A breathing monitoring method, device, wearable device and storage medium

Abstract

The present disclosure relates to a breathing monitoring method, apparatus, wearable device, and storage medium. The method includes: obtaining the state of a target object, where the state of the target object includes a first state and a second state; determining a sampling frequency according to the state of the target object; and collecting first breathing data of the target object based on the determined sampling frequency. The breathing monitoring method of the present disclosure collects the breathing data of the target object in different states through a wearable device, making the collected data more accurate, and generating an analysis result after processing the data, which can provide guidance for the breathing control of the target object.

Description

Technical Field

[0001] The present disclosure relates to the technical field of intelligent devices, and particularly to a breathing monitoring method, device, wearable device and storage medium. Background Art

[0002] Intelligent devices are the product of the combination of traditional electrical devices and computer technology, data processing technology, control theory, sensor technology, network communication technology, power electronics technology, etc. In people's daily lives, intelligent devices have been more and more widely used.

[0003] In the technology of intelligent devices, especially intelligent glasses, the existing applications are relatively single. The nose bridge of the glasses only plays the role of supporting and fixing the glasses, and does not make full use of the favorable conditions of the contact point between the glasses frame and the nose wing. For the technology of using intelligent glasses for breathing monitoring, the existing technology cannot provide further guidance and does not form a good health interaction plan with users. Summary of the Invention

[0004] The present disclosure provides a breathing monitoring method, device, wearable device and storage medium to realize real-time monitoring of the breathing condition of a target object.

[0005] According to one aspect of the embodiments of the present disclosure, a breathing monitoring method is provided, including:

[0006] Obtain the state of the target object, where the state of the target object includes a first state and a second state;

[0007] Determine the sampling frequency according to the state of the target object;

[0008] Collect first breathing data of the target object based on the determined sampling frequency.

[0009] In a possible implementation manner, obtaining the state of the target object includes:

[0010] Obtain a first input, and determine the state of the target object based on the first input.

[0011] In a possible implementation manner, obtaining the state of the target object includes:

[0012] Obtain second breathing data of the target object;

[0013] If the second breathing data of the target object is within a set range, determine that the state of the target object is the first state, otherwise determine that the state of the target object is the second state.

[0014] In a possible implementation manner, collecting first breathing data of the target object based on the determined sampling frequency includes:

[0015] Collect first respiratory data of the target object using one or more sensors at the sampling frequency.

[0016] In a possible implementation, the one or more sensors include one or more of a gas flow sensor, a blood oxygen sensor, a pressure sensor, a piezoelectric film sensor, a humidity sensor, a temperature sensor, and a magnetic sensor.

[0017] In a possible implementation, the first respiratory data includes one or more of a respiratory rate, a respiratory amplitude, an inhalation / exhalation humidity, and an inhalation / exhalation temperature.

[0018] In a possible implementation, the method further includes:

[0019] Generate an analysis result based on the first respiratory data, where the analysis result is used to characterize the first respiratory state of the target object.

[0020] In a possible implementation, the method further includes:

[0021] Obtain third respiratory data of the target object according to the state of the target object, where the third respiratory data is historical respiratory data of the target object in the same state;

[0022] Determine a second respiratory state of the target object based on the first respiratory data and the third respiratory data.

[0023] In a possible implementation, the method further includes:

[0024] Obtain fourth respiratory data of the target object according to the state of the target object, where the fourth respiratory data is historical respiratory data of the target object in the second state;

[0025] Determine a third respiratory state of the target object based on the first respiratory data and the fourth respiratory data.

[0026] In a possible implementation, when the second respiratory state is abnormal, notify the target object.

[0027] In a possible implementation, when the third respiratory state is abnormal, notify the target object.

[0028] According to another aspect of the present disclosure, there is provided a respiratory monitoring device, including:

[0029] A state acquisition module, configured to acquire the state of a target object, where the state of the target object includes a first state and a second state;

[0030] A sampling frequency determination module, configured to determine a sampling frequency according to the state of the target object;

[0031] A first respiratory data acquisition module, configured to acquire first respiratory data of the target object based on the determined sampling frequency.

[0032] According to another aspect of the present disclosure, there is provided a wearable device, which includes:

[0033] At least one processor; and

[0034] A memory communicatively connected to the at least one processor; wherein,

[0035] The memory stores a computer program executable by the at least one processor, and when the computer program is executed by the at least one processor, the at least one processor is enabled to execute the respiratory monitoring method according to any embodiment of the present disclosure.

[0036] In a possible implementation, the wearable device further includes:

[0037] A display component, the display component being coupled to the at least one processor, and the display component being configured to:

[0038] Display an analysis result generated according to the first respiratory data.

[0039] In a possible implementation, the wearable device further includes:

[0040] One or more sensors, the one or more sensors being coupled to the at least one processor, and the one or more sensors being configured to:

[0041] Acquire first respiratory data of the target object based on the determined sampling frequency.

[0042] In a possible implementation, the one or more sensors are disposed on a first part of the wearable device, and when the wearable device is worn by the target object, the first part is close to the respiratory part of the target object.

[0043] According to another aspect of the present disclosure, there is provided a computer-readable storage medium, which stores computer instructions for enabling a processor to implement the respiratory monitoring method according to any embodiment of the present disclosure when executed.

[0044] An embodiment of the present disclosure discloses a breathing monitoring method, including: obtaining the state of a target object, where the state of the target object includes a first state and a second state; determining a sampling frequency according to the state of the target object; and collecting first breathing data of the target object based on the determined sampling frequency. The breathing monitoring method disclosed in the present disclosure collects breathing data of the target object in different states through a wearable device, making the collected data more accurate, and generating an analysis result after processing the data, which can provide guidance for the breathing control of the target object.

