WO2023273834A1 - 一种检测方法及相关设备 - Google Patents

一种检测方法及相关设备 Download PDF

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Publication number
WO2023273834A1
WO2023273834A1 PCT/CN2022/098155 CN2022098155W WO2023273834A1 WO 2023273834 A1 WO2023273834 A1 WO 2023273834A1 CN 2022098155 W CN2022098155 W CN 2022098155W WO 2023273834 A1 WO2023273834 A1 WO 2023273834A1
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information
electronic device
user interface
physiological parameter
physiological
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PCT/CN2022/098155
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English (en)
French (fr)
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许德省
李靖
许培达
沈东崎
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华为技术有限公司
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Publication of WO2023273834A1 publication Critical patent/WO2023273834A1/zh

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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
    • A61B5/01—Measuring temperature of body parts ; Diagnostic temperature sensing, e.g. for malignant or inflamed tissue
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/0002—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network
    • A61B5/0015—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network characterised by features of the telemetry system
    • A61B5/0022—Monitoring a patient using a global network, e.g. telephone networks, internet
    • 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
    • A61B5/0205—Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
    • A61B5/02055—Simultaneously evaluating both cardiovascular condition and temperature
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/08—Detecting, measuring or recording devices for evaluating the respiratory organs
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
    • A61B5/14542—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue for measuring blood gases
    • 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
    • A61B5/4803—Speech analysis specially adapted for diagnostic purposes
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/74—Details of notification to user or communication with user or patient ; user input means
    • A61B5/746—Alarms related to a physiological condition, e.g. details of setting alarm thresholds or avoiding false alarms
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/74—Details of notification to user or communication with user or patient ; user input means
    • A61B5/7465—Arrangements for interactive communication between patient and care services, e.g. by using a telephone network
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B7/00—Instruments for auscultation
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B7/00—Instruments for auscultation
    • A61B7/003—Detecting lung or respiration noise
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B7/00—Instruments for auscultation
    • A61B7/02—Stethoscopes

