system

Abstract

We provide the system. [Solution] A full-body close-fitting garment, The sensor and low-frequency pad are placed inside the garment, A control unit connected to the garment, An external information processing device wirelessly connected to the control unit, The system is characterized in that an artificial intelligence module included in the information processing device visualizes the user's relaxation state based on data acquired by the sensor, generates operation instructions to optimize the relaxation state, and controls the low-frequency pad according to the operation instructions.

Description

Technical Field

[0004]

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Modern office workers and telecommuters are facing problems such as shoulder and neck stiffness, whole-body fatigue, and mental stress due to long hours of desk work and stress. In response, time and budget constraints for receiving regular massages and relaxation are major barriers. In addition, conventional massage devices and wearables can only provide general massage programs and are difficult to customize according to the individual user's condition and needs. In response to this problem, there is a demand for the provision of a more effective and individualized massage device.

Means for Solving the Problems

[0005] This invention provides a massage system comprising a garment that fits snugly to the entire body, sensors and low-frequency pads placed inside the garment, and an information processing device that controls these. Specifically, multiple sensors and low-frequency pads are placed inside the garment and powered via a control unit. The control unit is wirelessly connected to an external information processing device, and an artificial intelligence module included in the information processing device analyzes the user's biometric data acquired from the sensors. Based on this, the system visualizes the user's relaxation state, generates an optimal massage program, and operates the low-frequency pads. Furthermore, by collecting feedback from the user and allowing the artificial intelligence module to learn, it is possible to individually optimize the massage program for subsequent sessions. As a result, the user can always receive the optimal massage, effectively alleviating physical discomfort caused by prolonged desk work and stress.

[0006] "Full-body close-fitting clothing" refers to shirts and tights that are worn in close contact with the user's entire body, and are garments that have a structure that makes close contact with the user's body surface.

[0007] A "sensor" is a sensing device placed inside clothing to measure the user's body temperature, heart rate, skin conductance, and other biometric data.

[0008] A "low-frequency pad" is a device that provides a massage effect by applying low-frequency electrical currents to the user's muscles.

[0009] The "control unit" is a power supply and signal processing unit connected to the clothing to control the low-frequency pads and sensors.

[0010] An "information processing device" is an external device that is wirelessly connected to the control unit. Its role is to analyze data collected by sensors and execute a massage program.

[0011] An "artificial intelligence module" is an algorithm or program contained within an information processing device that analyzes the user's biometric data and generates an optimal massage program.

[0012] "Relaxed state" refers to a state that indicates the user's degree of physiological and psychological relaxation, and is evaluated based on data such as body temperature, heart rate, and skin conductance.

[0013] "Operation instructions" are massage operation commands generated by the artificial intelligence module and transmitted to the low-frequency pads via the control unit.

[0014] "Feedback" refers to evaluation information such as impressions, satisfaction levels, and suggestions for improvement that users provide after a massage session. [Brief explanation of the drawing]

[0015] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9]Shows an emotion map where multiple emotions are mapped. [Figure 10] Shows an emotion map where multiple emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Modes for Carrying Out the Invention

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

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

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

[0019] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

[0020] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

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

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0023] [First Embodiment]

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

[0025] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0026] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0027] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0028] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0032] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0033] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0034] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0035] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0036] The present invention is a system that provides an optimal massage for each individual user by incorporating sensors and low-frequency pads into full-body contact garments (shirts and tights) and wirelessly connecting them to an external information processing device (such as a smartphone). Specific embodiments of the present invention are described below.

[0037] System Configuration

[0038] clothing

[0039] The full-body garment is designed to fit snugly against the user's body surface. Multiple sensors are placed inside the garment to collect biometric data such as the user's body temperature, heart rate, and skin conductance. In addition, low-frequency pads are positioned in place and used to deliver low-frequency electrical currents to produce a massage effect.

[0040] control unit

[0041] The control unit is integrated into the clothing and serves as a power supply and signal processing unit for controlling the sensors and low-frequency pads. The control unit has an internal battery and can also communicate wirelessly.

[0042] Information processing device

[0043] The information processing device is an external device, such as a smartphone or tablet, that is wirelessly connected to the control unit. This information processing device is equipped with an artificial intelligence module that analyzes biometric data collected from sensors and visualizes the user's relaxation state. Based on this analysis, an optimal massage program is generated to maximize the user's relaxation level.

[0044] Program Implementation

[0045] User actions

[0046] The user first places a dedicated app on their smartphone and then puts on a full-body, form-fitting garment. Next, they turn on the power to the control unit. This activates the control unit and establishes a wireless connection with the smartphone.

[0047] Terminal processing

[0048] Once the device (smartphone) establishes a connection with the control unit, it begins collecting biometric data from sensors embedded in the clothing. This data is stored in internal memory in real time and transmitted to a cloud server using Wi-Fi or mobile data communication. For example, if a user performs this operation while working at a desk, their body temperature, heart rate, and skin conductance are monitored in real time.

[0049] Server Processing

[0050] The server analyzes the received biometric data to assess the user's current state of relaxation. An artificial intelligence module is used for the analysis, calculating a relaxation index based on heart rate variability and body temperature trends. Based on this relaxation index, an optimal massage pattern is generated, and instructions for the massage are created.

[0051] Receiving and controlling the device

[0052] The terminal receives operation instructions sent from the server and appropriately controls the low-frequency pads through the control unit. During this time, the user can experience the massage effect in real time.

[0053] User feedback

[0054] After a massage session, users provide feedback and comments within the app. This includes specific comments such as, "The shoulder massage was very effective," or "I'd like the back massage to be a little stronger." This feedback is sent from the device to the server and used to improve the accuracy of future massage programs.

[0055] Specific example

[0056] For example, consider a user A using this system to alleviate fatigue from daily desk work. In the morning, user A puts on a full-body garment, launches a dedicated app, and turns on the control unit. The device then collects biometric data, and the relaxation level is analyzed on a cloud server. AI generates an optimal massage program, and the low-frequency pads operate via the device. User A can receive an appropriate massage even while working, and provides feedback through the app afterward. This allows for an even more precise massage the next time the user uses the system.

[0057] In this way, the present invention allows the control unit, terminal, and server to work together to continuously provide the user with the optimal massage experience. By combining user feedback with the AI's learning function, the system's accuracy improves with each use, enabling more effective massages.

[0058] The following describes the processing flow.

[0059] Step 1:

[0060] The user launches the app on their smartphone. This starts the app and verifies the user's login information. Simultaneously, the user puts on a full-body garment and turns on the power to the control unit.

[0061] Step 2:

[0062] The device (smartphone) will turn on Bluetooth and attempt to connect to the control unit. If the connection is successful, "Connection successful" will be displayed on the smartphone screen.

[0063] Step 3:

[0064] The device begins collecting the user's biometric data (body temperature, heart rate, skin conductance, etc.) from sensors embedded in the clothing. This data is collected in real time and temporarily stored in the device's internal memory.

[0065] Step 4:

[0066] The device uses Wi-Fi or mobile data to send the collected biometric data to a cloud server. This allows the server to begin real-time analysis of the data.

[0067] Step 5:

[0068] The server analyzes the received biometric data and uses an AI algorithm to evaluate the user's relaxation state. A relaxation index is calculated, and analysis results based on the user's biometric data are generated.

[0069] Step 6:

[0070] Based on the analysis results, the server generates an optimal massage program to maximize the user's relaxation. Specifically, it determines instructions regarding the position, intensity, and rhythm of the low-frequency pads.

[0071] Step 7:

[0072] The server sends the generated massage program to the terminal. The terminal then confirms receipt and prepares to execute the massage.

[0073] Step 8:

[0074] The terminal sends instructions to the control unit based on the program received from the server. The control unit then causes the low-frequency pad to perform the operation as instructed.

[0075] Step 9:

[0076] The low-frequency pads deliver low-frequency electrical currents to the user's body at the instructed location, intensity, and rhythm, initiating a massage. During this time, the user can relax and experience the massage effect.

[0077] Step 10:

[0078] After the massage session ends, users record their thoughts and feedback about the massage experience within the app. For example, they can enter specific evaluations such as, "The shoulder massage was very effective," or "I would like the back massage to be more intense."

[0079] Step 11:

[0080] The device sends user feedback to the server. The server analyzes the received feedback, incorporates its contents into an AI module, and uses it to improve future massage programs.

[0081] Step 12:

[0082] The server retrains the AI ​​model based on this feedback data, improving it so that future massage programs are more effectively customized. This increases the system's accuracy and further enhances the massage effect for the user.

[0083] (Example 1)

[0084] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0085] Current massage systems struggle to provide optimal massage programs tailored to each user's individual needs. Many systems offer only fixed programs and cannot maximize massage effectiveness by utilizing user feedback or real-time biometric data. As a result, users do not experience sufficient relaxation, leading to inadequate relief from fatigue resulting from prolonged work or stress.

[0086] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0087] In this invention, the server includes means for wearing a full-body close-fitting garment, means for which sensors and a low-frequency generator are disposed inside the garment, means for which a control unit is connected to the garment, means for which an external information processing system is wirelessly connected to the control unit, and means for which a generating AI model installed in the information processing system displays the user's relaxation index based on biometric data acquired by the sensors, generates operation instructions to optimize the relaxation index, and controls the low-frequency generator according to the operation instructions. This makes it possible to provide an optimal massage program based on each user's biometric information and maximize the user's relaxation effect.

[0088] "Full-body contact clothing" refers to clothing designed to fit snugly against the user's entire body and incorporates various sensors and low-frequency generators.

[0089] A "sensor" is a device that detects biometric data such as a user's body temperature, heart rate, and skin conductance, and transmits this data to an external information processing system.

[0090] A "low-frequency generator" is a device that uses low-frequency electric current to produce a massage effect, stimulating the user's muscles by operating in a specified pattern.

[0091] A "control unit" is a device installed inside clothing that manages and controls sensors and low-frequency generators, and is equipped with power supply and wireless communication functions.

[0092] The "external information processing system" refers to a device wirelessly connected to the control unit, such as a smartphone or tablet, which analyzes the user's biometric data and generates a massage program.

[0093] A "generative AI model" is a type of artificial intelligence that uses machine learning and deep learning algorithms based on collected biometric data to calculate a user's relaxation index and generate the optimal massage program.

[0094] The "relaxation index" is an indicator calculated based on the user's biometric data, and it quantifies the user's state of relaxation.

[0095] "Operation instructions" refer to digital signals used to instruct the operation patterns of a low-frequency generator created by a generative AI model, and include instructions for executing a specific massage program.

[0096] The present invention is a system that provides an optimal massage for each individual user by incorporating sensors and a low-frequency generator into full-body contact clothing and wirelessly connecting them to an external information processing system (such as a smartphone). Specific embodiments of the present invention are described below.

[0097] System Configuration

[0098] clothing

[0099] The full-body contact garment is designed to fit snugly against the user's body surface. Multiple sensors are placed inside the garment to collect biometric data such as the user's body temperature, heart rate, and skin conductance. In addition, low-frequency generators are positioned in place and used to deliver low-frequency currents to produce a massage effect.

[0100] control unit

[0101] The control unit is integrated into the garment and serves as a power supply and signal processing unit for controlling the sensors and low-frequency generator. The control unit has an internal battery and can also communicate wirelessly.

[0102] Information processing system

[0103] The information processing system consists of an external device, such as a smartphone or tablet, that is wirelessly connected to the control unit. This information processing system is equipped with a generative AI model that analyzes biometric data collected from sensors and visualizes the user's relaxation state. Based on this analysis, an optimal massage program is generated to maximize the user's relaxation level.

[0104] Program Implementation

[0105] User actions

[0106] The user first launches a dedicated app on their smartphone and puts on the full-body, form-fitting clothing. Next, they turn on the power to the control unit. This activates the control unit and establishes a wireless connection with the smartphone.

[0107] Terminal processing

[0108] Once the device (smartphone) establishes a connection with the control unit, it begins collecting biometric data from sensors embedded in the clothing. This data is stored in internal memory in real time and transmitted to a cloud server using Wi-Fi or mobile data communication. For example, if a user performs this operation while working at a desk, their body temperature, heart rate, and skin conductance are monitored in real time.

[0109] Server Processing

[0110] The server analyzes the received biometric data to assess the user's current state of relaxation. A generative AI model is used for the analysis, calculating a relaxation index based on heart rate variability and body temperature trends. Based on this relaxation index, an optimal massage pattern is generated, and instructions are created.

[0111] Receiving and controlling the device

[0112] The terminal receives operation instructions transmitted from the server and appropriately controls the low-frequency generator through the control unit. During this time, the user can experience the massage effect in real time.

[0113] User feedback

[0114] After a massage session, users provide feedback and comments within the app. This includes specific comments such as, "The shoulder massage was very effective," or "I'd like the back massage to be a little stronger." This feedback is sent from the device to the server and used to improve the accuracy of future massage programs.

[0115] Specific example

[0116] For example, consider a user A using this system to alleviate fatigue from daily desk work. In the morning, user A puts on full-body contact clothing, launches a dedicated app, and turns on the control unit. The terminal then collects biometric data, and the relaxation level is analyzed on a cloud server. A generating AI model creates an optimal massage program, and the low-frequency generator operates via the terminal. User A can receive an appropriate massage even while working, and provides feedback via the app afterward. This allows for an even more precise massage the next time the system is used.

[0117] Example of a prompt

[0118] For example, the prompt might look like this: "Please generate an optimal massage program to relieve stiff shoulders and back pain caused by desk work. Evaluate the user's relaxation level based on their body temperature, heart rate, and skin conductance, and propose an operating pattern for the low-frequency generator."

[0119] In this way, the present invention allows the control unit, terminal, and server to work together to continuously provide the user with the optimal massage experience. By combining user feedback with the learning function of the generative AI model, the system's accuracy improves with each use, enabling more effective massages.

[0120] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0121] Step 1:

[0122] The user wears a full-body garment and launches a dedicated app on their smartphone. Next, they turn on the power to the control unit. The user's actions act as input, the control unit becomes active as output, and a wireless connection is established with the smartphone.

[0123] Step 2:

[0124] Once the smartphone (device) establishes a connection with the control unit, it begins collecting the user's biometric data (body temperature, heart rate, skin conductance) from sensors embedded in the clothing. The biometric data from the sensors is the input, and this is stored in the smartphone's internal memory in real time as the output. Furthermore, this data is transmitted to a cloud server using Wi-Fi or mobile data communication.

[0125] Step 3:

[0126] The cloud server receives biometric data transmitted from the smartphone. The biometric data is transferred to the server as input, and data analysis is performed on the server side as output. This allows the generating AI model to analyze heart rate variability and body temperature trends, and calculate a relaxation index. Specifically, it performs analysis of heart rate variability patterns and body temperature trends.

[0127] Step 4:

[0128] The generative AI model generates an optimal massage program based on a relaxation index. It takes analysis results as input and generates the optimal massage program as output. Specifically, prompts such as "Generate a relaxing massage pattern focusing on the shoulders and back based on the user's body temperature and heart rate data" are used.

[0129] Step 5:

[0130] The server sends the generated massage program to the smartphone. The generated massage program is the input, and this is received by the smartphone as the output. Specifically, the program data is transferred from the server.

[0131] Step 6:

[0132] The smartphone transfers the received massage program to the control unit, which then operates the low-frequency generator in the specified pattern. The input is an operation instruction from the server, and the output is the appropriate operation of the low-frequency generator. For example, the control might be: "To loosen the shoulder muscles, the low-frequency generator operates for 3 seconds, then pauses for 1 second."

[0133] Step 7:

[0134] After a massage session, users provide feedback through a dedicated app. The input consists of the user's impressions and opinions, and this feedback is sent to a cloud server via the device. Specific comments, such as "The shoulder massage was very effective" or "I'd like the back massage to be a little stronger," are recorded within the app.

[0135] Step 8:

[0136] The cloud server receives feedback from users, and the generating AI model uses this information to improve the accuracy of the next massage program generation. The input is user feedback data, and the output is an improved massage program for subsequent uses. Specifically, the AI ​​model performs a learning process based on the feedback data.

[0137] (Application Example 1)

[0138] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0139] The problem lies in the lack of efficient means of rest and relaxation for industrial workers who perform long hours of standing or heavy labor. Furthermore, conventional rest methods make it difficult to provide appropriate relaxation tailored to the individual needs of each worker.

[0140] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0141] In this invention, the server includes means for monitoring biometric data in real time and transmitting it to a cloud database, means for generating an optimal massage program using a generative AI model, means for notifying a head-mounted display, and means for collecting user feedback and adjusting the next massage program. This makes it possible for industrial workers to receive individually optimized relaxation.

[0142] "Full-body contact clothing" refers to clothing designed to fit snugly against the user's body surface and incorporating sensors for collecting biometric data and low-frequency pads to provide a massage effect.

[0143] A "sensor" is a device that measures a user's biometric data, such as body temperature, heart rate, and skin conductance.

[0144] A "low-frequency pad" is a device that produces a massage effect by applying a low-frequency electric current to a specific area.

[0145] The "control unit" is a device that controls the sensor and low-frequency pad, supplies power, and performs signal processing, and can be wirelessly connected to the information processing device.

[0146] An "information processing device" is an external device such as a smartphone or tablet that includes an artificial intelligence module for analyzing data acquired from sensors and generating an optimal massage program.

[0147] The "artificial intelligence module" is a software module that analyzes biometric data acquired by sensors, visualizes the user's relaxation state, and generates an optimal massage program.

[0148] A "generative AI model" is an artificial intelligence algorithm used to generate the optimal massage program based on biometric data.

[0149] A "head-mounted display" is a display device worn by the user and is used to display operation instructions generated by an artificial intelligence module.

[0150] "Feedback" is the process by which users provide their thoughts and opinions about their massage experience, and this information is used to improve future massage programs.

[0151] Modes for carrying out the invention

[0152] This invention is a system designed to improve the health management and rest efficiency of industrial workers. This invention makes it possible to provide individually optimized relaxation even during long hours of standing work or heavy labor.

[0153] System Configuration

[0154] clothing

[0155] The full-body contact garment is designed to fit snugly against the user's body surface. Inside the garment are multiple sensors and low-frequency pads. The sensors collect biometric data such as the user's body temperature, heart rate, and skin conductance. The low-frequency pads are used to produce a massage effect.

[0156] control unit

[0157] The control unit is integrated into the clothing and serves as a power supply and signal processing unit for controlling the sensors and low-frequency pads. The control unit has an internal battery and also communicates wirelessly.

[0158] Information processing device

[0159] The information processing device is an external device, such as a smartphone or tablet, that is wirelessly connected to the control unit. This information processing device is equipped with an artificial intelligence module that analyzes biometric data collected from sensors and visualizes the user's relaxation state. Based on this analysis, a generative AI model generates an optimal massage program.

[0160] Program Implementation

[0161] User actions

[0162] First, the user puts on a full-body garment and launches a dedicated app on their smartphone. Next, they turn on the power to the control unit. This activates the control unit and establishes a wireless connection with the smartphone.

[0163] Terminal processing

[0164] Once connected to the control unit, the device (smartphone) begins collecting biometric data from sensors embedded in the clothing. This data is stored in internal memory in real time and transmitted to a cloud server using Wi-Fi or mobile data communication. For example, if this operation is performed while the user is working, body temperature, heart rate, and skin conductance are monitored in real time.

[0165] Server Processing

[0166] The server analyzes the received biometric data to assess the user's current state of relaxation. A generative AI model is used for the analysis, calculating a relaxation index based on heart rate variability and body temperature trends. Based on this relaxation index, an optimal massage pattern is generated, and instructions are created.

[0167] Receiving and controlling the device

[0168] The terminal receives operation instructions sent from the server and appropriately controls the low-frequency pads through the control unit. During this time, the user can experience the massage effect in real time.

[0169] User feedback

[0170] After a massage session, users provide feedback and comments within the app. This includes specific comments such as "The shoulder massage was very effective" or "I'd like the back massage to be a little stronger." This feedback is sent from the device to the server and used to improve the accuracy of future massage programs.

[0171] Specific example

[0172] For example, if industrial worker A feels fatigued after working for a long time, the full-body contact garment detects this condition, and a generating AI model creates an optimal massage program. This instruction is sent to a terminal, and worker A can receive an appropriate massage using low-frequency pads during a break.

[0173] Example of a prompt

[0174] Monitor factory workers' vital data (heart rate, body temperature, skin conductance) in real time and generate an optimal massage program based on this data. Notify the worker of the results via a head-mounted display and provide them with the appropriate massage. Also, collect worker feedback to improve the next massage program.

[0175] In this way, the system of the present invention improves in accuracy with each use by combining user feedback and a generated AI model, providing more effective relaxation.

[0176] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0177] Step 1:

[0178] User operation: The user wears a full-body, form-fitting garment and launches a dedicated application on their smartphone to turn on the control unit. At this stage, the control unit becomes active and a wireless connection with the smartphone is established.

[0179] Input: User actions

[0180] Output: Establishment of wireless connection between the control unit and the smartphone.

[0181] Specific operation: The user launches the app and turns on the power to the control unit. The smartphone app recognizes the control unit and establishes a connection.

[0182] Step 2:

[0183] Data Collection: Once the device (smartphone) connects to the control unit, it begins collecting biometric data (heart rate, body temperature, skin conductance) from sensors embedded in the clothing. This data is stored in internal memory in real time and transmitted to a cloud server using Wi-Fi or mobile data communication.

[0184] Input: Data from sensors embedded in the clothing

[0185] Output: Biometric data sent to the cloud server

[0186] Specific operation: The sensor acquires the user's biometric data, the smartphone receives it, and sends it to a cloud server.

[0187] Step 3:

[0188] Data analysis and massage program generation: The server analyzes the received biometric data and calculates a relaxation index using a generated AI model. Based on the results, an optimal massage program is generated and action instructions are created.

[0189] Input: Biometric data sent to the cloud server

[0190] Output: Generated optimal massage program and operating instructions

[0191] Specific operation: The AI ​​module analyzes the data, and the generated AI model creates the optimal massage program and outputs it as an action instruction.

