Blood pressure assessment method, user interface, and related devices

Abstract

This application discloses a blood pressure assessment method, user interface, and related apparatus. In this method, an electronic device can acquire a user's first PPG signal, identify the user's group level using the first PPG signal, which describes the user's group or the probability that the user belongs to different groups, and then assess and display the user's blood pressure based on the group level. It is evident that this method first locates the user's group or the proximity of different groups based on the user's PPG signal before assessing the user's blood pressure, thus improving the accuracy of blood pressure assessment.

Description

Technical Field

[0001] This application relates to the field of terminal and computer technology, and in particular to blood pressure assessment methods, user interfaces and related devices. Background Technology

[0002] Blood pressure is an important physiological parameter reflecting human vital signs. Currently, the common method of blood pressure measurement is to collect photoplethysmography (PPG) signals using optical sensors and use the PPG signals to calculate the user's blood pressure value. However, this method of blood pressure measurement requires periodic calibration using blood pressure values ​​measured by instruments such as mercury sphygmomanometers or electronic sphygmomanometers, which is inconvenient and cumbersome for users. Summary of the Invention

[0003] This application provides a blood pressure assessment method, user interface, and related devices, enabling the assessment of a user's blood pressure using PPG signals without calibration.

[0004] In a first aspect, embodiments of this application provide a blood pressure assessment method applied to an electronic device. The method includes: acquiring a user's first photoplethysmography (PPG) signal; displaying the user's group level, the group level being identified based on the first PPG signal, the group level describing the group to which the user belongs or the probability that the user belongs to different groups; and displaying the user's blood pressure status assessed based on the group level.

[0005] By implementing the method provided in the first aspect, the user's group or proximity to each group can be located based on the user's PPG signal. The user's blood pressure can then be assessed based on the group, which can improve the accuracy of blood pressure assessment. Furthermore, it enables accurate assessment of the user's blood pressure using PPG signals without the need for calibration.

[0006] In conjunction with the first aspect, in one implementation, people in the same group show similar performance in systolic and / or diastolic blood pressure.

[0007] As can be seen, this method divides users into groups based on similar systolic and diastolic blood pressure, and uses the user's PPG signal to analyze the user's systolic and / or diastolic blood pressure. This allows the electronic device to analyze the user's blood pressure by combining the blood pressure data of people with similar blood pressure levels, avoiding the inconvenience of needing to periodically use external devices to measure blood pressure values ​​for calibration in existing technologies, and making the operation more convenient for users.

[0008] In conjunction with the first aspect, in one implementation, before displaying the user's blood pressure status assessed based on the group level, the method further includes: assessing the user's blood pressure status based on the group level and the blood pressure assessment model corresponding to the group.

[0009] In other words, electronic devices can incorporate models to assess a user's blood pressure, thereby achieving an accurate assessment of the user's blood pressure.

[0010] In conjunction with the first aspect, in one implementation, the first PPG signal includes at least two of the following: a PPG signal acquired during sleep, a PPG signal acquired during non-sleep, a PPG signal acquired during movement, and a PPG signal acquired during rest.

[0011] In other words, the PPG signals collected by electronic devices should include PPG signals collected from users in various states, so that the data used to assess users' blood pressure can represent the user's general state and make the blood pressure assessment results more comprehensive and accurate.

[0012] In conjunction with the first aspect, in one implementation, during the process of acquiring the user's first photoplethysmography (PPG) signal, the method further includes: displaying the acquisition progress of the PPG signal.

[0013] In this way, users can not only view the progress of PPG signal acquisition, but also estimate the time required for the electronic device to acquire the PPG signal, so that users can make reasonable time arrangements or avoid blindly waiting for the PPG signal to be acquired.

[0014] In conjunction with the first aspect, in one implementation, during the process of acquiring the user's first photoplethysmography (PPG) signal, the method further includes: if the number of PPG signals acquired within a first time period is less than a first threshold, outputting a first prompt message, the first prompt message being used to prompt the user that the number of PPG signals acquired within the first time period is insufficient.

[0015] This can remind users to take timely measures to increase the probability that electronic devices can collect PPG signals that meet the requirements, or to speed up the process of electronic devices acquiring PPG signals that meet the requirements.

[0016] In conjunction with the first aspect, in one implementation, the method further includes: when a first time is reached and the number of collected PPG signals is less than a second threshold, outputting a second prompt message, the second prompt message being used to prompt the user that the collected PPG signals are insufficient.

[0017] For example, the "first time" can refer to the preset time for the electronic device to assess blood pressure using PPG signals. Therefore, if the electronic device fails to collect sufficient PPG signals within the specified time, it can output a prompt message to remind the user that the currently collected PPG signals are insufficient, allowing the user to take timely measures to increase the collected PPG signals, or to prevent the user from blindly waiting for the blood pressure assessment results.

[0018] In conjunction with the first aspect, in one implementation, the method further includes: displaying a first progress bar, wherein when acquiring the user's first PPG signal, the first progress bar is used to indicate a first progress; when displaying the user's group level, the first progress bar is used to indicate a second progress; and when displaying the user's blood pressure status, the first progress bar is used to indicate a third progress, wherein the third progress is greater than the second progress, and the second progress is greater than the first progress.

[0019] In this way, users can understand the current progress of their blood pressure assessment through the progress bar.

[0020] In conjunction with the first aspect, in one implementation, the method further includes: displaying one or more of the following: measurement period, acquisition duration of PPG signals under various user states, acquisition duration of PPG signals at different time periods, blood pressure change trend, and PPG signal waveform; wherein, the various user states include at least two of the following: sleep state, non-sleep state, exercise state, and resting state, and the different time periods include: the corresponding time period during the day and the corresponding time period at night.

[0021] In other words, in addition to displaying the blood pressure readings assessed by the electronic device, it can also display other information to help users understand their blood pressure from multiple perspectives and gain a clearer understanding of their own blood pressure.

[0022] In conjunction with the first aspect, in one implementation, after acquiring the user's first photoplethysmography (PPG) signal and before displaying the user's group level, the method further includes: inputting a first feature extracted from the first PPG signal into a grouping baseline model to obtain N numerical values ​​corresponding to each group, wherein the N numerical values ​​corresponding to each group are used to indicate the user's group level, N≥2, wherein the group corresponding to the maximum or minimum value among the N values ​​is the group to which the user belongs, or the value represents the probability that the user belongs to the group corresponding to the value, and the grouping baseline model is a model trained using the tester's PPG signal when the tester's group is known.

[0023] As can be seen, the user's group level can be determined through the group baseline model, so that electronic devices can accurately identify the systolic and diastolic blood pressure reflected by the user's PPG signal using the PPG signal.

[0024] In conjunction with the first aspect, in one implementation, the grouping level describes the probability that a user belongs to different groups. After displaying the user's grouping level and before displaying the user's blood pressure status assessed based on the grouping level, the method further includes: inputting the second feature extracted from the first PPG signal into the blood pressure assessment models corresponding to the N groups respectively to obtain N risk intermediate values; and using the values ​​corresponding to the N groups as weights, weighting and summing the N risk intermediate values ​​to obtain the user's blood pressure status.

[0025] It is evident that a blood pressure assessment model can be introduced to assess a user's blood pressure using the user's group level and PPG signal.

[0026] In conjunction with the first aspect, in one implementation, the grouping level describes the probability that a user belongs to different groups. After displaying the user's grouping level and before displaying the user's blood pressure status assessed based on the grouping level, the method further includes: acquiring the user's second PPG signal; inputting the third feature extracted from the first PPG signal and the second PPG signal into the blood pressure assessment models corresponding to the N groups respectively to obtain N risk median values; and using the values ​​corresponding to the N groups as weights, weighting and summing the N risk median values ​​to obtain the user's blood pressure status.

[0027] In other words, when assessing a user's blood pressure, more PPG signals can be obtained and used to assess the user's blood pressure, thereby improving the accuracy of the blood pressure assessment model in assessing the user's blood pressure.

[0028] In conjunction with the first aspect, in one implementation, the group level describes the group to which the user belongs. After displaying the user's group level and before displaying the user's blood pressure status assessed based on the group level, the method further includes: inputting a fourth feature extracted from the first PPG signal into the blood pressure assessment model corresponding to the user's group to obtain the user's blood pressure status.

[0029] It is evident that a blood pressure assessment model can be introduced to assess a user's blood pressure using the user's group level and PPG signal.

[0030] In conjunction with the first aspect, in one implementation, the group level describes the group to which the user belongs. After displaying the user's group level and before displaying the user's blood pressure status assessed based on the group level, the method further includes: acquiring the user's second PPG signal; and inputting a fifth feature extracted from the first PPG signal and the second PPG signal into the blood pressure assessment model corresponding to the user's group to obtain the user's blood pressure status.

[0031] In other words, when assessing a user's blood pressure, more PPG signals can be obtained and used to assess the user's blood pressure, thereby improving the accuracy of the blood pressure assessment model in assessing the user's blood pressure.

[0032] In conjunction with the first aspect, in one implementation, the blood pressure assessment model corresponding to each group is trained using the PPG signals of the test subjects in the group, given the known blood pressure of the test subjects.

[0033] In conjunction with the first aspect, in one implementation, the user's blood pressure status includes one or more of the following: the user's risk of hypertension, the user's risk of hypotension, and the user's risk of abnormal blood pressure fluctuations.

[0034] In conjunction with the first aspect, in one implementation, different groups are obtained based on different systolic and / or diastolic blood pressure ranges.

[0035] In a second aspect, embodiments of this application provide an electronic device, including: a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the method as described in the first aspect or any implementation thereof.

[0036] Thirdly, embodiments of this application provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method as described in the first aspect or any implementation thereof.