Definitions

  • the present application relates to the field of computer technology, in particular to a detection method and related equipment.
  • Respiratory system disease is a common and frequently-occurring disease with complex disease types and an increasing incidence rate year by year. Among them, lower respiratory tract infection seriously affects health and has a high fatality rate. Respiratory infections have similar symptoms such as cough, fever, and difficulty breathing. Clinical manifestations of severe acute respiratory infection include, for example, axillary body temperature ⁇ 3 ⁇ °C, cough or sore throat, shortness of breath (respiratory rate ⁇ 25 breaths/minute) or dyspnea. Among respiratory infections, pneumonia is the most severe. Pneumonia is an acute respiratory disease that is perceived by the user, progresses rapidly, and has many types. When the pathogen grows beyond the host's defense capacity, it will cause exudate in the alveolar cavity and cause pneumonia. Typical symptoms of pneumonia are cough, sputum production, shortness of breath, dyspnea, fever, and fixed lung rales.
  • the user usually goes to a professional place such as a hospital by himself, and the professional staff makes a diagnosis through chest imaging, blood routine, sputum culture and other technologies.
  • a diagnosis is complicated, expensive, and poor in comfort. Time-consuming and labor-intensive, it is difficult to meet the needs of convenience and high efficiency of daily testing.
  • the embodiment of the present application discloses a detection method and related equipment, which can allow users to conveniently detect the infection risk of the respiratory system, while ensuring the accuracy of the detection results and low power consumption of the equipment.
  • the embodiment of the present application provides a detection method, which is applied to the first electronic device, and the method includes: detecting the first operation; in response to the first operation, sending the first information to the second electronic device; receiving the above-mentioned
  • the second electronic device sends the physiological parameter information based on the above-mentioned first information; when it is determined that the above-mentioned physiological parameter information satisfies the preset condition, acquires the audio information; determines the first physiological information according to the above-mentioned physiological parameter information and the above-mentioned audio information; displays the above-mentioned first physiological information.
  • the first electronic device is a mobile terminal, such as a smart phone
  • the second electronic device is a wearable device, such as a smart bracelet or a smart watch.
  • the first physiological information is used to indicate the infection risk level of the user's respiratory system, such as low risk, medium risk or high risk, or such as no abnormality, respiratory tract infection risk or pneumonia risk.
  • the user can detect the infection risk of the respiratory system (that is, obtain the first physiological information) through the first electronic device and the second electronic device, and the first physiological information is determined by combining physiological parameters and audio information, and the accuracy of the detection result High performance, to meet the needs of convenience and efficiency.
  • the audio information is acquired (for example, the microphone is turned on to collect audio information), which reduces the power consumption of electronic equipment and makes the product more competitive.
  • the above physiological parameter information includes one or more of the following: body temperature, blood oxygen saturation, respiratory rate, heart rate, pulse, and the above audio information includes one or more of the following: cough sound, breathing sounds, heart sounds, lung sounds.
  • the above preset conditions include one or more of the following: body temperature is greater than or equal to the preset body temperature threshold, blood oxygen saturation is less than or equal to the preset blood oxygen threshold, and the respiratory rate is greater than or equal to the preset Frequency threshold, the heart rate is greater than or equal to the preset heart rate threshold, and the pulse is greater than or equal to the preset pulse threshold.
  • the physiological parameter information is periodically sent by the second electronic device based on the first information.
  • the above-mentioned first operation is used to enable the function of periodically collecting the physiological parameter information
  • the above-mentioned first information is used to instruct the above-mentioned second electronic device to periodically collect the above-mentioned physiological parameter information.
  • the physiological parameter information is collected periodically, which can also be understood as being collected for a long time.
  • the first physiological information is determined through such physiological parameter information, which avoids the influence of accidental conditions and has higher accuracy.
  • the foregoing first information is used to instruct the foregoing second electronic device to collect the foregoing physiological parameter information within a first collection period.
  • the acquiring audio information when it is determined that the physiological parameter information satisfies the preset condition includes: displaying a first user interface when it is determined that the physiological parameter information satisfies the preset condition, and the first The user interface includes second information for prompting the detection of the audio information; detecting a second operation acting on the first user interface; displaying the second user interface in response to the second operation; collecting the audio based on the second user interface information.
  • the method further includes: detecting a first collection operation acting on the second user interface, and in response to the first collection operation, turning on the microphone of the first electronic device to collect the audio information.
  • the above-mentioned audio information is collected by the above-mentioned first electronic device within the second collection period.
  • the first electronic device when the physiological parameters meet the preset conditions, the first electronic device prompts the user to detect audio information, and then displays the user interface for collecting audio information and turns on the microphone to collect audio information when a user operation is subsequently detected, instead of At the beginning, the microphone is turned on to collect audio information, so as to reduce the power consumption of the first electronic device.
  • the acquiring audio information when it is determined that the physiological parameter information satisfies the preset condition includes: when it is determined that the physiological parameter information satisfies the preset condition, sending a third information, the third information is used by the second electronic device to display a third user interface, and the third user interface is used to collect the audio information; receive the audio information sent by the second electronic device.
  • the above-mentioned third information is specifically used for the above-mentioned second electronic device to display prompt information first, and the prompt information is used to prompt to detect the above-mentioned audio information, and when the second collection operation is detected, display the information of the collected audio information Third user interface. In some embodiments, when the second electronic device displays the third user interface, the microphone is turned on to collect audio information.
  • the first electronic device sends the third information to the second electronic device, so that the second electronic device prompts the user to detect the audio information, and then the second electronic device detects the user's operation Next, display the user interface for collecting audio information, and turn on the microphone to collect audio information, instead of turning on the microphone to collect audio information at the beginning, so as to reduce the power consumption of the second electronic device.
  • the above-mentioned first physiological information is used to characterize the infection risk of the user's respiratory system
  • the above-mentioned determining the first physiological information according to the above-mentioned physiological parameter information and the above-mentioned audio information includes: characterizing the above-mentioned physiological parameter information Extracting to obtain the first feature, performing feature extraction on the above audio information to obtain the second feature; encoding the above first feature and the above second feature to obtain the first code; classifying the above first code to determine the above first physiological information.
  • the method further includes: sending the first physiological information to the second electronic device.
  • the embodiment of the present application provides yet another detection method, which is applied to the first electronic device, and the method includes: receiving the first information sent by the second electronic device, the above-mentioned first information is used to indicate that the physiological parameter information satisfies the predetermined Set a condition; display a first user interface according to the above-mentioned first information, and the above-mentioned first user interface includes second information for prompting detection of audio information; detect a first operation acting on the above-mentioned first user interface; respond to the above-mentioned first Operation, displaying a second user interface, where the second user interface is used to acquire the audio information; determine the first physiological information according to the physiological parameter information and the audio information; and display the first physiological information.
  • the first electronic device is a mobile terminal, such as a smart phone
  • the second electronic device is a wearable device, such as a smart bracelet or a smart watch.
  • the first physiological information is used to indicate the infection risk level of the user's respiratory system, such as low risk, medium risk or high risk, or such as no abnormality, respiratory tract infection risk or pneumonia risk.
  • the user can detect the infection risk of the respiratory system (that is, obtain the first physiological information) through the first electronic device and the second electronic device, and the first physiological information is determined by combining physiological parameters and audio information, and the accuracy of the detection result High performance, to meet the needs of convenience and efficiency.
  • the physiological parameters meet the preset conditions
  • the user is prompted to detect audio information, and when the user operation is detected subsequently, the user interface for collecting audio information is displayed, and the microphone is turned on to collect audio information, instead of turning on the microphone to collect audio at the beginning information, reducing power consumption of the first electronic device.
  • the above physiological parameter information includes one or more of the following: body temperature, blood oxygen saturation, respiratory rate, heart rate, pulse, and the above audio information includes one or more of the following: cough sound, breathing sounds, heart sounds, lung sounds.
  • the above preset conditions include one or more of the following: body temperature is greater than or equal to the preset body temperature threshold, blood oxygen saturation is less than or equal to the preset blood oxygen threshold, and the respiratory rate is greater than or equal to the preset Frequency threshold, the heart rate is greater than or equal to the preset heart rate threshold, and the pulse is greater than or equal to the preset pulse threshold.
  • the method before receiving the first information sent by the second electronic device, the method further includes: detecting a second operation; in response to the second operation, sending third information to the second electronic device, The first information is determined by the second electronic device based on the third information.
  • the method further includes: the second electronic device sending the physiological parameter information to the first electronic device.
  • the above physiological parameter information is sent together with the above first information.
  • the third information is used to instruct the second electronic device to collect the physiological parameter information. In some embodiments, the third information is used to instruct the second electronic device to send the first information to the first electronic device when it determines that the physiological parameter information satisfies the preset condition.
  • the first information is determined by the second electronic device in response to the detected third operation.
  • the second electronic device after the second electronic device collects the physiological parameter information, it can judge whether the physiological parameter information meets the preset conditions, and notify the first electronic device when the physiological parameter information meets the preset conditions.
  • the first electronic device only needs to collect audio information and determine the first physiological information, reducing the processing pressure of the first electronic device.
  • the method before displaying the first user interface according to the first information, the method further includes: displaying a third user interface according to the first information, where the third user interface includes the second The lock screen interface of the information; detecting the unlocking operation; displaying the first user interface according to the first information includes: displaying the first user interface according to the first information in response to the unlocking operation.
  • displaying the first user interface according to the first information in response to the unlocking operation includes: performing user identity authentication in response to the unlocking operation, and when it is determined that the identity authentication is passed, displaying the first user interface according to the first information The information displays the above-mentioned first user interface.
  • the above-mentioned first physiological information is used to characterize the infection risk of the user's respiratory system
  • the above-mentioned determining the first physiological information according to the above-mentioned physiological parameter information and the above-mentioned audio information includes: characterizing the above-mentioned physiological parameter information Extracting to obtain the first feature, performing feature extraction on the above audio information to obtain the second feature; encoding the above first feature and the above second feature to obtain the first code; classifying the above first code to determine the above first physiological information.
  • the method further includes: sending the first physiological information to the second electronic device.
  • the embodiment of the present application provides yet another detection method, which is applied to the first electronic device, and the method includes: collecting physiological parameter information; when it is determined that the above physiological parameter information satisfies a preset condition, displaying a first user interface,
  • the above-mentioned first user interface includes first information for prompting detection of audio information; detecting a first operation acting on the above-mentioned first user interface; in response to the above-mentioned first operation, displaying a second user interface, and the above-mentioned second user interface is used for Acquiring the above audio information; determining first physiological information according to the above physiological parameter information and the above audio information; displaying the above first physiological information.
  • the first physiological information is used to indicate the infection risk level of the user's respiratory system, such as low risk, medium risk or high risk, or such as no abnormality, respiratory tract infection risk or pneumonia risk.
  • the user can detect the infection risk of the respiratory system through the first electronic device (that is, obtain the first physiological information), and the first physiological information is determined by combining physiological parameters and audio information.
  • the accuracy of the detection result is high and the convenience is met. and efficiency needs.
  • the user is prompted to detect audio information, and when the user operation is detected subsequently, the user interface for collecting audio information is displayed, and the microphone is turned on to collect audio information, instead of turning on the microphone to collect audio at the beginning information, reducing power consumption of the first electronic device.
  • the above physiological parameter information includes one or more of the following: body temperature, blood oxygen saturation, respiratory rate, heart rate, pulse, and the above audio information includes one or more of the following: cough sound, breathing sounds, heart sounds, lung sounds.
  • the above preset conditions include one or more of the following: body temperature is greater than or equal to the preset body temperature threshold, blood oxygen saturation is less than or equal to the preset blood oxygen threshold, and the respiratory rate is greater than or equal to the preset Frequency threshold, the heart rate is greater than or equal to the preset heart rate threshold, and the pulse is greater than or equal to the preset pulse threshold.
  • the method before the above-mentioned collection of physiological parameter information, the method further includes: detecting a second operation; the above-mentioned collection of physiological parameter information includes: collecting the above-mentioned physiological parameter information in response to the above-mentioned second operation.
  • the above-mentioned second operation is used to enable the function of periodically collecting physiological parameter information, and the above-mentioned physiological parameter information is periodically collected by the above-mentioned first electronic device. In some other embodiments, the above physiological parameter information is collected during the first collection period.
  • the physiological parameters can be collected periodically to avoid the influence of accidental conditions and have higher accuracy, or to collect within the preset first collection period to reduce power consumption of the device.
  • the acquisition mode of the physiological parameters may be determined according to the second operation, which is more flexible and meets user needs.
  • the method before collecting the physiological parameter information, further includes: receiving second information sent by the second electronic device, where the second information is the third operation detected by the second electronic device in response to Hence; the above-mentioned collection of physiological parameter information includes: collecting the above-mentioned physiological parameter information based on the above-mentioned second information.
  • the first electronic device is a wearable device, such as a smart bracelet or a smart watch.
  • the second electronic device is a mobile terminal, such as a smart phone.
  • the user operation that triggers the acquisition of the first physiological information may not only act on the first electronic device, but also act on the second electronic device, and the method of detecting the infection risk of the respiratory system is more flexible.
  • the above-mentioned first physiological information is used to characterize the infection risk of the user's respiratory system
  • the above-mentioned determining the first physiological information according to the above-mentioned physiological parameter information and the above-mentioned audio information includes: characterizing the above-mentioned physiological parameter information Extracting to obtain the first feature, performing feature extraction on the above audio information to obtain the second feature; encoding the above first feature and the above second feature to obtain the first code; classifying the above first code to determine the above first physiological information.
  • the method further includes: sending the first physiological information to the second electronic device.
  • the embodiment of the present application provides yet another detection method, which is applied to the first electronic device, and the method includes: detecting the first operation; in response to the above-mentioned first operation, sending the first information to the second electronic device; receiving The physiological parameter information sent by the second electronic device based on the first information; when it is determined that the physiological parameter information satisfies the preset condition, collect audio information; determine the first physiological information according to the physiological parameter information and the audio information; display the first physiological information - Physiological information.
  • collecting the audio information includes: when it is determined that the above-mentioned physiological parameter information satisfies the above-mentioned preset condition, turning on the microphone of the above-mentioned first electronic device to collect the above-mentioned audio information .
  • the audio information is collected by the first electronic device during the first collection period.
  • the user can detect the infection risk of the respiratory system (that is, obtain the first physiological information) through the first electronic device and the second electronic device, and the first physiological information is determined by combining physiological parameters and audio information, and the accuracy of the detection result High performance, to meet the needs of convenience and efficiency.
  • the first electronic device automatically turns on the microphone to collect audio information instead of turning on the microphone to collect audio information at the beginning, which reduces the power consumption of the first electronic device, and the user does not need to manually detect the audio information. It is more convenient to use.
  • the first electronic device is a mobile terminal, such as a smart phone
  • the second electronic device is a wearable device, such as a smart bracelet or a smart watch.
  • the first physiological information is used to indicate the infection risk level of the user's respiratory system, such as low risk, medium risk or high risk, or for example no abnormality, respiratory infection risk or pneumonia risk.
  • the above physiological parameter information includes one or more of the following: body temperature, blood oxygen saturation, respiratory rate, heart rate, pulse, and the above audio information includes one or more of the following: cough sound, breathing sounds, heart sounds, lung sounds.
  • the above preset conditions include one or more of the following: body temperature is greater than or equal to the preset body temperature threshold, blood oxygen saturation is less than or equal to the preset blood oxygen threshold, and the respiratory rate is greater than or equal to the preset Frequency threshold, the heart rate is greater than or equal to the preset heart rate threshold, and the pulse is greater than or equal to the preset pulse threshold.
  • the embodiment of the present application provides yet another detection method, which is applied to the first electronic device, and the method includes: receiving the first information sent by the second electronic device, the above-mentioned first information is used to indicate that the physiological parameter information satisfies the predetermined Setting conditions; collecting audio information according to the first information; determining first physiological information according to the physiological parameter information and the audio information; displaying the first physiological information.
  • the above-mentioned collecting audio information according to the above-mentioned first information includes: according to the above-mentioned first information, turning on the microphone of the above-mentioned first electronic device to collect the above-mentioned audio information.
  • the audio information is collected by the first electronic device during the first collection period.
  • the user can detect the infection risk of the respiratory system (that is, obtain the first physiological information) through the first electronic device and the second electronic device, and the first physiological information is determined by combining physiological parameters and audio information, and the accuracy of the detection result High performance, to meet the needs of convenience and efficiency.
  • the first electronic device automatically turns on the microphone to collect audio information, instead of turning on the microphone to collect audio information at the beginning, so as to reduce the power consumption of the first electronic device, and the user does not need to Manually detect audio information, which is more convenient to use.
  • the first electronic device is a mobile terminal, such as a smart phone
  • the second electronic device is a wearable device, such as a smart bracelet or a smart watch.
  • the first physiological information is used to indicate the infection risk level of the user's respiratory system, such as low risk, medium risk or high risk, or for example no abnormality, respiratory infection risk or pneumonia risk.
  • the above physiological parameter information includes one or more of the following: body temperature, blood oxygen saturation, respiratory rate, heart rate, pulse, and the above audio information includes one or more of the following: cough sound, breathing sounds, heart sounds, lung sounds.
  • the above preset conditions include one or more of the following: body temperature is greater than or equal to the preset body temperature threshold, blood oxygen saturation is less than or equal to the preset blood oxygen threshold, and the respiratory rate is greater than or equal to the preset Frequency threshold, the heart rate is greater than or equal to the preset heart rate threshold, and the pulse is greater than or equal to the preset pulse threshold.
  • the method before receiving the first information sent by the second electronic device, the method further includes: detecting a first operation; in response to the first operation, sending the second information to the second electronic device, The first information is determined by the second electronic device based on the second information.
  • the method further includes: the second electronic device sending the physiological parameter information to the first electronic device.
  • the above physiological parameter information is sent together with the above first information.
  • the second information is used to instruct the second electronic device to collect the physiological parameter information. In some embodiments, the second information is used to instruct the second electronic device to send the first information to the first electronic device when it determines that the physiological parameter information satisfies the preset condition.
  • the first information is determined by the second electronic device in response to the detected second operation.
  • the second electronic device after the second electronic device collects the physiological parameter information, it can judge whether the physiological parameter information meets the preset conditions, and notify the first electronic device when the physiological parameter information meets the preset conditions.
  • the first electronic device only needs to collect audio information and determine the first physiological information, reducing the processing pressure of the first electronic device.
  • the embodiment of the present application provides yet another detection method, which is applied to the first electronic device.
  • the method includes: collecting physiological parameter information; collecting audio information when it is determined that the above physiological parameter information satisfies a preset condition; according to the above-mentioned The physiological parameter information and the above-mentioned audio information determine the first physiological information; and display the above-mentioned first physiological information.
  • collecting the audio information includes: when it is determined that the above-mentioned physiological parameter information satisfies the above-mentioned preset condition, turning on the microphone of the above-mentioned first electronic device to collect the above-mentioned audio information .
  • the audio information is collected by the first electronic device during the first collection period.
  • the user can detect the infection risk of the respiratory system through the first electronic device (that is, obtain the first physiological information), and the first physiological information is determined by combining physiological parameters and audio information.
  • the accuracy of the detection result is high and the convenience is met. and efficiency requirements.
  • the first electronic device automatically turns on the microphone to collect audio information instead of turning on the microphone to collect audio information at the beginning, which reduces the power consumption of the first electronic device, and the user does not need to manually detect the audio information. It is more convenient to use.
  • the method before the above-mentioned collection of physiological parameter information, the method further includes: detecting a first operation; the above-mentioned collection of physiological parameter information includes: collecting the above-mentioned physiological parameter information in response to the above-mentioned first operation.
  • the above-mentioned first operation is used to enable the function of periodically collecting physiological parameter information, and the above-mentioned physiological parameter information is periodically collected by the above-mentioned first electronic device. In some other embodiments, the above physiological parameter information is collected during the first collection period.
  • the physiological parameters can be collected periodically to avoid the influence of accidental conditions and have higher accuracy, or to collect within the preset first collection period to reduce power consumption of the device.
  • the acquisition mode of the physiological parameters may be determined according to the first operation, which is more flexible and meets user needs.
  • the method before collecting the physiological parameter information, further includes: receiving first information sent by the second electronic device, where the first information is the response of the second electronic device to the detected second operation Hence; the above-mentioned collection of physiological parameter information includes: collecting the above-mentioned physiological parameter information based on the above-mentioned first information.
  • the first electronic device is a wearable device, such as a smart bracelet or a smart watch.
  • the second electronic device is a mobile terminal, such as a smart phone.
  • the user operation that triggers the acquisition of the first physiological information may not only act on the first electronic device, but also act on the second electronic device, and the method of detecting the infection risk of the respiratory system is more flexible.
  • the first physiological information is used to indicate the infection risk level of the user's respiratory system, such as low risk, medium risk or high risk, or for example no abnormality, respiratory infection risk or pneumonia risk.
  • the above physiological parameter information includes one or more of the following: body temperature, blood oxygen saturation, respiratory rate, heart rate, pulse, and the above audio information includes one or more of the following: cough sound, breathing sounds, heart sounds, lung sounds.
  • the above preset conditions include one or more of the following: body temperature is greater than or equal to the preset body temperature threshold, blood oxygen saturation is less than or equal to the preset blood oxygen threshold, and the respiratory rate is greater than or equal to the preset Frequency threshold, the heart rate is greater than or equal to the preset heart rate threshold, and the pulse is greater than or equal to the preset pulse threshold.
  • the embodiment of the present application provides an electronic device, including a transceiver, a processor, and a memory, the memory is used to store a computer program, and the processor invokes the computer program to execute the first aspect of the embodiment of the present application to the sixth aspect, and the detection method provided by any implementation manner of the first aspect to the sixth aspect.
  • the embodiments of the present application provide a computer storage medium, the computer storage medium stores a computer program, and when the computer program is executed by a processor, the first to sixth aspects of the embodiment of the present application, and the first The detection method provided by any one of the implementation manners from the aspect to the sixth aspect.
  • the embodiment of the present application provides a computer program product, which, when the computer program product is run on the electronic device, causes the electronic device to execute the first aspect to the sixth aspect, and the first aspect to the sixth aspect of the embodiment of the present application.
  • the detection method provided by any one of the implementation manners of the sixth aspect.
  • the embodiments of the present application provide an electronic device, where the electronic device includes executing the method or apparatus introduced in any embodiment of the present application.
  • the aforementioned electronic device is, for example, a chip.
  • FIG. 1 is a schematic diagram of a hardware structure of an electronic device provided in an embodiment of the present application
  • FIG. 2 is a schematic diagram of a software architecture of an electronic device provided in an embodiment of the present application.
  • Figures 3-13 are schematic diagrams of some user interface embodiments provided by the embodiments of the present application.
  • Figure 14- Figure 17 are schematic diagrams of cooperation of some detection methods provided by the embodiments of the present application.
  • Figure 1 ⁇ is a schematic flow diagram of a detection method provided in the embodiment of the present application.
  • Fig. 19 is a schematic structural diagram of another electronic device provided by the embodiment of the present application.
  • Fig. 20 is a schematic diagram of a method for determining the infection risk of the respiratory system provided by the embodiment of the present application.
  • the embodiment of the present application provides a detection method, which is applied to the first device and the second device.
  • the first device can collect the user's physiological parameters (such as body temperature, blood oxygen saturation, respiratory rate, heart rate, pulse, etc.), and can also collect the user's audio data (such as cough sounds, breath sounds, heart sounds, lung sounds, etc.).
  • the second device may acquire the infection risk of the user's respiratory system based on the collected physiological parameters and audio data, such as no abnormality, risk of respiratory tract infection, or risk of pneumonia. Users can screen for respiratory diseases anytime, anywhere through the first device and the second device.
  • the cost is low, which meets the convenience and efficiency requirements of daily detection, and realizes the monitoring and early warning of respiratory diseases, such as Reminding users to see a doctor before or at the time of onset is of positive significance for users to perceive and intervene early, and improve user awareness and doctor visit rate.
  • the embodiment of the present application may start the module for collecting audio data (referred to as the audio data collection module, such as a microphone) when the physiological parameters are abnormal, and the audio data collected by the audio data collection module is used to determine the respiratory system. Infection risk, saving equipment power consumption, higher product availability.
  • the audio data collection module such as a microphone
  • the electronic devices involved in the embodiments of the present application may be user terminal devices such as mobile phones, tablet computers, handheld computers, personal digital assistants (Personal Digital Assistant, PDA), smart home devices such as smart TVs and smart cameras, smart bracelets, smart watches, etc. , smart glasses and other wearable devices, or other desktops, laptops, notebooks, ultra-mobile personal computers (Ultra-mobile Personal Computer, UMPC), netbooks, smart screens and other devices.
  • PDA Personal Digital Assistant
  • smart home devices such as smart TVs and smart cameras, smart bracelets, smart watches, etc.
  • smart glasses and other wearable devices or other desktops, laptops, notebooks, ultra-mobile personal computers (Ultra-mobile Personal Computer, UMPC), netbooks, smart screens and other devices.
  • the first device may also be called a collection device, and the second device may also be called a processing device, and the collection device and the processing device are only used to distinguish the roles of devices performing the detection method.
  • the first device and the second device may be the same device, such as a smart phone.
  • the first device and the second device may be different devices, for example, the first device is a smart watch, and the second device is a smart phone.
  • the first device and the second device are the same device, such as electronic device 100 .
  • the first device and the second device are different devices, and optionally, the structure of the first device and/or the second device may be consistent with that of the electronic device 100 .
  • FIG. 1 shows a schematic diagram of a hardware structure of an electronic device 100 .
  • the electronic device 100 may include a processor 110 , a memory 120 , a display screen 130 , a communication module 140 , an audio module 150 and a sensor module 160 .
  • the communication module 140 may include a mobile communication module 141 and a wireless communication module 142 .
  • the audio module 150 may include a microphone 151 and a speaker 152 .
  • the sensor module 160 may include a pressure sensor 161 , an acceleration sensor 162 , a bone conduction sensor 163 , a temperature sensor 164 , a blood oxygen sensor 165 , a pulse sensor 166 , a heart rate sensor 167 and the like.
  • the structure illustrated in the embodiment of the present application does not constitute a specific limitation on the electronic device 100 .
  • the electronic device 100 may include more or fewer components than shown in the figure, or combine certain components, or separate certain components, or arrange different components.
  • the illustrated components can be realized in hardware, software or a combination of software and hardware.
  • the electronic device 100 shown in FIG. 1 is the second device and may not include the audio module 150 and the sensor module 160 .
  • 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 (modem), 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) etc.
  • application processor application processor, AP
  • modem modem
  • graphics processing unit graphics processing unit
  • ISP image Signal processor
  • controller memory, video codec, digital signal processor (digital signal processor, DSP), baseband processor, and/or neural network processor (neural-network processing unit , NPU) etc.
  • different processing units may be independent devices, or may be integrated in one or more processors.
  • the controller may be the nerve center and command center of the electronic device 100 . The controller can generate an operation control signal according to the instruction opcode and timing signal, and complete the control of fetching and
  • a memory may also be provided in the processor 110 for storing instructions and data.
  • the memory in the 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 memory 120 may be used to store computer-executable program codes including instructions.
  • the processor 110 can execute various functional applications and data processing of the electronic device 100 by running the instructions stored in the memory 120, for example, execute at least one step in the detection method shown in Figure 14- Figure 1 ⁇ below, as shown in Figure 20 at least one step in the process.
  • the memory 120 may include an area for storing programs and an area for storing data.
  • the stored program area can store an operating system, at least one application program required by a function (such as a sound playing function, an image playing function, etc.) and the like.
  • the storage data area can store data created during the use of the electronic device 100 (such as audio data, phonebook, etc.) and the like.
  • the memory 120 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 display screen 130 is used to display images, videos and the like.
  • the display screen 130 includes a display panel, and the display panel may include a non-self-luminous screen and a self-luminous screen.
  • the non-self-illuminating screen may be a liquid crystal display (LCD).
  • Self-luminous screens can be organic light-emitting diodes (organic light-emitting diode, OLED), active matrix organic light-emitting diodes or active-matrix organic light emitting diodes (active-matrix organic light emitting diode, AMOLED), flexible light-emitting diodes (flex light-emitting diode, FLED), Miniled, MicroLed, Micro-oLed, quantum dot light emitting diodes (quantum dot light emitting diodes, QLED), etc.
  • the electronic device 100 may include one or more display screens 130 .
  • the electronic device 100 may implement a display function through a GPU, a display screen 130, and an AP.
  • the GPU is a microprocessor for image processing, and is connected to the display screen 130 and the AP. GPUs are used to perform mathematical and geometric calculations for graphics rendering.
  • Processor 110 may include one or more GPUs that execute program instructions to generate or change display information.
  • the wireless communication function of the electronic device 100 may be implemented through an antenna (not shown), a mobile communication module 141, a wireless communication module 142, a modem processor (not shown) and a baseband processor (not shown) ) and so on.
  • the antenna is used to transmit and receive electromagnetic wave signals.
  • multiple antennas may be included in the electronic device 100, and each antenna may be used to cover a single or multiple communication frequency bands. Different antennas can also be multiplexed to improve antenna utilization, for example, the antennas can be multiplexed as diversity antennas for a wireless local area network.
  • the mobile communication module 141 may provide wireless communication solutions including 2G/3G/4G/5G applied on the electronic device 100 .
  • the mobile communication module 141 may include at least one filter, switch, power amplifier, low noise amplifier (low noise amplifier, LNA) and the like.
  • the mobile communication module 141 can receive electromagnetic waves through the antenna, filter and amplify the received electromagnetic waves, and send them to the modem processor for demodulation.
  • the mobile communication module 141 can also amplify the signal modulated by the modem processor, and convert it into electromagnetic wave and radiate it through the antenna.
  • at least part of the functional modules of the mobile communication module 141 may be set in the processor 110 .
  • at least part of the functional modules of the mobile communication module 141 and at least part of the modules of the processor 110 may be set in the same device.
  • the modem processor may include a modulator and a demodulator.
  • the modulator is used for modulating the low-frequency baseband signal to be transmitted into a medium-high frequency signal.
  • the demodulator is used to demodulate the received electromagnetic wave signal into a low frequency baseband signal. Then the demodulator sends the demodulated low-frequency baseband signal to the baseband processor for processing.
  • the low-frequency baseband signal is passed to the AP after being processed by the baseband processor.
  • the AP outputs sound signals through audio equipment (such as the speaker 152 , etc.), or displays images or videos through the display screen 130 .
  • the modem processor can be a stand-alone device.
  • the modem processor may be independent of the processor 110, and be set in the same device as the mobile communication module 141 or other functional modules.
  • the wireless communication module 142 can provide wireless local area networks (wireless local area networks, WLAN) (such as wireless fidelity (Wi-Fi) network), bluetooth (bluetooth, BT) applied on the electronic device 100. , 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 142 may be one or more devices integrating at least one communication processing module.
  • the wireless communication module 142 receives electromagnetic waves via the antenna, frequency-modulates and filters the electromagnetic wave signals, and sends the processed signals to the processor 110 .
  • the wireless communication module 142 can also receive the signal to be sent from the processor 110, frequency-modulate it, amplify it, and convert it into electromagnetic wave and radiate it through the antenna.
  • the electronic device 100 includes an antenna 1 (not shown) and an antenna 2 (not shown), optionally, the antenna 1 is coupled to the mobile communication module 141, and the antenna 2 is coupled to the wireless communication module 142, so that the electronic device 100 It can communicate with the network and other devices through wireless communication technology.
  • the wireless communication technologies mentioned above may include global system for mobile communications (GSM), general packet radio service (GPRS), code division multiple access (CDMA), broadband code 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 above-mentioned GNSS may include global positioning system (global positioning system, GPS), global navigation satellite system (global navigation satellite system, GLONASS), Beidou satellite navigation system (beidou navigation satellite system, BDS), quasi-zenith satellite system (quasi- zenith satellite system (QZSS) and/or satellite based augmentation systems (SBAS).
  • global positioning system global positioning system, GPS
  • global navigation satellite system global navigation satellite system
  • GLONASS global navigation satellite system
  • Beidou satellite navigation system beidou navigation satellite system, BDS
  • quasi-zenith satellite system quasi-zenith satellite system
  • QZSS quasi-zenith satellite system
  • SBAS satellite based augmentation systems
  • the electronic device 100 can implement audio functions, such as music playing and recording, through the audio module 150 and the AP.
  • audio functions such as music playing and recording
  • the audio module 150 is used to convert digital audio information into analog audio signal output, and is also used to convert analog audio input into digital audio signal.
  • the audio module 150 may also be used to encode and decode audio signals.
  • the audio module 150 may be set in the processor 110 , or some functional modules of the audio module 150 may be set in the processor 110 .
  • the microphone 151 also called “microphone” or “microphone”, is used to convert sound signals into electrical signals.
  • the user can approach the microphone 151 to make a sound, and input the sound signal to the microphone 151 .
  • the electronic device 100 may be provided with at least one microphone 151 .
  • the electronic device 100 may be provided with two microphones 151, which may also implement a noise reduction function in addition to collecting sound signals.
  • the electronic device 100 can also be provided with three, four or more microphones 151 to collect sound signals, reduce noise, identify sound sources, and realize directional recording functions, etc.
  • the electronic device 100 can collect audio data of the user through the microphone 151, such as cough sounds, breath sounds, heart sounds, lung sounds, etc., and the collected audio data is used to determine the infection risk of the respiratory system.
  • Speaker 152 also called “horn” is used to convert audio electrical signals into sound signals.
  • the electronic device 100 can listen to music through the speaker 152, or listen to a hands-free call.
  • the pressure sensor 161 is used for sensing pressure signals, and can convert the pressure signals into electrical signals.
  • pressure sensors 161 such as resistive pressure sensors, inductive pressure sensors, capacitive pressure sensors, and piezoelectric pressure sensors.
  • the pressure sensor 161 may be a capacitive pressure sensor, and the capacitive pressure sensor may include at least two parallel plates with conductive materials.
  • the electronic device 100 determines the intensity of pressure according to the change in capacitance.
  • the pressure sensor 161 may be disposed in the display screen 130 .
  • the electronic device 100 may detect the intensity of the touch operation according to the pressure sensor 161.
  • the electronic device 100 may also calculate the touched position according to the detection signal of the pressure sensor 161 .
  • touch operations acting on the same touch position but with different touch operation intensities may correspond to different operation instructions.
  • the pressure sensor 161 may be a piezoelectric pressure sensor.
  • a piezoelectric sensor is a sensor based on the piezoelectric effect.
  • a piezoelectric sensor is a self-generating and electromechanical conversion sensor. The sensitive element of the piezoelectric sensor is made of piezoelectric material. After the piezoelectric material is stressed, a charge is generated on the surface. After the charge amplifier and the measurement circuit amplify and transform the impedance, the charge becomes an electric output proportional to the external force. Piezoelectric sensors are used to measure force and non-electrical quantities that can be converted into electricity.
  • An acceleration sensor (accelerometer, ACC) 162 can detect acceleration signals.
  • the acceleration sensor 162 may be disposed on the user's body (for example, attached to the user's abdomen) for collecting the user's breathing signal, such as breathing frequency.
  • the acceleration sensor 162 may detect the acceleration of the electronic device 100 in various directions (generally three axes). When the electronic device 100 is stationary, the magnitude and direction of gravity can be detected. It can also be used to identify the posture of electronic devices, and can be used in applications such as horizontal and vertical screen switching, pedometers, etc.