[0045] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present disclosure, nor is it used to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present disclosure. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0047] Figure 1 is a schematic structural diagram of a wearable device provided in an embodiment of the present disclosure;

[0048] Figure 2 is a flowchart of a breathing monitoring method provided in an embodiment of the present disclosure;

[0049] Figure 3 is a flowchart of another breathing monitoring method provided in an embodiment of the present disclosure;

[0050] Figure 4 is a schematic diagram of a sensor setting method provided in an embodiment of the present disclosure;

[0051] Figure 5 is a schematic structural diagram of a breathing monitoring device provided in an embodiment of the present disclosure;

[0052] Figure 6 is a schematic structural diagram of a wearable device for implementing the breathing monitoring method in an embodiment of the present disclosure. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0053] To enable those skilled in the art to better understand the present disclosure solution, the following will clearly and completely describe the technical solutions in the embodiments of the present disclosure in conjunction with the accompanying drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only a part of the embodiments of the present disclosure, rather than all the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present disclosure.

[0054] It should be noted that the terms "first", "second", etc. in the specification and claims of the present disclosure and the above-mentioned accompanying drawings are used to distinguish similar objects, and do not necessarily need to be used to describe a specific order or sequence. It should be understood that such used data can be interchanged under appropriate circumstances so that the embodiments of the present disclosure described here can be implemented in an order other than those illustrated or described here. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products, or devices.

[0055] The breathing monitoring method provided by the embodiments of the present disclosure can be applied to wearable devices. Among them, the above-mentioned wearable devices can be devices such as AR glasses or smart helmets; the embodiments of the present disclosure do not impose any restrictions on the specific types of intelligent wearable devices.

[0056] Exemplarily, Figure 1 is a schematic structural diagram of a wearable device provided by an embodiment of the present disclosure. As Figure 1 shown, the wearable device 100 may include a processor 110, an internal memory 121, a universal serial bus (USB) interface 130, a charging management module 140, a power management module 141, a battery 142, an antenna 1, a wireless communication module 160, a sensor module 180, a button 190, a light emitting diode (LED) lamp 191, a camera 193, a display component 194, and an optical engine 195, etc.; among them, the sensor module 180 includes a touch sensor 180K. Although not shown, the sensor module may further include a gas flow sensor, a blood oxygen sensor, a pressure sensor, a piezoelectric thin film sensor, a humidity sensor, a temperature sensor, and a magnetic sensor, etc.; the optical engine 195 includes a lens and a display screen.

[0057] It can be understood that the structure illustrated in the embodiments of the present disclosure does not constitute a specific limitation on the wearable device 100. In other embodiments of the present disclosure, the wearable device 100 may include more or fewer components than shown in the figures, or combine certain components, or split certain components, or have different component arrangements. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

[0058] The processor 110 may include one or more processing units. For example, the processor 110 may include an application processor (AP), a modem processor, a graphics processing unit (GPU), an image signal processor (ISP), a controller, a video codec, a digital signal processor (DSP), a baseband processor, and / or a neural-network processing unit (NPU), etc. Among them, different processing units may be independent devices or integrated in one or more processors.

[0059] The controller may generate operation control signals according to the instruction operation code and timing signals to complete the control of fetching and executing instructions.

[0060] A memory may also be provided in the processor 110 for storing instructions and data. In some embodiments, the memory in the processor 110 is a cache memory. This memory may store the instructions or data that the processor 110 has just used or recycled. If the processor 110 needs to use the instruction or data again, it can be directly called from the memory. This avoids repeated accesses, reduces the waiting time of the processor 110, and thus improves the efficiency of the system.

[0061] In some embodiments, the processor 110 may include one or more interfaces. The interfaces may include an inter-integrated circuit (I2C) interface, a universal asynchronous receiver / transmitter (UART) interface, a mobile industry processor interface (MIPI), a general-purpose input / output (GPIO) interface, a subscriber identity module (SIM) interface, and / or a universal serial bus (USB) interface, etc.

[0062] The I2C interface is a bidirectional synchronous serial bus that includes a serial data line (SDA) and a serial clock line (DCL). In some embodiments, the processor 110 may include multiple groups of I2C buses. The processor 110 may be respectively coupled to the touch sensor 180K, the charger, the flash, the camera 193, etc. through different I2C bus interfaces. For example: The processor 110 may be coupled to the sensor module 180 through the I2C interface, enabling the processor 110 and the sensor module 180 to communicate through the I2C bus interface to implement the touch function of the wearable device 100.

[0063] The UART interface is a universal serial data bus for asynchronous communication. This bus can be a bidirectional communication bus. It converts the data to be transmitted between serial communication and parallel communication. In some embodiments, the UART interface is typically used to connect the processor 110 to the wireless communication module 160. For example: The processor 110 communicates with the Bluetooth module in the wireless communication module 160 through the UART interface to implement the Bluetooth function.

[0064] The MIPI interface can be used to connect the processor 110 to peripheral devices such as the display component 194 and the camera 193. The MIPI interface includes a camera serial interface (CSI), a display serial interface (DSI), etc. In some embodiments, the processor 110 and the camera 193 communicate through the CSI interface to implement the shooting function of the wearable device 100. The processor 110 and the display component 194 communicate through the DSI interface to implement the display function of the wearable device 100.

[0065] The GPIO interface can be configured by software. The GPIO interface can be configured as a control signal or a data signal. In some embodiments, the GPIO interface can be used to connect the processor 110 to the camera 193, the display component 194, the wireless communication module 160, the sensor module 180, etc. The GPIO interface can also be configured as an I2C interface, an I2S interface, a UART interface, a MIPI interface, etc.