[0037] Fourthly, embodiments of this application provide a computer program product, which includes a computer program that, when executed by a processor, implements the method described in the first aspect or any of the implementations of the first aspect. Attached Figure Description

[0038] Figures 1A-1G , Figure 2 , Figure 3 , Figure 4 The electronic device 100 provided in this application embodiment involves a user interface ranging from acquiring PPG signals to assessing the user's hypertension risk;

[0039] Figure 5 A schematic flowchart of a blood pressure assessment method provided in an embodiment of this application;

[0040] Figure 6 A schematic diagram illustrating the principle of the blood pressure assessment model for evaluating users using PPG signals, provided in an embodiment of this application.

[0041] Figure 7 A schematic diagram illustrating the principle of grouping and partitioning provided in an embodiment of this application;

[0042] Figure 8 A schematic diagram illustrating the generation principle of the grouped baseline model provided in this application embodiment;

[0043] Figure 9 A schematic diagram illustrating the generation principle of the blood pressure assessment model provided in this application embodiment;

[0044] Figure 10 A schematic diagram of the hardware structure of the electronic device 100 provided in the embodiments of this application;

[0045] Figure 11 This is a schematic diagram of the structure of the blood pressure assessment device 200 provided in the embodiments of this application. Detailed Implementation

[0046] The technical solutions in the embodiments of this application will be clearly and thoroughly described below with reference to the accompanying drawings.

[0047] The term "user interface (UI)" used in the following embodiments of this application refers to the medium interface through which an application or operating system interacts and exchanges information with the user. It realizes the conversion between the internal form of information and the form that the user can accept. The user interface is source code written in a specific computer language such as Java or Extensible Markup Language (XML). The interface source code is parsed and rendered on the electronic device, ultimately presenting content that the user can recognize. A common form of user interface is the graphical user interface (GUI), which refers to a user interface related to computer operation displayed graphically. It can be visible interface elements such as text, icons, buttons, menus, tabs, text boxes, dialog boxes, status bars, navigation bars, and widgets displayed on the screen of an electronic device.

[0048] This application provides a blood pressure assessment method that can collect a user's PPG signal, identify the user's group level based on the collected PPG signal, and then assess the user's blood pressure based on the user's group level.

[0049] The user's group level describes the group to which the user belongs, or the probability that the user belongs to different groups. A group represents a blood pressure population, and different groups are divided according to different ranges of systolic blood pressure (SBP) and / or diastolic blood pressure (DBP). That is, people in the same group have similar systolic and / or diastolic blood pressure.

[0050] This application takes into account that the causes of blood pressure abnormalities may vary among different populations. Some may be caused by improper diet, others by aging, and still others by different stages of blood pressure abnormalities. Taking hypertension as an example, some people may be in the first stage of hypertension, characterized by elevated diastolic blood pressure, commonly seen in obese individuals, those with a long-term high-salt diet, those who stay up late, or young people under high stress. Some people may be in the second stage of hypertension, characterized by both high systolic and diastolic blood pressure, commonly seen in middle-aged and elderly people and those with unhealthy lifestyles. Some people may be in the third stage of hypertension, characterized by gradually decreasing diastolic blood pressure and persistently elevated systolic blood pressure, commonly seen in elderly people with weakened vascular elasticity. Hypertension in the first stage is usually reversible, meaning that it can be restored to normal blood pressure through external intervention. Hypertension in the second and third stages is usually irreversible, meaning that it cannot be restored to normal blood pressure through external intervention.

[0051] Furthermore, the characteristics of PPG signals reflected in hypertension at different stages are also different. Therefore, if only the same model is used to assess the blood pressure of different people, the assessment results will not be accurate enough, and it will be impossible to analyze the user's blood pressure according to the actual situation of different groups.

[0052] Therefore, before assessing a user's blood pressure, this solution first locates the user's group or the proximity of the user to each group based on the user's PPG signal. The blood pressure is then assessed based on the group, improving the accuracy of blood pressure assessment. Compared to existing technologies that use PPG signals to measure a user's blood pressure, this method does not require periodic calibration using blood pressure values ​​measured by mercury sphygmomanometers or electronic sphygmomanometers, making the operation more convenient for users.

[0053] In addition, assessing a user's blood pressure status can refer to assessing the user's risk of hypertension, risk of hypotension, and risk of abnormal blood pressure fluctuations. Hypertension risk refers to the likelihood that the user has hypertension, hypotension risk refers to the likelihood that the user has hypotension, and abnormal blood pressure fluctuation risk refers to the likelihood that the user's blood pressure fluctuates abnormally.

[0054] Taking the assessment of a user's hypertension risk as an example, the system can output the user's hypertension risk level, such as high risk, medium risk, and low risk. High risk means that the user has a relatively high probability of having hypertension, medium risk means that the user has a moderate probability of having hypertension, and low risk means that the user has a relatively low probability of having hypertension. In this way, the user can understand their own probability of having hypertension based on these three levels. Alternatively, the system can output a numerical value of the user's hypertension risk. For example, the higher the value, the higher the user's hypertension risk, and the lower the value, the lower the user's hypertension risk. In this way, the user can intuitively understand their own probability of having hypertension through this numerical value.

[0055] The following describes the relevant user interface involved in the blood pressure assessment method provided by the electronic device 100 in this application embodiment, taking the assessment of a user's blood pressure as an example to assess the user's risk of hypertension.

[0056] Figures 1A-1G , Figure 2 , Figure 3 , Figure 4 The electronic device 100 provided in this application embodiment involves a user interface related to the acquisition of PPG signals and the assessment of a user's hypertension risk.

[0057] It is important to note that Figures 1A-1G , Figure 2 , Figure 3 , Figure 4 Taking a watch worn on a user's wrist as an example, in other embodiments of this application, the electronic device 100 may also be a mobile phone, tablet computer or other types of device, and this application does not limit it.

[0058] like Figure 1A As shown, the user interface 10 may include a hypertension risk screening option 101. This hypertension risk screening option 101 can be used to trigger the electronic device 100 to display a relevant interface for hypertension risk screening.

[0059] For example, if electronic device 100 detects a user action, such as a click, on the hypertension risk screening option 101, electronic device 100 may display the following in response to the action: Figure 1B The user interface 20 shown.

[0060] like Figure 1B As shown, the user interface 20 can be used to display relevant instructions for hypertension risk screening. Additionally, the user interface 20 may include a switch 201. This switch 201 can be used to turn the electronic device 100's hypertension risk screening on or off.

[0061] For example, if the electronic device 100 detects a user operation on the switch 201, thus activating the screening of the user's hypertension risk, the electronic device 100 can enter the data acquisition phase of the hypertension risk screening, that is, begin acquiring the user's PPG signal and displaying it. Figure 1C The user interface 30 shown.

[0062] like Figure 1C As shown, the user interface 30 may include: a prompt message 301. This prompt message 301 can be used to indicate the progress of PPG signal acquisition. For example, in... Figure 1C In this context, the prompt information 301 may include the value 20%, which indicates that 20% of the PPG signal has been collected. After the electronic device 100 collects 100% of the PPG signal, it can use the collected PPG signal to identify the user's group level, that is, to identify the group to which the user belongs, or the probability that the user belongs to a different group.

[0063] Additionally, the user interface 30 may include a progress bar 302. This progress bar 302 can be used to indicate the progress of the electronic device 100 in the process of starting to acquire PPG signals and assessing the user's risk of hypertension.

[0064] For example, the progress bar 302 can be presented as a progress bar surrounding the edge of the display area of ​​the electronic device 100, avoiding obscuring the main display content on the electronic device 100. Further optionally, the progress bar 302 can remain displayed even when the electronic device 100 is in a screen-on or unlocked state. This way, even when the electronic device 100 is not in a screen-on or unlocked state, the progress bar remains visible. Figures 1C-1G In any of the hypertension risk screening interfaces shown, the electronic device 100 still displays a progress bar for that hypertension risk screening, so that the user can keep track of the progress at any time. This is because hypertension risk screening may require collecting PPG signals from the user for a relatively long period of time. The electronic device 100 is generally not always on the hypertension risk screening interface. Therefore, keeping the progress bar displayed will not only not affect the user's use of the electronic device 100 to handle other business, but also make it convenient for the user to keep track of the hypertension risk screening status at any time.

[0065] In some embodiments, the electronic device 100 may also display the duration of PPG signal acquisition in various user states on the user interface 30. The user's state may include at least two of the following: sleep state, non-sleep state, active state, and resting state. In this way, the user can understand through the user interface 30 what state the PPG signal acquired by the electronic device 100 was in when it was acquired, and the duration of the PPG signal acquisition.

[0066] Furthermore, if the electronic device 100 has acquired sufficient PPG signals, it can proceed to the baseline assessment phase of hypertension risk screening, i.e., using the acquired PPG signals to identify the user's group level. During this identification process, the electronic device 100 can display... Figure 1D The user interface shown is 40.

[0067] like Figure 1D As shown, the user interface 40 may include a prompt message 401. This prompt message 401 can be used to indicate the progress of recognizing the user's grouping level. For example, in Figure 1D In this context, the prompt message 401 may include the value 60%, which indicates that the current progress in identifying the user's group level is 60%.

[0068] Understandably, considering that the time spent by the electronic device 100 in identifying the user's group level may be short, the electronic device 100 may not display the group level when identifying the user. Figure 1D The user interface 40 shown can directly display the PPG signal after the electronic device 100 has completed the acquisition of the PPG signal and used the PPG signal to identify the user's group level. Figure 1E The user interface 50 shown avoids the electronic device 100 switching between display screens too frequently.

[0069] Figure 1E The user interface 50 shown can be the interface displayed by the electronic device 100 after recognizing the user's group level.

[0070] like Figure 1E As shown, the user interface 50 may include: a prompt message 501. The prompt message 501 can be used to indicate to the user which group they belong to, for example, in... Figure 1E In this context, the notification message 501 may include the text: "Your PPG signal circadian rhythm is closer to that of people with high blood pressure." The "people with high blood pressure" refers to the blood pressure group to which the user belongs, as identified by the electronic device 100.

