Method of detecting vascular health and electronic device

Abstract

This application provides a method and electronic device for detecting vascular health. The electronic device can determine the probability of a user developing cardiovascular disease by detecting their daily physiological data. This daily physiological data can include data from multiple time periods and / or multiple scenarios. The vascular health detection results determined using this data are highly accurate and reliable. Furthermore, the electronic device can analyze this data to determine whether the user exhibits symptoms related to acute cardiovascular disease, thereby determining the user's risk of sudden cardiovascular event. In cases where there is a risk of sudden cardiovascular event, the electronic device can provide early warning and timely emergency calls, increasing the user's chances of survival in such situations.

Description

Technical Field

[0001] This application relates to the field of terminal device software, and more specifically, to a method and electronic device for detecting vascular health. Background Technology

[0002] Blood vessels are an important part of the human circulatory system. Healthy blood vessels ensure smooth blood flow, maintain normal blood pressure levels, and support the function of the heart, brain, and other organs.

[0003] Taking coronary artery disease as an example, cardiovascular diseases can include chronic cardiovascular diseases and acute cardiovascular diseases. Chronic cardiovascular diseases are vascular lesions caused by long-term unhealthy lifestyles, with low awareness and a certain degree of insidicity. Long-term chronic coronary artery disease can cause complications such as arrhythmia, angina pectoris, myocardial infarction, or heart failure. In some cases, chronic cardiovascular disease may also induce acute cardiovascular disease, seriously endangering life.

[0004] Improving the efficiency of cardiovascular disease detection and providing early warnings of potential acute cardiovascular diseases are urgent problems that need to be solved. Summary of the Invention

[0005] This application provides a method and electronic device for detecting vascular health. This method can be applied to wearable devices, which can detect physiological data from users over multiple time periods and / or in multiple scenarios during daily wear to determine the probability of cardiovascular disease. This method does not rely on specialized medical equipment and enables long-term, continuous monitoring of a user's vascular health. The device outputs highly accurate and reliable cardiovascular disease detection results. In cases where a user is at risk of sudden cardiovascular disease, the electronic device can provide early warning, increasing the chances of survival in such situations.

[0006] In a first aspect, a method for detecting vascular health is provided, applied to a wearable device. The method includes: detecting a user's first physiological data within a first time period using a photoplethysmography (PPG) sensor; detecting a user's second physiological data at rest using an electrocardiogram (ECG) sensor; detecting a third physiological data after exercise using the ECG sensor; and displaying the detection result of vascular health, the detection result being determined based on the first physiological data, the second physiological data, and the third physiological data.

[0007] In one possible implementation, the results of vascular health testing can include the probability of developing cardiovascular disease, which can include one or more of the following: coronary artery disease (including chronic coronary artery disease, acute coronary syndrome), hypertension, heart failure, stroke, rheumatic heart disease, and congenital heart disease.

[0008] In one possible implementation, the first physiological data may include time-domain and frequency-domain information on the user's heart rate changes, such as the user's heart rate, heart rate variability, estimated blood oxygen saturation, and estimated blood pressure.

[0009] In one possible implementation, the second physiological data can be detected multiple times.

[0010] In one possible implementation, the second physiological data can be used to determine the user's electrocardiogram characteristics, such as ST segment morphology and / or T wave morphology.

[0011] In one possible implementation, the electronic device can detect the user's motion state through a motion sensor, thereby determining whether the user is in a state of motion.

[0012] In one possible implementation, the first duration includes multiple effective measurement cycles, wherein the wearing duration within each effective measurement cycle is greater than or equal to a duration threshold.

[0013] In one possible implementation, the above detection results can also be determined based on one or more of the following: physiological data detected by the ECG sensor in a reference scenario, physiological data detected by the PPG sensor in the user's resting state, physiological data detected by the PPG sensor in the user's pain state, respiratory rate, blood pressure, blood oxygen content or pulse in the user's arrhythmia state, wherein the reference scenario includes one or more of the following: the user is in a post-exercise state, the user is in a pain state, the user is in an emotional fluctuation state, the user is in a cold environment, the user is in a post-eating state, etc.

[0014] This technical solution is applied to wearable devices that can continuously monitor a user's primary physiological data and repeatedly measure their electrocardiogram (ECG) data during wear. Based on these two types of data, the probability of the user developing cardiovascular disease can be determined. This solution does not rely on specialized medical equipment. By extending the monitoring time for primary physiological data and increasing the number of ECG measurements, more physiological data related to cardiovascular disease is obtained, which improves the accuracy and reliability of vascular health monitoring results. This allows users to understand changes in their individual vascular health and enables early treatment of potential cardiovascular diseases. Furthermore, this technical solution can facilitate preliminary screening for cardiovascular diseases with high prevalence, which to some extent improves the efficiency of limited social medical resources and helps alleviate the psychological stress on patients.

[0015] In determining a user's vascular health, this technical solution combines the user's physiological data at rest (such as resting electrocardiogram information) and physiological data after exercise (such as post-exercise electrocardiogram information). These two types of data are strongly correlated with the user's cardiovascular status, and the detection results for determining vascular health are more accurate when using these two types of data.

[0016] In conjunction with the first aspect, in certain implementations of the first aspect, before displaying the detection result of vascular health, the method further includes: detecting a reference scenario and / or a reference physiological condition, the reference scenario being associated with cardiovascular disease, the reference physiological condition being used to indicate an abnormality in a fourth physiological data associated with cardiovascular disease; detecting a fifth physiological data while the user is in the reference scenario; and / or, detecting the fifth physiological data while the user is in the reference physiological condition; and determining the detection result based on the first physiological data, the second physiological data, the third physiological data, the fifth physiological data, and the reference scenario and / or the reference physiological condition.

[0017] Here, the association between the reference scenario and cardiovascular disease can be understood as follows: under the reference scenario, users with cardiovascular disease are more likely to exhibit symptoms. In other words, under the reference scenario, the activity of the human cardiovascular system is more likely to change.

[0018] Here, the fourth physiological data associated with cardiovascular disease can be understood as follows: compared to other physiological data, the fourth physiological data is more likely to reflect whether a user is experiencing symptoms of cardiovascular disease. In other words, the fourth physiological data can be used to directly or indirectly determine whether a user has cardiovascular disease.

[0019] In one possible implementation, the aforementioned vascular health test results can also be determined based on the first physiological data, the second physiological data, the third physiological data, and the fifth physiological data.

[0020] In conjunction with the first aspect, in some implementations of the first aspect, the method further includes, before displaying the test results for vascular health, displaying a third interface that includes one or more test tasks to be completed.

[0021] In conjunction with the first aspect, in some implementations of the first aspect, upon detecting a reference scenario and / or a reference physiological condition, a target detection task is displayed on the third interface. The target detection task is used to instruct the detection of a fifth physiological data point, which is used to determine the detection result. The reference scenario is associated with cardiovascular disease, and the reference physiological condition is used to indicate an abnormality in the fourth physiological data point associated with cardiovascular disease.

[0022] In conjunction with the first aspect, in some implementations of the first aspect, the reference scenario includes one or more of the following: the user is in a state of having finished exercising, the user is in a state of pain, the user is in a state of emotional fluctuation, the user is in a cold environment, the user is in a state of having eaten; and / or, the fourth physiological data or the fifth physiological data includes one or more of the following: physiological data detected by the ECG sensor, physiological data detected by the PPG sensor, respiratory rate, blood pressure, blood oxygen content, and pulse.

[0023] In one possible implementation, the fourth and fifth physiological data can be the same or different.

[0024] In one possible implementation, the above-mentioned reference scenario could be that the user is in a state of having finished exercising. In this case, the fifth physiological data mentioned above could refer to the third physiological data mentioned earlier.

[0025] In one possible implementation, the electronic device can detect the user's motion state through a motion sensor to determine whether the user is in a motion scenario; the electronic device can detect the user's skin conductance data through a skin conductance sensor, and / or detect the user's facial expressions and movements through an image sensor to determine whether the user is in a state of pain; the electronic device can detect changes in the user's heart rate and body temperature based on a PPG sensor, a body temperature sensor, etc., to determine whether the user is in a state of emotional fluctuation, in a cold environment, or in a state after eating.

[0026] In one possible implementation, the electronic device can detect the user's aforementioned fourth physiological data, and if the fourth physiological data is abnormal, the electronic device can determine that a reference physiological condition has been detected.

[0027] The aforementioned reference scenarios can all be understood as situations where the activity state of the human cardiovascular system may undergo significant changes. Electronic devices can detect users' electrocardiogram (ECG) data in scenarios strongly associated with cardiovascular diseases. ECG data from these scenarios is more reflective of the user's cardiovascular status, which helps improve the accuracy and reliability of the vascular health detection results output by electronic devices.

[0028] Furthermore, during vascular health testing, wearable devices can add new testing tasks based on the actual testing situation. This makes the entire vascular health testing process more closely aligned with the user's actual physiological condition and lifestyle habits, resulting in more accurate vascular health test results when combined with the results of the new testing tasks. In addition, for newly added testing tasks, the wearable device can promptly perform measurements or add them to the list of pending testing tasks. This allows users to more clearly understand the different situations and relevant details that arise throughout the testing process, thus improving the user experience.

[0029] In conjunction with the first aspect, in some implementations of the first aspect, before detecting the second physiological data after the user's movement via the ECG sensor, the method further includes: detecting the user's movement state; and displaying first information when the user is in a state of completed movement, the first information being used to indicate the measurement of the third physiological data.

[0030] In one possible implementation, the first information can be used to indicate a method for measuring third physiological data via an ECG sensor. For example, the first information can be used to indicate the location where the user places their right hand fingers on the ECG electrode of the device.

[0031] In one possible implementation, when the user places their finger on the ECG electrode of the device, the first information can be used to indicate that a third physiological data is being measured.

[0032] Since the measurement of third physiological data requires the user's manual cooperation, the electronic device prompts the user to detect third physiological data after the user moves. This helps to improve the success rate of third physiological data acquisition in the reference scenario and helps the electronic device output more accurate and reliable vascular health detection results.

[0033] In conjunction with the first aspect, in certain implementations of the first aspect, before displaying the test results for vascular health, the method further includes: displaying a first interface including a questionnaire for determining a user's health information, the health information including one or more of the following: gender, age, lifestyle, family medical history, personal medical history, and current physical condition; and determining the test results based on the health information, the first physiological data, the second physiological data, and the third physiological data.

[0034] In this technical solution, the electronic device can obtain the user's health information through a questionnaire and output the detection results of vascular health based on this health information. In other words, the detection results can be obtained based on data analysis from more dimensions, making the detection results more accurate and reliable.

[0035] In conjunction with the first aspect, in certain implementations of the first aspect, before displaying the detection result of vascular health, the method further includes: acquiring image data via an image sensor, the image data being used to determine a first symptom, the first symptom including one or more of the following: earlobe creases, nasal bridge wrinkles, abnormal facial skin color, facial edema, corneal arch, and baldness on the top of the head; and determining the detection result based on the image data, the first physiological data, the second physiological data, and the third physiological data.

[0036] The first symptom mentioned above can be understood as a symptom closely related to cardiovascular disease.

[0037] In this technical solution, the electronic device can acquire image data through an image sensor and analyze this image data to determine whether the user has symptoms associated with cardiovascular disease. The detection results of vascular health can also be determined by combining the analysis results of this image data; in other words, the detection results can be obtained based on data analysis from more dimensions, making the detection results more accurate and reliable.

[0038] In conjunction with the first aspect, in some implementations of the first aspect, the method further includes, before displaying the detection results of vascular health, displaying second information indicating insufficient wearing time.

[0039] In conjunction with the first aspect, in some implementations of the first aspect, the method further includes: displaying third information, which indicates an extension of the wearing time, or, which indicates a re-detection.

[0040] In one possible implementation, during a single test, if the wearing time is insufficient for the first time, the electronic device can prompt the user to extend the wearing time; if the wearing time is insufficient for the second time, the electronic device can prompt the user to retest.

[0041] If the wearing time of the electronic device does not meet the preset requirements, the device may be unable to output vascular health test results. In this case, the electronic device can output a prompt message to enable it to output vascular health test results. Implementing this technical solution improves the user experience during vascular health testing. The retesting method helps obtain the user's current physiological data and, combined with this data, determines the user's vascular health test results, which to some extent also improves the accuracy and reliability of the test results.

[0042] In conjunction with the first aspect, in some implementations of the first aspect, the method further includes: accepting an operation to initiate a new round of vascular health detection; detecting a sixth physiological data of the user within a second duration, the second duration being shorter than the first duration, using the PPG sensor; detecting a seventh physiological data of the user in a resting state using the ECG sensor; detecting an eighth physiological data of the user after exercise using the ECG sensor; and determining the result of the new round of vascular health detection based on the first physiological data, the seventh physiological data, and the eighth physiological data if the similarity between the sixth physiological data and the first physiological data is greater than a preset threshold.

[0043] If the similarity of the physiological data detected by the electronic device is greater than or equal to the similarity threshold during two rounds of testing, it can be determined that the user of the device has not changed and that the user's physiological condition (especially cardiovascular condition) is in a relatively stable state. In this case, the electronic device can reuse the detection data from the PPG sensor in the previous round. Implementing this technical solution helps to shorten the testing time in the subsequent round, improve the testing efficiency in the subsequent round, and enhance the user experience.

[0044] In conjunction with the first aspect, in some implementations of the first aspect, the method further includes, before displaying the detection results of vascular health, displaying a second interface that includes the detection progress of vascular health.

[0045] In one possible implementation, the second interface may also include unfinished detection tasks.

[0046] In conjunction with the first aspect, in some implementations of the first aspect, the second interface includes fourth information and / or fifth information, the fourth information being used to indicate that the wearing process during the first time period meets the preset requirements, and the fifth information being used to indicate that the wearing process during the second time period does not meet the preset requirements, and the first duration including the first time period and / or the second time period.

[0047] In one possible implementation, the aforementioned preset requirements may include correct wearing method and / or wearing duration greater than or equal to a duration threshold.

[0048] In one possible implementation, the fifth piece of information can also be used to indicate why the wearing process during the second time period does not meet the preset requirements.

[0049] Since a single vascular health test can take a considerable amount of time, displaying the test progress on an electronic device helps users understand the process and improves the user experience. Before outputting the test results, the electronic device can display the time periods that meet preset requirements and / or the time periods that do not. This allows users to better understand the test status and take appropriate measures in a timely manner, thereby improving the efficiency of the electronic device in outputting vascular health test results.

[0050] In conjunction with the first aspect, in some implementations of the first aspect, the detection result is determined based on historical data of vascular health detection results, the first physiological data, the second physiological data, and the third physiological data.

[0051] Considering the user's historical vascular health test results when determining the user's current vascular health test results helps to identify changes in the user's physiological data, thereby facilitating the output of more accurate vascular health test results.

[0052] Secondly, a method for detecting vascular health is provided, applied to a wearable device. The method includes: acquiring a user's heart rate information and / or electrocardiogram information; displaying a first interface for indicating that the user has arrhythmia and / or electrocardiogram abnormalities; performing a first operation for determining whether the user has a first symptom, which indicates that the user has cardiac arrest; and displaying a second interface when the user has the first symptom, which indicates that the user has a risk of sudden cardiovascular disease.

[0053] In this technical solution, the electronic device can perform a first operation upon detecting a user's arrhythmia to detect whether the user has experienced cardiac arrest. If cardiac arrest occurs, the electronic device can determine that the user is at risk of sudden coronary heart disease. The process of detecting the risk of sudden coronary heart disease can be performed automatically without user intervention. The implementation of this technical solution facilitates early warning and emergency calls for acute cardiovascular diseases, thereby increasing the chances of patient survival in emergency situations.

[0054] In conjunction with the second aspect, in some implementations of the second aspect, before performing the first operation, the method further includes: determining whether the user has a second symptom based on the heart rate information; and if the user has the second symptom, displaying a third interface to indicate that the user has the second symptom.

[0055] In one possible implementation, the aforementioned first operation is performed upon determining that the user exhibits a second symptom.

[0056] In one possible implementation, the second symptom is used to indicate an abnormal heartbeat in the user. For example, the second symptom may include one or more of the following: ventricular fibrillation, atrial fibrillation, premature ventricular contractions, ventricular tachycardia, sinus tachycardia, conduction block, bundle branch block, cardiac arrest, etc.

[0057] Electronic devices can analyze a user's heart rate information to detect potential heart rhythm abnormalities, improving the accuracy and reliability of identifying the risk of sudden cardiovascular events and enhancing the feasibility of using this solution for early warning of such events. To some extent, it also improves the energy efficiency of the electronic device during the warning process.

[0058] In conjunction with the second aspect, in some implementations of the second aspect, acquiring the user's heart rate information includes: in the target scenario, detecting the user's first physiological data using a photoplethysmography (PPG) sensor, the first physiological data being used to determine the heart rate information; and / or, in the target scenario, detecting the user's second physiological data using an electrocardiogram (ECG) sensor, the second physiological data being used to determine the electrocardiogram (ECG) information.

[0059] In one possible implementation, the target scenario includes: the user is in a static state (e.g., a resting state after exercise) and / or the user is in pain.

[0060] In the target scenario, the user's heart rate information can more accurately reflect the user's arrhythmia, and the primary physiological data in the target scenario can more accurately assess the user's cardiovascular status. Detecting the primary physiological data in the target scenario helps improve the accuracy and reliability of electronic devices in determining the risk of a user experiencing a sudden cardiovascular disease, and improves the feasibility of using this solution for early warning of sudden cardiovascular diseases. To a certain extent, it also helps improve the energy utilization efficiency of electronic devices during the aforementioned early warning process.

[0061] In conjunction with the second aspect, in some implementations of the second aspect, the execution of the first operation includes: measuring a user's third physiological data, which includes one or more of the following: respiratory rate, blood pressure, pulse, or blood oxygen content, and the first symptom includes the third physiological data meeting preset conditions; the method further includes: displaying a fourth interface, which includes the measurement results of the third physiological data.

[0062] In one possible implementation, the aforementioned third physiological data satisfying preset conditions includes at least one of the following: respiratory rate satisfies a first preset condition, blood pressure satisfies a second preset condition, pulse satisfies a third preset condition, and blood oxygen content satisfies a fourth preset condition; wherein, the first preset condition may include a respiratory rate greater than or equal to a first threshold; the aforementioned second preset condition may include diastolic blood pressure greater than or equal to a second threshold, and / or systolic blood pressure greater than or equal to a third threshold; the third preset condition may include no detectable pulse; and the fourth preset condition may include blood oxygen content less than or equal to a fourth threshold.

[0063] In conjunction with the second aspect, in some implementations of the second aspect, the method further includes: performing an emergency call for help when the user exhibits the first symptom.

[0064] One possibility is that the electronic device can detect if the user has fallen, and if so, execute an emergency call for help.

[0065] Displaying respiratory rate and / or blood pressure measurements helps users understand their physical condition, enabling them to take timely measures and increasing their chances of survival in the event of a sudden cardiovascular event.

[0066] Thirdly, a method for detecting vascular health is provided, applied to an electronic device. The method includes: acquiring first data, which indicates a first symptom associated with cardiovascular disease; and outputting a detection result of the vascular health, which indicates the probability of developing the cardiovascular disease, the detection result being determined based on the first data; wherein the first data includes detection data from multiple measurement periods.

[0067] In this technical solution, electronic devices can analyze whether a user has the first symptom associated with cardiovascular disease by using the detection data of the user in multiple measurement cycles. The amount of detection data corresponding to multiple measurement cycles is larger, and the detection results of vascular health obtained by analyzing these data are more accurate and reliable, which is conducive to the application of this technical solution in wearable electronic devices.

[0068] In conjunction with the third aspect, in some implementations of the third aspect, before outputting the vascular health test result, the method further includes: obtaining the user's health information, which includes one or more of the following: gender, age, lifestyle, family medical history, personal medical history, and current physical condition; and determining the test result based on the first data and the health information.

[0069] Electronic devices can combine various health information related to cardiovascular diseases to output vascular health test results. In other words, the test results can be obtained based on data analysis from more dimensions, making the test results more accurate and reliable.

[0070] In conjunction with the third aspect, in some implementations of the third aspect, the first data includes the detection data under a reference scenario, which includes one or more of the following: exercise scenario, sleep scenario, user in pain state, user in emotional fluctuation state, user in cold environment, user in post-eating state.