[0192] Step 4:

[0193] Receiving and executing operation instructions: The terminal (smartphone) receives operation instructions from the server and appropriately controls the low-frequency pads via the control unit. This allows the user to experience massage effects in real time.

[0194] Input: Operation instructions sent from the server

[0195] Output: Operation control of low-frequency pads

[0196] Specific operation: The smartphone receives operation instructions from the server and controls the operation of the low-frequency pad via the control unit.

[0197] Step 5:

[0198] User Feedback Collection: After a massage session ends, users provide feedback within the app. This feedback is sent from the device to the server and used to improve the accuracy of future massage programs.

[0199] Input: User feedback

[0200] Output: Data from the improved massage program

[0201] Specific operation: Users enter feedback within the app, which is sent to the server, and the AI ​​module incorporates it into the next program.

[0202] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0203] The present invention is a system for optimizing the user's relaxation state, comprising a sensor and low-frequency pad embedded in a full-body garment, as well as an information processing device equipped with an emotion engine. Specific embodiments of the present invention will be described below, along with specific examples illustrating the system's program and processing flow.

[0204] System Configuration

[0205] clothing

[0206] The full-body garment is designed to fit snugly against the user's body surface. Inside the garment are multiple sensors and low-frequency pads that collect biometric data such as the user's body temperature, heart rate, and skin conductance, and use low-frequency electrical currents to stimulate the muscles and produce a massage effect.

[0207] control unit

[0208] The control unit is integrated into the clothing and serves as a power supply and signal processing unit for controlling the sensors and low-frequency pads. The control unit has an internal battery and can also communicate wirelessly.

[0209] Information processing device

[0210] The information processing device is an external device, such as a smartphone or tablet, that is wirelessly connected to the control unit. This information processing device is equipped with an artificial intelligence module that analyzes biometric data collected from sensors and visualizes the user's relaxation state. It also includes an emotion engine that recognizes the user's emotions and provides auxiliary information to optimize the relaxation state.

[0211] Program Implementation

[0212] User actions

[0213] First, the user launches a dedicated app on their smartphone and puts on a full-body, form-fitting garment. Then, they turn on the power to the control unit. This activates the control unit and establishes a wireless connection with the smartphone.

[0214] Terminal processing

[0215] Once the device (smartphone) establishes a connection with the control unit, it begins collecting the user's biometric data (body temperature, heart rate, skin conductance, etc.) from sensors embedded in the clothing. This data is collected in real time and temporarily stored in the device's internal memory. The collected data is then sent to a cloud server.

[0216] Server Processing

[0217] The server analyzes the received biometric data and emotional data acquired by the emotion engine. An AI algorithm is used for the analysis to evaluate the user's relaxation state. A relaxation index is calculated, and analysis results are generated based on this index.

[0218] Analysis of the Emotion Engine

[0219] The emotion engine analyzes the user's facial expressions, voice tone, and body temperature changes to recognize their emotional state. For example, it can determine whether a user is stressed based on the movement of their facial muscles. This emotional data is also sent to the server and used to assess their state of relaxation.

[0220] Massage program generation

[0221] Based on the analysis results, the server generates an optimal massage program that maximizes the user's relaxation state. This also incorporates data from the emotion engine. Specifically, the position, intensity, and rhythm of the low-frequency pads are determined.

[0222] Control Unit Operation

[0223] The terminal sends instructions to the control unit based on the massage program received from the server. The control unit then instructs the low-frequency pads to perform the actions as instructed. During this time, the user can experience the massage effect.

[0224] User feedback

[0225] After the massage session ends, users record their thoughts and feedback about the massage experience within the app. For example, they can enter specific evaluations such as, "The shoulder massage was very effective," or "I would like the back massage to be more intense."

[0226] Feedback analysis

[0227] The device sends user feedback to the server. The server analyzes the received feedback, incorporates its contents into the AI ​​module and emotion engine, and uses it to improve future massage programs.

[0228] Specific example

[0229] For example, consider a user A using this system to alleviate fatigue from daily desk work. In the morning, user A puts on a full-body garment, launches a dedicated app, and turns on the control unit. The device then collects biometric data and emotional data such as facial expressions, which are analyzed on a cloud server. The AI ​​and emotion engine generate an optimal massage program, and the operation instructions are sent to the control unit via the device. User A can receive an appropriate massage even while working, and provides feedback through the app afterward. This allows for an even more precise massage the next time the system is used.

[0230] In this way, the present invention combines an emotion engine to create a system that provides a more precise relaxation effect. By incorporating user feedback and emotional data, the AI ​​continuously learns, improving the system's accuracy with each use and enabling a more effective massage.

[0231] The following describes the processing flow.

[0232] Step 1:

[0233] The user launches a dedicated app on their smartphone. This starts the app and verifies the user's login information. Simultaneously, the user puts on a full-body form-fitting garment and turns on the power to the control unit.

[0234] Step 2:

[0235] The device (smartphone) will turn on Bluetooth and attempt to connect to the control unit. If the connection is successful, "Connection successful" will be displayed on the smartphone screen.

[0236] Step 3:

[0237] The device begins collecting the user's biometric data (body temperature, heart rate, skin conductance, etc.) from sensors embedded in the clothing. This data is collected in real time and temporarily stored in the device's internal memory.

[0238] Step 4:

[0239] The device uses Wi-Fi or mobile data to send the collected biometric data to a cloud server. This allows the server to begin real-time analysis of the data.

[0240] Step 5:

[0241] The server analyzes the received biometric data and uses an AI algorithm to evaluate the user's relaxation state. A relaxation index is calculated, and the analysis results are generated.

[0242] Step 6:

[0243] The server's emotion engine analyzes the user's facial expressions, voice tone, body temperature changes, and other factors to recognize the user's emotional state. For example, it can identify situations where the user is feeling stressed.

[0244] Step 7:

[0245] Based on the recognition results from the emotion engine, the server performs further detailed analysis and evaluates the user's relaxed state, taking into account their emotional condition.

[0246] Step 8:

[0247] Based on the analysis results, the server generates an optimal massage program to maximize the user's relaxation. Specifically, it determines instructions regarding the position, intensity, and rhythm of the low-frequency pads.

[0248] Step 9:

[0249] The server sends the generated massage program to the terminal. The terminal confirms receipt and is ready to execute the massage.

[0250] Step 10:

[0251] The terminal sends instructions to the control unit based on the program received from the server. The control unit then causes the low-frequency pad to perform the operation as instructed.

[0252] Step 11:

[0253] The low-frequency pads deliver low-frequency electrical currents to the user's body at the instructed location, intensity, and rhythm, initiating a massage. During this time, the user can relax and experience the massage effect.

[0254] Step 12:

[0255] After the massage session ends, users record their thoughts and feedback about the massage experience within the app. For example, they can enter specific evaluations such as, "The shoulder massage was very effective," or "I would like the back massage to be more intense."

[0256] Step 13:

[0257] The device sends user feedback to the server. The server analyzes the received feedback, incorporates its contents into the AI ​​module and emotion engine, and uses it to improve future massage programs.

[0258] Step 14:

[0259] The server retrains the AI ​​model based on feedback data, improving it so that subsequent massage programs are more effectively customized. This increases the system's accuracy and further enhances the massage effect for the user.

[0260] (Example 2)

[0261] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0262] In modern society, health problems caused by stress and overwork are increasing, with physical fatigue and mental stress from desk work being particularly problematic. In this situation, there is a need to provide effective relaxation methods. However, conventional massage and relaxation devices often fail to adequately reflect the individual state and emotions of users, instead offering uniform programs. Therefore, it has been difficult to enhance relaxation effects tailored to each user's individual needs.

[0263] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for evaluating the user's relaxation state based on biometric data and emotional data, means for generating action instructions to optimize the user's relaxation state, and means for collecting and learning user feedback. This makes it possible to provide an optimal massage program tailored to the individual user's condition and to improve its accuracy.

[0264] "Full-body contact clothing" refers to clothing designed to fit snugly against the user's body surface, with sensors and low-frequency pads placed inside to collect biometric data and produce a massage effect.

[0265] A "sensor" is a device that collects biometric data such as body temperature, heart rate, and skin conductance in real time.

[0266] A "low-frequency pad" is a device that uses low-frequency electrical currents to stimulate muscles, producing a massage effect.

[0267] The "control unit" is a power supply and signal processing unit for controlling the sensor and low-frequency pad. It operates using a built-in battery and has wireless connectivity.

[0268] An "information processing device" is an external device such as a smartphone or tablet that is wirelessly connected to the control unit. It is equipped with an artificial intelligence module and analyzes data collected from sensors to visualize and optimize the user's relaxation state.

[0269] The "artificial intelligence module" is software that analyzes biometric data acquired by sensors and utilizes AI algorithms to evaluate and optimize the user's relaxation state.

[0270] The "emotion engine" is software that analyzes the user's facial expressions, voice tone, body temperature changes, etc., to recognize their emotional state, and it works in conjunction with the artificial intelligence module.

[0271] "Operation instructions" refer to control instructions that include the position, intensity, and rhythm of the low-frequency pads generated to optimize the user's relaxation state.

[0272] "Feedback" refers to the user's comments and evaluations regarding the effectiveness of the massage and areas for improvement after a massage session.

[0273] A "cloud server" is a remote server used to analyze collected biometric and emotional data and generate the optimal massage program.

[0274] This invention comprises a full-body, form-fitting garment with built-in sensors and low-frequency pads, as well as an information processing device equipped with an emotion engine, and is a system for optimizing the user's relaxation state. This system is implemented using the following hardware and software.

[0275] Hardware configuration

[0276] clothing

[0277] The full-body close-fitting clothing is designed to closely fit the user's body surface. Inside the clothing, a plurality of sensors and low-frequency pads with the following functions are arranged.

[0278] Sensors that collect biometric data such as body temperature, heart rate, and skin conductance

[0279] Low-frequency pads that generate a massage effect by passing a low-frequency current through the muscles

[0280] Control unit

[0281] The control unit is mounted on a part of the clothing and is a power supply and signal processing device for controlling the sensors and low-frequency pads. The control unit has the following functions.

[0282] It has a battery inside and also performs communication via wireless connection

[0283] Information processing device

[0284] The information processing device is an external device that is wirelessly connected to the control unit, such as a smartphone or a tablet. An artificial intelligence module with the following functions is installed in this information processing device.

[0285] Analyze the biometric data collected from the sensors

[0286] Using an emotion engine (software that analyzes facial expressions, voice tones, body temperature changes, etc. to recognize the user's emotional state), generate operation instructions for visualizing and optimizing the user's relaxation state

[0287] Software configuration

[0288] Dedicated app

[0289] The user installs the dedicated app on the smartphone, launches the app, and operates the system. This app has the following functions.

[0290] Collecting biometric data from sensors embedded in clothing.

[0291] Establish a wireless connection with the control unit and transmit control signals for the low-frequency pad.

[0292] Collect user feedback and send it to the cloud server.

[0293] Cloud Server

[0294] The cloud server has the following functions and operates as the central hub of the entire system.

[0295] Analysis of collected biometric and emotional data

[0296] Generating the optimal massage program to optimize relaxation.

[0297] The server uses an AI algorithm to evaluate the user's relaxation level and calculate a relaxation index.

[0298] Instructions for use (specific examples)

[0299] For example, consider a case where user A uses this system to alleviate fatigue from daily desk work. The system can be used by following these steps:

[0300] 1. In the morning, User A puts on full-body clothing and activates a dedicated app on their smartphone to turn on the control unit.

[0301] 2. The device (smartphone) collects biometric data and emotional data and sends it to a cloud server.

[0302] 3. The cloud server analyzes the data and generates the optimal massage program.

[0303] 4. Operation instructions from the server are sent to the control unit via the terminal, and the low-frequency pad performs the specified operation.

[0304] 5. User A can receive appropriate massages even during work.

[0305] 6. After the massage session, User A provides feedback in the app.

[0306] 7. The feedback is reflected for subsequent use, and more accurate massages are provided.

[0307] Examples of prompt sentences

[0308] As an example, the following shows the prompt sentences when evaluating the user's relaxation state on the server side and generating an optimal massage program.

[0309] "Analyze the user's biological data and emotional data, evaluate the relaxation state, and generate an optimal massage program. The biological data includes body temperature, heart rate, and skin conductance, and the emotional data is obtained based on facial expressions, voice tones, and body temperature changes."

[0310] <( The flow of the specific process in Example 2 will be described using FIG. 13.

[0311] <00,00980>Step 1:

[0312] Input: The user wears full-body close-fitting clothes and launches the dedicated app on the smartphone.

[0313] Operation: The user turns on the power of the control unit.

[0314] Output: A wireless connection between the control unit and the smartphone is established, and the connection status can be confirmed on the app.

[0315] Step 2:

[0316] [[ID=SO]]Input: Connection information from the control unit

[0317] Operation: The device (smartphone) confirms that a wireless connection has been established with the control unit and begins collecting biometric data (body temperature, heart rate, skin conductance, etc.) in real time from sensors embedded in the clothing.

[0318] Output: The collected biometric data is temporarily stored in the device's internal memory.

[0319] Step 3:

[0320] Input: Biometric data stored on the device

[0321] Operation: The device sends collected biometric data to a cloud server at regular intervals (e.g., every 10 seconds).

[0322] Output: Biometric data is uploaded to a cloud server.

[0323] Step 4:

[0324] Input: Biometric data and emotional data uploaded to a cloud server

[0325] Operation: Based on the received biometric and emotional data, the server uses an AI algorithm and emotion engine to analyze the user's relaxation state and calculate a relaxation index.

[0326] Output: Analysis results and a relaxation index are generated.

[0327] Step 5:

[0328] Input: Analysis results and relaxation index

[0329] Operation: Based on this data, the server generates an optimal massage program to optimize the user's relaxation state.

[0330] Output: The generated massage program is saved on the server.

[0331] Step 6:

[0332] Input: Generated massage program

[0333] Operation: The terminal sends instructions to the control unit based on the massage program received from the server.

[0334] Output: The instruction reaches the control unit, and the operation of the low-frequency pad begins.

[0335] Step 7:

[0336] Input: Operation instructions from the control unit.

[0337] Operation: The control unit applies the specified current to the low-frequency pad, providing a massage effect to the user's body.

[0338] Output: The user experiences the massage effect.

[0339] Step 8:

[0340] Input: Feedback form after massage session

[0341] Operation: Users enter their feedback and ratings about their massage experience within the app.

[0342] Output: Feedback is saved to the device.

[0343] Step 9:

[0344] Input: Feedback saved on the device

[0345] Operation: The device sends user feedback to the cloud server.

[0346] Output: Feedback is uploaded to the cloud server.

[0347] Step 10:

[0348] Input: Feedback uploaded to the cloud server

[0349] Operation: The server analyzes the received feedback, incorporates its contents into the AI ​​module and emotion engine, and uses them to improve future massage programs.

[0350] Output: Data is updated to generate more accurate massage programs for future sessions.

[0351] (Application Example 2)

[0352] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0353] In aesthetic and massage salons, there is a demand for treatments that optimize the user's relaxation state. However, because this depends on the skill and experience of the staff, it is difficult to provide the optimal relaxation effect for each individual user. Furthermore, there is a need for a system that analyzes the user's biometric data and emotional state in real time and provides an optimal massage program based on that analysis. However, conventional technology does not have a sufficiently established means of effectively collecting, analyzing, and reflecting this data in treatments.

[0354] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0355] In this invention, the server includes means for collecting biometric data acquired by sensors in real time, means for analyzing the user's emotional state using an emotion engine, and means for generating an optimal massage program based on the analysis results. This enables the staff to accurately analyze the user's relaxation state and perform the most appropriate treatment based on that analysis.

[0356] "Full-body contact clothing" refers to clothing designed to fit snugly to the user's entire body, and is a device that uses built-in sensors and low-frequency pads to collect biometric data and provide relaxation effects.

[0357] A "sensor" is a device used to collect biological data such as body temperature, heart rate, and skin conductance.

[0358] A "low-frequency pad" is a device that uses low-frequency electrical currents to produce a massage effect on muscles.

[0359] The "control unit" is a power supply and signal processing device for controlling sensors and low-frequency pads embedded in clothing. It also has a built-in battery and communicates wirelessly.

[0360] An "information processing device" is an external device that is wirelessly connected to the control unit. It is equipped with an artificial intelligence module, analyzes biometric data collected from sensors, visualizes the user's relaxation state, and generates optimal action instructions.

[0361] An "artificial intelligence module" is software or hardware that analyzes the user's relaxation state based on data acquired by sensors and generates optimal action instructions.

[0362] An "emotion engine" is an artificial intelligence technology that analyzes a user's emotional state and is used to evaluate their relaxation level and generate the optimal massage program.

[0363] "Feedback" refers to the comments and evaluations that users provide about their massage experience, and this information is used to improve future treatments.

[0364] A "massage program" is a plan that includes specific instructions regarding the position, intensity, and rhythm of the low-frequency pads in order to optimize the user's relaxation state.

[0365] A "cloud server" is a computer server located in a remote location that stores and analyzes data via the internet.

[0366] An "aesthetic salon" is a business that provides treatments for the purpose of beauty and relaxation.

[0367] A "massage salon" is a business that provides massage treatments for the purpose of relaxation and fatigue relief.

[0368] composition

[0369] This invention is a system consisting of a full-body garment, sensors and low-frequency pads placed inside the garment, a control unit connected to the garment, and an external information processing device wirelessly connected to the control unit. This system is particularly intended for use in aesthetic salons and massage salons.

[0370] Full-body close-fitting clothing

[0371] The full-body garment is designed to fit snugly against the user's body surface. It incorporates multiple sensors to collect biometric data such as body temperature, heart rate, and skin conductance, as well as low-frequency pads that deliver low-frequency electrical currents for muscle massage.

[0372] control unit

[0373] The control unit is integrated into the clothing and controls the built-in sensors and low-frequency pads. The control unit has a built-in battery that supplies the necessary power. Furthermore, the control unit can communicate with an external information processing device via wireless connection.

[0374] Information processing device

[0375] The information processing device is an external device, such as a smartphone or tablet, that is wirelessly connected to the control unit. This information processing device is equipped with an artificial intelligence module and an emotion engine. It analyzes biometric data collected from sensors and emotional data from the emotion engine to generate action instructions that optimize the user's relaxation state.

[0376] User operation and treatment

[0377] The user wears a full-body, form-fitting garment and launches a dedicated application on their smartphone. Next, they turn on the power to the control unit, which activates the unit and establishes a wireless connection with the smartphone. The smartphone collects biometric data from the sensors in real time and transmits it to a cloud server.

[0378] Server Processing

[0379] The server uses AI algorithms to analyze the received biometric and emotional data. The analysis assesses the user's relaxation state, and a relaxation index is calculated based on this data. The final analysis results generate an optimal massage program.

[0380] Staff collaboration

[0381] Staff at aesthetic and massage salons perform treatments according to the optimal massage program provided by the information processing device. After the treatment, users provide feedback on their massage experience within the app. This feedback, along with biometric data, is sent to a cloud server and used to optimize future treatments.

[0382] Hardware and software used

[0383] Sensors: Devices that measure body temperature, heart rate, and skin conductance.

[0384] Low-frequency pads: Devices that use low-frequency electrical currents to perform muscle massage.

[0385] Control Unit: A device that controls sensors and low-frequency pads and has wireless communication capabilities.

[0386] Information processing device: Smartphones, tablets, and other devices with internet connectivity.

[0387] Artificial Intelligence Module: Uses Python and machine learning libraries such as scikit-learn for data analysis.

[0388] Cloud server: A remote computer system for storing and analyzing data.

[0389] Specific example

[0390] A user visiting an aesthetic salon wears a full-body garment and begins treatment using a dedicated application. A smartphone collects biometric data from sensors in the garment and analyzes it in real time on a cloud server. AI and an emotion engine generate an optimal massage program, which is then provided to the staff. After the treatment, the user's feedback is analyzed again, and a more precise massage is provided on the next visit.

[0391] Example of a prompt

[0392] "To enhance the massage effect, collect the user's heart rate, body temperature, and skin conductance data in real time and analyze it using an emotion engine. Based on the analysis results, write Python code to generate the optimal massage program."

[0393] The above describes a specific embodiment for carrying out this invention. This system makes it possible to accurately analyze the user's relaxation state and provide the optimal treatment.

[0394] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0395] Step 1:

[0396] User actions

[0397] The user wears a full-body garment and launches a dedicated application on their smartphone. The user then turns on the control unit and confirms the wireless connection between the smartphone and the control unit.

[0398] Input: The user puts on clothes and launches a smartphone app.

[0399] Output: The control unit is powered on and a wireless connection is established.

[0400] Step 2:

[0401] Collection of biometric data

[0402] Once the device (smartphone) establishes a wireless connection with the control unit, it begins collecting the user's biometric data (body temperature, heart rate, skin conductance) in real time from sensors embedded in the clothing. This data is temporarily stored in the device's internal memory.

[0403] Input: Biometric data from connected sensors.

[0404] Output: Biometric data stored in the device's internal memory.

[0405] Step 3:

[0406] Sending data

[0407] The device sends the collected biometric data to a cloud server. The data is transferred using a secure protocol.

[0408] Input: Biometric data stored in the device's internal memory.

[0409] Output: Biometric data sent to the cloud server.

[0410] Step 4:

[0411] Data Analysis

[0412] The server analyzes the received biometric data using AI algorithms. Specifically, it performs preprocessing such as smoothing and filtering, and then uses statistical methods and machine learning models (for example, scikit-learn's RandomForestClassifier) ​​to calculate a relaxation index. In addition, an emotion engine analyzes the user's emotional data.

[0413] Input: Biometric data sent to the server.

[0414] Output: Analyzed relaxation state and relaxation index.

[0415] Step 5:

[0416] Massage program generation

[0417] The server generates an optimal massage program based on the analysis results. This program includes specific operational instructions such as the position, intensity, and rhythm of the low-frequency pads. The server then transmits this data to the terminal.

[0418] Input: Analyzed relaxation state and relaxation index.

[0419] Output: The optimal massage program sent to the terminal.