[0071] Understandable, Figure 1E Taking the user's grouping level as an example, which describes the group to which the user belongs, the user interface displayed by the electronic device 100 after recognizing the user's grouping level is shown. If the user's grouping level describes the probability that the user belongs to different groups, then... Figure 1E The prompt message 501 shown can be used to indicate to the user the probability of belonging to different groups. Specifically, the prompt message 501 can display the blood pressure groups represented by multiple groups, and then each blood pressure group is marked with a value, which can be used to indicate the probability that the user belongs to the group corresponding to that value.

[0072] In addition, after identifying the user's group level, the electronic device 100, through... Figure 1E In addition to displaying the user's group level, the user interface 50 shown can also display the user's group level when the electronic device 100 assesses the user's hypertension risk, or when the electronic device 100 displays the assessment results of hypertension risk screening.

[0073] Optionally, the user interface 50 may further include a "Continue Assessment" option 502. The "Continue Assessment" option 502 can be used to trigger continued assessment of the user's hypertension risk using PPG signals. For example, if the electronic device 100 detects a user action, such as a click, on the "Continue Assessment" option 502, in response to this action, the electronic device 100 can enter the risk assessment phase of hypertension risk screening, i.e., assess the user's hypertension risk using PPG signals, and display... Figure 1F The user interface 60 shown.

[0074] Understandably, in addition to triggering the electronic device 100 to continue using PPG signals to assess the user's hypertension risk through user operation, the electronic device 100 can also display... Figure 1E If no user action is detected within a specified time period for the user interface 50 shown, the PPG signal will continue to be used to assess the user's hypertension risk. Alternatively, if the electronic device 100 does not use the PPG signal after identifying the user's group level, it may continue to assess the user's hypertension risk. Figure 1E If the user's group level is displayed, the electronic device 100 can automatically trigger the continued use of PPG signals to assess the user's hypertension risk after recognizing the user's group level.

[0075] like Figure 1F As shown, the user interface 60 may include: a prompt message 601. This prompt message 601 can be used to indicate the progress of the user's hypertension risk assessment. For example, in Figure 1F In the context of the message 601, the message may include the value 10%, which indicates that the current assessment of the user's risk of hypertension is at 10%.

[0076] Internally, after the electronic device 100 identifies the user's group level using the acquired PPG signal, it can assess the user's hypertension risk based on the group level and the corresponding blood pressure assessment model. Specifically, the electronic device 100 can select a blood pressure assessment model based on the user's group level, or determine the weights for weighted summation of the blood pressure assessment model's output values ​​based on the user's group level. By inputting the PPG signal into the blood pressure assessment model, the user's hypertension risk can be determined based on the model's output value.

[0077] For detailed information regarding the use of electronic devices to assess a user's blood pressure, please refer to the subsequent articles. Figure 5 The relevant content will not be elaborated here.

[0078] Similar to Figure 1D As described in the text, if the electronic device 100 spends less time assessing the user's hypertension risk, then the electronic device 100 may not display [the relevant information] when assessing the user's hypertension risk. Figure 1F The user interface 60 shown avoids the electronic device 100 switching between display screens too frequently.

[0079] In some implementations, after the electronic device 100 identifies the user's group level, it can continue to collect PPG signals for a period of time. Then, when assessing the user's hypertension risk, the electronic device 100 can utilize the PPG signals collected at the beginning of the hypertension risk screening process, as well as the PPG signals collected after identifying the user's group level, to assess the user's hypertension risk. This increases the number of PPG signals used in assessing hypertension risk, further improving the accuracy of the assessment. In this case, Figure 1F The displayed prompt message 601 can be used to indicate the progress of the electronic device 100 in acquiring PPG signals and assessing the user's risk of hypertension.

[0080] After the electronic device 100 assesses the user's risk of hypertension, the electronic device 100 can display... Figure 1G The user interface 70 shown can be used to display the user's hypertension risk level.

[0081] For example, in Figure 1G In the user interface 70 shown, the user's hypertension risk level is: high risk.

[0082] In some implementations, the user interface 70 may also display the measurement cycle of this hypertension risk screening, i.e., the time elapsed from the start of PPG signal acquisition by the electronic device 100 to the output of the hypertension risk screening assessment results, for example, in Figure 1G The "January 1st - January 5th" displayed in the user interface 70 indicates that this hypertension risk screening took place over several days, from the collection of PPG signals on January 1st to the assessment of the user's hypertension risk on January 5th.

[0083] In some implementations, the user interface 70 may also display the duration of PPG signal acquisition by the electronic device 100 at different times during this hypertension risk assessment, such as the duration of PPG signal acquisition during the day and the duration of PPG signal acquisition at night. For example, in Figure 1G The “effective duration of 2 hours during the day” displayed in the user interface 70 can refer to the electronic device 100 collecting PPG signals for 2 hours during the day, and the “effective duration of 3 hours at night” can refer to the electronic device 100 collecting PPG signals for 3 hours at night.

[0084] Furthermore, the PPG signal mentioned in the acquisition duration can refer to a PPG signal that meets the requirements. For example, these requirements may include, but are not limited to, one or more of the following: signal quality requirements, signal fluctuation requirements, signal continuity requirements, etc. That is to say, during or after the electronic device 100 acquires PPG signals, PPG signals that meet the requirements can be selected, and then these compliant PPG signals can be used to assess the user's blood pressure. Therefore, Figure 1G The “daytime effective duration of 2 hours” displayed in the user interface 70 can refer to the electronic device 100 collecting PPG signals that meet the requirements for 2 hours during the day, and the “nighttime effective duration of 3 hours” can refer to the electronic device 100 collecting PPG signals that meet the requirements for 3 hours at night.

[0085] It should be understood that the corresponding time periods during the day and the corresponding time periods at night can be preset designated time periods. For example, the corresponding time period during the day is the period from 7:00 AM to 7:00 PM, and the corresponding time period at night is the period from 7:00 PM to 7:00 AM. Alternatively, the corresponding time periods during the day and the corresponding time periods at night can refer to time periods divided according to sunrise and sunset. For example, in a day, the time period from sunrise to sunset is the corresponding time period during the day, and the time period from sunset to sunrise is the corresponding time period at night. Furthermore, the corresponding time periods during the day and the corresponding time periods at night can also be divided based on whether the user is asleep. For example, the time period from sunrise to sunset and the time period when the user is not asleep is the corresponding time period during the day, and the time period from sunset to sunrise and the time period when the user is asleep is the corresponding time period at night. The definitions of day and night in this application embodiment are not limited.

[0086] from Figures 1A-1G It can be seen that the electronic device 100 can provide a user interface that allows users to follow up on the progress of the hypertension risk assessment, from the user initiating the hypertension risk screening to the electronic device 100 assessing the hypertension risk results. This can improve user compliance with the hypertension risk screening, increase user health participation, and enhance users' health management awareness.

[0087] Understandably, during the hypertension risk screening process, the electronic device 100 does not need to be constantly displayed. Figures 1C-1GIn the user interface shown, the electronic device 100 can switch to other user interfaces based on user operation and perform hypertension risk screening in the background. Furthermore, during the hypertension risk screening process, the electronic device 100 can also switch back to the relevant hypertension risk screening interface based on user operation. For example, the electronic device 100 can switch back to the relevant interface based on user operation. Figure 1A The user operation of the hypertension risk screening option 101 shown displays the relevant interface for hypertension risk screening. It is assumed that the electronic device 100 detects the effect on... Figure 1A If the user is in the data acquisition phase when operating the hypertension risk screening option 101 shown, the electronic device 100 can switch to... Figure 1C The user interface 30 shown, or, assuming the electronic device 100 detects an action on Figure 1A If the user is in the baseline assessment phase when operating the hypertension risk screening option 101 shown, the electronic device 100 can switch to... Figure 1D The user interface 40 shown, or, assuming the electronic device 100 detects an action on Figure 1A If the user is in the risk assessment phase when operating the hypertension risk screening option 101 shown, the electronic device 100 can switch to... Figure 1F The user interface 60 shown.

[0088] In some implementations, if the electronic device 100 is assessing a user's hypertension risk but is not on a hypertension risk screening interface, for example... Figures 1C-1G The user interface shown indicates that the electronic device 100 can display an assessment of the user's hypertension risk. Figure 2 The user interface 80 shown can be used to display the assessment results of hypertension risk screening by the electronic device 100.

[0089] For example, the user interface 80 may include a prompt message 801, a view details option 802, and a re-evaluation option 803. Wherein:

[0090] The notification message 801 can be used to display the assessment results of the hypertension risk screening by the electronic device 100. For example, the notification message 801 can be displayed as: "Your risk assessment result from January 1st to January 5th is 'high risk'. If you feel unwell, please seek medical attention promptly. Click to view details."

[0091] Option 802, which allows you to view details, can be used to trigger electronic device 100 to display detailed information about the assessment results of hypertension risk screening conducted by electronic device 100.

[0092] The reassessment option 803 can be used to trigger the electronic device 100 to restart the hypertension risk screening.

[0093] Furthermore, the electronic device 100 can also combine the severity of the assessment results to determine whether to display similar [symptoms] after assessing the user's risk of hypertension. Figure 2 The user interface 80 shown. For example, if the assessment result obtained by the electronic device 100 is "low risk", the electronic device 100 does not need to display something similar to the one shown when assessing the user's risk of hypertension. Figure 2 The user interface 80 shown does not need to display the assessment results of the hypertension risk screening. If the assessment result obtained by the electronic device 100 is "high risk", the electronic device 100 can display something similar to the one shown when assessing the user's hypertension risk. Figure 2 The user interface 80 shown is designed to promptly remind users to pay attention to their blood pressure when their risk of hypertension is relatively high.

[0094] In some implementations, during the process of acquiring PPG signals, the electronic device 100 can also identify whether the number of PPG signals acquired within a specified time period meets the requirements. If the requirements are not met, the electronic device 100 can promptly output a prompt message to remind the user to pay attention to the acquisition of signals during that time period. The specified time period can refer to either the daytime period or the nighttime period.

