A wearable human-computer interaction system and method based on respiratory signal and application thereof

Abstract

The application relates to the technical field of respiratory signals, in particular to a wearable human-computer interaction system and method based on a respiratory signal and application thereof, the system comprising a respiratory signal acquisition module, a signal processing module and an instruction generation module; the respiratory signal acquisition module comprises a head-mounted double-channel respiratory detection device provided with a mouth-nose double-channel and a high-sensitivity humidity sensor of silk; the respiratory signal acquisition module respectively collects respiratory data of a mouth and a nose of a user, and converts gas humidity in the respiratory data into a capacitance signal; the signal processing module comprises a respiratory signal denoising unit, a capacitance-digital conversion chip and a Bluetooth sending chip; the instruction generation module comprises a feature extraction unit, a respiratory pattern recognition unit and a control instruction generation unit. The human-computer interaction system provided by the application is suitable for the fields of medical health, life assistance of physiological defect groups, entertainment games, intelligent wearable devices and the like, and has the advantages of convenience, universality, high precision and expansibility and the like.

Description

Technical Field

[0001] This application relates to the field of human-computer interaction technology, and in particular to a wearable human-computer interaction system, method and application based on respiratory signals. Background Technology

[0002] Traditional human-computer interaction methods mainly rely on hand operations (such as mouse, keyboard, and touchscreen) or voice control, which have significant limitations in certain special scenarios (such as medical rehabilitation). For example, people with physical disabilities (such as aphasic patients and patients with total paralysis) cannot communicate effectively through traditional methods; in special scenarios, the need for discreet operation limits the use of traditional interaction methods. In recent years, the development of wearable devices has provided new possibilities for human-computer interaction, but existing technologies are mostly focused on monitoring physiological signals such as heart rate and movement, lacking in-depth utilization of respiratory signals. Summary of the Invention

[0003] This application provides a wearable human-computer interaction system, method, and application based on respiratory signals. By developing a lightweight and convenient wearable respiratory sensor, the respiratory humidity signal is converted into a high-resolution analog signal, and a digital signal is output through an intelligent algorithm. This realizes a new mode of human-computer interaction based on respiratory signals, which is applicable to multiple fields such as medical health, life assistance for people with physical disabilities, military missions, entertainment games, and smart wearable devices. It can achieve efficient and convenient human-computer interaction using respiratory signals and has broad application prospects.

[0004] To address the aforementioned technical problems, in a first aspect, embodiments of this application provide a wearable human-computer interaction system based on respiratory signals, comprising: a respiratory signal acquisition module, a signal processing module, and an instruction generation module connected in sequence; wherein, the respiratory signal acquisition module includes a head-mounted dual-channel respiratory detection device; the head-mounted dual-channel respiratory detection device is equipped with a mouth-nose dual-channel and a silk high-sensitivity humidity sensor; the respiratory signal acquisition module acquires respiratory data from the user's mouth and nose respectively through the mouth-nose dual-channel and the silk high-sensitivity humidity sensor, and converts the gas humidity in the respiratory data into a capacitance signal; the signal processing module includes a respiratory signal denoising unit, a capacitance-to-digital converter chip, and a Bluetooth transmitter connected in sequence. The chip; the signal processing module denoises the capacitive signal acquired by the respiratory signal acquisition module through the respiratory signal denoising unit, converts the denoised capacitive signal into a digital signal through the capacitance-to-digital converter chip, and transmits the digital signal to the computer terminal through the Bluetooth transmitting chip; the instruction generation module includes a feature extraction unit, a respiratory pattern recognition unit, and a control instruction generation unit; the instruction generation module is used to extract respiratory signal feature values ​​through the feature extraction unit based on the digital signal output by the signal processing module, and to identify different respiratory patterns through the respiratory pattern recognition unit; and to compile an instruction set based on the respiratory signal feature values ​​through the control instruction generation unit, and then send the instruction set to the application software.

[0005] In some exemplary embodiments, the mouth and nose dual channels of the head-mounted dual-channel breathing detection device are connected to the silk high-sensitivity humidity sensor via a circuit board; the mouth and nose dual channels are used to capture breathing signals from the mouth and nose respectively; the silk high-sensitivity humidity sensor can accurately sense minute humidity changes during mouth breathing and nasal breathing, and convert humidity changes into changes in capacitance values.

[0006] In some exemplary embodiments, the respiratory signal acquisition module and the signal processing module are connected by wires; the signal processing module and the instruction generation module are connected via Bluetooth; and the instruction generation module and the application software are connected via memory.

[0007] In some exemplary embodiments, the breathing signal denoising unit is connected to the capacitive-to-digital converter chip via a circuit; the capacitive-to-digital converter chip is connected to the Bluetooth transmitting chip via a circuit.

[0008] In some exemplary embodiments, the respiratory signal denoising unit is used to remove ambient humidity and other interferences, and to denoise the capacitive signal acquired by the respiratory signal acquisition module.

[0009] In some exemplary embodiments, the feature extraction unit of the instruction generation module uses an intelligent algorithm to classify and extract features from the respiratory signals, and the respiratory pattern recognition unit identifies different respiratory patterns; the control instruction generation unit supports user-defined correspondence between respiratory patterns and instructions, and can generate corresponding control instructions according to different application scenarios.