[0071] The aforementioned reference scenarios can all be understood as situations where the activity state of the human cardiovascular system may undergo significant changes. Electronic devices can detect users' secondary physiological data in scenarios strongly associated with cardiovascular diseases. This secondary physiological data in these scenarios is more reflective of the user's cardiovascular activity state, which helps improve the accuracy and reliability of the vascular health detection results output by electronic devices.

[0072] In conjunction with the third aspect, in some implementations of the third aspect, the first symptom includes one or more of the following: arrhythmia, abnormal facial features, atrial fibrillation, abnormal blood pressure, abnormal blood oxygen content, sleep apnea syndrome, and abnormal cardiac output.

[0073] In some implementations of the third aspect, the detection data includes one or more of the following: data from a photoplethysmography (PPG) sensor, data from an electrocardiogram (ECG) sensor, image data, data from a motion sensor, and data from a temperature sensor.

[0074] In some implementations of the third aspect, the cardiovascular disease includes: chronic coronary artery disease and / or acute coronary syndrome.

[0075] In some implementations of the third aspect, the first data includes first sub-data, and before outputting the detection result of the vascular health, the method further includes: determining a first result based on the first sub-data; determining a second result based on the first data; and determining the detection result of the vascular health based on the first result and the second result; wherein the plurality of measurement cycles includes a first measurement cycle, and the first sub-data is the detection data within the first measurement cycle.

[0076] Electronic devices analyze primary data related to cardiovascular disease from multiple dimensions. Compared to single-dimensional analysis methods, the vascular health detection results obtained through this analysis method are more accurate and reliable.

[0077] In some implementations of the third aspect, two adjacent measurement cycles are consecutive in multiple measurement cycles.

[0078] The first data obtained within a continuous measurement cycle can more accurately reflect the user's cardiovascular activity, which is conducive to outputting more accurate and reliable vascular health test results.

[0079] For detailed explanations and descriptions of the beneficial effects in the following technical solutions, please refer to the relevant content in the first, second and third aspects, which will not be repeated here.

[0080] Fourthly, a device for vascular health detection is provided, comprising an acquisition module and a processing module. The acquisition module is used to: detect a user's first physiological data within a first time period using a photoplethysmography (PPG) sensor; detect a user's second physiological data at rest using an electrocardiogram (ECG) sensor; and detect a third physiological data after exercise using an ECG sensor. The processing module is used to: display the vascular health detection result, which is determined based on the first, second, and third physiological data.

[0081] In conjunction with the fourth aspect, in some implementations of the fourth aspect, before displaying the detection results of vascular health, the processing module is further configured to: detect a reference scenario and / or a reference physiological condition, the reference scenario being associated with cardiovascular disease, the reference physiological condition being used to indicate an abnormality in the fourth physiological data associated with cardiovascular disease; detect a fifth physiological data when the user is in the reference scenario; and / or, detect the fifth physiological data when the user is in the reference physiological condition; and determine the detection result based on the first physiological data, the second physiological data, the third physiological data, the reference scenario, the reference physiological condition, and the fifth physiological data.

[0082] In conjunction with the fourth aspect, in some implementations of the fourth aspect, before displaying the test results for vascular health, the processing module is also used to: display a third interface, which includes one or more test tasks to be completed.

[0083] In conjunction with the fourth aspect, in some implementations of the fourth aspect, when a reference scenario and / or reference physiological condition are detected, the processing module is further configured to: display a target detection task on the third interface, the target detection task being used to instruct the detection of a fifth physiological data, the fifth physiological data being used to determine the detection result; wherein the reference scenario is associated with cardiovascular disease, and the reference physiological condition is used to indicate that the fourth physiological data associated with cardiovascular disease is abnormal.

[0084] In conjunction with the fourth aspect, in some implementations of the fourth aspect, the reference scenario includes one or more of the following: the user is in a state of having finished exercising, the user is in a state of pain, the user is in a state of emotional fluctuation, the user is in a cold environment, the user is in a state of having eaten; and / or, the fourth physiological data or the fifth physiological data includes one or more of the following: physiological data detected by the ECG sensor, physiological data detected by the PPG sensor, respiratory rate, blood pressure, blood oxygen content, and pulse.

[0085] In one possible implementation, the fourth and fifth physiological data can be the same or different.

[0086] In conjunction with the fourth aspect, in some implementations of the fourth aspect, before the second physiological data after the user's movement is obtained via the ECG sensor, the acquisition module is further configured to: detect the user's movement state; the processing module is specifically configured to: display first information when the user is in a state of completed movement, the first information being used to indicate the measurement of the third physiological data after the movement.

[0087] In conjunction with the fourth aspect, in some implementations of the fourth aspect, before displaying the vascular health test results, the processing module is further configured to: display a first interface including a questionnaire for determining the user's health information, which includes one or more of the following: gender, age, lifestyle, family medical history, personal medical history, and current physical condition; and determine the test results based on the health information, the first physiological data, the second physiological data, and the third physiological data.

[0088] In conjunction with the fourth aspect, in some implementations of the fourth aspect, before displaying the detection results of vascular health, the acquisition module is further configured to: acquire image data via an image sensor, the image data being used to determine a first symptom, the first symptom including one or more of the following: earlobe creases, nasal bridge wrinkles, abnormal facial skin color, facial edema, corneal arch, and baldness on the top of the head; the processing module is specifically configured to: determine the detection result based on the image data, the first physiological data, the second physiological data, and the third physiological data.

[0089] In conjunction with the fourth aspect, in some implementations of the fourth aspect, before displaying the detection results of vascular health, the processing module is also used to: display second information indicating insufficient wearing time.

[0090] In conjunction with the fourth aspect, in some implementations of the fourth aspect, the processing module is also used to: display third information, which indicates an extension of the wearing time, or, which indicates a re-detection.

[0091] In conjunction with the fourth aspect, in some implementations of the fourth aspect, the acquisition module is further configured to: accept the operation to initiate a new round of vascular health detection; detect the user's sixth physiological data within a second duration, which is shorter than the first duration, using the PPG sensor; detect the user's seventh physiological data in a resting state using the ECG sensor; detect the user's eighth physiological data after exercise using the ECG sensor; the processing module is further configured to: determine the results of the new round of vascular health detection based on the first physiological data, the seventh physiological data, and the eighth physiological data, if the similarity between the sixth physiological data and the first physiological data is greater than a preset threshold.

[0092] In conjunction with the fourth aspect, in some implementations of the fourth aspect, before displaying the detection results of vascular health, the processing module is further configured to: display a second interface, the second interface including the detection progress of vascular health.

[0093] In conjunction with the fourth aspect, in some implementations of the fourth aspect, the second interface includes fourth information and / or fifth information. The fourth information is used to indicate that the wearing process during the first time period meets the preset requirements, and the fifth information is used to indicate that the wearing process during the second time period does not meet the preset requirements. The first duration includes the first time period and / or the second time period.

[0094] In conjunction with the fourth aspect, in some implementations of the fourth aspect, the first duration includes multiple effective measurement periods, wherein the effective wearing duration within the effective measurement period is greater than or equal to the duration threshold.

[0095] In conjunction with the fourth aspect, in some implementations of the fourth aspect, the detection result is determined based on historical data of vascular health detection results, the first physiological data, the second physiological data, and the third physiological data.

[0096] Fifthly, a wearable device is provided, comprising a processor and a memory storing computer program instructions, the processor being configured to: detect first physiological data of a user within a first duration using a photoplethysmography (PPG) sensor; detect second physiological data of the user at rest using an electrocardiogram (ECG) sensor; detect third physiological data of the user after exercise using an ECG sensor; and display a vascular health detection result, the detection result being determined based on the first, second, and third physiological data.

[0097] In conjunction with the fifth aspect, in some implementations of the fifth aspect, before displaying the detection results for vascular health, the processor is further configured to: detect a reference scenario and / or a reference physiological condition, the reference scenario being associated with cardiovascular disease, the reference physiological condition being used to indicate an abnormality in a fourth physiological data associated with cardiovascular disease; detect a fifth physiological data when the user is in the reference scenario; and / or, detect the fifth physiological data when the user is in the reference physiological condition; and determine the detection result based on the first physiological data, the second physiological data, the third physiological data, the reference scenario, the reference physiological condition, and the fifth physiological data.

[0098] In conjunction with the fifth aspect, in some implementations of the fifth aspect, before displaying the detection results of vascular health, the processor is also used to: display a third interface, which includes one or more detection tasks to be completed.

[0099] In conjunction with the fifth aspect, in some implementations of the fifth aspect, when a reference scenario and / or reference physiological condition are detected, the processor is further configured to: display a target detection task on the third interface, the target detection task being used to instruct the detection of fifth physiological data, the fifth physiological data being used to determine the detection result; wherein the reference scenario is associated with cardiovascular disease, and the reference physiological condition is used to indicate that a fourth physiological data associated with cardiovascular disease is abnormal.

[0100] In conjunction with the fifth aspect, in some implementations of the fifth aspect, the reference scenario includes one or more of the following: the user is in a state of having finished exercising, the user is in a state of pain, the user is in a state of emotional fluctuation, the user is in a cold environment, the user is in a state of having eaten; and / or, the fourth physiological data or the fifth physiological data includes one or more of the following: physiological data detected by the ECG sensor, physiological data detected by the PPG sensor, respiratory rate, blood pressure, blood oxygen content, and pulse.

[0101] In one possible implementation, the fourth and fifth physiological data can be the same or different.

[0102] In conjunction with the fifth aspect, in some implementations of the fifth aspect, prior to the second physiological data obtained after the user's movement via the ECG sensor, the processor is further configured to: detect the user's movement state; and, when the user is in a state of completed movement, display first information indicating the measurement of the third physiological data after the movement.

[0103] In conjunction with the fifth aspect, in some implementations of the fifth aspect, before displaying the test results for vascular health, the processor is further configured to: display a first interface including a questionnaire for determining a user's health information, the health information including one or more of the following: gender, age, lifestyle, family medical history, personal medical history, and current physical condition; and determine the test results based on the health information, the first physiological data, the second physiological data, and the third physiological data.

[0104] In conjunction with the fifth aspect, in some implementations of the fifth aspect, before displaying the detection results of vascular health, the processor is further configured to: acquire image data via an image sensor, the image data being used to determine a first symptom, the first symptom including one or more of the following: earlobe creases, nasal bridge wrinkles, abnormal facial skin color, facial edema, corneal arch, and baldness on the top of the head; and determine the detection results based on the image data, the first physiological data, the second physiological data, and the third physiological data.

[0105] In conjunction with the fifth aspect, in some implementations of the fifth aspect, the processor is also used to: display second information, which indicates insufficient wearing time, before displaying the detection results of vascular health.

[0106] In conjunction with the fifth aspect, in some implementations of the fifth aspect, the processor is also used to: display third information indicating an extension of the wearing time, or to indicate a re-detection.

[0107] In conjunction with the fifth aspect, in some implementations of the fifth aspect, the processor is further configured to: accept an operation to initiate a new round of vascular health detection; detect the user's sixth physiological data via the PPG sensor within a second duration, the second duration being shorter than the first duration; detect the user's seventh physiological data in a resting state via the ECG sensor; detect the user's eighth physiological data after exercise via the ECG sensor; and, if the similarity between the sixth physiological data and the first physiological data is greater than a preset threshold, determine the result of the new round of vascular health detection based on the first physiological data, the seventh physiological data, and the eighth physiological data.

[0108] In conjunction with the fifth aspect, in some implementations of the fifth aspect, before displaying the detection results of vascular health, the processor is also configured to: display a second interface including the detection progress of vascular health.

[0109] In conjunction with the fifth aspect, in some implementations of the fifth aspect, the second interface includes fourth information and / or fifth information, the fourth information being used to indicate that the wearing process during the first time period meets the preset requirements, and the fifth information being used to indicate that the wearing process during the second time period does not meet the preset requirements, and the first duration including the first time period and / or the second time period.

[0110] In conjunction with the fifth aspect, in some implementations of the fifth aspect, the first duration includes multiple effective measurement periods, wherein the effective wearing duration within the effective measurement period is greater than or equal to the duration threshold.

[0111] In conjunction with the fifth aspect, in some implementations of the fifth aspect, the detection result is determined based on historical data of vascular health detection results, the first physiological data, the second physiological data, and the third physiological data.

[0112] In a sixth aspect, a device for vascular health detection is provided, the device comprising an acquisition module and a processing module, the acquisition module being configured to: acquire a user's heart rate information and / or electrocardiogram information; the processing module being configured to: display a first interface indicating that the user has arrhythmia and / or an abnormal electrocardiogram; perform a first operation to determine whether the user has a first symptom, the first symptom indicating that the user has cardiac arrest; and, if the user has the first symptom, display a second interface indicating that the user has a risk of sudden cardiovascular disease.

[0113] In conjunction with the sixth aspect, in some implementations of the sixth aspect, before performing the first operation, the processing module is further configured to: determine whether the user has experienced a second symptom based on the heart rate information; and if the user has experienced the second symptom, display a third interface that indicates to the user that the second symptom has occurred.

[0114] In conjunction with the sixth aspect, in some implementations of the sixth aspect, the acquisition module is specifically used to: detect the user's first physiological data using a photoplethysmography (PPG) sensor in the target scenario, the first physiological data being used to determine the heart rate information; and / or, in the target scenario, detect the user's second physiological data using an electrocardiogram (ECG) sensor, the second physiological data being used to determine the electrocardiogram information.

[0115] In one possible implementation, the target scenario includes: the user is in a static state and / or the user is in pain.

[0116] In conjunction with the sixth aspect, in some implementations of the sixth aspect, the processing module is specifically used to: measure the user's third physiological data, which includes one or more of the following: respiratory rate, blood pressure, pulse, or blood oxygen content, and the first symptom includes the third physiological data meeting preset conditions; the method further includes: displaying a fourth interface, which includes the measurement results of the third physiological data.

[0117] In conjunction with the sixth aspect, in some implementations of the sixth aspect, the processing module is also used to: perform an emergency call operation when the user exhibits the first symptom.

[0118] In a seventh aspect, a wearable device is provided, including a processor and a memory, the memory storing computer program instructions, the processor being configured to: acquire a user's heart rate information and / or electrocardiogram information; display a first interface for indicating that the user has arrhythmia and / or electrocardiogram abnormality; perform a first operation for determining whether the user has a first symptom, the first symptom indicating that the user has cardiac arrest; and, if the user has the first symptom, display a second interface for indicating that the user has a risk of sudden cardiovascular disease.

[0119] In conjunction with the seventh aspect, in some implementations of the seventh aspect, before performing the first operation, the processor is further configured to: determine whether the user has experienced a second symptom based on the heart rate information; and if the user has experienced the second symptom, display a third interface for indicating that the user has experienced the second symptom.

[0120] In conjunction with the seventh aspect, in some implementations of the seventh aspect, the processor is specifically used to: detect a user's first physiological data using a photoplethysmography (PPG) sensor in the target scenario, the first physiological data being used to determine the heart rate information; and / or, in the target scenario, detect a user's second physiological data using an electrocardiogram (ECG) sensor, the second physiological data being used to determine the electrocardiogram information.

[0121] In one possible implementation, the target scenario includes: the user is in a static state and / or the user is in pain.

[0122] In conjunction with the seventh aspect, in certain implementations of the seventh aspect, the processor is specifically used to: measure a user's third physiological data, which includes one or more of the following: respiratory rate, blood pressure, pulse, or blood oxygen content, and the first symptom includes the third physiological data meeting preset conditions; the method further includes: displaying a fourth interface, which includes the measurement results of the third physiological data.

[0123] In conjunction with the seventh aspect, in some implementations of the seventh aspect, the processor is also used to: perform an emergency call operation in the event that the user exhibits the first symptom.

[0124] Eighthly, an apparatus for vascular health detection is provided, the apparatus comprising an acquisition module and a processing module, the acquisition module being configured to: acquire first data, the first data being used to indicate a first symptom, the first symptom being associated with cardiovascular disease; the processing module being configured to: output a vascular health detection result, the detection result being used to indicate the probability of having the cardiovascular disease, the detection result being determined based on the first data; wherein the first data includes detection data over multiple measurement periods.

[0125] In conjunction with the eighth aspect, in some implementations of the eighth aspect, before outputting the vascular health test result, the acquisition module is further configured to: acquire the user's health information, which includes one or more of the following: gender, age, lifestyle, family medical history, personal medical history, and current physical condition; and determine the test result based on the first data and the health information.

[0126] In conjunction with the eighth aspect, in some implementations of the eighth aspect, the first data includes the detection data under a reference scenario, which includes one or more of the following: exercise scenario, sleep scenario, user in pain state, user in emotional fluctuation state, user in cold environment, user in post-eating state.

[0127] In conjunction with the eighth aspect, in some implementations of the eighth aspect, the first symptom includes one or more of the following: arrhythmia, abnormal facial features, atrial fibrillation, abnormal blood pressure, abnormal blood oxygen content, sleep apnea syndrome, and abnormal cardiac output.

[0128] In a ninth aspect, an electronic device is provided, comprising a processor and a memory storing computer program instructions, the processor being configured to: acquire first data indicating a first symptom associated with cardiovascular disease; output a vascular health test result indicating the probability of developing cardiovascular disease, the test result being determined based on the first data; wherein the first data includes test data over multiple measurement periods.

[0129] In conjunction with the ninth aspect, in some implementations of the ninth aspect, before outputting the vascular health test result, the processor is further configured to: acquire the user's health information, which includes one or more of the following: gender, age, lifestyle, family medical history, personal medical history, and current physical condition; and determine the test result based on the first data and the health information.

[0130] In conjunction with the ninth aspect, in some implementations of the ninth aspect, the first data includes the detection data under a reference scenario, which includes one or more of the following: exercise scenario, sleep scenario, user in pain state, user in emotional fluctuation state, user in cold environment, user in post-eating state.

[0131] In conjunction with the ninth aspect, in some implementations of the ninth aspect, the first symptom includes one or more of the following: arrhythmia, abnormal facial features, atrial fibrillation, abnormal blood pressure, abnormal blood oxygen content, sleep apnea syndrome, and abnormal cardiac output.

[0132] In a tenth aspect, a method for detecting vascular health is provided, applied to a wearable device. The method includes: displaying a first interface for indicating that a user has a first symptom; performing a first operation for determining whether the user has a second symptom; and displaying a second interface when the user has a second symptom, the second interface indicating that the user has a risk of sudden cardiovascular disease; wherein the risk of the user having cardiovascular disease when the first symptom is present is lower than the risk of the user having cardiovascular disease when the second symptom is present.

[0133] In conjunction with the tenth aspect, in some implementations of the tenth aspect, before performing the first operation, the method further includes performing a second operation to determine whether the user has a third symptom, wherein the user's risk of having cardiovascular disease is higher than the user's risk of having cardiovascular disease when the third symptom is present, but lower than the user's risk of having cardiovascular disease when the first symptom is present.

[0134] In conjunction with the tenth aspect, in some implementations of the tenth aspect, the first symptom is determined based on the user's heart rate information and / or electrocardiogram information.

[0135] In conjunction with the tenth aspect, in some implementations of the tenth aspect, the first symptom includes arrhythmia and / or electrocardiogram abnormalities.

[0136] In conjunction with the tenth aspect, in some implementations of the tenth aspect, the second symptom includes cardiac arrest.

[0137] Eleventhly, a device for vascular health detection is provided, the device including a processing module, the processing module being configured to: display a first interface for indicating to a user the presence of a first symptom; perform a first operation for determining whether the user has a second symptom; and, if the user has a second symptom, display a second interface for indicating to the user the risk of sudden cardiovascular disease; wherein the risk of the user having cardiovascular disease when the first symptom is present is lower than the risk of the user having cardiovascular disease when the second symptom is present.

[0138] In conjunction with the eleventh aspect, in some implementations of the eleventh aspect, before performing the first operation, the processing module is further configured to: perform a second operation, the second operation being configured to determine whether the user has a third symptom, wherein the user's risk of having cardiovascular disease is higher than the user's risk of having cardiovascular disease when the third symptom is present, but lower than the user's risk of having cardiovascular disease when the first symptom is present.

[0139] In conjunction with the eleventh aspect, in some implementations of the eleventh aspect, the first symptom is determined based on the user's heart rate information and / or electrocardiogram information.