[0066] The USB interface 130 is an interface that conforms to the USB standard specification, and can specifically be a Mini USB interface, a Micro USB interface, a USB Type C interface, etc. The USB interface 130 can be used to connect a charger to charge the wearable device 100, and can also be used to transfer data between the wearable device 100 and peripheral devices. It can also be used to connect headphones to play audio through the headphones. This interface can also be used to connect other smart wearable devices, such as AR devices, etc.

[0067] It can be understood that the interface connection relationships between the modules illustrated in the embodiments of the present disclosure are only illustrative descriptions and do not constitute a structural limitation on the wearable device 100. In other embodiments of the present disclosure, the wearable device 100 can also adopt different interface connection methods in the above embodiments, or a combination of multiple interface connection methods.

[0068] The charging management module 140 is used to receive a charging input from a charger. Among them, the charger can be a wireless charger or a wired charger. In some embodiments of wired charging, the charging management module 140 can receive the charging input from a wired charger through the USB interface 130. In some embodiments of wireless charging, the charging management module 140 can receive the wireless charging input through the wireless charging coil of the smart wearable device 100. While charging the battery 142, the charging management module 140 can also supply power to the smart wearable device 100 through the power management module 141.

[0069] The power management module 141 is used to connect the battery 142, the charging management module 140, and the processor 110. The power management module 141 receives the inputs from the battery 142 and / or the charging management module 140 and supplies power to the processor 110, the internal memory 121, the display component 194, the camera 193, the wireless communication module 160, etc. The power management module 141 can also be used to monitor parameters such as the battery capacity, the number of battery cycles, and the battery health status (leakage, impedance). In some other embodiments, the power management module 141 can also be disposed in the processor 110. In other embodiments, the power management module 141 and the charging management module 140 can also be disposed in the same device.

[0070] The wireless communication function of the wearable device 100 can be implemented by the antenna 1, the wireless communication module 160, the modulation and demodulation processor, the baseband processor, etc.

[0071] The antenna 1 is used to transmit and receive electromagnetic wave signals. Each antenna in the wearable device 100 can be used to cover a single or multiple communication frequency bands. Different antennas can also be multiplexed to improve the utilization rate of the antennas. For example, the antenna 1 can be multiplexed as a diversity antenna for a wireless local area network. In some other embodiments, the antenna can be used in combination with a tuning switch.

[0072] The wireless communication module 160 can provide solutions for wireless communications applied to the wearable device 100, including wireless local area networks (WLANs) (such as wireless fidelity (Wi-Fi) networks), Bluetooth (BT), global navigation satellite systems (GNSSs), frequency modulation (FM), near field communication (NFC), infrared technology (IR), etc. The wireless communication module 160 can be one or more devices integrating at least one communication processing module. The wireless communication module 160 receives electromagnetic waves via the antenna 2, performs frequency modulation and filtering processing on the electromagnetic wave signals, and sends the processed signals to the processor 110. The wireless communication module 160 can also receive the signals to be sent from the processor 110, perform frequency modulation and amplification on them, and convert them into electromagnetic waves through the antenna 1 for radiation.

[0073] In some embodiments, the antenna 1 of the wearable device 100 is coupled to the wireless communication module 160, so that the wearable device 100 can communicate with the network and other devices through wireless communication technologies. The wireless communication technologies may include global system for mobile communications (GSM), general packet radio service (GPRS), code division multiple access (CDMA), wideband code division multiple access (WCDMA), time-division code division multiple access (TD-SCDMA), long term evolution (LTE), BT, GNSS, WLAN, NFC, FM, and / or IR technology, etc. The GNSS may include global positioning system (GPS), global navigation satellite system (GLONASS), beidou navigation satellite system (BDS), quasi-zenith satellite system (QZSS), and / or satellite based augmentation systems (SBAS).

[0074] The wearable device 100 implements the display function through the GPU, the display component 194, and the application processor, etc. The GPU is a microprocessor for image processing, and is connected to the display component 194 and the application processor. The GPU is used to perform mathematical and geometric calculations for graphics rendering. The processor 110 may include one or more GPUs, which execute program instructions to generate or change display information.

[0075] The display component 194 is used to display images, videos, etc. The display component 194 may include a display lens or a display mask, and the display component 194 may also include a display screen. The display lens or the display mask may be an optical waveguide, a free-form prism, or free space, etc.; the display lens or the display mask is the propagation path of the imaging optical path and can transmit the virtual image to the human eye. In order for the AR glasses to see both the real and virtual images simultaneously, an optical waveguide can be used to transmit the virtual image light into the human eye. For example, the display component 194 may also be used to display the analysis result generated according to the first respiratory data.

[0076] The above display screen may be a display panel, and the display panel may adopt a liquid crystal display (LCD), an organic light-emitting diode (OLED), an active matrix organic light-emitting diode or an active-matrix organic light-emitting diode (AMOLED), a flexible light-emitting diode (FLED), a MiniLED, a MicroLED, a Micro-oLED, a quantum dot light-emitting diode (QLED), etc.

[0077] In some embodiments, the wearable device 100 may include one or N display components 194, where N is a positive integer greater than 1.

[0078] The wearable device 100 can implement a shooting function through an ISP, a camera 193, a video codec, a GPU, a display component 194, an application processor, etc.

[0079] The ISP is used to process the data fed back by the camera 193. For example, when taking a photo, the shutter is opened, and light passes through the lens and is transmitted to the camera sensor. The light signal is converted into an electrical signal, and the camera sensor transmits the electrical signal to the ISP for processing and converts it into an image visible to the naked eye. The ISP can also optimize the noise, brightness, and skin color of the image through algorithms. The ISP can also optimize parameters such as the exposure and color temperature of the shooting scene. In some embodiments, the ISP may be provided in the camera 193.