[0095] For example, if the electronic device 100 detects that the number of PPG signals collected during the day is less than a threshold, the electronic device 100 can output a prompt message to remind the user that the number of PPG signals collected during the day is insufficient. In this way, the user can consciously increase the duration of wearing the electronic device 100 during the day so that the electronic device 100 can collect a sufficient number of PPG signals during the day.

[0096] For example, if the electronic device 100 detects that the number of PPG signals collected at night is less than a threshold, the electronic device 100 can output a prompt message to remind the user that the number of PPG signals collected at night is insufficient. In this way, the user can consciously increase the duration of wearing the electronic device 100 at night so that the electronic device 100 can collect a sufficient number of PPG signals at night.

[0097] For example, Figure 3 The electronic device 100 provided in this application displays a user interface 91 when it is detected that the PPG signal collected at night is insufficient.

[0098] like Figure 3 As shown, the user interface 91 may include a prompt message 911. This prompt message 911 can be used to remind the user that the PPG signal collected at night is insufficient. For example, the prompt message 911 could be: "Insufficient nighttime data detected; please continue wearing it at night."

[0099] In some implementations, the electronic device 100 can use the collected PPG signal to assess the user's hypertension risk at a designated time. For example, the electronic device 100 uses the collected PPG signal to assess the user's hypertension risk at 12 noon every day. Exemplarily, this designated time can be a time set by the user or a time preset by the electronic device 100; this embodiment does not impose any limitations on this. In this way, the user can view the hypertension risk assessment result of the electronic device 100 at the designated time, without blindly guessing when the electronic device 100 will provide the risk assessment result.

[0100] Furthermore, if the electronic device 100 fails to collect a sufficient number of PPG signals by the designated time, it can output a prompt message to remind the user that the number of PPG signals collected is insufficient. Afterward, the electronic device 100 can extend the PPG signal collection time or skip this hypertension risk screening and not output the assessment results.

[0101] For example, Figure 4 The user interface 92 displayed by the electronic device 100 provided in this application embodiment when a specified time has been reached but a sufficient number of PPG signals have not yet been collected.

[0102] like Figure 4 As shown, the user interface 92 may include a prompt message 921. This prompt message 921 can be used to remind the user that the currently collected PPG signal is insufficient. For example, the prompt message 921 could be: "Current data is insufficient for risk assessment; please continue wearing the device."

[0103] In some implementations, after the electronic device 100 identifies the user's group level, if the user's group corresponds to a high-risk blood pressure group, such as people with high blood pressure, or if there is a high probability that the user belongs to a high-risk blood pressure group, the electronic device 100 can output a prompt message reminding the user to continue wearing the device for further blood pressure assessment. In this way, if the electronic device 100 initially assesses that the user's blood pressure may be at risk based on the group level, it can remind the user to pay attention to the subsequent blood pressure assessment results.

[0104] Figure 5 This is a flowchart illustrating a blood pressure assessment method provided in an embodiment of this application.

[0105] S101. Electronic device 100 acquires the user's PPG signal.

[0106] For example, electronic device 100 can be a mobile phone, watch, bracelet, tablet computer, or other devices. This application embodiment does not limit the type of device 100.

[0107] If the electronic device 100 is a wearable device such as a watch or bracelet, it can directly collect the user's PPG signal. If the electronic device 100 is a non-wearable device such as a mobile phone, tablet, or computer, it can acquire the PPG signal collected by the wearable device worn by the user.

[0108] For example, the electronic device 100 may trigger the execution of S101-S104 under any of the following circumstances:

[0109] 1) Electronic device 100 detects that the user has initiated a blood pressure assessment.

[0110] The operation can be a touch operation on a touch screen, a physical operation on a button, a user's voice command, or a specified body movement, etc. The embodiments of this application do not limit the form of the operation.

[0111] For example, this operation can be Figure 1B The operation shown is for the switch 201.

[0112] In other words, the electronic device 100 allows users to proactively assess their own blood pressure. This allows users to understand their health status at any time, based on their own wishes.

[0113] 2) Electronic device 100 detects arrival at the designated time

[0114] In other words, the electronic device 100 can begin to perform operations related to assessing the user's blood pressure when a specified time is reached, including: acquiring PPG signals, identifying the user's group level, and using PPG signals to assess the user's blood pressure, etc.

[0115] For example, the electronic device 100 can periodically execute steps S101-S104. In this way, the electronic device 100 can automatically assess the user's blood pressure at regular intervals, helping the user to continuously monitor their own blood pressure.

[0116] 3) Electronic device 100 recognizes that the user is in a specified state.

[0117] For example, the specified state can be a resting state, a sleeping state, etc., and the embodiments of this application do not limit this.

[0118] In other words, the electronic device 100 can also monitor the user's status at all times. When it recognizes that the user's physical condition meets the requirements for assessing blood pressure, it can start to perform the relevant operations for assessing the user's blood pressure.

[0119] It is understood that the electronic device 100 may also trigger the execution of steps S101-S104 under other circumstances, and this application embodiment does not limit this.

[0120] In one application scenario, if the electronic device 100 can acquire historically collected PPG signals, it can trigger the use of PPG signals collected over a historical period to identify the user's blood pressure group level and assess the user's blood pressure based on that group level, upon detecting user operation, reaching a specified time, or being in a specified state. For example, taking user operation as an example, the electronic device 100 can use historically acquired PPG signals over a period of time to identify the user's blood pressure group level and assess the user's blood pressure based on that group level upon detecting user operation. In this way, after initiating a blood pressure assessment, the user can quickly view the blood pressure assessed by the electronic device 100 without waiting for it to acquire PPG signals over a period of time, achieving an "instant value" response.

[0121] In some implementations, during the process of acquiring the user's PPG signal, the electronic device 100 can display the acquisition progress of the PPG signal. This allows the user to not only view the acquisition progress but also estimate the time required for the electronic device 100 to acquire the PPG signal.

[0122] S102. Electronic device 100 determines whether a PPG signal that meets the requirements has been acquired.

[0123] For example, the requirement may include one or more of the following:

[0124] 1) Signal fluctuation requirements

[0125] The electronic device 100 can calculate the fluctuation amplitude of the acquired PPG signal. If the fluctuation amplitude is less than the threshold, the acquired PPG signal meets the signal fluctuation requirements.

[0126] 2) Signal quality requirements

[0127] The electronic device 100 can calculate the signal quality of the acquired PPG signal. If the signal quality is higher than the threshold, the acquired PPG signal meets the signal quality requirements.

[0128] 3) Signal continuity requirements

[0129] The electronic device 100 can calculate the continuity of the acquired PPG signal. If the continuity is greater than a threshold, the acquired PPG signal meets the signal continuity requirement.

[0130] 4) Signal quantity requirements

[0131] The electronic device 100 can count the number of PPG signals during the acquisition of PPG signals. If the number of PPG signals is greater than a threshold, then the acquired PPG signals meet the signal quantity requirements.

[0132] In some implementations, the signal quantity requirement can also be reflected by the signal acquisition duration. That is, the electronic device 100 can record the acquisition duration of the PPG signal during the acquisition process. If the acquisition duration of the PPG signal is greater than a threshold, it indicates that the acquired PPG signal meets the signal quantity requirement.

[0133] 5) User status requirements

[0134] User state requirements refer to the requirements for the user state when the electronic device 100 acquires the PPG signal. If the user is in the specified user state when the electronic device 100 acquires the PPG signal, it means that the PPG signal meets the user state requirements; otherwise, it does not meet the user state requirements.

[0135] The specified user state may include one or more of the following: sleep state, non-sleep state, exercise state, and resting state.

[0136] Furthermore, the specified user state can include at least two of the states exemplified above. This ensures that the PPG signal acquired by the electronic device 100 includes at least the following two: a PPG signal acquired during sleep, a PPG signal acquired during non-sleep, a PPG signal acquired during exercise, and a PPG signal acquired during rest. This ensures that the PPG signal acquired by the electronic device 100 can reflect the user's cardiovascular status in multiple states, making the blood pressure assessment by the electronic device 100 more comprehensive and accurate.

[0137] Furthermore, if the electronic device 100 fails to acquire a PPG signal that meets the requirements, the electronic device 100 can output a prompt message to the user, indicating that a PPG signal that meets the requirements has not been acquired, so that the user can take timely measures to increase the probability of the electronic device 100 acquiring a PPG signal that meets the requirements or speed up the acquisition of a PPG signal that meets the requirements.

[0138] Taking the required PPG signal as an example that meets the requirements of signal quantity and user status, if the PPG signal acquired by the electronic device 100 does not contain a sufficient number of PPG signals collected in the user's sleep and non-sleep states, the electronic device 100 can output a prompt message to remind the user that the currently acquired PPG signal is insufficient.

[0139] It is understood that the embodiments of this application do not limit this requirement. For example, the requirement may also include requirements for user heart rate and skin temperature during signal acquisition.

[0140] If the electronic device 100 obtains a PPG signal that meets the requirements, the electronic device 100 can execute step S103; otherwise, the electronic device 100 can execute step S101, that is, continue to obtain the PPG signal.

[0141] It is understood that step S102 is an optional step. The electronic device 100 does not need to determine whether a PPG signal that meets the requirements has been collected. After acquiring the PPG signal, it can directly identify the user's group level based on the acquired PPG signal.

[0142] In some implementations, after the electronic device 100 acquires a PPG signal that meets the requirements, the electronic device 100 can process the acquired PPG signal. This processing may include feature extraction, which can be used to extract features from the PPG signal so that it can be used as input parameters for a subsequent model. These features may include waveform features, time-domain features, etc., for example, these features may include, but are not limited to, one or more of the following: peak values, valley values, amplitude variability, frequency power distribution, etc.