[0010] In some exemplary embodiments, the intelligent algorithm includes deep learning and support vector machines; different breathing modes include deep breathing, shallow breathing, fast breathing, and slow breathing; control commands include switching devices on and off, breathing training, and breathing control mini-games.

[0011] Secondly, this application also provides a wearable human-computer interaction method based on respiratory signals, which interacts with the wearable human-computer interaction system based on respiratory signals described in the above embodiments. The method includes the following steps: First, a respiratory signal acquisition module is worn around the user's mouth and nose. The respiratory signal acquisition module collects respiratory data from the user's mouth and nose, and then obtains capacitance changes based on the changes in humidity at the mouth and nose. Then, a signal processing module filters the capacitance values ​​output by the respiratory signal acquisition module for noise and converts them into digital signals. The digital signals are then sent to a computer terminal via Bluetooth. Next, an instruction generation module classifies and extracts features from the digital signals output by the signal processing module to identify different breathing patterns. Different breathing patterns include deep breathing, shallow breathing, fast breathing, and slow breathing. The instruction generation module supports user-defined correspondence between breathing patterns and instructions and can generate corresponding control instructions according to different application scenarios. The control instructions include switching devices on and off, breathing training, and breathing control mini-games. Finally, the respiratory signal feature values ​​extracted by the instruction generation module are sent to the application software to control the target.

[0012] Thirdly, this application also provides an application of the wearable human-computer interaction system based on respiratory signals described in the above embodiments in the fields of medical and health care, entertainment and games, and smart wearable devices.

[0013] In some exemplary embodiments, wearable human-computer interaction systems based on respiratory signals are applied to respiratory health monitoring, feedback-based breathing training, and interactive breathing training experience games.

[0014] The technical solution provided in this application has at least the following advantages: This application provides a wearable human-computer interaction system, method, and application based on respiratory signals. The wearable human-computer interaction system includes: a respiratory signal acquisition module, a signal processing module, and a command generation module connected in sequence. The respiratory signal acquisition module includes a head-mounted dual-channel respiratory detection device. The head-mounted dual-channel respiratory detection device is equipped with a mouth-nose dual-channel sensor and a silk high-sensitivity humidity sensor. The respiratory signal acquisition module acquires respiratory data from the user's mouth and nose through the mouth-nose dual-channel sensor and the silk high-sensitivity humidity sensor, respectively, and converts the gas humidity in the respiratory data into a capacitance signal. The signal processing module includes a respiratory signal denoising unit, a capacitance-to-digital converter chip, and a Bluetooth transmitter connected in sequence. The chip; the signal processing module denoises the capacitive signal acquired by the respiratory signal acquisition module through the respiratory signal denoising unit, converts the denoised capacitive signal into a digital signal through the capacitance-to-digital converter chip, and transmits the digital signal to the computer terminal through the Bluetooth transmitting chip; the instruction generation module includes a feature extraction unit, a respiratory pattern recognition unit, and a control instruction generation unit; the instruction generation module is used to extract respiratory signal feature values ​​through the feature extraction unit based on the digital signal output by the signal processing module, and to identify different respiratory patterns through the respiratory pattern recognition unit; and to compile an instruction set based on the respiratory signal feature values ​​through the control instruction generation unit, and then send the instruction set to the application software.

[0015] This application provides a wearable human-computer interaction system, method, and application based on respiratory signals. It employs a high-sensitivity silk humidity sensor, whose capacitance changes according to variations in ambient humidity. When a user breathes, the humidity of the airflow near the mouth and nose changes, and the sensor detects these minute humidity changes to capture respiratory signals in real time. The system uses a dual-channel design to capture respiratory signals from both the mouth and nose. Through differential data processing, the system can generate a richer set of instructions, enhancing the flexibility and diversity of interaction. The dual-channel design not only enhances the system's sensitivity but also provides users with more interactive possibilities, such as enabling complex control commands through coordinated mouth and nose breathing. This wearable human-computer interaction system based on respiratory signals is applied to respiratory health monitoring, feedback-based respiratory training, and interactive respiratory training games, aiming to build a comprehensive and personalized respiratory health management system for users. The product relies on a self-developed high-sensitivity humidity sensor, combined with advanced wireless communication and intelligent algorithm technology, to achieve accurate and long-term monitoring of respiratory status and transform the monitoring data into intuitive and easy-to-understand visual information, laying a solid data foundation for users' respiratory health management. Meanwhile, the innovatively developed breathing training mini-games guide users to conduct scientific breathing training through a fun and interactive training mode, effectively improving the function of respiratory muscles and helping users establish a healthy breathing pattern. Attached Figure Description

[0016] One or more embodiments are illustrated by way of example with reference to the accompanying drawings. These illustrations do not constitute a limitation on the embodiments, and unless otherwise stated, the figures in the drawings are not to be limited by scale.

[0017] Figure 1 This is a schematic diagram of the module structure of a wearable human-computer interaction system based on respiratory signals, provided in an embodiment of this application.

[0018] Figure 2 This is a schematic diagram of the signal processing flow provided in an embodiment of this application.

[0019] Figure 3 This is a schematic diagram of the structure of the respiratory signal acquisition module provided in an embodiment of this application.

[0020] Figure 4 A schematic diagram of the breathing humidity curve of the breathing competition program provided in the embodiments of this application.