[0420] Step 6:

[0421] Execution of the procedure

[0422] The terminal sends instructions to the control unit based on the massage program received from the server. The control unit then instructs the low-frequency pads to perform the actions as instructed. During this time, the user experiences the massage effect.

[0423] Input: Optimal massage program.

[0424] Output: Massage effect applied to the user.

[0425] Step 7:

[0426] Collecting user feedback

[0427] After the treatment is complete, users record their thoughts and feedback about the massage experience within the app. This feedback is entered as a form within the application.

[0428] Input: User feedback.

[0429] Output: Feedback data stored on the device.

[0430] Step 8:

[0431] Sending and analyzing feedback

[0432] The device sends user feedback to a cloud server. The server analyzes the received feedback and incorporates it into the AI ​​module and emotion engine. This feedback is then used to improve future massage programs.

[0433] Input: Feedback data stored on the device.

[0434] Output: Improved massage program for future sessions.

[0435] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0436] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include those described above. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions shown by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0437] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0438] [Second Embodiment]

[0439] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0440] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0441] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0442] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0443] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0444] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0445] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0446] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0447] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0448] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0449] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0450] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0451] The present invention is a system that provides an optimal massage for each individual user by incorporating sensors and low-frequency pads into full-body, form-fitting clothing (shirts and tights) and wirelessly connecting them to an external information processing device (such as a smartphone). Specific embodiments of the present invention are described below.

[0452] System Configuration

[0453] clothing

[0454] The full-body garment is designed to fit snugly against the user's body surface. Multiple sensors are placed inside the garment to collect biometric data such as the user's body temperature, heart rate, and skin conductance. In addition, low-frequency pads are positioned in place and used to deliver low-frequency electrical currents to produce a massage effect.

[0455] control unit

[0456] The control unit is integrated into the clothing and serves as a power supply and signal processing unit for controlling the sensors and low-frequency pads. The control unit has an internal battery and can also communicate wirelessly.

[0457] Information processing device

[0458] The information processing device is an external device, such as a smartphone or tablet, that is wirelessly connected to the control unit. This information processing device is equipped with an artificial intelligence module that analyzes biometric data collected from sensors and visualizes the user's relaxation state. Based on this analysis, an optimal massage program is generated to maximize the user's relaxation level.

[0459] Program Implementation

[0460] User actions

[0461] The user first places a dedicated app on their smartphone and then puts on a full-body, form-fitting garment. Next, they turn on the power to the control unit. This activates the control unit and establishes a wireless connection with the smartphone.

[0462] Terminal processing

[0463] Once the device (smartphone) establishes a connection with the control unit, it begins collecting biometric data from sensors embedded in the clothing. This data is stored in internal memory in real time and transmitted to a cloud server using Wi-Fi or mobile data communication. For example, if a user performs this operation while working at a desk, their body temperature, heart rate, and skin conductance are monitored in real time.

[0464] Server Processing

[0465] The server analyzes the received biometric data to assess the user's current state of relaxation. An artificial intelligence module is used for the analysis, calculating a relaxation index based on heart rate variability and body temperature trends. Based on this relaxation index, an optimal massage pattern is generated, and instructions for the massage are created.

[0466] Receiving and controlling the device

[0467] The terminal receives operation instructions transmitted from the server and appropriately controls the low-frequency pads through the control unit. During this time, the user can experience the massage effect in real time.

[0468] User feedback

[0469] After a massage session, users provide feedback and comments within the app. This includes specific comments such as, "The shoulder massage was very effective," or "I'd like the back massage to be a little stronger." This feedback is sent from the device to the server and used to improve the accuracy of future massage programs.

[0470] Specific example

[0471] For example, consider a user A using this system to alleviate fatigue from daily desk work. In the morning, user A puts on a full-body garment, launches a dedicated app, and turns on the control unit. The device then collects biometric data, and the relaxation level is analyzed on a cloud server. AI generates an optimal massage program, and the low-frequency pads operate via the device. User A can receive an appropriate massage even while working, and provides feedback through the app afterward. This allows for an even more precise massage the next time the user uses the system.

[0472] In this way, the present invention allows the control unit, terminal, and server to work together to continuously provide the user with the optimal massage experience. By combining user feedback with AI learning capabilities, the system's accuracy improves with each use, enabling more effective massages.

[0473] The following describes the processing flow.

[0474] Step 1:

[0475] The user launches the app on their smartphone. This starts the app and verifies the user's login information. Simultaneously, the user puts on a full-body garment and turns on the power to the control unit.

[0476] Step 2:

[0477] The device (smartphone) will turn on Bluetooth and attempt to connect to the control unit. If the connection is successful, "Connection successful" will be displayed on the smartphone screen.

[0478] Step 3:

[0479] The device begins collecting the user's biometric data (such as body temperature, heart rate, and skin conductance) from sensors embedded in the clothing. This data is collected in real time and temporarily stored in the device's internal memory.

[0480] Step 4:

[0481] The device uses Wi-Fi or mobile data to send the collected biometric data to a cloud server. This allows the server to begin real-time analysis of the data.

[0482] Step 5:

[0483] The server analyzes the received biometric data and uses an AI algorithm to evaluate the user's relaxation state. A relaxation index is calculated, and analysis results based on the user's biometric data are generated.

[0484] Step 6:

[0485] Based on the analysis results, the server generates an optimal massage program to maximize the user's relaxation. Specifically, it determines instructions regarding the position, intensity, and rhythm of the low-frequency pads.

[0486] Step 7:

[0487] The server sends the generated massage program to the terminal. The terminal then confirms receipt and prepares to execute the massage.

[0488] Step 8:

[0489] The terminal sends instructions to the control unit based on the program received from the server. The control unit then causes the low-frequency pad to perform the operation as instructed.

[0490] Step 9:

[0491] The low-frequency pads deliver low-frequency electrical currents to the user's body at the instructed location, intensity, and rhythm, initiating a massage. During this time, the user can relax and experience the massage effect.

[0492] Step 10:

[0493] After the massage session ends, users record their thoughts and feedback about the massage experience within the app. For example, they can enter specific evaluations such as, "The shoulder massage was very effective," or "I would like the back massage to be more intense."

[0494] Step 11:

[0495] The device sends user feedback to the server. The server analyzes the received feedback, incorporates its contents into an AI module, and uses it to improve future massage programs.

[0496] Step 12:

[0497] The server retrains the AI ​​model based on this feedback data, improving it so that future massage programs are more effectively customized. This increases the system's accuracy and further enhances the massage effect for the user.

[0498] (Example 1)

[0499] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0500] Current massage systems struggle to provide optimal massage programs tailored to each user's individual needs. Many systems offer only fixed programs and cannot maximize massage effectiveness by utilizing user feedback or real-time biometric data. As a result, users do not experience sufficient relaxation, leading to inadequate relief from fatigue resulting from prolonged work or stress.

[0501] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0502] In this invention, the server includes means for wearing a full-body close-fitting garment, means for which sensors and a low-frequency generator are disposed inside the garment, means for which a control unit is connected to the garment, means for which an external information processing system is wirelessly connected to the control unit, and means for which a generating AI model installed in the information processing system displays the user's relaxation index based on biometric data acquired by the sensors, generates operation instructions to optimize the relaxation index, and controls the low-frequency generator according to the operation instructions. This makes it possible to provide an optimal massage program based on each user's biometric information and maximize the user's relaxation effect.

[0503] "Full-body contact clothing" refers to clothing designed to fit snugly against the user's entire body and incorporates various sensors and low-frequency generators.

[0504] A "sensor" is a device that detects biometric data such as a user's body temperature, heart rate, and skin conductance, and transmits this data to an external information processing system.

[0505] A "low-frequency generator" is a device that uses low-frequency electric current to produce a massage effect, stimulating the user's muscles by operating in a specified pattern.

[0506] A "control unit" is a device installed inside clothing that manages and controls sensors and low-frequency generators, and is equipped with power supply and wireless communication functions.

[0507] The "external information processing system" refers to a device wirelessly connected to the control unit, such as a smartphone or tablet, which analyzes the user's biometric data and generates a massage program.

[0508] A "generative AI model" is a type of artificial intelligence that uses machine learning and deep learning algorithms based on collected biometric data to calculate a user's relaxation index and generate the optimal massage program.

[0509] The "relaxation index" is an indicator calculated based on the user's biometric data, and it quantifies the user's state of relaxation.

[0510] "Operation instructions" refer to digital signals used to instruct the operation patterns of a low-frequency generator created by a generative AI model, and include instructions for executing a specific massage program.

[0511] The present invention is a system that provides an optimal massage for each individual user by incorporating sensors and a low-frequency generator into full-body contact clothing and wirelessly connecting them to an external information processing system (such as a smartphone). Specific embodiments of the present invention are described below.

[0512] System Configuration

[0513] clothing

[0514] The full-body contact garment is designed to fit snugly against the user's body surface. Multiple sensors are placed inside the garment to collect biometric data such as the user's body temperature, heart rate, and skin conductance. In addition, low-frequency generators are positioned in place and used to deliver low-frequency currents to produce a massage effect.

[0515] control unit

[0516] The control unit is integrated into the garment and serves as a power supply and signal processing unit for controlling the sensors and low-frequency generator. The control unit has an internal battery and can also communicate wirelessly.

[0517] Information processing system

[0518] The information processing system consists of an external device, such as a smartphone or tablet, that is wirelessly connected to the control unit. This information processing system is equipped with a generative AI model that analyzes biometric data collected from sensors and visualizes the user's relaxation state. Based on this analysis, an optimal massage program is generated to maximize the user's relaxation level.

[0519] Program Implementation

[0520] User actions

[0521] The user first launches a dedicated app on their smartphone and puts on the full-body, form-fitting clothing. Next, they turn on the power to the control unit. This activates the control unit and establishes a wireless connection with the smartphone.

[0522] Terminal processing

[0523] Once the device (smartphone) establishes a connection with the control unit, it begins collecting biometric data from sensors embedded in the clothing. This data is stored in internal memory in real time and transmitted to a cloud server using Wi-Fi or mobile data communication. For example, if a user performs this operation while working at a desk, their body temperature, heart rate, and skin conductance are monitored in real time.

[0524] Server Processing

[0525] The server analyzes the received biometric data to assess the user's current state of relaxation. A generative AI model is used for the analysis, calculating a relaxation index based on heart rate variability and body temperature trends. Based on this relaxation index, an optimal massage pattern is generated, and instructions are created.

[0526] Receiving and controlling the device

[0527] The terminal receives operation instructions transmitted from the server and appropriately controls the low-frequency generator through the control unit. During this time, the user can experience the massage effect in real time.

[0528] User feedback

[0529] After a massage session, users provide feedback and comments within the app. This includes specific comments such as, "The shoulder massage was very effective," or "I'd like the back massage to be a little stronger." This feedback is sent from the device to the server and used to improve the accuracy of future massage programs.

[0530] Specific example

[0531] For example, consider a user A using this system to alleviate fatigue from daily desk work. In the morning, user A puts on full-body contact clothing, launches a dedicated app, and turns on the control unit. The terminal then collects biometric data, and the relaxation level is analyzed on a cloud server. A generating AI model creates an optimal massage program, and the low-frequency generator operates via the terminal. User A can receive an appropriate massage even while working, and provides feedback via the app afterward. This allows for an even more precise massage the next time the system is used.

[0532] Example of a prompt

[0533] For example, the prompt might look like this: "Please generate an optimal massage program to relieve stiff shoulders and back pain caused by desk work. Evaluate the user's relaxation level based on their body temperature, heart rate, and skin conductance, and propose an operating pattern for the low-frequency generator."

[0534] In this way, the present invention allows the control unit, terminal, and server to work together to continuously provide the user with the optimal massage experience. By combining user feedback with the learning function of the generative AI model, the system's accuracy improves with each use, enabling more effective massages.

[0535] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0536] Step 1:

[0537] The user wears a full-body garment and launches a dedicated app on their smartphone. Next, they turn on the power to the control unit. The user's actions act as input, the control unit becomes active as output, and a wireless connection is established with the smartphone.

[0538] Step 2:

[0539] Once the smartphone (device) establishes a connection with the control unit, it begins collecting the user's biometric data (body temperature, heart rate, skin conductance) from sensors embedded in the clothing. The biometric data from the sensors is the input, and this is stored in the smartphone's internal memory in real time as the output. Furthermore, this data is transmitted to a cloud server using Wi-Fi or mobile data communication.

[0540] Step 3:

[0541] The cloud server receives biometric data transmitted from the smartphone. The biometric data is transferred to the server as input, and data analysis is performed on the server side as output. This allows the generating AI model to analyze heart rate variability and body temperature trends, and calculate a relaxation index. Specifically, it performs analysis of heart rate variability patterns and body temperature trends.

[0542] Step 4:

[0543] The generative AI model generates an optimal massage program based on a relaxation index. It takes analysis results as input and generates the optimal massage program as output. Specifically, prompts such as "Generate a relaxing massage pattern focusing on the shoulders and back based on the user's body temperature and heart rate data" are used.

[0544] Step 5:

[0545] The server sends the generated massage program to the smartphone. The generated massage program is the input, and this is received by the smartphone as the output. Specifically, the program data is transferred from the server.

[0546] Step 6:

[0547] The smartphone transfers the received massage program to the control unit, which then operates the low-frequency generator in the specified pattern. The input is an operation instruction from the server, and the output is the appropriate operation of the low-frequency generator. For example, the control might be: "To loosen the shoulder muscles, the low-frequency generator operates for 3 seconds, then pauses for 1 second."

[0548] Step 7:

[0549] After a massage session, users provide feedback through a dedicated app. The input consists of the user's impressions and opinions, and this feedback is sent to a cloud server via the device. Specific comments, such as "The shoulder massage was very effective" or "I'd like the back massage to be a little stronger," are recorded within the app.

[0550] Step 8:

[0551] The cloud server receives feedback from users, and the generating AI model uses this information to improve the accuracy of the next massage program generation. The input is user feedback data, and the output is an improved massage program for subsequent uses. Specifically, the AI ​​model performs a learning process based on the feedback data.

[0552] (Application Example 1)

[0553] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0554] The problem lies in the lack of efficient means of rest and relaxation for industrial workers who perform long hours of standing or heavy labor. Furthermore, conventional rest methods make it difficult to provide appropriate relaxation tailored to the individual needs of each worker.

[0555] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0556] In this invention, the server includes means for monitoring biometric data in real time and transmitting it to a cloud database, means for generating an optimal massage program using a generative AI model, means for notifying a head-mounted display, and means for collecting user feedback and adjusting the next massage program. This makes it possible for industrial workers to receive individually optimized relaxation.

[0557] "Full-body contact clothing" refers to clothing designed to fit snugly against the user's body surface and incorporating sensors for collecting biometric data and low-frequency pads to provide a massage effect.

[0558] A "sensor" is a device that measures a user's biometric data, such as body temperature, heart rate, and skin conductance.

[0559] A "low-frequency pad" is a device that produces a massage effect by applying a low-frequency electric current to a specific area.

[0560] The "control unit" is a device that controls the sensor and low-frequency pad, supplies power, and performs signal processing, and can be wirelessly connected to the information processing device.

[0561] An "information processing device" is an external device such as a smartphone or tablet that includes an artificial intelligence module for analyzing data acquired from sensors and generating an optimal massage program.

[0562] The "artificial intelligence module" is a software module that analyzes biometric data acquired by sensors, visualizes the user's relaxation state, and generates an optimal massage program.

[0563] A "generative AI model" is an artificial intelligence algorithm used to generate the optimal massage program based on biometric data.

[0564] A "head-mounted display" is a display device worn by the user and is used to display operation instructions generated by an artificial intelligence module.

[0565] "Feedback" is the process by which users provide their thoughts and opinions about their massage experience, and this information is used to improve future massage programs.

[0566] Modes for carrying out the invention

[0567] This invention is a system designed to improve the health management and rest efficiency of industrial workers. This invention makes it possible to provide individually optimized relaxation even during long hours of standing work or heavy labor.

[0568] System Configuration

[0569] clothing

[0570] The full-body contact garment is designed to fit snugly against the user's body surface. Inside the garment are multiple sensors and low-frequency pads. The sensors collect biometric data such as the user's body temperature, heart rate, and skin conductance. The low-frequency pads are used to produce a massage effect.

[0571] control unit

[0572] The control unit is integrated into the clothing and serves as a power supply and signal processing unit for controlling the sensors and low-frequency pads. The control unit has an internal battery and also communicates wirelessly.

[0573] Information processing device

[0574] The information processing device is an external device, such as a smartphone or tablet, that is wirelessly connected to the control unit. This information processing device is equipped with an artificial intelligence module that analyzes biometric data collected from sensors and visualizes the user's relaxation state. Based on this analysis, a generative AI model generates an optimal massage program.

[0575] Program Implementation

[0576] User actions

[0577] First, the user puts on a full-body garment and launches a dedicated app on their smartphone. Next, they turn on the power to the control unit. This activates the control unit and establishes a wireless connection with the smartphone.

[0578] Terminal processing

[0579] Once connected to the control unit, the device (smartphone) begins collecting biometric data from sensors embedded in the clothing. This data is stored in internal memory in real time and transmitted to a cloud server using Wi-Fi or mobile data communication. For example, if this operation is performed while the user is working, body temperature, heart rate, and skin conductance are monitored in real time.

[0580] Server Processing

[0581] The server analyzes the received biometric data to assess the user's current state of relaxation. A generative AI model is used for the analysis, calculating a relaxation index based on heart rate variability and body temperature trends. Based on this relaxation index, an optimal massage pattern is generated, and instructions are created.

[0582] Receiving and controlling the device

[0583] The terminal receives operation instructions transmitted from the server and appropriately controls the low-frequency pads through the control unit. During this time, the user can experience the massage effect in real time.

[0584] User feedback

[0585] After a massage session, users provide feedback and comments within the app. This includes specific comments such as "The shoulder massage was very effective" or "I'd like the back massage to be a little stronger." This feedback is sent from the device to the server and used to improve the accuracy of future massage programs.

[0586] Specific example

[0587] For example, if industrial worker A feels fatigued after working for a long time, the full-body contact garment detects this condition, and a generating AI model creates an optimal massage program. This instruction is sent to a terminal, and worker A can receive an appropriate massage using low-frequency pads during a break.

[0588] Example of a prompt

[0589] Monitor factory workers' vital data (heart rate, body temperature, skin conductance) in real time and generate an optimal massage program based on this data. Notify the worker of the results via a head-mounted display and provide them with the appropriate massage. Also, collect worker feedback to improve the next massage program.

[0590] In this way, the system of the present invention improves in accuracy with each use by combining user feedback and a generated AI model, providing more effective relaxation.

[0591] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0592] Step 1:

[0593] User Operation: The user wears a full-body, form-fitting garment and activates a dedicated application on their smartphone to turn on the control unit. At this stage, the control unit becomes active and a wireless connection with the smartphone is established.

[0594] Input: User actions

[0595] Output: Establishment of wireless connection between the control unit and the smartphone.

[0596] Specific operation: The user launches the app and turns on the power to the control unit. The smartphone app recognizes the control unit and establishes a connection.

[0597] Step 2:

[0598] Data Collection: Once the device (smartphone) connects to the control unit, it begins collecting biometric data (heart rate, body temperature, skin conductance) from sensors embedded in the clothing. This data is stored in internal memory in real time and transmitted to a cloud server using Wi-Fi or mobile data communication.

[0599] Input: Data from sensors embedded in the clothing

[0600] Output: Biometric data sent to the cloud server

[0601] Specific operation: The sensor acquires the user's biometric data, the smartphone receives it, and sends it to a cloud server.

[0602] Step 3:

[0603] Data analysis and massage program generation: The server analyzes the received biometric data and calculates a relaxation index using a generated AI model. Based on the results, an optimal massage program is generated and action instructions are created.

[0604] Input: Biometric data sent to the cloud server

[0605] Output: Generated optimal massage program and operating instructions

[0606] Specific operation: The AI ​​module analyzes the data, and the generated AI model creates the optimal massage program and outputs it as an action instruction.

[0607] Step 4:

[0608] Receiving and executing operation instructions: The terminal (smartphone) receives operation instructions from the server and appropriately controls the low-frequency pads via the control unit. This allows the user to experience massage effects in real time.

[0609] Input: Operation instructions sent from the server

[0610] Output: Operation control of low-frequency pads

[0611] Specific operation: The smartphone receives operation instructions from the server and controls the operation of the low-frequency pad via the control unit.

[0612] Step 5:

[0613] User Feedback Collection: After a massage session ends, users provide feedback within the app. This feedback is sent from the device to the server and used to improve the accuracy of future massage programs.

[0614] Input: User feedback

[0615] Output: Data from the improved massage program

[0616] Specific operation: Users enter feedback within the app, which is sent to the server, and the AI ​​module incorporates it into the next program.

[0617] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0618] The present invention is a system for optimizing the user's relaxation state, comprising a sensor and low-frequency pad embedded in a full-body garment, as well as an information processing device equipped with an emotion engine. Specific embodiments of the present invention will be described below, along with specific examples illustrating the system's program and processing flow.

[0619] System Configuration

[0620] clothing

[0621] The full-body garment is designed to fit snugly against the user's body surface. Inside the garment are multiple sensors and low-frequency pads that collect biometric data such as the user's body temperature, heart rate, and skin conductance, and use low-frequency electrical currents to stimulate the muscles and produce a massage effect.

[0622] control unit

[0623] The control unit is integrated into the clothing and serves as a power supply and signal processing unit for controlling the sensors and low-frequency pads. The control unit has an internal battery and can also communicate wirelessly.

[0624] Information processing device

[0625] The information processing device is an external device, such as a smartphone or tablet, that is wirelessly connected to the control unit. This information processing device is equipped with an artificial intelligence module that analyzes biometric data collected from sensors and visualizes the user's relaxation state. It also includes an emotion engine that recognizes the user's emotions and provides auxiliary information to optimize the relaxation state.

[0626] Program Implementation

[0627] User actions

[0628] First, the user launches a dedicated app on their smartphone and puts on a full-body, form-fitting garment. Then, they turn on the power to the control unit. This activates the control unit and establishes a wireless connection with the smartphone.