[0140] In conjunction with the eleventh aspect, in some implementations of the eleventh aspect, the first symptom includes arrhythmia and / or electrocardiogram abnormalities.

[0141] In conjunction with the eleventh aspect, in some implementations of the eleventh aspect, the second symptom includes cardiac arrest.

[0142] In a twelfth aspect, an electronic device is provided, the device including a processing module, the electronic device including a processor and a memory, the memory storing computer program instructions, the processor being configured to: display a first interface for indicating to a user the presence of a first symptom; perform a first operation for determining whether the user has a second symptom; and, in the event of the user having a second symptom, display a second interface for indicating to the user the risk of sudden cardiovascular disease; wherein the risk of the user having cardiovascular disease in the presence of the first symptom is lower than the risk of the user having cardiovascular disease in the presence of the second symptom.

[0143] In conjunction with the twelfth aspect, in some implementations of the twelfth aspect, before performing the first operation, the processor is further configured to: perform a second operation to determine whether the user has a third symptom, in which the user has a higher risk of cardiovascular disease than in which the user has a first symptom, but a lower risk than in which the user has a second symptom.

[0144] In conjunction with the twelfth aspect, in some implementations of the twelfth aspect, the first symptom is determined based on the user's heart rate information and / or electrocardiogram information.

[0145] In conjunction with the twelfth aspect, in some implementations of the twelfth aspect, the first symptom includes arrhythmia and / or electrocardiogram abnormalities.

[0146] In conjunction with the twelfth aspect, in some implementations of the twelfth aspect, the second symptom includes cardiac arrest.

[0147] In a thirteenth aspect, a computer program product is provided, comprising computer program code that, when executed on a computer, causes the methods in the first aspect and any possible implementation thereof to be executed, or causes the methods in the second aspect and any possible implementation thereof to be executed, or causes the methods in the third aspect and any possible implementation thereof to be executed, or causes the methods in the tenth aspect and any possible implementation thereof to be executed.

[0148] In a fourteenth aspect, a computer-readable storage medium is provided that stores computer program code, which, when executed on a computer, causes the methods in the first aspect and any possible implementation thereof to be executed, or causes the methods in the second aspect and any possible implementation thereof to be executed, or causes the methods in the third aspect and any possible implementation thereof to be executed, or causes the methods in the tenth aspect and any possible implementation thereof to be executed.

[0149] In a fifteenth aspect, a chip is provided, including a processor for reading instructions stored in a memory, wherein when the processor executes the instructions, the chip implements the method of the first aspect and any possible implementation thereof, or implements the method of the second aspect and any possible implementation thereof, or implements the method of the third aspect and any possible implementation thereof, or implements the method of the tenth aspect and any possible implementation thereof. Attached Figure Description

[0150] Figure 1 This is a schematic diagram of the hardware architecture of an electronic device provided in an embodiment of this application.

[0151] Figure 2 This is a schematic diagram of the software architecture of an electronic device provided in an embodiment of this application.

[0152] Figures 3 to 5 This is a schematic diagram of a user interface for initiating a vascular health detection according to an embodiment of this application.

[0153] Figure 6 and Figure 7 This is a schematic diagram of the user interface of the questionnaire provided in the embodiments of this application.

[0154] Figures 8 to 14 This is a schematic diagram of the user interface of the electrocardiogram measurement method provided in the embodiments of this application.

[0155] Figures 15 to 20 This is a schematic diagram of the user interface for a physiological data measurement scenario provided in an embodiment of this application.

[0156] Figures 21 to 24 This is a schematic diagram of a user interface for monitoring the progress of vascular health detection, provided in an embodiment of this application.

[0157] Figures 25 to 31 This is a schematic diagram of the user interface for the vascular health detection results provided in the embodiments of this application.

[0158] Figure 32 This is a schematic diagram of another user interface for initiating vascular health detection provided in an embodiment of this application.

[0159] Figure 33 This is a schematic diagram of the detection results of arrhythmia provided in the embodiments of this application.

[0160] Figure 34 This is a schematic diagram of the user interface of a physiological data detection method provided in an embodiment of this application.

[0161] Figure 35 This is a schematic diagram of the user interface of another physiological data detection method provided in the embodiments of this application.

[0162] Figure 36 This is a schematic diagram of the user interface of another physiological data detection method provided in the embodiments of this application.

[0163] Figure 37 This is a schematic diagram of the user interface for the respiratory rate measurement results provided in the embodiments of this application.

[0164] Figure 38 This is a schematic diagram of the user interface for blood pressure measurement results provided in an embodiment of this application.

[0165] Figure 39 and Figure 40 This is a schematic diagram of the user interface for the vascular health detection results provided in the embodiments of this application.

[0166] Figure 41 This is a schematic diagram of a method for detecting vascular health provided in an embodiment of this application.

[0167] Figure 42 and Figure 43 This application provides an assessment model for determining the detection results of vascular health.

[0168] Figure 44 This is a schematic diagram of another method for detecting vascular health provided in the embodiments of this application.

[0169] Figure 45 This is a schematic diagram of another method for detecting vascular health provided in the embodiments of this application.

[0170] Figure 46 This is a schematic diagram of an image data processing method provided in an embodiment of this application.

[0171] Figure 47 This is a schematic diagram of a vascular health detection device provided in an embodiment of this application.

[0172] Figure 48 This is a schematic diagram of an electronic device provided in an embodiment of this application. Detailed Implementation

[0173] The technical solutions in this application will now be described with reference to the accompanying drawings.

[0174] The terminology used in the following embodiments is for the purpose of describing particular embodiments only and is not intended to be limiting of this application. As used in the specification and appended claims of this application, the singular expressions “a,” “an,” “the,” “the,” “the,” and “this” are intended to also include expressions such as “one or more,” unless the context clearly indicates otherwise. It should also be understood that in the following embodiments of this application, “at least one” and “one or more” refer to one, two, or more than two. The term “and / or” is used to describe the relationship between related objects, indicating that three relationships may exist; for example, A and / or B can indicate: A alone, A and B simultaneously, or B alone, where A and B can be singular or plural. The character “ / ” generally indicates that the preceding and following related objects are in an “or” relationship.

[0175] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0176] The methods provided in this application can be applied to electronic devices such as mobile phones, tablets, wearable devices, in-vehicle devices, augmented reality (AR) / 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.

[0177] 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.

[0178] 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.

[0179] 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."

[0180] 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).

[0181] 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.

[0182] 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.

[0183] 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.

[0184] 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.

[0185] 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.

[0186] 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.

[0187] 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.

[0188] 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.

[0189] 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.

[0190] 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.

[0191] 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.

[0192] 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.

[0193] The wireless communication module 160 can provide solutions for wireless communication applications on the electronic device 100, including wireless local area networks (WLANs) (such as wireless fidelity (Wi-Fi) networks), Bluetooth (BT), global navigation satellite system (GNSS), frequency modulation (FM), near field communication (NFC), and infrared (IR) technologies. 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 signals, 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.

[0194] 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.

[0195] 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.

[0196] Electronic device 100 can perform shooting functions through ISP, camera 193, video codec, GPU, display 194 and application processor.

[0197] 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 optimization of image noise, brightness, and skin tone. 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.

[0198] 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.

[0199] 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.

[0200] 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.

[0201] 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, MPEG 2, MPEG 3, MPEG 4, etc.

[0202] 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.

[0203] 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.

[0204] 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.

[0205] 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.

[0206] 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.

[0207] 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.

[0208] 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 the layered architecture Android system as an example to exemplify the software structure of electronic device 100.

[0209] 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 Android 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 may include a series of application packages.

[0210] 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.

[0211] 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.

[0212] 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.

[0213] 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.

[0214] 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.

[0215] 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.

[0216] The phone manager is used to provide communication functions for electronic device 100. For example, it manages call status (including connection and disconnection).

[0217] The file explorer provides applications with various resources, such as localized strings, icons, images, layout files, video files, and more.

[0218] 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.

[0219] The Android runtime consists of core libraries and a virtual machine. The Android runtime is responsible for scheduling and managing the Android system.

[0220] 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.

[0221] 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.

[0222] 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.

[0223] The Surface Manager is used to manage the display subsystem and provides the blending of 2D and 3D layers for multiple applications.

[0224] 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.

[0225] The 3D graphics processing library is used to implement 3D graphics drawing, image rendering, compositing, and layer processing.

[0226] A 2D graphics engine is a graphics engine for 2D drawing.

[0227] 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.

[0228] It should be understood that the technical solutions in the embodiments of this application can be used in systems such as Android, iOS, and HarmonyOS.

[0229] Coronary heart disease, hypertension, heart failure, stroke, rheumatic heart disease, and congenital heart disease are all cardiovascular diseases. Long-term unhealthy lifestyle and dietary habits may trigger these diseases, and if patients with these diseases do not receive timely medical attention during a sudden attack, their lives may be in serious danger.

[0230] To improve the efficiency and accuracy of cardiovascular disease detection and enable users to better understand their own health conditions, providing early warnings for potential coronary heart disease and other conditions, this application provides a method for vascular health detection. This method can be applied to wearable devices, which, through daily wear, can monitor the user's physical condition over a long period and provide timely warnings of cardiovascular disease risks. The following description illustrates the process of a user conducting vascular health detection using an electronic device.

[0231] It should be noted that the vascular health detection method provided in this application embodiment can be applied to both patients suspected of having cardiovascular disease and patients with cardiovascular disease.

[0232] As an example, for patients suspected of having cardiovascular disease, the vascular health detection method provided in this application can assess their risk of having cardiovascular disease. For instance, it can assess whether a patient suspected of having cardiovascular disease actually has cardiovascular disease, and the severity of the disease.

[0233] As an example, for patients with cardiovascular disease, the vascular health detection method provided in this application embodiment can assess their current cardiovascular disease status. For example, it can assess whether the cardiovascular disease patient's condition has improved, the extent of improvement, whether it has worsened, and the degree of worsening. As one implementation, in the process of detecting the vascular health of a cardiovascular disease patient, the degree of vascular blockage before the detection can be obtained first. Based on this, the degree of vascular blockage determined by the detection process is output. Combining the vascular blockage degrees before and after the detection, it can be determined whether the patient's condition has improved, the extent of improvement, whether it has worsened, and the degree of worsening.

[0234] The detection method provided in this application can be applied to wearable devices such as wristbands, watches, smart glasses, and smart rings, as well as portable devices such as mobile phones and tablets. It can also be applied to device groups or pairs comprising multiple devices, including both portable and wearable devices. In other words, the relevant steps of the detection method in the following examples can be performed individually by the aforementioned wearable or portable devices, or jointly by both. The following examples primarily use a watch 20 as the wearable device for illustration.

[0235] like Figure 3 The image shows the interface 201A of the watch 20, which can be used to initiate the vascular health detection process. In other words, in response to an operation on this interface 201A, the watch 20 can initiate a vascular health detection process for the user.

[0236] For example, interface 201A may include control 301, and watch 20 may detect the user's vascular health in response to the selection of control 301A.

[0237] For example, interface 201A can display historical testing information for vascular health. This historical testing information may include the results of historical tests, and may also include information such as the time of the historical tests and / or the users of the historical tests.

[0238] As one implementation, interface 201A may include information 401A, which may be the aforementioned historical detection information.

[0239] For example, 401A could be "No data available," in which case it indicates that the user has not yet undergone vascular health testing. Another example is "June 1st, low risk," indicating that the user's vascular health test result on June 1st was "low risk." Yet another example is "July 2nd, no risk, User A," indicating that User A's vascular health test result on July 2nd was "no risk."

[0240] like Figure 4 The image shows the interface 201B of the watch 20, which can be used to initiate the vascular health detection process.

[0241] Similar to control 301A in the aforementioned interface 201A, interface 201B may also include control 301B. In response to the selection of control 301B, watch 20 can detect the user's vascular health.

[0242] For example, interface 201B may also include information 401B, which may include historical detection information of vascular health.

[0243] For example, this 401B information may include textual information such as "low risk, September 6", "medium risk, October 22", "high risk, November 12", etc.

[0244] For example, the information 401B may also include detection prompt information, which can be used to remind the user to repeat the vascular health test within a predetermined period of time.

[0245] For example, the 401B information may include messages such as “Please have your vascular health checked again before December 6th,” “Please have your coronary heart disease risk assessment again before November 22nd,” and “Please have your vascular health checked again before December 12th.”

[0246] As an example, the aforementioned predetermined duration can be determined based on the user's most recent vascular health test results. For instance, if the most recent vascular health test results indicate that the user's vascular health is poor (e.g., a high risk of coronary heart disease), the aforementioned predetermined duration can be shorter; if the most recent vascular health test results indicate that the user's vascular health is good (e.g., a low risk of coronary heart disease), the aforementioned predetermined duration can be longer.

[0247] For example, if the user's risk level for coronary heart disease is low, the aforementioned predetermined duration can be a longer duration such as 2 months or 3 months; if the user's risk level for coronary heart disease is medium, the aforementioned predetermined duration can be a shorter duration such as 15 days or 1 month; if the user's risk level for coronary heart disease is high, the aforementioned predetermined duration can be a shorter duration such as 7 days, 15 days or 1 month.

[0248] In one implementation, the watch 20, or an electronic device capable of establishing a communication connection with the watch 20, can remind the user to perform vascular health checks once or multiple times within the aforementioned predetermined time period. For example, reminding the user once every 3 days.

[0249] As an implementation, in response to a click on the area containing information 401A or 401B, watch 20 can display a user interface containing detailed historical detection information. This user interface includes the historical detection results of the user's vascular health checks using watch 20. A detailed explanation of the vascular health detection results will be provided later and will not be elaborated upon here.

[0250] Unlike initiating vascular health detection via watch 20, in some examples, users can also control watch 20 to perform vascular health detection via other electronic devices. Here, "other electronic devices" can be understood as electronic devices capable of establishing a communication connection with watch 20, including electronic devices that have previously established a communication connection with watch 20 and those that have already established a communication connection. Examples include portable electronic devices such as mobile phones and tablets; wearable devices such as smart glasses and smart rings; and electronic devices in home settings such as smart speakers and smart screens. This application does not limit the types of electronic devices that can be used to control watch 20 to perform vascular health detection; the following explanation uses mobile phone 30 as an example.

[0251] like Figure 5 The image shows the interface 201C of the mobile phone 30, which can be used to initiate the vascular health detection process. As an example, interface 201C can be the interface of a "Health" application, which can be used to control the watch 20 to perform one or more physiological data (such as electrocardiogram, respiratory rate, blood pressure, blood oxygen content, etc.) detection, and the "Health" application can also be used to view the results of the aforementioned physiological data detection.

[0252] For example, the interface 201C may include a control 301C, which, when selected by the user, allows the mobile phone 30 to control the watch 20 to perform vascular health detection. For instance, in response to the user tapping the control 301C, the mobile phone 30 may send an instruction message to the watch 20, which can be used to instruct the watch 20 to perform the vascular health detection operation.

[0253] For example, the interface 201C may also include information 401C, which may include historical detection information of vascular health.

[0254] For example, the 401C information could include "medium risk, September 14", "low risk, July 23", "medium risk, July 14", etc.

[0255] For example, the information 401C may also include detection prompt information, which can be used to remind the user to repeat the vascular health test within a predetermined period of time.

[0256] For example, the interface 201C may also include one or more of the following: basic information of the test results, information for interpreting the test results for vascular health, and suggestions for improving the test results. This part will be described in detail later and will not be repeated here.

[0257] In one possible implementation, during a new round of vascular health testing, the watch 20 can combine the user's previous vascular health test results to output the current test results. In outputting the new round of vascular health test results, the watch 20 can analyze changes in the user's cardiovascular status based on historical test results, thereby outputting more accurate vascular health test results.

[0258] In some examples, watch 20 can output the user's vascular health test results based on the user's physiological data. In other words, the user's vascular health test results can be determined based on the user's physiological data.

[0259] For example, the physiological data here may include one or more of the following: heart rate, heart rate variability, blood oxygen saturation, blood pressure, electrocardiogram, facial features (such as earlobe creases, nasal wrinkles, facial skin color, etc.), respiratory rate, cardiac output, etc.

[0260] As one implementation, the aforementioned physiological data can be detected by one or more of the following sensors: PPG sensor, electrocardiogram sensor, skin conductance sensor, image sensor, etc.

[0261] In some examples, the watch 20 can also output the user's vascular health test results by combining the user's health information. In other words, the user's vascular health test results can be determined based on the user's physiological data and health information.

[0262] Here, the user's health information is related to cardiovascular disease. As an example, health information may include one or more of the following: basic personal information (such as age, gender, etc.), lifestyle (such as dietary habits, exercise frequency), family medical history, personal medical history, and current physical condition.

[0263] As one implementation, the Watch 20 can obtain users' health information through questionnaires filled out by the users.

[0264] One possible scenario is that the user is using the watch 20 for the first time to check their vascular health, or that the watch 20 cannot obtain the user's health information before filling out the questionnaire. In this case, the content of the questionnaire can be more detailed. For ease of distinction, this type of questionnaire can be called Questionnaire Qa.

[0265] In some examples, the questionnaire Qa can be used to obtain one or more of the following user information: family history of cardiovascular disease, prevalence of hyperlipidemia, prevalence of hypertension, history of percutaneous coronary intervention (PCI), use of antihypertensive medication, smoking habits, drinking habits, etc.

[0266] In some contexts, a survey questionnaire (Qa) can also be called a chronic disease and lifestyle survey questionnaire.

[0267] As an example, watch 20 can display Figure 6 As shown in interface 202, users can fill out the aforementioned questionnaire Qa on this interface 202.

[0268] One possibility is that the user is using the watch 20 to check their vascular health for the second or third time (e.g., the second or third time), or that the watch 20 can obtain the user's health information before the user fills out the questionnaire. In this case, the content of the questionnaire can be more concise. For ease of distinction, this type of questionnaire can be called Questionnaire Qb.

[0269] In some examples, the questionnaire Qb can be used to obtain one or more of the following user information: chest pain (whether chest pain occurs, duration of chest pain, frequency of chest pain, etc.), chest tightness (whether chest tightness occurs, duration of chest tightness, frequency of chest tightness, etc.), difficulty breathing, palpitations, fainting, exercise, duration of exercise, etc.

[0270] In some scenarios, a survey questionnaire (Qb) can also be called a user status questionnaire.

[0271] As an example, watch 20 can display Figure 7 As shown in interface 203, users can fill out the aforementioned questionnaire Qb on this interface 203.

[0272] After the user completes the above questionnaire Qa or Qb, the watch 20 can save the results. Within a preset time period (e.g., 1 day, 3 days, etc.), when the user uses the watch 20 to check their vascular health again, the watch 20 can directly determine the user's health information based on the saved questionnaire results, and the user does not need to fill out the above questionnaire again.

[0273] After completing the above questionnaire, watch 20 can prompt the user to perform an electrocardiogram (ECG) measurement. For example, watch 20 can display the following: Figure 8 The interface 204 shown may include controls 302 and 303. In response to the user's selection of control 302, the watch 20 may begin to perform an electrocardiogram (ECG) measurement for the user; in response to the user's selection of control 303, the watch 20 may cancel the ECG measurement for the user.

[0274] As an implementation, when the user selects control 303 on interface 204, watch 20 can determine that the user has cancelled using watch 20 for electrocardiogram measurement. To improve the efficiency of watch 20 in detecting cardiovascular diseases, watch 20 can save the results of completed questionnaires and use them in subsequent vascular health monitoring processes. In other words, watch 20 can save the results of completed questionnaires even without performing an electrocardiogram measurement.

[0275] In some examples, during an electrocardiogram (ECG) measurement for a user, watch 20 can display, for example... Figure 9The interface 205A shown may include electrocardiogram measurement information.

[0276] As an example, the measurement information of an electrocardiogram (ECG) may include the waveform characteristics of the ECG, which may include ST segment morphology and / or T wave morphology, such as ST segment depression, ST segment elevation, T wave inversion, T wave peaking, J point deviation, etc.

[0277] As an example, electrocardiogram (ECG) measurement information may include the measurement time of the ECG.

[0278] As an example, the electrocardiogram (ECG) measurement information may also include information 402A, which can be used to guide the user to perform ECG measurements correctly.