[0080] The camera 193 is used to capture still images or videos. An object generates an optical image through the lens and projects it onto the sensor. The sensor may be a charge-coupled device (CCD) or a complementary metal-oxide-semiconductor (CMOS) phototransistor. The sensor converts the light signal into an electrical signal, and then transmits the electrical signal to the ISP to convert it into a digital image signal. The ISP outputs the digital image signal to the DSP for processing. The DSP converts the digital image signal into an image signal in standard RGB, YUV, etc. formats. In some embodiments, the wearable device 100 may include one or N cameras 193, where N is a positive integer greater than 1. In the embodiments of the present disclosure, the camera 193 may include at least one infrared camera.

[0081] The digital signal processor is used to process digital signals. In addition to processing digital image signals, it can also process other digital signals. For example, when the wearable device 100 selects a frequency point, the digital signal processor is used to perform Fourier transform on the frequency point energy, etc.

[0082] The video codec is used to compress or decompress digital videos. The wearable device 100 can support one or more video codecs. In this way, the wearable device 100 can play or record videos in multiple coding formats, such as: Moving Picture Experts Group (MPEG) 1, MPEG2, MPEG3, MPEG4, etc.

[0083] The NPU is a neural-network (NN) computing processor. By learning from the biological neural network structure, such as learning from the transmission mode between human brain neurons, it can quickly process the input information and can also continuously self-learn. Through the NPU, applications such as intelligent cognition of the wearable device 100 can be realized, such as: image recognition, face recognition, speech recognition, text understanding, etc.

[0084] The internal memory 121 can be used to store computer-executable program codes, and the executable program codes include instructions. The internal memory 121 can include a program storage area and a data storage area. Among them, the program storage area can store the operating system, application programs required for at least one function (such as the sound playback function, the image playback function, etc.). The data storage area can store the data created during the use of the wearable device 100 (such as audio data, phone book, etc.). In addition, the internal memory 121 can include high-speed random access memory, and can also include non-volatile memory, such as at least one disk storage device, flash memory device, universal flash storage (UFS), etc. The processor 110 executes various functional applications and data processing of the intelligent wearable device 100 by running the instructions stored in the internal memory 121, and / or the instructions stored in the memory provided in the processor.

[0085] The touch sensor 180K, also known as the "touch control device". The touch sensor 180K can be disposed on the display component 194, and the touch sensor 180K and the display component 194 form a touch screen, also known as the "touch control screen". The touch sensor 180K is used to detect a touch operation acting thereon or nearby. The touch sensor can transmit the detected touch operation to the application processor to determine the type of touch event. Visual output related to the touch operation can be provided through the display component 194. In some other embodiments, the touch sensor 180K can also be disposed on the surface of the wearable device 100, at a different position from that of the display component 194. For example, a first input entered by the user can be obtained through the touch sensor 180K, and based on the first input, the state of the target object can be determined.

[0086] The button 190 includes a power-on button, a volume button, etc. The button 190 can be a mechanical button or a touch button. The wearable device 100 can receive button inputs and generate key signal inputs related to the user settings and function control of the wearable device 100.

[0087] The optical engine 195 is mainly used for imaging, which includes a lens and a display screen, and the lens here can be an optical component.

[0088] Figure 2 The flowchart of a respiration monitoring method provided by an embodiment of the present disclosure. This embodiment is applicable to the situation of monitoring the respiration data of a target object by using a wearable device. This method can be executed by a respiration monitoring device, and the respiration monitoring device can be implemented in the form of hardware and / or software. The respiration monitoring device can be configured in the wearable device. As Figure 2 shown, the method includes:

[0089] S110. Obtain the state of the target object.

[0090] Wherein, the state of the target object includes a first state and a second state.

[0091] In this embodiment, the target object can be the object whose respiration is monitored by using this respiration monitoring method. For example, the respiration monitoring device executing this respiration monitoring method can be configured in the wearable device, and the target object can be the wearer of the wearable device. The first state and the second state can be used to distinguish the motion state and the non-motion state of the target object. For example, the first state can be set to represent the motion state, and the second state can be set to represent the non-motion state.

[0092] Further, when the wearable device is powered on, wear detection can be performed first to confirm whether the target object has worn the wearable device. If the target object has not worn the wearable device, relevant detection modules and devices, such as various sensors, stop working to save energy consumption; if the target object has worn the wearable device, relevant detection modules and devices on the wearable device can be started, and the state of the target object can be obtained, that is, it is determined whether the target object is in the first state or the second state. In some embodiments, the way to obtain the state of the target object can be to respond to the operation of the target object, determine the current state set by the target object according to the operation of the target object, and use the current state set by the target object as the state of the target object. The way to obtain the state of the target object can also be to collect relevant physiological sign data of the target object in real time, such as breathing data, etc. When the target object is exercising, the amplitude and frequency of breathing will increase or decrease to a certain extent. For example, when performing exercises mainly based on static states such as meditation, sitting in meditation, and standing postures, the amplitude and frequency of breathing will decrease to a certain extent. When performing exercises mainly based on dynamic states such as running, gymnastics, and playing ball, the amplitude and frequency of breathing will increase to a certain extent. Generally, there are corresponding physiological sign data ranges for exercises mainly based on static states and exercises mainly based on dynamic states. Therefore, according to the change of relevant physiological sign data, when the collected physiological sign data is not within the two set data ranges or shows a large fluctuation, it can be determined that the target object is in a moving state, otherwise it is in a non-moving state.

[0093] S120. Determine the sampling frequency according to the state of the target object.

[0094] In this embodiment, different sampling frequencies can correspond to different states of the target object. Generally, the sampling frequency corresponding to the moving state can be made greater than the sampling frequency corresponding to the non-moving state. For example, if the state of the target object is the moving state, the sampling frequency can be determined to be once per minute for data collection. If the state of the target object is the non-moving state, the sampling frequency can be determined to be once per ten minutes for data collection.