  • the bone conduction sensor 163 can acquire vibration signals.
  • the bone conduction sensor 163 may acquire the vibration signal of the vibrating bone mass of the human voice.
  • the bone conduction sensor 163 can be in contact with the pulse of the human body to receive the blood pressure beating signal.
  • the audio module 150 can analyze the voice signal based on the vibration signal of the vibrating bone mass of the vocal part acquired by the bone conduction sensor 163 to realize the voice function.
  • the AP may analyze the heart rate signal based on the blood pressure beating signal acquired by the bone conduction sensor 163 to realize the function of collecting the heart rate.
  • the bone conduction sensor 163 may also detect a pulse signal, and the electronic device 100 may collect the user's pulse through the bone conduction sensor 163 .
  • the temperature sensor 164 is used to detect temperature.
  • the temperature sensor 164 can also be used to detect the temperature of the processor 110, and implement a temperature processing strategy, for example, when the temperature reported by the temperature sensor exceeds a certain threshold, the electronic device 100 executes reducing the performance of the processor located near the temperature sensor 164. , in order to reduce power dissipation and implement thermal protection.
  • the blood oxygen sensor 165 is used to detect blood oxygen saturation.
  • the blood oxygen sensor 165 may include a light emitting device and a receiving device.
  • the light-emitting device is composed of red light with a wavelength of 660 nm (or 650 nm) and an infrared light emitting tube with a wavelength of 940 nm (or 910 nm).
  • the receiving device can be a photosensitive receiving device, most of which adopt a PIN type photosensitive diode with large receiving area, high sensitivity, small dark current and low noise, which converts the received incident light signal into an electrical signal.
  • the electronic device 100 can obtain the blood oxygen saturation of the user according to the detection signal of the blood oxygen sensor 165 .
  • the pulse sensor 166 can detect a pulse signal.
  • the pulse sensor 166 can detect pressure changes produced by arterial pulses and convert them into electrical signals.
  • pulse sensor 166 there are many types of pulse sensor 166 , such as piezoelectric pulse sensor, piezoresistive pulse sensor, photoelectric pulse sensor and so on.
  • the piezoelectric pulse sensor and piezoresistive pulse sensor can convert the pressure process of pulse beating into signal output through micro-pressure materials (such as piezoelectric sheets, electric bridges, etc.).
  • the photoelectric pulse sensor can convert the change of the light transmittance of the blood vessel during pulse beating into signal output through reflection or transmission, that is, the pulse signal is obtained by photoplethysmography (PPG).
  • PPG photoplethysmography
  • the heart rate sensor 167 may detect a heart rate signal.
  • the heart rate sensor 167 can acquire the heart rate signal through the PPG.
  • the heart rate sensor 167 can convert changes in vascular dynamics, such as changes in blood pulse rate (heart rate) or blood volume (cardiac output), into electrical signal output through reflection or transmission.
  • the heart rate sensor 167 can measure the signal of the electrical activity induced in the heart tissue through electrodes connected to the skin of the human body, that is, obtain the heart rate signal through electrocardiography (ECG).
  • ECG electrocardiography
  • the electronic device 100 is a first device, such as a smart bracelet.
  • the electronic device 100 can connect and communicate with the second device through the communication module 140, for example, connect and communicate through Wi-Fi, Bluetooth, NFC, IR and other technologies.
  • the electronic device 100 can collect the user's physiological parameters (such as body temperature, blood oxygen saturation, respiratory rate, heart rate, pulse, etc.) and audio data (such as cough sounds, breath sounds, heart sounds, lung sounds, etc.).
  • the electronic device 100 may send the collected physiological parameters to the second device for analysis and processing through the communication module 140, so as to determine the infection risk of the respiratory system.
  • the electronic device 100 is a second device, such as a smart phone.
  • the electronic device 100 may connect and communicate with the first device through the communication module 140, for example, connect and communicate through technologies such as Wi-Fi, Bluetooth, NFC, and IR.
  • the communication module 140 may receive the physiological parameters and audio data collected by the first device, and transmit them to the processor 110 for processing, so as to determine the infection risk of the respiratory system.
  • the electronic device 100 may also collect some data by itself through the audio module 150 and/or the sensor module 160 (such as collecting cough sounds and breathing sounds through the microphone 151), combined with some data collected by the first device (such as physiological parameters, heart sounds, etc.) and lung sounds) are analyzed and processed to determine the risk of infection of the respiratory system.
  • the collected physiological parameters and/or the collected audio data may be transmitted to the memory 120 for storage.
  • the collected physiological parameters and audio data may be transmitted to the processor 110 .
  • the processor 110 can count the collected physiological parameters and audio data, and determine the infection risk of the respiratory system based on quantitative analysis, such as low risk, medium risk, or high risk.
  • the processor 110 may instruct the display screen 130 to display the infection risk of the respiratory system.
  • the electronic device 100 may prompt the user to seek medical intervention before or during the onset of the disease.
  • the processor 110 may instruct the display screen 130 to display prompt information to remind the user when the risk of respiratory system infection is medium risk or high risk. Medical intervention.
  • the user can know the respiratory health status in time through the electronic device 100, and realize the monitoring and early warning of respiratory diseases, which is more convenient and efficient for the user.
  • the module for collecting audio data may also include sound sensors, ultrasound, etc., to collect the user's cough sound, breath sound, heart sound, lung sound Wait.
  • the module for collecting physiological parameters may also include a respiratory frequency sensor, etc., and the respiratory frequency sensor is used for collecting respiratory frequency.
  • the pulse sensor 166 and the heart rate sensor 167 as the physiological parameter acquisition module can be packaged in one sensor, and the sensor can acquire the pulse signal and the heart rate signal through the PGG. This application does not limit the specific form types of the audio data collection module and the physiological parameter collection module.
  • the software system of the electronic device 100 may adopt a layered architecture, an event-driven architecture, a micro-kernel architecture, a micro-service architecture, or a cloud architecture.
  • a software system with a layered architecture may be an Android system or a Huawei mobile services (HMS) system.
  • the embodiment of the present application takes the Android system with a layered architecture as an example to illustrate the software structure of the electronic device 100 .
  • FIG. 2 exemplarily shows a schematic diagram of a software architecture of an electronic device 100 .
  • the layered architecture divides the software into several layers, and each layer has a clear role and division of labor. Layers communicate through software interfaces.
  • the Android system is divided into four layers, which are respectively the application program layer, the application program framework layer, the Android runtime (Android runtime) and the system library, and the kernel layer from top to bottom.
  • the application layer can consist of a series of application packages.
  • the application package can include camera, gallery, music, video, file management, short message, browser and respiratory health.
  • the user can actively detect the infection risk of the respiratory system through the respiratory health application.
  • the user can check the infection risk of the respiratory system through the respiratory health application.
  • the application framework layer provides an application programming interface (application programming interface, API) and a programming framework for applications in the application layer.
  • the application framework layer includes some predefined functions.
  • the application framework layer may include a sensor manager, a window manager, a content provider, a view system, a phone manager, a resource manager, and a notification manager.
  • the sensor manager is used to manage individual sensors. For example, but not limited to, the sensor manager may receive an interrupt event sent by the pressure sensor 161, so as to control the acceleration sensor 162 to collect the respiratory rate. Wherein, each sensor may be part or all of the modules included in the sensor module 160 of FIG. 1 .
  • a window manager is used to manage window programs.
  • the window manager can, but is not limited to, obtain the size of the display screen, determine whether there is a status bar, lock the screen, capture the screen, etc.
  • Content providers are used to store and retrieve data and make that data accessible to applications.
  • this data may include but not limited to video, images, audio, calls made and received, browsing history and bookmarks, phonebook, etc.
  • the view system can include visual controls, such as controls for displaying text, controls for displaying pictures, and so on.
  • the view system can be used to build applications.
  • a display interface can consist of one or more views.
  • a display interface including a notification icon of a respiratory health application includes a view displaying text and a view displaying pictures.
  • the phone manager is used to provide communication functions of the electronic device 100 . For example but not limited to the management of call status (including connected, hung up, etc.).
  • the resource manager provides various resources for the application, such as but not limited to localized strings, icons, pictures, layout files, video files and so on.
  • the notification manager enables the application to display notification information in the status bar, which can be used to convey notification-type messages, and can automatically disappear after a short stay without user interaction.
  • the notification manager is used to notify download completion, message reminders, etc.
  • the notification manager can also be a notification that appears on the top status bar of the system in the form of a chart or scroll bar text, such as a notification of an application running in the background, or a notification that appears on the screen in the form of a dialog window.
  • prompting text information in the status bar making a prompt sound, vibrating the electronic device, and flashing the indicator light, etc. Not limited to this.
  • the Android Runtime includes core library and virtual machine. The Android runtime is responsible for the scheduling and management of the Android system.
  • the core library consists of two parts: one part is the function function that the java language needs to call, and the other part is the core library of Android.
  • the application layer and the application framework layer run in virtual machines.
  • the virtual machine executes the java files of the application program layer and the application program framework layer as binary files.
  • the virtual machine is used to perform functions such as object life cycle management, stack management, thread management, security and exception management, and garbage collection.
  • a system library can include multiple function modules. For example, but not limited to, surface manager (surface manager), media library (Media Libraries), three-dimensional (3D) graphics processing library (such as OpenGL ES), and two-dimensional (2D) graphics engine (such as SGL), etc.
  • the surface manager is used to manage the display subsystem (DSS) and provides the fusion of 2D and 3D layers for multiple applications.
  • DSS display subsystem
  • the media library supports playback and recording of various commonly used audio and video formats, as well as still image files, etc.
  • the media library can support a variety of audio and video encoding formats, such as: MPEG4, H.264, MP3, AAC, AMR, JPG, PNG, etc.
  • the 3D graphics processing library is used to implement 3D graphics drawing, image rendering, compositing, and layer processing, etc.
  • 2D graphics engine is a drawing engine for 2D drawing.
  • the kernel layer is the layer between hardware and software.
  • the kernel layer can include display drivers, camera drivers, audio drivers, power management and sensor drivers, etc.
  • the Android system can also include a hardware abstraction layer (hardware abstraction layer, HAL), and the HAL is an interface layer between the kernel layer and the system library (and Android Runtime).
  • HAL is the encapsulation of the driver at the kernel layer, which abstracts the hardware and shields the underlying implementation details.
  • the HAL layer can contain sensor interfaces, Bluetooth interfaces, camera interfaces, etc.
  • a corresponding hardware interrupt is sent to the kernel layer.
  • the kernel layer processes the touch operation into an original input event (including touch coordinates, touch operation time stamp and other information), and the original input event is stored in the kernel layer.
  • the application framework layer obtains the original input event from the kernel layer, and identifies the control corresponding to the input event. Take the touch operation as a touch-click operation, and the control corresponding to the click operation is the recording control of the Respiratory Health application as an example.
  • the Respiratory Health application calls the interface of the application framework layer, and then starts the audio driver by calling the kernel layer. 151 receives the user's cough and breath sounds.
  • the detection modes of respiratory diseases can include multiple types, so as to meet the different detection needs of users in different scenarios, multi-scenario and multi-coverage, and better user experience.
  • the detection modes of respiratory diseases may include a first mode, a second mode, a third mode and a fourth mode, wherein:
  • the first mode is applied to a scenario where the user actively detects.
  • the user can actively collect physiological parameters and audio data through the electronic device, and the collected physiological parameters and audio data are used to obtain the infection risk of the respiratory system. Specific examples are shown in Figure 3, Figure 5, and Figure 6 below.
  • the second mode is applied to a scenario where the device is continuously (long-term) automatically detected.
  • the electronic device can automatically collect physiological parameters, and the collected physiological parameters are used to determine the infection risk of the respiratory system.
  • a specific example is shown in Figure 7- Figure ⁇ below.
  • the electronic device may automatically collect physiological parameters and audio data, and the collected physiological parameters and audio data are used to determine the infection risk of the respiratory system.
  • the third mode is applied to a scenario where the user detects audio data under the prompt of the device.
  • the electronic device determines that the physiological parameters are abnormal, it prompts the user to collect audio data, and the collected physiological parameters and audio data are used to obtain the infection risk of the respiratory system. Specific examples are shown in Figure 4 and Figure 9 below.
  • the fourth mode is applied to a scenario where the device automatically detects audio data.
  • the electronic device determines that the physiological parameters are abnormal, it automatically turns on the audio data acquisition module (such as a microphone) to collect audio data, and the collected physiological parameters and audio data are used to determine the infection risk of the respiratory system.
  • the audio data acquisition module such as a microphone
  • the abnormal physiological parameters include, for example but not limited to, at least one of the following: body temperature greater than or equal to the body temperature threshold (for example, in degrees Celsius), blood oxygen saturation less than or equal to the blood oxygen threshold (for example, in percentage), respiratory rate greater than or equal to Frequency threshold (for example, times/minute), the heart rate is greater than or equal to the heart rate threshold (for example, times/minute), and the pulse is greater than or equal to the pulse threshold (for example, times/minute).
  • body temperature greater than or equal to the body temperature threshold (for example, in degrees Celsius)
  • blood oxygen saturation less than or equal to the blood oxygen threshold (for example, in percentage)
  • respiratory rate greater than or equal to Frequency threshold for example, times/minute
  • the heart rate is greater than or equal to the heart rate threshold (for example, times/minute)
  • the pulse is greater than or equal to the pulse threshold (for example, times/minute).
  • the physiological parameters in the third mode and the fourth mode, may be actively collected by the user through the electronic device. In some other embodiments, in the third mode and the fourth mode, the physiological parameters may be automatically collected by the electronic device.
  • the following embodiments are described by taking a smart phone and a smart watch as examples, wherein the smart phone is both the first device (that is, the collection device) and the second device (that is, the processing device), and the smart watch is the first device (that is, the collection device), as
  • the smart phone of the first device is used to collect audio data (also referred to as audio information, such as cough sound, breath sound, heart sound and lung sound, etc.), and the smart watch as the first device is used to collect physiological parameters (also referred to as Physiological parameter information, such as blood oxygen saturation, respiratory rate, heart rate, body temperature and pulse, etc.).
  • the detection function of respiratory diseases is implemented through a respiratory health application on a smart phone as an example for illustration.
  • the smart phone or the smart watch can turn on the detection function of the respiratory system disease in response to the user operation.
  • the detection function of respiratory diseases may be enabled by default.
  • the user can actively collect physiological parameters and audio data through the smart phone, and examples of the specific detection process are shown in Figures 3-5 below.
  • FIG. 3 exemplarily shows a schematic diagram of an embodiment of a user interface.
  • (A) of FIG. 3 shows the user interface 600 before the collection option 633 is clicked, and
  • FIG. 3 (B) shows the user interface 600 after the collection option 633 is clicked.
  • the smart phone 200 can display a user interface 600.
  • the user interface 600 is a user interface of a respiratory health application, and the user can realize the detection function of respiratory diseases through the user interface 600.
  • the user interface 600 may be an interface displayed by the smart phone 200 in response to a touch operation on an icon of a respiratory health application.
  • the user interface 600 may include a page theme 610 (namely "respiratory health"), a connection identifier 620, a physiological parameter collection column 630 and a page identification column 650, wherein:
  • connection identifier 620 may represent whether other devices are connected, for example, whether to connect to wearable devices such as smart watches, and smart home devices such as smart large screens.
  • the icon 620A and text 620B (namely "connected") included in the connection mark 620 shown in (A) of FIG. 3 indicate that other devices have been connected.
  • This application takes the smart phone 200 connected to the smart watch 300 as an example for illustration.
  • Physiological parameter collection column 630 can include column topic 631 (ie "physiological parameter"), collection content 632 and collection option 633, wherein: collection content 632 includes the type of physiological parameter collected, for example including blood oxygen saturation, respiratory rate , heart rate, body temperature and pulse.
  • the collection option 633 can be used to enable the function of collecting the aforementioned physiological parameters.
  • the smart phone 200 may receive a touch operation (for example, a click operation) acting on the collection option 633, and in response to the touch operation, the smart phone 200 may send instruction information to the smart watch 300 indicating collection of physiological parameters. In response to the received instruction information, the smart watch 300 can collect the user's physiological parameters in the background without feeling, and the smart watch 300 can send the collected physiological parameters to the smart phone 200 .
  • the smart watch 300 can collect physiological parameters according to a preset duration, for example, the preset duration is 1 minute. In other embodiments, the duration of collecting physiological parameters can also be set by the user.
  • the smart watch 300 is instructed to start collecting physiological parameters;
  • the time interval between each click operation is the time period for collecting physiological parameters, and the application does not limit the method for determining the time period for collecting physiological parameters.
  • the page identification column 650 may include three page options: home page 651 , statistics 652 and my 653 .
  • the smart phone 200 may receive a user's touch operation (for example, a click operation) on any page option, and in response to the touch operation, the smart phone 200 may display a user interface corresponding to the page option.
  • the home page 651 in the user interface 600 is selected, which means that the user interface 600 is the user interface corresponding to the page option of the home page 651 .
  • the smart phone 200 may prompt the user to collect audio data, for example, display the user interface 600 shown in (B) of FIG. 3 .
  • the user interface 600 displayed on the smart phone 200 is similar to the user interface 600 shown in (A) of FIG. 3 , the difference is that the user interface 600 shown in (B) of FIG. 3 also includes Prompt content 640, the prompt content 640 includes a prompt 641 and an audio option 642, wherein: the prompt 641 includes the text: "Physiological parameter collection is complete, please collect audio data", and the audio option 642 includes the text: "Collect audio data”.
  • the smart phone 200 can receive a touch operation (such as a click operation) acting on the audio option 642, and in response to the touch operation, the smart phone 200 can display a user interface for collecting audio data, such as the user interface shown in (A) of FIG. 5 below 600.
  • the smart phone 200 after the smart phone 200 acquires the collected physiological parameters, it can determine whether the physiological parameters are abnormal, and when it is determined that the physiological parameters are abnormal, prompt the user to collect audio data.
  • a specific example is shown in FIG. 4 below.
  • FIG. 4 exemplarily shows a schematic diagram of another user interface embodiment.
  • the user interface 600 displayed on the smart phone 200 is similar to the user interface 600 shown in (B) of FIG. 3, the difference is that the prompt 641 in the user interface 600 shown in FIG. Your physiological parameters are abnormal, please make an audio recording for further confirmation."
  • the smart phone 200 can receive a touch operation (such as a click operation) acting on the audio option 642, and in response to the touch operation, the smart phone 200 can display a user interface for collecting audio data, such as the user interface shown in (A) of FIG. 5 below 600.
  • the smart phone 200 when the smart phone 200 determines that the physiological parameters are normal, it may prompt the user that the physiological parameters are normal, and determine whether to display the user interface for collecting audio data according to user operations. For example, when the smart phone 200 determines that the physiological parameters are normal, the prompt 641 in the displayed user interface 600 may contain the text: "Your physiological parameters are normal. If you want to obtain more accurate test results, you can perform audio recording for further confirmation.”
  • the smart phone 200 receives a touch operation (such as a click operation) acting on the audio option 642
  • it may respond to the touch operation and display a user interface for collecting audio data, such as the user interface 600 shown in (A) of FIG. 5 below.
  • FIG. 5 exemplarily shows a schematic diagram of another user interface embodiment.
  • (A), (B), (C), and (D) of FIG. 5 respectively show user interfaces 600 for collecting different types of audio data.
  • the user interface 600 displayed on the smart phone 200 is similar to the user interface 600 shown in (A) of FIG. 3 , the difference is that the user interface 600 shown in FIG.
  • An audio data collection field 660 is included.
  • the audio data collection column 660 can include a column theme 661 (ie "audio data"), collection content 662, collection options 663 and prompt content 664, wherein:
  • the collected content 662 may include a prompt 662A and an option of collected audio data, and the prompt 662A includes text: "type of collected audio data", which is used to prompt the user to select the type of collected audio data.
  • the options for collected audio data may include options for cough sounds 642B, options for breath sounds 642C, options for heart sounds 642D, and options for lung sounds 642E.
  • the smart phone 200 may receive a touch operation (for example, a click operation) acting on any option, and in response to the touch operation, the smart phone 200 may determine that the type of audio data currently collected is the type corresponding to the option.
  • the collection option 663 is used to enable the function of collecting audio data.
  • the collected audio data corresponding to the collection option 663 is also different, and the collected audio data corresponding to the collection option 663 is the audio data corresponding to the selected option.
  • Prompt content 664 is used to prompt the user to collect audio data.
  • the options of the selected audio data in the collection content 662 are different, the content included in the prompt content 664 is also different, and the prompt content 664 prompts that the collected audio data is the audio data corresponding to the selected option.
  • the option 642B of cough sound is selected, indicating that the audio data currently collected is cough sound
  • the user interface 600 shown in (A) of Figure 5 can be understood as the user who collects cough sound interface.
  • the prompt content 664 includes text 664A: "Please cough hard 2-3 times", which is used to remind the user how to collect cough sounds.
  • the smart phone 200 can receive a touch operation (such as a click operation) acting on the collection option 663, and in response to the touch operation, the smart phone 200 can start an audio data collection module (such as a microphone) to collect audio data, and determine that the collected audio data is a cough. cough sounds, for example, storing the collected audio data in a database corresponding to cough sounds.
  • the smart phone 200 may collect audio data according to a preset duration or preset times, for example, the preset duration is 15 seconds, and cough sounds are collected 3 times.
  • the duration or times of collecting audio data can also be set by the user.
  • the smart phone 200 receives a long press operation acting on the collection option 663, and the duration of the long press operation (that is, acts on the collection option 663 The touch duration of the touch operation) is the duration for collecting audio data.
  • the smart phone 200 receives the click operation acting on the collection option 663 for the first time, turn on the microphone, and when receiving the click operation acting on the collection option 663 for the second time, turn off the microphone.
  • the interval is the duration of collecting audio data, and the present application does not limit the method of determining the duration of collecting audio data.
  • the option 642C of breath sound is selected, indicating that the audio data currently collected is breath sound
  • the user interface 600 shown in (B) of Figure 5 can be understood as the user who collects breath sound interface.
  • the prompt content 664 includes the text 664B: "Please put the microphone near your mouth to breathe for 15 seconds", which is used to prompt the user how to collect breath sounds.
  • the smart phone 200 can receive a touch operation (such as a click operation) acting on the collection option 663, and in response to the touch operation, the smart phone 200 can turn on the audio data collection module (such as a microphone) to collect audio data, and determine that the collected audio data is breathing. sounds, for example, storing the collected audio data in a database corresponding to breath sounds.
  • the method of determining the duration of collecting breath sounds is similar to the method of determining the duration of collecting cough sounds.
  • the heart sound option 642D is selected, indicating that the currently collected audio data is heart sound.
  • the user interface 600 shown in (C) of FIG. 5 can be understood as a user interface for collecting heart sounds.
  • the prompt content 664 includes text 664C: "Please place the mobile phone on the heart for 15 seconds", which is used to prompt the user to collect the heart sound.
  • the smart phone 200 can receive a touch operation (such as a click operation) acting on the collection option 663, and in response to the touch operation, the smart phone 200 can open an audio data collection module (such as a microphone) to collect audio data, and determine that the collected audio data is heart sound , for example, storing the collected audio data in a database corresponding to heart sounds.
  • the method of determining the duration of collecting heart sounds is similar to the method of determining the duration of collecting cough sounds.
  • the option 642E of lung sounds is selected, indicating that the audio data currently collected is lung sounds, and the user interface 600 shown in (D) of Figure 5 can be understood as the user who collects lung sounds interface.
  • the prompt content 664 includes the text 664D: "Please place the mobile phone on the lungs for 15 seconds", which is used to prompt the user how to collect lung sounds.
  • the smart phone 200 can receive a touch operation (such as a click operation) acting on the collection option 663, and in response to the touch operation, the smart phone 200 can turn on the audio data collection module (such as a microphone) to collect audio data, and determine that the collected audio data is lung sounds, for example, storing the collected audio data in a database corresponding to lung sounds.
  • the method of determining the duration of collecting lung sounds is similar to the method of determining the duration of collecting cough sounds.
  • the user interface for collecting audio data displayed on the smart phone 200 may be a user interface for collecting cough sounds, that is, the user interface 600 shown in (A) of FIG. 5 .
  • the smart phone 200 can display prompt information to remind the user to collect other types of audio data, and the user can select other audio data options other than the cough sound option 642B according to the prompt information.
  • the smart phone 200 may respond to a touch operation (such as a click operation) acting on an option of other audio data, display a user interface for collecting the audio data corresponding to the option, and continue to collect the audio data corresponding to the option until the smart phone 200 collects all audio data. type of audio data.
  • the user interface for collecting audio data displayed by the smart phone 200 can also be the user interface 600 shown in any one of (B), (C), and (D) of FIG. 5 , the subsequent process is similar to the above process.
  • the smart phone 200 after the smart phone 200 acquires the collected physiological parameters and audio data, it can analyze and process the physiological parameters and audio data to obtain the infection risk of the respiratory system (also referred to as the detection result). In some embodiments, after the smart phone 200 obtains the detection result, it may prompt the user to view the detection result, for example, display the user interface 600 shown in (A) of FIG. 6 .
  • FIG. 6 exemplarily shows a schematic diagram of another user interface embodiment.
  • (A) of FIG. 6 shows the user interface 600 before the viewing option 672 is clicked
  • FIG. 6(B) shows the user interface > 00 after the viewing option 672 is clicked.
  • the user interface 600 displayed on the smart phone 200 is similar to the user interface 600 shown in (D) of FIG. 5 , the difference is that the user interface 600 shown in (A) of FIG. 6 also includes Prompt content 670.
  • the prompt content 670 includes a prompt 671 and a view option 672.
  • the prompt 671 includes the text: "The test is complete, please check the test result", which is used to remind the user to check the infection risk of the respiratory system.
  • Touch operation for example, click operation
  • the infection risk of the respiratory system is displayed, for example, the user interface ⁇ 00 shown in (B) of FIG. 6 .
  • the smartphone 200 may display a user interface ⁇ 00.
  • User interface ⁇ 00 may include page theme ⁇ 01 (namely "respiratory system infection risk", representing the current interface for displaying test results), risk level ⁇ 10, multiple specific test results and page identification bar 650, wherein:
  • the risk level ⁇ 10 can be "low risk”, “medium risk” or “high risk” as shown in (B) of Figure 6, but is not limited to this, and can also be identified by no abnormalities, respiratory system infection risk, pneumonia risk, etc. risk level.
  • the following examples illustrate by taking respiratory system infection risks including low risk, medium risk and high risk as examples.
  • the user interface ⁇ 00 may also include related instructions of risk level ⁇ 10, for example, including text: "Your respiratory health is poor, and the possibility of being infected with respiratory diseases such as pneumonia is high. It is recommended that you seek medical treatment in time" .
  • test results include, for example: the test result of body temperature ⁇ 20, the test result of blood oxygen ⁇ 30, the test result of heart rate ⁇ 40, the test result of pulse ⁇ 50, the test result of respiratory rate ⁇ 60, the test result of cough sound ⁇ 70, the detection result of breath sound ⁇ 0 and the detection result of heart and lung sound ⁇ 90, which means that the smartphone 200 has collected physiological parameters such as body temperature, blood oxygen, heart rate, pulse and respiratory rate, as well as cough sound, breath sound and heart sound and audio data of lung sounds, which also characterize the risk level ⁇ 10 is determined based on the above collected physiological parameters and audio data.
  • Body temperature detection results ⁇ 20 may include result summary ⁇ 21 and statistical data ⁇ 22, wherein, result summary ⁇ 21 may include data type ⁇ 21A (namely "body temperature"), detection status ⁇ 21B and expanded and collapsed options ⁇ 21C.
  • the detection status ⁇ 21B can include three states: normal, abnormal, and undetected, which respectively indicate that the detection result of body temperature is normal, the detection result of body temperature is abnormal and undetected body temperature (for example, no body temperature data is collected, body temperature data collection fails, or body temperature collected data not available).
  • ExpandCollapseOptions ⁇ 21C is used to switch whether to display statistics ⁇ 22.
  • Statistical data ⁇ 22 may include statistical graphs of body temperature data over a period of time.
  • test results are similar to body temperature test results ⁇ 20, except that the statistical data of other test results except body temperature test results ⁇ 20 are not displayed in the user interface ⁇ 00, for example, the statistics of blood oxygen test results ⁇ 30 The data does not show that the blood oxygen test result ⁇ 30 is different from the expand option ⁇ 33 in the body temperature test result ⁇ 20 ⁇ 21C.
  • the smart phone 200 may receive a touch operation (such as a click operation) that acts on the body temperature detection result ⁇ 20 and expand and close options ⁇ 21C, and in response to the touch operation, the smart phone 200 may cancel the display of statistical data ⁇ 22, in some embodiments , in response to the touch operation, the expanded and collapsed option ⁇ 21C will change, for example, it will change to the state shown in the expanded and collapsed option ⁇ 33 in the blood oxygen detection result ⁇ 30. In some embodiments, the smart phone 200 may receive a touch operation (such as a click operation) that acts on the blood oxygen detection result ⁇ 30 and expand and close options ⁇ 33, and in response to the touch operation, the smart phone 200 may display the blood oxygen Statistical data.
  • a touch operation such as a click operation
  • the detection status ⁇ 21B when the number of times the body temperature is greater than or equal to the body temperature threshold (for example, 37.5 degrees Celsius) is greater than or equal to the first number, the detection status ⁇ 21B is abnormal, otherwise the detection status ⁇ 21B is normal.
  • the blood oxygen detection result ⁇ 30 and the detection status ⁇ 32 when the number of times the blood oxygen saturation is less than or equal to the blood oxygen threshold is greater than or equal to the second time, the blood oxygen detection result ⁇ 30 and the detection status ⁇ 32 are abnormal, otherwise the detection status ⁇ 32 is normal.
  • the heart rate detection result ⁇ 40 and the detection state ⁇ 42 when the number of times the heart rate is greater than or equal to the heart rate threshold is greater than or equal to the third time, the heart rate detection result ⁇ 40 and the detection state ⁇ 42 are abnormal, otherwise the detection state ⁇ 42 is normal.
  • the pulse detection result ⁇ 50 and the detection status ⁇ 52 are abnormal, otherwise the detection status ⁇ 52 is normal.
  • the detection result of respiratory frequency ⁇ 60 and the detection status ⁇ 62 are abnormal, otherwise the detection status ⁇ 62 is normal.
  • the detection status can also be judged by the duration, for example, when the duration of the body temperature is greater than or equal to the body temperature threshold is greater than or equal to the first duration, the detection result of the body temperature ⁇ 20 and the detection status ⁇ 21B are abnormal, and the detection status of other data The judgment of detection status is similar.
  • the statistical data of the cough sound detection result ⁇ 70 may include a cough sound spectrogram (for example, the abscissa is frequency, and the ordinate is signal energy).
  • the cough sound spectrogram is concentrated in When the percentage of the signal energy in the preset frequency range to the total signal energy is greater than or equal to the preset percentage, the detection status ⁇ 72 in the cough sound detection result ⁇ 70 is abnormal, otherwise the detection status ⁇ 72 is normal.
  • the determination of the detection status of breath sounds and heart-lung sounds is similar.
  • the statistics 652 in the page identification column 650 is selected, indicating that the user interface ⁇ 00 is the user interface corresponding to the page option of the statistics 652 .
  • the smart phone 200 after the smart phone 200 obtains the infection risk of the respiratory system, it can receive the page option for the statistics 652 in the user interface 600 shown in (A) of FIG. 6 .
  • a touch operation for example, a click operation
  • a user interface ⁇ 00 shown in (B) of FIG. 6 is displayed.
  • the smart phone 200 may instruct the smart watch 300 to automatically collect the physiological parameters of the user.
  • the smart phone 200 may send instruction information to the smart watch 300, and the instruction information is used to instruct the smart watch 300 to continuously (for a long time) collect the physiological parameters of the user, for example, collect physiological parameters all the time, or collect physiological parameters periodically .
  • the smart watch 300 can periodically send the collected physiological parameters to the smart phone 200 .
  • the smart phone 200 may analyze and process the physiological parameters to determine the infection risk of the respiratory system.
  • the smart phone 200 may analyze and process the physiological parameters after receiving the physiological parameters sent by the smart watch 300 for a preset number of times, so as to determine the infection risk of the respiratory system.
  • the smart phone 200 can also construct the waveform of the physiological parameters of the first user based on the physiological parameters of the first user collected for a long time (for example, 14 days), and construct the baseline of the physiological parameters of the healthy user. For example, it is a waveform of a physiological parameter of a user whose risk level is low.
  • the smart phone 200 can analyze the degree of deviation between the waveform of the physiological parameter collected for a long time and the baseline, and when the degree of deviation is greater than or equal to a preset deviation threshold, it can be determined that the physiological parameter is abnormal.
  • the smart phone 200 can choose whether to enable the function of automatically collecting physiological parameters and obtaining the detection result according to the physiological parameters according to the actual scene.
  • Function may be referred to as the automatic detection function for short
  • the smart phone 200 may enable or disable the automatic detection function in response to user operations, as shown in FIG. 7 below for a specific example.
  • FIG. 7 exemplarily shows a schematic diagram of another user interface embodiment.
  • the user interface 600 displayed on the smart phone 200 is similar to the user interface 600 shown in (A) of FIG. 3 , the difference is that the user interface 600 shown in FIG. 7 also includes function options 6 ⁇ 0.
  • the function option 6 ⁇ 0 may include a function name 6 ⁇ 1 (ie "automatic detection"), a function switch 6 ⁇ 2 and a function description 6 ⁇ 3 (ie "automatically collect physiological parameters and determine the test result").
  • the function switch 6 ⁇ 2 is used to turn on or off the automatic detection function.
  • the smart phone 200 when the smart phone 200 determines that the physiological parameter is abnormal, it may prompt the user to view the detection result, a specific example is shown in the following figure ⁇ .
  • FIG. ⁇ exemplarily shows a schematic diagram of another user interface embodiment.
  • (A) of Figure ⁇ shows the user interface 900 before clicking the first notification bar 930
  • (B) of Figure ⁇ shows the user interface ⁇ 00 after clicking the first notification bar 930 .
  • the smart phone 200 may display a user interface 900, and in some embodiments, the user interface 900 may be a lock screen interface.
  • the user interface 900 may include a date and time 910, an unlock prompt 920 (ie "slide to unlock"), a first notification bar 930 and a second notification bar 940, wherein: the first notification bar 930 is used to display a notification message about breathing health, and the second The notification bar 940 is used to display notification messages of music.
  • the first notification bar 930 may include an application identification 931 and a notification content 932.
  • the application identification 931 may include the name and icon of Respiratory Health
  • the notification content 932 may include text: "Your physiological parameters are abnormal, please check the test results for details".
  • the smart phone 200 may receive a touch operation (for example, a click operation) acting on the first notification bar 930, and in response to the touch operation, the detection result may be displayed, for example, the user shown in (B) shown in Figure ⁇ Interface ⁇ 00.
  • a touch operation for example, a click operation
  • the smart phone 200 before displaying the detection result, the smart phone 200 will first authenticate the user's identity, and the detection result will be displayed only when the identity authentication is passed.
  • the smart phone 200 may display a user interface for pattern unlocking or password unlocking in response to the touch operation, and the smart phone 200 may receive a touch operation or a number input by the user based on the user interface, and verify whether the touch operation or the number is legal ( For example, whether the event information of the touch operation is the same as the stored event information, or whether the number is the same as the stored number), and if it is legal, it is determined that the identity authentication is passed.
  • the smart phone 200 may receive a touch operation acting on the fingerprint recognition area, collect the fingerprint information of the touch operation, and verify whether the fingerprint information is legal (for example, whether the similarity with the stored fingerprint information is greater than or equal to the first similarity threshold) , if it is legal, it is determined that the identity authentication is passed.
  • the smart phone 200 can respond to the touch operation, turn on the camera to collect the face information of the user, and verify whether the face information is legal (for example, whether the similarity with the stored face information is greater than or equal to the second similarity threshold), If it is legal, it is determined that the identity authentication is passed.
  • the user interface ⁇ 00 displayed on the smartphone 200 is similar to the user interface ⁇ 00 shown in (B) of FIG. Including the detection results of audio data (such as the detection results of cough sounds ⁇ 70, the detection results of breath sounds ⁇ ⁇ 0 and the detection results of heart and lung sounds ⁇ 90), indicating that the currently displayed detection results are based on physiological parameters (such as body temperature, blood oxygen, heart rate, pulse and respiratory rate), audio data is not detected.
  • the detection results of audio data such as the detection results of cough sounds ⁇ 70, the detection results of breath sounds ⁇ ⁇ 0 and the detection results of heart and lung sounds ⁇ 90
  • physiological parameters such as body temperature, blood oxygen, heart rate, pulse and respiratory rate
  • the smart phone 200 can also send indication information to the smart watch 300, and the smart watch 300 can display the prompt information for prompting the user to check the detection result after receiving the indication information, as shown in (C) of Figure ⁇ , the smart watch 300 can display a user interface 700, and the user interface 700 can include text: "Your physiological parameters are abnormal, please check the test results on your mobile phone".
  • the smart phone 200 may receive a user's touch operation (such as a click operation) on the respiratory health icon, and in response to the touch operation, display the detection result, such as ( B)
  • the user interface shown is ⁇ 00.
  • the physiological parameters acquired by the smart phone 200 may not be triggered by the user, but automatically collected by the device.
  • the smart phone 200 can send instruction information to the smart watch 300, and the instruction information is used to instruct the smart watch 300 to collect the user's physiological parameters. Instruction information is sent, and the user operation is used to enable or disable the function of automatically collecting physiological parameters.
  • the specific example is similar to that in FIG. 7 .
  • the above indication information is used to instruct the smart watch 300 to continuously (for a long time) collect the physiological parameters of the user, for example, collect the physiological parameters all the time, or collect the physiological parameters periodically.
  • the smart watch 300 can periodically send the collected physiological parameters to the smart phone 200 .
  • the above instruction information is used to instruct the smart watch 300 to collect the user's physiological parameters according to a preset time period (for example, 1 minute). The physiological parameters collected by the smart watch 300 can be sent to the smart phone 200 .
  • the smart phone 200 can determine whether the physiological parameters are abnormal, and when it is determined that the physiological parameters are abnormal, it can prompt the user to collect audio data.
  • a specific example is shown in FIG. 9 below.
  • FIG. 9 exemplarily shows a schematic diagram of another user interface embodiment.
  • FIG. 9(A) shows the user interface 900 before the first notification bar 410 is clicked
  • FIG. 9(B) shows the user interface 600 after the first notification bar 410 is clicked.
  • the smart phone 200 may display a user interface 400.
  • the user interface 400 is a sliding notification interface.
  • the smart phone 200 responds to a user operation sliding down from the upper edge of the screen, The displayed user interface.
  • the user interface 400 may include at least one notification bar, such as a first notification bar 410 and a second notification bar 420, wherein: the first notification bar 410 is used to display notification messages of respiratory health, and the second notification bar 420 is used to display music notifications information.
  • the first notification bar 410 may include an application identification 411 and a notification content 412.
  • the application identification 411 may include the name and icon of Respiratory Health
  • the notification content 412 may include text: "Your physiological parameters are abnormal, please perform audio recording for further confirmation".
  • the smart phone 200 may receive a touch operation (for example, a click operation) acting on the first notification bar 410, and in response to the touch operation, a user interface for collecting audio data may be displayed, for example, the (B) of FIG. 9 is displayed.
  • the user interface 600 shown is the user interface 600 shown in (A) of FIG. 5 .
  • the process in which the user collects audio data through the smart phone 200 is similar to the process in which the user actively collects audio data shown in FIG. 5 above.
  • the smart phone 200 can determine the infection risk of the respiratory system based on automatically collected physiological parameters and audio data collected in response to user operations.
  • the process of the smart phone 200 prompting the user to check the test results is similar to the embodiment shown in FIG. 6 above.
