unit can store advice that integrates traditional Chinese medicine and modern medical knowledge in cloud storage for later analysis. For example, advice that integrates traditional Chinese medicine and modern medical knowledge can be stored in the cloud for later analysis. This allows for more comprehensive health advice to be provided by integrating traditional Chinese medicine and modern medical knowledge.

[0065] The health trend display unit can provide more personalized advice by taking into account the user's lifestyle habits or dietary content when displaying the health trend. For example, a system can be developed in which the health trend display unit provides personalized advice by taking into account the user's lifestyle habit data when displaying the health trend. For example, advice can be provided based on exercise habits and sleep patterns. The health trend display unit can also provide personalized advice by taking into account the user's dietary content. For example, advice can be provided based on nutritional balance and meal frequency. Furthermore, the health trend display unit can store data on lifestyle habits and dietary content in cloud storage for later use in analysis. For example, data on lifestyle habits and dietary content can be stored in the cloud for later use in analysis. This allows for more personalized health advice to be provided by taking into account the lifestyle habits and dietary content.

[0066] The health trend display unit can use the emotion estimation function to provide health advice according to the user's emotional state and make suggestions for balancing emotions and health. The health trend display unit can, for example, use the emotion estimation function to develop a system that provides health advice according to the user's emotional state. For example, if stress is high, it can suggest relaxation methods. The health trend display unit can also make specific suggestions for balancing emotions and health. For example, it can make suggestions for improving the health state based on evaluation criteria for the emotional state. Furthermore, the health trend display unit can store data on the emotional state and health state in cloud storage for later analysis. For example, it can store data on the emotional state and health state in the cloud for later analysis. This makes it possible to provide health advice according to the emotional state and make suggestions for balancing emotions and health.

[0067] The health trend display unit can provide more accurate advice by taking into account the user's past medical diagnoses or treatment history when displaying the health trend. For example, a system can be developed in which the health trend display unit takes into account the user's past medical diagnosis data when displaying the health trend and provides more accurate advice. For example, the health trend display unit displays the health trend based on past diagnosis results. The health trend display unit can also provide specific health management advice by taking into account the user's past treatment history. For example, the health trend display unit can make suggestions for improving lifestyle habits based on the details of past treatment. Furthermore, the health trend display unit can store data on past medical diagnoses and treatment history in cloud storage for later analysis. For example, the health trend display unit can store data on past medical diagnoses and treatment history in the cloud for later analysis. In this way, more accurate health advice can be provided by taking into account the user's past medical diagnoses and treatment history.

[0068] The health trend display unit can provide a display of the health trend in a visually easy-to-understand graph or chart, allowing the user to intuitively understand. For example, a system is developed in which the health trend display unit provides a display of the health trend in a visually easy-to-understand graph or chart. For example, changes in the condition of the tongue are displayed in a line graph. The health trend display unit can also display the health condition evaluation results in a pie chart or heat map. For example, the health score is displayed in a pie chart and the risk assessment is displayed in a heat map. Furthermore, the health trend display unit can save the data of the visually easy-to-understand graph or chart in cloud storage for later use in analysis. For example, the data of the graph or chart is saved in the cloud for later use in analysis. In this way, by providing the data in a visually easy-to-understand graph or chart, the user can intuitively understand their health condition.

[0069] The health trend display unit uses the emotion estimation function to provide health advice that will evoke the most positive emotions in the user, thereby increasing motivation for health management. For example, a system is developed in which the health trend display unit uses the emotion estimation function to provide health advice that will evoke the most positive emotions in the user. For example, positive messages and encouraging words are displayed. The health trend display unit can also monitor the emotional state in real time and provide specific advice to elicit positive emotions. For example, if the emotion score is low, an encouraging message is displayed. Furthermore, the health trend display unit can save advice to elicit positive emotions in cloud storage for later analysis. For example, advice to elicit positive emotions is saved in the cloud for later analysis. This makes it possible to provide health advice that will evoke positive emotions and increase motivation for health management.

[0070] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0071] The health management system can also add a function to evaluate tongue movement and flexibility when recording the user's tongue condition. For example, the speed and range of tongue movement can be measured to evaluate tongue muscle strength and flexibility. Tongue movement data can also be saved in cloud storage for later analysis. This allows for a more detailed understanding of health conditions by evaluating tongue movement and flexibility.

[0072] The health management system can also measure the temperature of the user's tongue when recording the condition of the tongue and use the data for analysis. For example, a sensor that measures tongue temperature can be incorporated into the camera, automatically measuring the temperature when photographing. In addition, tongue temperature data can be saved in cloud storage and used for later analysis. This allows for more detailed analysis of health conditions by recording tongue temperature.

[0073] The health management system can also measure the humidity on the surface of the user's tongue when recording the condition of the tongue and use the data for analysis. For example, a humidity sensor can be built into the camera to automatically measure humidity when taking a photo. The humidity data on the surface of the tongue can also be saved in cloud storage and used for later analysis. This allows for more detailed analysis of health conditions by recording the humidity on the surface of the tongue.

[0074] The health management system can also add a function to analyze the surface texture of the user's tongue when recording the condition of the tongue. For example, the system can analyze the unevenness and smoothness of the tongue surface to evaluate the health condition. In addition, tongue surface texture data can be saved in cloud storage and used for later analysis. This allows for a more detailed evaluation of the health condition by analyzing the tongue surface texture.

[0075] The health management system can also add a function to analyze the state of the fine blood vessels in the user's tongue when recording the state of the tongue. For example, the state of the blood vessels in the tongue can be analyzed to evaluate the health state. In addition, data on the fine blood vessels in the tongue can be saved in cloud storage and used for later analysis. This allows for a more detailed evaluation of the health state by analyzing the state of the fine blood vessels in the tongue.