[0143] Feature extraction can include: hop-by-hop feature extraction and secondary statistical feature extraction. Hop-by-hop feature extraction refers to extracting waveform features, time-domain features, etc., from a PPG signal on a per-heartbeat basis. Secondary statistical feature extraction refers to performing mathematical processing on the extracted features after hop-by-hop feature extraction of a continuous PPG signal. This mathematical processing may include, but is not limited to, one or more of the following: taking the mean, maximum, minimum, and median values; calculating the variance and mean squared error, etc.

[0144] Furthermore, the processing may include one or more of the following: filtering and screening, wherein filtering is used to reduce signal noise before feature extraction. Screening is used to select signals that meet specified requirements before feature extraction. This reduces the number of PPG signals processed during feature extraction and improves the accuracy of the evaluation results.

[0145] It is important to note that the specified requirements mentioned here may differ from the requirements mentioned by the electronic device 100 in determining whether a signal that meets the requirements has been acquired. For example, a signal that meets the requirements may refer to a PPG signal that meets both the signal quantity requirement and the user status requirement, while the specified requirements here may refer to signal quality requirements. In other words, the electronic device 100 can filter out PPG signals with high signal quality before performing feature extraction, so that the electronic device 100 can use high-quality signals to assess the user's blood pressure.

[0146] For ease of description, the PPG signal acquired by the electronic device 100 in step S101 will be referred to as the first PPG signal. Alternatively, if the electronic device 100 performs filtering processing on the PPG signal after acquiring it, the first PPG signal may refer to the filtered PPG signal.

[0147] S103. Electronic device 100 identifies the user’s grouping level based on the acquired PPG signal, which describes the group to which the user belongs or the probability that the user belongs to different groups.

[0148] One group represents a blood pressure population. People in the same blood pressure population have similar performance in systolic and / or diastolic blood pressure, for example, the range of systolic blood pressure fluctuation is the same, and / or the range of diastolic blood pressure fluctuation is the same.

[0149] This is because people in the same group have similar causes of hypertension, hypotension, or abnormal blood pressure fluctuations, which manifests as similar fluctuations in systolic and diastolic blood pressure. Therefore, the fluctuations in systolic and diastolic blood pressure of users can be identified by their PPG signals, that is, the user's group level can be identified. Then, the user's group level can be used as a baseline to identify the risk of hypertension, hypotension, or abnormal blood pressure fluctuations, thus improving the accuracy of identification.

[0150] For example, electronic device 100 can utilize a grouping baseline model to identify a user's grouping level. This grouping baseline model, which can be used to identify a user's grouping level, can be a model trained using the tester's PPG signal, given that the tester's group is known.

[0151] Specifically, the electronic device 100 can input the features (e.g., the first feature) extracted from the first PPG signal into the grouping baseline model to obtain the values ​​corresponding to N groups respectively, wherein the values ​​corresponding to these N groups are used to indicate the user's grouping level, and N≥2.

[0152] One approach is to determine a user's group based on the magnitude of the numerical value. For example, the group corresponding to the maximum or minimum value among N values ​​is the user's group. Alternatively, the probability of a user belonging to different groups can be determined based on the magnitude of the numerical value. For instance, a larger numerical value indicates a higher probability that the user belongs to the group corresponding to that value, and a smaller numerical value indicates a lower probability that the user belongs to the group corresponding to that value.

[0153] It is understood that, in addition to using the grouping baseline model, the electronic device 100 may also identify the user's grouping level in other ways, and this application embodiment does not limit this.

[0154] For details on the generation principles of the grouped baseline model, please refer to the following sections. Figure 7 and Figure 8 The relevant content will not be elaborated here.

[0155] S104. Electronic device 100 displays the user's grouping level.

[0156] Specifically, the electronic device 100 can display the group to which the user belongs or the possibility that the user belongs to different groups.

[0157] For example, Figure 1E The 501 message in the error message is used to display the group to which the user belongs.

[0158] It is understood that step S104 is optional, and the electronic device 100 may choose not to display the user's group level after identifying it. Alternatively, the electronic device 100 may display the user's group level while displaying the user's blood pressure information.

[0159] S105. Electronic device 100 assesses a user's blood pressure based on the user's group level.

[0160] For example, a user's blood pressure status may include one or more of the following: the user's risk of high blood pressure, the user's risk of low blood pressure, and the user's risk of abnormal fluctuations in blood pressure.

[0161] Specifically, the electronic device 100 can assess the user's blood pressure based on the user's group level and the blood pressure assessment model corresponding to the group.

[0162] The electronic device 100 can be pre-set with multiple blood pressure assessment models corresponding to different groups. After the electronic device 100 identifies the user's group level, there are two ways to assess the user's blood pressure:

[0163] 1) If the group level describes the probability that a user belongs to different groups, the electronic device 100 can assess the user's blood pressure based on the probability that the user belongs to different groups and the blood pressure assessment models corresponding to the multiple groups.

[0164] Specifically, the electronic device 100 can input the features (e.g., the second feature) extracted from the first PPG signal into the blood pressure assessment models corresponding to the multiple groups respectively, thereby obtaining multiple risk intermediate values. Then, the multiple risk intermediate values ​​are weighted and summed to obtain the user's blood pressure status, using the probability of the user belonging to different groups as the weight.

[0165] Further optionally, in order to improve the accuracy of the blood pressure assessment model in assessing the user's blood pressure, after the electronic device 100 identifies the user's group level, the electronic device 100 can continue to acquire a PPG signal (hereinafter referred to as the second PPG signal), and then, when assessing the user's blood pressure, combine the first PPG signal and the second PPG signal to assess the user's blood pressure.

[0166] Specifically, the electronic device 100 can input the features (e.g., the third feature) extracted from the first PPG signal and the second PPG signal into the blood pressure assessment models corresponding to the multiple groups respectively, thereby obtaining multiple risk intermediate values. Then, the multiple risk intermediate values ​​are weighted and summed to obtain the user's blood pressure status, using the probability of the user belonging to different groups as the weight.

[0167] 2) If the group level describes the group to which the user belongs, the electronic device 100 can find the blood pressure assessment model corresponding to the user's group from the blood pressure assessment models corresponding to multiple groups, and then use the blood pressure assessment model corresponding to the user's group to assess the user's blood pressure.

[0168] Specifically, the electronic device 100 can input the features (e.g., the fourth feature) extracted from the first PPG signal into the blood pressure assessment model corresponding to the user's group to obtain the user's blood pressure status.

[0169] Further optionally, in order to improve the accuracy of the blood pressure assessment model in assessing the user's blood pressure, after the electronic device 100 identifies the user's group level, the electronic device 100 may continue to acquire a PPG signal (hereinafter referred to as the second PPG signal), and then, when assessing the user's blood pressure, combine the first PPG signal and the second PPG signal to assess the user's blood pressure.

[0170] Specifically, the electronic device 100 can input features (e.g., the fifth feature) extracted from the first PPG signal and the second PPG signal into the blood pressure assessment model corresponding to the user's group to obtain the user's blood pressure status.

[0171] Detailed descriptions of these two methods for assessing a user's blood pressure can be found in subsequent articles. Figures 6-9 The content.

[0172] S106. Electronic device 100 displays the user's blood pressure.

[0173] For example, if a user's blood pressure indicates a risk of hypertension, the electronic device 100 can specifically display the level of the user's hypertension risk when showing the user's blood pressure.

[0174] For example, Figure 1G The system displays the user's hypertension risk level as assessed by the electronic device 100, indicating a high-risk level.

[0175] Furthermore, taking blood pressure as an example of hypertension risk, in addition to displaying the user's hypertension risk, the electronic device 100 can also display the user's blood pressure day-night pattern and / or the stage the user is in in the course of hypertension.

[0176] The blood pressure diurnal pattern is a classification based on the rhythm of blood pressure changes throughout the day, including: dipper pattern, morning hypertension pattern, nighttime hypertension pattern, morning peak hypertension pattern, reverse dipper pattern, non-dipper pattern, and super-dipper pattern, etc. The user's stage in the course of hypertension includes three stages: stage one, stage two, and stage three. The systolic and diastolic blood pressure patterns differ in each stage.

[0177] In this way, users can not only understand the possibility of having high blood pressure, but also understand their blood pressure diurnal pattern and / or the stage of their hypertension, helping them to have a more comprehensive understanding of their blood pressure.

[0178] For example, electronic device 100 can determine a user's blood pressure day-night pattern in any of the following ways:

[0179] 1) Electronic device 100 can use a blood pressure assessment model to determine the user's blood pressure diurnal pattern.

[0180] In other words, when the electronic device 100 uses a blood pressure assessment model to assess a user's blood pressure, the output of the blood pressure assessment model can also include the user's blood pressure day-night pattern.

[0181] 2) Electronic device 100 can determine the user's blood pressure diurnal pattern using a pattern recognition model that differs from the blood pressure assessment model.

[0182] The pattern recognition model can be a model trained using PPG signals from test subjects with known blood pressure day-night patterns.

[0183] Furthermore, after assessing the user's blood pressure, the electronic device 100 can choose whether to use a pattern recognition model to determine the user's diurnal blood pressure pattern based on the user's blood pressure. This is because when a user's blood pressure is normal, it presents a dipper-shaped pattern. Only when the user has hypertension will the blood pressure exhibit multiple possible patterns, such as morning hypertension, nocturnal hypertension, morning peak hypertension, reverse dipper hypertension, non-dipper hypertension, and super-dipper hypertension. Therefore, the electronic device 100 can determine the user's diurnal blood pressure pattern only when the assessment indicates a relatively serious risk of hypertension, such as a high-risk or medium-risk level. In this way, the user's diurnal blood pressure pattern can be presented when the likelihood of hypertension is high, minimizing the computational load on the electronic device 100.

[0184] Similar to the description of blood pressure day and night patterns, the electronic device 100 can also determine the stage of the user's hypertension course in two ways: one is to determine it using a blood pressure assessment model, and the other is to determine it using a model different from the blood pressure assessment model. Furthermore, the electronic device 100 can also combine the blood pressure assessment results to choose whether to use a model to determine the stage of the user's hypertension course.