[0021] Figure 5 This is a schematic diagram of a breathing training game provided in an embodiment of this application.

[0022] Figure 6 This is a schematic diagram of the side appearance design of the functional integration box provided in an embodiment of this application.

[0023] Figure 7 A schematic diagram of the end face appearance design of the functional integration box provided in the embodiments of this application. Detailed Implementation

[0024] As can be seen from the background technology, current wearable devices usually focus on monitoring physiological signals such as heart rate and exercise, and lack in-depth utilization of respiratory signals.

[0025] To address the aforementioned technical problems, this application provides a wearable human-computer interaction system, method, and application based on respiratory signals. The human-computer interaction system includes: a respiratory signal acquisition module, a signal processing module, and an instruction generation module connected in sequence; wherein the respiratory signal acquisition module includes a head-mounted dual-channel respiratory detection device; the head-mounted dual-channel respiratory detection device is equipped with a mouth-nose dual-channel and a silk high-sensitivity humidity sensor; the respiratory signal acquisition module acquires respiratory data from the user's mouth and nose through the mouth-nose dual-channel and the silk high-sensitivity humidity sensor, respectively, and converts the gas humidity in the respiratory data into a capacitance signal; the signal processing module includes a respiratory signal denoising unit, a capacitance-to-digital converter chip, and an instruction generation module connected in sequence. The system includes a Bluetooth transmitter chip; a signal processing module that denoises the capacitive signal acquired by the respiratory signal acquisition module using a respiratory signal denoising unit, converts the denoised capacitive signal into a digital signal using a capacitance-to-digital converter chip, and transmits the digital signal to the computer terminal via the Bluetooth transmitter chip; and an instruction generation module comprising a feature extraction unit, a respiratory pattern recognition unit, and a control instruction generation unit. The instruction generation module extracts respiratory signal feature values ​​from the digital signal output by the signal processing module using the feature extraction unit, identifies different respiratory patterns using the respiratory pattern recognition unit, and compiles an instruction set based on the respiratory signal feature values ​​using the control instruction generation unit, which then sends the instruction set to the application software.

[0026] This application provides a wearable human-computer interaction system, method, and application based on respiratory signals. By developing a lightweight and convenient wearable respiratory sensor, the respiratory humidity signal is converted into a high-resolution analog signal, and a digital signal is output through an intelligent algorithm. This realizes a new mode of human-computer interaction based on respiratory signals, which is applicable to multiple fields such as medical health, life assistance for people with physical disabilities, military missions, entertainment games, and smart wearable devices. It can achieve efficient and convenient human-computer interaction using respiratory signals and has broad application prospects.

[0027] The embodiments of this application will now be described in detail with reference to the accompanying drawings. However, those skilled in the art will understand that many technical details have been provided in the embodiments of this application to facilitate a better understanding of the application. However, the technical solutions claimed in this application can be implemented even without these technical details and various variations and modifications based on the following embodiments.

[0028] See Figure 1This application provides a wearable human-computer interaction system based on respiratory signals, comprising: a respiratory signal acquisition module, a signal processing module, and a command generation module connected in sequence; wherein, the respiratory signal acquisition module includes a head-mounted dual-channel respiratory detection device; the head-mounted dual-channel respiratory detection device is equipped with a mouth and nose dual-channel and a silk high-sensitivity humidity sensor; the respiratory signal acquisition module acquires respiratory data from the user's mouth and nose through the mouth and nose dual-channel and the silk high-sensitivity humidity sensor respectively, and converts the gas humidity in the respiratory data into a capacitance signal; the signal processing module includes a respiratory signal denoising unit, a capacitance-to-digital converter chip, and a Bluetooth transmission chip connected in sequence; the signal processing module... The module denoises the capacitive signal acquired by the respiratory signal acquisition module through a respiratory signal denoising unit, converts the denoised capacitive signal into a digital signal through a capacitance-to-digital converter chip, and transmits the digital signal to the computer terminal through a Bluetooth transmitter chip. The instruction generation module includes a feature extraction unit, a respiratory pattern recognition unit, and a control instruction generation unit. The instruction generation module is used to extract respiratory signal feature values ​​from the digital signal output by the signal processing module through the feature extraction unit, and to identify different respiratory patterns through the respiratory pattern recognition unit. Based on the respiratory signal feature values, the control instruction generation unit compiles an instruction set, which is then sent to the application software.

[0029] The purpose of this application is to provide a wearable human-computer interaction system based on respiratory signals, which captures the user's respiratory signals and converts them into control commands, providing convenient life assistance for people with physical disabilities, and extending to applications in special tasks, entertainment games, smart wearable devices and other fields.

[0030] This application provides a wearable human-computer interaction system based on respiratory signals, comprising the following components: a respiratory signal acquisition module, a signal processing module, and a command generation module. The respiratory signal acquisition module includes a dual-channel system for both the mouth and nose, and a high-sensitivity humidity sensor made of silk. This high-sensitivity humidity sensor changes its capacitance value according to changes in ambient humidity. When a user breathes, the humidity of the airflow near the mouth and nose changes, and the sensor detects these minute humidity changes to capture the respiratory signal in real time. The signal is then converted to a capacitance value; a capacitance-to-digital converter chip further converts the capacitance value into a digital signal for processing; a Bluetooth transmitter chip transmits the digital signal to a computer terminal via Bluetooth 5.0 technology. Signal processing and feature extraction are then performed; the received digital signal is processed by the signal processing module.