[0076] The health management system can also use an emotion estimation function to analyze the effect of a user's emotional state on the color and shape of their tongue. For example, it can analyze the effect of stress on tongue color. It can also introduce an algorithm to analyze the relationship between emotional state and tongue condition and analyze the data. This allows for a more detailed understanding of the user's health condition by analyzing the relationship between emotional state and tongue condition.

[0077] The health management system can further use the emotion estimation function to provide relaxing music or images so that the user can take a tongue photo in a relaxed state. For example, the app can play relaxing music to help the user take a photo in a calm state. It can also provide images with a relaxing effect. This allows the user to take a tongue photo in a relaxed state with the relaxing music and images.

[0078] The health management system can further use the emotion estimation function to provide health advice according to the user's emotional state and make suggestions to balance emotions and health. For example, if stress levels are high, it can suggest relaxation methods. It can also make specific suggestions to balance emotions and health. This makes it possible to provide health advice according to the user's emotional state and make suggestions to balance emotions and health.

[0079] The health management system can further use the emotion estimation function to provide health advice that will evoke the most positive emotions in the user, thereby increasing motivation for health management. For example, it can display positive messages and encouraging words. It can also monitor the user's emotional state in real time and provide specific advice to elicit positive emotions. This makes it possible to provide health advice that will evoke positive emotions and increase motivation for health management.

[0080] The health management system can also use its emotion estimation function to suggest the optimal timing to take a tongue photo so that the user can take the photo in the most relaxed state. For example, it can recommend a time of day when the emotion score is high. It can also monitor the user's emotional state in real time and suggest the optimal timing to take a photo. This allows the user to take a tongue photo in a relaxed state by suggesting the optimal timing.

[0081] The processing flow of the second embodiment will be briefly explained below.

[0082] Step 1: The tongue state recording unit acquires a photograph of the tongue. For example, the tongue photograph can be taken using a smartphone or a dedicated device. The tongue state recording unit can also save the photograph of the tongue as digital data. For example, the tongue photograph can be saved in cloud storage for later analysis. Step 2: The tongue color or shape analysis unit analyzes the photograph of the tongue captured by the tongue condition recording unit. For example, AI evaluates the color, shape, and surface condition of the tongue. The tongue color and shape analysis unit can also perform detailed analysis of various conditions, such as whether the tongue is red or has a lot of white coating. For example, AI can detect changes in tongue color and evaluate the health condition. Step 3: The health trend display unit displays health trends based on the results of the analysis by the tongue color or shape analysis unit. For example, based on the theory of traditional Chinese medicine, if there is a possibility that the body is overheated, it will advise the user to eat cool foods and drinks. The health trend display unit can also provide specific health management advice based on the analysis results. For example, if stress is building up, it will suggest that the user spend more time relaxing.

[0083] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0084] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0085] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0086] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0087] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0088] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0089] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0090] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0091] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0092] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0093] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0094] 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.

[0095] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0096] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart glasses 214 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0097] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0098] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0099] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0100] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0101] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0102] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0103] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0104] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0105] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0106] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0107] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0108] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0109] 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.

[0110] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0111] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 may also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0112] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0113] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0114] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0115] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0116] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0117] 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.

[0118] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0119] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0120] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0121] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0122] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0123] The control 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 emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0124] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0125] 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.

[0126] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0127] In the robot 414, the processor 46 performs the identification process. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0128] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0129] 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 control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0130] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0131] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0132] The emotion identification model 59 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 an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0133] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0134] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[0135] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0136] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0137] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs 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 a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[0138] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[0139] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0140] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0141] 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.

[0142] It is not necessary to store all 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 all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[0143] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A processor also includes a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0144] The hardware resource that executes the specific process may be configured with one of these various processors, or may be configured with 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). Also, the hardware resource that executes the specific process may be a single processor.

[0145] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0146] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[0147] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0148] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0149] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference. [Explanation of symbols]

[0150] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. a tongue condition recording unit that acquires a photograph of the tongue; a tongue color or shape analysis unit that analyzes the tongue photograph acquired by the tongue condition recording unit; a health trend display unit that displays health trends based on the results of analysis by the tongue color or shape analysis unit. A system characterized by:

2. The tongue state recording unit When taking the tongue photograph, the oral temperature or humidity is also recorded and this data is used for analysis.

2. The system of claim 1.

3. The tongue state recording unit In addition to the tongue photo, the system also takes photos of the entire mouth, simultaneously recording and analyzing the condition of the teeth and gums.

2. The system of claim 1.

4. The tongue color and shape analysis unit Introducing an algorithm that analyzes not only the color or shape of the tongue, but also the texture or state of the fine blood vessels on the surface of the tongue.

2. The system of claim 1.

5. The health trend display unit In addition to displaying health trends based on traditional Chinese medicine theory, the app provides comprehensive health advice that incorporates modern medical knowledge.

2. The system of claim 1.

6. The tongue state recording unit When taking the photograph of the tongue, the emotional state of the user at the time of taking the photograph is recorded, and the relationship between the emotion and the state of the tongue is analyzed.

2. The system of claim 1.

7. The tongue color and shape analysis unit Analyzing the effect of a user's emotional state on the color or shape of their tongue to clarify the relationship between emotions and health status 2. The system of claim 1.

8. The health trend display unit Providing health advice that evokes the most positive feelings in users and increasing their motivation to manage their health 2. The system of claim 1.

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