[0279] In some examples, during a round of vascular health monitoring, watch 20 can perform multiple electrocardiogram (ECG) measurements on the user to obtain ECG information under different activity states. For example, ECG information at rest and ECG information after exercise.

[0280] One feasible approach is that the watch 20 can detect the user's motion status through a motion sensor. When the user is stationary, the watch 20 can prompt the user to perform an electrocardiogram (ECG) measurement. When the user is in a state of exercise, the watch 20 can also prompt the user to perform an ECG measurement.

[0281] As implemented above, after the user completes... Figure 6 or Figure 7 In the case of the questionnaire shown, watch 20 can prompt the user to measure an electrocardiogram (ECG) at rest.

[0282] Here, the resting state refers to a relatively calm state in which the body does not engage in physical activity. In this state, the body's energy consumption is mainly used to maintain basic life functions. In the resting state, the body's various systems operate smoothly, and energy consumption is relatively low, mainly used to maintain basic physiological functions such as body temperature, respiration, and heartbeat.

[0283] One possibility is that the user failed to complete the electrocardiogram measurement. In this case, the watch 20 can display information indicating the measurement failure.

[0284] like Figure 10 The interface 205B shown is a schematic diagram of a measurement result of an electrocardiogram (ECG) measurement performed by the watch 20. The interface 205B may include information 402B, which can be used to indicate that the ECG measurement failed, and the information 402B can also be used to indicate the reason for the ECG measurement failure.

[0285] For example, message 402B could include text similar to "Measurement failed. Please wear your watch and ensure your finger is in contact with the electrode." Alternatively, message 402B could include text similar to "Measurement failed. Please remain still and try again by touching the electrode with your finger." Yet another example is that message 402B could include text similar to "Measurement failed. Poor signal quality. Please touch the electrode with your finger to measure again. If your skin is dry, you can wipe your finger with a small amount of water and try again."

[0286] One possibility is that before the user performs an electrocardiogram (ECG) measurement, the watch 20 can determine whether the user's operation meets the measurement requirements and whether the state of the electrodes used to measure the ECG meets the measurement requirements. If the user's operation does not meet the measurement requirements and / or the state of the electrodes does not meet the measurement requirements, the watch 20 can display information to indicate that the measurement should be stopped.

[0287] like Figure 11 The interface 205C shown is a schematic diagram of another measurement result of the watch 20 performing an electrocardiogram measurement. The interface 205C may include information 402C, which can be used to indicate that the electrocardiogram measurement has stopped. The information 402C can also be used to indicate the reason for stopping the electrocardiogram measurement.

[0288] For example, message 402C could include text like "Measurement stopped. To ensure accurate measurement, please touch gently and do not press the electrode forcefully." Alternatively, message 402C could include text like "Measurement stopped. The electrode appears to be dirty and cannot be measured normally. Please clean the electrode and try again."

[0289] One possibility is that the user can follow the prompts on the watch 20 to successfully complete the electrocardiogram (ECG) measurement. The watch 20 can then record the user's ECG measurement results and use them to determine the results of vascular health testing.

[0290] For example, if an electrocardiogram (ECG) measurement is successfully completed, the watch 20 can display the results of the ECG measurement.

[0291] like Figure 12 The interface 205D shown is a schematic diagram of another measurement result of the electrocardiogram (ECG) measurement performed by the watch 20. The interface 205D can include information 402D, which can be used to indicate the ECG measurement result. For example, the information 402D can be "sinus rhythm: average heart rate 80 beats / minute", etc.

[0292] In some examples, in order to more realistically record the user's condition when performing an electrocardiogram (ECG) measurement, the interface 205D may also include a control 334, which can be used to record the user's physical condition when performing an ECG measurement.

[0293] For example, in response to the user's selection of control 334, watch 20 can display as follows: Figure 13 The interface 205E shown may include one or more options 514, which can be used to indicate different physical conditions. For example, option 514 may include one or more of the following: "chest tightness", "chest pain", "palpitations", "shortness of breath", "fatigue", "poor sleep", "cold and fever", "other discomfort", "no symptoms of discomfort", etc.

[0294] For example, in response to a user selecting one or more options 514 on interface 205E and confirming, watch 20 may display as follows: Figure 14 The interface 205F shown can be regarded as an updated interface 205E. In other words, compared with interface 205E, interface 205F can also include relevant information about the user's physical condition when performing electrocardiogram measurement.

[0295] In some examples, to improve the accuracy of the detection results, the watch 20 can measure the user's physiological data in multiple scenarios. For example, the aforementioned scenarios may include sleep scenarios, exercise scenarios, when the user is in pain (e.g., experiencing chest tightness or chest pain), when the user is experiencing emotional fluctuations, when the user is in a cold environment, or when the user is in a post-eating state.

[0296] As an example, watch 20 can detect whether the user is in the aforementioned scenario. If the user is in the aforementioned scenario, watch 20 can automatically detect the user's vascular health, or watch 20 can prompt the user to perform a vascular health test.

[0297] Specifically, for physiological data that can be measured automatically by the watch 20 without requiring manual operation by the user (e.g., physiological data detected by the PPG sensor), the watch 20 can automatically measure the physiological data and record the measurement results when the user is detected in the aforementioned scenario.

[0298] As a result, the watch 20 can display text messages such as "You are currently in scene Se1. To assess your vascular health, physiological data PhDt1 will be measured soon."

[0299] For physiological data that requires manual operation by the user (e.g., physiological data detected by an ECG sensor), when the user is detected in the aforementioned scenario, the watch 20 can prompt the user to manually perform the measurement of the physiological data by displaying prompts, playing audio, or vibrating a motor, etc.

[0300] As a result, the watch 20 can display text messages such as "You are currently in scene Se2. To assess your vascular health, please complete the measurement of physiological data PhDt2 according to the prompts."

[0301] For example, such as Figure 15 As shown, watch 20 can display interface 206, which can be used to activate the watch 20's vascular health measurement function during the user's sleep. Interface 206 can include information 403, which can be used to prompt the user to measure physiological data during sleep. For example, information 403 could be "Activate sleep measurement to assess your sleep and vascular health?"

[0302] As one implementation, interface 206 may include controls 304 and 305. In response to the operation of selecting control 304, watch 20 may measure the user's physiological data during sleep, etc.; in response to the operation of selecting control 305, watch 20 may not measure the user's physiological data during sleep, etc.

[0303] For example, when sleep mode is enabled, watch 20 can prompt the user to activate the vascular health monitoring function during sleep. Figure 16 As shown, watch 20 can display interface 207, which can include information 404. This information 404 can be used to prompt the user to activate the function of measuring vascular health during sleep. For example, the information 404 could be "Sleep mode is on. Do you want to measure vascular health during sleep?"

[0304] As one implementation, interface 404 may include controls 306 and 307. In response to the operation of selecting control 306, watch 20 may measure the user's physiological data during the user's sleep, etc.; in response to the operation of selecting control 307, watch 20 may not measure the user's physiological data during the user's sleep, etc.

[0305] It should be noted that when the user selects control 305 or control 307, or when the watch 20 does not measure the user's physiological data during the user's sleep, the watch 20 can detect the user's physiological data at other times and then output the user's vascular health test results.

[0306] For example, such as Figure 17 As shown, watch 20 can display interface 208, which can be used to activate the watch 20's function of measuring vascular health before and after exercise. Interface 208 can include information 405, which can be used to prompt the user to measure physiological data before and after exercise. For example, information 405 could be "Start measuring before and after exercise to assess your exercise and vascular health?".

[0307] As one implementation, interface 208 may include controls 308 and 309. In response to the operation of selecting control 308, watch 20 may measure the user's physiological data before and after exercise; in response to the operation of selecting control 309, watch 20 may not measure the user's physiological data before and after exercise.

[0308] For example, watch 20 can detect the user's activity status through motion sensors, etc. If it detects that the user is in a warm-up state before exercise, watch 20 can prompt the user to activate the pre- and post-exercise vascular health measurement function. Figure 18 As shown, watch 20 can display interface 209, which can include information 406. This information 406 can be used to prompt the user to activate the function of measuring vascular health before and after exercise. For example, the information 406 could be, "You are detected to be warming up. Do you want to measure your vascular health before and after exercise?"

[0309] As one implementation, interface 209 may include controls 310 and 311. In response to the operation of selecting control 310, watch 20 may measure the user's physiological data before and after exercise; in response to the operation of selecting control 311, watch 20 may not measure the user's physiological data before and after exercise.

[0310] As an example, when the function of measuring vascular health before and after exercise is enabled, the watch 20 can detect the user's exercise status. When the exercise ends, the watch 20 can prompt the user to perform an ECG measurement. Alternatively, when the exercise ends and the watch detects that the user has placed their finger on the detection electrode, the watch 20 can automatically perform an ECG measurement.

[0311] For example, when the watch 20 detects that the user's exercise has ended, it can display something like this: Figure 19 The interface 210 shown can be used to prompt a user to perform an ECG measurement. As one implementation, interface 210 may include information 407, which can be used to prompt the user to measure ECG after exercise. For example, information 407 could be: "Exercise is over. Please use your right hand to lightly press the watch button (including the ECG electrode) to start the ECG measurement."

[0312] One possibility is that the user can complete the measurement of physiological data after exercise according to the prompts on interface 210, and watch 20 can then determine the user's vascular health test results based on the physiological data in this scenario. Another possibility is that the user does not complete the measurement of physiological data after exercise according to the prompts on interface 210. In this case, watch 20 can remind the user again within a preset time period (e.g., by displaying interface 210 again). If the user does not perform physiological data measurement within the preset time period, watch 20 can ignore this measurement, or in other words, not consider this exercise in the process of determining the user's vascular health test results.

[0313] It should be noted that when the user selects control 309 or control 311, or in other words, when watch 20 does not measure the user's physiological data before or after exercise, watch 20 can detect the user's physiological data at other times and then output the user's vascular health test results. For example, the user's physiological data before exercise can be regarded as the user's physiological data in a resting state. When watch 20 does not measure the user's physiological data in front of the user, watch 20 can also measure the user's physiological data in a resting state before going to sleep, after waking up, before eating, etc.

[0314] For example, watch 20 can detect whether the user is in pain through an image sensor or a skin conductance sensor, and if the user is in pain, watch 20 can prompt the user to measure the condition of their blood vessels.

[0315] For example, such as Figure 20 As shown, the watch 20 can display an interface 211, which can be used to activate the watch 20's function of measuring vascular health when the user experiences chest tightness or chest pain. This interface 211 can include information 408, which can be used to prompt the user to measure physiological data when experiencing chest tightness or chest pain. For example, the information 408 could be, "Experiencing chest tightness or chest pain? Please perform an electrocardiogram (ECG) measurement."

[0316] As one implementation, interface 211 may include controls 312 and 313. In response to the selection of control 312, watch 20 can measure the user's physiological data when the user experiences chest tightness or chest pain. For example, watch 20 may display the data mentioned above. Figure 19 The interface 210 shown is for use until the user performs an ECG measurement; in response to the operation of the selection control 313, the watch 20 does not measure the user's physiological data if the user experiences chest tightness or chest pain.

[0317] It should be noted that when the user selects the above control 313, or when the watch 20 does not measure the user's physiological data when the user is experiencing chest tightness or chest pain, the watch 20 can detect the user's physiological data in other scenarios and then output the user's vascular health test results.

[0318] For example, the watch 20 can also detect the user's heart rate, body temperature, etc. through PPG sensors, body temperature sensors, etc., to determine whether the user is experiencing emotional fluctuations, whether they are in a cold environment, or whether they have just eaten. In these situations, the watch 20 can prompt the user to perform a vascular health check, or the watch 20 can automatically perform a vascular health check.

[0319] In some examples, in order to collect physiological data related to vascular health more promptly and improve the accuracy of test results, the watch 20 can measure the user's physiological data PD2 if the user's physiological data PD1 is abnormal.

[0320] In some examples, the results of vascular health testing can be determined based on the aforementioned physiological data PD1 and / or physiological data PD2.

[0321] One possibility is that physiological data PD1 and physiological data PD2 can be the same. For example, if a user's arrhythmia is detected, the watch 20 can continuously acquire physiological data detected by the PPG sensor for a preset duration, thereby obtaining more complete heart rate information and more accurately analyzing whether the user has symptoms such as atrial fibrillation or cardiac arrest. Another example is that if the user's blood oxygen level is detected to be below a blood oxygen level threshold, the watch 20 can continuously monitor the user's blood oxygen level for a preset duration.

[0322] One possibility is that physiological data PD1 and physiological data PD2 can be different. For example, if a user's arrhythmia is detected, watch 20 can measure the user's respiratory rate, blood pressure, pulse, etc., to determine whether the user has experienced cardiac arrest. Another example is that if an abnormal blood pressure is detected, watch 20 can remind the user to perform an ECG measurement.

[0323] For example, the physiological data PD1 and physiological data PD2 mentioned above may include one or more of the following: physiological data detected by the ECG sensor, physiological data detected by the PPG sensor, respiratory rate, blood pressure, blood oxygen content, pulse, etc.

[0324] For example, if an abnormality is detected in physiological data PD1, watch 20 can add a detection task to detect physiological data PD2 during the overall process of the user's vascular health detection.

[0325] The newly added detection task can be completed promptly when the physiological data PD1 is abnormal, or it can be completed during the entire vascular health detection process without needing to be completed promptly.

[0326] For testing tasks that need to be completed promptly, the Watch 20 can perform measurements automatically, or remind the user to perform manual measurements.

[0327] In one possible implementation, for physiological data PD2 (e.g., physiological data detected by a PPG sensor) that can be automatically measured by the watch 20 without manual operation by the user, if an abnormality is detected in physiological data PD1, the watch 20 can automatically measure the physiological data PD2 and record the measurement result.

[0328] As a result, the watch 20 can display text messages such as "An abnormality in your physiological data PD1 has been detected. To assess your vascular health, a physiological data PD2 measurement will be performed soon."

[0329] In one possible implementation, for physiological data PD2 that requires manual operation by the user (e.g., physiological data detected by an ECG sensor), if an abnormality is detected in physiological data PD1, the watch 20 can prompt the user to manually complete the measurement of physiological data PD2 by displaying prompt information, playing audio, or vibrating a motor.

[0330] As a result, the watch 20 can display text messages such as "An abnormality was detected in your physiological data PD1. To assess your vascular health, please complete the measurement of physiological data PD2 according to the prompts."

[0331] For testing tasks that do not need to be completed immediately, the watch 20 can add the new testing task to the relevant interface for displaying the progress of vascular health testing, making it easy for users to view and complete the testing task.

[0332] During the vascular health monitoring process, the Watch 20 can add new testing tasks based on the actual test results. This makes the entire vascular health monitoring process more closely aligned with the user's actual physiological condition and lifestyle, leading to more accurate vascular health test results. Furthermore, for newly added testing tasks, the Watch 20 can promptly perform measurements or add them to the pending testing task list. This allows users to clearly understand the different situations and related details that occur throughout the testing process, enhancing the user experience.

[0333] This part will be explained in detail below, and will not be elaborated here.

[0334] To provide more accurate vascular health test results, the watch 20 can measure the user's physiological data over multiple measurement cycles and determine the user's vascular health status based on the physiological data obtained from these multiple measurement cycles. In other words, a single vascular health measurement process can include one or more measurement cycles.

[0335] In some examples, the measurement period mentioned above can be 24 hours, 12 hours, 18 hours, or 36 hours, etc.

[0336] In cases where a single measurement process comprises multiple measurement cycles, the watch 20 can display the progress of vascular health testing in some examples to help users understand the testing status.

[0337] For example, watch 20 can display as follows Figure 21 The interface 212 shown can display the progress of vascular health detection.

[0338] As one implementation, interface 212 may display information 409, which can be used to indicate the progress of vascular health testing. For example, information 409 may include text information such as "assessment progress 40%".

[0339] As one implementation, interface 212 can display information 410, which can be used to indicate the completed and incomplete measurement cycles during the vascular detection process.

[0340] refer to Figure 21 For example, a measurement process may consist of three measurement cycles, each lasting 24 hours. Information 410 above could show that the completed measurement cycles are 15 days, 16 days, and 17 days.

[0341] In some examples, the above information 410 can also be used to indicate the measurement cycles that meet the measurement requirements and the measurement cycles that do not meet the measurement requirements among the aforementioned completed measurement cycles.

[0342] Continue to refer to Figure 21 Of the completed measurement cycles of 15, 16 and 17, the cycles that met the measurement requirements were 15 and 16, while the cycle that did not meet the requirements was 17.

[0343] As an example, the above measurement requirement may refer to the wearing time of watch 20 being greater than or equal to a preset duration within a measurement cycle. In other words, if the wearing time of watch 20 is greater than or equal to the preset duration within a measurement cycle, watch 20 can determine that the measurement cycle is valid; if the wearing time of watch 20 is less than the preset duration within a measurement cycle, watch 20 can determine that the measurement cycle is invalid.

[0344] In one implementation, the aforementioned wearing time can include multiple time periods, which can be consecutive or discontinuous. Wearing time greater than or equal to a preset duration can be understood as the total duration accumulated from the aforementioned multiple time periods being greater than or equal to the preset duration.

[0345] As one implementation, the duration of each time segment within the aforementioned wearing time can be greater than or equal to the unit duration. In other words, if the duration of a time segment is greater than or equal to the unit duration, that time segment is a valid time segment; if the duration of a time segment is less than the unit duration, that time segment is an invalid time segment. Based on this, the aforementioned wearing time can be considered as consisting of one or more valid time segments.

[0346] As an example, the aforementioned unit duration can refer to the shortest duration for which watch 20 can collect effective physiological data. For instance, if watch 20 detects the user's heart rate using a PPG sensor, the unit duration can be understood as the shortest duration for which the data detected by the PPG sensor reflects the user's heart rate. Similarly, if watch 20 detects the user's electrocardiogram (ECG) using an ECG sensor, the unit duration can be understood as the shortest duration for which the data detected by the ECG sensor reflects the user's ECG. Likewise, if watch 20 detects whether the user is in pain using a skin conductance sensor, the unit duration can be understood as the shortest duration for which the surface electromyography (EMG) signal detected by the skin conductance sensor reflects whether the user is in pain.

[0347] Based on the above examples, it can be understood that the value of the aforementioned minimum duration is related to the performance of different sensors, the type of detection data, and detection requirements. In scenarios where multiple sensors are used simultaneously to detect a user's vascular health, the aforementioned unit duration can refer to the maximum value among multiple unit durations corresponding to each sensor. For example, in the above example, the unit duration corresponding to the PPG sensor could be 12 seconds, the unit duration corresponding to the ECG sensor could be 10 seconds, and the unit duration corresponding to the electrodermal sensor could be 15 seconds. In this case, when using these three sensors simultaneously to detect a user's vascular health, the unit duration corresponding to watch 20 can be determined to be 15 seconds.

[0348] As an example, the above measurement requirement may refer to the correct way the watch 20 is worn (e.g., tightness, position, etc.) within a measurement cycle. In other words, if the watch 20 is worn correctly within a measurement cycle, the watch 20 can determine that the measurement cycle is valid; if the watch 20 is worn incorrectly within a measurement cycle, the watch 20 can determine that the measurement cycle is invalid.

[0349] In some scenarios, a measurement cycle that meets the measurement requirements can be called a valid measurement cycle, while a measurement cycle that does not meet the requirements can be called an invalid measurement cycle. Based on this, Figure 21 In this context, the 15th and 16th can be considered valid measurement periods, while the 17th can be considered invalid measurement periods.

[0350] For example, watch 20 can display as follows Figure 22 The interface 228A shown can display the progress of vascular health detection.

[0351] As one implementation, interface 228A can display information 413A, which can be used to indicate the progress of vascular health testing. For example, information 413A can include text information such as "assessment progress 10%" or "assessment progress 90%".

[0352] As an example, information 413 can also be used to indicate the number and content of testing tasks that still need to be completed during the testing process. For example, information 413 may include text messages such as "1 task to be completed" or "ECG measurement to be completed".

[0353] As an implementation, if the information 413A does not include the content of the detection tasks that still need to be completed, the interface 228A may also include a control 331, and in response to the operation of selecting the control 331, the watch 20 may display the content of the detection tasks that still need to be completed.