  • the smart phone 200 may also send instruction information to the smart watch 300, the smart watch 300 may receive the instruction information, and may display a prompt information for prompting the user to collect audio data, as shown in (C) of FIG. 9 , the smart watch 300 may display a user interface 700, and the user interface 700 may include text: "Your physiological parameters are abnormal, please go to the mobile phone to perform audio recording for further confirmation".
  • the smart phone 200 may receive a user's touch operation (such as a click operation) on the icon of respiratory health, and in response to the touch operation, a user interface for collecting audio data may be displayed, For example, the user interface 600 shown in (A) of FIG. 5 .
  • a user's touch operation such as a click operation
  • the collection of audio data may not be performed temporarily.
  • the smart phone 200 may store the collected physiological parameters, and after the user collects audio data through the smart phone 200, the risk of infection of the respiratory system is determined according to the audio data and the physiological parameters.
  • the smart phone 200 can also automatically turn on the audio data acquisition module (such as a microphone) to collect audio data, or the smart phone 200 can also directly determine the infection risk of the respiratory system according to physiological parameters.
  • the smart phone 200 can determine whether the physiological parameters are abnormal. audio data, and then determine the infection risk of the respiratory system based on the collected audio data and physiological parameters.
  • the physiological parameters acquired by the smart phone 200 may be actively triggered by the user, for example, in response to a touch operation on the acquisition option 633 in the user interface 600 shown in FIG.
  • the physiological parameters acquired by the smart phone 200 may be automatically collected by the device, for example, the smart phone 200 instructs the smart watch 300 to collect them for a long time (for example, periodically).
  • Physiological parameters may not be triggered by the user to be collected actively, but related instructions automatically collected by the device.
  • the smart phone 200 when the smart phone 200 determines that the physiological parameters are abnormal, it can turn on the microphone to collect the user's audio data, and the smart phone 200 can identify and process the collected audio data. You can turn off the microphone when at least one of the tones is selected. For example, the smart phone 200 can determine whether the data model of the cough sound matches the collected audio data, and if they match, the microphone can be turned off. In some other embodiments, when the smart phone 200 determines that the physiological parameter is abnormal, it may turn on the microphone according to a preset time period to collect the user's audio data, for example, the preset time period is 10 minutes.
  • the user may be prompted to check the test result.
  • the smart phone 200 determines that the risk level of the infection risk is relatively high, such as medium risk or high risk. , the user can be prompted to view the detection results, as shown in Figure 10 below for a specific example.
  • FIG. 10 exemplarily shows a schematic diagram of another user interface embodiment. Among them, (A) of FIG. 10 shows the user interface 900 before the first notification bar 930 is clicked, and (B) of FIG. 10 shows an embodiment of the user interface after the first notification bar 930 is clicked.
  • the user interface 900 displayed on the smart phone 200 is similar to the user interface 900 shown in (A) of FIG.
  • the notification content 932 is: "Your risk of infection is high, please check the test result for details".
  • the smart phone 200 may receive a touch operation (such as a click operation) acting on the first notification bar 930, and in response to the touch operation, the detection result may be displayed, for example, the user information shown in (B) of FIG. 10 may be displayed. Interface ⁇ 00.
  • the smart phone 200 before displaying the detection result, the smart phone 200 will authenticate the user first, and the detection result will be displayed only when the identity authentication is passed. For a specific example, refer to the example of identity authentication shown in FIG. ⁇ .
  • the user interface ⁇ 00 displayed on the smart phone 200 is similar to the user interface ⁇ 00 shown in (B) of FIG.
  • the detection results of different kinds of data are different. For example, if the detection result of body temperature ⁇ 20, the detection status ⁇ 21B is abnormal, and the statistical data ⁇ 22 is also different.
  • the detection result of blood oxygen detection ⁇ 30 is abnormal, and the detection status ⁇ 32 is abnormal, and the detection result of heart rate ⁇ 40
  • the detection status of ⁇ 42 is normal, the detection status of respiratory frequency ⁇ 60 is abnormal, and the detection status of cough sound ⁇ 70 is abnormal.
  • the smart phone 200 may also send instruction information to the smart watch 300.
  • the smart watch 300 may display prompt information for prompting the user to view the test result, as shown in (C) of FIG. 10 for a specific example. shown.
  • the smart phone 200 may receive a user's touch operation (such as a click operation) on the icon of respiratory health, and in response to the touch operation, the detection result may be displayed, such as that shown in FIG. 10 .
  • a user's touch operation such as a click operation
  • the detection result may be displayed, such as that shown in FIG. 10 .
  • the smart watch 300 can display a user interface 700, and the user interface 700 can include text: "Your risk of infection is high, please check the test result on your mobile phone".
  • the smart phone 200 can judge whether the collected physiological parameters are abnormal, and when it is determined that the physiological parameters are abnormal, the audio data collection module is automatically turned on (such as a microphone) senselessly collects audio data, and determines the detection result based on the collected physiological parameters and audio data.
  • the audio data collection module is automatically turned on (such as a microphone) senselessly collects audio data, and determines the detection result based on the collected physiological parameters and audio data.
  • the smart phone 200 may also construct the waveform of the physiological parameters of the first user based on the physiological parameters of the first user collected for a long time (for example, 14 days), and construct the first
  • the baseline of the user's physiological parameters, the baseline may be the waveform of the physiological parameters of the user not infected with respiratory diseases, that is, the waveform of the physiological parameters of the healthy user.
  • the smart phone 200 can analyze the waveform of the physiological parameter collected for a long time, and the deviation degree of the baseline of the physiological parameter, and when the deviation degree is greater than or equal to the preset deviation threshold, it can determine that the physiological parameter is abnormal.
  • the present application does not limit the specific way of judging whether the physiological parameters are abnormal or whether the audio data is abnormal.
  • the smart phone 200 may determine the detection mode of the respiratory system disease to be used according to a preset rule.
  • the preset rule is determined based on the power of the smart phone 200 .
  • the smart phone 200 when the power of the smart phone 200 is less than the first power value, the smart phone 200 only collects physiological parameters and audio data under the operation of the user, and specific examples are shown in FIGS. 3-6 above.
  • the smartphone 200 When the power is greater than or equal to the first power value and less than the second power value, the smartphone 200 automatically acquires physiological parameters, and prompts the user to collect audio data when it is determined that the physiological parameters are abnormal. A specific example is shown in FIG. 9 .
  • the smart phone 200 When the power is greater than or equal to the second power value, the smart phone 200 automatically acquires the physiological parameters, and automatically turns on the audio data acquisition module (such as a microphone) to collect the user's audio data insensibly when it is determined that the physiological parameters are abnormal, wherein the first power value is less than A specific example of the second power value is shown in FIG. 10 .
  • the smart phone 200 can also determine the detection mode of the respiratory system disease used in response to the user operation, for example, in the embodiment shown in FIG.
  • the smart phone 200 can respond to the A touch operation (such as a click operation), in response to the touch operation, the automatic detection function is turned on, that is, the smart phone 200 can instruct the smart watch 300 to automatically collect the user's physiological parameters, and determine the detection result according to the collected physiological parameters, a specific example is shown in Figure ⁇ shown. This application does not limit how to determine the detection mode of the respiratory disease to be used.
  • the smart phone 200 can also instruct the smart watch 300 to collect the user's physiological parameters and audio data in response to an operation of the user, as shown in Fig. 11 - Fig. 13.
  • FIG. 11 exemplarily shows a schematic diagram of another user interface embodiment.
  • the smart phone 200 can display a user interface 1 ⁇ 00.
  • the user interface 1 ⁇ 00 is a user interface of a respiratory health application, and the user can realize the detection of respiratory diseases through the user interface 1 ⁇ 00 function, and view test results.
  • the user interface 1 ⁇ 00 may be an interface displayed by the smart phone 200 in response to a touch operation on an icon of the respiratory health application.
  • User interface 1 ⁇ 00 can include page topic 1 ⁇ 01 (i.e. "respiratory health"), results overview 1 ⁇ 10, results description 1 ⁇ 20, statistics 1 ⁇ 30, two page options (home page 1 ⁇ 41 and my ⁇ 42), detection control 1 ⁇ 43 and prompt 1 ⁇ 50, where:
  • the smart phone 200 may receive a user's touch operation (such as a click operation) on any page option, and in response to the touch operation, the smart phone 200 may display a user interface corresponding to the page option.
  • a user's touch operation such as a click operation
  • the smart phone 200 may display a user interface corresponding to the page option.
  • the homepage 1 ⁇ 41 in the user interface 1 ⁇ 00 is selected, which means that the user interface 1 ⁇ 00 is the user interface corresponding to the page option of the homepage 1 ⁇ 41.
  • Detection control 1 ⁇ 43 is used to enable the detection function of respiratory diseases.
  • the smart phone 200 may receive a user's touch operation (such as a click operation, a long press operation) on the detection control 1 ⁇ 43, and in response to the touch operation, the smart phone 200 may instruct the smart watch 300 to collect physiological parameters, And open the audio data acquisition module (such as a microphone) to collect audio data by itself.
  • the detection control 1 ⁇ 43 may include the function of the collection option 633 in the user interface 600 shown in FIG. 3 above, and the function of the collection option 663 in the user interface 600 shown in FIG. 5 above.
  • the smart phone 200 may determine the infection risk of the respiratory system (ie, the detection result) according to the physiological parameters and audio data.
  • the smart phone 200 may prompt the user to view the test result, for example, display a prompt 1 ⁇ 50 (including text: "The test is completed, please check the test result").
  • Test results can be displayed by Result Summary 1 ⁇ 10, Result Description 1 ⁇ 20 and Statistical Data 1 ⁇ 30.
  • Result summary 1 ⁇ 10 may include the test results obtained from the user's latest test, and may include theme 1 ⁇ 11 (ie "risk level”), risk level 1 ⁇ 12, test time 1 ⁇ 13 and health icon 1 ⁇ 14.
  • the risk level 1 ⁇ 12 can be "no abnormality", “respiratory tract infection risk” or “pneumonia risk”
  • the health icon 1 ⁇ 14 can correspond to the risk level 1 ⁇ 12, and the color depth of the health icon 1 ⁇ 14 Risk class characterizing the risk of respiratory infection.
  • the health icon 1 ⁇ 14 shown in Figure 11 is light gray, corresponding to the risk level 1 ⁇ 12 of "no abnormality", which means that the risk level obtained by the user's latest respiratory disease detection is "no abnormality”.
  • the detection time 1 ⁇ 13 may include the text: “latest detection: 2021/4/20 12:35", which means that the user's latest respiratory disease detection time is 12:35 on April 20, 2021.
  • the result description 1 ⁇ 20 may include a description of the detection result obtained by the user's latest detection, which corresponds to the result summary 1 ⁇ 10.
  • Result statement 1 ⁇ 20 may include topic 1 ⁇ 21 (ie "interpretation of results"), content statement 1 ⁇ 22 and prompt 1 ⁇ 24 (ie "click to view full text").
  • Content description 1 ⁇ 22 includes text, for example: “Through analysis of your recent tests, your risk of respiratory tract infection is low, which is within the healthy range, and continuing to maintain good habits will bring you continuous health."
  • the smart phone 200 can receive a touch operation (such as a click operation) acting on the result description 1 ⁇ 20, and in response to the touch operation, the smart phone 200 can display a detailed description of the test result, for example, it can include the above figure 5
  • a touch operation such as a click operation
  • the smart phone 200 can display a detailed description of the test result, for example, it can include the above figure 5
  • the statistical data 1 ⁇ 30 may include the statistical results of the risk level detected by the user recently (for example, three months). It can include theme 1 ⁇ 31 (that is, "historical records in the past three months"), total risk trend 1 ⁇ 32, number of detections 1 ⁇ 33, and statistical graph of risk level 1 ⁇ 34. Among them, the total risk trend 1 ⁇ 32 can represent the change trend of the risk level detected by the user in the past three months. Steady, with rising risk levels. The number of detection times 1 ⁇ 33 can represent the number of detections performed by the user in the past three months, and can include a number: "55”. The overall risk trend 1 ⁇ 32 corresponds to the statistical graph 1 ⁇ 34 of the risk level. In the statistical chart of risk level 1 ⁇ 34, the waveform is a straight line, and corresponds to the vertical axis: "no risk", which means that the risk level obtained by the user in the past three months is "no abnormality".
  • the risk level may also be "respiratory tract infection risk", a specific example is shown in Figure 12 below.
  • FIG. 12 exemplarily shows a schematic diagram of another user interface embodiment.
  • the user interface 1 ⁇ 00 displayed on the smart phone 200 is similar to the user interface 1 ⁇ 00 shown in Figure 11, the difference is that the risk level 1 ⁇ 12 in the user interface 1 ⁇ 00 shown in Figure 12 is " Risk of Respiratory Tract Infection", the corresponding health icon 1 ⁇ 14 is dark gray, indicating that the risk level obtained by the user's latest respiratory disease detection is "Risk of Respiratory Tract Infection”.
  • the content statement 1 ⁇ 22 in the result statement 1 ⁇ 20 includes, for example, the text: "Through analysis of your recent test, you have a high risk of respiratory tract infection, and it is recommended to see a doctor for further confirmation.".
  • the total risk trend 1 ⁇ 32 in the statistical data 1 ⁇ 30 is "increasing", and the corresponding risk level in the statistical chart 1 ⁇ 34, the waveform changes from the corresponding vertical axis: "no risk” to the corresponding vertical axis:
  • the straight line of "respiratory tract infection risk” indicates that the user has been tested for respiratory system diseases in the past three months, and the obtained risk level has changed from "no abnormality" to "respiratory tract infection risk”.
  • the risk level can also be "pneumonia risk", a specific example is shown in Figure 13 below.
  • FIG. 13 exemplarily shows a schematic diagram of another user interface embodiment.
  • the user interface 1 ⁇ 00 displayed on the smartphone 200 is similar to the user interface 1 ⁇ 00 shown in Figure 11, the difference is that the risk level 1 ⁇ 12 in the user interface 1 ⁇ 00 shown in Figure 13 is " Pneumonia risk", the corresponding health icon 1 ⁇ 14 is black, indicating that the user's latest respiratory disease detection has a risk level of "pneumonia risk”.
  • the content statement 1 ⁇ 22 in the result statement 1 ⁇ 20 includes, for example, the text: "Through analysis of your recent test, you have a high risk of respiratory tract infection and may suffer from pneumonia, and you are recommended to see a doctor in time.".
  • the total risk trend 1 ⁇ 32 in the statistical data 1 ⁇ 30 is "increased".
  • the waveform changes from the straight line corresponding to the vertical axis: "respiratory tract infection risk” to the corresponding vertical axis:
  • the straight line of "pneumonia risk” indicates that the user has been tested for respiratory diseases in the past three months, and the resulting risk level has changed from "respiratory tract infection risk” to "pneumonia risk”.
  • the smart phone 200 can instruct the smart watch 300 to automatically collect the user's physiological parameters, and when it is determined that the physiological parameters are abnormal, the user can be prompted to collect audio data.
  • the specific example is similar to that in Figure 9 above, except that the user interface for collecting audio data (For example, the user interface 600 shown in (B) of FIG. 9 ) can be replaced with the user interface 1 ⁇ 00 shown in FIG. 11-FIG.
  • the smart phone 200 can start an audio data collection module (such as a microphone) to collect audio data.
  • the smart phone 200 can determine the detection result according to the collected physiological parameters and audio data. Specific examples are not listed one by one.
  • the smart watch 300 after the smart watch 300 collects the physiological parameters, it can judge whether the physiological parameters are abnormal, and send indication information to the smart phone 200 when it is determined that the physiological parameters are abnormal.
  • the smart phone 200 determines that the physiological parameters are abnormal according to the indication information, it can prompt the user to detect the audio data.
  • the audio data acquisition module (such as a microphone) can be automatically turned on to collect audio data.
  • the specific example is similar to that in Figure 10 above.
  • the smart watch 300 can collect physiological parameters by itself, and when it is determined that the physiological parameter information meets the preset conditions, it prompts the user to collect audio data, or automatically turns on the audio data collection module (such as a microphone ) to collect audio data.
  • the collection of physiological parameters by the smart watch 300 may be triggered by a user operation acting on the smart watch 300; in other embodiments, the collection of physiological parameters by the smart watch 300 may be triggered by a user operation acting on the smart phone 200 Triggered, for example, the smart phone 200 instructs the smart watch 300 to collect physiological parameters in response to a touch operation acting on the detection control 1 ⁇ 43 of the user interface 1 ⁇ 00 shown in FIGS. 11-13 .
  • the smart phone 200 can collect physiological parameters by itself.
  • the smart phone 200 can instruct the smart watch 300 to collect audio data.
  • the smart phone 200 can send instruction information to the smart watch 300, and the smart watch 300 can prompt the user to collect audio data according to the instruction information.
  • the data and interface example are similar to those in Figure 9.
  • the smart watch 300 can display a user interface for collecting audio data in response to user operations, such as the audio data collection column 660 in the user interface 600 shown in FIG.
  • a touch operation for example, a click operation
  • starts an audio data acquisition module for example, a microphone
  • the smart watch 300 acquires the collected physiological parameters, and can determine the infection risk of the respiratory system according to the physiological parameters. In other embodiments, after the smart watch 300 acquires the collected physiological parameters and audio data, it may determine the infection risk of the respiratory system according to the physiological parameters and audio data. In some embodiments, the infection risk of the respiratory system determined by the smart watch 300 may be sent to the smart phone 200 .
  • the present application does not limit the electronic device for determining the infection risk of the respiratory system.
  • the following is an exemplary introduction of the detection methods performed by the first device (that is, the collection device) and the second device (that is, the processing device) under different primary screening modes for respiratory system infections. collaborative relationship.
  • the first device and the second device may be the same device, and in other embodiments, the first device and the second device may be different devices.
  • the first device includes a physiological parameter collection module and an audio data collection module as an example for description.
  • the physiological parameter collection module and audio data collection module please refer to the description of FIG. 1 above.
  • the second device has the structure shown in FIG. 1 , and the sensor for detecting user operation is the pressure sensor 161 on the second device as an example for description.
  • the pressure sensor 161 of the second device detects that the user clicks on the first collection control. For example, when the second device displays the user interface 600 shown in (A) of FIG. 3 through the display screen 130 , the pressure sensor 161 of the second device detects a click operation on the collection control 633 .
  • the pressure sensor 161 reports a click event that the user clicks on the first collection control to the processor 110 .
  • the processor 110 of the second device determines the click event, instructs the physiological parameter collection module of the first device to collect physiological parameters, for example, sends instruction information for instructing collection of physiological parameters to the first device.
  • the physiological parameter collection module of the first device collects physiological parameters in response to the instruction of the second device.
  • the physiological parameter collection module of the first device sends the collected physiological parameters to the processor 110 of the second device.
  • the pressure sensor 161 of the second device detects that the user clicks on the second collection control.
  • the second device displays the user interface 600 shown in FIG. 5 through the display screen 130 , and the pressure sensor 161 of the second device detects a click operation on the acquisition control 663 .
  • the pressure sensor 161 reports a click event that the user clicks on the second collection control to the processor 110 .
  • the processor 110 of the second device determines the click event, instructs the audio data collection module of the first device to collect audio data, for example, sends instruction information for instructing the collection of audio data to the first device.
  • the audio data collection module of the first device starts and collects audio data in response to the instruction of the second device.
  • the audio data collection module of the first device sends the collected audio data to the processor 110 of the second device.
  • the processor 110 of the second device obtains the infection risk of the respiratory system, that is, the detection result, according to the collected physiological parameters and audio data.
  • the processor 110 instructs the display screen 130 to display the detection result.
  • the display screen 130 responds to the instruction of the processor 110 to display the detection result.
  • the second device displays the user interface ⁇ 00 shown in (B) of FIG. 6 and (B) of FIG. 10 through the display screen 130 , and the user interface 1 ⁇ 00 shown in FIGS.
  • sequence of 1-5 and 6-10 shown in FIG. 14 is not limited.
  • examples of user interface embodiments in the scenario of user active detection can refer to the embodiments shown in Figure 3, Figure 5, and Figure 6 above.
  • 1-5 shown in Figure 14 corresponds to Figure 3 above
  • 6-10 shown in FIG. 14 corresponds to the embodiment shown in FIG. 5 above
  • 11-13 shown in FIG. 14 corresponds to the embodiment shown in FIG. 6 above.
  • the pressure sensor 161 of the first device can also detect the click operation of the user clicking on the third collection control, for example, the second device displays the information shown in FIGS. 11-13 through the display screen 130.
  • the pressure sensor 161 of the second device detects a click operation on the detection control 1 ⁇ 43.
  • the processor 110 of the first device receives the click event reported by the pressure sensor 161 that the user clicks on the third collection control, it can instruct the audio data collection module of the first device to collect audio data, and instruct the physiological parameter collection module of the first device to collect Physiological parameters.
  • user interface embodiments refer to the embodiments shown in FIGS. 11-13 above.
  • the physiological parameter collection module of the first device continuously collects physiological parameters, for example, collects physiological parameters according to a first cycle.
  • the physiological parameter collection module of the first device sends the collected physiological parameters to the processor 110 of the second device, for example, sends the collected physiological parameters according to the second period, or sends the collected physiological parameters after collecting the physiological parameters for a preset duration.
  • the processor 110 of the second device determines that the collected physiological parameters are abnormal. For example, it is determined whether the physiological parameter is abnormal each time the physiological parameter is received, or whether the physiological parameter is abnormal when the physiological parameter is received a preset number of times.
  • abnormal physiological parameters please refer to the description of abnormal physiological parameters in Figure 3-13 above.
  • the processor 110 of the second device determines the detection result according to the collected physiological parameters.
  • the processor 110 instructs the display screen 130 to display the detection result.
  • the display screen 130 responds to the instruction of the processor 110 to display the detection result.
  • the second device displays the user interface ⁇ 00 shown in (B) of Figure ⁇ , and the user interface 1 ⁇ 00 shown in FIGS. 11-13 through the display screen 130 .
  • examples of user interface embodiments in the scenario where the device continues to automatically detect can refer to the embodiment shown in Figure 7- Figure ⁇ above, and optionally, 1-6 shown in Figure 15 corresponds to the above Figure ⁇ Example.
  • the physiological parameter collection module of the first device collects physiological parameters.
  • the processor 110 of the second device instructs the physiological parameter collection module of the first device to continuously collect physiological parameters, such as collecting physiological parameters according to the first cycle, In some other embodiments, the processor 110 of the second device instructs the physiological parameter collection module of the first device to collect the physiological parameters when it determines that a click event of clicking the first collection control is received.
  • the physiological parameter collection module of the first device sends the collected physiological parameters to the processor 110 of the second device.
  • the processor 110 of the second device determines that the physiological parameters collected by the first device are abnormal.
  • abnormal physiological parameters please refer to the description of abnormal physiological parameters in Figure 3-13 above.
  • the processor 110 determines that the physiological parameter is abnormal, it instructs the display screen 130 to display a prompt message that the physiological parameter is abnormal.
  • the display screen 130 responds to the instruction of the processor 110, and displays the prompt information of abnormal physiological parameters.
  • the second device displays the user interface 400 shown in (A) of FIG.
  • the second device displays the user interface 600 shown in FIG. 4 through the display screen 130 , and the prompt information is the prompt word 641 of the prompt content 640 in the user interface 600 .
  • the pressure sensor 161 of the second device detects that the user clicks on the second collection control.
  • the second device displays the user interface 600 shown in FIG. 5 through the display screen 130 , and the pressure sensor 161 of the second device detects a click operation on the collection control 663 .
  • the pressure sensor 161 reports a click event that the user clicks on the second collection control to the processor 110 .
  • the processor 110 of the second device determines the click event and instructs the audio data collection module of the first device to collect audio data.
  • the audio data collection module of the first device starts and collects audio data in response to the instruction of the second device.
  • the audio data collection module of the first device sends the collected audio data to the processor 110 of the second device.
  • the processor 110 of the second device determines the detection result according to the collected physiological parameters and audio data.
  • the processor 110 instructs the display screen 130 to display the detection result.
  • the display screen 130 responds to the instruction of the processor 110 to display the detection result.
  • the second device displays the user interface ⁇ 00 shown in (B) of FIG. 6 and (B) of FIG. 10 through the display screen 130 , and the user interface 1 ⁇ 00 shown in FIGS.
  • examples of user interface embodiments in the scenario where the user detects audio data under the prompt of the device can refer to the embodiments shown in Fig. 4 and Fig. 9 above.
  • 3-5 shown in Fig. 16 corresponds to the above The embodiment shown in Fig. 4 and Fig. 9 .
  • the physiological parameter collection module of the first device collects physiological parameters.
  • the processor 110 of the second device instructs the physiological parameter collection module of the first device to continuously collect physiological parameters, such as collecting physiological parameters according to the first cycle, In some other embodiments, the processor 110 of the second device instructs the physiological parameter collection module of the first device to collect the physiological parameters when it determines that a click event of clicking the first collection control is received.
  • the physiological parameter collection module of the first device sends the collected physiological parameters to the processor 110 of the second device.
  • the processor 110 of the second device determines that the physiological parameters collected by the first device are abnormal.
  • abnormal physiological parameters please refer to the description of abnormal physiological parameters in Figure 3-13 above.
  • the processor 110 of the second device determines that the physiological parameter is abnormal, it instructs the audio data collection module of the first device to collect audio data.
  • the audio data collection module of the first device starts and collects audio data in response to the instruction of the second device.
  • the audio data collection module of the first device sends the collected audio data to the processor 110 of the second device.
  • the processor 110 of the second device determines the detection result according to the physiological parameters and audio data collected by the first device.
  • the processor 110 instructs the display screen 130 to display the detection result.
  • the display screen 130 responds to the instruction of the processor 110 to display the detection result.
  • the second device displays the user interface ⁇ 00 shown in (B) of FIG. 6 and (B) of FIG. 10 through the display screen 130 , and the user interface 1 ⁇ 00 shown in FIGS.
  • the example of the user interface embodiment in the scene where the device automatically detects audio data can refer to the embodiment shown in Figure 10 above, and optionally, 3-9 shown in Figure 17 corresponds to the embodiment shown in Figure 10 above .
  • the embodiments of the present application can be applied to different detection scenarios, satisfying different needs of users in different scenarios, covering multiple scenarios, and improving user experience while ensuring the accuracy of detection results.
  • the audio data collection module can be restarted to collect audio data when the physiological parameters are abnormal, so as to reduce the power consumption of the device and increase the product availability.
  • Figure 1 ⁇ is a schematic flowchart of a detection method provided in the embodiment of the present application. This method can be applied to the electronic device 100 shown in FIG. 1 . This method can be applied to the electronic device 100 shown in FIG. 2 . The method may include, but is not limited to, the following steps:
  • S101 The electronic device acquires physiological parameters.
  • the electronic device collects the physiological parameters by itself. In other embodiments, the electronic device receives the physiological parameters collected by other devices. Optionally, the electronic device may instruct other devices to collect the physiological parameters.
  • the physiological parameters include, for example but not limited to, at least one of the following: body temperature, blood oxygen saturation, respiratory rate, heart rate, pulse, and the like.
  • a collection module for collecting physiological parameters refer to the physiological parameter collection module shown in FIG. 1 .
  • the electronic device acquires audio data when it is determined that the physiological parameters meet a preset condition.
  • the preset conditions may include but are not limited to at least one of the following: body temperature is greater than or equal to the body temperature threshold (unit is, for example, Celsius), blood oxygen saturation is less than or equal to the blood oxygen threshold (unit is, for example, percentage), breathing
  • the frequency is greater than or equal to the frequency threshold (for example, times/minute)
  • the heart rate is greater than or equal to the heart rate threshold (for example, times/minute)
  • the pulse is greater than or equal to the pulse threshold (for example, times/minute).
  • physiological parameters satisfying preset conditions represent abnormal physiological parameters.
  • abnormal physiological parameters refer to the descriptions of abnormal physiological parameters shown in FIGS. 3-13 above.
  • the audio data includes, for example but not limited to, at least one of the following: cough sounds, breath sounds, heart sounds, lung sounds, and the like.
  • the electronic device when it determines that the physiological parameter meets the preset condition, it may display prompt information, and the prompt information is used to prompt the user to collect audio data.
  • the electronic device may receive a user operation, such as a user operation acting on the collection option 663 of the user interface 600 shown in FIG. 5 , and collect audio data by itself in response to the user operation.
  • the electronic device may receive audio data collected by other devices, and optionally, the electronic device may instruct other devices to collect audio data in response to the received user operation.
  • other devices connected to the electronic device may receive user operations, collect audio data in response to the user operations, and then send them to the electronic device.
  • the electronic device can display prompt information by itself.
  • the electronic device displays the user interface 400 shown in (A) of FIG.
  • the electronic device displays the user interface 600 shown in FIG. 4
  • the prompt information is the prompt word 641 of the prompt content 640 in the user interface 600 .
  • the electronic device can instruct other connected devices to display prompt information.
  • the electronic device is a smart phone 200, and the smart phone 200 can instruct the connected smart watch 300 to display the user interface shown in (C) of FIG. 9 700 , the prompt information is the text included in the user interface 700 .
  • the audio data may be acquired directly. In some embodiments, when the electronic device determines that the physiological parameter meets the preset condition, it collects the audio data by itself. In some other embodiments, when the electronic device determines that the physiological parameter meets the preset condition, it instructs other devices to collect audio data, and receives the audio data sent by other devices.
  • S103 The electronic device determines the infection risk of the respiratory system according to the physiological parameters and the audio data.
  • the risk of infection may include multiple risk levels, such as low risk, medium risk and high risk.
  • risk levels such as low risk, medium risk and high risk.
  • the user interface ⁇ 00 shown in (B) of FIG. 6 and (B) of FIG. 10 refer to the user interface ⁇ 00 shown in (B) of FIG. 6 and (B) of FIG. 10 .
  • no abnormality, respiratory infection risk, and pneumonia risk specific examples can be found in the user interface 1 ⁇ 00 shown in Figures 11-13.
  • the electronic device can receive indication information sent by other devices, the indication information is used to indicate that the physiological parameters meet the preset conditions, and the indication information is for other devices to collect physiological parameters. Obtained after confirming.
  • the electronic device determines that the physiological parameter satisfies the preset condition according to the above indication information, it acquires the audio data, and the specific process is similar to S102. Then the electronic device can determine the infection risk of the respiratory system according to the physiological parameters and the audio data, and the specific process is similar to S103.
  • the present application can comprehensively analyze physiological parameters and audio data to realize the detection of infection risk of the respiratory system, which has higher accuracy than using only physiological parameters or only audio data to determine the detection result.
  • This application can prompt the user to detect the audio data when the physiological parameters are abnormal, and open the audio data acquisition module (such as a microphone) to collect audio data according to the user operation, or automatically open the audio data acquisition module to collect audio data, instead of opening it all the time Microphones can improve user experience while ensuring the accuracy of detection results, reduce device power consumption, and enhance product competitiveness.
  • the software architecture of the electronic device 100 may also be other architectures, such as the architecture shown in FIG. 19 below.
  • FIG. 19 exemplarily shows a schematic diagram of a software architecture of an electronic device 100 .
  • the electronic device 100 may include a collection module 310 , a full-active detection module 320 , a semi-active detection module 330 , a continuous automatic detection module 340 , a real-time automatic detection module 350 and a risk assessment module 360 .
  • the collection module 310 is used to collect the user's physiological parameters (such as body temperature, blood oxygen saturation, respiratory rate, heart rate, pulse, etc.), and in some embodiments, the collection module 310 is used to collect the user's audio data (such as cough sounds, breath sounds, heart and lung sounds, etc.).
  • the acquisition module 310 may include a physiological parameter acquisition module, such as the sensors in the sensor module 160 shown in FIG. 1 above except the pressure sensor 161 .
  • the collection module 310 may include an audio data collection module, such as the microphone 151 and the pressure sensor 161 shown in FIG. 1 above.
  • the full active detection module 320 is applied to scenarios where users actively detect.
  • the fully active detection module 320 may instruct the collection module 310 to collect physiological parameters and audio data in response to user operations, and the collected physiological parameters and audio data are used to determine the infection risk of the respiratory system.
  • the semi-active detection module 330 is applied to the scene where the user detects audio data under the prompt of the device. In some embodiments, the semi-active detection module 330 can instruct the acquisition module 310 to collect physiological parameters. In some embodiments, the semi-active detection module 330 can determine whether the physiological parameters are abnormal, and prompt the user to detect audio data when it is determined that the physiological parameters are abnormal. In some embodiments, the semi-active detection module 330 may instruct the collection module 310 to collect audio data in response to a user operation. The collected physiological parameters and audio data are used to determine the infection risk of the respiratory system.
  • the continuous automatic detection module 340 is applied to the scene of continuous (long-term) automatic detection of equipment.
  • the continuous automatic detection module 340 may instruct the collection module 310 to collect physiological parameters.
  • the collected physiological parameters are used to determine the infection risk of the respiratory system.
  • the real-time automatic detection module 350 is applied to the scene where the device automatically detects audio data. In some embodiments, the real-time automatic detection module 350 can instruct the collection module 310 to collect physiological parameters. In some embodiments, the real-time automatic detection module 350 can determine whether the physiological parameters are abnormal, and instruct the collection module 310 to collect audio data when it is determined that the physiological parameters are abnormal. . The collected physiological parameters and audio data are used to determine the infection risk of the respiratory system.
  • the risk assessment module 360 is used to analyze and process the collected physiological parameters and audio data to determine the infection risk of the respiratory system. In other embodiments, the risk assessment module 360 is used to analyze and process the collected physiological parameters to determine the infection risk of the respiratory system. For a specific example of determining the infection risk of the respiratory system by the risk assessment module 360, refer to the embodiment shown in FIG. 20 below, which will not be described in detail.
  • the processor 110 shown in FIG. 1 may include a fully automatic detection module 320 , a semi-active detection module 330 , a continuous automatic detection module 340 , a real-time automatic detection module 350 and a risk assessment module 360 shown in FIG. 19 .
  • the structure illustrated in the embodiment of the present application does not constitute a specific limitation on the electronic device 100 .
  • the electronic device 100 may include more or fewer components than shown in the figure, or combine certain components, or separate certain components, or arrange different components.
  • the illustrated components can be realized in hardware, software or a combination of software and hardware.
  • the electronic device 100 shown in FIG. 19 is the second device and may not include the collection module 310 .
  • the electronic device 100 shown in FIG. 19 is the first device and may not include the risk assessment module 360 .
  • FIG. 20 exemplarily shows a schematic structural diagram of a manner of determining an infection risk of the respiratory system.
  • FIG. 20 illustrates that the first device and the second device have the structure shown in FIG. 19 as an example, wherein the collection module 310 belongs to the first device (ie, the collection device), and the risk assessment module 360 belongs to the second device (ie, the processing device).
  • the collection module 310 may include a physiological parameter collection module 311 and an audio data collection module 312 .
  • the risk assessment module 360 may include a first feature extraction module 361 , a preprocessing module 362 , a second feature extraction module 363 , an encoding module 364 and a classification module 365 .
  • the body temperature, blood oxygen saturation, respiratory rate, heart rate, pulse and other data collected by the physiological parameter collection module 311 are referred to as raw physiological data, and the collected body temperature, blood oxygen saturation, respiratory rate, heart rate , pulse and other data are called physiological parameters, which can be understood as the physiological parameter acquisition module 311 converts the detected raw physiological data into physiological parameters. which is converted into an electrical signal.
  • the heart rate sensor 167 can convert changes in vascular dynamics, such as changes in blood pulse rate (heart rate) or blood volume (cardiac output), into electrical signal output through reflection or transmission.
  • the cough sound, breath sound, heart sound, lung sound and other data collected by the audio data collection module 312 are called original audio data
  • the collected cough sound, breath sound, heart sound, lung sound and other data are called Audio data
  • the pressure sensor 161 is used to sense the pressure signal, which can convert the pressure signal into an electrical signal.
  • the microphone 151 is used to convert sound signals into electrical signals.
  • the physiological parameters collected by the physiological parameter collection module 311 can be transmitted to the first feature extraction module 361 for feature extraction, for example but not limited to include at least one of the following: singular value decomposition (singular value decomposition, SVD), Principal component analysis (principal component analysis, PCA), linear discriminant analysis, etc.
  • FIG. 20 may refer to the output of the first feature extraction module 361 as physiological feature data.
  • the audio data collected by the audio data collection module 312 can be transmitted to the preprocessing module 362 for preprocessing.
  • amplitude normalization, median filtering and bandpass filtering can be performed in sequence, wherein, Amplitude normalization can eliminate the influence of the magnitude of the data and its own local fluctuations, median filtering and bandpass filtering can eliminate the interference of noise, and the data output by the preprocessing module 362 can be transmitted to the second feature extraction module 363 for feature extraction, for example
  • the original feature extraction is performed first, and then the statistical features are aggregated.
  • the features extracted in the original feature extraction include, for example but not limited to, at least one of the following: Mel-frequency cepstral coefficients, differential features, and spectral flatness.
  • the features obtained from the aggregated statistical features include, for example but not limited to, at least one of the following: mean, variance, kurtosis, skewness, distance features.
  • FIG. 20 may refer to the output of the second feature extraction module 363 as physiological feature data. Subsequent feature extraction after preprocessing can improve the accuracy of estimating the risk of respiratory infection.
  • the output of the first feature extraction module 361 physiological feature data
  • the output of the second feature extraction module 363 audio feature data, which can be transmitted to the encoding module 364 for encoding.
  • Tree gradient boosting decison tree, GBDT
  • GBDT gradient boosting decison tree
  • the obtained combination can be [0,1,1,1,0], which specifically means: abnormal body temperature (corresponding to the first code 0 of the combination ), respiratory rate is normal (corresponding to the second code 1 of the combination), blood oxygen saturation is normal (corresponding to the third code 1 of the combination), heart rate is normal (corresponding to the fourth code 1 of the combination), audio data (cough sound and breath sounds) are abnormal (corresponding to the fifth code 0 of the combination).
  • the output of the coding module 364 can be transmitted to the classification module 365 for classification, so as to obtain the infection risk of the respiratory system.
  • the output of the encoding module 364 can be input into a logistic regression (logistic regression, LR) model, and the risk level of the output includes, for example but not limited to, low risk, medium risk, and high risk, or no abnormality, respiratory system infection risk, and pneumonia risk.
  • the infection risk of the respiratory system may also include specific detection results of each feature, for example, the specific detection results of body temperature may be statistical data within 7 days.
  • the above-mentioned physiological parameters can be collected by the physiological parameter collection module 311 for a long time (continuously), and the above-mentioned audio data can be collected in real time after the audio data collection module 312 is turned on when the physiological parameters are abnormal.
  • the process is user-insensitive, which improves user experience while reducing power consumption, making the product more competitive.
  • the combination of real-time detection and long-term tracking greatly improves the user experience while ensuring the accuracy of the evaluation results.
  • words such as “first” and “second” are only used for the purpose of distinguishing descriptions, and cannot be understood as indicating or implying relative importance, nor can they be understood as indicating or implying order .
  • Features defined as “first” and “second” may explicitly or implicitly include one or more of these features.
  • words such as “exemplary” or “for example” are used as examples, illustrations or descriptions. Any embodiment or design scheme described as “exemplary” or “for example” in the embodiments of the present application shall not be interpreted as being more preferred or more advantageous than other embodiments or design schemes. Rather, the use of words such as “exemplary” or “such as” is intended to present related concepts in a concrete manner.
  • the processes can be completed by computer programs or hardware related to the computer programs.
  • the computer programs can be stored in computer-readable storage media.
  • the computer programs During execution, it may include the processes of the foregoing method embodiments.
  • the aforementioned storage medium includes: various media capable of storing computer program codes such as read-only memory (ROM) or random access memory (RAM), magnetic disk or optical disk.