[0031] The respiratory signal acquisition module employs a head-mounted dual-channel respiratory detection device equipped with both oral and nasal channels and a high-sensitivity humidity sensor made of silk. Specifically, "Cloud Breath" is a wearable intelligent respiratory monitoring system that deeply integrates cutting-edge technology and innovative concepts. Combined with a breathing training mini-game, it aims to build a comprehensive and personalized respiratory health management system for users. The product relies on a self-developed high-sensitivity humidity sensor, combined with advanced wireless communication and intelligent algorithm technology, to achieve accurate and long-term monitoring of respiratory status, and transforms the monitoring data into intuitive and easy-to-understand visual information, laying a solid data foundation for users' respiratory health management. Simultaneously, the innovatively developed breathing training mini-game, with its fun and interactive training mode, guides users in scientific breathing training, effectively improving respiratory muscle function and helping users establish healthy breathing habits.

[0032] One of the core technologies of "Cloud Breathing" is its self-developed high-sensitivity humidity sensor. This wearable human-computer interaction system incorporates this high-sensitivity humidity sensor technology. This sensor possesses extremely high sensitivity and response speed, enabling it to accurately detect even minute changes in humidity during breathing. By monitoring the moisture content in the respiratory airflow in real time, it provides a reliable data source for accurate monitoring of breathing status. Simultaneously, the sensor undergoes special packaging and calibration, exhibiting excellent stability and environmental adaptability, maintaining high-precision monitoring performance under varying temperature and humidity conditions.

[0033] Furthermore, this wearable human-computer interaction system employs intelligent algorithms (such as deep learning and support vector machines) to extract features from respiratory signals and identify different breathing patterns (such as deep breathing, shallow breathing, rapid breathing, and slow breathing). The intelligent algorithms integrated with the software are one of the key technologies for realizing the product's powerful functions. This application combines intelligent algorithms with data analysis technology. Based on deep learning and big data analysis, the algorithm can quickly and accurately analyze and process the large amounts of respiratory data collected by sensors. Through in-depth mining of data such as respiratory frequency, intensity, and volume, functions such as respiratory health monitoring are achieved. For example, in respiratory health monitoring, the algorithm can promptly detect abnormal breathing conditions and provide corresponding early warnings through trend analysis of respiratory data; in respiratory training, the algorithm dynamically adjusts the training difficulty and guidance suggestions based on the user's real-time respiratory data to ensure the scientific nature and effectiveness of the training.

[0034] This application utilizes intelligent algorithms to enable the system to perform in-depth analysis of key indicators such as the frequency, intensity, and volume of respiratory signals, ensuring the accuracy of command generation. Finally, command generation and feedback: based on the extracted respiratory feature values, the system maps them to preset control commands (such as switching equipment on / off, breathing training, and breathing-controlled mini-games). Users can customize the mapping between breathing patterns and commands to achieve a personalized interactive experience. Simultaneously, the system is equipped with a user feedback module, providing real-time feedback through vibration, sound, or visual cues to help users adjust their breathing patterns to optimize the interactive effect.

[0035] Furthermore, the wearable human-computer interaction system provided in this application employs advanced wireless communication technology, specifically Bluetooth 5.0, to enable data transmission between the device and terminal devices such as mobile phones and tablets. This wireless communication technology boasts advantages such as high transmission speed, high stability, and low power consumption, ensuring real-time and accurate transmission of respiratory data. Users can view respiratory data, conduct breathing training, and set device parameters anytime, anywhere via the accompanying app, conveniently and quickly managing their respiratory health. Simultaneously, the wireless communication technology also supports remote device upgrades and maintenance, ensuring timely updates to product functionality and performance optimization.

[0036] In some embodiments, the respiratory signal acquisition module is connected to the signal processing module via a wire; the signal processing module is connected to the instruction generation module via Bluetooth; and the instruction generation module is connected to the application software via memory.

[0037] In some embodiments, the oral and nasal dual channels are connected to the silk high-sensitivity humidity sensor via a circuit board. The oral and nasal dual channels are used to capture breathing signals from the mouth and nose, respectively; the silk high-sensitivity humidity sensor can accurately sense minute humidity changes during mouth and nose breathing and convert humidity changes into changes in capacitance.

[0038] Specifically, the respiratory signal acquisition module adopts a dual-channel design, using the difference between oral and nasal breathing data to generate complex control commands, resulting in a richer command set and improved flexibility and diversity of interaction. The system employs a dual-channel design to capture respiratory signals from both the mouth and nose. Through differential data processing, the system can generate a richer command set, enhancing the flexibility and diversity of interaction. This dual-channel design not only enhances the system's sensitivity but also provides users with more interactive possibilities, such as enabling complex control commands through the coordination of oral and nasal breathing.

[0039] In some embodiments, the signal processing module includes a respiratory signal denoising unit, a capacitance-to-digital converter chip, and a Bluetooth transmitter chip; wherein the respiratory signal denoising unit is connected to the capacitance-to-digital converter chip via a circuit; and the capacitance-to-digital converter chip is connected to the Bluetooth transmitter chip via a circuit. A schematic diagram of the signal processing flow is shown below. Figure 2 As shown.

