WO2022237598A1 - Procédé de test d'état de sommeil et dispositif électronique - Google Patents

Procédé de test d'état de sommeil et dispositif électronique Download PDF

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Publication number
WO2022237598A1
WO2022237598A1 PCT/CN2022/090568 CN2022090568W WO2022237598A1 WO 2022237598 A1 WO2022237598 A1 WO 2022237598A1 CN 2022090568 W CN2022090568 W CN 2022090568W WO 2022237598 A1 WO2022237598 A1 WO 2022237598A1
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Prior art keywords
wearable device
target user
detection result
user
sleep
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PCT/CN2022/090568
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English (en)
Chinese (zh)
Inventor
夏凯伦
徐腾
赵帅
叶际隆
杨斌
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华为技术有限公司
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Publication of WO2022237598A1 publication Critical patent/WO2022237598A1/fr

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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/48—Other medical applications
    • A61B5/4806—Sleep evaluation
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/0205—Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/024—Detecting, measuring or recording pulse rate or heart rate
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/024—Detecting, measuring or recording pulse rate or heart rate
    • A61B5/02438—Detecting, measuring or recording pulse rate or heart rate with portable devices, e.g. worn by the patient
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
    • A61B5/1118—Determining activity level
    • A—HUMAN NECESSITIES
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    • A61B5/6801—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
    • A61B5/6802—Sensor mounted on worn items
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    • A61B5/6802—Sensor mounted on worn items
    • A61B5/6803—Head-worn items, e.g. helmets, masks, headphones or goggles
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    • A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
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    • A61B5/6802—Sensor mounted on worn items
    • A61B5/6804—Garments; Clothes
    • A—HUMAN NECESSITIES
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    • A61B5/6801—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
    • A61B5/6802—Sensor mounted on worn items
    • A61B5/681—Wristwatch-type devices
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    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
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    • A61B5/6887—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient mounted on external non-worn devices, e.g. non-medical devices
    • A61B5/6892—Mats

Definitions

  • the present application relates to the technical field of terminals, and in particular to a sleep state detection method and electronic equipment.
  • Sleep is an important physiological activity of the human body, which can help the body recover physical, mental and spiritual strength, relieve stress, enhance learning ability, and maintain good health. If people lack sleep or suffer from sleep disorders (such as insomnia, narcolepsy, sleepwalking, etc.), it may lead to some sequelae, such as emotional instability, depression, anxiety, etc. Therefore, sleep state detection is very necessary and can help people understand their sleep quality and improve sleep.
  • sleep disorders such as insomnia, narcolepsy, sleepwalking, etc.
  • the purpose of the present application is to provide a sleep state detection method and an electronic device, which can improve the accuracy of sleep state detection.
  • a sleep state detection method is provided, which is applied to a wearable device, and the wearable device is currently in a non-wearing mode.
  • the method includes: collecting behavior data generated when the target user sleeps, and the behavior data includes A motion signal and/or a sound signal; wherein, the motion signal is used to determine the first detection result characterizing the sleep state of the target user, and the sound signal is used to determine the first detection result characterizing the sleep state of the target user.
  • Two detection results according to the first detection result and/or the second detection result, determine the final detection result of the sleep state of the target user.
  • the sleep state is detected from two different angles of the motion signal and the sound signal, and the final detection result is determined according to the two detection results, which helps to improve the accuracy of detecting the user's sleep state.
  • the behavior data may be sent to an electronic device connected to the wearable device.
  • the electronic device determines the first detection result based on the operating signal in the behavior data, determines the second detection result based on the sound signal in the behavior data, and then obtains the final detection result according to the first detection result and/or the second detection result result. That is to say, all or part of the execution steps of the wearable device may be executed by an electronic device connected to the wearable device. After the electronic device obtains the final detection result, it can be sent to the wearable device for display or displayed locally by the electronic device.
  • the electronic device connected with the wearable device may be, for example, a portable electronic device such as a mobile phone or a tablet computer.
  • the final detection result is an average or weighted average of the first detection result and the second detection result. Exemplarily, for example, if the first detection result is 70 points and the second detection result is 80 points, then the final detection result is 75 points.
  • the first detection result and the second detection result can also have other representations, such as grades, such as, the first detection result is the first grade, and the second detection result is the third grade, then the final The detection result is an intermediate grade between the first grade and the third grade.
  • the target user sleeps before collecting the behavior data generated when the target user sleeps, it also includes: outputting first prompt information when it is determined that there are many people in the environment, and the first prompt information is used to prompt to enter the A specific sound signal of the target user; extracting a sound signal matching the specific sound signal of the target user from the sound signals according to the entered specific sound signal of the target user; wherein, the extracted sound signal is used for Determining the second detection result characterizing the sleep state of the target user.
  • the embodiment of the present application in a multi-person environment, if the sleep state of the target user is to be detected, then the sound signal of the target user is input, so that the sound signal of the target user can be extracted from the collected sound signal to be used to determine The second detection result of the target user. That is to say, even in a multi-person environment, the embodiment of the present application can detect the sleep state of a specific user, which is convenient to use.
  • outputting first prompt information includes: when the electronic device connected to the wearable device determines that there are multiple people in the environment, outputting the first prompt information; After the electronic device detects the specific sound signal recorded by the target user, it sends an instruction to the wearable device, and the instruction is used to instruct the wearable device to start collecting behavior data.
  • the electronic device may not need to send instructions, for example, the wearable device always collects behavior data by default. After the wearable device collects the behavior data, it sends the behavior data to the electronic device, and the electronic device extracts from the sound signal in the behavior data according to the input specific sound signal of the target user. A sound signal matching the specific sound signal of the target user is selected, and a second detection result is determined according to the extracted sound signal.
  • the second prompt information is used to prompt to enter the target user.
  • the orientation of the user relative to the wearable device according to the entered orientation of the target user relative to the wearable device, extract from the motion signal that matches the orientation of the target user relative to the wearable device motion signal; wherein, the extracted motion signal is used to determine the first detection result characterizing the sleep state of the target user.
  • the sleep state of the target user in a multi-person environment, if the sleep state of the target user is to be detected, the orientation of the target user relative to the wearable device is entered, and in this case, the motion matching the orientation is extracted from the collected motion signal signal, and the motion signal can be used to determine the first detection result of the target user.
  • the sleep state of a specific user can be detected, and it can be detected from two aspects of motion signals and sound signals, with high accuracy.
  • outputting second prompt information includes: when the electronic device connected to the wearable device determines that there are multiple people in the environment, outputting the second prompt information; After detecting that the orientation of the target user is entered relative to the wearable device, the electronic device sends an instruction to the wearable device, where the instruction is used to instruct the wearable device to collect behavior data.
  • the electronic device may not need to send instructions, for example, the wearable device always collects behavior data by default.