[0354] As an implementation, if information 413A includes information about detection tasks that still need to be completed, interface 228A may also include control 332. In response to selecting control 332, watch 20 can perform the aforementioned detection tasks that still need to be completed. For example, the aforementioned task that still needs to be completed may be an electrocardiogram (ECG) measurement. In this case, in response to the user selecting control 332, watch 20 can begin performing an ECG measurement for the user.

[0355] As an example, in response to the user selecting control 331 on interface 228A, watch 20 can display as follows: Figure 23 The interface 228B shown can be used to display the test tasks that the watch 20 still needs to complete, and it can also be used to display the test tasks that the watch 20 has already completed.

[0356] For example, interface 228B may include information 413B, which can be used to indicate that the acquisition of test data is not yet complete, or to indicate that there are 2 days left to complete the acquisition of test data. As another example, information 413B can be used to indicate that the post-exercise electrocardiogram measurement is not yet complete.

[0357] For example, interface 228B may include information 413C, which can be used to indicate that a resting-state electrocardiogram (ECG) measurement has been completed. Information 413C may include the measurement results of the resting-state ECG (e.g., an average heart rate of 80 beats per minute). As another example, information 413C may be used to indicate that a post-exercise ECG measurement has been completed. Information 413C may include the measurement results of the post-exercise ECG (e.g., atrial fibrillation, premature ventricular contractions, average heart rate of 88 beats per minute).

[0358] In some examples, watch 20 can send information during the evaluation process to electronic devices such as mobile phone 30, so that users can view the current evaluation progress, completed testing tasks, and remaining testing tasks on their mobile phones or other electronic devices.

[0359] For example, upon receiving information from watch 20, mobile phone 30 can display as follows: Figure 24 The interface 228C may include information such as the current evaluation progress, completed testing tasks, and testing tasks that still need to be completed.

[0360] For example, interface 228C may include information 413D, which can be used to indicate the current progress of coronary artery disease assessment. For instance, information 413D may include textual information such as "46%" to indicate that the progress of coronary artery disease assessment is 46%.

[0361] For example, interface 228C may include information 413E, which can be used to indicate an incomplete testing task. For instance, information 413E can indicate that data collection is not yet complete, or that there are two days remaining to complete data collection. As another example, information 413E can indicate that a post-exercise electrocardiogram (ECG) measurement is not yet complete.

[0362] For example, interface 228C may include information 413F, which can be used to indicate that a detection task has been completed. For instance, information 413F can indicate that a resting-state electrocardiogram (ECG) measurement has been completed, and this information 413F may include the measurement results of the resting-state ECG (e.g., an average heart rate of 80 beats per minute). As another example, information 413F can indicate that a post-exercise ECG measurement has been completed, and this information 413F may include the measurement results of the post-exercise ECG (e.g., atrial fibrillation, premature ventricular contractions, average heart rate of 88 beats per minute).

[0363] Normally, such as Figure 22 The progress of vascular health testing shown or Figure 27The progress of coronary artery disease risk assessment can gradually increase as the number of tests to be performed decreases. In some examples, the aforementioned testing or assessment progress may also decrease if one or more new tests are added during the vascular health testing process or coronary artery disease risk assessment.

[0364] As an example, as mentioned earlier, if an anomaly is detected in the user's physiological data PD1, the watch 20 can add a new detection task to detect physiological data PD2. For example, in this case, Figure 22 The control 331 shown can be adjusted from indicating one task to be completed to indicating two tasks to be completed. Accordingly, the information 413A can be adjusted from "Assess progress 90%" to "Assess progress 85%".

[0365] Similarly, in the case of adding a new task to detect physiological data PD2, Figure 23 The interface 228B shown can be changed from displaying "2 tasks to be completed" to "3 tasks to be completed". Correspondingly, information 413B can also be used to indicate that the detection task of physiological data PD2 is pending.

[0366] Similarly, in the case of adding a new task to detect physiological data PD2, Figure 24 The information 413C in the interface 228C shown can be adjusted from "Assessment progress 46%" to "Assessment progress 41%", and information 413E can also be used to indicate that the detection task of physiological data PD2 is pending completion.

[0367] In some examples, when the number of valid measurement periods is insufficient, watch 20 may display as follows: Figure 25 The interface 213 shown can be used to indicate that the effective measurement cycle is insufficient.

[0368] by Figure 21 For example, the wearing time on the 17th may be less than the preset time. In this case, the interface 213 may include information 411, which can be used to indicate that the wearing time does not meet the requirements. For example, information 411 may be "The current effective wearing time is insufficient, and the vascular health test cannot be completed".

[0369] For example, the information 411 above can also be used to indicate that the detection can be completed by extending the wearing time. For example, information 411 could be "The current effective wearing time is insufficient, it is recommended to extend the wearing time by 1 day".

[0370] As one implementation, controls 314 and 315 can be displayed on the interface 213. In response to the operation of selecting control 314, the watch 20 can determine that the user chooses to extend the wearing time to complete the detection; in response to the operation of selecting control 315, the watch 20 can determine that the user cancels the detection.

[0371] If the user chooses to extend the wearing time to complete the test, one possibility is that the effective wearing time in the next measurement cycle can meet the measurement requirements. In this case, watch 20 can display as follows: Figure 26 The interface 214 shown can be used to indicate the test results of vascular health.

[0372] For example, interface 214 can display the risk of cardiovascular disease (e.g., the risk of coronary heart disease), such as no risk, low risk, medium risk, or high risk.

[0373] For example, interface 214 can display the results of physiological data detection during the vascular health detection process, such as heart rate, heart rate variability, etc. For instance, interface 214 can display that the user's average heart rate during this measurement is 128 beats / minute.

[0374] For example, interface 214 can display the detection time of vascular health, such as 10:08 on April 12.

[0375] For example, interface 214 may also display control 316, which, in response to the selection of control 316, allows watch 20 to begin a new round of vascular health measurements for the user.

[0376] In some examples, if the number of valid measurement cycles meets the requirements, watch 20 can display as follows: Figure 27 The interface 229 shown can be used to indicate that the effective measurement cycle meets the requirements.

[0377] As an example, interface 229 may include information 414, which can be used to indicate that the effective measurement period has met the requirements. For example, information 414 may include text messages such as "Effective wearing time has been met".

[0378] As an example, the aforementioned information 414 can also be used to indicate the content of testing tasks that still need to be completed. For example, information 414 may include text messages such as "The test will be completed after completing one more electrocardiogram measurement."

[0379] As an implementation, when information 414 indicates the content of the testing tasks that still need to be completed, interface 229 may also include controls 332 and 333. In response to selecting control 332, watch 20 can perform the aforementioned testing task; in response to selecting control 333, watch 20 can temporarily suspend the aforementioned testing task, for example, by reminding the user to perform the test again after a preset time. For example, if information 414 indicates that an electrocardiogram (ECG) measurement still needs to be completed, in response to the user selecting control 333, watch 20 can perform an ECG measurement for the user; in response to the user selecting control 332, watch 20 can remind the user to perform an ECG measurement again after 30 minutes.

[0380] Due to the limited size of the display screen of the watch 20, in order to facilitate users to obtain more detailed vascular health test results, in one possible implementation, the watch 20 can send the vascular health test results to other electronic devices (e.g., mobile phones, tablets, etc.). These electronic devices may include larger displays, allowing users to view more detailed vascular health test results on other electronic devices.

[0381] As an example, the watch 20 can send the results of vascular health checks to a mobile phone, which can then display the results. Figure 28 The interface 215 shown may include more detailed vascular health test results.

[0382] For example, the interface 215 may include a region 501, which can be used to display basic information about the vascular health test results. For example, region 501 may display whether the user has a risk of coronary heart disease, and if the user has a risk of coronary heart disease, the risk level of the user having coronary heart disease.

[0383] Zone 501 can also display information used to interpret test results related to vascular health. For example, if a user's risk level for coronary heart disease is low, Zone 501 can display the physical conditions associated with low-risk coronary heart disease, such as slightly poor arterial elasticity and a vascular age greater than physiological age. The user's arterial elasticity and vascular age can be determined based on the detected physiological data of the user.

[0384] Zone 501 can also display suggestions for improving vascular health based on test results. For example, if a user's risk level for coronary heart disease is low, Zone 501 may display information such as "improve lifestyle and increase exercise appropriately."

[0385] For example, the interface 215 may include a region 502, which can be used to display detailed information of the vascular health test results, such as blood pressure, blood sugar, whether there are symptoms of angina, whether there are abnormal electrocardiograms, whether there are arrhythmias, etc.

[0386] For example, if a user's risk level for coronary heart disease is low, area 502 can display that the user's blood pressure is 120 / 75 mmHg, blood sugar level is within the normal range, no angina is detected, the abnormal ECG phenomenon is ST segment depression, and the arrhythmia symptom is atrial fibrillation, etc.

[0387] Here's a brief explanation of arrhythmia: Arrhythmia, also known as irregular heartbeat or arrhythmia, is an abnormal manifestation of the heart's automaticity or conduction disorders, causing tachycardia, bradycardia, or irregular heartbeats. It broadly refers to any abnormal heartbeat or rhythm problem, including abnormalities in rhythm and frequency. Abnormalities in the origin, rhythm, transmission sequence, or transmission speed of cardiac impulses at various points can lead to arrhythmia.

[0388] Many arrhythmias are asymptomatic, but when symptoms do appear, they often manifest as palpitations or a feeling of pause in heartbeat. Severe arrhythmias can cause dizziness, fainting, shortness of breath, or chest pain. Even though most are benign, some arrhythmias can increase the risk of complications such as stroke or heart failure, and may even lead to cardiac arrest, shock, or sudden death.

[0389] Cardiac arrhythmias can generally be classified into five categories: premature contractions, supraventricular tachycardia, ventricular arrhythmias, tachycardia, and bradycardia. Premature contractions include atrial premature contractions and ventricular premature contractions. Supraventricular tachycardia includes atrial fibrillation, atrial flutter, and paroxysmal supraventricular tachycardia. Ventricular arrhythmias include ventricular fibrillation and ventricular tachycardia. Tachycardia (or tachycardia) is defined as a heart rate greater than 100 beats per minute in adults, while bradycardia (or bradycardia) is defined as a heart rate less than 60 beats per minute in adults.

[0390] In some examples, the symptoms most closely associated with cardiovascular disease among the various symptoms included in the aforementioned arrhythmias can be termed abnormal heartbeats, such as ventricular fibrillation, atrial fibrillation, premature ventricular contractions, ventricular tachycardia, sinus tachycardia, conduction block, bundle branch block, and cardiac arrest. In other words, abnormal heartbeats here can be understood as a more serious symptom of arrhythmia.

[0391] Cardiac arrest, also known as sudden cardiac arrest, is caused by various reasons that lead to a sudden failure of the heart to contract or ineffective contraction, resulting in systemic circulatory failure, reduced pulse in the major arteries, loss of consciousness, rapid and shallow breathing, and then cessation of breathing. The electrocardiogram shows ventricular fibrillation or cardiac arrest.

[0392] In some examples, the detailed information of the aforementioned vascular health detection results can be obtained by watch 20, or it can be acquired by watch 20 from other detection devices via communication. This application does not impose any limitations on this.

[0393] For example, the interface 215 may include a region 503, which can be used to display detailed improvement suggestions based on the vascular health test results. For instance, if the user's risk level for coronary heart disease is low, region 503 may display "Enhance heart function by increasing aerobic exercise such as brisk walking, jogging, and swimming."

[0394] For example, the interface 215 may include area 504, which can be used to display consultation channels that can provide professional and detailed explanations of the test results for vascular health. For instance, if the user's risk level for coronary heart disease is low, area 504 may display the phone number, address, etc. of Medical Research Center A.

[0395] If the user chooses to extend the wearing time to complete the test, one possibility is that the user's effective wearing time in the next measurement cycle will not meet the measurement requirements. In this case, watch 20 may display something like... Figure 29 The interface 216 is shown. For example, this interface 216 can be used to indicate that the effective wearing time is too short to complete the vascular health test. This interface 216 can also be used to indicate that a vascular health test result can be generated by retesting.

[0396] For example, interface 216 can display information such as "Short effective wearing time, measurement terminated, it is recommended to start a new round of measurement." Interface 216 may also include controls 317 and 318. In response to the selection of control 317, watch 20 can start a new round of vascular health detection. For example, watch 20 can display the information mentioned above. Figure 8 The interface 204 shown prompts the user to perform ECG measurements, etc.; in response to the operation of the selection control 318, the watch 20 can determine whether the user terminates this round of vascular health monitoring.

[0397] One possibility is that the interval between the two rounds of vascular health measurements performed by the watch 20 is relatively short. In this case, in order to shorten the time of the second round of vascular health measurement and improve the user experience, the watch 20 can reuse the user's physiological data detected in the first round of vascular health measurement.

[0398] For example, watch 20 can reuse detection data from the PPG sensor in the previous round of detection.

[0399] As an implementation, watch 20 can determine the similarity between the detection data of the PPG sensor in the first round of detection and the detection data of the PPG sensor in the second round of detection. If the similarity between the two sets of data is greater than or equal to the similarity threshold, watch 20 can reuse the detection data of the PPG sensor in the first round of detection.

[0400] For example, watch 20 can determine one or more of the following based on the detection data from the PPG sensor in the previous round of detection: heart rate information, heart rate variability information, blood pressure information, and blood oxygen saturation information. Similarly, watch 20 can determine one or more of the following based on the detection data from the PPG sensor in the subsequent round of detection: heart rate information, heart rate variability information, blood pressure information, and blood oxygen saturation information. Based on this, watch 20 can determine the similarity between the previous and subsequent heart rate information, the similarity between the previous and subsequent heart rate variability information, the similarity between the previous and subsequent blood pressure information, and the similarity between the previous and subsequent blood oxygen saturation information, and determine the similarity between the aforementioned two sets of data based on the similarity of these data types.

[0401] For example, watch 20 can determine N similarities between the detection data in N time periods of the PPG sensor detection data in the first round of detection and the detection data in N time periods of the PPG sensor detection data in the second round of detection, and determine the similarity between the two sets of data based on these N similarities. Here, N is an integer greater than or equal to 2.

[0402] In some examples, the time taken for the PPG sensor to detect data in the subsequent round of detection, which is used to assess the similarity between the two sets of data, can be much shorter than the time taken for a complete vascular health detection process. Thus, by reusing the detection data from the previous round, the total time taken for the subsequent vascular health detection process can be shortened.

[0403] As one implementation, if the similarity between the detection data of the PPG sensor in the previous round of detection and the detection data of the PPG sensor in the subsequent round of detection is greater than or equal to a similarity threshold, the watch 20 can display as follows: Figure 30 The interface 217 shown can be used to prompt the user to reuse the detection data of the PPG sensor in the previous round of detection.

[0404] For example, interface 217 may include information 412, which can be used to indicate whether the detection data of the PPG sensor in the previous detection process can be reused. For example, information 412 can be "The similarity of the detection data of the PPG sensor in the previous round meets the requirements. Should it be reused in this round of detection?" Interface 217 may also include controls 319 and 320. In response to the operation of selecting control 319, watch 20 can use the detection data of the PPG sensor in the previous detection process in the current detection process; in response to the operation of selecting control 320, watch 20 may not use the data of the PPG sensor in the previous detection process. For example, watch 20 can re-detect using the PPG sensor in this round of detection.

[0405] Before reusing the PPG sensor data from the previous round of testing in the current round, it is necessary to determine the similarity of the user's physiological data between the two rounds of testing. This helps to avoid situations where the user's physiological data changes between the two rounds of testing. Furthermore, a high similarity of the user's physiological data between the two rounds of testing indicates that the user's cardiovascular system is in a relatively stable physiological state. In this case, the test results of the user's vascular health can better reflect the true condition of the user's cardiovascular system.

[0406] In some scenarios, during vascular health monitoring, the user of the watch 20 may change. In such cases, the watch 20 can display the following: Figure 31 The interface 218 shown can be used to indicate that the user cannot be changed during the detection process.

[0407] For example, interface 218 may display a message similar to "Keep this on during measurement; do not allow others to wear it." Interface 218 may also include controls 321 and 322. In response to the selection of control 321, watch 20 may determine that the user is about to replace the wearer of watch 20 as the previous user. In this case, watch 20 may pause the measurement of the current wearer's physiological data. After the wearer of watch 20 is replaced by the previous user, watch 20 may resume measuring the user's physiological data. In response to the selection of control 322, watch 20 may determine that the user chooses to have the next user continue wearing watch 20. In this case, watch 20 may terminate this round of vascular health detection.

[0408] For example, watch 20 can determine whether the user of watch 20 has changed by detecting the physiological data of previous users and subsequent users. For instance, watch 20 can detect the user's physiological data using a PPG sensor and determine whether the user has changed based on the similarity of this physiological data.

[0409] The method for determining whether the wearer has changed based on the similarity of physiological data is similar to the method described above for determining whether to reuse the detection data from the previous round in the subsequent round of detection. For details, please refer to the description above.

[0410] In the process of detecting a user's vascular health, the watch 20 can acquire physiological data from various life scenarios and combine this data to determine the user's vascular health status, thereby improving the accuracy and reliability of the vascular health detection results output by the watch 20. In one possible implementation, during the assessment of a user's vascular health status, the watch 20 can also combine the detection results of the user's risk of sudden acute coronary syndrome to analyze the user's vascular health status. The following describes another vascular health detection method provided in this application, using the watch 20's process of detecting the user's risk of sudden acute coronary syndrome.

[0411] It is understood that the various vascular health detection methods provided in this application embodiment can be combined with each other. For example, as mentioned above, watch 20 can assess the user's vascular health status by combining the user's risk of sudden acute coronary syndrome. As another example, watch 20 can assess the user's risk of sudden acute coronary syndrome by combining the user's vascular health detection results.

[0412] To improve the detection efficiency and accuracy of acute coronary syndrome and to promptly identify the risk of sudden acute coronary syndrome in users, this application provides another method for detecting vascular health, which is described below in conjunction with the process of users using electronic devices to detect acute coronary disease.

[0413] In some examples, watch 20 may have the function of detecting acute coronary syndrome, which may be enabled by default or manually controlled by the user.

[0414] For example, watch 20 can display as follows Figure 32 The interface 219 shown may include a function to enable "Acute Coronary Syndrome Warning". For example, the interface 219 may include an option 511. In response to the user enabling the option 511, the watch 20 may enable the detection function for acute coronary syndrome; in response to the user disabling the option 511, the watch 20 may disable the detection function for acute coronary syndrome.

[0415] For example, the interface 219 may also include other functional items, and the watch 20 may turn the corresponding function on or off in response to operations on these functional items.

[0416] For example, interface 219 may also include function item 512. In response to the operation of activating function item 512, watch 20 can monitor the user's vascular health during sleep; in response to the operation of deactivating function item 512, watch 20 may not monitor the user's vascular health during sleep.

[0417] For example, interface 219 may also include function item 513. In response to the operation of activating function item 513, watch 20 can detect the user's vascular health before and after exercise; in response to the operation of deactivating function item 513, watch 20 may not detect the user's vascular health before and after exercise.

[0418] In some examples, watch 20 can detect whether the user has arrhythmia to determine the user's risk of developing acute coronary syndrome. If a user's arrhythmia is detected, watch 20 can display, for example... Figure 33 The interface 220 shown can be used to display abnormal heart rate data. For example, interface 220 can display that the user's heart rate is 149 beats per minute, which is too high.

[0419] As a means of implementation, watch 20 can detect the user's exercise status to determine whether the user is in a resting state after exercise. If the user is in a resting state after exercise, watch 20 can detect the user's heart rate.

[0420] In some examples, when the user is in a resting state after exercise, watch 20 can display something like this. Figure 34 The interface 221 shown can be used to indicate that the user is currently in a resting state after exercise. The interface 221 can also be used to instruct the watch 20 to automatically detect physiological data.

[0421] For example, interface 221 may display information indicating that the PPG sensor is about to begin measurement. For example, interface 221 may also include controls 323 and 324, wherein, in response to the operation of selecting control 323, watch 20 may begin measuring the user's physiological data, such as measuring the user's heart rate using the PPG sensor; and, in response to the operation of selecting control 324, watch 20 may choose not to measure the user's physiological data.

[0422] As one implementation, the watch 20 can determine whether the user is in pain by detecting the user's skin conductance data. If the user is in pain, the watch 20 can detect the user's heart rate.