[0629] Terminal processing

[0630] Once the device (smartphone) establishes a connection with the control unit, it begins collecting the user's biometric data (body temperature, heart rate, skin conductance, etc.) from sensors embedded in the clothing. This data is collected in real time and temporarily stored in the device's internal memory. The collected data is then sent to a cloud server.

[0631] Server Processing

[0632] The server analyzes the received biometric data and emotional data acquired by the emotion engine. An AI algorithm is used for the analysis to evaluate the user's relaxation state. A relaxation index is calculated, and analysis results are generated based on this index.

[0633] Analysis of the Emotion Engine

[0634] The emotion engine analyzes the user's facial expressions, voice tone, and body temperature changes to recognize their emotional state. For example, it can determine whether a user is stressed based on the movement of their facial muscles. This emotional data is also sent to the server and used to assess their state of relaxation.

[0635] Massage program generation

[0636] Based on the analysis results, the server generates an optimal massage program that maximizes the user's relaxation state. This also incorporates data from the emotion engine. Specifically, the position, intensity, and rhythm of the low-frequency pads are determined.

[0637] Control Unit Operation

[0638] The terminal sends instructions to the control unit based on the massage program received from the server. The control unit then instructs the low-frequency pads to perform the actions as instructed. During this time, the user can experience the massage effect.

[0639] User feedback

[0640] After the massage session ends, users record their thoughts and feedback about the massage experience within the app. For example, they can enter specific evaluations such as, "The shoulder massage was very effective," or "I would like the back massage to be more intense."

[0641] Feedback analysis

[0642] The device sends user feedback to the server. The server analyzes the received feedback, incorporates its contents into the AI ​​module and emotion engine, and uses it to improve future massage programs.

[0643] Specific example

[0644] For example, consider a user A using this system to alleviate fatigue from daily desk work. In the morning, user A puts on a full-body garment, launches a dedicated app, and turns on the control unit. The device then collects biometric data and emotional data such as facial expressions, which are analyzed on a cloud server. The AI ​​and emotion engine generate an optimal massage program, and the operation instructions are sent to the control unit via the device. User A can receive an appropriate massage even while working, and provides feedback through the app afterward. This allows for an even more precise massage the next time the system is used.

[0645] In this way, the present invention combines an emotion engine to create a system that provides a more precise relaxation effect. By incorporating user feedback and emotional data, the AI ​​continuously learns, improving the system's accuracy with each use and enabling a more effective massage.

[0646] The following describes the processing flow.

[0647] Step 1:

[0648] The user launches a dedicated app on their smartphone. This starts the app and verifies the user's login information. Simultaneously, the user puts on a full-body form-fitting garment and turns on the power to the control unit.

[0649] Step 2:

[0650] The device (smartphone) will turn on Bluetooth and attempt to connect to the control unit. If the connection is successful, "Connection successful" will be displayed on the smartphone screen.

[0651] Step 3:

[0652] The device begins collecting the user's biometric data (body temperature, heart rate, skin conductance, etc.) from sensors embedded in the clothing. This data is collected in real time and temporarily stored in the device's internal memory.

[0653] Step 4:

[0654] The device uses Wi-Fi or mobile data to send the collected biometric data to a cloud server. This allows the server to begin real-time analysis of the data.

[0655] Step 5:

[0656] The server analyzes the received biometric data and uses an AI algorithm to evaluate the user's relaxation state. A relaxation index is calculated, and the analysis results are generated.

[0657] Step 6:

[0658] The server's emotion engine analyzes the user's facial expressions, voice tone, body temperature changes, and other factors to recognize the user's emotional state. For example, it can identify situations where the user is experiencing stress.

[0659] Step 7:

[0660] Based on the recognition results from the emotion engine, the server performs further detailed analysis and evaluates the user's relaxed state, taking into account their emotional condition.

[0661] Step 8:

[0662] Based on the analysis results, the server generates an optimal massage program to maximize the user's relaxation. Specifically, it determines instructions regarding the position, intensity, and rhythm of the low-frequency pads.

[0663] Step 9:

[0664] The server sends the generated massage program to the terminal. The terminal confirms receipt and is ready to execute the massage.

[0665] Step 10:

[0666] The terminal sends instructions to the control unit based on the program received from the server. The control unit then causes the low-frequency pad to perform the operation as instructed.

[0667] Step 11:

[0668] The low-frequency pads deliver low-frequency electrical currents to the user's body at the instructed location, intensity, and rhythm, initiating a massage. During this time, the user can relax and experience the massage effect.

[0669] Step 12:

[0670] After the massage session ends, users record their thoughts and feedback about the massage experience within the app. For example, they can enter specific evaluations such as, "The shoulder massage was very effective," or "I would like the back massage to be more intense."

[0671] Step 13:

[0672] The device sends user feedback to the server. The server analyzes the received feedback, incorporates its contents into the AI ​​module and emotion engine, and uses it to improve future massage programs.

[0673] Step 14:

[0674] The server retrains the AI ​​model based on feedback data, improving it so that subsequent massage programs are more effectively customized. This increases the system's accuracy and further enhances the massage effect for the user.

[0675] (Example 2)

[0676] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0677] In modern society, health problems caused by stress and overwork are increasing, with physical fatigue and mental stress from desk work being particularly problematic. In this situation, there is a need to provide effective relaxation methods. However, conventional massage and relaxation devices often fail to adequately reflect the individual state and emotions of users, instead offering uniform programs. Therefore, it has been difficult to enhance relaxation effects tailored to each user's individual needs.

[0678] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for evaluating the user's relaxation state based on biometric data and emotional data, means for generating action instructions to optimize the user's relaxation state, and means for collecting and learning user feedback. This makes it possible to provide an optimal massage program tailored to the individual user's condition and to improve its accuracy.

[0679] "Full-body contact clothing" refers to clothing designed to fit snugly against the user's body surface, with sensors and low-frequency pads placed inside to collect biometric data and produce a massage effect.

[0680] A "sensor" is a device that collects biometric data such as body temperature, heart rate, and skin conductance in real time.

[0681] A "low-frequency pad" is a device that uses low-frequency electrical currents to stimulate muscles, producing a massage effect.

[0682] The "control unit" is a power supply and signal processing unit for controlling the sensor and low-frequency pad. It operates using a built-in battery and has wireless connectivity.

[0683] An "information processing device" is an external device such as a smartphone or tablet that is wirelessly connected to the control unit. It is equipped with an artificial intelligence module and analyzes data collected from sensors to visualize and optimize the user's relaxation state.

[0684] The "artificial intelligence module" is software that analyzes biometric data acquired by sensors and utilizes AI algorithms to evaluate and optimize the user's relaxation state.

[0685] The "emotion engine" is software that analyzes the user's facial expressions, voice tone, body temperature changes, etc., to recognize their emotional state, and it works in conjunction with the artificial intelligence module.

[0686] "Operation instructions" refer to control instructions that include the position, intensity, and rhythm of the low-frequency pads generated to optimize the user's relaxation state.

[0687] "Feedback" refers to the user's comments and evaluations regarding the effectiveness of the massage and areas for improvement after a massage session.

[0688] A "cloud server" is a remote server used to analyze collected biometric and emotional data and generate the optimal massage program.

[0689] This invention comprises a full-body, form-fitting garment with built-in sensors and low-frequency pads, as well as an information processing device equipped with an emotion engine, and is a system for optimizing the user's relaxation state. This system is implemented using the following hardware and software.

[0690] Hardware configuration

[0691] clothing

[0692] The full-body garment is designed to fit snugly against the user's body surface. Inside the garment are multiple sensors and low-frequency pads with the following functions:

[0693] Sensors that collect biometric data such as body temperature, heart rate, and skin conductance.

[0694] Low-frequency pads that produce a massage effect by applying low-frequency electrical currents to the muscles.

[0695] control unit

[0696] The control unit is integrated into the clothing and serves as a power supply and signal processing unit for controlling the sensors and low-frequency pads. The control unit has the following functions:

[0697] It has an internal battery and also communicates wirelessly.

[0698] Information processing device

[0699] The information processing device is an external device, such as a smartphone or tablet, that is wirelessly connected to the control unit. This information processing device is equipped with an artificial intelligence module that has the following functions:

[0700] Analyze biometric data collected from sensors.

[0701] Using an emotion engine (software that analyzes facial expressions, voice tone, body temperature changes, etc., to recognize the user's emotional state), it generates action instructions to visualize and optimize the user's relaxation state.

[0702] Software Configuration

[0703] Dedicated app

[0704] Users install a dedicated app on their smartphone and operate the system by launching the app. This app has the following functions:

[0705] Collecting biometric data from sensors embedded in clothing.

[0706] Establish a wireless connection with the control unit and transmit control signals for the low-frequency pad.

[0707] Collect user feedback and send it to the cloud server.

[0708] Cloud Server

[0709] The cloud server has the following functions and operates as the central hub of the entire system.

[0710] Analysis of collected biometric and emotional data

[0711] Generating the optimal massage program to optimize relaxation.

[0712] The server uses an AI algorithm to evaluate the user's relaxation level and calculate a relaxation index.

[0713] Instructions for use (specific examples)

[0714] For example, consider a case where user A uses this system to alleviate fatigue from daily desk work. The system can be used by following the steps below.

[0715] 1. In the morning, User A puts on full-body clothing and activates a dedicated app on their smartphone to turn on the control unit.

[0716] 2. The device (smartphone) collects biometric data and emotional data and sends it to a cloud server.

[0717] 3. The cloud server analyzes the data and generates the optimal massage program.

[0718] 4. Operation instructions from the server are sent to the control unit via the terminal, and the low-frequency pad performs the specified operation.

[0719] 5. User A can receive a suitable massage even while working.

[0720] 6. After the massage session, User A provides feedback via the app.

[0721] 7. Your feedback will be incorporated into future visits, resulting in even more precise massages.

[0722] Example of a prompt

[0723] As an example, the following is a prompt message used when the server evaluates the user's relaxation state and generates the optimal massage program.

[0724] "Analyze the user's biometric and emotional data to assess their relaxation state and generate the optimal massage program. Biometric data should include body temperature, heart rate, and skin conductance, while emotional data should be obtained based on facial expressions, voice tone, and changes in body temperature."

[0725] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0726] Step 1:

[0727] Input: The user wears full-body clothing and launches a dedicated app on their smartphone.

[0728] Operation: The user turns on the power to the control unit.

[0729] Output: A wireless connection is established between the control unit and the smartphone, and the connection status can be checked on the app.

[0730] Step 2:

[0731] Input: Connection information from the control unit

[0732] Operation: The device (smartphone) confirms that a wireless connection has been established with the control unit and begins collecting biometric data (body temperature, heart rate, skin conductance, etc.) in real time from sensors embedded in the clothing.

[0733] Output: The collected biometric data is temporarily stored in the device's internal memory.

[0734] Step 3:

[0735] Input: Biometric data stored on the device

[0736] Operation: The device sends collected biometric data to a cloud server at regular intervals (e.g., every 10 seconds).

[0737] Output: Biometric data is uploaded to a cloud server.

[0738] Step 4:

[0739] Input: Biometric data and emotional data uploaded to a cloud server

[0740] Operation: The server uses AI algorithms and an emotion engine based on received biometric and emotional data to analyze the user's relaxation state and calculate a relaxation index.

[0741] Output: Analysis results and a relaxation index are generated.

[0742] Step 5:

[0743] Input: Analysis results and relaxation index

[0744] Operation: Based on this data, the server generates an optimal massage program to optimize the user's relaxation state.

[0745] Output: The generated massage program is saved on the server.

[0746] Step 6:

[0747] Input: Generated massage program

[0748] Operation: The terminal sends instructions to the control unit based on the massage program received from the server.

[0749] Output: The instruction reaches the control unit, and the operation of the low-frequency pad begins.

[0750] Step 7:

[0751] Input: Operation instructions from the control unit.

[0752] Operation: The control unit applies the specified current to the low-frequency pad, providing a massage effect to the user's body.

[0753] Output: The user experiences the massage effect.

[0754] Step 8:

[0755] Input: Feedback form after massage session

[0756] Operation: Users enter their feedback and ratings about their massage experience within the app.

[0757] Output: Feedback is saved to the device.

[0758] Step 9:

[0759] Input: Feedback saved on the device

[0760] Operation: The device sends user feedback to the cloud server.

[0761] Output: Feedback is uploaded to the cloud server.

[0762] Step 10:

[0763] Input: Feedback uploaded to the cloud server

[0764] Operation: The server analyzes the received feedback, incorporates its contents into the AI ​​module and emotion engine, and uses them to improve future massage programs.

[0765] Output: Data is updated to generate more accurate massage programs for future sessions.

[0766] (Application Example 2)

[0767] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0768] In aesthetic and massage salons, there is a demand for treatments that optimize the user's relaxation state. However, because this depends on the skill and experience of the staff, it is difficult to provide the optimal relaxation effect for each individual user. Furthermore, there is a need for a system that analyzes the user's biometric data and emotional state in real time and provides an optimal massage program based on that analysis. However, conventional technology does not have a sufficiently established means of effectively collecting, analyzing, and reflecting this data in treatments.

[0769] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0770] In this invention, the server includes means for collecting biometric data acquired by sensors in real time, means for analyzing the user's emotional state using an emotion engine, and means for generating an optimal massage program based on the analysis results. This enables the staff to accurately analyze the user's relaxation state and perform the most appropriate treatment based on that analysis.

[0771] "Full-body contact clothing" refers to clothing designed to fit snugly to the user's entire body, and is a device that uses built-in sensors and low-frequency pads to collect biometric data and provide relaxation effects.

[0772] A "sensor" is a device used to collect biological data such as body temperature, heart rate, and skin conductance.

[0773] A "low-frequency pad" is a device that uses low-frequency electrical currents to produce a massage effect on muscles.

[0774] The "control unit" is a power supply and signal processing device for controlling sensors and low-frequency pads embedded in clothing. It also has a built-in battery and communicates wirelessly.

[0775] An "information processing device" is an external device that is wirelessly connected to the control unit. It is equipped with an artificial intelligence module, analyzes biometric data collected from sensors, visualizes the user's relaxation state, and generates optimal action instructions.

[0776] An "artificial intelligence module" is software or hardware that analyzes the user's relaxation state based on data acquired by sensors and generates optimal action instructions.

[0777] An "emotion engine" is an artificial intelligence technology that analyzes a user's emotional state and is used to evaluate their relaxation level and generate the optimal massage program.

[0778] "Feedback" refers to the comments and evaluations that users provide about their massage experience, and this information is used to improve future treatments.

[0779] A "massage program" is a plan that includes specific instructions regarding the position, intensity, and rhythm of the low-frequency pads in order to optimize the user's relaxation state.

[0780] A "cloud server" is a computer server located in a remote location that stores and analyzes data via the internet.

[0781] An "aesthetic salon" is a business that provides treatments for the purpose of beauty and relaxation.

[0782] A "massage salon" is a business that provides massage treatments for the purpose of relaxation and fatigue relief.

[0783] composition

[0784] This invention is a system consisting of a full-body garment, sensors and low-frequency pads placed inside the garment, a control unit connected to the garment, and an external information processing device wirelessly connected to the control unit. This system is particularly intended for use in aesthetic salons and massage salons.

[0785] Full-body close-fitting clothing

[0786] The full-body garment is designed to fit snugly against the user's body surface. It incorporates multiple sensors to collect biometric data such as body temperature, heart rate, and skin conductance, as well as low-frequency pads that deliver low-frequency electrical currents for muscle massage.

[0787] control unit

[0788] The control unit is integrated into the clothing and controls the built-in sensors and low-frequency pads. The control unit has a built-in battery that supplies the necessary power. Furthermore, the control unit can communicate with an external information processing device via wireless connection.

[0789] Information processing device

[0790] The information processing device is an external device, such as a smartphone or tablet, that is wirelessly connected to the control unit. This information processing device is equipped with an artificial intelligence module and an emotion engine. It analyzes biometric data collected from sensors and emotional data from the emotion engine to generate action instructions that optimize the user's relaxation state.

[0791] User operation and treatment

[0792] The user wears a full-body, form-fitting garment and launches a dedicated application on their smartphone. Next, they turn on the power to the control unit, which activates the unit and establishes a wireless connection with the smartphone. The smartphone collects biometric data from the sensors in real time and transmits it to a cloud server.

[0793] Server Processing

[0794] The server uses AI algorithms to analyze the received biometric and emotional data. The analysis assesses the user's relaxation state, and a relaxation index is calculated based on this data. The final analysis results generate an optimal massage program.

[0795] Staff collaboration

[0796] Staff at aesthetic and massage salons perform treatments according to the optimal massage program provided by the information processing device. After the treatment, users provide feedback on their massage experience within the app. This feedback, along with biometric data, is sent to a cloud server and used to optimize future treatments.

[0797] Hardware and software used

[0798] Sensors: Devices that measure body temperature, heart rate, and skin conductance.

[0799] Low-frequency pads: Devices that use low-frequency electrical currents to perform muscle massage.

[0800] Control Unit: A device that controls sensors and low-frequency pads and has wireless communication capabilities.

[0801] Information processing device: Smartphones, tablets, and other devices with internet connectivity.

[0802] Artificial Intelligence Module: Uses Python and machine learning libraries such as scikit-learn for data analysis.

[0803] Cloud server: A remote computer system for storing and analyzing data.

[0804] Specific example

[0805] A user visiting an aesthetic salon wears a full-body garment and begins treatment using a dedicated application. A smartphone collects biometric data from sensors in the garment and analyzes it in real time on a cloud server. AI and an emotion engine generate an optimal massage program, which is then provided to the staff. After the treatment, the user's feedback is analyzed again, and a more precise massage is provided on the next visit.

[0806] Example of a prompt

[0807] "To enhance the massage effect, collect the user's heart rate, body temperature, and skin conductance data in real time and analyze it using an emotion engine. Based on the analysis results, write Python code to generate the optimal massage program."

[0808] The above describes a specific embodiment for carrying out this invention. This system makes it possible to accurately analyze the user's relaxation state and provide the optimal treatment.

[0809] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0810] Step 1:

[0811] User actions

[0812] The user wears a full-body garment and launches a dedicated application on their smartphone. The user then turns on the control unit and confirms the wireless connection between the smartphone and the control unit.

[0813] Input: The user puts on clothes and launches a smartphone app.

[0814] Output: The control unit is powered on and a wireless connection is established.

[0815] Step 2:

[0816] Collection of biometric data

[0817] Once the device (smartphone) establishes a wireless connection with the control unit, it begins collecting the user's biometric data (body temperature, heart rate, skin conductance) in real time from sensors embedded in the clothing. This data is temporarily stored in the device's internal memory.

[0818] Input: Biometric data from connected sensors.

[0819] Output: Biometric data stored in the device's internal memory.

[0820] Step 3:

[0821] Sending data

[0822] The device sends the collected biometric data to a cloud server. The data is transferred using a secure protocol.

[0823] Input: Biometric data stored in the device's internal memory.

[0824] Output: Biometric data sent to the cloud server.

[0825] Step 4:

[0826] Data Analysis

[0827] The server analyzes the received biometric data using AI algorithms. Specifically, it performs preprocessing such as smoothing and filtering, and then uses statistical methods and machine learning models (for example, scikit-learn's RandomForestClassifier) ​​to calculate a relaxation index. In addition, an emotion engine analyzes the user's emotional data.

[0828] Input: Biometric data sent to the server.

[0829] Output: Analyzed relaxation state and relaxation index.

[0830] Step 5:

[0831] Massage program generation

[0832] The server generates an optimal massage program based on the analysis results. This program includes specific operational instructions such as the position, intensity, and rhythm of the low-frequency pads. The server then transmits this data to the terminal.

[0833] Input: Analyzed relaxation state and relaxation index.

[0834] Output: The optimal massage program sent to the terminal.

[0835] Step 6:

[0836] Execution of the procedure

[0837] The terminal sends instructions to the control unit based on the massage program received from the server. The control unit then instructs the low-frequency pads to perform the actions as instructed. During this time, the user experiences the massage effect.

[0838] Input: Optimal massage program.

[0839] Output: Massage effect applied to the user.

[0840] Step 7:

[0841] Collecting user feedback

[0842] After the treatment is complete, users record their thoughts and feedback about the massage experience within the app. This feedback is entered as a form within the application.

[0843] Input: User feedback.

[0844] Output: Feedback data stored on the device.

[0845] Step 8:

[0846] Sending and analyzing feedback

[0847] The device sends user feedback to a cloud server. The server analyzes the received feedback and incorporates it into the AI ​​module and emotion engine. This feedback is then used to improve future massage programs.

[0848] Input: Feedback data stored on the device.

[0849] Output: Improved massage program for future sessions.

[0850] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0851] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include those described above. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions shown by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0852] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0853] [Third Embodiment]

[0854] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0855] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0856] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0857] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0858] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0859] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0860] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0861] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0862] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0863] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0864] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0865] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0866] The present invention is a system that provides an optimal massage for each individual user by incorporating sensors and low-frequency pads into full-body, form-fitting clothing (shirts and tights) and wirelessly connecting them to an external information processing device (such as a smartphone). Specific embodiments of the present invention are described below.

[0867] System Configuration

[0868] clothing

[0869] The full-body garment is designed to fit snugly against the user's body surface. Multiple sensors are placed inside the garment to collect biometric data such as the user's body temperature, heart rate, and skin conductance. In addition, low-frequency pads are positioned in place and used to deliver low-frequency electrical currents to produce a massage effect.

[0870] control unit

[0871] The control unit is integrated into the clothing and serves as a power supply and signal processing unit for controlling the sensors and low-frequency pads. The control unit has an internal battery and can also communicate wirelessly.

[0872] Information processing device

[0873] The information processing device is an external device, such as a smartphone or tablet, that is wirelessly connected to the control unit. This information processing device is equipped with an artificial intelligence module that analyzes biometric data collected from sensors and visualizes the user's relaxation state. Based on this analysis, an optimal massage program is generated to maximize the user's relaxation level.