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Abstract

一种检测方法及相关设备，该方法应用于第一电子设备（200），该方法包括：检测第一操作；响应于第一操作，向第二电子设备（300）发送第一信息；接收第二电子设备（300）基于第一信息发送的生理参数信息；当确定生理参数信息满足预设条件时，获取音频信息；根据生理参数信息和音频信息确定第一生理信息；显示第一生理信息。可以让用户便捷地检测呼吸系统的感染风险，同时保证了检测结果的准确性和设备的低功耗。

Description

一种检测方法及相关设备
本申请要求于2021年06月29日提交中国专利局、申请号为202110725573.0、申请名称为“一种检测方法及相关设备”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及计算机技术领域，尤其涉及一种检测方法及相关设备。
背景技术
呼吸系统疾病是一种常见病、多发病，疾病种类复杂，发病率逐年升高，其中下呼吸道感染严重影响健康，致死率高。呼吸系统感染具有相似的症状如咳嗽、发热、呼吸困难等。严重急性呼吸道感染的临床表现例如包括腋下体温≥3≥℃、咳嗽或咽痛、气促(呼吸频率≥25次/分钟)或呼吸困难。呼吸系统感染中，肺炎的严重程度最高，肺炎为急性呼吸系统疾病，用户有感知，进展快，类型多，病原体生长超过宿主防御能力时，导致肺泡腔内出现渗出物，引发肺炎。肺炎的典型症状是咳嗽、咳痰、呼吸急促、呼吸困难、发热、肺部固定啰音。
用户出现上述症状后，通常自行前往医院等专业场所，由专业人员通过胸部影像学、血常规、痰培养等技术进行诊断，但这样诊断复杂，费用昂贵且舒适性差，用户可能需要经常前往医院，费时费力，难以满足日常检测的便捷性和高效性的需求。
发明内容
本申请实施例公开了一种检测方法及相关设备，可以让用户便捷地检测呼吸系统的感染风险，同时保证了检测结果的准确性和设备的低功耗。
第一方面，本申请实施例提供了一种检测方法，应用于第一电子设备，该方法包括：检测第一操作；响应于上述第一操作，向第二电子设备发送第一信息；接收上述第二电子设备基于上述第一信息发送的生理参数信息；当确定上述生理参数信息满足预设条件时，获取音频信息；根据上述生理参数信息和上述音频信息确定第一生理信息；显示上述第一生理信息。
在一些实施例中，第一电子设备为移动终端，例如智能手机，第二电子设备为可穿戴设备，例如智能手环、智能手表。
在一些实施例中，第一生理信息用于指示用户的呼吸系统的感染风险等级，例如为低风险、中风险或高风险，或者例如为未见异常、呼吸道感染风险或肺炎风险。
本申请中，用户可以通过第一电子设备和第二电子设备检测呼吸系统的感染风险(即获取第一生理信息)，并且第一生理信息是结合生理参数和音频信息确定的，检测结果的准确性高，满足便捷性和高效性的需求。并且，当生理参数满足预设条件时再获取音频信息(例如开启麦克风采集音频信息)，减少电子设备的功耗，产品竞争力更高。
在一种可能的实现方式中，上述生理参数信息包括以下一项或多项：体温、血氧饱和度、呼吸频率、心率、脉搏，上述音频信息包括以下一项或多项：咳嗽音、呼吸音、心音、肺音。
在一种可能的实现方式中，上述预设条件包括以下一项或多项：体温大于或等于预设体温阈值，血氧饱和度小于或等于预设血氧阈值，呼吸频率大于或等于预设频率阈值，心率大 于或等于预设心率阈值，脉搏大于或等于预设脉搏阈值。
在一种可能的实现方式中，上述生理参数信息是上述第二电子设备基于上述第一信息周期性发送的。
在一些实施例中，上述第一操作用于开启周期性采集生理参数信息的功能，上述第一信息用于指示上述第二电子设备周期性采集上述生理参数信息。
本申请中，生理参数信息是周期性采集得到的，也可理解为是长时间采集得到的，通过这样的生理参数信息确定第一生理信息，避免偶然情况的影响，准确性更高。
在一种可能的实现方式中，上述第一信息用于指示上述第二电子设备在第一采集时段内采集上述生理参数信息。
在一种可能的实现方式中，上述当确定上述生理参数信息满足预设条件时，获取音频信息，包括：当确定上述生理参数信息满足上述预设条件时，显示第一用户界面，上述第一用户界面包括用于提示检测上述音频信息的第二信息；检测作用于上述第一用户界面的第二操作；响应于上述第二操作，显示第二用户界面；基于上述第二用户界面采集上述音频信息。
在一些实施例中，该方法还包括：检测作用于上述第二用户界面的第一采集操作，响应于上述第一采集操作，开启上述第一电子设备的麦克风采集上述音频信息。在一些实施例中，上述音频信息为上述第一电子设备在第二采集时段内采集得到的。
本申请中，当生理参数满足预设条件时，第一电子设备提示用户检测音频信息，后续检测到用户操作的情况下，再显示采集音频信息的用户界面，以及开启麦克风采集音频信息，而不是一开始就开启麦克风采集音频信息，减少第一电子设备的功耗。
在一种可能的实现方式中，上述当确定上述生理参数信息满足预设条件时，获取音频信息，包括：当确定上述生理参数信息满足上述预设条件时，向上述第二电子设备发送第三信息，上述第三信息用于上述第二电子设备显示第三用户界面，上述第三用户界面用于采集上述音频信息；接收上述第二电子设备发送的上述音频信息。
在一些实施例中，上述第三信息具体用于上述第二电子设备先显示提示信息，提示信息用于提示检测上述音频信息，以及在检测到第二采集操作的情况下，显示采集音频信息的第三用户界面。在一些实施例中，上述第二电子设备显示上述第三用户界面时，开启麦克风采集音频信息。
本申请中，当生理参数满足预设条件时，第一电子设备向第二电子设备发送第三信息，以使第二电子设备提示用户检测音频信息，后续第二电子设备检测到用户操作的情况下，再显示采集音频信息的用户界面，以及开启麦克风采集音频信息，而不是一开始就开启麦克风采集音频信息，减少第二电子设备的功耗。
在一种可能的实现方式中，上述第一生理信息用于表征用户的呼吸系统的感染风险，上述根据上述生理参数信息和上述音频信息确定第一生理信息，包括：对上述生理参数信息进行特征提取以得到第一特征，对上述音频信息进行特征提取以得到第二特征；对上述第一特征和上述第二特征进行编码以得到第一编码；对上述第一编码进行分类以确定上述第一生理信息。
在一种可能的实现方式中，该方法还包括：向上述第二电子设备发送上述第一生理信息。
第二方面，本申请实施例提供了又一种检测方法，应用于第一电子设备，该方法包括：接收第二电子设备发送的第一信息，上述第一信息用于指示生理参数信息满足预设条件；根据上述第一信息，显示第一用户界面，上述第一用户界面包括用于提示检测音频信息的第二 信息；检测作用于上述第一用户界面的第一操作；响应于上述第一操作，显示第二用户界面，上述第二用户界面用于获取上述音频信息；根据上述生理参数信息和上述音频信息确定第一生理信息；显示上述第一生理信息。
在一些实施例中，第一电子设备为移动终端，例如智能手机，第二电子设备为可穿戴设备，例如智能手环、智能手表。
在一些实施例中，第一生理信息用于指示用户的呼吸系统的感染风险等级，例如为低风险、中风险或高风险，或者例如为未见异常、呼吸道感染风险或肺炎风险。
本申请中，用户可以通过第一电子设备和第二电子设备检测呼吸系统的感染风险(即获取第一生理信息)，并且第一生理信息是结合生理参数和音频信息确定的，检测结果的准确性高，满足便捷性和高效性的需求。并且，当生理参数满足预设条件时提示用户检测音频信息，后续检测到用户操作的情况下，再显示采集音频信息的用户界面，以及开启麦克风采集音频信息，而不是一开始就开启麦克风采集音频信息，减少第一电子设备的功耗。
在一种可能的实现方式中，上述生理参数信息包括以下一项或多项：体温、血氧饱和度、呼吸频率、心率、脉搏，上述音频信息包括以下一项或多项：咳嗽音、呼吸音、心音、肺音。
在一种可能的实现方式中，上述预设条件包括以下一项或多项：体温大于或等于预设体温阈值，血氧饱和度小于或等于预设血氧阈值，呼吸频率大于或等于预设频率阈值，心率大于或等于预设心率阈值，脉搏大于或等于预设脉搏阈值。
在一种可能的实现方式中，上述接收第二电子设备发送的第一信息之前，该方法还包括：检测第二操作；响应于上述第二操作，向上述第二电子设备发送第三信息，上述第一信息是上述第二电子设备基于上述第三信息确定的。
在一种可能的实现方式中，该方法还包括：上述第二电子设备向上述第一电子设备发送上述生理参数信息。在一些实施例中，上述生理参数信息是和上述第一信息一起发送的。
在一些实施例中，上述第三信息用于指示上述第二电子设备采集上述生理参数信息。在一些实施例中，上述第三信息用于指示上述第二电子设备确定上述生理参数信息满足上述预设条件时，向上述第一电子设备发送上述第一信息。
在一种可能的实现方式中，上述第一信息是上述第二电子设备响应于检测到的第三操作确定的。
本申请中，第二电子设备采集生理参数信息后，可以自行判断生理参数信息是否满足预设条件，并在生理参数信息满足预设条件时通知第一电子设备，第一电子设备只需采集音频信息和确定第一生理信息，减小第一电子设备的处理压力。
在一种可能的实现方式中，上述根据上述第一信息，显示第一用户界面之前，该方法还包括：根据上述第一信息，显示第三用户界面，上述第三用户界面为包括上述第二信息的锁屏界面；检测解锁操作；上述根据上述第一信息，显示第一用户界面，包括：响应于上述解锁操作，根据上述第一信息显示上述第一用户界面。
在一些实施例中，上述响应于上述解锁操作，根据上述第一信息显示上述第一用户界面，包括：响应于上述解锁操作，进行用户的身份认证，确定上述身份认证通过时，根据上述第一信息显示上述第一用户界面。
在一种可能的实现方式中，上述第一生理信息用于表征用户的呼吸系统的感染风险，上述根据上述生理参数信息和上述音频信息确定第一生理信息，包括：对上述生理参数信息进行特征提取以得到第一特征，对上述音频信息进行特征提取以得到第二特征；对上述第一特征和上述第二特征进行编码以得到第一编码；对上述第一编码进行分类以确定上述第一生理 信息。
在一种可能的实现方式中，该方法还包括：向上述第二电子设备发送上述第一生理信息。
第三方面，本申请实施例提供了又一种检测方法，应用于第一电子设备，该方法包括：采集生理参数信息；当确定上述生理参数信息满足预设条件时，显示第一用户界面，上述第一用户界面包括用于提示检测音频信息的第一信息；检测作用于上述第一用户界面的第一操作；响应于上述第一操作，显示第二用户界面，上述第二用户界面用于获取上述音频信息；根据上述生理参数信息和上述音频信息确定第一生理信息；显示上述第一生理信息。
在一些实施例中，第一生理信息用于指示用户的呼吸系统的感染风险等级，例如为低风险、中风险或高风险，或者例如为未见异常、呼吸道感染风险或肺炎风险。
本申请中，用户可以通过第一电子设备检测呼吸系统的感染风险(即获取第一生理信息)，并且第一生理信息是结合生理参数和音频信息确定的，检测结果的准确性高，满足便捷性和高效性的需求。并且，当生理参数满足预设条件时提示用户检测音频信息，后续检测到用户操作的情况下，再显示采集音频信息的用户界面，以及开启麦克风采集音频信息，而不是一开始就开启麦克风采集音频信息，减少第一电子设备的功耗。
在一种可能的实现方式中，上述生理参数信息包括以下一项或多项：体温、血氧饱和度、呼吸频率、心率、脉搏，上述音频信息包括以下一项或多项：咳嗽音、呼吸音、心音、肺音。
在一种可能的实现方式中，上述预设条件包括以下一项或多项：体温大于或等于预设体温阈值，血氧饱和度小于或等于预设血氧阈值，呼吸频率大于或等于预设频率阈值，心率大于或等于预设心率阈值，脉搏大于或等于预设脉搏阈值。
在一种可能的实现方式中，上述采集生理参数信息之前，该方法还包括：检测第二操作；上述采集生理参数信息，包括：响应于上述第二操作，采集上述生理参数信息。
在一些实施例中，上述第二操作用于开启周期性采集生理参数信息的功能，上述生理参数信息是上述第一电子设备周期性采集得到的。在另一些实施例中，上述生理参数信息是在第一采集时段采集得到的。
本申请中，生理参数的采集方式可以为是周期性采集，避免偶然情况的影响，准确性更高，也可以是在预设的第一采集时段内采集，减少设备功耗。生理参数的采集方式可以是根据第二操作确定的，更加灵活和符合用户需求。
在一种可能的实现方式中，上述采集生理参数信息之前，该方法还包括：接收第二电子设备发送的第二信息，上述第二信息为上述第二电子设备响应于检测到的第三操作确定的；上述采集生理参数信息，包括：基于上述第二信息，采集上述生理参数信息。
在一些实施例中，第一电子设备为可穿戴设备，例如智能手环、智能手表。第二电子设备为移动终端，例如智能手机。
本申请中，触发获取第一生理信息的用户操作不仅可以是作用于第一电子设备上的，也可以是作用于第二电子设备上的，检测呼吸系统的感染风险的方式更加灵活。
在一种可能的实现方式中，上述第一生理信息用于表征用户的呼吸系统的感染风险，上述根据上述生理参数信息和上述音频信息确定第一生理信息，包括：对上述生理参数信息进行特征提取以得到第一特征，对上述音频信息进行特征提取以得到第二特征；对上述第一特征和上述第二特征进行编码以得到第一编码；对上述第一编码进行分类以确定上述第一生理信息。
在一种可能的实现方式中，该方法还包括：向上述第二电子设备发送上述第一生理信息。
第四方面，本申请实施例提供了又一种检测方法，应用于第一电子设备，该方法包括：检测第一操作；响应于上述第一操作，向第二电子设备发送第一信息；接收上述第二电子设备基于上述第一信息发送的生理参数信息；当确定上述生理参数信息满足预设条件时，采集音频信息；根据上述生理参数信息和上述音频信息确定第一生理信息；显示上述第一生理信息。
在一些实施例中，上述当确定上述生理参数信息满足预设条件时，采集音频信息，包括：当确定上述生理参数信息满足上述预设条件时，开启上述第一电子设备的麦克风采集上述音频信息。在一些实施例中，上述音频信息为上述第一电子设备在第一采集时段采集得到的。
本申请中，用户可以通过第一电子设备和第二电子设备检测呼吸系统的感染风险(即获取第一生理信息)，并且第一生理信息是结合生理参数和音频信息确定的，检测结果的准确性高，满足便捷性和高效性的需求。并且，当生理参数满足预设条件时，第一电子设备自动开启麦克风采集音频信息，而不是一开始就开启麦克风采集音频信息，减少第一电子设备的功耗，用户也无需手动检测音频信息，使用更便捷。
在一种可能的实现方式中，第一电子设备为移动终端，例如智能手机，第二电子设备为可穿戴设备，例如智能手环、智能手表。
在一种可能的实现方式中，第一生理信息用于指示用户的呼吸系统的感染风险等级，例如为低风险、中风险或高风险，或者例如为未见异常、呼吸道感染风险或肺炎风险。
在一种可能的实现方式中，上述生理参数信息包括以下一项或多项：体温、血氧饱和度、呼吸频率、心率、脉搏，上述音频信息包括以下一项或多项：咳嗽音、呼吸音、心音、肺音。
在一种可能的实现方式中，上述预设条件包括以下一项或多项：体温大于或等于预设体温阈值，血氧饱和度小于或等于预设血氧阈值，呼吸频率大于或等于预设频率阈值，心率大于或等于预设心率阈值，脉搏大于或等于预设脉搏阈值。
第五方面，本申请实施例提供了又一种检测方法，应用于第一电子设备，该方法包括：接收第二电子设备发送的第一信息，上述第一信息用于指示生理参数信息满足预设条件；根据上述第一信息，采集音频信息；根据上述生理参数信息和上述音频信息确定第一生理信息；显示上述第一生理信息。
在一些实施例中，上述根据上述第一信息，采集音频信息，包括：根据上述第一信息，开启上述第一电子设备的麦克风采集上述音频信息。在一些实施例中，上述音频信息为上述第一电子设备在第一采集时段采集得到的。
本申请中，用户可以通过第一电子设备和第二电子设备检测呼吸系统的感染风险(即获取第一生理信息)，并且第一生理信息是结合生理参数和音频信息确定的，检测结果的准确性高，满足便捷性和高效性的需求。并且，当根据第一信息确定生理参数满足预设条件时，第一电子设备自动开启麦克风采集音频信息，而不是一开始就开启麦克风采集音频信息，减少第一电子设备的功耗，用户也无需手动检测音频信息，使用更便捷。
在一种可能的实现方式中，第一电子设备为移动终端，例如智能手机，第二电子设备为可穿戴设备，例如智能手环、智能手表。
在一种可能的实现方式中，第一生理信息用于指示用户的呼吸系统的感染风险等级，例如为低风险、中风险或高风险，或者例如为未见异常、呼吸道感染风险或肺炎风险。
在一种可能的实现方式中，上述生理参数信息包括以下一项或多项：体温、血氧饱和度、 呼吸频率、心率、脉搏，上述音频信息包括以下一项或多项：咳嗽音、呼吸音、心音、肺音。
在一种可能的实现方式中，上述预设条件包括以下一项或多项：体温大于或等于预设体温阈值，血氧饱和度小于或等于预设血氧阈值，呼吸频率大于或等于预设频率阈值，心率大于或等于预设心率阈值，脉搏大于或等于预设脉搏阈值。
在一种可能的实现方式中，上述接收第二电子设备发送的第一信息之前，该方法还包括：检测第一操作；响应于上述第一操作，向上述第二电子设备发送第二信息，上述第一信息是上述第二电子设备基于上述第二信息确定的。
在一种可能的实现方式中，该方法还包括：上述第二电子设备向上述第一电子设备发送上述生理参数信息。在一些实施例中，上述生理参数信息是和上述第一信息一起发送的。
在一些实施例中，上述第二信息用于指示上述第二电子设备采集上述生理参数信息。在一些实施例中，上述第二信息用于指示上述第二电子设备确定上述生理参数信息满足上述预设条件时，向上述第一电子设备发送上述第一信息。
在一种可能的实现方式中，上述第一信息是上述第二电子设备响应于检测到的第二操作确定的。
本申请中，第二电子设备采集生理参数信息后，可以自行判断生理参数信息是否满足预设条件，并在生理参数信息满足预设条件时通知第一电子设备，第一电子设备只需采集音频信息和确定第一生理信息，减小第一电子设备的处理压力。
第六方面，本申请实施例提供了又一种检测方法，应用于第一电子设备，该方法包括：采集生理参数信息；当确定上述生理参数信息满足预设条件时，采集音频信息；根据上述生理参数信息和上述音频信息确定第一生理信息；显示上述第一生理信息。
在一些实施例中，上述当确定上述生理参数信息满足预设条件时，采集音频信息，包括：当确定上述生理参数信息满足上述预设条件时，开启上述第一电子设备的麦克风采集上述音频信息。在一些实施例中，上述音频信息为上述第一电子设备在第一采集时段采集得到的。
本申请中，用户可以通过第一电子设备检测呼吸系统的感染风险(即获取第一生理信息)，并且第一生理信息是结合生理参数和音频信息确定的，检测结果的准确性高，满足便捷性和高效性的需求。并且，当生理参数满足预设条件时，第一电子设备自动开启麦克风采集音频信息，而不是一开始就开启麦克风采集音频信息，减少第一电子设备的功耗，用户也无需手动检测音频信息，使用更便捷。
在一种可能的实现方式中，上述采集生理参数信息之前，该方法还包括：检测第一操作；上述采集生理参数信息，包括：响应于上述第一操作，采集上述生理参数信息。
在一些实施例中，上述第一操作用于开启周期性采集生理参数信息的功能，上述生理参数信息是上述第一电子设备周期性采集得到的。在另一些实施例中，上述生理参数信息是在第一采集时段采集得到的。
本申请中，生理参数的采集方式可以为是周期性采集，避免偶然情况的影响，准确性更高，也可以是在预设的第一采集时段内采集，减少设备功耗。生理参数的采集方式可以是根据第一操作确定的，更加灵活和符合用户需求。
在一种可能的实现方式中，上述采集生理参数信息之前，该方法还包括：接收第二电子设备发送的第一信息，上述第一信息为上述第二电子设备响应于检测到的第二操作确定的；上述采集生理参数信息，包括：基于上述第一信息，采集上述生理参数信息。
在一些实施例中，第一电子设备为可穿戴设备，例如智能手环、智能手表。第二电子设 备为移动终端，例如智能手机。
本申请中，触发获取第一生理信息的用户操作不仅可以是作用于第一电子设备上的，也可以是作用于第二电子设备上的，检测呼吸系统的感染风险的方式更加灵活。
在一种可能的实现方式中，第一生理信息用于指示用户的呼吸系统的感染风险等级，例如为低风险、中风险或高风险，或者例如为未见异常、呼吸道感染风险或肺炎风险。
在一种可能的实现方式中，上述生理参数信息包括以下一项或多项：体温、血氧饱和度、呼吸频率、心率、脉搏，上述音频信息包括以下一项或多项：咳嗽音、呼吸音、心音、肺音。
在一种可能的实现方式中，上述预设条件包括以下一项或多项：体温大于或等于预设体温阈值，血氧饱和度小于或等于预设血氧阈值，呼吸频率大于或等于预设频率阈值，心率大于或等于预设心率阈值，脉搏大于或等于预设脉搏阈值。
第七方面，本申请实施例提供了一种电子设备，包括收发器、处理器和存储器，上述存储器用于存储计算机程序，上述处理器调用上述计算机程序，用于执行本申请实施例第一方面至第六方面，以及第一方面至第六方面的任意一种实现方式提供的检测方法。
第八方面，本申请实施例提供了一种计算机存储介质，该计算机存储介质存储有计算机程序，该计算机程序被处理器执行时，实现本申请实施例第一方面至第六方面，以及第一方面至第六方面的任意一种实现方式提供的检测方法。
第九方面，本申请实施例提供了一种计算机程序产品，当该计算机程序产品在电子设备上运行时，使得该电子设备执行本申请实施例第一方面至第六方面，以及第一方面至第六方面的任意一种实现方式提供的检测方法。
第十方面，本申请实施例提供一种电子设备，该电子设备包括执行本申请任一实施例所介绍的方法或装置。上述电子设备例如为芯片。
应当理解的是，本申请中对技术特征、技术方案、有益效果或类似语言的描述并不是暗示在任意的单个实施例中可以实现所有的特点和优点。相反，可以理解的是对于特征或有益效果的描述意味着在至少一个实施例中包括特定的技术特征、技术方案或有益效果。因此，本说明书中对于技术特征、技术方案或有益效果的描述并不一定是指相同的实施例。进而，还可以任何适当的方式组合本实施例中所描述的技术特征、技术方案和有益效果。本领域技术人员将会理解，无需特定实施例的一个或多个特定的技术特征、技术方案或有益效果即可实现实施例。在其他实施例中，还可在没有体现所有实施例的特定实施例中识别出额外的技术特征和有益效果。
附图说明
以下对本申请实施例用到的附图进行介绍。
图1是本申请实施例提供的一种电子设备的硬件结构示意图；
图2是本申请实施例提供的一种电子设备的软件架构示意图；
图3-图13是本申请实施例提供的一些用户界面实施例的示意图；
图14-图17是本申请实施例提供的一些检测方法的协作示意图；
图1≥是本申请实施例提供的一种检测方法的流程示意图；
图19是本申请实施例提供的又一种电子设备的结构示意图；
图20是本申请实施例提供的一种呼吸系统的感染风险的确定方式的示意图。
具体实施方式
下面结合本申请实施例中的附图对本申请实施例进行描述。本申请实施例的实施方式部分使用的术语仅用于对本申请的具体实施例进行解释，而非旨在限定本申请。
本申请实施例提供了一种检测方法，应用于第一设备和第二设备。第一设备可以采集用户的生理参数(例如体温、血氧饱和度、呼吸频率、心率、脉搏等)，也可以采集用户的音频数据(例如咳嗽音、呼吸音、心音、肺音等)。第二设备可以基于采集的生理参数和音频数据获取用户的呼吸系统的感染风险，例如未见异常、呼吸道感染风险或肺炎风险等风险等级。用户可以随时随地通过第一设备和第二设备进行呼吸系统疾病的筛查，成本较低，满足了日常检测的便捷性和高效性需求，并且，实现了呼吸系统疾病的监测预警，例如在发病前或发病时提醒用户就诊，对于用户早感知、早干预有积极意义，提高用户认知和就诊率。
在一些实施例中，本申请实施例可以在生理参数异常时才启动用于采集音频数据的模块(简称音频数据采集模块，例如麦克风)，音频数据采集模块采集的音频数据用于确定呼吸系统的感染风险，节省设备功耗，产品可用性更高。
本申请实施例中涉及的电子设备可以是手机、平板电脑、手持计算机、个人数字助理(Personal Digital Assistant，PDA)等用户终端设备，智能电视、智能摄像头等智能家居设备，智能手环、智能手表、智能眼镜等可穿戴设备，或其他桌面型、膝上型、笔记本电脑、超级移动个人计算机(Ultra-mobile Personal Computer，UMPC)、上网本、智慧屏等设备。
可以理解地，第一设备也可以称为采集设备，第二设备也可以称为处理设备，采集设备和处理设备仅用于区分执行检测方法的设备角色。在一些实施例中，第一设备和第二设备可以是同一设备，例如为智能手机。在另一些实施例中，第一设备和第二设备可以是不同设备，例如第一设备为智能手表，第二设备为智能手机。可选地，第一设备可以有多个，可选地，第二设备可以有多个。
接下来介绍本申请实施例示例性的电子设备100。在一些实施例中，第一设备和第二设备是同一设备，例如电子设备100。在另一些实施例中，第一设备和第二设备是不同设备，可选地，第一设备和/或第二设备的结构可以和电子设备100一致。
请参见图1，图1示出了电子设备100的硬件结构示意图。
如图1所示，电子设备100可以包括处理器110，存储器120，显示屏130，通信模块140，音频模块150以及传感器模块160。其中，通信模块140可以包括移动通信模块141和无线通信模块142。音频模块150可以包括麦克风151和扬声器152。传感器模块160可以包括压力传感器161，加速度传感器162，骨传导传感器163，温度传感器164，血氧传感器165，脉搏传感器166，心率传感器167等。
可以理解的是，本申请实施例示意的结构并不构成对电子设备100的具体限定。在本申请另一些实施例中，电子设备100可以包括比图示更多或更少的部件，或者组合某些部件，或者拆分某些部件，或者不同的部件布置。图示的部件可以以硬件，软件或软件和硬件的组合实现。例如，图1所示的电子设备100为第二设备，可以不包括音频模块150和传感器模块160。
处理器110可以包括一个或多个处理单元，例如，处理器110可以包括应用处理器(application processor，AP)，调制解调处理器(modem)，图形处理器(graphics processing unit，GPU)，图像信号处理器(image signal processor，ISP)，控制器，存储器，视频编解码器，数字信号处理器(digital signal processor，DSP)，基带处理器，和/或神经网络处理器(neural-network processing unit，NPU)等。可选地，不同的处理单元可以是独立的器件，也可以集成在一个或 多个处理器中。可选地，控制器可以是电子设备100的神经中枢和指挥中心。控制器可以根据指令操作码和时序信号，产生操作控制信号，完成取指令和执行指令的控制。
在一些实施例中，处理器110中还可以设置存储器，用于存储指令和数据。可选地，处理器110中的存储器为高速缓冲存储器。该存储器可以保存处理器110刚用过或循环使用的指令或数据。如果处理器110需要再次使用该指令或数据，可从所述存储器中直接调用。避免了重复存取，减少了处理器110的等待时间，因而提高了系统的效率。
存储器120可以用于存储计算机可执行程序代码，上述可执行程序代码包括指令。处理器110可以通过运行存储在存储器120的指令，从而执行电子设备100的各种功能应用以及数据处理，例如执行下图14-图1≥所示的检测方法中至少一个步骤，图20所示过程中至少一个步骤。存储器120可以包括存储程序区和存储数据区。其中，存储程序区可存储操作系统，至少一个功能所需的应用程序(比如声音播放功能，图像播放功能等)等。存储数据区可存储电子设备100使用过程中所创建的数据(比如音频数据，电话本等)等。此外，存储器120可以包括高速随机存取存储器，还可以包括非易失性存储器，例如至少一个磁盘存储器件，闪存器件，通用闪存存储器(universal flash storage，UFS)等。
显示屏130用于显示图像，视频等。显示屏130包括显示面板，显示面板可以包括非自发光屏和自发光屏。非自发光屏可以为液晶显示屏(liquid crystal display，LCD)。自发光屏可以为有机发光二极管(organic light-emitting diode，OLED)，有源矩阵有机发光二极体或主动矩阵有机发光二极体(active-matrix organic light emitting diode的，AMOLED)，柔性发光二极管(flex light-emitting diode，FLED)，Miniled，MicroLed，Micro-oLed，量子点发光二极管(quantum dot light emitting diodes，QLED)等。可选地，电子设备100可以包括一个或多个显示屏130。
在一些实施例中，电子设备100可以通过GPU，显示屏130，以及AP等实现显示功能。GPU为图像处理的微处理器，连接显示屏130和AP。GPU用于执行数学和几何计算，用于图形渲染。处理器110可包括一个或多个GPU，其执行程序指令以生成或改变显示信息。
在一些实施例中，电子设备100的无线通信功能可以通过天线(未示出)，移动通信模块141，无线通信模块142，调制解调处理器(未示出)以及基带处理器(未示出)等实现。
可选地，天线用于发射和接收电磁波信号。可选地，电子设备100中可以包含多个天线，每个天线可用于覆盖单个或多个通信频带。不同的天线还可以复用，以提高天线的利用率，例如，可以将天线复用为无线局域网的分集天线。
可选地，移动通信模块141可以提供应用在电子设备100上的包括2G/3G/4G/5G等无线通信的解决方案。移动通信模块141可以包括至少一个滤波器，开关，功率放大器，低噪声放大器(low noise amplifier，LNA)等。移动通信模块141可以由天线接收电磁波，并对接收的电磁波进行滤波，放大等处理，传送至调制解调处理器进行解调。移动通信模块141还可以对经调制解调处理器调制后的信号放大，经天线转为电磁波辐射出去。可选地，移动通信模块141的至少部分功能模块可以被设置于处理器110中。可选地，移动通信模块141的至少部分功能模块可以与处理器110的至少部分模块被设置在同一个器件中。
可选地，调制解调处理器可以包括调制器和解调器。其中，调制器用于将待发送的低频基带信号调制成中高频信号。解调器用于将接收的电磁波信号解调为低频基带信号。随后解调器将解调得到的低频基带信号传送至基带处理器处理。低频基带信号经基带处理器处理后，被传递给AP。AP通过音频设备(例如扬声器152等)输出声音信号，或通过显示屏130显示图像或视频。可选地，调制解调处理器可以是独立的器件。可选地，调制解调处理器可以独立于处理器110，与移动通信模块141或其他功能模块设置在同一个器件中。
可选地，无线通信模块142可以提供应用在电子设备100上的包括无线局域网(wireless local area networks，WLAN)(如无线保真(wireless fidelity，Wi-Fi)网络)，蓝牙(bluetooth，BT)，全球导航卫星系统(global navigation satellite system，GNSS)，调频(frequency modulation，FM)，近距离无线通信技术(near field communication，NFC)，红外技术(infrared，IR)等无线通信的解决方案。无线通信模块142可以是集成至少一个通信处理模块的一个或多个器件。无线通信模块142经由天线接收电磁波，将电磁波信号调频以及滤波处理，将处理后的信号发送到处理器110。无线通信模块142还可以从处理器110接收待发送的信号，对其进行调频，放大，经天线转为电磁波辐射出去。
可选地，电子设备100包括天线1(未示出)和天线2(未示出)，可选地，天线1和移动通信模块141耦合，天线2和无线通信模块142耦合，使得电子设备100可以通过无线通信技术与网络以及其他设备通信。上述无线通信技术可以包括全球移动通讯系统(global system for mobile communications，GSM)，通用分组无线服务(general packet radio service，GPRS)，码分多址接入(code division multiple access，CDMA)，宽带码分多址(wideband code division multiple access，WCDMA)，时分码分多址(time-division code division multiple access，TD-SCDMA)，长期演进(long term evolution，LTE)，BT，GNSS，WLAN，NFC，FM，和/或IR技术等。上述GNSS可以包括全球卫星定位系统(global positioning system，GPS)，全球导航卫星系统(global navigation satellite system，GLONASS)，北斗卫星导航系统(beidou navigation satellite system，BDS)，准天顶卫星系统(quasi-zenith satellite system，QZSS)和/或星基增强系统(satellite based augmentation systems，SBAS)。
在一些实施例中，电子设备100可以通过音频模块150以及AP等实现音频功能，例如音乐播放，录音等。
音频模块150用于将数字音频信息转换成模拟音频信号输出，也用于将模拟音频输入转换为数字音频信号。音频模块150还可以用于对音频信号编码和解码。可选地，音频模块150可以设置于处理器110中，或者将音频模块150的部分功能模块设置于处理器110中。
麦克风151，也称“话筒”，“传声器”，用于将声音信号转换为电信号。可选地，当拨打电话、发送语音信息、录音时，用户可以通过人嘴靠近麦克风151发声，将声音信号输入到麦克风151。电子设备100可以设置至少一个麦克风151。可选地，电子设备100可以设置两个麦克风151，除了采集声音信号，还可以实现降噪功能。可选地，电子设备100还可以设置三个，四个或更多麦克风151，实现采集声音信号，降噪，还可以识别声音来源，实现定向录音功能等。
在一些实施例中，电子设备100可以通过麦克风151采集用户的音频数据，例如咳嗽音、呼吸音、心音、肺音等，采集的音频数据用于确定呼吸系统的感染风险。
扬声器152，也称“喇叭”，用于将音频电信号转换为声音信号。电子设备100可以通过扬声器152收听音乐，或收听免提通话。
压力传感器161用于感受压力信号，可以将压力信号转换成电信号。压力传感器161的种类很多，如电阻式压力传感器，电感式压力传感器，电容式压力传感器，压电式压力传感器。
可选地，压力传感器161可以是电容式压力传感器，电容式压力传感器可以是包括至少两个具有导电材料的平行板。当有力作用于压力传感器161，电极之间的电容改变。电子设备100根据电容的变化确定压力的强度。可选地，压力传感器161可以设置于显示屏130中。可选地，当有触摸操作作用于显示屏130，电子设备100可以根据压力传感器161检测上述 触摸操作强度。电子设备100也可以根据压力传感器161的检测信号来计算触摸的位置。可选地，作用于相同触摸位置，但不同触摸操作强度的触摸操作，可以对应不同的操作指令。例如但不限于，当有压力值小于第一压力阈值的触摸操作作用于短消息应用图标时，执行查看短消息的指令。当有压力值大于或等于第一压力阈值的触摸操作作用于短消息应用图标时，执行新建短消息的指令。可选地，压力传感器161可以是压电式压力传感器。压电式传感器是一种基于压电效应的传感器。压电式传感器是一种自发电式和机电转换式传感器。压电式传感器的敏感元件由压电材料制成，压电材料受力后表面产生电荷，此电荷经电荷放大器和测量电路放大和变换阻抗后就成为正比于所受外力的电量输出。压电式传感器用于测量力和能变换为电的非电物理量。
加速度传感器(accelerometer，ACC)162可以检测加速度信号。可选地，加速度传感器162可以设置在用户身上(例如贴在用户腹部上)，用于采集用户的呼吸信号，例如呼吸频率。可选地，加速度传感器162可以检测电子设备100在各个方向上(一般为三轴)加速度的大小。当电子设备100静止时可检测出重力的大小及方向。还可以用于识别电子设备姿态，应用于横竖屏切换，计步器等应用。
