Method and device for evaluating risk of coronary heart disease

Abstract

The invention provides a coronary heart disease risk assessment method and device, and relates to the technical field of terminals. The method comprises the following steps: acquiring first electrocardiogram data in a first time period; acquiring second electrocardiogram data and / or second pulse wave data in a second time period, wherein the duration of the second time period is greater than that of the first time period; determining a coronary heart disease risk assessment result according to first data, wherein the first data comprises the first electrocardiogram data, the second electrocardiogram data and / or the second pulse wave data; wherein the second pulse wave data comprises pulse wave data of the user in a sleep state and pulse wave data of the user in a non-sleep state. According to the method in the embodiment of the invention, the accuracy of coronary heart disease risk assessment can be improved, so that the user experience can be improved.

Description

Technical Field

[0001] This application relates to the field of terminal technology, and specifically to a method and apparatus for assessing the risk of coronary heart disease. Background Technology

[0002] Coronary atherosclerotic heart disease (CAD) is a chronic disease caused by atherosclerosis in the coronary arteries. CAD can lead to myocardial infarction and sudden cardiac death, making it a highly dangerous disease.

[0003] Currently, there are various methods for detecting coronary heart disease, such as electrocardiogram (ECG), blood parameter tests, coronary computed tomography (CT) scans, and coronary angiography. However, these methods all require examination in a hospital and cannot be performed at home. Some of these methods are relatively complex to operate, and others are invasive examinations, posing certain risks. Summary of the Invention

[0004] This application provides a method and apparatus for assessing the risk of coronary heart disease, which can improve the user experience.

[0005] Firstly, it provides a method for assessing the risk of coronary heart disease, including:

[0006] Acquire first electrocardiogram (ECG) data during a first time period; acquire second ECG data and / or second pulse wave data during a second time period, the duration of the second time period being longer than the duration of the first time period; determine the coronary heart disease risk assessment result based on the first data, the first data including: the first ECG data, the second ECG data, and / or the second pulse wave data; wherein, the second pulse wave data includes the pulse wave data of the user in a sleep state and the pulse wave data of the user in a non-sleep state.

[0007] In this embodiment, first electrocardiogram (ECG) data is acquired during a first time period, and second ECG data and / or second pulse wave data are acquired during a second time period. The coronary heart disease risk assessment result is determined based on the first ECG data, the second ECG data, and / or the second pulse wave data. Compared with assessment methods based on single measurement data (such as ECG data or pulse wave data), the accuracy of coronary heart disease risk assessment can be improved by using multiple measurement data (such as first ECG data, second ECG data, and / or second pulse wave data), thereby enhancing the user experience.

[0008] Meanwhile, the second time period is longer than the first time period. The second electrocardiogram (ECG) data includes ECG data of the user during sleep and ECG data of the user during non-sleep. In this way, by combining data obtained from short-term measurements (such as the first ECG data) and data obtained from long-term measurements (such as the second ECG data and / or the second pulse wave data), as well as ECG data of the user during sleep and non-sleep, the results of the coronary heart disease risk assessment can be determined, which can further improve the accuracy of the coronary heart disease risk assessment and thus further enhance the user experience.

[0009] Furthermore, the method in this embodiment does not require specialized medical equipment, which can improve the convenience of coronary heart disease risk assessment and thus enhance the user experience.

[0010] In some possible implementations, the second electrocardiogram (ECG) data includes ECG data of the user during sleep and ECG data of the user during non-sleep.

[0011] In this embodiment, the second electrocardiogram (ECG) data includes ECG data of the user during sleep and ECG data of the user during non-sleep. In this way, combining ECG data of the user during sleep and non-sleep in the process of determining the risk assessment results of coronary heart disease can further improve the accuracy of the risk assessment of coronary heart disease, thereby further enhancing the user experience.

[0012] In some possible implementations, the first electrocardiogram (ECG) data is static ECG data, and the second ECG data is dynamic ECG data.

[0013] In this embodiment, the first electrocardiogram (ECG) data is static ECG data, and the second ECG data is dynamic ECG data. In this way, combining static ECG data and dynamic ECG data in the process of determining the risk assessment results of coronary heart disease can improve the accuracy of the risk assessment and thus enhance the user experience.

[0014] In some possible implementations, acquiring the first electrocardiogram data in the first time period includes:

[0015] The first electrocardiogram data and the first pulse wave data are acquired during the first time period; wherein, the first data further includes the first pulse wave data.

[0016] In this embodiment, first electrocardiogram data and first pulse wave data are acquired in the first time period. In this way, combining the first pulse wave data in the process of determining the coronary heart disease risk assessment result can improve the accuracy of the coronary heart disease risk assessment, thereby improving the user experience.

[0017] In some possible implementations, the method further includes:

[0018] If the user is detected to be exercising during the second time period, first information is output, which is used to remind the user to perform an electrocardiogram (ECG) measurement after completing the exercise; third ECG data is acquired after the user completes the exercise; wherein, the first data also includes the third ECG data.

[0019] In this embodiment of the application, when it is detected that the user is exercising during the second time period, the user is reminded to have an electrocardiogram (ECG) measurement after completing the exercise. This can avoid the risk of myocardial infarction induced by actively guiding the user to perform load training (such as during an exercise stress test ECG), thereby improving the safety of coronary heart disease risk assessment.

[0020] In some possible implementations, the method further includes:

[0021] The system outputs second information at a preset time during the second time period, the second information being used to remind the user to perform an electrocardiogram (ECG) measurement; and acquires fourth ECG data during the second time period; wherein, the first data further includes the fourth ECG data.

[0022] In this embodiment of the application, reminding the user to perform electrocardiogram (ECG) measurement at a preset time during the second time period helps to obtain more ECG data during the second time period. This helps to combine more ECG data in the process of determining the risk assessment results of coronary heart disease, and helps to improve the accuracy of the risk assessment of coronary heart disease.

[0023] In some possible implementations, the method further includes: outputting third information, which is used to indicate the progress of coronary artery disease risk assessment.

[0024] In this embodiment of the application, the third information is used to indicate the progress of the coronary heart disease risk assessment. Outputting the third information allows users to keep track of the progress of the coronary heart disease risk assessment in a timely manner, thereby improving user evaluation.

[0025] In some possible implementations, the third information is determined based on the measurement progress of the second electrocardiogram data and / or the second pulse wave data.

[0026] In some possible implementations, the output of the third information includes: outputting the third information at the first moment after the user wakes up from sleep.

[0027] In this embodiment of the application, the third information is output immediately after the user wakes up from sleep, which allows the user to understand the progress of the night's assessment in a timely manner after waking up, thereby improving the user's evaluation.

[0028] In some possible implementations, the third information is also used for one or more of the following: indicating whether the user has achieved the required wearing standard during sleep, indicating the current overall assessment progress percentage, and indicating the estimated remaining wearing time.

[0029] In this embodiment of the application, the third information is also used to indicate whether the user has achieved the target during sleep, to indicate the current overall assessment progress percentage, and / or the estimated remaining wearing time. In this way, the user can have a clearer understanding of the assessment situation at night, which makes it easier for the user to take corresponding measures in a timely manner based on the assessment situation at night, thereby helping to improve the efficiency of coronary heart disease risk assessment.

[0030] In some possible implementations, the output of the third information includes: outputting the third information at a second moment before the user falls asleep.

[0031] In this embodiment of the application, the third information is output at a second moment before the user falls asleep, which allows the user to understand the evaluation progress of the day in a timely manner before falling asleep, thereby improving the user's evaluation.

[0032] In some possible implementations, the third information is also used for one or more of the following: indicating whether the user has achieved the required wearing time during non-sleep periods, indicating the estimated remaining wearing time, and reminding the user to wear the wearable device during sleep.

[0033] In this embodiment of the application, the third information is also used to indicate whether the user's wearing of the device during non-sleep periods meets the standard, to indicate the estimated remaining wearing time, and / or to remind the user to wear the wearable device during sleep. In this way, the user can have a clearer understanding of the daytime assessment, which makes it easier for the user to take corresponding measures in a timely manner based on the daytime assessment, thereby helping to improve the efficiency of coronary heart disease risk assessment.

[0034] In some possible implementations, the method further includes:

[0035] If it is anticipated that the user will be unable to complete the coronary heart disease risk assessment, a fourth piece of information will be output, which will be used to suggest that the user undergo the coronary heart disease risk assessment again.

[0036] In this embodiment of the application, the fourth information is used to suggest that the user re-evaluate the risk of coronary heart disease. The fourth information is output when it is estimated that the user is unable to complete the risk assessment of coronary heart disease, so that the user can restart a new round of assessment in a timely manner, thereby helping to improve the efficiency of the risk assessment of coronary heart disease.

[0037] In some possible implementations, the method further includes:

[0038] Acquire fifth electrocardiogram data and / or third pulse wave data during the third time period; wherein the second time period is after the first time period, the third time period is after the second time period or the third time period is within the second time period, and the first data also includes the third electrocardiogram data and / or the third pulse wave data.

[0039] In this embodiment of the application, the fifth electrocardiogram data and / or the third pulse wave data are acquired during the third time period. In this way, combining the fifth electrocardiogram data and / or the third pulse wave data in the process of determining the coronary heart disease risk assessment result can improve the accuracy of the coronary heart disease risk assessment, thereby enhancing the user experience.

[0040] In some possible implementations, the method further includes:

[0041] The system acquires second data input by the user, which is used to assess the user's health status; wherein the first data further includes the second data.

[0042] In this embodiment of the application, the second data is used to assess the user's health status. By obtaining the second data, the accuracy of the coronary heart disease risk assessment can be improved by combining the second data in the process of determining the coronary heart disease risk assessment result, thereby enhancing the user experience.

[0043] In some possible implementations, the second data includes one or more of the following information:

[0044] Do you have a history of coronary heart disease, cardiovascular or cerebrovascular disease, high blood pressure, high cholesterol, high blood sugar, high uric acid, chest tightness, or chest pain?

[0045] In some possible implementations, the method further includes:

[0046] Waveform analysis is performed on the first electrocardiogram (ECG) data to obtain the waveform characteristics of the first ECG data; fifth information is output, which is used to indicate the waveform characteristics of the first ECG data; wherein, the coronary heart disease risk assessment result includes the waveform characteristics of the first ECG data.

[0047] In this embodiment of the application, waveform analysis is performed on the first electrocardiogram data to obtain and output the waveform characteristics of the first electrocardiogram data. In this way, users can know the measurement results of the first electrocardiogram data, which makes it easier for users to take corresponding measures in a timely manner based on the measurement results, thereby helping to improve the efficiency of coronary heart disease risk assessment.

[0048] In some possible implementations, the coronary heart disease risk assessment results include the user's risk level for coronary heart disease.

[0049] In this embodiment of the application, the coronary heart disease risk assessment result includes the user's risk level of coronary heart disease. This allows the user to understand the coronary heart disease risk assessment result more intuitively, thereby improving the user experience.

[0050] In some possible implementations, the method further includes:

[0051] During the second time period, acquire the user's motion data and / or the user's physiological data in a resting state; wherein, the first data further includes the motion data and / or the physiological data.

[0052] Optionally, the user's motion data and the user's physiological data in the resting state are both data from a non-sleep state.

[0053] In this embodiment of the application, the user's exercise data and / or the user's physiological data in a resting state are acquired during the second time period. In this way, more dimensions of data (such as exercise data and / or physiological data) can be combined to conduct coronary heart disease risk assessment, which can improve the accuracy of coronary heart disease risk assessment and thus enhance the user experience.

[0054] In a second aspect, an apparatus for assessing the risk of coronary heart disease is provided, comprising: a module or unit for performing a method as described in the first aspect or any possible implementation thereof.

[0055] Thirdly, an apparatus for assessing the risk of coronary heart disease is provided, comprising: a processor and a memory, the memory for storing a computer program (also referred to as code or instructions), the computer program being executed by the processor causing the apparatus to perform the method of the first aspect or any possible implementation thereof.

[0056] Fourthly, an electronic device is provided, comprising means for assessing the risk of coronary heart disease as described in the second aspect or any possible implementation thereof, or means for assessing the risk of coronary heart disease as described in the third aspect or any possible implementation thereof.

[0057] Fifthly, a computer-readable storage medium is provided that stores a computer program (also referred to as code or instructions) that, when run on a computer, causes the computer to perform the methods of any of the above aspects or any possible implementations thereof.

[0058] In a sixth aspect, a computer program product is provided, comprising: a computer program (also referred to as code or instructions) that, when run on a computer, causes the computer to perform the method in any of the above aspects or any possible implementations of any of the above aspects.

[0059] In a seventh aspect, a chip is provided, comprising: a processor and a memory, the memory for storing a computer program (also referred to as code or instructions), the processor for calling and running the computer program stored in the memory, such that an apparatus or device on which the chip is mounted performs the method of any of the above aspects or any possible implementation thereof.

[0060] It is understood that the beneficial effects of the second to seventh aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here. Attached Figure Description

[0061] Figure 1 This is a schematic diagram of the hardware architecture of an electronic device provided in an embodiment of this application.

[0062] Figure 2 This is a schematic diagram of the software architecture of an electronic device provided in an embodiment of this application.

[0063] Figure 3 This is a schematic diagram of a scenario for assessing the risk of coronary heart disease provided in an embodiment of this application.

[0064] Figure 4 This is a schematic diagram of the hardware architecture of a wearable device provided in an embodiment of this application.

[0065] Figure 5 This is a schematic diagram of a smartwatch provided in an embodiment of this application.

[0066] Figure 6 This is a schematic diagram of another smartwatch provided in an embodiment of this application.

[0067] Figure 7 This is a schematic flowchart illustrating a method for assessing the risk of coronary heart disease provided in one embodiment of this application.

[0068] Figure 8 This is a schematic diagram of an electrocardiogram measurement method provided in an embodiment of this application.

[0069] Figure 9 This is a schematic diagram showing the characteristics corresponding to the electrocardiogram data and pulse data provided in the embodiments of this application.

[0070] Figure 10 This is a schematic flowchart illustrating a method for filling out a questionnaire, as provided in an embodiment of this application.

[0071] Figure 11 and Figure 12 This is a schematic diagram of the user interface for filling out a questionnaire provided in an embodiment of this application.

[0072] Figure 13 This is a schematic flowchart of a method for assessing coronary heart disease provided in an embodiment of this application.

[0073] Figure 14 This is a schematic flowchart illustrating a method for determining whether a questionnaire has been updated, provided in an embodiment of this application.

[0074] Figure 15 This is a schematic flowchart of a method for statistically measuring the progress of continuous pulse waves, provided in an embodiment of this application.

[0075] Figures 16 to 20 This is a schematic diagram of the reminder interface provided in the embodiments of this application.

[0076] Figure 21 This is a schematic diagram of a reminder process provided in an embodiment of this application, whereby a user wears the watch normally until the wearing goal is achieved.

[0077] Figure 22 This is a schematic diagram of a prompt process provided in an embodiment of this application, indicating that the user's wearing time is seriously insufficient, resulting in the inability to complete the assessment.

[0078] Figure 23 This is a schematic diagram of a post-exercise electrocardiogram measurement method provided in an embodiment of this application.