[0095] In a possible implementation manner, according to the state of the target object, if the target object is in a non-moving state, data can be collected at a lower frequency, and the collected data is mainly used as a reference for the data in the moving state, such as the determination of abnormal data; if the target object is in a moving state, data can be collected at a higher frequency. In some embodiments, the breathing data collected in the moving state and the non-moving state can be stored separately, and the time of data collection can be recorded in the data storage, so as to perform analysis in combination with the time dimension in subsequent data analysis.

[0096] S130. Collect the first breathing data of the target object based on the determined sampling frequency.

[0097] Among them, the first respiratory data is the respiratory data obtained by setting a collection device to collect data from a target object at a set sampling frequency.

[0098] In this embodiment, the first respiratory data can be one or more of respiratory rate, respiratory amplitude, inhalation and exhalation humidity, and inhalation and exhalation temperature.

[0099] Optionally, the method of collecting the first respiratory data of the target object based on the determined sampling frequency can be to collect the first respiratory data of the target object through a set sensor. For example, the respiratory amplitude of the target object can be collected through a gas flow sensor, the oxygen partial pressure signal can be collected through a blood oxygen sensor, and the exhalation humidity and temperature can be collected through a humidity sensor and a temperature sensor. The specific type and quantity of sensors can be adjusted according to requirements.

[0100] To facilitate data collection, since when the target object wears a wearable device, the glasses frame is very close to the target object's nose and there is a contact point with the target object's nasal wing, various sensors can be set on the frame of the wearable device.

[0101] In a possible implementation, the method further includes: generating an analysis result based on the first respiratory data, where the analysis result is used to characterize the first respiratory state of the target object.

[0102] In this embodiment, after the respiratory data is collected, the respiratory data for different time periods can be statistically analyzed according to the time of data collection, and an analysis result of the respiratory data can be generated based on the statistical situation.

[0103] Optionally, a motion target preset by the target object can be obtained, and it can be compared whether the respiratory data of the target object during the time period of the motion state reaches the motion target; or the average value of the respiratory data can be calculated every once in a while, for example, every ten minutes, and the average value of the respiratory data in the current time period can be compared with the average value of the respiratory data in the previous time period to analyze the change of the respiratory data of the target object over time; the respiratory data of the target object in the non-motion state can also be obtained, and the respiratory data in the non-motion state can be compared with the respiratory data in the motion state to analyze the change of the respiratory data of the target object in the motion state and the non-motion state.

[0104] In a possible implementation, the method further includes: obtaining the third respiratory data of the target object according to the state of the target object, where the third respiratory data is the historical respiratory data of the target object in the same state; determining the second respiratory state of the target object based on the first respiratory data and the third respiratory data.

[0105] Optionally, to record and analyze the changes in the respiratory data of the target object, the respiratory state of the target object can be determined based on the current respiratory data of the target object and the historical respiratory data in the same state. For example, when the target object is exercising, the current respiratory data can be compared with the historical respiratory data of the target object during the same exercise to judge the respiratory changes of the target object, so as to evaluate the exercise effect.

[0106] Optionally, when the second respiratory state is abnormal, the target object is notified.

[0107] Specifically, according to the comparative analysis result of the first respiratory data and the third respiratory data, when the respiratory state is abnormal, for example, the respiratory rate is abnormally high compared with the historical data, the target object can be reminded through the wearable device at this time. For example, when an abnormality occurs, the target object can be notified through the display interface of the wearable device in a set color, image, or text, or a set sound can be emitted by the wearable device to remind.

[0108] In a possible implementation manner, the method further includes: obtaining the fourth respiratory data of the target object according to the state of the target object, where the fourth respiratory data is the historical respiratory data of the target object in the second state; determining the third respiratory state of the target object based on the first respiratory data and the fourth respiratory data.

[0109] Optionally, when the third respiratory state is abnormal, the target object is notified.

[0110] Similarly, the respiratory state of the target object can be determined based on the current respiratory data of the target object and the historical respiratory data in the second state. When the state of the target object is the second state, the third respiratory data and the fourth respiratory data are the same. According to the comparative analysis result of the first respiratory data and the fourth respiratory data, when the respiratory state is abnormal, for example, the respiratory rate is abnormally high compared with the historical data, the target object can be reminded through the wearable device at this time.

[0111] In a possible implementation manner, the analysis result includes a waveform image. According to the collected respiratory data, a waveform image can be generated along the time axis, so as to intuitively reflect the change of the respiratory data of the target object over time.

[0112] In some embodiments, the manner of generating a waveform image according to the respiratory data may be: obtaining at least one of the moving target data, historical respiratory data, and non-moving state data, comparing the at least one data with the respiratory data; generating a waveform image according to the comparison result.

[0113] Specifically, the exercise target data can be set by the target object according to its own needs. Based on the waveform diagram generated from the collected breathing data, it can be displayed in the form of a line of a set color, etc., so that the target object can directly compare the current breathing data with the exercise target data to determine whether it has reached the preset target. Similarly, the historical breathing data and non-exercise state data can also be displayed on the waveform diagram generated from the collected breathing data with lines of different colors, so that the target object can determine its own breathing level according to the comparison in the waveform image.

[0114] Further, after generating the analysis result of the breathing data, it can also:

[0115] Display the analysis result through a wearable device.

[0116] Among them, the wearable device can be a wearable glasses device that has basic "glasses" functions, an independent operating system and a display interface, and can realize various functions through software installation. After generating the analysis result of the breathing data, the analysis result can be displayed through the display interface of the wearable device.