骨传导传感器163可以获取振动信号。可选地，骨传导传感器163可以获取人体声部振动骨块的振动信号。可选地，骨传导传感器163可以接触人体脉搏，接收血压跳动信号。可选地，音频模块150可以基于骨传导传感器163获取的声部振动骨块的振动信号，解析出语音信号，实现语音功能。可选地，AP可以基于骨传导传感器163获取的血压跳动信号解析心率信号，实现采集心率的功能。可选地，骨传导传感器163也可以检测脉搏信号，电子设备100可以通过骨传导传感器163采集用户的脉搏。
温度传感器164用于检测温度。可选地，温度传感器164也可以用于检测处理器110的温度，执行温度处理策略，例如当温度传感器上报的温度超过某一阈值，电子设备100执行降低位于温度传感器164附近的处理器的性能，以便降低功耗实施热保护。
血氧传感器165用于检测血氧饱和度。可选地，血氧传感器165可以包括发光器件和接收器件。发光器件是由波长为660纳米(nm)(也可以是650nm)的红光和波长为940nm(也可以是910nm)的红外光发射管组成。接收器件可以是光敏接收器件，大都采用接收面积大，灵敏度高，暗电流小，噪声低的PIN型光敏二极管，由它将接收到的入射光信号转换成电信号。电子设备100可以根据血氧传感器165的检测信号获取用户的血氧饱和度。
脉搏传感器166可以检测脉搏信号。可选地，脉搏传感器166可以检测动脉搏动时产生的压力变化，并将其转换为电信号。脉搏传感器166的种类很多，例如压电式脉搏传感器、压阻式脉搏传感器、光电式脉搏传感器等。可选地，压电式脉搏传感器和压阻式脉搏传感器可以通过微压力型的材料(如压电片、电桥等)将脉搏跳动的压力过程转换为信号输出。可选地，光电式脉搏传感器可以通过反射或透射等方式，将血管在脉搏跳动过程中透光率的变化转换为信号输出，即通过光电体积描记法(photoplethysmogram，PPG)获取脉搏信号。
心率传感器167可以检测心率信号。可选地，心率传感器167可以通过PPG获取心率信号。心率传感器167可以通过反射或透射等方式，将血管动力发生的变化，例如血脉搏率(心率)或血容积(心输出量)发生的变化，转换为电信号输出。可选地，心率传感器167可以通过连接到人体皮肤上的电极来测量心脏组织中所引发电气活动的信号，即通过心电描记法(electrocardiography，ECG)获取心率信号。
在一些实施例中，电子设备100为第一设备，例如为智能手环。可选地，电子设备100可以通过通信模块140和第二设备连接和通信，例如通过Wi-Fi、蓝牙、NFC、IR等技术连 接和通信。可选地，电子设备100可以通过音频模块150和传感器模块160采集用户的生理参数(例如体温、血氧饱和度、呼吸频率、心率、脉搏等)，以及音频数据(例如咳嗽音、呼吸音、心音、肺音等)。可选地，电子设备100可以通过通信模块140，将采集的生理参数发送给第二设备进行分析处理，以确定呼吸系统的感染风险。
在一些实施例中，电子设备100为第二设备，例如为智能手机。可选地，电子设备100可以通过通信模块140和第一设备连接和通信，例如通过Wi-Fi、蓝牙、NFC、IR等技术连接和通信。可选地，通信模块140可以接收第一设备采集的生理参数和音频数据，并传输给处理器110进行处理，以确定呼吸系统的感染风险。可选地，电子设备100也可以通过音频模块150和/或传感器模块160自行采集部分数据(例如通过麦克风151采集咳嗽音和呼吸音)，结合第一设备采集的部分数据(例如生理参数、心音和肺音)进行分析处理，以确定呼吸系统的感染风险。
在一些实施例中，采集的生理参数，和/或，采集的音频数据可以传输至存储器120内存储起来。
在一些实施例中，假设电子设备100为第二设备，采集的生理参数以及音频数据可以传输至处理器110。处理器110可以统计采集的生理参数和音频数据，基于定量分析法确定呼吸系统的感染风险，例如为低风险、中风险或高风险等风险等级。可选地，处理器110可以指示显示屏130显示呼吸系统的感染风险。可选地，电子设备100可以在用户发病前或发病时提示用户就诊干预，例如，处理器110可以在呼吸系统感染风险为中风险或高风险时，指示显示屏130显示提示信息，以提醒用户就诊干预。用户可以通过电子设备100及时了解到呼吸健康状态，实现呼吸系统疾病的监测预警，用户使用更加方便和高效。
不限于上述列举的情况，在具体实现中，用于采集音频数据的模块(简称音频数据采集模块)也可以包括声音传感器、超声等，用于采集用户的咳嗽音、呼吸音、心音、肺音等。用于采集生理参数的模块(简称生理参数采集模块)也可以包括呼吸频率传感器等，呼吸频率传感器用于采集呼吸频率。作为生理参数采集模块的脉搏传感器166和心率传感器167，可以封装在一个传感器中，该传感器可以通过PGG来获取脉搏信号和心率信号。本申请对音频数据采集模块和生理参数采集模块的具体形态类型不作限定。
电子设备100的软件系统可以采用分层架构，事件驱动架构，微核架构，微服务架构，或云架构。例如，分层架构的软件系统可以是安卓(Android)系统，也可以是华为移动服务(huawei mobile services，HMS)系统。本申请实施例以分层架构的Android系统为例，示例性说明电子设备100的软件结构。
图2示例性示出了一种电子设备100的软件架构示意图。
分层架构将软件分成若干个层，每一层都有清晰的角色和分工。层与层之间通过软件接口通信。在一些实施例中，将Android系统分为四层，从上至下分别为应用程序层，应用程序框架层，安卓运行时(Android runtime)和系统库，以及内核层。
应用程序层可以包括一系列应用程序包。
如图2所示，应用程序包可以包括相机、图库、音乐、视频、文件管理、短消息、浏览器和呼吸健康。可选地，用户可以通过呼吸健康应用主动检测呼吸系统的感染风险。可选地，用户可以通过呼吸健康应用查看呼吸系统的感染风险。
应用程序框架层为应用程序层的应用程序提供应用编程接口(application programming interface，API)和编程框架。应用程序框架层包括一些预先定义的函数。
如图2所示，应用程序框架层可以包括传感器管理器、窗口管理器、内容提供器、视图系统、电话管理器、资源管理器和通知管理器等。
传感器管理器用于管理各个传感器。例如但不限于，传感器管理器可以接收压力传感器161发送的中断事件，从而控制加速度传感器162采集呼吸频率。其中，各个传感器可以为上述图1的传感器模块160包括的部分或所有模块。
窗口管理器用于管理窗口程序。窗口管理器可以但不限于获取显示屏大小，判断是否有状态栏，锁定屏幕，截取屏幕等。
内容提供器用来存放和获取数据，并使该数据可以被应用程序访问。其中，该数据可以包括但不限于视频，图像，音频，拨打和接听的电话，浏览历史和书签，电话簿等。
视图系统可以包括可视控件，例如显示文字的控件，显示图片的控件等。视图系统可用于构建应用程序。显示界面可以由一个或多个视图组成的。例如但不限于，包括呼吸健康应用的通知图标的显示界面，包括显示文字的视图以及显示图片的视图。
电话管理器用于提供电子设备100的通信功能。例如但不限于通话状态的管理(包括接通，挂断等)。
资源管理器为应用程序提供各种资源，例如但不限于本地化字符串，图标，图片，布局文件，视频文件等等。
通知管理器使应用程序可以在状态栏中显示通知信息，可以用于传达告知类型的消息，可以短暂停留后自动消失，无需用户交互。例如通知管理器被用于告知下载完成，消息提醒等。通知管理器还可以是以图表或者滚动条文本形式出现在系统顶部状态栏的通知，例如后台运行的应用程序的通知，还可以是以对话窗口形式出现在屏幕上的通知。例如但不限于，在状态栏提示文本信息，发出提示音，电子设备振动，指示灯闪烁等。不限于此。
Android Runtime包括核心库和虚拟机。Android runtime负责安卓系统的调度和管理。
核心库包含两部分：一部分是java语言需要调用的功能函数，另一部分是安卓的核心库。
应用程序层和应用程序框架层运行在虚拟机中。虚拟机将应用程序层和应用程序框架层的java文件执行为二进制文件。虚拟机用于执行对象生命周期的管理，堆栈管理，线程管理，安全和异常的管理，以及垃圾回收等功能。
系统库可以包括多个功能模块。例如但不限于，表面管理器(surface manager)、媒体库(Media Libraries)、三维(3D)图形处理库(例如OpenGL ES)以及二维(2D)图形引擎(例如SGL)等。
表面管理器用于对显示子系统(display subsystem，DSS)进行管理，并且为多个应用程序提供了2D和3D图层的融合。
媒体库支持多种常用的音频，视频格式回放和录制，以及静态图像文件等。媒体库可以支持多种音视频编码格式，例如:MPEG4，H.264，MP3，AAC，AMR，JPG，PNG等。
三维图形处理库用于实现三维图形绘图，图像渲染，合成，和图层处理等。
二维图形引擎是二维绘图的绘图引擎。
内核层是硬件和软件之间的层。内核层可以包含显示驱动、摄像头驱动、音频驱动、电源管理和传感器驱动等。
在一些实施例中，Android系统还可以包括硬件抽象层(hardware abstraction layer，HAL)，HAL是位于内核层和系统库(和Android Runtime)之间的接口层。HAL是对内核层的驱动程序的封装，将硬件抽象化，屏蔽底层的实现细节。HAL层可以包含传感器接口、蓝牙接口、相机接口等。
下面结合录音过程，示例性说明电子设备100软件以及硬件的工作流程。
当压力传感器161接收到触摸操作，相应的硬件中断被发送给内核层。内核层将该触摸操作加工成原始输入事件(包括触摸坐标，触摸操作的时间戳等信息)，原始输入事件被存储在内核层。应用程序框架层从内核层获取原始输入事件，识别该输入事件所对应的控件。以该触摸操作是触摸单击操作，该单击操作所对应的控件为呼吸健康应用的录音控件为例，呼吸健康应用调用应用程序框架层的接口，进而通过调用内核层启动音频驱动，通过麦克风151接收用户的咳嗽音和呼吸音。
本申请中，呼吸系统疾病的检测模式可以包括多种，从而满足用户不同场景下不同的检测需求，多场景多覆盖，用户体验感更好。
示例性地，呼吸系统疾病的检测模式可以包括第一模式、第二模式、第三模式和第四模式，其中：
第一模式应用于用户主动检测的场景。第一模式下，用户可以通过电子设备主动采集生理参数和音频数据，采集的生理参数和音频数据用于获取呼吸系统的感染风险，具体示例如下图3、图5、图6所示。
第二模式应用于设备持续(长时间)自动检测的场景。第二模式下，电子设备可以自动采集生理参数，采集的生理参数用于确定呼吸系统的感染风险，具体示例如下图7-图≥所示。不限于此，在另一些实施例中，第二模式下，电子设备可以自动采集生理参数和音频数据，采集的生理参数和音频数据用于确定呼吸系统的感染风险。
第三模式应用于用户在设备提示下检测音频数据的场景。第三模式下，电子设备确定生理参数异常时，提示用户采集音频数据，采集的生理参数和音频数据用于获取呼吸系统的感染风险，具体示例如下图4、图9所示。
第四模式应用于设备自动检测音频数据的场景。第四模式下，电子设备确定生理参数异常时，自动开启音频数据采集模块(如麦克风)采集音频数据，采集的生理参数和音频数据用于确定呼吸系统的感染风险，具体示例如下图10所示。
其中，生理参数异常例如但不限于包括以下至少一项：体温大于或等于体温阈值(单位例如为摄氏度)，血氧饱和度小于或等于血氧阈值(单位例如为百分比)，呼吸频率大于或等于频率阈值(单位例如为次/分钟)，心率大于或等于心率阈值(单位例如为次/分钟)，脉搏大于或等于脉搏阈值(单位例如为次/分钟)。
在一些实施例中，第三模式和第四模式下，生理参数可以是用户主动通过电子设备采集得到的。在另一些实施例中，第三模式和第四模式下，生理参数可以是电子设备自动采集得到的。
下面介绍本申请实施例涉及的应用场景以及该场景下的用户界面实施例。
以下实施例以智能手机和智能手表为例进行说明，其中智能手机既是第一设备(即采集设备)，也是第二设备(即处理设备)，智能手表是第一设备(即采集设备)，作为第一设备的智能手机用于采集音频数据(也可称为音频信息，例如咳嗽音、呼吸音、心音和肺音等)，作为第一设备的智能手表用于采集生理参数(也可称为生理参数信息，例如血氧饱和度、呼吸频率、心率、体温和脉搏等)。以下实施例以呼吸系统疾病的检测功能通过智能手机上的呼吸健康应用实现为例进行说明。
在一些实施例中，智能手机或智能手表可以响应于用户操作，开启呼吸系统疾病的检测 功能。在另一些实施例中，呼吸系统疾病的检测功能可以默认为开启状态。
在一种可能的实现方式中，用户可以通过智能手机主动采集生理参数和音频数据，具体检测过程的示例如下图3-图5所示。
请参见图3，图3示例性示出一种用户界面实施例的示意图。图3的(A)示出了点击采集选项633之前的用户界面600，图3的(B)示出了点击采集选项633之后的用户界面600。
如图3的(A)所示，智能手机200可以显示用户界面600，在一些实施例中，用户界面600为呼吸健康应用的用户界面，用户可以通过用户界面600实现呼吸系统疾病的检测功能，在一些实施例中，用户界面600可以是智能手机200响应于作用于呼吸健康应用的图标的触摸操作显示的界面。用户界面600可以包括页面主题610(即“呼吸健康”)，连接标识620，生理参数采集栏位630以及页面标识栏650，其中：
连接标识620可以表征是否连接其他设备，例如是否连接智能手表等可穿戴设备，智能大屏等智能家居设备。图3的(A)所示的连接标识620包括的图标620A和文字620B(即“已连接”)，表征已连接其他设备，本申请以智能手机200已连接智能手表300为例进行说明。
生理参数采集栏位630可以包括栏位主题631(即“生理参数”)，采集内容632和采集选项633，其中：采集内容632包括采集的生理参数的类型，例如包括血氧饱和度、呼吸频率、心率、体温和脉搏。采集选项633可以用于开启采集上述生理参数的功能。智能手机200可以接收作用于采集选项633的触摸操作(例如点击操作)，响应于该触摸操作，智能手机200可以向智能手表300发送指示采集生理参数的指示信息。响应于接收到的指示信息，智能手表300可以在后台无感采集用户的生理参数，智能手表300可以将采集的生理参数发送给智能手机200。在一些实施例中，智能手表300可以按照预设时长采集生理参数，例如预设时长为1分钟，在另一些实施例中，采集生理参数的时长也可以由用户设置，例如智能手机200第一次接收作用于采集选项633的点击操作时，指示智能手表300开始采集生理参数，第二次接收作用于采集选项633的点击操作时，指示智能手表300结束采集生理参数，智能手机200接收这两次点击操作的时间间隔即为采集生理参数的时长，本申请对采集生理参数的时长的确定方式不作限定。
页面标识栏650可以包括三个页面选项：首页651、统计652和我的653。智能手机200可以接收用户作用于任意一个页面选项的触摸操作(例如点击操作)，响应于该触摸操作，智能手机200可以显示和该页面选项对应的用户界面。用户界面600中的首页651被选中，即表征用户界面600为首页651的页面选项对应的用户界面。
在一些实施例中，智能手机200获取到采集的生理参数后，可以提示用户采集音频数据，例如显示图3的(B)所示的用户界面600。
如图3的(B)所示，智能手机200显示的用户界面600和图3的(A)所示的用户界面600类似，区别在于，图3的(B)所示的用户界面600还包括提示内容640，提示内容640包括提示语641和音频选项642，其中：提示语641包括文字：“生理参数采集完成，请采集音频数据”，音频选项642包括文字：“采集音频数据”。智能手机200可以接收作用于音频选项642的触摸操作(例如点击操作)，响应于该触摸操作，智能手机200可以显示采集音频数据的用户界面，例如下图5的(A)所示的用户界面600。
在另一些实施例中，智能手机200获取到采集的生理参数后，可以判断生理参数是否异常，当确定生理参数异常时，提示用户采集音频数据，具体示例如下图4所示。
请参见图4，图4示例性示出又一种用户界面实施例的示意图。
如图4所示，智能手机200显示的用户界面600和图3的(B)所示的用户界面600类 似，区别在于，图4所示的用户界面600中提示语641包括的文字为：“您的生理参数异常，请进行音频录制进一步确认”。智能手机200可以接收作用于音频选项642的触摸操作(例如点击操作)，响应于该触摸操作，智能手机200可以显示采集音频数据的用户界面，例如下图5的(A)所示的用户界面600。
在另一些实施例中，智能手机200确定生理参数正常时，可以提示用户生理参数正常，并根据用户操作确定是否显示采集音频数据的用户界面。例如，智能手机200确定生理参数正常时，显示的用户界面600中提示语641包括的文字可以为：“您的生理参数正常，若想获取更精确的检测结果可进行音频录制进一步确认”。智能手机200接收到作用于音频选项642的触摸操作(例如点击操作)时，可以响应于该触摸操作，显示采集音频数据的用户界面，例如下图5的(A)所示的用户界面600。
请参见图5，图5示例性示出又一种用户界面实施例的示意图。图5的(A)、(B)、(C)、(D)分别示出了用于采集不同类型的音频数据的用户界面600。
如图5所示，智能手机200显示的用户界面600和图3的(A)所示的用户界面600类似，区别在于，图5所示的用户界面600不包括生理参数采集栏位630，还包括音频数据采集栏位660。音频数据采集栏位660可以包括栏位主题661(即“音频数据”)、采集内容662、采集选项663和提示内容664，其中：
采集内容662可以包括提示语662A和采集的音频数据的选项，提示语662A包括文字：“采集的音频数据的类型”，用于提示用户选择采集的音频数据的类型。采集的音频数据的选项可以包括咳嗽音的选项642B、呼吸音的选项642C、心音的选项642D和肺音的选项642E。智能手机200可以接收作用于任意一个选项的触摸操作(例如点击操作)，响应于该触摸操作，智能手机200可以确定当前采集的音频数据的类型为该选项对应的类型。
采集选项663用于开启采集音频数据的功能。采集内容662中处于选中状态的音频数据的选项不同时，采集选项663对应采集的音频数据也不同，采集选项663对应采集的音频数据为处于选中状态的选项对应的音频数据。
提示内容664用于提示用户采集音频数据的方式。采集内容662中处于选中状态的音频数据的选项不同时，提示内容664包括的内容也不同，提示内容664提示采集的音频数据为处于选中状态的选项对应的音频数据。
如图5的(A)所示，咳嗽音的选项642B为选中状态，表征当前采集的音频数据为咳嗽音，图5的(A)所示的用户界面600可以理解为是采集咳嗽音的用户界面。此时，提示内容664包括的内容为文字664A：“请用力咳嗽2-3次”，用于提示用户采集咳嗽音的方式。智能手机200可以接收作用于采集选项663的触摸操作(例如点击操作)，响应于该触摸操作，智能手机200可以开启音频数据采集模块(如麦克风)采集音频数据，并确定采集的音频数据为咳嗽音，例如将采集的音频数据存储在咳嗽音对应的数据库中。在一些实施例中，智能手机200可以按照预设时长或预设次数采集音频数据，例如预设时长为15秒，采集3次咳嗽音。在另一些实施例中，采集音频数据的时长或次数也可以由用户设置，例如智能手机200接收作用于采集选项663的长按操作，该长按操作的维持时长(也即作用于采集选项663的触摸操作的触摸时长)为采集音频数据的时长。或者，智能手机200第一次接收作用于采集选项663的点击操作时，开启麦克风，第二次接收作用于采集选项663的点击操作时，关闭麦克风，智能手机200接收这两次点击操作的时间间隔即为采集音频数据的时长，本申请对采集音频数据的时长的确定方式不作限定。
如图5的(B)所示，呼吸音的选项642C为选中状态，表征当前采集的音频数据为呼吸 音，图5的(B)所示的用户界面600可以理解为是采集呼吸音的用户界面。此时，提示内容664包括的内容为文字664B：“请将麦克风放置在嘴边呼吸15秒”，用于提示用户采集呼吸音的方式。智能手机200可以接收作用于采集选项663的触摸操作(例如点击操作)，响应于该触摸操作，智能手机200可以开启音频数据采集模块(如麦克风)采集音频数据，并确定采集的音频数据为呼吸音，例如将采集的音频数据存储在呼吸音对应的数据库中。采集呼吸音的时长的确定方式和采集咳嗽音的时长的确定方式类似。
如图5的(C)所示，心音的选项642D为选中状态，表征当前采集的音频数据为心音，图5的(C)所示的用户界面600可以理解为是采集心音的用户界面。此时，提示内容664包括的内容为文字664C：“请将手机放置在心脏处15秒”，用于提示用户采集心音的方式。智能手机200可以接收作用于采集选项663的触摸操作(例如点击操作)，响应于该触摸操作，智能手机200可以开启音频数据采集模块(如麦克风)采集音频数据，并确定采集的音频数据为心音，例如将采集的音频数据存储在心音对应的数据库中。采集心音的时长的确定方式和采集咳嗽音的时长的确定方式类似。
如图5的(D)所示，肺音的选项642E为选中状态，表征当前采集的音频数据为肺音，图5的(D)所示的用户界面600可以理解为是采集肺音的用户界面。此时，提示内容664包括的内容为文字664D：“请将手机放置在肺部15秒”，用于提示用户采集肺音的方式。智能手机200可以接收作用于采集选项663的触摸操作(例如点击操作)，响应于该触摸操作，智能手机200可以开启音频数据采集模块(如麦克风)采集音频数据，并确定采集的音频数据为肺音，例如将采集的音频数据存储在肺音对应的数据库中。采集肺音的时长的确定方式和采集咳嗽音的时长的确定方式类似。
在一些实施例中，智能手机200跳转显示的采集音频数据的用户界面可以为采集咳嗽音的用户界面，即图5的(A)所示的用户界面600。智能手机200采集到咳嗽音后，可以显示提示信息，以提示用户采集其他类型的音频数据，用户可以根据提示信息选择咳嗽音的选项642B以外的其他音频数据的选项。智能手机200可以响应于作用于其他音频数据的选项的触摸操作(例如点击操作)，显示采集该选项对应的音频数据的用户界面，继续采集该选项对应的音频数据，直到智能手机200采集到全部类型的音频数据。不限于此，在另一些实施例中，智能手机200跳转显示的采集音频数据的用户界面也可以为图5的(B)、(C)、(D)中任意一个所示的用户界面600，后续过程和上述过程类似。
在一些实施例中，智能手机200获取到采集的生理参数和音频数据后，可以对生理参数和音频数据进行分析处理，以得到呼吸系统的感染风险(也可称为检测结果)。在一些实施例中，智能手机200获取到检测结果后，可以提示用户查看检测结果，例如显示图6的(A)所示的用户界面600。
请参见图6，图6示例性示出又一种用户界面实施例的示意图。图6的(A)示出了点击查看选项672之前的用户界面600，图6的(B)示出了点击查看选项672之后的用户界面≥00。
如图6的(A)所示，智能手机200显示的用户界面600和图5的(D)所示的用户界面600类似，区别在于，图6的(A)所示的用户界面600还包括提示内容670。提示内容670包括提示语671和查看选项672，提示语671包括文字：“检测完成，请查看检测结果”，用于提示用户查看呼吸系统的感染风险，智能手机200可以接收作用于查看选项672的触摸操作(例如点击操作)，响应于该触摸操作，显示呼吸系统的感染风险，例如图6的(B)所示的用户界面≥00。
如图6的(B)所示，智能手机200可以显示用户界面≥00。用户界面≥00可以包括页面主题≥01(即“呼吸系统的感染风险”，表征当前界面用于显示检测结果)，风险等级≥10，多个具体检测结果和页面标识栏650，其中：
风险等级≥10可以为图6的(B)所示的“低风险”、“中风险”或“高风险”，不限于此，也可以通过未见异常、呼吸系统感染风险、肺炎风险等标识风险等级。以下实施例以呼吸系统感染风险包括低风险、中风险和高风险为例进行说明。不限于此，用户界面≥00还可以包括风险等级≥10的相关说明，例如包括文字：“您的呼吸健康状态较差，已感染肺炎等呼吸系统疾病的可能性较高，建议您及时就诊”。
多个具体检测结果例如包括：体温的检测结果≥20，血氧的检测结果≥30，心率的检测结果≥40，脉搏的检测结果≥50，呼吸频率的检测结果≥60，咳嗽音的检测结果≥70，呼吸音检测结果≥≥0和心肺音的检测结果≥90，表征智能手机200采集到了体温、血氧、心率、脉搏和呼吸频率的生理参数，以及采集到了咳嗽音、呼吸音、心音和肺音的音频数据，也表征了风险等级≥10是根据上述采集到的生理参数和音频数据确定的。
体温的检测结果≥20可以包括结果概述≥21和统计数据≥22，其中，结果概述≥21可以包括数据类型≥21A(即“体温”)，检测状态≥21B和展开收起选项≥21C。检测状态≥21B可以包括正常、异常和未检测三种状态，分别表征体温的检测结果为正常，体温的检测结果为异常和未检测体温(例如未采集体温数据、采集体温数据失败或采集的体温数据不可用)。展开收起选项≥21C用于切换是否显示统计数据≥22。统计数据≥22可以包括一段时间内的体温数据的统计图。
可以理解地，其他检测结果和体温的检测结果≥20类似，只是用户界面≥00中除体温的检测结果≥20外其他检测结果的统计数据均未显示，例如血氧的检测结果≥30的统计数据未显示，血氧的检测结果≥30的展开收起选项≥33和体温的检测结果≥20中的展开收起选项≥21C不同。智能手机200可以接收作用于体温的检测结果≥20的展开收起选项≥21C的触摸操作(例如点击操作)，响应于该触摸操作，智能手机200可以取消显示统计数据≥22，在一些实施例中，响应于该触摸操作，展开收起选项≥21C会改变，例如改变为血氧的检测结果≥30中的展开收起选项≥33所示状态。在一些实施例中，智能手机200可以接收作用于血氧的检测结果≥30的展开收起选项≥33的触摸操作(例如点击操作)，响应于该触摸操作，智能手机200可以显示血氧的统计数据。
在一些实施例中，体温大于或等于体温阈值(例如为37.5摄氏度)的次数大于或等于第一次数时，检测状态≥21B为异常，否则检测状态≥21B为正常。在一些实施例中，血氧饱和度小于或等于血氧阈值的次数大于或等于第二次数时，血氧的检测结果≥30的检测状态≥32为异常，否则检测状态≥32为正常。在一些实施例中，心率大于或等于心率阈值的次数大于或等于第三次数时，心率的检测结果≥40的检测状态≥42为异常，否则检测状态≥42为正常。在一些实施例中，脉搏大于或等于脉搏阈值的次数大于或等于第四次数时，脉搏的检测结果≥50的检测状态≥52为异常，否则检测状态≥52为正常。在一些实施例中，呼吸频率大于或等于频率阈值的次数大于或等于第五次数时，呼吸频率的检测结果≥60的检测状态≥62为异常，否则检测状态≥62为正常。
在另一些实施例中，还可以通过时长来判断检测状态，例如体温大于或等于体温阈值的时长大于或等于第一时长时，体温的检测结果≥20的检测状态≥21B为异常，其他数据的检测状态的判断类似。
在一些实施例中，咳嗽音的检测结果≥70的统计数据可以包括咳嗽音的频谱图(例如横 坐标为频率，纵坐标为信号能量)，可选地，咳嗽音的频谱图中，集中在预设频率范围内的信号能量占全部信号能量的百分比大于或等于预设百分比时，咳嗽音的检测结果≥70中的检测状态≥72为异常，否则检测状态≥72为正常。呼吸音和心肺音的检测状态的判断类似。
页面标识栏650中的统计652被选中，表征用户界面≥00为统计652的页面选项对应的用户界面。
不限于上述列举的示例，在另一些实施例中，智能手机200获取到呼吸系统的感染风险后，可以接收作用于图6的(A)所示的用户界面600中的统计652的页面选项的触摸操作(例如点击操作)，响应于该触摸操作，显示图6的(B)所示的用户界面≥00。
在一种可能的实现方式中，智能手机200可以指示智能手表300自动采集用户的生理参数。在一些实施例中，智能手机200可以向智能手表300发送指示信息，该指示信息用于指示智能手表300持续(长时间)采集用户的生理参数，例如一直采集生理参数，或者周期性采集生理参数。智能手表300可以周期性向智能手机200发送采集的生理参数。在一些实施例中，智能手机200可以在接收到智能手表300发送的生理参数后，对生理参数进行分析处理，以确定呼吸系统的感染风险。在另一些实施例中，智能手机200可以在接收了预设次数次智能手表300发送的生理参数后，对生理参数进行分析处理，以确定呼吸系统的感染风险。
在一些实施例中，智能手机200也可以基于长时间(例如14天)采集的第一用户的生理参数，构建第一用户的生理参数的波形，并且构建健康用户的生理参数的基线，健康用户例如是风险等级为低风险的用户的生理参数的波形。智能手机200可以分析长时间采集的生理参数的波形和基线的偏离程度，当偏离程度大于或等于预设偏离阈值时，可以确定生理参数异常。可以理解地，相比根据生理参数和音频数据确定检测结果，仅通过生理参数确定检测结果的精度较低，智能手机200可以根据实际场景选择是否开启自动采集生理参数和根据生理参数得到检测结果的功能(可简称为自动检测功能)，例如智能手机200可以响应于用户操作，开启或关闭自动检测功能，具体示例如下图7所示。
请参见图7，图7示例性示出又一种用户界面实施例的示意图。
如图7所示，智能手机200显示的用户界面600和图3的(A)所示的用户界面600类似，区别在于，图7所示的用户界面600还包括功能选项6≥0。功能选项6≥0可以包括功能名称6≥1(即“自动检测”)、功能开关6≥2和功能说明6≥3(即“自动采集生理参数，并确定检测结果”)。功能开关6≥2用于开启或关闭自动检测功能，图7所示的功能开关6≥2为关闭状态，表征当前自动检测功能已关闭，智能手机200可以接收作用于功能开关6≥2的触摸操作(例如点击操作)，响应于该触摸操作，开启自动检测功能。
在一些实施例中，智能手机200确定生理参数异常时，可以提示用户查看检测结果，具体示例如下图≥所示。
请参见图≥，图≥示例性示出又一种用户界面实施例的示意图。其中，图≥的(A)示出了点击第一通知栏930之前的用户界面900，图≥的(B)示出了点击第一通知栏930之后的用户界面≥00。
如图≥的(A)所示，智能手机200可以显示用户界面900，在一些实施例中，用户界面900可以为锁屏界面。用户界面900可以包括日期时间910，解锁提示920(即“滑动解锁”)，第一通知栏930和第二通知栏940，其中：第一通知栏930用于显示呼吸健康的通知消息，第二通知栏940用于显示音乐的通知消息。第一通知栏930可以包括应用标识931和通知内容932，应用标识931可以包括呼吸健康的名称和图标，通知内容932可以包括文字：“您的生理参数异常，具体请查看检测结果”。在一些实施例中，智能手机200可以接收作用于第一 通知栏930的触摸操作(例如点击操作)，响应于该触摸操作，可以显示检测结果，例如显示图≥的(B)所示的用户界面≥00。
在一些实施例中，显示检测结果之前，智能手机200会先对用户进行身份认证，身份认证通过的情况下才会显示检测结果。例如，智能手机200可以响应于该触摸操作，显示图案解锁或密码解锁的用户界面，智能手机200可以接收用户基于该用户界面输入的触摸操作或数字，并验证该触摸操作或该数字是否合法(例如该触摸操作的事件信息和存储的事件信息是否相同，或者该数字和存储的数字是否相同)，合法的情况下确定身份认证通过。或者，智能手机200可以接收作用于指纹识别区域的触摸操作，采集该触摸操作的指纹信息，并验证该指纹信息是否合法(例如和存储的指纹信息的相似程度是否大于或等于第一相似阈值)，合法的情况下确定身份认证通过。或者，智能手机200可以响应于该触摸操作，开启摄像头采集用户的人脸信息，并验证该人脸信息是否合法(例如和存储的人脸信息的相似程度是否大于或等于第二相似阈值)，合法的情况下确定身份认证通过。
如图≥的(B)所示，智能手机200显示的用户界面≥00和图6的(B)所示的用户界面≥00类似，区别在于，风险等级≥10为“中风险”，以及不包括音频数据的检测结果(例如咳嗽音的检测结果≥70，呼吸音检测结果≥≥0和心肺音的检测结果≥90)，表征当前显示的检测结果是根据生理参数(例如体温、血氧、心率、脉搏和呼吸频率)得到的，未检测音频数据。
在一些实施例中，智能手机200也可以向智能手表300发送指示信息，智能手表300接收到该指示信息，可以显示用于提示用户查看检测结果的提示信息，例如图≥的(C)所示，智能手表300可以显示用户界面700，用户界面700可以包括文字：“您的生理参数异常，请到手机上查看检测结果”。
不限于上述列举的示例，在另一些实施例中，智能手机200可以接收用户作用于呼吸健康的图标的触摸操作(例如点击操作)，响应于该触摸操作，显示检测结果，例如图≥的(B)所示的用户界面≥00。
不限于图4列举的情况，在另一些实施例中，智能手机200获取到的生理参数可以不是用户主动触发采集的，而是设备自动采集的。示例性地，智能手机200可以向智能手表300发送指示信息，该指示信息用于指示智能手表300采集用户的生理参数，在一些实施例中，智能手机200可以响应于用户操作，向智能手表300发送指示信息，该用户操作用于开启或关闭自动采集生理参数的功能，具体示例和图7类似。
在一些实施例中，上述指示信息用于指示智能手表300持续(长时间)采集用户的生理参数，例如一直采集生理参数，或者周期性采集生理参数。智能手表300可以周期性向智能手机200发送采集的生理参数。在另一些实施例中，上述指示信息用于指示智能手表300按照预设时长(例如1分钟)采集用户的生理参数。智能手表300采集到生理参数后可以发送给智能手机200。
在一些实施例中，智能手机200可以判断生理参数是否异常，当确定生理参数异常时，可以提示用户采集音频数据，具体示例如下图9所示。
请参见图9，图9示例性示出又一种用户界面实施例的示意图。其中，图9的(A)示出了点击第一通知栏410之前的用户界面900，图9的(B)示出了点击第一通知栏410之后的用户界面600。
如图9的(A)所示，智能手机200可以显示用户界面400，在一些实施例中，用户界面400为下滑通知界面，例如智能手机200响应于从屏幕上边缘向下滑动的用户操作，显示的用户界面。用户界面400可以包括至少一个通知栏，例如第一通知栏410和第二通知栏420， 其中：第一通知栏410用于显示呼吸健康的通知消息，第二通知栏420用于显示音乐的通知消息。第一通知栏410可以包括应用标识411和通知内容412，应用标识411可以包括呼吸健康的名称和图标，通知内容412可以包括文字：“您的生理参数异常，请进行音频录制进一步确认”。在一些实施例中，智能手机200可以接收作用于第一通知栏410的触摸操作(例如点击操作)，响应于该触摸操作，可以显示采集音频数据的用户界面，例如显示图9的(B)所示的用户界面600，即图5的(A)所示的用户界面600。用户通过智能手机200采集音频数据的过程和上图5所示的用户主动采集音频数据的过程类似。智能手机200可以根据自动采集的生理参数和响应于用户操作采集的音频数据，确定呼吸系统的感染风险，智能手机200提示用户查看检测结果的过程和上图6所示实施例类似。
在一些实施例中，智能手机200也可以向智能手表300发送指示信息，智能手表300接收到该指示信息，可以显示用于提示用户采集音频数据的提示信息，例如图9的(C)所示，智能手表300可以显示用户界面700，用户界面700可以包括文字：“您的生理参数异常，请到手机上进行音频录制进一步确认”。
不限于上述列举的示例，在另一些实施例中，智能手机200可以接收用户作用于呼吸健康的图标的触摸操作(例如点击操作)，响应于该触摸操作，可以显示采集音频数据的用户界面，例如图5的(A)所示的用户界面600。
不限于上述列举的示例，在另一些实施例中，用户获取到图4所示的用户界面600中的提示语641，或图9的(A)所示的用户界面400中的通知内容412后，可以暂时不进行音频数据的采集。示例性地，智能手机200可以存储采集的生理参数，后续用户通过智能手机200采集音频数据后，再根据音频数据和生理参数确定呼吸系统的感染风险。不限于此，智能手机200还可以自动开启音频数据采集模块(如麦克风)采集音频数据，或者智能手机200也可以直接根据生理参数确定呼吸系统的感染风险。