[0079] Figure 24 and Figure 25 This is a schematic diagram illustrating the comprehensive features of multiple ECGs provided in the embodiments of this application.

[0080] Figure 26 This is a schematic diagram of a process for analyzing multiple ECG features provided in an embodiment of this application.

[0081] Figure 27 This is a schematic diagram of a continuous pulse wave analysis process provided in an embodiment of this application.

[0082] Figure 28 This is a schematic diagram of a heart rate variability feature analysis process for continuous pulse wave data provided in an embodiment of this application.

[0083] Figure 29 This is a schematic diagram of an evaluation result calculation process provided in an embodiment of this application.

[0084] Figure 30 This is a schematic diagram of a coronary heart disease risk assessment model provided in an embodiment of this application.

[0085] Figures 31 to 36 This is a schematic diagram of the user interface for the coronary heart disease risk assessment results provided in the embodiments of this application.

[0086] Figure 37This is a schematic diagram of an electrocardiogram measurement reminder method provided in an embodiment of this application.

[0087] Figures 38 to 41 This is a schematic diagram illustrating the use of different vibration levels to provide reminders, as provided in the embodiments of this application.

[0088] Figure 42 This is a schematic diagram of a user interface for data reuse provided in an embodiment of this application.

[0089] Figure 43 and Figure 44 This is a schematic diagram of the data reuse process provided in the embodiments of this application.

[0090] Figure 45 This is a schematic diagram of an assessment process for a coronary heart disease risk study provided in an embodiment of this application.

[0091] Figures 46 to 50 This is a schematic diagram of the user interface related to coronary heart disease risk research provided in the embodiments of this application.

[0092] Figure 51 This is a schematic diagram of the user interface for filling out a questionnaire provided in an embodiment of this application.

[0093] Figures 52 to 62 This is a schematic diagram of the user interface related to coronary heart disease risk research provided in the embodiments of this application.

[0094] Figure 63 This is a schematic diagram of an electrocardiogram measurement method provided in an embodiment of this application.

[0095] Figures 64 to 78 This is a schematic diagram of the user interface related to electrocardiogram measurement provided in the embodiments of this application.

[0096] Figures 79 to 105 This is a schematic diagram of the user interface related to coronary heart disease risk assessment provided in the embodiments of this application.

[0097] Figure 106 This is a schematic structural diagram of a device for assessing the risk of coronary heart disease provided in one embodiment of this application.

[0098] Figure 107 This is a schematic structural diagram of an apparatus provided in one embodiment of this application. Detailed Implementation

[0099] The technical solutions provided in the embodiments of this application will be described in detail below with reference to the accompanying drawings.

[0100] In the description of this application, unless otherwise stated, the character " / " indicates that the objects before and after it are in an "or" relationship. For example, A / B can mean A or B. "And / or" in this application is merely a description of the relationship between the related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, and B alone, where A and B can be singular or plural. Furthermore, in the description of this application, unless otherwise stated, "at least one" means one or more, and "more than" means two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of singular or plural items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple. Furthermore, to facilitate a clear description of the technical solutions in the embodiments of this application, the terms "first" and "second" are used in the embodiments of this application to distinguish identical or similar items with substantially the same function and effect. Those skilled in the art will understand that the terms "first" and "second" do not limit the quantity or execution order, and that "first" and "second" are not necessarily different. It should be understood that in this application, descriptions such as "in the case of," "if," "when," and "if..." can be used interchangeably.

[0101] The method provided in this application can be applied to electronic devices such as mobile phones, tablets, wearable devices, in-vehicle devices, augmented reality (AR) and virtual reality (VR) devices, laptops, ultra-mobile personal computers (UMPCs), netbooks, and personal digital assistants (PDAs). This application does not impose any restrictions on the specific type of electronic device.

[0102] For example, Figure 1A schematic diagram of the structure of electronic device 100 is shown. Electronic device 100 may include a processor 110, an external memory interface 120, an internal memory 121, a universal serial bus (USB) interface 130, a charging management module 140, a power management module 141, a battery 142, antenna 1, antenna 2, a mobile communication module 150, a wireless communication module 160, an audio module 170, a speaker 170A, a receiver 170B, a microphone 170C, a headphone jack 170D, a sensor module 180, buttons 190, a motor 191, an indicator 192, a camera 193, a display screen 194, and a subscriber identification module (SIM) card interface 195, etc. The sensor module 180 may include a pressure sensor 180A, a gyroscope sensor 180B, an electrocardiogram (ECG) sensor 180C, a magnetic sensor 180D, an accelerometer 180E, a photoplethysmography (PPG) sensor 180F, a skin conduction sensor 180G, a fingerprint sensor 180H, a temperature sensor 180J, a touch sensor 180K, an ambient light sensor 180L, a bone conduction sensor 180M, etc.

[0103] Among them, the ECG sensor 180C can be used to measure physiological data such as the user's heart rate, the PPG sensor 180F can be used to acquire time-domain and frequency-domain information of the user's heart rate changes, and the skin conductance sensor 180G can be used to detect electrical signals on the user's skin surface.

[0104] In some examples, data detected by the PPG sensor 180F can also be referred to as PPG sensor 180F data. Both can be used to determine one or more physiological data points of the user. For ease of explanation, in the following examples, unless otherwise specified, the terms "data detected by the PPG sensor," "PPG sensor data," "physiological data detected by the PPG sensor," and "physiological data determined based on the PPG sensor data" are not distinguished and are uniformly represented as "physiological data detected by the PPG sensor." Similarly, the terms "data detected by the ECG sensor," "ECG sensor data," "physiological data detected by the ECG sensor," and "physiological data determined based on the ECG sensor data" are not distinguished and are uniformly represented as "physiological data detected by the ECG sensor."

[0105] In some scenarios, the gyroscope sensor 180B, the magnetometer sensor 180D, and the accelerometer sensor 180G can together form a motion sensor, which can be used to determine the user's motion state. For example, the aforementioned motion sensor can also be referred to as an inertial measurement unit (IMU).

[0106] It is understood that the structures illustrated in the embodiments of this application do not constitute a specific limitation on the electronic device 100. In other embodiments of this application, the electronic device 100 may include more or fewer components than illustrated, or combine some components, or split some components, or have different component arrangements. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

[0107] Processor 110 may include one or more processing units, such as: application processor (AP), modem processor, graphics processing unit (GPU), image signal processor (ISP), controller, memory, video codec, digital signal processor (DSP), baseband processor, and / or neural network processing unit (NPU), etc. Different processing units may be independent devices or integrated into one or more processors.

[0108] The controller can be the nerve center and command center of the electronic device 100. The controller can generate operation control signals according to the instruction opcode and timing signals to complete the control of fetching and executing instructions.

[0109] The processor 110 may also include a memory for storing instructions and data. In some embodiments, the memory in the processor 110 is a cache memory. This memory can store instructions or data that the processor 110 has just used or that are used repeatedly. If the processor 110 needs to use the instruction or data again, it can retrieve it directly from the memory. This avoids repeated accesses, reduces the waiting time of the processor 110, and thus improves the efficiency of the system.

[0110] In some embodiments, the processor 110 may include one or more interfaces. Interfaces may include an inter-integrated circuit (I2C) interface, an inter-integrated circuit sound (I2S) interface, a pulse code modulation (PCM) interface, a universal asynchronous receiver / transmitter (UART) interface, a mobile industry processor interface (MIPI), a general-purpose input / output (GPIO) interface, a subscriber identity module (SIM) interface, and / or a universal serial bus (USB) interface, etc.

[0111] USB port 130 is a USB standard compliant interface, specifically a Mini USB port, Micro USB port, USB Type-C port, etc. USB port 130 can be used to connect a charger to charge electronic device 100, and can also be used for data transfer between electronic device 100 and peripheral devices. It can also be used to connect headphones for audio playback. This interface can also be used to connect other electronic devices, such as AR devices.

[0112] It is understood that the interface connection relationships between the modules illustrated in the embodiments of this application are merely illustrative and do not constitute a structural limitation on the electronic device 100. In other embodiments of this application, the electronic device 100 may also employ different interface connection methods or combinations of multiple interface connection methods as described in the above embodiments.

[0113] The charging management module 140 receives charging input from a charger. The charger can be a wireless charger or a wired charger. In some wired charging embodiments, the charging management module 140 receives charging input from the wired charger via the USB interface 130. In some wireless charging embodiments, the charging management module 140 receives wireless charging input via the wireless charging coil of the electronic device 100. While charging the battery 142, the charging management module 140 can also supply power to the electronic device via the power management module 141.

[0114] The power management module 141 connects the battery 142, the charging management module 140, and the processor 110. The power management module 141 receives input from the battery 142 and / or the charging management module 140, providing power to the processor 110, internal memory 121, external memory, display screen 194, camera 193, and wireless communication module 160, etc. The power management module 141 can also monitor parameters such as battery capacity, battery cycle count, and battery health status (leakage current, impedance). In some other embodiments, the power management module 141 may also be located within the processor 110. In other embodiments, the power management module 141 and the charging management module 140 may be located in the same device.

[0115] The wireless communication function of electronic device 100 can be realized through antenna 1, antenna 2, mobile communication module 150, wireless communication module 160, modem processor and baseband processor, etc.

[0116] Antenna 1 and antenna 2 are used to transmit and receive electromagnetic wave signals. Each antenna in electronic device 100 can be used to cover one or more communication frequency bands. Different antennas can also be multiplexed to improve antenna utilization. For example, antenna 1 can be multiplexed as a diversity antenna for a wireless local area network. In some other embodiments, the antennas can be used in conjunction with tuning switches.

[0117] The mobile communication module 150 can provide solutions for wireless communication, including 2G / 3G / 4G / 5G, applied to the electronic device 100. The mobile communication module 150 may include at least one filter, switch, power amplifier, low noise amplifier (LNA), etc.

[0118] The wireless communication module 160 can provide solutions for wireless communication applications on the electronic device 100, including wireless local area networks (WLAN) (such as Wi-Fi), Bluetooth (BT), global navigation satellite system (GNSS), frequency modulation (FM), near field communication (NFC), and infrared (IR). The wireless communication module 160 can be one or more devices integrating at least one communication processing module. The wireless communication module 160 receives electromagnetic waves via antenna 2, performs frequency modulation and filtering of the electromagnetic wave signal, and sends the processed signal to processor 110. The wireless communication module 160 can also receive signals to be transmitted from processor 110, perform frequency modulation and amplification, and convert them into electromagnetic waves for radiation via antenna 2.

[0119] Electronic device 100 implements display functions through a GPU, a display screen 194, and an application processor. The GPU is a microprocessor for image processing, connected to the display screen 194 and the application processor. The GPU is used to perform mathematical and geometric calculations and for graphics rendering. Processor 110 may include one or more GPUs, which execute program instructions to generate or modify display information.

[0120] Display screen 194 is used to display images, videos, etc. Display screen 194 includes a display panel. The display panel may be a liquid crystal display (LCD), an organic light-emitting diode (OLED), an active-matrix organic light-emitting diode (AMOLED), a flexible light-emitting diode (FLED), a miniature LED, a microLED, a quantum dot light-emitting diode (QLED), etc. In some embodiments, electronic device 100 may include one or N displays 194, where N is a positive integer greater than 1.

[0121] Electronic device 100 can perform shooting functions through ISP, camera 193, video codec, GPU, display 194 and application processor.

[0122] The ISP (Image Signal Processor) is used to process data fed back from the camera 193. For example, when taking a picture, the shutter is opened, and light is transmitted through the lens to the camera's photosensitive element. The light signal is converted into an electrical signal, and the camera's photosensitive element transmits the electrical signal to the ISP for processing, transforming it into an image visible to the naked eye. The ISP can also perform algorithmic optimizations on image noise, brightness, etc. The ISP can also optimize parameters such as exposure and color temperature of the shooting scene. In some embodiments, the ISP can be set in the camera 193.

[0123] Camera 193 is used to capture still images or videos. An object is projected onto a photosensitive element by generating an optical image through the lens. The photosensitive element can be a charge-coupled device (CCD) or a complementary metal-oxide-semiconductor (CMOS) phototransistor. The photosensitive element converts the light signal into an electrical signal, which is then passed to an ISP for conversion into a digital image signal. The ISP outputs the digital image signal to a DSP for processing. The DSP converts the digital image signal into image signals in standard RGB, YUV, or other formats. In some embodiments, the electronic device 100 may include one or N cameras 193, where N is a positive integer greater than 1.

[0124] In some scenarios, the camera 193 can also be called an image sensor, which can be used to acquire facial image information of users, etc.

[0125] Digital signal processors (DSPs) are used to process digital signals. Besides digital image signals, they can also process other digital signals. For example, when electronic device 100 selects a frequency, the DSP can perform Fourier transforms on the frequency energy.

[0126] Video codecs are used to compress or decompress digital video. Electronic device 100 may support one or more video codecs. Thus, electronic device 100 can play or record videos in various encoding formats, such as Moving Picture Experts Group (MPEG) 1, MPEG2, MPEG3, MPEG4, etc.

[0127] An NPU (Neural Processing Unit) is a computational processor for neural networks (NNs). By borrowing the structure of biological neural networks, such as the transmission patterns between neurons in the human brain, it can rapidly process input information and continuously learn on its own. NPUs enable intelligent cognitive applications in electronic devices, such as image recognition, facial recognition, speech recognition, and text understanding.

[0128] The external storage interface 120 can be used to connect an external memory card, such as a Micro SD card, to expand the storage capacity of the electronic device 100. The external memory card communicates with the processor 110 through the external storage interface 120 to perform data storage functions. For example, music, video, and other files can be saved on the external memory card.

[0129] Internal memory 121 can be used to store computer executable program code, which includes instructions. Processor 110 executes various functional applications and data processing of electronic device 100 by running the instructions stored in internal memory 121. Internal memory 121 may include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as sound playback, image playback, etc.), etc. The data storage area may store data created during the use of electronic device 100 (such as audio data, phonebook, etc.). Furthermore, internal memory 121 may include high-speed random access memory and may also include non-volatile memory, such as at least one disk storage device, flash memory device, universal flash storage (UFS), etc.

[0130] Electronic device 100 can implement audio functions, such as music playback and recording, through audio module 170, speaker 170A, receiver 170B, microphone 170C, headphone jack 170D, and application processor.

[0131] The audio module 170 is used to convert digital audio information into analog audio signals for output, and also to convert analog audio input into digital audio signals. The audio module 170 can also be used for encoding and decoding audio signals. In some embodiments, the audio module 170 may be located in the processor 110, or some functional modules of the audio module 170 may be located in the processor 110.

[0132] Buttons 190 include a power button, volume buttons, etc. Buttons 190 can be mechanical buttons or touch-sensitive buttons. Electronic device 100 can receive button input and generate key signal inputs related to user settings and function control of electronic device 100.

[0133] The software system of electronic device 100 can adopt a layered architecture, event-driven architecture, microkernel architecture, microservice architecture, or cloud architecture. This application embodiment uses a layered architecture. Taking the system as an example, the software structure of electronic device 100 is illustrated.