[0040] In some embodiments, the breathing signal denoising unit is used to remove ambient humidity and other interference; the capacitor-to-digital converter chip is used to convert changes in capacitance into digital signals; and the Bluetooth transmitter chip is used to transmit digital signals to a computer terminal.

[0041] In some embodiments, the instruction generation module employs intelligent algorithms to classify and extract features from respiratory signals and identify different breathing patterns; the instruction generation module supports user-defined correspondence between breathing patterns and instructions, and can generate corresponding control instructions according to different application scenarios.

[0042] In some embodiments, the intelligent algorithm includes deep learning and support vector machines; different breathing modes include deep breathing, shallow breathing, fast breathing, and slow breathing; the control commands include switching devices on and off, breathing training, and breathing control mini-games.

[0043] The wearable human-computer interaction system based on respiratory signals provided in this application will be described in detail below through specific embodiments.

[0044] This system includes the following components: wearable respiratory detection devices, such as... Figure 3 As shown, it includes an integrated high-sensitivity humidity sensor made of silk, supports Bluetooth 5.0 communication, and supports multiple wearing methods; breathing training software (Breathing Competition), which runs on the Windows platform and supports breathing waveform analysis and real-time feedback; and a "Jump Jump" game module, developed based on the Unity engine, which supports breathing signals to control character movements and dynamically adjusts the game difficulty.

[0045] This product is designed with user experience in mind. It is compact, lightweight, and comfortable to wear, without adding any extra burden. Adopting an ergonomic design, it offers multiple wearing options to suit user preferences and usage scenarios, ensuring comfort even during extended wear. Whether sleeping, exercising, or engaging in daily activities, users can wear it easily without disrupting their normal lives.

[0046] Respiratory Health Monitoring Example: "Cloud-based Nasal Breathing" can monitor key indicators such as breathing intensity, frequency, and volume in real time and with top-tier accuracy and precision in the market. Whether during daily activities, sleep, or exercise, it continuously and stably tracks and monitors nasal and oral breathing, providing users with comprehensive respiratory health data. Through this data, users can promptly understand their respiratory health status and identify potential respiratory problems, such as abnormal breathing rate or changes in breathing intensity, providing a basis for early disease detection and prevention.

[0047] Feedback-based breathing training example: Based on the user's breathing data and individual needs, a personalized breathing training plan is customized for the user. Through a real-time feedback mechanism, guidance and suggestions are provided to the user during training to help adjust breathing rhythm and depth, ensuring maximum training effectiveness. For example, for users with weak respiratory function, the system will gradually guide them to increase breathing depth and frequency, improving respiratory muscle strength and endurance. In specific operation, the user turns on the breathing detection device, and the device enters standby mode. The user then opens computer settings - Bluetooth - Add Bluetooth or other devices, finds the breathing detection device, and connects to it, ensuring communication and data transmission between the device and the computer. The user wears the breathing detection device, ensuring the sensor is near the mouth and nose for accurate breathing signal acquisition.

[0048] Open the "Breathing Challenge" software on your computer and select the COM port corresponding to the breathing detection device in the "Power Transmission Channel".

[0049] The user clicks the "Breathing Training - Start" button on the software interface, and the device begins collecting breathing signals. The breathing waveform is displayed on the software interface in real time. When the user exhales, the "breathing amplitude" decreases, and when they inhale, the "breathing amplitude" increases. As the user breathes normally, the breathing waveform updates in real time according to changes in breathing frequency, intensity, and volume. The user can also input their breathing waveform through the software, and the system provides training feedback based on the waveform.

[0050] After the breathing training begins, the user clicks the "Breathing Training - End" button on the software interface. The system automatically analyzes the user's breathing waveform data to determine if the breathing rate, intensity, and volume are within the normal range. It then compares the user's breathing waveform data with standard breathing waveform data, generating a score between 0 and 100. A higher score indicates a healthier breathing pattern. The breathing humidity curve in the breathing competition program is shown below. Figure 4 As shown.

[0051] Example of an interactive breathing training game: As a key feature of this application, the breathing training mini-game transforms the tedious breathing training into a fun and interactive experience. Users can choose different training scenarios according to their needs. During the game, the user's breathing directly controls the game character's actions, making the training process fun and challenging. Simultaneously, the game difficulty is dynamically adjusted based on the user's breathing data, maintaining a moderate level of challenge and increasing user engagement and adherence.

[0052] Example of using the "Jump Jump" game: The user turns on the respiratory detection device, which then enters standby mode. The user opens computer settings - Bluetooth - Add Bluetooth or other devices, locates the respiratory detection device, and connects to it, ensuring communication and data transmission between the device and the computer. The user wears the respiratory detection device, ensuring the sensor is near the mouth and nose for accurate respiratory signal collection.

[0053] Once the connection is established, the user opens the "Jump Jump" game software, clicks the "Start Game" button on the game interface, and the game enters the preparation state.

[0054] Users control the game character's movements through rhythmic breathing. When the sensor detects continuous exhalation, the game character begins to accumulate power, with the power bar on the left side of the screen gradually increasing from zero. Upon inhalation, the game character jumps at varying distances depending on the amount of power accumulated. This breathing training exercise is similar to the "Jump Jump" mini-game. Figure 5 As shown.