[0185] Furthermore, optionally, since hypertension in the first stage is reversible while hypertension in the second and third stages is not, the electronic device 100 can also provide different advice and suggestions for different stages of hypertension. For example, if the user is in the first stage of hypertension, the electronic device 100 can provide relevant advice and suggestions to help the user restore normal blood pressure.

[0186] In some embodiments, the electronic device 100 may also display one or more of the following: measurement period, acquisition duration of PPG signals under various user states, acquisition duration of PPG signals at different time periods, blood pressure change trend, and PPG signal waveform. The various user states may include at least two of the following: sleep state, non-sleep state, exercise state, and resting state. Different time periods may include: daytime periods and nighttime periods. The blood pressure change trend describes the change in blood pressure assessed in this instance compared to historical blood pressure assessments. The PPG signal waveform can be a waveform plotted using the acquired PPG signals.

[0187] In some implementations, the electronic device 100 may also display a first progress bar. This first progress bar can be used to indicate the progress of the electronic device 100 from the start of acquiring PPG signals to assessing the user's blood pressure.

[0188] Specifically, when acquiring the user's first PPG signal, the first progress bar can be used to indicate the first progress; when displaying the user's group level, the first progress bar can be used to indicate the second progress; and when displaying the user's blood pressure, the first progress bar can be used to indicate the third progress. The third progress is greater than the second progress, and the second progress is greater than the first progress.

[0189] Alternatively, the first progress bar can be displayed as a progress bar surrounding the edge of the display area. This prevents the first progress bar from obscuring the main display content of the electronic device 100.

[0190] In some implementations, in addition to acquiring PPG signals, the electronic device 100 can also acquire signals related to user motion, such as IMU signals acquired by an inertial measurement unit (IMU). These IMU signals may include one or more of the following: acceleration signals, gyroscope signals, etc. Acceleration signals can be signals acquired by an accelerometer sensor, used to indicate the magnitude of an object's acceleration in various directions (typically three coordinate axes), and are usually used to calculate the object's attitude and motion state. Gyroscope signals can be signals acquired by a gyroscope sensor, used to indicate the object's angular velocity around the three coordinate axes, and are usually used to determine the object's rotational state.

[0191] For example, the IMU signal can be a signal collected by the electronic device 100, or a signal collected by other devices and sent to the electronic device 100. This application embodiment does not limit the source of the IMU signal.

[0192] In practical applications, the electronic device 100 can identify the user's activity scenario based on the acquired IMU signal during the acquisition of PPG signal, so that the electronic device 100 can distinguish between the user's active and resting states. This allows the electronic device 100 to acquire PPG signals in both active and resting states. Alternatively, the electronic device 100 can combine PPG and IMU signals to identify the user's group level or assess the user's blood pressure. For example, the IMU signal can be added as an input parameter to the group baseline model and / or blood pressure assessment model, enabling the electronic device 100 to analyze the user's blood pressure by combining the user's cardiovascular condition and activity status, thereby improving the accuracy of the blood pressure assessment results.

[0193] To better understand the two methods of assessing a user's blood pressure mentioned in step S104, the following will explain... Figures 6-9 This describes in detail the process by which electronic device 100 uses a grouped baseline model and a blood pressure assessment model to assess a user's blood pressure.

[0194] in, Figure 6This is a schematic diagram illustrating the principle of a blood pressure assessment model for evaluating users using PPG signals, as provided in an embodiment of this application.

[0195] Figure 6 (a) is a schematic diagram of the principle of electronic device 100 assessing a user's blood pressure when the group to which the user belongs is described at the group level, according to an embodiment of this application.

[0196] like Figure 6 As shown in (a), after the electronic device 100 acquires the PPG signal, it can extract features from the PPG signal and then input the extracted features into the grouped baseline model to obtain N values: a1, a2, ..., aN.

[0197] Each value corresponds to a group, where a1 corresponds to group 1, a2 corresponds to group 2, ..., aN corresponds to group N. Each group corresponds to a blood pressure assessment model, where group 1 corresponds to blood pressure assessment model 1, group 2 corresponds to blood pressure assessment model 2, ..., group N corresponds to blood pressure assessment model N. Each blood pressure assessment model can output a blood pressure assessment result, where blood pressure assessment model 1 outputs blood pressure assessment result 1, blood pressure assessment model 2 outputs blood pressure assessment result 2, ..., blood pressure assessment model N outputs blood pressure assessment result N.

[0198] Assuming the group corresponding to the maximum value among N values ​​is the user's group, taking a2 as the maximum value as an example, then group 2 is the user's group. Furthermore, the electronic device 100 can input the features extracted from the PPG signal into the blood pressure assessment model corresponding to the user's group, i.e., blood pressure assessment model 2, thereby obtaining blood pressure assessment result 2. This blood pressure assessment result 2 is the user's final blood pressure assessment result, i.e., the user's blood pressure status assessed by the electronic device 100.

[0199] In some implementations, the output data of the grouping baseline model may also include only a single value, with different groups corresponding to different value ranges. The group to which the user belongs is the range in which the value falls. For example, suppose there are two groups, where the range 0-0.5 corresponds to group 1 and the range 0.5-1 corresponds to group 2. Then, if the value output by the grouping baseline model is between 0 and 0.5, it means that the user belongs to group 1; if the output value is between 0.5 and 1, it means that the user belongs to group 2.

[0200] It is evident that regardless of the form of the output data of the group baseline model, the group to which a user belongs can be identified through the correspondence between the output data of the group baseline model and the group. This application embodiment does not limit the form of the output data of the group baseline model.

[0201] Figure 6 (b) is a schematic diagram of the principle of electronic device 100 assessing a user's blood pressure when the group level describes the possibility that the user belongs to different groups, as provided in the embodiments of this application.

[0202] like Figure 6 As shown in (b), after the electronic device 100 acquires the PPG signal, it can extract features from the PPG signal and then input the extracted features into the grouped baseline model to obtain N values: a1, a2, ..., aN.

[0203] Similar to Figure 6 The relevant description in (a) states that each value corresponds to a group, and each group corresponds to a blood pressure assessment model. Each blood pressure assessment model can output blood pressure assessment results.

[0204] Among them, the N values ​​output by the group baseline model are used to indicate the probability that the user belongs to the group corresponding to the value. The magnitude of the probability determines the weight when the blood pressure assessment results output by multiple blood pressure assessment models are weighted and summed.

[0205] Furthermore, the electronic device 100 can input the features extracted from the PPG signal into N blood pressure assessment models respectively, thereby obtaining N blood pressure assessment results: blood pressure assessment result 1, blood pressure assessment result 2, ..., blood pressure assessment result N. The user's blood pressure status assessed by the electronic device 100, i.e., the user's final blood pressure assessment result = blood pressure assessment result 1 × a1 + blood pressure assessment result 2 × a2 + ... + blood pressure assessment result N × aN.

[0206] It should be noted that in the above Figure 6 (a) and Figure 6 In (b) of the diagram, the input data for each blood pressure assessment model can be the same or different. For example, suppose the input data for blood pressure assessment model 1, blood pressure assessment model 2, ..., blood pressure assessment model N are features A1, A2, ..., A1 extracted from the PPG signal, respectively. N Among them, features A1, A2, ... A N The input data can be completely the same, partially the same, or completely different. Furthermore, taking any blood pressure assessment model as an example, the input data of the grouped baseline model and the blood pressure assessment model can be the same or different. For instance, suppose the input data of the grouped baseline model is feature B extracted from the PPG signal, and the input data of the blood pressure assessment model is feature A extracted from the PPG signal. Feature A and feature B can be the same or different.

[0207] Furthermore, Figure 6 Both the grouped baseline model and the blood pressure assessment model were trained using known PPG signals from the test subjects.

[0208] The following is through Figure 7 , Figure 8 , Figure 9 Describe the generation principles of the grouped baseline model and blood pressure assessment model.

[0209] Specifically, before training the grouped baseline model and the blood pressure assessment model, the test subjects need to be grouped according to their systolic and diastolic blood pressure. The test subjects are divided into multiple groups, such as group 1 to group N. Then, given the grouping of the test subjects, the grouped baseline model is trained using the test subjects' PPG signals, and the blood pressure assessment model corresponding to that group is trained using the PPG signals of the test subjects in the same group.

[0210] For example, taking a division into 6 groups as an example, Figure 7 This is a schematic diagram illustrating the principle of grouping and partitioning provided in an embodiment of this application.

[0211] exist Figure 7 In this context, the base value serves as the dividing line. This base value includes a systolic blood pressure baseline and a diastolic blood pressure baseline. The test subject's group is determined based on the difference between their systolic and diastolic blood pressure and this base value. This base value can be located in the higher end of the normal blood pressure range; for example, the base value could be a systolic blood pressure baseline of 120 mmHg and a diastolic blood pressure baseline of 70 mmHg.

[0212] In this grouping, if a test subject's systolic and diastolic blood pressure are lower than the base values ​​by a certain threshold, the test subject belongs to Group 1, which represents people with normal to low blood pressure. If a test subject's systolic and diastolic blood pressure are slightly lower than the base values ​​but higher than Group 1, the test subject belongs to Group 2, which represents people with normal blood pressure. If a test subject's systolic and diastolic blood pressure are slightly higher than the base values, the test subject belongs to Group 3, which represents people with high blood pressure. If a test subject's systolic and diastolic blood pressure are higher than the base values ​​by a certain threshold, the test subject belongs to Group 3, which represents people with high blood pressure. If the test subject is in group 3, then the test subject belongs to group 4, which represents people with significantly high blood pressure. If the test subject's systolic blood pressure is slightly lower than the baseline systolic blood pressure value and the diastolic blood pressure is higher than the baseline diastolic blood pressure value by a certain threshold, then the test subject belongs to group 5, which represents people with significantly high diastolic blood pressure. If the test subject's systolic blood pressure is higher than the baseline systolic blood pressure value by a certain threshold and the diastolic blood pressure is slightly lower than the baseline diastolic blood pressure value, then the test subject belongs to group 6, which represents people with significantly high systolic blood pressure.