  • the wearable device collects the behavior data, it sends the behavior data to the electronic device, and the electronic device extracts the movement data from the behavior data according to the entered orientation of the target user relative to the wearable device.
  • the corresponding motion signal is extracted from the signal, and the first detection result is determined according to the extracted motion signal.
  • determining that there are multiple people in the environment includes: outputting third prompt information, the third prompt information is used to prompt whether there are multiple people in the environment; many people. That is to say, the wearable device can determine whether the environment is a multi-person environment by outputting prompt information.
  • the embodiment of the present application can detect the sleeping state of a specific user in a multi-person environment, and can detect from two aspects of motion signals and sound signals, with high accuracy.
  • determining that there are multiple people in the environment includes: outputting third prompt information through an electronic device connected to the wearable device, and the electronic device determines that there are multiple people in the environment according to a confirmation instruction input by the user.
  • the electronic device determines that there are multiple people involved, it may output the first prompt information or the second prompt information, refer to the foregoing description.
  • before collecting the behavior data generated when the target user sleeps it also includes: responding to user operations, setting the current mode as the non-wearing mode; outputting fourth prompt information, the fourth prompt information Used to prompt the user to fix the wearable device.
  • the wearable device has a wearing mode and a non-wearing mode.
  • the sleep detection process in the wearing mode can be used in the wearing mode
  • the sleep detection process in the non-wearing mode can be used in the non-wearing mode.
  • the user can be prompted to fix the device, such as fixing it on a mattress, pillow, etc., and the user experience is higher.
  • setting the current mode to the non-wearing mode includes: an electronic device connected to the wearable device responds to a user operation setting the current mode of the wearable device to the non-wearing mode, and outputs a fourth prompt message, prompting the user to secure the wearable.
  • the wearable device may be connected with an electronic device (such as a mobile phone), and all or part of the above steps of the wearable device may be performed by the electronic device.
  • an electronic device such as a mobile phone
  • the wearable device may be connected with an electronic device (such as a mobile phone), and all or part of the above steps of the wearable device may be performed by the electronic device.
  • at least one of the first prompt information, the second prompt information, the third prompt information and the fourth prompt information may be displayed by an electronic device connected to the wearable device.
  • the final detection result may be used to characterize the overall sleep quality of the multiple people. That is to say, the embodiment of the present application can detect the overall sleep status of multiple people, so that the sleep status of multiple people can be detected at one time, which is more efficient.
  • the collection of motion signals generated by the target user during sleep may use a motion sensor to collect motion signals caused by the target user's behavior of turning over, getting up or shaking during sleep, and the motion signal Including at least one of displacement, acceleration, velocity, angular velocity and angular acceleration; the method also includes: identifying body motion characteristics according to the motion signal, and the body motion characteristics include turning over, getting up and shaking; according to the set
  • the first detection result is determined by at least one of the occurrence times, frequency and intensity of the body movement feature within a time period. That is to say, in the embodiment of the present application, the wearable device determines the first detection result according to the number, frequency, intensity, etc. of the body movement characteristics of the target user, and the body movement characteristics (such as turning over, getting up, etc.) sleep state, so this detection method is more accurate.
  • At least one sound feature of the target user's snoring sound, breathing sound, etc. is included in the collected sound signal generated by the target user during sleep; the method further includes: according to the set The second detection result is determined by at least one of intensity, frequency, and frequency of at least one sound feature of the target user's snoring sound or breathing sound within a time period. That is to say, in this embodiment of the application, the wearable device determines the second detection result according to the intensity and frequency of the target user's snoring or breathing sound, and the breathing or snoring sound can more accurately reflect the user's sleep state, so this The detection method is more accurate.
  • an electronic device including a processor, a memory, and one or more programs; wherein the one or more programs are stored in the memory, and the one or more programs include instructions , when the instruction is executed by the processor, the terminal device is made to execute the method steps provided in the first aspect above.
  • a computer-readable storage medium is provided, the computer-readable storage medium is used to store a computer program, and when the computer program is run on a computer, the computer executes the method as provided in the above-mentioned first aspect .
  • a computer program product including a computer program, and when the computer program is run on a computer, the computer is made to execute the method provided in the first aspect above.
  • a graphical user interface on an electronic device the electronic device has a display screen, a memory, and a processor, and the processor is configured to execute one or more computer programs stored in the memory,
  • the graphical user interface includes a graphical user interface displayed when the electronic device executes the method described in the first aspect above.
  • the embodiment of the present application further provides a chip, the chip is coupled with the memory in the electronic device, and is used to call the computer program stored in the memory and execute the technical solution of the first aspect of the embodiment of the present application.
  • the implementation of the present application "Coupled" in the examples means that two elements are joined to each other directly or indirectly.
  • FIG. 1 is a schematic diagram of a hardware structure of a wearable device provided by an embodiment of the present application
  • FIG. 2 is a schematic flowchart of a sleep state detection method provided by an embodiment of the present application
  • FIG. 3 is a schematic diagram of information displayed on a display screen of a wearable device provided by an embodiment of the present application
  • FIG. 4 is a schematic diagram of information displayed on a display screen of a wearable device provided by an embodiment of the present application.
  • FIG. 5A is a schematic diagram of a mobile phone displaying a prompt to a user to fix a device provided by an embodiment of the present application
  • FIG. 5B and FIG. 5C are schematic diagrams of displaying sleep state detection results on a mobile phone provided by an embodiment of the present application.
  • FIG. 6 is a schematic diagram of a user sleep state detection process in non-wearing mode provided by an embodiment of the present application.
  • FIG. 7 is another schematic flowchart of a sleep state detection method provided by an embodiment of the present application.
  • FIGS. 8A to 8B are schematic diagrams of a mobile phone prompting to input voice information of a target user provided by an embodiment of the present application
  • FIG. 9 is another schematic diagram of a mobile phone prompting to input voice information of a target user provided by an embodiment of the present application.
  • Figures 10 to 12 are schematic diagrams of prompting multiple detection modes on the mobile phone provided by an embodiment of the present application.
  • Fig. 13 is a schematic structural diagram of a wearable device provided by an embodiment of the present application.
  • Common sleep state detection methods mainly include the following:
  • the most traditional sleep state detection method is to use medical professional medical instruments (such as polysomnography) to scan the user's EEG and breathing when the user is sleeping, which can provide users with scientific and accurate clinical diagnosis.
  • the instrument is complex and large in size, and it is impossible to realize daily sleep detection.
  • Detect sleep state when user sleeps Generally, an electrode sheet is provided on a sports bracelet or a watch. When the electrode sheet touches the user's body, a body signal (such as heart rate) can be sensed, and the sleep state can be judged through the body signal. That is to say, when the user sleeps, he needs to wear a sports bracelet or watch to detect the sleep state, but most users don't like to wear something on their wrist when they sleep, which will affect their sleep, so this method has a low user experience.