[0134] Figure 2This is a software structure block diagram of an electronic device 100 according to an embodiment of this application. The layered architecture divides the software into several layers, each with a clear role and function. Layers communicate with each other through software interfaces. In some embodiments, [the following is omitted as the text is incomplete and requires further context]. The system is divided into four layers, from top to bottom: the application layer, the application framework layer, the Android runtime and system libraries, and the kernel layer. The application layer can include a series of application packages.

[0135] like Figure 2 As shown, the application package may include applications such as camera, gallery, calendar, call, map, navigation, WLAN, Bluetooth, music, video, and SMS.

[0136] The application framework layer provides application programming interfaces (APIs) and a programming framework for applications in the application layer. The application framework layer includes some predefined functions.

[0137] like Figure 2 As shown, the application framework layer may include a window manager, content provider, view system, phone manager, resource manager, notification manager, etc.

[0138] The window manager is used to manage windowed applications. It can retrieve screen size, determine the presence of a status bar, lock the screen, and capture screenshots, among other things.

[0139] Content providers store and retrieve data, making that data accessible to applications. This data may include videos, images, audio, made and received phone calls, browsing history and bookmarks, phone books, etc.

[0140] A view system includes visual controls, such as controls for displaying text and controls for displaying images. View systems can be used to build applications. A display interface can consist of one or more views. For example, a display interface including a text notification icon could include views for displaying text and views for displaying images.

[0141] The phone manager is used to provide communication functions for electronic device 100. For example, it manages call status (including connection and disconnection).

[0142] The file explorer provides applications with various resources, such as localized strings, icons, images, layout files, video files, and more.

[0143] The notification manager allows applications to display notifications in the status bar. These notifications can be used to deliver informational messages and can disappear automatically after a short pause, requiring no user interaction. For example, the notification manager can be used to notify users of completed downloads or message alerts. The notification manager can also display notifications as icons or scrolling text in the top status bar, such as notifications from background applications, or as dialog boxes on the screen. Examples include displaying text messages in the status bar, emitting sounds, vibrating electronic devices, and flashing indicator lights.

[0144] The Android runtime consists of core libraries and a virtual machine. The Android runtime is responsible for scheduling and managing the Android system.

[0145] The core library consists of two parts: one part is the functionalities that need to be called by the Java language, and the other part is the Android core library.

[0146] The application layer and application framework layer run in a virtual machine. The virtual machine executes the Java files of the application layer and application framework layer as binary files. The virtual machine is used to perform functions such as object lifecycle management, stack management, thread management, security and exception management, and garbage collection.

[0147] System libraries can include multiple functional modules. For example: surface manager, media libraries, 3D graphics processing libraries (e.g., OpenGL ES), 2D graphics engines (e.g., SGL), etc.

[0148] The Surface Manager is used to manage the display subsystem and provides the blending of 2D and 3D layers for multiple applications.

[0149] The media library supports playback and recording of various common audio and video formats, as well as still image files. It supports multiple audio and video encoding formats, such as MPEG4, H.264, MP3, AAC, AMR, JPG, and PNG.

[0150] The 3D graphics processing library is used to implement 3D graphics drawing, image rendering, compositing, and layer processing.

[0151] A 2D graphics engine is a graphics engine for 2D drawing.

[0152] The kernel layer is the layer between hardware and software. The kernel layer contains at least the display driver, camera driver, audio driver, and sensor driver.

[0153] It should be understood that the technical solutions in the embodiments of this application can be used for

[0154] Operating systems and other systems.

[0155] Coronary atherosclerotic heart disease (CAD) is a chronic disease caused by atherosclerosis in the coronary arteries. CAD can lead to myocardial infarction and sudden cardiac death, making it a highly dangerous condition. While CAD can be life-threatening, awareness of it is low; therefore, convenient and highly accurate methods for diagnosing or assessing the risk of CAD are of great importance.

[0156] Hospitals typically use three methods to diagnose coronary heart disease: electrocardiogram (ECG), blood parameter tests, and medical imaging examinations. Clinically, these three methods are usually combined to arrive at a final diagnosis.

[0157] (1) Electrocardiogram (ECG) examination:

[0158] Electrocardiogram (ECG) examinations mainly include three forms: 1) resting ECG examination (also known as a single ECG examination), which usually lasts 10 to 60 seconds; 2) Holter monitoring, which involves wearing a Holter monitor (also known as a Holter monitor), which usually lasts for 24 hours; and 3) exercise stress test, which requires the patient to perform load training on exercise equipment such as a treadmill until exhaustion, in order to create a scenario where the myocardium's blood supply demand increases.

[0159] However, all of the above-mentioned electrocardiogram (ECG) examinations have some problems. For example, while resting ECG is relatively convenient, its accuracy in detecting coronary heart disease is limited. Holter monitoring requires continuous wearing of electrodes and an ECG monitor, which is not convenient enough. Exercise stress test requires the user to wear the device and exercise to exhaustion, which poses a risk of inducing acute myocardial infarction to the patient.

[0160] (2) Blood parameter examination

[0161] Blood parameter tests typically focus on whether there is an abnormal increase in the level of troponin in the blood, thereby providing early warning of myocardial infarction. This method is mainly used as a diagnostic basis for subtypes of coronary heart disease or myocardial infarction when symptoms such as acute myocardial infarction are present.

[0162] However, blood parameter tests are invasive procedures with certain risks, and cannot be performed at home.

[0163] (3) Medical imaging examination

[0164] Medical imaging examinations mainly include two diagnostic methods: coronary computed tomography (CT) and coronary angiography. Coronary CT, using contrast agents, makes the coronary arteries clearly visible in CT images. By observing the course and changes in thickness of the coronary arteries in the images, the degree of stenosis can be determined, often revealing the extent of stenosis in certain coronary artery branches. Coronary angiography, on the other hand, is the gold standard for diagnosing coronary heart disease. This method has high accuracy and can determine the location and extent of blockage in coronary artery branches.

[0165] However, both coronary CT and coronary angiography need to be performed in a hospital. Coronary angiography is an invasive procedure and carries certain risks of injury and infection. In addition, both coronary CT and coronary angiography involve radiation, making them unsuitable for home examinations and long-term follow-up.

[0166] In summary, all of the above diagnostic methods require examination in a hospital and cannot be performed at home. Some of these methods are quite complex to perform, and some are invasive examinations that carry certain risks.

[0167] To address one or more of the aforementioned technical problems, this application proposes a method and apparatus for assessing the risk of coronary heart disease, which can improve the accuracy of coronary heart disease risk assessment and thus enhance the user experience.

[0168] The method for assessing the risk of coronary heart disease provided in this application embodiment can be applied to various wearable devices, such as smartwatches, smart bracelets, smart headphones, smart jewelry (such as smart rings), smart chest patches, smart glasses, smart gloves, smart clothing, smart shoes, etc.; it can also be applied to various portable devices, such as mobile phones, tablets, etc.; or it can also be applied to a device group or device pair consisting of the aforementioned portable devices and wearable devices, which includes multiple devices. In other words, the relevant steps of the method for assessing the risk of coronary heart disease in the following examples can be performed by the aforementioned wearable devices or portable devices alone, or by the wearable devices and portable devices together.

[0169] For example, when an electronic device has all the conditions for measurement and result presentation, the method for assessing the risk of coronary heart disease in the embodiments of this application can be implemented by an electronic device. When the measurement conditions are constituted by multiple devices, multiple electronic devices can participate in the method for assessing the risk of coronary heart disease in the embodiments of this application.

[0170] like Figure 3As shown, the evaluation process can involve multiple devices, including electronic device 1, electronic device 2, electronic device 3, ..., electronic device n (where n is a positive integer), and a cloud device. Multiple electronic devices can collect the user's physiological data, and the cloud device can receive and merge the physiological data collected by these electronic devices, and perform comprehensive analysis based on this physiological data to obtain the final evaluation result (such as a coronary heart disease risk assessment result). It can be seen that the method for assessing coronary heart disease risk in this embodiment can also be executed in the cloud.

[0171] For ease of understanding, the following embodiments will primarily use smartwatches (also referred to as watches) as wearable devices and mobile phones as portable devices for illustrative purposes.

[0172] Figure 4 This is a schematic diagram of the hardware architecture of a wearable device provided in an embodiment of this application. Figure 4 As shown, wearable devices may include an electrocardiogram (ECG) sensing module, a pulse wave sensing module, a motion sensing module, an image sensing module, a power module, a storage module, a communication module, a display module, and a processor, etc.

[0173] Figure 5 This is a schematic diagram of a smartwatch provided in an embodiment of this application. For example... Figure 5 As shown, the smartwatch includes an electrocardiogram (ECG) sensing module and a pulse wave sensing module. The ECG sensing module may include ECG sensing module electrode 1, ECG sensing module electrode 2, and ECG sensing module electrode 3. It should be understood that the ECG sensing module may also include more or fewer ECG sensing module electrodes, and this is not limited in the embodiments of this application.

[0174] like Figure 5 As shown, the ECG sensor module electrode 1, ECG sensor module electrode 2, and pulse wave sensor module can be located at the bottom of the smartwatch, such as... Figure 6 As shown, the electrocardiogram sensing module electrode 3 can be located on the side of the smartwatch.

[0175] It should be noted that, Figure 5 and Figure 6 The positions of the various modules and / or electrodes are merely examples and not limitations; for example, in Figure 6 In this embodiment, the electrocardiogram (ECG) sensor module electrode 3 is located at the 3 o'clock position on the front of the smartwatch. The ECG sensor module electrode 3 can also be located at the 4 o'clock or 9 o'clock position on the front of the smartwatch, etc., and this embodiment is not limited to this.

[0176] The following is combined Figure 7 The methods for assessing the risk of coronary heart disease in the embodiments of this application are illustrated in detail.

[0177] Figure 7 This is a schematic flowchart illustrating a method for assessing the risk of coronary heart disease according to one embodiment of this application. This method can be applied to wearable devices, portable devices, and cloud-based devices. Figure 7 The method 700 shown may include steps S710, S720 and S730, as detailed below:

[0178] S710 acquires the first electrocardiogram data within the first time period.

[0179] The first electrocardiogram (ECG) data can be static ECG data. For example, the measurement process of the first ECG data can last from 10 to 60 seconds.

[0180] Based on the above Figure 5 and Figure 6 Taking the ECG sensing module shown as an example, as Figure 8 As shown, if the user wears the smartwatch on their left wrist, they can use their right fingers to press the ECG sensor module electrode 3 (located on the side of the watch) to perform an ECG measurement (also known as ECG measurement). (The ECG sensor module electrode 1 and ECG sensor module electrode 2 at the bottom of the watch are in contact with the user's wrist, so there is no need to press them.)

[0181] In some embodiments, the first time period may refer to the measurement period of the first electrocardiogram data.

[0182] In some embodiments, the first electrocardiogram (ECG) data can be analyzed and processed to obtain ECG arrhythmia characteristics and waveform characteristics associated with coronary heart disease. For example... Figure 9 As shown, ECG arrhythmia features can be used to assess sinus rhythm, atrial fibrillation, premature beats, etc., while waveform features associated with coronary heart disease can be used to assess ST segment elevation, ST segment depression, T wave inversion, and decreased high-frequency QRS components, etc.

[0183] For example, waveform analysis can be performed on the first electrocardiogram (ECG) data to obtain its waveform characteristics. Furthermore, a fifth piece of information can be output to the watch or mobile phone interface to indicate the waveform characteristics of the first ECG data.

[0184] Optionally, the waveform characteristics of the first electrocardiogram (ECG) data can also be displayed in the coronary artery disease risk assessment results. For example, the coronary artery disease risk assessment results obtained in subsequent step S730 may include the waveform characteristics of the first ECG data.

[0185] In some embodiments, the first pulse wave data can also be acquired within a first time period. For example, in step S710 above, the first electrocardiogram data and the first pulse wave data can be acquired within a first time period. The first pulse wave data can be measured in a short period of time; for example, the measurement process of the first pulse wave data can last from 10 to 60 seconds.

[0186] Accordingly, the first data in the subsequent step S730 may also include the first pulse wave data.

[0187] In some embodiments, the first pulse wave data can be analyzed and processed to obtain heart rate variability (HRV) characteristics, PPG waveform characteristics, and diurnal heart rate variability differences. The heart rate variability characteristics can refer to the temporal differences between consecutive heartbeat intervals (commonly referred to as RR intervals or NN intervals). Figure 9 As shown, heart rate variability characteristics and PPG waveform characteristics can be used to assess the standard deviation of all normal sinus intervals (NN) (SDNN), and diurnal heart rate variability characteristics can be used to assess SDNN, etc.

[0188] In some embodiments, users may also fill out a questionnaire to collect basic user information.

[0189] For example, prior to step S710 above, second data input by the user can be obtained, which can be used to assess the user's health status.

[0190] The second data may include one or more of the following information:

[0191] Do you have a history of coronary heart disease, cardiovascular or cerebrovascular disease, high blood pressure, high cholesterol, high blood sugar, high uric acid, chest tightness, or chest pain?

[0192] Accordingly, the first data in the subsequent step S730 may also include the second data.

[0193] In some embodiments, users may be required to complete a questionnaire during their initial coronary artery disease assessment. The electronic device may store this questionnaire information. This step may be optional for subsequent assessments.

[0194] like Figure 10 As shown, when filling out the questionnaire, you can fill in whether you have a family history of coronary heart disease, whether you have high blood pressure, and whether you have symptoms such as chest pain or chest tightness.

[0195] For example, when a user fills out a questionnaire via a watch, they can... Figure 11 The screens shown require you to fill in information such as whether you have a family history of coronary heart disease, whether you have high blood pressure, and whether you have chest tightness or chest pain.

[0196] For example, when users fill out a questionnaire via their mobile phones, they can... Figure 12 The interface shown asks you to fill in information such as whether you have a family history of coronary heart disease, whether you have high blood pressure, and whether you have chest tightness or chest pain.

[0197] Because users' health status may change over time, questionnaires need to be updated as necessary, such as monthly or semi-annually. The update method is to remind users to fill out the questionnaire again via electronic devices to overwrite the previous questionnaire information.

[0198] like Figure 13 As shown, after starting the coronary heart disease assessment, it can be determined whether the questionnaire needs to be updated. If an update is needed, the above information can be displayed on the watch or mobile phone screen. Figure 11 or Figure 12 The interface shown is for users to fill out the questionnaire; if no update is needed, the remaining evaluation steps can be completed.

[0199] In some embodiments, the need to update a questionnaire can be determined by combining historical records (such as previous coronary heart disease risk assessment results) and / or historical questionnaires (such as information filled in by the user in previous questionnaires and / or the date of completion of previous questionnaires).

[0200] The process for determining whether a questionnaire needs updating can be as follows: Figure 14 As shown. For example, it can determine whether the historical record (such as the previous assessment result) is high-risk. If it is high-risk, it can determine whether the questionnaire has expired for more than one month (e.g., more than one month since the last questionnaire was filled out). If it has expired for more than one month, it returns: Yes; if it has not expired for more than one month, it returns: No.

[0201] If it is not considered high-risk, then determine if the questionnaire has expired for more than 3 months (e.g., more than 3 months since the last questionnaire was completed). If it has expired for more than 3 months, then return: Yes. If it has not expired for more than 3 months, then determine if there were symptoms such as chest pain or chest tightness in the last questionnaire.