[0213] It should be understood that Figure 7Taking six groups as an example, other embodiments of this application may include more or fewer groups, and each group may be divided according to other criteria. Furthermore, in other embodiments of this application, in addition to dividing testers into groups based on a base value, testers may also be divided into groups based on a range of values. Figure 7 This is merely an example to illustrate the principle of grouping test subjects using systolic and diastolic blood pressure. Figure 7 The six groups shown do not constitute a limitation on the grouping of the embodiments of this application.

[0214] In some implementations, when grouping test subjects, the systolic blood pressure used can be the average systolic blood pressure of the test subjects over a period of time, and the diastolic blood pressure used can be the average diastolic blood pressure of the test subjects over a period of time. Further optionally, this period of time can include multiple time periods, which may include, but are not limited to, one or more of the following: time periods when the test subjects are asleep, time periods when the test subjects are not asleep, time periods when the test subjects are exercising, time periods when the test subjects are at rest, daytime corresponding time periods, nighttime corresponding time periods, etc. This allows for a comprehensive consideration of the test subjects' blood pressure status under different states to determine the systolic and diastolic blood pressure, making the grouping of test subjects more accurate.

[0215] Figure 8 This is a schematic diagram illustrating the generation principle of the grouped baseline model provided in the embodiments of this application.

[0216] like Figure 8 As shown, after knowing the group to which the tester belongs, the model can be trained using the PPG signals of the testers in each group to obtain the group baseline model. The input of the group baseline model is the features extracted from the PPG signals, and the output is a numerical value used to indicate the group level.

[0217] Specifically, if there are N groups, the PPG signals of the testers in groups 1 to N can be used to train the group baseline model.

[0218] Figure 9 This is a schematic diagram illustrating the generation principle of the blood pressure assessment model provided in the embodiments of this application.

[0219] like Figure 9 As shown, after knowing the group to which the tester belongs, the model can be trained using the PPG signals of the testers in the same group to obtain the blood pressure assessment model corresponding to that group. The input of the blood pressure assessment model is the features extracted from the PPG signal, and the output is the blood pressure assessment result.

[0220] The blood pressure assessment results of the test subjects can be those assessed by doctors, experts, or other professionals. Therefore, when training the blood pressure assessment model, given the blood pressure assessment results of the test subjects, the PPG signals of test subjects within the same group can be used to train the blood pressure assessment model corresponding to that group.

[0221] Specifically, if there are N groups, the blood pressure assessment model 1 corresponding to group 1 can be trained using the PPG signals of the testers in group 1, the blood pressure assessment model 2 corresponding to group 2 can be trained using the PPG signals of the testers in group 2, and so on, and the blood pressure assessment model N corresponding to group N can be trained using the PPG signals of the testers in group N.

[0222] Figure 10 This is a schematic diagram of the hardware structure of the electronic device 100 provided in an embodiment of this application.

[0223] Electronic device 100 may be a mobile phone, tablet computer, desktop computer, laptop computer, handheld computer, notebook computer, ultra-mobile personal computer (UMPC), netbook, as well as cellular phone, personal digital assistant (PDA), augmented reality (AR) device, virtual reality (VR) device, artificial intelligence (AI) device, wearable device, in-vehicle device, smart home device and / or smart city device. The embodiments of this application do not impose any special restrictions on the specific type of electronic device.

[0224] Preferably, in the embodiments of this application, electronic device 100 may refer to wearable devices such as watches or bracelets.

[0225] Electronic device 100 may include processor 110, internal memory 120, universal serial bus (USB) interface 130, charging management module 140, power management module 141, battery 142, antenna 1 and antenna 2, mobile communication module 150, wireless communication module 160, audio module 170, speaker 170A, microphone 170B, sensor module 180, button 190, motor 191, indicator 192, camera 193, and subscriber identification module (SIM) card interface 195, etc.

[0226] Processor 110 may include one or more processing units, such as: application processor (AP), microcontroller unit (MCU), modem processor, graphics processing unit (GPU), image signal processor (ISP), controller, video codec, digital signal processor (DSP), baseband processor, and / or neural network processing unit (NPU), etc. The different processing units may be independent devices or integrated into one or more processors. For example, the application processor may include a graphics processor and a digital signal processor, and the microcontroller unit may include a graphics processor.

[0227] Electronic device 100 can implement display functions through a GPU, display screen 194, application processor, microcontroller unit, etc. The GPU is a microprocessor for image processing, connected to the display screen 194, application processor, and microcontroller unit. 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.

[0228] In some implementations, the processor 110 can control the acquisition of PPG signals, identify the user's group level based on the PPG signals, and assess the user's blood pressure based on the group level, wherein the user's group level describes the group to which the user belongs or the probability that the user belongs to different groups.

[0229] Internal memory 120 may include one or more random access memory (RAM) and one or more non-volatile memory (NVM). The RAM can be directly read and written by the processor 110 and can be used to store executable programs (e.g., machine instructions) of the operating system or other running programs, as well as user and application data. The NVM can also store executable programs and user and application data, and can be pre-loaded into the RAM for direct read and write operations by the processor 110.

[0230] In some implementations, the internal memory 120 may be used to store the user's PPG signal, multiple groups in the blood pressure assessment, the user's group level, and the user's blood pressure status, etc.

[0231] 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 port can also be used to connect other electronic devices, such as AR devices.

[0232] The charging management module 140 is used to receive charging input from the charger. The charger can be a wireless charger or a wired charger. In some wired charging embodiments, the charging management module 140 can receive charging input from the wired charger via the USB interface 130.

[0233] The power management module 141 is used to connect the battery 142, the charging management module 140, and the processor 110. The power management module 141 receives input from the battery 142 and / or the charging management module 140 to power the processor 110, internal memory 120, display screen 194, wireless communication module 160, sensor module 180, etc.

[0234] 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.

[0235] The mobile communication module 150 can provide wireless communication solutions, including 2G / 3G / 4G / 5G, for use on electronic devices 100.

[0236] The wireless communication module 160 can provide solutions for wireless communication applications on the electronic device 100, including wireless local area networks (WLAN) (such as wireless fidelity (Wi-Fi) networks), Bluetooth (BT), global navigation satellite system (GNSS), frequency modulation (FM), near field communication (NFC), infrared (IR), and intrabody communication (IBC).

[0237] In some embodiments, antenna 1 of electronic device 100 is coupled to mobile communication module 150, and antenna 2 is coupled to wireless communication module 160, so that electronic device 100 can communicate with networks and other devices through wireless communication technology.

[0238] Electronic device 100 can implement audio functions through audio module 170, speaker 170A, microphone 170B, and processor 110, such as music playback and recording.

[0239] The audio module 170 is used to convert digital audio information into analog audio signal output, and also to convert analog audio input into digital audio signal.

[0240] The speaker 170A, also known as a "loudspeaker," is used to convert audio electrical signals into sound signals. The electronic device 100 can listen to music or make hands-free calls through the speaker 170A.

[0241] Microphone 170B, also known as a "microphone" or "voice transducer," is used to convert sound signals into electrical signals. When making a phone call or sending a voice message, the user can speak by bringing their mouth close to microphone 170B, inputting the sound signal into microphone 170B.

[0242] The sensor module 180 may include: a touch sensor 180A and a photoelectric sensor 180B.

[0243] Touch sensor 180A, also known as a "touch device," can be disposed on display screen 194. The touch sensor 180A and display screen 194 together form a touchscreen, also known as a "touchscreen." Touch sensor 180A is used to detect touch operations applied to or near it. The touch sensor can transmit the detected touch operation to the application processor to determine the type of touch event. Visual output related to the touch operation can be provided through display screen 194. In other embodiments, touch sensor 180A may also be disposed on the surface of electronic device 100, in a different location than display screen 194.

[0244] The photoelectric sensor 180B is used to monitor cardiovascular vital signs. The photoelectric sensor 180B includes a photodetector and a light emitter. The photodetector can be, for example, a photodiode (PD), and the light emitter can be, for example, a light-emitting diode (LED). The light emitter acts as a light source to illuminate the skin. The photodetector detects the remaining transmitted or reflected light after it has been absorbed by the blood and tissues during penetration, and converts it into an electrical signal to obtain a PPG signal. Since the intensity of the transmitted or reflected light varies with arterial pulsation, the PPG signal also follows the arterial pulsation, i.e., the rhythmic fluctuation of the user's heartbeat. The user's heart rate, blood oxygen saturation, blood pressure, and other parameters can be calculated using this PPG signal. In this embodiment, the user's group level and blood pressure status can be identified using this PPG signal.

[0245] In some embodiments, the sensor module 180 may further include one or more of the following sensors: pressure sensor, gyroscope sensor, barometric pressure sensor, magnetic sensor, accelerometer, distance sensor, proximity sensor, fingerprint sensor, humidity sensor, temperature sensor, ambient light sensor, heart rate sensor, electrocardiogram sensor, etc.

[0246] Motor 191 can generate vibration alerts. Motor 191 can be used for incoming call vibration alerts or for touch vibration feedback.

[0247] Indicator 192 can be an indicator light, used to indicate charging status, power changes, or to indicate messages, missed calls, notifications, etc.

[0248] Display screen 194 is used to display images, videos, etc. Display screen 194 includes a display panel. The display panel can be a liquid crystal display (LCD), or it can be manufactured using organic light-emitting diodes (OLEDs), active-matrix organic light-emitting diodes (AMOLEDs), flexible light-emitting diodes (FLEDs), minimized LEDs, microLEDs, micro-OLEDs, quantum dot light-emitting diodes (QLEDs), etc. In some embodiments, electronic device 100 may include one or N displays 194, where N is a positive integer greater than 1.

[0249] In some implementations, the display screen 194 may be used to display the user's group level, the user's blood pressure status, and a user interface related to assessing the user's blood pressure, etc. See the above for details. Figures 1A-1G , Figures 2-4 The user interface shown.