在一种可能的实现方式中，智能手机200获取到采集的生理参数后，可以判断生理参数是否异常，当确定生理参数异常时，可以自动开启音频数据采集模块(如麦克风)无感采集用户的音频数据，然后根据采集的音频数据和生理参数确定呼吸系统的感染风险。
在一些实施例中，智能手机200获取到的生理参数可以是用户主动触发采集的，例如响应于作用于图3所示的用户界面600中的采集选项633的触摸操作，指示智能手表300在一定时长内采集到的，具体可参见图3的(A)的说明。在另一些实施例中，智能手机200获取的生理参数可以是设备自动采集的，例如智能手机200指示智能手表300长时间(例如周期性)采集到的，具体可参见上述智能手机200获取到的生理参数可以不是用户主动触发采集的，而是设备自动采集的相关说明。
在一些实施例中，智能手机200确定生理参数异常时，可以开启麦克风来采集用户的音频数据，智能手机200可以对采集的音频数据进行识别处理，当确定包括咳嗽音、呼吸音、心音和肺音中至少一项时，可以关闭麦克风。例如，智能手机200可以判断咳嗽音的数据模型和采集的音频数据是否匹配，若匹配，可以关闭麦克风。在另一些实施例中，智能手机200确定生理参数异常时，可以按照预设时长开启麦克风来采集用户的音频数据，例如预设时长为10分钟。
在一些实施例中，智能手机200获取到呼吸系统的感染风险后，可以提示用户查看检测结果，在一些实施例中，智能手机200确定感染风险的风险等级较高，例如为中风险或高风险时，可以提示用户查看检测结果，具体示例如下图10所示。
请参见图10，图10示例性示出又一种用户界面实施例的示意图。其中，图10的(A) 示出了点击第一通知栏930之前的用户界面900，图10的(B)示出了点击第一通知栏930之后的用户界面实施例。
如图10的(A)所示，智能手机200显示的用户界面900和图≥的(A)所示的用户界面900类似，区别在于，图10的(A)所示的用户界面900包括的通知内容932为：“您的感染风险较高，具体请查看检测结果”。在一些实施例中，智能手机200可以接收作用于第一通知栏930的触摸操作(例如点击操作)，响应于该触摸操作，可以显示检测结果，例如显示图10的(B)所示的用户界面≥00。在一些实施例中，显示检测结果之前，智能手机200会先对用户进行身份认证，身份认证通过的情况下才会显示检测结果，具体示例可参见图≥所示的身份认证的示例。
如图10的(B)所示，智能手机200显示的用户界面≥00和图6的(B)所示的用户界面≥00类似，区别在于，风险等级≥10为“高风险”，以及多种数据的检测结果不同，例如体温的检测结果≥20的检测状态≥21B为异常，统计数据≥22也不同，血氧的检测结果≥30的检测状态≥32为异常，心率的检测结果≥40的检测状态≥42为正常，呼吸频率的检测结果≥60的检测状态≥62为异常，咳嗽音的检测结果≥70的检测状态≥72为异常。
在一些实施例中，智能手机200也可以向智能手表300发送指示信息，智能手表300接收到该指示信息，可以显示用于提示用户查看检测结果的提示信息，具体示例如图10的(C)所示。
不限于上述列举的示例，在另一些实施例中，智能手机200可以接收用户作用于呼吸健康的图标的触摸操作(例如点击操作)，响应于该触摸操作，可以显示检测结果，例如图10的(B)所示的用户界面≥00。智能手表300可以显示用户界面700，用户界面700可以包括文字：“您的感染风险较高，请到手机上查看检测结果”。
不限于上述列举的示例，在另一些实施例中，用户通过智能手机200主动采集生理参数后，智能手机200可以判断采集的生理参数是否异常，当确定生理参数异常时，自动开启音频数据采集模块(如麦克风)无感采集音频数据，并根据采集的生理参数和音频数据确定检测结果。
不限于上述列举的情况，在另一些实施例中，智能手机200也可以基于长时间(例如14天)采集的第一用户的生理参数，构建第一用户的生理参数的波形，并且构建第一用户的生理参数的基线，该基线可以是未感染呼吸系统疾病的用户的生理参数的波形，即健康用户的生理参数的波形。智能手机200可以分析长时间采集的生理参数的波形，以及生理参数的基线的偏离程度，当偏离程度大于或等于预设偏离阈值时，可以确定生理参数异常。本申请对生理参数是否异常，音频数据是否异常的具体判断方式不作限定。
在一些实施例中，智能手机200可以按照预设规则确定使用的呼吸系统疾病的检测模式，可选地，预设规则为基于智能手机200的电量确定的。示例性地，智能手机200的电量小于第一电量值的情况下，智能手机200在用户操作下才采集生理参数和音频数据，具体示例如上图3-图6所示。电量大于或等于第一电量值且小于第二电量值的情况下，智能手机200自动获取生理参数，确定生理参数异常时提示用户采集音频数据，具体示例如图9所示。电量大于或等于第二电量值的情况下，智能手机200自动获取生理参数，确定生理参数异常时自动开启音频数据采集模块(如麦克风)无感采集用户的音频数据，其中，第一电量值小于第二电量值，具体示例如图10所示。在另一些实施例中，智能手机200也可以响应于用户操作，确定使用的呼吸系统疾病的检测模式，例如图7所示实施例中，智能手机200可以响应于作用于功能开关6≥2的触摸操作(例如点击操作)，响应于该触摸操作，开启自动检测功能，即 智能手机200可以指示智能手表300自动采集用户的生理参数，并根据采集的生理参数确定检测结果，具体示例如图≥所示。本申请对如何确定使用的呼吸系统疾病的检测模式不作限定。
不限于上述列举的情况，在另一些实施例中，智能手机200也可以响应于用户的一次操作，指示智能手表300采集用户的生理参数，以及采集用户的音频数据，具体示例如下图11-图13所示。
请参见图11，图11示例性示出又一种用户界面实施例的示意图。
如图11所示，智能手机200可以显示用户界面1≥00，在一些实施例中，用户界面1≥00为呼吸健康应用的用户界面，用户可以通过用户界面1≥00实现呼吸系统疾病的检测功能，以及查看检测结果。在一些实施例中，用户界面1≥00可以是智能手机200响应于作用于呼吸健康应用的图标的触摸操作显示的界面。用户界面1≥00可以包括页面主题1≥01(即“呼吸健康”)，结果概述1≥10，结果说明1≥20，统计数据1≥30，两个页面选项(首页1≥41和我的≥42)，检测控件1≥43和提示语1≥50，其中：
在一些实施例中，智能手机200可以接收用户作用于任意一个页面选项的触摸操作(例如点击操作)，响应于该触摸操作，智能手机200可以显示和该页面选项对应的用户界面。用户界面1≥00中的首页1≥41被选中，即表征用户界面1≥00为首页1≥41的页面选项对应的用户界面。
检测控件1≥43用于开启呼吸系统疾病的检测功能。在一些实施例中，智能手机200可以接收用户作用于检测控件1≥43的触摸操作(例如点击操作，长按操作)，响应于该触摸操作，智能手机200可以指示智能手表300采集生理参数，并且自行开启音频数据采集模块(如麦克风)采集音频数据。示例性地，检测控件1≥43可以包括上图3所示的用户界面600中采集选项633的功能，以及上图5所示的用户界面600中采集选项663的功能。在一些实施例中，智能手机200获取到采集的生理参数和音频数据后，可以根据生理参数和音频数据确定呼吸系统的感染风险(即检测结果)。在一些实施例中，智能手机200获取到检测结果后，可以提示用户查看检测结果，例如显示提示语1≥50(包括文字：“检测完成，请查看检测结果”)。检测结果可以通过结果概述1≥10、结果说明1≥20和统计数据1≥30显示。
结果概述1≥10可以包括用户最近一次进行检测得到的检测结果，可以包括主题1≥11(即“风险等级”)，风险等级1≥12，检测时间1≥13以及健康图示1≥14。其中，风险等级1≥12可以为“未见异常”、“呼吸道感染风险”或“肺炎风险”，健康图示1≥14可以和风险等级1≥12对应，健康图示1≥14的颜色深浅表征呼吸系统感染风险的风险等级。图11所示的健康图示1≥14为浅灰色，和“未见异常”的风险等级1≥12对应，表征用户最近一次进行呼吸系统疾病的检测得到的风险等级为“未见异常”。检测时间1≥13可以包括文字：“最近检测：2021/4/20 12:35”，表征用户最近一次进行呼吸系统疾病的检测的时间为2021年4月20日12点35分。
结果说明1≥20可以包括用户最近一次进行检测得到的检测结果的说明，和结果概述1≥10对应。结果说明1≥20可以包括主题1≥21(即“结果解读”)，内容说明1≥22和提示语1≥24(即“点击查看全文”)。内容说明1≥22例如包括文字：“通过分析您的近期检测，您的呼吸道感染风险较低，属于健康的范围，继续保持良好的习惯，将为您带来持续的健康...”。在一些实施例中，智能手机200可以接收作用于结果说明1≥20的触摸操作(例如点击操作)，响应与该触摸操作，智能手机200可以显示检测结果的详细说明，例如可以包括上图5的(B)所示的用户界面≥00中多个数据的检测结果。
统计数据1≥30可以包括用户近期(例如为三个月)进行检测得到的风险等级的统计结果。 可以包括主题1≥31(即“近三个月历史记录”)，总风险趋势1≥32，检测次数1≥33，以及风险等级的统计图1≥34。其中，总风险趋势1≥32可以表征用户近三个月进行检测得到的风险等级的变化趋势说明，可以为“下降”，“平稳”，“升高”，分别表征，风险等级下降，风险等级平稳，风险等级升高。检测次数1≥33可以表征用户近三个月进行检测的次数，可以包括数字：“55”。总风险趋势1≥32和风险等级的统计图1≥34对应。风险等级的统计图1≥34中，波形为直线，且对应纵坐标：“未见风险”，表征用户近三个月进行检测得到的风险等级均为“未见异常”。
在另一些实施例中，风险等级也可以为“呼吸道感染风险”，具体示例如下图12所示。
请参见图12，图12示例性示出又一种用户界面实施例的示意图。
如图12所示，智能手机200显示的用户界面1≥00和图11所示的用户界面1≥00类似，区别在于，图12所示的用户界面1≥00中风险等级1≥12为“呼吸道感染风险”，对应的健康图示1≥14为深灰色，表征用户最近一次进行呼吸系统疾病的检测得到的风险等级为“呼吸道感染风险”。结果说明1≥20中的内容说明1≥22例如包括文字：“通过分析您的近期检测，您的呼吸道感染风险较高，建议就诊进一步确认...”。统计数据1≥30中总风险趋势1≥32为“升高”，对应的风险等级的统计图1≥34中，波形从对应纵坐标：“未见风险”的直线，变为对应纵坐标：“呼吸道感染风险”的直线，表征用户近三个月内进行呼吸系统疾病的检测，得到的风险等级从“未见异常”变为“呼吸道感染风险”。
在另一些实施例中，风险等级也可以为“肺炎风险”，具体示例如下图13所示。
请参见图13，图13示例性示出又一种用户界面实施例的示意图。
如图13所示，智能手机200显示的用户界面1≥00和图11所示的用户界面1≥00类似，区别在于，图13所示的用户界面1≥00中风险等级1≥12为“肺炎风险”，对应的健康图示1≥14为黑色，表征用户最近一次进行呼吸系统疾病的检测得到的风险等级为“肺炎风险”。结果说明1≥20中的内容说明1≥22例如包括文字：“通过分析您的近期检测，您的呼吸道感染风险很高，可能患有肺炎，建议您及时就诊...”。统计数据1≥30中总风险趋势1≥32为“升高”，对应的风险等级的统计图1≥34中，波形从对应纵坐标：“呼吸道感染风险”的直线，变为对应纵坐标：“肺炎风险”的直线，表征用户近三个月内进行呼吸系统疾病的检测，得到的风险等级从“呼吸道感染风险”变为“肺炎风险”。
在一些实施例中，智能手机200可以指示智能手表300自动采集用户的生理参数，确定生理参数异常时，可以提示用户采集音频数据，具体示例和上图9类似，区别在于采集音频数据的用户界面(例如图9的(B)所示的用户界面600)可以替换为上图11-图13所示的用户界面1≥00，智能手机200可以接收用户作用于检测控件1≥43的触摸操作(例如点击操作，长按操作)，响应于该触摸操作，智能手机200可以开启音频数据采集模块(如麦克风)采集音频数据。智能手机200可以根据采集到的生理参数和音频数据确定检测结果。具体示例不再一一列出。
不限于上述列举的示例，在另一些实施例中，智能手表300采集到生理参数后，可以自行判断生理参数是否异常，在确定生理参数异常时，向智能手机200发送指示信息。在一些实施例中，智能手机200根据该指示信息确定生理参数异常时，可以提示用户检测音频数据，具体示例和上图4、图9类似，在另一些实施例中，智能手机200根据该指示信息确定生理参数异常时，可以自动开启音频数据采集模块(如麦克风)采集音频数据，具体示例和上图10类似。
不限于上述列举的示例，在另一些实施例中，智能手表300可以自行采集生理参数，并 确定生理参数信息满足预设条件时，提示用户采集音频数据，或者自动开启音频数据采集模块(如麦克风)采集音频数据。在一些实施例中，智能手表300采集生理参数可以是作用于智能手表300上的用户操作触发的，在另一些实施例中，智能手表300采集生理参数可以是作用于智能手机200上的用户操作触发的，例如智能手机200响应于作用于图11-图13所示的用户界面1≥00的检测控件1≥43的触摸操作时，指示智能手表300采集生理参数。
不限于上述列举的示例，在另一些实施例中，智能手机200可以自行采集生理参数。在另一些实施例中，智能手机200可以指示智能手表300采集音频数据，例如，智能手机200确定生理参数异常时，可以向智能手表300发送指示信息，智能手表300可以根据指示信息提示用户采集音频数据，界面示例和图9类似。然后，智能手表300可以响应于用户操作，显示采集音频数据的用户界面，例如上图5所示的用户界面600中的音频数据采集栏位660，智能手表300可以响应于作用于采集选项663的触摸操作(例如点击操作)，开启音频数据采集模块(如麦克风)采集音频数据。本申请对采集生理参数和音频数据的电子设备不作限定。
不限于上述列举的示例，在另一些实施例中，智能手表300获取到采集的生理参数，可以根据生理参数确定呼吸系统的感染风险。在另一些实施例中，智能手表300获取到采集的生理参数和音频数据后，可以根据生理参数和音频数据确定呼吸系统的感染风险。在一些实施例中，智能手表300确定的呼吸系统的感染风险可以发送给智能手机200。本申请对确定呼吸系统的感染风险的电子设备不作限定。
基于上述图1-图13所示的一些实施例，接下来示例性介绍不同呼吸系统感染初筛模式下，第一设备(即采集设备)和第二设备(即处理设备)执行检测方法时的协作关系。在一些实施例中，第一设备和第二设备可以是同一设备，在另一些实施例中，第一设备和第二设备可以是不同设备。
以下实施例以用户操作为上图3-图13所示的用户操作为例进行说明。并且，以第一设备包括生理参数采集模块和音频数据采集模块为例进行说明，生理参数采集模块和音频数据采集模块的示例可参见上图1的说明。以第二设备为图1所示结构，检测用户操作的传感器为第二设备上的压力传感器161为例进行说明。
首先示例性介绍用户主动检测的场景下第一设备和第二设备的一种协作关系，具体可参见图14所示流程：
1.第二设备的压力传感器161检测到用户点击第一采集控件的点击操作。例如，第二设备通过显示屏130显示图3的(A)所示的用户界面600时，第二设备的压力传感器161检测到作用于采集控件633的点击操作。
2.压力传感器161将用户点击第一采集控件的点击事件上报至处理器110。
3.第二设备的处理器110确定点击事件，指示第一设备的生理参数采集模块采集生理参数，例如向第一设备发送用于指示采集生理参数的指示信息。
4.第一设备的生理参数采集模块响应于第二设备的指示，采集生理参数。
5.第一设备的生理参数采集模块向第二设备的处理器110发送采集的生理参数。
6.第二设备的压力传感器161检测到用户点击第二采集控件的点击操作。例如第二设备通过显示屏130显示图5所示的用户界面600，第二设备的压力传感器161检测到作用于采集控件663的点击操作。
7.压力传感器161将用户点击第二采集控件的点击事件上报至处理器110。
≥.第二设备的处理器110确定点击事件，指示第一设备的音频数据采集模块采集音频数 据，例如向第一设备发送用于指示采集音频数据的指示信息。
9.第一设备的音频数据采集模块响应于第二设备的指示，开启并采集音频数据。
10.第一设备的音频数据采集模块向第二设备的处理器110发送采集的音频数据。
11.第二设备的处理器110根据采集到的生理参数和音频数据，得到呼吸系统的感染风险，即检测结果。
12.处理器110指示显示屏130显示检测结果。
13.显示屏130响应于处理器110的指示，显示检测结果。例如，第二设备通过显示屏130显示图6的(B)、图10的(B)所示的用户界面≥00，图11-图13所示的用户界面1≥00。
在一些实施例中，图14所示的1-5和6-10的顺序不作限定。
在一些实施例中，用户主动检测的场景下用户界面实施例的示例可参见上图3、图5、图6所示实施例，可选地，图14所示的1-5对应上图3所示实施例，可选地，图14所示的6-10对应上图5所示实施例，可选地，图14所示的11-13对应上图6所示实施例。
不限于图14列举的流程，在另一些实施例中，第一设备的压力传感器161也可以检测到用户点击第三采集控件的点击操作，例如第二设备通过显示屏130显示图11-图13所示的用户界面1≥00，第二设备的压力传感器161检测到作用于检测控件1≥43的点击操作。第一设备的处理器110接收到压力传感器161上报的用户点击第三采集控件的点击事件时，可以指示第一设备的音频数据采集模块采集音频数据，以及指示第一设备的生理参数采集模块采集生理参数。用户界面实施例的示例可参见上图11-图13所示实施例。
接下来示例性介绍设备持续自动检测的场景下第一设备和第二设备的一种协作关系，具体可参见图15所示流程：
1.第一设备的生理参数采集模块持续采集生理参数，例如按照第一周期采集生理参数。
2.第一设备的生理参数采集模块向第二设备的处理器110发送采集的生理参数，例如按照第二周期发送采集的生理参数，或者采集到预设时长的生理参数后就发送。
3.第二设备的处理器110确定采集到的生理参数异常。例如每次接收到生理参数后就判断生理参数是否异常，或者接收到预设次数次生理参数时判断生理参数是否异常。生理参数异常的说明具体可参见上图3-图13中生理参数异常的说明。
4.第二设备的处理器110根据采集到的生理参数确定检测结果。
5.处理器110指示显示屏130显示检测结果。
6.显示屏130响应于处理器110的指示，显示检测结果。例如，第二设备通过显示屏130显示图≥的(B)所示的用户界面≥00，图11-图13所示的用户界面1≥00。
在一些实施例中，设备持续自动检测的场景下用户界面实施例的示例可参见上图7-图≥所示实施例，可选地，图15所示的1-6对应上图≥所示实施例。
接下来示例性介绍用户在设备提示下检测音频数据的场景下第一设备和第二设备的一种协作关系，具体可参见图16所示流程：
1.第一设备的生理参数采集模块采集生理参数，在一些实施例中，第二设备的处理器110指示第一设备的生理参数采集模块持续采集生理参数，例如按照第一周期采集生理参数，在另一些实施例中，第二设备的处理器110确定接收到点击第一采集控件的点击事件时，指示第一设备的生理参数采集模块采集生理参数。
2.第一设备的生理参数采集模块向第二设备的处理器110发送采集的生理参数。
3.第二设备的处理器110确定第一设备采集的生理参数异常。生理参数异常的说明具体可参见上图3-图13中生理参数异常的说明。
4.处理器110确定生理参数异常的情况下，指示显示屏130显示生理参数异常的提示信息。
5.显示屏130响应于处理器110的指示，显示生理参数异常的提示信息。例如，第二设备通过显示屏130显示图9的(A)所示的用户界面400，提示信息即为用户界面400中第一通知栏410的通知内容412。例如，第二设备通过显示屏130显示图4所示的用户界面600，提示信息即为用户界面600中提示内容640的提示语641。
6.第二设备的压力传感器161检测到用户点击第二采集控件的点击操作。例如第二设备通过显示屏130显示图5所示的用户界面600，第二设备的压力传感器161检测到作用于采集控件663的点击操作。
7.压力传感器161将用户点击第二采集控件的点击事件上报至处理器110。
≥.第二设备的处理器110确定点击事件，指示第一设备的音频数据采集模块采集音频数据。
9.第一设备的音频数据采集模块响应于第二设备的指示，开启并采集音频数据。
10.第一设备的音频数据采集模块向第二设备的处理器110发送采集的音频数据。
11.第二设备的处理器110根据采集到的生理参数和音频数据，确定检测结果。
12.处理器110指示显示屏130显示检测结果。
13.显示屏130响应于处理器110的指示，显示检测结果。例如，第二设备通过显示屏130显示图6的(B)、图10的(B)所示的用户界面≥00，图11-图13所示的用户界面1≥00。
在一些实施例中，用户在设备提示下检测音频数据的场景下用户界面实施例的示例可参见上图4、图9所示实施例，可选地，图16所示的3-5对应上图4、图9所示实施例。
接下来示例性介绍设备自动检测音频数据的场景下第一设备和第二设备的一种协作关系，具体可参见图17所示流程：
1.第一设备的生理参数采集模块采集生理参数，在一些实施例中，第二设备的处理器110指示第一设备的生理参数采集模块持续采集生理参数，例如按照第一周期采集生理参数，在另一些实施例中，第二设备的处理器110确定接收到点击第一采集控件的点击事件时，指示第一设备的生理参数采集模块采集生理参数。
2.第一设备的生理参数采集模块向第二设备的处理器110发送采集的生理参数。
3.第二设备的处理器110确定第一设备采集的生理参数异常。生理参数异常的说明具体可参见上图3-图13中生理参数异常的说明。
4.第二设备的处理器110确定生理参数异常的情况下，指示第一设备的音频数据采集模块采集音频数据。
5.第一设备的音频数据采集模块响应于第二设备的指示，开启并采集音频数据。
6.第一设备的音频数据采集模块向第二设备的处理器110发送采集的音频数据。
7.第二设备的处理器110根据第一设备采集的生理参数和音频数据，确定检测结果。
≥.处理器110指示显示屏130显示检测结果。
9.显示屏130响应于处理器110的指示，显示检测结果。例如，第二设备通过显示屏130显示图6的(B)、图10的(B)所示的用户界面≥00，图11-图13所示的用户界面1≥00。
在一些实施例中，设备自动检测音频数据的场景下用户界面实施例的示例可参见上图10 所示实施例，可选地，图17所示的3-9对应上图10所示实施例。
本申请实施例可以应用于不同的检测场景，满足用户在不同场景下的不同需求，多场景多覆盖，在保证检测结果的准确性的同时提升用户体验感。并且，在图16-图17所示流程中，可以在生理参数异常的情况下再启动音频数据采集模块采集音频数据，减少设备功耗，产品可用性更高。
基于上图1-图17所示的一些实施例，接下来介绍本申请提供的检测方法。
请参见图1≥，图1≥是本申请实施例提供的一种检测方法的流程示意图。该方法可以应用于图1所示的电子设备100。该方法可以应用于图2所示的电子设备100。该方法可以包括但不限于如下步骤：
S101：电子设备获取生理参数。
在一些实施例中，电子设备自行采集生理参数，在另一些实施例中，电子设备接收其他设备采集的生理参数，可选地，电子设备可以指示其他设备采集生理参数。生理参数例如但不限于包括以下至少一项：体温、血氧饱和度、呼吸频率、心率、脉搏等。用于采集生理参数的采集模块的示例可参见图1所示的生理参数采集模块。
S102：电子设备确定生理参数满足预设条件的情况下，获取音频数据。
在一些实施例中，预设条件可以包括但不限于以下至少一项：体温大于或等于体温阈值(单位例如为摄氏度)，血氧饱和度小于或等于血氧阈值(单位例如为百分比)，呼吸频率大于或等于频率阈值(单位例如为次/分钟)，心率大于或等于心率阈值(单位例如为次/分钟)，脉搏大于或等于脉搏阈值(单位例如为次/分钟)。可选地，生理参数满足预设条件表征生理参数异常，生理参数异常的示例可参见上图3-图13所示的生理参数异常的说明。
在一些实施例中，音频数据例如但不限于包括以下至少一项：咳嗽音、呼吸音、心音、肺音等。
在一种可能的实现方式中，电子设备确定生理参数满足预设条件的情况下，可以显示提示信息，提示信息用于提示用户采集音频数据。在一些实施例中，电子设备可以接收用户操作，例如作用于图5所示的用户界面600的采集选项663的用户操作，响应于该用户操作，自行采集音频数据。在另一些实施例中，电子设备可以接收其他设备采集的音频数据，可选地，电子设备可以响应于接收的用户操作，指示其他设备采集音频数据。在另一些实施例中，和电子设备连接的其他设备可以接收用户操作，响应于该用户操作，采集音频数据，然后发送给电子设备。
在一些实施例中，电子设备可以自行显示提示信息，例如，电子设备显示图9的(A)所示的用户界面400，提示信息即为用户界面400中第一通知栏410的通知内容412。例如，电子设备显示图4所示的用户界面600，提示信息即为用户界面600中提示内容640的提示语641。在另一些实施例中，电子设备可以指示连接的其他设备显示提示信息，例如，电子设备为智能手机200，智能手机200可以指示连接的智能手表300显示图9的(C)所示的用户界面700，提示信息即为用户界面700包括的文字。
在又一种可能的实现方式中，电子设备确定生理参数满足预设条件的情况下，可以直接获取音频数据。在一些实施例中，电子设备确定生理参数满足预设条件时，自行采集音频数据。在另一些实施例中，电子设备确定生理参数满足预设条件时，指示其他设备采集音频数据，并接收其他设备发送的音频数据。
S103：电子设备根据生理参数和音频数据确定呼吸系统的感染风险。
在一些实施例中，感染风险可以包括多个风险等级，例如低风险、中风险和高风险，具体示例可参见图6的(B)、图10的(B)所示的用户界面≥00。或者，未见异常、呼吸道感染风险和肺炎风险，具体示例可参见图11-图13所示的用户界面1≥00。
S103的具体示例可参见下图20所示实施例。
示例性地，图1≥所示流程的示例可参见上图4、图9、图10所示实施例。
不限于图1≥示例的检测方法，在另一些实施例中，电子设备可以接收其他设备发送的指示信息，该指示信息用于指示生理参数满足预设条件，该指示信息为其他设备采集生理参数后确定得到的。电子设备根据上述指示信息确定生理参数满足预设条件时，获取音频数据，具体过程和S102类似。然后电子设备可以根据生理参数和音频数据确定呼吸系统的感染风险，具体过程和S103类似。
本申请可以综合分析生理参数和音频数据，以实现呼吸系统的感染风险的检测，相比仅使用生理参数或仅使用音频数据确定检测结果，精度更高。本申请可以在确定生理参数异常的情况下，提示用户检测音频数据，并根据用户操作开启音频数据采集模块(如麦克风)采集音频数据，或者自动开启音频数据采集模块采集音频数据，而不是一直开启麦克风，在保证检测结果的准确性的同时提升用户体验，减少设备功耗，提升产品竞争力。
在一些实施例中，电子设备100的软件架构也可以为其他架构，例如下图19所示架构。
请参见图19，图19示例性示出了一种电子设备100的软件架构示意图。
如图19所示，电子设备100可以包括采集模块310，全主动检测模块320，半主动检测模块330，持续自动检测模块340，实时自动检测模块350和风险评估模块360。
在一些实施例中，采集模块310用于采集用户的生理参数(例如体温、血氧饱和度、呼吸频率、心率、脉搏等)，在一些实施例中，采集模块310用于采集用户的音频数据(例如咳嗽音、呼吸音、心肺音等)。在一些实施例中，采集模块310可以包括生理参数采集模块，例如上图1所示的传感器模块160中除压力传感器161外的传感器。在一些实施例中，采集模块310可以包括音频数据采集模块，例如上图1所示的麦克风151和压力传感器161。
全主动检测模块320应用于用户主动检测的场景。在一些实施例中，全主动检测模块320可以响应于用户操作指示采集模块310采集生理参数和音频数据，采集的生理参数和音频数据用于确定呼吸系统的感染风险。
半主动检测模块330应用于用户在设备提示下检测音频数据的场景。在一些实施例中，半主动检测模块330可以指示采集模块310采集生理参数，在一些实施例中，半主动检测模块330可以判断生理参数是否异常，确定生理参数异常时提示用户检测音频数据，在一些实施例中，半主动检测模块330可以响应于用户操作指示采集模块310采集音频数据。采集的生理参数和音频数据用于确定呼吸系统的感染风险。
持续自动检测模块340应用于设备持续(长时间)自动检测的场景。在一些实施例中，持续自动检测模块340可以指示采集模块310采集生理参数。采集的生理参数用于确定呼吸系统的感染风险。
实时自动检测模块350应用于设备自动检测音频数据的场景。在一些实施例中，实时自动检测模块350可以指示采集模块310采集生理参数，在一些实施例中，实时自动检测模块350可以判断生理参数是否异常，确定生理参数异常时指示采集模块310采集音频数据。采集的生理参数和音频数据用于确定呼吸系统的感染风险。
在一些实施例中，风险评估模块360用于对采集的生理参数和音频数据进行分析处理， 以确定呼吸系统的感染风险。在另一些实施例中，风险评估模块360用于对采集的生理参数进行分析处理，以确定呼吸系统的感染风险。风险评估模块360确定呼吸系统的感染风险的具体示例可参见下图20所示实施例，暂不详述。
在一些实施例中，图1所示的处理器110可以包括图19所示的全自动检测模块320，半主动检测模块330，持续自动检测模块340，实时自动检测模块350以及风险评估模块360。
可以理解的是，本申请实施例示意的结构并不构成对电子设备100的具体限定。在本申请另一些实施例中，电子设备100可以包括比图示更多或更少的部件，或者组合某些部件，或者拆分某些部件，或者不同的部件布置。图示的部件可以以硬件，软件或软件和硬件的组合实现。例如，图19所示的电子设备100为第二设备，可以不包括采集模块310。例如，图19所示的电子设备100为第一设备，可以不包括风险评估模块360。
接下来示例性介绍上图1≥的S103的具体实现方式，具体如下图20所示。
请参见图20，图20示例性示出一种呼吸系统的感染风险的确定方式的架构示意图。图20以第一设备和第二设备为图19所示结构为例进行说明，其中，采集模块310属于第一设备(即采集设备)，风险评估模块360属于第二设备(即处理设备)。
如图20所示，采集模块310可以包括生理参数采集模块311和音频数据采集模块312，生理参数采集模块和音频数据采集模块的示例可参见上图1的说明。风险评估模块360可以包括第一特征提取模块361，预处理模块362，第二特征提取模块363，编码模块364，分类模块365。
为了方便理解，图20将生理参数采集模块311采集前的体温、血氧饱和度、呼吸频率、心率、脉搏等数据称为原始生理数据，采集得到的体温、血氧饱和度、呼吸频率、心率、脉搏等数据称为生理参数，可以理解为是生理参数采集模块311将检测的原始生理数据转换为生理参数，例如上图1中，脉搏传感器166可以检测动脉搏动时产生的压力变化，并将其转换为电信号。心率传感器167可以通过反射或透射等方式，将血管动力发生的变化，例如血脉搏率(心率)或血容积(心输出量)发生的变化，转换为电信号输出。
为了方便理解，图20将音频数据采集模块312采集前的咳嗽音、呼吸音、心音、肺音等数据称为原始音频数据，采集得到的咳嗽音、呼吸音、心音、肺音等数据称为音频数据，可以理解为是音频数据采集模块312将检测的原始音频数据转换为音频数据，例如上图1中，压力传感器161用于感受压力信号，可以将压力信号转换成电信号。麦克风151用于将声音信号转换为电信号。
如图20所示，生理参数采集模块311采集得到的生理参数可以传输至第一特征提取模块361进行特征提取，例如但不限于包括以下至少一项：奇异值分解(singular value decomposition，SVD)，主成分分析(principal component analysis，PCA)，线性判别分析等。图20可以将第一特征提取模块361的输出称为生理特征数据。
如图20所示，音频数据采集模块312采集得到的音频数据可以传输至预处理模块362进行预处理，示例性地，可以依次进行幅值归一化、中值滤波和带通滤波，其中，幅值归一化可以消除数据数量级与本身局部波动的影响，中值滤波和带通滤波可以消除噪声的干扰，预处理模块362输出的数据可以传输至第二特征提取模块363进行特征提取，例如先进行原始特征提取，再聚合统计特征。原始特征提取中提取的特征例如但不限于包括以下至少一项：梅尔频率倒谱系数，差分特征，光谱平坦度。聚合统计特征中得到的特征例如但不限于包括以下至少一项：均值、方差，峰度、偏度、距特征。图20可以将第二特征提取模块363的输 出称为生理特征数据。预处理后再进行后续的特征提取可以提高评估呼吸系统感染风险的准确性。
如图20所示，第一特征提取模块361的输出：生理特征数据，第二特征提取模块363的输出：音频特征数据，可以传输至编码模块364进行编码，示例性地，可以输入梯度提升随机树(gradient boosting decison tree，GBDT)，以对生理特征数据和音频特征数据进行编码和组合，假设得到的特征编码为0或1，其中，0表示该项特征异常，1表示该项特征正常，若生理参数包括体温、呼吸频率、血氧饱和度和心率四类，则得到的组合可以是[0,1,1,1,0]，具体表示：体温异常(对应组合的第一个编码0)，呼吸频率正常(对应组合的第二个编码1)，血氧饱和度正常(对应组合的第三个编码1)，心率正常(对应组合的第四个编码1)，音频数据(咳嗽音和呼吸音)异常(对应组合的第五个编码0)。
如图20所示，编码模块364的输出可以传输至分类模块365进行分类，以获取呼吸系统的感染风险。示例性地，编码模块364的输出可以输入逻辑回归(logistic regression，LR)模型，输出的风险等级例如但不限于包括低风险、中风险和高风险，或者未见异常、呼吸系统感染风险和肺炎风险。在一些实施例中，呼吸系统的感染风险还可以包括每项特征的具体检测结果，例如体温的具体检测结果可以是7天内的统计数据。
在一些实施例中，上述生理参数可以是生理参数采集模块311长时间(持续)采集得到的，上述音频数据可以是生理参数异常的情况下，音频数据采集模块312开启后实时采集得到的，采集过程用户无感，提高用户体验的同时减少了功耗，产品竞争力更高。本申请中，实时检测和长时间跟踪结合，在保证评估结果的准确性的同时大大提升了用户体验。
需要说明的是，本申请实施例中“至少一个”是指一个或者多个，多个是指两个或两个以上。除非另有定义，本文所使用的所有的技术和科学术语与属于本申请中的技术领域的技术人员通常理解的含义相同。本申请的说明书中所使用的术语只是为了描述具体的实施例的目的，不是旨在于限制本发明申请。应理解，本申请中除非另有说明，“/”表示或的意思。例如，A/B可以表示A或B。本申请中的“和/或”仅仅是一种描述关联对象的关联关系，表示可以存在三种关系。
需要说明的是，本申请实施例中，“第一”、“第二”等词汇，仅用于区分描述的目的，而不能理解为指示或暗示相对重要性，也不能理解为指示或暗示顺序。限定有“第一”、“第二”的特征可以明示或者隐含地包括一个或者更多个该特征。在本申请实施例的描述中，“示例性的”或者“例如”等词用于表示作例子、例证或说明。本申请实施例中被描述为“示例性的”或者“例如”的任何实施例或设计方案不应被解释为比其它实施例或设计方案更优选或更具优势。确切而言，使用“示例性的”或者“例如”等词旨在以具体方式呈现相关概念。
本领域普通技术人员可以理解实现上述实施例方法中的全部或部分流程，该流程可以由计算机程序来计算机程序相关的硬件完成，该计算机程序可存储于计算机可读取存储介质中，该计算机程序在执行时，可包括如上述各方法实施例的流程。而前述的存储介质包括：只读存储器(read-only memory，ROM)或随机存取存储器(random access memory，RAM)、磁碟或者光盘等各种可存储计算机程序代码的介质。