[0055] Users can control the timing and force of their character's jumps by adjusting their breathing frequency and intensity, based on the distance to the next platform in the game scene, in order to complete the game task. If the character successfully jumps to the next platform, the game will generate a new platform for the user to control the jump with their breathing. If the character fails to jump to the platform, the game will display "Game Over," at which point the user can choose to restart the game or quit the game.

[0056] Although the features and elements of this system are described above in a specific combination, those skilled in the art will understand that each feature or element can be used alone or in any combination with other features and elements.

[0057] The design concept of this application starts from the theme style of mini-games and the magical and futuristic visual elements. Through the strong contrast of black and red tones and the use of technological textures, it gives the components a mysterious and futuristic visual effect. The design not only focuses on visual impact but also attracts the user's attention through unique shapes and detailed processing, creating a cool and immersive experience. At the same time, we have incorporated anti-slip features into the design to ensure a stable grip during operation, balancing aesthetics and practicality, further enhancing the user experience of the product. Figure 6 and Figure 7 As shown.

[0058] The wearable human-computer interaction system based on respiratory signals provided in this application is not only aesthetically pleasing and practical, but also simple and easy to operate. The user interface is concise and intuitive; users can complete device connection, function settings, and data viewing through simple steps. The accompanying application (APP) has a user-friendly interface and a logical function layout, allowing even users unfamiliar with technology products to quickly get started. Furthermore, the APP provides detailed tutorials and guidance to help users better understand and use the product's various functions.

[0059] Moreover, the wearable human-computer interaction system of this application is adaptable to multiple scenarios and has excellent multi-scenario adaptability. It can operate stably and accurately monitor respiratory data in quiet sleep environments, intense exercise scenarios, or busy daily life scenarios. In sleep scenarios, the device's low power consumption design and quiet operation characteristics will not disturb the user's sleep; in exercise scenarios, its stable wearing method and reliable monitoring performance can meet the user's monitoring needs during running, fitness, and other sports activities.

[0060] This application provides a wearable human-computer interaction system based on respiratory signals, which has the advantages of convenience, universality, high precision, and scalability. This application adopts a lightweight wearable design, enabling human-computer interaction without complex operations. Furthermore, this application is applicable to multiple fields such as medical and health care, entertainment games, and smart wearable devices. Simultaneously, this application ensures the accuracy of command recognition through high-resolution signal processing and intelligent algorithms. In addition, this application supports user-defined mapping between breathing patterns and commands, adapting to diverse needs.

[0061] In addition, this application embodiment also provides a wearable human-computer interaction method based on respiratory signals, which interacts with the wearable human-computer interaction system based on respiratory signals described in the above embodiment, including the following steps: First, a respiratory signal acquisition module is worn around the user's mouth and nose, and respiratory data from the user's mouth and nose are collected using the respiratory signal acquisition module. Then, the capacitance value change is obtained based on the humidity value change at the mouth and nose. Next, a signal processing module filters the capacitance value output by the respiratory signal acquisition module for noise and converts it into a digital signal. The digital signal is then sent to a computer terminal via Bluetooth. Next, an instruction generation module classifies and extracts features from the digital signal output by the signal processing module to identify different breathing patterns. Different breathing patterns include deep breathing, shallow breathing, fast breathing, and slow breathing. The instruction generation module supports user-defined correspondence between breathing patterns and instructions and can generate corresponding control instructions according to different application scenarios. The control instructions include switching devices on and off, breathing training, and breathing control mini-games. Finally, the respiratory signal feature values ​​extracted by the instruction generation module are sent to the application software to control the target.

[0062] Specifically, the wearable human-computer interaction system provided in this application is used as follows: ① Device Wearing: Choose the appropriate wearing method according to personal needs and usage scenarios. Adjust the position to ensure that the sensor is near the mouth and nose to accurately collect breathing data, and ensure that the sensor is in close contact with the skin and that data collection is not affected by factors such as clothing friction.

[0063] ② Device Connection: Turn on the device power, and it will automatically enter pairing mode. Open the "Cloud Breath" app on your phone, search for and select the "Cloud Breath" device in the app's device connection interface, and click connect. Once the connection is successful, the app will display the device's connected status.

[0064] ③ Function Usage: After successful connection, real-time breathing data, including respiratory rate, intensity, and volume, can be viewed on the main interface of the app. Clicking the "Start Breathing Training" function will initiate device monitoring of breathing, visualizing respiratory rate and depth. For more engaging breathing training, click "Breathing Training Mini-Game." Once in the game interface, select a training scenario that interests you, such as the "Jump Jump" scenario. Users control the jump of the game piece by rhythmically breathing, exhaling to build up energy and inhaling to release it. During the game, the app will provide real-time feedback and guidance based on the breathing data.

[0065] ④ Data Viewing and Management: On the "Historical Data" page of the app, users can view respiratory monitoring data over a period of time, including daily, weekly, and monthly respiratory data statistical charts, making it easy for users to understand the changing trends of their respiratory health. The app also supports data export, allowing users to export data to Excel or PDF formats for sharing with doctors or for more in-depth analysis.

[0066] Furthermore, this application also provides an application of the wearable human-computer interaction system based on respiratory signals described in the above embodiments in the fields of medical and health care, entertainment and games, and smart wearable devices.