[0117] In some embodiments, the way to display the analysis result through the wearable device can be: display the analysis result through the interface of the wearable device; determine the abnormal data in the analysis result and display the abnormal data in a set manner.

[0118] Specifically, through the display interface of the wearable device, the breathing data of the target object at the current moment can be displayed in real time. For example, it can be in the form of a waveform diagram, and indicators such as the average breathing frequency and average breathing amplitude can be marked on the waveform diagram, so that the target object can clearly understand its own breathing state and can consciously control its own breathing. Through this timely cycle of breathing - feedback - adjusting breathing - feedback, it is beneficial for the target object to enter the "flow" state, that is, the state of focusing on breathing, which is a good exercise method and physical and mental state. Further, when abnormal data appears in the analysis result, the target object can be prompted through the display interface. For example, the display interface can be controlled to display the abnormal data in a special color, such as using red to indicate that the breathing is too rapid or interrupted, or a warning sign can be popped up on the display interface, etc., to prompt the target object that there may be a life-threatening situation or a breathing disease such as snoring.

[0119] Figure 3 It is a flowchart of another breathing monitoring method provided by the embodiments of the present disclosure, and this step is a refinement of the above steps. As Figure 3 shown, the method includes:

[0120] S210. Obtain the second breathing data of the target object.

[0121] In this embodiment, the breathing data may be data such as breathing frequency and breathing amplitude. Generally, when the target object is in a moving state and a non-moving state, there are relatively obvious differences in the breathing data. Therefore, according to the differences in the breathing data, it can be determined whether the target object is currently in a moving state or a non-moving state.

[0122] Specifically, the method for obtaining the second breathing data of the target object may be to convert the sensor data into breathing data through a set sensor. For example, a gas flow sensor can be used to convert the collected gas flow data into the breathing amplitude of the target object, or a blood oxygen sensor, a pressure sensor, etc. can be used to convert the change frequency of blood oxygen and pressure into the breathing frequency of the target object.

[0123] S220. If the second breathing data of the target object is within the set range, determine that the state of the target object is the first state; otherwise, determine that the state of the target object is the second state.

[0124] Specifically, exercise can be divided into two types. One is exercises mainly involving static states such as meditation, sitting in meditation, and standing postures, and the other is exercises mainly involving dynamic states such as running, gymnastics, and ball games. Compared with the non-exercise state, when the target object performs exercises mainly involving static states such as meditation, sitting in meditation, and standing postures, the amplitude and frequency of breathing will decrease to a certain extent; when the target object performs exercises mainly involving dynamic states such as running, gymnastics, and ball games, the amplitude and frequency of breathing will increase to a certain extent. Correspondingly, both exercises mainly involving static states and exercises mainly involving dynamic states have their respective corresponding ranges of physical sign data. If the first state is defined as the exercise state and the second state is defined as the non-exercise state, according to the breathing data collected at the current moment, if it is within the set range corresponding to the exercise mainly involving static states or the exercise mainly involving dynamic states, it can be determined that the state of the target object is the exercise state, that is, the first state; otherwise, it is the non-exercise state, that is, the second state.

[0125] In some embodiments, the method for obtaining the state of the target object may also be: obtaining a first input and determining the state of the target object based on the first input.

[0126] Among them, the first input may be input through a smart terminal connected to the wearable device, or may be input by the wearable device itself.

[0127] Further, the state of the target object can also be set by the target object itself. For example, the target object can set the exercise time (such as 30 minutes - 2 hours) on a wearable device or through the interface of a mobile terminal that has a communication connection with the wearable device. Then, within the time set by the target object, the state of the target object can be determined as the exercise state; or the target object can directly set the current state to the exercise state or the non - exercise state. Then, according to the operation of the target object, the set content of the target object can be directly determined as the state of the target object.

[0128] In addition, the state of the target object can be judged by integrating other conditions. For example, a gyroscope can be used to detect whether the body posture of the target object is in an active state. If so, it can be used as one of the judgment conditions for the target object being in the exercise state.

[0129] S230. Determine the sampling frequency according to the state of the target object.

[0130] In this embodiment, different sampling frequencies can correspond to different states of the target object. Generally, the sampling frequency corresponding to the exercise state can be made greater than the sampling frequency corresponding to the non - exercise state. For example, if the state of the target object is the exercise state, the target frequency can be determined to be data collection once per minute. If the state of the target object is the non - exercise state, the target frequency can be determined to be data collection once every ten minutes.

[0131] S240. Use one or more sensors to collect the first respiratory data of the target object at the sampling frequency.

[0132] In this embodiment, after determining the target frequency, the sensor can be used to collect the respiratory data of the target object at this target frequency.

[0133] Among them, the sensors include, but are not limited to, one or more of a gas flow sensor, a blood oxygen sensor, a pressure sensor, a piezoelectric film sensor, a humidity sensor, a temperature sensor, and a magnetic sensor. The gas flow sensor can collect the cumulative gas flow and instantaneous gas flow in the vicinity, so it can reflect the breathing amplitude of the target object; the blood oxygen sensor can collect the oxygen partial pressure data in the blood, and according to the change of the oxygen partial pressure data, it can reflect the breathing frequency of the target object; both the pressure sensor and the piezoelectric film sensor can collect the pressure change caused by the nostril flapping of the target object, so they can reflect the breathing amplitude and frequency of the target object; the humidity sensor and the temperature sensor can respectively collect the inhalation and exhalation humidity and temperature of the target object; the magnetic sensor can convert the change of the magnetic properties of the sensitive element caused by external factors such as magnetic field, current, stress strain, temperature, and light into an electrical signal, so it can collect the electrical signal generated by the breathing of the target object, and then reflect the breathing amplitude and frequency.