[0423] In some examples, when a user's ESC data is abnormal, watch 20 can display, for example... Figure 35The interface 222 shown can be used to indicate abnormal skin conductance data of the user, to indicate that the user may be in pain, and to indicate that the watch 20 will automatically detect physiological data.

[0424] For example, interface 222 may display information indicating that the PPG sensor is about to begin measurement. For example, interface 222 may also include controls 325 and 326, wherein, in response to the operation of selecting control 325, watch 20 may begin measuring the user's physiological data, such as measuring the user's heart rate using the PPG sensor; and, in response to the operation of selecting control 326, watch 20 may choose not to measure the user's physiological data.

[0425] In some examples, if a user's heart arrhythmia is detected, the watch 20 can detect whether the user is experiencing abnormal heartbeat symptoms and, based on the detection results, determine the user's risk of developing acute coronary syndrome.

[0426] Heart rhythm abnormalities can be understood as a more serious form of arrhythmia. For example, the aforementioned heart rhythm abnormalities may include one or more of the following: ventricular fibrillation, atrial fibrillation, premature ventricular contractions, ventricular tachycardia, sinus tachycardia, conduction block, bundle branch block, cardiac arrest, etc.

[0427] As one implementation, the aforementioned abnormal heartbeat phenomena can be determined through signal analysis detected by a PPG sensor. For example, by extracting physiological signals detected by the PPG sensor to determine the user's heart rate and heart rate variability, one or more of the aforementioned abnormal heartbeat phenomena can be identified.

[0428] In some examples, if an abnormal heartbeat is detected in the user, watch 20 can display something like this. Figure 36 The interface 223 shown can be used to indicate to a user that there is an abnormal heartbeat, such as atrial fibrillation or cardiac arrest.

[0429] For example, the interface 223 can also be used to indicate that the watch 20 is about to measure one or more of the following: blood pressure, respiratory rate, pulse, and blood oxygen saturation. In some examples, these aforementioned detection operations can be used to determine whether the user has experienced cardiac arrest.

[0430] For example, interface 223 may display information such as "Atrial fibrillation detected, blood pressure and respiratory rate to be measured soon." Exemplarily, interface 223 may also include controls 327 and 328, whereby, in response to selecting control 327, watch 20 may begin measuring the user's blood pressure and respiratory rate; and in response to selecting control 328, watch 20 may choose not to measure the user's blood pressure and respiratory rate.

[0431] In order to respond more promptly to any potential acute coronary syndrome and increase the chances of the user being rescued, if the watch 20 detects abnormal heartbeat again after the user has canceled automatic blood pressure and respiratory rate measurement, the watch 20 can automatically measure the user's blood pressure and respiratory rate. This will enable the watch 20 to determine more promptly whether the user has acute coronary syndrome and take emergency measures such as calling for help accordingly.

[0432] One possibility is that the watch 20 may not have the function of measuring blood pressure or respiratory rate. In this case, if an abnormal heartbeat is detected in the user, the watch 20 can instruct the user to measure blood pressure and / or respiratory rate in a timely manner.

[0433] If an abnormal breathing rate is detected in the user, the watch 20 can display the following: Figure 37 The interface 224 shown can be used to indicate an abnormal respiratory rate in a user. Exemplarily, interface 224 may include a measurement of the user's respiratory rate (e.g., 31 breaths / min). Exemplarily, interface 224 may also include a range of normal respiratory rate values.

[0434] If the watch 20 detects an abnormal blood pressure reading in the user, it can display the following: Figure 38 The interface 225 shown can be used to indicate abnormal blood pressure in a user. Exemplarily, interface 225 may include the user's blood pressure measurement results (e.g., systolic pressure 135 mmHg, diastolic pressure 85 mmHg). Exemplarily, interface 225 may also include a normal blood pressure range.

[0435] In some examples, cardiac arrest is determined when a user's pulse cannot be detected; cardiac arrest is determined when a user's blood oxygen level is below or equal to a blood oxygen level threshold.

[0436] In cases where the user's respiratory rate is abnormal, and / or, in cases where the user's blood pressure is abnormal, and / or, in cases where the user's pulse is abnormal, and / or, in cases where the blood oxygen content is abnormal, watch 20 can determine that the user is at risk of acute coronary syndrome. In such cases, watch 20 can display as follows: Figure 39 The interface shown is 226 or as follows Figure 40 Interface 227, shown below, along with interfaces 226 and 227, can be used to indicate to a user the risk of acute coronary syndrome.

[0437] As an implementation, interface 226 may also include control 329, which, in response to the user's selection of the control 329, allows watch 20 to call an emergency contact or make an emergency call.

[0438] As one implementation, interface 227 may also include control 330, which can be used to automatically call an emergency contact or make an emergency call. For example, control 330 may include a countdown timer, which, upon the countdown ending, allows watch 20 to automatically call an emergency contact or make an emergency call.

[0439] As a means of implementation, watch 20 can detect whether the user has fallen, and if the user falls, watch 20 can immediately execute an emergency call for help.

[0440] In some examples, one or more of the following data detected during the process of detecting the risk of sudden acute coronary syndrome in a user, such as the user's heart rate, physiological data collected by the PPG sensor after exercise, physiological data collected by the PPG sensor under pain conditions, blood pressure and respiratory rate under abnormal heartbeat conditions, and the detection results of whether there is a risk of sudden acute coronary heart disease, can be used for the assessment of the user's vascular health status mentioned above.

[0441] like Figure 41 The illustration shows a method for detecting vascular health provided in this application. This method can be applied to wearable electronic devices. The electronic device can acquire detection data related to cardiovascular diseases in multiple measurement cycles and / or multiple measurement scenarios, and combine this detection data to output the user's vascular health detection results. This technical solution does not rely on professional medical equipment and can achieve long-term, continuous monitoring of the user's vascular health, improving the accuracy and reliability of the vascular health detection results output by the device.

[0442] S101, the electronic device acquires the detection data within the first measurement cycle.

[0443] In some examples, the test data is used to identify symptoms associated with cardiovascular disease (hereinafter referred to as disease symptoms).

[0444] In some examples, to improve the accuracy of detecting disease symptoms, the electronic device can continuously acquire the above detection data for a preset duration during a single measurement.

[0445] For example, the preset duration may include multiple time periods, which may be consecutive or non-consecutive. The preset duration can be understood as the total duration accumulated from the aforementioned multiple time periods.

[0446] As an example, the multiple time periods included in the above preset duration can be multiple measurement cycles. In other words, the above preset duration can include multiple measurement cycles, such as a first measurement cycle and a second measurement cycle.

[0447] As an example, multiple measurement cycles within a preset duration (e.g., the first measurement cycle and the second measurement cycle) can be considered valid measurement cycles, or in other words, the detection conditions within multiple measurement cycles within a preset duration all meet the measurement requirements.

[0448] As an implementation, the electronic device is a wearable device, and the wearing method and position of the wearable device are correct during the first and second measurement cycles.

[0449] As an implementation, the duration of both the first and second measurement cycles can be greater than or equal to the unit duration.

[0450] Understandably, in order to identify disease symptoms associated with cardiovascular disease through data analysis, the test data needs to meet a certain data volume requirement, or in other words, the test data needs to have a certain time span. In other words, there exists a unit of time within which the test data measured by the electronic device can be used to determine disease symptoms; if the measurement time is shorter than this unit of time, the electronic device cannot determine disease symptoms based on the detected data.

[0451] As an example, the aforementioned unit duration can refer to the shortest duration for which an electronic device can collect valid physiological data. For instance, if an electronic device detects a user's heart rate using a PPG sensor, the unit duration can be understood as the shortest duration for which the data detected by the PPG sensor reflects the user's heart rate. Similarly, if an electronic device detects a user's electrocardiogram (ECG) using an ECG sensor, the unit duration can be understood as the shortest duration for which the data detected by the ECG sensor reflects the user's ECG. Furthermore, if an electronic device can detect whether a user is in pain using a skin conductance sensor, the unit duration can be understood as the shortest duration for which the surface electromyography (EMG) signal detected by the skin conductance sensor reflects whether the user is in pain.

[0452] Based on the above examples, it can be understood that the value of the aforementioned minimum duration is related to the performance of different sensors, the type of detection data, and the detection requirements. In scenarios where multiple sensors are used simultaneously to detect a user's vascular health, the aforementioned unit duration can refer to the maximum value among the multiple unit durations corresponding to each sensor. For example, in the above example, the unit duration corresponding to the PPG sensor could be 12 seconds, the unit duration corresponding to the ECG sensor could be 10 seconds, and the unit duration corresponding to the electrodermal sensor could be 15 seconds. In this case, when using these three sensors simultaneously to detect a user's vascular health, the unit duration corresponding to the electronic device can be determined to be 15 seconds.

[0453] In some examples, the first measurement period may include one or more unit durations.

[0454] As an example, the aforementioned unit duration can be 15 seconds, and the duration of the first measurement cycle can be 24 hours, 12 hours, 18 hours, or 36 hours, etc.

[0455] In some examples, cardiovascular diseases can include coronary artery disease, hypertension, heart failure, stroke, rheumatic heart disease, congenital heart disease, etc. Among them, coronary artery disease can include chronic coronary artery disease or acute coronary syndrome.

[0456] In some examples, disease symptoms are associated with cardiovascular disease; in other words, users experiencing disease symptoms have an increased probability of developing cardiovascular disease. The types of disease symptoms associated with cardiovascular disease can be varied.

[0457] For example, disease symptoms may include cardiac arrhythmias.

[0458] As an implementation, PPG sensors can detect symptoms of arrhythmia, or rather, one or more of the following information can reflect disease symptoms: abnormal standard deviation of normal to normal intervals (SDNN), abnormal ratio of low-frequency to high-frequency components in heart rate variability, abnormal Poincare plot, etc.

[0459] As a means of detection, ECG sensors can detect symptoms of arrhythmias. In other words, the waveform characteristics of an electrocardiogram (ECG) can reflect disease symptoms, such as ST segment depression, ST segment elevation, T wave inversion, peaked T waves, and J point deviation. In some scenarios, the aforementioned abnormal waveforms on an ECG can also be referred to as ECG abnormalities.

[0460] For example, disease symptoms may include abnormal facial features of the user, such as earlobe creases, nasal bridge wrinkles, abnormal facial skin color (e.g., yellow or orange patches), facial edema, corneal arcus (arcus senilis or corneal lipid arcus), and baldness on the top of the head.

[0461] As one implementation, image data of the user's face is acquired through an image sensor (e.g., camera 193), which can be used to determine the symptoms of the aforementioned facial feature abnormalities.

[0462] For example, disease symptoms may include one or more of the following: atrial fibrillation, abnormal blood pressure, abnormal blood oxygen content, sleep apnea syndrome, abnormal cardiac output, etc.

[0463] In one implementation, electronic devices can use PPG and ECG sensors to determine whether a user is experiencing symptoms of atrial fibrillation.

[0464] As one implementation, electronic devices can use PPG sensors to detect whether a user's blood pressure and blood oxygen levels are abnormal.

[0465] As one implementation, electronic devices can use PPG sensors, accelerometers, and gyroscopes to detect whether a user is experiencing sleep apnea syndrome.

[0466] In one implementation, electronic devices can use PPG sensors, ECG sensors, accelerometers, gyroscopes, temperature sensors, etc., to determine whether a user has symptoms of abnormal cardiac output.

[0467] To help users identify one or more of the above-mentioned disease symptoms, the detection data may include one or more of the following: data from a PPG sensor, data from an ECG sensor, image data, data from an accelerometer sensor, data from a gyroscope sensor, data from a temperature sensor, etc.

[0468] For example, the detection data may include data from a PPG sensor, such as time-domain information of heart rate variability, frequency-domain information of heart rate variability, etc.

[0469] For example, the detection data may include data from an ECG sensor, such as feature information of the ST segment of an electrocardiogram.

[0470] For example, the detection data may include image data, such as a frontal image of the user's face, a 45° side view of the face, an image of the top of the user's head, etc.

[0471] In some examples, to more accurately assess a user's vascular health, electronic devices can acquire detection data from the user in different scenarios. In other words, the aforementioned detection data can include data from different scenarios, such as data from exercise, sleep, when the user is in pain, when the user is experiencing emotional fluctuations, when the user is in a cold environment, or when the user is in a post-eating state.

[0472] For example, the detection data may include data from a PPG sensor, a motion sensor, and an ECG sensor during exercise. Specifically, ECG sensor data can be used to determine the ST segment and P wave in an electrocardiogram, PPG sensor data can be used to determine post-exercise blood pressure and recovery heart rate, and motion sensor data can be used to determine exercise load (exercise duration, exercise intensity, etc.).

[0473] For example, the detection data may include data from a PPG sensor and an ECG sensor during sleep. Data from these two sensors can be used to determine resting heart rate, heart rate variability, blood pressure, blood oxygen content, presence of obstructive sleep apnea (OSA), sleep duration, sleep stage, and whether symptoms such as arrhythmia or cardiac arrest occur during sleep.

[0474] For example, the detection data may include data from a PPG sensor and an ECG sensor during non-sleep scenarios. Data from these two sensors can be used to determine resting heart rate, heart rate variability, blood pressure, atrial fibrillation, premature beats, and activity levels during non-sleep periods.

[0475] For example, the detection data may include data from PPG sensors and ECG sensors during emotional fluctuations.

[0476] For ease of explanation, the detection data in the first measurement cycle can be referred to as the first data, and similarly, the detection data in the second measurement cycle can be referred to as the second data.

[0477] In some examples, the first data can be used to determine the first symptom, which can be one or more of the disease symptoms mentioned above.

[0478] For example, the first symptom may include one or more of the following: arrhythmia, abnormal facial features, atrial fibrillation, abnormal blood pressure, abnormal blood oxygen content, sleep apnea syndrome, abnormal cardiac output, etc.

[0479] For example, the first data may include one or more of the following: data from a PPG sensor, data from an ECG sensor, image data, data from an accelerometer sensor, data from a gyroscope sensor, data from a temperature sensor, etc.

[0480] S102, the electronic device acquires the detection data during the second measurement cycle.

[0481] Here, the detection data within the second measurement period is referred to as the second data, which can be used to determine the second symptom.

[0482] In some examples, the second measurement period may include one or more of the aforementioned unit durations.

[0483] For example, the unit duration can be 15 seconds, and the second measurement period can be 24 hours, 12 hours, 18 hours, or 36 hours, etc.

[0484] In some examples, the first measurement period and the second measurement period are two adjacent measurement periods.

[0485] For example, the first measurement period can be the nth measurement period, and the second measurement period can be the (n+1)th measurement period, where n is a positive integer.

[0486] In some examples, the first measurement period and the second measurement period can be two non-adjacent measurement periods.

[0487] For example, the first measurement period can be the nth measurement period, and the second measurement period can be the (n+5)th measurement period, where n is a positive integer.

[0488] Similar to the first data mentioned above, in some examples, the second data may include one or more of the following: data from a PPG sensor, data from an ECG sensor, image data, data from an accelerometer sensor, data from a gyroscope sensor, data from a temperature sensor, etc.

[0489] Similar to the first data mentioned above, in some examples, the second data may include one or more of the following different scenarios: data in a sports scenario, data in a sleep scenario, data when the user is in pain, data when the user is experiencing emotional fluctuations, data when the user is in a cold environment, data when the user is in a post-eating state, etc.

[0490] For an explanation of the second data, please refer to the relevant description of the first data above.

[0491] Similar to the first symptom described above, in some examples, the second symptom may include one or more of the above-mentioned disease symptoms. In other words, the second symptom may include one or more of the following: arrhythmia, abnormal facial features, atrial fibrillation, abnormal blood pressure, abnormal blood oxygen content, sleep apnea syndrome, abnormal cardiac output, etc.

[0492] One possibility is that the second symptom can be the same disease symptom as the first symptom mentioned above; for example, both the second and first symptoms could be arrhythmias. Alternatively, the second symptom can be a different disease symptom than the first symptom mentioned above; for example, the second symptom could be abnormal blood pressure, while the first symptom could be abnormal cardiac output. This application does not impose any limitations on this.

[0493] For an explanation of the second symptom, please refer to the relevant description of the first symptom mentioned above.

[0494] S103, the electronic device determines the detection result of vascular health based on the first data and the second data.

[0495] In one possible implementation, the first data and the second data may include physiological data measured by the ECG sensor at least twice, such as physiological data detected by the ECG sensor when the user is at rest and physiological data detected by the ECG sensor after the user has exercised.

[0496] In some examples, vascular health test results can include the user's probability of having cardiovascular disease.

[0497] For example, the results of vascular health testing can be: the current probability of having coronary heart disease is 5%, the current risk level of having coronary heart disease is 0-10%, and the current vascular health status is sub-healthy, etc.

[0498] Similarly, the risk levels for coronary heart disease can also be categorized as: 10%-25%, 25%-50%, 50%-75%, and ≥75%.

[0499] Similarly, vascular health status can also be categorized as: healthy, medium risk, and high risk.

[0500] As a result, a healthy vascular health status can be used to indicate a risk level of 0-10% for coronary heart disease, a sub-healthy vascular health status can be used to indicate a risk level of 10%-25% for coronary heart disease, a medium-risk vascular health status can be used to indicate a risk level of 25%-75% for coronary heart disease, and a high-risk vascular health status can be used to indicate a risk level of ≥75% for coronary heart disease.

[0501] In some examples, the results of vascular health testing may include the results of physiological data detected during the current round of vascular health testing, such as heart rate, heart rate variability, blood pressure, blood sugar, whether there are symptoms of angina, whether there are abnormal electrocardiograms, and whether there are arrhythmias.

[0502] In some examples, the vascular health test results may include the time of the current vascular health test, for example, 10:08 on April 12.

[0503] In some examples, vascular health test results may include explanatory information that details the findings. For instance, if a user's risk level for coronary heart disease is low, the explanatory information might include slightly poor arterial elasticity and a vascular age greater than their physiological age.

[0504] In some examples, the results of vascular health tests can include recommendations for improving vascular health.

[0505] For example, the above recommendations may include one or more of the following: healthy eating, regular exercise, quitting smoking and limiting alcohol consumption, managing stress, etc.

[0506] For example, healthy eating recommendations may include reducing the intake of saturated fat, trans fat, cholesterol, salt, and sugar, and increasing the intake of fiber-rich foods such as whole grains, vegetables, and fruits.

[0507] Recommendations for regular exercise may include at least 150 minutes of moderate-intensity aerobic exercise or 75 minutes of vigorous-intensity aerobic exercise per week.

[0508] Suggestions for quitting smoking and limiting alcohol consumption may include: completely eliminating tobacco products and limiting alcohol intake.

[0509] Stress management tips may include: deep breathing, meditation, yoga, maintaining an optimistic attitude, actively participating in social activities, and maintaining good communication with family and friends.

[0510] In some examples, vascular health test results may include a consultation channel that can provide a professional and detailed interpretation of the results. For example, this consultation channel could include the phone number and address of Medical Research Center A.

[0511] The historical vascular health test results mentioned earlier contain similar information to the vascular health test results presented here, so they will not be repeated here.

[0512] In some examples, electronic devices determine the probability of a user experiencing a first symptom based on first data, and determine the probability of a user having cardiovascular disease based on the probability of experiencing the first symptom. The results of vascular health testing can be used to indicate the probability of a user having cardiovascular disease.

[0513] For example, an electronic device can determine the probability that the current user has cardiovascular disease based on the probability that the detected user (hereinafter referred to as the current user) has the first symptom, the probability that a general user has cardiovascular disease, and the probability that a general user has the first symptom in the case of cardiovascular disease.

[0514] For example, based on the first data, the probability that the current user exhibits symptom A is P(A); the probability that a general user has cardiovascular disease is P(S); the probability that a general user with cardiovascular disease exhibits symptom A is P(A|S); and the probability that the current user, given the presence of symptom A, has cardiovascular disease is...

[0515] In some examples, electronic devices determine the probability of a user experiencing a second symptom based on second data, and determine the probability of a user having cardiovascular disease based on the probability of experiencing the second symptom. The results of vascular health testing can be used to indicate the probability of a user having cardiovascular disease.

[0516] For example, an electronic device can determine the probability that a user has cardiovascular disease based on the probability that the current user will experience a second symptom, the probability that a general user has cardiovascular disease, and the probability that a general user will experience a second symptom while having cardiovascular disease.