[0202] If the previous questionnaire did not contain symptoms such as chest pain or chest tightness, return: No; if the previous questionnaire contained symptoms such as chest pain or chest tightness, determine if the questionnaire has expired for 1 month. If it has expired for 1 month, return: Yes; if it has not expired for 1 month, return: No.

[0203] exist Figure 14 In the process shown, "Return: Yes" can be interpreted as: the questionnaire needs to be updated; "Return: No" can be interpreted as: the questionnaire does not need to be updated.

[0204] S720 acquires second electrocardiogram data and / or second pulse wave data during the second time period.

[0205] The second electrocardiogram (ECG) data can be Holter monitoring data. Users can continuously wear a Holter monitor to continuously measure ECG data during the second time period; for example, the measurement process can last for 24, 48, or 72 hours. The Holter monitor can be a smart chest patch (or smart patch) capable of Holter monitoring, or it can be a watch or other device capable of Holter monitoring.

[0206] The second pulse wave data can be continuous pulse wave data. For example, the second pulse wave data can be measured over a relatively long period of time, such as 24 hours, 48 ​​hours, or 72 hours.

[0207] In some embodiments, the duration of the second time period may be longer than the duration of the first time period. Optionally, the second time period may refer to the measurement period of the second electrocardiogram data and / or the second pulse wave data. That is, the measurement duration of the second electrocardiogram data and / or the second pulse wave data may be much longer than the measurement duration of the first electrocardiogram data and / or the first pulse wave data.

[0208] In some embodiments, the following types of reminders may be included in the coronary artery disease risk assessment process:

[0209] (1) Daytime progress reminder (e.g., non-sleep progress reminder): Summarize the measurement or wearing progress during the day and remind the user to wear it at night;

[0210] (2) Morning sleep reminder (e.g., sleep progress reminder): Summarize the measurement progress or wearing progress during the day and night of yesterday;

[0211] (3) Risk warning cannot be achieved: If the coronary heart disease assessment cannot be completed, it is recommended that the user start the next round of assessment;

[0212] (4) Evaluation result notification: Inform users of the evaluation results;

[0213] (5) ECG measurement reminder: Remind users to perform ECG measurements to improve assessment accuracy.

[0214] The various reminder types will be described in detail in subsequent embodiments.

[0215] In some embodiments, measurement progress reminders can be provided during the measurement of second electrocardiogram data and / or second pulse wave data. For example, the user can be advised to perform three consecutive days of pulse wave measurements, and the measurement process can be presented linearly according to the measurement progress, making the measurement process predictable. During the measurement process, the user is reminded of the measurement progress daily based on the real-time calculated measurement progress and the estimated number of days remaining, preventing the user from forgetting the measurement process.

[0216] For example, third information can be output, which can be used to indicate the progress of coronary artery disease risk assessment. This third information can be determined based on the measurement progress of second electrocardiogram data and / or second pulse wave data.

[0217] In some embodiments, the second electrocardiogram (ECG) data may include ECG data of the user during sleep and ECG data of the user during non-sleep. For example, a user may wear a smart chest patch during sleep to measure ECG data during sleep; a user may also wear a smart chest patch during non-sleep to measure ECG data during non-sleep.

[0218] In some embodiments, the second pulse wave data may include pulse wave data of the user during sleep and pulse wave data of the user during non-sleep.

[0219] Figure 15 This describes the process for tracking the progress of continuous pulse wave measurements. For example... Figure 15 As shown, we can first determine whether the currently collected data is from a sleep state. If the data is from a sleep state, we accumulate the number of signals that meet the signal quality requirements during sleep (i.e., increase the number of signals that meet the signal quality requirements during sleep), and calculate the percentage of sleep state completion based on the required number of signals. For example, assuming that a coronary heart disease risk assessment needs to last about 3 days, and the required number of signals during sleep each day is 7*6 (e.g., if the user is required to measure for 7 hours each day during sleep, measuring one signal every 10 minutes, that is, 6 signals per hour), then a total of 3*7*6 signals are needed for 3 days of continuous measurement. Thus, based on the accumulated number of signals that meet the signal quality requirements during sleep, the percentage of sleep state completion can be obtained.

[0220] If the currently collected data is not from a sleep state, the number of signals meeting the signal quality requirements in the non-sleep state is accumulated (i.e., the number of signals meeting the signal quality requirements in the non-sleep state is increased), and the percentage of completion in the non-sleep state is calculated based on the required number of signals in the non-sleep state. For example, assuming that the coronary heart disease risk assessment needs to last for about 3 days, and the required number of signals in the non-sleep state each day is 10*6 (if the user is required to measure for 10 hours a day in the non-sleep state, measuring one signal every 10 minutes, that is, 6 signals per hour), then a total of 3*10*6 signals are needed for continuous measurement for 3 days. Thus, based on the current accumulated number of signals meeting the signal quality requirements in the non-sleep state, the percentage of completion in the non-sleep state can be obtained.

[0221] At this point, based on the percentage of completion during sleep and the percentage of completion during non-sleep, the percentage of the overall assessment process can be calculated, and the estimated remaining days can be calculated; finally, the user is reminded to measure their progress.

[0222] For example, it can be done through Figure 16 The watch interface in the device provides reminders to the user. Figure 16 The image shows the real-time measurement progress display interface, which displays the real-time measurement progress percentage, the estimated remaining days, and a progress bar to indicate the real-time measurement progress.

[0223] For example, it can be done through Figure 17 The watch interface in the device provides reminders to the user. Figure 17 The image shown is a pop-up window displaying the measurement progress reminder. This window can display the estimated remaining measurement days and remind the user whether previous wearing guidelines have been met. For example, it can... Figure 17 The upper left section shows, "Insufficient nighttime wearing time; this round of evaluation is expected to take another 2.8 days. Please continue wearing it at night."; Alternatively, as shown... Figure 17 As shown in the upper right corner, it displays "Insufficient valid data detected in your past 2 days; we suggest you start a new round of evaluation"; or you can... Figure 17 As shown in the lower left section, it displays "The assessment is progressing well, and it is estimated that this round of assessment will still take 2.1 days to complete. Please continue to wear it."; or as shown in the image below. Figure 17 As shown in the lower right part, it displays "Valid data has been obtained. One more ECG measurement is needed to complete the evaluation."

[0224] For example, it can be done through Figure 18 The phone's interface provides reminders to the user. Figure 18 The interface shown can display the real-time measurement progress percentage, estimated remaining days, and electrocardiogram measurement results. It can also remind the user to wear the watch both day and night. Figure 18As shown, it can display "2 days remaining", the duration of this assessment, i.e. "7 / 5 10:20–7 / 8 10:20", the user's average heart rate of 78 beats per minute, i.e. "average heart rate 78 beats / minute", and the user may have sinus rhythm, i.e. "sinus rhythm".

[0225] For wearable devices, such as smartwatches, smart rings, smart earphones, or smart chest patches, in order to improve the effectiveness of dynamic electrocardiogram data and / or continuous pulse wave signals obtained by users during the coronary heart disease assessment cycle, users are encouraged to wear them both day and night, and day and night wearing progress reminder logic should be designed.

[0226] In some embodiments, reminders can be provided based on the time the user initiates the assessment, the user's non-sleep state, and the user's sleep state, including sleep progress reminders (such as the morning wake-up reminder among the various reminder types described in the foregoing embodiments) and non-sleep progress reminders (such as the daytime progress reminder among the various reminder types described in the foregoing embodiments). Specifically, sleep progress reminders are used to inform the user of their wearing status, assessment progress, and / or remaining wearing time while they are asleep, while non-sleep progress reminders are used to inform the user of their wearing status, assessment progress, and / or remaining wearing time while they are not asleep.

[0227] Sleep progress reminders can occur at a specific time after the user wakes up. This specific time can be determined by the electronic device to indicate that the user has just woken up or at a certain moment after waking up (e.g., a watch or mobile phone can determine this specific time based on the user's average sleep time over the past few days). The reminder content includes data such as the user's sleep performance last night, the current overall progress percentage, and the estimated remaining wearing time.

[0228] For example, third information can be output the moment after the user wakes up from sleep.

[0229] The third piece of information can also be used for one or more of the following: indicating whether the user has achieved the required standard during sleep, indicating the current overall assessment progress percentage, and indicating the estimated remaining wearing time.

[0230] The "first moment" here could be any point after the user wakes up from sleep, set according to the time when it's convenient for the user to view notifications. For example, it could be 1 minute after the user wakes up, or the first consecutive period of stillness after the user wakes up (e.g., after the user has been still for 5 minutes). The stillness can be determined using the accelerometer (ACC) sensor in the watch or phone.

[0231] An example of a sleep progress reminder could be as follows: Figure 19 As shown. For example, as Figure 19As shown, it can display "Evaluation progress 20%" and "The wearing time last night reached the target, but the effective data during the day is insufficient. Please continue to wear it. It is estimated that this round of evaluation will still take 2.6 days to complete."

[0232] Non-sleep progress reminders can occur at a specific time before the user falls asleep. This specific time can be determined by the electronic device to indicate that the user is ready to sleep, or at a certain moment before falling asleep (e.g., a watch or phone can determine this specific time based on the user's average sleep time over the past few days). The reminders include information such as daytime wear compliance, the current overall progress percentage, and the estimated remaining wear time. Non-sleep progress reminders can also include encouragement and reminders for the user to wear the device while sleeping that day.

[0233] For example, a third message could be output at the second moment before the user falls asleep.

[0234] The third information may also be used for one or more of the following: instructing the user whether the wear is up to standard during non-sleep periods, indicating the estimated remaining wear time, and reminding the user to wear the wearable device during sleep.

[0235] The second "time" here can be a specific moment before falling asleep. This time can be set according to the user's convenient time to view notifications, such as one hour before the user's average sleep time over the past few days. If there is no available record of the user's sleep time over the past few days, a default time can be used, such as 8:00 PM or 10:00 PM daily.

[0236] An example of a non-sleep progress reminder could be as follows: Figure 20 As shown. For example, as Figure 20 As shown, it can display "Evaluation progress 30%" and "Great, the daytime wearing time has been met. It is estimated that this round of evaluation will still take 2.0 days to complete. Please continue to wear it at night."

[0237] The coronary heart disease assessment cycle includes several sleep progress reminders and non-sleep progress reminders until the user's progress reaches the predetermined target. Occasionally, there may be insufficient progress during the assessment cycle; these will be addressed through sleep and non-sleep prompts on the interface, without affecting the overall assessment progress.

[0238] Figure 21 An example of a reminder process for users to wear the watch normally until the wearing goal is achieved, such as... Figure 21 As shown, after a user begins the assessment, they will receive progress reminders from the watch every day after waking up and before falling asleep, until the assessment is completed on the 4th day, at which point the assessment results will be output to the user.

[0239] If a user's progress in wearing the device is significantly insufficient during the evaluation period, and it is estimated that the user will not be able to achieve the wearing goal, the system can suggest that the user restart a new round of evaluation.

[0240] Optionally, if the actual wearing progress is less than a certain threshold, or if the actual data obtained that meets the requirements is less than a certain threshold, it can be determined that the user cannot achieve the wearing goal or cannot complete the coronary heart disease assessment.

[0241] For example, if a coronary heart disease risk assessment has been conducted for 2 days, but the actual amount of valid data (i.e., data that meets quality requirements) obtained so far is less than 50% of the total data required in these 2 days, it can be considered that the user's progress in wearing the device during the assessment cycle is seriously insufficient. In this case, it can be suggested that the user restart a new round of assessment.

[0242] In some embodiments, if it is anticipated that a user will be unable to complete a coronary heart disease risk assessment, a fourth piece of information may be output, which may be used to suggest that the user undergo a coronary heart disease risk assessment again.

[0243] In this embodiment of the application, the fourth information is used to suggest that the user re-evaluate the risk of coronary heart disease. The fourth information is output when it is estimated that the user is unable to complete the risk assessment of coronary heart disease, so that the user can restart a new round of assessment in a timely manner, thereby helping to improve the efficiency of the risk assessment of coronary heart disease.

[0244] Figure 22 This is an example of a notification process that indicates the assessment cannot be completed due to insufficient user wear time. Figure 22 As shown, if the system detects that the user's valid data from the past two days is severely insufficient on the third day, the user will be reminded that the assessment cannot be completed and advised to start a new round of assessment.

[0245] In some embodiments, during the second time period (i.e., during the acquisition of the second electrocardiogram data and / or the second pulse wave data), the user may be reminded to perform a post-exercise electrocardiogram measurement (such as the risk reminder for failure to achieve the various reminder types described in the foregoing embodiments).

[0246] During the acquisition of second electrocardiogram (ECG) data and / or second pulse wave data, after a motion sensor (such as an accelerometer) detects that the user has engaged in strenuous exercise, the user can be prompted to perform a post-exercise electrocardiography (ECG) measurement. This helps to identify characteristics of coronary artery disease (such as ST-segment elevation, T-wave inversion or alternation, and decreased high-frequency QRS components), thus contributing to the accuracy of the final diagnosis. In subsequent evaluation of multiple ECGs, if post-exercise measurements are included, it is considered to have the same effect as the exercise stress ECG method used in medical diagnosis. That is, if ST-segment elevation, T-wave inversion or alternation, or decreased high-frequency QRS components are observed in the post-exercise ECG, these characteristics are marked as key inputs for the end-user's coronary artery disease risk.

[0247] For example, if the system detects that the user is exercising during the second time period, it can output first information, which can be used to remind the user to perform an electrocardiogram (ECG) measurement after completing the exercise (such as the ECG measurement reminder among the various reminder types described in the foregoing embodiments).

[0248] Furthermore, third-party electrocardiogram (ECG) data can be obtained after the user completes the exercise.

[0249] The third electrocardiogram (ECG) data can be static ECG data. For example, the third ECG data can be static ECG data obtained through a single ECG measurement during the acquisition of the second ECG data and / or the second pulse wave data.

[0250] Accordingly, the first data in the subsequent step S730 may also include third electrocardiogram data.

[0251] like Figure 23 As shown, if the system detects that the user is exercising during the second time period, it can remind the user to perform an electrocardiogram (ECG) measurement after the user finishes exercising, such as outputting "One minute after exercise is one of the best times to detect coronary heart disease. It is recommended to perform an ECG measurement." After the user clicks the "ECG Measurement" button, it can remind the user to "Touch the side electrode lightly and hold." Finally, the system can obtain the coronary heart disease risk assessment results, such as indicating that the user has "sinus rhythm" and "average heart rate of 80 beats / minute".

[0252] In some embodiments, during the second time period (i.e., during the acquisition of second electrocardiogram data and / or second pulse wave data), the user may also be reminded to perform an electrocardiogram measurement at a preset time (such as the electrocardiogram measurement reminder among the various reminder types described in the foregoing embodiments).

[0253] For example, a second message can be output at a preset time within the second time period, which can be used to remind the user to perform an electrocardiogram (ECG) measurement.

[0254] Furthermore, fourth electrocardiogram data can be obtained during the second time period.