[0134] In some embodiments, the sensor is disposed on a frame of the wearable device.

[0135] Specifically, a gas mass flow sensor can be built into the nose bracket to detect the breathing cycle, so that the user will not feel uncomfortable and improve the accuracy of the user's breathing data statistics. A pressure sensor can also be built into the nose bracket, which is mainly used to convert the airway pressure into a differential signal, and the measurement value is handed over to the circuit microcontroller unit (MCU) to accurately make inhalation and exhalation judgments, detect changes and vibrations in respiratory pressure, and the carbon dioxide level during exhalation can be calculated using a differential pressure sensor. Piezoelectric film sensors can also be preset on the nose frame of the glasses to detect the breathing amplitude and frequency of the target object by measuring the vibration during the breathing process, and then detect the effect of exercise or the depth of sleep. A temperature / humidity sensor can also be preset near the nostrils of the glasses to monitor the temperature / humidity difference of the user's inhaled / exhaled airflow as a reference indicator for judging the target object's exercise effect or breathing level.

[0136] Figure 4 This is a schematic diagram of a sensor setting method provided in an embodiment of the present disclosure. As shown in the figure, the pressure sensor is located on the nose bridge on both sides of the nose, which can conveniently monitor the amplitude and frequency of nostril flaring, while the gas flow sensor is placed on the tip of the nose or just below the nostrils, which can be used to monitor the coarseness and fineness of breathing.

[0137] In some embodiments, the respiratory data includes, but is not limited to, respiratory rate, respiratory amplitude, inhaled and exhaled humidity, and inhaled and exhaled temperature.

[0138] In this embodiment, the respiratory data collected each time can be stored separately according to the different states of the target object for the next step of data processing and analysis.

[0139] Figure 5 Schematic diagram of a respiratory monitoring device provided by an embodiment of the present disclosure. Figure 5 As shown, the device includes: a state acquisition module 310 , a sampling frequency determination module 320 and a first respiratory data acquisition module 330 .

[0140] The state acquisition module 310 is used to acquire the state of the target object. The state of the target object includes a first state and a second state.

[0141] Furthermore, the status acquisition module 310 is also used for:

[0142] A first input is obtained, and a state of a target object is determined based on the first input.

[0143] Furthermore, the status acquisition module 310 is also used for:

[0144] Obtain the second breathing data of the target object; if the second breathing data of the target object is within the set range, determine the state of the target object as the first state, otherwise determine the state of the target object as the second state.

[0145] A sampling frequency determination module 320, configured to determine a sampling frequency according to the state of the target object.

[0146] A first breathing data acquisition module 330, configured to acquire the first breathing data of the target object based on the determined sampling frequency.

[0147] Further, the first breathing data acquisition module 330 is further configured to: acquire the first breathing data of the target object at the sampling frequency by using one or more sensors.

[0148] Further, the one or more sensors include one or more of a gas flow sensor, a blood oxygen sensor, a pressure sensor, a piezoelectric thin film sensor, a humidity sensor, a temperature sensor, and a magnetic sensor.

[0149] Further, the first breathing data includes one or more of a breathing frequency, a breathing amplitude, an inhalation and exhalation humidity, and an inhalation and exhalation temperature.

[0150] Further, the device further includes an analysis result generation module 340, configured to generate an analysis result according to the first breathing data, and the analysis result is used to characterize the first breathing state of the target object.

[0151] Further, the device further includes a third breathing data acquisition module 350 and a second breathing state determination module 360.

[0152] The third breathing data acquisition module 350 is configured to acquire the third breathing data of the target object according to the state of the target object, where the third breathing data is the historical breathing data of the target object in the same state.

[0153] The second breathing state determination module 360 is configured to determine the second breathing state of the target object based on the first breathing data and the third breathing data.

[0154] Further, the device further includes a fourth breathing data acquisition module 370 and a third breathing state determination module 380.

[0155] The fourth breathing data acquisition module 370 is configured to acquire the fourth breathing data of the target object according to the state of the target object, where the fourth breathing data is the historical breathing data of the target object in the second state.

[0156] The third breathing state determination module 380 is configured to determine the third breathing state of the target object based on the first breathing data and the fourth breathing data.

[0157] Further, the device further includes a first notification module 391 and a second notification module 392.

[0158] The first notification module 391 is configured to notify the target object when the second breathing state is abnormal.

[0159] The second notification module 392 is configured to notify the target object when the third breathing state is abnormal.

[0160] The breathing monitoring device provided by the embodiments of the present disclosure can execute the breathing monitoring method provided by any embodiment of the present disclosure, and has the corresponding functional modules and beneficial effects for executing the method.

[0161] Figure 6 FIG. shows a schematic structural diagram of a wearable device 10 that can be used to implement the embodiments of the present disclosure. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0162] As Figure 6 shown, the wearable device 10 includes at least one processor 11, and a memory communicatively connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc. The memory stores a computer program executable by the at least one processor. The processor 11 can execute various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the wearable device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. The input / output (I / O) interface 15 is also connected to the bus 14.

[0163] Multiple components in the wearable device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a magnetic disk, an optical disc, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the wearable device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0164] Processor 11 may be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 executes the various methods and processes described above, such as the breathing monitoring method.

[0165] In some embodiments, the breathing monitoring method may be implemented as a computer program tangibly embodied in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed onto the wearable device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the breathing monitoring described above may be executed. Alternatively, in other embodiments, processor 11 may be configured to execute the breathing monitoring method by any other suitable means (e.g., by means of firmware).

[0166] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuitry, integrated circuit systems, field programmable gate arrays (FPGA), application specific integrated circuits (ASIC), application specific standard products (ASSP), systems on a chip (SOC), complex programmable logic devices (CPLD), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special or general-purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit the data and instructions to the storage system, the at least one input device, and the at least one output device.