[0517] For example, the second data can determine the probability that the current user has symptom B as P(B); the probability that a general user has cardiovascular disease is P(S); the probability that a general user with cardiovascular disease has symptom B is P(B|S); and the probability that the current user has cardiovascular disease in addition to having symptom B is...

[0518] In some examples, electronic devices can determine the probability that a user has cardiovascular disease based on the first and second symptoms. In other words, electronic devices can combine the first and second data to determine the detection result of cardiovascular health.

[0519] For example, an electronic device can determine the probability that a user has cardiovascular disease based on the probability of the current user having a first disease symptom, the probability of the current user having a second symptom, the probability of a general user having cardiovascular disease (P(S)), and the probability of a general user having both the first and second symptoms while having cardiovascular disease.

[0520] For example, the probability of a current user exhibiting symptom A can be determined using the first data point as P(A), and the probability of a current user exhibiting symptom B can be determined using the second data point as P(B). The probability of a general user having cardiovascular disease is P(S), and the probability of a general user with cardiovascular disease exhibiting both the first and second symptoms is P(A∩B|S). Given that the current user exhibits both symptoms A and B, the probability that they have cardiovascular disease is...

[0521] In some examples, the electronic device can determine the probability of a user experiencing a first symptom based on the first data and the second data, and determine the vascular health test result based on the probability of the user experiencing the first symptom; alternatively, the electronic device can determine the probability of a user experiencing a second symptom based on the first data and the second data, and determine the vascular health test result based on the probability of the user experiencing the second symptom; or alternatively, the electronic device can determine the probability of a user experiencing both the first and second symptoms based on the first data and the second data, and determine the vascular health test result based on the probability of the user experiencing the first and second symptoms.

[0522] The method by which electronic devices determine the test results for vascular health based on the probability of the first symptom and / or the probability of the second symptom can be found in the previous text and will not be repeated here.

[0523] In some examples, electronic devices can determine the detection results of vascular health based on detection data from one or more scenarios.

[0524] For example, the above scenarios may include one or more of the following: exercise scenario, sleep scenario, user in pain state, user in emotional fluctuation state, user in cold environment, user in post-eating state.

[0525] For example, the detection data of electronic devices can be the same in different scenarios.

[0526] For example, detection data in multiple scenarios may include one or more of the following: data from PPG sensors, data from ECG sensors, image data, data from motion sensors, data from temperature sensors, etc.

[0527] For example, the detection data of electronic devices may differ in different scenarios.

[0528] For example, in a sports scenario, the detection data may include data from the ECG sensor, motion sensor, and PPG sensor; in a sleep scenario, the detection data may include data from the PPG sensor and motion sensor; when the user is in pain, the detection data may include data from the PPG sensor and image sensor; when the user is in a cold environment, the detection data may include data from the temperature sensor and PPG sensor; and when the user is experiencing emotional fluctuations or has just eaten, the detection data may include data from the PPG sensor.

[0529] Using the same detection data in different scenarios simplifies the data detection process for electronic devices. Conversely, using different detection data in different scenarios improves the targeting of the data detection process, enhances the energy efficiency of electronic devices, and increases the accuracy and reliability of the vascular health detection results output by the electronic devices.

[0530] For example, an electronic device can determine the probability of a user having a third symptom based on the detection data in scenario 1, and the probability of a user having a cardiovascular disease based on the probability of a user having a third symptom. The detection results of vascular health can be used to indicate the probability of a user having a cardiovascular disease.

[0531] For example, an electronic device can determine the probability of a user having a third symptom based on the detection data in scenario 1, determine the probability of a user having a fourth symptom based on the detection data in scenario 2, and combine the probability of the user having a third symptom and the probability of the user having a fourth symptom to determine the probability that the user has cardiovascular disease.

[0532] The third and fourth symptoms mentioned above can be understood as one or more of the various disease symptoms described earlier. Alternatively, the third and fourth symptoms can include one or more of the following: arrhythmia, abnormal facial features, atrial fibrillation, abnormal blood pressure, abnormal blood oxygenation, sleep apnea syndrome, abnormal cardiac output, etc.

[0533] The third and fourth symptoms may be the same as or different from the first or second symptoms mentioned above, and this application does not impose any restrictions on this.

[0534] The methods by which electronic devices determine the results of a user's vascular health detection based on detection data in different scenarios can be found in the description above regarding the determination of the results of a user's vascular health detection based on detection data within different measurement periods, and will not be repeated here.

[0535] In some examples, electronic devices can determine vascular health results based on detection data over one or more measurement periods and detection data from one or more scenarios.

[0536] For example, the electronic device determines the probability of a user experiencing a first symptom based on first data, and determines the probability of a user having cardiovascular disease based on the probability of a user experiencing a first symptom. The vascular health test results can be used to indicate the probability of a user having cardiovascular disease.

[0537] For example, an electronic device can determine the probability of a user having a third symptom based on the detection data in scenario 1, and the probability of a user having a cardiovascular disease based on the probability of a user having a third symptom. The detection results of vascular health can be used to indicate the probability of a user having a cardiovascular disease.

[0538] For example, the electronic device can determine the probability of a user having a first symptom based on the first data, determine the probability of a user having a third symptom based on the detection data under scenario 1, and determine the probability of a user having cardiovascular disease by combining the probability of a user having a first symptom and the probability of a user having a third symptom.

[0539] The methods by which electronic devices determine the results of a user's vascular health detection based on detection data in different scenarios can be found in the description above regarding the determination of the results of a user's vascular health detection based on detection data within different measurement periods, and will not be repeated here.

[0540] In some examples, a measurement period may include one or more measurement scenarios. These could include motion scenarios, sleep scenarios, or scenarios where the user is in pain. In other words, the detection data within a measurement period can include detection data from one or more measurement scenarios.

[0541] In some examples, a scenario can be within a single measurement period, or a scenario can span multiple measurement periods. For instance, scenario 1 is a sleep scenario with a measurement period from 0:00 to 24:00. In this case, scenario 1 can be included in two adjacent measurement periods. In other words, the detection data under scenario 1 can be included in the detection data of one or more measurement periods.

[0542] It is understood that measurement period and scenario are different dimensions of preset duration. The two dimensions can overlap or be independent of each other. This application does not impose any restrictions on this.

[0543] In some examples, electronic devices can combine third-party data to determine the results of vascular health tests, where the third-party data may include the user's health information.

[0544] For example, third-party data may include one or more of the following: basic personal information (such as age, gender, etc.), lifestyle (such as dietary habits, exercise frequency), family medical history, personal medical history, current physical condition, etc.

[0545] As one implementation method, electronic devices can obtain the aforementioned third data through questionnaires; relevant content can be found in the preceding text. Figure 6 and Figure 7 Related explanations.

[0546] In one possible implementation, the electronic device can determine the probability of a user having cardiovascular disease through an evaluation model; in other words, the evaluation model can be used to determine the results of vascular health tests. The input data for the evaluation model may include test data from multiple measurement periods and / or test data from one or more scenarios.

[0547] Figure 42 and Figure 43 Two exemplary diagrams are provided illustrating how assessment models process test data and output vascular health test results. Figure 42 In this process, the input data for the evaluation model can include detection data from multiple measurement periods. Figure 43 The input data for the evaluation model can include detection data from multiple scenarios.

[0548] In some examples, Figure 42 In this measurement, the first measurement period, the second measurement period, the i-th measurement period (where i is a positive integer), and the N-th measurement period (where N is greater than or equal to i, and N is a positive integer) can each include multiple unit durations. Furthermore, each measurement period can be a valid measurement period, meaning that each measurement period contains valid data. For example, the wearing time of the electronic device within the measurement period meets the duration requirement, and / or, the electronic device is worn correctly within the measurement period.

[0549] In some examples, Figure 42 In the measurement, the detection data in the first measurement period, the detection data in the second measurement period, the detection data in the i-th measurement period (i is a positive integer), and the detection data in the N-th measurement period (N is greater than or equal to i, and N is a positive integer) can all include one or more of the following: data from the PPG sensor, data from the ECG sensor, image data, data from the motion sensor, data from the temperature sensor, etc.

[0550] For a description of the measurement cycle and the detection data within the measurement cycle, please refer to the relevant content in S101 and S102 above, which will not be repeated here.

[0551] In some examples, Figure 43 In the context, scenario 1, scenario 2, scenario j (where j is a positive integer), and scenario M (where M is greater than or equal to j and M is a positive integer) can all be one or more of the following: exercise scenario, sleep scenario, user in pain, user in emotional fluctuation, user in a cold environment, or user in a post-eating state.

[0552] In some examples, Figure 43 In this context, the detection data in scenario 1, scenario 2, scenario j, and scenario M can be the same.

[0553] For example, the detection data in the above-mentioned scenarios includes one or more of the following: data from PPG sensors, data from ECG sensors, image data, data from motion sensors, data from temperature sensors, etc.

[0554] In some examples, Figure 43 In this context, the detection data in scenario 1, scenario 2, scenario j, and scenario M can be different.

[0555] For example, scenario 1 can be a motion scenario, in which the detection data may include: data from the ECG sensor, data from the motion sensor, data from the PPG sensor, etc.; scenario 2 can be a sleep scenario, in which the detection data may include: data from the PPG sensor, data from the motion sensor, etc.; scenario j can be a pain scenario (the user is in pain), in which the detection data may include: data from the PPG sensor, data from the image sensor, etc.; scenario M can be a cold environment scenario (the user is in a cold environment), in which the detection data may include: data from the temperature sensor, data from the PPG sensor, etc.

[0556] In some examples, the input to the above evaluation model may also include the user's health information.

[0557] In some examples, the output of the above assessment model may include one or more of the vascular health test results mentioned above. For example, the output of the assessment model may include the probability that the user has cardiovascular disease and suggestions for improving vascular health.

[0558] In some examples, the assessment model described above can classify one or more types of input data, with different classifications corresponding to a user's risk level for cardiovascular disease. The following example illustrates this using four risk levels for cardiovascular disease: Level A, Level B, Level C, and Level D. The risk of cardiovascular disease increases progressively with each of these four levels.

[0559] For example, the evaluation model described above may include one or more of the following classification algorithms: decision trees, random forests, gradient boosting decision trees (GBDT), or extreme gradient boosting (XGBoost). These classification algorithms can be used to classify the input data of the evaluation model.

[0560] For example, the input data for the evaluation model can include detection data from multiple measurement periods.

[0561] In one implementation, the electronic device can determine the user's risk level for cardiovascular disease within each measurement cycle based on the detection data in that measurement cycle, and combine the risk level determination results from all measurement cycles to determine the vascular health detection results output by the assessment model.

[0562] As one implementation, the electronic device can determine the feature values ​​(e.g., mean, median, etc.) of the same type of detection data across multiple measurement cycles based on the detection data within each measurement cycle. Based on the feature values ​​of multiple types of detection data, the classification of these feature values ​​can be determined using one or more of the aforementioned classification algorithms, thereby determining the vascular health detection result output by the evaluation model.

[0563] As one implementation, the electronic device can combine the two methods described above to determine the vascular health detection result output by the assessment model. Specifically, the electronic device can determine the user's risk level of cardiovascular disease within each measurement cycle based on the detection data within that cycle. Furthermore, the electronic device can determine the feature values ​​of the same type of detection data across multiple measurement cycles based on the detection data within each cycle. By combining the user's risk level of cardiovascular disease within each measurement cycle and the feature values ​​of the detection data across multiple measurement cycles, and using one or more of the aforementioned classification algorithms to determine the classification of these data, the vascular health detection result output by the assessment model can be determined.

[0564] For example, the input data for evaluating the model can include detection data from multiple scenarios.

[0565] As one implementation, electronic devices can determine the risk level of a user's cardiovascular disease in each scenario based on the detection data in each scenario, and combine the risk level classification results in all scenarios to determine the vascular health detection results output by the assessment model.

[0566] As one implementation, the electronic device can categorize multiple scenarios occurring within a preset time period into various different scenarios based on scenario categories. Each scenario can include one or more scenarios. Based on the detection data in each scenario, the device determines the feature values ​​(e.g., mean, median, etc.) of the detection data in each scenario. Using the feature values ​​of the detection data in each scenario as a basis, one or more of the aforementioned classification algorithms can be used to determine the classification of these feature values, thereby determining the vascular health detection result output by the evaluation model.

[0567] For example, the input data for the evaluation model may include detection data from multiple measurement periods and detection data from one or more scenarios.

[0568] In one implementation, the electronic device can determine the user's risk level of cardiovascular disease within each measurement cycle based on the detection data, and determine the user's risk level of cardiovascular disease in each scenario based on the detection data in each scenario. Based on the risk levels within different measurement cycles and the risk levels in one or more scenarios, the classification of these data can be determined using one or more of the aforementioned classification algorithms, thereby determining the vascular health detection result output by the assessment model.

[0569] As one implementation, the electronic device can determine the feature values ​​of the same type of detection data across multiple measurement cycles based on the detection data within each measurement cycle; it can also categorize multiple scenarios occurring within a preset time period into various different scenarios based on scenario categories, with each scenario potentially including one or more scenarios, and determine the feature values ​​of the detection data within each scenario based on the detection data in each scenario. Based on the feature values ​​of the detection data across multiple measurement cycles and the feature values ​​of the detection data under one or more scenarios, the classification of these data can be determined using one or more of the aforementioned classification algorithms, thereby determining the vascular health detection result output by the evaluation model.

[0570] For example, the input data for the evaluation model may include the user's health information and detection data over multiple measurement periods.

[0571] One implementation involves the electronic device determining feature values ​​for the same type of detection data across multiple measurement cycles based on the data collected in each measurement cycle. Using these feature values ​​and the user's health information, the classification of this data can be determined through one or more of the aforementioned classification algorithms, thereby determining the vascular health detection result output by the evaluation model.

[0572] For example, the input data for evaluating the model can include the user's health information and detection data from multiple scenarios.

[0573] One possibility is that the same type of scenario may appear multiple times within a preset duration. For example, the preset duration may include sleep scenario Ss1, sleep scenario Ss2, sleep scenario Ss3, exercise scenario Es1, exercise scenario Es2, and pain scenario As1. Among these, sleep scenario Ss1, sleep scenario Ss2, and sleep scenario Ss3 belong to the same type of scenario (sleep scenario), exercise scenario Es1 and exercise scenario Es2 belong to the same type of scenario (exercise scenario), and pain scenario As1 belongs to another type of scenario.

[0574] In one implementation, the electronic device can group detection data from multiple scenarios occurring within a preset time period according to scenario type. Each group of data corresponds to the same scenario type, and each group can consist of detection data from one or more scenarios. Based on the detection data from each scenario within the same group, the feature value of each group can be determined. Using the feature values ​​of one or more groups of data and the user's health information as a basis, one or more of the aforementioned classification algorithms can be used to determine the classification of these data, thereby determining the vascular health detection result output by the evaluation model.

[0575] Taking the above example, the electronic device can determine the feature value Fv1 of the detection data in the sleep scenario based on the detection data of sleep scenario Ss1, sleep scenario Ss2 and sleep scenario Ss3; determine the feature value Fv2 of the detection data in the exercise scenario based on the detection data of exercise scenario Es1 and exercise scenario Es2; determine the feature value Fv3 of the detection data in the pain scenario based on the detection data of pain scenario As1; and classify the aforementioned feature values ​​Fv1, Fv2, Fv3 and the user's health information through the above classification algorithm to determine the detection result of vascular health within a preset time period.

[0576] In some examples, the evaluation model may also include correlation information that can be used to indicate the association between test data and the probability of developing cardiovascular disease, and the correlation information can also be used to indicate the association between a user's health information and the probability of developing cardiovascular disease.

[0577] For example, this association information can be used to indicate the correlation between the frequency of a user's arrhythmia symptoms and the probability of developing coronary heart disease; for another example, this association information can be used to indicate the correlation between a user's drinking habits and the probability of developing coronary heart disease; for yet another example, this association information can be used to indicate the correlation between a user's heart rate variability at rest after exercise and the probability of developing coronary heart disease.

[0578] As one approach, the aforementioned correlation information can be established through statistical analysis. For example, by statistically analyzing the frequency of arrhythmias among 100,000 users (including ordinary users and patients with coronary heart disease) and the severity of their coronary heart disease, a correlation can be established between the frequency of arrhythmia symptoms and the probability of developing coronary heart disease.

[0579] Processing test data through evaluation models and outputting vascular health test results to users improves the data processing efficiency of electronic devices. Furthermore, the evaluation model can be continuously iterated and upgraded during use, which also helps improve the accuracy and reliability of the vascular health test results output by electronic devices. This allows users to better understand their own health conditions, seek medical attention early, and improve their overall health.

[0580] like Figure 44 The illustration shows another method for detecting vascular health provided in this application, which can be applied to wearable devices. The wearable device can combine physiological data detected by a PPG sensor over a period of time, physiological data detected by an ECG sensor in a resting state, and physiological data detected by an ECG sensor after exercise to jointly determine the user's vascular health. Physiological data detected by the ECG sensor in a resting state and after exercise are strongly correlated with the user's cardiovascular status; therefore, the vascular health detection result determined by combining these two types of data is more accurate.

[0581] S401, the wearable device detects the user's first physiological data within a first duration using a PPG sensor.

[0582] In some examples, the first duration includes multiple valid measurement periods, within which the wearing duration is greater than or equal to a duration threshold. For example, the first duration can be 3 days, 72 hours, 48 ​​hours, 24 hours, etc., and this application does not impose any restrictions on this. For example, the first duration can be a continuous period of time, or it can be multiple discontinuous time periods, and this application does not impose any restrictions on this either.

[0583] For an explanation of the effective measurement period, please refer to the previous text. Figure 21 , Figure 25 and Figure 27 The relevant content will not be elaborated here.

[0584] For example, the first physiological data may include time-domain and frequency-domain information on the user's heart rate changes, such as the user's heart rate, heart rate variability, estimated blood oxygen saturation, and estimated blood pressure. In some scenarios, the first physiological data can also be understood as physiological data detected by a PPG sensor, or data from the PPG sensor during the detection process.

[0585] In one possible implementation, if the similarity between the first physiological data detected in the previous round of vascular health testing and the first physiological data detected in the current round of vascular health testing is greater than or equal to a preset threshold, the wearable device can reuse the first physiological data detected in the previous round of vascular health testing to determine the test result for the current round of vascular health testing. Implementing this technical solution can, to some extent, shorten the testing time for the current round of vascular health testing and improve the user experience.

[0586] For the method of determining the similarity of the first physiological data in the two consecutive rounds, please refer to the previous text. Figure 30 and Figure 31 The relevant content will not be elaborated here.

[0587] S402, the wearable device uses an ECG sensor to detect the user's second physiological data at rest and third physiological data after exercise.

[0588] In some examples, electronic devices can use motion sensors to detect the user's motion state, thereby determining whether the user is in motion.

[0589] For example, the second and third physiological data can both be used to determine the user's electrocardiogram characteristics, such as ST segment morphology and / or T wave morphology.

[0590] As an implementation, when the wearable device detects that the user has finished exercising, it can display first information, which can be used to indicate the measurement of third physiological data after exercise. Similarly, when the device detects that the user is in a resting state (e.g., after the user has filled out the form above), it can also display first information. Figure 6 or Figure 7 After completing the questionnaire, the wearable device can also display the aforementioned first information to remind the user to measure the second physiological data of the resting state.

[0591] As an example, the aforementioned first information can be used to indicate the method of measuring the second or third physiological data through the ECG sensor. For instance, the first information can be used to instruct the user to place their right hand fingers on the ECG electrode of the device.

[0592] As an example, when a user places their finger on the ECG electrode of the device, the first information can be used to indicate that a second or third physiological data is being measured.

[0593] In determining a user's vascular health, this technical solution combines physiological data detected by an ECG sensor at rest and after exercise. These two types of data are strongly correlated with the user's cardiovascular status, making the vascular health determination results more accurate.

[0594] In some examples, wearable devices can also check the following reference scenarios and remind users to use ECG sensors to measure physiological data in the following reference scenarios: when the user is in pain, when the user is experiencing emotional fluctuations, when the user is in a cold environment, when the user is in a post-eating state, etc.

[0595] S403, the wearable device determines the detection results of vascular detection based on the first physiological data, the second physiological data and the third physiological data.