  • a body signal such as heart rate
  • non-wearable sleep detection devices such as sleep trackers, which can be fixed on the bed by the user, and the sleep tracker can collect changes in the breathing and heart rate of the user during sleep;
  • the pillow in the groove of the ring or watch when the sports bracelet or watch is fixed in the groove, can detect the head movement signal during the user's sleep to judge the user's sleep quality.
  • this method requires the user to purchase an additional non-wearable sleep detection device (such as a pillow with grooves), and the non-wearable sleep detection device has a single function, which can only detect the sleep state and cannot satisfy the user's daily exercise (such as running). The detection of motion state.
  • an embodiment of the present application provides a sleep state detection method, which is applicable to a wearable device, and the wearable device has two states, a wearing state and a non-wearing state.
  • the wearable device In the wearing state, the user can wear the wearable device for daily motion detection.
  • the non-wearing state In the non-wearing state, the user can set it near the user's sleeping position, and can detect the sleeping state without the user wearing it on the wrist.
  • the wearable device can collect motion signals (such as turning over) during the user's sleep, and/or Or a sound signal (such as the sound of breathing), wherein the motion signal can be used to determine the first detection result of the user's sleep state, and the sound signal is used to determine the second detection result of the user's sleep state; according to the first detection result and/or The second detection result determines the final detection result of the sleep state of the target user, so that the sleep state detection result is more accurate.
  • motion signals such as turning over
  • a sound signal such as the sound of breathing
  • the sleep state detection method provided in the embodiment of the present application can be applied to wearable devices.
  • the wearable device may be a smart watch, smart bracelet, smart necklace, smart clothing, smart shoes, smart earrings, etc.
  • the embodiment of the present application does not limit the form of the wearable device.
  • FIG. 1 shows a schematic structural diagram of a wearable device.
  • the wearable device may include a processor 110, an external memory interface 120, an internal memory 121, a universal serial bus (universal serial bus, USB) interface 130, a charging management module 140, a power management module 141, and a battery 142 , antenna 1, antenna 2, mobile communication module 150, wireless communication module 160, audio module 170, speaker 170A, receiver 170B, microphone 170C, earphone jack 170D, sensor module 180, button 190, motor 191, indicator 192, camera 193 , a display screen 194, and a subscriber identification module (subscriber identification module, SIM) card interface 195, etc.
  • SIM subscriber identification module
  • the sensor module 180 may include a pressure sensor 180A, a gyroscope sensor 180B, an air pressure sensor 180C, a magnetic sensor 180D, an acceleration sensor 180E, a distance sensor 180F, a proximity light sensor 180G, a fingerprint sensor 180H, a temperature sensor 180J, a touch sensor 180K, an ambient light sensor 180L, bone conduction sensor 180M, etc.
  • the processor 110 may include one or more processing units, for example: the processor 110 may include an application processor (application processor, AP), a modem processor, a graphics processing unit (graphics processing unit, GPU), an image signal processor (image signal processor, ISP), controller, memory, video codec, digital signal processor (digital signal processor, DSP), baseband processor, and/or neural network processor (neural-network processing unit, NPU) Wait.
  • application processor application processor
  • AP application processor
  • modem processor graphics processing unit
  • graphics processing unit graphics processing unit
  • ISP image signal processor
  • controller memory
  • video codec digital signal processor
  • DSP digital signal processor
  • baseband processor baseband processor
  • neural network processor neural-network processing unit, NPU
  • different processing units may be independent devices, or may be integrated in one or more processors.
  • the controller can be the nerve center and command center of the wearable device.
  • the controller can generate an operation control signal according to the instruction opcode and timing signal, and complete the control of fetching and executing the instruction
  • a memory may also be provided in the processor 110 for storing instructions and data.
  • the memory in processor 110 is a cache memory.
  • the memory may hold 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 called directly from the memory. Repeated access is avoided, and the waiting time of the processor 110 is reduced, thereby improving the efficiency of the system.
  • the USB interface 130 is an interface conforming to the USB standard specification, specifically, it can be a Mini USB interface, a Micro USB interface, a USB Type C interface, and the like.
  • the USB interface 130 can be used to connect a charger to charge the wearable device, and can also be used to transmit data between the wearable device and peripheral devices.
  • the charging management module 140 is configured to receive a charging input from a charger.
  • the power management module 141 is used for connecting the battery 142 , the charging management module 140 and the processor 110 .
  • the power management module 141 receives the input of the battery 142 and/or the charging management module 140, and supplies power for the processor 110, the internal memory 121, the external memory, the display screen 194, the camera 193, and the wireless communication module 160, etc.
  • the wireless communication function of the wearable device can be realized by the antenna 1, the antenna 2, the mobile communication module 150, the wireless communication module 160, the modem processor and the baseband processor.
  • Antenna 1 and Antenna 2 are used to transmit and receive electromagnetic wave signals.
  • Each antenna in a wearable device can be used to cover single or multiple communication frequency bands. Different antennas can also be multiplexed to improve the utilization of the antennas.
  • Antenna 1 can be multiplexed as a diversity antenna of a wireless local area network.
  • the antenna may be used in conjunction with a tuning switch.
  • the mobile communication module 150 can provide wireless communication solutions including 2G/3G/4G/5G applied to wearable devices.
  • the mobile communication module 150 may include at least one filter, switch, power amplifier, low noise amplifier (low noise amplifier, LNA) and the like.
  • the mobile communication module 150 can receive electromagnetic waves through the antenna 1, filter and amplify the received electromagnetic waves, and send them to the modem processor for demodulation.
  • the mobile communication module 150 can also amplify the signals modulated by the modem processor, and convert them into electromagnetic waves through the antenna 1 for radiation.
  • at least part of the functional modules of the mobile communication module 150 may be set in the processor 110 .
  • at least part of the functional modules of the mobile communication module 150 and at least part of the modules of the processor 110 may be set in the same device.
  • the wireless communication module 160 can provide wireless local area networks (wireless local area networks, WLAN) (such as wireless fidelity (Wireless Fidelity, Wi-Fi) network), bluetooth (bluetooth, BT), global navigation satellite System (global navigation satellite system, GNSS), frequency modulation (frequency modulation, FM), near field communication technology (near field communication, NFC), infrared technology (infrared, IR) and other wireless communication solutions.
  • the wireless communication module 160 may be one or more devices integrating at least one communication processing module.
  • the wireless communication module 160 receives electromagnetic waves via the antenna 2 , frequency-modulates and filters the electromagnetic wave signals, and sends the processed signals to the processor 110 .
  • the wireless communication module 160 can also receive the signal to be sent from the processor 110 , frequency-modulate it, amplify it, and convert it into electromagnetic waves through the antenna 2 for radiation.
  • the antenna 1 of the wearable device is coupled to the mobile communication module 150, and the antenna 2 is coupled to the wireless communication module 160, so that the wearable device can communicate with the network and other devices through wireless communication technology.