[0255] The fourth electrocardiogram (ECG) data can be static ECG data. For example, the fourth ECG data can be static ECG data obtained through a single ECG measurement during the acquisition of the second ECG data and / or the second pulse wave data.

[0256] The preset time here can be set according to the user's needs. For example, the user can be reminded to take an electrocardiogram at 20:00 every day.

[0257] Accordingly, the first data in the subsequent step S730 may also include the fourth electrocardiogram data.

[0258] In some embodiments, fifth electrocardiogram data and / or third pulse wave data may be acquired during a third time period.

[0259] The fifth electrocardiogram (ECG) data can be static ECG data. For example, the fifth ECG data can be static ECG data obtained through a single ECG measurement during the acquisition of the second ECG data and / or the second pulse wave data.

[0260] The third pulse wave data can be obtained in a short period of time (i.e., non-continuous pulse wave data), such as a measurement process that can last 10 to 60 seconds. For example, the third pulse wave data can be obtained by measuring a pulse wave for 10 to 60 seconds during the acquisition of the second electrocardiogram data and / or the second pulse wave data.

[0261] The second time period can be located after the first time period, and the third time period can be located after the second time period or within the second time period.

[0262] Accordingly, the first data in the subsequent step S730 may also include third electrocardiogram data and / or third pulse wave data.

[0263] In some embodiments, user motion data and / or user physiological data in a resting state may also be acquired during the second time period.

[0264] For example, user activity data and / or physiological data at rest can be acquired during a second time period. Activity data can include low-intensity activity data (such as walking) and high-intensity activity data (such as swimming, running).

[0265] Accordingly, the first data in the subsequent step S730 may also include motion data and / or physiological data.

[0266] In the embodiments of this application, the non-sleep state may include the resting state and the exercise state, and the exercise state may include the low-intensity activity state and the high-intensity activity state.

[0267] S730, based on the first data, determines the risk assessment results for coronary heart disease.

[0268] The first data may include: first electrocardiogram data, second electrocardiogram data and / or second pulse wave data;

[0269] In some embodiments, feature analysis and waveform analysis can be performed on each electrocardiogram data obtained in steps S710 and S720.

[0270] In patients with coronary artery disease, increased cardiac load and limited blood supply can lead to specific changes in cardiac electrical activity, such as ST segment elevation, T wave inversion, and decreased high-frequency QRS components. Normal individuals can withstand these increased cardiac loads. This application uses heart rate as a standard to measure cardiac load, calculating the trends of electrocardiogram characteristics at different heart rates, and using the magnitude of these trends to measure the relative risk of coronary artery disease.

[0271] For example, such as Figure 24 and Figure 25 As shown, in a coordinate system with heart rate on the horizontal axis and specific characteristic values ​​(such as ST segment amplitude, T wave amplitude, high-frequency QRS component amplitude, etc.) on the vertical axis, each ECG (one ECG can be understood as one ECG data point, such as the first ECG data in the aforementioned embodiment being one ECG, and the second ECG data also being one ECG) can be plotted as a point in this coordinate system (e.g., one ECG corresponds to one point). Multiple ECGs (≥2) can be plotted as multiple points in this coordinate system. One ECG can be understood as one ECG data point (e.g., the first ECG data in the aforementioned embodiment can be one ECG, and the second ECG data can also be one ECG), and one ECG can correspond to one point. For example, for one ECG, the average value of its vertical axis (i.e., average characteristic value) and the average value of its horizontal axis (i.e., average heart rate) can be calculated separately. In this way, one ECG can be transformed into one point (the vertical axis of this point is the calculated average value of the vertical axis, and the horizontal axis of this point is the calculated average value of the horizontal axis).

[0272] After sorting the obtained points according to their average heart rate, connecting these sorted points sequentially yields a curve showing the characteristic value changing with heart rate. The area under the curve (AUC) can then be calculated and used as a comprehensive feature of multiple ECG data. This comprehensive feature represents the stability of the user's ECG characteristics under varying cardiac load conditions.

[0273] For example, some thresholds can be set. When the area under the curve (i.e., the combined characteristics of multiple ECGs) exceeds a certain threshold, the user (corresponding to the combined characteristics) can be considered to have a risk of coronary heart disease. When the area under the curve (i.e., the combined characteristics of multiple ECGs) does not exceed a certain threshold, the user (corresponding to the combined characteristics) can be considered not to have a risk of coronary heart disease.

[0274] Figure 24 and Figure 25 Taking three ECGs (ECG1, ECG2, and ECG3) as an example, such as... Figure 24 The figure shown is a characteristic curve for users with coronary heart disease, such as Figure 25 The figure shows the characteristic curves for users without coronary heart disease.

[0275] Figure 26 This is an example of a process for analyzing multiple ECG features. For example... Figure 26 As shown, it can acquire the characteristic values ​​of each ECG (such as ST segment amplitude, T wave amplitude, high-frequency QRS component amplitude, etc.); calculate and store the average characteristic value of each ECG (i.e., the average value of the vertical axis of each ECG); and statistically analyze the average heart rate of each ECG (i.e., the average value of the horizontal axis of each ECG) and the corresponding exercise state for each ECG. The exercise state here can include post-exercise and post-exercise states, i.e., determining whether each ECG is a post-exercise ECG or a post-exercise ECG.

[0276] The system determines whether a post-exercise ECG measurement was taken. If so, it checks for abnormalities (such as ST-segment elevation). If no post-exercise ECG measurement was taken, all ECGs are sorted according to their average heart rate. For example, if there are a total of 5 ECGs, and none of them are post-exercise ECGs, then these 5 ECGs can be sorted according to their average heart rate.

[0277] At this point, by connecting all sorted ECGs (each ECG can correspond to a point) in sequence, a heart rate characteristic curve (i.e., a curve showing how the characteristic value changes with heart rate) can be drawn, the approximate area under the curve can be calculated, and the comprehensive feature, i.e., the area under the curve, can be output.

[0278] Determine whether there are abnormalities in ECG after exercise (such as ST segment elevation). If there are abnormalities in ECG after exercise (such as ST segment elevation), the abnormal features (such as ST segment abnormality after exercise) can be output.

[0279] If the ECG is normal after exercise, then exclude the ECG (i.e., exclude that particular ECG after exercise) and sort the other ECGs according to their average heart rate. For example, suppose there are a total of 5 ECGs, one of which is an ECG after exercise and has no abnormalities. In this case, the ECG after exercise can be excluded, and the other 4 ECGs (excluding the ECG after exercise) can be sorted according to their average heart rate.

[0280] At this point, by connecting the sorted ECGs (excluding the ECGs after exercise, each ECG can correspond to a point) in sequence, a heart rate characteristic curve can be drawn, the approximate area under the curve can be calculated, and the comprehensive feature, i.e., the area under the curve, can be output.

[0281] In some embodiments, feature analysis can be performed on the continuous pulse wave data (such as the second pulse wave data) obtained in step S720 above.

[0282] Optionally, the duration of continuous pulse wave assessment (or continuous pulse wave) can be at least one day, i.e., covering a full day and night.

[0283] Heart rate variability (HRV) in patients with coronary artery disease (CAD) exhibits unique characteristics due to abnormalities in the autonomic nervous system (sympathetic and parasympathetic nervous systems). This includes either excessive sympathetic activity or weakened parasympathetic (vagus nerve) regulation, resulting in lower HRV compared to healthy individuals. Furthermore, HRV is easily influenced by external environmental factors and physiological conditions. Therefore, measuring a user's stable HRV level using continuous pulse wave measurements over multiple days can help improve the accuracy of CAD screening.

[0284] Meanwhile, the human heart rate variability exhibits a diurnal variation pattern, with higher variability during the day and lower variability at night. In normal individuals, the diurnal heart rate variability shows a significant difference, while in patients with coronary heart disease, this difference is not significant. It also serves as an important indicator for multi-day continuous pulse wave assessment.

[0285] To encourage users to wear the watch during both sleep and non-sleep periods, thereby accumulating heart rate variability during sleep and non-sleep, prompts are displayed on the watch interface (such as user experience (UX)) suggesting that users wear it both day and night.

[0286] In some embodiments, signals that meet signal quality requirements can be screened for coronary heart disease risk assessment. Figure 27 This is an example of a continuous pulse wave analysis workflow. For example... Figure 27 As shown, we can first determine whether the signal quality meets the requirements. If it does not, the pulse wave measurement ends. If it does, the signal is filtered.

[0287] After signal filtering, feature points can be extracted and calculated. The feature results can then be stored, at which point the pulse wave measurement is complete.

[0288] In some embodiments, heart rate variability analysis can be performed on the currently acquired continuous pulse wave data. Figure 28 This is an example of a workflow for analyzing the heart rate variability characteristics of continuous pulse wave data. For example... Figure 28 As shown, the current continuous pulse wave features can be obtained, the heart rate interval (RR interval, RRI) can be calculated based on the continuous pulse wave features, and it can be determined whether the RRI (i.e. the RRI of the current continuous pulse wave features) is the sleep state RRI.

[0289] If the RRI is a sleep RRI, then sleep heart rate variability is calculated based on this RRI. Furthermore, 24-hour heart rate variability and the diurnal heart rate variability difference are calculated based on the (calculated) sleep heart rate variability and the (previously calculated) non-sleep heart rate variability. At this point, the continuous pulse wave heart rate variability processing ends. 24-hour heart rate variability can include both non-sleep and sleep heart rate variability, and the diurnal heart rate variability difference can be the difference between non-sleep and sleep heart rate variability.

[0290] If the RRI is not during sleep, then the non-sleep heart rate variability is calculated based on the RRI, and the total daily heart rate variability and the diurnal heart rate variability difference are calculated based on the (calculated) non-sleep heart rate variability and the (previously calculated) sleep heart rate variability.

[0291] Through the above Figure 28 By processing each step, we can obtain the 24-hour heart rate variability and the diurnal heart rate variability differences.

[0292] At this point, the 24-hour heart rate variability and diurnal heart rate variability differences, along with questionnaire features obtained from other embodiments, the average features of each ECG, and the comprehensive features of multiple ECGs (such as the area under the curve), are input into the pre-trained assessment model to calculate the coronary heart disease risk assessment results. The following section combines... Figure 29 and Figure 30 The process will be explained.

[0293] Figure 29 This is an example of the evaluation result calculation process in the embodiments of this application. For example... Figure 29 As shown, it can acquire questionnaire features, average features of each ECG, comprehensive features of multiple ECGs (such as area under the curve), heart rate variability features (such as all-day heart rate variability, sleep heart rate variability, and / or non-sleep heart rate variability), and diurnal heart rate variability differences. In the case of post-exercise ECG, it can also acquire post-exercise ECG features. These features are combined into a vector and input into a pre-trained assessment model (such as a classification model or fitting model) to calculate the coronary heart disease risk assessment results (such as risk assessment index and / or classification results) and display the coronary heart disease risk assessment results (such as risk assessment index and / or classification results).

[0294] Figure 30 This is an example of a coronary artery disease risk assessment model in the embodiments of this application. For example... Figure 30As shown, questionnaire features, average features of each ECG, comprehensive features of multiple ECGs (such as area under the curve), post-exercise ECG features, heart rate variability features (such as all-day heart rate variability, sleep heart rate variability, and / or non-sleep heart rate variability), and diurnal heart rate variability differences can be combined into a feature vector. This feature vector is then input into a pre-trained assessment model (such as a classification model or a fitting model) to calculate and display the coronary heart disease risk assessment results (such as risk assessment index and / or classification results).

[0295] In some embodiments, the results of a coronary heart disease risk assessment may include the user's risk level for coronary heart disease, such as high risk, medium risk, and low risk.

[0296] For example, the results of coronary heart disease risk assessment can include a risk assessment index, which can be a decimal between (0,1), with a larger value indicating a higher risk of coronary heart disease.

[0297] For example, the index can be divided into three parts, corresponding to low, medium and high risk of coronary heart disease, respectively. Alternatively, the assessment model can directly output vector results representing the classification results and present these results on the UX interface of electronic devices.

[0298] Figures 31 to 33 This is a diagram showing the results of coronary heart disease risk level displayed on the watch screen. Figure 31 The interface indicates a low risk level and tells users, "No abnormalities were found in this round of assessment. Please continue to monitor your health." Figure 32 The interface indicates a medium risk level and tells the user, "The risk of developing coronary heart disease is at a moderate level. Please continue to monitor your condition. If you experience any discomfort, please seek medical attention promptly." Figure 33 The interface indicates a high risk and informs the user that "the risk of coronary heart disease is at a high level, which may cause chest pain, chest tightness, myocardial infarction, etc. If you feel unwell, please seek medical attention promptly."

[0299] Figure 34 This is a diagram illustrating how the results of coronary heart disease risk levels are displayed on a mobile phone screen. Figure 34 The mobile phone interface shows that the user's coronary heart disease risk assessment result is low risk, and also instructs the user that "no abnormalities were found in this round of assessment. Please continue to pay attention to your health.", as well as the electrocardiogram measurement results.

[0300] Figure 35 This is a diagram illustrating how coronary heart disease risk level results are displayed on a mobile phone and watch screen. Figure 35The left side of the phone screen shows that the user's coronary heart disease risk assessment result is medium risk, and also indicates to the user, "The risk of developing coronary heart disease is at a moderate level. Please continue to monitor. If you feel unwell, please seek medical attention promptly.", as well as the electrocardiogram measurement results; Figure 35 The watch interface shown on the right indicates that the user's coronary heart disease risk assessment result is medium risk. It also instructs the user to "avoid emotional excitement and seek medical attention promptly if you feel unwell." It also displays ECG measurement results, correlation factor analysis (such as resting heart rate), mean heart rate variability, and mean blood pressure.

[0301] Figure 36 This is a diagram illustrating how the results of coronary heart disease risk levels are displayed on a mobile phone screen. Figure 36 The interface indicates a high risk and informs the user that "the risk of coronary heart disease is at a high level, which may cause chest pain, chest tightness, myocardial infarction, etc. If you feel unwell, please seek medical attention immediately. If the coronary arteries are severely narrowed or completely blocked, it may lead to myocardial infarction (heart attack), which is a life-threatening emergency." It also displays the electrocardiogram (ECG) measurement results.

[0302] In this embodiment, first electrocardiogram (ECG) data is acquired during a first time period, and second ECG data and / or second pulse wave data are acquired during a second time period. The coronary heart disease risk assessment result is determined based on the first ECG data, the second ECG data, and / or the second pulse wave data. Compared with assessment methods based on single measurement data (such as ECG data or pulse wave data), the accuracy of coronary heart disease risk assessment can be improved by using multiple measurement data (such as first ECG data, second ECG data, and / or second pulse wave data), thereby enhancing the user experience.

[0303] Meanwhile, the second time period is longer than the first time period. The second electrocardiogram (ECG) data includes ECG data of the user during sleep and ECG data of the user during non-sleep. In this way, by combining data obtained from short-term measurements (such as the first ECG data) and data obtained from long-term measurements (such as the second ECG data and / or the second pulse wave data), as well as ECG data of the user during sleep and non-sleep, the results of the coronary heart disease risk assessment can be determined, which can further improve the accuracy of the coronary heart disease risk assessment and thus further enhance the user experience.