[0874] Program Implementation

[0875] User actions

[0876] The user first places a dedicated app on their smartphone and then puts on a full-body, form-fitting garment. Next, they turn on the power to the control unit. This activates the control unit and establishes a wireless connection with the smartphone.

[0877] Terminal processing

[0878] Once the device (smartphone) establishes a connection with the control unit, it begins collecting biometric data from sensors embedded in the clothing. This data is stored in internal memory in real time and transmitted to a cloud server using Wi-Fi or mobile data communication. For example, if a user performs this operation while working at a desk, their body temperature, heart rate, and skin conductance are monitored in real time.

[0879] Server Processing

[0880] The server analyzes the received biometric data to assess the user's current state of relaxation. An artificial intelligence module is used for the analysis, calculating a relaxation index based on heart rate variability and body temperature trends. Based on this relaxation index, an optimal massage pattern is generated, and instructions for the massage are created.

[0881] Receiving and controlling the device

[0882] The terminal receives operation instructions transmitted from the server and appropriately controls the low-frequency pads through the control unit. During this time, the user can experience the massage effect in real time.

[0883] User feedback

[0884] After a massage session, users provide feedback and comments within the app. This includes specific comments such as, "The shoulder massage was very effective," or "I'd like the back massage to be a little stronger." This feedback is sent from the device to the server and used to improve the accuracy of future massage programs.

[0885] Specific example

[0886] For example, consider a user A using this system to alleviate fatigue from daily desk work. In the morning, user A puts on a full-body garment, launches a dedicated app, and turns on the control unit. The device then collects biometric data, and the relaxation level is analyzed on a cloud server. AI generates an optimal massage program, and the low-frequency pads operate via the device. User A can receive an appropriate massage even while working, and provides feedback through the app afterward. This allows for an even more precise massage the next time the user uses the system.

[0887] In this way, the present invention allows the control unit, terminal, and server to work together to continuously provide the user with the optimal massage experience. By combining user feedback with AI learning capabilities, the system's accuracy improves with each use, enabling more effective massages.

[0888] The following describes the processing flow.

[0889] Step 1:

[0890] The user launches the app on their smartphone. This starts the app and verifies the user's login information. Simultaneously, the user puts on a full-body garment and turns on the power to the control unit.

[0891] Step 2:

[0892] The device (smartphone) will turn on Bluetooth and attempt to connect to the control unit. If the connection is successful, "Connection successful" will be displayed on the smartphone screen.

[0893] Step 3:

[0894] The device begins collecting the user's biometric data (such as body temperature, heart rate, and skin conductance) from sensors embedded in the clothing. This data is collected in real time and temporarily stored in the device's internal memory.

[0895] Step 4:

[0896] The device uses Wi-Fi or mobile data to send the collected biometric data to a cloud server. This allows the server to begin real-time analysis of the data.

[0897] Step 5:

[0898] The server analyzes the received biometric data and uses an AI algorithm to evaluate the user's relaxation state. A relaxation index is calculated, and analysis results based on the user's biometric data are generated.

[0899] Step 6:

[0900] Based on the analysis results, the server generates an optimal massage program to maximize the user's relaxation. Specifically, it determines instructions regarding the position, intensity, and rhythm of the low-frequency pads.

[0901] Step 7:

[0902] The server sends the generated massage program to the terminal. The terminal then confirms receipt and prepares to execute the massage.

[0903] Step 8:

[0904] The terminal sends instructions to the control unit based on the program received from the server. The control unit then causes the low-frequency pad to perform the operation as instructed.

[0905] Step 9:

[0906] The low-frequency pads deliver low-frequency electrical currents to the user's body at the instructed location, intensity, and rhythm, initiating a massage. During this time, the user can relax and experience the massage effect.

[0907] Step 10:

[0908] After the massage session ends, users record their thoughts and feedback about the massage experience within the app. For example, they can enter specific evaluations such as, "The shoulder massage was very effective," or "I would like the back massage to be more intense."

[0909] Step 11:

[0910] The device sends user feedback to the server. The server analyzes the received feedback, incorporates its contents into an AI module, and uses it to improve future massage programs.

[0911] Step 12:

[0912] The server retrains the AI ​​model based on this feedback data, improving it so that future massage programs are more effectively customized. This increases the system's accuracy and further enhances the massage effect for the user.

[0913] (Example 1)

[0914] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0915] Current massage systems struggle to provide optimal massage programs tailored to each user's individual needs. Many systems offer only fixed programs and cannot maximize massage effectiveness by utilizing user feedback or real-time biometric data. As a result, users do not experience sufficient relaxation, leading to inadequate relief from fatigue resulting from prolonged work or stress.

[0916] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0917] In this invention, the server includes means for wearing a full-body close-fitting garment, means for which sensors and a low-frequency generator are disposed inside the garment, means for which a control unit is connected to the garment, means for which an external information processing system is wirelessly connected to the control unit, and means for which a generating AI model installed in the information processing system displays the user's relaxation index based on biometric data acquired by the sensors, generates operation instructions to optimize the relaxation index, and controls the low-frequency generator according to the operation instructions. This makes it possible to provide an optimal massage program based on each user's biometric information and maximize the user's relaxation effect.

[0918] "Full-body contact clothing" refers to clothing designed to fit snugly against the user's entire body and incorporates various sensors and low-frequency generators.

[0919] A "sensor" is a device that detects biometric data such as a user's body temperature, heart rate, and skin conductance, and transmits this data to an external information processing system.

[0920] A "low-frequency generator" is a device that uses low-frequency electric current to produce a massage effect, stimulating the user's muscles by operating in a specified pattern.

[0921] A "control unit" is a device installed inside clothing that manages and controls sensors and low-frequency generators, and is equipped with power supply and wireless communication functions.

[0922] The "external information processing system" refers to a device wirelessly connected to the control unit, such as a smartphone or tablet, which analyzes the user's biometric data and generates a massage program.

[0923] A "generative AI model" is a type of artificial intelligence that uses machine learning and deep learning algorithms based on collected biometric data to calculate a user's relaxation index and generate the optimal massage program.

[0924] The "relaxation index" is an indicator calculated based on the user's biometric data, and it quantifies the user's state of relaxation.

[0925] "Operation instructions" refer to digital signals used to instruct the operation patterns of a low-frequency generator created by a generative AI model, and include instructions for executing a specific massage program.

[0926] The present invention is a system that provides an optimal massage for each individual user by incorporating sensors and a low-frequency generator into full-body contact clothing and wirelessly connecting them to an external information processing system (such as a smartphone). Specific embodiments of the present invention are described below.

[0927] System Configuration

[0928] clothing

[0929] The full-body contact garment is designed to fit snugly against the user's body surface. Multiple sensors are placed inside the garment to collect biometric data such as the user's body temperature, heart rate, and skin conductance. In addition, low-frequency generators are positioned in place and used to deliver low-frequency currents to produce a massage effect.

[0930] control unit

[0931] The control unit is integrated into the garment and serves as a power supply and signal processing unit for controlling the sensors and low-frequency generator. The control unit has an internal battery and can also communicate wirelessly.

[0932] Information processing system

[0933] The information processing system consists of an external device, such as a smartphone or tablet, that is wirelessly connected to the control unit. This information processing system is equipped with a generative AI model that analyzes biometric data collected from sensors and visualizes the user's relaxation state. Based on this analysis, an optimal massage program is generated to maximize the user's relaxation level.

[0934] Program Implementation

[0935] User actions

[0936] The user first launches a dedicated app on their smartphone and puts on the full-body, form-fitting clothing. Next, they turn on the power to the control unit. This activates the control unit and establishes a wireless connection with the smartphone.

[0937] Terminal processing

[0938] Once the device (smartphone) establishes a connection with the control unit, it begins collecting biometric data from sensors embedded in the clothing. This data is stored in internal memory in real time and transmitted to a cloud server using Wi-Fi or mobile data communication. For example, if a user performs this operation while working at a desk, their body temperature, heart rate, and skin conductance are monitored in real time.

[0939] Server Processing

[0940] The server analyzes the received biometric data to assess the user's current state of relaxation. A generative AI model is used for the analysis, calculating a relaxation index based on heart rate variability and body temperature trends. Based on this relaxation index, an optimal massage pattern is generated, and instructions are created.

[0941] Receiving and controlling the device

[0942] The terminal receives operation instructions transmitted from the server and appropriately controls the low-frequency generator through the control unit. During this time, the user can experience the massage effect in real time.

[0943] User feedback

[0944] After a massage session, users provide feedback and comments within the app. This includes specific comments such as, "The shoulder massage was very effective," or "I'd like the back massage to be a little stronger." This feedback is sent from the device to the server and used to improve the accuracy of future massage programs.

[0945] Specific example

[0946] For example, consider a user A using this system to alleviate fatigue from daily desk work. In the morning, user A puts on full-body contact clothing, launches a dedicated app, and turns on the control unit. The terminal then collects biometric data, and the relaxation level is analyzed on a cloud server. A generating AI model creates an optimal massage program, and the low-frequency generator operates via the terminal. User A can receive an appropriate massage even while working, and provides feedback via the app afterward. This allows for an even more precise massage the next time the system is used.

[0947] Example of a prompt

[0948] For example, the prompt might look like this: "Please generate an optimal massage program to relieve stiff shoulders and back pain caused by desk work. Evaluate the user's relaxation level based on their body temperature, heart rate, and skin conductance, and propose an operating pattern for the low-frequency generator."

[0949] In this way, the present invention allows the control unit, terminal, and server to work together to continuously provide the user with the optimal massage experience. By combining user feedback with the learning function of the generative AI model, the system's accuracy improves with each use, enabling more effective massages.

[0950] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0951] Step 1:

[0952] The user wears a full-body garment and launches a dedicated app on their smartphone. Next, they turn on the power to the control unit. The user's actions act as input, the control unit becomes active as output, and a wireless connection is established with the smartphone.

[0953] Step 2:

[0954] Once the smartphone (device) establishes a connection with the control unit, it begins collecting the user's biometric data (body temperature, heart rate, skin conductance) from sensors embedded in the clothing. The biometric data from the sensors is the input, and this is stored in the smartphone's internal memory in real time as the output. Furthermore, this data is transmitted to a cloud server using Wi-Fi or mobile data communication.

[0955] Step 3:

[0956] The cloud server receives biometric data transmitted from the smartphone. The biometric data is transferred to the server as input, and data analysis is performed on the server side as output. This allows the generating AI model to analyze heart rate variability and body temperature trends, and calculate a relaxation index. Specifically, it performs analysis of heart rate variability patterns and body temperature trends.

[0957] Step 4:

[0958] The generative AI model generates an optimal massage program based on a relaxation index. It takes analysis results as input and generates the optimal massage program as output. Specifically, prompts such as "Generate a relaxing massage pattern focusing on the shoulders and back based on the user's body temperature and heart rate data" are used.

[0959] Step 5:

[0960] The server sends the generated massage program to the smartphone. The generated massage program is the input, and this is received by the smartphone as the output. Specifically, the program data is transferred from the server.

[0961] Step 6:

[0962] The smartphone transfers the received massage program to the control unit, which then operates the low-frequency generator in the specified pattern. The input is an operation instruction from the server, and the output is the appropriate operation of the low-frequency generator. For example, the control might be: "To loosen the shoulder muscles, the low-frequency generator operates for 3 seconds, then pauses for 1 second."

[0963] Step 7:

[0964] After a massage session, users provide feedback through a dedicated app. The input consists of the user's impressions and opinions, and this feedback is sent to a cloud server via the device. Specific comments, such as "The shoulder massage was very effective" or "I'd like the back massage to be a little stronger," are recorded within the app.

[0965] Step 8:

[0966] The cloud server receives feedback from users, and the generating AI model uses this information to improve the accuracy of the next massage program generation. The input is user feedback data, and the output is an improved massage program for subsequent uses. Specifically, the AI ​​model performs a learning process based on the feedback data.

[0967] (Application Example 1)

[0968] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0969] The problem lies in the lack of efficient means of rest and relaxation for industrial workers who perform long hours of standing or heavy labor. Furthermore, conventional rest methods make it difficult to provide appropriate relaxation tailored to the individual needs of each worker.

[0970] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0971] In this invention, the server includes means for monitoring biometric data in real time and transmitting it to a cloud database, means for generating an optimal massage program using a generative AI model, means for notifying a head-mounted display, and means for collecting user feedback and adjusting the next massage program. This makes it possible for industrial workers to receive individually optimized relaxation.

[0972] "Full-body contact clothing" refers to clothing designed to fit snugly against the user's body surface and incorporating sensors for collecting biometric data and low-frequency pads to provide a massage effect.

[0973] A "sensor" is a device that measures a user's biometric data, such as body temperature, heart rate, and skin conductance.

[0974] A "low-frequency pad" is a device that produces a massage effect by applying a low-frequency electric current to a specific area.

[0975] The "control unit" is a device that controls the sensor and low-frequency pad, supplies power, and performs signal processing, and can be wirelessly connected to the information processing device.

[0976] An "information processing device" is an external device such as a smartphone or tablet that includes an artificial intelligence module for analyzing data acquired from sensors and generating an optimal massage program.

[0977] The "artificial intelligence module" is a software module that analyzes biometric data acquired by sensors, visualizes the user's relaxation state, and generates an optimal massage program.

[0978] A "generative AI model" is an artificial intelligence algorithm used to generate the optimal massage program based on biometric data.

[0979] A "head-mounted display" is a display device worn by the user and is used to display operation instructions generated by an artificial intelligence module.

[0980] "Feedback" is the process by which users provide their thoughts and opinions about their massage experience, and this information is used to improve future massage programs.

[0981] Modes for carrying out the invention

[0982] This invention is a system designed to improve the health management and rest efficiency of industrial workers. This invention makes it possible to provide individually optimized relaxation even during long hours of standing work or heavy labor.

[0983] System Configuration

[0984] clothing

[0985] The full-body contact garment is designed to fit snugly against the user's body surface. Inside the garment are multiple sensors and low-frequency pads. The sensors collect biometric data such as the user's body temperature, heart rate, and skin conductance. The low-frequency pads are used to produce a massage effect.

[0986] control unit

[0987] The control unit is integrated into the clothing and serves as a power supply and signal processing unit for controlling the sensors and low-frequency pads. The control unit has an internal battery and also communicates wirelessly.

[0988] Information processing device

[0989] The information processing device is an external device, such as a smartphone or tablet, that is wirelessly connected to the control unit. This information processing device is equipped with an artificial intelligence module that analyzes biometric data collected from sensors and visualizes the user's relaxation state. Based on this analysis, a generative AI model generates an optimal massage program.

[0990] Program Implementation

[0991] User actions

[0992] First, the user puts on a full-body garment and launches a dedicated app on their smartphone. Next, they turn on the power to the control unit. This activates the control unit and establishes a wireless connection with the smartphone.

[0993] Terminal processing

[0994] Once connected to the control unit, the device (smartphone) begins collecting biometric data from sensors embedded in the clothing. This data is stored in internal memory in real time and transmitted to a cloud server using Wi-Fi or mobile data communication. For example, if this operation is performed while the user is working, body temperature, heart rate, and skin conductance are monitored in real time.

[0995] Server Processing

[0996] The server analyzes the received biometric data to assess the user's current state of relaxation. A generative AI model is used for the analysis, calculating a relaxation index based on heart rate variability and body temperature trends. Based on this relaxation index, an optimal massage pattern is generated, and instructions are created.

[0997] Receiving and controlling the device

[0998] The terminal receives operation instructions transmitted from the server and appropriately controls the low-frequency pads through the control unit. During this time, the user can experience the massage effect in real time.

[0999] User feedback

[1000] After a massage session, users provide feedback and comments within the app. This includes specific comments such as "The shoulder massage was very effective" or "I'd like the back massage to be a little stronger." This feedback is sent from the device to the server and used to improve the accuracy of future massage programs.

[1001] Specific example

[1002] For example, if industrial worker A feels fatigued after working for a long time, the full-body contact garment detects this condition, and a generating AI model creates an optimal massage program. This instruction is sent to a terminal, and worker A can receive an appropriate massage using low-frequency pads during a break.

[1003] Example of a prompt

[1004] Monitor factory workers' vital data (heart rate, body temperature, skin conductance) in real time and generate an optimal massage program based on this data. Notify the worker of the results via a head-mounted display and provide them with the appropriate massage. Also, collect worker feedback to improve the next massage program.

[1005] In this way, the system of the present invention improves in accuracy with each use by combining user feedback and a generated AI model, providing more effective relaxation.

[1006] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1007] Step 1:

[1008] User Operation: The user wears a full-body, form-fitting garment and activates a dedicated application on their smartphone to turn on the control unit. At this stage, the control unit becomes active and a wireless connection with the smartphone is established.

[1009] Input: User actions

[1010] Output: Establishment of wireless connection between the control unit and the smartphone.

[1011] Specific operation: The user launches the app and turns on the power to the control unit. The smartphone app recognizes the control unit and establishes a connection.

[1012] Step 2:

[1013] Data Collection: Once the device (smartphone) connects to the control unit, it begins collecting biometric data (heart rate, body temperature, skin conductance) from sensors embedded in the clothing. This data is stored in internal memory in real time and transmitted to a cloud server using Wi-Fi or mobile data communication.

[1014] Input: Data from sensors embedded in the clothing

[1015] Output: Biometric data sent to the cloud server

[1016] Specific operation: The sensor acquires the user's biometric data, the smartphone receives it, and sends it to a cloud server.

[1017] Step 3:

[1018] Data analysis and massage program generation: The server analyzes the received biometric data and calculates a relaxation index using a generated AI model. Based on the results, an optimal massage program is generated and action instructions are created.

[1019] Input: Biometric data sent to the cloud server

[1020] Output: Generated optimal massage program and operating instructions

[1021] Specific operation: The AI ​​module analyzes the data, and the generated AI model creates the optimal massage program and outputs it as an action instruction.

[1022] Step 4:

[1023] Receiving and executing operation instructions: The terminal (smartphone) receives operation instructions from the server and appropriately controls the low-frequency pads via the control unit. This allows the user to experience massage effects in real time.

[1024] Input: Operation instructions sent from the server

[1025] Output: Operation control of low-frequency pads

[1026] Specific operation: The smartphone receives operation instructions from the server and controls the operation of the low-frequency pad via the control unit.

[1027] Step 5:

[1028] User Feedback Collection: After a massage session ends, users provide feedback within the app. This feedback is sent from the device to the server and used to improve the accuracy of future massage programs.

[1029] Input: User feedback

[1030] Output: Data from the improved massage program

[1031] Specific operation: Users enter feedback within the app, which is sent to the server, and the AI ​​module incorporates it into the next program.

[1032] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1033] The present invention is a system for optimizing the user's relaxation state, comprising a sensor and low-frequency pad embedded in a full-body garment, as well as an information processing device equipped with an emotion engine. Specific embodiments of the present invention will be described below, along with specific examples illustrating the system's program and processing flow.

[1034] System Configuration

[1035] clothing

[1036] The full-body garment is designed to fit snugly against the user's body surface. Inside the garment are multiple sensors and low-frequency pads that collect biometric data such as the user's body temperature, heart rate, and skin conductance, and use low-frequency electrical currents to stimulate the muscles and produce a massage effect.

[1037] control unit

[1038] The control unit is integrated into the clothing and serves as a power supply and signal processing unit for controlling the sensors and low-frequency pads. The control unit has an internal battery and can also communicate wirelessly.

[1039] Information processing device

[1040] The information processing device is an external device, such as a smartphone or tablet, that is wirelessly connected to the control unit. This information processing device is equipped with an artificial intelligence module that analyzes biometric data collected from sensors and visualizes the user's relaxation state. It also includes an emotion engine that recognizes the user's emotions and provides auxiliary information to optimize the relaxation state.

[1041] Program Implementation

[1042] User actions

[1043] First, the user launches a dedicated app on their smartphone and puts on a full-body, form-fitting garment. Then, they turn on the power to the control unit. This activates the control unit and establishes a wireless connection with the smartphone.

[1044] Terminal processing

[1045] Once the device (smartphone) establishes a connection with the control unit, it begins collecting the user's biometric data (body temperature, heart rate, skin conductance, etc.) from sensors embedded in the clothing. This data is collected in real time and temporarily stored in the device's internal memory. The collected data is then sent to a cloud server.

[1046] Server Processing

[1047] The server analyzes the received biometric data and emotional data acquired by the emotion engine. An AI algorithm is used for the analysis to evaluate the user's relaxation state. A relaxation index is calculated, and analysis results are generated based on this index.

[1048] Analysis of the Emotion Engine

[1049] The emotion engine analyzes the user's facial expressions, voice tone, and body temperature changes to recognize their emotional state. For example, it can determine whether a user is stressed based on the movement of their facial muscles. This emotional data is also sent to the server and used to assess their state of relaxation.

[1050] Massage program generation

[1051] Based on the analysis results, the server generates an optimal massage program that maximizes the user's relaxation state. This also incorporates data from the emotion engine. Specifically, the position, intensity, and rhythm of the low-frequency pads are determined.

[1052] Control Unit Operation

[1053] The terminal sends instructions to the control unit based on the massage program received from the server. The control unit then instructs the low-frequency pads to perform the actions as instructed. During this time, the user can experience the massage effect.

[1054] User feedback

[1055] After the massage session ends, users record their thoughts and feedback about the massage experience within the app. For example, they can enter specific evaluations such as, "The shoulder massage was very effective," or "I would like the back massage to be more intense."

[1056] Feedback analysis

[1057] The device sends user feedback to the server. The server analyzes the received feedback, incorporates its contents into the AI ​​module and emotion engine, and uses it to improve future massage programs.

[1058] Specific example

[1059] For example, consider a user A using this system to alleviate fatigue from daily desk work. In the morning, user A puts on a full-body garment, launches a dedicated app, and turns on the control unit. The device then collects biometric data and emotional data such as facial expressions, which are analyzed on a cloud server. The AI ​​and emotion engine generate an optimal massage program, and the operation instructions are sent to the control unit via the device. User A can receive an appropriate massage even while working, and provides feedback through the app afterward. This allows for an even more precise massage the next time the system is used.