[0167] The computer programs for implementing the methods of the present disclosure can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that the computer programs, when executed by the processor, cause the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The computer programs can be executed entirely on the machine, partially on the machine, as a stand-alone software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0168] In the context of this disclosure, a computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer-readable storage medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, the computer-readable storage medium can be a machine-readable signal medium. More specific examples of the machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0169] In order to provide interaction with a user, the systems and techniques described herein can be implemented on a wearable device that has: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the wearable device. Other kinds of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, speech input, or tactile input).

[0170] The systems and techniques described herein can be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer having a graphical user interface or a web browser through which the user can interact with an implementation of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0171] A computing system may include a client and a server. The client and the server are generally far from each other and usually interact via a communication network. The client-server relationship is created by computer programs running on respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or a cloud host, which is a host product in the cloud computing service system, solving the defects of difficult management and weak business scalability existing in traditional physical hosts and VPS services.

[0172] It should be understood that various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps recited in this disclosure can be executed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of this disclosure can be achieved, and no limitation is imposed herein.

[0173] The above specific embodiments do not constitute a limitation on the protection scope of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principle of this disclosure shall be included within the protection scope of this disclosure.

Claims

1. A respiratory monitoring method, characterized in that, Including: Obtaining the state of a target object wearing the wearable device through the wearable device, where the state of the target object includes a first state and a second state. Among them, the first state is a motion state, and the second state is a non-motion state; Determining a sampling frequency according to the state of the target object; The pressure sensor and gas flow sensor of the wearable device collect first respiratory data of the target object based on the determined sampling frequency; where the pressure sensor is located on the nose bridge of the wearable device, the gas flow sensor is located on the frame of the wearable device, and when the wearable device is worn by the target object, the gas flow sensor is located directly below the nose tip of the target object. The wearable device further includes a display component configured to display an analysis result generated based on the first respiratory data; The method further includes: Obtaining third respiratory data of the target object according to the state of the target object, where the third respiratory data is historical respiratory data of the target object in the same state; Determining a second respiratory state of the target object based on the first respiratory data and the third respiratory data.

2. The method according to claim 1, wherein Obtaining the state of the target object includes: Obtaining a first input and determining the state of the target object based on the first input.

3. The method according to claim 1, wherein Obtaining the state of the target object includes: Obtaining second respiratory data of the target object; If the second respiratory data of the target object is within a set range, determining that the state of the target object is the first state; otherwise, determining that the state of the target object is the second state.

4. The method according to claim 1, wherein Collecting first respiratory data of the target object based on the determined sampling frequency includes: Collecting first respiratory data of the target object by using one or more sensors at the sampling frequency.

5. The method according to claim 4, wherein The one or more sensors include one or more of a gas flow sensor, a blood oxygen sensor, a pressure sensor, a piezoelectric film sensor, a humidity sensor, a temperature sensor, and a magnetic sensor.

6. The method according to claim 1, wherein The first respiratory data includes one or more of a respiratory rate, a respiratory amplitude, an inhalation and exhalation humidity, and an inhalation and exhalation temperature.

7. The method according to claim 1, wherein It further includes: Generating an analysis result according to the first respiratory data, and the analysis result is used to characterize the first respiratory state of the target object.

8. The method according to claim 1, wherein It further includes: Obtaining fourth respiratory data of the target object according to the state of the target object, where the fourth respiratory data is historical respiratory data of the target object in the second state; Determining a third respiratory state of the target object based on the first respiratory data and the fourth respiratory data.

9. The method according to claim 1, wherein It further includes: When the second respiratory state is abnormal, notifying the target object.

10. The method according to claim 8, wherein It further includes: When the third respiratory state is abnormal, notifying the target object.

11. A respiration monitoring device, characterized in that, Including: A state acquisition module for obtaining the state of a target object wearing the wearable device through the wearable device, where the state of the target object includes a first state and a second state. Among them, the first state is a motion state, and the second state is a non-motion state; A sampling frequency determination module for determining a sampling frequency according to the state of the target object; The first respiratory data acquisition module, including a pressure sensor and a gas flow sensor, is configured to acquire the first respiratory data of the target object based on the determined sampling frequency; wherein, the pressure sensor is located on the nose bridge of the wearable device, the gas flow sensor is located on the frame of the wearable device, and when the wearable device is worn by the target object, the gas flow sensor is located directly below the nose tip of the target object. The wearable device further includes a display component, which is configured to display the analysis result generated according to the first respiratory data. The device further includes a third respiratory data acquisition module and a second respiratory state determination module. The third respiratory data acquisition module is configured to acquire the third respiratory data of the target object according to the state of the target object, where the third respiratory data is the historical respiratory data of the target object in the same state. The second respiratory state determination module is configured to determine the second respiratory state of the target object based on the first respiratory data and the third respiratory data.

12. A wearable device, characterized in that, The wearable device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and when the computer program is executed by the at least one processor, the at least one processor is enabled to execute the respiratory monitoring method according to any one of claims 1-10.

13. The wearable device according to claim 12, characterized in that, The wearable device further includes: A display component, which is coupled to the at least one processor and is configured to: Display the analysis result generated according to the first respiratory data.

14. The wearable device according to claim 12, wherein The wearable device further includes: One or more sensors, which are coupled to the at least one processor and are configured to: Acquire the first respiratory data of the target object based on the determined sampling frequency.

15. The wearable device according to claim 14, wherein The one or more sensors are disposed on a first part of the wearable device, and when the wearable device is worn by the target object, the first part is close to the respiratory part of the target object.

16. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions, which are used to enable the processor to execute the respiratory monitoring method according to any one of claims 1-10 when executed.

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