[0304] Furthermore, the method in this embodiment does not require specialized medical equipment, which can improve the convenience of coronary heart disease risk assessment and thus enhance the user experience.

[0305] In the embodiment of method 700 described above, during the second time period (i.e., during the acquisition of second electrocardiogram data and / or second pulse wave data), the user can also be reminded to perform electrocardiogram measurement at a preset time.

[0306] For example, users can be reminded to take an electrocardiogram at a preset time each day (within the second time period).

[0307] In some embodiments, if a user successfully completes an electrocardiogram measurement, reminders may not be required for a subsequent period of time.

[0308] like Figure 37 As shown, suppose a user needs to continuously measure their pulse wave for 3 days. The watch's interface displays a prompt message at 15:00 on the first day: "ECG measurement is an important standard for assessing coronary heart disease," reminding the user to perform an ECG measurement. However, the user does not perform an ECG measurement at 15:00 on the first day. The watch's interface displays the prompt message "ECG measurement is an important standard for assessing coronary heart disease" again at 15:00 on the second day. After seeing this prompt message, the user successfully completes an ECG measurement. Then, the watch's interface will no longer display the prompt message at 15:00 on the first day.

[0309] If the user does not perform an electrocardiogram (ECG) measurement by 3:00 PM on the second day, the watch interface can continue to display the message "ECG measurement is an important standard for assessing coronary heart disease" at 3:00 PM on the third day.

[0310] Figure 37 The three interfaces on the left can also display "Measure Now" and "Don't Remind Me Again" icons. When a click is detected on the "Measure Now" icon, the ECG measurement will start immediately. When a click is detected on the "Don't Remind Me Again" icon, no more reminders will be sent for a period of time.

[0311] pass Figure 37 As can be seen from the rightmost interface, even if no ECG measurement is performed during the second time period (i.e., the measurement period for the second ECG data and / or the second pulse wave data), the coronary heart disease risk assessment result can still be obtained normally (i.e., the value can be output normally). However, as long as the number of ECG measurements is greater than 1 (i.e., ECG measurement is performed), not only can the coronary heart disease risk assessment result be obtained normally, but the accuracy of the coronary heart disease risk assessment result can also be improved.

[0312] Figure 37 The rightmost interface can also display a "View Details" icon and a "Start a New Round of Assessment" icon. If the watch detects a click on the "View Details" icon, it will display the details corresponding to the current risk type (such as "Low Risk"). If the watch detects a click on the "Start a New Round of Assessment" icon, it can start a new round of assessment.

[0313] In the embodiments shown in method 700 above, various types of reminders can be issued to the user. In some embodiments, different types of reminders can be issued to the user in different ways.

[0314] In some embodiments, different types of alerts can correspond to different vibration levels. For example, a higher vibration level can be used to alert users of assessment results that are at risk of not being achieved or that are high-risk; a lower vibration level can be used to alert users of assessment progress, reminders to measure, low-risk assessment results, and high-risk assessment results.

[0315] like Figure 38 As shown, progress can be indicated by the three vibration levels; for example... Figure 39 As shown, a risk warning can be issued if vibration level 5 fails to achieve its intended effect; for example... Figure 40 As shown, the vibration level can be adjusted to provide measurement alerts; for example... Figure 41 As shown, you can receive result notifications using the three vibration levels.

[0316] In the embodiment of method 700 described above, the coronary heart disease risk assessment can be initiated by a watch or a mobile phone.

[0317] In some embodiments, when a coronary heart disease risk assessment is initiated by a mobile phone, the watch and the mobile phone can maintain a Bluetooth connection, which can help the watch and the mobile phone synchronize their functions.

[0318] In the embodiment of method 700 described above, when a user restarts a new round of evaluation, some data from the previous round can be reused. For example, as... Figure 42 As shown, when a user restarts a new round of evaluation, the phone can display a prompt message to remind the user that some data from the previous round will be reused in this round of evaluation.

[0319] In some embodiments, when reusing data, one or more of the following reuse rules may be followed:

[0320] Only reuse valid data from a certain period of time in the previous round (such as the last day, i.e., 24 hours);

[0321] The maximum amount of data reused shall not exceed a certain percentage (e.g., 50%) of the data from the previous round.

[0322] In some embodiments, when reusing data, one or more of the following non-reuse rules may be followed:

[0323] ECG data is not reused;

[0324] If the previous round of evaluation results was successful, it will not be reused;

[0325] If the interval between two rounds of evaluation is longer than a certain period (such as 7 days), it will not be reused.

[0326] For example, such as Figure 43As shown, assuming the first round of evaluation fails, the user initiates a second round of evaluation after the first round, and the interval between the end time of the first round of evaluation and the start time of the second round of evaluation is less than 7 days. Since the interval between the first and second rounds of evaluation is less than 7 days, the data from the first round of evaluation can be reused in the second round of evaluation.

[0327] When reusing data, you can first look back to the last valid data in the previous round of evaluation (i.e., the first round of evaluation), then determine the valid data within the last 24 hours, and finally reuse the valid data within the last 24 hours.

[0328] For example, such as Figure 44 As shown, assuming the first round of evaluation fails, the user initiates a second round of evaluation after the first round, and the interval between the end time of the first round of evaluation and the start time of the second round of evaluation is greater than 7 days. Because the interval between the first and second rounds of evaluation is greater than 7 days, the data from the first round of evaluation cannot be reused in the second round of evaluation.

[0329] Figure 45 This is a schematic diagram of the assessment process for coronary artery disease risk studies. Figure 45 As shown, the first step is to add the user to the coronary heart disease risk study. For example, when using the coronary heart disease risk study function for the first time, the user needs to fill out an informed consent form and a questionnaire. These steps can be performed on the mobile phone.

[0330] The second step is to demonstrate the assessment tutorial. Optionally, during the demonstration, the user can be guided to take at least one ECG measurement using prompts. As an example, this process can be performed on the mobile phone.

[0331] The third step is to collect valid data within a continuous time period. At least one of the start time, duration, and end time of this time period can be preset or set by the user in the first two steps.

[0332] The fourth step is optional, which means that at least one ECG measurement must be completed within the aforementioned time period.

[0333] Step 5: Present the evaluation results. Optionally, the evaluation results can be presented via mobile phone and / or watch.

[0334] Figure 46 This is a diagram illustrating the location of the coronary heart disease risk research function on a mobile phone. (Example:) Figure 46 As shown, the phone has an "Innovation Research" app installed, which includes a user interface for "cardiovascular" research. For example, this user interface includes research options such as "Hypertension Risk Research," "Coronary Artery Disease Research," "Heart Health Research," "Exercise and Blood Pressure Research," and "Vascular Health Research."

[0335] The content displayed in the "Coronary Heart Disease Research" option varies depending on the stage of the research. Figure 47 and Figure 48 This is an example display of content at different stages of coronary artery disease research.

[0336] Figure 47 (a) shows an example of the content displayed in the coronary heart disease study options before joining the study. It includes a "Join" icon.

[0337] Figure 47 (b) is an example of what is displayed in the coronary heart disease study options when joining the study but before data has been collected.

[0338] Figure 47 (c) represents an example of the content displayed in the Coronary Artery Disease Study option when the patient is enrolled in a coronary artery disease study and is currently undergoing evaluation, but the results have not yet been assessed and there are no historical evaluation records. This can include the start time and / or progress of the current evaluation. The evaluation progress can be displayed as a progress bar and / or as a percentage.

[0339] Figure 47 (d) represents an example of the content displayed in the Coronary Artery Disease Study option when the patient has joined a coronary artery disease study and is currently undergoing evaluation, but the results of this evaluation have not yet been determined, and there are historical evaluation records. This can include the start time and / or progress of the current evaluation, as well as the time and / or results of the previous evaluation.

[0340] Figure 48 This is an example of what the "Coronary Artery Disease Study" option displays when someone joins a coronary artery disease study but is currently in an unassessed state, and has undergone historical assessments. It displays the most recent assessment result. For example, the assessment result is one of four: low risk, medium risk, high risk, or no assessment result, corresponding to... Figure 48 (a), (b), (c), and (d). The time of the most recent assessment can be displayed. Low, medium, and high risk can be represented by different colored graphics; for example, the darker the color, the higher the risk. The indicator icon indicates which color of the graphic represents the risk level of the most recent result.

[0341] If in Figure 47 If the "Join" icon is clicked in (a), the following will be displayed: Figure 49 The interface shown. Figure 49The interface shown grants the user permission to join a coronary heart disease study. This interface displays the user's information and two action icons: "Agree" and "Cancel." For example, if a "Cancel" click is detected, the current interface can be closed and the following message can be displayed: Figure 46 The interface shown below. If a "Agree" icon click is detected, the following will be displayed: Figure 50 .

[0342] Figure 50 The content of the informed consent form is displayed for users to read. Figure 50 The app also displays the option "I have carefully read and agree to the above terms," ​​which, as an example, is unselected by default. Figure 50 The system also displays a "Join Research" icon. When a click is detected on this icon, and "I have carefully read and agree to the above terms" is selected, the following will be displayed: Figure 51 The interface shown.

[0343] Optionally, if a click is detected on the "Join Research" icon, but "I have carefully read and agree to the above terms" is not selected, a prompt message is output to inform the user that the "I have carefully read and agree to the above terms" option has not been selected.

[0344] Figure 51 The system displays the content to be surveyed. As an example, each survey item has multiple options for the user to choose from, allowing the user to select the corresponding option for each survey item based on their health status. Figure 51 The system also displays a "Submit" icon. When a click on the "Submit" icon is detected, and at least one option for each survey item is selected, a notification will be displayed. Figure 52 The content includes information on the "Submit" icon. If a click is detected on the "Submit" icon, but all options for at least one survey item are not selected, a message is displayed indicating that the survey has not been completed. Optionally, the system can further indicate which survey items were not selected, for example, by highlighting these items.

[0345] Figure 52 The system can display available devices that connect to a mobile phone to perform measurements on the user for coronary heart disease research. For example, the wearable device is a watch. Figure 52 It also displays an icon that says "Learn about the risks of coronary heart disease." When a click on the "Learn about the risks of coronary heart disease" icon is detected, information about the health risks associated with coronary heart disease is displayed. Figure 52 The system also displays a "Start Evaluation" icon. When a click is detected on the "Start Evaluation" icon, it displays... Figure 53 The content shown.

[0346] Figure 53 This is a user interface for entering information needed for coronary heart disease research, such as the user's height, weight, gender, and date of birth. Multiple user interfaces can be used for this purpose; if the current interface is not the last one, a "Next" icon is displayed. If a click is detected on the "Next" icon, the next interface for entering user information is displayed.

[0347] If the user interface used for entering user information is the last of multiple user interfaces used for entering user information, then the “Start Evaluation” icon is displayed in that last user interface.

[0348] If the user interface used for entering user information is not the first among multiple user interfaces used for entering user information, a "Previous" icon can also be displayed. If a click operation is detected on the "Previous" icon, the previous user interface used for entering user information will be displayed.

[0349] Optionally, if it is determined that the user is under 18 years old based on the date of birth entered by the user, then as follows: Figure 54 As shown, the output prompt message "This study is only applicable to people aged 18 and above", and the "Next" icon will not display the next interface for entering user information even if it is clicked.

[0350] like Figure 46 The card under the coronary heart disease research report shows the following: Figure 47 If the content of (c) or (d) in the document is selected, and a user click on the card is detected, then the following will be displayed: Figure 55 The content in [the document / article].

[0351] like Figure 55 As shown, the user interface contains four cards: “Coronary Artery Disease Risk Assessment”, “Coronary Artery Disease Risk Assessment Record”, “Available Devices”, and “About Coronary Artery Disease Risk”.

[0352] The "Coronary Artery Disease Risk Assessment" card displays the following: current assessment progress (or assessment task), which, for example, is displayed as a progress bar and / or percentage, such as 38%; remaining assessment time, such as 3 days; assessment prompts, such as "Please wear it during the day and night"; and an option to end the assessment, such as "End this round of assessment". Optionally, if the remaining assessment time is less than 1 day, it is displayed in hours, such as "X hours"; if the remaining assessment time is less than 1 hour, it is displayed in minutes, such as "X minutes".

[0353] The “Coronary Artery Disease Risk Assessment Record” card is used to display historical assessment records. If there are no historical assessment records, the card will not be displayed, or the card will be displayed but will not contain any assessment records.

[0354] If there are historical assessment records, the "Coronary Artery Disease Risk Assessment Record" card will show at least one assessment record. Each assessment record includes the following: risk level; assessment time, such as the assessment end time.

[0355] Taking three historical assessment records as an example, the first historical assessment record includes: low risk, 2025 / 5 / 28 10:22; the second historical assessment record includes: high risk, 2025 / 3 / 08 16:22; low risk, 2024 / 7 / 25 15:12.

[0356] The "Available Devices" card displays the names of wearable devices used to collect data related to coronary artery disease. The "About Coronary Artery Disease Risk" card refers to the relevant information in the aforementioned illustration.

[0357] like Figure 46 The card under the coronary heart disease research report shows the following: Figure 47 If the content of (b) in the diagram is detected, and a click on the card is detected, then the following will be displayed: Figure 56 The interface contains three cards: "Coronary Artery Disease Risk Assessment," "Available Devices," and "About Coronary Artery Disease Risk." The "Coronary Artery Disease Risk Assessment" card displays "No Data Available" and includes a "Start Assessment" icon; the "Available Devices" and "About Coronary Artery Disease Risk" cards can be found in the aforementioned content.

[0358] like Figure 46 The card under the coronary heart disease research report shows the following: Figure 48 If the content of (a) in the image is displayed, and a click on the card is detected, then the following will be displayed: Figure 57 The interface.

[0359] like Figure 57 As shown, the user interface contains four cards: "Coronary Artery Disease Risk Assessment," "Coronary Artery Disease Risk Assessment Record," "Available Devices," and "About Coronary Artery Disease Risk." The "Coronary Artery Disease Risk Assessment" card displays the most recent assessment record and an icon to "Start a New Assessment." The content of the "Coronary Artery Disease Risk Assessment Record," "Available Devices," and "About Coronary Artery Disease Risk" cards is the same as the aforementioned related content.

[0360] When in such Figure 56 If a click is detected on the "Start Evaluation" icon, the following will be displayed: Figure 58 The user interface shown. Figure 58 The user interface shown is used to present the evaluation tutorial.

[0361] As an example, the assessment tutorial is used to show the steps included in a single assessment. An example of the steps included in a single assessment is as follows: Step 1: Measure ECG; Step 2: This assessment is expected to take approximately 3 days, with a maximum of 4 days; the watch needs to be worn both day and night. Furthermore, Figure 58 The interface shown also includes a "Next" icon.

[0362] when Figure 58 A click was detected on the "Next" icon in the middle, or Figure 57 The "Start a new round of evaluation" option checks whether the phone successfully pulls up the watch (i.e., whether the phone successfully triggers the watch to start a new round of evaluation).