  • the wireless communication technology may include global system for mobile communications (GSM), general packet radio service (general packet radio service, GPRS), code division multiple access (code division multiple access, CDMA), broadband Code division multiple access (wideband code division multiple access, WCDMA), time division code division multiple access (time-division code division multiple access, TD-SCDMA), long term evolution (long term evolution, LTE), BT, GNSS, WLAN, NFC , FM, and/or IR techniques, etc.
  • GSM global system for mobile communications
  • GPRS general packet radio service
  • code division multiple access code division multiple access
  • CDMA broadband Code division multiple access
  • WCDMA wideband code division multiple access
  • time division code division multiple access time-division code division multiple access
  • TD-SCDMA time-division code division multiple access
  • the GNSS may include a global positioning system (global positioning system, GPS), a global navigation satellite system (global navigation satellite system, GLONASS), a Beidou navigation satellite system (beidou navigation satellite system, BDS), a quasi-zenith satellite system (quasi -zenith satellite system (QZSS) and/or satellite based augmentation systems (SBAS).
  • GPS global positioning system
  • GLONASS global navigation satellite system
  • Beidou navigation satellite system beidou navigation satellite system
  • BDS Beidou navigation satellite system
  • QZSS quasi-zenith satellite system
  • SBAS satellite based augmentation systems
  • the display screen 194 is used to display the display interface of the application and the like.
  • the display screen 194 includes a display panel.
  • the display panel can be 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 (active-matrix organic light emitting diode, AMOLED), flexible light-emitting diode (flex light-emitting diode, FLED), Miniled, MicroLed, Micro-oLed, quantum dot light emitting diodes (quantum dot light emitting diodes, QLED), etc.
  • the wearable device may include 1 or N display screens 194, where N is a positive integer greater than 1.
  • the wearable device 100 can realize the shooting function through ISP, camera 193, video codec, GPU, display screen 194 and application processor.
  • the ISP is used for processing the data fed back by the camera 193 .
  • the light is transmitted to the photosensitive element of the camera through the lens, and the light signal is converted into an electrical signal, and the photosensitive element of the camera transmits the electrical signal to the ISP for processing, and converts it into an image visible to the naked eye.
  • ISP can also perform algorithm optimization on image noise, brightness, and skin color.
  • ISP can also optimize the exposure, color temperature and other parameters of the shooting scene.
  • the ISP may be located in the camera 193 .
  • Camera 193 is used to capture still images or video.
  • the object generates an optical image through the lens and projects it to the photosensitive element.
  • the photosensitive element may be a charge coupled device (CCD) or a complementary metal-oxide-semiconductor (CMOS) phototransistor.
  • CMOS complementary metal-oxide-semiconductor
  • the photosensitive element 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.
  • DSP converts digital image signals into standard RGB, YUV and other image signals.
  • the wearable device may include 1 or N cameras 193, where N is a positive integer greater than 1.
  • the internal memory 121 may be used to store computer-executable program codes including instructions.
  • the processor 110 executes various functional applications and data processing of the wearable device by executing instructions stored in the internal memory 121 .
  • the internal memory 121 may include an area for storing programs and an area for storing data.
  • the storage program area can store the operating system and software codes of at least one application program (such as iQiyi application, WeChat application, etc.).
  • the data storage area can store data (such as images, videos, etc.) generated during use of the wearable device.
  • the internal memory 121 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one magnetic disk storage device, flash memory device, universal flash storage (universal flash storage, UFS) and the like.
  • the external memory interface 120 can be used to connect an external memory card, such as a Micro SD card, to expand the storage capacity of the wearable device.
  • the external memory card communicates with the processor 110 through the external memory interface 120 to implement a data storage function. For example, save pictures, videos and other files in the external memory card.
  • the wearable device can realize the audio function through the audio module 170, the speaker 170A, the receiver 170B, the microphone 170C, the earphone interface 170D, and the application processor. Such as music playback, recording, etc.
  • the pressure sensor 180A is used to sense the pressure signal and convert the pressure signal into an electrical signal.
  • pressure sensor 180A may be disposed on display screen 194 .
  • the gyroscope sensor 180B can be used to determine the motion gesture of the wearable device.
  • the angular velocity of the wearable device about three axes ie, x, y and z axes
  • the gyro sensor 180B can be used for image stabilization.
  • the air pressure sensor 180C is used to measure air pressure.
  • the wearable device calculates the altitude through the air pressure value measured by the air pressure sensor 180C to assist positioning and navigation.
  • the magnetic sensor 180D includes a Hall sensor.
  • the wearable device may utilize the magnetic sensor 180D to detect opening and closing of the flip holster.
  • the wearable device when the wearable device is a flip phone, the wearable device can detect the opening and closing of the flip according to the magnetic sensor 180D.
  • features such as automatic unlocking of the flip cover are set.
  • the acceleration sensor 180E can detect the acceleration of the wearable device in various directions (generally three axes).
  • the magnitude and direction of gravity can be detected when the wearable device is stationary. It can also be used to recognize the posture of wearable devices, and can be used in applications such as horizontal and vertical screen switching, pedometers, etc.
  • the distance sensor 180F is used to measure the distance. Wearables can measure distance via infrared or laser light. In some embodiments, when shooting a scene, the wearable device can use the distance sensor 180F for distance measurement to achieve fast focusing.
  • Proximity light sensor 180G may include, for example, light emitting diodes (LEDs) and light detectors, such as photodiodes. The light emitting diodes may be infrared light emitting diodes. Wearable devices emit infrared light outwards through light-emitting diodes. Wearable devices use photodiodes to detect reflected infrared light from nearby objects. When sufficient reflected light is detected, it can be determined that there is an object in the vicinity of the wearable device.
  • LEDs light emitting diodes
  • light detectors such as photodiodes.
  • the light emitting diodes may be infrared light emitting diodes.
  • Wearable devices emit infrared light outwards through light-emitting dio
  • the wearable device may determine that there are no objects near the wearable device.
  • the wearable device can use the proximity light sensor 180G to detect that the user holds the wearable device close to the ear to make a call, so as to automatically turn off the screen to save power.
  • the proximity light sensor 180G can also be used in leather case mode, automatic unlock and lock screen in pocket mode.
  • the ambient light sensor 180L is used for sensing ambient light brightness.
  • the wearable device can adaptively adjust the brightness of the display screen 194 according to the perceived ambient light brightness.
  • the ambient light sensor 180L can also be used to automatically adjust the white balance when taking pictures.
  • the ambient light sensor 180L can also cooperate with the proximity light sensor 180G to detect whether the wearable device is in the pocket to prevent accidental touch.
  • the fingerprint sensor 180H is used to collect fingerprints. Wearable devices can use the collected fingerprint features to unlock fingerprints, access application locks, take pictures with fingerprints, answer incoming calls with fingerprints, etc.
  • the temperature sensor 180J is used to detect temperature.