[1060] In this way, the present invention combines an emotion engine to create a system that provides a more precise relaxation effect. By incorporating user feedback and emotional data, the AI ​​continuously learns, improving the system's accuracy with each use and enabling a more effective massage.

[1061] The following describes the processing flow.

[1062] Step 1:

[1063] The user launches a dedicated app on their smartphone. This starts the app and verifies the user's login information. Simultaneously, the user puts on a full-body form-fitting garment and turns on the power to the control unit.

[1064] Step 2:

[1065] The device (smartphone) will turn on Bluetooth and attempt to connect to the control unit. If the connection is successful, "Connection successful" will be displayed on the smartphone screen.

[1066] Step 3:

[1067] The device begins collecting the user's biometric data (body temperature, heart rate, skin conductance, etc.) from sensors embedded in the clothing. This data is collected in real time and temporarily stored in the device's internal memory.

[1068] Step 4:

[1069] The device uses Wi-Fi or mobile data to send the collected biometric data to a cloud server. This allows the server to begin real-time analysis of the data.

[1070] Step 5:

[1071] The server analyzes the received biometric data and uses an AI algorithm to evaluate the user's relaxation state. A relaxation index is calculated, and the analysis results are generated.

[1072] Step 6:

[1073] The server's emotion engine analyzes the user's facial expressions, voice tone, body temperature changes, and other factors to recognize the user's emotional state. For example, it can identify situations where the user is experiencing stress.

[1074] Step 7:

[1075] Based on the recognition results from the emotion engine, the server performs further detailed analysis and evaluates the user's relaxed state, taking into account their emotional condition.

[1076] Step 8:

[1077] Based on the analysis results, the server generates an optimal massage program to maximize the user's relaxation. Specifically, it determines instructions regarding the position, intensity, and rhythm of the low-frequency pads.

[1078] Step 9:

[1079] The server sends the generated massage program to the terminal. The terminal confirms receipt and is ready to execute the massage.

[1080] Step 10:

[1081] The terminal sends instructions to the control unit based on the program received from the server. The control unit then causes the low-frequency pad to perform the operation as instructed.

[1082] Step 11:

[1083] The low-frequency pads deliver low-frequency electrical currents to the user's body at the instructed location, intensity, and rhythm, initiating a massage. During this time, the user can relax and experience the massage effect.

[1084] Step 12:

[1085] After the massage session ends, users record their thoughts and feedback about the massage experience within the app. For example, they can enter specific evaluations such as, "The shoulder massage was very effective," or "I would like the back massage to be more intense."

[1086] Step 13:

[1087] The device sends user feedback to the server. The server analyzes the received feedback, incorporates its contents into the AI ​​module and emotion engine, and uses it to improve future massage programs.

[1088] Step 14:

[1089] The server retrains the AI ​​model based on feedback data, improving it so that subsequent massage programs are more effectively customized. This increases the system's accuracy and further enhances the massage effect for the user.

[1090] (Example 2)

[1091] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1092] In modern society, health problems caused by stress and overwork are increasing, with physical fatigue and mental stress from desk work being particularly problematic. In this situation, there is a need to provide effective relaxation methods. However, conventional massage and relaxation devices often fail to adequately reflect the individual state and emotions of users, instead offering uniform programs. Therefore, it has been difficult to enhance relaxation effects tailored to each user's individual needs.

[1093] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for evaluating the user's relaxation state based on biometric data and emotional data, means for generating action instructions to optimize the user's relaxation state, and means for collecting and learning user feedback. This makes it possible to provide an optimal massage program tailored to the individual user's condition and to improve its accuracy.

[1094] "Full-body contact clothing" refers to clothing designed to fit snugly against the user's body surface, with sensors and low-frequency pads placed inside to collect biometric data and produce a massage effect.

[1095] A "sensor" is a device that collects biometric data such as body temperature, heart rate, and skin conductance in real time.

[1096] A "low-frequency pad" is a device that uses low-frequency electrical currents to stimulate muscles, producing a massage effect.

[1097] The "control unit" is a power supply and signal processing unit for controlling the sensor and low-frequency pad. It operates using a built-in battery and has wireless connectivity.

[1098] An "information processing device" is an external device such as a smartphone or tablet that is wirelessly connected to the control unit. It is equipped with an artificial intelligence module and analyzes data collected from sensors to visualize and optimize the user's relaxation state.

[1099] The "artificial intelligence module" is software that analyzes biometric data acquired by sensors and utilizes AI algorithms to evaluate and optimize the user's relaxation state.

[1100] The "emotion engine" is software that analyzes the user's facial expressions, voice tone, body temperature changes, etc., to recognize their emotional state, and it works in conjunction with the artificial intelligence module.

[1101] "Operation instructions" refer to control instructions that include the position, intensity, and rhythm of the low-frequency pads generated to optimize the user's relaxation state.

[1102] "Feedback" refers to the user's comments and evaluations regarding the effectiveness of the massage and areas for improvement after a massage session.

[1103] A "cloud server" is a remote server used to analyze collected biometric and emotional data and generate the optimal massage program.

[1104] This invention comprises a full-body, form-fitting garment with built-in sensors and low-frequency pads, as well as an information processing device equipped with an emotion engine, and is a system for optimizing the user's relaxation state. This system is implemented using the following hardware and software.

[1105] Hardware configuration

[1106] clothing

[1107] The full-body garment is designed to fit snugly against the user's body surface. Inside the garment are multiple sensors and low-frequency pads with the following functions:

[1108] Sensors that collect biometric data such as body temperature, heart rate, and skin conductance.

[1109] Low-frequency pads that produce a massage effect by applying low-frequency electrical currents to the muscles.

[1110] control unit

[1111] The control unit is integrated into the clothing and serves as a power supply and signal processing unit for controlling the sensors and low-frequency pads. The control unit has the following functions:

[1112] It has an internal battery and also communicates wirelessly.

[1113] Information processing device

[1114] The information processing device is an external device, such as a smartphone or tablet, that is wirelessly connected to the control unit. This information processing device is equipped with an artificial intelligence module that has the following functions:

[1115] Analyze biometric data collected from sensors.

[1116] Using an emotion engine (software that analyzes facial expressions, voice tone, body temperature changes, etc., to recognize the user's emotional state), it generates action instructions to visualize and optimize the user's relaxation state.

[1117] Software Configuration

[1118] Dedicated app

[1119] Users install a dedicated app on their smartphone and operate the system by launching the app. This app has the following functions:

[1120] Collecting biometric data from sensors embedded in clothing.

[1121] Establish a wireless connection with the control unit and transmit control signals for the low-frequency pad.

[1122] Collect user feedback and send it to the cloud server.

[1123] Cloud Server

[1124] The cloud server has the following functions and operates as the central hub of the entire system.

[1125] Analysis of collected biometric and emotional data

[1126] Generating the optimal massage program to optimize relaxation.

[1127] The server uses an AI algorithm to evaluate the user's relaxation level and calculate a relaxation index.

[1128] Instructions for use (specific examples)

[1129] For example, consider a case where user A uses this system to alleviate fatigue from daily desk work. The system can be used by following the steps below.

[1130] 1. In the morning, User A puts on full-body clothing and activates a dedicated app on their smartphone to turn on the control unit.

[1131] 2. The device (smartphone) collects biometric data and emotional data and sends it to a cloud server.

[1132] 3. The cloud server analyzes the data and generates the optimal massage program.

[1133] 4. Operation instructions from the server are sent to the control unit via the terminal, and the low-frequency pad performs the specified operation.

[1134] 5. User A can receive a suitable massage even while working.

[1135] 6. After the massage session, User A provides feedback via the app.

[1136] 7. Your feedback will be incorporated into future visits, resulting in even more precise massages.

[1137] Example of a prompt

[1138] As an example, the following is a prompt message used when the server evaluates the user's relaxation state and generates the optimal massage program.

[1139] "Analyze the user's biometric and emotional data to assess their relaxation state and generate the optimal massage program. Biometric data should include body temperature, heart rate, and skin conductance, while emotional data should be obtained based on facial expressions, voice tone, and changes in body temperature."

[1140] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1141] Step 1:

[1142] Input: The user wears full-body clothing and launches a dedicated app on their smartphone.

[1143] Operation: The user turns on the power to the control unit.

[1144] Output: A wireless connection is established between the control unit and the smartphone, and the connection status can be checked on the app.

[1145] Step 2:

[1146] Input: Connection information from the control unit

[1147] Operation: The device (smartphone) confirms that a wireless connection has been established with the control unit and begins collecting biometric data (body temperature, heart rate, skin conductance, etc.) in real time from sensors embedded in the clothing.

[1148] Output: The collected biometric data is temporarily stored in the device's internal memory.

[1149] Step 3:

[1150] Input: Biometric data stored on the device

[1151] Operation: The device sends collected biometric data to a cloud server at regular intervals (e.g., every 10 seconds).

[1152] Output: Biometric data is uploaded to a cloud server.

[1153] Step 4:

[1154] Input: Biometric data and emotional data uploaded to a cloud server

[1155] Operation: The server uses AI algorithms and an emotion engine based on received biometric and emotional data to analyze the user's relaxation state and calculate a relaxation index.

[1156] Output: Analysis results and a relaxation index are generated.

[1157] Step 5:

[1158] Input: Analysis results and relaxation index

[1159] Operation: Based on this data, the server generates an optimal massage program to optimize the user's relaxation state.

[1160] Output: The generated massage program is saved on the server.

[1161] Step 6:

[1162] Input: Generated massage program

[1163] Operation: The terminal sends instructions to the control unit based on the massage program received from the server.

[1164] Output: The instruction reaches the control unit, and the operation of the low-frequency pad begins.

[1165] Step 7:

[1166] Input: Operation instructions from the control unit.

[1167] Operation: The control unit applies the specified current to the low-frequency pad, providing a massage effect to the user's body.

[1168] Output: The user experiences the massage effect.

[1169] Step 8:

[1170] Input: Feedback form after massage session

[1171] Operation: Users enter their feedback and ratings about their massage experience within the app.

[1172] Output: Feedback is saved to the device.

[1173] Step 9:

[1174] Input: Feedback saved on the device

[1175] Operation: The device sends user feedback to the cloud server.

[1176] Output: Feedback is uploaded to the cloud server.

[1177] Step 10:

[1178] Input: Feedback uploaded to the cloud server

[1179] Operation: The server analyzes the received feedback, incorporates its contents into the AI ​​module and emotion engine, and uses them to improve future massage programs.

[1180] Output: Data is updated to generate more accurate massage programs for future sessions.

[1181] (Application Example 2)

[1182] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1183] In aesthetic and massage salons, there is a demand for treatments that optimize the user's relaxation state. However, because this depends on the skill and experience of the staff, it is difficult to provide the optimal relaxation effect for each individual user. Furthermore, there is a need for a system that analyzes the user's biometric data and emotional state in real time and provides an optimal massage program based on that analysis. However, conventional technology does not have a sufficiently established means of effectively collecting, analyzing, and reflecting this data in treatments.

[1184] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1185] In this invention, the server includes means for collecting biometric data acquired by sensors in real time, means for analyzing the user's emotional state using an emotion engine, and means for generating an optimal massage program based on the analysis results. This enables the staff to accurately analyze the user's relaxation state and perform the most appropriate treatment based on that analysis.

[1186] "Full-body contact clothing" refers to clothing designed to fit snugly to the user's entire body, and is a device that uses built-in sensors and low-frequency pads to collect biometric data and provide relaxation effects.

[1187] A "sensor" is a device used to collect biological data such as body temperature, heart rate, and skin conductance.

[1188] A "low-frequency pad" is a device that uses low-frequency electrical currents to produce a massage effect on muscles.

[1189] The "control unit" is a power supply and signal processing device for controlling sensors and low-frequency pads embedded in clothing. It also has a built-in battery and communicates wirelessly.

[1190] An "information processing device" is an external device that is wirelessly connected to the control unit. It is equipped with an artificial intelligence module, analyzes biometric data collected from sensors, visualizes the user's relaxation state, and generates optimal action instructions.

[1191] An "artificial intelligence module" is software or hardware that analyzes the user's relaxation state based on data acquired by sensors and generates optimal action instructions.

[1192] An "emotion engine" is an artificial intelligence technology that analyzes a user's emotional state and is used to evaluate their relaxation level and generate the optimal massage program.

[1193] "Feedback" refers to the comments and evaluations that users provide about their massage experience, and this information is used to improve future treatments.

[1194] A "massage program" is a plan that includes specific instructions regarding the position, intensity, and rhythm of the low-frequency pads in order to optimize the user's relaxation state.

[1195] A "cloud server" is a computer server located in a remote location that stores and analyzes data via the internet.

[1196] An "aesthetic salon" is a business that provides treatments for the purpose of beauty and relaxation.

[1197] A "massage salon" is a business that provides massage treatments for the purpose of relaxation and fatigue relief.

[1198] composition

[1199] This invention is a system consisting of a full-body garment, sensors and low-frequency pads placed inside the garment, a control unit connected to the garment, and an external information processing device wirelessly connected to the control unit. This system is particularly intended for use in aesthetic salons and massage salons.

[1200] Full-body close-fitting clothing

[1201] The full-body garment is designed to fit snugly against the user's body surface. It incorporates multiple sensors to collect biometric data such as body temperature, heart rate, and skin conductance, as well as low-frequency pads that deliver low-frequency electrical currents for muscle massage.

[1202] control unit

[1203] The control unit is integrated into the clothing and controls the built-in sensors and low-frequency pads. The control unit has a built-in battery that supplies the necessary power. Furthermore, the control unit can communicate with an external information processing device via wireless connection.

[1204] Information processing device

[1205] The information processing device is an external device, such as a smartphone or tablet, that is wirelessly connected to the control unit. This information processing device is equipped with an artificial intelligence module and an emotion engine. It analyzes biometric data collected from sensors and emotional data from the emotion engine to generate action instructions that optimize the user's relaxation state.

[1206] User operation and treatment

[1207] The user wears a full-body, form-fitting garment and launches a dedicated application on their smartphone. Next, they turn on the power to the control unit, which activates the unit and establishes a wireless connection with the smartphone. The smartphone collects biometric data from the sensors in real time and transmits it to a cloud server.

[1208] Server Processing

[1209] The server uses AI algorithms to analyze the received biometric and emotional data. The analysis assesses the user's relaxation state, and a relaxation index is calculated based on this data. The final analysis results generate an optimal massage program.

[1210] Staff collaboration

[1211] Staff at aesthetic and massage salons perform treatments according to the optimal massage program provided by the information processing device. After the treatment, users provide feedback on their massage experience within the app. This feedback, along with biometric data, is sent to a cloud server and used to optimize future treatments.

[1212] Hardware and software used

[1213] Sensors: Devices that measure body temperature, heart rate, and skin conductance.

[1214] Low-frequency pads: Devices that use low-frequency electrical currents to perform muscle massage.

[1215] Control Unit: A device that controls sensors and low-frequency pads and has wireless communication capabilities.

[1216] Information processing device: Smartphones, tablets, and other devices with internet connectivity.

[1217] Artificial Intelligence Module: Uses Python and machine learning libraries such as scikit-learn for data analysis.

[1218] Cloud server: A remote computer system for storing and analyzing data.

[1219] Specific example

[1220] A user visiting an aesthetic salon wears a full-body garment and begins treatment using a dedicated application. A smartphone collects biometric data from sensors in the garment and analyzes it in real time on a cloud server. AI and an emotion engine generate an optimal massage program, which is then provided to the staff. After the treatment, the user's feedback is analyzed again, and a more precise massage is provided on the next visit.

[1221] Example of a prompt

[1222] "To enhance the massage effect, collect the user's heart rate, body temperature, and skin conductance data in real time and analyze it using an emotion engine. Based on the analysis results, write Python code to generate the optimal massage program."

[1223] The above describes a specific embodiment for carrying out this invention. This system makes it possible to accurately analyze the user's relaxation state and provide the optimal treatment.

[1224] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1225] Step 1:

[1226] User actions

[1227] The user wears a full-body garment and launches a dedicated application on their smartphone. The user then turns on the control unit and confirms the wireless connection between the smartphone and the control unit.

[1228] Input: The user puts on clothes and launches a smartphone app.

[1229] Output: The control unit is powered on and a wireless connection is established.

[1230] Step 2:

[1231] Collection of biometric data

[1232] Once the device (smartphone) establishes a wireless connection with the control unit, it begins collecting the user's biometric data (body temperature, heart rate, skin conductance) in real time from sensors embedded in the clothing. This data is temporarily stored in the device's internal memory.

[1233] Input: Biometric data from connected sensors.

[1234] Output: Biometric data stored in the device's internal memory.

[1235] Step 3:

[1236] Sending data

[1237] The device sends the collected biometric data to a cloud server. The data is transferred using a secure protocol.

[1238] Input: Biometric data stored in the device's internal memory.

[1239] Output: Biometric data sent to the cloud server.

[1240] Step 4:

[1241] Data Analysis

[1242] The server analyzes the received biometric data using AI algorithms. Specifically, it performs preprocessing such as smoothing and filtering, and then uses statistical methods and machine learning models (for example, scikit-learn's RandomForestClassifier) ​​to calculate a relaxation index. In addition, an emotion engine analyzes the user's emotional data.

[1243] Input: Biometric data sent to the server.

[1244] Output: Analyzed relaxation state and relaxation index.

[1245] Step 5:

[1246] Massage program generation

[1247] The server generates an optimal massage program based on the analysis results. This program includes specific operational instructions such as the position, intensity, and rhythm of the low-frequency pads. The server then transmits this data to the terminal.

[1248] Input: Analyzed relaxation state and relaxation index.

[1249] Output: The optimal massage program sent to the terminal.

[1250] Step 6:

[1251] Execution of the procedure

[1252] The terminal sends instructions to the control unit based on the massage program received from the server. The control unit then instructs the low-frequency pads to perform the actions as instructed. During this time, the user experiences the massage effect.

[1253] Input: Optimal massage program.

[1254] Output: Massage effect applied to the user.

[1255] Step 7:

[1256] Collecting user feedback

[1257] After the treatment is complete, users record their thoughts and feedback about the massage experience within the app. This feedback is entered as a form within the application.

[1258] Input: User feedback.

[1259] Output: Feedback data stored on the device.

[1260] Step 8:

[1261] Sending and analyzing feedback

[1262] The device sends user feedback to a cloud server. The server analyzes the received feedback and incorporates it into the AI ​​module and emotion engine. This feedback is then used to improve future massage programs.

[1263] Input: Feedback data stored on the device.

[1264] Output: Improved massage program for future sessions.

[1265] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1266] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include those described above. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions shown by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1267] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[1268] [Fourth Embodiment]

[1269] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1270] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1271] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1272] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[1273] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1274] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1275] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1276] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[1277] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1278] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1279] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1280] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1281] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1282] The present invention is a system that provides an optimal massage for each individual user by incorporating sensors and low-frequency pads into full-body, form-fitting clothing (shirts and tights) and wirelessly connecting them to an external information processing device (such as a smartphone). Specific embodiments of the present invention are described below.

[1283] System Configuration

[1284] clothing

[1285] The full-body garment is designed to fit snugly against the user's body surface. Multiple sensors are placed inside the garment to collect biometric data such as the user's body temperature, heart rate, and skin conductance. In addition, low-frequency pads are positioned in place and used to deliver low-frequency electrical currents to produce a massage effect.

[1286] control unit

[1287] The control unit is integrated into the clothing and serves as a power supply and signal processing unit for controlling the sensors and low-frequency pads. The control unit has an internal battery and can also communicate wirelessly.

[1288] Information processing device

[1289] The information processing device is an external device, such as a smartphone or tablet, that is wirelessly connected to the control unit. This information processing device is equipped with an artificial intelligence module that analyzes biometric data collected from sensors and visualizes the user's relaxation state. Based on this analysis, an optimal massage program is generated to maximize the user's relaxation level.

[1290] Program Implementation

[1291] User actions

[1292] The user first places a dedicated app on their smartphone and then puts on a full-body, form-fitting garment. Next, they turn on the power to the control unit. This activates the control unit and establishes a wireless connection with the smartphone.

[1293] Terminal processing

[1294] Once the device (smartphone) establishes a connection with the control unit, it begins collecting biometric data from sensors embedded in the clothing. This data is stored in internal memory in real time and transmitted to a cloud server using Wi-Fi or mobile data communication. For example, if a user performs this operation while working at a desk, their body temperature, heart rate, and skin conductance are monitored in real time.

[1295] Server Processing

[1296] The server analyzes the received biometric data to assess the user's current state of relaxation. An artificial intelligence module is used for the analysis, calculating a relaxation index based on heart rate variability and body temperature trends. Based on this relaxation index, an optimal massage pattern is generated, and instructions for the massage are created.

[1297] Receiving and controlling the device

[1298] The terminal receives operation instructions transmitted from the server and appropriately controls the low-frequency pads through the control unit. During this time, the user can experience the massage effect in real time.

[1299] User feedback

[1300] After a massage session, users provide feedback and comments within the app. This includes specific comments such as, "The shoulder massage was very effective," or "I'd like the back massage to be a little stronger." This feedback is sent from the device to the server and used to improve the accuracy of future massage programs.

[1301] Specific example

[1302] For example, consider a user A using this system to alleviate fatigue from daily desk work. In the morning, user A puts on a full-body garment, launches a dedicated app, and turns on the control unit. The device then collects biometric data, and the relaxation level is analyzed on a cloud server. AI generates an optimal massage program, and the low-frequency pads operate via the device. User A can receive an appropriate massage even while working, and provides feedback through the app afterward. This allows for an even more precise massage the next time the user uses the system.

[1303] In this way, the present invention allows the control unit, terminal, and server to work together to continuously provide the user with the optimal massage experience. By combining user feedback with AI learning capabilities, the system's accuracy improves with each use, enabling more effective massages.

[1304] The following describes the processing flow.

[1305] Step 1:

[1306] The user launches the app on their smartphone. This starts the app and verifies the user's login information. Simultaneously, the user puts on a full-body garment and turns on the power to the control unit.