[0363] If the phone fails to successfully pull up the watch, it will display the following: Figure 59 The user interface shown is an example. Figure 59 The following message is displayed: "Unable to measure. Please check if other measurements are being performed on the watch. If so, please close the other measurements and restart the evaluation." Figure 59 The system also displays a "Reassess" icon. If a click is detected on the "Reassess" icon, the system will re-evaluate whether the watch has been pulled up on the phone.

[0364] If the phone successfully pulls up the watch, the watch will display as follows: Figure 60 The user interface shown; optionally, the phone displays as shown Figure 61 The user interface shown.

[0365] Figure 61 The interface shown displays measurement guidance. As an example, it outputs the reminder message "Please proceed to the watch for ECG measurement," along with an image of the correct measurement posture and / or a description of the correct posture. For example, the description of the measurement posture includes: Step 1, place your arm flat on a table or knee, remain still during the measurement, breathe evenly and steadily, and do not speak; Step 2, gently touch the side electrode with your fingers, avoiding excessively dry fingers, ensuring your fingers do not cover beyond the edge of the electrode, and do not squeeze forcefully. Hold this position for 30 seconds.

[0366] Figure 60 Used for user privacy authorization. For example... Figure 60 As shown, the watch displays a statement regarding innovative research and privacy, along with "Agree" and "Cancel" icons. If the watch detects a click on the "Agree" icon, it checks if access to the body sensors is enabled. If not, it displays... Figure 62 (a) If enabled, the watch begins detecting touch input on the electrodes. If the watch detects a click on the "Cancel" icon, it ends the current evaluation round. For example, the watch's user interface might look like this: Figure 86 .

[0367] Figure 62 (a) is used to ask the user whether they allow the "Innovation Research" app on the phone to use the body sensors on the watch. Figure 62 (a) contains "Allow" and "Deny" icons. If the watch detects a click on the "Allow" icon, it begins detecting touch operations on the electrodes. If the watch detects a click on the "Deny" icon, it ends the current evaluation round.

[0368] Optionally, if this is the first time using the watch to measure coronary heart disease data, the display will show... Figure 62 (b) Figure 62 (b) is used to prompt the user to select whether the watch is worn on the left or right hand, so as to indicate the position of the electrodes on the watch.

[0369] like Figure 62 As shown in (b), the watch offers two wearing options: one for the left wrist and the other for the right wrist. Furthermore, Figure 62 (b) also displays an "OK" icon. When the watch detects a click on the "OK" icon, and the "Wear on left wrist" option is selected, it displays... Figure 63 (a) When the watch detects a click on the "OK" icon and the "Wear on right hand" option is selected, it displays... Figure 63 (b)

[0370] Figure 63 (a) shows how the user touches the electrodes when wearing the watch on their left wrist; Figure 63 (b) shows how the user touches the electrodes when the user is wearing the watch on their right hand.

[0371] Once the watch detects a touch, it begins measurement and displays the result. Figure 64 (a) Figure 64 In (a), the displayed content includes: touch duration, such as 30 seconds; electrocardiogram; heart rate, such as 78 beats / min. Optionally, Figure 64 (a) also outputs the prompt message "Please keep your fingers in good contact with the electrodes" to improve measurement quality.

[0372] After the watch measures the preset duration, it checks if the measurement was successful. If successful, it displays... Figure 64 (b) Figure 64 (b) contains the following cards: Coronary artery disease risk assessment; Electrocardiogram measurement results.

[0373] The "Coronary Artery Disease Risk Assessment" card displays an "i" icon, a "Terminate This Assessment" icon, the measurement item (i.e., ECG measurement), and the measurement time (e.g., July 8th, 10:20 AM). When the watch detects a click on the "i" icon in the "Coronary Artery Disease Risk Assessment" card, an information window pops up displaying relevant information about the card; when the watch detects a click on the "Terminate This Assessment" icon, it transmits the current ECG measurement results to the mobile phone. After receiving the ECG measurement results, the mobile phone displays an exemplary user interface as follows: Figure 65 As shown.

[0374] If the watch fails to detect or measure, the display will show the reason for the failure. The user interface for different failure reasons is as follows: Figure 66 , Figure 67 , Figure 68 , Figure 69 , Figure 70 , Figure 71 , Figure 72 As shown.

[0375] Figure 69 , Figure 70 , Figure 72 The watch also includes a "Remeasure" icon. If the watch detects a tap on the "Remeasure" icon, it will restart the measurement. The watch displays... Figure 72 For example, the mobile phone can display the information synchronously. Figure 73 .

[0376] like Figure 73 As shown, the phone outputs a message reminding the user that "the connection between the phone and the watch has been lost. Please reconnect and start measuring again."

[0377] Figure 64 The exemplary ECG measurement result given in (b) is of type "sinus rhythm" and includes an average heart rate, such as 80 beats / minute. The measurement result may also be at least one of the following: atrial premature beats, ventricular premature beats, atrial fibrillation, or indeterminate.

[0378] An "i" icon can also be displayed next to the ECG measurement result type. When the watch detects a click on the "i" icon next to the ECG measurement result type, it displays relevant information about that ECG measurement result type. Examples of various ECG measurement result types and their corresponding descriptions are shown below. Figure 74 , Figure 75 , Figure 76 , Figure 77 , Figure 78 As shown.

[0379] The watch continues to measure the user's electrocardiogram (ECG). The following example illustrates the process, using a four-day measurement period required for a coronary heart disease assessment.

[0380] At a fixed time on the first day of the assessment, such as 6 PM or 9 PM, the system checks whether the user has worn the watch for the required duration during the day. For example, if the user begins the assessment before 6 PM, the measurement is taken at 6 PM; if the user begins the assessment between 6 PM and 9 PM, the measurement is taken at 9 PM; and if the user begins the assessment between 9 PM and midnight, the following day is considered the first day of the assessment.

[0381] If the watch detects that the wearer has been worn for a certain amount of time during the day, it will display... Figure 79 (a) If the watch detects that the wearer has been worn for a specified period of time during the day, it will display... Figure 79 (b)

[0382] A bedtime reminder will be sent the morning after the assessment measurement. For example, if the user goes to bed before 8 o'clock, the bedtime reminder will be sent at 8 o'clock. That is to say, when the user goes to bed before 8 o'clock, regardless of what time the user goes to bed, the bedtime reminder will be sent at 8 o'clock. This can avoid disturbing the user by sending the reminder message too early (before 8 o'clock) and thus affecting the user experience.

[0383] For example, if a user wakes up between 8 pm and 12 am, the wake-up reminder will be output 10 minutes later. This delay avoids outputting the wake-up reminder when the user has just woken up and is not fully awake, thus avoiding affecting the user experience.

[0384] For example, if a user goes to bed after midnight, then no bedtime reminder will be sent today.

[0385] Sleep reminders help users stay informed about their assessment progress and remind them to correct their assessment behavior when assessment time is insufficient, thus improving assessment efficiency. Furthermore, the different methods of sleep reminders at different times enhance the user experience.

[0386] The four examples of sleep reminder messages are as follows: The first is "You wore the device for the required duration last night, but there is insufficient valid data during the day. Please continue wearing it. It is estimated that this round of evaluation will take X days to complete," where X is a positive number, such as 2.3. The second is "You wore the device for the required duration during the day yesterday, but there is insufficient valid data at night. Please continue wearing it. It is estimated that this round of evaluation will take X days to complete." The third is "You wore the device for both day and night yesterday, and the progress of this round of evaluation is good. It is estimated that this round of evaluation will take X days to complete." The fourth is "You wore the device for both day and night yesterday, but there is insufficient data at night. Please increase your wearing time. It is estimated that this round of evaluation will take X days to complete." The user interface for the first type is as follows: Figure 80 As shown in (a).

[0387] Optionally, if X is less than 1, the remaining time can be indicated in hours, for example, X hours are still needed to complete this round of evaluation.

[0388] Optionally, if the remaining time is less than 1 hour, the remaining time can be indicated in minutes, for example, X minutes are still needed to complete this round of evaluation.

[0389] Optionally, a reminder can be sent at 3 PM on the second day after the assessment measurement. For example, if the user is not asleep or has low activity at 3 PM, a reminder will be sent, and the user interface for the reminder will be as follows: Figure 80 (b) Because this is near the end of the day, reminding users at this time helps them understand the assessment status in a timely manner, and also helps remind users to correct their assessment behavior when the assessment time is insufficient, thus improving assessment efficiency. Low activity level can be understood as the user being in a relatively static state, such as sitting or standing still. Assessment measurements are more accurate when users are in a low activity level state; therefore, reminding users to perform assessment measurements when they are in a low activity level state helps improve the accuracy of the assessment measurements.

[0390] If at 3 PM, the user is in a high-activity state, the watch is performing other measurements, or the watch is in Do Not Disturb or Sleep mode, the watch will check every certain interval (e.g., 5 minutes). If, after that interval, the user is still in a high-activity state, the watch is performing other measurements, or the watch is in Do Not Disturb or Sleep mode, the interval will be delayed by that interval. If the interval is delayed a certain number of times (e.g., 5 times), the alert will no longer be issued. High activity level can be understood as the user being in a state of exercise, such as running, cycling, or swimming. When the user is in a low-activity state, assessment and measurement are not suitable (as the accuracy of assessment and measurement will be lower).

[0391] If, after any delay, the user is not in a high-activity state, or the watch is not performing other measurements, or the watch is not in Do Not Disturb or Sleep mode, then the output will be as follows: Figure 80 (b) Outputting prompts when the user is not in a high-activity state, or the watch is not in other measurements, or the watch is not in Do Not Disturb mode or sleep mode helps to avoid invalid prompts caused by the user being in an unsuitable state for measurement or the watch being in a state where measurement is not possible after the user selects to measure immediately based on the prompt.

[0392] At 6 PM on the second day of the assessment, the watch will issue a reminder, such as... Figure 80 (c) is another reminder, as shown in (d). Among them, Figure 80 (c) is a daytime progress reminder; Figure 80 (d) is a risk warning that the assessment cannot be achieved.

[0393] in, Figure 80(d) also includes a "Start a new round of evaluation" icon. If the watch detects a click on this icon, it can display... Figure 63 .

[0394] On the third day of the evaluation, the watch's behavior can be referenced from that of the second day, and will not be elaborated here. Optionally, on the third day, the user can be prompted to perform at least one ECG measurement to improve the accuracy of the evaluation results.

[0395] On the fourth day of the evaluation, a value output reminder will be issued. For example, the value output reminder would be: Figure 81 (a) or Figure 81 (b) As an example, if the assessment progress is 100% and the user is not currently asleep, the output reminder would be... Figure 81 (a) If the assessment progress is less than 100%, the output value will be alerted. Figure 81 (b)

[0396] Figure 81 (b) may also include a "Start a new round of evaluation" icon. Optionally, Figure 81 (a) may include a "Start a new round of evaluation" icon. If the watch detects a click on this icon, it can display... Figure 63 .

[0397] When the watch detects a click on the "Start a New Round of Evaluation" icon, for example, the watch notifies the phone that the phone can reuse the measurement data from the previous round, or the watch can directly reuse the measurement data from the previous round. Optionally, the phone displays... Figure 82 This indicates that the interval between the previous evaluation and the current evaluation is short, and some measurement data from the previous round will be reused.

[0398] Figure 81 (a) may also include a "View Details" icon. If the watch detects a click on the "View Details" icon, it will display the details corresponding to the current risk type. Details for low risk, medium risk, and high risk are as follows: Figure 83 , Figure 84 and Figure 85 As shown.

[0399] Figure 83 , Figure 84 and Figure 85 The watch can include an "OK" icon. When the watch detects a click on the "OK" icon, it can display the watch's main screen (or desktop). An example of the watch's main screen is shown below. Figure 86 As shown.

[0400] Figure 83 , Figure 84 and Figure 85The watch can include an "i" icon next to the text "Coronary Artery Disease Risk Assessment". When the watch detects a click on the "i" icon next to the "Coronary Artery Disease Risk Assessment" text, it can display relevant information about the coronary artery disease risk assessment. An example user interface for the relevant information about the coronary artery disease risk assessment is shown below. Figure 87 As shown.

[0401] Understandably, in other user interfaces, an "i" icon can also be included next to the text "Coronary Artery Disease Risk Assessment," which, when clicked, displays... Figure 87 .

[0402] After the measurement is completed on the watch side, the evaluation results are synchronized to the mobile phone side. Upon receiving the evaluation results, the mobile phone side displays an exemplary user interface as follows: Figure 88 As shown. Figure 88 The system prompts the user that the coronary heart disease risk assessment results have been generated. Figure 88 The evaluation can include a "Go to View" icon. When the phone detects a click on the "Go to View" icon, it displays the evaluation results.

[0403] The exemplary user interfaces for the assessment results corresponding to low risk, medium risk, and high risk are respectively... Figure 89 , Figure 90 and Figure 91 The "ECG Measurement" card displays the ECG, measurement time, and ECG result type of at least one ECG measurement during this assessment.

[0404] Optionally, the user interface for medium-risk and high-risk assessment results can also display the consultation phone number and working hours of relevant doctors for user convenience.

[0405] When there are no evaluation results in the current round, exemplary user interfaces for different reasons for the lack of evaluation results are as follows: Figure 92 or Figure 93 As shown. Figure 92 or Figure 93 The user interface shown provides the reasons for no evaluation results, so that users can make adjustments based on the reasons.

[0406] Figure 89 , Figure 90 , Figure 91 , Figure 92 or Figure 93 In this example, when the phone detects a tap on the card displaying each ECG measurement result, the phone can display details of that ECG measurement. An example image showing details of a single ECG measurement is shown below. Figure 94 As shown.

[0407] In such Figure 94As shown, optionally, the ECG measurement details user interface may include an "Add Symptom" icon. When the phone detects a click on the "Add Symptom" icon, the user interface for adding symptoms can be displayed. An example of the user interface for adding symptoms is shown below. Figure 95 As shown, providing users with additional symptoms to add during ECG measurements can help improve the accuracy of coronary artery disease assessments.

[0408] When the phone is Figure 95 If a click is detected on the "Submit" icon and one or more symptoms are selected in the symptom options, an example user interface for the ECG details displayed on the phone is as follows: Figure 96 As shown.

[0409] During the evaluation process, if the watch detects that the user has finished exercising, as an example, one minute after the user finishes exercising, the watch outputs a prompt message reminding the user to perform an ECG test. An example of the user interface for this prompt is shown below. Figure 97 As shown in (a). If the watch detects... Figure 97 If the “ECG Measurement” icon in (a) has a clickable action, the watch will output measurement guidance information. An exemplary user interface for the measurement guidance is as follows: Figure 63 As shown in (a) or (b).

[0410] If the watch detects a touch, it outputs the data from the ECG measurement process. An example of the ECG measurement data display is shown below. Figure 64 As shown in (a).

[0411] When the ECG measurement is complete, the watch displays the ECG measurement results. An illustrative user interface showing the ECG measurement results is as follows: Figure 64 As shown in (b).

[0412] When the watch detects Figure 64 When the "Done" icon in (b) is clicked, the watch's main screen (or desktop) can be displayed. An example of the watch's main screen is shown below. Figure 86 As shown.

[0413] Optionally, the watch outputs an ECG measurement prompt 30 minutes after the user finishes exercising. An exemplary user interface for this prompt is as follows: Figure 23 As shown.