[0250] The SIM card interface 195 is used to connect a SIM card. The electronic device 100 can support one or N SIM card interfaces, where N is a positive integer greater than 1.

[0251] 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.

[0252] Figure 11 This is a schematic diagram of the structure of the blood pressure assessment device 200 provided in the embodiments of this application.

[0253] like Figure 11 As shown, the blood pressure assessment device 200 may include components such as a processor 201 and a memory 202. These components can be connected via a bus 203 or other means. Figure 11 Taking a bus connection as an example, bus 203 is used to connect the processor 201 and the memory 202.

[0254] The processor 201 may include one or more processing units. The processor 201 can be used to provide computing and control capabilities to support the operation of the entire blood pressure assessment device 200.

[0255] The memory 202 can be used to store various software programs and / or multiple sets of instructions. Specifically, the memory 202 may include high-speed random access memory, and may also include non-volatile memory, such as one or more disk storage devices, flash memory devices, or other non-volatile solid-state storage devices.

[0256] In some embodiments, the blood pressure assessment device 200 may be the aforementioned electronic device 100. The processor 201 may be used to acquire a user's first PPG signal, determine the user's group level based on the first PPG signal (which describes the user's group or the probability that the user belongs to a different group), and assess the user's blood pressure based on the user's group level. The memory 202 may be used to store the PPG signal, the user's group level, the user's blood pressure, and the software or program code required for all or part of the functions of the electronic device 100 in the above method embodiments.

[0257] It should be noted that, Figure 11 The blood pressure assessment device 200 shown is merely one implementation of the embodiments of this application. In actual applications, the blood pressure assessment device 200 may include more or fewer components than shown, or combine certain components, or deploy different components. No limitation is made here.

[0258] It should be understood that each step in the above method embodiments can be completed by integrated logic circuits in the processor hardware or by instructions in software form. The method steps disclosed in the embodiments of this application can be directly manifested as being executed by a hardware processor, or being executed by a combination of hardware and software modules in the processor.

[0259] This application also provides an electronic device that may include a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the method performed by the electronic device as described in any of the above embodiments.

[0260] This application also provides a chip system including a processing circuit and an interface circuit. The interface circuit is used to receive computer instructions and transmit them to the processing circuit. The processing circuit is used to execute the computer instructions to implement the method performed by the electronic device as in any of the above embodiments.

[0261] This application also provides a chip system including at least one processor for implementing the methods executed by the electronic device in any of the above embodiments. In one possible design, the chip system further includes a memory for storing program instructions and data, the memory being located within or outside the processor.

[0262] A chip system can consist of chips or include chips and other discrete components.

[0263] Optionally, there may be one or more processors in the chip system. The processor can be implemented in hardware or software. When implemented in hardware, the processor can be a logic circuit, integrated circuit, etc. When implemented in software, the processor can be a general-purpose processor, implemented by reading software code stored in memory.

[0264] Optionally, the chip system may contain one or more memories. These memories may be integrated with the processor or disposed separately; this application does not limit this. For example, the memory may be a non-transient processor, such as a read-only memory (ROM), which may be integrated with the processor on the same chip or disposed on different chips. This application does not specifically limit the type of memory or the arrangement of the memory and processor.

[0265] For example, the chip system may be a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), a system on chip (SoC), a central processor unit (CPU), a network processor (NP), a digital signal processor (DSP), a micro controller unit (MCU), a programmable logic device (PLD), or other integrated chips.

[0266] This application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method executed by the electronic device in any of the above embodiments.

[0267] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the method executed by the electronic device as described in any of the above embodiments.

[0268] The various embodiments of this application can be combined arbitrarily to achieve different technical effects.

[0269] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium accessible to a computer or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state disk (SSD)).

[0270] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This program can be stored in a computer-readable storage medium, and when executed, it can include the processes described in the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM or random access memory (RAM), magnetic disks, or optical disks.

[0271] In the description of the embodiments of this application, unless otherwise stated, " / " means "or". For example, A / B can mean A or B. The "and / or" in the text is merely a description of the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist simultaneously, and B exists alone. In addition, in the description of the embodiments of this application, "multiple" means two or more.

[0272] The terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of indicated technical features. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the embodiments of this application, unless otherwise stated, "multiple" means two or more.

[0273] In summary, the above description is merely an embodiment of the technical solution of this application and is not intended to limit the scope of protection of this application. Any modifications, equivalent substitutions, improvements, etc., made based on the disclosure of this application should be included within the scope of protection of this application.

Claims

1. A method for assessing blood pressure, characterized in that, The method is applied to an electronic device, and the method includes: Acquire the user's first photoplethysmography (PPG) signal; The user's grouping level is displayed, which is obtained based on the first PPG signal and describes the group to which the user belongs or the probability that the user belongs to different groups; Displays the user's blood pressure based on the group level assessment.

2. The method according to claim 1, characterized in that, People in the same group showed similar systolic and / or diastolic blood pressure.

3. The method according to claim 1 or 2, characterized in that, Before displaying the user's blood pressure based on the group level assessment, the method further includes: The user's blood pressure is assessed based on the group level and the corresponding blood pressure assessment model.

4. The method according to any one of claims 1-3, characterized in that, The first PPG signal includes at least two of the following: a PPG signal collected in a sleep state, a PPG signal collected in a non-sleep state, a PPG signal collected in a movement state, and a PPG signal collected in a resting state.

5. The method according to any one of claims 1-4, characterized in that, In the process of acquiring the user's first photoplethysmography (PPG) signal, the method further includes: Displays the progress of PPG signal acquisition.

6. The method according to any one of claims 1-5, characterized in that, In the process of acquiring the user's first photoplethysmography (PPG) signal, the method further includes: If the number of PPG signals collected in the first time period is less than a first threshold, a first prompt message is output, which is used to remind the user that there are not enough PPG signals collected in the first time period.

7. The method according to any one of claims 1-6, characterized in that, The method further includes: Upon reaching the first time and if the number of PPG signals collected is less than the second threshold, a second prompt message is output, which is used to remind the user that the number of PPG signals collected is insufficient.

8. The method according to any one of claims 1-7, characterized in that, The method further includes: The first progress bar is displayed, wherein when acquiring the user's first PPG signal, the first progress bar is used to indicate the first progress; when displaying the user's group level, the first progress bar is used to indicate the second progress; and when displaying the user's blood pressure, the first progress bar is used to indicate the third progress, wherein the third progress is greater than the second progress, and the second progress is greater than the first progress.

9. The method according to any one of claims 1-8, characterized in that, The method further includes: Display one or more of the following: measurement period, acquisition duration of PPG signals under various user states, acquisition duration of PPG signals at different time periods, blood pressure change trend, and PPG signal waveform; wherein, the various user states include at least two of the following: sleep state, non-sleep state, exercise state, and resting state, and the different time periods include: the time period corresponding to daytime and the time period corresponding to nighttime.

10. The method according to any one of claims 1-9, characterized in that, After acquiring the user's first photoplethysmography (PPG) signal and before displaying the user's group level, the method further includes: The first feature extracted from the first PPG signal is input into the grouping baseline model to obtain numerical values ​​corresponding to N groups. These numerical values ​​are used to indicate the user's grouping level, where N ≥ 2. Wherein, the group corresponding to the maximum or minimum value among the N values ​​is the group to which the user belongs, or the value represents the probability that the user belongs to the group corresponding to the value, and the group baseline model is a model trained using the PPG signal of the tester when the group to which the tester belongs is known.

11. The method according to claim 10, characterized in that, The grouping level describes the likelihood that a user belongs to different groups. After displaying the user's group level and before displaying the user's blood pressure assessed based on the group level, the method further includes: The second feature extracted from the first PPG signal is input into the blood pressure assessment model corresponding to each of the N groups to obtain N intermediate risk values; Using the values ​​corresponding to the N groups as weights, the user's blood pressure is obtained by weighted summation of the N risk median values.

12. The method according to claim 10, characterized in that, The grouping level describes the likelihood that a user belongs to different groups. After displaying the user's group level and before displaying the user's blood pressure assessed based on the group level, the method further includes: Acquire the user's second PPG signal; The third feature extracted from the first PPG signal and the second PPG signal is input into the blood pressure assessment model corresponding to each of the N groups to obtain N intermediate risk values; Using the values ​​corresponding to the N groups as weights, the user's blood pressure is obtained by weighted summation of the N risk median values.

13. The method according to any one of claims 1-10, characterized in that, The grouping level describes the group to which the user belongs. After displaying the user's group level and before displaying the user's blood pressure assessed based on the group level, the method further includes: The fourth feature extracted from the first PPG signal is input into the blood pressure assessment model corresponding to the user's group to obtain the user's blood pressure status.

14. The method according to any one of claims 1-10, characterized in that, The grouping level describes the group to which the user belongs. After displaying the user's group level and before displaying the user's blood pressure assessed based on the group level, the method further includes: Acquire the user's second PPG signal; The fifth feature extracted from the first PPG signal and the second PPG signal is input into the blood pressure assessment model corresponding to the user's group to obtain the user's blood pressure status.

15. The method according to any one of claims 11-14, characterized in that, The blood pressure assessment model for each group is trained using the PPG signals of the test subjects in that group, given their known blood pressure.

16. The method according to any one of claims 1-15, characterized in that, The user's blood pressure includes one or more of the following: The user's risk of high blood pressure, the user's risk of low blood pressure, and the user's risk of abnormal blood pressure fluctuations.

17. The method according to any one of claims 1-16, characterized in that, Different groups were formed based on different systolic and / or diastolic blood pressure ranges.

18. An electronic device, characterized in that, include: A memory, a processor, and a computer program stored on the memory, wherein the processor executes the computer program to implement the method as described in any one of claims 1-17.

19. A computer-readable storage medium, characterized in that, It stores a computer program thereon, which, when executed by a processor, implements the method as described in any one of claims 1-17.

20. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the method as described in any one of claims 1-17.

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