[1307] Step 2:

[1308] The device (smartphone) will turn on Bluetooth and attempt to connect to the control unit. If the connection is successful, "Connection successful" will be displayed on the smartphone screen.

[1309] Step 3:

[1310] The device begins collecting the user's biometric data (such as body temperature, heart rate, and skin conductance) from sensors embedded in the clothing. This data is collected in real time and temporarily stored in the device's internal memory.

[1311] Step 4:

[1312] The device uses Wi-Fi or mobile data to send the collected biometric data to a cloud server. This allows the server to begin real-time analysis of the data.

[1313] Step 5:

[1314] The server analyzes the received biometric data and uses an AI algorithm to evaluate the user's relaxation state. A relaxation index is calculated, and analysis results based on the user's biometric data are generated.

[1315] Step 6:

[1316] Based on the analysis results, the server generates an optimal massage program to maximize the user's relaxation. Specifically, it determines instructions regarding the position, intensity, and rhythm of the low-frequency pads.

[1317] Step 7:

[1318] The server sends the generated massage program to the terminal. The terminal then confirms receipt and prepares to execute the massage.

[1319] Step 8:

[1320] The terminal sends instructions to the control unit based on the program received from the server. The control unit then causes the low-frequency pad to perform the operation as instructed.

[1321] Step 9:

[1322] The low-frequency pads deliver low-frequency electrical currents to the user's body at the instructed location, intensity, and rhythm, initiating a massage. During this time, the user can relax and experience the massage effect.

[1323] Step 10:

[1324] After the massage session ends, users record their thoughts and feedback about the massage experience within the app. For example, they can enter specific evaluations such as, "The shoulder massage was very effective," or "I would like the back massage to be more intense."

[1325] Step 11:

[1326] The device sends user feedback to the server. The server analyzes the received feedback, incorporates its contents into an AI module, and uses it to improve future massage programs.

[1327] Step 12:

[1328] The server retrains the AI ​​model based on this feedback data, improving it so that future massage programs are more effectively customized. This increases the system's accuracy and further enhances the massage effect for the user.

[1329] (Example 1)

[1330] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1331] Current massage systems struggle to provide optimal massage programs tailored to each user's individual needs. Many systems offer only fixed programs and cannot maximize massage effectiveness by utilizing user feedback or real-time biometric data. As a result, users do not experience sufficient relaxation, leading to inadequate relief from fatigue resulting from prolonged work or stress.

[1332] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1333] In this invention, the server includes means for wearing a full-body close-fitting garment, means for which sensors and a low-frequency generator are disposed inside the garment, means for which a control unit is connected to the garment, means for which an external information processing system is wirelessly connected to the control unit, and means for which a generating AI model installed in the information processing system displays the user's relaxation index based on biometric data acquired by the sensors, generates operation instructions to optimize the relaxation index, and controls the low-frequency generator according to the operation instructions. This makes it possible to provide an optimal massage program based on each user's biometric information and maximize the user's relaxation effect.

[1334] "Full-body contact clothing" refers to clothing designed to fit snugly against the user's entire body and incorporates various sensors and low-frequency generators.

[1335] A "sensor" is a device that detects biometric data such as a user's body temperature, heart rate, and skin conductance, and transmits this data to an external information processing system.

[1336] A "low-frequency generator" is a device that uses low-frequency electric current to produce a massage effect, stimulating the user's muscles by operating in a specified pattern.

[1337] A "control unit" is a device installed inside clothing that manages and controls sensors and low-frequency generators, and is equipped with power supply and wireless communication functions.

[1338] The "external information processing system" refers to a device wirelessly connected to the control unit, such as a smartphone or tablet, which analyzes the user's biometric data and generates a massage program.

[1339] A "generative AI model" is a type of artificial intelligence that uses machine learning and deep learning algorithms based on collected biometric data to calculate a user's relaxation index and generate the optimal massage program.

[1340] The "relaxation index" is an indicator calculated based on the user's biometric data, and it quantifies the user's state of relaxation.

[1341] "Operation instructions" refer to digital signals used to instruct the operation patterns of a low-frequency generator created by a generative AI model, and include instructions for executing a specific massage program.

[1342] The present invention is a system that provides an optimal massage for each individual user by incorporating sensors and a low-frequency generator into full-body contact clothing and wirelessly connecting them to an external information processing system (such as a smartphone). Specific embodiments of the present invention are described below.

[1343] System Configuration

[1344] clothing

[1345] The full-body contact garment is designed to fit snugly against the user's body surface. Multiple sensors are placed inside the garment to collect biometric data such as the user's body temperature, heart rate, and skin conductance. In addition, low-frequency generators are positioned in place and used to deliver low-frequency currents to produce a massage effect.

[1346] control unit

[1347] The control unit is integrated into the garment and serves as a power supply and signal processing unit for controlling the sensors and low-frequency generator. The control unit has an internal battery and can also communicate wirelessly.

[1348] Information processing system

[1349] The information processing system consists of an external device, such as a smartphone or tablet, that is wirelessly connected to the control unit. This information processing system is equipped with a generative AI model that analyzes biometric data collected from sensors and visualizes the user's relaxation state. Based on this analysis, an optimal massage program is generated to maximize the user's relaxation level.

[1350] Program Implementation

[1351] User actions

[1352] The user first launches a dedicated app on their smartphone and puts on the full-body, form-fitting clothing. Next, they turn on the power to the control unit. This activates the control unit and establishes a wireless connection with the smartphone.

[1353] Terminal processing

[1354] Once the device (smartphone) establishes a connection with the control unit, it begins collecting biometric data from sensors embedded in the clothing. This data is stored in internal memory in real time and transmitted to a cloud server using Wi-Fi or mobile data communication. For example, if a user performs this operation while working at a desk, their body temperature, heart rate, and skin conductance are monitored in real time.

[1355] Server Processing

[1356] The server analyzes the received biometric data to assess the user's current state of relaxation. A generative AI model is used for the analysis, calculating a relaxation index based on heart rate variability and body temperature trends. Based on this relaxation index, an optimal massage pattern is generated, and instructions are created.

[1357] Receiving and controlling the device

[1358] The terminal receives operation instructions transmitted from the server and appropriately controls the low-frequency generator through the control unit. During this time, the user can experience the massage effect in real time.

[1359] User feedback

[1360] After a massage session, users provide feedback and comments within the app. This includes specific comments such as, "The shoulder massage was very effective," or "I'd like the back massage to be a little stronger." This feedback is sent from the device to the server and used to improve the accuracy of future massage programs.

[1361] Specific example

[1362] For example, consider a user A using this system to alleviate fatigue from daily desk work. In the morning, user A puts on full-body contact clothing, launches a dedicated app, and turns on the control unit. The terminal then collects biometric data, and the relaxation level is analyzed on a cloud server. A generating AI model creates an optimal massage program, and the low-frequency generator operates via the terminal. User A can receive an appropriate massage even while working, and provides feedback via the app afterward. This allows for an even more precise massage the next time the system is used.

[1363] Example of a prompt

[1364] For example, the prompt might look like this: "Please generate an optimal massage program to relieve stiff shoulders and back pain caused by desk work. Evaluate the user's relaxation level based on their body temperature, heart rate, and skin conductance, and propose an operating pattern for the low-frequency generator."

[1365] In this way, the present invention allows the control unit, terminal, and server to work together to continuously provide the user with the optimal massage experience. By combining user feedback with the learning function of the generative AI model, the system's accuracy improves with each use, enabling more effective massages.

[1366] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1367] Step 1:

[1368] The user wears a full-body garment and launches a dedicated app on their smartphone. Next, they turn on the power to the control unit. The user's actions act as input, the control unit becomes active as output, and a wireless connection is established with the smartphone.

[1369] Step 2:

[1370] Once the smartphone (device) establishes a connection with the control unit, it begins collecting the user's biometric data (body temperature, heart rate, skin conductance) from sensors embedded in the clothing. The biometric data from the sensors is the input, and this is stored in the smartphone's internal memory in real time as the output. Furthermore, this data is transmitted to a cloud server using Wi-Fi or mobile data communication.

[1371] Step 3:

[1372] The cloud server receives biometric data transmitted from the smartphone. The biometric data is transferred to the server as input, and data analysis is performed on the server side as output. This allows the generating AI model to analyze heart rate variability and body temperature trends, and calculate a relaxation index. Specifically, it performs analysis of heart rate variability patterns and body temperature trends.

[1373] Step 4:

[1374] The generative AI model generates an optimal massage program based on a relaxation index. It takes analysis results as input and generates the optimal massage program as output. Specifically, prompts such as "Generate a relaxing massage pattern focusing on the shoulders and back based on the user's body temperature and heart rate data" are used.

[1375] Step 5:

[1376] The server sends the generated massage program to the smartphone. The generated massage program is the input, and this is received by the smartphone as the output. Specifically, the program data is transferred from the server.

[1377] Step 6:

[1378] The smartphone transfers the received massage program to the control unit, which then operates the low-frequency generator in the specified pattern. The input is an operation instruction from the server, and the output is the appropriate operation of the low-frequency generator. For example, the control might be: "To loosen the shoulder muscles, the low-frequency generator operates for 3 seconds, then pauses for 1 second."

[1379] Step 7:

[1380] After a massage session, users provide feedback through a dedicated app. The input consists of the user's impressions and opinions, and this feedback is sent to a cloud server via the device. Specific comments, such as "The shoulder massage was very effective" or "I'd like the back massage to be a little stronger," are recorded within the app.

[1381] Step 8:

[1382] The cloud server receives feedback from users, and the generating AI model uses this information to improve the accuracy of the next massage program generation. The input is user feedback data, and the output is an improved massage program for subsequent uses. Specifically, the AI ​​model performs a learning process based on the feedback data.

[1383] (Application Example 1)

[1384] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1385] The problem lies in the lack of efficient means of rest and relaxation for industrial workers who perform long hours of standing or heavy labor. Furthermore, conventional rest methods make it difficult to provide appropriate relaxation tailored to the individual needs of each worker.

[1386] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1387] In this invention, the server includes means for monitoring biometric data in real time and transmitting it to a cloud database, means for generating an optimal massage program using a generative AI model, means for notifying a head-mounted display, and means for collecting user feedback and adjusting the next massage program. This makes it possible for industrial workers to receive individually optimized relaxation.

[1388] "Full-body contact clothing" refers to clothing designed to fit snugly against the user's body surface and incorporating sensors for collecting biometric data and low-frequency pads to provide a massage effect.

[1389] A "sensor" is a device that measures a user's biometric data, such as body temperature, heart rate, and skin conductance.

[1390] A "low-frequency pad" is a device that produces a massage effect by applying a low-frequency electric current to a specific area.

[1391] The "control unit" is a device that controls the sensor and low-frequency pad, supplies power, and performs signal processing, and can be wirelessly connected to the information processing device.

[1392] An "information processing device" is an external device such as a smartphone or tablet that includes an artificial intelligence module for analyzing data acquired from sensors and generating an optimal massage program.

[1393] The "artificial intelligence module" is a software module that analyzes biometric data acquired by sensors, visualizes the user's relaxation state, and generates an optimal massage program.

[1394] A "generative AI model" is an artificial intelligence algorithm used to generate the optimal massage program based on biometric data.

[1395] A "head-mounted display" is a display device worn by the user and is used to display operation instructions generated by an artificial intelligence module.

[1396] "Feedback" is the process by which users provide their thoughts and opinions about their massage experience, and this information is used to improve future massage programs.

[1397] Modes for carrying out the invention

[1398] This invention is a system designed to improve the health management and rest efficiency of industrial workers. This invention makes it possible to provide individually optimized relaxation even during long hours of standing work or heavy labor.

[1399] System Configuration

[1400] clothing

[1401] The full-body contact garment is designed to fit snugly against the user's body surface. Inside the garment are multiple sensors and low-frequency pads. The sensors collect biometric data such as the user's body temperature, heart rate, and skin conductance. The low-frequency pads are used to produce a massage effect.

[1402] control unit

[1403] The control unit is integrated into the clothing and serves as a power supply and signal processing unit for controlling the sensors and low-frequency pads. The control unit has an internal battery and also communicates wirelessly.

[1404] Information processing device

[1405] The information processing device is an external device, such as a smartphone or tablet, that is wirelessly connected to the control unit. This information processing device is equipped with an artificial intelligence module that analyzes biometric data collected from sensors and visualizes the user's relaxation state. Based on this analysis, a generative AI model generates an optimal massage program.

[1406] Program Implementation

[1407] User actions

[1408] First, the user puts on a full-body garment and launches a dedicated app on their smartphone. Next, they turn on the power to the control unit. This activates the control unit and establishes a wireless connection with the smartphone.

[1409] Terminal processing

[1410] Once connected to the control unit, the device (smartphone) begins collecting biometric data from sensors embedded in the clothing. This data is stored in internal memory in real time and transmitted to a cloud server using Wi-Fi or mobile data communication. For example, if this operation is performed while the user is working, body temperature, heart rate, and skin conductance are monitored in real time.

[1411] Server Processing

[1412] The server analyzes the received biometric data to assess the user's current state of relaxation. A generative AI model is used for the analysis, calculating a relaxation index based on heart rate variability and body temperature trends. Based on this relaxation index, an optimal massage pattern is generated, and instructions are created.

[1413] Receiving and controlling the device

[1414] The terminal receives operation instructions transmitted from the server and appropriately controls the low-frequency pads through the control unit. During this time, the user can experience the massage effect in real time.

[1415] User feedback

[1416] After a massage session, users provide feedback and comments within the app. This includes specific comments such as "The shoulder massage was very effective" or "I'd like the back massage to be a little stronger." This feedback is sent from the device to the server and used to improve the accuracy of future massage programs.

[1417] Specific example

[1418] For example, if industrial worker A feels fatigued after working for a long time, the full-body contact garment detects this condition, and a generating AI model creates an optimal massage program. This instruction is sent to a terminal, and worker A can receive an appropriate massage using low-frequency pads during a break.

[1419] Example of a prompt

[1420] Monitor factory workers' vital data (heart rate, body temperature, skin conductance) in real time and generate an optimal massage program based on this data. Notify the worker of the results via a head-mounted display and provide them with the appropriate massage. Also, collect worker feedback to improve the next massage program.

[1421] In this way, the system of the present invention improves in accuracy with each use by combining user feedback and a generated AI model, providing more effective relaxation.

[1422] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1423] Step 1:

[1424] User Operation: The user wears a full-body, form-fitting garment and activates a dedicated application on their smartphone to turn on the control unit. At this stage, the control unit becomes active and a wireless connection with the smartphone is established.

[1425] Input: User actions

[1426] Output: Establishment of wireless connection between the control unit and the smartphone.

[1427] Specific operation: The user launches the app and turns on the power to the control unit. The smartphone app recognizes the control unit and establishes a connection.

[1428] Step 2:

[1429] Data Collection: Once the device (smartphone) connects to the control unit, it begins collecting biometric data (heart rate, body temperature, skin conductance) from sensors embedded in the clothing. This data is stored in internal memory in real time and transmitted to a cloud server using Wi-Fi or mobile data communication.

[1430] Input: Data from sensors embedded in the clothing

[1431] Output: Biometric data sent to the cloud server

[1432] Specific operation: The sensor acquires the user's biometric data, the smartphone receives it, and sends it to a cloud server.

[1433] Step 3:

[1434] Data analysis and massage program generation: The server analyzes the received biometric data and calculates a relaxation index using a generated AI model. Based on the results, an optimal massage program is generated and action instructions are created.

[1435] Input: Biometric data sent to the cloud server

[1436] Output: Generated optimal massage program and operating instructions

[1437] Specific operation: The AI ​​module analyzes the data, and the generated AI model creates the optimal massage program and outputs it as an action instruction.

[1438] Step 4:

[1439] Receiving and executing operation instructions: The terminal (smartphone) receives operation instructions from the server and appropriately controls the low-frequency pads via the control unit. This allows the user to experience massage effects in real time.

[1440] Input: Operation instructions sent from the server

[1441] Output: Operation control of low-frequency pads

[1442] Specific operation: The smartphone receives operation instructions from the server and controls the operation of the low-frequency pad via the control unit.

[1443] Step 5:

[1444] User Feedback Collection: After a massage session ends, users provide feedback within the app. This feedback is sent from the device to the server and used to improve the accuracy of future massage programs.

[1445] Input: User feedback

[1446] Output: Data from the improved massage program

[1447] Specific operation: Users enter feedback within the app, which is sent to the server, and the AI ​​module incorporates it into the next program.

[1448] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1449] The present invention is a system for optimizing the user's relaxation state, comprising a sensor and low-frequency pad embedded in a full-body garment, as well as an information processing device equipped with an emotion engine. Specific embodiments of the present invention will be described below, along with specific examples illustrating the system's program and processing flow.

[1450] System Configuration

[1451] clothing

[1452] The full-body garment is designed to fit snugly against the user's body surface. Inside the garment are multiple sensors and low-frequency pads that collect biometric data such as the user's body temperature, heart rate, and skin conductance, and use low-frequency electrical currents to stimulate the muscles and produce a massage effect.

[1453] control unit

[1454] The control unit is integrated into the clothing and serves as a power supply and signal processing unit for controlling the sensors and low-frequency pads. The control unit has an internal battery and can also communicate wirelessly.

[1455] Information processing device

[1456] The information processing device is an external device, such as a smartphone or tablet, that is wirelessly connected to the control unit. This information processing device is equipped with an artificial intelligence module that analyzes biometric data collected from sensors and visualizes the user's relaxation state. It also includes an emotion engine that recognizes the user's emotions and provides auxiliary information to optimize the relaxation state.

[1457] Program Implementation

[1458] User actions

[1459] First, the user launches a dedicated app on their smartphone and puts on a full-body, form-fitting garment. Then, they turn on the power to the control unit. This activates the control unit and establishes a wireless connection with the smartphone.

[1460] Terminal processing

[1461] Once the device (smartphone) establishes a connection with the control unit, it begins collecting the user's biometric data (body temperature, heart rate, skin conductance, etc.) from sensors embedded in the clothing. This data is collected in real time and temporarily stored in the device's internal memory. The collected data is then sent to a cloud server.

[1462] Server Processing

[1463] The server analyzes the received biometric data and emotional data acquired by the emotion engine. An AI algorithm is used for the analysis to evaluate the user's relaxation state. A relaxation index is calculated, and analysis results are generated based on this index.

[1464] Analysis of the Emotion Engine

[1465] The emotion engine analyzes the user's facial expressions, voice tone, and body temperature changes to recognize their emotional state. For example, it can determine whether a user is stressed based on the movement of their facial muscles. This emotional data is also sent to the server and used to assess their state of relaxation.

[1466] Massage program generation

[1467] Based on the analysis results, the server generates an optimal massage program that maximizes the user's relaxation state. This also incorporates data from the emotion engine. Specifically, the position, intensity, and rhythm of the low-frequency pads are determined.

[1468] Control Unit Operation

[1469] The terminal sends instructions to the control unit based on the massage program received from the server. The control unit then instructs the low-frequency pads to perform the actions as instructed. During this time, the user can experience the massage effect.

[1470] User feedback

[1471] After the massage session ends, users record their thoughts and feedback about the massage experience within the app. For example, they can enter specific evaluations such as, "The shoulder massage was very effective," or "I would like the back massage to be more intense."

[1472] Feedback analysis

[1473] The device sends user feedback to the server. The server analyzes the received feedback, incorporates its contents into the AI ​​module and emotion engine, and uses it to improve future massage programs.

[1474] Specific example

[1475] For example, consider a user A using this system to alleviate fatigue from daily desk work. In the morning, user A puts on a full-body garment, launches a dedicated app, and turns on the control unit. The device then collects biometric data and emotional data such as facial expressions, which are analyzed on a cloud server. The AI ​​and emotion engine generate an optimal massage program, and the operation instructions are sent to the control unit via the device. User A can receive an appropriate massage even while working, and provides feedback through the app afterward. This allows for an even more precise massage the next time the system is used.

[1476] In this way, the present invention combines an emotion engine to create a system that provides a more precise relaxation effect. By incorporating user feedback and emotional data, the AI ​​continuously learns, improving the system's accuracy with each use and enabling a more effective massage.

[1477] The following describes the processing flow.

[1478] Step 1:

[1479] The user launches a dedicated app on their smartphone. This starts the app and verifies the user's login information. Simultaneously, the user puts on a full-body form-fitting garment and turns on the power to the control unit.

[1480] Step 2:

[1481] The device (smartphone) will turn on Bluetooth and attempt to connect to the control unit. If the connection is successful, "Connection successful" will be displayed on the smartphone screen.

[1482] Step 3:

[1483] The device begins collecting the user's biometric data (body temperature, heart rate, skin conductance, etc.) from sensors embedded in the clothing. This data is collected in real time and temporarily stored in the device's internal memory.

[1484] Step 4:

[1485] The device uses Wi-Fi or mobile data to send the collected biometric data to a cloud server. This allows the server to begin real-time analysis of the data.

[1486] Step 5:

[1487] The server analyzes the received biometric data and uses an AI algorithm to evaluate the user's relaxation state. A relaxation index is calculated, and the analysis results are generated.

[1488] Step 6:

[1489] The server's emotion engine analyzes the user's facial expressions, voice tone, body temperature changes, and other factors to recognize the user's emotional state. For example, it can identify situations where the user is experiencing stress.

[1490] Step 7:

[1491] Based on the recognition results from the emotion engine, the server performs further detailed analysis and evaluates the user's relaxed state, taking into account their emotional condition.

[1492] Step 8:

[1493] Based on the analysis results, the server generates an optimal massage program to maximize the user's relaxation. Specifically, it determines instructions regarding the position, intensity, and rhythm of the low-frequency pads.

[1494] Step 9:

[1495] The server sends the generated massage program to the terminal. The terminal confirms receipt and is ready to execute the massage.

[1496] Step 10:

[1497] The terminal sends instructions to the control unit based on the program received from the server. The control unit then causes the low-frequency pad to perform the operation as instructed.

[1498] Step 11:

[1499] The low-frequency pads deliver low-frequency electrical currents to the user's body at the instructed location, intensity, and rhythm, initiating a massage. During this time, the user can relax and experience the massage effect.