[0596] In some examples, before outputting the test results, the wearable device may also display a first interface, which includes a questionnaire that can be used to determine the user's health information, which may include one or more of the following: gender, age, lifestyle, family medical history, personal medical history, and current physical condition.

[0597] Wearable devices can determine test results based on the aforementioned health information, first physiological data, second physiological data, and third physiological data.

[0598] In some examples, before outputting detection results, the wearable device can acquire image data through an image sensor, which can be used to determine a primary symptom, including one or more of the following: earlobe creases, nasal bridge wrinkles, abnormal facial skin color, facial edema, corneal arch, and baldness on the top of the head.

[0599] Wearable devices can determine the detection results based on the aforementioned image data, first physiological data, second physiological data, and third physiological data.

[0600] In some examples, before outputting the test results, the wearable device can detect a reference scenario associated with cardiovascular disease; while the user is in the reference scenario, it acquires an eighth physiological data point; and the test results are determined based on the first, second, third, and fifth physiological data points.

[0601] In some examples, before outputting the test results, the wearable device can detect a reference physiological condition that indicates an abnormality in a fourth physiological data point associated with cardiovascular disease; while the user is in the reference physiological condition, a fifth physiological data point is detected; and the test results are determined based on the first, second, third, and eighth physiological data points.

[0602] For example, the above reference scenarios include one or more of the following: the user is in a state of having finished exercising, the user is in a state of pain, the user is in a state of emotional fluctuation, the user is in a cold environment, and the user is in a state of having eaten.

[0603] For example, the fourth or fifth physiological data mentioned above includes one or more of the following: physiological data detected by the ECG sensor, physiological data detected by the PPG sensor, respiratory rate, blood pressure, blood oxygen content, and pulse.

[0604] As an example, the fourth and fifth physiological data may be the same or different.

[0605] In one possible implementation, the wearable device can determine the test results based on historical data of vascular health detection results, first physiological data, second physiological data, and third physiological data.

[0606] The method for wearable devices to determine the detection results of vascular detection based on the first physiological data, the second physiological data, and the third physiological data can be found in S103 above, and will not be repeated here.

[0607] This technical solution is applied to wearable devices that can continuously monitor a user's primary physiological data and repeatedly measure their electrocardiogram (ECG) data during wear. Based on these two types of data, the probability of the user developing cardiovascular disease can be determined. This solution does not rely on specialized medical equipment. By extending the monitoring time for primary physiological data and increasing the number of ECG measurements, more physiological data related to cardiovascular disease is obtained, which improves the accuracy and reliability of vascular health monitoring results. This allows users to understand changes in their individual vascular health and enables early treatment of potential cardiovascular diseases. Furthermore, this technical solution can facilitate preliminary screening for cardiovascular diseases with high prevalence, which to some extent improves the efficiency of limited social medical resources and helps alleviate the psychological stress on patients.

[0608] To improve the chances of survival for cardiovascular disease patients in the event of a sudden illness, such as... Figure 45The illustration shows another method for detecting vascular health provided in this application, which can be applied to wearable devices. When an arrhythmia is detected in a user, the electronic device can detect whether the user exhibits other symptoms associated with cardiovascular disease. If multiple symptoms are detected simultaneously, the electronic device can determine that the user is at risk of sudden coronary heart disease and promptly execute an emergency call.

[0609] S201, The electronic device determines that the user has a heart rhythm disorder and / or an abnormal electrocardiogram.

[0610] In some examples, electronic devices can determine whether a user has arrhythmia based on detection data from multiple scenarios.

[0611] For example, electronic devices can determine whether a user has arrhythmia based on detection data during a motion scenario and / or detection data when the user is in pain.

[0612] For example, an electronic device can determine that a user is in a resting state after exercise using a motion sensor. In this case, the electronic device can detect whether the user has symptoms of arrhythmia using a PPG sensor.

[0613] For example, an electronic device can determine that a user is in pain by using a skin conductance sensor and / or an image sensor. In this case, the electronic device can detect whether the user is experiencing symptoms of arrhythmia by using a PPG sensor.

[0614] In some examples, when abnormalities in a user's electrodermal data are detected, the electronic device may display the following: Figure 35 The interface 222 shown can be used to display abnormal skin conductance data of the user, indicating that the user may be in pain. The interface 222 can also be used to display that the device is about to automatically detect the vascular health status.

[0615] As a form of implementation, electronic devices can be configured according to... Figure 46 The flowchart shown uses an image sensor to detect and analyze the user's pain state.

[0616] S301, detection and interception of critical components.

[0617] Electronic devices can acquire one or more of the following images through an image sensor: a frontal image of the user's face, a 45° side view of the face, and an image of the top of the head.

[0618] In some examples, the image sensor here can be an image sensor contained within an electronic device. Alternatively, the image sensor here can also belong to other devices, and the electronic device can access the image sensor of other devices to capture one or more of the aforementioned images via communication.

[0619] In some examples, electronic devices can crop the above images and obtain images of one or more of the following body parts: ears, glasses, nose, forehead, jaw, etc. These body parts may contain symptoms closely associated with cardiovascular disease. In some scenarios, these body parts can be understood as key areas for determining whether a user is in pain.

[0620] S302, Identification of key features of cardiovascular diseases.

[0621] In some examples, key features of cardiovascular disease can also be understood as typical symptoms of cardiovascular disease.

[0622] For example, the key features of cardiovascular disease mentioned above may include one or more of the following: earlobe creases, nasal bridge wrinkles, abnormal facial skin color, facial edema, corneal arch, baldness on the top of the head, etc.

[0623] Electronic devices can analyze images of the aforementioned key areas and identify the aforementioned key features.

[0624] For example, electronic devices can identify the above key features through one or more of the following image analysis algorithms: convolutional neural network, support vector machine, random forest, k-nearest neighbor algorithm, component analysis, etc.

[0625] S303, Feature Analysis, Hierarchical Coding.

[0626] The electronic device can combine the image analysis results of the aforementioned key areas to determine the types of key features of potential cardiovascular disease in the user, as well as the probability of each type of key feature occurring. Based on this data and information, the electronic device can generate a detection result indicating that the user is in a state of pain. This detection result can be represented in a coded form, facilitating further analysis by the electronic device in subsequent processing.

[0627] In some examples, electronic devices can use ECG sensors to detect a user's physiological data and determine the user's electrocardiogram (ECG) based on this data, thereby determining whether the ECG is abnormal.

[0628] For example, the above-mentioned electrocardiogram abnormalities may include one or more of the following: ST segment depression, ST segment elevation, T wave inversion, T wave peaking, J point deviation, etc.

[0629] In one implementation, the electronic device can perform ECG measurements when the user is at rest and / or after exercise, and thereby determine whether the user has ECG abnormalities.

[0630] S202, The electronic device has determined that the user's heartbeat is abnormal.

[0631] In some examples, abnormal heartbeats may include one or more of the following: ventricular fibrillation, atrial fibrillation, premature ventricular contractions, ventricular tachycardia, sinus tachycardia, conduction block, bundle branch block, cardiac arrest, etc.

[0632] In one implementation, electronic devices can analyze the data detected by PPG sensors to detect the user's heart rate and heart rate variability, and use this data analysis to determine whether there are features associated with the aforementioned abnormal heartbeat symptoms. If such features are present, it can be determined that the user has an abnormal heartbeat.

[0633] For example, an electronic device may display as described above. Figure 36 The interface 223 shown can be used to display symptoms of abnormal heartbeat.

[0634] S203, Electronic device determines that user has suffered cardiac arrest.

[0635] In some examples, when an abnormal heartbeat is detected in a user, the electronic device can detect the user's blood pressure, pulse, blood oxygen saturation, and breathing. If at least one of the following conditions is present: abnormal blood pressure, decreased respiratory rate, undetectable pulse, or excessively low blood oxygen saturation, it can be determined that the user has experienced cardiac arrest.

[0636] For example, an electronic device may display as described above. Figure 37 The interface 224 shown can be used to display the user's respiratory rate measurement results.

[0637] For example, an electronic device may display as described above. Figure 38 The interface 225 shown can be used to display the user's blood pressure measurement results.

[0638] S204, The electronic device determines that the user is at risk of sudden coronary heart disease.

[0639] If a user experiences cardiac arrest, the electronic device can determine that the user is at risk of sudden coronary heart disease. In this case, the electronic device can trigger emergency operations, such as automatically calling emergency contacts or automatically dialing emergency numbers.

[0640] For example, an electronic device may display as described above. Figure 39 or Figure 40 The interfaces shown allow electronic devices to perform emergency call operations.

[0641] Based on the foregoing descriptions of methods for determining a user's vascular health and for determining whether a user has a sudden cardiovascular disease, this application also provides a method for detecting vascular health. When a slight abnormality is detected in a user's physiological data, the wearable device can promptly perform more in-depth physiological data analysis to accurately analyze and output the user's vascular health status and implement corresponding response measures.

[0642] S501, Display the first interface, which is used to indicate to the user the onset of the first symptom.

[0643] In some examples, the first symptom mentioned above may include arrhythmias and / or electrocardiogram abnormalities.

[0644] In one possible implementation, the aforementioned first symptom can be determined based on the user's heart rate information and / or electrocardiogram information.

[0645] For explanations regarding arrhythmias and abnormal electrocardiograms, please refer to the previous descriptions; they will not be repeated here.

[0646] S502, Perform a first operation to determine whether the user has a second symptom.

[0647] Here, the risk of cardiovascular disease for users with the first symptom is lower than the risk of cardiovascular disease for users with the second symptom.

[0648] In some examples, the second symptom mentioned above may include cardiac arrest. In such cases, wearable devices can perform emergency calls for help.

[0649] In one possible implementation, the aforementioned second symptom can be determined based on one or more of the following: electrocardiogram, respiratory rate, blood oxygen saturation, pulse, blood pressure, etc. In other words, the aforementioned first operation can include one or more of the following: measuring electrocardiogram, measuring respiratory rate, measuring blood oxygen saturation, measuring pulse, measuring blood pressure, etc.

[0650] As a result, before performing the first operation, the wearable device can perform a second operation to determine whether the user has a third symptom. If the third symptom is present, the user's risk of cardiovascular disease is higher than if the first symptom is present, but lower than if the second symptom is present.

[0651] In some scenarios, the measurement of the user's physiological data PD2 by the watch 20 when the user's physiological data PD1 is abnormal can also be understood as an example of the above technical solution. In other words, in some scenarios, an abnormality in physiological data PD1 can be used to indicate that the user has the aforementioned first symptom; physiological data PD2 can be used to determine whether the user has the aforementioned second symptom, or physiological data PD1 and physiological data PD2 can be used together to determine whether the user has the aforementioned second symptom.

[0652] Based on the same inventive concept, such as Figure 47 As shown in the illustration, this application also provides a vascular health detection device 4700. This device 4700 can possess the functions of the electronic device described in the above method embodiments and can be used to execute the steps performed by the electronic device in the above method embodiments. This function can be implemented in hardware, or in software, or by hardware executing corresponding software. The hardware or software includes one or more modules corresponding to the above functions.

[0653] In one possible implementation, the vascular health detection device 4700 may include an acquisition module 4710 and a processing module 4720, which are coupled to each other.

[0654] In some examples, the acquisition module 4710 can be used to support the electronic device in the foregoing embodiments in acquiring the user's physiological data, etc.

[0655] The processing module 4720 is used to support the electronic device in performing the processing actions in the above method embodiments, such as determining the detection results of the user's vascular health based on physiological data and image data.

[0656] Optionally, the vascular health detection device 4700 may also include a storage unit 4730 for storing the program code and data of the vascular health detection device 4700.

[0657] Figure 48 An electronic device 4800 provided in this application embodiment is shown in the figure. The electronic device 4800 includes at least one processor 4810 and a transceiver 4820. The processor 4810 is coupled to a memory and is used to execute instructions stored in the memory to control the transceiver 4820 to transmit and / or receive signals.

[0658] Optionally, the electronic device 4800 also includes a memory 4830 for storing instructions.

[0659] In some embodiments, the processor 4810 and the memory 4830 can be combined into a single processing device, with the processor 4810 executing program code stored in the memory 4830 to achieve the aforementioned functions. Specifically, the memory 4830 can be integrated into the processor 4810 or independent of it.

[0660] In some embodiments, transceiver 4820 may include a receiver and a transmitter.

[0661] The transceiver 4820 may further include an antenna, and the number of antennas may be one or more. The transceiver 4820 may be a communication interface or an interface circuit.

[0662] When the electronic device 4800 is a chip, the chip includes a transceiver module and a processing module. The transceiver module can be an input / output circuit or a communication interface; the processing module can be a processor, microprocessor, or integrated circuit integrated on the chip.

[0663] This embodiment also provides a computer-readable storage medium storing computer instructions. When the computer instructions are executed on an electronic device, the electronic device performs the aforementioned method steps to implement the vascular health detection method in the above embodiment.

[0664] This embodiment also provides a computer program product that, when run on a computer, causes the computer to perform the aforementioned steps to implement the vascular health detection method described in the above embodiment.

[0665] Furthermore, embodiments of this application also provide an apparatus, which may specifically be a chip, component, or module. The apparatus may include a connected processor and a memory. The memory stores computer-executable instructions. When the apparatus is running, the processor executes the computer-executable instructions stored in the memory, causing the chip to perform the vascular health detection methods described in the above-described method embodiments.

[0666] 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.

[0667] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0668] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of 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 coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0669] 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.

[0670] In addition, the functional units in the various embodiments of this application 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.

[0671] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0672] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method of detecting vascular health, characterized by, Applied to wearable devices, the method includes: The PPG sensor detects the user's first physiological data within the first time period using the photovolume change mapping method. Secondary physiological data of the user's resting state are detected using an electrocardiogram (ECG) sensor; The ECG sensor detects third physiological data after the user's exercise. The test results, which display vascular health, are determined based on the first physiological data, the second physiological data, and the third physiological data.

2. The method of claim 1, wherein, Prior to displaying the test results for vascular health, the method further includes: Detect reference scenarios and / or reference physiological conditions, wherein the reference scenarios are associated with cardiovascular disease and the reference physiological conditions are used to indicate abnormalities in fourth physiological data associated with cardiovascular disease; The fifth physiological data is detected when the user is in the reference scenario; and / or, the fifth physiological data is detected when the user is in the reference physiological condition. The detection result is determined based on the first physiological data, the second physiological data, the third physiological data, the fifth physiological data, and the reference scenario and / or the reference physiological condition.

3. The method according to claim 1 or 2, characterized in that, Prior to displaying the test results for vascular health, the method further includes: A third interface is displayed, which includes one or more detection tasks to be completed.

4. The method of claim 3, wherein, The method further includes: When a reference scenario and / or reference physiological condition is detected, a target detection task is displayed on the third interface. The target detection task is used to instruct the detection of a fifth physiological data, which is used to determine the detection result. The reference scenario is associated with cardiovascular disease, and the reference physiological condition is used to indicate abnormalities in the fourth physiological data associated with cardiovascular disease.

5. The method according to any one of claims 2 to 4, characterized in that, The reference scenarios include one or more of the following: the user is in a state of having finished exercising, the user is in a state of pain, the user is in a state of emotional fluctuation, the user is in a cold environment, and the user is in a state of having eaten. And / or, The fourth or fifth physiological data includes one or more of the following: physiological data detected by the ECG sensor, physiological data detected by the PPG sensor, respiratory rate, blood pressure, blood oxygen content, and pulse.

6. The method according to any one of claims 1 to 5, characterized in that, Before detecting third physiological data after user movement via the ECG sensor, the method further includes: Detect the user's movement status; When the user is in a state where exercise has ended, the first information is displayed, which is used to indicate the measurement of the third physiological data.

7. The method according to any one of claims 1 to 6, characterized in that, Prior to displaying the test results for vascular health, the method further includes: The first interface is displayed, which includes a questionnaire to determine the user's health information, which includes one or more of the following: gender, age, lifestyle, family medical history, personal medical history, and current physical condition. The test results are determined based on the health information, the first physiological data, the second physiological data, and the third physiological data.

8. The method according to any one of claims 1 to 7, characterized in that, Prior to displaying the test results for vascular health, the method further includes: Image data is acquired through an image sensor, and the image data is used to determine a first symptom, which includes one or more of the following: earlobe creases, nasal bridge wrinkles, abnormal facial skin color, facial edema, corneal arch, and baldness on the top of the head. The detection result is determined based on the image data, the first physiological data, the second physiological data, and the third physiological data.

9. The method according to any one of claims 1 to 8, characterized in that, Prior to displaying the test results for vascular health, the method further includes: The second message is displayed to indicate that the wearing time is insufficient.

10. The method of claim 9, wherein, The method further includes: The third information is displayed, which indicates whether to extend the wearing time or to indicate a retest.

11. The method according to any one of claims 1 to 10, characterized in that, The method further includes: Accept the procedure to begin a new round of vascular health testing; The user's sixth physiological data is detected by the PPG sensor during a second duration, which is shorter than the first duration. The seventh physiological data of the user's resting state is detected by the ECG sensor; The ECG sensor is used to detect the eighth physiological data of the user after exercise. If the similarity between the sixth physiological data and the first physiological data is greater than a preset threshold, the results of the new round of vascular health detection are determined based on the first physiological data, the seventh physiological data, and the eighth physiological data.

12. The method according to any one of claims 1 to 11, characterized in that, Prior to displaying the test results for vascular health, the method further includes: The second interface is displayed, which includes the progress of the vascular health detection.

13. The method of claim 12, wherein, The second interface includes fourth information and / or fifth information. The fourth information is used to indicate that the wearing process in the first time period meets the preset requirements, and the fifth information is used to indicate that the wearing process in the second time period does not meet the preset requirements. The first duration includes the first time period and / or the second time period.

14. The method according to any one of claims 1 to 13, characterized in that, The test results are determined based on historical data of the vascular health test results, the first physiological data, the second physiological data, and the third physiological data.

15. A method for detecting vascular health, characterized in that, Applied to wearable devices, the method includes: Obtain the user's heart rate information and / or electrocardiogram information; Display a first interface, which is used to indicate user arrhythmia and / or user electrocardiogram abnormalities; Perform a first operation, the first operation being used to determine whether the user has experienced a first symptom, the first symptom being used to indicate that the user has suffered cardiac arrest; If the user exhibits the first symptom, a second interface is displayed, which indicates that the user is at risk of sudden cardiovascular disease.

16. The method of claim 15, wherein, Before performing the first operation, the method further includes: Based on the heart rate information, determine whether the user is experiencing a second symptom; If the user exhibits the second symptom, a third interface is displayed, which is used to indicate to the user that the second symptom has been present.

17. The method according to claim 15 or 16, characterized in that, The acquisition of the user's heart rate information includes: In the target scenario, the user's first physiological data is detected using a photovolume plethysmography (PPG) sensor, and this first physiological data is used to determine the heart rate information; and / or In the target scenario, the user's second physiological data is detected by an electrocardiogram (ECG) sensor, and the second physiological data is used to determine the ECG information.

18. The method of any one of claims 15-17, wherein, The execution of the first operation includes: The user's third physiological data is measured, which includes one or more of the following: respiratory rate, blood pressure, pulse or blood oxygen content, and the first symptom includes the third physiological data meeting preset conditions; The method further includes: The fourth interface is displayed, which includes the measurement results of the third physiological data.

19. The method according to any one of claims 15 to 18, characterized in that, The method further includes: If the user exhibits the first symptom, an emergency call will be made.

20. An electronic device, comprising: The device includes a memory and a processor, the memory storing program instructions, and the processor executing the program instructions to cause the electronic device to perform the method of any one of claims 1 to 14, or to cause the electronic device to perform the method of any one of claims 15 to 19.

21. A computer-readable storage medium, characterized in that, It contains a computer program that, when executed by a computer, enables the implementation of the method of any one of claims 1 to 14 or claims 15 to 19.

22. A computer program product, characterised in that, Includes computer program code that, when run on a computer, causes the method of any one of claims 1 to 14 or claims 15 to 19 to be performed.

23. A device for detecting vascular health, characterized by Includes modules for implementing the method of any one of claims 1 to 14 or claims 15 to 19.

24. A chip, characterized by The device includes a processor and a memory, the processor being configured to read instructions from the memory, and when the processor executes the instructions, causing the chip to implement the method of any one of claims 1 to 14 or claims 15 to 19.

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