  • the wearable device utilizes the temperature detected by the temperature sensor 180J to implement a temperature handling strategy. For example, when the temperature reported by the temperature sensor 180J exceeds a threshold, the wearable device may reduce the performance of a processor located near the temperature sensor 180J, so as to reduce power consumption and implement thermal protection.
  • the wearable device when the temperature is lower than another threshold, the wearable device heats the battery 142 to avoid abnormal shutdown of the wearable device due to low temperature.
  • the wearable device boosts the output voltage of the battery 142 to avoid abnormal shutdown caused by low temperature.
  • Touch sensor 180K also known as "touch panel”.
  • the touch sensor 180K can be disposed on the display screen 194, and the touch sensor 180K and the display screen 194 form a touch screen, also called a “touch screen”.
  • the touch sensor 180K is used to detect a touch operation on or near it.
  • the touch sensor can pass 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 screen 194 .
  • the touch sensor 180K may also be disposed on the surface of the wearable device, which is different from the position of the display screen 194 .
  • the bone conduction sensor 180M can acquire vibration signals.
  • the bone conduction sensor 180M can acquire the vibration signal of the vibrating bone mass of the human voice.
  • the bone conduction sensor 180M can also contact the human pulse and receive the blood pressure beating signal.
  • the keys 190 include a power key, a volume key and the like.
  • the key 190 may be a mechanical key. It can also be a touch button.
  • the wearable device can receive key input and generate key signal input related to user settings and function control of the wearable device.
  • the motor 191 can generate a vibrating reminder.
  • the motor 191 can be used for incoming call vibration prompts, and can also be used for touch vibration feedback. For example, touch operations applied to different applications (such as taking pictures, playing audio, etc.) may correspond to different vibration feedback effects.
  • the indicator 192 can be an indicator light, and can be used to indicate charging status, power change, and can also be used to indicate messages, missed calls, notifications, and the like.
  • the SIM card interface 195 is used for connecting a SIM card. The SIM card can be inserted into the SIM card interface 195 or pulled out from the SIM card interface 195 to achieve contact and separation with the wearable device.
  • FIG. 1 do not specifically limit the wearable device.
  • the wearable device in the embodiment of the present invention may include more or less components than those shown in FIG. 1 .
  • the combination/connection relationship between the components in FIG. 1 can also be adjusted and modified.
  • the following embodiments take the wearable device as a smart bracelet (bracelet for short) as an example for introduction.
  • FIG. 2 is a schematic flowchart of a method for detecting a sleep state provided in an embodiment of the present application.
  • the method can be executed by a wearable device, or by an electronic device (such as a mobile phone) connected to the wearable device.
  • the following mainly takes the implementation of wearable devices as an example for introduction.
  • the flow process of the method includes:
  • the wearable device judges whether the wearable device is currently in a sleep mode or a non-sleep mode.
  • the sleep mode refers to a mode for detecting a sleep state
  • the non-sleep mode refers to a mode for detecting a daily exercise state (such as running).
  • the calculation process in the background of the wearable device in sleep mode and non-sleep mode is different, and the specific process will be introduced later.
  • a step may also be included: setting the wearable device in a sleep mode or a non-sleep mode.
  • Specific implementation methods include but are not limited to at least one of the following:
  • the wearable device can automatically enter a sleep mode or a non-sleep mode. For example, when the wearable device detects that the current time is sleep time (such as 12:00-1:00 am), it will automatically enter the sleep mode; when the wearable device detects that the current time is the wake-up time (for example, 8:00-9:00 am) , automatically enters non-sleep mode.
  • the specific value of the sleep time and/or wake-up time may be a default value set by the system of the wearable device, or may also be manually input by the user into the setting of the wearable device, which is not limited in this embodiment of the present application.
  • the user can manually set the wearable device to enter the sleep mode or the non-sleep mode.
  • the mode setting icon is displayed on the display screen of the wristband, and when an operation instruction for the icon is detected, the logo and the sleep mode of (b) in FIG. 3 are displayed.
  • the logo of the non-sleep mode the user can select one of the logos to set a certain mode.
  • the wearable device is connected to the mobile phone, and the mobile phone can control the wearable device (for example, an app is set on the mobile phone, and the app is used to control the wearable device), then the user can set the wearable device on the mobile phone to enter sleep mode or non-sleep mode .
  • the following embodiments are introduced by taking the user controlling the wearable device on the mobile phone to set the sleep mode or the non-sleep mode as an example.
  • the sleep flag (flag) in the wearable device is set to the first flag (such as 1), and when the wearable device is in non-sleep mode, the sleep flag in the wearable device is set to the second flag (such as 0). Therefore, in S201, the wearable device can read the sleep flag, if the sleep flag is the first flag, it is determined that it is currently in the sleep mode, and if the sleep flag is the second flag, it is determined that it is currently in the non-sleep mode.
  • the sleep flag (flag) can be stored in the memory and not displayed on the display screen of the wearable device; or, it can also be displayed on the display screen of the wearable device, and the display position can be arbitrary, such as displayed in the status bar (for Display power, operator information, wireless signal mark, etc.).
  • S201 is an optional step, which may or may not be performed, and is not limited in this embodiment of the present application.
  • the wearable device judges whether it is a non-wearing mode in the sleep mode.
  • the sleep mode includes wearing mode and non-wearing mode. If the user chooses the wearing mode, the sleep detection process in the wearing mode can be used. If the user chooses the non-wearing mode, the wearable device can use the non-wearing mode. Sleep detection process.
  • S201 is not executed, S202 is replaced by the wearable device judging whether it is in the non-wearing mode.
  • One possible implementation method is that when the wearable device determines that it is currently in the sleep mode, it can automatically enter the non-wearing mode. For example, when the user or the system has set the current sleep mode in advance, it automatically enters the non-wearing mode.
  • the user can set the wearing mode or the non-wearing mode.
  • the bracelet detects a click operation on the sleep mode logo, it is determined to enter the sleep mode, and the logo of the wearing mode and the non-wearing mode are displayed as shown in (b) in Figure 4
  • the logo of the mode the user can set a certain mode by selecting a logo.
  • the wearable device determines that it is currently in the sleep mode, it detects whether it is currently worn on the user's wrist, and if so, enters the wearing mode; otherwise, enters the non-wearing mode. For example, the wearable device can determine whether the wearable device is worn on the user's wrist through the electrode pads set on the wearable device. For example, when the electrode pad can sense the user's body signal, it is determined that the wearable device is worn on the user's wrist; otherwise, Make sure the wearable is not on the user's wrist.
  • the motion sensor on the wearable device detects whether the wearable device is in a motion state, and if it is in a motion state, it is determined that the wearable device is worn on the user's wrist, otherwise it is determined that the wearable device is not worn on the user's wrist.
  • the wearable device executes the sleep state detection process in wearing mode.