[0067] In some embodiments, wearable human-computer interaction systems based on respiratory signals are applied to respiratory health monitoring, feedback-based breathing training, and interactive breathing training games.

[0068] The application scenario module of the human-computer interaction system in this application includes the following application scenarios: In the medical and health field: for speech expression in patients with aphasia or total paralysis, as well as respiratory monitoring and early warning.

[0069] Entertainment and Gaming: Interactive experiences for enhancing virtual reality (VR) and augmented reality (AR) games.

[0070] Special mission: Used for transmitting tactical information to soldiers.

[0071] Smart wearable devices: used for health monitoring and feedback, as well as exercise management.

[0072] Specifically, in assistive living scenarios, users with mobility impairments can control their wheelchairs to move forward by taking deep breaths and to stop by taking shallow breaths. They can also control smart home devices (such as turning lights on and off and adjusting air conditioning temperatures) by using specific breathing patterns (such as long inhales and short exhales).

[0073] In the medical and health field, communication between aphasic and paralyzed patients: Aphasic or paralyzed patients express themselves through breathing signals. The system converts the breathing signals into electrical signals and then outputs complete sentences through Morse code rules, thus enabling communication with the outside world.

[0074] In the field of assisting patients with respiratory training and recovery, the system provides real-time respiratory feedback for patients with chronic obstructive pulmonary disease (COPD) or those recovering from surgery, helping them master the correct breathing rhythm (such as diaphragmatic breathing). By setting a target breathing pattern (such as deep inhalation and slow exhalation), the system monitors the patient's respiratory status and provides rewarding feedback (such as audio prompts or visual progress bars) to encourage patients to persist in training. In the entertainment and gaming industry, users control the actions of characters or changes in the environment in games through breathing signals, providing a more immersive gaming experience.

[0075] In special mission domains, respiratory signals are used to transmit tactical information or control equipment, especially in scenarios requiring covert operations.

[0076] In the field of smart wearable devices, respiratory signals are integrated into smart wearable devices to monitor the user's breathing rate and depth in real time, providing health monitoring and feedback.

[0077] In sports scenarios, breathing signals are used to optimize exercise rhythm and intensity, helping users better manage their exercise status and improve exercise results.

[0078] In the area of ​​training athletes' breathing capacity, the system provides guidance on high-intensity breathing patterns (such as rapid deep breathing and intermittent breathing). By monitoring athletes' breathing rate and depth in real time, the system optimizes training plans to help athletes improve their lung capacity and respiratory control.

[0079] Based on the above technical solutions, this application provides a wearable human-computer interaction system, method, and application based on respiratory signals. The wearable human-computer interaction system includes: a respiratory signal acquisition module, a signal processing module, and a command generation module connected in sequence; wherein, the respiratory signal acquisition module includes a head-mounted dual-channel respiratory detection device; the head-mounted dual-channel respiratory detection device is equipped with a mouth-nose dual-channel and a silk high-sensitivity humidity sensor; the respiratory signal acquisition module acquires respiratory data from the user's mouth and nose through the mouth-nose dual-channel and the silk high-sensitivity humidity sensor, respectively, and converts the gas humidity in the respiratory data into a capacitance signal; the signal processing module includes a respiratory signal denoising unit, a capacitance-to-digital converter chip, and a command generation module connected in sequence. The system includes a Bluetooth transmitter chip; a signal processing module that denoises the capacitive signal acquired by the respiratory signal acquisition module using a respiratory signal denoising unit, converts the denoised capacitive signal into a digital signal using a capacitance-to-digital converter chip, and transmits the digital signal to the computer terminal via the Bluetooth transmitter chip; and an instruction generation module comprising a feature extraction unit, a respiratory pattern recognition unit, and a control instruction generation unit. The instruction generation module extracts respiratory signal feature values ​​from the digital signal output by the signal processing module using the feature extraction unit, identifies different respiratory patterns using the respiratory pattern recognition unit, and compiles an instruction set based on the respiratory signal feature values ​​using the control instruction generation unit, which then sends the instruction set to the application software.

[0080] This application provides a wearable human-computer interaction system, method, and application based on respiratory signals. It employs a high-sensitivity silk humidity sensor, whose capacitance changes according to variations in ambient humidity. When a user breathes, the humidity of the airflow near the mouth and nose changes, and the sensor detects these minute humidity changes to capture respiratory signals in real time. The system uses a dual-channel design to capture respiratory signals from both the mouth and nose. Through differential data processing, the system can generate a richer set of instructions, enhancing the flexibility and diversity of interaction. The dual-channel design not only enhances the system's sensitivity but also provides users with more interactive possibilities, such as enabling complex control commands through coordinated mouth and nose breathing. This wearable human-computer interaction system based on respiratory signals is applied to respiratory health monitoring, feedback-based respiratory training, and interactive respiratory training games, aiming to build a comprehensive and personalized respiratory health management system for users. The product relies on a self-developed high-sensitivity humidity sensor, combined with advanced wireless communication and intelligent algorithm technology, to achieve accurate and long-term monitoring of respiratory status and transform the monitoring data into intuitive and easy-to-understand visual information, laying a solid data foundation for users' respiratory health management. Meanwhile, the innovatively developed breathing training mini-games guide users to conduct scientific breathing training through a fun and interactive training mode, effectively improving the function of respiratory muscles and helping users establish a healthy breathing pattern.