Claims (19)

  1. 一种检测方法，其特征在于，应用于第一电子设备，所述方法包括：
    检测第一操作；
    响应于所述第一操作，向第二电子设备发送第一信息；
    接收所述第二电子设备基于所述第一信息发送的生理参数信息；
    当确定所述生理参数信息满足预设条件时，获取音频信息；
    根据所述生理参数信息和所述音频信息确定第一生理信息；
    显示所述第一生理信息。
  2. 如权利要求1所述的方法，其特征在于，所述生理参数信息包括以下一项或多项：体温、血氧饱和度、呼吸频率、心率、脉搏，所述音频信息包括以下一项或多项：咳嗽音、呼吸音、心音、肺音。
  3. 如权利要求2所述的方法，其特征在于，所述预设条件包括以下一项或多项：体温大于或等于预设体温阈值，血氧饱和度小于或等于预设血氧阈值，呼吸频率大于或等于预设频率阈值，心率大于或等于预设心率阈值，脉搏大于或等于预设脉搏阈值。
  4. 如权利要求1-3任一项所述的方法，其特征在于，所述生理参数信息是所述第二电子设备基于所述第一信息周期性发送的。
  5. 如权利要求1-4任一项所述的方法，其特征在于，所述当确定所述生理参数信息满足预设条件时，获取音频信息，包括：
    当确定所述生理参数信息满足所述预设条件时，显示第一用户界面，所述第一用户界面包括用于提示检测所述音频信息的第二信息；
    检测作用于所述第一用户界面的第二操作；
    响应于所述第二操作，显示第二用户界面；
    基于所述第二用户界面采集所述音频信息。
  6. 如权利要求1-4任一项所述的方法，其特征在于，所述当确定所述生理参数信息满足预设条件时，获取音频信息，包括：
    当确定所述生理参数信息满足所述预设条件时，向所述第二电子设备发送第三信息，所述第三信息用于所述第二电子设备显示第三用户界面，所述第三用户界面用于采集所述音频信息；
    接收所述第二电子设备发送的所述音频信息。
  7. 一种检测方法，其特征在于，应用于第一电子设备，所述方法还包括：
    接收第二电子设备发送的第一信息，所述第一信息用于指示生理参数信息满足预设条件；
    根据所述第一信息，显示第一用户界面，所述第一用户界面包括用于提示检测音频信息的第二信息；
    检测作用于所述第一用户界面的第一操作；
    响应于所述第一操作，显示第二用户界面，所述第二用户界面用于获取所述音频信息；
    根据所述生理参数信息和所述音频信息确定第一生理信息；
    显示所述第一生理信息。
  8. 如权利要求7所述的方法，其特征在于，所述生理参数信息包括以下一项或多项：体温、血氧饱和度、呼吸频率、心率、脉搏，所述音频信息包括以下一项或多项：咳嗽音、呼吸音、心音、肺音。
  9. 如权利要求8所述的方法，其特征在于，所述预设条件包括以下一项或多项：体温大于或等于预设体温阈值，血氧饱和度小于或等于预设血氧阈值，呼吸频率大于或等于预设频率阈值，心率大于或等于预设心率阈值，脉搏大于或等于预设脉搏阈值。
  10. 如权利要求7-9任一项所述的方法，其特征在于，所述接收第二电子设备发送的第一信息之前，所述方法还包括：
    检测第二操作；
    响应于所述第二操作，向所述第二电子设备发送第三信息，所述第一信息是所述第二电子设备基于所述第三信息确定的。
  11. 如权利要求7-9任一项所述的方法，其特征在于，所述第一信息是所述第二电子设备响应于检测到的第三操作确定的。
  12. 如权利要求7-11任一项所述的方法，其特征在于，所述根据所述第一信息，显示第一用户界面之前，所述方法还包括：
    根据所述第一信息，显示第三用户界面，所述第三用户界面为包括所述第二信息的锁屏界面；
    检测解锁操作；
    所述根据所述第一信息，显示第一用户界面，包括：
    响应于所述解锁操作，根据所述第一信息显示所述第一用户界面。
  13. 一种检测方法，其特征在于，应用于第一电子设备，所述方法还包括：
    采集生理参数信息；
    当确定所述生理参数信息满足预设条件时，显示第一用户界面，所述第一用户界面包括用于提示检测音频信息的第一信息；
    检测作用于所述第一用户界面的第一操作；
    响应于所述第一操作，显示第二用户界面，所述第二用户界面用于获取所述音频信息；
    根据所述生理参数信息和所述音频信息确定第一生理信息；
    显示所述第一生理信息。
  14. 如权利要求13所述的方法，其特征在于，所述生理参数信息包括以下一项或多项：体温、血氧饱和度、呼吸频率、心率、脉搏，所述音频信息包括以下一项或多项：咳嗽音、呼吸音、心音、肺音。
  15. 如权利要求14所述的方法，其特征在于，所述预设条件包括以下一项或多项：体温大于或等于预设体温阈值，血氧饱和度小于或等于预设血氧阈值，呼吸频率大于或等于预设频率阈值，心率大于或等于预设心率阈值，脉搏大于或等于预设脉搏阈值。
  16. 如权利要求13-15任一项所述的方法，其特征在于，所述采集生理参数信息之前，所述方法还包括：检测第二操作；
    所述采集生理参数信息，包括：响应于所述第二操作，采集所述生理参数信息。
  17. 如权利要求13-15任一项所述的方法，其特征在于，所述采集生理参数信息之前，所述方法还包括：接收第二电子设备发送的第二信息，所述第二信息为所述第二电子设备响应于检测到的第三操作确定的；
    所述采集生理参数信息，包括：基于所述第二信息，采集所述生理参数信息。
  18. 一种电子设备，其特征在于，包括收发器、处理器和存储器，所述存储器用于存储计算机程序，所述处理器调用所述计算机程序，用于执行如权利要求1-17任一项所述的方法。
  19. 一种计算机存储介质，其特征在于，所述计算机存储介质存储有计算机程序，所述计算机程序被处理器执行时，实现权利要求1-17任一项所述的方法。
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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116090691A (zh) * 2023-04-07 2023-05-09 成都超有范儿科技有限公司 一种社区云平台健康管理方法
CN116999024A (zh) * 2023-05-26 2023-11-07 荣耀终端有限公司 生理参数检测方法、电子设备、存储介质及程序产品

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104434142A (zh) * 2014-11-14 2015-03-25 惠州Tcl移动通信有限公司 可穿戴设备以及情绪提醒的方法
CN105380655A (zh) * 2015-10-23 2016-03-09 广东小天才科技有限公司 一种移动终端的情绪预警方法、装置及移动终端
WO2016142360A1 (en) * 2015-03-09 2016-09-15 Koninklijke Philips N.V. Wearable device obtaining audio data for diagnosis
CN206080518U (zh) * 2016-06-08 2017-04-12 任昊星 一种可穿戴式呼吸监护系统
CN107595259A (zh) * 2017-09-19 2018-01-19 广东小天才科技有限公司 一种报警方法、装置、穿戴设备及存储介质
CN112998669A (zh) * 2021-02-08 2021-06-22 深圳市沃特沃德信息有限公司 用于健康检测的智能设备和用于健康检测的智能手表
CN113854969A (zh) * 2021-10-29 2021-12-31 海信视像科技股份有限公司 一种智能终端及睡眠监测方法

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104434142A (zh) * 2014-11-14 2015-03-25 惠州Tcl移动通信有限公司 可穿戴设备以及情绪提醒的方法
WO2016142360A1 (en) * 2015-03-09 2016-09-15 Koninklijke Philips N.V. Wearable device obtaining audio data for diagnosis
CN105380655A (zh) * 2015-10-23 2016-03-09 广东小天才科技有限公司 一种移动终端的情绪预警方法、装置及移动终端
CN206080518U (zh) * 2016-06-08 2017-04-12 任昊星 一种可穿戴式呼吸监护系统
CN107595259A (zh) * 2017-09-19 2018-01-19 广东小天才科技有限公司 一种报警方法、装置、穿戴设备及存储介质
CN112998669A (zh) * 2021-02-08 2021-06-22 深圳市沃特沃德信息有限公司 用于健康检测的智能设备和用于健康检测的智能手表
CN113854969A (zh) * 2021-10-29 2021-12-31 海信视像科技股份有限公司 一种智能终端及睡眠监测方法

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116090691A (zh) * 2023-04-07 2023-05-09 成都超有范儿科技有限公司 一种社区云平台健康管理方法
CN116090691B (zh) * 2023-04-07 2023-07-14 成都超有范儿科技有限公司 一种社区云平台健康管理方法
CN116999024A (zh) * 2023-05-26 2023-11-07 荣耀终端有限公司 生理参数检测方法、电子设备、存储介质及程序产品

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