  • the electrodes on the wearable device sense the user's body signal (such as heart rate, pulse, etc.), and judge the sleep state through the body signal. For example, the higher the heart rate, the worse the sleep state. If it is not wearing mode, you can follow the steps below.
  • the wearable device prompts the user whether to fix the device.
  • FIG. 5A For example, please refer to (a) in FIG. 5A.
  • the mobile phone detects a click operation on the non-wearing mode logo, it is determined to enter the non-wearing mode, and a prompt message as shown in (b) in FIG. 5A is displayed: Is the device Fixed, also showing two keys.
  • the mobile phone detects that the user selects the "Yes" button, it determines that the wearable device is fixed.
  • the mobile phone can also prompt the user to fix the device on pillows, mattresses, mattress pads, user pajamas, etc.
  • the wearable device when the wearable device is a bracelet, the bracelet has a detachable module, and the module has a holding device, which can be used to hold on a pillow, pajamas, mattress or bedding.
  • the user buys the wristband, he can purchase it together or the merchant presents a device for binding the wristband, and use the binding device to fix the wristband on the pillow, pajamas, mattress or bedding.
  • the wearable device executes a non-wearing mode detection process to detect the sleep state of the user.
  • the specific implementation process of S204 will be described in detail later.
  • the wearable device outputs a detection result.
  • the wearable device can directly output the detection result, or send the detection result to the mobile phone, and display the detection result through the mobile phone.
  • a step may also be included: stop sleep state detection.
  • the wearable device can automatically stop the sleep state detection, for example, automatically stop the detection (such as exiting the sleep mode) at a specific time (such as 8:00 in the morning), and then execute S205 to output the detection result.
  • the specific time may be set by the user or set by default by the bracelet system.
  • a prompt message is displayed on the mobile phone: Hello, whether to stop sleep detection, and two buttons are also displayed.
  • the detection result is a score value used to represent a sleep state, and a higher score value represents a better sleep quality.
  • the test results may also be in other forms, such as quality levels such as “excellent”, “good”, and “poor”, sleep curves, etc., which are not limited in this embodiment of the present application.
  • FIG. 5C for an example of the detection result.
  • the detection result is a sleep quality report, which includes a sleep quality curve, which is used to characterize the user's sleep quality at different times, and also includes historical records, such as time to fall asleep, sleep duration, Duration of deep sleep, duration of light sleep, etc.
  • the wearable device performs the non-wearing mode detection process to detect the user's sleep state, including at least one of the two detection branches, wherein the first branch It is the first detection result of determining the sleep state of the user through the motion signal, the second branch is the second detection result of determining the sleep state of the user according to the sound signal, and then the final detection result is obtained according to the first detection result and/or the second detection result.
  • the first branch It is the first detection result of determining the sleep state of the user through the motion signal
  • the second branch is the second detection result of determining the sleep state of the user according to the sound signal
  • the final detection result is obtained according to the first detection result and/or the second detection result.
  • Figure 6 it specifically includes the following steps:
  • Step 1 the wearable device collects motion signals.
  • the wearable device can collect motion signals.
  • the motion signal includes, but is not limited to, parameters such as displacement, acceleration, velocity, angular velocity, and angular acceleration.
  • motion sensors accelerometers, gyroscopes, etc.
  • wearable devices can collect motion signals.
  • step 2 the wearable device recognizes body movement characteristics according to the movement signal.
  • the body motion features include, for example, turning over, getting up, shaking, and the like. Assuming that the motion speed collected by the wearable device is greater than the first threshold, it is determined that the user stands up; or, if it is determined that the motion speed is smaller than the second threshold, it is determined that the user turns over.
  • Step 3 the wearable device determines the first detection result according to the body motion feature.
  • the wearable device detects the body movement characteristics in real time, determines the number and/or frequency of body movement characteristics (such as turning over) within a period of time, and determines the first detection result according to the number and/or frequency. For example, the higher the number and/or the higher the frequency, the lower the first detection result.
  • the wearable device detects the body motion feature in real time, determines the intensity of the body motion feature, and determines the first detection result according to the intensity.
  • the strength of turning over can be determined through the motion signal, such as including turning angle (angle change detected by the motion sensor), turning speed (angular velocity detected by the motion sensor), etc., if The greater the intensity, the lower the first detection result, indicating that the sleep quality is worse.
  • the first detection result may be a score value, and the higher the number of times and/or the higher the frequency, the lower the score.
  • the wearable device stores a corresponding relationship between the times and/or frequencies of body movement features as fractional values, and the wearable device may determine the fractional value according to the corresponding relationship.
  • Step 4 the wearable device collects the sound signal.
  • step 5 the wearable device extracts sound features such as the user's snoring sound and breathing sound from the collected sound signal.
  • the collected sound signals include breathing sounds, snoring sounds and the like generated by the user during sleep.
  • the room is a quiet environment when sleeping, so the sound of breathing or snoring is easier to recognize.
  • Step 6 the wearable device determines a second detection result according to the extracted sound signal.
  • the wearable device collects sound signals in real time, can extract continuous breathing sound or snoring sound, and can determine the second detection result according to the number or frequency of breathing sound or snoring sound.
  • the second detection result may be a score value, and the higher the number of times and/or the higher the frequency, the lower the score.
  • the number and/or frequency of breathing sounds or snoring sounds is stored in the wearable device as a fractional relationship, and the wearable device can determine the fractional value according to the corresponding relationship.
  • the wearable device may determine the second detection result according to the sound intensity of the breathing sound or the snoring sound. For example, the louder the sound intensity, the lower the score value.
  • the first detection result can be determined through the motion signal first, and then the second detection result can be determined according to the sound signal; or, The second detection result is first determined according to the sound signal, and then the first detection result is determined through the motion signal; or, both are performed simultaneously, which is not limited in this embodiment of the present application.
  • Step 7 the wearable device obtains the final detection result according to the first detection result and/or the second detection result.
  • Step 7 is to fuse the first detection result and the second detection result to obtain the final detection result.
  • the following describes the process of fusing the first detection result and the second detection result to obtain the final detection result.
  • a first implementation manner is that the first detection result is a first score, the second detection result is a second score, and the final detection result may be an average or a weighted average of the first score and the second score.
  • the weighted average as an example, if the weight of the first branch is higher than that of the second branch, the first weight corresponding to the first score may be higher than the second weight corresponding to the second score.
  • the final detection result P1*X1+P2*X2, where X1 is the first score, X2 is the second score, P1 is the first weight, P2 is the second weight, and P1 is higher than P2.
  • the weight relationship between the first branch and the second branch may be set by default by the system, or set by the user.
  • the first detection result and the second detection result may be the total score for one night.
  • one night can be divided into multiple time periods, and the first detection result and the second detection result in each time period can be counted once, and then the final detection can be obtained according to the statistical results of multiple time periods.
  • the second kind of implementation is that the periodic detection of the first branch (such as step 3) obtains the first detection result, and the periodic detection of the second branch (such as step 6) obtains the second detection result.