[0081] Those skilled in the art will understand that the above-described embodiments are specific examples of implementing this application, and in practical applications, various changes in form and detail may be made without departing from the spirit and scope of this application. Any person skilled in the art can make their own modifications and alterations without departing from the spirit and scope of this application; therefore, the scope of protection of this application should be determined by the scope defined in the claims.

Claims

1. A wearable human-computer interaction system based on respiratory signals, characterized in that, include: The respiratory signal acquisition module, signal processing module, and command generation module are connected in sequence; among them, The respiratory signal acquisition module includes a head-mounted dual-channel respiratory detection device; The head-mounted dual-channel breathing detection device is equipped with a mouth and nose dual-channel and a silk high-sensitivity humidity sensor; the breathing signal acquisition module collects the user's breathing data from the mouth and nose through the mouth and nose dual-channel and the silk high-sensitivity humidity sensor, and converts the gas humidity in the breathing data into a capacitance signal; The signal processing module includes a respiratory signal denoising unit, a capacitance-to-digital converter chip, and a Bluetooth transmitter chip connected in sequence. The signal processing module denoises the capacitance signal acquired by the respiratory signal acquisition module through the respiratory signal denoising unit, converts the denoised capacitance signal into a digital signal through the capacitance-to-digital converter chip, and transmits the digital signal to a computer terminal through the Bluetooth transmitter chip. The instruction generation module includes a feature extraction unit, a breathing pattern recognition unit, and a control instruction generation unit. The instruction generation module is used to extract breathing signal feature values ​​through the feature extraction unit and identify different breathing patterns through the breathing pattern recognition unit based on the digital signal output by the signal processing module; and to compile an instruction set based on the breathing signal feature values ​​through the control instruction generation unit, and then send the instruction set to the application software.

2. The wearable human-computer interaction system based on respiratory signals according to claim 1, characterized in that, The head-mounted dual-channel breathing detection device is connected to the oral and nasal channels and the silk high-sensitivity humidity sensor via a circuit board. The oral and nasal dual channels are used to capture breathing signals from the mouth and nose, respectively; the silk high-sensitivity humidity sensor can accurately sense minute humidity changes during mouth and nose breathing and convert humidity changes into changes in capacitance.

3. The wearable human-computer interaction system based on respiratory signals according to claim 1, characterized in that, The respiratory signal acquisition module and the signal processing module are connected by wires; the signal processing module and the instruction generation module are connected via Bluetooth; the instruction generation module and the application software are connected via memory.

4. The wearable human-computer interaction system based on respiratory signals according to claim 1, characterized in that, The respiratory signal denoising unit is connected to the capacitor-to-digital converter chip via a circuit. The capacitor-to-digital converter chip and the Bluetooth transmitter chip are connected by a circuit.

5. The wearable human-computer interaction system based on respiratory signals according to claim 1, characterized in that, The respiratory signal denoising unit is used to remove external environmental humidity and other interference, and to denoise the capacitive signal acquired by the respiratory signal acquisition module.

6. The wearable human-computer interaction system based on respiratory signals according to claim 1, characterized in that, The feature extraction unit of the instruction generation module uses an intelligent algorithm to classify and extract features from respiratory signals, and the respiratory pattern recognition unit identifies different respiratory patterns. The control instruction generation unit supports user-defined correspondence between respiratory patterns and instructions, and can generate corresponding control instructions according to different application scenarios.

7. The wearable human-computer interaction system based on respiratory signals according to claim 1, characterized in that, The intelligent algorithm includes deep learning and support vector machine; the different breathing modes include deep breathing, shallow breathing, fast breathing and slow breathing; the control commands include switching devices on and off, breathing training and breathing control mini-games.

8. A wearable human-computer interaction method based on respiratory signals, wherein the interaction is based on the wearable human-computer interaction system based on respiratory signals as described in any one of claims 1 to 7, characterized in that, Includes the following steps: The breathing signal acquisition module is worn on the user's mouth and nose. The breathing signal acquisition module is used to collect breathing data from the user's mouth and nose. Then, the change in capacitance value is obtained based on the change in humidity value at the mouth and nose. The signal processing module first filters the capacitance value output by the respiratory signal acquisition module to remove noise, then converts it into a digital signal, and then sends the digital signal to the computer terminal via Bluetooth. The instruction generation module classifies and extracts features from the digital signals output by the signal processing module to identify different breathing patterns. These different breathing patterns include deep breathing, shallow breathing, fast breathing, and slow breathing. The instruction generation module supports user-defined correspondence between breathing patterns and instructions and can generate corresponding control instructions according to different application scenarios. These control instructions include switching devices on and off, breathing training, and breathing control mini-games. The respiratory signal feature values ​​extracted by the instruction generation module are sent to the application software to control the target.

9. The application of a wearable human-computer interaction system based on respiratory signals as described in any one of claims 1 to 7 in the fields of medical and health care, entertainment and games, and smart wearable devices.

10. The application according to claim 9, characterized in that, The wearable human-computer interaction system based on respiratory signals is applied to respiratory health monitoring, feedback-based breathing training, and interactive breathing training games.

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