[1500] Step 12:

[1501] After the massage session ends, users record their thoughts and feedback about the massage experience within the app. For example, they can enter specific evaluations such as, "The shoulder massage was very effective," or "I would like the back massage to be more intense."

[1502] Step 13:

[1503] The device sends user feedback to the server. The server analyzes the received feedback, incorporates its contents into the AI ​​module and emotion engine, and uses it to improve future massage programs.

[1504] Step 14:

[1505] The server retrains the AI ​​model based on feedback data, improving it so that subsequent massage programs are more effectively customized. This increases the system's accuracy and further enhances the massage effect for the user.

[1506] (Example 2)

[1507] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1508] In modern society, health problems caused by stress and overwork are increasing, with physical fatigue and mental stress from desk work being particularly problematic. In this situation, there is a need to provide effective relaxation methods. However, conventional massage and relaxation devices often fail to adequately reflect the individual state and emotions of users, instead offering uniform programs. Therefore, it has been difficult to enhance relaxation effects tailored to each user's individual needs.

[1509] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for evaluating the user's relaxation state based on biometric data and emotional data, means for generating action instructions to optimize the user's relaxation state, and means for collecting and learning user feedback. This makes it possible to provide an optimal massage program tailored to the individual user's condition and to improve its accuracy.

[1510] "Full-body contact clothing" refers to clothing designed to fit snugly against the user's body surface, with sensors and low-frequency pads placed inside to collect biometric data and produce a massage effect.

[1511] A "sensor" is a device that collects biometric data such as body temperature, heart rate, and skin conductance in real time.

[1512] A "low-frequency pad" is a device that uses low-frequency electrical currents to stimulate muscles, producing a massage effect.

[1513] The "control unit" is a power supply and signal processing unit for controlling the sensor and low-frequency pad. It operates using a built-in battery and has wireless connectivity.

[1514] An "information processing device" is an external device such as a smartphone or tablet that is wirelessly connected to the control unit. It is equipped with an artificial intelligence module and analyzes data collected from sensors to visualize and optimize the user's relaxation state.

[1515] The "artificial intelligence module" is software that analyzes biometric data acquired by sensors and utilizes AI algorithms to evaluate and optimize the user's relaxation state.

[1516] The "emotion engine" is software that analyzes the user's facial expressions, voice tone, body temperature changes, etc., to recognize their emotional state, and it works in conjunction with the artificial intelligence module.

[1517] "Operation instructions" refer to control instructions that include the position, intensity, and rhythm of the low-frequency pads generated to optimize the user's relaxation state.

[1518] "Feedback" refers to the user's comments and evaluations regarding the effectiveness of the massage and areas for improvement after a massage session.

[1519] A "cloud server" is a remote server used to analyze collected biometric and emotional data and generate the optimal massage program.

[1520] This invention comprises a full-body, form-fitting garment with built-in sensors and low-frequency pads, as well as an information processing device equipped with an emotion engine, and is a system for optimizing the user's relaxation state. This system is implemented using the following hardware and software.

[1521] Hardware configuration

[1522] clothing

[1523] The full-body garment is designed to fit snugly against the user's body surface. Inside the garment are multiple sensors and low-frequency pads with the following functions:

[1524] Sensors that collect biometric data such as body temperature, heart rate, and skin conductance.

[1525] Low-frequency pads that produce a massage effect by applying low-frequency electrical currents to the muscles.

[1526] control unit

[1527] The control unit is integrated into the clothing and serves as a power supply and signal processing unit for controlling the sensors and low-frequency pads. The control unit has the following functions:

[1528] It has an internal battery and also communicates wirelessly.

[1529] Information processing device

[1530] The information processing device is an external device, such as a smartphone or tablet, that is wirelessly connected to the control unit. This information processing device is equipped with an artificial intelligence module that has the following functions:

[1531] Analyze biometric data collected from sensors.

[1532] Using an emotion engine (software that analyzes facial expressions, voice tone, body temperature changes, etc., to recognize the user's emotional state), it generates action instructions to visualize and optimize the user's relaxation state.

[1533] Software Configuration

[1534] Dedicated app

[1535] Users install a dedicated app on their smartphone and operate the system by launching the app. This app has the following functions:

[1536] Collecting biometric data from sensors embedded in clothing.

[1537] Establish a wireless connection with the control unit and transmit control signals for the low-frequency pad.

[1538] Collect user feedback and send it to the cloud server.

[1539] Cloud Server

[1540] The cloud server has the following functions and operates as the central hub of the entire system.

[1541] Analysis of collected biometric and emotional data

[1542] Generating the optimal massage program to optimize relaxation.

[1543] The server uses an AI algorithm to evaluate the user's relaxation level and calculate a relaxation index.

[1544] Instructions for use (specific examples)

[1545] For example, consider a case where user A uses this system to alleviate fatigue from daily desk work. The system can be used by following the steps below.

[1546] 1. In the morning, User A puts on full-body clothing and activates a dedicated app on their smartphone to turn on the control unit.

[1547] 2. The device (smartphone) collects biometric data and emotional data and sends it to a cloud server.

[1548] 3. The cloud server analyzes the data and generates the optimal massage program.

[1549] 4. Operation instructions from the server are sent to the control unit via the terminal, and the low-frequency pad performs the specified operation.

[1550] 5. User A can receive a suitable massage even while working.

[1551] 6. After the massage session, User A provides feedback via the app.

[1552] 7. Your feedback will be incorporated into future visits, resulting in even more precise massages.

[1553] Example of a prompt

[1554] As an example, the following is a prompt message used when the server evaluates the user's relaxation state and generates the optimal massage program.

[1555] "Analyze the user's biometric and emotional data to assess their relaxation state and generate the optimal massage program. Biometric data should include body temperature, heart rate, and skin conductance, while emotional data should be obtained based on facial expressions, voice tone, and changes in body temperature."

[1556] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1557] Step 1:

[1558] Input: The user wears full-body clothing and launches a dedicated app on their smartphone.

[1559] Operation: The user turns on the power to the control unit.

[1560] Output: A wireless connection is established between the control unit and the smartphone, and the connection status can be checked on the app.

[1561] Step 2:

[1562] Input: Connection information from the control unit

[1563] Operation: The device (smartphone) confirms that a wireless connection has been established with the control unit and begins collecting biometric data (body temperature, heart rate, skin conductance, etc.) in real time from sensors embedded in the clothing.

[1564] Output: The collected biometric data is temporarily stored in the device's internal memory.

[1565] Step 3:

[1566] Input: Biometric data stored on the device

[1567] Operation: The device sends collected biometric data to a cloud server at regular intervals (e.g., every 10 seconds).

[1568] Output: Biometric data is uploaded to a cloud server.

[1569] Step 4:

[1570] Input: Biometric data and emotional data uploaded to a cloud server

[1571] Operation: The server uses AI algorithms and an emotion engine based on received biometric and emotional data to analyze the user's relaxation state and calculate a relaxation index.

[1572] Output: Analysis results and a relaxation index are generated.

[1573] Step 5:

[1574] Input: Analysis results and relaxation index

[1575] Operation: Based on this data, the server generates an optimal massage program to optimize the user's relaxation state.

[1576] Output: The generated massage program is saved on the server.

[1577] Step 6:

[1578] Input: Generated massage program

[1579] Operation: The terminal sends instructions to the control unit based on the massage program received from the server.

[1580] Output: The instruction reaches the control unit, and the operation of the low-frequency pad begins.

[1581] Step 7:

[1582] Input: Operation instructions from the control unit.

[1583] Operation: The control unit applies the specified current to the low-frequency pad, providing a massage effect to the user's body.

[1584] Output: The user experiences the massage effect.

[1585] Step 8:

[1586] Input: Feedback form after massage session

[1587] Operation: Users enter their feedback and ratings about their massage experience within the app.

[1588] Output: Feedback is saved to the device.

[1589] Step 9:

[1590] Input: Feedback saved on the device

[1591] Operation: The device sends user feedback to the cloud server.

[1592] Output: Feedback is uploaded to the cloud server.

[1593] Step 10:

[1594] Input: Feedback uploaded to the cloud server

[1595] Operation: The server analyzes the received feedback, incorporates its contents into the AI ​​module and emotion engine, and uses them to improve future massage programs.

[1596] Output: Data is updated to generate more accurate massage programs for future sessions.

[1597] (Application Example 2)

[1598] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1599] In aesthetic and massage salons, there is a demand for treatments that optimize the user's relaxation state. However, because this depends on the skill and experience of the staff, it is difficult to provide the optimal relaxation effect for each individual user. Furthermore, there is a need for a system that analyzes the user's biometric data and emotional state in real time and provides an optimal massage program based on that analysis. However, conventional technology does not have a sufficiently established means of effectively collecting, analyzing, and reflecting this data in treatments.

[1600] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1601] In this invention, the server includes means for collecting biometric data acquired by sensors in real time, means for analyzing the user's emotional state using an emotion engine, and means for generating an optimal massage program based on the analysis results. This enables the staff to accurately analyze the user's relaxation state and perform the most appropriate treatment based on that analysis.

[1602] "Full-body contact clothing" refers to clothing designed to fit snugly to the user's entire body, and is a device that uses built-in sensors and low-frequency pads to collect biometric data and provide relaxation effects.

[1603] A "sensor" is a device used to collect biological data such as body temperature, heart rate, and skin conductance.

[1604] A "low-frequency pad" is a device that uses low-frequency electrical currents to produce a massage effect on muscles.

[1605] The "control unit" is a power supply and signal processing device for controlling sensors and low-frequency pads embedded in clothing. It also has a built-in battery and communicates wirelessly.

[1606] An "information processing device" is an external device that is wirelessly connected to the control unit. It is equipped with an artificial intelligence module, analyzes biometric data collected from sensors, visualizes the user's relaxation state, and generates optimal action instructions.

[1607] An "artificial intelligence module" is software or hardware that analyzes the user's relaxation state based on data acquired by sensors and generates optimal action instructions.

[1608] An "emotion engine" is an artificial intelligence technology that analyzes a user's emotional state and is used to evaluate their relaxation level and generate the optimal massage program.

[1609] "Feedback" refers to the comments and evaluations that users provide about their massage experience, and this information is used to improve future treatments.

[1610] A "massage program" is a plan that includes specific instructions regarding the position, intensity, and rhythm of the low-frequency pads in order to optimize the user's relaxation state.

[1611] A "cloud server" is a computer server located in a remote location that stores and analyzes data via the internet.

[1612] An "aesthetic salon" is a business that provides treatments for the purpose of beauty and relaxation.

[1613] A "massage salon" is a business that provides massage treatments for the purpose of relaxation and fatigue relief.

[1614] composition

[1615] This invention is a system consisting of a full-body garment, sensors and low-frequency pads placed inside the garment, a control unit connected to the garment, and an external information processing device wirelessly connected to the control unit. This system is particularly intended for use in aesthetic salons and massage salons.

[1616] Full-body close-fitting clothing

[1617] The full-body garment is designed to fit snugly against the user's body surface. It incorporates multiple sensors to collect biometric data such as body temperature, heart rate, and skin conductance, as well as low-frequency pads that deliver low-frequency electrical currents for muscle massage.

[1618] control unit

[1619] The control unit is integrated into the clothing and controls the built-in sensors and low-frequency pads. The control unit has a built-in battery that supplies the necessary power. Furthermore, the control unit can communicate with an external information processing device via wireless connection.

[1620] Information processing device

[1621] The information processing device is an external device, such as a smartphone or tablet, that is wirelessly connected to the control unit. This information processing device is equipped with an artificial intelligence module and an emotion engine. It analyzes biometric data collected from sensors and emotional data from the emotion engine to generate action instructions that optimize the user's relaxation state.

[1622] User operation and treatment

[1623] The user wears a full-body, form-fitting garment and launches a dedicated application on their smartphone. Next, they turn on the power to the control unit, which activates the unit and establishes a wireless connection with the smartphone. The smartphone collects biometric data from the sensors in real time and transmits it to a cloud server.

[1624] Server Processing

[1625] The server uses AI algorithms to analyze the received biometric and emotional data. The analysis assesses the user's relaxation state, and a relaxation index is calculated based on this data. The final analysis results generate an optimal massage program.

[1626] Staff collaboration

[1627] Staff at aesthetic and massage salons perform treatments according to the optimal massage program provided by the information processing device. After the treatment, users provide feedback on their massage experience within the app. This feedback, along with biometric data, is sent to a cloud server and used to optimize future treatments.

[1628] Hardware and software used

[1629] Sensors: Devices that measure body temperature, heart rate, and skin conductance.

[1630] Low-frequency pads: Devices that use low-frequency electrical currents to perform muscle massage.

[1631] Control Unit: A device that controls sensors and low-frequency pads and has wireless communication capabilities.

[1632] Information processing device: Smartphones, tablets, and other devices with internet connectivity.

[1633] Artificial Intelligence Module: Uses Python and machine learning libraries such as scikit-learn for data analysis.

[1634] Cloud server: A remote computer system for storing and analyzing data.

[1635] Specific example

[1636] A user visiting an aesthetic salon wears a full-body garment and begins treatment using a dedicated application. A smartphone collects biometric data from sensors in the garment and analyzes it in real time on a cloud server. AI and an emotion engine generate an optimal massage program, which is then provided to the staff. After the treatment, the user's feedback is analyzed again, and a more precise massage is provided on the next visit.

[1637] Example of a prompt

[1638] "To enhance the massage effect, collect the user's heart rate, body temperature, and skin conductance data in real time and analyze it using an emotion engine. Based on the analysis results, write Python code to generate the optimal massage program."

[1639] The above describes a specific embodiment for carrying out this invention. This system makes it possible to accurately analyze the user's relaxation state and provide the optimal treatment.

[1640] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1641] Step 1:

[1642] User actions

[1643] The user wears a full-body garment and launches a dedicated application on their smartphone. The user then turns on the control unit and confirms the wireless connection between the smartphone and the control unit.

[1644] Input: The user puts on clothes and launches a smartphone app.

[1645] Output: The control unit is powered on and a wireless connection is established.

[1646] Step 2:

[1647] Collection of biometric data

[1648] Once the device (smartphone) establishes a wireless connection with the control unit, it begins collecting the user's biometric data (body temperature, heart rate, skin conductance) in real time from sensors embedded in the clothing. This data is temporarily stored in the device's internal memory.

[1649] Input: Biometric data from connected sensors.

[1650] Output: Biometric data stored in the device's internal memory.

[1651] Step 3:

[1652] Sending data

[1653] The device sends the collected biometric data to a cloud server. The data is transferred using a secure protocol.

[1654] Input: Biometric data stored in the device's internal memory.

[1655] Output: Biometric data sent to the cloud server.

[1656] Step 4:

[1657] Data Analysis

[1658] The server analyzes the received biometric data using AI algorithms. Specifically, it performs preprocessing such as smoothing and filtering, and then uses statistical methods and machine learning models (for example, scikit-learn's RandomForestClassifier) ​​to calculate a relaxation index. In addition, an emotion engine analyzes the user's emotional data.

[1659] Input: Biometric data sent to the server.

[1660] Output: Analyzed relaxation state and relaxation index.

[1661] Step 5:

[1662] Massage program generation

[1663] The server generates an optimal massage program based on the analysis results. This program includes specific operational instructions such as the position, intensity, and rhythm of the low-frequency pads. The server then transmits this data to the terminal.

[1664] Input: Analyzed relaxation state and relaxation index.

[1665] Output: The optimal massage program sent to the terminal.

[1666] Step 6:

[1667] Execution of the procedure

[1668] The terminal sends instructions to the control unit based on the massage program received from the server. The control unit then instructs the low-frequency pads to perform the actions as instructed. During this time, the user experiences the massage effect.

[1669] Input: Optimal massage program.

[1670] Output: Massage effect applied to the user.

[1671] Step 7:

[1672] Collecting user feedback

[1673] After the treatment is complete, users record their thoughts and feedback about the massage experience within the app. This feedback is entered as a form within the application.

[1674] Input: User feedback.

[1675] Output: Feedback data stored on the device.

[1676] Step 8:

[1677] Sending and analyzing feedback

[1678] The device sends user feedback to a cloud server. The server analyzes the received feedback and incorporates it into the AI ​​module and emotion engine. This feedback is then used to improve future massage programs.

[1679] Input: Feedback data stored on the device.

[1680] Output: Improved massage program for future sessions.

[1681] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1682] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include those described above. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions shown by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1683] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[1684] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1685] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. In the upper and lower directions of the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. Also, the upper side of the concentric circles is where "pleasant" emotions are located, and the lower side is where "unpleasant" emotions are located. In this way, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[1686] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[1687] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[1688] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[1689] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[1690] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[1691] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[1692] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[1693] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[1694] 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.

[1695] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[1696] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[1697] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[1698] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[1699] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[1700] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[1701] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[1702] The following is further disclosed regarding the embodiments described above.

[1703] (Claim 1)

[1704] Full-body close-fitting clothing,

[1705] The sensor and low-frequency pad are placed inside the garment,

[1706] A control unit connected to the garment,

[1707] An external information processing device wirelessly connected to the control unit,

[1708] The system is characterized in that an artificial intelligence module included in the information processing device visualizes the user's relaxation state based on data acquired by the sensor, generates operation instructions to optimize the relaxation state, and controls the low-frequency pad according to the operation instructions.

[1709] (Claim 2)

[1710] The system according to claim 1, characterized in that the power supply to the control unit is provided using a battery built into the control unit.

[1711] (Claim 3)

[1712] The system according to claim 1, characterized in that the artificial intelligence module learns the user's feedback and improves subsequent operation instructions.

[1713] "Example 1"

[1714] (Claim 1)

[1715] A means of wearing full-body close-fitting clothing,

[1716] The means comprising a sensor and a low-frequency generator placed inside the garment,

[1717] Means including a control unit connected to the garment,

[1718] Means including an external information processing system wirelessly connected to the control unit,

[1719] A system that uses a generating AI model installed in the information processing system to display the user's relaxation index based on biometric data acquired by the sensor, generates operation instructions to optimize the relaxation index, and controls the low-frequency generator according to the operation instructions.

[1720] (Claim 2)

[1721] The system according to claim 1, characterized in that the control unit is powered by a battery in which it is built.

[1722] (Claim 3)

[1723] The system according to claim 1, characterized in that the generating AI model learns the user's feedback and improves subsequent operation instructions.

[1724] "Application Example 1"

[1725] (Claim 1)

[1726] Full-body close-fitting clothing,

[1727] The sensor and low-frequency pad are placed inside the garment,

[1728] A control unit connected to the garment,

[1729] An external information processing device wirelessly connected to the control unit,

[1730] The artificial intelligence module included in the aforementioned information processing device

[1731] Based on the data acquired by the aforementioned sensor, the user's relaxation state is visualized.

[1732] Generate an action instruction to optimize the aforementioned relaxation state,

[1733] A system characterized by controlling the low-frequency pad in accordance with the aforementioned operation instructions,

[1734] The vital data of industrial workers is monitored in real time.

[1735] Means of sending to a cloud database,

[1736] Based on the aforementioned real-time data, an optimal massage program is generated using a generative AI model.

[1737] Means for notifying a head-mounted display to provide the aforementioned appropriate massage,

[1738] A system that includes means for collecting user feedback and adjusting the next massage program.

[1739] (Claim 2)

[1740] The system according to claim 1, characterized in that the power supply to the control unit is provided using a battery built into the control unit.

[1741] (Claim 3)

[1742] The system according to claim 1, characterized in that the artificial intelligence module learns the user's feedback and improves subsequent operation instructions.

[1743] "Example 2 of combining an emotion engine"

[1744] (Claim 1)

[1745] Full-body close-fitting clothing,

[1746] The sensor and low-frequency pad are placed inside the garment,

[1747] A control unit connected to the garment,

[1748] An external information processing device wirelessly connected to the control unit,

[1749] The artificial intelligence module included in the information processing device evaluates the user's relaxation state based on biometric data acquired by the sensor and emotional data from the emotion engine, generates action instructions to optimize the relaxation state, and controls the low-frequency pad according to the action instructions.

[1750] Means for the artificial intelligence module to learn user feedback in order to collect user feedback and improve subsequent operation instructions,

[1751] A system that includes this.

[1752] (Claim 2)

[1753] The system according to claim 1, characterized in that the power supply to the control unit is provided using a battery built into the control unit.

[1754] (Claim 3)

[1755] The system according to claim 1, characterized in that a cloud server is used for the aforementioned data analysis.

[1756] "Application example 2 when combining with an emotional engine"

[1757] (Claim 1)

[1758] Full-body close-fitting clothing,

[1759] The sensor and low-frequency pad are placed inside the garment,

[1760] A control unit connected to the garment,

[1761] An external information processing device wirelessly connected to the control unit,

[1762] The artificial intelligence module included in the information processing device visualizes the user's relaxation state based on the data acquired by the sensor, generates operation instructions to optimize the relaxation state, and controls the low-frequency pad according to the operation instructions.

[1763] This system is designed for use in aesthetic salons and massage salons, and is characterized by its collaboration with the staff performing the treatments.

[1764] (Claim 2)

[1765] The system according to claim 1, characterized in that the power supply to the control unit is provided using a battery built into the control unit.

[1766] (Claim 3)

[1767] The system according to claim 1, characterized in that the artificial intelligence module learns user feedback and improves subsequent operation instructions, and collects and analyzes user feedback after the procedure and optimizes the procedure. [Explanation of Symbols]

[1768] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. Full-body close-fitting clothing, The sensor and low-frequency pad are placed inside the garment, A control unit connected to the garment, An external information processing device wirelessly connected to the control unit, The system is characterized in that an artificial intelligence module included in the information processing device visualizes the user's relaxation state based on data acquired by the sensor, generates operation instructions to optimize the relaxation state, and controls the low-frequency pad according to the operation instructions.

2. The system according to claim 1, characterized in that the power supply to the control unit is provided using a battery built into the control unit.

3. The system according to claim 1, characterized in that the artificial intelligence module learns user feedback and improves subsequent operation instructions.

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