[0414] Watch detected Figure 97 When the "ECG Measurement" icon in (b) is clickable, the subsequent operation of the watch and the possible user interface output can be found by referring to the watch's detection. Figure 97 The “ECG measurement” icon in (a) contains information about what happens after clicking it.

[0415] As an example, the watch can periodically output assessment reminders. For example, the reminder interval for the next assessment will differ depending on the risk level of the most recent assessment result. The higher the risk level, the shorter the reminder interval.

[0416] For example, when the latest assessment results are high risk, medium risk, and low risk, the assessment alert cycle is shown in Table 1.

[0417] Table 1

[0418] Risk level Regular measurement cycle Low risk Regular measurement: Measure once every 3 months Medium risk Regular measurement: Measure once every 2 months High risk Regular measurement: Once a month

[0419] Exemplary user interfaces for low-risk and high-risk periodic measurement alerts are as follows: Figure 98 As shown in (a) and (b). If the "Start a New Round of Evaluation" icon in the figure is clicked, the watch's behavior can be referenced. Figure 63 (a) or (b)).

[0420] Figure 57 The "Coronary Artery Disease Risk Assessment" card displays a low-risk assessment result. Example images showing intermediate-risk, high-risk, and no assessment results are shown below. Figure 99 , Figure 100 , Figure 101 and Figure 102 As shown. When the "Start a New Round of Evaluation" icon is clicked, it determines whether the watch was successfully activated, and the subsequent evaluation process can refer to the aforementioned content.

[0421] As an example, the "Coronary Artery Disease Risk Assessment" card on the mobile phone contains an "i" icon. When the phone detects a click on the "i" icon, an exemplary user interface is displayed as follows: Figure 103 As shown.

[0422] As an example, the "Coronary Artery Disease Risk Assessment Record" card on the mobile phone includes a "More" icon. When the phone detects a click on this "More" icon, it determines whether there is an assessment record. If there is no assessment record, the exemplary user interface displayed is as follows: Figure 104 As shown; if there are evaluation records, an exemplary user interface will be displayed as follows. Figure 105 As shown.

[0423] As an example, such as Figure 105 As shown, assessment records can be displayed either without risk level classification or with risk level classification. For example, when not classified by risk level, the assessment results can be arranged in reverse chronological order, meaning the later the assessment date, the earlier it appears in the display list.

[0424] When displayed according to risk level categories, clicking on any risk level category icon will show the assessment result for that risk level. For example, the assessment results for that risk level are arranged in reverse chronological order.

[0425] like Figure 105 When any displayed assessment record is clicked, the watch can display the details of that assessment record. An exemplary user interface for the assessment record details is as follows: Figure 89 , Figure 90 , Figure 91 , Figure 92 or Figure 93 As shown.

[0426] The above text combined Figures 1 to 105 The method embodiments of this application are described in detail below, in conjunction with... Figure 106 and Figure 107 The present application provides a detailed description of the apparatus embodiments. It should be understood that the descriptions of the method embodiments correspond to the descriptions of the apparatus embodiments; therefore, any parts not described in detail can be found in the foregoing method embodiments.

[0427] Figure 106 This is a schematic structural diagram of a device for assessing the risk of coronary heart disease provided in an embodiment of this application. Figure 106 As shown, the device 10600 includes a first acquisition unit 10610, a second acquisition unit 10620, and a determination unit 10630, as detailed below:

[0428] The first acquisition unit 10610 is used to acquire first electrocardiogram data within a first time period;

[0429] The second acquisition unit 10620 is used to acquire second electrocardiogram data and / or second pulse wave data during a second time period, wherein the duration of the second time period is longer than the duration of the first time period.

[0430] The determining unit 10630 is used to determine the coronary heart disease risk assessment result based on the first data, the first data including: the first electrocardiogram data, the second electrocardiogram data and / or the second pulse wave data;

[0431] The second pulse wave data includes the user's pulse wave data during sleep and the user's pulse wave data during non-sleep.

[0432] In some possible implementations, the second electrocardiogram (ECG) data includes ECG data of the user during sleep and ECG data of the user during non-sleep.

[0433] In some possible implementations, the first electrocardiogram (ECG) data is static ECG data, and the second ECG data is dynamic ECG data.

[0434] In some possible implementations, the first acquisition unit 10610 is specifically used for:

[0435] Acquire the first electrocardiogram data and the first pulse wave data during the first time period;

[0436] The first data also includes the first pulse wave data.

[0437] In some possible implementations, the device 10600 further includes an output unit 10640, for:

[0438] If the user is detected to be exercising during the second time period, first information is output, which is used to remind the user to perform an electrocardiogram measurement after completing the exercise;

[0439] The first acquisition unit 10610 is further configured to: acquire third electrocardiogram data after the user completes the exercise;

[0440] The first data also includes the third electrocardiogram data.

[0441] In some possible implementations, the device 10600 further includes an output unit 10640, for:

[0442] The second information is output at a preset time within the second time period, and the second information is used to remind the user to perform an electrocardiogram measurement.

[0443] The first acquisition unit 10610 is further configured to: acquire fourth electrocardiogram data during the second time period;

[0444] The first data also includes the fourth electrocardiogram data.

[0445] In some possible implementations, the device 10600 further includes an output unit 10640, for:

[0446] Output a third piece of information, which is used to indicate the progress of the coronary heart disease risk assessment.

[0447] In some possible implementations, the third information is determined based on the measurement progress of the second electrocardiogram data and / or the second pulse wave data.

[0448] In some possible implementations, the output unit 10640 is specifically used for:

[0449] The third information is output immediately after the user wakes up from sleep.

[0450] In some possible implementations, the third information is also used for one or more of the following: indicating whether the user has achieved the required wearing standard during sleep, indicating the current overall assessment progress percentage, and indicating the estimated remaining wearing time.

[0451] In some possible implementations, the output unit 10640 is specifically used for:

[0452] The third information is output at a second moment before the user falls asleep.

[0453] In some possible implementations, the third information is also used for one or more of the following: indicating whether the user has achieved the required wearing time during non-sleep periods, indicating the estimated remaining wearing time, and reminding the user to wear the wearable device during sleep.

[0454] In some possible implementations, the device 10600 further includes an output unit 10640, for:

[0455] If it is anticipated that the user will be unable to complete the coronary heart disease risk assessment, a fourth piece of information is output, which is used to suggest that the user undergo the coronary heart disease risk assessment again.

[0456] In some possible implementations, the first acquisition unit 10610 is further configured to:

[0457] Acquire the fifth electrocardiogram data and / or the third pulse wave data during the third time period;

[0458] Wherein, the second time period is after the first time period, the third time period is after the second time period or within the second time period, and the first data also includes the third electrocardiogram data and / or the third pulse wave data.

[0459] In some possible implementations, the device 10600 further includes a third acquisition unit 10650, used for:

[0460] Obtain the second data input by the user, the second data being used to assess the user's health status;

[0461] The first data also includes the second data.

[0462] In some possible implementations, the second data includes one or more of the following information:

[0463] Do you have a history of coronary heart disease, cardiovascular or cerebrovascular disease, high blood pressure, high cholesterol, high blood sugar, high uric acid, chest tightness, or chest pain?

[0464] In some possible implementations, the device 10600 further includes an output unit 10640 and a waveform analysis unit 10660, the waveform analysis unit 10660 being used for:

[0465] Waveform analysis is performed on the first electrocardiogram data to obtain the waveform characteristics of the first electrocardiogram data;

[0466] The output unit 10640 is used to: output fifth information, the fifth information being used to indicate the waveform characteristics of the first electrocardiogram data;

[0467] The coronary heart disease risk assessment results include the waveform characteristics of the first electrocardiogram data.

[0468] In some possible implementations, the coronary heart disease risk assessment results include the user's risk level for coronary heart disease.

[0469] In some possible implementations, the device 10600 further includes a third acquisition unit 10650, used for:

[0470] Acquire the user's motion data and / or the user's physiological data in a resting state during the second time period;

[0471] The first data further includes the motion data and / or the physiological data.

[0472] Figure 107 This is a schematic structural diagram of a device provided in an embodiment of this application. Figure 107 The dashed lines indicate that the unit or module is optional. The device 10700 can be used to implement the methods described in the above method embodiments. The device 10700 can be a chip or a device for assessing the risk of coronary heart disease.

[0473] Apparatus 10700 may include one or more processors 10710. The processor 10710 may support apparatus 10700 in implementing the methods described in the preceding method embodiments. The processor 10710 may be a general-purpose processor or a special-purpose processor. For example, the processor may be a central processing unit (CPU). Alternatively, the processor may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0474] The apparatus 10700 may further include one or more memories 10720. The memories 10720 store a program that can be executed by the processor 10710, causing the processor 10710 to perform the methods described in the preceding method embodiments. The memories 10720 may be independent of the processor 10710 or integrated within the processor 10710.

[0475] The device 10700 may also include a transceiver 10730. The processor 10710 can communicate with other devices or chips via the transceiver 10730. For example, the processor 10710 can send and receive data with other devices or chips via the transceiver 10730.

[0476] It should be noted that the information interaction and execution process between the above-mentioned devices / units are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, and they will not be repeated here.

[0477] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0478] This application also provides a computer-readable storage medium storing a computer program, which, when executed by a computer, causes the computer to perform the steps in the above-described method embodiments.

[0479] This application provides a computer program product that, when run on an electronic device, enables the electronic device to perform the steps described in the various method embodiments above.

[0480] This application provides a chip including a processor and a memory. The memory stores a computer program, and the processor calls and runs the computer program stored in the memory, causing an electronic device equipped with the chip to perform the steps described in the various method embodiments above.

[0481] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of this application can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or some intermediate form. The computer-readable storage medium can include at least: any entity or device capable of carrying computer program code to a device / electronic device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks. In some possible implementations, the computer-readable storage medium cannot be an electrical carrier signal or a telecommunication signal.

[0482] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0483] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0484] In the embodiments provided in this application, it should be understood that the disclosed devices / electronic devices and methods can be implemented in other ways. For example, the device / electronic device embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual couplings or direct couplings or communication connections may be through some interfaces; indirect couplings or communication connections between devices or units may be electrical, mechanical, or other forms.

[0485] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0486] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method for assessing the risk of coronary heart disease, characterized in that, include: Acquire the first electrocardiogram data within the first time period; Acquire second electrocardiogram data and / or second pulse wave data during a second time period, the duration of which is longer than that of the first time period; The coronary heart disease risk assessment result is determined based on the first data, which includes: the first electrocardiogram data, the second electrocardiogram data, and / or the second pulse wave data; The second pulse wave data includes the user's pulse wave data during sleep and the user's pulse wave data during non-sleep.

2. The method according to claim 1, characterized in that, The second electrocardiogram (ECG) data includes the ECG data of the user during sleep and the ECG data of the user during non-sleep.

3. The method according to claim 1 or 2, characterized in that, The first electrocardiogram (ECG) data is static ECG data, and the second ECG data is dynamic ECG data.

4. The method according to any one of claims 1 to 3, characterized in that, The acquisition of the first electrocardiogram data in the first time period includes: Acquire the first electrocardiogram data and the first pulse wave data during the first time period; The first data also includes the first pulse wave data.

5. The method according to any one of claims 1 to 4, characterized in that, The method further includes: If the user is detected to be exercising during the second time period, first information is output, which is used to remind the user to perform an electrocardiogram measurement after completing the exercise; Acquire third electrocardiogram data after the user completes the exercise; The first data also includes the third electrocardiogram data.

6. The method according to any one of claims 1 to 4, characterized in that, The method further includes: The second information is output at a preset time within the second time period, and the second information is used to remind the user to perform an electrocardiogram measurement. Acquire the fourth electrocardiogram data during the second time period; The first data also includes the fourth electrocardiogram data.

7. The method according to any one of claims 1 to 6, characterized in that, The method further includes: Output a third piece of information, which is used to indicate the progress of the coronary heart disease risk assessment.

8. The method according to claim 7, characterized in that, The output of the third information includes: The third information is output immediately after the user wakes up from sleep.

9. The method according to claim 8, characterized in that, The third information is also used for one or more of the following: indicating whether the user has achieved the required wearing standard during sleep, indicating the current overall assessment progress percentage, and indicating the estimated remaining wearing time.

10. The method according to claim 7, characterized in that, The output of the third information includes: The third information is output at a second moment before the user falls asleep.

11. The method according to claim 10, characterized in that, The third information is also used for one or more of the following: indicating whether the user's wearing of the device during non-sleep periods meets the standard, indicating the estimated remaining wearing time, and reminding the user to wear the wearable device during sleep.

12. The method according to any one of claims 1 to 11, characterized in that, The method further includes: If it is anticipated that the user will be unable to complete the coronary heart disease risk assessment, a fourth piece of information is output, which is used to suggest that the user undergo the coronary heart disease risk assessment again.

13. The method according to any one of claims 1 to 12, characterized in that, The method further includes: Acquire the fifth electrocardiogram data and / or the third pulse wave data during the third time period; Wherein, the second time period is after the first time period, the third time period is after the second time period or within the second time period, and the first data also includes the third electrocardiogram data and / or the third pulse wave data.

14. The method according to any one of claims 1 to 13, characterized in that, The method further includes: Obtain the second data input by the user, the second data being used to assess the user's health status; The first data also includes the second data.

15. The method according to claim 14, characterized in that, The second data includes one or more of the following information: Do you have a history of coronary heart disease, cardiovascular or cerebrovascular disease, high blood pressure, high cholesterol, high blood sugar, high uric acid, chest tightness, or chest pain? 16. The method according to claim 14, characterized in that, The method further includes: Waveform analysis is performed on the first electrocardiogram data to obtain the waveform characteristics of the first electrocardiogram data; Output the fifth information, which is used to indicate the waveform characteristics of the first electrocardiogram data; The coronary heart disease risk assessment results include the waveform characteristics of the first electrocardiogram data.

17. The method according to claim 14, characterized in that, The coronary heart disease risk assessment results include the user's risk level for coronary heart disease.

18. The method according to any one of claims 1 to 17, characterized in that, The method further includes: Acquire the user's motion data and / or the user's physiological data in a resting state during the second time period; The first data further includes the motion data and / or the physiological data.

19. A device for assessing the risk of coronary heart disease, characterized in that, include: A module or unit for performing the method as described in any one of claims 1 to 18.

20. A device for assessing the risk of coronary heart disease, characterized in that, include: A processor and a memory, the memory being used to store a computer program that, when executed by the processor, causes the apparatus to perform the method as described in any one of claims 1 to 18.

21. A wearable device, characterized in that, The wearable device includes the apparatus for assessing the risk of coronary heart disease as described in claim 19 or 20.

22. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when run on a computer, causes the computer to perform the method as described in any one of claims 1 to 18.

23. A computer program product, characterized in that, include: A computer program that, when run on a computer, causes the computer to perform the method as described in any one of claims 1 to 18.

24. A chip, characterized in that, include: A processor and a memory, the memory for storing a computer program, the processor for calling and running the computer program stored in the memory, causing a device or apparatus on which the chip is mounted to perform the method as described in any one of claims 1 to 18.

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