  • the first detection result and the second detection result obtain the third detection result in the cycle, so that the third detection results in multiple cycles can be obtained, and the final detection result is obtained according to the third detection results in multiple cycles.
  • the final detection result is the average or weighted average of multiple third detection results.
  • the above table 1 is an example, in cycle 1, the first branch obtains the first test result is 80 points, the second branch obtains the second test result is 90 points, so the third test result is 85 points (with the third test result being The average value of the first test result and the second test result is taken as an example).
  • the first branch obtains the first detection result and is 70 points
  • the second branch obtains the second detection result and is 80 points
  • the third detection result is 75 points (the first detection result and the second detection result are obtained by the third detection result.
  • the average of the two test results is taken as an example).
  • the average of the third test result (ie 85 points) in cycle 1 and the third test result (ie 75 points) in cycle 2 is the final test result. It is understandable that the above Table 1 takes two cycles as an example, but actually may include more cycles, and the more cycles, the more accurate the calculation.
  • the second embodiment takes into account the fact that other people sleep with the user.
  • the wearable device can only detect the sleep state of the user.
  • the application scenario of the second embodiment is to detect the sleep status of a specific user (or target user) in an environment where multiple people are sleeping together.
  • FIG. 7 is a schematic flowchart of a sleep state detection method provided in this embodiment.
  • steps S202-1 and S202-3 are added between S202 and S203.
  • steps S202-1 to S202-3 in FIG. 7 will be introduced below, and other steps in FIG. 7 can be referred to the introduction in FIG. 2 .
  • the wearable device if it is in the non-wearing mode, the wearable device prompts the user whether there are other people around.
  • the second embodiment considers that if it is a multi-person environment, the sound signals collected by the wearable device include the sound signals of multiple people. In order to detect the sleep state of a specific user, it is necessary to collect the The sound signal of the target user is determined from the signal.
  • the target user refers to a user who needs to detect a sleep state when there are multiple people. If there are many people, which person's sleep state is to be detected, and whose voice is recorded.
  • One implementation is, please refer to (a) in FIG. 8A , when the mobile phone detects an operation for the non-wearing mode logo, it displays a prompt message as shown in (b) in FIG. 8A : whether there are other people around, Two keys are also shown.
  • a prompt message as shown in (c) in Figure 8A is displayed: Hello, record 10s of breathing sound, and a prompt message "long press keystroke recording”.
  • an interface as shown in (d) in FIG. 8A is displayed.
  • the display order of the interface in Figure 8A above can be adjusted, for example, please refer to (a) in Figure 8A, when the bracelet detects an operation for the non-wearing mode logo, it will first display (d) in Figure 8A interface, when “Yes” is selected, the interface shown in (b) in FIG. 8A is displayed again.
  • FIG. 8B Another possible way is, please refer to (a) in FIG. 8B.
  • the mobile phone detects an operation for the non-wearing mode logo, it displays a prompt message as shown in (b) in FIG. 8B: Hello, record 10s breathing sound, and the prompt message "long press the button to record” and the prompt message “skip” can also be displayed, which means that the user confirms that if there is no one else around, he can choose to skip this setting process.
  • an interface as shown in (c) in FIG. 8B may be displayed.
  • step 5 shown in FIG. 6 may be refined as: extracting the breathing sound matching the pre-recorded breathing sound from the collected sound signal according to the pre-recorded breathing sound.
  • the sound signal collected by the wearable device includes the breathing sound of all people.
  • the breathing sound of each person has specific characteristics (such as intensity, frequency, duration, etc.) , so according to the pre-recorded breathing sound, the breathing sound of the target user can be identified from the collected sound signals.
  • the target user refers to the user who needs to detect the sleep state in the case of multiple people. Then the breathing sound of which user is extracted.
  • the second embodiment considers that if it is a multi-person environment, everyone may have actions such as turning over and getting up when sleeping, which may drive the movement of the mattress (assuming that the wearable device is fixed on the mattress), and then Drive the wearable device to move, so the motion signal collected by the wearable device includes motion signals corresponding to multiple people. In order to more accurately detect the sleep state of a specific user, the user can be prompted to place the wearable device near the specific user.
  • the interface shown in (e) in Figure 9 can also be displayed, and the interface prompts information: the device is on your left Still on the right side, assuming that the wristband detects that the user selects the left side, it means that the specific user who needs to detect the sleep state is on the right side of the device, then when the wristband detects a motion signal, it will filter the motion signal from the left side and keep the motion signal from the right side. side motion signal (that is, the motion signal corresponding to the target user), and then determine the first detection result of the target user according to the retained motion signal.
  • side motion signal that is, the motion signal corresponding to the target user
  • Embodiment 1 is called single-person detection mode
  • the method of Embodiment 2 is called non-single-person detection mode (or multi-person detection mode)
  • the user can choose to use the single person detection mode or the non-single person detection mode.
  • a prompt message as shown in (b) in Figure 10 is displayed: Hello, please select the following mode, An icon for Solo detection mode and an icon for non-Solo detection are also displayed.
  • the mobile phone detects that the user selects the single-person detection mode it is determined that it is a single-person environment (that is, there are no other people in the environment), and the method of Embodiment 1 (such as the process shown in Figure 2) can be used for processing.
  • the display is as follows The interface shown in (c) in FIG. 10 .
  • a prompt message as shown in (b) in Figure 11 is displayed: Hello, please select the following mode, An icon for Solo detection mode and an icon for non-Solo detection are also displayed.
  • the mobile phone detects that the user selects the non-single-person mode it is determined that it is a non-single-person environment (that is, there are other people in the environment), and the method of Embodiment 2 (such as the process shown in FIG. 7 ) is used for processing.
  • an interface as shown in (c) in FIG. 11 is displayed, and prompt information is displayed in the interface for prompting the user to record breathing sounds.
  • an interface as shown in (d) in FIG. 11 is displayed.
  • the previous embodiment 1 is a single-person detection mode
  • embodiment 2 is a non-single-person detection mode.
  • This embodiment 3 introduces a non-single-person overall detection mode.
  • embodiment 2 detects a multi-person environment
  • the third embodiment detects the overall sleep state of all people in a multi-person environment.
  • the realization principle of the third embodiment is the same as the realization principle of the foregoing first embodiment.
  • the motion signals collected by the wearable device include the motion signals of multiple people, which can be understood as the total motion signal, and the sound collected by the wearable device
  • the signal includes sound signals of multiple people (such as breathing sounds of multiple people), which can be understood as a total sound signal.
  • determine the first detection result for characterizing the overall sleep state of multiple people according to the total motion signal determine the second detection result for characterizing the overall sleep state of multiple people according to the total sound signal, according to the first detection result
  • the second detection result determines the final detection result used to characterize the sleep state of multiple people.
  • the interface shown in (b) in Figure 12 is displayed, and the interface includes a single person detection mode , non-single-person individual detection mode, non-single-person overall detection mode, when the mobile phone detects that the user has selected a non-single-person overall detection mode, an interface as shown in (c) in Figure 12 is displayed, which is used to prompt whether the device fixed.
  • the implementation principle of the third embodiment is the same as that of the first embodiment, that is, the flow chart shown in Figure 2, specifically, the details collected in the first branch of the refinement process in S204 in Figure 2 (that is, Figure 6).
  • the motion signal reflects the sum of the movements generated by each person's turning over, getting up and other actions when multiple people are sleeping.
  • the sound signals collected by the second branch include the sound signals generated by each person during multiple people's sleep.
  • FIG. 13 shows an electronic device 1300 provided by this application.
  • the electronic device 1300 may be the aforementioned mobile phone or wearable device.
  • the electronic device 1300 may include: one or more processors 1301; one or more memories 1302; a communication interface 1303, and one or more computer programs 1304, and each of the above devices may communicate through one or more Bus 1305 connection.
  • the one or more computer programs 1304 are stored in the memory 1302 and are configured to be executed by the one or more processors 1301, the one or more computer programs 1304 include instructions, and the instructions can be used to perform the above Relevant steps of the mobile phone in the corresponding embodiment.
  • the communication interface 1303 is used to implement communication with other devices, for example, the communication interface may be a transceiver.
  • the methods provided in the embodiments of the present application are introduced from the perspective of an electronic device (such as a mobile phone) as an execution subject.
  • the electronic device may include a hardware structure and/or a software module, and realize the above-mentioned functions in the form of a hardware structure, a software module, or a hardware structure plus a software module. Whether one of the above-mentioned functions is executed in the form of a hardware structure, a software module, or a hardware structure plus a software module depends on the specific application and design constraints of the technical solution.
  • the terms “when” or “after” may be interpreted to mean “if” or “after” or “in response to determining" or “in response to detecting ".
  • the phrases “in determining” or “if detected (a stated condition or event)” may be interpreted to mean “if determining" or “in response to determining" or “on detecting (a stated condition or event)” or “in response to detecting (a stated condition or event)”.
  • relational terms such as first and second are used to distinguish one entity from another, without limiting any actual relationship and order between these entities.
  • references to "one embodiment” or “some embodiments” or the like in this specification means that a particular feature, structure, or characteristic described in connection with the embodiment is included in one or more embodiments of the present application.
  • appearances of the phrases “in one embodiment,” “in some embodiments,” “in other embodiments,” “in other embodiments,” etc. in various places in this specification are not necessarily All refer to the same embodiment, but mean “one or more but not all embodiments” unless specifically stated otherwise.
  • the terms “including”, “comprising”, “having” and variations thereof mean “including but not limited to”, unless specifically stated otherwise.
  • all or part of them may be implemented by software, hardware, firmware or any combination thereof.
  • software When implemented using software, it may be implemented in whole or in part in the form of a computer program product.
  • the computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on the computer, the processes or functions according to the embodiments of the present invention will be generated in whole or in part.
  • the computer can be a general purpose computer, a special purpose computer, a computer network, or other programmable devices.
  • the computer instructions may be stored in or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from a website, computer, server or data center Transmission to another website site, computer, server, or data center by wired (eg, coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (eg, infrared, wireless, microwave, etc.).
  • the computer-readable storage medium may be any available medium that can be accessed by a computer, or a data storage device such as a server or a data center integrated with one or more available media.
  • the available medium may be a magnetic medium (for example, a floppy disk, a hard disk, or a magnetic tape), an optical medium (for example, DVD), or a semiconductor medium (for example, a Solid State Disk (SSD)).
  • a magnetic medium for example, a floppy disk, a hard disk, or a magnetic tape
  • an optical medium for example, DVD
  • a semiconductor medium for example, a Solid State Disk (SSD)

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Abstract

Procédé de test d'état de sommeil appliqué à un dispositif portable. Le procédé consiste : à collecter, par un dispositif vestimentaire, des données de comportement générées pendant le sommeil d'un utilisateur cible, les données de comportement comprenant un signal de mouvement et/ou un signal sonore, le signal de mouvement servant à déterminer un premier résultat de test représentant un état de sommeil de l'utilisateur cible et le signal sonore servant à déterminer un second résultat de test représentant l'état de sommeil de l'utilisateur cible ; et à déterminer un résultat final de test de l'état de sommeil de l'utilisateur cible, selon le premier résultat de test et/ou selon le second résultat de test.
PCT/CN2022/090568 2021-05-12 2022-04-29 Procédé de test d'état de sommeil et dispositif électronique WO2022237598A1 (fr)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116491902A (zh) * 2023-04-19 2023-07-28 深圳市金东方电子有限公司 一种基于智能手表的睡眠监测系统

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106897576A (zh) * 2017-04-17 2017-06-27 安徽咏鹅家纺股份有限公司 一种智能睡眠监测及助眠云服务系统
CN108937866A (zh) * 2018-06-29 2018-12-07 出门问问信息科技有限公司 睡眠状态的监测方法及装置
US20190215611A1 (en) * 2016-07-29 2019-07-11 Goertek Inc. Wearing state detection method for wearable device, and wearable device
CN110134229A (zh) * 2019-03-22 2019-08-16 华为技术有限公司 一种可穿戴设备及活动数据采集方法
CN110687835A (zh) * 2018-07-06 2020-01-14 医博科技股份有限公司 睡眠质量改善方法与枕具
US20200178887A1 (en) * 2016-04-29 2020-06-11 Fitbit, Inc. Sleep monitoring system with optional alarm functionality
CN111657890A (zh) * 2020-06-23 2020-09-15 深圳市联奕实业有限公司 睡眠状态的监控方法、装置、智能床垫及介质

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20200178887A1 (en) * 2016-04-29 2020-06-11 Fitbit, Inc. Sleep monitoring system with optional alarm functionality
US20190215611A1 (en) * 2016-07-29 2019-07-11 Goertek Inc. Wearing state detection method for wearable device, and wearable device
CN106897576A (zh) * 2017-04-17 2017-06-27 安徽咏鹅家纺股份有限公司 一种智能睡眠监测及助眠云服务系统
CN108937866A (zh) * 2018-06-29 2018-12-07 出门问问信息科技有限公司 睡眠状态的监测方法及装置
CN110687835A (zh) * 2018-07-06 2020-01-14 医博科技股份有限公司 睡眠质量改善方法与枕具
CN110134229A (zh) * 2019-03-22 2019-08-16 华为技术有限公司 一种可穿戴设备及活动数据采集方法
CN111657890A (zh) * 2020-06-23 2020-09-15 深圳市联奕实业有限公司 睡眠状态的监控方法、装置、智能床垫及介质

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116491902A (zh) * 2023-04-19 2023-07-28 深圳市金东方电子有限公司 一种基于智能手表的睡眠监测系统

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